[2025-01-17 21:41:35 internimage_t_1k_224] (main.py 665): INFO Full config saved to work_dirs/internimage_t_1k_224/config.json
[2025-01-17 21:41:35 internimage_t_1k_224] (main.py 668): INFO AMP_OPT_LEVEL: O1
AMP_TYPE: float16
AUG:
  AUTO_AUGMENT: rand-m9-mstd0.5-inc1
  COLOR_JITTER: 0.4
  CUTMIX: 1.0
  CUTMIX_MINMAX: null
  MEAN:
  - 0.485
  - 0.456
  - 0.406
  MIXUP: 0.8
  MIXUP_MODE: batch
  MIXUP_PROB: 1.0
  MIXUP_SWITCH_PROB: 0.5
  RANDOM_RESIZED_CROP: false
  RECOUNT: 1
  REMODE: pixel
  REPROB: 0.25
  STD:
  - 0.229
  - 0.224
  - 0.225
BASE:
- ''
DATA:
  BATCH_SIZE: 128
  CACHE_MODE: part
  DATASET: imagenet
  DATA_PATH: data/imagenet
  IMG_ON_MEMORY: true
  IMG_SIZE: 224
  INTERPOLATION: bicubic
  NUM_WORKERS: 8
  PIN_MEMORY: true
  ZIP_MODE: false
EVAL_22K_TO_1K: false
EVAL_FREQ: 1
EVAL_MODE: false
LOCAL_RANK: 0
MODEL:
  DROP_PATH_RATE: 0.1
  DROP_PATH_TYPE: linear
  DROP_RATE: 0.0
  INTERN_IMAGE:
    CENTER_FEATURE_SCALE: false
    CHANNELS: 64
    CORE_OP: DCNv3
    DEPTHS:
    - 4
    - 4
    - 18
    - 4
    DW_KERNEL_SIZE: null
    GROUPS:
    - 4
    - 8
    - 16
    - 32
    LAYER_SCALE: null
    LEVEL2_POST_NORM: false
    LEVEL2_POST_NORM_BLOCK_IDS: null
    MLP_RATIO: 4.0
    OFFSET_SCALE: 1.0
    POST_NORM: false
    REMOVE_CENTER: false
    RES_POST_NORM: false
    USE_CLIP_PROJECTOR: false
  LABEL_SMOOTHING: 0.1
  NAME: internimage_t_1k_224
  NUM_CLASSES: 1000
  PRETRAINED: ''
  RESUME: ''
  TYPE: intern_image
OUTPUT: work_dirs/internimage_t_1k_224
PRINT_FREQ: 10
SAVE_CKPT_NUM: 1
SAVE_FREQ: 1
SEED: 0
TAG: default
TEST:
  CROP: true
  SEQUENTIAL: false
THROUGHPUT_MODE: false
TRAIN:
  ACCUMULATION_STEPS: 1
  AUTO_RESUME: true
  BASE_LR: 0.004
  CLIP_GRAD: 5.0
  EMA:
    DECAY: 0.9999
    ENABLE: true
  EPOCHS: 300
  LR_LAYER_DECAY: false
  LR_LAYER_DECAY_RATIO: 0.875
  LR_SCHEDULER:
    DECAY_EPOCHS: 30
    DECAY_RATE: 0.1
    NAME: cosine
  MIN_LR: 4.0e-05
  OPTIMIZER:
    BETAS:
    - 0.9
    - 0.999
    DCN_LR_MUL: null
    EPS: 1.0e-08
    FREEZE_BACKBONE: null
    MOMENTUM: 0.9
    NAME: adamw
    USE_ZERO: false
  RAND_INIT_FT_HEAD: false
  START_EPOCH: 0
  USE_CHECKPOINT: false
  WARMUP_EPOCHS: 20
  WARMUP_LR: 4.0e-06
  WEIGHT_DECAY: 0.05

[2025-01-17 21:46:54 internimage_t_1k_224] (main.py 174): INFO Creating model:intern_image/internimage_t_1k_224
[2025-01-17 21:47:16 internimage_t_1k_224] (main.py 177): INFO InternImage(
  (patch_embed): StemLayer(
    (conv1): Conv2d(3, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
    (norm1): Sequential(
      (0): to_channels_last()
      (1): LayerNorm((32,), eps=1e-06, elementwise_affine=True)
      (2): to_channels_first()
    )
    (act): GELU()
    (conv2): Conv2d(32, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
    (norm2): Sequential(
      (0): to_channels_last()
      (1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
    )
  )
  (pos_drop): Dropout(p=0.0, inplace=False)
  (levels): ModuleList(
    (0): InternImageBlock(
      (blocks): ModuleList(
        (0): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=64, out_features=72, bias=True)
            (mask): Linear(in_features=64, out_features=36, bias=True)
            (input_proj): Linear(in_features=64, out_features=64, bias=True)
            (output_proj): Linear(in_features=64, out_features=64, bias=True)
          )
          (drop_path): Identity()
          (norm2): Sequential(
            (0): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=64, out_features=256, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=256, out_features=64, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (1): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=64, out_features=72, bias=True)
            (mask): Linear(in_features=64, out_features=36, bias=True)
            (input_proj): Linear(in_features=64, out_features=64, bias=True)
            (output_proj): Linear(in_features=64, out_features=64, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.003)
          (norm2): Sequential(
            (0): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=64, out_features=256, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=256, out_features=64, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (2): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=64, out_features=72, bias=True)
            (mask): Linear(in_features=64, out_features=36, bias=True)
            (input_proj): Linear(in_features=64, out_features=64, bias=True)
            (output_proj): Linear(in_features=64, out_features=64, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.007)
          (norm2): Sequential(
            (0): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=64, out_features=256, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=256, out_features=64, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (3): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=64, out_features=72, bias=True)
            (mask): Linear(in_features=64, out_features=36, bias=True)
            (input_proj): Linear(in_features=64, out_features=64, bias=True)
            (output_proj): Linear(in_features=64, out_features=64, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.010)
          (norm2): Sequential(
            (0): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=64, out_features=256, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=256, out_features=64, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
      )
      (norm): Sequential(
        (0): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
      )
      (downsample): DownsampleLayer(
        (conv): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (norm): Sequential(
          (0): to_channels_last()
          (1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
        )
      )
    )
    (1): InternImageBlock(
      (blocks): ModuleList(
        (0): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=128, out_features=144, bias=True)
            (mask): Linear(in_features=128, out_features=72, bias=True)
            (input_proj): Linear(in_features=128, out_features=128, bias=True)
            (output_proj): Linear(in_features=128, out_features=128, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.014)
          (norm2): Sequential(
            (0): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=128, out_features=512, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=512, out_features=128, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (1): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=128, out_features=144, bias=True)
            (mask): Linear(in_features=128, out_features=72, bias=True)
            (input_proj): Linear(in_features=128, out_features=128, bias=True)
            (output_proj): Linear(in_features=128, out_features=128, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.017)
          (norm2): Sequential(
            (0): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=128, out_features=512, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=512, out_features=128, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (2): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=128, out_features=144, bias=True)
            (mask): Linear(in_features=128, out_features=72, bias=True)
            (input_proj): Linear(in_features=128, out_features=128, bias=True)
            (output_proj): Linear(in_features=128, out_features=128, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.021)
          (norm2): Sequential(
            (0): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=128, out_features=512, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=512, out_features=128, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (3): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=128, out_features=144, bias=True)
            (mask): Linear(in_features=128, out_features=72, bias=True)
            (input_proj): Linear(in_features=128, out_features=128, bias=True)
            (output_proj): Linear(in_features=128, out_features=128, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.024)
          (norm2): Sequential(
            (0): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=128, out_features=512, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=512, out_features=128, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
      )
      (norm): Sequential(
        (0): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
      )
      (downsample): DownsampleLayer(
        (conv): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (norm): Sequential(
          (0): to_channels_last()
          (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
        )
      )
    )
    (2): InternImageBlock(
      (blocks): ModuleList(
        (0): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.028)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (1): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.031)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (2): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.034)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (3): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.038)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (4): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.041)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (5): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.045)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (6): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.048)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (7): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.052)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (8): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.055)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (9): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.059)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (10): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.062)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (11): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.066)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (12): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.069)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (13): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.072)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (14): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.076)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (15): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.079)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (16): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.083)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (17): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=256, out_features=288, bias=True)
            (mask): Linear(in_features=256, out_features=144, bias=True)
            (input_proj): Linear(in_features=256, out_features=256, bias=True)
            (output_proj): Linear(in_features=256, out_features=256, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.086)
          (norm2): Sequential(
            (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=256, out_features=1024, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=1024, out_features=256, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
      )
      (norm): Sequential(
        (0): LayerNorm((256,), eps=1e-06, elementwise_affine=True)
      )
      (downsample): DownsampleLayer(
        (conv): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (norm): Sequential(
          (0): to_channels_last()
          (1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
        )
      )
    )
    (3): InternImageBlock(
      (blocks): ModuleList(
        (0): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=512, out_features=576, bias=True)
            (mask): Linear(in_features=512, out_features=288, bias=True)
            (input_proj): Linear(in_features=512, out_features=512, bias=True)
            (output_proj): Linear(in_features=512, out_features=512, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.090)
          (norm2): Sequential(
            (0): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=512, out_features=2048, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=2048, out_features=512, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (1): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=512, out_features=576, bias=True)
            (mask): Linear(in_features=512, out_features=288, bias=True)
            (input_proj): Linear(in_features=512, out_features=512, bias=True)
            (output_proj): Linear(in_features=512, out_features=512, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.093)
          (norm2): Sequential(
            (0): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=512, out_features=2048, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=2048, out_features=512, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (2): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=512, out_features=576, bias=True)
            (mask): Linear(in_features=512, out_features=288, bias=True)
            (input_proj): Linear(in_features=512, out_features=512, bias=True)
            (output_proj): Linear(in_features=512, out_features=512, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.097)
          (norm2): Sequential(
            (0): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=512, out_features=2048, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=2048, out_features=512, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
        (3): InternImageLayer(
          (norm1): Sequential(
            (0): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
          )
          (dcn): DCNv3(
            (dw_conv): Sequential(
              (0): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
              (1): Sequential(
                (0): to_channels_last()
                (1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
              )
              (2): GELU()
            )
            (offset): Linear(in_features=512, out_features=576, bias=True)
            (mask): Linear(in_features=512, out_features=288, bias=True)
            (input_proj): Linear(in_features=512, out_features=512, bias=True)
            (output_proj): Linear(in_features=512, out_features=512, bias=True)
          )
          (drop_path): DropPath(drop_prob=0.100)
          (norm2): Sequential(
            (0): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
          )
          (mlp): MLPLayer(
            (fc1): Linear(in_features=512, out_features=2048, bias=True)
            (act): GELU()
            (fc2): Linear(in_features=2048, out_features=512, bias=True)
            (drop): Dropout(p=0.0, inplace=False)
          )
        )
      )
      (norm): Sequential(
        (0): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
      )
    )
  )
  (conv_head): Sequential(
    (0): Conv2d(512, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
    (1): Sequential(
      (0): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (2): GELU()
  )
  (head): Linear(in_features=768, out_features=1000, bias=True)
  (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))
)
[2025-01-17 21:47:16 internimage_t_1k_224] (main.py 213): INFO Using native Torch AMP. Training in mixed precision.
[2025-01-17 21:47:17 internimage_t_1k_224] (main.py 225): INFO using fp16_compress_hook!
[2025-01-17 21:47:17 internimage_t_1k_224] (main.py 233): INFO number of params: 29918424
[2025-01-17 21:47:17 internimage_t_1k_224] (main.py 267): INFO no checkpoint found in work_dirs/internimage_t_1k_224, ignoring auto resume
[2025-01-17 21:47:17 internimage_t_1k_224] (main.py 308): INFO Start training
[2025-01-17 21:47:24 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][0/312]	eta 0:37:05 lr 0.000004	time 7.1327 (7.1327)	model_time 3.5897 (3.5897)	loss 6.9363 (6.9363)	grad_norm 0.5964 (0.5964/0.0000)	mem 15750MB
[2025-01-17 21:47:29 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][10/312]	eta 0:05:33 lr 0.000010	time 0.4424 (1.1036)	model_time 0.4422 (0.7812)	loss 6.9431 (6.9553)	grad_norm 0.4755 (0.5357/0.0277)	mem 16099MB
[2025-01-17 21:47:33 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][20/312]	eta 0:03:51 lr 0.000017	time 0.4464 (0.7944)	model_time 0.4460 (0.6254)	loss 6.9539 (6.9486)	grad_norm 0.4948 (0.5235/0.0267)	mem 16099MB
[2025-01-17 21:47:38 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][30/312]	eta 0:03:13 lr 0.000023	time 0.4534 (0.6845)	model_time 0.4533 (0.5699)	loss 6.9064 (6.9409)	grad_norm 0.4668 (0.5094/0.0313)	mem 16099MB
[2025-01-17 21:47:42 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][40/312]	eta 0:02:51 lr 0.000030	time 0.4477 (0.6289)	model_time 0.4475 (0.5421)	loss 6.9170 (6.9368)	grad_norm 0.4043 (0.4894/0.0452)	mem 16099MB
[2025-01-17 21:47:47 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][50/312]	eta 0:02:36 lr 0.000036	time 0.4609 (0.5961)	model_time 0.4607 (0.5263)	loss 6.8691 (6.9289)	grad_norm 0.4182 (0.4733/0.0524)	mem 16099MB
[2025-01-17 21:47:52 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][60/312]	eta 0:02:24 lr 0.000042	time 0.4379 (0.5728)	model_time 0.4377 (0.5144)	loss 6.9049 (6.9228)	grad_norm 0.3863 (0.4616/0.0562)	mem 16099MB
[2025-01-17 21:47:56 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][70/312]	eta 0:02:14 lr 0.000049	time 0.4382 (0.5575)	model_time 0.4380 (0.5072)	loss 6.8734 (6.9178)	grad_norm 0.4156 (0.4511/0.0586)	mem 16099MB
[2025-01-17 21:48:01 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][80/312]	eta 0:02:06 lr 0.000055	time 0.4590 (0.5455)	model_time 0.4588 (0.5015)	loss 6.8451 (6.9133)	grad_norm 0.3945 (0.4440/0.0599)	mem 16099MB
[2025-01-17 21:48:05 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][90/312]	eta 0:01:58 lr 0.000062	time 0.4745 (0.5354)	model_time 0.4743 (0.4962)	loss 6.8973 (6.9085)	grad_norm 0.3735 (0.4430/0.0584)	mem 16099MB
[2025-01-17 21:48:10 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][100/312]	eta 0:01:51 lr 0.000068	time 0.4395 (0.5270)	model_time 0.4391 (0.4916)	loss 6.8747 (6.9045)	grad_norm 0.4788 (0.4461/0.0625)	mem 16099MB
[2025-01-17 21:48:14 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][110/312]	eta 0:01:45 lr 0.000074	time 0.4439 (0.5207)	model_time 0.4435 (0.4884)	loss 6.7811 (6.8993)	grad_norm 0.6120 (0.4569/0.0763)	mem 16099MB
[2025-01-17 21:48:19 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][120/312]	eta 0:01:38 lr 0.000081	time 0.4471 (0.5155)	model_time 0.4467 (0.4859)	loss 6.8082 (6.8943)	grad_norm 0.7132 (0.4732/0.0976)	mem 16099MB
[2025-01-17 21:48:23 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][130/312]	eta 0:01:32 lr 0.000087	time 0.4487 (0.5107)	model_time 0.4485 (0.4833)	loss 6.8781 (6.8896)	grad_norm 0.6191 (0.4940/0.1384)	mem 16099MB
[2025-01-17 21:48:28 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][140/312]	eta 0:01:27 lr 0.000094	time 0.5009 (0.5072)	model_time 0.5005 (0.4818)	loss 6.7929 (6.8837)	grad_norm 0.8867 (0.5068/0.1441)	mem 16099MB
[2025-01-17 21:48:33 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][150/312]	eta 0:01:21 lr 0.000100	time 0.4403 (0.5034)	model_time 0.4401 (0.4796)	loss 6.7813 (6.8794)	grad_norm 0.6639 (0.5257/0.1633)	mem 16099MB
[2025-01-17 21:48:37 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][160/312]	eta 0:01:16 lr 0.000106	time 0.4512 (0.5004)	model_time 0.4510 (0.4780)	loss 6.8519 (6.8747)	grad_norm 1.6084 (0.5606/0.2220)	mem 16099MB
[2025-01-17 21:48:42 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][170/312]	eta 0:01:10 lr 0.000113	time 0.4469 (0.4977)	model_time 0.4464 (0.4766)	loss 6.7766 (6.8697)	grad_norm 1.3393 (0.6019/0.2803)	mem 16099MB
[2025-01-17 21:48:46 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][180/312]	eta 0:01:05 lr 0.000119	time 0.4394 (0.4954)	model_time 0.4392 (0.4755)	loss 6.8242 (6.8638)	grad_norm 1.7728 (0.6452/0.3378)	mem 16099MB
[2025-01-17 21:48:51 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][190/312]	eta 0:01:00 lr 0.000126	time 0.4479 (0.4934)	model_time 0.4475 (0.4745)	loss 6.7642 (6.8590)	grad_norm 1.8268 (0.6862/0.3767)	mem 16099MB
[2025-01-17 21:48:55 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][200/312]	eta 0:00:55 lr 0.000132	time 0.4698 (0.4915)	model_time 0.4693 (0.4736)	loss 6.7502 (6.8528)	grad_norm 1.5288 (0.7376/0.4360)	mem 16099MB
[2025-01-17 21:49:00 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][210/312]	eta 0:00:49 lr 0.000138	time 0.4496 (0.4898)	model_time 0.4495 (0.4726)	loss 6.7611 (6.8480)	grad_norm 2.1617 (0.7854/0.4842)	mem 16099MB
[2025-01-17 21:49:04 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][220/312]	eta 0:00:44 lr 0.000145	time 0.4407 (0.4879)	model_time 0.4406 (0.4715)	loss 6.7481 (6.8423)	grad_norm 2.9866 (0.8331/0.5334)	mem 16099MB
[2025-01-17 21:49:09 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][230/312]	eta 0:00:39 lr 0.000151	time 0.4480 (0.4866)	model_time 0.4479 (0.4708)	loss 6.6709 (6.8380)	grad_norm 2.6711 (0.9088/0.6511)	mem 16099MB
[2025-01-17 21:49:14 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][240/312]	eta 0:00:34 lr 0.000158	time 0.4397 (0.4855)	model_time 0.4393 (0.4704)	loss 6.7324 (6.8334)	grad_norm 2.2392 (0.9722/0.7200)	mem 16099MB
[2025-01-17 21:49:18 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][250/312]	eta 0:00:30 lr 0.000164	time 0.4419 (0.4842)	model_time 0.4418 (0.4697)	loss 6.7239 (6.8278)	grad_norm 2.8250 (1.0272/0.7657)	mem 16099MB
[2025-01-17 21:49:23 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][260/312]	eta 0:00:25 lr 0.000170	time 0.4614 (0.4833)	model_time 0.4613 (0.4693)	loss 6.6860 (6.8229)	grad_norm 1.8314 (1.0871/0.8166)	mem 16099MB
[2025-01-17 21:49:27 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][270/312]	eta 0:00:20 lr 0.000177	time 0.4873 (0.4823)	model_time 0.4871 (0.4688)	loss 6.6811 (6.8185)	grad_norm 2.3664 (1.1509/0.8779)	mem 16099MB
[2025-01-17 21:49:32 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][280/312]	eta 0:00:15 lr 0.000183	time 0.4445 (0.4813)	model_time 0.4440 (0.4684)	loss 6.7257 (6.8159)	grad_norm 3.5013 (1.2356/0.9832)	mem 16099MB
[2025-01-17 21:49:36 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][290/312]	eta 0:00:10 lr 0.000190	time 0.4481 (0.4804)	model_time 0.4480 (0.4678)	loss 6.5332 (6.8110)	grad_norm 1.8865 (1.2842/1.0135)	mem 16099MB
[2025-01-17 21:49:41 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][300/312]	eta 0:00:05 lr 0.000196	time 0.4386 (0.4800)	model_time 0.4385 (0.4678)	loss 6.7027 (6.8055)	grad_norm 2.6551 (1.3470/1.0645)	mem 16099MB
[2025-01-17 21:49:45 internimage_t_1k_224] (main.py 510): INFO Train: [0/300][310/312]	eta 0:00:00 lr 0.000203	time 0.4324 (0.4788)	model_time 0.4323 (0.4670)	loss 6.8173 (6.8029)	grad_norm 5.4406 (1.4486/1.1532)	mem 16099MB
[2025-01-17 21:49:46 internimage_t_1k_224] (main.py 519): INFO EPOCH 0 training takes 0:02:29
[2025-01-17 21:49:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_0.pth saving......
[2025-01-17 21:49:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_0.pth saved !!!
[2025-01-17 21:49:57 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 9.885 (9.885)	Loss 6.1458 (6.1458)	Acc@1 1.831 (1.831)	Acc@5 8.130 (8.130)	Mem 16099MB
[2025-01-17 21:49:59 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.087)	Loss 6.2849 (6.2797)	Acc@1 1.514 (1.649)	Acc@5 6.274 (5.970)	Mem 16099MB
[2025-01-17 21:49:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:0] * Acc@1 2.005 Acc@5 7.034
[2025-01-17 21:49:59 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 2.0%
[2025-01-17 21:49:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 21:50:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 21:50:00 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 2.01%
[2025-01-17 21:50:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.281 (7.281)	Loss 6.9095 (6.9095)	Acc@1 0.806 (0.806)	Acc@5 2.148 (2.148)	Mem 16099MB
[2025-01-17 21:50:11 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.976)	Loss 6.9464 (6.9159)	Acc@1 0.000 (0.111)	Acc@5 0.073 (0.604)	Mem 16099MB
[2025-01-17 21:50:11 internimage_t_1k_224] (main.py 575): INFO [Epoch:0] * Acc@1 0.102 Acc@5 0.558
[2025-01-17 21:50:11 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.1%
[2025-01-17 21:50:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 21:50:13 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 21:50:13 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.10%
[2025-01-17 21:50:16 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][0/312]	eta 0:14:55 lr 0.000204	time 2.8714 (2.8714)	model_time 0.7260 (0.7260)	loss 6.7528 (6.7528)	grad_norm 3.5790 (3.5790/0.0000)	mem 16099MB
[2025-01-17 21:50:20 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][10/312]	eta 0:03:25 lr 0.000210	time 0.4598 (0.6788)	model_time 0.4593 (0.4835)	loss 6.7782 (6.7480)	grad_norm 2.8419 (3.2305/0.7709)	mem 16099MB
[2025-01-17 21:50:25 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][20/312]	eta 0:02:47 lr 0.000217	time 0.4612 (0.5722)	model_time 0.4610 (0.4697)	loss 6.7139 (6.7057)	grad_norm 1.7682 (3.0185/0.7595)	mem 16099MB
[2025-01-17 21:50:29 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][30/312]	eta 0:02:30 lr 0.000223	time 0.4485 (0.5344)	model_time 0.4483 (0.4649)	loss 6.6877 (6.6916)	grad_norm 2.1410 (3.0317/0.8332)	mem 16099MB
[2025-01-17 21:50:34 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][40/312]	eta 0:02:20 lr 0.000229	time 0.4433 (0.5151)	model_time 0.4431 (0.4625)	loss 6.6388 (6.6794)	grad_norm 2.8389 (3.0401/0.8909)	mem 16099MB
[2025-01-17 21:50:39 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][50/312]	eta 0:02:11 lr 0.000236	time 0.4535 (0.5031)	model_time 0.4534 (0.4607)	loss 6.6240 (6.6667)	grad_norm 5.0263 (3.1460/0.9846)	mem 16099MB
[2025-01-17 21:50:43 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][60/312]	eta 0:02:04 lr 0.000242	time 0.4432 (0.4951)	model_time 0.4430 (0.4596)	loss 6.5655 (6.6564)	grad_norm 3.1072 (3.2022/0.9378)	mem 16099MB
[2025-01-17 21:50:48 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][70/312]	eta 0:01:58 lr 0.000249	time 0.4459 (0.4888)	model_time 0.4457 (0.4583)	loss 6.4549 (6.6492)	grad_norm 2.2013 (3.2042/0.9443)	mem 16099MB
[2025-01-17 21:50:52 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][80/312]	eta 0:01:52 lr 0.000255	time 0.4455 (0.4839)	model_time 0.4451 (0.4571)	loss 6.7089 (6.6383)	grad_norm 2.8437 (3.2828/0.9826)	mem 16099MB
[2025-01-17 21:50:57 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][90/312]	eta 0:01:46 lr 0.000261	time 0.4557 (0.4806)	model_time 0.4555 (0.4567)	loss 6.4861 (6.6374)	grad_norm 3.7592 (3.2868/0.9614)	mem 16099MB
[2025-01-17 21:51:01 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][100/312]	eta 0:01:41 lr 0.000268	time 0.4447 (0.4780)	model_time 0.4445 (0.4564)	loss 6.5923 (6.6368)	grad_norm 2.9605 (3.2625/0.9361)	mem 16099MB
[2025-01-17 21:51:06 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][110/312]	eta 0:01:36 lr 0.000274	time 0.4063 (0.4753)	model_time 0.4059 (0.4557)	loss 6.3623 (6.6281)	grad_norm inf (3.2905/0.9232)	mem 16099MB
[2025-01-17 21:51:10 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][120/312]	eta 0:01:30 lr 0.000281	time 0.4463 (0.4736)	model_time 0.4459 (0.4555)	loss 6.6681 (6.6295)	grad_norm 3.3136 (3.2823/0.9383)	mem 16099MB
[2025-01-17 21:51:15 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][130/312]	eta 0:01:25 lr 0.000287	time 0.4496 (0.4720)	model_time 0.4494 (0.4553)	loss 6.5549 (6.6276)	grad_norm 2.7823 (3.3342/0.9818)	mem 16099MB
[2025-01-17 21:51:19 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][140/312]	eta 0:01:20 lr 0.000293	time 0.4503 (0.4702)	model_time 0.4502 (0.4547)	loss 6.4405 (6.6219)	grad_norm 2.9916 (3.3427/0.9834)	mem 16099MB
[2025-01-17 21:51:24 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][150/312]	eta 0:01:15 lr 0.000300	time 0.4437 (0.4690)	model_time 0.4432 (0.4544)	loss 6.5041 (6.6137)	grad_norm 1.8569 (3.3196/0.9670)	mem 16099MB
[2025-01-17 21:51:28 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][160/312]	eta 0:01:11 lr 0.000306	time 0.4601 (0.4688)	model_time 0.4599 (0.4551)	loss 6.3991 (6.6044)	grad_norm 3.9315 (3.3148/0.9731)	mem 16099MB
[2025-01-17 21:51:33 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][170/312]	eta 0:01:06 lr 0.000313	time 0.4395 (0.4679)	model_time 0.4387 (0.4549)	loss 6.7631 (6.6014)	grad_norm 3.8043 (3.2974/0.9659)	mem 16099MB
[2025-01-17 21:51:37 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][180/312]	eta 0:01:01 lr 0.000319	time 0.4527 (0.4674)	model_time 0.4523 (0.4551)	loss 6.2023 (6.5984)	grad_norm 3.5282 (3.3000/0.9579)	mem 16099MB
[2025-01-17 21:51:42 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][190/312]	eta 0:00:56 lr 0.000325	time 0.4513 (0.4664)	model_time 0.4508 (0.4548)	loss 6.2827 (6.5935)	grad_norm 3.0732 (3.3008/0.9447)	mem 16099MB
[2025-01-17 21:51:47 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][200/312]	eta 0:00:52 lr 0.000332	time 0.4597 (0.4658)	model_time 0.4593 (0.4547)	loss 6.6574 (6.5945)	grad_norm 3.4928 (3.3046/0.9303)	mem 16099MB
[2025-01-17 21:51:51 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][210/312]	eta 0:00:47 lr 0.000338	time 0.4405 (0.4650)	model_time 0.4403 (0.4545)	loss 6.4767 (6.5876)	grad_norm 4.6659 (3.3461/0.9637)	mem 16099MB
[2025-01-17 21:51:55 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][220/312]	eta 0:00:42 lr 0.000345	time 0.4404 (0.4642)	model_time 0.4402 (0.4541)	loss 6.5688 (6.5841)	grad_norm 3.5619 (3.3945/0.9903)	mem 16099MB
[2025-01-17 21:52:00 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][230/312]	eta 0:00:38 lr 0.000351	time 0.4407 (0.4649)	model_time 0.4403 (0.4552)	loss 6.5282 (6.5779)	grad_norm 3.3145 (3.3900/0.9785)	mem 16099MB
[2025-01-17 21:52:05 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][240/312]	eta 0:00:33 lr 0.000357	time 0.4854 (0.4644)	model_time 0.4852 (0.4552)	loss 6.5391 (6.5761)	grad_norm 3.0546 (3.3901/0.9757)	mem 16099MB
[2025-01-17 21:52:09 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][250/312]	eta 0:00:28 lr 0.000364	time 0.4518 (0.4638)	model_time 0.4517 (0.4549)	loss 6.5371 (6.5755)	grad_norm 3.6224 (3.3763/0.9741)	mem 16099MB
[2025-01-17 21:52:14 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][260/312]	eta 0:00:24 lr 0.000370	time 0.4482 (0.4633)	model_time 0.4480 (0.4547)	loss 6.3134 (6.5728)	grad_norm 2.9860 (3.4012/0.9775)	mem 16099MB
[2025-01-17 21:52:18 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][270/312]	eta 0:00:19 lr 0.000377	time 0.4495 (0.4628)	model_time 0.4493 (0.4545)	loss 6.6599 (6.5709)	grad_norm 3.7649 (3.4138/1.0024)	mem 16099MB
[2025-01-17 21:52:23 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][280/312]	eta 0:00:14 lr 0.000383	time 0.4477 (0.4624)	model_time 0.4473 (0.4544)	loss 6.2167 (6.5682)	grad_norm 3.5551 (3.4108/0.9991)	mem 16099MB
[2025-01-17 21:52:27 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][290/312]	eta 0:00:10 lr 0.000390	time 0.4562 (0.4619)	model_time 0.4561 (0.4542)	loss 6.1319 (6.5614)	grad_norm 6.6186 (3.4267/1.0181)	mem 16099MB
[2025-01-17 21:52:32 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][300/312]	eta 0:00:05 lr 0.000396	time 0.4359 (0.4615)	model_time 0.4358 (0.4540)	loss 6.5682 (6.5583)	grad_norm 2.8770 (3.4731/1.0666)	mem 16099MB
[2025-01-17 21:52:36 internimage_t_1k_224] (main.py 510): INFO Train: [1/300][310/312]	eta 0:00:00 lr 0.000402	time 0.4370 (0.4609)	model_time 0.4369 (0.4536)	loss 6.6663 (6.5587)	grad_norm 2.4216 (3.4708/1.0706)	mem 16099MB
[2025-01-17 21:52:37 internimage_t_1k_224] (main.py 519): INFO EPOCH 1 training takes 0:02:23
[2025-01-17 21:52:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_1.pth saving......
[2025-01-17 21:52:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_1.pth saved !!!
[2025-01-17 21:52:45 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.262 (7.262)	Loss 5.5874 (5.5874)	Acc@1 3.003 (3.003)	Acc@5 13.257 (13.257)	Mem 16099MB
[2025-01-17 21:52:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.992)	Loss 5.7907 (5.7081)	Acc@1 3.784 (3.893)	Acc@5 12.476 (12.698)	Mem 16099MB
[2025-01-17 21:52:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:1] * Acc@1 4.505 Acc@5 13.994
[2025-01-17 21:52:49 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 4.5%
[2025-01-17 21:52:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 21:52:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 21:52:50 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 4.50%
[2025-01-17 21:52:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.496 (7.496)	Loss 6.8962 (6.8962)	Acc@1 0.610 (0.610)	Acc@5 1.855 (1.855)	Mem 16099MB
[2025-01-17 21:53:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.988)	Loss 6.9434 (6.9078)	Acc@1 0.000 (0.107)	Acc@5 0.024 (0.668)	Mem 16099MB
[2025-01-17 21:53:01 internimage_t_1k_224] (main.py 575): INFO [Epoch:1] * Acc@1 0.102 Acc@5 0.626
[2025-01-17 21:53:01 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.1%
[2025-01-17 21:53:01 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.10%
[2025-01-17 21:53:04 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][0/312]	eta 0:15:56 lr 0.000404	time 3.0669 (3.0669)	model_time 0.4747 (0.4747)	loss 6.5293 (6.5293)	grad_norm 3.2293 (3.2293/0.0000)	mem 16099MB
[2025-01-17 21:53:09 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][10/312]	eta 0:03:32 lr 0.000410	time 0.4376 (0.7029)	model_time 0.4375 (0.4669)	loss 6.3989 (6.4666)	grad_norm 2.7317 (3.6829/0.6929)	mem 16099MB
[2025-01-17 21:53:14 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][20/312]	eta 0:02:51 lr 0.000416	time 0.4522 (0.5867)	model_time 0.4521 (0.4629)	loss 6.2451 (6.4021)	grad_norm 3.6750 (3.8124/0.6537)	mem 16099MB
[2025-01-17 21:53:18 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][30/312]	eta 0:02:33 lr 0.000423	time 0.4467 (0.5428)	model_time 0.4465 (0.4588)	loss 6.2997 (6.4114)	grad_norm 2.7026 (3.9609/0.8400)	mem 16099MB
[2025-01-17 21:53:23 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][40/312]	eta 0:02:22 lr 0.000429	time 0.4349 (0.5231)	model_time 0.4347 (0.4595)	loss 6.4079 (6.3914)	grad_norm 3.9970 (4.0543/0.8379)	mem 16099MB
[2025-01-17 21:53:27 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][50/312]	eta 0:02:13 lr 0.000436	time 0.4404 (0.5084)	model_time 0.4400 (0.4573)	loss 6.5018 (6.4115)	grad_norm 5.2497 (3.9719/0.9166)	mem 16099MB
[2025-01-17 21:53:32 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][60/312]	eta 0:02:05 lr 0.000442	time 0.4448 (0.4990)	model_time 0.4444 (0.4562)	loss 6.5110 (6.4084)	grad_norm 3.6224 (3.8597/0.9181)	mem 16099MB
[2025-01-17 21:53:36 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][70/312]	eta 0:01:59 lr 0.000448	time 0.4454 (0.4926)	model_time 0.4450 (0.4557)	loss 6.4248 (6.4006)	grad_norm 2.9732 (3.7919/0.9128)	mem 16099MB
[2025-01-17 21:53:41 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][80/312]	eta 0:01:53 lr 0.000455	time 0.4373 (0.4877)	model_time 0.4372 (0.4553)	loss 6.4850 (6.3923)	grad_norm 4.5285 (3.8044/0.9075)	mem 16099MB
[2025-01-17 21:53:45 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][90/312]	eta 0:01:47 lr 0.000461	time 0.4466 (0.4839)	model_time 0.4461 (0.4550)	loss 6.5159 (6.3806)	grad_norm 2.5859 (3.7376/0.9054)	mem 16099MB
[2025-01-17 21:53:50 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][100/312]	eta 0:01:41 lr 0.000468	time 0.4473 (0.4806)	model_time 0.4469 (0.4545)	loss 6.2102 (6.3735)	grad_norm 2.1190 (3.6721/0.9006)	mem 16099MB
[2025-01-17 21:53:54 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][110/312]	eta 0:01:36 lr 0.000474	time 0.4441 (0.4774)	model_time 0.4439 (0.4537)	loss 6.4051 (6.3755)	grad_norm 4.0387 (3.7253/0.9368)	mem 16099MB
[2025-01-17 21:53:59 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][120/312]	eta 0:01:31 lr 0.000480	time 0.4453 (0.4751)	model_time 0.4449 (0.4533)	loss 6.4870 (6.3791)	grad_norm 4.4871 (3.7690/0.9788)	mem 16099MB
[2025-01-17 21:54:03 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][130/312]	eta 0:01:26 lr 0.000487	time 0.4520 (0.4733)	model_time 0.4519 (0.4531)	loss 5.9878 (6.3715)	grad_norm 3.3281 (3.7686/0.9775)	mem 16099MB
[2025-01-17 21:54:08 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][140/312]	eta 0:01:21 lr 0.000493	time 0.4625 (0.4733)	model_time 0.4621 (0.4545)	loss 6.4211 (6.3749)	grad_norm 2.7184 (3.7299/0.9779)	mem 16099MB
[2025-01-17 21:54:12 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][150/312]	eta 0:01:16 lr 0.000500	time 0.4472 (0.4717)	model_time 0.4470 (0.4542)	loss 6.0119 (6.3756)	grad_norm 2.9887 (3.6833/0.9712)	mem 16099MB
[2025-01-17 21:54:17 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][160/312]	eta 0:01:11 lr 0.000506	time 0.4442 (0.4704)	model_time 0.4438 (0.4539)	loss 6.0717 (6.3746)	grad_norm 3.4472 (3.6819/0.9473)	mem 16099MB
[2025-01-17 21:54:21 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][170/312]	eta 0:01:06 lr 0.000512	time 0.4485 (0.4694)	model_time 0.4483 (0.4538)	loss 6.1887 (6.3746)	grad_norm 2.9022 (3.6566/0.9394)	mem 16099MB
[2025-01-17 21:54:26 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][180/312]	eta 0:01:01 lr 0.000519	time 0.4590 (0.4683)	model_time 0.4586 (0.4536)	loss 6.6173 (6.3698)	grad_norm 3.1551 (3.6545/0.9461)	mem 16099MB
[2025-01-17 21:54:31 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][190/312]	eta 0:00:57 lr 0.000525	time 0.4432 (0.4678)	model_time 0.4430 (0.4538)	loss 6.4738 (6.3585)	grad_norm 5.5837 (3.6539/0.9500)	mem 16099MB
[2025-01-17 21:54:35 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][200/312]	eta 0:00:52 lr 0.000532	time 0.4463 (0.4668)	model_time 0.4458 (0.4536)	loss 5.8879 (6.3557)	grad_norm 3.2619 (3.6265/0.9456)	mem 16099MB
[2025-01-17 21:54:39 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][210/312]	eta 0:00:47 lr 0.000538	time 0.4425 (0.4658)	model_time 0.4423 (0.4532)	loss 5.8964 (6.3451)	grad_norm 4.0295 (3.6209/0.9473)	mem 16099MB
[2025-01-17 21:54:44 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][220/312]	eta 0:00:42 lr 0.000544	time 0.4374 (0.4650)	model_time 0.4373 (0.4528)	loss 5.8759 (6.3373)	grad_norm 3.2515 (3.6153/0.9323)	mem 16099MB
[2025-01-17 21:54:49 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][230/312]	eta 0:00:38 lr 0.000551	time 0.4461 (0.4646)	model_time 0.4457 (0.4530)	loss 6.3940 (6.3365)	grad_norm 3.0014 (3.6108/0.9294)	mem 16099MB
[2025-01-17 21:54:53 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][240/312]	eta 0:00:33 lr 0.000557	time 0.4405 (0.4640)	model_time 0.4400 (0.4529)	loss 6.1831 (6.3335)	grad_norm 2.3355 (3.5876/0.9268)	mem 16099MB
[2025-01-17 21:54:58 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][250/312]	eta 0:00:28 lr 0.000564	time 0.4560 (0.4637)	model_time 0.4555 (0.4530)	loss 6.1547 (6.3331)	grad_norm 3.4283 (3.5680/0.9252)	mem 16099MB
[2025-01-17 21:55:02 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][260/312]	eta 0:00:24 lr 0.000570	time 0.4484 (0.4637)	model_time 0.4480 (0.4534)	loss 5.8070 (6.3246)	grad_norm 3.5221 (3.5600/0.9268)	mem 16099MB
[2025-01-17 21:55:07 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][270/312]	eta 0:00:19 lr 0.000577	time 0.4615 (0.4642)	model_time 0.4613 (0.4542)	loss 6.3366 (6.3213)	grad_norm 2.7848 (3.5308/0.9230)	mem 16099MB
[2025-01-17 21:55:11 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][280/312]	eta 0:00:14 lr 0.000583	time 0.4469 (0.4637)	model_time 0.4465 (0.4541)	loss 6.3015 (6.3173)	grad_norm 3.3044 (3.5260/0.9132)	mem 16099MB
[2025-01-17 21:55:16 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][290/312]	eta 0:00:10 lr 0.000589	time 0.4514 (0.4632)	model_time 0.4510 (0.4539)	loss 6.4490 (6.3107)	grad_norm 2.6261 (3.4946/0.9154)	mem 16099MB
[2025-01-17 21:55:20 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][300/312]	eta 0:00:05 lr 0.000596	time 0.4361 (0.4626)	model_time 0.4360 (0.4536)	loss 6.3754 (6.3122)	grad_norm 3.8083 (3.5198/0.9236)	mem 16099MB
[2025-01-17 21:55:25 internimage_t_1k_224] (main.py 510): INFO Train: [2/300][310/312]	eta 0:00:00 lr 0.000602	time 0.4351 (0.4618)	model_time 0.4350 (0.4531)	loss 5.6755 (6.3081)	grad_norm 3.6231 (3.5070/0.9300)	mem 16099MB
[2025-01-17 21:55:25 internimage_t_1k_224] (main.py 519): INFO EPOCH 2 training takes 0:02:24
[2025-01-17 21:55:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_2.pth saving......
[2025-01-17 21:55:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_2.pth saved !!!
[2025-01-17 21:55:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.582 (7.582)	Loss 5.1909 (5.1909)	Acc@1 7.617 (7.617)	Acc@5 22.095 (22.095)	Mem 16099MB
[2025-01-17 21:55:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.000)	Loss 5.2090 (5.1415)	Acc@1 7.520 (7.990)	Acc@5 19.238 (21.598)	Mem 16099MB
[2025-01-17 21:55:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:2] * Acc@1 8.717 Acc@5 22.773
[2025-01-17 21:55:38 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 8.7%
[2025-01-17 21:55:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 21:55:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 21:55:39 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 8.72%
[2025-01-17 21:55:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.530 (7.530)	Loss 6.8758 (6.8758)	Acc@1 0.317 (0.317)	Acc@5 1.440 (1.440)	Mem 16099MB
[2025-01-17 21:55:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.011)	Loss 6.9404 (6.8959)	Acc@1 0.000 (0.149)	Acc@5 0.049 (0.790)	Mem 16099MB
[2025-01-17 21:55:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:2] * Acc@1 0.144 Acc@5 0.764
[2025-01-17 21:55:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.1%
[2025-01-17 21:55:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 21:55:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 21:55:51 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.14%
[2025-01-17 21:55:55 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][0/312]	eta 0:15:50 lr 0.000603	time 3.0449 (3.0449)	model_time 0.4774 (0.4774)	loss 6.4907 (6.4907)	grad_norm 3.4651 (3.4651/0.0000)	mem 16099MB
[2025-01-17 21:55:59 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][10/312]	eta 0:03:27 lr 0.000610	time 0.4481 (0.6876)	model_time 0.4476 (0.4538)	loss 5.8668 (6.1112)	grad_norm 3.3467 (3.6320/0.6695)	mem 16099MB
[2025-01-17 21:56:04 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][20/312]	eta 0:02:48 lr 0.000616	time 0.4422 (0.5764)	model_time 0.4418 (0.4538)	loss 6.0630 (6.0915)	grad_norm 2.4052 (3.4944/0.8053)	mem 16099MB
[2025-01-17 21:56:08 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][30/312]	eta 0:02:31 lr 0.000623	time 0.4398 (0.5370)	model_time 0.4394 (0.4538)	loss 6.4504 (6.1404)	grad_norm 2.8392 (3.3266/0.8110)	mem 16099MB
[2025-01-17 21:56:13 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][40/312]	eta 0:02:20 lr 0.000629	time 0.4493 (0.5154)	model_time 0.4492 (0.4524)	loss 5.5905 (6.1632)	grad_norm 2.6243 (3.3179/0.7675)	mem 16099MB
[2025-01-17 21:56:17 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][50/312]	eta 0:02:11 lr 0.000635	time 0.4448 (0.5026)	model_time 0.4443 (0.4519)	loss 6.5354 (6.1712)	grad_norm 3.9580 (3.3699/0.9282)	mem 16099MB
[2025-01-17 21:56:22 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][60/312]	eta 0:02:04 lr 0.000642	time 0.4418 (0.4937)	model_time 0.4416 (0.4513)	loss 5.5975 (6.1542)	grad_norm 2.3473 (3.3798/0.9133)	mem 16099MB
[2025-01-17 21:56:26 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][70/312]	eta 0:01:57 lr 0.000648	time 0.4438 (0.4873)	model_time 0.4434 (0.4508)	loss 6.1443 (6.1567)	grad_norm 2.6670 (3.4659/0.9814)	mem 16099MB
[2025-01-17 21:56:31 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][80/312]	eta 0:01:52 lr 0.000655	time 0.4562 (0.4834)	model_time 0.4561 (0.4513)	loss 5.6462 (6.1644)	grad_norm 4.1880 (3.4866/0.9610)	mem 16099MB
[2025-01-17 21:56:35 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][90/312]	eta 0:01:46 lr 0.000661	time 0.4827 (0.4802)	model_time 0.4822 (0.4516)	loss 6.1309 (6.1406)	grad_norm 2.6283 (3.4937/0.9949)	mem 16099MB
[2025-01-17 21:56:40 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][100/312]	eta 0:01:41 lr 0.000667	time 0.4637 (0.4788)	model_time 0.4633 (0.4530)	loss 6.3190 (6.1436)	grad_norm 3.4667 (3.4714/1.0075)	mem 16099MB
[2025-01-17 21:56:44 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][110/312]	eta 0:01:36 lr 0.000674	time 0.4387 (0.4761)	model_time 0.4382 (0.4526)	loss 5.9544 (6.1459)	grad_norm 2.4126 (3.4568/1.0055)	mem 16099MB
[2025-01-17 21:56:49 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][120/312]	eta 0:01:31 lr 0.000680	time 0.5540 (0.4744)	model_time 0.5539 (0.4528)	loss 6.2059 (6.1487)	grad_norm 4.3833 (3.5224/1.0839)	mem 16099MB
[2025-01-17 21:56:53 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][130/312]	eta 0:01:25 lr 0.000687	time 0.4443 (0.4723)	model_time 0.4441 (0.4523)	loss 5.9247 (6.1470)	grad_norm 2.5498 (3.5052/1.0919)	mem 16099MB
[2025-01-17 21:56:58 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][140/312]	eta 0:01:20 lr 0.000693	time 0.4459 (0.4707)	model_time 0.4454 (0.4521)	loss 6.3988 (6.1395)	grad_norm 2.6008 (3.5308/1.1052)	mem 16099MB
[2025-01-17 21:57:02 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][150/312]	eta 0:01:16 lr 0.000699	time 0.4451 (0.4703)	model_time 0.4447 (0.4529)	loss 6.1493 (6.1360)	grad_norm 3.8154 (3.5150/1.0781)	mem 16099MB
[2025-01-17 21:57:07 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][160/312]	eta 0:01:11 lr 0.000706	time 0.4441 (0.4689)	model_time 0.4436 (0.4525)	loss 6.3351 (6.1294)	grad_norm 3.1432 (3.5253/1.0696)	mem 16099MB
[2025-01-17 21:57:12 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][170/312]	eta 0:01:06 lr 0.000712	time 0.4535 (0.4686)	model_time 0.4534 (0.4532)	loss 6.1938 (6.1280)	grad_norm 3.3866 (3.5095/1.0546)	mem 16099MB
[2025-01-17 21:57:16 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][180/312]	eta 0:01:01 lr 0.000719	time 0.4453 (0.4681)	model_time 0.4448 (0.4536)	loss 6.2520 (6.1309)	grad_norm 3.6099 (3.4976/1.0348)	mem 16099MB
[2025-01-17 21:57:21 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][190/312]	eta 0:00:57 lr 0.000725	time 0.4428 (0.4675)	model_time 0.4427 (0.4537)	loss 6.1400 (6.1280)	grad_norm 3.5803 (3.4864/1.0239)	mem 16099MB
[2025-01-17 21:57:25 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][200/312]	eta 0:00:52 lr 0.000731	time 0.4460 (0.4666)	model_time 0.4456 (0.4534)	loss 5.9697 (6.1266)	grad_norm 4.7246 (3.5165/1.0307)	mem 16099MB
[2025-01-17 21:57:30 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][210/312]	eta 0:00:47 lr 0.000738	time 0.4466 (0.4659)	model_time 0.4462 (0.4534)	loss 6.5646 (6.1262)	grad_norm 2.4386 (3.5369/1.0257)	mem 16099MB
[2025-01-17 21:57:34 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][220/312]	eta 0:00:42 lr 0.000744	time 0.4454 (0.4652)	model_time 0.4450 (0.4532)	loss 5.9961 (6.1234)	grad_norm 4.6414 (3.5565/1.0230)	mem 16099MB
[2025-01-17 21:57:39 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][230/312]	eta 0:00:38 lr 0.000751	time 0.4492 (0.4647)	model_time 0.4487 (0.4532)	loss 6.1272 (6.1138)	grad_norm 2.6910 (3.5536/1.0150)	mem 16099MB
[2025-01-17 21:57:43 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][240/312]	eta 0:00:33 lr 0.000757	time 0.4511 (0.4640)	model_time 0.4507 (0.4530)	loss 6.3642 (6.1174)	grad_norm 2.4156 (3.5330/1.0107)	mem 16099MB
[2025-01-17 21:57:48 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][250/312]	eta 0:00:28 lr 0.000763	time 0.4413 (0.4634)	model_time 0.4412 (0.4527)	loss 6.3371 (6.1225)	grad_norm 2.8603 (3.5244/1.0160)	mem 16099MB
[2025-01-17 21:57:52 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][260/312]	eta 0:00:24 lr 0.000770	time 0.4530 (0.4629)	model_time 0.4526 (0.4527)	loss 6.1475 (6.1173)	grad_norm 6.9975 (3.5067/1.0372)	mem 16099MB
[2025-01-17 21:57:57 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][270/312]	eta 0:00:19 lr 0.000776	time 0.4492 (0.4629)	model_time 0.4488 (0.4530)	loss 6.1688 (6.1190)	grad_norm 3.2824 (3.4984/1.0269)	mem 16099MB
[2025-01-17 21:58:01 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][280/312]	eta 0:00:14 lr 0.000783	time 0.4457 (0.4624)	model_time 0.4455 (0.4529)	loss 6.4802 (6.1171)	grad_norm 2.1711 (3.4859/1.0189)	mem 16099MB
[2025-01-17 21:58:06 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][290/312]	eta 0:00:10 lr 0.000789	time 0.4458 (0.4619)	model_time 0.4454 (0.4527)	loss 5.9471 (6.1088)	grad_norm 3.4431 (3.4909/1.0108)	mem 16099MB
[2025-01-17 21:58:10 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][300/312]	eta 0:00:05 lr 0.000796	time 0.4342 (0.4614)	model_time 0.4341 (0.4525)	loss 6.2087 (6.1041)	grad_norm 3.3555 (3.4973/1.0130)	mem 16099MB
[2025-01-17 21:58:15 internimage_t_1k_224] (main.py 510): INFO Train: [3/300][310/312]	eta 0:00:00 lr 0.000802	time 0.4397 (0.4608)	model_time 0.4396 (0.4521)	loss 6.1866 (6.1020)	grad_norm 6.3064 (3.4972/1.0352)	mem 16099MB
[2025-01-17 21:58:15 internimage_t_1k_224] (main.py 519): INFO EPOCH 3 training takes 0:02:23
[2025-01-17 21:58:15 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_3.pth saving......
[2025-01-17 21:58:16 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_3.pth saved !!!
[2025-01-17 21:58:24 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.614 (7.614)	Loss 4.4098 (4.4098)	Acc@1 14.941 (14.941)	Acc@5 36.646 (36.646)	Mem 16099MB
[2025-01-17 21:58:27 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.006)	Loss 4.7669 (4.5656)	Acc@1 12.354 (14.198)	Acc@5 28.833 (33.689)	Mem 16099MB
[2025-01-17 21:58:28 internimage_t_1k_224] (main.py 575): INFO [Epoch:3] * Acc@1 14.895 Acc@5 34.679
[2025-01-17 21:58:28 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 14.9%
[2025-01-17 21:58:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 21:58:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 21:58:29 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 14.90%
[2025-01-17 21:58:36 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.288 (7.288)	Loss 6.8494 (6.8494)	Acc@1 0.195 (0.195)	Acc@5 1.367 (1.367)	Mem 16099MB
[2025-01-17 21:58:40 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.988)	Loss 6.9417 (6.8834)	Acc@1 0.000 (0.215)	Acc@5 0.073 (0.959)	Mem 16099MB
[2025-01-17 21:58:40 internimage_t_1k_224] (main.py 575): INFO [Epoch:3] * Acc@1 0.198 Acc@5 0.996
[2025-01-17 21:58:40 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.2%
[2025-01-17 21:58:40 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 21:58:41 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 21:58:41 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.20%
[2025-01-17 21:58:44 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][0/312]	eta 0:15:28 lr 0.000803	time 2.9759 (2.9759)	model_time 0.4636 (0.4636)	loss 5.2360 (5.2360)	grad_norm 5.2968 (5.2968/0.0000)	mem 16099MB
[2025-01-17 21:58:49 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][10/312]	eta 0:03:26 lr 0.000810	time 0.4510 (0.6833)	model_time 0.4509 (0.4547)	loss 6.3976 (5.9681)	grad_norm 3.6790 (3.7268/0.9383)	mem 16099MB
[2025-01-17 21:58:53 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][20/312]	eta 0:02:50 lr 0.000816	time 0.4481 (0.5832)	model_time 0.4479 (0.4633)	loss 6.2372 (6.0470)	grad_norm 4.7038 (3.4624/0.9696)	mem 16099MB
[2025-01-17 21:58:58 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][30/312]	eta 0:02:32 lr 0.000822	time 0.4545 (0.5396)	model_time 0.4543 (0.4583)	loss 5.7657 (6.0365)	grad_norm 2.6987 (3.6461/1.1800)	mem 16099MB
[2025-01-17 21:59:03 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][40/312]	eta 0:02:21 lr 0.000829	time 0.4451 (0.5184)	model_time 0.4450 (0.4568)	loss 5.7793 (6.0630)	grad_norm 4.5481 (3.5645/1.1135)	mem 16099MB
[2025-01-17 21:59:07 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][50/312]	eta 0:02:12 lr 0.000835	time 0.4426 (0.5054)	model_time 0.4421 (0.4558)	loss 6.3204 (6.0525)	grad_norm 4.0038 (3.6642/1.1089)	mem 16099MB
[2025-01-17 21:59:12 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][60/312]	eta 0:02:05 lr 0.000842	time 0.4796 (0.4965)	model_time 0.4794 (0.4550)	loss 5.4624 (6.0294)	grad_norm 3.5428 (3.6080/1.0743)	mem 16099MB
[2025-01-17 21:59:16 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][70/312]	eta 0:01:58 lr 0.000848	time 0.4406 (0.4903)	model_time 0.4405 (0.4546)	loss 5.7166 (5.9965)	grad_norm 4.1289 (3.5390/1.0310)	mem 16099MB
[2025-01-17 21:59:21 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][80/312]	eta 0:01:52 lr 0.000854	time 0.4478 (0.4861)	model_time 0.4476 (0.4547)	loss 5.9568 (5.9836)	grad_norm 2.5250 (3.5154/1.0133)	mem 16099MB
[2025-01-17 21:59:25 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][90/312]	eta 0:01:47 lr 0.000861	time 0.4462 (0.4827)	model_time 0.4457 (0.4548)	loss 6.4175 (5.9802)	grad_norm 4.7524 (3.5045/0.9975)	mem 16099MB
[2025-01-17 21:59:30 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][100/312]	eta 0:01:41 lr 0.000867	time 0.4544 (0.4796)	model_time 0.4539 (0.4544)	loss 6.2950 (5.9786)	grad_norm 5.5893 (3.5021/1.0446)	mem 16099MB
[2025-01-17 21:59:34 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][110/312]	eta 0:01:36 lr 0.000874	time 0.4425 (0.4780)	model_time 0.4423 (0.4550)	loss 5.5355 (5.9856)	grad_norm 3.5372 (3.4879/1.0308)	mem 16099MB
[2025-01-17 21:59:39 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][120/312]	eta 0:01:31 lr 0.000880	time 0.5344 (0.4764)	model_time 0.5342 (0.4553)	loss 5.7226 (5.9867)	grad_norm 2.7996 (3.4754/1.0276)	mem 16099MB
[2025-01-17 21:59:43 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][130/312]	eta 0:01:26 lr 0.000886	time 0.4384 (0.4751)	model_time 0.4379 (0.4555)	loss 6.0895 (5.9902)	grad_norm 3.1452 (3.4851/1.0114)	mem 16099MB
[2025-01-17 21:59:48 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][140/312]	eta 0:01:21 lr 0.000893	time 0.4448 (0.4734)	model_time 0.4444 (0.4553)	loss 6.2601 (5.9904)	grad_norm 4.2923 (3.4813/1.0064)	mem 16099MB
[2025-01-17 21:59:53 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][150/312]	eta 0:01:16 lr 0.000899	time 0.4540 (0.4722)	model_time 0.4538 (0.4552)	loss 5.3964 (5.9845)	grad_norm 2.9781 (3.5277/1.1168)	mem 16099MB
[2025-01-17 21:59:57 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][160/312]	eta 0:01:11 lr 0.000906	time 0.4431 (0.4707)	model_time 0.4429 (0.4547)	loss 5.7587 (5.9858)	grad_norm 3.8558 (3.5709/1.1341)	mem 16099MB
[2025-01-17 22:00:02 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][170/312]	eta 0:01:06 lr 0.000912	time 0.4466 (0.4696)	model_time 0.4462 (0.4545)	loss 6.1861 (5.9818)	grad_norm 4.3427 (3.5817/1.1166)	mem 16099MB
[2025-01-17 22:00:06 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][180/312]	eta 0:01:01 lr 0.000918	time 0.4469 (0.4684)	model_time 0.4465 (0.4541)	loss 5.6480 (5.9717)	grad_norm 4.2260 (3.5732/1.1220)	mem 16099MB
[2025-01-17 22:00:11 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][190/312]	eta 0:00:57 lr 0.000925	time 0.4450 (0.4676)	model_time 0.4448 (0.4540)	loss 5.5414 (5.9649)	grad_norm 3.2611 (3.7265/1.4169)	mem 16099MB
[2025-01-17 22:00:15 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][200/312]	eta 0:00:52 lr 0.000931	time 0.4499 (0.4666)	model_time 0.4498 (0.4537)	loss 5.3395 (5.9621)	grad_norm 2.2198 (3.7003/1.3954)	mem 16099MB
[2025-01-17 22:00:20 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][210/312]	eta 0:00:47 lr 0.000938	time 0.4553 (0.4660)	model_time 0.4549 (0.4538)	loss 5.3400 (5.9617)	grad_norm 2.2678 (3.6727/1.3928)	mem 16099MB
[2025-01-17 22:00:24 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][220/312]	eta 0:00:42 lr 0.000944	time 0.4545 (0.4654)	model_time 0.4544 (0.4537)	loss 5.9837 (5.9615)	grad_norm 2.4191 (3.6626/1.3714)	mem 16099MB
[2025-01-17 22:00:29 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][230/312]	eta 0:00:38 lr 0.000950	time 0.4376 (0.4649)	model_time 0.4371 (0.4537)	loss 5.5914 (5.9507)	grad_norm 2.6888 (3.6527/1.3525)	mem 16099MB
[2025-01-17 22:00:33 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][240/312]	eta 0:00:33 lr 0.000957	time 0.4445 (0.4645)	model_time 0.4443 (0.4537)	loss 6.0518 (5.9342)	grad_norm 4.5383 (3.6558/1.3362)	mem 16099MB
[2025-01-17 22:00:38 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][250/312]	eta 0:00:28 lr 0.000963	time 0.4377 (0.4646)	model_time 0.4375 (0.4543)	loss 5.8075 (5.9229)	grad_norm 2.1080 (3.6239/1.3218)	mem 16099MB
[2025-01-17 22:00:42 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][260/312]	eta 0:00:24 lr 0.000970	time 0.4413 (0.4642)	model_time 0.4411 (0.4542)	loss 5.5926 (5.9254)	grad_norm 2.9527 (3.6114/1.3166)	mem 16099MB
[2025-01-17 22:00:47 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][270/312]	eta 0:00:19 lr 0.000976	time 0.4537 (0.4635)	model_time 0.4532 (0.4539)	loss 5.9477 (5.9259)	grad_norm 3.3277 (3.5886/1.3049)	mem 16099MB
[2025-01-17 22:00:51 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][280/312]	eta 0:00:14 lr 0.000983	time 0.4512 (0.4630)	model_time 0.4508 (0.4537)	loss 5.8740 (5.9217)	grad_norm 2.7680 (3.5746/1.2905)	mem 16099MB
[2025-01-17 22:00:56 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][290/312]	eta 0:00:10 lr 0.000989	time 0.4357 (0.4628)	model_time 0.4353 (0.4538)	loss 5.7337 (5.9164)	grad_norm 5.4274 (3.5711/1.2878)	mem 16099MB
[2025-01-17 22:01:01 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][300/312]	eta 0:00:05 lr 0.000995	time 0.4342 (0.4627)	model_time 0.4341 (0.4540)	loss 5.0189 (5.9067)	grad_norm 3.0094 (3.5868/1.3053)	mem 16099MB
[2025-01-17 22:01:05 internimage_t_1k_224] (main.py 510): INFO Train: [4/300][310/312]	eta 0:00:00 lr 0.001002	time 0.4330 (0.4618)	model_time 0.4329 (0.4534)	loss 5.9965 (5.9063)	grad_norm 3.5414 (3.5805/1.2960)	mem 16099MB
[2025-01-17 22:01:05 internimage_t_1k_224] (main.py 519): INFO EPOCH 4 training takes 0:02:24
[2025-01-17 22:01:05 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_4.pth saving......
[2025-01-17 22:01:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_4.pth saved !!!
[2025-01-17 22:01:14 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.326 (7.326)	Loss 3.8630 (3.8630)	Acc@1 22.949 (22.949)	Acc@5 47.388 (47.388)	Mem 16099MB
[2025-01-17 22:01:17 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.990)	Loss 4.2660 (4.0237)	Acc@1 18.286 (21.123)	Acc@5 39.600 (44.183)	Mem 16099MB
[2025-01-17 22:01:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:4] * Acc@1 21.925 Acc@5 45.146
[2025-01-17 22:01:18 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 21.9%
[2025-01-17 22:01:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:01:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:01:19 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 21.92%
[2025-01-17 22:01:26 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.406 (7.406)	Loss 6.8170 (6.8170)	Acc@1 0.317 (0.317)	Acc@5 1.880 (1.880)	Mem 16099MB
[2025-01-17 22:01:30 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.988)	Loss 6.9476 (6.8723)	Acc@1 0.000 (0.249)	Acc@5 0.024 (1.101)	Mem 16099MB
[2025-01-17 22:01:30 internimage_t_1k_224] (main.py 575): INFO [Epoch:4] * Acc@1 0.258 Acc@5 1.208
[2025-01-17 22:01:30 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.3%
[2025-01-17 22:01:30 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 22:01:31 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 22:01:31 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.26%
[2025-01-17 22:01:34 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][0/312]	eta 0:15:27 lr 0.001003	time 2.9727 (2.9727)	model_time 0.4718 (0.4718)	loss 4.9557 (4.9557)	grad_norm 2.6308 (2.6308/0.0000)	mem 16099MB
[2025-01-17 22:01:39 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][10/312]	eta 0:03:33 lr 0.001009	time 0.4409 (0.7055)	model_time 0.4407 (0.4778)	loss 5.8251 (5.5164)	grad_norm 4.8259 (3.2549/0.8356)	mem 16099MB
[2025-01-17 22:01:43 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][20/312]	eta 0:02:50 lr 0.001016	time 0.4585 (0.5846)	model_time 0.4584 (0.4652)	loss 5.2412 (5.6500)	grad_norm 3.0882 (3.5072/1.1044)	mem 16099MB
[2025-01-17 22:01:48 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][30/312]	eta 0:02:32 lr 0.001022	time 0.4632 (0.5420)	model_time 0.4631 (0.4610)	loss 5.9397 (5.7157)	grad_norm 2.7060 (3.2281/1.0130)	mem 16099MB
[2025-01-17 22:01:52 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][40/312]	eta 0:02:21 lr 0.001029	time 0.4509 (0.5198)	model_time 0.4505 (0.4585)	loss 6.2521 (5.7867)	grad_norm 4.6541 (3.2578/0.9531)	mem 16099MB
[2025-01-17 22:01:57 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][50/312]	eta 0:02:12 lr 0.001035	time 0.4479 (0.5063)	model_time 0.4477 (0.4569)	loss 5.5662 (5.7927)	grad_norm 2.7199 (3.4048/1.2346)	mem 16099MB
[2025-01-17 22:02:02 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][60/312]	eta 0:02:05 lr 0.001041	time 0.4435 (0.4987)	model_time 0.4431 (0.4574)	loss 5.4947 (5.7846)	grad_norm 2.7589 (3.3511/1.2422)	mem 16099MB
[2025-01-17 22:02:06 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][70/312]	eta 0:01:59 lr 0.001048	time 0.4744 (0.4922)	model_time 0.4739 (0.4567)	loss 6.1978 (5.7905)	grad_norm 4.1143 (3.3068/1.2004)	mem 16099MB
[2025-01-17 22:02:11 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][80/312]	eta 0:01:52 lr 0.001054	time 0.4477 (0.4869)	model_time 0.4473 (0.4557)	loss 5.8274 (5.7808)	grad_norm 3.8030 (3.3430/1.1469)	mem 16099MB
[2025-01-17 22:02:15 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][90/312]	eta 0:01:47 lr 0.001061	time 0.4431 (0.4826)	model_time 0.4429 (0.4548)	loss 5.2753 (5.7364)	grad_norm 2.6264 (3.3556/1.1206)	mem 16099MB
[2025-01-17 22:02:20 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][100/312]	eta 0:01:41 lr 0.001067	time 0.4400 (0.4805)	model_time 0.4398 (0.4554)	loss 5.4994 (5.7099)	grad_norm 2.4640 (3.3797/1.1856)	mem 16099MB
[2025-01-17 22:02:24 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][110/312]	eta 0:01:36 lr 0.001073	time 0.4366 (0.4781)	model_time 0.4364 (0.4552)	loss 6.0277 (5.7127)	grad_norm 2.9641 (3.4766/1.2883)	mem 16099MB
[2025-01-17 22:02:29 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][120/312]	eta 0:01:31 lr 0.001080	time 0.4371 (0.4763)	model_time 0.4367 (0.4553)	loss 6.1460 (5.7133)	grad_norm 3.7643 (3.4037/1.2697)	mem 16099MB
[2025-01-17 22:02:33 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][130/312]	eta 0:01:26 lr 0.001086	time 0.4396 (0.4741)	model_time 0.4395 (0.4547)	loss 5.3560 (5.7140)	grad_norm 2.1267 (3.3629/1.2368)	mem 16099MB
[2025-01-17 22:02:38 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][140/312]	eta 0:01:21 lr 0.001093	time 0.4384 (0.4733)	model_time 0.4383 (0.4553)	loss 6.0458 (5.7297)	grad_norm 3.2118 (3.4016/1.2384)	mem 16099MB
[2025-01-17 22:02:42 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][150/312]	eta 0:01:16 lr 0.001099	time 0.4448 (0.4723)	model_time 0.4446 (0.4554)	loss 5.4580 (5.7250)	grad_norm 6.6049 (3.4821/1.3438)	mem 16099MB
[2025-01-17 22:02:47 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][160/312]	eta 0:01:11 lr 0.001105	time 0.4358 (0.4714)	model_time 0.4353 (0.4555)	loss 5.0129 (5.7139)	grad_norm 2.7586 (3.4685/1.3156)	mem 16099MB
[2025-01-17 22:02:51 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][170/312]	eta 0:01:06 lr 0.001112	time 0.4550 (0.4700)	model_time 0.4548 (0.4550)	loss 6.1092 (5.7248)	grad_norm 2.9470 (3.4850/1.3644)	mem 16099MB
[2025-01-17 22:02:56 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][180/312]	eta 0:01:01 lr 0.001118	time 0.4469 (0.4687)	model_time 0.4467 (0.4545)	loss 5.2584 (5.7158)	grad_norm 3.3797 (3.4946/1.3374)	mem 16099MB
[2025-01-17 22:03:00 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][190/312]	eta 0:00:57 lr 0.001125	time 0.4460 (0.4675)	model_time 0.4458 (0.4540)	loss 5.3326 (5.7061)	grad_norm 2.0926 (3.4494/1.3235)	mem 16099MB
[2025-01-17 22:03:05 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][200/312]	eta 0:00:52 lr 0.001131	time 0.4388 (0.4671)	model_time 0.4383 (0.4544)	loss 6.2331 (5.7037)	grad_norm 2.9323 (3.4538/1.3016)	mem 16099MB
[2025-01-17 22:03:10 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][210/312]	eta 0:00:47 lr 0.001137	time 0.4441 (0.4666)	model_time 0.4437 (0.4544)	loss 5.6259 (5.7055)	grad_norm 2.9267 (3.4559/1.2762)	mem 16099MB
[2025-01-17 22:03:14 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][220/312]	eta 0:00:42 lr 0.001144	time 0.4455 (0.4659)	model_time 0.4454 (0.4542)	loss 5.9832 (5.7054)	grad_norm 2.9429 (3.4496/1.2602)	mem 16099MB
[2025-01-17 22:03:19 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][230/312]	eta 0:00:38 lr 0.001150	time 0.4430 (0.4656)	model_time 0.4428 (0.4544)	loss 5.6971 (5.6955)	grad_norm 3.2285 (3.4445/1.2601)	mem 16099MB
[2025-01-17 22:03:23 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][240/312]	eta 0:00:33 lr 0.001157	time 0.4488 (0.4648)	model_time 0.4483 (0.4541)	loss 5.3835 (5.7001)	grad_norm 2.4136 (3.4292/1.2420)	mem 16099MB
[2025-01-17 22:03:28 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][250/312]	eta 0:00:28 lr 0.001163	time 0.4612 (0.4648)	model_time 0.4610 (0.4545)	loss 5.0156 (5.6935)	grad_norm 3.8868 (3.4391/1.2457)	mem 16099MB
[2025-01-17 22:03:32 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][260/312]	eta 0:00:24 lr 0.001170	time 0.4463 (0.4642)	model_time 0.4458 (0.4543)	loss 5.8853 (5.6935)	grad_norm 4.7957 (3.4415/1.2426)	mem 16099MB
[2025-01-17 22:03:37 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][270/312]	eta 0:00:19 lr 0.001176	time 0.4434 (0.4638)	model_time 0.4432 (0.4543)	loss 6.1021 (5.6967)	grad_norm 2.6322 (3.4814/1.3332)	mem 16099MB
[2025-01-17 22:03:41 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][280/312]	eta 0:00:14 lr 0.001182	time 0.4425 (0.4632)	model_time 0.4423 (0.4540)	loss 4.9210 (5.6932)	grad_norm 3.1568 (3.4833/1.3418)	mem 16099MB
[2025-01-17 22:03:46 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][290/312]	eta 0:00:10 lr 0.001189	time 0.4490 (0.4628)	model_time 0.4488 (0.4539)	loss 4.8320 (5.6847)	grad_norm 3.5216 (3.4566/1.3350)	mem 16099MB
[2025-01-17 22:03:50 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][300/312]	eta 0:00:05 lr 0.001195	time 0.4321 (0.4623)	model_time 0.4320 (0.4537)	loss 5.6721 (5.6825)	grad_norm 4.0384 (3.4853/1.3526)	mem 16099MB
[2025-01-17 22:03:55 internimage_t_1k_224] (main.py 510): INFO Train: [5/300][310/312]	eta 0:00:00 lr 0.001202	time 0.4387 (0.4616)	model_time 0.4386 (0.4532)	loss 5.8732 (5.6737)	grad_norm 3.6174 (3.5065/1.3648)	mem 16099MB
[2025-01-17 22:03:55 internimage_t_1k_224] (main.py 519): INFO EPOCH 5 training takes 0:02:23
[2025-01-17 22:03:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_5.pth saving......
[2025-01-17 22:03:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_5.pth saved !!!
[2025-01-17 22:04:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.234 (7.234)	Loss 3.5593 (3.5593)	Acc@1 27.905 (27.905)	Acc@5 54.175 (54.175)	Mem 16099MB
[2025-01-17 22:04:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.989)	Loss 4.0042 (3.6978)	Acc@1 21.411 (26.030)	Acc@5 44.678 (51.181)	Mem 16099MB
[2025-01-17 22:04:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:5] * Acc@1 26.843 Acc@5 51.911
[2025-01-17 22:04:07 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 26.8%
[2025-01-17 22:04:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:04:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:04:09 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 26.84%
[2025-01-17 22:04:16 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.533 (7.533)	Loss 6.7796 (6.7796)	Acc@1 0.854 (0.854)	Acc@5 2.881 (2.881)	Mem 16099MB
[2025-01-17 22:04:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.016)	Loss 6.9550 (6.8623)	Acc@1 0.000 (0.311)	Acc@5 0.024 (1.225)	Mem 16099MB
[2025-01-17 22:04:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:5] * Acc@1 0.370 Acc@5 1.512
[2025-01-17 22:04:20 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 22:04:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 22:04:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 22:04:21 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.37%
[2025-01-17 22:04:24 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][0/312]	eta 0:12:09 lr 0.001203	time 2.3381 (2.3381)	model_time 0.4915 (0.4915)	loss 6.0179 (6.0179)	grad_norm 2.3733 (2.3733/0.0000)	mem 16099MB
[2025-01-17 22:04:28 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][10/312]	eta 0:03:09 lr 0.001209	time 0.4451 (0.6266)	model_time 0.4447 (0.4585)	loss 4.9961 (5.7960)	grad_norm 3.4857 (3.0137/0.7400)	mem 16099MB
[2025-01-17 22:04:33 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][20/312]	eta 0:02:38 lr 0.001216	time 0.4496 (0.5415)	model_time 0.4492 (0.4532)	loss 5.9510 (5.6724)	grad_norm 3.4391 (3.5231/1.3841)	mem 16099MB
[2025-01-17 22:04:37 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][30/312]	eta 0:02:24 lr 0.001222	time 0.4464 (0.5110)	model_time 0.4460 (0.4511)	loss 5.6422 (5.6182)	grad_norm 2.8037 (3.4360/1.2614)	mem 16099MB
[2025-01-17 22:04:42 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][40/312]	eta 0:02:14 lr 0.001228	time 0.4403 (0.4953)	model_time 0.4399 (0.4499)	loss 5.2852 (5.6214)	grad_norm 13.9809 (3.6554/1.9985)	mem 16099MB
[2025-01-17 22:04:46 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][50/312]	eta 0:02:07 lr 0.001235	time 0.4840 (0.4870)	model_time 0.4836 (0.4504)	loss 5.0596 (5.5534)	grad_norm 3.2759 (4.0505/2.5093)	mem 16099MB
[2025-01-17 22:04:51 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][60/312]	eta 0:02:01 lr 0.001241	time 0.4399 (0.4823)	model_time 0.4397 (0.4516)	loss 5.4359 (5.5328)	grad_norm 3.3070 (4.0029/2.3368)	mem 16099MB
[2025-01-17 22:04:55 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][70/312]	eta 0:01:55 lr 0.001248	time 0.4499 (0.4780)	model_time 0.4495 (0.4516)	loss 5.7169 (5.5362)	grad_norm 2.3672 (3.8013/2.2280)	mem 16099MB
[2025-01-17 22:05:00 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][80/312]	eta 0:01:50 lr 0.001254	time 0.4480 (0.4760)	model_time 0.4478 (0.4528)	loss 4.6431 (5.5080)	grad_norm 3.8491 (3.7455/2.1080)	mem 16099MB
[2025-01-17 22:05:04 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][90/312]	eta 0:01:44 lr 0.001260	time 0.4365 (0.4727)	model_time 0.4360 (0.4520)	loss 4.9310 (5.5061)	grad_norm 7.7186 (3.7221/2.0554)	mem 16099MB
[2025-01-17 22:05:09 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][100/312]	eta 0:01:39 lr 0.001267	time 0.4491 (0.4705)	model_time 0.4487 (0.4518)	loss 5.4983 (5.4881)	grad_norm 2.4797 (3.6441/1.9712)	mem 16099MB
[2025-01-17 22:05:13 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][110/312]	eta 0:01:34 lr 0.001273	time 0.4574 (0.4684)	model_time 0.4572 (0.4514)	loss 5.9764 (5.4772)	grad_norm 2.2634 (3.6372/1.9308)	mem 16099MB
[2025-01-17 22:05:18 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][120/312]	eta 0:01:29 lr 0.001280	time 0.4471 (0.4682)	model_time 0.4470 (0.4525)	loss 4.9758 (5.4788)	grad_norm 2.3813 (3.5933/1.8660)	mem 16099MB
[2025-01-17 22:05:23 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][130/312]	eta 0:01:25 lr 0.001286	time 0.4471 (0.4681)	model_time 0.4470 (0.4536)	loss 5.9438 (5.4801)	grad_norm 5.1720 (3.5807/1.8177)	mem 16099MB
[2025-01-17 22:05:27 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][140/312]	eta 0:01:20 lr 0.001292	time 0.4456 (0.4681)	model_time 0.4454 (0.4546)	loss 4.7092 (5.4956)	grad_norm 3.1511 (3.6173/1.8099)	mem 16099MB
[2025-01-17 22:05:32 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][150/312]	eta 0:01:15 lr 0.001299	time 0.4457 (0.4675)	model_time 0.4455 (0.4549)	loss 5.9333 (5.5012)	grad_norm 2.6076 (3.6109/1.7643)	mem 16099MB
[2025-01-17 22:05:36 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][160/312]	eta 0:01:10 lr 0.001305	time 0.4433 (0.4664)	model_time 0.4429 (0.4545)	loss 5.8374 (5.5150)	grad_norm 6.0089 (3.5829/1.7335)	mem 16099MB
[2025-01-17 22:05:41 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][170/312]	eta 0:01:06 lr 0.001312	time 0.4416 (0.4658)	model_time 0.4411 (0.4546)	loss 5.5134 (5.5174)	grad_norm 2.8860 (3.6170/1.8024)	mem 16099MB
[2025-01-17 22:05:45 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][180/312]	eta 0:01:01 lr 0.001318	time 0.4435 (0.4653)	model_time 0.4431 (0.4547)	loss 6.1043 (5.5148)	grad_norm 6.6857 (3.6385/1.7964)	mem 16099MB
[2025-01-17 22:05:50 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][190/312]	eta 0:00:56 lr 0.001324	time 0.4424 (0.4642)	model_time 0.4421 (0.4542)	loss 5.3686 (5.5002)	grad_norm 2.4541 (3.5950/1.7653)	mem 16099MB
[2025-01-17 22:05:54 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][200/312]	eta 0:00:51 lr 0.001331	time 0.4396 (0.4639)	model_time 0.4392 (0.4543)	loss 5.4208 (5.5134)	grad_norm 2.6514 (3.6361/1.7634)	mem 16099MB
[2025-01-17 22:05:59 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][210/312]	eta 0:00:47 lr 0.001337	time 0.4386 (0.4634)	model_time 0.4384 (0.4543)	loss 5.3088 (5.5058)	grad_norm 2.5703 (3.6223/1.7486)	mem 16099MB
[2025-01-17 22:06:04 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][220/312]	eta 0:00:42 lr 0.001344	time 0.4421 (0.4630)	model_time 0.4417 (0.4542)	loss 6.0936 (5.5162)	grad_norm 5.4132 (3.6323/1.7231)	mem 16099MB
[2025-01-17 22:06:08 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][230/312]	eta 0:00:37 lr 0.001350	time 0.4463 (0.4627)	model_time 0.4461 (0.4543)	loss 5.8395 (5.5121)	grad_norm 1.9149 (3.6219/1.7143)	mem 16099MB
[2025-01-17 22:06:13 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][240/312]	eta 0:00:33 lr 0.001356	time 0.4692 (0.4624)	model_time 0.4688 (0.4543)	loss 5.1645 (5.5083)	grad_norm 2.6392 (3.5838/1.6936)	mem 16099MB
[2025-01-17 22:06:17 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][250/312]	eta 0:00:28 lr 0.001363	time 0.4375 (0.4621)	model_time 0.4373 (0.4543)	loss 5.5677 (5.5089)	grad_norm 2.4875 (3.6001/1.6765)	mem 16099MB
[2025-01-17 22:06:22 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][260/312]	eta 0:00:24 lr 0.001369	time 0.4444 (0.4615)	model_time 0.4439 (0.4541)	loss 6.0251 (5.5166)	grad_norm 2.8610 (3.6044/1.6542)	mem 16099MB
[2025-01-17 22:06:26 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][270/312]	eta 0:00:19 lr 0.001376	time 0.4368 (0.4613)	model_time 0.4364 (0.4541)	loss 4.7079 (5.5164)	grad_norm 3.4104 (3.5842/1.6307)	mem 16099MB
[2025-01-17 22:06:31 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][280/312]	eta 0:00:14 lr 0.001382	time 0.4907 (0.4611)	model_time 0.4902 (0.4542)	loss 5.3149 (5.5152)	grad_norm 4.8376 (3.5679/1.6112)	mem 16099MB
[2025-01-17 22:06:36 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][290/312]	eta 0:00:10 lr 0.001389	time 0.4390 (0.4616)	model_time 0.4386 (0.4549)	loss 5.8575 (5.5159)	grad_norm 4.8497 (3.5657/1.5881)	mem 16099MB
[2025-01-17 22:06:40 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][300/312]	eta 0:00:05 lr 0.001395	time 0.4345 (0.4613)	model_time 0.4344 (0.4548)	loss 4.9069 (5.5165)	grad_norm 2.1428 (3.5840/1.6017)	mem 16099MB
[2025-01-17 22:06:44 internimage_t_1k_224] (main.py 510): INFO Train: [6/300][310/312]	eta 0:00:00 lr 0.001401	time 0.4332 (0.4605)	model_time 0.4332 (0.4542)	loss 5.1277 (5.5159)	grad_norm 3.9259 (3.6011/1.6151)	mem 16099MB
[2025-01-17 22:06:45 internimage_t_1k_224] (main.py 519): INFO EPOCH 6 training takes 0:02:23
[2025-01-17 22:06:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_6.pth saving......
[2025-01-17 22:06:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_6.pth saved !!!
[2025-01-17 22:06:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.945 (7.945)	Loss 3.0904 (3.0904)	Acc@1 35.303 (35.303)	Acc@5 61.792 (61.792)	Mem 16099MB
[2025-01-17 22:06:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.069)	Loss 3.7632 (3.3790)	Acc@1 25.195 (31.157)	Acc@5 49.438 (57.373)	Mem 16099MB
[2025-01-17 22:06:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:6] * Acc@1 31.944 Acc@5 58.299
[2025-01-17 22:06:58 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 31.9%
[2025-01-17 22:06:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:06:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:06:59 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 31.94%
[2025-01-17 22:07:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.467 (7.467)	Loss 6.7374 (6.7374)	Acc@1 0.952 (0.952)	Acc@5 4.028 (4.028)	Mem 16099MB
[2025-01-17 22:07:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.108 (1.016)	Loss 6.9592 (6.8525)	Acc@1 0.000 (0.282)	Acc@5 0.000 (1.314)	Mem 16099MB
[2025-01-17 22:07:10 internimage_t_1k_224] (main.py 575): INFO [Epoch:6] * Acc@1 0.422 Acc@5 1.743
[2025-01-17 22:07:10 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 22:07:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 22:07:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 22:07:12 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.42%
[2025-01-17 22:07:14 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][0/312]	eta 0:12:58 lr 0.001403	time 2.4958 (2.4958)	model_time 0.4751 (0.4751)	loss 5.8233 (5.8233)	grad_norm 2.4791 (2.4791/0.0000)	mem 16099MB
[2025-01-17 22:07:19 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][10/312]	eta 0:03:15 lr 0.001409	time 0.4493 (0.6476)	model_time 0.4491 (0.4637)	loss 5.0557 (5.6985)	grad_norm 3.0685 (3.6448/1.3356)	mem 16099MB
[2025-01-17 22:07:23 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][20/312]	eta 0:02:41 lr 0.001415	time 0.4433 (0.5542)	model_time 0.4431 (0.4577)	loss 4.6236 (5.4351)	grad_norm 10.5365 (4.2815/2.2041)	mem 16099MB
[2025-01-17 22:07:28 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][30/312]	eta 0:02:26 lr 0.001422	time 0.4529 (0.5206)	model_time 0.4527 (0.4551)	loss 5.7226 (5.4613)	grad_norm 2.4746 (4.0346/1.9742)	mem 16099MB
[2025-01-17 22:07:32 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][40/312]	eta 0:02:16 lr 0.001428	time 0.4449 (0.5029)	model_time 0.4447 (0.4533)	loss 4.9237 (5.3820)	grad_norm 4.0451 (3.8435/1.7868)	mem 16099MB
[2025-01-17 22:07:37 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][50/312]	eta 0:02:09 lr 0.001435	time 0.4462 (0.4937)	model_time 0.4457 (0.4537)	loss 5.6559 (5.3496)	grad_norm 3.2567 (3.6741/1.6992)	mem 16099MB
[2025-01-17 22:07:41 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][60/312]	eta 0:02:02 lr 0.001441	time 0.4438 (0.4859)	model_time 0.4437 (0.4525)	loss 5.0724 (5.3470)	grad_norm 2.6059 (3.7053/1.6697)	mem 16099MB
[2025-01-17 22:07:46 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][70/312]	eta 0:01:56 lr 0.001447	time 0.4401 (0.4817)	model_time 0.4396 (0.4529)	loss 4.8515 (5.3378)	grad_norm 3.5309 (3.5536/1.6050)	mem 16099MB
[2025-01-17 22:07:51 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][80/312]	eta 0:01:51 lr 0.001454	time 0.4366 (0.4789)	model_time 0.4364 (0.4536)	loss 5.9474 (5.3485)	grad_norm 3.1521 (3.4665/1.5480)	mem 16099MB
[2025-01-17 22:07:55 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][90/312]	eta 0:01:45 lr 0.001460	time 0.4506 (0.4765)	model_time 0.4501 (0.4540)	loss 5.7360 (5.3655)	grad_norm 2.7882 (3.5069/1.5361)	mem 16099MB
[2025-01-17 22:08:00 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][100/312]	eta 0:01:40 lr 0.001467	time 0.4669 (0.4744)	model_time 0.4668 (0.4541)	loss 4.7283 (5.3540)	grad_norm 3.6893 (3.5230/1.5517)	mem 16099MB
[2025-01-17 22:08:04 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][110/312]	eta 0:01:35 lr 0.001473	time 0.4402 (0.4736)	model_time 0.4397 (0.4551)	loss 4.5467 (5.3517)	grad_norm 2.1246 (3.4782/1.5013)	mem 16099MB
[2025-01-17 22:08:09 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][120/312]	eta 0:01:30 lr 0.001479	time 0.4386 (0.4720)	model_time 0.4384 (0.4549)	loss 4.5932 (5.3464)	grad_norm 2.7783 (3.4847/1.4772)	mem 16099MB
[2025-01-17 22:08:13 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][130/312]	eta 0:01:25 lr 0.001486	time 0.4419 (0.4699)	model_time 0.4415 (0.4542)	loss 5.2427 (5.3464)	grad_norm 3.6935 (3.5163/1.5532)	mem 16099MB
[2025-01-17 22:08:18 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][140/312]	eta 0:01:20 lr 0.001492	time 0.4774 (0.4685)	model_time 0.4773 (0.4538)	loss 5.5406 (5.3581)	grad_norm 3.9441 (3.4843/1.5162)	mem 16099MB
[2025-01-17 22:08:22 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][150/312]	eta 0:01:15 lr 0.001499	time 0.4435 (0.4671)	model_time 0.4430 (0.4534)	loss 5.5789 (5.3649)	grad_norm 2.4290 (3.4274/1.4882)	mem 16099MB
[2025-01-17 22:08:27 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][160/312]	eta 0:01:10 lr 0.001505	time 0.4501 (0.4660)	model_time 0.4497 (0.4531)	loss 5.3198 (5.3622)	grad_norm 2.1806 (3.3781/1.4589)	mem 16099MB
[2025-01-17 22:08:31 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][170/312]	eta 0:01:06 lr 0.001511	time 0.4532 (0.4655)	model_time 0.4528 (0.4533)	loss 4.7982 (5.3606)	grad_norm 3.0767 (3.3467/1.4460)	mem 16099MB
[2025-01-17 22:08:36 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][180/312]	eta 0:01:01 lr 0.001518	time 0.4600 (0.4645)	model_time 0.4595 (0.4529)	loss 5.3450 (5.3537)	grad_norm 2.3953 (3.3486/1.4133)	mem 16099MB
[2025-01-17 22:08:40 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][190/312]	eta 0:00:56 lr 0.001524	time 0.4727 (0.4637)	model_time 0.4723 (0.4528)	loss 4.4008 (5.3488)	grad_norm 1.9017 (3.4158/1.4904)	mem 16099MB
[2025-01-17 22:08:45 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][200/312]	eta 0:00:51 lr 0.001531	time 0.4848 (0.4635)	model_time 0.4844 (0.4531)	loss 5.8761 (5.3500)	grad_norm 2.6165 (3.3660/1.4769)	mem 16099MB
[2025-01-17 22:08:49 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][210/312]	eta 0:00:47 lr 0.001537	time 0.4361 (0.4627)	model_time 0.4359 (0.4528)	loss 5.1216 (5.3375)	grad_norm 2.3485 (3.3765/1.5274)	mem 16099MB
[2025-01-17 22:08:54 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][220/312]	eta 0:00:42 lr 0.001543	time 0.4390 (0.4625)	model_time 0.4385 (0.4530)	loss 5.6877 (5.3435)	grad_norm 2.8068 (3.3652/1.5041)	mem 16099MB
[2025-01-17 22:08:58 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][230/312]	eta 0:00:37 lr 0.001550	time 0.4383 (0.4618)	model_time 0.4382 (0.4527)	loss 5.6100 (5.3412)	grad_norm 4.4035 (3.4018/1.5460)	mem 16099MB
[2025-01-17 22:09:03 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][240/312]	eta 0:00:33 lr 0.001556	time 0.4368 (0.4617)	model_time 0.4366 (0.4529)	loss 5.1299 (5.3323)	grad_norm 3.9093 (3.4156/1.5311)	mem 16099MB
[2025-01-17 22:09:08 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][250/312]	eta 0:00:28 lr 0.001563	time 0.4366 (0.4613)	model_time 0.4361 (0.4529)	loss 5.4883 (5.3356)	grad_norm 2.8394 (3.4039/1.5153)	mem 16099MB
[2025-01-17 22:09:12 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][260/312]	eta 0:00:23 lr 0.001569	time 0.4452 (0.4608)	model_time 0.4448 (0.4527)	loss 5.7536 (5.3384)	grad_norm 2.4210 (3.4664/1.6203)	mem 16099MB
[2025-01-17 22:09:17 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][270/312]	eta 0:00:19 lr 0.001576	time 0.4406 (0.4606)	model_time 0.4404 (0.4528)	loss 5.6457 (5.3498)	grad_norm 2.5328 (3.4475/1.6011)	mem 16099MB
[2025-01-17 22:09:21 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][280/312]	eta 0:00:14 lr 0.001582	time 0.5279 (0.4608)	model_time 0.5277 (0.4533)	loss 5.6631 (5.3344)	grad_norm 4.2819 (3.4564/1.5827)	mem 16099MB
[2025-01-17 22:09:26 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][290/312]	eta 0:00:10 lr 0.001588	time 0.4492 (0.4606)	model_time 0.4488 (0.4533)	loss 5.4917 (5.3313)	grad_norm 3.0236 (3.4662/1.5752)	mem 16099MB
[2025-01-17 22:09:30 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][300/312]	eta 0:00:05 lr 0.001595	time 0.4380 (0.4605)	model_time 0.4379 (0.4534)	loss 5.5584 (5.3313)	grad_norm 3.6834 (3.4507/1.5589)	mem 16099MB
[2025-01-17 22:09:35 internimage_t_1k_224] (main.py 510): INFO Train: [7/300][310/312]	eta 0:00:00 lr 0.001601	time 0.4347 (0.4597)	model_time 0.4346 (0.4528)	loss 5.3923 (5.3303)	grad_norm 4.0925 (3.4371/1.5427)	mem 16099MB
[2025-01-17 22:09:35 internimage_t_1k_224] (main.py 519): INFO EPOCH 7 training takes 0:02:23
[2025-01-17 22:09:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_7.pth saving......
[2025-01-17 22:09:36 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_7.pth saved !!!
[2025-01-17 22:09:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.459 (7.459)	Loss 3.0721 (3.0721)	Acc@1 37.891 (37.891)	Acc@5 62.646 (62.646)	Mem 16099MB
[2025-01-17 22:09:47 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.999)	Loss 3.5047 (3.0711)	Acc@1 28.760 (36.441)	Acc@5 55.298 (63.124)	Mem 16099MB
[2025-01-17 22:09:47 internimage_t_1k_224] (main.py 575): INFO [Epoch:7] * Acc@1 37.314 Acc@5 63.818
[2025-01-17 22:09:47 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 37.3%
[2025-01-17 22:09:47 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:09:49 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:09:49 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 37.31%
[2025-01-17 22:09:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.415 (7.415)	Loss 6.6912 (6.6912)	Acc@1 1.025 (1.025)	Acc@5 5.127 (5.127)	Mem 16099MB
[2025-01-17 22:10:00 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.995)	Loss 6.9587 (6.8428)	Acc@1 0.000 (0.249)	Acc@5 0.024 (1.356)	Mem 16099MB
[2025-01-17 22:10:00 internimage_t_1k_224] (main.py 575): INFO [Epoch:7] * Acc@1 0.418 Acc@5 1.903
[2025-01-17 22:10:00 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 22:10:00 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.42%
[2025-01-17 22:10:03 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][0/312]	eta 0:14:55 lr 0.001602	time 2.8697 (2.8697)	model_time 1.1304 (1.1304)	loss 4.9526 (4.9526)	grad_norm 2.6706 (2.6706/0.0000)	mem 16099MB
[2025-01-17 22:10:07 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][10/312]	eta 0:03:30 lr 0.001609	time 0.4725 (0.6968)	model_time 0.4723 (0.5384)	loss 4.7315 (5.1311)	grad_norm 2.7321 (3.0623/0.6610)	mem 16099MB
[2025-01-17 22:10:12 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][20/312]	eta 0:02:50 lr 0.001615	time 0.5068 (0.5833)	model_time 0.5064 (0.5001)	loss 5.9137 (5.2378)	grad_norm 1.7689 (2.8584/0.6707)	mem 16099MB
[2025-01-17 22:10:17 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][30/312]	eta 0:02:33 lr 0.001622	time 0.4487 (0.5460)	model_time 0.4483 (0.4896)	loss 5.5573 (5.3025)	grad_norm 3.0196 (2.9060/0.7967)	mem 16099MB
[2025-01-17 22:10:21 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][40/312]	eta 0:02:22 lr 0.001628	time 0.4491 (0.5255)	model_time 0.4489 (0.4828)	loss 5.4384 (5.3056)	grad_norm 2.8983 (3.2329/1.2168)	mem 16099MB
[2025-01-17 22:10:26 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][50/312]	eta 0:02:14 lr 0.001634	time 0.4785 (0.5125)	model_time 0.4783 (0.4781)	loss 5.8132 (5.2907)	grad_norm 4.1744 (3.3894/1.3824)	mem 16099MB
[2025-01-17 22:10:30 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][60/312]	eta 0:02:07 lr 0.001641	time 0.6110 (0.5050)	model_time 0.6109 (0.4762)	loss 5.7236 (5.3356)	grad_norm 3.0608 (3.5791/1.6814)	mem 16099MB
[2025-01-17 22:10:35 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][70/312]	eta 0:02:00 lr 0.001647	time 0.4530 (0.4975)	model_time 0.4526 (0.4727)	loss 5.3032 (5.3565)	grad_norm 3.8608 (3.4766/1.6070)	mem 16099MB
[2025-01-17 22:10:40 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][80/312]	eta 0:01:54 lr 0.001654	time 0.4405 (0.4931)	model_time 0.4401 (0.4713)	loss 4.3384 (5.3508)	grad_norm 2.5299 (3.3934/1.5308)	mem 16099MB
[2025-01-17 22:10:44 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][90/312]	eta 0:01:48 lr 0.001660	time 0.4557 (0.4885)	model_time 0.4555 (0.4690)	loss 5.6095 (5.3432)	grad_norm 2.9085 (3.3806/1.4610)	mem 16099MB
[2025-01-17 22:10:49 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][100/312]	eta 0:01:42 lr 0.001666	time 0.4621 (0.4847)	model_time 0.4620 (0.4671)	loss 5.1428 (5.3182)	grad_norm 4.9890 (3.3516/1.4161)	mem 16099MB
[2025-01-17 22:10:53 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][110/312]	eta 0:01:37 lr 0.001673	time 0.4498 (0.4828)	model_time 0.4494 (0.4668)	loss 5.5112 (5.3151)	grad_norm 3.1967 (3.3594/1.4034)	mem 16099MB
[2025-01-17 22:10:58 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][120/312]	eta 0:01:32 lr 0.001679	time 0.4366 (0.4808)	model_time 0.4361 (0.4660)	loss 5.5716 (5.3016)	grad_norm 7.2274 (3.4105/1.4020)	mem 16099MB
[2025-01-17 22:11:02 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][130/312]	eta 0:01:27 lr 0.001686	time 0.4424 (0.4786)	model_time 0.4422 (0.4649)	loss 5.9474 (5.3022)	grad_norm 7.8825 (3.4187/1.4300)	mem 16099MB
[2025-01-17 22:11:07 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][140/312]	eta 0:01:22 lr 0.001692	time 0.4789 (0.4768)	model_time 0.4784 (0.4641)	loss 4.5015 (5.2961)	grad_norm 5.4409 (3.3921/1.4204)	mem 16099MB
[2025-01-17 22:11:11 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][150/312]	eta 0:01:16 lr 0.001698	time 0.4540 (0.4748)	model_time 0.4538 (0.4629)	loss 5.8220 (5.3091)	grad_norm 2.3944 (3.3821/1.4218)	mem 16099MB
[2025-01-17 22:11:16 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][160/312]	eta 0:01:12 lr 0.001705	time 0.5581 (0.4742)	model_time 0.5579 (0.4630)	loss 5.4541 (5.2940)	grad_norm 2.5919 (3.3583/1.3935)	mem 16099MB
[2025-01-17 22:11:21 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][170/312]	eta 0:01:07 lr 0.001711	time 0.4492 (0.4729)	model_time 0.4491 (0.4623)	loss 4.8640 (5.2875)	grad_norm 4.0722 (3.3694/1.4244)	mem 16099MB
[2025-01-17 22:11:25 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][180/312]	eta 0:01:02 lr 0.001718	time 0.4510 (0.4715)	model_time 0.4506 (0.4616)	loss 5.6419 (5.2894)	grad_norm 2.9244 (3.4150/1.4088)	mem 16099MB
[2025-01-17 22:11:30 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][190/312]	eta 0:00:57 lr 0.001724	time 0.4542 (0.4712)	model_time 0.4540 (0.4617)	loss 6.0162 (5.2928)	grad_norm 4.2669 (3.3886/1.3835)	mem 16099MB
[2025-01-17 22:11:34 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][200/312]	eta 0:00:52 lr 0.001730	time 0.4366 (0.4699)	model_time 0.4361 (0.4609)	loss 5.8620 (5.2937)	grad_norm 2.6775 (3.3497/1.3719)	mem 16099MB
[2025-01-17 22:11:39 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][210/312]	eta 0:00:47 lr 0.001737	time 0.4568 (0.4691)	model_time 0.4567 (0.4605)	loss 5.8293 (5.3069)	grad_norm 3.4018 (3.3472/1.3565)	mem 16099MB
[2025-01-17 22:11:43 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][220/312]	eta 0:00:43 lr 0.001743	time 0.4666 (0.4681)	model_time 0.4664 (0.4598)	loss 4.1337 (5.3007)	grad_norm 4.1446 (3.3524/1.3400)	mem 16099MB
[2025-01-17 22:11:48 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][230/312]	eta 0:00:38 lr 0.001750	time 0.4405 (0.4675)	model_time 0.4401 (0.4596)	loss 5.7155 (5.3027)	grad_norm 1.6672 (3.3675/1.3726)	mem 16099MB
[2025-01-17 22:11:52 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][240/312]	eta 0:00:33 lr 0.001756	time 0.4402 (0.4668)	model_time 0.4398 (0.4592)	loss 5.4113 (5.2922)	grad_norm 2.7009 (3.3594/1.3558)	mem 16099MB
[2025-01-17 22:11:57 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][250/312]	eta 0:00:28 lr 0.001762	time 0.4487 (0.4664)	model_time 0.4486 (0.4591)	loss 3.9718 (5.2798)	grad_norm 3.3567 (3.3367/1.3391)	mem 16099MB
[2025-01-17 22:12:01 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][260/312]	eta 0:00:24 lr 0.001769	time 0.4483 (0.4658)	model_time 0.4479 (0.4588)	loss 5.3410 (5.2691)	grad_norm 3.7614 (3.3553/1.3486)	mem 16099MB
[2025-01-17 22:12:06 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][270/312]	eta 0:00:19 lr 0.001775	time 0.4787 (0.4658)	model_time 0.4782 (0.4590)	loss 5.5014 (5.2681)	grad_norm 3.1647 (3.3394/1.3326)	mem 16099MB
[2025-01-17 22:12:10 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][280/312]	eta 0:00:14 lr 0.001782	time 0.4437 (0.4653)	model_time 0.4435 (0.4587)	loss 5.9466 (5.2702)	grad_norm 3.6483 (3.3414/1.3275)	mem 16099MB
[2025-01-17 22:12:15 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][290/312]	eta 0:00:10 lr 0.001788	time 0.4515 (0.4646)	model_time 0.4511 (0.4583)	loss 4.1861 (5.2546)	grad_norm 2.5799 (3.3345/1.3200)	mem 16099MB
[2025-01-17 22:12:19 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][300/312]	eta 0:00:05 lr 0.001795	time 0.5074 (0.4644)	model_time 0.5073 (0.4583)	loss 5.2248 (5.2463)	grad_norm 4.4039 (3.3615/1.3276)	mem 16099MB
[2025-01-17 22:12:24 internimage_t_1k_224] (main.py 510): INFO Train: [8/300][310/312]	eta 0:00:00 lr 0.001801	time 0.4362 (0.4635)	model_time 0.4361 (0.4575)	loss 5.3349 (5.2430)	grad_norm 7.4145 (3.3521/1.3571)	mem 16099MB
[2025-01-17 22:12:24 internimage_t_1k_224] (main.py 519): INFO EPOCH 8 training takes 0:02:24
[2025-01-17 22:12:24 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_8.pth saving......
[2025-01-17 22:12:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_8.pth saved !!!
[2025-01-17 22:12:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.698 (7.698)	Loss 2.5863 (2.5863)	Acc@1 46.338 (46.338)	Acc@5 72.095 (72.095)	Mem 16099MB
[2025-01-17 22:12:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.035)	Loss 3.1399 (2.8317)	Acc@1 35.376 (40.936)	Acc@5 62.280 (67.960)	Mem 16099MB
[2025-01-17 22:12:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:8] * Acc@1 41.537 Acc@5 68.520
[2025-01-17 22:12:37 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 41.5%
[2025-01-17 22:12:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:12:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:12:38 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 41.54%
[2025-01-17 22:12:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.580 (7.580)	Loss 6.6438 (6.6438)	Acc@1 0.879 (0.879)	Acc@5 5.493 (5.493)	Mem 16099MB
[2025-01-17 22:12:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.028)	Loss 6.9530 (6.8324)	Acc@1 0.000 (0.231)	Acc@5 0.049 (1.307)	Mem 16099MB
[2025-01-17 22:12:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:8] * Acc@1 0.422 Acc@5 1.973
[2025-01-17 22:12:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 22:12:50 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.42%
[2025-01-17 22:12:53 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][0/312]	eta 0:15:58 lr 0.001802	time 3.0737 (3.0737)	model_time 0.8578 (0.8578)	loss 5.2389 (5.2389)	grad_norm 3.1946 (3.1946/0.0000)	mem 16099MB
[2025-01-17 22:12:57 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][10/312]	eta 0:03:33 lr 0.001809	time 0.4465 (0.7063)	model_time 0.4461 (0.5045)	loss 4.7272 (5.1257)	grad_norm 2.5158 (2.6741/0.7683)	mem 16099MB
[2025-01-17 22:13:02 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][20/312]	eta 0:02:53 lr 0.001815	time 0.4662 (0.5929)	model_time 0.4661 (0.4870)	loss 5.3270 (5.1220)	grad_norm 4.2192 (2.9171/1.2229)	mem 16099MB
[2025-01-17 22:13:07 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][30/312]	eta 0:02:34 lr 0.001821	time 0.4433 (0.5467)	model_time 0.4431 (0.4749)	loss 5.2819 (5.0801)	grad_norm 2.6799 (3.0232/1.1018)	mem 16099MB
[2025-01-17 22:13:11 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][40/312]	eta 0:02:22 lr 0.001828	time 0.4528 (0.5232)	model_time 0.4524 (0.4689)	loss 5.4907 (5.0285)	grad_norm 2.7506 (3.0202/1.0710)	mem 16099MB
[2025-01-17 22:13:16 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][50/312]	eta 0:02:13 lr 0.001834	time 0.4389 (0.5099)	model_time 0.4385 (0.4662)	loss 4.0994 (4.9603)	grad_norm 1.8698 (3.1222/1.1992)	mem 16099MB
[2025-01-17 22:13:20 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][60/312]	eta 0:02:06 lr 0.001841	time 0.4522 (0.5008)	model_time 0.4517 (0.4641)	loss 5.5553 (4.9324)	grad_norm 2.6589 (3.0548/1.1326)	mem 16099MB
[2025-01-17 22:13:25 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][70/312]	eta 0:01:59 lr 0.001847	time 0.4664 (0.4944)	model_time 0.4662 (0.4628)	loss 4.6689 (4.9491)	grad_norm 2.7660 (3.1637/1.2840)	mem 16099MB
[2025-01-17 22:13:29 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][80/312]	eta 0:01:53 lr 0.001853	time 0.4463 (0.4893)	model_time 0.4462 (0.4616)	loss 5.0077 (4.9282)	grad_norm 2.9375 (3.1206/1.2328)	mem 16099MB
[2025-01-17 22:13:34 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][90/312]	eta 0:01:48 lr 0.001860	time 0.4480 (0.4867)	model_time 0.4476 (0.4620)	loss 5.6054 (4.9718)	grad_norm 1.9973 (3.1359/1.2291)	mem 16099MB
[2025-01-17 22:13:38 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][100/312]	eta 0:01:42 lr 0.001866	time 0.4455 (0.4829)	model_time 0.4454 (0.4606)	loss 4.0971 (4.9646)	grad_norm 2.9236 (3.2593/1.4793)	mem 16099MB
[2025-01-17 22:13:43 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][110/312]	eta 0:01:36 lr 0.001873	time 0.4469 (0.4798)	model_time 0.4467 (0.4595)	loss 4.5367 (4.9840)	grad_norm 5.3830 (3.3082/1.4916)	mem 16099MB
[2025-01-17 22:13:47 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][120/312]	eta 0:01:31 lr 0.001879	time 0.4387 (0.4778)	model_time 0.4385 (0.4592)	loss 5.9163 (5.0020)	grad_norm 4.2167 (3.3739/1.4976)	mem 16099MB
[2025-01-17 22:13:52 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][130/312]	eta 0:01:26 lr 0.001885	time 0.4457 (0.4760)	model_time 0.4455 (0.4587)	loss 5.4961 (5.0256)	grad_norm 2.8979 (3.3302/1.4700)	mem 16099MB
[2025-01-17 22:13:57 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][140/312]	eta 0:01:21 lr 0.001892	time 0.4408 (0.4746)	model_time 0.4406 (0.4585)	loss 4.4401 (5.0125)	grad_norm 2.0016 (3.3445/1.4393)	mem 16099MB
[2025-01-17 22:14:01 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][150/312]	eta 0:01:16 lr 0.001898	time 0.4402 (0.4744)	model_time 0.4397 (0.4593)	loss 4.6278 (5.0126)	grad_norm 3.3986 (3.3780/1.4730)	mem 16099MB
[2025-01-17 22:14:06 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][160/312]	eta 0:01:11 lr 0.001905	time 0.4396 (0.4731)	model_time 0.4392 (0.4590)	loss 5.4685 (5.0117)	grad_norm 2.2116 (3.3458/1.4509)	mem 16099MB
[2025-01-17 22:14:10 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][170/312]	eta 0:01:06 lr 0.001911	time 0.4466 (0.4718)	model_time 0.4464 (0.4585)	loss 4.7333 (5.0227)	grad_norm 1.6704 (3.3123/1.4339)	mem 16099MB
[2025-01-17 22:14:15 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][180/312]	eta 0:01:02 lr 0.001917	time 0.4459 (0.4709)	model_time 0.4454 (0.4583)	loss 5.2030 (5.0157)	grad_norm 2.8873 (3.3402/1.4451)	mem 16099MB
[2025-01-17 22:14:19 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][190/312]	eta 0:00:57 lr 0.001924	time 0.4388 (0.4698)	model_time 0.4384 (0.4579)	loss 3.8616 (5.0158)	grad_norm 3.0169 (3.4184/1.5168)	mem 16099MB
[2025-01-17 22:14:24 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][200/312]	eta 0:00:52 lr 0.001930	time 0.4480 (0.4691)	model_time 0.4476 (0.4577)	loss 5.0005 (5.0152)	grad_norm 2.2500 (3.3630/1.5018)	mem 16099MB
[2025-01-17 22:14:28 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][210/312]	eta 0:00:47 lr 0.001937	time 0.4412 (0.4679)	model_time 0.4408 (0.4570)	loss 5.1530 (5.0229)	grad_norm 3.4039 (3.3527/1.4720)	mem 16099MB
[2025-01-17 22:14:33 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][220/312]	eta 0:00:42 lr 0.001943	time 0.4400 (0.4671)	model_time 0.4396 (0.4567)	loss 5.1417 (5.0176)	grad_norm 2.4948 (3.3712/1.4930)	mem 16099MB
[2025-01-17 22:14:37 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][230/312]	eta 0:00:38 lr 0.001949	time 0.4638 (0.4663)	model_time 0.4634 (0.4564)	loss 5.0765 (5.0250)	grad_norm 3.5447 (3.3734/1.4689)	mem 16099MB
[2025-01-17 22:14:42 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][240/312]	eta 0:00:33 lr 0.001956	time 0.4477 (0.4655)	model_time 0.4475 (0.4559)	loss 5.7626 (5.0203)	grad_norm 4.7828 (3.3450/1.4587)	mem 16099MB
[2025-01-17 22:14:46 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][250/312]	eta 0:00:28 lr 0.001962	time 0.4920 (0.4649)	model_time 0.4916 (0.4557)	loss 4.2453 (5.0211)	grad_norm 3.1842 (3.3266/1.4456)	mem 16099MB
[2025-01-17 22:14:51 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][260/312]	eta 0:00:24 lr 0.001969	time 0.4432 (0.4645)	model_time 0.4428 (0.4556)	loss 5.3515 (5.0106)	grad_norm 5.0602 (3.3257/1.4286)	mem 16099MB
[2025-01-17 22:14:55 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][270/312]	eta 0:00:19 lr 0.001975	time 0.4533 (0.4643)	model_time 0.4529 (0.4558)	loss 5.1299 (5.0077)	grad_norm 2.1978 (3.3108/1.4230)	mem 16099MB
[2025-01-17 22:15:00 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][280/312]	eta 0:00:14 lr 0.001982	time 0.4757 (0.4639)	model_time 0.4752 (0.4556)	loss 4.4850 (4.9997)	grad_norm 3.9919 (3.3092/1.4205)	mem 16099MB
[2025-01-17 22:15:05 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][290/312]	eta 0:00:10 lr 0.001988	time 0.4366 (0.4638)	model_time 0.4362 (0.4558)	loss 4.2945 (5.0047)	grad_norm 3.5358 (3.3182/1.4077)	mem 16099MB
[2025-01-17 22:15:09 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][300/312]	eta 0:00:05 lr 0.001994	time 0.4288 (0.4630)	model_time 0.4287 (0.4553)	loss 4.7799 (5.0016)	grad_norm 5.5802 (3.2957/1.4052)	mem 16099MB
[2025-01-17 22:15:13 internimage_t_1k_224] (main.py 510): INFO Train: [9/300][310/312]	eta 0:00:00 lr 0.002001	time 0.4350 (0.4627)	model_time 0.4350 (0.4552)	loss 4.7740 (5.0046)	grad_norm 2.3855 (3.2995/1.4000)	mem 16099MB
[2025-01-17 22:15:14 internimage_t_1k_224] (main.py 519): INFO EPOCH 9 training takes 0:02:24
[2025-01-17 22:15:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_9.pth saving......
[2025-01-17 22:15:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_9.pth saved !!!
[2025-01-17 22:15:23 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.312 (7.312)	Loss 2.4112 (2.4112)	Acc@1 49.341 (49.341)	Acc@5 74.585 (74.585)	Mem 16099MB
[2025-01-17 22:15:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.984)	Loss 2.9806 (2.6123)	Acc@1 38.794 (45.179)	Acc@5 64.038 (71.618)	Mem 16099MB
[2025-01-17 22:15:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:9] * Acc@1 45.635 Acc@5 72.011
[2025-01-17 22:15:26 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 45.6%
[2025-01-17 22:15:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:15:27 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:15:27 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 45.64%
[2025-01-17 22:15:35 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.408 (7.408)	Loss 6.5989 (6.5989)	Acc@1 0.830 (0.830)	Acc@5 5.322 (5.322)	Mem 16099MB
[2025-01-17 22:15:39 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.056)	Loss 6.9423 (6.8220)	Acc@1 0.000 (0.200)	Acc@5 0.073 (1.265)	Mem 16099MB
[2025-01-17 22:15:39 internimage_t_1k_224] (main.py 575): INFO [Epoch:9] * Acc@1 0.404 Acc@5 2.049
[2025-01-17 22:15:39 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 22:15:39 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.42%
[2025-01-17 22:15:42 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][0/312]	eta 0:15:08 lr 0.002002	time 2.9130 (2.9130)	model_time 0.9621 (0.9621)	loss 5.1500 (5.1500)	grad_norm 2.3796 (2.3796/0.0000)	mem 16099MB
[2025-01-17 22:15:47 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][10/312]	eta 0:03:31 lr 0.002008	time 0.4475 (0.6987)	model_time 0.4471 (0.5209)	loss 5.3179 (5.0055)	grad_norm 3.1128 (2.1352/0.4167)	mem 16099MB
[2025-01-17 22:15:51 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][20/312]	eta 0:02:51 lr 0.002015	time 0.4481 (0.5865)	model_time 0.4479 (0.4932)	loss 4.4405 (4.8351)	grad_norm 3.2726 (2.4082/0.6827)	mem 16099MB
[2025-01-17 22:15:56 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][30/312]	eta 0:02:33 lr 0.002021	time 0.4511 (0.5452)	model_time 0.4507 (0.4819)	loss 3.8755 (4.8726)	grad_norm 3.3640 (2.9242/1.5342)	mem 16099MB
[2025-01-17 22:16:01 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][40/312]	eta 0:02:21 lr 0.002028	time 0.4539 (0.5219)	model_time 0.4537 (0.4739)	loss 4.3348 (4.8913)	grad_norm 1.5055 (3.2103/1.7333)	mem 16099MB
[2025-01-17 22:16:05 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][50/312]	eta 0:02:14 lr 0.002034	time 0.4534 (0.5127)	model_time 0.4532 (0.4741)	loss 5.4015 (4.9047)	grad_norm 5.9938 (3.3092/1.7399)	mem 16099MB
[2025-01-17 22:16:10 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][60/312]	eta 0:02:06 lr 0.002040	time 0.4447 (0.5021)	model_time 0.4443 (0.4697)	loss 5.3619 (4.9228)	grad_norm 2.6507 (3.2808/1.6524)	mem 16099MB
[2025-01-17 22:16:14 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][70/312]	eta 0:01:59 lr 0.002047	time 0.4577 (0.4947)	model_time 0.4576 (0.4669)	loss 5.2696 (4.8939)	grad_norm 4.4802 (3.2399/1.5676)	mem 16099MB
[2025-01-17 22:16:19 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][80/312]	eta 0:01:53 lr 0.002053	time 0.4418 (0.4911)	model_time 0.4405 (0.4666)	loss 5.7245 (4.9080)	grad_norm 2.5314 (3.2012/1.4775)	mem 16099MB
[2025-01-17 22:16:23 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][90/312]	eta 0:01:47 lr 0.002060	time 0.4448 (0.4863)	model_time 0.4444 (0.4644)	loss 5.5733 (4.9169)	grad_norm 2.8617 (3.1986/1.4634)	mem 16099MB
[2025-01-17 22:16:28 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][100/312]	eta 0:01:42 lr 0.002066	time 0.4507 (0.4829)	model_time 0.4505 (0.4631)	loss 5.8304 (4.9308)	grad_norm 7.4935 (3.3041/1.5347)	mem 16099MB
[2025-01-17 22:16:32 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][110/312]	eta 0:01:36 lr 0.002072	time 0.4480 (0.4799)	model_time 0.4479 (0.4619)	loss 5.5607 (4.9464)	grad_norm 2.3641 (3.3108/1.5077)	mem 16099MB
[2025-01-17 22:16:37 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][120/312]	eta 0:01:31 lr 0.002079	time 0.4440 (0.4774)	model_time 0.4436 (0.4609)	loss 5.8893 (4.9871)	grad_norm 2.3260 (3.3306/1.5268)	mem 16099MB
[2025-01-17 22:16:41 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][130/312]	eta 0:01:26 lr 0.002085	time 0.4475 (0.4759)	model_time 0.4470 (0.4606)	loss 5.6624 (4.9873)	grad_norm 3.9213 (3.2880/1.4949)	mem 16099MB
[2025-01-17 22:16:46 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][140/312]	eta 0:01:21 lr 0.002092	time 0.4364 (0.4740)	model_time 0.4360 (0.4598)	loss 4.3270 (4.9833)	grad_norm 3.1101 (3.2444/1.4609)	mem 16099MB
[2025-01-17 22:16:50 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][150/312]	eta 0:01:16 lr 0.002098	time 0.4444 (0.4724)	model_time 0.4442 (0.4591)	loss 4.3209 (4.9679)	grad_norm 1.7994 (3.1948/1.4326)	mem 16099MB
[2025-01-17 22:16:55 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][160/312]	eta 0:01:11 lr 0.002104	time 0.4624 (0.4713)	model_time 0.4622 (0.4588)	loss 5.2170 (4.9598)	grad_norm 2.3891 (3.1706/1.4323)	mem 16099MB
[2025-01-17 22:17:00 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][170/312]	eta 0:01:06 lr 0.002111	time 0.4438 (0.4705)	model_time 0.4434 (0.4587)	loss 5.2387 (4.9585)	grad_norm 3.0239 (3.1512/1.3958)	mem 16099MB
[2025-01-17 22:17:04 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][180/312]	eta 0:01:02 lr 0.002117	time 0.4457 (0.4711)	model_time 0.4453 (0.4599)	loss 3.6979 (4.9560)	grad_norm 1.9685 (3.1470/1.3855)	mem 16099MB
[2025-01-17 22:17:09 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][190/312]	eta 0:00:57 lr 0.002124	time 0.4377 (0.4697)	model_time 0.4376 (0.4591)	loss 5.8197 (4.9686)	grad_norm 2.6518 (3.1442/1.3675)	mem 16099MB
[2025-01-17 22:17:13 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][200/312]	eta 0:00:52 lr 0.002130	time 0.5038 (0.4693)	model_time 0.5034 (0.4591)	loss 5.0432 (4.9732)	grad_norm 2.7963 (3.1530/1.3850)	mem 16099MB
[2025-01-17 22:17:18 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][210/312]	eta 0:00:47 lr 0.002136	time 0.4453 (0.4685)	model_time 0.4451 (0.4588)	loss 4.4052 (4.9527)	grad_norm 3.4275 (3.1649/1.4049)	mem 16099MB
[2025-01-17 22:17:22 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][220/312]	eta 0:00:43 lr 0.002143	time 0.4435 (0.4677)	model_time 0.4431 (0.4585)	loss 5.5538 (4.9341)	grad_norm 3.3631 (3.2270/1.5199)	mem 16099MB
[2025-01-17 22:17:27 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][230/312]	eta 0:00:38 lr 0.002149	time 0.4479 (0.4669)	model_time 0.4475 (0.4580)	loss 5.1799 (4.9318)	grad_norm 2.5164 (3.2739/1.5569)	mem 16099MB
[2025-01-17 22:17:31 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][240/312]	eta 0:00:33 lr 0.002156	time 0.4478 (0.4661)	model_time 0.4474 (0.4576)	loss 5.1779 (4.9325)	grad_norm 3.1460 (3.2482/1.5389)	mem 16099MB
[2025-01-17 22:17:36 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][250/312]	eta 0:00:28 lr 0.002162	time 0.4356 (0.4654)	model_time 0.4354 (0.4572)	loss 5.0030 (4.9327)	grad_norm 2.4083 (3.2401/1.5272)	mem 16099MB
[2025-01-17 22:17:40 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][260/312]	eta 0:00:24 lr 0.002169	time 0.4459 (0.4647)	model_time 0.4455 (0.4568)	loss 5.0965 (4.9373)	grad_norm 2.4785 (3.2171/1.5157)	mem 16099MB
[2025-01-17 22:17:45 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][270/312]	eta 0:00:19 lr 0.002175	time 0.4380 (0.4643)	model_time 0.4378 (0.4566)	loss 5.3547 (4.9415)	grad_norm 3.4362 (3.2102/1.4918)	mem 16099MB
[2025-01-17 22:17:49 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][280/312]	eta 0:00:14 lr 0.002181	time 0.4443 (0.4638)	model_time 0.4439 (0.4565)	loss 4.0433 (4.9295)	grad_norm 3.1042 (3.1954/1.4727)	mem 16099MB
[2025-01-17 22:17:54 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][290/312]	eta 0:00:10 lr 0.002188	time 0.4393 (0.4643)	model_time 0.4392 (0.4571)	loss 5.3349 (4.9345)	grad_norm 2.6173 (3.2281/1.4894)	mem 16099MB
[2025-01-17 22:17:59 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][300/312]	eta 0:00:05 lr 0.002194	time 0.4372 (0.4638)	model_time 0.4372 (0.4569)	loss 3.9630 (4.9310)	grad_norm 1.4780 (3.2079/1.4762)	mem 16099MB
[2025-01-17 22:18:03 internimage_t_1k_224] (main.py 510): INFO Train: [10/300][310/312]	eta 0:00:00 lr 0.002201	time 0.4348 (0.4630)	model_time 0.4347 (0.4563)	loss 4.4899 (4.9261)	grad_norm 3.2682 (3.2231/1.4747)	mem 16099MB
[2025-01-17 22:18:04 internimage_t_1k_224] (main.py 519): INFO EPOCH 10 training takes 0:02:24
[2025-01-17 22:18:04 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_10.pth saving......
[2025-01-17 22:18:05 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_10.pth saved !!!
[2025-01-17 22:18:13 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.740 (7.740)	Loss 2.2174 (2.2174)	Acc@1 53.101 (53.101)	Acc@5 78.247 (78.247)	Mem 16099MB
[2025-01-17 22:18:16 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.016)	Loss 2.8275 (2.4459)	Acc@1 40.601 (48.189)	Acc@5 67.676 (74.265)	Mem 16099MB
[2025-01-17 22:18:16 internimage_t_1k_224] (main.py 575): INFO [Epoch:10] * Acc@1 48.578 Acc@5 74.558
[2025-01-17 22:18:16 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 48.6%
[2025-01-17 22:18:16 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:18:17 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:18:17 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 48.58%
[2025-01-17 22:18:25 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.545 (7.545)	Loss 6.5694 (6.5694)	Acc@1 0.854 (0.854)	Acc@5 5.029 (5.029)	Mem 16099MB
[2025-01-17 22:18:28 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.013)	Loss 6.9291 (6.8128)	Acc@1 0.000 (0.200)	Acc@5 0.146 (1.236)	Mem 16099MB
[2025-01-17 22:18:29 internimage_t_1k_224] (main.py 575): INFO [Epoch:10] * Acc@1 0.418 Acc@5 2.115
[2025-01-17 22:18:29 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 22:18:29 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.42%
[2025-01-17 22:18:32 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][0/312]	eta 0:15:38 lr 0.002202	time 3.0064 (3.0064)	model_time 0.6815 (0.6815)	loss 5.5022 (5.5022)	grad_norm 1.8977 (1.8977/0.0000)	mem 16099MB
[2025-01-17 22:18:36 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][10/312]	eta 0:03:29 lr 0.002208	time 0.4461 (0.6951)	model_time 0.4460 (0.4834)	loss 5.3878 (4.8354)	grad_norm 2.6802 (2.7143/0.7361)	mem 16099MB
[2025-01-17 22:18:41 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][20/312]	eta 0:02:48 lr 0.002215	time 0.4480 (0.5768)	model_time 0.4478 (0.4657)	loss 5.2766 (4.8396)	grad_norm 1.6421 (2.7366/0.6920)	mem 16099MB
[2025-01-17 22:18:45 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][30/312]	eta 0:02:31 lr 0.002221	time 0.4397 (0.5379)	model_time 0.4393 (0.4626)	loss 5.6033 (4.8848)	grad_norm 2.1447 (2.9491/1.1129)	mem 16099MB
[2025-01-17 22:18:50 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][40/312]	eta 0:02:20 lr 0.002227	time 0.4469 (0.5174)	model_time 0.4464 (0.4603)	loss 4.6791 (4.7772)	grad_norm 3.7828 (3.0480/1.2048)	mem 16099MB
[2025-01-17 22:18:55 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][50/312]	eta 0:02:13 lr 0.002234	time 0.4465 (0.5089)	model_time 0.4460 (0.4629)	loss 3.8909 (4.7758)	grad_norm 2.1274 (2.9521/1.1586)	mem 16099MB
[2025-01-17 22:18:59 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][60/312]	eta 0:02:05 lr 0.002240	time 0.4484 (0.4993)	model_time 0.4480 (0.4608)	loss 5.0408 (4.7919)	grad_norm 2.2228 (3.0430/1.3452)	mem 16099MB
[2025-01-17 22:19:04 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][70/312]	eta 0:01:59 lr 0.002247	time 0.4564 (0.4930)	model_time 0.4560 (0.4599)	loss 5.5557 (4.7971)	grad_norm 2.5482 (3.1248/1.4742)	mem 16099MB
[2025-01-17 22:19:08 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][80/312]	eta 0:01:53 lr 0.002253	time 0.4563 (0.4892)	model_time 0.4562 (0.4601)	loss 5.6084 (4.8115)	grad_norm 2.7168 (3.0698/1.4483)	mem 16099MB
[2025-01-17 22:19:13 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][90/312]	eta 0:01:47 lr 0.002259	time 0.4461 (0.4848)	model_time 0.4457 (0.4589)	loss 5.3242 (4.7863)	grad_norm 4.1888 (3.1698/1.6863)	mem 16099MB
[2025-01-17 22:19:17 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][100/312]	eta 0:01:42 lr 0.002266	time 0.4433 (0.4820)	model_time 0.4428 (0.4587)	loss 5.5051 (4.7996)	grad_norm 2.0218 (3.1804/1.6644)	mem 16099MB
[2025-01-17 22:19:22 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][110/312]	eta 0:01:37 lr 0.002272	time 0.5632 (0.4806)	model_time 0.5627 (0.4593)	loss 3.7166 (4.7816)	grad_norm 2.0366 (3.1322/1.6072)	mem 16099MB
[2025-01-17 22:19:27 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][120/312]	eta 0:01:32 lr 0.002279	time 0.4358 (0.4799)	model_time 0.4354 (0.4603)	loss 5.3773 (4.7796)	grad_norm 2.9314 (3.1053/1.5620)	mem 16099MB
[2025-01-17 22:19:31 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][130/312]	eta 0:01:26 lr 0.002285	time 0.4490 (0.4776)	model_time 0.4486 (0.4595)	loss 5.6626 (4.8079)	grad_norm 2.1184 (3.0776/1.5178)	mem 16099MB
[2025-01-17 22:19:36 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][140/312]	eta 0:01:21 lr 0.002291	time 0.4483 (0.4759)	model_time 0.4482 (0.4591)	loss 5.0714 (4.8070)	grad_norm 2.6336 (3.0896/1.4993)	mem 16099MB
[2025-01-17 22:19:40 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][150/312]	eta 0:01:17 lr 0.002298	time 0.4803 (0.4754)	model_time 0.4801 (0.4596)	loss 4.8836 (4.8219)	grad_norm 2.1864 (3.1018/1.5458)	mem 16099MB
[2025-01-17 22:19:45 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][160/312]	eta 0:01:12 lr 0.002304	time 0.4480 (0.4748)	model_time 0.4475 (0.4600)	loss 3.9060 (4.8238)	grad_norm 2.0871 (3.1389/1.5998)	mem 16099MB
[2025-01-17 22:19:49 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][170/312]	eta 0:01:07 lr 0.002311	time 0.4366 (0.4733)	model_time 0.4364 (0.4594)	loss 4.0063 (4.8039)	grad_norm 1.6418 (3.0966/1.5754)	mem 16099MB
[2025-01-17 22:19:54 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][180/312]	eta 0:01:02 lr 0.002317	time 0.4363 (0.4721)	model_time 0.4359 (0.4589)	loss 4.6525 (4.8202)	grad_norm 2.5363 (3.0849/1.5470)	mem 16099MB
[2025-01-17 22:19:59 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][190/312]	eta 0:00:57 lr 0.002323	time 0.4486 (0.4711)	model_time 0.4481 (0.4585)	loss 4.2438 (4.8239)	grad_norm 2.7272 (3.1222/1.6060)	mem 16099MB
[2025-01-17 22:20:03 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][200/312]	eta 0:00:52 lr 0.002330	time 0.4552 (0.4704)	model_time 0.4548 (0.4585)	loss 4.8087 (4.8372)	grad_norm 3.7132 (3.1309/1.5879)	mem 16099MB
[2025-01-17 22:20:08 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][210/312]	eta 0:00:47 lr 0.002336	time 0.5264 (0.4696)	model_time 0.5260 (0.4583)	loss 5.5295 (4.8387)	grad_norm 2.5027 (3.1143/1.5546)	mem 16099MB
[2025-01-17 22:20:12 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][220/312]	eta 0:00:43 lr 0.002343	time 0.4569 (0.4687)	model_time 0.4564 (0.4578)	loss 5.0196 (4.8423)	grad_norm 3.3184 (3.0992/1.5360)	mem 16099MB
[2025-01-17 22:20:17 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][230/312]	eta 0:00:38 lr 0.002349	time 0.4380 (0.4681)	model_time 0.4374 (0.4577)	loss 5.0988 (4.8387)	grad_norm 2.2986 (3.0903/1.5250)	mem 16099MB
[2025-01-17 22:20:21 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][240/312]	eta 0:00:33 lr 0.002355	time 0.4615 (0.4677)	model_time 0.4611 (0.4577)	loss 4.3575 (4.8423)	grad_norm 3.9345 (3.1245/1.5407)	mem 16099MB
[2025-01-17 22:20:26 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][250/312]	eta 0:00:28 lr 0.002362	time 0.4399 (0.4672)	model_time 0.4398 (0.4576)	loss 4.9469 (4.8447)	grad_norm 3.1261 (3.1269/1.5564)	mem 16099MB
[2025-01-17 22:20:30 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][260/312]	eta 0:00:24 lr 0.002368	time 0.4593 (0.4668)	model_time 0.4588 (0.4575)	loss 4.2323 (4.8433)	grad_norm 2.3913 (3.1277/1.5467)	mem 16099MB
[2025-01-17 22:20:35 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][270/312]	eta 0:00:19 lr 0.002375	time 0.4495 (0.4660)	model_time 0.4494 (0.4571)	loss 4.9317 (4.8396)	grad_norm 2.9080 (3.0918/1.5324)	mem 16099MB
[2025-01-17 22:20:39 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][280/312]	eta 0:00:14 lr 0.002381	time 0.4557 (0.4658)	model_time 0.4553 (0.4572)	loss 5.3349 (4.8337)	grad_norm 3.0079 (3.0842/1.5129)	mem 16099MB
[2025-01-17 22:20:44 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][290/312]	eta 0:00:10 lr 0.002388	time 0.4386 (0.4659)	model_time 0.4385 (0.4575)	loss 5.1516 (4.8400)	grad_norm 1.8499 (3.0891/1.5333)	mem 16099MB
[2025-01-17 22:20:49 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][300/312]	eta 0:00:05 lr 0.002394	time 0.4346 (0.4652)	model_time 0.4345 (0.4571)	loss 4.4074 (4.8401)	grad_norm 10.8186 (3.1155/1.5860)	mem 16099MB
[2025-01-17 22:20:53 internimage_t_1k_224] (main.py 510): INFO Train: [11/300][310/312]	eta 0:00:00 lr 0.002400	time 0.5095 (0.4646)	model_time 0.5094 (0.4568)	loss 5.0417 (4.8422)	grad_norm 1.7116 (3.1152/1.5882)	mem 16099MB
[2025-01-17 22:20:53 internimage_t_1k_224] (main.py 519): INFO EPOCH 11 training takes 0:02:24
[2025-01-17 22:20:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_11.pth saving......
[2025-01-17 22:20:55 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_11.pth saved !!!
[2025-01-17 22:21:02 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.480 (7.480)	Loss 2.0725 (2.0725)	Acc@1 56.006 (56.006)	Acc@5 80.688 (80.688)	Mem 16099MB
[2025-01-17 22:21:06 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.022)	Loss 2.6746 (2.3100)	Acc@1 44.409 (50.974)	Acc@5 69.629 (76.762)	Mem 16099MB
[2025-01-17 22:21:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:11] * Acc@1 51.400 Acc@5 77.075
[2025-01-17 22:21:06 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 51.4%
[2025-01-17 22:21:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:21:07 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:21:07 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 51.40%
[2025-01-17 22:21:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.315 (7.315)	Loss 6.5622 (6.5622)	Acc@1 0.879 (0.879)	Acc@5 4.834 (4.834)	Mem 16099MB
[2025-01-17 22:21:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.984)	Loss 6.9109 (6.8039)	Acc@1 0.000 (0.220)	Acc@5 0.244 (1.238)	Mem 16099MB
[2025-01-17 22:21:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:11] * Acc@1 0.452 Acc@5 2.157
[2025-01-17 22:21:18 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.5%
[2025-01-17 22:21:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 22:21:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 22:21:20 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.45%
[2025-01-17 22:21:22 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][0/312]	eta 0:13:09 lr 0.002402	time 2.5304 (2.5304)	model_time 0.4745 (0.4745)	loss 4.9289 (4.9289)	grad_norm 3.6087 (3.6087/0.0000)	mem 16099MB
[2025-01-17 22:21:27 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][10/312]	eta 0:03:18 lr 0.002408	time 0.4457 (0.6559)	model_time 0.4455 (0.4687)	loss 5.1371 (4.5382)	grad_norm 2.4873 (2.7459/0.8573)	mem 16099MB
[2025-01-17 22:21:32 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][20/312]	eta 0:02:43 lr 0.002414	time 0.4567 (0.5587)	model_time 0.4566 (0.4606)	loss 3.9386 (4.6727)	grad_norm 5.3375 (3.0639/1.2603)	mem 16099MB
[2025-01-17 22:21:36 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][30/312]	eta 0:02:28 lr 0.002421	time 0.4489 (0.5270)	model_time 0.4483 (0.4604)	loss 4.8984 (4.6966)	grad_norm 2.8998 (2.8579/1.1083)	mem 16099MB
[2025-01-17 22:21:41 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][40/312]	eta 0:02:18 lr 0.002427	time 0.4522 (0.5076)	model_time 0.4520 (0.4572)	loss 4.8312 (4.7059)	grad_norm 2.5274 (3.0878/1.5159)	mem 16099MB
[2025-01-17 22:21:45 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][50/312]	eta 0:02:10 lr 0.002434	time 0.4457 (0.4973)	model_time 0.4456 (0.4567)	loss 4.6781 (4.7324)	grad_norm 1.8096 (2.9117/1.4333)	mem 16099MB
[2025-01-17 22:21:50 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][60/312]	eta 0:02:04 lr 0.002440	time 0.4593 (0.4924)	model_time 0.4588 (0.4584)	loss 3.6391 (4.7368)	grad_norm 4.0537 (2.8997/1.3600)	mem 16099MB
[2025-01-17 22:21:54 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][70/312]	eta 0:01:58 lr 0.002446	time 0.4453 (0.4881)	model_time 0.4451 (0.4588)	loss 3.7815 (4.6936)	grad_norm 2.8311 (2.8466/1.3016)	mem 16099MB
[2025-01-17 22:21:59 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][80/312]	eta 0:01:52 lr 0.002453	time 0.4455 (0.4840)	model_time 0.4451 (0.4583)	loss 5.2383 (4.7240)	grad_norm 2.1699 (2.7958/1.2426)	mem 16099MB
[2025-01-17 22:22:04 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][90/312]	eta 0:01:46 lr 0.002459	time 0.4609 (0.4812)	model_time 0.4607 (0.4583)	loss 4.7951 (4.7360)	grad_norm 2.8421 (2.8476/1.2029)	mem 16099MB
[2025-01-17 22:22:08 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][100/312]	eta 0:01:41 lr 0.002466	time 0.4309 (0.4779)	model_time 0.4304 (0.4572)	loss 5.4516 (4.7203)	grad_norm 1.6728 (2.8813/1.2536)	mem 16099MB
[2025-01-17 22:22:13 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][110/312]	eta 0:01:36 lr 0.002472	time 0.4489 (0.4753)	model_time 0.4485 (0.4564)	loss 3.5533 (4.7305)	grad_norm 1.7885 (2.8753/1.2310)	mem 16099MB
[2025-01-17 22:22:17 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][120/312]	eta 0:01:30 lr 0.002478	time 0.4426 (0.4732)	model_time 0.4422 (0.4558)	loss 4.2161 (4.7136)	grad_norm 2.4511 (2.8362/1.2099)	mem 16099MB
[2025-01-17 22:22:22 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][130/312]	eta 0:01:25 lr 0.002485	time 0.5396 (0.4721)	model_time 0.5392 (0.4560)	loss 5.6501 (4.7121)	grad_norm 2.5859 (2.8487/1.1873)	mem 16099MB
[2025-01-17 22:22:26 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][140/312]	eta 0:01:21 lr 0.002491	time 0.4443 (0.4712)	model_time 0.4438 (0.4562)	loss 5.2005 (4.6971)	grad_norm 2.0511 (2.8079/1.1660)	mem 16099MB
[2025-01-17 22:22:31 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][150/312]	eta 0:01:16 lr 0.002498	time 0.4641 (0.4702)	model_time 0.4637 (0.4563)	loss 4.7687 (4.6943)	grad_norm 5.1670 (2.8327/1.2038)	mem 16099MB
[2025-01-17 22:22:35 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][160/312]	eta 0:01:11 lr 0.002504	time 0.4539 (0.4690)	model_time 0.4537 (0.4559)	loss 4.2408 (4.6817)	grad_norm 3.1172 (2.8649/1.2504)	mem 16099MB
[2025-01-17 22:22:40 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][170/312]	eta 0:01:06 lr 0.002510	time 0.4440 (0.4684)	model_time 0.4436 (0.4560)	loss 5.4953 (4.6890)	grad_norm 2.6897 (2.8492/1.2215)	mem 16099MB
[2025-01-17 22:22:44 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][180/312]	eta 0:01:01 lr 0.002517	time 0.4522 (0.4677)	model_time 0.4517 (0.4560)	loss 4.2904 (4.6882)	grad_norm 3.1784 (2.8206/1.2034)	mem 16099MB
[2025-01-17 22:22:49 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][190/312]	eta 0:00:56 lr 0.002523	time 0.4425 (0.4667)	model_time 0.4421 (0.4556)	loss 4.1790 (4.6821)	grad_norm 5.0424 (2.8232/1.1891)	mem 16099MB
[2025-01-17 22:22:54 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][200/312]	eta 0:00:52 lr 0.002530	time 0.4540 (0.4663)	model_time 0.4535 (0.4557)	loss 4.7466 (4.6747)	grad_norm 5.7217 (2.8927/1.2650)	mem 16099MB
[2025-01-17 22:22:58 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][210/312]	eta 0:00:47 lr 0.002536	time 0.4446 (0.4653)	model_time 0.4442 (0.4551)	loss 4.7803 (4.6719)	grad_norm 3.2996 (2.9351/1.4826)	mem 16099MB
[2025-01-17 22:23:03 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][220/312]	eta 0:00:42 lr 0.002542	time 0.4549 (0.4653)	model_time 0.4545 (0.4556)	loss 5.1221 (4.6791)	grad_norm 2.4132 (2.9177/1.4576)	mem 16099MB
[2025-01-17 22:23:07 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][230/312]	eta 0:00:38 lr 0.002549	time 0.4490 (0.4653)	model_time 0.4488 (0.4561)	loss 4.5748 (4.6844)	grad_norm 4.8076 (2.9122/1.4510)	mem 16099MB
[2025-01-17 22:23:12 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][240/312]	eta 0:00:33 lr 0.002555	time 0.4379 (0.4650)	model_time 0.4375 (0.4561)	loss 3.9757 (4.6877)	grad_norm 2.1023 (2.8690/1.4374)	mem 16099MB
[2025-01-17 22:23:16 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][250/312]	eta 0:00:28 lr 0.002562	time 0.4632 (0.4644)	model_time 0.4628 (0.4559)	loss 3.5916 (4.6924)	grad_norm 2.6331 (2.8778/1.4291)	mem 16099MB
[2025-01-17 22:23:21 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][260/312]	eta 0:00:24 lr 0.002568	time 0.4507 (0.4639)	model_time 0.4503 (0.4557)	loss 4.6325 (4.6913)	grad_norm 2.5206 (2.8955/1.4453)	mem 16099MB
[2025-01-17 22:23:25 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][270/312]	eta 0:00:19 lr 0.002575	time 0.4452 (0.4633)	model_time 0.4451 (0.4554)	loss 3.9891 (4.6838)	grad_norm 2.8896 (2.8918/1.4281)	mem 16099MB
[2025-01-17 22:23:30 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][280/312]	eta 0:00:14 lr 0.002581	time 0.4438 (0.4628)	model_time 0.4434 (0.4551)	loss 5.8526 (4.6963)	grad_norm 2.8952 (2.8905/1.4128)	mem 16099MB
[2025-01-17 22:23:35 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][290/312]	eta 0:00:10 lr 0.002587	time 0.4531 (0.4632)	model_time 0.4530 (0.4558)	loss 4.8054 (4.6893)	grad_norm 2.6697 (2.8831/1.3997)	mem 16099MB
[2025-01-17 22:23:39 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][300/312]	eta 0:00:05 lr 0.002594	time 0.4383 (0.4629)	model_time 0.4382 (0.4557)	loss 4.9877 (4.7006)	grad_norm 2.1429 (2.8832/1.3829)	mem 16099MB
[2025-01-17 22:23:44 internimage_t_1k_224] (main.py 510): INFO Train: [12/300][310/312]	eta 0:00:00 lr 0.002600	time 0.5291 (0.4625)	model_time 0.5290 (0.4555)	loss 5.6630 (4.7097)	grad_norm 3.3496 (2.8760/1.3824)	mem 16099MB
[2025-01-17 22:23:44 internimage_t_1k_224] (main.py 519): INFO EPOCH 12 training takes 0:02:24
[2025-01-17 22:23:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_12.pth saving......
[2025-01-17 22:23:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_12.pth saved !!!
[2025-01-17 22:23:53 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.633 (7.633)	Loss 2.0576 (2.0576)	Acc@1 55.737 (55.737)	Acc@5 80.591 (80.591)	Mem 16099MB
[2025-01-17 22:23:56 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.998)	Loss 2.7069 (2.3057)	Acc@1 44.849 (51.301)	Acc@5 70.264 (76.989)	Mem 16099MB
[2025-01-17 22:23:56 internimage_t_1k_224] (main.py 575): INFO [Epoch:12] * Acc@1 51.831 Acc@5 77.437
[2025-01-17 22:23:56 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 51.8%
[2025-01-17 22:23:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:23:58 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:23:58 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 51.83%
[2025-01-17 22:24:05 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.613 (7.613)	Loss 6.5743 (6.5743)	Acc@1 0.854 (0.854)	Acc@5 4.419 (4.419)	Mem 16099MB
[2025-01-17 22:24:09 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.040)	Loss 6.8950 (6.7972)	Acc@1 0.000 (0.262)	Acc@5 0.464 (1.247)	Mem 16099MB
[2025-01-17 22:24:09 internimage_t_1k_224] (main.py 575): INFO [Epoch:12] * Acc@1 0.496 Acc@5 2.189
[2025-01-17 22:24:09 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.5%
[2025-01-17 22:24:09 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 22:24:11 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 22:24:11 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.50%
[2025-01-17 22:24:13 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][0/312]	eta 0:12:36 lr 0.002601	time 2.4247 (2.4247)	model_time 0.4682 (0.4682)	loss 5.0825 (5.0825)	grad_norm 11.3529 (11.3529/0.0000)	mem 16099MB
[2025-01-17 22:24:18 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][10/312]	eta 0:03:13 lr 0.002608	time 0.4583 (0.6392)	model_time 0.4582 (0.4591)	loss 3.5330 (4.3024)	grad_norm 3.0323 (3.4566/2.6382)	mem 16099MB
[2025-01-17 22:24:22 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][20/312]	eta 0:02:40 lr 0.002614	time 0.4458 (0.5513)	model_time 0.4454 (0.4568)	loss 5.3405 (4.4176)	grad_norm 2.2112 (3.0813/2.1628)	mem 16099MB
[2025-01-17 22:24:27 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][30/312]	eta 0:02:26 lr 0.002621	time 0.4484 (0.5203)	model_time 0.4480 (0.4561)	loss 4.3233 (4.3581)	grad_norm 1.7450 (2.8378/1.8793)	mem 16099MB
[2025-01-17 22:24:31 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][40/312]	eta 0:02:17 lr 0.002627	time 0.4711 (0.5041)	model_time 0.4710 (0.4554)	loss 4.1235 (4.4369)	grad_norm 2.3858 (2.9228/1.8627)	mem 16099MB
[2025-01-17 22:24:36 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][50/312]	eta 0:02:09 lr 0.002633	time 0.4367 (0.4954)	model_time 0.4365 (0.4562)	loss 5.0268 (4.4090)	grad_norm 2.2904 (2.7597/1.7225)	mem 16099MB
[2025-01-17 22:24:40 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][60/312]	eta 0:02:03 lr 0.002640	time 0.4569 (0.4899)	model_time 0.4564 (0.4571)	loss 4.5259 (4.4664)	grad_norm 1.6060 (2.8260/1.6444)	mem 16099MB
[2025-01-17 22:24:45 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][70/312]	eta 0:01:57 lr 0.002646	time 0.4473 (0.4871)	model_time 0.4471 (0.4589)	loss 5.6050 (4.4900)	grad_norm 1.3667 (2.7143/1.5592)	mem 16099MB
[2025-01-17 22:24:50 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][80/312]	eta 0:01:52 lr 0.002653	time 0.5815 (0.4843)	model_time 0.5810 (0.4595)	loss 4.6192 (4.4845)	grad_norm 2.4258 (2.6903/1.4661)	mem 16099MB
[2025-01-17 22:24:54 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][90/312]	eta 0:01:46 lr 0.002659	time 0.4600 (0.4810)	model_time 0.4598 (0.4588)	loss 4.3392 (4.4889)	grad_norm 1.5763 (2.7643/1.5184)	mem 16099MB
[2025-01-17 22:24:59 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][100/312]	eta 0:01:41 lr 0.002665	time 0.4462 (0.4782)	model_time 0.4458 (0.4582)	loss 5.1807 (4.5276)	grad_norm 1.8618 (2.7325/1.4745)	mem 16099MB
[2025-01-17 22:25:04 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][110/312]	eta 0:01:36 lr 0.002672	time 0.4541 (0.4773)	model_time 0.4536 (0.4590)	loss 4.8932 (4.5435)	grad_norm 1.3230 (2.6865/1.4381)	mem 16099MB
[2025-01-17 22:25:08 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][120/312]	eta 0:01:31 lr 0.002678	time 0.4380 (0.4763)	model_time 0.4379 (0.4596)	loss 4.9920 (4.5639)	grad_norm 1.7815 (2.6339/1.4021)	mem 16099MB
[2025-01-17 22:25:13 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][130/312]	eta 0:01:26 lr 0.002685	time 0.4694 (0.4745)	model_time 0.4693 (0.4590)	loss 3.9949 (4.5649)	grad_norm 4.8469 (2.6738/1.4017)	mem 16099MB
[2025-01-17 22:25:17 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][140/312]	eta 0:01:21 lr 0.002691	time 0.4483 (0.4727)	model_time 0.4479 (0.4583)	loss 5.7296 (4.5727)	grad_norm 1.9273 (2.7121/1.4513)	mem 16099MB
[2025-01-17 22:25:22 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][150/312]	eta 0:01:16 lr 0.002697	time 0.4378 (0.4716)	model_time 0.4374 (0.4581)	loss 4.7429 (4.5717)	grad_norm 2.0785 (2.6656/1.4146)	mem 16099MB
[2025-01-17 22:25:26 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][160/312]	eta 0:01:11 lr 0.002704	time 0.5367 (0.4707)	model_time 0.5366 (0.4580)	loss 5.1790 (4.5821)	grad_norm 1.7677 (2.7211/1.4986)	mem 16099MB
[2025-01-17 22:25:31 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][170/312]	eta 0:01:06 lr 0.002710	time 0.4584 (0.4715)	model_time 0.4579 (0.4596)	loss 4.6974 (4.5842)	grad_norm 1.8190 (2.7341/1.4955)	mem 16099MB
[2025-01-17 22:25:36 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][180/312]	eta 0:01:02 lr 0.002717	time 0.4499 (0.4702)	model_time 0.4495 (0.4588)	loss 4.6512 (4.5705)	grad_norm 1.4798 (2.7054/1.4631)	mem 16099MB
[2025-01-17 22:25:40 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][190/312]	eta 0:00:57 lr 0.002723	time 0.4646 (0.4691)	model_time 0.4644 (0.4583)	loss 5.3836 (4.5751)	grad_norm 2.6944 (2.6779/1.4328)	mem 16099MB
[2025-01-17 22:25:45 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][200/312]	eta 0:00:52 lr 0.002729	time 0.4497 (0.4683)	model_time 0.4495 (0.4581)	loss 4.9769 (4.5875)	grad_norm 2.1041 (2.6598/1.4074)	mem 16099MB
[2025-01-17 22:25:49 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][210/312]	eta 0:00:47 lr 0.002736	time 0.4398 (0.4677)	model_time 0.4394 (0.4579)	loss 3.9745 (4.5763)	grad_norm 1.7565 (2.6754/1.3940)	mem 16099MB
[2025-01-17 22:25:54 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][220/312]	eta 0:00:42 lr 0.002742	time 0.4501 (0.4669)	model_time 0.4499 (0.4576)	loss 3.7074 (4.5706)	grad_norm 1.7447 (2.6480/1.3703)	mem 16099MB
[2025-01-17 22:25:59 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][230/312]	eta 0:00:38 lr 0.002749	time 0.4512 (0.4673)	model_time 0.4510 (0.4583)	loss 5.4942 (4.5738)	grad_norm 1.9276 (2.6337/1.3518)	mem 16099MB
[2025-01-17 22:26:03 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][240/312]	eta 0:00:33 lr 0.002755	time 0.4417 (0.4669)	model_time 0.4412 (0.4583)	loss 5.4870 (4.5767)	grad_norm 2.3881 (2.6427/1.3347)	mem 16099MB
[2025-01-17 22:26:08 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][250/312]	eta 0:00:28 lr 0.002761	time 0.4365 (0.4670)	model_time 0.4363 (0.4587)	loss 4.6138 (4.5650)	grad_norm 3.4809 (2.6284/1.3144)	mem 16099MB
[2025-01-17 22:26:12 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][260/312]	eta 0:00:24 lr 0.002768	time 0.4366 (0.4670)	model_time 0.4364 (0.4590)	loss 4.7839 (4.5769)	grad_norm 2.2417 (2.6565/1.3319)	mem 16099MB
[2025-01-17 22:26:17 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][270/312]	eta 0:00:19 lr 0.002774	time 0.4437 (0.4667)	model_time 0.4435 (0.4590)	loss 3.6903 (4.5797)	grad_norm 1.9204 (2.6415/1.3189)	mem 16099MB
[2025-01-17 22:26:22 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][280/312]	eta 0:00:14 lr 0.002781	time 0.4436 (0.4661)	model_time 0.4432 (0.4587)	loss 3.4293 (4.5763)	grad_norm 2.0003 (2.6283/1.3021)	mem 16099MB
[2025-01-17 22:26:26 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][290/312]	eta 0:00:10 lr 0.002787	time 0.4400 (0.4655)	model_time 0.4399 (0.4583)	loss 4.8288 (4.5710)	grad_norm 1.8384 (2.6110/1.2941)	mem 16099MB
[2025-01-17 22:26:31 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][300/312]	eta 0:00:05 lr 0.002794	time 0.4340 (0.4650)	model_time 0.4339 (0.4581)	loss 4.8152 (4.5730)	grad_norm 2.4965 (2.5637/1.1768)	mem 16099MB
[2025-01-17 22:26:35 internimage_t_1k_224] (main.py 510): INFO Train: [13/300][310/312]	eta 0:00:00 lr 0.002800	time 0.4344 (0.4646)	model_time 0.4343 (0.4579)	loss 4.7560 (4.5675)	grad_norm 2.0842 (2.5679/1.1976)	mem 16099MB
[2025-01-17 22:26:36 internimage_t_1k_224] (main.py 519): INFO EPOCH 13 training takes 0:02:24
[2025-01-17 22:26:36 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_13.pth saving......
[2025-01-17 22:26:37 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_13.pth saved !!!
[2025-01-17 22:26:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.562 (7.562)	Loss 1.8406 (1.8406)	Acc@1 60.034 (60.034)	Acc@5 83.130 (83.130)	Mem 16099MB
[2025-01-17 22:26:48 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.004)	Loss 2.4541 (2.1217)	Acc@1 48.413 (54.909)	Acc@5 74.170 (79.909)	Mem 16099MB
[2025-01-17 22:26:48 internimage_t_1k_224] (main.py 575): INFO [Epoch:13] * Acc@1 55.310 Acc@5 80.214
[2025-01-17 22:26:48 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 55.3%
[2025-01-17 22:26:48 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:26:49 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:26:49 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 55.31%
[2025-01-17 22:26:57 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.616 (7.616)	Loss 6.6088 (6.6088)	Acc@1 0.928 (0.928)	Acc@5 4.053 (4.053)	Mem 16099MB
[2025-01-17 22:27:00 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.004)	Loss 6.8817 (6.7928)	Acc@1 0.000 (0.315)	Acc@5 0.635 (1.287)	Mem 16099MB
[2025-01-17 22:27:00 internimage_t_1k_224] (main.py 575): INFO [Epoch:13] * Acc@1 0.542 Acc@5 2.197
[2025-01-17 22:27:00 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.5%
[2025-01-17 22:27:00 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 22:27:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 22:27:02 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.54%
[2025-01-17 22:27:04 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][0/312]	eta 0:12:09 lr 0.002801	time 2.3372 (2.3372)	model_time 0.4653 (0.4653)	loss 4.7450 (4.7450)	grad_norm 1.8995 (1.8995/0.0000)	mem 16099MB
[2025-01-17 22:27:08 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][10/312]	eta 0:03:09 lr 0.002808	time 0.4516 (0.6286)	model_time 0.4515 (0.4581)	loss 3.3296 (4.4675)	grad_norm 3.0343 (1.9784/0.4780)	mem 16099MB
[2025-01-17 22:27:13 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][20/312]	eta 0:02:42 lr 0.002814	time 0.5240 (0.5550)	model_time 0.5238 (0.4656)	loss 5.1591 (4.4888)	grad_norm 3.2750 (2.0961/0.4939)	mem 16099MB
[2025-01-17 22:27:18 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][30/312]	eta 0:02:28 lr 0.002820	time 0.4441 (0.5261)	model_time 0.4439 (0.4654)	loss 5.1868 (4.5791)	grad_norm 1.5135 (2.3845/0.9885)	mem 16099MB
[2025-01-17 22:27:23 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][40/312]	eta 0:02:19 lr 0.002827	time 0.4581 (0.5116)	model_time 0.4577 (0.4657)	loss 4.9560 (4.6014)	grad_norm 1.4785 (2.4544/1.1927)	mem 16099MB
[2025-01-17 22:27:27 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][50/312]	eta 0:02:11 lr 0.002833	time 0.4447 (0.5012)	model_time 0.4445 (0.4642)	loss 4.7487 (4.5544)	grad_norm 1.2013 (2.5469/1.2976)	mem 16099MB
[2025-01-17 22:27:32 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][60/312]	eta 0:02:04 lr 0.002840	time 0.4401 (0.4927)	model_time 0.4400 (0.4618)	loss 5.1581 (4.5499)	grad_norm 1.5421 (2.5747/1.3621)	mem 16099MB
[2025-01-17 22:27:36 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][70/312]	eta 0:01:58 lr 0.002846	time 0.4613 (0.4877)	model_time 0.4612 (0.4610)	loss 4.9777 (4.5705)	grad_norm 1.9814 (2.5595/1.3129)	mem 16099MB
[2025-01-17 22:27:41 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][80/312]	eta 0:01:52 lr 0.002852	time 0.4413 (0.4832)	model_time 0.4411 (0.4598)	loss 4.7447 (4.5934)	grad_norm 2.2733 (2.5694/1.2806)	mem 16099MB
[2025-01-17 22:27:45 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][90/312]	eta 0:01:46 lr 0.002859	time 0.4598 (0.4797)	model_time 0.4594 (0.4588)	loss 4.4366 (4.5612)	grad_norm 1.7865 (2.5027/1.2284)	mem 16099MB
[2025-01-17 22:27:50 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][100/312]	eta 0:01:41 lr 0.002865	time 0.4447 (0.4775)	model_time 0.4446 (0.4587)	loss 4.3321 (4.5865)	grad_norm 4.6349 (2.5323/1.2260)	mem 16099MB
[2025-01-17 22:27:54 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][110/312]	eta 0:01:35 lr 0.002872	time 0.4539 (0.4750)	model_time 0.4537 (0.4578)	loss 3.8876 (4.5898)	grad_norm 1.5146 (2.6054/1.3147)	mem 16099MB
[2025-01-17 22:27:59 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][120/312]	eta 0:01:30 lr 0.002878	time 0.4683 (0.4730)	model_time 0.4682 (0.4572)	loss 3.5731 (4.5809)	grad_norm 3.3130 (2.5811/1.2779)	mem 16099MB
[2025-01-17 22:28:03 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][130/312]	eta 0:01:25 lr 0.002884	time 0.4473 (0.4719)	model_time 0.4469 (0.4573)	loss 4.6344 (4.5828)	grad_norm 2.7679 (2.5751/1.2635)	mem 16099MB
[2025-01-17 22:28:08 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][140/312]	eta 0:01:21 lr 0.002891	time 0.4474 (0.4710)	model_time 0.4470 (0.4574)	loss 5.1069 (4.5896)	grad_norm 2.1428 (2.5714/1.2277)	mem 16099MB
[2025-01-17 22:28:13 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][150/312]	eta 0:01:16 lr 0.002897	time 0.4375 (0.4709)	model_time 0.4374 (0.4582)	loss 5.1487 (4.5844)	grad_norm 2.1302 (2.5692/1.2084)	mem 16099MB
[2025-01-17 22:28:17 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][160/312]	eta 0:01:11 lr 0.002904	time 0.4522 (0.4704)	model_time 0.4521 (0.4584)	loss 5.0833 (4.5872)	grad_norm 1.8672 (2.6078/1.2663)	mem 16099MB
[2025-01-17 22:28:22 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][170/312]	eta 0:01:06 lr 0.002910	time 0.4472 (0.4704)	model_time 0.4467 (0.4592)	loss 3.3936 (4.5735)	grad_norm 2.1960 (2.5828/1.2406)	mem 16099MB
[2025-01-17 22:28:26 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][180/312]	eta 0:01:01 lr 0.002916	time 0.4501 (0.4693)	model_time 0.4497 (0.4586)	loss 5.3359 (4.5778)	grad_norm 5.9693 (2.6020/1.2503)	mem 16099MB
[2025-01-17 22:28:31 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][190/312]	eta 0:00:57 lr 0.002923	time 0.4467 (0.4682)	model_time 0.4466 (0.4581)	loss 4.3994 (4.5855)	grad_norm 1.9321 (2.5732/1.2354)	mem 16099MB
[2025-01-17 22:28:36 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][200/312]	eta 0:00:52 lr 0.002929	time 0.4524 (0.4679)	model_time 0.4520 (0.4582)	loss 4.7516 (4.5850)	grad_norm 2.0985 (2.5614/1.2193)	mem 16099MB
[2025-01-17 22:28:40 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][210/312]	eta 0:00:47 lr 0.002936	time 0.4458 (0.4672)	model_time 0.4456 (0.4580)	loss 5.0523 (4.5849)	grad_norm 1.7336 (2.5432/1.2009)	mem 16099MB
[2025-01-17 22:28:45 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][220/312]	eta 0:00:42 lr 0.002942	time 0.4459 (0.4669)	model_time 0.4457 (0.4581)	loss 4.2208 (4.5935)	grad_norm 1.7068 (2.5442/1.1791)	mem 16099MB
[2025-01-17 22:28:49 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][230/312]	eta 0:00:38 lr 0.002948	time 0.4484 (0.4663)	model_time 0.4479 (0.4579)	loss 4.5842 (4.5945)	grad_norm 3.9737 (2.5296/1.1645)	mem 16099MB
[2025-01-17 22:28:54 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][240/312]	eta 0:00:33 lr 0.002955	time 0.4496 (0.4660)	model_time 0.4495 (0.4579)	loss 4.1702 (4.5812)	grad_norm 2.5803 (2.5818/1.2199)	mem 16099MB
[2025-01-17 22:28:58 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][250/312]	eta 0:00:28 lr 0.002961	time 0.4470 (0.4653)	model_time 0.4466 (0.4576)	loss 4.5543 (4.5907)	grad_norm 3.0071 (2.5924/1.2076)	mem 16099MB
[2025-01-17 22:29:03 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][260/312]	eta 0:00:24 lr 0.002968	time 0.4401 (0.4651)	model_time 0.4399 (0.4576)	loss 5.1982 (4.5882)	grad_norm 2.1082 (2.5776/1.1890)	mem 16099MB
[2025-01-17 22:29:07 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][270/312]	eta 0:00:19 lr 0.002974	time 0.4473 (0.4647)	model_time 0.4471 (0.4575)	loss 4.1372 (4.5876)	grad_norm 1.3906 (2.5641/1.1789)	mem 16099MB
[2025-01-17 22:29:12 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][280/312]	eta 0:00:14 lr 0.002981	time 0.4441 (0.4641)	model_time 0.4440 (0.4572)	loss 4.0212 (4.5878)	grad_norm 1.3209 (2.5590/1.1687)	mem 16099MB
[2025-01-17 22:29:17 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][290/312]	eta 0:00:10 lr 0.002987	time 0.4443 (0.4639)	model_time 0.4439 (0.4571)	loss 4.8712 (4.5955)	grad_norm 2.4422 (2.5454/1.1548)	mem 16099MB
[2025-01-17 22:29:21 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][300/312]	eta 0:00:05 lr 0.002993	time 0.4360 (0.4634)	model_time 0.4359 (0.4568)	loss 4.4720 (4.5979)	grad_norm 5.7480 (2.5658/1.1606)	mem 16099MB
[2025-01-17 22:29:25 internimage_t_1k_224] (main.py 510): INFO Train: [14/300][310/312]	eta 0:00:00 lr 0.003000	time 0.4378 (0.4627)	model_time 0.4377 (0.4564)	loss 5.4228 (4.5978)	grad_norm 3.5519 (2.5785/1.1605)	mem 16099MB
[2025-01-17 22:29:26 internimage_t_1k_224] (main.py 519): INFO EPOCH 14 training takes 0:02:24
[2025-01-17 22:29:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_14.pth saving......
[2025-01-17 22:29:27 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_14.pth saved !!!
[2025-01-17 22:29:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.151 (7.151)	Loss 1.7114 (1.7114)	Acc@1 61.304 (61.304)	Acc@5 85.669 (85.669)	Mem 16099MB
[2025-01-17 22:29:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.960)	Loss 2.5354 (2.0506)	Acc@1 46.387 (56.254)	Acc@5 72.974 (80.961)	Mem 16099MB
[2025-01-17 22:29:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:14] * Acc@1 56.436 Acc@5 81.158
[2025-01-17 22:29:38 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 56.4%
[2025-01-17 22:29:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:29:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:29:39 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 56.44%
[2025-01-17 22:29:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.263 (7.263)	Loss 6.6566 (6.6566)	Acc@1 1.025 (1.025)	Acc@5 3.589 (3.589)	Mem 16099MB
[2025-01-17 22:29:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.983)	Loss 6.8719 (6.7906)	Acc@1 0.024 (0.364)	Acc@5 0.830 (1.332)	Mem 16099MB
[2025-01-17 22:29:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:14] * Acc@1 0.582 Acc@5 2.173
[2025-01-17 22:29:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.6%
[2025-01-17 22:29:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 22:29:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 22:29:51 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:29:54 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][0/312]	eta 0:12:00 lr 0.003001	time 2.3088 (2.3088)	model_time 0.4872 (0.4872)	loss 4.5969 (4.5969)	grad_norm 3.1772 (3.1772/0.0000)	mem 16099MB
[2025-01-17 22:29:58 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][10/312]	eta 0:03:08 lr 0.003007	time 0.4389 (0.6258)	model_time 0.4385 (0.4599)	loss 4.9788 (4.6386)	grad_norm 1.4837 (2.2207/0.6887)	mem 16099MB
[2025-01-17 22:30:03 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][20/312]	eta 0:02:42 lr 0.003014	time 0.4871 (0.5555)	model_time 0.4870 (0.4684)	loss 5.4205 (4.7540)	grad_norm 2.4461 (2.2254/0.5319)	mem 16099MB
[2025-01-17 22:30:07 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][30/312]	eta 0:02:26 lr 0.003020	time 0.4411 (0.5209)	model_time 0.4409 (0.4618)	loss 4.6386 (4.6448)	grad_norm 1.5580 (2.3020/0.7787)	mem 16099MB
[2025-01-17 22:30:12 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][40/312]	eta 0:02:17 lr 0.003027	time 0.4696 (0.5066)	model_time 0.4694 (0.4619)	loss 4.8925 (4.6309)	grad_norm 2.5392 (2.5673/1.1049)	mem 16099MB
[2025-01-17 22:30:17 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][50/312]	eta 0:02:10 lr 0.003033	time 0.4502 (0.4988)	model_time 0.4500 (0.4627)	loss 3.9400 (4.5760)	grad_norm 1.8944 (2.4896/1.0247)	mem 16099MB
[2025-01-17 22:30:21 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][60/312]	eta 0:02:03 lr 0.003039	time 0.4464 (0.4914)	model_time 0.4463 (0.4613)	loss 4.7046 (4.5987)	grad_norm 1.4992 (2.4686/0.9820)	mem 16099MB
[2025-01-17 22:30:26 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][70/312]	eta 0:01:57 lr 0.003046	time 0.4467 (0.4871)	model_time 0.4465 (0.4611)	loss 4.1290 (4.5860)	grad_norm 4.3515 (2.6413/1.2864)	mem 16099MB
[2025-01-17 22:30:30 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][80/312]	eta 0:01:51 lr 0.003052	time 0.4489 (0.4826)	model_time 0.4487 (0.4598)	loss 3.9451 (4.5466)	grad_norm 2.0214 (2.5389/1.2419)	mem 16099MB
[2025-01-17 22:30:35 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][90/312]	eta 0:01:46 lr 0.003059	time 0.4531 (0.4804)	model_time 0.4529 (0.4601)	loss 4.8333 (4.5303)	grad_norm 2.5821 (2.5861/1.2972)	mem 16099MB
[2025-01-17 22:30:40 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][100/312]	eta 0:01:41 lr 0.003065	time 0.4444 (0.4780)	model_time 0.4443 (0.4596)	loss 4.7703 (4.5305)	grad_norm 1.9296 (2.6428/1.3208)	mem 16099MB
[2025-01-17 22:30:44 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][110/312]	eta 0:01:36 lr 0.003071	time 0.4407 (0.4774)	model_time 0.4406 (0.4607)	loss 5.3408 (4.5342)	grad_norm 2.8274 (2.5733/1.2860)	mem 16099MB
[2025-01-17 22:30:49 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][120/312]	eta 0:01:31 lr 0.003078	time 0.4469 (0.4753)	model_time 0.4464 (0.4599)	loss 4.8508 (4.5321)	grad_norm 1.8420 (2.5794/1.2633)	mem 16099MB
[2025-01-17 22:30:53 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][130/312]	eta 0:01:26 lr 0.003084	time 0.4468 (0.4739)	model_time 0.4466 (0.4597)	loss 4.1019 (4.5293)	grad_norm 3.4163 (2.5543/1.2409)	mem 16099MB
[2025-01-17 22:30:58 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][140/312]	eta 0:01:21 lr 0.003091	time 0.4493 (0.4722)	model_time 0.4492 (0.4589)	loss 3.7517 (4.5321)	grad_norm 2.1996 (2.5167/1.2069)	mem 16099MB
[2025-01-17 22:31:02 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][150/312]	eta 0:01:16 lr 0.003097	time 0.4461 (0.4714)	model_time 0.4459 (0.4590)	loss 4.5969 (4.5189)	grad_norm 2.1308 (2.5644/1.3060)	mem 16099MB
[2025-01-17 22:31:07 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][160/312]	eta 0:01:11 lr 0.003103	time 0.4560 (0.4705)	model_time 0.4556 (0.4588)	loss 4.4286 (4.5260)	grad_norm 1.6200 (2.5239/1.2760)	mem 16099MB
[2025-01-17 22:31:12 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][170/312]	eta 0:01:06 lr 0.003110	time 0.4481 (0.4695)	model_time 0.4480 (0.4585)	loss 4.5718 (4.5168)	grad_norm 2.3442 (2.5093/1.2439)	mem 16099MB
[2025-01-17 22:31:16 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][180/312]	eta 0:01:01 lr 0.003116	time 0.4444 (0.4687)	model_time 0.4443 (0.4583)	loss 4.3277 (4.4979)	grad_norm 3.5754 (2.5150/1.2269)	mem 16099MB
[2025-01-17 22:31:21 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][190/312]	eta 0:00:57 lr 0.003123	time 0.4461 (0.4677)	model_time 0.4457 (0.4578)	loss 3.5494 (4.4775)	grad_norm 3.8634 (2.5163/1.2160)	mem 16099MB
[2025-01-17 22:31:25 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][200/312]	eta 0:00:52 lr 0.003129	time 0.4601 (0.4671)	model_time 0.4600 (0.4577)	loss 5.3460 (4.4750)	grad_norm 2.2815 (2.5148/1.2453)	mem 16099MB
[2025-01-17 22:31:30 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][210/312]	eta 0:00:47 lr 0.003135	time 0.5349 (0.4666)	model_time 0.5348 (0.4576)	loss 4.6687 (4.4692)	grad_norm 1.2940 (2.4789/1.2280)	mem 16099MB
[2025-01-17 22:31:34 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][220/312]	eta 0:00:42 lr 0.003142	time 0.4488 (0.4658)	model_time 0.4486 (0.4572)	loss 3.6953 (4.4560)	grad_norm 2.4038 (2.4487/1.2105)	mem 16099MB
[2025-01-17 22:31:39 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][230/312]	eta 0:00:38 lr 0.003148	time 0.4374 (0.4656)	model_time 0.4372 (0.4573)	loss 3.1765 (4.4532)	grad_norm 4.0933 (2.5146/1.2627)	mem 16099MB
[2025-01-17 22:31:43 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][240/312]	eta 0:00:33 lr 0.003155	time 0.4539 (0.4648)	model_time 0.4537 (0.4569)	loss 4.1786 (4.4612)	grad_norm 1.5767 (2.4918/1.2457)	mem 16099MB
[2025-01-17 22:31:48 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][250/312]	eta 0:00:28 lr 0.003161	time 0.4477 (0.4644)	model_time 0.4475 (0.4568)	loss 4.5549 (4.4572)	grad_norm 1.5218 (2.4908/1.2710)	mem 16099MB
[2025-01-17 22:31:52 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][260/312]	eta 0:00:24 lr 0.003168	time 0.4368 (0.4643)	model_time 0.4366 (0.4570)	loss 5.6359 (4.4744)	grad_norm 1.5592 (2.4725/1.2513)	mem 16099MB
[2025-01-17 22:31:57 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][270/312]	eta 0:00:19 lr 0.003174	time 0.4567 (0.4640)	model_time 0.4563 (0.4570)	loss 4.2063 (4.4753)	grad_norm 1.8621 (2.4760/1.2356)	mem 16099MB
[2025-01-17 22:32:02 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][280/312]	eta 0:00:14 lr 0.003180	time 0.4450 (0.4641)	model_time 0.4448 (0.4573)	loss 3.8195 (4.4771)	grad_norm 1.5430 (2.4676/1.2227)	mem 16099MB
[2025-01-17 22:32:06 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][290/312]	eta 0:00:10 lr 0.003187	time 0.4435 (0.4641)	model_time 0.4433 (0.4575)	loss 4.9728 (4.4690)	grad_norm 1.5410 (2.4378/1.2152)	mem 16099MB
[2025-01-17 22:32:11 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][300/312]	eta 0:00:05 lr 0.003193	time 0.4345 (0.4634)	model_time 0.4344 (0.4571)	loss 4.6965 (4.4772)	grad_norm 3.7833 (2.4342/1.2018)	mem 16099MB
[2025-01-17 22:32:15 internimage_t_1k_224] (main.py 510): INFO Train: [15/300][310/312]	eta 0:00:00 lr 0.003200	time 0.4386 (0.4628)	model_time 0.4385 (0.4566)	loss 4.4161 (4.4786)	grad_norm 2.6437 (2.4375/1.1985)	mem 16099MB
[2025-01-17 22:32:16 internimage_t_1k_224] (main.py 519): INFO EPOCH 15 training takes 0:02:24
[2025-01-17 22:32:16 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_15.pth saving......
[2025-01-17 22:32:17 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_15.pth saved !!!
[2025-01-17 22:32:24 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.340 (7.340)	Loss 1.6788 (1.6788)	Acc@1 63.672 (63.672)	Acc@5 86.499 (86.499)	Mem 16099MB
[2025-01-17 22:32:28 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.987)	Loss 2.2939 (1.9420)	Acc@1 51.514 (58.123)	Acc@5 77.100 (82.573)	Mem 16099MB
[2025-01-17 22:32:28 internimage_t_1k_224] (main.py 575): INFO [Epoch:15] * Acc@1 58.453 Acc@5 82.734
[2025-01-17 22:32:28 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 58.5%
[2025-01-17 22:32:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:32:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:32:29 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 58.45%
[2025-01-17 22:32:37 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.544 (7.544)	Loss 6.7116 (6.7116)	Acc@1 0.879 (0.879)	Acc@5 2.930 (2.930)	Mem 16099MB
[2025-01-17 22:32:40 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.012)	Loss 6.8639 (6.7922)	Acc@1 0.049 (0.344)	Acc@5 0.830 (1.303)	Mem 16099MB
[2025-01-17 22:32:40 internimage_t_1k_224] (main.py 575): INFO [Epoch:15] * Acc@1 0.550 Acc@5 2.047
[2025-01-17 22:32:40 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.5%
[2025-01-17 22:32:40 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:32:43 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][0/312]	eta 0:14:00 lr 0.003201	time 2.6950 (2.6950)	model_time 1.0030 (1.0030)	loss 4.4589 (4.4589)	grad_norm 2.7603 (2.7603/0.0000)	mem 16099MB
[2025-01-17 22:32:48 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][10/312]	eta 0:03:25 lr 0.003207	time 0.5440 (0.6820)	model_time 0.5436 (0.5279)	loss 3.4980 (4.5543)	grad_norm 1.6843 (2.4626/0.5746)	mem 16099MB
[2025-01-17 22:32:52 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][20/312]	eta 0:02:47 lr 0.003214	time 0.4597 (0.5747)	model_time 0.4595 (0.4938)	loss 5.0257 (4.5388)	grad_norm 3.4304 (2.5626/0.8577)	mem 16099MB
[2025-01-17 22:32:57 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][30/312]	eta 0:02:31 lr 0.003220	time 0.4642 (0.5373)	model_time 0.4641 (0.4824)	loss 4.0232 (4.4763)	grad_norm 1.9999 (2.5039/1.0951)	mem 16099MB
[2025-01-17 22:33:01 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][40/312]	eta 0:02:20 lr 0.003226	time 0.4394 (0.5153)	model_time 0.4389 (0.4738)	loss 3.6626 (4.4457)	grad_norm 1.2050 (2.4938/1.1116)	mem 16099MB
[2025-01-17 22:33:06 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][50/312]	eta 0:02:12 lr 0.003233	time 0.4498 (0.5061)	model_time 0.4494 (0.4726)	loss 3.8999 (4.4382)	grad_norm 2.3472 (2.4123/1.0396)	mem 16099MB
[2025-01-17 22:33:11 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][60/312]	eta 0:02:05 lr 0.003239	time 0.4544 (0.4984)	model_time 0.4543 (0.4703)	loss 4.1505 (4.4266)	grad_norm 2.1159 (2.3500/0.9687)	mem 16099MB
[2025-01-17 22:33:15 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][70/312]	eta 0:01:59 lr 0.003246	time 0.4420 (0.4933)	model_time 0.4418 (0.4691)	loss 4.0976 (4.4636)	grad_norm 1.8727 (2.4554/1.0946)	mem 16099MB
[2025-01-17 22:33:20 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][80/312]	eta 0:01:53 lr 0.003252	time 0.4472 (0.4880)	model_time 0.4468 (0.4668)	loss 3.6906 (4.4414)	grad_norm 1.2550 (2.4173/1.0569)	mem 16099MB
[2025-01-17 22:33:24 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][90/312]	eta 0:01:47 lr 0.003258	time 0.5269 (0.4843)	model_time 0.5267 (0.4654)	loss 5.2933 (4.4505)	grad_norm 2.1129 (2.3252/1.0346)	mem 16099MB
[2025-01-17 22:33:29 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][100/312]	eta 0:01:42 lr 0.003265	time 0.4488 (0.4815)	model_time 0.4484 (0.4644)	loss 3.6080 (4.4181)	grad_norm 2.5545 (2.3964/1.0927)	mem 16099MB
[2025-01-17 22:33:33 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][110/312]	eta 0:01:36 lr 0.003271	time 0.4476 (0.4787)	model_time 0.4474 (0.4631)	loss 4.8348 (4.4173)	grad_norm 1.2841 (2.3782/1.0677)	mem 16099MB
[2025-01-17 22:33:38 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][120/312]	eta 0:01:31 lr 0.003278	time 0.4439 (0.4761)	model_time 0.4438 (0.4618)	loss 4.7713 (4.4237)	grad_norm 1.4238 (2.3867/1.0760)	mem 16099MB
[2025-01-17 22:33:43 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][130/312]	eta 0:01:26 lr 0.003284	time 0.4394 (0.4752)	model_time 0.4393 (0.4620)	loss 4.1976 (4.4109)	grad_norm 1.3345 (2.3403/1.0576)	mem 16099MB
[2025-01-17 22:33:47 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][140/312]	eta 0:01:21 lr 0.003290	time 0.4406 (0.4759)	model_time 0.4401 (0.4635)	loss 4.5171 (4.4305)	grad_norm 1.5406 (2.3011/1.0338)	mem 16099MB
[2025-01-17 22:33:52 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][150/312]	eta 0:01:16 lr 0.003297	time 0.4477 (0.4741)	model_time 0.4475 (0.4625)	loss 4.7929 (4.4436)	grad_norm 2.7694 (2.3470/1.0276)	mem 16099MB
[2025-01-17 22:33:57 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][160/312]	eta 0:01:12 lr 0.003303	time 0.4390 (0.4737)	model_time 0.4386 (0.4628)	loss 3.9914 (4.4385)	grad_norm 1.9153 (2.3332/1.0075)	mem 16099MB
[2025-01-17 22:34:01 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][170/312]	eta 0:01:07 lr 0.003310	time 0.4410 (0.4721)	model_time 0.4406 (0.4619)	loss 5.4777 (4.4516)	grad_norm 1.5693 (2.3034/0.9934)	mem 16099MB
[2025-01-17 22:34:06 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][180/312]	eta 0:01:02 lr 0.003316	time 0.5589 (0.4721)	model_time 0.5587 (0.4624)	loss 5.0642 (4.4456)	grad_norm 2.0758 (2.3366/1.0202)	mem 16099MB
[2025-01-17 22:34:10 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][190/312]	eta 0:00:57 lr 0.003322	time 0.4380 (0.4711)	model_time 0.4378 (0.4619)	loss 4.8821 (4.4583)	grad_norm 2.0630 (2.3183/1.0068)	mem 16099MB
[2025-01-17 22:34:15 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][200/312]	eta 0:00:52 lr 0.003329	time 0.4477 (0.4703)	model_time 0.4476 (0.4615)	loss 4.1986 (4.4435)	grad_norm 1.7679 (2.2971/0.9894)	mem 16099MB
[2025-01-17 22:34:19 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][210/312]	eta 0:00:47 lr 0.003335	time 0.4521 (0.4694)	model_time 0.4520 (0.4610)	loss 5.2387 (4.4543)	grad_norm 2.0599 (2.2834/0.9704)	mem 16099MB
[2025-01-17 22:34:24 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][220/312]	eta 0:00:43 lr 0.003342	time 0.4372 (0.4689)	model_time 0.4371 (0.4609)	loss 4.0515 (4.4525)	grad_norm 1.9735 (2.2668/0.9563)	mem 16099MB
[2025-01-17 22:34:28 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][230/312]	eta 0:00:38 lr 0.003348	time 0.4458 (0.4683)	model_time 0.4457 (0.4606)	loss 4.2839 (4.4631)	grad_norm 3.9461 (2.2759/0.9551)	mem 16099MB
[2025-01-17 22:34:33 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][240/312]	eta 0:00:33 lr 0.003354	time 0.4467 (0.4677)	model_time 0.4463 (0.4603)	loss 4.7268 (4.4567)	grad_norm 1.7656 (2.3038/0.9925)	mem 16099MB
[2025-01-17 22:34:38 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][250/312]	eta 0:00:28 lr 0.003361	time 0.4496 (0.4669)	model_time 0.4491 (0.4598)	loss 4.1447 (4.4645)	grad_norm 2.3371 (2.2858/0.9780)	mem 16099MB
[2025-01-17 22:34:42 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][260/312]	eta 0:00:24 lr 0.003367	time 0.4555 (0.4664)	model_time 0.4553 (0.4595)	loss 4.1300 (4.4673)	grad_norm 1.9012 (2.2803/0.9654)	mem 16099MB
[2025-01-17 22:34:47 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][270/312]	eta 0:00:19 lr 0.003374	time 0.4496 (0.4662)	model_time 0.4494 (0.4596)	loss 3.6182 (4.4689)	grad_norm 2.2667 (2.3057/0.9982)	mem 16099MB
[2025-01-17 22:34:51 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][280/312]	eta 0:00:14 lr 0.003380	time 0.4356 (0.4656)	model_time 0.4355 (0.4592)	loss 4.6456 (4.4675)	grad_norm 1.1997 (2.2812/0.9941)	mem 16099MB
[2025-01-17 22:34:56 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][290/312]	eta 0:00:10 lr 0.003387	time 0.4449 (0.4654)	model_time 0.4447 (0.4592)	loss 4.3260 (4.4660)	grad_norm 2.6607 (2.3018/0.9947)	mem 16099MB
[2025-01-17 22:35:00 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][300/312]	eta 0:00:05 lr 0.003393	time 0.4345 (0.4656)	model_time 0.4344 (0.4596)	loss 5.2750 (4.4736)	grad_norm 2.3421 (2.3079/1.0130)	mem 16099MB
[2025-01-17 22:35:05 internimage_t_1k_224] (main.py 510): INFO Train: [16/300][310/312]	eta 0:00:00 lr 0.003399	time 0.4415 (0.4648)	model_time 0.4414 (0.4590)	loss 4.7507 (4.4800)	grad_norm 1.0572 (2.2867/1.0148)	mem 16099MB
[2025-01-17 22:35:05 internimage_t_1k_224] (main.py 519): INFO EPOCH 16 training takes 0:02:24
[2025-01-17 22:35:05 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_16.pth saving......
[2025-01-17 22:35:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_16.pth saved !!!
[2025-01-17 22:35:14 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.171 (7.171)	Loss 1.6684 (1.6684)	Acc@1 64.014 (64.014)	Acc@5 86.597 (86.597)	Mem 16099MB
[2025-01-17 22:35:17 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.977)	Loss 2.2436 (1.9173)	Acc@1 52.905 (59.235)	Acc@5 77.026 (82.948)	Mem 16099MB
[2025-01-17 22:35:17 internimage_t_1k_224] (main.py 575): INFO [Epoch:16] * Acc@1 59.531 Acc@5 83.243
[2025-01-17 22:35:17 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 59.5%
[2025-01-17 22:35:17 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:35:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:35:19 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 59.53%
[2025-01-17 22:35:26 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.408 (7.408)	Loss 6.7667 (6.7667)	Acc@1 0.854 (0.854)	Acc@5 2.637 (2.637)	Mem 16099MB
[2025-01-17 22:35:30 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.994)	Loss 6.8564 (6.7960)	Acc@1 0.098 (0.335)	Acc@5 0.830 (1.329)	Mem 16099MB
[2025-01-17 22:35:30 internimage_t_1k_224] (main.py 575): INFO [Epoch:16] * Acc@1 0.504 Acc@5 1.935
[2025-01-17 22:35:30 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.5%
[2025-01-17 22:35:30 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:35:33 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][0/312]	eta 0:16:15 lr 0.003401	time 3.1252 (3.1252)	model_time 1.3752 (1.3752)	loss 4.3938 (4.3938)	grad_norm 1.3100 (1.3100/0.0000)	mem 16099MB
[2025-01-17 22:35:38 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][10/312]	eta 0:03:34 lr 0.003407	time 0.4529 (0.7115)	model_time 0.4528 (0.5522)	loss 4.5395 (4.1818)	grad_norm 1.1255 (2.0634/0.6949)	mem 16099MB
[2025-01-17 22:35:42 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][20/312]	eta 0:02:53 lr 0.003413	time 0.4534 (0.5943)	model_time 0.4530 (0.5106)	loss 5.0722 (4.2680)	grad_norm 1.8466 (2.2806/0.9750)	mem 16099MB
[2025-01-17 22:35:47 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][30/312]	eta 0:02:35 lr 0.003420	time 0.4360 (0.5508)	model_time 0.4359 (0.4940)	loss 3.5125 (4.2395)	grad_norm 1.5801 (2.1123/0.8813)	mem 16099MB
[2025-01-17 22:35:51 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][40/312]	eta 0:02:23 lr 0.003426	time 0.4518 (0.5262)	model_time 0.4517 (0.4832)	loss 4.5117 (4.3147)	grad_norm 1.7044 (2.1198/0.8244)	mem 16099MB
[2025-01-17 22:35:56 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][50/312]	eta 0:02:14 lr 0.003433	time 0.4588 (0.5129)	model_time 0.4586 (0.4782)	loss 4.8216 (4.3652)	grad_norm 1.9334 (2.1604/0.8105)	mem 16099MB
[2025-01-17 22:36:00 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][60/312]	eta 0:02:07 lr 0.003439	time 0.4403 (0.5051)	model_time 0.4398 (0.4761)	loss 4.1622 (4.3634)	grad_norm 1.9118 (2.0889/0.7796)	mem 16099MB
[2025-01-17 22:36:05 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][70/312]	eta 0:02:00 lr 0.003445	time 0.4372 (0.4975)	model_time 0.4370 (0.4725)	loss 4.4056 (4.3492)	grad_norm 1.6922 (2.0576/0.7439)	mem 16099MB
[2025-01-17 22:36:09 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][80/312]	eta 0:01:54 lr 0.003452	time 0.4454 (0.4916)	model_time 0.4450 (0.4696)	loss 4.5972 (4.3350)	grad_norm 5.2362 (2.1546/0.8316)	mem 16099MB
[2025-01-17 22:36:14 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][90/312]	eta 0:01:48 lr 0.003458	time 0.4487 (0.4880)	model_time 0.4486 (0.4684)	loss 4.5887 (4.3297)	grad_norm 2.6669 (2.2152/0.9152)	mem 16099MB
[2025-01-17 22:36:19 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][100/312]	eta 0:01:42 lr 0.003465	time 0.4380 (0.4848)	model_time 0.4376 (0.4672)	loss 4.7283 (4.3564)	grad_norm 1.6854 (2.2023/0.8834)	mem 16099MB
[2025-01-17 22:36:23 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][110/312]	eta 0:01:37 lr 0.003471	time 0.4491 (0.4819)	model_time 0.4487 (0.4658)	loss 4.8507 (4.3706)	grad_norm 2.5212 (2.2546/1.0049)	mem 16099MB
[2025-01-17 22:36:28 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][120/312]	eta 0:01:32 lr 0.003477	time 0.4601 (0.4799)	model_time 0.4596 (0.4651)	loss 3.9270 (4.3499)	grad_norm 3.2133 (2.2151/0.9932)	mem 16099MB
[2025-01-17 22:36:32 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][130/312]	eta 0:01:26 lr 0.003484	time 0.4494 (0.4775)	model_time 0.4492 (0.4638)	loss 4.7295 (4.3499)	grad_norm 1.4694 (2.1968/0.9861)	mem 16099MB
[2025-01-17 22:36:37 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][140/312]	eta 0:01:22 lr 0.003490	time 0.4390 (0.4768)	model_time 0.4386 (0.4641)	loss 5.0440 (4.3542)	grad_norm 3.0574 (2.1972/0.9583)	mem 16099MB
[2025-01-17 22:36:41 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][150/312]	eta 0:01:16 lr 0.003497	time 0.4387 (0.4752)	model_time 0.4385 (0.4633)	loss 4.0688 (4.3605)	grad_norm 1.1786 (2.2194/0.9986)	mem 16099MB
[2025-01-17 22:36:46 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][160/312]	eta 0:01:12 lr 0.003503	time 0.4603 (0.4750)	model_time 0.4599 (0.4638)	loss 4.7025 (4.3745)	grad_norm 1.6041 (2.2082/0.9878)	mem 16099MB
[2025-01-17 22:36:51 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][170/312]	eta 0:01:07 lr 0.003509	time 0.4429 (0.4736)	model_time 0.4427 (0.4630)	loss 4.5397 (4.3763)	grad_norm 1.2495 (2.1716/0.9749)	mem 16099MB
[2025-01-17 22:36:55 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][180/312]	eta 0:01:02 lr 0.003516	time 0.4380 (0.4730)	model_time 0.4378 (0.4630)	loss 3.5387 (4.3610)	grad_norm 2.1997 (2.1696/0.9613)	mem 16099MB
[2025-01-17 22:37:00 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][190/312]	eta 0:00:57 lr 0.003522	time 0.5324 (0.4724)	model_time 0.5323 (0.4628)	loss 4.7492 (4.3739)	grad_norm 1.9682 (2.1764/0.9487)	mem 16099MB
[2025-01-17 22:37:04 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][200/312]	eta 0:00:52 lr 0.003529	time 0.4461 (0.4715)	model_time 0.4460 (0.4624)	loss 5.1693 (4.3734)	grad_norm 1.8683 (2.1682/0.9444)	mem 16099MB
[2025-01-17 22:37:09 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][210/312]	eta 0:00:47 lr 0.003535	time 0.4387 (0.4706)	model_time 0.4385 (0.4619)	loss 4.1078 (4.3691)	grad_norm 1.3474 (2.1866/0.9613)	mem 16099MB
[2025-01-17 22:37:13 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][220/312]	eta 0:00:43 lr 0.003541	time 0.4474 (0.4697)	model_time 0.4472 (0.4614)	loss 5.2328 (4.3806)	grad_norm 1.3286 (2.1772/0.9535)	mem 16099MB
[2025-01-17 22:37:18 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][230/312]	eta 0:00:38 lr 0.003548	time 0.4675 (0.4689)	model_time 0.4671 (0.4610)	loss 3.4431 (4.3637)	grad_norm 2.4076 (2.1704/0.9367)	mem 16099MB
[2025-01-17 22:37:23 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][240/312]	eta 0:00:33 lr 0.003554	time 0.4433 (0.4689)	model_time 0.4429 (0.4612)	loss 3.0911 (4.3604)	grad_norm 1.7021 (2.1431/0.9301)	mem 16099MB
[2025-01-17 22:37:27 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][250/312]	eta 0:00:29 lr 0.003561	time 0.4395 (0.4687)	model_time 0.4394 (0.4614)	loss 4.4211 (4.3530)	grad_norm 2.3483 (2.1841/0.9758)	mem 16099MB
[2025-01-17 22:37:32 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][260/312]	eta 0:00:24 lr 0.003567	time 0.4549 (0.4683)	model_time 0.4545 (0.4613)	loss 3.3989 (4.3539)	grad_norm 3.3740 (2.1843/0.9711)	mem 16099MB
[2025-01-17 22:37:36 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][270/312]	eta 0:00:19 lr 0.003574	time 0.4475 (0.4679)	model_time 0.4470 (0.4611)	loss 3.6108 (4.3469)	grad_norm 1.5234 (2.1823/0.9606)	mem 16099MB
[2025-01-17 22:37:41 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][280/312]	eta 0:00:14 lr 0.003580	time 0.4694 (0.4674)	model_time 0.4690 (0.4608)	loss 4.8354 (4.3487)	grad_norm 2.1045 (2.1775/0.9534)	mem 16099MB
[2025-01-17 22:37:46 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][290/312]	eta 0:00:10 lr 0.003586	time 0.4550 (0.4676)	model_time 0.4548 (0.4612)	loss 5.3422 (4.3589)	grad_norm 1.5816 (2.1698/0.9444)	mem 16099MB
[2025-01-17 22:37:50 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][300/312]	eta 0:00:05 lr 0.003593	time 0.4346 (0.4671)	model_time 0.4345 (0.4609)	loss 3.7780 (4.3527)	grad_norm 3.0754 (2.1969/0.9468)	mem 16099MB
[2025-01-17 22:37:55 internimage_t_1k_224] (main.py 510): INFO Train: [17/300][310/312]	eta 0:00:00 lr 0.003599	time 0.4379 (0.4669)	model_time 0.4378 (0.4609)	loss 4.6903 (4.3556)	grad_norm 4.3846 (2.1958/0.9552)	mem 16099MB
[2025-01-17 22:37:55 internimage_t_1k_224] (main.py 519): INFO EPOCH 17 training takes 0:02:25
[2025-01-17 22:37:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_17.pth saving......
[2025-01-17 22:37:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_17.pth saved !!!
[2025-01-17 22:38:05 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.322 (8.322)	Loss 1.5776 (1.5776)	Acc@1 65.161 (65.161)	Acc@5 87.549 (87.549)	Mem 16099MB
[2025-01-17 22:38:09 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.098)	Loss 2.2069 (1.8701)	Acc@1 53.491 (60.147)	Acc@5 77.441 (83.780)	Mem 16099MB
[2025-01-17 22:38:09 internimage_t_1k_224] (main.py 575): INFO [Epoch:17] * Acc@1 60.437 Acc@5 83.947
[2025-01-17 22:38:09 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 60.4%
[2025-01-17 22:38:09 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:38:10 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:38:10 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 60.44%
[2025-01-17 22:38:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.485 (7.485)	Loss 6.8114 (6.8114)	Acc@1 0.781 (0.781)	Acc@5 2.417 (2.417)	Mem 16099MB
[2025-01-17 22:38:21 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.007)	Loss 6.8500 (6.7996)	Acc@1 0.171 (0.302)	Acc@5 0.708 (1.316)	Mem 16099MB
[2025-01-17 22:38:21 internimage_t_1k_224] (main.py 575): INFO [Epoch:17] * Acc@1 0.440 Acc@5 1.861
[2025-01-17 22:38:21 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 22:38:21 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:38:24 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][0/312]	eta 0:15:18 lr 0.003600	time 2.9446 (2.9446)	model_time 1.2400 (1.2400)	loss 3.7687 (3.7687)	grad_norm 3.1427 (3.1427/0.0000)	mem 16099MB
[2025-01-17 22:38:29 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][10/312]	eta 0:03:27 lr 0.003607	time 0.4503 (0.6877)	model_time 0.4499 (0.5324)	loss 5.5662 (4.4794)	grad_norm 1.7804 (2.2278/0.6641)	mem 16099MB
[2025-01-17 22:38:33 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][20/312]	eta 0:02:49 lr 0.003613	time 0.5205 (0.5798)	model_time 0.5201 (0.4983)	loss 3.7339 (4.5549)	grad_norm 2.6066 (2.1797/0.6858)	mem 16099MB
[2025-01-17 22:38:38 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][30/312]	eta 0:02:32 lr 0.003620	time 0.4402 (0.5411)	model_time 0.4401 (0.4858)	loss 3.6723 (4.4451)	grad_norm 2.6157 (2.2546/0.7014)	mem 16099MB
[2025-01-17 22:38:42 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][40/312]	eta 0:02:21 lr 0.003626	time 0.4371 (0.5186)	model_time 0.4369 (0.4767)	loss 3.6555 (4.3865)	grad_norm 2.9789 (2.3530/0.8779)	mem 16099MB
[2025-01-17 22:38:47 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][50/312]	eta 0:02:13 lr 0.003632	time 0.4428 (0.5084)	model_time 0.4426 (0.4746)	loss 4.2737 (4.4023)	grad_norm 1.1236 (2.3437/1.0075)	mem 16099MB
[2025-01-17 22:38:52 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][60/312]	eta 0:02:05 lr 0.003639	time 0.4695 (0.4988)	model_time 0.4693 (0.4705)	loss 4.7648 (4.3920)	grad_norm 1.3891 (2.2764/0.9948)	mem 16099MB
[2025-01-17 22:38:56 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][70/312]	eta 0:01:59 lr 0.003645	time 0.4484 (0.4927)	model_time 0.4480 (0.4684)	loss 4.5343 (4.3934)	grad_norm 1.8075 (2.2383/0.9484)	mem 16099MB
[2025-01-17 22:39:01 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][80/312]	eta 0:01:53 lr 0.003652	time 0.4462 (0.4884)	model_time 0.4458 (0.4670)	loss 4.6033 (4.4058)	grad_norm 2.9288 (2.1783/0.9171)	mem 16099MB
[2025-01-17 22:39:05 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][90/312]	eta 0:01:47 lr 0.003658	time 0.4474 (0.4846)	model_time 0.4469 (0.4655)	loss 3.6544 (4.4059)	grad_norm 2.5690 (2.2119/0.8800)	mem 16099MB
[2025-01-17 22:39:10 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][100/312]	eta 0:01:42 lr 0.003664	time 0.4638 (0.4814)	model_time 0.4637 (0.4642)	loss 3.5085 (4.3854)	grad_norm 3.1957 (2.2805/0.9221)	mem 16099MB
[2025-01-17 22:39:14 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][110/312]	eta 0:01:36 lr 0.003671	time 0.4444 (0.4785)	model_time 0.4443 (0.4628)	loss 4.4803 (4.3766)	grad_norm 1.5375 (2.2456/0.9054)	mem 16099MB
[2025-01-17 22:39:19 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][120/312]	eta 0:01:31 lr 0.003677	time 0.4558 (0.4768)	model_time 0.4556 (0.4624)	loss 3.9095 (4.3579)	grad_norm 1.4270 (2.2352/0.8922)	mem 16099MB
[2025-01-17 22:39:24 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][130/312]	eta 0:01:26 lr 0.003684	time 0.4423 (0.4774)	model_time 0.4417 (0.4640)	loss 4.5112 (4.3583)	grad_norm 1.6645 (2.2036/0.8720)	mem 16099MB
[2025-01-17 22:39:29 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][140/312]	eta 0:01:22 lr 0.003690	time 0.4675 (0.4785)	model_time 0.4673 (0.4660)	loss 4.5294 (4.3675)	grad_norm 1.7194 (2.2446/0.9865)	mem 16099MB
[2025-01-17 22:39:33 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][150/312]	eta 0:01:17 lr 0.003696	time 0.4382 (0.4774)	model_time 0.4380 (0.4658)	loss 4.3827 (4.3811)	grad_norm 2.9669 (2.2275/0.9625)	mem 16099MB
[2025-01-17 22:39:38 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][160/312]	eta 0:01:12 lr 0.003703	time 0.5304 (0.4768)	model_time 0.5302 (0.4659)	loss 4.6496 (4.3795)	grad_norm 1.5218 (2.1922/0.9443)	mem 16099MB
[2025-01-17 22:39:42 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][170/312]	eta 0:01:07 lr 0.003709	time 0.4441 (0.4754)	model_time 0.4439 (0.4651)	loss 2.9504 (4.3660)	grad_norm 1.9928 (2.2392/1.0681)	mem 16099MB
[2025-01-17 22:39:47 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][180/312]	eta 0:01:02 lr 0.003716	time 0.4584 (0.4744)	model_time 0.4582 (0.4646)	loss 4.2641 (4.3570)	grad_norm 2.9540 (2.2252/1.0499)	mem 16099MB
[2025-01-17 22:39:51 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][190/312]	eta 0:00:57 lr 0.003722	time 0.4459 (0.4730)	model_time 0.4457 (0.4637)	loss 5.2992 (4.3682)	grad_norm 0.9964 (2.2050/1.0310)	mem 16099MB
[2025-01-17 22:39:56 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][200/312]	eta 0:00:52 lr 0.003728	time 0.4568 (0.4724)	model_time 0.4566 (0.4635)	loss 3.8027 (4.3520)	grad_norm 1.2634 (2.2246/1.0653)	mem 16099MB
[2025-01-17 22:40:01 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][210/312]	eta 0:00:48 lr 0.003735	time 0.5330 (0.4721)	model_time 0.5328 (0.4637)	loss 4.7153 (4.3716)	grad_norm 1.8170 (2.2205/1.0463)	mem 16099MB
[2025-01-17 22:40:05 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][220/312]	eta 0:00:43 lr 0.003741	time 0.4452 (0.4712)	model_time 0.4450 (0.4632)	loss 4.5480 (4.3790)	grad_norm 1.8828 (2.1897/1.0332)	mem 16099MB
[2025-01-17 22:40:10 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][230/312]	eta 0:00:38 lr 0.003748	time 0.4524 (0.4702)	model_time 0.4518 (0.4625)	loss 4.2761 (4.3727)	grad_norm 1.5176 (2.1710/1.0158)	mem 16099MB
[2025-01-17 22:40:14 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][240/312]	eta 0:00:33 lr 0.003754	time 0.4847 (0.4695)	model_time 0.4845 (0.4621)	loss 4.4257 (4.3688)	grad_norm 2.2900 (2.2256/1.1074)	mem 16099MB
[2025-01-17 22:40:19 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][250/312]	eta 0:00:29 lr 0.003760	time 0.4494 (0.4687)	model_time 0.4492 (0.4616)	loss 5.0783 (4.3841)	grad_norm 1.6709 (2.2058/1.0966)	mem 16099MB
[2025-01-17 22:40:23 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][260/312]	eta 0:00:24 lr 0.003767	time 0.4469 (0.4680)	model_time 0.4467 (0.4611)	loss 4.6651 (4.4019)	grad_norm 1.7841 (2.1928/1.0798)	mem 16099MB
[2025-01-17 22:40:28 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][270/312]	eta 0:00:19 lr 0.003773	time 0.4445 (0.4673)	model_time 0.4442 (0.4606)	loss 5.2799 (4.4043)	grad_norm 2.4589 (2.1946/1.0707)	mem 16099MB
[2025-01-17 22:40:32 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][280/312]	eta 0:00:14 lr 0.003780	time 0.4589 (0.4668)	model_time 0.4587 (0.4604)	loss 3.4415 (4.3878)	grad_norm 1.4722 (2.1937/1.0612)	mem 16099MB
[2025-01-17 22:40:37 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][290/312]	eta 0:00:10 lr 0.003786	time 0.4504 (0.4664)	model_time 0.4501 (0.4602)	loss 5.2243 (4.3880)	grad_norm 1.0209 (2.1763/1.0551)	mem 16099MB
[2025-01-17 22:40:41 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][300/312]	eta 0:00:05 lr 0.003793	time 0.4349 (0.4658)	model_time 0.4348 (0.4598)	loss 3.2591 (4.3837)	grad_norm 1.9606 (2.2092/1.1734)	mem 16099MB
[2025-01-17 22:40:46 internimage_t_1k_224] (main.py 510): INFO Train: [18/300][310/312]	eta 0:00:00 lr 0.003799	time 0.4367 (0.4654)	model_time 0.4366 (0.4596)	loss 3.3098 (4.3836)	grad_norm 1.7960 (2.1989/1.1717)	mem 16099MB
[2025-01-17 22:40:46 internimage_t_1k_224] (main.py 519): INFO EPOCH 18 training takes 0:02:25
[2025-01-17 22:40:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_18.pth saving......
[2025-01-17 22:40:48 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_18.pth saved !!!
[2025-01-17 22:40:55 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.421 (7.421)	Loss 1.5995 (1.5995)	Acc@1 65.674 (65.674)	Acc@5 86.841 (86.841)	Mem 16099MB
[2025-01-17 22:40:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.982)	Loss 2.1764 (1.8143)	Acc@1 54.590 (61.697)	Acc@5 78.442 (84.703)	Mem 16099MB
[2025-01-17 22:40:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:18] * Acc@1 61.976 Acc@5 84.929
[2025-01-17 22:40:59 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 62.0%
[2025-01-17 22:40:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:41:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:41:00 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 61.98%
[2025-01-17 22:41:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.380 (7.380)	Loss 6.8465 (6.8465)	Acc@1 0.610 (0.610)	Acc@5 2.148 (2.148)	Mem 16099MB
[2025-01-17 22:41:11 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.006)	Loss 6.8377 (6.8006)	Acc@1 0.146 (0.257)	Acc@5 0.659 (1.298)	Mem 16099MB
[2025-01-17 22:41:11 internimage_t_1k_224] (main.py 575): INFO [Epoch:18] * Acc@1 0.374 Acc@5 1.793
[2025-01-17 22:41:11 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 22:41:11 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:41:14 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][0/312]	eta 0:14:53 lr 0.003800	time 2.8643 (2.8643)	model_time 1.3589 (1.3589)	loss 4.7112 (4.7112)	grad_norm 3.1409 (3.1409/0.0000)	mem 16099MB
[2025-01-17 22:41:18 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][10/312]	eta 0:03:27 lr 0.003807	time 0.4547 (0.6886)	model_time 0.4543 (0.5514)	loss 4.7743 (4.5667)	grad_norm 1.8591 (1.8074/0.5282)	mem 16099MB
[2025-01-17 22:41:23 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][20/312]	eta 0:02:49 lr 0.003813	time 0.5292 (0.5791)	model_time 0.5289 (0.5070)	loss 4.7150 (4.4951)	grad_norm 1.3666 (2.0734/0.7904)	mem 16099MB
[2025-01-17 22:41:28 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][30/312]	eta 0:02:33 lr 0.003819	time 0.4776 (0.5428)	model_time 0.4774 (0.4938)	loss 3.7104 (4.3511)	grad_norm 2.7146 (2.0051/0.7078)	mem 16099MB
[2025-01-17 22:41:32 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][40/312]	eta 0:02:23 lr 0.003826	time 0.4460 (0.5265)	model_time 0.4458 (0.4894)	loss 5.0020 (4.3868)	grad_norm 1.1407 (2.1211/1.0209)	mem 16099MB
[2025-01-17 22:41:37 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][50/312]	eta 0:02:14 lr 0.003832	time 0.4374 (0.5139)	model_time 0.4372 (0.4840)	loss 4.9621 (4.3827)	grad_norm 2.1411 (2.0949/0.9329)	mem 16099MB
[2025-01-17 22:41:42 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][60/312]	eta 0:02:07 lr 0.003839	time 0.5277 (0.5052)	model_time 0.5275 (0.4802)	loss 4.7702 (4.4060)	grad_norm 3.5582 (2.1998/1.0369)	mem 16099MB
[2025-01-17 22:41:46 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][70/312]	eta 0:02:00 lr 0.003845	time 0.4436 (0.4992)	model_time 0.4434 (0.4776)	loss 3.5461 (4.3922)	grad_norm 1.6096 (2.2011/1.0196)	mem 16099MB
[2025-01-17 22:41:51 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][80/312]	eta 0:01:54 lr 0.003851	time 0.4437 (0.4934)	model_time 0.4433 (0.4744)	loss 4.4521 (4.3907)	grad_norm 1.1162 (2.1392/0.9851)	mem 16099MB
[2025-01-17 22:41:55 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][90/312]	eta 0:01:48 lr 0.003858	time 0.4508 (0.4887)	model_time 0.4506 (0.4717)	loss 3.9737 (4.3908)	grad_norm 1.7705 (2.1336/0.9429)	mem 16099MB
[2025-01-17 22:42:00 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][100/312]	eta 0:01:43 lr 0.003864	time 0.4697 (0.4866)	model_time 0.4695 (0.4713)	loss 3.2811 (4.3650)	grad_norm 2.6779 (2.1259/0.9198)	mem 16099MB
[2025-01-17 22:42:05 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][110/312]	eta 0:01:37 lr 0.003871	time 0.5435 (0.4842)	model_time 0.5433 (0.4702)	loss 4.3173 (4.3419)	grad_norm 1.7516 (2.0728/0.9067)	mem 16099MB
[2025-01-17 22:42:09 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][120/312]	eta 0:01:32 lr 0.003877	time 0.4399 (0.4820)	model_time 0.4397 (0.4692)	loss 3.4749 (4.3313)	grad_norm 1.8542 (2.0525/0.8829)	mem 16099MB
[2025-01-17 22:42:14 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][130/312]	eta 0:01:27 lr 0.003883	time 0.4599 (0.4798)	model_time 0.4594 (0.4679)	loss 3.7165 (4.3220)	grad_norm 1.5953 (2.0417/0.8602)	mem 16099MB
[2025-01-17 22:42:18 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][140/312]	eta 0:01:22 lr 0.003890	time 0.4401 (0.4779)	model_time 0.4399 (0.4669)	loss 4.8152 (4.3498)	grad_norm 2.5170 (2.1051/1.0139)	mem 16099MB
[2025-01-17 22:42:23 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][150/312]	eta 0:01:17 lr 0.003896	time 0.4456 (0.4769)	model_time 0.4454 (0.4665)	loss 4.9645 (4.3497)	grad_norm 2.8351 (2.0838/0.9929)	mem 16099MB
[2025-01-17 22:42:27 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][160/312]	eta 0:01:12 lr 0.003903	time 0.4472 (0.4753)	model_time 0.4470 (0.4655)	loss 3.6711 (4.3473)	grad_norm 1.4829 (2.0471/0.9748)	mem 16099MB
[2025-01-17 22:42:32 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][170/312]	eta 0:01:07 lr 0.003909	time 0.4475 (0.4744)	model_time 0.4473 (0.4652)	loss 3.5384 (4.3414)	grad_norm 2.0810 (2.0218/0.9550)	mem 16099MB
[2025-01-17 22:42:37 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][180/312]	eta 0:01:02 lr 0.003915	time 0.4451 (0.4734)	model_time 0.4449 (0.4647)	loss 3.6918 (4.3336)	grad_norm 3.8550 (2.0729/0.9834)	mem 16099MB
[2025-01-17 22:42:41 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][190/312]	eta 0:00:57 lr 0.003922	time 0.4448 (0.4729)	model_time 0.4445 (0.4646)	loss 4.9576 (4.3326)	grad_norm 2.6760 (2.0799/0.9671)	mem 16099MB
[2025-01-17 22:42:46 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][200/312]	eta 0:00:52 lr 0.003928	time 0.4435 (0.4717)	model_time 0.4433 (0.4638)	loss 4.8929 (4.3281)	grad_norm 1.2669 (2.0826/0.9590)	mem 16099MB
[2025-01-17 22:42:50 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][210/312]	eta 0:00:48 lr 0.003935	time 0.4458 (0.4711)	model_time 0.4453 (0.4636)	loss 4.1665 (4.3204)	grad_norm 1.2227 (2.0493/0.9497)	mem 16099MB
[2025-01-17 22:42:55 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][220/312]	eta 0:00:43 lr 0.003941	time 0.4480 (0.4702)	model_time 0.4478 (0.4630)	loss 5.3632 (4.3130)	grad_norm 2.3900 (2.0525/0.9368)	mem 16099MB
[2025-01-17 22:42:59 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][230/312]	eta 0:00:38 lr 0.003947	time 0.4549 (0.4695)	model_time 0.4547 (0.4626)	loss 3.1978 (4.3097)	grad_norm 1.5953 (2.0525/0.9269)	mem 16099MB
[2025-01-17 22:43:04 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][240/312]	eta 0:00:33 lr 0.003954	time 0.4287 (0.4691)	model_time 0.4286 (0.4625)	loss 3.7190 (4.3110)	grad_norm 6.2318 (2.0670/0.9612)	mem 16099MB
[2025-01-17 22:43:09 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][250/312]	eta 0:00:29 lr 0.003960	time 0.4506 (0.4685)	model_time 0.4500 (0.4621)	loss 3.9665 (4.3211)	grad_norm 1.3762 (2.0785/0.9768)	mem 16099MB
[2025-01-17 22:43:13 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][260/312]	eta 0:00:24 lr 0.003967	time 0.4407 (0.4678)	model_time 0.4406 (0.4617)	loss 5.0331 (4.3214)	grad_norm 1.3553 (2.0717/0.9648)	mem 16099MB
[2025-01-17 22:43:18 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][270/312]	eta 0:00:19 lr 0.003973	time 0.4300 (0.4675)	model_time 0.4298 (0.4616)	loss 4.5147 (4.3243)	grad_norm 1.6414 (2.0686/0.9571)	mem 16099MB
[2025-01-17 22:43:23 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][280/312]	eta 0:00:15 lr 0.003980	time 0.4481 (0.4689)	model_time 0.4480 (0.4632)	loss 3.3199 (4.3121)	grad_norm 2.4629 (2.0485/0.9500)	mem 16099MB
[2025-01-17 22:43:27 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][290/312]	eta 0:00:10 lr 0.003986	time 0.4493 (0.4684)	model_time 0.4488 (0.4629)	loss 4.3674 (4.3064)	grad_norm 1.7508 (2.0350/0.9383)	mem 16099MB
[2025-01-17 22:43:32 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][300/312]	eta 0:00:05 lr 0.003992	time 0.4333 (0.4679)	model_time 0.4332 (0.4626)	loss 4.1860 (4.3027)	grad_norm 2.4303 (2.0299/0.9283)	mem 16099MB
[2025-01-17 22:43:36 internimage_t_1k_224] (main.py 510): INFO Train: [19/300][310/312]	eta 0:00:00 lr 0.003999	time 0.4365 (0.4676)	model_time 0.4364 (0.4624)	loss 4.5838 (4.3096)	grad_norm 1.2513 (2.0686/1.0039)	mem 16099MB
[2025-01-17 22:43:37 internimage_t_1k_224] (main.py 519): INFO EPOCH 19 training takes 0:02:25
[2025-01-17 22:43:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_19.pth saving......
[2025-01-17 22:43:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_19.pth saved !!!
[2025-01-17 22:43:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.361 (8.361)	Loss 1.5098 (1.5098)	Acc@1 66.626 (66.626)	Acc@5 88.525 (88.525)	Mem 16099MB
[2025-01-17 22:43:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.110)	Loss 2.1065 (1.7594)	Acc@1 55.811 (62.314)	Acc@5 80.005 (85.596)	Mem 16099MB
[2025-01-17 22:43:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:19] * Acc@1 62.408 Acc@5 85.705
[2025-01-17 22:43:50 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 62.4%
[2025-01-17 22:43:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:43:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:43:52 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 62.41%
[2025-01-17 22:43:59 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.885 (7.885)	Loss 6.8693 (6.8693)	Acc@1 0.537 (0.537)	Acc@5 2.075 (2.075)	Mem 16099MB
[2025-01-17 22:44:03 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.038)	Loss 6.8222 (6.7997)	Acc@1 0.146 (0.237)	Acc@5 0.806 (1.354)	Mem 16099MB
[2025-01-17 22:44:03 internimage_t_1k_224] (main.py 575): INFO [Epoch:19] * Acc@1 0.346 Acc@5 1.795
[2025-01-17 22:44:03 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.3%
[2025-01-17 22:44:03 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:44:06 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][0/312]	eta 0:15:55 lr 0.003957	time 3.0620 (3.0620)	model_time 0.9690 (0.9690)	loss 4.7554 (4.7554)	grad_norm 1.9582 (1.9582/0.0000)	mem 16099MB
[2025-01-17 22:44:11 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][10/312]	eta 0:03:33 lr 0.003957	time 0.4566 (0.7083)	model_time 0.4562 (0.5177)	loss 5.2645 (4.6864)	grad_norm 2.4796 (1.9284/0.5873)	mem 16099MB
[2025-01-17 22:44:16 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][20/312]	eta 0:02:52 lr 0.003956	time 0.4496 (0.5900)	model_time 0.4494 (0.4900)	loss 5.4030 (4.5353)	grad_norm 1.8272 (1.7985/0.5329)	mem 16099MB
[2025-01-17 22:44:20 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][30/312]	eta 0:02:34 lr 0.003956	time 0.4573 (0.5461)	model_time 0.4571 (0.4783)	loss 4.4213 (4.5840)	grad_norm 1.3677 (1.8216/0.4758)	mem 16099MB
[2025-01-17 22:44:25 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][40/312]	eta 0:02:24 lr 0.003956	time 0.5655 (0.5326)	model_time 0.5653 (0.4812)	loss 5.1425 (4.5202)	grad_norm 2.6621 (1.9807/0.6849)	mem 16099MB
[2025-01-17 22:44:30 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][50/312]	eta 0:02:15 lr 0.003956	time 0.4642 (0.5186)	model_time 0.4639 (0.4772)	loss 5.1840 (4.5033)	grad_norm 1.6533 (1.9768/0.6759)	mem 16099MB
[2025-01-17 22:44:34 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][60/312]	eta 0:02:07 lr 0.003956	time 0.4548 (0.5070)	model_time 0.4546 (0.4723)	loss 4.5769 (4.5031)	grad_norm 4.7723 (2.0937/1.0621)	mem 16099MB
[2025-01-17 22:44:39 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][70/312]	eta 0:02:01 lr 0.003956	time 0.4449 (0.5007)	model_time 0.4447 (0.4708)	loss 5.4913 (4.5420)	grad_norm 1.0236 (2.0419/1.0164)	mem 16099MB
[2025-01-17 22:44:43 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][80/312]	eta 0:01:55 lr 0.003956	time 0.4346 (0.4968)	model_time 0.4344 (0.4706)	loss 3.7877 (4.5034)	grad_norm 1.5547 (1.9959/0.9856)	mem 16099MB
[2025-01-17 22:44:48 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][90/312]	eta 0:01:49 lr 0.003955	time 0.4471 (0.4914)	model_time 0.4469 (0.4681)	loss 4.2638 (4.4909)	grad_norm 1.8982 (2.0215/0.9946)	mem 16099MB
[2025-01-17 22:44:52 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][100/312]	eta 0:01:43 lr 0.003955	time 0.4455 (0.4872)	model_time 0.4452 (0.4661)	loss 3.0406 (4.4682)	grad_norm 1.7960 (2.0901/1.0505)	mem 16099MB
[2025-01-17 22:44:57 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][110/312]	eta 0:01:38 lr 0.003955	time 0.4556 (0.4865)	model_time 0.4554 (0.4673)	loss 3.1990 (4.4468)	grad_norm 1.3373 (2.0533/1.0248)	mem 16099MB
[2025-01-17 22:45:02 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][120/312]	eta 0:01:32 lr 0.003955	time 0.4781 (0.4839)	model_time 0.4779 (0.4662)	loss 5.2106 (4.4338)	grad_norm 1.8918 (2.0377/0.9916)	mem 16099MB
[2025-01-17 22:45:06 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][130/312]	eta 0:01:27 lr 0.003955	time 0.4343 (0.4815)	model_time 0.4338 (0.4651)	loss 4.7055 (4.4249)	grad_norm 1.6849 (2.0007/0.9659)	mem 16099MB
[2025-01-17 22:45:11 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][140/312]	eta 0:01:22 lr 0.003955	time 0.4487 (0.4797)	model_time 0.4485 (0.4645)	loss 5.1063 (4.4332)	grad_norm 2.4443 (1.9837/0.9491)	mem 16099MB
[2025-01-17 22:45:15 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][150/312]	eta 0:01:17 lr 0.003955	time 0.4431 (0.4787)	model_time 0.4429 (0.4645)	loss 5.3138 (4.4166)	grad_norm 1.2368 (1.9700/0.9308)	mem 16099MB
[2025-01-17 22:45:20 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][160/312]	eta 0:01:12 lr 0.003954	time 0.4514 (0.4791)	model_time 0.4512 (0.4657)	loss 2.8431 (4.4044)	grad_norm 1.4170 (1.9620/0.9084)	mem 16099MB
[2025-01-17 22:45:25 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][170/312]	eta 0:01:07 lr 0.003954	time 0.4406 (0.4778)	model_time 0.4404 (0.4652)	loss 3.6301 (4.3970)	grad_norm 1.5451 (2.0004/1.0684)	mem 16099MB
[2025-01-17 22:45:29 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][180/312]	eta 0:01:02 lr 0.003954	time 0.4437 (0.4761)	model_time 0.4435 (0.4641)	loss 4.9175 (4.4071)	grad_norm 1.3238 (1.9790/1.0460)	mem 16099MB
[2025-01-17 22:45:34 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][190/312]	eta 0:00:57 lr 0.003954	time 0.4741 (0.4750)	model_time 0.4739 (0.4636)	loss 4.0379 (4.3796)	grad_norm 3.8763 (1.9829/1.0522)	mem 16099MB
[2025-01-17 22:45:38 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][200/312]	eta 0:00:53 lr 0.003954	time 0.4453 (0.4742)	model_time 0.4452 (0.4634)	loss 4.4022 (4.3729)	grad_norm 1.8041 (2.0038/1.0414)	mem 16099MB
[2025-01-17 22:45:43 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][210/312]	eta 0:00:48 lr 0.003954	time 0.4375 (0.4734)	model_time 0.4372 (0.4631)	loss 4.9806 (4.3543)	grad_norm 1.9809 (2.0083/1.0191)	mem 16099MB
[2025-01-17 22:45:48 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][220/312]	eta 0:00:43 lr 0.003954	time 0.4459 (0.4724)	model_time 0.4457 (0.4625)	loss 3.7724 (4.3433)	grad_norm 1.2226 (1.9964/1.0003)	mem 16099MB
[2025-01-17 22:45:52 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][230/312]	eta 0:00:38 lr 0.003953	time 0.5365 (0.4720)	model_time 0.5363 (0.4626)	loss 3.4465 (4.3305)	grad_norm 0.9884 (2.0075/1.0514)	mem 16099MB
[2025-01-17 22:45:57 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][240/312]	eta 0:00:33 lr 0.003953	time 0.4414 (0.4713)	model_time 0.4412 (0.4622)	loss 4.5738 (4.3150)	grad_norm 1.6171 (1.9855/1.0364)	mem 16099MB
[2025-01-17 22:46:01 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][250/312]	eta 0:00:29 lr 0.003953	time 0.4427 (0.4709)	model_time 0.4425 (0.4622)	loss 5.0056 (4.3143)	grad_norm 1.0809 (1.9940/1.0239)	mem 16099MB
[2025-01-17 22:46:06 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][260/312]	eta 0:00:24 lr 0.003953	time 0.4457 (0.4704)	model_time 0.4455 (0.4620)	loss 4.3415 (4.3064)	grad_norm 1.6717 (2.0242/1.0823)	mem 16099MB
[2025-01-17 22:46:11 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][270/312]	eta 0:00:19 lr 0.003953	time 0.4414 (0.4703)	model_time 0.4412 (0.4622)	loss 4.5402 (4.3147)	grad_norm 0.9387 (2.0149/1.0709)	mem 16099MB
[2025-01-17 22:46:15 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][280/312]	eta 0:00:15 lr 0.003953	time 0.4449 (0.4705)	model_time 0.4447 (0.4627)	loss 3.5941 (4.3121)	grad_norm 1.2188 (1.9914/1.0636)	mem 16099MB
[2025-01-17 22:46:20 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][290/312]	eta 0:00:10 lr 0.003953	time 0.4502 (0.4698)	model_time 0.4497 (0.4622)	loss 3.2840 (4.3127)	grad_norm 1.5166 (1.9782/1.0501)	mem 16099MB
[2025-01-17 22:46:24 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][300/312]	eta 0:00:05 lr 0.003952	time 0.4351 (0.4690)	model_time 0.4350 (0.4617)	loss 5.0253 (4.3172)	grad_norm 1.7378 (1.9799/1.0447)	mem 16099MB
[2025-01-17 22:46:29 internimage_t_1k_224] (main.py 510): INFO Train: [20/300][310/312]	eta 0:00:00 lr 0.003952	time 0.4359 (0.4683)	model_time 0.4358 (0.4612)	loss 4.9293 (4.3193)	grad_norm 2.6685 (1.9975/1.0492)	mem 16099MB
[2025-01-17 22:46:29 internimage_t_1k_224] (main.py 519): INFO EPOCH 20 training takes 0:02:26
[2025-01-17 22:46:29 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_20.pth saving......
[2025-01-17 22:46:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_20.pth saved !!!
[2025-01-17 22:46:38 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.251 (7.251)	Loss 1.4761 (1.4761)	Acc@1 67.554 (67.554)	Acc@5 88.623 (88.623)	Mem 16099MB
[2025-01-17 22:46:41 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.985)	Loss 2.1072 (1.6984)	Acc@1 55.396 (63.681)	Acc@5 80.396 (86.057)	Mem 16099MB
[2025-01-17 22:46:41 internimage_t_1k_224] (main.py 575): INFO [Epoch:20] * Acc@1 63.826 Acc@5 86.220
[2025-01-17 22:46:41 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 63.8%
[2025-01-17 22:46:41 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:46:43 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:46:43 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 63.83%
[2025-01-17 22:46:50 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.367 (7.367)	Loss 6.8816 (6.8816)	Acc@1 0.488 (0.488)	Acc@5 1.807 (1.807)	Mem 16099MB
[2025-01-17 22:46:54 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.999)	Loss 6.8026 (6.7968)	Acc@1 0.171 (0.235)	Acc@5 0.830 (1.356)	Mem 16099MB
[2025-01-17 22:46:54 internimage_t_1k_224] (main.py 575): INFO [Epoch:20] * Acc@1 0.336 Acc@5 1.767
[2025-01-17 22:46:54 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.3%
[2025-01-17 22:46:54 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:46:57 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][0/312]	eta 0:15:08 lr 0.003952	time 2.9117 (2.9117)	model_time 1.2566 (1.2566)	loss 3.6027 (3.6027)	grad_norm 2.0162 (2.0162/0.0000)	mem 16099MB
[2025-01-17 22:47:01 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][10/312]	eta 0:03:32 lr 0.003952	time 0.5850 (0.7038)	model_time 0.5848 (0.5530)	loss 3.3219 (4.0557)	grad_norm 2.8134 (1.6643/0.4533)	mem 16099MB
[2025-01-17 22:47:06 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][20/312]	eta 0:02:50 lr 0.003952	time 0.4724 (0.5841)	model_time 0.4722 (0.5049)	loss 4.8796 (4.2970)	grad_norm 1.2674 (2.1332/0.9195)	mem 16099MB
[2025-01-17 22:47:11 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][30/312]	eta 0:02:34 lr 0.003952	time 0.4578 (0.5482)	model_time 0.4576 (0.4945)	loss 4.3051 (4.1871)	grad_norm 1.0996 (1.9952/0.8746)	mem 16099MB
[2025-01-17 22:47:15 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][40/312]	eta 0:02:24 lr 0.003952	time 0.4391 (0.5300)	model_time 0.4386 (0.4892)	loss 4.5159 (4.2428)	grad_norm 2.4073 (1.9756/0.8102)	mem 16099MB
[2025-01-17 22:47:20 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][50/312]	eta 0:02:14 lr 0.003952	time 0.4546 (0.5152)	model_time 0.4542 (0.4824)	loss 3.3948 (4.2328)	grad_norm 2.8706 (1.9047/0.7737)	mem 16099MB
[2025-01-17 22:47:25 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][60/312]	eta 0:02:07 lr 0.003951	time 0.5333 (0.5073)	model_time 0.5330 (0.4798)	loss 4.1047 (4.1896)	grad_norm 1.4214 (1.9998/0.9100)	mem 16099MB
[2025-01-17 22:47:29 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][70/312]	eta 0:02:00 lr 0.003951	time 0.4416 (0.4989)	model_time 0.4412 (0.4752)	loss 4.6936 (4.2430)	grad_norm 1.3964 (1.9498/0.8660)	mem 16099MB
[2025-01-17 22:47:34 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][80/312]	eta 0:01:54 lr 0.003951	time 0.4391 (0.4946)	model_time 0.4389 (0.4738)	loss 4.0022 (4.2038)	grad_norm 1.7641 (1.9468/0.8186)	mem 16099MB
[2025-01-17 22:47:38 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][90/312]	eta 0:01:48 lr 0.003951	time 0.4575 (0.4899)	model_time 0.4573 (0.4713)	loss 4.8548 (4.2165)	grad_norm 1.2132 (1.9493/0.8012)	mem 16099MB
[2025-01-17 22:47:43 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][100/312]	eta 0:01:43 lr 0.003951	time 0.4711 (0.4860)	model_time 0.4706 (0.4692)	loss 4.2069 (4.2152)	grad_norm 2.0061 (1.9563/0.7857)	mem 16099MB
[2025-01-17 22:47:47 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][110/312]	eta 0:01:37 lr 0.003951	time 0.4713 (0.4839)	model_time 0.4711 (0.4686)	loss 3.2354 (4.2001)	grad_norm 1.4151 (1.9384/0.7759)	mem 16099MB
[2025-01-17 22:47:52 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][120/312]	eta 0:01:32 lr 0.003951	time 0.4411 (0.4812)	model_time 0.4409 (0.4671)	loss 4.3435 (4.1869)	grad_norm 2.8777 (1.9989/0.9918)	mem 16099MB
[2025-01-17 22:47:57 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][130/312]	eta 0:01:27 lr 0.003950	time 0.5214 (0.4807)	model_time 0.5212 (0.4676)	loss 4.3583 (4.1713)	grad_norm 1.1093 (1.9664/0.9658)	mem 16099MB
[2025-01-17 22:48:01 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][140/312]	eta 0:01:22 lr 0.003950	time 0.4333 (0.4807)	model_time 0.4327 (0.4686)	loss 4.4467 (4.1563)	grad_norm 1.2361 (1.9986/1.0250)	mem 16099MB
[2025-01-17 22:48:06 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][150/312]	eta 0:01:17 lr 0.003950	time 0.4425 (0.4804)	model_time 0.4423 (0.4690)	loss 4.9217 (4.1802)	grad_norm 1.2920 (1.9722/1.0017)	mem 16099MB
[2025-01-17 22:48:11 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][160/312]	eta 0:01:12 lr 0.003950	time 0.4374 (0.4796)	model_time 0.4372 (0.4689)	loss 4.3891 (4.1866)	grad_norm 2.9045 (1.9506/0.9817)	mem 16099MB
[2025-01-17 22:48:16 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][170/312]	eta 0:01:07 lr 0.003950	time 0.4631 (0.4785)	model_time 0.4630 (0.4684)	loss 4.7490 (4.2078)	grad_norm 1.4690 (1.9474/0.9651)	mem 16099MB
[2025-01-17 22:48:20 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][180/312]	eta 0:01:03 lr 0.003950	time 0.4427 (0.4778)	model_time 0.4425 (0.4682)	loss 3.7985 (4.2066)	grad_norm 1.1803 (1.9711/0.9775)	mem 16099MB
[2025-01-17 22:48:25 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][190/312]	eta 0:00:58 lr 0.003950	time 0.4369 (0.4767)	model_time 0.4367 (0.4676)	loss 3.6039 (4.2008)	grad_norm 1.4708 (1.9654/0.9682)	mem 16099MB
[2025-01-17 22:48:29 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][200/312]	eta 0:00:53 lr 0.003949	time 0.4641 (0.4757)	model_time 0.4636 (0.4671)	loss 4.6162 (4.1820)	grad_norm 2.7666 (1.9476/0.9526)	mem 16099MB
[2025-01-17 22:48:34 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][210/312]	eta 0:00:48 lr 0.003949	time 0.4435 (0.4748)	model_time 0.4433 (0.4666)	loss 5.2368 (4.1826)	grad_norm 1.9950 (1.9471/0.9372)	mem 16099MB
[2025-01-17 22:48:38 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][220/312]	eta 0:00:43 lr 0.003949	time 0.4382 (0.4743)	model_time 0.4377 (0.4664)	loss 4.0679 (4.1681)	grad_norm 1.3683 (1.9468/0.9330)	mem 16099MB
[2025-01-17 22:48:43 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][230/312]	eta 0:00:38 lr 0.003949	time 0.4465 (0.4734)	model_time 0.4460 (0.4658)	loss 3.2330 (4.1752)	grad_norm 1.1104 (1.9449/0.9348)	mem 16099MB
[2025-01-17 22:48:48 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][240/312]	eta 0:00:34 lr 0.003949	time 0.4509 (0.4726)	model_time 0.4508 (0.4653)	loss 4.7588 (4.1920)	grad_norm 0.9567 (1.9308/0.9315)	mem 16099MB
[2025-01-17 22:48:52 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][250/312]	eta 0:00:29 lr 0.003949	time 0.4546 (0.4718)	model_time 0.4544 (0.4648)	loss 4.5844 (4.1915)	grad_norm 1.5412 (1.9567/0.9467)	mem 16099MB
[2025-01-17 22:48:57 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][260/312]	eta 0:00:24 lr 0.003948	time 0.4479 (0.4712)	model_time 0.4474 (0.4645)	loss 3.0989 (4.1856)	grad_norm 3.8485 (1.9594/0.9428)	mem 16099MB
[2025-01-17 22:49:01 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][270/312]	eta 0:00:19 lr 0.003948	time 0.4486 (0.4707)	model_time 0.4483 (0.4642)	loss 3.3391 (4.1854)	grad_norm 1.3865 (1.9492/0.9307)	mem 16099MB
[2025-01-17 22:49:06 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][280/312]	eta 0:00:15 lr 0.003948	time 0.4625 (0.4704)	model_time 0.4623 (0.4641)	loss 3.1009 (4.1834)	grad_norm 1.4367 (1.9455/0.9188)	mem 16099MB
[2025-01-17 22:49:10 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][290/312]	eta 0:00:10 lr 0.003948	time 0.4392 (0.4696)	model_time 0.4390 (0.4635)	loss 5.1478 (4.1852)	grad_norm 2.8332 (1.9447/0.9148)	mem 16099MB
[2025-01-17 22:49:15 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][300/312]	eta 0:00:05 lr 0.003948	time 0.4354 (0.4694)	model_time 0.4353 (0.4635)	loss 3.9064 (4.1774)	grad_norm 1.5449 (1.9465/0.9177)	mem 16099MB
[2025-01-17 22:49:19 internimage_t_1k_224] (main.py 510): INFO Train: [21/300][310/312]	eta 0:00:00 lr 0.003948	time 0.4367 (0.4684)	model_time 0.4366 (0.4627)	loss 4.2822 (4.1788)	grad_norm 1.0543 (1.9528/0.9178)	mem 16099MB
[2025-01-17 22:49:20 internimage_t_1k_224] (main.py 519): INFO EPOCH 21 training takes 0:02:26
[2025-01-17 22:49:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_21.pth saving......
[2025-01-17 22:49:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_21.pth saved !!!
[2025-01-17 22:49:29 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.582 (7.582)	Loss 1.4432 (1.4432)	Acc@1 69.019 (69.019)	Acc@5 90.112 (90.112)	Mem 16099MB
[2025-01-17 22:49:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.028)	Loss 2.0390 (1.7066)	Acc@1 57.349 (63.761)	Acc@5 80.420 (86.361)	Mem 16099MB
[2025-01-17 22:49:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:21] * Acc@1 64.067 Acc@5 86.546
[2025-01-17 22:49:32 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 64.1%
[2025-01-17 22:49:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:49:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:49:34 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 64.07%
[2025-01-17 22:49:41 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.469 (7.469)	Loss 6.8843 (6.8843)	Acc@1 0.366 (0.366)	Acc@5 1.807 (1.807)	Mem 16099MB
[2025-01-17 22:49:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.008)	Loss 6.7788 (6.7921)	Acc@1 0.195 (0.229)	Acc@5 0.879 (1.418)	Mem 16099MB
[2025-01-17 22:49:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:21] * Acc@1 0.336 Acc@5 1.821
[2025-01-17 22:49:45 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.3%
[2025-01-17 22:49:45 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:49:48 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][0/312]	eta 0:15:50 lr 0.003948	time 3.0461 (3.0461)	model_time 1.5999 (1.5999)	loss 4.3007 (4.3007)	grad_norm 2.3190 (2.3190/0.0000)	mem 16099MB
[2025-01-17 22:49:53 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][10/312]	eta 0:03:34 lr 0.003948	time 0.5441 (0.7105)	model_time 0.5439 (0.5787)	loss 4.5719 (4.3518)	grad_norm 1.6048 (2.1360/0.8480)	mem 16099MB
[2025-01-17 22:49:57 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][20/312]	eta 0:02:51 lr 0.003947	time 0.4883 (0.5881)	model_time 0.4881 (0.5189)	loss 3.1490 (4.1810)	grad_norm 2.4723 (2.0099/0.7368)	mem 16099MB
[2025-01-17 22:50:02 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][30/312]	eta 0:02:33 lr 0.003947	time 0.4491 (0.5434)	model_time 0.4488 (0.4964)	loss 4.5135 (4.1801)	grad_norm 3.3568 (2.0244/0.7376)	mem 16099MB
[2025-01-17 22:50:06 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][40/312]	eta 0:02:21 lr 0.003947	time 0.4461 (0.5209)	model_time 0.4456 (0.4853)	loss 3.2853 (4.1387)	grad_norm 1.7429 (2.0788/0.8321)	mem 16099MB
[2025-01-17 22:50:11 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][50/312]	eta 0:02:13 lr 0.003947	time 0.4617 (0.5099)	model_time 0.4616 (0.4812)	loss 4.8900 (4.1536)	grad_norm 1.2696 (1.9875/0.8036)	mem 16099MB
[2025-01-17 22:50:16 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][60/312]	eta 0:02:07 lr 0.003947	time 0.4637 (0.5047)	model_time 0.4635 (0.4806)	loss 3.4750 (4.1297)	grad_norm 1.6866 (1.9279/0.7668)	mem 16099MB
[2025-01-17 22:50:20 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][70/312]	eta 0:02:00 lr 0.003947	time 0.4471 (0.4972)	model_time 0.4470 (0.4765)	loss 3.9722 (4.1645)	grad_norm 1.9646 (1.9204/0.8424)	mem 16099MB
[2025-01-17 22:50:25 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][80/312]	eta 0:01:54 lr 0.003946	time 0.4668 (0.4925)	model_time 0.4666 (0.4743)	loss 3.2094 (4.1329)	grad_norm 1.0456 (1.9113/0.8176)	mem 16099MB
[2025-01-17 22:50:29 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][90/312]	eta 0:01:48 lr 0.003946	time 0.4465 (0.4882)	model_time 0.4463 (0.4719)	loss 3.2604 (4.1114)	grad_norm 1.3133 (1.9216/0.8487)	mem 16099MB
[2025-01-17 22:50:34 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][100/312]	eta 0:01:43 lr 0.003946	time 0.4474 (0.4861)	model_time 0.4472 (0.4714)	loss 4.6136 (4.1275)	grad_norm 2.4957 (1.9233/0.8380)	mem 16099MB
[2025-01-17 22:50:39 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][110/312]	eta 0:01:37 lr 0.003946	time 0.4642 (0.4850)	model_time 0.4641 (0.4717)	loss 3.2207 (4.1288)	grad_norm 2.1030 (1.9101/0.8236)	mem 16099MB
[2025-01-17 22:50:43 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][120/312]	eta 0:01:32 lr 0.003946	time 0.4537 (0.4830)	model_time 0.4535 (0.4707)	loss 4.7770 (4.1376)	grad_norm 6.9194 (1.9370/0.9267)	mem 16099MB
[2025-01-17 22:50:48 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][130/312]	eta 0:01:27 lr 0.003946	time 0.4552 (0.4817)	model_time 0.4547 (0.4703)	loss 3.9147 (4.1276)	grad_norm 2.1411 (1.9431/0.9145)	mem 16099MB
[2025-01-17 22:50:53 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][140/312]	eta 0:01:22 lr 0.003946	time 0.4482 (0.4805)	model_time 0.4480 (0.4699)	loss 3.9111 (4.0959)	grad_norm 1.1525 (1.9082/0.8972)	mem 16099MB
[2025-01-17 22:50:57 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][150/312]	eta 0:01:17 lr 0.003945	time 0.4559 (0.4791)	model_time 0.4557 (0.4692)	loss 4.3800 (4.0947)	grad_norm 0.9454 (1.9291/0.9611)	mem 16099MB
[2025-01-17 22:51:02 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][160/312]	eta 0:01:12 lr 0.003945	time 0.4346 (0.4778)	model_time 0.4343 (0.4685)	loss 2.9920 (4.0967)	grad_norm 1.7540 (1.9147/0.9500)	mem 16099MB
[2025-01-17 22:51:07 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][170/312]	eta 0:01:07 lr 0.003945	time 0.5275 (0.4771)	model_time 0.5273 (0.4683)	loss 4.6330 (4.1053)	grad_norm 2.1616 (1.9498/0.9696)	mem 16099MB
[2025-01-17 22:51:11 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][180/312]	eta 0:01:02 lr 0.003945	time 0.4467 (0.4762)	model_time 0.4465 (0.4678)	loss 4.5908 (4.0982)	grad_norm 2.0284 (1.9397/0.9472)	mem 16099MB
[2025-01-17 22:51:16 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][190/312]	eta 0:00:57 lr 0.003945	time 0.4508 (0.4749)	model_time 0.4504 (0.4670)	loss 3.3511 (4.0949)	grad_norm 2.2351 (1.9331/0.9293)	mem 16099MB
[2025-01-17 22:51:20 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][200/312]	eta 0:00:53 lr 0.003945	time 0.4559 (0.4737)	model_time 0.4557 (0.4662)	loss 4.0031 (4.1080)	grad_norm 1.6252 (1.9444/0.9485)	mem 16099MB
[2025-01-17 22:51:25 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][210/312]	eta 0:00:48 lr 0.003944	time 0.4463 (0.4727)	model_time 0.4457 (0.4655)	loss 3.4905 (4.1020)	grad_norm 1.2101 (1.9404/0.9358)	mem 16099MB
[2025-01-17 22:51:29 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][220/312]	eta 0:00:43 lr 0.003944	time 0.4551 (0.4717)	model_time 0.4549 (0.4648)	loss 4.2176 (4.0929)	grad_norm 3.2659 (1.9208/0.9285)	mem 16099MB
[2025-01-17 22:51:34 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][230/312]	eta 0:00:38 lr 0.003944	time 0.4542 (0.4708)	model_time 0.4540 (0.4642)	loss 3.2593 (4.1024)	grad_norm 2.7293 (1.9302/0.9225)	mem 16099MB
[2025-01-17 22:51:38 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][240/312]	eta 0:00:33 lr 0.003944	time 0.4495 (0.4706)	model_time 0.4485 (0.4642)	loss 4.0183 (4.1061)	grad_norm 1.7621 (1.9129/0.9093)	mem 16099MB
[2025-01-17 22:51:43 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][250/312]	eta 0:00:29 lr 0.003944	time 0.4377 (0.4698)	model_time 0.4375 (0.4636)	loss 4.5260 (4.1032)	grad_norm 0.9798 (1.8922/0.8986)	mem 16099MB
[2025-01-17 22:51:47 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][260/312]	eta 0:00:24 lr 0.003944	time 0.4482 (0.4693)	model_time 0.4478 (0.4634)	loss 4.3659 (4.1024)	grad_norm 2.6439 (1.8925/0.8973)	mem 16099MB
[2025-01-17 22:51:52 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][270/312]	eta 0:00:19 lr 0.003944	time 0.4428 (0.4690)	model_time 0.4426 (0.4633)	loss 3.1633 (4.1082)	grad_norm 2.1406 (1.9104/0.9258)	mem 16099MB
[2025-01-17 22:51:57 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][280/312]	eta 0:00:14 lr 0.003943	time 0.4568 (0.4687)	model_time 0.4566 (0.4632)	loss 4.5248 (4.1075)	grad_norm 1.6599 (1.9034/0.9208)	mem 16099MB
[2025-01-17 22:52:01 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][290/312]	eta 0:00:10 lr 0.003943	time 0.5503 (0.4688)	model_time 0.5498 (0.4635)	loss 4.8054 (4.1270)	grad_norm 1.3512 (1.9003/0.9079)	mem 16099MB
[2025-01-17 22:52:06 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][300/312]	eta 0:00:05 lr 0.003943	time 0.4366 (0.4684)	model_time 0.4365 (0.4632)	loss 4.2305 (4.1387)	grad_norm 0.8520 (1.8811/0.9036)	mem 16099MB
[2025-01-17 22:52:10 internimage_t_1k_224] (main.py 510): INFO Train: [22/300][310/312]	eta 0:00:00 lr 0.003943	time 0.5267 (0.4678)	model_time 0.5266 (0.4628)	loss 4.6004 (4.1450)	grad_norm 3.7824 (1.8779/0.9066)	mem 16099MB
[2025-01-17 22:52:11 internimage_t_1k_224] (main.py 519): INFO EPOCH 22 training takes 0:02:25
[2025-01-17 22:52:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_22.pth saving......
[2025-01-17 22:52:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_22.pth saved !!!
[2025-01-17 22:52:20 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.577 (7.577)	Loss 1.3789 (1.3789)	Acc@1 70.239 (70.239)	Acc@5 89.746 (89.746)	Mem 16099MB
[2025-01-17 22:52:23 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.029)	Loss 1.9538 (1.6338)	Acc@1 58.472 (64.846)	Acc@5 82.349 (87.023)	Mem 16099MB
[2025-01-17 22:52:23 internimage_t_1k_224] (main.py 575): INFO [Epoch:22] * Acc@1 65.023 Acc@5 87.152
[2025-01-17 22:52:23 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 65.0%
[2025-01-17 22:52:23 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:52:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:52:25 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 65.02%
[2025-01-17 22:52:32 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.582 (7.582)	Loss 6.8711 (6.8711)	Acc@1 0.415 (0.415)	Acc@5 1.831 (1.831)	Mem 16099MB
[2025-01-17 22:52:36 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.024)	Loss 6.7558 (6.7818)	Acc@1 0.171 (0.237)	Acc@5 1.025 (1.529)	Mem 16099MB
[2025-01-17 22:52:36 internimage_t_1k_224] (main.py 575): INFO [Epoch:22] * Acc@1 0.342 Acc@5 1.917
[2025-01-17 22:52:36 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.3%
[2025-01-17 22:52:36 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:52:39 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][0/312]	eta 0:14:32 lr 0.003943	time 2.7980 (2.7980)	model_time 1.2526 (1.2526)	loss 4.0311 (4.0311)	grad_norm 2.3634 (2.3634/0.0000)	mem 16099MB
[2025-01-17 22:52:44 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][10/312]	eta 0:03:27 lr 0.003943	time 0.4322 (0.6871)	model_time 0.4320 (0.5462)	loss 3.1433 (3.7376)	grad_norm 1.2126 (1.6821/0.4846)	mem 16099MB
[2025-01-17 22:52:48 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][20/312]	eta 0:02:49 lr 0.003943	time 0.4502 (0.5818)	model_time 0.4497 (0.5078)	loss 4.9584 (4.0521)	grad_norm 3.0853 (1.8733/0.5948)	mem 16099MB
[2025-01-17 22:52:53 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][30/312]	eta 0:02:34 lr 0.003942	time 0.5261 (0.5480)	model_time 0.5259 (0.4977)	loss 3.5555 (4.0348)	grad_norm 1.2432 (1.7745/0.5650)	mem 16099MB
[2025-01-17 22:52:58 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][40/312]	eta 0:02:23 lr 0.003942	time 0.4559 (0.5270)	model_time 0.4554 (0.4889)	loss 4.8731 (4.0938)	grad_norm 3.0900 (1.8119/0.5850)	mem 16099MB
[2025-01-17 22:53:03 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][50/312]	eta 0:02:17 lr 0.003942	time 0.5116 (0.5231)	model_time 0.5114 (0.4924)	loss 3.7009 (4.1145)	grad_norm 0.9091 (1.8605/0.6418)	mem 16099MB
[2025-01-17 22:53:07 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][60/312]	eta 0:02:08 lr 0.003942	time 0.4459 (0.5113)	model_time 0.4455 (0.4856)	loss 4.2284 (4.1412)	grad_norm 3.5482 (1.9762/0.9657)	mem 16099MB
[2025-01-17 22:53:12 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][70/312]	eta 0:02:01 lr 0.003942	time 0.4445 (0.5029)	model_time 0.4443 (0.4807)	loss 3.2667 (4.1355)	grad_norm 0.9369 (1.8885/0.9542)	mem 16099MB
[2025-01-17 22:53:16 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][80/312]	eta 0:01:55 lr 0.003942	time 0.4486 (0.4968)	model_time 0.4485 (0.4773)	loss 4.7564 (4.1495)	grad_norm 1.5396 (1.8615/0.9043)	mem 16099MB
[2025-01-17 22:53:21 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][90/312]	eta 0:01:49 lr 0.003941	time 0.4489 (0.4929)	model_time 0.4487 (0.4755)	loss 4.4086 (4.1902)	grad_norm 1.2469 (1.8903/0.8751)	mem 16099MB
[2025-01-17 22:53:25 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][100/312]	eta 0:01:43 lr 0.003941	time 0.4459 (0.4887)	model_time 0.4454 (0.4730)	loss 4.9070 (4.2086)	grad_norm 1.9780 (1.9020/0.8815)	mem 16099MB
[2025-01-17 22:53:30 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][110/312]	eta 0:01:38 lr 0.003941	time 0.4588 (0.4857)	model_time 0.4583 (0.4714)	loss 4.5290 (4.1653)	grad_norm 1.1190 (1.8773/0.8619)	mem 16099MB
[2025-01-17 22:53:34 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][120/312]	eta 0:01:32 lr 0.003941	time 0.4525 (0.4824)	model_time 0.4520 (0.4693)	loss 4.2670 (4.1641)	grad_norm 1.3579 (1.8927/0.8630)	mem 16099MB
[2025-01-17 22:53:39 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][130/312]	eta 0:01:27 lr 0.003941	time 0.4343 (0.4800)	model_time 0.4340 (0.4678)	loss 3.9658 (4.1772)	grad_norm 1.7187 (1.8683/0.8432)	mem 16099MB
[2025-01-17 22:53:43 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][140/312]	eta 0:01:22 lr 0.003941	time 0.4496 (0.4782)	model_time 0.4494 (0.4668)	loss 3.8582 (4.1877)	grad_norm 1.4111 (1.8268/0.8333)	mem 16099MB
[2025-01-17 22:53:48 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][150/312]	eta 0:01:17 lr 0.003940	time 0.4449 (0.4764)	model_time 0.4447 (0.4658)	loss 3.9011 (4.1772)	grad_norm 1.9519 (1.7949/0.8175)	mem 16099MB
[2025-01-17 22:53:53 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][160/312]	eta 0:01:12 lr 0.003940	time 0.4516 (0.4764)	model_time 0.4511 (0.4664)	loss 4.2654 (4.1660)	grad_norm 1.5280 (1.7927/0.8001)	mem 16099MB
[2025-01-17 22:53:57 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][170/312]	eta 0:01:07 lr 0.003940	time 0.4532 (0.4755)	model_time 0.4530 (0.4661)	loss 5.1567 (4.1883)	grad_norm 3.3892 (1.7986/0.7981)	mem 16099MB
[2025-01-17 22:54:02 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][180/312]	eta 0:01:02 lr 0.003940	time 0.4533 (0.4741)	model_time 0.4529 (0.4652)	loss 5.0257 (4.1822)	grad_norm 1.2505 (1.7971/0.7914)	mem 16099MB
[2025-01-17 22:54:06 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][190/312]	eta 0:00:57 lr 0.003940	time 0.4457 (0.4735)	model_time 0.4453 (0.4650)	loss 3.8665 (4.1795)	grad_norm 1.3693 (1.7997/0.7744)	mem 16099MB
[2025-01-17 22:54:11 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][200/312]	eta 0:00:52 lr 0.003940	time 0.4443 (0.4722)	model_time 0.4439 (0.4641)	loss 5.0392 (4.1835)	grad_norm 1.7359 (1.7887/0.7609)	mem 16099MB
[2025-01-17 22:54:16 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][210/312]	eta 0:00:48 lr 0.003939	time 0.4696 (0.4719)	model_time 0.4694 (0.4642)	loss 5.0030 (4.1830)	grad_norm 2.2790 (1.7998/0.7645)	mem 16099MB
[2025-01-17 22:54:20 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][220/312]	eta 0:00:43 lr 0.003939	time 0.4561 (0.4729)	model_time 0.4556 (0.4655)	loss 4.0481 (4.1760)	grad_norm 1.6315 (1.8247/0.7803)	mem 16099MB
[2025-01-17 22:54:25 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][230/312]	eta 0:00:38 lr 0.003939	time 0.4400 (0.4719)	model_time 0.4398 (0.4648)	loss 4.1187 (4.1593)	grad_norm 2.0144 (1.8210/0.7710)	mem 16099MB
[2025-01-17 22:54:30 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][240/312]	eta 0:00:33 lr 0.003939	time 0.5287 (0.4714)	model_time 0.5285 (0.4646)	loss 4.2741 (4.1591)	grad_norm 1.4833 (1.8173/0.7640)	mem 16099MB
[2025-01-17 22:54:34 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][250/312]	eta 0:00:29 lr 0.003939	time 0.4556 (0.4705)	model_time 0.4554 (0.4639)	loss 4.2330 (4.1622)	grad_norm 2.2195 (1.8085/0.7607)	mem 16099MB
[2025-01-17 22:54:39 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][260/312]	eta 0:00:24 lr 0.003939	time 0.4577 (0.4705)	model_time 0.4576 (0.4642)	loss 3.4705 (4.1516)	grad_norm 1.4999 (1.8208/0.7751)	mem 16099MB
[2025-01-17 22:54:44 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][270/312]	eta 0:00:19 lr 0.003938	time 0.5122 (0.4710)	model_time 0.5120 (0.4649)	loss 5.1852 (4.1475)	grad_norm 1.1122 (1.8201/0.7969)	mem 16099MB
[2025-01-17 22:54:48 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][280/312]	eta 0:00:15 lr 0.003938	time 0.4560 (0.4705)	model_time 0.4555 (0.4646)	loss 2.9801 (4.1437)	grad_norm 4.8166 (1.8182/0.8119)	mem 16099MB
[2025-01-17 22:54:53 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][290/312]	eta 0:00:10 lr 0.003938	time 0.4659 (0.4706)	model_time 0.4657 (0.4649)	loss 5.2397 (4.1536)	grad_norm 1.6587 (1.8330/0.8232)	mem 16099MB
[2025-01-17 22:54:57 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][300/312]	eta 0:00:05 lr 0.003938	time 0.4373 (0.4698)	model_time 0.4372 (0.4643)	loss 4.2490 (4.1540)	grad_norm 1.6511 (1.8236/0.8176)	mem 16099MB
[2025-01-17 22:55:02 internimage_t_1k_224] (main.py 510): INFO Train: [23/300][310/312]	eta 0:00:00 lr 0.003938	time 0.4373 (0.4689)	model_time 0.4372 (0.4635)	loss 3.5448 (4.1535)	grad_norm 1.3057 (1.8361/0.8252)	mem 16099MB
[2025-01-17 22:55:02 internimage_t_1k_224] (main.py 519): INFO EPOCH 23 training takes 0:02:26
[2025-01-17 22:55:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_23.pth saving......
[2025-01-17 22:55:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_23.pth saved !!!
[2025-01-17 22:55:11 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.385 (7.385)	Loss 1.3433 (1.3433)	Acc@1 69.434 (69.434)	Acc@5 90.308 (90.308)	Mem 16099MB
[2025-01-17 22:55:15 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.998)	Loss 1.9331 (1.5935)	Acc@1 58.594 (65.612)	Acc@5 82.520 (87.456)	Mem 16099MB
[2025-01-17 22:55:15 internimage_t_1k_224] (main.py 575): INFO [Epoch:23] * Acc@1 65.679 Acc@5 87.590
[2025-01-17 22:55:15 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 65.7%
[2025-01-17 22:55:15 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:55:16 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:55:16 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 65.68%
[2025-01-17 22:55:23 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.408 (7.408)	Loss 6.8431 (6.8431)	Acc@1 0.439 (0.439)	Acc@5 1.953 (1.953)	Mem 16099MB
[2025-01-17 22:55:27 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.008)	Loss 6.7310 (6.7648)	Acc@1 0.146 (0.257)	Acc@5 1.245 (1.614)	Mem 16099MB
[2025-01-17 22:55:27 internimage_t_1k_224] (main.py 575): INFO [Epoch:23] * Acc@1 0.374 Acc@5 2.001
[2025-01-17 22:55:27 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 22:55:27 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:55:30 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][0/312]	eta 0:14:54 lr 0.003938	time 2.8659 (2.8659)	model_time 1.3794 (1.3794)	loss 4.1889 (4.1889)	grad_norm 1.1647 (1.1647/0.0000)	mem 16099MB
[2025-01-17 22:55:35 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][10/312]	eta 0:03:29 lr 0.003938	time 0.4532 (0.6935)	model_time 0.4530 (0.5579)	loss 4.1479 (4.0676)	grad_norm 1.1675 (1.2814/0.2882)	mem 16099MB
[2025-01-17 22:55:40 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][20/312]	eta 0:02:51 lr 0.003937	time 0.5463 (0.5866)	model_time 0.5461 (0.5155)	loss 4.1688 (4.0123)	grad_norm 1.3597 (1.2759/0.2497)	mem 16099MB
[2025-01-17 22:55:44 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][30/312]	eta 0:02:35 lr 0.003937	time 0.4446 (0.5524)	model_time 0.4442 (0.5041)	loss 4.6047 (4.0121)	grad_norm 1.1231 (1.6861/0.9584)	mem 16099MB
[2025-01-17 22:55:49 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][40/312]	eta 0:02:23 lr 0.003937	time 0.4353 (0.5279)	model_time 0.4352 (0.4912)	loss 4.3279 (4.0232)	grad_norm 3.3327 (1.7847/0.9181)	mem 16099MB
[2025-01-17 22:55:54 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][50/312]	eta 0:02:14 lr 0.003937	time 0.5217 (0.5149)	model_time 0.5212 (0.4853)	loss 3.7154 (4.0025)	grad_norm 1.1994 (1.7464/0.8637)	mem 16099MB
[2025-01-17 22:55:58 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][60/312]	eta 0:02:07 lr 0.003937	time 0.4533 (0.5059)	model_time 0.4528 (0.4811)	loss 4.7673 (4.0578)	grad_norm 0.9327 (1.6386/0.8307)	mem 16099MB
[2025-01-17 22:56:03 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][70/312]	eta 0:02:01 lr 0.003937	time 0.4307 (0.5002)	model_time 0.4306 (0.4788)	loss 4.1982 (4.0143)	grad_norm 4.9706 (1.6756/0.8885)	mem 16099MB
[2025-01-17 22:56:07 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][80/312]	eta 0:01:54 lr 0.003936	time 0.4547 (0.4940)	model_time 0.4542 (0.4752)	loss 4.4081 (3.9836)	grad_norm 1.3587 (1.7118/0.8771)	mem 16099MB
[2025-01-17 22:56:12 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][90/312]	eta 0:01:48 lr 0.003936	time 0.4421 (0.4892)	model_time 0.4419 (0.4725)	loss 4.3741 (3.9994)	grad_norm 0.9554 (1.6556/0.8487)	mem 16099MB
[2025-01-17 22:56:16 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][100/312]	eta 0:01:42 lr 0.003936	time 0.4412 (0.4856)	model_time 0.4410 (0.4705)	loss 2.9169 (4.0156)	grad_norm 1.3161 (1.6518/0.8129)	mem 16099MB
[2025-01-17 22:56:21 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][110/312]	eta 0:01:37 lr 0.003936	time 0.4497 (0.4832)	model_time 0.4492 (0.4694)	loss 4.3732 (4.0163)	grad_norm 0.9232 (1.6462/0.7907)	mem 16099MB
[2025-01-17 22:56:25 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][120/312]	eta 0:01:32 lr 0.003936	time 0.4623 (0.4805)	model_time 0.4621 (0.4679)	loss 3.6254 (4.0301)	grad_norm 1.8252 (1.7098/0.8090)	mem 16099MB
[2025-01-17 22:56:30 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][130/312]	eta 0:01:27 lr 0.003936	time 0.4536 (0.4798)	model_time 0.4534 (0.4681)	loss 4.8365 (4.0317)	grad_norm 1.3521 (1.7137/0.7922)	mem 16099MB
[2025-01-17 22:56:35 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][140/312]	eta 0:01:22 lr 0.003935	time 0.5490 (0.4784)	model_time 0.5488 (0.4675)	loss 4.2526 (4.0428)	grad_norm 1.1363 (1.6891/0.7764)	mem 16099MB
[2025-01-17 22:56:39 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][150/312]	eta 0:01:17 lr 0.003935	time 0.4628 (0.4782)	model_time 0.4623 (0.4680)	loss 4.3920 (4.0458)	grad_norm 4.2391 (1.6857/0.7875)	mem 16099MB
[2025-01-17 22:56:45 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][160/312]	eta 0:01:13 lr 0.003935	time 0.4402 (0.4803)	model_time 0.4401 (0.4707)	loss 4.0546 (4.0524)	grad_norm 2.2767 (1.7240/0.8018)	mem 16099MB
[2025-01-17 22:56:49 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][170/312]	eta 0:01:07 lr 0.003935	time 0.4510 (0.4786)	model_time 0.4506 (0.4695)	loss 4.3828 (4.0566)	grad_norm 1.7317 (1.7396/0.8000)	mem 16099MB
[2025-01-17 22:56:54 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][180/312]	eta 0:01:03 lr 0.003935	time 0.4416 (0.4776)	model_time 0.4411 (0.4690)	loss 4.5067 (4.0768)	grad_norm 1.4525 (1.7125/0.7865)	mem 16099MB
[2025-01-17 22:56:58 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][190/312]	eta 0:00:58 lr 0.003935	time 0.4503 (0.4769)	model_time 0.4498 (0.4688)	loss 4.4851 (4.0643)	grad_norm 1.9911 (1.7086/0.7735)	mem 16099MB
[2025-01-17 22:57:03 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][200/312]	eta 0:00:53 lr 0.003934	time 0.4501 (0.4757)	model_time 0.4500 (0.4679)	loss 4.8150 (4.0698)	grad_norm 2.1836 (1.6999/0.7613)	mem 16099MB
[2025-01-17 22:57:08 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][210/312]	eta 0:00:48 lr 0.003934	time 0.4378 (0.4752)	model_time 0.4372 (0.4678)	loss 4.0616 (4.0812)	grad_norm 1.8165 (1.6921/0.7464)	mem 16099MB
[2025-01-17 22:57:12 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][220/312]	eta 0:00:43 lr 0.003934	time 0.4475 (0.4743)	model_time 0.4470 (0.4671)	loss 4.2168 (4.0979)	grad_norm 3.6347 (1.7147/0.7596)	mem 16099MB
[2025-01-17 22:57:17 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][230/312]	eta 0:00:38 lr 0.003934	time 0.4500 (0.4736)	model_time 0.4498 (0.4668)	loss 2.9304 (4.0790)	grad_norm 2.8242 (1.7474/0.7879)	mem 16099MB
[2025-01-17 22:57:21 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][240/312]	eta 0:00:34 lr 0.003934	time 0.4473 (0.4729)	model_time 0.4471 (0.4663)	loss 4.2731 (4.0689)	grad_norm 7.1201 (1.7687/0.8639)	mem 16099MB
[2025-01-17 22:57:26 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][250/312]	eta 0:00:29 lr 0.003934	time 0.4324 (0.4729)	model_time 0.4320 (0.4665)	loss 4.4581 (4.0712)	grad_norm 1.6784 (1.7660/0.8555)	mem 16099MB
[2025-01-17 22:57:31 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][260/312]	eta 0:00:24 lr 0.003933	time 0.4472 (0.4726)	model_time 0.4467 (0.4665)	loss 3.7367 (4.0684)	grad_norm 1.5827 (1.7480/0.8462)	mem 16099MB
[2025-01-17 22:57:35 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][270/312]	eta 0:00:19 lr 0.003933	time 0.4420 (0.4722)	model_time 0.4415 (0.4663)	loss 4.1073 (4.0677)	grad_norm 1.6639 (1.7735/0.8975)	mem 16099MB
[2025-01-17 22:57:40 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][280/312]	eta 0:00:15 lr 0.003933	time 0.4479 (0.4717)	model_time 0.4474 (0.4660)	loss 3.7497 (4.0640)	grad_norm 1.2975 (1.7701/0.8907)	mem 16099MB
[2025-01-17 22:57:44 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][290/312]	eta 0:00:10 lr 0.003933	time 0.4486 (0.4716)	model_time 0.4484 (0.4661)	loss 3.5224 (4.0638)	grad_norm 1.7255 (1.7656/0.8788)	mem 16099MB
[2025-01-17 22:57:49 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][300/312]	eta 0:00:05 lr 0.003933	time 0.4386 (0.4717)	model_time 0.4386 (0.4664)	loss 4.8391 (4.0684)	grad_norm 1.0805 (1.7527/0.8710)	mem 16099MB
[2025-01-17 22:57:54 internimage_t_1k_224] (main.py 510): INFO Train: [24/300][310/312]	eta 0:00:00 lr 0.003933	time 0.4374 (0.4712)	model_time 0.4373 (0.4660)	loss 2.5728 (4.0678)	grad_norm 1.2738 (1.7614/0.8704)	mem 16099MB
[2025-01-17 22:57:54 internimage_t_1k_224] (main.py 519): INFO EPOCH 24 training takes 0:02:26
[2025-01-17 22:57:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_24.pth saving......
[2025-01-17 22:57:55 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_24.pth saved !!!
[2025-01-17 22:58:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.278 (7.278)	Loss 1.3624 (1.3624)	Acc@1 69.995 (69.995)	Acc@5 90.796 (90.796)	Mem 16099MB
[2025-01-17 22:58:06 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.999)	Loss 1.8611 (1.5601)	Acc@1 60.425 (66.448)	Acc@5 84.058 (88.079)	Mem 16099MB
[2025-01-17 22:58:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:24] * Acc@1 66.605 Acc@5 88.112
[2025-01-17 22:58:07 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 66.6%
[2025-01-17 22:58:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 22:58:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 22:58:08 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 66.60%
[2025-01-17 22:58:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.763 (7.763)	Loss 6.8081 (6.8081)	Acc@1 0.269 (0.269)	Acc@5 2.246 (2.246)	Mem 16099MB
[2025-01-17 22:58:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.045)	Loss 6.7072 (6.7428)	Acc@1 0.269 (0.277)	Acc@5 1.392 (1.722)	Mem 16099MB
[2025-01-17 22:58:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:24] * Acc@1 0.406 Acc@5 2.123
[2025-01-17 22:58:19 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 22:58:19 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 22:58:22 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][0/312]	eta 0:14:19 lr 0.003933	time 2.7557 (2.7557)	model_time 0.8872 (0.8872)	loss 4.9897 (4.9897)	grad_norm 0.9110 (0.9110/0.0000)	mem 16099MB
[2025-01-17 22:58:27 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][10/312]	eta 0:03:26 lr 0.003932	time 0.4370 (0.6824)	model_time 0.4368 (0.5122)	loss 4.4179 (4.2123)	grad_norm 1.2008 (1.7306/0.6222)	mem 16099MB
[2025-01-17 22:58:31 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][20/312]	eta 0:02:48 lr 0.003932	time 0.4403 (0.5784)	model_time 0.4401 (0.4890)	loss 4.2621 (4.2075)	grad_norm 1.6825 (1.6939/0.5492)	mem 16099MB
[2025-01-17 22:58:36 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][30/312]	eta 0:02:31 lr 0.003932	time 0.4390 (0.5372)	model_time 0.4388 (0.4766)	loss 3.4068 (4.0995)	grad_norm 2.5976 (2.0615/0.9276)	mem 16099MB
[2025-01-17 22:58:40 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][40/312]	eta 0:02:20 lr 0.003932	time 0.4521 (0.5169)	model_time 0.4519 (0.4710)	loss 4.9615 (4.0838)	grad_norm 1.2959 (1.8992/0.8779)	mem 16099MB
[2025-01-17 22:58:45 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][50/312]	eta 0:02:12 lr 0.003932	time 0.4533 (0.5040)	model_time 0.4528 (0.4670)	loss 3.1090 (4.1292)	grad_norm 1.3799 (1.8915/0.8426)	mem 16099MB
[2025-01-17 22:58:50 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][60/312]	eta 0:02:05 lr 0.003931	time 0.4772 (0.4963)	model_time 0.4770 (0.4653)	loss 3.8679 (4.1014)	grad_norm 2.4422 (1.8589/0.8080)	mem 16099MB
[2025-01-17 22:58:54 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][70/312]	eta 0:01:58 lr 0.003931	time 0.4474 (0.4913)	model_time 0.4472 (0.4646)	loss 4.1489 (4.1292)	grad_norm 2.4748 (1.8357/0.7674)	mem 16099MB
[2025-01-17 22:58:59 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][80/312]	eta 0:01:52 lr 0.003931	time 0.4598 (0.4870)	model_time 0.4596 (0.4635)	loss 3.9934 (4.1176)	grad_norm 1.1498 (1.8317/0.7617)	mem 16099MB
[2025-01-17 22:59:03 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][90/312]	eta 0:01:47 lr 0.003931	time 0.4708 (0.4831)	model_time 0.4703 (0.4622)	loss 4.1265 (4.1093)	grad_norm 1.8339 (1.8120/0.7321)	mem 16099MB
[2025-01-17 22:59:08 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][100/312]	eta 0:01:41 lr 0.003931	time 0.4555 (0.4809)	model_time 0.4554 (0.4620)	loss 4.3364 (4.1134)	grad_norm 1.5123 (1.8143/0.7365)	mem 16099MB
[2025-01-17 22:59:12 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][110/312]	eta 0:01:36 lr 0.003931	time 0.4479 (0.4783)	model_time 0.4477 (0.4611)	loss 3.8356 (4.1289)	grad_norm 1.6947 (1.8338/0.7358)	mem 16099MB
[2025-01-17 22:59:17 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][120/312]	eta 0:01:31 lr 0.003930	time 0.4464 (0.4776)	model_time 0.4463 (0.4618)	loss 3.4818 (4.1008)	grad_norm 1.7977 (1.8064/0.7175)	mem 16099MB
[2025-01-17 22:59:22 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][130/312]	eta 0:01:27 lr 0.003930	time 0.4619 (0.4785)	model_time 0.4614 (0.4639)	loss 3.9919 (4.1017)	grad_norm 1.8842 (1.7808/0.7024)	mem 16099MB
[2025-01-17 22:59:27 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][140/312]	eta 0:01:22 lr 0.003930	time 0.5122 (0.4794)	model_time 0.5120 (0.4658)	loss 5.0241 (4.1130)	grad_norm 1.0249 (1.7586/0.6842)	mem 16099MB
[2025-01-17 22:59:32 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][150/312]	eta 0:01:17 lr 0.003930	time 0.4410 (0.4785)	model_time 0.4405 (0.4657)	loss 3.6012 (4.1195)	grad_norm 2.2742 (1.8181/0.8497)	mem 16099MB
[2025-01-17 22:59:36 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][160/312]	eta 0:01:12 lr 0.003930	time 0.5252 (0.4783)	model_time 0.5250 (0.4663)	loss 4.1354 (4.1050)	grad_norm 1.8946 (1.8187/0.8331)	mem 16099MB
[2025-01-17 22:59:41 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][170/312]	eta 0:01:07 lr 0.003930	time 0.4468 (0.4768)	model_time 0.4463 (0.4655)	loss 3.1250 (4.0795)	grad_norm 2.3286 (1.8716/0.9499)	mem 16099MB
[2025-01-17 22:59:45 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][180/312]	eta 0:01:02 lr 0.003929	time 0.4626 (0.4755)	model_time 0.4624 (0.4648)	loss 4.3355 (4.0810)	grad_norm 1.2653 (1.8424/0.9319)	mem 16099MB
[2025-01-17 22:59:50 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][190/312]	eta 0:00:57 lr 0.003929	time 0.4621 (0.4743)	model_time 0.4616 (0.4641)	loss 2.7137 (4.0736)	grad_norm 1.8539 (1.8167/0.9174)	mem 16099MB
[2025-01-17 22:59:54 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][200/312]	eta 0:00:52 lr 0.003929	time 0.4616 (0.4731)	model_time 0.4614 (0.4634)	loss 4.5698 (4.0718)	grad_norm 1.2308 (1.7989/0.8994)	mem 16099MB
[2025-01-17 22:59:59 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][210/312]	eta 0:00:48 lr 0.003929	time 0.4569 (0.4725)	model_time 0.4564 (0.4633)	loss 3.9702 (4.0696)	grad_norm 2.6948 (1.8085/0.8931)	mem 16099MB
[2025-01-17 23:00:04 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][220/312]	eta 0:00:43 lr 0.003929	time 0.4775 (0.4723)	model_time 0.4770 (0.4635)	loss 3.3530 (4.0750)	grad_norm 1.2285 (1.7920/0.8768)	mem 16099MB
[2025-01-17 23:00:08 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][230/312]	eta 0:00:38 lr 0.003929	time 0.4514 (0.4715)	model_time 0.4509 (0.4631)	loss 3.3087 (4.0628)	grad_norm 2.4371 (1.7837/0.8621)	mem 16099MB
[2025-01-17 23:00:13 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][240/312]	eta 0:00:33 lr 0.003928	time 0.4565 (0.4707)	model_time 0.4560 (0.4626)	loss 3.9225 (4.0624)	grad_norm 2.0676 (1.7913/0.8548)	mem 16099MB
[2025-01-17 23:00:17 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][250/312]	eta 0:00:29 lr 0.003928	time 0.4477 (0.4701)	model_time 0.4475 (0.4622)	loss 3.9119 (4.0478)	grad_norm 1.0972 (1.7773/0.8446)	mem 16099MB
[2025-01-17 23:00:22 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][260/312]	eta 0:00:24 lr 0.003928	time 0.4508 (0.4694)	model_time 0.4506 (0.4619)	loss 4.3131 (4.0438)	grad_norm 1.6027 (1.7658/0.8310)	mem 16099MB
[2025-01-17 23:00:26 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][270/312]	eta 0:00:19 lr 0.003928	time 0.4554 (0.4691)	model_time 0.4549 (0.4618)	loss 4.9754 (4.0513)	grad_norm 2.4158 (1.7722/0.8347)	mem 16099MB
[2025-01-17 23:00:31 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][280/312]	eta 0:00:14 lr 0.003928	time 0.4514 (0.4684)	model_time 0.4512 (0.4614)	loss 3.8980 (4.0529)	grad_norm 1.3189 (1.7657/0.8246)	mem 16099MB
[2025-01-17 23:00:36 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][290/312]	eta 0:00:10 lr 0.003927	time 0.4425 (0.4682)	model_time 0.4423 (0.4614)	loss 5.1908 (4.0643)	grad_norm 0.9804 (1.8089/1.0290)	mem 16099MB
[2025-01-17 23:00:40 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][300/312]	eta 0:00:05 lr 0.003927	time 0.4365 (0.4683)	model_time 0.4364 (0.4617)	loss 4.2511 (4.0639)	grad_norm 1.8485 (1.8116/1.0152)	mem 16099MB
[2025-01-17 23:00:45 internimage_t_1k_224] (main.py 510): INFO Train: [25/300][310/312]	eta 0:00:00 lr 0.003927	time 0.5174 (0.4683)	model_time 0.5173 (0.4619)	loss 3.6432 (4.0592)	grad_norm 4.9994 (1.8217/1.0378)	mem 16099MB
[2025-01-17 23:00:45 internimage_t_1k_224] (main.py 519): INFO EPOCH 25 training takes 0:02:26
[2025-01-17 23:00:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_25.pth saving......
[2025-01-17 23:00:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_25.pth saved !!!
[2025-01-17 23:00:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.246 (7.246)	Loss 1.3358 (1.3358)	Acc@1 70.215 (70.215)	Acc@5 90.552 (90.552)	Mem 16099MB
[2025-01-17 23:00:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (0.980)	Loss 1.9245 (1.5527)	Acc@1 58.325 (66.562)	Acc@5 83.130 (88.095)	Mem 16099MB
[2025-01-17 23:00:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:25] * Acc@1 66.647 Acc@5 88.204
[2025-01-17 23:00:58 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 66.6%
[2025-01-17 23:00:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:00:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:00:59 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 66.65%
[2025-01-17 23:01:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.661 (7.661)	Loss 6.7560 (6.7560)	Acc@1 0.366 (0.366)	Acc@5 2.832 (2.832)	Mem 16099MB
[2025-01-17 23:01:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.028)	Loss 6.6888 (6.7163)	Acc@1 0.269 (0.291)	Acc@5 1.440 (1.900)	Mem 16099MB
[2025-01-17 23:01:10 internimage_t_1k_224] (main.py 575): INFO [Epoch:25] * Acc@1 0.426 Acc@5 2.313
[2025-01-17 23:01:10 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.4%
[2025-01-17 23:01:10 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 23:01:13 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][0/312]	eta 0:15:38 lr 0.003927	time 3.0079 (3.0079)	model_time 1.4263 (1.4263)	loss 4.4505 (4.4505)	grad_norm 1.7987 (1.7987/0.0000)	mem 16099MB
[2025-01-17 23:01:18 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][10/312]	eta 0:03:30 lr 0.003927	time 0.4636 (0.6978)	model_time 0.4634 (0.5537)	loss 4.2584 (4.0641)	grad_norm 1.7071 (1.5955/0.4547)	mem 16099MB
[2025-01-17 23:01:23 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][20/312]	eta 0:02:51 lr 0.003927	time 0.4336 (0.5858)	model_time 0.4334 (0.5101)	loss 3.1073 (4.0102)	grad_norm 2.7222 (1.7620/0.4941)	mem 16099MB
[2025-01-17 23:01:27 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][30/312]	eta 0:02:33 lr 0.003927	time 0.4524 (0.5429)	model_time 0.4520 (0.4916)	loss 4.0358 (4.0303)	grad_norm 1.9719 (1.6489/0.4917)	mem 16099MB
[2025-01-17 23:01:32 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][40/312]	eta 0:02:23 lr 0.003926	time 0.4571 (0.5258)	model_time 0.4569 (0.4869)	loss 3.0105 (4.0000)	grad_norm 1.0252 (1.6789/0.5536)	mem 16099MB
[2025-01-17 23:01:37 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][50/312]	eta 0:02:14 lr 0.003926	time 0.4556 (0.5135)	model_time 0.4554 (0.4822)	loss 3.0621 (3.9950)	grad_norm 1.6535 (1.6180/0.5318)	mem 16099MB
[2025-01-17 23:01:41 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][60/312]	eta 0:02:06 lr 0.003926	time 0.4466 (0.5032)	model_time 0.4464 (0.4769)	loss 3.0272 (4.0104)	grad_norm 1.1725 (1.7099/0.6415)	mem 16099MB
[2025-01-17 23:01:46 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][70/312]	eta 0:02:00 lr 0.003926	time 0.4330 (0.4964)	model_time 0.4328 (0.4738)	loss 3.2700 (4.0230)	grad_norm 2.1777 (1.6984/0.6189)	mem 16099MB
[2025-01-17 23:01:50 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][80/312]	eta 0:01:53 lr 0.003926	time 0.4462 (0.4911)	model_time 0.4460 (0.4712)	loss 4.1931 (4.0236)	grad_norm 1.1446 (1.7114/0.6555)	mem 16099MB
[2025-01-17 23:01:55 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][90/312]	eta 0:01:48 lr 0.003925	time 0.4516 (0.4891)	model_time 0.4514 (0.4714)	loss 4.3622 (4.0224)	grad_norm 1.7763 (1.7310/0.6689)	mem 16099MB
[2025-01-17 23:02:00 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][100/312]	eta 0:01:43 lr 0.003925	time 0.5285 (0.4869)	model_time 0.5283 (0.4709)	loss 2.9556 (4.0321)	grad_norm 1.4686 (1.7547/0.6710)	mem 16099MB
[2025-01-17 23:02:04 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][110/312]	eta 0:01:37 lr 0.003925	time 0.4500 (0.4837)	model_time 0.4499 (0.4691)	loss 3.9610 (4.0342)	grad_norm 1.4799 (1.7399/0.6569)	mem 16099MB
[2025-01-17 23:02:09 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][120/312]	eta 0:01:32 lr 0.003925	time 0.4567 (0.4823)	model_time 0.4562 (0.4688)	loss 3.4167 (4.0061)	grad_norm 2.2797 (1.7505/0.6767)	mem 16099MB
[2025-01-17 23:02:14 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][130/312]	eta 0:01:27 lr 0.003925	time 0.4538 (0.4831)	model_time 0.4537 (0.4707)	loss 2.9035 (4.0069)	grad_norm 1.0967 (1.7474/0.6628)	mem 16099MB
[2025-01-17 23:02:18 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][140/312]	eta 0:01:22 lr 0.003925	time 0.5432 (0.4818)	model_time 0.5431 (0.4702)	loss 4.5951 (4.0087)	grad_norm 1.2373 (1.7199/0.6500)	mem 16099MB
[2025-01-17 23:02:23 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][150/312]	eta 0:01:17 lr 0.003924	time 0.4410 (0.4801)	model_time 0.4405 (0.4693)	loss 4.4225 (4.0294)	grad_norm 2.5971 (1.7355/0.6467)	mem 16099MB
[2025-01-17 23:02:27 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][160/312]	eta 0:01:12 lr 0.003924	time 0.4461 (0.4788)	model_time 0.4459 (0.4687)	loss 4.1412 (4.0443)	grad_norm 1.0927 (1.7122/0.6408)	mem 16099MB
[2025-01-17 23:02:32 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][170/312]	eta 0:01:07 lr 0.003924	time 0.4489 (0.4778)	model_time 0.4484 (0.4682)	loss 4.4974 (4.0495)	grad_norm 1.6052 (1.6996/0.6298)	mem 16099MB
[2025-01-17 23:02:37 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][180/312]	eta 0:01:02 lr 0.003924	time 0.4447 (0.4770)	model_time 0.4445 (0.4679)	loss 4.5427 (4.0628)	grad_norm 2.1954 (1.7330/0.6566)	mem 16099MB
[2025-01-17 23:02:41 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][190/312]	eta 0:00:58 lr 0.003924	time 0.4428 (0.4757)	model_time 0.4426 (0.4671)	loss 3.3383 (4.0507)	grad_norm 3.1316 (1.7278/0.6591)	mem 16099MB
[2025-01-17 23:02:46 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][200/312]	eta 0:00:53 lr 0.003923	time 0.4577 (0.4746)	model_time 0.4576 (0.4664)	loss 4.1016 (4.0476)	grad_norm 1.2750 (1.7311/0.6583)	mem 16099MB
[2025-01-17 23:02:50 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][210/312]	eta 0:00:48 lr 0.003923	time 0.4477 (0.4740)	model_time 0.4475 (0.4662)	loss 5.0359 (4.0456)	grad_norm 1.0164 (1.7042/0.6559)	mem 16099MB
[2025-01-17 23:02:55 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][220/312]	eta 0:00:43 lr 0.003923	time 0.4457 (0.4732)	model_time 0.4455 (0.4657)	loss 3.7072 (4.0367)	grad_norm 1.1621 (1.7420/0.7317)	mem 16099MB
[2025-01-17 23:03:00 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][230/312]	eta 0:00:38 lr 0.003923	time 0.4398 (0.4724)	model_time 0.4396 (0.4652)	loss 4.6945 (4.0469)	grad_norm 2.1551 (1.7405/0.7245)	mem 16099MB
[2025-01-17 23:03:04 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][240/312]	eta 0:00:33 lr 0.003923	time 0.4414 (0.4715)	model_time 0.4410 (0.4645)	loss 4.4460 (4.0416)	grad_norm 1.4287 (1.7330/0.7150)	mem 16099MB
[2025-01-17 23:03:09 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][250/312]	eta 0:00:29 lr 0.003923	time 0.4441 (0.4711)	model_time 0.4439 (0.4644)	loss 5.0931 (4.0518)	grad_norm 1.5748 (1.7492/0.7420)	mem 16099MB
[2025-01-17 23:03:13 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][260/312]	eta 0:00:24 lr 0.003922	time 0.4533 (0.4709)	model_time 0.4528 (0.4644)	loss 4.1052 (4.0444)	grad_norm 1.2294 (1.7318/0.7356)	mem 16099MB
[2025-01-17 23:03:18 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][270/312]	eta 0:00:19 lr 0.003922	time 0.5519 (0.4710)	model_time 0.5517 (0.4648)	loss 3.8995 (4.0446)	grad_norm 1.2747 (1.7173/0.7274)	mem 16099MB
[2025-01-17 23:03:23 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][280/312]	eta 0:00:15 lr 0.003922	time 0.4451 (0.4708)	model_time 0.4449 (0.4648)	loss 3.7096 (4.0525)	grad_norm 1.7421 (1.7327/0.7348)	mem 16099MB
[2025-01-17 23:03:27 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][290/312]	eta 0:00:10 lr 0.003922	time 0.4515 (0.4704)	model_time 0.4509 (0.4646)	loss 4.8434 (4.0536)	grad_norm 1.1286 (1.7289/0.7264)	mem 16099MB
[2025-01-17 23:03:32 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][300/312]	eta 0:00:05 lr 0.003922	time 0.4369 (0.4703)	model_time 0.4368 (0.4646)	loss 3.5441 (4.0543)	grad_norm 1.0640 (1.7139/0.7218)	mem 16099MB
[2025-01-17 23:03:36 internimage_t_1k_224] (main.py 510): INFO Train: [26/300][310/312]	eta 0:00:00 lr 0.003921	time 0.4388 (0.4697)	model_time 0.4387 (0.4643)	loss 4.1847 (4.0447)	grad_norm 2.2228 (1.7085/0.7222)	mem 16099MB
[2025-01-17 23:03:37 internimage_t_1k_224] (main.py 519): INFO EPOCH 26 training takes 0:02:26
[2025-01-17 23:03:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_26.pth saving......
[2025-01-17 23:03:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_26.pth saved !!!
[2025-01-17 23:03:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.488 (7.488)	Loss 1.2502 (1.2502)	Acc@1 71.265 (71.265)	Acc@5 91.602 (91.602)	Mem 16099MB
[2025-01-17 23:03:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.018)	Loss 1.7521 (1.4315)	Acc@1 60.815 (67.623)	Acc@5 83.643 (88.900)	Mem 16099MB
[2025-01-17 23:03:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:26] * Acc@1 67.724 Acc@5 88.944
[2025-01-17 23:03:49 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 67.7%
[2025-01-17 23:03:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:03:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:03:51 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 67.72%
[2025-01-17 23:03:59 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.996 (7.996)	Loss 6.7016 (6.7016)	Acc@1 0.464 (0.464)	Acc@5 2.808 (2.808)	Mem 16099MB
[2025-01-17 23:04:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.052)	Loss 6.6725 (6.6891)	Acc@1 0.464 (0.304)	Acc@5 1.514 (1.982)	Mem 16099MB
[2025-01-17 23:04:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:26] * Acc@1 0.468 Acc@5 2.431
[2025-01-17 23:04:02 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.5%
[2025-01-17 23:04:02 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 23:04:05 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][0/312]	eta 0:14:48 lr 0.003921	time 2.8488 (2.8488)	model_time 1.3147 (1.3147)	loss 3.9307 (3.9307)	grad_norm 0.9216 (0.9216/0.0000)	mem 16099MB
[2025-01-17 23:04:10 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][10/312]	eta 0:03:28 lr 0.003921	time 0.4539 (0.6896)	model_time 0.4536 (0.5499)	loss 3.3403 (3.8107)	grad_norm 4.0186 (1.6722/0.8351)	mem 16099MB
[2025-01-17 23:04:15 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][20/312]	eta 0:02:49 lr 0.003921	time 0.4511 (0.5814)	model_time 0.4509 (0.5081)	loss 4.3701 (4.0605)	grad_norm 0.8495 (2.1676/1.3994)	mem 16099MB
[2025-01-17 23:04:19 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][30/312]	eta 0:02:34 lr 0.003921	time 0.5165 (0.5492)	model_time 0.5164 (0.4993)	loss 4.1618 (4.1098)	grad_norm 0.9591 (1.9026/1.2322)	mem 16099MB
[2025-01-17 23:04:24 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][40/312]	eta 0:02:24 lr 0.003921	time 0.4494 (0.5297)	model_time 0.4490 (0.4920)	loss 3.4020 (4.1089)	grad_norm 0.9823 (1.8577/1.1097)	mem 16099MB
[2025-01-17 23:04:29 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][50/312]	eta 0:02:15 lr 0.003920	time 0.4639 (0.5189)	model_time 0.4634 (0.4885)	loss 5.0187 (4.0507)	grad_norm 1.4906 (1.7029/1.0539)	mem 16099MB
[2025-01-17 23:04:33 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][60/312]	eta 0:02:08 lr 0.003920	time 0.4481 (0.5082)	model_time 0.4477 (0.4827)	loss 3.8276 (4.0056)	grad_norm 1.6441 (1.6229/0.9858)	mem 16099MB
[2025-01-17 23:04:38 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][70/312]	eta 0:02:01 lr 0.003920	time 0.4549 (0.5002)	model_time 0.4547 (0.4783)	loss 4.2124 (4.0493)	grad_norm 1.8182 (1.6474/0.9341)	mem 16099MB
[2025-01-17 23:04:43 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][80/312]	eta 0:01:55 lr 0.003920	time 0.4461 (0.4957)	model_time 0.4456 (0.4764)	loss 4.1148 (4.0632)	grad_norm 1.3532 (1.6538/0.9026)	mem 16099MB
[2025-01-17 23:04:47 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][90/312]	eta 0:01:49 lr 0.003920	time 0.4495 (0.4935)	model_time 0.4491 (0.4762)	loss 3.6238 (4.0712)	grad_norm 1.9409 (1.7483/1.0349)	mem 16099MB
[2025-01-17 23:04:52 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][100/312]	eta 0:01:43 lr 0.003920	time 0.4717 (0.4900)	model_time 0.4713 (0.4744)	loss 4.4233 (4.0613)	grad_norm 1.4566 (1.7029/0.9959)	mem 16099MB
[2025-01-17 23:04:56 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][110/312]	eta 0:01:38 lr 0.003919	time 0.4494 (0.4867)	model_time 0.4492 (0.4725)	loss 3.4834 (4.0586)	grad_norm 1.1481 (1.6886/0.9660)	mem 16099MB
[2025-01-17 23:05:01 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][120/312]	eta 0:01:33 lr 0.003919	time 0.4489 (0.4846)	model_time 0.4485 (0.4716)	loss 3.2870 (4.0687)	grad_norm 2.1571 (1.6947/0.9469)	mem 16099MB
[2025-01-17 23:05:06 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][130/312]	eta 0:01:27 lr 0.003919	time 0.4467 (0.4820)	model_time 0.4464 (0.4699)	loss 3.3974 (4.0827)	grad_norm 2.3339 (1.7333/0.9903)	mem 16099MB
[2025-01-17 23:05:10 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][140/312]	eta 0:01:22 lr 0.003919	time 0.4434 (0.4801)	model_time 0.4429 (0.4689)	loss 4.3219 (4.0825)	grad_norm 1.0344 (1.6979/0.9675)	mem 16099MB
[2025-01-17 23:05:15 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][150/312]	eta 0:01:17 lr 0.003919	time 0.5458 (0.4795)	model_time 0.5456 (0.4690)	loss 4.5092 (4.0733)	grad_norm 1.0210 (1.6881/0.9435)	mem 16099MB
[2025-01-17 23:05:20 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][160/312]	eta 0:01:12 lr 0.003918	time 0.4410 (0.4794)	model_time 0.4405 (0.4695)	loss 2.8563 (4.0512)	grad_norm 1.1410 (1.6811/0.9202)	mem 16099MB
[2025-01-17 23:05:24 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][170/312]	eta 0:01:07 lr 0.003918	time 0.4364 (0.4788)	model_time 0.4362 (0.4694)	loss 4.6991 (4.0732)	grad_norm 1.1432 (1.6763/0.8990)	mem 16099MB
[2025-01-17 23:05:29 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][180/312]	eta 0:01:03 lr 0.003918	time 0.4512 (0.4773)	model_time 0.4509 (0.4684)	loss 4.8142 (4.0803)	grad_norm 1.5128 (1.6849/0.8920)	mem 16099MB
[2025-01-17 23:05:33 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][190/312]	eta 0:00:58 lr 0.003918	time 0.4392 (0.4760)	model_time 0.4391 (0.4675)	loss 3.9303 (4.0730)	grad_norm 1.4745 (1.7158/0.9192)	mem 16099MB
[2025-01-17 23:05:38 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][200/312]	eta 0:00:53 lr 0.003918	time 0.4562 (0.4754)	model_time 0.4560 (0.4674)	loss 3.1316 (4.0736)	grad_norm 3.2434 (1.7136/0.9064)	mem 16099MB
[2025-01-17 23:05:43 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][210/312]	eta 0:00:48 lr 0.003917	time 0.4506 (0.4755)	model_time 0.4504 (0.4678)	loss 2.8803 (4.0611)	grad_norm 1.0354 (1.7106/0.8987)	mem 16099MB
[2025-01-17 23:05:47 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][220/312]	eta 0:00:43 lr 0.003917	time 0.4457 (0.4748)	model_time 0.4454 (0.4675)	loss 4.1883 (4.0685)	grad_norm 1.9695 (1.7196/0.8933)	mem 16099MB
[2025-01-17 23:05:52 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][230/312]	eta 0:00:38 lr 0.003917	time 0.4511 (0.4742)	model_time 0.4508 (0.4672)	loss 4.2359 (4.0694)	grad_norm 2.1721 (1.7193/0.8805)	mem 16099MB
[2025-01-17 23:05:56 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][240/312]	eta 0:00:34 lr 0.003917	time 0.4669 (0.4735)	model_time 0.4665 (0.4667)	loss 2.8618 (4.0559)	grad_norm 1.3424 (1.7196/0.8692)	mem 16099MB
[2025-01-17 23:06:01 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][250/312]	eta 0:00:29 lr 0.003917	time 0.4433 (0.4728)	model_time 0.4428 (0.4664)	loss 4.1459 (4.0555)	grad_norm 1.0197 (1.7278/0.8689)	mem 16099MB
[2025-01-17 23:06:06 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][260/312]	eta 0:00:24 lr 0.003916	time 0.4535 (0.4728)	model_time 0.4531 (0.4666)	loss 3.1260 (4.0392)	grad_norm 0.9550 (1.7118/0.8629)	mem 16099MB
[2025-01-17 23:06:11 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][270/312]	eta 0:00:19 lr 0.003916	time 0.4561 (0.4729)	model_time 0.4560 (0.4669)	loss 3.4208 (4.0341)	grad_norm 3.3969 (1.7261/0.8688)	mem 16099MB
[2025-01-17 23:06:15 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][280/312]	eta 0:00:15 lr 0.003916	time 0.4472 (0.4723)	model_time 0.4470 (0.4665)	loss 4.1560 (4.0407)	grad_norm 1.6384 (1.7325/0.8616)	mem 16099MB
[2025-01-17 23:06:20 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][290/312]	eta 0:00:10 lr 0.003916	time 0.4437 (0.4716)	model_time 0.4435 (0.4660)	loss 3.9857 (4.0349)	grad_norm 1.9851 (1.7231/0.8516)	mem 16099MB
[2025-01-17 23:06:24 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][300/312]	eta 0:00:05 lr 0.003916	time 0.4370 (0.4710)	model_time 0.4369 (0.4656)	loss 4.4764 (4.0368)	grad_norm 1.1897 (1.7217/0.8423)	mem 16099MB
[2025-01-17 23:06:29 internimage_t_1k_224] (main.py 510): INFO Train: [27/300][310/312]	eta 0:00:00 lr 0.003916	time 0.4378 (0.4701)	model_time 0.4377 (0.4648)	loss 3.4925 (4.0363)	grad_norm 1.5134 (1.7122/0.8330)	mem 16099MB
[2025-01-17 23:06:29 internimage_t_1k_224] (main.py 519): INFO EPOCH 27 training takes 0:02:26
[2025-01-17 23:06:29 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_27.pth saving......
[2025-01-17 23:06:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_27.pth saved !!!
[2025-01-17 23:06:38 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.335 (7.335)	Loss 1.2469 (1.2469)	Acc@1 72.925 (72.925)	Acc@5 92.310 (92.310)	Mem 16099MB
[2025-01-17 23:06:41 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.984)	Loss 1.7994 (1.4876)	Acc@1 61.597 (68.151)	Acc@5 84.009 (88.936)	Mem 16099MB
[2025-01-17 23:06:41 internimage_t_1k_224] (main.py 575): INFO [Epoch:27] * Acc@1 68.166 Acc@5 89.042
[2025-01-17 23:06:41 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 68.2%
[2025-01-17 23:06:42 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:06:43 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:06:43 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 68.17%
[2025-01-17 23:06:50 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.416 (7.416)	Loss 6.6485 (6.6485)	Acc@1 0.537 (0.537)	Acc@5 3.174 (3.174)	Mem 16099MB
[2025-01-17 23:06:54 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.002)	Loss 6.6488 (6.6576)	Acc@1 0.562 (0.364)	Acc@5 1.855 (2.293)	Mem 16099MB
[2025-01-17 23:06:54 internimage_t_1k_224] (main.py 575): INFO [Epoch:27] * Acc@1 0.544 Acc@5 2.757
[2025-01-17 23:06:54 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.5%
[2025-01-17 23:06:54 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.58%
[2025-01-17 23:06:57 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][0/312]	eta 0:14:38 lr 0.003915	time 2.8149 (2.8149)	model_time 1.3528 (1.3528)	loss 5.0111 (5.0111)	grad_norm 0.8461 (0.8461/0.0000)	mem 16099MB
[2025-01-17 23:07:01 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][10/312]	eta 0:03:26 lr 0.003915	time 0.4443 (0.6827)	model_time 0.4441 (0.5494)	loss 4.3431 (4.2309)	grad_norm 1.5023 (1.9031/0.8852)	mem 16099MB
[2025-01-17 23:07:06 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][20/312]	eta 0:02:47 lr 0.003915	time 0.4453 (0.5727)	model_time 0.4451 (0.5027)	loss 4.3634 (4.1963)	grad_norm 1.6864 (1.7447/0.7045)	mem 16099MB
[2025-01-17 23:07:11 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][30/312]	eta 0:02:31 lr 0.003915	time 0.4546 (0.5390)	model_time 0.4544 (0.4914)	loss 4.9454 (4.1747)	grad_norm 3.8086 (1.8571/0.8182)	mem 16099MB
[2025-01-17 23:07:15 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][40/312]	eta 0:02:20 lr 0.003915	time 0.4645 (0.5182)	model_time 0.4643 (0.4822)	loss 3.7056 (4.1577)	grad_norm 1.4056 (1.8417/0.7621)	mem 16099MB
[2025-01-17 23:07:20 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][50/312]	eta 0:02:12 lr 0.003915	time 0.4558 (0.5076)	model_time 0.4556 (0.4786)	loss 4.8280 (4.1390)	grad_norm 1.0287 (1.7303/0.7395)	mem 16099MB
[2025-01-17 23:07:24 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][60/312]	eta 0:02:05 lr 0.003914	time 0.4427 (0.4995)	model_time 0.4426 (0.4752)	loss 3.2056 (4.1247)	grad_norm 1.0993 (1.7207/0.7309)	mem 16099MB
[2025-01-17 23:07:29 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][70/312]	eta 0:01:59 lr 0.003914	time 0.4584 (0.4942)	model_time 0.4579 (0.4732)	loss 3.6587 (4.0877)	grad_norm 1.1499 (1.6791/0.7076)	mem 16099MB
[2025-01-17 23:07:33 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][80/312]	eta 0:01:53 lr 0.003914	time 0.4737 (0.4892)	model_time 0.4736 (0.4708)	loss 4.3416 (4.0796)	grad_norm 3.1523 (1.6815/0.6933)	mem 16099MB
[2025-01-17 23:07:38 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][90/312]	eta 0:01:47 lr 0.003914	time 0.4462 (0.4848)	model_time 0.4460 (0.4683)	loss 4.2613 (4.0786)	grad_norm 1.7520 (1.7169/0.7170)	mem 16099MB
[2025-01-17 23:07:42 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][100/312]	eta 0:01:42 lr 0.003914	time 0.4748 (0.4819)	model_time 0.4746 (0.4670)	loss 4.3268 (4.0700)	grad_norm 0.9844 (1.6950/0.6916)	mem 16099MB
[2025-01-17 23:07:47 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][110/312]	eta 0:01:37 lr 0.003913	time 0.4515 (0.4811)	model_time 0.4513 (0.4676)	loss 4.4020 (4.0883)	grad_norm 1.2913 (1.6675/0.6707)	mem 16099MB
[2025-01-17 23:07:52 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][120/312]	eta 0:01:32 lr 0.003913	time 0.5347 (0.4793)	model_time 0.5345 (0.4669)	loss 4.0406 (4.0696)	grad_norm 4.0969 (1.7375/0.7286)	mem 16099MB
[2025-01-17 23:07:56 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][130/312]	eta 0:01:26 lr 0.003913	time 0.4431 (0.4778)	model_time 0.4429 (0.4662)	loss 2.7672 (4.0522)	grad_norm 2.0355 (1.7715/0.7717)	mem 16099MB
[2025-01-17 23:08:01 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][140/312]	eta 0:01:22 lr 0.003913	time 0.4559 (0.4772)	model_time 0.4557 (0.4665)	loss 2.5401 (4.0435)	grad_norm 2.2480 (1.7512/0.7552)	mem 16099MB
[2025-01-17 23:08:06 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][150/312]	eta 0:01:17 lr 0.003913	time 0.5380 (0.4785)	model_time 0.5378 (0.4685)	loss 3.5963 (4.0405)	grad_norm 2.4917 (1.7679/0.7583)	mem 16099MB
[2025-01-17 23:08:11 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][160/312]	eta 0:01:12 lr 0.003912	time 0.4498 (0.4776)	model_time 0.4493 (0.4681)	loss 4.3828 (4.0305)	grad_norm 1.0811 (1.7661/0.7497)	mem 16099MB
[2025-01-17 23:08:15 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][170/312]	eta 0:01:07 lr 0.003912	time 0.4459 (0.4767)	model_time 0.4457 (0.4678)	loss 3.8058 (4.0207)	grad_norm 0.7205 (1.7371/0.7460)	mem 16099MB
[2025-01-17 23:08:20 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][180/312]	eta 0:01:02 lr 0.003912	time 0.5340 (0.4759)	model_time 0.5338 (0.4675)	loss 2.7918 (4.0308)	grad_norm 1.1474 (1.7151/0.7323)	mem 16099MB
[2025-01-17 23:08:24 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][190/312]	eta 0:00:57 lr 0.003912	time 0.4421 (0.4748)	model_time 0.4419 (0.4667)	loss 4.5312 (4.0357)	grad_norm 2.4433 (1.7042/0.7227)	mem 16099MB
[2025-01-17 23:08:29 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][200/312]	eta 0:00:53 lr 0.003912	time 0.4457 (0.4736)	model_time 0.4455 (0.4659)	loss 4.5154 (4.0452)	grad_norm 0.9958 (1.6960/0.7281)	mem 16099MB
[2025-01-17 23:08:34 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][210/312]	eta 0:00:48 lr 0.003911	time 0.4511 (0.4729)	model_time 0.4509 (0.4656)	loss 3.8805 (4.0331)	grad_norm 1.4600 (1.6768/0.7175)	mem 16099MB
[2025-01-17 23:08:38 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][220/312]	eta 0:00:43 lr 0.003911	time 0.4374 (0.4721)	model_time 0.4372 (0.4651)	loss 4.4303 (4.0278)	grad_norm 1.7352 (1.7123/0.8724)	mem 16099MB
[2025-01-17 23:08:43 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][230/312]	eta 0:00:38 lr 0.003911	time 0.4514 (0.4720)	model_time 0.4512 (0.4653)	loss 4.4826 (4.0482)	grad_norm 1.2239 (1.7180/0.8678)	mem 16099MB
[2025-01-17 23:08:47 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][240/312]	eta 0:00:33 lr 0.003911	time 0.4343 (0.4717)	model_time 0.4339 (0.4653)	loss 3.2303 (4.0397)	grad_norm 2.3745 (1.6981/0.8595)	mem 16099MB
[2025-01-17 23:08:52 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][250/312]	eta 0:00:29 lr 0.003911	time 0.4692 (0.4713)	model_time 0.4690 (0.4651)	loss 5.0605 (4.0403)	grad_norm 2.3887 (1.6943/0.8657)	mem 16099MB
[2025-01-17 23:08:57 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][260/312]	eta 0:00:24 lr 0.003910	time 0.4388 (0.4707)	model_time 0.4386 (0.4647)	loss 3.8018 (4.0360)	grad_norm 1.4046 (1.6735/0.8566)	mem 16099MB
[2025-01-17 23:09:01 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][270/312]	eta 0:00:19 lr 0.003910	time 0.4432 (0.4706)	model_time 0.4430 (0.4648)	loss 4.3530 (4.0170)	grad_norm 1.1205 (1.6663/0.8438)	mem 16099MB
[2025-01-17 23:09:06 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][280/312]	eta 0:00:15 lr 0.003910	time 0.4843 (0.4703)	model_time 0.4841 (0.4647)	loss 4.6995 (4.0107)	grad_norm 1.3124 (1.6730/0.8356)	mem 16099MB
[2025-01-17 23:09:11 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][290/312]	eta 0:00:10 lr 0.003910	time 0.4451 (0.4701)	model_time 0.4449 (0.4647)	loss 4.4602 (4.0195)	grad_norm 2.3907 (1.6722/0.8297)	mem 16099MB
[2025-01-17 23:09:15 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][300/312]	eta 0:00:05 lr 0.003910	time 0.4437 (0.4699)	model_time 0.4435 (0.4647)	loss 3.7463 (4.0193)	grad_norm 3.7678 (1.6809/0.8302)	mem 16099MB
[2025-01-17 23:09:20 internimage_t_1k_224] (main.py 510): INFO Train: [28/300][310/312]	eta 0:00:00 lr 0.003909	time 0.4387 (0.4698)	model_time 0.4386 (0.4647)	loss 4.4854 (4.0114)	grad_norm 1.9731 (1.6883/0.8420)	mem 16099MB
[2025-01-17 23:09:20 internimage_t_1k_224] (main.py 519): INFO EPOCH 28 training takes 0:02:26
[2025-01-17 23:09:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_28.pth saving......
[2025-01-17 23:09:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_28.pth saved !!!
[2025-01-17 23:09:29 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.448 (7.448)	Loss 1.2700 (1.2700)	Acc@1 73.022 (73.022)	Acc@5 91.577 (91.577)	Mem 16099MB
[2025-01-17 23:09:33 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.006)	Loss 1.8037 (1.4649)	Acc@1 60.669 (68.535)	Acc@5 84.814 (89.120)	Mem 16099MB
[2025-01-17 23:09:33 internimage_t_1k_224] (main.py 575): INFO [Epoch:28] * Acc@1 68.684 Acc@5 89.233
[2025-01-17 23:09:33 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 68.7%
[2025-01-17 23:09:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:09:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:09:34 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 68.68%
[2025-01-17 23:09:41 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.209 (7.209)	Loss 6.6059 (6.6059)	Acc@1 0.513 (0.513)	Acc@5 3.149 (3.149)	Mem 16099MB
[2025-01-17 23:09:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.975)	Loss 6.6211 (6.6206)	Acc@1 0.732 (0.471)	Acc@5 2.271 (2.750)	Mem 16099MB
[2025-01-17 23:09:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:28] * Acc@1 0.662 Acc@5 3.221
[2025-01-17 23:09:45 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.7%
[2025-01-17 23:09:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:09:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:09:46 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.66%
[2025-01-17 23:09:48 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][0/312]	eta 0:10:47 lr 0.003909	time 2.0745 (2.0745)	model_time 0.4649 (0.4649)	loss 3.3681 (3.3681)	grad_norm 1.5253 (1.5253/0.0000)	mem 16099MB
[2025-01-17 23:09:53 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][10/312]	eta 0:03:09 lr 0.003909	time 0.5517 (0.6272)	model_time 0.5516 (0.4806)	loss 3.0197 (3.8613)	grad_norm 2.0404 (1.6114/0.3226)	mem 16099MB
[2025-01-17 23:09:58 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][20/312]	eta 0:02:38 lr 0.003909	time 0.4643 (0.5431)	model_time 0.4641 (0.4661)	loss 3.2095 (3.8873)	grad_norm 2.0014 (1.9855/1.1193)	mem 16099MB
[2025-01-17 23:10:02 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][30/312]	eta 0:02:25 lr 0.003909	time 0.4462 (0.5142)	model_time 0.4455 (0.4620)	loss 3.3619 (3.9337)	grad_norm 1.5060 (1.7945/0.9848)	mem 16099MB
[2025-01-17 23:10:07 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][40/312]	eta 0:02:15 lr 0.003909	time 0.4482 (0.4986)	model_time 0.4480 (0.4590)	loss 4.1282 (3.9460)	grad_norm 0.8674 (1.6583/0.9107)	mem 16099MB
[2025-01-17 23:10:11 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][50/312]	eta 0:02:08 lr 0.003908	time 0.4468 (0.4898)	model_time 0.4463 (0.4579)	loss 4.4457 (3.9468)	grad_norm 1.6013 (1.8177/1.0036)	mem 16099MB
[2025-01-17 23:10:16 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][60/312]	eta 0:02:02 lr 0.003908	time 0.4478 (0.4864)	model_time 0.4471 (0.4596)	loss 4.1281 (3.9940)	grad_norm 1.6069 (1.7790/0.9487)	mem 16099MB
[2025-01-17 23:10:20 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][70/312]	eta 0:01:56 lr 0.003908	time 0.4574 (0.4816)	model_time 0.4569 (0.4585)	loss 3.5068 (3.9412)	grad_norm 1.6688 (1.7359/0.8903)	mem 16099MB
[2025-01-17 23:10:25 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][80/312]	eta 0:01:50 lr 0.003908	time 0.4542 (0.4777)	model_time 0.4540 (0.4574)	loss 3.7295 (3.9408)	grad_norm 0.8053 (1.6713/0.8545)	mem 16099MB
[2025-01-17 23:10:29 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][90/312]	eta 0:01:45 lr 0.003908	time 0.4615 (0.4763)	model_time 0.4610 (0.4583)	loss 3.8124 (3.9357)	grad_norm 1.2190 (1.6265/0.8195)	mem 16099MB
[2025-01-17 23:10:34 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][100/312]	eta 0:01:40 lr 0.003907	time 0.4456 (0.4738)	model_time 0.4454 (0.4575)	loss 2.6127 (3.9310)	grad_norm 1.6089 (1.6446/0.8056)	mem 16099MB
[2025-01-17 23:10:39 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][110/312]	eta 0:01:35 lr 0.003907	time 0.4614 (0.4732)	model_time 0.4612 (0.4583)	loss 2.6233 (3.9087)	grad_norm 0.7195 (1.6559/0.8182)	mem 16099MB
[2025-01-17 23:10:43 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][120/312]	eta 0:01:30 lr 0.003907	time 0.6092 (0.4734)	model_time 0.6091 (0.4597)	loss 2.8975 (3.9226)	grad_norm 1.3356 (1.6621/0.8007)	mem 16099MB
[2025-01-17 23:10:48 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][130/312]	eta 0:01:26 lr 0.003907	time 0.4475 (0.4734)	model_time 0.4474 (0.4608)	loss 3.7040 (3.9046)	grad_norm 1.5238 (1.6288/0.7823)	mem 16099MB
[2025-01-17 23:10:53 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][140/312]	eta 0:01:21 lr 0.003907	time 0.4809 (0.4745)	model_time 0.4804 (0.4627)	loss 4.4106 (3.9034)	grad_norm 1.2085 (1.6511/0.7792)	mem 16099MB
[2025-01-17 23:10:58 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][150/312]	eta 0:01:16 lr 0.003906	time 0.4543 (0.4733)	model_time 0.4541 (0.4623)	loss 3.7085 (3.9167)	grad_norm 2.2523 (1.6502/0.7630)	mem 16099MB
[2025-01-17 23:11:02 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][160/312]	eta 0:01:11 lr 0.003906	time 0.4522 (0.4732)	model_time 0.4518 (0.4629)	loss 4.6222 (3.9123)	grad_norm 1.6736 (1.6572/0.7582)	mem 16099MB
[2025-01-17 23:11:07 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][170/312]	eta 0:01:07 lr 0.003906	time 0.4411 (0.4720)	model_time 0.4403 (0.4622)	loss 4.6433 (3.9261)	grad_norm 2.2520 (1.6382/0.7509)	mem 16099MB
[2025-01-17 23:11:11 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][180/312]	eta 0:01:02 lr 0.003906	time 0.4426 (0.4707)	model_time 0.4424 (0.4614)	loss 3.5667 (3.9288)	grad_norm 3.3550 (1.6620/0.7684)	mem 16099MB
[2025-01-17 23:11:16 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][190/312]	eta 0:00:57 lr 0.003906	time 0.4515 (0.4698)	model_time 0.4513 (0.4609)	loss 4.2857 (3.9277)	grad_norm 2.2431 (1.6677/0.7583)	mem 16099MB
[2025-01-17 23:11:20 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][200/312]	eta 0:00:52 lr 0.003905	time 0.4380 (0.4689)	model_time 0.4376 (0.4605)	loss 4.1633 (3.9141)	grad_norm 2.9022 (1.6693/0.7531)	mem 16099MB
[2025-01-17 23:11:25 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][210/312]	eta 0:00:47 lr 0.003905	time 0.5591 (0.4685)	model_time 0.5586 (0.4605)	loss 4.0842 (3.9187)	grad_norm 0.6084 (1.6811/0.7963)	mem 16099MB
[2025-01-17 23:11:30 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][220/312]	eta 0:00:43 lr 0.003905	time 0.4541 (0.4680)	model_time 0.4539 (0.4603)	loss 3.3533 (3.9304)	grad_norm 0.9353 (1.6653/0.7849)	mem 16099MB
[2025-01-17 23:11:34 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][230/312]	eta 0:00:38 lr 0.003905	time 0.4427 (0.4683)	model_time 0.4426 (0.4610)	loss 4.9111 (3.9395)	grad_norm 1.0046 (1.6908/0.8052)	mem 16099MB
[2025-01-17 23:11:39 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][240/312]	eta 0:00:33 lr 0.003905	time 0.4481 (0.4680)	model_time 0.4476 (0.4609)	loss 4.2110 (3.9404)	grad_norm 1.5241 (1.6709/0.7956)	mem 16099MB
[2025-01-17 23:11:44 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][250/312]	eta 0:00:28 lr 0.003904	time 0.4423 (0.4677)	model_time 0.4418 (0.4609)	loss 4.3651 (3.9319)	grad_norm 1.6323 (1.6581/0.7854)	mem 16099MB
[2025-01-17 23:11:48 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][260/312]	eta 0:00:24 lr 0.003904	time 0.4437 (0.4673)	model_time 0.4432 (0.4608)	loss 4.4743 (3.9432)	grad_norm 1.0772 (1.6707/0.7892)	mem 16099MB
[2025-01-17 23:11:53 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][270/312]	eta 0:00:19 lr 0.003904	time 0.4532 (0.4671)	model_time 0.4526 (0.4608)	loss 4.9622 (3.9373)	grad_norm 1.4515 (1.6745/0.7900)	mem 16099MB
[2025-01-17 23:11:57 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][280/312]	eta 0:00:14 lr 0.003904	time 0.4458 (0.4670)	model_time 0.4453 (0.4609)	loss 3.7507 (3.9305)	grad_norm 1.0058 (1.6613/0.7823)	mem 16099MB
[2025-01-17 23:12:02 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][290/312]	eta 0:00:10 lr 0.003904	time 0.4523 (0.4667)	model_time 0.4518 (0.4608)	loss 3.9931 (3.9277)	grad_norm 1.0996 (1.6517/0.7719)	mem 16099MB
[2025-01-17 23:12:06 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][300/312]	eta 0:00:05 lr 0.003903	time 0.4382 (0.4664)	model_time 0.4381 (0.4607)	loss 3.3852 (3.9245)	grad_norm 1.0847 (1.6423/0.7699)	mem 16099MB
[2025-01-17 23:12:11 internimage_t_1k_224] (main.py 510): INFO Train: [29/300][310/312]	eta 0:00:00 lr 0.003903	time 0.4383 (0.4659)	model_time 0.4382 (0.4604)	loss 4.2049 (3.9284)	grad_norm 1.4502 (1.6456/0.7760)	mem 16099MB
[2025-01-17 23:12:11 internimage_t_1k_224] (main.py 519): INFO EPOCH 29 training takes 0:02:25
[2025-01-17 23:12:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_29.pth saving......
[2025-01-17 23:12:13 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_29.pth saved !!!
[2025-01-17 23:12:20 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.348 (7.348)	Loss 1.2407 (1.2407)	Acc@1 72.070 (72.070)	Acc@5 91.699 (91.699)	Mem 16099MB
[2025-01-17 23:12:24 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.994)	Loss 1.6839 (1.4401)	Acc@1 63.647 (68.896)	Acc@5 85.889 (89.216)	Mem 16099MB
[2025-01-17 23:12:24 internimage_t_1k_224] (main.py 575): INFO [Epoch:29] * Acc@1 68.864 Acc@5 89.249
[2025-01-17 23:12:24 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 68.9%
[2025-01-17 23:12:24 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:12:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:12:25 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 68.86%
[2025-01-17 23:12:32 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.433 (7.433)	Loss 6.5593 (6.5593)	Acc@1 0.586 (0.586)	Acc@5 3.687 (3.687)	Mem 16099MB
[2025-01-17 23:12:36 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.001)	Loss 6.5824 (6.5727)	Acc@1 0.952 (0.621)	Acc@5 2.881 (3.309)	Mem 16099MB
[2025-01-17 23:12:36 internimage_t_1k_224] (main.py 575): INFO [Epoch:29] * Acc@1 0.842 Acc@5 3.779
[2025-01-17 23:12:36 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 0.8%
[2025-01-17 23:12:36 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:12:37 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:12:37 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 0.84%
[2025-01-17 23:12:40 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][0/312]	eta 0:12:03 lr 0.003903	time 2.3199 (2.3199)	model_time 0.4813 (0.4813)	loss 4.6200 (4.6200)	grad_norm 2.5794 (2.5794/0.0000)	mem 16099MB
[2025-01-17 23:12:44 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][10/312]	eta 0:03:11 lr 0.003903	time 0.4345 (0.6330)	model_time 0.4341 (0.4654)	loss 4.1864 (4.2343)	grad_norm 1.0032 (1.7097/0.5895)	mem 16099MB
[2025-01-17 23:12:49 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][20/312]	eta 0:02:39 lr 0.003903	time 0.4407 (0.5476)	model_time 0.4406 (0.4596)	loss 5.0877 (4.0847)	grad_norm 3.7700 (1.7624/0.7333)	mem 16099MB
[2025-01-17 23:12:53 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][30/312]	eta 0:02:26 lr 0.003902	time 0.4778 (0.5210)	model_time 0.4776 (0.4613)	loss 4.5285 (4.0710)	grad_norm 1.6296 (1.6978/0.6906)	mem 16099MB
[2025-01-17 23:12:58 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][40/312]	eta 0:02:19 lr 0.003902	time 0.4480 (0.5113)	model_time 0.4475 (0.4661)	loss 3.9849 (4.0177)	grad_norm 1.6004 (1.6679/0.6667)	mem 16099MB
[2025-01-17 23:13:03 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][50/312]	eta 0:02:11 lr 0.003902	time 0.4476 (0.5005)	model_time 0.4474 (0.4641)	loss 4.3305 (4.0484)	grad_norm 1.8126 (1.6945/0.7380)	mem 16099MB
[2025-01-17 23:13:07 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][60/312]	eta 0:02:04 lr 0.003902	time 0.4457 (0.4929)	model_time 0.4452 (0.4623)	loss 4.1969 (4.0766)	grad_norm 2.1972 (1.6740/0.7031)	mem 16099MB
[2025-01-17 23:13:12 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][70/312]	eta 0:01:58 lr 0.003902	time 0.4822 (0.4883)	model_time 0.4820 (0.4620)	loss 4.4765 (4.0908)	grad_norm 1.2859 (1.6333/0.6844)	mem 16099MB
[2025-01-17 23:13:17 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][80/312]	eta 0:01:52 lr 0.003901	time 0.4519 (0.4844)	model_time 0.4514 (0.4613)	loss 4.4982 (4.0625)	grad_norm 1.8010 (1.5884/0.6599)	mem 16099MB
[2025-01-17 23:13:21 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][90/312]	eta 0:01:46 lr 0.003901	time 0.4461 (0.4813)	model_time 0.4459 (0.4607)	loss 3.6140 (4.0617)	grad_norm 2.7436 (1.6463/0.7289)	mem 16099MB
[2025-01-17 23:13:26 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][100/312]	eta 0:01:41 lr 0.003901	time 0.4477 (0.4784)	model_time 0.4476 (0.4598)	loss 3.3398 (4.0287)	grad_norm 0.9910 (1.6182/0.7093)	mem 16099MB
[2025-01-17 23:13:30 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][110/312]	eta 0:01:36 lr 0.003901	time 0.4523 (0.4785)	model_time 0.4521 (0.4616)	loss 4.1740 (4.0408)	grad_norm 1.1570 (1.6080/0.6840)	mem 16099MB
[2025-01-17 23:13:35 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][120/312]	eta 0:01:31 lr 0.003901	time 0.4484 (0.4762)	model_time 0.4482 (0.4606)	loss 4.0620 (4.0527)	grad_norm 4.6667 (1.6317/0.7262)	mem 16099MB
[2025-01-17 23:13:40 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][130/312]	eta 0:01:26 lr 0.003900	time 0.4427 (0.4756)	model_time 0.4422 (0.4612)	loss 2.9728 (4.0544)	grad_norm 2.1087 (1.6580/0.7283)	mem 16099MB
[2025-01-17 23:13:44 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][140/312]	eta 0:01:21 lr 0.003900	time 0.4416 (0.4743)	model_time 0.4414 (0.4608)	loss 3.6011 (4.0490)	grad_norm 1.7574 (1.6620/0.7432)	mem 16099MB
[2025-01-17 23:13:49 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][150/312]	eta 0:01:16 lr 0.003900	time 0.4468 (0.4742)	model_time 0.4464 (0.4616)	loss 3.7190 (4.0019)	grad_norm 1.9113 (1.6374/0.7279)	mem 16099MB
[2025-01-17 23:13:54 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][160/312]	eta 0:01:11 lr 0.003900	time 0.5537 (0.4734)	model_time 0.5535 (0.4616)	loss 4.1360 (3.9933)	grad_norm 2.3946 (1.6348/0.7377)	mem 16099MB
[2025-01-17 23:13:58 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][170/312]	eta 0:01:07 lr 0.003900	time 0.4475 (0.4719)	model_time 0.4470 (0.4607)	loss 3.8036 (3.9925)	grad_norm 1.9895 (1.6254/0.7241)	mem 16099MB
[2025-01-17 23:14:03 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][180/312]	eta 0:01:02 lr 0.003899	time 0.4447 (0.4712)	model_time 0.4445 (0.4606)	loss 4.2952 (4.0036)	grad_norm 0.9390 (1.6045/0.7121)	mem 16099MB
[2025-01-17 23:14:07 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][190/312]	eta 0:00:57 lr 0.003899	time 0.4652 (0.4706)	model_time 0.4647 (0.4606)	loss 4.2510 (3.9948)	grad_norm 0.9522 (1.5922/0.7035)	mem 16099MB
[2025-01-17 23:14:12 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][200/312]	eta 0:00:52 lr 0.003899	time 0.4538 (0.4706)	model_time 0.4536 (0.4610)	loss 2.5517 (3.9966)	grad_norm 1.9721 (1.6049/0.6957)	mem 16099MB
[2025-01-17 23:14:17 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][210/312]	eta 0:00:47 lr 0.003899	time 0.4432 (0.4701)	model_time 0.4427 (0.4610)	loss 3.8090 (3.9955)	grad_norm 1.2652 (1.6157/0.6985)	mem 16099MB
[2025-01-17 23:14:21 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][220/312]	eta 0:00:43 lr 0.003899	time 0.4520 (0.4693)	model_time 0.4515 (0.4606)	loss 3.4862 (3.9912)	grad_norm 1.9900 (1.6050/0.6914)	mem 16099MB
[2025-01-17 23:14:26 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][230/312]	eta 0:00:38 lr 0.003898	time 0.4506 (0.4686)	model_time 0.4504 (0.4603)	loss 4.3579 (3.9917)	grad_norm 1.2388 (1.6134/0.6875)	mem 16099MB
[2025-01-17 23:14:30 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][240/312]	eta 0:00:33 lr 0.003898	time 0.4458 (0.4682)	model_time 0.4453 (0.4602)	loss 4.6950 (3.9866)	grad_norm 1.6215 (1.6461/0.7263)	mem 16099MB
[2025-01-17 23:14:35 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][250/312]	eta 0:00:29 lr 0.003898	time 0.4422 (0.4679)	model_time 0.4417 (0.4602)	loss 4.4396 (3.9862)	grad_norm 1.5923 (1.6349/0.7209)	mem 16099MB
[2025-01-17 23:14:40 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][260/312]	eta 0:00:24 lr 0.003898	time 0.4550 (0.4681)	model_time 0.4545 (0.4606)	loss 4.4187 (3.9747)	grad_norm 1.7427 (1.6192/0.7150)	mem 16099MB
[2025-01-17 23:14:44 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][270/312]	eta 0:00:19 lr 0.003897	time 0.4448 (0.4681)	model_time 0.4446 (0.4609)	loss 4.2682 (3.9797)	grad_norm 1.3849 (1.6286/0.7162)	mem 16099MB
[2025-01-17 23:14:49 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][280/312]	eta 0:00:14 lr 0.003897	time 0.4489 (0.4687)	model_time 0.4484 (0.4617)	loss 3.1081 (3.9610)	grad_norm 1.6118 (1.6191/0.7090)	mem 16099MB
[2025-01-17 23:14:54 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][290/312]	eta 0:00:10 lr 0.003897	time 0.4709 (0.4686)	model_time 0.4704 (0.4619)	loss 4.4716 (3.9641)	grad_norm 0.8589 (1.6031/0.7057)	mem 16099MB
[2025-01-17 23:14:58 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][300/312]	eta 0:00:05 lr 0.003897	time 0.4375 (0.4684)	model_time 0.4374 (0.4619)	loss 4.8800 (3.9674)	grad_norm 1.5097 (1.6182/0.7716)	mem 16099MB
[2025-01-17 23:15:03 internimage_t_1k_224] (main.py 510): INFO Train: [30/300][310/312]	eta 0:00:00 lr 0.003897	time 0.4498 (0.4676)	model_time 0.4497 (0.4613)	loss 4.3693 (3.9757)	grad_norm 2.7255 (1.6087/0.7736)	mem 16099MB
[2025-01-17 23:15:03 internimage_t_1k_224] (main.py 519): INFO EPOCH 30 training takes 0:02:25
[2025-01-17 23:15:03 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_30.pth saving......
[2025-01-17 23:15:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_30.pth saved !!!
[2025-01-17 23:15:12 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.556 (7.556)	Loss 1.2428 (1.2428)	Acc@1 73.413 (73.413)	Acc@5 92.383 (92.383)	Mem 16099MB
[2025-01-17 23:15:16 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.020)	Loss 1.7079 (1.4265)	Acc@1 63.647 (69.254)	Acc@5 85.547 (89.837)	Mem 16099MB
[2025-01-17 23:15:16 internimage_t_1k_224] (main.py 575): INFO [Epoch:30] * Acc@1 69.308 Acc@5 89.921
[2025-01-17 23:15:16 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 69.3%
[2025-01-17 23:15:16 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:15:17 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:15:17 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 69.31%
[2025-01-17 23:15:24 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.414 (7.414)	Loss 6.5335 (6.5335)	Acc@1 0.513 (0.513)	Acc@5 3.882 (3.882)	Mem 16099MB
[2025-01-17 23:15:28 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.015)	Loss 6.5271 (6.5157)	Acc@1 1.221 (0.828)	Acc@5 3.735 (4.013)	Mem 16099MB
[2025-01-17 23:15:28 internimage_t_1k_224] (main.py 575): INFO [Epoch:30] * Acc@1 1.056 Acc@5 4.505
[2025-01-17 23:15:28 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 1.1%
[2025-01-17 23:15:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:15:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:15:29 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 1.06%
[2025-01-17 23:15:31 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][0/312]	eta 0:09:51 lr 0.003897	time 1.8946 (1.8946)	model_time 0.4738 (0.4738)	loss 3.3379 (3.3379)	grad_norm 1.4382 (1.4382/0.0000)	mem 16099MB
[2025-01-17 23:15:36 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][10/312]	eta 0:03:03 lr 0.003896	time 0.4502 (0.6069)	model_time 0.4500 (0.4774)	loss 4.4960 (4.0548)	grad_norm 1.9056 (1.6538/0.4087)	mem 16099MB
[2025-01-17 23:15:41 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][20/312]	eta 0:02:35 lr 0.003896	time 0.4554 (0.5336)	model_time 0.4553 (0.4656)	loss 3.9278 (3.9684)	grad_norm 0.9889 (1.7801/0.6191)	mem 16099MB
[2025-01-17 23:15:45 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][30/312]	eta 0:02:23 lr 0.003896	time 0.4657 (0.5078)	model_time 0.4652 (0.4617)	loss 3.9725 (4.0127)	grad_norm 0.8812 (1.7784/0.6691)	mem 16099MB
[2025-01-17 23:15:50 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][40/312]	eta 0:02:14 lr 0.003896	time 0.4675 (0.4956)	model_time 0.4672 (0.4606)	loss 3.9959 (4.0577)	grad_norm 0.8356 (1.6215/0.6542)	mem 16099MB
[2025-01-17 23:15:54 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][50/312]	eta 0:02:07 lr 0.003896	time 0.4525 (0.4872)	model_time 0.4521 (0.4590)	loss 4.2860 (3.9774)	grad_norm 1.3237 (1.5472/0.6194)	mem 16099MB
[2025-01-17 23:15:59 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][60/312]	eta 0:02:01 lr 0.003895	time 0.4444 (0.4828)	model_time 0.4440 (0.4591)	loss 4.1632 (3.9974)	grad_norm 1.5459 (1.4823/0.5901)	mem 16099MB
[2025-01-17 23:16:03 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][70/312]	eta 0:01:55 lr 0.003895	time 0.4523 (0.4784)	model_time 0.4521 (0.4581)	loss 3.3572 (3.9789)	grad_norm 2.4369 (1.5595/0.6624)	mem 16099MB
[2025-01-17 23:16:08 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][80/312]	eta 0:01:50 lr 0.003895	time 0.4494 (0.4764)	model_time 0.4489 (0.4585)	loss 2.8238 (3.9557)	grad_norm 0.9679 (1.5525/0.6496)	mem 16099MB
[2025-01-17 23:16:13 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][90/312]	eta 0:01:45 lr 0.003895	time 0.4489 (0.4751)	model_time 0.4487 (0.4591)	loss 4.1673 (3.9578)	grad_norm 1.0520 (1.5341/0.6281)	mem 16099MB
[2025-01-17 23:16:17 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][100/312]	eta 0:01:40 lr 0.003894	time 0.4478 (0.4729)	model_time 0.4473 (0.4584)	loss 4.1767 (3.9321)	grad_norm 1.3999 (1.6131/0.7697)	mem 16099MB
[2025-01-17 23:16:22 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][110/312]	eta 0:01:35 lr 0.003894	time 0.4495 (0.4718)	model_time 0.4493 (0.4587)	loss 4.2431 (3.9321)	grad_norm 0.9554 (1.5934/0.7453)	mem 16099MB
[2025-01-17 23:16:26 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][120/312]	eta 0:01:30 lr 0.003894	time 0.4476 (0.4717)	model_time 0.4474 (0.4596)	loss 3.3512 (3.9483)	grad_norm 0.8766 (1.5920/0.7336)	mem 16099MB
[2025-01-17 23:16:31 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][130/312]	eta 0:01:25 lr 0.003894	time 0.4619 (0.4706)	model_time 0.4614 (0.4593)	loss 2.8234 (3.9467)	grad_norm 1.7322 (1.5769/0.7177)	mem 16099MB
[2025-01-17 23:16:35 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][140/312]	eta 0:01:20 lr 0.003894	time 0.4601 (0.4691)	model_time 0.4596 (0.4587)	loss 2.9703 (3.9388)	grad_norm 0.8266 (1.5708/0.7351)	mem 16099MB
[2025-01-17 23:16:40 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][150/312]	eta 0:01:16 lr 0.003893	time 0.4401 (0.4703)	model_time 0.4399 (0.4605)	loss 2.9968 (3.9383)	grad_norm 0.8524 (1.5521/0.7187)	mem 16099MB
[2025-01-17 23:16:45 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][160/312]	eta 0:01:11 lr 0.003893	time 0.4714 (0.4705)	model_time 0.4709 (0.4613)	loss 4.2692 (3.9315)	grad_norm 1.7211 (1.5404/0.7126)	mem 16099MB
[2025-01-17 23:16:50 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][170/312]	eta 0:01:06 lr 0.003893	time 0.4633 (0.4702)	model_time 0.4631 (0.4615)	loss 3.5246 (3.9358)	grad_norm 3.2052 (1.5527/0.7123)	mem 16099MB
[2025-01-17 23:16:54 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][180/312]	eta 0:01:01 lr 0.003893	time 0.4505 (0.4692)	model_time 0.4499 (0.4609)	loss 3.2793 (3.9160)	grad_norm 1.5062 (1.5664/0.7083)	mem 16099MB
[2025-01-17 23:16:59 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][190/312]	eta 0:00:57 lr 0.003893	time 0.4505 (0.4696)	model_time 0.4504 (0.4618)	loss 4.1829 (3.9072)	grad_norm 0.9472 (1.5502/0.6993)	mem 16099MB
[2025-01-17 23:17:04 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][200/312]	eta 0:00:52 lr 0.003892	time 0.4515 (0.4686)	model_time 0.4510 (0.4612)	loss 3.0065 (3.9052)	grad_norm 1.9313 (1.5924/0.8481)	mem 16099MB
[2025-01-17 23:17:08 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][210/312]	eta 0:00:47 lr 0.003892	time 0.5745 (0.4692)	model_time 0.5740 (0.4620)	loss 4.1972 (3.9093)	grad_norm 1.1983 (1.5962/0.8310)	mem 16099MB
[2025-01-17 23:17:13 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][220/312]	eta 0:00:43 lr 0.003892	time 0.4570 (0.4685)	model_time 0.4569 (0.4617)	loss 3.4355 (3.9169)	grad_norm 2.9250 (1.5949/0.8181)	mem 16099MB
[2025-01-17 23:17:17 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][230/312]	eta 0:00:38 lr 0.003892	time 0.4515 (0.4680)	model_time 0.4514 (0.4615)	loss 3.6058 (3.9073)	grad_norm 1.6066 (1.5943/0.8084)	mem 16099MB
[2025-01-17 23:17:22 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][240/312]	eta 0:00:33 lr 0.003891	time 0.5475 (0.4681)	model_time 0.5471 (0.4618)	loss 4.7357 (3.9119)	grad_norm 1.4450 (1.5834/0.7960)	mem 16099MB
[2025-01-17 23:17:27 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][250/312]	eta 0:00:29 lr 0.003891	time 0.4410 (0.4681)	model_time 0.4408 (0.4620)	loss 4.2038 (3.9131)	grad_norm 1.4872 (1.5775/0.7866)	mem 16099MB
[2025-01-17 23:17:31 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][260/312]	eta 0:00:24 lr 0.003891	time 0.4515 (0.4675)	model_time 0.4513 (0.4617)	loss 4.2087 (3.9170)	grad_norm 2.3280 (1.5820/0.7761)	mem 16099MB
[2025-01-17 23:17:36 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][270/312]	eta 0:00:19 lr 0.003891	time 0.4485 (0.4668)	model_time 0.4483 (0.4611)	loss 4.0234 (3.9156)	grad_norm 1.0180 (1.6426/1.0544)	mem 16099MB
[2025-01-17 23:17:40 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][280/312]	eta 0:00:14 lr 0.003891	time 0.4428 (0.4665)	model_time 0.4423 (0.4611)	loss 4.0203 (3.9164)	grad_norm 1.5007 (1.6406/1.0425)	mem 16099MB
[2025-01-17 23:17:45 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][290/312]	eta 0:00:10 lr 0.003890	time 0.4495 (0.4664)	model_time 0.4490 (0.4611)	loss 3.7788 (3.9081)	grad_norm 1.1698 (1.6395/1.0303)	mem 16099MB
[2025-01-17 23:17:50 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][300/312]	eta 0:00:05 lr 0.003890	time 0.4438 (0.4659)	model_time 0.4437 (0.4607)	loss 2.4848 (3.9098)	grad_norm 1.3094 (1.6249/1.0175)	mem 16099MB
[2025-01-17 23:17:54 internimage_t_1k_224] (main.py 510): INFO Train: [31/300][310/312]	eta 0:00:00 lr 0.003890	time 0.4450 (0.4652)	model_time 0.4449 (0.4601)	loss 4.3361 (3.9173)	grad_norm 0.8836 (1.6146/1.0170)	mem 16099MB
[2025-01-17 23:17:54 internimage_t_1k_224] (main.py 519): INFO EPOCH 31 training takes 0:02:25
[2025-01-17 23:17:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_31.pth saving......
[2025-01-17 23:17:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_31.pth saved !!!
[2025-01-17 23:18:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.634 (7.634)	Loss 1.1454 (1.1454)	Acc@1 73.706 (73.706)	Acc@5 92.651 (92.651)	Mem 16099MB
[2025-01-17 23:18:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.031)	Loss 1.6211 (1.3650)	Acc@1 63.159 (69.609)	Acc@5 85.767 (89.870)	Mem 16099MB
[2025-01-17 23:18:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:31] * Acc@1 69.556 Acc@5 89.959
[2025-01-17 23:18:07 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 69.6%
[2025-01-17 23:18:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:18:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:18:08 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 69.56%
[2025-01-17 23:18:16 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.475 (7.475)	Loss 6.5150 (6.5150)	Acc@1 0.537 (0.537)	Acc@5 3.833 (3.833)	Mem 16099MB
[2025-01-17 23:18:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.993)	Loss 6.4545 (6.4482)	Acc@1 1.709 (1.110)	Acc@5 4.761 (4.987)	Mem 16099MB
[2025-01-17 23:18:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:31] * Acc@1 1.362 Acc@5 5.462
[2025-01-17 23:18:19 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 1.4%
[2025-01-17 23:18:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:18:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:18:21 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 1.36%
[2025-01-17 23:18:22 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][0/312]	eta 0:09:13 lr 0.003890	time 1.7725 (1.7725)	model_time 0.4752 (0.4752)	loss 3.2836 (3.2836)	grad_norm 1.5914 (1.5914/0.0000)	mem 16099MB
[2025-01-17 23:18:27 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][10/312]	eta 0:03:03 lr 0.003890	time 0.4516 (0.6086)	model_time 0.4514 (0.4779)	loss 3.0996 (3.6874)	grad_norm 1.2787 (2.2556/0.9340)	mem 16099MB
[2025-01-17 23:18:32 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][20/312]	eta 0:02:37 lr 0.003889	time 0.4560 (0.5397)	model_time 0.4559 (0.4711)	loss 4.7051 (3.7758)	grad_norm 1.7769 (2.3329/1.0550)	mem 16099MB
[2025-01-17 23:18:37 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][30/312]	eta 0:02:25 lr 0.003889	time 0.4511 (0.5148)	model_time 0.4509 (0.4682)	loss 4.1641 (3.8858)	grad_norm 0.8833 (1.9301/1.0557)	mem 16099MB
[2025-01-17 23:18:41 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][40/312]	eta 0:02:15 lr 0.003889	time 0.4522 (0.4999)	model_time 0.4520 (0.4646)	loss 4.1880 (3.9181)	grad_norm 1.7582 (1.7934/0.9701)	mem 16099MB
[2025-01-17 23:18:46 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][50/312]	eta 0:02:08 lr 0.003889	time 0.4639 (0.4906)	model_time 0.4637 (0.4621)	loss 4.2988 (3.9726)	grad_norm 1.1223 (1.6732/0.9094)	mem 16099MB
[2025-01-17 23:18:50 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][60/312]	eta 0:02:02 lr 0.003889	time 0.5356 (0.4858)	model_time 0.5355 (0.4619)	loss 3.6133 (3.9740)	grad_norm 2.8063 (1.6437/0.8686)	mem 16099MB
[2025-01-17 23:18:55 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][70/312]	eta 0:01:56 lr 0.003888	time 0.4455 (0.4809)	model_time 0.4453 (0.4603)	loss 4.8295 (3.9701)	grad_norm 1.9532 (1.6743/0.8444)	mem 16099MB
[2025-01-17 23:18:59 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][80/312]	eta 0:01:51 lr 0.003888	time 0.4493 (0.4786)	model_time 0.4490 (0.4605)	loss 4.2267 (3.9894)	grad_norm 1.0173 (1.6768/0.8280)	mem 16099MB
[2025-01-17 23:19:04 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][90/312]	eta 0:01:45 lr 0.003888	time 0.5392 (0.4767)	model_time 0.5390 (0.4605)	loss 4.8158 (3.9888)	grad_norm 0.9112 (1.6537/0.7945)	mem 16099MB
[2025-01-17 23:19:09 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][100/312]	eta 0:01:40 lr 0.003888	time 0.4518 (0.4744)	model_time 0.4516 (0.4599)	loss 3.5449 (3.9928)	grad_norm 0.7691 (1.6198/0.7674)	mem 16099MB
[2025-01-17 23:19:13 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][110/312]	eta 0:01:35 lr 0.003887	time 0.4610 (0.4735)	model_time 0.4605 (0.4602)	loss 4.5637 (3.9882)	grad_norm 1.5720 (1.5946/0.7415)	mem 16099MB
[2025-01-17 23:19:18 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][120/312]	eta 0:01:30 lr 0.003887	time 0.5412 (0.4738)	model_time 0.5410 (0.4616)	loss 4.0664 (3.9690)	grad_norm 0.9681 (1.6257/0.7948)	mem 16099MB
[2025-01-17 23:19:23 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][130/312]	eta 0:01:26 lr 0.003887	time 0.4457 (0.4740)	model_time 0.4452 (0.4627)	loss 4.1737 (3.9872)	grad_norm 0.9811 (1.6325/0.8302)	mem 16099MB
[2025-01-17 23:19:28 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][140/312]	eta 0:01:21 lr 0.003887	time 0.5652 (0.4748)	model_time 0.5650 (0.4642)	loss 4.3404 (3.9905)	grad_norm 0.8759 (1.6261/0.8214)	mem 16099MB
[2025-01-17 23:19:32 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][150/312]	eta 0:01:16 lr 0.003887	time 0.4569 (0.4733)	model_time 0.4564 (0.4634)	loss 4.0288 (3.9809)	grad_norm 1.1949 (1.6135/0.8002)	mem 16099MB
[2025-01-17 23:19:37 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][160/312]	eta 0:01:11 lr 0.003886	time 0.4648 (0.4719)	model_time 0.4646 (0.4626)	loss 4.9048 (3.9728)	grad_norm 0.9745 (1.5892/0.7845)	mem 16099MB
[2025-01-17 23:19:41 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][170/312]	eta 0:01:06 lr 0.003886	time 0.4466 (0.4709)	model_time 0.4461 (0.4622)	loss 2.8924 (3.9653)	grad_norm 1.5622 (1.6020/0.7764)	mem 16099MB
[2025-01-17 23:19:46 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][180/312]	eta 0:01:02 lr 0.003886	time 0.4632 (0.4706)	model_time 0.4627 (0.4623)	loss 4.3887 (3.9471)	grad_norm 1.4614 (1.6383/0.7914)	mem 16099MB
[2025-01-17 23:19:50 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][190/312]	eta 0:00:57 lr 0.003886	time 0.4487 (0.4696)	model_time 0.4482 (0.4617)	loss 5.0620 (3.9613)	grad_norm 1.1615 (1.6357/0.7775)	mem 16099MB
[2025-01-17 23:19:55 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][200/312]	eta 0:00:52 lr 0.003885	time 0.4555 (0.4692)	model_time 0.4548 (0.4616)	loss 4.3923 (3.9575)	grad_norm 1.6946 (1.6073/0.7699)	mem 16099MB
[2025-01-17 23:20:00 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][210/312]	eta 0:00:47 lr 0.003885	time 0.4519 (0.4689)	model_time 0.4517 (0.4617)	loss 3.4960 (3.9576)	grad_norm 1.3882 (1.5960/0.7666)	mem 16099MB
[2025-01-17 23:20:04 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][220/312]	eta 0:00:43 lr 0.003885	time 0.4373 (0.4682)	model_time 0.4368 (0.4613)	loss 3.7704 (3.9658)	grad_norm 2.3102 (1.5925/0.7579)	mem 16099MB
[2025-01-17 23:20:09 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][230/312]	eta 0:00:38 lr 0.003885	time 0.4495 (0.4679)	model_time 0.4490 (0.4613)	loss 2.9920 (3.9594)	grad_norm 1.3729 (1.5817/0.7463)	mem 16099MB
[2025-01-17 23:20:13 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][240/312]	eta 0:00:33 lr 0.003885	time 0.4786 (0.4674)	model_time 0.4784 (0.4610)	loss 4.1268 (3.9513)	grad_norm 1.0953 (1.5697/0.7366)	mem 16099MB
[2025-01-17 23:20:18 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][250/312]	eta 0:00:28 lr 0.003884	time 0.4452 (0.4670)	model_time 0.4447 (0.4609)	loss 4.0762 (3.9411)	grad_norm 1.2007 (1.5969/0.7730)	mem 16099MB
[2025-01-17 23:20:23 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][260/312]	eta 0:00:24 lr 0.003884	time 0.4613 (0.4673)	model_time 0.4609 (0.4614)	loss 4.9064 (3.9432)	grad_norm 1.1262 (1.6190/0.7976)	mem 16099MB
[2025-01-17 23:20:27 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][270/312]	eta 0:00:19 lr 0.003884	time 0.4503 (0.4667)	model_time 0.4501 (0.4610)	loss 4.1612 (3.9618)	grad_norm 0.9469 (1.6162/0.7917)	mem 16099MB
[2025-01-17 23:20:32 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][280/312]	eta 0:00:14 lr 0.003884	time 0.4464 (0.4661)	model_time 0.4459 (0.4606)	loss 5.0041 (3.9715)	grad_norm 1.3737 (1.6080/0.7799)	mem 16099MB
[2025-01-17 23:20:36 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][290/312]	eta 0:00:10 lr 0.003883	time 0.4614 (0.4659)	model_time 0.4612 (0.4605)	loss 3.2192 (3.9537)	grad_norm 2.3124 (1.6267/0.8017)	mem 16099MB
[2025-01-17 23:20:41 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][300/312]	eta 0:00:05 lr 0.003883	time 0.4364 (0.4659)	model_time 0.4363 (0.4607)	loss 4.5121 (3.9578)	grad_norm 1.3314 (1.6377/0.8021)	mem 16099MB
[2025-01-17 23:20:46 internimage_t_1k_224] (main.py 510): INFO Train: [32/300][310/312]	eta 0:00:00 lr 0.003883	time 0.5123 (0.4663)	model_time 0.5122 (0.4612)	loss 3.3668 (3.9561)	grad_norm 2.4622 (1.6266/0.7873)	mem 16099MB
[2025-01-17 23:20:46 internimage_t_1k_224] (main.py 519): INFO EPOCH 32 training takes 0:02:25
[2025-01-17 23:20:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_32.pth saving......
[2025-01-17 23:20:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_32.pth saved !!!
[2025-01-17 23:20:55 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.468 (7.468)	Loss 1.2168 (1.2168)	Acc@1 73.608 (73.608)	Acc@5 92.749 (92.749)	Mem 16099MB
[2025-01-17 23:20:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.002)	Loss 1.7459 (1.4430)	Acc@1 63.281 (69.735)	Acc@5 85.742 (89.935)	Mem 16099MB
[2025-01-17 23:20:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:32] * Acc@1 69.786 Acc@5 90.079
[2025-01-17 23:20:58 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 69.8%
[2025-01-17 23:20:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:21:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:21:00 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 69.79%
[2025-01-17 23:21:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.265 (7.265)	Loss 6.4937 (6.4937)	Acc@1 0.610 (0.610)	Acc@5 3.882 (3.882)	Mem 16099MB
[2025-01-17 23:21:11 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.992)	Loss 6.3693 (6.3743)	Acc@1 2.124 (1.523)	Acc@5 6.055 (6.146)	Mem 16099MB
[2025-01-17 23:21:11 internimage_t_1k_224] (main.py 575): INFO [Epoch:32] * Acc@1 1.781 Acc@5 6.654
[2025-01-17 23:21:11 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 1.8%
[2025-01-17 23:21:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:21:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:21:12 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 1.78%
[2025-01-17 23:21:14 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][0/312]	eta 0:10:45 lr 0.003883	time 2.0684 (2.0684)	model_time 0.7207 (0.7207)	loss 3.8166 (3.8166)	grad_norm 1.1774 (1.1774/0.0000)	mem 16099MB
[2025-01-17 23:21:19 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][10/312]	eta 0:03:04 lr 0.003883	time 0.4706 (0.6122)	model_time 0.4705 (0.4893)	loss 4.6334 (4.2675)	grad_norm 1.3663 (1.1746/0.2900)	mem 16099MB
[2025-01-17 23:21:23 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][20/312]	eta 0:02:37 lr 0.003882	time 0.4490 (0.5389)	model_time 0.4488 (0.4744)	loss 4.2171 (3.9154)	grad_norm 1.4660 (1.3344/0.3877)	mem 16099MB
[2025-01-17 23:21:28 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][30/312]	eta 0:02:24 lr 0.003882	time 0.4502 (0.5116)	model_time 0.4500 (0.4678)	loss 4.1018 (3.8677)	grad_norm 1.2006 (1.3900/0.5163)	mem 16099MB
[2025-01-17 23:21:32 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][40/312]	eta 0:02:15 lr 0.003882	time 0.4527 (0.4982)	model_time 0.4522 (0.4649)	loss 4.2407 (3.8666)	grad_norm 1.1364 (1.3456/0.4679)	mem 16099MB
[2025-01-17 23:21:37 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][50/312]	eta 0:02:09 lr 0.003882	time 0.4393 (0.4927)	model_time 0.4390 (0.4659)	loss 3.8209 (3.9023)	grad_norm 1.3369 (1.3991/0.4709)	mem 16099MB
[2025-01-17 23:21:42 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][60/312]	eta 0:02:03 lr 0.003882	time 0.4647 (0.4883)	model_time 0.4642 (0.4658)	loss 4.1956 (3.9156)	grad_norm 2.3269 (1.5644/0.7336)	mem 16099MB
[2025-01-17 23:21:46 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][70/312]	eta 0:01:57 lr 0.003881	time 0.4584 (0.4844)	model_time 0.4582 (0.4651)	loss 4.8396 (3.9116)	grad_norm 1.4474 (1.5413/0.7019)	mem 16099MB
[2025-01-17 23:21:51 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][80/312]	eta 0:01:51 lr 0.003881	time 0.4427 (0.4824)	model_time 0.4424 (0.4654)	loss 3.3206 (3.8755)	grad_norm 1.4096 (1.5182/0.6720)	mem 16099MB
[2025-01-17 23:21:56 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][90/312]	eta 0:01:46 lr 0.003881	time 0.4429 (0.4817)	model_time 0.4424 (0.4665)	loss 3.1669 (3.8418)	grad_norm 2.0157 (1.5226/0.6409)	mem 16099MB
[2025-01-17 23:22:00 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][100/312]	eta 0:01:41 lr 0.003881	time 0.4346 (0.4788)	model_time 0.4340 (0.4651)	loss 3.4487 (3.8635)	grad_norm 1.6380 (1.5406/0.6283)	mem 16099MB
[2025-01-17 23:22:05 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][110/312]	eta 0:01:36 lr 0.003880	time 0.4435 (0.4782)	model_time 0.4430 (0.4657)	loss 3.4383 (3.8455)	grad_norm 1.0365 (1.5596/0.6561)	mem 16099MB
[2025-01-17 23:22:09 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][120/312]	eta 0:01:31 lr 0.003880	time 0.4476 (0.4767)	model_time 0.4471 (0.4652)	loss 3.3577 (3.8618)	grad_norm 1.6060 (1.5350/0.6460)	mem 16099MB
[2025-01-17 23:22:14 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][130/312]	eta 0:01:26 lr 0.003880	time 0.4511 (0.4756)	model_time 0.4509 (0.4649)	loss 3.3061 (3.8575)	grad_norm 1.3250 (1.5339/0.6300)	mem 16099MB
[2025-01-17 23:22:19 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][140/312]	eta 0:01:21 lr 0.003880	time 0.4311 (0.4740)	model_time 0.4309 (0.4641)	loss 3.4600 (3.8460)	grad_norm 1.2842 (1.5937/0.7885)	mem 16099MB
[2025-01-17 23:22:23 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][150/312]	eta 0:01:16 lr 0.003880	time 0.4549 (0.4736)	model_time 0.4544 (0.4643)	loss 3.9055 (3.8477)	grad_norm 1.1531 (1.5875/0.7713)	mem 16099MB
[2025-01-17 23:22:28 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][160/312]	eta 0:01:11 lr 0.003879	time 0.4574 (0.4723)	model_time 0.4572 (0.4635)	loss 2.6332 (3.8498)	grad_norm 1.0710 (1.5541/0.7616)	mem 16099MB
[2025-01-17 23:22:32 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][170/312]	eta 0:01:06 lr 0.003879	time 0.4547 (0.4711)	model_time 0.4542 (0.4628)	loss 4.2273 (3.8422)	grad_norm 3.5823 (1.5470/0.7616)	mem 16099MB
[2025-01-17 23:22:37 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][180/312]	eta 0:01:02 lr 0.003879	time 0.4655 (0.4701)	model_time 0.4650 (0.4622)	loss 4.2068 (3.8630)	grad_norm 1.9191 (1.6134/0.8537)	mem 16099MB
[2025-01-17 23:22:41 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][190/312]	eta 0:00:57 lr 0.003879	time 0.4537 (0.4693)	model_time 0.4532 (0.4619)	loss 4.2225 (3.8683)	grad_norm 0.7749 (1.6055/0.8371)	mem 16099MB
[2025-01-17 23:22:46 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][200/312]	eta 0:00:52 lr 0.003878	time 0.4467 (0.4683)	model_time 0.4465 (0.4612)	loss 2.8208 (3.8592)	grad_norm 4.1177 (1.6125/0.8445)	mem 16099MB
[2025-01-17 23:22:50 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][210/312]	eta 0:00:47 lr 0.003878	time 0.4820 (0.4676)	model_time 0.4815 (0.4608)	loss 4.0210 (3.8741)	grad_norm 1.6821 (1.5984/0.8327)	mem 16099MB
[2025-01-17 23:22:55 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][220/312]	eta 0:00:42 lr 0.003878	time 0.4476 (0.4670)	model_time 0.4472 (0.4605)	loss 3.7197 (3.8744)	grad_norm 3.4015 (1.6192/0.8348)	mem 16099MB
[2025-01-17 23:23:00 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][230/312]	eta 0:00:38 lr 0.003878	time 0.4412 (0.4670)	model_time 0.4407 (0.4608)	loss 3.7924 (3.8720)	grad_norm 0.9531 (1.6240/0.8279)	mem 16099MB
[2025-01-17 23:23:04 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][240/312]	eta 0:00:33 lr 0.003877	time 0.4478 (0.4665)	model_time 0.4473 (0.4605)	loss 4.6591 (3.8733)	grad_norm 2.7746 (1.6375/0.8256)	mem 16099MB
[2025-01-17 23:23:09 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][250/312]	eta 0:00:28 lr 0.003877	time 0.4481 (0.4667)	model_time 0.4479 (0.4609)	loss 3.5659 (3.8681)	grad_norm 2.0583 (1.6423/0.8141)	mem 16099MB
[2025-01-17 23:23:14 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][260/312]	eta 0:00:24 lr 0.003877	time 0.4461 (0.4665)	model_time 0.4456 (0.4610)	loss 3.7854 (3.8735)	grad_norm 0.9275 (1.6272/0.8032)	mem 16099MB
[2025-01-17 23:23:18 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][270/312]	eta 0:00:19 lr 0.003877	time 0.4520 (0.4662)	model_time 0.4515 (0.4608)	loss 2.6347 (3.8543)	grad_norm 1.0276 (1.6208/0.7925)	mem 16099MB
[2025-01-17 23:23:23 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][280/312]	eta 0:00:14 lr 0.003877	time 0.4473 (0.4670)	model_time 0.4470 (0.4618)	loss 4.0199 (3.8557)	grad_norm 2.3989 (1.6185/0.7855)	mem 16099MB
[2025-01-17 23:23:28 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][290/312]	eta 0:00:10 lr 0.003876	time 0.4441 (0.4667)	model_time 0.4436 (0.4617)	loss 3.6501 (3.8621)	grad_norm 1.6250 (1.6079/0.7764)	mem 16099MB
[2025-01-17 23:23:32 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][300/312]	eta 0:00:05 lr 0.003876	time 0.4369 (0.4661)	model_time 0.4368 (0.4612)	loss 2.8587 (3.8507)	grad_norm 1.3145 (1.6086/0.7708)	mem 16099MB
[2025-01-17 23:23:37 internimage_t_1k_224] (main.py 510): INFO Train: [33/300][310/312]	eta 0:00:00 lr 0.003876	time 0.4382 (0.4655)	model_time 0.4380 (0.4607)	loss 4.1209 (3.8466)	grad_norm 1.3726 (1.6249/0.7745)	mem 16099MB
[2025-01-17 23:23:37 internimage_t_1k_224] (main.py 519): INFO EPOCH 33 training takes 0:02:25
[2025-01-17 23:23:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_33.pth saving......
[2025-01-17 23:23:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_33.pth saved !!!
[2025-01-17 23:23:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.626 (7.626)	Loss 1.1632 (1.1632)	Acc@1 74.438 (74.438)	Acc@5 93.042 (93.042)	Mem 16099MB
[2025-01-17 23:23:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.007)	Loss 1.6866 (1.4097)	Acc@1 64.282 (69.804)	Acc@5 85.962 (89.970)	Mem 16099MB
[2025-01-17 23:23:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:33] * Acc@1 69.896 Acc@5 90.099
[2025-01-17 23:23:49 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 69.9%
[2025-01-17 23:23:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:23:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:23:51 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 69.90%
[2025-01-17 23:23:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.491 (7.491)	Loss 6.4580 (6.4580)	Acc@1 0.806 (0.806)	Acc@5 4.492 (4.492)	Mem 16099MB
[2025-01-17 23:24:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.995)	Loss 6.2729 (6.2881)	Acc@1 2.808 (2.089)	Acc@5 7.788 (7.659)	Mem 16099MB
[2025-01-17 23:24:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:33] * Acc@1 2.343 Acc@5 8.189
[2025-01-17 23:24:02 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 2.3%
[2025-01-17 23:24:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:24:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:24:03 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 2.34%
[2025-01-17 23:24:06 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][0/312]	eta 0:12:58 lr 0.003876	time 2.4937 (2.4937)	model_time 0.4806 (0.4806)	loss 4.1404 (4.1404)	grad_norm 1.4115 (1.4115/0.0000)	mem 16099MB
[2025-01-17 23:24:10 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][10/312]	eta 0:03:19 lr 0.003876	time 0.4438 (0.6596)	model_time 0.4434 (0.4762)	loss 3.6687 (3.8055)	grad_norm 1.5425 (1.2229/0.2948)	mem 16099MB
[2025-01-17 23:24:15 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][20/312]	eta 0:02:44 lr 0.003875	time 0.4419 (0.5619)	model_time 0.4418 (0.4656)	loss 4.5017 (3.7850)	grad_norm 0.9350 (1.2057/0.3495)	mem 16099MB
[2025-01-17 23:24:20 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][30/312]	eta 0:02:31 lr 0.003875	time 0.4402 (0.5374)	model_time 0.4397 (0.4720)	loss 3.6593 (3.9442)	grad_norm 1.5604 (1.3547/0.4797)	mem 16099MB
[2025-01-17 23:24:24 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][40/312]	eta 0:02:21 lr 0.003875	time 0.4499 (0.5220)	model_time 0.4497 (0.4725)	loss 4.3546 (3.8959)	grad_norm 0.7888 (1.4324/0.5463)	mem 16099MB
[2025-01-17 23:24:29 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][50/312]	eta 0:02:13 lr 0.003875	time 0.4420 (0.5106)	model_time 0.4417 (0.4708)	loss 3.5547 (3.8413)	grad_norm 1.8755 (1.4748/0.5573)	mem 16099MB
[2025-01-17 23:24:34 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][60/312]	eta 0:02:06 lr 0.003874	time 0.4486 (0.5025)	model_time 0.4484 (0.4691)	loss 3.8662 (3.8500)	grad_norm 2.0130 (1.5334/0.5582)	mem 16099MB
[2025-01-17 23:24:38 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][70/312]	eta 0:02:00 lr 0.003874	time 0.4977 (0.4959)	model_time 0.4974 (0.4672)	loss 4.1318 (3.8494)	grad_norm 1.2029 (1.6244/0.7710)	mem 16099MB
[2025-01-17 23:24:43 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][80/312]	eta 0:01:53 lr 0.003874	time 0.4489 (0.4904)	model_time 0.4487 (0.4651)	loss 4.4505 (3.9022)	grad_norm 1.0069 (1.5560/0.7481)	mem 16099MB
[2025-01-17 23:24:47 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][90/312]	eta 0:01:48 lr 0.003874	time 0.4567 (0.4872)	model_time 0.4565 (0.4647)	loss 4.1460 (3.9070)	grad_norm 4.1420 (1.5666/0.7642)	mem 16099MB
[2025-01-17 23:24:52 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][100/312]	eta 0:01:42 lr 0.003873	time 0.4538 (0.4851)	model_time 0.4536 (0.4648)	loss 3.4074 (3.9085)	grad_norm 2.0595 (1.6716/1.0665)	mem 16099MB
[2025-01-17 23:24:57 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][110/312]	eta 0:01:37 lr 0.003873	time 0.4465 (0.4823)	model_time 0.4463 (0.4638)	loss 2.8554 (3.8953)	grad_norm 1.3094 (1.6481/1.0317)	mem 16099MB
[2025-01-17 23:25:01 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][120/312]	eta 0:01:32 lr 0.003873	time 0.4637 (0.4805)	model_time 0.4635 (0.4635)	loss 4.1881 (3.8803)	grad_norm 1.4619 (1.6161/0.9953)	mem 16099MB
[2025-01-17 23:25:06 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][130/312]	eta 0:01:27 lr 0.003873	time 0.4463 (0.4798)	model_time 0.4462 (0.4640)	loss 4.8199 (3.9014)	grad_norm 1.6331 (1.5895/0.9654)	mem 16099MB
[2025-01-17 23:25:11 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][140/312]	eta 0:01:22 lr 0.003873	time 0.4402 (0.4783)	model_time 0.4398 (0.4637)	loss 3.5080 (3.8986)	grad_norm 2.5965 (1.5958/0.9430)	mem 16099MB
[2025-01-17 23:25:15 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][150/312]	eta 0:01:17 lr 0.003872	time 0.4516 (0.4770)	model_time 0.4515 (0.4633)	loss 2.8530 (3.8988)	grad_norm 2.2243 (1.6046/0.9263)	mem 16099MB
[2025-01-17 23:25:20 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][160/312]	eta 0:01:12 lr 0.003872	time 0.4454 (0.4767)	model_time 0.4452 (0.4639)	loss 4.0694 (3.8912)	grad_norm 2.6456 (1.6088/0.9135)	mem 16099MB
[2025-01-17 23:25:24 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][170/312]	eta 0:01:07 lr 0.003872	time 0.4491 (0.4753)	model_time 0.4490 (0.4632)	loss 3.7944 (3.8826)	grad_norm 2.7116 (1.6079/0.8942)	mem 16099MB
[2025-01-17 23:25:29 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][180/312]	eta 0:01:02 lr 0.003872	time 0.4734 (0.4751)	model_time 0.4730 (0.4636)	loss 4.2321 (3.8920)	grad_norm 0.9687 (1.6356/0.9110)	mem 16099MB
[2025-01-17 23:25:34 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][190/312]	eta 0:00:57 lr 0.003871	time 0.4440 (0.4738)	model_time 0.4438 (0.4629)	loss 3.0368 (3.8703)	grad_norm 1.3244 (1.6367/0.9005)	mem 16099MB
[2025-01-17 23:25:38 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][200/312]	eta 0:00:52 lr 0.003871	time 0.4481 (0.4730)	model_time 0.4479 (0.4626)	loss 3.9642 (3.8713)	grad_norm 0.7937 (1.6094/0.8874)	mem 16099MB
[2025-01-17 23:25:43 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][210/312]	eta 0:00:48 lr 0.003871	time 0.4463 (0.4733)	model_time 0.4461 (0.4634)	loss 3.9871 (3.8717)	grad_norm 1.8866 (1.5990/0.8730)	mem 16099MB
[2025-01-17 23:25:47 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][220/312]	eta 0:00:43 lr 0.003871	time 0.4505 (0.4723)	model_time 0.4503 (0.4628)	loss 3.2524 (3.8614)	grad_norm 1.6988 (1.6020/0.8584)	mem 16099MB
[2025-01-17 23:25:52 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][230/312]	eta 0:00:38 lr 0.003870	time 0.4457 (0.4714)	model_time 0.4455 (0.4623)	loss 4.3119 (3.8686)	grad_norm 2.0462 (1.6044/0.8427)	mem 16099MB
[2025-01-17 23:25:57 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][240/312]	eta 0:00:33 lr 0.003870	time 0.4573 (0.4707)	model_time 0.4572 (0.4620)	loss 4.5538 (3.8711)	grad_norm 2.3642 (1.6087/0.8465)	mem 16099MB
[2025-01-17 23:26:01 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][250/312]	eta 0:00:29 lr 0.003870	time 0.4552 (0.4706)	model_time 0.4551 (0.4622)	loss 4.2659 (3.8728)	grad_norm 0.8413 (1.6177/0.8615)	mem 16099MB
[2025-01-17 23:26:06 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][260/312]	eta 0:00:24 lr 0.003870	time 0.4460 (0.4706)	model_time 0.4455 (0.4625)	loss 3.8687 (3.8816)	grad_norm 1.1095 (1.6060/0.8504)	mem 16099MB
[2025-01-17 23:26:11 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][270/312]	eta 0:00:19 lr 0.003869	time 0.4397 (0.4713)	model_time 0.4392 (0.4635)	loss 4.8288 (3.8809)	grad_norm 1.9341 (1.5951/0.8383)	mem 16099MB
[2025-01-17 23:26:15 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][280/312]	eta 0:00:15 lr 0.003869	time 0.4525 (0.4709)	model_time 0.4521 (0.4634)	loss 4.1817 (3.8835)	grad_norm 2.3341 (1.6270/0.8828)	mem 16099MB
[2025-01-17 23:26:20 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][290/312]	eta 0:00:10 lr 0.003869	time 0.4479 (0.4709)	model_time 0.4477 (0.4636)	loss 3.6776 (3.8801)	grad_norm 1.0118 (1.6187/0.8728)	mem 16099MB
[2025-01-17 23:26:25 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][300/312]	eta 0:00:05 lr 0.003869	time 0.4377 (0.4705)	model_time 0.4377 (0.4635)	loss 3.7002 (3.8809)	grad_norm 1.1075 (1.6206/0.8794)	mem 16099MB
[2025-01-17 23:26:29 internimage_t_1k_224] (main.py 510): INFO Train: [34/300][310/312]	eta 0:00:00 lr 0.003869	time 0.4386 (0.4696)	model_time 0.4385 (0.4627)	loss 4.2967 (3.8702)	grad_norm 1.5919 (1.6313/0.8774)	mem 16099MB
[2025-01-17 23:26:30 internimage_t_1k_224] (main.py 519): INFO EPOCH 34 training takes 0:02:26
[2025-01-17 23:26:30 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_34.pth saving......
[2025-01-17 23:26:31 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_34.pth saved !!!
[2025-01-17 23:26:38 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.412 (7.412)	Loss 1.1737 (1.1737)	Acc@1 74.194 (74.194)	Acc@5 92.944 (92.944)	Mem 16099MB
[2025-01-17 23:26:42 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.997)	Loss 1.6200 (1.3718)	Acc@1 64.575 (70.408)	Acc@5 87.305 (90.403)	Mem 16099MB
[2025-01-17 23:26:42 internimage_t_1k_224] (main.py 575): INFO [Epoch:34] * Acc@1 70.435 Acc@5 90.497
[2025-01-17 23:26:42 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 70.4%
[2025-01-17 23:26:42 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:26:43 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:26:43 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 70.44%
[2025-01-17 23:26:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.447 (7.447)	Loss 6.4060 (6.4060)	Acc@1 1.196 (1.196)	Acc@5 5.151 (5.151)	Mem 16099MB
[2025-01-17 23:26:54 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.004)	Loss 6.1650 (6.1886)	Acc@1 3.809 (2.805)	Acc@5 9.619 (9.513)	Mem 16099MB
[2025-01-17 23:26:54 internimage_t_1k_224] (main.py 575): INFO [Epoch:34] * Acc@1 3.057 Acc@5 10.045
[2025-01-17 23:26:54 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 3.1%
[2025-01-17 23:26:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:26:55 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:26:55 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 3.06%
[2025-01-17 23:26:58 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][0/312]	eta 0:10:38 lr 0.003868	time 2.0464 (2.0464)	model_time 0.4769 (0.4769)	loss 3.2503 (3.2503)	grad_norm 1.4748 (1.4748/0.0000)	mem 16099MB
[2025-01-17 23:27:02 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][10/312]	eta 0:03:07 lr 0.003868	time 0.4418 (0.6216)	model_time 0.4413 (0.4786)	loss 3.1233 (3.7748)	grad_norm 1.8837 (1.2901/0.2760)	mem 16099MB
[2025-01-17 23:27:07 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][20/312]	eta 0:02:39 lr 0.003868	time 0.4494 (0.5455)	model_time 0.4490 (0.4704)	loss 3.7616 (3.7906)	grad_norm 1.2655 (1.5115/0.7334)	mem 16099MB
[2025-01-17 23:27:12 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][30/312]	eta 0:02:26 lr 0.003868	time 0.5017 (0.5193)	model_time 0.5016 (0.4683)	loss 4.3311 (3.8947)	grad_norm 1.1540 (1.6268/0.7511)	mem 16099MB
[2025-01-17 23:27:16 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][40/312]	eta 0:02:17 lr 0.003868	time 0.4476 (0.5038)	model_time 0.4474 (0.4652)	loss 4.1216 (3.8553)	grad_norm 1.3427 (1.6764/0.8162)	mem 16099MB
[2025-01-17 23:27:21 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][50/312]	eta 0:02:09 lr 0.003867	time 0.4592 (0.4942)	model_time 0.4591 (0.4631)	loss 2.8615 (3.8832)	grad_norm 1.1735 (1.5812/0.7623)	mem 16099MB
[2025-01-17 23:27:25 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][60/312]	eta 0:02:03 lr 0.003867	time 0.4758 (0.4892)	model_time 0.4754 (0.4631)	loss 4.1027 (3.9055)	grad_norm 1.5625 (1.5938/0.7480)	mem 16099MB
[2025-01-17 23:27:30 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][70/312]	eta 0:01:57 lr 0.003867	time 0.4602 (0.4849)	model_time 0.4597 (0.4625)	loss 2.6918 (3.8603)	grad_norm 2.1465 (1.6131/0.7280)	mem 16099MB
[2025-01-17 23:27:34 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][80/312]	eta 0:01:51 lr 0.003867	time 0.4497 (0.4809)	model_time 0.4495 (0.4612)	loss 4.0407 (3.8739)	grad_norm 2.3470 (1.6217/0.7161)	mem 16099MB
[2025-01-17 23:27:39 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][90/312]	eta 0:01:46 lr 0.003866	time 0.4543 (0.4794)	model_time 0.4542 (0.4618)	loss 4.1107 (3.8940)	grad_norm 0.9320 (1.6255/0.6988)	mem 16099MB
[2025-01-17 23:27:44 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][100/312]	eta 0:01:41 lr 0.003866	time 0.4501 (0.4797)	model_time 0.4497 (0.4638)	loss 3.5291 (3.9144)	grad_norm 1.1400 (1.6028/0.6771)	mem 16099MB
[2025-01-17 23:27:49 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][110/312]	eta 0:01:36 lr 0.003866	time 0.5258 (0.4789)	model_time 0.5257 (0.4644)	loss 4.3282 (3.9160)	grad_norm 1.8824 (1.6424/0.6968)	mem 16099MB
[2025-01-17 23:27:53 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][120/312]	eta 0:01:31 lr 0.003866	time 0.5348 (0.4782)	model_time 0.5347 (0.4649)	loss 3.8865 (3.8948)	grad_norm 0.9048 (1.6475/0.6959)	mem 16099MB
[2025-01-17 23:27:58 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][130/312]	eta 0:01:26 lr 0.003865	time 0.4451 (0.4761)	model_time 0.4450 (0.4638)	loss 3.2294 (3.9063)	grad_norm 1.8532 (1.6604/0.7162)	mem 16099MB
[2025-01-17 23:28:03 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][140/312]	eta 0:01:21 lr 0.003865	time 0.5039 (0.4759)	model_time 0.5034 (0.4644)	loss 4.0991 (3.8986)	grad_norm 1.4039 (1.6697/0.7165)	mem 16099MB
[2025-01-17 23:28:07 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][150/312]	eta 0:01:17 lr 0.003865	time 0.4549 (0.4764)	model_time 0.4548 (0.4657)	loss 4.3588 (3.9073)	grad_norm 2.4940 (1.6655/0.7036)	mem 16099MB
[2025-01-17 23:28:12 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][160/312]	eta 0:01:12 lr 0.003865	time 0.4865 (0.4764)	model_time 0.4863 (0.4663)	loss 3.2911 (3.8910)	grad_norm 1.6004 (1.6792/0.7046)	mem 16099MB
[2025-01-17 23:28:17 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][170/312]	eta 0:01:07 lr 0.003864	time 0.4754 (0.4756)	model_time 0.4752 (0.4661)	loss 4.1903 (3.8815)	grad_norm 2.1646 (1.6778/0.6922)	mem 16099MB
[2025-01-17 23:28:21 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][180/312]	eta 0:01:02 lr 0.003864	time 0.4519 (0.4750)	model_time 0.4518 (0.4660)	loss 3.0738 (3.8864)	grad_norm 1.5174 (1.6516/0.6905)	mem 16099MB
[2025-01-17 23:28:26 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][190/312]	eta 0:00:57 lr 0.003864	time 0.4406 (0.4740)	model_time 0.4402 (0.4654)	loss 3.4497 (3.8762)	grad_norm 3.3173 (1.6439/0.6893)	mem 16099MB
[2025-01-17 23:28:31 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][200/312]	eta 0:00:52 lr 0.003864	time 0.4631 (0.4730)	model_time 0.4627 (0.4648)	loss 4.0170 (3.8674)	grad_norm 2.2579 (1.6702/0.7096)	mem 16099MB
[2025-01-17 23:28:35 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][210/312]	eta 0:00:48 lr 0.003863	time 0.4454 (0.4725)	model_time 0.4452 (0.4647)	loss 4.5860 (3.8768)	grad_norm 1.3353 (1.6748/0.7066)	mem 16099MB
[2025-01-17 23:28:40 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][220/312]	eta 0:00:43 lr 0.003863	time 0.4556 (0.4717)	model_time 0.4554 (0.4643)	loss 3.5669 (3.8694)	grad_norm 1.0594 (1.6695/0.7140)	mem 16099MB
[2025-01-17 23:28:44 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][230/312]	eta 0:00:38 lr 0.003863	time 0.4436 (0.4718)	model_time 0.4434 (0.4647)	loss 4.2818 (3.8815)	grad_norm 1.7161 (1.6520/0.7099)	mem 16099MB
[2025-01-17 23:28:49 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][240/312]	eta 0:00:33 lr 0.003863	time 0.4445 (0.4713)	model_time 0.4444 (0.4644)	loss 3.9171 (3.8774)	grad_norm 1.4238 (1.6556/0.7034)	mem 16099MB
[2025-01-17 23:28:54 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][250/312]	eta 0:00:29 lr 0.003862	time 0.4609 (0.4710)	model_time 0.4608 (0.4644)	loss 4.1761 (3.8766)	grad_norm 1.7778 (1.6426/0.6959)	mem 16099MB
[2025-01-17 23:28:58 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][260/312]	eta 0:00:24 lr 0.003862	time 0.4465 (0.4709)	model_time 0.4463 (0.4646)	loss 2.8789 (3.8722)	grad_norm 1.9313 (1.6286/0.6882)	mem 16099MB
[2025-01-17 23:29:03 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][270/312]	eta 0:00:19 lr 0.003862	time 0.4391 (0.4704)	model_time 0.4386 (0.4643)	loss 4.0451 (3.8655)	grad_norm 1.0109 (1.6336/0.6947)	mem 16099MB
[2025-01-17 23:29:08 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][280/312]	eta 0:00:15 lr 0.003862	time 0.4421 (0.4703)	model_time 0.4419 (0.4643)	loss 4.8747 (3.8711)	grad_norm 1.2624 (1.6377/0.6978)	mem 16099MB
[2025-01-17 23:29:12 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][290/312]	eta 0:00:10 lr 0.003861	time 0.4526 (0.4705)	model_time 0.4524 (0.4647)	loss 4.2240 (3.8638)	grad_norm 1.1379 (1.6291/0.6919)	mem 16099MB
[2025-01-17 23:29:17 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][300/312]	eta 0:00:05 lr 0.003861	time 0.4364 (0.4697)	model_time 0.4364 (0.4642)	loss 3.3721 (3.8668)	grad_norm 1.7088 (1.6272/0.6852)	mem 16099MB
[2025-01-17 23:29:22 internimage_t_1k_224] (main.py 510): INFO Train: [35/300][310/312]	eta 0:00:00 lr 0.003861	time 0.4395 (0.4695)	model_time 0.4394 (0.4641)	loss 4.7507 (3.8731)	grad_norm 1.6071 (1.6460/0.6845)	mem 16099MB
[2025-01-17 23:29:22 internimage_t_1k_224] (main.py 519): INFO EPOCH 35 training takes 0:02:26
[2025-01-17 23:29:22 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_35.pth saving......
[2025-01-17 23:29:23 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_35.pth saved !!!
[2025-01-17 23:29:31 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.238 (8.238)	Loss 1.2177 (1.2177)	Acc@1 74.023 (74.023)	Acc@5 92.627 (92.627)	Mem 16099MB
[2025-01-17 23:29:35 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.102)	Loss 1.6782 (1.4006)	Acc@1 64.966 (70.790)	Acc@5 87.109 (90.514)	Mem 16099MB
[2025-01-17 23:29:35 internimage_t_1k_224] (main.py 575): INFO [Epoch:35] * Acc@1 70.859 Acc@5 90.629
[2025-01-17 23:29:35 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 70.9%
[2025-01-17 23:29:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:29:37 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:29:37 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 70.86%
[2025-01-17 23:29:45 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.576 (8.576)	Loss 6.3369 (6.3369)	Acc@1 1.514 (1.514)	Acc@5 6.323 (6.323)	Mem 16099MB
[2025-01-17 23:29:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.166)	Loss 6.0387 (6.0696)	Acc@1 5.249 (3.860)	Acc@5 12.012 (11.774)	Mem 16099MB
[2025-01-17 23:29:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:35] * Acc@1 4.099 Acc@5 12.312
[2025-01-17 23:29:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 4.1%
[2025-01-17 23:29:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:29:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:29:51 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 4.10%
[2025-01-17 23:29:53 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][0/312]	eta 0:11:03 lr 0.003861	time 2.1274 (2.1274)	model_time 0.5202 (0.5202)	loss 4.1483 (4.1483)	grad_norm 1.3081 (1.3081/0.0000)	mem 16099MB
[2025-01-17 23:29:58 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][10/312]	eta 0:03:13 lr 0.003861	time 0.4414 (0.6398)	model_time 0.4412 (0.4934)	loss 4.2057 (3.7266)	grad_norm 1.1364 (1.4080/0.5248)	mem 16099MB
[2025-01-17 23:30:03 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][20/312]	eta 0:02:43 lr 0.003860	time 0.4480 (0.5591)	model_time 0.4478 (0.4823)	loss 3.6956 (3.7156)	grad_norm 1.3268 (1.5569/0.7897)	mem 16099MB
[2025-01-17 23:30:07 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][30/312]	eta 0:02:31 lr 0.003860	time 0.7413 (0.5387)	model_time 0.7409 (0.4865)	loss 2.6886 (3.7075)	grad_norm 1.2696 (1.6746/0.9204)	mem 16099MB
[2025-01-17 23:30:12 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][40/312]	eta 0:02:21 lr 0.003860	time 0.4477 (0.5188)	model_time 0.4473 (0.4790)	loss 4.7035 (3.7441)	grad_norm 1.1402 (1.6269/0.8406)	mem 16099MB
[2025-01-17 23:30:17 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][50/312]	eta 0:02:13 lr 0.003860	time 0.4541 (0.5081)	model_time 0.4536 (0.4760)	loss 3.9392 (3.7029)	grad_norm 1.7039 (1.5986/0.7998)	mem 16099MB
[2025-01-17 23:30:21 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][60/312]	eta 0:02:05 lr 0.003859	time 0.4523 (0.4999)	model_time 0.4521 (0.4730)	loss 4.1498 (3.7550)	grad_norm 0.9375 (1.6360/0.8288)	mem 16099MB
[2025-01-17 23:30:26 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][70/312]	eta 0:01:59 lr 0.003859	time 0.4492 (0.4953)	model_time 0.4490 (0.4721)	loss 4.2360 (3.7775)	grad_norm 0.9636 (1.6929/0.8256)	mem 16099MB
[2025-01-17 23:30:31 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][80/312]	eta 0:01:54 lr 0.003859	time 0.4437 (0.4916)	model_time 0.4431 (0.4712)	loss 3.6979 (3.7780)	grad_norm 1.4497 (1.6719/0.7849)	mem 16099MB
[2025-01-17 23:30:35 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][90/312]	eta 0:01:48 lr 0.003859	time 0.4481 (0.4875)	model_time 0.4477 (0.4693)	loss 4.4034 (3.7841)	grad_norm 2.4804 (1.6914/0.7708)	mem 16099MB
[2025-01-17 23:30:40 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][100/312]	eta 0:01:42 lr 0.003859	time 0.4477 (0.4849)	model_time 0.4475 (0.4685)	loss 4.1902 (3.7837)	grad_norm 2.4951 (1.6734/0.7515)	mem 16099MB
[2025-01-17 23:30:44 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][110/312]	eta 0:01:37 lr 0.003858	time 0.4575 (0.4828)	model_time 0.4571 (0.4678)	loss 4.2851 (3.8084)	grad_norm 1.7772 (1.6595/0.7276)	mem 16099MB
[2025-01-17 23:30:49 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][120/312]	eta 0:01:32 lr 0.003858	time 0.5371 (0.4818)	model_time 0.5367 (0.4681)	loss 2.6746 (3.8243)	grad_norm 3.0363 (1.6778/0.7440)	mem 16099MB
[2025-01-17 23:30:54 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][130/312]	eta 0:01:27 lr 0.003858	time 0.4830 (0.4814)	model_time 0.4829 (0.4687)	loss 4.0915 (3.8279)	grad_norm 1.0300 (1.6619/0.7298)	mem 16099MB
[2025-01-17 23:30:59 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][140/312]	eta 0:01:22 lr 0.003858	time 0.4509 (0.4824)	model_time 0.4508 (0.4706)	loss 4.5095 (3.8384)	grad_norm 1.3756 (1.6601/0.7227)	mem 16099MB
[2025-01-17 23:31:03 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][150/312]	eta 0:01:17 lr 0.003857	time 0.4532 (0.4810)	model_time 0.4528 (0.4699)	loss 3.1653 (3.8387)	grad_norm 1.6381 (1.6431/0.7068)	mem 16099MB
[2025-01-17 23:31:08 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][160/312]	eta 0:01:12 lr 0.003857	time 0.4458 (0.4798)	model_time 0.4454 (0.4693)	loss 4.0561 (3.8325)	grad_norm 0.9508 (1.6718/0.7469)	mem 16099MB
[2025-01-17 23:31:13 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][170/312]	eta 0:01:08 lr 0.003857	time 0.4497 (0.4789)	model_time 0.4495 (0.4690)	loss 2.8446 (3.8278)	grad_norm 1.1081 (1.6501/0.7351)	mem 16099MB
[2025-01-17 23:31:17 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][180/312]	eta 0:01:03 lr 0.003857	time 0.4555 (0.4775)	model_time 0.4551 (0.4682)	loss 4.1593 (3.8213)	grad_norm 1.8449 (1.6544/0.7369)	mem 16099MB
[2025-01-17 23:31:22 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][190/312]	eta 0:00:58 lr 0.003856	time 0.4461 (0.4765)	model_time 0.4457 (0.4677)	loss 2.9868 (3.8387)	grad_norm 2.7572 (1.6494/0.7270)	mem 16099MB
[2025-01-17 23:31:26 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][200/312]	eta 0:00:53 lr 0.003856	time 0.4910 (0.4756)	model_time 0.4906 (0.4671)	loss 4.7530 (3.8413)	grad_norm 2.6244 (1.6484/0.7225)	mem 16099MB
[2025-01-17 23:31:31 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][210/312]	eta 0:00:48 lr 0.003856	time 0.4517 (0.4747)	model_time 0.4516 (0.4666)	loss 3.4140 (3.8377)	grad_norm 1.4682 (1.6683/0.7443)	mem 16099MB
[2025-01-17 23:31:35 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][220/312]	eta 0:00:43 lr 0.003856	time 0.4493 (0.4738)	model_time 0.4489 (0.4660)	loss 2.6760 (3.8424)	grad_norm 1.1974 (1.6409/0.7389)	mem 16099MB
[2025-01-17 23:31:40 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][230/312]	eta 0:00:38 lr 0.003855	time 0.4977 (0.4731)	model_time 0.4975 (0.4657)	loss 4.2520 (3.8512)	grad_norm 2.4189 (1.6512/0.7330)	mem 16099MB
[2025-01-17 23:31:45 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][240/312]	eta 0:00:34 lr 0.003855	time 0.4389 (0.4732)	model_time 0.4384 (0.4661)	loss 4.6801 (3.8517)	grad_norm 1.0609 (1.6541/0.7295)	mem 16099MB
[2025-01-17 23:31:50 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][250/312]	eta 0:00:29 lr 0.003855	time 0.4401 (0.4739)	model_time 0.4396 (0.4670)	loss 4.8162 (3.8555)	grad_norm 2.1203 (1.6534/0.7263)	mem 16099MB
[2025-01-17 23:31:54 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][260/312]	eta 0:00:24 lr 0.003855	time 0.4525 (0.4733)	model_time 0.4521 (0.4667)	loss 3.9901 (3.8619)	grad_norm 1.1184 (1.6639/0.7379)	mem 16099MB
[2025-01-17 23:31:59 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][270/312]	eta 0:00:19 lr 0.003854	time 0.4739 (0.4731)	model_time 0.4738 (0.4668)	loss 4.2911 (3.8794)	grad_norm 1.0091 (1.6601/0.7313)	mem 16099MB
[2025-01-17 23:32:04 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][280/312]	eta 0:00:15 lr 0.003854	time 0.4527 (0.4723)	model_time 0.4525 (0.4662)	loss 4.1931 (3.8841)	grad_norm 0.9145 (1.6471/0.7264)	mem 16099MB
[2025-01-17 23:32:08 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][290/312]	eta 0:00:10 lr 0.003854	time 0.4427 (0.4723)	model_time 0.4426 (0.4663)	loss 4.2334 (3.8746)	grad_norm 1.1013 (1.6408/0.7248)	mem 16099MB
[2025-01-17 23:32:13 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][300/312]	eta 0:00:05 lr 0.003854	time 0.4383 (0.4719)	model_time 0.4383 (0.4661)	loss 4.4941 (3.8673)	grad_norm 0.8212 (1.6346/0.7230)	mem 16099MB
[2025-01-17 23:32:18 internimage_t_1k_224] (main.py 510): INFO Train: [36/300][310/312]	eta 0:00:00 lr 0.003853	time 0.5473 (0.4722)	model_time 0.5472 (0.4667)	loss 3.3442 (3.8714)	grad_norm 0.9256 (1.6509/0.7219)	mem 16099MB
[2025-01-17 23:32:18 internimage_t_1k_224] (main.py 519): INFO EPOCH 36 training takes 0:02:27
[2025-01-17 23:32:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_36.pth saving......
[2025-01-17 23:32:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_36.pth saved !!!
[2025-01-17 23:32:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.771 (7.771)	Loss 1.2131 (1.2131)	Acc@1 74.927 (74.927)	Acc@5 93.579 (93.579)	Mem 16099MB
[2025-01-17 23:32:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.051)	Loss 1.7161 (1.4149)	Acc@1 64.209 (70.972)	Acc@5 86.450 (90.785)	Mem 16099MB
[2025-01-17 23:32:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:36] * Acc@1 71.053 Acc@5 90.875
[2025-01-17 23:32:31 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 71.1%
[2025-01-17 23:32:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:32:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:32:32 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 71.05%
[2025-01-17 23:32:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.867 (7.867)	Loss 6.2523 (6.2523)	Acc@1 2.246 (2.246)	Acc@5 7.593 (7.593)	Mem 16099MB
[2025-01-17 23:32:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.046)	Loss 5.9117 (5.9482)	Acc@1 6.250 (4.974)	Acc@5 14.429 (14.180)	Mem 16099MB
[2025-01-17 23:32:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:36] * Acc@1 5.222 Acc@5 14.701
[2025-01-17 23:32:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 5.2%
[2025-01-17 23:32:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:32:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:32:45 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 5.22%
[2025-01-17 23:32:47 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][0/312]	eta 0:11:25 lr 0.003853	time 2.1959 (2.1959)	model_time 0.4701 (0.4701)	loss 4.5974 (4.5974)	grad_norm 2.2811 (2.2811/0.0000)	mem 16099MB
[2025-01-17 23:32:52 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][10/312]	eta 0:03:11 lr 0.003853	time 0.4519 (0.6355)	model_time 0.4514 (0.4784)	loss 3.1748 (4.0355)	grad_norm 0.7191 (1.4864/0.5283)	mem 16099MB
[2025-01-17 23:32:57 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][20/312]	eta 0:02:41 lr 0.003853	time 0.4602 (0.5517)	model_time 0.4598 (0.4692)	loss 3.9787 (3.8439)	grad_norm 1.1937 (1.6948/0.9435)	mem 16099MB
[2025-01-17 23:33:02 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][30/312]	eta 0:02:27 lr 0.003852	time 0.4527 (0.5247)	model_time 0.4525 (0.4687)	loss 3.6779 (3.8101)	grad_norm 1.8687 (1.6296/0.7931)	mem 16099MB
[2025-01-17 23:33:06 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][40/312]	eta 0:02:19 lr 0.003852	time 0.4575 (0.5145)	model_time 0.4574 (0.4721)	loss 4.0890 (3.7191)	grad_norm 1.5899 (1.5266/0.7303)	mem 16099MB
[2025-01-17 23:33:11 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][50/312]	eta 0:02:12 lr 0.003852	time 0.4402 (0.5046)	model_time 0.4401 (0.4704)	loss 2.5770 (3.7199)	grad_norm 0.6650 (1.4927/0.6725)	mem 16099MB
[2025-01-17 23:33:16 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][60/312]	eta 0:02:05 lr 0.003852	time 0.4504 (0.4982)	model_time 0.4500 (0.4696)	loss 3.8769 (3.7585)	grad_norm 1.5752 (1.6249/0.9518)	mem 16099MB
[2025-01-17 23:33:20 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][70/312]	eta 0:01:58 lr 0.003851	time 0.4532 (0.4917)	model_time 0.4528 (0.4671)	loss 3.8587 (3.7615)	grad_norm 1.6929 (1.6784/1.0197)	mem 16099MB
[2025-01-17 23:33:25 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][80/312]	eta 0:01:53 lr 0.003851	time 0.4558 (0.4876)	model_time 0.4554 (0.4660)	loss 4.0402 (3.7364)	grad_norm 2.6546 (1.6321/0.9806)	mem 16099MB
[2025-01-17 23:33:29 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][90/312]	eta 0:01:47 lr 0.003851	time 0.4410 (0.4840)	model_time 0.4409 (0.4647)	loss 4.3194 (3.7447)	grad_norm 0.8195 (1.6538/0.9693)	mem 16099MB
[2025-01-17 23:33:34 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][100/312]	eta 0:01:42 lr 0.003851	time 0.4531 (0.4834)	model_time 0.4527 (0.4660)	loss 3.0773 (3.7642)	grad_norm 1.6221 (1.6486/0.9389)	mem 16099MB
[2025-01-17 23:33:39 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][110/312]	eta 0:01:37 lr 0.003850	time 0.4554 (0.4808)	model_time 0.4550 (0.4649)	loss 4.2074 (3.7673)	grad_norm 1.2205 (1.6131/0.9164)	mem 16099MB
[2025-01-17 23:33:43 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][120/312]	eta 0:01:31 lr 0.003850	time 0.4605 (0.4789)	model_time 0.4601 (0.4643)	loss 4.8379 (3.8126)	grad_norm 0.8086 (1.5854/0.8859)	mem 16099MB
[2025-01-17 23:33:48 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][130/312]	eta 0:01:26 lr 0.003850	time 0.4494 (0.4772)	model_time 0.4493 (0.4637)	loss 4.4580 (3.7990)	grad_norm 0.9957 (1.5462/0.8632)	mem 16099MB
[2025-01-17 23:33:52 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][140/312]	eta 0:01:21 lr 0.003850	time 0.4445 (0.4766)	model_time 0.4444 (0.4640)	loss 3.1424 (3.7984)	grad_norm 1.9602 (1.5334/0.8380)	mem 16099MB
[2025-01-17 23:33:57 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][150/312]	eta 0:01:17 lr 0.003849	time 0.4518 (0.4763)	model_time 0.4517 (0.4645)	loss 3.5041 (3.8028)	grad_norm 1.1675 (1.5535/0.8252)	mem 16099MB
[2025-01-17 23:34:02 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][160/312]	eta 0:01:12 lr 0.003849	time 0.4529 (0.4755)	model_time 0.4524 (0.4644)	loss 3.4322 (3.8035)	grad_norm 1.9871 (1.5619/0.8155)	mem 16099MB
[2025-01-17 23:34:07 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][170/312]	eta 0:01:07 lr 0.003849	time 0.4512 (0.4755)	model_time 0.4511 (0.4651)	loss 3.0950 (3.7994)	grad_norm 3.0096 (1.5641/0.8064)	mem 16099MB
[2025-01-17 23:34:11 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][180/312]	eta 0:01:02 lr 0.003849	time 0.4505 (0.4744)	model_time 0.4500 (0.4645)	loss 3.5196 (3.7776)	grad_norm 2.9513 (1.6109/0.8417)	mem 16099MB
[2025-01-17 23:34:16 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][190/312]	eta 0:00:57 lr 0.003848	time 0.4485 (0.4731)	model_time 0.4483 (0.4637)	loss 4.0140 (3.7759)	grad_norm 0.8312 (1.6138/0.8358)	mem 16099MB
[2025-01-17 23:34:21 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][200/312]	eta 0:00:53 lr 0.003848	time 0.4651 (0.4747)	model_time 0.4649 (0.4658)	loss 4.6269 (3.7813)	grad_norm 2.3741 (1.6186/0.8345)	mem 16099MB
[2025-01-17 23:34:25 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][210/312]	eta 0:00:48 lr 0.003848	time 0.4597 (0.4738)	model_time 0.4592 (0.4653)	loss 3.2766 (3.7687)	grad_norm 1.0967 (1.6018/0.8236)	mem 16099MB
[2025-01-17 23:34:30 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][220/312]	eta 0:00:43 lr 0.003848	time 0.4558 (0.4731)	model_time 0.4556 (0.4649)	loss 4.1271 (3.7748)	grad_norm 0.7000 (1.6067/0.8272)	mem 16099MB
[2025-01-17 23:34:34 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][230/312]	eta 0:00:38 lr 0.003847	time 0.4471 (0.4720)	model_time 0.4467 (0.4642)	loss 4.3711 (3.7718)	grad_norm 2.7762 (1.6334/0.8525)	mem 16099MB
[2025-01-17 23:34:39 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][240/312]	eta 0:00:33 lr 0.003847	time 0.4441 (0.4719)	model_time 0.4436 (0.4644)	loss 4.2216 (3.7790)	grad_norm 2.1173 (1.6257/0.8393)	mem 16099MB
[2025-01-17 23:34:44 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][250/312]	eta 0:00:29 lr 0.003847	time 0.4468 (0.4716)	model_time 0.4464 (0.4643)	loss 3.8725 (3.7750)	grad_norm 1.2854 (1.6155/0.8256)	mem 16099MB
[2025-01-17 23:34:48 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][260/312]	eta 0:00:24 lr 0.003847	time 0.4505 (0.4715)	model_time 0.4501 (0.4645)	loss 4.5896 (3.7797)	grad_norm 1.9226 (1.6185/0.8198)	mem 16099MB
[2025-01-17 23:34:53 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][270/312]	eta 0:00:19 lr 0.003846	time 0.4676 (0.4716)	model_time 0.4675 (0.4649)	loss 3.9548 (3.7894)	grad_norm 1.2266 (1.6253/0.8329)	mem 16099MB
[2025-01-17 23:34:58 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][280/312]	eta 0:00:15 lr 0.003846	time 0.4422 (0.4712)	model_time 0.4420 (0.4647)	loss 2.7515 (3.7918)	grad_norm 1.6927 (1.6209/0.8237)	mem 16099MB
[2025-01-17 23:35:03 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][290/312]	eta 0:00:10 lr 0.003846	time 0.4522 (0.4716)	model_time 0.4520 (0.4653)	loss 3.8919 (3.7875)	grad_norm 1.0769 (1.5998/0.8181)	mem 16099MB
[2025-01-17 23:35:07 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][300/312]	eta 0:00:05 lr 0.003846	time 0.4397 (0.4711)	model_time 0.4396 (0.4650)	loss 4.4512 (3.7880)	grad_norm 1.0399 (1.6031/0.8220)	mem 16099MB
[2025-01-17 23:35:11 internimage_t_1k_224] (main.py 510): INFO Train: [37/300][310/312]	eta 0:00:00 lr 0.003845	time 0.4411 (0.4700)	model_time 0.4409 (0.4641)	loss 4.4954 (3.7983)	grad_norm 1.6899 (1.6135/0.8284)	mem 16099MB
[2025-01-17 23:35:12 internimage_t_1k_224] (main.py 519): INFO EPOCH 37 training takes 0:02:26
[2025-01-17 23:35:12 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_37.pth saving......
[2025-01-17 23:35:13 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_37.pth saved !!!
[2025-01-17 23:35:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.090 (8.090)	Loss 1.0954 (1.0954)	Acc@1 75.903 (75.903)	Acc@5 93.433 (93.433)	Mem 16099MB
[2025-01-17 23:35:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.070)	Loss 1.6163 (1.3284)	Acc@1 64.502 (70.941)	Acc@5 87.109 (90.687)	Mem 16099MB
[2025-01-17 23:35:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:37] * Acc@1 70.881 Acc@5 90.759
[2025-01-17 23:35:25 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 70.9%
[2025-01-17 23:35:25 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 71.05%
[2025-01-17 23:35:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.583 (8.583)	Loss 6.1544 (6.1544)	Acc@1 3.125 (3.125)	Acc@5 9.644 (9.644)	Mem 16099MB
[2025-01-17 23:35:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.159)	Loss 5.7755 (5.8141)	Acc@1 7.471 (6.248)	Acc@5 16.553 (16.855)	Mem 16099MB
[2025-01-17 23:35:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:37] * Acc@1 6.436 Acc@5 17.362
[2025-01-17 23:35:38 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 6.4%
[2025-01-17 23:35:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:35:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:35:39 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 6.44%
[2025-01-17 23:35:42 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][0/312]	eta 0:13:06 lr 0.003845	time 2.5206 (2.5206)	model_time 0.4760 (0.4760)	loss 3.0415 (3.0415)	grad_norm 1.8864 (1.8864/0.0000)	mem 16099MB
[2025-01-17 23:35:46 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][10/312]	eta 0:03:16 lr 0.003845	time 0.4563 (0.6504)	model_time 0.4562 (0.4643)	loss 3.0099 (3.5772)	grad_norm 1.2321 (1.3676/0.3825)	mem 16099MB
[2025-01-17 23:35:51 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][20/312]	eta 0:02:44 lr 0.003845	time 0.4615 (0.5640)	model_time 0.4614 (0.4664)	loss 3.2322 (3.6776)	grad_norm 1.8912 (1.5543/0.5773)	mem 16099MB
[2025-01-17 23:35:56 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][30/312]	eta 0:02:31 lr 0.003845	time 0.5322 (0.5359)	model_time 0.5321 (0.4697)	loss 2.9212 (3.6797)	grad_norm 1.2183 (1.4942/0.5204)	mem 16099MB
[2025-01-17 23:36:00 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][40/312]	eta 0:02:20 lr 0.003844	time 0.4472 (0.5166)	model_time 0.4467 (0.4665)	loss 4.2061 (3.7474)	grad_norm 0.7827 (1.3983/0.4944)	mem 16099MB
[2025-01-17 23:36:05 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][50/312]	eta 0:02:13 lr 0.003844	time 0.4486 (0.5096)	model_time 0.4485 (0.4693)	loss 2.8399 (3.8202)	grad_norm 1.8913 (1.3905/0.4698)	mem 16099MB
[2025-01-17 23:36:10 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][60/312]	eta 0:02:06 lr 0.003844	time 0.4575 (0.5016)	model_time 0.4573 (0.4678)	loss 4.1981 (3.8099)	grad_norm 3.2289 (1.3814/0.5090)	mem 16099MB
[2025-01-17 23:36:15 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][70/312]	eta 0:02:00 lr 0.003843	time 0.4526 (0.4972)	model_time 0.4521 (0.4681)	loss 4.1150 (3.8224)	grad_norm 1.7835 (1.4005/0.5109)	mem 16099MB
[2025-01-17 23:36:19 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][80/312]	eta 0:01:54 lr 0.003843	time 0.4589 (0.4933)	model_time 0.4584 (0.4677)	loss 2.9872 (3.7942)	grad_norm 2.8605 (1.4852/0.5817)	mem 16099MB
[2025-01-17 23:36:24 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][90/312]	eta 0:01:48 lr 0.003843	time 0.4413 (0.4902)	model_time 0.4411 (0.4674)	loss 4.1025 (3.7960)	grad_norm 1.1273 (1.4979/0.5779)	mem 16099MB
[2025-01-17 23:36:28 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][100/312]	eta 0:01:43 lr 0.003843	time 0.4650 (0.4867)	model_time 0.4648 (0.4661)	loss 3.2551 (3.7899)	grad_norm 2.1934 (1.5098/0.5645)	mem 16099MB
[2025-01-17 23:36:33 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][110/312]	eta 0:01:38 lr 0.003842	time 0.6028 (0.4862)	model_time 0.6026 (0.4674)	loss 4.1510 (3.7936)	grad_norm 2.3309 (1.5441/0.5618)	mem 16099MB
[2025-01-17 23:36:38 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][120/312]	eta 0:01:32 lr 0.003842	time 0.4593 (0.4841)	model_time 0.4589 (0.4669)	loss 2.9064 (3.7924)	grad_norm 1.6164 (1.5519/0.5571)	mem 16099MB
[2025-01-17 23:36:43 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][130/312]	eta 0:01:27 lr 0.003842	time 0.4460 (0.4833)	model_time 0.4459 (0.4674)	loss 3.6082 (3.7742)	grad_norm 1.9949 (1.5440/0.5417)	mem 16099MB
[2025-01-17 23:36:47 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][140/312]	eta 0:01:22 lr 0.003842	time 0.4459 (0.4817)	model_time 0.4457 (0.4668)	loss 4.4999 (3.7699)	grad_norm 1.5742 (1.5446/0.5382)	mem 16099MB
[2025-01-17 23:36:52 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][150/312]	eta 0:01:17 lr 0.003841	time 0.4411 (0.4799)	model_time 0.4406 (0.4661)	loss 2.6959 (3.7790)	grad_norm 3.3294 (1.5643/0.5968)	mem 16099MB
[2025-01-17 23:36:56 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][160/312]	eta 0:01:12 lr 0.003841	time 0.4663 (0.4785)	model_time 0.4659 (0.4655)	loss 4.2146 (3.7860)	grad_norm 2.2299 (1.5598/0.5933)	mem 16099MB
[2025-01-17 23:37:01 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][170/312]	eta 0:01:07 lr 0.003841	time 0.4434 (0.4771)	model_time 0.4432 (0.4648)	loss 3.8668 (3.7860)	grad_norm 0.9475 (1.5298/0.5897)	mem 16099MB
[2025-01-17 23:37:06 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][180/312]	eta 0:01:02 lr 0.003841	time 0.4477 (0.4766)	model_time 0.4476 (0.4650)	loss 4.0709 (3.7864)	grad_norm 2.7824 (1.5373/0.5978)	mem 16099MB
[2025-01-17 23:37:10 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][190/312]	eta 0:00:58 lr 0.003840	time 0.4542 (0.4755)	model_time 0.4538 (0.4644)	loss 3.3010 (3.7832)	grad_norm 0.9181 (1.5319/0.5929)	mem 16099MB
[2025-01-17 23:37:15 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][200/312]	eta 0:00:53 lr 0.003840	time 0.4574 (0.4750)	model_time 0.4570 (0.4645)	loss 4.4171 (3.7874)	grad_norm 1.1638 (1.5669/0.6685)	mem 16099MB
[2025-01-17 23:37:20 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][210/312]	eta 0:00:48 lr 0.003840	time 0.4483 (0.4754)	model_time 0.4481 (0.4654)	loss 3.2360 (3.7944)	grad_norm 0.8706 (1.5545/0.6591)	mem 16099MB
[2025-01-17 23:37:25 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][220/312]	eta 0:00:43 lr 0.003840	time 0.4465 (0.4765)	model_time 0.4460 (0.4669)	loss 3.2293 (3.8100)	grad_norm 0.7386 (1.5469/0.6554)	mem 16099MB
[2025-01-17 23:37:29 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][230/312]	eta 0:00:39 lr 0.003839	time 0.4483 (0.4761)	model_time 0.4478 (0.4669)	loss 3.7421 (3.8050)	grad_norm 3.3715 (1.5911/0.7285)	mem 16099MB
[2025-01-17 23:37:34 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][240/312]	eta 0:00:34 lr 0.003839	time 0.4404 (0.4753)	model_time 0.4400 (0.4664)	loss 2.9183 (3.7931)	grad_norm 1.3910 (1.5880/0.7159)	mem 16099MB
[2025-01-17 23:37:38 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][250/312]	eta 0:00:29 lr 0.003839	time 0.4488 (0.4746)	model_time 0.4486 (0.4661)	loss 3.5886 (3.7881)	grad_norm 0.8351 (1.5785/0.7106)	mem 16099MB
[2025-01-17 23:37:43 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][260/312]	eta 0:00:24 lr 0.003839	time 0.4451 (0.4741)	model_time 0.4449 (0.4659)	loss 2.6483 (3.7920)	grad_norm 1.4325 (1.5723/0.7019)	mem 16099MB
[2025-01-17 23:37:48 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][270/312]	eta 0:00:19 lr 0.003838	time 0.4520 (0.4738)	model_time 0.4516 (0.4660)	loss 3.2444 (3.7873)	grad_norm 1.2577 (1.5561/0.6957)	mem 16099MB
[2025-01-17 23:37:52 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][280/312]	eta 0:00:15 lr 0.003838	time 0.4742 (0.4739)	model_time 0.4741 (0.4663)	loss 2.9565 (3.7796)	grad_norm 3.2182 (1.5508/0.6944)	mem 16099MB
[2025-01-17 23:37:57 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][290/312]	eta 0:00:10 lr 0.003838	time 0.4497 (0.4738)	model_time 0.4493 (0.4664)	loss 4.2083 (3.7787)	grad_norm 1.4120 (1.5467/0.6864)	mem 16099MB
[2025-01-17 23:38:02 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][300/312]	eta 0:00:05 lr 0.003837	time 0.4353 (0.4736)	model_time 0.4352 (0.4664)	loss 3.9082 (3.7730)	grad_norm 1.5141 (1.5360/0.6797)	mem 16099MB
[2025-01-17 23:38:06 internimage_t_1k_224] (main.py 510): INFO Train: [38/300][310/312]	eta 0:00:00 lr 0.003837	time 0.4380 (0.4730)	model_time 0.4379 (0.4661)	loss 3.8280 (3.7761)	grad_norm 3.4526 (1.5783/0.7824)	mem 16099MB
[2025-01-17 23:38:07 internimage_t_1k_224] (main.py 519): INFO EPOCH 38 training takes 0:02:27
[2025-01-17 23:38:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_38.pth saving......
[2025-01-17 23:38:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_38.pth saved !!!
[2025-01-17 23:38:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.084 (7.084)	Loss 1.0774 (1.0774)	Acc@1 75.171 (75.171)	Acc@5 93.164 (93.164)	Mem 16099MB
[2025-01-17 23:38:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.961)	Loss 1.6055 (1.2973)	Acc@1 64.966 (71.553)	Acc@5 87.695 (91.151)	Mem 16099MB
[2025-01-17 23:38:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:38] * Acc@1 71.565 Acc@5 91.171
[2025-01-17 23:38:19 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 71.6%
[2025-01-17 23:38:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:38:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:38:20 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 71.57%
[2025-01-17 23:38:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.350 (7.350)	Loss 6.0339 (6.0339)	Acc@1 4.272 (4.272)	Acc@5 11.914 (11.914)	Mem 16099MB
[2025-01-17 23:38:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.984)	Loss 5.6335 (5.6705)	Acc@1 8.984 (7.688)	Acc@5 19.360 (19.698)	Mem 16099MB
[2025-01-17 23:38:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:38] * Acc@1 7.829 Acc@5 20.150
[2025-01-17 23:38:31 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 7.8%
[2025-01-17 23:38:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:38:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:38:32 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 7.83%
[2025-01-17 23:38:35 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][0/312]	eta 0:14:09 lr 0.003837	time 2.7227 (2.7227)	model_time 0.4646 (0.4646)	loss 3.8782 (3.8782)	grad_norm 1.2912 (1.2912/0.0000)	mem 16099MB
[2025-01-17 23:38:40 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][10/312]	eta 0:03:24 lr 0.003837	time 0.4498 (0.6774)	model_time 0.4497 (0.4718)	loss 4.8635 (3.6542)	grad_norm 2.3035 (1.8041/0.6502)	mem 16099MB
[2025-01-17 23:38:44 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][20/312]	eta 0:02:47 lr 0.003837	time 0.4620 (0.5753)	model_time 0.4619 (0.4674)	loss 2.7670 (3.6078)	grad_norm 1.1050 (1.5617/0.5689)	mem 16099MB
[2025-01-17 23:38:49 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][30/312]	eta 0:02:31 lr 0.003836	time 0.4583 (0.5383)	model_time 0.4579 (0.4651)	loss 2.7401 (3.5868)	grad_norm 1.9082 (1.5918/0.5782)	mem 16099MB
[2025-01-17 23:38:54 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][40/312]	eta 0:02:20 lr 0.003836	time 0.4617 (0.5180)	model_time 0.4616 (0.4626)	loss 2.4253 (3.5684)	grad_norm 2.2106 (1.5802/0.5625)	mem 16099MB
[2025-01-17 23:38:58 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][50/312]	eta 0:02:12 lr 0.003836	time 0.4490 (0.5048)	model_time 0.4488 (0.4602)	loss 3.8978 (3.6074)	grad_norm 1.5443 (1.5666/0.5481)	mem 16099MB
[2025-01-17 23:39:03 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][60/312]	eta 0:02:05 lr 0.003836	time 0.5386 (0.4975)	model_time 0.5384 (0.4602)	loss 4.3071 (3.6334)	grad_norm 1.1055 (1.6384/0.7030)	mem 16099MB
[2025-01-17 23:39:07 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][70/312]	eta 0:01:58 lr 0.003835	time 0.4395 (0.4913)	model_time 0.4390 (0.4592)	loss 2.8796 (3.6593)	grad_norm 1.4336 (1.6603/0.6704)	mem 16099MB
[2025-01-17 23:39:12 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][80/312]	eta 0:01:53 lr 0.003835	time 0.4913 (0.4880)	model_time 0.4911 (0.4598)	loss 4.5399 (3.6780)	grad_norm 0.9480 (1.6002/0.6506)	mem 16099MB
[2025-01-17 23:39:16 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][90/312]	eta 0:01:47 lr 0.003835	time 0.4518 (0.4852)	model_time 0.4517 (0.4601)	loss 3.1551 (3.7041)	grad_norm 1.0438 (1.5626/0.6363)	mem 16099MB
[2025-01-17 23:39:21 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][100/312]	eta 0:01:42 lr 0.003835	time 0.4612 (0.4829)	model_time 0.4611 (0.4602)	loss 3.7708 (3.7414)	grad_norm 1.8391 (1.5903/0.6341)	mem 16099MB
[2025-01-17 23:39:26 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][110/312]	eta 0:01:37 lr 0.003834	time 0.4571 (0.4824)	model_time 0.4569 (0.4617)	loss 3.8246 (3.7153)	grad_norm 0.8900 (1.5986/0.6353)	mem 16099MB
[2025-01-17 23:39:30 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][120/312]	eta 0:01:32 lr 0.003834	time 0.4500 (0.4804)	model_time 0.4498 (0.4614)	loss 3.4401 (3.7462)	grad_norm 1.0666 (1.5858/0.6211)	mem 16099MB
[2025-01-17 23:39:35 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][130/312]	eta 0:01:27 lr 0.003834	time 0.4419 (0.4801)	model_time 0.4417 (0.4625)	loss 4.3613 (3.7578)	grad_norm 1.1077 (1.5601/0.6143)	mem 16099MB
[2025-01-17 23:39:40 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][140/312]	eta 0:01:22 lr 0.003833	time 0.4437 (0.4798)	model_time 0.4435 (0.4634)	loss 4.0767 (3.7629)	grad_norm 1.4382 (1.5566/0.6025)	mem 16099MB
[2025-01-17 23:39:45 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][150/312]	eta 0:01:17 lr 0.003833	time 0.4526 (0.4788)	model_time 0.4521 (0.4636)	loss 3.4624 (3.7652)	grad_norm 1.9112 (1.5565/0.5923)	mem 16099MB
[2025-01-17 23:39:49 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][160/312]	eta 0:01:12 lr 0.003833	time 0.4429 (0.4789)	model_time 0.4427 (0.4646)	loss 2.6713 (3.7755)	grad_norm 1.2831 (1.6225/0.7014)	mem 16099MB
[2025-01-17 23:39:54 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][170/312]	eta 0:01:07 lr 0.003833	time 0.4500 (0.4775)	model_time 0.4498 (0.4640)	loss 4.4595 (3.7667)	grad_norm 0.8436 (1.6169/0.6960)	mem 16099MB
[2025-01-17 23:39:59 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][180/312]	eta 0:01:02 lr 0.003832	time 0.4410 (0.4763)	model_time 0.4408 (0.4635)	loss 3.3391 (3.7797)	grad_norm 1.1360 (1.5822/0.6927)	mem 16099MB
[2025-01-17 23:40:03 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][190/312]	eta 0:00:57 lr 0.003832	time 0.4643 (0.4751)	model_time 0.4639 (0.4630)	loss 3.8809 (3.7703)	grad_norm 0.8290 (1.6173/0.7355)	mem 16099MB
[2025-01-17 23:40:08 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][200/312]	eta 0:00:53 lr 0.003832	time 0.4494 (0.4740)	model_time 0.4490 (0.4624)	loss 2.8468 (3.7538)	grad_norm 0.9362 (1.5996/0.7282)	mem 16099MB
[2025-01-17 23:40:12 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][210/312]	eta 0:00:48 lr 0.003832	time 0.4632 (0.4731)	model_time 0.4631 (0.4621)	loss 4.3490 (3.7466)	grad_norm 1.1208 (1.5792/0.7203)	mem 16099MB
[2025-01-17 23:40:17 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][220/312]	eta 0:00:43 lr 0.003831	time 0.4473 (0.4727)	model_time 0.4471 (0.4622)	loss 2.9135 (3.7475)	grad_norm 1.8051 (1.5874/0.7122)	mem 16099MB
[2025-01-17 23:40:21 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][230/312]	eta 0:00:38 lr 0.003831	time 0.4471 (0.4725)	model_time 0.4469 (0.4624)	loss 3.9581 (3.7401)	grad_norm 1.3811 (1.5763/0.7008)	mem 16099MB
[2025-01-17 23:40:26 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][240/312]	eta 0:00:34 lr 0.003831	time 0.4441 (0.4731)	model_time 0.4439 (0.4634)	loss 4.6701 (3.7483)	grad_norm 1.7066 (1.5757/0.6916)	mem 16099MB
[2025-01-17 23:40:31 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][250/312]	eta 0:00:29 lr 0.003830	time 0.4514 (0.4728)	model_time 0.4510 (0.4635)	loss 4.6125 (3.7384)	grad_norm 3.0949 (1.5865/0.6949)	mem 16099MB
[2025-01-17 23:40:36 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][260/312]	eta 0:00:24 lr 0.003830	time 0.4882 (0.4726)	model_time 0.4880 (0.4636)	loss 3.8468 (3.7388)	grad_norm 1.7172 (1.5941/0.7032)	mem 16099MB
[2025-01-17 23:40:40 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][270/312]	eta 0:00:19 lr 0.003830	time 0.4599 (0.4719)	model_time 0.4597 (0.4632)	loss 3.7648 (3.7296)	grad_norm 3.5282 (1.5857/0.7064)	mem 16099MB
[2025-01-17 23:40:45 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][280/312]	eta 0:00:15 lr 0.003830	time 0.4499 (0.4715)	model_time 0.4497 (0.4631)	loss 3.9113 (3.7300)	grad_norm 1.9826 (1.5902/0.7200)	mem 16099MB
[2025-01-17 23:40:49 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][290/312]	eta 0:00:10 lr 0.003829	time 0.4512 (0.4712)	model_time 0.4507 (0.4631)	loss 4.2288 (3.7257)	grad_norm 1.2310 (1.5939/0.7178)	mem 16099MB
[2025-01-17 23:40:54 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][300/312]	eta 0:00:05 lr 0.003829	time 0.4380 (0.4708)	model_time 0.4379 (0.4630)	loss 3.9347 (3.7317)	grad_norm 1.2544 (1.6114/0.7293)	mem 16099MB
[2025-01-17 23:40:58 internimage_t_1k_224] (main.py 510): INFO Train: [39/300][310/312]	eta 0:00:00 lr 0.003829	time 0.4395 (0.4698)	model_time 0.4394 (0.4622)	loss 3.5106 (3.7305)	grad_norm 1.5424 (1.6006/0.7257)	mem 16099MB
[2025-01-17 23:40:59 internimage_t_1k_224] (main.py 519): INFO EPOCH 39 training takes 0:02:26
[2025-01-17 23:40:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_39.pth saving......
[2025-01-17 23:41:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_39.pth saved !!!
[2025-01-17 23:41:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.378 (7.378)	Loss 1.0974 (1.0974)	Acc@1 75.220 (75.220)	Acc@5 93.481 (93.481)	Mem 16099MB
[2025-01-17 23:41:11 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.990)	Loss 1.5445 (1.2793)	Acc@1 65.967 (72.024)	Acc@5 87.915 (91.244)	Mem 16099MB
[2025-01-17 23:41:11 internimage_t_1k_224] (main.py 575): INFO [Epoch:39] * Acc@1 72.113 Acc@5 91.291
[2025-01-17 23:41:11 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 72.1%
[2025-01-17 23:41:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:41:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:41:12 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 72.11%
[2025-01-17 23:41:20 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.425 (7.425)	Loss 5.8929 (5.8929)	Acc@1 5.420 (5.420)	Acc@5 14.844 (14.844)	Mem 16099MB
[2025-01-17 23:41:23 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.009)	Loss 5.4787 (5.5097)	Acc@1 10.718 (9.504)	Acc@5 22.437 (22.967)	Mem 16099MB
[2025-01-17 23:41:24 internimage_t_1k_224] (main.py 575): INFO [Epoch:39] * Acc@1 9.595 Acc@5 23.375
[2025-01-17 23:41:24 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 9.6%
[2025-01-17 23:41:24 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:41:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:41:25 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 9.59%
[2025-01-17 23:41:28 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][0/312]	eta 0:13:06 lr 0.003829	time 2.5212 (2.5212)	model_time 0.4697 (0.4697)	loss 3.4227 (3.4227)	grad_norm 1.1687 (1.1687/0.0000)	mem 16099MB
[2025-01-17 23:41:32 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][10/312]	eta 0:03:15 lr 0.003829	time 0.4573 (0.6478)	model_time 0.4569 (0.4610)	loss 3.1196 (3.6311)	grad_norm 1.8092 (1.6500/0.9845)	mem 16099MB
[2025-01-17 23:41:37 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][20/312]	eta 0:02:48 lr 0.003828	time 0.4408 (0.5785)	model_time 0.4407 (0.4805)	loss 4.1033 (3.7685)	grad_norm 1.2167 (1.5049/0.7722)	mem 16099MB
[2025-01-17 23:41:42 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][30/312]	eta 0:02:32 lr 0.003828	time 0.4501 (0.5409)	model_time 0.4496 (0.4744)	loss 4.1579 (3.7880)	grad_norm 1.5230 (1.5955/0.7218)	mem 16099MB
[2025-01-17 23:41:46 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][40/312]	eta 0:02:22 lr 0.003828	time 0.4498 (0.5222)	model_time 0.4494 (0.4719)	loss 4.1480 (3.8398)	grad_norm 1.4192 (1.6965/0.8254)	mem 16099MB
[2025-01-17 23:41:51 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][50/312]	eta 0:02:15 lr 0.003827	time 0.4409 (0.5158)	model_time 0.4407 (0.4753)	loss 3.2228 (3.8498)	grad_norm 1.1558 (1.7080/0.8064)	mem 16099MB
[2025-01-17 23:41:56 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][60/312]	eta 0:02:08 lr 0.003827	time 0.5548 (0.5117)	model_time 0.5547 (0.4778)	loss 4.6797 (3.8115)	grad_norm 0.9806 (1.6469/0.7779)	mem 16099MB
[2025-01-17 23:42:01 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][70/312]	eta 0:02:02 lr 0.003827	time 0.4497 (0.5049)	model_time 0.4495 (0.4757)	loss 4.0574 (3.8056)	grad_norm 0.7808 (1.6026/0.7500)	mem 16099MB
[2025-01-17 23:42:05 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][80/312]	eta 0:01:55 lr 0.003827	time 0.4597 (0.4994)	model_time 0.4592 (0.4737)	loss 3.0172 (3.7835)	grad_norm 1.3974 (1.5682/0.7227)	mem 16099MB
[2025-01-17 23:42:10 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][90/312]	eta 0:01:50 lr 0.003826	time 0.5120 (0.4961)	model_time 0.5118 (0.4733)	loss 3.7793 (3.7691)	grad_norm 1.1448 (1.6213/0.7720)	mem 16099MB
[2025-01-17 23:42:15 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][100/312]	eta 0:01:44 lr 0.003826	time 0.4602 (0.4917)	model_time 0.4600 (0.4711)	loss 3.3123 (3.7913)	grad_norm 1.5137 (1.6114/0.7471)	mem 16099MB
[2025-01-17 23:42:19 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][110/312]	eta 0:01:38 lr 0.003826	time 0.4502 (0.4891)	model_time 0.4498 (0.4703)	loss 4.1519 (3.8150)	grad_norm 1.3330 (1.5961/0.7237)	mem 16099MB
[2025-01-17 23:42:24 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][120/312]	eta 0:01:33 lr 0.003826	time 0.4484 (0.4875)	model_time 0.4483 (0.4702)	loss 4.4141 (3.8063)	grad_norm 1.9925 (1.5672/0.7064)	mem 16099MB
[2025-01-17 23:42:29 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][130/312]	eta 0:01:28 lr 0.003825	time 0.4440 (0.4876)	model_time 0.4438 (0.4716)	loss 3.7338 (3.7879)	grad_norm 1.1758 (1.5766/0.6939)	mem 16099MB
[2025-01-17 23:42:34 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][140/312]	eta 0:01:23 lr 0.003825	time 0.4467 (0.4873)	model_time 0.4465 (0.4724)	loss 3.5771 (3.7958)	grad_norm 1.5179 (1.6284/0.8401)	mem 16099MB
[2025-01-17 23:42:38 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][150/312]	eta 0:01:18 lr 0.003825	time 0.4642 (0.4855)	model_time 0.4640 (0.4716)	loss 4.1630 (3.7975)	grad_norm 0.9007 (1.6535/0.8535)	mem 16099MB
[2025-01-17 23:42:43 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][160/312]	eta 0:01:13 lr 0.003824	time 0.4862 (0.4844)	model_time 0.4857 (0.4713)	loss 4.2017 (3.7917)	grad_norm 1.6088 (1.6662/0.8432)	mem 16099MB
[2025-01-17 23:42:48 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][170/312]	eta 0:01:08 lr 0.003824	time 0.4526 (0.4826)	model_time 0.4524 (0.4702)	loss 3.7992 (3.7918)	grad_norm 2.2646 (1.6552/0.8262)	mem 16099MB
[2025-01-17 23:42:52 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][180/312]	eta 0:01:03 lr 0.003824	time 0.4665 (0.4810)	model_time 0.4663 (0.4693)	loss 3.9757 (3.7962)	grad_norm 1.4743 (1.6475/0.8108)	mem 16099MB
[2025-01-17 23:42:57 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][190/312]	eta 0:00:58 lr 0.003824	time 0.4730 (0.4796)	model_time 0.4726 (0.4685)	loss 4.1341 (3.7992)	grad_norm 1.4715 (1.6285/0.7939)	mem 16099MB
[2025-01-17 23:43:01 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][200/312]	eta 0:00:53 lr 0.003823	time 0.4425 (0.4791)	model_time 0.4423 (0.4686)	loss 4.1022 (3.8074)	grad_norm 1.2165 (1.6367/0.7943)	mem 16099MB
[2025-01-17 23:43:06 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][210/312]	eta 0:00:48 lr 0.003823	time 0.4702 (0.4791)	model_time 0.4697 (0.4690)	loss 4.4447 (3.8111)	grad_norm 1.2005 (1.6308/0.7821)	mem 16099MB
[2025-01-17 23:43:11 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][220/312]	eta 0:00:43 lr 0.003823	time 0.4421 (0.4778)	model_time 0.4419 (0.4681)	loss 3.8745 (3.8127)	grad_norm 1.8563 (1.6285/0.7680)	mem 16099MB
[2025-01-17 23:43:15 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][230/312]	eta 0:00:39 lr 0.003823	time 0.4515 (0.4778)	model_time 0.4514 (0.4686)	loss 4.1467 (3.8107)	grad_norm 1.0903 (1.6181/0.7583)	mem 16099MB
[2025-01-17 23:43:20 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][240/312]	eta 0:00:34 lr 0.003822	time 0.4389 (0.4768)	model_time 0.4388 (0.4680)	loss 4.7054 (3.8211)	grad_norm 1.7961 (1.6290/0.7550)	mem 16099MB
[2025-01-17 23:43:25 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][250/312]	eta 0:00:29 lr 0.003822	time 0.4500 (0.4762)	model_time 0.4496 (0.4677)	loss 3.2089 (3.8258)	grad_norm 1.6206 (1.6282/0.7454)	mem 16099MB
[2025-01-17 23:43:30 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][260/312]	eta 0:00:24 lr 0.003822	time 0.4494 (0.4775)	model_time 0.4493 (0.4693)	loss 4.8322 (3.8274)	grad_norm 2.3255 (1.6318/0.7451)	mem 16099MB
[2025-01-17 23:43:34 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][270/312]	eta 0:00:20 lr 0.003821	time 0.4472 (0.4765)	model_time 0.4468 (0.4686)	loss 3.3108 (3.8126)	grad_norm 0.8298 (1.6161/0.7383)	mem 16099MB
[2025-01-17 23:43:39 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][280/312]	eta 0:00:15 lr 0.003821	time 0.4543 (0.4760)	model_time 0.4541 (0.4683)	loss 2.9705 (3.8114)	grad_norm 0.8656 (1.6240/0.7394)	mem 16099MB
[2025-01-17 23:43:43 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][290/312]	eta 0:00:10 lr 0.003821	time 0.4467 (0.4760)	model_time 0.4462 (0.4686)	loss 4.6567 (3.8231)	grad_norm 5.6459 (1.6407/0.7846)	mem 16099MB
[2025-01-17 23:43:48 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][300/312]	eta 0:00:05 lr 0.003821	time 0.4400 (0.4759)	model_time 0.4399 (0.4688)	loss 3.4798 (3.8158)	grad_norm 1.6010 (1.6289/0.7794)	mem 16099MB
[2025-01-17 23:43:53 internimage_t_1k_224] (main.py 510): INFO Train: [40/300][310/312]	eta 0:00:00 lr 0.003820	time 0.4379 (0.4750)	model_time 0.4378 (0.4681)	loss 3.7569 (3.8105)	grad_norm 1.7443 (1.6375/0.7762)	mem 16099MB
[2025-01-17 23:43:53 internimage_t_1k_224] (main.py 519): INFO EPOCH 40 training takes 0:02:28
[2025-01-17 23:43:53 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_40.pth saving......
[2025-01-17 23:43:54 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_40.pth saved !!!
[2025-01-17 23:44:02 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.461 (7.461)	Loss 1.0806 (1.0806)	Acc@1 76.270 (76.270)	Acc@5 93.970 (93.970)	Mem 16099MB
[2025-01-17 23:44:05 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.993)	Loss 1.5459 (1.3037)	Acc@1 67.114 (71.970)	Acc@5 87.964 (91.093)	Mem 16099MB
[2025-01-17 23:44:05 internimage_t_1k_224] (main.py 575): INFO [Epoch:40] * Acc@1 72.025 Acc@5 91.127
[2025-01-17 23:44:05 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 72.0%
[2025-01-17 23:44:05 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 72.11%
[2025-01-17 23:44:14 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.344 (8.344)	Loss 5.7388 (5.7388)	Acc@1 7.056 (7.056)	Acc@5 17.993 (17.993)	Mem 16099MB
[2025-01-17 23:44:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.125)	Loss 5.3253 (5.3405)	Acc@1 12.354 (11.430)	Acc@5 25.366 (26.367)	Mem 16099MB
[2025-01-17 23:44:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:40] * Acc@1 11.486 Acc@5 26.747
[2025-01-17 23:44:18 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 11.5%
[2025-01-17 23:44:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:44:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:44:19 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 11.49%
[2025-01-17 23:44:22 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][0/312]	eta 0:12:25 lr 0.003820	time 2.3894 (2.3894)	model_time 0.4821 (0.4821)	loss 3.1449 (3.1449)	grad_norm 2.0047 (2.0047/0.0000)	mem 16099MB
[2025-01-17 23:44:26 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][10/312]	eta 0:03:12 lr 0.003820	time 0.4798 (0.6378)	model_time 0.4796 (0.4641)	loss 2.7254 (3.5382)	grad_norm 2.6743 (1.7679/0.6261)	mem 16099MB
[2025-01-17 23:44:31 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][20/312]	eta 0:02:42 lr 0.003820	time 0.4563 (0.5553)	model_time 0.4559 (0.4641)	loss 3.9963 (3.7288)	grad_norm 1.0818 (1.6132/0.6070)	mem 16099MB
[2025-01-17 23:44:36 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][30/312]	eta 0:02:28 lr 0.003819	time 0.4469 (0.5252)	model_time 0.4465 (0.4634)	loss 3.7497 (3.7251)	grad_norm 2.5353 (1.5018/0.5971)	mem 16099MB
[2025-01-17 23:44:40 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][40/312]	eta 0:02:18 lr 0.003819	time 0.4580 (0.5095)	model_time 0.4578 (0.4627)	loss 4.6024 (3.7847)	grad_norm 1.4064 (1.6795/0.8875)	mem 16099MB
[2025-01-17 23:44:45 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][50/312]	eta 0:02:10 lr 0.003819	time 0.4498 (0.4992)	model_time 0.4494 (0.4614)	loss 3.6751 (3.7378)	grad_norm 1.8353 (1.6813/0.8394)	mem 16099MB
[2025-01-17 23:44:49 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][60/312]	eta 0:02:04 lr 0.003819	time 0.4548 (0.4933)	model_time 0.4544 (0.4616)	loss 4.3825 (3.7883)	grad_norm 1.4431 (1.6765/0.7883)	mem 16099MB
[2025-01-17 23:44:54 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][70/312]	eta 0:01:57 lr 0.003818	time 0.4520 (0.4875)	model_time 0.4516 (0.4603)	loss 3.4757 (3.7355)	grad_norm 1.1030 (1.6733/0.7644)	mem 16099MB
[2025-01-17 23:44:59 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][80/312]	eta 0:01:52 lr 0.003818	time 0.5356 (0.4841)	model_time 0.5354 (0.4602)	loss 3.4167 (3.7653)	grad_norm 1.9561 (1.6780/0.7650)	mem 16099MB
[2025-01-17 23:45:03 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][90/312]	eta 0:01:46 lr 0.003818	time 0.4695 (0.4813)	model_time 0.4690 (0.4600)	loss 4.1443 (3.7615)	grad_norm 1.3486 (1.6934/0.7868)	mem 16099MB
[2025-01-17 23:45:08 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][100/312]	eta 0:01:41 lr 0.003818	time 0.4532 (0.4799)	model_time 0.4528 (0.4606)	loss 4.1973 (3.7635)	grad_norm 2.0485 (1.7031/0.7710)	mem 16099MB
[2025-01-17 23:45:12 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][110/312]	eta 0:01:36 lr 0.003817	time 0.4675 (0.4790)	model_time 0.4673 (0.4614)	loss 4.6291 (3.7804)	grad_norm 0.9048 (1.6616/0.7512)	mem 16099MB
[2025-01-17 23:45:17 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][120/312]	eta 0:01:31 lr 0.003817	time 0.4572 (0.4788)	model_time 0.4570 (0.4627)	loss 4.6387 (3.7968)	grad_norm 1.7885 (1.6737/0.7542)	mem 16099MB
[2025-01-17 23:45:22 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][130/312]	eta 0:01:26 lr 0.003817	time 0.4494 (0.4778)	model_time 0.4489 (0.4629)	loss 4.1432 (3.8201)	grad_norm 1.9362 (1.6407/0.7407)	mem 16099MB
[2025-01-17 23:45:27 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][140/312]	eta 0:01:22 lr 0.003816	time 0.4418 (0.4771)	model_time 0.4414 (0.4631)	loss 3.6578 (3.7982)	grad_norm 2.3093 (1.6324/0.7305)	mem 16099MB
[2025-01-17 23:45:31 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][150/312]	eta 0:01:17 lr 0.003816	time 0.4561 (0.4772)	model_time 0.4560 (0.4641)	loss 4.6007 (3.8025)	grad_norm 1.3242 (1.6434/0.7305)	mem 16099MB
[2025-01-17 23:45:36 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][160/312]	eta 0:01:12 lr 0.003816	time 0.4630 (0.4775)	model_time 0.4629 (0.4652)	loss 3.7113 (3.7955)	grad_norm 0.8966 (1.6408/0.7304)	mem 16099MB
[2025-01-17 23:45:41 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][170/312]	eta 0:01:07 lr 0.003816	time 0.4501 (0.4764)	model_time 0.4497 (0.4648)	loss 4.0212 (3.8013)	grad_norm 1.3733 (1.6389/0.7260)	mem 16099MB
[2025-01-17 23:45:45 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][180/312]	eta 0:01:02 lr 0.003815	time 0.4621 (0.4750)	model_time 0.4619 (0.4640)	loss 3.9605 (3.7999)	grad_norm 0.9530 (1.6188/0.7177)	mem 16099MB
[2025-01-17 23:45:50 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][190/312]	eta 0:00:57 lr 0.003815	time 0.4413 (0.4737)	model_time 0.4407 (0.4633)	loss 3.0928 (3.7848)	grad_norm 1.4092 (1.6115/0.7089)	mem 16099MB
[2025-01-17 23:45:54 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][200/312]	eta 0:00:52 lr 0.003815	time 0.4593 (0.4727)	model_time 0.4591 (0.4628)	loss 4.6946 (3.7766)	grad_norm 1.5060 (1.6183/0.7015)	mem 16099MB
[2025-01-17 23:45:59 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][210/312]	eta 0:00:48 lr 0.003814	time 0.4566 (0.4731)	model_time 0.4561 (0.4636)	loss 3.1903 (3.7630)	grad_norm 1.6826 (1.6193/0.6907)	mem 16099MB
[2025-01-17 23:46:04 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][220/312]	eta 0:00:43 lr 0.003814	time 0.4574 (0.4727)	model_time 0.4569 (0.4637)	loss 2.7392 (3.7765)	grad_norm 1.6662 (1.6339/0.6917)	mem 16099MB
[2025-01-17 23:46:08 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][230/312]	eta 0:00:38 lr 0.003814	time 0.4674 (0.4723)	model_time 0.4672 (0.4636)	loss 4.5722 (3.7976)	grad_norm 1.8640 (1.6267/0.6843)	mem 16099MB
[2025-01-17 23:46:13 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][240/312]	eta 0:00:33 lr 0.003814	time 0.4426 (0.4718)	model_time 0.4422 (0.4635)	loss 4.9187 (3.7988)	grad_norm 1.7427 (1.6240/0.6866)	mem 16099MB
[2025-01-17 23:46:18 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][250/312]	eta 0:00:29 lr 0.003813	time 0.4483 (0.4716)	model_time 0.4481 (0.4635)	loss 4.7799 (3.8046)	grad_norm 1.1887 (1.6080/0.6790)	mem 16099MB
[2025-01-17 23:46:22 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][260/312]	eta 0:00:24 lr 0.003813	time 0.4320 (0.4711)	model_time 0.4319 (0.4634)	loss 3.5620 (3.8088)	grad_norm 1.8032 (1.6209/0.6772)	mem 16099MB
[2025-01-17 23:46:27 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][270/312]	eta 0:00:19 lr 0.003813	time 0.4570 (0.4704)	model_time 0.4566 (0.4630)	loss 4.7324 (3.8077)	grad_norm 1.3813 (1.6261/0.6902)	mem 16099MB
[2025-01-17 23:46:31 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][280/312]	eta 0:00:15 lr 0.003812	time 0.4508 (0.4703)	model_time 0.4506 (0.4631)	loss 2.6348 (3.7972)	grad_norm 1.6674 (1.6299/0.6837)	mem 16099MB
[2025-01-17 23:46:36 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][290/312]	eta 0:00:10 lr 0.003812	time 0.4541 (0.4703)	model_time 0.4537 (0.4633)	loss 4.3953 (3.7898)	grad_norm 0.8406 (1.6197/0.6819)	mem 16099MB
[2025-01-17 23:46:41 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][300/312]	eta 0:00:05 lr 0.003812	time 0.4382 (0.4699)	model_time 0.4381 (0.4632)	loss 3.6798 (3.7954)	grad_norm 0.7671 (1.6155/0.6780)	mem 16099MB
[2025-01-17 23:46:45 internimage_t_1k_224] (main.py 510): INFO Train: [41/300][310/312]	eta 0:00:00 lr 0.003812	time 0.4384 (0.4690)	model_time 0.4383 (0.4625)	loss 4.5506 (3.8018)	grad_norm 1.7156 (1.6233/0.6798)	mem 16099MB
[2025-01-17 23:46:46 internimage_t_1k_224] (main.py 519): INFO EPOCH 41 training takes 0:02:26
[2025-01-17 23:46:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_41.pth saving......
[2025-01-17 23:46:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_41.pth saved !!!
[2025-01-17 23:46:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.376 (7.376)	Loss 1.1207 (1.1207)	Acc@1 75.317 (75.317)	Acc@5 93.213 (93.213)	Mem 16099MB
[2025-01-17 23:46:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (0.996)	Loss 1.5442 (1.2850)	Acc@1 65.820 (72.290)	Acc@5 88.403 (91.324)	Mem 16099MB
[2025-01-17 23:46:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:41] * Acc@1 72.321 Acc@5 91.359
[2025-01-17 23:46:58 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 72.3%
[2025-01-17 23:46:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:46:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:46:59 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 72.32%
[2025-01-17 23:47:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.373 (7.373)	Loss 5.5763 (5.5763)	Acc@1 9.155 (9.155)	Acc@5 21.362 (21.362)	Mem 16099MB
[2025-01-17 23:47:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.004)	Loss 5.1657 (5.1638)	Acc@1 14.062 (13.676)	Acc@5 28.662 (30.032)	Mem 16099MB
[2025-01-17 23:47:10 internimage_t_1k_224] (main.py 575): INFO [Epoch:41] * Acc@1 13.744 Acc@5 30.422
[2025-01-17 23:47:10 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 13.7%
[2025-01-17 23:47:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:47:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:47:12 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 13.74%
[2025-01-17 23:47:15 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][0/312]	eta 0:15:52 lr 0.003812	time 3.0514 (3.0514)	model_time 0.4623 (0.4623)	loss 4.8071 (4.8071)	grad_norm 1.9909 (1.9909/0.0000)	mem 16099MB
[2025-01-17 23:47:19 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][10/312]	eta 0:03:31 lr 0.003811	time 0.4578 (0.6991)	model_time 0.4577 (0.4635)	loss 3.6881 (3.6808)	grad_norm 1.2268 (1.2991/0.3193)	mem 16099MB
[2025-01-17 23:47:24 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][20/312]	eta 0:02:51 lr 0.003811	time 0.5449 (0.5859)	model_time 0.5448 (0.4623)	loss 4.7225 (3.7642)	grad_norm 2.4835 (1.6905/0.7362)	mem 16099MB
[2025-01-17 23:47:29 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][30/312]	eta 0:02:35 lr 0.003811	time 0.4491 (0.5510)	model_time 0.4490 (0.4672)	loss 3.8115 (3.7154)	grad_norm 0.9441 (1.6710/0.6731)	mem 16099MB
[2025-01-17 23:47:33 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][40/312]	eta 0:02:24 lr 0.003810	time 0.4458 (0.5295)	model_time 0.4456 (0.4661)	loss 4.1878 (3.7465)	grad_norm 5.5162 (1.8124/0.9599)	mem 16099MB
[2025-01-17 23:47:38 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][50/312]	eta 0:02:14 lr 0.003810	time 0.4481 (0.5147)	model_time 0.4479 (0.4636)	loss 3.5918 (3.8318)	grad_norm 1.3234 (1.8004/0.9042)	mem 16099MB
[2025-01-17 23:47:43 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][60/312]	eta 0:02:07 lr 0.003810	time 0.4560 (0.5068)	model_time 0.4555 (0.4640)	loss 3.9459 (3.7724)	grad_norm 1.3900 (1.7116/0.8817)	mem 16099MB
[2025-01-17 23:47:47 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][70/312]	eta 0:02:00 lr 0.003810	time 0.4493 (0.4992)	model_time 0.4491 (0.4624)	loss 4.7923 (3.7666)	grad_norm 1.4464 (1.6501/0.8388)	mem 16099MB
[2025-01-17 23:47:52 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][80/312]	eta 0:01:55 lr 0.003809	time 0.4391 (0.4974)	model_time 0.4387 (0.4651)	loss 3.7362 (3.7870)	grad_norm 1.7578 (1.6396/0.8132)	mem 16099MB
[2025-01-17 23:47:57 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][90/312]	eta 0:01:49 lr 0.003809	time 0.4493 (0.4938)	model_time 0.4492 (0.4650)	loss 3.4741 (3.7547)	grad_norm 1.2130 (1.6164/0.7900)	mem 16099MB
[2025-01-17 23:48:01 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][100/312]	eta 0:01:44 lr 0.003809	time 0.4409 (0.4911)	model_time 0.4405 (0.4651)	loss 3.4584 (3.7479)	grad_norm 1.3869 (1.6642/0.7901)	mem 16099MB
[2025-01-17 23:48:06 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][110/312]	eta 0:01:38 lr 0.003808	time 0.4628 (0.4877)	model_time 0.4626 (0.4641)	loss 3.9545 (3.7911)	grad_norm 1.1634 (1.6521/0.7632)	mem 16099MB
[2025-01-17 23:48:11 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][120/312]	eta 0:01:33 lr 0.003808	time 0.4531 (0.4864)	model_time 0.4529 (0.4647)	loss 3.8353 (3.7938)	grad_norm 2.4331 (1.6296/0.7468)	mem 16099MB
[2025-01-17 23:48:15 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][130/312]	eta 0:01:28 lr 0.003808	time 0.5659 (0.4855)	model_time 0.5655 (0.4654)	loss 3.3618 (3.7910)	grad_norm 1.1384 (1.6151/0.7250)	mem 16099MB
[2025-01-17 23:48:20 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][140/312]	eta 0:01:23 lr 0.003808	time 0.4431 (0.4848)	model_time 0.4430 (0.4661)	loss 3.6405 (3.7644)	grad_norm 1.0185 (1.5978/0.7066)	mem 16099MB
[2025-01-17 23:48:25 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][150/312]	eta 0:01:18 lr 0.003807	time 0.4724 (0.4842)	model_time 0.4722 (0.4667)	loss 3.8252 (3.7671)	grad_norm 1.1326 (1.5832/0.6962)	mem 16099MB
[2025-01-17 23:48:30 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][160/312]	eta 0:01:13 lr 0.003807	time 0.5474 (0.4829)	model_time 0.5472 (0.4664)	loss 4.2139 (3.7688)	grad_norm 1.0288 (1.5528/0.6906)	mem 16099MB
[2025-01-17 23:48:34 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][170/312]	eta 0:01:08 lr 0.003807	time 0.4518 (0.4815)	model_time 0.4517 (0.4660)	loss 3.3750 (3.7538)	grad_norm 1.4628 (1.5663/0.6996)	mem 16099MB
[2025-01-17 23:48:39 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][180/312]	eta 0:01:03 lr 0.003806	time 0.4522 (0.4800)	model_time 0.4520 (0.4654)	loss 2.5705 (3.7528)	grad_norm 1.2886 (1.6015/0.7495)	mem 16099MB
[2025-01-17 23:48:43 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][190/312]	eta 0:00:58 lr 0.003806	time 0.4433 (0.4785)	model_time 0.4431 (0.4646)	loss 2.8997 (3.7646)	grad_norm 0.7676 (1.5763/0.7408)	mem 16099MB
[2025-01-17 23:48:48 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][200/312]	eta 0:00:53 lr 0.003806	time 0.4475 (0.4782)	model_time 0.4470 (0.4650)	loss 3.0008 (3.7489)	grad_norm 1.7826 (1.5557/0.7313)	mem 16099MB
[2025-01-17 23:48:53 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][210/312]	eta 0:00:48 lr 0.003806	time 0.4496 (0.4775)	model_time 0.4495 (0.4649)	loss 4.2707 (3.7341)	grad_norm 5.1319 (1.5726/0.7617)	mem 16099MB
[2025-01-17 23:48:57 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][220/312]	eta 0:00:43 lr 0.003805	time 0.4564 (0.4766)	model_time 0.4562 (0.4646)	loss 4.0422 (3.7376)	grad_norm 1.0996 (1.5969/0.7727)	mem 16099MB
[2025-01-17 23:49:02 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][230/312]	eta 0:00:39 lr 0.003805	time 0.4542 (0.4766)	model_time 0.4540 (0.4651)	loss 4.4059 (3.7361)	grad_norm 1.7567 (1.6168/0.7729)	mem 16099MB
[2025-01-17 23:49:06 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][240/312]	eta 0:00:34 lr 0.003805	time 0.4421 (0.4760)	model_time 0.4419 (0.4650)	loss 4.3089 (3.7375)	grad_norm 3.0281 (1.6257/0.7675)	mem 16099MB
[2025-01-17 23:49:11 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][250/312]	eta 0:00:29 lr 0.003804	time 0.4515 (0.4752)	model_time 0.4510 (0.4645)	loss 4.0542 (3.7420)	grad_norm 1.8677 (1.6082/0.7610)	mem 16099MB
[2025-01-17 23:49:16 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][260/312]	eta 0:00:24 lr 0.003804	time 0.4994 (0.4749)	model_time 0.4992 (0.4647)	loss 3.9119 (3.7410)	grad_norm 0.9929 (1.5998/0.7543)	mem 16099MB
[2025-01-17 23:49:20 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][270/312]	eta 0:00:19 lr 0.003804	time 0.4852 (0.4748)	model_time 0.4851 (0.4650)	loss 4.2091 (3.7529)	grad_norm 0.9917 (1.5907/0.7515)	mem 16099MB
[2025-01-17 23:49:25 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][280/312]	eta 0:00:15 lr 0.003804	time 0.4818 (0.4744)	model_time 0.4816 (0.4649)	loss 3.1393 (3.7590)	grad_norm 0.9233 (1.5851/0.7500)	mem 16099MB
[2025-01-17 23:49:30 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][290/312]	eta 0:00:10 lr 0.003803	time 0.4672 (0.4741)	model_time 0.4669 (0.4648)	loss 3.3040 (3.7528)	grad_norm 2.4811 (1.6071/0.7705)	mem 16099MB
[2025-01-17 23:49:34 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][300/312]	eta 0:00:05 lr 0.003803	time 0.4317 (0.4732)	model_time 0.4316 (0.4642)	loss 3.4192 (3.7344)	grad_norm 2.2185 (1.6037/0.7637)	mem 16099MB
[2025-01-17 23:49:39 internimage_t_1k_224] (main.py 510): INFO Train: [42/300][310/312]	eta 0:00:00 lr 0.003803	time 0.4373 (0.4730)	model_time 0.4372 (0.4644)	loss 4.7477 (3.7345)	grad_norm 1.2026 (1.6124/0.7670)	mem 16099MB
[2025-01-17 23:49:39 internimage_t_1k_224] (main.py 519): INFO EPOCH 42 training takes 0:02:27
[2025-01-17 23:49:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_42.pth saving......
[2025-01-17 23:49:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_42.pth saved !!!
[2025-01-17 23:49:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.742 (7.742)	Loss 1.0368 (1.0368)	Acc@1 76.733 (76.733)	Acc@5 93.970 (93.970)	Mem 16099MB
[2025-01-17 23:49:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.030)	Loss 1.5062 (1.2484)	Acc@1 65.601 (72.232)	Acc@5 87.964 (91.335)	Mem 16099MB
[2025-01-17 23:49:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:42] * Acc@1 72.285 Acc@5 91.377
[2025-01-17 23:49:52 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 72.3%
[2025-01-17 23:49:52 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 72.32%
[2025-01-17 23:50:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.429 (8.429)	Loss 5.3990 (5.3990)	Acc@1 11.377 (11.377)	Acc@5 24.414 (24.414)	Mem 16099MB
[2025-01-17 23:50:04 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.129)	Loss 5.0055 (4.9836)	Acc@1 15.771 (16.025)	Acc@5 32.251 (33.638)	Mem 16099MB
[2025-01-17 23:50:04 internimage_t_1k_224] (main.py 575): INFO [Epoch:42] * Acc@1 16.051 Acc@5 33.977
[2025-01-17 23:50:04 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 16.1%
[2025-01-17 23:50:05 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:50:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:50:06 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 16.05%
[2025-01-17 23:50:08 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][0/312]	eta 0:12:07 lr 0.003803	time 2.3318 (2.3318)	model_time 0.4802 (0.4802)	loss 3.7970 (3.7970)	grad_norm 1.1130 (1.1130/0.0000)	mem 16099MB
[2025-01-17 23:50:13 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][10/312]	eta 0:03:17 lr 0.003802	time 0.5502 (0.6549)	model_time 0.5500 (0.4863)	loss 4.1620 (3.5619)	grad_norm 0.7840 (1.4564/0.5081)	mem 16099MB
[2025-01-17 23:50:18 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][20/312]	eta 0:02:44 lr 0.003802	time 0.4652 (0.5620)	model_time 0.4650 (0.4735)	loss 4.5003 (3.8503)	grad_norm 2.1193 (1.5765/0.4945)	mem 16099MB
[2025-01-17 23:50:23 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][30/312]	eta 0:02:31 lr 0.003802	time 0.4463 (0.5374)	model_time 0.4462 (0.4774)	loss 3.6900 (3.8637)	grad_norm 2.1237 (1.5604/0.4937)	mem 16099MB
[2025-01-17 23:50:27 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][40/312]	eta 0:02:20 lr 0.003801	time 0.4509 (0.5165)	model_time 0.4507 (0.4711)	loss 3.3096 (3.8091)	grad_norm 1.8278 (1.6435/0.5543)	mem 16099MB
[2025-01-17 23:50:32 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][50/312]	eta 0:02:12 lr 0.003801	time 0.4556 (0.5067)	model_time 0.4555 (0.4701)	loss 4.1492 (3.8168)	grad_norm 1.1516 (1.5483/0.5510)	mem 16099MB
[2025-01-17 23:50:36 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][60/312]	eta 0:02:06 lr 0.003801	time 0.5230 (0.5005)	model_time 0.5229 (0.4698)	loss 3.4125 (3.7734)	grad_norm 1.0113 (1.4596/0.5481)	mem 16099MB
[2025-01-17 23:50:41 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][70/312]	eta 0:01:59 lr 0.003801	time 0.4957 (0.4945)	model_time 0.4955 (0.4681)	loss 3.6916 (3.7408)	grad_norm 1.4529 (1.4134/0.5319)	mem 16099MB
[2025-01-17 23:50:46 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][80/312]	eta 0:01:54 lr 0.003800	time 0.4429 (0.4916)	model_time 0.4428 (0.4684)	loss 3.6321 (3.7630)	grad_norm 1.3263 (1.4830/0.6600)	mem 16099MB
[2025-01-17 23:50:50 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][90/312]	eta 0:01:48 lr 0.003800	time 0.4789 (0.4876)	model_time 0.4788 (0.4670)	loss 4.1728 (3.7604)	grad_norm 1.7544 (1.4997/0.6356)	mem 16099MB
[2025-01-17 23:50:55 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][100/312]	eta 0:01:43 lr 0.003800	time 0.4600 (0.4862)	model_time 0.4596 (0.4676)	loss 3.8094 (3.7522)	grad_norm 1.0528 (1.4775/0.6176)	mem 16099MB
[2025-01-17 23:51:00 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][110/312]	eta 0:01:37 lr 0.003799	time 0.4521 (0.4836)	model_time 0.4517 (0.4666)	loss 3.6388 (3.6857)	grad_norm 0.9856 (1.4860/0.6528)	mem 16099MB
[2025-01-17 23:51:04 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][120/312]	eta 0:01:32 lr 0.003799	time 0.4551 (0.4828)	model_time 0.4549 (0.4672)	loss 4.0970 (3.6982)	grad_norm 1.4209 (1.5179/0.6581)	mem 16099MB
[2025-01-17 23:51:09 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][130/312]	eta 0:01:27 lr 0.003799	time 0.4396 (0.4811)	model_time 0.4394 (0.4666)	loss 4.0533 (3.6884)	grad_norm 0.7567 (1.5475/0.6826)	mem 16099MB
[2025-01-17 23:51:14 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][140/312]	eta 0:01:22 lr 0.003799	time 0.4535 (0.4798)	model_time 0.4534 (0.4664)	loss 2.6333 (3.6953)	grad_norm 1.3991 (1.5678/0.7124)	mem 16099MB
[2025-01-17 23:51:18 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][150/312]	eta 0:01:17 lr 0.003798	time 0.4442 (0.4793)	model_time 0.4437 (0.4667)	loss 3.6885 (3.6821)	grad_norm 0.6709 (1.5492/0.6983)	mem 16099MB
[2025-01-17 23:51:23 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][160/312]	eta 0:01:12 lr 0.003798	time 0.4500 (0.4779)	model_time 0.4498 (0.4660)	loss 4.5155 (3.6920)	grad_norm 1.0732 (1.5360/0.6870)	mem 16099MB
[2025-01-17 23:51:27 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][170/312]	eta 0:01:07 lr 0.003798	time 0.4561 (0.4769)	model_time 0.4560 (0.4658)	loss 4.1208 (3.6884)	grad_norm 1.7433 (1.5448/0.6960)	mem 16099MB
[2025-01-17 23:51:32 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][180/312]	eta 0:01:02 lr 0.003797	time 0.4663 (0.4762)	model_time 0.4658 (0.4656)	loss 4.2888 (3.6769)	grad_norm 0.7806 (1.5399/0.6952)	mem 16099MB
[2025-01-17 23:51:37 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][190/312]	eta 0:00:58 lr 0.003797	time 0.4742 (0.4760)	model_time 0.4737 (0.4659)	loss 3.1527 (3.6729)	grad_norm 2.3094 (1.5375/0.6871)	mem 16099MB
[2025-01-17 23:51:41 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][200/312]	eta 0:00:53 lr 0.003797	time 0.4545 (0.4750)	model_time 0.4540 (0.4655)	loss 3.0157 (3.6809)	grad_norm 2.0005 (1.5810/0.7392)	mem 16099MB
[2025-01-17 23:51:46 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][210/312]	eta 0:00:48 lr 0.003797	time 0.4528 (0.4745)	model_time 0.4526 (0.4654)	loss 4.4797 (3.6886)	grad_norm 2.3031 (1.5885/0.7404)	mem 16099MB
[2025-01-17 23:51:51 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][220/312]	eta 0:00:43 lr 0.003796	time 0.4554 (0.4742)	model_time 0.4550 (0.4655)	loss 4.3025 (3.6831)	grad_norm 1.1339 (1.5729/0.7296)	mem 16099MB
[2025-01-17 23:51:55 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][230/312]	eta 0:00:38 lr 0.003796	time 0.4577 (0.4736)	model_time 0.4573 (0.4652)	loss 4.0270 (3.6660)	grad_norm 1.6162 (1.5612/0.7191)	mem 16099MB
[2025-01-17 23:52:00 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][240/312]	eta 0:00:34 lr 0.003796	time 0.4480 (0.4737)	model_time 0.4475 (0.4656)	loss 3.9477 (3.6507)	grad_norm 1.2653 (1.5495/0.7075)	mem 16099MB
[2025-01-17 23:52:05 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][250/312]	eta 0:00:29 lr 0.003795	time 0.4445 (0.4732)	model_time 0.4443 (0.4655)	loss 4.2095 (3.6562)	grad_norm 1.0645 (1.5496/0.6995)	mem 16099MB
[2025-01-17 23:52:09 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][260/312]	eta 0:00:24 lr 0.003795	time 0.4592 (0.4729)	model_time 0.4590 (0.4654)	loss 3.1152 (3.6624)	grad_norm 0.8924 (1.5522/0.6921)	mem 16099MB
[2025-01-17 23:52:14 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][270/312]	eta 0:00:19 lr 0.003795	time 0.4431 (0.4726)	model_time 0.4430 (0.4654)	loss 2.6447 (3.6682)	grad_norm 1.1942 (1.5688/0.7014)	mem 16099MB
[2025-01-17 23:52:19 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][280/312]	eta 0:00:15 lr 0.003794	time 0.4559 (0.4721)	model_time 0.4557 (0.4651)	loss 3.9516 (3.6683)	grad_norm 1.9057 (1.5538/0.6957)	mem 16099MB
[2025-01-17 23:52:23 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][290/312]	eta 0:00:10 lr 0.003794	time 0.4424 (0.4716)	model_time 0.4420 (0.4649)	loss 3.1032 (3.6669)	grad_norm 1.2904 (1.5498/0.6865)	mem 16099MB
[2025-01-17 23:52:28 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][300/312]	eta 0:00:05 lr 0.003794	time 0.4366 (0.4709)	model_time 0.4365 (0.4644)	loss 4.1339 (3.6755)	grad_norm 3.2277 (1.5520/0.6858)	mem 16099MB
[2025-01-17 23:52:32 internimage_t_1k_224] (main.py 510): INFO Train: [43/300][310/312]	eta 0:00:00 lr 0.003794	time 0.4374 (0.4699)	model_time 0.4373 (0.4636)	loss 3.9951 (3.6791)	grad_norm 1.8441 (1.5880/0.7381)	mem 16099MB
[2025-01-17 23:52:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 43 training takes 0:02:26
[2025-01-17 23:52:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_43.pth saving......
[2025-01-17 23:52:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_43.pth saved !!!
[2025-01-17 23:52:41 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.462 (7.462)	Loss 1.0631 (1.0631)	Acc@1 75.757 (75.757)	Acc@5 93.896 (93.896)	Mem 16099MB
[2025-01-17 23:52:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.002)	Loss 1.5552 (1.2622)	Acc@1 66.553 (72.388)	Acc@5 87.378 (91.524)	Mem 16099MB
[2025-01-17 23:52:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:43] * Acc@1 72.453 Acc@5 91.635
[2025-01-17 23:52:45 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 72.5%
[2025-01-17 23:52:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:52:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:52:46 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 72.45%
[2025-01-17 23:52:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.668 (7.668)	Loss 5.2077 (5.2077)	Acc@1 13.794 (13.794)	Acc@5 29.102 (29.102)	Mem 16099MB
[2025-01-17 23:52:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.011)	Loss 4.8420 (4.7975)	Acc@1 18.115 (18.650)	Acc@5 35.425 (37.447)	Mem 16099MB
[2025-01-17 23:52:57 internimage_t_1k_224] (main.py 575): INFO [Epoch:43] * Acc@1 18.662 Acc@5 37.714
[2025-01-17 23:52:57 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 18.7%
[2025-01-17 23:52:57 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:52:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:52:59 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 18.66%
[2025-01-17 23:53:02 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][0/312]	eta 0:13:57 lr 0.003794	time 2.6841 (2.6841)	model_time 0.4599 (0.4599)	loss 3.6708 (3.6708)	grad_norm 1.1750 (1.1750/0.0000)	mem 16099MB
[2025-01-17 23:53:06 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][10/312]	eta 0:03:25 lr 0.003793	time 0.4392 (0.6789)	model_time 0.4391 (0.4763)	loss 3.6225 (3.6686)	grad_norm 1.8139 (1.3655/0.2952)	mem 16099MB
[2025-01-17 23:53:11 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][20/312]	eta 0:02:47 lr 0.003793	time 0.4420 (0.5719)	model_time 0.4416 (0.4657)	loss 3.5299 (3.7833)	grad_norm 2.0426 (1.4404/0.4749)	mem 16099MB
[2025-01-17 23:53:16 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][30/312]	eta 0:02:31 lr 0.003793	time 0.4581 (0.5370)	model_time 0.4576 (0.4649)	loss 4.3548 (3.8062)	grad_norm 0.9646 (1.5638/0.6609)	mem 16099MB
[2025-01-17 23:53:20 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][40/312]	eta 0:02:21 lr 0.003792	time 0.4463 (0.5196)	model_time 0.4458 (0.4650)	loss 3.5950 (3.8084)	grad_norm 1.5391 (1.5938/0.7359)	mem 16099MB
[2025-01-17 23:53:25 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][50/312]	eta 0:02:13 lr 0.003792	time 0.4469 (0.5082)	model_time 0.4468 (0.4642)	loss 4.4013 (3.8654)	grad_norm 1.3734 (1.6227/0.7109)	mem 16099MB
[2025-01-17 23:53:29 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][60/312]	eta 0:02:06 lr 0.003792	time 0.4484 (0.5020)	model_time 0.4483 (0.4652)	loss 5.0000 (3.8492)	grad_norm 1.7347 (1.5756/0.6766)	mem 16099MB
[2025-01-17 23:53:34 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][70/312]	eta 0:01:59 lr 0.003791	time 0.4557 (0.4949)	model_time 0.4553 (0.4632)	loss 4.7122 (3.8427)	grad_norm 1.3363 (1.5947/0.7147)	mem 16099MB
[2025-01-17 23:53:39 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][80/312]	eta 0:01:54 lr 0.003791	time 0.5617 (0.4927)	model_time 0.5613 (0.4648)	loss 2.5780 (3.7933)	grad_norm 2.7143 (1.6283/0.7714)	mem 16099MB
[2025-01-17 23:53:43 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][90/312]	eta 0:01:48 lr 0.003791	time 0.4550 (0.4905)	model_time 0.4549 (0.4656)	loss 3.7564 (3.7756)	grad_norm 1.9616 (1.6034/0.7468)	mem 16099MB
[2025-01-17 23:53:48 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][100/312]	eta 0:01:43 lr 0.003791	time 0.4501 (0.4869)	model_time 0.4497 (0.4645)	loss 3.5274 (3.7557)	grad_norm 2.0916 (1.5777/0.7185)	mem 16099MB
[2025-01-17 23:53:53 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][110/312]	eta 0:01:37 lr 0.003790	time 0.4486 (0.4845)	model_time 0.4481 (0.4641)	loss 3.9314 (3.7518)	grad_norm 1.0580 (1.5851/0.7387)	mem 16099MB
[2025-01-17 23:53:57 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][120/312]	eta 0:01:32 lr 0.003790	time 0.4479 (0.4843)	model_time 0.4477 (0.4655)	loss 3.8254 (3.7484)	grad_norm 1.4570 (1.6327/0.8143)	mem 16099MB
[2025-01-17 23:54:02 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][130/312]	eta 0:01:28 lr 0.003790	time 0.5401 (0.4847)	model_time 0.5400 (0.4673)	loss 3.5305 (3.7661)	grad_norm 0.5990 (1.6020/0.8000)	mem 16099MB
[2025-01-17 23:54:07 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][140/312]	eta 0:01:23 lr 0.003789	time 0.4475 (0.4832)	model_time 0.4470 (0.4670)	loss 4.6103 (3.7600)	grad_norm 0.7576 (1.5813/0.7846)	mem 16099MB
[2025-01-17 23:54:12 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][150/312]	eta 0:01:18 lr 0.003789	time 0.4452 (0.4832)	model_time 0.4450 (0.4680)	loss 4.1673 (3.7564)	grad_norm 0.8963 (1.5644/0.7688)	mem 16099MB
[2025-01-17 23:54:17 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][160/312]	eta 0:01:13 lr 0.003789	time 0.4414 (0.4823)	model_time 0.4408 (0.4681)	loss 4.1204 (3.7518)	grad_norm 1.2206 (1.5734/0.7690)	mem 16099MB
[2025-01-17 23:54:21 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][170/312]	eta 0:01:08 lr 0.003788	time 0.4487 (0.4805)	model_time 0.4485 (0.4671)	loss 3.8803 (3.7644)	grad_norm 1.2928 (1.5658/0.7569)	mem 16099MB
[2025-01-17 23:54:26 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][180/312]	eta 0:01:03 lr 0.003788	time 0.4595 (0.4790)	model_time 0.4594 (0.4663)	loss 3.9154 (3.7537)	grad_norm 1.5104 (1.5904/0.7545)	mem 16099MB
[2025-01-17 23:54:30 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][190/312]	eta 0:00:58 lr 0.003788	time 0.4517 (0.4785)	model_time 0.4515 (0.4665)	loss 2.6723 (3.7462)	grad_norm 0.8123 (1.5591/0.7475)	mem 16099MB
[2025-01-17 23:54:35 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][200/312]	eta 0:00:53 lr 0.003788	time 0.4560 (0.4772)	model_time 0.4555 (0.4658)	loss 3.7803 (3.7383)	grad_norm 0.9219 (1.5405/0.7358)	mem 16099MB
[2025-01-17 23:54:39 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][210/312]	eta 0:00:48 lr 0.003787	time 0.4434 (0.4765)	model_time 0.4432 (0.4655)	loss 4.2607 (3.7346)	grad_norm 1.6435 (1.5397/0.7290)	mem 16099MB
[2025-01-17 23:54:44 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][220/312]	eta 0:00:43 lr 0.003787	time 0.4419 (0.4758)	model_time 0.4414 (0.4653)	loss 3.8418 (3.7312)	grad_norm 1.6280 (1.5258/0.7195)	mem 16099MB
[2025-01-17 23:54:49 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][230/312]	eta 0:00:38 lr 0.003787	time 0.4473 (0.4753)	model_time 0.4468 (0.4652)	loss 3.4764 (3.7261)	grad_norm 1.8313 (1.5157/0.7081)	mem 16099MB
[2025-01-17 23:54:53 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][240/312]	eta 0:00:34 lr 0.003786	time 0.4593 (0.4747)	model_time 0.4589 (0.4651)	loss 4.1612 (3.7276)	grad_norm 1.5145 (1.5620/0.7643)	mem 16099MB
[2025-01-17 23:54:58 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][250/312]	eta 0:00:29 lr 0.003786	time 0.4526 (0.4743)	model_time 0.4525 (0.4650)	loss 3.8431 (3.7174)	grad_norm 1.7262 (1.5550/0.7522)	mem 16099MB
[2025-01-17 23:55:03 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][260/312]	eta 0:00:24 lr 0.003786	time 0.4402 (0.4739)	model_time 0.4400 (0.4650)	loss 3.8099 (3.7241)	grad_norm 1.5554 (1.5706/0.7702)	mem 16099MB
[2025-01-17 23:55:07 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][270/312]	eta 0:00:19 lr 0.003785	time 0.4466 (0.4731)	model_time 0.4461 (0.4645)	loss 4.2059 (3.7399)	grad_norm 1.9180 (1.5593/0.7642)	mem 16099MB
[2025-01-17 23:55:12 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][280/312]	eta 0:00:15 lr 0.003785	time 0.4501 (0.4732)	model_time 0.4497 (0.4649)	loss 4.0539 (3.7434)	grad_norm 3.3251 (1.5582/0.7641)	mem 16099MB
[2025-01-17 23:55:17 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][290/312]	eta 0:00:10 lr 0.003785	time 0.4550 (0.4731)	model_time 0.4548 (0.4651)	loss 4.5260 (3.7500)	grad_norm 0.9138 (1.5578/0.7610)	mem 16099MB
[2025-01-17 23:55:21 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][300/312]	eta 0:00:05 lr 0.003785	time 0.4380 (0.4727)	model_time 0.4378 (0.4649)	loss 3.3686 (3.7488)	grad_norm 1.2432 (1.5553/0.7574)	mem 16099MB
[2025-01-17 23:55:26 internimage_t_1k_224] (main.py 510): INFO Train: [44/300][310/312]	eta 0:00:00 lr 0.003784	time 0.4404 (0.4720)	model_time 0.4403 (0.4645)	loss 3.2808 (3.7494)	grad_norm 0.9604 (1.5495/0.7592)	mem 16099MB
[2025-01-17 23:55:26 internimage_t_1k_224] (main.py 519): INFO EPOCH 44 training takes 0:02:27
[2025-01-17 23:55:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_44.pth saving......
[2025-01-17 23:55:27 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_44.pth saved !!!
[2025-01-17 23:55:35 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.411 (7.411)	Loss 1.0556 (1.0556)	Acc@1 77.075 (77.075)	Acc@5 94.409 (94.409)	Mem 16099MB
[2025-01-17 23:55:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.982)	Loss 1.5533 (1.2684)	Acc@1 65.332 (72.363)	Acc@5 87.622 (91.526)	Mem 16099MB
[2025-01-17 23:55:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:44] * Acc@1 72.465 Acc@5 91.609
[2025-01-17 23:55:38 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 72.5%
[2025-01-17 23:55:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:55:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:55:39 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 72.46%
[2025-01-17 23:55:47 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.297 (7.297)	Loss 4.9978 (4.9978)	Acc@1 16.943 (16.943)	Acc@5 33.740 (33.740)	Mem 16099MB
[2025-01-17 23:55:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.982)	Loss 4.6744 (4.6073)	Acc@1 20.581 (21.444)	Acc@5 38.379 (41.269)	Mem 16099MB
[2025-01-17 23:55:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:44] * Acc@1 21.379 Acc@5 41.585
[2025-01-17 23:55:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 21.4%
[2025-01-17 23:55:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:55:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:55:52 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 21.38%
[2025-01-17 23:55:54 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][0/312]	eta 0:13:04 lr 0.003784	time 2.5138 (2.5138)	model_time 0.5013 (0.5013)	loss 2.6869 (2.6869)	grad_norm 1.2465 (1.2465/0.0000)	mem 16099MB
[2025-01-17 23:55:59 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][10/312]	eta 0:03:16 lr 0.003784	time 0.4511 (0.6498)	model_time 0.4509 (0.4665)	loss 3.9295 (3.6615)	grad_norm 0.9744 (1.3170/0.2834)	mem 16099MB
[2025-01-17 23:56:03 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][20/312]	eta 0:02:44 lr 0.003784	time 0.4493 (0.5628)	model_time 0.4492 (0.4666)	loss 4.0323 (3.6114)	grad_norm 4.0512 (1.6577/0.8603)	mem 16099MB
[2025-01-17 23:56:08 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][30/312]	eta 0:02:30 lr 0.003783	time 0.4678 (0.5328)	model_time 0.4676 (0.4676)	loss 4.1338 (3.7597)	grad_norm 1.5123 (1.8064/1.1966)	mem 16099MB
[2025-01-17 23:56:13 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][40/312]	eta 0:02:19 lr 0.003783	time 0.4526 (0.5135)	model_time 0.4521 (0.4641)	loss 4.5319 (3.7797)	grad_norm 0.9873 (1.8854/1.3668)	mem 16099MB
[2025-01-17 23:56:17 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][50/312]	eta 0:02:12 lr 0.003783	time 0.4511 (0.5056)	model_time 0.4507 (0.4658)	loss 3.5758 (3.8247)	grad_norm 1.8778 (1.8051/1.2472)	mem 16099MB
[2025-01-17 23:56:22 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][60/312]	eta 0:02:05 lr 0.003782	time 0.4543 (0.4988)	model_time 0.4541 (0.4655)	loss 2.6177 (3.7992)	grad_norm 1.6345 (1.7092/1.1651)	mem 16099MB
[2025-01-17 23:56:27 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][70/312]	eta 0:01:59 lr 0.003782	time 0.4436 (0.4933)	model_time 0.4434 (0.4646)	loss 4.4637 (3.7693)	grad_norm 0.8571 (1.6535/1.0957)	mem 16099MB
[2025-01-17 23:56:31 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][80/312]	eta 0:01:53 lr 0.003782	time 0.5735 (0.4902)	model_time 0.5731 (0.4650)	loss 3.0538 (3.7421)	grad_norm 1.0179 (1.6377/1.0352)	mem 16099MB
[2025-01-17 23:56:36 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][90/312]	eta 0:01:48 lr 0.003781	time 0.4524 (0.4875)	model_time 0.4520 (0.4651)	loss 2.8756 (3.7476)	grad_norm 1.3471 (1.6831/1.0324)	mem 16099MB
[2025-01-17 23:56:41 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][100/312]	eta 0:01:43 lr 0.003781	time 0.5432 (0.4863)	model_time 0.5430 (0.4660)	loss 3.8259 (3.7476)	grad_norm 1.6786 (1.7098/1.0131)	mem 16099MB
[2025-01-17 23:56:45 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][110/312]	eta 0:01:37 lr 0.003781	time 0.4481 (0.4844)	model_time 0.4479 (0.4659)	loss 2.7772 (3.7667)	grad_norm 1.5042 (1.7049/0.9777)	mem 16099MB
[2025-01-17 23:56:50 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][120/312]	eta 0:01:32 lr 0.003781	time 0.5398 (0.4830)	model_time 0.5397 (0.4660)	loss 2.7874 (3.7583)	grad_norm 1.0140 (1.6583/0.9503)	mem 16099MB
[2025-01-17 23:56:55 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][130/312]	eta 0:01:27 lr 0.003780	time 0.4496 (0.4829)	model_time 0.4495 (0.4672)	loss 2.4072 (3.7498)	grad_norm 1.8889 (1.6676/0.9346)	mem 16099MB
[2025-01-17 23:57:00 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][140/312]	eta 0:01:22 lr 0.003780	time 0.4622 (0.4819)	model_time 0.4620 (0.4673)	loss 2.4103 (3.7391)	grad_norm 1.2548 (1.6564/0.9095)	mem 16099MB
[2025-01-17 23:57:04 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][150/312]	eta 0:01:17 lr 0.003780	time 0.4509 (0.4806)	model_time 0.4507 (0.4670)	loss 4.1243 (3.7574)	grad_norm 0.8641 (1.6387/0.8880)	mem 16099MB
[2025-01-17 23:57:09 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][160/312]	eta 0:01:12 lr 0.003779	time 0.4486 (0.4798)	model_time 0.4484 (0.4670)	loss 3.5113 (3.7695)	grad_norm 1.6111 (1.6456/0.8770)	mem 16099MB
[2025-01-17 23:57:13 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][170/312]	eta 0:01:07 lr 0.003779	time 0.4481 (0.4785)	model_time 0.4476 (0.4664)	loss 3.7249 (3.7351)	grad_norm 1.4754 (1.6178/0.8610)	mem 16099MB
[2025-01-17 23:57:18 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][180/312]	eta 0:01:03 lr 0.003779	time 0.4489 (0.4783)	model_time 0.4487 (0.4669)	loss 3.8114 (3.7219)	grad_norm 1.6637 (1.6059/0.8411)	mem 16099MB
[2025-01-17 23:57:23 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][190/312]	eta 0:00:58 lr 0.003778	time 0.4506 (0.4778)	model_time 0.4505 (0.4669)	loss 4.0375 (3.7167)	grad_norm 1.4026 (1.6613/0.9357)	mem 16099MB
[2025-01-17 23:57:28 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][200/312]	eta 0:00:53 lr 0.003778	time 0.4385 (0.4769)	model_time 0.4383 (0.4665)	loss 4.0895 (3.7216)	grad_norm 2.3090 (1.6672/0.9263)	mem 16099MB
[2025-01-17 23:57:32 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][210/312]	eta 0:00:48 lr 0.003778	time 0.4453 (0.4762)	model_time 0.4449 (0.4664)	loss 3.7459 (3.7268)	grad_norm 1.2623 (1.6518/0.9092)	mem 16099MB
[2025-01-17 23:57:37 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][220/312]	eta 0:00:43 lr 0.003778	time 0.4409 (0.4756)	model_time 0.4408 (0.4662)	loss 4.0183 (3.7247)	grad_norm 1.0290 (1.6369/0.8948)	mem 16099MB
[2025-01-17 23:57:41 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][230/312]	eta 0:00:38 lr 0.003777	time 0.4412 (0.4749)	model_time 0.4408 (0.4659)	loss 4.3887 (3.7245)	grad_norm 1.1853 (1.6269/0.8787)	mem 16099MB
[2025-01-17 23:57:46 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][240/312]	eta 0:00:34 lr 0.003777	time 0.4676 (0.4744)	model_time 0.4675 (0.4657)	loss 3.0175 (3.7231)	grad_norm 1.2915 (1.6225/0.8667)	mem 16099MB
[2025-01-17 23:57:51 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][250/312]	eta 0:00:29 lr 0.003777	time 0.4452 (0.4735)	model_time 0.4448 (0.4652)	loss 4.5168 (3.7301)	grad_norm 1.6692 (1.6107/0.8544)	mem 16099MB
[2025-01-17 23:57:55 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][260/312]	eta 0:00:24 lr 0.003776	time 0.4436 (0.4730)	model_time 0.4434 (0.4650)	loss 4.0716 (3.7274)	grad_norm 0.9925 (1.5953/0.8419)	mem 16099MB
[2025-01-17 23:58:00 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][270/312]	eta 0:00:19 lr 0.003776	time 0.4496 (0.4736)	model_time 0.4494 (0.4659)	loss 2.8302 (3.7202)	grad_norm 2.8290 (1.6305/0.8951)	mem 16099MB
[2025-01-17 23:58:05 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][280/312]	eta 0:00:15 lr 0.003776	time 0.4562 (0.4741)	model_time 0.4558 (0.4665)	loss 3.7900 (3.7253)	grad_norm 1.0620 (1.6252/0.8850)	mem 16099MB
[2025-01-17 23:58:10 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][290/312]	eta 0:00:10 lr 0.003775	time 0.4417 (0.4737)	model_time 0.4412 (0.4664)	loss 3.8509 (3.7238)	grad_norm 2.0891 (1.6116/0.8759)	mem 16099MB
[2025-01-17 23:58:14 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][300/312]	eta 0:00:05 lr 0.003775	time 0.4392 (0.4731)	model_time 0.4391 (0.4660)	loss 3.8804 (3.7237)	grad_norm 1.9738 (1.6025/0.8668)	mem 16099MB
[2025-01-17 23:58:19 internimage_t_1k_224] (main.py 510): INFO Train: [45/300][310/312]	eta 0:00:00 lr 0.003775	time 0.4368 (0.4724)	model_time 0.4367 (0.4656)	loss 3.9336 (3.7260)	grad_norm 1.0312 (1.6112/0.8747)	mem 16099MB
[2025-01-17 23:58:19 internimage_t_1k_224] (main.py 519): INFO EPOCH 45 training takes 0:02:27
[2025-01-17 23:58:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_45.pth saving......
[2025-01-17 23:58:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_45.pth saved !!!
[2025-01-17 23:58:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.302 (7.302)	Loss 1.0799 (1.0799)	Acc@1 76.636 (76.636)	Acc@5 94.263 (94.263)	Mem 16099MB
[2025-01-17 23:58:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.990)	Loss 1.5890 (1.3071)	Acc@1 66.357 (72.692)	Acc@5 88.721 (91.542)	Mem 16099MB
[2025-01-17 23:58:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:45] * Acc@1 72.765 Acc@5 91.663
[2025-01-17 23:58:31 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 72.8%
[2025-01-17 23:58:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-17 23:58:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-17 23:58:32 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 72.76%
[2025-01-17 23:58:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.465 (7.465)	Loss 4.7744 (4.7744)	Acc@1 20.312 (20.312)	Acc@5 38.818 (38.818)	Mem 16099MB
[2025-01-17 23:58:43 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.994)	Loss 4.5023 (4.4117)	Acc@1 23.315 (24.390)	Acc@5 41.602 (45.268)	Mem 16099MB
[2025-01-17 23:58:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:45] * Acc@1 24.308 Acc@5 45.569
[2025-01-17 23:58:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 24.3%
[2025-01-17 23:58:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-17 23:58:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-17 23:58:45 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 24.31%
[2025-01-17 23:58:48 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][0/312]	eta 0:14:27 lr 0.003775	time 2.7807 (2.7807)	model_time 0.4778 (0.4778)	loss 3.6529 (3.6529)	grad_norm 1.0162 (1.0162/0.0000)	mem 16099MB
[2025-01-17 23:58:53 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][10/312]	eta 0:03:28 lr 0.003774	time 0.4628 (0.6893)	model_time 0.4623 (0.4796)	loss 4.0746 (3.6344)	grad_norm 1.1565 (1.3357/0.5421)	mem 16099MB
[2025-01-17 23:58:57 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][20/312]	eta 0:02:48 lr 0.003774	time 0.4704 (0.5778)	model_time 0.4703 (0.4678)	loss 3.2180 (3.6782)	grad_norm 3.0986 (1.3827/0.5909)	mem 16099MB
[2025-01-17 23:59:02 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][30/312]	eta 0:02:33 lr 0.003774	time 0.4582 (0.5447)	model_time 0.4580 (0.4701)	loss 4.2207 (3.7368)	grad_norm 3.4510 (1.7241/0.9506)	mem 16099MB
[2025-01-17 23:59:06 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][40/312]	eta 0:02:22 lr 0.003773	time 0.4399 (0.5224)	model_time 0.4395 (0.4659)	loss 3.5068 (3.7364)	grad_norm 1.6030 (1.6417/0.8641)	mem 16099MB
[2025-01-17 23:59:11 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][50/312]	eta 0:02:14 lr 0.003773	time 0.5384 (0.5135)	model_time 0.5383 (0.4680)	loss 4.0236 (3.8053)	grad_norm 1.2439 (1.6002/0.7908)	mem 16099MB
[2025-01-17 23:59:16 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][60/312]	eta 0:02:07 lr 0.003773	time 0.4393 (0.5051)	model_time 0.4388 (0.4670)	loss 3.5932 (3.8093)	grad_norm 1.2878 (1.5954/0.7389)	mem 16099MB
[2025-01-17 23:59:20 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][70/312]	eta 0:02:00 lr 0.003773	time 0.4672 (0.4992)	model_time 0.4667 (0.4664)	loss 4.4683 (3.7940)	grad_norm 2.4353 (1.7224/0.8797)	mem 16099MB
[2025-01-17 23:59:25 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][80/312]	eta 0:01:54 lr 0.003772	time 0.4586 (0.4938)	model_time 0.4581 (0.4651)	loss 3.7269 (3.8074)	grad_norm 1.2219 (1.7205/0.8618)	mem 16099MB
[2025-01-17 23:59:30 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][90/312]	eta 0:01:49 lr 0.003772	time 0.4478 (0.4913)	model_time 0.4477 (0.4656)	loss 2.9921 (3.7878)	grad_norm 2.2188 (1.6769/0.8388)	mem 16099MB
[2025-01-17 23:59:34 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][100/312]	eta 0:01:43 lr 0.003772	time 0.4922 (0.4890)	model_time 0.4920 (0.4658)	loss 4.4841 (3.7919)	grad_norm 1.9083 (1.6814/0.8193)	mem 16099MB
[2025-01-17 23:59:39 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][110/312]	eta 0:01:38 lr 0.003771	time 0.4493 (0.4867)	model_time 0.4488 (0.4655)	loss 4.0164 (3.7964)	grad_norm 2.3712 (1.6871/0.8207)	mem 16099MB
[2025-01-17 23:59:44 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][120/312]	eta 0:01:33 lr 0.003771	time 0.4595 (0.4853)	model_time 0.4591 (0.4658)	loss 4.1775 (3.8326)	grad_norm 1.4725 (1.6904/0.8066)	mem 16099MB
[2025-01-17 23:59:48 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][130/312]	eta 0:01:28 lr 0.003771	time 0.4499 (0.4837)	model_time 0.4495 (0.4656)	loss 3.8615 (3.8196)	grad_norm 1.0732 (1.6504/0.7905)	mem 16099MB
[2025-01-17 23:59:53 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][140/312]	eta 0:01:23 lr 0.003770	time 0.4430 (0.4831)	model_time 0.4428 (0.4663)	loss 2.7112 (3.8316)	grad_norm 1.5594 (1.6310/0.7722)	mem 16099MB
[2025-01-17 23:59:58 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][150/312]	eta 0:01:18 lr 0.003770	time 0.4469 (0.4816)	model_time 0.4465 (0.4659)	loss 2.7099 (3.8206)	grad_norm 2.9518 (1.6303/0.7646)	mem 16099MB
[2025-01-18 00:00:02 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][160/312]	eta 0:01:13 lr 0.003770	time 0.4411 (0.4812)	model_time 0.4407 (0.4664)	loss 3.6459 (3.8163)	grad_norm 2.5462 (1.6377/0.7600)	mem 16099MB
[2025-01-18 00:00:07 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][170/312]	eta 0:01:08 lr 0.003769	time 0.4451 (0.4797)	model_time 0.4449 (0.4658)	loss 2.9983 (3.8263)	grad_norm 2.8830 (1.6681/0.7700)	mem 16099MB
[2025-01-18 00:00:12 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][180/312]	eta 0:01:03 lr 0.003769	time 0.4484 (0.4784)	model_time 0.4479 (0.4653)	loss 3.3907 (3.8259)	grad_norm 0.6828 (1.6393/0.7677)	mem 16099MB
[2025-01-18 00:00:16 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][190/312]	eta 0:00:58 lr 0.003769	time 0.4527 (0.4777)	model_time 0.4525 (0.4652)	loss 4.3824 (3.8258)	grad_norm 1.9703 (1.6267/0.7588)	mem 16099MB
[2025-01-18 00:00:21 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][200/312]	eta 0:00:53 lr 0.003768	time 0.4471 (0.4771)	model_time 0.4467 (0.4652)	loss 4.6943 (3.8242)	grad_norm 1.2365 (1.6353/0.7644)	mem 16099MB
[2025-01-18 00:00:26 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][210/312]	eta 0:00:48 lr 0.003768	time 0.4476 (0.4762)	model_time 0.4471 (0.4649)	loss 2.4700 (3.8145)	grad_norm 1.6886 (1.6439/0.7562)	mem 16099MB
[2025-01-18 00:00:30 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][220/312]	eta 0:00:43 lr 0.003768	time 0.4526 (0.4767)	model_time 0.4522 (0.4658)	loss 4.4675 (3.8104)	grad_norm 1.1702 (1.6320/0.7461)	mem 16099MB
[2025-01-18 00:00:35 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][230/312]	eta 0:00:39 lr 0.003768	time 0.4474 (0.4758)	model_time 0.4472 (0.4654)	loss 4.2140 (3.8096)	grad_norm 1.8838 (1.6221/0.7384)	mem 16099MB
[2025-01-18 00:00:40 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][240/312]	eta 0:00:34 lr 0.003767	time 0.4637 (0.4755)	model_time 0.4632 (0.4656)	loss 3.7223 (3.8081)	grad_norm 0.6622 (1.6199/0.7331)	mem 16099MB
[2025-01-18 00:00:44 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][250/312]	eta 0:00:29 lr 0.003767	time 0.4626 (0.4749)	model_time 0.4622 (0.4653)	loss 3.9721 (3.8092)	grad_norm 1.7187 (1.6073/0.7255)	mem 16099MB
[2025-01-18 00:00:49 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][260/312]	eta 0:00:24 lr 0.003767	time 0.4524 (0.4744)	model_time 0.4519 (0.4651)	loss 4.4895 (3.8234)	grad_norm 2.8527 (1.6068/0.7189)	mem 16099MB
[2025-01-18 00:00:54 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][270/312]	eta 0:00:19 lr 0.003766	time 0.4550 (0.4743)	model_time 0.4546 (0.4654)	loss 3.3689 (3.8204)	grad_norm 2.4000 (1.6514/0.7753)	mem 16099MB
[2025-01-18 00:00:58 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][280/312]	eta 0:00:15 lr 0.003766	time 0.4511 (0.4739)	model_time 0.4509 (0.4653)	loss 2.5895 (3.8145)	grad_norm 0.8619 (1.6440/0.7727)	mem 16099MB
[2025-01-18 00:01:03 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][290/312]	eta 0:00:10 lr 0.003766	time 0.4425 (0.4732)	model_time 0.4420 (0.4649)	loss 4.5522 (3.8082)	grad_norm 0.9858 (1.6225/0.7683)	mem 16099MB
[2025-01-18 00:01:07 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][300/312]	eta 0:00:05 lr 0.003765	time 0.4378 (0.4724)	model_time 0.4377 (0.4643)	loss 4.6073 (3.8001)	grad_norm 0.8513 (1.6127/0.7599)	mem 16099MB
[2025-01-18 00:01:12 internimage_t_1k_224] (main.py 510): INFO Train: [46/300][310/312]	eta 0:00:00 lr 0.003765	time 0.4374 (0.4716)	model_time 0.4373 (0.4638)	loss 2.7086 (3.7973)	grad_norm 1.0259 (1.6207/0.7637)	mem 16099MB
[2025-01-18 00:01:12 internimage_t_1k_224] (main.py 519): INFO EPOCH 46 training takes 0:02:27
[2025-01-18 00:01:12 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_46.pth saving......
[2025-01-18 00:01:13 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_46.pth saved !!!
[2025-01-18 00:01:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.430 (7.430)	Loss 1.0510 (1.0510)	Acc@1 76.538 (76.538)	Acc@5 93.408 (93.408)	Mem 16099MB
[2025-01-18 00:01:24 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.989)	Loss 1.5113 (1.2382)	Acc@1 66.943 (72.614)	Acc@5 88.257 (91.564)	Mem 16099MB
[2025-01-18 00:01:24 internimage_t_1k_224] (main.py 575): INFO [Epoch:46] * Acc@1 72.679 Acc@5 91.653
[2025-01-18 00:01:24 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 72.7%
[2025-01-18 00:01:24 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 72.76%
[2025-01-18 00:01:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.195 (8.195)	Loss 4.5596 (4.5596)	Acc@1 23.389 (23.389)	Acc@5 43.262 (43.262)	Mem 16099MB
[2025-01-18 00:01:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.103)	Loss 4.3389 (4.2249)	Acc@1 25.464 (27.271)	Acc@5 44.653 (48.919)	Mem 16099MB
[2025-01-18 00:01:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:46] * Acc@1 27.147 Acc@5 49.230
[2025-01-18 00:01:37 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 27.1%
[2025-01-18 00:01:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:01:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:01:38 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 27.15%
[2025-01-18 00:01:41 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][0/312]	eta 0:14:32 lr 0.003765	time 2.7969 (2.7969)	model_time 0.4626 (0.4626)	loss 3.9322 (3.9322)	grad_norm 2.3908 (2.3908/0.0000)	mem 16099MB
[2025-01-18 00:01:46 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][10/312]	eta 0:03:26 lr 0.003765	time 0.4901 (0.6834)	model_time 0.4899 (0.4709)	loss 3.6913 (3.6323)	grad_norm 2.6274 (2.0421/0.5985)	mem 16099MB
[2025-01-18 00:01:50 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][20/312]	eta 0:02:50 lr 0.003764	time 0.4532 (0.5823)	model_time 0.4530 (0.4709)	loss 3.5647 (3.5172)	grad_norm 1.0014 (1.7189/0.6146)	mem 16099MB
[2025-01-18 00:01:55 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][30/312]	eta 0:02:34 lr 0.003764	time 0.4504 (0.5461)	model_time 0.4502 (0.4705)	loss 2.5956 (3.4002)	grad_norm 0.8833 (1.5257/0.5851)	mem 16099MB
[2025-01-18 00:02:00 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][40/312]	eta 0:02:23 lr 0.003764	time 0.4517 (0.5261)	model_time 0.4512 (0.4688)	loss 3.9956 (3.4383)	grad_norm 0.9667 (1.4982/0.5522)	mem 16099MB
[2025-01-18 00:02:04 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][50/312]	eta 0:02:14 lr 0.003763	time 0.4581 (0.5140)	model_time 0.4579 (0.4679)	loss 4.1892 (3.4805)	grad_norm 1.1177 (1.5115/0.5366)	mem 16099MB
[2025-01-18 00:02:09 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][60/312]	eta 0:02:07 lr 0.003763	time 0.5347 (0.5068)	model_time 0.5346 (0.4682)	loss 4.3467 (3.4790)	grad_norm 2.0492 (1.5753/0.6179)	mem 16099MB
[2025-01-18 00:02:14 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][70/312]	eta 0:02:00 lr 0.003763	time 0.4512 (0.4994)	model_time 0.4510 (0.4661)	loss 3.7756 (3.4985)	grad_norm 1.8209 (1.5905/0.5928)	mem 16099MB
[2025-01-18 00:02:18 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][80/312]	eta 0:01:54 lr 0.003762	time 0.4562 (0.4940)	model_time 0.4557 (0.4649)	loss 4.1459 (3.5307)	grad_norm 1.0096 (1.5909/0.6077)	mem 16099MB
[2025-01-18 00:02:23 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][90/312]	eta 0:01:48 lr 0.003762	time 0.4567 (0.4899)	model_time 0.4563 (0.4639)	loss 4.0372 (3.5457)	grad_norm 1.8390 (1.5630/0.5921)	mem 16099MB
[2025-01-18 00:02:27 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][100/312]	eta 0:01:43 lr 0.003762	time 0.4641 (0.4871)	model_time 0.4634 (0.4637)	loss 3.9829 (3.5482)	grad_norm 1.0425 (1.5381/0.5803)	mem 16099MB
[2025-01-18 00:02:32 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][110/312]	eta 0:01:38 lr 0.003762	time 0.4565 (0.4857)	model_time 0.4561 (0.4643)	loss 3.7675 (3.5386)	grad_norm 1.1714 (1.5369/0.5660)	mem 16099MB
[2025-01-18 00:02:37 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][120/312]	eta 0:01:32 lr 0.003761	time 0.4492 (0.4840)	model_time 0.4490 (0.4644)	loss 3.7259 (3.5421)	grad_norm 1.1348 (1.5506/0.5936)	mem 16099MB
[2025-01-18 00:02:42 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][130/312]	eta 0:01:28 lr 0.003761	time 0.4419 (0.4846)	model_time 0.4415 (0.4664)	loss 3.4277 (3.5773)	grad_norm 1.3444 (1.5525/0.5860)	mem 16099MB
[2025-01-18 00:02:46 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][140/312]	eta 0:01:23 lr 0.003761	time 0.4414 (0.4842)	model_time 0.4412 (0.4672)	loss 3.8570 (3.5949)	grad_norm 1.8938 (1.5874/0.6496)	mem 16099MB
[2025-01-18 00:02:51 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][150/312]	eta 0:01:18 lr 0.003760	time 0.7305 (0.4842)	model_time 0.7300 (0.4684)	loss 3.6368 (3.6008)	grad_norm 0.7220 (1.5859/0.6468)	mem 16099MB
[2025-01-18 00:02:56 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][160/312]	eta 0:01:13 lr 0.003760	time 0.4522 (0.4823)	model_time 0.4521 (0.4674)	loss 3.2446 (3.5842)	grad_norm 1.5488 (1.5736/0.6380)	mem 16099MB
[2025-01-18 00:03:01 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][170/312]	eta 0:01:08 lr 0.003760	time 0.4521 (0.4818)	model_time 0.4517 (0.4678)	loss 4.6244 (3.6101)	grad_norm 0.5628 (1.5679/0.6330)	mem 16099MB
[2025-01-18 00:03:05 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][180/312]	eta 0:01:03 lr 0.003759	time 0.4480 (0.4804)	model_time 0.4476 (0.4671)	loss 4.3652 (3.6231)	grad_norm 1.5268 (1.5478/0.6288)	mem 16099MB
[2025-01-18 00:03:10 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][190/312]	eta 0:00:58 lr 0.003759	time 0.4624 (0.4800)	model_time 0.4622 (0.4674)	loss 3.5800 (3.6235)	grad_norm 0.7850 (1.5339/0.6244)	mem 16099MB
[2025-01-18 00:03:14 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][200/312]	eta 0:00:53 lr 0.003759	time 0.4433 (0.4790)	model_time 0.4432 (0.4670)	loss 4.2987 (3.6369)	grad_norm 1.7723 (1.5370/0.6331)	mem 16099MB
[2025-01-18 00:03:19 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][210/312]	eta 0:00:48 lr 0.003758	time 0.4530 (0.4790)	model_time 0.4529 (0.4675)	loss 3.8476 (3.6410)	grad_norm 2.8298 (1.5720/0.7097)	mem 16099MB
[2025-01-18 00:03:24 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][220/312]	eta 0:00:44 lr 0.003758	time 0.4489 (0.4784)	model_time 0.4484 (0.4675)	loss 3.1317 (3.6433)	grad_norm 1.2127 (1.5663/0.7006)	mem 16099MB
[2025-01-18 00:03:28 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][230/312]	eta 0:00:39 lr 0.003758	time 0.4466 (0.4774)	model_time 0.4461 (0.4669)	loss 3.3457 (3.6453)	grad_norm 1.6099 (1.5648/0.6956)	mem 16099MB
[2025-01-18 00:03:33 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][240/312]	eta 0:00:34 lr 0.003757	time 0.4763 (0.4765)	model_time 0.4759 (0.4665)	loss 4.2210 (3.6494)	grad_norm 1.1332 (1.5581/0.6867)	mem 16099MB
[2025-01-18 00:03:38 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][250/312]	eta 0:00:29 lr 0.003757	time 0.4386 (0.4768)	model_time 0.4384 (0.4671)	loss 3.9379 (3.6638)	grad_norm 0.8762 (1.5465/0.6781)	mem 16099MB
[2025-01-18 00:03:43 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][260/312]	eta 0:00:24 lr 0.003757	time 0.4456 (0.4765)	model_time 0.4451 (0.4672)	loss 3.8918 (3.6620)	grad_norm 1.0500 (1.5413/0.6710)	mem 16099MB
[2025-01-18 00:03:47 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][270/312]	eta 0:00:20 lr 0.003756	time 0.4479 (0.4763)	model_time 0.4475 (0.4673)	loss 4.5289 (3.6546)	grad_norm 3.5043 (1.5755/0.7285)	mem 16099MB
[2025-01-18 00:03:52 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][280/312]	eta 0:00:15 lr 0.003756	time 0.4487 (0.4756)	model_time 0.4486 (0.4669)	loss 3.1924 (3.6595)	grad_norm 1.2346 (1.5823/0.7371)	mem 16099MB
[2025-01-18 00:03:57 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][290/312]	eta 0:00:10 lr 0.003756	time 0.4548 (0.4756)	model_time 0.4544 (0.4671)	loss 3.3082 (3.6645)	grad_norm 1.4757 (1.5672/0.7301)	mem 16099MB
[2025-01-18 00:04:01 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][300/312]	eta 0:00:05 lr 0.003755	time 0.4376 (0.4747)	model_time 0.4375 (0.4666)	loss 3.7425 (3.6676)	grad_norm 2.2844 (1.5506/0.7256)	mem 16099MB
[2025-01-18 00:04:06 internimage_t_1k_224] (main.py 510): INFO Train: [47/300][310/312]	eta 0:00:00 lr 0.003755	time 0.4376 (0.4740)	model_time 0.4375 (0.4662)	loss 3.9348 (3.6614)	grad_norm 4.0730 (1.5355/0.7388)	mem 16099MB
[2025-01-18 00:04:06 internimage_t_1k_224] (main.py 519): INFO EPOCH 47 training takes 0:02:27
[2025-01-18 00:04:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_47.pth saving......
[2025-01-18 00:04:07 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_47.pth saved !!!
[2025-01-18 00:04:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.618 (7.618)	Loss 1.0674 (1.0674)	Acc@1 76.025 (76.025)	Acc@5 93.457 (93.457)	Mem 16099MB
[2025-01-18 00:04:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.993)	Loss 1.5443 (1.2652)	Acc@1 66.284 (72.496)	Acc@5 87.817 (91.502)	Mem 16099MB
[2025-01-18 00:04:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:47] * Acc@1 72.641 Acc@5 91.583
[2025-01-18 00:04:18 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 72.6%
[2025-01-18 00:04:18 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 72.76%
[2025-01-18 00:04:26 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.132 (8.132)	Loss 4.3413 (4.3413)	Acc@1 26.514 (26.514)	Acc@5 47.705 (47.705)	Mem 16099MB
[2025-01-18 00:04:30 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.089)	Loss 4.1802 (4.0409)	Acc@1 27.393 (30.027)	Acc@5 47.778 (52.472)	Mem 16099MB
[2025-01-18 00:04:30 internimage_t_1k_224] (main.py 575): INFO [Epoch:47] * Acc@1 29.934 Acc@5 52.739
[2025-01-18 00:04:30 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 29.9%
[2025-01-18 00:04:30 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:04:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:04:32 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 29.93%
[2025-01-18 00:04:34 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][0/312]	eta 0:11:18 lr 0.003755	time 2.1762 (2.1762)	model_time 0.4883 (0.4883)	loss 3.4607 (3.4607)	grad_norm 2.4255 (2.4255/0.0000)	mem 16099MB
[2025-01-18 00:04:39 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][10/312]	eta 0:03:04 lr 0.003755	time 0.4441 (0.6121)	model_time 0.4440 (0.4584)	loss 2.5605 (3.8037)	grad_norm 1.0623 (1.8749/0.8174)	mem 16099MB
[2025-01-18 00:04:44 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][20/312]	eta 0:02:41 lr 0.003754	time 0.4589 (0.5526)	model_time 0.4588 (0.4719)	loss 4.4359 (3.7456)	grad_norm 1.1398 (1.7763/0.7070)	mem 16099MB
[2025-01-18 00:04:48 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][30/312]	eta 0:02:27 lr 0.003754	time 0.4703 (0.5241)	model_time 0.4702 (0.4694)	loss 4.2952 (3.8290)	grad_norm 1.3240 (1.6212/0.6564)	mem 16099MB
[2025-01-18 00:04:53 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][40/312]	eta 0:02:18 lr 0.003754	time 0.4509 (0.5085)	model_time 0.4505 (0.4670)	loss 4.1361 (3.8067)	grad_norm 1.4398 (1.6015/0.6164)	mem 16099MB
[2025-01-18 00:04:57 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][50/312]	eta 0:02:10 lr 0.003753	time 0.4394 (0.4986)	model_time 0.4392 (0.4651)	loss 3.1095 (3.7771)	grad_norm 1.1114 (1.5821/0.6135)	mem 16099MB
[2025-01-18 00:05:02 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][60/312]	eta 0:02:04 lr 0.003753	time 0.5463 (0.4931)	model_time 0.5461 (0.4651)	loss 3.3292 (3.7705)	grad_norm 1.2537 (1.5250/0.6089)	mem 16099MB
[2025-01-18 00:05:07 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][70/312]	eta 0:01:58 lr 0.003753	time 0.4635 (0.4880)	model_time 0.4633 (0.4639)	loss 2.8692 (3.7391)	grad_norm 3.5027 (1.5656/0.6897)	mem 16099MB
[2025-01-18 00:05:11 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][80/312]	eta 0:01:52 lr 0.003753	time 0.5307 (0.4852)	model_time 0.5303 (0.4640)	loss 3.1259 (3.7245)	grad_norm 0.6712 (1.5838/0.7226)	mem 16099MB
[2025-01-18 00:05:16 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][90/312]	eta 0:01:47 lr 0.003752	time 0.4462 (0.4830)	model_time 0.4460 (0.4640)	loss 4.2109 (3.6903)	grad_norm 2.3564 (1.5676/0.6989)	mem 16099MB
[2025-01-18 00:05:21 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][100/312]	eta 0:01:42 lr 0.003752	time 0.4493 (0.4816)	model_time 0.4491 (0.4645)	loss 4.1659 (3.7005)	grad_norm 2.1739 (1.6181/0.7346)	mem 16099MB
[2025-01-18 00:05:25 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][110/312]	eta 0:01:37 lr 0.003752	time 0.4650 (0.4828)	model_time 0.4648 (0.4672)	loss 2.4117 (3.6903)	grad_norm 3.2298 (1.6739/0.7763)	mem 16099MB
[2025-01-18 00:05:30 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][120/312]	eta 0:01:32 lr 0.003751	time 0.4563 (0.4817)	model_time 0.4558 (0.4674)	loss 4.2724 (3.7196)	grad_norm 1.0432 (1.6725/0.7773)	mem 16099MB
[2025-01-18 00:05:35 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][130/312]	eta 0:01:27 lr 0.003751	time 0.4851 (0.4821)	model_time 0.4847 (0.4688)	loss 4.1345 (3.6973)	grad_norm 1.1267 (1.6687/0.7865)	mem 16099MB
[2025-01-18 00:05:40 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][140/312]	eta 0:01:22 lr 0.003751	time 0.4586 (0.4807)	model_time 0.4582 (0.4683)	loss 4.0594 (3.7137)	grad_norm 1.4808 (1.6536/0.7651)	mem 16099MB
[2025-01-18 00:05:44 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][150/312]	eta 0:01:17 lr 0.003750	time 0.4429 (0.4798)	model_time 0.4427 (0.4682)	loss 4.4653 (3.7128)	grad_norm 1.0074 (1.6246/0.7514)	mem 16099MB
[2025-01-18 00:05:49 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][160/312]	eta 0:01:13 lr 0.003750	time 0.7243 (0.4815)	model_time 0.7239 (0.4706)	loss 4.6045 (3.6960)	grad_norm 2.1534 (1.6615/0.8651)	mem 16099MB
[2025-01-18 00:05:54 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][170/312]	eta 0:01:08 lr 0.003750	time 0.4533 (0.4807)	model_time 0.4528 (0.4705)	loss 4.6514 (3.7094)	grad_norm 1.1243 (1.6412/0.8460)	mem 16099MB
[2025-01-18 00:05:59 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][180/312]	eta 0:01:03 lr 0.003749	time 0.4644 (0.4792)	model_time 0.4639 (0.4695)	loss 4.2252 (3.7214)	grad_norm 1.3193 (1.6210/0.8327)	mem 16099MB
[2025-01-18 00:06:03 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][190/312]	eta 0:00:58 lr 0.003749	time 0.4403 (0.4794)	model_time 0.4399 (0.4702)	loss 3.7654 (3.7194)	grad_norm 1.2971 (1.6009/0.8167)	mem 16099MB
[2025-01-18 00:06:08 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][200/312]	eta 0:00:53 lr 0.003749	time 0.4604 (0.4788)	model_time 0.4603 (0.4700)	loss 3.6307 (3.7210)	grad_norm 0.8590 (1.5714/0.8088)	mem 16099MB
[2025-01-18 00:06:13 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][210/312]	eta 0:00:48 lr 0.003748	time 0.4508 (0.4775)	model_time 0.4506 (0.4691)	loss 4.1276 (3.7265)	grad_norm 0.8859 (1.5820/0.8118)	mem 16099MB
[2025-01-18 00:06:17 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][220/312]	eta 0:00:43 lr 0.003748	time 0.4571 (0.4768)	model_time 0.4566 (0.4687)	loss 3.4113 (3.7167)	grad_norm 1.5112 (1.5920/0.8200)	mem 16099MB
[2025-01-18 00:06:22 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][230/312]	eta 0:00:39 lr 0.003748	time 0.4452 (0.4762)	model_time 0.4448 (0.4685)	loss 3.2436 (3.7141)	grad_norm 0.9554 (1.6085/0.8179)	mem 16099MB
[2025-01-18 00:06:27 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][240/312]	eta 0:00:34 lr 0.003747	time 0.4712 (0.4765)	model_time 0.4710 (0.4691)	loss 3.1447 (3.7100)	grad_norm 1.8612 (1.6031/0.8039)	mem 16099MB
[2025-01-18 00:06:31 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][250/312]	eta 0:00:29 lr 0.003747	time 0.4492 (0.4756)	model_time 0.4490 (0.4685)	loss 4.7212 (3.7158)	grad_norm 2.4435 (1.6213/0.8299)	mem 16099MB
[2025-01-18 00:06:36 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][260/312]	eta 0:00:24 lr 0.003747	time 0.4623 (0.4751)	model_time 0.4619 (0.4683)	loss 4.0638 (3.7158)	grad_norm 1.3766 (1.6280/0.8343)	mem 16099MB
[2025-01-18 00:06:40 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][270/312]	eta 0:00:19 lr 0.003746	time 0.4415 (0.4745)	model_time 0.4411 (0.4679)	loss 4.7668 (3.7177)	grad_norm 1.2772 (1.6155/0.8242)	mem 16099MB
[2025-01-18 00:06:45 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][280/312]	eta 0:00:15 lr 0.003746	time 0.4531 (0.4738)	model_time 0.4527 (0.4674)	loss 3.2424 (3.7161)	grad_norm 0.9206 (1.5998/0.8163)	mem 16099MB
[2025-01-18 00:06:50 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][290/312]	eta 0:00:10 lr 0.003746	time 0.4412 (0.4737)	model_time 0.4408 (0.4675)	loss 3.2664 (3.7159)	grad_norm 0.8668 (1.5981/0.8173)	mem 16099MB
[2025-01-18 00:06:54 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][300/312]	eta 0:00:05 lr 0.003745	time 0.4372 (0.4731)	model_time 0.4371 (0.4671)	loss 4.6498 (3.7214)	grad_norm 2.0002 (1.5931/0.8134)	mem 16099MB
[2025-01-18 00:06:59 internimage_t_1k_224] (main.py 510): INFO Train: [48/300][310/312]	eta 0:00:00 lr 0.003745	time 0.4375 (0.4721)	model_time 0.4374 (0.4663)	loss 3.9769 (3.7184)	grad_norm 3.6800 (1.5946/0.8206)	mem 16099MB
[2025-01-18 00:06:59 internimage_t_1k_224] (main.py 519): INFO EPOCH 48 training takes 0:02:27
[2025-01-18 00:06:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_48.pth saving......
[2025-01-18 00:07:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_48.pth saved !!!
[2025-01-18 00:07:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.237 (7.237)	Loss 1.1160 (1.1160)	Acc@1 75.806 (75.806)	Acc@5 94.165 (94.165)	Mem 16099MB
[2025-01-18 00:07:11 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.982)	Loss 1.5301 (1.2677)	Acc@1 66.675 (73.140)	Acc@5 88.721 (91.950)	Mem 16099MB
[2025-01-18 00:07:11 internimage_t_1k_224] (main.py 575): INFO [Epoch:48] * Acc@1 73.185 Acc@5 92.029
[2025-01-18 00:07:11 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 73.2%
[2025-01-18 00:07:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 00:07:13 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 00:07:13 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 73.18%
[2025-01-18 00:07:20 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.349 (7.349)	Loss 4.1256 (4.1256)	Acc@1 29.639 (29.639)	Acc@5 51.611 (51.611)	Mem 16099MB
[2025-01-18 00:07:23 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.982)	Loss 4.0301 (3.8668)	Acc@1 29.370 (32.706)	Acc@5 50.439 (55.546)	Mem 16099MB
[2025-01-18 00:07:23 internimage_t_1k_224] (main.py 575): INFO [Epoch:48] * Acc@1 32.618 Acc@5 55.782
[2025-01-18 00:07:23 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 32.6%
[2025-01-18 00:07:23 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:07:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:07:25 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 32.62%
[2025-01-18 00:07:27 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][0/312]	eta 0:14:10 lr 0.003745	time 2.7258 (2.7258)	model_time 0.4720 (0.4720)	loss 4.0385 (4.0385)	grad_norm 0.9938 (0.9938/0.0000)	mem 16099MB
[2025-01-18 00:07:32 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][10/312]	eta 0:03:20 lr 0.003745	time 0.4760 (0.6631)	model_time 0.4756 (0.4579)	loss 3.0043 (3.9148)	grad_norm 2.0415 (2.1316/1.1842)	mem 16099MB
[2025-01-18 00:07:37 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][20/312]	eta 0:02:47 lr 0.003744	time 0.4652 (0.5733)	model_time 0.4651 (0.4657)	loss 2.7587 (3.6585)	grad_norm 0.9178 (1.6345/1.0075)	mem 16099MB
[2025-01-18 00:07:41 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][30/312]	eta 0:02:32 lr 0.003744	time 0.4520 (0.5391)	model_time 0.4518 (0.4661)	loss 2.2956 (3.6640)	grad_norm 1.0099 (1.4365/0.8856)	mem 16099MB
[2025-01-18 00:07:46 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][40/312]	eta 0:02:21 lr 0.003744	time 0.4447 (0.5206)	model_time 0.4445 (0.4653)	loss 3.8686 (3.6067)	grad_norm 1.2167 (1.6438/1.0334)	mem 16099MB
[2025-01-18 00:07:51 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][50/312]	eta 0:02:13 lr 0.003743	time 0.4533 (0.5097)	model_time 0.4529 (0.4652)	loss 3.2503 (3.6045)	grad_norm 0.9895 (1.6032/0.9433)	mem 16099MB
[2025-01-18 00:07:55 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][60/312]	eta 0:02:06 lr 0.003743	time 0.4956 (0.5026)	model_time 0.4954 (0.4653)	loss 2.6983 (3.6033)	grad_norm 1.4949 (1.6025/0.8863)	mem 16099MB
[2025-01-18 00:08:00 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][70/312]	eta 0:02:00 lr 0.003743	time 0.4516 (0.4966)	model_time 0.4514 (0.4645)	loss 3.6763 (3.6742)	grad_norm 0.9448 (1.5596/0.8517)	mem 16099MB
[2025-01-18 00:08:05 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][80/312]	eta 0:01:54 lr 0.003742	time 0.4531 (0.4939)	model_time 0.4529 (0.4657)	loss 3.7727 (3.6761)	grad_norm 0.8583 (1.5630/0.8424)	mem 16099MB
[2025-01-18 00:08:09 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][90/312]	eta 0:01:49 lr 0.003742	time 0.4482 (0.4914)	model_time 0.4477 (0.4663)	loss 2.7834 (3.7053)	grad_norm 1.6528 (1.5584/0.8061)	mem 16099MB
[2025-01-18 00:08:14 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][100/312]	eta 0:01:43 lr 0.003742	time 0.4542 (0.4895)	model_time 0.4540 (0.4668)	loss 3.1328 (3.6980)	grad_norm 1.6718 (1.5601/0.7954)	mem 16099MB
[2025-01-18 00:08:19 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][110/312]	eta 0:01:38 lr 0.003741	time 0.4423 (0.4878)	model_time 0.4419 (0.4672)	loss 4.5107 (3.6681)	grad_norm 0.8820 (1.5316/0.7670)	mem 16099MB
[2025-01-18 00:08:24 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][120/312]	eta 0:01:33 lr 0.003741	time 0.4666 (0.4865)	model_time 0.4664 (0.4675)	loss 3.9817 (3.6680)	grad_norm 1.9213 (1.5088/0.7448)	mem 16099MB
[2025-01-18 00:08:28 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][130/312]	eta 0:01:28 lr 0.003741	time 0.4489 (0.4852)	model_time 0.4488 (0.4676)	loss 4.6246 (3.6817)	grad_norm 2.3142 (1.5250/0.7500)	mem 16099MB
[2025-01-18 00:08:33 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][140/312]	eta 0:01:23 lr 0.003740	time 0.4476 (0.4844)	model_time 0.4472 (0.4680)	loss 3.9018 (3.6678)	grad_norm 2.3490 (1.5435/0.7363)	mem 16099MB
[2025-01-18 00:08:38 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][150/312]	eta 0:01:18 lr 0.003740	time 0.4501 (0.4828)	model_time 0.4500 (0.4675)	loss 3.5330 (3.6722)	grad_norm 1.4620 (1.5373/0.7229)	mem 16099MB
[2025-01-18 00:08:42 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][160/312]	eta 0:01:13 lr 0.003740	time 0.4432 (0.4817)	model_time 0.4431 (0.4674)	loss 3.9876 (3.6806)	grad_norm 1.6138 (1.5403/0.7093)	mem 16099MB
[2025-01-18 00:08:47 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][170/312]	eta 0:01:08 lr 0.003739	time 0.4397 (0.4799)	model_time 0.4392 (0.4663)	loss 2.8317 (3.6630)	grad_norm 1.3955 (1.5450/0.6949)	mem 16099MB
[2025-01-18 00:08:51 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][180/312]	eta 0:01:03 lr 0.003739	time 0.4656 (0.4784)	model_time 0.4652 (0.4656)	loss 3.2095 (3.6590)	grad_norm 0.9570 (1.5356/0.6868)	mem 16099MB
[2025-01-18 00:08:56 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][190/312]	eta 0:00:58 lr 0.003739	time 0.4548 (0.4783)	model_time 0.4547 (0.4661)	loss 2.8829 (3.6520)	grad_norm 3.7594 (1.5365/0.7186)	mem 16099MB
[2025-01-18 00:09:01 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][200/312]	eta 0:00:53 lr 0.003738	time 0.4446 (0.4778)	model_time 0.4442 (0.4662)	loss 4.2815 (3.6631)	grad_norm 1.3669 (1.5380/0.7050)	mem 16099MB
[2025-01-18 00:09:05 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][210/312]	eta 0:00:48 lr 0.003738	time 0.4570 (0.4772)	model_time 0.4568 (0.4661)	loss 4.0063 (3.6775)	grad_norm 1.9788 (1.5276/0.6976)	mem 16099MB
[2025-01-18 00:09:10 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][220/312]	eta 0:00:43 lr 0.003738	time 0.4531 (0.4763)	model_time 0.4526 (0.4658)	loss 2.9301 (3.6731)	grad_norm 2.5173 (1.5524/0.7187)	mem 16099MB
[2025-01-18 00:09:15 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][230/312]	eta 0:00:38 lr 0.003737	time 0.4483 (0.4754)	model_time 0.4478 (0.4653)	loss 3.9772 (3.6756)	grad_norm 2.1973 (1.5606/0.7163)	mem 16099MB
[2025-01-18 00:09:20 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][240/312]	eta 0:00:34 lr 0.003737	time 0.5360 (0.4763)	model_time 0.5353 (0.4666)	loss 3.0928 (3.6850)	grad_norm 1.2090 (1.5577/0.7058)	mem 16099MB
[2025-01-18 00:09:24 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][250/312]	eta 0:00:29 lr 0.003737	time 0.4421 (0.4756)	model_time 0.4419 (0.4663)	loss 2.5904 (3.6819)	grad_norm 1.1663 (1.5493/0.6995)	mem 16099MB
[2025-01-18 00:09:29 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][260/312]	eta 0:00:24 lr 0.003736	time 0.4449 (0.4759)	model_time 0.4447 (0.4668)	loss 3.3566 (3.6848)	grad_norm 1.0051 (1.5825/0.7444)	mem 16099MB
[2025-01-18 00:09:34 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][270/312]	eta 0:00:19 lr 0.003736	time 0.4522 (0.4754)	model_time 0.4518 (0.4667)	loss 2.9338 (3.6840)	grad_norm 1.1895 (1.5595/0.7406)	mem 16099MB
[2025-01-18 00:09:38 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][280/312]	eta 0:00:15 lr 0.003736	time 0.4509 (0.4746)	model_time 0.4507 (0.4662)	loss 4.0815 (3.6957)	grad_norm 1.2178 (1.5658/0.7438)	mem 16099MB
[2025-01-18 00:09:43 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][290/312]	eta 0:00:10 lr 0.003735	time 0.4502 (0.4750)	model_time 0.4496 (0.4669)	loss 3.9901 (3.7022)	grad_norm 1.2722 (1.5680/0.7462)	mem 16099MB
[2025-01-18 00:09:48 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][300/312]	eta 0:00:05 lr 0.003735	time 0.4381 (0.4745)	model_time 0.4380 (0.4666)	loss 3.7004 (3.6932)	grad_norm 1.2627 (1.5607/0.7419)	mem 16099MB
[2025-01-18 00:09:52 internimage_t_1k_224] (main.py 510): INFO Train: [49/300][310/312]	eta 0:00:00 lr 0.003735	time 0.4402 (0.4737)	model_time 0.4401 (0.4660)	loss 4.0509 (3.6849)	grad_norm 1.4844 (1.5643/0.7449)	mem 16099MB
[2025-01-18 00:09:53 internimage_t_1k_224] (main.py 519): INFO EPOCH 49 training takes 0:02:27
[2025-01-18 00:09:53 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_49.pth saving......
[2025-01-18 00:09:54 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_49.pth saved !!!
[2025-01-18 00:10:01 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.225 (7.225)	Loss 1.0885 (1.0885)	Acc@1 76.660 (76.660)	Acc@5 93.652 (93.652)	Mem 16099MB
[2025-01-18 00:10:05 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.988)	Loss 1.4850 (1.2400)	Acc@1 66.479 (73.158)	Acc@5 88.696 (91.979)	Mem 16099MB
[2025-01-18 00:10:05 internimage_t_1k_224] (main.py 575): INFO [Epoch:49] * Acc@1 73.215 Acc@5 92.071
[2025-01-18 00:10:05 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 73.2%
[2025-01-18 00:10:05 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 00:10:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 00:10:06 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 73.21%
[2025-01-18 00:10:13 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.477 (7.477)	Loss 3.9161 (3.9161)	Acc@1 33.350 (33.350)	Acc@5 55.078 (55.078)	Mem 16099MB
[2025-01-18 00:10:17 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.010)	Loss 3.8838 (3.6997)	Acc@1 31.396 (35.436)	Acc@5 53.418 (58.612)	Mem 16099MB
[2025-01-18 00:10:17 internimage_t_1k_224] (main.py 575): INFO [Epoch:49] * Acc@1 35.329 Acc@5 58.847
[2025-01-18 00:10:17 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 35.3%
[2025-01-18 00:10:17 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:10:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:10:19 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 35.33%
[2025-01-18 00:10:21 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][0/312]	eta 0:12:26 lr 0.003735	time 2.3941 (2.3941)	model_time 0.4792 (0.4792)	loss 3.4854 (3.4854)	grad_norm 1.0018 (1.0018/0.0000)	mem 16099MB
[2025-01-18 00:10:26 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][10/312]	eta 0:03:10 lr 0.003734	time 0.4574 (0.6322)	model_time 0.4568 (0.4576)	loss 2.8630 (3.6737)	grad_norm 1.1287 (1.2243/0.2493)	mem 16099MB
[2025-01-18 00:10:30 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][20/312]	eta 0:02:39 lr 0.003734	time 0.4491 (0.5477)	model_time 0.4487 (0.4561)	loss 4.6000 (3.7797)	grad_norm 1.2288 (1.2591/0.3905)	mem 16099MB
[2025-01-18 00:10:35 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][30/312]	eta 0:02:26 lr 0.003734	time 0.4397 (0.5192)	model_time 0.4396 (0.4570)	loss 3.8827 (3.8298)	grad_norm 0.9223 (1.2238/0.3755)	mem 16099MB
[2025-01-18 00:10:39 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][40/312]	eta 0:02:16 lr 0.003733	time 0.4476 (0.5029)	model_time 0.4475 (0.4558)	loss 4.6684 (3.7864)	grad_norm 0.9893 (1.1483/0.3579)	mem 16099MB
[2025-01-18 00:10:44 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][50/312]	eta 0:02:10 lr 0.003733	time 0.4442 (0.4993)	model_time 0.4436 (0.4614)	loss 3.3211 (3.6985)	grad_norm 1.5316 (1.1980/0.3926)	mem 16099MB
[2025-01-18 00:10:49 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][60/312]	eta 0:02:03 lr 0.003733	time 0.4567 (0.4906)	model_time 0.4565 (0.4588)	loss 3.8434 (3.7429)	grad_norm 1.8811 (1.2493/0.4046)	mem 16099MB
[2025-01-18 00:10:53 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][70/312]	eta 0:01:58 lr 0.003732	time 0.4437 (0.4903)	model_time 0.4435 (0.4629)	loss 4.2458 (3.7608)	grad_norm 2.1974 (1.4625/0.7557)	mem 16099MB
[2025-01-18 00:10:58 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][80/312]	eta 0:01:53 lr 0.003732	time 0.4511 (0.4896)	model_time 0.4506 (0.4656)	loss 3.2896 (3.7734)	grad_norm 2.1586 (1.5294/0.7575)	mem 16099MB
[2025-01-18 00:11:03 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][90/312]	eta 0:01:47 lr 0.003732	time 0.4495 (0.4857)	model_time 0.4493 (0.4642)	loss 3.3475 (3.7436)	grad_norm 1.5449 (1.5506/0.7517)	mem 16099MB
[2025-01-18 00:11:07 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][100/312]	eta 0:01:42 lr 0.003731	time 0.4518 (0.4831)	model_time 0.4516 (0.4637)	loss 3.8714 (3.7445)	grad_norm 2.2131 (1.5759/0.7432)	mem 16099MB
[2025-01-18 00:11:12 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][110/312]	eta 0:01:37 lr 0.003731	time 0.4865 (0.4811)	model_time 0.4863 (0.4635)	loss 3.8132 (3.7590)	grad_norm 2.5142 (1.6233/0.7643)	mem 16099MB
[2025-01-18 00:11:17 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][120/312]	eta 0:01:32 lr 0.003731	time 0.4589 (0.4796)	model_time 0.4588 (0.4634)	loss 3.5994 (3.7812)	grad_norm 1.3997 (1.7090/0.8525)	mem 16099MB
[2025-01-18 00:11:21 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][130/312]	eta 0:01:27 lr 0.003730	time 0.4393 (0.4786)	model_time 0.4392 (0.4636)	loss 3.1790 (3.7660)	grad_norm 1.6451 (1.7062/0.8208)	mem 16099MB
[2025-01-18 00:11:26 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][140/312]	eta 0:01:22 lr 0.003730	time 0.5296 (0.4786)	model_time 0.5295 (0.4646)	loss 2.9984 (3.7776)	grad_norm 1.7527 (1.7036/0.7969)	mem 16099MB
[2025-01-18 00:11:31 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][150/312]	eta 0:01:17 lr 0.003730	time 0.4690 (0.4773)	model_time 0.4686 (0.4643)	loss 3.6501 (3.7968)	grad_norm 1.4388 (1.7062/0.7819)	mem 16099MB
[2025-01-18 00:11:35 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][160/312]	eta 0:01:12 lr 0.003729	time 0.4444 (0.4764)	model_time 0.4440 (0.4642)	loss 3.7872 (3.7995)	grad_norm 1.8009 (1.6831/0.7650)	mem 16099MB
[2025-01-18 00:11:40 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][170/312]	eta 0:01:07 lr 0.003729	time 0.4568 (0.4750)	model_time 0.4563 (0.4635)	loss 4.6150 (3.7955)	grad_norm 2.8805 (1.6886/0.7616)	mem 16099MB
[2025-01-18 00:11:44 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][180/312]	eta 0:01:02 lr 0.003729	time 0.4412 (0.4744)	model_time 0.4408 (0.4634)	loss 4.2115 (3.7854)	grad_norm 3.4430 (1.7175/0.8085)	mem 16099MB
[2025-01-18 00:11:49 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][190/312]	eta 0:00:57 lr 0.003728	time 0.4550 (0.4733)	model_time 0.4546 (0.4629)	loss 2.5451 (3.7814)	grad_norm 1.8733 (1.7830/0.8957)	mem 16099MB
[2025-01-18 00:11:54 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][200/312]	eta 0:00:52 lr 0.003728	time 0.4422 (0.4722)	model_time 0.4418 (0.4623)	loss 4.2832 (3.7984)	grad_norm 3.4547 (1.8720/1.0933)	mem 16099MB
[2025-01-18 00:11:58 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][210/312]	eta 0:00:48 lr 0.003728	time 0.4412 (0.4722)	model_time 0.4408 (0.4627)	loss 3.4912 (3.8072)	grad_norm 2.2097 (1.9226/1.0976)	mem 16099MB
[2025-01-18 00:12:03 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][220/312]	eta 0:00:43 lr 0.003727	time 0.4494 (0.4715)	model_time 0.4489 (0.4624)	loss 4.1367 (3.8446)	grad_norm 5.2359 (2.0940/1.4997)	mem 16099MB
[2025-01-18 00:12:08 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][230/312]	eta 0:00:38 lr 0.003727	time 0.4703 (0.4720)	model_time 0.4701 (0.4633)	loss 4.5325 (3.8950)	grad_norm 1.9735 (2.1624/1.5318)	mem 16099MB
[2025-01-18 00:12:12 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][240/312]	eta 0:00:33 lr 0.003727	time 0.4428 (0.4715)	model_time 0.4424 (0.4632)	loss 4.9611 (3.9317)	grad_norm 6.2692 (2.1711/1.5272)	mem 16099MB
[2025-01-18 00:12:17 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][250/312]	eta 0:00:29 lr 0.003726	time 0.4572 (0.4710)	model_time 0.4568 (0.4630)	loss 3.4141 (3.9507)	grad_norm 1.6275 (2.1791/1.5088)	mem 16099MB
[2025-01-18 00:12:21 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][260/312]	eta 0:00:24 lr 0.003726	time 0.4512 (0.4703)	model_time 0.4508 (0.4625)	loss 4.0302 (3.9740)	grad_norm 1.6270 (2.1679/1.4840)	mem 16099MB
[2025-01-18 00:12:26 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][270/312]	eta 0:00:19 lr 0.003726	time 0.4526 (0.4696)	model_time 0.4525 (0.4622)	loss 4.3108 (3.9839)	grad_norm 1.4481 (2.1450/1.4619)	mem 16099MB
[2025-01-18 00:12:30 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][280/312]	eta 0:00:15 lr 0.003725	time 0.4457 (0.4691)	model_time 0.4455 (0.4619)	loss 5.0667 (3.9978)	grad_norm 0.8567 (2.1204/1.4465)	mem 16099MB
[2025-01-18 00:12:35 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][290/312]	eta 0:00:10 lr 0.003725	time 0.4400 (0.4688)	model_time 0.4398 (0.4619)	loss 4.5482 (3.9986)	grad_norm 2.5618 (2.1005/1.4283)	mem 16099MB
[2025-01-18 00:12:40 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][300/312]	eta 0:00:05 lr 0.003725	time 0.4362 (0.4683)	model_time 0.4362 (0.4616)	loss 3.6690 (4.0006)	grad_norm 2.0708 (2.1053/1.4149)	mem 16099MB
[2025-01-18 00:12:44 internimage_t_1k_224] (main.py 510): INFO Train: [50/300][310/312]	eta 0:00:00 lr 0.003724	time 0.4408 (0.4680)	model_time 0.4407 (0.4615)	loss 3.0746 (3.9946)	grad_norm 1.9460 (2.0998/1.4072)	mem 16099MB
[2025-01-18 00:12:45 internimage_t_1k_224] (main.py 519): INFO EPOCH 50 training takes 0:02:26
[2025-01-18 00:12:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_50.pth saving......
[2025-01-18 00:12:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_50.pth saved !!!
[2025-01-18 00:12:53 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.394 (7.394)	Loss 1.2151 (1.2151)	Acc@1 75.220 (75.220)	Acc@5 92.847 (92.847)	Mem 16099MB
[2025-01-18 00:12:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.996)	Loss 1.6910 (1.3977)	Acc@1 64.697 (71.382)	Acc@5 87.256 (90.654)	Mem 16099MB
[2025-01-18 00:12:57 internimage_t_1k_224] (main.py 575): INFO [Epoch:50] * Acc@1 71.345 Acc@5 90.751
[2025-01-18 00:12:57 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 71.3%
[2025-01-18 00:12:57 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 73.21%
[2025-01-18 00:13:05 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.143 (8.143)	Loss 3.6917 (3.6917)	Acc@1 36.353 (36.353)	Acc@5 59.253 (59.253)	Mem 16099MB
[2025-01-18 00:13:09 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.092)	Loss 3.7269 (3.5218)	Acc@1 33.789 (38.252)	Acc@5 56.787 (61.854)	Mem 16099MB
[2025-01-18 00:13:09 internimage_t_1k_224] (main.py 575): INFO [Epoch:50] * Acc@1 38.170 Acc@5 62.050
[2025-01-18 00:13:09 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 38.2%
[2025-01-18 00:13:09 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:13:11 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:13:11 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 38.17%
[2025-01-18 00:13:13 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][0/312]	eta 0:13:07 lr 0.003724	time 2.5233 (2.5233)	model_time 0.4845 (0.4845)	loss 4.1782 (4.1782)	grad_norm 1.3258 (1.3258/0.0000)	mem 16099MB
[2025-01-18 00:13:18 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][10/312]	eta 0:03:16 lr 0.003724	time 0.4511 (0.6512)	model_time 0.4510 (0.4655)	loss 4.8634 (3.8959)	grad_norm 2.8704 (1.7518/0.7388)	mem 16099MB
[2025-01-18 00:13:22 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][20/312]	eta 0:02:43 lr 0.003724	time 0.4405 (0.5610)	model_time 0.4403 (0.4636)	loss 3.3540 (3.6251)	grad_norm 1.6230 (1.7366/0.6957)	mem 16099MB
[2025-01-18 00:13:27 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][30/312]	eta 0:02:31 lr 0.003723	time 0.4405 (0.5361)	model_time 0.4401 (0.4700)	loss 4.5108 (3.7062)	grad_norm 1.5743 (1.7359/0.7590)	mem 16099MB
[2025-01-18 00:13:32 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][40/312]	eta 0:02:21 lr 0.003723	time 0.4382 (0.5186)	model_time 0.4381 (0.4685)	loss 3.6413 (3.6916)	grad_norm 1.6292 (1.7175/0.7362)	mem 16099MB
[2025-01-18 00:13:36 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][50/312]	eta 0:02:12 lr 0.003723	time 0.4540 (0.5062)	model_time 0.4538 (0.4659)	loss 4.7516 (3.7235)	grad_norm 1.2905 (1.6705/0.6807)	mem 16099MB
[2025-01-18 00:13:41 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][60/312]	eta 0:02:05 lr 0.003722	time 0.4567 (0.4973)	model_time 0.4563 (0.4635)	loss 4.0290 (3.7264)	grad_norm 0.7730 (1.5860/0.6628)	mem 16099MB
[2025-01-18 00:13:46 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][70/312]	eta 0:01:58 lr 0.003722	time 0.4494 (0.4917)	model_time 0.4493 (0.4626)	loss 2.7876 (3.7173)	grad_norm 0.9291 (1.5349/0.6387)	mem 16099MB
[2025-01-18 00:13:50 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][80/312]	eta 0:01:53 lr 0.003722	time 0.4477 (0.4879)	model_time 0.4473 (0.4624)	loss 3.8454 (3.6981)	grad_norm 1.0279 (1.4992/0.6180)	mem 16099MB
[2025-01-18 00:13:55 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][90/312]	eta 0:01:47 lr 0.003721	time 0.5528 (0.4861)	model_time 0.5526 (0.4633)	loss 4.3666 (3.7235)	grad_norm 4.3903 (1.5405/0.6778)	mem 16099MB
[2025-01-18 00:14:00 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][100/312]	eta 0:01:43 lr 0.003721	time 0.4475 (0.4867)	model_time 0.4474 (0.4662)	loss 3.6719 (3.7167)	grad_norm 1.4183 (1.5887/0.7238)	mem 16099MB
[2025-01-18 00:14:04 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][110/312]	eta 0:01:37 lr 0.003721	time 0.4469 (0.4849)	model_time 0.4467 (0.4662)	loss 2.9787 (3.7317)	grad_norm 0.7019 (1.6324/0.7699)	mem 16099MB
[2025-01-18 00:14:09 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][120/312]	eta 0:01:32 lr 0.003720	time 0.4529 (0.4839)	model_time 0.4525 (0.4667)	loss 4.1630 (3.7248)	grad_norm 1.1240 (1.5870/0.7565)	mem 16099MB
[2025-01-18 00:14:14 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][130/312]	eta 0:01:27 lr 0.003720	time 0.4549 (0.4825)	model_time 0.4547 (0.4665)	loss 3.4328 (3.7298)	grad_norm 0.6808 (1.5763/0.7491)	mem 16099MB
[2025-01-18 00:14:18 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][140/312]	eta 0:01:22 lr 0.003720	time 0.4528 (0.4803)	model_time 0.4523 (0.4655)	loss 2.8774 (3.7277)	grad_norm 0.8815 (1.5820/0.7490)	mem 16099MB
[2025-01-18 00:14:23 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][150/312]	eta 0:01:17 lr 0.003719	time 0.4462 (0.4787)	model_time 0.4458 (0.4649)	loss 4.3680 (3.7242)	grad_norm 1.0825 (1.5619/0.7374)	mem 16099MB
[2025-01-18 00:14:28 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][160/312]	eta 0:01:12 lr 0.003719	time 0.4593 (0.4799)	model_time 0.4589 (0.4668)	loss 4.1255 (3.7287)	grad_norm 2.7243 (1.6262/0.8045)	mem 16099MB
[2025-01-18 00:14:32 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][170/312]	eta 0:01:07 lr 0.003718	time 0.4619 (0.4782)	model_time 0.4618 (0.4659)	loss 4.7717 (3.7458)	grad_norm 0.7016 (1.6034/0.7958)	mem 16099MB
[2025-01-18 00:14:37 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][180/312]	eta 0:01:02 lr 0.003718	time 0.4973 (0.4771)	model_time 0.4971 (0.4655)	loss 2.9325 (3.7394)	grad_norm 1.0641 (1.5918/0.7799)	mem 16099MB
[2025-01-18 00:14:42 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][190/312]	eta 0:00:58 lr 0.003718	time 0.4424 (0.4761)	model_time 0.4422 (0.4650)	loss 3.7747 (3.7281)	grad_norm 1.6867 (1.5941/0.7693)	mem 16099MB
[2025-01-18 00:14:46 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][200/312]	eta 0:00:53 lr 0.003717	time 0.4440 (0.4754)	model_time 0.4436 (0.4649)	loss 3.2680 (3.7258)	grad_norm 0.7502 (1.5632/0.7640)	mem 16099MB
[2025-01-18 00:14:51 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][210/312]	eta 0:00:48 lr 0.003717	time 0.4524 (0.4743)	model_time 0.4523 (0.4643)	loss 2.5002 (3.7253)	grad_norm 1.0696 (1.5347/0.7575)	mem 16099MB
[2025-01-18 00:14:55 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][220/312]	eta 0:00:43 lr 0.003717	time 0.4442 (0.4734)	model_time 0.4441 (0.4639)	loss 3.3405 (3.7221)	grad_norm 0.9960 (1.5565/0.7990)	mem 16099MB
[2025-01-18 00:15:00 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][230/312]	eta 0:00:38 lr 0.003716	time 0.4620 (0.4732)	model_time 0.4619 (0.4640)	loss 2.9642 (3.7269)	grad_norm 1.6574 (1.5796/0.8226)	mem 16099MB
[2025-01-18 00:15:05 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][240/312]	eta 0:00:34 lr 0.003716	time 0.4396 (0.4731)	model_time 0.4391 (0.4643)	loss 3.2450 (3.7355)	grad_norm 1.6885 (1.5692/0.8091)	mem 16099MB
[2025-01-18 00:15:09 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][250/312]	eta 0:00:29 lr 0.003716	time 0.4478 (0.4731)	model_time 0.4477 (0.4646)	loss 2.6169 (3.7311)	grad_norm 1.0977 (1.5563/0.7991)	mem 16099MB
[2025-01-18 00:15:14 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][260/312]	eta 0:00:24 lr 0.003715	time 0.4757 (0.4728)	model_time 0.4753 (0.4646)	loss 3.8578 (3.7310)	grad_norm 2.2621 (1.5610/0.7985)	mem 16099MB
[2025-01-18 00:15:19 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][270/312]	eta 0:00:19 lr 0.003715	time 0.4388 (0.4721)	model_time 0.4386 (0.4642)	loss 3.5762 (3.7172)	grad_norm 1.4656 (1.5418/0.7919)	mem 16099MB
[2025-01-18 00:15:24 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][280/312]	eta 0:00:15 lr 0.003715	time 0.4561 (0.4730)	model_time 0.4555 (0.4654)	loss 4.0163 (3.7185)	grad_norm 1.1770 (1.5370/0.7816)	mem 16099MB
[2025-01-18 00:15:28 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][290/312]	eta 0:00:10 lr 0.003714	time 0.4452 (0.4731)	model_time 0.4450 (0.4657)	loss 4.4374 (3.7266)	grad_norm 1.8700 (1.5464/0.7787)	mem 16099MB
[2025-01-18 00:15:33 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][300/312]	eta 0:00:05 lr 0.003714	time 0.4381 (0.4723)	model_time 0.4381 (0.4651)	loss 2.8526 (3.7289)	grad_norm 1.0942 (1.5490/0.7756)	mem 16099MB
[2025-01-18 00:15:37 internimage_t_1k_224] (main.py 510): INFO Train: [51/300][310/312]	eta 0:00:00 lr 0.003714	time 0.4389 (0.4714)	model_time 0.4388 (0.4645)	loss 3.9805 (3.7253)	grad_norm 1.2653 (1.5389/0.7657)	mem 16099MB
[2025-01-18 00:15:38 internimage_t_1k_224] (main.py 519): INFO EPOCH 51 training takes 0:02:27
[2025-01-18 00:15:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_51.pth saving......
[2025-01-18 00:15:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_51.pth saved !!!
[2025-01-18 00:15:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.187 (7.187)	Loss 1.0537 (1.0537)	Acc@1 76.953 (76.953)	Acc@5 94.141 (94.141)	Mem 16099MB
[2025-01-18 00:15:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.978)	Loss 1.5057 (1.2449)	Acc@1 67.334 (73.184)	Acc@5 88.403 (91.915)	Mem 16099MB
[2025-01-18 00:15:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:51] * Acc@1 73.071 Acc@5 91.905
[2025-01-18 00:15:50 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 73.1%
[2025-01-18 00:15:50 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 73.21%
[2025-01-18 00:15:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.132 (8.132)	Loss 3.4775 (3.4775)	Acc@1 39.551 (39.551)	Acc@5 63.525 (63.525)	Mem 16099MB
[2025-01-18 00:16:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.095)	Loss 3.5704 (3.3476)	Acc@1 35.889 (40.831)	Acc@5 60.010 (65.006)	Mem 16099MB
[2025-01-18 00:16:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:51] * Acc@1 40.751 Acc@5 65.195
[2025-01-18 00:16:02 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 40.8%
[2025-01-18 00:16:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:16:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:16:03 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 40.75%
[2025-01-18 00:16:06 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][0/312]	eta 0:13:37 lr 0.003714	time 2.6207 (2.6207)	model_time 0.4606 (0.4606)	loss 3.8953 (3.8953)	grad_norm 1.0420 (1.0420/0.0000)	mem 16099MB
[2025-01-18 00:16:11 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][10/312]	eta 0:03:16 lr 0.003713	time 0.4521 (0.6519)	model_time 0.4520 (0.4552)	loss 2.8383 (3.6804)	grad_norm 3.0162 (1.5616/0.6466)	mem 16099MB
[2025-01-18 00:16:15 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][20/312]	eta 0:02:43 lr 0.003713	time 0.5326 (0.5612)	model_time 0.5325 (0.4581)	loss 4.4877 (3.6348)	grad_norm 1.5977 (1.6323/0.7416)	mem 16099MB
[2025-01-18 00:16:20 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][30/312]	eta 0:02:30 lr 0.003713	time 0.4487 (0.5336)	model_time 0.4485 (0.4637)	loss 3.5167 (3.6253)	grad_norm 1.0927 (1.6326/0.6726)	mem 16099MB
[2025-01-18 00:16:25 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][40/312]	eta 0:02:22 lr 0.003712	time 0.4427 (0.5229)	model_time 0.4426 (0.4699)	loss 4.2733 (3.6663)	grad_norm 0.8951 (1.6170/0.6264)	mem 16099MB
[2025-01-18 00:16:30 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][50/312]	eta 0:02:13 lr 0.003712	time 0.4481 (0.5107)	model_time 0.4480 (0.4681)	loss 4.2915 (3.6234)	grad_norm 2.4445 (1.5703/0.6279)	mem 16099MB
[2025-01-18 00:16:34 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][60/312]	eta 0:02:06 lr 0.003712	time 0.4657 (0.5016)	model_time 0.4655 (0.4659)	loss 3.3703 (3.6391)	grad_norm 3.9711 (1.6039/0.6896)	mem 16099MB
[2025-01-18 00:16:39 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][70/312]	eta 0:01:59 lr 0.003711	time 0.4505 (0.4947)	model_time 0.4503 (0.4639)	loss 4.0728 (3.6445)	grad_norm 2.4418 (1.6234/0.6813)	mem 16099MB
[2025-01-18 00:16:43 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][80/312]	eta 0:01:54 lr 0.003711	time 0.5344 (0.4920)	model_time 0.5339 (0.4650)	loss 3.7405 (3.6218)	grad_norm 1.1451 (1.6913/0.8430)	mem 16099MB
[2025-01-18 00:16:48 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][90/312]	eta 0:01:48 lr 0.003711	time 0.4418 (0.4873)	model_time 0.4416 (0.4632)	loss 4.8216 (3.6495)	grad_norm 0.7029 (1.6448/0.8280)	mem 16099MB
[2025-01-18 00:16:52 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][100/312]	eta 0:01:42 lr 0.003710	time 0.4501 (0.4849)	model_time 0.4497 (0.4632)	loss 3.4538 (3.6621)	grad_norm 1.0992 (1.5908/0.8119)	mem 16099MB
[2025-01-18 00:16:57 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][110/312]	eta 0:01:37 lr 0.003710	time 0.4584 (0.4840)	model_time 0.4579 (0.4641)	loss 4.3843 (3.6589)	grad_norm 0.9879 (1.5462/0.7899)	mem 16099MB
[2025-01-18 00:17:02 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][120/312]	eta 0:01:32 lr 0.003709	time 0.4606 (0.4814)	model_time 0.4602 (0.4632)	loss 3.0068 (3.6466)	grad_norm 1.8251 (1.5274/0.7618)	mem 16099MB
[2025-01-18 00:17:06 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][130/312]	eta 0:01:27 lr 0.003709	time 0.4732 (0.4798)	model_time 0.4731 (0.4629)	loss 2.4804 (3.6283)	grad_norm 0.8576 (1.4935/0.7459)	mem 16099MB
[2025-01-18 00:17:11 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][140/312]	eta 0:01:22 lr 0.003709	time 0.4477 (0.4783)	model_time 0.4475 (0.4627)	loss 3.8096 (3.6291)	grad_norm 1.5349 (1.4922/0.7309)	mem 16099MB
[2025-01-18 00:17:16 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][150/312]	eta 0:01:17 lr 0.003708	time 0.4527 (0.4804)	model_time 0.4525 (0.4657)	loss 4.2435 (3.6289)	grad_norm 1.0222 (1.5012/0.7231)	mem 16099MB
[2025-01-18 00:17:21 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][160/312]	eta 0:01:12 lr 0.003708	time 0.4484 (0.4785)	model_time 0.4480 (0.4647)	loss 3.7289 (3.6246)	grad_norm 3.6917 (1.5168/0.7420)	mem 16099MB
[2025-01-18 00:17:25 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][170/312]	eta 0:01:07 lr 0.003708	time 0.4399 (0.4768)	model_time 0.4397 (0.4638)	loss 4.0448 (3.6369)	grad_norm 0.8238 (1.5076/0.7339)	mem 16099MB
[2025-01-18 00:17:30 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][180/312]	eta 0:01:02 lr 0.003707	time 0.4638 (0.4756)	model_time 0.4633 (0.4633)	loss 3.4042 (3.6336)	grad_norm 1.0711 (1.5167/0.7322)	mem 16099MB
[2025-01-18 00:17:34 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][190/312]	eta 0:00:57 lr 0.003707	time 0.4453 (0.4748)	model_time 0.4451 (0.4632)	loss 3.9317 (3.6422)	grad_norm 4.7431 (1.5310/0.7675)	mem 16099MB
[2025-01-18 00:17:39 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][200/312]	eta 0:00:53 lr 0.003707	time 0.4464 (0.4772)	model_time 0.4459 (0.4661)	loss 4.0691 (3.6353)	grad_norm 0.9803 (1.5397/0.7610)	mem 16099MB
[2025-01-18 00:17:44 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][210/312]	eta 0:00:48 lr 0.003706	time 0.4533 (0.4772)	model_time 0.4529 (0.4666)	loss 4.8050 (3.6341)	grad_norm 0.8059 (1.5164/0.7510)	mem 16099MB
[2025-01-18 00:17:49 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][220/312]	eta 0:00:43 lr 0.003706	time 0.4462 (0.4770)	model_time 0.4460 (0.4669)	loss 4.6156 (3.6609)	grad_norm 0.7376 (1.5024/0.7406)	mem 16099MB
[2025-01-18 00:17:53 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][230/312]	eta 0:00:39 lr 0.003706	time 0.4694 (0.4761)	model_time 0.4692 (0.4664)	loss 3.5184 (3.6471)	grad_norm 1.5224 (1.5011/0.7307)	mem 16099MB
[2025-01-18 00:17:58 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][240/312]	eta 0:00:34 lr 0.003705	time 0.4494 (0.4751)	model_time 0.4490 (0.4658)	loss 3.6471 (3.6434)	grad_norm 2.4868 (1.4869/0.7259)	mem 16099MB
[2025-01-18 00:18:03 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][250/312]	eta 0:00:29 lr 0.003705	time 0.4504 (0.4741)	model_time 0.4499 (0.4651)	loss 3.5519 (3.6487)	grad_norm 1.1700 (1.4986/0.7432)	mem 16099MB
[2025-01-18 00:18:07 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][260/312]	eta 0:00:24 lr 0.003705	time 0.4464 (0.4738)	model_time 0.4459 (0.4652)	loss 4.6469 (3.6478)	grad_norm 1.4231 (1.5172/0.7561)	mem 16099MB
[2025-01-18 00:18:12 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][270/312]	eta 0:00:19 lr 0.003704	time 0.4474 (0.4733)	model_time 0.4472 (0.4650)	loss 4.4481 (3.6462)	grad_norm 0.7608 (1.5047/0.7470)	mem 16099MB
[2025-01-18 00:18:16 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][280/312]	eta 0:00:15 lr 0.003704	time 0.4503 (0.4728)	model_time 0.4501 (0.4647)	loss 4.3076 (3.6594)	grad_norm 1.3605 (1.4902/0.7405)	mem 16099MB
[2025-01-18 00:18:21 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][290/312]	eta 0:00:10 lr 0.003704	time 0.4589 (0.4723)	model_time 0.4585 (0.4646)	loss 3.7540 (3.6656)	grad_norm 1.0339 (1.4781/0.7338)	mem 16099MB
[2025-01-18 00:18:25 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][300/312]	eta 0:00:05 lr 0.003703	time 0.4385 (0.4716)	model_time 0.4384 (0.4641)	loss 4.0262 (3.6605)	grad_norm 2.0858 (1.4733/0.7273)	mem 16099MB
[2025-01-18 00:18:30 internimage_t_1k_224] (main.py 510): INFO Train: [52/300][310/312]	eta 0:00:00 lr 0.003703	time 0.4369 (0.4706)	model_time 0.4368 (0.4633)	loss 3.6507 (3.6558)	grad_norm 1.7165 (1.4768/0.7334)	mem 16099MB
[2025-01-18 00:18:30 internimage_t_1k_224] (main.py 519): INFO EPOCH 52 training takes 0:02:26
[2025-01-18 00:18:30 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_52.pth saving......
[2025-01-18 00:18:31 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_52.pth saved !!!
[2025-01-18 00:18:39 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.538 (7.538)	Loss 1.0053 (1.0053)	Acc@1 77.319 (77.319)	Acc@5 94.263 (94.263)	Mem 16099MB
[2025-01-18 00:18:43 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.014)	Loss 1.4719 (1.1947)	Acc@1 67.358 (73.509)	Acc@5 88.574 (91.850)	Mem 16099MB
[2025-01-18 00:18:43 internimage_t_1k_224] (main.py 575): INFO [Epoch:52] * Acc@1 73.532 Acc@5 91.939
[2025-01-18 00:18:43 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 73.5%
[2025-01-18 00:18:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 00:18:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 00:18:44 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 73.53%
[2025-01-18 00:18:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.509 (7.509)	Loss 3.2939 (3.2939)	Acc@1 42.310 (42.310)	Acc@5 66.870 (66.870)	Mem 16099MB
[2025-01-18 00:18:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.015)	Loss 3.4406 (3.2015)	Acc@1 37.598 (43.277)	Acc@5 62.524 (67.489)	Mem 16099MB
[2025-01-18 00:18:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:52] * Acc@1 43.206 Acc@5 67.684
[2025-01-18 00:18:55 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 43.2%
[2025-01-18 00:18:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:18:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:18:57 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 43.21%
[2025-01-18 00:18:59 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][0/312]	eta 0:12:58 lr 0.003703	time 2.4942 (2.4942)	model_time 0.5905 (0.5905)	loss 3.6645 (3.6645)	grad_norm 1.7624 (1.7624/0.0000)	mem 16099MB
[2025-01-18 00:19:04 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][10/312]	eta 0:03:17 lr 0.003702	time 0.4425 (0.6542)	model_time 0.4420 (0.4807)	loss 2.7203 (3.5501)	grad_norm 1.0634 (1.1040/0.3190)	mem 16099MB
[2025-01-18 00:19:09 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][20/312]	eta 0:02:44 lr 0.003702	time 0.4432 (0.5649)	model_time 0.4431 (0.4739)	loss 3.5728 (3.4343)	grad_norm 1.5022 (1.3681/0.4641)	mem 16099MB
[2025-01-18 00:19:13 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][30/312]	eta 0:02:29 lr 0.003702	time 0.4387 (0.5286)	model_time 0.4385 (0.4669)	loss 3.5953 (3.5044)	grad_norm 1.1771 (1.4074/0.4819)	mem 16099MB
[2025-01-18 00:19:18 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][40/312]	eta 0:02:19 lr 0.003701	time 0.4597 (0.5110)	model_time 0.4595 (0.4642)	loss 4.1602 (3.5341)	grad_norm 3.7126 (1.4454/0.5754)	mem 16099MB
[2025-01-18 00:19:22 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][50/312]	eta 0:02:11 lr 0.003701	time 0.4492 (0.5010)	model_time 0.4488 (0.4633)	loss 3.8729 (3.6274)	grad_norm 1.4085 (1.5551/0.7203)	mem 16099MB
[2025-01-18 00:19:27 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][60/312]	eta 0:02:04 lr 0.003701	time 0.4405 (0.4934)	model_time 0.4404 (0.4618)	loss 2.5207 (3.5944)	grad_norm 0.8480 (1.5624/0.6989)	mem 16099MB
[2025-01-18 00:19:31 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][70/312]	eta 0:01:57 lr 0.003700	time 0.4580 (0.4875)	model_time 0.4579 (0.4603)	loss 3.6532 (3.5927)	grad_norm 2.2536 (1.6053/0.7005)	mem 16099MB
[2025-01-18 00:19:36 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][80/312]	eta 0:01:52 lr 0.003700	time 0.4512 (0.4843)	model_time 0.4507 (0.4604)	loss 4.0147 (3.5903)	grad_norm 1.0429 (1.5602/0.6828)	mem 16099MB
[2025-01-18 00:19:41 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][90/312]	eta 0:01:47 lr 0.003700	time 0.4968 (0.4825)	model_time 0.4964 (0.4612)	loss 4.0751 (3.5901)	grad_norm 0.9473 (1.5257/0.6646)	mem 16099MB
[2025-01-18 00:19:45 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][100/312]	eta 0:01:41 lr 0.003699	time 0.4707 (0.4798)	model_time 0.4703 (0.4606)	loss 3.3077 (3.5964)	grad_norm 1.6571 (1.5211/0.6776)	mem 16099MB
[2025-01-18 00:19:50 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][110/312]	eta 0:01:36 lr 0.003699	time 0.4519 (0.4789)	model_time 0.4515 (0.4614)	loss 3.8535 (3.6079)	grad_norm 1.1096 (1.4727/0.6711)	mem 16099MB
[2025-01-18 00:19:55 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][120/312]	eta 0:01:31 lr 0.003699	time 0.5439 (0.4788)	model_time 0.5438 (0.4627)	loss 3.3577 (3.6003)	grad_norm 1.4396 (1.4733/0.6675)	mem 16099MB
[2025-01-18 00:20:00 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][130/312]	eta 0:01:27 lr 0.003698	time 0.4471 (0.4807)	model_time 0.4469 (0.4658)	loss 4.0147 (3.6034)	grad_norm 1.7499 (1.5318/0.7407)	mem 16099MB
[2025-01-18 00:20:04 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][140/312]	eta 0:01:22 lr 0.003698	time 0.4401 (0.4788)	model_time 0.4396 (0.4649)	loss 3.4256 (3.5960)	grad_norm 1.2161 (1.5464/0.7730)	mem 16099MB
[2025-01-18 00:20:09 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][150/312]	eta 0:01:17 lr 0.003698	time 0.5297 (0.4780)	model_time 0.5295 (0.4650)	loss 3.3535 (3.6071)	grad_norm 0.9695 (1.5144/0.7613)	mem 16099MB
[2025-01-18 00:20:13 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][160/312]	eta 0:01:12 lr 0.003697	time 0.4472 (0.4768)	model_time 0.4470 (0.4646)	loss 3.7311 (3.6250)	grad_norm 1.5832 (1.4952/0.7448)	mem 16099MB
[2025-01-18 00:20:18 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][170/312]	eta 0:01:07 lr 0.003697	time 0.4417 (0.4761)	model_time 0.4412 (0.4646)	loss 4.2908 (3.6471)	grad_norm 0.8280 (1.4772/0.7307)	mem 16099MB
[2025-01-18 00:20:23 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][180/312]	eta 0:01:02 lr 0.003696	time 0.4530 (0.4754)	model_time 0.4529 (0.4645)	loss 3.9381 (3.6482)	grad_norm 2.4203 (1.5081/0.7647)	mem 16099MB
[2025-01-18 00:20:27 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][190/312]	eta 0:00:57 lr 0.003696	time 0.4513 (0.4741)	model_time 0.4511 (0.4637)	loss 4.1936 (3.6340)	grad_norm 1.3400 (1.4937/0.7526)	mem 16099MB
[2025-01-18 00:20:32 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][200/312]	eta 0:00:53 lr 0.003696	time 0.5256 (0.4733)	model_time 0.5252 (0.4635)	loss 3.5305 (3.6310)	grad_norm 1.2371 (1.4931/0.7538)	mem 16099MB
[2025-01-18 00:20:37 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][210/312]	eta 0:00:48 lr 0.003695	time 0.4396 (0.4733)	model_time 0.4392 (0.4639)	loss 4.7512 (3.6413)	grad_norm 1.8214 (1.4895/0.7449)	mem 16099MB
[2025-01-18 00:20:41 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][220/312]	eta 0:00:43 lr 0.003695	time 0.4565 (0.4724)	model_time 0.4563 (0.4634)	loss 3.9673 (3.6521)	grad_norm 0.7758 (1.4756/0.7333)	mem 16099MB
[2025-01-18 00:20:46 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][230/312]	eta 0:00:38 lr 0.003695	time 0.4475 (0.4720)	model_time 0.4470 (0.4633)	loss 3.4140 (3.6624)	grad_norm 1.6153 (1.5364/0.8376)	mem 16099MB
[2025-01-18 00:20:50 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][240/312]	eta 0:00:33 lr 0.003694	time 0.4385 (0.4720)	model_time 0.4383 (0.4637)	loss 3.9752 (3.6785)	grad_norm 0.7874 (1.5417/0.8313)	mem 16099MB
[2025-01-18 00:20:55 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][250/312]	eta 0:00:29 lr 0.003694	time 0.4493 (0.4718)	model_time 0.4492 (0.4639)	loss 3.6750 (3.6674)	grad_norm 1.0631 (1.5293/0.8204)	mem 16099MB
[2025-01-18 00:21:00 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][260/312]	eta 0:00:24 lr 0.003694	time 0.4494 (0.4712)	model_time 0.4493 (0.4635)	loss 3.4646 (3.6540)	grad_norm 1.1998 (1.5234/0.8107)	mem 16099MB
[2025-01-18 00:21:04 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][270/312]	eta 0:00:19 lr 0.003693	time 0.4499 (0.4705)	model_time 0.4495 (0.4631)	loss 4.4332 (3.6546)	grad_norm 2.2069 (1.5294/0.8007)	mem 16099MB
[2025-01-18 00:21:09 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][280/312]	eta 0:00:15 lr 0.003693	time 0.4472 (0.4703)	model_time 0.4468 (0.4631)	loss 2.3749 (3.6399)	grad_norm 1.0575 (1.5282/0.7902)	mem 16099MB
[2025-01-18 00:21:13 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][290/312]	eta 0:00:10 lr 0.003693	time 0.4409 (0.4700)	model_time 0.4405 (0.4631)	loss 4.1023 (3.6477)	grad_norm 1.3809 (1.5179/0.7805)	mem 16099MB
[2025-01-18 00:21:18 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][300/312]	eta 0:00:05 lr 0.003692	time 0.4367 (0.4699)	model_time 0.4366 (0.4632)	loss 3.8539 (3.6519)	grad_norm 1.4645 (1.5197/0.7786)	mem 16099MB
[2025-01-18 00:21:23 internimage_t_1k_224] (main.py 510): INFO Train: [53/300][310/312]	eta 0:00:00 lr 0.003692	time 0.4409 (0.4691)	model_time 0.4408 (0.4626)	loss 3.3275 (3.6542)	grad_norm 1.1713 (1.5302/0.7801)	mem 16099MB
[2025-01-18 00:21:23 internimage_t_1k_224] (main.py 519): INFO EPOCH 53 training takes 0:02:26
[2025-01-18 00:21:23 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_53.pth saving......
[2025-01-18 00:21:24 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_53.pth saved !!!
[2025-01-18 00:21:31 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.318 (7.318)	Loss 1.0532 (1.0532)	Acc@1 78.101 (78.101)	Acc@5 94.629 (94.629)	Mem 16099MB
[2025-01-18 00:21:35 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.984)	Loss 1.4689 (1.2394)	Acc@1 68.140 (73.706)	Acc@5 89.111 (92.068)	Mem 16099MB
[2025-01-18 00:21:35 internimage_t_1k_224] (main.py 575): INFO [Epoch:53] * Acc@1 73.740 Acc@5 92.214
[2025-01-18 00:21:35 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 73.7%
[2025-01-18 00:21:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 00:21:36 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 00:21:36 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 73.74%
[2025-01-18 00:21:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.462 (7.462)	Loss 3.1276 (3.1276)	Acc@1 44.971 (44.971)	Acc@5 69.409 (69.409)	Mem 16099MB
[2025-01-18 00:21:47 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.008)	Loss 3.3191 (3.0665)	Acc@1 39.697 (45.364)	Acc@5 64.990 (69.684)	Mem 16099MB
[2025-01-18 00:21:48 internimage_t_1k_224] (main.py 575): INFO [Epoch:53] * Acc@1 45.278 Acc@5 69.858
[2025-01-18 00:21:48 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 45.3%
[2025-01-18 00:21:48 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:21:49 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:21:49 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 45.28%
[2025-01-18 00:21:52 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][0/312]	eta 0:13:45 lr 0.003692	time 2.6454 (2.6454)	model_time 0.4824 (0.4824)	loss 4.5264 (4.5264)	grad_norm 1.0944 (1.0944/0.0000)	mem 16099MB
[2025-01-18 00:21:56 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][10/312]	eta 0:03:17 lr 0.003691	time 0.4526 (0.6540)	model_time 0.4520 (0.4571)	loss 2.3189 (3.4682)	grad_norm 0.9323 (1.0037/0.1099)	mem 16099MB
[2025-01-18 00:22:01 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][20/312]	eta 0:02:43 lr 0.003691	time 0.4466 (0.5583)	model_time 0.4465 (0.4550)	loss 3.5736 (3.6633)	grad_norm 1.2312 (1.1332/0.2597)	mem 16099MB
[2025-01-18 00:22:06 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][30/312]	eta 0:02:29 lr 0.003691	time 0.4517 (0.5311)	model_time 0.4515 (0.4610)	loss 4.4224 (3.6687)	grad_norm 2.3310 (1.4081/0.5796)	mem 16099MB
[2025-01-18 00:22:10 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][40/312]	eta 0:02:19 lr 0.003690	time 0.4576 (0.5123)	model_time 0.4575 (0.4592)	loss 3.1200 (3.6494)	grad_norm 2.1378 (1.4560/0.5469)	mem 16099MB
[2025-01-18 00:22:15 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][50/312]	eta 0:02:11 lr 0.003690	time 0.4513 (0.5031)	model_time 0.4509 (0.4604)	loss 4.2503 (3.6481)	grad_norm 1.0310 (1.4425/0.5461)	mem 16099MB
[2025-01-18 00:22:19 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][60/312]	eta 0:02:05 lr 0.003690	time 0.4473 (0.4962)	model_time 0.4468 (0.4604)	loss 3.0616 (3.5887)	grad_norm 0.9657 (1.4436/0.5212)	mem 16099MB
[2025-01-18 00:22:24 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][70/312]	eta 0:01:58 lr 0.003689	time 0.4570 (0.4903)	model_time 0.4568 (0.4595)	loss 4.1887 (3.6283)	grad_norm 1.0052 (1.4371/0.5165)	mem 16099MB
[2025-01-18 00:22:29 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][80/312]	eta 0:01:53 lr 0.003689	time 0.4520 (0.4888)	model_time 0.4518 (0.4617)	loss 3.1844 (3.6072)	grad_norm 0.9290 (1.4511/0.5405)	mem 16099MB
[2025-01-18 00:22:33 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][90/312]	eta 0:01:48 lr 0.003689	time 0.5593 (0.4877)	model_time 0.5591 (0.4635)	loss 3.8795 (3.5840)	grad_norm 0.9689 (1.4205/0.5221)	mem 16099MB
[2025-01-18 00:22:38 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][100/312]	eta 0:01:43 lr 0.003688	time 0.4393 (0.4863)	model_time 0.4391 (0.4646)	loss 4.1080 (3.6139)	grad_norm 1.8443 (1.4737/0.5915)	mem 16099MB
[2025-01-18 00:22:43 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][110/312]	eta 0:01:38 lr 0.003688	time 0.4510 (0.4857)	model_time 0.4506 (0.4659)	loss 3.0957 (3.6269)	grad_norm 1.0005 (1.5463/0.6924)	mem 16099MB
[2025-01-18 00:22:48 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][120/312]	eta 0:01:32 lr 0.003687	time 0.4401 (0.4837)	model_time 0.4399 (0.4654)	loss 3.2964 (3.6111)	grad_norm 1.2318 (1.5530/0.6940)	mem 16099MB
[2025-01-18 00:22:52 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][130/312]	eta 0:01:27 lr 0.003687	time 0.4513 (0.4825)	model_time 0.4509 (0.4656)	loss 2.4728 (3.6246)	grad_norm 0.9521 (1.5042/0.6890)	mem 16099MB
[2025-01-18 00:22:57 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][140/312]	eta 0:01:23 lr 0.003687	time 0.5691 (0.4832)	model_time 0.5687 (0.4675)	loss 3.0983 (3.6115)	grad_norm 1.1033 (1.4731/0.6766)	mem 16099MB
[2025-01-18 00:23:02 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][150/312]	eta 0:01:17 lr 0.003686	time 0.4441 (0.4811)	model_time 0.4437 (0.4664)	loss 3.4692 (3.6158)	grad_norm 1.1264 (1.4737/0.6753)	mem 16099MB
[2025-01-18 00:23:06 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][160/312]	eta 0:01:12 lr 0.003686	time 0.4589 (0.4795)	model_time 0.4588 (0.4657)	loss 4.5367 (3.6210)	grad_norm 1.7871 (1.5143/0.7151)	mem 16099MB
[2025-01-18 00:23:11 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][170/312]	eta 0:01:07 lr 0.003686	time 0.4388 (0.4784)	model_time 0.4384 (0.4653)	loss 3.7995 (3.6170)	grad_norm 1.2384 (1.5358/0.7186)	mem 16099MB
[2025-01-18 00:23:16 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][180/312]	eta 0:01:03 lr 0.003685	time 0.4848 (0.4778)	model_time 0.4847 (0.4655)	loss 2.3223 (3.5991)	grad_norm 0.9776 (1.5174/0.7058)	mem 16099MB
[2025-01-18 00:23:20 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][190/312]	eta 0:00:58 lr 0.003685	time 0.4564 (0.4764)	model_time 0.4562 (0.4647)	loss 3.7789 (3.5865)	grad_norm 1.0325 (1.4962/0.6960)	mem 16099MB
[2025-01-18 00:23:25 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][200/312]	eta 0:00:53 lr 0.003685	time 0.4600 (0.4758)	model_time 0.4595 (0.4647)	loss 2.4361 (3.5842)	grad_norm 0.9361 (1.4724/0.6910)	mem 16099MB
[2025-01-18 00:23:29 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][210/312]	eta 0:00:48 lr 0.003684	time 0.4494 (0.4751)	model_time 0.4493 (0.4645)	loss 3.8780 (3.5850)	grad_norm 0.9708 (1.4717/0.6869)	mem 16099MB
[2025-01-18 00:23:34 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][220/312]	eta 0:00:43 lr 0.003684	time 0.4389 (0.4744)	model_time 0.4385 (0.4642)	loss 3.0508 (3.5883)	grad_norm 1.0200 (1.4562/0.6785)	mem 16099MB
[2025-01-18 00:23:38 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][230/312]	eta 0:00:38 lr 0.003684	time 0.4720 (0.4734)	model_time 0.4715 (0.4637)	loss 3.1334 (3.5886)	grad_norm 1.5708 (1.4732/0.7056)	mem 16099MB
[2025-01-18 00:23:43 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][240/312]	eta 0:00:34 lr 0.003683	time 0.4573 (0.4727)	model_time 0.4569 (0.4634)	loss 3.3230 (3.6022)	grad_norm 0.7905 (1.4609/0.6978)	mem 16099MB
[2025-01-18 00:23:48 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][250/312]	eta 0:00:29 lr 0.003683	time 0.4959 (0.4724)	model_time 0.4957 (0.4634)	loss 3.7783 (3.6037)	grad_norm 2.0139 (1.4607/0.6912)	mem 16099MB
[2025-01-18 00:23:52 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][260/312]	eta 0:00:24 lr 0.003682	time 0.4487 (0.4725)	model_time 0.4486 (0.4638)	loss 3.9766 (3.6081)	grad_norm 1.8240 (1.4796/0.7073)	mem 16099MB
[2025-01-18 00:23:57 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][270/312]	eta 0:00:19 lr 0.003682	time 0.4607 (0.4718)	model_time 0.4605 (0.4635)	loss 4.1004 (3.6191)	grad_norm 1.9287 (1.4761/0.7018)	mem 16099MB
[2025-01-18 00:24:02 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][280/312]	eta 0:00:15 lr 0.003682	time 0.4590 (0.4713)	model_time 0.4586 (0.4632)	loss 2.5807 (3.6108)	grad_norm 1.0288 (1.4709/0.6912)	mem 16099MB
[2025-01-18 00:24:06 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][290/312]	eta 0:00:10 lr 0.003681	time 0.4539 (0.4712)	model_time 0.4535 (0.4634)	loss 3.9390 (3.6156)	grad_norm 1.0465 (1.4696/0.6892)	mem 16099MB
[2025-01-18 00:24:11 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][300/312]	eta 0:00:05 lr 0.003681	time 0.4388 (0.4713)	model_time 0.4387 (0.4638)	loss 4.3868 (3.6181)	grad_norm 1.1072 (1.5094/0.7454)	mem 16099MB
[2025-01-18 00:24:16 internimage_t_1k_224] (main.py 510): INFO Train: [54/300][310/312]	eta 0:00:00 lr 0.003681	time 0.4389 (0.4712)	model_time 0.4388 (0.4639)	loss 4.3711 (3.6285)	grad_norm 1.6934 (1.5211/0.7457)	mem 16099MB
[2025-01-18 00:24:16 internimage_t_1k_224] (main.py 519): INFO EPOCH 54 training takes 0:02:27
[2025-01-18 00:24:16 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_54.pth saving......
[2025-01-18 00:24:17 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_54.pth saved !!!
[2025-01-18 00:24:25 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.309 (7.309)	Loss 1.0582 (1.0582)	Acc@1 78.271 (78.271)	Acc@5 94.849 (94.849)	Mem 16099MB
[2025-01-18 00:24:28 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.992)	Loss 1.4506 (1.2345)	Acc@1 69.287 (73.972)	Acc@5 88.989 (92.303)	Mem 16099MB
[2025-01-18 00:24:28 internimage_t_1k_224] (main.py 575): INFO [Epoch:54] * Acc@1 73.952 Acc@5 92.326
[2025-01-18 00:24:28 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.0%
[2025-01-18 00:24:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 00:24:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 00:24:30 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 73.95%
[2025-01-18 00:24:37 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.091 (7.091)	Loss 2.9751 (2.9751)	Acc@1 47.729 (47.729)	Acc@5 71.875 (71.875)	Mem 16099MB
[2025-01-18 00:24:41 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.006)	Loss 3.2072 (2.9425)	Acc@1 41.406 (47.374)	Acc@5 66.870 (71.609)	Mem 16099MB
[2025-01-18 00:24:41 internimage_t_1k_224] (main.py 575): INFO [Epoch:54] * Acc@1 47.221 Acc@5 71.783
[2025-01-18 00:24:41 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 47.2%
[2025-01-18 00:24:41 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:24:42 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:24:42 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 47.22%
[2025-01-18 00:24:45 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][0/312]	eta 0:13:12 lr 0.003681	time 2.5414 (2.5414)	model_time 0.4715 (0.4715)	loss 4.6898 (4.6898)	grad_norm 1.0936 (1.0936/0.0000)	mem 16099MB
[2025-01-18 00:24:49 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][10/312]	eta 0:03:14 lr 0.003680	time 0.4515 (0.6448)	model_time 0.4511 (0.4564)	loss 3.5983 (3.6793)	grad_norm 0.9815 (1.4938/0.7400)	mem 16099MB
[2025-01-18 00:24:54 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][20/312]	eta 0:02:47 lr 0.003680	time 0.5317 (0.5739)	model_time 0.5313 (0.4750)	loss 2.5424 (3.6060)	grad_norm 3.2741 (1.9056/0.9325)	mem 16099MB
[2025-01-18 00:24:59 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][30/312]	eta 0:02:33 lr 0.003679	time 0.4427 (0.5428)	model_time 0.4426 (0.4757)	loss 3.7987 (3.4913)	grad_norm 1.5204 (1.8379/0.8071)	mem 16099MB
[2025-01-18 00:25:03 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][40/312]	eta 0:02:22 lr 0.003679	time 0.4517 (0.5232)	model_time 0.4512 (0.4724)	loss 3.4225 (3.5432)	grad_norm 0.9504 (1.7297/0.7654)	mem 16099MB
[2025-01-18 00:25:08 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][50/312]	eta 0:02:14 lr 0.003679	time 0.4667 (0.5137)	model_time 0.4662 (0.4728)	loss 3.7916 (3.5735)	grad_norm 1.6006 (1.8197/0.8776)	mem 16099MB
[2025-01-18 00:25:13 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][60/312]	eta 0:02:07 lr 0.003678	time 0.4478 (0.5040)	model_time 0.4477 (0.4697)	loss 4.2746 (3.5860)	grad_norm 1.6810 (1.7396/0.8329)	mem 16099MB
[2025-01-18 00:25:17 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][70/312]	eta 0:02:00 lr 0.003678	time 0.4519 (0.4973)	model_time 0.4517 (0.4677)	loss 3.0117 (3.5673)	grad_norm 1.0350 (1.6758/0.8049)	mem 16099MB
[2025-01-18 00:25:22 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][80/312]	eta 0:01:54 lr 0.003678	time 0.4546 (0.4939)	model_time 0.4544 (0.4680)	loss 3.2406 (3.5866)	grad_norm 0.8493 (1.6436/0.7844)	mem 16099MB
[2025-01-18 00:25:27 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][90/312]	eta 0:01:49 lr 0.003677	time 0.4420 (0.4924)	model_time 0.4416 (0.4693)	loss 3.6218 (3.6142)	grad_norm 1.1997 (1.6102/0.7540)	mem 16099MB
[2025-01-18 00:25:31 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][100/312]	eta 0:01:43 lr 0.003677	time 0.4563 (0.4896)	model_time 0.4559 (0.4687)	loss 4.4199 (3.6329)	grad_norm 1.8902 (1.6100/0.7263)	mem 16099MB
[2025-01-18 00:25:36 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][110/312]	eta 0:01:38 lr 0.003677	time 0.4381 (0.4863)	model_time 0.4377 (0.4673)	loss 2.5376 (3.6278)	grad_norm 0.7554 (1.5550/0.7193)	mem 16099MB
[2025-01-18 00:25:41 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][120/312]	eta 0:01:32 lr 0.003676	time 0.4570 (0.4840)	model_time 0.4569 (0.4665)	loss 3.7085 (3.6042)	grad_norm 2.4491 (1.5812/0.7450)	mem 16099MB
[2025-01-18 00:25:45 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][130/312]	eta 0:01:27 lr 0.003676	time 0.4472 (0.4825)	model_time 0.4467 (0.4663)	loss 3.9726 (3.6311)	grad_norm 1.6088 (1.5635/0.7263)	mem 16099MB
[2025-01-18 00:25:50 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][140/312]	eta 0:01:22 lr 0.003675	time 0.4639 (0.4811)	model_time 0.4638 (0.4660)	loss 3.6027 (3.6265)	grad_norm 1.4033 (1.5440/0.7065)	mem 16099MB
[2025-01-18 00:25:54 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][150/312]	eta 0:01:17 lr 0.003675	time 0.4468 (0.4790)	model_time 0.4467 (0.4649)	loss 3.5654 (3.6314)	grad_norm 1.4262 (1.5128/0.6948)	mem 16099MB
[2025-01-18 00:25:59 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][160/312]	eta 0:01:12 lr 0.003675	time 0.5272 (0.4789)	model_time 0.5270 (0.4657)	loss 4.1337 (3.6350)	grad_norm 1.4348 (1.4992/0.6845)	mem 16099MB
[2025-01-18 00:26:04 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][170/312]	eta 0:01:07 lr 0.003674	time 0.4647 (0.4777)	model_time 0.4645 (0.4652)	loss 3.8624 (3.6383)	grad_norm 1.1495 (1.5188/0.6807)	mem 16099MB
[2025-01-18 00:26:08 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][180/312]	eta 0:01:02 lr 0.003674	time 0.4418 (0.4769)	model_time 0.4414 (0.4651)	loss 2.9636 (3.6325)	grad_norm 4.7025 (1.5585/0.7413)	mem 16099MB
[2025-01-18 00:26:13 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][190/312]	eta 0:00:58 lr 0.003674	time 0.4436 (0.4763)	model_time 0.4432 (0.4651)	loss 4.2393 (3.6281)	grad_norm 3.6782 (1.5849/0.7616)	mem 16099MB
[2025-01-18 00:26:18 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][200/312]	eta 0:00:53 lr 0.003673	time 0.4483 (0.4752)	model_time 0.4482 (0.4645)	loss 3.5320 (3.6279)	grad_norm 0.9144 (1.5753/0.7512)	mem 16099MB
[2025-01-18 00:26:22 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][210/312]	eta 0:00:48 lr 0.003673	time 0.7473 (0.4757)	model_time 0.7469 (0.4654)	loss 4.5290 (3.6316)	grad_norm 0.9938 (1.5561/0.7402)	mem 16099MB
[2025-01-18 00:26:27 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][220/312]	eta 0:00:43 lr 0.003673	time 0.4459 (0.4747)	model_time 0.4457 (0.4649)	loss 2.4128 (3.6139)	grad_norm 0.9208 (1.5404/0.7308)	mem 16099MB
[2025-01-18 00:26:32 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][230/312]	eta 0:00:38 lr 0.003672	time 0.4646 (0.4745)	model_time 0.4645 (0.4651)	loss 4.3482 (3.6165)	grad_norm 2.0527 (1.5399/0.7243)	mem 16099MB
[2025-01-18 00:26:36 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][240/312]	eta 0:00:34 lr 0.003672	time 0.5372 (0.4740)	model_time 0.5368 (0.4649)	loss 3.6375 (3.6213)	grad_norm 1.1929 (1.5559/0.7437)	mem 16099MB
[2025-01-18 00:26:41 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][250/312]	eta 0:00:29 lr 0.003671	time 0.5552 (0.4735)	model_time 0.5550 (0.4649)	loss 3.2433 (3.6230)	grad_norm 1.1057 (1.5441/0.7337)	mem 16099MB
[2025-01-18 00:26:45 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][260/312]	eta 0:00:24 lr 0.003671	time 0.4484 (0.4731)	model_time 0.4479 (0.4647)	loss 4.4634 (3.6284)	grad_norm 1.0190 (1.5285/0.7252)	mem 16099MB
[2025-01-18 00:26:50 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][270/312]	eta 0:00:19 lr 0.003671	time 0.4711 (0.4733)	model_time 0.4707 (0.4653)	loss 4.2253 (3.6308)	grad_norm 0.7980 (1.5145/0.7182)	mem 16099MB
[2025-01-18 00:26:55 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][280/312]	eta 0:00:15 lr 0.003670	time 0.4527 (0.4729)	model_time 0.4526 (0.4652)	loss 3.3812 (3.6341)	grad_norm 1.2900 (1.5351/0.7357)	mem 16099MB
[2025-01-18 00:27:00 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][290/312]	eta 0:00:10 lr 0.003670	time 0.4539 (0.4726)	model_time 0.4535 (0.4651)	loss 2.9491 (3.6231)	grad_norm 1.9206 (1.5301/0.7267)	mem 16099MB
[2025-01-18 00:27:04 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][300/312]	eta 0:00:05 lr 0.003670	time 0.4380 (0.4722)	model_time 0.4379 (0.4649)	loss 3.9556 (3.6160)	grad_norm 0.7647 (1.5345/0.7292)	mem 16099MB
[2025-01-18 00:27:09 internimage_t_1k_224] (main.py 510): INFO Train: [55/300][310/312]	eta 0:00:00 lr 0.003669	time 0.4446 (0.4713)	model_time 0.4445 (0.4642)	loss 4.3713 (3.6234)	grad_norm 0.7700 (1.5229/0.7278)	mem 16099MB
[2025-01-18 00:27:09 internimage_t_1k_224] (main.py 519): INFO EPOCH 55 training takes 0:02:27
[2025-01-18 00:27:09 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_55.pth saving......
[2025-01-18 00:27:10 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_55.pth saved !!!
[2025-01-18 00:27:18 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.459 (7.459)	Loss 1.0143 (1.0143)	Acc@1 77.368 (77.368)	Acc@5 94.360 (94.360)	Mem 16099MB
[2025-01-18 00:27:21 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.979)	Loss 1.4428 (1.1940)	Acc@1 68.213 (74.268)	Acc@5 89.185 (92.516)	Mem 16099MB
[2025-01-18 00:27:21 internimage_t_1k_224] (main.py 575): INFO [Epoch:55] * Acc@1 74.204 Acc@5 92.586
[2025-01-18 00:27:21 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.2%
[2025-01-18 00:27:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 00:27:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 00:27:22 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.20%
[2025-01-18 00:27:30 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.388 (7.388)	Loss 2.8321 (2.8321)	Acc@1 49.756 (49.756)	Acc@5 73.804 (73.804)	Mem 16099MB
[2025-01-18 00:27:33 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.003)	Loss 3.1022 (2.8264)	Acc@1 43.091 (49.170)	Acc@5 68.188 (73.273)	Mem 16099MB
[2025-01-18 00:27:33 internimage_t_1k_224] (main.py 575): INFO [Epoch:55] * Acc@1 49.026 Acc@5 73.442
[2025-01-18 00:27:33 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 49.0%
[2025-01-18 00:27:34 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:27:35 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:27:35 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 49.03%
[2025-01-18 00:27:38 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][0/312]	eta 0:15:11 lr 0.003669	time 2.9212 (2.9212)	model_time 0.4758 (0.4758)	loss 3.2447 (3.2447)	grad_norm 1.0441 (1.0441/0.0000)	mem 16099MB
[2025-01-18 00:27:42 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][10/312]	eta 0:03:29 lr 0.003669	time 0.4387 (0.6931)	model_time 0.4386 (0.4706)	loss 3.7964 (3.5282)	grad_norm 4.3414 (1.6885/1.0341)	mem 16099MB
[2025-01-18 00:27:47 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][20/312]	eta 0:02:49 lr 0.003668	time 0.4507 (0.5809)	model_time 0.4506 (0.4642)	loss 2.5609 (3.5545)	grad_norm 1.0967 (1.6311/0.8271)	mem 16099MB
[2025-01-18 00:27:52 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][30/312]	eta 0:02:32 lr 0.003668	time 0.4461 (0.5404)	model_time 0.4459 (0.4612)	loss 2.6955 (3.4420)	grad_norm 1.5365 (1.6637/0.9017)	mem 16099MB
[2025-01-18 00:27:56 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][40/312]	eta 0:02:22 lr 0.003668	time 0.4551 (0.5255)	model_time 0.4547 (0.4655)	loss 2.7322 (3.4974)	grad_norm 0.9990 (1.5814/0.8465)	mem 16099MB
[2025-01-18 00:28:01 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][50/312]	eta 0:02:13 lr 0.003667	time 0.4532 (0.5112)	model_time 0.4530 (0.4629)	loss 4.3877 (3.5773)	grad_norm 1.1052 (1.5478/0.7798)	mem 16099MB
[2025-01-18 00:28:06 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][60/312]	eta 0:02:07 lr 0.003667	time 0.4658 (0.5047)	model_time 0.4656 (0.4643)	loss 3.0505 (3.5457)	grad_norm 0.8192 (1.5341/0.7517)	mem 16099MB
[2025-01-18 00:28:11 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][70/312]	eta 0:02:01 lr 0.003667	time 0.4573 (0.5021)	model_time 0.4569 (0.4673)	loss 4.2003 (3.5928)	grad_norm 1.9451 (1.4957/0.7304)	mem 16099MB
[2025-01-18 00:28:15 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][80/312]	eta 0:01:56 lr 0.003666	time 0.5482 (0.5012)	model_time 0.5477 (0.4707)	loss 4.6538 (3.5721)	grad_norm 1.2797 (1.4809/0.6948)	mem 16099MB
[2025-01-18 00:28:20 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][90/312]	eta 0:01:50 lr 0.003666	time 0.4402 (0.4962)	model_time 0.4397 (0.4690)	loss 3.0371 (3.5524)	grad_norm 1.4583 (1.4438/0.6745)	mem 16099MB
[2025-01-18 00:28:25 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][100/312]	eta 0:01:44 lr 0.003665	time 0.4390 (0.4943)	model_time 0.4389 (0.4697)	loss 4.1420 (3.5897)	grad_norm 5.0458 (1.5105/0.7779)	mem 16099MB
[2025-01-18 00:28:29 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][110/312]	eta 0:01:39 lr 0.003665	time 0.4488 (0.4905)	model_time 0.4487 (0.4681)	loss 3.8039 (3.5968)	grad_norm 0.7998 (1.5541/0.7942)	mem 16099MB
[2025-01-18 00:28:34 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][120/312]	eta 0:01:33 lr 0.003665	time 0.4470 (0.4872)	model_time 0.4466 (0.4666)	loss 3.8475 (3.6154)	grad_norm 1.0465 (1.5571/0.7925)	mem 16099MB
[2025-01-18 00:28:38 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][130/312]	eta 0:01:28 lr 0.003664	time 0.4628 (0.4848)	model_time 0.4623 (0.4658)	loss 3.7205 (3.6201)	grad_norm 1.4304 (1.5382/0.7713)	mem 16099MB
[2025-01-18 00:28:43 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][140/312]	eta 0:01:23 lr 0.003664	time 0.4472 (0.4831)	model_time 0.4468 (0.4654)	loss 3.9740 (3.6212)	grad_norm 1.9646 (1.5412/0.7611)	mem 16099MB
[2025-01-18 00:28:48 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][150/312]	eta 0:01:18 lr 0.003664	time 0.4371 (0.4826)	model_time 0.4365 (0.4661)	loss 3.9096 (3.6174)	grad_norm 2.2175 (1.5756/0.7883)	mem 16099MB
[2025-01-18 00:28:53 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][160/312]	eta 0:01:13 lr 0.003663	time 0.4530 (0.4824)	model_time 0.4528 (0.4669)	loss 2.5046 (3.6059)	grad_norm 1.0895 (1.5468/0.7737)	mem 16099MB
[2025-01-18 00:28:57 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][170/312]	eta 0:01:08 lr 0.003663	time 0.4511 (0.4807)	model_time 0.4506 (0.4661)	loss 4.0160 (3.6230)	grad_norm 1.5532 (1.5293/0.7569)	mem 16099MB
[2025-01-18 00:29:02 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][180/312]	eta 0:01:03 lr 0.003663	time 0.4451 (0.4796)	model_time 0.4449 (0.4657)	loss 3.9011 (3.6092)	grad_norm 0.8780 (1.5381/0.7598)	mem 16099MB
[2025-01-18 00:29:07 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][190/312]	eta 0:00:58 lr 0.003662	time 0.5689 (0.4805)	model_time 0.5685 (0.4673)	loss 3.7214 (3.6118)	grad_norm 1.0895 (1.5602/0.7850)	mem 16099MB
[2025-01-18 00:29:11 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][200/312]	eta 0:00:53 lr 0.003662	time 0.4513 (0.4798)	model_time 0.4508 (0.4673)	loss 4.2086 (3.6176)	grad_norm 0.8037 (1.5611/0.7987)	mem 16099MB
[2025-01-18 00:29:16 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][210/312]	eta 0:00:48 lr 0.003661	time 0.4482 (0.4786)	model_time 0.4480 (0.4667)	loss 4.5901 (3.6093)	grad_norm 0.9343 (1.5381/0.7894)	mem 16099MB
[2025-01-18 00:29:21 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][220/312]	eta 0:00:44 lr 0.003661	time 0.4412 (0.4783)	model_time 0.4411 (0.4669)	loss 2.4339 (3.5904)	grad_norm 0.9694 (1.5210/0.7789)	mem 16099MB
[2025-01-18 00:29:25 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][230/312]	eta 0:00:39 lr 0.003661	time 0.4439 (0.4776)	model_time 0.4437 (0.4667)	loss 3.8165 (3.5948)	grad_norm 0.9396 (1.4992/0.7699)	mem 16099MB
[2025-01-18 00:29:30 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][240/312]	eta 0:00:34 lr 0.003660	time 0.4464 (0.4790)	model_time 0.4463 (0.4685)	loss 4.4744 (3.5975)	grad_norm 1.1157 (1.5186/0.7813)	mem 16099MB
[2025-01-18 00:29:35 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][250/312]	eta 0:00:29 lr 0.003660	time 0.4761 (0.4781)	model_time 0.4759 (0.4680)	loss 3.6061 (3.5967)	grad_norm 1.5783 (1.5098/0.7686)	mem 16099MB
[2025-01-18 00:29:39 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][260/312]	eta 0:00:24 lr 0.003660	time 0.4433 (0.4775)	model_time 0.4428 (0.4678)	loss 3.4368 (3.5965)	grad_norm 1.6041 (1.5038/0.7558)	mem 16099MB
[2025-01-18 00:29:44 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][270/312]	eta 0:00:20 lr 0.003659	time 0.4465 (0.4768)	model_time 0.4463 (0.4675)	loss 4.5539 (3.6003)	grad_norm 1.2616 (1.4995/0.7490)	mem 16099MB
[2025-01-18 00:29:49 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][280/312]	eta 0:00:15 lr 0.003659	time 0.4448 (0.4762)	model_time 0.4446 (0.4671)	loss 4.6275 (3.6024)	grad_norm 0.7228 (1.5209/0.7553)	mem 16099MB
[2025-01-18 00:29:53 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][290/312]	eta 0:00:10 lr 0.003658	time 0.4520 (0.4758)	model_time 0.4518 (0.4670)	loss 4.0544 (3.6049)	grad_norm 1.0067 (1.5131/0.7462)	mem 16099MB
[2025-01-18 00:29:58 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][300/312]	eta 0:00:05 lr 0.003658	time 0.4526 (0.4755)	model_time 0.4525 (0.4671)	loss 4.2248 (3.6079)	grad_norm 0.8207 (1.5072/0.7394)	mem 16099MB
[2025-01-18 00:30:03 internimage_t_1k_224] (main.py 510): INFO Train: [56/300][310/312]	eta 0:00:00 lr 0.003658	time 0.4374 (0.4755)	model_time 0.4373 (0.4673)	loss 3.3964 (3.6020)	grad_norm 1.4915 (1.4862/0.7172)	mem 16099MB
[2025-01-18 00:30:03 internimage_t_1k_224] (main.py 519): INFO EPOCH 56 training takes 0:02:28
[2025-01-18 00:30:03 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_56.pth saving......
[2025-01-18 00:30:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_56.pth saved !!!
[2025-01-18 00:30:12 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.570 (7.570)	Loss 1.0014 (1.0014)	Acc@1 78.027 (78.027)	Acc@5 94.995 (94.995)	Mem 16099MB
[2025-01-18 00:30:15 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.004)	Loss 1.4529 (1.2126)	Acc@1 68.701 (73.910)	Acc@5 89.282 (92.427)	Mem 16099MB
[2025-01-18 00:30:16 internimage_t_1k_224] (main.py 575): INFO [Epoch:56] * Acc@1 73.942 Acc@5 92.470
[2025-01-18 00:30:16 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 73.9%
[2025-01-18 00:30:16 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.20%
[2025-01-18 00:30:24 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.018 (8.018)	Loss 2.6968 (2.6968)	Acc@1 51.685 (51.685)	Acc@5 75.757 (75.757)	Mem 16099MB
[2025-01-18 00:30:28 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.093)	Loss 3.0041 (2.7183)	Acc@1 44.824 (50.819)	Acc@5 69.678 (74.900)	Mem 16099MB
[2025-01-18 00:30:28 internimage_t_1k_224] (main.py 575): INFO [Epoch:56] * Acc@1 50.732 Acc@5 75.058
[2025-01-18 00:30:28 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 50.7%
[2025-01-18 00:30:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:30:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:30:29 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 50.73%
[2025-01-18 00:30:31 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][0/312]	eta 0:10:44 lr 0.003658	time 2.0645 (2.0645)	model_time 0.4955 (0.4955)	loss 2.6106 (2.6106)	grad_norm 1.5957 (1.5957/0.0000)	mem 16099MB
[2025-01-18 00:30:36 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][10/312]	eta 0:03:09 lr 0.003657	time 0.4472 (0.6279)	model_time 0.4470 (0.4621)	loss 3.6044 (3.4806)	grad_norm 1.5335 (1.4412/0.5906)	mem 16099MB
[2025-01-18 00:30:41 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][20/312]	eta 0:02:39 lr 0.003657	time 0.4758 (0.5454)	model_time 0.4755 (0.4584)	loss 3.8555 (3.5377)	grad_norm 1.1158 (1.7666/0.8595)	mem 16099MB
[2025-01-18 00:30:45 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][30/312]	eta 0:02:25 lr 0.003656	time 0.4780 (0.5165)	model_time 0.4775 (0.4574)	loss 2.9779 (3.5846)	grad_norm 1.0558 (1.7468/0.7819)	mem 16099MB
[2025-01-18 00:30:50 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][40/312]	eta 0:02:16 lr 0.003656	time 0.4538 (0.5006)	model_time 0.4536 (0.4558)	loss 3.5778 (3.5111)	grad_norm 1.7244 (1.6892/0.7145)	mem 16099MB
[2025-01-18 00:30:54 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][50/312]	eta 0:02:08 lr 0.003656	time 0.4530 (0.4913)	model_time 0.4527 (0.4553)	loss 3.8528 (3.5178)	grad_norm 1.2034 (1.5785/0.6929)	mem 16099MB
[2025-01-18 00:30:59 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][60/312]	eta 0:02:02 lr 0.003655	time 0.4474 (0.4859)	model_time 0.4470 (0.4557)	loss 3.7001 (3.5453)	grad_norm 1.3146 (1.5178/0.6687)	mem 16099MB
[2025-01-18 00:31:04 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][70/312]	eta 0:01:57 lr 0.003655	time 0.4564 (0.4836)	model_time 0.4562 (0.4575)	loss 3.5444 (3.5294)	grad_norm 1.0433 (1.5750/0.7367)	mem 16099MB
[2025-01-18 00:31:08 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][80/312]	eta 0:01:51 lr 0.003655	time 0.4635 (0.4802)	model_time 0.4633 (0.4573)	loss 3.2242 (3.5460)	grad_norm 0.9140 (1.5359/0.7083)	mem 16099MB
[2025-01-18 00:31:13 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][90/312]	eta 0:01:46 lr 0.003654	time 0.4565 (0.4780)	model_time 0.4563 (0.4576)	loss 4.4279 (3.5657)	grad_norm 2.9081 (1.5224/0.6954)	mem 16099MB
[2025-01-18 00:31:17 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][100/312]	eta 0:01:41 lr 0.003654	time 0.4611 (0.4769)	model_time 0.4609 (0.4585)	loss 3.9052 (3.5522)	grad_norm 0.6917 (1.5172/0.6859)	mem 16099MB
[2025-01-18 00:31:22 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][110/312]	eta 0:01:36 lr 0.003653	time 0.4597 (0.4754)	model_time 0.4595 (0.4586)	loss 3.0269 (3.5675)	grad_norm 1.4910 (1.4891/0.6652)	mem 16099MB
[2025-01-18 00:31:27 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][120/312]	eta 0:01:31 lr 0.003653	time 0.4555 (0.4755)	model_time 0.4553 (0.4601)	loss 4.2795 (3.5744)	grad_norm 2.4705 (1.5337/0.6876)	mem 16099MB
[2025-01-18 00:31:32 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][130/312]	eta 0:01:27 lr 0.003653	time 0.4829 (0.4799)	model_time 0.4827 (0.4656)	loss 3.7988 (3.5887)	grad_norm 1.1912 (1.5532/0.6873)	mem 16099MB
[2025-01-18 00:31:37 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][140/312]	eta 0:01:22 lr 0.003652	time 0.4449 (0.4803)	model_time 0.4447 (0.4670)	loss 4.1641 (3.5937)	grad_norm 1.2609 (1.5499/0.6719)	mem 16099MB
[2025-01-18 00:31:42 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][150/312]	eta 0:01:17 lr 0.003652	time 0.4445 (0.4789)	model_time 0.4443 (0.4665)	loss 3.0191 (3.5796)	grad_norm 0.6881 (1.5263/0.6746)	mem 16099MB
[2025-01-18 00:31:47 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][160/312]	eta 0:01:12 lr 0.003652	time 0.7237 (0.4800)	model_time 0.7235 (0.4683)	loss 3.7732 (3.5927)	grad_norm 1.5727 (1.5286/0.6693)	mem 16099MB
[2025-01-18 00:31:51 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][170/312]	eta 0:01:08 lr 0.003651	time 0.4414 (0.4790)	model_time 0.4413 (0.4680)	loss 3.7226 (3.5770)	grad_norm 1.8925 (1.5180/0.6589)	mem 16099MB
[2025-01-18 00:31:56 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][180/312]	eta 0:01:03 lr 0.003651	time 0.4530 (0.4780)	model_time 0.4528 (0.4675)	loss 3.6570 (3.5777)	grad_norm 1.0237 (1.5643/0.7110)	mem 16099MB
[2025-01-18 00:32:01 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][190/312]	eta 0:00:58 lr 0.003650	time 0.4471 (0.4778)	model_time 0.4466 (0.4679)	loss 4.0270 (3.5900)	grad_norm 1.0593 (1.5557/0.7043)	mem 16099MB
[2025-01-18 00:32:05 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][200/312]	eta 0:00:53 lr 0.003650	time 0.4508 (0.4765)	model_time 0.4506 (0.4671)	loss 4.4919 (3.5760)	grad_norm 1.5457 (1.5287/0.6990)	mem 16099MB
[2025-01-18 00:32:10 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][210/312]	eta 0:00:48 lr 0.003650	time 0.4483 (0.4754)	model_time 0.4482 (0.4664)	loss 2.9428 (3.5767)	grad_norm 1.8259 (1.5237/0.6925)	mem 16099MB
[2025-01-18 00:32:14 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][220/312]	eta 0:00:43 lr 0.003649	time 0.4556 (0.4743)	model_time 0.4552 (0.4657)	loss 3.5292 (3.5858)	grad_norm 1.0725 (1.5218/0.6897)	mem 16099MB
[2025-01-18 00:32:19 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][230/312]	eta 0:00:38 lr 0.003649	time 0.4483 (0.4734)	model_time 0.4481 (0.4651)	loss 4.5772 (3.5924)	grad_norm 1.5345 (1.5107/0.6773)	mem 16099MB
[2025-01-18 00:32:23 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][240/312]	eta 0:00:34 lr 0.003649	time 0.4787 (0.4738)	model_time 0.4785 (0.4659)	loss 3.1909 (3.5976)	grad_norm 1.4991 (1.5173/0.6797)	mem 16099MB
[2025-01-18 00:32:28 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][250/312]	eta 0:00:29 lr 0.003648	time 0.4526 (0.4729)	model_time 0.4524 (0.4653)	loss 3.8971 (3.5975)	grad_norm 0.8792 (1.5418/0.7206)	mem 16099MB
[2025-01-18 00:32:33 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][260/312]	eta 0:00:24 lr 0.003648	time 0.4536 (0.4726)	model_time 0.4534 (0.4653)	loss 4.0162 (3.5969)	grad_norm 2.0693 (1.5386/0.7159)	mem 16099MB
[2025-01-18 00:32:37 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][270/312]	eta 0:00:19 lr 0.003647	time 0.4528 (0.4722)	model_time 0.4526 (0.4651)	loss 2.3755 (3.5884)	grad_norm 1.2212 (1.5338/0.7080)	mem 16099MB
[2025-01-18 00:32:42 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][280/312]	eta 0:00:15 lr 0.003647	time 0.4364 (0.4716)	model_time 0.4362 (0.4647)	loss 2.4733 (3.5902)	grad_norm 1.4663 (1.5219/0.7005)	mem 16099MB
[2025-01-18 00:32:46 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][290/312]	eta 0:00:10 lr 0.003647	time 0.4641 (0.4711)	model_time 0.4636 (0.4644)	loss 3.1965 (3.5970)	grad_norm 1.3706 (1.5286/0.7263)	mem 16099MB
[2025-01-18 00:32:51 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][300/312]	eta 0:00:05 lr 0.003646	time 0.4365 (0.4706)	model_time 0.4364 (0.4641)	loss 3.5064 (3.5999)	grad_norm 1.7306 (1.5238/0.7219)	mem 16099MB
[2025-01-18 00:32:56 internimage_t_1k_224] (main.py 510): INFO Train: [57/300][310/312]	eta 0:00:00 lr 0.003646	time 0.4421 (0.4706)	model_time 0.4420 (0.4644)	loss 4.6175 (3.6127)	grad_norm 0.8729 (1.5259/0.7185)	mem 16099MB
[2025-01-18 00:32:56 internimage_t_1k_224] (main.py 519): INFO EPOCH 57 training takes 0:02:26
[2025-01-18 00:32:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_57.pth saving......
[2025-01-18 00:32:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_57.pth saved !!!
[2025-01-18 00:33:05 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.301 (7.301)	Loss 0.9645 (0.9645)	Acc@1 77.954 (77.954)	Acc@5 94.800 (94.800)	Mem 16099MB
[2025-01-18 00:33:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.988)	Loss 1.4389 (1.1896)	Acc@1 67.627 (74.077)	Acc@5 89.380 (92.225)	Mem 16099MB
[2025-01-18 00:33:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:57] * Acc@1 74.124 Acc@5 92.318
[2025-01-18 00:33:08 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.1%
[2025-01-18 00:33:08 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.20%
[2025-01-18 00:33:16 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.156 (8.156)	Loss 2.5692 (2.5692)	Acc@1 53.809 (53.809)	Acc@5 77.490 (77.490)	Mem 16099MB
[2025-01-18 00:33:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.096)	Loss 2.9114 (2.6163)	Acc@1 46.729 (52.577)	Acc@5 71.436 (76.325)	Mem 16099MB
[2025-01-18 00:33:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:57] * Acc@1 52.507 Acc@5 76.472
[2025-01-18 00:33:20 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 52.5%
[2025-01-18 00:33:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:33:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:33:22 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 52.51%
[2025-01-18 00:33:24 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][0/312]	eta 0:13:19 lr 0.003646	time 2.5615 (2.5615)	model_time 0.4767 (0.4767)	loss 4.0259 (4.0259)	grad_norm 1.1650 (1.1650/0.0000)	mem 16099MB
[2025-01-18 00:33:29 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][10/312]	eta 0:03:17 lr 0.003645	time 0.4497 (0.6536)	model_time 0.4496 (0.4635)	loss 2.9247 (3.7693)	grad_norm 1.4342 (1.1858/0.3614)	mem 16099MB
[2025-01-18 00:33:33 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][20/312]	eta 0:02:43 lr 0.003645	time 0.4562 (0.5586)	model_time 0.4560 (0.4589)	loss 2.4755 (3.7183)	grad_norm 1.1593 (1.2866/0.4231)	mem 16099MB
[2025-01-18 00:33:38 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][30/312]	eta 0:02:29 lr 0.003645	time 0.5392 (0.5306)	model_time 0.5390 (0.4629)	loss 4.0770 (3.7000)	grad_norm 1.4821 (1.4222/0.6082)	mem 16099MB
[2025-01-18 00:33:43 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][40/312]	eta 0:02:20 lr 0.003644	time 0.4492 (0.5163)	model_time 0.4487 (0.4650)	loss 4.0841 (3.6511)	grad_norm 1.3237 (1.5083/0.6586)	mem 16099MB
[2025-01-18 00:33:47 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][50/312]	eta 0:02:12 lr 0.003644	time 0.4810 (0.5043)	model_time 0.4806 (0.4630)	loss 3.7352 (3.6328)	grad_norm 0.9318 (1.6171/0.7215)	mem 16099MB
[2025-01-18 00:33:52 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][60/312]	eta 0:02:05 lr 0.003644	time 0.4358 (0.4989)	model_time 0.4353 (0.4643)	loss 3.7934 (3.6260)	grad_norm 1.3928 (1.5771/0.6816)	mem 16099MB
[2025-01-18 00:33:57 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][70/312]	eta 0:01:59 lr 0.003643	time 0.4438 (0.4939)	model_time 0.4436 (0.4642)	loss 3.6711 (3.6015)	grad_norm 0.7514 (1.5593/0.6598)	mem 16099MB
[2025-01-18 00:34:01 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][80/312]	eta 0:01:53 lr 0.003643	time 0.4559 (0.4898)	model_time 0.4557 (0.4636)	loss 3.4809 (3.6330)	grad_norm 0.6873 (1.6070/0.7552)	mem 16099MB
[2025-01-18 00:34:06 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][90/312]	eta 0:01:47 lr 0.003642	time 0.4541 (0.4862)	model_time 0.4536 (0.4628)	loss 3.2534 (3.6262)	grad_norm 0.8493 (1.5537/0.7315)	mem 16099MB
[2025-01-18 00:34:11 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][100/312]	eta 0:01:42 lr 0.003642	time 0.4426 (0.4835)	model_time 0.4424 (0.4624)	loss 3.6546 (3.6336)	grad_norm 1.9379 (1.5511/0.7019)	mem 16099MB
[2025-01-18 00:34:16 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][110/312]	eta 0:01:37 lr 0.003642	time 0.4450 (0.4848)	model_time 0.4448 (0.4656)	loss 3.3607 (3.6299)	grad_norm 1.3100 (1.5427/0.6844)	mem 16099MB
[2025-01-18 00:34:20 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][120/312]	eta 0:01:32 lr 0.003641	time 0.5463 (0.4834)	model_time 0.5461 (0.4658)	loss 4.3176 (3.6447)	grad_norm 2.6521 (1.5599/0.6903)	mem 16099MB
[2025-01-18 00:34:25 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][130/312]	eta 0:01:28 lr 0.003641	time 0.4382 (0.4836)	model_time 0.4381 (0.4673)	loss 4.2334 (3.6529)	grad_norm 0.9696 (1.5548/0.6745)	mem 16099MB
[2025-01-18 00:34:30 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][140/312]	eta 0:01:22 lr 0.003641	time 0.4543 (0.4824)	model_time 0.4541 (0.4672)	loss 3.6064 (3.6585)	grad_norm 1.3965 (1.5330/0.6673)	mem 16099MB
[2025-01-18 00:34:34 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][150/312]	eta 0:01:17 lr 0.003640	time 0.4638 (0.4809)	model_time 0.4636 (0.4667)	loss 3.1575 (3.6674)	grad_norm 0.9483 (1.5611/0.6713)	mem 16099MB
[2025-01-18 00:34:39 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][160/312]	eta 0:01:12 lr 0.003640	time 0.5343 (0.4796)	model_time 0.5341 (0.4663)	loss 4.0862 (3.6832)	grad_norm 1.7770 (1.5763/0.6862)	mem 16099MB
[2025-01-18 00:34:44 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][170/312]	eta 0:01:08 lr 0.003639	time 0.4623 (0.4792)	model_time 0.4618 (0.4666)	loss 3.8339 (3.6937)	grad_norm 2.2263 (1.5982/0.7064)	mem 16099MB
[2025-01-18 00:34:48 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][180/312]	eta 0:01:03 lr 0.003639	time 0.4744 (0.4778)	model_time 0.4742 (0.4659)	loss 3.9717 (3.7053)	grad_norm 1.4138 (1.5767/0.6956)	mem 16099MB
[2025-01-18 00:34:53 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][190/312]	eta 0:00:58 lr 0.003639	time 0.4806 (0.4764)	model_time 0.4804 (0.4651)	loss 4.1627 (3.7120)	grad_norm 1.8814 (1.5564/0.6869)	mem 16099MB
[2025-01-18 00:34:57 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][200/312]	eta 0:00:53 lr 0.003638	time 0.4623 (0.4756)	model_time 0.4621 (0.4649)	loss 3.7115 (3.6977)	grad_norm 1.2872 (1.5630/0.6965)	mem 16099MB
[2025-01-18 00:35:02 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][210/312]	eta 0:00:48 lr 0.003638	time 0.4645 (0.4747)	model_time 0.4643 (0.4645)	loss 2.9321 (3.6989)	grad_norm 1.8289 (1.5663/0.6881)	mem 16099MB
[2025-01-18 00:35:07 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][220/312]	eta 0:00:43 lr 0.003637	time 0.4467 (0.4744)	model_time 0.4462 (0.4646)	loss 3.6406 (3.6962)	grad_norm 0.8012 (1.5566/0.6793)	mem 16099MB
[2025-01-18 00:35:11 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][230/312]	eta 0:00:38 lr 0.003637	time 0.4734 (0.4737)	model_time 0.4732 (0.4643)	loss 2.8035 (3.7007)	grad_norm 1.5791 (1.5488/0.6681)	mem 16099MB
[2025-01-18 00:35:16 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][240/312]	eta 0:00:34 lr 0.003637	time 0.4489 (0.4730)	model_time 0.4487 (0.4640)	loss 4.4131 (3.7008)	grad_norm 2.7832 (1.5531/0.6662)	mem 16099MB
[2025-01-18 00:35:20 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][250/312]	eta 0:00:29 lr 0.003636	time 0.4775 (0.4729)	model_time 0.4771 (0.4642)	loss 3.5648 (3.6883)	grad_norm 2.0501 (1.5533/0.6700)	mem 16099MB
[2025-01-18 00:35:25 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][260/312]	eta 0:00:24 lr 0.003636	time 0.4515 (0.4723)	model_time 0.4513 (0.4640)	loss 3.1817 (3.6823)	grad_norm 2.3786 (1.5567/0.6698)	mem 16099MB
[2025-01-18 00:35:30 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][270/312]	eta 0:00:19 lr 0.003636	time 0.4618 (0.4716)	model_time 0.4614 (0.4635)	loss 3.0088 (3.6764)	grad_norm 1.9117 (1.5577/0.6634)	mem 16099MB
[2025-01-18 00:35:35 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][280/312]	eta 0:00:15 lr 0.003635	time 0.5604 (0.4731)	model_time 0.5601 (0.4653)	loss 3.6147 (3.6747)	grad_norm 2.7981 (1.5759/0.6781)	mem 16099MB
[2025-01-18 00:35:39 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][290/312]	eta 0:00:10 lr 0.003635	time 0.4486 (0.4726)	model_time 0.4481 (0.4650)	loss 3.8196 (3.6800)	grad_norm 1.2890 (1.5782/0.6760)	mem 16099MB
[2025-01-18 00:35:44 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][300/312]	eta 0:00:05 lr 0.003634	time 0.4327 (0.4728)	model_time 0.4326 (0.4655)	loss 3.3368 (3.6798)	grad_norm 1.0444 (1.5908/0.7007)	mem 16099MB
[2025-01-18 00:35:49 internimage_t_1k_224] (main.py 510): INFO Train: [58/300][310/312]	eta 0:00:00 lr 0.003634	time 0.4404 (0.4723)	model_time 0.4403 (0.4652)	loss 3.6795 (3.6807)	grad_norm 0.8218 (1.6125/0.7281)	mem 16099MB
[2025-01-18 00:35:49 internimage_t_1k_224] (main.py 519): INFO EPOCH 58 training takes 0:02:27
[2025-01-18 00:35:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_58.pth saving......
[2025-01-18 00:35:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_58.pth saved !!!
[2025-01-18 00:35:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.406 (7.406)	Loss 1.0082 (1.0082)	Acc@1 77.832 (77.832)	Acc@5 94.775 (94.775)	Mem 16099MB
[2025-01-18 00:36:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.987)	Loss 1.4297 (1.1951)	Acc@1 69.580 (74.574)	Acc@5 89.795 (92.483)	Mem 16099MB
[2025-01-18 00:36:01 internimage_t_1k_224] (main.py 575): INFO [Epoch:58] * Acc@1 74.500 Acc@5 92.490
[2025-01-18 00:36:01 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.5%
[2025-01-18 00:36:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 00:36:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 00:36:02 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.50%
[2025-01-18 00:36:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.545 (7.545)	Loss 2.4520 (2.4520)	Acc@1 55.713 (55.713)	Acc@5 78.979 (78.979)	Mem 16099MB
[2025-01-18 00:36:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.015)	Loss 2.8264 (2.5239)	Acc@1 47.803 (53.920)	Acc@5 72.656 (77.632)	Mem 16099MB
[2025-01-18 00:36:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:58] * Acc@1 53.879 Acc@5 77.749
[2025-01-18 00:36:14 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 53.9%
[2025-01-18 00:36:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:36:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:36:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 53.88%
[2025-01-18 00:36:17 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][0/312]	eta 0:13:03 lr 0.003634	time 2.5105 (2.5105)	model_time 0.4543 (0.4543)	loss 3.5216 (3.5216)	grad_norm 1.0954 (1.0954/0.0000)	mem 16099MB
[2025-01-18 00:36:22 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][10/312]	eta 0:03:16 lr 0.003634	time 0.4465 (0.6498)	model_time 0.4463 (0.4626)	loss 3.4699 (3.8529)	grad_norm 2.3160 (1.5737/1.0787)	mem 16099MB
[2025-01-18 00:36:27 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][20/312]	eta 0:02:44 lr 0.003633	time 0.5471 (0.5634)	model_time 0.5466 (0.4652)	loss 2.3315 (3.6491)	grad_norm 1.0321 (1.7743/1.1379)	mem 16099MB
[2025-01-18 00:36:31 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][30/312]	eta 0:02:29 lr 0.003633	time 0.4495 (0.5289)	model_time 0.4493 (0.4622)	loss 2.8897 (3.6789)	grad_norm 1.2928 (1.5956/0.9922)	mem 16099MB
[2025-01-18 00:36:36 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][40/312]	eta 0:02:19 lr 0.003632	time 0.4518 (0.5118)	model_time 0.4516 (0.4613)	loss 2.7204 (3.6319)	grad_norm 0.9832 (1.5313/0.8945)	mem 16099MB
[2025-01-18 00:36:41 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][50/312]	eta 0:02:11 lr 0.003632	time 0.4455 (0.5011)	model_time 0.4451 (0.4604)	loss 4.1472 (3.6108)	grad_norm 1.2893 (1.4201/0.8377)	mem 16099MB
[2025-01-18 00:36:45 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][60/312]	eta 0:02:05 lr 0.003632	time 0.4377 (0.4973)	model_time 0.4375 (0.4632)	loss 3.5742 (3.5750)	grad_norm 2.3341 (1.4683/0.8432)	mem 16099MB
[2025-01-18 00:36:50 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][70/312]	eta 0:01:59 lr 0.003631	time 0.5375 (0.4926)	model_time 0.5374 (0.4632)	loss 3.5378 (3.6254)	grad_norm 1.2253 (1.4706/0.8077)	mem 16099MB
[2025-01-18 00:36:54 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][80/312]	eta 0:01:53 lr 0.003631	time 0.4435 (0.4879)	model_time 0.4433 (0.4621)	loss 3.0067 (3.6188)	grad_norm 1.4983 (1.4757/0.7671)	mem 16099MB
[2025-01-18 00:36:59 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][90/312]	eta 0:01:47 lr 0.003630	time 0.4373 (0.4838)	model_time 0.4369 (0.4608)	loss 4.1492 (3.6324)	grad_norm 1.6597 (1.4786/0.7361)	mem 16099MB
[2025-01-18 00:37:04 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][100/312]	eta 0:01:41 lr 0.003630	time 0.4485 (0.4806)	model_time 0.4480 (0.4598)	loss 2.3581 (3.6469)	grad_norm 0.8200 (1.4821/0.7155)	mem 16099MB
[2025-01-18 00:37:08 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][110/312]	eta 0:01:36 lr 0.003630	time 0.4544 (0.4781)	model_time 0.4543 (0.4592)	loss 3.9923 (3.6630)	grad_norm 0.9170 (1.4568/0.6934)	mem 16099MB
[2025-01-18 00:37:13 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][120/312]	eta 0:01:31 lr 0.003629	time 0.4499 (0.4761)	model_time 0.4494 (0.4587)	loss 4.1362 (3.6631)	grad_norm 1.7258 (1.4511/0.6712)	mem 16099MB
[2025-01-18 00:37:17 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][130/312]	eta 0:01:26 lr 0.003629	time 0.4615 (0.4743)	model_time 0.4610 (0.4582)	loss 4.0973 (3.6330)	grad_norm 1.0515 (1.5066/0.7109)	mem 16099MB
[2025-01-18 00:37:22 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][140/312]	eta 0:01:22 lr 0.003629	time 0.5491 (0.4782)	model_time 0.5486 (0.4632)	loss 3.8116 (3.6100)	grad_norm 2.1760 (1.5236/0.7082)	mem 16099MB
[2025-01-18 00:37:27 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][150/312]	eta 0:01:17 lr 0.003628	time 0.4826 (0.4770)	model_time 0.4821 (0.4630)	loss 3.7474 (3.6232)	grad_norm 1.0560 (1.5083/0.6981)	mem 16099MB
[2025-01-18 00:37:32 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][160/312]	eta 0:01:12 lr 0.003628	time 0.4506 (0.4759)	model_time 0.4501 (0.4627)	loss 3.0665 (3.6015)	grad_norm 2.4655 (1.5266/0.7022)	mem 16099MB
[2025-01-18 00:37:36 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][170/312]	eta 0:01:07 lr 0.003627	time 0.4472 (0.4749)	model_time 0.4468 (0.4624)	loss 3.1695 (3.6070)	grad_norm 1.1341 (1.5402/0.6952)	mem 16099MB
[2025-01-18 00:37:41 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][180/312]	eta 0:01:02 lr 0.003627	time 0.5363 (0.4741)	model_time 0.5360 (0.4623)	loss 2.7824 (3.6086)	grad_norm 0.9347 (1.5444/0.6960)	mem 16099MB
[2025-01-18 00:37:45 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][190/312]	eta 0:00:57 lr 0.003627	time 0.4639 (0.4730)	model_time 0.4637 (0.4618)	loss 2.8328 (3.6050)	grad_norm 0.9138 (1.5250/0.6853)	mem 16099MB
[2025-01-18 00:37:50 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][200/312]	eta 0:00:52 lr 0.003626	time 0.4531 (0.4730)	model_time 0.4530 (0.4624)	loss 4.0716 (3.6101)	grad_norm 1.8864 (1.5374/0.6845)	mem 16099MB
[2025-01-18 00:37:55 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][210/312]	eta 0:00:48 lr 0.003626	time 0.4467 (0.4724)	model_time 0.4466 (0.4623)	loss 3.5639 (3.6046)	grad_norm 0.9247 (1.5303/0.6747)	mem 16099MB
[2025-01-18 00:37:59 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][220/312]	eta 0:00:43 lr 0.003625	time 0.4458 (0.4719)	model_time 0.4452 (0.4622)	loss 3.9086 (3.5842)	grad_norm 1.0689 (1.5045/0.6704)	mem 16099MB
[2025-01-18 00:38:04 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][230/312]	eta 0:00:38 lr 0.003625	time 0.4425 (0.4719)	model_time 0.4424 (0.4626)	loss 4.1041 (3.5827)	grad_norm 4.1830 (1.5068/0.6846)	mem 16099MB
[2025-01-18 00:38:09 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][240/312]	eta 0:00:33 lr 0.003625	time 0.4478 (0.4718)	model_time 0.4476 (0.4629)	loss 3.8311 (3.5938)	grad_norm 1.7492 (1.5202/0.7064)	mem 16099MB
[2025-01-18 00:38:13 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][250/312]	eta 0:00:29 lr 0.003624	time 0.5417 (0.4714)	model_time 0.5415 (0.4628)	loss 4.2151 (3.6014)	grad_norm 0.9562 (1.5114/0.6987)	mem 16099MB
[2025-01-18 00:38:18 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][260/312]	eta 0:00:24 lr 0.003624	time 0.4641 (0.4709)	model_time 0.4636 (0.4627)	loss 3.2490 (3.6045)	grad_norm 1.2087 (1.4968/0.6925)	mem 16099MB
[2025-01-18 00:38:22 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][270/312]	eta 0:00:19 lr 0.003623	time 0.4621 (0.4704)	model_time 0.4619 (0.4625)	loss 3.8267 (3.5958)	grad_norm 2.7597 (1.5089/0.6926)	mem 16099MB
[2025-01-18 00:38:27 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][280/312]	eta 0:00:15 lr 0.003623	time 0.4400 (0.4698)	model_time 0.4398 (0.4622)	loss 4.4702 (3.6025)	grad_norm 2.0813 (1.5074/0.6868)	mem 16099MB
[2025-01-18 00:38:32 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][290/312]	eta 0:00:10 lr 0.003623	time 0.4478 (0.4698)	model_time 0.4476 (0.4623)	loss 3.6894 (3.6090)	grad_norm 2.7059 (1.5264/0.7013)	mem 16099MB
[2025-01-18 00:38:36 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][300/312]	eta 0:00:05 lr 0.003622	time 0.4381 (0.4697)	model_time 0.4380 (0.4625)	loss 3.0290 (3.6046)	grad_norm 0.8077 (1.5085/0.6991)	mem 16099MB
[2025-01-18 00:38:41 internimage_t_1k_224] (main.py 510): INFO Train: [59/300][310/312]	eta 0:00:00 lr 0.003622	time 0.4407 (0.4693)	model_time 0.4406 (0.4624)	loss 3.2085 (3.5966)	grad_norm 1.7036 (1.5143/0.6966)	mem 16099MB
[2025-01-18 00:38:41 internimage_t_1k_224] (main.py 519): INFO EPOCH 59 training takes 0:02:26
[2025-01-18 00:38:41 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_59.pth saving......
[2025-01-18 00:38:43 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_59.pth saved !!!
[2025-01-18 00:38:50 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.405 (7.405)	Loss 1.0052 (1.0052)	Acc@1 77.002 (77.002)	Acc@5 94.751 (94.751)	Mem 16099MB
[2025-01-18 00:38:53 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.990)	Loss 1.4380 (1.2041)	Acc@1 69.312 (74.339)	Acc@5 89.502 (92.429)	Mem 16099MB
[2025-01-18 00:38:54 internimage_t_1k_224] (main.py 575): INFO [Epoch:59] * Acc@1 74.302 Acc@5 92.510
[2025-01-18 00:38:54 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.3%
[2025-01-18 00:38:54 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.50%
[2025-01-18 00:39:02 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.090 (8.090)	Loss 2.3458 (2.3458)	Acc@1 56.982 (56.982)	Acc@5 80.322 (80.322)	Mem 16099MB
[2025-01-18 00:39:06 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.087)	Loss 2.7465 (2.4379)	Acc@1 48.828 (55.167)	Acc@5 73.535 (78.815)	Mem 16099MB
[2025-01-18 00:39:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:59] * Acc@1 55.128 Acc@5 78.919
[2025-01-18 00:39:06 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 55.1%
[2025-01-18 00:39:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:39:07 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:39:07 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 55.13%
[2025-01-18 00:39:09 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][0/312]	eta 0:10:22 lr 0.003622	time 1.9938 (1.9938)	model_time 0.4794 (0.4794)	loss 3.6008 (3.6008)	grad_norm 1.1870 (1.1870/0.0000)	mem 16099MB
[2025-01-18 00:39:14 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][10/312]	eta 0:03:04 lr 0.003621	time 0.4578 (0.6122)	model_time 0.4573 (0.4742)	loss 2.9553 (3.5921)	grad_norm 1.0419 (1.3460/0.3042)	mem 16099MB
[2025-01-18 00:39:18 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][20/312]	eta 0:02:38 lr 0.003621	time 0.4707 (0.5419)	model_time 0.4705 (0.4694)	loss 3.4389 (3.4858)	grad_norm 1.7890 (1.3437/0.3079)	mem 16099MB
[2025-01-18 00:39:23 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][30/312]	eta 0:02:25 lr 0.003621	time 0.4619 (0.5150)	model_time 0.4617 (0.4658)	loss 2.2806 (3.5056)	grad_norm 1.3765 (1.3157/0.3612)	mem 16099MB
[2025-01-18 00:39:27 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][40/312]	eta 0:02:16 lr 0.003620	time 0.4484 (0.5005)	model_time 0.4482 (0.4632)	loss 2.9890 (3.4863)	grad_norm 1.4074 (1.3625/0.3661)	mem 16099MB
[2025-01-18 00:39:32 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][50/312]	eta 0:02:09 lr 0.003620	time 0.4620 (0.4950)	model_time 0.4618 (0.4649)	loss 3.8678 (3.5227)	grad_norm 3.1226 (1.6225/0.7207)	mem 16099MB
[2025-01-18 00:39:37 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][60/312]	eta 0:02:03 lr 0.003620	time 0.4460 (0.4893)	model_time 0.4459 (0.4641)	loss 3.8518 (3.5483)	grad_norm 2.9720 (1.6721/0.7158)	mem 16099MB
[2025-01-18 00:39:41 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][70/312]	eta 0:01:57 lr 0.003619	time 0.5484 (0.4859)	model_time 0.5482 (0.4642)	loss 2.9821 (3.5587)	grad_norm 1.7972 (1.6509/0.7084)	mem 16099MB
[2025-01-18 00:39:46 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][80/312]	eta 0:01:51 lr 0.003619	time 0.4498 (0.4821)	model_time 0.4496 (0.4630)	loss 4.6188 (3.5926)	grad_norm 1.0339 (1.6170/0.6924)	mem 16099MB
[2025-01-18 00:39:51 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][90/312]	eta 0:01:46 lr 0.003618	time 0.4551 (0.4790)	model_time 0.4549 (0.4620)	loss 3.7897 (3.6058)	grad_norm 1.1735 (1.5999/0.6800)	mem 16099MB
[2025-01-18 00:39:55 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][100/312]	eta 0:01:41 lr 0.003618	time 0.4577 (0.4779)	model_time 0.4575 (0.4625)	loss 2.9263 (3.5866)	grad_norm 0.7060 (1.5651/0.6687)	mem 16099MB
[2025-01-18 00:40:00 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][110/312]	eta 0:01:36 lr 0.003618	time 0.4391 (0.4773)	model_time 0.4389 (0.4633)	loss 2.7680 (3.5823)	grad_norm 1.8533 (1.5440/0.6519)	mem 16099MB
[2025-01-18 00:40:05 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][120/312]	eta 0:01:31 lr 0.003617	time 0.4499 (0.4772)	model_time 0.4497 (0.4643)	loss 3.0249 (3.5869)	grad_norm 1.2843 (1.4955/0.6471)	mem 16099MB
[2025-01-18 00:40:09 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][130/312]	eta 0:01:26 lr 0.003617	time 0.4412 (0.4765)	model_time 0.4410 (0.4645)	loss 3.8826 (3.5676)	grad_norm 2.1879 (1.5103/0.6381)	mem 16099MB
[2025-01-18 00:40:14 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][140/312]	eta 0:01:22 lr 0.003616	time 0.4512 (0.4770)	model_time 0.4507 (0.4659)	loss 3.3875 (3.5664)	grad_norm 2.7894 (1.5446/0.6691)	mem 16099MB
[2025-01-18 00:40:19 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][150/312]	eta 0:01:17 lr 0.003616	time 0.4526 (0.4756)	model_time 0.4521 (0.4651)	loss 3.9080 (3.5805)	grad_norm 2.9022 (1.5662/0.6766)	mem 16099MB
[2025-01-18 00:40:23 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][160/312]	eta 0:01:12 lr 0.003616	time 0.4541 (0.4746)	model_time 0.4537 (0.4648)	loss 2.6475 (3.5804)	grad_norm 1.1532 (1.5371/0.6710)	mem 16099MB
[2025-01-18 00:40:28 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][170/312]	eta 0:01:07 lr 0.003615	time 0.4652 (0.4748)	model_time 0.4650 (0.4656)	loss 3.7342 (3.6049)	grad_norm 1.5033 (1.5347/0.6614)	mem 16099MB
[2025-01-18 00:40:33 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][180/312]	eta 0:01:02 lr 0.003615	time 0.4447 (0.4741)	model_time 0.4445 (0.4653)	loss 4.1926 (3.6116)	grad_norm 1.4842 (1.5130/0.6524)	mem 16099MB
[2025-01-18 00:40:37 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][190/312]	eta 0:00:57 lr 0.003614	time 0.4491 (0.4731)	model_time 0.4489 (0.4648)	loss 3.5021 (3.6057)	grad_norm 1.7281 (1.5044/0.6410)	mem 16099MB
[2025-01-18 00:40:42 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][200/312]	eta 0:00:52 lr 0.003614	time 0.4475 (0.4723)	model_time 0.4470 (0.4644)	loss 3.4783 (3.5978)	grad_norm 2.1209 (1.5311/0.6731)	mem 16099MB
[2025-01-18 00:40:46 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][210/312]	eta 0:00:48 lr 0.003614	time 0.4464 (0.4716)	model_time 0.4462 (0.4640)	loss 3.1201 (3.6093)	grad_norm 0.6326 (1.5167/0.6636)	mem 16099MB
[2025-01-18 00:40:51 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][220/312]	eta 0:00:43 lr 0.003613	time 0.5577 (0.4711)	model_time 0.5573 (0.4639)	loss 2.9768 (3.5961)	grad_norm 1.7968 (1.5018/0.6549)	mem 16099MB
[2025-01-18 00:40:56 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][230/312]	eta 0:00:38 lr 0.003613	time 0.4551 (0.4707)	model_time 0.4550 (0.4637)	loss 3.8247 (3.5977)	grad_norm 2.2252 (1.5131/0.6517)	mem 16099MB
[2025-01-18 00:41:00 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][240/312]	eta 0:00:33 lr 0.003612	time 0.4779 (0.4700)	model_time 0.4777 (0.4633)	loss 2.9532 (3.5811)	grad_norm 0.9842 (1.5056/0.6447)	mem 16099MB
[2025-01-18 00:41:05 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][250/312]	eta 0:00:29 lr 0.003612	time 0.4481 (0.4699)	model_time 0.4478 (0.4635)	loss 4.0109 (3.5868)	grad_norm 0.8351 (1.4919/0.6378)	mem 16099MB
[2025-01-18 00:41:10 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][260/312]	eta 0:00:24 lr 0.003612	time 0.4333 (0.4699)	model_time 0.4330 (0.4637)	loss 2.9491 (3.5916)	grad_norm 2.3117 (1.5321/0.7312)	mem 16099MB
[2025-01-18 00:41:14 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][270/312]	eta 0:00:19 lr 0.003611	time 0.4418 (0.4696)	model_time 0.4413 (0.4636)	loss 4.0089 (3.5873)	grad_norm 0.8253 (1.5370/0.7328)	mem 16099MB
[2025-01-18 00:41:19 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][280/312]	eta 0:00:15 lr 0.003611	time 0.4575 (0.4700)	model_time 0.4573 (0.4642)	loss 3.8080 (3.5790)	grad_norm 1.5665 (1.5281/0.7232)	mem 16099MB
[2025-01-18 00:41:24 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][290/312]	eta 0:00:10 lr 0.003610	time 0.4462 (0.4701)	model_time 0.4460 (0.4645)	loss 3.6491 (3.5845)	grad_norm 0.9291 (1.5107/0.7176)	mem 16099MB
[2025-01-18 00:41:28 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][300/312]	eta 0:00:05 lr 0.003610	time 0.4345 (0.4694)	model_time 0.4343 (0.4640)	loss 3.7563 (3.5861)	grad_norm 1.0196 (1.5059/0.7122)	mem 16099MB
[2025-01-18 00:41:33 internimage_t_1k_224] (main.py 510): INFO Train: [60/300][310/312]	eta 0:00:00 lr 0.003610	time 0.4385 (0.4687)	model_time 0.4384 (0.4634)	loss 3.5879 (3.5839)	grad_norm 1.9685 (1.5182/0.7176)	mem 16099MB
[2025-01-18 00:41:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 60 training takes 0:02:26
[2025-01-18 00:41:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_60.pth saving......
[2025-01-18 00:41:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_60.pth saved !!!
[2025-01-18 00:41:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.625 (7.625)	Loss 0.9531 (0.9531)	Acc@1 79.102 (79.102)	Acc@5 95.117 (95.117)	Mem 16099MB
[2025-01-18 00:41:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.998)	Loss 1.3971 (1.1608)	Acc@1 68.384 (74.223)	Acc@5 89.868 (92.611)	Mem 16099MB
[2025-01-18 00:41:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:60] * Acc@1 74.232 Acc@5 92.708
[2025-01-18 00:41:45 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.2%
[2025-01-18 00:41:45 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.50%
[2025-01-18 00:41:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.114 (8.114)	Loss 2.2480 (2.2480)	Acc@1 58.545 (58.545)	Acc@5 81.592 (81.592)	Mem 16099MB
[2025-01-18 00:41:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.092)	Loss 2.6714 (2.3582)	Acc@1 50.293 (56.425)	Acc@5 74.683 (79.909)	Mem 16099MB
[2025-01-18 00:41:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:60] * Acc@1 56.382 Acc@5 79.988
[2025-01-18 00:41:58 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 56.4%
[2025-01-18 00:41:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:41:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:41:59 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 56.38%
[2025-01-18 00:42:01 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][0/312]	eta 0:10:15 lr 0.003610	time 1.9733 (1.9733)	model_time 0.4873 (0.4873)	loss 3.8946 (3.8946)	grad_norm 1.4929 (1.4929/0.0000)	mem 16099MB
[2025-01-18 00:42:06 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][10/312]	eta 0:03:02 lr 0.003609	time 0.4417 (0.6033)	model_time 0.4414 (0.4678)	loss 2.5397 (3.3062)	grad_norm 4.0396 (2.0624/0.8210)	mem 16099MB
[2025-01-18 00:42:10 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][20/312]	eta 0:02:37 lr 0.003609	time 0.5533 (0.5380)	model_time 0.5531 (0.4670)	loss 4.0183 (3.4755)	grad_norm 0.8884 (1.7965/0.7680)	mem 16099MB
[2025-01-18 00:42:15 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][30/312]	eta 0:02:23 lr 0.003608	time 0.4490 (0.5095)	model_time 0.4485 (0.4612)	loss 3.6684 (3.5452)	grad_norm 1.4245 (1.7139/0.7162)	mem 16099MB
[2025-01-18 00:42:19 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][40/312]	eta 0:02:16 lr 0.003608	time 0.4998 (0.5004)	model_time 0.4996 (0.4638)	loss 3.2322 (3.6148)	grad_norm 1.8801 (1.6065/0.6714)	mem 16099MB
[2025-01-18 00:42:24 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][50/312]	eta 0:02:09 lr 0.003608	time 0.4728 (0.4937)	model_time 0.4727 (0.4642)	loss 3.7935 (3.6405)	grad_norm 0.9988 (1.5055/0.6436)	mem 16099MB
[2025-01-18 00:42:29 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][60/312]	eta 0:02:02 lr 0.003607	time 0.4442 (0.4870)	model_time 0.4440 (0.4623)	loss 4.3581 (3.5889)	grad_norm 1.0351 (1.5645/0.8457)	mem 16099MB
[2025-01-18 00:42:33 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][70/312]	eta 0:01:56 lr 0.003607	time 0.4451 (0.4821)	model_time 0.4449 (0.4608)	loss 3.8237 (3.6408)	grad_norm 1.8067 (1.6523/0.8594)	mem 16099MB
[2025-01-18 00:42:38 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][80/312]	eta 0:01:51 lr 0.003606	time 0.4456 (0.4803)	model_time 0.4453 (0.4615)	loss 2.6066 (3.6771)	grad_norm 0.6862 (1.6311/0.8305)	mem 16099MB
[2025-01-18 00:42:42 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][90/312]	eta 0:01:46 lr 0.003606	time 0.4469 (0.4775)	model_time 0.4464 (0.4608)	loss 3.2565 (3.6516)	grad_norm 1.0915 (1.5959/0.8225)	mem 16099MB
[2025-01-18 00:42:47 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][100/312]	eta 0:01:41 lr 0.003606	time 0.4743 (0.4774)	model_time 0.4738 (0.4623)	loss 2.0284 (3.6025)	grad_norm 0.7956 (1.5378/0.8047)	mem 16099MB
[2025-01-18 00:42:52 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][110/312]	eta 0:01:36 lr 0.003605	time 0.4703 (0.4779)	model_time 0.4698 (0.4641)	loss 3.8682 (3.5878)	grad_norm 1.1076 (1.5050/0.7834)	mem 16099MB
[2025-01-18 00:42:56 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][120/312]	eta 0:01:31 lr 0.003605	time 0.4537 (0.4756)	model_time 0.4535 (0.4630)	loss 3.3230 (3.5905)	grad_norm 1.1838 (1.5303/0.7759)	mem 16099MB
[2025-01-18 00:43:01 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][130/312]	eta 0:01:26 lr 0.003604	time 0.4478 (0.4743)	model_time 0.4475 (0.4626)	loss 4.0031 (3.5825)	grad_norm 1.2806 (1.5324/0.7685)	mem 16099MB
[2025-01-18 00:43:06 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][140/312]	eta 0:01:21 lr 0.003604	time 0.4530 (0.4734)	model_time 0.4528 (0.4624)	loss 3.3024 (3.6026)	grad_norm 2.3472 (1.5683/0.7714)	mem 16099MB
[2025-01-18 00:43:10 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][150/312]	eta 0:01:16 lr 0.003604	time 0.4511 (0.4734)	model_time 0.4510 (0.4632)	loss 3.7415 (3.6118)	grad_norm 1.3016 (1.5402/0.7588)	mem 16099MB
[2025-01-18 00:43:15 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][160/312]	eta 0:01:11 lr 0.003603	time 0.5005 (0.4734)	model_time 0.5003 (0.4638)	loss 3.7399 (3.6130)	grad_norm 1.2317 (1.5041/0.7493)	mem 16099MB
[2025-01-18 00:43:20 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][170/312]	eta 0:01:07 lr 0.003603	time 0.4462 (0.4727)	model_time 0.4460 (0.4636)	loss 3.9344 (3.6207)	grad_norm 2.9032 (1.5167/0.7566)	mem 16099MB
[2025-01-18 00:43:24 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][180/312]	eta 0:01:02 lr 0.003602	time 0.4479 (0.4725)	model_time 0.4477 (0.4639)	loss 3.3938 (3.6251)	grad_norm 1.0060 (1.5210/0.7570)	mem 16099MB
[2025-01-18 00:43:29 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][190/312]	eta 0:00:57 lr 0.003602	time 0.4619 (0.4716)	model_time 0.4617 (0.4634)	loss 4.0559 (3.6420)	grad_norm 1.6056 (1.5323/0.7460)	mem 16099MB
[2025-01-18 00:43:33 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][200/312]	eta 0:00:52 lr 0.003602	time 0.4471 (0.4707)	model_time 0.4466 (0.4629)	loss 4.5368 (3.6540)	grad_norm 2.0135 (1.5369/0.7360)	mem 16099MB
[2025-01-18 00:43:38 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][210/312]	eta 0:00:47 lr 0.003601	time 0.4525 (0.4703)	model_time 0.4523 (0.4629)	loss 3.4736 (3.6509)	grad_norm 2.8532 (1.5316/0.7276)	mem 16099MB
[2025-01-18 00:43:43 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][220/312]	eta 0:00:43 lr 0.003601	time 0.4589 (0.4701)	model_time 0.4587 (0.4630)	loss 2.8887 (3.6374)	grad_norm 2.9479 (1.5516/0.7342)	mem 16099MB
[2025-01-18 00:43:47 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][230/312]	eta 0:00:38 lr 0.003600	time 0.4501 (0.4696)	model_time 0.4499 (0.4628)	loss 4.0834 (3.6339)	grad_norm 1.8792 (1.5452/0.7233)	mem 16099MB
[2025-01-18 00:43:52 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][240/312]	eta 0:00:33 lr 0.003600	time 0.4482 (0.4690)	model_time 0.4480 (0.4624)	loss 3.3135 (3.6258)	grad_norm 1.1484 (1.5241/0.7176)	mem 16099MB
[2025-01-18 00:43:56 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][250/312]	eta 0:00:29 lr 0.003600	time 0.4572 (0.4686)	model_time 0.4567 (0.4623)	loss 2.6665 (3.6142)	grad_norm 2.0940 (1.5411/0.7361)	mem 16099MB
[2025-01-18 00:44:01 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][260/312]	eta 0:00:24 lr 0.003599	time 0.4462 (0.4684)	model_time 0.4460 (0.4623)	loss 3.7367 (3.6205)	grad_norm 1.0872 (1.5446/0.7270)	mem 16099MB
[2025-01-18 00:44:06 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][270/312]	eta 0:00:19 lr 0.003599	time 0.4647 (0.4684)	model_time 0.4645 (0.4626)	loss 3.9301 (3.6190)	grad_norm 1.3570 (1.5455/0.7229)	mem 16099MB
[2025-01-18 00:44:10 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][280/312]	eta 0:00:14 lr 0.003598	time 0.4497 (0.4680)	model_time 0.4492 (0.4623)	loss 4.7982 (3.6199)	grad_norm 1.3317 (1.5322/0.7153)	mem 16099MB
[2025-01-18 00:44:15 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][290/312]	eta 0:00:10 lr 0.003598	time 0.4511 (0.4675)	model_time 0.4509 (0.4620)	loss 3.9716 (3.6158)	grad_norm 1.4580 (1.5375/0.7127)	mem 16099MB
[2025-01-18 00:44:20 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][300/312]	eta 0:00:05 lr 0.003598	time 0.4373 (0.4677)	model_time 0.4372 (0.4624)	loss 3.3710 (3.6073)	grad_norm 0.7641 (1.5206/0.7091)	mem 16099MB
[2025-01-18 00:44:24 internimage_t_1k_224] (main.py 510): INFO Train: [61/300][310/312]	eta 0:00:00 lr 0.003597	time 0.4374 (0.4668)	model_time 0.4373 (0.4616)	loss 3.9563 (3.6142)	grad_norm 0.9314 (1.5289/0.7620)	mem 16099MB
[2025-01-18 00:44:24 internimage_t_1k_224] (main.py 519): INFO EPOCH 61 training takes 0:02:25
[2025-01-18 00:44:24 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_61.pth saving......
[2025-01-18 00:44:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_61.pth saved !!!
[2025-01-18 00:44:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.557 (7.557)	Loss 1.0250 (1.0250)	Acc@1 78.589 (78.589)	Acc@5 94.531 (94.531)	Mem 16099MB
[2025-01-18 00:44:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.000)	Loss 1.4005 (1.1866)	Acc@1 68.896 (74.814)	Acc@5 89.966 (92.762)	Mem 16099MB
[2025-01-18 00:44:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:61] * Acc@1 74.738 Acc@5 92.776
[2025-01-18 00:44:37 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.7%
[2025-01-18 00:44:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 00:44:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 00:44:38 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.74%
[2025-01-18 00:44:45 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.504 (7.504)	Loss 2.1535 (2.1535)	Acc@1 60.059 (60.059)	Acc@5 82.959 (82.959)	Mem 16099MB
[2025-01-18 00:44:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.015)	Loss 2.5958 (2.2801)	Acc@1 51.611 (57.659)	Acc@5 75.684 (80.937)	Mem 16099MB
[2025-01-18 00:44:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:61] * Acc@1 57.630 Acc@5 81.002
[2025-01-18 00:44:49 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 57.6%
[2025-01-18 00:44:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:44:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:44:51 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 57.63%
[2025-01-18 00:44:53 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][0/312]	eta 0:10:06 lr 0.003597	time 1.9424 (1.9424)	model_time 0.5031 (0.5031)	loss 4.0632 (4.0632)	grad_norm 0.8603 (0.8603/0.0000)	mem 16099MB
[2025-01-18 00:44:57 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][10/312]	eta 0:03:02 lr 0.003597	time 0.4617 (0.6044)	model_time 0.4613 (0.4732)	loss 4.0777 (3.6991)	grad_norm 0.7537 (0.9969/0.2162)	mem 16099MB
[2025-01-18 00:45:02 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][20/312]	eta 0:02:38 lr 0.003596	time 0.4585 (0.5422)	model_time 0.4583 (0.4733)	loss 3.6715 (3.7220)	grad_norm 0.9770 (1.1827/0.4262)	mem 16099MB
[2025-01-18 00:45:07 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][30/312]	eta 0:02:27 lr 0.003596	time 0.4490 (0.5239)	model_time 0.4486 (0.4770)	loss 3.9592 (3.5952)	grad_norm 2.0556 (1.4014/0.7060)	mem 16099MB
[2025-01-18 00:45:11 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][40/312]	eta 0:02:18 lr 0.003596	time 0.4501 (0.5086)	model_time 0.4499 (0.4731)	loss 4.1068 (3.5463)	grad_norm 2.2756 (1.3968/0.6611)	mem 16099MB
[2025-01-18 00:45:16 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][50/312]	eta 0:02:10 lr 0.003595	time 0.4546 (0.4993)	model_time 0.4544 (0.4707)	loss 2.6376 (3.4891)	grad_norm 1.8692 (1.4950/0.7053)	mem 16099MB
[2025-01-18 00:45:21 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][60/312]	eta 0:02:04 lr 0.003595	time 0.4480 (0.4934)	model_time 0.4479 (0.4695)	loss 4.3144 (3.5266)	grad_norm 1.2217 (1.4755/0.6826)	mem 16099MB
[2025-01-18 00:45:25 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][70/312]	eta 0:01:58 lr 0.003594	time 0.4575 (0.4884)	model_time 0.4571 (0.4678)	loss 3.1783 (3.5626)	grad_norm 0.8730 (1.4600/0.6512)	mem 16099MB
[2025-01-18 00:45:30 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][80/312]	eta 0:01:52 lr 0.003594	time 0.4695 (0.4854)	model_time 0.4691 (0.4673)	loss 4.3595 (3.6170)	grad_norm 1.6403 (1.4820/0.6500)	mem 16099MB
[2025-01-18 00:45:35 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][90/312]	eta 0:01:47 lr 0.003594	time 0.4551 (0.4844)	model_time 0.4549 (0.4682)	loss 3.4822 (3.6116)	grad_norm 1.6064 (1.4844/0.6432)	mem 16099MB
[2025-01-18 00:45:39 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][100/312]	eta 0:01:42 lr 0.003593	time 0.4519 (0.4817)	model_time 0.4518 (0.4671)	loss 2.5658 (3.6300)	grad_norm 2.5546 (1.5026/0.6288)	mem 16099MB
[2025-01-18 00:45:44 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][110/312]	eta 0:01:36 lr 0.003593	time 0.4537 (0.4795)	model_time 0.4535 (0.4662)	loss 4.0614 (3.6402)	grad_norm 1.8509 (1.5414/0.6550)	mem 16099MB
[2025-01-18 00:45:48 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][120/312]	eta 0:01:31 lr 0.003592	time 0.4555 (0.4784)	model_time 0.4553 (0.4661)	loss 2.8650 (3.6418)	grad_norm 1.8096 (1.5305/0.6399)	mem 16099MB
[2025-01-18 00:45:53 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][130/312]	eta 0:01:26 lr 0.003592	time 0.4567 (0.4778)	model_time 0.4564 (0.4664)	loss 3.4651 (3.6425)	grad_norm 1.2809 (1.5554/0.6442)	mem 16099MB
[2025-01-18 00:45:58 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][140/312]	eta 0:01:21 lr 0.003591	time 0.4678 (0.4766)	model_time 0.4675 (0.4661)	loss 3.6719 (3.6607)	grad_norm 2.7898 (1.5893/0.6959)	mem 16099MB
[2025-01-18 00:46:02 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][150/312]	eta 0:01:17 lr 0.003591	time 0.4582 (0.4755)	model_time 0.4580 (0.4656)	loss 3.9412 (3.6568)	grad_norm 1.5155 (1.5640/0.6815)	mem 16099MB
[2025-01-18 00:46:07 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][160/312]	eta 0:01:12 lr 0.003591	time 0.4726 (0.4748)	model_time 0.4724 (0.4654)	loss 2.6560 (3.6477)	grad_norm 1.0710 (1.5421/0.6738)	mem 16099MB
[2025-01-18 00:46:12 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][170/312]	eta 0:01:07 lr 0.003590	time 0.4509 (0.4738)	model_time 0.4504 (0.4650)	loss 4.0343 (3.6364)	grad_norm 0.8139 (1.5387/0.6704)	mem 16099MB
[2025-01-18 00:46:16 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][180/312]	eta 0:01:02 lr 0.003590	time 0.4505 (0.4727)	model_time 0.4500 (0.4644)	loss 4.0271 (3.6369)	grad_norm 1.9311 (1.5429/0.6614)	mem 16099MB
[2025-01-18 00:46:21 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][190/312]	eta 0:00:57 lr 0.003589	time 0.5508 (0.4722)	model_time 0.5506 (0.4643)	loss 4.4374 (3.6447)	grad_norm 0.7912 (1.5378/0.6539)	mem 16099MB
[2025-01-18 00:46:25 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][200/312]	eta 0:00:52 lr 0.003589	time 0.4453 (0.4711)	model_time 0.4450 (0.4636)	loss 2.9869 (3.6476)	grad_norm 1.7041 (1.5463/0.6652)	mem 16099MB
[2025-01-18 00:46:30 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][210/312]	eta 0:00:47 lr 0.003589	time 0.4488 (0.4705)	model_time 0.4487 (0.4633)	loss 3.8451 (3.6426)	grad_norm 1.5395 (1.5445/0.6552)	mem 16099MB
[2025-01-18 00:46:34 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][220/312]	eta 0:00:43 lr 0.003588	time 0.4495 (0.4701)	model_time 0.4493 (0.4632)	loss 4.4030 (3.6441)	grad_norm 0.8524 (1.5288/0.6468)	mem 16099MB
[2025-01-18 00:46:39 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][230/312]	eta 0:00:38 lr 0.003588	time 0.4508 (0.4697)	model_time 0.4506 (0.4631)	loss 3.7575 (3.6517)	grad_norm 1.3625 (1.5309/0.6402)	mem 16099MB
[2025-01-18 00:46:44 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][240/312]	eta 0:00:33 lr 0.003587	time 0.4739 (0.4699)	model_time 0.4734 (0.4636)	loss 2.5445 (3.6441)	grad_norm 1.8563 (1.5261/0.6350)	mem 16099MB
[2025-01-18 00:46:48 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][250/312]	eta 0:00:29 lr 0.003587	time 0.4507 (0.4696)	model_time 0.4501 (0.4635)	loss 3.7117 (3.6436)	grad_norm 1.8855 (1.5220/0.6282)	mem 16099MB
[2025-01-18 00:46:53 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][260/312]	eta 0:00:24 lr 0.003587	time 0.4493 (0.4703)	model_time 0.4488 (0.4644)	loss 4.0648 (3.6429)	grad_norm 2.4798 (1.5574/0.6850)	mem 16099MB
[2025-01-18 00:46:58 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][270/312]	eta 0:00:19 lr 0.003586	time 0.4520 (0.4697)	model_time 0.4518 (0.4640)	loss 3.4749 (3.6401)	grad_norm 0.8488 (1.5512/0.6782)	mem 16099MB
[2025-01-18 00:47:02 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][280/312]	eta 0:00:15 lr 0.003586	time 0.4615 (0.4694)	model_time 0.4614 (0.4639)	loss 4.6514 (3.6420)	grad_norm 1.3473 (1.5422/0.6690)	mem 16099MB
[2025-01-18 00:47:07 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][290/312]	eta 0:00:10 lr 0.003585	time 0.4620 (0.4696)	model_time 0.4618 (0.4642)	loss 4.0473 (3.6424)	grad_norm 3.5059 (1.5387/0.6707)	mem 16099MB
[2025-01-18 00:47:12 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][300/312]	eta 0:00:05 lr 0.003585	time 0.4410 (0.4694)	model_time 0.4409 (0.4642)	loss 3.2603 (3.6375)	grad_norm 1.1657 (1.5500/0.6737)	mem 16099MB
[2025-01-18 00:47:16 internimage_t_1k_224] (main.py 510): INFO Train: [62/300][310/312]	eta 0:00:00 lr 0.003585	time 0.5166 (0.4688)	model_time 0.5165 (0.4638)	loss 4.2436 (3.6284)	grad_norm 0.8780 (1.5668/0.6755)	mem 16099MB
[2025-01-18 00:47:17 internimage_t_1k_224] (main.py 519): INFO EPOCH 62 training takes 0:02:26
[2025-01-18 00:47:17 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_62.pth saving......
[2025-01-18 00:47:18 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_62.pth saved !!!
[2025-01-18 00:47:26 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.535 (7.535)	Loss 1.0249 (1.0249)	Acc@1 78.247 (78.247)	Acc@5 95.117 (95.117)	Mem 16099MB
[2025-01-18 00:47:29 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.020)	Loss 1.4819 (1.2228)	Acc@1 68.262 (74.512)	Acc@5 88.965 (92.403)	Mem 16099MB
[2025-01-18 00:47:29 internimage_t_1k_224] (main.py 575): INFO [Epoch:62] * Acc@1 74.546 Acc@5 92.464
[2025-01-18 00:47:29 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.5%
[2025-01-18 00:47:29 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.74%
[2025-01-18 00:47:38 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.070 (8.070)	Loss 2.0678 (2.0678)	Acc@1 61.182 (61.182)	Acc@5 83.765 (83.765)	Mem 16099MB
[2025-01-18 00:47:41 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.086)	Loss 2.5267 (2.2087)	Acc@1 52.612 (58.685)	Acc@5 76.929 (81.789)	Mem 16099MB
[2025-01-18 00:47:42 internimage_t_1k_224] (main.py 575): INFO [Epoch:62] * Acc@1 58.675 Acc@5 81.852
[2025-01-18 00:47:42 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 58.7%
[2025-01-18 00:47:42 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:47:43 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:47:43 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 58.68%
[2025-01-18 00:47:45 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][0/312]	eta 0:09:45 lr 0.003585	time 1.8757 (1.8757)	model_time 0.4655 (0.4655)	loss 2.7623 (2.7623)	grad_norm 2.0770 (2.0770/0.0000)	mem 16099MB
[2025-01-18 00:47:49 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][10/312]	eta 0:03:03 lr 0.003584	time 0.4503 (0.6073)	model_time 0.4498 (0.4787)	loss 4.0549 (3.4683)	grad_norm 1.4157 (1.2251/0.4189)	mem 16099MB
[2025-01-18 00:47:54 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][20/312]	eta 0:02:37 lr 0.003584	time 0.4526 (0.5397)	model_time 0.4522 (0.4722)	loss 2.8237 (3.5214)	grad_norm 1.7372 (1.5504/0.7743)	mem 16099MB
[2025-01-18 00:47:59 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][30/312]	eta 0:02:26 lr 0.003583	time 0.4510 (0.5179)	model_time 0.4508 (0.4720)	loss 2.2112 (3.5610)	grad_norm 0.8836 (1.5226/0.7219)	mem 16099MB
[2025-01-18 00:48:03 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][40/312]	eta 0:02:17 lr 0.003583	time 0.4473 (0.5037)	model_time 0.4472 (0.4690)	loss 3.9155 (3.5781)	grad_norm 1.0402 (1.5540/0.7674)	mem 16099MB
[2025-01-18 00:48:08 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][50/312]	eta 0:02:09 lr 0.003582	time 0.4486 (0.4957)	model_time 0.4484 (0.4677)	loss 3.9315 (3.6235)	grad_norm 1.1741 (1.4820/0.7109)	mem 16099MB
[2025-01-18 00:48:13 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][60/312]	eta 0:02:03 lr 0.003582	time 0.5421 (0.4899)	model_time 0.5420 (0.4664)	loss 3.4465 (3.5465)	grad_norm 1.6083 (1.5082/0.6963)	mem 16099MB
[2025-01-18 00:48:17 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][70/312]	eta 0:01:57 lr 0.003582	time 0.4631 (0.4847)	model_time 0.4626 (0.4645)	loss 3.5123 (3.5898)	grad_norm 1.8133 (1.5081/0.6649)	mem 16099MB
[2025-01-18 00:48:22 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][80/312]	eta 0:01:51 lr 0.003581	time 0.4423 (0.4807)	model_time 0.4418 (0.4629)	loss 3.1334 (3.6091)	grad_norm 2.3162 (1.4887/0.6446)	mem 16099MB
[2025-01-18 00:48:26 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][90/312]	eta 0:01:46 lr 0.003581	time 0.4516 (0.4775)	model_time 0.4515 (0.4617)	loss 3.6004 (3.6071)	grad_norm 1.0031 (1.5145/0.6787)	mem 16099MB
[2025-01-18 00:48:31 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][100/312]	eta 0:01:40 lr 0.003580	time 0.4496 (0.4760)	model_time 0.4492 (0.4617)	loss 2.7100 (3.5950)	grad_norm 0.9014 (1.5074/0.6607)	mem 16099MB
[2025-01-18 00:48:35 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][110/312]	eta 0:01:35 lr 0.003580	time 0.4413 (0.4750)	model_time 0.4409 (0.4619)	loss 3.9413 (3.6151)	grad_norm 3.2347 (1.5534/0.6911)	mem 16099MB
[2025-01-18 00:48:40 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][120/312]	eta 0:01:30 lr 0.003580	time 0.4473 (0.4733)	model_time 0.4472 (0.4613)	loss 3.5072 (3.5989)	grad_norm 2.5071 (1.5618/0.6861)	mem 16099MB
[2025-01-18 00:48:45 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][130/312]	eta 0:01:25 lr 0.003579	time 0.4517 (0.4722)	model_time 0.4516 (0.4611)	loss 4.6207 (3.5970)	grad_norm 0.9715 (1.5283/0.6742)	mem 16099MB
[2025-01-18 00:48:49 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][140/312]	eta 0:01:21 lr 0.003579	time 0.4393 (0.4713)	model_time 0.4388 (0.4609)	loss 2.5407 (3.5770)	grad_norm 1.9416 (1.5068/0.6594)	mem 16099MB
[2025-01-18 00:48:54 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][150/312]	eta 0:01:16 lr 0.003578	time 0.4476 (0.4728)	model_time 0.4472 (0.4630)	loss 2.9096 (3.5715)	grad_norm 0.6613 (1.4917/0.6481)	mem 16099MB
[2025-01-18 00:48:59 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][160/312]	eta 0:01:11 lr 0.003578	time 0.4493 (0.4722)	model_time 0.4488 (0.4630)	loss 3.9454 (3.5603)	grad_norm 1.1288 (1.5276/0.7256)	mem 16099MB
[2025-01-18 00:49:03 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][170/312]	eta 0:01:06 lr 0.003578	time 0.4373 (0.4717)	model_time 0.4372 (0.4631)	loss 3.8408 (3.5474)	grad_norm 1.6336 (1.5468/0.7552)	mem 16099MB
[2025-01-18 00:49:08 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][180/312]	eta 0:01:02 lr 0.003577	time 0.4607 (0.4712)	model_time 0.4602 (0.4630)	loss 3.7384 (3.5528)	grad_norm 0.9408 (1.5422/0.7696)	mem 16099MB
[2025-01-18 00:49:13 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][190/312]	eta 0:00:57 lr 0.003577	time 0.4536 (0.4705)	model_time 0.4532 (0.4628)	loss 2.4168 (3.5536)	grad_norm 0.8671 (1.5267/0.7554)	mem 16099MB
[2025-01-18 00:49:17 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][200/312]	eta 0:00:52 lr 0.003576	time 0.4657 (0.4697)	model_time 0.4656 (0.4623)	loss 3.8847 (3.5496)	grad_norm 1.0059 (1.5247/0.7413)	mem 16099MB
[2025-01-18 00:49:22 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][210/312]	eta 0:00:47 lr 0.003576	time 0.4790 (0.4705)	model_time 0.4786 (0.4635)	loss 3.2441 (3.5588)	grad_norm 1.5698 (1.5389/0.7532)	mem 16099MB
[2025-01-18 00:49:27 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][220/312]	eta 0:00:43 lr 0.003576	time 0.4438 (0.4697)	model_time 0.4434 (0.4630)	loss 2.7493 (3.5518)	grad_norm 1.5881 (1.5424/0.7486)	mem 16099MB
[2025-01-18 00:49:31 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][230/312]	eta 0:00:38 lr 0.003575	time 0.4479 (0.4701)	model_time 0.4475 (0.4636)	loss 3.8033 (3.5659)	grad_norm 1.4987 (1.5304/0.7427)	mem 16099MB
[2025-01-18 00:49:36 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][240/312]	eta 0:00:33 lr 0.003575	time 0.4432 (0.4695)	model_time 0.4428 (0.4633)	loss 3.9464 (3.5729)	grad_norm 0.9366 (1.5249/0.7298)	mem 16099MB
[2025-01-18 00:49:40 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][250/312]	eta 0:00:29 lr 0.003574	time 0.4477 (0.4691)	model_time 0.4476 (0.4631)	loss 3.7931 (3.5734)	grad_norm 3.8950 (1.5485/0.7454)	mem 16099MB
[2025-01-18 00:49:45 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][260/312]	eta 0:00:24 lr 0.003574	time 0.4539 (0.4688)	model_time 0.4535 (0.4630)	loss 4.0934 (3.5757)	grad_norm 1.2421 (1.5624/0.7436)	mem 16099MB
[2025-01-18 00:49:50 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][270/312]	eta 0:00:19 lr 0.003573	time 0.4505 (0.4683)	model_time 0.4503 (0.4627)	loss 3.2333 (3.5761)	grad_norm 0.8721 (1.5505/0.7371)	mem 16099MB
[2025-01-18 00:49:54 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][280/312]	eta 0:00:14 lr 0.003573	time 0.4532 (0.4684)	model_time 0.4528 (0.4630)	loss 4.4181 (3.5848)	grad_norm 1.1139 (1.5504/0.7257)	mem 16099MB
[2025-01-18 00:49:59 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][290/312]	eta 0:00:10 lr 0.003573	time 0.4636 (0.4682)	model_time 0.4634 (0.4630)	loss 3.5082 (3.5765)	grad_norm 1.0356 (1.5363/0.7190)	mem 16099MB
[2025-01-18 00:50:04 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][300/312]	eta 0:00:05 lr 0.003572	time 0.5275 (0.4679)	model_time 0.5274 (0.4628)	loss 3.7900 (3.5808)	grad_norm 2.5665 (1.5284/0.7165)	mem 16099MB
[2025-01-18 00:50:08 internimage_t_1k_224] (main.py 510): INFO Train: [63/300][310/312]	eta 0:00:00 lr 0.003572	time 0.4375 (0.4670)	model_time 0.4374 (0.4622)	loss 3.9671 (3.5829)	grad_norm 0.9033 (1.5314/0.7141)	mem 16099MB
[2025-01-18 00:50:08 internimage_t_1k_224] (main.py 519): INFO EPOCH 63 training takes 0:02:25
[2025-01-18 00:50:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_63.pth saving......
[2025-01-18 00:50:10 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_63.pth saved !!!
[2025-01-18 00:50:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.666 (7.666)	Loss 0.9973 (0.9973)	Acc@1 77.612 (77.612)	Acc@5 94.824 (94.824)	Mem 16099MB
[2025-01-18 00:50:21 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.023)	Loss 1.3942 (1.1842)	Acc@1 69.141 (74.339)	Acc@5 89.819 (92.640)	Mem 16099MB
[2025-01-18 00:50:21 internimage_t_1k_224] (main.py 575): INFO [Epoch:63] * Acc@1 74.338 Acc@5 92.682
[2025-01-18 00:50:21 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.3%
[2025-01-18 00:50:21 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.74%
[2025-01-18 00:50:30 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.637 (8.637)	Loss 1.9869 (1.9869)	Acc@1 62.109 (62.109)	Acc@5 84.766 (84.766)	Mem 16099MB
[2025-01-18 00:50:34 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.141)	Loss 2.4607 (2.1402)	Acc@1 53.662 (59.768)	Acc@5 77.832 (82.566)	Mem 16099MB
[2025-01-18 00:50:34 internimage_t_1k_224] (main.py 575): INFO [Epoch:63] * Acc@1 59.769 Acc@5 82.602
[2025-01-18 00:50:34 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 59.8%
[2025-01-18 00:50:34 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:50:35 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:50:35 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 59.77%
[2025-01-18 00:50:37 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][0/312]	eta 0:11:29 lr 0.003572	time 2.2102 (2.2102)	model_time 0.4673 (0.4673)	loss 3.4966 (3.4966)	grad_norm 1.1202 (1.1202/0.0000)	mem 16099MB
[2025-01-18 00:50:42 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][10/312]	eta 0:03:08 lr 0.003571	time 0.4545 (0.6238)	model_time 0.4543 (0.4650)	loss 4.3437 (3.4768)	grad_norm 2.8860 (1.8189/0.7420)	mem 16099MB
[2025-01-18 00:50:46 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][20/312]	eta 0:02:38 lr 0.003571	time 0.4598 (0.5437)	model_time 0.4597 (0.4603)	loss 3.6351 (3.4539)	grad_norm 3.4480 (2.0711/1.0697)	mem 16099MB
[2025-01-18 00:50:51 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][30/312]	eta 0:02:27 lr 0.003570	time 0.4819 (0.5213)	model_time 0.4818 (0.4648)	loss 3.1518 (3.4716)	grad_norm 2.0190 (1.9915/0.9252)	mem 16099MB
[2025-01-18 00:50:56 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][40/312]	eta 0:02:17 lr 0.003570	time 0.4546 (0.5070)	model_time 0.4544 (0.4641)	loss 2.2871 (3.4877)	grad_norm 0.6829 (1.7737/0.9131)	mem 16099MB
[2025-01-18 00:51:00 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][50/312]	eta 0:02:10 lr 0.003570	time 0.4447 (0.4980)	model_time 0.4442 (0.4635)	loss 3.5642 (3.5319)	grad_norm 1.6556 (1.6802/0.8596)	mem 16099MB
[2025-01-18 00:51:05 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][60/312]	eta 0:02:03 lr 0.003569	time 0.4487 (0.4908)	model_time 0.4483 (0.4618)	loss 4.4341 (3.5315)	grad_norm 1.5435 (1.6462/0.8410)	mem 16099MB
[2025-01-18 00:51:09 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][70/312]	eta 0:01:57 lr 0.003569	time 0.4877 (0.4856)	model_time 0.4872 (0.4607)	loss 3.9855 (3.5883)	grad_norm 0.8654 (1.6465/0.8166)	mem 16099MB
[2025-01-18 00:51:14 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][80/312]	eta 0:01:51 lr 0.003568	time 0.4545 (0.4819)	model_time 0.4543 (0.4600)	loss 3.7042 (3.5930)	grad_norm 1.8110 (1.5973/0.7841)	mem 16099MB
[2025-01-18 00:51:18 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][90/312]	eta 0:01:46 lr 0.003568	time 0.4605 (0.4794)	model_time 0.4604 (0.4598)	loss 3.6126 (3.5810)	grad_norm 1.0285 (1.5548/0.7614)	mem 16099MB
[2025-01-18 00:51:23 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][100/312]	eta 0:01:41 lr 0.003568	time 0.4537 (0.4786)	model_time 0.4535 (0.4609)	loss 3.7909 (3.6008)	grad_norm 1.1474 (1.5566/0.7470)	mem 16099MB
[2025-01-18 00:51:28 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][110/312]	eta 0:01:36 lr 0.003567	time 0.4431 (0.4777)	model_time 0.4427 (0.4616)	loss 4.1064 (3.6268)	grad_norm 1.3640 (1.5266/0.7256)	mem 16099MB
[2025-01-18 00:51:33 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][120/312]	eta 0:01:31 lr 0.003567	time 0.5411 (0.4777)	model_time 0.5410 (0.4630)	loss 2.1786 (3.6167)	grad_norm 1.0596 (1.5098/0.7025)	mem 16099MB
[2025-01-18 00:51:37 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][130/312]	eta 0:01:27 lr 0.003566	time 0.4386 (0.4780)	model_time 0.4382 (0.4643)	loss 4.2766 (3.6407)	grad_norm 0.9311 (1.5624/0.7824)	mem 16099MB
[2025-01-18 00:51:42 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][140/312]	eta 0:01:22 lr 0.003566	time 0.4584 (0.4774)	model_time 0.4580 (0.4646)	loss 3.2051 (3.6319)	grad_norm 0.9735 (1.5789/0.7849)	mem 16099MB
[2025-01-18 00:51:47 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][150/312]	eta 0:01:17 lr 0.003566	time 0.4542 (0.4766)	model_time 0.4540 (0.4646)	loss 2.4290 (3.6083)	grad_norm 0.8626 (1.5610/0.7650)	mem 16099MB
[2025-01-18 00:51:51 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][160/312]	eta 0:01:12 lr 0.003565	time 0.4389 (0.4759)	model_time 0.4388 (0.4647)	loss 2.7578 (3.6025)	grad_norm 1.1037 (1.5404/0.7500)	mem 16099MB
[2025-01-18 00:51:56 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][170/312]	eta 0:01:07 lr 0.003565	time 0.4631 (0.4749)	model_time 0.4629 (0.4644)	loss 4.0775 (3.5960)	grad_norm 2.4686 (1.5859/0.7893)	mem 16099MB
[2025-01-18 00:52:01 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][180/312]	eta 0:01:02 lr 0.003564	time 0.4530 (0.4739)	model_time 0.4529 (0.4639)	loss 4.1406 (3.5950)	grad_norm 1.8562 (1.6064/0.7879)	mem 16099MB
[2025-01-18 00:52:05 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][190/312]	eta 0:00:57 lr 0.003564	time 0.4412 (0.4735)	model_time 0.4410 (0.4640)	loss 3.2896 (3.5969)	grad_norm 1.1721 (1.5896/0.7766)	mem 16099MB
[2025-01-18 00:52:10 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][200/312]	eta 0:00:52 lr 0.003563	time 0.4545 (0.4727)	model_time 0.4541 (0.4637)	loss 2.5917 (3.5914)	grad_norm 1.1822 (1.5672/0.7675)	mem 16099MB
[2025-01-18 00:52:15 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][210/312]	eta 0:00:48 lr 0.003563	time 0.4418 (0.4723)	model_time 0.4414 (0.4637)	loss 2.4072 (3.5867)	grad_norm 0.8434 (1.5436/0.7602)	mem 16099MB
[2025-01-18 00:52:19 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][220/312]	eta 0:00:43 lr 0.003563	time 0.4524 (0.4719)	model_time 0.4520 (0.4637)	loss 3.7628 (3.5790)	grad_norm 1.2598 (1.5505/0.7516)	mem 16099MB
[2025-01-18 00:52:24 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][230/312]	eta 0:00:38 lr 0.003562	time 0.4440 (0.4711)	model_time 0.4438 (0.4632)	loss 3.8119 (3.5797)	grad_norm 1.0556 (1.5500/0.7444)	mem 16099MB
[2025-01-18 00:52:28 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][240/312]	eta 0:00:33 lr 0.003562	time 0.4511 (0.4703)	model_time 0.4507 (0.4627)	loss 3.9184 (3.5742)	grad_norm 0.7807 (1.5354/0.7340)	mem 16099MB
[2025-01-18 00:52:33 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][250/312]	eta 0:00:29 lr 0.003561	time 0.4639 (0.4699)	model_time 0.4634 (0.4626)	loss 3.5355 (3.5750)	grad_norm 2.4653 (1.5478/0.7330)	mem 16099MB
[2025-01-18 00:52:37 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][260/312]	eta 0:00:24 lr 0.003561	time 0.4504 (0.4694)	model_time 0.4499 (0.4623)	loss 4.0163 (3.5810)	grad_norm 1.7153 (1.5723/0.7428)	mem 16099MB
[2025-01-18 00:52:42 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][270/312]	eta 0:00:19 lr 0.003561	time 0.4516 (0.4695)	model_time 0.4515 (0.4626)	loss 3.9517 (3.5774)	grad_norm 1.7256 (1.5772/0.7409)	mem 16099MB
[2025-01-18 00:52:47 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][280/312]	eta 0:00:15 lr 0.003560	time 0.4621 (0.4693)	model_time 0.4617 (0.4627)	loss 2.4227 (3.5805)	grad_norm 1.0925 (1.5731/0.7360)	mem 16099MB
[2025-01-18 00:52:51 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][290/312]	eta 0:00:10 lr 0.003560	time 0.4552 (0.4691)	model_time 0.4550 (0.4627)	loss 4.5858 (3.5737)	grad_norm 0.8954 (1.5657/0.7304)	mem 16099MB
[2025-01-18 00:52:56 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][300/312]	eta 0:00:05 lr 0.003559	time 0.4372 (0.4692)	model_time 0.4371 (0.4631)	loss 3.3439 (3.5726)	grad_norm 2.1158 (1.5640/0.7227)	mem 16099MB
[2025-01-18 00:53:01 internimage_t_1k_224] (main.py 510): INFO Train: [64/300][310/312]	eta 0:00:00 lr 0.003559	time 0.5573 (0.4691)	model_time 0.5572 (0.4631)	loss 3.7044 (3.5739)	grad_norm 1.5786 (1.5593/0.7171)	mem 16099MB
[2025-01-18 00:53:01 internimage_t_1k_224] (main.py 519): INFO EPOCH 64 training takes 0:02:26
[2025-01-18 00:53:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_64.pth saving......
[2025-01-18 00:53:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_64.pth saved !!!
[2025-01-18 00:53:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.302 (7.302)	Loss 0.9845 (0.9845)	Acc@1 78.882 (78.882)	Acc@5 95.312 (95.312)	Mem 16099MB
[2025-01-18 00:53:13 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.984)	Loss 1.4287 (1.1860)	Acc@1 68.604 (74.916)	Acc@5 89.990 (92.793)	Mem 16099MB
[2025-01-18 00:53:13 internimage_t_1k_224] (main.py 575): INFO [Epoch:64] * Acc@1 74.816 Acc@5 92.826
[2025-01-18 00:53:13 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.8%
[2025-01-18 00:53:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 00:53:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 00:53:15 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.82%
[2025-01-18 00:53:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.587 (7.587)	Loss 1.9147 (1.9147)	Acc@1 63.403 (63.403)	Acc@5 85.645 (85.645)	Mem 16099MB
[2025-01-18 00:53:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.000)	Loss 2.3989 (2.0776)	Acc@1 54.517 (60.691)	Acc@5 78.564 (83.347)	Mem 16099MB
[2025-01-18 00:53:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:64] * Acc@1 60.677 Acc@5 83.371
[2025-01-18 00:53:26 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 60.7%
[2025-01-18 00:53:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:53:27 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:53:27 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 60.68%
[2025-01-18 00:53:29 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][0/312]	eta 0:11:32 lr 0.003559	time 2.2204 (2.2204)	model_time 0.6677 (0.6677)	loss 4.1051 (4.1051)	grad_norm 1.0236 (1.0236/0.0000)	mem 16099MB
[2025-01-18 00:53:34 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][10/312]	eta 0:03:10 lr 0.003558	time 0.4641 (0.6311)	model_time 0.4640 (0.4897)	loss 3.4430 (3.7079)	grad_norm 0.6130 (1.7322/0.6808)	mem 16099MB
[2025-01-18 00:53:39 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][20/312]	eta 0:02:44 lr 0.003558	time 0.4455 (0.5634)	model_time 0.4453 (0.4892)	loss 2.5658 (3.6683)	grad_norm 3.2201 (1.6520/0.8474)	mem 16099MB
[2025-01-18 00:53:43 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][30/312]	eta 0:02:30 lr 0.003557	time 0.4763 (0.5323)	model_time 0.4759 (0.4819)	loss 3.9795 (3.5902)	grad_norm 1.0481 (1.4879/0.7473)	mem 16099MB
[2025-01-18 00:53:48 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][40/312]	eta 0:02:20 lr 0.003557	time 0.4522 (0.5157)	model_time 0.4518 (0.4775)	loss 3.6318 (3.5711)	grad_norm 1.3266 (1.5047/0.7204)	mem 16099MB
[2025-01-18 00:53:53 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][50/312]	eta 0:02:12 lr 0.003557	time 0.4558 (0.5039)	model_time 0.4553 (0.4731)	loss 3.4193 (3.5747)	grad_norm 0.8642 (1.4025/0.6871)	mem 16099MB
[2025-01-18 00:53:57 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][60/312]	eta 0:02:05 lr 0.003556	time 0.4563 (0.4981)	model_time 0.4562 (0.4716)	loss 4.3868 (3.6200)	grad_norm 1.6766 (1.4708/0.7085)	mem 16099MB
[2025-01-18 00:54:02 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][70/312]	eta 0:01:59 lr 0.003556	time 0.4507 (0.4918)	model_time 0.4505 (0.4691)	loss 3.1250 (3.5524)	grad_norm 1.7409 (1.4578/0.6819)	mem 16099MB
[2025-01-18 00:54:06 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][80/312]	eta 0:01:53 lr 0.003555	time 0.4472 (0.4880)	model_time 0.4470 (0.4680)	loss 3.3232 (3.5302)	grad_norm 0.9271 (1.4896/0.6994)	mem 16099MB
[2025-01-18 00:54:11 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][90/312]	eta 0:01:48 lr 0.003555	time 0.4402 (0.4874)	model_time 0.4398 (0.4695)	loss 3.6758 (3.5502)	grad_norm 1.0370 (1.5087/0.6945)	mem 16099MB
[2025-01-18 00:54:16 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][100/312]	eta 0:01:42 lr 0.003555	time 0.4460 (0.4849)	model_time 0.4456 (0.4687)	loss 3.5598 (3.5561)	grad_norm 1.4541 (1.5198/0.6796)	mem 16099MB
[2025-01-18 00:54:20 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][110/312]	eta 0:01:37 lr 0.003554	time 0.5382 (0.4828)	model_time 0.5377 (0.4681)	loss 4.1848 (3.5649)	grad_norm 1.2741 (1.4926/0.6637)	mem 16099MB
[2025-01-18 00:54:25 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][120/312]	eta 0:01:32 lr 0.003554	time 0.4553 (0.4810)	model_time 0.4549 (0.4675)	loss 2.9344 (3.5576)	grad_norm 1.0170 (1.4974/0.6569)	mem 16099MB
[2025-01-18 00:54:30 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][130/312]	eta 0:01:27 lr 0.003553	time 0.4667 (0.4798)	model_time 0.4666 (0.4673)	loss 4.4592 (3.5350)	grad_norm 1.0052 (1.4826/0.6438)	mem 16099MB
[2025-01-18 00:54:34 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][140/312]	eta 0:01:22 lr 0.003553	time 0.4504 (0.4785)	model_time 0.4500 (0.4669)	loss 3.8332 (3.5495)	grad_norm 2.1874 (1.5088/0.6541)	mem 16099MB
[2025-01-18 00:54:39 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][150/312]	eta 0:01:17 lr 0.003552	time 0.4462 (0.4775)	model_time 0.4460 (0.4666)	loss 2.9915 (3.5663)	grad_norm 2.1329 (1.5181/0.6421)	mem 16099MB
[2025-01-18 00:54:44 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][160/312]	eta 0:01:12 lr 0.003552	time 0.4592 (0.4774)	model_time 0.4588 (0.4672)	loss 2.8298 (3.5541)	grad_norm 3.4457 (1.5196/0.6468)	mem 16099MB
[2025-01-18 00:54:48 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][170/312]	eta 0:01:07 lr 0.003552	time 0.4566 (0.4758)	model_time 0.4562 (0.4661)	loss 3.3766 (3.5485)	grad_norm 1.8693 (1.5543/0.6825)	mem 16099MB
[2025-01-18 00:54:53 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][180/312]	eta 0:01:02 lr 0.003551	time 0.4493 (0.4757)	model_time 0.4489 (0.4665)	loss 3.9385 (3.5581)	grad_norm 1.5042 (1.5467/0.6710)	mem 16099MB
[2025-01-18 00:54:58 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][190/312]	eta 0:00:57 lr 0.003551	time 0.4490 (0.4745)	model_time 0.4486 (0.4658)	loss 3.4998 (3.5622)	grad_norm 0.9304 (1.5530/0.6879)	mem 16099MB
[2025-01-18 00:55:02 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][200/312]	eta 0:00:53 lr 0.003550	time 0.4473 (0.4737)	model_time 0.4469 (0.4654)	loss 4.0267 (3.5718)	grad_norm 1.6721 (1.5800/0.7055)	mem 16099MB
[2025-01-18 00:55:07 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][210/312]	eta 0:00:48 lr 0.003550	time 0.4448 (0.4735)	model_time 0.4446 (0.4656)	loss 4.4393 (3.5771)	grad_norm 0.8087 (1.5889/0.7083)	mem 16099MB
[2025-01-18 00:55:11 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][220/312]	eta 0:00:43 lr 0.003550	time 0.4565 (0.4731)	model_time 0.4561 (0.4655)	loss 2.5167 (3.5684)	grad_norm 1.1514 (1.5724/0.7019)	mem 16099MB
[2025-01-18 00:55:16 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][230/312]	eta 0:00:38 lr 0.003549	time 0.4466 (0.4721)	model_time 0.4462 (0.4649)	loss 3.5303 (3.5725)	grad_norm 2.5542 (1.5705/0.7036)	mem 16099MB
[2025-01-18 00:55:21 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][240/312]	eta 0:00:33 lr 0.003549	time 0.4821 (0.4720)	model_time 0.4817 (0.4650)	loss 3.5873 (3.5727)	grad_norm 0.8741 (1.5695/0.7001)	mem 16099MB
[2025-01-18 00:55:25 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][250/312]	eta 0:00:29 lr 0.003548	time 0.4415 (0.4723)	model_time 0.4414 (0.4656)	loss 3.9329 (3.5715)	grad_norm 1.1210 (1.5574/0.6939)	mem 16099MB
[2025-01-18 00:55:30 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][260/312]	eta 0:00:24 lr 0.003548	time 0.4516 (0.4722)	model_time 0.4512 (0.4657)	loss 3.9085 (3.5834)	grad_norm 0.9295 (1.5564/0.6910)	mem 16099MB
[2025-01-18 00:55:35 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][270/312]	eta 0:00:19 lr 0.003547	time 0.4497 (0.4718)	model_time 0.4493 (0.4656)	loss 4.3816 (3.5824)	grad_norm 1.2913 (1.5516/0.6842)	mem 16099MB
[2025-01-18 00:55:39 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][280/312]	eta 0:00:15 lr 0.003547	time 0.4459 (0.4715)	model_time 0.4457 (0.4654)	loss 3.9825 (3.5761)	grad_norm 3.5902 (1.5755/0.7002)	mem 16099MB
[2025-01-18 00:55:44 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][290/312]	eta 0:00:10 lr 0.003547	time 0.4496 (0.4711)	model_time 0.4492 (0.4652)	loss 3.9615 (3.5826)	grad_norm 1.1106 (1.5663/0.6933)	mem 16099MB
[2025-01-18 00:55:49 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][300/312]	eta 0:00:05 lr 0.003546	time 0.4385 (0.4706)	model_time 0.4384 (0.4649)	loss 3.6339 (3.5819)	grad_norm 1.1930 (1.5656/0.6861)	mem 16099MB
[2025-01-18 00:55:53 internimage_t_1k_224] (main.py 510): INFO Train: [65/300][310/312]	eta 0:00:00 lr 0.003546	time 0.5169 (0.4701)	model_time 0.5168 (0.4646)	loss 3.5558 (3.5921)	grad_norm 1.5457 (1.5675/0.6879)	mem 16099MB
[2025-01-18 00:55:54 internimage_t_1k_224] (main.py 519): INFO EPOCH 65 training takes 0:02:26
[2025-01-18 00:55:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_65.pth saving......
[2025-01-18 00:55:55 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_65.pth saved !!!
[2025-01-18 00:56:02 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.178 (7.178)	Loss 0.9447 (0.9447)	Acc@1 78.735 (78.735)	Acc@5 95.166 (95.166)	Mem 16099MB
[2025-01-18 00:56:05 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.963)	Loss 1.3521 (1.1436)	Acc@1 69.995 (74.898)	Acc@5 90.186 (92.718)	Mem 16099MB
[2025-01-18 00:56:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:65] * Acc@1 74.922 Acc@5 92.788
[2025-01-18 00:56:06 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.9%
[2025-01-18 00:56:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 00:56:07 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 00:56:07 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.92%
[2025-01-18 00:56:14 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.392 (7.392)	Loss 1.8455 (1.8455)	Acc@1 64.771 (64.771)	Acc@5 86.548 (86.548)	Mem 16099MB
[2025-01-18 00:56:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.002)	Loss 2.3391 (2.0171)	Acc@1 55.347 (61.614)	Acc@5 79.419 (84.031)	Mem 16099MB
[2025-01-18 00:56:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:65] * Acc@1 61.604 Acc@5 84.071
[2025-01-18 00:56:18 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 61.6%
[2025-01-18 00:56:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:56:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:56:19 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 61.60%
[2025-01-18 00:56:21 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][0/312]	eta 0:11:41 lr 0.003546	time 2.2494 (2.2494)	model_time 0.4773 (0.4773)	loss 3.9441 (3.9441)	grad_norm 0.8309 (0.8309/0.0000)	mem 16099MB
[2025-01-18 00:56:26 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][10/312]	eta 0:03:12 lr 0.003545	time 0.4517 (0.6379)	model_time 0.4512 (0.4765)	loss 4.4592 (3.8093)	grad_norm 2.7109 (1.9312/0.8823)	mem 16099MB
[2025-01-18 00:56:31 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][20/312]	eta 0:02:43 lr 0.003545	time 0.4457 (0.5612)	model_time 0.4452 (0.4765)	loss 4.5109 (3.8215)	grad_norm 0.6966 (1.6378/0.7625)	mem 16099MB
[2025-01-18 00:56:36 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][30/312]	eta 0:02:31 lr 0.003544	time 0.4610 (0.5365)	model_time 0.4609 (0.4790)	loss 3.8629 (3.7663)	grad_norm 1.1626 (1.5341/0.6795)	mem 16099MB
[2025-01-18 00:56:40 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][40/312]	eta 0:02:20 lr 0.003544	time 0.4544 (0.5164)	model_time 0.4543 (0.4729)	loss 3.5076 (3.6843)	grad_norm 2.2271 (1.5607/0.6841)	mem 16099MB
[2025-01-18 00:56:45 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][50/312]	eta 0:02:12 lr 0.003543	time 0.4511 (0.5071)	model_time 0.4507 (0.4720)	loss 4.4318 (3.6283)	grad_norm 1.0332 (1.5734/0.7572)	mem 16099MB
[2025-01-18 00:56:50 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][60/312]	eta 0:02:05 lr 0.003543	time 0.4624 (0.4992)	model_time 0.4622 (0.4698)	loss 3.8991 (3.6464)	grad_norm 1.8492 (1.5409/0.7119)	mem 16099MB
[2025-01-18 00:56:54 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][70/312]	eta 0:01:59 lr 0.003543	time 0.4525 (0.4936)	model_time 0.4524 (0.4683)	loss 3.8548 (3.6437)	grad_norm 0.7831 (1.5006/0.6792)	mem 16099MB
[2025-01-18 00:56:59 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][80/312]	eta 0:01:53 lr 0.003542	time 0.4739 (0.4900)	model_time 0.4738 (0.4678)	loss 2.7263 (3.6299)	grad_norm 2.3779 (1.5259/0.6598)	mem 16099MB
[2025-01-18 00:57:03 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][90/312]	eta 0:01:48 lr 0.003542	time 0.4715 (0.4871)	model_time 0.4714 (0.4673)	loss 3.7074 (3.6444)	grad_norm 2.1387 (1.5628/0.6859)	mem 16099MB
[2025-01-18 00:57:08 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][100/312]	eta 0:01:42 lr 0.003541	time 0.4600 (0.4844)	model_time 0.4596 (0.4666)	loss 3.8876 (3.6342)	grad_norm 1.0001 (1.5421/0.6647)	mem 16099MB
[2025-01-18 00:57:13 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][110/312]	eta 0:01:37 lr 0.003541	time 0.5488 (0.4825)	model_time 0.5484 (0.4662)	loss 4.2705 (3.6426)	grad_norm 1.1670 (1.6130/0.7879)	mem 16099MB
[2025-01-18 00:57:17 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][120/312]	eta 0:01:32 lr 0.003541	time 0.4432 (0.4800)	model_time 0.4428 (0.4650)	loss 2.8163 (3.6256)	grad_norm 4.2248 (1.6341/0.8072)	mem 16099MB
[2025-01-18 00:57:22 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][130/312]	eta 0:01:27 lr 0.003540	time 0.4481 (0.4796)	model_time 0.4480 (0.4657)	loss 3.7440 (3.6185)	grad_norm 1.8658 (1.6126/0.7903)	mem 16099MB
[2025-01-18 00:57:27 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][140/312]	eta 0:01:22 lr 0.003540	time 0.4533 (0.4785)	model_time 0.4529 (0.4656)	loss 3.5084 (3.6179)	grad_norm 1.2393 (1.6102/0.7711)	mem 16099MB
[2025-01-18 00:57:31 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][150/312]	eta 0:01:17 lr 0.003539	time 0.4467 (0.4781)	model_time 0.4463 (0.4660)	loss 4.3563 (3.6035)	grad_norm 0.9255 (1.6122/0.7592)	mem 16099MB
[2025-01-18 00:57:36 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][160/312]	eta 0:01:12 lr 0.003539	time 0.4461 (0.4767)	model_time 0.4460 (0.4653)	loss 3.6475 (3.6042)	grad_norm 4.2332 (1.6490/0.7815)	mem 16099MB
[2025-01-18 00:57:40 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][170/312]	eta 0:01:07 lr 0.003538	time 0.4485 (0.4759)	model_time 0.4483 (0.4652)	loss 3.9178 (3.6042)	grad_norm 0.8518 (1.6368/0.7812)	mem 16099MB
[2025-01-18 00:57:45 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][180/312]	eta 0:01:02 lr 0.003538	time 0.5644 (0.4755)	model_time 0.5640 (0.4653)	loss 4.0554 (3.6068)	grad_norm 2.3275 (1.6257/0.7766)	mem 16099MB
[2025-01-18 00:57:50 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][190/312]	eta 0:00:57 lr 0.003538	time 0.4465 (0.4751)	model_time 0.4464 (0.4655)	loss 3.9050 (3.6071)	grad_norm 1.3052 (1.6010/0.7668)	mem 16099MB
[2025-01-18 00:57:55 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][200/312]	eta 0:00:53 lr 0.003537	time 0.4530 (0.4762)	model_time 0.4528 (0.4670)	loss 4.2873 (3.6087)	grad_norm 0.7916 (1.5971/0.7624)	mem 16099MB
[2025-01-18 00:58:00 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][210/312]	eta 0:00:48 lr 0.003537	time 0.4464 (0.4761)	model_time 0.4462 (0.4673)	loss 2.4535 (3.5880)	grad_norm 1.2766 (1.6009/0.7531)	mem 16099MB
[2025-01-18 00:58:04 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][220/312]	eta 0:00:43 lr 0.003536	time 0.4512 (0.4752)	model_time 0.4511 (0.4669)	loss 3.6751 (3.5929)	grad_norm 2.2843 (1.6046/0.7541)	mem 16099MB
[2025-01-18 00:58:09 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][230/312]	eta 0:00:38 lr 0.003536	time 0.4502 (0.4747)	model_time 0.4497 (0.4667)	loss 3.4474 (3.6003)	grad_norm 1.3436 (1.5901/0.7439)	mem 16099MB
[2025-01-18 00:58:13 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][240/312]	eta 0:00:34 lr 0.003535	time 0.4539 (0.4742)	model_time 0.4538 (0.4665)	loss 3.3895 (3.6003)	grad_norm 0.8126 (1.5651/0.7389)	mem 16099MB
[2025-01-18 00:58:18 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][250/312]	eta 0:00:29 lr 0.003535	time 0.4468 (0.4737)	model_time 0.4464 (0.4663)	loss 3.5274 (3.6096)	grad_norm 1.5849 (1.5467/0.7320)	mem 16099MB
[2025-01-18 00:58:23 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][260/312]	eta 0:00:24 lr 0.003535	time 0.4518 (0.4736)	model_time 0.4516 (0.4664)	loss 3.2794 (3.6002)	grad_norm 0.7473 (1.5520/0.7364)	mem 16099MB
[2025-01-18 00:58:27 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][270/312]	eta 0:00:19 lr 0.003534	time 0.4502 (0.4729)	model_time 0.4497 (0.4660)	loss 3.6846 (3.5985)	grad_norm 1.3543 (1.5531/0.7350)	mem 16099MB
[2025-01-18 00:58:32 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][280/312]	eta 0:00:15 lr 0.003534	time 0.4527 (0.4721)	model_time 0.4523 (0.4655)	loss 2.8961 (3.5937)	grad_norm 1.2747 (1.5819/0.7607)	mem 16099MB
[2025-01-18 00:58:36 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][290/312]	eta 0:00:10 lr 0.003533	time 0.4436 (0.4717)	model_time 0.4432 (0.4652)	loss 2.3552 (3.5945)	grad_norm 1.1119 (1.5761/0.7518)	mem 16099MB
[2025-01-18 00:58:41 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][300/312]	eta 0:00:05 lr 0.003533	time 0.5428 (0.4715)	model_time 0.5427 (0.4653)	loss 4.3372 (3.5967)	grad_norm 1.0987 (1.5848/0.7563)	mem 16099MB
[2025-01-18 00:58:45 internimage_t_1k_224] (main.py 510): INFO Train: [66/300][310/312]	eta 0:00:00 lr 0.003532	time 0.4392 (0.4705)	model_time 0.4391 (0.4644)	loss 4.3810 (3.5969)	grad_norm 1.2620 (1.5543/0.7407)	mem 16099MB
[2025-01-18 00:58:46 internimage_t_1k_224] (main.py 519): INFO EPOCH 66 training takes 0:02:26
[2025-01-18 00:58:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_66.pth saving......
[2025-01-18 00:58:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_66.pth saved !!!
[2025-01-18 00:58:55 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.546 (7.546)	Loss 0.9344 (0.9344)	Acc@1 78.833 (78.833)	Acc@5 95.288 (95.288)	Mem 16099MB
[2025-01-18 00:58:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.003)	Loss 1.3076 (1.1275)	Acc@1 70.239 (74.827)	Acc@5 90.674 (92.882)	Mem 16099MB
[2025-01-18 00:58:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:66] * Acc@1 74.796 Acc@5 92.948
[2025-01-18 00:58:58 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.8%
[2025-01-18 00:58:58 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 74.92%
[2025-01-18 00:59:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.394 (8.394)	Loss 1.7781 (1.7781)	Acc@1 65.894 (65.894)	Acc@5 87.329 (87.329)	Mem 16099MB
[2025-01-18 00:59:11 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.118)	Loss 2.2799 (1.9580)	Acc@1 56.396 (62.604)	Acc@5 80.029 (84.719)	Mem 16099MB
[2025-01-18 00:59:11 internimage_t_1k_224] (main.py 575): INFO [Epoch:66] * Acc@1 62.596 Acc@5 84.765
[2025-01-18 00:59:11 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 62.6%
[2025-01-18 00:59:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 00:59:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 00:59:12 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 62.60%
[2025-01-18 00:59:14 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][0/312]	eta 0:10:30 lr 0.003532	time 2.0215 (2.0215)	model_time 0.5262 (0.5262)	loss 3.5821 (3.5821)	grad_norm 1.7116 (1.7116/0.0000)	mem 16099MB
[2025-01-18 00:59:19 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][10/312]	eta 0:03:06 lr 0.003532	time 0.4522 (0.6176)	model_time 0.4521 (0.4813)	loss 3.7014 (3.4915)	grad_norm 1.1459 (1.6332/0.8542)	mem 16099MB
[2025-01-18 00:59:23 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][20/312]	eta 0:02:38 lr 0.003531	time 0.4497 (0.5439)	model_time 0.4492 (0.4724)	loss 3.2153 (3.5568)	grad_norm 0.6428 (1.5164/0.6914)	mem 16099MB
[2025-01-18 00:59:28 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][30/312]	eta 0:02:25 lr 0.003531	time 0.4476 (0.5162)	model_time 0.4474 (0.4677)	loss 3.9587 (3.5040)	grad_norm 1.9936 (1.5511/0.6361)	mem 16099MB
[2025-01-18 00:59:33 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][40/312]	eta 0:02:16 lr 0.003531	time 0.4421 (0.5032)	model_time 0.4420 (0.4665)	loss 3.1302 (3.4484)	grad_norm 1.7577 (1.5697/0.6595)	mem 16099MB
[2025-01-18 00:59:37 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][50/312]	eta 0:02:09 lr 0.003530	time 0.4748 (0.4956)	model_time 0.4744 (0.4659)	loss 4.5054 (3.5177)	grad_norm 2.1121 (1.5666/0.6382)	mem 16099MB
[2025-01-18 00:59:42 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][60/312]	eta 0:02:03 lr 0.003530	time 0.4496 (0.4888)	model_time 0.4494 (0.4640)	loss 2.7110 (3.5166)	grad_norm 1.2888 (1.5813/0.6556)	mem 16099MB
[2025-01-18 00:59:46 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][70/312]	eta 0:01:57 lr 0.003529	time 0.4464 (0.4862)	model_time 0.4460 (0.4648)	loss 3.8941 (3.5037)	grad_norm 0.9749 (1.5515/0.6574)	mem 16099MB
[2025-01-18 00:59:51 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][80/312]	eta 0:01:52 lr 0.003529	time 0.4538 (0.4834)	model_time 0.4537 (0.4646)	loss 4.6805 (3.5123)	grad_norm 1.8885 (1.5528/0.6406)	mem 16099MB
[2025-01-18 00:59:56 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][90/312]	eta 0:01:47 lr 0.003528	time 0.5346 (0.4826)	model_time 0.5342 (0.4658)	loss 3.5556 (3.5151)	grad_norm 2.0652 (1.5444/0.6207)	mem 16099MB
[2025-01-18 01:00:01 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][100/312]	eta 0:01:42 lr 0.003528	time 0.4543 (0.4822)	model_time 0.4539 (0.4671)	loss 3.6431 (3.5348)	grad_norm 1.3012 (1.5667/0.6954)	mem 16099MB
[2025-01-18 01:00:05 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][110/312]	eta 0:01:36 lr 0.003528	time 0.4638 (0.4797)	model_time 0.4634 (0.4659)	loss 2.7508 (3.5320)	grad_norm 1.3352 (1.5236/0.6811)	mem 16099MB
[2025-01-18 01:00:10 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][120/312]	eta 0:01:31 lr 0.003527	time 0.4549 (0.4777)	model_time 0.4544 (0.4650)	loss 3.8878 (3.5206)	grad_norm 4.6602 (1.5912/0.7721)	mem 16099MB
[2025-01-18 01:00:15 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][130/312]	eta 0:01:27 lr 0.003527	time 0.4426 (0.4802)	model_time 0.4422 (0.4684)	loss 2.9212 (3.5181)	grad_norm 1.2827 (1.6112/0.7838)	mem 16099MB
[2025-01-18 01:00:20 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][140/312]	eta 0:01:22 lr 0.003526	time 0.4525 (0.4796)	model_time 0.4521 (0.4686)	loss 3.6750 (3.5318)	grad_norm 1.0631 (1.5815/0.7659)	mem 16099MB
[2025-01-18 01:00:24 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][150/312]	eta 0:01:17 lr 0.003526	time 0.4955 (0.4785)	model_time 0.4954 (0.4682)	loss 4.4977 (3.5304)	grad_norm 0.6654 (1.5453/0.7553)	mem 16099MB
[2025-01-18 01:00:29 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][160/312]	eta 0:01:12 lr 0.003525	time 0.4627 (0.4778)	model_time 0.4625 (0.4682)	loss 4.4605 (3.5378)	grad_norm 1.4494 (1.5365/0.7375)	mem 16099MB
[2025-01-18 01:00:33 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][170/312]	eta 0:01:07 lr 0.003525	time 0.4627 (0.4765)	model_time 0.4625 (0.4674)	loss 3.3571 (3.5274)	grad_norm 2.0381 (1.5401/0.7278)	mem 16099MB
[2025-01-18 01:00:38 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][180/312]	eta 0:01:02 lr 0.003525	time 0.4516 (0.4760)	model_time 0.4512 (0.4673)	loss 3.1786 (3.5219)	grad_norm 3.4322 (1.5640/0.7446)	mem 16099MB
[2025-01-18 01:00:43 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][190/312]	eta 0:00:57 lr 0.003524	time 0.4508 (0.4753)	model_time 0.4504 (0.4671)	loss 3.6865 (3.5235)	grad_norm 1.3549 (1.5771/0.7430)	mem 16099MB
[2025-01-18 01:00:47 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][200/312]	eta 0:00:53 lr 0.003524	time 0.4654 (0.4747)	model_time 0.4649 (0.4669)	loss 3.7014 (3.5249)	grad_norm 1.4837 (1.5690/0.7346)	mem 16099MB
[2025-01-18 01:00:52 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][210/312]	eta 0:00:48 lr 0.003523	time 0.4503 (0.4743)	model_time 0.4499 (0.4668)	loss 4.5390 (3.5221)	grad_norm 2.1144 (1.5899/0.7428)	mem 16099MB
[2025-01-18 01:00:57 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][220/312]	eta 0:00:43 lr 0.003523	time 0.4526 (0.4734)	model_time 0.4522 (0.4663)	loss 4.3083 (3.5112)	grad_norm 1.3142 (1.5808/0.7297)	mem 16099MB
[2025-01-18 01:01:01 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][230/312]	eta 0:00:38 lr 0.003522	time 0.4493 (0.4734)	model_time 0.4488 (0.4666)	loss 4.3124 (3.5110)	grad_norm 1.6990 (1.5650/0.7211)	mem 16099MB
[2025-01-18 01:01:06 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][240/312]	eta 0:00:34 lr 0.003522	time 0.4473 (0.4732)	model_time 0.4469 (0.4666)	loss 3.9660 (3.5145)	grad_norm 0.7830 (1.5632/0.7247)	mem 16099MB
[2025-01-18 01:01:10 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][250/312]	eta 0:00:29 lr 0.003522	time 0.4498 (0.4725)	model_time 0.4494 (0.4661)	loss 2.4414 (3.5250)	grad_norm 1.5335 (1.5527/0.7158)	mem 16099MB
[2025-01-18 01:01:15 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][260/312]	eta 0:00:24 lr 0.003521	time 0.4510 (0.4724)	model_time 0.4505 (0.4663)	loss 3.0289 (3.5226)	grad_norm 0.8919 (1.5552/0.7077)	mem 16099MB
[2025-01-18 01:01:20 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][270/312]	eta 0:00:19 lr 0.003521	time 0.4556 (0.4721)	model_time 0.4552 (0.4662)	loss 2.7186 (3.5185)	grad_norm 0.6273 (1.5576/0.7131)	mem 16099MB
[2025-01-18 01:01:24 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][280/312]	eta 0:00:15 lr 0.003520	time 0.4401 (0.4717)	model_time 0.4397 (0.4660)	loss 4.0243 (3.5165)	grad_norm 0.8593 (1.5732/0.7549)	mem 16099MB
[2025-01-18 01:01:29 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][290/312]	eta 0:00:10 lr 0.003520	time 0.4461 (0.4718)	model_time 0.4457 (0.4663)	loss 4.4569 (3.5308)	grad_norm 1.9278 (1.5696/0.7482)	mem 16099MB
[2025-01-18 01:01:34 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][300/312]	eta 0:00:05 lr 0.003519	time 0.4386 (0.4713)	model_time 0.4386 (0.4659)	loss 3.2759 (3.5361)	grad_norm 1.6879 (1.5589/0.7410)	mem 16099MB
[2025-01-18 01:01:38 internimage_t_1k_224] (main.py 510): INFO Train: [67/300][310/312]	eta 0:00:00 lr 0.003519	time 0.4398 (0.4705)	model_time 0.4397 (0.4653)	loss 2.7517 (3.5379)	grad_norm 1.2173 (1.5571/0.7275)	mem 16099MB
[2025-01-18 01:01:39 internimage_t_1k_224] (main.py 519): INFO EPOCH 67 training takes 0:02:26
[2025-01-18 01:01:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_67.pth saving......
[2025-01-18 01:01:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_67.pth saved !!!
[2025-01-18 01:01:47 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.491 (7.491)	Loss 1.0131 (1.0131)	Acc@1 79.272 (79.272)	Acc@5 95.093 (95.093)	Mem 16099MB
[2025-01-18 01:01:51 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.003)	Loss 1.3641 (1.1572)	Acc@1 69.922 (75.255)	Acc@5 90.381 (92.829)	Mem 16099MB
[2025-01-18 01:01:51 internimage_t_1k_224] (main.py 575): INFO [Epoch:67] * Acc@1 75.186 Acc@5 92.872
[2025-01-18 01:01:51 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.2%
[2025-01-18 01:01:51 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 01:01:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 01:01:52 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.19%
[2025-01-18 01:02:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.480 (7.480)	Loss 1.7162 (1.7162)	Acc@1 66.675 (66.675)	Acc@5 88.037 (88.037)	Mem 16099MB
[2025-01-18 01:02:03 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.007)	Loss 2.2216 (1.9020)	Acc@1 57.227 (63.523)	Acc@5 80.688 (85.334)	Mem 16099MB
[2025-01-18 01:02:03 internimage_t_1k_224] (main.py 575): INFO [Epoch:67] * Acc@1 63.500 Acc@5 85.381
[2025-01-18 01:02:03 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 63.5%
[2025-01-18 01:02:03 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:02:05 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:02:05 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 63.50%
[2025-01-18 01:02:07 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][0/312]	eta 0:12:49 lr 0.003519	time 2.4679 (2.4679)	model_time 0.5099 (0.5099)	loss 3.8734 (3.8734)	grad_norm 0.9090 (0.9090/0.0000)	mem 16099MB
[2025-01-18 01:02:12 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][10/312]	eta 0:03:16 lr 0.003518	time 0.4435 (0.6494)	model_time 0.4433 (0.4711)	loss 3.7972 (3.5939)	grad_norm 1.3259 (1.7864/0.6010)	mem 16099MB
[2025-01-18 01:02:17 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][20/312]	eta 0:02:43 lr 0.003518	time 0.4554 (0.5611)	model_time 0.4550 (0.4675)	loss 3.4375 (3.6007)	grad_norm 3.2077 (1.8701/0.6909)	mem 16099MB
[2025-01-18 01:02:21 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][30/312]	eta 0:02:28 lr 0.003518	time 0.4446 (0.5275)	model_time 0.4443 (0.4640)	loss 3.8184 (3.6339)	grad_norm 1.6132 (1.8719/0.6682)	mem 16099MB
[2025-01-18 01:02:26 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][40/312]	eta 0:02:18 lr 0.003517	time 0.4492 (0.5107)	model_time 0.4488 (0.4626)	loss 3.9529 (3.6081)	grad_norm 1.1631 (1.7536/0.6474)	mem 16099MB
[2025-01-18 01:02:30 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][50/312]	eta 0:02:11 lr 0.003517	time 0.4522 (0.5028)	model_time 0.4518 (0.4640)	loss 3.6676 (3.6007)	grad_norm 1.1230 (1.6673/0.6159)	mem 16099MB
[2025-01-18 01:02:35 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][60/312]	eta 0:02:04 lr 0.003516	time 0.4548 (0.4947)	model_time 0.4544 (0.4622)	loss 3.0072 (3.6008)	grad_norm 1.7121 (1.6324/0.6003)	mem 16099MB
[2025-01-18 01:02:40 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][70/312]	eta 0:01:58 lr 0.003516	time 0.4477 (0.4912)	model_time 0.4473 (0.4633)	loss 3.9230 (3.6174)	grad_norm 0.8929 (1.7160/0.7066)	mem 16099MB
[2025-01-18 01:02:44 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][80/312]	eta 0:01:53 lr 0.003515	time 0.4484 (0.4879)	model_time 0.4482 (0.4633)	loss 3.4237 (3.5779)	grad_norm 2.5315 (1.6720/0.6919)	mem 16099MB
[2025-01-18 01:02:49 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][90/312]	eta 0:01:47 lr 0.003515	time 0.4477 (0.4846)	model_time 0.4473 (0.4627)	loss 2.4457 (3.5554)	grad_norm 1.1188 (1.6677/0.6977)	mem 16099MB
[2025-01-18 01:02:54 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][100/312]	eta 0:01:42 lr 0.003514	time 0.4636 (0.4840)	model_time 0.4632 (0.4642)	loss 3.2382 (3.4972)	grad_norm 1.5514 (1.6451/0.6896)	mem 16099MB
[2025-01-18 01:02:58 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][110/312]	eta 0:01:37 lr 0.003514	time 0.4379 (0.4819)	model_time 0.4377 (0.4639)	loss 3.6308 (3.5112)	grad_norm 1.1114 (1.6139/0.6813)	mem 16099MB
[2025-01-18 01:03:03 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][120/312]	eta 0:01:32 lr 0.003514	time 0.4495 (0.4825)	model_time 0.4494 (0.4659)	loss 3.8223 (3.5201)	grad_norm 1.0397 (1.5811/0.6698)	mem 16099MB
[2025-01-18 01:03:08 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][130/312]	eta 0:01:27 lr 0.003513	time 0.4772 (0.4809)	model_time 0.4767 (0.4656)	loss 2.9929 (3.5320)	grad_norm 1.0598 (1.6309/0.7059)	mem 16099MB
[2025-01-18 01:03:12 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][140/312]	eta 0:01:22 lr 0.003513	time 0.4514 (0.4801)	model_time 0.4509 (0.4658)	loss 3.3455 (3.5455)	grad_norm 1.0186 (1.6298/0.6987)	mem 16099MB
[2025-01-18 01:03:17 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][150/312]	eta 0:01:17 lr 0.003512	time 0.4544 (0.4794)	model_time 0.4540 (0.4661)	loss 3.0755 (3.5594)	grad_norm 1.3671 (1.6273/0.6911)	mem 16099MB
[2025-01-18 01:03:22 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][160/312]	eta 0:01:12 lr 0.003512	time 0.4469 (0.4786)	model_time 0.4464 (0.4661)	loss 3.7216 (3.5567)	grad_norm 0.6654 (1.6180/0.6835)	mem 16099MB
[2025-01-18 01:03:26 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][170/312]	eta 0:01:07 lr 0.003511	time 0.4493 (0.4773)	model_time 0.4492 (0.4655)	loss 4.0976 (3.5421)	grad_norm 1.4462 (1.6010/0.6750)	mem 16099MB
[2025-01-18 01:03:31 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][180/312]	eta 0:01:02 lr 0.003511	time 0.5001 (0.4772)	model_time 0.4997 (0.4660)	loss 3.2565 (3.5445)	grad_norm 1.1354 (1.5870/0.6717)	mem 16099MB
[2025-01-18 01:03:36 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][190/312]	eta 0:00:58 lr 0.003511	time 0.4535 (0.4762)	model_time 0.4533 (0.4656)	loss 3.4152 (3.5386)	grad_norm 1.4712 (1.6054/0.6864)	mem 16099MB
[2025-01-18 01:03:40 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][200/312]	eta 0:00:53 lr 0.003510	time 0.4606 (0.4751)	model_time 0.4605 (0.4650)	loss 2.5195 (3.5364)	grad_norm 1.6999 (1.5934/0.6748)	mem 16099MB
[2025-01-18 01:03:45 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][210/312]	eta 0:00:48 lr 0.003510	time 0.4499 (0.4740)	model_time 0.4498 (0.4643)	loss 3.7590 (3.5359)	grad_norm 1.1393 (1.5879/0.6662)	mem 16099MB
[2025-01-18 01:03:50 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][220/312]	eta 0:00:43 lr 0.003509	time 0.4400 (0.4744)	model_time 0.4398 (0.4651)	loss 3.1914 (3.5320)	grad_norm 1.4902 (1.5724/0.6578)	mem 16099MB
[2025-01-18 01:03:54 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][230/312]	eta 0:00:38 lr 0.003509	time 0.4500 (0.4735)	model_time 0.4496 (0.4646)	loss 3.5682 (3.5268)	grad_norm 0.7194 (1.5539/0.6543)	mem 16099MB
[2025-01-18 01:03:59 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][240/312]	eta 0:00:34 lr 0.003508	time 0.4503 (0.4729)	model_time 0.4499 (0.4644)	loss 3.3958 (3.5220)	grad_norm 1.1434 (1.5360/0.6483)	mem 16099MB
[2025-01-18 01:04:03 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][250/312]	eta 0:00:29 lr 0.003508	time 0.4614 (0.4721)	model_time 0.4613 (0.4640)	loss 3.7143 (3.5137)	grad_norm 1.5531 (1.5271/0.6388)	mem 16099MB
[2025-01-18 01:04:08 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][260/312]	eta 0:00:24 lr 0.003508	time 0.4381 (0.4719)	model_time 0.4380 (0.4641)	loss 3.6942 (3.5206)	grad_norm 1.9524 (1.5424/0.6476)	mem 16099MB
[2025-01-18 01:04:13 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][270/312]	eta 0:00:19 lr 0.003507	time 0.4794 (0.4717)	model_time 0.4789 (0.4641)	loss 3.5076 (3.5238)	grad_norm 1.4361 (1.5336/0.6409)	mem 16099MB
[2025-01-18 01:04:17 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][280/312]	eta 0:00:15 lr 0.003507	time 0.4500 (0.4713)	model_time 0.4499 (0.4639)	loss 2.7985 (3.5166)	grad_norm 2.5427 (1.5294/0.6374)	mem 16099MB
[2025-01-18 01:04:22 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][290/312]	eta 0:00:10 lr 0.003506	time 0.4559 (0.4711)	model_time 0.4555 (0.4640)	loss 3.1479 (3.5131)	grad_norm 1.8980 (1.5729/0.6942)	mem 16099MB
[2025-01-18 01:04:27 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][300/312]	eta 0:00:05 lr 0.003506	time 0.4380 (0.4711)	model_time 0.4379 (0.4643)	loss 2.5019 (3.5081)	grad_norm 1.1738 (1.5674/0.6855)	mem 16099MB
[2025-01-18 01:04:31 internimage_t_1k_224] (main.py 510): INFO Train: [68/300][310/312]	eta 0:00:00 lr 0.003505	time 0.4390 (0.4707)	model_time 0.4389 (0.4640)	loss 3.7265 (3.5156)	grad_norm 1.9683 (1.5518/0.6806)	mem 16099MB
[2025-01-18 01:04:32 internimage_t_1k_224] (main.py 519): INFO EPOCH 68 training takes 0:02:26
[2025-01-18 01:04:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_68.pth saving......
[2025-01-18 01:04:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_68.pth saved !!!
[2025-01-18 01:04:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.324 (7.324)	Loss 0.9583 (0.9583)	Acc@1 78.662 (78.662)	Acc@5 95.020 (95.020)	Mem 16099MB
[2025-01-18 01:04:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.979)	Loss 1.4198 (1.1660)	Acc@1 68.750 (74.838)	Acc@5 89.868 (92.640)	Mem 16099MB
[2025-01-18 01:04:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:68] * Acc@1 74.860 Acc@5 92.726
[2025-01-18 01:04:44 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.9%
[2025-01-18 01:04:44 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.19%
[2025-01-18 01:04:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.424 (8.424)	Loss 1.6587 (1.6587)	Acc@1 67.603 (67.603)	Acc@5 88.525 (88.525)	Mem 16099MB
[2025-01-18 01:04:56 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.127)	Loss 2.1684 (1.8500)	Acc@1 57.959 (64.355)	Acc@5 81.177 (85.835)	Mem 16099MB
[2025-01-18 01:04:56 internimage_t_1k_224] (main.py 575): INFO [Epoch:68] * Acc@1 64.311 Acc@5 85.897
[2025-01-18 01:04:56 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 64.3%
[2025-01-18 01:04:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:04:58 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:04:58 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 64.31%
[2025-01-18 01:05:00 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][0/312]	eta 0:12:01 lr 0.003505	time 2.3120 (2.3120)	model_time 0.4707 (0.4707)	loss 2.9082 (2.9082)	grad_norm 1.4431 (1.4431/0.0000)	mem 16099MB
[2025-01-18 01:05:05 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][10/312]	eta 0:03:12 lr 0.003505	time 0.4518 (0.6381)	model_time 0.4516 (0.4705)	loss 2.8410 (3.1855)	grad_norm 1.0671 (1.2221/0.3500)	mem 16099MB
[2025-01-18 01:05:09 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][20/312]	eta 0:02:40 lr 0.003504	time 0.4558 (0.5500)	model_time 0.4557 (0.4621)	loss 3.4711 (3.2844)	grad_norm 1.0422 (1.3057/0.3941)	mem 16099MB
[2025-01-18 01:05:14 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][30/312]	eta 0:02:28 lr 0.003504	time 0.4707 (0.5257)	model_time 0.4702 (0.4661)	loss 2.8397 (3.2484)	grad_norm 4.5533 (1.5075/0.7425)	mem 16099MB
[2025-01-18 01:05:19 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][40/312]	eta 0:02:18 lr 0.003503	time 0.4606 (0.5095)	model_time 0.4602 (0.4643)	loss 4.2818 (3.3712)	grad_norm 2.6556 (1.5989/0.8283)	mem 16099MB
[2025-01-18 01:05:23 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][50/312]	eta 0:02:11 lr 0.003503	time 0.4520 (0.5014)	model_time 0.4518 (0.4649)	loss 3.7216 (3.4118)	grad_norm 2.0091 (1.6109/0.8516)	mem 16099MB
[2025-01-18 01:05:28 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][60/312]	eta 0:02:04 lr 0.003503	time 0.4596 (0.4935)	model_time 0.4592 (0.4630)	loss 3.0538 (3.4300)	grad_norm 0.7415 (1.5895/0.8192)	mem 16099MB
[2025-01-18 01:05:32 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][70/312]	eta 0:01:58 lr 0.003502	time 0.6053 (0.4897)	model_time 0.6049 (0.4634)	loss 3.7409 (3.3808)	grad_norm 2.4938 (1.5697/0.7808)	mem 16099MB
[2025-01-18 01:05:37 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][80/312]	eta 0:01:53 lr 0.003502	time 0.4624 (0.4879)	model_time 0.4620 (0.4648)	loss 2.5516 (3.3805)	grad_norm 1.1818 (1.6336/0.8043)	mem 16099MB
[2025-01-18 01:05:42 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][90/312]	eta 0:01:48 lr 0.003501	time 0.4578 (0.4884)	model_time 0.4576 (0.4679)	loss 4.2531 (3.3787)	grad_norm 1.1173 (1.5970/0.7806)	mem 16099MB
[2025-01-18 01:05:47 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][100/312]	eta 0:01:43 lr 0.003501	time 0.4680 (0.4859)	model_time 0.4678 (0.4673)	loss 3.7888 (3.4124)	grad_norm 1.7008 (1.5876/0.7633)	mem 16099MB
[2025-01-18 01:05:51 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][110/312]	eta 0:01:37 lr 0.003500	time 0.4678 (0.4843)	model_time 0.4676 (0.4674)	loss 3.3861 (3.4356)	grad_norm 2.5791 (1.5738/0.7475)	mem 16099MB
[2025-01-18 01:05:56 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][120/312]	eta 0:01:32 lr 0.003500	time 0.4620 (0.4840)	model_time 0.4615 (0.4684)	loss 3.9549 (3.4554)	grad_norm 2.2703 (1.5685/0.7285)	mem 16099MB
[2025-01-18 01:06:01 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][130/312]	eta 0:01:27 lr 0.003499	time 0.4450 (0.4827)	model_time 0.4446 (0.4683)	loss 2.9952 (3.4490)	grad_norm 1.3447 (1.5350/0.7201)	mem 16099MB
[2025-01-18 01:06:06 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][140/312]	eta 0:01:22 lr 0.003499	time 0.4618 (0.4822)	model_time 0.4616 (0.4688)	loss 3.3291 (3.4547)	grad_norm 1.1376 (1.5270/0.7081)	mem 16099MB
[2025-01-18 01:06:10 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][150/312]	eta 0:01:17 lr 0.003499	time 0.4430 (0.4814)	model_time 0.4425 (0.4688)	loss 4.4029 (3.4695)	grad_norm 3.1824 (1.5396/0.7064)	mem 16099MB
[2025-01-18 01:06:15 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][160/312]	eta 0:01:13 lr 0.003498	time 0.4497 (0.4804)	model_time 0.4495 (0.4686)	loss 3.2142 (3.4678)	grad_norm 2.0697 (1.5401/0.6961)	mem 16099MB
[2025-01-18 01:06:20 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][170/312]	eta 0:01:08 lr 0.003498	time 0.4418 (0.4803)	model_time 0.4414 (0.4691)	loss 3.1865 (3.4788)	grad_norm 2.2828 (1.5419/0.6921)	mem 16099MB
[2025-01-18 01:06:24 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][180/312]	eta 0:01:03 lr 0.003497	time 0.4564 (0.4792)	model_time 0.4562 (0.4687)	loss 4.0573 (3.4844)	grad_norm 1.7405 (1.5483/0.6791)	mem 16099MB
[2025-01-18 01:06:29 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][190/312]	eta 0:00:58 lr 0.003497	time 0.4608 (0.4781)	model_time 0.4603 (0.4681)	loss 3.8723 (3.5019)	grad_norm 2.4806 (1.5647/0.6810)	mem 16099MB
[2025-01-18 01:06:34 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][200/312]	eta 0:00:53 lr 0.003496	time 0.4537 (0.4774)	model_time 0.4533 (0.4679)	loss 2.8090 (3.5065)	grad_norm 0.9603 (1.5456/0.6710)	mem 16099MB
[2025-01-18 01:06:38 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][210/312]	eta 0:00:48 lr 0.003496	time 0.4613 (0.4763)	model_time 0.4609 (0.4672)	loss 3.5614 (3.5119)	grad_norm 1.9856 (1.5872/0.7881)	mem 16099MB
[2025-01-18 01:06:43 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][220/312]	eta 0:00:43 lr 0.003496	time 0.4609 (0.4752)	model_time 0.4608 (0.4665)	loss 2.8723 (3.5098)	grad_norm 1.8066 (1.5788/0.7742)	mem 16099MB
[2025-01-18 01:06:47 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][230/312]	eta 0:00:38 lr 0.003495	time 0.4586 (0.4742)	model_time 0.4584 (0.4659)	loss 3.9223 (3.5160)	grad_norm 0.9441 (1.5809/0.7736)	mem 16099MB
[2025-01-18 01:06:52 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][240/312]	eta 0:00:34 lr 0.003495	time 0.4517 (0.4732)	model_time 0.4516 (0.4652)	loss 2.9353 (3.5259)	grad_norm 1.4248 (1.5857/0.7978)	mem 16099MB
[2025-01-18 01:06:56 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][250/312]	eta 0:00:29 lr 0.003494	time 0.4554 (0.4730)	model_time 0.4550 (0.4652)	loss 3.7868 (3.5252)	grad_norm 1.8460 (1.5752/0.7932)	mem 16099MB
[2025-01-18 01:07:01 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][260/312]	eta 0:00:24 lr 0.003494	time 0.4502 (0.4726)	model_time 0.4501 (0.4652)	loss 2.9599 (3.5291)	grad_norm 1.1367 (1.5723/0.7820)	mem 16099MB
[2025-01-18 01:07:06 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][270/312]	eta 0:00:19 lr 0.003493	time 0.4585 (0.4732)	model_time 0.4580 (0.4660)	loss 3.7766 (3.5188)	grad_norm 1.5970 (1.5645/0.7728)	mem 16099MB
[2025-01-18 01:07:11 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][280/312]	eta 0:00:15 lr 0.003493	time 0.4540 (0.4736)	model_time 0.4537 (0.4666)	loss 4.1389 (3.5273)	grad_norm 1.0088 (1.5609/0.7688)	mem 16099MB
[2025-01-18 01:07:15 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][290/312]	eta 0:00:10 lr 0.003492	time 0.4539 (0.4732)	model_time 0.4538 (0.4665)	loss 4.1608 (3.5383)	grad_norm 0.9930 (1.5694/0.7675)	mem 16099MB
[2025-01-18 01:07:20 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][300/312]	eta 0:00:05 lr 0.003492	time 0.4440 (0.4728)	model_time 0.4439 (0.4663)	loss 4.6805 (3.5468)	grad_norm 1.9502 (1.5644/0.7595)	mem 16099MB
[2025-01-18 01:07:25 internimage_t_1k_224] (main.py 510): INFO Train: [69/300][310/312]	eta 0:00:00 lr 0.003492	time 0.5446 (0.4722)	model_time 0.5445 (0.4660)	loss 3.9704 (3.5407)	grad_norm 1.0207 (1.5661/0.7596)	mem 16099MB
[2025-01-18 01:07:25 internimage_t_1k_224] (main.py 519): INFO EPOCH 69 training takes 0:02:27
[2025-01-18 01:07:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_69.pth saving......
[2025-01-18 01:07:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_69.pth saved !!!
[2025-01-18 01:07:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.963 (7.963)	Loss 0.9446 (0.9446)	Acc@1 78.784 (78.784)	Acc@5 95.215 (95.215)	Mem 16099MB
[2025-01-18 01:07:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.067)	Loss 1.3756 (1.1399)	Acc@1 68.506 (75.040)	Acc@5 90.161 (92.991)	Mem 16099MB
[2025-01-18 01:07:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:69] * Acc@1 74.936 Acc@5 93.010
[2025-01-18 01:07:38 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.9%
[2025-01-18 01:07:38 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.19%
[2025-01-18 01:07:47 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.473 (8.473)	Loss 1.6039 (1.6039)	Acc@1 68.726 (68.726)	Acc@5 89.160 (89.160)	Mem 16099MB
[2025-01-18 01:07:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.130)	Loss 2.1171 (1.8006)	Acc@1 58.911 (65.186)	Acc@5 81.934 (86.441)	Mem 16099MB
[2025-01-18 01:07:51 internimage_t_1k_224] (main.py 575): INFO [Epoch:69] * Acc@1 65.143 Acc@5 86.526
[2025-01-18 01:07:51 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 65.1%
[2025-01-18 01:07:51 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:07:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:07:52 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 65.14%
[2025-01-18 01:07:55 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][0/312]	eta 0:14:22 lr 0.003491	time 2.7657 (2.7657)	model_time 0.5727 (0.5727)	loss 4.0858 (4.0858)	grad_norm 2.5221 (2.5221/0.0000)	mem 16099MB
[2025-01-18 01:07:59 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][10/312]	eta 0:03:21 lr 0.003491	time 0.4559 (0.6679)	model_time 0.4554 (0.4682)	loss 4.0707 (3.4837)	grad_norm 4.4486 (2.3169/1.1039)	mem 16099MB
[2025-01-18 01:08:04 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][20/312]	eta 0:02:46 lr 0.003491	time 0.5318 (0.5696)	model_time 0.5314 (0.4648)	loss 3.3150 (3.4825)	grad_norm 0.9940 (1.9477/1.0482)	mem 16099MB
[2025-01-18 01:08:09 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][30/312]	eta 0:02:30 lr 0.003490	time 0.4507 (0.5345)	model_time 0.4505 (0.4634)	loss 4.4644 (3.6054)	grad_norm 1.1451 (1.6922/0.9496)	mem 16099MB
[2025-01-18 01:08:13 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][40/312]	eta 0:02:20 lr 0.003490	time 0.4556 (0.5170)	model_time 0.4551 (0.4632)	loss 2.9743 (3.5949)	grad_norm 1.0166 (1.6186/0.8814)	mem 16099MB
[2025-01-18 01:08:18 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][50/312]	eta 0:02:12 lr 0.003489	time 0.4451 (0.5045)	model_time 0.4447 (0.4611)	loss 4.0056 (3.5702)	grad_norm 1.0858 (1.5245/0.8195)	mem 16099MB
[2025-01-18 01:08:22 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][60/312]	eta 0:02:05 lr 0.003489	time 0.4575 (0.4984)	model_time 0.4570 (0.4621)	loss 4.1332 (3.6200)	grad_norm 1.1203 (1.6004/0.9117)	mem 16099MB
[2025-01-18 01:08:27 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][70/312]	eta 0:01:59 lr 0.003488	time 0.4565 (0.4921)	model_time 0.4563 (0.4609)	loss 2.8429 (3.5495)	grad_norm 1.2577 (1.5824/0.9021)	mem 16099MB
[2025-01-18 01:08:32 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][80/312]	eta 0:01:53 lr 0.003488	time 0.4531 (0.4890)	model_time 0.4526 (0.4616)	loss 3.0118 (3.5759)	grad_norm 1.1115 (1.5545/0.8626)	mem 16099MB
[2025-01-18 01:08:36 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][90/312]	eta 0:01:48 lr 0.003487	time 0.4420 (0.4867)	model_time 0.4416 (0.4622)	loss 2.8351 (3.5882)	grad_norm 1.7875 (1.5296/0.8225)	mem 16099MB
[2025-01-18 01:08:41 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][100/312]	eta 0:01:43 lr 0.003487	time 0.4420 (0.4866)	model_time 0.4418 (0.4644)	loss 4.3612 (3.5875)	grad_norm 2.0578 (1.5801/0.8122)	mem 16099MB
[2025-01-18 01:08:46 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][110/312]	eta 0:01:38 lr 0.003487	time 0.4496 (0.4855)	model_time 0.4492 (0.4653)	loss 3.8450 (3.5680)	grad_norm 1.7378 (1.6048/0.8072)	mem 16099MB
[2025-01-18 01:08:50 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][120/312]	eta 0:01:32 lr 0.003486	time 0.4486 (0.4831)	model_time 0.4484 (0.4645)	loss 4.0257 (3.5679)	grad_norm 0.8078 (1.5568/0.7922)	mem 16099MB
[2025-01-18 01:08:55 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][130/312]	eta 0:01:27 lr 0.003486	time 0.4513 (0.4809)	model_time 0.4508 (0.4637)	loss 3.1129 (3.5515)	grad_norm 1.1165 (1.5323/0.7753)	mem 16099MB
[2025-01-18 01:09:00 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][140/312]	eta 0:01:22 lr 0.003485	time 0.4505 (0.4793)	model_time 0.4501 (0.4633)	loss 2.5809 (3.5659)	grad_norm 1.2516 (1.5077/0.7553)	mem 16099MB
[2025-01-18 01:09:05 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][150/312]	eta 0:01:18 lr 0.003485	time 0.5383 (0.4815)	model_time 0.5381 (0.4666)	loss 2.7246 (3.5701)	grad_norm 0.8602 (1.5075/0.7460)	mem 16099MB
[2025-01-18 01:09:09 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][160/312]	eta 0:01:13 lr 0.003484	time 0.4470 (0.4807)	model_time 0.4466 (0.4666)	loss 3.1571 (3.5683)	grad_norm 1.5540 (1.5491/0.7986)	mem 16099MB
[2025-01-18 01:09:14 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][170/312]	eta 0:01:08 lr 0.003484	time 0.4571 (0.4807)	model_time 0.4567 (0.4675)	loss 3.2538 (3.5882)	grad_norm 1.1796 (1.5363/0.7844)	mem 16099MB
[2025-01-18 01:09:19 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][180/312]	eta 0:01:03 lr 0.003483	time 0.4628 (0.4793)	model_time 0.4626 (0.4667)	loss 3.4083 (3.5840)	grad_norm 1.5638 (1.5469/0.7751)	mem 16099MB
[2025-01-18 01:09:23 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][190/312]	eta 0:00:58 lr 0.003483	time 0.4396 (0.4783)	model_time 0.4392 (0.4664)	loss 2.4018 (3.5719)	grad_norm 1.3224 (1.5662/0.7906)	mem 16099MB
[2025-01-18 01:09:28 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][200/312]	eta 0:00:53 lr 0.003483	time 0.4421 (0.4780)	model_time 0.4416 (0.4667)	loss 4.2253 (3.5600)	grad_norm 2.1005 (1.5882/0.7881)	mem 16099MB
[2025-01-18 01:09:33 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][210/312]	eta 0:00:48 lr 0.003482	time 0.4361 (0.4770)	model_time 0.4356 (0.4662)	loss 3.0417 (3.5651)	grad_norm 1.6336 (1.5864/0.7710)	mem 16099MB
[2025-01-18 01:09:37 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][220/312]	eta 0:00:43 lr 0.003482	time 0.4505 (0.4767)	model_time 0.4503 (0.4663)	loss 2.7855 (3.5647)	grad_norm 0.6559 (1.5742/0.7615)	mem 16099MB
[2025-01-18 01:09:42 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][230/312]	eta 0:00:39 lr 0.003481	time 0.4507 (0.4758)	model_time 0.4506 (0.4658)	loss 3.9271 (3.5744)	grad_norm 0.6831 (1.5808/0.7667)	mem 16099MB
[2025-01-18 01:09:47 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][240/312]	eta 0:00:34 lr 0.003481	time 0.4403 (0.4759)	model_time 0.4398 (0.4664)	loss 3.9510 (3.5681)	grad_norm 1.5720 (1.5708/0.7575)	mem 16099MB
[2025-01-18 01:09:51 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][250/312]	eta 0:00:29 lr 0.003480	time 0.4510 (0.4753)	model_time 0.4506 (0.4661)	loss 4.4953 (3.5649)	grad_norm 0.9566 (1.5580/0.7479)	mem 16099MB
[2025-01-18 01:09:56 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][260/312]	eta 0:00:24 lr 0.003480	time 0.4486 (0.4745)	model_time 0.4482 (0.4657)	loss 3.5599 (3.5597)	grad_norm 0.8523 (1.5430/0.7395)	mem 16099MB
[2025-01-18 01:10:00 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][270/312]	eta 0:00:19 lr 0.003479	time 0.4496 (0.4739)	model_time 0.4492 (0.4654)	loss 3.6725 (3.5606)	grad_norm 0.9503 (1.5492/0.7407)	mem 16099MB
[2025-01-18 01:10:05 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][280/312]	eta 0:00:15 lr 0.003479	time 0.4808 (0.4735)	model_time 0.4804 (0.4653)	loss 2.6305 (3.5491)	grad_norm 1.9612 (1.5498/0.7376)	mem 16099MB
[2025-01-18 01:10:10 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][290/312]	eta 0:00:10 lr 0.003478	time 0.4506 (0.4732)	model_time 0.4502 (0.4653)	loss 2.8357 (3.5435)	grad_norm 1.3912 (1.5410/0.7312)	mem 16099MB
[2025-01-18 01:10:14 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][300/312]	eta 0:00:05 lr 0.003478	time 0.4390 (0.4724)	model_time 0.4389 (0.4647)	loss 3.7292 (3.5419)	grad_norm 2.1501 (1.5475/0.7219)	mem 16099MB
[2025-01-18 01:10:19 internimage_t_1k_224] (main.py 510): INFO Train: [70/300][310/312]	eta 0:00:00 lr 0.003478	time 0.4422 (0.4714)	model_time 0.4421 (0.4639)	loss 4.1296 (3.5449)	grad_norm 2.7277 (1.5535/0.7123)	mem 16099MB
[2025-01-18 01:10:19 internimage_t_1k_224] (main.py 519): INFO EPOCH 70 training takes 0:02:27
[2025-01-18 01:10:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_70.pth saving......
[2025-01-18 01:10:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_70.pth saved !!!
[2025-01-18 01:10:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.161 (7.161)	Loss 0.9790 (0.9790)	Acc@1 79.126 (79.126)	Acc@5 95.044 (95.044)	Mem 16099MB
[2025-01-18 01:10:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.977)	Loss 1.4214 (1.1658)	Acc@1 67.773 (74.905)	Acc@5 89.917 (92.876)	Mem 16099MB
[2025-01-18 01:10:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:70] * Acc@1 74.912 Acc@5 92.946
[2025-01-18 01:10:31 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 74.9%
[2025-01-18 01:10:31 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.19%
[2025-01-18 01:10:39 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.049 (8.049)	Loss 1.5548 (1.5548)	Acc@1 69.458 (69.458)	Acc@5 89.819 (89.819)	Mem 16099MB
[2025-01-18 01:10:43 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.086)	Loss 2.0691 (1.7552)	Acc@1 59.595 (65.916)	Acc@5 82.642 (86.981)	Mem 16099MB
[2025-01-18 01:10:43 internimage_t_1k_224] (main.py 575): INFO [Epoch:70] * Acc@1 65.873 Acc@5 87.062
[2025-01-18 01:10:43 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 65.9%
[2025-01-18 01:10:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:10:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:10:45 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 65.87%
[2025-01-18 01:10:47 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][0/312]	eta 0:14:19 lr 0.003477	time 2.7537 (2.7537)	model_time 0.4795 (0.4795)	loss 2.8240 (2.8240)	grad_norm 5.4877 (5.4877/0.0000)	mem 16099MB
[2025-01-18 01:10:52 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][10/312]	eta 0:03:28 lr 0.003477	time 0.5697 (0.6915)	model_time 0.5696 (0.4844)	loss 4.1389 (3.3010)	grad_norm 1.6206 (2.0542/1.1547)	mem 16099MB
[2025-01-18 01:10:57 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][20/312]	eta 0:02:49 lr 0.003477	time 0.4802 (0.5801)	model_time 0.4800 (0.4714)	loss 3.6398 (3.4490)	grad_norm 0.7861 (1.6824/0.9469)	mem 16099MB
[2025-01-18 01:11:01 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][30/312]	eta 0:02:33 lr 0.003476	time 0.4590 (0.5426)	model_time 0.4586 (0.4689)	loss 3.8911 (3.5612)	grad_norm 1.0727 (1.5157/0.8350)	mem 16099MB
[2025-01-18 01:11:06 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][40/312]	eta 0:02:23 lr 0.003476	time 0.4596 (0.5274)	model_time 0.4594 (0.4716)	loss 3.1543 (3.5301)	grad_norm 1.8087 (1.5450/0.7850)	mem 16099MB
[2025-01-18 01:11:11 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][50/312]	eta 0:02:14 lr 0.003475	time 0.4516 (0.5143)	model_time 0.4514 (0.4694)	loss 3.6703 (3.5179)	grad_norm 2.8260 (1.5797/0.7510)	mem 16099MB
[2025-01-18 01:11:15 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][60/312]	eta 0:02:07 lr 0.003475	time 0.4396 (0.5047)	model_time 0.4394 (0.4671)	loss 4.0420 (3.5244)	grad_norm 1.2730 (1.5764/0.7332)	mem 16099MB
[2025-01-18 01:11:20 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][70/312]	eta 0:02:00 lr 0.003474	time 0.4455 (0.4986)	model_time 0.4451 (0.4660)	loss 4.3797 (3.5544)	grad_norm 1.2609 (1.5244/0.6969)	mem 16099MB
[2025-01-18 01:11:25 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][80/312]	eta 0:01:54 lr 0.003474	time 0.4640 (0.4944)	model_time 0.4639 (0.4658)	loss 4.2794 (3.5483)	grad_norm 1.6162 (1.5423/0.6770)	mem 16099MB
[2025-01-18 01:11:29 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][90/312]	eta 0:01:49 lr 0.003473	time 0.4454 (0.4925)	model_time 0.4453 (0.4671)	loss 3.6852 (3.5410)	grad_norm 1.3594 (1.5053/0.6534)	mem 16099MB
[2025-01-18 01:11:34 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][100/312]	eta 0:01:43 lr 0.003473	time 0.4511 (0.4886)	model_time 0.4509 (0.4656)	loss 3.8559 (3.5614)	grad_norm 1.5532 (1.4932/0.6358)	mem 16099MB
[2025-01-18 01:11:39 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][110/312]	eta 0:01:38 lr 0.003473	time 0.4406 (0.4877)	model_time 0.4402 (0.4667)	loss 4.0581 (3.5923)	grad_norm 2.4109 (1.4886/0.6226)	mem 16099MB
[2025-01-18 01:11:43 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][120/312]	eta 0:01:33 lr 0.003472	time 0.4675 (0.4857)	model_time 0.4674 (0.4664)	loss 3.4621 (3.6107)	grad_norm 0.7936 (1.4830/0.6346)	mem 16099MB
[2025-01-18 01:11:48 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][130/312]	eta 0:01:28 lr 0.003472	time 0.4444 (0.4854)	model_time 0.4442 (0.4676)	loss 3.9905 (3.6288)	grad_norm 1.8844 (1.4893/0.6270)	mem 16099MB
[2025-01-18 01:11:53 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][140/312]	eta 0:01:23 lr 0.003471	time 0.4449 (0.4838)	model_time 0.4445 (0.4672)	loss 3.9536 (3.6112)	grad_norm 2.0157 (1.4960/0.6367)	mem 16099MB
[2025-01-18 01:11:58 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][150/312]	eta 0:01:18 lr 0.003471	time 0.4475 (0.4830)	model_time 0.4471 (0.4674)	loss 4.6504 (3.5935)	grad_norm 1.1122 (1.5149/0.6711)	mem 16099MB
[2025-01-18 01:12:02 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][160/312]	eta 0:01:13 lr 0.003470	time 0.4647 (0.4822)	model_time 0.4643 (0.4677)	loss 3.8444 (3.5971)	grad_norm 1.9434 (1.5540/0.6875)	mem 16099MB
[2025-01-18 01:12:07 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][170/312]	eta 0:01:08 lr 0.003470	time 0.4670 (0.4817)	model_time 0.4666 (0.4679)	loss 4.3358 (3.6041)	grad_norm 0.7838 (1.5386/0.6747)	mem 16099MB
[2025-01-18 01:12:12 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][180/312]	eta 0:01:03 lr 0.003469	time 0.4467 (0.4818)	model_time 0.4463 (0.4688)	loss 4.2002 (3.6242)	grad_norm 1.4484 (1.5446/0.6832)	mem 16099MB
[2025-01-18 01:12:16 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][190/312]	eta 0:00:58 lr 0.003469	time 0.4619 (0.4805)	model_time 0.4617 (0.4681)	loss 3.3664 (3.6301)	grad_norm 2.0243 (1.5340/0.6708)	mem 16099MB
[2025-01-18 01:12:21 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][200/312]	eta 0:00:53 lr 0.003468	time 0.4663 (0.4797)	model_time 0.4661 (0.4680)	loss 3.0352 (3.6273)	grad_norm 1.0629 (1.5267/0.6598)	mem 16099MB
[2025-01-18 01:12:26 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][210/312]	eta 0:00:48 lr 0.003468	time 0.4400 (0.4789)	model_time 0.4398 (0.4677)	loss 3.8312 (3.6321)	grad_norm 1.0201 (1.5318/0.6565)	mem 16099MB
[2025-01-18 01:12:30 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][220/312]	eta 0:00:43 lr 0.003468	time 0.4770 (0.4781)	model_time 0.4766 (0.4674)	loss 4.2589 (3.6238)	grad_norm 1.5274 (1.5348/0.6535)	mem 16099MB
[2025-01-18 01:12:35 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][230/312]	eta 0:00:39 lr 0.003467	time 0.4476 (0.4773)	model_time 0.4475 (0.4671)	loss 3.6212 (3.6249)	grad_norm 1.1090 (1.5332/0.6472)	mem 16099MB
[2025-01-18 01:12:39 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][240/312]	eta 0:00:34 lr 0.003467	time 0.4462 (0.4762)	model_time 0.4458 (0.4664)	loss 3.3928 (3.6241)	grad_norm 1.7157 (1.5236/0.6397)	mem 16099MB
[2025-01-18 01:12:44 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][250/312]	eta 0:00:29 lr 0.003466	time 0.4426 (0.4767)	model_time 0.4424 (0.4672)	loss 4.4463 (3.6271)	grad_norm 2.6952 (1.5530/0.6909)	mem 16099MB
[2025-01-18 01:12:49 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][260/312]	eta 0:00:24 lr 0.003466	time 0.4467 (0.4765)	model_time 0.4465 (0.4673)	loss 2.7369 (3.6181)	grad_norm 2.8147 (1.5483/0.6891)	mem 16099MB
[2025-01-18 01:12:54 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][270/312]	eta 0:00:19 lr 0.003465	time 0.4486 (0.4762)	model_time 0.4482 (0.4673)	loss 3.4804 (3.6216)	grad_norm 1.4949 (1.5446/0.6863)	mem 16099MB
[2025-01-18 01:12:58 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][280/312]	eta 0:00:15 lr 0.003465	time 0.4525 (0.4759)	model_time 0.4520 (0.4674)	loss 3.6155 (3.6203)	grad_norm 1.7340 (1.5608/0.6943)	mem 16099MB
[2025-01-18 01:13:03 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][290/312]	eta 0:00:10 lr 0.003464	time 0.4687 (0.4753)	model_time 0.4686 (0.4671)	loss 2.7819 (3.6234)	grad_norm 0.8703 (1.5465/0.6894)	mem 16099MB
[2025-01-18 01:13:08 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][300/312]	eta 0:00:05 lr 0.003464	time 0.4375 (0.4752)	model_time 0.4374 (0.4672)	loss 3.8189 (3.6293)	grad_norm 1.5197 (1.5230/0.6445)	mem 16099MB
[2025-01-18 01:13:12 internimage_t_1k_224] (main.py 510): INFO Train: [71/300][310/312]	eta 0:00:00 lr 0.003463	time 0.4503 (0.4743)	model_time 0.4502 (0.4666)	loss 4.0053 (3.6319)	grad_norm 0.9771 (1.5127/0.6495)	mem 16099MB
[2025-01-18 01:13:13 internimage_t_1k_224] (main.py 519): INFO EPOCH 71 training takes 0:02:27
[2025-01-18 01:13:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_71.pth saving......
[2025-01-18 01:13:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_71.pth saved !!!
[2025-01-18 01:13:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.426 (7.426)	Loss 0.9473 (0.9473)	Acc@1 78.955 (78.955)	Acc@5 95.386 (95.386)	Mem 16099MB
[2025-01-18 01:13:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.002)	Loss 1.3734 (1.1409)	Acc@1 68.433 (75.260)	Acc@5 90.381 (92.944)	Mem 16099MB
[2025-01-18 01:13:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:71] * Acc@1 75.296 Acc@5 93.002
[2025-01-18 01:13:25 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.3%
[2025-01-18 01:13:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 01:13:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 01:13:26 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.30%
[2025-01-18 01:13:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.325 (7.325)	Loss 1.5081 (1.5081)	Acc@1 70.312 (70.312)	Acc@5 90.283 (90.283)	Mem 16099MB
[2025-01-18 01:13:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.001)	Loss 2.0217 (1.7108)	Acc@1 60.400 (66.595)	Acc@5 83.276 (87.447)	Mem 16099MB
[2025-01-18 01:13:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:71] * Acc@1 66.547 Acc@5 87.538
[2025-01-18 01:13:37 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 66.5%
[2025-01-18 01:13:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:13:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:13:39 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 66.55%
[2025-01-18 01:13:41 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][0/312]	eta 0:12:47 lr 0.003463	time 2.4611 (2.4611)	model_time 0.5300 (0.5300)	loss 2.7237 (2.7237)	grad_norm 1.7950 (1.7950/0.0000)	mem 16099MB
[2025-01-18 01:13:46 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][10/312]	eta 0:03:18 lr 0.003463	time 0.4479 (0.6580)	model_time 0.4474 (0.4821)	loss 3.6547 (3.3368)	grad_norm 0.7816 (1.4231/0.5076)	mem 16099MB
[2025-01-18 01:13:51 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][20/312]	eta 0:02:48 lr 0.003462	time 0.4466 (0.5754)	model_time 0.4462 (0.4831)	loss 4.1222 (3.4623)	grad_norm 0.8322 (1.3872/0.4695)	mem 16099MB
[2025-01-18 01:13:55 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][30/312]	eta 0:02:32 lr 0.003462	time 0.4714 (0.5394)	model_time 0.4710 (0.4767)	loss 3.2870 (3.4495)	grad_norm 1.6178 (1.3533/0.4384)	mem 16099MB
[2025-01-18 01:14:00 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][40/312]	eta 0:02:21 lr 0.003462	time 0.4458 (0.5210)	model_time 0.4454 (0.4734)	loss 3.8816 (3.4933)	grad_norm 3.0940 (1.6091/0.8901)	mem 16099MB
[2025-01-18 01:14:05 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][50/312]	eta 0:02:14 lr 0.003461	time 0.4455 (0.5117)	model_time 0.4453 (0.4735)	loss 3.7339 (3.5728)	grad_norm 2.3447 (1.7145/0.9200)	mem 16099MB
[2025-01-18 01:14:10 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][60/312]	eta 0:02:07 lr 0.003461	time 0.4422 (0.5053)	model_time 0.4418 (0.4733)	loss 3.9840 (3.5751)	grad_norm 1.3900 (1.7248/0.8613)	mem 16099MB
[2025-01-18 01:14:14 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][70/312]	eta 0:02:00 lr 0.003460	time 0.4735 (0.4992)	model_time 0.4733 (0.4716)	loss 2.3613 (3.5616)	grad_norm 0.7663 (1.6685/0.8420)	mem 16099MB
[2025-01-18 01:14:19 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][80/312]	eta 0:01:54 lr 0.003460	time 0.4390 (0.4943)	model_time 0.4388 (0.4701)	loss 2.2753 (3.5363)	grad_norm 0.6845 (1.6103/0.8172)	mem 16099MB
[2025-01-18 01:14:23 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][90/312]	eta 0:01:48 lr 0.003459	time 0.5247 (0.4909)	model_time 0.5242 (0.4693)	loss 4.5101 (3.5439)	grad_norm 1.1422 (1.5607/0.7888)	mem 16099MB
[2025-01-18 01:14:28 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][100/312]	eta 0:01:43 lr 0.003459	time 0.4479 (0.4872)	model_time 0.4474 (0.4677)	loss 3.9567 (3.5265)	grad_norm 1.1152 (1.5570/0.7684)	mem 16099MB
[2025-01-18 01:14:33 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][110/312]	eta 0:01:38 lr 0.003458	time 0.4530 (0.4853)	model_time 0.4528 (0.4675)	loss 4.6230 (3.5407)	grad_norm 1.2153 (1.5704/0.7606)	mem 16099MB
[2025-01-18 01:14:37 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][120/312]	eta 0:01:32 lr 0.003458	time 0.4603 (0.4830)	model_time 0.4602 (0.4667)	loss 4.0782 (3.5385)	grad_norm 1.3274 (1.5757/0.7386)	mem 16099MB
[2025-01-18 01:14:42 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][130/312]	eta 0:01:27 lr 0.003457	time 0.5418 (0.4827)	model_time 0.5416 (0.4676)	loss 3.9358 (3.5114)	grad_norm 0.8008 (1.5694/0.7309)	mem 16099MB
[2025-01-18 01:14:47 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][140/312]	eta 0:01:23 lr 0.003457	time 0.7338 (0.4839)	model_time 0.7336 (0.4698)	loss 3.4997 (3.5231)	grad_norm 0.8471 (1.5640/0.7332)	mem 16099MB
[2025-01-18 01:14:52 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][150/312]	eta 0:01:18 lr 0.003457	time 0.4498 (0.4822)	model_time 0.4494 (0.4690)	loss 4.4100 (3.5237)	grad_norm 0.8127 (1.5656/0.7294)	mem 16099MB
[2025-01-18 01:14:56 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][160/312]	eta 0:01:13 lr 0.003456	time 0.4496 (0.4812)	model_time 0.4494 (0.4688)	loss 3.2360 (3.5252)	grad_norm 0.7871 (1.5867/0.7385)	mem 16099MB
[2025-01-18 01:15:01 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][170/312]	eta 0:01:08 lr 0.003456	time 0.4432 (0.4799)	model_time 0.4431 (0.4682)	loss 3.7880 (3.5357)	grad_norm 0.9788 (1.5597/0.7273)	mem 16099MB
[2025-01-18 01:15:05 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][180/312]	eta 0:01:03 lr 0.003455	time 0.4598 (0.4789)	model_time 0.4594 (0.4678)	loss 3.3586 (3.5398)	grad_norm 2.4970 (1.5638/0.7580)	mem 16099MB
[2025-01-18 01:15:10 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][190/312]	eta 0:00:58 lr 0.003455	time 0.4561 (0.4775)	model_time 0.4556 (0.4670)	loss 4.0896 (3.5521)	grad_norm 0.9532 (1.5403/0.7481)	mem 16099MB
[2025-01-18 01:15:15 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][200/312]	eta 0:00:53 lr 0.003454	time 0.4477 (0.4777)	model_time 0.4473 (0.4677)	loss 2.8574 (3.5522)	grad_norm 0.8305 (1.5313/0.7350)	mem 16099MB
[2025-01-18 01:15:19 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][210/312]	eta 0:00:48 lr 0.003454	time 0.4472 (0.4771)	model_time 0.4466 (0.4676)	loss 2.9323 (3.5419)	grad_norm 1.3573 (1.5317/0.7281)	mem 16099MB
[2025-01-18 01:15:24 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][220/312]	eta 0:00:43 lr 0.003453	time 0.4529 (0.4765)	model_time 0.4525 (0.4674)	loss 3.5397 (3.5297)	grad_norm 1.1391 (1.5173/0.7185)	mem 16099MB
[2025-01-18 01:15:29 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][230/312]	eta 0:00:39 lr 0.003453	time 0.4501 (0.4758)	model_time 0.4497 (0.4670)	loss 3.1049 (3.5181)	grad_norm 0.6783 (1.5077/0.7072)	mem 16099MB
[2025-01-18 01:15:33 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][240/312]	eta 0:00:34 lr 0.003452	time 0.4426 (0.4757)	model_time 0.4424 (0.4673)	loss 2.6459 (3.5131)	grad_norm 0.9710 (1.5291/0.7273)	mem 16099MB
[2025-01-18 01:15:38 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][250/312]	eta 0:00:29 lr 0.003452	time 0.4527 (0.4755)	model_time 0.4522 (0.4674)	loss 2.5959 (3.5112)	grad_norm 2.3734 (1.5539/0.7461)	mem 16099MB
[2025-01-18 01:15:43 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][260/312]	eta 0:00:24 lr 0.003451	time 0.4521 (0.4756)	model_time 0.4517 (0.4678)	loss 4.4349 (3.5155)	grad_norm 1.5656 (1.5478/0.7370)	mem 16099MB
[2025-01-18 01:15:47 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][270/312]	eta 0:00:19 lr 0.003451	time 0.4543 (0.4748)	model_time 0.4539 (0.4672)	loss 2.5410 (3.5175)	grad_norm 1.7229 (1.5675/0.7611)	mem 16099MB
[2025-01-18 01:15:52 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][280/312]	eta 0:00:15 lr 0.003451	time 0.4403 (0.4746)	model_time 0.4398 (0.4673)	loss 3.5786 (3.5218)	grad_norm 1.7045 (1.5615/0.7545)	mem 16099MB
[2025-01-18 01:15:57 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][290/312]	eta 0:00:10 lr 0.003450	time 0.4510 (0.4743)	model_time 0.4506 (0.4672)	loss 3.4421 (3.5243)	grad_norm 0.6285 (1.5522/0.7487)	mem 16099MB
[2025-01-18 01:16:01 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][300/312]	eta 0:00:05 lr 0.003450	time 0.4384 (0.4740)	model_time 0.4383 (0.4672)	loss 2.8658 (3.5300)	grad_norm 0.9007 (1.5404/0.7437)	mem 16099MB
[2025-01-18 01:16:06 internimage_t_1k_224] (main.py 510): INFO Train: [72/300][310/312]	eta 0:00:00 lr 0.003449	time 0.4394 (0.4730)	model_time 0.4394 (0.4664)	loss 3.6103 (3.5200)	grad_norm 1.0771 (1.5528/0.7529)	mem 16099MB
[2025-01-18 01:16:06 internimage_t_1k_224] (main.py 519): INFO EPOCH 72 training takes 0:02:27
[2025-01-18 01:16:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_72.pth saving......
[2025-01-18 01:16:07 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_72.pth saved !!!
[2025-01-18 01:16:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.194 (7.194)	Loss 0.9706 (0.9706)	Acc@1 78.613 (78.613)	Acc@5 95.605 (95.605)	Mem 16099MB
[2025-01-18 01:16:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.100 (0.992)	Loss 1.3845 (1.1631)	Acc@1 70.117 (75.435)	Acc@5 90.576 (93.122)	Mem 16099MB
[2025-01-18 01:16:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:72] * Acc@1 75.424 Acc@5 93.208
[2025-01-18 01:16:18 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.4%
[2025-01-18 01:16:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 01:16:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 01:16:20 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.42%
[2025-01-18 01:16:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.573 (7.573)	Loss 1.4649 (1.4649)	Acc@1 70.972 (70.972)	Acc@5 90.723 (90.723)	Mem 16099MB
[2025-01-18 01:16:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.030)	Loss 1.9780 (1.6692)	Acc@1 61.084 (67.250)	Acc@5 83.789 (87.942)	Mem 16099MB
[2025-01-18 01:16:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:72] * Acc@1 67.202 Acc@5 88.042
[2025-01-18 01:16:31 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 67.2%
[2025-01-18 01:16:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:16:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:16:33 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 67.20%
[2025-01-18 01:16:35 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][0/312]	eta 0:14:25 lr 0.003449	time 2.7743 (2.7743)	model_time 0.4821 (0.4821)	loss 4.1798 (4.1798)	grad_norm 2.3350 (2.3350/0.0000)	mem 16099MB
[2025-01-18 01:16:40 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][10/312]	eta 0:03:21 lr 0.003449	time 0.4656 (0.6678)	model_time 0.4652 (0.4591)	loss 4.3710 (3.8931)	grad_norm 1.9275 (1.8152/0.6734)	mem 16099MB
[2025-01-18 01:16:45 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][20/312]	eta 0:02:45 lr 0.003448	time 0.4523 (0.5671)	model_time 0.4521 (0.4576)	loss 3.5255 (3.6594)	grad_norm 1.0888 (1.7163/0.6698)	mem 16099MB
[2025-01-18 01:16:49 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][30/312]	eta 0:02:30 lr 0.003448	time 0.4421 (0.5344)	model_time 0.4419 (0.4601)	loss 3.7929 (3.7129)	grad_norm 1.0768 (1.5725/0.6120)	mem 16099MB
[2025-01-18 01:16:54 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][40/312]	eta 0:02:21 lr 0.003447	time 0.4622 (0.5199)	model_time 0.4621 (0.4636)	loss 4.4211 (3.6831)	grad_norm 1.3371 (1.5140/0.5853)	mem 16099MB
[2025-01-18 01:16:59 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][50/312]	eta 0:02:14 lr 0.003447	time 0.4604 (0.5132)	model_time 0.4603 (0.4679)	loss 3.5280 (3.5865)	grad_norm 2.0685 (1.5085/0.5532)	mem 16099MB
[2025-01-18 01:17:03 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][60/312]	eta 0:02:07 lr 0.003446	time 0.4723 (0.5058)	model_time 0.4719 (0.4679)	loss 3.4552 (3.5887)	grad_norm 1.0196 (1.4987/0.6247)	mem 16099MB
[2025-01-18 01:17:08 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][70/312]	eta 0:02:01 lr 0.003446	time 0.4415 (0.5002)	model_time 0.4413 (0.4675)	loss 3.3727 (3.5664)	grad_norm 1.4002 (1.4922/0.6005)	mem 16099MB
[2025-01-18 01:17:13 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][80/312]	eta 0:01:55 lr 0.003445	time 0.4434 (0.4983)	model_time 0.4429 (0.4697)	loss 3.8509 (3.5643)	grad_norm 3.0702 (1.5213/0.6430)	mem 16099MB
[2025-01-18 01:17:18 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][90/312]	eta 0:01:50 lr 0.003445	time 0.4650 (0.4964)	model_time 0.4649 (0.4708)	loss 3.9590 (3.5329)	grad_norm 1.1947 (1.5532/0.6773)	mem 16099MB
[2025-01-18 01:17:22 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][100/312]	eta 0:01:44 lr 0.003444	time 0.4500 (0.4920)	model_time 0.4496 (0.4689)	loss 2.9999 (3.5007)	grad_norm 1.6930 (1.5389/0.6500)	mem 16099MB
[2025-01-18 01:17:27 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][110/312]	eta 0:01:38 lr 0.003444	time 0.4403 (0.4888)	model_time 0.4398 (0.4678)	loss 3.5652 (3.5052)	grad_norm 0.8855 (1.5776/0.6894)	mem 16099MB
[2025-01-18 01:17:31 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][120/312]	eta 0:01:33 lr 0.003444	time 0.4447 (0.4860)	model_time 0.4446 (0.4666)	loss 2.5471 (3.5155)	grad_norm 3.3437 (1.5836/0.6878)	mem 16099MB
[2025-01-18 01:17:36 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][130/312]	eta 0:01:28 lr 0.003443	time 0.4715 (0.4854)	model_time 0.4714 (0.4675)	loss 3.8140 (3.5169)	grad_norm 0.8742 (1.5788/0.6736)	mem 16099MB
[2025-01-18 01:17:41 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][140/312]	eta 0:01:23 lr 0.003443	time 0.4478 (0.4836)	model_time 0.4476 (0.4670)	loss 3.2412 (3.5358)	grad_norm 1.8175 (1.5627/0.6554)	mem 16099MB
[2025-01-18 01:17:45 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][150/312]	eta 0:01:18 lr 0.003442	time 0.4453 (0.4821)	model_time 0.4449 (0.4665)	loss 3.3890 (3.5295)	grad_norm 2.1461 (1.5935/0.6780)	mem 16099MB
[2025-01-18 01:17:50 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][160/312]	eta 0:01:13 lr 0.003442	time 0.4497 (0.4816)	model_time 0.4493 (0.4670)	loss 3.8437 (3.5308)	grad_norm 1.3665 (1.6378/0.7272)	mem 16099MB
[2025-01-18 01:17:55 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][170/312]	eta 0:01:08 lr 0.003441	time 0.4574 (0.4802)	model_time 0.4573 (0.4665)	loss 3.9444 (3.5312)	grad_norm 1.3941 (1.6114/0.7199)	mem 16099MB
[2025-01-18 01:17:59 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][180/312]	eta 0:01:03 lr 0.003441	time 0.4498 (0.4798)	model_time 0.4493 (0.4668)	loss 3.2712 (3.5283)	grad_norm 2.2099 (1.6101/0.7211)	mem 16099MB
[2025-01-18 01:18:04 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][190/312]	eta 0:00:58 lr 0.003440	time 0.4540 (0.4792)	model_time 0.4536 (0.4668)	loss 2.9177 (3.5341)	grad_norm 1.0535 (1.5914/0.7120)	mem 16099MB
[2025-01-18 01:18:09 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][200/312]	eta 0:00:53 lr 0.003440	time 0.5452 (0.4792)	model_time 0.5448 (0.4674)	loss 4.0343 (3.5272)	grad_norm 0.8449 (1.5593/0.7091)	mem 16099MB
[2025-01-18 01:18:14 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][210/312]	eta 0:00:48 lr 0.003439	time 0.4472 (0.4794)	model_time 0.4470 (0.4682)	loss 3.6258 (3.5271)	grad_norm 3.1037 (1.5603/0.7040)	mem 16099MB
[2025-01-18 01:18:18 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][220/312]	eta 0:00:44 lr 0.003439	time 0.5463 (0.4786)	model_time 0.5461 (0.4678)	loss 3.7740 (3.5296)	grad_norm 1.5120 (1.5591/0.6931)	mem 16099MB
[2025-01-18 01:18:23 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][230/312]	eta 0:00:39 lr 0.003438	time 0.4554 (0.4780)	model_time 0.4549 (0.4677)	loss 3.6078 (3.5325)	grad_norm 0.9316 (1.5390/0.6877)	mem 16099MB
[2025-01-18 01:18:28 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][240/312]	eta 0:00:34 lr 0.003438	time 0.4500 (0.4777)	model_time 0.4498 (0.4678)	loss 4.4527 (3.5431)	grad_norm 1.9092 (1.5359/0.6826)	mem 16099MB
[2025-01-18 01:18:32 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][250/312]	eta 0:00:29 lr 0.003438	time 0.4472 (0.4768)	model_time 0.4467 (0.4673)	loss 3.7110 (3.5332)	grad_norm 1.8020 (1.5422/0.6844)	mem 16099MB
[2025-01-18 01:18:37 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][260/312]	eta 0:00:24 lr 0.003437	time 0.4958 (0.4764)	model_time 0.4956 (0.4673)	loss 4.2883 (3.5304)	grad_norm 1.0373 (1.5413/0.6746)	mem 16099MB
[2025-01-18 01:18:42 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][270/312]	eta 0:00:19 lr 0.003437	time 0.4475 (0.4761)	model_time 0.4471 (0.4672)	loss 3.0112 (3.5271)	grad_norm 1.1049 (1.5337/0.6694)	mem 16099MB
[2025-01-18 01:18:46 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][280/312]	eta 0:00:15 lr 0.003436	time 0.4448 (0.4758)	model_time 0.4442 (0.4672)	loss 2.3934 (3.5189)	grad_norm 1.3073 (1.5474/0.6701)	mem 16099MB
[2025-01-18 01:18:51 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][290/312]	eta 0:00:10 lr 0.003436	time 0.4643 (0.4760)	model_time 0.4639 (0.4677)	loss 3.8254 (3.5186)	grad_norm 1.5686 (1.5758/0.7192)	mem 16099MB
[2025-01-18 01:18:56 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][300/312]	eta 0:00:05 lr 0.003435	time 0.4386 (0.4753)	model_time 0.4385 (0.4673)	loss 2.2348 (3.5161)	grad_norm 0.8549 (1.5596/0.7188)	mem 16099MB
[2025-01-18 01:19:00 internimage_t_1k_224] (main.py 510): INFO Train: [73/300][310/312]	eta 0:00:00 lr 0.003435	time 0.4377 (0.4742)	model_time 0.4376 (0.4665)	loss 3.6245 (3.5258)	grad_norm 1.7337 (1.5368/0.7136)	mem 16099MB
[2025-01-18 01:19:01 internimage_t_1k_224] (main.py 519): INFO EPOCH 73 training takes 0:02:27
[2025-01-18 01:19:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_73.pth saving......
[2025-01-18 01:19:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_73.pth saved !!!
[2025-01-18 01:19:09 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.700 (7.700)	Loss 0.9480 (0.9480)	Acc@1 79.761 (79.761)	Acc@5 95.728 (95.728)	Mem 16099MB
[2025-01-18 01:19:13 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.035)	Loss 1.4144 (1.1468)	Acc@1 70.068 (75.573)	Acc@5 89.795 (93.180)	Mem 16099MB
[2025-01-18 01:19:13 internimage_t_1k_224] (main.py 575): INFO [Epoch:73] * Acc@1 75.626 Acc@5 93.230
[2025-01-18 01:19:13 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.6%
[2025-01-18 01:19:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 01:19:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 01:19:14 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.63%
[2025-01-18 01:19:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.609 (7.609)	Loss 1.4256 (1.4256)	Acc@1 71.851 (71.851)	Acc@5 91.357 (91.357)	Mem 16099MB
[2025-01-18 01:19:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.039)	Loss 1.9360 (1.6308)	Acc@1 61.426 (67.844)	Acc@5 84.375 (88.361)	Mem 16099MB
[2025-01-18 01:19:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:73] * Acc@1 67.820 Acc@5 88.464
[2025-01-18 01:19:26 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 67.8%
[2025-01-18 01:19:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:19:27 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:19:27 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 67.82%
[2025-01-18 01:19:30 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][0/312]	eta 0:13:18 lr 0.003435	time 2.5605 (2.5605)	model_time 0.4974 (0.4974)	loss 3.5055 (3.5055)	grad_norm 3.0145 (3.0145/0.0000)	mem 16099MB
[2025-01-18 01:19:35 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][10/312]	eta 0:03:17 lr 0.003434	time 0.5394 (0.6555)	model_time 0.5393 (0.4675)	loss 3.9747 (3.6012)	grad_norm 1.3833 (2.0326/0.8053)	mem 16099MB
[2025-01-18 01:19:39 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][20/312]	eta 0:02:45 lr 0.003434	time 0.4525 (0.5664)	model_time 0.4524 (0.4678)	loss 3.7117 (3.6754)	grad_norm 1.1822 (1.6725/0.7380)	mem 16099MB
[2025-01-18 01:19:44 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][30/312]	eta 0:02:31 lr 0.003433	time 0.4397 (0.5360)	model_time 0.4395 (0.4691)	loss 4.2274 (3.5302)	grad_norm 0.9367 (1.6317/0.7843)	mem 16099MB
[2025-01-18 01:19:49 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][40/312]	eta 0:02:20 lr 0.003433	time 0.4536 (0.5170)	model_time 0.4532 (0.4663)	loss 3.4594 (3.5529)	grad_norm 1.6062 (1.5050/0.7428)	mem 16099MB
[2025-01-18 01:19:53 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][50/312]	eta 0:02:12 lr 0.003432	time 0.4538 (0.5048)	model_time 0.4536 (0.4640)	loss 4.2799 (3.5438)	grad_norm 1.8920 (1.6499/0.8026)	mem 16099MB
[2025-01-18 01:19:58 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][60/312]	eta 0:02:05 lr 0.003432	time 0.4593 (0.4964)	model_time 0.4591 (0.4622)	loss 3.7793 (3.5524)	grad_norm 1.3822 (1.6617/0.7741)	mem 16099MB
[2025-01-18 01:20:02 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][70/312]	eta 0:01:59 lr 0.003431	time 0.4590 (0.4934)	model_time 0.4586 (0.4640)	loss 3.8144 (3.5691)	grad_norm 1.0332 (1.6095/0.7479)	mem 16099MB
[2025-01-18 01:20:07 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][80/312]	eta 0:01:53 lr 0.003431	time 0.4834 (0.4895)	model_time 0.4829 (0.4637)	loss 2.2436 (3.5400)	grad_norm 1.5986 (1.5596/0.7243)	mem 16099MB
[2025-01-18 01:20:12 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][90/312]	eta 0:01:47 lr 0.003430	time 0.4515 (0.4858)	model_time 0.4511 (0.4627)	loss 4.2584 (3.5452)	grad_norm 2.8033 (1.5423/0.7116)	mem 16099MB
[2025-01-18 01:20:16 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][100/312]	eta 0:01:42 lr 0.003430	time 0.4441 (0.4854)	model_time 0.4436 (0.4646)	loss 3.4743 (3.5191)	grad_norm 1.0523 (1.5790/0.7868)	mem 16099MB
[2025-01-18 01:20:21 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][110/312]	eta 0:01:37 lr 0.003430	time 0.4528 (0.4836)	model_time 0.4523 (0.4647)	loss 4.2025 (3.5378)	grad_norm 1.5716 (1.5471/0.7634)	mem 16099MB
[2025-01-18 01:20:26 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][120/312]	eta 0:01:32 lr 0.003429	time 0.4441 (0.4837)	model_time 0.4437 (0.4663)	loss 4.3967 (3.5315)	grad_norm 1.2001 (1.5573/0.7640)	mem 16099MB
[2025-01-18 01:20:31 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][130/312]	eta 0:01:27 lr 0.003429	time 0.4657 (0.4821)	model_time 0.4652 (0.4659)	loss 3.8991 (3.5280)	grad_norm 1.5265 (1.5316/0.7441)	mem 16099MB
[2025-01-18 01:20:35 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][140/312]	eta 0:01:22 lr 0.003428	time 0.5411 (0.4812)	model_time 0.5407 (0.4661)	loss 4.1144 (3.5509)	grad_norm 1.1136 (1.5795/0.7986)	mem 16099MB
[2025-01-18 01:20:40 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][150/312]	eta 0:01:17 lr 0.003428	time 0.4559 (0.4805)	model_time 0.4557 (0.4664)	loss 3.4491 (3.5599)	grad_norm 1.1958 (1.5480/0.7846)	mem 16099MB
[2025-01-18 01:20:45 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][160/312]	eta 0:01:13 lr 0.003427	time 0.4409 (0.4816)	model_time 0.4405 (0.4683)	loss 3.3942 (3.5526)	grad_norm 0.9763 (1.5684/0.7785)	mem 16099MB
[2025-01-18 01:20:49 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][170/312]	eta 0:01:08 lr 0.003427	time 0.4653 (0.4800)	model_time 0.4651 (0.4675)	loss 3.8707 (3.5503)	grad_norm 0.8122 (1.5341/0.7695)	mem 16099MB
[2025-01-18 01:20:54 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][180/312]	eta 0:01:03 lr 0.003426	time 0.4421 (0.4794)	model_time 0.4417 (0.4676)	loss 2.9447 (3.5667)	grad_norm 0.8598 (1.5400/0.7757)	mem 16099MB
[2025-01-18 01:20:59 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][190/312]	eta 0:00:58 lr 0.003426	time 0.4580 (0.4780)	model_time 0.4575 (0.4668)	loss 4.3821 (3.5692)	grad_norm 1.6905 (1.5369/0.7685)	mem 16099MB
[2025-01-18 01:21:03 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][200/312]	eta 0:00:53 lr 0.003425	time 0.4527 (0.4769)	model_time 0.4526 (0.4662)	loss 2.2818 (3.5447)	grad_norm 1.1106 (1.5609/0.8214)	mem 16099MB
[2025-01-18 01:21:08 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][210/312]	eta 0:00:48 lr 0.003425	time 0.4853 (0.4762)	model_time 0.4851 (0.4660)	loss 1.9929 (3.5384)	grad_norm 1.0903 (1.5764/0.8358)	mem 16099MB
[2025-01-18 01:21:13 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][220/312]	eta 0:00:43 lr 0.003424	time 0.4446 (0.4756)	model_time 0.4441 (0.4659)	loss 4.1399 (3.5460)	grad_norm 0.9957 (1.5667/0.8284)	mem 16099MB
[2025-01-18 01:21:17 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][230/312]	eta 0:00:38 lr 0.003424	time 0.4713 (0.4753)	model_time 0.4709 (0.4660)	loss 3.3328 (3.5525)	grad_norm 1.2985 (1.5592/0.8165)	mem 16099MB
[2025-01-18 01:21:22 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][240/312]	eta 0:00:34 lr 0.003423	time 0.4386 (0.4749)	model_time 0.4384 (0.4659)	loss 3.8302 (3.5517)	grad_norm 0.7340 (1.5492/0.8050)	mem 16099MB
[2025-01-18 01:21:26 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][250/312]	eta 0:00:29 lr 0.003423	time 0.4420 (0.4744)	model_time 0.4418 (0.4658)	loss 3.0268 (3.5423)	grad_norm 2.3445 (1.5496/0.7992)	mem 16099MB
[2025-01-18 01:21:31 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][260/312]	eta 0:00:24 lr 0.003423	time 0.4400 (0.4744)	model_time 0.4396 (0.4661)	loss 3.6002 (3.5482)	grad_norm 1.2445 (1.5400/0.7895)	mem 16099MB
[2025-01-18 01:21:36 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][270/312]	eta 0:00:19 lr 0.003422	time 0.4528 (0.4743)	model_time 0.4524 (0.4662)	loss 3.6406 (3.5479)	grad_norm 1.0816 (1.5447/0.7854)	mem 16099MB
[2025-01-18 01:21:41 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][280/312]	eta 0:00:15 lr 0.003422	time 0.4452 (0.4738)	model_time 0.4447 (0.4660)	loss 3.8514 (3.5495)	grad_norm 1.2132 (1.5400/0.7782)	mem 16099MB
[2025-01-18 01:21:45 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][290/312]	eta 0:00:10 lr 0.003421	time 0.4499 (0.4734)	model_time 0.4494 (0.4659)	loss 3.5888 (3.5438)	grad_norm 2.5593 (1.5491/0.7789)	mem 16099MB
[2025-01-18 01:21:50 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][300/312]	eta 0:00:05 lr 0.003421	time 0.4379 (0.4730)	model_time 0.4378 (0.4657)	loss 2.8592 (3.5406)	grad_norm 0.9164 (1.5527/0.7861)	mem 16099MB
[2025-01-18 01:21:55 internimage_t_1k_224] (main.py 510): INFO Train: [74/300][310/312]	eta 0:00:00 lr 0.003420	time 0.4418 (0.4730)	model_time 0.4417 (0.4660)	loss 3.8708 (3.5374)	grad_norm 1.8404 (1.5390/0.7732)	mem 16099MB
[2025-01-18 01:21:55 internimage_t_1k_224] (main.py 519): INFO EPOCH 74 training takes 0:02:27
[2025-01-18 01:21:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_74.pth saving......
[2025-01-18 01:21:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_74.pth saved !!!
[2025-01-18 01:22:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.436 (7.436)	Loss 0.9699 (0.9699)	Acc@1 78.638 (78.638)	Acc@5 95.654 (95.654)	Mem 16099MB
[2025-01-18 01:22:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.006)	Loss 1.4153 (1.1796)	Acc@1 70.142 (75.657)	Acc@5 89.917 (93.086)	Mem 16099MB
[2025-01-18 01:22:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:74] * Acc@1 75.558 Acc@5 93.114
[2025-01-18 01:22:07 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.6%
[2025-01-18 01:22:07 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.63%
[2025-01-18 01:22:16 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.278 (8.278)	Loss 1.3898 (1.3898)	Acc@1 72.339 (72.339)	Acc@5 91.650 (91.650)	Mem 16099MB
[2025-01-18 01:22:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.112)	Loss 1.8970 (1.5946)	Acc@1 61.914 (68.393)	Acc@5 84.570 (88.681)	Mem 16099MB
[2025-01-18 01:22:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:74] * Acc@1 68.350 Acc@5 88.776
[2025-01-18 01:22:20 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 68.4%
[2025-01-18 01:22:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:22:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:22:21 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 68.35%
[2025-01-18 01:22:24 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][0/312]	eta 0:12:31 lr 0.003420	time 2.4092 (2.4092)	model_time 0.4620 (0.4620)	loss 3.6559 (3.6559)	grad_norm 1.2145 (1.2145/0.0000)	mem 16099MB
[2025-01-18 01:22:28 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][10/312]	eta 0:03:12 lr 0.003420	time 0.4394 (0.6362)	model_time 0.4393 (0.4588)	loss 3.3534 (3.3004)	grad_norm 2.0921 (1.2658/0.3527)	mem 16099MB
[2025-01-18 01:22:33 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][20/312]	eta 0:02:40 lr 0.003419	time 0.4594 (0.5513)	model_time 0.4593 (0.4582)	loss 3.9094 (3.2413)	grad_norm 0.8900 (1.6254/0.8230)	mem 16099MB
[2025-01-18 01:22:37 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][30/312]	eta 0:02:26 lr 0.003419	time 0.4520 (0.5199)	model_time 0.4518 (0.4567)	loss 3.8238 (3.2558)	grad_norm 1.4089 (1.6786/0.7554)	mem 16099MB
[2025-01-18 01:22:42 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][40/312]	eta 0:02:17 lr 0.003418	time 0.4414 (0.5039)	model_time 0.4410 (0.4561)	loss 2.5958 (3.3009)	grad_norm 1.9975 (1.8352/0.7872)	mem 16099MB
[2025-01-18 01:22:47 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][50/312]	eta 0:02:10 lr 0.003418	time 0.4496 (0.4986)	model_time 0.4495 (0.4601)	loss 3.4383 (3.3687)	grad_norm 0.8187 (1.7624/0.7672)	mem 16099MB
[2025-01-18 01:22:51 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][60/312]	eta 0:02:04 lr 0.003417	time 0.5483 (0.4928)	model_time 0.5481 (0.4605)	loss 3.7210 (3.4484)	grad_norm 1.1662 (1.6672/0.7437)	mem 16099MB
[2025-01-18 01:22:56 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][70/312]	eta 0:01:58 lr 0.003417	time 0.4964 (0.4905)	model_time 0.4962 (0.4628)	loss 3.3452 (3.4595)	grad_norm 1.0702 (1.6764/0.7420)	mem 16099MB
[2025-01-18 01:23:01 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][80/312]	eta 0:01:53 lr 0.003416	time 0.4447 (0.4875)	model_time 0.4443 (0.4631)	loss 3.0685 (3.4761)	grad_norm 1.2278 (1.6606/0.7324)	mem 16099MB
[2025-01-18 01:23:06 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][90/312]	eta 0:01:47 lr 0.003416	time 0.5582 (0.4850)	model_time 0.5577 (0.4633)	loss 3.0857 (3.4680)	grad_norm 3.4518 (1.6563/0.7361)	mem 16099MB
[2025-01-18 01:23:10 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][100/312]	eta 0:01:42 lr 0.003415	time 0.4637 (0.4825)	model_time 0.4635 (0.4629)	loss 2.9103 (3.4445)	grad_norm 1.1720 (1.6372/0.7100)	mem 16099MB
[2025-01-18 01:23:15 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][110/312]	eta 0:01:37 lr 0.003415	time 0.4435 (0.4809)	model_time 0.4434 (0.4631)	loss 2.9594 (3.4588)	grad_norm 0.9512 (1.6142/0.6898)	mem 16099MB
[2025-01-18 01:23:19 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][120/312]	eta 0:01:32 lr 0.003414	time 0.5329 (0.4800)	model_time 0.5328 (0.4635)	loss 3.0399 (3.4622)	grad_norm 1.3307 (1.5769/0.6784)	mem 16099MB
[2025-01-18 01:23:24 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][130/312]	eta 0:01:27 lr 0.003414	time 0.4444 (0.4803)	model_time 0.4440 (0.4651)	loss 3.7902 (3.4731)	grad_norm 3.1502 (1.6345/0.7306)	mem 16099MB
[2025-01-18 01:23:29 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][140/312]	eta 0:01:22 lr 0.003413	time 0.5340 (0.4812)	model_time 0.5336 (0.4670)	loss 4.0706 (3.4737)	grad_norm 1.6131 (1.6238/0.7106)	mem 16099MB
[2025-01-18 01:23:34 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][150/312]	eta 0:01:17 lr 0.003413	time 0.4445 (0.4805)	model_time 0.4444 (0.4673)	loss 4.3721 (3.4855)	grad_norm 1.5123 (1.6113/0.6937)	mem 16099MB
[2025-01-18 01:23:39 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][160/312]	eta 0:01:12 lr 0.003413	time 0.4499 (0.4792)	model_time 0.4497 (0.4667)	loss 3.7663 (3.4995)	grad_norm 0.8861 (1.6498/0.7345)	mem 16099MB
[2025-01-18 01:23:43 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][170/312]	eta 0:01:08 lr 0.003412	time 0.4597 (0.4799)	model_time 0.4595 (0.4681)	loss 3.8254 (3.5079)	grad_norm 0.8388 (1.6113/0.7313)	mem 16099MB
[2025-01-18 01:23:48 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][180/312]	eta 0:01:03 lr 0.003412	time 0.4903 (0.4793)	model_time 0.4899 (0.4682)	loss 4.0312 (3.5212)	grad_norm 0.8290 (1.5834/0.7285)	mem 16099MB
[2025-01-18 01:23:53 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][190/312]	eta 0:00:58 lr 0.003411	time 0.4595 (0.4778)	model_time 0.4594 (0.4673)	loss 4.0807 (3.5263)	grad_norm 0.9029 (1.5769/0.7239)	mem 16099MB
[2025-01-18 01:23:57 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][200/312]	eta 0:00:53 lr 0.003411	time 0.4625 (0.4766)	model_time 0.4620 (0.4665)	loss 3.5018 (3.5315)	grad_norm 0.9731 (1.5853/0.7296)	mem 16099MB
[2025-01-18 01:24:02 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][210/312]	eta 0:00:48 lr 0.003410	time 0.4526 (0.4760)	model_time 0.4521 (0.4664)	loss 4.0254 (3.5458)	grad_norm 2.1493 (1.5763/0.7171)	mem 16099MB
[2025-01-18 01:24:06 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][220/312]	eta 0:00:43 lr 0.003410	time 0.4671 (0.4754)	model_time 0.4669 (0.4662)	loss 3.5691 (3.5529)	grad_norm 1.1530 (1.5693/0.7046)	mem 16099MB
[2025-01-18 01:24:11 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][230/312]	eta 0:00:38 lr 0.003409	time 0.4472 (0.4749)	model_time 0.4471 (0.4661)	loss 3.3986 (3.5495)	grad_norm 0.7103 (1.5621/0.6995)	mem 16099MB
[2025-01-18 01:24:16 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][240/312]	eta 0:00:34 lr 0.003409	time 0.4421 (0.4744)	model_time 0.4416 (0.4659)	loss 2.7157 (3.5487)	grad_norm 0.8596 (1.5468/0.6917)	mem 16099MB
[2025-01-18 01:24:20 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][250/312]	eta 0:00:29 lr 0.003408	time 0.4495 (0.4739)	model_time 0.4494 (0.4658)	loss 3.0228 (3.5412)	grad_norm 2.7316 (1.5459/0.6858)	mem 16099MB
[2025-01-18 01:24:25 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][260/312]	eta 0:00:24 lr 0.003408	time 0.4503 (0.4732)	model_time 0.4502 (0.4654)	loss 2.7508 (3.5366)	grad_norm 0.8340 (1.5399/0.6780)	mem 16099MB
[2025-01-18 01:24:30 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][270/312]	eta 0:00:19 lr 0.003407	time 0.4502 (0.4728)	model_time 0.4498 (0.4653)	loss 2.9971 (3.5392)	grad_norm 2.1997 (1.5288/0.6749)	mem 16099MB
[2025-01-18 01:24:34 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][280/312]	eta 0:00:15 lr 0.003407	time 0.4470 (0.4721)	model_time 0.4468 (0.4648)	loss 2.8244 (3.5505)	grad_norm 1.1318 (1.5474/0.6840)	mem 16099MB
[2025-01-18 01:24:39 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][290/312]	eta 0:00:10 lr 0.003406	time 0.4531 (0.4724)	model_time 0.4529 (0.4653)	loss 4.3414 (3.5497)	grad_norm 0.7311 (1.5440/0.6788)	mem 16099MB
[2025-01-18 01:24:43 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][300/312]	eta 0:00:05 lr 0.003406	time 0.4418 (0.4721)	model_time 0.4417 (0.4653)	loss 3.7292 (3.5506)	grad_norm 1.3435 (1.5636/0.7034)	mem 16099MB
[2025-01-18 01:24:48 internimage_t_1k_224] (main.py 510): INFO Train: [75/300][310/312]	eta 0:00:00 lr 0.003405	time 0.5175 (0.4722)	model_time 0.5174 (0.4655)	loss 2.8556 (3.5455)	grad_norm 2.6244 (1.5665/0.7083)	mem 16099MB
[2025-01-18 01:24:49 internimage_t_1k_224] (main.py 519): INFO EPOCH 75 training takes 0:02:27
[2025-01-18 01:24:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_75.pth saving......
[2025-01-18 01:24:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_75.pth saved !!!
[2025-01-18 01:24:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.847 (7.847)	Loss 0.9396 (0.9396)	Acc@1 79.297 (79.297)	Acc@5 95.825 (95.825)	Mem 16099MB
[2025-01-18 01:25:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.029)	Loss 1.3782 (1.1281)	Acc@1 69.141 (75.351)	Acc@5 89.917 (93.073)	Mem 16099MB
[2025-01-18 01:25:01 internimage_t_1k_224] (main.py 575): INFO [Epoch:75] * Acc@1 75.276 Acc@5 93.142
[2025-01-18 01:25:01 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.3%
[2025-01-18 01:25:01 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.63%
[2025-01-18 01:25:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.462 (8.462)	Loss 1.3561 (1.3561)	Acc@1 72.876 (72.876)	Acc@5 92.041 (92.041)	Mem 16099MB
[2025-01-18 01:25:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.125)	Loss 1.8595 (1.5599)	Acc@1 62.354 (68.908)	Acc@5 84.912 (88.976)	Mem 16099MB
[2025-01-18 01:25:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:75] * Acc@1 68.870 Acc@5 89.062
[2025-01-18 01:25:14 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 68.9%
[2025-01-18 01:25:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:25:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:25:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 68.87%
[2025-01-18 01:25:18 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][0/312]	eta 0:15:17 lr 0.003405	time 2.9404 (2.9404)	model_time 0.4811 (0.4811)	loss 3.5998 (3.5998)	grad_norm 3.4315 (3.4315/0.0000)	mem 16099MB
[2025-01-18 01:25:23 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][10/312]	eta 0:03:30 lr 0.003405	time 0.4608 (0.6958)	model_time 0.4607 (0.4719)	loss 3.7589 (3.6448)	grad_norm 1.1896 (1.6433/0.8859)	mem 16099MB
[2025-01-18 01:25:28 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][20/312]	eta 0:02:52 lr 0.003404	time 0.4402 (0.5902)	model_time 0.4400 (0.4728)	loss 3.7199 (3.4978)	grad_norm 0.9569 (1.5410/0.8021)	mem 16099MB
[2025-01-18 01:25:32 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][30/312]	eta 0:02:34 lr 0.003404	time 0.4506 (0.5466)	model_time 0.4502 (0.4669)	loss 3.2025 (3.4871)	grad_norm 3.9740 (1.7487/0.8690)	mem 16099MB
[2025-01-18 01:25:37 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][40/312]	eta 0:02:24 lr 0.003403	time 0.4494 (0.5300)	model_time 0.4492 (0.4697)	loss 4.2572 (3.4970)	grad_norm 0.7944 (1.8849/0.9179)	mem 16099MB
[2025-01-18 01:25:42 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][50/312]	eta 0:02:15 lr 0.003403	time 0.4449 (0.5188)	model_time 0.4447 (0.4702)	loss 3.5627 (3.4729)	grad_norm 1.0560 (1.8259/0.8643)	mem 16099MB
[2025-01-18 01:25:46 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][60/312]	eta 0:02:08 lr 0.003402	time 0.5314 (0.5112)	model_time 0.5309 (0.4705)	loss 3.5738 (3.4966)	grad_norm 1.3252 (1.7835/0.8598)	mem 16099MB
[2025-01-18 01:25:51 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][70/312]	eta 0:02:02 lr 0.003402	time 0.4478 (0.5058)	model_time 0.4473 (0.4707)	loss 2.6129 (3.4951)	grad_norm 3.1993 (1.7693/0.8773)	mem 16099MB
[2025-01-18 01:25:56 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][80/312]	eta 0:01:56 lr 0.003402	time 0.5561 (0.5015)	model_time 0.5559 (0.4708)	loss 3.2805 (3.4732)	grad_norm 2.5991 (1.7681/0.8674)	mem 16099MB
[2025-01-18 01:26:01 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][90/312]	eta 0:01:50 lr 0.003401	time 0.4532 (0.4978)	model_time 0.4528 (0.4704)	loss 3.5271 (3.4681)	grad_norm 1.4399 (1.7654/0.8373)	mem 16099MB
[2025-01-18 01:26:05 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][100/312]	eta 0:01:44 lr 0.003401	time 0.4478 (0.4942)	model_time 0.4476 (0.4695)	loss 3.7696 (3.4636)	grad_norm 0.8917 (1.7084/0.8185)	mem 16099MB
[2025-01-18 01:26:10 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][110/312]	eta 0:01:39 lr 0.003400	time 0.4679 (0.4906)	model_time 0.4674 (0.4681)	loss 4.4843 (3.4617)	grad_norm 0.7102 (1.6579/0.8027)	mem 16099MB
[2025-01-18 01:26:15 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][120/312]	eta 0:01:34 lr 0.003400	time 0.5609 (0.4901)	model_time 0.5608 (0.4693)	loss 3.6435 (3.4750)	grad_norm 1.2974 (1.6211/0.7851)	mem 16099MB
[2025-01-18 01:26:19 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][130/312]	eta 0:01:28 lr 0.003399	time 0.4598 (0.4885)	model_time 0.4597 (0.4694)	loss 2.6752 (3.4767)	grad_norm 1.1845 (1.6101/0.7679)	mem 16099MB
[2025-01-18 01:26:24 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][140/312]	eta 0:01:23 lr 0.003399	time 0.4521 (0.4867)	model_time 0.4516 (0.4689)	loss 2.9381 (3.4637)	grad_norm 1.0001 (1.6420/0.7903)	mem 16099MB
[2025-01-18 01:26:28 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][150/312]	eta 0:01:18 lr 0.003398	time 0.4597 (0.4849)	model_time 0.4593 (0.4682)	loss 3.2972 (3.4820)	grad_norm 1.4007 (1.6359/0.7758)	mem 16099MB
[2025-01-18 01:26:33 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][160/312]	eta 0:01:13 lr 0.003398	time 0.5503 (0.4847)	model_time 0.5499 (0.4690)	loss 2.3646 (3.4992)	grad_norm 1.4966 (1.6205/0.7641)	mem 16099MB
[2025-01-18 01:26:38 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][170/312]	eta 0:01:08 lr 0.003397	time 0.4473 (0.4837)	model_time 0.4467 (0.4689)	loss 4.1272 (3.4957)	grad_norm 1.2867 (1.5933/0.7517)	mem 16099MB
[2025-01-18 01:26:43 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][180/312]	eta 0:01:03 lr 0.003397	time 0.4640 (0.4826)	model_time 0.4635 (0.4687)	loss 2.4326 (3.5031)	grad_norm 2.6386 (1.6222/0.7793)	mem 16099MB
[2025-01-18 01:26:47 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][190/312]	eta 0:00:58 lr 0.003396	time 0.4511 (0.4811)	model_time 0.4506 (0.4678)	loss 3.6956 (3.5084)	grad_norm 1.0876 (1.6134/0.7733)	mem 16099MB
[2025-01-18 01:26:52 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][200/312]	eta 0:00:53 lr 0.003396	time 0.4458 (0.4803)	model_time 0.4454 (0.4676)	loss 3.6603 (3.5009)	grad_norm 1.0240 (1.5996/0.7606)	mem 16099MB
[2025-01-18 01:26:56 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][210/312]	eta 0:00:48 lr 0.003395	time 0.4504 (0.4791)	model_time 0.4502 (0.4670)	loss 2.9388 (3.5084)	grad_norm 2.9274 (1.6058/0.7539)	mem 16099MB
[2025-01-18 01:27:01 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][220/312]	eta 0:00:43 lr 0.003395	time 0.4521 (0.4781)	model_time 0.4517 (0.4666)	loss 3.6018 (3.5124)	grad_norm 1.1938 (1.5995/0.7467)	mem 16099MB
[2025-01-18 01:27:06 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][230/312]	eta 0:00:39 lr 0.003394	time 0.4503 (0.4787)	model_time 0.4501 (0.4676)	loss 2.8306 (3.5111)	grad_norm 1.1350 (1.5900/0.7407)	mem 16099MB
[2025-01-18 01:27:11 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][240/312]	eta 0:00:34 lr 0.003394	time 0.4428 (0.4783)	model_time 0.4424 (0.4677)	loss 4.1146 (3.5143)	grad_norm 1.4813 (1.5826/0.7328)	mem 16099MB
[2025-01-18 01:27:15 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][250/312]	eta 0:00:29 lr 0.003393	time 0.4441 (0.4781)	model_time 0.4440 (0.4679)	loss 4.2825 (3.5218)	grad_norm 1.6390 (1.5866/0.7267)	mem 16099MB
[2025-01-18 01:27:20 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][260/312]	eta 0:00:24 lr 0.003393	time 0.4478 (0.4777)	model_time 0.4476 (0.4679)	loss 2.4658 (3.5197)	grad_norm 3.1054 (1.5927/0.7259)	mem 16099MB
[2025-01-18 01:27:25 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][270/312]	eta 0:00:20 lr 0.003392	time 0.5379 (0.4777)	model_time 0.5375 (0.4683)	loss 3.9137 (3.5271)	grad_norm 1.8281 (1.5963/0.7282)	mem 16099MB
[2025-01-18 01:27:29 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][280/312]	eta 0:00:15 lr 0.003392	time 0.4522 (0.4773)	model_time 0.4518 (0.4681)	loss 4.1465 (3.5240)	grad_norm 1.4091 (1.5827/0.7243)	mem 16099MB
[2025-01-18 01:27:34 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][290/312]	eta 0:00:10 lr 0.003391	time 0.4481 (0.4766)	model_time 0.4479 (0.4678)	loss 3.6908 (3.5238)	grad_norm 0.7634 (1.5692/0.7175)	mem 16099MB
[2025-01-18 01:27:39 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][300/312]	eta 0:00:05 lr 0.003391	time 0.4457 (0.4763)	model_time 0.4456 (0.4677)	loss 3.6050 (3.5307)	grad_norm 2.9506 (1.5775/0.7330)	mem 16099MB
[2025-01-18 01:27:43 internimage_t_1k_224] (main.py 510): INFO Train: [76/300][310/312]	eta 0:00:00 lr 0.003391	time 0.4470 (0.4752)	model_time 0.4469 (0.4669)	loss 3.7618 (3.5272)	grad_norm 0.7085 (1.5664/0.7275)	mem 16099MB
[2025-01-18 01:27:44 internimage_t_1k_224] (main.py 519): INFO EPOCH 76 training takes 0:02:28
[2025-01-18 01:27:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_76.pth saving......
[2025-01-18 01:27:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_76.pth saved !!!
[2025-01-18 01:27:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.639 (7.639)	Loss 0.9618 (0.9618)	Acc@1 79.004 (79.004)	Acc@5 95.532 (95.532)	Mem 16099MB
[2025-01-18 01:27:56 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.030)	Loss 1.3436 (1.1179)	Acc@1 69.409 (75.775)	Acc@5 90.527 (93.262)	Mem 16099MB
[2025-01-18 01:27:56 internimage_t_1k_224] (main.py 575): INFO [Epoch:76] * Acc@1 75.768 Acc@5 93.322
[2025-01-18 01:27:56 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.8%
[2025-01-18 01:27:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 01:27:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 01:27:57 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.77%
[2025-01-18 01:28:05 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.598 (7.598)	Loss 1.3237 (1.3237)	Acc@1 73.535 (73.535)	Acc@5 92.383 (92.383)	Mem 16099MB
[2025-01-18 01:28:09 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.025)	Loss 1.8245 (1.5270)	Acc@1 62.866 (69.418)	Acc@5 85.205 (89.380)	Mem 16099MB
[2025-01-18 01:28:09 internimage_t_1k_224] (main.py 575): INFO [Epoch:76] * Acc@1 69.380 Acc@5 89.455
[2025-01-18 01:28:09 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 69.4%
[2025-01-18 01:28:09 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:28:10 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:28:10 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 69.38%
[2025-01-18 01:28:13 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][0/312]	eta 0:14:34 lr 0.003390	time 2.8014 (2.8014)	model_time 0.4749 (0.4749)	loss 4.1393 (4.1393)	grad_norm 1.4801 (1.4801/0.0000)	mem 16099MB
[2025-01-18 01:28:18 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][10/312]	eta 0:03:24 lr 0.003390	time 0.4417 (0.6783)	model_time 0.4413 (0.4664)	loss 3.2865 (3.2413)	grad_norm 1.4902 (1.4361/0.5313)	mem 16099MB
[2025-01-18 01:28:22 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][20/312]	eta 0:02:47 lr 0.003389	time 0.4590 (0.5729)	model_time 0.4588 (0.4618)	loss 3.9782 (3.4473)	grad_norm 1.3688 (1.3103/0.4383)	mem 16099MB
[2025-01-18 01:28:27 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][30/312]	eta 0:02:32 lr 0.003389	time 0.4422 (0.5400)	model_time 0.4420 (0.4646)	loss 3.7855 (3.4989)	grad_norm 1.5290 (1.6534/0.9227)	mem 16099MB
[2025-01-18 01:28:32 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][40/312]	eta 0:02:21 lr 0.003389	time 0.4409 (0.5187)	model_time 0.4405 (0.4616)	loss 3.1228 (3.4626)	grad_norm 1.0982 (1.5555/0.8472)	mem 16099MB
[2025-01-18 01:28:36 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][50/312]	eta 0:02:13 lr 0.003388	time 0.5838 (0.5095)	model_time 0.5833 (0.4635)	loss 4.1665 (3.4701)	grad_norm 1.1116 (1.5656/0.7768)	mem 16099MB
[2025-01-18 01:28:41 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][60/312]	eta 0:02:07 lr 0.003388	time 0.4485 (0.5049)	model_time 0.4480 (0.4664)	loss 3.2422 (3.4688)	grad_norm 1.9038 (1.5552/0.7319)	mem 16099MB
[2025-01-18 01:28:46 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][70/312]	eta 0:02:00 lr 0.003387	time 0.4518 (0.4977)	model_time 0.4513 (0.4645)	loss 4.2261 (3.5280)	grad_norm 1.3085 (1.5136/0.6934)	mem 16099MB
[2025-01-18 01:28:50 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][80/312]	eta 0:01:54 lr 0.003387	time 0.4456 (0.4947)	model_time 0.4451 (0.4656)	loss 2.9644 (3.5252)	grad_norm 0.8198 (1.6089/0.8395)	mem 16099MB
[2025-01-18 01:28:55 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][90/312]	eta 0:01:49 lr 0.003386	time 0.4538 (0.4917)	model_time 0.4536 (0.4658)	loss 4.1535 (3.5225)	grad_norm 0.9436 (1.6021/0.8484)	mem 16099MB
[2025-01-18 01:29:00 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][100/312]	eta 0:01:44 lr 0.003386	time 0.4486 (0.4909)	model_time 0.4482 (0.4675)	loss 3.5952 (3.4973)	grad_norm 1.4728 (1.5859/0.8279)	mem 16099MB
[2025-01-18 01:29:05 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][110/312]	eta 0:01:39 lr 0.003385	time 0.4426 (0.4917)	model_time 0.4420 (0.4704)	loss 4.3995 (3.5060)	grad_norm 1.0605 (1.5286/0.8128)	mem 16099MB
[2025-01-18 01:29:10 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][120/312]	eta 0:01:33 lr 0.003385	time 0.4571 (0.4894)	model_time 0.4569 (0.4698)	loss 2.4599 (3.5260)	grad_norm 1.4728 (1.5137/0.7861)	mem 16099MB
[2025-01-18 01:29:14 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][130/312]	eta 0:01:28 lr 0.003384	time 0.4581 (0.4874)	model_time 0.4580 (0.4692)	loss 2.8366 (3.5211)	grad_norm 1.0944 (1.5139/0.7712)	mem 16099MB
[2025-01-18 01:29:19 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][140/312]	eta 0:01:23 lr 0.003384	time 0.4575 (0.4851)	model_time 0.4573 (0.4682)	loss 4.2107 (3.5476)	grad_norm 0.8169 (1.5028/0.7511)	mem 16099MB
[2025-01-18 01:29:23 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][150/312]	eta 0:01:18 lr 0.003383	time 0.5580 (0.4836)	model_time 0.5578 (0.4678)	loss 3.1289 (3.5256)	grad_norm 0.8052 (1.4879/0.7356)	mem 16099MB
[2025-01-18 01:29:28 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][160/312]	eta 0:01:13 lr 0.003383	time 0.4678 (0.4834)	model_time 0.4674 (0.4685)	loss 3.8099 (3.5370)	grad_norm 1.1388 (1.4771/0.7175)	mem 16099MB
[2025-01-18 01:29:33 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][170/312]	eta 0:01:08 lr 0.003382	time 0.4578 (0.4816)	model_time 0.4576 (0.4676)	loss 3.7274 (3.5361)	grad_norm 3.7502 (1.4960/0.7374)	mem 16099MB
[2025-01-18 01:29:37 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][180/312]	eta 0:01:03 lr 0.003382	time 0.4412 (0.4799)	model_time 0.4410 (0.4667)	loss 4.0148 (3.5374)	grad_norm 0.9456 (1.5086/0.7595)	mem 16099MB
[2025-01-18 01:29:42 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][190/312]	eta 0:00:58 lr 0.003381	time 0.4402 (0.4791)	model_time 0.4400 (0.4665)	loss 2.7392 (3.5373)	grad_norm 0.9165 (1.4936/0.7474)	mem 16099MB
[2025-01-18 01:29:47 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][200/312]	eta 0:00:53 lr 0.003381	time 0.4531 (0.4789)	model_time 0.4526 (0.4669)	loss 3.7794 (3.5355)	grad_norm 0.8176 (1.4892/0.7384)	mem 16099MB
[2025-01-18 01:29:52 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][210/312]	eta 0:00:49 lr 0.003380	time 0.4547 (0.4808)	model_time 0.4543 (0.4694)	loss 3.5818 (3.5214)	grad_norm 1.1403 (1.4947/0.7432)	mem 16099MB
[2025-01-18 01:29:56 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][220/312]	eta 0:00:44 lr 0.003380	time 0.4543 (0.4797)	model_time 0.4538 (0.4688)	loss 3.8734 (3.5250)	grad_norm 1.5732 (1.5104/0.7444)	mem 16099MB
[2025-01-18 01:30:01 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][230/312]	eta 0:00:39 lr 0.003379	time 0.5457 (0.4795)	model_time 0.5452 (0.4690)	loss 3.4486 (3.5232)	grad_norm 0.8695 (1.5070/0.7363)	mem 16099MB
[2025-01-18 01:30:06 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][240/312]	eta 0:00:34 lr 0.003379	time 0.4405 (0.4784)	model_time 0.4403 (0.4683)	loss 3.8232 (3.5336)	grad_norm 1.6892 (1.5081/0.7264)	mem 16099MB
[2025-01-18 01:30:10 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][250/312]	eta 0:00:29 lr 0.003378	time 0.4482 (0.4784)	model_time 0.4478 (0.4688)	loss 3.8232 (3.5336)	grad_norm 1.2741 (1.4875/0.7200)	mem 16099MB
[2025-01-18 01:30:15 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][260/312]	eta 0:00:24 lr 0.003378	time 0.4684 (0.4777)	model_time 0.4680 (0.4684)	loss 3.0768 (3.5305)	grad_norm 1.7774 (1.5002/0.7216)	mem 16099MB
[2025-01-18 01:30:20 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][270/312]	eta 0:00:20 lr 0.003377	time 0.4670 (0.4781)	model_time 0.4666 (0.4691)	loss 3.7710 (3.5294)	grad_norm 1.2827 (1.4887/0.7123)	mem 16099MB
[2025-01-18 01:30:24 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][280/312]	eta 0:00:15 lr 0.003377	time 0.4595 (0.4772)	model_time 0.4589 (0.4686)	loss 3.9293 (3.5370)	grad_norm 1.9878 (1.4954/0.7100)	mem 16099MB
[2025-01-18 01:30:29 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][290/312]	eta 0:00:10 lr 0.003376	time 0.4565 (0.4774)	model_time 0.4561 (0.4690)	loss 3.5283 (3.5399)	grad_norm 2.5276 (1.5019/0.7070)	mem 16099MB
[2025-01-18 01:30:34 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][300/312]	eta 0:00:05 lr 0.003376	time 0.4374 (0.4772)	model_time 0.4373 (0.4691)	loss 3.5697 (3.5447)	grad_norm 0.8407 (1.4930/0.7054)	mem 16099MB
[2025-01-18 01:30:38 internimage_t_1k_224] (main.py 510): INFO Train: [77/300][310/312]	eta 0:00:00 lr 0.003376	time 0.4381 (0.4764)	model_time 0.4380 (0.4685)	loss 2.8212 (3.5412)	grad_norm 2.0758 (1.5045/0.7071)	mem 16099MB
[2025-01-18 01:30:39 internimage_t_1k_224] (main.py 519): INFO EPOCH 77 training takes 0:02:28
[2025-01-18 01:30:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_77.pth saving......
[2025-01-18 01:30:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_77.pth saved !!!
[2025-01-18 01:30:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.489 (7.489)	Loss 0.9549 (0.9549)	Acc@1 79.712 (79.712)	Acc@5 95.117 (95.117)	Mem 16099MB
[2025-01-18 01:30:51 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.034)	Loss 1.3437 (1.1387)	Acc@1 71.240 (75.890)	Acc@5 90.625 (93.264)	Mem 16099MB
[2025-01-18 01:30:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:77] * Acc@1 75.818 Acc@5 93.366
[2025-01-18 01:30:52 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.8%
[2025-01-18 01:30:52 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 01:30:53 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 01:30:53 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.82%
[2025-01-18 01:31:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.523 (7.523)	Loss 1.2950 (1.2950)	Acc@1 73.926 (73.926)	Acc@5 92.627 (92.627)	Mem 16099MB
[2025-01-18 01:31:04 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.028)	Loss 1.7933 (1.4977)	Acc@1 63.428 (69.951)	Acc@5 85.669 (89.682)	Mem 16099MB
[2025-01-18 01:31:04 internimage_t_1k_224] (main.py 575): INFO [Epoch:77] * Acc@1 69.910 Acc@5 89.751
[2025-01-18 01:31:04 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 69.9%
[2025-01-18 01:31:04 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:31:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:31:06 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 69.91%
[2025-01-18 01:31:08 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][0/312]	eta 0:14:26 lr 0.003375	time 2.7788 (2.7788)	model_time 0.4569 (0.4569)	loss 2.3225 (2.3225)	grad_norm 2.5142 (2.5142/0.0000)	mem 16099MB
[2025-01-18 01:31:13 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][10/312]	eta 0:03:26 lr 0.003375	time 0.4447 (0.6821)	model_time 0.4445 (0.4707)	loss 3.6421 (3.4998)	grad_norm 1.3840 (1.7283/0.4949)	mem 16099MB
[2025-01-18 01:31:18 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][20/312]	eta 0:02:49 lr 0.003374	time 0.4905 (0.5789)	model_time 0.4903 (0.4680)	loss 3.2411 (3.3555)	grad_norm 2.3408 (1.6119/0.4938)	mem 16099MB
[2025-01-18 01:31:23 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][30/312]	eta 0:02:33 lr 0.003374	time 0.4496 (0.5439)	model_time 0.4494 (0.4687)	loss 2.5431 (3.4098)	grad_norm 2.6220 (1.6314/0.6453)	mem 16099MB
[2025-01-18 01:31:27 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][40/312]	eta 0:02:22 lr 0.003373	time 0.4667 (0.5237)	model_time 0.4663 (0.4667)	loss 3.2711 (3.4443)	grad_norm 1.2995 (1.7121/0.6670)	mem 16099MB
[2025-01-18 01:31:32 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][50/312]	eta 0:02:13 lr 0.003373	time 0.4494 (0.5114)	model_time 0.4492 (0.4655)	loss 2.9889 (3.4024)	grad_norm 0.9035 (1.6216/0.6333)	mem 16099MB
[2025-01-18 01:31:36 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][60/312]	eta 0:02:07 lr 0.003372	time 0.4450 (0.5053)	model_time 0.4449 (0.4669)	loss 4.2313 (3.4555)	grad_norm 1.2890 (1.5768/0.6061)	mem 16099MB
[2025-01-18 01:31:41 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][70/312]	eta 0:02:00 lr 0.003372	time 0.4528 (0.4980)	model_time 0.4524 (0.4649)	loss 4.1877 (3.4663)	grad_norm 0.8619 (1.5274/0.6026)	mem 16099MB
[2025-01-18 01:31:46 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][80/312]	eta 0:01:54 lr 0.003372	time 0.4485 (0.4926)	model_time 0.4484 (0.4636)	loss 2.6461 (3.4868)	grad_norm 1.4189 (1.5772/0.6670)	mem 16099MB
[2025-01-18 01:31:50 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][90/312]	eta 0:01:48 lr 0.003371	time 0.4452 (0.4895)	model_time 0.4447 (0.4637)	loss 4.1045 (3.4715)	grad_norm 0.9740 (1.5346/0.6493)	mem 16099MB
[2025-01-18 01:31:55 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][100/312]	eta 0:01:43 lr 0.003371	time 0.5036 (0.4872)	model_time 0.5034 (0.4638)	loss 2.1456 (3.4551)	grad_norm 1.3228 (1.5124/0.6248)	mem 16099MB
[2025-01-18 01:32:00 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][110/312]	eta 0:01:38 lr 0.003370	time 0.4418 (0.4866)	model_time 0.4417 (0.4653)	loss 3.5778 (3.4397)	grad_norm 1.3038 (1.5030/0.6120)	mem 16099MB
[2025-01-18 01:32:04 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][120/312]	eta 0:01:32 lr 0.003370	time 0.4542 (0.4842)	model_time 0.4540 (0.4647)	loss 4.4010 (3.4243)	grad_norm 0.9713 (1.5299/0.6467)	mem 16099MB
[2025-01-18 01:32:09 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][130/312]	eta 0:01:27 lr 0.003369	time 0.5441 (0.4832)	model_time 0.5436 (0.4651)	loss 3.8598 (3.4291)	grad_norm 0.6914 (1.4962/0.6398)	mem 16099MB
[2025-01-18 01:32:14 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][140/312]	eta 0:01:22 lr 0.003369	time 0.4441 (0.4817)	model_time 0.4439 (0.4648)	loss 4.4596 (3.4491)	grad_norm 1.6032 (1.5059/0.6600)	mem 16099MB
[2025-01-18 01:32:18 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][150/312]	eta 0:01:17 lr 0.003368	time 0.4557 (0.4808)	model_time 0.4553 (0.4651)	loss 2.7726 (3.4453)	grad_norm 1.1405 (1.5173/0.6607)	mem 16099MB
[2025-01-18 01:32:23 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][160/312]	eta 0:01:12 lr 0.003368	time 0.4535 (0.4801)	model_time 0.4531 (0.4653)	loss 2.4567 (3.4552)	grad_norm 3.9884 (1.5358/0.6806)	mem 16099MB
[2025-01-18 01:32:28 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][170/312]	eta 0:01:07 lr 0.003367	time 0.4426 (0.4788)	model_time 0.4421 (0.4649)	loss 3.5092 (3.4608)	grad_norm 1.4870 (1.5500/0.6985)	mem 16099MB
[2025-01-18 01:32:32 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][180/312]	eta 0:01:03 lr 0.003367	time 0.4425 (0.4796)	model_time 0.4420 (0.4664)	loss 3.8092 (3.4634)	grad_norm 2.0307 (1.5419/0.6925)	mem 16099MB
[2025-01-18 01:32:37 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][190/312]	eta 0:00:58 lr 0.003366	time 0.4532 (0.4783)	model_time 0.4530 (0.4658)	loss 3.8267 (3.4673)	grad_norm 1.4159 (1.5627/0.7089)	mem 16099MB
[2025-01-18 01:32:42 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][200/312]	eta 0:00:53 lr 0.003366	time 0.4656 (0.4779)	model_time 0.4655 (0.4660)	loss 4.5844 (3.4819)	grad_norm 1.2034 (1.5512/0.7055)	mem 16099MB
[2025-01-18 01:32:46 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][210/312]	eta 0:00:48 lr 0.003365	time 0.4537 (0.4769)	model_time 0.4533 (0.4654)	loss 4.0291 (3.4930)	grad_norm 1.2125 (1.5467/0.6921)	mem 16099MB
[2025-01-18 01:32:51 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][220/312]	eta 0:00:43 lr 0.003365	time 0.4478 (0.4773)	model_time 0.4477 (0.4663)	loss 4.2933 (3.4943)	grad_norm 1.8122 (1.5505/0.6813)	mem 16099MB
[2025-01-18 01:32:56 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][230/312]	eta 0:00:39 lr 0.003364	time 0.4455 (0.4780)	model_time 0.4451 (0.4675)	loss 3.6018 (3.4902)	grad_norm 1.2123 (1.5410/0.6809)	mem 16099MB
[2025-01-18 01:33:01 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][240/312]	eta 0:00:34 lr 0.003364	time 0.4405 (0.4770)	model_time 0.4404 (0.4669)	loss 3.7775 (3.4991)	grad_norm 0.9924 (1.5517/0.6909)	mem 16099MB
[2025-01-18 01:33:05 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][250/312]	eta 0:00:29 lr 0.003363	time 0.4655 (0.4764)	model_time 0.4651 (0.4668)	loss 2.7457 (3.4977)	grad_norm 1.2489 (1.5413/0.6886)	mem 16099MB
[2025-01-18 01:33:10 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][260/312]	eta 0:00:24 lr 0.003363	time 0.4577 (0.4764)	model_time 0.4575 (0.4671)	loss 3.7651 (3.5035)	grad_norm 1.1829 (1.5419/0.6873)	mem 16099MB
[2025-01-18 01:33:15 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][270/312]	eta 0:00:19 lr 0.003362	time 0.4518 (0.4760)	model_time 0.4514 (0.4670)	loss 2.7169 (3.4979)	grad_norm 1.5530 (1.5565/0.7048)	mem 16099MB
[2025-01-18 01:33:19 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][280/312]	eta 0:00:15 lr 0.003362	time 0.4520 (0.4751)	model_time 0.4515 (0.4664)	loss 3.8436 (3.4945)	grad_norm 1.2489 (1.5404/0.6988)	mem 16099MB
[2025-01-18 01:33:24 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][290/312]	eta 0:00:10 lr 0.003361	time 0.4590 (0.4745)	model_time 0.4585 (0.4661)	loss 3.8461 (3.5059)	grad_norm 1.1499 (1.5247/0.6936)	mem 16099MB
[2025-01-18 01:33:28 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][300/312]	eta 0:00:05 lr 0.003361	time 0.4388 (0.4744)	model_time 0.4387 (0.4663)	loss 3.2322 (3.5093)	grad_norm 2.5728 (1.5174/0.6879)	mem 16099MB
[2025-01-18 01:33:33 internimage_t_1k_224] (main.py 510): INFO Train: [78/300][310/312]	eta 0:00:00 lr 0.003360	time 0.4385 (0.4737)	model_time 0.4385 (0.4658)	loss 3.5190 (3.5118)	grad_norm 2.1376 (1.5205/0.7010)	mem 16099MB
[2025-01-18 01:33:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 78 training takes 0:02:27
[2025-01-18 01:33:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_78.pth saving......
[2025-01-18 01:33:35 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_78.pth saved !!!
[2025-01-18 01:33:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.504 (7.504)	Loss 0.9367 (0.9367)	Acc@1 79.102 (79.102)	Acc@5 95.435 (95.435)	Mem 16099MB
[2025-01-18 01:33:46 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.020)	Loss 1.3617 (1.1351)	Acc@1 70.190 (75.699)	Acc@5 90.845 (93.237)	Mem 16099MB
[2025-01-18 01:33:46 internimage_t_1k_224] (main.py 575): INFO [Epoch:78] * Acc@1 75.650 Acc@5 93.286
[2025-01-18 01:33:46 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.6%
[2025-01-18 01:33:46 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 75.82%
[2025-01-18 01:33:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.508 (8.508)	Loss 1.2674 (1.2674)	Acc@1 74.316 (74.316)	Acc@5 92.749 (92.749)	Mem 16099MB
[2025-01-18 01:33:59 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.145)	Loss 1.7631 (1.4692)	Acc@1 64.014 (70.415)	Acc@5 86.182 (89.981)	Mem 16099MB
[2025-01-18 01:33:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:78] * Acc@1 70.385 Acc@5 90.049
[2025-01-18 01:33:59 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 70.4%
[2025-01-18 01:33:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:34:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:34:00 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 70.39%
[2025-01-18 01:34:03 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][0/312]	eta 0:11:55 lr 0.003360	time 2.2942 (2.2942)	model_time 0.4558 (0.4558)	loss 3.1823 (3.1823)	grad_norm 4.0668 (4.0668/0.0000)	mem 16099MB
[2025-01-18 01:34:07 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][10/312]	eta 0:03:09 lr 0.003360	time 0.4462 (0.6279)	model_time 0.4458 (0.4604)	loss 4.5433 (3.7384)	grad_norm 0.8441 (1.6787/0.9907)	mem 16099MB
[2025-01-18 01:34:12 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][20/312]	eta 0:02:44 lr 0.003359	time 0.4519 (0.5639)	model_time 0.4514 (0.4760)	loss 2.6829 (3.6737)	grad_norm 1.7001 (1.7657/0.8234)	mem 16099MB
[2025-01-18 01:34:17 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][30/312]	eta 0:02:29 lr 0.003359	time 0.4527 (0.5308)	model_time 0.4526 (0.4712)	loss 4.0520 (3.5921)	grad_norm 1.5299 (1.7703/0.8266)	mem 16099MB
[2025-01-18 01:34:21 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][40/312]	eta 0:02:19 lr 0.003358	time 0.4550 (0.5143)	model_time 0.4548 (0.4691)	loss 3.3383 (3.5914)	grad_norm 0.6584 (1.7260/0.7825)	mem 16099MB
[2025-01-18 01:34:26 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][50/312]	eta 0:02:12 lr 0.003358	time 0.4459 (0.5039)	model_time 0.4457 (0.4674)	loss 4.1889 (3.5883)	grad_norm 1.6518 (1.6616/0.7230)	mem 16099MB
[2025-01-18 01:34:31 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][60/312]	eta 0:02:05 lr 0.003357	time 0.4402 (0.4974)	model_time 0.4396 (0.4668)	loss 2.7104 (3.5500)	grad_norm 2.4900 (1.6392/0.6949)	mem 16099MB
[2025-01-18 01:34:36 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][70/312]	eta 0:02:00 lr 0.003357	time 0.7909 (0.4959)	model_time 0.7907 (0.4697)	loss 3.8984 (3.5492)	grad_norm 1.2847 (1.6676/0.6692)	mem 16099MB
[2025-01-18 01:34:40 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][80/312]	eta 0:01:54 lr 0.003356	time 0.4489 (0.4916)	model_time 0.4487 (0.4686)	loss 3.5163 (3.5467)	grad_norm 1.0350 (1.6802/0.6765)	mem 16099MB
[2025-01-18 01:34:45 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][90/312]	eta 0:01:48 lr 0.003356	time 0.4537 (0.4887)	model_time 0.4533 (0.4681)	loss 3.6261 (3.6001)	grad_norm 1.1258 (1.6475/0.6585)	mem 16099MB
[2025-01-18 01:34:49 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][100/312]	eta 0:01:43 lr 0.003355	time 0.5296 (0.4859)	model_time 0.5292 (0.4674)	loss 3.5817 (3.6220)	grad_norm 1.6180 (1.6632/0.6646)	mem 16099MB
[2025-01-18 01:34:54 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][110/312]	eta 0:01:38 lr 0.003355	time 0.4514 (0.4866)	model_time 0.4512 (0.4697)	loss 4.2903 (3.6203)	grad_norm 1.7164 (1.6240/0.6527)	mem 16099MB
[2025-01-18 01:34:59 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][120/312]	eta 0:01:33 lr 0.003354	time 0.4692 (0.4848)	model_time 0.4690 (0.4692)	loss 3.1163 (3.6172)	grad_norm 2.8265 (1.6314/0.6509)	mem 16099MB
[2025-01-18 01:35:03 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][130/312]	eta 0:01:27 lr 0.003354	time 0.4489 (0.4823)	model_time 0.4485 (0.4679)	loss 4.2659 (3.6315)	grad_norm 1.8954 (1.6277/0.6630)	mem 16099MB
[2025-01-18 01:35:08 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][140/312]	eta 0:01:22 lr 0.003353	time 0.4496 (0.4814)	model_time 0.4494 (0.4679)	loss 3.1134 (3.5771)	grad_norm 1.6779 (1.6004/0.6518)	mem 16099MB
[2025-01-18 01:35:13 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][150/312]	eta 0:01:17 lr 0.003353	time 0.4397 (0.4796)	model_time 0.4393 (0.4670)	loss 2.3761 (3.5706)	grad_norm 0.9557 (1.6079/0.6676)	mem 16099MB
[2025-01-18 01:35:17 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][160/312]	eta 0:01:12 lr 0.003352	time 0.4396 (0.4790)	model_time 0.4394 (0.4672)	loss 2.5313 (3.5590)	grad_norm 2.1411 (1.6037/0.6642)	mem 16099MB
[2025-01-18 01:35:22 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][170/312]	eta 0:01:07 lr 0.003352	time 0.4446 (0.4784)	model_time 0.4445 (0.4672)	loss 3.8124 (3.5631)	grad_norm 1.0247 (1.5955/0.6635)	mem 16099MB
[2025-01-18 01:35:27 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][180/312]	eta 0:01:03 lr 0.003351	time 0.6064 (0.4783)	model_time 0.6062 (0.4678)	loss 3.0552 (3.5567)	grad_norm 1.2521 (1.6013/0.6881)	mem 16099MB
[2025-01-18 01:35:31 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][190/312]	eta 0:00:58 lr 0.003351	time 0.4660 (0.4774)	model_time 0.4658 (0.4674)	loss 3.6441 (3.5522)	grad_norm 1.5829 (1.5985/0.6714)	mem 16099MB
[2025-01-18 01:35:36 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][200/312]	eta 0:00:53 lr 0.003350	time 0.4579 (0.4770)	model_time 0.4574 (0.4674)	loss 3.9882 (3.5526)	grad_norm 2.0816 (1.5816/0.6634)	mem 16099MB
[2025-01-18 01:35:41 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][210/312]	eta 0:00:48 lr 0.003350	time 0.4581 (0.4766)	model_time 0.4576 (0.4675)	loss 3.7515 (3.5567)	grad_norm 1.9330 (1.5927/0.6646)	mem 16099MB
[2025-01-18 01:35:45 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][220/312]	eta 0:00:43 lr 0.003349	time 0.4932 (0.4758)	model_time 0.4930 (0.4671)	loss 4.4870 (3.5646)	grad_norm 2.7543 (1.6161/0.6784)	mem 16099MB
[2025-01-18 01:35:50 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][230/312]	eta 0:00:38 lr 0.003349	time 0.4548 (0.4749)	model_time 0.4544 (0.4666)	loss 2.9670 (3.5601)	grad_norm 2.5663 (1.6343/0.7051)	mem 16099MB
[2025-01-18 01:35:55 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][240/312]	eta 0:00:34 lr 0.003348	time 0.4503 (0.4740)	model_time 0.4501 (0.4659)	loss 4.0737 (3.5679)	grad_norm 1.0196 (1.6177/0.7006)	mem 16099MB
[2025-01-18 01:35:59 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][250/312]	eta 0:00:29 lr 0.003348	time 0.4396 (0.4731)	model_time 0.4391 (0.4654)	loss 3.8266 (3.5544)	grad_norm 0.8428 (1.5916/0.6998)	mem 16099MB
[2025-01-18 01:36:04 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][260/312]	eta 0:00:24 lr 0.003347	time 0.4507 (0.4729)	model_time 0.4503 (0.4655)	loss 3.3472 (3.5472)	grad_norm 0.7806 (1.5797/0.6937)	mem 16099MB
[2025-01-18 01:36:08 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][270/312]	eta 0:00:19 lr 0.003347	time 0.4631 (0.4723)	model_time 0.4627 (0.4652)	loss 3.3850 (3.5387)	grad_norm 1.5527 (1.5756/0.6873)	mem 16099MB
[2025-01-18 01:36:13 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][280/312]	eta 0:00:15 lr 0.003346	time 0.5609 (0.4723)	model_time 0.5607 (0.4654)	loss 3.7141 (3.5401)	grad_norm 1.3092 (1.5623/0.6806)	mem 16099MB
[2025-01-18 01:36:18 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][290/312]	eta 0:00:10 lr 0.003346	time 0.4414 (0.4723)	model_time 0.4413 (0.4656)	loss 2.2943 (3.5347)	grad_norm 5.0406 (1.6002/0.7461)	mem 16099MB
[2025-01-18 01:36:22 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][300/312]	eta 0:00:05 lr 0.003345	time 0.4370 (0.4723)	model_time 0.4369 (0.4658)	loss 2.9828 (3.5416)	grad_norm 1.1668 (1.5949/0.7280)	mem 16099MB
[2025-01-18 01:36:27 internimage_t_1k_224] (main.py 510): INFO Train: [79/300][310/312]	eta 0:00:00 lr 0.003345	time 0.4393 (0.4720)	model_time 0.4392 (0.4657)	loss 3.5757 (3.5491)	grad_norm 2.4199 (1.5934/0.7244)	mem 16099MB
[2025-01-18 01:36:28 internimage_t_1k_224] (main.py 519): INFO EPOCH 79 training takes 0:02:27
[2025-01-18 01:36:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_79.pth saving......
[2025-01-18 01:36:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_79.pth saved !!!
[2025-01-18 01:36:36 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.433 (7.433)	Loss 0.9261 (0.9261)	Acc@1 79.590 (79.590)	Acc@5 95.386 (95.386)	Mem 16099MB
[2025-01-18 01:36:40 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.016)	Loss 1.2776 (1.0959)	Acc@1 71.826 (76.194)	Acc@5 91.089 (93.388)	Mem 16099MB
[2025-01-18 01:36:40 internimage_t_1k_224] (main.py 575): INFO [Epoch:79] * Acc@1 76.128 Acc@5 93.422
[2025-01-18 01:36:40 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.1%
[2025-01-18 01:36:40 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 01:36:41 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 01:36:41 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.13%
[2025-01-18 01:36:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.171 (7.171)	Loss 1.2403 (1.2403)	Acc@1 74.780 (74.780)	Acc@5 93.115 (93.115)	Mem 16099MB
[2025-01-18 01:36:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.991)	Loss 1.7340 (1.4421)	Acc@1 64.526 (70.872)	Acc@5 86.377 (90.248)	Mem 16099MB
[2025-01-18 01:36:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:79] * Acc@1 70.843 Acc@5 90.311
[2025-01-18 01:36:52 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 70.8%
[2025-01-18 01:36:52 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:36:54 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:36:54 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 70.84%
[2025-01-18 01:36:56 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][0/312]	eta 0:11:52 lr 0.003345	time 2.2825 (2.2825)	model_time 0.5219 (0.5219)	loss 3.8037 (3.8037)	grad_norm 1.0003 (1.0003/0.0000)	mem 16099MB
[2025-01-18 01:37:01 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][10/312]	eta 0:03:12 lr 0.003344	time 0.5336 (0.6362)	model_time 0.5334 (0.4758)	loss 4.2216 (3.4978)	grad_norm 1.1291 (1.0769/0.2963)	mem 16099MB
[2025-01-18 01:37:05 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][20/312]	eta 0:02:41 lr 0.003344	time 0.5441 (0.5531)	model_time 0.5440 (0.4689)	loss 3.3655 (3.6452)	grad_norm 1.2192 (1.3994/0.5688)	mem 16099MB
[2025-01-18 01:37:10 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][30/312]	eta 0:02:28 lr 0.003343	time 0.5344 (0.5268)	model_time 0.5340 (0.4696)	loss 3.0874 (3.5130)	grad_norm 1.6257 (1.3821/0.5232)	mem 16099MB
[2025-01-18 01:37:15 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][40/312]	eta 0:02:19 lr 0.003343	time 0.4414 (0.5121)	model_time 0.4413 (0.4688)	loss 3.8059 (3.5518)	grad_norm 0.8664 (1.3447/0.5182)	mem 16099MB
[2025-01-18 01:37:19 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][50/312]	eta 0:02:11 lr 0.003342	time 0.4410 (0.5012)	model_time 0.4409 (0.4664)	loss 4.2794 (3.5666)	grad_norm 1.1583 (1.3147/0.5210)	mem 16099MB
[2025-01-18 01:37:24 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][60/312]	eta 0:02:04 lr 0.003342	time 0.5420 (0.4959)	model_time 0.5415 (0.4667)	loss 3.2249 (3.5403)	grad_norm 1.4765 (1.4213/0.6209)	mem 16099MB
[2025-01-18 01:37:29 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][70/312]	eta 0:01:58 lr 0.003341	time 0.4920 (0.4907)	model_time 0.4918 (0.4655)	loss 2.9553 (3.5551)	grad_norm 1.1584 (1.4949/0.6718)	mem 16099MB
[2025-01-18 01:37:33 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][80/312]	eta 0:01:52 lr 0.003341	time 0.5352 (0.4870)	model_time 0.5350 (0.4650)	loss 2.9625 (3.5692)	grad_norm 0.9211 (1.4847/0.6496)	mem 16099MB
[2025-01-18 01:37:38 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][90/312]	eta 0:01:47 lr 0.003340	time 0.4403 (0.4851)	model_time 0.4398 (0.4654)	loss 4.4012 (3.5570)	grad_norm 1.8710 (1.4739/0.6365)	mem 16099MB
[2025-01-18 01:37:42 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][100/312]	eta 0:01:42 lr 0.003340	time 0.4568 (0.4828)	model_time 0.4564 (0.4650)	loss 2.5650 (3.5176)	grad_norm 1.4725 (1.4627/0.6213)	mem 16099MB
[2025-01-18 01:37:47 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][110/312]	eta 0:01:37 lr 0.003339	time 0.4516 (0.4817)	model_time 0.4514 (0.4655)	loss 2.4944 (3.5053)	grad_norm 1.6938 (1.4420/0.6046)	mem 16099MB
[2025-01-18 01:37:52 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][120/312]	eta 0:01:32 lr 0.003339	time 0.4698 (0.4814)	model_time 0.4697 (0.4665)	loss 3.1280 (3.5028)	grad_norm 1.3023 (1.4643/0.6354)	mem 16099MB
[2025-01-18 01:37:57 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][130/312]	eta 0:01:27 lr 0.003338	time 0.4433 (0.4801)	model_time 0.4428 (0.4663)	loss 3.5856 (3.5126)	grad_norm 1.6019 (1.5033/0.6622)	mem 16099MB
[2025-01-18 01:38:01 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][140/312]	eta 0:01:22 lr 0.003338	time 0.4417 (0.4782)	model_time 0.4412 (0.4653)	loss 3.7209 (3.5107)	grad_norm 1.5452 (1.5019/0.6571)	mem 16099MB
[2025-01-18 01:38:06 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][150/312]	eta 0:01:17 lr 0.003337	time 0.4484 (0.4791)	model_time 0.4480 (0.4671)	loss 2.9741 (3.4955)	grad_norm 1.6350 (1.4938/0.6674)	mem 16099MB
[2025-01-18 01:38:11 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][160/312]	eta 0:01:13 lr 0.003337	time 0.4418 (0.4803)	model_time 0.4414 (0.4690)	loss 3.4371 (3.4607)	grad_norm 0.8729 (1.4810/0.6586)	mem 16099MB
[2025-01-18 01:38:16 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][170/312]	eta 0:01:08 lr 0.003336	time 0.5419 (0.4798)	model_time 0.5417 (0.4692)	loss 4.4164 (3.4698)	grad_norm 1.4097 (1.4850/0.6485)	mem 16099MB
[2025-01-18 01:38:20 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][180/312]	eta 0:01:03 lr 0.003336	time 0.5636 (0.4794)	model_time 0.5632 (0.4693)	loss 3.7184 (3.4647)	grad_norm 0.9863 (1.4838/0.6374)	mem 16099MB
[2025-01-18 01:38:25 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][190/312]	eta 0:00:58 lr 0.003335	time 0.5771 (0.4788)	model_time 0.5770 (0.4692)	loss 2.8057 (3.4620)	grad_norm 1.6216 (1.4859/0.6268)	mem 16099MB
[2025-01-18 01:38:30 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][200/312]	eta 0:00:53 lr 0.003335	time 0.4469 (0.4784)	model_time 0.4465 (0.4692)	loss 3.4709 (3.4560)	grad_norm 1.0560 (1.4782/0.6188)	mem 16099MB
[2025-01-18 01:38:35 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][210/312]	eta 0:00:48 lr 0.003334	time 0.4549 (0.4777)	model_time 0.4547 (0.4690)	loss 3.4267 (3.4650)	grad_norm 1.2000 (1.4636/0.6135)	mem 16099MB
[2025-01-18 01:38:39 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][220/312]	eta 0:00:43 lr 0.003334	time 0.4558 (0.4771)	model_time 0.4554 (0.4687)	loss 3.9077 (3.4691)	grad_norm 1.0581 (1.4847/0.6263)	mem 16099MB
[2025-01-18 01:38:44 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][230/312]	eta 0:00:39 lr 0.003333	time 0.4591 (0.4769)	model_time 0.4587 (0.4689)	loss 2.6128 (3.4559)	grad_norm 1.9415 (1.4862/0.6206)	mem 16099MB
[2025-01-18 01:38:49 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][240/312]	eta 0:00:34 lr 0.003333	time 0.5489 (0.4765)	model_time 0.5488 (0.4688)	loss 3.8583 (3.4661)	grad_norm 1.5718 (1.4763/0.6158)	mem 16099MB
[2025-01-18 01:38:53 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][250/312]	eta 0:00:29 lr 0.003332	time 0.4393 (0.4756)	model_time 0.4389 (0.4682)	loss 3.0710 (3.4793)	grad_norm 2.1010 (1.4937/0.6204)	mem 16099MB
[2025-01-18 01:38:58 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][260/312]	eta 0:00:24 lr 0.003332	time 0.4554 (0.4755)	model_time 0.4550 (0.4684)	loss 3.1915 (3.4941)	grad_norm 0.8677 (1.4833/0.6146)	mem 16099MB
[2025-01-18 01:39:03 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][270/312]	eta 0:00:19 lr 0.003331	time 0.4441 (0.4756)	model_time 0.4437 (0.4687)	loss 2.8492 (3.4994)	grad_norm 1.2782 (1.4814/0.6071)	mem 16099MB
[2025-01-18 01:39:07 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][280/312]	eta 0:00:15 lr 0.003331	time 0.4484 (0.4748)	model_time 0.4479 (0.4681)	loss 2.4222 (3.5011)	grad_norm 4.3883 (1.4875/0.6257)	mem 16099MB
[2025-01-18 01:39:12 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][290/312]	eta 0:00:10 lr 0.003330	time 0.4876 (0.4744)	model_time 0.4870 (0.4680)	loss 3.5778 (3.5040)	grad_norm 0.8866 (1.5017/0.6432)	mem 16099MB
[2025-01-18 01:39:16 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][300/312]	eta 0:00:05 lr 0.003330	time 0.4420 (0.4738)	model_time 0.4418 (0.4675)	loss 2.6113 (3.5027)	grad_norm 1.1052 (1.5038/0.6395)	mem 16099MB
[2025-01-18 01:39:21 internimage_t_1k_224] (main.py 510): INFO Train: [80/300][310/312]	eta 0:00:00 lr 0.003329	time 0.5318 (0.4733)	model_time 0.5317 (0.4673)	loss 3.5765 (3.5018)	grad_norm 2.5194 (1.5170/0.6409)	mem 16099MB
[2025-01-18 01:39:21 internimage_t_1k_224] (main.py 519): INFO EPOCH 80 training takes 0:02:27
[2025-01-18 01:39:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_80.pth saving......
[2025-01-18 01:39:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_80.pth saved !!!
[2025-01-18 01:39:30 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.578 (7.578)	Loss 0.9735 (0.9735)	Acc@1 78.882 (78.882)	Acc@5 95.410 (95.410)	Mem 16099MB
[2025-01-18 01:39:34 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.009)	Loss 1.3802 (1.1482)	Acc@1 69.849 (75.892)	Acc@5 90.161 (93.237)	Mem 16099MB
[2025-01-18 01:39:34 internimage_t_1k_224] (main.py 575): INFO [Epoch:80] * Acc@1 75.838 Acc@5 93.312
[2025-01-18 01:39:34 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.8%
[2025-01-18 01:39:34 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.13%
[2025-01-18 01:39:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.307 (8.307)	Loss 1.2152 (1.2152)	Acc@1 75.049 (75.049)	Acc@5 93.262 (93.262)	Mem 16099MB
[2025-01-18 01:39:46 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.116)	Loss 1.7055 (1.4159)	Acc@1 64.941 (71.258)	Acc@5 86.743 (90.470)	Mem 16099MB
[2025-01-18 01:39:46 internimage_t_1k_224] (main.py 575): INFO [Epoch:80] * Acc@1 71.241 Acc@5 90.533
[2025-01-18 01:39:46 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 71.2%
[2025-01-18 01:39:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:39:48 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:39:48 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 71.24%
[2025-01-18 01:39:50 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][0/312]	eta 0:14:12 lr 0.003329	time 2.7313 (2.7313)	model_time 0.4673 (0.4673)	loss 4.2685 (4.2685)	grad_norm 2.4232 (2.4232/0.0000)	mem 16099MB
[2025-01-18 01:39:55 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][10/312]	eta 0:03:26 lr 0.003329	time 0.4453 (0.6849)	model_time 0.4452 (0.4787)	loss 3.6520 (3.6227)	grad_norm 1.9751 (1.6584/0.6241)	mem 16099MB
[2025-01-18 01:40:00 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][20/312]	eta 0:02:49 lr 0.003328	time 0.4473 (0.5789)	model_time 0.4471 (0.4708)	loss 3.4653 (3.5105)	grad_norm 2.0557 (1.5279/0.5585)	mem 16099MB
[2025-01-18 01:40:05 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][30/312]	eta 0:02:33 lr 0.003328	time 0.4452 (0.5444)	model_time 0.4451 (0.4711)	loss 3.5406 (3.5438)	grad_norm 1.7753 (1.4597/0.5101)	mem 16099MB
[2025-01-18 01:40:09 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][40/312]	eta 0:02:21 lr 0.003327	time 0.4542 (0.5219)	model_time 0.4537 (0.4663)	loss 4.1597 (3.5291)	grad_norm 1.0416 (1.7108/0.9293)	mem 16099MB
[2025-01-18 01:40:14 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][50/312]	eta 0:02:13 lr 0.003327	time 0.4494 (0.5087)	model_time 0.4493 (0.4640)	loss 3.2339 (3.5112)	grad_norm 0.9747 (1.7135/0.9358)	mem 16099MB
[2025-01-18 01:40:18 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][60/312]	eta 0:02:06 lr 0.003326	time 0.4514 (0.5025)	model_time 0.4509 (0.4649)	loss 3.5884 (3.4955)	grad_norm 0.9521 (1.6127/0.9023)	mem 16099MB
[2025-01-18 01:40:23 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][70/312]	eta 0:02:01 lr 0.003326	time 0.7839 (0.5024)	model_time 0.7833 (0.4701)	loss 2.3011 (3.4829)	grad_norm 0.9050 (1.5261/0.8674)	mem 16099MB
[2025-01-18 01:40:28 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][80/312]	eta 0:01:55 lr 0.003325	time 0.4476 (0.4986)	model_time 0.4471 (0.4702)	loss 3.8618 (3.5205)	grad_norm 2.8262 (1.5316/0.8340)	mem 16099MB
[2025-01-18 01:40:33 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][90/312]	eta 0:01:49 lr 0.003325	time 0.4442 (0.4937)	model_time 0.4440 (0.4684)	loss 3.8253 (3.5375)	grad_norm 3.3895 (1.5889/0.8484)	mem 16099MB
[2025-01-18 01:40:37 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][100/312]	eta 0:01:43 lr 0.003324	time 0.4625 (0.4899)	model_time 0.4620 (0.4671)	loss 3.7629 (3.5220)	grad_norm 1.7198 (1.5747/0.8194)	mem 16099MB
[2025-01-18 01:40:42 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][110/312]	eta 0:01:38 lr 0.003324	time 0.5754 (0.4877)	model_time 0.5752 (0.4669)	loss 2.7192 (3.5009)	grad_norm 0.6684 (1.5503/0.7943)	mem 16099MB
[2025-01-18 01:40:47 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][120/312]	eta 0:01:33 lr 0.003323	time 0.4622 (0.4870)	model_time 0.4618 (0.4679)	loss 2.7575 (3.4978)	grad_norm 0.9957 (1.5632/0.7847)	mem 16099MB
[2025-01-18 01:40:51 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][130/312]	eta 0:01:28 lr 0.003323	time 0.4655 (0.4856)	model_time 0.4650 (0.4680)	loss 3.3911 (3.5024)	grad_norm 1.2557 (1.5570/0.7718)	mem 16099MB
[2025-01-18 01:40:56 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][140/312]	eta 0:01:23 lr 0.003322	time 0.5388 (0.4851)	model_time 0.5384 (0.4686)	loss 3.9600 (3.4942)	grad_norm 1.8280 (1.5505/0.7510)	mem 16099MB
[2025-01-18 01:41:01 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][150/312]	eta 0:01:18 lr 0.003322	time 0.4413 (0.4846)	model_time 0.4411 (0.4692)	loss 2.7637 (3.4777)	grad_norm 1.9592 (1.5382/0.7361)	mem 16099MB
[2025-01-18 01:41:06 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][160/312]	eta 0:01:13 lr 0.003321	time 0.4603 (0.4848)	model_time 0.4602 (0.4703)	loss 4.1558 (3.4895)	grad_norm 0.9347 (1.5148/0.7207)	mem 16099MB
[2025-01-18 01:41:10 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][170/312]	eta 0:01:08 lr 0.003321	time 0.4567 (0.4831)	model_time 0.4565 (0.4694)	loss 3.5398 (3.5154)	grad_norm 0.8723 (1.5007/0.7093)	mem 16099MB
[2025-01-18 01:41:15 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][180/312]	eta 0:01:03 lr 0.003320	time 0.4474 (0.4816)	model_time 0.4469 (0.4687)	loss 2.1753 (3.5172)	grad_norm 3.8798 (1.5067/0.7305)	mem 16099MB
[2025-01-18 01:41:19 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][190/312]	eta 0:00:58 lr 0.003320	time 0.4511 (0.4804)	model_time 0.4505 (0.4681)	loss 3.7056 (3.5055)	grad_norm 1.8604 (1.5469/0.7804)	mem 16099MB
[2025-01-18 01:41:24 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][200/312]	eta 0:00:53 lr 0.003319	time 0.4547 (0.4794)	model_time 0.4543 (0.4677)	loss 3.9682 (3.4925)	grad_norm 0.8204 (1.5570/0.7848)	mem 16099MB
[2025-01-18 01:41:29 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][210/312]	eta 0:00:48 lr 0.003319	time 0.4653 (0.4783)	model_time 0.4651 (0.4672)	loss 3.7682 (3.5028)	grad_norm 1.0416 (1.5505/0.7695)	mem 16099MB
[2025-01-18 01:41:33 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][220/312]	eta 0:00:43 lr 0.003318	time 0.4508 (0.4771)	model_time 0.4504 (0.4664)	loss 3.7201 (3.5018)	grad_norm 2.9520 (1.5649/0.7705)	mem 16099MB
[2025-01-18 01:41:38 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][230/312]	eta 0:00:39 lr 0.003318	time 0.4448 (0.4767)	model_time 0.4443 (0.4665)	loss 3.6809 (3.4886)	grad_norm 1.1655 (1.5558/0.7584)	mem 16099MB
[2025-01-18 01:41:42 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][240/312]	eta 0:00:34 lr 0.003317	time 0.4541 (0.4764)	model_time 0.4537 (0.4666)	loss 3.8807 (3.4837)	grad_norm 1.1585 (1.5518/0.7489)	mem 16099MB
[2025-01-18 01:41:47 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][250/312]	eta 0:00:29 lr 0.003317	time 0.4540 (0.4762)	model_time 0.4538 (0.4668)	loss 3.4986 (3.4755)	grad_norm 1.2808 (1.5531/0.7391)	mem 16099MB
[2025-01-18 01:41:52 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][260/312]	eta 0:00:24 lr 0.003316	time 0.4445 (0.4752)	model_time 0.4443 (0.4661)	loss 2.9196 (3.4584)	grad_norm 1.1189 (1.5479/0.7340)	mem 16099MB
[2025-01-18 01:41:56 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][270/312]	eta 0:00:19 lr 0.003316	time 0.4552 (0.4751)	model_time 0.4548 (0.4663)	loss 3.1183 (3.4550)	grad_norm 1.1186 (1.5445/0.7236)	mem 16099MB
[2025-01-18 01:42:01 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][280/312]	eta 0:00:15 lr 0.003315	time 0.4477 (0.4743)	model_time 0.4472 (0.4658)	loss 2.4167 (3.4557)	grad_norm 1.6411 (1.5475/0.7236)	mem 16099MB
[2025-01-18 01:42:05 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][290/312]	eta 0:00:10 lr 0.003315	time 0.4549 (0.4737)	model_time 0.4548 (0.4655)	loss 3.8959 (3.4551)	grad_norm 1.7804 (1.5477/0.7191)	mem 16099MB
[2025-01-18 01:42:10 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][300/312]	eta 0:00:05 lr 0.003314	time 0.4439 (0.4740)	model_time 0.4438 (0.4660)	loss 2.8103 (3.4554)	grad_norm 1.0551 (1.5334/0.7110)	mem 16099MB
[2025-01-18 01:42:15 internimage_t_1k_224] (main.py 510): INFO Train: [81/300][310/312]	eta 0:00:00 lr 0.003314	time 0.5247 (0.4735)	model_time 0.5246 (0.4658)	loss 3.4669 (3.4591)	grad_norm 1.3652 (1.5285/0.7114)	mem 16099MB
[2025-01-18 01:42:15 internimage_t_1k_224] (main.py 519): INFO EPOCH 81 training takes 0:02:27
[2025-01-18 01:42:15 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_81.pth saving......
[2025-01-18 01:42:16 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_81.pth saved !!!
[2025-01-18 01:42:24 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.541 (7.541)	Loss 0.8999 (0.8999)	Acc@1 80.151 (80.151)	Acc@5 95.508 (95.508)	Mem 16099MB
[2025-01-18 01:42:28 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.025)	Loss 1.2900 (1.0792)	Acc@1 70.654 (76.343)	Acc@5 91.284 (93.599)	Mem 16099MB
[2025-01-18 01:42:28 internimage_t_1k_224] (main.py 575): INFO [Epoch:81] * Acc@1 76.308 Acc@5 93.638
[2025-01-18 01:42:28 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.3%
[2025-01-18 01:42:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 01:42:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 01:42:29 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.31%
[2025-01-18 01:42:37 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.844 (7.844)	Loss 1.1916 (1.1916)	Acc@1 75.195 (75.195)	Acc@5 93.481 (93.481)	Mem 16099MB
[2025-01-18 01:42:41 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.048)	Loss 1.6784 (1.3906)	Acc@1 65.283 (71.589)	Acc@5 86.987 (90.683)	Mem 16099MB
[2025-01-18 01:42:41 internimage_t_1k_224] (main.py 575): INFO [Epoch:81] * Acc@1 71.569 Acc@5 90.729
[2025-01-18 01:42:41 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 71.6%
[2025-01-18 01:42:41 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:42:42 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:42:42 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 71.57%
[2025-01-18 01:42:44 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][0/312]	eta 0:10:53 lr 0.003314	time 2.0934 (2.0934)	model_time 0.4984 (0.4984)	loss 2.8125 (2.8125)	grad_norm 0.9602 (0.9602/0.0000)	mem 16099MB
[2025-01-18 01:42:50 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][10/312]	eta 0:03:21 lr 0.003313	time 0.5335 (0.6679)	model_time 0.5331 (0.4741)	loss 3.5184 (3.5936)	grad_norm 0.9450 (1.8637/1.0700)	mem 16099MB
[2025-01-18 01:42:54 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][20/312]	eta 0:02:44 lr 0.003313	time 0.4395 (0.5640)	model_time 0.4393 (0.4623)	loss 3.9113 (3.4254)	grad_norm 1.4308 (1.6654/0.8446)	mem 16099MB
[2025-01-18 01:42:59 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][30/312]	eta 0:02:30 lr 0.003312	time 0.4471 (0.5334)	model_time 0.4467 (0.4643)	loss 3.8983 (3.5982)	grad_norm 0.8287 (1.5884/0.7870)	mem 16099MB
[2025-01-18 01:43:03 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][40/312]	eta 0:02:19 lr 0.003312	time 0.4493 (0.5144)	model_time 0.4489 (0.4620)	loss 2.8316 (3.5608)	grad_norm 1.0829 (1.5040/0.7227)	mem 16099MB
[2025-01-18 01:43:08 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][50/312]	eta 0:02:12 lr 0.003311	time 0.4559 (0.5057)	model_time 0.4558 (0.4636)	loss 2.5007 (3.5505)	grad_norm 1.5595 (1.5979/0.7201)	mem 16099MB
[2025-01-18 01:43:13 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][60/312]	eta 0:02:05 lr 0.003311	time 0.4502 (0.4971)	model_time 0.4498 (0.4618)	loss 3.3885 (3.5012)	grad_norm 1.5162 (1.5827/0.6858)	mem 16099MB
[2025-01-18 01:43:17 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][70/312]	eta 0:01:59 lr 0.003310	time 0.4572 (0.4926)	model_time 0.4567 (0.4622)	loss 3.2095 (3.4995)	grad_norm 1.3708 (1.5315/0.6593)	mem 16099MB
[2025-01-18 01:43:22 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][80/312]	eta 0:01:53 lr 0.003310	time 0.4508 (0.4905)	model_time 0.4506 (0.4638)	loss 3.8919 (3.4881)	grad_norm 1.2181 (1.5200/0.6393)	mem 16099MB
[2025-01-18 01:43:27 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][90/312]	eta 0:01:48 lr 0.003309	time 0.4530 (0.4868)	model_time 0.4526 (0.4629)	loss 3.6943 (3.4696)	grad_norm 2.8377 (1.5408/0.6244)	mem 16099MB
[2025-01-18 01:43:31 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][100/312]	eta 0:01:42 lr 0.003309	time 0.4448 (0.4840)	model_time 0.4444 (0.4625)	loss 3.4375 (3.4464)	grad_norm 2.0970 (1.6063/0.7203)	mem 16099MB
[2025-01-18 01:43:36 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][110/312]	eta 0:01:37 lr 0.003308	time 0.4457 (0.4825)	model_time 0.4452 (0.4629)	loss 4.0977 (3.4375)	grad_norm 1.6639 (1.6028/0.7012)	mem 16099MB
[2025-01-18 01:43:41 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][120/312]	eta 0:01:32 lr 0.003308	time 0.4659 (0.4811)	model_time 0.4653 (0.4630)	loss 4.2191 (3.4519)	grad_norm 1.4594 (1.5664/0.6881)	mem 16099MB
[2025-01-18 01:43:45 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][130/312]	eta 0:01:27 lr 0.003307	time 0.4586 (0.4805)	model_time 0.4582 (0.4638)	loss 3.2027 (3.4616)	grad_norm 1.4403 (1.5596/0.6679)	mem 16099MB
[2025-01-18 01:43:50 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][140/312]	eta 0:01:22 lr 0.003307	time 0.4522 (0.4803)	model_time 0.4520 (0.4647)	loss 2.9992 (3.4813)	grad_norm 3.4008 (1.6331/0.7582)	mem 16099MB
[2025-01-18 01:43:55 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][150/312]	eta 0:01:17 lr 0.003306	time 0.4456 (0.4791)	model_time 0.4451 (0.4645)	loss 4.4056 (3.4956)	grad_norm 0.7525 (1.6114/0.7453)	mem 16099MB
[2025-01-18 01:43:59 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][160/312]	eta 0:01:12 lr 0.003306	time 0.4496 (0.4773)	model_time 0.4491 (0.4636)	loss 2.8549 (3.4926)	grad_norm 1.2993 (1.6008/0.7346)	mem 16099MB
[2025-01-18 01:44:04 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][170/312]	eta 0:01:07 lr 0.003305	time 0.4425 (0.4769)	model_time 0.4423 (0.4640)	loss 3.7486 (3.4868)	grad_norm 2.3329 (1.5835/0.7254)	mem 16099MB
[2025-01-18 01:44:08 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][180/312]	eta 0:01:02 lr 0.003305	time 0.4492 (0.4759)	model_time 0.4490 (0.4636)	loss 2.6527 (3.4799)	grad_norm 1.4879 (1.5800/0.7165)	mem 16099MB
[2025-01-18 01:44:13 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][190/312]	eta 0:00:57 lr 0.003304	time 0.4544 (0.4747)	model_time 0.4542 (0.4631)	loss 4.2270 (3.4737)	grad_norm 1.5827 (1.5741/0.7060)	mem 16099MB
[2025-01-18 01:44:18 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][200/312]	eta 0:00:53 lr 0.003304	time 0.4739 (0.4741)	model_time 0.4735 (0.4630)	loss 3.2711 (3.4785)	grad_norm 2.5664 (1.6104/0.7345)	mem 16099MB
[2025-01-18 01:44:22 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][210/312]	eta 0:00:48 lr 0.003303	time 0.4515 (0.4742)	model_time 0.4511 (0.4637)	loss 2.8124 (3.4740)	grad_norm 1.3806 (1.6160/0.7317)	mem 16099MB
[2025-01-18 01:44:27 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][220/312]	eta 0:00:43 lr 0.003303	time 0.4503 (0.4736)	model_time 0.4499 (0.4635)	loss 3.4953 (3.4843)	grad_norm 1.2990 (1.6113/0.7251)	mem 16099MB
[2025-01-18 01:44:32 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][230/312]	eta 0:00:38 lr 0.003302	time 0.4464 (0.4728)	model_time 0.4462 (0.4632)	loss 3.7900 (3.4837)	grad_norm 0.7264 (1.5878/0.7225)	mem 16099MB
[2025-01-18 01:44:36 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][240/312]	eta 0:00:34 lr 0.003302	time 0.4739 (0.4729)	model_time 0.4738 (0.4636)	loss 3.6267 (3.4806)	grad_norm 0.8301 (1.5674/0.7189)	mem 16099MB
[2025-01-18 01:44:41 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][250/312]	eta 0:00:29 lr 0.003301	time 0.4480 (0.4724)	model_time 0.4476 (0.4634)	loss 2.6965 (3.4841)	grad_norm 0.8242 (1.5482/0.7126)	mem 16099MB
[2025-01-18 01:44:45 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][260/312]	eta 0:00:24 lr 0.003301	time 0.4595 (0.4720)	model_time 0.4591 (0.4633)	loss 3.4366 (3.4842)	grad_norm 2.0622 (1.5475/0.7097)	mem 16099MB
[2025-01-18 01:44:50 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][270/312]	eta 0:00:19 lr 0.003300	time 0.5442 (0.4725)	model_time 0.5440 (0.4642)	loss 3.9421 (3.4994)	grad_norm 0.7555 (1.5407/0.7042)	mem 16099MB
[2025-01-18 01:44:55 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][280/312]	eta 0:00:15 lr 0.003300	time 0.4836 (0.4722)	model_time 0.4832 (0.4641)	loss 3.7757 (3.5060)	grad_norm 1.4636 (1.5601/0.7324)	mem 16099MB
[2025-01-18 01:45:00 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][290/312]	eta 0:00:10 lr 0.003299	time 0.4486 (0.4730)	model_time 0.4485 (0.4652)	loss 4.2849 (3.5121)	grad_norm 1.1031 (1.5684/0.7306)	mem 16099MB
[2025-01-18 01:45:05 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][300/312]	eta 0:00:05 lr 0.003299	time 0.4424 (0.4728)	model_time 0.4423 (0.4653)	loss 3.3197 (3.4927)	grad_norm 1.5249 (1.5873/0.7607)	mem 16099MB
[2025-01-18 01:45:09 internimage_t_1k_224] (main.py 510): INFO Train: [82/300][310/312]	eta 0:00:00 lr 0.003298	time 0.4460 (0.4722)	model_time 0.4459 (0.4649)	loss 3.7805 (3.4875)	grad_norm 1.2255 (1.5688/0.7367)	mem 16099MB
[2025-01-18 01:45:10 internimage_t_1k_224] (main.py 519): INFO EPOCH 82 training takes 0:02:27
[2025-01-18 01:45:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_82.pth saving......
[2025-01-18 01:45:11 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_82.pth saved !!!
[2025-01-18 01:45:18 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.477 (7.477)	Loss 0.9579 (0.9579)	Acc@1 78.979 (78.979)	Acc@5 94.946 (94.946)	Mem 16099MB
[2025-01-18 01:45:22 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.025)	Loss 1.3747 (1.1237)	Acc@1 70.435 (75.872)	Acc@5 90.161 (93.102)	Mem 16099MB
[2025-01-18 01:45:22 internimage_t_1k_224] (main.py 575): INFO [Epoch:82] * Acc@1 75.910 Acc@5 93.218
[2025-01-18 01:45:22 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 75.9%
[2025-01-18 01:45:22 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.31%
[2025-01-18 01:45:31 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.413 (8.413)	Loss 1.1692 (1.1692)	Acc@1 75.586 (75.586)	Acc@5 93.677 (93.677)	Mem 16099MB
[2025-01-18 01:45:35 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.140)	Loss 1.6525 (1.3670)	Acc@1 65.747 (71.986)	Acc@5 87.402 (90.922)	Mem 16099MB
[2025-01-18 01:45:35 internimage_t_1k_224] (main.py 575): INFO [Epoch:82] * Acc@1 71.943 Acc@5 90.963
[2025-01-18 01:45:35 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 71.9%
[2025-01-18 01:45:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:45:37 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:45:37 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 71.94%
[2025-01-18 01:45:39 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][0/312]	eta 0:12:14 lr 0.003298	time 2.3558 (2.3558)	model_time 0.4575 (0.4575)	loss 3.5702 (3.5702)	grad_norm 1.7497 (1.7497/0.0000)	mem 16099MB
[2025-01-18 01:45:44 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][10/312]	eta 0:03:13 lr 0.003297	time 0.4541 (0.6411)	model_time 0.4539 (0.4682)	loss 3.6101 (3.1732)	grad_norm 1.1954 (1.3046/0.3280)	mem 16099MB
[2025-01-18 01:45:48 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][20/312]	eta 0:02:41 lr 0.003297	time 0.4610 (0.5522)	model_time 0.4605 (0.4614)	loss 3.3242 (3.3633)	grad_norm 3.1160 (1.5348/0.7820)	mem 16099MB
[2025-01-18 01:45:53 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][30/312]	eta 0:02:26 lr 0.003296	time 0.4648 (0.5208)	model_time 0.4646 (0.4593)	loss 3.2492 (3.3856)	grad_norm 1.8022 (1.6181/0.7543)	mem 16099MB
[2025-01-18 01:45:57 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][40/312]	eta 0:02:17 lr 0.003296	time 0.4820 (0.5059)	model_time 0.4818 (0.4592)	loss 2.3196 (3.3734)	grad_norm 1.4198 (1.4910/0.7005)	mem 16099MB
[2025-01-18 01:46:02 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][50/312]	eta 0:02:11 lr 0.003295	time 0.4556 (0.5008)	model_time 0.4554 (0.4632)	loss 3.5447 (3.3928)	grad_norm 1.1632 (1.4503/0.6392)	mem 16099MB
[2025-01-18 01:46:07 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][60/312]	eta 0:02:04 lr 0.003295	time 0.4400 (0.4945)	model_time 0.4398 (0.4630)	loss 3.0830 (3.3498)	grad_norm 0.8244 (1.4095/0.6064)	mem 16099MB
[2025-01-18 01:46:11 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][70/312]	eta 0:01:59 lr 0.003294	time 0.4550 (0.4924)	model_time 0.4548 (0.4653)	loss 4.3678 (3.3702)	grad_norm 0.9576 (1.4382/0.6242)	mem 16099MB
[2025-01-18 01:46:16 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][80/312]	eta 0:01:53 lr 0.003294	time 0.4523 (0.4877)	model_time 0.4522 (0.4639)	loss 3.1647 (3.3675)	grad_norm 1.5681 (1.5044/0.6527)	mem 16099MB
[2025-01-18 01:46:21 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][90/312]	eta 0:01:47 lr 0.003293	time 0.4686 (0.4838)	model_time 0.4685 (0.4626)	loss 3.1995 (3.3557)	grad_norm 1.2253 (1.5064/0.6332)	mem 16099MB
[2025-01-18 01:46:25 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][100/312]	eta 0:01:42 lr 0.003293	time 0.4845 (0.4819)	model_time 0.4843 (0.4627)	loss 3.2533 (3.3453)	grad_norm 1.1579 (1.5196/0.6262)	mem 16099MB
[2025-01-18 01:46:30 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][110/312]	eta 0:01:36 lr 0.003292	time 0.4506 (0.4796)	model_time 0.4505 (0.4621)	loss 3.3170 (3.3542)	grad_norm 1.2336 (1.5121/0.6080)	mem 16099MB
[2025-01-18 01:46:34 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][120/312]	eta 0:01:31 lr 0.003292	time 0.4593 (0.4778)	model_time 0.4589 (0.4617)	loss 2.4297 (3.3521)	grad_norm 0.9662 (1.5386/0.6490)	mem 16099MB
[2025-01-18 01:46:39 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][130/312]	eta 0:01:26 lr 0.003291	time 0.4537 (0.4766)	model_time 0.4536 (0.4618)	loss 4.4157 (3.3789)	grad_norm 2.3489 (1.5263/0.6379)	mem 16099MB
[2025-01-18 01:46:44 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][140/312]	eta 0:01:22 lr 0.003291	time 0.4833 (0.4772)	model_time 0.4831 (0.4634)	loss 3.8228 (3.3880)	grad_norm 1.1847 (1.5121/0.6294)	mem 16099MB
[2025-01-18 01:46:48 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][150/312]	eta 0:01:17 lr 0.003290	time 0.4578 (0.4766)	model_time 0.4577 (0.4636)	loss 2.8701 (3.3837)	grad_norm 0.8144 (1.5292/0.6604)	mem 16099MB
[2025-01-18 01:46:53 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][160/312]	eta 0:01:12 lr 0.003290	time 0.4591 (0.4768)	model_time 0.4587 (0.4646)	loss 2.6496 (3.3797)	grad_norm 0.7859 (1.5135/0.6506)	mem 16099MB
[2025-01-18 01:46:58 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][170/312]	eta 0:01:07 lr 0.003289	time 0.4503 (0.4768)	model_time 0.4501 (0.4653)	loss 3.5969 (3.3775)	grad_norm 0.6886 (1.4982/0.6460)	mem 16099MB
[2025-01-18 01:47:03 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][180/312]	eta 0:01:02 lr 0.003289	time 0.4558 (0.4759)	model_time 0.4556 (0.4650)	loss 3.8540 (3.3887)	grad_norm 1.9537 (1.4836/0.6364)	mem 16099MB
[2025-01-18 01:47:07 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][190/312]	eta 0:00:58 lr 0.003288	time 0.4475 (0.4754)	model_time 0.4473 (0.4651)	loss 4.1441 (3.4054)	grad_norm 1.0208 (1.4724/0.6294)	mem 16099MB
[2025-01-18 01:47:12 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][200/312]	eta 0:00:53 lr 0.003288	time 0.5080 (0.4746)	model_time 0.5075 (0.4647)	loss 3.8693 (3.4100)	grad_norm 3.3583 (1.4728/0.6305)	mem 16099MB
[2025-01-18 01:47:17 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][210/312]	eta 0:00:48 lr 0.003287	time 0.4977 (0.4738)	model_time 0.4975 (0.4643)	loss 3.8257 (3.4080)	grad_norm 1.2973 (1.4746/0.6274)	mem 16099MB
[2025-01-18 01:47:21 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][220/312]	eta 0:00:43 lr 0.003287	time 0.5286 (0.4737)	model_time 0.5284 (0.4647)	loss 3.3525 (3.4109)	grad_norm 1.4826 (1.4689/0.6315)	mem 16099MB
[2025-01-18 01:47:26 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][230/312]	eta 0:00:38 lr 0.003286	time 0.4436 (0.4740)	model_time 0.4435 (0.4653)	loss 2.8295 (3.4182)	grad_norm 1.7838 (1.4835/0.6338)	mem 16099MB
[2025-01-18 01:47:31 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][240/312]	eta 0:00:34 lr 0.003286	time 0.4574 (0.4737)	model_time 0.4395 (0.4653)	loss 3.5540 (3.4218)	grad_norm 3.3169 (1.5031/0.6622)	mem 16099MB
[2025-01-18 01:47:35 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][250/312]	eta 0:00:29 lr 0.003285	time 0.4590 (0.4732)	model_time 0.4586 (0.4651)	loss 2.9506 (3.4167)	grad_norm 1.1629 (1.5432/0.7196)	mem 16099MB
[2025-01-18 01:47:40 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][260/312]	eta 0:00:24 lr 0.003285	time 0.4635 (0.4726)	model_time 0.4631 (0.4648)	loss 2.5621 (3.4163)	grad_norm 1.0430 (1.5400/0.7229)	mem 16099MB
[2025-01-18 01:47:44 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][270/312]	eta 0:00:19 lr 0.003284	time 0.4624 (0.4721)	model_time 0.4620 (0.4645)	loss 2.2308 (3.4150)	grad_norm 1.3743 (1.5289/0.7150)	mem 16099MB
[2025-01-18 01:47:49 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][280/312]	eta 0:00:15 lr 0.003284	time 0.4680 (0.4719)	model_time 0.4674 (0.4646)	loss 3.9203 (3.4261)	grad_norm 0.9700 (1.5131/0.7088)	mem 16099MB
[2025-01-18 01:47:54 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][290/312]	eta 0:00:10 lr 0.003283	time 0.4550 (0.4722)	model_time 0.4546 (0.4652)	loss 3.6011 (3.4262)	grad_norm 1.0893 (1.5111/0.7027)	mem 16099MB
[2025-01-18 01:47:59 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][300/312]	eta 0:00:05 lr 0.003283	time 0.4424 (0.4721)	model_time 0.4423 (0.4652)	loss 3.5031 (3.4239)	grad_norm 1.5574 (1.5350/0.7209)	mem 16099MB
[2025-01-18 01:48:03 internimage_t_1k_224] (main.py 510): INFO Train: [83/300][310/312]	eta 0:00:00 lr 0.003282	time 0.4441 (0.4716)	model_time 0.4440 (0.4650)	loss 3.4581 (3.4211)	grad_norm 1.2496 (1.5368/0.7197)	mem 16099MB
[2025-01-18 01:48:04 internimage_t_1k_224] (main.py 519): INFO EPOCH 83 training takes 0:02:27
[2025-01-18 01:48:04 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_83.pth saving......
[2025-01-18 01:48:05 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_83.pth saved !!!
[2025-01-18 01:48:12 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.420 (7.420)	Loss 0.9101 (0.9101)	Acc@1 80.078 (80.078)	Acc@5 95.557 (95.557)	Mem 16099MB
[2025-01-18 01:48:16 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.993)	Loss 1.3288 (1.0961)	Acc@1 70.215 (76.136)	Acc@5 90.869 (93.359)	Mem 16099MB
[2025-01-18 01:48:16 internimage_t_1k_224] (main.py 575): INFO [Epoch:83] * Acc@1 76.054 Acc@5 93.388
[2025-01-18 01:48:16 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.1%
[2025-01-18 01:48:16 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.31%
[2025-01-18 01:48:24 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.254 (8.254)	Loss 1.1472 (1.1472)	Acc@1 76.001 (76.001)	Acc@5 94.067 (94.067)	Mem 16099MB
[2025-01-18 01:48:28 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.110)	Loss 1.6279 (1.3443)	Acc@1 66.211 (72.328)	Acc@5 87.671 (91.118)	Mem 16099MB
[2025-01-18 01:48:28 internimage_t_1k_224] (main.py 575): INFO [Epoch:83] * Acc@1 72.283 Acc@5 91.157
[2025-01-18 01:48:28 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 72.3%
[2025-01-18 01:48:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:48:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:48:30 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 72.28%
[2025-01-18 01:48:33 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][0/312]	eta 0:14:14 lr 0.003282	time 2.7374 (2.7374)	model_time 0.4671 (0.4671)	loss 3.2685 (3.2685)	grad_norm 1.1162 (1.1162/0.0000)	mem 16099MB
[2025-01-18 01:48:37 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][10/312]	eta 0:03:20 lr 0.003282	time 0.4401 (0.6642)	model_time 0.4396 (0.4574)	loss 2.5789 (3.6293)	grad_norm 2.5649 (1.7465/0.8152)	mem 16099MB
[2025-01-18 01:48:42 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][20/312]	eta 0:02:45 lr 0.003281	time 0.4425 (0.5682)	model_time 0.4423 (0.4597)	loss 2.3670 (3.5257)	grad_norm 0.8752 (1.4210/0.7100)	mem 16099MB
[2025-01-18 01:48:47 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][30/312]	eta 0:02:31 lr 0.003281	time 0.4817 (0.5376)	model_time 0.4812 (0.4640)	loss 3.4789 (3.4711)	grad_norm 1.6902 (1.4441/0.6166)	mem 16099MB
[2025-01-18 01:48:51 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][40/312]	eta 0:02:21 lr 0.003280	time 0.4418 (0.5190)	model_time 0.4416 (0.4633)	loss 3.7507 (3.5015)	grad_norm 1.2311 (1.4528/0.5774)	mem 16099MB
[2025-01-18 01:48:56 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][50/312]	eta 0:02:14 lr 0.003280	time 0.4500 (0.5122)	model_time 0.4496 (0.4674)	loss 4.2778 (3.5649)	grad_norm 2.3124 (1.4996/0.6065)	mem 16099MB
[2025-01-18 01:49:01 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][60/312]	eta 0:02:07 lr 0.003279	time 0.4857 (0.5042)	model_time 0.4852 (0.4666)	loss 3.4114 (3.5762)	grad_norm 1.4576 (1.5447/0.6366)	mem 16099MB
[2025-01-18 01:49:05 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][70/312]	eta 0:02:00 lr 0.003279	time 0.4747 (0.4975)	model_time 0.4745 (0.4652)	loss 2.9879 (3.5853)	grad_norm 1.2394 (1.5314/0.6014)	mem 16099MB
[2025-01-18 01:49:10 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][80/312]	eta 0:01:54 lr 0.003278	time 0.4507 (0.4916)	model_time 0.4505 (0.4632)	loss 3.8638 (3.6104)	grad_norm 2.3679 (1.5222/0.5905)	mem 16099MB
[2025-01-18 01:49:14 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][90/312]	eta 0:01:48 lr 0.003277	time 0.4508 (0.4874)	model_time 0.4503 (0.4621)	loss 4.3950 (3.5801)	grad_norm 2.7775 (1.6747/0.8736)	mem 16099MB
[2025-01-18 01:49:19 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][100/312]	eta 0:01:42 lr 0.003277	time 0.4760 (0.4845)	model_time 0.4756 (0.4616)	loss 4.0998 (3.5849)	grad_norm 1.1466 (1.6544/0.8594)	mem 16099MB
[2025-01-18 01:49:24 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][110/312]	eta 0:01:37 lr 0.003276	time 0.4566 (0.4836)	model_time 0.4564 (0.4627)	loss 4.0044 (3.5581)	grad_norm 1.1460 (1.6147/0.8350)	mem 16099MB
[2025-01-18 01:49:28 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][120/312]	eta 0:01:32 lr 0.003276	time 0.4705 (0.4823)	model_time 0.4704 (0.4632)	loss 4.0876 (3.5763)	grad_norm 1.3341 (1.5890/0.8087)	mem 16099MB
[2025-01-18 01:49:33 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][130/312]	eta 0:01:27 lr 0.003275	time 0.4689 (0.4803)	model_time 0.4688 (0.4625)	loss 4.3623 (3.5736)	grad_norm 1.4905 (1.5465/0.7935)	mem 16099MB
[2025-01-18 01:49:37 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][140/312]	eta 0:01:22 lr 0.003275	time 0.4463 (0.4794)	model_time 0.4461 (0.4629)	loss 3.1375 (3.5779)	grad_norm 1.0617 (1.5674/0.7977)	mem 16099MB
[2025-01-18 01:49:42 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][150/312]	eta 0:01:17 lr 0.003274	time 0.4539 (0.4798)	model_time 0.4537 (0.4644)	loss 4.3141 (3.5653)	grad_norm 1.4813 (1.5447/0.7797)	mem 16099MB
[2025-01-18 01:49:47 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][160/312]	eta 0:01:12 lr 0.003274	time 0.4821 (0.4796)	model_time 0.4820 (0.4651)	loss 3.7179 (3.5652)	grad_norm 1.5424 (1.5600/0.7774)	mem 16099MB
[2025-01-18 01:49:52 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][170/312]	eta 0:01:07 lr 0.003273	time 0.4502 (0.4783)	model_time 0.4497 (0.4647)	loss 3.1825 (3.5671)	grad_norm 1.4125 (1.5489/0.7683)	mem 16099MB
[2025-01-18 01:49:56 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][180/312]	eta 0:01:03 lr 0.003273	time 0.5534 (0.4778)	model_time 0.5528 (0.4649)	loss 3.0841 (3.5637)	grad_norm 1.1737 (1.5266/0.7538)	mem 16099MB
[2025-01-18 01:50:01 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][190/312]	eta 0:00:58 lr 0.003272	time 0.4472 (0.4775)	model_time 0.4471 (0.4652)	loss 3.5173 (3.5586)	grad_norm 0.5962 (1.5062/0.7520)	mem 16099MB
[2025-01-18 01:50:06 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][200/312]	eta 0:00:53 lr 0.003272	time 0.4759 (0.4772)	model_time 0.4754 (0.4655)	loss 4.0984 (3.5490)	grad_norm 2.1886 (1.5179/0.7442)	mem 16099MB
[2025-01-18 01:50:11 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][210/312]	eta 0:00:48 lr 0.003271	time 0.4409 (0.4772)	model_time 0.4404 (0.4661)	loss 3.9959 (3.5560)	grad_norm 0.9936 (1.5326/0.7548)	mem 16099MB
[2025-01-18 01:50:15 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][220/312]	eta 0:00:43 lr 0.003271	time 0.4620 (0.4769)	model_time 0.4616 (0.4663)	loss 3.8195 (3.5487)	grad_norm 0.7109 (1.5263/0.7425)	mem 16099MB
[2025-01-18 01:50:20 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][230/312]	eta 0:00:39 lr 0.003270	time 0.5477 (0.4768)	model_time 0.5476 (0.4666)	loss 3.5336 (3.5532)	grad_norm 0.7830 (1.5092/0.7371)	mem 16099MB
[2025-01-18 01:50:25 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][240/312]	eta 0:00:34 lr 0.003270	time 0.4537 (0.4760)	model_time 0.4536 (0.4662)	loss 3.8190 (3.5480)	grad_norm 1.4011 (1.5026/0.7262)	mem 16099MB
[2025-01-18 01:50:29 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][250/312]	eta 0:00:29 lr 0.003269	time 0.4472 (0.4755)	model_time 0.4468 (0.4661)	loss 3.4886 (3.5512)	grad_norm 0.9002 (1.4959/0.7202)	mem 16099MB
[2025-01-18 01:50:34 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][260/312]	eta 0:00:24 lr 0.003269	time 0.4540 (0.4751)	model_time 0.4539 (0.4660)	loss 4.1680 (3.5527)	grad_norm 1.6043 (1.5032/0.7137)	mem 16099MB
[2025-01-18 01:50:38 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][270/312]	eta 0:00:19 lr 0.003268	time 0.4520 (0.4747)	model_time 0.4518 (0.4659)	loss 3.6748 (3.5338)	grad_norm 1.3591 (1.5100/0.7076)	mem 16099MB
[2025-01-18 01:50:43 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][280/312]	eta 0:00:15 lr 0.003268	time 0.4755 (0.4748)	model_time 0.4753 (0.4663)	loss 2.9294 (3.5318)	grad_norm 3.1620 (1.5191/0.7106)	mem 16099MB
[2025-01-18 01:50:48 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][290/312]	eta 0:00:10 lr 0.003267	time 0.4583 (0.4747)	model_time 0.4579 (0.4665)	loss 4.1214 (3.5278)	grad_norm 1.0485 (1.5157/0.7058)	mem 16099MB
[2025-01-18 01:50:52 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][300/312]	eta 0:00:05 lr 0.003267	time 0.4437 (0.4738)	model_time 0.4436 (0.4659)	loss 3.8126 (3.5295)	grad_norm 1.9331 (1.5189/0.7076)	mem 16099MB
[2025-01-18 01:50:57 internimage_t_1k_224] (main.py 510): INFO Train: [84/300][310/312]	eta 0:00:00 lr 0.003266	time 0.4442 (0.4729)	model_time 0.4441 (0.4652)	loss 3.7979 (3.5262)	grad_norm 1.6687 (1.5481/0.7990)	mem 16099MB
[2025-01-18 01:50:57 internimage_t_1k_224] (main.py 519): INFO EPOCH 84 training takes 0:02:27
[2025-01-18 01:50:57 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_84.pth saving......
[2025-01-18 01:50:58 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_84.pth saved !!!
[2025-01-18 01:51:06 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.530 (7.530)	Loss 0.9187 (0.9187)	Acc@1 80.249 (80.249)	Acc@5 95.654 (95.654)	Mem 16099MB
[2025-01-18 01:51:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.019)	Loss 1.3356 (1.0996)	Acc@1 71.069 (76.467)	Acc@5 90.137 (93.390)	Mem 16099MB
[2025-01-18 01:51:10 internimage_t_1k_224] (main.py 575): INFO [Epoch:84] * Acc@1 76.398 Acc@5 93.464
[2025-01-18 01:51:10 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.4%
[2025-01-18 01:51:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 01:51:11 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 01:51:11 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.40%
[2025-01-18 01:51:19 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.100 (8.100)	Loss 1.1267 (1.1267)	Acc@1 76.392 (76.392)	Acc@5 94.312 (94.312)	Mem 16099MB
[2025-01-18 01:51:23 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.097)	Loss 1.6057 (1.3231)	Acc@1 66.357 (72.661)	Acc@5 87.866 (91.331)	Mem 16099MB
[2025-01-18 01:51:23 internimage_t_1k_224] (main.py 575): INFO [Epoch:84] * Acc@1 72.601 Acc@5 91.387
[2025-01-18 01:51:23 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 72.6%
[2025-01-18 01:51:23 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:51:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:51:25 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 72.60%
[2025-01-18 01:51:27 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][0/312]	eta 0:11:22 lr 0.003266	time 2.1887 (2.1887)	model_time 0.5528 (0.5528)	loss 3.0914 (3.0914)	grad_norm 0.8778 (0.8778/0.0000)	mem 16099MB
[2025-01-18 01:51:32 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][10/312]	eta 0:03:09 lr 0.003266	time 0.4528 (0.6274)	model_time 0.4527 (0.4783)	loss 3.3376 (3.4762)	grad_norm 1.4874 (1.2207/0.3711)	mem 16099MB
[2025-01-18 01:51:36 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][20/312]	eta 0:02:39 lr 0.003265	time 0.4709 (0.5469)	model_time 0.4705 (0.4687)	loss 3.7546 (3.6493)	grad_norm 1.8609 (1.6116/0.7170)	mem 16099MB
[2025-01-18 01:51:41 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][30/312]	eta 0:02:26 lr 0.003265	time 0.4528 (0.5199)	model_time 0.4524 (0.4667)	loss 3.6065 (3.6519)	grad_norm 1.3834 (1.4691/0.6386)	mem 16099MB
[2025-01-18 01:51:46 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][40/312]	eta 0:02:18 lr 0.003264	time 0.5131 (0.5074)	model_time 0.5126 (0.4671)	loss 4.3065 (3.6313)	grad_norm 2.7031 (1.5377/0.6506)	mem 16099MB
[2025-01-18 01:51:50 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][50/312]	eta 0:02:11 lr 0.003263	time 0.5453 (0.5021)	model_time 0.5449 (0.4697)	loss 3.8491 (3.6256)	grad_norm 1.4832 (1.5065/0.6221)	mem 16099MB
[2025-01-18 01:51:55 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][60/312]	eta 0:02:05 lr 0.003263	time 0.5412 (0.4973)	model_time 0.5411 (0.4701)	loss 3.2858 (3.6015)	grad_norm 1.1984 (1.4914/0.6000)	mem 16099MB
[2025-01-18 01:52:00 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][70/312]	eta 0:01:59 lr 0.003262	time 0.4608 (0.4935)	model_time 0.4604 (0.4700)	loss 3.8600 (3.5931)	grad_norm 0.9570 (1.5298/0.6045)	mem 16099MB
[2025-01-18 01:52:04 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][80/312]	eta 0:01:53 lr 0.003262	time 0.4574 (0.4890)	model_time 0.4572 (0.4684)	loss 3.6798 (3.5615)	grad_norm 1.0524 (1.5109/0.5912)	mem 16099MB
[2025-01-18 01:52:09 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][90/312]	eta 0:01:48 lr 0.003261	time 0.5529 (0.4880)	model_time 0.5525 (0.4696)	loss 2.4189 (3.5351)	grad_norm 1.4762 (1.5629/0.6511)	mem 16099MB
[2025-01-18 01:52:14 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][100/312]	eta 0:01:42 lr 0.003261	time 0.4524 (0.4851)	model_time 0.4522 (0.4685)	loss 3.0990 (3.5153)	grad_norm 1.4039 (1.5642/0.6236)	mem 16099MB
[2025-01-18 01:52:18 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][110/312]	eta 0:01:37 lr 0.003260	time 0.4395 (0.4845)	model_time 0.4394 (0.4694)	loss 3.8035 (3.5052)	grad_norm 3.1760 (1.5844/0.6331)	mem 16099MB
[2025-01-18 01:52:23 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][120/312]	eta 0:01:32 lr 0.003260	time 0.4419 (0.4827)	model_time 0.4417 (0.4688)	loss 2.6882 (3.4765)	grad_norm 1.0554 (1.5765/0.6180)	mem 16099MB
[2025-01-18 01:52:28 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][130/312]	eta 0:01:27 lr 0.003259	time 0.5447 (0.4820)	model_time 0.5442 (0.4691)	loss 3.9789 (3.4933)	grad_norm 0.8973 (1.5779/0.6360)	mem 16099MB
[2025-01-18 01:52:33 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][140/312]	eta 0:01:22 lr 0.003259	time 0.4485 (0.4819)	model_time 0.4480 (0.4699)	loss 3.5691 (3.5210)	grad_norm 1.2641 (1.5914/0.6574)	mem 16099MB
[2025-01-18 01:52:37 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][150/312]	eta 0:01:17 lr 0.003258	time 0.4591 (0.4809)	model_time 0.4589 (0.4697)	loss 3.0012 (3.5334)	grad_norm 1.3203 (1.5798/0.6474)	mem 16099MB
[2025-01-18 01:52:42 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][160/312]	eta 0:01:13 lr 0.003258	time 0.5334 (0.4813)	model_time 0.5330 (0.4707)	loss 4.1211 (3.5479)	grad_norm 0.9623 (1.5562/0.6363)	mem 16099MB
[2025-01-18 01:52:47 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][170/312]	eta 0:01:08 lr 0.003257	time 0.4476 (0.4800)	model_time 0.4474 (0.4701)	loss 2.9951 (3.5460)	grad_norm 1.3850 (1.5729/0.6968)	mem 16099MB
[2025-01-18 01:52:51 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][180/312]	eta 0:01:03 lr 0.003257	time 0.4429 (0.4786)	model_time 0.4424 (0.4692)	loss 4.1849 (3.5474)	grad_norm 2.1843 (1.5849/0.7030)	mem 16099MB
[2025-01-18 01:52:56 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][190/312]	eta 0:00:58 lr 0.003256	time 0.4651 (0.4778)	model_time 0.4649 (0.4688)	loss 3.1846 (3.5449)	grad_norm 0.8302 (1.5766/0.6919)	mem 16099MB
[2025-01-18 01:53:01 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][200/312]	eta 0:00:53 lr 0.003256	time 0.4435 (0.4770)	model_time 0.4433 (0.4685)	loss 3.6150 (3.5437)	grad_norm 1.1619 (1.5605/0.6885)	mem 16099MB
[2025-01-18 01:53:05 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][210/312]	eta 0:00:48 lr 0.003255	time 0.4700 (0.4770)	model_time 0.4695 (0.4689)	loss 3.8205 (3.5512)	grad_norm 3.1303 (1.5624/0.6905)	mem 16099MB
[2025-01-18 01:53:10 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][220/312]	eta 0:00:43 lr 0.003255	time 0.4490 (0.4763)	model_time 0.4486 (0.4685)	loss 3.2938 (3.5452)	grad_norm 1.2209 (1.5595/0.6779)	mem 16099MB
[2025-01-18 01:53:15 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][230/312]	eta 0:00:39 lr 0.003254	time 0.4421 (0.4762)	model_time 0.4420 (0.4687)	loss 4.2600 (3.5420)	grad_norm 1.1108 (1.5551/0.6703)	mem 16099MB
[2025-01-18 01:53:19 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][240/312]	eta 0:00:34 lr 0.003254	time 0.4572 (0.4757)	model_time 0.4568 (0.4685)	loss 3.3215 (3.5264)	grad_norm 3.4615 (1.5556/0.6732)	mem 16099MB
[2025-01-18 01:53:24 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][250/312]	eta 0:00:29 lr 0.003253	time 0.4638 (0.4747)	model_time 0.4636 (0.4678)	loss 3.7029 (3.5275)	grad_norm 1.1053 (1.5739/0.6937)	mem 16099MB
[2025-01-18 01:53:28 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][260/312]	eta 0:00:24 lr 0.003253	time 0.4533 (0.4742)	model_time 0.4528 (0.4675)	loss 4.2548 (3.5271)	grad_norm 0.6974 (1.5594/0.6867)	mem 16099MB
[2025-01-18 01:53:33 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][270/312]	eta 0:00:19 lr 0.003252	time 0.4625 (0.4734)	model_time 0.4623 (0.4669)	loss 3.9092 (3.5330)	grad_norm 2.0543 (1.5532/0.6810)	mem 16099MB
[2025-01-18 01:53:38 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][280/312]	eta 0:00:15 lr 0.003252	time 0.4497 (0.4735)	model_time 0.4495 (0.4673)	loss 3.6101 (3.5319)	grad_norm 2.7521 (1.5694/0.6956)	mem 16099MB
[2025-01-18 01:53:42 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][290/312]	eta 0:00:10 lr 0.003251	time 0.4564 (0.4735)	model_time 0.4560 (0.4675)	loss 3.1902 (3.5363)	grad_norm 0.8252 (1.5612/0.6881)	mem 16099MB
[2025-01-18 01:53:47 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][300/312]	eta 0:00:05 lr 0.003250	time 0.4445 (0.4726)	model_time 0.4445 (0.4668)	loss 3.3709 (3.5379)	grad_norm 1.2455 (1.5724/0.7046)	mem 16099MB
[2025-01-18 01:53:52 internimage_t_1k_224] (main.py 510): INFO Train: [85/300][310/312]	eta 0:00:00 lr 0.003250	time 0.5195 (0.4722)	model_time 0.5194 (0.4665)	loss 3.4084 (3.5389)	grad_norm 0.5174 (1.5644/0.7091)	mem 16099MB
[2025-01-18 01:53:52 internimage_t_1k_224] (main.py 519): INFO EPOCH 85 training takes 0:02:27
[2025-01-18 01:53:52 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_85.pth saving......
[2025-01-18 01:53:53 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_85.pth saved !!!
[2025-01-18 01:54:01 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.656 (7.656)	Loss 0.9518 (0.9518)	Acc@1 79.932 (79.932)	Acc@5 95.898 (95.898)	Mem 16099MB
[2025-01-18 01:54:04 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.028)	Loss 1.3028 (1.1210)	Acc@1 72.607 (76.278)	Acc@5 91.162 (93.659)	Mem 16099MB
[2025-01-18 01:54:05 internimage_t_1k_224] (main.py 575): INFO [Epoch:85] * Acc@1 76.314 Acc@5 93.690
[2025-01-18 01:54:05 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.3%
[2025-01-18 01:54:05 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.40%
[2025-01-18 01:54:13 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.205 (8.205)	Loss 1.1067 (1.1067)	Acc@1 76.587 (76.587)	Acc@5 94.507 (94.507)	Mem 16099MB
[2025-01-18 01:54:17 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.100 (1.102)	Loss 1.5841 (1.3029)	Acc@1 66.748 (72.989)	Acc@5 88.159 (91.519)	Mem 16099MB
[2025-01-18 01:54:17 internimage_t_1k_224] (main.py 575): INFO [Epoch:85] * Acc@1 72.947 Acc@5 91.581
[2025-01-18 01:54:17 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 72.9%
[2025-01-18 01:54:17 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:54:18 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:54:18 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 72.95%
[2025-01-18 01:54:21 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][0/312]	eta 0:14:05 lr 0.003250	time 2.7086 (2.7086)	model_time 0.4658 (0.4658)	loss 2.4212 (2.4212)	grad_norm 1.0642 (1.0642/0.0000)	mem 16099MB
[2025-01-18 01:54:26 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][10/312]	eta 0:03:20 lr 0.003249	time 0.4544 (0.6648)	model_time 0.4540 (0.4606)	loss 3.1176 (3.1767)	grad_norm 1.0952 (1.4013/0.4952)	mem 16099MB
[2025-01-18 01:54:30 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][20/312]	eta 0:02:47 lr 0.003249	time 0.5364 (0.5741)	model_time 0.5360 (0.4669)	loss 3.8703 (3.3787)	grad_norm 1.0925 (1.5130/0.6006)	mem 16099MB
[2025-01-18 01:54:35 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][30/312]	eta 0:02:31 lr 0.003248	time 0.4710 (0.5359)	model_time 0.4706 (0.4632)	loss 3.8017 (3.4720)	grad_norm 1.1425 (1.4815/0.5324)	mem 16099MB
[2025-01-18 01:54:39 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][40/312]	eta 0:02:20 lr 0.003248	time 0.4483 (0.5156)	model_time 0.4481 (0.4605)	loss 4.1952 (3.5080)	grad_norm 2.3190 (1.5022/0.5401)	mem 16099MB
[2025-01-18 01:54:44 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][50/312]	eta 0:02:12 lr 0.003247	time 0.4594 (0.5076)	model_time 0.4592 (0.4632)	loss 4.3149 (3.5224)	grad_norm 1.5720 (1.5545/0.5441)	mem 16099MB
[2025-01-18 01:54:49 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][60/312]	eta 0:02:06 lr 0.003247	time 0.4472 (0.5002)	model_time 0.4470 (0.4630)	loss 2.8200 (3.4824)	grad_norm 1.0618 (1.4852/0.5430)	mem 16099MB
[2025-01-18 01:54:53 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][70/312]	eta 0:01:59 lr 0.003246	time 0.4422 (0.4957)	model_time 0.4417 (0.4637)	loss 3.3395 (3.5085)	grad_norm 1.0954 (1.4662/0.5349)	mem 16099MB
[2025-01-18 01:54:58 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][80/312]	eta 0:01:54 lr 0.003246	time 0.5127 (0.4938)	model_time 0.5123 (0.4657)	loss 3.4184 (3.5049)	grad_norm 1.4424 (1.5447/0.6845)	mem 16099MB
[2025-01-18 01:55:03 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][90/312]	eta 0:01:49 lr 0.003245	time 0.4451 (0.4935)	model_time 0.4447 (0.4684)	loss 3.3138 (3.5014)	grad_norm 1.3618 (1.5008/0.6660)	mem 16099MB
[2025-01-18 01:55:08 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][100/312]	eta 0:01:44 lr 0.003245	time 0.5308 (0.4925)	model_time 0.5306 (0.4699)	loss 3.7168 (3.4797)	grad_norm 1.2205 (1.4717/0.6475)	mem 16099MB
[2025-01-18 01:55:13 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][110/312]	eta 0:01:38 lr 0.003244	time 0.4546 (0.4901)	model_time 0.4541 (0.4694)	loss 3.3980 (3.4830)	grad_norm 1.4450 (1.4408/0.6300)	mem 16099MB
[2025-01-18 01:55:17 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][120/312]	eta 0:01:33 lr 0.003244	time 0.4526 (0.4871)	model_time 0.4525 (0.4682)	loss 3.7844 (3.4956)	grad_norm 1.8359 (1.4804/0.6760)	mem 16099MB
[2025-01-18 01:55:22 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][130/312]	eta 0:01:28 lr 0.003243	time 0.4410 (0.4848)	model_time 0.4405 (0.4672)	loss 2.8258 (3.5030)	grad_norm 1.0247 (1.4991/0.6795)	mem 16099MB
[2025-01-18 01:55:27 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][140/312]	eta 0:01:23 lr 0.003243	time 0.4531 (0.4848)	model_time 0.4527 (0.4684)	loss 2.8938 (3.4924)	grad_norm 1.9226 (1.5229/0.6861)	mem 16099MB
[2025-01-18 01:55:31 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][150/312]	eta 0:01:18 lr 0.003242	time 0.4497 (0.4831)	model_time 0.4496 (0.4678)	loss 3.3302 (3.4835)	grad_norm 1.1548 (1.5287/0.6744)	mem 16099MB
[2025-01-18 01:55:36 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][160/312]	eta 0:01:13 lr 0.003242	time 0.5326 (0.4817)	model_time 0.5321 (0.4673)	loss 3.8455 (3.4886)	grad_norm 0.8318 (1.5333/0.6787)	mem 16099MB
[2025-01-18 01:55:40 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][170/312]	eta 0:01:08 lr 0.003241	time 0.4545 (0.4807)	model_time 0.4543 (0.4671)	loss 4.0452 (3.4964)	grad_norm 2.2328 (1.5160/0.6683)	mem 16099MB
[2025-01-18 01:55:45 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][180/312]	eta 0:01:03 lr 0.003240	time 0.4493 (0.4794)	model_time 0.4491 (0.4666)	loss 3.7544 (3.4852)	grad_norm 1.3475 (1.5163/0.6694)	mem 16099MB
[2025-01-18 01:55:50 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][190/312]	eta 0:00:58 lr 0.003240	time 0.4474 (0.4786)	model_time 0.4470 (0.4664)	loss 2.9928 (3.4748)	grad_norm 3.4903 (1.5328/0.7030)	mem 16099MB
[2025-01-18 01:55:54 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][200/312]	eta 0:00:53 lr 0.003239	time 0.4476 (0.4774)	model_time 0.4474 (0.4658)	loss 3.6928 (3.4824)	grad_norm 1.3675 (1.5284/0.6973)	mem 16099MB
[2025-01-18 01:55:59 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][210/312]	eta 0:00:48 lr 0.003239	time 0.4467 (0.4771)	model_time 0.4463 (0.4661)	loss 3.6895 (3.4815)	grad_norm 1.0284 (1.5408/0.7168)	mem 16099MB
[2025-01-18 01:56:04 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][220/312]	eta 0:00:43 lr 0.003238	time 0.4435 (0.4765)	model_time 0.4431 (0.4660)	loss 3.6235 (3.4918)	grad_norm 1.5412 (1.5394/0.7110)	mem 16099MB
[2025-01-18 01:56:08 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][230/312]	eta 0:00:39 lr 0.003238	time 0.4663 (0.4757)	model_time 0.4661 (0.4656)	loss 4.3152 (3.4899)	grad_norm 0.8908 (1.5466/0.7260)	mem 16099MB
[2025-01-18 01:56:13 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][240/312]	eta 0:00:34 lr 0.003237	time 0.4586 (0.4750)	model_time 0.4581 (0.4653)	loss 3.1204 (3.4785)	grad_norm 0.9308 (1.5549/0.7230)	mem 16099MB
[2025-01-18 01:56:17 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][250/312]	eta 0:00:29 lr 0.003237	time 0.4742 (0.4749)	model_time 0.4738 (0.4656)	loss 4.2247 (3.4802)	grad_norm 1.0825 (1.5544/0.7140)	mem 16099MB
[2025-01-18 01:56:22 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][260/312]	eta 0:00:24 lr 0.003236	time 0.4526 (0.4744)	model_time 0.4524 (0.4653)	loss 4.3236 (3.4950)	grad_norm 1.7986 (1.5487/0.7021)	mem 16099MB
[2025-01-18 01:56:27 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][270/312]	eta 0:00:19 lr 0.003236	time 0.4672 (0.4744)	model_time 0.4670 (0.4657)	loss 3.5732 (3.4969)	grad_norm 1.7706 (1.5620/0.7082)	mem 16099MB
[2025-01-18 01:56:32 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][280/312]	eta 0:00:15 lr 0.003235	time 0.4691 (0.4751)	model_time 0.4689 (0.4667)	loss 3.5818 (3.5035)	grad_norm 1.1723 (1.5593/0.7022)	mem 16099MB
[2025-01-18 01:56:36 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][290/312]	eta 0:00:10 lr 0.003235	time 0.4475 (0.4748)	model_time 0.4474 (0.4667)	loss 4.1195 (3.5099)	grad_norm 1.6495 (1.5497/0.6944)	mem 16099MB
[2025-01-18 01:56:41 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][300/312]	eta 0:00:05 lr 0.003234	time 0.4382 (0.4748)	model_time 0.4381 (0.4669)	loss 3.6316 (3.5083)	grad_norm 1.5427 (1.5465/0.6892)	mem 16099MB
[2025-01-18 01:56:46 internimage_t_1k_224] (main.py 510): INFO Train: [86/300][310/312]	eta 0:00:00 lr 0.003234	time 0.4445 (0.4748)	model_time 0.4444 (0.4672)	loss 3.4305 (3.5060)	grad_norm 1.0083 (1.5469/0.6882)	mem 16099MB
[2025-01-18 01:56:46 internimage_t_1k_224] (main.py 519): INFO EPOCH 86 training takes 0:02:28
[2025-01-18 01:56:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_86.pth saving......
[2025-01-18 01:56:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_86.pth saved !!!
[2025-01-18 01:56:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.092 (8.092)	Loss 0.9684 (0.9684)	Acc@1 79.224 (79.224)	Acc@5 95.142 (95.142)	Mem 16099MB
[2025-01-18 01:56:59 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.073)	Loss 1.3469 (1.1187)	Acc@1 70.776 (76.114)	Acc@5 90.796 (93.359)	Mem 16099MB
[2025-01-18 01:56:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:86] * Acc@1 75.970 Acc@5 93.378
[2025-01-18 01:56:59 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.0%
[2025-01-18 01:56:59 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.40%
[2025-01-18 01:57:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.538 (8.538)	Loss 1.0887 (1.0887)	Acc@1 76.855 (76.855)	Acc@5 94.629 (94.629)	Mem 16099MB
[2025-01-18 01:57:12 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.169)	Loss 1.5626 (1.2840)	Acc@1 66.992 (73.273)	Acc@5 88.354 (91.688)	Mem 16099MB
[2025-01-18 01:57:12 internimage_t_1k_224] (main.py 575): INFO [Epoch:86] * Acc@1 73.213 Acc@5 91.739
[2025-01-18 01:57:12 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 73.2%
[2025-01-18 01:57:12 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 01:57:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 01:57:14 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 73.21%
[2025-01-18 01:57:16 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][0/312]	eta 0:11:25 lr 0.003234	time 2.1985 (2.1985)	model_time 0.4600 (0.4600)	loss 3.1737 (3.1737)	grad_norm 1.1627 (1.1627/0.0000)	mem 16099MB
[2025-01-18 01:57:21 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][10/312]	eta 0:03:11 lr 0.003233	time 0.4587 (0.6326)	model_time 0.4585 (0.4743)	loss 3.6119 (3.7366)	grad_norm 0.9996 (1.3731/0.6526)	mem 16099MB
[2025-01-18 01:57:26 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][20/312]	eta 0:02:45 lr 0.003233	time 0.5983 (0.5682)	model_time 0.5979 (0.4851)	loss 3.8067 (3.7001)	grad_norm 1.4947 (1.3851/0.5196)	mem 16099MB
[2025-01-18 01:57:31 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][30/312]	eta 0:02:30 lr 0.003232	time 0.4552 (0.5340)	model_time 0.4547 (0.4776)	loss 3.4268 (3.6064)	grad_norm 4.7451 (1.7327/0.9501)	mem 16099MB
[2025-01-18 01:57:35 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][40/312]	eta 0:02:19 lr 0.003231	time 0.4624 (0.5142)	model_time 0.4623 (0.4715)	loss 3.0798 (3.5671)	grad_norm 1.3206 (1.6959/0.8483)	mem 16099MB
[2025-01-18 01:57:40 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][50/312]	eta 0:02:13 lr 0.003231	time 0.4508 (0.5100)	model_time 0.4504 (0.4756)	loss 4.2142 (3.5675)	grad_norm 1.8018 (1.6279/0.7932)	mem 16099MB
[2025-01-18 01:57:45 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][60/312]	eta 0:02:06 lr 0.003230	time 0.4493 (0.5006)	model_time 0.4488 (0.4718)	loss 3.4653 (3.5717)	grad_norm 1.4948 (1.6240/0.7486)	mem 16099MB
[2025-01-18 01:57:49 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][70/312]	eta 0:01:59 lr 0.003230	time 0.4488 (0.4946)	model_time 0.4487 (0.4697)	loss 3.9612 (3.5168)	grad_norm 0.9890 (1.6073/0.7161)	mem 16099MB
[2025-01-18 01:57:54 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][80/312]	eta 0:01:53 lr 0.003229	time 0.4720 (0.4896)	model_time 0.4718 (0.4678)	loss 3.3174 (3.4847)	grad_norm 1.0183 (1.5928/0.6871)	mem 16099MB
[2025-01-18 01:57:58 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][90/312]	eta 0:01:47 lr 0.003229	time 0.4535 (0.4860)	model_time 0.4533 (0.4665)	loss 4.4637 (3.4594)	grad_norm 2.5703 (1.6068/0.6828)	mem 16099MB
[2025-01-18 01:58:03 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][100/312]	eta 0:01:42 lr 0.003228	time 0.4433 (0.4830)	model_time 0.4431 (0.4655)	loss 2.4867 (3.4316)	grad_norm 2.6107 (1.6011/0.6752)	mem 16099MB
[2025-01-18 01:58:07 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][110/312]	eta 0:01:37 lr 0.003228	time 0.4463 (0.4809)	model_time 0.4458 (0.4649)	loss 4.1115 (3.4587)	grad_norm 0.7863 (1.5984/0.6826)	mem 16099MB
[2025-01-18 01:58:12 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][120/312]	eta 0:01:31 lr 0.003227	time 0.4485 (0.4788)	model_time 0.4483 (0.4640)	loss 3.6425 (3.4777)	grad_norm 2.5483 (1.6383/0.6941)	mem 16099MB
[2025-01-18 01:58:17 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][130/312]	eta 0:01:26 lr 0.003227	time 0.4634 (0.4777)	model_time 0.4633 (0.4640)	loss 2.7514 (3.4838)	grad_norm 1.3322 (1.6274/0.6749)	mem 16099MB
[2025-01-18 01:58:21 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][140/312]	eta 0:01:22 lr 0.003226	time 0.4506 (0.4773)	model_time 0.4505 (0.4646)	loss 3.7375 (3.4733)	grad_norm 2.2206 (1.6144/0.6701)	mem 16099MB
[2025-01-18 01:58:26 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][150/312]	eta 0:01:17 lr 0.003226	time 0.4550 (0.4779)	model_time 0.4546 (0.4660)	loss 2.3995 (3.4710)	grad_norm 0.9974 (1.5888/0.6642)	mem 16099MB
[2025-01-18 01:58:31 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][160/312]	eta 0:01:12 lr 0.003225	time 0.5422 (0.4784)	model_time 0.5421 (0.4672)	loss 3.5380 (3.4652)	grad_norm 0.8650 (1.5577/0.6593)	mem 16099MB
[2025-01-18 01:58:36 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][170/312]	eta 0:01:07 lr 0.003225	time 0.4688 (0.4783)	model_time 0.4684 (0.4678)	loss 2.6356 (3.4576)	grad_norm 1.9013 (1.5529/0.6526)	mem 16099MB
[2025-01-18 01:58:41 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][180/312]	eta 0:01:03 lr 0.003224	time 0.4524 (0.4776)	model_time 0.4523 (0.4676)	loss 4.2923 (3.4775)	grad_norm 2.4410 (1.5615/0.6522)	mem 16099MB
[2025-01-18 01:58:45 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][190/312]	eta 0:00:58 lr 0.003224	time 0.4469 (0.4778)	model_time 0.4464 (0.4682)	loss 2.7823 (3.4734)	grad_norm 2.1397 (1.5581/0.6517)	mem 16099MB
[2025-01-18 01:58:50 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][200/312]	eta 0:00:53 lr 0.003223	time 0.4528 (0.4771)	model_time 0.4527 (0.4680)	loss 4.3801 (3.4645)	grad_norm 2.8080 (1.5633/0.6517)	mem 16099MB
[2025-01-18 01:58:55 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][210/312]	eta 0:00:48 lr 0.003222	time 0.4523 (0.4765)	model_time 0.4519 (0.4677)	loss 2.6247 (3.4562)	grad_norm 1.5195 (1.5550/0.6458)	mem 16099MB
[2025-01-18 01:58:59 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][220/312]	eta 0:00:43 lr 0.003222	time 0.4522 (0.4761)	model_time 0.4518 (0.4677)	loss 3.4570 (3.4627)	grad_norm 1.7581 (1.5499/0.6393)	mem 16099MB
[2025-01-18 01:59:04 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][230/312]	eta 0:00:39 lr 0.003221	time 0.5476 (0.4761)	model_time 0.5472 (0.4681)	loss 3.4866 (3.4675)	grad_norm 2.9954 (1.5640/0.6715)	mem 16099MB
[2025-01-18 01:59:09 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][240/312]	eta 0:00:34 lr 0.003221	time 0.4456 (0.4756)	model_time 0.4451 (0.4679)	loss 3.7341 (3.4692)	grad_norm 1.3296 (1.5847/0.6857)	mem 16099MB
[2025-01-18 01:59:13 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][250/312]	eta 0:00:29 lr 0.003220	time 0.4532 (0.4751)	model_time 0.4527 (0.4677)	loss 2.9800 (3.4753)	grad_norm 1.2280 (1.6021/0.7028)	mem 16099MB
[2025-01-18 01:59:18 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][260/312]	eta 0:00:24 lr 0.003220	time 0.4627 (0.4745)	model_time 0.4623 (0.4673)	loss 3.9306 (3.4756)	grad_norm 0.8173 (1.5884/0.6989)	mem 16099MB
[2025-01-18 01:59:23 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][270/312]	eta 0:00:19 lr 0.003219	time 0.4516 (0.4740)	model_time 0.4514 (0.4670)	loss 3.7328 (3.4748)	grad_norm 1.4073 (1.5802/0.6917)	mem 16099MB
[2025-01-18 01:59:27 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][280/312]	eta 0:00:15 lr 0.003219	time 0.4428 (0.4735)	model_time 0.4426 (0.4668)	loss 4.3457 (3.4742)	grad_norm 2.0058 (1.5714/0.6858)	mem 16099MB
[2025-01-18 01:59:32 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][290/312]	eta 0:00:10 lr 0.003218	time 0.4494 (0.4740)	model_time 0.4490 (0.4675)	loss 3.5881 (3.4696)	grad_norm 1.8233 (1.6038/0.7266)	mem 16099MB
[2025-01-18 01:59:36 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][300/312]	eta 0:00:05 lr 0.003218	time 0.4390 (0.4732)	model_time 0.4389 (0.4669)	loss 3.7173 (3.4716)	grad_norm 1.9882 (1.5988/0.7217)	mem 16099MB
[2025-01-18 01:59:41 internimage_t_1k_224] (main.py 510): INFO Train: [87/300][310/312]	eta 0:00:00 lr 0.003217	time 0.4350 (0.4723)	model_time 0.4350 (0.4663)	loss 2.9095 (3.4710)	grad_norm 1.3821 (1.6053/0.7175)	mem 16099MB
[2025-01-18 01:59:41 internimage_t_1k_224] (main.py 519): INFO EPOCH 87 training takes 0:02:27
[2025-01-18 01:59:41 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_87.pth saving......
[2025-01-18 01:59:42 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_87.pth saved !!!
[2025-01-18 01:59:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 9.353 (9.353)	Loss 0.9400 (0.9400)	Acc@1 79.858 (79.858)	Acc@5 95.166 (95.166)	Mem 16099MB
[2025-01-18 01:59:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.286)	Loss 1.3421 (1.1031)	Acc@1 70.459 (76.400)	Acc@5 91.260 (93.490)	Mem 16099MB
[2025-01-18 01:59:57 internimage_t_1k_224] (main.py 575): INFO [Epoch:87] * Acc@1 76.296 Acc@5 93.500
[2025-01-18 01:59:57 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.3%
[2025-01-18 01:59:57 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.40%
[2025-01-18 02:00:05 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.371 (8.371)	Loss 1.0718 (1.0718)	Acc@1 77.148 (77.148)	Acc@5 94.800 (94.800)	Mem 16099MB
[2025-01-18 02:00:09 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.134)	Loss 1.5425 (1.2660)	Acc@1 67.261 (73.551)	Acc@5 88.550 (91.852)	Mem 16099MB
[2025-01-18 02:00:09 internimage_t_1k_224] (main.py 575): INFO [Epoch:87] * Acc@1 73.488 Acc@5 91.907
[2025-01-18 02:00:09 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 73.5%
[2025-01-18 02:00:09 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:00:11 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:00:11 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 73.49%
[2025-01-18 02:00:14 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][0/312]	eta 0:14:26 lr 0.003217	time 2.7784 (2.7784)	model_time 0.4725 (0.4725)	loss 2.5247 (2.5247)	grad_norm 2.5085 (2.5085/0.0000)	mem 16099MB
[2025-01-18 02:00:18 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][10/312]	eta 0:03:20 lr 0.003217	time 0.4454 (0.6643)	model_time 0.4450 (0.4544)	loss 3.1230 (3.1387)	grad_norm 1.2108 (1.4326/0.4042)	mem 16099MB
[2025-01-18 02:00:23 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][20/312]	eta 0:02:46 lr 0.003216	time 0.4514 (0.5713)	model_time 0.4509 (0.4612)	loss 2.5734 (3.2519)	grad_norm 1.1983 (1.3045/0.4214)	mem 16099MB
[2025-01-18 02:00:28 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][30/312]	eta 0:02:30 lr 0.003216	time 0.4645 (0.5342)	model_time 0.4641 (0.4595)	loss 3.1760 (3.3426)	grad_norm 1.3185 (1.2923/0.3914)	mem 16099MB
[2025-01-18 02:00:32 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][40/312]	eta 0:02:20 lr 0.003215	time 0.4831 (0.5169)	model_time 0.4829 (0.4603)	loss 4.3494 (3.4011)	grad_norm 1.0608 (1.4521/0.6036)	mem 16099MB
[2025-01-18 02:00:37 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][50/312]	eta 0:02:13 lr 0.003214	time 0.4412 (0.5083)	model_time 0.4410 (0.4628)	loss 3.4292 (3.3990)	grad_norm 2.5028 (1.4377/0.5911)	mem 16099MB
[2025-01-18 02:00:42 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][60/312]	eta 0:02:07 lr 0.003214	time 0.4461 (0.5045)	model_time 0.4459 (0.4664)	loss 2.7047 (3.3684)	grad_norm 2.2274 (1.4421/0.5669)	mem 16099MB
[2025-01-18 02:00:47 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][70/312]	eta 0:02:01 lr 0.003213	time 0.4482 (0.5003)	model_time 0.4481 (0.4675)	loss 3.2955 (3.3934)	grad_norm 0.9547 (1.3966/0.5688)	mem 16099MB
[2025-01-18 02:00:52 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][80/312]	eta 0:01:56 lr 0.003213	time 0.4751 (0.5011)	model_time 0.4747 (0.4723)	loss 2.5528 (3.4210)	grad_norm 1.7227 (1.3970/0.5760)	mem 16099MB
[2025-01-18 02:00:56 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][90/312]	eta 0:01:50 lr 0.003212	time 0.7365 (0.4991)	model_time 0.7363 (0.4734)	loss 3.9661 (3.4390)	grad_norm 1.2571 (1.4937/0.6924)	mem 16099MB
[2025-01-18 02:01:01 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][100/312]	eta 0:01:44 lr 0.003212	time 0.4558 (0.4950)	model_time 0.4556 (0.4719)	loss 4.4778 (3.4593)	grad_norm 1.2542 (1.4741/0.6721)	mem 16099MB
[2025-01-18 02:01:06 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][110/312]	eta 0:01:39 lr 0.003211	time 0.4539 (0.4935)	model_time 0.4535 (0.4724)	loss 2.1188 (3.4412)	grad_norm 1.1863 (1.4697/0.6545)	mem 16099MB
[2025-01-18 02:01:10 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][120/312]	eta 0:01:34 lr 0.003211	time 0.4528 (0.4914)	model_time 0.4523 (0.4720)	loss 3.3806 (3.4214)	grad_norm 1.4635 (1.4885/0.6444)	mem 16099MB
[2025-01-18 02:01:15 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][130/312]	eta 0:01:29 lr 0.003210	time 0.4818 (0.4899)	model_time 0.4814 (0.4719)	loss 3.7471 (3.4294)	grad_norm 2.1914 (1.5669/0.7599)	mem 16099MB
[2025-01-18 02:01:20 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][140/312]	eta 0:01:23 lr 0.003210	time 0.4454 (0.4872)	model_time 0.4452 (0.4706)	loss 3.5248 (3.4285)	grad_norm 1.6962 (1.5649/0.7430)	mem 16099MB
[2025-01-18 02:01:24 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][150/312]	eta 0:01:18 lr 0.003209	time 0.4554 (0.4864)	model_time 0.4552 (0.4708)	loss 3.8319 (3.4464)	grad_norm 0.8273 (1.5311/0.7320)	mem 16099MB
[2025-01-18 02:01:29 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][160/312]	eta 0:01:14 lr 0.003209	time 0.4421 (0.4869)	model_time 0.4416 (0.4723)	loss 3.6537 (3.4428)	grad_norm 1.8675 (1.5411/0.7216)	mem 16099MB
[2025-01-18 02:01:34 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][170/312]	eta 0:01:08 lr 0.003208	time 0.4658 (0.4851)	model_time 0.4656 (0.4713)	loss 3.5047 (3.4350)	grad_norm 1.3353 (1.5451/0.7102)	mem 16099MB
[2025-01-18 02:01:39 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][180/312]	eta 0:01:03 lr 0.003208	time 0.4567 (0.4836)	model_time 0.4565 (0.4705)	loss 3.2661 (3.4505)	grad_norm 1.2807 (1.5550/0.7341)	mem 16099MB
[2025-01-18 02:01:43 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][190/312]	eta 0:00:58 lr 0.003207	time 0.4522 (0.4832)	model_time 0.4517 (0.4708)	loss 3.2864 (3.4404)	grad_norm 1.6649 (1.5399/0.7210)	mem 16099MB
[2025-01-18 02:01:48 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][200/312]	eta 0:00:54 lr 0.003206	time 0.5367 (0.4829)	model_time 0.5366 (0.4710)	loss 4.4660 (3.4496)	grad_norm 1.6164 (1.5266/0.7099)	mem 16099MB
[2025-01-18 02:01:53 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][210/312]	eta 0:00:49 lr 0.003206	time 0.4550 (0.4820)	model_time 0.4548 (0.4707)	loss 3.8063 (3.4589)	grad_norm 0.8847 (1.5056/0.7013)	mem 16099MB
[2025-01-18 02:01:57 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][220/312]	eta 0:00:44 lr 0.003205	time 0.4623 (0.4811)	model_time 0.4621 (0.4703)	loss 2.3851 (3.4387)	grad_norm 1.9018 (1.5159/0.6942)	mem 16099MB
[2025-01-18 02:02:02 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][230/312]	eta 0:00:39 lr 0.003205	time 0.4617 (0.4802)	model_time 0.4615 (0.4698)	loss 3.7520 (3.4442)	grad_norm 1.9984 (1.5441/0.7168)	mem 16099MB
[2025-01-18 02:02:07 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][240/312]	eta 0:00:34 lr 0.003204	time 0.4507 (0.4794)	model_time 0.4503 (0.4695)	loss 3.5155 (3.4502)	grad_norm 0.9534 (1.5762/0.7596)	mem 16099MB
[2025-01-18 02:02:11 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][250/312]	eta 0:00:29 lr 0.003204	time 0.4501 (0.4789)	model_time 0.4499 (0.4693)	loss 2.9476 (3.4550)	grad_norm 0.9955 (1.5770/0.7595)	mem 16099MB
[2025-01-18 02:02:16 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][260/312]	eta 0:00:24 lr 0.003203	time 0.4500 (0.4784)	model_time 0.4498 (0.4692)	loss 3.7355 (3.4493)	grad_norm 0.9878 (1.5642/0.7521)	mem 16099MB
[2025-01-18 02:02:20 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][270/312]	eta 0:00:20 lr 0.003203	time 0.4835 (0.4776)	model_time 0.4831 (0.4687)	loss 3.6424 (3.4532)	grad_norm 0.9653 (1.5546/0.7429)	mem 16099MB
[2025-01-18 02:02:25 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][280/312]	eta 0:00:15 lr 0.003202	time 0.4553 (0.4777)	model_time 0.4551 (0.4691)	loss 2.9911 (3.4481)	grad_norm 0.8984 (1.5354/0.7368)	mem 16099MB
[2025-01-18 02:02:30 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][290/312]	eta 0:00:10 lr 0.003202	time 0.4446 (0.4770)	model_time 0.4444 (0.4687)	loss 3.1838 (3.4487)	grad_norm 1.1041 (1.5430/0.7321)	mem 16099MB
[2025-01-18 02:02:35 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][300/312]	eta 0:00:05 lr 0.003201	time 0.4401 (0.4768)	model_time 0.4400 (0.4688)	loss 3.2842 (3.4480)	grad_norm 0.9855 (1.5560/0.7372)	mem 16099MB
[2025-01-18 02:02:39 internimage_t_1k_224] (main.py 510): INFO Train: [88/300][310/312]	eta 0:00:00 lr 0.003201	time 0.4418 (0.4766)	model_time 0.4417 (0.4688)	loss 3.1008 (3.4445)	grad_norm 1.9500 (1.5674/0.7454)	mem 16099MB
[2025-01-18 02:02:40 internimage_t_1k_224] (main.py 519): INFO EPOCH 88 training takes 0:02:28
[2025-01-18 02:02:40 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_88.pth saving......
[2025-01-18 02:02:41 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_88.pth saved !!!
[2025-01-18 02:02:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.477 (7.477)	Loss 0.9146 (0.9146)	Acc@1 80.396 (80.396)	Acc@5 95.581 (95.581)	Mem 16099MB
[2025-01-18 02:02:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.009)	Loss 1.3128 (1.0897)	Acc@1 70.850 (76.434)	Acc@5 90.894 (93.468)	Mem 16099MB
[2025-01-18 02:02:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:88] * Acc@1 76.396 Acc@5 93.520
[2025-01-18 02:02:52 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.4%
[2025-01-18 02:02:52 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.40%
[2025-01-18 02:03:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.212 (8.212)	Loss 1.0567 (1.0567)	Acc@1 77.393 (77.393)	Acc@5 94.946 (94.946)	Mem 16099MB
[2025-01-18 02:03:04 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.105)	Loss 1.5235 (1.2492)	Acc@1 67.407 (73.837)	Acc@5 88.770 (92.012)	Mem 16099MB
[2025-01-18 02:03:04 internimage_t_1k_224] (main.py 575): INFO [Epoch:88] * Acc@1 73.788 Acc@5 92.063
[2025-01-18 02:03:04 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 73.8%
[2025-01-18 02:03:04 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:03:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:03:06 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 73.79%
[2025-01-18 02:03:08 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][0/312]	eta 0:13:03 lr 0.003201	time 2.5120 (2.5120)	model_time 0.4872 (0.4872)	loss 4.1135 (4.1135)	grad_norm 1.3858 (1.3858/0.0000)	mem 16099MB
[2025-01-18 02:03:13 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][10/312]	eta 0:03:18 lr 0.003200	time 0.4504 (0.6557)	model_time 0.4503 (0.4713)	loss 3.2172 (3.6267)	grad_norm 2.7832 (1.3265/0.5239)	mem 16099MB
[2025-01-18 02:03:18 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][20/312]	eta 0:02:43 lr 0.003199	time 0.4537 (0.5591)	model_time 0.4535 (0.4623)	loss 3.6469 (3.5062)	grad_norm 0.9661 (1.5935/0.7607)	mem 16099MB
[2025-01-18 02:03:22 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][30/312]	eta 0:02:28 lr 0.003199	time 0.4696 (0.5256)	model_time 0.4694 (0.4600)	loss 4.3448 (3.4994)	grad_norm 1.2578 (1.5653/0.6621)	mem 16099MB
[2025-01-18 02:03:27 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][40/312]	eta 0:02:18 lr 0.003198	time 0.4398 (0.5090)	model_time 0.4394 (0.4593)	loss 4.1669 (3.5402)	grad_norm 2.6592 (1.5688/0.6592)	mem 16099MB
[2025-01-18 02:03:32 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][50/312]	eta 0:02:11 lr 0.003198	time 0.4552 (0.5027)	model_time 0.4547 (0.4627)	loss 4.1112 (3.5116)	grad_norm 1.8888 (1.5474/0.6401)	mem 16099MB
[2025-01-18 02:03:36 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][60/312]	eta 0:02:04 lr 0.003197	time 0.4497 (0.4948)	model_time 0.4492 (0.4613)	loss 3.7949 (3.5252)	grad_norm 0.9943 (1.4924/0.6131)	mem 16099MB
[2025-01-18 02:03:41 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][70/312]	eta 0:01:58 lr 0.003197	time 0.4548 (0.4897)	model_time 0.4547 (0.4608)	loss 4.1749 (3.5283)	grad_norm 2.0240 (1.5095/0.5891)	mem 16099MB
[2025-01-18 02:03:45 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][80/312]	eta 0:01:52 lr 0.003196	time 0.4492 (0.4865)	model_time 0.4491 (0.4611)	loss 3.9514 (3.5385)	grad_norm 0.9045 (1.5102/0.5954)	mem 16099MB
[2025-01-18 02:03:50 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][90/312]	eta 0:01:47 lr 0.003196	time 0.4478 (0.4837)	model_time 0.4476 (0.4611)	loss 4.0538 (3.5541)	grad_norm 1.1441 (1.5572/0.6527)	mem 16099MB
[2025-01-18 02:03:55 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][100/312]	eta 0:01:42 lr 0.003195	time 0.4522 (0.4826)	model_time 0.4520 (0.4622)	loss 3.0976 (3.5575)	grad_norm 1.6474 (1.5265/0.6380)	mem 16099MB
[2025-01-18 02:03:59 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][110/312]	eta 0:01:37 lr 0.003195	time 0.4788 (0.4812)	model_time 0.4786 (0.4626)	loss 3.6614 (3.5716)	grad_norm 0.7745 (1.5614/0.6875)	mem 16099MB
[2025-01-18 02:04:04 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][120/312]	eta 0:01:32 lr 0.003194	time 0.4532 (0.4801)	model_time 0.4528 (0.4630)	loss 3.7578 (3.5569)	grad_norm 0.8637 (1.5349/0.6686)	mem 16099MB
[2025-01-18 02:04:09 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][130/312]	eta 0:01:27 lr 0.003194	time 0.4444 (0.4798)	model_time 0.4443 (0.4640)	loss 2.7953 (3.5348)	grad_norm 1.8069 (1.5128/0.6509)	mem 16099MB
[2025-01-18 02:04:14 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][140/312]	eta 0:01:22 lr 0.003193	time 0.4593 (0.4797)	model_time 0.4591 (0.4649)	loss 3.2110 (3.5067)	grad_norm 1.3389 (1.5455/0.6695)	mem 16099MB
[2025-01-18 02:04:18 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][150/312]	eta 0:01:17 lr 0.003193	time 0.4981 (0.4790)	model_time 0.4979 (0.4653)	loss 3.8211 (3.5033)	grad_norm 5.0947 (1.5808/0.7240)	mem 16099MB
[2025-01-18 02:04:23 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][160/312]	eta 0:01:12 lr 0.003192	time 0.4473 (0.4788)	model_time 0.4472 (0.4659)	loss 3.3540 (3.5053)	grad_norm 1.0512 (1.5808/0.7292)	mem 16099MB
[2025-01-18 02:04:28 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][170/312]	eta 0:01:08 lr 0.003191	time 0.4487 (0.4804)	model_time 0.4486 (0.4682)	loss 2.4158 (3.4928)	grad_norm 1.1136 (1.5587/0.7170)	mem 16099MB
[2025-01-18 02:04:33 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][180/312]	eta 0:01:03 lr 0.003191	time 0.4418 (0.4795)	model_time 0.4413 (0.4679)	loss 4.2668 (3.4984)	grad_norm 1.2500 (1.5370/0.7081)	mem 16099MB
[2025-01-18 02:04:37 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][190/312]	eta 0:00:58 lr 0.003190	time 0.4525 (0.4783)	model_time 0.4523 (0.4673)	loss 3.0883 (3.4891)	grad_norm 1.5787 (1.5282/0.6930)	mem 16099MB
[2025-01-18 02:04:42 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][200/312]	eta 0:00:53 lr 0.003190	time 0.4435 (0.4770)	model_time 0.4433 (0.4666)	loss 3.7959 (3.4985)	grad_norm 0.9262 (1.5360/0.6864)	mem 16099MB
[2025-01-18 02:04:46 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][210/312]	eta 0:00:48 lr 0.003189	time 0.4575 (0.4765)	model_time 0.4573 (0.4665)	loss 3.1978 (3.4999)	grad_norm 1.3489 (1.5256/0.6798)	mem 16099MB
[2025-01-18 02:04:51 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][220/312]	eta 0:00:43 lr 0.003189	time 0.4523 (0.4757)	model_time 0.4521 (0.4662)	loss 2.9912 (3.4919)	grad_norm 0.8616 (1.5088/0.6752)	mem 16099MB
[2025-01-18 02:04:56 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][230/312]	eta 0:00:38 lr 0.003188	time 0.4809 (0.4752)	model_time 0.4807 (0.4661)	loss 4.1672 (3.4898)	grad_norm 1.3225 (1.4926/0.6663)	mem 16099MB
[2025-01-18 02:05:00 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][240/312]	eta 0:00:34 lr 0.003188	time 0.4553 (0.4747)	model_time 0.4549 (0.4660)	loss 4.3828 (3.4956)	grad_norm 3.2869 (1.5181/0.7006)	mem 16099MB
[2025-01-18 02:05:05 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][250/312]	eta 0:00:29 lr 0.003187	time 0.5443 (0.4746)	model_time 0.5441 (0.4661)	loss 2.9968 (3.4931)	grad_norm 1.0230 (1.5034/0.6913)	mem 16099MB
[2025-01-18 02:05:10 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][260/312]	eta 0:00:24 lr 0.003187	time 0.4714 (0.4741)	model_time 0.4709 (0.4660)	loss 2.8775 (3.4789)	grad_norm 1.9481 (1.5102/0.6893)	mem 16099MB
[2025-01-18 02:05:14 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][270/312]	eta 0:00:19 lr 0.003186	time 0.4501 (0.4734)	model_time 0.4500 (0.4655)	loss 2.9733 (3.4821)	grad_norm 1.4461 (1.5203/0.6921)	mem 16099MB
[2025-01-18 02:05:19 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][280/312]	eta 0:00:15 lr 0.003186	time 0.4890 (0.4728)	model_time 0.4889 (0.4652)	loss 3.6576 (3.4824)	grad_norm 0.9323 (1.5220/0.6926)	mem 16099MB
[2025-01-18 02:05:23 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][290/312]	eta 0:00:10 lr 0.003185	time 0.4570 (0.4728)	model_time 0.4566 (0.4655)	loss 4.2268 (3.4810)	grad_norm 1.1966 (1.5068/0.6880)	mem 16099MB
[2025-01-18 02:05:28 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][300/312]	eta 0:00:05 lr 0.003184	time 0.4382 (0.4721)	model_time 0.4381 (0.4650)	loss 3.9720 (3.4735)	grad_norm 1.3527 (1.5306/0.7178)	mem 16099MB
[2025-01-18 02:05:33 internimage_t_1k_224] (main.py 510): INFO Train: [89/300][310/312]	eta 0:00:00 lr 0.003184	time 0.5400 (0.4719)	model_time 0.5399 (0.4650)	loss 4.1311 (3.4776)	grad_norm 1.3146 (1.5250/0.7138)	mem 16099MB
[2025-01-18 02:05:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 89 training takes 0:02:27
[2025-01-18 02:05:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_89.pth saving......
[2025-01-18 02:05:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_89.pth saved !!!
[2025-01-18 02:05:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.670 (7.670)	Loss 0.9350 (0.9350)	Acc@1 79.443 (79.443)	Acc@5 95.410 (95.410)	Mem 16099MB
[2025-01-18 02:05:46 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.028)	Loss 1.3153 (1.0906)	Acc@1 71.216 (76.285)	Acc@5 91.357 (93.557)	Mem 16099MB
[2025-01-18 02:05:46 internimage_t_1k_224] (main.py 575): INFO [Epoch:89] * Acc@1 76.334 Acc@5 93.636
[2025-01-18 02:05:46 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.3%
[2025-01-18 02:05:46 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.40%
[2025-01-18 02:05:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.547 (8.547)	Loss 1.0418 (1.0418)	Acc@1 77.734 (77.734)	Acc@5 94.995 (94.995)	Mem 16099MB
[2025-01-18 02:05:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.143)	Loss 1.5048 (1.2328)	Acc@1 67.651 (74.117)	Acc@5 88.989 (92.154)	Mem 16099MB
[2025-01-18 02:05:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:89] * Acc@1 74.072 Acc@5 92.206
[2025-01-18 02:05:58 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 74.1%
[2025-01-18 02:05:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:06:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:06:00 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 74.07%
[2025-01-18 02:06:03 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][0/312]	eta 0:14:12 lr 0.003184	time 2.7312 (2.7312)	model_time 0.4820 (0.4820)	loss 2.6181 (2.6181)	grad_norm 1.4972 (1.4972/0.0000)	mem 16099MB
[2025-01-18 02:06:07 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][10/312]	eta 0:03:20 lr 0.003183	time 0.4531 (0.6623)	model_time 0.4530 (0.4575)	loss 4.1447 (3.7202)	grad_norm 2.3860 (1.3664/0.5137)	mem 16099MB
[2025-01-18 02:06:12 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][20/312]	eta 0:02:48 lr 0.003183	time 0.5358 (0.5778)	model_time 0.5356 (0.4704)	loss 3.6110 (3.4171)	grad_norm 1.1356 (1.6198/0.7175)	mem 16099MB
[2025-01-18 02:06:17 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][30/312]	eta 0:02:32 lr 0.003182	time 0.4544 (0.5415)	model_time 0.4540 (0.4686)	loss 3.6231 (3.4453)	grad_norm 0.8611 (1.6201/0.7312)	mem 16099MB
[2025-01-18 02:06:22 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][40/312]	eta 0:02:23 lr 0.003182	time 0.5449 (0.5267)	model_time 0.5447 (0.4714)	loss 3.0602 (3.4452)	grad_norm 3.2821 (1.6482/0.7151)	mem 16099MB
[2025-01-18 02:06:26 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][50/312]	eta 0:02:15 lr 0.003181	time 0.4521 (0.5167)	model_time 0.4516 (0.4722)	loss 3.7235 (3.4372)	grad_norm 0.7656 (1.6382/0.6866)	mem 16099MB
[2025-01-18 02:06:31 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][60/312]	eta 0:02:08 lr 0.003181	time 0.4585 (0.5107)	model_time 0.4583 (0.4735)	loss 4.1693 (3.3881)	grad_norm 1.0918 (1.5693/0.6578)	mem 16099MB
[2025-01-18 02:06:36 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][70/312]	eta 0:02:03 lr 0.003180	time 0.4473 (0.5101)	model_time 0.4472 (0.4781)	loss 3.7356 (3.4496)	grad_norm 1.3765 (1.5260/0.6352)	mem 16099MB
[2025-01-18 02:06:41 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][80/312]	eta 0:01:57 lr 0.003180	time 0.4472 (0.5065)	model_time 0.4468 (0.4784)	loss 4.0632 (3.4485)	grad_norm 2.6127 (1.5264/0.6662)	mem 16099MB
[2025-01-18 02:06:46 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][90/312]	eta 0:01:51 lr 0.003179	time 0.4523 (0.5005)	model_time 0.4522 (0.4755)	loss 4.2674 (3.4598)	grad_norm 1.6028 (1.5607/0.7256)	mem 16099MB
[2025-01-18 02:06:50 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][100/312]	eta 0:01:45 lr 0.003178	time 0.4509 (0.4974)	model_time 0.4504 (0.4748)	loss 3.5609 (3.4724)	grad_norm 0.6655 (1.5329/0.7066)	mem 16099MB
[2025-01-18 02:06:55 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][110/312]	eta 0:01:39 lr 0.003178	time 0.4455 (0.4946)	model_time 0.4454 (0.4740)	loss 3.3070 (3.4618)	grad_norm 0.8100 (1.5055/0.6877)	mem 16099MB
[2025-01-18 02:06:59 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][120/312]	eta 0:01:34 lr 0.003177	time 0.4622 (0.4914)	model_time 0.4617 (0.4724)	loss 3.6344 (3.4534)	grad_norm 1.1026 (1.4777/0.6686)	mem 16099MB
[2025-01-18 02:07:04 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][130/312]	eta 0:01:29 lr 0.003177	time 0.4495 (0.4898)	model_time 0.4494 (0.4723)	loss 3.2892 (3.4583)	grad_norm 1.2822 (1.4943/0.6771)	mem 16099MB
[2025-01-18 02:07:09 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][140/312]	eta 0:01:23 lr 0.003176	time 0.4406 (0.4875)	model_time 0.4401 (0.4711)	loss 3.1307 (3.4433)	grad_norm 1.5857 (1.5443/0.7194)	mem 16099MB
[2025-01-18 02:07:13 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][150/312]	eta 0:01:18 lr 0.003176	time 0.4572 (0.4853)	model_time 0.4568 (0.4700)	loss 3.6019 (3.4558)	grad_norm 2.5114 (1.5666/0.7262)	mem 16099MB
[2025-01-18 02:07:18 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][160/312]	eta 0:01:13 lr 0.003175	time 0.5449 (0.4838)	model_time 0.5444 (0.4695)	loss 2.3674 (3.4474)	grad_norm 1.0487 (1.5554/0.7148)	mem 16099MB
[2025-01-18 02:07:23 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][170/312]	eta 0:01:08 lr 0.003175	time 0.4857 (0.4834)	model_time 0.4852 (0.4698)	loss 3.4647 (3.4422)	grad_norm 2.3607 (1.5291/0.7095)	mem 16099MB
[2025-01-18 02:07:27 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][180/312]	eta 0:01:03 lr 0.003174	time 0.4504 (0.4818)	model_time 0.4499 (0.4690)	loss 4.2680 (3.4560)	grad_norm 0.9256 (1.5158/0.7087)	mem 16099MB
[2025-01-18 02:07:32 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][190/312]	eta 0:00:58 lr 0.003174	time 0.4539 (0.4803)	model_time 0.4537 (0.4682)	loss 3.3186 (3.4628)	grad_norm 3.3952 (1.5077/0.7095)	mem 16099MB
[2025-01-18 02:07:36 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][200/312]	eta 0:00:53 lr 0.003173	time 0.4490 (0.4797)	model_time 0.4485 (0.4681)	loss 3.2104 (3.4680)	grad_norm 1.3530 (1.5212/0.7069)	mem 16099MB
[2025-01-18 02:07:41 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][210/312]	eta 0:00:48 lr 0.003172	time 0.4528 (0.4797)	model_time 0.4524 (0.4686)	loss 3.7908 (3.4574)	grad_norm 1.4428 (1.5312/0.7063)	mem 16099MB
[2025-01-18 02:07:46 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][220/312]	eta 0:00:44 lr 0.003172	time 0.4406 (0.4788)	model_time 0.4404 (0.4682)	loss 3.6316 (3.4515)	grad_norm 1.0723 (1.5299/0.7002)	mem 16099MB
[2025-01-18 02:07:50 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][230/312]	eta 0:00:39 lr 0.003171	time 0.4488 (0.4784)	model_time 0.4486 (0.4683)	loss 3.7904 (3.4550)	grad_norm 1.8327 (1.5402/0.7291)	mem 16099MB
[2025-01-18 02:07:55 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][240/312]	eta 0:00:34 lr 0.003171	time 0.4667 (0.4785)	model_time 0.4665 (0.4688)	loss 3.9249 (3.4515)	grad_norm 1.0617 (1.5529/0.7340)	mem 16099MB
[2025-01-18 02:08:00 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][250/312]	eta 0:00:29 lr 0.003170	time 0.4756 (0.4782)	model_time 0.4751 (0.4689)	loss 2.6763 (3.4519)	grad_norm 3.0232 (1.5629/0.7355)	mem 16099MB
[2025-01-18 02:08:05 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][260/312]	eta 0:00:24 lr 0.003170	time 0.4546 (0.4783)	model_time 0.4544 (0.4693)	loss 3.1630 (3.4464)	grad_norm 1.7011 (1.5555/0.7300)	mem 16099MB
[2025-01-18 02:08:10 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][270/312]	eta 0:00:20 lr 0.003169	time 0.4985 (0.4781)	model_time 0.4984 (0.4694)	loss 3.3280 (3.4356)	grad_norm 1.2825 (1.5420/0.7230)	mem 16099MB
[2025-01-18 02:08:14 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][280/312]	eta 0:00:15 lr 0.003169	time 0.4517 (0.4775)	model_time 0.4513 (0.4691)	loss 2.3940 (3.4410)	grad_norm 1.4344 (1.5511/0.7285)	mem 16099MB
[2025-01-18 02:08:19 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][290/312]	eta 0:00:10 lr 0.003168	time 0.4460 (0.4776)	model_time 0.4458 (0.4695)	loss 3.9729 (3.4443)	grad_norm 1.9823 (1.5461/0.7227)	mem 16099MB
[2025-01-18 02:08:24 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][300/312]	eta 0:00:05 lr 0.003168	time 0.4845 (0.4776)	model_time 0.4844 (0.4697)	loss 3.0432 (3.4423)	grad_norm 1.3136 (1.5468/0.7191)	mem 16099MB
[2025-01-18 02:08:28 internimage_t_1k_224] (main.py 510): INFO Train: [90/300][310/312]	eta 0:00:00 lr 0.003167	time 0.4357 (0.4766)	model_time 0.4356 (0.4690)	loss 3.1234 (3.4400)	grad_norm 0.8022 (1.5486/0.7181)	mem 16099MB
[2025-01-18 02:08:29 internimage_t_1k_224] (main.py 519): INFO EPOCH 90 training takes 0:02:28
[2025-01-18 02:08:29 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_90.pth saving......
[2025-01-18 02:08:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_90.pth saved !!!
[2025-01-18 02:08:37 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.285 (7.285)	Loss 0.9658 (0.9658)	Acc@1 80.200 (80.200)	Acc@5 95.752 (95.752)	Mem 16099MB
[2025-01-18 02:08:41 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.987)	Loss 1.3212 (1.1178)	Acc@1 71.631 (76.551)	Acc@5 91.431 (93.786)	Mem 16099MB
[2025-01-18 02:08:41 internimage_t_1k_224] (main.py 575): INFO [Epoch:90] * Acc@1 76.518 Acc@5 93.830
[2025-01-18 02:08:41 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.5%
[2025-01-18 02:08:41 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 02:08:42 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 02:08:42 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.52%
[2025-01-18 02:08:49 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.217 (7.217)	Loss 1.0273 (1.0273)	Acc@1 77.954 (77.954)	Acc@5 95.117 (95.117)	Mem 16099MB
[2025-01-18 02:08:53 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.994)	Loss 1.4864 (1.2169)	Acc@1 67.993 (74.381)	Acc@5 89.209 (92.321)	Mem 16099MB
[2025-01-18 02:08:53 internimage_t_1k_224] (main.py 575): INFO [Epoch:90] * Acc@1 74.336 Acc@5 92.358
[2025-01-18 02:08:53 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 74.3%
[2025-01-18 02:08:53 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:08:54 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:08:54 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 74.34%
[2025-01-18 02:08:57 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][0/312]	eta 0:11:56 lr 0.003167	time 2.2974 (2.2974)	model_time 0.5123 (0.5123)	loss 3.1997 (3.1997)	grad_norm 0.6249 (0.6249/0.0000)	mem 16099MB
[2025-01-18 02:09:01 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][10/312]	eta 0:03:11 lr 0.003166	time 0.4493 (0.6328)	model_time 0.4491 (0.4702)	loss 4.3914 (3.4505)	grad_norm 1.0928 (1.6842/0.5460)	mem 16099MB
[2025-01-18 02:09:06 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][20/312]	eta 0:02:40 lr 0.003166	time 0.4404 (0.5490)	model_time 0.4402 (0.4637)	loss 3.8462 (3.4219)	grad_norm 1.4090 (2.0308/0.9887)	mem 16099MB
[2025-01-18 02:09:11 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][30/312]	eta 0:02:26 lr 0.003165	time 0.4495 (0.5199)	model_time 0.4494 (0.4619)	loss 3.4811 (3.3989)	grad_norm 0.9799 (1.7356/0.9321)	mem 16099MB
[2025-01-18 02:09:15 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][40/312]	eta 0:02:18 lr 0.003165	time 0.4747 (0.5089)	model_time 0.4746 (0.4650)	loss 2.8613 (3.3884)	grad_norm 1.2759 (1.6044/0.8664)	mem 16099MB
[2025-01-18 02:09:20 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][50/312]	eta 0:02:10 lr 0.003164	time 0.4501 (0.4992)	model_time 0.4499 (0.4639)	loss 3.7157 (3.3528)	grad_norm 2.0802 (1.7330/0.9824)	mem 16099MB
[2025-01-18 02:09:25 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][60/312]	eta 0:02:04 lr 0.003164	time 0.4498 (0.4934)	model_time 0.4496 (0.4638)	loss 2.9590 (3.3574)	grad_norm 0.7613 (1.6606/0.9247)	mem 16099MB
[2025-01-18 02:09:29 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][70/312]	eta 0:01:58 lr 0.003163	time 0.4514 (0.4884)	model_time 0.4512 (0.4629)	loss 3.7772 (3.3803)	grad_norm 0.7842 (1.5792/0.8855)	mem 16099MB
[2025-01-18 02:09:34 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][80/312]	eta 0:01:52 lr 0.003163	time 0.4637 (0.4852)	model_time 0.4632 (0.4628)	loss 3.3709 (3.3826)	grad_norm 1.4319 (1.5918/0.8541)	mem 16099MB
[2025-01-18 02:09:39 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][90/312]	eta 0:01:47 lr 0.003162	time 0.5352 (0.4850)	model_time 0.5350 (0.4650)	loss 3.6807 (3.3803)	grad_norm 1.9009 (1.5943/0.8157)	mem 16099MB
[2025-01-18 02:09:43 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][100/312]	eta 0:01:42 lr 0.003162	time 0.4478 (0.4818)	model_time 0.4476 (0.4638)	loss 3.0652 (3.4022)	grad_norm 0.8850 (1.5551/0.7897)	mem 16099MB
[2025-01-18 02:09:48 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][110/312]	eta 0:01:37 lr 0.003161	time 0.4731 (0.4807)	model_time 0.4726 (0.4643)	loss 4.0944 (3.4162)	grad_norm 1.2795 (1.5111/0.7680)	mem 16099MB
[2025-01-18 02:09:52 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][120/312]	eta 0:01:31 lr 0.003160	time 0.4497 (0.4785)	model_time 0.4492 (0.4634)	loss 3.7068 (3.4357)	grad_norm 0.9840 (1.5272/0.7802)	mem 16099MB
[2025-01-18 02:09:57 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][130/312]	eta 0:01:26 lr 0.003160	time 0.4537 (0.4766)	model_time 0.4536 (0.4626)	loss 3.4505 (3.4219)	grad_norm 0.8305 (1.5644/0.8103)	mem 16099MB
[2025-01-18 02:10:02 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][140/312]	eta 0:01:21 lr 0.003159	time 0.4414 (0.4760)	model_time 0.4412 (0.4630)	loss 3.7264 (3.4220)	grad_norm 1.3515 (1.5705/0.7940)	mem 16099MB
[2025-01-18 02:10:06 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][150/312]	eta 0:01:17 lr 0.003159	time 0.4507 (0.4763)	model_time 0.4505 (0.4641)	loss 4.2170 (3.4325)	grad_norm 1.2319 (1.5448/0.7784)	mem 16099MB
[2025-01-18 02:10:11 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][160/312]	eta 0:01:12 lr 0.003158	time 0.5261 (0.4771)	model_time 0.5257 (0.4656)	loss 4.1157 (3.4322)	grad_norm 1.0302 (1.5464/0.7713)	mem 16099MB
[2025-01-18 02:10:16 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][170/312]	eta 0:01:07 lr 0.003158	time 0.4525 (0.4766)	model_time 0.4523 (0.4658)	loss 3.6592 (3.4449)	grad_norm 3.7535 (1.5730/0.7933)	mem 16099MB
[2025-01-18 02:10:20 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][180/312]	eta 0:01:02 lr 0.003157	time 0.4487 (0.4755)	model_time 0.4486 (0.4653)	loss 3.9384 (3.4334)	grad_norm 0.7423 (1.5892/0.7910)	mem 16099MB
[2025-01-18 02:10:25 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][190/312]	eta 0:00:57 lr 0.003157	time 0.4530 (0.4744)	model_time 0.4525 (0.4647)	loss 3.7749 (3.4438)	grad_norm 1.4096 (1.5795/0.7765)	mem 16099MB
[2025-01-18 02:10:30 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][200/312]	eta 0:00:53 lr 0.003156	time 0.4862 (0.4737)	model_time 0.4861 (0.4645)	loss 3.7054 (3.4436)	grad_norm 1.0838 (1.5547/0.7655)	mem 16099MB
[2025-01-18 02:10:35 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][210/312]	eta 0:00:48 lr 0.003156	time 0.4936 (0.4745)	model_time 0.4934 (0.4657)	loss 4.1153 (3.4489)	grad_norm 1.8274 (1.5330/0.7566)	mem 16099MB
[2025-01-18 02:10:39 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][220/312]	eta 0:00:43 lr 0.003155	time 0.4495 (0.4737)	model_time 0.4493 (0.4652)	loss 4.2432 (3.4598)	grad_norm 2.3195 (1.5374/0.7469)	mem 16099MB
[2025-01-18 02:10:44 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][230/312]	eta 0:00:38 lr 0.003154	time 0.4531 (0.4740)	model_time 0.4526 (0.4659)	loss 4.5049 (3.4785)	grad_norm 1.6496 (1.5330/0.7341)	mem 16099MB
[2025-01-18 02:10:49 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][240/312]	eta 0:00:34 lr 0.003154	time 0.4446 (0.4738)	model_time 0.4445 (0.4660)	loss 4.0251 (3.4746)	grad_norm 0.8797 (1.5247/0.7282)	mem 16099MB
[2025-01-18 02:10:53 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][250/312]	eta 0:00:29 lr 0.003153	time 0.4394 (0.4735)	model_time 0.4393 (0.4660)	loss 2.2553 (3.4731)	grad_norm 2.2974 (1.5322/0.7254)	mem 16099MB
[2025-01-18 02:10:58 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][260/312]	eta 0:00:24 lr 0.003153	time 0.4467 (0.4734)	model_time 0.4465 (0.4662)	loss 2.8135 (3.4739)	grad_norm 1.5695 (1.5431/0.7270)	mem 16099MB
[2025-01-18 02:11:03 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][270/312]	eta 0:00:19 lr 0.003152	time 0.4801 (0.4732)	model_time 0.4799 (0.4662)	loss 3.3214 (3.4809)	grad_norm 1.5812 (1.5395/0.7188)	mem 16099MB
[2025-01-18 02:11:07 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][280/312]	eta 0:00:15 lr 0.003152	time 0.4613 (0.4731)	model_time 0.4611 (0.4664)	loss 2.8705 (3.4746)	grad_norm 1.7816 (1.5501/0.7183)	mem 16099MB
[2025-01-18 02:11:12 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][290/312]	eta 0:00:10 lr 0.003151	time 0.4515 (0.4730)	model_time 0.4510 (0.4665)	loss 3.7334 (3.4772)	grad_norm 3.2803 (1.5773/0.7415)	mem 16099MB
[2025-01-18 02:11:17 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][300/312]	eta 0:00:05 lr 0.003151	time 0.4383 (0.4730)	model_time 0.4382 (0.4667)	loss 3.8969 (3.4804)	grad_norm 1.6203 (1.5817/0.7380)	mem 16099MB
[2025-01-18 02:11:21 internimage_t_1k_224] (main.py 510): INFO Train: [91/300][310/312]	eta 0:00:00 lr 0.003150	time 0.4366 (0.4721)	model_time 0.4366 (0.4660)	loss 4.2169 (3.4845)	grad_norm 0.8762 (1.5699/0.7450)	mem 16099MB
[2025-01-18 02:11:22 internimage_t_1k_224] (main.py 519): INFO EPOCH 91 training takes 0:02:27
[2025-01-18 02:11:22 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_91.pth saving......
[2025-01-18 02:11:23 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_91.pth saved !!!
[2025-01-18 02:11:31 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.413 (8.413)	Loss 0.9254 (0.9254)	Acc@1 79.565 (79.565)	Acc@5 95.142 (95.142)	Mem 16099MB
[2025-01-18 02:11:35 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.112)	Loss 1.3047 (1.1031)	Acc@1 71.045 (76.392)	Acc@5 91.602 (93.617)	Mem 16099MB
[2025-01-18 02:11:35 internimage_t_1k_224] (main.py 575): INFO [Epoch:91] * Acc@1 76.402 Acc@5 93.674
[2025-01-18 02:11:35 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.4%
[2025-01-18 02:11:35 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.52%
[2025-01-18 02:11:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.888 (8.888)	Loss 1.0140 (1.0140)	Acc@1 78.052 (78.052)	Acc@5 95.117 (95.117)	Mem 16099MB
[2025-01-18 02:11:48 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.186)	Loss 1.4691 (1.2021)	Acc@1 68.335 (74.649)	Acc@5 89.331 (92.454)	Mem 16099MB
[2025-01-18 02:11:48 internimage_t_1k_224] (main.py 575): INFO [Epoch:91] * Acc@1 74.600 Acc@5 92.492
[2025-01-18 02:11:48 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 74.6%
[2025-01-18 02:11:48 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:11:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:11:50 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 74.60%
[2025-01-18 02:11:53 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][0/312]	eta 0:14:54 lr 0.003150	time 2.8660 (2.8660)	model_time 0.4611 (0.4611)	loss 4.4268 (4.4268)	grad_norm 1.1196 (1.1196/0.0000)	mem 16099MB
[2025-01-18 02:11:58 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][10/312]	eta 0:03:28 lr 0.003149	time 0.4516 (0.6916)	model_time 0.4515 (0.4727)	loss 3.6672 (3.3984)	grad_norm 1.8065 (1.6650/0.7182)	mem 16099MB
[2025-01-18 02:12:02 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][20/312]	eta 0:02:50 lr 0.003149	time 0.4518 (0.5849)	model_time 0.4517 (0.4700)	loss 2.5349 (3.4788)	grad_norm 1.2479 (1.6033/0.6286)	mem 16099MB
[2025-01-18 02:12:07 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][30/312]	eta 0:02:33 lr 0.003148	time 0.4426 (0.5444)	model_time 0.4424 (0.4665)	loss 4.3340 (3.5408)	grad_norm 1.4735 (1.5810/0.5839)	mem 16099MB
[2025-01-18 02:12:11 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][40/312]	eta 0:02:22 lr 0.003148	time 0.4444 (0.5222)	model_time 0.4442 (0.4633)	loss 4.0364 (3.4927)	grad_norm 0.8437 (1.4554/0.5691)	mem 16099MB
[2025-01-18 02:12:16 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][50/312]	eta 0:02:13 lr 0.003147	time 0.4618 (0.5094)	model_time 0.4616 (0.4619)	loss 3.1016 (3.4941)	grad_norm 1.9433 (1.4979/0.5870)	mem 16099MB
[2025-01-18 02:12:21 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][60/312]	eta 0:02:06 lr 0.003147	time 0.4535 (0.5015)	model_time 0.4533 (0.4617)	loss 2.9321 (3.4369)	grad_norm 1.2778 (1.6005/0.6148)	mem 16099MB
[2025-01-18 02:12:25 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][70/312]	eta 0:01:59 lr 0.003146	time 0.4451 (0.4954)	model_time 0.4446 (0.4612)	loss 3.0549 (3.4016)	grad_norm 1.6352 (1.6115/0.6612)	mem 16099MB
[2025-01-18 02:12:30 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][80/312]	eta 0:01:54 lr 0.003146	time 0.4514 (0.4921)	model_time 0.4510 (0.4620)	loss 2.9255 (3.4032)	grad_norm 0.7534 (1.6152/0.6642)	mem 16099MB
[2025-01-18 02:12:35 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][90/312]	eta 0:01:48 lr 0.003145	time 0.4552 (0.4882)	model_time 0.4550 (0.4614)	loss 2.5176 (3.4187)	grad_norm 1.3624 (1.6002/0.6430)	mem 16099MB
[2025-01-18 02:12:39 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][100/312]	eta 0:01:42 lr 0.003145	time 0.4509 (0.4849)	model_time 0.4508 (0.4608)	loss 3.6593 (3.4288)	grad_norm 2.3022 (1.5821/0.6278)	mem 16099MB
[2025-01-18 02:12:44 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][110/312]	eta 0:01:37 lr 0.003144	time 0.4466 (0.4827)	model_time 0.4461 (0.4607)	loss 4.0094 (3.4267)	grad_norm 1.0856 (1.5788/0.6128)	mem 16099MB
[2025-01-18 02:12:48 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][120/312]	eta 0:01:32 lr 0.003143	time 0.4519 (0.4814)	model_time 0.4517 (0.4612)	loss 3.1753 (3.4254)	grad_norm 2.6099 (1.5846/0.6079)	mem 16099MB
[2025-01-18 02:12:53 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][130/312]	eta 0:01:27 lr 0.003143	time 0.5312 (0.4820)	model_time 0.5310 (0.4633)	loss 3.6723 (3.4242)	grad_norm 3.3517 (1.6016/0.6220)	mem 16099MB
[2025-01-18 02:12:58 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][140/312]	eta 0:01:23 lr 0.003142	time 0.4593 (0.4842)	model_time 0.4589 (0.4668)	loss 3.2294 (3.4167)	grad_norm 1.6033 (1.6200/0.6296)	mem 16099MB
[2025-01-18 02:13:03 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][150/312]	eta 0:01:18 lr 0.003142	time 0.5449 (0.4838)	model_time 0.5445 (0.4675)	loss 3.6412 (3.4350)	grad_norm 1.4928 (1.6015/0.6149)	mem 16099MB
[2025-01-18 02:13:08 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][160/312]	eta 0:01:13 lr 0.003141	time 0.5321 (0.4840)	model_time 0.5320 (0.4687)	loss 3.9009 (3.4554)	grad_norm 1.1524 (1.5769/0.6083)	mem 16099MB
[2025-01-18 02:13:13 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][170/312]	eta 0:01:08 lr 0.003141	time 0.4570 (0.4825)	model_time 0.4569 (0.4681)	loss 3.0793 (3.4680)	grad_norm 1.4598 (1.5807/0.6018)	mem 16099MB
[2025-01-18 02:13:17 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][180/312]	eta 0:01:03 lr 0.003140	time 0.4392 (0.4822)	model_time 0.4385 (0.4685)	loss 2.1424 (3.4566)	grad_norm 0.8952 (1.5576/0.6010)	mem 16099MB
[2025-01-18 02:13:22 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][190/312]	eta 0:00:58 lr 0.003140	time 0.5484 (0.4815)	model_time 0.5479 (0.4685)	loss 2.5190 (3.4425)	grad_norm 0.7876 (1.5510/0.6005)	mem 16099MB
[2025-01-18 02:13:27 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][200/312]	eta 0:00:53 lr 0.003139	time 0.4730 (0.4807)	model_time 0.4728 (0.4684)	loss 3.4552 (3.4386)	grad_norm 2.5144 (1.5502/0.5927)	mem 16099MB
[2025-01-18 02:13:31 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][210/312]	eta 0:00:48 lr 0.003139	time 0.4633 (0.4796)	model_time 0.4631 (0.4679)	loss 3.6706 (3.4350)	grad_norm 2.3523 (1.5783/0.6591)	mem 16099MB
[2025-01-18 02:13:36 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][220/312]	eta 0:00:44 lr 0.003138	time 0.4535 (0.4786)	model_time 0.4533 (0.4674)	loss 3.0253 (3.4226)	grad_norm 1.6974 (1.5953/0.6706)	mem 16099MB
[2025-01-18 02:13:41 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][230/312]	eta 0:00:39 lr 0.003137	time 0.4624 (0.4787)	model_time 0.4620 (0.4679)	loss 3.9195 (3.4267)	grad_norm 1.1101 (1.5834/0.6620)	mem 16099MB
[2025-01-18 02:13:45 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][240/312]	eta 0:00:34 lr 0.003137	time 0.4565 (0.4777)	model_time 0.4560 (0.4674)	loss 3.0274 (3.4230)	grad_norm 1.8825 (1.5681/0.6556)	mem 16099MB
[2025-01-18 02:13:50 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][250/312]	eta 0:00:29 lr 0.003136	time 0.4769 (0.4769)	model_time 0.4767 (0.4670)	loss 3.8746 (3.4197)	grad_norm 1.0465 (1.5509/0.6525)	mem 16099MB
[2025-01-18 02:13:54 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][260/312]	eta 0:00:24 lr 0.003136	time 0.4468 (0.4760)	model_time 0.4466 (0.4665)	loss 4.0133 (3.4286)	grad_norm 1.1159 (1.5421/0.6450)	mem 16099MB
[2025-01-18 02:13:59 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][270/312]	eta 0:00:19 lr 0.003135	time 0.4514 (0.4756)	model_time 0.4510 (0.4664)	loss 2.7358 (3.4261)	grad_norm 0.8511 (1.5469/0.6515)	mem 16099MB
[2025-01-18 02:14:04 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][280/312]	eta 0:00:15 lr 0.003135	time 0.4683 (0.4749)	model_time 0.4681 (0.4660)	loss 4.3000 (3.4352)	grad_norm 2.3781 (1.5428/0.6452)	mem 16099MB
[2025-01-18 02:14:08 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][290/312]	eta 0:00:10 lr 0.003134	time 0.4475 (0.4746)	model_time 0.4470 (0.4660)	loss 4.1008 (3.4332)	grad_norm 1.4722 (1.5323/0.6384)	mem 16099MB
[2025-01-18 02:14:13 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][300/312]	eta 0:00:05 lr 0.003134	time 0.4390 (0.4743)	model_time 0.4389 (0.4659)	loss 3.8813 (3.4332)	grad_norm 1.3966 (1.5392/0.6390)	mem 16099MB
[2025-01-18 02:14:18 internimage_t_1k_224] (main.py 510): INFO Train: [92/300][310/312]	eta 0:00:00 lr 0.003133	time 0.4388 (0.4744)	model_time 0.4387 (0.4663)	loss 3.7289 (3.4283)	grad_norm 1.2369 (1.5253/0.6307)	mem 16099MB
[2025-01-18 02:14:18 internimage_t_1k_224] (main.py 519): INFO EPOCH 92 training takes 0:02:28
[2025-01-18 02:14:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_92.pth saving......
[2025-01-18 02:14:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_92.pth saved !!!
[2025-01-18 02:14:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.368 (7.368)	Loss 0.9034 (0.9034)	Acc@1 80.054 (80.054)	Acc@5 95.581 (95.581)	Mem 16099MB
[2025-01-18 02:14:30 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.004)	Loss 1.2744 (1.0866)	Acc@1 71.973 (76.485)	Acc@5 91.626 (93.544)	Mem 16099MB
[2025-01-18 02:14:30 internimage_t_1k_224] (main.py 575): INFO [Epoch:92] * Acc@1 76.456 Acc@5 93.590
[2025-01-18 02:14:30 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.5%
[2025-01-18 02:14:30 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.52%
[2025-01-18 02:14:39 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.367 (8.367)	Loss 1.0021 (1.0021)	Acc@1 78.247 (78.247)	Acc@5 95.215 (95.215)	Mem 16099MB
[2025-01-18 02:14:43 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.108 (1.129)	Loss 1.4525 (1.1880)	Acc@1 68.579 (74.871)	Acc@5 89.380 (92.569)	Mem 16099MB
[2025-01-18 02:14:43 internimage_t_1k_224] (main.py 575): INFO [Epoch:92] * Acc@1 74.818 Acc@5 92.610
[2025-01-18 02:14:43 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 74.8%
[2025-01-18 02:14:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:14:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:14:45 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 74.82%
[2025-01-18 02:14:48 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][0/312]	eta 0:15:41 lr 0.003133	time 3.0186 (3.0186)	model_time 0.4732 (0.4732)	loss 3.8117 (3.8117)	grad_norm 2.2018 (2.2018/0.0000)	mem 16099MB
[2025-01-18 02:14:52 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][10/312]	eta 0:03:32 lr 0.003132	time 0.4661 (0.7021)	model_time 0.4657 (0.4703)	loss 3.6475 (3.4912)	grad_norm 1.3025 (1.7766/0.7018)	mem 16099MB
[2025-01-18 02:14:57 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][20/312]	eta 0:02:50 lr 0.003132	time 0.4513 (0.5829)	model_time 0.4511 (0.4613)	loss 3.0735 (3.4804)	grad_norm 1.9631 (1.7355/0.6463)	mem 16099MB
[2025-01-18 02:15:01 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][30/312]	eta 0:02:33 lr 0.003131	time 0.5455 (0.5448)	model_time 0.5453 (0.4624)	loss 3.5940 (3.4854)	grad_norm 1.3901 (1.6981/0.5649)	mem 16099MB
[2025-01-18 02:15:06 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][40/312]	eta 0:02:22 lr 0.003131	time 0.4571 (0.5237)	model_time 0.4570 (0.4612)	loss 2.5290 (3.4595)	grad_norm 1.0498 (1.6367/0.5307)	mem 16099MB
[2025-01-18 02:15:11 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][50/312]	eta 0:02:14 lr 0.003130	time 0.4481 (0.5139)	model_time 0.4480 (0.4636)	loss 2.8225 (3.5065)	grad_norm 1.8418 (1.6853/0.5335)	mem 16099MB
[2025-01-18 02:15:15 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][60/312]	eta 0:02:07 lr 0.003130	time 0.4514 (0.5050)	model_time 0.4512 (0.4629)	loss 3.3882 (3.4555)	grad_norm 0.9032 (1.6260/0.5220)	mem 16099MB
[2025-01-18 02:15:20 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][70/312]	eta 0:02:00 lr 0.003129	time 0.4409 (0.4998)	model_time 0.4407 (0.4636)	loss 3.9897 (3.4872)	grad_norm 1.2444 (1.5928/0.5244)	mem 16099MB
[2025-01-18 02:15:25 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][80/312]	eta 0:01:54 lr 0.003129	time 0.4448 (0.4954)	model_time 0.4443 (0.4636)	loss 3.2181 (3.4682)	grad_norm 1.1468 (1.5604/0.5153)	mem 16099MB
[2025-01-18 02:15:29 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][90/312]	eta 0:01:49 lr 0.003128	time 0.4627 (0.4917)	model_time 0.4623 (0.4633)	loss 2.2862 (3.4515)	grad_norm 3.6021 (1.6442/0.6725)	mem 16099MB
[2025-01-18 02:15:34 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][100/312]	eta 0:01:44 lr 0.003127	time 0.4539 (0.4908)	model_time 0.4536 (0.4652)	loss 2.5336 (3.4542)	grad_norm 1.2863 (1.6685/0.7032)	mem 16099MB
[2025-01-18 02:15:39 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][110/312]	eta 0:01:38 lr 0.003127	time 0.4490 (0.4900)	model_time 0.4489 (0.4667)	loss 3.2576 (3.4392)	grad_norm 0.7594 (1.6229/0.6938)	mem 16099MB
[2025-01-18 02:15:44 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][120/312]	eta 0:01:33 lr 0.003126	time 0.4639 (0.4892)	model_time 0.4637 (0.4678)	loss 3.4397 (3.4305)	grad_norm 1.0003 (1.5906/0.6800)	mem 16099MB
[2025-01-18 02:15:48 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][130/312]	eta 0:01:28 lr 0.003126	time 0.4644 (0.4882)	model_time 0.4640 (0.4684)	loss 3.9490 (3.4514)	grad_norm 1.0267 (1.5630/0.6650)	mem 16099MB
[2025-01-18 02:15:53 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][140/312]	eta 0:01:23 lr 0.003125	time 0.4602 (0.4870)	model_time 0.4601 (0.4686)	loss 3.7108 (3.4538)	grad_norm 1.0514 (1.5837/0.6670)	mem 16099MB
[2025-01-18 02:15:58 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][150/312]	eta 0:01:18 lr 0.003125	time 0.4571 (0.4859)	model_time 0.4569 (0.4687)	loss 3.6302 (3.4515)	grad_norm 1.0862 (1.5834/0.6612)	mem 16099MB
[2025-01-18 02:16:02 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][160/312]	eta 0:01:13 lr 0.003124	time 0.4573 (0.4843)	model_time 0.4572 (0.4681)	loss 3.2284 (3.4475)	grad_norm 1.6099 (1.5847/0.6538)	mem 16099MB
[2025-01-18 02:16:07 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][170/312]	eta 0:01:08 lr 0.003124	time 0.4600 (0.4836)	model_time 0.4596 (0.4684)	loss 4.3910 (3.4546)	grad_norm 1.6251 (1.6168/0.6828)	mem 16099MB
[2025-01-18 02:16:12 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][180/312]	eta 0:01:03 lr 0.003123	time 0.4410 (0.4823)	model_time 0.4406 (0.4679)	loss 3.4755 (3.4420)	grad_norm 0.9732 (1.6154/0.6875)	mem 16099MB
[2025-01-18 02:16:16 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][190/312]	eta 0:00:58 lr 0.003122	time 0.4566 (0.4808)	model_time 0.4564 (0.4671)	loss 3.6412 (3.4503)	grad_norm 0.7948 (1.5892/0.6823)	mem 16099MB
[2025-01-18 02:16:21 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][200/312]	eta 0:00:53 lr 0.003122	time 0.4437 (0.4796)	model_time 0.4436 (0.4666)	loss 3.6838 (3.4424)	grad_norm 0.9174 (1.5650/0.6783)	mem 16099MB
[2025-01-18 02:16:26 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][210/312]	eta 0:00:48 lr 0.003121	time 0.5470 (0.4794)	model_time 0.5465 (0.4670)	loss 3.7022 (3.4367)	grad_norm 1.8418 (1.5802/0.6763)	mem 16099MB
[2025-01-18 02:16:30 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][220/312]	eta 0:00:43 lr 0.003121	time 0.4534 (0.4782)	model_time 0.4532 (0.4663)	loss 3.5385 (3.4418)	grad_norm 2.0467 (1.5814/0.6738)	mem 16099MB
[2025-01-18 02:16:35 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][230/312]	eta 0:00:39 lr 0.003120	time 0.4519 (0.4776)	model_time 0.4517 (0.4662)	loss 3.9202 (3.4277)	grad_norm 1.0536 (1.5688/0.6638)	mem 16099MB
[2025-01-18 02:16:39 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][240/312]	eta 0:00:34 lr 0.003120	time 0.4878 (0.4768)	model_time 0.4874 (0.4659)	loss 3.7063 (3.4369)	grad_norm 0.9164 (1.5615/0.6547)	mem 16099MB
[2025-01-18 02:16:44 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][250/312]	eta 0:00:29 lr 0.003119	time 0.4496 (0.4764)	model_time 0.4494 (0.4659)	loss 3.2669 (3.4270)	grad_norm 0.7760 (1.5452/0.6532)	mem 16099MB
[2025-01-18 02:16:49 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][260/312]	eta 0:00:24 lr 0.003119	time 0.4547 (0.4756)	model_time 0.4546 (0.4654)	loss 4.3926 (3.4446)	grad_norm 3.9039 (1.5479/0.6683)	mem 16099MB
[2025-01-18 02:16:54 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][270/312]	eta 0:00:20 lr 0.003118	time 0.5450 (0.4763)	model_time 0.5445 (0.4665)	loss 3.7391 (3.4566)	grad_norm 0.7152 (1.5529/0.6724)	mem 16099MB
[2025-01-18 02:16:58 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][280/312]	eta 0:00:15 lr 0.003117	time 0.4580 (0.4762)	model_time 0.4575 (0.4668)	loss 4.2633 (3.4633)	grad_norm 2.6479 (1.5475/0.6688)	mem 16099MB
[2025-01-18 02:17:03 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][290/312]	eta 0:00:10 lr 0.003117	time 0.4418 (0.4761)	model_time 0.4417 (0.4669)	loss 3.1777 (3.4617)	grad_norm 1.8635 (1.5568/0.6722)	mem 16099MB
[2025-01-18 02:17:08 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][300/312]	eta 0:00:05 lr 0.003116	time 0.4374 (0.4760)	model_time 0.4373 (0.4672)	loss 3.1159 (3.4659)	grad_norm 1.7146 (1.5898/0.7075)	mem 16099MB
[2025-01-18 02:17:12 internimage_t_1k_224] (main.py 510): INFO Train: [93/300][310/312]	eta 0:00:00 lr 0.003116	time 0.5185 (0.4751)	model_time 0.5184 (0.4665)	loss 4.2652 (3.4656)	grad_norm 1.2770 (1.5821/0.7017)	mem 16099MB
[2025-01-18 02:17:13 internimage_t_1k_224] (main.py 519): INFO EPOCH 93 training takes 0:02:28
[2025-01-18 02:17:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_93.pth saving......
[2025-01-18 02:17:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_93.pth saved !!!
[2025-01-18 02:17:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.623 (7.623)	Loss 0.9925 (0.9925)	Acc@1 79.858 (79.858)	Acc@5 95.117 (95.117)	Mem 16099MB
[2025-01-18 02:17:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.033)	Loss 1.3208 (1.1135)	Acc@1 71.899 (76.649)	Acc@5 91.138 (93.661)	Mem 16099MB
[2025-01-18 02:17:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:93] * Acc@1 76.556 Acc@5 93.654
[2025-01-18 02:17:25 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.6%
[2025-01-18 02:17:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 02:17:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 02:17:26 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.56%
[2025-01-18 02:17:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.545 (7.545)	Loss 0.9910 (0.9910)	Acc@1 78.467 (78.467)	Acc@5 95.215 (95.215)	Mem 16099MB
[2025-01-18 02:17:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.022)	Loss 1.4371 (1.1745)	Acc@1 68.652 (75.102)	Acc@5 89.551 (92.667)	Mem 16099MB
[2025-01-18 02:17:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:93] * Acc@1 75.044 Acc@5 92.716
[2025-01-18 02:17:38 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 75.0%
[2025-01-18 02:17:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:17:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:17:39 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 75.04%
[2025-01-18 02:17:42 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][0/312]	eta 0:13:25 lr 0.003116	time 2.5819 (2.5819)	model_time 0.4630 (0.4630)	loss 3.9101 (3.9101)	grad_norm 1.4279 (1.4279/0.0000)	mem 16099MB
[2025-01-18 02:17:47 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][10/312]	eta 0:03:21 lr 0.003115	time 0.5334 (0.6661)	model_time 0.5333 (0.4731)	loss 4.1863 (3.7230)	grad_norm 1.9172 (1.1462/0.2903)	mem 16099MB
[2025-01-18 02:17:51 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][20/312]	eta 0:02:45 lr 0.003115	time 0.4558 (0.5657)	model_time 0.4556 (0.4645)	loss 2.6848 (3.6769)	grad_norm 2.0734 (1.3880/0.4835)	mem 16099MB
[2025-01-18 02:17:56 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][30/312]	eta 0:02:31 lr 0.003114	time 0.4480 (0.5385)	model_time 0.4479 (0.4698)	loss 3.6826 (3.5737)	grad_norm 1.7195 (1.4110/0.5488)	mem 16099MB
[2025-01-18 02:18:01 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][40/312]	eta 0:02:22 lr 0.003114	time 0.4570 (0.5240)	model_time 0.4566 (0.4719)	loss 3.4851 (3.5320)	grad_norm 2.2618 (1.5031/0.6356)	mem 16099MB
[2025-01-18 02:18:06 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][50/312]	eta 0:02:14 lr 0.003113	time 0.4714 (0.5133)	model_time 0.4712 (0.4714)	loss 3.0151 (3.5241)	grad_norm 1.9915 (1.5408/0.6501)	mem 16099MB
[2025-01-18 02:18:10 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][60/312]	eta 0:02:06 lr 0.003112	time 0.4460 (0.5035)	model_time 0.4456 (0.4683)	loss 4.2615 (3.4839)	grad_norm 1.4171 (1.6218/0.7030)	mem 16099MB
[2025-01-18 02:18:15 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][70/312]	eta 0:02:00 lr 0.003112	time 0.4534 (0.4981)	model_time 0.4532 (0.4679)	loss 2.5869 (3.5044)	grad_norm 1.6578 (1.6174/0.6951)	mem 16099MB
[2025-01-18 02:18:19 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][80/312]	eta 0:01:54 lr 0.003111	time 0.4669 (0.4945)	model_time 0.4664 (0.4679)	loss 3.4121 (3.4753)	grad_norm 1.6233 (1.5656/0.6723)	mem 16099MB
[2025-01-18 02:18:24 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][90/312]	eta 0:01:49 lr 0.003111	time 0.5340 (0.4924)	model_time 0.5339 (0.4687)	loss 2.9945 (3.4759)	grad_norm 1.1886 (1.5997/0.6843)	mem 16099MB
[2025-01-18 02:18:29 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][100/312]	eta 0:01:43 lr 0.003110	time 0.4665 (0.4893)	model_time 0.4661 (0.4680)	loss 4.2389 (3.4774)	grad_norm 1.8467 (1.6167/0.6761)	mem 16099MB
[2025-01-18 02:18:33 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][110/312]	eta 0:01:38 lr 0.003110	time 0.5336 (0.4868)	model_time 0.5332 (0.4673)	loss 3.6375 (3.4770)	grad_norm 0.8618 (1.5826/0.6784)	mem 16099MB
[2025-01-18 02:18:38 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][120/312]	eta 0:01:33 lr 0.003109	time 0.4406 (0.4850)	model_time 0.4404 (0.4671)	loss 3.2410 (3.4451)	grad_norm 0.7700 (1.5429/0.6687)	mem 16099MB
[2025-01-18 02:18:43 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][130/312]	eta 0:01:28 lr 0.003109	time 0.4533 (0.4836)	model_time 0.4529 (0.4670)	loss 3.9764 (3.4448)	grad_norm 1.5900 (1.5481/0.6626)	mem 16099MB
[2025-01-18 02:18:48 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][140/312]	eta 0:01:23 lr 0.003108	time 0.4608 (0.4838)	model_time 0.4606 (0.4684)	loss 3.8415 (3.4497)	grad_norm 1.2824 (1.5909/0.6823)	mem 16099MB
[2025-01-18 02:18:52 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][150/312]	eta 0:01:18 lr 0.003107	time 0.4586 (0.4820)	model_time 0.4584 (0.4676)	loss 4.2231 (3.4629)	grad_norm 1.9455 (1.5971/0.6777)	mem 16099MB
[2025-01-18 02:18:57 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][160/312]	eta 0:01:13 lr 0.003107	time 0.5334 (0.4824)	model_time 0.5332 (0.4689)	loss 3.2488 (3.4546)	grad_norm 1.5932 (1.6002/0.6745)	mem 16099MB
[2025-01-18 02:19:02 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][170/312]	eta 0:01:08 lr 0.003106	time 0.4535 (0.4814)	model_time 0.4531 (0.4686)	loss 3.3021 (3.4773)	grad_norm 1.9660 (1.5739/0.6678)	mem 16099MB
[2025-01-18 02:19:06 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][180/312]	eta 0:01:03 lr 0.003106	time 0.4515 (0.4802)	model_time 0.4511 (0.4681)	loss 4.0019 (3.4825)	grad_norm 1.4589 (1.5777/0.6758)	mem 16099MB
[2025-01-18 02:19:11 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][190/312]	eta 0:00:58 lr 0.003105	time 0.4450 (0.4799)	model_time 0.4448 (0.4684)	loss 2.7952 (3.4726)	grad_norm 2.2987 (1.5996/0.7224)	mem 16099MB
[2025-01-18 02:19:16 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][200/312]	eta 0:00:53 lr 0.003105	time 0.4499 (0.4789)	model_time 0.4497 (0.4680)	loss 3.8131 (3.4672)	grad_norm 0.9738 (1.6045/0.7196)	mem 16099MB
[2025-01-18 02:19:20 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][210/312]	eta 0:00:48 lr 0.003104	time 0.4653 (0.4789)	model_time 0.4648 (0.4684)	loss 4.0612 (3.4646)	grad_norm 2.7034 (1.6175/0.7233)	mem 16099MB
[2025-01-18 02:19:25 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][220/312]	eta 0:00:44 lr 0.003104	time 0.5609 (0.4787)	model_time 0.5607 (0.4687)	loss 2.9623 (3.4595)	grad_norm 0.7983 (1.6101/0.7176)	mem 16099MB
[2025-01-18 02:19:30 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][230/312]	eta 0:00:39 lr 0.003103	time 0.4447 (0.4780)	model_time 0.4443 (0.4685)	loss 3.4018 (3.4629)	grad_norm 1.4739 (1.5996/0.7075)	mem 16099MB
[2025-01-18 02:19:34 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][240/312]	eta 0:00:34 lr 0.003102	time 0.4538 (0.4773)	model_time 0.4534 (0.4682)	loss 3.3652 (3.4601)	grad_norm 0.9333 (1.5870/0.6985)	mem 16099MB
[2025-01-18 02:19:39 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][250/312]	eta 0:00:29 lr 0.003102	time 0.4449 (0.4766)	model_time 0.4444 (0.4677)	loss 3.6675 (3.4693)	grad_norm 1.0330 (1.5687/0.6906)	mem 16099MB
[2025-01-18 02:19:44 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][260/312]	eta 0:00:24 lr 0.003101	time 0.4530 (0.4764)	model_time 0.4526 (0.4679)	loss 4.1981 (3.4665)	grad_norm 3.3448 (1.5912/0.7210)	mem 16099MB
[2025-01-18 02:19:49 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][270/312]	eta 0:00:20 lr 0.003101	time 0.4526 (0.4771)	model_time 0.4520 (0.4688)	loss 3.5707 (3.4574)	grad_norm 1.9086 (1.6124/0.7460)	mem 16099MB
[2025-01-18 02:19:53 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][280/312]	eta 0:00:15 lr 0.003100	time 0.4705 (0.4763)	model_time 0.4703 (0.4683)	loss 3.0777 (3.4533)	grad_norm 0.8774 (1.6253/0.7579)	mem 16099MB
[2025-01-18 02:19:58 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][290/312]	eta 0:00:10 lr 0.003100	time 0.4507 (0.4757)	model_time 0.4502 (0.4680)	loss 3.0866 (3.4446)	grad_norm 1.0337 (1.6247/0.7614)	mem 16099MB
[2025-01-18 02:20:02 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][300/312]	eta 0:00:05 lr 0.003099	time 0.4470 (0.4751)	model_time 0.4469 (0.4677)	loss 3.6729 (3.4376)	grad_norm 3.4698 (1.6266/0.7656)	mem 16099MB
[2025-01-18 02:20:07 internimage_t_1k_224] (main.py 510): INFO Train: [94/300][310/312]	eta 0:00:00 lr 0.003098	time 0.5129 (0.4742)	model_time 0.5128 (0.4670)	loss 3.7172 (3.4505)	grad_norm 1.4430 (1.6316/0.7626)	mem 16099MB
[2025-01-18 02:20:07 internimage_t_1k_224] (main.py 519): INFO EPOCH 94 training takes 0:02:27
[2025-01-18 02:20:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_94.pth saving......
[2025-01-18 02:20:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_94.pth saved !!!
[2025-01-18 02:20:16 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.563 (7.563)	Loss 0.8911 (0.8911)	Acc@1 79.272 (79.272)	Acc@5 95.605 (95.605)	Mem 16099MB
[2025-01-18 02:20:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.003)	Loss 1.2410 (1.0513)	Acc@1 72.437 (76.853)	Acc@5 92.090 (93.803)	Mem 16099MB
[2025-01-18 02:20:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:94] * Acc@1 76.761 Acc@5 93.840
[2025-01-18 02:20:20 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.8%
[2025-01-18 02:20:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 02:20:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 02:20:21 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.76%
[2025-01-18 02:20:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.649 (7.649)	Loss 0.9796 (0.9796)	Acc@1 78.687 (78.687)	Acc@5 95.312 (95.312)	Mem 16099MB
[2025-01-18 02:20:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.009)	Loss 1.4222 (1.1618)	Acc@1 68.970 (75.364)	Acc@5 89.673 (92.769)	Mem 16099MB
[2025-01-18 02:20:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:94] * Acc@1 75.304 Acc@5 92.816
[2025-01-18 02:20:32 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 75.3%
[2025-01-18 02:20:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:20:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:20:34 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 75.30%
[2025-01-18 02:20:36 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][0/312]	eta 0:14:23 lr 0.003098	time 2.7669 (2.7669)	model_time 0.4679 (0.4679)	loss 3.4389 (3.4389)	grad_norm 1.2204 (1.2204/0.0000)	mem 16099MB
[2025-01-18 02:20:41 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][10/312]	eta 0:03:20 lr 0.003098	time 0.4473 (0.6636)	model_time 0.4472 (0.4542)	loss 3.9283 (3.4426)	grad_norm 1.2860 (1.2179/0.2485)	mem 16099MB
[2025-01-18 02:20:46 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][20/312]	eta 0:02:46 lr 0.003097	time 0.4450 (0.5691)	model_time 0.4449 (0.4593)	loss 2.6883 (3.4019)	grad_norm 1.9379 (1.2628/0.3461)	mem 16099MB
[2025-01-18 02:20:50 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][30/312]	eta 0:02:31 lr 0.003097	time 0.4938 (0.5369)	model_time 0.4936 (0.4623)	loss 3.7005 (3.4416)	grad_norm 1.1802 (1.5362/0.7040)	mem 16099MB
[2025-01-18 02:20:55 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][40/312]	eta 0:02:20 lr 0.003096	time 0.4486 (0.5179)	model_time 0.4484 (0.4615)	loss 3.6045 (3.4894)	grad_norm 1.0873 (1.5832/0.7498)	mem 16099MB
[2025-01-18 02:21:00 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][50/312]	eta 0:02:13 lr 0.003096	time 0.4657 (0.5112)	model_time 0.4655 (0.4657)	loss 3.7783 (3.5144)	grad_norm 1.2966 (1.5900/0.6915)	mem 16099MB
[2025-01-18 02:21:04 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][60/312]	eta 0:02:07 lr 0.003095	time 0.4562 (0.5067)	model_time 0.4561 (0.4687)	loss 4.3956 (3.5263)	grad_norm 0.6382 (1.5585/0.6880)	mem 16099MB
[2025-01-18 02:21:09 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][70/312]	eta 0:02:01 lr 0.003094	time 0.4439 (0.5005)	model_time 0.4437 (0.4678)	loss 3.4047 (3.5062)	grad_norm 1.1392 (1.5521/0.6646)	mem 16099MB
[2025-01-18 02:21:14 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][80/312]	eta 0:01:55 lr 0.003094	time 0.5331 (0.4963)	model_time 0.5326 (0.4676)	loss 3.7685 (3.5032)	grad_norm 0.9440 (1.5381/0.6503)	mem 16099MB
[2025-01-18 02:21:18 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][90/312]	eta 0:01:49 lr 0.003093	time 0.4565 (0.4930)	model_time 0.4561 (0.4674)	loss 2.6667 (3.4853)	grad_norm 3.5399 (1.6009/0.8098)	mem 16099MB
[2025-01-18 02:21:23 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][100/312]	eta 0:01:44 lr 0.003093	time 0.4445 (0.4910)	model_time 0.4443 (0.4678)	loss 3.2889 (3.4713)	grad_norm 1.1191 (1.5505/0.7874)	mem 16099MB
[2025-01-18 02:21:28 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][110/312]	eta 0:01:38 lr 0.003092	time 0.4400 (0.4899)	model_time 0.4396 (0.4689)	loss 3.7168 (3.4665)	grad_norm 1.5515 (1.5956/0.8375)	mem 16099MB
[2025-01-18 02:21:33 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][120/312]	eta 0:01:33 lr 0.003092	time 0.4761 (0.4889)	model_time 0.4756 (0.4696)	loss 2.8967 (3.4576)	grad_norm 1.2726 (1.5846/0.8348)	mem 16099MB
[2025-01-18 02:21:37 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][130/312]	eta 0:01:28 lr 0.003091	time 0.4595 (0.4874)	model_time 0.4590 (0.4695)	loss 3.4310 (3.4603)	grad_norm 1.7681 (1.5714/0.8142)	mem 16099MB
[2025-01-18 02:21:42 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][140/312]	eta 0:01:23 lr 0.003091	time 0.4426 (0.4865)	model_time 0.4421 (0.4698)	loss 2.4777 (3.4344)	grad_norm 1.2949 (1.5425/0.7933)	mem 16099MB
[2025-01-18 02:21:47 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][150/312]	eta 0:01:18 lr 0.003090	time 0.4456 (0.4847)	model_time 0.4451 (0.4691)	loss 4.1083 (3.4420)	grad_norm 2.1539 (1.5329/0.7751)	mem 16099MB
[2025-01-18 02:21:51 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][160/312]	eta 0:01:13 lr 0.003089	time 0.4579 (0.4830)	model_time 0.4578 (0.4684)	loss 3.8028 (3.4506)	grad_norm 1.1519 (1.5436/0.7828)	mem 16099MB
[2025-01-18 02:21:56 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][170/312]	eta 0:01:08 lr 0.003089	time 0.4678 (0.4814)	model_time 0.4676 (0.4676)	loss 3.0351 (3.4582)	grad_norm 2.2119 (1.5554/0.7677)	mem 16099MB
[2025-01-18 02:22:01 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][180/312]	eta 0:01:03 lr 0.003088	time 0.4541 (0.4810)	model_time 0.4536 (0.4679)	loss 3.7726 (3.4493)	grad_norm 1.9449 (1.5546/0.7522)	mem 16099MB
[2025-01-18 02:22:05 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][190/312]	eta 0:00:58 lr 0.003088	time 0.4604 (0.4806)	model_time 0.4602 (0.4682)	loss 3.5168 (3.4513)	grad_norm 2.6062 (1.5475/0.7470)	mem 16099MB
[2025-01-18 02:22:10 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][200/312]	eta 0:00:53 lr 0.003087	time 0.4434 (0.4794)	model_time 0.4432 (0.4675)	loss 3.2650 (3.4538)	grad_norm 1.6431 (1.5559/0.7394)	mem 16099MB
[2025-01-18 02:22:15 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][210/312]	eta 0:00:48 lr 0.003087	time 0.4443 (0.4789)	model_time 0.4438 (0.4676)	loss 3.6471 (3.4546)	grad_norm 1.6560 (1.5571/0.7341)	mem 16099MB
[2025-01-18 02:22:19 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][220/312]	eta 0:00:44 lr 0.003086	time 0.4384 (0.4792)	model_time 0.4382 (0.4684)	loss 3.4165 (3.4537)	grad_norm 1.2747 (1.5672/0.7253)	mem 16099MB
[2025-01-18 02:22:24 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][230/312]	eta 0:00:39 lr 0.003086	time 0.4432 (0.4786)	model_time 0.4427 (0.4683)	loss 2.4694 (3.4496)	grad_norm 1.8992 (1.5810/0.7241)	mem 16099MB
[2025-01-18 02:22:29 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][240/312]	eta 0:00:34 lr 0.003085	time 0.4446 (0.4781)	model_time 0.4444 (0.4682)	loss 3.1653 (3.4554)	grad_norm 1.5631 (1.5801/0.7163)	mem 16099MB
[2025-01-18 02:22:33 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][250/312]	eta 0:00:29 lr 0.003084	time 0.4522 (0.4772)	model_time 0.4518 (0.4677)	loss 3.8397 (3.4438)	grad_norm 1.5052 (1.5999/0.7246)	mem 16099MB
[2025-01-18 02:22:38 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][260/312]	eta 0:00:24 lr 0.003084	time 0.5479 (0.4770)	model_time 0.5475 (0.4678)	loss 3.2610 (3.4383)	grad_norm 2.9849 (1.6140/0.7397)	mem 16099MB
[2025-01-18 02:22:43 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][270/312]	eta 0:00:20 lr 0.003083	time 0.4497 (0.4765)	model_time 0.4494 (0.4677)	loss 2.4661 (3.4402)	grad_norm 1.2920 (1.6090/0.7332)	mem 16099MB
[2025-01-18 02:22:48 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][280/312]	eta 0:00:15 lr 0.003083	time 0.4597 (0.4768)	model_time 0.4595 (0.4683)	loss 3.8530 (3.4320)	grad_norm 1.4172 (1.6105/0.7319)	mem 16099MB
[2025-01-18 02:22:52 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][290/312]	eta 0:00:10 lr 0.003082	time 0.4525 (0.4769)	model_time 0.4524 (0.4686)	loss 3.1485 (3.4305)	grad_norm 0.6851 (1.6033/0.7260)	mem 16099MB
[2025-01-18 02:22:57 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][300/312]	eta 0:00:05 lr 0.003082	time 0.4384 (0.4763)	model_time 0.4383 (0.4683)	loss 3.8305 (3.4314)	grad_norm 1.0848 (1.5988/0.7192)	mem 16099MB
[2025-01-18 02:23:01 internimage_t_1k_224] (main.py 510): INFO Train: [95/300][310/312]	eta 0:00:00 lr 0.003081	time 0.4384 (0.4752)	model_time 0.4383 (0.4674)	loss 4.1762 (3.4357)	grad_norm 4.1843 (1.6420/0.7575)	mem 16099MB
[2025-01-18 02:23:02 internimage_t_1k_224] (main.py 519): INFO EPOCH 95 training takes 0:02:28
[2025-01-18 02:23:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_95.pth saving......
[2025-01-18 02:23:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_95.pth saved !!!
[2025-01-18 02:23:11 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.557 (7.557)	Loss 0.9240 (0.9240)	Acc@1 80.713 (80.713)	Acc@5 95.850 (95.850)	Mem 16099MB
[2025-01-18 02:23:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.022)	Loss 1.2794 (1.0821)	Acc@1 72.461 (77.066)	Acc@5 91.479 (93.794)	Mem 16099MB
[2025-01-18 02:23:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:95] * Acc@1 76.973 Acc@5 93.830
[2025-01-18 02:23:14 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.0%
[2025-01-18 02:23:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 02:23:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 02:23:15 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.97%
[2025-01-18 02:23:23 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.513 (7.513)	Loss 0.9685 (0.9685)	Acc@1 78.833 (78.833)	Acc@5 95.386 (95.386)	Mem 16099MB
[2025-01-18 02:23:27 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.010)	Loss 1.4079 (1.1498)	Acc@1 69.019 (75.537)	Acc@5 89.771 (92.858)	Mem 16099MB
[2025-01-18 02:23:27 internimage_t_1k_224] (main.py 575): INFO [Epoch:95] * Acc@1 75.490 Acc@5 92.906
[2025-01-18 02:23:27 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 75.5%
[2025-01-18 02:23:27 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:23:28 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:23:28 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 75.49%
[2025-01-18 02:23:31 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][0/312]	eta 0:14:52 lr 0.003081	time 2.8595 (2.8595)	model_time 0.4726 (0.4726)	loss 4.3135 (4.3135)	grad_norm 2.4310 (2.4310/0.0000)	mem 16099MB
[2025-01-18 02:23:36 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][10/312]	eta 0:03:23 lr 0.003080	time 0.4674 (0.6737)	model_time 0.4672 (0.4564)	loss 3.6349 (3.5191)	grad_norm 1.0208 (1.4794/0.4947)	mem 16099MB
[2025-01-18 02:23:40 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][20/312]	eta 0:02:47 lr 0.003080	time 0.4584 (0.5743)	model_time 0.4579 (0.4603)	loss 4.0321 (3.6083)	grad_norm 1.5625 (1.5286/0.5144)	mem 16099MB
[2025-01-18 02:23:45 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][30/312]	eta 0:02:33 lr 0.003079	time 0.4562 (0.5426)	model_time 0.4561 (0.4653)	loss 2.4908 (3.4633)	grad_norm 1.2876 (1.4920/0.5128)	mem 16099MB
[2025-01-18 02:23:50 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][40/312]	eta 0:02:21 lr 0.003079	time 0.4447 (0.5211)	model_time 0.4440 (0.4625)	loss 3.9993 (3.4817)	grad_norm 1.8342 (1.5151/0.4893)	mem 16099MB
[2025-01-18 02:23:54 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][50/312]	eta 0:02:13 lr 0.003078	time 0.4465 (0.5114)	model_time 0.4463 (0.4643)	loss 2.7910 (3.5152)	grad_norm 1.0707 (1.6159/0.6671)	mem 16099MB
[2025-01-18 02:23:59 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][60/312]	eta 0:02:06 lr 0.003078	time 0.4475 (0.5032)	model_time 0.4470 (0.4637)	loss 3.3086 (3.4925)	grad_norm 0.8937 (1.5694/0.6366)	mem 16099MB
[2025-01-18 02:24:04 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][70/312]	eta 0:02:01 lr 0.003077	time 0.4605 (0.5010)	model_time 0.4603 (0.4670)	loss 3.2921 (3.4817)	grad_norm 2.4887 (1.5500/0.6134)	mem 16099MB
[2025-01-18 02:24:08 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][80/312]	eta 0:01:54 lr 0.003076	time 0.4576 (0.4952)	model_time 0.4574 (0.4654)	loss 3.3765 (3.4636)	grad_norm 2.2515 (1.5088/0.6034)	mem 16099MB
[2025-01-18 02:24:13 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][90/312]	eta 0:01:49 lr 0.003076	time 0.5405 (0.4936)	model_time 0.5403 (0.4670)	loss 2.8302 (3.4508)	grad_norm 1.2657 (1.5414/0.6913)	mem 16099MB
[2025-01-18 02:24:18 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][100/312]	eta 0:01:44 lr 0.003075	time 0.4417 (0.4910)	model_time 0.4415 (0.4670)	loss 3.5490 (3.4552)	grad_norm 1.1877 (1.5019/0.6712)	mem 16099MB
[2025-01-18 02:24:23 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][110/312]	eta 0:01:38 lr 0.003075	time 0.4670 (0.4891)	model_time 0.4666 (0.4672)	loss 3.7585 (3.4724)	grad_norm 2.1960 (1.4790/0.6587)	mem 16099MB
[2025-01-18 02:24:27 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][120/312]	eta 0:01:33 lr 0.003074	time 0.4506 (0.4865)	model_time 0.4504 (0.4664)	loss 2.5507 (3.4546)	grad_norm 1.0906 (1.5529/0.7678)	mem 16099MB
[2025-01-18 02:24:32 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][130/312]	eta 0:01:28 lr 0.003074	time 0.4522 (0.4859)	model_time 0.4518 (0.4673)	loss 3.0126 (3.4385)	grad_norm 2.2682 (1.5466/0.7507)	mem 16099MB
[2025-01-18 02:24:37 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][140/312]	eta 0:01:23 lr 0.003073	time 0.4493 (0.4842)	model_time 0.4489 (0.4669)	loss 2.4462 (3.4341)	grad_norm 1.0030 (1.5450/0.7450)	mem 16099MB
[2025-01-18 02:24:41 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][150/312]	eta 0:01:18 lr 0.003073	time 0.4502 (0.4822)	model_time 0.4497 (0.4661)	loss 3.9394 (3.4555)	grad_norm 0.8984 (1.5125/0.7367)	mem 16099MB
[2025-01-18 02:24:46 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][160/312]	eta 0:01:13 lr 0.003072	time 0.5418 (0.4823)	model_time 0.5417 (0.4671)	loss 3.9236 (3.4631)	grad_norm 1.0564 (1.5057/0.7170)	mem 16099MB
[2025-01-18 02:24:51 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][170/312]	eta 0:01:08 lr 0.003071	time 0.4587 (0.4811)	model_time 0.4585 (0.4668)	loss 3.9243 (3.4678)	grad_norm 2.1543 (1.5057/0.7125)	mem 16099MB
[2025-01-18 02:24:55 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][180/312]	eta 0:01:03 lr 0.003071	time 0.4699 (0.4803)	model_time 0.4698 (0.4668)	loss 3.7411 (3.4830)	grad_norm 1.1614 (1.5157/0.7116)	mem 16099MB
[2025-01-18 02:25:00 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][190/312]	eta 0:00:58 lr 0.003070	time 0.4570 (0.4796)	model_time 0.4568 (0.4667)	loss 2.6711 (3.4772)	grad_norm 1.2195 (1.5483/0.7899)	mem 16099MB
[2025-01-18 02:25:05 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][200/312]	eta 0:00:53 lr 0.003070	time 0.4555 (0.4796)	model_time 0.4554 (0.4674)	loss 3.9016 (3.4819)	grad_norm 2.0263 (1.5854/0.8481)	mem 16099MB
[2025-01-18 02:25:09 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][210/312]	eta 0:00:48 lr 0.003069	time 0.4444 (0.4787)	model_time 0.4443 (0.4670)	loss 3.5826 (3.4815)	grad_norm 0.8159 (1.5741/0.8347)	mem 16099MB
[2025-01-18 02:25:14 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][220/312]	eta 0:00:43 lr 0.003069	time 0.4669 (0.4777)	model_time 0.4665 (0.4665)	loss 3.8215 (3.4851)	grad_norm 0.7896 (1.5695/0.8216)	mem 16099MB
[2025-01-18 02:25:19 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][230/312]	eta 0:00:39 lr 0.003068	time 0.4577 (0.4773)	model_time 0.4572 (0.4666)	loss 2.8024 (3.4792)	grad_norm 1.2846 (1.5708/0.8140)	mem 16099MB
[2025-01-18 02:25:23 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][240/312]	eta 0:00:34 lr 0.003067	time 0.4493 (0.4772)	model_time 0.4492 (0.4670)	loss 3.3717 (3.4877)	grad_norm 1.6801 (1.5784/0.8044)	mem 16099MB
[2025-01-18 02:25:28 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][250/312]	eta 0:00:29 lr 0.003067	time 0.4484 (0.4763)	model_time 0.4483 (0.4665)	loss 3.2467 (3.4848)	grad_norm 1.2942 (1.5736/0.7908)	mem 16099MB
[2025-01-18 02:25:33 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][260/312]	eta 0:00:24 lr 0.003066	time 0.4422 (0.4759)	model_time 0.4420 (0.4664)	loss 3.0748 (3.4909)	grad_norm 0.9537 (1.5591/0.7802)	mem 16099MB
[2025-01-18 02:25:37 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][270/312]	eta 0:00:19 lr 0.003066	time 0.4608 (0.4756)	model_time 0.4603 (0.4664)	loss 2.6893 (3.4784)	grad_norm 1.0286 (1.5701/0.7769)	mem 16099MB
[2025-01-18 02:25:42 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][280/312]	eta 0:00:15 lr 0.003065	time 0.4804 (0.4753)	model_time 0.4802 (0.4665)	loss 4.0988 (3.4670)	grad_norm 1.7668 (1.6008/0.8143)	mem 16099MB
[2025-01-18 02:25:47 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][290/312]	eta 0:00:10 lr 0.003065	time 0.4538 (0.4749)	model_time 0.4537 (0.4663)	loss 3.3973 (3.4641)	grad_norm 1.6779 (1.6152/0.8167)	mem 16099MB
[2025-01-18 02:25:51 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][300/312]	eta 0:00:05 lr 0.003064	time 0.4361 (0.4741)	model_time 0.4360 (0.4658)	loss 4.0443 (3.4739)	grad_norm 1.1966 (1.6056/0.8100)	mem 16099MB
[2025-01-18 02:25:56 internimage_t_1k_224] (main.py 510): INFO Train: [96/300][310/312]	eta 0:00:00 lr 0.003063	time 0.4383 (0.4733)	model_time 0.4382 (0.4653)	loss 3.6383 (3.4789)	grad_norm 1.4734 (1.5900/0.8121)	mem 16099MB
[2025-01-18 02:25:56 internimage_t_1k_224] (main.py 519): INFO EPOCH 96 training takes 0:02:27
[2025-01-18 02:25:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_96.pth saving......
[2025-01-18 02:25:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_96.pth saved !!!
[2025-01-18 02:26:05 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.448 (7.448)	Loss 0.9585 (0.9585)	Acc@1 79.102 (79.102)	Acc@5 95.459 (95.459)	Mem 16099MB
[2025-01-18 02:26:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.001)	Loss 1.2670 (1.0564)	Acc@1 71.558 (76.818)	Acc@5 91.479 (93.801)	Mem 16099MB
[2025-01-18 02:26:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:96] * Acc@1 76.733 Acc@5 93.826
[2025-01-18 02:26:08 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.7%
[2025-01-18 02:26:08 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.97%
[2025-01-18 02:26:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.346 (8.346)	Loss 0.9581 (0.9581)	Acc@1 79.126 (79.126)	Acc@5 95.483 (95.483)	Mem 16099MB
[2025-01-18 02:26:21 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.112)	Loss 1.3943 (1.1385)	Acc@1 69.092 (75.755)	Acc@5 89.819 (92.953)	Mem 16099MB
[2025-01-18 02:26:21 internimage_t_1k_224] (main.py 575): INFO [Epoch:96] * Acc@1 75.700 Acc@5 93.000
[2025-01-18 02:26:21 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 75.7%
[2025-01-18 02:26:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:26:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:26:22 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 75.70%
[2025-01-18 02:26:25 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][0/312]	eta 0:13:03 lr 0.003063	time 2.5109 (2.5109)	model_time 0.4627 (0.4627)	loss 3.3373 (3.3373)	grad_norm 1.7661 (1.7661/0.0000)	mem 16099MB
[2025-01-18 02:26:30 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][10/312]	eta 0:03:23 lr 0.003063	time 0.4738 (0.6722)	model_time 0.4737 (0.4857)	loss 2.8718 (3.3384)	grad_norm 1.8583 (1.5504/0.5509)	mem 16099MB
[2025-01-18 02:26:34 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][20/312]	eta 0:02:46 lr 0.003062	time 0.4544 (0.5716)	model_time 0.4540 (0.4738)	loss 2.3977 (3.3458)	grad_norm 1.4458 (1.3999/0.4656)	mem 16099MB
[2025-01-18 02:26:39 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][30/312]	eta 0:02:31 lr 0.003062	time 0.4557 (0.5381)	model_time 0.4555 (0.4718)	loss 3.6612 (3.3472)	grad_norm 1.4336 (1.3656/0.4131)	mem 16099MB
[2025-01-18 02:26:44 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][40/312]	eta 0:02:23 lr 0.003061	time 0.5563 (0.5287)	model_time 0.5559 (0.4785)	loss 2.4817 (3.4226)	grad_norm 0.8423 (1.4119/0.4701)	mem 16099MB
[2025-01-18 02:26:48 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][50/312]	eta 0:02:14 lr 0.003061	time 0.4484 (0.5146)	model_time 0.4479 (0.4741)	loss 3.2975 (3.4229)	grad_norm 0.8254 (1.5049/0.5163)	mem 16099MB
[2025-01-18 02:26:53 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][60/312]	eta 0:02:08 lr 0.003060	time 0.4503 (0.5083)	model_time 0.4501 (0.4744)	loss 3.2071 (3.4540)	grad_norm 1.3305 (1.5229/0.5756)	mem 16099MB
[2025-01-18 02:26:58 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][70/312]	eta 0:02:01 lr 0.003059	time 0.4427 (0.5038)	model_time 0.4425 (0.4746)	loss 2.8959 (3.4445)	grad_norm 1.4017 (1.4817/0.5569)	mem 16099MB
[2025-01-18 02:27:03 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][80/312]	eta 0:01:55 lr 0.003059	time 0.4877 (0.4984)	model_time 0.4872 (0.4727)	loss 3.2709 (3.4473)	grad_norm 2.3540 (1.4649/0.5512)	mem 16099MB
[2025-01-18 02:27:07 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][90/312]	eta 0:01:50 lr 0.003058	time 0.5391 (0.4961)	model_time 0.5389 (0.4732)	loss 2.7310 (3.4280)	grad_norm 1.5105 (1.4819/0.5767)	mem 16099MB
[2025-01-18 02:27:12 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][100/312]	eta 0:01:44 lr 0.003058	time 0.4503 (0.4932)	model_time 0.4498 (0.4723)	loss 2.6711 (3.4399)	grad_norm 0.9584 (1.4706/0.5644)	mem 16099MB
[2025-01-18 02:27:17 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][110/312]	eta 0:01:39 lr 0.003057	time 0.4574 (0.4909)	model_time 0.4572 (0.4719)	loss 2.4799 (3.4271)	grad_norm 3.5597 (1.5240/0.6078)	mem 16099MB
[2025-01-18 02:27:21 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][120/312]	eta 0:01:33 lr 0.003057	time 0.4594 (0.4879)	model_time 0.4589 (0.4705)	loss 3.0412 (3.4303)	grad_norm 0.7629 (1.5151/0.6066)	mem 16099MB
[2025-01-18 02:27:26 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][130/312]	eta 0:01:28 lr 0.003056	time 0.4948 (0.4863)	model_time 0.4944 (0.4701)	loss 4.1037 (3.4328)	grad_norm 3.4272 (1.5364/0.6221)	mem 16099MB
[2025-01-18 02:27:31 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][140/312]	eta 0:01:23 lr 0.003055	time 0.4503 (0.4867)	model_time 0.4499 (0.4717)	loss 3.7891 (3.4239)	grad_norm 0.9061 (1.5556/0.6288)	mem 16099MB
[2025-01-18 02:27:35 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][150/312]	eta 0:01:18 lr 0.003055	time 0.4582 (0.4846)	model_time 0.4580 (0.4706)	loss 3.0054 (3.4093)	grad_norm 3.2156 (1.5839/0.6487)	mem 16099MB
[2025-01-18 02:27:40 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][160/312]	eta 0:01:13 lr 0.003054	time 0.5678 (0.4836)	model_time 0.5673 (0.4704)	loss 3.5785 (3.4247)	grad_norm 1.4192 (1.5996/0.6738)	mem 16099MB
[2025-01-18 02:27:45 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][170/312]	eta 0:01:08 lr 0.003054	time 0.4499 (0.4827)	model_time 0.4497 (0.4702)	loss 3.7166 (3.4316)	grad_norm 0.9093 (1.5811/0.6623)	mem 16099MB
[2025-01-18 02:27:49 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][180/312]	eta 0:01:03 lr 0.003053	time 0.4853 (0.4815)	model_time 0.4849 (0.4697)	loss 3.1761 (3.4420)	grad_norm 0.9031 (1.5571/0.6552)	mem 16099MB
[2025-01-18 02:27:54 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][190/312]	eta 0:00:58 lr 0.003053	time 0.4472 (0.4805)	model_time 0.4470 (0.4693)	loss 3.3136 (3.4231)	grad_norm 0.9870 (1.5355/0.6521)	mem 16099MB
[2025-01-18 02:27:59 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][200/312]	eta 0:00:53 lr 0.003052	time 0.4540 (0.4798)	model_time 0.4538 (0.4692)	loss 3.8440 (3.4254)	grad_norm 2.3705 (1.5379/0.6502)	mem 16099MB
[2025-01-18 02:28:03 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][210/312]	eta 0:00:48 lr 0.003051	time 0.4328 (0.4794)	model_time 0.4323 (0.4692)	loss 3.5380 (3.4270)	grad_norm 2.3042 (1.5481/0.6517)	mem 16099MB
[2025-01-18 02:28:08 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][220/312]	eta 0:00:44 lr 0.003051	time 0.4433 (0.4786)	model_time 0.4429 (0.4689)	loss 4.0163 (3.4364)	grad_norm 1.1253 (1.5462/0.6467)	mem 16099MB
[2025-01-18 02:28:13 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][230/312]	eta 0:00:39 lr 0.003050	time 0.4390 (0.4782)	model_time 0.4389 (0.4688)	loss 2.6073 (3.4384)	grad_norm 1.7730 (1.5294/0.6423)	mem 16099MB
[2025-01-18 02:28:17 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][240/312]	eta 0:00:34 lr 0.003050	time 0.4444 (0.4775)	model_time 0.4440 (0.4686)	loss 3.9649 (3.4352)	grad_norm 1.0961 (1.5217/0.6319)	mem 16099MB
[2025-01-18 02:28:22 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][250/312]	eta 0:00:29 lr 0.003049	time 0.4495 (0.4777)	model_time 0.4494 (0.4691)	loss 3.6799 (3.4216)	grad_norm 3.5920 (1.5386/0.6490)	mem 16099MB
[2025-01-18 02:28:27 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][260/312]	eta 0:00:24 lr 0.003049	time 0.4800 (0.4773)	model_time 0.4799 (0.4690)	loss 2.3254 (3.4103)	grad_norm 2.4139 (1.5675/0.6964)	mem 16099MB
[2025-01-18 02:28:31 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][270/312]	eta 0:00:20 lr 0.003048	time 0.4531 (0.4768)	model_time 0.4529 (0.4688)	loss 3.7592 (3.4024)	grad_norm 1.3782 (1.5642/0.6879)	mem 16099MB
[2025-01-18 02:28:36 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][280/312]	eta 0:00:15 lr 0.003048	time 0.4544 (0.4770)	model_time 0.4540 (0.4692)	loss 3.7193 (3.4063)	grad_norm 1.0921 (1.5732/0.6870)	mem 16099MB
[2025-01-18 02:28:41 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][290/312]	eta 0:00:10 lr 0.003047	time 0.4470 (0.4765)	model_time 0.4466 (0.4690)	loss 3.6779 (3.4071)	grad_norm 0.9388 (1.5832/0.7063)	mem 16099MB
[2025-01-18 02:28:45 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][300/312]	eta 0:00:05 lr 0.003046	time 0.4395 (0.4758)	model_time 0.4394 (0.4686)	loss 3.0782 (3.3992)	grad_norm 1.5034 (1.5796/0.7010)	mem 16099MB
[2025-01-18 02:28:50 internimage_t_1k_224] (main.py 510): INFO Train: [97/300][310/312]	eta 0:00:00 lr 0.003046	time 0.5701 (0.4754)	model_time 0.5699 (0.4684)	loss 3.7538 (3.3945)	grad_norm 1.3193 (1.5768/0.6962)	mem 16099MB
[2025-01-18 02:28:50 internimage_t_1k_224] (main.py 519): INFO EPOCH 97 training takes 0:02:28
[2025-01-18 02:28:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_97.pth saving......
[2025-01-18 02:28:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_97.pth saved !!!
[2025-01-18 02:28:59 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.347 (7.347)	Loss 0.9037 (0.9037)	Acc@1 80.273 (80.273)	Acc@5 95.923 (95.923)	Mem 16099MB
[2025-01-18 02:29:03 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.000)	Loss 1.2283 (1.0540)	Acc@1 72.241 (76.946)	Acc@5 91.895 (93.841)	Mem 16099MB
[2025-01-18 02:29:03 internimage_t_1k_224] (main.py 575): INFO [Epoch:97] * Acc@1 76.941 Acc@5 93.910
[2025-01-18 02:29:03 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.9%
[2025-01-18 02:29:03 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.97%
[2025-01-18 02:29:11 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.389 (8.389)	Loss 0.9485 (0.9485)	Acc@1 79.346 (79.346)	Acc@5 95.483 (95.483)	Mem 16099MB
[2025-01-18 02:29:15 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.105)	Loss 1.3806 (1.1273)	Acc@1 69.336 (75.963)	Acc@5 90.039 (93.075)	Mem 16099MB
[2025-01-18 02:29:15 internimage_t_1k_224] (main.py 575): INFO [Epoch:97] * Acc@1 75.908 Acc@5 93.116
[2025-01-18 02:29:15 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 75.9%
[2025-01-18 02:29:15 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:29:17 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:29:17 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 75.91%
[2025-01-18 02:29:19 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][0/312]	eta 0:11:35 lr 0.003046	time 2.2302 (2.2302)	model_time 0.5626 (0.5626)	loss 3.6242 (3.6242)	grad_norm 1.0548 (1.0548/0.0000)	mem 16099MB
[2025-01-18 02:29:24 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][10/312]	eta 0:03:09 lr 0.003045	time 0.4414 (0.6286)	model_time 0.4409 (0.4766)	loss 3.6079 (3.3970)	grad_norm 2.9512 (1.5974/0.6635)	mem 16099MB
[2025-01-18 02:29:28 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][20/312]	eta 0:02:39 lr 0.003045	time 0.4569 (0.5465)	model_time 0.4567 (0.4668)	loss 2.6618 (3.4292)	grad_norm 0.8908 (1.8002/0.8644)	mem 16099MB
[2025-01-18 02:29:33 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][30/312]	eta 0:02:25 lr 0.003044	time 0.4536 (0.5164)	model_time 0.4534 (0.4622)	loss 3.5786 (3.4123)	grad_norm 2.9927 (1.8482/0.7831)	mem 16099MB
[2025-01-18 02:29:37 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][40/312]	eta 0:02:16 lr 0.003043	time 0.4719 (0.5023)	model_time 0.4718 (0.4612)	loss 3.5158 (3.4171)	grad_norm 1.7418 (1.8014/0.7063)	mem 16099MB
[2025-01-18 02:29:42 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][50/312]	eta 0:02:10 lr 0.003043	time 0.4555 (0.4986)	model_time 0.4553 (0.4656)	loss 3.5047 (3.4327)	grad_norm 2.9943 (1.8432/0.7715)	mem 16099MB
[2025-01-18 02:29:47 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][60/312]	eta 0:02:04 lr 0.003042	time 0.4525 (0.4925)	model_time 0.4521 (0.4648)	loss 2.8101 (3.4150)	grad_norm 1.3438 (1.8151/0.7220)	mem 16099MB
[2025-01-18 02:29:51 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][70/312]	eta 0:01:58 lr 0.003042	time 0.4478 (0.4885)	model_time 0.4473 (0.4646)	loss 2.4869 (3.4026)	grad_norm 1.1944 (1.7505/0.7046)	mem 16099MB
[2025-01-18 02:29:56 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][80/312]	eta 0:01:52 lr 0.003041	time 0.5216 (0.4854)	model_time 0.5214 (0.4644)	loss 4.4494 (3.4539)	grad_norm 1.1211 (1.7030/0.6881)	mem 16099MB
[2025-01-18 02:30:01 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][90/312]	eta 0:01:47 lr 0.003041	time 0.5368 (0.4843)	model_time 0.5366 (0.4656)	loss 2.4704 (3.4654)	grad_norm 0.7064 (1.7054/0.6933)	mem 16099MB
[2025-01-18 02:30:05 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][100/312]	eta 0:01:42 lr 0.003040	time 0.4742 (0.4824)	model_time 0.4738 (0.4655)	loss 3.0576 (3.4472)	grad_norm 1.0750 (1.6678/0.6759)	mem 16099MB
[2025-01-18 02:30:10 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][110/312]	eta 0:01:37 lr 0.003039	time 0.4574 (0.4817)	model_time 0.4572 (0.4663)	loss 2.1507 (3.4119)	grad_norm 3.8200 (1.7254/0.7655)	mem 16099MB
[2025-01-18 02:30:15 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][120/312]	eta 0:01:32 lr 0.003039	time 0.4507 (0.4798)	model_time 0.4505 (0.4657)	loss 4.1236 (3.4180)	grad_norm 1.2008 (1.7001/0.7473)	mem 16099MB
[2025-01-18 02:30:20 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][130/312]	eta 0:01:27 lr 0.003038	time 0.4506 (0.4807)	model_time 0.4502 (0.4676)	loss 2.3752 (3.4070)	grad_norm 0.9266 (1.6823/0.7295)	mem 16099MB
[2025-01-18 02:30:25 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][140/312]	eta 0:01:22 lr 0.003038	time 0.5527 (0.4814)	model_time 0.5525 (0.4692)	loss 3.5787 (3.4127)	grad_norm 1.2379 (1.6607/0.7192)	mem 16099MB
[2025-01-18 02:30:29 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][150/312]	eta 0:01:17 lr 0.003037	time 0.4470 (0.4808)	model_time 0.4466 (0.4693)	loss 3.9775 (3.4246)	grad_norm 1.2317 (1.6577/0.7139)	mem 16099MB
[2025-01-18 02:30:34 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][160/312]	eta 0:01:12 lr 0.003037	time 0.4644 (0.4792)	model_time 0.4640 (0.4685)	loss 3.1475 (3.4174)	grad_norm 1.8912 (1.7045/0.7615)	mem 16099MB
[2025-01-18 02:30:39 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][170/312]	eta 0:01:08 lr 0.003036	time 0.4395 (0.4792)	model_time 0.4393 (0.4691)	loss 3.4745 (3.4138)	grad_norm 1.4729 (1.7173/0.7708)	mem 16099MB
[2025-01-18 02:30:43 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][180/312]	eta 0:01:03 lr 0.003035	time 0.4825 (0.4781)	model_time 0.4821 (0.4685)	loss 3.7453 (3.4247)	grad_norm 1.2953 (1.6842/0.7632)	mem 16099MB
[2025-01-18 02:30:48 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][190/312]	eta 0:00:58 lr 0.003035	time 0.4513 (0.4773)	model_time 0.4511 (0.4682)	loss 3.7758 (3.4340)	grad_norm 1.6823 (1.6606/0.7533)	mem 16099MB
[2025-01-18 02:30:53 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][200/312]	eta 0:00:53 lr 0.003034	time 0.4394 (0.4771)	model_time 0.4389 (0.4685)	loss 2.9251 (3.4348)	grad_norm 1.0144 (1.6489/0.7497)	mem 16099MB
[2025-01-18 02:30:57 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][210/312]	eta 0:00:48 lr 0.003034	time 0.4414 (0.4767)	model_time 0.4409 (0.4684)	loss 3.5574 (3.4348)	grad_norm 1.9565 (1.6324/0.7398)	mem 16099MB
[2025-01-18 02:31:02 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][220/312]	eta 0:00:43 lr 0.003033	time 0.4487 (0.4765)	model_time 0.4483 (0.4685)	loss 3.3962 (3.4432)	grad_norm 4.8752 (1.6420/0.7602)	mem 16099MB
[2025-01-18 02:31:07 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][230/312]	eta 0:00:39 lr 0.003033	time 0.4533 (0.4764)	model_time 0.4532 (0.4688)	loss 3.4661 (3.4511)	grad_norm 3.0214 (1.6675/0.7781)	mem 16099MB
[2025-01-18 02:31:11 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][240/312]	eta 0:00:34 lr 0.003032	time 0.4514 (0.4760)	model_time 0.4510 (0.4687)	loss 3.2066 (3.4682)	grad_norm 0.7664 (1.6515/0.7690)	mem 16099MB
[2025-01-18 02:31:16 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][250/312]	eta 0:00:29 lr 0.003031	time 0.4474 (0.4756)	model_time 0.4469 (0.4686)	loss 3.9101 (3.4758)	grad_norm 3.1108 (1.6645/0.7784)	mem 16099MB
[2025-01-18 02:31:21 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][260/312]	eta 0:00:24 lr 0.003031	time 0.4483 (0.4752)	model_time 0.4478 (0.4685)	loss 3.9265 (3.4731)	grad_norm 0.7785 (1.6654/0.7774)	mem 16099MB
[2025-01-18 02:31:25 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][270/312]	eta 0:00:19 lr 0.003030	time 0.4442 (0.4745)	model_time 0.4440 (0.4680)	loss 3.7265 (3.4755)	grad_norm 1.3640 (1.6516/0.7697)	mem 16099MB
[2025-01-18 02:31:30 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][280/312]	eta 0:00:15 lr 0.003030	time 0.4505 (0.4749)	model_time 0.4500 (0.4686)	loss 3.8017 (3.4778)	grad_norm 1.2374 (1.6413/0.7602)	mem 16099MB
[2025-01-18 02:31:35 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][290/312]	eta 0:00:10 lr 0.003029	time 0.4459 (0.4744)	model_time 0.4458 (0.4683)	loss 4.0555 (3.4899)	grad_norm 6.0783 (1.6602/0.8141)	mem 16099MB
[2025-01-18 02:31:39 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][300/312]	eta 0:00:05 lr 0.003029	time 0.4376 (0.4743)	model_time 0.4375 (0.4683)	loss 3.7506 (3.4922)	grad_norm 1.4669 (1.6729/0.8136)	mem 16099MB
[2025-01-18 02:31:44 internimage_t_1k_224] (main.py 510): INFO Train: [98/300][310/312]	eta 0:00:00 lr 0.003028	time 0.4413 (0.4733)	model_time 0.4412 (0.4675)	loss 2.7870 (3.4904)	grad_norm 1.0199 (1.6554/0.8133)	mem 16099MB
[2025-01-18 02:31:44 internimage_t_1k_224] (main.py 519): INFO EPOCH 98 training takes 0:02:27
[2025-01-18 02:31:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_98.pth saving......
[2025-01-18 02:31:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_98.pth saved !!!
[2025-01-18 02:31:53 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.936 (7.936)	Loss 0.8789 (0.8789)	Acc@1 80.469 (80.469)	Acc@5 95.337 (95.337)	Mem 16099MB
[2025-01-18 02:31:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.064)	Loss 1.2533 (1.0469)	Acc@1 71.582 (76.933)	Acc@5 91.138 (93.719)	Mem 16099MB
[2025-01-18 02:31:57 internimage_t_1k_224] (main.py 575): INFO [Epoch:98] * Acc@1 76.945 Acc@5 93.764
[2025-01-18 02:31:57 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.9%
[2025-01-18 02:31:57 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.97%
[2025-01-18 02:32:06 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.503 (8.503)	Loss 0.9398 (0.9398)	Acc@1 79.492 (79.492)	Acc@5 95.557 (95.557)	Mem 16099MB
[2025-01-18 02:32:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.148)	Loss 1.3674 (1.1169)	Acc@1 69.629 (76.134)	Acc@5 90.186 (93.220)	Mem 16099MB
[2025-01-18 02:32:10 internimage_t_1k_224] (main.py 575): INFO [Epoch:98] * Acc@1 76.080 Acc@5 93.258
[2025-01-18 02:32:10 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 76.1%
[2025-01-18 02:32:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:32:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:32:12 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 76.08%
[2025-01-18 02:32:14 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][0/312]	eta 0:11:53 lr 0.003028	time 2.2874 (2.2874)	model_time 0.4884 (0.4884)	loss 3.5284 (3.5284)	grad_norm 0.9942 (0.9942/0.0000)	mem 16099MB
[2025-01-18 02:32:18 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][10/312]	eta 0:03:11 lr 0.003027	time 0.4562 (0.6334)	model_time 0.4560 (0.4696)	loss 3.3257 (3.3342)	grad_norm 1.1258 (1.5877/0.4301)	mem 16099MB
[2025-01-18 02:32:23 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][20/312]	eta 0:02:41 lr 0.003027	time 0.4614 (0.5530)	model_time 0.4609 (0.4670)	loss 3.2661 (3.4227)	grad_norm 1.6202 (1.4654/0.4082)	mem 16099MB
[2025-01-18 02:32:28 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][30/312]	eta 0:02:28 lr 0.003026	time 0.4471 (0.5257)	model_time 0.4467 (0.4674)	loss 2.6697 (3.4509)	grad_norm 2.8414 (1.4891/0.4771)	mem 16099MB
[2025-01-18 02:32:32 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][40/312]	eta 0:02:18 lr 0.003026	time 0.4578 (0.5088)	model_time 0.4576 (0.4646)	loss 4.3589 (3.4279)	grad_norm 1.9854 (1.5102/0.4661)	mem 16099MB
[2025-01-18 02:32:37 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][50/312]	eta 0:02:11 lr 0.003025	time 0.4615 (0.5013)	model_time 0.4611 (0.4657)	loss 2.1452 (3.4393)	grad_norm 1.7153 (1.5203/0.4349)	mem 16099MB
[2025-01-18 02:32:42 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][60/312]	eta 0:02:04 lr 0.003024	time 0.4646 (0.4954)	model_time 0.4645 (0.4655)	loss 3.8861 (3.4224)	grad_norm 1.9823 (1.5801/0.5174)	mem 16099MB
[2025-01-18 02:32:46 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][70/312]	eta 0:01:58 lr 0.003024	time 0.4545 (0.4908)	model_time 0.4543 (0.4651)	loss 3.9139 (3.4001)	grad_norm 1.7848 (1.5552/0.4990)	mem 16099MB
[2025-01-18 02:32:51 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][80/312]	eta 0:01:52 lr 0.003023	time 0.4607 (0.4866)	model_time 0.4606 (0.4640)	loss 2.6573 (3.3934)	grad_norm 1.5462 (1.5458/0.4970)	mem 16099MB
[2025-01-18 02:32:56 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][90/312]	eta 0:01:47 lr 0.003023	time 0.4508 (0.4845)	model_time 0.4504 (0.4643)	loss 3.4873 (3.4008)	grad_norm 1.8300 (1.5772/0.5289)	mem 16099MB
[2025-01-18 02:33:00 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][100/312]	eta 0:01:42 lr 0.003022	time 0.4528 (0.4838)	model_time 0.4524 (0.4656)	loss 3.2968 (3.3887)	grad_norm 1.5508 (1.5668/0.5213)	mem 16099MB
[2025-01-18 02:33:05 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][110/312]	eta 0:01:37 lr 0.003022	time 0.4581 (0.4836)	model_time 0.4580 (0.4671)	loss 3.6702 (3.3856)	grad_norm 1.2462 (1.5663/0.5303)	mem 16099MB
[2025-01-18 02:33:10 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][120/312]	eta 0:01:32 lr 0.003021	time 0.4519 (0.4825)	model_time 0.4515 (0.4673)	loss 2.5794 (3.3735)	grad_norm 2.7006 (1.5902/0.5636)	mem 16099MB
[2025-01-18 02:33:15 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][130/312]	eta 0:01:28 lr 0.003020	time 0.5522 (0.4844)	model_time 0.5518 (0.4703)	loss 3.8197 (3.3830)	grad_norm 1.1011 (1.6298/0.6032)	mem 16099MB
[2025-01-18 02:33:20 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][140/312]	eta 0:01:23 lr 0.003020	time 0.4566 (0.4835)	model_time 0.4561 (0.4704)	loss 3.6488 (3.3836)	grad_norm 1.5213 (1.6134/0.5866)	mem 16099MB
[2025-01-18 02:33:24 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][150/312]	eta 0:01:18 lr 0.003019	time 0.4537 (0.4826)	model_time 0.4533 (0.4703)	loss 3.7885 (3.3871)	grad_norm 1.3006 (1.6196/0.6002)	mem 16099MB
[2025-01-18 02:33:29 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][160/312]	eta 0:01:13 lr 0.003019	time 0.4427 (0.4832)	model_time 0.4425 (0.4717)	loss 3.5958 (3.4191)	grad_norm 1.0566 (1.5848/0.6002)	mem 16099MB
[2025-01-18 02:33:34 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][170/312]	eta 0:01:08 lr 0.003018	time 0.4538 (0.4836)	model_time 0.4537 (0.4727)	loss 3.6787 (3.4296)	grad_norm 2.5759 (1.6215/0.6226)	mem 16099MB
[2025-01-18 02:33:39 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][180/312]	eta 0:01:03 lr 0.003018	time 0.4549 (0.4821)	model_time 0.4545 (0.4718)	loss 4.2707 (3.4452)	grad_norm 2.7769 (1.6190/0.6186)	mem 16099MB
[2025-01-18 02:33:43 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][190/312]	eta 0:00:58 lr 0.003017	time 0.5026 (0.4809)	model_time 0.5022 (0.4711)	loss 3.4736 (3.4401)	grad_norm 1.9945 (1.6332/0.6198)	mem 16099MB
[2025-01-18 02:33:48 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][200/312]	eta 0:00:53 lr 0.003016	time 0.4452 (0.4801)	model_time 0.4450 (0.4707)	loss 4.2369 (3.4507)	grad_norm 0.8866 (1.6461/0.6267)	mem 16099MB
[2025-01-18 02:33:53 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][210/312]	eta 0:00:48 lr 0.003016	time 0.4449 (0.4799)	model_time 0.4445 (0.4710)	loss 3.0691 (3.4590)	grad_norm 0.6939 (1.6273/0.6293)	mem 16099MB
[2025-01-18 02:33:57 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][220/312]	eta 0:00:44 lr 0.003015	time 0.4577 (0.4790)	model_time 0.4575 (0.4704)	loss 3.3623 (3.4705)	grad_norm 2.5263 (1.6223/0.6325)	mem 16099MB
[2025-01-18 02:34:02 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][230/312]	eta 0:00:39 lr 0.003015	time 0.4436 (0.4781)	model_time 0.4432 (0.4699)	loss 3.6460 (3.4729)	grad_norm 1.2001 (1.6288/0.6380)	mem 16099MB
[2025-01-18 02:34:07 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][240/312]	eta 0:00:34 lr 0.003014	time 0.4695 (0.4774)	model_time 0.4693 (0.4696)	loss 4.1585 (3.4801)	grad_norm 1.7618 (1.6200/0.6278)	mem 16099MB
[2025-01-18 02:34:11 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][250/312]	eta 0:00:29 lr 0.003014	time 0.4539 (0.4765)	model_time 0.4538 (0.4689)	loss 3.4698 (3.4881)	grad_norm 3.1137 (1.6456/0.6862)	mem 16099MB
[2025-01-18 02:34:16 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][260/312]	eta 0:00:24 lr 0.003013	time 0.4497 (0.4760)	model_time 0.4493 (0.4688)	loss 3.9265 (3.4920)	grad_norm 0.9754 (1.6279/0.6819)	mem 16099MB
[2025-01-18 02:34:20 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][270/312]	eta 0:00:19 lr 0.003012	time 0.4503 (0.4755)	model_time 0.4501 (0.4685)	loss 2.8727 (3.4942)	grad_norm 1.4923 (1.6424/0.6940)	mem 16099MB
[2025-01-18 02:34:25 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][280/312]	eta 0:00:15 lr 0.003012	time 0.4556 (0.4751)	model_time 0.4554 (0.4683)	loss 3.7101 (3.4827)	grad_norm 0.7183 (1.6235/0.6932)	mem 16099MB
[2025-01-18 02:34:30 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][290/312]	eta 0:00:10 lr 0.003011	time 0.5300 (0.4754)	model_time 0.5296 (0.4688)	loss 2.9292 (3.4805)	grad_norm 1.2823 (1.6122/0.6913)	mem 16099MB
[2025-01-18 02:34:34 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][300/312]	eta 0:00:05 lr 0.003011	time 0.4388 (0.4747)	model_time 0.4387 (0.4683)	loss 2.8173 (3.4752)	grad_norm 0.8562 (1.6330/0.7207)	mem 16099MB
[2025-01-18 02:34:39 internimage_t_1k_224] (main.py 510): INFO Train: [99/300][310/312]	eta 0:00:00 lr 0.003010	time 0.4374 (0.4739)	model_time 0.4373 (0.4678)	loss 3.6951 (3.4697)	grad_norm 1.2607 (1.6125/0.7262)	mem 16099MB
[2025-01-18 02:34:39 internimage_t_1k_224] (main.py 519): INFO EPOCH 99 training takes 0:02:27
[2025-01-18 02:34:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_99.pth saving......
[2025-01-18 02:34:41 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_99.pth saved !!!
[2025-01-18 02:34:49 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.083 (8.083)	Loss 0.9047 (0.9047)	Acc@1 79.932 (79.932)	Acc@5 95.776 (95.776)	Mem 16099MB
[2025-01-18 02:34:53 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.129)	Loss 1.3103 (1.0916)	Acc@1 71.680 (76.911)	Acc@5 91.479 (93.872)	Mem 16099MB
[2025-01-18 02:34:53 internimage_t_1k_224] (main.py 575): INFO [Epoch:99] * Acc@1 76.833 Acc@5 93.876
[2025-01-18 02:34:53 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.8%
[2025-01-18 02:34:53 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.97%
[2025-01-18 02:35:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 9.882 (9.882)	Loss 0.9314 (0.9314)	Acc@1 79.492 (79.492)	Acc@5 95.630 (95.630)	Mem 16099MB
[2025-01-18 02:35:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.348)	Loss 1.3552 (1.1069)	Acc@1 69.800 (76.261)	Acc@5 90.259 (93.277)	Mem 16099MB
[2025-01-18 02:35:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:99] * Acc@1 76.210 Acc@5 93.318
[2025-01-18 02:35:08 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 76.2%
[2025-01-18 02:35:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:35:10 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:35:10 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 76.21%
[2025-01-18 02:35:12 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][0/312]	eta 0:13:27 lr 0.003010	time 2.5889 (2.5889)	model_time 0.4620 (0.4620)	loss 2.7490 (2.7490)	grad_norm 0.8922 (0.8922/0.0000)	mem 16099MB
[2025-01-18 02:35:17 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][10/312]	eta 0:03:19 lr 0.003009	time 0.4509 (0.6615)	model_time 0.4508 (0.4679)	loss 2.5829 (3.2362)	grad_norm 1.0820 (1.0516/0.2570)	mem 16099MB
[2025-01-18 02:35:22 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][20/312]	eta 0:02:48 lr 0.003009	time 0.5709 (0.5773)	model_time 0.5704 (0.4756)	loss 2.7505 (3.3280)	grad_norm 3.0149 (1.5592/0.9937)	mem 16099MB
[2025-01-18 02:35:27 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][30/312]	eta 0:02:35 lr 0.003008	time 0.5471 (0.5506)	model_time 0.5470 (0.4816)	loss 4.1783 (3.3752)	grad_norm 1.7922 (1.7090/0.9826)	mem 16099MB
[2025-01-18 02:35:31 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][40/312]	eta 0:02:24 lr 0.003008	time 0.4642 (0.5294)	model_time 0.4638 (0.4771)	loss 2.9931 (3.4237)	grad_norm 1.8590 (1.6517/0.8920)	mem 16099MB
[2025-01-18 02:35:36 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][50/312]	eta 0:02:15 lr 0.003007	time 0.4459 (0.5175)	model_time 0.4457 (0.4754)	loss 3.5215 (3.4358)	grad_norm 0.7382 (1.5789/0.8572)	mem 16099MB
[2025-01-18 02:35:41 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][60/312]	eta 0:02:08 lr 0.003007	time 0.4571 (0.5097)	model_time 0.4569 (0.4744)	loss 2.1572 (3.4268)	grad_norm 1.1643 (1.5136/0.8041)	mem 16099MB
[2025-01-18 02:35:45 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][70/312]	eta 0:02:01 lr 0.003006	time 0.4435 (0.5025)	model_time 0.4433 (0.4721)	loss 3.2469 (3.4213)	grad_norm 4.6573 (1.5792/0.8994)	mem 16099MB
[2025-01-18 02:35:50 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][80/312]	eta 0:01:55 lr 0.003005	time 0.4543 (0.4974)	model_time 0.4541 (0.4707)	loss 3.7800 (3.4420)	grad_norm 0.9721 (1.6353/0.9392)	mem 16099MB
[2025-01-18 02:35:54 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][90/312]	eta 0:01:49 lr 0.003005	time 0.4588 (0.4928)	model_time 0.4584 (0.4690)	loss 3.3639 (3.4415)	grad_norm 1.1534 (1.5935/0.9076)	mem 16099MB
[2025-01-18 02:35:59 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][100/312]	eta 0:01:44 lr 0.003004	time 0.4387 (0.4915)	model_time 0.4385 (0.4700)	loss 3.9374 (3.4083)	grad_norm 0.9423 (1.5662/0.8705)	mem 16099MB
[2025-01-18 02:36:04 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][110/312]	eta 0:01:39 lr 0.003004	time 0.4684 (0.4914)	model_time 0.4681 (0.4718)	loss 3.3981 (3.4107)	grad_norm 2.1407 (1.5479/0.8404)	mem 16099MB
[2025-01-18 02:36:09 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][120/312]	eta 0:01:33 lr 0.003003	time 0.5148 (0.4888)	model_time 0.5146 (0.4708)	loss 2.6837 (3.3816)	grad_norm 1.8254 (1.5580/0.8301)	mem 16099MB
[2025-01-18 02:36:13 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][130/312]	eta 0:01:28 lr 0.003003	time 0.4582 (0.4870)	model_time 0.4580 (0.4704)	loss 3.6162 (3.3973)	grad_norm 1.1261 (1.5566/0.8081)	mem 16099MB
[2025-01-18 02:36:18 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][140/312]	eta 0:01:23 lr 0.003002	time 0.5311 (0.4855)	model_time 0.5309 (0.4700)	loss 4.0771 (3.4190)	grad_norm 3.2736 (1.5450/0.8061)	mem 16099MB
[2025-01-18 02:36:23 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][150/312]	eta 0:01:18 lr 0.003001	time 0.4714 (0.4836)	model_time 0.4708 (0.4692)	loss 3.5429 (3.4018)	grad_norm 1.7292 (1.5515/0.7850)	mem 16099MB
[2025-01-18 02:36:27 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][160/312]	eta 0:01:13 lr 0.003001	time 0.4521 (0.4819)	model_time 0.4518 (0.4682)	loss 4.1167 (3.4081)	grad_norm 1.3679 (1.5515/0.7700)	mem 16099MB
[2025-01-18 02:36:32 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][170/312]	eta 0:01:08 lr 0.003000	time 0.4470 (0.4828)	model_time 0.4468 (0.4700)	loss 3.7559 (3.4081)	grad_norm 2.5087 (1.5798/0.7789)	mem 16099MB
[2025-01-18 02:36:37 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][180/312]	eta 0:01:03 lr 0.003000	time 0.4622 (0.4816)	model_time 0.4621 (0.4695)	loss 3.1548 (3.4068)	grad_norm 2.0570 (1.5956/0.7884)	mem 16099MB
[2025-01-18 02:36:41 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][190/312]	eta 0:00:58 lr 0.002999	time 0.4530 (0.4805)	model_time 0.4528 (0.4690)	loss 3.8302 (3.4257)	grad_norm 0.9077 (1.5848/0.7777)	mem 16099MB
[2025-01-18 02:36:46 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][200/312]	eta 0:00:53 lr 0.002998	time 0.4469 (0.4794)	model_time 0.4467 (0.4684)	loss 2.7207 (3.4165)	grad_norm 0.8207 (1.5782/0.7674)	mem 16099MB
[2025-01-18 02:36:51 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][210/312]	eta 0:00:48 lr 0.002998	time 0.4634 (0.4787)	model_time 0.4632 (0.4682)	loss 2.7790 (3.4152)	grad_norm 1.3067 (1.5693/0.7553)	mem 16099MB
[2025-01-18 02:36:55 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][220/312]	eta 0:00:43 lr 0.002997	time 0.4523 (0.4775)	model_time 0.4521 (0.4675)	loss 3.6302 (3.4200)	grad_norm 1.4333 (1.5895/0.7693)	mem 16099MB
[2025-01-18 02:37:00 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][230/312]	eta 0:00:39 lr 0.002997	time 0.4443 (0.4768)	model_time 0.4438 (0.4673)	loss 2.4228 (3.4297)	grad_norm 2.0733 (1.5927/0.7625)	mem 16099MB
[2025-01-18 02:37:05 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][240/312]	eta 0:00:34 lr 0.002996	time 0.4500 (0.4767)	model_time 0.4498 (0.4675)	loss 3.9327 (3.4400)	grad_norm 1.1360 (1.6134/0.7701)	mem 16099MB
[2025-01-18 02:37:09 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][250/312]	eta 0:00:29 lr 0.002996	time 0.4471 (0.4757)	model_time 0.4470 (0.4669)	loss 3.6636 (3.4355)	grad_norm 1.4395 (1.6105/0.7605)	mem 16099MB
[2025-01-18 02:37:14 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][260/312]	eta 0:00:24 lr 0.002995	time 0.4551 (0.4756)	model_time 0.4546 (0.4670)	loss 4.3965 (3.4413)	grad_norm 3.4750 (1.6130/0.7615)	mem 16099MB
[2025-01-18 02:37:18 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][270/312]	eta 0:00:19 lr 0.002994	time 0.4418 (0.4755)	model_time 0.4413 (0.4672)	loss 2.9873 (3.4361)	grad_norm 1.0689 (1.6229/0.7678)	mem 16099MB
[2025-01-18 02:37:23 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][280/312]	eta 0:00:15 lr 0.002994	time 0.4557 (0.4754)	model_time 0.4552 (0.4674)	loss 3.8450 (3.4427)	grad_norm 2.8589 (1.6279/0.7615)	mem 16099MB
[2025-01-18 02:37:28 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][290/312]	eta 0:00:10 lr 0.002993	time 0.4617 (0.4750)	model_time 0.4615 (0.4672)	loss 3.7028 (3.4385)	grad_norm 2.4890 (1.6252/0.7646)	mem 16099MB
[2025-01-18 02:37:32 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][300/312]	eta 0:00:05 lr 0.002993	time 0.4390 (0.4744)	model_time 0.4388 (0.4669)	loss 3.6628 (3.4410)	grad_norm 1.9425 (1.6294/0.7637)	mem 16099MB
[2025-01-18 02:37:37 internimage_t_1k_224] (main.py 510): INFO Train: [100/300][310/312]	eta 0:00:00 lr 0.002992	time 0.4382 (0.4740)	model_time 0.4381 (0.4667)	loss 4.1828 (3.4412)	grad_norm 0.9101 (1.6385/0.7614)	mem 16099MB
[2025-01-18 02:37:38 internimage_t_1k_224] (main.py 519): INFO EPOCH 100 training takes 0:02:27
[2025-01-18 02:37:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_100.pth saving......
[2025-01-18 02:37:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_100.pth saved !!!
[2025-01-18 02:37:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.601 (7.601)	Loss 0.8986 (0.8986)	Acc@1 80.762 (80.762)	Acc@5 95.581 (95.581)	Mem 16099MB
[2025-01-18 02:37:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.030)	Loss 1.2975 (1.0601)	Acc@1 71.021 (76.831)	Acc@5 91.504 (93.908)	Mem 16099MB
[2025-01-18 02:37:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:100] * Acc@1 76.737 Acc@5 93.926
[2025-01-18 02:37:50 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.7%
[2025-01-18 02:37:50 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.97%
[2025-01-18 02:37:59 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.842 (8.842)	Loss 0.9231 (0.9231)	Acc@1 79.761 (79.761)	Acc@5 95.703 (95.703)	Mem 16099MB
[2025-01-18 02:38:03 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.169)	Loss 1.3432 (1.0975)	Acc@1 70.117 (76.447)	Acc@5 90.332 (93.357)	Mem 16099MB
[2025-01-18 02:38:03 internimage_t_1k_224] (main.py 575): INFO [Epoch:100] * Acc@1 76.382 Acc@5 93.392
[2025-01-18 02:38:03 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 76.4%
[2025-01-18 02:38:03 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:38:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:38:05 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 76.38%
[2025-01-18 02:38:07 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][0/312]	eta 0:11:44 lr 0.002992	time 2.2569 (2.2569)	model_time 0.4832 (0.4832)	loss 3.3229 (3.3229)	grad_norm 2.1524 (2.1524/0.0000)	mem 16099MB
[2025-01-18 02:38:11 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][10/312]	eta 0:03:11 lr 0.002991	time 0.4647 (0.6341)	model_time 0.4646 (0.4725)	loss 3.4083 (3.7178)	grad_norm 1.8655 (1.6177/0.4325)	mem 16099MB
[2025-01-18 02:38:16 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][20/312]	eta 0:02:41 lr 0.002991	time 0.4527 (0.5518)	model_time 0.4525 (0.4670)	loss 3.2312 (3.5770)	grad_norm 1.3507 (1.5131/0.4376)	mem 16099MB
[2025-01-18 02:38:21 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][30/312]	eta 0:02:29 lr 0.002990	time 0.4486 (0.5285)	model_time 0.4479 (0.4709)	loss 2.6830 (3.4720)	grad_norm 1.0136 (1.4590/0.4527)	mem 16099MB
[2025-01-18 02:38:26 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][40/312]	eta 0:02:19 lr 0.002990	time 0.4515 (0.5138)	model_time 0.4512 (0.4701)	loss 2.7293 (3.4158)	grad_norm 3.5695 (1.6918/0.7712)	mem 16099MB
[2025-01-18 02:38:30 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][50/312]	eta 0:02:13 lr 0.002989	time 0.4538 (0.5088)	model_time 0.4533 (0.4737)	loss 3.2924 (3.3816)	grad_norm 2.9838 (1.7930/0.7892)	mem 16099MB
[2025-01-18 02:38:35 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][60/312]	eta 0:02:07 lr 0.002989	time 0.4742 (0.5056)	model_time 0.4737 (0.4761)	loss 2.9916 (3.3997)	grad_norm 1.0215 (1.8364/0.8568)	mem 16099MB
[2025-01-18 02:38:40 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][70/312]	eta 0:02:00 lr 0.002988	time 0.4592 (0.4983)	model_time 0.4590 (0.4730)	loss 3.3428 (3.4454)	grad_norm 1.5663 (1.7313/0.8415)	mem 16099MB
[2025-01-18 02:38:45 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][80/312]	eta 0:01:54 lr 0.002987	time 0.4498 (0.4941)	model_time 0.4493 (0.4718)	loss 4.2854 (3.4723)	grad_norm 1.8590 (1.6862/0.8046)	mem 16099MB
[2025-01-18 02:38:49 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][90/312]	eta 0:01:49 lr 0.002987	time 0.4503 (0.4916)	model_time 0.4498 (0.4717)	loss 2.8251 (3.4624)	grad_norm 2.7847 (1.6988/0.7865)	mem 16099MB
[2025-01-18 02:38:54 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][100/312]	eta 0:01:43 lr 0.002986	time 0.4545 (0.4883)	model_time 0.4540 (0.4703)	loss 2.4660 (3.4301)	grad_norm 2.2530 (1.7091/0.7906)	mem 16099MB
[2025-01-18 02:38:58 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][110/312]	eta 0:01:37 lr 0.002986	time 0.4439 (0.4851)	model_time 0.4435 (0.4687)	loss 2.8147 (3.4226)	grad_norm 0.9488 (1.7039/0.7784)	mem 16099MB
[2025-01-18 02:39:03 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][120/312]	eta 0:01:32 lr 0.002985	time 0.4536 (0.4826)	model_time 0.4531 (0.4675)	loss 2.8016 (3.4135)	grad_norm 2.8602 (1.6815/0.7773)	mem 16099MB
[2025-01-18 02:39:08 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][130/312]	eta 0:01:27 lr 0.002984	time 0.4579 (0.4808)	model_time 0.4578 (0.4668)	loss 2.4545 (3.4223)	grad_norm 1.4327 (1.6824/0.7652)	mem 16099MB
[2025-01-18 02:39:13 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][140/312]	eta 0:01:22 lr 0.002984	time 0.4465 (0.4825)	model_time 0.4463 (0.4695)	loss 4.4307 (3.4379)	grad_norm 1.5089 (1.6817/0.7529)	mem 16099MB
[2025-01-18 02:39:17 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][150/312]	eta 0:01:17 lr 0.002983	time 0.5040 (0.4812)	model_time 0.5035 (0.4690)	loss 3.6043 (3.4259)	grad_norm 2.4447 (1.6575/0.7433)	mem 16099MB
[2025-01-18 02:39:22 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][160/312]	eta 0:01:13 lr 0.002983	time 0.4477 (0.4804)	model_time 0.4472 (0.4690)	loss 3.8650 (3.4267)	grad_norm 1.0814 (1.6465/0.7414)	mem 16099MB
[2025-01-18 02:39:27 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][170/312]	eta 0:01:08 lr 0.002982	time 0.4414 (0.4800)	model_time 0.4413 (0.4692)	loss 3.6927 (3.4418)	grad_norm 1.0336 (1.6241/0.7328)	mem 16099MB
[2025-01-18 02:39:31 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][180/312]	eta 0:01:03 lr 0.002982	time 0.4944 (0.4788)	model_time 0.4942 (0.4686)	loss 4.0880 (3.4311)	grad_norm 0.9707 (1.6032/0.7211)	mem 16099MB
[2025-01-18 02:39:36 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][190/312]	eta 0:00:58 lr 0.002981	time 0.5393 (0.4795)	model_time 0.5391 (0.4698)	loss 3.4656 (3.4452)	grad_norm 2.0395 (1.6001/0.7182)	mem 16099MB
[2025-01-18 02:39:41 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][200/312]	eta 0:00:53 lr 0.002980	time 0.4728 (0.4783)	model_time 0.4723 (0.4691)	loss 3.6459 (3.4464)	grad_norm 1.4958 (1.5787/0.7093)	mem 16099MB
[2025-01-18 02:39:45 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][210/312]	eta 0:00:48 lr 0.002980	time 0.4516 (0.4774)	model_time 0.4514 (0.4686)	loss 2.9984 (3.4483)	grad_norm 0.8694 (1.5646/0.7052)	mem 16099MB
[2025-01-18 02:39:50 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][220/312]	eta 0:00:43 lr 0.002979	time 0.4529 (0.4779)	model_time 0.4527 (0.4695)	loss 2.8956 (3.4433)	grad_norm 2.0937 (1.5722/0.6980)	mem 16099MB
[2025-01-18 02:39:55 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][230/312]	eta 0:00:39 lr 0.002979	time 0.4447 (0.4767)	model_time 0.4442 (0.4686)	loss 3.7459 (3.4372)	grad_norm 2.6912 (1.5831/0.6944)	mem 16099MB
[2025-01-18 02:39:59 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][240/312]	eta 0:00:34 lr 0.002978	time 0.4306 (0.4763)	model_time 0.4304 (0.4685)	loss 3.7150 (3.4421)	grad_norm 1.7074 (1.5882/0.6962)	mem 16099MB
[2025-01-18 02:40:04 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][250/312]	eta 0:00:29 lr 0.002977	time 0.4576 (0.4756)	model_time 0.4574 (0.4681)	loss 3.6331 (3.4473)	grad_norm 1.9116 (1.5929/0.6942)	mem 16099MB
[2025-01-18 02:40:09 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][260/312]	eta 0:00:24 lr 0.002977	time 0.5383 (0.4760)	model_time 0.5381 (0.4687)	loss 3.7689 (3.4563)	grad_norm 3.3011 (1.6242/0.7661)	mem 16099MB
[2025-01-18 02:40:13 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][270/312]	eta 0:00:19 lr 0.002976	time 0.5635 (0.4758)	model_time 0.5630 (0.4688)	loss 4.1809 (3.4587)	grad_norm 1.2477 (1.6123/0.7582)	mem 16099MB
[2025-01-18 02:40:18 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][280/312]	eta 0:00:15 lr 0.002976	time 0.4473 (0.4750)	model_time 0.4468 (0.4683)	loss 4.2534 (3.4632)	grad_norm 1.4451 (1.5958/0.7509)	mem 16099MB
[2025-01-18 02:40:23 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][290/312]	eta 0:00:10 lr 0.002975	time 0.4493 (0.4754)	model_time 0.4490 (0.4689)	loss 3.5003 (3.4631)	grad_norm 3.5011 (1.6054/0.7581)	mem 16099MB
[2025-01-18 02:40:28 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][300/312]	eta 0:00:05 lr 0.002975	time 0.4444 (0.4755)	model_time 0.4443 (0.4692)	loss 3.9321 (3.4606)	grad_norm 2.2941 (1.6319/0.7927)	mem 16099MB
[2025-01-18 02:40:32 internimage_t_1k_224] (main.py 510): INFO Train: [101/300][310/312]	eta 0:00:00 lr 0.002974	time 0.4379 (0.4744)	model_time 0.4377 (0.4683)	loss 4.0438 (3.4588)	grad_norm 2.0004 (1.6319/0.7936)	mem 16099MB
[2025-01-18 02:40:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 101 training takes 0:02:27
[2025-01-18 02:40:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_101.pth saving......
[2025-01-18 02:40:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_101.pth saved !!!
[2025-01-18 02:40:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.905 (7.905)	Loss 0.9274 (0.9274)	Acc@1 80.371 (80.371)	Acc@5 95.386 (95.386)	Mem 16099MB
[2025-01-18 02:40:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.053)	Loss 1.2415 (1.0688)	Acc@1 72.363 (76.953)	Acc@5 92.090 (93.925)	Mem 16099MB
[2025-01-18 02:40:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:101] * Acc@1 76.899 Acc@5 93.900
[2025-01-18 02:40:45 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.9%
[2025-01-18 02:40:45 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.97%
[2025-01-18 02:40:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.726 (8.726)	Loss 0.9163 (0.9163)	Acc@1 79.907 (79.907)	Acc@5 95.801 (95.801)	Mem 16099MB
[2025-01-18 02:40:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.169)	Loss 1.3327 (1.0892)	Acc@1 70.264 (76.582)	Acc@5 90.381 (93.441)	Mem 16099MB
[2025-01-18 02:40:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:101] * Acc@1 76.526 Acc@5 93.476
[2025-01-18 02:40:58 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 76.5%
[2025-01-18 02:40:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:41:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:41:00 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 76.53%
[2025-01-18 02:41:02 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][0/312]	eta 0:12:48 lr 0.002974	time 2.4633 (2.4633)	model_time 0.4638 (0.4638)	loss 4.1342 (4.1342)	grad_norm 0.8223 (0.8223/0.0000)	mem 16099MB
[2025-01-18 02:41:07 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][10/312]	eta 0:03:25 lr 0.002973	time 0.4570 (0.6794)	model_time 0.4563 (0.4974)	loss 3.6265 (3.5894)	grad_norm 0.8207 (1.2716/0.4217)	mem 16099MB
[2025-01-18 02:41:12 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][20/312]	eta 0:02:47 lr 0.002973	time 0.4560 (0.5729)	model_time 0.4554 (0.4774)	loss 3.9678 (3.4557)	grad_norm 2.4857 (1.4242/0.5836)	mem 16099MB
[2025-01-18 02:41:16 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][30/312]	eta 0:02:31 lr 0.002972	time 0.5484 (0.5384)	model_time 0.5479 (0.4735)	loss 2.2983 (3.3307)	grad_norm 1.7534 (1.5492/0.5705)	mem 16099MB
[2025-01-18 02:41:21 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][40/312]	eta 0:02:21 lr 0.002972	time 0.4542 (0.5205)	model_time 0.4536 (0.4714)	loss 3.4885 (3.3339)	grad_norm 1.3027 (1.5188/0.5451)	mem 16099MB
[2025-01-18 02:41:26 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][50/312]	eta 0:02:14 lr 0.002971	time 0.4497 (0.5121)	model_time 0.4495 (0.4726)	loss 3.5847 (3.3661)	grad_norm 1.0871 (1.6001/0.7706)	mem 16099MB
[2025-01-18 02:41:30 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][60/312]	eta 0:02:06 lr 0.002970	time 0.4464 (0.5039)	model_time 0.4459 (0.4708)	loss 3.7866 (3.3640)	grad_norm 0.9956 (1.5869/0.8049)	mem 16099MB
[2025-01-18 02:41:35 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][70/312]	eta 0:02:00 lr 0.002970	time 0.4586 (0.4982)	model_time 0.4585 (0.4697)	loss 2.7142 (3.3533)	grad_norm 1.9984 (1.5505/0.7600)	mem 16099MB
[2025-01-18 02:41:40 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][80/312]	eta 0:01:54 lr 0.002969	time 0.5451 (0.4944)	model_time 0.5447 (0.4693)	loss 2.7262 (3.3641)	grad_norm 1.9106 (1.5453/0.7222)	mem 16099MB
[2025-01-18 02:41:44 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][90/312]	eta 0:01:49 lr 0.002969	time 0.4543 (0.4918)	model_time 0.4539 (0.4694)	loss 3.5543 (3.3773)	grad_norm 0.7962 (1.5592/0.7491)	mem 16099MB
[2025-01-18 02:41:49 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][100/312]	eta 0:01:43 lr 0.002968	time 0.4516 (0.4879)	model_time 0.4514 (0.4677)	loss 3.6563 (3.3980)	grad_norm 1.6893 (1.5120/0.7307)	mem 16099MB
[2025-01-18 02:41:54 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][110/312]	eta 0:01:37 lr 0.002967	time 0.4574 (0.4848)	model_time 0.4569 (0.4664)	loss 2.6311 (3.4093)	grad_norm 1.0261 (1.5423/0.7437)	mem 16099MB
[2025-01-18 02:41:58 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][120/312]	eta 0:01:32 lr 0.002967	time 0.4489 (0.4821)	model_time 0.4487 (0.4652)	loss 3.8735 (3.4150)	grad_norm 1.5130 (1.5295/0.7204)	mem 16099MB
[2025-01-18 02:42:03 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][130/312]	eta 0:01:27 lr 0.002966	time 0.4548 (0.4812)	model_time 0.4544 (0.4656)	loss 3.8955 (3.4274)	grad_norm 0.8383 (1.5414/0.7603)	mem 16099MB
[2025-01-18 02:42:07 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][140/312]	eta 0:01:22 lr 0.002966	time 0.4528 (0.4805)	model_time 0.4524 (0.4659)	loss 3.5930 (3.4158)	grad_norm 1.2380 (1.5273/0.7434)	mem 16099MB
[2025-01-18 02:42:12 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][150/312]	eta 0:01:17 lr 0.002965	time 0.4743 (0.4795)	model_time 0.4738 (0.4659)	loss 3.2560 (3.4125)	grad_norm 3.5762 (1.5664/0.7918)	mem 16099MB
[2025-01-18 02:42:17 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][160/312]	eta 0:01:12 lr 0.002965	time 0.4568 (0.4787)	model_time 0.4566 (0.4659)	loss 2.5856 (3.3908)	grad_norm 0.9370 (1.5563/0.7776)	mem 16099MB
[2025-01-18 02:42:22 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][170/312]	eta 0:01:07 lr 0.002964	time 0.5801 (0.4786)	model_time 0.5796 (0.4665)	loss 2.6162 (3.3926)	grad_norm 0.8545 (1.5382/0.7654)	mem 16099MB
[2025-01-18 02:42:26 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][180/312]	eta 0:01:03 lr 0.002963	time 0.4754 (0.4786)	model_time 0.4749 (0.4672)	loss 3.8949 (3.3943)	grad_norm 1.3131 (1.5224/0.7526)	mem 16099MB
[2025-01-18 02:42:31 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][190/312]	eta 0:00:58 lr 0.002963	time 0.4326 (0.4774)	model_time 0.4322 (0.4665)	loss 2.6283 (3.3810)	grad_norm 1.4904 (1.5541/0.7899)	mem 16099MB
[2025-01-18 02:42:36 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][200/312]	eta 0:00:53 lr 0.002962	time 0.4450 (0.4782)	model_time 0.4446 (0.4678)	loss 4.0982 (3.3844)	grad_norm 1.0149 (1.5740/0.7866)	mem 16099MB
[2025-01-18 02:42:40 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][210/312]	eta 0:00:48 lr 0.002962	time 0.4465 (0.4772)	model_time 0.4463 (0.4673)	loss 2.8441 (3.3837)	grad_norm 0.7982 (1.5767/0.7804)	mem 16099MB
[2025-01-18 02:42:45 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][220/312]	eta 0:00:43 lr 0.002961	time 0.4427 (0.4768)	model_time 0.4425 (0.4674)	loss 2.6882 (3.3736)	grad_norm 1.7023 (1.5631/0.7674)	mem 16099MB
[2025-01-18 02:42:50 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][230/312]	eta 0:00:39 lr 0.002960	time 0.4597 (0.4768)	model_time 0.4592 (0.4678)	loss 3.1839 (3.3730)	grad_norm 2.9294 (1.5788/0.7632)	mem 16099MB
[2025-01-18 02:42:54 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][240/312]	eta 0:00:34 lr 0.002960	time 0.4479 (0.4760)	model_time 0.4474 (0.4673)	loss 3.7560 (3.3781)	grad_norm 1.4341 (1.5735/0.7500)	mem 16099MB
[2025-01-18 02:42:59 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][250/312]	eta 0:00:29 lr 0.002959	time 0.5387 (0.4769)	model_time 0.5382 (0.4685)	loss 3.2786 (3.3801)	grad_norm 1.3402 (1.5694/0.7426)	mem 16099MB
[2025-01-18 02:43:04 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][260/312]	eta 0:00:24 lr 0.002959	time 0.4658 (0.4762)	model_time 0.4656 (0.4681)	loss 2.3938 (3.3838)	grad_norm 1.4770 (1.5960/0.7597)	mem 16099MB
[2025-01-18 02:43:09 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][270/312]	eta 0:00:19 lr 0.002958	time 0.4461 (0.4755)	model_time 0.4459 (0.4677)	loss 3.4320 (3.3833)	grad_norm 2.2084 (1.6136/0.7679)	mem 16099MB
[2025-01-18 02:43:13 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][280/312]	eta 0:00:15 lr 0.002958	time 0.4817 (0.4752)	model_time 0.4812 (0.4677)	loss 3.7968 (3.3894)	grad_norm 0.9633 (1.6058/0.7585)	mem 16099MB
[2025-01-18 02:43:18 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][290/312]	eta 0:00:10 lr 0.002957	time 0.4558 (0.4749)	model_time 0.4553 (0.4676)	loss 3.4392 (3.3916)	grad_norm 1.4054 (1.5961/0.7482)	mem 16099MB
[2025-01-18 02:43:23 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][300/312]	eta 0:00:05 lr 0.002956	time 0.4377 (0.4745)	model_time 0.4376 (0.4674)	loss 4.0365 (3.4064)	grad_norm 2.4668 (1.5912/0.7446)	mem 16099MB
[2025-01-18 02:43:27 internimage_t_1k_224] (main.py 510): INFO Train: [102/300][310/312]	eta 0:00:00 lr 0.002956	time 0.4390 (0.4737)	model_time 0.4389 (0.4668)	loss 3.4867 (3.4031)	grad_norm 1.3047 (1.6053/0.7463)	mem 16099MB
[2025-01-18 02:43:27 internimage_t_1k_224] (main.py 519): INFO EPOCH 102 training takes 0:02:27
[2025-01-18 02:43:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_102.pth saving......
[2025-01-18 02:43:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_102.pth saved !!!
[2025-01-18 02:43:36 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.314 (7.314)	Loss 0.8885 (0.8885)	Acc@1 80.493 (80.493)	Acc@5 95.850 (95.850)	Mem 16099MB
[2025-01-18 02:43:40 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.995)	Loss 1.2720 (1.0570)	Acc@1 71.509 (76.980)	Acc@5 91.528 (93.941)	Mem 16099MB
[2025-01-18 02:43:40 internimage_t_1k_224] (main.py 575): INFO [Epoch:102] * Acc@1 76.815 Acc@5 93.932
[2025-01-18 02:43:40 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.8%
[2025-01-18 02:43:40 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 76.97%
[2025-01-18 02:43:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.371 (8.371)	Loss 0.9097 (0.9097)	Acc@1 80.054 (80.054)	Acc@5 95.825 (95.825)	Mem 16099MB
[2025-01-18 02:43:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.113)	Loss 1.3222 (1.0811)	Acc@1 70.459 (76.733)	Acc@5 90.430 (93.517)	Mem 16099MB
[2025-01-18 02:43:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:102] * Acc@1 76.671 Acc@5 93.556
[2025-01-18 02:43:52 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 76.7%
[2025-01-18 02:43:52 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:43:53 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:43:53 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 76.67%
[2025-01-18 02:43:56 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][0/312]	eta 0:15:05 lr 0.002956	time 2.9025 (2.9025)	model_time 0.5137 (0.5137)	loss 4.3599 (4.3599)	grad_norm 1.7403 (1.7403/0.0000)	mem 16099MB
[2025-01-18 02:44:01 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][10/312]	eta 0:03:23 lr 0.002955	time 0.4476 (0.6734)	model_time 0.4471 (0.4558)	loss 4.0550 (3.6544)	grad_norm 1.4451 (1.5680/0.4751)	mem 16099MB
[2025-01-18 02:44:06 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][20/312]	eta 0:02:47 lr 0.002954	time 0.4529 (0.5748)	model_time 0.4527 (0.4606)	loss 2.8182 (3.5699)	grad_norm 1.3232 (1.5156/0.4377)	mem 16099MB
[2025-01-18 02:44:10 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][30/312]	eta 0:02:32 lr 0.002954	time 0.4417 (0.5396)	model_time 0.4415 (0.4622)	loss 3.7477 (3.5849)	grad_norm 1.2383 (1.5324/0.4811)	mem 16099MB
[2025-01-18 02:44:15 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][40/312]	eta 0:02:21 lr 0.002953	time 0.4777 (0.5189)	model_time 0.4772 (0.4603)	loss 3.6942 (3.5521)	grad_norm 1.3403 (1.5310/0.4996)	mem 16099MB
[2025-01-18 02:44:19 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][50/312]	eta 0:02:13 lr 0.002953	time 0.4506 (0.5080)	model_time 0.4504 (0.4607)	loss 3.5947 (3.5484)	grad_norm 0.9514 (1.4983/0.5084)	mem 16099MB
[2025-01-18 02:44:24 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][60/312]	eta 0:02:06 lr 0.002952	time 0.4679 (0.5004)	model_time 0.4674 (0.4608)	loss 3.6562 (3.5488)	grad_norm 1.0801 (1.4548/0.4908)	mem 16099MB
[2025-01-18 02:44:29 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][70/312]	eta 0:02:00 lr 0.002952	time 0.4691 (0.4998)	model_time 0.4689 (0.4657)	loss 3.1665 (3.5239)	grad_norm 2.1626 (1.5621/0.5708)	mem 16099MB
[2025-01-18 02:44:34 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][80/312]	eta 0:01:54 lr 0.002951	time 0.4441 (0.4949)	model_time 0.4439 (0.4650)	loss 2.9504 (3.5305)	grad_norm 1.3628 (1.5996/0.6210)	mem 16099MB
[2025-01-18 02:44:38 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][90/312]	eta 0:01:49 lr 0.002950	time 0.4482 (0.4942)	model_time 0.4480 (0.4675)	loss 4.1864 (3.5237)	grad_norm 1.9650 (1.6697/0.7480)	mem 16099MB
[2025-01-18 02:44:43 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][100/312]	eta 0:01:44 lr 0.002950	time 0.4503 (0.4910)	model_time 0.4501 (0.4670)	loss 2.6646 (3.4879)	grad_norm 1.7904 (1.6619/0.7301)	mem 16099MB
[2025-01-18 02:44:48 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][110/312]	eta 0:01:38 lr 0.002949	time 0.4516 (0.4884)	model_time 0.4511 (0.4665)	loss 2.1298 (3.4890)	grad_norm 1.6953 (1.6340/0.7087)	mem 16099MB
[2025-01-18 02:44:52 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][120/312]	eta 0:01:33 lr 0.002949	time 0.5469 (0.4868)	model_time 0.5467 (0.4666)	loss 2.4941 (3.4760)	grad_norm 1.6702 (1.6569/0.7026)	mem 16099MB
[2025-01-18 02:44:57 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][130/312]	eta 0:01:28 lr 0.002948	time 0.5425 (0.4849)	model_time 0.5421 (0.4662)	loss 2.4167 (3.4757)	grad_norm 1.0426 (1.6334/0.6848)	mem 16099MB
[2025-01-18 02:45:02 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][140/312]	eta 0:01:23 lr 0.002947	time 0.4441 (0.4845)	model_time 0.4436 (0.4671)	loss 3.9759 (3.4757)	grad_norm 1.2577 (1.6108/0.6759)	mem 16099MB
[2025-01-18 02:45:06 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][150/312]	eta 0:01:18 lr 0.002947	time 0.4560 (0.4825)	model_time 0.4558 (0.4663)	loss 2.8751 (3.4711)	grad_norm 1.1692 (1.5828/0.6669)	mem 16099MB
[2025-01-18 02:45:11 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][160/312]	eta 0:01:13 lr 0.002946	time 0.4543 (0.4826)	model_time 0.4539 (0.4673)	loss 4.0405 (3.4668)	grad_norm 1.4036 (1.6103/0.6934)	mem 16099MB
[2025-01-18 02:45:16 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][170/312]	eta 0:01:08 lr 0.002946	time 0.4596 (0.4813)	model_time 0.4594 (0.4669)	loss 3.6840 (3.4773)	grad_norm 1.5817 (1.6016/0.6823)	mem 16099MB
[2025-01-18 02:45:20 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][180/312]	eta 0:01:03 lr 0.002945	time 0.4554 (0.4799)	model_time 0.4552 (0.4663)	loss 3.6063 (3.4840)	grad_norm 2.9591 (1.6186/0.6801)	mem 16099MB
[2025-01-18 02:45:25 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][190/312]	eta 0:00:58 lr 0.002945	time 0.4803 (0.4786)	model_time 0.4802 (0.4657)	loss 3.4850 (3.4819)	grad_norm 2.4948 (1.6299/0.6856)	mem 16099MB
[2025-01-18 02:45:30 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][200/312]	eta 0:00:53 lr 0.002944	time 0.4663 (0.4780)	model_time 0.4659 (0.4657)	loss 2.9255 (3.4873)	grad_norm 1.0889 (1.6214/0.6777)	mem 16099MB
[2025-01-18 02:45:34 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][210/312]	eta 0:00:48 lr 0.002943	time 0.4447 (0.4767)	model_time 0.4446 (0.4650)	loss 4.2324 (3.5028)	grad_norm 0.8356 (1.5993/0.6721)	mem 16099MB
[2025-01-18 02:45:39 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][220/312]	eta 0:00:43 lr 0.002943	time 0.4575 (0.4760)	model_time 0.4573 (0.4648)	loss 2.6918 (3.4916)	grad_norm 2.2502 (1.6192/0.7015)	mem 16099MB
[2025-01-18 02:45:43 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][230/312]	eta 0:00:38 lr 0.002942	time 0.4496 (0.4750)	model_time 0.4492 (0.4642)	loss 2.5907 (3.4779)	grad_norm 0.9817 (1.6055/0.6957)	mem 16099MB
[2025-01-18 02:45:48 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][240/312]	eta 0:00:34 lr 0.002942	time 0.4535 (0.4758)	model_time 0.4534 (0.4655)	loss 3.2382 (3.4756)	grad_norm 2.9703 (1.6021/0.6900)	mem 16099MB
[2025-01-18 02:45:53 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][250/312]	eta 0:00:29 lr 0.002941	time 0.4479 (0.4750)	model_time 0.4475 (0.4650)	loss 4.1480 (3.4803)	grad_norm 2.1029 (1.6155/0.7169)	mem 16099MB
[2025-01-18 02:45:57 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][260/312]	eta 0:00:24 lr 0.002940	time 0.4496 (0.4747)	model_time 0.4491 (0.4651)	loss 3.5581 (3.4797)	grad_norm 1.1396 (1.5969/0.7103)	mem 16099MB
[2025-01-18 02:46:02 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][270/312]	eta 0:00:19 lr 0.002940	time 0.4547 (0.4753)	model_time 0.4545 (0.4661)	loss 3.7451 (3.4820)	grad_norm 1.2834 (1.5833/0.7012)	mem 16099MB
[2025-01-18 02:46:07 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][280/312]	eta 0:00:15 lr 0.002939	time 0.4638 (0.4747)	model_time 0.4636 (0.4658)	loss 3.5613 (3.4747)	grad_norm 0.9267 (1.5778/0.6929)	mem 16099MB
[2025-01-18 02:46:11 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][290/312]	eta 0:00:10 lr 0.002939	time 0.4534 (0.4740)	model_time 0.4530 (0.4654)	loss 3.6855 (3.4744)	grad_norm 1.6647 (1.5902/0.6895)	mem 16099MB
[2025-01-18 02:46:16 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][300/312]	eta 0:00:05 lr 0.002938	time 0.4374 (0.4735)	model_time 0.4373 (0.4651)	loss 3.4776 (3.4699)	grad_norm 1.2005 (1.6050/0.7073)	mem 16099MB
[2025-01-18 02:46:21 internimage_t_1k_224] (main.py 510): INFO Train: [103/300][310/312]	eta 0:00:00 lr 0.002937	time 0.4415 (0.4735)	model_time 0.4413 (0.4654)	loss 2.6875 (3.4772)	grad_norm 0.9473 (1.5946/0.7079)	mem 16099MB
[2025-01-18 02:46:21 internimage_t_1k_224] (main.py 519): INFO EPOCH 103 training takes 0:02:27
[2025-01-18 02:46:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_103.pth saving......
[2025-01-18 02:46:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_103.pth saved !!!
[2025-01-18 02:46:30 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.398 (7.398)	Loss 0.8941 (0.8941)	Acc@1 80.249 (80.249)	Acc@5 95.825 (95.825)	Mem 16099MB
[2025-01-18 02:46:33 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.996)	Loss 1.2556 (1.0609)	Acc@1 71.973 (77.162)	Acc@5 91.162 (93.923)	Mem 16099MB
[2025-01-18 02:46:33 internimage_t_1k_224] (main.py 575): INFO [Epoch:103] * Acc@1 77.099 Acc@5 93.978
[2025-01-18 02:46:33 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.1%
[2025-01-18 02:46:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 02:46:35 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 02:46:35 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.10%
[2025-01-18 02:46:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.482 (7.482)	Loss 0.9034 (0.9034)	Acc@1 80.200 (80.200)	Acc@5 95.947 (95.947)	Mem 16099MB
[2025-01-18 02:46:46 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.979)	Loss 1.3117 (1.0731)	Acc@1 70.752 (76.900)	Acc@5 90.674 (93.601)	Mem 16099MB
[2025-01-18 02:46:46 internimage_t_1k_224] (main.py 575): INFO [Epoch:103] * Acc@1 76.823 Acc@5 93.648
[2025-01-18 02:46:46 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 76.8%
[2025-01-18 02:46:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:46:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:46:47 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 76.82%
[2025-01-18 02:46:50 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][0/312]	eta 0:13:41 lr 0.002937	time 2.6318 (2.6318)	model_time 0.4548 (0.4548)	loss 2.9951 (2.9951)	grad_norm 0.9072 (0.9072/0.0000)	mem 16099MB
[2025-01-18 02:46:54 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][10/312]	eta 0:03:18 lr 0.002937	time 0.4471 (0.6583)	model_time 0.4469 (0.4601)	loss 3.8514 (3.2778)	grad_norm 1.2925 (1.2471/0.2506)	mem 16099MB
[2025-01-18 02:46:59 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][20/312]	eta 0:02:46 lr 0.002936	time 0.5433 (0.5707)	model_time 0.5431 (0.4667)	loss 3.1349 (3.3776)	grad_norm 2.1143 (1.4134/0.4191)	mem 16099MB
[2025-01-18 02:47:04 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][30/312]	eta 0:02:30 lr 0.002936	time 0.4566 (0.5350)	model_time 0.4564 (0.4644)	loss 3.6001 (3.3728)	grad_norm 0.9161 (1.5112/0.5590)	mem 16099MB
[2025-01-18 02:47:08 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][40/312]	eta 0:02:20 lr 0.002935	time 0.4530 (0.5175)	model_time 0.4525 (0.4641)	loss 2.8254 (3.3330)	grad_norm 1.4043 (1.5940/0.6057)	mem 16099MB
[2025-01-18 02:47:13 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][50/312]	eta 0:02:13 lr 0.002934	time 0.4505 (0.5081)	model_time 0.4501 (0.4651)	loss 2.7942 (3.3121)	grad_norm 1.1468 (1.5619/0.6020)	mem 16099MB
[2025-01-18 02:47:18 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][60/312]	eta 0:02:07 lr 0.002934	time 0.5337 (0.5040)	model_time 0.5335 (0.4680)	loss 2.8382 (3.3442)	grad_norm 1.8708 (1.5834/0.5794)	mem 16099MB
[2025-01-18 02:47:22 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][70/312]	eta 0:02:00 lr 0.002933	time 0.4645 (0.4965)	model_time 0.4644 (0.4655)	loss 3.3623 (3.3448)	grad_norm 1.0466 (1.6646/0.6631)	mem 16099MB
[2025-01-18 02:47:27 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][80/312]	eta 0:01:54 lr 0.002933	time 0.4461 (0.4928)	model_time 0.4459 (0.4655)	loss 2.9973 (3.3416)	grad_norm 1.4712 (1.7176/0.7537)	mem 16099MB
[2025-01-18 02:47:32 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][90/312]	eta 0:01:48 lr 0.002932	time 0.4342 (0.4898)	model_time 0.4340 (0.4655)	loss 4.0418 (3.3419)	grad_norm 0.6909 (1.6673/0.7352)	mem 16099MB
[2025-01-18 02:47:36 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][100/312]	eta 0:01:43 lr 0.002931	time 0.6351 (0.4889)	model_time 0.6346 (0.4669)	loss 3.2877 (3.3266)	grad_norm 0.7472 (1.6011/0.7285)	mem 16099MB
[2025-01-18 02:47:41 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][110/312]	eta 0:01:38 lr 0.002931	time 0.5523 (0.4869)	model_time 0.5519 (0.4669)	loss 2.0701 (3.3064)	grad_norm 1.1686 (1.5812/0.7132)	mem 16099MB
[2025-01-18 02:47:46 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][120/312]	eta 0:01:33 lr 0.002930	time 0.4333 (0.4866)	model_time 0.4331 (0.4682)	loss 3.7319 (3.3348)	grad_norm 3.0097 (1.6161/0.7430)	mem 16099MB
[2025-01-18 02:47:51 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][130/312]	eta 0:01:28 lr 0.002930	time 0.4385 (0.4860)	model_time 0.4380 (0.4689)	loss 3.5989 (3.3555)	grad_norm 1.3142 (1.6127/0.7411)	mem 16099MB
[2025-01-18 02:47:55 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][140/312]	eta 0:01:23 lr 0.002929	time 0.5632 (0.4855)	model_time 0.5627 (0.4696)	loss 3.6480 (3.3639)	grad_norm 0.9615 (1.6149/0.7316)	mem 16099MB
[2025-01-18 02:48:00 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][150/312]	eta 0:01:18 lr 0.002928	time 0.4559 (0.4841)	model_time 0.4557 (0.4693)	loss 2.9974 (3.3573)	grad_norm 1.1486 (1.6076/0.7275)	mem 16099MB
[2025-01-18 02:48:05 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][160/312]	eta 0:01:13 lr 0.002928	time 0.4500 (0.4829)	model_time 0.4495 (0.4689)	loss 3.3043 (3.3504)	grad_norm 0.9321 (1.6034/0.7094)	mem 16099MB
[2025-01-18 02:48:09 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][170/312]	eta 0:01:08 lr 0.002927	time 0.4592 (0.4820)	model_time 0.4587 (0.4688)	loss 2.3713 (3.3486)	grad_norm 1.3462 (1.5927/0.7008)	mem 16099MB
[2025-01-18 02:48:14 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][180/312]	eta 0:01:03 lr 0.002927	time 0.4407 (0.4804)	model_time 0.4402 (0.4680)	loss 2.5920 (3.3492)	grad_norm 1.5400 (1.5904/0.6845)	mem 16099MB
[2025-01-18 02:48:19 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][190/312]	eta 0:00:58 lr 0.002926	time 0.4529 (0.4795)	model_time 0.4523 (0.4676)	loss 3.9251 (3.3685)	grad_norm 1.3919 (1.6074/0.7121)	mem 16099MB
[2025-01-18 02:48:23 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][200/312]	eta 0:00:53 lr 0.002926	time 0.4437 (0.4785)	model_time 0.4432 (0.4672)	loss 3.4976 (3.3740)	grad_norm 1.3624 (1.6439/0.7634)	mem 16099MB
[2025-01-18 02:48:28 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][210/312]	eta 0:00:48 lr 0.002925	time 0.4451 (0.4779)	model_time 0.4446 (0.4672)	loss 3.4467 (3.3662)	grad_norm 1.6538 (1.6620/0.7712)	mem 16099MB
[2025-01-18 02:48:32 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][220/312]	eta 0:00:43 lr 0.002924	time 0.4503 (0.4768)	model_time 0.4502 (0.4665)	loss 3.4723 (3.3678)	grad_norm 1.2613 (1.6453/0.7595)	mem 16099MB
[2025-01-18 02:48:37 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][230/312]	eta 0:00:39 lr 0.002924	time 0.4499 (0.4761)	model_time 0.4495 (0.4662)	loss 3.7388 (3.3697)	grad_norm 2.5416 (1.6429/0.7571)	mem 16099MB
[2025-01-18 02:48:42 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][240/312]	eta 0:00:34 lr 0.002923	time 0.4621 (0.4755)	model_time 0.4619 (0.4660)	loss 2.3971 (3.3713)	grad_norm 1.1029 (1.6431/0.7529)	mem 16099MB
[2025-01-18 02:48:46 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][250/312]	eta 0:00:29 lr 0.002923	time 0.4493 (0.4749)	model_time 0.4489 (0.4658)	loss 2.2697 (3.3667)	grad_norm 2.2520 (1.6316/0.7434)	mem 16099MB
[2025-01-18 02:48:51 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][260/312]	eta 0:00:24 lr 0.002922	time 0.4495 (0.4741)	model_time 0.4491 (0.4654)	loss 3.8594 (3.3654)	grad_norm 1.0242 (1.6152/0.7368)	mem 16099MB
[2025-01-18 02:48:55 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][270/312]	eta 0:00:19 lr 0.002921	time 0.4488 (0.4735)	model_time 0.4484 (0.4650)	loss 3.3057 (3.3738)	grad_norm 1.1077 (1.5969/0.7310)	mem 16099MB
[2025-01-18 02:49:00 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][280/312]	eta 0:00:15 lr 0.002921	time 0.4442 (0.4734)	model_time 0.4441 (0.4653)	loss 3.7662 (3.3833)	grad_norm 2.5281 (1.6281/0.7676)	mem 16099MB
[2025-01-18 02:49:05 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][290/312]	eta 0:00:10 lr 0.002920	time 0.5908 (0.4741)	model_time 0.5906 (0.4662)	loss 2.0001 (3.3865)	grad_norm 1.6819 (1.6208/0.7601)	mem 16099MB
[2025-01-18 02:49:09 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][300/312]	eta 0:00:05 lr 0.002920	time 0.4412 (0.4733)	model_time 0.4411 (0.4656)	loss 3.0549 (3.3844)	grad_norm 1.6283 (1.6295/0.7676)	mem 16099MB
[2025-01-18 02:49:14 internimage_t_1k_224] (main.py 510): INFO Train: [104/300][310/312]	eta 0:00:00 lr 0.002919	time 0.4383 (0.4728)	model_time 0.4382 (0.4654)	loss 3.5333 (3.3826)	grad_norm 1.3265 (1.6416/0.7752)	mem 16099MB
[2025-01-18 02:49:14 internimage_t_1k_224] (main.py 519): INFO EPOCH 104 training takes 0:02:27
[2025-01-18 02:49:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_104.pth saving......
[2025-01-18 02:49:16 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_104.pth saved !!!
[2025-01-18 02:49:23 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.295 (7.295)	Loss 0.9218 (0.9218)	Acc@1 80.176 (80.176)	Acc@5 95.874 (95.874)	Mem 16099MB
[2025-01-18 02:49:27 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.989)	Loss 1.3161 (1.0859)	Acc@1 71.460 (77.128)	Acc@5 91.699 (94.041)	Mem 16099MB
[2025-01-18 02:49:27 internimage_t_1k_224] (main.py 575): INFO [Epoch:104] * Acc@1 77.095 Acc@5 94.084
[2025-01-18 02:49:27 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.1%
[2025-01-18 02:49:27 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.10%
[2025-01-18 02:49:35 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.097 (8.097)	Loss 0.8976 (0.8976)	Acc@1 80.298 (80.298)	Acc@5 95.972 (95.972)	Mem 16099MB
[2025-01-18 02:49:39 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.092)	Loss 1.3023 (1.0657)	Acc@1 70.996 (77.064)	Acc@5 90.869 (93.688)	Mem 16099MB
[2025-01-18 02:49:39 internimage_t_1k_224] (main.py 575): INFO [Epoch:104] * Acc@1 76.985 Acc@5 93.728
[2025-01-18 02:49:39 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 77.0%
[2025-01-18 02:49:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:49:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:49:40 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 76.99%
[2025-01-18 02:49:42 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][0/312]	eta 0:10:23 lr 0.002919	time 1.9991 (1.9991)	model_time 0.4648 (0.4648)	loss 2.1274 (2.1274)	grad_norm 2.4427 (2.4427/0.0000)	mem 16099MB
[2025-01-18 02:49:47 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][10/312]	eta 0:03:04 lr 0.002918	time 0.5345 (0.6104)	model_time 0.5342 (0.4706)	loss 3.6828 (3.3364)	grad_norm 1.2711 (1.7110/0.6565)	mem 16099MB
[2025-01-18 02:49:51 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][20/312]	eta 0:02:36 lr 0.002918	time 0.4450 (0.5376)	model_time 0.4446 (0.4642)	loss 3.5984 (3.3962)	grad_norm 1.9953 (1.6073/0.7013)	mem 16099MB
[2025-01-18 02:49:56 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][30/312]	eta 0:02:26 lr 0.002917	time 0.4631 (0.5192)	model_time 0.4627 (0.4693)	loss 3.4786 (3.4272)	grad_norm 3.0879 (1.7958/0.8340)	mem 16099MB
[2025-01-18 02:50:01 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][40/312]	eta 0:02:18 lr 0.002917	time 0.4614 (0.5093)	model_time 0.4612 (0.4715)	loss 3.5132 (3.4246)	grad_norm 1.4240 (1.7132/0.7923)	mem 16099MB
[2025-01-18 02:50:06 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][50/312]	eta 0:02:10 lr 0.002916	time 0.4469 (0.4997)	model_time 0.4468 (0.4692)	loss 3.6542 (3.4134)	grad_norm 1.0328 (1.6622/0.7525)	mem 16099MB
[2025-01-18 02:50:10 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][60/312]	eta 0:02:04 lr 0.002915	time 0.4639 (0.4938)	model_time 0.4637 (0.4683)	loss 3.5025 (3.4426)	grad_norm 1.0100 (1.6108/0.7160)	mem 16099MB
[2025-01-18 02:50:15 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][70/312]	eta 0:01:58 lr 0.002915	time 0.4530 (0.4883)	model_time 0.4525 (0.4663)	loss 3.5265 (3.4946)	grad_norm 2.0828 (1.6429/0.7279)	mem 16099MB
[2025-01-18 02:50:19 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][80/312]	eta 0:01:52 lr 0.002914	time 0.4443 (0.4837)	model_time 0.4441 (0.4644)	loss 2.5207 (3.4641)	grad_norm 1.5918 (1.6329/0.6975)	mem 16099MB
[2025-01-18 02:50:24 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][90/312]	eta 0:01:47 lr 0.002914	time 0.5318 (0.4830)	model_time 0.5313 (0.4657)	loss 4.5056 (3.5104)	grad_norm 2.3619 (1.6543/0.7462)	mem 16099MB
[2025-01-18 02:50:29 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][100/312]	eta 0:01:42 lr 0.002913	time 0.4497 (0.4814)	model_time 0.4493 (0.4658)	loss 4.0217 (3.5126)	grad_norm 1.7570 (1.6112/0.7290)	mem 16099MB
[2025-01-18 02:50:33 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][110/312]	eta 0:01:36 lr 0.002912	time 0.4441 (0.4796)	model_time 0.4439 (0.4653)	loss 3.3534 (3.5000)	grad_norm 2.2863 (1.6250/0.7425)	mem 16099MB
[2025-01-18 02:50:38 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][120/312]	eta 0:01:31 lr 0.002912	time 0.4615 (0.4787)	model_time 0.4611 (0.4656)	loss 2.2228 (3.4708)	grad_norm 2.1539 (1.6102/0.7336)	mem 16099MB
[2025-01-18 02:50:43 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][130/312]	eta 0:01:26 lr 0.002911	time 0.4407 (0.4772)	model_time 0.4405 (0.4651)	loss 4.4382 (3.4565)	grad_norm 1.5991 (1.6102/0.7137)	mem 16099MB
[2025-01-18 02:50:47 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][140/312]	eta 0:01:21 lr 0.002911	time 0.4465 (0.4760)	model_time 0.4460 (0.4647)	loss 2.7002 (3.4434)	grad_norm 1.5798 (1.6138/0.7005)	mem 16099MB
[2025-01-18 02:50:52 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][150/312]	eta 0:01:16 lr 0.002910	time 0.4500 (0.4745)	model_time 0.4495 (0.4639)	loss 4.3155 (3.4492)	grad_norm 1.0550 (1.6265/0.7261)	mem 16099MB
[2025-01-18 02:50:56 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][160/312]	eta 0:01:11 lr 0.002909	time 0.4528 (0.4732)	model_time 0.4522 (0.4633)	loss 3.6784 (3.4467)	grad_norm 1.5345 (1.6455/0.7339)	mem 16099MB
[2025-01-18 02:51:01 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][170/312]	eta 0:01:07 lr 0.002909	time 0.4454 (0.4726)	model_time 0.4452 (0.4632)	loss 4.4883 (3.4406)	grad_norm 1.0583 (1.6509/0.7377)	mem 16099MB
[2025-01-18 02:51:06 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][180/312]	eta 0:01:02 lr 0.002908	time 0.4459 (0.4719)	model_time 0.4454 (0.4630)	loss 3.4978 (3.4604)	grad_norm 1.4741 (1.6489/0.7272)	mem 16099MB
[2025-01-18 02:51:10 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][190/312]	eta 0:00:57 lr 0.002908	time 0.4530 (0.4708)	model_time 0.4526 (0.4623)	loss 3.0328 (3.4562)	grad_norm 1.3939 (1.6271/0.7172)	mem 16099MB
[2025-01-18 02:51:15 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][200/312]	eta 0:00:52 lr 0.002907	time 0.4517 (0.4704)	model_time 0.4512 (0.4623)	loss 3.8493 (3.4435)	grad_norm 1.2622 (1.6249/0.7071)	mem 16099MB
[2025-01-18 02:51:20 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][210/312]	eta 0:00:48 lr 0.002906	time 0.5531 (0.4708)	model_time 0.5526 (0.4631)	loss 4.1510 (3.4416)	grad_norm 1.0975 (1.6082/0.6971)	mem 16099MB
[2025-01-18 02:51:24 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][220/312]	eta 0:00:43 lr 0.002906	time 0.4551 (0.4699)	model_time 0.4546 (0.4626)	loss 3.4688 (3.4321)	grad_norm 3.3336 (1.6182/0.7069)	mem 16099MB
[2025-01-18 02:51:29 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][230/312]	eta 0:00:38 lr 0.002905	time 0.4512 (0.4696)	model_time 0.4510 (0.4625)	loss 3.4209 (3.4263)	grad_norm 1.7648 (1.6276/0.6999)	mem 16099MB
[2025-01-18 02:51:33 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][240/312]	eta 0:00:33 lr 0.002905	time 0.4613 (0.4693)	model_time 0.4611 (0.4626)	loss 3.6914 (3.4191)	grad_norm 1.1848 (1.6159/0.6894)	mem 16099MB
[2025-01-18 02:51:38 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][250/312]	eta 0:00:29 lr 0.002904	time 0.4494 (0.4688)	model_time 0.4489 (0.4622)	loss 3.2773 (3.4305)	grad_norm 1.6793 (1.6262/0.6862)	mem 16099MB
[2025-01-18 02:51:42 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][260/312]	eta 0:00:24 lr 0.002903	time 0.4414 (0.4686)	model_time 0.4413 (0.4623)	loss 4.2342 (3.4257)	grad_norm 1.2416 (1.6284/0.6870)	mem 16099MB
[2025-01-18 02:51:47 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][270/312]	eta 0:00:19 lr 0.002903	time 0.4395 (0.4687)	model_time 0.4390 (0.4626)	loss 3.7209 (3.4355)	grad_norm 0.7788 (1.6222/0.6814)	mem 16099MB
[2025-01-18 02:51:52 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][280/312]	eta 0:00:14 lr 0.002902	time 0.4459 (0.4687)	model_time 0.4457 (0.4628)	loss 3.7004 (3.4343)	grad_norm 0.8552 (1.6194/0.6785)	mem 16099MB
[2025-01-18 02:51:56 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][290/312]	eta 0:00:10 lr 0.002902	time 0.4559 (0.4684)	model_time 0.4557 (0.4627)	loss 4.5287 (3.4474)	grad_norm 2.1318 (1.6170/0.6755)	mem 16099MB
[2025-01-18 02:52:01 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][300/312]	eta 0:00:05 lr 0.002901	time 0.4394 (0.4683)	model_time 0.4393 (0.4628)	loss 4.1726 (3.4562)	grad_norm 1.5031 (1.6124/0.6734)	mem 16099MB
[2025-01-18 02:52:06 internimage_t_1k_224] (main.py 510): INFO Train: [105/300][310/312]	eta 0:00:00 lr 0.002900	time 0.4421 (0.4675)	model_time 0.4420 (0.4621)	loss 2.9024 (3.4425)	grad_norm 0.7843 (1.6078/0.6688)	mem 16099MB
[2025-01-18 02:52:06 internimage_t_1k_224] (main.py 519): INFO EPOCH 105 training takes 0:02:25
[2025-01-18 02:52:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_105.pth saving......
[2025-01-18 02:52:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_105.pth saved !!!
[2025-01-18 02:52:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.081 (7.081)	Loss 0.9446 (0.9446)	Acc@1 80.444 (80.444)	Acc@5 96.045 (96.045)	Mem 16099MB
[2025-01-18 02:52:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.972)	Loss 1.2446 (1.0675)	Acc@1 72.583 (77.293)	Acc@5 92.114 (94.189)	Mem 16099MB
[2025-01-18 02:52:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:105] * Acc@1 77.261 Acc@5 94.248
[2025-01-18 02:52:18 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.3%
[2025-01-18 02:52:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 02:52:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 02:52:20 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.26%
[2025-01-18 02:52:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.410 (7.410)	Loss 0.8916 (0.8916)	Acc@1 80.444 (80.444)	Acc@5 96.045 (96.045)	Mem 16099MB
[2025-01-18 02:52:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.023)	Loss 1.2940 (1.0591)	Acc@1 71.216 (77.144)	Acc@5 90.991 (93.786)	Mem 16099MB
[2025-01-18 02:52:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:105] * Acc@1 77.069 Acc@5 93.824
[2025-01-18 02:52:31 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 77.1%
[2025-01-18 02:52:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:52:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:52:32 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 77.07%
[2025-01-18 02:52:34 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][0/312]	eta 0:11:40 lr 0.002900	time 2.2443 (2.2443)	model_time 0.4580 (0.4580)	loss 2.7516 (2.7516)	grad_norm 0.9484 (0.9484/0.0000)	mem 16099MB
[2025-01-18 02:52:39 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][10/312]	eta 0:03:11 lr 0.002900	time 0.4542 (0.6356)	model_time 0.4540 (0.4729)	loss 3.1587 (3.4577)	grad_norm 1.8040 (1.3406/0.2972)	mem 16099MB
[2025-01-18 02:52:44 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][20/312]	eta 0:02:44 lr 0.002899	time 0.4468 (0.5628)	model_time 0.4466 (0.4773)	loss 3.3520 (3.4998)	grad_norm 1.2714 (1.4078/0.4283)	mem 16099MB
[2025-01-18 02:52:49 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][30/312]	eta 0:02:30 lr 0.002899	time 0.4477 (0.5325)	model_time 0.4472 (0.4745)	loss 3.1234 (3.4684)	grad_norm 2.7581 (1.5611/0.6236)	mem 16099MB
[2025-01-18 02:52:53 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][40/312]	eta 0:02:20 lr 0.002898	time 0.4460 (0.5181)	model_time 0.4457 (0.4742)	loss 4.0856 (3.5443)	grad_norm 1.2220 (1.5850/0.6241)	mem 16099MB
[2025-01-18 02:52:58 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][50/312]	eta 0:02:12 lr 0.002897	time 0.4601 (0.5058)	model_time 0.4599 (0.4704)	loss 3.6639 (3.5185)	grad_norm 1.0266 (1.6432/0.6940)	mem 16099MB
[2025-01-18 02:53:03 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][60/312]	eta 0:02:05 lr 0.002897	time 0.4540 (0.4992)	model_time 0.4538 (0.4696)	loss 3.2819 (3.4841)	grad_norm 1.4203 (1.5766/0.6766)	mem 16099MB
[2025-01-18 02:53:07 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][70/312]	eta 0:01:59 lr 0.002896	time 0.4415 (0.4942)	model_time 0.4410 (0.4687)	loss 2.2571 (3.4094)	grad_norm 1.9063 (1.5204/0.6515)	mem 16099MB
[2025-01-18 02:53:12 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][80/312]	eta 0:01:53 lr 0.002896	time 0.4529 (0.4895)	model_time 0.4527 (0.4671)	loss 3.7257 (3.3797)	grad_norm 1.3469 (1.4992/0.6192)	mem 16099MB
[2025-01-18 02:53:16 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][90/312]	eta 0:01:48 lr 0.002895	time 0.4537 (0.4869)	model_time 0.4533 (0.4669)	loss 3.5954 (3.3975)	grad_norm 2.2394 (1.4851/0.6101)	mem 16099MB
[2025-01-18 02:53:21 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][100/312]	eta 0:01:42 lr 0.002894	time 0.4595 (0.4838)	model_time 0.4593 (0.4658)	loss 2.5267 (3.4026)	grad_norm 2.2484 (1.5238/0.6425)	mem 16099MB
[2025-01-18 02:53:26 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][110/312]	eta 0:01:37 lr 0.002894	time 0.4441 (0.4811)	model_time 0.4436 (0.4647)	loss 4.0996 (3.3983)	grad_norm 2.8660 (1.5750/0.6755)	mem 16099MB
[2025-01-18 02:53:30 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][120/312]	eta 0:01:32 lr 0.002893	time 0.4515 (0.4796)	model_time 0.4513 (0.4645)	loss 3.6204 (3.4053)	grad_norm 1.5284 (1.6283/0.7556)	mem 16099MB
[2025-01-18 02:53:35 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][130/312]	eta 0:01:27 lr 0.002893	time 0.4350 (0.4795)	model_time 0.4345 (0.4655)	loss 3.2306 (3.4007)	grad_norm 1.4599 (1.5937/0.7419)	mem 16099MB
[2025-01-18 02:53:40 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][140/312]	eta 0:01:22 lr 0.002892	time 0.4485 (0.4782)	model_time 0.4480 (0.4652)	loss 2.9440 (3.3889)	grad_norm 1.8916 (1.5813/0.7284)	mem 16099MB
[2025-01-18 02:53:44 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][150/312]	eta 0:01:17 lr 0.002891	time 0.5167 (0.4778)	model_time 0.5165 (0.4656)	loss 2.8079 (3.3713)	grad_norm 2.8795 (1.5902/0.7306)	mem 16099MB
[2025-01-18 02:53:49 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][160/312]	eta 0:01:12 lr 0.002891	time 0.4461 (0.4781)	model_time 0.4456 (0.4666)	loss 3.3592 (3.3764)	grad_norm 0.8408 (1.5668/0.7284)	mem 16099MB
[2025-01-18 02:53:54 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][170/312]	eta 0:01:07 lr 0.002890	time 0.4582 (0.4768)	model_time 0.4580 (0.4660)	loss 4.0226 (3.3999)	grad_norm 1.6561 (1.5466/0.7152)	mem 16099MB
[2025-01-18 02:53:58 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][180/312]	eta 0:01:02 lr 0.002890	time 0.4705 (0.4769)	model_time 0.4700 (0.4667)	loss 3.6243 (3.3906)	grad_norm 2.1149 (1.5564/0.6998)	mem 16099MB
[2025-01-18 02:54:03 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][190/312]	eta 0:00:58 lr 0.002889	time 0.4452 (0.4758)	model_time 0.4450 (0.4661)	loss 3.7812 (3.3960)	grad_norm 3.4741 (1.5572/0.7006)	mem 16099MB
[2025-01-18 02:54:08 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][200/312]	eta 0:00:53 lr 0.002888	time 0.4536 (0.4751)	model_time 0.4530 (0.4659)	loss 3.1323 (3.3996)	grad_norm 1.6784 (1.5699/0.6994)	mem 16099MB
[2025-01-18 02:54:12 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][210/312]	eta 0:00:48 lr 0.002888	time 0.4377 (0.4741)	model_time 0.4374 (0.4653)	loss 4.1887 (3.3996)	grad_norm 1.2490 (1.5973/0.7218)	mem 16099MB
[2025-01-18 02:54:17 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][220/312]	eta 0:00:43 lr 0.002887	time 0.4659 (0.4733)	model_time 0.4657 (0.4649)	loss 3.0941 (3.4057)	grad_norm 0.8545 (1.6039/0.7333)	mem 16099MB
[2025-01-18 02:54:22 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][230/312]	eta 0:00:38 lr 0.002887	time 0.5848 (0.4738)	model_time 0.5846 (0.4657)	loss 3.5314 (3.4138)	grad_norm 1.0625 (1.5904/0.7269)	mem 16099MB
[2025-01-18 02:54:26 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][240/312]	eta 0:00:34 lr 0.002886	time 0.4521 (0.4729)	model_time 0.4518 (0.4651)	loss 3.4457 (3.4134)	grad_norm 0.8218 (1.5780/0.7213)	mem 16099MB
[2025-01-18 02:54:31 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][250/312]	eta 0:00:29 lr 0.002885	time 0.4590 (0.4727)	model_time 0.4589 (0.4652)	loss 3.6618 (3.4241)	grad_norm 1.0630 (1.5620/0.7123)	mem 16099MB
[2025-01-18 02:54:36 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][260/312]	eta 0:00:24 lr 0.002885	time 0.4534 (0.4732)	model_time 0.4532 (0.4660)	loss 2.8094 (3.4295)	grad_norm 1.2348 (1.5492/0.7034)	mem 16099MB
[2025-01-18 02:54:40 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][270/312]	eta 0:00:19 lr 0.002884	time 0.4405 (0.4726)	model_time 0.4401 (0.4656)	loss 3.0491 (3.4271)	grad_norm 3.3577 (1.5662/0.7071)	mem 16099MB
[2025-01-18 02:54:45 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][280/312]	eta 0:00:15 lr 0.002884	time 0.4487 (0.4724)	model_time 0.4485 (0.4657)	loss 3.7270 (3.4326)	grad_norm 0.8658 (1.5562/0.7032)	mem 16099MB
[2025-01-18 02:54:50 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][290/312]	eta 0:00:10 lr 0.002883	time 0.4638 (0.4720)	model_time 0.4636 (0.4655)	loss 4.0893 (3.4277)	grad_norm 1.2974 (1.5424/0.6956)	mem 16099MB
[2025-01-18 02:54:54 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][300/312]	eta 0:00:05 lr 0.002882	time 0.4381 (0.4712)	model_time 0.4380 (0.4649)	loss 2.8220 (3.4171)	grad_norm 2.3745 (1.5828/0.7576)	mem 16099MB
[2025-01-18 02:54:58 internimage_t_1k_224] (main.py 510): INFO Train: [106/300][310/312]	eta 0:00:00 lr 0.002882	time 0.4383 (0.4702)	model_time 0.4382 (0.4641)	loss 3.1946 (3.4229)	grad_norm 2.5022 (1.5985/0.7641)	mem 16099MB
[2025-01-18 02:54:59 internimage_t_1k_224] (main.py 519): INFO EPOCH 106 training takes 0:02:26
[2025-01-18 02:54:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_106.pth saving......
[2025-01-18 02:55:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_106.pth saved !!!
[2025-01-18 02:55:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.335 (7.335)	Loss 0.9021 (0.9021)	Acc@1 80.225 (80.225)	Acc@5 95.068 (95.068)	Mem 16099MB
[2025-01-18 02:55:11 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.108 (0.977)	Loss 1.2085 (1.0116)	Acc@1 72.168 (77.561)	Acc@5 91.846 (94.045)	Mem 16099MB
[2025-01-18 02:55:11 internimage_t_1k_224] (main.py 575): INFO [Epoch:106] * Acc@1 77.457 Acc@5 94.036
[2025-01-18 02:55:11 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.5%
[2025-01-18 02:55:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 02:55:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 02:55:12 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.46%
[2025-01-18 02:55:20 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.423 (7.423)	Loss 0.8860 (0.8860)	Acc@1 80.688 (80.688)	Acc@5 96.094 (96.094)	Mem 16099MB
[2025-01-18 02:55:23 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.994)	Loss 1.2859 (1.0524)	Acc@1 71.289 (77.273)	Acc@5 91.113 (93.874)	Mem 16099MB
[2025-01-18 02:55:23 internimage_t_1k_224] (main.py 575): INFO [Epoch:106] * Acc@1 77.195 Acc@5 93.912
[2025-01-18 02:55:23 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 77.2%
[2025-01-18 02:55:23 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:55:24 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:55:24 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 77.20%
[2025-01-18 02:55:27 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][0/312]	eta 0:13:16 lr 0.002882	time 2.5518 (2.5518)	model_time 0.4586 (0.4586)	loss 3.4193 (3.4193)	grad_norm 2.9219 (2.9219/0.0000)	mem 16099MB
[2025-01-18 02:55:32 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][10/312]	eta 0:03:25 lr 0.002881	time 0.5770 (0.6797)	model_time 0.5766 (0.4891)	loss 2.8110 (3.3493)	grad_norm 1.0820 (1.8321/1.0290)	mem 16099MB
[2025-01-18 02:55:37 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][20/312]	eta 0:02:47 lr 0.002881	time 0.4537 (0.5748)	model_time 0.4535 (0.4746)	loss 2.7631 (3.2987)	grad_norm 0.6932 (1.4488/0.8566)	mem 16099MB
[2025-01-18 02:55:41 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][30/312]	eta 0:02:31 lr 0.002880	time 0.5386 (0.5382)	model_time 0.5385 (0.4702)	loss 2.3382 (3.1793)	grad_norm 2.3219 (1.4096/0.7535)	mem 16099MB
[2025-01-18 02:55:46 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][40/312]	eta 0:02:21 lr 0.002879	time 0.4547 (0.5184)	model_time 0.4542 (0.4669)	loss 3.0812 (3.2082)	grad_norm 3.2120 (1.4721/0.7239)	mem 16099MB
[2025-01-18 02:55:50 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][50/312]	eta 0:02:13 lr 0.002879	time 0.4518 (0.5091)	model_time 0.4516 (0.4676)	loss 3.1262 (3.2415)	grad_norm 0.7707 (1.4705/0.7256)	mem 16099MB
[2025-01-18 02:55:55 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][60/312]	eta 0:02:06 lr 0.002878	time 0.4526 (0.5008)	model_time 0.4525 (0.4661)	loss 3.5844 (3.2672)	grad_norm 1.4744 (1.5298/0.7058)	mem 16099MB
[2025-01-18 02:56:00 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][70/312]	eta 0:01:59 lr 0.002878	time 0.4434 (0.4938)	model_time 0.4433 (0.4639)	loss 4.1450 (3.2721)	grad_norm 1.2731 (1.5347/0.6855)	mem 16099MB
[2025-01-18 02:56:04 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][80/312]	eta 0:01:53 lr 0.002877	time 0.4533 (0.4892)	model_time 0.4528 (0.4629)	loss 4.2088 (3.2945)	grad_norm 4.1193 (1.6454/0.8180)	mem 16099MB
[2025-01-18 02:56:09 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][90/312]	eta 0:01:48 lr 0.002876	time 0.5879 (0.4881)	model_time 0.5877 (0.4647)	loss 4.1396 (3.3526)	grad_norm 1.0276 (1.6397/0.8050)	mem 16099MB
[2025-01-18 02:56:13 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][100/312]	eta 0:01:42 lr 0.002876	time 0.4477 (0.4849)	model_time 0.4473 (0.4638)	loss 3.7080 (3.3921)	grad_norm 0.9847 (1.6035/0.7755)	mem 16099MB
[2025-01-18 02:56:18 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][110/312]	eta 0:01:37 lr 0.002875	time 0.4529 (0.4828)	model_time 0.4525 (0.4635)	loss 3.6585 (3.3720)	grad_norm 0.9083 (1.5714/0.7586)	mem 16099MB
[2025-01-18 02:56:23 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][120/312]	eta 0:01:32 lr 0.002875	time 0.4451 (0.4836)	model_time 0.4447 (0.4659)	loss 3.7728 (3.3913)	grad_norm 2.5596 (1.5564/0.7404)	mem 16099MB
[2025-01-18 02:56:28 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][130/312]	eta 0:01:27 lr 0.002874	time 0.4523 (0.4824)	model_time 0.4521 (0.4661)	loss 3.5347 (3.4007)	grad_norm 0.8141 (1.5509/0.7278)	mem 16099MB
[2025-01-18 02:56:33 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][140/312]	eta 0:01:23 lr 0.002873	time 0.4532 (0.4826)	model_time 0.4527 (0.4674)	loss 3.5821 (3.4004)	grad_norm 1.6781 (1.5560/0.7177)	mem 16099MB
[2025-01-18 02:56:37 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][150/312]	eta 0:01:18 lr 0.002873	time 0.4533 (0.4820)	model_time 0.4529 (0.4677)	loss 3.6165 (3.4077)	grad_norm 1.4438 (1.5564/0.7126)	mem 16099MB
[2025-01-18 02:56:42 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][160/312]	eta 0:01:13 lr 0.002872	time 0.4469 (0.4807)	model_time 0.4464 (0.4673)	loss 3.7617 (3.4104)	grad_norm 0.9444 (1.5768/0.7602)	mem 16099MB
[2025-01-18 02:56:46 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][170/312]	eta 0:01:08 lr 0.002872	time 0.4554 (0.4792)	model_time 0.4553 (0.4666)	loss 3.4197 (3.4032)	grad_norm 1.5364 (1.5741/0.7525)	mem 16099MB
[2025-01-18 02:56:51 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][180/312]	eta 0:01:03 lr 0.002871	time 0.4521 (0.4780)	model_time 0.4520 (0.4660)	loss 3.3425 (3.4154)	grad_norm 0.8112 (1.5775/0.7410)	mem 16099MB
[2025-01-18 02:56:56 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][190/312]	eta 0:00:58 lr 0.002870	time 0.4415 (0.4769)	model_time 0.4413 (0.4656)	loss 3.3978 (3.4183)	grad_norm 3.3318 (1.5994/0.7603)	mem 16099MB
[2025-01-18 02:57:00 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][200/312]	eta 0:00:53 lr 0.002870	time 0.4506 (0.4756)	model_time 0.4501 (0.4648)	loss 3.2387 (3.4169)	grad_norm 1.0207 (1.6163/0.7691)	mem 16099MB
[2025-01-18 02:57:05 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][210/312]	eta 0:00:48 lr 0.002869	time 0.4846 (0.4752)	model_time 0.4844 (0.4649)	loss 3.2715 (3.4225)	grad_norm 2.0873 (1.6260/0.7584)	mem 16099MB
[2025-01-18 02:57:09 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][220/312]	eta 0:00:43 lr 0.002869	time 0.4411 (0.4740)	model_time 0.4409 (0.4641)	loss 2.2664 (3.4217)	grad_norm 2.2170 (1.6113/0.7497)	mem 16099MB
[2025-01-18 02:57:14 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][230/312]	eta 0:00:38 lr 0.002868	time 0.4517 (0.4731)	model_time 0.4513 (0.4637)	loss 3.5110 (3.4338)	grad_norm 1.1866 (1.6014/0.7389)	mem 16099MB
[2025-01-18 02:57:18 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][240/312]	eta 0:00:34 lr 0.002867	time 0.4464 (0.4727)	model_time 0.4462 (0.4636)	loss 3.8168 (3.4332)	grad_norm 0.9835 (1.6053/0.7375)	mem 16099MB
[2025-01-18 02:57:23 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][250/312]	eta 0:00:29 lr 0.002867	time 0.4503 (0.4722)	model_time 0.4499 (0.4635)	loss 2.7769 (3.4342)	grad_norm 2.1764 (1.6056/0.7319)	mem 16099MB
[2025-01-18 02:57:28 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][260/312]	eta 0:00:24 lr 0.002866	time 0.4533 (0.4718)	model_time 0.4532 (0.4634)	loss 2.5313 (3.4168)	grad_norm 0.8214 (1.6121/0.7357)	mem 16099MB
[2025-01-18 02:57:32 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][270/312]	eta 0:00:19 lr 0.002866	time 0.4487 (0.4716)	model_time 0.4483 (0.4634)	loss 2.9078 (3.4139)	grad_norm 1.1575 (1.5990/0.7301)	mem 16099MB
[2025-01-18 02:57:37 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][280/312]	eta 0:00:15 lr 0.002865	time 0.4453 (0.4710)	model_time 0.4450 (0.4632)	loss 3.1885 (3.4168)	grad_norm 1.1559 (1.5893/0.7212)	mem 16099MB
[2025-01-18 02:57:41 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][290/312]	eta 0:00:10 lr 0.002864	time 0.4539 (0.4708)	model_time 0.4537 (0.4632)	loss 3.3896 (3.4155)	grad_norm 1.1600 (1.5929/0.7173)	mem 16099MB
[2025-01-18 02:57:46 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][300/312]	eta 0:00:05 lr 0.002864	time 0.4376 (0.4705)	model_time 0.4375 (0.4632)	loss 2.3275 (3.4093)	grad_norm 1.0619 (1.5855/0.7073)	mem 16099MB
[2025-01-18 02:57:51 internimage_t_1k_224] (main.py 510): INFO Train: [107/300][310/312]	eta 0:00:00 lr 0.002863	time 0.5638 (0.4703)	model_time 0.5637 (0.4632)	loss 3.6071 (3.4067)	grad_norm 2.9313 (1.5820/0.6945)	mem 16099MB
[2025-01-18 02:57:51 internimage_t_1k_224] (main.py 519): INFO EPOCH 107 training takes 0:02:26
[2025-01-18 02:57:51 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_107.pth saving......
[2025-01-18 02:57:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_107.pth saved !!!
[2025-01-18 02:58:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.175 (7.175)	Loss 0.8380 (0.8380)	Acc@1 80.859 (80.859)	Acc@5 95.972 (95.972)	Mem 16099MB
[2025-01-18 02:58:03 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (0.966)	Loss 1.1957 (1.0112)	Acc@1 73.560 (77.657)	Acc@5 91.943 (94.010)	Mem 16099MB
[2025-01-18 02:58:03 internimage_t_1k_224] (main.py 575): INFO [Epoch:107] * Acc@1 77.591 Acc@5 94.030
[2025-01-18 02:58:03 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.6%
[2025-01-18 02:58:03 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 02:58:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 02:58:04 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.59%
[2025-01-18 02:58:12 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.373 (7.373)	Loss 0.8806 (0.8806)	Acc@1 80.835 (80.835)	Acc@5 96.191 (96.191)	Mem 16099MB
[2025-01-18 02:58:15 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.996)	Loss 1.2782 (1.0461)	Acc@1 71.533 (77.424)	Acc@5 91.235 (93.987)	Mem 16099MB
[2025-01-18 02:58:15 internimage_t_1k_224] (main.py 575): INFO [Epoch:107] * Acc@1 77.339 Acc@5 94.014
[2025-01-18 02:58:15 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 77.3%
[2025-01-18 02:58:15 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 02:58:17 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 02:58:17 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 77.34%
[2025-01-18 02:58:19 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][0/312]	eta 0:11:58 lr 0.002863	time 2.3030 (2.3030)	model_time 0.4614 (0.4614)	loss 3.5583 (3.5583)	grad_norm 1.9661 (1.9661/0.0000)	mem 16099MB
[2025-01-18 02:58:24 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][10/312]	eta 0:03:10 lr 0.002862	time 0.4395 (0.6313)	model_time 0.4392 (0.4635)	loss 3.7109 (3.3349)	grad_norm 0.7812 (1.8303/0.7288)	mem 16099MB
[2025-01-18 02:58:28 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][20/312]	eta 0:02:41 lr 0.002862	time 0.4560 (0.5523)	model_time 0.4559 (0.4642)	loss 2.9959 (3.3203)	grad_norm 1.2318 (1.8984/0.8484)	mem 16099MB
[2025-01-18 02:58:33 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][30/312]	eta 0:02:27 lr 0.002861	time 0.4632 (0.5234)	model_time 0.4627 (0.4636)	loss 3.4947 (3.1968)	grad_norm 1.4502 (1.7013/0.7693)	mem 16099MB
[2025-01-18 02:58:37 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][40/312]	eta 0:02:17 lr 0.002861	time 0.4531 (0.5064)	model_time 0.4527 (0.4612)	loss 3.4973 (3.2397)	grad_norm 1.1040 (1.5547/0.7278)	mem 16099MB
[2025-01-18 02:58:42 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][50/312]	eta 0:02:11 lr 0.002860	time 0.5196 (0.5013)	model_time 0.5195 (0.4649)	loss 3.4260 (3.3478)	grad_norm 1.8762 (1.6210/0.7451)	mem 16099MB
[2025-01-18 02:58:47 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][60/312]	eta 0:02:04 lr 0.002859	time 0.4555 (0.4948)	model_time 0.4553 (0.4642)	loss 3.2014 (3.3133)	grad_norm 1.7101 (1.6275/0.6880)	mem 16099MB
[2025-01-18 02:58:51 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][70/312]	eta 0:01:58 lr 0.002859	time 0.4510 (0.4902)	model_time 0.4505 (0.4639)	loss 2.5343 (3.3014)	grad_norm 1.6655 (1.6408/0.6689)	mem 16099MB
[2025-01-18 02:58:56 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][80/312]	eta 0:01:52 lr 0.002858	time 0.4550 (0.4856)	model_time 0.4548 (0.4625)	loss 3.3980 (3.3146)	grad_norm 1.3872 (1.6999/0.7220)	mem 16099MB
[2025-01-18 02:59:01 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][90/312]	eta 0:01:48 lr 0.002858	time 0.4566 (0.4872)	model_time 0.4564 (0.4666)	loss 3.7282 (3.2899)	grad_norm 2.4134 (1.7511/0.8399)	mem 16099MB
[2025-01-18 02:59:06 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][100/312]	eta 0:01:42 lr 0.002857	time 0.4528 (0.4854)	model_time 0.4527 (0.4668)	loss 3.8946 (3.2806)	grad_norm 1.8178 (1.7157/0.8126)	mem 16099MB
[2025-01-18 02:59:10 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][110/312]	eta 0:01:37 lr 0.002856	time 0.4519 (0.4825)	model_time 0.4515 (0.4655)	loss 3.8078 (3.3207)	grad_norm 1.4534 (1.6793/0.7931)	mem 16099MB
[2025-01-18 02:59:15 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][120/312]	eta 0:01:32 lr 0.002856	time 0.4526 (0.4826)	model_time 0.4522 (0.4670)	loss 3.4658 (3.3252)	grad_norm 0.8933 (1.6534/0.7712)	mem 16099MB
[2025-01-18 02:59:20 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][130/312]	eta 0:01:27 lr 0.002855	time 0.4786 (0.4808)	model_time 0.4781 (0.4663)	loss 3.7521 (3.3259)	grad_norm 1.8028 (1.6518/0.7593)	mem 16099MB
[2025-01-18 02:59:24 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][140/312]	eta 0:01:22 lr 0.002855	time 0.4421 (0.4793)	model_time 0.4419 (0.4659)	loss 3.9195 (3.3346)	grad_norm 1.3270 (1.6770/0.7646)	mem 16099MB
[2025-01-18 02:59:29 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][150/312]	eta 0:01:17 lr 0.002854	time 0.4440 (0.4781)	model_time 0.4438 (0.4655)	loss 3.7086 (3.3425)	grad_norm 1.2522 (1.6813/0.7621)	mem 16099MB
[2025-01-18 02:59:34 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][160/312]	eta 0:01:12 lr 0.002853	time 0.5215 (0.4777)	model_time 0.5213 (0.4659)	loss 3.3771 (3.3497)	grad_norm 1.6603 (1.7304/0.7951)	mem 16099MB
[2025-01-18 02:59:38 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][170/312]	eta 0:01:07 lr 0.002853	time 0.4429 (0.4771)	model_time 0.4427 (0.4660)	loss 3.3308 (3.3709)	grad_norm 2.9349 (1.7202/0.7902)	mem 16099MB
[2025-01-18 02:59:43 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][180/312]	eta 0:01:02 lr 0.002852	time 0.4448 (0.4757)	model_time 0.4446 (0.4652)	loss 3.4907 (3.3817)	grad_norm 2.0964 (1.7093/0.7778)	mem 16099MB
[2025-01-18 02:59:47 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][190/312]	eta 0:00:57 lr 0.002852	time 0.4541 (0.4748)	model_time 0.4537 (0.4648)	loss 3.7667 (3.3797)	grad_norm 1.2597 (1.6863/0.7692)	mem 16099MB
[2025-01-18 02:59:52 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][200/312]	eta 0:00:53 lr 0.002851	time 0.5354 (0.4745)	model_time 0.5350 (0.4650)	loss 3.9124 (3.3922)	grad_norm 0.9322 (1.6606/0.7613)	mem 16099MB
[2025-01-18 02:59:57 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][210/312]	eta 0:00:48 lr 0.002850	time 0.4448 (0.4738)	model_time 0.4444 (0.4647)	loss 2.2614 (3.3824)	grad_norm 2.0393 (1.6912/0.8210)	mem 16099MB
[2025-01-18 03:00:01 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][220/312]	eta 0:00:43 lr 0.002850	time 0.4588 (0.4733)	model_time 0.4586 (0.4646)	loss 3.2079 (3.3712)	grad_norm 1.8993 (1.6911/0.8131)	mem 16099MB
[2025-01-18 03:00:06 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][230/312]	eta 0:00:38 lr 0.002849	time 0.4513 (0.4727)	model_time 0.4509 (0.4643)	loss 3.9816 (3.3704)	grad_norm 2.1070 (1.6922/0.8042)	mem 16099MB
[2025-01-18 03:00:10 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][240/312]	eta 0:00:34 lr 0.002849	time 0.4426 (0.4723)	model_time 0.4422 (0.4642)	loss 2.9654 (3.3753)	grad_norm 1.2509 (1.6761/0.7948)	mem 16099MB
[2025-01-18 03:00:15 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][250/312]	eta 0:00:29 lr 0.002848	time 0.4566 (0.4721)	model_time 0.4564 (0.4644)	loss 3.7144 (3.3654)	grad_norm 1.2031 (1.6830/0.7920)	mem 16099MB
[2025-01-18 03:00:20 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][260/312]	eta 0:00:24 lr 0.002847	time 0.4475 (0.4718)	model_time 0.4471 (0.4644)	loss 2.4736 (3.3491)	grad_norm 2.4978 (1.6766/0.7903)	mem 16099MB
[2025-01-18 03:00:24 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][270/312]	eta 0:00:19 lr 0.002847	time 0.4560 (0.4716)	model_time 0.4558 (0.4644)	loss 2.7256 (3.3567)	grad_norm 1.2751 (1.6778/0.7827)	mem 16099MB
[2025-01-18 03:00:29 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][280/312]	eta 0:00:15 lr 0.002846	time 0.4598 (0.4710)	model_time 0.4593 (0.4641)	loss 3.9820 (3.3631)	grad_norm 1.6020 (1.6805/0.7749)	mem 16099MB
[2025-01-18 03:00:34 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][290/312]	eta 0:00:10 lr 0.002846	time 0.4415 (0.4721)	model_time 0.4411 (0.4653)	loss 3.2281 (3.3580)	grad_norm 1.5276 (1.6663/0.7692)	mem 16099MB
[2025-01-18 03:00:38 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][300/312]	eta 0:00:05 lr 0.002845	time 0.4375 (0.4714)	model_time 0.4374 (0.4649)	loss 2.5292 (3.3558)	grad_norm 3.9998 (1.6627/0.7743)	mem 16099MB
[2025-01-18 03:00:43 internimage_t_1k_224] (main.py 510): INFO Train: [108/300][310/312]	eta 0:00:00 lr 0.002844	time 0.4379 (0.4705)	model_time 0.4378 (0.4642)	loss 3.3760 (3.3642)	grad_norm 0.9714 (1.6526/0.7690)	mem 16099MB
[2025-01-18 03:00:43 internimage_t_1k_224] (main.py 519): INFO EPOCH 108 training takes 0:02:26
[2025-01-18 03:00:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_108.pth saving......
[2025-01-18 03:00:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_108.pth saved !!!
[2025-01-18 03:00:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.351 (7.351)	Loss 0.9207 (0.9207)	Acc@1 80.688 (80.688)	Acc@5 95.825 (95.825)	Mem 16099MB
[2025-01-18 03:00:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.979)	Loss 1.3620 (1.0933)	Acc@1 70.459 (76.924)	Acc@5 90.894 (93.859)	Mem 16099MB
[2025-01-18 03:00:56 internimage_t_1k_224] (main.py 575): INFO [Epoch:108] * Acc@1 76.869 Acc@5 93.918
[2025-01-18 03:00:56 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 76.9%
[2025-01-18 03:00:56 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.59%
[2025-01-18 03:01:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.116 (8.116)	Loss 0.8757 (0.8757)	Acc@1 80.957 (80.957)	Acc@5 96.167 (96.167)	Mem 16099MB
[2025-01-18 03:01:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.099)	Loss 1.2704 (1.0401)	Acc@1 71.680 (77.570)	Acc@5 91.455 (94.036)	Mem 16099MB
[2025-01-18 03:01:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:108] * Acc@1 77.471 Acc@5 94.068
[2025-01-18 03:01:08 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 77.5%
[2025-01-18 03:01:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:01:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:01:09 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 77.47%
[2025-01-18 03:01:11 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][0/312]	eta 0:11:11 lr 0.002844	time 2.1537 (2.1537)	model_time 0.4835 (0.4835)	loss 2.8867 (2.8867)	grad_norm 2.1661 (2.1661/0.0000)	mem 16099MB
[2025-01-18 03:01:16 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][10/312]	eta 0:03:06 lr 0.002844	time 0.4472 (0.6191)	model_time 0.4471 (0.4670)	loss 3.0656 (3.2691)	grad_norm 1.6739 (1.8482/0.5578)	mem 16099MB
[2025-01-18 03:01:20 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][20/312]	eta 0:02:37 lr 0.002843	time 0.4499 (0.5402)	model_time 0.4495 (0.4604)	loss 2.5737 (3.3096)	grad_norm 2.0975 (1.6211/0.5324)	mem 16099MB
[2025-01-18 03:01:25 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][30/312]	eta 0:02:28 lr 0.002842	time 0.4832 (0.5255)	model_time 0.4830 (0.4713)	loss 2.6395 (3.3524)	grad_norm 1.3849 (1.4586/0.5252)	mem 16099MB
[2025-01-18 03:01:30 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][40/312]	eta 0:02:18 lr 0.002842	time 0.4754 (0.5096)	model_time 0.4749 (0.4686)	loss 3.5735 (3.3572)	grad_norm 0.7776 (1.4138/0.4896)	mem 16099MB
[2025-01-18 03:01:35 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][50/312]	eta 0:02:10 lr 0.002841	time 0.4690 (0.4999)	model_time 0.4686 (0.4669)	loss 4.2143 (3.3661)	grad_norm 2.3991 (1.4334/0.5095)	mem 16099MB
[2025-01-18 03:01:39 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][60/312]	eta 0:02:04 lr 0.002841	time 0.4586 (0.4934)	model_time 0.4585 (0.4657)	loss 3.0550 (3.3791)	grad_norm 1.6564 (1.4605/0.5154)	mem 16099MB
[2025-01-18 03:01:44 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][70/312]	eta 0:01:57 lr 0.002840	time 0.4592 (0.4876)	model_time 0.4591 (0.4637)	loss 3.3360 (3.3863)	grad_norm 1.2818 (1.4263/0.5061)	mem 16099MB
[2025-01-18 03:01:48 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][80/312]	eta 0:01:52 lr 0.002839	time 0.5337 (0.4850)	model_time 0.5336 (0.4641)	loss 3.9232 (3.3577)	grad_norm 2.2382 (1.4423/0.5220)	mem 16099MB
[2025-01-18 03:01:53 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][90/312]	eta 0:01:46 lr 0.002839	time 0.4512 (0.4816)	model_time 0.4511 (0.4630)	loss 4.2777 (3.3866)	grad_norm 3.8930 (1.5022/0.5931)	mem 16099MB
[2025-01-18 03:01:57 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][100/312]	eta 0:01:41 lr 0.002838	time 0.4642 (0.4790)	model_time 0.4641 (0.4622)	loss 3.0863 (3.3597)	grad_norm 1.3914 (1.5028/0.5784)	mem 16099MB
[2025-01-18 03:02:02 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][110/312]	eta 0:01:36 lr 0.002838	time 0.4518 (0.4781)	model_time 0.4516 (0.4628)	loss 3.5777 (3.3623)	grad_norm 1.4649 (1.5254/0.6271)	mem 16099MB
[2025-01-18 03:02:07 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][120/312]	eta 0:01:31 lr 0.002837	time 0.4523 (0.4760)	model_time 0.4521 (0.4619)	loss 3.0329 (3.3593)	grad_norm 1.0953 (1.4860/0.6175)	mem 16099MB
[2025-01-18 03:02:11 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][130/312]	eta 0:01:26 lr 0.002836	time 0.4454 (0.4750)	model_time 0.4453 (0.4619)	loss 3.5258 (3.3729)	grad_norm 0.9677 (1.4595/0.6139)	mem 16099MB
[2025-01-18 03:02:16 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][140/312]	eta 0:01:21 lr 0.002836	time 0.4513 (0.4733)	model_time 0.4511 (0.4611)	loss 2.8987 (3.3600)	grad_norm 3.2911 (1.5455/0.7744)	mem 16099MB
[2025-01-18 03:02:21 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][150/312]	eta 0:01:16 lr 0.002835	time 0.4536 (0.4737)	model_time 0.4532 (0.4623)	loss 4.0861 (3.3731)	grad_norm 1.5671 (1.5399/0.7534)	mem 16099MB
[2025-01-18 03:02:25 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][160/312]	eta 0:01:12 lr 0.002835	time 0.5310 (0.4748)	model_time 0.5309 (0.4641)	loss 2.0484 (3.3691)	grad_norm 0.7867 (1.5391/0.7392)	mem 16099MB
[2025-01-18 03:02:30 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][170/312]	eta 0:01:07 lr 0.002834	time 0.4486 (0.4744)	model_time 0.4484 (0.4643)	loss 3.4179 (3.3580)	grad_norm 0.9562 (1.5243/0.7240)	mem 16099MB
[2025-01-18 03:02:35 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][180/312]	eta 0:01:02 lr 0.002833	time 0.4442 (0.4736)	model_time 0.4441 (0.4640)	loss 3.4542 (3.3795)	grad_norm 1.3820 (1.5287/0.7127)	mem 16099MB
[2025-01-18 03:02:39 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][190/312]	eta 0:00:57 lr 0.002833	time 0.4474 (0.4727)	model_time 0.4473 (0.4636)	loss 2.3453 (3.3599)	grad_norm 1.3728 (1.5131/0.7024)	mem 16099MB
[2025-01-18 03:02:44 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][200/312]	eta 0:00:52 lr 0.002832	time 0.4524 (0.4720)	model_time 0.4520 (0.4634)	loss 3.9426 (3.3572)	grad_norm 1.7818 (1.5108/0.6902)	mem 16099MB
[2025-01-18 03:02:48 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][210/312]	eta 0:00:48 lr 0.002832	time 0.4387 (0.4713)	model_time 0.4386 (0.4630)	loss 3.5633 (3.3533)	grad_norm 1.5966 (1.5119/0.6848)	mem 16099MB
[2025-01-18 03:02:53 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][220/312]	eta 0:00:43 lr 0.002831	time 0.4585 (0.4704)	model_time 0.4583 (0.4625)	loss 3.3230 (3.3311)	grad_norm 1.6673 (1.5158/0.6741)	mem 16099MB
[2025-01-18 03:02:58 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][230/312]	eta 0:00:38 lr 0.002830	time 0.4513 (0.4699)	model_time 0.4511 (0.4624)	loss 3.4752 (3.3432)	grad_norm 2.5156 (1.5284/0.6761)	mem 16099MB
[2025-01-18 03:03:02 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][240/312]	eta 0:00:33 lr 0.002830	time 0.4541 (0.4691)	model_time 0.4539 (0.4619)	loss 3.6319 (3.3394)	grad_norm 1.1918 (1.5184/0.6660)	mem 16099MB
[2025-01-18 03:03:07 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][250/312]	eta 0:00:29 lr 0.002829	time 0.4439 (0.4700)	model_time 0.4438 (0.4630)	loss 3.1559 (3.3354)	grad_norm 2.3774 (1.5287/0.6725)	mem 16099MB
[2025-01-18 03:03:12 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][260/312]	eta 0:00:24 lr 0.002828	time 0.5382 (0.4701)	model_time 0.5380 (0.4634)	loss 4.3194 (3.3370)	grad_norm 4.2548 (1.5453/0.6934)	mem 16099MB
[2025-01-18 03:03:16 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][270/312]	eta 0:00:19 lr 0.002828	time 0.4564 (0.4699)	model_time 0.4562 (0.4635)	loss 3.4631 (3.3420)	grad_norm 3.0533 (1.5769/0.7107)	mem 16099MB
[2025-01-18 03:03:21 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][280/312]	eta 0:00:15 lr 0.002827	time 0.4461 (0.4698)	model_time 0.4457 (0.4636)	loss 3.7936 (3.3475)	grad_norm 1.5183 (1.5712/0.7049)	mem 16099MB
[2025-01-18 03:03:26 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][290/312]	eta 0:00:10 lr 0.002827	time 0.4546 (0.4695)	model_time 0.4544 (0.4634)	loss 3.3231 (3.3473)	grad_norm 3.4747 (1.5764/0.7138)	mem 16099MB
[2025-01-18 03:03:30 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][300/312]	eta 0:00:05 lr 0.002826	time 0.4415 (0.4688)	model_time 0.4414 (0.4629)	loss 2.3741 (3.3526)	grad_norm 0.9412 (1.5724/0.7218)	mem 16099MB
[2025-01-18 03:03:35 internimage_t_1k_224] (main.py 510): INFO Train: [109/300][310/312]	eta 0:00:00 lr 0.002825	time 0.4383 (0.4682)	model_time 0.4382 (0.4625)	loss 4.0171 (3.3575)	grad_norm 1.3464 (1.5624/0.7150)	mem 16099MB
[2025-01-18 03:03:35 internimage_t_1k_224] (main.py 519): INFO EPOCH 109 training takes 0:02:26
[2025-01-18 03:03:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_109.pth saving......
[2025-01-18 03:03:36 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_109.pth saved !!!
[2025-01-18 03:03:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.292 (7.292)	Loss 0.8758 (0.8758)	Acc@1 80.444 (80.444)	Acc@5 95.752 (95.752)	Mem 16099MB
[2025-01-18 03:03:47 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.000)	Loss 1.2580 (1.0304)	Acc@1 71.875 (77.455)	Acc@5 92.090 (94.176)	Mem 16099MB
[2025-01-18 03:03:48 internimage_t_1k_224] (main.py 575): INFO [Epoch:109] * Acc@1 77.333 Acc@5 94.218
[2025-01-18 03:03:48 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.3%
[2025-01-18 03:03:48 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.59%
[2025-01-18 03:03:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.458 (8.458)	Loss 0.8711 (0.8711)	Acc@1 81.128 (81.128)	Acc@5 96.191 (96.191)	Mem 16099MB
[2025-01-18 03:04:00 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.131)	Loss 1.2627 (1.0344)	Acc@1 71.802 (77.672)	Acc@5 91.577 (94.116)	Mem 16099MB
[2025-01-18 03:04:00 internimage_t_1k_224] (main.py 575): INFO [Epoch:109] * Acc@1 77.575 Acc@5 94.144
[2025-01-18 03:04:00 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 77.6%
[2025-01-18 03:04:00 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:04:01 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:04:01 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 77.58%
[2025-01-18 03:04:04 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][0/312]	eta 0:11:33 lr 0.002825	time 2.2229 (2.2229)	model_time 0.4986 (0.4986)	loss 3.6454 (3.6454)	grad_norm 1.3205 (1.3205/0.0000)	mem 16099MB
[2025-01-18 03:04:08 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][10/312]	eta 0:03:09 lr 0.002825	time 0.5229 (0.6275)	model_time 0.5225 (0.4705)	loss 3.1743 (3.5310)	grad_norm 2.0621 (1.3423/0.3879)	mem 16099MB
[2025-01-18 03:04:13 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][20/312]	eta 0:02:41 lr 0.002824	time 0.4656 (0.5524)	model_time 0.4655 (0.4700)	loss 2.6829 (3.3363)	grad_norm 2.5675 (1.3766/0.4993)	mem 16099MB
[2025-01-18 03:04:18 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][30/312]	eta 0:02:29 lr 0.002824	time 0.4550 (0.5289)	model_time 0.4549 (0.4730)	loss 3.6401 (3.2993)	grad_norm 0.8772 (1.3818/0.4678)	mem 16099MB
[2025-01-18 03:04:22 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][40/312]	eta 0:02:19 lr 0.002823	time 0.4526 (0.5133)	model_time 0.4525 (0.4710)	loss 3.5831 (3.3649)	grad_norm 1.7133 (1.4011/0.4865)	mem 16099MB
[2025-01-18 03:04:27 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][50/312]	eta 0:02:11 lr 0.002822	time 0.4599 (0.5030)	model_time 0.4597 (0.4690)	loss 3.5423 (3.4186)	grad_norm 1.3106 (1.6680/0.9660)	mem 16099MB
[2025-01-18 03:04:32 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][60/312]	eta 0:02:05 lr 0.002822	time 0.4553 (0.4971)	model_time 0.4549 (0.4686)	loss 3.3112 (3.4303)	grad_norm 1.3507 (1.6541/0.9296)	mem 16099MB
[2025-01-18 03:04:36 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][70/312]	eta 0:01:59 lr 0.002821	time 0.5236 (0.4918)	model_time 0.5235 (0.4672)	loss 2.6661 (3.4192)	grad_norm 0.9540 (1.7049/0.9998)	mem 16099MB
[2025-01-18 03:04:41 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][80/312]	eta 0:01:53 lr 0.002820	time 0.4550 (0.4879)	model_time 0.4545 (0.4661)	loss 3.2570 (3.4223)	grad_norm 0.8386 (1.6582/0.9516)	mem 16099MB
[2025-01-18 03:04:45 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][90/312]	eta 0:01:47 lr 0.002820	time 0.4473 (0.4845)	model_time 0.4471 (0.4650)	loss 3.4505 (3.4251)	grad_norm 3.2111 (1.6562/0.9360)	mem 16099MB
[2025-01-18 03:04:50 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][100/312]	eta 0:01:42 lr 0.002819	time 0.4500 (0.4816)	model_time 0.4495 (0.4641)	loss 4.0201 (3.3991)	grad_norm 0.9132 (1.6345/0.9186)	mem 16099MB
[2025-01-18 03:04:55 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][110/312]	eta 0:01:36 lr 0.002819	time 0.4580 (0.4790)	model_time 0.4578 (0.4630)	loss 3.4805 (3.3881)	grad_norm 1.0740 (1.5840/0.8969)	mem 16099MB
[2025-01-18 03:04:59 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][120/312]	eta 0:01:31 lr 0.002818	time 0.4563 (0.4778)	model_time 0.4561 (0.4631)	loss 3.4343 (3.3915)	grad_norm 1.4407 (1.5898/0.8745)	mem 16099MB
[2025-01-18 03:05:04 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][130/312]	eta 0:01:26 lr 0.002817	time 0.5180 (0.4774)	model_time 0.5178 (0.4638)	loss 3.6050 (3.4009)	grad_norm 1.2220 (1.5710/0.8470)	mem 16099MB
[2025-01-18 03:05:09 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][140/312]	eta 0:01:22 lr 0.002817	time 0.6054 (0.4775)	model_time 0.6050 (0.4648)	loss 2.7915 (3.3861)	grad_norm 3.0488 (1.5736/0.8438)	mem 16099MB
[2025-01-18 03:05:13 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][150/312]	eta 0:01:17 lr 0.002816	time 0.4397 (0.4768)	model_time 0.4396 (0.4649)	loss 3.3452 (3.3755)	grad_norm 1.1733 (1.5886/0.8226)	mem 16099MB
[2025-01-18 03:05:18 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][160/312]	eta 0:01:12 lr 0.002816	time 0.4457 (0.4757)	model_time 0.4452 (0.4646)	loss 3.7192 (3.3854)	grad_norm 1.4249 (1.5843/0.8038)	mem 16099MB
[2025-01-18 03:05:23 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][170/312]	eta 0:01:07 lr 0.002815	time 0.4457 (0.4760)	model_time 0.4455 (0.4655)	loss 4.0868 (3.4016)	grad_norm 2.8818 (1.5757/0.7958)	mem 16099MB
[2025-01-18 03:05:27 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][180/312]	eta 0:01:02 lr 0.002814	time 0.4593 (0.4754)	model_time 0.4589 (0.4655)	loss 2.8876 (3.4000)	grad_norm 1.0200 (1.5628/0.7809)	mem 16099MB
[2025-01-18 03:05:32 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][190/312]	eta 0:00:57 lr 0.002814	time 0.4471 (0.4747)	model_time 0.4470 (0.4653)	loss 3.1362 (3.3856)	grad_norm 1.8016 (1.5762/0.7679)	mem 16099MB
[2025-01-18 03:05:37 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][200/312]	eta 0:00:53 lr 0.002813	time 0.4510 (0.4742)	model_time 0.4506 (0.4652)	loss 2.8801 (3.3869)	grad_norm 1.5924 (1.6034/0.7861)	mem 16099MB
[2025-01-18 03:05:41 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][210/312]	eta 0:00:48 lr 0.002813	time 0.4985 (0.4735)	model_time 0.4981 (0.4649)	loss 3.6041 (3.3804)	grad_norm 0.7911 (1.5902/0.7783)	mem 16099MB
[2025-01-18 03:05:46 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][220/312]	eta 0:00:43 lr 0.002812	time 0.4520 (0.4730)	model_time 0.4516 (0.4648)	loss 2.9066 (3.3822)	grad_norm 2.1103 (1.5931/0.7764)	mem 16099MB
[2025-01-18 03:05:50 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][230/312]	eta 0:00:38 lr 0.002811	time 0.4505 (0.4721)	model_time 0.4503 (0.4642)	loss 4.1183 (3.3869)	grad_norm 1.8150 (1.5910/0.7730)	mem 16099MB
[2025-01-18 03:05:55 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][240/312]	eta 0:00:34 lr 0.002811	time 0.4570 (0.4722)	model_time 0.4569 (0.4647)	loss 3.5288 (3.3804)	grad_norm 1.5448 (1.5937/0.7622)	mem 16099MB
[2025-01-18 03:06:00 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][250/312]	eta 0:00:29 lr 0.002810	time 0.4618 (0.4716)	model_time 0.4614 (0.4644)	loss 3.7410 (3.3753)	grad_norm 1.3036 (1.5853/0.7530)	mem 16099MB
[2025-01-18 03:06:04 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][260/312]	eta 0:00:24 lr 0.002810	time 0.4484 (0.4714)	model_time 0.4480 (0.4644)	loss 3.4923 (3.3764)	grad_norm 2.3669 (1.6094/0.7649)	mem 16099MB
[2025-01-18 03:06:09 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][270/312]	eta 0:00:19 lr 0.002809	time 0.4473 (0.4707)	model_time 0.4472 (0.4639)	loss 3.5940 (3.3822)	grad_norm 2.2757 (1.6294/0.7804)	mem 16099MB
[2025-01-18 03:06:14 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][280/312]	eta 0:00:15 lr 0.002808	time 0.4514 (0.4704)	model_time 0.4510 (0.4639)	loss 2.8462 (3.3787)	grad_norm 0.6753 (1.6222/0.7751)	mem 16099MB
[2025-01-18 03:06:19 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][290/312]	eta 0:00:10 lr 0.002808	time 0.5503 (0.4712)	model_time 0.5499 (0.4648)	loss 3.3119 (3.3797)	grad_norm 0.9897 (1.6111/0.7687)	mem 16099MB
[2025-01-18 03:06:23 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][300/312]	eta 0:00:05 lr 0.002807	time 0.4385 (0.4712)	model_time 0.4384 (0.4651)	loss 3.5301 (3.3691)	grad_norm 0.8653 (1.5987/0.7605)	mem 16099MB
[2025-01-18 03:06:28 internimage_t_1k_224] (main.py 510): INFO Train: [110/300][310/312]	eta 0:00:00 lr 0.002806	time 0.4402 (0.4708)	model_time 0.4401 (0.4649)	loss 3.0870 (3.3652)	grad_norm 0.9286 (1.6041/0.7614)	mem 16099MB
[2025-01-18 03:06:28 internimage_t_1k_224] (main.py 519): INFO EPOCH 110 training takes 0:02:26
[2025-01-18 03:06:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_110.pth saving......
[2025-01-18 03:06:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_110.pth saved !!!
[2025-01-18 03:06:37 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.476 (7.476)	Loss 0.8682 (0.8682)	Acc@1 81.494 (81.494)	Acc@5 96.143 (96.143)	Mem 16099MB
[2025-01-18 03:06:40 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.010)	Loss 1.2181 (1.0391)	Acc@1 72.803 (77.346)	Acc@5 92.334 (94.161)	Mem 16099MB
[2025-01-18 03:06:41 internimage_t_1k_224] (main.py 575): INFO [Epoch:110] * Acc@1 77.327 Acc@5 94.176
[2025-01-18 03:06:41 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.3%
[2025-01-18 03:06:41 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.59%
[2025-01-18 03:06:49 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.256 (8.256)	Loss 0.8667 (0.8667)	Acc@1 81.177 (81.177)	Acc@5 96.265 (96.265)	Mem 16099MB
[2025-01-18 03:06:53 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.100)	Loss 1.2553 (1.0289)	Acc@1 71.973 (77.832)	Acc@5 91.650 (94.183)	Mem 16099MB
[2025-01-18 03:06:53 internimage_t_1k_224] (main.py 575): INFO [Epoch:110] * Acc@1 77.725 Acc@5 94.204
[2025-01-18 03:06:53 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 77.7%
[2025-01-18 03:06:53 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:06:54 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:06:54 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 77.73%
[2025-01-18 03:06:57 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][0/312]	eta 0:12:27 lr 0.002806	time 2.3943 (2.3943)	model_time 0.5895 (0.5895)	loss 3.4508 (3.4508)	grad_norm 1.6764 (1.6764/0.0000)	mem 16099MB
[2025-01-18 03:07:01 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][10/312]	eta 0:03:10 lr 0.002806	time 0.4556 (0.6319)	model_time 0.4552 (0.4675)	loss 3.8504 (3.0847)	grad_norm 1.8280 (1.7163/0.7931)	mem 16099MB
[2025-01-18 03:07:06 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][20/312]	eta 0:02:40 lr 0.002805	time 0.4508 (0.5502)	model_time 0.4507 (0.4639)	loss 3.4656 (3.1703)	grad_norm 1.5584 (2.1036/1.2097)	mem 16099MB
[2025-01-18 03:07:10 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][30/312]	eta 0:02:26 lr 0.002805	time 0.4480 (0.5211)	model_time 0.4479 (0.4625)	loss 3.7368 (3.1838)	grad_norm 1.4972 (1.9019/1.0623)	mem 16099MB
[2025-01-18 03:07:15 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][40/312]	eta 0:02:17 lr 0.002804	time 0.4478 (0.5066)	model_time 0.4476 (0.4622)	loss 3.3020 (3.2752)	grad_norm 1.9484 (1.9502/0.9913)	mem 16099MB
[2025-01-18 03:07:20 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][50/312]	eta 0:02:10 lr 0.002803	time 0.4449 (0.4994)	model_time 0.4445 (0.4637)	loss 3.3741 (3.2392)	grad_norm 1.3061 (1.9085/0.9232)	mem 16099MB
[2025-01-18 03:07:24 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][60/312]	eta 0:02:04 lr 0.002803	time 0.4568 (0.4929)	model_time 0.4564 (0.4629)	loss 3.7413 (3.3419)	grad_norm 1.0863 (1.8252/0.8737)	mem 16099MB
[2025-01-18 03:07:29 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][70/312]	eta 0:01:58 lr 0.002802	time 0.5323 (0.4902)	model_time 0.5318 (0.4644)	loss 4.3881 (3.3823)	grad_norm 1.0498 (1.8129/0.8445)	mem 16099MB
[2025-01-18 03:07:34 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][80/312]	eta 0:01:53 lr 0.002801	time 0.4504 (0.4876)	model_time 0.4500 (0.4649)	loss 3.6393 (3.4402)	grad_norm 2.6644 (1.7854/0.8102)	mem 16099MB
[2025-01-18 03:07:38 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][90/312]	eta 0:01:47 lr 0.002801	time 0.4578 (0.4851)	model_time 0.4576 (0.4649)	loss 2.9790 (3.4234)	grad_norm 1.8384 (1.7781/0.7885)	mem 16099MB
[2025-01-18 03:07:43 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][100/312]	eta 0:01:42 lr 0.002800	time 0.4697 (0.4833)	model_time 0.4695 (0.4650)	loss 4.0077 (3.4248)	grad_norm 3.9206 (1.7710/0.8029)	mem 16099MB
[2025-01-18 03:07:47 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][110/312]	eta 0:01:37 lr 0.002800	time 0.4457 (0.4803)	model_time 0.4453 (0.4636)	loss 3.8409 (3.4078)	grad_norm 2.3613 (1.8053/0.8239)	mem 16099MB
[2025-01-18 03:07:52 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][120/312]	eta 0:01:31 lr 0.002799	time 0.4454 (0.4786)	model_time 0.4450 (0.4633)	loss 4.1866 (3.4098)	grad_norm 1.2561 (1.7749/0.8050)	mem 16099MB
[2025-01-18 03:07:57 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][130/312]	eta 0:01:26 lr 0.002798	time 0.4633 (0.4772)	model_time 0.4631 (0.4630)	loss 3.3870 (3.4259)	grad_norm 1.3744 (1.7539/0.7945)	mem 16099MB
[2025-01-18 03:08:01 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][140/312]	eta 0:01:21 lr 0.002798	time 0.4786 (0.4762)	model_time 0.4781 (0.4630)	loss 4.2497 (3.4424)	grad_norm 2.0832 (1.7721/0.8081)	mem 16099MB
[2025-01-18 03:08:06 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][150/312]	eta 0:01:16 lr 0.002797	time 0.4449 (0.4745)	model_time 0.4444 (0.4622)	loss 3.4947 (3.4566)	grad_norm 0.9618 (1.7485/0.8155)	mem 16099MB
[2025-01-18 03:08:11 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][160/312]	eta 0:01:12 lr 0.002797	time 0.4472 (0.4757)	model_time 0.4467 (0.4641)	loss 3.1224 (3.4367)	grad_norm 1.4115 (1.7084/0.8069)	mem 16099MB
[2025-01-18 03:08:15 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][170/312]	eta 0:01:07 lr 0.002796	time 0.4547 (0.4744)	model_time 0.4543 (0.4635)	loss 3.4126 (3.4234)	grad_norm 2.5138 (1.7126/0.7920)	mem 16099MB
[2025-01-18 03:08:20 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][180/312]	eta 0:01:02 lr 0.002795	time 0.4446 (0.4733)	model_time 0.4445 (0.4629)	loss 4.2694 (3.4299)	grad_norm 1.1874 (1.6880/0.7795)	mem 16099MB
[2025-01-18 03:08:24 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][190/312]	eta 0:00:57 lr 0.002795	time 0.4670 (0.4721)	model_time 0.4666 (0.4623)	loss 2.7061 (3.4216)	grad_norm 1.3197 (1.6821/0.7704)	mem 16099MB
[2025-01-18 03:08:29 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][200/312]	eta 0:00:52 lr 0.002794	time 0.4505 (0.4721)	model_time 0.4504 (0.4627)	loss 3.6131 (3.4234)	grad_norm 1.6689 (1.6890/0.7691)	mem 16099MB
[2025-01-18 03:08:34 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][210/312]	eta 0:00:48 lr 0.002794	time 0.4760 (0.4717)	model_time 0.4756 (0.4627)	loss 3.9343 (3.4244)	grad_norm 2.2187 (1.6831/0.7578)	mem 16099MB
[2025-01-18 03:08:38 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][220/312]	eta 0:00:43 lr 0.002793	time 0.4505 (0.4711)	model_time 0.4504 (0.4625)	loss 4.2298 (3.4225)	grad_norm 0.8131 (1.6782/0.7516)	mem 16099MB
[2025-01-18 03:08:43 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][230/312]	eta 0:00:38 lr 0.002792	time 0.4423 (0.4707)	model_time 0.4418 (0.4625)	loss 3.5524 (3.4296)	grad_norm 1.7355 (1.6649/0.7427)	mem 16099MB
[2025-01-18 03:08:47 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][240/312]	eta 0:00:33 lr 0.002792	time 0.4433 (0.4700)	model_time 0.4428 (0.4621)	loss 3.4752 (3.4328)	grad_norm 1.1876 (1.6676/0.7418)	mem 16099MB
[2025-01-18 03:08:52 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][250/312]	eta 0:00:29 lr 0.002791	time 0.4516 (0.4699)	model_time 0.4514 (0.4623)	loss 3.2187 (3.4276)	grad_norm 1.9704 (1.6709/0.7375)	mem 16099MB
[2025-01-18 03:08:57 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][260/312]	eta 0:00:24 lr 0.002790	time 0.4786 (0.4696)	model_time 0.4784 (0.4623)	loss 3.6765 (3.4182)	grad_norm 1.5430 (1.6723/0.7358)	mem 16099MB
[2025-01-18 03:09:01 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][270/312]	eta 0:00:19 lr 0.002790	time 0.4617 (0.4690)	model_time 0.4615 (0.4620)	loss 3.9628 (3.4241)	grad_norm 2.4388 (1.6704/0.7271)	mem 16099MB
[2025-01-18 03:09:06 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][280/312]	eta 0:00:14 lr 0.002789	time 0.4631 (0.4686)	model_time 0.4627 (0.4618)	loss 4.1276 (3.4173)	grad_norm 1.7950 (1.6613/0.7207)	mem 16099MB
[2025-01-18 03:09:11 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][290/312]	eta 0:00:10 lr 0.002789	time 0.4523 (0.4688)	model_time 0.4521 (0.4622)	loss 3.1147 (3.4161)	grad_norm 2.6102 (1.6699/0.7191)	mem 16099MB
[2025-01-18 03:09:15 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][300/312]	eta 0:00:05 lr 0.002788	time 0.4385 (0.4686)	model_time 0.4384 (0.4622)	loss 3.0418 (3.4215)	grad_norm 1.6649 (1.6891/0.7444)	mem 16099MB
[2025-01-18 03:09:20 internimage_t_1k_224] (main.py 510): INFO Train: [111/300][310/312]	eta 0:00:00 lr 0.002787	time 0.5269 (0.4686)	model_time 0.5268 (0.4624)	loss 3.6228 (3.4123)	grad_norm 1.6909 (1.6876/0.7339)	mem 16099MB
[2025-01-18 03:09:20 internimage_t_1k_224] (main.py 519): INFO EPOCH 111 training takes 0:02:26
[2025-01-18 03:09:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_111.pth saving......
[2025-01-18 03:09:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_111.pth saved !!!
[2025-01-18 03:09:29 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.348 (7.348)	Loss 0.8714 (0.8714)	Acc@1 80.835 (80.835)	Acc@5 95.947 (95.947)	Mem 16099MB
[2025-01-18 03:09:33 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.992)	Loss 1.2178 (1.0237)	Acc@1 72.510 (77.559)	Acc@5 92.090 (94.349)	Mem 16099MB
[2025-01-18 03:09:33 internimage_t_1k_224] (main.py 575): INFO [Epoch:111] * Acc@1 77.465 Acc@5 94.348
[2025-01-18 03:09:33 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.5%
[2025-01-18 03:09:33 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.59%
[2025-01-18 03:09:41 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.350 (8.350)	Loss 0.8625 (0.8625)	Acc@1 81.250 (81.250)	Acc@5 96.289 (96.289)	Mem 16099MB
[2025-01-18 03:09:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.112)	Loss 1.2485 (1.0237)	Acc@1 72.070 (77.945)	Acc@5 91.699 (94.218)	Mem 16099MB
[2025-01-18 03:09:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:111] * Acc@1 77.835 Acc@5 94.238
[2025-01-18 03:09:45 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 77.8%
[2025-01-18 03:09:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:09:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:09:46 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 77.84%
[2025-01-18 03:09:49 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][0/312]	eta 0:11:41 lr 0.002787	time 2.2498 (2.2498)	model_time 0.4774 (0.4774)	loss 3.9132 (3.9132)	grad_norm 1.4619 (1.4619/0.0000)	mem 16099MB
[2025-01-18 03:09:53 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][10/312]	eta 0:03:08 lr 0.002787	time 0.4590 (0.6239)	model_time 0.4589 (0.4625)	loss 4.1812 (3.6362)	grad_norm 2.0132 (1.4238/0.5361)	mem 16099MB
[2025-01-18 03:09:58 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][20/312]	eta 0:02:40 lr 0.002786	time 0.4520 (0.5483)	model_time 0.4516 (0.4636)	loss 3.7454 (3.6043)	grad_norm 1.9257 (1.8570/0.8819)	mem 16099MB
[2025-01-18 03:10:03 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][30/312]	eta 0:02:27 lr 0.002785	time 0.4584 (0.5239)	model_time 0.4580 (0.4665)	loss 3.4775 (3.5824)	grad_norm 1.2223 (1.7142/0.7706)	mem 16099MB
[2025-01-18 03:10:07 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][40/312]	eta 0:02:19 lr 0.002785	time 0.4648 (0.5122)	model_time 0.4647 (0.4686)	loss 3.5675 (3.4515)	grad_norm 1.3125 (1.5990/0.7354)	mem 16099MB
[2025-01-18 03:10:12 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][50/312]	eta 0:02:11 lr 0.002784	time 0.4538 (0.5008)	model_time 0.4534 (0.4657)	loss 4.2043 (3.4148)	grad_norm 0.9773 (1.5759/0.7659)	mem 16099MB
[2025-01-18 03:10:17 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][60/312]	eta 0:02:04 lr 0.002784	time 0.4384 (0.4943)	model_time 0.4382 (0.4649)	loss 3.5095 (3.4251)	grad_norm 1.7350 (1.6151/0.7878)	mem 16099MB
[2025-01-18 03:10:21 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][70/312]	eta 0:01:58 lr 0.002783	time 0.4535 (0.4884)	model_time 0.4531 (0.4631)	loss 3.7504 (3.3934)	grad_norm 1.4128 (1.5752/0.7602)	mem 16099MB
[2025-01-18 03:10:26 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][80/312]	eta 0:01:52 lr 0.002782	time 0.4521 (0.4856)	model_time 0.4520 (0.4634)	loss 3.5331 (3.3817)	grad_norm 0.8483 (1.5192/0.7304)	mem 16099MB
[2025-01-18 03:10:30 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][90/312]	eta 0:01:47 lr 0.002782	time 0.5443 (0.4842)	model_time 0.5442 (0.4644)	loss 3.7942 (3.3608)	grad_norm 3.6502 (1.5107/0.7338)	mem 16099MB
[2025-01-18 03:10:35 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][100/312]	eta 0:01:41 lr 0.002781	time 0.4501 (0.4807)	model_time 0.4497 (0.4628)	loss 2.0723 (3.3525)	grad_norm 1.7320 (1.6141/0.8355)	mem 16099MB
[2025-01-18 03:10:39 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][110/312]	eta 0:01:36 lr 0.002781	time 0.4514 (0.4785)	model_time 0.4509 (0.4622)	loss 3.3645 (3.3530)	grad_norm 2.0891 (1.6851/0.8743)	mem 16099MB
[2025-01-18 03:10:44 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][120/312]	eta 0:01:31 lr 0.002780	time 0.4647 (0.4781)	model_time 0.4646 (0.4631)	loss 2.4098 (3.3397)	grad_norm 1.2883 (1.6768/0.8666)	mem 16099MB
[2025-01-18 03:10:49 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][130/312]	eta 0:01:26 lr 0.002779	time 0.4386 (0.4778)	model_time 0.4382 (0.4640)	loss 2.5213 (3.3540)	grad_norm 1.7900 (1.6508/0.8474)	mem 16099MB
[2025-01-18 03:10:54 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][140/312]	eta 0:01:22 lr 0.002779	time 0.4384 (0.4775)	model_time 0.4380 (0.4646)	loss 2.9440 (3.3363)	grad_norm 1.0108 (1.6319/0.8240)	mem 16099MB
[2025-01-18 03:10:59 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][150/312]	eta 0:01:17 lr 0.002778	time 0.4404 (0.4782)	model_time 0.4400 (0.4661)	loss 4.2801 (3.3575)	grad_norm 1.5962 (1.6054/0.8091)	mem 16099MB
[2025-01-18 03:11:03 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][160/312]	eta 0:01:12 lr 0.002777	time 0.4490 (0.4772)	model_time 0.4489 (0.4659)	loss 2.6963 (3.3472)	grad_norm 0.9235 (1.5694/0.7973)	mem 16099MB
[2025-01-18 03:11:08 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][170/312]	eta 0:01:07 lr 0.002777	time 0.4716 (0.4768)	model_time 0.4711 (0.4660)	loss 3.5874 (3.3581)	grad_norm 0.7875 (1.5753/0.7958)	mem 16099MB
[2025-01-18 03:11:13 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][180/312]	eta 0:01:02 lr 0.002776	time 0.5425 (0.4759)	model_time 0.5421 (0.4658)	loss 3.6701 (3.3758)	grad_norm 2.4313 (1.6061/0.8084)	mem 16099MB
[2025-01-18 03:11:17 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][190/312]	eta 0:00:57 lr 0.002776	time 0.4390 (0.4746)	model_time 0.4389 (0.4650)	loss 3.4236 (3.3918)	grad_norm 1.7460 (1.6214/0.7976)	mem 16099MB
[2025-01-18 03:11:22 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][200/312]	eta 0:00:53 lr 0.002775	time 0.4386 (0.4740)	model_time 0.4385 (0.4648)	loss 3.7955 (3.3959)	grad_norm 1.2049 (1.6008/0.7859)	mem 16099MB
[2025-01-18 03:11:26 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][210/312]	eta 0:00:48 lr 0.002774	time 0.4473 (0.4728)	model_time 0.4471 (0.4641)	loss 3.6266 (3.4007)	grad_norm 1.2131 (1.6038/0.7716)	mem 16099MB
[2025-01-18 03:11:31 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][220/312]	eta 0:00:43 lr 0.002774	time 0.4504 (0.4721)	model_time 0.4499 (0.4637)	loss 3.6530 (3.4017)	grad_norm 0.9516 (1.5919/0.7624)	mem 16099MB
[2025-01-18 03:11:35 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][230/312]	eta 0:00:38 lr 0.002773	time 0.4479 (0.4715)	model_time 0.4474 (0.4635)	loss 3.9278 (3.4081)	grad_norm 0.9164 (1.6006/0.7623)	mem 16099MB
[2025-01-18 03:11:40 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][240/312]	eta 0:00:33 lr 0.002773	time 0.5387 (0.4714)	model_time 0.5386 (0.4637)	loss 4.1750 (3.4167)	grad_norm 0.8745 (1.5912/0.7550)	mem 16099MB
[2025-01-18 03:11:45 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][250/312]	eta 0:00:29 lr 0.002772	time 0.4471 (0.4710)	model_time 0.4467 (0.4636)	loss 3.3864 (3.4240)	grad_norm 1.0989 (1.6039/0.7740)	mem 16099MB
[2025-01-18 03:11:49 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][260/312]	eta 0:00:24 lr 0.002771	time 0.4518 (0.4703)	model_time 0.4513 (0.4632)	loss 4.0517 (3.4299)	grad_norm 1.0714 (1.5929/0.7661)	mem 16099MB
[2025-01-18 03:11:54 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][270/312]	eta 0:00:19 lr 0.002771	time 0.4516 (0.4705)	model_time 0.4511 (0.4636)	loss 3.8083 (3.4283)	grad_norm 1.7515 (1.6026/0.7753)	mem 16099MB
[2025-01-18 03:11:59 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][280/312]	eta 0:00:15 lr 0.002770	time 0.4517 (0.4704)	model_time 0.4516 (0.4637)	loss 3.3899 (3.4254)	grad_norm 3.2144 (1.6546/0.8642)	mem 16099MB
[2025-01-18 03:12:03 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][290/312]	eta 0:00:10 lr 0.002769	time 0.4507 (0.4701)	model_time 0.4503 (0.4637)	loss 3.7123 (3.4240)	grad_norm 1.6073 (1.6615/0.8689)	mem 16099MB
[2025-01-18 03:12:08 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][300/312]	eta 0:00:05 lr 0.002769	time 0.4717 (0.4699)	model_time 0.4716 (0.4636)	loss 4.1862 (3.4275)	grad_norm 1.2630 (1.6428/0.8627)	mem 16099MB
[2025-01-18 03:12:13 internimage_t_1k_224] (main.py 510): INFO Train: [112/300][310/312]	eta 0:00:00 lr 0.002768	time 0.4380 (0.4702)	model_time 0.4379 (0.4642)	loss 3.6919 (3.4395)	grad_norm 1.1387 (1.6422/0.8593)	mem 16099MB
[2025-01-18 03:12:13 internimage_t_1k_224] (main.py 519): INFO EPOCH 112 training takes 0:02:26
[2025-01-18 03:12:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_112.pth saving......
[2025-01-18 03:12:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_112.pth saved !!!
[2025-01-18 03:12:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.362 (7.362)	Loss 0.9167 (0.9167)	Acc@1 80.469 (80.469)	Acc@5 96.021 (96.021)	Mem 16099MB
[2025-01-18 03:12:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.964)	Loss 1.2841 (1.0619)	Acc@1 72.290 (77.654)	Acc@5 91.895 (94.147)	Mem 16099MB
[2025-01-18 03:12:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:112] * Acc@1 77.587 Acc@5 94.152
[2025-01-18 03:12:25 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.6%
[2025-01-18 03:12:25 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.59%
[2025-01-18 03:12:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.375 (8.375)	Loss 0.8587 (0.8587)	Acc@1 81.396 (81.396)	Acc@5 96.313 (96.313)	Mem 16099MB
[2025-01-18 03:12:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.120)	Loss 1.2415 (1.0187)	Acc@1 72.241 (78.061)	Acc@5 91.772 (94.287)	Mem 16099MB
[2025-01-18 03:12:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:112] * Acc@1 77.949 Acc@5 94.308
[2025-01-18 03:12:38 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 77.9%
[2025-01-18 03:12:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:12:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:12:39 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 77.95%
[2025-01-18 03:12:41 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][0/312]	eta 0:11:31 lr 0.002768	time 2.2155 (2.2155)	model_time 0.4704 (0.4704)	loss 3.8543 (3.8543)	grad_norm 1.1656 (1.1656/0.0000)	mem 16099MB
[2025-01-18 03:12:46 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][10/312]	eta 0:03:08 lr 0.002768	time 0.4708 (0.6254)	model_time 0.4704 (0.4664)	loss 3.3209 (3.2875)	grad_norm 1.4988 (1.3338/0.1351)	mem 16099MB
[2025-01-18 03:12:50 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][20/312]	eta 0:02:40 lr 0.002767	time 0.4445 (0.5500)	model_time 0.4441 (0.4665)	loss 2.6552 (3.2635)	grad_norm 0.8464 (1.3412/0.3615)	mem 16099MB
[2025-01-18 03:12:55 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][30/312]	eta 0:02:27 lr 0.002766	time 0.4389 (0.5224)	model_time 0.4388 (0.4658)	loss 2.7461 (3.2389)	grad_norm 1.8765 (1.3468/0.3996)	mem 16099MB
[2025-01-18 03:12:59 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][40/312]	eta 0:02:17 lr 0.002766	time 0.4480 (0.5055)	model_time 0.4476 (0.4625)	loss 3.2229 (3.2591)	grad_norm 2.7163 (1.4955/0.4948)	mem 16099MB
[2025-01-18 03:13:04 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][50/312]	eta 0:02:10 lr 0.002765	time 0.4564 (0.4971)	model_time 0.4562 (0.4625)	loss 1.9595 (3.2690)	grad_norm 1.1737 (1.5704/0.5858)	mem 16099MB
[2025-01-18 03:13:09 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][60/312]	eta 0:02:03 lr 0.002764	time 0.4519 (0.4905)	model_time 0.4517 (0.4616)	loss 3.6239 (3.2923)	grad_norm 1.3986 (1.5553/0.5615)	mem 16099MB
[2025-01-18 03:13:13 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][70/312]	eta 0:01:57 lr 0.002764	time 0.4738 (0.4868)	model_time 0.4733 (0.4619)	loss 3.5254 (3.2823)	grad_norm 0.6958 (1.5992/0.5870)	mem 16099MB
[2025-01-18 03:13:18 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][80/312]	eta 0:01:52 lr 0.002763	time 0.4475 (0.4857)	model_time 0.4471 (0.4638)	loss 2.6615 (3.2782)	grad_norm 3.5001 (1.6361/0.6357)	mem 16099MB
[2025-01-18 03:13:23 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][90/312]	eta 0:01:47 lr 0.002763	time 0.5389 (0.4850)	model_time 0.5387 (0.4655)	loss 3.1499 (3.2770)	grad_norm 0.9218 (1.6303/0.6292)	mem 16099MB
[2025-01-18 03:13:27 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][100/312]	eta 0:01:42 lr 0.002762	time 0.4415 (0.4830)	model_time 0.4411 (0.4654)	loss 2.9112 (3.2546)	grad_norm 1.6621 (1.5972/0.6127)	mem 16099MB
[2025-01-18 03:13:32 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][110/312]	eta 0:01:37 lr 0.002761	time 0.4915 (0.4814)	model_time 0.4911 (0.4653)	loss 4.0005 (3.2618)	grad_norm 1.2046 (1.5822/0.5938)	mem 16099MB
[2025-01-18 03:13:37 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][120/312]	eta 0:01:32 lr 0.002761	time 0.4666 (0.4799)	model_time 0.4665 (0.4651)	loss 3.1166 (3.2580)	grad_norm 1.8730 (1.6165/0.6081)	mem 16099MB
[2025-01-18 03:13:41 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][130/312]	eta 0:01:26 lr 0.002760	time 0.4480 (0.4780)	model_time 0.4478 (0.4643)	loss 4.2857 (3.2683)	grad_norm 1.1769 (1.5964/0.5972)	mem 16099MB
[2025-01-18 03:13:46 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][140/312]	eta 0:01:22 lr 0.002760	time 0.5321 (0.4785)	model_time 0.5320 (0.4658)	loss 2.2730 (3.2412)	grad_norm 2.9055 (1.5999/0.6032)	mem 16099MB
[2025-01-18 03:13:51 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][150/312]	eta 0:01:17 lr 0.002759	time 0.4519 (0.4767)	model_time 0.4515 (0.4648)	loss 2.2193 (3.2435)	grad_norm 1.2941 (1.6139/0.6325)	mem 16099MB
[2025-01-18 03:13:56 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][160/312]	eta 0:01:12 lr 0.002758	time 0.5503 (0.4775)	model_time 0.5502 (0.4663)	loss 3.2514 (3.2544)	grad_norm 1.2029 (1.6274/0.6502)	mem 16099MB
[2025-01-18 03:14:00 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][170/312]	eta 0:01:07 lr 0.002758	time 0.4512 (0.4766)	model_time 0.4508 (0.4660)	loss 2.9820 (3.2670)	grad_norm 1.1510 (1.6130/0.6447)	mem 16099MB
[2025-01-18 03:14:05 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][180/312]	eta 0:01:02 lr 0.002757	time 0.4483 (0.4756)	model_time 0.4478 (0.4656)	loss 3.3097 (3.2794)	grad_norm 4.0850 (1.6075/0.6613)	mem 16099MB
[2025-01-18 03:14:09 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][190/312]	eta 0:00:57 lr 0.002756	time 0.4629 (0.4754)	model_time 0.4627 (0.4659)	loss 4.1225 (3.2872)	grad_norm 3.1150 (1.6253/0.6766)	mem 16099MB
[2025-01-18 03:14:14 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][200/312]	eta 0:00:53 lr 0.002756	time 0.4522 (0.4743)	model_time 0.4521 (0.4653)	loss 1.9352 (3.2826)	grad_norm 1.6697 (1.6339/0.6701)	mem 16099MB
[2025-01-18 03:14:19 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][210/312]	eta 0:00:48 lr 0.002755	time 0.4476 (0.4737)	model_time 0.4475 (0.4651)	loss 3.8527 (3.2919)	grad_norm 1.2545 (1.6280/0.6675)	mem 16099MB
[2025-01-18 03:14:23 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][220/312]	eta 0:00:43 lr 0.002755	time 0.4399 (0.4734)	model_time 0.4395 (0.4651)	loss 3.9186 (3.3016)	grad_norm 0.9010 (1.6313/0.6815)	mem 16099MB
[2025-01-18 03:14:28 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][230/312]	eta 0:00:38 lr 0.002754	time 0.4398 (0.4725)	model_time 0.4394 (0.4646)	loss 3.7590 (3.3085)	grad_norm 1.6041 (1.6558/0.7260)	mem 16099MB
[2025-01-18 03:14:32 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][240/312]	eta 0:00:33 lr 0.002753	time 0.4496 (0.4721)	model_time 0.4492 (0.4645)	loss 3.5143 (3.3071)	grad_norm 3.5471 (1.6637/0.7392)	mem 16099MB
[2025-01-18 03:14:37 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][250/312]	eta 0:00:29 lr 0.002753	time 0.4411 (0.4716)	model_time 0.4407 (0.4643)	loss 2.7180 (3.3055)	grad_norm 1.1890 (1.6540/0.7299)	mem 16099MB
[2025-01-18 03:14:42 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][260/312]	eta 0:00:24 lr 0.002752	time 0.4545 (0.4714)	model_time 0.4544 (0.4644)	loss 3.2473 (3.3162)	grad_norm 1.4686 (1.6538/0.7178)	mem 16099MB
[2025-01-18 03:14:46 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][270/312]	eta 0:00:19 lr 0.002751	time 0.4408 (0.4711)	model_time 0.4404 (0.4642)	loss 3.5951 (3.3201)	grad_norm 1.9263 (1.6422/0.7118)	mem 16099MB
[2025-01-18 03:14:51 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][280/312]	eta 0:00:15 lr 0.002751	time 0.4483 (0.4705)	model_time 0.4481 (0.4639)	loss 2.5922 (3.3079)	grad_norm 3.7877 (1.6639/0.7405)	mem 16099MB
[2025-01-18 03:14:56 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][290/312]	eta 0:00:10 lr 0.002750	time 0.4617 (0.4705)	model_time 0.4616 (0.4641)	loss 3.7575 (3.3142)	grad_norm 2.0271 (1.6676/0.7379)	mem 16099MB
[2025-01-18 03:15:00 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][300/312]	eta 0:00:05 lr 0.002750	time 0.4402 (0.4702)	model_time 0.4401 (0.4640)	loss 3.9413 (3.3158)	grad_norm 3.3025 (1.6686/0.7403)	mem 16099MB
[2025-01-18 03:15:05 internimage_t_1k_224] (main.py 510): INFO Train: [113/300][310/312]	eta 0:00:00 lr 0.002749	time 0.4389 (0.4696)	model_time 0.4389 (0.4636)	loss 3.7933 (3.3210)	grad_norm 1.3551 (1.6709/0.7420)	mem 16099MB
[2025-01-18 03:15:05 internimage_t_1k_224] (main.py 519): INFO EPOCH 113 training takes 0:02:26
[2025-01-18 03:15:05 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_113.pth saving......
[2025-01-18 03:15:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_113.pth saved !!!
[2025-01-18 03:15:14 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.437 (7.437)	Loss 0.8550 (0.8550)	Acc@1 81.030 (81.030)	Acc@5 96.191 (96.191)	Mem 16099MB
[2025-01-18 03:15:17 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.008)	Loss 1.2835 (1.0355)	Acc@1 70.435 (77.652)	Acc@5 92.065 (94.234)	Mem 16099MB
[2025-01-18 03:15:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:113] * Acc@1 77.641 Acc@5 94.258
[2025-01-18 03:15:18 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.6%
[2025-01-18 03:15:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 03:15:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 03:15:19 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.64%
[2025-01-18 03:15:26 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.336 (7.336)	Loss 0.8551 (0.8551)	Acc@1 81.543 (81.543)	Acc@5 96.484 (96.484)	Mem 16099MB
[2025-01-18 03:15:30 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.008)	Loss 1.2353 (1.0141)	Acc@1 72.339 (78.203)	Acc@5 91.895 (94.367)	Mem 16099MB
[2025-01-18 03:15:30 internimage_t_1k_224] (main.py 575): INFO [Epoch:113] * Acc@1 78.091 Acc@5 94.378
[2025-01-18 03:15:30 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 78.1%
[2025-01-18 03:15:30 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:15:31 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:15:31 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 78.09%
[2025-01-18 03:15:33 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][0/312]	eta 0:10:27 lr 0.002749	time 2.0120 (2.0120)	model_time 0.4703 (0.4703)	loss 2.6591 (2.6591)	grad_norm 1.3687 (1.3687/0.0000)	mem 16099MB
[2025-01-18 03:15:38 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][10/312]	eta 0:03:07 lr 0.002748	time 0.4626 (0.6225)	model_time 0.4622 (0.4820)	loss 3.4008 (3.3749)	grad_norm 2.6261 (1.6915/0.4976)	mem 16099MB
[2025-01-18 03:15:42 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][20/312]	eta 0:02:38 lr 0.002748	time 0.4518 (0.5425)	model_time 0.4514 (0.4687)	loss 3.1078 (3.3916)	grad_norm 1.6611 (1.7070/0.5216)	mem 16099MB
[2025-01-18 03:15:47 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][30/312]	eta 0:02:27 lr 0.002747	time 0.5681 (0.5248)	model_time 0.5679 (0.4747)	loss 3.4214 (3.3997)	grad_norm 1.4761 (1.7712/0.7110)	mem 16099MB
[2025-01-18 03:15:52 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][40/312]	eta 0:02:17 lr 0.002746	time 0.4524 (0.5073)	model_time 0.4520 (0.4694)	loss 3.5571 (3.4767)	grad_norm 1.9538 (1.7116/0.6710)	mem 16099MB
[2025-01-18 03:15:57 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][50/312]	eta 0:02:10 lr 0.002746	time 0.4409 (0.4987)	model_time 0.4407 (0.4681)	loss 3.4635 (3.4379)	grad_norm 1.0607 (1.6382/0.6476)	mem 16099MB
[2025-01-18 03:16:01 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][60/312]	eta 0:02:03 lr 0.002745	time 0.4397 (0.4913)	model_time 0.4393 (0.4657)	loss 3.6819 (3.4982)	grad_norm 0.9909 (1.5387/0.6403)	mem 16099MB
[2025-01-18 03:16:06 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][70/312]	eta 0:01:57 lr 0.002745	time 0.4450 (0.4867)	model_time 0.4446 (0.4647)	loss 3.6632 (3.4697)	grad_norm 1.3123 (1.5150/0.6166)	mem 16099MB
[2025-01-18 03:16:10 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][80/312]	eta 0:01:52 lr 0.002744	time 0.4508 (0.4831)	model_time 0.4504 (0.4637)	loss 3.7168 (3.4026)	grad_norm 0.8303 (1.5247/0.6318)	mem 16099MB
[2025-01-18 03:16:15 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][90/312]	eta 0:01:46 lr 0.002743	time 0.4819 (0.4804)	model_time 0.4818 (0.4631)	loss 4.1864 (3.4126)	grad_norm 1.7882 (1.5213/0.6449)	mem 16099MB
[2025-01-18 03:16:19 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][100/312]	eta 0:01:41 lr 0.002743	time 0.4488 (0.4773)	model_time 0.4486 (0.4617)	loss 2.8051 (3.3697)	grad_norm 1.7869 (1.5350/0.6324)	mem 16099MB
[2025-01-18 03:16:24 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][110/312]	eta 0:01:36 lr 0.002742	time 0.4444 (0.4761)	model_time 0.4442 (0.4618)	loss 2.8736 (3.3631)	grad_norm 0.9162 (1.5686/0.6552)	mem 16099MB
[2025-01-18 03:16:29 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][120/312]	eta 0:01:31 lr 0.002741	time 0.4514 (0.4759)	model_time 0.4510 (0.4628)	loss 2.1476 (3.3534)	grad_norm 1.4364 (1.5540/0.6401)	mem 16099MB
[2025-01-18 03:16:34 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][130/312]	eta 0:01:26 lr 0.002741	time 0.4451 (0.4767)	model_time 0.4450 (0.4646)	loss 3.0901 (3.3642)	grad_norm 1.6813 (1.5466/0.6221)	mem 16099MB
[2025-01-18 03:16:38 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][140/312]	eta 0:01:21 lr 0.002740	time 0.4387 (0.4757)	model_time 0.4382 (0.4644)	loss 3.6039 (3.3641)	grad_norm 2.2630 (1.5620/0.6220)	mem 16099MB
[2025-01-18 03:16:43 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][150/312]	eta 0:01:17 lr 0.002740	time 0.4543 (0.4763)	model_time 0.4541 (0.4657)	loss 2.5693 (3.3388)	grad_norm 3.2550 (1.6294/0.7225)	mem 16099MB
[2025-01-18 03:16:48 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][160/312]	eta 0:01:12 lr 0.002739	time 0.5323 (0.4757)	model_time 0.5321 (0.4658)	loss 3.4783 (3.3469)	grad_norm 1.4277 (1.6426/0.7197)	mem 16099MB
[2025-01-18 03:16:52 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][170/312]	eta 0:01:07 lr 0.002738	time 0.4882 (0.4745)	model_time 0.4878 (0.4651)	loss 3.4425 (3.3329)	grad_norm 1.3181 (1.6309/0.7051)	mem 16099MB
[2025-01-18 03:16:57 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][180/312]	eta 0:01:02 lr 0.002738	time 0.4517 (0.4744)	model_time 0.4512 (0.4656)	loss 3.4672 (3.3387)	grad_norm 1.3035 (1.6251/0.6902)	mem 16099MB
[2025-01-18 03:17:02 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][190/312]	eta 0:00:57 lr 0.002737	time 0.4385 (0.4738)	model_time 0.4383 (0.4653)	loss 2.8545 (3.3585)	grad_norm 1.0159 (1.6373/0.6969)	mem 16099MB
[2025-01-18 03:17:06 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][200/312]	eta 0:00:53 lr 0.002737	time 0.4474 (0.4736)	model_time 0.4473 (0.4655)	loss 2.6956 (3.3301)	grad_norm 0.8775 (1.6492/0.6946)	mem 16099MB
[2025-01-18 03:17:11 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][210/312]	eta 0:00:48 lr 0.002736	time 0.4445 (0.4727)	model_time 0.4440 (0.4650)	loss 3.2900 (3.3277)	grad_norm 0.9264 (1.6296/0.6902)	mem 16099MB
[2025-01-18 03:17:15 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][220/312]	eta 0:00:43 lr 0.002735	time 0.4546 (0.4721)	model_time 0.4542 (0.4647)	loss 3.3443 (3.3354)	grad_norm 0.9014 (1.6022/0.6869)	mem 16099MB
[2025-01-18 03:17:20 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][230/312]	eta 0:00:38 lr 0.002735	time 0.4969 (0.4716)	model_time 0.4965 (0.4646)	loss 3.5823 (3.3447)	grad_norm 1.6510 (1.5938/0.6815)	mem 16099MB
[2025-01-18 03:17:25 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][240/312]	eta 0:00:33 lr 0.002734	time 0.4399 (0.4709)	model_time 0.4395 (0.4641)	loss 3.4500 (3.3451)	grad_norm 0.8101 (1.5996/0.6854)	mem 16099MB
[2025-01-18 03:17:29 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][250/312]	eta 0:00:29 lr 0.002733	time 0.4686 (0.4703)	model_time 0.4685 (0.4636)	loss 2.9621 (3.3440)	grad_norm 1.1553 (1.5966/0.6810)	mem 16099MB
[2025-01-18 03:17:34 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][260/312]	eta 0:00:24 lr 0.002733	time 0.4451 (0.4696)	model_time 0.4447 (0.4631)	loss 3.4555 (3.3487)	grad_norm 1.5897 (1.6035/0.6769)	mem 16099MB
[2025-01-18 03:17:38 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][270/312]	eta 0:00:19 lr 0.002732	time 0.4446 (0.4696)	model_time 0.4442 (0.4634)	loss 3.3539 (3.3484)	grad_norm 3.2456 (1.6232/0.6823)	mem 16099MB
[2025-01-18 03:17:43 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][280/312]	eta 0:00:15 lr 0.002732	time 0.4486 (0.4692)	model_time 0.4484 (0.4632)	loss 2.9183 (3.3517)	grad_norm 1.9424 (1.6383/0.6957)	mem 16099MB
[2025-01-18 03:17:48 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][290/312]	eta 0:00:10 lr 0.002731	time 0.4516 (0.4693)	model_time 0.4511 (0.4635)	loss 3.3380 (3.3418)	grad_norm 1.1107 (1.6300/0.6883)	mem 16099MB
[2025-01-18 03:17:52 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][300/312]	eta 0:00:05 lr 0.002730	time 0.4373 (0.4692)	model_time 0.4372 (0.4635)	loss 2.7145 (3.3368)	grad_norm 1.4982 (1.6381/0.6838)	mem 16099MB
[2025-01-18 03:17:57 internimage_t_1k_224] (main.py 510): INFO Train: [114/300][310/312]	eta 0:00:00 lr 0.002730	time 0.4449 (0.4694)	model_time 0.4448 (0.4639)	loss 2.4290 (3.3403)	grad_norm 1.1428 (1.6287/0.6834)	mem 16099MB
[2025-01-18 03:17:58 internimage_t_1k_224] (main.py 519): INFO EPOCH 114 training takes 0:02:26
[2025-01-18 03:17:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_114.pth saving......
[2025-01-18 03:17:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_114.pth saved !!!
[2025-01-18 03:18:06 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.379 (7.379)	Loss 0.9312 (0.9312)	Acc@1 81.250 (81.250)	Acc@5 96.265 (96.265)	Mem 16099MB
[2025-01-18 03:18:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.988)	Loss 1.2369 (1.0701)	Acc@1 73.486 (77.754)	Acc@5 92.432 (94.303)	Mem 16099MB
[2025-01-18 03:18:10 internimage_t_1k_224] (main.py 575): INFO [Epoch:114] * Acc@1 77.705 Acc@5 94.374
[2025-01-18 03:18:10 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.7%
[2025-01-18 03:18:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 03:18:11 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 03:18:11 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.71%
[2025-01-18 03:18:18 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.247 (7.247)	Loss 0.8515 (0.8515)	Acc@1 81.592 (81.592)	Acc@5 96.582 (96.582)	Mem 16099MB
[2025-01-18 03:18:22 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.987)	Loss 1.2290 (1.0095)	Acc@1 72.314 (78.300)	Acc@5 92.017 (94.442)	Mem 16099MB
[2025-01-18 03:18:22 internimage_t_1k_224] (main.py 575): INFO [Epoch:114] * Acc@1 78.187 Acc@5 94.468
[2025-01-18 03:18:22 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 78.2%
[2025-01-18 03:18:22 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:18:23 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:18:23 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 78.19%
[2025-01-18 03:18:25 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][0/312]	eta 0:12:17 lr 0.002730	time 2.3627 (2.3627)	model_time 0.4610 (0.4610)	loss 2.5087 (2.5087)	grad_norm 0.8137 (0.8137/0.0000)	mem 16099MB
[2025-01-18 03:18:30 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][10/312]	eta 0:03:16 lr 0.002729	time 0.5410 (0.6507)	model_time 0.5409 (0.4776)	loss 2.5311 (3.0513)	grad_norm 1.2029 (1.0819/0.2148)	mem 16099MB
[2025-01-18 03:18:35 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][20/312]	eta 0:02:43 lr 0.002728	time 0.4504 (0.5616)	model_time 0.4503 (0.4707)	loss 3.0510 (3.1158)	grad_norm 0.9795 (1.4016/0.4725)	mem 16099MB
[2025-01-18 03:18:40 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][30/312]	eta 0:02:29 lr 0.002728	time 0.5421 (0.5310)	model_time 0.5419 (0.4693)	loss 3.2590 (3.2067)	grad_norm 2.0527 (1.6109/0.7376)	mem 16099MB
[2025-01-18 03:18:44 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][40/312]	eta 0:02:21 lr 0.002727	time 0.4510 (0.5194)	model_time 0.4506 (0.4727)	loss 3.5148 (3.2210)	grad_norm 1.4588 (1.7387/0.7915)	mem 16099MB
[2025-01-18 03:18:49 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][50/312]	eta 0:02:12 lr 0.002726	time 0.4547 (0.5065)	model_time 0.4545 (0.4689)	loss 2.6610 (3.2110)	grad_norm 2.1417 (1.6353/0.7577)	mem 16099MB
[2025-01-18 03:18:54 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][60/312]	eta 0:02:05 lr 0.002726	time 0.4544 (0.4983)	model_time 0.4542 (0.4668)	loss 3.7031 (3.2568)	grad_norm 1.6144 (1.6627/0.7115)	mem 16099MB
[2025-01-18 03:18:58 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][70/312]	eta 0:01:59 lr 0.002725	time 0.4452 (0.4944)	model_time 0.4447 (0.4672)	loss 2.1615 (3.2627)	grad_norm 1.3263 (1.6338/0.6932)	mem 16099MB
[2025-01-18 03:19:03 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][80/312]	eta 0:01:53 lr 0.002725	time 0.4608 (0.4903)	model_time 0.4607 (0.4665)	loss 3.6435 (3.3245)	grad_norm 1.5577 (1.6709/0.7077)	mem 16099MB
[2025-01-18 03:19:07 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][90/312]	eta 0:01:48 lr 0.002724	time 0.4462 (0.4869)	model_time 0.4456 (0.4656)	loss 2.2555 (3.2932)	grad_norm 1.5298 (1.7216/0.7536)	mem 16099MB
[2025-01-18 03:19:12 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][100/312]	eta 0:01:42 lr 0.002723	time 0.4470 (0.4850)	model_time 0.4466 (0.4658)	loss 2.6014 (3.2550)	grad_norm 1.1566 (1.6830/0.7313)	mem 16099MB
[2025-01-18 03:19:17 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][110/312]	eta 0:01:37 lr 0.002723	time 0.4566 (0.4829)	model_time 0.4564 (0.4654)	loss 4.0088 (3.2694)	grad_norm 1.0118 (1.6455/0.7155)	mem 16099MB
[2025-01-18 03:19:21 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][120/312]	eta 0:01:32 lr 0.002722	time 0.5407 (0.4816)	model_time 0.5405 (0.4655)	loss 2.5679 (3.2540)	grad_norm 1.2001 (1.6225/0.6980)	mem 16099MB
[2025-01-18 03:19:26 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][130/312]	eta 0:01:27 lr 0.002721	time 0.4967 (0.4801)	model_time 0.4965 (0.4652)	loss 3.2083 (3.2569)	grad_norm 0.7723 (1.6641/0.7385)	mem 16099MB
[2025-01-18 03:19:31 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][140/312]	eta 0:01:22 lr 0.002721	time 0.5729 (0.4798)	model_time 0.5725 (0.4659)	loss 2.3201 (3.2550)	grad_norm 1.3684 (1.6944/0.7760)	mem 16099MB
[2025-01-18 03:19:35 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][150/312]	eta 0:01:17 lr 0.002720	time 0.4620 (0.4785)	model_time 0.4616 (0.4656)	loss 3.5602 (3.2773)	grad_norm 1.2232 (1.6650/0.7621)	mem 16099MB
[2025-01-18 03:19:40 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][160/312]	eta 0:01:12 lr 0.002720	time 0.4470 (0.4774)	model_time 0.4468 (0.4653)	loss 4.3922 (3.2918)	grad_norm 0.9005 (1.6671/0.7605)	mem 16099MB
[2025-01-18 03:19:45 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][170/312]	eta 0:01:07 lr 0.002719	time 0.4813 (0.4766)	model_time 0.4811 (0.4651)	loss 2.5489 (3.3032)	grad_norm 2.0972 (1.6722/0.7630)	mem 16099MB
[2025-01-18 03:19:49 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][180/312]	eta 0:01:02 lr 0.002718	time 0.4398 (0.4763)	model_time 0.4393 (0.4654)	loss 4.1214 (3.3065)	grad_norm 1.3207 (1.6707/0.7439)	mem 16099MB
[2025-01-18 03:19:54 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][190/312]	eta 0:00:57 lr 0.002718	time 0.4547 (0.4750)	model_time 0.4545 (0.4646)	loss 3.4068 (3.3088)	grad_norm 1.3478 (1.6615/0.7316)	mem 16099MB
[2025-01-18 03:19:58 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][200/312]	eta 0:00:53 lr 0.002717	time 0.4547 (0.4739)	model_time 0.4545 (0.4641)	loss 2.1833 (3.2955)	grad_norm 1.5464 (1.6643/0.7358)	mem 16099MB
[2025-01-18 03:20:03 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][210/312]	eta 0:00:48 lr 0.002717	time 0.4507 (0.4738)	model_time 0.4505 (0.4645)	loss 3.2942 (3.3039)	grad_norm 2.1236 (1.6807/0.7570)	mem 16099MB
[2025-01-18 03:20:08 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][220/312]	eta 0:00:43 lr 0.002716	time 0.4507 (0.4733)	model_time 0.4502 (0.4643)	loss 3.1052 (3.2985)	grad_norm 1.1961 (1.6886/0.7661)	mem 16099MB
[2025-01-18 03:20:12 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][230/312]	eta 0:00:38 lr 0.002715	time 0.4502 (0.4728)	model_time 0.4498 (0.4642)	loss 3.4950 (3.3018)	grad_norm 0.8296 (1.6835/0.7569)	mem 16099MB
[2025-01-18 03:20:17 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][240/312]	eta 0:00:34 lr 0.002715	time 0.4396 (0.4727)	model_time 0.4394 (0.4645)	loss 3.9325 (3.3035)	grad_norm 1.4515 (1.7124/0.7783)	mem 16099MB
[2025-01-18 03:20:22 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][250/312]	eta 0:00:29 lr 0.002714	time 0.4599 (0.4722)	model_time 0.4597 (0.4643)	loss 2.2754 (3.2969)	grad_norm 0.7625 (1.6874/0.7748)	mem 16099MB
[2025-01-18 03:20:26 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][260/312]	eta 0:00:24 lr 0.002713	time 0.4451 (0.4715)	model_time 0.4446 (0.4639)	loss 2.4944 (3.2991)	grad_norm 1.8012 (1.6833/0.7637)	mem 16099MB
[2025-01-18 03:20:31 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][270/312]	eta 0:00:19 lr 0.002713	time 0.4521 (0.4712)	model_time 0.4517 (0.4638)	loss 3.2342 (3.2993)	grad_norm 0.9342 (1.6706/0.7557)	mem 16099MB
[2025-01-18 03:20:36 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][280/312]	eta 0:00:15 lr 0.002712	time 0.4722 (0.4719)	model_time 0.4718 (0.4647)	loss 4.3645 (3.3146)	grad_norm 1.0285 (1.6532/0.7507)	mem 16099MB
[2025-01-18 03:20:40 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][290/312]	eta 0:00:10 lr 0.002712	time 0.4498 (0.4715)	model_time 0.4493 (0.4645)	loss 3.9782 (3.3114)	grad_norm 1.5769 (1.6720/0.7537)	mem 16099MB
[2025-01-18 03:20:45 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][300/312]	eta 0:00:05 lr 0.002711	time 0.4379 (0.4707)	model_time 0.4378 (0.4640)	loss 2.2566 (3.3073)	grad_norm 0.6339 (1.6677/0.7512)	mem 16099MB
[2025-01-18 03:20:49 internimage_t_1k_224] (main.py 510): INFO Train: [115/300][310/312]	eta 0:00:00 lr 0.002710	time 0.4396 (0.4705)	model_time 0.4396 (0.4641)	loss 3.2727 (3.3145)	grad_norm 0.9699 (1.6719/0.7492)	mem 16099MB
[2025-01-18 03:20:50 internimage_t_1k_224] (main.py 519): INFO EPOCH 115 training takes 0:02:26
[2025-01-18 03:20:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_115.pth saving......
[2025-01-18 03:20:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_115.pth saved !!!
[2025-01-18 03:20:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.210 (7.210)	Loss 0.9139 (0.9139)	Acc@1 80.981 (80.981)	Acc@5 95.825 (95.825)	Mem 16099MB
[2025-01-18 03:21:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.961)	Loss 1.2521 (1.0810)	Acc@1 73.193 (77.634)	Acc@5 92.236 (94.098)	Mem 16099MB
[2025-01-18 03:21:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:115] * Acc@1 77.459 Acc@5 94.082
[2025-01-18 03:21:02 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.5%
[2025-01-18 03:21:02 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.71%
[2025-01-18 03:21:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.106 (8.106)	Loss 0.8487 (0.8487)	Acc@1 81.738 (81.738)	Acc@5 96.655 (96.655)	Mem 16099MB
[2025-01-18 03:21:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.079)	Loss 1.2236 (1.0054)	Acc@1 72.461 (78.416)	Acc@5 92.017 (94.491)	Mem 16099MB
[2025-01-18 03:21:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:115] * Acc@1 78.293 Acc@5 94.518
[2025-01-18 03:21:14 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 78.3%
[2025-01-18 03:21:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:21:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:21:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 78.29%
[2025-01-18 03:21:17 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][0/312]	eta 0:12:21 lr 0.002710	time 2.3772 (2.3772)	model_time 0.4797 (0.4797)	loss 3.4234 (3.4234)	grad_norm 1.7998 (1.7998/0.0000)	mem 16099MB
[2025-01-18 03:21:22 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][10/312]	eta 0:03:15 lr 0.002710	time 0.4638 (0.6487)	model_time 0.4637 (0.4759)	loss 3.1806 (3.2435)	grad_norm 3.5396 (2.2002/1.0228)	mem 16099MB
[2025-01-18 03:21:27 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][20/312]	eta 0:02:43 lr 0.002709	time 0.4401 (0.5583)	model_time 0.4399 (0.4677)	loss 4.0827 (3.3078)	grad_norm 1.4270 (1.7331/0.9109)	mem 16099MB
[2025-01-18 03:21:32 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][30/312]	eta 0:02:29 lr 0.002708	time 0.4944 (0.5309)	model_time 0.4943 (0.4694)	loss 3.0822 (3.3208)	grad_norm 0.9055 (1.5751/0.8204)	mem 16099MB
[2025-01-18 03:21:36 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][40/312]	eta 0:02:21 lr 0.002708	time 0.5561 (0.5197)	model_time 0.5556 (0.4731)	loss 3.5662 (3.2897)	grad_norm 3.4003 (1.7342/0.9266)	mem 16099MB
[2025-01-18 03:21:41 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][50/312]	eta 0:02:12 lr 0.002707	time 0.4534 (0.5071)	model_time 0.4532 (0.4696)	loss 2.4894 (3.3023)	grad_norm 1.5492 (1.7744/0.9013)	mem 16099MB
[2025-01-18 03:21:46 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][60/312]	eta 0:02:07 lr 0.002706	time 0.4435 (0.5048)	model_time 0.4430 (0.4733)	loss 2.6742 (3.3138)	grad_norm 0.8594 (1.7367/0.8894)	mem 16099MB
[2025-01-18 03:21:50 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][70/312]	eta 0:02:00 lr 0.002706	time 0.4560 (0.4975)	model_time 0.4558 (0.4704)	loss 3.1310 (3.3422)	grad_norm 2.5708 (1.7197/0.8707)	mem 16099MB
[2025-01-18 03:21:55 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][80/312]	eta 0:01:54 lr 0.002705	time 0.4473 (0.4943)	model_time 0.4469 (0.4706)	loss 3.4395 (3.3628)	grad_norm 2.0034 (1.7852/0.8561)	mem 16099MB
[2025-01-18 03:22:00 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][90/312]	eta 0:01:48 lr 0.002705	time 0.4463 (0.4902)	model_time 0.4462 (0.4691)	loss 3.1793 (3.3754)	grad_norm 0.9530 (1.7546/0.8299)	mem 16099MB
[2025-01-18 03:22:05 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][100/312]	eta 0:01:43 lr 0.002704	time 0.5835 (0.4896)	model_time 0.5833 (0.4705)	loss 2.2205 (3.3694)	grad_norm 1.7506 (1.7278/0.8030)	mem 16099MB
[2025-01-18 03:22:09 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][110/312]	eta 0:01:38 lr 0.002703	time 0.4548 (0.4869)	model_time 0.4546 (0.4695)	loss 3.6668 (3.3699)	grad_norm 1.2679 (1.7243/0.7908)	mem 16099MB
[2025-01-18 03:22:14 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][120/312]	eta 0:01:33 lr 0.002703	time 0.4562 (0.4848)	model_time 0.4557 (0.4688)	loss 2.9193 (3.3541)	grad_norm 0.9428 (1.7146/0.7909)	mem 16099MB
[2025-01-18 03:22:18 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][130/312]	eta 0:01:28 lr 0.002702	time 0.4546 (0.4836)	model_time 0.4545 (0.4688)	loss 3.5763 (3.3426)	grad_norm 3.3164 (1.7771/0.8228)	mem 16099MB
[2025-01-18 03:22:23 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][140/312]	eta 0:01:22 lr 0.002701	time 0.4744 (0.4820)	model_time 0.4740 (0.4682)	loss 2.8016 (3.3385)	grad_norm 1.0297 (1.7538/0.8273)	mem 16099MB
[2025-01-18 03:22:28 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][150/312]	eta 0:01:17 lr 0.002701	time 0.4505 (0.4805)	model_time 0.4503 (0.4677)	loss 2.8912 (3.3131)	grad_norm 1.4977 (1.7318/0.8101)	mem 16099MB
[2025-01-18 03:22:32 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][160/312]	eta 0:01:12 lr 0.002700	time 0.4484 (0.4798)	model_time 0.4482 (0.4677)	loss 3.5914 (3.3162)	grad_norm 1.0431 (1.7122/0.7969)	mem 16099MB
[2025-01-18 03:22:37 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][170/312]	eta 0:01:08 lr 0.002700	time 0.4493 (0.4800)	model_time 0.4491 (0.4685)	loss 3.3111 (3.3121)	grad_norm 1.0668 (1.6836/0.7893)	mem 16099MB
[2025-01-18 03:22:42 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][180/312]	eta 0:01:03 lr 0.002699	time 0.4580 (0.4787)	model_time 0.4576 (0.4679)	loss 3.4302 (3.3218)	grad_norm 1.5673 (1.7082/0.8193)	mem 16099MB
[2025-01-18 03:22:46 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][190/312]	eta 0:00:58 lr 0.002698	time 0.4529 (0.4773)	model_time 0.4525 (0.4670)	loss 4.2691 (3.3255)	grad_norm 1.0163 (1.7031/0.8105)	mem 16099MB
[2025-01-18 03:22:51 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][200/312]	eta 0:00:53 lr 0.002698	time 0.4473 (0.4764)	model_time 0.4469 (0.4666)	loss 3.2838 (3.3109)	grad_norm 0.7976 (1.7112/0.8113)	mem 16099MB
[2025-01-18 03:22:55 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][210/312]	eta 0:00:48 lr 0.002697	time 0.4637 (0.4754)	model_time 0.4635 (0.4661)	loss 2.2439 (3.3132)	grad_norm 0.8214 (1.7175/0.8204)	mem 16099MB
[2025-01-18 03:23:00 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][220/312]	eta 0:00:43 lr 0.002696	time 0.4500 (0.4753)	model_time 0.4495 (0.4663)	loss 2.3546 (3.3169)	grad_norm 1.7712 (1.7015/0.8110)	mem 16099MB
[2025-01-18 03:23:05 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][230/312]	eta 0:00:38 lr 0.002696	time 0.4508 (0.4743)	model_time 0.4504 (0.4658)	loss 2.6360 (3.3225)	grad_norm 1.3375 (1.6989/0.7973)	mem 16099MB
[2025-01-18 03:23:09 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][240/312]	eta 0:00:34 lr 0.002695	time 0.4592 (0.4746)	model_time 0.4588 (0.4664)	loss 3.7772 (3.3268)	grad_norm 2.5309 (1.6897/0.7898)	mem 16099MB
[2025-01-18 03:23:14 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][250/312]	eta 0:00:29 lr 0.002695	time 0.4537 (0.4746)	model_time 0.4536 (0.4667)	loss 3.5532 (3.3329)	grad_norm 2.2735 (1.6828/0.7795)	mem 16099MB
[2025-01-18 03:23:19 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][260/312]	eta 0:00:24 lr 0.002694	time 0.4532 (0.4741)	model_time 0.4527 (0.4664)	loss 3.1392 (3.3330)	grad_norm 1.1154 (1.6899/0.7747)	mem 16099MB
[2025-01-18 03:23:24 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][270/312]	eta 0:00:19 lr 0.002693	time 0.5655 (0.4739)	model_time 0.5653 (0.4666)	loss 4.0584 (3.3356)	grad_norm 3.8350 (1.7063/0.7831)	mem 16099MB
[2025-01-18 03:23:28 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][280/312]	eta 0:00:15 lr 0.002693	time 0.4404 (0.4745)	model_time 0.4400 (0.4674)	loss 4.2948 (3.3294)	grad_norm 2.8397 (1.7146/0.7793)	mem 16099MB
[2025-01-18 03:23:33 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][290/312]	eta 0:00:10 lr 0.002692	time 0.4474 (0.4739)	model_time 0.4469 (0.4671)	loss 3.5715 (3.3229)	grad_norm 1.7066 (1.7128/0.7706)	mem 16099MB
[2025-01-18 03:23:38 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][300/312]	eta 0:00:05 lr 0.002691	time 0.4377 (0.4741)	model_time 0.4376 (0.4674)	loss 2.7330 (3.3246)	grad_norm 1.7154 (1.6875/0.7730)	mem 16099MB
[2025-01-18 03:23:42 internimage_t_1k_224] (main.py 510): INFO Train: [116/300][310/312]	eta 0:00:00 lr 0.002691	time 0.4423 (0.4731)	model_time 0.4422 (0.4667)	loss 3.6144 (3.3296)	grad_norm 1.0008 (1.6569/0.7464)	mem 16099MB
[2025-01-18 03:23:43 internimage_t_1k_224] (main.py 519): INFO EPOCH 116 training takes 0:02:27
[2025-01-18 03:23:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_116.pth saving......
[2025-01-18 03:23:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_116.pth saved !!!
[2025-01-18 03:23:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.191 (7.191)	Loss 0.8662 (0.8662)	Acc@1 80.566 (80.566)	Acc@5 95.923 (95.923)	Mem 16099MB
[2025-01-18 03:23:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.989)	Loss 1.2475 (1.0201)	Acc@1 72.632 (77.876)	Acc@5 91.943 (94.314)	Mem 16099MB
[2025-01-18 03:23:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:116] * Acc@1 77.785 Acc@5 94.348
[2025-01-18 03:23:55 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.8%
[2025-01-18 03:23:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 03:23:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 03:23:56 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.79%
[2025-01-18 03:24:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.547 (7.547)	Loss 0.8458 (0.8458)	Acc@1 81.714 (81.714)	Acc@5 96.704 (96.704)	Mem 16099MB
[2025-01-18 03:24:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.004)	Loss 1.2185 (1.0016)	Acc@1 72.729 (78.538)	Acc@5 92.065 (94.553)	Mem 16099MB
[2025-01-18 03:24:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:116] * Acc@1 78.419 Acc@5 94.572
[2025-01-18 03:24:07 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 78.4%
[2025-01-18 03:24:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:24:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:24:09 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 78.42%
[2025-01-18 03:24:11 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][0/312]	eta 0:12:09 lr 0.002691	time 2.3372 (2.3372)	model_time 0.4714 (0.4714)	loss 4.0448 (4.0448)	grad_norm 0.9319 (0.9319/0.0000)	mem 16099MB
[2025-01-18 03:24:16 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][10/312]	eta 0:03:16 lr 0.002690	time 0.5394 (0.6510)	model_time 0.5390 (0.4810)	loss 2.4858 (3.4495)	grad_norm 1.2982 (1.9222/1.1603)	mem 16099MB
[2025-01-18 03:24:20 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][20/312]	eta 0:02:45 lr 0.002689	time 0.4514 (0.5673)	model_time 0.4510 (0.4781)	loss 2.6140 (3.4875)	grad_norm 1.0335 (1.6197/0.9184)	mem 16099MB
[2025-01-18 03:24:25 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][30/312]	eta 0:02:31 lr 0.002689	time 0.4480 (0.5357)	model_time 0.4478 (0.4752)	loss 2.2845 (3.3387)	grad_norm 2.5806 (2.0121/1.3303)	mem 16099MB
[2025-01-18 03:24:30 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][40/312]	eta 0:02:21 lr 0.002688	time 0.4654 (0.5202)	model_time 0.4650 (0.4743)	loss 3.2119 (3.3464)	grad_norm 2.1700 (1.9015/1.2055)	mem 16099MB
[2025-01-18 03:24:34 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][50/312]	eta 0:02:13 lr 0.002688	time 0.4436 (0.5088)	model_time 0.4432 (0.4719)	loss 3.3242 (3.3397)	grad_norm 0.8325 (1.8447/1.1377)	mem 16099MB
[2025-01-18 03:24:39 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][60/312]	eta 0:02:06 lr 0.002687	time 0.4527 (0.5023)	model_time 0.4526 (0.4714)	loss 3.9758 (3.3100)	grad_norm 0.7179 (1.7156/1.0904)	mem 16099MB
[2025-01-18 03:24:44 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][70/312]	eta 0:01:59 lr 0.002686	time 0.4513 (0.4959)	model_time 0.4509 (0.4692)	loss 3.6296 (3.3541)	grad_norm 1.0423 (1.6370/1.0368)	mem 16099MB
[2025-01-18 03:24:48 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][80/312]	eta 0:01:53 lr 0.002686	time 0.4483 (0.4908)	model_time 0.4479 (0.4674)	loss 3.7632 (3.3396)	grad_norm 0.8530 (1.6468/1.0076)	mem 16099MB
[2025-01-18 03:24:53 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][90/312]	eta 0:01:48 lr 0.002685	time 0.4440 (0.4884)	model_time 0.4439 (0.4676)	loss 3.4955 (3.3566)	grad_norm 1.6549 (1.6029/0.9686)	mem 16099MB
[2025-01-18 03:24:58 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][100/312]	eta 0:01:43 lr 0.002684	time 0.4584 (0.4868)	model_time 0.4583 (0.4680)	loss 3.6613 (3.3799)	grad_norm 0.7007 (1.6068/0.9519)	mem 16099MB
[2025-01-18 03:25:02 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][110/312]	eta 0:01:38 lr 0.002684	time 0.4937 (0.4852)	model_time 0.4935 (0.4680)	loss 3.2917 (3.3725)	grad_norm 1.1410 (1.6250/0.9566)	mem 16099MB
[2025-01-18 03:25:07 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][120/312]	eta 0:01:32 lr 0.002683	time 0.4745 (0.4832)	model_time 0.4743 (0.4674)	loss 3.2568 (3.3592)	grad_norm 1.5404 (1.6084/0.9225)	mem 16099MB
[2025-01-18 03:25:12 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][130/312]	eta 0:01:27 lr 0.002683	time 0.4553 (0.4814)	model_time 0.4552 (0.4668)	loss 3.1979 (3.3374)	grad_norm 1.3824 (1.6267/0.9132)	mem 16099MB
[2025-01-18 03:25:16 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][140/312]	eta 0:01:22 lr 0.002682	time 0.4486 (0.4804)	model_time 0.4484 (0.4668)	loss 2.3372 (3.3361)	grad_norm 2.1455 (1.5989/0.8927)	mem 16099MB
[2025-01-18 03:25:21 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][150/312]	eta 0:01:17 lr 0.002681	time 0.5478 (0.4796)	model_time 0.5476 (0.4669)	loss 3.3360 (3.3499)	grad_norm 1.2488 (1.6334/0.9583)	mem 16099MB
[2025-01-18 03:25:26 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][160/312]	eta 0:01:12 lr 0.002681	time 0.4539 (0.4791)	model_time 0.4538 (0.4671)	loss 2.8768 (3.3628)	grad_norm 1.2009 (1.6364/0.9470)	mem 16099MB
[2025-01-18 03:25:30 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][170/312]	eta 0:01:07 lr 0.002680	time 0.4496 (0.4775)	model_time 0.4494 (0.4662)	loss 3.9926 (3.3652)	grad_norm 0.8716 (1.6237/0.9236)	mem 16099MB
[2025-01-18 03:25:35 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][180/312]	eta 0:01:02 lr 0.002679	time 0.4611 (0.4762)	model_time 0.4607 (0.4655)	loss 3.6812 (3.3500)	grad_norm 1.1467 (1.6119/0.9082)	mem 16099MB
[2025-01-18 03:25:40 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][190/312]	eta 0:00:58 lr 0.002679	time 0.4507 (0.4767)	model_time 0.4502 (0.4666)	loss 2.8823 (3.3498)	grad_norm 1.1916 (1.5899/0.8923)	mem 16099MB
[2025-01-18 03:25:44 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][200/312]	eta 0:00:53 lr 0.002678	time 0.4655 (0.4761)	model_time 0.4653 (0.4665)	loss 3.1703 (3.3439)	grad_norm 2.3457 (1.6122/0.8931)	mem 16099MB
[2025-01-18 03:25:49 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][210/312]	eta 0:00:48 lr 0.002678	time 0.4687 (0.4757)	model_time 0.4686 (0.4665)	loss 2.4055 (3.3320)	grad_norm 0.8054 (1.6469/0.9380)	mem 16099MB
[2025-01-18 03:25:54 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][220/312]	eta 0:00:43 lr 0.002677	time 0.4487 (0.4752)	model_time 0.4485 (0.4664)	loss 3.8624 (3.3482)	grad_norm 1.4922 (1.6462/0.9211)	mem 16099MB
[2025-01-18 03:25:58 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][230/312]	eta 0:00:38 lr 0.002676	time 0.4433 (0.4743)	model_time 0.4428 (0.4659)	loss 2.6815 (3.3333)	grad_norm 1.1177 (1.6395/0.9063)	mem 16099MB
[2025-01-18 03:26:03 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][240/312]	eta 0:00:34 lr 0.002676	time 0.4704 (0.4739)	model_time 0.4700 (0.4658)	loss 3.6706 (3.3328)	grad_norm 0.9313 (1.6359/0.8942)	mem 16099MB
[2025-01-18 03:26:07 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][250/312]	eta 0:00:29 lr 0.002675	time 0.4421 (0.4735)	model_time 0.4419 (0.4657)	loss 4.0344 (3.3434)	grad_norm 2.4120 (1.6519/0.8923)	mem 16099MB
[2025-01-18 03:26:12 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][260/312]	eta 0:00:24 lr 0.002674	time 0.4622 (0.4736)	model_time 0.4621 (0.4661)	loss 3.1609 (3.3526)	grad_norm 1.7147 (1.6461/0.8822)	mem 16099MB
[2025-01-18 03:26:17 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][270/312]	eta 0:00:19 lr 0.002674	time 0.4545 (0.4729)	model_time 0.4541 (0.4656)	loss 3.1012 (3.3550)	grad_norm 1.8222 (1.6341/0.8713)	mem 16099MB
[2025-01-18 03:26:21 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][280/312]	eta 0:00:15 lr 0.002673	time 0.4821 (0.4723)	model_time 0.4819 (0.4653)	loss 3.5277 (3.3469)	grad_norm 4.0625 (1.6612/0.8810)	mem 16099MB
[2025-01-18 03:26:26 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][290/312]	eta 0:00:10 lr 0.002673	time 0.4615 (0.4721)	model_time 0.4609 (0.4653)	loss 3.4542 (3.3498)	grad_norm 1.4630 (1.6855/0.8919)	mem 16099MB
[2025-01-18 03:26:30 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][300/312]	eta 0:00:05 lr 0.002672	time 0.4368 (0.4712)	model_time 0.4367 (0.4646)	loss 3.0716 (3.3451)	grad_norm 1.0632 (1.6812/0.8809)	mem 16099MB
[2025-01-18 03:26:35 internimage_t_1k_224] (main.py 510): INFO Train: [117/300][310/312]	eta 0:00:00 lr 0.002671	time 0.4385 (0.4703)	model_time 0.4384 (0.4640)	loss 3.4270 (3.3376)	grad_norm 1.6666 (1.6606/0.8561)	mem 16099MB
[2025-01-18 03:26:35 internimage_t_1k_224] (main.py 519): INFO EPOCH 117 training takes 0:02:26
[2025-01-18 03:26:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_117.pth saving......
[2025-01-18 03:26:37 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_117.pth saved !!!
[2025-01-18 03:26:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.126 (7.126)	Loss 0.8774 (0.8774)	Acc@1 81.250 (81.250)	Acc@5 96.265 (96.265)	Mem 16099MB
[2025-01-18 03:26:47 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.953)	Loss 1.2540 (1.0400)	Acc@1 73.193 (78.034)	Acc@5 92.505 (94.414)	Mem 16099MB
[2025-01-18 03:26:47 internimage_t_1k_224] (main.py 575): INFO [Epoch:117] * Acc@1 77.933 Acc@5 94.436
[2025-01-18 03:26:47 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.9%
[2025-01-18 03:26:47 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 03:26:48 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 03:26:48 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.93%
[2025-01-18 03:26:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.342 (7.342)	Loss 0.8438 (0.8438)	Acc@1 81.738 (81.738)	Acc@5 96.753 (96.753)	Mem 16099MB
[2025-01-18 03:26:59 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.979)	Loss 1.2140 (0.9982)	Acc@1 72.754 (78.635)	Acc@5 92.139 (94.607)	Mem 16099MB
[2025-01-18 03:26:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:117] * Acc@1 78.519 Acc@5 94.634
[2025-01-18 03:26:59 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 78.5%
[2025-01-18 03:26:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:27:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:27:00 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 78.52%
[2025-01-18 03:27:03 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][0/312]	eta 0:11:43 lr 0.002671	time 2.2547 (2.2547)	model_time 0.4613 (0.4613)	loss 3.9934 (3.9934)	grad_norm 1.6393 (1.6393/0.0000)	mem 16099MB
[2025-01-18 03:27:07 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][10/312]	eta 0:03:14 lr 0.002671	time 0.4527 (0.6453)	model_time 0.4523 (0.4819)	loss 3.4354 (3.4679)	grad_norm 1.0825 (1.4817/0.3719)	mem 16099MB
[2025-01-18 03:27:12 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][20/312]	eta 0:02:44 lr 0.002670	time 0.4491 (0.5633)	model_time 0.4487 (0.4775)	loss 4.0057 (3.2991)	grad_norm 1.2315 (1.4110/0.2938)	mem 16099MB
[2025-01-18 03:27:17 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][30/312]	eta 0:02:29 lr 0.002669	time 0.4576 (0.5300)	model_time 0.4571 (0.4718)	loss 2.3744 (3.3725)	grad_norm 0.9331 (1.3669/0.3012)	mem 16099MB
[2025-01-18 03:27:21 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][40/312]	eta 0:02:19 lr 0.002669	time 0.4679 (0.5116)	model_time 0.4677 (0.4674)	loss 3.7279 (3.3493)	grad_norm 1.7479 (1.7843/1.0865)	mem 16099MB
[2025-01-18 03:27:26 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][50/312]	eta 0:02:12 lr 0.002668	time 0.4862 (0.5059)	model_time 0.4860 (0.4703)	loss 3.5736 (3.3993)	grad_norm 1.0452 (1.7496/1.0054)	mem 16099MB
[2025-01-18 03:27:31 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][60/312]	eta 0:02:07 lr 0.002667	time 0.4492 (0.5047)	model_time 0.4490 (0.4750)	loss 3.3794 (3.3897)	grad_norm 1.1197 (1.6302/0.9617)	mem 16099MB
[2025-01-18 03:27:36 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][70/312]	eta 0:02:00 lr 0.002667	time 0.4644 (0.4995)	model_time 0.4642 (0.4739)	loss 3.5658 (3.4032)	grad_norm 2.8507 (1.5667/0.9308)	mem 16099MB
[2025-01-18 03:27:40 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][80/312]	eta 0:01:54 lr 0.002666	time 0.4533 (0.4945)	model_time 0.4531 (0.4720)	loss 3.6868 (3.4040)	grad_norm 2.1421 (1.6107/0.9531)	mem 16099MB
[2025-01-18 03:27:45 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][90/312]	eta 0:01:49 lr 0.002666	time 0.4424 (0.4918)	model_time 0.4422 (0.4717)	loss 2.2899 (3.3814)	grad_norm 1.0191 (1.6206/0.9327)	mem 16099MB
[2025-01-18 03:27:50 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][100/312]	eta 0:01:43 lr 0.002665	time 0.4489 (0.4886)	model_time 0.4487 (0.4705)	loss 3.6751 (3.3961)	grad_norm 0.8945 (1.6254/0.9027)	mem 16099MB
[2025-01-18 03:27:54 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][110/312]	eta 0:01:38 lr 0.002664	time 0.4389 (0.4865)	model_time 0.4385 (0.4700)	loss 2.8097 (3.3702)	grad_norm 2.2108 (1.6332/0.8845)	mem 16099MB
[2025-01-18 03:27:59 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][120/312]	eta 0:01:33 lr 0.002664	time 0.5333 (0.4855)	model_time 0.5329 (0.4703)	loss 4.0994 (3.4163)	grad_norm 1.4801 (1.6102/0.8558)	mem 16099MB
[2025-01-18 03:28:04 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][130/312]	eta 0:01:27 lr 0.002663	time 0.4470 (0.4834)	model_time 0.4465 (0.4694)	loss 3.4084 (3.3863)	grad_norm 1.3178 (1.5852/0.8366)	mem 16099MB
[2025-01-18 03:28:09 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][140/312]	eta 0:01:23 lr 0.002662	time 0.4483 (0.4838)	model_time 0.4482 (0.4707)	loss 2.9316 (3.3719)	grad_norm 0.8022 (1.5534/0.8181)	mem 16099MB
[2025-01-18 03:28:13 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][150/312]	eta 0:01:18 lr 0.002662	time 0.4468 (0.4833)	model_time 0.4466 (0.4710)	loss 3.4990 (3.3926)	grad_norm 2.7839 (1.5645/0.8134)	mem 16099MB
[2025-01-18 03:28:18 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][160/312]	eta 0:01:13 lr 0.002661	time 0.4639 (0.4819)	model_time 0.4635 (0.4704)	loss 4.0243 (3.3851)	grad_norm 1.2110 (1.5941/0.8201)	mem 16099MB
[2025-01-18 03:28:22 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][170/312]	eta 0:01:08 lr 0.002660	time 0.4560 (0.4803)	model_time 0.4554 (0.4695)	loss 2.9459 (3.3967)	grad_norm 1.9478 (1.5938/0.8041)	mem 16099MB
[2025-01-18 03:28:27 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][180/312]	eta 0:01:03 lr 0.002660	time 0.4701 (0.4790)	model_time 0.4695 (0.4687)	loss 3.8115 (3.3995)	grad_norm 2.6534 (1.5901/0.7902)	mem 16099MB
[2025-01-18 03:28:32 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][190/312]	eta 0:00:58 lr 0.002659	time 0.4458 (0.4781)	model_time 0.4456 (0.4684)	loss 2.3552 (3.4007)	grad_norm 1.4245 (1.6150/0.8053)	mem 16099MB
[2025-01-18 03:28:36 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][200/312]	eta 0:00:53 lr 0.002659	time 0.4564 (0.4775)	model_time 0.4559 (0.4682)	loss 3.4803 (3.3910)	grad_norm 1.1968 (1.5918/0.7933)	mem 16099MB
[2025-01-18 03:28:41 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][210/312]	eta 0:00:48 lr 0.002658	time 0.4674 (0.4769)	model_time 0.4672 (0.4680)	loss 2.8834 (3.3773)	grad_norm 1.3944 (1.5778/0.7807)	mem 16099MB
[2025-01-18 03:28:45 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][220/312]	eta 0:00:43 lr 0.002657	time 0.4516 (0.4757)	model_time 0.4514 (0.4673)	loss 3.4538 (3.3767)	grad_norm 1.0302 (1.6016/0.7978)	mem 16099MB
[2025-01-18 03:28:50 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][230/312]	eta 0:00:38 lr 0.002657	time 0.4424 (0.4754)	model_time 0.4421 (0.4672)	loss 2.7622 (3.3649)	grad_norm 0.8582 (1.6235/0.8175)	mem 16099MB
[2025-01-18 03:28:55 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][240/312]	eta 0:00:34 lr 0.002656	time 0.4500 (0.4747)	model_time 0.4496 (0.4668)	loss 3.4868 (3.3623)	grad_norm 0.8499 (1.6197/0.8027)	mem 16099MB
[2025-01-18 03:28:59 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][250/312]	eta 0:00:29 lr 0.002655	time 0.4444 (0.4743)	model_time 0.4439 (0.4667)	loss 3.5097 (3.3599)	grad_norm 1.0747 (1.6185/0.7910)	mem 16099MB
[2025-01-18 03:29:04 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][260/312]	eta 0:00:24 lr 0.002655	time 0.4544 (0.4737)	model_time 0.4539 (0.4664)	loss 3.9625 (3.3631)	grad_norm 1.3925 (1.6189/0.7814)	mem 16099MB
[2025-01-18 03:29:09 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][270/312]	eta 0:00:19 lr 0.002654	time 0.4453 (0.4734)	model_time 0.4450 (0.4663)	loss 2.9443 (3.3573)	grad_norm 0.8785 (1.6092/0.7733)	mem 16099MB
[2025-01-18 03:29:13 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][280/312]	eta 0:00:15 lr 0.002654	time 0.5377 (0.4733)	model_time 0.5375 (0.4665)	loss 3.6865 (3.3502)	grad_norm 0.8620 (1.5887/0.7675)	mem 16099MB
[2025-01-18 03:29:18 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][290/312]	eta 0:00:10 lr 0.002653	time 0.4429 (0.4743)	model_time 0.4424 (0.4677)	loss 2.9889 (3.3468)	grad_norm 2.4413 (1.5869/0.7608)	mem 16099MB
[2025-01-18 03:29:23 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][300/312]	eta 0:00:05 lr 0.002652	time 0.4397 (0.4741)	model_time 0.4397 (0.4677)	loss 3.8353 (3.3557)	grad_norm 1.5581 (1.5909/0.7528)	mem 16099MB
[2025-01-18 03:29:28 internimage_t_1k_224] (main.py 510): INFO Train: [118/300][310/312]	eta 0:00:00 lr 0.002652	time 0.5381 (0.4744)	model_time 0.5380 (0.4683)	loss 2.2376 (3.3441)	grad_norm 1.1516 (1.5976/0.7561)	mem 16099MB
[2025-01-18 03:29:28 internimage_t_1k_224] (main.py 519): INFO EPOCH 118 training takes 0:02:28
[2025-01-18 03:29:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_118.pth saving......
[2025-01-18 03:29:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_118.pth saved !!!
[2025-01-18 03:29:37 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.205 (7.205)	Loss 0.8793 (0.8793)	Acc@1 80.640 (80.640)	Acc@5 95.825 (95.825)	Mem 16099MB
[2025-01-18 03:29:40 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.959)	Loss 1.2434 (1.0425)	Acc@1 72.827 (77.557)	Acc@5 91.797 (94.278)	Mem 16099MB
[2025-01-18 03:29:40 internimage_t_1k_224] (main.py 575): INFO [Epoch:118] * Acc@1 77.503 Acc@5 94.310
[2025-01-18 03:29:40 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 77.5%
[2025-01-18 03:29:40 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 77.93%
[2025-01-18 03:29:49 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.402 (8.402)	Loss 0.8419 (0.8419)	Acc@1 81.860 (81.860)	Acc@5 96.777 (96.777)	Mem 16099MB
[2025-01-18 03:29:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.097)	Loss 1.2098 (0.9951)	Acc@1 72.681 (78.711)	Acc@5 92.261 (94.642)	Mem 16099MB
[2025-01-18 03:29:53 internimage_t_1k_224] (main.py 575): INFO [Epoch:118] * Acc@1 78.609 Acc@5 94.670
[2025-01-18 03:29:53 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 78.6%
[2025-01-18 03:29:53 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:29:54 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:29:54 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 78.61%
[2025-01-18 03:29:56 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][0/312]	eta 0:12:59 lr 0.002652	time 2.4996 (2.4996)	model_time 0.6122 (0.6122)	loss 3.5924 (3.5924)	grad_norm 1.8155 (1.8155/0.0000)	mem 16099MB
[2025-01-18 03:30:01 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][10/312]	eta 0:03:16 lr 0.002651	time 0.4524 (0.6506)	model_time 0.4523 (0.4788)	loss 4.5082 (3.6572)	grad_norm 0.9545 (1.5759/0.8595)	mem 16099MB
[2025-01-18 03:30:06 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][20/312]	eta 0:02:43 lr 0.002650	time 0.4600 (0.5601)	model_time 0.4598 (0.4699)	loss 3.1485 (3.4690)	grad_norm 1.3229 (1.4813/0.7057)	mem 16099MB
[2025-01-18 03:30:10 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][30/312]	eta 0:02:28 lr 0.002650	time 0.4734 (0.5263)	model_time 0.4729 (0.4651)	loss 3.7354 (3.4688)	grad_norm 1.6237 (1.5472/0.6130)	mem 16099MB
[2025-01-18 03:30:15 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][40/312]	eta 0:02:18 lr 0.002649	time 0.4515 (0.5082)	model_time 0.4511 (0.4618)	loss 2.3038 (3.4010)	grad_norm 1.2407 (1.5416/0.5872)	mem 16099MB
[2025-01-18 03:30:19 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][50/312]	eta 0:02:11 lr 0.002648	time 0.4441 (0.5014)	model_time 0.4439 (0.4640)	loss 3.3337 (3.4640)	grad_norm 1.2244 (1.5996/0.6562)	mem 16099MB
[2025-01-18 03:30:24 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][60/312]	eta 0:02:04 lr 0.002648	time 0.4616 (0.4947)	model_time 0.4614 (0.4633)	loss 2.8614 (3.4473)	grad_norm 2.2535 (1.7564/0.8315)	mem 16099MB
[2025-01-18 03:30:29 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][70/312]	eta 0:01:58 lr 0.002647	time 0.4525 (0.4903)	model_time 0.4521 (0.4634)	loss 3.5943 (3.3863)	grad_norm 0.8031 (1.7013/0.7943)	mem 16099MB
[2025-01-18 03:30:33 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][80/312]	eta 0:01:52 lr 0.002646	time 0.4473 (0.4859)	model_time 0.4472 (0.4622)	loss 3.1822 (3.3559)	grad_norm 1.3112 (1.6495/0.7610)	mem 16099MB
[2025-01-18 03:30:38 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][90/312]	eta 0:01:47 lr 0.002646	time 0.5349 (0.4854)	model_time 0.5348 (0.4643)	loss 3.7308 (3.3676)	grad_norm 0.9990 (1.6390/0.7596)	mem 16099MB
[2025-01-18 03:30:43 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][100/312]	eta 0:01:42 lr 0.002645	time 0.4607 (0.4829)	model_time 0.4603 (0.4638)	loss 3.0557 (3.3620)	grad_norm 2.2086 (1.6615/0.7496)	mem 16099MB
[2025-01-18 03:30:47 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][110/312]	eta 0:01:37 lr 0.002645	time 0.4405 (0.4809)	model_time 0.4401 (0.4635)	loss 3.4102 (3.3676)	grad_norm 1.6360 (1.6767/0.7839)	mem 16099MB
[2025-01-18 03:30:52 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][120/312]	eta 0:01:32 lr 0.002644	time 0.5566 (0.4797)	model_time 0.5562 (0.4638)	loss 3.4100 (3.3497)	grad_norm 0.8455 (1.6631/0.7734)	mem 16099MB
[2025-01-18 03:30:57 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][130/312]	eta 0:01:27 lr 0.002643	time 0.5597 (0.4807)	model_time 0.5595 (0.4659)	loss 3.4526 (3.3460)	grad_norm 2.3995 (1.6677/0.7578)	mem 16099MB
[2025-01-18 03:31:01 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][140/312]	eta 0:01:22 lr 0.002643	time 0.4489 (0.4787)	model_time 0.4484 (0.4650)	loss 2.6709 (3.3531)	grad_norm 1.0085 (1.6327/0.7434)	mem 16099MB
[2025-01-18 03:31:06 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][150/312]	eta 0:01:17 lr 0.002642	time 0.4504 (0.4781)	model_time 0.4503 (0.4652)	loss 3.4431 (3.3594)	grad_norm 0.8959 (1.6110/0.7268)	mem 16099MB
[2025-01-18 03:31:11 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][160/312]	eta 0:01:12 lr 0.002641	time 0.5447 (0.4788)	model_time 0.5443 (0.4667)	loss 2.5709 (3.3735)	grad_norm 3.3135 (1.6416/0.7465)	mem 16099MB
[2025-01-18 03:31:16 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][170/312]	eta 0:01:08 lr 0.002641	time 0.4541 (0.4791)	model_time 0.4539 (0.4677)	loss 4.0173 (3.3704)	grad_norm 1.2005 (1.6458/0.7420)	mem 16099MB
[2025-01-18 03:31:20 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][180/312]	eta 0:01:03 lr 0.002640	time 0.4494 (0.4784)	model_time 0.4490 (0.4676)	loss 3.7565 (3.3769)	grad_norm 3.0852 (1.6483/0.7488)	mem 16099MB
[2025-01-18 03:31:25 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][190/312]	eta 0:00:58 lr 0.002640	time 0.4499 (0.4777)	model_time 0.4495 (0.4675)	loss 3.6336 (3.3855)	grad_norm 1.1418 (1.6676/0.7880)	mem 16099MB
[2025-01-18 03:31:30 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][200/312]	eta 0:00:53 lr 0.002639	time 0.4407 (0.4783)	model_time 0.4403 (0.4685)	loss 3.3060 (3.3907)	grad_norm 1.5610 (1.6915/0.8281)	mem 16099MB
[2025-01-18 03:31:35 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][210/312]	eta 0:00:48 lr 0.002638	time 0.4811 (0.4773)	model_time 0.4809 (0.4680)	loss 2.6326 (3.3758)	grad_norm 2.7504 (1.7023/0.8310)	mem 16099MB
[2025-01-18 03:31:39 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][220/312]	eta 0:00:43 lr 0.002638	time 0.4495 (0.4767)	model_time 0.4490 (0.4678)	loss 3.3045 (3.3832)	grad_norm 0.9839 (1.6870/0.8263)	mem 16099MB
[2025-01-18 03:31:44 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][230/312]	eta 0:00:39 lr 0.002637	time 0.5444 (0.4764)	model_time 0.5443 (0.4678)	loss 3.2644 (3.3816)	grad_norm 1.1473 (1.6681/0.8168)	mem 16099MB
[2025-01-18 03:31:49 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][240/312]	eta 0:00:34 lr 0.002636	time 0.4484 (0.4764)	model_time 0.4480 (0.4682)	loss 2.9419 (3.3749)	grad_norm 1.9013 (1.6668/0.8104)	mem 16099MB
[2025-01-18 03:31:53 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][250/312]	eta 0:00:29 lr 0.002636	time 0.4495 (0.4755)	model_time 0.4494 (0.4676)	loss 3.6540 (3.3656)	grad_norm 1.2088 (1.6536/0.7997)	mem 16099MB
[2025-01-18 03:31:58 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][260/312]	eta 0:00:24 lr 0.002635	time 0.4483 (0.4745)	model_time 0.4482 (0.4669)	loss 3.6078 (3.3729)	grad_norm 0.6401 (1.6380/0.7921)	mem 16099MB
[2025-01-18 03:32:02 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][270/312]	eta 0:00:19 lr 0.002635	time 0.4545 (0.4737)	model_time 0.4544 (0.4663)	loss 4.1509 (3.3784)	grad_norm 2.8563 (1.6383/0.7899)	mem 16099MB
[2025-01-18 03:32:07 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][280/312]	eta 0:00:15 lr 0.002634	time 0.4555 (0.4730)	model_time 0.4554 (0.4659)	loss 3.7668 (3.3726)	grad_norm 2.8650 (1.6467/0.7840)	mem 16099MB
[2025-01-18 03:32:12 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][290/312]	eta 0:00:10 lr 0.002633	time 0.4611 (0.4737)	model_time 0.4610 (0.4669)	loss 3.4818 (3.3740)	grad_norm 0.6642 (1.6467/0.7930)	mem 16099MB
[2025-01-18 03:32:16 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][300/312]	eta 0:00:05 lr 0.002633	time 0.4378 (0.4731)	model_time 0.4377 (0.4665)	loss 2.6694 (3.3739)	grad_norm 1.0900 (1.6303/0.7866)	mem 16099MB
[2025-01-18 03:32:21 internimage_t_1k_224] (main.py 510): INFO Train: [119/300][310/312]	eta 0:00:00 lr 0.002632	time 0.4412 (0.4721)	model_time 0.4411 (0.4657)	loss 3.0708 (3.3654)	grad_norm 1.6122 (1.6375/0.7728)	mem 16099MB
[2025-01-18 03:32:21 internimage_t_1k_224] (main.py 519): INFO EPOCH 119 training takes 0:02:27
[2025-01-18 03:32:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_119.pth saving......
[2025-01-18 03:32:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_119.pth saved !!!
[2025-01-18 03:32:30 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.273 (7.273)	Loss 0.8635 (0.8635)	Acc@1 81.323 (81.323)	Acc@5 95.801 (95.801)	Mem 16099MB
[2025-01-18 03:32:33 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.971)	Loss 1.1973 (1.0000)	Acc@1 73.071 (78.078)	Acc@5 92.212 (94.287)	Mem 16099MB
[2025-01-18 03:32:33 internimage_t_1k_224] (main.py 575): INFO [Epoch:119] * Acc@1 78.039 Acc@5 94.346
[2025-01-18 03:32:33 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.0%
[2025-01-18 03:32:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 03:32:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 03:32:34 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.04%
[2025-01-18 03:32:41 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.159 (7.159)	Loss 0.8394 (0.8394)	Acc@1 81.885 (81.885)	Acc@5 96.777 (96.777)	Mem 16099MB
[2025-01-18 03:32:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.985)	Loss 1.2053 (0.9919)	Acc@1 72.754 (78.771)	Acc@5 92.261 (94.662)	Mem 16099MB
[2025-01-18 03:32:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:119] * Acc@1 78.671 Acc@5 94.692
[2025-01-18 03:32:45 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 78.7%
[2025-01-18 03:32:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:32:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:32:46 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 78.67%
[2025-01-18 03:32:49 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][0/312]	eta 0:13:15 lr 0.002632	time 2.5496 (2.5496)	model_time 0.5314 (0.5314)	loss 3.9666 (3.9666)	grad_norm 1.2743 (1.2743/0.0000)	mem 16099MB
[2025-01-18 03:32:54 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][10/312]	eta 0:03:21 lr 0.002631	time 0.4511 (0.6660)	model_time 0.4508 (0.4822)	loss 3.8690 (3.3463)	grad_norm 1.2714 (1.8288/0.8656)	mem 16099MB
[2025-01-18 03:32:59 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][20/312]	eta 0:02:48 lr 0.002631	time 0.4574 (0.5781)	model_time 0.4570 (0.4816)	loss 3.3052 (3.2820)	grad_norm 0.9561 (1.9096/0.9439)	mem 16099MB
[2025-01-18 03:33:03 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][30/312]	eta 0:02:32 lr 0.002630	time 0.4575 (0.5422)	model_time 0.4569 (0.4767)	loss 1.8863 (3.2503)	grad_norm 0.7905 (1.9043/0.9357)	mem 16099MB
[2025-01-18 03:33:08 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][40/312]	eta 0:02:21 lr 0.002629	time 0.4483 (0.5213)	model_time 0.4479 (0.4717)	loss 3.1553 (3.2619)	grad_norm 1.8471 (1.7391/0.8772)	mem 16099MB
[2025-01-18 03:33:12 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][50/312]	eta 0:02:13 lr 0.002629	time 0.4427 (0.5097)	model_time 0.4426 (0.4698)	loss 3.1618 (3.2448)	grad_norm 1.1764 (1.6657/0.8162)	mem 16099MB
[2025-01-18 03:33:17 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][60/312]	eta 0:02:07 lr 0.002628	time 0.5556 (0.5043)	model_time 0.5554 (0.4708)	loss 3.9586 (3.2252)	grad_norm 0.9734 (1.6445/0.7783)	mem 16099MB
[2025-01-18 03:33:22 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][70/312]	eta 0:02:00 lr 0.002627	time 0.4475 (0.4971)	model_time 0.4471 (0.4683)	loss 4.1392 (3.2660)	grad_norm 3.9751 (1.6530/0.8259)	mem 16099MB
[2025-01-18 03:33:26 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][80/312]	eta 0:01:54 lr 0.002627	time 0.4419 (0.4944)	model_time 0.4417 (0.4691)	loss 3.4610 (3.2579)	grad_norm 1.2830 (1.6897/0.8266)	mem 16099MB
[2025-01-18 03:33:31 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][90/312]	eta 0:01:48 lr 0.002626	time 0.4788 (0.4907)	model_time 0.4786 (0.4682)	loss 3.9871 (3.2747)	grad_norm 1.8461 (1.6925/0.7925)	mem 16099MB
[2025-01-18 03:33:36 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][100/312]	eta 0:01:43 lr 0.002626	time 0.4505 (0.4881)	model_time 0.4500 (0.4678)	loss 4.0142 (3.2760)	grad_norm 0.7292 (1.6677/0.7801)	mem 16099MB
[2025-01-18 03:33:40 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][110/312]	eta 0:01:38 lr 0.002625	time 0.4516 (0.4858)	model_time 0.4515 (0.4673)	loss 3.4461 (3.2831)	grad_norm 2.2708 (1.7053/0.7753)	mem 16099MB
[2025-01-18 03:33:45 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][120/312]	eta 0:01:32 lr 0.002624	time 0.4470 (0.4828)	model_time 0.4466 (0.4658)	loss 3.4069 (3.2900)	grad_norm 2.5728 (1.7346/0.7797)	mem 16099MB
[2025-01-18 03:33:50 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][130/312]	eta 0:01:27 lr 0.002624	time 0.4452 (0.4819)	model_time 0.4448 (0.4662)	loss 2.8395 (3.2912)	grad_norm 2.1281 (1.7541/0.7603)	mem 16099MB
[2025-01-18 03:33:55 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][140/312]	eta 0:01:23 lr 0.002623	time 0.4641 (0.4833)	model_time 0.4639 (0.4686)	loss 3.5712 (3.3068)	grad_norm 0.9665 (1.7560/0.7924)	mem 16099MB
[2025-01-18 03:33:59 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][150/312]	eta 0:01:18 lr 0.002622	time 0.4532 (0.4816)	model_time 0.4530 (0.4679)	loss 4.0952 (3.3213)	grad_norm 2.1177 (1.7486/0.7752)	mem 16099MB
[2025-01-18 03:34:04 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][160/312]	eta 0:01:13 lr 0.002622	time 0.4524 (0.4810)	model_time 0.4523 (0.4681)	loss 3.2638 (3.2959)	grad_norm 1.6351 (1.7392/0.7555)	mem 16099MB
[2025-01-18 03:34:09 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][170/312]	eta 0:01:08 lr 0.002621	time 0.5415 (0.4806)	model_time 0.5411 (0.4685)	loss 3.4095 (3.3050)	grad_norm 1.1186 (1.7214/0.7403)	mem 16099MB
[2025-01-18 03:34:14 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][180/312]	eta 0:01:03 lr 0.002620	time 0.4508 (0.4820)	model_time 0.4503 (0.4705)	loss 3.1038 (3.2972)	grad_norm 2.1158 (1.7091/0.7278)	mem 16099MB
[2025-01-18 03:34:18 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][190/312]	eta 0:00:58 lr 0.002620	time 0.4597 (0.4811)	model_time 0.4596 (0.4702)	loss 2.5512 (3.2958)	grad_norm 1.6899 (1.6916/0.7187)	mem 16099MB
[2025-01-18 03:34:23 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][200/312]	eta 0:00:53 lr 0.002619	time 0.4526 (0.4818)	model_time 0.4522 (0.4714)	loss 3.2758 (3.3146)	grad_norm 2.7935 (1.6764/0.7173)	mem 16099MB
[2025-01-18 03:34:28 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][210/312]	eta 0:00:48 lr 0.002619	time 0.4502 (0.4803)	model_time 0.4500 (0.4704)	loss 2.5723 (3.3284)	grad_norm 1.3834 (1.6800/0.7099)	mem 16099MB
[2025-01-18 03:34:32 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][220/312]	eta 0:00:44 lr 0.002618	time 0.4937 (0.4792)	model_time 0.4935 (0.4697)	loss 3.6168 (3.3331)	grad_norm 2.7920 (1.6847/0.7124)	mem 16099MB
[2025-01-18 03:34:37 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][230/312]	eta 0:00:39 lr 0.002617	time 0.4473 (0.4785)	model_time 0.4471 (0.4694)	loss 3.4934 (3.3364)	grad_norm 1.0707 (1.6689/0.7042)	mem 16099MB
[2025-01-18 03:34:42 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][240/312]	eta 0:00:34 lr 0.002617	time 0.5458 (0.4778)	model_time 0.5456 (0.4691)	loss 2.7377 (3.3276)	grad_norm 2.1415 (1.6790/0.7138)	mem 16099MB
[2025-01-18 03:34:46 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][250/312]	eta 0:00:29 lr 0.002616	time 0.4679 (0.4781)	model_time 0.4678 (0.4697)	loss 3.3057 (3.3397)	grad_norm 1.9175 (1.6785/0.7051)	mem 16099MB
[2025-01-18 03:34:51 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][260/312]	eta 0:00:24 lr 0.002615	time 0.4443 (0.4776)	model_time 0.4439 (0.4695)	loss 3.5720 (3.3406)	grad_norm 2.0256 (1.6747/0.6957)	mem 16099MB
[2025-01-18 03:34:56 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][270/312]	eta 0:00:20 lr 0.002615	time 0.4647 (0.4771)	model_time 0.4645 (0.4693)	loss 2.4254 (3.3388)	grad_norm 1.4323 (1.6869/0.6986)	mem 16099MB
[2025-01-18 03:35:00 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][280/312]	eta 0:00:15 lr 0.002614	time 0.4544 (0.4762)	model_time 0.4539 (0.4687)	loss 3.1627 (3.3458)	grad_norm 1.7831 (1.6858/0.6898)	mem 16099MB
[2025-01-18 03:35:05 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][290/312]	eta 0:00:10 lr 0.002613	time 0.4448 (0.4757)	model_time 0.4444 (0.4684)	loss 3.7775 (3.3465)	grad_norm 1.2814 (1.6771/0.6813)	mem 16099MB
[2025-01-18 03:35:10 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][300/312]	eta 0:00:05 lr 0.002613	time 0.4377 (0.4754)	model_time 0.4376 (0.4683)	loss 2.5789 (3.3425)	grad_norm 1.6999 (1.7114/0.7576)	mem 16099MB
[2025-01-18 03:35:14 internimage_t_1k_224] (main.py 510): INFO Train: [120/300][310/312]	eta 0:00:00 lr 0.002612	time 0.4384 (0.4748)	model_time 0.4383 (0.4680)	loss 2.4217 (3.3262)	grad_norm 1.0953 (1.6920/0.7454)	mem 16099MB
[2025-01-18 03:35:15 internimage_t_1k_224] (main.py 519): INFO EPOCH 120 training takes 0:02:28
[2025-01-18 03:35:15 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_120.pth saving......
[2025-01-18 03:35:16 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_120.pth saved !!!
[2025-01-18 03:35:23 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.246 (7.246)	Loss 0.8757 (0.8757)	Acc@1 81.470 (81.470)	Acc@5 95.874 (95.874)	Mem 16099MB
[2025-01-18 03:35:27 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.001)	Loss 1.2045 (1.0329)	Acc@1 74.414 (78.058)	Acc@5 92.407 (94.272)	Mem 16099MB
[2025-01-18 03:35:27 internimage_t_1k_224] (main.py 575): INFO [Epoch:120] * Acc@1 77.993 Acc@5 94.338
[2025-01-18 03:35:27 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.0%
[2025-01-18 03:35:27 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.04%
[2025-01-18 03:35:35 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.444 (8.444)	Loss 0.8372 (0.8372)	Acc@1 82.007 (82.007)	Acc@5 96.875 (96.875)	Mem 16099MB
[2025-01-18 03:35:39 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.122)	Loss 1.2012 (0.9890)	Acc@1 73.022 (78.904)	Acc@5 92.358 (94.724)	Mem 16099MB
[2025-01-18 03:35:39 internimage_t_1k_224] (main.py 575): INFO [Epoch:120] * Acc@1 78.803 Acc@5 94.750
[2025-01-18 03:35:39 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 78.8%
[2025-01-18 03:35:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:35:41 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:35:41 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 78.80%
[2025-01-18 03:35:43 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][0/312]	eta 0:12:49 lr 0.002612	time 2.4650 (2.4650)	model_time 0.4849 (0.4849)	loss 3.3244 (3.3244)	grad_norm 1.3180 (1.3180/0.0000)	mem 16099MB
[2025-01-18 03:35:48 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][10/312]	eta 0:03:17 lr 0.002611	time 0.4496 (0.6555)	model_time 0.4494 (0.4753)	loss 3.7115 (3.4358)	grad_norm 1.5946 (1.6357/0.5197)	mem 16099MB
[2025-01-18 03:35:53 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][20/312]	eta 0:02:44 lr 0.002611	time 0.4469 (0.5638)	model_time 0.4467 (0.4692)	loss 3.5211 (3.3486)	grad_norm 2.3642 (1.6781/0.6159)	mem 16099MB
[2025-01-18 03:35:57 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][30/312]	eta 0:02:29 lr 0.002610	time 0.4478 (0.5286)	model_time 0.4477 (0.4644)	loss 3.5727 (3.3288)	grad_norm 1.5131 (1.6188/0.5490)	mem 16099MB
[2025-01-18 03:36:02 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][40/312]	eta 0:02:18 lr 0.002610	time 0.4539 (0.5106)	model_time 0.4537 (0.4620)	loss 3.3100 (3.3169)	grad_norm 1.6766 (1.6163/0.5315)	mem 16099MB
[2025-01-18 03:36:06 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][50/312]	eta 0:02:10 lr 0.002609	time 0.4547 (0.4995)	model_time 0.4545 (0.4604)	loss 3.1603 (3.3804)	grad_norm 0.8186 (1.6327/0.6063)	mem 16099MB
[2025-01-18 03:36:11 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][60/312]	eta 0:02:04 lr 0.002608	time 0.4408 (0.4936)	model_time 0.4406 (0.4609)	loss 2.2503 (3.3155)	grad_norm 1.1795 (1.6072/0.5923)	mem 16099MB
[2025-01-18 03:36:15 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][70/312]	eta 0:01:58 lr 0.002608	time 0.4524 (0.4885)	model_time 0.4522 (0.4603)	loss 2.9281 (3.3105)	grad_norm 0.9502 (1.6071/0.5754)	mem 16099MB
[2025-01-18 03:36:20 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][80/312]	eta 0:01:52 lr 0.002607	time 0.4393 (0.4849)	model_time 0.4389 (0.4601)	loss 3.9179 (3.2928)	grad_norm 1.2624 (1.6384/0.5871)	mem 16099MB
[2025-01-18 03:36:25 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][90/312]	eta 0:01:47 lr 0.002606	time 0.4552 (0.4830)	model_time 0.4550 (0.4609)	loss 2.5344 (3.2760)	grad_norm 0.8846 (1.6263/0.5828)	mem 16099MB
[2025-01-18 03:36:29 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][100/312]	eta 0:01:42 lr 0.002606	time 0.4444 (0.4831)	model_time 0.4443 (0.4632)	loss 3.6590 (3.3013)	grad_norm 2.9804 (1.6636/0.6083)	mem 16099MB
[2025-01-18 03:36:34 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][110/312]	eta 0:01:37 lr 0.002605	time 0.5546 (0.4837)	model_time 0.5544 (0.4656)	loss 2.6696 (3.3017)	grad_norm 1.7712 (1.6829/0.6135)	mem 16099MB
[2025-01-18 03:36:39 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][120/312]	eta 0:01:32 lr 0.002604	time 0.4524 (0.4812)	model_time 0.4519 (0.4645)	loss 3.8835 (3.3118)	grad_norm 0.7675 (1.6451/0.6091)	mem 16099MB
[2025-01-18 03:36:44 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][130/312]	eta 0:01:27 lr 0.002604	time 0.4438 (0.4800)	model_time 0.4433 (0.4645)	loss 3.8809 (3.3367)	grad_norm 1.1903 (1.6183/0.6087)	mem 16099MB
[2025-01-18 03:36:48 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][140/312]	eta 0:01:22 lr 0.002603	time 0.5359 (0.4804)	model_time 0.5355 (0.4660)	loss 4.1298 (3.3343)	grad_norm 1.9986 (1.6308/0.6222)	mem 16099MB
[2025-01-18 03:36:53 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][150/312]	eta 0:01:17 lr 0.002603	time 0.4700 (0.4803)	model_time 0.4698 (0.4669)	loss 3.7329 (3.3203)	grad_norm 1.1103 (1.6458/0.6338)	mem 16099MB
[2025-01-18 03:36:58 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][160/312]	eta 0:01:12 lr 0.002602	time 0.5448 (0.4802)	model_time 0.5444 (0.4675)	loss 2.0862 (3.3200)	grad_norm 1.8791 (1.6433/0.6189)	mem 16099MB
[2025-01-18 03:37:03 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][170/312]	eta 0:01:08 lr 0.002601	time 0.4564 (0.4800)	model_time 0.4563 (0.4681)	loss 3.3285 (3.3237)	grad_norm 1.4083 (1.6499/0.6189)	mem 16099MB
[2025-01-18 03:37:07 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][180/312]	eta 0:01:03 lr 0.002601	time 0.4442 (0.4796)	model_time 0.4438 (0.4683)	loss 2.8332 (3.3244)	grad_norm 1.1234 (1.6227/0.6139)	mem 16099MB
[2025-01-18 03:37:12 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][190/312]	eta 0:00:58 lr 0.002600	time 0.4438 (0.4789)	model_time 0.4436 (0.4682)	loss 3.4809 (3.3119)	grad_norm 2.7869 (1.6549/0.6553)	mem 16099MB
[2025-01-18 03:37:17 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][200/312]	eta 0:00:53 lr 0.002599	time 0.4679 (0.4781)	model_time 0.4675 (0.4679)	loss 3.2333 (3.2929)	grad_norm 1.2126 (1.6536/0.6445)	mem 16099MB
[2025-01-18 03:37:21 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][210/312]	eta 0:00:48 lr 0.002599	time 0.4691 (0.4774)	model_time 0.4690 (0.4676)	loss 3.5032 (3.3076)	grad_norm 1.8726 (1.6691/0.6498)	mem 16099MB
[2025-01-18 03:37:26 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][220/312]	eta 0:00:43 lr 0.002598	time 0.4391 (0.4763)	model_time 0.4386 (0.4670)	loss 2.5409 (3.3023)	grad_norm 2.6699 (1.6866/0.6579)	mem 16099MB
[2025-01-18 03:37:31 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][230/312]	eta 0:00:39 lr 0.002597	time 0.4569 (0.4757)	model_time 0.4568 (0.4668)	loss 3.6767 (3.3020)	grad_norm 2.5951 (1.7025/0.6705)	mem 16099MB
[2025-01-18 03:37:35 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][240/312]	eta 0:00:34 lr 0.002597	time 0.4533 (0.4751)	model_time 0.4529 (0.4665)	loss 3.5119 (3.3011)	grad_norm 2.0051 (1.6909/0.6627)	mem 16099MB
[2025-01-18 03:37:40 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][250/312]	eta 0:00:29 lr 0.002596	time 0.4510 (0.4742)	model_time 0.4508 (0.4659)	loss 3.9770 (3.3056)	grad_norm 1.3503 (1.6902/0.6526)	mem 16099MB
[2025-01-18 03:37:44 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][260/312]	eta 0:00:24 lr 0.002596	time 0.4607 (0.4741)	model_time 0.4603 (0.4661)	loss 3.0107 (3.2931)	grad_norm 1.0944 (1.6736/0.6491)	mem 16099MB
[2025-01-18 03:37:49 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][270/312]	eta 0:00:19 lr 0.002595	time 0.4577 (0.4742)	model_time 0.4576 (0.4665)	loss 3.4092 (3.2979)	grad_norm 3.1712 (1.6850/0.6640)	mem 16099MB
[2025-01-18 03:37:54 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][280/312]	eta 0:00:15 lr 0.002594	time 0.4500 (0.4739)	model_time 0.4495 (0.4665)	loss 2.4874 (3.2915)	grad_norm 1.1048 (1.6904/0.6757)	mem 16099MB
[2025-01-18 03:37:59 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][290/312]	eta 0:00:10 lr 0.002594	time 0.4859 (0.4740)	model_time 0.4857 (0.4669)	loss 3.5387 (3.2945)	grad_norm 1.1278 (1.6783/0.6686)	mem 16099MB
[2025-01-18 03:38:03 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][300/312]	eta 0:00:05 lr 0.002593	time 0.4381 (0.4735)	model_time 0.4380 (0.4665)	loss 3.3365 (3.2907)	grad_norm 1.6725 (1.6748/0.6676)	mem 16099MB
[2025-01-18 03:38:08 internimage_t_1k_224] (main.py 510): INFO Train: [121/300][310/312]	eta 0:00:00 lr 0.002592	time 0.4385 (0.4730)	model_time 0.4384 (0.4663)	loss 2.8881 (3.2945)	grad_norm 1.9360 (1.6614/0.6673)	mem 16099MB
[2025-01-18 03:38:08 internimage_t_1k_224] (main.py 519): INFO EPOCH 121 training takes 0:02:27
[2025-01-18 03:38:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_121.pth saving......
[2025-01-18 03:38:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_121.pth saved !!!
[2025-01-18 03:38:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.395 (7.395)	Loss 0.8598 (0.8598)	Acc@1 81.152 (81.152)	Acc@5 96.265 (96.265)	Mem 16099MB
[2025-01-18 03:38:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.979)	Loss 1.2127 (1.0170)	Acc@1 72.559 (78.109)	Acc@5 92.456 (94.385)	Mem 16099MB
[2025-01-18 03:38:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:121] * Acc@1 78.019 Acc@5 94.462
[2025-01-18 03:38:20 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.0%
[2025-01-18 03:38:20 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.04%
[2025-01-18 03:38:29 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.275 (8.275)	Loss 0.8352 (0.8352)	Acc@1 82.104 (82.104)	Acc@5 96.875 (96.875)	Mem 16099MB
[2025-01-18 03:38:33 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.100)	Loss 1.1975 (0.9862)	Acc@1 73.145 (78.962)	Acc@5 92.334 (94.740)	Mem 16099MB
[2025-01-18 03:38:33 internimage_t_1k_224] (main.py 575): INFO [Epoch:121] * Acc@1 78.859 Acc@5 94.770
[2025-01-18 03:38:33 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 78.9%
[2025-01-18 03:38:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:38:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:38:34 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 78.86%
[2025-01-18 03:38:36 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][0/312]	eta 0:11:32 lr 0.002592	time 2.2188 (2.2188)	model_time 0.5645 (0.5645)	loss 3.6098 (3.6098)	grad_norm 1.2151 (1.2151/0.0000)	mem 16099MB
[2025-01-18 03:38:41 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][10/312]	eta 0:03:09 lr 0.002592	time 0.4451 (0.6261)	model_time 0.4447 (0.4753)	loss 3.5578 (3.2269)	grad_norm 1.0070 (1.4799/0.6304)	mem 16099MB
[2025-01-18 03:38:46 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][20/312]	eta 0:02:41 lr 0.002591	time 0.4418 (0.5545)	model_time 0.4417 (0.4753)	loss 3.5265 (3.2036)	grad_norm 1.1151 (1.3627/0.5328)	mem 16099MB
[2025-01-18 03:38:51 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][30/312]	eta 0:02:30 lr 0.002590	time 0.4483 (0.5330)	model_time 0.4482 (0.4792)	loss 3.3373 (3.2606)	grad_norm 1.1969 (1.4479/0.5561)	mem 16099MB
[2025-01-18 03:38:55 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][40/312]	eta 0:02:20 lr 0.002590	time 0.4539 (0.5164)	model_time 0.4535 (0.4757)	loss 3.9933 (3.3670)	grad_norm 0.9167 (1.6544/0.7343)	mem 16099MB
[2025-01-18 03:39:00 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][50/312]	eta 0:02:13 lr 0.002589	time 0.4470 (0.5092)	model_time 0.4466 (0.4764)	loss 3.6779 (3.3573)	grad_norm 0.9662 (1.6657/0.7224)	mem 16099MB
[2025-01-18 03:39:05 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][60/312]	eta 0:02:06 lr 0.002588	time 0.5472 (0.5032)	model_time 0.5471 (0.4757)	loss 3.8560 (3.3809)	grad_norm 1.5048 (1.6576/0.6998)	mem 16099MB
[2025-01-18 03:39:09 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][70/312]	eta 0:02:00 lr 0.002588	time 0.5363 (0.4991)	model_time 0.5362 (0.4755)	loss 2.5933 (3.3761)	grad_norm 1.9100 (1.6985/0.7165)	mem 16099MB
[2025-01-18 03:39:14 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][80/312]	eta 0:01:54 lr 0.002587	time 0.4501 (0.4933)	model_time 0.4500 (0.4725)	loss 3.6297 (3.3688)	grad_norm 2.0545 (1.7243/0.7742)	mem 16099MB
[2025-01-18 03:39:19 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][90/312]	eta 0:01:48 lr 0.002587	time 0.4398 (0.4892)	model_time 0.4393 (0.4707)	loss 3.9846 (3.4061)	grad_norm 1.9018 (1.6913/0.7476)	mem 16099MB
[2025-01-18 03:39:23 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][100/312]	eta 0:01:42 lr 0.002586	time 0.4843 (0.4858)	model_time 0.4839 (0.4690)	loss 3.7853 (3.3930)	grad_norm 1.9660 (1.7015/0.7326)	mem 16099MB
[2025-01-18 03:39:28 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][110/312]	eta 0:01:37 lr 0.002585	time 0.5027 (0.4835)	model_time 0.5025 (0.4682)	loss 3.6597 (3.3954)	grad_norm 3.9487 (1.7595/0.8199)	mem 16099MB
[2025-01-18 03:39:32 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][120/312]	eta 0:01:32 lr 0.002585	time 0.4524 (0.4824)	model_time 0.4519 (0.4684)	loss 3.6430 (3.3788)	grad_norm 1.1354 (1.7448/0.8045)	mem 16099MB
[2025-01-18 03:39:37 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][130/312]	eta 0:01:27 lr 0.002584	time 0.7321 (0.4833)	model_time 0.7317 (0.4703)	loss 2.5041 (3.3748)	grad_norm 0.9705 (1.7392/0.8025)	mem 16099MB
[2025-01-18 03:39:42 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][140/312]	eta 0:01:23 lr 0.002583	time 0.4513 (0.4827)	model_time 0.4509 (0.4706)	loss 3.9875 (3.3826)	grad_norm 1.3097 (1.8224/0.9092)	mem 16099MB
[2025-01-18 03:39:47 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][150/312]	eta 0:01:18 lr 0.002583	time 0.5358 (0.4826)	model_time 0.5356 (0.4713)	loss 3.7551 (3.3955)	grad_norm 2.2871 (1.8279/0.9296)	mem 16099MB
[2025-01-18 03:39:52 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][160/312]	eta 0:01:13 lr 0.002582	time 0.4535 (0.4814)	model_time 0.4530 (0.4708)	loss 2.4688 (3.3815)	grad_norm 1.8691 (1.8231/0.9268)	mem 16099MB
[2025-01-18 03:39:56 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][170/312]	eta 0:01:08 lr 0.002581	time 0.4594 (0.4803)	model_time 0.4590 (0.4702)	loss 4.2275 (3.3879)	grad_norm 2.0741 (1.8258/0.9337)	mem 16099MB
[2025-01-18 03:40:01 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][180/312]	eta 0:01:03 lr 0.002581	time 0.4484 (0.4801)	model_time 0.4479 (0.4706)	loss 3.8516 (3.3823)	grad_norm 1.6146 (1.7999/0.9198)	mem 16099MB
[2025-01-18 03:40:06 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][190/312]	eta 0:00:58 lr 0.002580	time 0.4948 (0.4796)	model_time 0.4944 (0.4706)	loss 4.3902 (3.3873)	grad_norm 1.2584 (1.7754/0.9033)	mem 16099MB
[2025-01-18 03:40:10 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][200/312]	eta 0:00:53 lr 0.002580	time 0.4737 (0.4791)	model_time 0.4736 (0.4705)	loss 3.2505 (3.3877)	grad_norm 2.5034 (1.7632/0.8906)	mem 16099MB
[2025-01-18 03:40:15 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][210/312]	eta 0:00:48 lr 0.002579	time 0.4572 (0.4782)	model_time 0.4571 (0.4700)	loss 3.8114 (3.3959)	grad_norm 1.4967 (1.7923/0.9168)	mem 16099MB
[2025-01-18 03:40:20 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][220/312]	eta 0:00:43 lr 0.002578	time 0.4427 (0.4774)	model_time 0.4422 (0.4695)	loss 4.0710 (3.3941)	grad_norm 1.4223 (1.8002/0.9105)	mem 16099MB
[2025-01-18 03:40:24 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][230/312]	eta 0:00:39 lr 0.002578	time 0.4465 (0.4772)	model_time 0.4463 (0.4696)	loss 3.7999 (3.3876)	grad_norm 1.6301 (1.7872/0.8964)	mem 16099MB
[2025-01-18 03:40:29 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][240/312]	eta 0:00:34 lr 0.002577	time 0.4453 (0.4765)	model_time 0.4452 (0.4693)	loss 2.4182 (3.3783)	grad_norm 2.0820 (1.7681/0.8850)	mem 16099MB
[2025-01-18 03:40:34 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][250/312]	eta 0:00:29 lr 0.002576	time 0.4497 (0.4761)	model_time 0.4493 (0.4692)	loss 3.8908 (3.3724)	grad_norm 1.3712 (1.7534/0.8738)	mem 16099MB
[2025-01-18 03:40:38 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][260/312]	eta 0:00:24 lr 0.002576	time 0.4523 (0.4755)	model_time 0.4519 (0.4688)	loss 3.2673 (3.3632)	grad_norm 1.5171 (1.7751/0.8984)	mem 16099MB
[2025-01-18 03:40:43 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][270/312]	eta 0:00:19 lr 0.002575	time 0.4535 (0.4752)	model_time 0.4534 (0.4687)	loss 2.3889 (3.3567)	grad_norm 1.8926 (1.7750/0.8894)	mem 16099MB
[2025-01-18 03:40:48 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][280/312]	eta 0:00:15 lr 0.002574	time 0.4671 (0.4752)	model_time 0.4667 (0.4690)	loss 2.6643 (3.3523)	grad_norm 0.8755 (1.7594/0.8814)	mem 16099MB
[2025-01-18 03:40:52 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][290/312]	eta 0:00:10 lr 0.002574	time 0.4521 (0.4753)	model_time 0.4519 (0.4693)	loss 3.7792 (3.3515)	grad_norm 2.7819 (1.7851/0.9115)	mem 16099MB
[2025-01-18 03:40:57 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][300/312]	eta 0:00:05 lr 0.002573	time 0.4376 (0.4745)	model_time 0.4375 (0.4686)	loss 3.6186 (3.3522)	grad_norm 1.2301 (1.7951/0.9184)	mem 16099MB
[2025-01-18 03:41:01 internimage_t_1k_224] (main.py 510): INFO Train: [122/300][310/312]	eta 0:00:00 lr 0.002573	time 0.4377 (0.4733)	model_time 0.4376 (0.4676)	loss 3.7911 (3.3511)	grad_norm 1.9188 (1.7917/0.9147)	mem 16099MB
[2025-01-18 03:41:02 internimage_t_1k_224] (main.py 519): INFO EPOCH 122 training takes 0:02:27
[2025-01-18 03:41:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_122.pth saving......
[2025-01-18 03:41:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_122.pth saved !!!
[2025-01-18 03:41:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.548 (7.548)	Loss 0.8712 (0.8712)	Acc@1 81.787 (81.787)	Acc@5 96.191 (96.191)	Mem 16099MB
[2025-01-18 03:41:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.998)	Loss 1.1981 (1.0010)	Acc@1 72.241 (78.021)	Acc@5 92.334 (94.460)	Mem 16099MB
[2025-01-18 03:41:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:122] * Acc@1 77.983 Acc@5 94.516
[2025-01-18 03:41:14 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.0%
[2025-01-18 03:41:14 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.04%
[2025-01-18 03:41:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.276 (8.276)	Loss 0.8333 (0.8333)	Acc@1 82.129 (82.129)	Acc@5 96.899 (96.899)	Mem 16099MB
[2025-01-18 03:41:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.111)	Loss 1.1936 (0.9835)	Acc@1 73.242 (79.062)	Acc@5 92.358 (94.784)	Mem 16099MB
[2025-01-18 03:41:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:122] * Acc@1 78.961 Acc@5 94.810
[2025-01-18 03:41:26 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.0%
[2025-01-18 03:41:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:41:28 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:41:28 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 78.96%
[2025-01-18 03:41:30 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][0/312]	eta 0:12:54 lr 0.002572	time 2.4823 (2.4823)	model_time 0.4870 (0.4870)	loss 3.0584 (3.0584)	grad_norm 1.4262 (1.4262/0.0000)	mem 16099MB
[2025-01-18 03:41:35 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][10/312]	eta 0:03:20 lr 0.002572	time 0.4549 (0.6644)	model_time 0.4548 (0.4748)	loss 3.4072 (3.1656)	grad_norm 1.1935 (1.3871/0.4805)	mem 16099MB
[2025-01-18 03:41:40 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][20/312]	eta 0:02:48 lr 0.002571	time 0.4532 (0.5765)	model_time 0.4528 (0.4770)	loss 3.2244 (3.2930)	grad_norm 1.8484 (1.4671/0.4501)	mem 16099MB
[2025-01-18 03:41:45 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][30/312]	eta 0:02:33 lr 0.002570	time 0.5461 (0.5442)	model_time 0.5459 (0.4767)	loss 3.0784 (3.2307)	grad_norm 1.3613 (1.3986/0.4607)	mem 16099MB
[2025-01-18 03:41:49 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][40/312]	eta 0:02:22 lr 0.002570	time 0.4544 (0.5243)	model_time 0.4542 (0.4731)	loss 3.4815 (3.2172)	grad_norm 2.0043 (1.4136/0.4383)	mem 16099MB
[2025-01-18 03:41:54 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][50/312]	eta 0:02:15 lr 0.002569	time 0.4628 (0.5188)	model_time 0.4624 (0.4776)	loss 3.4171 (3.2590)	grad_norm 1.4429 (1.3956/0.4396)	mem 16099MB
[2025-01-18 03:41:59 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][60/312]	eta 0:02:08 lr 0.002569	time 0.4532 (0.5088)	model_time 0.4528 (0.4743)	loss 3.6474 (3.3074)	grad_norm 0.7890 (1.3544/0.4339)	mem 16099MB
[2025-01-18 03:42:04 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][70/312]	eta 0:02:01 lr 0.002568	time 0.4943 (0.5029)	model_time 0.4942 (0.4732)	loss 2.4978 (3.2922)	grad_norm 0.9841 (1.3452/0.4250)	mem 16099MB
[2025-01-18 03:42:08 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][80/312]	eta 0:01:55 lr 0.002567	time 0.5420 (0.4993)	model_time 0.5418 (0.4732)	loss 3.9561 (3.2884)	grad_norm 2.4088 (1.4105/0.4795)	mem 16099MB
[2025-01-18 03:42:13 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][90/312]	eta 0:01:50 lr 0.002567	time 0.4837 (0.4963)	model_time 0.4833 (0.4730)	loss 2.7142 (3.2928)	grad_norm 1.7766 (1.4848/0.5669)	mem 16099MB
[2025-01-18 03:42:18 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][100/312]	eta 0:01:44 lr 0.002566	time 0.4610 (0.4931)	model_time 0.4606 (0.4721)	loss 2.7297 (3.3073)	grad_norm 1.9051 (1.4744/0.5491)	mem 16099MB
[2025-01-18 03:42:22 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][110/312]	eta 0:01:39 lr 0.002565	time 0.4402 (0.4908)	model_time 0.4400 (0.4716)	loss 4.0803 (3.2991)	grad_norm 2.3245 (1.4757/0.5535)	mem 16099MB
[2025-01-18 03:42:27 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][120/312]	eta 0:01:33 lr 0.002565	time 0.4576 (0.4879)	model_time 0.4572 (0.4703)	loss 3.2954 (3.2997)	grad_norm 1.8261 (1.4993/0.5619)	mem 16099MB
[2025-01-18 03:42:31 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][130/312]	eta 0:01:28 lr 0.002564	time 0.5072 (0.4855)	model_time 0.5070 (0.4692)	loss 4.2771 (3.3170)	grad_norm 3.2052 (1.5469/0.5981)	mem 16099MB
[2025-01-18 03:42:36 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][140/312]	eta 0:01:23 lr 0.002563	time 0.4896 (0.4841)	model_time 0.4894 (0.4689)	loss 4.1056 (3.3309)	grad_norm 1.3225 (1.5463/0.5984)	mem 16099MB
[2025-01-18 03:42:41 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][150/312]	eta 0:01:18 lr 0.002563	time 0.4506 (0.4830)	model_time 0.4504 (0.4688)	loss 3.5761 (3.3303)	grad_norm 1.3487 (1.5358/0.5857)	mem 16099MB
[2025-01-18 03:42:46 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][160/312]	eta 0:01:13 lr 0.002562	time 0.4512 (0.4832)	model_time 0.4510 (0.4698)	loss 2.0894 (3.3207)	grad_norm 2.8179 (1.5259/0.5849)	mem 16099MB
[2025-01-18 03:42:50 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][170/312]	eta 0:01:08 lr 0.002562	time 0.5015 (0.4819)	model_time 0.5010 (0.4693)	loss 2.9959 (3.3114)	grad_norm 1.1031 (1.5501/0.5852)	mem 16099MB
[2025-01-18 03:42:55 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][180/312]	eta 0:01:03 lr 0.002561	time 0.4637 (0.4808)	model_time 0.4633 (0.4689)	loss 3.3945 (3.3081)	grad_norm 1.2240 (1.5755/0.6030)	mem 16099MB
[2025-01-18 03:42:59 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][190/312]	eta 0:00:58 lr 0.002560	time 0.4459 (0.4797)	model_time 0.4458 (0.4684)	loss 2.9746 (3.3072)	grad_norm 1.0950 (1.5672/0.5964)	mem 16099MB
[2025-01-18 03:43:04 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][200/312]	eta 0:00:53 lr 0.002560	time 0.4433 (0.4795)	model_time 0.4428 (0.4687)	loss 3.4768 (3.3100)	grad_norm 2.0559 (1.5853/0.6046)	mem 16099MB
[2025-01-18 03:43:09 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][210/312]	eta 0:00:48 lr 0.002559	time 0.4580 (0.4788)	model_time 0.4575 (0.4686)	loss 2.8946 (3.3055)	grad_norm 1.3972 (1.6018/0.6283)	mem 16099MB
[2025-01-18 03:43:13 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][220/312]	eta 0:00:43 lr 0.002558	time 0.4442 (0.4780)	model_time 0.4437 (0.4681)	loss 3.2277 (3.3020)	grad_norm 1.1175 (1.6159/0.6369)	mem 16099MB
[2025-01-18 03:43:18 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][230/312]	eta 0:00:39 lr 0.002558	time 0.4614 (0.4770)	model_time 0.4612 (0.4676)	loss 2.9772 (3.3087)	grad_norm 1.4534 (1.6143/0.6365)	mem 16099MB
[2025-01-18 03:43:23 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][240/312]	eta 0:00:34 lr 0.002557	time 0.4518 (0.4760)	model_time 0.4513 (0.4669)	loss 3.6992 (3.3083)	grad_norm 1.4029 (1.6365/0.6712)	mem 16099MB
[2025-01-18 03:43:27 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][250/312]	eta 0:00:29 lr 0.002556	time 0.5048 (0.4759)	model_time 0.5044 (0.4672)	loss 2.3728 (3.3076)	grad_norm 1.6679 (1.6338/0.6664)	mem 16099MB
[2025-01-18 03:43:32 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][260/312]	eta 0:00:24 lr 0.002556	time 0.4432 (0.4755)	model_time 0.4430 (0.4671)	loss 3.6917 (3.3120)	grad_norm 1.4530 (1.6208/0.6596)	mem 16099MB
[2025-01-18 03:43:37 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][270/312]	eta 0:00:19 lr 0.002555	time 0.4466 (0.4755)	model_time 0.4465 (0.4674)	loss 4.2027 (3.3066)	grad_norm 1.1361 (1.6187/0.6543)	mem 16099MB
[2025-01-18 03:43:41 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][280/312]	eta 0:00:15 lr 0.002555	time 0.4824 (0.4752)	model_time 0.4823 (0.4673)	loss 4.2870 (3.3109)	grad_norm 0.8358 (1.6147/0.6616)	mem 16099MB
[2025-01-18 03:43:46 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][290/312]	eta 0:00:10 lr 0.002554	time 0.4505 (0.4751)	model_time 0.4500 (0.4676)	loss 3.2103 (3.3034)	grad_norm 0.9380 (1.6018/0.6580)	mem 16099MB
[2025-01-18 03:43:51 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][300/312]	eta 0:00:05 lr 0.002553	time 0.4386 (0.4746)	model_time 0.4385 (0.4672)	loss 2.5757 (3.3022)	grad_norm 1.8185 (1.5979/0.6556)	mem 16099MB
[2025-01-18 03:43:55 internimage_t_1k_224] (main.py 510): INFO Train: [123/300][310/312]	eta 0:00:00 lr 0.002553	time 0.4381 (0.4738)	model_time 0.4380 (0.4667)	loss 3.9095 (3.3024)	grad_norm 3.0181 (1.6249/0.6855)	mem 16099MB
[2025-01-18 03:43:56 internimage_t_1k_224] (main.py 519): INFO EPOCH 123 training takes 0:02:27
[2025-01-18 03:43:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_123.pth saving......
[2025-01-18 03:43:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_123.pth saved !!!
[2025-01-18 03:44:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.495 (7.495)	Loss 0.8743 (0.8743)	Acc@1 81.616 (81.616)	Acc@5 95.947 (95.947)	Mem 16099MB
[2025-01-18 03:44:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.099 (1.002)	Loss 1.2057 (1.0313)	Acc@1 74.438 (78.380)	Acc@5 92.383 (94.365)	Mem 16099MB
[2025-01-18 03:44:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:123] * Acc@1 78.305 Acc@5 94.430
[2025-01-18 03:44:08 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.3%
[2025-01-18 03:44:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 03:44:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 03:44:09 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.30%
[2025-01-18 03:44:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.254 (7.254)	Loss 0.8315 (0.8315)	Acc@1 82.129 (82.129)	Acc@5 96.826 (96.826)	Mem 16099MB
[2025-01-18 03:44:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.993)	Loss 1.1895 (0.9808)	Acc@1 73.291 (79.133)	Acc@5 92.480 (94.815)	Mem 16099MB
[2025-01-18 03:44:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:123] * Acc@1 79.029 Acc@5 94.842
[2025-01-18 03:44:20 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.0%
[2025-01-18 03:44:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:44:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:44:22 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.03%
[2025-01-18 03:44:24 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][0/312]	eta 0:12:40 lr 0.002552	time 2.4364 (2.4364)	model_time 0.4923 (0.4923)	loss 2.4534 (2.4534)	grad_norm 2.1092 (2.1092/0.0000)	mem 16099MB
[2025-01-18 03:44:29 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][10/312]	eta 0:03:13 lr 0.002552	time 0.4575 (0.6422)	model_time 0.4573 (0.4651)	loss 4.1080 (3.2820)	grad_norm 1.8566 (1.5942/0.4979)	mem 16099MB
[2025-01-18 03:44:33 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][20/312]	eta 0:02:42 lr 0.002551	time 0.4656 (0.5575)	model_time 0.4654 (0.4646)	loss 3.2120 (3.3021)	grad_norm 1.6251 (1.5959/0.4635)	mem 16099MB
[2025-01-18 03:44:38 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][30/312]	eta 0:02:28 lr 0.002551	time 0.4537 (0.5259)	model_time 0.4533 (0.4629)	loss 3.7481 (3.2796)	grad_norm 1.7353 (1.6319/0.5599)	mem 16099MB
[2025-01-18 03:44:43 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][40/312]	eta 0:02:18 lr 0.002550	time 0.4595 (0.5086)	model_time 0.4591 (0.4608)	loss 2.5919 (3.2542)	grad_norm 2.0370 (1.5342/0.5603)	mem 16099MB
[2025-01-18 03:44:47 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][50/312]	eta 0:02:12 lr 0.002549	time 0.4470 (0.5040)	model_time 0.4468 (0.4655)	loss 3.1142 (3.3482)	grad_norm 2.4298 (1.6815/0.6675)	mem 16099MB
[2025-01-18 03:44:52 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][60/312]	eta 0:02:05 lr 0.002549	time 0.4442 (0.4977)	model_time 0.4440 (0.4655)	loss 3.6059 (3.3525)	grad_norm 2.8181 (1.6858/0.6571)	mem 16099MB
[2025-01-18 03:44:57 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][70/312]	eta 0:01:59 lr 0.002548	time 0.4582 (0.4935)	model_time 0.4577 (0.4658)	loss 2.8101 (3.3393)	grad_norm 1.6672 (1.7132/0.6735)	mem 16099MB
[2025-01-18 03:45:01 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][80/312]	eta 0:01:53 lr 0.002547	time 0.4404 (0.4907)	model_time 0.4402 (0.4663)	loss 2.0443 (3.2836)	grad_norm 1.1451 (1.6856/0.6797)	mem 16099MB
[2025-01-18 03:45:06 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][90/312]	eta 0:01:48 lr 0.002547	time 0.4546 (0.4878)	model_time 0.4544 (0.4661)	loss 3.5726 (3.2893)	grad_norm 1.5647 (1.6861/0.6600)	mem 16099MB
[2025-01-18 03:45:11 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][100/312]	eta 0:01:42 lr 0.002546	time 0.4524 (0.4852)	model_time 0.4519 (0.4656)	loss 4.0324 (3.2905)	grad_norm 0.6419 (1.7160/0.7331)	mem 16099MB
[2025-01-18 03:45:15 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][110/312]	eta 0:01:37 lr 0.002545	time 0.4736 (0.4827)	model_time 0.4734 (0.4648)	loss 4.0151 (3.3188)	grad_norm 2.6388 (1.7509/0.8361)	mem 16099MB
[2025-01-18 03:45:20 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][120/312]	eta 0:01:32 lr 0.002545	time 0.4508 (0.4808)	model_time 0.4506 (0.4644)	loss 3.8915 (3.3145)	grad_norm 2.3610 (1.7702/0.8354)	mem 16099MB
[2025-01-18 03:45:25 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][130/312]	eta 0:01:27 lr 0.002544	time 0.4609 (0.4807)	model_time 0.4604 (0.4655)	loss 2.8781 (3.2875)	grad_norm 2.7914 (1.7563/0.8184)	mem 16099MB
[2025-01-18 03:45:29 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][140/312]	eta 0:01:22 lr 0.002543	time 0.4424 (0.4805)	model_time 0.4422 (0.4663)	loss 3.2206 (3.2659)	grad_norm 1.3394 (1.7511/0.8138)	mem 16099MB
[2025-01-18 03:45:34 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][150/312]	eta 0:01:17 lr 0.002543	time 0.4434 (0.4807)	model_time 0.4429 (0.4675)	loss 3.4043 (3.2680)	grad_norm 3.7487 (1.7452/0.8168)	mem 16099MB
[2025-01-18 03:45:39 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][160/312]	eta 0:01:13 lr 0.002542	time 0.4684 (0.4810)	model_time 0.4680 (0.4686)	loss 3.4552 (3.2548)	grad_norm 0.9233 (1.7375/0.8067)	mem 16099MB
[2025-01-18 03:45:44 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][170/312]	eta 0:01:08 lr 0.002542	time 0.4465 (0.4799)	model_time 0.4460 (0.4682)	loss 3.1971 (3.2510)	grad_norm 1.0835 (1.7084/0.7932)	mem 16099MB
[2025-01-18 03:45:48 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][180/312]	eta 0:01:03 lr 0.002541	time 0.4508 (0.4787)	model_time 0.4504 (0.4676)	loss 4.2301 (3.2604)	grad_norm 1.7250 (1.6778/0.7855)	mem 16099MB
[2025-01-18 03:45:53 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][190/312]	eta 0:00:58 lr 0.002540	time 0.4451 (0.4778)	model_time 0.4447 (0.4673)	loss 3.7758 (3.2725)	grad_norm 0.7714 (1.6713/0.7772)	mem 16099MB
[2025-01-18 03:45:58 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][200/312]	eta 0:00:53 lr 0.002540	time 0.4495 (0.4767)	model_time 0.4493 (0.4666)	loss 4.1759 (3.2863)	grad_norm 0.8309 (1.6508/0.7659)	mem 16099MB
[2025-01-18 03:46:02 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][210/312]	eta 0:00:48 lr 0.002539	time 0.4506 (0.4757)	model_time 0.4505 (0.4661)	loss 3.4447 (3.2980)	grad_norm 1.0178 (1.6569/0.7662)	mem 16099MB
[2025-01-18 03:46:07 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][220/312]	eta 0:00:43 lr 0.002538	time 0.4707 (0.4751)	model_time 0.4705 (0.4659)	loss 4.1165 (3.3095)	grad_norm 1.2358 (1.6564/0.7599)	mem 16099MB
[2025-01-18 03:46:11 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][230/312]	eta 0:00:38 lr 0.002538	time 0.4458 (0.4743)	model_time 0.4457 (0.4655)	loss 3.5894 (3.3092)	grad_norm 1.7128 (1.6505/0.7471)	mem 16099MB
[2025-01-18 03:46:16 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][240/312]	eta 0:00:34 lr 0.002537	time 0.4494 (0.4745)	model_time 0.4493 (0.4660)	loss 4.5126 (3.3031)	grad_norm 1.2414 (1.6878/0.7877)	mem 16099MB
[2025-01-18 03:46:21 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][250/312]	eta 0:00:29 lr 0.002536	time 0.4445 (0.4742)	model_time 0.4443 (0.4660)	loss 2.9727 (3.3019)	grad_norm 2.0497 (1.6897/0.7797)	mem 16099MB
[2025-01-18 03:46:25 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][260/312]	eta 0:00:24 lr 0.002536	time 0.4493 (0.4739)	model_time 0.4489 (0.4660)	loss 3.0248 (3.3003)	grad_norm 1.4563 (1.6771/0.7706)	mem 16099MB
[2025-01-18 03:46:30 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][270/312]	eta 0:00:19 lr 0.002535	time 0.4583 (0.4733)	model_time 0.4582 (0.4657)	loss 3.8030 (3.3151)	grad_norm 0.8781 (1.6689/0.7608)	mem 16099MB
[2025-01-18 03:46:35 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][280/312]	eta 0:00:15 lr 0.002535	time 0.4789 (0.4730)	model_time 0.4787 (0.4657)	loss 2.8474 (3.3082)	grad_norm 1.0407 (1.6570/0.7542)	mem 16099MB
[2025-01-18 03:46:39 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][290/312]	eta 0:00:10 lr 0.002534	time 0.4542 (0.4735)	model_time 0.4538 (0.4663)	loss 4.0027 (3.3084)	grad_norm 1.4080 (1.6504/0.7447)	mem 16099MB
[2025-01-18 03:46:44 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][300/312]	eta 0:00:05 lr 0.002533	time 0.4396 (0.4728)	model_time 0.4395 (0.4659)	loss 3.4816 (3.3159)	grad_norm 2.0367 (1.6689/0.7771)	mem 16099MB
[2025-01-18 03:46:49 internimage_t_1k_224] (main.py 510): INFO Train: [124/300][310/312]	eta 0:00:00 lr 0.002533	time 0.4395 (0.4730)	model_time 0.4394 (0.4663)	loss 3.5999 (3.3141)	grad_norm 2.6332 (1.6676/0.7784)	mem 16099MB
[2025-01-18 03:46:49 internimage_t_1k_224] (main.py 519): INFO EPOCH 124 training takes 0:02:27
[2025-01-18 03:46:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_124.pth saving......
[2025-01-18 03:46:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_124.pth saved !!!
[2025-01-18 03:46:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.236 (7.236)	Loss 0.8526 (0.8526)	Acc@1 81.836 (81.836)	Acc@5 96.265 (96.265)	Mem 16099MB
[2025-01-18 03:47:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.977)	Loss 1.1696 (0.9931)	Acc@1 73.169 (78.400)	Acc@5 92.896 (94.556)	Mem 16099MB
[2025-01-18 03:47:01 internimage_t_1k_224] (main.py 575): INFO [Epoch:124] * Acc@1 78.309 Acc@5 94.562
[2025-01-18 03:47:01 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.3%
[2025-01-18 03:47:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 03:47:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 03:47:02 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.31%
[2025-01-18 03:47:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.536 (7.536)	Loss 0.8299 (0.8299)	Acc@1 82.178 (82.178)	Acc@5 96.802 (96.802)	Mem 16099MB
[2025-01-18 03:47:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.009)	Loss 1.1859 (0.9782)	Acc@1 73.389 (79.219)	Acc@5 92.578 (94.844)	Mem 16099MB
[2025-01-18 03:47:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:124] * Acc@1 79.115 Acc@5 94.868
[2025-01-18 03:47:14 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.1%
[2025-01-18 03:47:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:47:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:47:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.11%
[2025-01-18 03:47:18 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][0/312]	eta 0:12:04 lr 0.002532	time 2.3233 (2.3233)	model_time 0.5041 (0.5041)	loss 3.8675 (3.8675)	grad_norm 3.0936 (3.0936/0.0000)	mem 16099MB
[2025-01-18 03:47:22 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][10/312]	eta 0:03:12 lr 0.002532	time 0.4672 (0.6373)	model_time 0.4670 (0.4716)	loss 3.4809 (3.1872)	grad_norm 1.1462 (2.0397/0.7475)	mem 16099MB
[2025-01-18 03:47:27 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][20/312]	eta 0:02:43 lr 0.002531	time 0.5693 (0.5611)	model_time 0.5692 (0.4742)	loss 3.0875 (3.0791)	grad_norm 1.0982 (1.6517/0.7119)	mem 16099MB
[2025-01-18 03:47:32 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][30/312]	eta 0:02:28 lr 0.002531	time 0.4598 (0.5264)	model_time 0.4597 (0.4673)	loss 3.5585 (3.1533)	grad_norm 1.7730 (1.7875/0.7204)	mem 16099MB
[2025-01-18 03:47:36 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][40/312]	eta 0:02:18 lr 0.002530	time 0.4501 (0.5088)	model_time 0.4499 (0.4640)	loss 1.8806 (3.2043)	grad_norm 1.3759 (1.8505/0.7527)	mem 16099MB
[2025-01-18 03:47:41 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][50/312]	eta 0:02:11 lr 0.002529	time 0.4447 (0.5012)	model_time 0.4442 (0.4652)	loss 2.4960 (3.2938)	grad_norm 1.0877 (1.7371/0.7217)	mem 16099MB
[2025-01-18 03:47:45 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][60/312]	eta 0:02:04 lr 0.002529	time 0.4946 (0.4950)	model_time 0.4941 (0.4648)	loss 3.7777 (3.2760)	grad_norm 0.7245 (1.6692/0.7099)	mem 16099MB
[2025-01-18 03:47:50 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][70/312]	eta 0:01:58 lr 0.002528	time 0.4562 (0.4909)	model_time 0.4558 (0.4650)	loss 2.6091 (3.3026)	grad_norm 3.9492 (1.7963/0.8485)	mem 16099MB
[2025-01-18 03:47:55 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][80/312]	eta 0:01:53 lr 0.002527	time 0.4420 (0.4878)	model_time 0.4418 (0.4649)	loss 3.2436 (3.3397)	grad_norm 1.3732 (1.7735/0.8130)	mem 16099MB
[2025-01-18 03:47:59 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][90/312]	eta 0:01:47 lr 0.002527	time 0.5468 (0.4854)	model_time 0.5466 (0.4650)	loss 3.5709 (3.3497)	grad_norm 0.7917 (1.7197/0.7976)	mem 16099MB
[2025-01-18 03:48:04 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][100/312]	eta 0:01:42 lr 0.002526	time 0.4603 (0.4840)	model_time 0.4598 (0.4656)	loss 3.1149 (3.3402)	grad_norm 1.2474 (1.7438/0.7812)	mem 16099MB
[2025-01-18 03:48:09 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][110/312]	eta 0:01:37 lr 0.002525	time 0.5037 (0.4818)	model_time 0.5032 (0.4650)	loss 4.1460 (3.3599)	grad_norm 2.6006 (1.7692/0.8085)	mem 16099MB
[2025-01-18 03:48:13 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][120/312]	eta 0:01:32 lr 0.002525	time 0.4421 (0.4794)	model_time 0.4417 (0.4640)	loss 2.4242 (3.3579)	grad_norm 1.9266 (1.7473/0.7951)	mem 16099MB
[2025-01-18 03:48:18 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][130/312]	eta 0:01:27 lr 0.002524	time 0.4605 (0.4792)	model_time 0.4603 (0.4650)	loss 3.0580 (3.3485)	grad_norm 0.8296 (1.7321/0.7850)	mem 16099MB
[2025-01-18 03:48:23 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][140/312]	eta 0:01:22 lr 0.002523	time 0.5486 (0.4805)	model_time 0.5484 (0.4673)	loss 3.9201 (3.3361)	grad_norm 1.0053 (1.7091/0.7730)	mem 16099MB
[2025-01-18 03:48:28 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][150/312]	eta 0:01:17 lr 0.002523	time 0.5480 (0.4807)	model_time 0.5479 (0.4683)	loss 3.5394 (3.3211)	grad_norm 1.5434 (1.7269/0.7680)	mem 16099MB
[2025-01-18 03:48:33 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][160/312]	eta 0:01:13 lr 0.002522	time 0.5028 (0.4814)	model_time 0.5024 (0.4697)	loss 3.7905 (3.3220)	grad_norm 1.1896 (1.7228/0.7498)	mem 16099MB
[2025-01-18 03:48:37 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][170/312]	eta 0:01:08 lr 0.002522	time 0.4493 (0.4800)	model_time 0.4491 (0.4690)	loss 3.1463 (3.3164)	grad_norm 2.4251 (1.7351/0.7542)	mem 16099MB
[2025-01-18 03:48:42 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][180/312]	eta 0:01:03 lr 0.002521	time 0.4539 (0.4796)	model_time 0.4538 (0.4692)	loss 4.4140 (3.3381)	grad_norm 1.3457 (1.7165/0.7431)	mem 16099MB
[2025-01-18 03:48:47 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][190/312]	eta 0:00:58 lr 0.002520	time 0.4463 (0.4781)	model_time 0.4461 (0.4682)	loss 2.6980 (3.3354)	grad_norm 1.2900 (1.6822/0.7400)	mem 16099MB
[2025-01-18 03:48:51 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][200/312]	eta 0:00:53 lr 0.002520	time 0.4501 (0.4772)	model_time 0.4497 (0.4677)	loss 2.4549 (3.3426)	grad_norm 2.3833 (1.6811/0.7280)	mem 16099MB
[2025-01-18 03:48:56 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][210/312]	eta 0:00:48 lr 0.002519	time 0.4483 (0.4765)	model_time 0.4478 (0.4675)	loss 2.9570 (3.3423)	grad_norm 1.2082 (1.6975/0.7509)	mem 16099MB
[2025-01-18 03:49:00 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][220/312]	eta 0:00:43 lr 0.002518	time 0.4488 (0.4758)	model_time 0.4483 (0.4672)	loss 3.7361 (3.3488)	grad_norm 1.0174 (1.6824/0.7442)	mem 16099MB
[2025-01-18 03:49:05 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][230/312]	eta 0:00:38 lr 0.002518	time 0.4837 (0.4751)	model_time 0.4835 (0.4669)	loss 3.5978 (3.3487)	grad_norm 3.2599 (1.6951/0.7670)	mem 16099MB
[2025-01-18 03:49:10 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][240/312]	eta 0:00:34 lr 0.002517	time 0.5158 (0.4747)	model_time 0.5157 (0.4667)	loss 3.2689 (3.3422)	grad_norm 1.4226 (1.7126/0.7781)	mem 16099MB
[2025-01-18 03:49:14 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][250/312]	eta 0:00:29 lr 0.002516	time 0.4417 (0.4743)	model_time 0.4412 (0.4667)	loss 3.8921 (3.3394)	grad_norm 1.0337 (1.7120/0.7697)	mem 16099MB
[2025-01-18 03:49:19 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][260/312]	eta 0:00:24 lr 0.002516	time 0.4535 (0.4735)	model_time 0.4530 (0.4661)	loss 3.7422 (3.3483)	grad_norm 1.0488 (1.6953/0.7629)	mem 16099MB
[2025-01-18 03:49:23 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][270/312]	eta 0:00:19 lr 0.002515	time 0.4518 (0.4729)	model_time 0.4517 (0.4658)	loss 3.3916 (3.3399)	grad_norm 1.2644 (1.6942/0.7710)	mem 16099MB
[2025-01-18 03:49:28 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][280/312]	eta 0:00:15 lr 0.002514	time 0.4469 (0.4727)	model_time 0.4467 (0.4658)	loss 3.1467 (3.3409)	grad_norm 0.7218 (1.6956/0.7661)	mem 16099MB
[2025-01-18 03:49:33 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][290/312]	eta 0:00:10 lr 0.002514	time 0.4406 (0.4725)	model_time 0.4402 (0.4659)	loss 2.3943 (3.3367)	grad_norm 2.8570 (1.7054/0.7658)	mem 16099MB
[2025-01-18 03:49:37 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][300/312]	eta 0:00:05 lr 0.002513	time 0.4499 (0.4727)	model_time 0.4498 (0.4662)	loss 3.5130 (3.3303)	grad_norm 1.0339 (1.7127/0.7681)	mem 16099MB
[2025-01-18 03:49:42 internimage_t_1k_224] (main.py 510): INFO Train: [125/300][310/312]	eta 0:00:00 lr 0.002513	time 0.4375 (0.4725)	model_time 0.4374 (0.4663)	loss 3.2943 (3.3367)	grad_norm 1.9649 (1.6958/0.7616)	mem 16099MB
[2025-01-18 03:49:43 internimage_t_1k_224] (main.py 519): INFO EPOCH 125 training takes 0:02:27
[2025-01-18 03:49:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_125.pth saving......
[2025-01-18 03:49:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_125.pth saved !!!
[2025-01-18 03:49:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.465 (7.465)	Loss 0.8632 (0.8632)	Acc@1 81.909 (81.909)	Acc@5 96.338 (96.338)	Mem 16099MB
[2025-01-18 03:49:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.004)	Loss 1.2316 (1.0454)	Acc@1 74.072 (78.305)	Acc@5 92.261 (94.471)	Mem 16099MB
[2025-01-18 03:49:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:125] * Acc@1 78.205 Acc@5 94.504
[2025-01-18 03:49:55 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.2%
[2025-01-18 03:49:55 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.31%
[2025-01-18 03:50:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.247 (8.247)	Loss 0.8284 (0.8284)	Acc@1 82.202 (82.202)	Acc@5 96.826 (96.826)	Mem 16099MB
[2025-01-18 03:50:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.113)	Loss 1.1824 (0.9759)	Acc@1 73.413 (79.277)	Acc@5 92.651 (94.889)	Mem 16099MB
[2025-01-18 03:50:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:125] * Acc@1 79.175 Acc@5 94.910
[2025-01-18 03:50:07 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.2%
[2025-01-18 03:50:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:50:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:50:09 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.17%
[2025-01-18 03:50:12 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][0/312]	eta 0:14:23 lr 0.002512	time 2.7678 (2.7678)	model_time 0.4833 (0.4833)	loss 3.2053 (3.2053)	grad_norm 1.5817 (1.5817/0.0000)	mem 16099MB
[2025-01-18 03:50:16 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][10/312]	eta 0:03:24 lr 0.002512	time 0.4641 (0.6764)	model_time 0.4637 (0.4683)	loss 3.9606 (3.5051)	grad_norm 1.7589 (1.8827/0.8552)	mem 16099MB
[2025-01-18 03:50:21 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][20/312]	eta 0:02:48 lr 0.002511	time 0.4507 (0.5777)	model_time 0.4503 (0.4686)	loss 4.3622 (3.2773)	grad_norm 3.1962 (1.9233/0.7822)	mem 16099MB
[2025-01-18 03:50:26 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][30/312]	eta 0:02:31 lr 0.002510	time 0.4493 (0.5389)	model_time 0.4491 (0.4649)	loss 3.2456 (3.2840)	grad_norm 2.7087 (2.4111/1.4781)	mem 16099MB
[2025-01-18 03:50:30 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][40/312]	eta 0:02:23 lr 0.002510	time 0.4682 (0.5274)	model_time 0.4681 (0.4714)	loss 4.2194 (3.3619)	grad_norm 1.4143 (2.1660/1.3600)	mem 16099MB
[2025-01-18 03:50:35 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][50/312]	eta 0:02:15 lr 0.002509	time 0.4491 (0.5165)	model_time 0.4487 (0.4713)	loss 3.9616 (3.3906)	grad_norm 1.2348 (2.0390/1.2729)	mem 16099MB
[2025-01-18 03:50:40 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][60/312]	eta 0:02:08 lr 0.002509	time 0.4545 (0.5099)	model_time 0.4544 (0.4720)	loss 2.8369 (3.3852)	grad_norm 1.4931 (1.9211/1.1978)	mem 16099MB
[2025-01-18 03:50:45 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][70/312]	eta 0:02:01 lr 0.002508	time 0.4544 (0.5037)	model_time 0.4543 (0.4712)	loss 4.3644 (3.3939)	grad_norm 2.3340 (1.8526/1.1337)	mem 16099MB
[2025-01-18 03:50:49 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][80/312]	eta 0:01:56 lr 0.002507	time 0.4403 (0.5001)	model_time 0.4401 (0.4716)	loss 3.4910 (3.3870)	grad_norm 1.2242 (1.8480/1.0757)	mem 16099MB
[2025-01-18 03:50:54 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][90/312]	eta 0:01:50 lr 0.002507	time 0.4541 (0.4959)	model_time 0.4536 (0.4704)	loss 3.2139 (3.4196)	grad_norm 1.4997 (1.8100/1.0271)	mem 16099MB
[2025-01-18 03:50:59 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][100/312]	eta 0:01:44 lr 0.002506	time 0.4753 (0.4924)	model_time 0.4752 (0.4694)	loss 2.2972 (3.4102)	grad_norm 2.3983 (1.7554/0.9999)	mem 16099MB
[2025-01-18 03:51:03 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][110/312]	eta 0:01:38 lr 0.002505	time 0.5402 (0.4897)	model_time 0.5398 (0.4687)	loss 3.5420 (3.4195)	grad_norm 2.4877 (1.7601/0.9698)	mem 16099MB
[2025-01-18 03:51:08 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][120/312]	eta 0:01:33 lr 0.002505	time 0.4709 (0.4876)	model_time 0.4707 (0.4683)	loss 3.5897 (3.4086)	grad_norm 1.1603 (1.7901/0.9630)	mem 16099MB
[2025-01-18 03:51:12 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][130/312]	eta 0:01:28 lr 0.002504	time 0.4450 (0.4854)	model_time 0.4446 (0.4676)	loss 3.4656 (3.3930)	grad_norm 1.1185 (1.7703/0.9389)	mem 16099MB
[2025-01-18 03:51:17 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][140/312]	eta 0:01:23 lr 0.002503	time 0.4498 (0.4838)	model_time 0.4494 (0.4672)	loss 3.3734 (3.3951)	grad_norm 1.9231 (1.7424/0.9161)	mem 16099MB
[2025-01-18 03:51:22 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][150/312]	eta 0:01:18 lr 0.002503	time 0.4508 (0.4824)	model_time 0.4506 (0.4669)	loss 3.5003 (3.3835)	grad_norm 2.3846 (1.7244/0.8994)	mem 16099MB
[2025-01-18 03:51:26 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][160/312]	eta 0:01:13 lr 0.002502	time 0.4426 (0.4823)	model_time 0.4424 (0.4678)	loss 3.1537 (3.3822)	grad_norm 2.3752 (1.7393/0.8928)	mem 16099MB
[2025-01-18 03:51:31 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][170/312]	eta 0:01:08 lr 0.002501	time 0.4413 (0.4820)	model_time 0.4411 (0.4683)	loss 3.5358 (3.3879)	grad_norm 2.6695 (1.7274/0.8755)	mem 16099MB
[2025-01-18 03:51:36 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][180/312]	eta 0:01:03 lr 0.002501	time 0.4506 (0.4804)	model_time 0.4501 (0.4674)	loss 3.6869 (3.3745)	grad_norm 3.8193 (1.7579/0.9051)	mem 16099MB
[2025-01-18 03:51:40 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][190/312]	eta 0:00:58 lr 0.002500	time 0.4856 (0.4792)	model_time 0.4854 (0.4669)	loss 3.3706 (3.3782)	grad_norm 1.1858 (1.7546/0.8886)	mem 16099MB
[2025-01-18 03:51:45 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][200/312]	eta 0:00:53 lr 0.002500	time 0.4548 (0.4782)	model_time 0.4546 (0.4664)	loss 3.7069 (3.3817)	grad_norm 0.8166 (1.7465/0.8736)	mem 16099MB
[2025-01-18 03:51:50 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][210/312]	eta 0:00:48 lr 0.002499	time 0.4732 (0.4776)	model_time 0.4730 (0.4664)	loss 4.0777 (3.3965)	grad_norm 1.2908 (1.7609/0.8819)	mem 16099MB
[2025-01-18 03:51:54 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][220/312]	eta 0:00:43 lr 0.002498	time 0.4513 (0.4769)	model_time 0.4509 (0.4662)	loss 2.0942 (3.3876)	grad_norm 1.1504 (1.7879/0.8932)	mem 16099MB
[2025-01-18 03:51:59 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][230/312]	eta 0:00:39 lr 0.002498	time 0.4461 (0.4769)	model_time 0.4459 (0.4666)	loss 2.8612 (3.3753)	grad_norm 1.5123 (1.7636/0.8831)	mem 16099MB
[2025-01-18 03:52:04 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][240/312]	eta 0:00:34 lr 0.002497	time 0.4609 (0.4763)	model_time 0.4605 (0.4664)	loss 3.5069 (3.3632)	grad_norm 3.2794 (1.7535/0.8779)	mem 16099MB
[2025-01-18 03:52:08 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][250/312]	eta 0:00:29 lr 0.002496	time 0.4548 (0.4764)	model_time 0.4544 (0.4669)	loss 3.9351 (3.3601)	grad_norm 1.1895 (1.7496/0.8712)	mem 16099MB
[2025-01-18 03:52:13 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][260/312]	eta 0:00:24 lr 0.002496	time 0.4416 (0.4764)	model_time 0.4411 (0.4672)	loss 3.3774 (3.3605)	grad_norm 2.7580 (1.7454/0.8607)	mem 16099MB
[2025-01-18 03:52:18 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][270/312]	eta 0:00:19 lr 0.002495	time 0.4496 (0.4757)	model_time 0.4494 (0.4669)	loss 3.7391 (3.3710)	grad_norm 1.0191 (1.7482/0.8653)	mem 16099MB
[2025-01-18 03:52:23 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][280/312]	eta 0:00:15 lr 0.002494	time 0.4413 (0.4759)	model_time 0.4408 (0.4673)	loss 3.7749 (3.3781)	grad_norm 0.9202 (1.7382/0.8569)	mem 16099MB
[2025-01-18 03:52:27 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][290/312]	eta 0:00:10 lr 0.002494	time 0.4588 (0.4763)	model_time 0.4586 (0.4680)	loss 3.3753 (3.3789)	grad_norm 2.2998 (1.7404/0.8501)	mem 16099MB
[2025-01-18 03:52:32 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][300/312]	eta 0:00:05 lr 0.002493	time 0.4387 (0.4764)	model_time 0.4386 (0.4685)	loss 3.5386 (3.3709)	grad_norm 1.0255 (1.7250/0.8415)	mem 16099MB
[2025-01-18 03:52:37 internimage_t_1k_224] (main.py 510): INFO Train: [126/300][310/312]	eta 0:00:00 lr 0.002492	time 0.4385 (0.4759)	model_time 0.4384 (0.4681)	loss 3.3173 (3.3731)	grad_norm 1.1945 (1.7210/0.8309)	mem 16099MB
[2025-01-18 03:52:37 internimage_t_1k_224] (main.py 519): INFO EPOCH 126 training takes 0:02:28
[2025-01-18 03:52:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_126.pth saving......
[2025-01-18 03:52:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_126.pth saved !!!
[2025-01-18 03:52:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.498 (7.498)	Loss 0.8860 (0.8860)	Acc@1 81.787 (81.787)	Acc@5 96.265 (96.265)	Mem 16099MB
[2025-01-18 03:52:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.025)	Loss 1.2045 (1.0348)	Acc@1 73.560 (78.445)	Acc@5 92.554 (94.411)	Mem 16099MB
[2025-01-18 03:52:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:126] * Acc@1 78.363 Acc@5 94.464
[2025-01-18 03:52:50 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.4%
[2025-01-18 03:52:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 03:52:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 03:52:51 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.36%
[2025-01-18 03:52:59 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.700 (7.700)	Loss 0.8271 (0.8271)	Acc@1 82.251 (82.251)	Acc@5 96.802 (96.802)	Mem 16099MB
[2025-01-18 03:53:03 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.108 (1.038)	Loss 1.1787 (0.9738)	Acc@1 73.535 (79.343)	Acc@5 92.700 (94.926)	Mem 16099MB
[2025-01-18 03:53:03 internimage_t_1k_224] (main.py 575): INFO [Epoch:126] * Acc@1 79.245 Acc@5 94.938
[2025-01-18 03:53:03 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.2%
[2025-01-18 03:53:03 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:53:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:53:04 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.24%
[2025-01-18 03:53:06 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][0/312]	eta 0:11:15 lr 0.002492	time 2.1660 (2.1660)	model_time 0.4986 (0.4986)	loss 3.5741 (3.5741)	grad_norm 1.0170 (1.0170/0.0000)	mem 16099MB
[2025-01-18 03:53:11 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][10/312]	eta 0:03:05 lr 0.002492	time 0.4544 (0.6137)	model_time 0.4543 (0.4618)	loss 3.1992 (3.3722)	grad_norm 1.6603 (1.2970/0.3257)	mem 16099MB
[2025-01-18 03:53:16 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][20/312]	eta 0:02:37 lr 0.002491	time 0.4764 (0.5397)	model_time 0.4759 (0.4600)	loss 3.5410 (3.4127)	grad_norm 1.5233 (1.4953/0.5966)	mem 16099MB
[2025-01-18 03:53:20 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][30/312]	eta 0:02:25 lr 0.002490	time 0.4470 (0.5143)	model_time 0.4463 (0.4602)	loss 2.3815 (3.3814)	grad_norm 0.8212 (1.7161/0.8215)	mem 16099MB
[2025-01-18 03:53:25 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][40/312]	eta 0:02:17 lr 0.002490	time 0.4521 (0.5037)	model_time 0.4516 (0.4627)	loss 2.3432 (3.3212)	grad_norm 3.0384 (1.7173/0.7944)	mem 16099MB
[2025-01-18 03:53:30 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][50/312]	eta 0:02:09 lr 0.002489	time 0.4550 (0.4952)	model_time 0.4543 (0.4622)	loss 3.0468 (3.3471)	grad_norm 1.4031 (1.7163/0.8224)	mem 16099MB
[2025-01-18 03:53:34 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][60/312]	eta 0:02:03 lr 0.002488	time 0.5402 (0.4911)	model_time 0.5401 (0.4634)	loss 3.5438 (3.3681)	grad_norm 1.0158 (1.7360/0.8261)	mem 16099MB
[2025-01-18 03:53:39 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][70/312]	eta 0:01:58 lr 0.002488	time 0.4537 (0.4887)	model_time 0.4535 (0.4648)	loss 3.3663 (3.3659)	grad_norm 1.1343 (1.6784/0.7984)	mem 16099MB
[2025-01-18 03:53:44 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][80/312]	eta 0:01:52 lr 0.002487	time 0.4627 (0.4845)	model_time 0.4623 (0.4636)	loss 2.5933 (3.3457)	grad_norm 0.9317 (1.6976/0.7853)	mem 16099MB
[2025-01-18 03:53:48 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][90/312]	eta 0:01:47 lr 0.002486	time 0.4561 (0.4823)	model_time 0.4560 (0.4636)	loss 3.5913 (3.3307)	grad_norm 1.3470 (1.6913/0.7809)	mem 16099MB
[2025-01-18 03:53:53 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][100/312]	eta 0:01:41 lr 0.002486	time 0.4487 (0.4810)	model_time 0.4485 (0.4641)	loss 3.6033 (3.3517)	grad_norm 1.4629 (1.7018/0.7977)	mem 16099MB
[2025-01-18 03:53:58 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][110/312]	eta 0:01:36 lr 0.002485	time 0.4507 (0.4796)	model_time 0.4502 (0.4642)	loss 3.8946 (3.3491)	grad_norm 1.3188 (1.7161/0.7899)	mem 16099MB
[2025-01-18 03:54:02 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][120/312]	eta 0:01:31 lr 0.002485	time 0.4583 (0.4781)	model_time 0.4582 (0.4640)	loss 3.5186 (3.3416)	grad_norm 1.2905 (1.7009/0.7636)	mem 16099MB
[2025-01-18 03:54:07 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][130/312]	eta 0:01:26 lr 0.002484	time 0.4575 (0.4776)	model_time 0.4574 (0.4645)	loss 3.8897 (3.3421)	grad_norm 1.6914 (1.7583/0.8114)	mem 16099MB
[2025-01-18 03:54:12 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][140/312]	eta 0:01:22 lr 0.002483	time 0.4523 (0.4773)	model_time 0.4518 (0.4651)	loss 2.4974 (3.3427)	grad_norm 4.6035 (1.8236/0.8989)	mem 16099MB
[2025-01-18 03:54:16 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][150/312]	eta 0:01:17 lr 0.002483	time 0.4442 (0.4782)	model_time 0.4441 (0.4668)	loss 2.8274 (3.3335)	grad_norm 1.0498 (1.8249/0.8964)	mem 16099MB
[2025-01-18 03:54:21 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][160/312]	eta 0:01:12 lr 0.002482	time 0.4487 (0.4777)	model_time 0.4482 (0.4669)	loss 2.7243 (3.3228)	grad_norm 0.9286 (1.8003/0.8823)	mem 16099MB
[2025-01-18 03:54:26 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][170/312]	eta 0:01:07 lr 0.002481	time 0.4678 (0.4779)	model_time 0.4676 (0.4677)	loss 3.8941 (3.3150)	grad_norm 1.1923 (1.7565/0.8748)	mem 16099MB
[2025-01-18 03:54:31 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][180/312]	eta 0:01:02 lr 0.002481	time 0.4702 (0.4768)	model_time 0.4697 (0.4673)	loss 2.3274 (3.3126)	grad_norm 1.0255 (1.7253/0.8615)	mem 16099MB
[2025-01-18 03:54:35 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][190/312]	eta 0:00:58 lr 0.002480	time 0.4441 (0.4758)	model_time 0.4436 (0.4667)	loss 3.6344 (3.3313)	grad_norm 1.4947 (1.6985/0.8509)	mem 16099MB
[2025-01-18 03:54:40 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][200/312]	eta 0:00:53 lr 0.002479	time 0.4614 (0.4748)	model_time 0.4612 (0.4661)	loss 2.2815 (3.3229)	grad_norm 1.1084 (1.6757/0.8369)	mem 16099MB
[2025-01-18 03:54:44 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][210/312]	eta 0:00:48 lr 0.002479	time 0.4508 (0.4743)	model_time 0.4504 (0.4660)	loss 3.4745 (3.3234)	grad_norm 1.0384 (1.6556/0.8247)	mem 16099MB
[2025-01-18 03:54:49 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][220/312]	eta 0:00:43 lr 0.002478	time 0.4493 (0.4739)	model_time 0.4488 (0.4660)	loss 2.5033 (3.3119)	grad_norm 2.3519 (1.6670/0.8213)	mem 16099MB
[2025-01-18 03:54:54 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][230/312]	eta 0:00:38 lr 0.002477	time 0.4495 (0.4742)	model_time 0.4490 (0.4666)	loss 3.6019 (3.3185)	grad_norm 1.7844 (1.6579/0.8060)	mem 16099MB
[2025-01-18 03:54:58 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][240/312]	eta 0:00:34 lr 0.002477	time 0.5416 (0.4738)	model_time 0.5414 (0.4665)	loss 3.4954 (3.3186)	grad_norm 2.1171 (1.6503/0.7947)	mem 16099MB
[2025-01-18 03:55:03 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][250/312]	eta 0:00:29 lr 0.002476	time 0.4484 (0.4731)	model_time 0.4482 (0.4661)	loss 3.3076 (3.3275)	grad_norm 3.4886 (1.6739/0.8172)	mem 16099MB
[2025-01-18 03:55:08 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][260/312]	eta 0:00:24 lr 0.002475	time 0.4530 (0.4724)	model_time 0.4525 (0.4656)	loss 3.3370 (3.3163)	grad_norm 2.4240 (1.7108/0.8689)	mem 16099MB
[2025-01-18 03:55:12 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][270/312]	eta 0:00:19 lr 0.002475	time 0.4604 (0.4721)	model_time 0.4600 (0.4656)	loss 3.0972 (3.3109)	grad_norm 1.4070 (1.7000/0.8558)	mem 16099MB
[2025-01-18 03:55:17 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][280/312]	eta 0:00:15 lr 0.002474	time 0.4448 (0.4721)	model_time 0.4446 (0.4658)	loss 3.3873 (3.3082)	grad_norm 0.8941 (1.6955/0.8453)	mem 16099MB
[2025-01-18 03:55:21 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][290/312]	eta 0:00:10 lr 0.002474	time 0.4534 (0.4714)	model_time 0.4532 (0.4653)	loss 3.5153 (3.3079)	grad_norm 1.1183 (1.6766/0.8382)	mem 16099MB
[2025-01-18 03:55:26 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][300/312]	eta 0:00:05 lr 0.002473	time 0.4391 (0.4708)	model_time 0.4390 (0.4649)	loss 3.4523 (3.3084)	grad_norm 1.8511 (1.6678/0.8291)	mem 16099MB
[2025-01-18 03:55:31 internimage_t_1k_224] (main.py 510): INFO Train: [127/300][310/312]	eta 0:00:00 lr 0.002472	time 0.4375 (0.4705)	model_time 0.4374 (0.4647)	loss 3.5162 (3.3031)	grad_norm 3.5562 (1.6870/0.8398)	mem 16099MB
[2025-01-18 03:55:31 internimage_t_1k_224] (main.py 519): INFO EPOCH 127 training takes 0:02:26
[2025-01-18 03:55:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_127.pth saving......
[2025-01-18 03:55:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_127.pth saved !!!
[2025-01-18 03:55:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.248 (7.248)	Loss 0.8078 (0.8078)	Acc@1 81.812 (81.812)	Acc@5 96.289 (96.289)	Mem 16099MB
[2025-01-18 03:55:43 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.974)	Loss 1.2038 (0.9847)	Acc@1 72.754 (78.285)	Acc@5 92.285 (94.513)	Mem 16099MB
[2025-01-18 03:55:43 internimage_t_1k_224] (main.py 575): INFO [Epoch:127] * Acc@1 78.211 Acc@5 94.524
[2025-01-18 03:55:43 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.2%
[2025-01-18 03:55:43 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.36%
[2025-01-18 03:55:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.351 (8.351)	Loss 0.8255 (0.8255)	Acc@1 82.422 (82.422)	Acc@5 96.826 (96.826)	Mem 16099MB
[2025-01-18 03:55:56 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.132)	Loss 1.1756 (0.9716)	Acc@1 73.682 (79.423)	Acc@5 92.749 (94.957)	Mem 16099MB
[2025-01-18 03:55:56 internimage_t_1k_224] (main.py 575): INFO [Epoch:127] * Acc@1 79.323 Acc@5 94.960
[2025-01-18 03:55:56 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.3%
[2025-01-18 03:55:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:55:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:55:57 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.32%
[2025-01-18 03:56:00 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][0/312]	eta 0:12:50 lr 0.002472	time 2.4710 (2.4710)	model_time 0.4783 (0.4783)	loss 3.6270 (3.6270)	grad_norm 1.3582 (1.3582/0.0000)	mem 16099MB
[2025-01-18 03:56:04 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][10/312]	eta 0:03:16 lr 0.002471	time 0.4489 (0.6499)	model_time 0.4487 (0.4685)	loss 4.0365 (3.5772)	grad_norm 1.0921 (1.8017/0.7450)	mem 16099MB
[2025-01-18 03:56:09 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][20/312]	eta 0:02:45 lr 0.002471	time 0.4496 (0.5671)	model_time 0.4491 (0.4720)	loss 2.5406 (3.4338)	grad_norm 2.3751 (1.7545/0.7706)	mem 16099MB
[2025-01-18 03:56:14 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][30/312]	eta 0:02:33 lr 0.002470	time 0.4444 (0.5431)	model_time 0.4442 (0.4786)	loss 2.9620 (3.3438)	grad_norm 1.6410 (1.6954/0.6922)	mem 16099MB
[2025-01-18 03:56:19 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][40/312]	eta 0:02:22 lr 0.002470	time 0.4433 (0.5223)	model_time 0.4429 (0.4734)	loss 4.0178 (3.3158)	grad_norm 0.8709 (1.6265/0.6766)	mem 16099MB
[2025-01-18 03:56:23 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][50/312]	eta 0:02:13 lr 0.002469	time 0.4522 (0.5101)	model_time 0.4520 (0.4707)	loss 3.4614 (3.3781)	grad_norm 1.8864 (1.6091/0.6310)	mem 16099MB
[2025-01-18 03:56:28 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][60/312]	eta 0:02:06 lr 0.002468	time 0.4507 (0.5023)	model_time 0.4502 (0.4693)	loss 3.4267 (3.3866)	grad_norm 1.6237 (1.5838/0.6019)	mem 16099MB
[2025-01-18 03:56:33 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][70/312]	eta 0:02:00 lr 0.002468	time 0.4710 (0.4972)	model_time 0.4706 (0.4688)	loss 3.9454 (3.3621)	grad_norm 2.1143 (1.5396/0.5965)	mem 16099MB
[2025-01-18 03:56:37 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][80/312]	eta 0:01:54 lr 0.002467	time 0.4518 (0.4916)	model_time 0.4516 (0.4667)	loss 3.3955 (3.3511)	grad_norm 1.4744 (1.5699/0.6103)	mem 16099MB
[2025-01-18 03:56:42 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][90/312]	eta 0:01:48 lr 0.002466	time 0.4578 (0.4893)	model_time 0.4577 (0.4671)	loss 2.5910 (3.3201)	grad_norm 0.8788 (1.5182/0.6000)	mem 16099MB
[2025-01-18 03:56:46 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][100/312]	eta 0:01:43 lr 0.002466	time 0.4575 (0.4862)	model_time 0.4570 (0.4662)	loss 4.0615 (3.3142)	grad_norm 1.2594 (1.5055/0.5923)	mem 16099MB
[2025-01-18 03:56:51 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][110/312]	eta 0:01:37 lr 0.002465	time 0.4507 (0.4840)	model_time 0.4502 (0.4657)	loss 3.7294 (3.2970)	grad_norm 1.6041 (1.5437/0.5975)	mem 16099MB
[2025-01-18 03:56:56 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][120/312]	eta 0:01:32 lr 0.002464	time 0.4542 (0.4830)	model_time 0.4538 (0.4662)	loss 3.2385 (3.2995)	grad_norm 2.3333 (1.5673/0.6102)	mem 16099MB
[2025-01-18 03:57:01 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][130/312]	eta 0:01:27 lr 0.002464	time 0.4628 (0.4829)	model_time 0.4626 (0.4673)	loss 3.4359 (3.3014)	grad_norm 3.6190 (1.6195/0.6436)	mem 16099MB
[2025-01-18 03:57:05 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][140/312]	eta 0:01:23 lr 0.002463	time 0.5307 (0.4836)	model_time 0.5305 (0.4691)	loss 2.3905 (3.3083)	grad_norm 1.8733 (1.6251/0.6315)	mem 16099MB
[2025-01-18 03:57:10 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][150/312]	eta 0:01:18 lr 0.002462	time 0.5398 (0.4835)	model_time 0.5393 (0.4700)	loss 2.6689 (3.3028)	grad_norm 1.0364 (1.6658/0.6520)	mem 16099MB
[2025-01-18 03:57:15 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][160/312]	eta 0:01:13 lr 0.002462	time 0.4858 (0.4824)	model_time 0.4856 (0.4697)	loss 4.0483 (3.3174)	grad_norm 2.3836 (1.6444/0.6494)	mem 16099MB
[2025-01-18 03:57:20 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][170/312]	eta 0:01:08 lr 0.002461	time 0.4549 (0.4812)	model_time 0.4547 (0.4692)	loss 3.7930 (3.3099)	grad_norm 3.2286 (1.7331/0.8387)	mem 16099MB
[2025-01-18 03:57:24 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][180/312]	eta 0:01:03 lr 0.002460	time 0.4400 (0.4806)	model_time 0.4398 (0.4693)	loss 3.8512 (3.3147)	grad_norm 1.0575 (1.7551/0.8445)	mem 16099MB
[2025-01-18 03:57:29 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][190/312]	eta 0:00:58 lr 0.002460	time 0.4623 (0.4791)	model_time 0.4618 (0.4683)	loss 2.9746 (3.2997)	grad_norm 0.8158 (1.7486/0.8387)	mem 16099MB
[2025-01-18 03:57:33 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][200/312]	eta 0:00:53 lr 0.002459	time 0.4481 (0.4786)	model_time 0.4476 (0.4683)	loss 3.9410 (3.2986)	grad_norm 1.2598 (1.7232/0.8269)	mem 16099MB
[2025-01-18 03:57:38 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][210/312]	eta 0:00:48 lr 0.002459	time 0.4397 (0.4774)	model_time 0.4396 (0.4675)	loss 3.5949 (3.3080)	grad_norm 1.8166 (1.7135/0.8133)	mem 16099MB
[2025-01-18 03:57:43 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][220/312]	eta 0:00:43 lr 0.002458	time 0.4421 (0.4764)	model_time 0.4418 (0.4670)	loss 3.1754 (3.3097)	grad_norm 2.0822 (1.7041/0.8001)	mem 16099MB
[2025-01-18 03:57:47 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][230/312]	eta 0:00:39 lr 0.002457	time 0.4768 (0.4760)	model_time 0.4767 (0.4670)	loss 3.9888 (3.3057)	grad_norm 1.1659 (1.6905/0.7928)	mem 16099MB
[2025-01-18 03:57:52 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][240/312]	eta 0:00:34 lr 0.002457	time 0.4559 (0.4753)	model_time 0.4554 (0.4666)	loss 2.6405 (3.3071)	grad_norm 1.2230 (1.6731/0.7818)	mem 16099MB
[2025-01-18 03:57:56 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][250/312]	eta 0:00:29 lr 0.002456	time 0.5356 (0.4747)	model_time 0.5355 (0.4664)	loss 2.7931 (3.3028)	grad_norm 2.6155 (1.6686/0.7739)	mem 16099MB
[2025-01-18 03:58:01 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][260/312]	eta 0:00:24 lr 0.002455	time 0.4621 (0.4750)	model_time 0.4619 (0.4670)	loss 4.0478 (3.3024)	grad_norm 0.8520 (1.6535/0.7683)	mem 16099MB
[2025-01-18 03:58:06 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][270/312]	eta 0:00:19 lr 0.002455	time 0.4793 (0.4746)	model_time 0.4791 (0.4669)	loss 3.2496 (3.3070)	grad_norm 5.1610 (1.6829/0.8100)	mem 16099MB
[2025-01-18 03:58:11 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][280/312]	eta 0:00:15 lr 0.002454	time 0.4442 (0.4745)	model_time 0.4438 (0.4670)	loss 3.5890 (3.3044)	grad_norm 1.2934 (1.6959/0.8174)	mem 16099MB
[2025-01-18 03:58:15 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][290/312]	eta 0:00:10 lr 0.002453	time 0.4504 (0.4745)	model_time 0.4502 (0.4672)	loss 3.5712 (3.3016)	grad_norm 1.2560 (1.6874/0.8083)	mem 16099MB
[2025-01-18 03:58:20 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][300/312]	eta 0:00:05 lr 0.002453	time 0.4380 (0.4743)	model_time 0.4379 (0.4673)	loss 2.4204 (3.2974)	grad_norm 1.2099 (1.6816/0.7982)	mem 16099MB
[2025-01-18 03:58:25 internimage_t_1k_224] (main.py 510): INFO Train: [128/300][310/312]	eta 0:00:00 lr 0.002452	time 0.5161 (0.4742)	model_time 0.5160 (0.4674)	loss 3.6541 (3.2953)	grad_norm 1.2790 (1.6634/0.7894)	mem 16099MB
[2025-01-18 03:58:25 internimage_t_1k_224] (main.py 519): INFO EPOCH 128 training takes 0:02:27
[2025-01-18 03:58:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_128.pth saving......
[2025-01-18 03:58:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_128.pth saved !!!
[2025-01-18 03:58:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.476 (7.476)	Loss 0.8798 (0.8798)	Acc@1 81.641 (81.641)	Acc@5 96.143 (96.143)	Mem 16099MB
[2025-01-18 03:58:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.014)	Loss 1.1933 (1.0161)	Acc@1 74.072 (78.880)	Acc@5 92.798 (94.600)	Mem 16099MB
[2025-01-18 03:58:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:128] * Acc@1 78.739 Acc@5 94.596
[2025-01-18 03:58:38 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.7%
[2025-01-18 03:58:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 03:58:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 03:58:39 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 03:58:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.573 (7.573)	Loss 0.8238 (0.8238)	Acc@1 82.544 (82.544)	Acc@5 96.826 (96.826)	Mem 16099MB
[2025-01-18 03:58:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.005)	Loss 1.1721 (0.9694)	Acc@1 73.853 (79.510)	Acc@5 92.871 (94.995)	Mem 16099MB
[2025-01-18 03:58:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:128] * Acc@1 79.411 Acc@5 94.998
[2025-01-18 03:58:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.4%
[2025-01-18 03:58:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 03:58:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 03:58:52 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.41%
[2025-01-18 03:58:54 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][0/312]	eta 0:14:17 lr 0.002452	time 2.7472 (2.7472)	model_time 0.4626 (0.4626)	loss 3.4812 (3.4812)	grad_norm 1.0542 (1.0542/0.0000)	mem 16099MB
[2025-01-18 03:58:59 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][10/312]	eta 0:03:25 lr 0.002451	time 0.4458 (0.6793)	model_time 0.4456 (0.4618)	loss 3.0614 (3.3499)	grad_norm 1.1360 (1.2899/0.4632)	mem 16099MB
[2025-01-18 03:59:04 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][20/312]	eta 0:02:48 lr 0.002451	time 0.4576 (0.5779)	model_time 0.4574 (0.4638)	loss 3.9048 (3.4891)	grad_norm 1.1796 (1.5402/0.6235)	mem 16099MB
[2025-01-18 03:59:08 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][30/312]	eta 0:02:31 lr 0.002450	time 0.4449 (0.5386)	model_time 0.4444 (0.4611)	loss 3.8469 (3.4626)	grad_norm 1.3142 (1.5293/0.5516)	mem 16099MB
[2025-01-18 03:59:13 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][40/312]	eta 0:02:21 lr 0.002449	time 0.4428 (0.5217)	model_time 0.4427 (0.4630)	loss 3.5921 (3.4878)	grad_norm 1.3014 (1.5383/0.5273)	mem 16099MB
[2025-01-18 03:59:18 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][50/312]	eta 0:02:13 lr 0.002449	time 0.4497 (0.5113)	model_time 0.4496 (0.4641)	loss 3.2416 (3.4708)	grad_norm 1.1809 (1.7294/0.7831)	mem 16099MB
[2025-01-18 03:59:22 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][60/312]	eta 0:02:07 lr 0.002448	time 0.5657 (0.5040)	model_time 0.5655 (0.4645)	loss 3.9979 (3.4841)	grad_norm 3.3651 (1.7016/0.7787)	mem 16099MB
[2025-01-18 03:59:27 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][70/312]	eta 0:02:00 lr 0.002447	time 0.4604 (0.4967)	model_time 0.4603 (0.4627)	loss 2.9451 (3.4578)	grad_norm 0.9847 (1.7009/0.7429)	mem 16099MB
[2025-01-18 03:59:32 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][80/312]	eta 0:01:54 lr 0.002447	time 0.4517 (0.4941)	model_time 0.4514 (0.4642)	loss 3.5260 (3.4309)	grad_norm 1.2026 (1.6422/0.7283)	mem 16099MB
[2025-01-18 03:59:36 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][90/312]	eta 0:01:48 lr 0.002446	time 0.4543 (0.4899)	model_time 0.4541 (0.4632)	loss 3.0733 (3.3978)	grad_norm 2.4787 (1.6348/0.7073)	mem 16099MB
[2025-01-18 03:59:41 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][100/312]	eta 0:01:43 lr 0.002445	time 0.4666 (0.4872)	model_time 0.4665 (0.4632)	loss 2.4889 (3.3740)	grad_norm 1.4502 (1.6402/0.6789)	mem 16099MB
[2025-01-18 03:59:45 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][110/312]	eta 0:01:38 lr 0.002445	time 0.4566 (0.4855)	model_time 0.4564 (0.4637)	loss 3.0761 (3.3615)	grad_norm 1.2737 (1.6271/0.6574)	mem 16099MB
[2025-01-18 03:59:50 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][120/312]	eta 0:01:32 lr 0.002444	time 0.4630 (0.4830)	model_time 0.4626 (0.4629)	loss 3.2576 (3.3523)	grad_norm 2.2017 (1.6891/0.7369)	mem 16099MB
[2025-01-18 03:59:55 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][130/312]	eta 0:01:27 lr 0.002443	time 0.4952 (0.4827)	model_time 0.4948 (0.4641)	loss 2.9151 (3.3548)	grad_norm 1.6824 (1.6838/0.7329)	mem 16099MB
[2025-01-18 03:59:59 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][140/312]	eta 0:01:22 lr 0.002443	time 0.4486 (0.4818)	model_time 0.4481 (0.4645)	loss 3.3364 (3.3616)	grad_norm 1.2760 (1.7139/0.7431)	mem 16099MB
[2025-01-18 04:00:04 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][150/312]	eta 0:01:17 lr 0.002442	time 0.4602 (0.4813)	model_time 0.4597 (0.4651)	loss 2.8221 (3.3569)	grad_norm 1.3501 (1.6985/0.7352)	mem 16099MB
[2025-01-18 04:00:09 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][160/312]	eta 0:01:12 lr 0.002442	time 0.4493 (0.4796)	model_time 0.4491 (0.4644)	loss 3.4168 (3.3380)	grad_norm 1.0362 (1.6622/0.7276)	mem 16099MB
[2025-01-18 04:00:14 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][170/312]	eta 0:01:08 lr 0.002441	time 0.4544 (0.4795)	model_time 0.4540 (0.4652)	loss 4.2750 (3.3335)	grad_norm 1.0845 (1.6731/0.7351)	mem 16099MB
[2025-01-18 04:00:18 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][180/312]	eta 0:01:03 lr 0.002440	time 0.4661 (0.4791)	model_time 0.4657 (0.4655)	loss 3.3078 (3.3324)	grad_norm 1.9301 (1.6692/0.7194)	mem 16099MB
[2025-01-18 04:00:23 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][190/312]	eta 0:00:58 lr 0.002440	time 0.4475 (0.4779)	model_time 0.4474 (0.4650)	loss 2.2760 (3.3243)	grad_norm 2.1126 (1.6674/0.7161)	mem 16099MB
[2025-01-18 04:00:28 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][200/312]	eta 0:00:53 lr 0.002439	time 0.4840 (0.4774)	model_time 0.4836 (0.4651)	loss 3.7125 (3.3304)	grad_norm 1.6654 (1.6743/0.7259)	mem 16099MB
[2025-01-18 04:00:32 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][210/312]	eta 0:00:48 lr 0.002438	time 0.4626 (0.4784)	model_time 0.4621 (0.4666)	loss 3.2945 (3.3386)	grad_norm 0.9318 (1.6734/0.7134)	mem 16099MB
[2025-01-18 04:00:37 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][220/312]	eta 0:00:43 lr 0.002438	time 0.4495 (0.4776)	model_time 0.4491 (0.4664)	loss 2.6501 (3.3510)	grad_norm 2.0886 (1.6678/0.7029)	mem 16099MB
[2025-01-18 04:00:42 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][230/312]	eta 0:00:39 lr 0.002437	time 0.4526 (0.4769)	model_time 0.4524 (0.4662)	loss 4.2013 (3.3524)	grad_norm 1.3171 (1.6625/0.6979)	mem 16099MB
[2025-01-18 04:00:46 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][240/312]	eta 0:00:34 lr 0.002436	time 0.4570 (0.4761)	model_time 0.4566 (0.4658)	loss 3.1881 (3.3587)	grad_norm 1.2478 (1.6735/0.7119)	mem 16099MB
[2025-01-18 04:00:51 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][250/312]	eta 0:00:29 lr 0.002436	time 0.4672 (0.4755)	model_time 0.4670 (0.4656)	loss 3.1271 (3.3592)	grad_norm 1.0080 (1.6562/0.7079)	mem 16099MB
[2025-01-18 04:00:56 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][260/312]	eta 0:00:24 lr 0.002435	time 0.4439 (0.4750)	model_time 0.4437 (0.4654)	loss 3.6471 (3.3590)	grad_norm 1.7317 (1.6653/0.7185)	mem 16099MB
[2025-01-18 04:01:00 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][270/312]	eta 0:00:19 lr 0.002434	time 0.4520 (0.4745)	model_time 0.4515 (0.4653)	loss 3.7165 (3.3641)	grad_norm 1.4523 (1.6546/0.7095)	mem 16099MB
[2025-01-18 04:01:05 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][280/312]	eta 0:00:15 lr 0.002434	time 0.4550 (0.4747)	model_time 0.4546 (0.4658)	loss 3.3766 (3.3686)	grad_norm 1.5805 (1.6786/0.7535)	mem 16099MB
[2025-01-18 04:01:10 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][290/312]	eta 0:00:10 lr 0.002433	time 0.4528 (0.4742)	model_time 0.4526 (0.4656)	loss 3.3022 (3.3617)	grad_norm 0.8768 (1.6721/0.7487)	mem 16099MB
[2025-01-18 04:01:14 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][300/312]	eta 0:00:05 lr 0.002432	time 0.4431 (0.4740)	model_time 0.4430 (0.4657)	loss 2.6482 (3.3531)	grad_norm 2.1423 (1.6723/0.7422)	mem 16099MB
[2025-01-18 04:01:19 internimage_t_1k_224] (main.py 510): INFO Train: [129/300][310/312]	eta 0:00:00 lr 0.002432	time 0.4396 (0.4738)	model_time 0.4395 (0.4658)	loss 3.0327 (3.3451)	grad_norm 1.3117 (1.6716/0.7402)	mem 16099MB
[2025-01-18 04:01:19 internimage_t_1k_224] (main.py 519): INFO EPOCH 129 training takes 0:02:27
[2025-01-18 04:01:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_129.pth saving......
[2025-01-18 04:01:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_129.pth saved !!!
[2025-01-18 04:01:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.398 (7.398)	Loss 0.8664 (0.8664)	Acc@1 81.689 (81.689)	Acc@5 96.338 (96.338)	Mem 16099MB
[2025-01-18 04:01:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.002)	Loss 1.2357 (1.0334)	Acc@1 72.998 (78.194)	Acc@5 92.725 (94.454)	Mem 16099MB
[2025-01-18 04:01:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:129] * Acc@1 78.129 Acc@5 94.472
[2025-01-18 04:01:32 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.1%
[2025-01-18 04:01:32 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:01:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.004 (8.004)	Loss 0.8225 (0.8225)	Acc@1 82.642 (82.642)	Acc@5 96.899 (96.899)	Mem 16099MB
[2025-01-18 04:01:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.089)	Loss 1.1688 (0.9673)	Acc@1 73.926 (79.543)	Acc@5 92.847 (95.020)	Mem 16099MB
[2025-01-18 04:01:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:129] * Acc@1 79.433 Acc@5 95.032
[2025-01-18 04:01:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.4%
[2025-01-18 04:01:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:01:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:01:45 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.43%
[2025-01-18 04:01:48 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][0/312]	eta 0:14:15 lr 0.002432	time 2.7431 (2.7431)	model_time 0.4942 (0.4942)	loss 3.0699 (3.0699)	grad_norm 2.1403 (2.1403/0.0000)	mem 16099MB
[2025-01-18 04:01:53 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][10/312]	eta 0:03:20 lr 0.002431	time 0.4569 (0.6644)	model_time 0.4567 (0.4596)	loss 3.9566 (3.5152)	grad_norm 1.0771 (2.7945/1.1247)	mem 16099MB
[2025-01-18 04:01:58 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][20/312]	eta 0:02:49 lr 0.002430	time 0.4485 (0.5805)	model_time 0.4483 (0.4730)	loss 3.6679 (3.4775)	grad_norm 1.2701 (2.3006/1.0773)	mem 16099MB
[2025-01-18 04:02:02 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][30/312]	eta 0:02:33 lr 0.002430	time 0.4394 (0.5461)	model_time 0.4389 (0.4731)	loss 3.3772 (3.3937)	grad_norm 1.0205 (2.0373/1.0357)	mem 16099MB
[2025-01-18 04:02:07 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][40/312]	eta 0:02:23 lr 0.002429	time 0.4406 (0.5262)	model_time 0.4404 (0.4709)	loss 3.4082 (3.3648)	grad_norm 0.9511 (1.8401/0.9764)	mem 16099MB
[2025-01-18 04:02:12 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][50/312]	eta 0:02:15 lr 0.002428	time 0.4505 (0.5160)	model_time 0.4504 (0.4716)	loss 3.3977 (3.3351)	grad_norm 2.3139 (1.8804/0.9432)	mem 16099MB
[2025-01-18 04:02:16 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][60/312]	eta 0:02:07 lr 0.002428	time 0.4533 (0.5061)	model_time 0.4527 (0.4689)	loss 3.3858 (3.3329)	grad_norm 2.3204 (1.8272/0.8868)	mem 16099MB
[2025-01-18 04:02:21 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][70/312]	eta 0:02:01 lr 0.002427	time 0.4910 (0.5000)	model_time 0.4906 (0.4680)	loss 2.8659 (3.3112)	grad_norm 2.1430 (1.8290/0.8473)	mem 16099MB
[2025-01-18 04:02:25 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][80/312]	eta 0:01:54 lr 0.002426	time 0.4426 (0.4954)	model_time 0.4422 (0.4672)	loss 3.2638 (3.3094)	grad_norm 2.0188 (1.8640/0.8362)	mem 16099MB
[2025-01-18 04:02:30 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][90/312]	eta 0:01:48 lr 0.002426	time 0.4609 (0.4908)	model_time 0.4605 (0.4656)	loss 3.6731 (3.3081)	grad_norm 1.2035 (1.8215/0.8136)	mem 16099MB
[2025-01-18 04:02:35 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][100/312]	eta 0:01:43 lr 0.002425	time 0.4509 (0.4890)	model_time 0.4507 (0.4663)	loss 3.3789 (3.3010)	grad_norm 1.3545 (1.7770/0.7931)	mem 16099MB
[2025-01-18 04:02:39 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][110/312]	eta 0:01:38 lr 0.002425	time 0.4494 (0.4856)	model_time 0.4492 (0.4650)	loss 3.3819 (3.3206)	grad_norm 1.3521 (1.8095/0.7992)	mem 16099MB
[2025-01-18 04:02:44 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][120/312]	eta 0:01:32 lr 0.002424	time 0.4593 (0.4831)	model_time 0.4591 (0.4641)	loss 3.1349 (3.3104)	grad_norm 1.2446 (1.8154/0.8085)	mem 16099MB
[2025-01-18 04:02:49 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][130/312]	eta 0:01:27 lr 0.002423	time 0.4514 (0.4823)	model_time 0.4509 (0.4647)	loss 4.1525 (3.2880)	grad_norm 1.9341 (1.7992/0.7963)	mem 16099MB
[2025-01-18 04:02:53 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][140/312]	eta 0:01:22 lr 0.002423	time 0.4471 (0.4810)	model_time 0.4469 (0.4647)	loss 2.4234 (3.2849)	grad_norm 1.4214 (1.7597/0.7851)	mem 16099MB
[2025-01-18 04:02:58 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][150/312]	eta 0:01:17 lr 0.002422	time 0.5553 (0.4809)	model_time 0.5547 (0.4656)	loss 3.5543 (3.2885)	grad_norm 1.5889 (1.7351/0.7743)	mem 16099MB
[2025-01-18 04:03:03 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][160/312]	eta 0:01:13 lr 0.002421	time 0.5503 (0.4815)	model_time 0.5501 (0.4671)	loss 3.1557 (3.2970)	grad_norm 2.3692 (1.7206/0.7658)	mem 16099MB
[2025-01-18 04:03:08 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][170/312]	eta 0:01:08 lr 0.002421	time 0.4443 (0.4804)	model_time 0.4439 (0.4669)	loss 2.9012 (3.3031)	grad_norm 2.0871 (1.7554/0.7701)	mem 16099MB
[2025-01-18 04:03:12 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][180/312]	eta 0:01:03 lr 0.002420	time 0.4476 (0.4796)	model_time 0.4474 (0.4668)	loss 2.1470 (3.2945)	grad_norm 1.2184 (1.7498/0.7633)	mem 16099MB
[2025-01-18 04:03:17 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][190/312]	eta 0:00:58 lr 0.002419	time 0.4569 (0.4792)	model_time 0.4565 (0.4670)	loss 3.8155 (3.3022)	grad_norm 3.5734 (1.7511/0.7649)	mem 16099MB
[2025-01-18 04:03:21 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][200/312]	eta 0:00:53 lr 0.002419	time 0.4436 (0.4778)	model_time 0.4431 (0.4662)	loss 3.1075 (3.2991)	grad_norm 1.1333 (1.7920/0.8310)	mem 16099MB
[2025-01-18 04:03:26 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][210/312]	eta 0:00:48 lr 0.002418	time 0.4397 (0.4772)	model_time 0.4393 (0.4661)	loss 2.7163 (3.2905)	grad_norm 0.8870 (1.7944/0.8375)	mem 16099MB
[2025-01-18 04:03:31 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][220/312]	eta 0:00:43 lr 0.002417	time 0.4613 (0.4768)	model_time 0.4608 (0.4662)	loss 2.7236 (3.2924)	grad_norm 2.0478 (1.7878/0.8327)	mem 16099MB
[2025-01-18 04:03:35 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][230/312]	eta 0:00:39 lr 0.002417	time 0.4515 (0.4759)	model_time 0.4513 (0.4658)	loss 3.2253 (3.2865)	grad_norm 1.7787 (1.7703/0.8201)	mem 16099MB
[2025-01-18 04:03:40 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][240/312]	eta 0:00:34 lr 0.002416	time 0.5460 (0.4765)	model_time 0.5458 (0.4668)	loss 3.1068 (3.2801)	grad_norm 0.7265 (1.7596/0.8097)	mem 16099MB
[2025-01-18 04:03:45 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][250/312]	eta 0:00:29 lr 0.002415	time 0.4454 (0.4759)	model_time 0.4449 (0.4665)	loss 3.8346 (3.2828)	grad_norm 1.9482 (1.7681/0.8097)	mem 16099MB
[2025-01-18 04:03:50 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][260/312]	eta 0:00:24 lr 0.002415	time 0.4624 (0.4762)	model_time 0.4622 (0.4672)	loss 3.5285 (3.2862)	grad_norm 1.4865 (1.7548/0.8000)	mem 16099MB
[2025-01-18 04:03:54 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][270/312]	eta 0:00:19 lr 0.002414	time 0.4579 (0.4761)	model_time 0.4575 (0.4674)	loss 3.6273 (3.2767)	grad_norm 4.0772 (1.7663/0.8027)	mem 16099MB
[2025-01-18 04:03:59 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][280/312]	eta 0:00:15 lr 0.002413	time 0.4531 (0.4754)	model_time 0.4529 (0.4670)	loss 3.1805 (3.2695)	grad_norm 3.3077 (1.7683/0.7993)	mem 16099MB
[2025-01-18 04:04:04 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][290/312]	eta 0:00:10 lr 0.002413	time 0.4449 (0.4751)	model_time 0.4447 (0.4669)	loss 3.0161 (3.2648)	grad_norm 2.1085 (1.7605/0.7900)	mem 16099MB
[2025-01-18 04:04:08 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][300/312]	eta 0:00:05 lr 0.002412	time 0.4388 (0.4744)	model_time 0.4387 (0.4665)	loss 3.2087 (3.2720)	grad_norm 2.3280 (1.7751/0.7975)	mem 16099MB
[2025-01-18 04:04:13 internimage_t_1k_224] (main.py 510): INFO Train: [130/300][310/312]	eta 0:00:00 lr 0.002411	time 0.4374 (0.4734)	model_time 0.4373 (0.4657)	loss 3.9577 (3.2804)	grad_norm 1.1940 (1.7494/0.7678)	mem 16099MB
[2025-01-18 04:04:13 internimage_t_1k_224] (main.py 519): INFO EPOCH 130 training takes 0:02:27
[2025-01-18 04:04:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_130.pth saving......
[2025-01-18 04:04:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_130.pth saved !!!
[2025-01-18 04:04:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.372 (7.372)	Loss 0.8575 (0.8575)	Acc@1 82.007 (82.007)	Acc@5 96.289 (96.289)	Mem 16099MB
[2025-01-18 04:04:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.981)	Loss 1.1745 (0.9972)	Acc@1 73.975 (78.624)	Acc@5 92.432 (94.518)	Mem 16099MB
[2025-01-18 04:04:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:130] * Acc@1 78.571 Acc@5 94.574
[2025-01-18 04:04:25 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.6%
[2025-01-18 04:04:25 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:04:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.221 (8.221)	Loss 0.8213 (0.8213)	Acc@1 82.690 (82.690)	Acc@5 96.973 (96.973)	Mem 16099MB
[2025-01-18 04:04:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.102)	Loss 1.1654 (0.9652)	Acc@1 74.048 (79.603)	Acc@5 92.920 (95.066)	Mem 16099MB
[2025-01-18 04:04:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:130] * Acc@1 79.501 Acc@5 95.074
[2025-01-18 04:04:37 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.5%
[2025-01-18 04:04:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:04:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:04:39 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.50%
[2025-01-18 04:04:41 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][0/312]	eta 0:12:31 lr 0.002411	time 2.4098 (2.4098)	model_time 0.4907 (0.4907)	loss 2.6837 (2.6837)	grad_norm 1.3263 (1.3263/0.0000)	mem 16099MB
[2025-01-18 04:04:46 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][10/312]	eta 0:03:14 lr 0.002411	time 0.4539 (0.6426)	model_time 0.4521 (0.4677)	loss 3.8172 (3.2263)	grad_norm 0.8729 (1.1823/0.2725)	mem 16099MB
[2025-01-18 04:04:51 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][20/312]	eta 0:02:43 lr 0.002410	time 0.4415 (0.5594)	model_time 0.4411 (0.4676)	loss 3.3378 (3.0901)	grad_norm 1.2461 (1.4012/0.4561)	mem 16099MB
[2025-01-18 04:04:55 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][30/312]	eta 0:02:29 lr 0.002409	time 0.4515 (0.5285)	model_time 0.4514 (0.4662)	loss 4.1619 (3.1975)	grad_norm 1.1921 (1.5149/0.4875)	mem 16099MB
[2025-01-18 04:05:00 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][40/312]	eta 0:02:20 lr 0.002409	time 0.4452 (0.5147)	model_time 0.4447 (0.4675)	loss 3.7054 (3.1544)	grad_norm 1.8048 (1.5775/0.4688)	mem 16099MB
[2025-01-18 04:05:05 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][50/312]	eta 0:02:11 lr 0.002408	time 0.4542 (0.5031)	model_time 0.4537 (0.4651)	loss 3.3316 (3.1924)	grad_norm 1.3374 (1.5975/0.4691)	mem 16099MB
[2025-01-18 04:05:09 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][60/312]	eta 0:02:05 lr 0.002407	time 0.5407 (0.4972)	model_time 0.5402 (0.4654)	loss 3.5508 (3.1879)	grad_norm 1.1571 (1.6479/0.5088)	mem 16099MB
[2025-01-18 04:05:14 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][70/312]	eta 0:01:58 lr 0.002407	time 0.4541 (0.4915)	model_time 0.4536 (0.4640)	loss 2.9009 (3.1752)	grad_norm 2.0919 (1.6880/0.5546)	mem 16099MB
[2025-01-18 04:05:18 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][80/312]	eta 0:01:53 lr 0.002406	time 0.4532 (0.4882)	model_time 0.4528 (0.4641)	loss 3.4684 (3.1662)	grad_norm 1.0648 (1.6936/0.5366)	mem 16099MB
[2025-01-18 04:05:23 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][90/312]	eta 0:01:47 lr 0.002405	time 0.4626 (0.4860)	model_time 0.4622 (0.4645)	loss 4.2344 (3.1807)	grad_norm 1.0517 (1.6941/0.5597)	mem 16099MB
[2025-01-18 04:05:28 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][100/312]	eta 0:01:42 lr 0.002405	time 0.4505 (0.4839)	model_time 0.4501 (0.4645)	loss 3.7586 (3.1995)	grad_norm 0.8656 (1.6861/0.5821)	mem 16099MB
[2025-01-18 04:05:32 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][110/312]	eta 0:01:37 lr 0.002404	time 0.4454 (0.4826)	model_time 0.4453 (0.4648)	loss 3.8868 (3.2282)	grad_norm 1.1243 (1.6714/0.5728)	mem 16099MB
[2025-01-18 04:05:37 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][120/312]	eta 0:01:32 lr 0.002404	time 0.4492 (0.4808)	model_time 0.4486 (0.4645)	loss 3.7057 (3.2404)	grad_norm 2.4421 (1.6835/0.6012)	mem 16099MB
[2025-01-18 04:05:42 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][130/312]	eta 0:01:27 lr 0.002403	time 0.4509 (0.4805)	model_time 0.4507 (0.4654)	loss 3.4695 (3.2411)	grad_norm 1.2690 (1.6809/0.5906)	mem 16099MB
[2025-01-18 04:05:47 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][140/312]	eta 0:01:22 lr 0.002402	time 0.5423 (0.4804)	model_time 0.5419 (0.4664)	loss 3.3250 (3.2476)	grad_norm 1.1074 (1.6964/0.6160)	mem 16099MB
[2025-01-18 04:05:51 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][150/312]	eta 0:01:17 lr 0.002402	time 0.4545 (0.4793)	model_time 0.4541 (0.4662)	loss 3.4377 (3.2554)	grad_norm 3.0763 (1.7111/0.6383)	mem 16099MB
[2025-01-18 04:05:56 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][160/312]	eta 0:01:12 lr 0.002401	time 0.5370 (0.4801)	model_time 0.5365 (0.4678)	loss 3.3489 (3.2714)	grad_norm 1.0406 (1.7427/0.7037)	mem 16099MB
[2025-01-18 04:06:01 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][170/312]	eta 0:01:08 lr 0.002400	time 0.4656 (0.4804)	model_time 0.4654 (0.4688)	loss 3.6657 (3.2715)	grad_norm 1.1397 (1.7348/0.7029)	mem 16099MB
[2025-01-18 04:06:06 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][180/312]	eta 0:01:03 lr 0.002400	time 0.4494 (0.4790)	model_time 0.4492 (0.4680)	loss 2.7512 (3.2770)	grad_norm 1.6650 (1.7290/0.6847)	mem 16099MB
[2025-01-18 04:06:10 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][190/312]	eta 0:00:58 lr 0.002399	time 0.4440 (0.4778)	model_time 0.4438 (0.4674)	loss 3.1604 (3.2772)	grad_norm 1.5587 (1.7013/0.6825)	mem 16099MB
[2025-01-18 04:06:15 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][200/312]	eta 0:00:53 lr 0.002398	time 0.4534 (0.4769)	model_time 0.4530 (0.4670)	loss 3.1579 (3.2843)	grad_norm 0.9740 (1.6702/0.6820)	mem 16099MB
[2025-01-18 04:06:19 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][210/312]	eta 0:00:48 lr 0.002398	time 0.4621 (0.4765)	model_time 0.4617 (0.4670)	loss 2.3738 (3.2871)	grad_norm 1.2288 (1.6556/0.6742)	mem 16099MB
[2025-01-18 04:06:24 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][220/312]	eta 0:00:43 lr 0.002397	time 0.4561 (0.4753)	model_time 0.4557 (0.4662)	loss 3.6270 (3.3007)	grad_norm 1.7531 (1.6492/0.6624)	mem 16099MB
[2025-01-18 04:06:29 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][230/312]	eta 0:00:38 lr 0.002396	time 0.4575 (0.4754)	model_time 0.4573 (0.4666)	loss 2.8910 (3.3103)	grad_norm 2.5343 (1.6827/0.6765)	mem 16099MB
[2025-01-18 04:06:33 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][240/312]	eta 0:00:34 lr 0.002396	time 0.4894 (0.4746)	model_time 0.4892 (0.4662)	loss 3.5392 (3.3129)	grad_norm 0.8982 (1.6733/0.6696)	mem 16099MB
[2025-01-18 04:06:38 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][250/312]	eta 0:00:29 lr 0.002395	time 0.4634 (0.4738)	model_time 0.4630 (0.4657)	loss 2.0665 (3.3160)	grad_norm 1.3927 (1.6692/0.6615)	mem 16099MB
[2025-01-18 04:06:43 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][260/312]	eta 0:00:24 lr 0.002394	time 0.4473 (0.4747)	model_time 0.4469 (0.4669)	loss 3.5465 (3.3240)	grad_norm 1.4096 (1.6836/0.6677)	mem 16099MB
[2025-01-18 04:06:47 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][270/312]	eta 0:00:19 lr 0.002394	time 0.4701 (0.4743)	model_time 0.4696 (0.4668)	loss 2.1541 (3.3366)	grad_norm 1.2242 (1.6924/0.6679)	mem 16099MB
[2025-01-18 04:06:52 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][280/312]	eta 0:00:15 lr 0.002393	time 0.4533 (0.4739)	model_time 0.4531 (0.4666)	loss 3.7755 (3.3424)	grad_norm 1.5951 (1.6871/0.6602)	mem 16099MB
[2025-01-18 04:06:57 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][290/312]	eta 0:00:10 lr 0.002392	time 0.4599 (0.4737)	model_time 0.4598 (0.4666)	loss 3.5713 (3.3386)	grad_norm 1.3236 (1.6953/0.6744)	mem 16099MB
[2025-01-18 04:07:01 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][300/312]	eta 0:00:05 lr 0.002392	time 0.4406 (0.4729)	model_time 0.4405 (0.4661)	loss 2.2313 (3.3346)	grad_norm 3.0639 (1.7372/0.7322)	mem 16099MB
[2025-01-18 04:07:06 internimage_t_1k_224] (main.py 510): INFO Train: [131/300][310/312]	eta 0:00:00 lr 0.002391	time 0.5656 (0.4728)	model_time 0.5655 (0.4662)	loss 3.3328 (3.3348)	grad_norm 1.1137 (1.7631/0.7315)	mem 16099MB
[2025-01-18 04:07:06 internimage_t_1k_224] (main.py 519): INFO EPOCH 131 training takes 0:02:27
[2025-01-18 04:07:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_131.pth saving......
[2025-01-18 04:07:07 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_131.pth saved !!!
[2025-01-18 04:07:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.388 (7.388)	Loss 0.8514 (0.8514)	Acc@1 81.885 (81.885)	Acc@5 96.411 (96.411)	Mem 16099MB
[2025-01-18 04:07:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.994)	Loss 1.2220 (1.0182)	Acc@1 72.095 (78.343)	Acc@5 92.480 (94.533)	Mem 16099MB
[2025-01-18 04:07:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:131] * Acc@1 78.247 Acc@5 94.542
[2025-01-18 04:07:19 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.2%
[2025-01-18 04:07:19 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:07:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.122 (8.122)	Loss 0.8203 (0.8203)	Acc@1 82.788 (82.788)	Acc@5 96.948 (96.948)	Mem 16099MB
[2025-01-18 04:07:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.091)	Loss 1.1622 (0.9635)	Acc@1 74.121 (79.676)	Acc@5 92.920 (95.106)	Mem 16099MB
[2025-01-18 04:07:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:131] * Acc@1 79.575 Acc@5 95.114
[2025-01-18 04:07:31 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.6%
[2025-01-18 04:07:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:07:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:07:32 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.57%
[2025-01-18 04:07:35 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][0/312]	eta 0:13:22 lr 0.002391	time 2.5705 (2.5705)	model_time 0.4619 (0.4619)	loss 2.4452 (2.4452)	grad_norm 1.3838 (1.3838/0.0000)	mem 16099MB
[2025-01-18 04:07:39 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][10/312]	eta 0:03:23 lr 0.002390	time 0.5379 (0.6734)	model_time 0.5377 (0.4813)	loss 3.2570 (3.2764)	grad_norm 2.9245 (1.7075/0.6692)	mem 16099MB
[2025-01-18 04:07:44 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][20/312]	eta 0:02:49 lr 0.002390	time 0.4534 (0.5816)	model_time 0.4532 (0.4809)	loss 4.0900 (3.3246)	grad_norm 1.2865 (1.5798/0.5572)	mem 16099MB
[2025-01-18 04:07:49 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][30/312]	eta 0:02:33 lr 0.002389	time 0.4403 (0.5434)	model_time 0.4399 (0.4751)	loss 3.4589 (3.3235)	grad_norm 1.0955 (1.6011/0.5660)	mem 16099MB
[2025-01-18 04:07:53 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][40/312]	eta 0:02:21 lr 0.002388	time 0.4451 (0.5212)	model_time 0.4450 (0.4695)	loss 2.5656 (3.2707)	grad_norm 1.5640 (1.6036/0.5079)	mem 16099MB
[2025-01-18 04:07:58 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][50/312]	eta 0:02:14 lr 0.002388	time 0.5001 (0.5141)	model_time 0.4999 (0.4724)	loss 3.4073 (3.2406)	grad_norm 1.0336 (1.5193/0.5034)	mem 16099MB
[2025-01-18 04:08:03 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][60/312]	eta 0:02:07 lr 0.002387	time 0.5429 (0.5058)	model_time 0.5427 (0.4709)	loss 3.4757 (3.2275)	grad_norm 2.0144 (1.4896/0.5028)	mem 16099MB
[2025-01-18 04:08:07 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][70/312]	eta 0:02:00 lr 0.002386	time 0.4415 (0.4985)	model_time 0.4414 (0.4684)	loss 2.7425 (3.2081)	grad_norm 1.6477 (1.5400/0.5634)	mem 16099MB
[2025-01-18 04:08:12 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][80/312]	eta 0:01:54 lr 0.002386	time 0.4699 (0.4942)	model_time 0.4694 (0.4678)	loss 2.2076 (3.2202)	grad_norm 2.6476 (1.6281/0.6329)	mem 16099MB
[2025-01-18 04:08:17 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][90/312]	eta 0:01:48 lr 0.002385	time 0.4588 (0.4909)	model_time 0.4586 (0.4674)	loss 3.1071 (3.2502)	grad_norm 1.3697 (1.6256/0.6496)	mem 16099MB
[2025-01-18 04:08:21 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][100/312]	eta 0:01:43 lr 0.002384	time 0.4626 (0.4891)	model_time 0.4625 (0.4679)	loss 3.5600 (3.2854)	grad_norm 1.2986 (1.6783/0.7059)	mem 16099MB
[2025-01-18 04:08:26 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][110/312]	eta 0:01:38 lr 0.002384	time 0.4552 (0.4876)	model_time 0.4551 (0.4682)	loss 3.9834 (3.3022)	grad_norm 1.0833 (1.6614/0.6851)	mem 16099MB
[2025-01-18 04:08:31 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][120/312]	eta 0:01:33 lr 0.002383	time 0.5334 (0.4860)	model_time 0.5329 (0.4681)	loss 2.7473 (3.3032)	grad_norm 2.2088 (1.6877/0.7167)	mem 16099MB
[2025-01-18 04:08:35 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][130/312]	eta 0:01:28 lr 0.002383	time 0.4706 (0.4841)	model_time 0.4701 (0.4676)	loss 3.3227 (3.2954)	grad_norm 1.7413 (1.6930/0.7079)	mem 16099MB
[2025-01-18 04:08:40 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][140/312]	eta 0:01:23 lr 0.002382	time 0.5683 (0.4831)	model_time 0.5678 (0.4677)	loss 3.4316 (3.2862)	grad_norm 3.4097 (1.6934/0.7070)	mem 16099MB
[2025-01-18 04:08:45 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][150/312]	eta 0:01:18 lr 0.002381	time 0.4458 (0.4821)	model_time 0.4454 (0.4677)	loss 3.4564 (3.2864)	grad_norm 1.0635 (1.7086/0.7162)	mem 16099MB
[2025-01-18 04:08:50 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][160/312]	eta 0:01:13 lr 0.002381	time 0.4547 (0.4812)	model_time 0.4542 (0.4676)	loss 3.2920 (3.2727)	grad_norm 1.4254 (1.7062/0.6992)	mem 16099MB
[2025-01-18 04:08:54 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][170/312]	eta 0:01:08 lr 0.002380	time 0.4505 (0.4797)	model_time 0.4500 (0.4670)	loss 2.2345 (3.2703)	grad_norm 1.2158 (1.6860/0.6901)	mem 16099MB
[2025-01-18 04:08:59 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][180/312]	eta 0:01:03 lr 0.002379	time 0.4647 (0.4788)	model_time 0.4643 (0.4667)	loss 2.1320 (3.2809)	grad_norm 0.8557 (1.6812/0.6922)	mem 16099MB
[2025-01-18 04:09:03 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][190/312]	eta 0:00:58 lr 0.002379	time 0.4395 (0.4774)	model_time 0.4390 (0.4660)	loss 3.2052 (3.2897)	grad_norm 0.9907 (1.6751/0.6835)	mem 16099MB
[2025-01-18 04:09:08 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][200/312]	eta 0:00:53 lr 0.002378	time 0.4568 (0.4762)	model_time 0.4563 (0.4653)	loss 2.9319 (3.2966)	grad_norm 1.6844 (1.6602/0.6732)	mem 16099MB
[2025-01-18 04:09:13 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][210/312]	eta 0:00:48 lr 0.002377	time 0.4491 (0.4762)	model_time 0.4487 (0.4658)	loss 3.1409 (3.2989)	grad_norm 4.2835 (1.7067/0.7389)	mem 16099MB
[2025-01-18 04:09:17 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][220/312]	eta 0:00:43 lr 0.002377	time 0.4496 (0.4752)	model_time 0.4494 (0.4652)	loss 2.6518 (3.3010)	grad_norm 1.9154 (1.7188/0.7417)	mem 16099MB
[2025-01-18 04:09:22 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][230/312]	eta 0:00:38 lr 0.002376	time 0.4558 (0.4750)	model_time 0.4552 (0.4654)	loss 3.4609 (3.3027)	grad_norm 1.1493 (1.7018/0.7332)	mem 16099MB
[2025-01-18 04:09:26 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][240/312]	eta 0:00:34 lr 0.002375	time 0.4443 (0.4746)	model_time 0.4438 (0.4654)	loss 2.5203 (3.2890)	grad_norm 1.5395 (1.6903/0.7252)	mem 16099MB
[2025-01-18 04:09:31 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][250/312]	eta 0:00:29 lr 0.002375	time 0.4747 (0.4744)	model_time 0.4743 (0.4655)	loss 2.3247 (3.2867)	grad_norm 1.3138 (1.6774/0.7167)	mem 16099MB
[2025-01-18 04:09:36 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][260/312]	eta 0:00:24 lr 0.002374	time 0.4497 (0.4735)	model_time 0.4492 (0.4650)	loss 3.9371 (3.2940)	grad_norm 1.1755 (1.6761/0.7238)	mem 16099MB
[2025-01-18 04:09:40 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][270/312]	eta 0:00:19 lr 0.002373	time 0.4609 (0.4735)	model_time 0.4607 (0.4653)	loss 3.2132 (3.2904)	grad_norm 2.2667 (1.7085/0.7702)	mem 16099MB
[2025-01-18 04:09:45 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][280/312]	eta 0:00:15 lr 0.002373	time 0.4545 (0.4735)	model_time 0.4543 (0.4656)	loss 2.0511 (3.2809)	grad_norm 2.2571 (1.7043/0.7622)	mem 16099MB
[2025-01-18 04:09:50 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][290/312]	eta 0:00:10 lr 0.002372	time 0.4405 (0.4736)	model_time 0.4403 (0.4659)	loss 3.5116 (3.2837)	grad_norm 0.8736 (1.6927/0.7673)	mem 16099MB
[2025-01-18 04:09:54 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][300/312]	eta 0:00:05 lr 0.002371	time 0.4417 (0.4729)	model_time 0.4416 (0.4654)	loss 4.1924 (3.2863)	grad_norm 0.9478 (1.6864/0.7637)	mem 16099MB
[2025-01-18 04:09:59 internimage_t_1k_224] (main.py 510): INFO Train: [132/300][310/312]	eta 0:00:00 lr 0.002371	time 0.4372 (0.4729)	model_time 0.4371 (0.4657)	loss 3.5556 (3.2842)	grad_norm 2.8698 (1.6808/0.7597)	mem 16099MB
[2025-01-18 04:10:00 internimage_t_1k_224] (main.py 519): INFO EPOCH 132 training takes 0:02:27
[2025-01-18 04:10:00 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_132.pth saving......
[2025-01-18 04:10:01 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_132.pth saved !!!
[2025-01-18 04:10:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.349 (7.349)	Loss 0.8366 (0.8366)	Acc@1 81.885 (81.885)	Acc@5 96.509 (96.509)	Mem 16099MB
[2025-01-18 04:10:12 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.991)	Loss 1.2404 (1.0171)	Acc@1 72.729 (78.405)	Acc@5 91.870 (94.367)	Mem 16099MB
[2025-01-18 04:10:12 internimage_t_1k_224] (main.py 575): INFO [Epoch:132] * Acc@1 78.325 Acc@5 94.438
[2025-01-18 04:10:12 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.3%
[2025-01-18 04:10:12 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:10:20 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.061 (8.061)	Loss 0.8193 (0.8193)	Acc@1 82.886 (82.886)	Acc@5 96.948 (96.948)	Mem 16099MB
[2025-01-18 04:10:24 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.089)	Loss 1.1591 (0.9618)	Acc@1 74.170 (79.752)	Acc@5 92.896 (95.122)	Mem 16099MB
[2025-01-18 04:10:24 internimage_t_1k_224] (main.py 575): INFO [Epoch:132] * Acc@1 79.653 Acc@5 95.132
[2025-01-18 04:10:24 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.7%
[2025-01-18 04:10:24 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:10:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:10:25 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.65%
[2025-01-18 04:10:28 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][0/312]	eta 0:14:08 lr 0.002371	time 2.7208 (2.7208)	model_time 0.4704 (0.4704)	loss 2.3643 (2.3643)	grad_norm 3.0766 (3.0766/0.0000)	mem 16099MB
[2025-01-18 04:10:33 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][10/312]	eta 0:03:26 lr 0.002370	time 0.5353 (0.6840)	model_time 0.5351 (0.4792)	loss 3.6546 (3.0975)	grad_norm 1.5454 (2.1574/0.9963)	mem 16099MB
[2025-01-18 04:10:38 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][20/312]	eta 0:02:50 lr 0.002369	time 0.4702 (0.5836)	model_time 0.4700 (0.4761)	loss 3.5297 (3.2141)	grad_norm 1.1312 (1.8235/0.8399)	mem 16099MB
[2025-01-18 04:10:42 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][30/312]	eta 0:02:33 lr 0.002369	time 0.4854 (0.5454)	model_time 0.4852 (0.4725)	loss 3.3810 (3.1249)	grad_norm 1.3516 (1.6641/0.7394)	mem 16099MB
[2025-01-18 04:10:47 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][40/312]	eta 0:02:23 lr 0.002368	time 0.4536 (0.5263)	model_time 0.4534 (0.4711)	loss 3.8611 (3.1539)	grad_norm 3.0632 (1.6905/0.7091)	mem 16099MB
[2025-01-18 04:10:52 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][50/312]	eta 0:02:15 lr 0.002367	time 0.4511 (0.5186)	model_time 0.4506 (0.4741)	loss 2.3594 (3.1604)	grad_norm 1.3182 (1.7982/0.9164)	mem 16099MB
[2025-01-18 04:10:56 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][60/312]	eta 0:02:08 lr 0.002367	time 0.4408 (0.5092)	model_time 0.4405 (0.4720)	loss 4.1317 (3.1859)	grad_norm 0.9785 (1.7294/0.8884)	mem 16099MB
[2025-01-18 04:11:01 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][70/312]	eta 0:02:01 lr 0.002366	time 0.4464 (0.5020)	model_time 0.4462 (0.4699)	loss 3.6062 (3.2556)	grad_norm 3.1648 (1.8890/1.0396)	mem 16099MB
[2025-01-18 04:11:05 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][80/312]	eta 0:01:55 lr 0.002365	time 0.4330 (0.4958)	model_time 0.4328 (0.4677)	loss 3.3342 (3.2776)	grad_norm 1.6224 (1.8570/1.0053)	mem 16099MB
[2025-01-18 04:11:10 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][90/312]	eta 0:01:49 lr 0.002365	time 0.4681 (0.4924)	model_time 0.4679 (0.4673)	loss 3.7063 (3.2981)	grad_norm 3.5698 (1.8679/0.9881)	mem 16099MB
[2025-01-18 04:11:15 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][100/312]	eta 0:01:44 lr 0.002364	time 0.4667 (0.4920)	model_time 0.4665 (0.4694)	loss 3.3431 (3.3022)	grad_norm 1.2945 (1.8734/0.9609)	mem 16099MB
[2025-01-18 04:11:20 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][110/312]	eta 0:01:39 lr 0.002363	time 0.7463 (0.4912)	model_time 0.7461 (0.4706)	loss 2.2985 (3.2756)	grad_norm 1.3043 (1.8355/0.9274)	mem 16099MB
[2025-01-18 04:11:24 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][120/312]	eta 0:01:33 lr 0.002363	time 0.4596 (0.4880)	model_time 0.4594 (0.4691)	loss 3.7322 (3.2800)	grad_norm 1.0035 (1.7922/0.9045)	mem 16099MB
[2025-01-18 04:11:29 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][130/312]	eta 0:01:28 lr 0.002362	time 0.4606 (0.4860)	model_time 0.4601 (0.4685)	loss 3.1213 (3.2832)	grad_norm 0.8031 (1.7598/0.8854)	mem 16099MB
[2025-01-18 04:11:34 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][140/312]	eta 0:01:23 lr 0.002361	time 0.4483 (0.4855)	model_time 0.4481 (0.4692)	loss 3.6450 (3.2694)	grad_norm 0.9957 (1.7349/0.8694)	mem 16099MB
[2025-01-18 04:11:38 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][150/312]	eta 0:01:18 lr 0.002361	time 0.4408 (0.4840)	model_time 0.4405 (0.4688)	loss 2.6146 (3.2471)	grad_norm 4.0843 (1.7669/0.8820)	mem 16099MB
[2025-01-18 04:11:43 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][160/312]	eta 0:01:13 lr 0.002360	time 0.4773 (0.4821)	model_time 0.4771 (0.4678)	loss 4.1290 (3.2557)	grad_norm 2.5434 (1.7781/0.8698)	mem 16099MB
[2025-01-18 04:11:48 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][170/312]	eta 0:01:08 lr 0.002360	time 0.4401 (0.4815)	model_time 0.4400 (0.4680)	loss 3.5662 (3.2541)	grad_norm 1.0304 (1.7642/0.8536)	mem 16099MB
[2025-01-18 04:11:53 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][180/312]	eta 0:01:03 lr 0.002359	time 0.4519 (0.4824)	model_time 0.4518 (0.4696)	loss 2.9779 (3.2506)	grad_norm 1.2439 (1.7786/0.8692)	mem 16099MB
[2025-01-18 04:11:57 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][190/312]	eta 0:00:58 lr 0.002358	time 0.4523 (0.4808)	model_time 0.4518 (0.4687)	loss 3.1887 (3.2448)	grad_norm 1.9157 (1.7862/0.8775)	mem 16099MB
[2025-01-18 04:12:02 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][200/312]	eta 0:00:53 lr 0.002358	time 0.4493 (0.4800)	model_time 0.4490 (0.4684)	loss 3.4296 (3.2500)	grad_norm 1.1469 (1.7569/0.8692)	mem 16099MB
[2025-01-18 04:12:06 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][210/312]	eta 0:00:48 lr 0.002357	time 0.4481 (0.4794)	model_time 0.4479 (0.4684)	loss 4.1068 (3.2408)	grad_norm 1.3421 (1.7365/0.8553)	mem 16099MB
[2025-01-18 04:12:11 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][220/312]	eta 0:00:44 lr 0.002356	time 0.4414 (0.4791)	model_time 0.4412 (0.4686)	loss 2.7985 (3.2398)	grad_norm 1.9648 (1.7899/0.9540)	mem 16099MB
[2025-01-18 04:12:16 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][230/312]	eta 0:00:39 lr 0.002356	time 0.4583 (0.4781)	model_time 0.4581 (0.4681)	loss 3.4405 (3.2392)	grad_norm 1.3175 (1.7795/0.9401)	mem 16099MB
[2025-01-18 04:12:20 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][240/312]	eta 0:00:34 lr 0.002355	time 0.4469 (0.4774)	model_time 0.4467 (0.4677)	loss 3.5788 (3.2401)	grad_norm 1.0144 (1.7713/0.9294)	mem 16099MB
[2025-01-18 04:12:25 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][250/312]	eta 0:00:29 lr 0.002354	time 0.4466 (0.4768)	model_time 0.4461 (0.4675)	loss 3.2308 (3.2410)	grad_norm 0.9697 (1.7745/0.9285)	mem 16099MB
[2025-01-18 04:12:30 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][260/312]	eta 0:00:24 lr 0.002354	time 0.4570 (0.4774)	model_time 0.4563 (0.4684)	loss 3.2812 (3.2301)	grad_norm 1.3147 (1.7613/0.9153)	mem 16099MB
[2025-01-18 04:12:35 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][270/312]	eta 0:00:20 lr 0.002353	time 0.4473 (0.4768)	model_time 0.4471 (0.4682)	loss 3.5582 (3.2315)	grad_norm 2.0035 (1.7721/0.9110)	mem 16099MB
[2025-01-18 04:12:39 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][280/312]	eta 0:00:15 lr 0.002352	time 0.4790 (0.4765)	model_time 0.4788 (0.4682)	loss 3.8138 (3.2278)	grad_norm 2.1975 (1.7716/0.8984)	mem 16099MB
[2025-01-18 04:12:44 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][290/312]	eta 0:00:10 lr 0.002352	time 0.4555 (0.4762)	model_time 0.4550 (0.4681)	loss 3.7563 (3.2343)	grad_norm 1.2063 (1.7502/0.8909)	mem 16099MB
[2025-01-18 04:12:48 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][300/312]	eta 0:00:05 lr 0.002351	time 0.4391 (0.4753)	model_time 0.4390 (0.4674)	loss 3.9808 (3.2382)	grad_norm 1.0067 (1.7438/0.8863)	mem 16099MB
[2025-01-18 04:12:53 internimage_t_1k_224] (main.py 510): INFO Train: [133/300][310/312]	eta 0:00:00 lr 0.002350	time 0.4449 (0.4752)	model_time 0.4448 (0.4676)	loss 3.2725 (3.2347)	grad_norm 1.2070 (1.7375/0.8750)	mem 16099MB
[2025-01-18 04:12:54 internimage_t_1k_224] (main.py 519): INFO EPOCH 133 training takes 0:02:28
[2025-01-18 04:12:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_133.pth saving......
[2025-01-18 04:12:55 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_133.pth saved !!!
[2025-01-18 04:13:02 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.204 (7.204)	Loss 0.8918 (0.8918)	Acc@1 81.519 (81.519)	Acc@5 96.094 (96.094)	Mem 16099MB
[2025-01-18 04:13:05 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.967)	Loss 1.1678 (1.0205)	Acc@1 74.292 (78.489)	Acc@5 93.384 (94.751)	Mem 16099MB
[2025-01-18 04:13:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:133] * Acc@1 78.491 Acc@5 94.764
[2025-01-18 04:13:06 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.5%
[2025-01-18 04:13:06 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:13:14 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.130 (8.130)	Loss 0.8186 (0.8186)	Acc@1 82.983 (82.983)	Acc@5 96.924 (96.924)	Mem 16099MB
[2025-01-18 04:13:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.105)	Loss 1.1559 (0.9601)	Acc@1 74.268 (79.843)	Acc@5 93.018 (95.159)	Mem 16099MB
[2025-01-18 04:13:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:133] * Acc@1 79.742 Acc@5 95.168
[2025-01-18 04:13:18 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.7%
[2025-01-18 04:13:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:13:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:13:19 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.74%
[2025-01-18 04:13:21 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][0/312]	eta 0:11:34 lr 0.002350	time 2.2253 (2.2253)	model_time 0.4625 (0.4625)	loss 4.4258 (4.4258)	grad_norm 2.1346 (2.1346/0.0000)	mem 16099MB
[2025-01-18 04:13:26 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][10/312]	eta 0:03:10 lr 0.002350	time 0.4475 (0.6321)	model_time 0.4473 (0.4714)	loss 3.4466 (3.2747)	grad_norm 1.6762 (1.9836/0.4403)	mem 16099MB
[2025-01-18 04:13:31 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][20/312]	eta 0:02:41 lr 0.002349	time 0.4537 (0.5534)	model_time 0.4535 (0.4691)	loss 3.9921 (3.1622)	grad_norm 1.1110 (1.6884/0.5083)	mem 16099MB
[2025-01-18 04:13:35 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][30/312]	eta 0:02:27 lr 0.002348	time 0.4471 (0.5238)	model_time 0.4466 (0.4665)	loss 2.1164 (3.0833)	grad_norm 1.3093 (1.6358/0.4650)	mem 16099MB
[2025-01-18 04:13:40 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][40/312]	eta 0:02:18 lr 0.002348	time 0.4564 (0.5084)	model_time 0.4562 (0.4651)	loss 3.2231 (3.1600)	grad_norm 2.5457 (1.5784/0.5063)	mem 16099MB
[2025-01-18 04:13:45 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][50/312]	eta 0:02:11 lr 0.002347	time 0.5381 (0.5025)	model_time 0.5375 (0.4676)	loss 3.4327 (3.1897)	grad_norm 1.3442 (1.5422/0.4795)	mem 16099MB
[2025-01-18 04:13:49 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][60/312]	eta 0:02:05 lr 0.002346	time 0.4703 (0.4971)	model_time 0.4698 (0.4678)	loss 2.7722 (3.1960)	grad_norm 1.3375 (1.6006/0.5224)	mem 16099MB
[2025-01-18 04:13:54 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][70/312]	eta 0:01:59 lr 0.002346	time 0.5138 (0.4933)	model_time 0.5133 (0.4681)	loss 3.3082 (3.2165)	grad_norm 2.9591 (1.6384/0.5362)	mem 16099MB
[2025-01-18 04:13:59 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][80/312]	eta 0:01:53 lr 0.002345	time 0.4773 (0.4906)	model_time 0.4771 (0.4684)	loss 3.0655 (3.2186)	grad_norm 1.2612 (1.7336/0.6937)	mem 16099MB
[2025-01-18 04:14:04 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][90/312]	eta 0:01:48 lr 0.002344	time 0.4385 (0.4886)	model_time 0.4383 (0.4689)	loss 3.4729 (3.2203)	grad_norm 0.9364 (1.7163/0.6827)	mem 16099MB
[2025-01-18 04:14:08 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][100/312]	eta 0:01:42 lr 0.002344	time 0.4505 (0.4853)	model_time 0.4500 (0.4674)	loss 3.4440 (3.2598)	grad_norm 1.9800 (1.7642/0.7116)	mem 16099MB
[2025-01-18 04:14:13 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][110/312]	eta 0:01:37 lr 0.002343	time 0.4497 (0.4840)	model_time 0.4487 (0.4677)	loss 3.1144 (3.2595)	grad_norm 1.1337 (1.7501/0.7017)	mem 16099MB
[2025-01-18 04:14:18 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][120/312]	eta 0:01:32 lr 0.002342	time 0.4562 (0.4827)	model_time 0.4560 (0.4678)	loss 2.0083 (3.2528)	grad_norm 0.9593 (1.7395/0.6837)	mem 16099MB
[2025-01-18 04:14:22 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][130/312]	eta 0:01:27 lr 0.002342	time 0.4373 (0.4834)	model_time 0.4371 (0.4696)	loss 3.6773 (3.2437)	grad_norm 1.5360 (1.7209/0.6820)	mem 16099MB
[2025-01-18 04:14:27 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][140/312]	eta 0:01:23 lr 0.002341	time 0.4524 (0.4827)	model_time 0.4522 (0.4698)	loss 3.5670 (3.2547)	grad_norm 3.3780 (1.6964/0.6882)	mem 16099MB
[2025-01-18 04:14:32 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][150/312]	eta 0:01:18 lr 0.002340	time 0.4513 (0.4821)	model_time 0.4509 (0.4700)	loss 3.1594 (3.2746)	grad_norm 4.7007 (1.7787/0.8110)	mem 16099MB
[2025-01-18 04:14:37 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][160/312]	eta 0:01:13 lr 0.002340	time 0.4531 (0.4817)	model_time 0.4529 (0.4703)	loss 3.6691 (3.2747)	grad_norm 2.6572 (1.8158/0.8742)	mem 16099MB
[2025-01-18 04:14:41 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][170/312]	eta 0:01:08 lr 0.002339	time 0.4385 (0.4799)	model_time 0.4381 (0.4692)	loss 4.2274 (3.2675)	grad_norm 2.7912 (1.8220/0.8706)	mem 16099MB
[2025-01-18 04:14:46 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][180/312]	eta 0:01:03 lr 0.002338	time 0.4636 (0.4800)	model_time 0.4634 (0.4699)	loss 3.5614 (3.2941)	grad_norm 1.3818 (1.8011/0.8580)	mem 16099MB
[2025-01-18 04:14:51 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][190/312]	eta 0:00:58 lr 0.002338	time 0.4382 (0.4785)	model_time 0.4379 (0.4689)	loss 3.5328 (3.2919)	grad_norm 0.9792 (1.7671/0.8499)	mem 16099MB
[2025-01-18 04:14:55 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][200/312]	eta 0:00:53 lr 0.002337	time 0.4588 (0.4786)	model_time 0.4583 (0.4695)	loss 3.2595 (3.2963)	grad_norm 1.7361 (1.7403/0.8402)	mem 16099MB
[2025-01-18 04:15:00 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][210/312]	eta 0:00:48 lr 0.002336	time 0.4457 (0.4778)	model_time 0.4452 (0.4690)	loss 3.6315 (3.2890)	grad_norm 1.1341 (1.7389/0.8421)	mem 16099MB
[2025-01-18 04:15:04 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][220/312]	eta 0:00:43 lr 0.002336	time 0.4467 (0.4766)	model_time 0.4462 (0.4682)	loss 2.0879 (3.2851)	grad_norm 2.3075 (1.7387/0.8319)	mem 16099MB
[2025-01-18 04:15:09 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][230/312]	eta 0:00:39 lr 0.002335	time 0.4505 (0.4761)	model_time 0.4500 (0.4680)	loss 4.1165 (3.2919)	grad_norm 2.1850 (1.7451/0.8258)	mem 16099MB
[2025-01-18 04:15:14 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][240/312]	eta 0:00:34 lr 0.002334	time 0.4565 (0.4754)	model_time 0.4560 (0.4677)	loss 3.2261 (3.2944)	grad_norm 1.2552 (1.7395/0.8131)	mem 16099MB
[2025-01-18 04:15:18 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][250/312]	eta 0:00:29 lr 0.002334	time 0.4486 (0.4746)	model_time 0.4484 (0.4671)	loss 3.3689 (3.2958)	grad_norm 0.8842 (1.7393/0.8024)	mem 16099MB
[2025-01-18 04:15:23 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][260/312]	eta 0:00:24 lr 0.002333	time 0.4503 (0.4746)	model_time 0.4498 (0.4674)	loss 3.0541 (3.2954)	grad_norm 3.6795 (1.7507/0.8062)	mem 16099MB
[2025-01-18 04:15:28 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][270/312]	eta 0:00:19 lr 0.002332	time 0.4785 (0.4738)	model_time 0.4780 (0.4669)	loss 3.0553 (3.2909)	grad_norm 2.5326 (1.7561/0.8030)	mem 16099MB
[2025-01-18 04:15:32 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][280/312]	eta 0:00:15 lr 0.002332	time 0.4465 (0.4735)	model_time 0.4460 (0.4668)	loss 3.4163 (3.2875)	grad_norm 2.6647 (1.7735/0.8163)	mem 16099MB
[2025-01-18 04:15:37 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][290/312]	eta 0:00:10 lr 0.002331	time 0.4472 (0.4734)	model_time 0.4467 (0.4670)	loss 3.3574 (3.2831)	grad_norm 2.7104 (1.7710/0.8145)	mem 16099MB
[2025-01-18 04:15:41 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][300/312]	eta 0:00:05 lr 0.002331	time 0.4390 (0.4729)	model_time 0.4389 (0.4666)	loss 2.8978 (3.2799)	grad_norm 1.4097 (1.7604/0.8136)	mem 16099MB
[2025-01-18 04:15:46 internimage_t_1k_224] (main.py 510): INFO Train: [134/300][310/312]	eta 0:00:00 lr 0.002330	time 0.4392 (0.4730)	model_time 0.4391 (0.4669)	loss 3.3755 (3.2872)	grad_norm 0.9533 (1.7371/0.8145)	mem 16099MB
[2025-01-18 04:15:47 internimage_t_1k_224] (main.py 519): INFO EPOCH 134 training takes 0:02:27
[2025-01-18 04:15:47 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_134.pth saving......
[2025-01-18 04:15:48 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_134.pth saved !!!
[2025-01-18 04:15:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.537 (7.537)	Loss 0.8647 (0.8647)	Acc@1 81.494 (81.494)	Acc@5 96.143 (96.143)	Mem 16099MB
[2025-01-18 04:15:59 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.016)	Loss 1.1907 (0.9961)	Acc@1 73.291 (78.471)	Acc@5 92.651 (94.507)	Mem 16099MB
[2025-01-18 04:15:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:134] * Acc@1 78.401 Acc@5 94.578
[2025-01-18 04:15:59 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.4%
[2025-01-18 04:15:59 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:16:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.390 (8.390)	Loss 0.8179 (0.8179)	Acc@1 82.983 (82.983)	Acc@5 96.973 (96.973)	Mem 16099MB
[2025-01-18 04:16:11 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.107)	Loss 1.1525 (0.9583)	Acc@1 74.316 (79.883)	Acc@5 93.091 (95.206)	Mem 16099MB
[2025-01-18 04:16:12 internimage_t_1k_224] (main.py 575): INFO [Epoch:134] * Acc@1 79.782 Acc@5 95.206
[2025-01-18 04:16:12 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.8%
[2025-01-18 04:16:12 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:16:13 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:16:13 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.78%
[2025-01-18 04:16:15 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][0/312]	eta 0:10:50 lr 0.002330	time 2.0835 (2.0835)	model_time 0.4893 (0.4893)	loss 4.1055 (4.1055)	grad_norm 1.1640 (1.1640/0.0000)	mem 16099MB
[2025-01-18 04:16:20 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][10/312]	eta 0:03:10 lr 0.002329	time 0.4512 (0.6309)	model_time 0.4510 (0.4857)	loss 2.9256 (3.0979)	grad_norm 2.8164 (1.6527/0.4279)	mem 16099MB
[2025-01-18 04:16:24 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][20/312]	eta 0:02:40 lr 0.002328	time 0.4736 (0.5482)	model_time 0.4734 (0.4719)	loss 2.7405 (3.2535)	grad_norm 1.3658 (1.5970/0.5091)	mem 16099MB
[2025-01-18 04:16:29 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][30/312]	eta 0:02:26 lr 0.002328	time 0.4593 (0.5206)	model_time 0.4591 (0.4689)	loss 3.1259 (3.2307)	grad_norm 1.4254 (1.4713/0.4949)	mem 16099MB
[2025-01-18 04:16:34 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][40/312]	eta 0:02:18 lr 0.002327	time 0.4562 (0.5096)	model_time 0.4557 (0.4704)	loss 2.5662 (3.1926)	grad_norm 1.1875 (1.5527/0.6692)	mem 16099MB
[2025-01-18 04:16:38 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][50/312]	eta 0:02:11 lr 0.002326	time 0.4376 (0.5015)	model_time 0.4374 (0.4699)	loss 3.9325 (3.1988)	grad_norm 1.0999 (1.5960/0.6367)	mem 16099MB
[2025-01-18 04:16:43 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][60/312]	eta 0:02:05 lr 0.002326	time 0.5319 (0.4971)	model_time 0.5314 (0.4706)	loss 3.7121 (3.2567)	grad_norm 1.0359 (1.6171/0.6453)	mem 16099MB
[2025-01-18 04:16:48 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][70/312]	eta 0:01:59 lr 0.002325	time 0.4731 (0.4929)	model_time 0.4729 (0.4701)	loss 3.4053 (3.2562)	grad_norm 1.6866 (1.5943/0.6179)	mem 16099MB
[2025-01-18 04:16:53 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][80/312]	eta 0:01:54 lr 0.002324	time 0.4497 (0.4938)	model_time 0.4496 (0.4738)	loss 2.6221 (3.2991)	grad_norm 2.8326 (1.5932/0.6425)	mem 16099MB
[2025-01-18 04:16:57 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][90/312]	eta 0:01:48 lr 0.002324	time 0.4696 (0.4898)	model_time 0.4694 (0.4719)	loss 2.0588 (3.2864)	grad_norm 2.0343 (1.6793/0.7257)	mem 16099MB
[2025-01-18 04:17:02 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][100/312]	eta 0:01:43 lr 0.002323	time 0.4788 (0.4870)	model_time 0.4783 (0.4709)	loss 2.9619 (3.2946)	grad_norm 1.1895 (1.6641/0.7051)	mem 16099MB
[2025-01-18 04:17:07 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][110/312]	eta 0:01:38 lr 0.002323	time 0.5387 (0.4858)	model_time 0.5385 (0.4711)	loss 3.3080 (3.3033)	grad_norm 2.0894 (1.6652/0.7042)	mem 16099MB
[2025-01-18 04:17:11 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][120/312]	eta 0:01:32 lr 0.002322	time 0.4507 (0.4839)	model_time 0.4506 (0.4704)	loss 2.8952 (3.3122)	grad_norm 0.9172 (1.6529/0.6875)	mem 16099MB
[2025-01-18 04:17:16 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][130/312]	eta 0:01:27 lr 0.002321	time 0.5936 (0.4824)	model_time 0.5931 (0.4699)	loss 3.9374 (3.2911)	grad_norm 2.7110 (1.6773/0.6921)	mem 16099MB
[2025-01-18 04:17:21 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][140/312]	eta 0:01:22 lr 0.002321	time 0.4439 (0.4813)	model_time 0.4436 (0.4697)	loss 3.2437 (3.3205)	grad_norm 1.2560 (1.6880/0.6943)	mem 16099MB
[2025-01-18 04:17:25 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][150/312]	eta 0:01:17 lr 0.002320	time 0.4578 (0.4809)	model_time 0.4573 (0.4700)	loss 2.3503 (3.2895)	grad_norm 1.4430 (1.6916/0.6965)	mem 16099MB
[2025-01-18 04:17:30 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][160/312]	eta 0:01:12 lr 0.002319	time 0.4562 (0.4791)	model_time 0.4557 (0.4688)	loss 3.6043 (3.2897)	grad_norm 0.8424 (1.6967/0.6961)	mem 16099MB
[2025-01-18 04:17:35 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][170/312]	eta 0:01:08 lr 0.002319	time 0.4638 (0.4793)	model_time 0.4635 (0.4696)	loss 2.5922 (3.2765)	grad_norm 2.0119 (1.7047/0.6992)	mem 16099MB
[2025-01-18 04:17:39 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][180/312]	eta 0:01:03 lr 0.002318	time 0.4545 (0.4782)	model_time 0.4543 (0.4690)	loss 3.7141 (3.2773)	grad_norm 3.1053 (1.7426/0.7249)	mem 16099MB
[2025-01-18 04:17:44 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][190/312]	eta 0:00:58 lr 0.002317	time 0.4961 (0.4772)	model_time 0.4956 (0.4685)	loss 2.7154 (3.2819)	grad_norm 2.4081 (1.7346/0.7131)	mem 16099MB
[2025-01-18 04:17:49 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][200/312]	eta 0:00:53 lr 0.002317	time 0.4515 (0.4760)	model_time 0.4513 (0.4677)	loss 3.3569 (3.2876)	grad_norm 1.4496 (1.7355/0.7095)	mem 16099MB
[2025-01-18 04:17:54 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][210/312]	eta 0:00:48 lr 0.002316	time 0.4638 (0.4771)	model_time 0.4636 (0.4691)	loss 3.5240 (3.2990)	grad_norm 1.1031 (1.7479/0.7087)	mem 16099MB
[2025-01-18 04:17:58 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][220/312]	eta 0:00:43 lr 0.002315	time 0.4532 (0.4763)	model_time 0.4527 (0.4687)	loss 3.7210 (3.2986)	grad_norm 1.1910 (1.7402/0.7084)	mem 16099MB
[2025-01-18 04:18:03 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][230/312]	eta 0:00:39 lr 0.002315	time 0.4495 (0.4759)	model_time 0.4490 (0.4686)	loss 3.6538 (3.2968)	grad_norm 1.4587 (1.7284/0.6990)	mem 16099MB
[2025-01-18 04:18:08 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][240/312]	eta 0:00:34 lr 0.002314	time 0.5497 (0.4762)	model_time 0.5495 (0.4692)	loss 2.6385 (3.2936)	grad_norm 4.8457 (1.7615/0.7396)	mem 16099MB
[2025-01-18 04:18:12 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][250/312]	eta 0:00:29 lr 0.002313	time 0.4499 (0.4757)	model_time 0.4494 (0.4689)	loss 3.5113 (3.2910)	grad_norm 2.6145 (1.7659/0.7367)	mem 16099MB
[2025-01-18 04:18:17 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][260/312]	eta 0:00:24 lr 0.002313	time 0.4467 (0.4749)	model_time 0.4465 (0.4684)	loss 3.7011 (3.2858)	grad_norm 1.5219 (1.7534/0.7276)	mem 16099MB
[2025-01-18 04:18:22 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][270/312]	eta 0:00:19 lr 0.002312	time 0.4471 (0.4748)	model_time 0.4470 (0.4685)	loss 3.0067 (3.2841)	grad_norm 0.9426 (1.7387/0.7197)	mem 16099MB
[2025-01-18 04:18:26 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][280/312]	eta 0:00:15 lr 0.002311	time 0.4427 (0.4755)	model_time 0.4422 (0.4694)	loss 3.6535 (3.2855)	grad_norm 1.7360 (1.7688/0.7480)	mem 16099MB
[2025-01-18 04:18:31 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][290/312]	eta 0:00:10 lr 0.002311	time 0.4536 (0.4747)	model_time 0.4376 (0.4688)	loss 4.1084 (3.2917)	grad_norm 1.9228 (1.7775/0.7497)	mem 16099MB
[2025-01-18 04:18:36 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][300/312]	eta 0:00:05 lr 0.002310	time 0.4378 (0.4745)	model_time 0.4377 (0.4687)	loss 3.4896 (3.2876)	grad_norm 0.8417 (1.7802/0.7508)	mem 16099MB
[2025-01-18 04:18:40 internimage_t_1k_224] (main.py 510): INFO Train: [135/300][310/312]	eta 0:00:00 lr 0.002309	time 0.5166 (0.4737)	model_time 0.5165 (0.4682)	loss 2.6585 (3.2884)	grad_norm 3.2200 (1.7975/0.7666)	mem 16099MB
[2025-01-18 04:18:41 internimage_t_1k_224] (main.py 519): INFO EPOCH 135 training takes 0:02:27
[2025-01-18 04:18:41 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_135.pth saving......
[2025-01-18 04:18:42 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_135.pth saved !!!
[2025-01-18 04:18:49 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.149 (7.149)	Loss 0.8333 (0.8333)	Acc@1 81.372 (81.372)	Acc@5 96.094 (96.094)	Mem 16099MB
[2025-01-18 04:18:53 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.988)	Loss 1.1596 (0.9782)	Acc@1 74.048 (78.589)	Acc@5 92.700 (94.502)	Mem 16099MB
[2025-01-18 04:18:53 internimage_t_1k_224] (main.py 575): INFO [Epoch:135] * Acc@1 78.477 Acc@5 94.548
[2025-01-18 04:18:53 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.5%
[2025-01-18 04:18:53 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:19:01 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.132 (8.132)	Loss 0.8172 (0.8172)	Acc@1 83.130 (83.130)	Acc@5 96.997 (96.997)	Mem 16099MB
[2025-01-18 04:19:05 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.082)	Loss 1.1494 (0.9569)	Acc@1 74.390 (79.989)	Acc@5 93.140 (95.233)	Mem 16099MB
[2025-01-18 04:19:05 internimage_t_1k_224] (main.py 575): INFO [Epoch:135] * Acc@1 79.888 Acc@5 95.234
[2025-01-18 04:19:05 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.9%
[2025-01-18 04:19:05 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:19:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:19:06 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.89%
[2025-01-18 04:19:08 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][0/312]	eta 0:12:38 lr 0.002309	time 2.4316 (2.4316)	model_time 0.4793 (0.4793)	loss 3.5388 (3.5388)	grad_norm 2.8107 (2.8107/0.0000)	mem 16099MB
[2025-01-18 04:19:13 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][10/312]	eta 0:03:15 lr 0.002309	time 0.4569 (0.6487)	model_time 0.4565 (0.4709)	loss 2.3691 (3.1811)	grad_norm 1.3076 (1.5734/0.5352)	mem 16099MB
[2025-01-18 04:19:18 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][20/312]	eta 0:02:43 lr 0.002308	time 0.4623 (0.5601)	model_time 0.4619 (0.4668)	loss 2.5832 (3.3055)	grad_norm 1.7533 (1.6284/0.5441)	mem 16099MB
[2025-01-18 04:19:22 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][30/312]	eta 0:02:28 lr 0.002307	time 0.4486 (0.5274)	model_time 0.4482 (0.4640)	loss 3.8346 (3.2766)	grad_norm 1.5111 (1.5753/0.4978)	mem 16099MB
[2025-01-18 04:19:27 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][40/312]	eta 0:02:19 lr 0.002307	time 0.4606 (0.5140)	model_time 0.4604 (0.4661)	loss 3.3165 (3.2647)	grad_norm 3.1628 (1.5470/0.5583)	mem 16099MB
[2025-01-18 04:19:32 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][50/312]	eta 0:02:12 lr 0.002306	time 0.4401 (0.5056)	model_time 0.4396 (0.4670)	loss 3.3489 (3.2885)	grad_norm 0.7511 (1.4630/0.5468)	mem 16099MB
[2025-01-18 04:19:36 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][60/312]	eta 0:02:05 lr 0.002305	time 0.5462 (0.4988)	model_time 0.5458 (0.4664)	loss 3.9988 (3.3038)	grad_norm 1.5897 (1.5287/0.5729)	mem 16099MB
[2025-01-18 04:19:41 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][70/312]	eta 0:01:59 lr 0.002305	time 0.4553 (0.4936)	model_time 0.4551 (0.4657)	loss 3.8016 (3.3485)	grad_norm 2.0402 (1.5839/0.6711)	mem 16099MB
[2025-01-18 04:19:46 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][80/312]	eta 0:01:53 lr 0.002304	time 0.4603 (0.4886)	model_time 0.4601 (0.4641)	loss 3.1271 (3.3467)	grad_norm 1.0753 (1.6478/0.7397)	mem 16099MB
[2025-01-18 04:19:50 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][90/312]	eta 0:01:47 lr 0.002303	time 0.4523 (0.4855)	model_time 0.4521 (0.4637)	loss 3.1510 (3.3490)	grad_norm 2.1086 (1.6497/0.7173)	mem 16099MB
[2025-01-18 04:19:55 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][100/312]	eta 0:01:42 lr 0.002303	time 0.4548 (0.4831)	model_time 0.4546 (0.4635)	loss 3.1366 (3.3271)	grad_norm 1.1154 (1.6253/0.6936)	mem 16099MB
[2025-01-18 04:20:00 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][110/312]	eta 0:01:37 lr 0.002302	time 0.5312 (0.4823)	model_time 0.5310 (0.4644)	loss 4.4415 (3.3315)	grad_norm 1.1600 (1.5826/0.6809)	mem 16099MB
[2025-01-18 04:20:04 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][120/312]	eta 0:01:32 lr 0.002301	time 0.5358 (0.4812)	model_time 0.5354 (0.4647)	loss 2.5068 (3.3184)	grad_norm 1.9863 (1.6275/0.6902)	mem 16099MB
[2025-01-18 04:20:09 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][130/312]	eta 0:01:27 lr 0.002301	time 0.4602 (0.4798)	model_time 0.4600 (0.4646)	loss 2.2670 (3.2691)	grad_norm 0.8820 (1.6489/0.7188)	mem 16099MB
[2025-01-18 04:20:14 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][140/312]	eta 0:01:22 lr 0.002300	time 0.4611 (0.4794)	model_time 0.4607 (0.4652)	loss 3.5193 (3.2913)	grad_norm 4.1388 (1.6930/0.7581)	mem 16099MB
[2025-01-18 04:20:18 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][150/312]	eta 0:01:17 lr 0.002299	time 0.4483 (0.4779)	model_time 0.4481 (0.4646)	loss 3.4550 (3.2848)	grad_norm 2.2105 (1.7012/0.7499)	mem 16099MB
[2025-01-18 04:20:23 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][160/312]	eta 0:01:12 lr 0.002299	time 0.4444 (0.4772)	model_time 0.4439 (0.4647)	loss 3.1597 (3.2762)	grad_norm 1.4259 (1.6803/0.7361)	mem 16099MB
[2025-01-18 04:20:27 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][170/312]	eta 0:01:07 lr 0.002298	time 0.4509 (0.4761)	model_time 0.4504 (0.4643)	loss 3.7585 (3.2668)	grad_norm 2.5114 (1.7051/0.7360)	mem 16099MB
[2025-01-18 04:20:32 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][180/312]	eta 0:01:02 lr 0.002297	time 0.4558 (0.4752)	model_time 0.4553 (0.4640)	loss 2.6911 (3.2591)	grad_norm 1.0349 (1.6812/0.7320)	mem 16099MB
[2025-01-18 04:20:37 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][190/312]	eta 0:00:57 lr 0.002297	time 0.4497 (0.4747)	model_time 0.4493 (0.4641)	loss 2.8975 (3.2602)	grad_norm 0.7480 (1.6710/0.7259)	mem 16099MB
[2025-01-18 04:20:41 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][200/312]	eta 0:00:53 lr 0.002296	time 0.4502 (0.4747)	model_time 0.4500 (0.4646)	loss 3.3218 (3.2585)	grad_norm 1.9355 (1.6649/0.7163)	mem 16099MB
[2025-01-18 04:20:46 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][210/312]	eta 0:00:48 lr 0.002295	time 0.4482 (0.4743)	model_time 0.4481 (0.4647)	loss 2.2147 (3.2620)	grad_norm 1.0975 (1.6569/0.7059)	mem 16099MB
[2025-01-18 04:20:51 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][220/312]	eta 0:00:43 lr 0.002295	time 0.4628 (0.4741)	model_time 0.4623 (0.4649)	loss 3.8186 (3.2754)	grad_norm 1.7144 (1.6412/0.6966)	mem 16099MB
[2025-01-18 04:20:55 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][230/312]	eta 0:00:38 lr 0.002294	time 0.4551 (0.4735)	model_time 0.4549 (0.4647)	loss 3.2056 (3.2672)	grad_norm 3.0830 (1.6439/0.6934)	mem 16099MB
[2025-01-18 04:21:00 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][240/312]	eta 0:00:34 lr 0.002293	time 0.4430 (0.4734)	model_time 0.4425 (0.4649)	loss 3.3615 (3.2621)	grad_norm 2.5283 (1.6895/0.7339)	mem 16099MB
[2025-01-18 04:21:05 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][250/312]	eta 0:00:29 lr 0.002293	time 0.4489 (0.4726)	model_time 0.4484 (0.4644)	loss 2.9965 (3.2660)	grad_norm 1.5224 (1.6774/0.7247)	mem 16099MB
[2025-01-18 04:21:09 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][260/312]	eta 0:00:24 lr 0.002292	time 0.4428 (0.4723)	model_time 0.4427 (0.4645)	loss 2.9918 (3.2590)	grad_norm 3.1060 (1.6842/0.7218)	mem 16099MB
[2025-01-18 04:21:14 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][270/312]	eta 0:00:19 lr 0.002291	time 0.4699 (0.4720)	model_time 0.4694 (0.4645)	loss 3.5244 (3.2542)	grad_norm 2.2550 (1.7179/0.7598)	mem 16099MB
[2025-01-18 04:21:19 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][280/312]	eta 0:00:15 lr 0.002291	time 0.4465 (0.4720)	model_time 0.4463 (0.4647)	loss 3.2313 (3.2496)	grad_norm 1.5353 (1.7198/0.7509)	mem 16099MB
[2025-01-18 04:21:23 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][290/312]	eta 0:00:10 lr 0.002290	time 0.4444 (0.4720)	model_time 0.4443 (0.4650)	loss 2.4394 (3.2520)	grad_norm 1.3531 (1.7160/0.7420)	mem 16099MB
[2025-01-18 04:21:28 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][300/312]	eta 0:00:05 lr 0.002290	time 0.5213 (0.4718)	model_time 0.5212 (0.4650)	loss 3.5583 (3.2562)	grad_norm 2.3675 (1.7219/0.7479)	mem 16099MB
[2025-01-18 04:21:33 internimage_t_1k_224] (main.py 510): INFO Train: [136/300][310/312]	eta 0:00:00 lr 0.002289	time 0.4402 (0.4709)	model_time 0.4401 (0.4643)	loss 3.9254 (3.2643)	grad_norm 1.0200 (1.7245/0.7477)	mem 16099MB
[2025-01-18 04:21:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 136 training takes 0:02:26
[2025-01-18 04:21:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_136.pth saving......
[2025-01-18 04:21:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_136.pth saved !!!
[2025-01-18 04:21:41 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.295 (7.295)	Loss 0.8506 (0.8506)	Acc@1 81.787 (81.787)	Acc@5 96.313 (96.313)	Mem 16099MB
[2025-01-18 04:21:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.998)	Loss 1.1543 (1.0012)	Acc@1 74.243 (78.667)	Acc@5 93.213 (94.591)	Mem 16099MB
[2025-01-18 04:21:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:136] * Acc@1 78.483 Acc@5 94.590
[2025-01-18 04:21:45 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.5%
[2025-01-18 04:21:45 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:21:53 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.157 (8.157)	Loss 0.8167 (0.8167)	Acc@1 83.252 (83.252)	Acc@5 96.973 (96.973)	Mem 16099MB
[2025-01-18 04:21:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.099)	Loss 1.1464 (0.9556)	Acc@1 74.438 (80.049)	Acc@5 93.237 (95.250)	Mem 16099MB
[2025-01-18 04:21:57 internimage_t_1k_224] (main.py 575): INFO [Epoch:136] * Acc@1 79.942 Acc@5 95.254
[2025-01-18 04:21:57 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 79.9%
[2025-01-18 04:21:57 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:21:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:21:59 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 79.94%
[2025-01-18 04:22:01 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][0/312]	eta 0:11:31 lr 0.002289	time 2.2148 (2.2148)	model_time 0.4861 (0.4861)	loss 3.9704 (3.9704)	grad_norm 1.7804 (1.7804/0.0000)	mem 16099MB
[2025-01-18 04:22:05 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][10/312]	eta 0:03:10 lr 0.002288	time 0.4570 (0.6293)	model_time 0.4568 (0.4717)	loss 2.3361 (3.2053)	grad_norm 1.5543 (1.2970/0.2458)	mem 16099MB
[2025-01-18 04:22:10 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][20/312]	eta 0:02:40 lr 0.002287	time 0.4393 (0.5512)	model_time 0.4388 (0.4684)	loss 3.8018 (3.2731)	grad_norm 1.2802 (1.4831/0.3524)	mem 16099MB
[2025-01-18 04:22:15 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][30/312]	eta 0:02:27 lr 0.002287	time 0.4490 (0.5243)	model_time 0.4489 (0.4681)	loss 3.7764 (3.2684)	grad_norm 1.4275 (1.4364/0.3365)	mem 16099MB
[2025-01-18 04:22:19 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][40/312]	eta 0:02:17 lr 0.002286	time 0.4358 (0.5071)	model_time 0.4356 (0.4645)	loss 3.7706 (3.2217)	grad_norm 1.2475 (1.7745/0.9347)	mem 16099MB
[2025-01-18 04:22:24 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][50/312]	eta 0:02:11 lr 0.002285	time 0.4467 (0.5030)	model_time 0.4465 (0.4687)	loss 3.1423 (3.2261)	grad_norm 1.0516 (1.7287/0.8607)	mem 16099MB
[2025-01-18 04:22:29 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][60/312]	eta 0:02:04 lr 0.002285	time 0.4551 (0.4946)	model_time 0.4550 (0.4658)	loss 3.5899 (3.2691)	grad_norm 1.2776 (1.6762/0.8212)	mem 16099MB
[2025-01-18 04:22:33 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][70/312]	eta 0:01:58 lr 0.002284	time 0.4523 (0.4903)	model_time 0.4519 (0.4656)	loss 2.4976 (3.2562)	grad_norm 1.1150 (1.6570/0.7941)	mem 16099MB
[2025-01-18 04:22:38 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][80/312]	eta 0:01:52 lr 0.002283	time 0.4524 (0.4862)	model_time 0.4519 (0.4644)	loss 3.6655 (3.2868)	grad_norm 1.1663 (1.7116/0.8417)	mem 16099MB
[2025-01-18 04:22:43 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][90/312]	eta 0:01:47 lr 0.002283	time 0.4562 (0.4837)	model_time 0.4558 (0.4643)	loss 3.4551 (3.2792)	grad_norm 1.7359 (1.6777/0.8106)	mem 16099MB
[2025-01-18 04:22:47 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][100/312]	eta 0:01:42 lr 0.002282	time 0.4411 (0.4816)	model_time 0.4407 (0.4641)	loss 3.6077 (3.2802)	grad_norm 0.9288 (1.7141/0.8348)	mem 16099MB
[2025-01-18 04:22:52 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][110/312]	eta 0:01:37 lr 0.002281	time 0.5383 (0.4810)	model_time 0.5378 (0.4651)	loss 3.6588 (3.2659)	grad_norm 2.8067 (1.7342/0.8284)	mem 16099MB
[2025-01-18 04:22:57 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][120/312]	eta 0:01:31 lr 0.002281	time 0.4444 (0.4790)	model_time 0.4439 (0.4643)	loss 3.0956 (3.2852)	grad_norm 0.8830 (1.7224/0.8107)	mem 16099MB
[2025-01-18 04:23:01 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][130/312]	eta 0:01:27 lr 0.002280	time 0.4423 (0.4785)	model_time 0.4422 (0.4649)	loss 3.4486 (3.2933)	grad_norm 2.5440 (1.7583/0.8302)	mem 16099MB
[2025-01-18 04:23:06 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][140/312]	eta 0:01:22 lr 0.002279	time 0.4508 (0.4778)	model_time 0.4506 (0.4651)	loss 3.4027 (3.2888)	grad_norm 1.8504 (1.7582/0.8064)	mem 16099MB
[2025-01-18 04:23:11 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][150/312]	eta 0:01:17 lr 0.002279	time 0.4579 (0.4767)	model_time 0.4574 (0.4648)	loss 2.9946 (3.2672)	grad_norm 2.4499 (1.7849/0.8339)	mem 16099MB
[2025-01-18 04:23:15 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][160/312]	eta 0:01:12 lr 0.002278	time 0.4592 (0.4758)	model_time 0.4587 (0.4646)	loss 3.7978 (3.2738)	grad_norm 2.7397 (1.7768/0.8243)	mem 16099MB
[2025-01-18 04:23:20 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][170/312]	eta 0:01:07 lr 0.002278	time 0.4608 (0.4745)	model_time 0.4607 (0.4640)	loss 4.1978 (3.2843)	grad_norm 1.5686 (1.7645/0.8056)	mem 16099MB
[2025-01-18 04:23:24 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][180/312]	eta 0:01:02 lr 0.002277	time 0.4537 (0.4735)	model_time 0.4534 (0.4636)	loss 4.0913 (3.2698)	grad_norm 2.3830 (1.7471/0.7952)	mem 16099MB
[2025-01-18 04:23:29 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][190/312]	eta 0:00:57 lr 0.002276	time 0.4516 (0.4731)	model_time 0.4512 (0.4637)	loss 2.8176 (3.2608)	grad_norm 0.9854 (1.7655/0.7962)	mem 16099MB
[2025-01-18 04:23:34 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][200/312]	eta 0:00:52 lr 0.002276	time 0.4531 (0.4725)	model_time 0.4529 (0.4635)	loss 2.5843 (3.2402)	grad_norm 0.7906 (1.7413/0.7908)	mem 16099MB
[2025-01-18 04:23:38 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][210/312]	eta 0:00:48 lr 0.002275	time 0.4515 (0.4730)	model_time 0.4511 (0.4644)	loss 3.6048 (3.2452)	grad_norm 0.6426 (1.7223/0.7860)	mem 16099MB
[2025-01-18 04:23:43 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][220/312]	eta 0:00:43 lr 0.002274	time 0.4472 (0.4720)	model_time 0.4468 (0.4638)	loss 3.2818 (3.2378)	grad_norm 1.3207 (1.7016/0.7761)	mem 16099MB
[2025-01-18 04:23:48 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][230/312]	eta 0:00:38 lr 0.002274	time 0.5262 (0.4721)	model_time 0.5260 (0.4643)	loss 2.0678 (3.2341)	grad_norm 1.6778 (1.6865/0.7644)	mem 16099MB
[2025-01-18 04:23:52 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][240/312]	eta 0:00:33 lr 0.002273	time 0.4496 (0.4715)	model_time 0.4495 (0.4639)	loss 2.5899 (3.2384)	grad_norm 3.0378 (1.7006/0.7692)	mem 16099MB
[2025-01-18 04:23:57 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][250/312]	eta 0:00:29 lr 0.002272	time 0.4558 (0.4713)	model_time 0.4554 (0.4640)	loss 2.5006 (3.2302)	grad_norm 1.9260 (1.6952/0.7594)	mem 16099MB
[2025-01-18 04:24:02 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][260/312]	eta 0:00:24 lr 0.002272	time 0.5861 (0.4716)	model_time 0.5855 (0.4646)	loss 2.6207 (3.2342)	grad_norm 1.3610 (1.6946/0.7505)	mem 16099MB
[2025-01-18 04:24:06 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][270/312]	eta 0:00:19 lr 0.002271	time 0.4508 (0.4714)	model_time 0.4507 (0.4646)	loss 3.4587 (3.2374)	grad_norm 1.1499 (1.6890/0.7409)	mem 16099MB
[2025-01-18 04:24:11 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][280/312]	eta 0:00:15 lr 0.002270	time 0.4494 (0.4717)	model_time 0.4493 (0.4651)	loss 3.7555 (3.2359)	grad_norm 1.1938 (1.6700/0.7359)	mem 16099MB
[2025-01-18 04:24:16 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][290/312]	eta 0:00:10 lr 0.002270	time 0.4527 (0.4713)	model_time 0.4525 (0.4650)	loss 3.3651 (3.2445)	grad_norm 1.2687 (1.6728/0.7343)	mem 16099MB
[2025-01-18 04:24:20 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][300/312]	eta 0:00:05 lr 0.002269	time 0.4416 (0.4710)	model_time 0.4416 (0.4648)	loss 3.5263 (3.2457)	grad_norm 2.0502 (1.6899/0.7476)	mem 16099MB
[2025-01-18 04:24:25 internimage_t_1k_224] (main.py 510): INFO Train: [137/300][310/312]	eta 0:00:00 lr 0.002268	time 0.5214 (0.4706)	model_time 0.5213 (0.4647)	loss 4.0960 (3.2477)	grad_norm 0.7952 (1.7154/0.7572)	mem 16099MB
[2025-01-18 04:24:25 internimage_t_1k_224] (main.py 519): INFO EPOCH 137 training takes 0:02:26
[2025-01-18 04:24:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_137.pth saving......
[2025-01-18 04:24:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_137.pth saved !!!
[2025-01-18 04:24:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.415 (7.415)	Loss 0.8661 (0.8661)	Acc@1 82.031 (82.031)	Acc@5 96.045 (96.045)	Mem 16099MB
[2025-01-18 04:24:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.018)	Loss 1.2128 (1.0177)	Acc@1 73.145 (78.553)	Acc@5 92.993 (94.673)	Mem 16099MB
[2025-01-18 04:24:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:137] * Acc@1 78.477 Acc@5 94.740
[2025-01-18 04:24:38 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.5%
[2025-01-18 04:24:38 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:24:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.095 (8.095)	Loss 0.8163 (0.8163)	Acc@1 83.276 (83.276)	Acc@5 96.997 (96.997)	Mem 16099MB
[2025-01-18 04:24:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.087)	Loss 1.1435 (0.9544)	Acc@1 74.609 (80.111)	Acc@5 93.262 (95.281)	Mem 16099MB
[2025-01-18 04:24:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:137] * Acc@1 79.996 Acc@5 95.282
[2025-01-18 04:24:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.0%
[2025-01-18 04:24:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:24:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:24:51 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.00%
[2025-01-18 04:24:53 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][0/312]	eta 0:10:27 lr 0.002268	time 2.0116 (2.0116)	model_time 0.4656 (0.4656)	loss 3.3235 (3.3235)	grad_norm 1.4570 (1.4570/0.0000)	mem 16099MB
[2025-01-18 04:24:58 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][10/312]	eta 0:03:05 lr 0.002268	time 0.4499 (0.6146)	model_time 0.4497 (0.4737)	loss 2.5167 (3.2683)	grad_norm 0.9886 (1.5840/0.6483)	mem 16099MB
[2025-01-18 04:25:03 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][20/312]	eta 0:02:39 lr 0.002267	time 0.4542 (0.5467)	model_time 0.4541 (0.4727)	loss 3.9061 (3.3778)	grad_norm 6.1534 (2.0758/1.2086)	mem 16099MB
[2025-01-18 04:25:07 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][30/312]	eta 0:02:27 lr 0.002266	time 0.4646 (0.5219)	model_time 0.4644 (0.4717)	loss 3.9951 (3.4277)	grad_norm 2.4121 (2.0661/1.0763)	mem 16099MB
[2025-01-18 04:25:12 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][40/312]	eta 0:02:18 lr 0.002266	time 0.4532 (0.5085)	model_time 0.4528 (0.4704)	loss 3.9629 (3.4545)	grad_norm 1.6125 (1.8951/1.0036)	mem 16099MB
[2025-01-18 04:25:17 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][50/312]	eta 0:02:10 lr 0.002265	time 0.4533 (0.4981)	model_time 0.4532 (0.4675)	loss 3.5458 (3.3987)	grad_norm 1.1508 (1.7903/0.9635)	mem 16099MB
[2025-01-18 04:25:21 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][60/312]	eta 0:02:04 lr 0.002264	time 0.4520 (0.4923)	model_time 0.4515 (0.4665)	loss 3.7159 (3.4044)	grad_norm 1.6254 (1.7692/0.8943)	mem 16099MB
[2025-01-18 04:25:26 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][70/312]	eta 0:01:58 lr 0.002264	time 0.4569 (0.4879)	model_time 0.4567 (0.4658)	loss 3.4284 (3.3523)	grad_norm 2.1212 (1.7472/0.8510)	mem 16099MB
[2025-01-18 04:25:30 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][80/312]	eta 0:01:52 lr 0.002263	time 0.4631 (0.4851)	model_time 0.4630 (0.4656)	loss 2.2124 (3.2956)	grad_norm 0.7873 (1.7896/0.8399)	mem 16099MB
[2025-01-18 04:25:35 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][90/312]	eta 0:01:47 lr 0.002262	time 0.4411 (0.4854)	model_time 0.4410 (0.4681)	loss 3.5542 (3.3021)	grad_norm 1.8978 (1.7576/0.8071)	mem 16099MB
[2025-01-18 04:25:40 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][100/312]	eta 0:01:42 lr 0.002262	time 0.4481 (0.4828)	model_time 0.4480 (0.4671)	loss 3.1868 (3.2871)	grad_norm 1.8540 (1.7222/0.8010)	mem 16099MB
[2025-01-18 04:25:45 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][110/312]	eta 0:01:37 lr 0.002261	time 0.4557 (0.4814)	model_time 0.4555 (0.4671)	loss 3.2255 (3.2709)	grad_norm 2.1544 (1.7380/0.7733)	mem 16099MB
[2025-01-18 04:25:49 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][120/312]	eta 0:01:31 lr 0.002260	time 0.4654 (0.4791)	model_time 0.4652 (0.4660)	loss 3.9014 (3.2942)	grad_norm 1.6154 (1.7976/0.8447)	mem 16099MB
[2025-01-18 04:25:54 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][130/312]	eta 0:01:27 lr 0.002260	time 0.4537 (0.4785)	model_time 0.4533 (0.4663)	loss 3.7579 (3.3020)	grad_norm 2.4426 (1.7654/0.8301)	mem 16099MB
[2025-01-18 04:25:59 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][140/312]	eta 0:01:22 lr 0.002259	time 0.5148 (0.4786)	model_time 0.5143 (0.4672)	loss 3.1911 (3.3008)	grad_norm 2.4861 (1.7538/0.8160)	mem 16099MB
[2025-01-18 04:26:03 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][150/312]	eta 0:01:17 lr 0.002258	time 0.4580 (0.4790)	model_time 0.4579 (0.4684)	loss 2.8206 (3.3004)	grad_norm 1.5664 (1.7281/0.7966)	mem 16099MB
[2025-01-18 04:26:08 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][160/312]	eta 0:01:12 lr 0.002258	time 0.4619 (0.4782)	model_time 0.4615 (0.4682)	loss 3.0823 (3.3088)	grad_norm 1.3342 (1.7713/0.8430)	mem 16099MB
[2025-01-18 04:26:13 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][170/312]	eta 0:01:07 lr 0.002257	time 0.4485 (0.4773)	model_time 0.4484 (0.4679)	loss 2.2722 (3.3036)	grad_norm 1.4843 (1.7693/0.8305)	mem 16099MB
[2025-01-18 04:26:17 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][180/312]	eta 0:01:02 lr 0.002256	time 0.4497 (0.4766)	model_time 0.4495 (0.4677)	loss 3.9608 (3.3167)	grad_norm 2.9523 (1.7726/0.8391)	mem 16099MB
[2025-01-18 04:26:22 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][190/312]	eta 0:00:57 lr 0.002256	time 0.4508 (0.4752)	model_time 0.4507 (0.4667)	loss 2.7702 (3.3245)	grad_norm 1.5167 (1.7535/0.8267)	mem 16099MB
[2025-01-18 04:26:27 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][200/312]	eta 0:00:53 lr 0.002255	time 0.5308 (0.4749)	model_time 0.5306 (0.4669)	loss 4.0301 (3.3348)	grad_norm 2.6343 (1.7625/0.8243)	mem 16099MB
[2025-01-18 04:26:31 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][210/312]	eta 0:00:48 lr 0.002254	time 0.4409 (0.4745)	model_time 0.4408 (0.4668)	loss 3.2978 (3.3306)	grad_norm 1.0204 (1.7517/0.8226)	mem 16099MB
[2025-01-18 04:26:36 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][220/312]	eta 0:00:43 lr 0.002254	time 0.4548 (0.4735)	model_time 0.4546 (0.4661)	loss 3.8611 (3.3311)	grad_norm 1.1694 (1.7572/0.8162)	mem 16099MB
[2025-01-18 04:26:41 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][230/312]	eta 0:00:38 lr 0.002253	time 0.4578 (0.4741)	model_time 0.4573 (0.4670)	loss 3.1260 (3.3354)	grad_norm 1.7886 (1.7388/0.8048)	mem 16099MB
[2025-01-18 04:26:45 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][240/312]	eta 0:00:34 lr 0.002252	time 0.4555 (0.4740)	model_time 0.4553 (0.4673)	loss 3.7052 (3.3427)	grad_norm 1.8222 (1.7321/0.7967)	mem 16099MB
[2025-01-18 04:26:50 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][250/312]	eta 0:00:29 lr 0.002252	time 0.4533 (0.4735)	model_time 0.4532 (0.4670)	loss 3.5066 (3.3260)	grad_norm 1.6207 (1.7311/0.7862)	mem 16099MB
[2025-01-18 04:26:55 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][260/312]	eta 0:00:24 lr 0.002251	time 0.4455 (0.4734)	model_time 0.4453 (0.4671)	loss 2.5045 (3.3274)	grad_norm 3.9655 (1.7344/0.7948)	mem 16099MB
[2025-01-18 04:26:59 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][270/312]	eta 0:00:19 lr 0.002250	time 0.4510 (0.4729)	model_time 0.4506 (0.4668)	loss 3.7041 (3.3249)	grad_norm 1.8288 (1.7432/0.8006)	mem 16099MB
[2025-01-18 04:27:04 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][280/312]	eta 0:00:15 lr 0.002250	time 0.4463 (0.4731)	model_time 0.4459 (0.4673)	loss 3.5700 (3.3239)	grad_norm 1.9673 (1.7538/0.8046)	mem 16099MB
[2025-01-18 04:27:09 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][290/312]	eta 0:00:10 lr 0.002249	time 0.4465 (0.4724)	model_time 0.4463 (0.4667)	loss 3.4944 (3.3288)	grad_norm 1.0691 (1.7723/0.8152)	mem 16099MB
[2025-01-18 04:27:13 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][300/312]	eta 0:00:05 lr 0.002248	time 0.4378 (0.4719)	model_time 0.4377 (0.4664)	loss 3.5693 (3.3222)	grad_norm 0.8232 (1.7805/0.8278)	mem 16099MB
[2025-01-18 04:27:18 internimage_t_1k_224] (main.py 510): INFO Train: [138/300][310/312]	eta 0:00:00 lr 0.002248	time 0.4386 (0.4711)	model_time 0.4385 (0.4658)	loss 3.9689 (3.3199)	grad_norm 3.9878 (1.7976/0.8344)	mem 16099MB
[2025-01-18 04:27:18 internimage_t_1k_224] (main.py 519): INFO EPOCH 138 training takes 0:02:26
[2025-01-18 04:27:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_138.pth saving......
[2025-01-18 04:27:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_138.pth saved !!!
[2025-01-18 04:27:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.514 (7.514)	Loss 0.8523 (0.8523)	Acc@1 81.738 (81.738)	Acc@5 96.289 (96.289)	Mem 16099MB
[2025-01-18 04:27:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.028)	Loss 1.1556 (0.9939)	Acc@1 73.779 (78.795)	Acc@5 92.969 (94.742)	Mem 16099MB
[2025-01-18 04:27:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:138] * Acc@1 78.665 Acc@5 94.750
[2025-01-18 04:27:31 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.7%
[2025-01-18 04:27:31 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:27:39 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.172 (8.172)	Loss 0.8156 (0.8156)	Acc@1 83.301 (83.301)	Acc@5 96.997 (96.997)	Mem 16099MB
[2025-01-18 04:27:43 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.101)	Loss 1.1405 (0.9532)	Acc@1 74.707 (80.147)	Acc@5 93.384 (95.306)	Mem 16099MB
[2025-01-18 04:27:43 internimage_t_1k_224] (main.py 575): INFO [Epoch:138] * Acc@1 80.028 Acc@5 95.310
[2025-01-18 04:27:43 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.0%
[2025-01-18 04:27:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:27:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:27:44 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.03%
[2025-01-18 04:27:47 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][0/312]	eta 0:12:17 lr 0.002248	time 2.3643 (2.3643)	model_time 0.4664 (0.4664)	loss 3.9681 (3.9681)	grad_norm 4.5913 (4.5913/0.0000)	mem 16099MB
[2025-01-18 04:27:51 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][10/312]	eta 0:03:15 lr 0.002247	time 0.4460 (0.6462)	model_time 0.4458 (0.4734)	loss 3.8685 (3.2672)	grad_norm 2.8971 (2.3960/1.6924)	mem 16099MB
[2025-01-18 04:27:56 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][20/312]	eta 0:02:43 lr 0.002246	time 0.4493 (0.5596)	model_time 0.4492 (0.4690)	loss 2.8909 (3.3882)	grad_norm 1.0003 (2.0086/1.3500)	mem 16099MB
[2025-01-18 04:28:01 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][30/312]	eta 0:02:32 lr 0.002246	time 0.7345 (0.5391)	model_time 0.7341 (0.4776)	loss 3.4439 (3.3130)	grad_norm 1.6461 (1.9959/1.2009)	mem 16099MB
[2025-01-18 04:28:06 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][40/312]	eta 0:02:20 lr 0.002245	time 0.4615 (0.5182)	model_time 0.4613 (0.4716)	loss 3.0480 (3.3001)	grad_norm 1.5493 (1.9735/1.0898)	mem 16099MB
[2025-01-18 04:28:10 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][50/312]	eta 0:02:12 lr 0.002244	time 0.4569 (0.5068)	model_time 0.4567 (0.4692)	loss 3.5659 (3.2971)	grad_norm 2.2564 (1.9495/1.0230)	mem 16099MB
[2025-01-18 04:28:15 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][60/312]	eta 0:02:05 lr 0.002244	time 0.4531 (0.4983)	model_time 0.4529 (0.4668)	loss 3.5629 (3.3288)	grad_norm 1.0872 (1.8353/0.9751)	mem 16099MB
[2025-01-18 04:28:19 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][70/312]	eta 0:01:59 lr 0.002243	time 0.4553 (0.4919)	model_time 0.4549 (0.4648)	loss 3.4133 (3.3267)	grad_norm 1.8016 (1.8960/0.9841)	mem 16099MB
[2025-01-18 04:28:24 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][80/312]	eta 0:01:53 lr 0.002242	time 0.4431 (0.4890)	model_time 0.4429 (0.4652)	loss 2.8255 (3.3126)	grad_norm 0.8461 (1.8926/0.9689)	mem 16099MB
[2025-01-18 04:28:29 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][90/312]	eta 0:01:47 lr 0.002242	time 0.4448 (0.4856)	model_time 0.4446 (0.4644)	loss 3.5073 (3.3247)	grad_norm 1.0783 (1.8628/0.9648)	mem 16099MB
[2025-01-18 04:28:33 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][100/312]	eta 0:01:42 lr 0.002241	time 0.4402 (0.4834)	model_time 0.4398 (0.4643)	loss 4.1050 (3.3224)	grad_norm 3.5979 (1.8961/0.9793)	mem 16099MB
[2025-01-18 04:28:38 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][110/312]	eta 0:01:37 lr 0.002240	time 0.4399 (0.4807)	model_time 0.4395 (0.4632)	loss 3.5833 (3.3293)	grad_norm 1.4463 (1.8626/0.9494)	mem 16099MB
[2025-01-18 04:28:42 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][120/312]	eta 0:01:32 lr 0.002240	time 0.4537 (0.4799)	model_time 0.4533 (0.4638)	loss 3.1760 (3.3039)	grad_norm 1.4786 (1.8066/0.9302)	mem 16099MB
[2025-01-18 04:28:47 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][130/312]	eta 0:01:27 lr 0.002239	time 0.4496 (0.4815)	model_time 0.4492 (0.4667)	loss 2.5660 (3.2838)	grad_norm 1.0293 (1.7984/0.9075)	mem 16099MB
[2025-01-18 04:28:52 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][140/312]	eta 0:01:22 lr 0.002238	time 0.4634 (0.4810)	model_time 0.4633 (0.4671)	loss 3.0639 (3.2844)	grad_norm 1.8148 (1.8161/0.9091)	mem 16099MB
[2025-01-18 04:28:57 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][150/312]	eta 0:01:18 lr 0.002238	time 0.4452 (0.4824)	model_time 0.4447 (0.4695)	loss 2.1921 (3.2711)	grad_norm 1.9691 (1.8094/0.8957)	mem 16099MB
[2025-01-18 04:29:02 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][160/312]	eta 0:01:13 lr 0.002237	time 0.4533 (0.4815)	model_time 0.4528 (0.4694)	loss 2.6582 (3.2812)	grad_norm 1.7476 (1.7905/0.8813)	mem 16099MB
[2025-01-18 04:29:06 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][170/312]	eta 0:01:08 lr 0.002236	time 0.4563 (0.4800)	model_time 0.4558 (0.4685)	loss 3.9139 (3.2796)	grad_norm 1.5000 (1.7842/0.8684)	mem 16099MB
[2025-01-18 04:29:11 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][180/312]	eta 0:01:03 lr 0.002236	time 0.4511 (0.4786)	model_time 0.4510 (0.4677)	loss 3.5342 (3.2833)	grad_norm 1.8725 (1.7741/0.8486)	mem 16099MB
[2025-01-18 04:29:16 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][190/312]	eta 0:00:58 lr 0.002235	time 0.5002 (0.4781)	model_time 0.4998 (0.4678)	loss 2.7841 (3.2875)	grad_norm 1.1384 (1.7608/0.8345)	mem 16099MB
[2025-01-18 04:29:20 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][200/312]	eta 0:00:53 lr 0.002234	time 0.4570 (0.4768)	model_time 0.4565 (0.4670)	loss 3.2323 (3.2806)	grad_norm 4.1732 (1.7821/0.8564)	mem 16099MB
[2025-01-18 04:29:25 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][210/312]	eta 0:00:48 lr 0.002234	time 0.5692 (0.4769)	model_time 0.5690 (0.4675)	loss 2.9343 (3.2696)	grad_norm 2.5743 (1.7985/0.8624)	mem 16099MB
[2025-01-18 04:29:30 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][220/312]	eta 0:00:43 lr 0.002233	time 0.4488 (0.4758)	model_time 0.4487 (0.4668)	loss 3.6593 (3.2715)	grad_norm 2.1443 (1.7974/0.8490)	mem 16099MB
[2025-01-18 04:29:34 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][230/312]	eta 0:00:38 lr 0.002232	time 0.4506 (0.4753)	model_time 0.4501 (0.4667)	loss 3.5472 (3.2733)	grad_norm 1.4399 (1.7960/0.8371)	mem 16099MB
[2025-01-18 04:29:39 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][240/312]	eta 0:00:34 lr 0.002232	time 0.4463 (0.4758)	model_time 0.4461 (0.4676)	loss 3.7856 (3.2735)	grad_norm 0.8736 (1.7807/0.8274)	mem 16099MB
[2025-01-18 04:29:44 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][250/312]	eta 0:00:29 lr 0.002231	time 0.4425 (0.4752)	model_time 0.4421 (0.4673)	loss 3.0102 (3.2696)	grad_norm 1.5882 (1.8049/0.8362)	mem 16099MB
[2025-01-18 04:29:48 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][260/312]	eta 0:00:24 lr 0.002230	time 0.4416 (0.4751)	model_time 0.4412 (0.4675)	loss 3.5558 (3.2621)	grad_norm 1.2433 (1.8214/0.8446)	mem 16099MB
[2025-01-18 04:29:53 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][270/312]	eta 0:00:19 lr 0.002230	time 0.4494 (0.4750)	model_time 0.4490 (0.4676)	loss 2.1883 (3.2537)	grad_norm 0.9211 (1.8181/0.8403)	mem 16099MB
[2025-01-18 04:29:58 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][280/312]	eta 0:00:15 lr 0.002229	time 0.4535 (0.4743)	model_time 0.4534 (0.4672)	loss 3.0496 (3.2658)	grad_norm 1.5500 (1.8081/0.8334)	mem 16099MB
[2025-01-18 04:30:02 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][290/312]	eta 0:00:10 lr 0.002228	time 0.4387 (0.4739)	model_time 0.4385 (0.4670)	loss 3.1546 (3.2638)	grad_norm 1.2196 (1.7898/0.8273)	mem 16099MB
[2025-01-18 04:30:07 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][300/312]	eta 0:00:05 lr 0.002228	time 0.4434 (0.4742)	model_time 0.4433 (0.4676)	loss 3.4060 (3.2687)	grad_norm 2.8683 (1.7835/0.8042)	mem 16099MB
[2025-01-18 04:30:12 internimage_t_1k_224] (main.py 510): INFO Train: [139/300][310/312]	eta 0:00:00 lr 0.002227	time 0.4388 (0.4731)	model_time 0.4388 (0.4667)	loss 2.9928 (3.2650)	grad_norm 1.6460 (1.7891/0.7665)	mem 16099MB
[2025-01-18 04:30:12 internimage_t_1k_224] (main.py 519): INFO EPOCH 139 training takes 0:02:27
[2025-01-18 04:30:12 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_139.pth saving......
[2025-01-18 04:30:13 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_139.pth saved !!!
[2025-01-18 04:30:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.251 (7.251)	Loss 0.8673 (0.8673)	Acc@1 82.568 (82.568)	Acc@5 96.558 (96.558)	Mem 16099MB
[2025-01-18 04:30:24 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.997)	Loss 1.2054 (1.0116)	Acc@1 73.755 (78.793)	Acc@5 92.944 (94.687)	Mem 16099MB
[2025-01-18 04:30:24 internimage_t_1k_224] (main.py 575): INFO [Epoch:139] * Acc@1 78.727 Acc@5 94.726
[2025-01-18 04:30:24 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.7%
[2025-01-18 04:30:24 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.74%
[2025-01-18 04:30:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.242 (8.242)	Loss 0.8150 (0.8150)	Acc@1 83.325 (83.325)	Acc@5 96.997 (96.997)	Mem 16099MB
[2025-01-18 04:30:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.110)	Loss 1.1378 (0.9521)	Acc@1 74.878 (80.238)	Acc@5 93.408 (95.330)	Mem 16099MB
[2025-01-18 04:30:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:139] * Acc@1 80.100 Acc@5 95.333
[2025-01-18 04:30:37 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.1%
[2025-01-18 04:30:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:30:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:30:38 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.10%
[2025-01-18 04:30:40 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][0/312]	eta 0:13:03 lr 0.002227	time 2.5112 (2.5112)	model_time 0.4591 (0.4591)	loss 2.9249 (2.9249)	grad_norm 1.8356 (1.8356/0.0000)	mem 16099MB
[2025-01-18 04:30:45 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][10/312]	eta 0:03:22 lr 0.002226	time 0.7315 (0.6718)	model_time 0.7313 (0.4849)	loss 3.3163 (3.4305)	grad_norm 1.8277 (1.7486/0.4415)	mem 16099MB
[2025-01-18 04:30:50 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][20/312]	eta 0:02:49 lr 0.002226	time 0.4528 (0.5790)	model_time 0.4526 (0.4810)	loss 2.7725 (3.4269)	grad_norm 1.3049 (1.9837/0.6585)	mem 16099MB
[2025-01-18 04:30:55 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][30/312]	eta 0:02:31 lr 0.002225	time 0.4574 (0.5388)	model_time 0.4573 (0.4722)	loss 3.5181 (3.3295)	grad_norm 1.2531 (1.9936/0.7799)	mem 16099MB
[2025-01-18 04:30:59 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][40/312]	eta 0:02:20 lr 0.002224	time 0.4631 (0.5175)	model_time 0.4629 (0.4671)	loss 3.2875 (3.3602)	grad_norm 1.3556 (1.9126/0.7161)	mem 16099MB
[2025-01-18 04:31:04 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][50/312]	eta 0:02:16 lr 0.002224	time 0.7147 (0.5196)	model_time 0.7143 (0.4790)	loss 3.8960 (3.2995)	grad_norm 1.1059 (1.8120/0.7483)	mem 16099MB
[2025-01-18 04:31:09 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][60/312]	eta 0:02:08 lr 0.002223	time 0.4562 (0.5103)	model_time 0.4560 (0.4763)	loss 3.6174 (3.2850)	grad_norm 1.0159 (1.7553/0.7200)	mem 16099MB
[2025-01-18 04:31:14 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][70/312]	eta 0:02:01 lr 0.002222	time 0.4608 (0.5034)	model_time 0.4606 (0.4741)	loss 2.7706 (3.2844)	grad_norm 0.8754 (1.7169/0.7126)	mem 16099MB
[2025-01-18 04:31:18 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][80/312]	eta 0:01:55 lr 0.002222	time 0.4481 (0.4979)	model_time 0.4477 (0.4721)	loss 3.3957 (3.2891)	grad_norm 1.0972 (1.7244/0.7540)	mem 16099MB
[2025-01-18 04:31:23 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][90/312]	eta 0:01:49 lr 0.002221	time 0.4522 (0.4940)	model_time 0.4521 (0.4710)	loss 3.6766 (3.2568)	grad_norm 1.4260 (1.6695/0.7369)	mem 16099MB
[2025-01-18 04:31:28 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][100/312]	eta 0:01:44 lr 0.002220	time 0.4428 (0.4928)	model_time 0.4424 (0.4720)	loss 3.3681 (3.2457)	grad_norm 1.2384 (1.6891/0.7360)	mem 16099MB
[2025-01-18 04:31:32 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][110/312]	eta 0:01:39 lr 0.002220	time 0.4632 (0.4904)	model_time 0.4630 (0.4715)	loss 3.6456 (3.2437)	grad_norm 1.0756 (1.6955/0.7522)	mem 16099MB
[2025-01-18 04:31:37 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][120/312]	eta 0:01:33 lr 0.002219	time 0.4556 (0.4873)	model_time 0.4554 (0.4700)	loss 2.5321 (3.2153)	grad_norm 1.4473 (1.7023/0.7347)	mem 16099MB
[2025-01-18 04:31:42 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][130/312]	eta 0:01:28 lr 0.002218	time 0.4417 (0.4880)	model_time 0.4413 (0.4719)	loss 2.9708 (3.2108)	grad_norm 3.8802 (1.7602/0.8160)	mem 16099MB
[2025-01-18 04:31:47 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][140/312]	eta 0:01:23 lr 0.002218	time 0.4479 (0.4865)	model_time 0.4478 (0.4715)	loss 3.5906 (3.2365)	grad_norm 1.8301 (1.7649/0.7933)	mem 16099MB
[2025-01-18 04:31:51 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][150/312]	eta 0:01:18 lr 0.002217	time 0.4450 (0.4851)	model_time 0.4448 (0.4712)	loss 3.5404 (3.2482)	grad_norm 1.0699 (1.7201/0.7868)	mem 16099MB
[2025-01-18 04:31:56 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][160/312]	eta 0:01:13 lr 0.002216	time 0.4687 (0.4851)	model_time 0.4682 (0.4720)	loss 3.9886 (3.2418)	grad_norm 2.3235 (1.7285/0.7834)	mem 16099MB
[2025-01-18 04:32:01 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][170/312]	eta 0:01:08 lr 0.002216	time 0.4503 (0.4835)	model_time 0.4499 (0.4711)	loss 3.3255 (3.2478)	grad_norm 0.6017 (1.7290/0.7696)	mem 16099MB
[2025-01-18 04:32:05 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][180/312]	eta 0:01:03 lr 0.002215	time 0.4396 (0.4830)	model_time 0.4395 (0.4712)	loss 4.2486 (3.2500)	grad_norm 2.4565 (1.7807/0.8093)	mem 16099MB
[2025-01-18 04:32:10 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][190/312]	eta 0:00:58 lr 0.002214	time 0.4677 (0.4816)	model_time 0.4676 (0.4704)	loss 3.0555 (3.2452)	grad_norm 1.4077 (1.7773/0.8044)	mem 16099MB
[2025-01-18 04:32:15 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][200/312]	eta 0:00:53 lr 0.002214	time 0.4734 (0.4806)	model_time 0.4730 (0.4700)	loss 2.6935 (3.2463)	grad_norm 1.6080 (1.7555/0.7932)	mem 16099MB
[2025-01-18 04:32:19 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][210/312]	eta 0:00:49 lr 0.002213	time 0.4505 (0.4805)	model_time 0.4500 (0.4704)	loss 2.2586 (3.2407)	grad_norm 1.2198 (1.7445/0.7793)	mem 16099MB
[2025-01-18 04:32:24 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][220/312]	eta 0:00:44 lr 0.002212	time 0.4527 (0.4797)	model_time 0.4526 (0.4700)	loss 2.6166 (3.2378)	grad_norm 1.8198 (1.7509/0.7680)	mem 16099MB
[2025-01-18 04:32:29 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][230/312]	eta 0:00:39 lr 0.002212	time 0.4784 (0.4787)	model_time 0.4782 (0.4695)	loss 3.8102 (3.2493)	grad_norm 0.7964 (1.7275/0.7632)	mem 16099MB
[2025-01-18 04:32:33 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][240/312]	eta 0:00:34 lr 0.002211	time 0.4413 (0.4781)	model_time 0.4411 (0.4692)	loss 3.2771 (3.2569)	grad_norm 1.5453 (1.7180/0.7505)	mem 16099MB
[2025-01-18 04:32:38 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][250/312]	eta 0:00:29 lr 0.002210	time 0.4462 (0.4771)	model_time 0.4460 (0.4685)	loss 3.3282 (3.2635)	grad_norm 0.7507 (1.6981/0.7458)	mem 16099MB
[2025-01-18 04:32:42 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][260/312]	eta 0:00:24 lr 0.002210	time 0.4869 (0.4771)	model_time 0.4864 (0.4689)	loss 2.6328 (3.2624)	grad_norm 2.8097 (1.7279/0.7676)	mem 16099MB
[2025-01-18 04:32:47 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][270/312]	eta 0:00:20 lr 0.002209	time 0.4534 (0.4766)	model_time 0.4530 (0.4686)	loss 3.0740 (3.2613)	grad_norm 0.9448 (1.7152/0.7590)	mem 16099MB
[2025-01-18 04:32:52 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][280/312]	eta 0:00:15 lr 0.002208	time 0.5071 (0.4777)	model_time 0.5066 (0.4700)	loss 3.4124 (3.2525)	grad_norm 1.6521 (1.7227/0.7539)	mem 16099MB
[2025-01-18 04:32:57 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][290/312]	eta 0:00:10 lr 0.002208	time 0.4426 (0.4780)	model_time 0.4422 (0.4706)	loss 4.0830 (3.2585)	grad_norm 3.0164 (1.7332/0.7596)	mem 16099MB
[2025-01-18 04:33:02 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][300/312]	eta 0:00:05 lr 0.002207	time 0.4367 (0.4770)	model_time 0.4365 (0.4698)	loss 4.0426 (3.2639)	grad_norm 3.4461 (1.7415/0.7588)	mem 16099MB
[2025-01-18 04:33:06 internimage_t_1k_224] (main.py 510): INFO Train: [140/300][310/312]	eta 0:00:00 lr 0.002206	time 0.4377 (0.4760)	model_time 0.4377 (0.4690)	loss 3.2996 (3.2611)	grad_norm 2.1061 (1.7383/0.7613)	mem 16099MB
[2025-01-18 04:33:06 internimage_t_1k_224] (main.py 519): INFO EPOCH 140 training takes 0:02:28
[2025-01-18 04:33:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_140.pth saving......
[2025-01-18 04:33:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_140.pth saved !!!
[2025-01-18 04:33:16 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.644 (7.644)	Loss 0.8678 (0.8678)	Acc@1 81.812 (81.812)	Acc@5 96.289 (96.289)	Mem 16099MB
[2025-01-18 04:33:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.009)	Loss 1.1903 (0.9923)	Acc@1 73.560 (78.806)	Acc@5 92.725 (94.818)	Mem 16099MB
[2025-01-18 04:33:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:140] * Acc@1 78.759 Acc@5 94.860
[2025-01-18 04:33:19 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.8%
[2025-01-18 04:33:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 04:33:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 04:33:20 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.76%
[2025-01-18 04:33:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.352 (7.352)	Loss 0.8144 (0.8144)	Acc@1 83.447 (83.447)	Acc@5 97.046 (97.046)	Mem 16099MB
[2025-01-18 04:33:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.008)	Loss 1.1353 (0.9510)	Acc@1 74.902 (80.285)	Acc@5 93.506 (95.355)	Mem 16099MB
[2025-01-18 04:33:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:140] * Acc@1 80.152 Acc@5 95.351
[2025-01-18 04:33:31 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.2%
[2025-01-18 04:33:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:33:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:33:33 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.15%
[2025-01-18 04:33:35 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][0/312]	eta 0:13:17 lr 0.002206	time 2.5564 (2.5564)	model_time 0.4825 (0.4825)	loss 3.6207 (3.6207)	grad_norm 1.1499 (1.1499/0.0000)	mem 16099MB
[2025-01-18 04:33:40 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][10/312]	eta 0:03:19 lr 0.002206	time 0.4522 (0.6601)	model_time 0.4521 (0.4714)	loss 4.1892 (3.4137)	grad_norm 2.0921 (1.9714/0.8847)	mem 16099MB
[2025-01-18 04:33:45 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][20/312]	eta 0:02:46 lr 0.002205	time 0.4532 (0.5699)	model_time 0.4530 (0.4708)	loss 2.9793 (3.2790)	grad_norm 1.4611 (1.8434/0.7364)	mem 16099MB
[2025-01-18 04:33:49 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][30/312]	eta 0:02:30 lr 0.002204	time 0.4573 (0.5350)	model_time 0.4572 (0.4678)	loss 3.0908 (3.1924)	grad_norm 4.5449 (1.8692/0.9195)	mem 16099MB
[2025-01-18 04:33:54 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][40/312]	eta 0:02:21 lr 0.002204	time 0.5521 (0.5199)	model_time 0.5520 (0.4690)	loss 4.0482 (3.2615)	grad_norm 2.4316 (1.9743/0.9121)	mem 16099MB
[2025-01-18 04:33:59 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][50/312]	eta 0:02:13 lr 0.002203	time 0.4436 (0.5093)	model_time 0.4431 (0.4683)	loss 3.8552 (3.3196)	grad_norm 2.3095 (1.9714/0.9455)	mem 16099MB
[2025-01-18 04:34:04 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][60/312]	eta 0:02:06 lr 0.002202	time 0.4509 (0.5033)	model_time 0.4504 (0.4689)	loss 3.9931 (3.3303)	grad_norm 1.5704 (1.8771/0.9008)	mem 16099MB
[2025-01-18 04:34:08 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][70/312]	eta 0:02:00 lr 0.002202	time 0.4530 (0.4966)	model_time 0.4529 (0.4670)	loss 3.3705 (3.3186)	grad_norm 1.0027 (1.8121/0.8568)	mem 16099MB
[2025-01-18 04:34:13 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][80/312]	eta 0:01:54 lr 0.002201	time 0.4575 (0.4926)	model_time 0.4573 (0.4666)	loss 3.0572 (3.3189)	grad_norm 1.9115 (1.7935/0.8466)	mem 16099MB
[2025-01-18 04:34:17 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][90/312]	eta 0:01:48 lr 0.002200	time 0.4421 (0.4901)	model_time 0.4419 (0.4669)	loss 4.1261 (3.3176)	grad_norm 1.0820 (1.7437/0.8217)	mem 16099MB
[2025-01-18 04:34:22 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][100/312]	eta 0:01:43 lr 0.002200	time 0.4726 (0.4874)	model_time 0.4721 (0.4665)	loss 3.5475 (3.3003)	grad_norm 1.0734 (1.6950/0.7976)	mem 16099MB
[2025-01-18 04:34:27 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][110/312]	eta 0:01:37 lr 0.002199	time 0.4674 (0.4843)	model_time 0.4669 (0.4652)	loss 2.7929 (3.3010)	grad_norm 2.3771 (1.6514/0.7846)	mem 16099MB
[2025-01-18 04:34:32 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][120/312]	eta 0:01:33 lr 0.002198	time 0.4938 (0.4860)	model_time 0.4934 (0.4685)	loss 3.2187 (3.3196)	grad_norm 2.0287 (1.6564/0.7658)	mem 16099MB
[2025-01-18 04:34:36 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][130/312]	eta 0:01:28 lr 0.002198	time 0.4447 (0.4840)	model_time 0.4446 (0.4678)	loss 3.2628 (3.3290)	grad_norm 1.0474 (1.7342/0.8964)	mem 16099MB
[2025-01-18 04:34:41 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][140/312]	eta 0:01:23 lr 0.002197	time 0.4543 (0.4832)	model_time 0.4542 (0.4682)	loss 3.4459 (3.3225)	grad_norm 4.2921 (1.7947/0.9443)	mem 16099MB
[2025-01-18 04:34:46 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][150/312]	eta 0:01:18 lr 0.002196	time 0.4555 (0.4820)	model_time 0.4551 (0.4680)	loss 3.4375 (3.3136)	grad_norm 0.9438 (1.7815/0.9306)	mem 16099MB
[2025-01-18 04:34:50 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][160/312]	eta 0:01:13 lr 0.002196	time 0.5325 (0.4825)	model_time 0.5321 (0.4692)	loss 3.2177 (3.3170)	grad_norm 1.0648 (1.7607/0.9105)	mem 16099MB
[2025-01-18 04:34:55 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][170/312]	eta 0:01:08 lr 0.002195	time 0.5304 (0.4819)	model_time 0.5303 (0.4694)	loss 3.1335 (3.3265)	grad_norm 1.2234 (1.7831/0.9313)	mem 16099MB
[2025-01-18 04:35:00 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][180/312]	eta 0:01:03 lr 0.002194	time 0.4584 (0.4822)	model_time 0.4583 (0.4704)	loss 3.7955 (3.3256)	grad_norm 1.1247 (1.7696/0.9111)	mem 16099MB
[2025-01-18 04:35:05 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][190/312]	eta 0:00:58 lr 0.002194	time 0.4499 (0.4808)	model_time 0.4498 (0.4696)	loss 3.4272 (3.3251)	grad_norm 0.9730 (1.7517/0.8962)	mem 16099MB
[2025-01-18 04:35:09 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][200/312]	eta 0:00:53 lr 0.002193	time 0.4516 (0.4802)	model_time 0.4514 (0.4695)	loss 4.0150 (3.3385)	grad_norm 3.3832 (1.7839/0.9167)	mem 16099MB
[2025-01-18 04:35:14 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][210/312]	eta 0:00:48 lr 0.002192	time 0.4462 (0.4793)	model_time 0.4461 (0.4691)	loss 2.2546 (3.3475)	grad_norm 1.9519 (1.7988/0.9141)	mem 16099MB
[2025-01-18 04:35:19 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][220/312]	eta 0:00:44 lr 0.002192	time 0.4455 (0.4785)	model_time 0.4453 (0.4688)	loss 3.1000 (3.3371)	grad_norm 2.9051 (1.8131/0.9100)	mem 16099MB
[2025-01-18 04:35:23 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][230/312]	eta 0:00:39 lr 0.002191	time 0.4665 (0.4785)	model_time 0.4660 (0.4692)	loss 3.2759 (3.3349)	grad_norm 2.3813 (1.8146/0.8983)	mem 16099MB
[2025-01-18 04:35:28 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][240/312]	eta 0:00:34 lr 0.002190	time 0.4489 (0.4773)	model_time 0.4485 (0.4684)	loss 3.2042 (3.3298)	grad_norm 1.1985 (1.8047/0.8853)	mem 16099MB
[2025-01-18 04:35:32 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][250/312]	eta 0:00:29 lr 0.002190	time 0.4443 (0.4766)	model_time 0.4441 (0.4680)	loss 3.4162 (3.3381)	grad_norm 2.3635 (1.7990/0.8761)	mem 16099MB
[2025-01-18 04:35:37 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][260/312]	eta 0:00:24 lr 0.002189	time 0.4412 (0.4763)	model_time 0.4408 (0.4680)	loss 3.2011 (3.3378)	grad_norm 1.1349 (1.7963/0.8633)	mem 16099MB
[2025-01-18 04:35:42 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][270/312]	eta 0:00:19 lr 0.002188	time 0.4453 (0.4754)	model_time 0.4448 (0.4674)	loss 2.8915 (3.3355)	grad_norm 1.7444 (1.8050/0.8505)	mem 16099MB
[2025-01-18 04:35:47 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][280/312]	eta 0:00:15 lr 0.002188	time 0.4620 (0.4759)	model_time 0.4616 (0.4682)	loss 3.4717 (3.3395)	grad_norm 0.8393 (1.7935/0.8466)	mem 16099MB
[2025-01-18 04:35:51 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][290/312]	eta 0:00:10 lr 0.002187	time 0.4499 (0.4761)	model_time 0.4497 (0.4686)	loss 3.2917 (3.3260)	grad_norm 0.8839 (1.7957/0.8384)	mem 16099MB
[2025-01-18 04:35:56 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][300/312]	eta 0:00:05 lr 0.002186	time 0.4458 (0.4752)	model_time 0.4457 (0.4680)	loss 3.1358 (3.3210)	grad_norm 0.9446 (1.7935/0.8336)	mem 16099MB
[2025-01-18 04:36:00 internimage_t_1k_224] (main.py 510): INFO Train: [141/300][310/312]	eta 0:00:00 lr 0.002186	time 0.4371 (0.4746)	model_time 0.4370 (0.4676)	loss 3.3645 (3.3252)	grad_norm 3.4524 (1.8135/0.8489)	mem 16099MB
[2025-01-18 04:36:01 internimage_t_1k_224] (main.py 519): INFO EPOCH 141 training takes 0:02:28
[2025-01-18 04:36:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_141.pth saving......
[2025-01-18 04:36:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_141.pth saved !!!
[2025-01-18 04:36:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.536 (7.536)	Loss 0.8338 (0.8338)	Acc@1 82.104 (82.104)	Acc@5 96.265 (96.265)	Mem 16099MB
[2025-01-18 04:36:13 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.010)	Loss 1.1650 (0.9663)	Acc@1 73.975 (78.802)	Acc@5 92.773 (94.711)	Mem 16099MB
[2025-01-18 04:36:13 internimage_t_1k_224] (main.py 575): INFO [Epoch:141] * Acc@1 78.707 Acc@5 94.744
[2025-01-18 04:36:13 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.7%
[2025-01-18 04:36:13 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.76%
[2025-01-18 04:36:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.393 (8.393)	Loss 0.8142 (0.8142)	Acc@1 83.618 (83.618)	Acc@5 97.070 (97.070)	Mem 16099MB
[2025-01-18 04:36:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.115)	Loss 1.1331 (0.9500)	Acc@1 74.854 (80.327)	Acc@5 93.579 (95.379)	Mem 16099MB
[2025-01-18 04:36:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:141] * Acc@1 80.196 Acc@5 95.381
[2025-01-18 04:36:26 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.2%
[2025-01-18 04:36:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:36:27 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:36:27 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.20%
[2025-01-18 04:36:30 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][0/312]	eta 0:13:57 lr 0.002186	time 2.6831 (2.6831)	model_time 0.4672 (0.4672)	loss 2.2825 (2.2825)	grad_norm 2.5344 (2.5344/0.0000)	mem 16099MB
[2025-01-18 04:36:34 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][10/312]	eta 0:03:18 lr 0.002185	time 0.4533 (0.6560)	model_time 0.4528 (0.4542)	loss 3.4194 (3.1634)	grad_norm 0.7391 (2.3580/1.2569)	mem 16099MB
[2025-01-18 04:36:39 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][20/312]	eta 0:02:47 lr 0.002184	time 0.5691 (0.5725)	model_time 0.5689 (0.4667)	loss 2.8291 (3.1184)	grad_norm 2.4944 (2.0256/1.0428)	mem 16099MB
[2025-01-18 04:36:44 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][30/312]	eta 0:02:32 lr 0.002184	time 0.4656 (0.5393)	model_time 0.4651 (0.4674)	loss 3.0991 (3.2231)	grad_norm 1.5517 (1.9069/0.9142)	mem 16099MB
[2025-01-18 04:36:48 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][40/312]	eta 0:02:21 lr 0.002183	time 0.4650 (0.5196)	model_time 0.4649 (0.4652)	loss 3.6155 (3.2288)	grad_norm 1.2658 (1.7766/0.8461)	mem 16099MB
[2025-01-18 04:36:53 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][50/312]	eta 0:02:13 lr 0.002182	time 0.4510 (0.5084)	model_time 0.4508 (0.4646)	loss 3.8764 (3.3132)	grad_norm 1.6034 (1.7329/0.7776)	mem 16099MB
[2025-01-18 04:36:58 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][60/312]	eta 0:02:06 lr 0.002182	time 0.4550 (0.5022)	model_time 0.4548 (0.4655)	loss 3.8241 (3.3237)	grad_norm 1.6107 (1.7383/0.7924)	mem 16099MB
[2025-01-18 04:37:02 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][70/312]	eta 0:02:00 lr 0.002181	time 0.4789 (0.4961)	model_time 0.4787 (0.4646)	loss 3.3584 (3.2979)	grad_norm 3.3909 (1.7804/0.8076)	mem 16099MB
[2025-01-18 04:37:07 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][80/312]	eta 0:01:54 lr 0.002180	time 0.4709 (0.4914)	model_time 0.4707 (0.4637)	loss 3.1854 (3.3209)	grad_norm 1.8904 (1.7611/0.7717)	mem 16099MB
[2025-01-18 04:37:11 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][90/312]	eta 0:01:48 lr 0.002180	time 0.4689 (0.4873)	model_time 0.4687 (0.4626)	loss 3.4341 (3.3176)	grad_norm 1.7947 (1.7220/0.7488)	mem 16099MB
[2025-01-18 04:37:16 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][100/312]	eta 0:01:42 lr 0.002179	time 0.4721 (0.4851)	model_time 0.4720 (0.4629)	loss 3.7578 (3.3135)	grad_norm 2.4591 (1.8281/0.8950)	mem 16099MB
[2025-01-18 04:37:21 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][110/312]	eta 0:01:37 lr 0.002178	time 0.5422 (0.4845)	model_time 0.5420 (0.4642)	loss 2.5978 (3.2844)	grad_norm 1.1373 (1.8029/0.8699)	mem 16099MB
[2025-01-18 04:37:26 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][120/312]	eta 0:01:32 lr 0.002178	time 0.5735 (0.4830)	model_time 0.5730 (0.4644)	loss 2.5947 (3.2645)	grad_norm 1.7123 (1.8003/0.8569)	mem 16099MB
[2025-01-18 04:37:30 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][130/312]	eta 0:01:27 lr 0.002177	time 0.4405 (0.4815)	model_time 0.4403 (0.4643)	loss 2.8753 (3.2652)	grad_norm 3.0505 (1.7958/0.8510)	mem 16099MB
[2025-01-18 04:37:35 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][140/312]	eta 0:01:22 lr 0.002176	time 0.5635 (0.4818)	model_time 0.5634 (0.4657)	loss 3.2205 (3.2545)	grad_norm 1.0722 (1.7763/0.8358)	mem 16099MB
[2025-01-18 04:37:40 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][150/312]	eta 0:01:17 lr 0.002176	time 0.4551 (0.4812)	model_time 0.4549 (0.4662)	loss 3.1662 (3.2380)	grad_norm 0.9709 (1.7477/0.8227)	mem 16099MB
[2025-01-18 04:37:45 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][160/312]	eta 0:01:13 lr 0.002175	time 0.4550 (0.4807)	model_time 0.4546 (0.4666)	loss 3.4481 (3.2460)	grad_norm 3.1296 (1.7645/0.8134)	mem 16099MB
[2025-01-18 04:37:49 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][170/312]	eta 0:01:08 lr 0.002174	time 0.4406 (0.4802)	model_time 0.4404 (0.4669)	loss 2.4854 (3.2424)	grad_norm 3.0451 (1.7784/0.8135)	mem 16099MB
[2025-01-18 04:37:54 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][180/312]	eta 0:01:03 lr 0.002174	time 0.4718 (0.4797)	model_time 0.4716 (0.4671)	loss 2.3566 (3.2347)	grad_norm 1.2764 (1.7896/0.8283)	mem 16099MB
[2025-01-18 04:37:59 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][190/312]	eta 0:00:58 lr 0.002173	time 0.7664 (0.4805)	model_time 0.7662 (0.4685)	loss 3.3899 (3.2438)	grad_norm 1.0178 (1.8075/0.8758)	mem 16099MB
[2025-01-18 04:38:04 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][200/312]	eta 0:00:53 lr 0.002172	time 0.4620 (0.4803)	model_time 0.4616 (0.4689)	loss 2.1904 (3.2380)	grad_norm 0.8868 (1.7808/0.8637)	mem 16099MB
[2025-01-18 04:38:08 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][210/312]	eta 0:00:48 lr 0.002172	time 0.4421 (0.4798)	model_time 0.4417 (0.4689)	loss 3.9726 (3.2325)	grad_norm 1.2955 (1.7529/0.8535)	mem 16099MB
[2025-01-18 04:38:13 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][220/312]	eta 0:00:44 lr 0.002171	time 0.4664 (0.4789)	model_time 0.4662 (0.4685)	loss 2.6118 (3.2254)	grad_norm 1.4480 (1.7498/0.8430)	mem 16099MB
[2025-01-18 04:38:18 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][230/312]	eta 0:00:39 lr 0.002170	time 0.4501 (0.4784)	model_time 0.4499 (0.4684)	loss 3.4374 (3.2166)	grad_norm 1.1771 (1.7522/0.8336)	mem 16099MB
[2025-01-18 04:38:22 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][240/312]	eta 0:00:34 lr 0.002170	time 0.4576 (0.4779)	model_time 0.4572 (0.4683)	loss 3.3709 (3.2295)	grad_norm 0.8065 (1.7633/0.8477)	mem 16099MB
[2025-01-18 04:38:27 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][250/312]	eta 0:00:29 lr 0.002169	time 0.4468 (0.4770)	model_time 0.4463 (0.4678)	loss 2.5599 (3.2279)	grad_norm 1.1477 (1.7482/0.8388)	mem 16099MB
[2025-01-18 04:38:32 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][260/312]	eta 0:00:24 lr 0.002168	time 0.4546 (0.4767)	model_time 0.4544 (0.4678)	loss 2.5251 (3.2247)	grad_norm 1.3608 (1.7535/0.8348)	mem 16099MB
[2025-01-18 04:38:36 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][270/312]	eta 0:00:20 lr 0.002168	time 0.4664 (0.4762)	model_time 0.4659 (0.4677)	loss 3.5079 (3.2267)	grad_norm 2.0207 (1.7762/0.8454)	mem 16099MB
[2025-01-18 04:38:41 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][280/312]	eta 0:00:15 lr 0.002167	time 0.4450 (0.4762)	model_time 0.4446 (0.4680)	loss 4.1437 (3.2303)	grad_norm 1.1438 (1.7736/0.8415)	mem 16099MB
[2025-01-18 04:38:46 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][290/312]	eta 0:00:10 lr 0.002166	time 0.4404 (0.4756)	model_time 0.4400 (0.4676)	loss 3.2113 (3.2341)	grad_norm 2.3429 (1.7715/0.8342)	mem 16099MB
[2025-01-18 04:38:50 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][300/312]	eta 0:00:05 lr 0.002166	time 0.4394 (0.4747)	model_time 0.4393 (0.4670)	loss 3.4735 (3.2376)	grad_norm 1.0797 (1.7647/0.8244)	mem 16099MB
[2025-01-18 04:38:55 internimage_t_1k_224] (main.py 510): INFO Train: [142/300][310/312]	eta 0:00:00 lr 0.002165	time 0.4372 (0.4740)	model_time 0.4371 (0.4666)	loss 3.3224 (3.2419)	grad_norm 1.7148 (1.7442/0.7880)	mem 16099MB
[2025-01-18 04:38:55 internimage_t_1k_224] (main.py 519): INFO EPOCH 142 training takes 0:02:27
[2025-01-18 04:38:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_142.pth saving......
[2025-01-18 04:38:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_142.pth saved !!!
[2025-01-18 04:39:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.281 (7.281)	Loss 0.8224 (0.8224)	Acc@1 82.007 (82.007)	Acc@5 96.387 (96.387)	Mem 16099MB
[2025-01-18 04:39:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.960)	Loss 1.1532 (0.9832)	Acc@1 75.073 (78.955)	Acc@5 93.018 (94.633)	Mem 16099MB
[2025-01-18 04:39:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:142] * Acc@1 78.849 Acc@5 94.700
[2025-01-18 04:39:07 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.8%
[2025-01-18 04:39:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 04:39:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 04:39:08 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 78.85%
[2025-01-18 04:39:16 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.295 (7.295)	Loss 0.8135 (0.8135)	Acc@1 83.691 (83.691)	Acc@5 97.021 (97.021)	Mem 16099MB
[2025-01-18 04:39:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.108 (1.008)	Loss 1.1308 (0.9491)	Acc@1 74.976 (80.351)	Acc@5 93.652 (95.399)	Mem 16099MB
[2025-01-18 04:39:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:142] * Acc@1 80.222 Acc@5 95.401
[2025-01-18 04:39:20 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.2%
[2025-01-18 04:39:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:39:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:39:21 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.22%
[2025-01-18 04:39:24 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][0/312]	eta 0:14:51 lr 0.002165	time 2.8583 (2.8583)	model_time 0.4631 (0.4631)	loss 3.0639 (3.0639)	grad_norm 1.9285 (1.9285/0.0000)	mem 16099MB
[2025-01-18 04:39:28 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][10/312]	eta 0:03:23 lr 0.002164	time 0.4513 (0.6727)	model_time 0.4511 (0.4547)	loss 3.9847 (3.3343)	grad_norm 2.5725 (1.7520/0.4840)	mem 16099MB
[2025-01-18 04:39:33 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][20/312]	eta 0:02:45 lr 0.002164	time 0.4536 (0.5683)	model_time 0.4532 (0.4539)	loss 3.2637 (3.2048)	grad_norm 0.9064 (1.7116/0.5196)	mem 16099MB
[2025-01-18 04:39:38 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][30/312]	eta 0:02:32 lr 0.002163	time 0.4439 (0.5394)	model_time 0.4435 (0.4618)	loss 3.5951 (3.2746)	grad_norm 0.9207 (1.6596/0.5327)	mem 16099MB
[2025-01-18 04:39:42 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][40/312]	eta 0:02:22 lr 0.002162	time 0.4554 (0.5235)	model_time 0.4553 (0.4647)	loss 1.9722 (3.2466)	grad_norm 1.2266 (1.6446/0.5436)	mem 16099MB
[2025-01-18 04:39:47 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][50/312]	eta 0:02:14 lr 0.002162	time 0.4730 (0.5121)	model_time 0.4729 (0.4648)	loss 2.9003 (3.2583)	grad_norm 0.9077 (1.6980/0.6411)	mem 16099MB
[2025-01-18 04:39:52 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][60/312]	eta 0:02:07 lr 0.002161	time 0.4699 (0.5066)	model_time 0.4698 (0.4670)	loss 2.7616 (3.2193)	grad_norm 1.1543 (1.6257/0.6160)	mem 16099MB
[2025-01-18 04:39:57 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][70/312]	eta 0:02:01 lr 0.002160	time 0.4907 (0.5025)	model_time 0.4905 (0.4684)	loss 4.0118 (3.2267)	grad_norm 1.0540 (1.6340/0.6176)	mem 16099MB
[2025-01-18 04:40:01 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][80/312]	eta 0:01:55 lr 0.002160	time 0.4616 (0.4999)	model_time 0.4615 (0.4700)	loss 2.2178 (3.2084)	grad_norm 3.3513 (1.7183/0.7420)	mem 16099MB
[2025-01-18 04:40:06 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][90/312]	eta 0:01:50 lr 0.002159	time 0.4477 (0.4955)	model_time 0.4472 (0.4688)	loss 3.1138 (3.2311)	grad_norm 1.7986 (1.7568/0.7378)	mem 16099MB
[2025-01-18 04:40:11 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][100/312]	eta 0:01:44 lr 0.002158	time 0.4735 (0.4935)	model_time 0.4730 (0.4694)	loss 3.2891 (3.2562)	grad_norm 1.6010 (1.7263/0.7125)	mem 16099MB
[2025-01-18 04:40:15 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][110/312]	eta 0:01:39 lr 0.002158	time 0.4526 (0.4905)	model_time 0.4522 (0.4686)	loss 3.3147 (3.2726)	grad_norm 3.8165 (1.7648/0.7678)	mem 16099MB
[2025-01-18 04:40:20 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][120/312]	eta 0:01:33 lr 0.002157	time 0.4627 (0.4876)	model_time 0.4622 (0.4674)	loss 2.6070 (3.2732)	grad_norm 1.6718 (1.8065/0.8014)	mem 16099MB
[2025-01-18 04:40:25 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][130/312]	eta 0:01:28 lr 0.002156	time 0.4860 (0.4855)	model_time 0.4856 (0.4668)	loss 3.5542 (3.2834)	grad_norm 1.1654 (1.7728/0.7884)	mem 16099MB
[2025-01-18 04:40:30 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][140/312]	eta 0:01:23 lr 0.002156	time 0.4636 (0.4860)	model_time 0.4634 (0.4686)	loss 4.0987 (3.2833)	grad_norm 2.7785 (1.7718/0.7685)	mem 16099MB
[2025-01-18 04:40:34 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][150/312]	eta 0:01:18 lr 0.002155	time 0.4604 (0.4843)	model_time 0.4600 (0.4681)	loss 3.5872 (3.2741)	grad_norm 2.4745 (1.7800/0.7535)	mem 16099MB
[2025-01-18 04:40:39 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][160/312]	eta 0:01:13 lr 0.002154	time 0.5485 (0.4865)	model_time 0.5481 (0.4712)	loss 3.5701 (3.2705)	grad_norm 2.2380 (1.7767/0.7388)	mem 16099MB
[2025-01-18 04:40:44 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][170/312]	eta 0:01:08 lr 0.002154	time 0.4468 (0.4856)	model_time 0.4466 (0.4712)	loss 3.4179 (3.2702)	grad_norm 1.3154 (1.7678/0.7305)	mem 16099MB
[2025-01-18 04:40:49 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][180/312]	eta 0:01:03 lr 0.002153	time 0.4513 (0.4843)	model_time 0.4511 (0.4707)	loss 3.0385 (3.2685)	grad_norm 1.3222 (1.7510/0.7201)	mem 16099MB
[2025-01-18 04:40:53 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][190/312]	eta 0:00:59 lr 0.002152	time 0.4625 (0.4839)	model_time 0.4621 (0.4710)	loss 2.5540 (3.2771)	grad_norm 2.1644 (1.7799/0.7764)	mem 16099MB
[2025-01-18 04:40:58 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][200/312]	eta 0:00:54 lr 0.002152	time 0.4449 (0.4829)	model_time 0.4444 (0.4705)	loss 3.3229 (3.2696)	grad_norm 1.2093 (1.7642/0.7659)	mem 16099MB
[2025-01-18 04:41:03 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][210/312]	eta 0:00:49 lr 0.002151	time 0.4461 (0.4826)	model_time 0.4457 (0.4709)	loss 3.4174 (3.2623)	grad_norm 1.5735 (1.7576/0.7530)	mem 16099MB
[2025-01-18 04:41:07 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][220/312]	eta 0:00:44 lr 0.002150	time 0.4575 (0.4819)	model_time 0.4571 (0.4707)	loss 2.3057 (3.2606)	grad_norm 1.6962 (1.7832/0.7859)	mem 16099MB
[2025-01-18 04:41:12 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][230/312]	eta 0:00:39 lr 0.002150	time 0.4458 (0.4816)	model_time 0.4453 (0.4708)	loss 3.7212 (3.2597)	grad_norm 2.0484 (1.8086/0.7927)	mem 16099MB
[2025-01-18 04:41:17 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][240/312]	eta 0:00:34 lr 0.002149	time 0.4516 (0.4806)	model_time 0.4511 (0.4702)	loss 2.9976 (3.2542)	grad_norm 2.6973 (1.7919/0.7856)	mem 16099MB
[2025-01-18 04:41:21 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][250/312]	eta 0:00:29 lr 0.002148	time 0.4526 (0.4801)	model_time 0.4521 (0.4701)	loss 2.1919 (3.2452)	grad_norm 0.9407 (1.7990/0.7794)	mem 16099MB
[2025-01-18 04:41:26 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][260/312]	eta 0:00:24 lr 0.002148	time 0.5575 (0.4802)	model_time 0.5571 (0.4707)	loss 3.2494 (3.2438)	grad_norm 3.0186 (1.7899/0.7750)	mem 16099MB
[2025-01-18 04:41:31 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][270/312]	eta 0:00:20 lr 0.002147	time 0.4588 (0.4803)	model_time 0.4584 (0.4710)	loss 2.9652 (3.2470)	grad_norm 1.7720 (1.8043/0.7824)	mem 16099MB
[2025-01-18 04:41:36 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][280/312]	eta 0:00:15 lr 0.002146	time 0.4423 (0.4798)	model_time 0.4418 (0.4708)	loss 2.1652 (3.2474)	grad_norm 1.6859 (1.7902/0.7794)	mem 16099MB
[2025-01-18 04:41:41 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][290/312]	eta 0:00:10 lr 0.002146	time 0.4418 (0.4797)	model_time 0.4416 (0.4710)	loss 3.0016 (3.2449)	grad_norm 1.4027 (1.7712/0.7746)	mem 16099MB
[2025-01-18 04:41:45 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][300/312]	eta 0:00:05 lr 0.002145	time 0.4379 (0.4790)	model_time 0.4377 (0.4706)	loss 3.7733 (3.2460)	grad_norm 3.6445 (1.7787/0.7763)	mem 16099MB
[2025-01-18 04:41:50 internimage_t_1k_224] (main.py 510): INFO Train: [143/300][310/312]	eta 0:00:00 lr 0.002144	time 0.4407 (0.4781)	model_time 0.4406 (0.4700)	loss 2.6502 (3.2450)	grad_norm 0.8162 (1.7932/0.8196)	mem 16099MB
[2025-01-18 04:41:50 internimage_t_1k_224] (main.py 519): INFO EPOCH 143 training takes 0:02:29
[2025-01-18 04:41:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_143.pth saving......
[2025-01-18 04:41:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_143.pth saved !!!
[2025-01-18 04:41:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 6.979 (6.979)	Loss 0.7901 (0.7901)	Acc@1 82.495 (82.495)	Acc@5 96.436 (96.436)	Mem 16099MB
[2025-01-18 04:42:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.952)	Loss 1.1318 (0.9622)	Acc@1 75.000 (79.215)	Acc@5 93.091 (94.829)	Mem 16099MB
[2025-01-18 04:42:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:143] * Acc@1 79.189 Acc@5 94.884
[2025-01-18 04:42:02 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.2%
[2025-01-18 04:42:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 04:42:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 04:42:03 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.19%
[2025-01-18 04:42:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.182 (7.182)	Loss 0.8128 (0.8128)	Acc@1 83.765 (83.765)	Acc@5 97.070 (97.070)	Mem 16099MB
[2025-01-18 04:42:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.969)	Loss 1.1286 (0.9480)	Acc@1 75.073 (80.418)	Acc@5 93.677 (95.423)	Mem 16099MB
[2025-01-18 04:42:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:143] * Acc@1 80.290 Acc@5 95.431
[2025-01-18 04:42:14 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.3%
[2025-01-18 04:42:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:42:16 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:42:16 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.29%
[2025-01-18 04:42:18 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][0/312]	eta 0:14:40 lr 0.002144	time 2.8236 (2.8236)	model_time 0.4657 (0.4657)	loss 3.2705 (3.2705)	grad_norm 2.6354 (2.6354/0.0000)	mem 16099MB
[2025-01-18 04:42:23 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][10/312]	eta 0:03:24 lr 0.002144	time 0.4600 (0.6761)	model_time 0.4596 (0.4614)	loss 4.0060 (3.2758)	grad_norm 2.3045 (1.9774/0.4923)	mem 16099MB
[2025-01-18 04:42:28 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][20/312]	eta 0:02:46 lr 0.002143	time 0.4618 (0.5703)	model_time 0.4614 (0.4576)	loss 3.8117 (3.3482)	grad_norm 1.4801 (1.7533/0.5000)	mem 16099MB
[2025-01-18 04:42:32 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][30/312]	eta 0:02:31 lr 0.002142	time 0.4561 (0.5370)	model_time 0.4559 (0.4606)	loss 3.0838 (3.3485)	grad_norm 0.9095 (1.7348/0.5459)	mem 16099MB
[2025-01-18 04:42:37 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][40/312]	eta 0:02:21 lr 0.002142	time 0.4634 (0.5190)	model_time 0.4630 (0.4611)	loss 3.3592 (3.3092)	grad_norm 3.7828 (1.7121/0.6129)	mem 16099MB
[2025-01-18 04:42:41 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][50/312]	eta 0:02:13 lr 0.002141	time 0.4586 (0.5087)	model_time 0.4584 (0.4621)	loss 3.0321 (3.2765)	grad_norm 2.7557 (1.8653/0.7043)	mem 16099MB
[2025-01-18 04:42:46 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][60/312]	eta 0:02:06 lr 0.002140	time 0.4456 (0.5024)	model_time 0.4454 (0.4634)	loss 3.4334 (3.2485)	grad_norm 1.6335 (1.8238/0.7040)	mem 16099MB
[2025-01-18 04:42:51 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][70/312]	eta 0:02:00 lr 0.002140	time 0.4817 (0.4965)	model_time 0.4816 (0.4629)	loss 4.2198 (3.2687)	grad_norm 2.0535 (1.8247/0.6988)	mem 16099MB
[2025-01-18 04:42:56 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][80/312]	eta 0:01:54 lr 0.002139	time 0.5546 (0.4940)	model_time 0.5544 (0.4645)	loss 3.8438 (3.2960)	grad_norm 1.2022 (1.7766/0.7163)	mem 16099MB
[2025-01-18 04:43:00 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][90/312]	eta 0:01:49 lr 0.002138	time 0.4525 (0.4913)	model_time 0.4523 (0.4651)	loss 2.6217 (3.2800)	grad_norm 1.4629 (1.7571/0.7146)	mem 16099MB
[2025-01-18 04:43:05 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][100/312]	eta 0:01:43 lr 0.002138	time 0.4651 (0.4885)	model_time 0.4647 (0.4648)	loss 3.5180 (3.2791)	grad_norm 1.0517 (1.7368/0.6961)	mem 16099MB
[2025-01-18 04:43:10 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][110/312]	eta 0:01:38 lr 0.002137	time 0.4510 (0.4861)	model_time 0.4505 (0.4645)	loss 3.6627 (3.2846)	grad_norm 2.1221 (1.8068/0.7909)	mem 16099MB
[2025-01-18 04:43:14 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][120/312]	eta 0:01:32 lr 0.002136	time 0.4409 (0.4838)	model_time 0.4407 (0.4640)	loss 3.7948 (3.2796)	grad_norm 1.7376 (1.8182/0.7804)	mem 16099MB
[2025-01-18 04:43:19 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][130/312]	eta 0:01:27 lr 0.002136	time 0.5530 (0.4825)	model_time 0.5528 (0.4641)	loss 3.1677 (3.2634)	grad_norm 2.9431 (1.8533/0.8067)	mem 16099MB
[2025-01-18 04:43:23 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][140/312]	eta 0:01:22 lr 0.002135	time 0.4791 (0.4813)	model_time 0.4789 (0.4642)	loss 2.8950 (3.2700)	grad_norm 0.8866 (1.8941/0.8588)	mem 16099MB
[2025-01-18 04:43:28 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][150/312]	eta 0:01:17 lr 0.002134	time 0.4557 (0.4795)	model_time 0.4555 (0.4635)	loss 3.7050 (3.2889)	grad_norm 2.2259 (1.9296/0.8769)	mem 16099MB
[2025-01-18 04:43:33 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][160/312]	eta 0:01:12 lr 0.002134	time 0.5719 (0.4797)	model_time 0.5714 (0.4647)	loss 3.2658 (3.3014)	grad_norm 1.6055 (1.9001/0.8735)	mem 16099MB
[2025-01-18 04:43:37 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][170/312]	eta 0:01:07 lr 0.002133	time 0.4422 (0.4786)	model_time 0.4420 (0.4644)	loss 4.1988 (3.3120)	grad_norm 0.9869 (1.8604/0.8640)	mem 16099MB
[2025-01-18 04:43:42 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][180/312]	eta 0:01:03 lr 0.002132	time 0.4661 (0.4786)	model_time 0.4659 (0.4652)	loss 3.7481 (3.3106)	grad_norm 1.4205 (1.8266/0.8540)	mem 16099MB
[2025-01-18 04:43:47 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][190/312]	eta 0:00:58 lr 0.002132	time 0.4474 (0.4783)	model_time 0.4470 (0.4655)	loss 3.2875 (3.3074)	grad_norm 1.9606 (1.8113/0.8396)	mem 16099MB
[2025-01-18 04:43:51 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][200/312]	eta 0:00:53 lr 0.002131	time 0.4473 (0.4773)	model_time 0.4469 (0.4652)	loss 3.4557 (3.2992)	grad_norm 3.1788 (1.8194/0.8332)	mem 16099MB
[2025-01-18 04:43:56 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][210/312]	eta 0:00:48 lr 0.002130	time 0.4534 (0.4778)	model_time 0.4532 (0.4662)	loss 2.4327 (3.3023)	grad_norm 3.6840 (1.8212/0.8344)	mem 16099MB
[2025-01-18 04:44:01 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][220/312]	eta 0:00:43 lr 0.002130	time 0.4519 (0.4772)	model_time 0.4517 (0.4661)	loss 3.7097 (3.3106)	grad_norm 2.8574 (1.8201/0.8280)	mem 16099MB
[2025-01-18 04:44:06 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][230/312]	eta 0:00:39 lr 0.002129	time 0.4491 (0.4781)	model_time 0.4487 (0.4676)	loss 2.2262 (3.2997)	grad_norm 2.0262 (1.8391/0.8316)	mem 16099MB
[2025-01-18 04:44:11 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][240/312]	eta 0:00:34 lr 0.002128	time 0.4498 (0.4772)	model_time 0.4496 (0.4670)	loss 2.8151 (3.2966)	grad_norm 1.9342 (1.8429/0.8233)	mem 16099MB
[2025-01-18 04:44:15 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][250/312]	eta 0:00:29 lr 0.002128	time 0.4487 (0.4768)	model_time 0.4483 (0.4670)	loss 3.4699 (3.3020)	grad_norm 0.9498 (1.8252/0.8217)	mem 16099MB
[2025-01-18 04:44:20 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][260/312]	eta 0:00:24 lr 0.002127	time 0.4551 (0.4761)	model_time 0.4550 (0.4667)	loss 3.1937 (3.3037)	grad_norm 0.9176 (1.8094/0.8147)	mem 16099MB
[2025-01-18 04:44:24 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][270/312]	eta 0:00:19 lr 0.002126	time 0.4565 (0.4753)	model_time 0.4560 (0.4662)	loss 3.3069 (3.2940)	grad_norm 0.9489 (1.8041/0.8067)	mem 16099MB
[2025-01-18 04:44:29 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][280/312]	eta 0:00:15 lr 0.002126	time 0.4402 (0.4745)	model_time 0.4400 (0.4657)	loss 3.1277 (3.2944)	grad_norm 4.2711 (1.8182/0.8198)	mem 16099MB
[2025-01-18 04:44:34 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][290/312]	eta 0:00:10 lr 0.002125	time 0.4477 (0.4751)	model_time 0.4475 (0.4666)	loss 4.0289 (3.2914)	grad_norm 1.0058 (1.8175/0.8343)	mem 16099MB
[2025-01-18 04:44:38 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][300/312]	eta 0:00:05 lr 0.002124	time 0.4392 (0.4746)	model_time 0.4391 (0.4664)	loss 3.1544 (3.2901)	grad_norm 2.1254 (1.7998/0.8287)	mem 16099MB
[2025-01-18 04:44:43 internimage_t_1k_224] (main.py 510): INFO Train: [144/300][310/312]	eta 0:00:00 lr 0.002124	time 0.4398 (0.4735)	model_time 0.4397 (0.4656)	loss 3.5258 (3.2915)	grad_norm 1.3892 (1.7920/0.8372)	mem 16099MB
[2025-01-18 04:44:43 internimage_t_1k_224] (main.py 519): INFO EPOCH 144 training takes 0:02:27
[2025-01-18 04:44:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_144.pth saving......
[2025-01-18 04:44:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_144.pth saved !!!
[2025-01-18 04:44:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.404 (7.404)	Loss 0.8670 (0.8670)	Acc@1 82.056 (82.056)	Acc@5 96.118 (96.118)	Mem 16099MB
[2025-01-18 04:44:56 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.002)	Loss 1.1887 (1.0059)	Acc@1 73.999 (79.204)	Acc@5 93.042 (94.806)	Mem 16099MB
[2025-01-18 04:44:56 internimage_t_1k_224] (main.py 575): INFO [Epoch:144] * Acc@1 79.067 Acc@5 94.848
[2025-01-18 04:44:56 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.1%
[2025-01-18 04:44:56 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.19%
[2025-01-18 04:45:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.092 (8.092)	Loss 0.8124 (0.8124)	Acc@1 83.765 (83.765)	Acc@5 97.070 (97.070)	Mem 16099MB
[2025-01-18 04:45:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.098)	Loss 1.1263 (0.9473)	Acc@1 75.122 (80.480)	Acc@5 93.701 (95.441)	Mem 16099MB
[2025-01-18 04:45:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:144] * Acc@1 80.348 Acc@5 95.455
[2025-01-18 04:45:08 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.3%
[2025-01-18 04:45:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:45:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:45:09 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.35%
[2025-01-18 04:45:12 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][0/312]	eta 0:13:54 lr 0.002124	time 2.6745 (2.6745)	model_time 0.4705 (0.4705)	loss 2.3854 (2.3854)	grad_norm 1.4579 (1.4579/0.0000)	mem 16099MB
[2025-01-18 04:45:17 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][10/312]	eta 0:03:26 lr 0.002123	time 0.6819 (0.6844)	model_time 0.6817 (0.4837)	loss 2.4270 (2.8631)	grad_norm 2.3183 (1.5189/0.4851)	mem 16099MB
[2025-01-18 04:45:22 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][20/312]	eta 0:02:50 lr 0.002122	time 0.4653 (0.5831)	model_time 0.4651 (0.4778)	loss 2.4455 (3.0951)	grad_norm 1.4216 (1.9961/1.0673)	mem 16099MB
[2025-01-18 04:45:26 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][30/312]	eta 0:02:32 lr 0.002122	time 0.4592 (0.5422)	model_time 0.4588 (0.4708)	loss 3.3700 (3.1982)	grad_norm 2.4503 (2.1204/1.0346)	mem 16099MB
[2025-01-18 04:45:31 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][40/312]	eta 0:02:22 lr 0.002121	time 0.4695 (0.5222)	model_time 0.4693 (0.4681)	loss 3.6523 (3.2058)	grad_norm 1.6555 (1.9491/0.9751)	mem 16099MB
[2025-01-18 04:45:35 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][50/312]	eta 0:02:13 lr 0.002120	time 0.4504 (0.5107)	model_time 0.4499 (0.4671)	loss 3.4497 (3.2429)	grad_norm 2.3972 (1.8684/0.9103)	mem 16099MB
[2025-01-18 04:45:40 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][60/312]	eta 0:02:06 lr 0.002120	time 0.4754 (0.5023)	model_time 0.4752 (0.4658)	loss 3.6550 (3.2923)	grad_norm 2.9380 (1.8131/0.8672)	mem 16099MB
[2025-01-18 04:45:45 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][70/312]	eta 0:02:00 lr 0.002119	time 0.4515 (0.4966)	model_time 0.4511 (0.4652)	loss 3.4012 (3.3194)	grad_norm 3.1358 (1.8622/0.8474)	mem 16099MB
[2025-01-18 04:45:49 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][80/312]	eta 0:01:54 lr 0.002118	time 0.4493 (0.4940)	model_time 0.4491 (0.4664)	loss 2.5770 (3.3061)	grad_norm 1.3406 (1.8155/0.8342)	mem 16099MB
[2025-01-18 04:45:54 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][90/312]	eta 0:01:48 lr 0.002118	time 0.4710 (0.4899)	model_time 0.4708 (0.4653)	loss 3.5374 (3.2669)	grad_norm 1.1083 (1.8311/0.8406)	mem 16099MB
[2025-01-18 04:45:59 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][100/312]	eta 0:01:43 lr 0.002117	time 0.5291 (0.4893)	model_time 0.5289 (0.4671)	loss 3.3939 (3.2632)	grad_norm 2.2903 (1.8465/0.8434)	mem 16099MB
[2025-01-18 04:46:03 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][110/312]	eta 0:01:38 lr 0.002116	time 0.4545 (0.4871)	model_time 0.4541 (0.4669)	loss 2.3082 (3.2508)	grad_norm 1.9249 (1.7902/0.8317)	mem 16099MB
[2025-01-18 04:46:08 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][120/312]	eta 0:01:33 lr 0.002116	time 0.5027 (0.4871)	model_time 0.5026 (0.4685)	loss 3.7563 (3.2426)	grad_norm 0.9257 (1.7658/0.8142)	mem 16099MB
[2025-01-18 04:46:13 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][130/312]	eta 0:01:28 lr 0.002115	time 0.5330 (0.4867)	model_time 0.5329 (0.4695)	loss 4.0236 (3.2412)	grad_norm 1.1216 (1.7449/0.8013)	mem 16099MB
[2025-01-18 04:46:18 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][140/312]	eta 0:01:23 lr 0.002114	time 0.4535 (0.4864)	model_time 0.4534 (0.4704)	loss 2.6457 (3.2065)	grad_norm 1.4167 (1.7642/0.8080)	mem 16099MB
[2025-01-18 04:46:23 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][150/312]	eta 0:01:18 lr 0.002114	time 0.4797 (0.4850)	model_time 0.4795 (0.4701)	loss 2.7004 (3.2376)	grad_norm 1.3160 (1.7453/0.7899)	mem 16099MB
[2025-01-18 04:46:28 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][160/312]	eta 0:01:13 lr 0.002113	time 0.4506 (0.4867)	model_time 0.4504 (0.4726)	loss 3.6634 (3.2501)	grad_norm 0.7725 (1.7374/0.7779)	mem 16099MB
[2025-01-18 04:46:33 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][170/312]	eta 0:01:09 lr 0.002112	time 0.4660 (0.4860)	model_time 0.4659 (0.4727)	loss 3.2399 (3.2451)	grad_norm 1.1438 (1.7455/0.7794)	mem 16099MB
[2025-01-18 04:46:37 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][180/312]	eta 0:01:04 lr 0.002112	time 0.4479 (0.4850)	model_time 0.4478 (0.4724)	loss 2.6563 (3.2511)	grad_norm 1.1397 (1.7354/0.7661)	mem 16099MB
[2025-01-18 04:46:42 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][190/312]	eta 0:00:59 lr 0.002111	time 0.4550 (0.4836)	model_time 0.4545 (0.4717)	loss 3.5567 (3.2561)	grad_norm 6.4507 (1.7688/0.8269)	mem 16099MB
[2025-01-18 04:46:46 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][200/312]	eta 0:00:54 lr 0.002110	time 0.4521 (0.4823)	model_time 0.4516 (0.4710)	loss 3.0207 (3.2520)	grad_norm 1.2846 (1.7714/0.8265)	mem 16099MB
[2025-01-18 04:46:51 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][210/312]	eta 0:00:49 lr 0.002110	time 0.4594 (0.4814)	model_time 0.4589 (0.4706)	loss 2.8083 (3.2474)	grad_norm 1.4402 (1.7779/0.8231)	mem 16099MB
[2025-01-18 04:46:56 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][220/312]	eta 0:00:44 lr 0.002109	time 0.4541 (0.4807)	model_time 0.4536 (0.4703)	loss 3.0118 (3.2464)	grad_norm 2.2681 (1.7842/0.8167)	mem 16099MB
[2025-01-18 04:47:00 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][230/312]	eta 0:00:39 lr 0.002108	time 0.4454 (0.4796)	model_time 0.4452 (0.4697)	loss 2.8101 (3.2450)	grad_norm 1.4272 (1.7700/0.8103)	mem 16099MB
[2025-01-18 04:47:05 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][240/312]	eta 0:00:34 lr 0.002108	time 0.4511 (0.4801)	model_time 0.4507 (0.4706)	loss 3.4580 (3.2513)	grad_norm 1.3916 (1.7560/0.8001)	mem 16099MB
[2025-01-18 04:47:10 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][250/312]	eta 0:00:29 lr 0.002107	time 0.4485 (0.4796)	model_time 0.4480 (0.4704)	loss 2.0509 (3.2591)	grad_norm 1.0160 (1.7427/0.7927)	mem 16099MB
[2025-01-18 04:47:14 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][260/312]	eta 0:00:24 lr 0.002106	time 0.4708 (0.4789)	model_time 0.4706 (0.4700)	loss 3.7946 (3.2510)	grad_norm 0.8896 (1.7408/0.7841)	mem 16099MB
[2025-01-18 04:47:19 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][270/312]	eta 0:00:20 lr 0.002106	time 0.4433 (0.4784)	model_time 0.4428 (0.4699)	loss 2.6451 (3.2498)	grad_norm 1.6915 (1.7394/0.7717)	mem 16099MB
[2025-01-18 04:47:24 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][280/312]	eta 0:00:15 lr 0.002105	time 0.4480 (0.4780)	model_time 0.4478 (0.4697)	loss 2.8462 (3.2465)	grad_norm 3.0615 (1.7743/0.8152)	mem 16099MB
[2025-01-18 04:47:28 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][290/312]	eta 0:00:10 lr 0.002104	time 0.5509 (0.4774)	model_time 0.5505 (0.4694)	loss 3.3587 (3.2384)	grad_norm 2.0802 (1.7958/0.8387)	mem 16099MB
[2025-01-18 04:47:33 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][300/312]	eta 0:00:05 lr 0.002104	time 0.4407 (0.4770)	model_time 0.4406 (0.4693)	loss 2.8198 (3.2250)	grad_norm 1.4864 (1.7981/0.8325)	mem 16099MB
[2025-01-18 04:47:37 internimage_t_1k_224] (main.py 510): INFO Train: [145/300][310/312]	eta 0:00:00 lr 0.002103	time 0.4428 (0.4762)	model_time 0.4427 (0.4687)	loss 2.3712 (3.2315)	grad_norm 1.4833 (1.8067/0.8357)	mem 16099MB
[2025-01-18 04:47:38 internimage_t_1k_224] (main.py 519): INFO EPOCH 145 training takes 0:02:28
[2025-01-18 04:47:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_145.pth saving......
[2025-01-18 04:47:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_145.pth saved !!!
[2025-01-18 04:47:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.367 (7.367)	Loss 0.8161 (0.8161)	Acc@1 82.129 (82.129)	Acc@5 96.777 (96.777)	Mem 16099MB
[2025-01-18 04:47:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.990)	Loss 1.1542 (0.9664)	Acc@1 73.682 (79.024)	Acc@5 93.408 (94.858)	Mem 16099MB
[2025-01-18 04:47:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:145] * Acc@1 78.971 Acc@5 94.940
[2025-01-18 04:47:50 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.0%
[2025-01-18 04:47:50 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.19%
[2025-01-18 04:47:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.061 (8.061)	Loss 0.8121 (0.8121)	Acc@1 83.765 (83.765)	Acc@5 97.095 (97.095)	Mem 16099MB
[2025-01-18 04:48:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.079)	Loss 1.1245 (0.9466)	Acc@1 75.195 (80.522)	Acc@5 93.750 (95.437)	Mem 16099MB
[2025-01-18 04:48:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:145] * Acc@1 80.392 Acc@5 95.451
[2025-01-18 04:48:02 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.4%
[2025-01-18 04:48:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:48:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:48:04 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.39%
[2025-01-18 04:48:06 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][0/312]	eta 0:15:15 lr 0.002103	time 2.9333 (2.9333)	model_time 0.4693 (0.4693)	loss 3.9110 (3.9110)	grad_norm 1.2248 (1.2248/0.0000)	mem 16099MB
[2025-01-18 04:48:11 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][10/312]	eta 0:03:28 lr 0.002102	time 0.4540 (0.6901)	model_time 0.4538 (0.4658)	loss 3.5393 (3.3071)	grad_norm 2.8317 (1.6973/0.7704)	mem 16099MB
[2025-01-18 04:48:16 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][20/312]	eta 0:02:49 lr 0.002102	time 0.5274 (0.5818)	model_time 0.5270 (0.4642)	loss 2.4503 (3.0880)	grad_norm 1.2058 (1.5925/0.7355)	mem 16099MB
[2025-01-18 04:48:20 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][30/312]	eta 0:02:33 lr 0.002101	time 0.4578 (0.5437)	model_time 0.4573 (0.4639)	loss 3.4487 (3.1207)	grad_norm 0.9791 (1.5775/0.6699)	mem 16099MB
[2025-01-18 04:48:25 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][40/312]	eta 0:02:21 lr 0.002100	time 0.4521 (0.5219)	model_time 0.4519 (0.4615)	loss 3.7397 (3.1787)	grad_norm 1.8720 (1.7857/0.8044)	mem 16099MB
[2025-01-18 04:48:30 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][50/312]	eta 0:02:14 lr 0.002100	time 0.4450 (0.5121)	model_time 0.4446 (0.4634)	loss 4.1090 (3.1762)	grad_norm 1.5383 (1.8413/0.7872)	mem 16099MB
[2025-01-18 04:48:34 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][60/312]	eta 0:02:07 lr 0.002099	time 0.4452 (0.5063)	model_time 0.4448 (0.4655)	loss 3.5498 (3.1991)	grad_norm 1.5975 (1.7597/0.7562)	mem 16099MB
[2025-01-18 04:48:39 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][70/312]	eta 0:02:00 lr 0.002098	time 0.4646 (0.4998)	model_time 0.4642 (0.4647)	loss 3.1751 (3.1956)	grad_norm 0.9755 (1.7848/0.7574)	mem 16099MB
[2025-01-18 04:48:44 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][80/312]	eta 0:01:55 lr 0.002098	time 0.4465 (0.4961)	model_time 0.4464 (0.4653)	loss 2.7891 (3.1901)	grad_norm 3.0357 (1.8255/0.7865)	mem 16099MB
[2025-01-18 04:48:48 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][90/312]	eta 0:01:49 lr 0.002097	time 0.4763 (0.4921)	model_time 0.4759 (0.4646)	loss 3.3566 (3.1828)	grad_norm 1.4274 (1.7703/0.7721)	mem 16099MB
[2025-01-18 04:48:53 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][100/312]	eta 0:01:43 lr 0.002096	time 0.4681 (0.4905)	model_time 0.4677 (0.4657)	loss 2.9165 (3.1540)	grad_norm 1.3706 (1.7396/0.7468)	mem 16099MB
[2025-01-18 04:48:58 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][110/312]	eta 0:01:38 lr 0.002096	time 0.4623 (0.4896)	model_time 0.4621 (0.4670)	loss 3.9022 (3.1687)	grad_norm 1.1825 (1.7239/0.7333)	mem 16099MB
[2025-01-18 04:49:03 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][120/312]	eta 0:01:33 lr 0.002095	time 0.4541 (0.4874)	model_time 0.4540 (0.4667)	loss 3.8860 (3.1977)	grad_norm 0.9317 (1.7455/0.7562)	mem 16099MB
[2025-01-18 04:49:07 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][130/312]	eta 0:01:28 lr 0.002094	time 0.4682 (0.4848)	model_time 0.4678 (0.4656)	loss 3.2283 (3.2034)	grad_norm 1.5197 (1.7370/0.7520)	mem 16099MB
[2025-01-18 04:49:12 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][140/312]	eta 0:01:23 lr 0.002094	time 0.5453 (0.4857)	model_time 0.5449 (0.4678)	loss 3.5731 (3.2070)	grad_norm 1.4283 (1.7512/0.7739)	mem 16099MB
[2025-01-18 04:49:17 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][150/312]	eta 0:01:18 lr 0.002093	time 0.4472 (0.4844)	model_time 0.4467 (0.4677)	loss 3.5978 (3.2295)	grad_norm 2.6729 (1.7465/0.7629)	mem 16099MB
[2025-01-18 04:49:21 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][160/312]	eta 0:01:13 lr 0.002092	time 0.5002 (0.4832)	model_time 0.4997 (0.4674)	loss 3.2337 (3.2113)	grad_norm 1.7929 (1.7455/0.7501)	mem 16099MB
[2025-01-18 04:49:26 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][170/312]	eta 0:01:08 lr 0.002092	time 0.4462 (0.4823)	model_time 0.4460 (0.4675)	loss 4.2483 (3.2322)	grad_norm 1.1050 (1.7223/0.7383)	mem 16099MB
[2025-01-18 04:49:31 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][180/312]	eta 0:01:03 lr 0.002091	time 0.4539 (0.4815)	model_time 0.4534 (0.4675)	loss 2.8560 (3.2301)	grad_norm 1.5323 (1.7178/0.7380)	mem 16099MB
[2025-01-18 04:49:35 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][190/312]	eta 0:00:58 lr 0.002090	time 0.4411 (0.4802)	model_time 0.4409 (0.4669)	loss 2.3545 (3.2280)	grad_norm 1.0462 (1.7012/0.7272)	mem 16099MB
[2025-01-18 04:49:40 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][200/312]	eta 0:00:53 lr 0.002090	time 0.4775 (0.4792)	model_time 0.4771 (0.4665)	loss 3.4042 (3.2191)	grad_norm 1.7009 (1.7348/0.7653)	mem 16099MB
[2025-01-18 04:49:44 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][210/312]	eta 0:00:48 lr 0.002089	time 0.4805 (0.4782)	model_time 0.4800 (0.4661)	loss 3.0127 (3.2199)	grad_norm 2.4564 (1.7579/0.8015)	mem 16099MB
[2025-01-18 04:49:49 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][220/312]	eta 0:00:43 lr 0.002088	time 0.4432 (0.4774)	model_time 0.4431 (0.4659)	loss 3.7205 (3.2237)	grad_norm 2.4126 (1.7606/0.7924)	mem 16099MB
[2025-01-18 04:49:54 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][230/312]	eta 0:00:39 lr 0.002088	time 0.4420 (0.4768)	model_time 0.4419 (0.4657)	loss 3.3858 (3.2274)	grad_norm 3.6066 (1.7879/0.7937)	mem 16099MB
[2025-01-18 04:49:58 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][240/312]	eta 0:00:34 lr 0.002087	time 0.4519 (0.4763)	model_time 0.4514 (0.4657)	loss 2.4852 (3.2237)	grad_norm 1.0879 (1.7681/0.7876)	mem 16099MB
[2025-01-18 04:50:03 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][250/312]	eta 0:00:29 lr 0.002086	time 0.5566 (0.4763)	model_time 0.5565 (0.4661)	loss 3.4119 (3.2201)	grad_norm 1.2045 (1.7554/0.7788)	mem 16099MB
[2025-01-18 04:50:08 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][260/312]	eta 0:00:24 lr 0.002086	time 0.4507 (0.4755)	model_time 0.4505 (0.4656)	loss 2.9457 (3.2125)	grad_norm 1.3105 (1.7378/0.7754)	mem 16099MB
[2025-01-18 04:50:12 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][270/312]	eta 0:00:19 lr 0.002085	time 0.4477 (0.4757)	model_time 0.4472 (0.4662)	loss 4.0334 (3.2147)	grad_norm 2.1008 (1.7627/0.8031)	mem 16099MB
[2025-01-18 04:50:17 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][280/312]	eta 0:00:15 lr 0.002084	time 0.4430 (0.4754)	model_time 0.4428 (0.4663)	loss 3.5072 (3.2181)	grad_norm 2.5232 (1.7693/0.7983)	mem 16099MB
[2025-01-18 04:50:22 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][290/312]	eta 0:00:10 lr 0.002084	time 0.4473 (0.4750)	model_time 0.4471 (0.4661)	loss 2.8896 (3.2157)	grad_norm 1.3511 (1.7619/0.7937)	mem 16099MB
[2025-01-18 04:50:26 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][300/312]	eta 0:00:05 lr 0.002083	time 0.4432 (0.4744)	model_time 0.4431 (0.4658)	loss 3.2438 (3.2186)	grad_norm 4.7115 (1.7748/0.8105)	mem 16099MB
[2025-01-18 04:50:31 internimage_t_1k_224] (main.py 510): INFO Train: [146/300][310/312]	eta 0:00:00 lr 0.002082	time 0.4498 (0.4738)	model_time 0.4497 (0.4655)	loss 3.3035 (3.2102)	grad_norm 1.0529 (1.7782/0.8072)	mem 16099MB
[2025-01-18 04:50:31 internimage_t_1k_224] (main.py 519): INFO EPOCH 146 training takes 0:02:27
[2025-01-18 04:50:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_146.pth saving......
[2025-01-18 04:50:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_146.pth saved !!!
[2025-01-18 04:50:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.291 (7.291)	Loss 0.8234 (0.8234)	Acc@1 82.349 (82.349)	Acc@5 96.777 (96.777)	Mem 16099MB
[2025-01-18 04:50:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.015)	Loss 1.1530 (0.9822)	Acc@1 75.293 (79.239)	Acc@5 92.920 (94.735)	Mem 16099MB
[2025-01-18 04:50:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:146] * Acc@1 79.109 Acc@5 94.784
[2025-01-18 04:50:44 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.1%
[2025-01-18 04:50:44 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.19%
[2025-01-18 04:50:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.160 (8.160)	Loss 0.8118 (0.8118)	Acc@1 83.789 (83.789)	Acc@5 97.095 (97.095)	Mem 16099MB
[2025-01-18 04:50:56 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.095)	Loss 1.1228 (0.9460)	Acc@1 75.244 (80.546)	Acc@5 93.799 (95.463)	Mem 16099MB
[2025-01-18 04:50:56 internimage_t_1k_224] (main.py 575): INFO [Epoch:146] * Acc@1 80.424 Acc@5 95.481
[2025-01-18 04:50:56 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.4%
[2025-01-18 04:50:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:50:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:50:57 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.42%
[2025-01-18 04:51:00 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][0/312]	eta 0:12:52 lr 0.002082	time 2.4775 (2.4775)	model_time 0.4807 (0.4807)	loss 2.6146 (2.6146)	grad_norm 3.1704 (3.1704/0.0000)	mem 16099MB
[2025-01-18 04:51:05 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][10/312]	eta 0:03:19 lr 0.002082	time 0.4816 (0.6608)	model_time 0.4814 (0.4788)	loss 3.4191 (2.9116)	grad_norm 1.0817 (2.3705/1.2363)	mem 16099MB
[2025-01-18 04:51:09 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][20/312]	eta 0:02:46 lr 0.002081	time 0.4548 (0.5686)	model_time 0.4546 (0.4732)	loss 3.4447 (3.0745)	grad_norm 1.3798 (2.3117/1.0735)	mem 16099MB
[2025-01-18 04:51:14 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][30/312]	eta 0:02:31 lr 0.002080	time 0.4516 (0.5363)	model_time 0.4514 (0.4715)	loss 3.4267 (3.1025)	grad_norm 2.3107 (2.1409/0.9620)	mem 16099MB
[2025-01-18 04:51:19 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][40/312]	eta 0:02:21 lr 0.002080	time 0.4647 (0.5217)	model_time 0.4642 (0.4726)	loss 3.3976 (3.0977)	grad_norm 1.7305 (2.0285/0.9182)	mem 16099MB
[2025-01-18 04:51:24 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][50/312]	eta 0:02:13 lr 0.002079	time 0.4398 (0.5106)	model_time 0.4396 (0.4710)	loss 3.2760 (3.0855)	grad_norm 1.4392 (1.9442/0.8729)	mem 16099MB
[2025-01-18 04:51:28 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][60/312]	eta 0:02:06 lr 0.002078	time 0.4519 (0.5023)	model_time 0.4513 (0.4692)	loss 2.1834 (3.1341)	grad_norm 0.7687 (1.8803/0.8596)	mem 16099MB
[2025-01-18 04:51:33 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][70/312]	eta 0:02:00 lr 0.002078	time 0.4521 (0.4969)	model_time 0.4520 (0.4684)	loss 3.5256 (3.1664)	grad_norm 1.1505 (1.8109/0.8272)	mem 16099MB
[2025-01-18 04:51:37 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][80/312]	eta 0:01:54 lr 0.002077	time 0.4517 (0.4932)	model_time 0.4513 (0.4681)	loss 3.5475 (3.1955)	grad_norm 1.6490 (1.8830/0.8781)	mem 16099MB
[2025-01-18 04:51:42 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][90/312]	eta 0:01:48 lr 0.002076	time 0.4539 (0.4910)	model_time 0.4538 (0.4687)	loss 3.0783 (3.1907)	grad_norm 5.3883 (1.9852/1.0129)	mem 16099MB
[2025-01-18 04:51:47 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][100/312]	eta 0:01:43 lr 0.002076	time 0.4556 (0.4889)	model_time 0.4555 (0.4688)	loss 3.1905 (3.1943)	grad_norm 2.0454 (2.0518/1.0799)	mem 16099MB
[2025-01-18 04:51:52 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][110/312]	eta 0:01:38 lr 0.002075	time 0.4489 (0.4868)	model_time 0.4487 (0.4684)	loss 4.1963 (3.2075)	grad_norm 1.9968 (2.0056/1.0576)	mem 16099MB
[2025-01-18 04:51:56 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][120/312]	eta 0:01:33 lr 0.002074	time 0.4520 (0.4868)	model_time 0.4516 (0.4700)	loss 3.0498 (3.1910)	grad_norm 1.0385 (1.9416/1.0394)	mem 16099MB
[2025-01-18 04:52:01 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][130/312]	eta 0:01:28 lr 0.002074	time 0.4450 (0.4844)	model_time 0.4446 (0.4687)	loss 2.2686 (3.1938)	grad_norm 1.0448 (1.8974/1.0168)	mem 16099MB
[2025-01-18 04:52:06 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][140/312]	eta 0:01:23 lr 0.002073	time 0.4464 (0.4827)	model_time 0.4462 (0.4682)	loss 3.5355 (3.2001)	grad_norm 1.8746 (1.8726/0.9884)	mem 16099MB
[2025-01-18 04:52:10 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][150/312]	eta 0:01:17 lr 0.002072	time 0.4530 (0.4813)	model_time 0.4529 (0.4677)	loss 3.9994 (3.2044)	grad_norm 2.2269 (1.8686/0.9794)	mem 16099MB
[2025-01-18 04:52:15 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][160/312]	eta 0:01:12 lr 0.002072	time 0.4791 (0.4798)	model_time 0.4787 (0.4670)	loss 2.4343 (3.2079)	grad_norm 1.9035 (1.8424/0.9602)	mem 16099MB
[2025-01-18 04:52:20 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][170/312]	eta 0:01:08 lr 0.002071	time 0.4652 (0.4806)	model_time 0.4647 (0.4686)	loss 3.3550 (3.2244)	grad_norm 1.8632 (1.8415/0.9513)	mem 16099MB
[2025-01-18 04:52:25 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][180/312]	eta 0:01:03 lr 0.002070	time 0.4793 (0.4811)	model_time 0.4791 (0.4697)	loss 2.7919 (3.2069)	grad_norm 1.1221 (1.8532/0.9469)	mem 16099MB
[2025-01-18 04:52:29 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][190/312]	eta 0:00:58 lr 0.002070	time 0.4712 (0.4802)	model_time 0.4707 (0.4693)	loss 4.2897 (3.2108)	grad_norm 1.6590 (1.8380/0.9287)	mem 16099MB
[2025-01-18 04:52:34 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][200/312]	eta 0:00:53 lr 0.002069	time 0.4405 (0.4798)	model_time 0.4401 (0.4695)	loss 2.8326 (3.2087)	grad_norm 1.1104 (1.8132/0.9153)	mem 16099MB
[2025-01-18 04:52:39 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][210/312]	eta 0:00:48 lr 0.002068	time 0.4421 (0.4790)	model_time 0.4417 (0.4691)	loss 3.1929 (3.2077)	grad_norm 1.6765 (1.8177/0.9027)	mem 16099MB
[2025-01-18 04:52:43 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][220/312]	eta 0:00:43 lr 0.002068	time 0.4473 (0.4781)	model_time 0.4472 (0.4686)	loss 2.5683 (3.2136)	grad_norm 1.5780 (1.8493/0.9199)	mem 16099MB
[2025-01-18 04:52:48 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][230/312]	eta 0:00:39 lr 0.002067	time 0.4467 (0.4781)	model_time 0.4462 (0.4690)	loss 2.4688 (3.2169)	grad_norm 1.8324 (1.8396/0.9084)	mem 16099MB
[2025-01-18 04:52:53 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][240/312]	eta 0:00:34 lr 0.002066	time 0.4496 (0.4773)	model_time 0.4492 (0.4686)	loss 3.2159 (3.2150)	grad_norm 1.1409 (1.8193/0.8973)	mem 16099MB
[2025-01-18 04:52:57 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][250/312]	eta 0:00:29 lr 0.002066	time 0.5372 (0.4770)	model_time 0.5366 (0.4686)	loss 3.8767 (3.2230)	grad_norm 1.0363 (1.8078/0.8842)	mem 16099MB
[2025-01-18 04:53:02 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][260/312]	eta 0:00:24 lr 0.002065	time 0.4703 (0.4765)	model_time 0.4701 (0.4684)	loss 3.0452 (3.2267)	grad_norm 1.1859 (1.8104/0.8768)	mem 16099MB
[2025-01-18 04:53:07 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][270/312]	eta 0:00:20 lr 0.002064	time 0.4769 (0.4765)	model_time 0.4764 (0.4687)	loss 3.3744 (3.2277)	grad_norm 1.3408 (1.7983/0.8689)	mem 16099MB
[2025-01-18 04:53:11 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][280/312]	eta 0:00:15 lr 0.002064	time 0.4692 (0.4765)	model_time 0.4688 (0.4690)	loss 3.3083 (3.2408)	grad_norm 2.1101 (1.7802/0.8624)	mem 16099MB
[2025-01-18 04:53:16 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][290/312]	eta 0:00:10 lr 0.002063	time 0.4688 (0.4763)	model_time 0.4686 (0.4691)	loss 3.1980 (3.2445)	grad_norm 2.2837 (1.7769/0.8528)	mem 16099MB
[2025-01-18 04:53:21 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][300/312]	eta 0:00:05 lr 0.002062	time 0.4730 (0.4756)	model_time 0.4729 (0.4686)	loss 4.1029 (3.2444)	grad_norm 2.5533 (1.7699/0.8412)	mem 16099MB
[2025-01-18 04:53:25 internimage_t_1k_224] (main.py 510): INFO Train: [147/300][310/312]	eta 0:00:00 lr 0.002062	time 0.4387 (0.4747)	model_time 0.4386 (0.4679)	loss 3.0975 (3.2521)	grad_norm 1.3869 (1.7505/0.8067)	mem 16099MB
[2025-01-18 04:53:26 internimage_t_1k_224] (main.py 519): INFO EPOCH 147 training takes 0:02:28
[2025-01-18 04:53:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_147.pth saving......
[2025-01-18 04:53:27 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_147.pth saved !!!
[2025-01-18 04:53:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.119 (7.119)	Loss 0.8501 (0.8501)	Acc@1 81.641 (81.641)	Acc@5 96.655 (96.655)	Mem 16099MB
[2025-01-18 04:53:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.983)	Loss 1.1555 (0.9875)	Acc@1 74.097 (78.997)	Acc@5 93.408 (94.762)	Mem 16099MB
[2025-01-18 04:53:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:147] * Acc@1 78.875 Acc@5 94.814
[2025-01-18 04:53:38 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 78.9%
[2025-01-18 04:53:38 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.19%
[2025-01-18 04:53:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.318 (8.318)	Loss 0.8117 (0.8117)	Acc@1 83.813 (83.813)	Acc@5 97.070 (97.070)	Mem 16099MB
[2025-01-18 04:53:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.119)	Loss 1.1215 (0.9457)	Acc@1 75.293 (80.578)	Acc@5 93.750 (95.459)	Mem 16099MB
[2025-01-18 04:53:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:147] * Acc@1 80.462 Acc@5 95.479
[2025-01-18 04:53:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.5%
[2025-01-18 04:53:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:53:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:53:52 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.46%
[2025-01-18 04:53:54 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][0/312]	eta 0:14:50 lr 0.002061	time 2.8541 (2.8541)	model_time 0.4608 (0.4608)	loss 3.3511 (3.3511)	grad_norm 2.3859 (2.3859/0.0000)	mem 16099MB
[2025-01-18 04:53:59 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][10/312]	eta 0:03:25 lr 0.002061	time 0.4436 (0.6818)	model_time 0.4434 (0.4640)	loss 4.1055 (3.2686)	grad_norm 1.0850 (1.8183/0.5228)	mem 16099MB
[2025-01-18 04:54:04 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][20/312]	eta 0:02:51 lr 0.002060	time 0.4835 (0.5875)	model_time 0.4833 (0.4732)	loss 3.8317 (3.4010)	grad_norm 1.4440 (1.8188/0.8107)	mem 16099MB
[2025-01-18 04:54:09 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][30/312]	eta 0:02:35 lr 0.002059	time 0.4394 (0.5510)	model_time 0.4393 (0.4735)	loss 3.5634 (3.2678)	grad_norm 2.4698 (1.7720/0.7287)	mem 16099MB
[2025-01-18 04:54:13 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][40/312]	eta 0:02:23 lr 0.002059	time 0.4720 (0.5283)	model_time 0.4717 (0.4695)	loss 3.1141 (3.2667)	grad_norm 1.1231 (1.7817/0.7395)	mem 16099MB
[2025-01-18 04:54:18 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][50/312]	eta 0:02:15 lr 0.002058	time 0.4624 (0.5153)	model_time 0.4622 (0.4680)	loss 3.9875 (3.2809)	grad_norm 2.1695 (1.7256/0.6941)	mem 16099MB
[2025-01-18 04:54:23 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][60/312]	eta 0:02:08 lr 0.002057	time 0.4400 (0.5108)	model_time 0.4399 (0.4712)	loss 3.4891 (3.2718)	grad_norm 2.3788 (1.8208/0.7769)	mem 16099MB
[2025-01-18 04:54:27 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][70/312]	eta 0:02:02 lr 0.002057	time 0.5481 (0.5042)	model_time 0.5480 (0.4701)	loss 3.4278 (3.2506)	grad_norm 3.1156 (1.8873/0.8185)	mem 16099MB
[2025-01-18 04:54:32 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][80/312]	eta 0:01:56 lr 0.002056	time 0.5404 (0.5014)	model_time 0.5402 (0.4714)	loss 3.7399 (3.2687)	grad_norm 1.9878 (1.9570/0.8442)	mem 16099MB
[2025-01-18 04:54:37 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][90/312]	eta 0:01:50 lr 0.002055	time 0.4397 (0.4969)	model_time 0.4392 (0.4702)	loss 2.1727 (3.2701)	grad_norm 1.8150 (1.9981/0.8786)	mem 16099MB
[2025-01-18 04:54:41 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][100/312]	eta 0:01:44 lr 0.002055	time 0.4550 (0.4928)	model_time 0.4546 (0.4687)	loss 3.8689 (3.2630)	grad_norm 2.2889 (1.9626/0.8531)	mem 16099MB
[2025-01-18 04:54:46 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][110/312]	eta 0:01:39 lr 0.002054	time 0.4483 (0.4905)	model_time 0.4479 (0.4685)	loss 3.5997 (3.2766)	grad_norm 3.6354 (1.9402/0.8484)	mem 16099MB
[2025-01-18 04:54:51 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][120/312]	eta 0:01:33 lr 0.002053	time 0.4473 (0.4878)	model_time 0.4469 (0.4676)	loss 2.3292 (3.2818)	grad_norm 1.4383 (1.9228/0.8418)	mem 16099MB
[2025-01-18 04:54:55 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][130/312]	eta 0:01:28 lr 0.002053	time 0.4545 (0.4860)	model_time 0.4540 (0.4673)	loss 2.3831 (3.2604)	grad_norm 3.9961 (1.9151/0.8402)	mem 16099MB
[2025-01-18 04:55:00 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][140/312]	eta 0:01:23 lr 0.002052	time 0.5555 (0.4846)	model_time 0.5550 (0.4672)	loss 3.3861 (3.2716)	grad_norm 1.3430 (1.9114/0.8584)	mem 16099MB
[2025-01-18 04:55:05 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][150/312]	eta 0:01:18 lr 0.002051	time 0.4408 (0.4833)	model_time 0.4404 (0.4670)	loss 3.0838 (3.2748)	grad_norm 1.3806 (1.9125/0.8454)	mem 16099MB
[2025-01-18 04:55:09 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][160/312]	eta 0:01:13 lr 0.002051	time 0.4479 (0.4829)	model_time 0.4475 (0.4677)	loss 3.2358 (3.2868)	grad_norm 1.0405 (1.8979/0.8276)	mem 16099MB
[2025-01-18 04:55:14 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][170/312]	eta 0:01:08 lr 0.002050	time 0.4527 (0.4819)	model_time 0.4525 (0.4675)	loss 3.4242 (3.2821)	grad_norm 1.4889 (1.9118/0.8359)	mem 16099MB
[2025-01-18 04:55:19 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][180/312]	eta 0:01:03 lr 0.002050	time 0.4465 (0.4808)	model_time 0.4464 (0.4672)	loss 3.5459 (3.2770)	grad_norm 1.2625 (1.8938/0.8273)	mem 16099MB
[2025-01-18 04:55:23 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][190/312]	eta 0:00:58 lr 0.002049	time 0.4573 (0.4793)	model_time 0.4569 (0.4664)	loss 4.0403 (3.2894)	grad_norm 1.4087 (1.8806/0.8214)	mem 16099MB
[2025-01-18 04:55:28 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][200/312]	eta 0:00:53 lr 0.002048	time 0.4652 (0.4786)	model_time 0.4648 (0.4662)	loss 2.3604 (3.2921)	grad_norm 1.0948 (1.8938/0.8467)	mem 16099MB
[2025-01-18 04:55:32 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][210/312]	eta 0:00:48 lr 0.002048	time 0.4432 (0.4781)	model_time 0.4431 (0.4663)	loss 2.4354 (3.2834)	grad_norm 2.0900 (1.9060/0.8525)	mem 16099MB
[2025-01-18 04:55:37 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][220/312]	eta 0:00:43 lr 0.002047	time 0.4590 (0.4771)	model_time 0.4589 (0.4659)	loss 2.7244 (3.2816)	grad_norm 1.4440 (1.9169/0.8573)	mem 16099MB
[2025-01-18 04:55:42 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][230/312]	eta 0:00:39 lr 0.002046	time 0.5033 (0.4774)	model_time 0.5029 (0.4666)	loss 3.8233 (3.2881)	grad_norm 0.9472 (1.9096/0.8504)	mem 16099MB
[2025-01-18 04:55:46 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][240/312]	eta 0:00:34 lr 0.002046	time 0.4401 (0.4768)	model_time 0.4400 (0.4665)	loss 3.2334 (3.2874)	grad_norm 2.8209 (1.9355/0.8838)	mem 16099MB
[2025-01-18 04:55:51 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][250/312]	eta 0:00:29 lr 0.002045	time 0.4593 (0.4768)	model_time 0.4591 (0.4668)	loss 3.6231 (3.2811)	grad_norm 2.3261 (1.9240/0.8767)	mem 16099MB
[2025-01-18 04:55:56 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][260/312]	eta 0:00:24 lr 0.002044	time 0.4419 (0.4764)	model_time 0.4414 (0.4669)	loss 2.7800 (3.2705)	grad_norm 0.8021 (1.9085/0.8713)	mem 16099MB
[2025-01-18 04:56:01 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][270/312]	eta 0:00:20 lr 0.002044	time 0.4442 (0.4766)	model_time 0.4441 (0.4673)	loss 2.2765 (3.2651)	grad_norm 0.8201 (1.9039/0.8647)	mem 16099MB
[2025-01-18 04:56:05 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][280/312]	eta 0:00:15 lr 0.002043	time 0.4508 (0.4763)	model_time 0.4503 (0.4674)	loss 2.6174 (3.2716)	grad_norm 1.4848 (1.8877/0.8569)	mem 16099MB
[2025-01-18 04:56:10 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][290/312]	eta 0:00:10 lr 0.002042	time 0.4514 (0.4757)	model_time 0.4512 (0.4671)	loss 3.6710 (3.2720)	grad_norm 0.9542 (1.8682/0.8505)	mem 16099MB
[2025-01-18 04:56:15 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][300/312]	eta 0:00:05 lr 0.002042	time 0.4438 (0.4754)	model_time 0.4437 (0.4670)	loss 2.2021 (3.2639)	grad_norm 1.1710 (1.8485/0.8451)	mem 16099MB
[2025-01-18 04:56:19 internimage_t_1k_224] (main.py 510): INFO Train: [148/300][310/312]	eta 0:00:00 lr 0.002041	time 0.4380 (0.4748)	model_time 0.4379 (0.4667)	loss 3.1011 (3.2598)	grad_norm 2.4882 (1.8477/0.8460)	mem 16099MB
[2025-01-18 04:56:20 internimage_t_1k_224] (main.py 519): INFO EPOCH 148 training takes 0:02:28
[2025-01-18 04:56:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_148.pth saving......
[2025-01-18 04:56:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_148.pth saved !!!
[2025-01-18 04:56:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.591 (7.591)	Loss 0.8178 (0.8178)	Acc@1 82.324 (82.324)	Acc@5 96.436 (96.436)	Mem 16099MB
[2025-01-18 04:56:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.024)	Loss 1.1570 (0.9568)	Acc@1 73.560 (79.270)	Acc@5 92.627 (94.818)	Mem 16099MB
[2025-01-18 04:56:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:148] * Acc@1 79.213 Acc@5 94.854
[2025-01-18 04:56:32 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.2%
[2025-01-18 04:56:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 04:56:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 04:56:33 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.21%
[2025-01-18 04:56:41 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.545 (7.545)	Loss 0.8114 (0.8114)	Acc@1 83.862 (83.862)	Acc@5 97.070 (97.070)	Mem 16099MB
[2025-01-18 04:56:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.038)	Loss 1.1199 (0.9451)	Acc@1 75.342 (80.631)	Acc@5 93.701 (95.466)	Mem 16099MB
[2025-01-18 04:56:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:148] * Acc@1 80.510 Acc@5 95.489
[2025-01-18 04:56:45 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.5%
[2025-01-18 04:56:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:56:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:56:46 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.51%
[2025-01-18 04:56:49 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][0/312]	eta 0:13:52 lr 0.002041	time 2.6686 (2.6686)	model_time 0.4774 (0.4774)	loss 3.4881 (3.4881)	grad_norm 3.1064 (3.1064/0.0000)	mem 16099MB
[2025-01-18 04:56:54 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][10/312]	eta 0:03:19 lr 0.002040	time 0.4515 (0.6607)	model_time 0.4514 (0.4612)	loss 2.5862 (3.0838)	grad_norm 2.2671 (2.2964/0.7017)	mem 16099MB
[2025-01-18 04:56:58 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][20/312]	eta 0:02:45 lr 0.002039	time 0.4482 (0.5681)	model_time 0.4481 (0.4635)	loss 2.2193 (3.1106)	grad_norm 1.6611 (2.1327/0.6941)	mem 16099MB
[2025-01-18 04:57:03 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][30/312]	eta 0:02:30 lr 0.002039	time 0.4567 (0.5328)	model_time 0.4563 (0.4617)	loss 3.6845 (3.1535)	grad_norm 1.4109 (1.9707/0.6548)	mem 16099MB
[2025-01-18 04:57:08 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][40/312]	eta 0:02:20 lr 0.002038	time 0.4677 (0.5162)	model_time 0.4675 (0.4625)	loss 3.4962 (3.1427)	grad_norm 1.2461 (1.8634/0.6121)	mem 16099MB
[2025-01-18 04:57:12 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][50/312]	eta 0:02:12 lr 0.002037	time 0.4528 (0.5069)	model_time 0.4524 (0.4636)	loss 3.5666 (3.1487)	grad_norm 1.4606 (1.8569/0.6091)	mem 16099MB
[2025-01-18 04:57:17 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][60/312]	eta 0:02:05 lr 0.002037	time 0.4610 (0.4989)	model_time 0.4605 (0.4626)	loss 3.9272 (3.1802)	grad_norm 1.7191 (1.8990/0.6610)	mem 16099MB
[2025-01-18 04:57:21 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][70/312]	eta 0:01:59 lr 0.002036	time 0.5612 (0.4949)	model_time 0.5610 (0.4636)	loss 2.1354 (3.1452)	grad_norm 1.3374 (1.9315/0.7212)	mem 16099MB
[2025-01-18 04:57:26 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][80/312]	eta 0:01:54 lr 0.002035	time 0.4557 (0.4915)	model_time 0.4553 (0.4638)	loss 2.5512 (3.1728)	grad_norm 1.2784 (1.8310/0.7314)	mem 16099MB
[2025-01-18 04:57:31 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][90/312]	eta 0:01:48 lr 0.002035	time 0.4492 (0.4886)	model_time 0.4486 (0.4640)	loss 3.2727 (3.2023)	grad_norm 2.5817 (1.8020/0.7223)	mem 16099MB
[2025-01-18 04:57:35 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][100/312]	eta 0:01:42 lr 0.002034	time 0.4401 (0.4856)	model_time 0.4396 (0.4634)	loss 3.6425 (3.2059)	grad_norm 2.2496 (1.8191/0.7243)	mem 16099MB
[2025-01-18 04:57:40 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][110/312]	eta 0:01:37 lr 0.002033	time 0.4496 (0.4844)	model_time 0.4494 (0.4641)	loss 2.5195 (3.1998)	grad_norm 2.4148 (1.7997/0.7124)	mem 16099MB
[2025-01-18 04:57:45 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][120/312]	eta 0:01:33 lr 0.002033	time 0.4699 (0.4848)	model_time 0.4695 (0.4662)	loss 3.6422 (3.2153)	grad_norm 2.5411 (1.8101/0.7394)	mem 16099MB
[2025-01-18 04:57:50 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][130/312]	eta 0:01:28 lr 0.002032	time 0.4453 (0.4841)	model_time 0.4448 (0.4669)	loss 2.9062 (3.1963)	grad_norm 2.1901 (1.8442/0.7424)	mem 16099MB
[2025-01-18 04:57:55 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][140/312]	eta 0:01:23 lr 0.002031	time 0.4877 (0.4836)	model_time 0.4873 (0.4675)	loss 2.9587 (3.1917)	grad_norm 3.2592 (1.8992/0.8527)	mem 16099MB
[2025-01-18 04:57:59 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][150/312]	eta 0:01:18 lr 0.002031	time 0.4530 (0.4839)	model_time 0.4528 (0.4689)	loss 3.7502 (3.2169)	grad_norm 1.2403 (1.9444/0.8796)	mem 16099MB
[2025-01-18 04:58:04 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][160/312]	eta 0:01:13 lr 0.002030	time 0.4573 (0.4833)	model_time 0.4571 (0.4692)	loss 3.4683 (3.2228)	grad_norm 0.9846 (1.9255/0.8669)	mem 16099MB
[2025-01-18 04:58:09 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][170/312]	eta 0:01:08 lr 0.002029	time 0.4411 (0.4839)	model_time 0.4409 (0.4706)	loss 1.9828 (3.2101)	grad_norm 1.3293 (1.9080/0.8473)	mem 16099MB
[2025-01-18 04:58:14 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][180/312]	eta 0:01:03 lr 0.002029	time 0.4499 (0.4825)	model_time 0.4495 (0.4699)	loss 3.6456 (3.2143)	grad_norm 4.5855 (1.8986/0.8686)	mem 16099MB
[2025-01-18 04:58:18 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][190/312]	eta 0:00:58 lr 0.002028	time 0.4405 (0.4811)	model_time 0.4404 (0.4692)	loss 3.2796 (3.2154)	grad_norm 0.9157 (1.8659/0.8610)	mem 16099MB
[2025-01-18 04:58:23 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][200/312]	eta 0:00:53 lr 0.002027	time 0.4766 (0.4798)	model_time 0.4764 (0.4685)	loss 3.6438 (3.2034)	grad_norm 1.3584 (1.8436/0.8474)	mem 16099MB
[2025-01-18 04:58:27 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][210/312]	eta 0:00:48 lr 0.002027	time 0.4574 (0.4787)	model_time 0.4572 (0.4679)	loss 2.7059 (3.2016)	grad_norm 3.4694 (1.8771/0.8613)	mem 16099MB
[2025-01-18 04:58:32 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][220/312]	eta 0:00:43 lr 0.002026	time 0.4428 (0.4777)	model_time 0.4424 (0.4674)	loss 2.9107 (3.1873)	grad_norm 1.2403 (1.8608/0.8533)	mem 16099MB
[2025-01-18 04:58:37 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][230/312]	eta 0:00:39 lr 0.002025	time 0.4558 (0.4769)	model_time 0.4557 (0.4669)	loss 4.1158 (3.1976)	grad_norm 1.4776 (1.8488/0.8401)	mem 16099MB
[2025-01-18 04:58:41 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][240/312]	eta 0:00:34 lr 0.002025	time 0.4573 (0.4759)	model_time 0.4568 (0.4664)	loss 3.8888 (3.1974)	grad_norm 0.9224 (1.8409/0.8298)	mem 16099MB
[2025-01-18 04:58:46 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][250/312]	eta 0:00:29 lr 0.002024	time 0.4559 (0.4751)	model_time 0.4557 (0.4659)	loss 3.3225 (3.1910)	grad_norm 1.4037 (1.8450/0.8339)	mem 16099MB
[2025-01-18 04:58:50 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][260/312]	eta 0:00:24 lr 0.002023	time 0.4602 (0.4745)	model_time 0.4600 (0.4656)	loss 3.5546 (3.1798)	grad_norm 2.0058 (1.8225/0.8279)	mem 16099MB
[2025-01-18 04:58:55 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][270/312]	eta 0:00:19 lr 0.002023	time 0.4407 (0.4742)	model_time 0.4402 (0.4657)	loss 3.5969 (3.1789)	grad_norm 2.7120 (1.8407/0.8276)	mem 16099MB
[2025-01-18 04:59:00 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][280/312]	eta 0:00:15 lr 0.002022	time 0.5274 (0.4740)	model_time 0.5273 (0.4658)	loss 2.6165 (3.1897)	grad_norm 0.9541 (1.8390/0.8201)	mem 16099MB
[2025-01-18 04:59:04 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][290/312]	eta 0:00:10 lr 0.002021	time 0.4498 (0.4740)	model_time 0.4496 (0.4660)	loss 3.6600 (3.2022)	grad_norm 1.3313 (1.8330/0.8098)	mem 16099MB
[2025-01-18 04:59:09 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][300/312]	eta 0:00:05 lr 0.002021	time 0.4419 (0.4735)	model_time 0.4418 (0.4658)	loss 3.8265 (3.2128)	grad_norm 2.6771 (1.8426/0.8083)	mem 16099MB
[2025-01-18 04:59:14 internimage_t_1k_224] (main.py 510): INFO Train: [149/300][310/312]	eta 0:00:00 lr 0.002020	time 0.4403 (0.4733)	model_time 0.4402 (0.4658)	loss 3.5173 (3.2238)	grad_norm 1.3061 (1.8341/0.8091)	mem 16099MB
[2025-01-18 04:59:14 internimage_t_1k_224] (main.py 519): INFO EPOCH 149 training takes 0:02:27
[2025-01-18 04:59:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_149.pth saving......
[2025-01-18 04:59:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_149.pth saved !!!
[2025-01-18 04:59:23 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.488 (7.488)	Loss 0.8232 (0.8232)	Acc@1 82.300 (82.300)	Acc@5 96.802 (96.802)	Mem 16099MB
[2025-01-18 04:59:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.015)	Loss 1.1077 (0.9718)	Acc@1 75.562 (79.268)	Acc@5 93.701 (94.993)	Mem 16099MB
[2025-01-18 04:59:27 internimage_t_1k_224] (main.py 575): INFO [Epoch:149] * Acc@1 79.217 Acc@5 95.010
[2025-01-18 04:59:27 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.2%
[2025-01-18 04:59:27 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 04:59:28 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 04:59:28 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.22%
[2025-01-18 04:59:35 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.433 (7.433)	Loss 0.8113 (0.8113)	Acc@1 83.887 (83.887)	Acc@5 97.095 (97.095)	Mem 16099MB
[2025-01-18 04:59:39 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.008)	Loss 1.1187 (0.9447)	Acc@1 75.220 (80.629)	Acc@5 93.701 (95.499)	Mem 16099MB
[2025-01-18 04:59:39 internimage_t_1k_224] (main.py 575): INFO [Epoch:149] * Acc@1 80.512 Acc@5 95.521
[2025-01-18 04:59:39 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.5%
[2025-01-18 04:59:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 04:59:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 04:59:40 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.51%
[2025-01-18 04:59:43 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][0/312]	eta 0:14:19 lr 0.002020	time 2.7552 (2.7552)	model_time 0.4787 (0.4787)	loss 2.5013 (2.5013)	grad_norm 2.2798 (2.2798/0.0000)	mem 16099MB
[2025-01-18 04:59:48 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][10/312]	eta 0:03:25 lr 0.002019	time 0.4476 (0.6817)	model_time 0.4475 (0.4743)	loss 3.8514 (3.1399)	grad_norm 1.5789 (1.6543/0.5422)	mem 16099MB
[2025-01-18 04:59:53 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][20/312]	eta 0:02:52 lr 0.002019	time 0.5914 (0.5893)	model_time 0.5913 (0.4797)	loss 3.4190 (3.2402)	grad_norm 0.8997 (1.5672/0.5090)	mem 16099MB
[2025-01-18 04:59:57 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][30/312]	eta 0:02:33 lr 0.002018	time 0.4522 (0.5460)	model_time 0.4520 (0.4716)	loss 3.3877 (3.3265)	grad_norm 1.5493 (1.5150/0.4706)	mem 16099MB
[2025-01-18 05:00:02 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][40/312]	eta 0:02:23 lr 0.002017	time 0.4532 (0.5267)	model_time 0.4530 (0.4704)	loss 4.2173 (3.3133)	grad_norm 2.4138 (1.5141/0.4726)	mem 16099MB
[2025-01-18 05:00:06 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][50/312]	eta 0:02:14 lr 0.002017	time 0.4480 (0.5144)	model_time 0.4476 (0.4691)	loss 2.5451 (3.2751)	grad_norm 1.7777 (1.5414/0.4694)	mem 16099MB
[2025-01-18 05:00:11 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][60/312]	eta 0:02:07 lr 0.002016	time 0.4401 (0.5067)	model_time 0.4399 (0.4687)	loss 3.2880 (3.2901)	grad_norm 3.9944 (1.6264/0.6015)	mem 16099MB
[2025-01-18 05:00:16 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][70/312]	eta 0:02:00 lr 0.002015	time 0.4444 (0.4992)	model_time 0.4442 (0.4665)	loss 3.2356 (3.2625)	grad_norm 1.0392 (1.6030/0.5754)	mem 16099MB
[2025-01-18 05:00:20 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][80/312]	eta 0:01:55 lr 0.002015	time 0.4592 (0.4959)	model_time 0.4587 (0.4672)	loss 3.4105 (3.2404)	grad_norm 1.3391 (1.6302/0.5656)	mem 16099MB
[2025-01-18 05:00:25 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][90/312]	eta 0:01:49 lr 0.002014	time 0.4527 (0.4916)	model_time 0.4525 (0.4660)	loss 3.3905 (3.2698)	grad_norm 1.7527 (1.6201/0.5598)	mem 16099MB
[2025-01-18 05:00:30 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][100/312]	eta 0:01:43 lr 0.002013	time 0.4781 (0.4899)	model_time 0.4776 (0.4668)	loss 3.9553 (3.2515)	grad_norm 1.3263 (1.6112/0.5410)	mem 16099MB
[2025-01-18 05:00:34 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][110/312]	eta 0:01:38 lr 0.002013	time 0.4707 (0.4869)	model_time 0.4706 (0.4659)	loss 2.3277 (3.2424)	grad_norm 0.9242 (1.6180/0.5677)	mem 16099MB
[2025-01-18 05:00:39 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][120/312]	eta 0:01:33 lr 0.002012	time 0.5423 (0.4859)	model_time 0.5418 (0.4666)	loss 3.8486 (3.2233)	grad_norm 3.6655 (1.6517/0.6091)	mem 16099MB
[2025-01-18 05:00:44 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][130/312]	eta 0:01:28 lr 0.002011	time 0.4693 (0.4851)	model_time 0.4691 (0.4672)	loss 2.7898 (3.2322)	grad_norm 1.9855 (1.7052/0.6631)	mem 16099MB
[2025-01-18 05:00:49 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][140/312]	eta 0:01:23 lr 0.002011	time 0.4514 (0.4846)	model_time 0.4512 (0.4679)	loss 3.6978 (3.2595)	grad_norm 3.5144 (1.7253/0.6744)	mem 16099MB
[2025-01-18 05:00:53 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][150/312]	eta 0:01:18 lr 0.002010	time 0.4496 (0.4827)	model_time 0.4491 (0.4671)	loss 2.3432 (3.2707)	grad_norm 3.3484 (1.7060/0.6833)	mem 16099MB
[2025-01-18 05:00:58 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][160/312]	eta 0:01:13 lr 0.002009	time 0.4480 (0.4828)	model_time 0.4478 (0.4681)	loss 4.0179 (3.2792)	grad_norm 0.9221 (1.7142/0.7030)	mem 16099MB
[2025-01-18 05:01:03 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][170/312]	eta 0:01:08 lr 0.002009	time 0.4617 (0.4822)	model_time 0.4615 (0.4684)	loss 2.8139 (3.2798)	grad_norm 1.7381 (1.7331/0.7027)	mem 16099MB
[2025-01-18 05:01:07 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][180/312]	eta 0:01:03 lr 0.002008	time 0.4521 (0.4818)	model_time 0.4517 (0.4687)	loss 2.6104 (3.2646)	grad_norm 1.7835 (1.7612/0.7183)	mem 16099MB
[2025-01-18 05:01:12 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][190/312]	eta 0:00:58 lr 0.002007	time 0.4607 (0.4811)	model_time 0.4606 (0.4687)	loss 3.7670 (3.2549)	grad_norm 2.2188 (1.7784/0.7275)	mem 16099MB
[2025-01-18 05:01:17 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][200/312]	eta 0:00:53 lr 0.002007	time 0.4799 (0.4798)	model_time 0.4795 (0.4681)	loss 3.4421 (3.2557)	grad_norm 1.3362 (1.7604/0.7157)	mem 16099MB
[2025-01-18 05:01:21 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][210/312]	eta 0:00:48 lr 0.002006	time 0.4560 (0.4788)	model_time 0.4558 (0.4675)	loss 3.6936 (3.2690)	grad_norm 1.1278 (1.7482/0.7086)	mem 16099MB
[2025-01-18 05:01:26 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][220/312]	eta 0:00:43 lr 0.002005	time 0.4492 (0.4777)	model_time 0.4490 (0.4669)	loss 3.4665 (3.2714)	grad_norm 1.6834 (1.7454/0.7052)	mem 16099MB
[2025-01-18 05:01:30 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][230/312]	eta 0:00:39 lr 0.002005	time 0.4608 (0.4772)	model_time 0.4606 (0.4669)	loss 2.2331 (3.2705)	grad_norm 1.1416 (1.7323/0.7000)	mem 16099MB
[2025-01-18 05:01:35 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][240/312]	eta 0:00:34 lr 0.002004	time 0.4573 (0.4767)	model_time 0.4569 (0.4668)	loss 4.1841 (3.2793)	grad_norm 1.1524 (1.7334/0.7007)	mem 16099MB
[2025-01-18 05:01:40 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][250/312]	eta 0:00:29 lr 0.002003	time 0.4393 (0.4766)	model_time 0.4390 (0.4671)	loss 3.2217 (3.2807)	grad_norm 1.9247 (1.7542/0.7034)	mem 16099MB
[2025-01-18 05:01:44 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][260/312]	eta 0:00:24 lr 0.002003	time 0.4527 (0.4758)	model_time 0.4525 (0.4666)	loss 3.1619 (3.2658)	grad_norm 1.2122 (1.7621/0.7041)	mem 16099MB
[2025-01-18 05:01:49 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][270/312]	eta 0:00:19 lr 0.002002	time 0.4570 (0.4753)	model_time 0.4568 (0.4665)	loss 3.1559 (3.2568)	grad_norm 1.8152 (1.7710/0.7091)	mem 16099MB
[2025-01-18 05:01:54 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][280/312]	eta 0:00:15 lr 0.002001	time 0.4833 (0.4748)	model_time 0.4831 (0.4663)	loss 3.3814 (3.2591)	grad_norm 0.9965 (1.7662/0.7093)	mem 16099MB
[2025-01-18 05:01:59 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][290/312]	eta 0:00:10 lr 0.002001	time 0.4466 (0.4753)	model_time 0.4462 (0.4670)	loss 3.0466 (3.2571)	grad_norm 1.8487 (1.7467/0.7063)	mem 16099MB
[2025-01-18 05:02:03 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][300/312]	eta 0:00:05 lr 0.002000	time 0.4396 (0.4748)	model_time 0.4395 (0.4668)	loss 3.4064 (3.2580)	grad_norm 1.6484 (1.7301/0.7045)	mem 16099MB
[2025-01-18 05:02:08 internimage_t_1k_224] (main.py 510): INFO Train: [150/300][310/312]	eta 0:00:00 lr 0.001999	time 0.4375 (0.4742)	model_time 0.4374 (0.4664)	loss 3.7947 (3.2594)	grad_norm 1.1027 (1.7488/0.7166)	mem 16099MB
[2025-01-18 05:02:08 internimage_t_1k_224] (main.py 519): INFO EPOCH 150 training takes 0:02:27
[2025-01-18 05:02:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_150.pth saving......
[2025-01-18 05:02:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_150.pth saved !!!
[2025-01-18 05:02:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.591 (7.591)	Loss 0.8207 (0.8207)	Acc@1 82.544 (82.544)	Acc@5 96.606 (96.606)	Mem 16099MB
[2025-01-18 05:02:21 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.027)	Loss 1.1498 (0.9643)	Acc@1 74.634 (79.368)	Acc@5 93.481 (95.002)	Mem 16099MB
[2025-01-18 05:02:21 internimage_t_1k_224] (main.py 575): INFO [Epoch:150] * Acc@1 79.249 Acc@5 95.012
[2025-01-18 05:02:21 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.2%
[2025-01-18 05:02:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 05:02:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 05:02:22 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.25%
[2025-01-18 05:02:29 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.347 (7.347)	Loss 0.8114 (0.8114)	Acc@1 83.911 (83.911)	Acc@5 97.095 (97.095)	Mem 16099MB
[2025-01-18 05:02:33 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.001)	Loss 1.1180 (0.9445)	Acc@1 75.391 (80.680)	Acc@5 93.726 (95.519)	Mem 16099MB
[2025-01-18 05:02:33 internimage_t_1k_224] (main.py 575): INFO [Epoch:150] * Acc@1 80.556 Acc@5 95.545
[2025-01-18 05:02:33 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.6%
[2025-01-18 05:02:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:02:35 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:02:35 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.56%
[2025-01-18 05:02:37 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][0/312]	eta 0:14:11 lr 0.001999	time 2.7280 (2.7280)	model_time 0.4840 (0.4840)	loss 2.9298 (2.9298)	grad_norm 1.1887 (1.1887/0.0000)	mem 16099MB
[2025-01-18 05:02:42 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][10/312]	eta 0:03:20 lr 0.001999	time 0.4425 (0.6652)	model_time 0.4419 (0.4608)	loss 3.6990 (3.0714)	grad_norm 0.9449 (1.8677/1.1860)	mem 16099MB
[2025-01-18 05:02:47 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][20/312]	eta 0:02:50 lr 0.001998	time 0.4534 (0.5836)	model_time 0.4530 (0.4764)	loss 2.4352 (3.0430)	grad_norm 5.6550 (2.0844/1.3561)	mem 16099MB
[2025-01-18 05:02:52 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][30/312]	eta 0:02:34 lr 0.001997	time 0.4602 (0.5493)	model_time 0.4597 (0.4766)	loss 2.9833 (3.1497)	grad_norm 1.4723 (1.9977/1.1996)	mem 16099MB
[2025-01-18 05:02:56 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][40/312]	eta 0:02:24 lr 0.001997	time 0.4399 (0.5294)	model_time 0.4394 (0.4743)	loss 3.8138 (3.1386)	grad_norm 1.7069 (1.8373/1.0926)	mem 16099MB
[2025-01-18 05:03:01 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][50/312]	eta 0:02:15 lr 0.001996	time 0.4876 (0.5156)	model_time 0.4871 (0.4712)	loss 3.8316 (3.2033)	grad_norm 3.1632 (1.8968/1.0524)	mem 16099MB
[2025-01-18 05:03:06 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][60/312]	eta 0:02:08 lr 0.001995	time 0.4404 (0.5080)	model_time 0.4402 (0.4708)	loss 3.1490 (3.1737)	grad_norm 1.9621 (1.9700/1.1097)	mem 16099MB
[2025-01-18 05:03:10 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][70/312]	eta 0:02:01 lr 0.001995	time 0.4539 (0.5013)	model_time 0.4534 (0.4694)	loss 3.5259 (3.2045)	grad_norm 3.2030 (1.9962/1.1066)	mem 16099MB
[2025-01-18 05:03:15 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][80/312]	eta 0:01:55 lr 0.001994	time 0.4525 (0.4981)	model_time 0.4521 (0.4700)	loss 3.2680 (3.1676)	grad_norm 2.3147 (2.0084/1.0867)	mem 16099MB
[2025-01-18 05:03:19 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][90/312]	eta 0:01:49 lr 0.001993	time 0.4572 (0.4935)	model_time 0.4568 (0.4684)	loss 3.6563 (3.1620)	grad_norm 1.1466 (1.9436/1.0505)	mem 16099MB
[2025-01-18 05:03:24 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][100/312]	eta 0:01:43 lr 0.001993	time 0.4602 (0.4894)	model_time 0.4600 (0.4668)	loss 2.7261 (3.1606)	grad_norm 1.5052 (1.9654/1.1203)	mem 16099MB
[2025-01-18 05:03:29 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][110/312]	eta 0:01:38 lr 0.001992	time 0.4437 (0.4871)	model_time 0.4436 (0.4665)	loss 3.0757 (3.1843)	grad_norm 1.6477 (2.0384/1.1335)	mem 16099MB
[2025-01-18 05:03:33 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][120/312]	eta 0:01:33 lr 0.001991	time 0.4483 (0.4856)	model_time 0.4481 (0.4667)	loss 2.4798 (3.1847)	grad_norm 1.5969 (2.0477/1.1087)	mem 16099MB
[2025-01-18 05:03:38 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][130/312]	eta 0:01:28 lr 0.001991	time 0.4510 (0.4838)	model_time 0.4506 (0.4663)	loss 2.1735 (3.2014)	grad_norm 1.4177 (2.0174/1.0741)	mem 16099MB
[2025-01-18 05:03:43 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][140/312]	eta 0:01:23 lr 0.001990	time 0.5238 (0.4833)	model_time 0.5233 (0.4670)	loss 4.3173 (3.2019)	grad_norm 1.4746 (2.0020/1.0584)	mem 16099MB
[2025-01-18 05:03:47 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][150/312]	eta 0:01:17 lr 0.001989	time 0.4495 (0.4813)	model_time 0.4490 (0.4661)	loss 4.0008 (3.2101)	grad_norm 0.8507 (1.9883/1.0498)	mem 16099MB
[2025-01-18 05:03:52 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][160/312]	eta 0:01:13 lr 0.001989	time 0.5333 (0.4812)	model_time 0.5328 (0.4669)	loss 3.5114 (3.2212)	grad_norm 1.2454 (1.9585/1.0337)	mem 16099MB
[2025-01-18 05:03:57 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][170/312]	eta 0:01:08 lr 0.001988	time 0.4440 (0.4801)	model_time 0.4435 (0.4666)	loss 3.1664 (3.2199)	grad_norm 2.3715 (1.9412/1.0158)	mem 16099MB
[2025-01-18 05:04:01 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][180/312]	eta 0:01:03 lr 0.001987	time 0.5319 (0.4798)	model_time 0.5315 (0.4670)	loss 3.2468 (3.2363)	grad_norm 2.0536 (1.9166/0.9972)	mem 16099MB
[2025-01-18 05:04:06 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][190/312]	eta 0:00:58 lr 0.001987	time 0.4651 (0.4790)	model_time 0.4650 (0.4669)	loss 3.5056 (3.2225)	grad_norm 1.6376 (1.9175/0.9873)	mem 16099MB
[2025-01-18 05:04:11 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][200/312]	eta 0:00:53 lr 0.001986	time 0.4438 (0.4789)	model_time 0.4437 (0.4673)	loss 2.2752 (3.2268)	grad_norm 2.2956 (1.8991/0.9692)	mem 16099MB
[2025-01-18 05:04:15 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][210/312]	eta 0:00:48 lr 0.001985	time 0.4479 (0.4779)	model_time 0.4474 (0.4669)	loss 3.0381 (3.2199)	grad_norm 1.6744 (1.9326/1.0032)	mem 16099MB
[2025-01-18 05:04:20 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][220/312]	eta 0:00:43 lr 0.001985	time 0.4537 (0.4769)	model_time 0.4535 (0.4663)	loss 2.9046 (3.2285)	grad_norm 1.3913 (1.9367/0.9938)	mem 16099MB
[2025-01-18 05:04:25 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][230/312]	eta 0:00:39 lr 0.001984	time 0.4523 (0.4764)	model_time 0.4522 (0.4663)	loss 3.8339 (3.2321)	grad_norm 1.3657 (1.9315/0.9808)	mem 16099MB
[2025-01-18 05:04:29 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][240/312]	eta 0:00:34 lr 0.001983	time 0.4662 (0.4757)	model_time 0.4661 (0.4660)	loss 3.8075 (3.2337)	grad_norm 1.7005 (1.9193/0.9693)	mem 16099MB
[2025-01-18 05:04:34 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][250/312]	eta 0:00:29 lr 0.001983	time 0.4509 (0.4749)	model_time 0.4505 (0.4656)	loss 3.5533 (3.2406)	grad_norm 1.2839 (1.9151/0.9601)	mem 16099MB
[2025-01-18 05:04:38 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][260/312]	eta 0:00:24 lr 0.001982	time 0.4585 (0.4746)	model_time 0.4580 (0.4657)	loss 3.6910 (3.2364)	grad_norm 1.8169 (1.9085/0.9496)	mem 16099MB
[2025-01-18 05:04:43 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][270/312]	eta 0:00:19 lr 0.001981	time 0.4596 (0.4741)	model_time 0.4594 (0.4655)	loss 3.3875 (3.2360)	grad_norm 1.4574 (1.9084/0.9386)	mem 16099MB
[2025-01-18 05:04:48 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][280/312]	eta 0:00:15 lr 0.001981	time 0.4519 (0.4737)	model_time 0.4517 (0.4654)	loss 4.2254 (3.2344)	grad_norm 1.4412 (1.9068/0.9306)	mem 16099MB
[2025-01-18 05:04:52 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][290/312]	eta 0:00:10 lr 0.001980	time 0.5196 (0.4736)	model_time 0.5194 (0.4655)	loss 3.3661 (3.2365)	grad_norm 1.8904 (1.8928/0.9205)	mem 16099MB
[2025-01-18 05:04:57 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][300/312]	eta 0:00:05 lr 0.001979	time 0.7161 (0.4741)	model_time 0.7160 (0.4663)	loss 3.9495 (3.2415)	grad_norm 1.9743 (1.8977/0.9086)	mem 16099MB
[2025-01-18 05:05:02 internimage_t_1k_224] (main.py 510): INFO Train: [151/300][310/312]	eta 0:00:00 lr 0.001979	time 0.4376 (0.4736)	model_time 0.4375 (0.4660)	loss 2.9150 (3.2435)	grad_norm 1.0769 (1.8825/0.8872)	mem 16099MB
[2025-01-18 05:05:02 internimage_t_1k_224] (main.py 519): INFO EPOCH 151 training takes 0:02:27
[2025-01-18 05:05:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_151.pth saving......
[2025-01-18 05:05:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_151.pth saved !!!
[2025-01-18 05:05:11 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.408 (7.408)	Loss 0.8379 (0.8379)	Acc@1 82.788 (82.788)	Acc@5 96.826 (96.826)	Mem 16099MB
[2025-01-18 05:05:15 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.005)	Loss 1.1623 (0.9847)	Acc@1 74.561 (79.301)	Acc@5 93.213 (94.833)	Mem 16099MB
[2025-01-18 05:05:15 internimage_t_1k_224] (main.py 575): INFO [Epoch:151] * Acc@1 79.103 Acc@5 94.846
[2025-01-18 05:05:15 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.1%
[2025-01-18 05:05:15 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.25%
[2025-01-18 05:05:23 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.368 (8.368)	Loss 0.8109 (0.8109)	Acc@1 83.984 (83.984)	Acc@5 97.119 (97.119)	Mem 16099MB
[2025-01-18 05:05:27 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.126)	Loss 1.1169 (0.9441)	Acc@1 75.342 (80.708)	Acc@5 93.823 (95.581)	Mem 16099MB
[2025-01-18 05:05:27 internimage_t_1k_224] (main.py 575): INFO [Epoch:151] * Acc@1 80.588 Acc@5 95.603
[2025-01-18 05:05:27 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.6%
[2025-01-18 05:05:27 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:05:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:05:29 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.59%
[2025-01-18 05:05:31 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][0/312]	eta 0:12:01 lr 0.001979	time 2.3120 (2.3120)	model_time 0.4991 (0.4991)	loss 3.5408 (3.5408)	grad_norm 0.9296 (0.9296/0.0000)	mem 16099MB
[2025-01-18 05:05:36 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][10/312]	eta 0:03:19 lr 0.001978	time 0.5475 (0.6599)	model_time 0.5474 (0.4948)	loss 3.5189 (3.3577)	grad_norm 0.9437 (1.9551/0.9408)	mem 16099MB
[2025-01-18 05:05:41 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][20/312]	eta 0:02:45 lr 0.001977	time 0.4477 (0.5656)	model_time 0.4474 (0.4789)	loss 3.7409 (3.3042)	grad_norm 1.5735 (1.9967/0.7968)	mem 16099MB
[2025-01-18 05:05:45 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][30/312]	eta 0:02:31 lr 0.001977	time 0.4544 (0.5365)	model_time 0.4542 (0.4776)	loss 2.8409 (3.2341)	grad_norm 2.3971 (1.9789/0.7729)	mem 16099MB
[2025-01-18 05:05:50 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][40/312]	eta 0:02:20 lr 0.001976	time 0.4472 (0.5168)	model_time 0.4470 (0.4722)	loss 3.4093 (3.2145)	grad_norm 2.3917 (1.9514/0.7361)	mem 16099MB
[2025-01-18 05:05:55 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][50/312]	eta 0:02:12 lr 0.001975	time 0.4512 (0.5049)	model_time 0.4511 (0.4690)	loss 3.6048 (3.2763)	grad_norm 1.0584 (1.8653/0.7342)	mem 16099MB
[2025-01-18 05:05:59 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][60/312]	eta 0:02:06 lr 0.001975	time 0.5471 (0.5015)	model_time 0.5466 (0.4714)	loss 3.2094 (3.2795)	grad_norm 2.8963 (1.9726/0.8357)	mem 16099MB
[2025-01-18 05:06:04 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][70/312]	eta 0:01:59 lr 0.001974	time 0.4504 (0.4949)	model_time 0.4503 (0.4690)	loss 3.8768 (3.2894)	grad_norm 2.3280 (1.9740/0.8470)	mem 16099MB
[2025-01-18 05:06:09 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][80/312]	eta 0:01:53 lr 0.001973	time 0.4525 (0.4909)	model_time 0.4521 (0.4681)	loss 2.8470 (3.2708)	grad_norm 1.1789 (1.8719/0.8430)	mem 16099MB
[2025-01-18 05:06:13 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][90/312]	eta 0:01:47 lr 0.001973	time 0.4457 (0.4865)	model_time 0.4452 (0.4662)	loss 2.4413 (3.2391)	grad_norm 1.2914 (1.8192/0.8240)	mem 16099MB
[2025-01-18 05:06:18 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][100/312]	eta 0:01:42 lr 0.001972	time 0.4479 (0.4841)	model_time 0.4477 (0.4658)	loss 2.3411 (3.2490)	grad_norm 1.0488 (1.7790/0.7952)	mem 16099MB
[2025-01-18 05:06:22 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][110/312]	eta 0:01:37 lr 0.001971	time 0.4708 (0.4835)	model_time 0.4707 (0.4668)	loss 3.1594 (3.2566)	grad_norm 2.5088 (1.7725/0.7814)	mem 16099MB
[2025-01-18 05:06:27 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][120/312]	eta 0:01:32 lr 0.001971	time 0.4441 (0.4828)	model_time 0.4440 (0.4674)	loss 3.4360 (3.2637)	grad_norm 2.3947 (1.8091/0.7893)	mem 16099MB
[2025-01-18 05:06:32 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][130/312]	eta 0:01:27 lr 0.001970	time 0.5452 (0.4821)	model_time 0.5447 (0.4679)	loss 3.7459 (3.2568)	grad_norm 2.4428 (1.7923/0.7706)	mem 16099MB
[2025-01-18 05:06:37 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][140/312]	eta 0:01:22 lr 0.001969	time 0.4683 (0.4801)	model_time 0.4681 (0.4669)	loss 3.1585 (3.2462)	grad_norm 2.0250 (1.8295/0.7923)	mem 16099MB
[2025-01-18 05:06:41 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][150/312]	eta 0:01:17 lr 0.001969	time 0.4497 (0.4796)	model_time 0.4493 (0.4672)	loss 3.2713 (3.2299)	grad_norm 1.4305 (1.8588/0.8054)	mem 16099MB
[2025-01-18 05:06:46 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][160/312]	eta 0:01:12 lr 0.001968	time 0.5536 (0.4794)	model_time 0.5534 (0.4678)	loss 3.4800 (3.2311)	grad_norm 1.1725 (1.8516/0.8002)	mem 16099MB
[2025-01-18 05:06:51 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][170/312]	eta 0:01:07 lr 0.001967	time 0.4906 (0.4786)	model_time 0.4904 (0.4677)	loss 3.7398 (3.2357)	grad_norm 1.0566 (1.8276/0.7899)	mem 16099MB
[2025-01-18 05:06:55 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][180/312]	eta 0:01:03 lr 0.001967	time 0.4463 (0.4788)	model_time 0.4458 (0.4684)	loss 3.3357 (3.2379)	grad_norm 1.9369 (1.8067/0.7778)	mem 16099MB
[2025-01-18 05:07:00 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][190/312]	eta 0:00:58 lr 0.001966	time 0.4606 (0.4786)	model_time 0.4601 (0.4687)	loss 3.2752 (3.2372)	grad_norm 1.1518 (1.7994/0.7712)	mem 16099MB
[2025-01-18 05:07:05 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][200/312]	eta 0:00:53 lr 0.001965	time 0.4574 (0.4776)	model_time 0.4569 (0.4682)	loss 3.7787 (3.2393)	grad_norm 1.7321 (1.8105/0.7700)	mem 16099MB
[2025-01-18 05:07:09 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][210/312]	eta 0:00:48 lr 0.001965	time 0.4506 (0.4766)	model_time 0.4502 (0.4677)	loss 3.6417 (3.2351)	grad_norm 1.0745 (1.7904/0.7621)	mem 16099MB
[2025-01-18 05:07:14 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][220/312]	eta 0:00:43 lr 0.001964	time 0.4640 (0.4757)	model_time 0.4636 (0.4671)	loss 2.6830 (3.2399)	grad_norm 3.2517 (1.8532/0.8442)	mem 16099MB
[2025-01-18 05:07:19 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][230/312]	eta 0:00:39 lr 0.001963	time 0.5434 (0.4759)	model_time 0.5429 (0.4676)	loss 2.6526 (3.2333)	grad_norm 0.7236 (1.8548/0.8500)	mem 16099MB
[2025-01-18 05:07:23 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][240/312]	eta 0:00:34 lr 0.001963	time 0.4883 (0.4753)	model_time 0.4878 (0.4674)	loss 3.3668 (3.2392)	grad_norm 1.2595 (1.8373/0.8417)	mem 16099MB
[2025-01-18 05:07:28 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][250/312]	eta 0:00:29 lr 0.001962	time 0.4632 (0.4746)	model_time 0.4627 (0.4670)	loss 2.9298 (3.2442)	grad_norm 1.8891 (1.8187/0.8336)	mem 16099MB
[2025-01-18 05:07:33 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][260/312]	eta 0:00:24 lr 0.001961	time 0.4426 (0.4748)	model_time 0.4421 (0.4675)	loss 3.6021 (3.2362)	grad_norm 2.5842 (1.8376/0.8310)	mem 16099MB
[2025-01-18 05:07:37 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][270/312]	eta 0:00:19 lr 0.001961	time 0.4791 (0.4742)	model_time 0.4789 (0.4671)	loss 3.4035 (3.2400)	grad_norm 1.5892 (1.8593/0.8606)	mem 16099MB
[2025-01-18 05:07:42 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][280/312]	eta 0:00:15 lr 0.001960	time 0.4414 (0.4733)	model_time 0.4412 (0.4665)	loss 2.7261 (3.2417)	grad_norm 2.9993 (1.8528/0.8541)	mem 16099MB
[2025-01-18 05:07:47 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][290/312]	eta 0:00:10 lr 0.001959	time 0.4603 (0.4736)	model_time 0.4599 (0.4670)	loss 3.3948 (3.2462)	grad_norm 1.2111 (1.8475/0.8467)	mem 16099MB
[2025-01-18 05:07:51 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][300/312]	eta 0:00:05 lr 0.001959	time 0.4380 (0.4732)	model_time 0.4379 (0.4668)	loss 2.6560 (3.2477)	grad_norm 1.6111 (1.8315/0.8404)	mem 16099MB
[2025-01-18 05:07:56 internimage_t_1k_224] (main.py 510): INFO Train: [152/300][310/312]	eta 0:00:00 lr 0.001958	time 0.4382 (0.4726)	model_time 0.4381 (0.4664)	loss 2.6218 (3.2399)	grad_norm 0.8901 (1.8046/0.8319)	mem 16099MB
[2025-01-18 05:07:56 internimage_t_1k_224] (main.py 519): INFO EPOCH 152 training takes 0:02:27
[2025-01-18 05:07:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_152.pth saving......
[2025-01-18 05:07:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_152.pth saved !!!
[2025-01-18 05:08:05 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.446 (7.446)	Loss 0.8721 (0.8721)	Acc@1 83.252 (83.252)	Acc@5 96.558 (96.558)	Mem 16099MB
[2025-01-18 05:08:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.992)	Loss 1.2032 (1.0054)	Acc@1 73.779 (79.375)	Acc@5 93.408 (95.077)	Mem 16099MB
[2025-01-18 05:08:09 internimage_t_1k_224] (main.py 575): INFO [Epoch:152] * Acc@1 79.305 Acc@5 95.076
[2025-01-18 05:08:09 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.3%
[2025-01-18 05:08:09 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 05:08:10 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 05:08:10 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.30%
[2025-01-18 05:08:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.404 (7.404)	Loss 0.8109 (0.8109)	Acc@1 84.131 (84.131)	Acc@5 97.095 (97.095)	Mem 16099MB
[2025-01-18 05:08:21 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.002)	Loss 1.1159 (0.9438)	Acc@1 75.439 (80.757)	Acc@5 93.774 (95.574)	Mem 16099MB
[2025-01-18 05:08:21 internimage_t_1k_224] (main.py 575): INFO [Epoch:152] * Acc@1 80.636 Acc@5 95.601
[2025-01-18 05:08:21 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.6%
[2025-01-18 05:08:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:08:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:08:22 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.64%
[2025-01-18 05:08:26 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][0/312]	eta 0:17:39 lr 0.001958	time 3.3962 (3.3962)	model_time 0.4576 (0.4576)	loss 2.9537 (2.9537)	grad_norm 1.4731 (1.4731/0.0000)	mem 16099MB
[2025-01-18 05:08:30 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][10/312]	eta 0:03:39 lr 0.001957	time 0.4658 (0.7279)	model_time 0.4651 (0.4604)	loss 3.0294 (3.3019)	grad_norm 1.8974 (2.1394/0.8711)	mem 16099MB
[2025-01-18 05:08:35 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][20/312]	eta 0:02:57 lr 0.001956	time 0.4531 (0.6070)	model_time 0.4529 (0.4667)	loss 2.8151 (3.3983)	grad_norm 1.0330 (1.9487/0.9750)	mem 16099MB
[2025-01-18 05:08:40 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][30/312]	eta 0:02:38 lr 0.001956	time 0.5042 (0.5605)	model_time 0.5040 (0.4654)	loss 2.2374 (3.3503)	grad_norm 1.6956 (1.8659/0.8707)	mem 16099MB
[2025-01-18 05:08:44 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][40/312]	eta 0:02:26 lr 0.001955	time 0.4604 (0.5388)	model_time 0.4600 (0.4667)	loss 3.0465 (3.3532)	grad_norm 2.9891 (1.8774/0.8112)	mem 16099MB
[2025-01-18 05:08:49 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][50/312]	eta 0:02:18 lr 0.001954	time 0.4521 (0.5278)	model_time 0.4520 (0.4698)	loss 2.8478 (3.3414)	grad_norm 1.1001 (1.8952/0.8016)	mem 16099MB
[2025-01-18 05:08:54 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][60/312]	eta 0:02:10 lr 0.001954	time 0.4508 (0.5189)	model_time 0.4507 (0.4703)	loss 3.6687 (3.3820)	grad_norm 1.1618 (1.8563/0.7973)	mem 16099MB
[2025-01-18 05:08:59 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][70/312]	eta 0:02:04 lr 0.001953	time 0.4500 (0.5144)	model_time 0.4496 (0.4726)	loss 3.7324 (3.3395)	grad_norm 1.4564 (1.9198/0.8133)	mem 16099MB
[2025-01-18 05:09:03 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][80/312]	eta 0:01:57 lr 0.001952	time 0.4541 (0.5077)	model_time 0.4539 (0.4710)	loss 2.4190 (3.3139)	grad_norm 0.8881 (1.9160/0.8020)	mem 16099MB
[2025-01-18 05:09:08 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][90/312]	eta 0:01:51 lr 0.001952	time 0.4482 (0.5034)	model_time 0.4480 (0.4707)	loss 3.8638 (3.3128)	grad_norm 1.6137 (1.9036/0.8276)	mem 16099MB
[2025-01-18 05:09:13 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][100/312]	eta 0:01:45 lr 0.001951	time 0.4483 (0.4998)	model_time 0.4481 (0.4703)	loss 2.6817 (3.2922)	grad_norm 1.3601 (1.9025/0.8238)	mem 16099MB
[2025-01-18 05:09:17 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][110/312]	eta 0:01:40 lr 0.001951	time 0.4461 (0.4967)	model_time 0.4457 (0.4698)	loss 3.3761 (3.2838)	grad_norm 1.3857 (1.9247/0.8170)	mem 16099MB
[2025-01-18 05:09:22 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][120/312]	eta 0:01:34 lr 0.001950	time 0.4444 (0.4946)	model_time 0.4440 (0.4699)	loss 3.0996 (3.2898)	grad_norm 1.1694 (1.9034/0.8045)	mem 16099MB
[2025-01-18 05:09:27 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][130/312]	eta 0:01:29 lr 0.001949	time 0.4608 (0.4930)	model_time 0.4604 (0.4701)	loss 3.7321 (3.2933)	grad_norm 1.3327 (1.8652/0.7900)	mem 16099MB
[2025-01-18 05:09:32 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][140/312]	eta 0:01:24 lr 0.001949	time 0.4532 (0.4926)	model_time 0.4528 (0.4713)	loss 3.4043 (3.3040)	grad_norm 1.2677 (1.8289/0.7748)	mem 16099MB
[2025-01-18 05:09:36 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][150/312]	eta 0:01:19 lr 0.001948	time 0.4466 (0.4915)	model_time 0.4464 (0.4716)	loss 3.9874 (3.2969)	grad_norm 0.8935 (1.8456/0.7870)	mem 16099MB
[2025-01-18 05:09:41 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][160/312]	eta 0:01:14 lr 0.001947	time 0.4442 (0.4901)	model_time 0.4438 (0.4714)	loss 3.8276 (3.2909)	grad_norm 1.3856 (1.8225/0.7757)	mem 16099MB
[2025-01-18 05:09:46 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][170/312]	eta 0:01:09 lr 0.001947	time 0.4530 (0.4884)	model_time 0.4525 (0.4708)	loss 3.3811 (3.2981)	grad_norm 1.8396 (1.8169/0.7614)	mem 16099MB
[2025-01-18 05:09:50 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][180/312]	eta 0:01:04 lr 0.001946	time 0.4764 (0.4874)	model_time 0.4758 (0.4708)	loss 3.0653 (3.2973)	grad_norm 0.9009 (1.8047/0.7530)	mem 16099MB
[2025-01-18 05:09:55 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][190/312]	eta 0:00:59 lr 0.001945	time 0.4800 (0.4876)	model_time 0.4795 (0.4718)	loss 3.8068 (3.2813)	grad_norm 1.3034 (1.7898/0.7425)	mem 16099MB
[2025-01-18 05:10:00 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][200/312]	eta 0:00:54 lr 0.001945	time 0.4499 (0.4865)	model_time 0.4495 (0.4715)	loss 3.8658 (3.2866)	grad_norm 1.2311 (1.7920/0.7379)	mem 16099MB
[2025-01-18 05:10:05 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][210/312]	eta 0:00:49 lr 0.001944	time 0.4478 (0.4855)	model_time 0.4474 (0.4712)	loss 3.2483 (3.2835)	grad_norm 2.4867 (1.7875/0.7332)	mem 16099MB
[2025-01-18 05:10:09 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][220/312]	eta 0:00:44 lr 0.001943	time 0.4520 (0.4843)	model_time 0.4519 (0.4706)	loss 2.7768 (3.2735)	grad_norm 1.4337 (1.8042/0.7430)	mem 16099MB
[2025-01-18 05:10:14 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][230/312]	eta 0:00:39 lr 0.001943	time 0.4608 (0.4834)	model_time 0.4604 (0.4703)	loss 3.2510 (3.2694)	grad_norm 1.4277 (1.8040/0.7306)	mem 16099MB
[2025-01-18 05:10:19 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][240/312]	eta 0:00:34 lr 0.001942	time 0.4440 (0.4825)	model_time 0.4439 (0.4699)	loss 2.6154 (3.2583)	grad_norm 2.2104 (1.8015/0.7265)	mem 16099MB
[2025-01-18 05:10:23 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][250/312]	eta 0:00:29 lr 0.001941	time 0.4439 (0.4816)	model_time 0.4435 (0.4695)	loss 3.2956 (3.2575)	grad_norm 2.6649 (1.8079/0.7220)	mem 16099MB
[2025-01-18 05:10:28 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][260/312]	eta 0:00:25 lr 0.001941	time 0.4536 (0.4814)	model_time 0.4535 (0.4698)	loss 2.5216 (3.2632)	grad_norm 1.5763 (1.8008/0.7169)	mem 16099MB
[2025-01-18 05:10:33 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][270/312]	eta 0:00:20 lr 0.001940	time 0.4535 (0.4808)	model_time 0.4533 (0.4696)	loss 3.8696 (3.2661)	grad_norm 0.9659 (1.8180/0.7263)	mem 16099MB
[2025-01-18 05:10:37 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][280/312]	eta 0:00:15 lr 0.001939	time 0.4418 (0.4801)	model_time 0.4414 (0.4693)	loss 3.8197 (3.2703)	grad_norm 1.7438 (1.8245/0.7330)	mem 16099MB
[2025-01-18 05:10:42 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][290/312]	eta 0:00:10 lr 0.001939	time 0.4709 (0.4797)	model_time 0.4705 (0.4692)	loss 4.0067 (3.2680)	grad_norm 0.7813 (1.8142/0.7262)	mem 16099MB
[2025-01-18 05:10:46 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][300/312]	eta 0:00:05 lr 0.001938	time 0.4325 (0.4787)	model_time 0.4324 (0.4686)	loss 3.9486 (3.2706)	grad_norm 2.0645 (1.8159/0.7194)	mem 16099MB
[2025-01-18 05:10:51 internimage_t_1k_224] (main.py 510): INFO Train: [153/300][310/312]	eta 0:00:00 lr 0.001937	time 0.5223 (0.4778)	model_time 0.5222 (0.4679)	loss 3.9070 (3.2736)	grad_norm 2.0470 (1.8091/0.7093)	mem 16099MB
[2025-01-18 05:10:51 internimage_t_1k_224] (main.py 519): INFO EPOCH 153 training takes 0:02:29
[2025-01-18 05:10:51 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_153.pth saving......
[2025-01-18 05:10:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_153.pth saved !!!
[2025-01-18 05:11:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.210 (7.210)	Loss 0.8398 (0.8398)	Acc@1 82.471 (82.471)	Acc@5 96.631 (96.631)	Mem 16099MB
[2025-01-18 05:11:03 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.985)	Loss 1.1734 (0.9813)	Acc@1 74.023 (79.319)	Acc@5 92.822 (94.940)	Mem 16099MB
[2025-01-18 05:11:03 internimage_t_1k_224] (main.py 575): INFO [Epoch:153] * Acc@1 79.219 Acc@5 94.936
[2025-01-18 05:11:03 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.2%
[2025-01-18 05:11:03 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.30%
[2025-01-18 05:11:12 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.467 (8.467)	Loss 0.8105 (0.8105)	Acc@1 84.106 (84.106)	Acc@5 97.095 (97.095)	Mem 16099MB
[2025-01-18 05:11:16 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.126)	Loss 1.1148 (0.9433)	Acc@1 75.513 (80.808)	Acc@5 93.872 (95.590)	Mem 16099MB
[2025-01-18 05:11:16 internimage_t_1k_224] (main.py 575): INFO [Epoch:153] * Acc@1 80.686 Acc@5 95.619
[2025-01-18 05:11:16 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.7%
[2025-01-18 05:11:16 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:11:17 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:11:17 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.69%
[2025-01-18 05:11:20 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][0/312]	eta 0:12:11 lr 0.001937	time 2.3430 (2.3430)	model_time 0.5241 (0.5241)	loss 3.3931 (3.3931)	grad_norm 1.0610 (1.0610/0.0000)	mem 16099MB
[2025-01-18 05:11:25 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][10/312]	eta 0:03:18 lr 0.001936	time 0.4700 (0.6566)	model_time 0.4698 (0.4800)	loss 4.0018 (3.1648)	grad_norm 2.7259 (1.7566/0.5885)	mem 16099MB
[2025-01-18 05:11:29 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][20/312]	eta 0:02:44 lr 0.001936	time 0.4497 (0.5640)	model_time 0.4492 (0.4713)	loss 4.0769 (3.1895)	grad_norm 2.8333 (1.6986/0.5729)	mem 16099MB
[2025-01-18 05:11:34 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][30/312]	eta 0:02:31 lr 0.001935	time 0.5547 (0.5378)	model_time 0.5545 (0.4749)	loss 2.5214 (3.1498)	grad_norm 3.9620 (1.8662/0.8071)	mem 16099MB
[2025-01-18 05:11:39 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][40/312]	eta 0:02:20 lr 0.001934	time 0.4489 (0.5178)	model_time 0.4487 (0.4702)	loss 2.5171 (3.1344)	grad_norm 3.7264 (1.9566/0.8451)	mem 16099MB
[2025-01-18 05:11:44 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][50/312]	eta 0:02:14 lr 0.001934	time 0.4513 (0.5119)	model_time 0.4508 (0.4735)	loss 2.3372 (3.0757)	grad_norm 1.9594 (1.9618/0.8418)	mem 16099MB
[2025-01-18 05:11:48 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][60/312]	eta 0:02:07 lr 0.001933	time 0.4545 (0.5052)	model_time 0.4544 (0.4731)	loss 3.2503 (3.1112)	grad_norm 1.6978 (1.9423/0.7862)	mem 16099MB
[2025-01-18 05:11:53 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][70/312]	eta 0:02:00 lr 0.001932	time 0.4471 (0.4993)	model_time 0.4469 (0.4716)	loss 3.7228 (3.1149)	grad_norm 2.4447 (1.9226/0.7524)	mem 16099MB
[2025-01-18 05:11:57 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][80/312]	eta 0:01:54 lr 0.001932	time 0.4429 (0.4936)	model_time 0.4425 (0.4693)	loss 3.0515 (3.1494)	grad_norm 2.7634 (1.8988/0.7470)	mem 16099MB
[2025-01-18 05:12:02 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][90/312]	eta 0:01:49 lr 0.001931	time 0.5394 (0.4927)	model_time 0.5390 (0.4710)	loss 4.0352 (3.1529)	grad_norm 3.1023 (1.9140/0.7779)	mem 16099MB
[2025-01-18 05:12:07 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][100/312]	eta 0:01:44 lr 0.001930	time 0.4473 (0.4912)	model_time 0.4469 (0.4716)	loss 3.2362 (3.1428)	grad_norm 1.6875 (1.8659/0.7677)	mem 16099MB
[2025-01-18 05:12:12 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][110/312]	eta 0:01:38 lr 0.001930	time 0.4624 (0.4879)	model_time 0.4623 (0.4701)	loss 3.9627 (3.1745)	grad_norm 3.0685 (1.8305/0.7715)	mem 16099MB
[2025-01-18 05:12:16 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][120/312]	eta 0:01:33 lr 0.001929	time 0.4595 (0.4865)	model_time 0.4590 (0.4701)	loss 3.5801 (3.1838)	grad_norm 3.8648 (1.8675/0.7909)	mem 16099MB
[2025-01-18 05:12:21 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][130/312]	eta 0:01:28 lr 0.001928	time 0.5769 (0.4850)	model_time 0.5765 (0.4698)	loss 2.8098 (3.1696)	grad_norm 1.6804 (1.8873/0.8013)	mem 16099MB
[2025-01-18 05:12:26 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][140/312]	eta 0:01:23 lr 0.001928	time 0.4460 (0.4833)	model_time 0.4455 (0.4692)	loss 3.6605 (3.1792)	grad_norm 1.6839 (1.8544/0.7869)	mem 16099MB
[2025-01-18 05:12:30 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][150/312]	eta 0:01:17 lr 0.001927	time 0.4409 (0.4813)	model_time 0.4404 (0.4681)	loss 3.0402 (3.1549)	grad_norm 1.0596 (1.8139/0.7791)	mem 16099MB
[2025-01-18 05:12:35 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][160/312]	eta 0:01:13 lr 0.001926	time 0.4564 (0.4809)	model_time 0.4560 (0.4684)	loss 3.1990 (3.1596)	grad_norm 0.9206 (1.7964/0.7756)	mem 16099MB
[2025-01-18 05:12:39 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][170/312]	eta 0:01:08 lr 0.001926	time 0.4494 (0.4800)	model_time 0.4492 (0.4683)	loss 2.3998 (3.1770)	grad_norm 2.2932 (1.8187/0.7794)	mem 16099MB
[2025-01-18 05:12:44 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][180/312]	eta 0:01:03 lr 0.001925	time 0.4495 (0.4792)	model_time 0.4491 (0.4680)	loss 2.9117 (3.1798)	grad_norm 1.4636 (1.8204/0.7823)	mem 16099MB
[2025-01-18 05:12:49 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][190/312]	eta 0:00:58 lr 0.001924	time 0.4695 (0.4784)	model_time 0.4691 (0.4677)	loss 3.9250 (3.1999)	grad_norm 1.7104 (1.8050/0.7672)	mem 16099MB
[2025-01-18 05:12:53 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][200/312]	eta 0:00:53 lr 0.001924	time 0.4498 (0.4776)	model_time 0.4494 (0.4674)	loss 3.4270 (3.2107)	grad_norm 3.3337 (1.8231/0.7878)	mem 16099MB
[2025-01-18 05:12:58 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][210/312]	eta 0:00:48 lr 0.001923	time 0.4488 (0.4766)	model_time 0.4487 (0.4669)	loss 3.3158 (3.2039)	grad_norm 2.2164 (1.8351/0.7900)	mem 16099MB
[2025-01-18 05:13:03 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][220/312]	eta 0:00:43 lr 0.001922	time 0.4531 (0.4760)	model_time 0.4529 (0.4667)	loss 4.1407 (3.2004)	grad_norm 1.9759 (1.8357/0.7806)	mem 16099MB
[2025-01-18 05:13:07 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][230/312]	eta 0:00:38 lr 0.001922	time 0.4598 (0.4751)	model_time 0.4594 (0.4662)	loss 2.5057 (3.1988)	grad_norm 2.5365 (1.8592/0.8028)	mem 16099MB
[2025-01-18 05:13:12 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][240/312]	eta 0:00:34 lr 0.001921	time 0.4545 (0.4742)	model_time 0.4543 (0.4657)	loss 4.2126 (3.2158)	grad_norm 0.8562 (1.8542/0.7956)	mem 16099MB
[2025-01-18 05:13:16 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][250/312]	eta 0:00:29 lr 0.001920	time 0.4495 (0.4744)	model_time 0.4493 (0.4662)	loss 2.5777 (3.2103)	grad_norm 0.8795 (1.8369/0.7864)	mem 16099MB
[2025-01-18 05:13:21 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][260/312]	eta 0:00:24 lr 0.001920	time 0.4433 (0.4740)	model_time 0.4429 (0.4661)	loss 3.3020 (3.2042)	grad_norm 2.8889 (1.8347/0.7819)	mem 16099MB
[2025-01-18 05:13:26 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][270/312]	eta 0:00:19 lr 0.001919	time 0.4450 (0.4743)	model_time 0.4449 (0.4667)	loss 3.0960 (3.1967)	grad_norm 0.9885 (1.8449/0.7966)	mem 16099MB
[2025-01-18 05:13:31 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][280/312]	eta 0:00:15 lr 0.001918	time 0.4477 (0.4740)	model_time 0.4472 (0.4666)	loss 2.6113 (3.1963)	grad_norm 1.2581 (1.8428/0.7905)	mem 16099MB
[2025-01-18 05:13:35 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][290/312]	eta 0:00:10 lr 0.001918	time 0.4448 (0.4738)	model_time 0.4446 (0.4667)	loss 2.9405 (3.2062)	grad_norm 1.3048 (1.8484/0.7934)	mem 16099MB
[2025-01-18 05:13:40 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][300/312]	eta 0:00:05 lr 0.001917	time 0.4410 (0.4730)	model_time 0.4409 (0.4661)	loss 2.3856 (3.2043)	grad_norm 1.1946 (1.8630/0.7976)	mem 16099MB
[2025-01-18 05:13:44 internimage_t_1k_224] (main.py 510): INFO Train: [154/300][310/312]	eta 0:00:00 lr 0.001917	time 0.5225 (0.4725)	model_time 0.5224 (0.4659)	loss 2.8889 (3.2003)	grad_norm 1.2269 (1.8572/0.7987)	mem 16099MB
[2025-01-18 05:13:45 internimage_t_1k_224] (main.py 519): INFO EPOCH 154 training takes 0:02:27
[2025-01-18 05:13:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_154.pth saving......
[2025-01-18 05:13:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_154.pth saved !!!
[2025-01-18 05:13:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.539 (7.539)	Loss 0.8092 (0.8092)	Acc@1 83.228 (83.228)	Acc@5 96.753 (96.753)	Mem 16099MB
[2025-01-18 05:13:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.025)	Loss 1.1748 (0.9772)	Acc@1 73.877 (79.450)	Acc@5 93.115 (94.982)	Mem 16099MB
[2025-01-18 05:13:57 internimage_t_1k_224] (main.py 575): INFO [Epoch:154] * Acc@1 79.417 Acc@5 95.040
[2025-01-18 05:13:57 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.4%
[2025-01-18 05:13:57 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 05:13:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 05:13:59 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.42%
[2025-01-18 05:14:06 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.418 (7.418)	Loss 0.8104 (0.8104)	Acc@1 84.180 (84.180)	Acc@5 97.119 (97.119)	Mem 16099MB
[2025-01-18 05:14:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.016)	Loss 1.1136 (0.9431)	Acc@1 75.562 (80.839)	Acc@5 93.896 (95.610)	Mem 16099MB
[2025-01-18 05:14:10 internimage_t_1k_224] (main.py 575): INFO [Epoch:154] * Acc@1 80.728 Acc@5 95.637
[2025-01-18 05:14:10 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.7%
[2025-01-18 05:14:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:14:11 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:14:11 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.73%
[2025-01-18 05:14:14 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][0/312]	eta 0:11:21 lr 0.001916	time 2.1846 (2.1846)	model_time 0.4682 (0.4682)	loss 3.2065 (3.2065)	grad_norm 2.2344 (2.2344/0.0000)	mem 16099MB
[2025-01-18 05:14:19 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][10/312]	eta 0:03:14 lr 0.001916	time 0.4507 (0.6430)	model_time 0.4503 (0.4565)	loss 3.4818 (3.3880)	grad_norm 1.2852 (1.8381/0.6294)	mem 16099MB
[2025-01-18 05:14:23 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][20/312]	eta 0:02:43 lr 0.001915	time 0.4479 (0.5590)	model_time 0.4477 (0.4612)	loss 2.7017 (3.3984)	grad_norm 1.8997 (1.6060/0.5651)	mem 16099MB
[2025-01-18 05:14:28 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][30/312]	eta 0:02:30 lr 0.001914	time 0.4499 (0.5328)	model_time 0.4498 (0.4664)	loss 2.8778 (3.3636)	grad_norm 1.2145 (1.5937/0.6492)	mem 16099MB
[2025-01-18 05:14:32 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][40/312]	eta 0:02:19 lr 0.001914	time 0.4511 (0.5134)	model_time 0.4509 (0.4631)	loss 3.6583 (3.4041)	grad_norm 1.7820 (1.5507/0.5944)	mem 16099MB
[2025-01-18 05:14:37 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][50/312]	eta 0:02:11 lr 0.001913	time 0.4496 (0.5016)	model_time 0.4494 (0.4611)	loss 3.5763 (3.3485)	grad_norm 1.2690 (1.5977/0.5824)	mem 16099MB
[2025-01-18 05:14:42 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][60/312]	eta 0:02:05 lr 0.001912	time 0.4514 (0.4964)	model_time 0.4512 (0.4625)	loss 3.7156 (3.3287)	grad_norm 1.2173 (1.6646/0.7189)	mem 16099MB
[2025-01-18 05:14:46 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][70/312]	eta 0:01:59 lr 0.001912	time 0.4408 (0.4920)	model_time 0.4406 (0.4628)	loss 3.4166 (3.2960)	grad_norm 1.1194 (1.6968/0.7431)	mem 16099MB
[2025-01-18 05:14:51 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][80/312]	eta 0:01:53 lr 0.001911	time 0.4518 (0.4892)	model_time 0.4516 (0.4636)	loss 3.8455 (3.3409)	grad_norm 2.3605 (1.6683/0.7250)	mem 16099MB
[2025-01-18 05:14:56 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][90/312]	eta 0:01:47 lr 0.001910	time 0.4524 (0.4861)	model_time 0.4522 (0.4632)	loss 2.8390 (3.3291)	grad_norm 1.3834 (1.6750/0.7119)	mem 16099MB
[2025-01-18 05:15:00 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][100/312]	eta 0:01:42 lr 0.001910	time 0.4556 (0.4839)	model_time 0.4554 (0.4633)	loss 3.5486 (3.3221)	grad_norm 1.3651 (1.6873/0.7104)	mem 16099MB
[2025-01-18 05:15:05 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][110/312]	eta 0:01:37 lr 0.001909	time 0.5588 (0.4838)	model_time 0.5587 (0.4650)	loss 2.1333 (3.2912)	grad_norm 1.3214 (1.6892/0.7365)	mem 16099MB
[2025-01-18 05:15:10 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][120/312]	eta 0:01:32 lr 0.001908	time 0.4605 (0.4814)	model_time 0.4603 (0.4641)	loss 3.6253 (3.3033)	grad_norm 1.5319 (1.7231/0.7946)	mem 16099MB
[2025-01-18 05:15:14 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][130/312]	eta 0:01:27 lr 0.001908	time 0.4611 (0.4800)	model_time 0.4606 (0.4640)	loss 3.1452 (3.2971)	grad_norm 1.0326 (1.7334/0.8075)	mem 16099MB
[2025-01-18 05:15:19 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][140/312]	eta 0:01:22 lr 0.001907	time 0.5464 (0.4795)	model_time 0.5460 (0.4646)	loss 3.2832 (3.2946)	grad_norm 1.8312 (1.7097/0.7875)	mem 16099MB
[2025-01-18 05:15:24 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][150/312]	eta 0:01:17 lr 0.001906	time 0.4395 (0.4797)	model_time 0.4393 (0.4657)	loss 2.7752 (3.2929)	grad_norm 1.2670 (1.7451/0.8037)	mem 16099MB
[2025-01-18 05:15:29 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][160/312]	eta 0:01:13 lr 0.001906	time 0.7339 (0.4808)	model_time 0.7334 (0.4677)	loss 2.7552 (3.2767)	grad_norm 3.1413 (1.7814/0.8136)	mem 16099MB
[2025-01-18 05:15:34 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][170/312]	eta 0:01:08 lr 0.001905	time 0.4526 (0.4809)	model_time 0.4524 (0.4686)	loss 3.2759 (3.2679)	grad_norm 2.0664 (1.7896/0.8006)	mem 16099MB
[2025-01-18 05:15:38 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][180/312]	eta 0:01:03 lr 0.001904	time 0.4645 (0.4799)	model_time 0.4643 (0.4683)	loss 2.4726 (3.2563)	grad_norm 1.9253 (1.8207/0.8165)	mem 16099MB
[2025-01-18 05:15:43 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][190/312]	eta 0:00:58 lr 0.001904	time 0.4506 (0.4793)	model_time 0.4501 (0.4682)	loss 2.6334 (3.2441)	grad_norm 1.2001 (1.8280/0.8123)	mem 16099MB
[2025-01-18 05:15:48 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][200/312]	eta 0:00:53 lr 0.001903	time 0.4430 (0.4783)	model_time 0.4428 (0.4678)	loss 3.4760 (3.2553)	grad_norm 1.5717 (1.8152/0.8003)	mem 16099MB
[2025-01-18 05:15:52 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][210/312]	eta 0:00:48 lr 0.001902	time 0.5134 (0.4777)	model_time 0.5132 (0.4676)	loss 3.8413 (3.2507)	grad_norm 1.7139 (1.8130/0.7899)	mem 16099MB
[2025-01-18 05:15:57 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][220/312]	eta 0:00:43 lr 0.001902	time 0.4610 (0.4770)	model_time 0.4608 (0.4674)	loss 2.7355 (3.2484)	grad_norm 2.0281 (1.7864/0.7840)	mem 16099MB
[2025-01-18 05:16:01 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][230/312]	eta 0:00:39 lr 0.001901	time 0.4513 (0.4764)	model_time 0.4509 (0.4671)	loss 3.2696 (3.2458)	grad_norm 2.2176 (1.7777/0.7757)	mem 16099MB
[2025-01-18 05:16:06 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][240/312]	eta 0:00:34 lr 0.001900	time 0.4491 (0.4759)	model_time 0.4490 (0.4670)	loss 3.1133 (3.2402)	grad_norm 2.1027 (1.7864/0.7870)	mem 16099MB
[2025-01-18 05:16:11 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][250/312]	eta 0:00:29 lr 0.001900	time 0.4571 (0.4761)	model_time 0.4569 (0.4675)	loss 3.7183 (3.2420)	grad_norm 0.9650 (1.7995/0.7867)	mem 16099MB
[2025-01-18 05:16:15 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][260/312]	eta 0:00:24 lr 0.001899	time 0.4418 (0.4751)	model_time 0.4416 (0.4669)	loss 2.8114 (3.2460)	grad_norm 1.9218 (1.7806/0.7784)	mem 16099MB
[2025-01-18 05:16:20 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][270/312]	eta 0:00:19 lr 0.001898	time 0.4448 (0.4758)	model_time 0.4446 (0.4679)	loss 2.9687 (3.2498)	grad_norm 3.4584 (1.7773/0.7750)	mem 16099MB
[2025-01-18 05:16:25 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][280/312]	eta 0:00:15 lr 0.001898	time 0.4490 (0.4752)	model_time 0.4485 (0.4675)	loss 3.8063 (3.2404)	grad_norm 2.3017 (1.7804/0.7693)	mem 16099MB
[2025-01-18 05:16:30 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][290/312]	eta 0:00:10 lr 0.001897	time 0.4475 (0.4747)	model_time 0.4474 (0.4673)	loss 3.8978 (3.2463)	grad_norm 1.1040 (1.7700/0.7642)	mem 16099MB
[2025-01-18 05:16:34 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][300/312]	eta 0:00:05 lr 0.001896	time 0.4377 (0.4742)	model_time 0.4376 (0.4670)	loss 3.1869 (3.2374)	grad_norm 1.2924 (1.7703/0.7638)	mem 16099MB
[2025-01-18 05:16:39 internimage_t_1k_224] (main.py 510): INFO Train: [155/300][310/312]	eta 0:00:00 lr 0.001896	time 0.4386 (0.4740)	model_time 0.4385 (0.4671)	loss 3.6822 (3.2290)	grad_norm 1.2235 (1.7772/0.7715)	mem 16099MB
[2025-01-18 05:16:39 internimage_t_1k_224] (main.py 519): INFO EPOCH 155 training takes 0:02:27
[2025-01-18 05:16:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_155.pth saving......
[2025-01-18 05:16:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_155.pth saved !!!
[2025-01-18 05:16:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.239 (7.239)	Loss 0.8387 (0.8387)	Acc@1 82.642 (82.642)	Acc@5 96.436 (96.436)	Mem 16099MB
[2025-01-18 05:16:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.001)	Loss 1.1575 (0.9825)	Acc@1 74.536 (79.470)	Acc@5 92.725 (94.800)	Mem 16099MB
[2025-01-18 05:16:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:155] * Acc@1 79.373 Acc@5 94.818
[2025-01-18 05:16:52 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.4%
[2025-01-18 05:16:52 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.42%
[2025-01-18 05:17:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.377 (8.377)	Loss 0.8106 (0.8106)	Acc@1 84.131 (84.131)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 05:17:04 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.125)	Loss 1.1127 (0.9431)	Acc@1 75.684 (80.897)	Acc@5 93.945 (95.619)	Mem 16099MB
[2025-01-18 05:17:04 internimage_t_1k_224] (main.py 575): INFO [Epoch:155] * Acc@1 80.786 Acc@5 95.641
[2025-01-18 05:17:04 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.8%
[2025-01-18 05:17:04 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:17:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:17:06 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.79%
[2025-01-18 05:17:08 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][0/312]	eta 0:13:42 lr 0.001896	time 2.6355 (2.6355)	model_time 0.4535 (0.4535)	loss 3.4422 (3.4422)	grad_norm 1.3789 (1.3789/0.0000)	mem 16099MB
[2025-01-18 05:17:13 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][10/312]	eta 0:03:26 lr 0.001895	time 0.4400 (0.6833)	model_time 0.4396 (0.4846)	loss 3.8424 (3.4597)	grad_norm 2.2733 (1.7729/0.5460)	mem 16099MB
[2025-01-18 05:17:18 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][20/312]	eta 0:02:49 lr 0.001894	time 0.4508 (0.5819)	model_time 0.4506 (0.4777)	loss 2.5251 (3.2655)	grad_norm 3.6040 (2.0484/0.7648)	mem 16099MB
[2025-01-18 05:17:22 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][30/312]	eta 0:02:33 lr 0.001894	time 0.4495 (0.5434)	model_time 0.4493 (0.4727)	loss 3.5216 (3.1865)	grad_norm 1.9266 (2.1106/0.7140)	mem 16099MB
[2025-01-18 05:17:27 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][40/312]	eta 0:02:21 lr 0.001893	time 0.4628 (0.5216)	model_time 0.4627 (0.4681)	loss 2.7640 (3.1597)	grad_norm 1.7275 (2.0919/0.8551)	mem 16099MB
[2025-01-18 05:17:32 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][50/312]	eta 0:02:13 lr 0.001892	time 0.4637 (0.5093)	model_time 0.4635 (0.4662)	loss 3.7189 (3.1451)	grad_norm 1.3054 (1.9432/0.8396)	mem 16099MB
[2025-01-18 05:17:36 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][60/312]	eta 0:02:06 lr 0.001892	time 0.4441 (0.5009)	model_time 0.4440 (0.4648)	loss 3.4477 (3.1463)	grad_norm 1.1461 (1.8609/0.8044)	mem 16099MB
[2025-01-18 05:17:41 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][70/312]	eta 0:02:00 lr 0.001891	time 0.4594 (0.4996)	model_time 0.4590 (0.4685)	loss 3.1853 (3.1547)	grad_norm 1.2278 (1.8319/0.7580)	mem 16099MB
[2025-01-18 05:17:46 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][80/312]	eta 0:01:54 lr 0.001890	time 0.4516 (0.4954)	model_time 0.4512 (0.4681)	loss 2.8849 (3.1739)	grad_norm 1.2159 (1.7885/0.7255)	mem 16099MB
[2025-01-18 05:17:50 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][90/312]	eta 0:01:49 lr 0.001890	time 0.4404 (0.4926)	model_time 0.4400 (0.4683)	loss 3.6939 (3.2029)	grad_norm 3.3282 (1.8089/0.7274)	mem 16099MB
[2025-01-18 05:17:55 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][100/312]	eta 0:01:43 lr 0.001889	time 0.5703 (0.4899)	model_time 0.5697 (0.4680)	loss 3.2187 (3.1920)	grad_norm 1.0730 (1.7643/0.7152)	mem 16099MB
[2025-01-18 05:18:00 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][110/312]	eta 0:01:38 lr 0.001888	time 0.4603 (0.4900)	model_time 0.4598 (0.4700)	loss 2.3384 (3.1956)	grad_norm 1.2553 (1.7590/0.7019)	mem 16099MB
[2025-01-18 05:18:05 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][120/312]	eta 0:01:33 lr 0.001888	time 0.4801 (0.4880)	model_time 0.4799 (0.4696)	loss 3.3527 (3.1811)	grad_norm 1.2575 (1.8184/0.7663)	mem 16099MB
[2025-01-18 05:18:09 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][130/312]	eta 0:01:28 lr 0.001887	time 0.4522 (0.4861)	model_time 0.4520 (0.4691)	loss 3.2127 (3.1882)	grad_norm 2.0531 (1.8621/0.7986)	mem 16099MB
[2025-01-18 05:18:14 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][140/312]	eta 0:01:23 lr 0.001886	time 0.4419 (0.4865)	model_time 0.4417 (0.4707)	loss 3.5546 (3.2019)	grad_norm 2.8928 (1.8721/0.8003)	mem 16099MB
[2025-01-18 05:18:19 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][150/312]	eta 0:01:18 lr 0.001886	time 0.4852 (0.4855)	model_time 0.4847 (0.4707)	loss 2.3827 (3.2027)	grad_norm 0.9047 (1.8848/0.8191)	mem 16099MB
[2025-01-18 05:18:24 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][160/312]	eta 0:01:13 lr 0.001885	time 0.4407 (0.4845)	model_time 0.4405 (0.4706)	loss 3.6137 (3.1891)	grad_norm 2.7609 (1.8861/0.8113)	mem 16099MB
[2025-01-18 05:18:28 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][170/312]	eta 0:01:08 lr 0.001884	time 0.4524 (0.4837)	model_time 0.4519 (0.4706)	loss 2.5673 (3.1722)	grad_norm 2.7700 (1.8809/0.8031)	mem 16099MB
[2025-01-18 05:18:33 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][180/312]	eta 0:01:03 lr 0.001884	time 0.4770 (0.4828)	model_time 0.4769 (0.4704)	loss 2.5727 (3.1674)	grad_norm 1.6136 (1.8606/0.7919)	mem 16099MB
[2025-01-18 05:18:37 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][190/312]	eta 0:00:58 lr 0.001883	time 0.4491 (0.4811)	model_time 0.4489 (0.4693)	loss 2.9261 (3.1712)	grad_norm 3.6038 (1.8605/0.7901)	mem 16099MB
[2025-01-18 05:18:42 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][200/312]	eta 0:00:53 lr 0.001882	time 0.5652 (0.4803)	model_time 0.5650 (0.4691)	loss 3.7648 (3.1738)	grad_norm 1.9102 (1.8677/0.7780)	mem 16099MB
[2025-01-18 05:18:47 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][210/312]	eta 0:00:48 lr 0.001882	time 0.4606 (0.4790)	model_time 0.4602 (0.4683)	loss 3.7916 (3.1906)	grad_norm 1.0053 (1.8551/0.7686)	mem 16099MB
[2025-01-18 05:18:51 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][220/312]	eta 0:00:43 lr 0.001881	time 0.4501 (0.4780)	model_time 0.4500 (0.4677)	loss 3.9026 (3.2033)	grad_norm 2.5406 (1.8416/0.7600)	mem 16099MB
[2025-01-18 05:18:56 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][230/312]	eta 0:00:39 lr 0.001880	time 0.4394 (0.4769)	model_time 0.4393 (0.4671)	loss 3.4580 (3.2073)	grad_norm 1.9302 (1.8304/0.7472)	mem 16099MB
[2025-01-18 05:19:00 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][240/312]	eta 0:00:34 lr 0.001880	time 0.5452 (0.4766)	model_time 0.5451 (0.4672)	loss 3.2852 (3.2210)	grad_norm 0.8578 (1.8114/0.7412)	mem 16099MB
[2025-01-18 05:19:05 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][250/312]	eta 0:00:29 lr 0.001879	time 0.4503 (0.4766)	model_time 0.4502 (0.4675)	loss 3.6150 (3.2312)	grad_norm 2.5509 (1.8066/0.7357)	mem 16099MB
[2025-01-18 05:19:10 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][260/312]	eta 0:00:24 lr 0.001878	time 0.4514 (0.4758)	model_time 0.4510 (0.4671)	loss 3.6242 (3.2293)	grad_norm 2.5647 (1.7954/0.7295)	mem 16099MB
[2025-01-18 05:19:14 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][270/312]	eta 0:00:19 lr 0.001878	time 0.4514 (0.4752)	model_time 0.4509 (0.4668)	loss 3.4652 (3.2343)	grad_norm 1.0860 (1.7999/0.7288)	mem 16099MB
[2025-01-18 05:19:19 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][280/312]	eta 0:00:15 lr 0.001877	time 0.4496 (0.4745)	model_time 0.4492 (0.4664)	loss 2.2545 (3.2191)	grad_norm 1.2554 (1.8134/0.7605)	mem 16099MB
[2025-01-18 05:19:24 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][290/312]	eta 0:00:10 lr 0.001876	time 0.4674 (0.4742)	model_time 0.4672 (0.4664)	loss 2.8107 (3.2232)	grad_norm 1.5617 (1.8020/0.7512)	mem 16099MB
[2025-01-18 05:19:28 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][300/312]	eta 0:00:05 lr 0.001876	time 0.4374 (0.4733)	model_time 0.4373 (0.4657)	loss 2.6515 (3.2261)	grad_norm 2.1310 (1.7958/0.7480)	mem 16099MB
[2025-01-18 05:19:33 internimage_t_1k_224] (main.py 510): INFO Train: [156/300][310/312]	eta 0:00:00 lr 0.001875	time 0.4378 (0.4725)	model_time 0.4377 (0.4651)	loss 3.9027 (3.2353)	grad_norm 2.3894 (1.7962/0.7486)	mem 16099MB
[2025-01-18 05:19:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 156 training takes 0:02:27
[2025-01-18 05:19:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_156.pth saving......
[2025-01-18 05:19:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_156.pth saved !!!
[2025-01-18 05:19:41 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.296 (7.296)	Loss 0.8402 (0.8402)	Acc@1 82.764 (82.764)	Acc@5 96.240 (96.240)	Mem 16099MB
[2025-01-18 05:19:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.994)	Loss 1.1188 (0.9596)	Acc@1 75.024 (79.610)	Acc@5 93.457 (94.993)	Mem 16099MB
[2025-01-18 05:19:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:156] * Acc@1 79.471 Acc@5 95.010
[2025-01-18 05:19:45 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.5%
[2025-01-18 05:19:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 05:19:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 05:19:46 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.47%
[2025-01-18 05:19:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.597 (7.597)	Loss 0.8108 (0.8108)	Acc@1 84.033 (84.033)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 05:19:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.011)	Loss 1.1119 (0.9431)	Acc@1 75.757 (80.915)	Acc@5 93.945 (95.643)	Mem 16099MB
[2025-01-18 05:19:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:156] * Acc@1 80.804 Acc@5 95.669
[2025-01-18 05:19:58 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.8%
[2025-01-18 05:19:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:19:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:19:59 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.80%
[2025-01-18 05:20:02 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][0/312]	eta 0:13:58 lr 0.001875	time 2.6882 (2.6882)	model_time 0.5988 (0.5988)	loss 3.5065 (3.5065)	grad_norm 1.1074 (1.1074/0.0000)	mem 16099MB
[2025-01-18 05:20:06 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][10/312]	eta 0:03:21 lr 0.001874	time 0.5315 (0.6659)	model_time 0.5311 (0.4756)	loss 3.3595 (3.1107)	grad_norm 1.6799 (2.1330/1.0817)	mem 16099MB
[2025-01-18 05:20:11 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][20/312]	eta 0:02:49 lr 0.001874	time 0.5447 (0.5800)	model_time 0.5445 (0.4802)	loss 3.7006 (3.0719)	grad_norm 1.1003 (1.9249/0.8842)	mem 16099MB
[2025-01-18 05:20:16 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][30/312]	eta 0:02:32 lr 0.001873	time 0.4499 (0.5415)	model_time 0.4495 (0.4738)	loss 3.4524 (3.2088)	grad_norm 1.5340 (1.7977/0.7866)	mem 16099MB
[2025-01-18 05:20:20 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][40/312]	eta 0:02:21 lr 0.001872	time 0.4393 (0.5218)	model_time 0.4392 (0.4705)	loss 3.1841 (3.2241)	grad_norm 2.0979 (2.2369/1.4006)	mem 16099MB
[2025-01-18 05:20:25 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][50/312]	eta 0:02:14 lr 0.001872	time 0.4900 (0.5141)	model_time 0.4896 (0.4728)	loss 3.1388 (3.1981)	grad_norm 1.4617 (2.1512/1.3068)	mem 16099MB
[2025-01-18 05:20:30 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][60/312]	eta 0:02:07 lr 0.001871	time 0.4739 (0.5069)	model_time 0.4737 (0.4724)	loss 3.5617 (3.1733)	grad_norm 1.4824 (2.0263/1.2423)	mem 16099MB
[2025-01-18 05:20:35 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][70/312]	eta 0:02:01 lr 0.001870	time 0.4561 (0.5004)	model_time 0.4559 (0.4706)	loss 3.0819 (3.1868)	grad_norm 1.0658 (1.9650/1.1712)	mem 16099MB
[2025-01-18 05:20:39 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][80/312]	eta 0:01:55 lr 0.001870	time 0.4492 (0.4986)	model_time 0.4490 (0.4725)	loss 3.2386 (3.1911)	grad_norm 0.8970 (1.9409/1.1294)	mem 16099MB
[2025-01-18 05:20:44 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][90/312]	eta 0:01:49 lr 0.001869	time 0.4486 (0.4936)	model_time 0.4482 (0.4703)	loss 3.1945 (3.1681)	grad_norm 1.7744 (2.0128/1.1541)	mem 16099MB
[2025-01-18 05:20:49 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][100/312]	eta 0:01:43 lr 0.001868	time 0.4777 (0.4903)	model_time 0.4773 (0.4692)	loss 2.9336 (3.1647)	grad_norm 1.8115 (1.9805/1.1081)	mem 16099MB
[2025-01-18 05:20:53 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][110/312]	eta 0:01:38 lr 0.001868	time 0.4428 (0.4890)	model_time 0.4423 (0.4698)	loss 3.2792 (3.1843)	grad_norm 2.5438 (1.9409/1.0724)	mem 16099MB
[2025-01-18 05:20:58 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][120/312]	eta 0:01:33 lr 0.001867	time 0.4590 (0.4870)	model_time 0.4588 (0.4694)	loss 3.2181 (3.1815)	grad_norm 1.4469 (1.9365/1.0598)	mem 16099MB
[2025-01-18 05:21:03 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][130/312]	eta 0:01:28 lr 0.001866	time 0.4839 (0.4849)	model_time 0.4837 (0.4685)	loss 3.3086 (3.1949)	grad_norm 3.2578 (1.9300/1.0370)	mem 16099MB
[2025-01-18 05:21:07 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][140/312]	eta 0:01:23 lr 0.001866	time 0.5470 (0.4836)	model_time 0.5468 (0.4684)	loss 3.3244 (3.1757)	grad_norm 2.0538 (1.9049/1.0121)	mem 16099MB
[2025-01-18 05:21:12 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][150/312]	eta 0:01:18 lr 0.001865	time 0.5286 (0.4826)	model_time 0.5282 (0.4684)	loss 3.2935 (3.1727)	grad_norm 1.7274 (1.8931/1.0179)	mem 16099MB
[2025-01-18 05:21:16 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][160/312]	eta 0:01:13 lr 0.001864	time 0.4684 (0.4808)	model_time 0.4678 (0.4674)	loss 2.5960 (3.1726)	grad_norm 2.7960 (1.8765/0.9999)	mem 16099MB
[2025-01-18 05:21:21 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][170/312]	eta 0:01:08 lr 0.001864	time 0.4532 (0.4795)	model_time 0.4530 (0.4669)	loss 3.5574 (3.1724)	grad_norm 1.2920 (1.8827/0.9852)	mem 16099MB
[2025-01-18 05:21:26 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][180/312]	eta 0:01:03 lr 0.001863	time 0.4509 (0.4784)	model_time 0.4507 (0.4665)	loss 3.6872 (3.1791)	grad_norm 1.0011 (1.9010/1.0211)	mem 16099MB
[2025-01-18 05:21:30 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][190/312]	eta 0:00:58 lr 0.001862	time 0.4497 (0.4774)	model_time 0.4493 (0.4661)	loss 3.4576 (3.1862)	grad_norm 1.4227 (1.9016/0.9990)	mem 16099MB
[2025-01-18 05:21:35 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][200/312]	eta 0:00:53 lr 0.001862	time 0.4687 (0.4767)	model_time 0.4685 (0.4659)	loss 4.0206 (3.1921)	grad_norm 1.4272 (1.8754/0.9822)	mem 16099MB
[2025-01-18 05:21:40 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][210/312]	eta 0:00:48 lr 0.001861	time 0.4615 (0.4762)	model_time 0.4611 (0.4659)	loss 3.3880 (3.2040)	grad_norm 1.0626 (1.8592/0.9677)	mem 16099MB
[2025-01-18 05:21:44 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][220/312]	eta 0:00:43 lr 0.001860	time 0.4499 (0.4754)	model_time 0.4497 (0.4655)	loss 3.9015 (3.2030)	grad_norm 1.7060 (1.8405/0.9535)	mem 16099MB
[2025-01-18 05:21:49 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][230/312]	eta 0:00:38 lr 0.001860	time 0.4428 (0.4749)	model_time 0.4426 (0.4655)	loss 3.4914 (3.2132)	grad_norm 1.0937 (1.8325/0.9451)	mem 16099MB
[2025-01-18 05:21:53 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][240/312]	eta 0:00:34 lr 0.001859	time 0.4400 (0.4743)	model_time 0.4396 (0.4653)	loss 3.7586 (3.2181)	grad_norm 2.1788 (1.8360/0.9512)	mem 16099MB
[2025-01-18 05:21:58 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][250/312]	eta 0:00:29 lr 0.001858	time 0.4452 (0.4746)	model_time 0.4450 (0.4659)	loss 3.6216 (3.2150)	grad_norm 2.3485 (1.8494/0.9751)	mem 16099MB
[2025-01-18 05:22:03 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][260/312]	eta 0:00:24 lr 0.001858	time 0.4531 (0.4737)	model_time 0.4529 (0.4653)	loss 3.5135 (3.2051)	grad_norm 2.5651 (1.8414/0.9677)	mem 16099MB
[2025-01-18 05:22:07 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][270/312]	eta 0:00:19 lr 0.001857	time 0.4858 (0.4732)	model_time 0.4852 (0.4651)	loss 3.6015 (3.2010)	grad_norm 1.8504 (1.8674/0.9953)	mem 16099MB
[2025-01-18 05:22:12 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][280/312]	eta 0:00:15 lr 0.001856	time 0.4445 (0.4737)	model_time 0.4443 (0.4659)	loss 4.0542 (3.2044)	grad_norm 2.2220 (1.8677/0.9899)	mem 16099MB
[2025-01-18 05:22:17 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][290/312]	eta 0:00:10 lr 0.001856	time 0.4549 (0.4736)	model_time 0.4544 (0.4660)	loss 3.2944 (3.2140)	grad_norm 1.3597 (1.8463/0.9813)	mem 16099MB
[2025-01-18 05:22:21 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][300/312]	eta 0:00:05 lr 0.001855	time 0.4398 (0.4730)	model_time 0.4397 (0.4657)	loss 2.2320 (3.2090)	grad_norm 1.3973 (1.8283/0.9734)	mem 16099MB
[2025-01-18 05:22:26 internimage_t_1k_224] (main.py 510): INFO Train: [157/300][310/312]	eta 0:00:00 lr 0.001854	time 0.4417 (0.4728)	model_time 0.4416 (0.4657)	loss 2.6410 (3.2087)	grad_norm 2.8413 (1.8105/0.9554)	mem 16099MB
[2025-01-18 05:22:27 internimage_t_1k_224] (main.py 519): INFO EPOCH 157 training takes 0:02:27
[2025-01-18 05:22:27 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_157.pth saving......
[2025-01-18 05:22:28 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_157.pth saved !!!
[2025-01-18 05:22:35 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.422 (7.422)	Loss 0.7803 (0.7803)	Acc@1 82.422 (82.422)	Acc@5 96.753 (96.753)	Mem 16099MB
[2025-01-18 05:22:39 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.000)	Loss 1.1139 (0.9167)	Acc@1 74.756 (79.843)	Acc@5 93.457 (95.133)	Mem 16099MB
[2025-01-18 05:22:39 internimage_t_1k_224] (main.py 575): INFO [Epoch:157] * Acc@1 79.698 Acc@5 95.144
[2025-01-18 05:22:39 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.7%
[2025-01-18 05:22:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 05:22:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 05:22:40 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.70%
[2025-01-18 05:22:47 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.213 (7.213)	Loss 0.8107 (0.8107)	Acc@1 84.106 (84.106)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 05:22:51 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.983)	Loss 1.1104 (0.9428)	Acc@1 75.952 (80.968)	Acc@5 94.019 (95.648)	Mem 16099MB
[2025-01-18 05:22:51 internimage_t_1k_224] (main.py 575): INFO [Epoch:157] * Acc@1 80.856 Acc@5 95.673
[2025-01-18 05:22:51 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.9%
[2025-01-18 05:22:51 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:22:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:22:52 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.86%
[2025-01-18 05:22:55 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][0/312]	eta 0:14:16 lr 0.001854	time 2.7441 (2.7441)	model_time 0.4658 (0.4658)	loss 4.0574 (4.0574)	grad_norm 2.8032 (2.8032/0.0000)	mem 16099MB
[2025-01-18 05:23:00 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][10/312]	eta 0:03:22 lr 0.001854	time 0.4460 (0.6709)	model_time 0.4459 (0.4634)	loss 3.1317 (3.4840)	grad_norm 2.7737 (2.5343/1.3964)	mem 16099MB
[2025-01-18 05:23:04 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][20/312]	eta 0:02:46 lr 0.001853	time 0.4388 (0.5704)	model_time 0.4384 (0.4616)	loss 2.9494 (3.2413)	grad_norm 1.0740 (2.3899/1.1448)	mem 16099MB
[2025-01-18 05:23:09 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][30/312]	eta 0:02:31 lr 0.001852	time 0.4465 (0.5362)	model_time 0.4462 (0.4624)	loss 2.7422 (3.1800)	grad_norm 1.3074 (2.3428/1.0266)	mem 16099MB
[2025-01-18 05:23:14 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][40/312]	eta 0:02:21 lr 0.001852	time 0.4539 (0.5187)	model_time 0.4534 (0.4628)	loss 2.2952 (3.1943)	grad_norm 0.8553 (2.1098/1.0329)	mem 16099MB
[2025-01-18 05:23:18 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][50/312]	eta 0:02:12 lr 0.001851	time 0.4584 (0.5075)	model_time 0.4582 (0.4625)	loss 3.4177 (3.2279)	grad_norm 2.2074 (2.0301/0.9637)	mem 16099MB
[2025-01-18 05:23:23 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][60/312]	eta 0:02:05 lr 0.001850	time 0.4664 (0.4987)	model_time 0.4661 (0.4610)	loss 3.6491 (3.2394)	grad_norm 1.3444 (2.0077/0.9416)	mem 16099MB
[2025-01-18 05:23:28 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][70/312]	eta 0:02:00 lr 0.001850	time 0.5583 (0.4963)	model_time 0.5582 (0.4638)	loss 3.7866 (3.2445)	grad_norm 1.4087 (1.9596/0.9027)	mem 16099MB
[2025-01-18 05:23:32 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][80/312]	eta 0:01:54 lr 0.001849	time 0.4494 (0.4956)	model_time 0.4492 (0.4671)	loss 2.1388 (3.2636)	grad_norm 2.3096 (1.9411/0.8739)	mem 16099MB
[2025-01-18 05:23:37 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][90/312]	eta 0:01:49 lr 0.001848	time 0.4480 (0.4913)	model_time 0.4479 (0.4659)	loss 3.4731 (3.2801)	grad_norm 2.7452 (1.8948/0.8579)	mem 16099MB
[2025-01-18 05:23:42 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][100/312]	eta 0:01:43 lr 0.001848	time 0.4600 (0.4887)	model_time 0.4599 (0.4657)	loss 3.6365 (3.3100)	grad_norm 2.0764 (1.9527/0.8548)	mem 16099MB
[2025-01-18 05:23:46 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][110/312]	eta 0:01:38 lr 0.001847	time 0.4607 (0.4872)	model_time 0.4602 (0.4663)	loss 2.7455 (3.3018)	grad_norm 3.1153 (1.9885/0.8725)	mem 16099MB
[2025-01-18 05:23:51 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][120/312]	eta 0:01:33 lr 0.001846	time 0.4526 (0.4854)	model_time 0.4521 (0.4662)	loss 3.6573 (3.2844)	grad_norm 1.4380 (2.0258/0.8893)	mem 16099MB
[2025-01-18 05:23:56 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][130/312]	eta 0:01:27 lr 0.001846	time 0.4625 (0.4833)	model_time 0.4622 (0.4655)	loss 3.2400 (3.2734)	grad_norm 2.8155 (1.9975/0.8772)	mem 16099MB
[2025-01-18 05:24:00 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][140/312]	eta 0:01:22 lr 0.001845	time 0.5536 (0.4821)	model_time 0.5535 (0.4656)	loss 2.3690 (3.2656)	grad_norm 3.0669 (1.9967/0.8631)	mem 16099MB
[2025-01-18 05:24:05 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][150/312]	eta 0:01:17 lr 0.001844	time 0.4478 (0.4802)	model_time 0.4473 (0.4647)	loss 2.1715 (3.2559)	grad_norm 1.8440 (2.0051/0.8596)	mem 16099MB
[2025-01-18 05:24:09 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][160/312]	eta 0:01:12 lr 0.001844	time 0.4501 (0.4791)	model_time 0.4499 (0.4645)	loss 3.1854 (3.2646)	grad_norm 2.9724 (1.9923/0.8554)	mem 16099MB
[2025-01-18 05:24:14 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][170/312]	eta 0:01:07 lr 0.001843	time 0.4395 (0.4775)	model_time 0.4393 (0.4638)	loss 3.3554 (3.2615)	grad_norm 2.8830 (1.9889/0.8491)	mem 16099MB
[2025-01-18 05:24:19 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][180/312]	eta 0:01:02 lr 0.001842	time 0.4461 (0.4765)	model_time 0.4459 (0.4636)	loss 3.5368 (3.2520)	grad_norm 1.5391 (1.9728/0.8361)	mem 16099MB
[2025-01-18 05:24:23 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][190/312]	eta 0:00:58 lr 0.001842	time 0.4499 (0.4764)	model_time 0.4497 (0.4641)	loss 3.4474 (3.2395)	grad_norm 1.5622 (1.9742/0.8243)	mem 16099MB
[2025-01-18 05:24:28 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][200/312]	eta 0:00:53 lr 0.001841	time 0.4953 (0.4767)	model_time 0.4948 (0.4650)	loss 3.5897 (3.2330)	grad_norm 1.3756 (1.9515/0.8226)	mem 16099MB
[2025-01-18 05:24:33 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][210/312]	eta 0:00:48 lr 0.001840	time 0.4491 (0.4766)	model_time 0.4489 (0.4654)	loss 2.8446 (3.2317)	grad_norm 1.0428 (1.9131/0.8233)	mem 16099MB
[2025-01-18 05:24:37 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][220/312]	eta 0:00:43 lr 0.001840	time 0.4525 (0.4757)	model_time 0.4523 (0.4650)	loss 3.2106 (3.2373)	grad_norm 1.0264 (1.9128/0.8265)	mem 16099MB
[2025-01-18 05:24:42 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][230/312]	eta 0:00:39 lr 0.001839	time 0.4353 (0.4761)	model_time 0.4351 (0.4659)	loss 2.5436 (3.2280)	grad_norm 0.8217 (1.9137/0.8221)	mem 16099MB
[2025-01-18 05:24:47 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][240/312]	eta 0:00:34 lr 0.001838	time 0.5717 (0.4760)	model_time 0.5712 (0.4662)	loss 2.8826 (3.2184)	grad_norm 2.6186 (1.9045/0.8168)	mem 16099MB
[2025-01-18 05:24:52 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][250/312]	eta 0:00:29 lr 0.001838	time 0.4506 (0.4758)	model_time 0.4504 (0.4663)	loss 2.1658 (3.2184)	grad_norm 3.9224 (1.9101/0.8153)	mem 16099MB
[2025-01-18 05:24:56 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][260/312]	eta 0:00:24 lr 0.001837	time 0.4861 (0.4751)	model_time 0.4859 (0.4660)	loss 2.9201 (3.2172)	grad_norm 1.4542 (1.9198/0.8258)	mem 16099MB
[2025-01-18 05:25:01 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][270/312]	eta 0:00:19 lr 0.001836	time 0.4554 (0.4745)	model_time 0.4552 (0.4658)	loss 4.0721 (3.2081)	grad_norm 1.2272 (1.9206/0.8324)	mem 16099MB
[2025-01-18 05:25:05 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][280/312]	eta 0:00:15 lr 0.001836	time 0.4497 (0.4738)	model_time 0.4495 (0.4654)	loss 3.6566 (3.2094)	grad_norm 1.4378 (1.9278/0.8446)	mem 16099MB
[2025-01-18 05:25:10 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][290/312]	eta 0:00:10 lr 0.001835	time 0.4449 (0.4734)	model_time 0.4447 (0.4652)	loss 2.9055 (3.2055)	grad_norm 0.9078 (1.8980/0.8469)	mem 16099MB
[2025-01-18 05:25:15 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][300/312]	eta 0:00:05 lr 0.001834	time 0.4378 (0.4729)	model_time 0.4377 (0.4650)	loss 3.4197 (3.2125)	grad_norm 3.0661 (1.8906/0.8428)	mem 16099MB
[2025-01-18 05:25:19 internimage_t_1k_224] (main.py 510): INFO Train: [158/300][310/312]	eta 0:00:00 lr 0.001834	time 0.4386 (0.4719)	model_time 0.4385 (0.4642)	loss 2.9504 (3.2053)	grad_norm 1.2767 (1.9026/0.8457)	mem 16099MB
[2025-01-18 05:25:19 internimage_t_1k_224] (main.py 519): INFO EPOCH 158 training takes 0:02:27
[2025-01-18 05:25:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_158.pth saving......
[2025-01-18 05:25:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_158.pth saved !!!
[2025-01-18 05:25:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.196 (7.196)	Loss 0.8289 (0.8289)	Acc@1 83.252 (83.252)	Acc@5 96.680 (96.680)	Mem 16099MB
[2025-01-18 05:25:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.108 (0.980)	Loss 1.1232 (0.9648)	Acc@1 75.342 (79.707)	Acc@5 93.457 (94.988)	Mem 16099MB
[2025-01-18 05:25:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:158] * Acc@1 79.553 Acc@5 95.034
[2025-01-18 05:25:32 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.6%
[2025-01-18 05:25:32 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.70%
[2025-01-18 05:25:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.229 (8.229)	Loss 0.8110 (0.8110)	Acc@1 84.155 (84.155)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 05:25:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.101)	Loss 1.1094 (0.9426)	Acc@1 76.074 (81.015)	Acc@5 94.043 (95.650)	Mem 16099MB
[2025-01-18 05:25:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:158] * Acc@1 80.900 Acc@5 95.677
[2025-01-18 05:25:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.9%
[2025-01-18 05:25:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:25:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:25:45 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.90%
[2025-01-18 05:25:48 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][0/312]	eta 0:13:50 lr 0.001834	time 2.6629 (2.6629)	model_time 0.4805 (0.4805)	loss 4.0906 (4.0906)	grad_norm 2.4336 (2.4336/0.0000)	mem 16099MB
[2025-01-18 05:25:53 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][10/312]	eta 0:03:24 lr 0.001833	time 0.4449 (0.6766)	model_time 0.4447 (0.4780)	loss 2.0674 (3.2058)	grad_norm 1.1285 (1.8433/0.5507)	mem 16099MB
[2025-01-18 05:25:57 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][20/312]	eta 0:02:49 lr 0.001832	time 0.4542 (0.5800)	model_time 0.4540 (0.4755)	loss 3.0327 (3.1271)	grad_norm 1.8750 (1.6966/0.4678)	mem 16099MB
[2025-01-18 05:26:02 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][30/312]	eta 0:02:32 lr 0.001832	time 0.4495 (0.5420)	model_time 0.4494 (0.4711)	loss 2.4259 (3.1124)	grad_norm 2.7451 (1.7724/0.5752)	mem 16099MB
[2025-01-18 05:26:07 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][40/312]	eta 0:02:22 lr 0.001831	time 0.4591 (0.5240)	model_time 0.4588 (0.4703)	loss 3.3958 (3.1754)	grad_norm 1.7595 (1.8481/0.6521)	mem 16099MB
[2025-01-18 05:26:12 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][50/312]	eta 0:02:15 lr 0.001830	time 0.4682 (0.5159)	model_time 0.4680 (0.4726)	loss 4.0696 (3.1866)	grad_norm 1.2331 (1.8527/0.6970)	mem 16099MB
[2025-01-18 05:26:16 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][60/312]	eta 0:02:09 lr 0.001830	time 0.4489 (0.5120)	model_time 0.4487 (0.4757)	loss 2.6794 (3.1623)	grad_norm 1.4736 (1.8643/0.7186)	mem 16099MB
[2025-01-18 05:26:21 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][70/312]	eta 0:02:02 lr 0.001829	time 0.4534 (0.5055)	model_time 0.4532 (0.4743)	loss 2.2952 (3.1708)	grad_norm 1.4889 (1.8495/0.6818)	mem 16099MB
[2025-01-18 05:26:26 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][80/312]	eta 0:01:56 lr 0.001828	time 0.5397 (0.5014)	model_time 0.5395 (0.4740)	loss 3.6789 (3.2091)	grad_norm 1.3636 (1.7950/0.6825)	mem 16099MB
[2025-01-18 05:26:30 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][90/312]	eta 0:01:50 lr 0.001828	time 0.4520 (0.4963)	model_time 0.4518 (0.4719)	loss 3.3562 (3.1993)	grad_norm 2.5116 (1.8489/0.6995)	mem 16099MB
[2025-01-18 05:26:35 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][100/312]	eta 0:01:44 lr 0.001827	time 0.4408 (0.4951)	model_time 0.4406 (0.4731)	loss 2.9272 (3.1779)	grad_norm 1.4609 (1.8856/0.7707)	mem 16099MB
[2025-01-18 05:26:40 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][110/312]	eta 0:01:39 lr 0.001826	time 0.4923 (0.4923)	model_time 0.4921 (0.4722)	loss 3.4049 (3.1584)	grad_norm 1.7427 (1.8617/0.7518)	mem 16099MB
[2025-01-18 05:26:45 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][120/312]	eta 0:01:34 lr 0.001826	time 0.4506 (0.4902)	model_time 0.4504 (0.4717)	loss 2.6499 (3.1576)	grad_norm 3.5411 (1.8599/0.7666)	mem 16099MB
[2025-01-18 05:26:49 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][130/312]	eta 0:01:28 lr 0.001825	time 0.4640 (0.4887)	model_time 0.4639 (0.4717)	loss 3.7947 (3.1740)	grad_norm 2.0129 (1.8748/0.7514)	mem 16099MB
[2025-01-18 05:26:54 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][140/312]	eta 0:01:23 lr 0.001824	time 0.4517 (0.4874)	model_time 0.4515 (0.4715)	loss 3.3431 (3.1716)	grad_norm 1.3719 (1.8760/0.7491)	mem 16099MB
[2025-01-18 05:26:59 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][150/312]	eta 0:01:18 lr 0.001824	time 0.4807 (0.4854)	model_time 0.4805 (0.4706)	loss 2.6602 (3.1586)	grad_norm 3.1954 (1.8803/0.7436)	mem 16099MB
[2025-01-18 05:27:03 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][160/312]	eta 0:01:13 lr 0.001823	time 0.4448 (0.4838)	model_time 0.4446 (0.4699)	loss 3.9693 (3.1708)	grad_norm 1.0885 (1.8594/0.7469)	mem 16099MB
[2025-01-18 05:27:08 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][170/312]	eta 0:01:08 lr 0.001822	time 0.5804 (0.4830)	model_time 0.5802 (0.4698)	loss 3.4007 (3.1567)	grad_norm 1.2344 (1.8555/0.7343)	mem 16099MB
[2025-01-18 05:27:13 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][180/312]	eta 0:01:03 lr 0.001822	time 0.4570 (0.4824)	model_time 0.4569 (0.4700)	loss 2.2647 (3.1653)	grad_norm 3.9403 (1.8665/0.7346)	mem 16099MB
[2025-01-18 05:27:17 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][190/312]	eta 0:00:58 lr 0.001821	time 0.4488 (0.4816)	model_time 0.4486 (0.4698)	loss 3.3336 (3.1680)	grad_norm 2.2576 (1.8989/0.7439)	mem 16099MB
[2025-01-18 05:27:22 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][200/312]	eta 0:00:53 lr 0.001820	time 0.4498 (0.4821)	model_time 0.4496 (0.4709)	loss 3.5129 (3.1723)	grad_norm 2.8518 (1.8986/0.7375)	mem 16099MB
[2025-01-18 05:27:27 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][210/312]	eta 0:00:49 lr 0.001820	time 0.4668 (0.4809)	model_time 0.4663 (0.4702)	loss 3.0424 (3.1855)	grad_norm 0.8543 (1.8921/0.7381)	mem 16099MB
[2025-01-18 05:27:31 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][220/312]	eta 0:00:44 lr 0.001819	time 0.4931 (0.4803)	model_time 0.4925 (0.4701)	loss 2.8986 (3.1889)	grad_norm 1.6072 (1.8798/0.7320)	mem 16099MB
[2025-01-18 05:27:36 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][230/312]	eta 0:00:39 lr 0.001818	time 0.4494 (0.4799)	model_time 0.4492 (0.4700)	loss 3.0375 (3.1898)	grad_norm 1.1237 (1.8571/0.7290)	mem 16099MB
[2025-01-18 05:27:41 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][240/312]	eta 0:00:34 lr 0.001818	time 0.4491 (0.4792)	model_time 0.4489 (0.4697)	loss 3.3262 (3.1904)	grad_norm 2.2629 (1.8475/0.7181)	mem 16099MB
[2025-01-18 05:27:45 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][250/312]	eta 0:00:29 lr 0.001817	time 0.4491 (0.4785)	model_time 0.4489 (0.4694)	loss 3.1236 (3.1814)	grad_norm 1.0130 (1.8610/0.7358)	mem 16099MB
[2025-01-18 05:27:50 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][260/312]	eta 0:00:24 lr 0.001816	time 0.4478 (0.4783)	model_time 0.4477 (0.4695)	loss 3.3565 (3.1885)	grad_norm 1.6740 (1.8655/0.7504)	mem 16099MB
[2025-01-18 05:27:55 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][270/312]	eta 0:00:20 lr 0.001816	time 0.4494 (0.4786)	model_time 0.4492 (0.4701)	loss 3.4535 (3.1951)	grad_norm 1.4814 (1.8518/0.7444)	mem 16099MB
[2025-01-18 05:27:59 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][280/312]	eta 0:00:15 lr 0.001815	time 0.4666 (0.4776)	model_time 0.4664 (0.4695)	loss 3.4354 (3.1963)	grad_norm 3.8841 (1.8658/0.7895)	mem 16099MB
[2025-01-18 05:28:04 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][290/312]	eta 0:00:10 lr 0.001814	time 0.4458 (0.4773)	model_time 0.4454 (0.4694)	loss 3.8077 (3.1993)	grad_norm 2.8723 (1.8821/0.8090)	mem 16099MB
[2025-01-18 05:28:09 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][300/312]	eta 0:00:05 lr 0.001814	time 0.4402 (0.4765)	model_time 0.4401 (0.4689)	loss 2.2924 (3.2004)	grad_norm 1.4225 (1.8713/0.8039)	mem 16099MB
[2025-01-18 05:28:13 internimage_t_1k_224] (main.py 510): INFO Train: [159/300][310/312]	eta 0:00:00 lr 0.001813	time 0.4385 (0.4763)	model_time 0.4384 (0.4689)	loss 3.8584 (3.2093)	grad_norm 1.0388 (1.8577/0.8052)	mem 16099MB
[2025-01-18 05:28:14 internimage_t_1k_224] (main.py 519): INFO EPOCH 159 training takes 0:02:28
[2025-01-18 05:28:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_159.pth saving......
[2025-01-18 05:28:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_159.pth saved !!!
[2025-01-18 05:28:23 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.511 (7.511)	Loss 0.8239 (0.8239)	Acc@1 82.422 (82.422)	Acc@5 96.777 (96.777)	Mem 16099MB
[2025-01-18 05:28:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.011)	Loss 1.1034 (0.9541)	Acc@1 74.927 (79.410)	Acc@5 93.750 (95.044)	Mem 16099MB
[2025-01-18 05:28:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:159] * Acc@1 79.305 Acc@5 95.088
[2025-01-18 05:28:26 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.3%
[2025-01-18 05:28:26 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.70%
[2025-01-18 05:28:35 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.437 (8.437)	Loss 0.8109 (0.8109)	Acc@1 84.131 (84.131)	Acc@5 97.144 (97.144)	Mem 16099MB
[2025-01-18 05:28:39 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.115)	Loss 1.1082 (0.9422)	Acc@1 76.025 (81.050)	Acc@5 94.067 (95.659)	Mem 16099MB
[2025-01-18 05:28:39 internimage_t_1k_224] (main.py 575): INFO [Epoch:159] * Acc@1 80.934 Acc@5 95.691
[2025-01-18 05:28:39 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 80.9%
[2025-01-18 05:28:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:28:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:28:40 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.93%
[2025-01-18 05:28:42 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][0/312]	eta 0:13:03 lr 0.001813	time 2.5112 (2.5112)	model_time 0.4802 (0.4802)	loss 2.8540 (2.8540)	grad_norm 1.0891 (1.0891/0.0000)	mem 16099MB
[2025-01-18 05:28:47 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][10/312]	eta 0:03:19 lr 0.001812	time 0.4592 (0.6605)	model_time 0.4587 (0.4755)	loss 3.9840 (3.3239)	grad_norm 1.4088 (1.0503/0.2315)	mem 16099MB
[2025-01-18 05:28:52 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][20/312]	eta 0:02:45 lr 0.001812	time 0.4412 (0.5668)	model_time 0.4409 (0.4697)	loss 3.8299 (3.4584)	grad_norm 1.6699 (1.4881/0.8583)	mem 16099MB
[2025-01-18 05:28:56 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][30/312]	eta 0:02:30 lr 0.001811	time 0.4512 (0.5344)	model_time 0.4510 (0.4686)	loss 3.1071 (3.4307)	grad_norm 2.2899 (1.7543/0.9427)	mem 16099MB
[2025-01-18 05:29:01 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][40/312]	eta 0:02:20 lr 0.001810	time 0.4668 (0.5167)	model_time 0.4666 (0.4668)	loss 3.3709 (3.3382)	grad_norm 1.7514 (1.7466/0.8607)	mem 16099MB
[2025-01-18 05:29:06 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][50/312]	eta 0:02:13 lr 0.001810	time 0.4518 (0.5086)	model_time 0.4516 (0.4684)	loss 3.1674 (3.2626)	grad_norm 4.7239 (1.8200/0.9198)	mem 16099MB
[2025-01-18 05:29:10 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][60/312]	eta 0:02:05 lr 0.001809	time 0.4547 (0.4995)	model_time 0.4545 (0.4659)	loss 3.2226 (3.3082)	grad_norm 0.9500 (1.7903/0.8639)	mem 16099MB
[2025-01-18 05:29:15 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][70/312]	eta 0:01:59 lr 0.001808	time 0.4552 (0.4947)	model_time 0.4550 (0.4657)	loss 2.7911 (3.3147)	grad_norm 3.4173 (1.8400/0.8609)	mem 16099MB
[2025-01-18 05:29:20 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][80/312]	eta 0:01:53 lr 0.001808	time 0.4612 (0.4908)	model_time 0.4608 (0.4654)	loss 2.2569 (3.2620)	grad_norm 1.0907 (1.8304/0.8297)	mem 16099MB
[2025-01-18 05:29:24 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][90/312]	eta 0:01:48 lr 0.001807	time 0.4395 (0.4890)	model_time 0.4394 (0.4663)	loss 2.9814 (3.2394)	grad_norm 1.4898 (1.8169/0.7925)	mem 16099MB
[2025-01-18 05:29:29 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][100/312]	eta 0:01:43 lr 0.001806	time 0.4518 (0.4864)	model_time 0.4516 (0.4659)	loss 2.2998 (3.2226)	grad_norm 0.9248 (1.8565/0.8899)	mem 16099MB
[2025-01-18 05:29:34 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][110/312]	eta 0:01:38 lr 0.001806	time 0.4379 (0.4855)	model_time 0.4376 (0.4669)	loss 2.7464 (3.2381)	grad_norm 1.9164 (1.8206/0.8663)	mem 16099MB
[2025-01-18 05:29:39 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][120/312]	eta 0:01:33 lr 0.001805	time 0.4707 (0.4852)	model_time 0.4704 (0.4681)	loss 2.1704 (3.2028)	grad_norm 2.1953 (1.8162/0.8435)	mem 16099MB
[2025-01-18 05:29:43 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][130/312]	eta 0:01:27 lr 0.001804	time 0.4599 (0.4835)	model_time 0.4594 (0.4676)	loss 2.9893 (3.2038)	grad_norm 1.2747 (1.8212/0.8703)	mem 16099MB
[2025-01-18 05:29:48 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][140/312]	eta 0:01:23 lr 0.001804	time 0.4415 (0.4827)	model_time 0.4412 (0.4679)	loss 3.4608 (3.2167)	grad_norm 3.4530 (1.8963/0.9533)	mem 16099MB
[2025-01-18 05:29:52 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][150/312]	eta 0:01:17 lr 0.001803	time 0.4423 (0.4807)	model_time 0.4416 (0.4669)	loss 2.8381 (3.2308)	grad_norm 2.1200 (1.9015/0.9349)	mem 16099MB
[2025-01-18 05:29:57 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][160/312]	eta 0:01:13 lr 0.001802	time 0.4392 (0.4804)	model_time 0.4391 (0.4674)	loss 4.1284 (3.2305)	grad_norm 2.2978 (1.8910/0.9150)	mem 16099MB
[2025-01-18 05:30:02 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][170/312]	eta 0:01:08 lr 0.001802	time 0.4407 (0.4802)	model_time 0.4404 (0.4679)	loss 2.3117 (3.2248)	grad_norm 2.0809 (1.8982/0.9010)	mem 16099MB
[2025-01-18 05:30:07 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][180/312]	eta 0:01:03 lr 0.001801	time 0.4501 (0.4789)	model_time 0.4496 (0.4673)	loss 2.0624 (3.2230)	grad_norm 1.4407 (1.8801/0.8828)	mem 16099MB
[2025-01-18 05:30:11 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][190/312]	eta 0:00:58 lr 0.001800	time 0.4344 (0.4775)	model_time 0.4340 (0.4665)	loss 3.0376 (3.1988)	grad_norm 1.1660 (1.8573/0.8730)	mem 16099MB
[2025-01-18 05:30:16 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][200/312]	eta 0:00:53 lr 0.001800	time 0.4515 (0.4764)	model_time 0.4510 (0.4659)	loss 3.2448 (3.2053)	grad_norm 0.9711 (1.8970/0.9240)	mem 16099MB
[2025-01-18 05:30:20 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][210/312]	eta 0:00:48 lr 0.001799	time 0.5347 (0.4761)	model_time 0.5345 (0.4661)	loss 3.6315 (3.1891)	grad_norm 1.2270 (1.8838/0.9102)	mem 16099MB
[2025-01-18 05:30:25 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][220/312]	eta 0:00:43 lr 0.001798	time 0.4586 (0.4750)	model_time 0.4584 (0.4655)	loss 3.7445 (3.1873)	grad_norm 1.6600 (1.8640/0.8975)	mem 16099MB
[2025-01-18 05:30:29 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][230/312]	eta 0:00:38 lr 0.001798	time 0.4498 (0.4742)	model_time 0.4493 (0.4650)	loss 2.1501 (3.1839)	grad_norm 0.9937 (1.8657/0.8863)	mem 16099MB
[2025-01-18 05:30:34 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][240/312]	eta 0:00:34 lr 0.001797	time 0.4426 (0.4744)	model_time 0.4424 (0.4656)	loss 3.9440 (3.1905)	grad_norm 1.1322 (1.8763/0.8783)	mem 16099MB
[2025-01-18 05:30:39 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][250/312]	eta 0:00:29 lr 0.001797	time 0.4506 (0.4740)	model_time 0.4505 (0.4655)	loss 2.6223 (3.1898)	grad_norm 2.1109 (1.9119/0.9107)	mem 16099MB
[2025-01-18 05:30:44 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][260/312]	eta 0:00:24 lr 0.001796	time 0.4638 (0.4742)	model_time 0.4636 (0.4661)	loss 3.5100 (3.1856)	grad_norm 1.2014 (1.9028/0.9067)	mem 16099MB
[2025-01-18 05:30:48 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][270/312]	eta 0:00:19 lr 0.001795	time 0.4414 (0.4737)	model_time 0.4412 (0.4659)	loss 3.3715 (3.1922)	grad_norm 2.6569 (1.8907/0.9049)	mem 16099MB
[2025-01-18 05:30:53 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][280/312]	eta 0:00:15 lr 0.001795	time 0.4523 (0.4737)	model_time 0.4521 (0.4661)	loss 3.5132 (3.1868)	grad_norm 1.5886 (1.8929/0.8978)	mem 16099MB
[2025-01-18 05:30:58 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][290/312]	eta 0:00:10 lr 0.001794	time 0.4402 (0.4733)	model_time 0.4400 (0.4659)	loss 3.4718 (3.1914)	grad_norm 1.7804 (1.8724/0.8913)	mem 16099MB
[2025-01-18 05:31:02 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][300/312]	eta 0:00:05 lr 0.001793	time 0.4406 (0.4724)	model_time 0.4405 (0.4653)	loss 2.7697 (3.1893)	grad_norm 1.4308 (1.8779/0.8877)	mem 16099MB
[2025-01-18 05:31:07 internimage_t_1k_224] (main.py 510): INFO Train: [160/300][310/312]	eta 0:00:00 lr 0.001793	time 0.4378 (0.4717)	model_time 0.4376 (0.4648)	loss 2.8294 (3.1866)	grad_norm 1.1059 (1.8932/0.8793)	mem 16099MB
[2025-01-18 05:31:07 internimage_t_1k_224] (main.py 519): INFO EPOCH 160 training takes 0:02:27
[2025-01-18 05:31:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_160.pth saving......
[2025-01-18 05:31:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_160.pth saved !!!
[2025-01-18 05:31:16 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.654 (7.654)	Loss 0.8425 (0.8425)	Acc@1 82.324 (82.324)	Acc@5 96.484 (96.484)	Mem 16099MB
[2025-01-18 05:31:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.001)	Loss 1.1221 (0.9555)	Acc@1 75.708 (79.690)	Acc@5 93.604 (95.093)	Mem 16099MB
[2025-01-18 05:31:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:160] * Acc@1 79.615 Acc@5 95.128
[2025-01-18 05:31:19 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.6%
[2025-01-18 05:31:19 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.70%
[2025-01-18 05:31:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.255 (8.255)	Loss 0.8110 (0.8110)	Acc@1 84.155 (84.155)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 05:31:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.109)	Loss 1.1072 (0.9417)	Acc@1 76.074 (81.086)	Acc@5 94.116 (95.672)	Mem 16099MB
[2025-01-18 05:31:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:160] * Acc@1 80.972 Acc@5 95.699
[2025-01-18 05:31:32 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.0%
[2025-01-18 05:31:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:31:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:31:33 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 80.97%
[2025-01-18 05:31:35 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][0/312]	eta 0:13:28 lr 0.001792	time 2.5901 (2.5901)	model_time 0.4686 (0.4686)	loss 2.6798 (2.6798)	grad_norm 1.6277 (1.6277/0.0000)	mem 16099MB
[2025-01-18 05:31:40 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][10/312]	eta 0:03:23 lr 0.001792	time 0.4465 (0.6723)	model_time 0.4461 (0.4790)	loss 3.5557 (3.0430)	grad_norm 1.2170 (1.6089/0.4853)	mem 16099MB
[2025-01-18 05:31:45 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][20/312]	eta 0:02:47 lr 0.001791	time 0.5416 (0.5740)	model_time 0.5414 (0.4727)	loss 2.8814 (3.1027)	grad_norm 1.2732 (1.7297/0.6088)	mem 16099MB
[2025-01-18 05:31:50 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][30/312]	eta 0:02:32 lr 0.001790	time 0.5381 (0.5415)	model_time 0.5377 (0.4727)	loss 2.5972 (3.0909)	grad_norm 1.7053 (1.6570/0.5387)	mem 16099MB
[2025-01-18 05:31:54 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][40/312]	eta 0:02:21 lr 0.001790	time 0.4604 (0.5220)	model_time 0.4599 (0.4699)	loss 3.6058 (3.1603)	grad_norm 1.0820 (1.6288/0.5054)	mem 16099MB
[2025-01-18 05:31:59 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][50/312]	eta 0:02:15 lr 0.001789	time 0.4611 (0.5168)	model_time 0.4609 (0.4748)	loss 2.9762 (3.1592)	grad_norm 1.8055 (1.6686/0.5415)	mem 16099MB
[2025-01-18 05:32:04 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][60/312]	eta 0:02:08 lr 0.001788	time 0.5734 (0.5112)	model_time 0.5732 (0.4761)	loss 3.0426 (3.1880)	grad_norm 1.3729 (1.6089/0.5300)	mem 16099MB
[2025-01-18 05:32:09 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][70/312]	eta 0:02:02 lr 0.001788	time 0.4585 (0.5060)	model_time 0.4583 (0.4757)	loss 2.1933 (3.1676)	grad_norm 2.4469 (1.7264/0.7429)	mem 16099MB
[2025-01-18 05:32:13 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][80/312]	eta 0:01:56 lr 0.001787	time 0.4495 (0.5004)	model_time 0.4494 (0.4738)	loss 2.9487 (3.1477)	grad_norm 1.6315 (1.7325/0.7437)	mem 16099MB
[2025-01-18 05:32:18 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][90/312]	eta 0:01:50 lr 0.001786	time 0.4535 (0.4963)	model_time 0.4528 (0.4726)	loss 3.3847 (3.1446)	grad_norm 1.3025 (1.7213/0.7124)	mem 16099MB
[2025-01-18 05:32:23 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][100/312]	eta 0:01:44 lr 0.001786	time 0.4518 (0.4927)	model_time 0.4513 (0.4713)	loss 2.9049 (3.1714)	grad_norm 2.5616 (1.8283/0.8423)	mem 16099MB
[2025-01-18 05:32:27 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][110/312]	eta 0:01:38 lr 0.001785	time 0.4502 (0.4897)	model_time 0.4500 (0.4702)	loss 3.3647 (3.1837)	grad_norm 1.4234 (1.8663/0.8675)	mem 16099MB
[2025-01-18 05:32:32 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][120/312]	eta 0:01:33 lr 0.001785	time 0.4464 (0.4868)	model_time 0.4462 (0.4689)	loss 2.6858 (3.1850)	grad_norm 2.5192 (1.8723/0.8590)	mem 16099MB
[2025-01-18 05:32:36 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][130/312]	eta 0:01:28 lr 0.001784	time 0.5343 (0.4855)	model_time 0.5342 (0.4689)	loss 3.9014 (3.1719)	grad_norm 2.2788 (1.8758/0.8338)	mem 16099MB
[2025-01-18 05:32:41 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][140/312]	eta 0:01:23 lr 0.001783	time 0.4601 (0.4849)	model_time 0.4599 (0.4694)	loss 3.8508 (3.1765)	grad_norm 1.4716 (1.8507/0.8314)	mem 16099MB
[2025-01-18 05:32:46 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][150/312]	eta 0:01:18 lr 0.001783	time 0.4440 (0.4835)	model_time 0.4438 (0.4691)	loss 2.4489 (3.1836)	grad_norm 1.4434 (1.8195/0.8159)	mem 16099MB
[2025-01-18 05:32:50 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][160/312]	eta 0:01:13 lr 0.001782	time 0.4541 (0.4818)	model_time 0.4539 (0.4683)	loss 3.4353 (3.1891)	grad_norm 3.5103 (1.8491/0.8360)	mem 16099MB
[2025-01-18 05:32:55 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][170/312]	eta 0:01:08 lr 0.001781	time 0.4567 (0.4805)	model_time 0.4565 (0.4677)	loss 3.5832 (3.2098)	grad_norm 1.6012 (1.8798/0.8824)	mem 16099MB
[2025-01-18 05:33:00 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][180/312]	eta 0:01:03 lr 0.001781	time 0.4564 (0.4791)	model_time 0.4560 (0.4670)	loss 3.8367 (3.2245)	grad_norm 1.7010 (1.8630/0.8647)	mem 16099MB
[2025-01-18 05:33:04 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][190/312]	eta 0:00:58 lr 0.001780	time 0.4445 (0.4784)	model_time 0.4439 (0.4669)	loss 3.8602 (3.2355)	grad_norm 1.4166 (1.8719/0.8640)	mem 16099MB
[2025-01-18 05:33:09 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][200/312]	eta 0:00:53 lr 0.001779	time 0.4508 (0.4789)	model_time 0.4504 (0.4680)	loss 3.6048 (3.2446)	grad_norm 2.0874 (1.8553/0.8473)	mem 16099MB
[2025-01-18 05:33:14 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][210/312]	eta 0:00:48 lr 0.001779	time 0.4508 (0.4793)	model_time 0.4506 (0.4689)	loss 2.2273 (3.2488)	grad_norm 2.5576 (1.8649/0.8387)	mem 16099MB
[2025-01-18 05:33:18 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][220/312]	eta 0:00:43 lr 0.001778	time 0.4831 (0.4782)	model_time 0.4829 (0.4682)	loss 3.5553 (3.2564)	grad_norm 1.5336 (1.8543/0.8241)	mem 16099MB
[2025-01-18 05:33:23 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][230/312]	eta 0:00:39 lr 0.001777	time 0.4507 (0.4778)	model_time 0.4505 (0.4682)	loss 3.4594 (3.2614)	grad_norm 1.9763 (1.8768/0.8380)	mem 16099MB
[2025-01-18 05:33:28 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][240/312]	eta 0:00:34 lr 0.001777	time 0.4473 (0.4781)	model_time 0.4471 (0.4690)	loss 2.7974 (3.2646)	grad_norm 1.4140 (1.8517/0.8342)	mem 16099MB
[2025-01-18 05:33:33 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][250/312]	eta 0:00:29 lr 0.001776	time 0.4377 (0.4786)	model_time 0.4375 (0.4698)	loss 2.1106 (3.2580)	grad_norm 1.6880 (1.8399/0.8249)	mem 16099MB
[2025-01-18 05:33:38 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][260/312]	eta 0:00:24 lr 0.001775	time 0.4479 (0.4780)	model_time 0.4474 (0.4695)	loss 4.0124 (3.2512)	grad_norm 1.5185 (1.8430/0.8154)	mem 16099MB
[2025-01-18 05:33:42 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][270/312]	eta 0:00:20 lr 0.001775	time 0.4458 (0.4774)	model_time 0.4456 (0.4692)	loss 3.5635 (3.2548)	grad_norm 1.1097 (1.8310/0.8123)	mem 16099MB
[2025-01-18 05:33:47 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][280/312]	eta 0:00:15 lr 0.001774	time 0.5288 (0.4779)	model_time 0.5286 (0.4699)	loss 3.4596 (3.2518)	grad_norm 1.8667 (1.8295/0.8016)	mem 16099MB
[2025-01-18 05:33:52 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][290/312]	eta 0:00:10 lr 0.001773	time 0.4418 (0.4775)	model_time 0.4414 (0.4699)	loss 2.8869 (3.2454)	grad_norm 1.3883 (1.8464/0.8145)	mem 16099MB
[2025-01-18 05:33:56 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][300/312]	eta 0:00:05 lr 0.001773	time 0.4382 (0.4769)	model_time 0.4381 (0.4694)	loss 2.8707 (3.2423)	grad_norm 2.1034 (1.8494/0.8260)	mem 16099MB
[2025-01-18 05:34:01 internimage_t_1k_224] (main.py 510): INFO Train: [161/300][310/312]	eta 0:00:00 lr 0.001772	time 0.4357 (0.4759)	model_time 0.4356 (0.4687)	loss 3.8887 (3.2522)	grad_norm 4.8049 (1.8864/0.8586)	mem 16099MB
[2025-01-18 05:34:01 internimage_t_1k_224] (main.py 519): INFO EPOCH 161 training takes 0:02:28
[2025-01-18 05:34:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_161.pth saving......
[2025-01-18 05:34:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_161.pth saved !!!
[2025-01-18 05:34:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.534 (7.534)	Loss 0.8046 (0.8046)	Acc@1 82.739 (82.739)	Acc@5 96.875 (96.875)	Mem 16099MB
[2025-01-18 05:34:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.016)	Loss 1.1211 (0.9375)	Acc@1 74.365 (79.599)	Acc@5 93.433 (95.157)	Mem 16099MB
[2025-01-18 05:34:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:161] * Acc@1 79.541 Acc@5 95.188
[2025-01-18 05:34:14 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.5%
[2025-01-18 05:34:14 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.70%
[2025-01-18 05:34:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.249 (8.249)	Loss 0.8111 (0.8111)	Acc@1 84.204 (84.204)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 05:34:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.118)	Loss 1.1063 (0.9415)	Acc@1 76.123 (81.146)	Acc@5 94.141 (95.670)	Mem 16099MB
[2025-01-18 05:34:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:161] * Acc@1 81.028 Acc@5 95.697
[2025-01-18 05:34:26 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.0%
[2025-01-18 05:34:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:34:27 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:34:27 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.03%
[2025-01-18 05:34:29 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][0/312]	eta 0:10:28 lr 0.001772	time 2.0129 (2.0129)	model_time 0.4878 (0.4878)	loss 3.5596 (3.5596)	grad_norm 1.9432 (1.9432/0.0000)	mem 16099MB
[2025-01-18 05:34:34 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][10/312]	eta 0:03:05 lr 0.001771	time 0.4543 (0.6153)	model_time 0.4539 (0.4763)	loss 3.3946 (3.4164)	grad_norm 2.6766 (2.1224/0.6701)	mem 16099MB
[2025-01-18 05:34:39 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][20/312]	eta 0:02:39 lr 0.001771	time 0.4496 (0.5453)	model_time 0.4494 (0.4724)	loss 2.7003 (3.2827)	grad_norm 1.9871 (1.8853/0.6404)	mem 16099MB
[2025-01-18 05:34:43 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][30/312]	eta 0:02:25 lr 0.001770	time 0.4659 (0.5162)	model_time 0.4654 (0.4667)	loss 3.4217 (3.3078)	grad_norm 0.9435 (1.7212/0.6199)	mem 16099MB
[2025-01-18 05:34:48 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][40/312]	eta 0:02:17 lr 0.001769	time 0.4554 (0.5041)	model_time 0.4552 (0.4665)	loss 3.9395 (3.2926)	grad_norm 2.0212 (1.8016/0.7659)	mem 16099MB
[2025-01-18 05:34:53 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][50/312]	eta 0:02:09 lr 0.001769	time 0.4495 (0.4955)	model_time 0.4489 (0.4652)	loss 2.7351 (3.2605)	grad_norm 1.2929 (1.7193/0.7137)	mem 16099MB
[2025-01-18 05:34:57 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][60/312]	eta 0:02:03 lr 0.001768	time 0.4475 (0.4893)	model_time 0.4473 (0.4639)	loss 3.8221 (3.2020)	grad_norm 1.5009 (1.8191/0.7462)	mem 16099MB
[2025-01-18 05:35:02 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][70/312]	eta 0:01:57 lr 0.001767	time 0.4530 (0.4868)	model_time 0.4526 (0.4649)	loss 3.2889 (3.1878)	grad_norm 1.1154 (1.8710/0.8034)	mem 16099MB
[2025-01-18 05:35:07 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][80/312]	eta 0:01:52 lr 0.001767	time 0.4382 (0.4839)	model_time 0.4377 (0.4647)	loss 2.7843 (3.1572)	grad_norm 0.7974 (1.8618/0.7837)	mem 16099MB
[2025-01-18 05:35:11 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][90/312]	eta 0:01:46 lr 0.001766	time 0.4494 (0.4814)	model_time 0.4493 (0.4642)	loss 2.5786 (3.1296)	grad_norm 1.7932 (1.8828/0.8018)	mem 16099MB
[2025-01-18 05:35:16 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][100/312]	eta 0:01:41 lr 0.001765	time 0.4640 (0.4804)	model_time 0.4638 (0.4649)	loss 3.3360 (3.1530)	grad_norm 1.2139 (1.8854/0.8029)	mem 16099MB
[2025-01-18 05:35:21 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][110/312]	eta 0:01:36 lr 0.001765	time 0.4540 (0.4784)	model_time 0.4539 (0.4643)	loss 2.6562 (3.1237)	grad_norm 1.2575 (1.8402/0.7829)	mem 16099MB
[2025-01-18 05:35:25 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][120/312]	eta 0:01:31 lr 0.001764	time 0.4740 (0.4771)	model_time 0.4738 (0.4642)	loss 3.5832 (3.1400)	grad_norm 3.3229 (1.8408/0.7818)	mem 16099MB
[2025-01-18 05:35:30 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][130/312]	eta 0:01:26 lr 0.001763	time 0.4540 (0.4764)	model_time 0.4538 (0.4644)	loss 3.8535 (3.1523)	grad_norm 1.5372 (1.8073/0.7711)	mem 16099MB
[2025-01-18 05:35:35 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][140/312]	eta 0:01:22 lr 0.001763	time 0.5698 (0.4780)	model_time 0.5697 (0.4668)	loss 3.7533 (3.1545)	grad_norm 1.4308 (1.7849/0.7575)	mem 16099MB
[2025-01-18 05:35:39 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][150/312]	eta 0:01:17 lr 0.001762	time 0.4507 (0.4770)	model_time 0.4505 (0.4665)	loss 3.8788 (3.1771)	grad_norm 4.1735 (1.8610/0.8485)	mem 16099MB
[2025-01-18 05:35:44 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][160/312]	eta 0:01:12 lr 0.001761	time 0.4698 (0.4766)	model_time 0.4697 (0.4667)	loss 2.7187 (3.1916)	grad_norm 2.1004 (1.8737/0.8527)	mem 16099MB
[2025-01-18 05:35:49 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][170/312]	eta 0:01:07 lr 0.001761	time 0.4583 (0.4759)	model_time 0.4582 (0.4666)	loss 3.5146 (3.1986)	grad_norm 1.3684 (1.8557/0.8359)	mem 16099MB
[2025-01-18 05:35:53 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][180/312]	eta 0:01:02 lr 0.001760	time 0.4462 (0.4748)	model_time 0.4457 (0.4660)	loss 3.6009 (3.2109)	grad_norm 1.9895 (1.8376/0.8222)	mem 16099MB
[2025-01-18 05:35:58 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][190/312]	eta 0:00:57 lr 0.001759	time 0.5451 (0.4746)	model_time 0.5450 (0.4663)	loss 3.5506 (3.2122)	grad_norm 2.0793 (1.8509/0.8200)	mem 16099MB
[2025-01-18 05:36:03 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][200/312]	eta 0:00:53 lr 0.001759	time 0.4520 (0.4750)	model_time 0.4515 (0.4671)	loss 3.8915 (3.2174)	grad_norm 1.3885 (1.8454/0.8086)	mem 16099MB
[2025-01-18 05:36:07 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][210/312]	eta 0:00:48 lr 0.001758	time 0.4492 (0.4741)	model_time 0.4488 (0.4665)	loss 3.4633 (3.2048)	grad_norm 1.9946 (1.8329/0.7966)	mem 16099MB
[2025-01-18 05:36:12 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][220/312]	eta 0:00:43 lr 0.001757	time 0.4524 (0.4736)	model_time 0.4522 (0.4663)	loss 2.9276 (3.1916)	grad_norm 1.7838 (1.8536/0.7984)	mem 16099MB
[2025-01-18 05:36:17 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][230/312]	eta 0:00:38 lr 0.001757	time 0.5350 (0.4732)	model_time 0.5346 (0.4662)	loss 2.8163 (3.1872)	grad_norm 1.6661 (1.8421/0.7993)	mem 16099MB
[2025-01-18 05:36:21 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][240/312]	eta 0:00:34 lr 0.001756	time 0.4489 (0.4725)	model_time 0.4485 (0.4658)	loss 2.8162 (3.1730)	grad_norm 1.3487 (1.8706/0.8235)	mem 16099MB
[2025-01-18 05:36:26 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][250/312]	eta 0:00:29 lr 0.001755	time 0.4432 (0.4724)	model_time 0.4427 (0.4659)	loss 3.0718 (3.1707)	grad_norm 0.8887 (1.8755/0.8289)	mem 16099MB
[2025-01-18 05:36:31 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][260/312]	eta 0:00:24 lr 0.001755	time 0.4527 (0.4719)	model_time 0.4523 (0.4657)	loss 3.5532 (3.1653)	grad_norm 1.0588 (1.8667/0.8276)	mem 16099MB
[2025-01-18 05:36:35 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][270/312]	eta 0:00:19 lr 0.001754	time 0.4482 (0.4723)	model_time 0.4478 (0.4663)	loss 3.4457 (3.1680)	grad_norm 1.5982 (1.8473/0.8191)	mem 16099MB
[2025-01-18 05:36:40 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][280/312]	eta 0:00:15 lr 0.001753	time 0.4429 (0.4720)	model_time 0.4424 (0.4662)	loss 3.8441 (3.1624)	grad_norm 1.7921 (1.8704/0.8358)	mem 16099MB
[2025-01-18 05:36:45 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][290/312]	eta 0:00:10 lr 0.001753	time 0.4479 (0.4723)	model_time 0.4475 (0.4667)	loss 3.0779 (3.1711)	grad_norm 1.0733 (1.8591/0.8267)	mem 16099MB
[2025-01-18 05:36:50 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][300/312]	eta 0:00:05 lr 0.001752	time 0.4397 (0.4721)	model_time 0.4396 (0.4667)	loss 3.3134 (3.1757)	grad_norm 5.1759 (1.8659/0.8407)	mem 16099MB
[2025-01-18 05:36:54 internimage_t_1k_224] (main.py 510): INFO Train: [162/300][310/312]	eta 0:00:00 lr 0.001751	time 0.4393 (0.4715)	model_time 0.4392 (0.4662)	loss 3.4918 (3.1842)	grad_norm 2.3717 (1.8736/0.8518)	mem 16099MB
[2025-01-18 05:36:54 internimage_t_1k_224] (main.py 519): INFO EPOCH 162 training takes 0:02:27
[2025-01-18 05:36:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_162.pth saving......
[2025-01-18 05:36:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_162.pth saved !!!
[2025-01-18 05:37:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.481 (7.481)	Loss 0.8353 (0.8353)	Acc@1 82.642 (82.642)	Acc@5 96.606 (96.606)	Mem 16099MB
[2025-01-18 05:37:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.994)	Loss 1.1110 (0.9587)	Acc@1 74.902 (79.756)	Acc@5 93.579 (95.086)	Mem 16099MB
[2025-01-18 05:37:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:162] * Acc@1 79.657 Acc@5 95.150
[2025-01-18 05:37:07 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.7%
[2025-01-18 05:37:07 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.70%
[2025-01-18 05:37:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.204 (8.204)	Loss 0.8111 (0.8111)	Acc@1 84.302 (84.302)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 05:37:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.111)	Loss 1.1052 (0.9411)	Acc@1 76.245 (81.203)	Acc@5 94.141 (95.694)	Mem 16099MB
[2025-01-18 05:37:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:162] * Acc@1 81.076 Acc@5 95.717
[2025-01-18 05:37:19 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.1%
[2025-01-18 05:37:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:37:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:37:20 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.08%
[2025-01-18 05:37:22 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][0/312]	eta 0:10:05 lr 0.001751	time 1.9407 (1.9407)	model_time 0.4855 (0.4855)	loss 2.9543 (2.9543)	grad_norm 1.5214 (1.5214/0.0000)	mem 16099MB
[2025-01-18 05:37:27 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][10/312]	eta 0:03:06 lr 0.001751	time 0.5480 (0.6173)	model_time 0.5476 (0.4848)	loss 3.3763 (3.5140)	grad_norm 1.1540 (2.0016/0.9539)	mem 16099MB
[2025-01-18 05:37:32 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][20/312]	eta 0:02:38 lr 0.001750	time 0.4492 (0.5443)	model_time 0.4491 (0.4747)	loss 3.9513 (3.4251)	grad_norm 1.1633 (1.7822/0.8955)	mem 16099MB
[2025-01-18 05:37:36 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][30/312]	eta 0:02:26 lr 0.001749	time 0.4534 (0.5182)	model_time 0.4530 (0.4710)	loss 3.4366 (3.3797)	grad_norm 1.8325 (1.6510/0.7918)	mem 16099MB
[2025-01-18 05:37:41 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][40/312]	eta 0:02:16 lr 0.001749	time 0.4470 (0.5026)	model_time 0.4469 (0.4668)	loss 3.3782 (3.3873)	grad_norm 1.6552 (1.6577/0.7174)	mem 16099MB
[2025-01-18 05:37:45 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][50/312]	eta 0:02:09 lr 0.001748	time 0.4404 (0.4936)	model_time 0.4403 (0.4647)	loss 3.3740 (3.3495)	grad_norm 2.1045 (1.6354/0.6560)	mem 16099MB
[2025-01-18 05:37:50 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][60/312]	eta 0:02:03 lr 0.001747	time 0.4400 (0.4883)	model_time 0.4395 (0.4642)	loss 3.5982 (3.3501)	grad_norm 0.8181 (1.6331/0.6343)	mem 16099MB
[2025-01-18 05:37:55 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][70/312]	eta 0:01:56 lr 0.001747	time 0.4481 (0.4834)	model_time 0.4479 (0.4626)	loss 2.9639 (3.3542)	grad_norm 3.0966 (1.7085/0.6555)	mem 16099MB
[2025-01-18 05:37:59 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][80/312]	eta 0:01:51 lr 0.001746	time 0.4503 (0.4798)	model_time 0.4499 (0.4615)	loss 2.7274 (3.3177)	grad_norm 3.7708 (1.8439/0.9097)	mem 16099MB
[2025-01-18 05:38:04 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][90/312]	eta 0:01:45 lr 0.001745	time 0.4530 (0.4774)	model_time 0.4528 (0.4611)	loss 2.5302 (3.3076)	grad_norm 1.3852 (1.8219/0.8743)	mem 16099MB
[2025-01-18 05:38:08 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][100/312]	eta 0:01:41 lr 0.001745	time 0.4493 (0.4766)	model_time 0.4491 (0.4618)	loss 3.0245 (3.3015)	grad_norm 1.1155 (1.8118/0.8489)	mem 16099MB
[2025-01-18 05:38:13 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][110/312]	eta 0:01:35 lr 0.001744	time 0.4618 (0.4745)	model_time 0.4617 (0.4611)	loss 2.1248 (3.2779)	grad_norm 2.4134 (1.8448/0.8564)	mem 16099MB
[2025-01-18 05:38:18 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][120/312]	eta 0:01:31 lr 0.001743	time 0.4458 (0.4756)	model_time 0.4456 (0.4632)	loss 3.5132 (3.2852)	grad_norm 1.3728 (1.8085/0.8340)	mem 16099MB
[2025-01-18 05:38:23 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][130/312]	eta 0:01:26 lr 0.001743	time 0.4559 (0.4753)	model_time 0.4557 (0.4639)	loss 2.6623 (3.2571)	grad_norm 1.3333 (1.8158/0.8136)	mem 16099MB
[2025-01-18 05:38:27 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][140/312]	eta 0:01:21 lr 0.001742	time 0.5249 (0.4763)	model_time 0.5248 (0.4656)	loss 4.0637 (3.2394)	grad_norm 1.5937 (1.8363/0.8162)	mem 16099MB
[2025-01-18 05:38:32 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][150/312]	eta 0:01:17 lr 0.001741	time 0.4497 (0.4766)	model_time 0.4493 (0.4666)	loss 2.4297 (3.2347)	grad_norm 1.2785 (1.8408/0.8138)	mem 16099MB
[2025-01-18 05:38:37 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][160/312]	eta 0:01:12 lr 0.001741	time 0.4531 (0.4763)	model_time 0.4527 (0.4669)	loss 3.4558 (3.2298)	grad_norm 3.3656 (1.8613/0.8551)	mem 16099MB
[2025-01-18 05:38:42 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][170/312]	eta 0:01:07 lr 0.001740	time 0.4535 (0.4757)	model_time 0.4531 (0.4669)	loss 3.2701 (3.2250)	grad_norm 1.3126 (1.8379/0.8365)	mem 16099MB
[2025-01-18 05:38:46 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][180/312]	eta 0:01:02 lr 0.001739	time 0.4518 (0.4759)	model_time 0.4513 (0.4675)	loss 3.4490 (3.2323)	grad_norm 1.1071 (1.8244/0.8277)	mem 16099MB
[2025-01-18 05:38:51 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][190/312]	eta 0:00:57 lr 0.001739	time 0.5469 (0.4752)	model_time 0.5468 (0.4672)	loss 3.5066 (3.2343)	grad_norm 1.6727 (1.8171/0.8287)	mem 16099MB
[2025-01-18 05:38:56 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][200/312]	eta 0:00:53 lr 0.001738	time 0.4568 (0.4746)	model_time 0.4563 (0.4670)	loss 3.2542 (3.2294)	grad_norm 1.3965 (1.8005/0.8211)	mem 16099MB
[2025-01-18 05:39:00 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][210/312]	eta 0:00:48 lr 0.001737	time 0.4502 (0.4741)	model_time 0.4501 (0.4669)	loss 3.3516 (3.2279)	grad_norm 4.1730 (1.8204/0.8356)	mem 16099MB
[2025-01-18 05:39:05 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][220/312]	eta 0:00:43 lr 0.001737	time 0.4534 (0.4735)	model_time 0.4529 (0.4665)	loss 2.0249 (3.2148)	grad_norm 4.6112 (1.8390/0.8462)	mem 16099MB
[2025-01-18 05:39:10 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][230/312]	eta 0:00:38 lr 0.001736	time 0.4580 (0.4732)	model_time 0.4575 (0.4666)	loss 2.5763 (3.2155)	grad_norm 1.4841 (1.8597/0.8724)	mem 16099MB
[2025-01-18 05:39:14 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][240/312]	eta 0:00:34 lr 0.001735	time 0.4450 (0.4723)	model_time 0.4447 (0.4659)	loss 3.5113 (3.2230)	grad_norm 1.8551 (1.8812/0.8868)	mem 16099MB
[2025-01-18 05:39:19 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][250/312]	eta 0:00:29 lr 0.001735	time 0.4536 (0.4719)	model_time 0.4534 (0.4658)	loss 3.2933 (3.2204)	grad_norm 1.8737 (1.8650/0.8768)	mem 16099MB
[2025-01-18 05:39:23 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][260/312]	eta 0:00:24 lr 0.001734	time 0.4526 (0.4718)	model_time 0.4525 (0.4659)	loss 4.2164 (3.2232)	grad_norm 1.9615 (1.8745/0.8662)	mem 16099MB
[2025-01-18 05:39:28 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][270/312]	eta 0:00:19 lr 0.001734	time 0.4583 (0.4711)	model_time 0.4582 (0.4654)	loss 3.3562 (3.2195)	grad_norm 0.9045 (1.8677/0.8540)	mem 16099MB
[2025-01-18 05:39:32 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][280/312]	eta 0:00:15 lr 0.001733	time 0.4409 (0.4705)	model_time 0.4404 (0.4649)	loss 2.4670 (3.2025)	grad_norm 4.4386 (1.8795/0.8639)	mem 16099MB
[2025-01-18 05:39:37 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][290/312]	eta 0:00:10 lr 0.001732	time 0.4518 (0.4707)	model_time 0.4516 (0.4654)	loss 2.5553 (3.2004)	grad_norm 2.1740 (1.8888/0.8642)	mem 16099MB
[2025-01-18 05:39:42 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][300/312]	eta 0:00:05 lr 0.001732	time 0.4381 (0.4707)	model_time 0.4380 (0.4655)	loss 3.3993 (3.2039)	grad_norm 1.2133 (1.9117/0.8859)	mem 16099MB
[2025-01-18 05:39:47 internimage_t_1k_224] (main.py 510): INFO Train: [163/300][310/312]	eta 0:00:00 lr 0.001731	time 0.4384 (0.4705)	model_time 0.4383 (0.4654)	loss 3.2414 (3.2099)	grad_norm 0.8293 (1.8956/0.8782)	mem 16099MB
[2025-01-18 05:39:47 internimage_t_1k_224] (main.py 519): INFO EPOCH 163 training takes 0:02:26
[2025-01-18 05:39:47 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_163.pth saving......
[2025-01-18 05:39:48 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_163.pth saved !!!
[2025-01-18 05:39:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.456 (7.456)	Loss 0.8298 (0.8298)	Acc@1 82.715 (82.715)	Acc@5 96.558 (96.558)	Mem 16099MB
[2025-01-18 05:39:59 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.013)	Loss 1.1274 (0.9595)	Acc@1 74.707 (79.823)	Acc@5 93.896 (95.173)	Mem 16099MB
[2025-01-18 05:39:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:163] * Acc@1 79.810 Acc@5 95.216
[2025-01-18 05:39:59 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.8%
[2025-01-18 05:39:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 05:40:01 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 05:40:01 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.81%
[2025-01-18 05:40:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.610 (7.610)	Loss 0.8109 (0.8109)	Acc@1 84.277 (84.277)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 05:40:12 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.006)	Loss 1.1038 (0.9404)	Acc@1 76.270 (81.228)	Acc@5 94.238 (95.688)	Mem 16099MB
[2025-01-18 05:40:12 internimage_t_1k_224] (main.py 575): INFO [Epoch:163] * Acc@1 81.106 Acc@5 95.711
[2025-01-18 05:40:12 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.1%
[2025-01-18 05:40:12 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:40:13 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:40:13 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.11%
[2025-01-18 05:40:15 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][0/312]	eta 0:11:06 lr 0.001731	time 2.1353 (2.1353)	model_time 0.4680 (0.4680)	loss 3.5298 (3.5298)	grad_norm 0.8358 (0.8358/0.0000)	mem 16099MB
[2025-01-18 05:40:20 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][10/312]	eta 0:03:05 lr 0.001730	time 0.4436 (0.6135)	model_time 0.4435 (0.4616)	loss 2.6436 (3.0657)	grad_norm 2.6612 (1.6348/0.6260)	mem 16099MB
[2025-01-18 05:40:24 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][20/312]	eta 0:02:38 lr 0.001729	time 0.5502 (0.5423)	model_time 0.5499 (0.4626)	loss 2.1981 (3.1381)	grad_norm 2.8142 (1.8506/0.7421)	mem 16099MB
[2025-01-18 05:40:29 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][30/312]	eta 0:02:27 lr 0.001729	time 0.4534 (0.5225)	model_time 0.4529 (0.4683)	loss 3.5199 (3.1831)	grad_norm 1.8968 (2.0655/0.9832)	mem 16099MB
[2025-01-18 05:40:34 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][40/312]	eta 0:02:18 lr 0.001728	time 0.4475 (0.5087)	model_time 0.4473 (0.4677)	loss 3.4356 (3.1176)	grad_norm 0.9808 (1.9895/0.9219)	mem 16099MB
[2025-01-18 05:40:38 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][50/312]	eta 0:02:10 lr 0.001727	time 0.4556 (0.4979)	model_time 0.4553 (0.4648)	loss 3.6350 (3.0803)	grad_norm 2.0969 (1.8854/0.8739)	mem 16099MB
[2025-01-18 05:40:43 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][60/312]	eta 0:02:03 lr 0.001727	time 0.4561 (0.4907)	model_time 0.4559 (0.4630)	loss 3.4501 (3.0653)	grad_norm 0.8597 (2.0145/1.0204)	mem 16099MB
[2025-01-18 05:40:48 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][70/312]	eta 0:01:57 lr 0.001726	time 0.4453 (0.4855)	model_time 0.4449 (0.4617)	loss 3.8528 (3.0373)	grad_norm 3.0772 (2.0672/1.0458)	mem 16099MB
[2025-01-18 05:40:52 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][80/312]	eta 0:01:52 lr 0.001725	time 0.4401 (0.4836)	model_time 0.4399 (0.4626)	loss 2.6986 (3.0162)	grad_norm 1.6868 (1.9848/1.0115)	mem 16099MB
[2025-01-18 05:40:57 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][90/312]	eta 0:01:46 lr 0.001725	time 0.4521 (0.4801)	model_time 0.4516 (0.4613)	loss 3.4830 (3.0245)	grad_norm 1.8932 (1.9107/0.9857)	mem 16099MB
[2025-01-18 05:41:01 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][100/312]	eta 0:01:41 lr 0.001724	time 0.4580 (0.4792)	model_time 0.4576 (0.4623)	loss 3.7847 (3.0579)	grad_norm 3.9350 (1.9360/0.9817)	mem 16099MB
[2025-01-18 05:41:06 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][110/312]	eta 0:01:36 lr 0.001724	time 0.5363 (0.4774)	model_time 0.5361 (0.4620)	loss 3.2031 (3.0683)	grad_norm 1.7744 (1.8876/0.9582)	mem 16099MB
[2025-01-18 05:41:11 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][120/312]	eta 0:01:31 lr 0.001723	time 0.5393 (0.4786)	model_time 0.5388 (0.4645)	loss 3.8274 (3.0711)	grad_norm 1.3429 (1.8731/0.9453)	mem 16099MB
[2025-01-18 05:41:16 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][130/312]	eta 0:01:26 lr 0.001722	time 0.4780 (0.4779)	model_time 0.4778 (0.4648)	loss 2.9747 (3.1036)	grad_norm 1.6090 (1.8857/0.9303)	mem 16099MB
[2025-01-18 05:41:20 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][140/312]	eta 0:01:22 lr 0.001722	time 0.4582 (0.4771)	model_time 0.4577 (0.4649)	loss 3.3451 (3.0917)	grad_norm 2.7996 (1.9063/0.9258)	mem 16099MB
[2025-01-18 05:41:25 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][150/312]	eta 0:01:17 lr 0.001721	time 0.4456 (0.4769)	model_time 0.4451 (0.4655)	loss 2.1266 (3.0750)	grad_norm 2.3335 (1.8972/0.9057)	mem 16099MB
[2025-01-18 05:41:30 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][160/312]	eta 0:01:12 lr 0.001720	time 0.4839 (0.4757)	model_time 0.4835 (0.4650)	loss 2.5618 (3.0814)	grad_norm 1.5717 (1.8875/0.8928)	mem 16099MB
[2025-01-18 05:41:34 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][170/312]	eta 0:01:07 lr 0.001720	time 0.4479 (0.4745)	model_time 0.4475 (0.4644)	loss 3.3503 (3.0902)	grad_norm 2.1344 (1.8866/0.8760)	mem 16099MB
[2025-01-18 05:41:39 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][180/312]	eta 0:01:02 lr 0.001719	time 0.4632 (0.4739)	model_time 0.4630 (0.4643)	loss 3.6565 (3.1024)	grad_norm 1.5744 (1.8965/0.8741)	mem 16099MB
[2025-01-18 05:41:43 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][190/312]	eta 0:00:57 lr 0.001718	time 0.4588 (0.4733)	model_time 0.4584 (0.4642)	loss 3.8018 (3.1150)	grad_norm 1.7509 (1.9231/0.8925)	mem 16099MB
[2025-01-18 05:41:48 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][200/312]	eta 0:00:52 lr 0.001718	time 0.4802 (0.4726)	model_time 0.4800 (0.4639)	loss 3.8472 (3.1202)	grad_norm 4.6444 (1.9539/0.9155)	mem 16099MB
[2025-01-18 05:41:53 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][210/312]	eta 0:00:48 lr 0.001717	time 0.4717 (0.4721)	model_time 0.4712 (0.4639)	loss 3.2733 (3.1124)	grad_norm 1.2767 (1.9416/0.9024)	mem 16099MB
[2025-01-18 05:41:57 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][220/312]	eta 0:00:43 lr 0.001716	time 0.4519 (0.4717)	model_time 0.4515 (0.4637)	loss 3.5291 (3.1220)	grad_norm 1.6813 (1.9552/0.8939)	mem 16099MB
[2025-01-18 05:42:02 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][230/312]	eta 0:00:38 lr 0.001716	time 0.4447 (0.4714)	model_time 0.4442 (0.4638)	loss 3.1944 (3.1253)	grad_norm 1.3030 (1.9411/0.8797)	mem 16099MB
[2025-01-18 05:42:06 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][240/312]	eta 0:00:33 lr 0.001715	time 0.4580 (0.4707)	model_time 0.4578 (0.4634)	loss 3.2834 (3.1244)	grad_norm 1.5122 (1.9249/0.8696)	mem 16099MB
[2025-01-18 05:42:11 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][250/312]	eta 0:00:29 lr 0.001714	time 0.4719 (0.4708)	model_time 0.4714 (0.4638)	loss 3.4899 (3.1371)	grad_norm 1.2337 (1.9331/0.8703)	mem 16099MB
[2025-01-18 05:42:16 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][260/312]	eta 0:00:24 lr 0.001714	time 0.4551 (0.4711)	model_time 0.4547 (0.4643)	loss 2.5851 (3.1429)	grad_norm 1.0559 (1.9086/0.8638)	mem 16099MB
[2025-01-18 05:42:21 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][270/312]	eta 0:00:19 lr 0.001713	time 0.4469 (0.4708)	model_time 0.4467 (0.4643)	loss 3.6350 (3.1407)	grad_norm 2.8172 (1.9164/0.8658)	mem 16099MB
[2025-01-18 05:42:25 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][280/312]	eta 0:00:15 lr 0.001712	time 0.4462 (0.4702)	model_time 0.4460 (0.4639)	loss 3.2352 (3.1468)	grad_norm 2.7085 (1.9306/0.8578)	mem 16099MB
[2025-01-18 05:42:30 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][290/312]	eta 0:00:10 lr 0.001712	time 0.4435 (0.4711)	model_time 0.4430 (0.4650)	loss 2.8856 (3.1463)	grad_norm 1.3719 (1.9324/0.8556)	mem 16099MB
[2025-01-18 05:42:35 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][300/312]	eta 0:00:05 lr 0.001711	time 0.4411 (0.4709)	model_time 0.4410 (0.4650)	loss 3.0279 (3.1511)	grad_norm 1.9248 (1.9403/0.8638)	mem 16099MB
[2025-01-18 05:42:39 internimage_t_1k_224] (main.py 510): INFO Train: [164/300][310/312]	eta 0:00:00 lr 0.001710	time 0.4370 (0.4702)	model_time 0.4369 (0.4645)	loss 2.2170 (3.1443)	grad_norm 1.0257 (1.9296/0.8648)	mem 16099MB
[2025-01-18 05:42:40 internimage_t_1k_224] (main.py 519): INFO EPOCH 164 training takes 0:02:26
[2025-01-18 05:42:40 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_164.pth saving......
[2025-01-18 05:42:41 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_164.pth saved !!!
[2025-01-18 05:42:49 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.802 (7.802)	Loss 0.7975 (0.7975)	Acc@1 82.886 (82.886)	Acc@5 96.875 (96.875)	Mem 16099MB
[2025-01-18 05:42:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.041)	Loss 1.1470 (0.9571)	Acc@1 74.902 (79.512)	Acc@5 93.164 (95.088)	Mem 16099MB
[2025-01-18 05:42:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:164] * Acc@1 79.455 Acc@5 95.106
[2025-01-18 05:42:52 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.5%
[2025-01-18 05:42:52 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.81%
[2025-01-18 05:43:01 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.412 (8.412)	Loss 0.8108 (0.8108)	Acc@1 84.302 (84.302)	Acc@5 97.192 (97.192)	Mem 16099MB
[2025-01-18 05:43:05 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.128)	Loss 1.1026 (0.9399)	Acc@1 76.294 (81.286)	Acc@5 94.214 (95.701)	Mem 16099MB
[2025-01-18 05:43:05 internimage_t_1k_224] (main.py 575): INFO [Epoch:164] * Acc@1 81.164 Acc@5 95.727
[2025-01-18 05:43:05 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.2%
[2025-01-18 05:43:05 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:43:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:43:06 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.16%
[2025-01-18 05:43:08 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][0/312]	eta 0:09:56 lr 0.001710	time 1.9134 (1.9134)	model_time 0.5192 (0.5192)	loss 2.6114 (2.6114)	grad_norm 1.7010 (1.7010/0.0000)	mem 16099MB
[2025-01-18 05:43:13 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][10/312]	eta 0:03:09 lr 0.001710	time 0.4569 (0.6262)	model_time 0.4565 (0.4991)	loss 2.1517 (2.9044)	grad_norm 1.3597 (1.8809/0.6783)	mem 16099MB
[2025-01-18 05:43:18 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][20/312]	eta 0:02:39 lr 0.001709	time 0.4625 (0.5445)	model_time 0.4623 (0.4778)	loss 3.3178 (3.1120)	grad_norm 1.3797 (1.7664/0.5808)	mem 16099MB
[2025-01-18 05:43:23 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][30/312]	eta 0:02:30 lr 0.001708	time 0.5407 (0.5343)	model_time 0.5405 (0.4890)	loss 3.5385 (3.1302)	grad_norm 1.0547 (1.8669/0.7598)	mem 16099MB
[2025-01-18 05:43:27 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][40/312]	eta 0:02:20 lr 0.001708	time 0.4652 (0.5180)	model_time 0.4648 (0.4836)	loss 2.9429 (3.1492)	grad_norm 1.6498 (1.8276/0.7220)	mem 16099MB
[2025-01-18 05:43:32 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][50/312]	eta 0:02:13 lr 0.001707	time 0.4583 (0.5092)	model_time 0.4578 (0.4815)	loss 4.0884 (3.2190)	grad_norm 2.9596 (1.7511/0.7256)	mem 16099MB
[2025-01-18 05:43:37 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][60/312]	eta 0:02:06 lr 0.001706	time 0.4404 (0.5034)	model_time 0.4400 (0.4801)	loss 3.1151 (3.2333)	grad_norm 1.3920 (1.7964/0.7035)	mem 16099MB
[2025-01-18 05:43:42 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][70/312]	eta 0:02:00 lr 0.001706	time 0.5428 (0.4989)	model_time 0.5426 (0.4789)	loss 2.8132 (3.1879)	grad_norm 2.7495 (1.9145/0.7825)	mem 16099MB
[2025-01-18 05:43:46 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][80/312]	eta 0:01:54 lr 0.001705	time 0.4536 (0.4950)	model_time 0.4531 (0.4774)	loss 2.1813 (3.2155)	grad_norm 2.1534 (1.9467/0.8044)	mem 16099MB
[2025-01-18 05:43:51 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][90/312]	eta 0:01:48 lr 0.001704	time 0.4532 (0.4903)	model_time 0.4531 (0.4746)	loss 2.1243 (3.1861)	grad_norm 1.4830 (1.9179/0.7859)	mem 16099MB
[2025-01-18 05:43:55 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][100/312]	eta 0:01:43 lr 0.001704	time 0.4734 (0.4869)	model_time 0.4732 (0.4727)	loss 3.3362 (3.1945)	grad_norm 0.9860 (1.9250/0.7881)	mem 16099MB
[2025-01-18 05:44:00 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][110/312]	eta 0:01:37 lr 0.001703	time 0.4563 (0.4848)	model_time 0.4562 (0.4718)	loss 3.8518 (3.1937)	grad_norm 1.7674 (1.9179/0.7794)	mem 16099MB
[2025-01-18 05:44:05 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][120/312]	eta 0:01:32 lr 0.001702	time 0.5576 (0.4829)	model_time 0.5575 (0.4710)	loss 3.5979 (3.2034)	grad_norm 1.7796 (1.9557/0.8234)	mem 16099MB
[2025-01-18 05:44:09 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][130/312]	eta 0:01:27 lr 0.001702	time 0.4475 (0.4810)	model_time 0.4472 (0.4700)	loss 3.8432 (3.2262)	grad_norm 2.5799 (2.0072/0.8780)	mem 16099MB
[2025-01-18 05:44:14 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][140/312]	eta 0:01:22 lr 0.001701	time 0.4464 (0.4791)	model_time 0.4460 (0.4689)	loss 2.9812 (3.2329)	grad_norm 1.4275 (1.9937/0.8700)	mem 16099MB
[2025-01-18 05:44:18 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][150/312]	eta 0:01:17 lr 0.001700	time 0.4388 (0.4787)	model_time 0.4386 (0.4691)	loss 3.4427 (3.2116)	grad_norm 1.7376 (1.9708/0.8530)	mem 16099MB
[2025-01-18 05:44:23 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][160/312]	eta 0:01:12 lr 0.001700	time 0.4451 (0.4772)	model_time 0.4447 (0.4682)	loss 3.8050 (3.2311)	grad_norm 1.4045 (2.0076/0.8833)	mem 16099MB
[2025-01-18 05:44:28 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][170/312]	eta 0:01:07 lr 0.001699	time 0.4572 (0.4765)	model_time 0.4569 (0.4680)	loss 2.9769 (3.2249)	grad_norm 0.9244 (1.9879/0.8760)	mem 16099MB
[2025-01-18 05:44:32 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][180/312]	eta 0:01:02 lr 0.001698	time 0.4529 (0.4754)	model_time 0.4528 (0.4673)	loss 2.3727 (3.2104)	grad_norm 1.8626 (1.9723/0.8768)	mem 16099MB
[2025-01-18 05:44:37 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][190/312]	eta 0:00:57 lr 0.001698	time 0.5460 (0.4754)	model_time 0.5456 (0.4677)	loss 2.5990 (3.2149)	grad_norm 1.8907 (1.9464/0.8730)	mem 16099MB
[2025-01-18 05:44:42 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][200/312]	eta 0:00:53 lr 0.001697	time 0.4477 (0.4749)	model_time 0.4474 (0.4676)	loss 3.2027 (3.2149)	grad_norm 3.1467 (1.9502/0.8668)	mem 16099MB
[2025-01-18 05:44:46 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][210/312]	eta 0:00:48 lr 0.001696	time 0.4510 (0.4740)	model_time 0.4505 (0.4670)	loss 2.7356 (3.2038)	grad_norm 1.9553 (1.9734/0.8590)	mem 16099MB
[2025-01-18 05:44:51 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][220/312]	eta 0:00:43 lr 0.001696	time 0.4592 (0.4734)	model_time 0.4590 (0.4667)	loss 3.2667 (3.1924)	grad_norm 2.6988 (1.9735/0.8467)	mem 16099MB
[2025-01-18 05:44:56 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][230/312]	eta 0:00:38 lr 0.001695	time 0.4551 (0.4735)	model_time 0.4550 (0.4671)	loss 3.4190 (3.1961)	grad_norm 0.9990 (1.9530/0.8372)	mem 16099MB
[2025-01-18 05:45:00 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][240/312]	eta 0:00:34 lr 0.001695	time 0.4548 (0.4729)	model_time 0.4543 (0.4667)	loss 2.4723 (3.1926)	grad_norm 2.4451 (1.9389/0.8308)	mem 16099MB
[2025-01-18 05:45:05 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][250/312]	eta 0:00:29 lr 0.001694	time 0.4501 (0.4723)	model_time 0.4497 (0.4664)	loss 2.6937 (3.1798)	grad_norm 2.0859 (1.9552/0.8333)	mem 16099MB
[2025-01-18 05:45:09 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][260/312]	eta 0:00:24 lr 0.001693	time 0.4597 (0.4722)	model_time 0.4595 (0.4665)	loss 3.5327 (3.1870)	grad_norm 1.6521 (1.9560/0.8255)	mem 16099MB
[2025-01-18 05:45:14 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][270/312]	eta 0:00:19 lr 0.001693	time 0.4599 (0.4723)	model_time 0.4594 (0.4668)	loss 3.3706 (3.1877)	grad_norm 2.8810 (1.9383/0.8216)	mem 16099MB
[2025-01-18 05:45:19 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][280/312]	eta 0:00:15 lr 0.001692	time 0.4428 (0.4721)	model_time 0.4426 (0.4668)	loss 2.5325 (3.1848)	grad_norm 1.4160 (1.9249/0.8123)	mem 16099MB
[2025-01-18 05:45:24 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][290/312]	eta 0:00:10 lr 0.001691	time 0.4412 (0.4725)	model_time 0.4411 (0.4673)	loss 2.6530 (3.1720)	grad_norm 1.9643 (1.9380/0.8361)	mem 16099MB
[2025-01-18 05:45:28 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][300/312]	eta 0:00:05 lr 0.001691	time 0.4384 (0.4717)	model_time 0.4383 (0.4667)	loss 2.9610 (3.1738)	grad_norm 1.2318 (1.9358/0.8329)	mem 16099MB
[2025-01-18 05:45:33 internimage_t_1k_224] (main.py 510): INFO Train: [165/300][310/312]	eta 0:00:00 lr 0.001690	time 0.4374 (0.4710)	model_time 0.4374 (0.4662)	loss 3.6214 (3.1758)	grad_norm 1.5259 (1.9382/0.8298)	mem 16099MB
[2025-01-18 05:45:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 165 training takes 0:02:26
[2025-01-18 05:45:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_165.pth saving......
[2025-01-18 05:45:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_165.pth saved !!!
[2025-01-18 05:45:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.650 (7.650)	Loss 0.8412 (0.8412)	Acc@1 83.472 (83.472)	Acc@5 96.533 (96.533)	Mem 16099MB
[2025-01-18 05:45:46 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.032)	Loss 1.1240 (0.9599)	Acc@1 75.024 (79.872)	Acc@5 93.335 (95.128)	Mem 16099MB
[2025-01-18 05:45:46 internimage_t_1k_224] (main.py 575): INFO [Epoch:165] * Acc@1 79.842 Acc@5 95.170
[2025-01-18 05:45:46 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.8%
[2025-01-18 05:45:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 05:45:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 05:45:47 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.84%
[2025-01-18 05:45:55 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.610 (7.610)	Loss 0.8104 (0.8104)	Acc@1 84.253 (84.253)	Acc@5 97.192 (97.192)	Mem 16099MB
[2025-01-18 05:45:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.034)	Loss 1.1016 (0.9393)	Acc@1 76.392 (81.317)	Acc@5 94.263 (95.716)	Mem 16099MB
[2025-01-18 05:45:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:165] * Acc@1 81.196 Acc@5 95.743
[2025-01-18 05:45:59 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.2%
[2025-01-18 05:45:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:46:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:46:00 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.20%
[2025-01-18 05:46:02 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][0/312]	eta 0:11:01 lr 0.001690	time 2.1203 (2.1203)	model_time 0.4760 (0.4760)	loss 3.2011 (3.2011)	grad_norm 1.3133 (1.3133/0.0000)	mem 16099MB
[2025-01-18 05:46:07 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][10/312]	eta 0:03:10 lr 0.001689	time 0.4641 (0.6323)	model_time 0.4639 (0.4825)	loss 3.6681 (3.0807)	grad_norm 1.5160 (1.7371/0.5294)	mem 16099MB
[2025-01-18 05:46:11 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][20/312]	eta 0:02:40 lr 0.001688	time 0.4489 (0.5483)	model_time 0.4484 (0.4697)	loss 3.0036 (3.1413)	grad_norm 3.5289 (1.8672/0.6274)	mem 16099MB
[2025-01-18 05:46:16 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][30/312]	eta 0:02:27 lr 0.001688	time 0.4609 (0.5241)	model_time 0.4605 (0.4707)	loss 4.1708 (3.1634)	grad_norm 1.7933 (1.8743/0.6532)	mem 16099MB
[2025-01-18 05:46:21 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][40/312]	eta 0:02:19 lr 0.001687	time 0.4489 (0.5120)	model_time 0.4486 (0.4715)	loss 3.4628 (3.1457)	grad_norm 1.3656 (1.8133/0.6517)	mem 16099MB
[2025-01-18 05:46:25 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][50/312]	eta 0:02:11 lr 0.001687	time 0.4503 (0.5030)	model_time 0.4499 (0.4704)	loss 3.3640 (3.1391)	grad_norm 1.2282 (1.7591/0.6409)	mem 16099MB
[2025-01-18 05:46:30 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][60/312]	eta 0:02:05 lr 0.001686	time 0.5517 (0.4966)	model_time 0.5513 (0.4692)	loss 2.5990 (3.1165)	grad_norm 1.2793 (1.7947/0.6865)	mem 16099MB
[2025-01-18 05:46:35 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][70/312]	eta 0:01:58 lr 0.001685	time 0.4546 (0.4917)	model_time 0.4545 (0.4682)	loss 2.7958 (3.1093)	grad_norm 1.8578 (1.7922/0.7052)	mem 16099MB
[2025-01-18 05:46:39 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][80/312]	eta 0:01:53 lr 0.001685	time 0.4763 (0.4884)	model_time 0.4762 (0.4677)	loss 3.1680 (3.1116)	grad_norm 2.6088 (1.8535/0.7266)	mem 16099MB
[2025-01-18 05:46:44 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][90/312]	eta 0:01:47 lr 0.001684	time 0.4528 (0.4844)	model_time 0.4524 (0.4660)	loss 2.2591 (3.0939)	grad_norm 1.3211 (1.8672/0.7166)	mem 16099MB
[2025-01-18 05:46:48 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][100/312]	eta 0:01:42 lr 0.001683	time 0.4551 (0.4821)	model_time 0.4549 (0.4654)	loss 3.8823 (3.1429)	grad_norm 1.5882 (1.8462/0.6890)	mem 16099MB
[2025-01-18 05:46:53 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][110/312]	eta 0:01:36 lr 0.001683	time 0.4564 (0.4796)	model_time 0.4563 (0.4644)	loss 2.8305 (3.1432)	grad_norm 1.0414 (1.8106/0.6759)	mem 16099MB
[2025-01-18 05:46:57 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][120/312]	eta 0:01:31 lr 0.001682	time 0.4489 (0.4779)	model_time 0.4487 (0.4639)	loss 4.0080 (3.1619)	grad_norm 1.6258 (1.7787/0.6620)	mem 16099MB
[2025-01-18 05:47:02 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][130/312]	eta 0:01:26 lr 0.001681	time 0.4480 (0.4776)	model_time 0.4477 (0.4646)	loss 2.7735 (3.1577)	grad_norm 1.2165 (1.7748/0.6603)	mem 16099MB
[2025-01-18 05:47:07 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][140/312]	eta 0:01:21 lr 0.001681	time 0.4438 (0.4766)	model_time 0.4434 (0.4645)	loss 3.4104 (3.1764)	grad_norm 2.3347 (1.7518/0.6536)	mem 16099MB
[2025-01-18 05:47:11 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][150/312]	eta 0:01:17 lr 0.001680	time 0.4528 (0.4754)	model_time 0.4527 (0.4641)	loss 3.4867 (3.1807)	grad_norm 1.5481 (1.8310/0.7974)	mem 16099MB
[2025-01-18 05:47:16 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][160/312]	eta 0:01:12 lr 0.001679	time 0.4478 (0.4759)	model_time 0.4473 (0.4653)	loss 2.9510 (3.1754)	grad_norm 2.1947 (1.8561/0.7928)	mem 16099MB
[2025-01-18 05:47:21 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][170/312]	eta 0:01:07 lr 0.001679	time 0.4470 (0.4751)	model_time 0.4469 (0.4651)	loss 3.2921 (3.1844)	grad_norm 2.5446 (1.9032/0.8220)	mem 16099MB
[2025-01-18 05:47:26 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][180/312]	eta 0:01:02 lr 0.001678	time 0.4495 (0.4742)	model_time 0.4491 (0.4648)	loss 3.5299 (3.1829)	grad_norm 1.1067 (1.9104/0.8177)	mem 16099MB
[2025-01-18 05:47:30 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][190/312]	eta 0:00:57 lr 0.001677	time 0.4467 (0.4735)	model_time 0.4463 (0.4645)	loss 2.9307 (3.1819)	grad_norm 1.0212 (1.9302/0.8436)	mem 16099MB
[2025-01-18 05:47:35 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][200/312]	eta 0:00:53 lr 0.001677	time 0.4486 (0.4737)	model_time 0.4482 (0.4652)	loss 3.3429 (3.1812)	grad_norm 1.5078 (1.9087/0.8338)	mem 16099MB
[2025-01-18 05:47:40 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][210/312]	eta 0:00:48 lr 0.001676	time 0.4561 (0.4736)	model_time 0.4559 (0.4655)	loss 4.0029 (3.1833)	grad_norm 2.2330 (1.9240/0.8625)	mem 16099MB
[2025-01-18 05:47:44 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][220/312]	eta 0:00:43 lr 0.001675	time 0.4760 (0.4742)	model_time 0.4758 (0.4664)	loss 2.8081 (3.1815)	grad_norm 2.0035 (1.9469/0.8629)	mem 16099MB
[2025-01-18 05:47:49 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][230/312]	eta 0:00:38 lr 0.001675	time 0.4727 (0.4735)	model_time 0.4723 (0.4660)	loss 3.1105 (3.1794)	grad_norm 1.7438 (1.9330/0.8539)	mem 16099MB
[2025-01-18 05:47:54 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][240/312]	eta 0:00:34 lr 0.001674	time 0.5523 (0.4734)	model_time 0.5519 (0.4662)	loss 3.0225 (3.1731)	grad_norm 2.2247 (1.9132/0.8478)	mem 16099MB
[2025-01-18 05:47:58 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][250/312]	eta 0:00:29 lr 0.001673	time 0.4440 (0.4729)	model_time 0.4439 (0.4660)	loss 3.7083 (3.1829)	grad_norm 1.8135 (1.9312/0.8673)	mem 16099MB
[2025-01-18 05:48:03 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][260/312]	eta 0:00:24 lr 0.001673	time 0.4583 (0.4724)	model_time 0.4578 (0.4658)	loss 3.3624 (3.1688)	grad_norm 2.2681 (1.9609/0.9142)	mem 16099MB
[2025-01-18 05:48:08 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][270/312]	eta 0:00:19 lr 0.001672	time 0.4488 (0.4725)	model_time 0.4487 (0.4661)	loss 3.8655 (3.1706)	grad_norm 1.1515 (1.9573/0.9084)	mem 16099MB
[2025-01-18 05:48:12 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][280/312]	eta 0:00:15 lr 0.001671	time 0.4459 (0.4721)	model_time 0.4455 (0.4659)	loss 3.8549 (3.1645)	grad_norm 1.2064 (1.9348/0.9031)	mem 16099MB
[2025-01-18 05:48:17 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][290/312]	eta 0:00:10 lr 0.001671	time 0.4628 (0.4717)	model_time 0.4626 (0.4657)	loss 3.4635 (3.1695)	grad_norm 1.9043 (1.9234/0.8917)	mem 16099MB
[2025-01-18 05:48:22 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][300/312]	eta 0:00:05 lr 0.001670	time 0.4375 (0.4718)	model_time 0.4374 (0.4660)	loss 3.9532 (3.1684)	grad_norm 2.5005 (1.9281/0.8973)	mem 16099MB
[2025-01-18 05:48:26 internimage_t_1k_224] (main.py 510): INFO Train: [166/300][310/312]	eta 0:00:00 lr 0.001670	time 0.4382 (0.4709)	model_time 0.4381 (0.4653)	loss 3.2203 (3.1683)	grad_norm 2.3334 (1.9413/0.9072)	mem 16099MB
[2025-01-18 05:48:27 internimage_t_1k_224] (main.py 519): INFO EPOCH 166 training takes 0:02:26
[2025-01-18 05:48:27 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_166.pth saving......
[2025-01-18 05:48:28 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_166.pth saved !!!
[2025-01-18 05:48:35 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.452 (7.452)	Loss 0.7717 (0.7717)	Acc@1 82.715 (82.715)	Acc@5 96.826 (96.826)	Mem 16099MB
[2025-01-18 05:48:39 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.012)	Loss 1.0953 (0.9140)	Acc@1 75.024 (79.850)	Acc@5 93.262 (95.219)	Mem 16099MB
[2025-01-18 05:48:39 internimage_t_1k_224] (main.py 575): INFO [Epoch:166] * Acc@1 79.784 Acc@5 95.230
[2025-01-18 05:48:39 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.8%
[2025-01-18 05:48:39 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.84%
[2025-01-18 05:48:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.446 (8.446)	Loss 0.8101 (0.8101)	Acc@1 84.253 (84.253)	Acc@5 97.217 (97.217)	Mem 16099MB
[2025-01-18 05:48:51 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.119)	Loss 1.1004 (0.9387)	Acc@1 76.367 (81.319)	Acc@5 94.214 (95.732)	Mem 16099MB
[2025-01-18 05:48:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:166] * Acc@1 81.200 Acc@5 95.763
[2025-01-18 05:48:52 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.2%
[2025-01-18 05:48:52 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:48:53 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:48:53 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.20%
[2025-01-18 05:48:55 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][0/312]	eta 0:11:46 lr 0.001669	time 2.2649 (2.2649)	model_time 0.4951 (0.4951)	loss 3.1214 (3.1214)	grad_norm 1.3369 (1.3369/0.0000)	mem 16099MB
[2025-01-18 05:49:00 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][10/312]	eta 0:03:10 lr 0.001669	time 0.4721 (0.6297)	model_time 0.4720 (0.4685)	loss 2.6046 (3.2383)	grad_norm 1.1048 (1.3973/0.4552)	mem 16099MB
[2025-01-18 05:49:04 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][20/312]	eta 0:02:40 lr 0.001668	time 0.4501 (0.5492)	model_time 0.4497 (0.4646)	loss 4.0578 (3.3294)	grad_norm 2.5389 (1.5835/0.5038)	mem 16099MB
[2025-01-18 05:49:09 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][30/312]	eta 0:02:28 lr 0.001667	time 0.4395 (0.5254)	model_time 0.4390 (0.4679)	loss 3.2996 (3.3619)	grad_norm 1.7490 (1.8528/0.8905)	mem 16099MB
[2025-01-18 05:49:14 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][40/312]	eta 0:02:18 lr 0.001667	time 0.4673 (0.5086)	model_time 0.4671 (0.4651)	loss 2.5749 (3.3448)	grad_norm 2.3631 (1.9584/0.8489)	mem 16099MB
[2025-01-18 05:49:18 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][50/312]	eta 0:02:10 lr 0.001666	time 0.4486 (0.4993)	model_time 0.4482 (0.4642)	loss 3.4821 (3.3359)	grad_norm 1.4073 (1.9581/0.8748)	mem 16099MB
[2025-01-18 05:49:23 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][60/312]	eta 0:02:04 lr 0.001665	time 0.4474 (0.4933)	model_time 0.4470 (0.4639)	loss 3.3762 (3.3394)	grad_norm 3.2605 (1.9821/0.8752)	mem 16099MB
[2025-01-18 05:49:28 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][70/312]	eta 0:01:58 lr 0.001665	time 0.4720 (0.4888)	model_time 0.4719 (0.4635)	loss 4.0417 (3.3359)	grad_norm 1.2394 (2.1598/1.1391)	mem 16099MB
[2025-01-18 05:49:32 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][80/312]	eta 0:01:52 lr 0.001664	time 0.4511 (0.4849)	model_time 0.4506 (0.4627)	loss 2.2056 (3.2853)	grad_norm 2.0142 (2.1864/1.1048)	mem 16099MB
[2025-01-18 05:49:37 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][90/312]	eta 0:01:47 lr 0.001663	time 0.4563 (0.4827)	model_time 0.4558 (0.4629)	loss 2.2491 (3.2656)	grad_norm 1.4051 (2.1028/1.0786)	mem 16099MB
[2025-01-18 05:49:41 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][100/312]	eta 0:01:41 lr 0.001663	time 0.4397 (0.4806)	model_time 0.4393 (0.4627)	loss 3.5048 (3.2567)	grad_norm 1.7913 (2.0323/1.0502)	mem 16099MB
[2025-01-18 05:49:46 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][110/312]	eta 0:01:36 lr 0.001662	time 0.4545 (0.4797)	model_time 0.4542 (0.4634)	loss 3.4118 (3.2539)	grad_norm 1.8338 (1.9751/1.0295)	mem 16099MB
[2025-01-18 05:49:51 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][120/312]	eta 0:01:31 lr 0.001662	time 0.5345 (0.4791)	model_time 0.5344 (0.4642)	loss 3.0379 (3.2611)	grad_norm 1.8210 (1.9222/1.0074)	mem 16099MB
[2025-01-18 05:49:55 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][130/312]	eta 0:01:27 lr 0.001661	time 0.4535 (0.4784)	model_time 0.4533 (0.4645)	loss 3.1941 (3.2666)	grad_norm 1.4154 (1.9253/0.9879)	mem 16099MB
[2025-01-18 05:50:00 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][140/312]	eta 0:01:22 lr 0.001660	time 0.5425 (0.4797)	model_time 0.5420 (0.4668)	loss 3.6864 (3.2647)	grad_norm 4.0947 (1.9434/0.9958)	mem 16099MB
[2025-01-18 05:50:05 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][150/312]	eta 0:01:17 lr 0.001660	time 0.4419 (0.4786)	model_time 0.4417 (0.4665)	loss 2.3855 (3.2686)	grad_norm 1.7924 (2.0013/1.0115)	mem 16099MB
[2025-01-18 05:50:10 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][160/312]	eta 0:01:12 lr 0.001659	time 0.4615 (0.4780)	model_time 0.4610 (0.4666)	loss 2.9515 (3.2499)	grad_norm 1.0915 (1.9866/0.9927)	mem 16099MB
[2025-01-18 05:50:14 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][170/312]	eta 0:01:07 lr 0.001658	time 0.4449 (0.4766)	model_time 0.4446 (0.4658)	loss 2.8472 (3.2432)	grad_norm 1.2273 (1.9593/0.9776)	mem 16099MB
[2025-01-18 05:50:19 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][180/312]	eta 0:01:02 lr 0.001658	time 0.4507 (0.4752)	model_time 0.4503 (0.4650)	loss 3.3194 (3.2402)	grad_norm 1.7256 (1.9635/0.9730)	mem 16099MB
[2025-01-18 05:50:23 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][190/312]	eta 0:00:57 lr 0.001657	time 0.4619 (0.4742)	model_time 0.4617 (0.4646)	loss 3.1321 (3.2336)	grad_norm 1.1328 (1.9425/0.9556)	mem 16099MB
[2025-01-18 05:50:28 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][200/312]	eta 0:00:53 lr 0.001656	time 0.4496 (0.4749)	model_time 0.4495 (0.4658)	loss 3.2872 (3.2338)	grad_norm 0.9360 (1.9235/0.9519)	mem 16099MB
[2025-01-18 05:50:33 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][210/312]	eta 0:00:48 lr 0.001656	time 0.4489 (0.4741)	model_time 0.4484 (0.4653)	loss 2.4669 (3.2366)	grad_norm 1.9020 (1.9180/0.9382)	mem 16099MB
[2025-01-18 05:50:38 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][220/312]	eta 0:00:43 lr 0.001655	time 0.4562 (0.4743)	model_time 0.4560 (0.4659)	loss 3.0839 (3.2357)	grad_norm 1.0855 (1.9043/0.9240)	mem 16099MB
[2025-01-18 05:50:42 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][230/312]	eta 0:00:38 lr 0.001654	time 0.5457 (0.4743)	model_time 0.5452 (0.4663)	loss 3.3349 (3.2399)	grad_norm 2.9840 (1.9171/0.9246)	mem 16099MB
[2025-01-18 05:50:47 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][240/312]	eta 0:00:34 lr 0.001654	time 0.4484 (0.4734)	model_time 0.4482 (0.4656)	loss 3.8502 (3.2234)	grad_norm 2.3822 (1.9631/0.9474)	mem 16099MB
[2025-01-18 05:50:51 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][250/312]	eta 0:00:29 lr 0.001653	time 0.4638 (0.4726)	model_time 0.4636 (0.4652)	loss 3.3000 (3.2098)	grad_norm 0.8915 (1.9582/0.9460)	mem 16099MB
[2025-01-18 05:50:56 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][260/312]	eta 0:00:24 lr 0.001652	time 0.4520 (0.4729)	model_time 0.4518 (0.4657)	loss 3.4152 (3.2107)	grad_norm 0.7178 (1.9281/0.9414)	mem 16099MB
[2025-01-18 05:51:01 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][270/312]	eta 0:00:19 lr 0.001652	time 0.4523 (0.4722)	model_time 0.4521 (0.4652)	loss 2.8389 (3.2111)	grad_norm 1.5522 (1.9097/0.9317)	mem 16099MB
[2025-01-18 05:51:05 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][280/312]	eta 0:00:15 lr 0.001651	time 0.5701 (0.4720)	model_time 0.5700 (0.4653)	loss 3.3876 (3.2183)	grad_norm 1.6937 (1.9139/0.9212)	mem 16099MB
[2025-01-18 05:51:10 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][290/312]	eta 0:00:10 lr 0.001650	time 0.4509 (0.4718)	model_time 0.4507 (0.4654)	loss 3.4834 (3.2209)	grad_norm 2.6760 (1.9126/0.9113)	mem 16099MB
[2025-01-18 05:51:15 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][300/312]	eta 0:00:05 lr 0.001650	time 0.4382 (0.4712)	model_time 0.4381 (0.4649)	loss 3.3347 (3.2172)	grad_norm 2.3575 (1.9168/0.9003)	mem 16099MB
[2025-01-18 05:51:19 internimage_t_1k_224] (main.py 510): INFO Train: [167/300][310/312]	eta 0:00:00 lr 0.001649	time 0.4381 (0.4712)	model_time 0.4380 (0.4651)	loss 3.7307 (3.2220)	grad_norm 2.6990 (1.9522/0.9080)	mem 16099MB
[2025-01-18 05:51:20 internimage_t_1k_224] (main.py 519): INFO EPOCH 167 training takes 0:02:26
[2025-01-18 05:51:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_167.pth saving......
[2025-01-18 05:51:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_167.pth saved !!!
[2025-01-18 05:51:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.412 (7.412)	Loss 0.8186 (0.8186)	Acc@1 82.861 (82.861)	Acc@5 96.753 (96.753)	Mem 16099MB
[2025-01-18 05:51:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.992)	Loss 1.1151 (0.9444)	Acc@1 74.780 (80.020)	Acc@5 93.530 (95.293)	Mem 16099MB
[2025-01-18 05:51:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:167] * Acc@1 79.916 Acc@5 95.323
[2025-01-18 05:51:32 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.9%
[2025-01-18 05:51:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 05:51:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 05:51:33 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.92%
[2025-01-18 05:51:41 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.320 (7.320)	Loss 0.8100 (0.8100)	Acc@1 84.253 (84.253)	Acc@5 97.241 (97.241)	Mem 16099MB
[2025-01-18 05:51:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (0.991)	Loss 1.0991 (0.9382)	Acc@1 76.514 (81.359)	Acc@5 94.263 (95.732)	Mem 16099MB
[2025-01-18 05:51:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:167] * Acc@1 81.242 Acc@5 95.769
[2025-01-18 05:51:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.2%
[2025-01-18 05:51:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:51:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:51:46 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.24%
[2025-01-18 05:51:48 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][0/312]	eta 0:10:20 lr 0.001649	time 1.9901 (1.9901)	model_time 0.5683 (0.5683)	loss 3.2478 (3.2478)	grad_norm 3.2354 (3.2354/0.0000)	mem 16099MB
[2025-01-18 05:51:52 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][10/312]	eta 0:03:04 lr 0.001648	time 0.4566 (0.6101)	model_time 0.4565 (0.4806)	loss 2.9844 (3.1847)	grad_norm 1.1262 (1.7912/0.5784)	mem 16099MB
[2025-01-18 05:51:57 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][20/312]	eta 0:02:36 lr 0.001648	time 0.4396 (0.5372)	model_time 0.4395 (0.4693)	loss 3.0910 (3.1135)	grad_norm 1.3989 (1.6401/0.5111)	mem 16099MB
[2025-01-18 05:52:01 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][30/312]	eta 0:02:25 lr 0.001647	time 0.4625 (0.5143)	model_time 0.4624 (0.4681)	loss 3.3493 (3.1333)	grad_norm 2.6129 (1.9465/0.9558)	mem 16099MB
[2025-01-18 05:52:06 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][40/312]	eta 0:02:17 lr 0.001646	time 0.4547 (0.5045)	model_time 0.4543 (0.4695)	loss 3.6054 (3.1425)	grad_norm 1.1351 (1.9811/0.9169)	mem 16099MB
[2025-01-18 05:52:11 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][50/312]	eta 0:02:10 lr 0.001646	time 0.4475 (0.4964)	model_time 0.4473 (0.4682)	loss 3.4163 (3.1757)	grad_norm 2.9277 (1.9972/0.8760)	mem 16099MB
[2025-01-18 05:52:15 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][60/312]	eta 0:02:03 lr 0.001645	time 0.4635 (0.4910)	model_time 0.4634 (0.4673)	loss 3.8252 (3.1773)	grad_norm 1.2062 (1.9934/0.9107)	mem 16099MB
[2025-01-18 05:52:20 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][70/312]	eta 0:01:57 lr 0.001644	time 0.4570 (0.4860)	model_time 0.4566 (0.4656)	loss 2.8092 (3.1392)	grad_norm 1.1619 (2.0093/0.9006)	mem 16099MB
[2025-01-18 05:52:25 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][80/312]	eta 0:01:51 lr 0.001644	time 0.4549 (0.4826)	model_time 0.4544 (0.4647)	loss 3.7970 (3.1432)	grad_norm 1.3921 (1.9810/0.8657)	mem 16099MB
[2025-01-18 05:52:29 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][90/312]	eta 0:01:47 lr 0.001643	time 0.5564 (0.4829)	model_time 0.5560 (0.4669)	loss 2.5911 (3.1226)	grad_norm 2.6504 (2.0077/0.8500)	mem 16099MB
[2025-01-18 05:52:34 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][100/312]	eta 0:01:42 lr 0.001642	time 0.4447 (0.4823)	model_time 0.4445 (0.4679)	loss 2.2884 (3.1299)	grad_norm 1.7087 (2.0591/0.8808)	mem 16099MB
[2025-01-18 05:52:39 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][110/312]	eta 0:01:37 lr 0.001642	time 0.4430 (0.4812)	model_time 0.4426 (0.4680)	loss 3.2918 (3.1318)	grad_norm 1.2591 (2.0558/0.8802)	mem 16099MB
[2025-01-18 05:52:44 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][120/312]	eta 0:01:32 lr 0.001641	time 0.4600 (0.4806)	model_time 0.4598 (0.4685)	loss 2.7339 (3.1321)	grad_norm 1.2663 (2.0640/0.8850)	mem 16099MB
[2025-01-18 05:52:48 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][130/312]	eta 0:01:27 lr 0.001641	time 0.4468 (0.4803)	model_time 0.4466 (0.4691)	loss 3.3471 (3.1550)	grad_norm 1.0444 (2.0792/0.8931)	mem 16099MB
[2025-01-18 05:52:53 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][140/312]	eta 0:01:22 lr 0.001640	time 0.4468 (0.4800)	model_time 0.4467 (0.4695)	loss 3.4296 (3.1782)	grad_norm 1.1954 (2.0610/0.8727)	mem 16099MB
[2025-01-18 05:52:58 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][150/312]	eta 0:01:17 lr 0.001639	time 0.4509 (0.4801)	model_time 0.4505 (0.4703)	loss 3.3989 (3.1799)	grad_norm 1.9223 (2.0308/0.8671)	mem 16099MB
[2025-01-18 05:53:03 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][160/312]	eta 0:01:12 lr 0.001639	time 0.4564 (0.4793)	model_time 0.4562 (0.4701)	loss 3.3543 (3.1940)	grad_norm 3.4844 (2.0552/0.8829)	mem 16099MB
[2025-01-18 05:53:07 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][170/312]	eta 0:01:07 lr 0.001638	time 0.4849 (0.4785)	model_time 0.4848 (0.4698)	loss 2.9270 (3.2032)	grad_norm 1.6332 (2.0560/0.8890)	mem 16099MB
[2025-01-18 05:53:12 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][180/312]	eta 0:01:02 lr 0.001637	time 0.4398 (0.4771)	model_time 0.4394 (0.4688)	loss 2.4569 (3.1965)	grad_norm 1.3313 (2.0343/0.8815)	mem 16099MB
[2025-01-18 05:53:16 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][190/312]	eta 0:00:58 lr 0.001637	time 0.4508 (0.4759)	model_time 0.4504 (0.4681)	loss 3.5998 (3.1911)	grad_norm 1.9225 (2.0165/0.8668)	mem 16099MB
[2025-01-18 05:53:21 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][200/312]	eta 0:00:53 lr 0.001636	time 0.5183 (0.4775)	model_time 0.5178 (0.4700)	loss 3.3802 (3.1956)	grad_norm 0.9848 (1.9963/0.8597)	mem 16099MB
[2025-01-18 05:53:26 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][210/312]	eta 0:00:48 lr 0.001635	time 0.4434 (0.4772)	model_time 0.4430 (0.4701)	loss 2.6258 (3.1846)	grad_norm 0.8993 (2.0434/0.9266)	mem 16099MB
[2025-01-18 05:53:31 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][220/312]	eta 0:00:43 lr 0.001635	time 0.4596 (0.4763)	model_time 0.4592 (0.4694)	loss 2.9362 (3.1856)	grad_norm 0.9559 (2.0484/0.9318)	mem 16099MB
[2025-01-18 05:53:35 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][230/312]	eta 0:00:39 lr 0.001634	time 0.4864 (0.4758)	model_time 0.4862 (0.4693)	loss 2.8558 (3.1808)	grad_norm 2.1815 (2.0169/0.9277)	mem 16099MB
[2025-01-18 05:53:40 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][240/312]	eta 0:00:34 lr 0.001633	time 0.4659 (0.4752)	model_time 0.4655 (0.4689)	loss 2.7418 (3.1715)	grad_norm 1.8427 (2.0124/0.9169)	mem 16099MB
[2025-01-18 05:53:45 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][250/312]	eta 0:00:29 lr 0.001633	time 0.4522 (0.4743)	model_time 0.4520 (0.4682)	loss 1.9936 (3.1604)	grad_norm 2.4876 (2.0183/0.9058)	mem 16099MB
[2025-01-18 05:53:49 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][260/312]	eta 0:00:24 lr 0.001632	time 0.4512 (0.4741)	model_time 0.4508 (0.4683)	loss 2.7526 (3.1477)	grad_norm 1.4274 (2.0235/0.8943)	mem 16099MB
[2025-01-18 05:53:54 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][270/312]	eta 0:00:19 lr 0.001631	time 0.4596 (0.4734)	model_time 0.4595 (0.4678)	loss 2.6655 (3.1484)	grad_norm 2.4277 (2.0225/0.8972)	mem 16099MB
[2025-01-18 05:53:58 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][280/312]	eta 0:00:15 lr 0.001631	time 0.4468 (0.4731)	model_time 0.4467 (0.4676)	loss 3.6293 (3.1602)	grad_norm 1.8819 (2.0135/0.8857)	mem 16099MB
[2025-01-18 05:54:03 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][290/312]	eta 0:00:10 lr 0.001630	time 0.4552 (0.4731)	model_time 0.4550 (0.4679)	loss 2.9284 (3.1601)	grad_norm 0.9677 (1.9960/0.8794)	mem 16099MB
[2025-01-18 05:54:08 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][300/312]	eta 0:00:05 lr 0.001629	time 0.4389 (0.4727)	model_time 0.4387 (0.4676)	loss 3.8682 (3.1622)	grad_norm 2.2640 (1.9849/0.8707)	mem 16099MB
[2025-01-18 05:54:12 internimage_t_1k_224] (main.py 510): INFO Train: [168/300][310/312]	eta 0:00:00 lr 0.001629	time 0.4396 (0.4720)	model_time 0.4395 (0.4671)	loss 2.8044 (3.1640)	grad_norm 0.8321 (2.0009/0.8986)	mem 16099MB
[2025-01-18 05:54:13 internimage_t_1k_224] (main.py 519): INFO EPOCH 168 training takes 0:02:27
[2025-01-18 05:54:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_168.pth saving......
[2025-01-18 05:54:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_168.pth saved !!!
[2025-01-18 05:54:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.233 (7.233)	Loss 0.8226 (0.8226)	Acc@1 82.788 (82.788)	Acc@5 96.753 (96.753)	Mem 16099MB
[2025-01-18 05:54:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.973)	Loss 1.1169 (0.9526)	Acc@1 75.781 (79.969)	Acc@5 93.335 (95.148)	Mem 16099MB
[2025-01-18 05:54:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:168] * Acc@1 79.932 Acc@5 95.164
[2025-01-18 05:54:25 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.9%
[2025-01-18 05:54:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 05:54:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 05:54:26 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.93%
[2025-01-18 05:54:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.344 (7.344)	Loss 0.8095 (0.8095)	Acc@1 84.302 (84.302)	Acc@5 97.217 (97.217)	Mem 16099MB
[2025-01-18 05:54:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.108 (1.003)	Loss 1.0976 (0.9374)	Acc@1 76.514 (81.379)	Acc@5 94.312 (95.728)	Mem 16099MB
[2025-01-18 05:54:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:168] * Acc@1 81.266 Acc@5 95.765
[2025-01-18 05:54:37 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.3%
[2025-01-18 05:54:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:54:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:54:38 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.27%
[2025-01-18 05:54:41 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][0/312]	eta 0:11:08 lr 0.001629	time 2.1439 (2.1439)	model_time 0.4816 (0.4816)	loss 3.1449 (3.1449)	grad_norm 2.5587 (2.5587/0.0000)	mem 16099MB
[2025-01-18 05:54:46 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][10/312]	eta 0:03:13 lr 0.001628	time 0.4524 (0.6419)	model_time 0.4523 (0.4904)	loss 2.6883 (2.9317)	grad_norm 1.7762 (2.2530/0.8995)	mem 16099MB
[2025-01-18 05:54:50 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][20/312]	eta 0:02:46 lr 0.001627	time 0.5762 (0.5699)	model_time 0.5757 (0.4904)	loss 3.4185 (3.0207)	grad_norm 1.6203 (2.0305/0.7663)	mem 16099MB
[2025-01-18 05:54:55 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][30/312]	eta 0:02:30 lr 0.001627	time 0.4554 (0.5326)	model_time 0.4552 (0.4787)	loss 3.3902 (3.1348)	grad_norm 0.9696 (1.7656/0.7593)	mem 16099MB
[2025-01-18 05:55:00 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][40/312]	eta 0:02:22 lr 0.001626	time 0.4549 (0.5245)	model_time 0.4544 (0.4832)	loss 2.8532 (3.1280)	grad_norm 1.2708 (1.7317/0.7019)	mem 16099MB
[2025-01-18 05:55:05 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][50/312]	eta 0:02:14 lr 0.001625	time 0.4532 (0.5119)	model_time 0.4528 (0.4786)	loss 3.5759 (3.0744)	grad_norm 2.7973 (1.8376/0.7989)	mem 16099MB
[2025-01-18 05:55:09 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][60/312]	eta 0:02:06 lr 0.001625	time 0.4743 (0.5031)	model_time 0.4738 (0.4751)	loss 3.2447 (3.0701)	grad_norm 2.3336 (1.8698/0.8121)	mem 16099MB
[2025-01-18 05:55:14 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][70/312]	eta 0:02:00 lr 0.001624	time 0.4529 (0.4965)	model_time 0.4527 (0.4724)	loss 3.2307 (3.1090)	grad_norm 1.3513 (1.8599/0.7906)	mem 16099MB
[2025-01-18 05:55:18 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][80/312]	eta 0:01:54 lr 0.001623	time 0.4549 (0.4914)	model_time 0.4547 (0.4703)	loss 3.8020 (3.1050)	grad_norm 1.4851 (1.8728/0.7728)	mem 16099MB
[2025-01-18 05:55:23 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][90/312]	eta 0:01:49 lr 0.001623	time 0.4410 (0.4924)	model_time 0.4406 (0.4735)	loss 3.4797 (3.0950)	grad_norm 1.2329 (1.8981/0.7850)	mem 16099MB
[2025-01-18 05:55:28 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][100/312]	eta 0:01:44 lr 0.001622	time 0.4492 (0.4920)	model_time 0.4488 (0.4750)	loss 3.6295 (3.1071)	grad_norm 2.0451 (1.9121/0.7562)	mem 16099MB
[2025-01-18 05:55:33 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][110/312]	eta 0:01:38 lr 0.001621	time 0.4639 (0.4894)	model_time 0.4635 (0.4739)	loss 2.8670 (3.1057)	grad_norm 2.6166 (1.9085/0.7490)	mem 16099MB
[2025-01-18 05:55:38 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][120/312]	eta 0:01:33 lr 0.001621	time 0.4493 (0.4895)	model_time 0.4488 (0.4752)	loss 2.4932 (3.0904)	grad_norm 1.6663 (1.8993/0.7512)	mem 16099MB
[2025-01-18 05:55:43 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][130/312]	eta 0:01:28 lr 0.001620	time 0.4393 (0.4886)	model_time 0.4392 (0.4754)	loss 3.2329 (3.1042)	grad_norm 1.6352 (1.8853/0.7451)	mem 16099MB
[2025-01-18 05:55:47 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][140/312]	eta 0:01:23 lr 0.001620	time 0.4434 (0.4872)	model_time 0.4430 (0.4749)	loss 2.6387 (3.1089)	grad_norm 1.6731 (1.8844/0.7426)	mem 16099MB
[2025-01-18 05:55:52 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][150/312]	eta 0:01:18 lr 0.001619	time 0.4611 (0.4852)	model_time 0.4607 (0.4737)	loss 3.2676 (3.1099)	grad_norm 2.0951 (1.8701/0.7292)	mem 16099MB
[2025-01-18 05:55:56 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][160/312]	eta 0:01:13 lr 0.001618	time 0.4530 (0.4839)	model_time 0.4526 (0.4731)	loss 2.4053 (3.1169)	grad_norm 1.0457 (1.8502/0.7134)	mem 16099MB
[2025-01-18 05:56:01 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][170/312]	eta 0:01:08 lr 0.001618	time 0.4624 (0.4829)	model_time 0.4623 (0.4727)	loss 2.4973 (3.1033)	grad_norm 1.4139 (1.8701/0.7484)	mem 16099MB
[2025-01-18 05:56:06 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][180/312]	eta 0:01:03 lr 0.001617	time 0.4467 (0.4819)	model_time 0.4463 (0.4722)	loss 2.9611 (3.0831)	grad_norm 1.3516 (1.8476/0.7377)	mem 16099MB
[2025-01-18 05:56:10 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][190/312]	eta 0:00:58 lr 0.001616	time 0.4560 (0.4808)	model_time 0.4555 (0.4716)	loss 2.4677 (3.0846)	grad_norm 1.8311 (1.8664/0.7429)	mem 16099MB
[2025-01-18 05:56:15 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][200/312]	eta 0:00:53 lr 0.001616	time 0.4534 (0.4803)	model_time 0.4532 (0.4716)	loss 3.2940 (3.0901)	grad_norm 2.2474 (1.8927/0.7429)	mem 16099MB
[2025-01-18 05:56:20 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][210/312]	eta 0:00:49 lr 0.001615	time 0.4646 (0.4808)	model_time 0.4641 (0.4724)	loss 3.6214 (3.0980)	grad_norm 2.3570 (1.9247/0.7807)	mem 16099MB
[2025-01-18 05:56:25 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][220/312]	eta 0:00:44 lr 0.001614	time 0.4738 (0.4808)	model_time 0.4733 (0.4728)	loss 3.7265 (3.1084)	grad_norm 2.9031 (1.9087/0.7740)	mem 16099MB
[2025-01-18 05:56:29 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][230/312]	eta 0:00:39 lr 0.001614	time 0.4409 (0.4799)	model_time 0.4404 (0.4722)	loss 3.7067 (3.1004)	grad_norm 2.5110 (1.9032/0.7693)	mem 16099MB
[2025-01-18 05:56:34 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][240/312]	eta 0:00:34 lr 0.001613	time 0.4499 (0.4794)	model_time 0.4498 (0.4720)	loss 3.1346 (3.0988)	grad_norm 1.2198 (1.9106/0.7657)	mem 16099MB
[2025-01-18 05:56:39 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][250/312]	eta 0:00:29 lr 0.001612	time 0.4590 (0.4787)	model_time 0.4588 (0.4716)	loss 3.5650 (3.1002)	grad_norm 1.6985 (1.8977/0.7567)	mem 16099MB
[2025-01-18 05:56:43 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][260/312]	eta 0:00:24 lr 0.001612	time 0.4441 (0.4788)	model_time 0.4436 (0.4719)	loss 2.4507 (3.1064)	grad_norm 1.7246 (1.9060/0.7534)	mem 16099MB
[2025-01-18 05:56:48 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][270/312]	eta 0:00:20 lr 0.001611	time 0.4494 (0.4781)	model_time 0.4490 (0.4715)	loss 1.9929 (3.1084)	grad_norm 3.6502 (1.9530/0.8039)	mem 16099MB
[2025-01-18 05:56:53 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][280/312]	eta 0:00:15 lr 0.001610	time 0.4581 (0.4777)	model_time 0.4577 (0.4714)	loss 2.2487 (3.1121)	grad_norm 1.2146 (1.9578/0.8122)	mem 16099MB
[2025-01-18 05:56:57 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][290/312]	eta 0:00:10 lr 0.001610	time 0.4518 (0.4771)	model_time 0.4517 (0.4709)	loss 3.5146 (3.1158)	grad_norm 1.1528 (1.9400/0.8077)	mem 16099MB
[2025-01-18 05:57:02 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][300/312]	eta 0:00:05 lr 0.001609	time 0.4367 (0.4761)	model_time 0.4366 (0.4701)	loss 2.5962 (3.1203)	grad_norm 1.9784 (1.9177/0.8047)	mem 16099MB
[2025-01-18 05:57:06 internimage_t_1k_224] (main.py 510): INFO Train: [169/300][310/312]	eta 0:00:00 lr 0.001608	time 0.4381 (0.4752)	model_time 0.4380 (0.4694)	loss 2.9769 (3.1280)	grad_norm 1.1925 (1.9032/0.7907)	mem 16099MB
[2025-01-18 05:57:07 internimage_t_1k_224] (main.py 519): INFO EPOCH 169 training takes 0:02:28
[2025-01-18 05:57:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_169.pth saving......
[2025-01-18 05:57:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_169.pth saved !!!
[2025-01-18 05:57:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.491 (7.491)	Loss 0.8314 (0.8314)	Acc@1 83.032 (83.032)	Acc@5 96.631 (96.631)	Mem 16099MB
[2025-01-18 05:57:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.013)	Loss 1.1389 (0.9581)	Acc@1 75.317 (80.018)	Acc@5 93.311 (95.199)	Mem 16099MB
[2025-01-18 05:57:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:169] * Acc@1 79.876 Acc@5 95.182
[2025-01-18 05:57:19 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 79.9%
[2025-01-18 05:57:19 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 79.93%
[2025-01-18 05:57:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.449 (8.449)	Loss 0.8092 (0.8092)	Acc@1 84.277 (84.277)	Acc@5 97.217 (97.217)	Mem 16099MB
[2025-01-18 05:57:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.123)	Loss 1.0965 (0.9368)	Acc@1 76.636 (81.439)	Acc@5 94.385 (95.741)	Mem 16099MB
[2025-01-18 05:57:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:169] * Acc@1 81.324 Acc@5 95.777
[2025-01-18 05:57:32 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.3%
[2025-01-18 05:57:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 05:57:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 05:57:33 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.32%
[2025-01-18 05:57:36 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][0/312]	eta 0:14:37 lr 0.001608	time 2.8127 (2.8127)	model_time 0.4782 (0.4782)	loss 2.1865 (2.1865)	grad_norm 0.7798 (0.7798/0.0000)	mem 16099MB
[2025-01-18 05:57:41 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][10/312]	eta 0:03:26 lr 0.001608	time 0.5431 (0.6847)	model_time 0.5430 (0.4722)	loss 3.0557 (3.0496)	grad_norm 1.4907 (1.3249/0.4502)	mem 16099MB
[2025-01-18 05:57:45 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][20/312]	eta 0:02:49 lr 0.001607	time 0.4563 (0.5808)	model_time 0.4561 (0.4693)	loss 3.2145 (3.1456)	grad_norm 1.9306 (1.3364/0.4295)	mem 16099MB
[2025-01-18 05:57:50 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][30/312]	eta 0:02:34 lr 0.001606	time 0.4477 (0.5464)	model_time 0.4475 (0.4708)	loss 2.3704 (3.0880)	grad_norm 2.3619 (1.3988/0.4374)	mem 16099MB
[2025-01-18 05:57:55 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][40/312]	eta 0:02:22 lr 0.001606	time 0.4827 (0.5255)	model_time 0.4825 (0.4683)	loss 3.6157 (3.1068)	grad_norm 1.2182 (1.6354/0.7311)	mem 16099MB
[2025-01-18 05:57:59 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][50/312]	eta 0:02:14 lr 0.001605	time 0.4590 (0.5123)	model_time 0.4589 (0.4663)	loss 1.9650 (3.0959)	grad_norm 1.1054 (1.7163/0.7339)	mem 16099MB
[2025-01-18 05:58:04 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][60/312]	eta 0:02:07 lr 0.001604	time 0.4729 (0.5046)	model_time 0.4727 (0.4660)	loss 3.1396 (3.1118)	grad_norm 3.4724 (1.8058/0.8004)	mem 16099MB
[2025-01-18 05:58:09 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][70/312]	eta 0:02:00 lr 0.001604	time 0.4451 (0.4992)	model_time 0.4449 (0.4661)	loss 2.8763 (3.1005)	grad_norm 2.4375 (1.9940/1.0344)	mem 16099MB
[2025-01-18 05:58:13 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][80/312]	eta 0:01:54 lr 0.001603	time 0.4542 (0.4944)	model_time 0.4538 (0.4653)	loss 3.1236 (3.1284)	grad_norm 1.6264 (2.0478/1.0651)	mem 16099MB
[2025-01-18 05:58:18 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][90/312]	eta 0:01:48 lr 0.001602	time 0.4562 (0.4908)	model_time 0.4560 (0.4649)	loss 3.3586 (3.1182)	grad_norm 2.9228 (2.1701/1.0908)	mem 16099MB
[2025-01-18 05:58:23 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][100/312]	eta 0:01:44 lr 0.001602	time 0.4840 (0.4916)	model_time 0.4835 (0.4682)	loss 3.9809 (3.1346)	grad_norm 1.9076 (2.1409/1.0656)	mem 16099MB
[2025-01-18 05:58:28 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][110/312]	eta 0:01:39 lr 0.001601	time 0.4520 (0.4916)	model_time 0.4515 (0.4703)	loss 3.0680 (3.1470)	grad_norm 0.9945 (2.0711/1.0468)	mem 16099MB
[2025-01-18 05:58:33 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][120/312]	eta 0:01:34 lr 0.001601	time 0.4594 (0.4911)	model_time 0.4477 (0.4715)	loss 4.0672 (3.1651)	grad_norm 2.4299 (2.0169/1.0250)	mem 16099MB
[2025-01-18 05:58:38 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][130/312]	eta 0:01:29 lr 0.001600	time 0.4622 (0.4924)	model_time 0.4620 (0.4742)	loss 3.5158 (3.1449)	grad_norm 2.4680 (2.0009/1.0186)	mem 16099MB
[2025-01-18 05:58:42 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][140/312]	eta 0:01:24 lr 0.001599	time 0.4432 (0.4906)	model_time 0.4426 (0.4736)	loss 3.3664 (3.1242)	grad_norm 1.0236 (1.9818/1.0015)	mem 16099MB
[2025-01-18 05:58:47 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][150/312]	eta 0:01:19 lr 0.001599	time 0.5224 (0.4896)	model_time 0.5222 (0.4737)	loss 3.2418 (3.1319)	grad_norm 1.1387 (1.9861/1.0266)	mem 16099MB
[2025-01-18 05:58:52 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][160/312]	eta 0:01:14 lr 0.001598	time 0.4484 (0.4872)	model_time 0.4480 (0.4723)	loss 3.0009 (3.1273)	grad_norm 2.5580 (1.9904/1.0168)	mem 16099MB
[2025-01-18 05:58:56 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][170/312]	eta 0:01:08 lr 0.001597	time 0.4502 (0.4859)	model_time 0.4498 (0.4719)	loss 2.0413 (3.1147)	grad_norm 0.9260 (1.9870/1.0090)	mem 16099MB
[2025-01-18 05:59:01 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][180/312]	eta 0:01:03 lr 0.001597	time 0.4461 (0.4845)	model_time 0.4459 (0.4712)	loss 3.5677 (3.1178)	grad_norm 1.2733 (1.9915/1.0102)	mem 16099MB
[2025-01-18 05:59:06 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][190/312]	eta 0:00:59 lr 0.001596	time 0.4552 (0.4843)	model_time 0.4550 (0.4717)	loss 2.8873 (3.1208)	grad_norm 2.6951 (1.9794/0.9903)	mem 16099MB
[2025-01-18 05:59:10 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][200/312]	eta 0:00:54 lr 0.001595	time 0.4519 (0.4829)	model_time 0.4515 (0.4709)	loss 2.3156 (3.1115)	grad_norm 1.7982 (1.9736/0.9729)	mem 16099MB
[2025-01-18 05:59:15 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][210/312]	eta 0:00:49 lr 0.001595	time 0.4706 (0.4816)	model_time 0.4702 (0.4702)	loss 2.0542 (3.1104)	grad_norm 1.6098 (1.9513/0.9599)	mem 16099MB
[2025-01-18 05:59:19 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][220/312]	eta 0:00:44 lr 0.001594	time 0.4544 (0.4809)	model_time 0.4540 (0.4699)	loss 3.3014 (3.1075)	grad_norm 1.7880 (1.9380/0.9451)	mem 16099MB
[2025-01-18 05:59:24 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][230/312]	eta 0:00:39 lr 0.001593	time 0.4538 (0.4808)	model_time 0.4536 (0.4704)	loss 3.7759 (3.0993)	grad_norm 1.3793 (1.9296/0.9348)	mem 16099MB
[2025-01-18 05:59:29 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][240/312]	eta 0:00:34 lr 0.001593	time 0.4618 (0.4797)	model_time 0.4614 (0.4697)	loss 3.7091 (3.1083)	grad_norm 2.2310 (1.9401/0.9421)	mem 16099MB
[2025-01-18 05:59:33 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][250/312]	eta 0:00:29 lr 0.001592	time 0.4479 (0.4788)	model_time 0.4475 (0.4692)	loss 2.3204 (3.1090)	grad_norm 1.3756 (1.9424/0.9312)	mem 16099MB
[2025-01-18 05:59:38 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][260/312]	eta 0:00:24 lr 0.001591	time 0.4498 (0.4782)	model_time 0.4497 (0.4689)	loss 2.8486 (3.1130)	grad_norm 1.1595 (1.9465/0.9242)	mem 16099MB
[2025-01-18 05:59:43 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][270/312]	eta 0:00:20 lr 0.001591	time 0.4468 (0.4792)	model_time 0.4466 (0.4703)	loss 3.1313 (3.1106)	grad_norm 1.1864 (1.9344/0.9164)	mem 16099MB
[2025-01-18 05:59:48 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][280/312]	eta 0:00:15 lr 0.001590	time 0.4415 (0.4785)	model_time 0.4414 (0.4699)	loss 2.3987 (3.1035)	grad_norm 3.0608 (1.9798/0.9573)	mem 16099MB
[2025-01-18 05:59:52 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][290/312]	eta 0:00:10 lr 0.001590	time 0.5508 (0.4783)	model_time 0.5503 (0.4699)	loss 3.3802 (3.1069)	grad_norm 1.6982 (1.9771/0.9488)	mem 16099MB
[2025-01-18 05:59:57 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][300/312]	eta 0:00:05 lr 0.001589	time 0.4376 (0.4782)	model_time 0.4375 (0.4701)	loss 3.4897 (3.1099)	grad_norm 1.2850 (1.9623/0.9425)	mem 16099MB
[2025-01-18 06:00:02 internimage_t_1k_224] (main.py 510): INFO Train: [170/300][310/312]	eta 0:00:00 lr 0.001588	time 0.4675 (0.4775)	model_time 0.4674 (0.4697)	loss 3.3230 (3.1090)	grad_norm 0.9052 (1.9757/0.9399)	mem 16099MB
[2025-01-18 06:00:02 internimage_t_1k_224] (main.py 519): INFO EPOCH 170 training takes 0:02:28
[2025-01-18 06:00:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_170.pth saving......
[2025-01-18 06:00:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_170.pth saved !!!
[2025-01-18 06:00:11 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.176 (7.176)	Loss 0.8294 (0.8294)	Acc@1 83.105 (83.105)	Acc@5 96.704 (96.704)	Mem 16099MB
[2025-01-18 06:00:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.959)	Loss 1.1246 (0.9551)	Acc@1 75.220 (80.231)	Acc@5 93.481 (95.275)	Mem 16099MB
[2025-01-18 06:00:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:170] * Acc@1 80.126 Acc@5 95.298
[2025-01-18 06:00:14 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.1%
[2025-01-18 06:00:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 06:00:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 06:00:15 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.13%
[2025-01-18 06:00:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.272 (7.272)	Loss 0.8089 (0.8089)	Acc@1 84.277 (84.277)	Acc@5 97.241 (97.241)	Mem 16099MB
[2025-01-18 06:00:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.988)	Loss 1.0950 (0.9359)	Acc@1 76.758 (81.441)	Acc@5 94.385 (95.754)	Mem 16099MB
[2025-01-18 06:00:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:170] * Acc@1 81.326 Acc@5 95.793
[2025-01-18 06:00:26 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.3%
[2025-01-18 06:00:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:00:28 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:00:28 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.33%
[2025-01-18 06:00:30 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][0/312]	eta 0:14:24 lr 0.001588	time 2.7719 (2.7719)	model_time 0.4602 (0.4602)	loss 3.1716 (3.1716)	grad_norm 1.0949 (1.0949/0.0000)	mem 16099MB
[2025-01-18 06:00:35 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][10/312]	eta 0:03:28 lr 0.001587	time 0.4514 (0.6888)	model_time 0.4510 (0.4783)	loss 3.3408 (3.3138)	grad_norm 2.4341 (1.3684/0.3922)	mem 16099MB
[2025-01-18 06:00:40 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][20/312]	eta 0:02:50 lr 0.001587	time 0.4516 (0.5830)	model_time 0.4512 (0.4725)	loss 3.5518 (3.2656)	grad_norm 1.9736 (1.3335/0.3746)	mem 16099MB
[2025-01-18 06:00:45 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][30/312]	eta 0:02:33 lr 0.001586	time 0.4548 (0.5443)	model_time 0.4540 (0.4694)	loss 2.4663 (3.1468)	grad_norm 3.2801 (1.6124/0.6909)	mem 16099MB
[2025-01-18 06:00:49 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][40/312]	eta 0:02:23 lr 0.001585	time 0.4402 (0.5271)	model_time 0.4397 (0.4703)	loss 3.0832 (3.1267)	grad_norm 1.3935 (1.7705/0.7135)	mem 16099MB
[2025-01-18 06:00:54 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][50/312]	eta 0:02:14 lr 0.001585	time 0.4537 (0.5134)	model_time 0.4533 (0.4677)	loss 2.5186 (3.1460)	grad_norm 1.8698 (1.8404/0.7480)	mem 16099MB
[2025-01-18 06:00:58 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][60/312]	eta 0:02:07 lr 0.001584	time 0.4491 (0.5049)	model_time 0.4486 (0.4667)	loss 3.1832 (3.1489)	grad_norm 3.3140 (1.8612/0.7811)	mem 16099MB
[2025-01-18 06:01:03 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][70/312]	eta 0:02:00 lr 0.001584	time 0.4447 (0.4992)	model_time 0.4446 (0.4662)	loss 3.1889 (3.1439)	grad_norm 5.1248 (1.9647/0.9000)	mem 16099MB
[2025-01-18 06:01:08 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][80/312]	eta 0:01:54 lr 0.001583	time 0.4401 (0.4951)	model_time 0.4399 (0.4662)	loss 3.2230 (3.1352)	grad_norm 3.5693 (2.0102/0.8866)	mem 16099MB
[2025-01-18 06:01:13 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][90/312]	eta 0:01:49 lr 0.001582	time 0.5328 (0.4932)	model_time 0.5326 (0.4675)	loss 3.7212 (3.1343)	grad_norm 1.5489 (1.9648/0.8509)	mem 16099MB
[2025-01-18 06:01:17 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][100/312]	eta 0:01:43 lr 0.001582	time 0.4485 (0.4900)	model_time 0.4484 (0.4668)	loss 3.5313 (3.1485)	grad_norm 2.0876 (2.0013/0.8872)	mem 16099MB
[2025-01-18 06:01:22 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][110/312]	eta 0:01:38 lr 0.001581	time 0.4552 (0.4877)	model_time 0.4547 (0.4665)	loss 3.8295 (3.1196)	grad_norm 1.5938 (1.9965/0.8771)	mem 16099MB
[2025-01-18 06:01:27 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][120/312]	eta 0:01:33 lr 0.001580	time 0.5805 (0.4875)	model_time 0.5800 (0.4680)	loss 2.7895 (3.1256)	grad_norm 2.3207 (1.9746/0.8582)	mem 16099MB
[2025-01-18 06:01:31 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][130/312]	eta 0:01:28 lr 0.001580	time 0.4473 (0.4869)	model_time 0.4469 (0.4689)	loss 2.8220 (3.1094)	grad_norm 1.9746 (1.9818/0.8557)	mem 16099MB
[2025-01-18 06:01:36 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][140/312]	eta 0:01:23 lr 0.001579	time 0.4672 (0.4850)	model_time 0.4670 (0.4683)	loss 3.8762 (3.1261)	grad_norm 1.9806 (1.9734/0.8413)	mem 16099MB
[2025-01-18 06:01:41 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][150/312]	eta 0:01:18 lr 0.001578	time 0.4445 (0.4843)	model_time 0.4440 (0.4686)	loss 3.2891 (3.1286)	grad_norm 1.2846 (1.9396/0.8366)	mem 16099MB
[2025-01-18 06:01:46 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][160/312]	eta 0:01:13 lr 0.001578	time 0.4478 (0.4839)	model_time 0.4476 (0.4691)	loss 3.2558 (3.1345)	grad_norm 1.0441 (1.9005/0.8316)	mem 16099MB
[2025-01-18 06:01:50 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][170/312]	eta 0:01:08 lr 0.001577	time 0.4430 (0.4828)	model_time 0.4429 (0.4689)	loss 3.5656 (3.1415)	grad_norm 3.5748 (1.9301/0.8408)	mem 16099MB
[2025-01-18 06:01:55 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][180/312]	eta 0:01:03 lr 0.001576	time 0.4522 (0.4820)	model_time 0.4517 (0.4688)	loss 3.5933 (3.1536)	grad_norm 1.1579 (1.9268/0.8325)	mem 16099MB
[2025-01-18 06:02:00 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][190/312]	eta 0:00:58 lr 0.001576	time 0.4812 (0.4808)	model_time 0.4811 (0.4683)	loss 2.3331 (3.1439)	grad_norm 1.2557 (1.8880/0.8301)	mem 16099MB
[2025-01-18 06:02:04 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][200/312]	eta 0:00:53 lr 0.001575	time 0.4537 (0.4803)	model_time 0.4532 (0.4684)	loss 3.7641 (3.1510)	grad_norm 3.8634 (1.8976/0.8344)	mem 16099MB
[2025-01-18 06:02:09 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][210/312]	eta 0:00:48 lr 0.001574	time 0.5861 (0.4800)	model_time 0.5856 (0.4687)	loss 3.3192 (3.1454)	grad_norm 1.8787 (1.8967/0.8317)	mem 16099MB
[2025-01-18 06:02:14 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][220/312]	eta 0:00:44 lr 0.001574	time 0.4711 (0.4788)	model_time 0.4710 (0.4680)	loss 2.8907 (3.1471)	grad_norm 3.8567 (1.9371/0.8593)	mem 16099MB
[2025-01-18 06:02:18 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][230/312]	eta 0:00:39 lr 0.001573	time 0.4705 (0.4781)	model_time 0.4703 (0.4677)	loss 2.5243 (3.1459)	grad_norm 1.1416 (1.9464/0.8663)	mem 16099MB
[2025-01-18 06:02:23 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][240/312]	eta 0:00:34 lr 0.001573	time 0.4420 (0.4781)	model_time 0.4415 (0.4681)	loss 3.2946 (3.1586)	grad_norm 2.0964 (1.9308/0.8563)	mem 16099MB
[2025-01-18 06:02:28 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][250/312]	eta 0:00:29 lr 0.001572	time 0.4407 (0.4775)	model_time 0.4402 (0.4679)	loss 3.7805 (3.1586)	grad_norm 1.7813 (1.9149/0.8468)	mem 16099MB
[2025-01-18 06:02:32 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][260/312]	eta 0:00:24 lr 0.001571	time 0.4642 (0.4768)	model_time 0.4637 (0.4676)	loss 2.9230 (3.1598)	grad_norm 1.4775 (1.9097/0.8347)	mem 16099MB
[2025-01-18 06:02:37 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][270/312]	eta 0:00:20 lr 0.001571	time 0.4533 (0.4769)	model_time 0.4531 (0.4680)	loss 3.4840 (3.1519)	grad_norm 2.1042 (1.9244/0.8369)	mem 16099MB
[2025-01-18 06:02:41 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][280/312]	eta 0:00:15 lr 0.001570	time 0.4459 (0.4760)	model_time 0.4454 (0.4674)	loss 3.1568 (3.1483)	grad_norm 3.5334 (1.9479/0.8476)	mem 16099MB
[2025-01-18 06:02:46 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][290/312]	eta 0:00:10 lr 0.001569	time 0.4428 (0.4759)	model_time 0.4424 (0.4675)	loss 3.2235 (3.1378)	grad_norm 1.5211 (1.9663/0.8879)	mem 16099MB
[2025-01-18 06:02:51 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][300/312]	eta 0:00:05 lr 0.001569	time 0.4391 (0.4750)	model_time 0.4390 (0.4670)	loss 3.2028 (3.1388)	grad_norm 1.8580 (1.9724/0.8846)	mem 16099MB
[2025-01-18 06:02:55 internimage_t_1k_224] (main.py 510): INFO Train: [171/300][310/312]	eta 0:00:00 lr 0.001568	time 0.4395 (0.4744)	model_time 0.4394 (0.4666)	loss 2.3494 (3.1283)	grad_norm 1.2342 (1.9771/0.8808)	mem 16099MB
[2025-01-18 06:02:56 internimage_t_1k_224] (main.py 519): INFO EPOCH 171 training takes 0:02:27
[2025-01-18 06:02:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_171.pth saving......
[2025-01-18 06:02:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_171.pth saved !!!
[2025-01-18 06:03:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.621 (7.621)	Loss 0.7988 (0.7988)	Acc@1 83.545 (83.545)	Acc@5 96.875 (96.875)	Mem 16099MB
[2025-01-18 06:03:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.017)	Loss 1.1021 (0.9365)	Acc@1 74.976 (79.989)	Acc@5 93.750 (95.255)	Mem 16099MB
[2025-01-18 06:03:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:171] * Acc@1 79.950 Acc@5 95.302
[2025-01-18 06:03:08 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.0%
[2025-01-18 06:03:08 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.13%
[2025-01-18 06:03:16 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.165 (8.165)	Loss 0.8079 (0.8079)	Acc@1 84.277 (84.277)	Acc@5 97.241 (97.241)	Mem 16099MB
[2025-01-18 06:03:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.093)	Loss 1.0933 (0.9348)	Acc@1 76.758 (81.452)	Acc@5 94.385 (95.781)	Mem 16099MB
[2025-01-18 06:03:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:171] * Acc@1 81.332 Acc@5 95.813
[2025-01-18 06:03:20 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.3%
[2025-01-18 06:03:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:03:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:03:22 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.33%
[2025-01-18 06:03:24 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][0/312]	eta 0:12:05 lr 0.001568	time 2.3256 (2.3256)	model_time 0.4724 (0.4724)	loss 3.5630 (3.5630)	grad_norm 1.6593 (1.6593/0.0000)	mem 16099MB
[2025-01-18 06:03:29 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][10/312]	eta 0:03:12 lr 0.001567	time 0.4485 (0.6375)	model_time 0.4481 (0.4687)	loss 3.3651 (3.0234)	grad_norm 2.1402 (2.0534/0.7887)	mem 16099MB
[2025-01-18 06:03:34 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][20/312]	eta 0:02:43 lr 0.001567	time 0.4735 (0.5609)	model_time 0.4730 (0.4723)	loss 3.4680 (3.0849)	grad_norm 2.4475 (2.0979/0.8742)	mem 16099MB
[2025-01-18 06:03:38 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][30/312]	eta 0:02:30 lr 0.001566	time 0.4416 (0.5326)	model_time 0.4414 (0.4725)	loss 2.4754 (3.0742)	grad_norm 3.1433 (2.4379/1.2474)	mem 16099MB
[2025-01-18 06:03:43 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][40/312]	eta 0:02:20 lr 0.001565	time 0.4801 (0.5158)	model_time 0.4799 (0.4703)	loss 3.6571 (3.1381)	grad_norm 2.5161 (2.4171/1.2729)	mem 16099MB
[2025-01-18 06:03:48 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][50/312]	eta 0:02:12 lr 0.001565	time 0.4707 (0.5070)	model_time 0.4705 (0.4704)	loss 2.8998 (3.1296)	grad_norm 1.3926 (2.2498/1.2131)	mem 16099MB
[2025-01-18 06:03:52 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][60/312]	eta 0:02:06 lr 0.001564	time 0.4755 (0.5013)	model_time 0.4753 (0.4706)	loss 3.3746 (3.1323)	grad_norm 1.0567 (2.1081/1.1606)	mem 16099MB
[2025-01-18 06:03:57 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][70/312]	eta 0:01:59 lr 0.001563	time 0.4542 (0.4954)	model_time 0.4537 (0.4690)	loss 2.8615 (3.1105)	grad_norm 4.3896 (2.2072/1.2472)	mem 16099MB
[2025-01-18 06:04:02 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][80/312]	eta 0:01:54 lr 0.001563	time 0.5690 (0.4937)	model_time 0.5688 (0.4704)	loss 2.7731 (3.1252)	grad_norm 2.6052 (2.1858/1.1920)	mem 16099MB
[2025-01-18 06:04:07 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][90/312]	eta 0:01:49 lr 0.001562	time 0.5461 (0.4933)	model_time 0.5456 (0.4726)	loss 3.6596 (3.1272)	grad_norm 1.6748 (2.1365/1.1471)	mem 16099MB
[2025-01-18 06:04:11 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][100/312]	eta 0:01:43 lr 0.001561	time 0.4517 (0.4898)	model_time 0.4515 (0.4711)	loss 1.9808 (3.1257)	grad_norm 2.0346 (2.1026/1.1141)	mem 16099MB
[2025-01-18 06:04:16 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][110/312]	eta 0:01:38 lr 0.001561	time 0.4566 (0.4872)	model_time 0.4562 (0.4702)	loss 2.8610 (3.1165)	grad_norm 1.3895 (2.0445/1.1005)	mem 16099MB
[2025-01-18 06:04:20 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][120/312]	eta 0:01:33 lr 0.001560	time 0.4544 (0.4845)	model_time 0.4542 (0.4688)	loss 3.1511 (3.1280)	grad_norm 2.6093 (2.0723/1.0913)	mem 16099MB
[2025-01-18 06:04:25 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][130/312]	eta 0:01:27 lr 0.001559	time 0.4587 (0.4832)	model_time 0.4585 (0.4687)	loss 3.1526 (3.1162)	grad_norm 1.1605 (2.0551/1.0622)	mem 16099MB
[2025-01-18 06:04:30 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][140/312]	eta 0:01:22 lr 0.001559	time 0.4490 (0.4817)	model_time 0.4447 (0.4682)	loss 4.0984 (3.1299)	grad_norm 2.2660 (2.0400/1.0374)	mem 16099MB
[2025-01-18 06:04:34 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][150/312]	eta 0:01:17 lr 0.001558	time 0.4422 (0.4810)	model_time 0.4418 (0.4684)	loss 3.7760 (3.1299)	grad_norm 2.3279 (2.0455/1.0167)	mem 16099MB
[2025-01-18 06:04:39 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][160/312]	eta 0:01:13 lr 0.001558	time 0.5088 (0.4803)	model_time 0.5083 (0.4684)	loss 2.1479 (3.1404)	grad_norm 1.3936 (2.0296/0.9954)	mem 16099MB
[2025-01-18 06:04:44 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][170/312]	eta 0:01:08 lr 0.001557	time 0.4488 (0.4791)	model_time 0.4484 (0.4679)	loss 3.0311 (3.1479)	grad_norm 3.3149 (2.0641/1.0002)	mem 16099MB
[2025-01-18 06:04:48 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][180/312]	eta 0:01:03 lr 0.001556	time 0.4471 (0.4787)	model_time 0.4469 (0.4681)	loss 3.8656 (3.1604)	grad_norm 1.4486 (2.0373/0.9809)	mem 16099MB
[2025-01-18 06:04:53 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][190/312]	eta 0:00:58 lr 0.001556	time 0.4578 (0.4779)	model_time 0.4576 (0.4678)	loss 3.8316 (3.1641)	grad_norm 1.7965 (2.0255/0.9761)	mem 16099MB
[2025-01-18 06:04:58 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][200/312]	eta 0:00:53 lr 0.001555	time 0.4613 (0.4771)	model_time 0.4609 (0.4675)	loss 2.8891 (3.1575)	grad_norm 1.4271 (2.0068/0.9572)	mem 16099MB
[2025-01-18 06:05:02 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][210/312]	eta 0:00:48 lr 0.001554	time 0.4582 (0.4761)	model_time 0.4578 (0.4669)	loss 3.6219 (3.1613)	grad_norm 1.1127 (1.9732/0.9474)	mem 16099MB
[2025-01-18 06:05:07 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][220/312]	eta 0:00:43 lr 0.001554	time 0.4527 (0.4751)	model_time 0.4522 (0.4663)	loss 2.9759 (3.1677)	grad_norm 1.4712 (1.9678/0.9392)	mem 16099MB
[2025-01-18 06:05:11 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][230/312]	eta 0:00:38 lr 0.001553	time 0.4846 (0.4744)	model_time 0.4841 (0.4660)	loss 3.3759 (3.1699)	grad_norm 2.0686 (1.9639/0.9442)	mem 16099MB
[2025-01-18 06:05:16 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][240/312]	eta 0:00:34 lr 0.001552	time 0.4539 (0.4735)	model_time 0.4535 (0.4654)	loss 3.2856 (3.1699)	grad_norm 1.4687 (1.9481/0.9329)	mem 16099MB
[2025-01-18 06:05:21 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][250/312]	eta 0:00:29 lr 0.001552	time 0.5395 (0.4751)	model_time 0.5393 (0.4673)	loss 2.1045 (3.1606)	grad_norm 1.1133 (1.9401/0.9189)	mem 16099MB
[2025-01-18 06:05:26 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][260/312]	eta 0:00:24 lr 0.001551	time 0.4522 (0.4752)	model_time 0.4517 (0.4676)	loss 3.4082 (3.1562)	grad_norm 1.1646 (1.9166/0.9107)	mem 16099MB
[2025-01-18 06:05:31 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][270/312]	eta 0:00:19 lr 0.001550	time 0.4430 (0.4754)	model_time 0.4425 (0.4682)	loss 3.5000 (3.1557)	grad_norm 4.1434 (1.9297/0.9158)	mem 16099MB
[2025-01-18 06:05:35 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][280/312]	eta 0:00:15 lr 0.001550	time 0.4541 (0.4752)	model_time 0.4539 (0.4682)	loss 2.7310 (3.1609)	grad_norm 1.9378 (1.9320/0.9128)	mem 16099MB
[2025-01-18 06:05:40 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][290/312]	eta 0:00:10 lr 0.001549	time 0.4451 (0.4750)	model_time 0.4449 (0.4682)	loss 2.9542 (3.1626)	grad_norm 2.1138 (1.9547/0.9380)	mem 16099MB
[2025-01-18 06:05:45 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][300/312]	eta 0:00:05 lr 0.001548	time 0.4386 (0.4743)	model_time 0.4385 (0.4677)	loss 3.7997 (3.1626)	grad_norm 0.9950 (1.9563/0.9387)	mem 16099MB
[2025-01-18 06:05:49 internimage_t_1k_224] (main.py 510): INFO Train: [172/300][310/312]	eta 0:00:00 lr 0.001548	time 0.4419 (0.4732)	model_time 0.4418 (0.4669)	loss 3.8980 (3.1576)	grad_norm 1.5001 (1.9630/0.9801)	mem 16099MB
[2025-01-18 06:05:49 internimage_t_1k_224] (main.py 519): INFO EPOCH 172 training takes 0:02:27
[2025-01-18 06:05:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_172.pth saving......
[2025-01-18 06:05:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_172.pth saved !!!
[2025-01-18 06:05:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.162 (7.162)	Loss 0.8094 (0.8094)	Acc@1 83.618 (83.618)	Acc@5 96.777 (96.777)	Mem 16099MB
[2025-01-18 06:06:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.990)	Loss 1.1525 (0.9480)	Acc@1 75.000 (80.225)	Acc@5 93.237 (95.270)	Mem 16099MB
[2025-01-18 06:06:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:172] * Acc@1 80.158 Acc@5 95.317
[2025-01-18 06:06:02 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.2%
[2025-01-18 06:06:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 06:06:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 06:06:03 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.16%
[2025-01-18 06:06:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.221 (7.221)	Loss 0.8071 (0.8071)	Acc@1 84.326 (84.326)	Acc@5 97.266 (97.266)	Mem 16099MB
[2025-01-18 06:06:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.992)	Loss 1.0918 (0.9338)	Acc@1 76.782 (81.461)	Acc@5 94.409 (95.807)	Mem 16099MB
[2025-01-18 06:06:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:172] * Acc@1 81.346 Acc@5 95.841
[2025-01-18 06:06:14 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.3%
[2025-01-18 06:06:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:06:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:06:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.35%
[2025-01-18 06:06:18 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][0/312]	eta 0:13:56 lr 0.001548	time 2.6799 (2.6799)	model_time 0.4683 (0.4683)	loss 3.8141 (3.8141)	grad_norm 1.2154 (1.2154/0.0000)	mem 16099MB
[2025-01-18 06:06:23 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][10/312]	eta 0:03:18 lr 0.001547	time 0.4509 (0.6581)	model_time 0.4508 (0.4568)	loss 3.3549 (2.9920)	grad_norm 1.4052 (1.9827/0.8139)	mem 16099MB
[2025-01-18 06:06:27 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][20/312]	eta 0:02:45 lr 0.001546	time 0.4617 (0.5657)	model_time 0.4612 (0.4601)	loss 2.1176 (2.9815)	grad_norm 1.2078 (1.8718/0.7470)	mem 16099MB
[2025-01-18 06:06:32 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][30/312]	eta 0:02:31 lr 0.001546	time 0.4493 (0.5373)	model_time 0.4492 (0.4657)	loss 3.0456 (2.9680)	grad_norm 1.1425 (1.8082/0.6704)	mem 16099MB
[2025-01-18 06:06:37 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][40/312]	eta 0:02:21 lr 0.001545	time 0.4533 (0.5193)	model_time 0.4529 (0.4650)	loss 3.5721 (2.9899)	grad_norm 1.8575 (1.7188/0.6372)	mem 16099MB
[2025-01-18 06:06:41 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][50/312]	eta 0:02:13 lr 0.001544	time 0.4590 (0.5083)	model_time 0.4589 (0.4646)	loss 4.2630 (3.0423)	grad_norm 1.3077 (1.6802/0.6135)	mem 16099MB
[2025-01-18 06:06:46 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][60/312]	eta 0:02:06 lr 0.001544	time 0.4556 (0.5006)	model_time 0.4554 (0.4641)	loss 2.5080 (3.0864)	grad_norm 3.4556 (1.8336/0.8075)	mem 16099MB
[2025-01-18 06:06:50 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][70/312]	eta 0:01:59 lr 0.001543	time 0.4485 (0.4942)	model_time 0.4484 (0.4628)	loss 3.3790 (3.0695)	grad_norm 2.8134 (2.0214/1.0707)	mem 16099MB
[2025-01-18 06:06:55 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][80/312]	eta 0:01:53 lr 0.001543	time 0.4522 (0.4911)	model_time 0.4516 (0.4635)	loss 4.0712 (3.1004)	grad_norm 2.0357 (2.0016/1.0203)	mem 16099MB
[2025-01-18 06:07:00 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][90/312]	eta 0:01:48 lr 0.001542	time 0.4558 (0.4870)	model_time 0.4554 (0.4623)	loss 3.1390 (3.1218)	grad_norm 1.6303 (1.9449/0.9804)	mem 16099MB
[2025-01-18 06:07:04 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][100/312]	eta 0:01:42 lr 0.001541	time 0.4445 (0.4842)	model_time 0.4444 (0.4619)	loss 3.4414 (3.1249)	grad_norm 1.1400 (1.9259/0.9469)	mem 16099MB
[2025-01-18 06:07:09 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][110/312]	eta 0:01:37 lr 0.001541	time 0.4475 (0.4828)	model_time 0.4470 (0.4626)	loss 3.4403 (3.1386)	grad_norm 2.9169 (1.9369/0.9347)	mem 16099MB
[2025-01-18 06:07:14 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][120/312]	eta 0:01:32 lr 0.001540	time 0.4743 (0.4821)	model_time 0.4739 (0.4635)	loss 2.3744 (3.1319)	grad_norm 1.4382 (1.9204/0.9052)	mem 16099MB
[2025-01-18 06:07:18 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][130/312]	eta 0:01:27 lr 0.001539	time 0.6163 (0.4821)	model_time 0.6161 (0.4649)	loss 3.0210 (3.1100)	grad_norm 1.3578 (2.0098/1.0320)	mem 16099MB
[2025-01-18 06:07:23 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][140/312]	eta 0:01:22 lr 0.001539	time 0.5414 (0.4813)	model_time 0.5413 (0.4652)	loss 3.6714 (3.1264)	grad_norm 1.6973 (1.9745/1.0077)	mem 16099MB
[2025-01-18 06:07:28 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][150/312]	eta 0:01:17 lr 0.001538	time 0.4751 (0.4799)	model_time 0.4749 (0.4649)	loss 2.6318 (3.0990)	grad_norm 3.1864 (2.0200/1.0416)	mem 16099MB
[2025-01-18 06:07:33 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][160/312]	eta 0:01:12 lr 0.001537	time 0.4413 (0.4795)	model_time 0.4411 (0.4654)	loss 3.3087 (3.0917)	grad_norm 1.0122 (2.0163/1.0255)	mem 16099MB
[2025-01-18 06:07:37 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][170/312]	eta 0:01:07 lr 0.001537	time 0.4492 (0.4788)	model_time 0.4490 (0.4655)	loss 3.2057 (3.0876)	grad_norm 1.0444 (1.9971/1.0048)	mem 16099MB
[2025-01-18 06:07:42 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][180/312]	eta 0:01:03 lr 0.001536	time 0.4602 (0.4776)	model_time 0.4597 (0.4650)	loss 3.5385 (3.0925)	grad_norm 1.5038 (1.9644/0.9885)	mem 16099MB
[2025-01-18 06:07:46 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][190/312]	eta 0:00:58 lr 0.001535	time 0.4441 (0.4775)	model_time 0.4437 (0.4655)	loss 2.3127 (3.0825)	grad_norm 2.8686 (2.0190/1.0499)	mem 16099MB
[2025-01-18 06:07:51 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][200/312]	eta 0:00:53 lr 0.001535	time 0.4475 (0.4772)	model_time 0.4472 (0.4658)	loss 3.7162 (3.0919)	grad_norm 1.9694 (2.0203/1.0341)	mem 16099MB
[2025-01-18 06:07:56 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][210/312]	eta 0:00:48 lr 0.001534	time 0.4598 (0.4765)	model_time 0.4593 (0.4656)	loss 3.9490 (3.0958)	grad_norm 1.9302 (2.0212/1.0157)	mem 16099MB
[2025-01-18 06:08:00 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][220/312]	eta 0:00:43 lr 0.001534	time 0.4471 (0.4759)	model_time 0.4469 (0.4655)	loss 3.6783 (3.1001)	grad_norm 1.3560 (2.0175/1.0048)	mem 16099MB
[2025-01-18 06:08:05 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][230/312]	eta 0:00:39 lr 0.001533	time 0.4584 (0.4759)	model_time 0.4580 (0.4659)	loss 3.9148 (3.1073)	grad_norm 1.7830 (2.0059/0.9911)	mem 16099MB
[2025-01-18 06:08:10 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][240/312]	eta 0:00:34 lr 0.001532	time 0.4523 (0.4753)	model_time 0.4519 (0.4657)	loss 3.7540 (3.1068)	grad_norm 1.4508 (2.0063/0.9873)	mem 16099MB
[2025-01-18 06:08:14 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][250/312]	eta 0:00:29 lr 0.001532	time 0.4412 (0.4748)	model_time 0.4408 (0.4656)	loss 3.3166 (3.1083)	grad_norm 1.2804 (1.9989/0.9940)	mem 16099MB
[2025-01-18 06:08:19 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][260/312]	eta 0:00:24 lr 0.001531	time 0.4449 (0.4745)	model_time 0.4447 (0.4657)	loss 3.6813 (3.1145)	grad_norm 5.0571 (2.0363/1.0237)	mem 16099MB
[2025-01-18 06:08:24 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][270/312]	eta 0:00:19 lr 0.001530	time 0.4510 (0.4739)	model_time 0.4506 (0.4654)	loss 2.8657 (3.1156)	grad_norm 2.0775 (2.0298/1.0125)	mem 16099MB
[2025-01-18 06:08:28 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][280/312]	eta 0:00:15 lr 0.001530	time 0.4569 (0.4739)	model_time 0.4567 (0.4657)	loss 3.4860 (3.1204)	grad_norm 1.5393 (2.0157/0.9997)	mem 16099MB
[2025-01-18 06:08:33 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][290/312]	eta 0:00:10 lr 0.001529	time 0.4664 (0.4736)	model_time 0.4660 (0.4656)	loss 3.9357 (3.1311)	grad_norm 1.9527 (2.0175/0.9908)	mem 16099MB
[2025-01-18 06:08:38 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][300/312]	eta 0:00:05 lr 0.001528	time 0.5273 (0.4736)	model_time 0.5272 (0.4659)	loss 2.9187 (3.1308)	grad_norm 2.1086 (2.0016/0.9836)	mem 16099MB
[2025-01-18 06:08:42 internimage_t_1k_224] (main.py 510): INFO Train: [173/300][310/312]	eta 0:00:00 lr 0.001528	time 0.4392 (0.4730)	model_time 0.4391 (0.4655)	loss 2.2913 (3.1295)	grad_norm 2.8258 (1.9904/0.9779)	mem 16099MB
[2025-01-18 06:08:43 internimage_t_1k_224] (main.py 519): INFO EPOCH 173 training takes 0:02:27
[2025-01-18 06:08:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_173.pth saving......
[2025-01-18 06:08:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_173.pth saved !!!
[2025-01-18 06:08:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.506 (7.506)	Loss 0.7576 (0.7576)	Acc@1 83.618 (83.618)	Acc@5 96.777 (96.777)	Mem 16099MB
[2025-01-18 06:08:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.008)	Loss 1.0687 (0.9006)	Acc@1 74.976 (80.415)	Acc@5 93.750 (95.372)	Mem 16099MB
[2025-01-18 06:08:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:173] * Acc@1 80.310 Acc@5 95.363
[2025-01-18 06:08:55 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.3%
[2025-01-18 06:08:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 06:08:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 06:08:56 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.31%
[2025-01-18 06:09:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.562 (7.562)	Loss 0.8060 (0.8060)	Acc@1 84.448 (84.448)	Acc@5 97.314 (97.314)	Mem 16099MB
[2025-01-18 06:09:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.006)	Loss 1.0902 (0.9327)	Acc@1 76.758 (81.532)	Acc@5 94.434 (95.821)	Mem 16099MB
[2025-01-18 06:09:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:173] * Acc@1 81.414 Acc@5 95.855
[2025-01-18 06:09:08 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.4%
[2025-01-18 06:09:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:09:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:09:09 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.41%
[2025-01-18 06:09:12 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][0/312]	eta 0:13:26 lr 0.001528	time 2.5864 (2.5864)	model_time 0.4684 (0.4684)	loss 2.8864 (2.8864)	grad_norm 1.0455 (1.0455/0.0000)	mem 16099MB
[2025-01-18 06:09:16 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][10/312]	eta 0:03:21 lr 0.001527	time 0.4392 (0.6683)	model_time 0.4391 (0.4753)	loss 3.2845 (3.1779)	grad_norm 1.9479 (2.1179/1.0384)	mem 16099MB
[2025-01-18 06:09:21 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][20/312]	eta 0:02:46 lr 0.001526	time 0.4575 (0.5700)	model_time 0.4573 (0.4688)	loss 2.1053 (3.1432)	grad_norm 0.9181 (1.9147/0.8733)	mem 16099MB
[2025-01-18 06:09:26 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][30/312]	eta 0:02:30 lr 0.001526	time 0.4441 (0.5330)	model_time 0.4437 (0.4643)	loss 2.5061 (3.1295)	grad_norm 1.7314 (1.9827/0.7731)	mem 16099MB
[2025-01-18 06:09:30 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][40/312]	eta 0:02:20 lr 0.001525	time 0.4874 (0.5155)	model_time 0.4872 (0.4634)	loss 2.8245 (3.1361)	grad_norm 1.0318 (1.9240/0.7970)	mem 16099MB
[2025-01-18 06:09:35 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][50/312]	eta 0:02:12 lr 0.001524	time 0.4480 (0.5056)	model_time 0.4478 (0.4637)	loss 3.3728 (3.1183)	grad_norm 1.8802 (1.9090/0.8049)	mem 16099MB
[2025-01-18 06:09:39 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][60/312]	eta 0:02:05 lr 0.001524	time 0.4421 (0.4976)	model_time 0.4420 (0.4625)	loss 3.1027 (3.0745)	grad_norm 2.7393 (1.9198/0.7730)	mem 16099MB
[2025-01-18 06:09:44 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][70/312]	eta 0:01:59 lr 0.001523	time 0.5596 (0.4937)	model_time 0.5591 (0.4635)	loss 3.2164 (3.0275)	grad_norm 1.5492 (1.9292/0.7409)	mem 16099MB
[2025-01-18 06:09:49 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][80/312]	eta 0:01:53 lr 0.001522	time 0.4649 (0.4900)	model_time 0.4648 (0.4635)	loss 2.2134 (3.0131)	grad_norm 2.5872 (2.0066/0.8111)	mem 16099MB
[2025-01-18 06:09:53 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][90/312]	eta 0:01:48 lr 0.001522	time 0.4610 (0.4868)	model_time 0.4606 (0.4631)	loss 3.2922 (3.0304)	grad_norm 2.3314 (2.1008/0.9479)	mem 16099MB
[2025-01-18 06:09:58 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][100/312]	eta 0:01:42 lr 0.001521	time 0.4478 (0.4855)	model_time 0.4476 (0.4642)	loss 3.7058 (3.0744)	grad_norm 1.4158 (2.0934/0.9705)	mem 16099MB
[2025-01-18 06:10:03 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][110/312]	eta 0:01:37 lr 0.001521	time 0.4624 (0.4838)	model_time 0.4620 (0.4643)	loss 3.6369 (3.0889)	grad_norm 1.0425 (2.0270/0.9594)	mem 16099MB
[2025-01-18 06:10:08 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][120/312]	eta 0:01:32 lr 0.001520	time 0.5632 (0.4827)	model_time 0.5628 (0.4649)	loss 1.9676 (3.0514)	grad_norm 1.3452 (1.9785/0.9384)	mem 16099MB
[2025-01-18 06:10:12 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][130/312]	eta 0:01:27 lr 0.001519	time 0.5309 (0.4824)	model_time 0.5307 (0.4658)	loss 3.1336 (3.0521)	grad_norm 2.2791 (1.9582/0.9145)	mem 16099MB
[2025-01-18 06:10:17 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][140/312]	eta 0:01:22 lr 0.001519	time 0.4587 (0.4824)	model_time 0.4585 (0.4670)	loss 3.5077 (3.0545)	grad_norm 1.1646 (1.9171/0.8985)	mem 16099MB
[2025-01-18 06:10:22 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][150/312]	eta 0:01:17 lr 0.001518	time 0.4454 (0.4810)	model_time 0.4449 (0.4666)	loss 2.7019 (3.0680)	grad_norm 1.8576 (1.8957/0.8750)	mem 16099MB
[2025-01-18 06:10:27 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][160/312]	eta 0:01:13 lr 0.001517	time 0.4512 (0.4810)	model_time 0.4508 (0.4675)	loss 2.4473 (3.0497)	grad_norm 1.8522 (1.9328/0.9016)	mem 16099MB
[2025-01-18 06:10:31 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][170/312]	eta 0:01:08 lr 0.001517	time 0.5786 (0.4802)	model_time 0.5782 (0.4674)	loss 2.2623 (3.0509)	grad_norm 1.7229 (1.9511/0.8921)	mem 16099MB
[2025-01-18 06:10:36 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][180/312]	eta 0:01:03 lr 0.001516	time 0.4940 (0.4788)	model_time 0.4935 (0.4667)	loss 2.8512 (3.0533)	grad_norm 2.3602 (1.9588/0.8712)	mem 16099MB
[2025-01-18 06:10:40 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][190/312]	eta 0:00:58 lr 0.001515	time 0.4469 (0.4785)	model_time 0.4464 (0.4670)	loss 3.4436 (3.0732)	grad_norm 2.9803 (1.9701/0.8623)	mem 16099MB
[2025-01-18 06:10:45 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][200/312]	eta 0:00:53 lr 0.001515	time 0.5186 (0.4779)	model_time 0.5182 (0.4669)	loss 3.4306 (3.0702)	grad_norm 2.0895 (1.9644/0.8506)	mem 16099MB
[2025-01-18 06:10:50 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][210/312]	eta 0:00:48 lr 0.001514	time 0.4433 (0.4769)	model_time 0.4432 (0.4665)	loss 2.8454 (3.0770)	grad_norm 3.6001 (1.9836/0.8496)	mem 16099MB
[2025-01-18 06:10:54 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][220/312]	eta 0:00:43 lr 0.001513	time 0.4486 (0.4760)	model_time 0.4482 (0.4660)	loss 3.4942 (3.0863)	grad_norm 1.2183 (1.9722/0.8377)	mem 16099MB
[2025-01-18 06:10:59 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][230/312]	eta 0:00:38 lr 0.001513	time 0.5166 (0.4755)	model_time 0.5161 (0.4659)	loss 1.8974 (3.0896)	grad_norm 1.2474 (1.9944/0.8598)	mem 16099MB
[2025-01-18 06:11:04 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][240/312]	eta 0:00:34 lr 0.001512	time 0.4750 (0.4750)	model_time 0.4746 (0.4658)	loss 2.6374 (3.0907)	grad_norm 1.8707 (1.9897/0.8621)	mem 16099MB
[2025-01-18 06:11:08 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][250/312]	eta 0:00:29 lr 0.001512	time 0.4436 (0.4748)	model_time 0.4431 (0.4659)	loss 3.0160 (3.0852)	grad_norm 1.1298 (1.9907/0.8655)	mem 16099MB
[2025-01-18 06:11:13 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][260/312]	eta 0:00:24 lr 0.001511	time 0.4546 (0.4744)	model_time 0.4541 (0.4658)	loss 3.5612 (3.0863)	grad_norm 3.0679 (2.0040/0.8786)	mem 16099MB
[2025-01-18 06:11:18 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][270/312]	eta 0:00:19 lr 0.001510	time 0.4500 (0.4740)	model_time 0.4496 (0.4657)	loss 3.6263 (3.0921)	grad_norm 1.6380 (2.0174/0.8852)	mem 16099MB
[2025-01-18 06:11:22 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][280/312]	eta 0:00:15 lr 0.001510	time 0.4432 (0.4737)	model_time 0.4428 (0.4658)	loss 2.7313 (3.1002)	grad_norm 1.7229 (2.0373/0.8919)	mem 16099MB
[2025-01-18 06:11:27 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][290/312]	eta 0:00:10 lr 0.001509	time 0.4612 (0.4733)	model_time 0.4607 (0.4656)	loss 2.0761 (3.1047)	grad_norm 0.9953 (2.0524/0.8926)	mem 16099MB
[2025-01-18 06:11:31 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][300/312]	eta 0:00:05 lr 0.001508	time 0.4382 (0.4726)	model_time 0.4381 (0.4651)	loss 2.8025 (3.1076)	grad_norm 1.3451 (2.0739/0.9375)	mem 16099MB
[2025-01-18 06:11:36 internimage_t_1k_224] (main.py 510): INFO Train: [174/300][310/312]	eta 0:00:00 lr 0.001508	time 0.5411 (0.4720)	model_time 0.5410 (0.4648)	loss 3.1039 (3.1162)	grad_norm 1.5850 (2.0737/0.9441)	mem 16099MB
[2025-01-18 06:11:36 internimage_t_1k_224] (main.py 519): INFO EPOCH 174 training takes 0:02:27
[2025-01-18 06:11:36 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_174.pth saving......
[2025-01-18 06:11:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_174.pth saved !!!
[2025-01-18 06:11:45 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.342 (7.342)	Loss 0.8090 (0.8090)	Acc@1 83.838 (83.838)	Acc@5 96.558 (96.558)	Mem 16099MB
[2025-01-18 06:11:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.998)	Loss 1.1379 (0.9461)	Acc@1 75.000 (80.231)	Acc@5 93.628 (95.288)	Mem 16099MB
[2025-01-18 06:11:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:174] * Acc@1 80.138 Acc@5 95.317
[2025-01-18 06:11:49 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.1%
[2025-01-18 06:11:49 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.31%
[2025-01-18 06:11:57 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.247 (8.247)	Loss 0.8050 (0.8050)	Acc@1 84.375 (84.375)	Acc@5 97.241 (97.241)	Mem 16099MB
[2025-01-18 06:12:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.113)	Loss 1.0883 (0.9314)	Acc@1 76.758 (81.552)	Acc@5 94.409 (95.825)	Mem 16099MB
[2025-01-18 06:12:01 internimage_t_1k_224] (main.py 575): INFO [Epoch:174] * Acc@1 81.438 Acc@5 95.861
[2025-01-18 06:12:01 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.4%
[2025-01-18 06:12:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:12:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:12:03 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.44%
[2025-01-18 06:12:05 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][0/312]	eta 0:13:44 lr 0.001508	time 2.6438 (2.6438)	model_time 0.4616 (0.4616)	loss 3.5988 (3.5988)	grad_norm 2.2027 (2.2027/0.0000)	mem 16099MB
[2025-01-18 06:12:10 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][10/312]	eta 0:03:19 lr 0.001507	time 0.4571 (0.6616)	model_time 0.4569 (0.4629)	loss 2.4638 (2.9266)	grad_norm 1.6673 (2.0416/0.6003)	mem 16099MB
[2025-01-18 06:12:14 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][20/312]	eta 0:02:45 lr 0.001506	time 0.4524 (0.5663)	model_time 0.4522 (0.4621)	loss 3.0720 (3.0700)	grad_norm 1.5613 (1.8590/0.5243)	mem 16099MB
[2025-01-18 06:12:19 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][30/312]	eta 0:02:30 lr 0.001506	time 0.4472 (0.5349)	model_time 0.4469 (0.4643)	loss 4.0028 (3.1692)	grad_norm 1.5578 (1.6619/0.5387)	mem 16099MB
[2025-01-18 06:12:24 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][40/312]	eta 0:02:22 lr 0.001505	time 0.4536 (0.5229)	model_time 0.4534 (0.4694)	loss 3.0741 (3.1488)	grad_norm 1.3495 (1.6981/0.6183)	mem 16099MB
[2025-01-18 06:12:29 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][50/312]	eta 0:02:16 lr 0.001504	time 0.4502 (0.5218)	model_time 0.4500 (0.4787)	loss 3.8394 (3.1105)	grad_norm 2.3602 (1.7722/0.6424)	mem 16099MB
[2025-01-18 06:12:34 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][60/312]	eta 0:02:08 lr 0.001504	time 0.4513 (0.5116)	model_time 0.4508 (0.4756)	loss 3.0106 (3.1083)	grad_norm 3.1551 (1.8735/0.7738)	mem 16099MB
[2025-01-18 06:12:38 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][70/312]	eta 0:02:01 lr 0.001503	time 0.4595 (0.5040)	model_time 0.4591 (0.4729)	loss 3.1638 (3.0901)	grad_norm 1.4579 (1.9650/0.8909)	mem 16099MB
[2025-01-18 06:12:43 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][80/312]	eta 0:01:56 lr 0.001502	time 0.4521 (0.5007)	model_time 0.4519 (0.4735)	loss 2.7690 (3.1199)	grad_norm 1.0632 (1.8787/0.8686)	mem 16099MB
[2025-01-18 06:12:48 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][90/312]	eta 0:01:50 lr 0.001502	time 0.4462 (0.4961)	model_time 0.4458 (0.4718)	loss 2.6868 (3.1159)	grad_norm 2.0028 (1.9091/0.9121)	mem 16099MB
[2025-01-18 06:12:52 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][100/312]	eta 0:01:44 lr 0.001501	time 0.4766 (0.4921)	model_time 0.4764 (0.4701)	loss 4.0007 (3.0889)	grad_norm 1.3927 (1.9286/0.9220)	mem 16099MB
[2025-01-18 06:12:57 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][110/312]	eta 0:01:39 lr 0.001500	time 0.5486 (0.4904)	model_time 0.5482 (0.4704)	loss 3.1427 (3.0641)	grad_norm 1.1327 (1.9512/0.9553)	mem 16099MB
[2025-01-18 06:13:02 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][120/312]	eta 0:01:33 lr 0.001500	time 0.5281 (0.4888)	model_time 0.5277 (0.4704)	loss 2.5313 (3.0679)	grad_norm 1.1023 (1.9144/0.9293)	mem 16099MB
[2025-01-18 06:13:07 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][130/312]	eta 0:01:28 lr 0.001499	time 0.4609 (0.4882)	model_time 0.4603 (0.4712)	loss 3.5526 (3.0569)	grad_norm 2.6381 (1.9703/0.9937)	mem 16099MB
[2025-01-18 06:13:11 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][140/312]	eta 0:01:23 lr 0.001499	time 0.4456 (0.4870)	model_time 0.4452 (0.4712)	loss 2.4230 (3.0490)	grad_norm 3.0477 (1.9427/0.9829)	mem 16099MB
[2025-01-18 06:13:16 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][150/312]	eta 0:01:18 lr 0.001498	time 0.4463 (0.4849)	model_time 0.4461 (0.4701)	loss 3.6379 (3.0528)	grad_norm 4.4767 (1.9879/1.0170)	mem 16099MB
[2025-01-18 06:13:20 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][160/312]	eta 0:01:13 lr 0.001497	time 0.4603 (0.4831)	model_time 0.4599 (0.4692)	loss 3.3564 (3.0532)	grad_norm 1.9525 (1.9879/0.9994)	mem 16099MB
[2025-01-18 06:13:25 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][170/312]	eta 0:01:08 lr 0.001497	time 0.4595 (0.4825)	model_time 0.4593 (0.4693)	loss 2.7891 (3.0420)	grad_norm 1.0707 (1.9560/0.9807)	mem 16099MB
[2025-01-18 06:13:30 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][180/312]	eta 0:01:03 lr 0.001496	time 0.4798 (0.4813)	model_time 0.4797 (0.4688)	loss 3.5837 (3.0529)	grad_norm 1.8462 (1.9402/0.9615)	mem 16099MB
[2025-01-18 06:13:34 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][190/312]	eta 0:00:58 lr 0.001495	time 0.4408 (0.4807)	model_time 0.4404 (0.4689)	loss 3.2575 (3.0569)	grad_norm 2.2918 (1.9563/0.9575)	mem 16099MB
[2025-01-18 06:13:39 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][200/312]	eta 0:00:53 lr 0.001495	time 0.4730 (0.4805)	model_time 0.4728 (0.4692)	loss 3.0142 (3.0602)	grad_norm 2.5778 (1.9650/0.9394)	mem 16099MB
[2025-01-18 06:13:44 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][210/312]	eta 0:00:48 lr 0.001494	time 0.4419 (0.4799)	model_time 0.4417 (0.4692)	loss 2.9787 (3.0601)	grad_norm 2.8257 (1.9865/0.9484)	mem 16099MB
[2025-01-18 06:13:49 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][220/312]	eta 0:00:44 lr 0.001493	time 0.4892 (0.4793)	model_time 0.4890 (0.4690)	loss 4.1241 (3.0637)	grad_norm 1.1486 (1.9566/0.9382)	mem 16099MB
[2025-01-18 06:13:53 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][230/312]	eta 0:00:39 lr 0.001493	time 0.4525 (0.4782)	model_time 0.4521 (0.4684)	loss 3.7418 (3.0686)	grad_norm 2.0251 (1.9592/0.9295)	mem 16099MB
[2025-01-18 06:13:58 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][240/312]	eta 0:00:34 lr 0.001492	time 0.4501 (0.4774)	model_time 0.4497 (0.4680)	loss 2.4305 (3.0610)	grad_norm 2.5410 (1.9795/0.9312)	mem 16099MB
[2025-01-18 06:14:03 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][250/312]	eta 0:00:29 lr 0.001492	time 0.4597 (0.4779)	model_time 0.4595 (0.4689)	loss 3.3457 (3.0765)	grad_norm 1.3130 (1.9735/0.9225)	mem 16099MB
[2025-01-18 06:14:07 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][260/312]	eta 0:00:24 lr 0.001491	time 0.4607 (0.4774)	model_time 0.4605 (0.4687)	loss 3.8040 (3.0690)	grad_norm 1.2815 (1.9601/0.9167)	mem 16099MB
[2025-01-18 06:14:12 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][270/312]	eta 0:00:20 lr 0.001490	time 0.4622 (0.4777)	model_time 0.4620 (0.4693)	loss 3.0668 (3.0777)	grad_norm 1.3135 (1.9373/0.9083)	mem 16099MB
[2025-01-18 06:14:17 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][280/312]	eta 0:00:15 lr 0.001490	time 0.4498 (0.4778)	model_time 0.4494 (0.4696)	loss 3.2984 (3.0866)	grad_norm 1.1755 (1.9294/0.8980)	mem 16099MB
[2025-01-18 06:14:22 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][290/312]	eta 0:00:10 lr 0.001489	time 0.4598 (0.4775)	model_time 0.4594 (0.4696)	loss 3.1221 (3.0854)	grad_norm 3.2732 (1.9334/0.8909)	mem 16099MB
[2025-01-18 06:14:26 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][300/312]	eta 0:00:05 lr 0.001488	time 0.4391 (0.4772)	model_time 0.4390 (0.4696)	loss 3.0532 (3.0980)	grad_norm 1.3392 (1.9230/0.8865)	mem 16099MB
[2025-01-18 06:14:31 internimage_t_1k_224] (main.py 510): INFO Train: [175/300][310/312]	eta 0:00:00 lr 0.001488	time 0.5202 (0.4764)	model_time 0.5200 (0.4690)	loss 2.6715 (3.0962)	grad_norm 1.1550 (1.9087/0.8848)	mem 16099MB
[2025-01-18 06:14:31 internimage_t_1k_224] (main.py 519): INFO EPOCH 175 training takes 0:02:28
[2025-01-18 06:14:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_175.pth saving......
[2025-01-18 06:14:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_175.pth saved !!!
[2025-01-18 06:14:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.408 (7.408)	Loss 0.8067 (0.8067)	Acc@1 83.325 (83.325)	Acc@5 96.729 (96.729)	Mem 16099MB
[2025-01-18 06:14:43 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.002)	Loss 1.0990 (0.9434)	Acc@1 75.952 (80.289)	Acc@5 93.994 (95.384)	Mem 16099MB
[2025-01-18 06:14:43 internimage_t_1k_224] (main.py 575): INFO [Epoch:175] * Acc@1 80.240 Acc@5 95.423
[2025-01-18 06:14:43 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.2%
[2025-01-18 06:14:43 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.31%
[2025-01-18 06:14:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.158 (8.158)	Loss 0.8044 (0.8044)	Acc@1 84.497 (84.497)	Acc@5 97.314 (97.314)	Mem 16099MB
[2025-01-18 06:14:56 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.094)	Loss 1.0867 (0.9304)	Acc@1 76.904 (81.601)	Acc@5 94.434 (95.834)	Mem 16099MB
[2025-01-18 06:14:56 internimage_t_1k_224] (main.py 575): INFO [Epoch:175] * Acc@1 81.478 Acc@5 95.871
[2025-01-18 06:14:56 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.5%
[2025-01-18 06:14:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:14:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:14:57 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.48%
[2025-01-18 06:15:00 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][0/312]	eta 0:12:29 lr 0.001488	time 2.4013 (2.4013)	model_time 0.4783 (0.4783)	loss 3.4367 (3.4367)	grad_norm 0.8023 (0.8023/0.0000)	mem 16099MB
[2025-01-18 06:15:04 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][10/312]	eta 0:03:14 lr 0.001487	time 0.4568 (0.6447)	model_time 0.4567 (0.4696)	loss 3.9491 (3.0330)	grad_norm 1.6396 (1.6860/0.5575)	mem 16099MB
[2025-01-18 06:15:09 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][20/312]	eta 0:02:45 lr 0.001486	time 0.4490 (0.5659)	model_time 0.4486 (0.4739)	loss 3.3358 (3.0552)	grad_norm 1.4219 (2.0601/0.8318)	mem 16099MB
[2025-01-18 06:15:14 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][30/312]	eta 0:02:30 lr 0.001486	time 0.4794 (0.5331)	model_time 0.4792 (0.4707)	loss 2.9979 (3.1223)	grad_norm 1.8441 (2.0165/0.8146)	mem 16099MB
[2025-01-18 06:15:18 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][40/312]	eta 0:02:19 lr 0.001485	time 0.4578 (0.5143)	model_time 0.4576 (0.4670)	loss 3.3140 (3.0782)	grad_norm 2.8857 (2.0607/0.8448)	mem 16099MB
[2025-01-18 06:15:23 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][50/312]	eta 0:02:11 lr 0.001484	time 0.4727 (0.5033)	model_time 0.4722 (0.4653)	loss 3.4105 (3.0902)	grad_norm 1.5374 (2.0562/0.8822)	mem 16099MB
[2025-01-18 06:15:28 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][60/312]	eta 0:02:05 lr 0.001484	time 0.7425 (0.4997)	model_time 0.7420 (0.4678)	loss 3.4815 (3.0448)	grad_norm 1.0733 (2.0081/0.8486)	mem 16099MB
[2025-01-18 06:15:32 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][70/312]	eta 0:01:59 lr 0.001483	time 0.4568 (0.4946)	model_time 0.4566 (0.4671)	loss 3.4361 (3.0543)	grad_norm 1.7103 (1.9422/0.8199)	mem 16099MB
[2025-01-18 06:15:37 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][80/312]	eta 0:01:54 lr 0.001482	time 0.4521 (0.4929)	model_time 0.4516 (0.4687)	loss 2.8697 (3.0547)	grad_norm 2.1868 (1.9351/0.7975)	mem 16099MB
[2025-01-18 06:15:42 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][90/312]	eta 0:01:48 lr 0.001482	time 0.4540 (0.4888)	model_time 0.4538 (0.4673)	loss 3.3472 (3.0634)	grad_norm 1.5749 (1.8867/0.7879)	mem 16099MB
[2025-01-18 06:15:46 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][100/312]	eta 0:01:43 lr 0.001481	time 0.4677 (0.4867)	model_time 0.4675 (0.4673)	loss 2.3130 (3.0605)	grad_norm 2.2308 (1.8843/0.7562)	mem 16099MB
[2025-01-18 06:15:51 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][110/312]	eta 0:01:37 lr 0.001481	time 0.4466 (0.4841)	model_time 0.4462 (0.4664)	loss 3.5501 (3.0809)	grad_norm 5.6707 (1.9385/0.9539)	mem 16099MB
[2025-01-18 06:15:55 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][120/312]	eta 0:01:32 lr 0.001480	time 0.4534 (0.4815)	model_time 0.4529 (0.4653)	loss 4.0407 (3.0865)	grad_norm 2.6381 (1.9502/0.9331)	mem 16099MB
[2025-01-18 06:16:00 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][130/312]	eta 0:01:27 lr 0.001479	time 0.5673 (0.4814)	model_time 0.5671 (0.4664)	loss 3.1253 (3.0774)	grad_norm 3.9033 (1.9955/0.9370)	mem 16099MB
[2025-01-18 06:16:05 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][140/312]	eta 0:01:22 lr 0.001479	time 0.4594 (0.4807)	model_time 0.4592 (0.4667)	loss 3.5065 (3.0840)	grad_norm 2.8783 (1.9972/0.9202)	mem 16099MB
[2025-01-18 06:16:10 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][150/312]	eta 0:01:17 lr 0.001478	time 0.4618 (0.4798)	model_time 0.4613 (0.4667)	loss 2.8362 (3.0916)	grad_norm 4.3043 (2.0284/0.9311)	mem 16099MB
[2025-01-18 06:16:15 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][160/312]	eta 0:01:13 lr 0.001477	time 0.4480 (0.4806)	model_time 0.4476 (0.4682)	loss 3.2771 (3.1113)	grad_norm 1.3312 (2.0315/0.9144)	mem 16099MB
[2025-01-18 06:16:19 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][170/312]	eta 0:01:08 lr 0.001477	time 0.4470 (0.4803)	model_time 0.4468 (0.4686)	loss 3.0313 (3.1056)	grad_norm 1.8695 (2.0152/0.8991)	mem 16099MB
[2025-01-18 06:16:24 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][180/312]	eta 0:01:03 lr 0.001476	time 0.4421 (0.4796)	model_time 0.4419 (0.4686)	loss 2.9645 (3.1135)	grad_norm 2.0720 (2.0271/0.8833)	mem 16099MB
[2025-01-18 06:16:29 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][190/312]	eta 0:00:58 lr 0.001475	time 0.4502 (0.4791)	model_time 0.4498 (0.4687)	loss 4.0867 (3.1114)	grad_norm 1.9906 (2.0275/0.8699)	mem 16099MB
[2025-01-18 06:16:33 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][200/312]	eta 0:00:53 lr 0.001475	time 0.4429 (0.4782)	model_time 0.4424 (0.4683)	loss 2.9126 (3.1067)	grad_norm 1.2778 (2.0205/0.8615)	mem 16099MB
[2025-01-18 06:16:38 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][210/312]	eta 0:00:48 lr 0.001474	time 0.4687 (0.4776)	model_time 0.4685 (0.4681)	loss 2.8972 (3.1088)	grad_norm 2.7540 (2.0355/0.8511)	mem 16099MB
[2025-01-18 06:16:43 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][220/312]	eta 0:00:44 lr 0.001473	time 0.7098 (0.4787)	model_time 0.7097 (0.4696)	loss 2.7275 (3.1102)	grad_norm 1.4033 (2.0359/0.8481)	mem 16099MB
[2025-01-18 06:16:48 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][230/312]	eta 0:00:39 lr 0.001473	time 0.4499 (0.4784)	model_time 0.4494 (0.4697)	loss 2.6260 (3.1104)	grad_norm 2.3479 (2.0247/0.8371)	mem 16099MB
[2025-01-18 06:16:52 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][240/312]	eta 0:00:34 lr 0.001472	time 0.4581 (0.4774)	model_time 0.4576 (0.4690)	loss 2.7975 (3.1095)	grad_norm 3.3730 (2.0423/0.8457)	mem 16099MB
[2025-01-18 06:16:57 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][250/312]	eta 0:00:29 lr 0.001472	time 0.4447 (0.4768)	model_time 0.4442 (0.4687)	loss 2.3464 (3.1064)	grad_norm 3.0894 (2.0678/0.8678)	mem 16099MB
[2025-01-18 06:17:02 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][260/312]	eta 0:00:24 lr 0.001471	time 0.5472 (0.4765)	model_time 0.5471 (0.4688)	loss 3.4368 (3.1087)	grad_norm 1.7817 (2.0746/0.8770)	mem 16099MB
[2025-01-18 06:17:06 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][270/312]	eta 0:00:19 lr 0.001470	time 0.4588 (0.4756)	model_time 0.4586 (0.4681)	loss 3.2856 (3.1125)	grad_norm 3.0941 (2.0739/0.8787)	mem 16099MB
[2025-01-18 06:17:11 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][280/312]	eta 0:00:15 lr 0.001470	time 0.5037 (0.4750)	model_time 0.5035 (0.4677)	loss 2.2386 (3.1080)	grad_norm 1.4228 (2.0964/0.9021)	mem 16099MB
[2025-01-18 06:17:15 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][290/312]	eta 0:00:10 lr 0.001469	time 0.4475 (0.4746)	model_time 0.4473 (0.4676)	loss 3.6558 (3.1143)	grad_norm 1.1156 (2.0842/0.8986)	mem 16099MB
[2025-01-18 06:17:20 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][300/312]	eta 0:00:05 lr 0.001468	time 0.4382 (0.4741)	model_time 0.4381 (0.4673)	loss 2.7058 (3.1148)	grad_norm 1.9874 (2.0771/0.8914)	mem 16099MB
[2025-01-18 06:17:24 internimage_t_1k_224] (main.py 510): INFO Train: [176/300][310/312]	eta 0:00:00 lr 0.001468	time 0.4393 (0.4733)	model_time 0.4391 (0.4667)	loss 3.0932 (3.1198)	grad_norm 1.5801 (2.0615/0.8973)	mem 16099MB
[2025-01-18 06:17:25 internimage_t_1k_224] (main.py 519): INFO EPOCH 176 training takes 0:02:27
[2025-01-18 06:17:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_176.pth saving......
[2025-01-18 06:17:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_176.pth saved !!!
[2025-01-18 06:17:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.482 (7.482)	Loss 0.7377 (0.7377)	Acc@1 83.862 (83.862)	Acc@5 97.314 (97.314)	Mem 16099MB
[2025-01-18 06:17:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.006)	Loss 1.0513 (0.8813)	Acc@1 76.172 (80.558)	Acc@5 93.799 (95.466)	Mem 16099MB
[2025-01-18 06:17:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:176] * Acc@1 80.380 Acc@5 95.459
[2025-01-18 06:17:37 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.4%
[2025-01-18 06:17:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 06:17:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 06:17:38 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.38%
[2025-01-18 06:17:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.288 (7.288)	Loss 0.8034 (0.8034)	Acc@1 84.521 (84.521)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 06:17:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.005)	Loss 1.0850 (0.9293)	Acc@1 77.100 (81.654)	Acc@5 94.458 (95.847)	Mem 16099MB
[2025-01-18 06:17:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:176] * Acc@1 81.536 Acc@5 95.883
[2025-01-18 06:17:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.5%
[2025-01-18 06:17:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:17:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:17:51 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.54%
[2025-01-18 06:17:54 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][0/312]	eta 0:12:51 lr 0.001468	time 2.4743 (2.4743)	model_time 0.5239 (0.5239)	loss 3.1894 (3.1894)	grad_norm 3.1502 (3.1502/0.0000)	mem 16099MB
[2025-01-18 06:17:58 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][10/312]	eta 0:03:14 lr 0.001467	time 0.4362 (0.6446)	model_time 0.4361 (0.4670)	loss 3.1650 (3.1436)	grad_norm 1.4380 (2.3975/0.7737)	mem 16099MB
[2025-01-18 06:18:03 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][20/312]	eta 0:02:43 lr 0.001466	time 0.4608 (0.5599)	model_time 0.4606 (0.4668)	loss 2.3123 (3.0438)	grad_norm 1.4768 (1.9618/0.7892)	mem 16099MB
[2025-01-18 06:18:07 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][30/312]	eta 0:02:28 lr 0.001466	time 0.4516 (0.5255)	model_time 0.4514 (0.4623)	loss 3.1189 (3.1308)	grad_norm 1.4025 (1.8387/0.6871)	mem 16099MB
[2025-01-18 06:18:12 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][40/312]	eta 0:02:18 lr 0.001465	time 0.4418 (0.5095)	model_time 0.4413 (0.4616)	loss 2.7627 (3.0611)	grad_norm 1.5444 (1.8391/0.7327)	mem 16099MB
[2025-01-18 06:18:17 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][50/312]	eta 0:02:10 lr 0.001464	time 0.4699 (0.4988)	model_time 0.4695 (0.4602)	loss 3.7390 (3.0730)	grad_norm 3.3439 (1.9669/0.7996)	mem 16099MB
[2025-01-18 06:18:21 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][60/312]	eta 0:02:04 lr 0.001464	time 0.4590 (0.4928)	model_time 0.4586 (0.4605)	loss 3.3109 (3.0693)	grad_norm 2.4751 (2.0092/0.8665)	mem 16099MB
[2025-01-18 06:18:26 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][70/312]	eta 0:01:58 lr 0.001463	time 0.4597 (0.4879)	model_time 0.4596 (0.4601)	loss 2.7320 (3.0685)	grad_norm 1.0712 (1.9553/0.8395)	mem 16099MB
[2025-01-18 06:18:30 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][80/312]	eta 0:01:52 lr 0.001462	time 0.4462 (0.4850)	model_time 0.4458 (0.4606)	loss 3.4519 (3.0803)	grad_norm 2.2968 (1.9581/0.8268)	mem 16099MB
[2025-01-18 06:18:35 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][90/312]	eta 0:01:46 lr 0.001462	time 0.4410 (0.4818)	model_time 0.4408 (0.4601)	loss 3.0671 (3.0805)	grad_norm 3.6108 (1.9581/0.8145)	mem 16099MB
[2025-01-18 06:18:40 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][100/312]	eta 0:01:42 lr 0.001461	time 0.4431 (0.4816)	model_time 0.4426 (0.4620)	loss 3.1348 (3.0712)	grad_norm 4.7577 (1.9970/0.8563)	mem 16099MB
[2025-01-18 06:18:45 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][110/312]	eta 0:01:38 lr 0.001461	time 0.4468 (0.4855)	model_time 0.4466 (0.4676)	loss 3.3118 (3.0902)	grad_norm 1.2375 (2.0635/0.8976)	mem 16099MB
[2025-01-18 06:18:50 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][120/312]	eta 0:01:32 lr 0.001460	time 0.4460 (0.4827)	model_time 0.4459 (0.4662)	loss 3.1843 (3.0982)	grad_norm 1.6632 (2.0415/0.8736)	mem 16099MB
[2025-01-18 06:18:54 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][130/312]	eta 0:01:27 lr 0.001459	time 0.4567 (0.4818)	model_time 0.4565 (0.4666)	loss 3.1794 (3.1017)	grad_norm 2.5534 (2.0117/0.8594)	mem 16099MB
[2025-01-18 06:18:59 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][140/312]	eta 0:01:23 lr 0.001459	time 0.4531 (0.4836)	model_time 0.4527 (0.4695)	loss 3.1107 (3.1094)	grad_norm 4.1753 (2.0695/0.8758)	mem 16099MB
[2025-01-18 06:19:04 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][150/312]	eta 0:01:18 lr 0.001458	time 0.4436 (0.4831)	model_time 0.4435 (0.4698)	loss 4.2240 (3.1309)	grad_norm 1.3519 (2.0676/0.8716)	mem 16099MB
[2025-01-18 06:19:09 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][160/312]	eta 0:01:13 lr 0.001457	time 0.4423 (0.4822)	model_time 0.4419 (0.4697)	loss 2.6221 (3.1166)	grad_norm 1.4988 (2.0467/0.8561)	mem 16099MB
[2025-01-18 06:19:13 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][170/312]	eta 0:01:08 lr 0.001457	time 0.4794 (0.4813)	model_time 0.4790 (0.4695)	loss 3.0900 (3.1187)	grad_norm 1.0781 (2.0513/0.8425)	mem 16099MB
[2025-01-18 06:19:18 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][180/312]	eta 0:01:03 lr 0.001456	time 0.4657 (0.4802)	model_time 0.4653 (0.4691)	loss 2.7474 (3.1069)	grad_norm 0.9979 (2.0204/0.8362)	mem 16099MB
[2025-01-18 06:19:23 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][190/312]	eta 0:00:58 lr 0.001455	time 0.4509 (0.4800)	model_time 0.4508 (0.4694)	loss 3.9128 (3.1191)	grad_norm 1.5994 (2.0012/0.8237)	mem 16099MB
[2025-01-18 06:19:27 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][200/312]	eta 0:00:53 lr 0.001455	time 0.4424 (0.4785)	model_time 0.4422 (0.4685)	loss 3.3253 (3.1274)	grad_norm 1.4492 (2.0009/0.8269)	mem 16099MB
[2025-01-18 06:19:32 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][210/312]	eta 0:00:48 lr 0.001454	time 0.4491 (0.4778)	model_time 0.4486 (0.4682)	loss 3.4985 (3.1223)	grad_norm 2.0817 (2.0595/0.9099)	mem 16099MB
[2025-01-18 06:19:36 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][220/312]	eta 0:00:43 lr 0.001454	time 0.4573 (0.4769)	model_time 0.4571 (0.4677)	loss 3.0595 (3.1221)	grad_norm 4.2616 (2.0750/0.9135)	mem 16099MB
[2025-01-18 06:19:41 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][230/312]	eta 0:00:39 lr 0.001453	time 0.4574 (0.4761)	model_time 0.4573 (0.4673)	loss 3.6846 (3.1196)	grad_norm 3.2649 (2.0679/0.9194)	mem 16099MB
[2025-01-18 06:19:46 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][240/312]	eta 0:00:34 lr 0.001452	time 0.4579 (0.4753)	model_time 0.4577 (0.4669)	loss 3.1860 (3.1142)	grad_norm 2.0322 (2.0752/0.9052)	mem 16099MB
[2025-01-18 06:19:50 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][250/312]	eta 0:00:29 lr 0.001452	time 0.4459 (0.4744)	model_time 0.4457 (0.4663)	loss 3.7047 (3.1190)	grad_norm 3.3638 (2.0772/0.8983)	mem 16099MB
[2025-01-18 06:19:55 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][260/312]	eta 0:00:24 lr 0.001451	time 0.4469 (0.4736)	model_time 0.4467 (0.4658)	loss 3.7247 (3.1257)	grad_norm 1.1818 (2.0694/0.8889)	mem 16099MB
[2025-01-18 06:19:59 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][270/312]	eta 0:00:19 lr 0.001450	time 0.4511 (0.4732)	model_time 0.4509 (0.4656)	loss 2.3093 (3.1269)	grad_norm 1.5201 (2.0592/0.8817)	mem 16099MB
[2025-01-18 06:20:04 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][280/312]	eta 0:00:15 lr 0.001450	time 0.4473 (0.4724)	model_time 0.4468 (0.4651)	loss 3.6612 (3.1184)	grad_norm 1.3977 (2.0587/0.8841)	mem 16099MB
[2025-01-18 06:20:08 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][290/312]	eta 0:00:10 lr 0.001449	time 0.5432 (0.4720)	model_time 0.5427 (0.4650)	loss 3.4641 (3.1238)	grad_norm 1.4462 (2.0565/0.8769)	mem 16099MB
[2025-01-18 06:20:13 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][300/312]	eta 0:00:05 lr 0.001448	time 0.4383 (0.4720)	model_time 0.4382 (0.4651)	loss 3.1304 (3.1302)	grad_norm 2.0462 (2.0762/0.8852)	mem 16099MB
[2025-01-18 06:20:18 internimage_t_1k_224] (main.py 510): INFO Train: [177/300][310/312]	eta 0:00:00 lr 0.001448	time 0.5496 (0.4714)	model_time 0.5495 (0.4648)	loss 2.4684 (3.1322)	grad_norm 2.0706 (2.0869/0.8931)	mem 16099MB
[2025-01-18 06:20:18 internimage_t_1k_224] (main.py 519): INFO EPOCH 177 training takes 0:02:27
[2025-01-18 06:20:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_177.pth saving......
[2025-01-18 06:20:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_177.pth saved !!!
[2025-01-18 06:20:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.521 (7.521)	Loss 0.7981 (0.7981)	Acc@1 83.032 (83.032)	Acc@5 96.851 (96.851)	Mem 16099MB
[2025-01-18 06:20:30 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.002)	Loss 1.0969 (0.9215)	Acc@1 75.317 (80.320)	Acc@5 93.506 (95.304)	Mem 16099MB
[2025-01-18 06:20:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:177] * Acc@1 80.238 Acc@5 95.317
[2025-01-18 06:20:31 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.2%
[2025-01-18 06:20:31 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.38%
[2025-01-18 06:20:39 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.199 (8.199)	Loss 0.8026 (0.8026)	Acc@1 84.595 (84.595)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 06:20:43 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.099)	Loss 1.0833 (0.9283)	Acc@1 77.075 (81.687)	Acc@5 94.531 (95.874)	Mem 16099MB
[2025-01-18 06:20:43 internimage_t_1k_224] (main.py 575): INFO [Epoch:177] * Acc@1 81.568 Acc@5 95.909
[2025-01-18 06:20:43 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.6%
[2025-01-18 06:20:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:20:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:20:44 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.57%
[2025-01-18 06:20:47 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][0/312]	eta 0:14:45 lr 0.001448	time 2.8368 (2.8368)	model_time 0.4730 (0.4730)	loss 3.3105 (3.3105)	grad_norm 1.1655 (1.1655/0.0000)	mem 16099MB
[2025-01-18 06:20:52 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][10/312]	eta 0:03:31 lr 0.001447	time 0.4489 (0.6997)	model_time 0.4484 (0.4845)	loss 3.3148 (2.9272)	grad_norm 1.4714 (2.0478/0.9218)	mem 16099MB
[2025-01-18 06:20:57 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][20/312]	eta 0:02:51 lr 0.001446	time 0.4534 (0.5861)	model_time 0.4533 (0.4733)	loss 3.6522 (3.1058)	grad_norm 1.9820 (1.7692/0.7998)	mem 16099MB
[2025-01-18 06:21:01 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][30/312]	eta 0:02:36 lr 0.001446	time 0.4585 (0.5562)	model_time 0.4584 (0.4796)	loss 2.8107 (3.1657)	grad_norm 3.2130 (1.9199/0.7984)	mem 16099MB
[2025-01-18 06:21:06 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][40/312]	eta 0:02:25 lr 0.001445	time 0.4556 (0.5339)	model_time 0.4552 (0.4759)	loss 2.5256 (3.0839)	grad_norm 1.5844 (1.9817/0.8177)	mem 16099MB
[2025-01-18 06:21:11 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][50/312]	eta 0:02:17 lr 0.001445	time 0.5644 (0.5250)	model_time 0.5642 (0.4783)	loss 3.2952 (3.1281)	grad_norm 1.9464 (2.0160/0.8865)	mem 16099MB
[2025-01-18 06:21:16 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][60/312]	eta 0:02:09 lr 0.001444	time 0.4519 (0.5145)	model_time 0.4517 (0.4754)	loss 2.7750 (3.1197)	grad_norm 1.5188 (2.0128/0.8811)	mem 16099MB
[2025-01-18 06:21:20 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][70/312]	eta 0:02:03 lr 0.001443	time 0.4494 (0.5090)	model_time 0.4492 (0.4754)	loss 3.3039 (3.1440)	grad_norm 2.3721 (2.0247/0.8601)	mem 16099MB
[2025-01-18 06:21:25 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][80/312]	eta 0:01:56 lr 0.001443	time 0.4621 (0.5028)	model_time 0.4616 (0.4732)	loss 2.9285 (3.1387)	grad_norm 2.0390 (2.0610/0.8369)	mem 16099MB
[2025-01-18 06:21:30 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][90/312]	eta 0:01:50 lr 0.001442	time 0.4454 (0.4989)	model_time 0.4449 (0.4726)	loss 3.2685 (3.1533)	grad_norm 2.2367 (2.0581/0.8286)	mem 16099MB
[2025-01-18 06:21:35 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][100/312]	eta 0:01:45 lr 0.001441	time 0.4465 (0.4983)	model_time 0.4463 (0.4745)	loss 3.7777 (3.1554)	grad_norm 2.3834 (2.0538/0.8265)	mem 16099MB
[2025-01-18 06:21:39 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][110/312]	eta 0:01:39 lr 0.001441	time 0.4471 (0.4949)	model_time 0.4467 (0.4733)	loss 2.4111 (3.1342)	grad_norm 1.9999 (2.0646/0.8510)	mem 16099MB
[2025-01-18 06:21:44 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][120/312]	eta 0:01:35 lr 0.001440	time 0.7253 (0.4955)	model_time 0.7249 (0.4756)	loss 3.1096 (3.1107)	grad_norm 2.0851 (2.0684/0.8418)	mem 16099MB
[2025-01-18 06:21:49 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][130/312]	eta 0:01:29 lr 0.001439	time 0.4450 (0.4931)	model_time 0.4445 (0.4747)	loss 3.5549 (3.1152)	grad_norm 4.2044 (2.0767/0.8666)	mem 16099MB
[2025-01-18 06:21:53 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][140/312]	eta 0:01:24 lr 0.001439	time 0.4534 (0.4907)	model_time 0.4532 (0.4736)	loss 3.1949 (3.1057)	grad_norm 2.5401 (2.0685/0.8467)	mem 16099MB
[2025-01-18 06:21:58 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][150/312]	eta 0:01:19 lr 0.001438	time 0.7441 (0.4906)	model_time 0.7439 (0.4746)	loss 3.5941 (3.1011)	grad_norm 1.4732 (2.0196/0.8430)	mem 16099MB
[2025-01-18 06:22:03 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][160/312]	eta 0:01:14 lr 0.001438	time 0.4563 (0.4882)	model_time 0.4558 (0.4731)	loss 3.8385 (3.1188)	grad_norm 1.9318 (1.9848/0.8344)	mem 16099MB
[2025-01-18 06:22:08 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][170/312]	eta 0:01:09 lr 0.001437	time 0.4739 (0.4872)	model_time 0.4735 (0.4729)	loss 2.2225 (3.1176)	grad_norm 1.9871 (2.0040/0.8521)	mem 16099MB
[2025-01-18 06:22:12 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][180/312]	eta 0:01:04 lr 0.001436	time 0.4489 (0.4860)	model_time 0.4485 (0.4725)	loss 2.3881 (3.1076)	grad_norm 2.5827 (2.0524/0.9116)	mem 16099MB
[2025-01-18 06:22:17 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][190/312]	eta 0:00:59 lr 0.001436	time 0.4510 (0.4844)	model_time 0.4508 (0.4716)	loss 3.3732 (3.1085)	grad_norm 2.1488 (2.0726/0.9247)	mem 16099MB
[2025-01-18 06:22:21 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][200/312]	eta 0:00:54 lr 0.001435	time 0.4505 (0.4832)	model_time 0.4500 (0.4710)	loss 3.1274 (3.0979)	grad_norm 5.3148 (2.1028/0.9663)	mem 16099MB
[2025-01-18 06:22:26 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][210/312]	eta 0:00:49 lr 0.001434	time 0.4543 (0.4835)	model_time 0.4541 (0.4719)	loss 3.6938 (3.0979)	grad_norm 2.3187 (2.1481/0.9994)	mem 16099MB
[2025-01-18 06:22:31 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][220/312]	eta 0:00:44 lr 0.001434	time 0.4449 (0.4822)	model_time 0.4445 (0.4711)	loss 1.8463 (3.1009)	grad_norm 1.2296 (2.1397/0.9847)	mem 16099MB
[2025-01-18 06:22:36 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][230/312]	eta 0:00:39 lr 0.001433	time 0.4532 (0.4821)	model_time 0.4528 (0.4715)	loss 3.2450 (3.0979)	grad_norm 1.3606 (2.1166/0.9835)	mem 16099MB
[2025-01-18 06:22:40 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][240/312]	eta 0:00:34 lr 0.001432	time 0.4817 (0.4814)	model_time 0.4813 (0.4712)	loss 3.1921 (3.0962)	grad_norm 1.6597 (2.0883/0.9752)	mem 16099MB
[2025-01-18 06:22:45 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][250/312]	eta 0:00:29 lr 0.001432	time 0.4618 (0.4808)	model_time 0.4616 (0.4709)	loss 3.6359 (3.0928)	grad_norm 1.7729 (2.0750/0.9647)	mem 16099MB
[2025-01-18 06:22:50 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][260/312]	eta 0:00:24 lr 0.001431	time 0.4493 (0.4802)	model_time 0.4488 (0.4707)	loss 2.5642 (3.0888)	grad_norm 0.8002 (2.0519/0.9563)	mem 16099MB
[2025-01-18 06:22:54 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][270/312]	eta 0:00:20 lr 0.001431	time 0.4529 (0.4798)	model_time 0.4527 (0.4707)	loss 3.2277 (3.0960)	grad_norm 1.9909 (2.0843/0.9802)	mem 16099MB
[2025-01-18 06:22:59 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][280/312]	eta 0:00:15 lr 0.001430	time 0.4410 (0.4791)	model_time 0.4408 (0.4703)	loss 2.9641 (3.0954)	grad_norm 1.2650 (2.1047/1.0073)	mem 16099MB
[2025-01-18 06:23:04 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][290/312]	eta 0:00:10 lr 0.001429	time 0.4606 (0.4802)	model_time 0.4602 (0.4716)	loss 2.5927 (3.0836)	grad_norm 1.1664 (2.0887/0.9983)	mem 16099MB
[2025-01-18 06:23:09 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][300/312]	eta 0:00:05 lr 0.001429	time 0.4445 (0.4794)	model_time 0.4444 (0.4711)	loss 3.3437 (3.0840)	grad_norm 1.3465 (2.0735/0.9893)	mem 16099MB
[2025-01-18 06:23:13 internimage_t_1k_224] (main.py 510): INFO Train: [178/300][310/312]	eta 0:00:00 lr 0.001428	time 0.4397 (0.4784)	model_time 0.4396 (0.4704)	loss 1.8549 (3.0753)	grad_norm 4.3964 (2.0782/0.9858)	mem 16099MB
[2025-01-18 06:23:13 internimage_t_1k_224] (main.py 519): INFO EPOCH 178 training takes 0:02:29
[2025-01-18 06:23:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_178.pth saving......
[2025-01-18 06:23:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_178.pth saved !!!
[2025-01-18 06:23:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.374 (7.374)	Loss 0.7545 (0.7545)	Acc@1 83.496 (83.496)	Acc@5 96.924 (96.924)	Mem 16099MB
[2025-01-18 06:23:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.996)	Loss 1.0569 (0.8903)	Acc@1 76.294 (80.553)	Acc@5 93.750 (95.497)	Mem 16099MB
[2025-01-18 06:23:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:178] * Acc@1 80.450 Acc@5 95.527
[2025-01-18 06:23:26 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.5%
[2025-01-18 06:23:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 06:23:27 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 06:23:27 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.45%
[2025-01-18 06:23:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.202 (7.202)	Loss 0.8017 (0.8017)	Acc@1 84.570 (84.570)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 06:23:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.985)	Loss 1.0812 (0.9269)	Acc@1 77.124 (81.747)	Acc@5 94.507 (95.881)	Mem 16099MB
[2025-01-18 06:23:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:178] * Acc@1 81.620 Acc@5 95.915
[2025-01-18 06:23:38 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.6%
[2025-01-18 06:23:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:23:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:23:39 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.62%
[2025-01-18 06:23:42 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][0/312]	eta 0:13:54 lr 0.001428	time 2.6734 (2.6734)	model_time 0.4745 (0.4745)	loss 3.1096 (3.1096)	grad_norm 4.3727 (4.3727/0.0000)	mem 16099MB
[2025-01-18 06:23:46 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][10/312]	eta 0:03:21 lr 0.001427	time 0.4583 (0.6669)	model_time 0.4579 (0.4667)	loss 3.3535 (3.1448)	grad_norm 3.2631 (2.3701/1.1565)	mem 16099MB
[2025-01-18 06:23:51 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][20/312]	eta 0:02:49 lr 0.001427	time 0.5030 (0.5816)	model_time 0.5028 (0.4766)	loss 3.4844 (3.2011)	grad_norm 1.3236 (1.9542/1.0367)	mem 16099MB
[2025-01-18 06:23:56 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][30/312]	eta 0:02:34 lr 0.001426	time 0.5560 (0.5489)	model_time 0.5555 (0.4776)	loss 3.4047 (3.1570)	grad_norm 1.3789 (1.8103/0.8888)	mem 16099MB
[2025-01-18 06:24:01 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][40/312]	eta 0:02:23 lr 0.001425	time 0.4429 (0.5290)	model_time 0.4427 (0.4750)	loss 3.1498 (3.1244)	grad_norm 1.6344 (1.8396/0.8388)	mem 16099MB
[2025-01-18 06:24:05 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][50/312]	eta 0:02:14 lr 0.001425	time 0.4686 (0.5149)	model_time 0.4683 (0.4715)	loss 3.6591 (3.1579)	grad_norm 1.5478 (1.8518/0.8156)	mem 16099MB
[2025-01-18 06:24:10 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][60/312]	eta 0:02:07 lr 0.001424	time 0.4672 (0.5069)	model_time 0.4671 (0.4705)	loss 3.3887 (3.0774)	grad_norm 1.3312 (1.7995/0.7821)	mem 16099MB
[2025-01-18 06:24:15 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][70/312]	eta 0:02:01 lr 0.001423	time 0.5531 (0.5004)	model_time 0.5530 (0.4691)	loss 3.1937 (3.1032)	grad_norm 2.1658 (1.8353/0.7655)	mem 16099MB
[2025-01-18 06:24:19 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][80/312]	eta 0:01:55 lr 0.001423	time 0.4509 (0.4960)	model_time 0.4507 (0.4685)	loss 3.6407 (3.1228)	grad_norm 3.1558 (1.8522/0.7577)	mem 16099MB
[2025-01-18 06:24:24 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][90/312]	eta 0:01:50 lr 0.001422	time 0.5397 (0.4975)	model_time 0.5393 (0.4730)	loss 3.5740 (3.1151)	grad_norm 1.3848 (1.8382/0.7276)	mem 16099MB
[2025-01-18 06:24:29 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][100/312]	eta 0:01:44 lr 0.001422	time 0.4620 (0.4944)	model_time 0.4615 (0.4723)	loss 2.5236 (3.1206)	grad_norm 2.0188 (1.8840/0.7454)	mem 16099MB
[2025-01-18 06:24:34 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][110/312]	eta 0:01:39 lr 0.001421	time 0.4515 (0.4916)	model_time 0.4511 (0.4714)	loss 2.4115 (3.1298)	grad_norm 1.7232 (1.9107/0.7798)	mem 16099MB
[2025-01-18 06:24:38 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][120/312]	eta 0:01:33 lr 0.001420	time 0.4585 (0.4890)	model_time 0.4583 (0.4705)	loss 2.8217 (3.1312)	grad_norm 2.2062 (1.9317/0.7649)	mem 16099MB
[2025-01-18 06:24:43 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][130/312]	eta 0:01:28 lr 0.001420	time 0.4576 (0.4870)	model_time 0.4571 (0.4699)	loss 3.1473 (3.1540)	grad_norm 2.0096 (1.9702/0.8316)	mem 16099MB
[2025-01-18 06:24:48 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][140/312]	eta 0:01:23 lr 0.001419	time 0.4519 (0.4862)	model_time 0.4517 (0.4703)	loss 2.5911 (3.1481)	grad_norm 3.1632 (1.9559/0.8215)	mem 16099MB
[2025-01-18 06:24:52 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][150/312]	eta 0:01:18 lr 0.001418	time 0.4549 (0.4847)	model_time 0.4545 (0.4698)	loss 2.7486 (3.1497)	grad_norm 2.0618 (2.0024/0.8465)	mem 16099MB
[2025-01-18 06:24:57 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][160/312]	eta 0:01:13 lr 0.001418	time 0.4497 (0.4836)	model_time 0.4495 (0.4696)	loss 3.2438 (3.1443)	grad_norm 1.2918 (1.9820/0.8319)	mem 16099MB
[2025-01-18 06:25:02 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][170/312]	eta 0:01:08 lr 0.001417	time 0.4504 (0.4821)	model_time 0.4500 (0.4688)	loss 3.4575 (3.1488)	grad_norm 1.2318 (1.9565/0.8238)	mem 16099MB
[2025-01-18 06:25:06 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][180/312]	eta 0:01:03 lr 0.001416	time 0.4443 (0.4811)	model_time 0.4441 (0.4686)	loss 2.8376 (3.1332)	grad_norm 3.7384 (1.9725/0.8407)	mem 16099MB
[2025-01-18 06:25:11 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][190/312]	eta 0:00:58 lr 0.001416	time 0.4582 (0.4806)	model_time 0.4580 (0.4687)	loss 2.2283 (3.1350)	grad_norm 2.7868 (1.9725/0.8288)	mem 16099MB
[2025-01-18 06:25:16 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][200/312]	eta 0:00:53 lr 0.001415	time 0.4439 (0.4798)	model_time 0.4435 (0.4685)	loss 2.2221 (3.1354)	grad_norm 1.6269 (1.9943/0.8257)	mem 16099MB
[2025-01-18 06:25:20 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][210/312]	eta 0:00:48 lr 0.001415	time 0.4466 (0.4788)	model_time 0.4462 (0.4680)	loss 3.8257 (3.1423)	grad_norm 2.0075 (1.9926/0.8172)	mem 16099MB
[2025-01-18 06:25:25 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][220/312]	eta 0:00:43 lr 0.001414	time 0.4587 (0.4776)	model_time 0.4586 (0.4673)	loss 2.2916 (3.1433)	grad_norm 0.8151 (2.0007/0.8255)	mem 16099MB
[2025-01-18 06:25:29 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][230/312]	eta 0:00:39 lr 0.001413	time 0.4445 (0.4770)	model_time 0.4440 (0.4671)	loss 3.0186 (3.1326)	grad_norm 1.5893 (2.0089/0.8215)	mem 16099MB
[2025-01-18 06:25:34 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][240/312]	eta 0:00:34 lr 0.001413	time 0.4528 (0.4761)	model_time 0.4523 (0.4666)	loss 3.1236 (3.1348)	grad_norm 2.9942 (1.9958/0.8135)	mem 16099MB
[2025-01-18 06:25:39 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][250/312]	eta 0:00:29 lr 0.001412	time 0.4667 (0.4761)	model_time 0.4666 (0.4669)	loss 3.1749 (3.1277)	grad_norm 2.1341 (2.0297/0.8508)	mem 16099MB
[2025-01-18 06:25:43 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][260/312]	eta 0:00:24 lr 0.001411	time 0.4407 (0.4759)	model_time 0.4405 (0.4671)	loss 3.2124 (3.1289)	grad_norm 2.1353 (2.0278/0.8452)	mem 16099MB
[2025-01-18 06:25:48 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][270/312]	eta 0:00:19 lr 0.001411	time 0.4504 (0.4758)	model_time 0.4500 (0.4673)	loss 2.2101 (3.1271)	grad_norm 2.5423 (2.0462/0.8495)	mem 16099MB
[2025-01-18 06:25:53 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][280/312]	eta 0:00:15 lr 0.001410	time 0.4543 (0.4750)	model_time 0.4538 (0.4668)	loss 3.2103 (3.1194)	grad_norm 1.6759 (2.0340/0.8449)	mem 16099MB
[2025-01-18 06:25:57 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][290/312]	eta 0:00:10 lr 0.001410	time 0.4508 (0.4745)	model_time 0.4503 (0.4666)	loss 3.0244 (3.1172)	grad_norm 3.3616 (2.0316/0.8474)	mem 16099MB
[2025-01-18 06:26:02 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][300/312]	eta 0:00:05 lr 0.001409	time 0.5180 (0.4740)	model_time 0.5179 (0.4663)	loss 3.3015 (3.1091)	grad_norm 1.0480 (2.0267/0.8396)	mem 16099MB
[2025-01-18 06:26:06 internimage_t_1k_224] (main.py 510): INFO Train: [179/300][310/312]	eta 0:00:00 lr 0.001408	time 0.4395 (0.4730)	model_time 0.4394 (0.4655)	loss 3.6364 (3.1063)	grad_norm 0.9494 (2.0116/0.8288)	mem 16099MB
[2025-01-18 06:26:07 internimage_t_1k_224] (main.py 519): INFO EPOCH 179 training takes 0:02:27
[2025-01-18 06:26:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_179.pth saving......
[2025-01-18 06:26:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_179.pth saved !!!
[2025-01-18 06:26:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.494 (7.494)	Loss 0.8057 (0.8057)	Acc@1 83.569 (83.569)	Acc@5 96.948 (96.948)	Mem 16099MB
[2025-01-18 06:26:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.023)	Loss 1.0414 (0.9169)	Acc@1 77.246 (80.575)	Acc@5 94.189 (95.468)	Mem 16099MB
[2025-01-18 06:26:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:179] * Acc@1 80.502 Acc@5 95.491
[2025-01-18 06:26:19 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.5%
[2025-01-18 06:26:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 06:26:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 06:26:20 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.50%
[2025-01-18 06:26:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.627 (7.627)	Loss 0.8008 (0.8008)	Acc@1 84.619 (84.619)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 06:26:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.023)	Loss 1.0794 (0.9256)	Acc@1 77.148 (81.794)	Acc@5 94.507 (95.885)	Mem 16099MB
[2025-01-18 06:26:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:179] * Acc@1 81.666 Acc@5 95.917
[2025-01-18 06:26:32 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.7%
[2025-01-18 06:26:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:26:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:26:33 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.67%
[2025-01-18 06:26:36 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][0/312]	eta 0:15:48 lr 0.001408	time 3.0401 (3.0401)	model_time 0.6343 (0.6343)	loss 3.3722 (3.3722)	grad_norm 3.1108 (3.1108/0.0000)	mem 16099MB
[2025-01-18 06:26:41 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][10/312]	eta 0:03:30 lr 0.001408	time 0.4511 (0.6971)	model_time 0.4507 (0.4781)	loss 2.9780 (3.1555)	grad_norm 8.0494 (3.4482/2.2392)	mem 16099MB
[2025-01-18 06:26:45 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][20/312]	eta 0:02:50 lr 0.001407	time 0.4583 (0.5830)	model_time 0.4578 (0.4681)	loss 3.2715 (3.0888)	grad_norm 1.4084 (2.8385/1.8712)	mem 16099MB
[2025-01-18 06:26:50 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][30/312]	eta 0:02:34 lr 0.001406	time 0.4527 (0.5489)	model_time 0.4526 (0.4709)	loss 3.2483 (3.1965)	grad_norm 1.4240 (2.3745/1.6931)	mem 16099MB
[2025-01-18 06:26:55 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][40/312]	eta 0:02:23 lr 0.001406	time 0.4467 (0.5263)	model_time 0.4462 (0.4672)	loss 2.8925 (3.1445)	grad_norm 1.7830 (2.0933/1.5590)	mem 16099MB
[2025-01-18 06:27:00 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][50/312]	eta 0:02:15 lr 0.001405	time 0.4498 (0.5170)	model_time 0.4494 (0.4695)	loss 3.6503 (3.0861)	grad_norm 2.6241 (2.0397/1.4413)	mem 16099MB
[2025-01-18 06:27:04 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][60/312]	eta 0:02:07 lr 0.001404	time 0.4427 (0.5070)	model_time 0.4426 (0.4672)	loss 2.5217 (3.1105)	grad_norm 1.7311 (2.0027/1.3406)	mem 16099MB
[2025-01-18 06:27:09 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][70/312]	eta 0:02:01 lr 0.001404	time 0.4611 (0.5013)	model_time 0.4609 (0.4670)	loss 2.4810 (3.0758)	grad_norm 1.5066 (1.9361/1.2585)	mem 16099MB
[2025-01-18 06:27:14 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][80/312]	eta 0:01:55 lr 0.001403	time 0.5676 (0.4999)	model_time 0.5674 (0.4698)	loss 4.0048 (3.1205)	grad_norm 1.8566 (1.8692/1.1952)	mem 16099MB
[2025-01-18 06:27:18 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][90/312]	eta 0:01:50 lr 0.001402	time 0.5336 (0.4978)	model_time 0.5331 (0.4710)	loss 3.1846 (3.1470)	grad_norm 1.4940 (1.8962/1.2196)	mem 16099MB
[2025-01-18 06:27:23 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][100/312]	eta 0:01:44 lr 0.001402	time 0.4433 (0.4944)	model_time 0.4428 (0.4702)	loss 2.8326 (3.1182)	grad_norm 3.5124 (1.8854/1.1892)	mem 16099MB
[2025-01-18 06:27:28 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][110/312]	eta 0:01:39 lr 0.001401	time 0.4431 (0.4932)	model_time 0.4427 (0.4711)	loss 2.7413 (3.1210)	grad_norm 1.9786 (1.9317/1.2006)	mem 16099MB
[2025-01-18 06:27:33 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][120/312]	eta 0:01:34 lr 0.001401	time 0.4531 (0.4912)	model_time 0.4529 (0.4710)	loss 2.2803 (3.1253)	grad_norm 1.3201 (1.9334/1.1702)	mem 16099MB
[2025-01-18 06:27:37 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][130/312]	eta 0:01:29 lr 0.001400	time 0.5414 (0.4903)	model_time 0.5409 (0.4716)	loss 3.0749 (3.1167)	grad_norm 1.3225 (1.9528/1.1643)	mem 16099MB
[2025-01-18 06:27:42 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][140/312]	eta 0:01:23 lr 0.001399	time 0.4506 (0.4883)	model_time 0.4502 (0.4709)	loss 2.8206 (3.1232)	grad_norm 1.4237 (1.9651/1.1469)	mem 16099MB
[2025-01-18 06:27:47 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][150/312]	eta 0:01:18 lr 0.001399	time 0.4425 (0.4865)	model_time 0.4421 (0.4702)	loss 3.5113 (3.1255)	grad_norm 3.1371 (1.9665/1.1263)	mem 16099MB
[2025-01-18 06:27:51 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][160/312]	eta 0:01:13 lr 0.001398	time 0.4679 (0.4848)	model_time 0.4674 (0.4695)	loss 3.1575 (3.1559)	grad_norm 1.9185 (1.9426/1.1032)	mem 16099MB
[2025-01-18 06:27:56 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][170/312]	eta 0:01:08 lr 0.001397	time 0.4674 (0.4835)	model_time 0.4672 (0.4691)	loss 3.2848 (3.1599)	grad_norm 1.8505 (1.9626/1.1017)	mem 16099MB
[2025-01-18 06:28:01 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][180/312]	eta 0:01:03 lr 0.001397	time 0.4562 (0.4833)	model_time 0.4561 (0.4696)	loss 2.1846 (3.1579)	grad_norm 1.1899 (2.0131/1.1546)	mem 16099MB
[2025-01-18 06:28:05 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][190/312]	eta 0:00:58 lr 0.001396	time 0.4620 (0.4824)	model_time 0.4616 (0.4694)	loss 2.8597 (3.1460)	grad_norm 1.4993 (2.0478/1.1764)	mem 16099MB
[2025-01-18 06:28:10 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][200/312]	eta 0:00:53 lr 0.001396	time 0.4525 (0.4817)	model_time 0.4523 (0.4693)	loss 3.3876 (3.1537)	grad_norm 1.5587 (2.0454/1.1654)	mem 16099MB
[2025-01-18 06:28:15 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][210/312]	eta 0:00:49 lr 0.001395	time 0.4462 (0.4812)	model_time 0.4457 (0.4694)	loss 3.0528 (3.1545)	grad_norm 1.7348 (2.0245/1.1473)	mem 16099MB
[2025-01-18 06:28:19 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][220/312]	eta 0:00:44 lr 0.001394	time 0.4510 (0.4806)	model_time 0.4506 (0.4694)	loss 4.0051 (3.1675)	grad_norm 2.2332 (2.0160/1.1263)	mem 16099MB
[2025-01-18 06:28:24 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][230/312]	eta 0:00:39 lr 0.001394	time 0.4615 (0.4796)	model_time 0.4613 (0.4688)	loss 3.4753 (3.1702)	grad_norm 1.6123 (2.0252/1.1083)	mem 16099MB
[2025-01-18 06:28:29 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][240/312]	eta 0:00:34 lr 0.001393	time 0.4446 (0.4791)	model_time 0.4445 (0.4688)	loss 2.6439 (3.1722)	grad_norm 1.8534 (2.0318/1.0922)	mem 16099MB
[2025-01-18 06:28:33 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][250/312]	eta 0:00:29 lr 0.001392	time 0.4451 (0.4782)	model_time 0.4446 (0.4683)	loss 3.1063 (3.1710)	grad_norm 0.9761 (2.0050/1.0823)	mem 16099MB
[2025-01-18 06:28:38 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][260/312]	eta 0:00:24 lr 0.001392	time 0.4683 (0.4779)	model_time 0.4678 (0.4683)	loss 3.4149 (3.1732)	grad_norm 2.9865 (2.0358/1.0932)	mem 16099MB
[2025-01-18 06:28:42 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][270/312]	eta 0:00:20 lr 0.001391	time 0.4499 (0.4769)	model_time 0.4495 (0.4676)	loss 2.6529 (3.1664)	grad_norm 1.7026 (2.0400/1.0844)	mem 16099MB
[2025-01-18 06:28:47 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][280/312]	eta 0:00:15 lr 0.001390	time 0.5320 (0.4766)	model_time 0.5315 (0.4676)	loss 2.9196 (3.1611)	grad_norm 2.1335 (2.0276/1.0746)	mem 16099MB
[2025-01-18 06:28:52 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][290/312]	eta 0:00:10 lr 0.001390	time 0.4496 (0.4763)	model_time 0.4494 (0.4677)	loss 2.0140 (3.1624)	grad_norm 1.2379 (2.0420/1.0757)	mem 16099MB
[2025-01-18 06:28:56 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][300/312]	eta 0:00:05 lr 0.001389	time 0.4428 (0.4758)	model_time 0.4427 (0.4674)	loss 2.7648 (3.1542)	grad_norm 1.8429 (2.0439/1.0664)	mem 16099MB
[2025-01-18 06:29:01 internimage_t_1k_224] (main.py 510): INFO Train: [180/300][310/312]	eta 0:00:00 lr 0.001389	time 0.4383 (0.4747)	model_time 0.4382 (0.4666)	loss 2.8539 (3.1523)	grad_norm 2.2059 (2.0042/0.9540)	mem 16099MB
[2025-01-18 06:29:01 internimage_t_1k_224] (main.py 519): INFO EPOCH 180 training takes 0:02:28
[2025-01-18 06:29:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_180.pth saving......
[2025-01-18 06:29:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_180.pth saved !!!
[2025-01-18 06:29:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.506 (7.506)	Loss 0.8017 (0.8017)	Acc@1 83.472 (83.472)	Acc@5 96.533 (96.533)	Mem 16099MB
[2025-01-18 06:29:13 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.999)	Loss 1.1116 (0.9200)	Acc@1 75.415 (80.560)	Acc@5 93.555 (95.395)	Mem 16099MB
[2025-01-18 06:29:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:180] * Acc@1 80.484 Acc@5 95.417
[2025-01-18 06:29:14 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.5%
[2025-01-18 06:29:14 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.50%
[2025-01-18 06:29:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.173 (8.173)	Loss 0.8002 (0.8002)	Acc@1 84.668 (84.668)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 06:29:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.110)	Loss 1.0774 (0.9244)	Acc@1 77.173 (81.836)	Acc@5 94.580 (95.898)	Mem 16099MB
[2025-01-18 06:29:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:180] * Acc@1 81.700 Acc@5 95.931
[2025-01-18 06:29:26 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.7%
[2025-01-18 06:29:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:29:27 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:29:27 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.70%
[2025-01-18 06:29:30 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][0/312]	eta 0:14:16 lr 0.001388	time 2.7442 (2.7442)	model_time 0.4730 (0.4730)	loss 3.5282 (3.5282)	grad_norm 2.3515 (2.3515/0.0000)	mem 16099MB
[2025-01-18 06:29:35 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][10/312]	eta 0:03:23 lr 0.001388	time 0.4905 (0.6736)	model_time 0.4901 (0.4667)	loss 2.9530 (3.1282)	grad_norm 1.0474 (1.8303/0.6384)	mem 16099MB
[2025-01-18 06:29:39 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][20/312]	eta 0:02:47 lr 0.001387	time 0.4615 (0.5749)	model_time 0.4614 (0.4663)	loss 3.0862 (3.1658)	grad_norm 1.3209 (1.6898/0.4959)	mem 16099MB
[2025-01-18 06:29:44 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][30/312]	eta 0:02:33 lr 0.001387	time 0.4503 (0.5435)	model_time 0.4502 (0.4699)	loss 3.1631 (3.1387)	grad_norm 1.2025 (1.5968/0.4575)	mem 16099MB
[2025-01-18 06:29:49 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][40/312]	eta 0:02:22 lr 0.001386	time 0.4599 (0.5225)	model_time 0.4594 (0.4668)	loss 3.5465 (3.1550)	grad_norm 0.8426 (1.7201/0.8086)	mem 16099MB
[2025-01-18 06:29:53 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][50/312]	eta 0:02:13 lr 0.001385	time 0.4476 (0.5093)	model_time 0.4472 (0.4644)	loss 2.4790 (3.1418)	grad_norm 1.7376 (1.8117/0.8180)	mem 16099MB
[2025-01-18 06:29:58 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][60/312]	eta 0:02:06 lr 0.001385	time 0.4760 (0.5011)	model_time 0.4758 (0.4636)	loss 1.8294 (3.0987)	grad_norm 2.0291 (1.7876/0.7787)	mem 16099MB
[2025-01-18 06:30:03 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][70/312]	eta 0:01:59 lr 0.001384	time 0.4610 (0.4951)	model_time 0.4605 (0.4628)	loss 2.8235 (3.0949)	grad_norm 1.3711 (1.7720/0.7824)	mem 16099MB
[2025-01-18 06:30:07 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][80/312]	eta 0:01:54 lr 0.001383	time 0.4548 (0.4940)	model_time 0.4543 (0.4656)	loss 3.2823 (3.1121)	grad_norm 1.5299 (1.8768/0.8594)	mem 16099MB
[2025-01-18 06:30:12 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][90/312]	eta 0:01:49 lr 0.001383	time 0.4480 (0.4913)	model_time 0.4478 (0.4659)	loss 2.5232 (3.1104)	grad_norm 2.6946 (1.9572/0.9534)	mem 16099MB
[2025-01-18 06:30:17 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][100/312]	eta 0:01:43 lr 0.001382	time 0.4477 (0.4885)	model_time 0.4472 (0.4656)	loss 2.9060 (3.0801)	grad_norm 1.5275 (2.0789/1.1217)	mem 16099MB
[2025-01-18 06:30:21 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][110/312]	eta 0:01:38 lr 0.001382	time 0.4424 (0.4863)	model_time 0.4422 (0.4655)	loss 3.5263 (3.0798)	grad_norm 1.9550 (2.0426/1.0920)	mem 16099MB
[2025-01-18 06:30:26 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][120/312]	eta 0:01:33 lr 0.001381	time 0.4485 (0.4854)	model_time 0.4481 (0.4663)	loss 2.3268 (3.0784)	grad_norm 2.0131 (2.0488/1.0996)	mem 16099MB
[2025-01-18 06:30:31 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][130/312]	eta 0:01:28 lr 0.001380	time 0.4462 (0.4837)	model_time 0.4460 (0.4660)	loss 1.8512 (3.0846)	grad_norm 3.2641 (2.0852/1.1013)	mem 16099MB
[2025-01-18 06:30:35 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][140/312]	eta 0:01:22 lr 0.001380	time 0.4502 (0.4823)	model_time 0.4500 (0.4658)	loss 3.7221 (3.0862)	grad_norm 2.3750 (2.0740/1.0769)	mem 16099MB
[2025-01-18 06:30:40 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][150/312]	eta 0:01:17 lr 0.001379	time 0.4496 (0.4813)	model_time 0.4491 (0.4659)	loss 2.5923 (3.0954)	grad_norm 3.0963 (2.0635/1.0510)	mem 16099MB
[2025-01-18 06:30:45 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][160/312]	eta 0:01:13 lr 0.001378	time 0.4428 (0.4807)	model_time 0.4426 (0.4662)	loss 3.2377 (3.0904)	grad_norm 2.2269 (2.0634/1.0237)	mem 16099MB
[2025-01-18 06:30:49 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][170/312]	eta 0:01:08 lr 0.001378	time 0.4474 (0.4799)	model_time 0.4470 (0.4663)	loss 3.0012 (3.0867)	grad_norm 1.7671 (2.0254/1.0103)	mem 16099MB
[2025-01-18 06:30:54 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][180/312]	eta 0:01:03 lr 0.001377	time 0.4632 (0.4791)	model_time 0.4628 (0.4662)	loss 3.3441 (3.1010)	grad_norm 3.4199 (2.0577/1.0366)	mem 16099MB
[2025-01-18 06:30:59 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][190/312]	eta 0:00:58 lr 0.001377	time 0.4409 (0.4779)	model_time 0.4405 (0.4656)	loss 2.7578 (3.1007)	grad_norm 2.2187 (2.0641/1.0176)	mem 16099MB
[2025-01-18 06:31:04 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][200/312]	eta 0:00:53 lr 0.001376	time 0.5594 (0.4786)	model_time 0.5593 (0.4669)	loss 3.7538 (3.1024)	grad_norm 1.4508 (2.0426/1.0066)	mem 16099MB
[2025-01-18 06:31:08 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][210/312]	eta 0:00:48 lr 0.001375	time 0.4560 (0.4779)	model_time 0.4555 (0.4668)	loss 2.2704 (3.1157)	grad_norm 1.3391 (2.0083/0.9978)	mem 16099MB
[2025-01-18 06:31:13 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][220/312]	eta 0:00:43 lr 0.001375	time 0.4520 (0.4771)	model_time 0.4519 (0.4664)	loss 3.2543 (3.1156)	grad_norm 2.1991 (1.9932/0.9818)	mem 16099MB
[2025-01-18 06:31:17 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][230/312]	eta 0:00:39 lr 0.001374	time 0.4433 (0.4761)	model_time 0.4431 (0.4658)	loss 3.2216 (3.1139)	grad_norm 2.1615 (2.0078/0.9798)	mem 16099MB
[2025-01-18 06:31:22 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][240/312]	eta 0:00:34 lr 0.001373	time 0.4471 (0.4759)	model_time 0.4467 (0.4661)	loss 2.6037 (3.1117)	grad_norm 3.5559 (2.0209/0.9771)	mem 16099MB
[2025-01-18 06:31:27 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][250/312]	eta 0:00:29 lr 0.001373	time 0.4556 (0.4754)	model_time 0.4554 (0.4659)	loss 3.3039 (3.1122)	grad_norm 1.3105 (1.9992/0.9680)	mem 16099MB
[2025-01-18 06:31:31 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][260/312]	eta 0:00:24 lr 0.001372	time 0.4570 (0.4747)	model_time 0.4568 (0.4656)	loss 3.4532 (3.1129)	grad_norm 2.1894 (1.9952/0.9531)	mem 16099MB
[2025-01-18 06:31:36 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][270/312]	eta 0:00:19 lr 0.001371	time 0.4402 (0.4749)	model_time 0.4401 (0.4661)	loss 3.4053 (3.1094)	grad_norm 1.5422 (2.0169/0.9570)	mem 16099MB
[2025-01-18 06:31:41 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][280/312]	eta 0:00:15 lr 0.001371	time 0.4697 (0.4743)	model_time 0.4694 (0.4658)	loss 2.8330 (3.1064)	grad_norm 1.2530 (2.0057/0.9442)	mem 16099MB
[2025-01-18 06:31:45 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][290/312]	eta 0:00:10 lr 0.001370	time 0.4425 (0.4736)	model_time 0.4420 (0.4654)	loss 3.7959 (3.1000)	grad_norm 0.8096 (1.9840/0.9378)	mem 16099MB
[2025-01-18 06:31:50 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][300/312]	eta 0:00:05 lr 0.001370	time 0.4396 (0.4729)	model_time 0.4395 (0.4650)	loss 3.8792 (3.1043)	grad_norm 1.9882 (1.9831/0.9387)	mem 16099MB
[2025-01-18 06:31:54 internimage_t_1k_224] (main.py 510): INFO Train: [181/300][310/312]	eta 0:00:00 lr 0.001369	time 0.4385 (0.4719)	model_time 0.4384 (0.4642)	loss 3.3490 (3.1066)	grad_norm 3.7131 (2.0161/0.9630)	mem 16099MB
[2025-01-18 06:31:55 internimage_t_1k_224] (main.py 519): INFO EPOCH 181 training takes 0:02:27
[2025-01-18 06:31:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_181.pth saving......
[2025-01-18 06:31:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_181.pth saved !!!
[2025-01-18 06:32:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.285 (7.285)	Loss 0.7970 (0.7970)	Acc@1 83.228 (83.228)	Acc@5 96.680 (96.680)	Mem 16099MB
[2025-01-18 06:32:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.996)	Loss 1.0913 (0.9269)	Acc@1 76.538 (80.475)	Acc@5 93.774 (95.366)	Mem 16099MB
[2025-01-18 06:32:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:181] * Acc@1 80.386 Acc@5 95.393
[2025-01-18 06:32:07 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.4%
[2025-01-18 06:32:07 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.50%
[2025-01-18 06:32:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.205 (8.205)	Loss 0.8000 (0.8000)	Acc@1 84.668 (84.668)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 06:32:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.102)	Loss 1.0757 (0.9235)	Acc@1 77.148 (81.858)	Acc@5 94.604 (95.921)	Mem 16099MB
[2025-01-18 06:32:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:181] * Acc@1 81.722 Acc@5 95.951
[2025-01-18 06:32:19 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.7%
[2025-01-18 06:32:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:32:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:32:20 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.72%
[2025-01-18 06:32:23 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][0/312]	eta 0:13:13 lr 0.001369	time 2.5444 (2.5444)	model_time 0.4794 (0.4794)	loss 3.6717 (3.6717)	grad_norm 1.5020 (1.5020/0.0000)	mem 16099MB
[2025-01-18 06:32:28 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][10/312]	eta 0:03:19 lr 0.001368	time 0.4487 (0.6598)	model_time 0.4486 (0.4718)	loss 3.1375 (3.2595)	grad_norm 1.0185 (2.1575/1.4858)	mem 16099MB
[2025-01-18 06:32:32 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][20/312]	eta 0:02:46 lr 0.001368	time 0.5494 (0.5714)	model_time 0.5493 (0.4728)	loss 2.4250 (3.0791)	grad_norm 0.9884 (1.8081/1.1570)	mem 16099MB
[2025-01-18 06:32:37 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][30/312]	eta 0:02:32 lr 0.001367	time 0.4468 (0.5411)	model_time 0.4463 (0.4741)	loss 2.0372 (3.0401)	grad_norm 3.3810 (1.9749/1.1477)	mem 16099MB
[2025-01-18 06:32:42 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][40/312]	eta 0:02:21 lr 0.001366	time 0.4471 (0.5220)	model_time 0.4470 (0.4713)	loss 3.5982 (3.0999)	grad_norm 1.4091 (1.9240/1.0631)	mem 16099MB
[2025-01-18 06:32:46 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][50/312]	eta 0:02:13 lr 0.001366	time 0.4576 (0.5107)	model_time 0.4572 (0.4699)	loss 3.3751 (3.1222)	grad_norm 2.0225 (1.8991/0.9812)	mem 16099MB
[2025-01-18 06:32:51 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][60/312]	eta 0:02:07 lr 0.001365	time 0.4653 (0.5042)	model_time 0.4651 (0.4699)	loss 3.3997 (3.1634)	grad_norm 3.2429 (1.8854/0.9816)	mem 16099MB
[2025-01-18 06:32:56 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][70/312]	eta 0:02:01 lr 0.001364	time 0.5583 (0.5003)	model_time 0.5582 (0.4709)	loss 3.0781 (3.1529)	grad_norm 1.3790 (1.9950/1.0415)	mem 16099MB
[2025-01-18 06:33:01 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][80/312]	eta 0:01:55 lr 0.001364	time 0.4524 (0.4961)	model_time 0.4520 (0.4703)	loss 3.5094 (3.1536)	grad_norm 1.3884 (2.1340/1.0901)	mem 16099MB
[2025-01-18 06:33:05 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][90/312]	eta 0:01:49 lr 0.001363	time 0.4528 (0.4926)	model_time 0.4523 (0.4696)	loss 2.5707 (3.1199)	grad_norm 1.7810 (2.0816/1.0475)	mem 16099MB
[2025-01-18 06:33:10 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][100/312]	eta 0:01:44 lr 0.001363	time 0.4618 (0.4911)	model_time 0.4617 (0.4703)	loss 3.7243 (3.1243)	grad_norm 2.0534 (2.0382/1.0148)	mem 16099MB
[2025-01-18 06:33:15 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][110/312]	eta 0:01:38 lr 0.001362	time 0.4429 (0.4888)	model_time 0.4427 (0.4698)	loss 2.8676 (3.0978)	grad_norm 2.3612 (2.0369/0.9875)	mem 16099MB
[2025-01-18 06:33:20 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][120/312]	eta 0:01:33 lr 0.001361	time 0.5602 (0.4883)	model_time 0.5598 (0.4708)	loss 3.5879 (3.1203)	grad_norm 1.1432 (2.0100/0.9584)	mem 16099MB
[2025-01-18 06:33:24 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][130/312]	eta 0:01:28 lr 0.001361	time 0.4622 (0.4865)	model_time 0.4620 (0.4704)	loss 2.5563 (3.1160)	grad_norm 3.1416 (2.0277/0.9765)	mem 16099MB
[2025-01-18 06:33:29 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][140/312]	eta 0:01:23 lr 0.001360	time 0.4499 (0.4859)	model_time 0.4498 (0.4709)	loss 3.4288 (3.1143)	grad_norm 4.4646 (2.1097/1.0514)	mem 16099MB
[2025-01-18 06:33:34 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][150/312]	eta 0:01:18 lr 0.001359	time 0.4596 (0.4847)	model_time 0.4591 (0.4707)	loss 3.2641 (3.0974)	grad_norm 3.9625 (2.1873/1.1488)	mem 16099MB
[2025-01-18 06:33:38 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][160/312]	eta 0:01:13 lr 0.001359	time 0.4567 (0.4829)	model_time 0.4565 (0.4696)	loss 3.0299 (3.0951)	grad_norm 1.6610 (2.1676/1.1244)	mem 16099MB
[2025-01-18 06:33:43 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][170/312]	eta 0:01:08 lr 0.001358	time 0.5406 (0.4819)	model_time 0.5400 (0.4694)	loss 3.2079 (3.0838)	grad_norm 2.2751 (2.1307/1.1064)	mem 16099MB
[2025-01-18 06:33:47 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][180/312]	eta 0:01:03 lr 0.001358	time 0.4536 (0.4810)	model_time 0.4531 (0.4692)	loss 3.9359 (3.0858)	grad_norm 1.4810 (2.1046/1.0914)	mem 16099MB
[2025-01-18 06:33:52 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][190/312]	eta 0:00:58 lr 0.001357	time 0.4430 (0.4796)	model_time 0.4425 (0.4684)	loss 3.3741 (3.0845)	grad_norm 1.0298 (2.0992/1.0748)	mem 16099MB
[2025-01-18 06:33:57 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][200/312]	eta 0:00:53 lr 0.001356	time 0.4655 (0.4788)	model_time 0.4651 (0.4681)	loss 3.3190 (3.0944)	grad_norm 1.5995 (2.1032/1.0685)	mem 16099MB
[2025-01-18 06:34:01 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][210/312]	eta 0:00:48 lr 0.001356	time 0.4576 (0.4784)	model_time 0.4572 (0.4682)	loss 3.3098 (3.0932)	grad_norm 0.7093 (2.0892/1.0539)	mem 16099MB
[2025-01-18 06:34:06 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][220/312]	eta 0:00:43 lr 0.001355	time 0.4412 (0.4780)	model_time 0.4407 (0.4683)	loss 2.0905 (3.0842)	grad_norm 1.8733 (2.0750/1.0359)	mem 16099MB
[2025-01-18 06:34:11 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][230/312]	eta 0:00:39 lr 0.001354	time 0.4503 (0.4770)	model_time 0.4501 (0.4677)	loss 3.3095 (3.0924)	grad_norm 2.1705 (2.0654/1.0201)	mem 16099MB
[2025-01-18 06:34:15 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][240/312]	eta 0:00:34 lr 0.001354	time 0.4520 (0.4763)	model_time 0.4518 (0.4674)	loss 2.1111 (3.0807)	grad_norm 1.3867 (2.0537/1.0044)	mem 16099MB
[2025-01-18 06:34:20 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][250/312]	eta 0:00:29 lr 0.001353	time 0.5077 (0.4758)	model_time 0.5075 (0.4672)	loss 2.5624 (3.0747)	grad_norm 1.4766 (2.0313/0.9925)	mem 16099MB
[2025-01-18 06:34:25 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][260/312]	eta 0:00:24 lr 0.001353	time 0.4479 (0.4762)	model_time 0.4474 (0.4679)	loss 3.2580 (3.0713)	grad_norm 2.2022 (2.0256/0.9766)	mem 16099MB
[2025-01-18 06:34:29 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][270/312]	eta 0:00:19 lr 0.001352	time 0.4416 (0.4758)	model_time 0.4411 (0.4678)	loss 3.3554 (3.0820)	grad_norm 1.2715 (2.0415/0.9861)	mem 16099MB
[2025-01-18 06:34:34 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][280/312]	eta 0:00:15 lr 0.001351	time 0.4634 (0.4760)	model_time 0.4630 (0.4682)	loss 3.2360 (3.0917)	grad_norm 2.2496 (2.0749/1.0073)	mem 16099MB
[2025-01-18 06:34:39 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][290/312]	eta 0:00:10 lr 0.001351	time 0.4550 (0.4759)	model_time 0.4546 (0.4684)	loss 2.1310 (3.0852)	grad_norm 1.7345 (2.0820/1.0050)	mem 16099MB
[2025-01-18 06:34:43 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][300/312]	eta 0:00:05 lr 0.001350	time 0.4390 (0.4751)	model_time 0.4389 (0.4678)	loss 2.7209 (3.0831)	grad_norm 2.1498 (2.0850/0.9922)	mem 16099MB
[2025-01-18 06:34:48 internimage_t_1k_224] (main.py 510): INFO Train: [182/300][310/312]	eta 0:00:00 lr 0.001349	time 0.4396 (0.4748)	model_time 0.4395 (0.4678)	loss 3.3974 (3.0854)	grad_norm 5.0366 (2.0888/0.9724)	mem 16099MB
[2025-01-18 06:34:49 internimage_t_1k_224] (main.py 519): INFO EPOCH 182 training takes 0:02:28
[2025-01-18 06:34:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_182.pth saving......
[2025-01-18 06:34:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_182.pth saved !!!
[2025-01-18 06:34:57 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.251 (7.251)	Loss 0.7970 (0.7970)	Acc@1 83.057 (83.057)	Acc@5 96.875 (96.875)	Mem 16099MB
[2025-01-18 06:35:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.999)	Loss 1.0624 (0.9260)	Acc@1 76.294 (80.435)	Acc@5 93.921 (95.388)	Mem 16099MB
[2025-01-18 06:35:01 internimage_t_1k_224] (main.py 575): INFO [Epoch:182] * Acc@1 80.266 Acc@5 95.391
[2025-01-18 06:35:01 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.3%
[2025-01-18 06:35:01 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.50%
[2025-01-18 06:35:09 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.251 (8.251)	Loss 0.7995 (0.7995)	Acc@1 84.717 (84.717)	Acc@5 97.412 (97.412)	Mem 16099MB
[2025-01-18 06:35:13 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.111)	Loss 1.0741 (0.9223)	Acc@1 77.246 (81.903)	Acc@5 94.629 (95.936)	Mem 16099MB
[2025-01-18 06:35:13 internimage_t_1k_224] (main.py 575): INFO [Epoch:182] * Acc@1 81.772 Acc@5 95.971
[2025-01-18 06:35:13 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.8%
[2025-01-18 06:35:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:35:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:35:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.77%
[2025-01-18 06:35:17 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][0/312]	eta 0:13:08 lr 0.001349	time 2.5271 (2.5271)	model_time 0.4613 (0.4613)	loss 2.6998 (2.6998)	grad_norm 3.7815 (3.7815/0.0000)	mem 16099MB
[2025-01-18 06:35:22 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][10/312]	eta 0:03:15 lr 0.001349	time 0.4532 (0.6462)	model_time 0.4531 (0.4582)	loss 2.9927 (3.0866)	grad_norm 1.0077 (1.8291/0.6866)	mem 16099MB
[2025-01-18 06:35:27 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][20/312]	eta 0:02:44 lr 0.001348	time 0.4540 (0.5644)	model_time 0.4536 (0.4657)	loss 2.3852 (3.0071)	grad_norm 1.8415 (1.9459/0.7454)	mem 16099MB
[2025-01-18 06:35:31 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][30/312]	eta 0:02:29 lr 0.001347	time 0.4798 (0.5314)	model_time 0.4796 (0.4644)	loss 3.3784 (3.1579)	grad_norm 1.2490 (1.8461/0.6456)	mem 16099MB
[2025-01-18 06:35:36 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][40/312]	eta 0:02:20 lr 0.001347	time 0.4565 (0.5154)	model_time 0.4550 (0.4646)	loss 2.0224 (3.0475)	grad_norm 0.9112 (1.8888/0.6333)	mem 16099MB
[2025-01-18 06:35:40 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][50/312]	eta 0:02:12 lr 0.001346	time 0.4746 (0.5046)	model_time 0.4741 (0.4637)	loss 3.4708 (3.1029)	grad_norm 1.5489 (1.8963/0.6719)	mem 16099MB
[2025-01-18 06:35:45 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][60/312]	eta 0:02:05 lr 0.001346	time 0.4428 (0.4988)	model_time 0.4426 (0.4646)	loss 3.2325 (3.1148)	grad_norm 3.1940 (1.9411/0.7554)	mem 16099MB
[2025-01-18 06:35:50 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][70/312]	eta 0:01:59 lr 0.001345	time 0.4529 (0.4952)	model_time 0.4527 (0.4657)	loss 3.4316 (3.1135)	grad_norm 5.1395 (2.0409/0.8540)	mem 16099MB
[2025-01-18 06:35:55 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][80/312]	eta 0:01:54 lr 0.001344	time 0.4625 (0.4917)	model_time 0.4623 (0.4659)	loss 2.8150 (3.0900)	grad_norm 2.3870 (2.0606/0.8443)	mem 16099MB
[2025-01-18 06:35:59 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][90/312]	eta 0:01:48 lr 0.001344	time 0.4560 (0.4885)	model_time 0.4558 (0.4655)	loss 3.3845 (3.0631)	grad_norm 1.7591 (2.0111/0.8153)	mem 16099MB
[2025-01-18 06:36:04 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][100/312]	eta 0:01:42 lr 0.001343	time 0.4510 (0.4852)	model_time 0.4509 (0.4644)	loss 3.2178 (3.0552)	grad_norm 1.7635 (2.0546/0.8755)	mem 16099MB
[2025-01-18 06:36:09 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][110/312]	eta 0:01:38 lr 0.001342	time 0.5769 (0.4853)	model_time 0.5765 (0.4663)	loss 2.2908 (3.0723)	grad_norm 1.0893 (2.1387/0.9901)	mem 16099MB
[2025-01-18 06:36:13 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][120/312]	eta 0:01:32 lr 0.001342	time 0.4464 (0.4840)	model_time 0.4462 (0.4666)	loss 3.1192 (3.0649)	grad_norm 1.8516 (2.1707/1.0026)	mem 16099MB
[2025-01-18 06:36:18 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][130/312]	eta 0:01:27 lr 0.001341	time 0.4556 (0.4832)	model_time 0.4551 (0.4671)	loss 2.0692 (3.0489)	grad_norm 1.4464 (2.1136/0.9859)	mem 16099MB
[2025-01-18 06:36:23 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][140/312]	eta 0:01:22 lr 0.001341	time 0.4554 (0.4820)	model_time 0.4549 (0.4670)	loss 2.4614 (3.0390)	grad_norm 1.3377 (2.0705/0.9728)	mem 16099MB
[2025-01-18 06:36:27 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][150/312]	eta 0:01:17 lr 0.001340	time 0.4548 (0.4813)	model_time 0.4543 (0.4672)	loss 2.7797 (3.0234)	grad_norm 1.2616 (2.0486/0.9518)	mem 16099MB
[2025-01-18 06:36:32 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][160/312]	eta 0:01:12 lr 0.001339	time 0.4494 (0.4802)	model_time 0.4490 (0.4670)	loss 3.7961 (3.0332)	grad_norm 2.5425 (2.0821/0.9440)	mem 16099MB
[2025-01-18 06:36:37 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][170/312]	eta 0:01:08 lr 0.001339	time 0.4477 (0.4793)	model_time 0.4475 (0.4669)	loss 2.7168 (3.0387)	grad_norm 1.1843 (2.0716/0.9402)	mem 16099MB
[2025-01-18 06:36:41 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][180/312]	eta 0:01:03 lr 0.001338	time 0.5412 (0.4790)	model_time 0.5410 (0.4672)	loss 3.2117 (3.0445)	grad_norm 3.2837 (2.0550/0.9267)	mem 16099MB
[2025-01-18 06:36:46 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][190/312]	eta 0:00:58 lr 0.001337	time 0.4659 (0.4783)	model_time 0.4658 (0.4671)	loss 3.6892 (3.0501)	grad_norm 1.6735 (2.0526/0.9232)	mem 16099MB
[2025-01-18 06:36:51 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][200/312]	eta 0:00:53 lr 0.001337	time 0.4479 (0.4771)	model_time 0.4474 (0.4664)	loss 2.1134 (3.0365)	grad_norm 2.1225 (2.0776/0.9431)	mem 16099MB
[2025-01-18 06:36:55 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][210/312]	eta 0:00:48 lr 0.001336	time 0.5591 (0.4773)	model_time 0.5590 (0.4671)	loss 3.1342 (3.0471)	grad_norm 1.4301 (2.0686/0.9443)	mem 16099MB
[2025-01-18 06:37:00 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][220/312]	eta 0:00:43 lr 0.001336	time 0.4961 (0.4772)	model_time 0.4960 (0.4674)	loss 2.1522 (3.0549)	grad_norm 2.0794 (2.0876/0.9494)	mem 16099MB
[2025-01-18 06:37:05 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][230/312]	eta 0:00:39 lr 0.001335	time 0.4031 (0.4764)	model_time 0.4030 (0.4670)	loss 3.0403 (3.0728)	grad_norm inf (2.0905/0.9390)	mem 16099MB
[2025-01-18 06:37:09 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][240/312]	eta 0:00:34 lr 0.001334	time 0.5750 (0.4761)	model_time 0.5748 (0.4671)	loss 3.5812 (3.0681)	grad_norm 2.6446 (2.1076/0.9441)	mem 16099MB
[2025-01-18 06:37:14 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][250/312]	eta 0:00:29 lr 0.001334	time 0.4477 (0.4757)	model_time 0.4476 (0.4671)	loss 2.4231 (3.0665)	grad_norm 1.4947 (2.1014/0.9415)	mem 16099MB
[2025-01-18 06:37:19 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][260/312]	eta 0:00:24 lr 0.001333	time 0.4526 (0.4754)	model_time 0.4522 (0.4671)	loss 2.0904 (3.0614)	grad_norm 2.4724 (2.0896/0.9279)	mem 16099MB
[2025-01-18 06:37:23 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][270/312]	eta 0:00:19 lr 0.001332	time 0.4583 (0.4748)	model_time 0.4581 (0.4668)	loss 2.6838 (3.0589)	grad_norm 1.2944 (2.0893/0.9338)	mem 16099MB
[2025-01-18 06:37:28 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][280/312]	eta 0:00:15 lr 0.001332	time 0.4454 (0.4747)	model_time 0.4450 (0.4670)	loss 2.5257 (3.0556)	grad_norm 2.2464 (2.0871/0.9262)	mem 16099MB
[2025-01-18 06:37:33 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][290/312]	eta 0:00:10 lr 0.001331	time 0.4501 (0.4753)	model_time 0.4499 (0.4679)	loss 3.4459 (3.0656)	grad_norm 1.9476 (2.0906/0.9212)	mem 16099MB
[2025-01-18 06:37:38 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][300/312]	eta 0:00:05 lr 0.001331	time 0.4392 (0.4746)	model_time 0.4391 (0.4673)	loss 2.1348 (3.0568)	grad_norm 0.7655 (2.0782/0.9158)	mem 16099MB
[2025-01-18 06:37:42 internimage_t_1k_224] (main.py 510): INFO Train: [183/300][310/312]	eta 0:00:00 lr 0.001330	time 0.5225 (0.4743)	model_time 0.5225 (0.4673)	loss 3.2056 (3.0559)	grad_norm 1.2974 (2.0780/0.9156)	mem 16099MB
[2025-01-18 06:37:43 internimage_t_1k_224] (main.py 519): INFO EPOCH 183 training takes 0:02:27
[2025-01-18 06:37:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_183.pth saving......
[2025-01-18 06:37:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_183.pth saved !!!
[2025-01-18 06:37:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.053 (7.053)	Loss 0.7727 (0.7727)	Acc@1 83.716 (83.716)	Acc@5 96.973 (96.973)	Mem 16099MB
[2025-01-18 06:37:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.964)	Loss 1.1001 (0.9178)	Acc@1 75.146 (80.799)	Acc@5 94.189 (95.641)	Mem 16099MB
[2025-01-18 06:37:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:183] * Acc@1 80.652 Acc@5 95.649
[2025-01-18 06:37:55 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.7%
[2025-01-18 06:37:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 06:37:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 06:37:56 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.65%
[2025-01-18 06:38:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.203 (7.203)	Loss 0.7988 (0.7988)	Acc@1 84.741 (84.741)	Acc@5 97.412 (97.412)	Mem 16099MB
[2025-01-18 06:38:06 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.957)	Loss 1.0726 (0.9213)	Acc@1 77.368 (81.967)	Acc@5 94.629 (95.945)	Mem 16099MB
[2025-01-18 06:38:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:183] * Acc@1 81.824 Acc@5 95.979
[2025-01-18 06:38:06 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.8%
[2025-01-18 06:38:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:38:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:38:08 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.82%
[2025-01-18 06:38:11 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][0/312]	eta 0:15:58 lr 0.001330	time 3.0732 (3.0732)	model_time 0.4690 (0.4690)	loss 3.3641 (3.3641)	grad_norm 1.2208 (1.2208/0.0000)	mem 16099MB
[2025-01-18 06:38:16 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][10/312]	eta 0:03:32 lr 0.001329	time 0.4458 (0.7049)	model_time 0.4457 (0.4679)	loss 3.0819 (3.2226)	grad_norm 1.4245 (1.7021/0.4992)	mem 16099MB
[2025-01-18 06:38:20 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][20/312]	eta 0:02:52 lr 0.001329	time 0.4461 (0.5914)	model_time 0.4459 (0.4671)	loss 3.2187 (3.0574)	grad_norm 0.8284 (1.7074/0.4921)	mem 16099MB
[2025-01-18 06:38:25 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][30/312]	eta 0:02:35 lr 0.001328	time 0.4517 (0.5511)	model_time 0.4516 (0.4668)	loss 2.7746 (3.0617)	grad_norm 1.3231 (1.6724/0.4813)	mem 16099MB
[2025-01-18 06:38:30 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][40/312]	eta 0:02:24 lr 0.001327	time 0.4425 (0.5327)	model_time 0.4424 (0.4688)	loss 3.6059 (3.0688)	grad_norm 5.5441 (1.7780/0.7953)	mem 16099MB
[2025-01-18 06:38:34 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][50/312]	eta 0:02:15 lr 0.001327	time 0.4584 (0.5170)	model_time 0.4580 (0.4656)	loss 2.8638 (3.0679)	grad_norm 2.8449 (1.9996/1.2040)	mem 16099MB
[2025-01-18 06:38:39 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][60/312]	eta 0:02:07 lr 0.001326	time 0.4495 (0.5075)	model_time 0.4493 (0.4644)	loss 2.3089 (3.0159)	grad_norm 1.6181 (2.1074/1.1933)	mem 16099MB
[2025-01-18 06:38:44 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][70/312]	eta 0:02:01 lr 0.001325	time 0.4482 (0.5021)	model_time 0.4478 (0.4650)	loss 3.7546 (3.0172)	grad_norm 2.1747 (2.0514/1.1504)	mem 16099MB
[2025-01-18 06:38:48 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][80/312]	eta 0:01:55 lr 0.001325	time 0.4596 (0.4989)	model_time 0.4594 (0.4664)	loss 2.1034 (3.0060)	grad_norm 2.5749 (2.0378/1.1068)	mem 16099MB
[2025-01-18 06:38:53 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][90/312]	eta 0:01:49 lr 0.001324	time 0.4423 (0.4953)	model_time 0.4418 (0.4663)	loss 2.8797 (3.0047)	grad_norm 2.7807 (2.0210/1.0643)	mem 16099MB
[2025-01-18 06:38:58 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][100/312]	eta 0:01:44 lr 0.001324	time 0.4418 (0.4922)	model_time 0.4412 (0.4660)	loss 3.3405 (3.0030)	grad_norm 1.4781 (1.9978/1.0195)	mem 16099MB
[2025-01-18 06:39:02 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][110/312]	eta 0:01:38 lr 0.001323	time 0.4541 (0.4892)	model_time 0.4539 (0.4654)	loss 2.7453 (3.0254)	grad_norm 1.7270 (1.9706/0.9926)	mem 16099MB
[2025-01-18 06:39:07 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][120/312]	eta 0:01:33 lr 0.001322	time 0.4371 (0.4872)	model_time 0.4366 (0.4653)	loss 3.2442 (3.0207)	grad_norm 2.0861 (1.9726/0.9664)	mem 16099MB
[2025-01-18 06:39:12 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][130/312]	eta 0:01:28 lr 0.001322	time 0.4552 (0.4877)	model_time 0.4551 (0.4675)	loss 3.3354 (3.0312)	grad_norm 1.3142 (2.0120/0.9676)	mem 16099MB
[2025-01-18 06:39:16 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][140/312]	eta 0:01:23 lr 0.001321	time 0.4586 (0.4854)	model_time 0.4582 (0.4665)	loss 1.9737 (3.0208)	grad_norm 2.5365 (2.0198/0.9519)	mem 16099MB
[2025-01-18 06:39:21 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][150/312]	eta 0:01:18 lr 0.001320	time 0.4647 (0.4859)	model_time 0.4645 (0.4682)	loss 2.2098 (3.0239)	grad_norm 2.0901 (2.0091/0.9286)	mem 16099MB
[2025-01-18 06:39:26 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][160/312]	eta 0:01:13 lr 0.001320	time 0.4884 (0.4840)	model_time 0.4879 (0.4675)	loss 3.2281 (3.0288)	grad_norm 2.1754 (2.0086/0.9539)	mem 16099MB
[2025-01-18 06:39:30 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][170/312]	eta 0:01:08 lr 0.001319	time 0.4538 (0.4830)	model_time 0.4536 (0.4674)	loss 3.3564 (3.0334)	grad_norm 0.8223 (2.0127/0.9437)	mem 16099MB
[2025-01-18 06:39:35 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][180/312]	eta 0:01:03 lr 0.001319	time 0.4581 (0.4827)	model_time 0.4577 (0.4680)	loss 3.2825 (3.0548)	grad_norm 3.1577 (2.0150/0.9388)	mem 16099MB
[2025-01-18 06:39:40 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][190/312]	eta 0:00:58 lr 0.001318	time 0.4659 (0.4821)	model_time 0.4658 (0.4681)	loss 3.7887 (3.0597)	grad_norm 1.0639 (2.0268/0.9366)	mem 16099MB
[2025-01-18 06:39:45 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][200/312]	eta 0:00:53 lr 0.001317	time 0.4546 (0.4811)	model_time 0.4541 (0.4678)	loss 2.9123 (3.0703)	grad_norm 2.0881 (2.0450/0.9335)	mem 16099MB
[2025-01-18 06:39:49 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][210/312]	eta 0:00:49 lr 0.001317	time 0.4413 (0.4806)	model_time 0.4411 (0.4678)	loss 3.6729 (3.0817)	grad_norm 2.8265 (2.0531/0.9342)	mem 16099MB
[2025-01-18 06:39:54 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][220/312]	eta 0:00:44 lr 0.001316	time 0.4688 (0.4794)	model_time 0.4686 (0.4672)	loss 3.3320 (3.0818)	grad_norm 3.1505 (2.0639/0.9252)	mem 16099MB
[2025-01-18 06:39:58 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][230/312]	eta 0:00:39 lr 0.001316	time 0.4424 (0.4785)	model_time 0.4420 (0.4668)	loss 2.5532 (3.0924)	grad_norm 1.7677 (2.0755/0.9284)	mem 16099MB
[2025-01-18 06:40:03 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][240/312]	eta 0:00:34 lr 0.001315	time 0.4430 (0.4782)	model_time 0.4429 (0.4670)	loss 2.3576 (3.0904)	grad_norm 1.9700 (2.0634/0.9201)	mem 16099MB
[2025-01-18 06:40:08 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][250/312]	eta 0:00:29 lr 0.001314	time 0.4536 (0.4778)	model_time 0.4531 (0.4670)	loss 3.3976 (3.0877)	grad_norm 1.7102 (2.0604/0.9149)	mem 16099MB
[2025-01-18 06:40:13 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][260/312]	eta 0:00:24 lr 0.001314	time 0.4473 (0.4780)	model_time 0.4469 (0.4676)	loss 3.4670 (3.0898)	grad_norm 3.4175 (2.0708/0.9105)	mem 16099MB
[2025-01-18 06:40:17 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][270/312]	eta 0:00:20 lr 0.001313	time 0.4764 (0.4779)	model_time 0.4759 (0.4679)	loss 3.6778 (3.0914)	grad_norm 1.5674 (2.0650/0.9030)	mem 16099MB
[2025-01-18 06:40:22 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][280/312]	eta 0:00:15 lr 0.001312	time 0.4556 (0.4773)	model_time 0.4552 (0.4676)	loss 3.3848 (3.0988)	grad_norm 3.7514 (2.0704/0.9000)	mem 16099MB
[2025-01-18 06:40:27 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][290/312]	eta 0:00:10 lr 0.001312	time 0.4420 (0.4770)	model_time 0.4418 (0.4677)	loss 3.5444 (3.1044)	grad_norm 3.7278 (2.0974/0.9182)	mem 16099MB
[2025-01-18 06:40:31 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][300/312]	eta 0:00:05 lr 0.001311	time 0.4383 (0.4768)	model_time 0.4382 (0.4678)	loss 2.9018 (3.0969)	grad_norm 1.6367 (2.0858/0.9128)	mem 16099MB
[2025-01-18 06:40:36 internimage_t_1k_224] (main.py 510): INFO Train: [184/300][310/312]	eta 0:00:00 lr 0.001311	time 0.4431 (0.4757)	model_time 0.4430 (0.4669)	loss 3.1943 (3.0900)	grad_norm 1.9168 (2.0843/0.9194)	mem 16099MB
[2025-01-18 06:40:36 internimage_t_1k_224] (main.py 519): INFO EPOCH 184 training takes 0:02:28
[2025-01-18 06:40:36 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_184.pth saving......
[2025-01-18 06:40:37 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_184.pth saved !!!
[2025-01-18 06:40:45 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.369 (7.369)	Loss 0.7628 (0.7628)	Acc@1 83.643 (83.643)	Acc@5 96.924 (96.924)	Mem 16099MB
[2025-01-18 06:40:48 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.991)	Loss 1.0731 (0.9008)	Acc@1 76.221 (80.700)	Acc@5 94.067 (95.492)	Mem 16099MB
[2025-01-18 06:40:48 internimage_t_1k_224] (main.py 575): INFO [Epoch:184] * Acc@1 80.578 Acc@5 95.513
[2025-01-18 06:40:48 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.6%
[2025-01-18 06:40:48 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.65%
[2025-01-18 06:40:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.012 (8.012)	Loss 0.7982 (0.7982)	Acc@1 84.766 (84.766)	Acc@5 97.437 (97.437)	Mem 16099MB
[2025-01-18 06:41:00 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.086)	Loss 1.0711 (0.9202)	Acc@1 77.466 (82.000)	Acc@5 94.629 (95.958)	Mem 16099MB
[2025-01-18 06:41:01 internimage_t_1k_224] (main.py 575): INFO [Epoch:184] * Acc@1 81.862 Acc@5 95.993
[2025-01-18 06:41:01 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.9%
[2025-01-18 06:41:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:41:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:41:02 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.86%
[2025-01-18 06:41:05 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][0/312]	eta 0:13:58 lr 0.001310	time 2.6891 (2.6891)	model_time 0.4661 (0.4661)	loss 2.4408 (2.4408)	grad_norm 3.0880 (3.0880/0.0000)	mem 16099MB
[2025-01-18 06:41:10 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][10/312]	eta 0:03:27 lr 0.001310	time 0.4494 (0.6859)	model_time 0.4492 (0.4834)	loss 3.0911 (3.1214)	grad_norm 2.4691 (1.8022/0.5866)	mem 16099MB
[2025-01-18 06:41:14 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][20/312]	eta 0:02:48 lr 0.001309	time 0.4620 (0.5764)	model_time 0.4618 (0.4702)	loss 3.3455 (3.0081)	grad_norm 2.5763 (2.0175/0.7097)	mem 16099MB
[2025-01-18 06:41:19 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][30/312]	eta 0:02:33 lr 0.001309	time 0.4481 (0.5440)	model_time 0.4479 (0.4720)	loss 3.4483 (3.0896)	grad_norm 0.8610 (2.0207/0.8298)	mem 16099MB
[2025-01-18 06:41:23 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][40/312]	eta 0:02:21 lr 0.001308	time 0.4525 (0.5217)	model_time 0.4523 (0.4672)	loss 3.0904 (3.0669)	grad_norm 5.1295 (2.3517/1.2586)	mem 16099MB
[2025-01-18 06:41:28 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][50/312]	eta 0:02:13 lr 0.001307	time 0.4514 (0.5101)	model_time 0.4512 (0.4662)	loss 2.6813 (3.0996)	grad_norm 2.1929 (2.5072/1.2431)	mem 16099MB
[2025-01-18 06:41:33 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][60/312]	eta 0:02:06 lr 0.001307	time 0.4750 (0.5019)	model_time 0.4745 (0.4651)	loss 2.0521 (3.0900)	grad_norm 2.1832 (2.4263/1.1793)	mem 16099MB
[2025-01-18 06:41:37 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][70/312]	eta 0:02:00 lr 0.001306	time 0.4733 (0.4975)	model_time 0.4732 (0.4659)	loss 3.3368 (3.1053)	grad_norm 2.1384 (2.3812/1.1638)	mem 16099MB
[2025-01-18 06:41:42 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][80/312]	eta 0:01:54 lr 0.001305	time 0.5446 (0.4935)	model_time 0.5441 (0.4657)	loss 3.3408 (3.1230)	grad_norm 2.6598 (2.3155/1.1399)	mem 16099MB
[2025-01-18 06:41:47 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][90/312]	eta 0:01:48 lr 0.001305	time 0.4521 (0.4898)	model_time 0.4519 (0.4651)	loss 3.0641 (3.0988)	grad_norm 1.8338 (2.2863/1.1154)	mem 16099MB
[2025-01-18 06:41:51 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][100/312]	eta 0:01:43 lr 0.001304	time 0.4516 (0.4899)	model_time 0.4514 (0.4676)	loss 3.5911 (3.0871)	grad_norm 2.3554 (2.2880/1.1055)	mem 16099MB
[2025-01-18 06:41:56 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][110/312]	eta 0:01:38 lr 0.001304	time 0.4811 (0.4873)	model_time 0.4806 (0.4670)	loss 3.3833 (3.0703)	grad_norm 3.2397 (2.4546/1.3638)	mem 16099MB
[2025-01-18 06:42:01 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][120/312]	eta 0:01:33 lr 0.001303	time 0.4503 (0.4885)	model_time 0.4501 (0.4698)	loss 3.4276 (3.0658)	grad_norm 1.4808 (2.4070/1.3288)	mem 16099MB
[2025-01-18 06:42:06 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][130/312]	eta 0:01:29 lr 0.001302	time 0.5564 (0.4900)	model_time 0.5563 (0.4727)	loss 3.3572 (3.0784)	grad_norm 1.0682 (2.3857/1.3062)	mem 16099MB
[2025-01-18 06:42:11 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][140/312]	eta 0:01:24 lr 0.001302	time 0.4497 (0.4886)	model_time 0.4495 (0.4725)	loss 3.1137 (3.0634)	grad_norm 1.0147 (2.3324/1.2814)	mem 16099MB
[2025-01-18 06:42:15 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][150/312]	eta 0:01:18 lr 0.001301	time 0.4452 (0.4867)	model_time 0.4450 (0.4716)	loss 3.4603 (3.0447)	grad_norm 2.1374 (2.3212/1.2613)	mem 16099MB
[2025-01-18 06:42:20 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][160/312]	eta 0:01:14 lr 0.001301	time 0.4547 (0.4869)	model_time 0.4543 (0.4728)	loss 3.0954 (3.0240)	grad_norm 1.8552 (2.2823/1.2351)	mem 16099MB
[2025-01-18 06:42:25 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][170/312]	eta 0:01:09 lr 0.001300	time 0.4579 (0.4861)	model_time 0.4577 (0.4728)	loss 2.6048 (3.0335)	grad_norm 1.2204 (2.2410/1.2153)	mem 16099MB
[2025-01-18 06:42:30 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][180/312]	eta 0:01:04 lr 0.001299	time 0.4610 (0.4859)	model_time 0.4608 (0.4733)	loss 1.9901 (3.0266)	grad_norm 1.3549 (2.1972/1.1978)	mem 16099MB
[2025-01-18 06:42:34 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][190/312]	eta 0:00:59 lr 0.001299	time 0.4453 (0.4843)	model_time 0.4451 (0.4724)	loss 3.3561 (3.0225)	grad_norm 2.0267 (2.1914/1.1842)	mem 16099MB
[2025-01-18 06:42:39 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][200/312]	eta 0:00:54 lr 0.001298	time 0.4462 (0.4832)	model_time 0.4457 (0.4718)	loss 3.1017 (3.0203)	grad_norm 1.9626 (2.1987/1.1843)	mem 16099MB
[2025-01-18 06:42:44 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][210/312]	eta 0:00:49 lr 0.001297	time 0.4571 (0.4820)	model_time 0.4569 (0.4711)	loss 1.8347 (3.0109)	grad_norm 1.2946 (2.2420/1.2043)	mem 16099MB
[2025-01-18 06:42:48 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][220/312]	eta 0:00:44 lr 0.001297	time 0.4509 (0.4814)	model_time 0.4505 (0.4710)	loss 2.0328 (3.0096)	grad_norm 2.0547 (2.2586/1.2121)	mem 16099MB
[2025-01-18 06:42:53 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][230/312]	eta 0:00:39 lr 0.001296	time 0.4683 (0.4806)	model_time 0.4679 (0.4706)	loss 2.5739 (3.0203)	grad_norm 1.8357 (2.2323/1.1958)	mem 16099MB
[2025-01-18 06:42:58 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][240/312]	eta 0:00:34 lr 0.001296	time 0.4727 (0.4805)	model_time 0.4725 (0.4710)	loss 3.5010 (3.0252)	grad_norm 1.7809 (2.2222/1.1884)	mem 16099MB
[2025-01-18 06:43:02 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][250/312]	eta 0:00:29 lr 0.001295	time 0.4422 (0.4796)	model_time 0.4420 (0.4704)	loss 2.0587 (3.0267)	grad_norm 1.7868 (2.1957/1.1764)	mem 16099MB
[2025-01-18 06:43:07 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][260/312]	eta 0:00:24 lr 0.001294	time 0.4494 (0.4787)	model_time 0.4492 (0.4698)	loss 3.3284 (3.0253)	grad_norm 1.2050 (2.1694/1.1633)	mem 16099MB
[2025-01-18 06:43:12 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][270/312]	eta 0:00:20 lr 0.001294	time 0.4598 (0.4782)	model_time 0.4593 (0.4697)	loss 3.4084 (3.0279)	grad_norm 1.8308 (2.1843/1.1725)	mem 16099MB
[2025-01-18 06:43:16 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][280/312]	eta 0:00:15 lr 0.001293	time 0.4723 (0.4777)	model_time 0.4719 (0.4694)	loss 3.4192 (3.0221)	grad_norm 2.4177 (2.1717/1.1566)	mem 16099MB
[2025-01-18 06:43:21 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][290/312]	eta 0:00:10 lr 0.001292	time 0.4433 (0.4774)	model_time 0.4428 (0.4695)	loss 2.7046 (3.0276)	grad_norm 2.1917 (2.1904/1.1684)	mem 16099MB
[2025-01-18 06:43:26 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][300/312]	eta 0:00:05 lr 0.001292	time 0.4402 (0.4774)	model_time 0.4401 (0.4696)	loss 2.9819 (3.0275)	grad_norm 2.5293 (2.1994/1.1738)	mem 16099MB
[2025-01-18 06:43:30 internimage_t_1k_224] (main.py 510): INFO Train: [185/300][310/312]	eta 0:00:00 lr 0.001291	time 0.4410 (0.4766)	model_time 0.4409 (0.4691)	loss 3.5142 (3.0307)	grad_norm 1.2952 (2.1976/1.1738)	mem 16099MB
[2025-01-18 06:43:31 internimage_t_1k_224] (main.py 519): INFO EPOCH 185 training takes 0:02:28
[2025-01-18 06:43:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_185.pth saving......
[2025-01-18 06:43:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_185.pth saved !!!
[2025-01-18 06:43:39 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.461 (7.461)	Loss 0.7428 (0.7428)	Acc@1 83.740 (83.740)	Acc@5 97.144 (97.144)	Mem 16099MB
[2025-01-18 06:43:43 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.005)	Loss 1.0945 (0.8988)	Acc@1 75.366 (80.635)	Acc@5 93.457 (95.432)	Mem 16099MB
[2025-01-18 06:43:43 internimage_t_1k_224] (main.py 575): INFO [Epoch:185] * Acc@1 80.588 Acc@5 95.479
[2025-01-18 06:43:43 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.6%
[2025-01-18 06:43:43 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.65%
[2025-01-18 06:43:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.232 (8.232)	Loss 0.7973 (0.7973)	Acc@1 84.814 (84.814)	Acc@5 97.437 (97.437)	Mem 16099MB
[2025-01-18 06:43:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.108)	Loss 1.0692 (0.9188)	Acc@1 77.563 (82.042)	Acc@5 94.531 (95.958)	Mem 16099MB
[2025-01-18 06:43:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:185] * Acc@1 81.902 Acc@5 95.995
[2025-01-18 06:43:55 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.9%
[2025-01-18 06:43:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:43:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:43:57 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.90%
[2025-01-18 06:43:59 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][0/312]	eta 0:13:37 lr 0.001291	time 2.6186 (2.6186)	model_time 0.5092 (0.5092)	loss 3.5746 (3.5746)	grad_norm 1.0262 (1.0262/0.0000)	mem 16099MB
[2025-01-18 06:44:04 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][10/312]	eta 0:03:21 lr 0.001290	time 0.4539 (0.6658)	model_time 0.4535 (0.4736)	loss 3.2038 (3.2674)	grad_norm 2.8216 (1.7598/0.5424)	mem 16099MB
[2025-01-18 06:44:09 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][20/312]	eta 0:02:48 lr 0.001290	time 0.4510 (0.5767)	model_time 0.4509 (0.4759)	loss 2.9642 (3.3081)	grad_norm 2.4152 (1.6460/0.5073)	mem 16099MB
[2025-01-18 06:44:14 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][30/312]	eta 0:02:33 lr 0.001289	time 0.5412 (0.5454)	model_time 0.5408 (0.4770)	loss 3.3303 (3.3025)	grad_norm 0.9660 (1.6711/0.6322)	mem 16099MB
[2025-01-18 06:44:18 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][40/312]	eta 0:02:23 lr 0.001289	time 0.4591 (0.5282)	model_time 0.4589 (0.4763)	loss 3.4431 (3.2968)	grad_norm 1.5794 (2.0185/1.3233)	mem 16099MB
[2025-01-18 06:44:23 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][50/312]	eta 0:02:15 lr 0.001288	time 0.4465 (0.5172)	model_time 0.4460 (0.4754)	loss 3.2877 (3.2322)	grad_norm 1.3536 (2.0402/1.2285)	mem 16099MB
[2025-01-18 06:44:28 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][60/312]	eta 0:02:08 lr 0.001287	time 0.4548 (0.5098)	model_time 0.4547 (0.4748)	loss 3.6556 (3.1750)	grad_norm 1.3702 (2.1449/1.2211)	mem 16099MB
[2025-01-18 06:44:32 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][70/312]	eta 0:02:01 lr 0.001287	time 0.4536 (0.5033)	model_time 0.4531 (0.4732)	loss 3.2381 (3.2018)	grad_norm 2.2218 (2.1338/1.1515)	mem 16099MB
[2025-01-18 06:44:37 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][80/312]	eta 0:01:56 lr 0.001286	time 0.4733 (0.5006)	model_time 0.4731 (0.4742)	loss 3.8201 (3.2151)	grad_norm 3.0605 (2.1040/1.1045)	mem 16099MB
[2025-01-18 06:44:42 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][90/312]	eta 0:01:50 lr 0.001286	time 0.4802 (0.4975)	model_time 0.4800 (0.4740)	loss 2.0594 (3.1859)	grad_norm 1.7674 (2.0857/1.0884)	mem 16099MB
[2025-01-18 06:44:47 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][100/312]	eta 0:01:44 lr 0.001285	time 0.4528 (0.4952)	model_time 0.4524 (0.4739)	loss 3.3767 (3.1949)	grad_norm 2.1415 (2.0925/1.0612)	mem 16099MB
[2025-01-18 06:44:51 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][110/312]	eta 0:01:39 lr 0.001284	time 0.4506 (0.4918)	model_time 0.4502 (0.4724)	loss 3.5043 (3.1755)	grad_norm 1.8872 (2.0818/1.0396)	mem 16099MB
[2025-01-18 06:44:56 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][120/312]	eta 0:01:34 lr 0.001284	time 0.4534 (0.4901)	model_time 0.4533 (0.4723)	loss 2.8950 (3.1218)	grad_norm 1.5688 (2.0488/1.0074)	mem 16099MB
[2025-01-18 06:45:01 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][130/312]	eta 0:01:28 lr 0.001283	time 0.4646 (0.4876)	model_time 0.4645 (0.4711)	loss 2.4000 (3.1166)	grad_norm 1.6384 (2.0388/0.9819)	mem 16099MB
[2025-01-18 06:45:05 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][140/312]	eta 0:01:23 lr 0.001282	time 0.4549 (0.4861)	model_time 0.4545 (0.4707)	loss 2.9933 (3.1055)	grad_norm 1.9818 (2.0341/0.9761)	mem 16099MB
[2025-01-18 06:45:10 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][150/312]	eta 0:01:18 lr 0.001282	time 0.4455 (0.4843)	model_time 0.4453 (0.4700)	loss 3.6851 (3.1017)	grad_norm 2.1885 (2.0417/0.9538)	mem 16099MB
[2025-01-18 06:45:15 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][160/312]	eta 0:01:13 lr 0.001281	time 0.4416 (0.4831)	model_time 0.4412 (0.4696)	loss 3.2256 (3.1034)	grad_norm 1.5478 (2.0667/0.9703)	mem 16099MB
[2025-01-18 06:45:19 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][170/312]	eta 0:01:08 lr 0.001281	time 0.4496 (0.4814)	model_time 0.4494 (0.4687)	loss 3.8517 (3.1115)	grad_norm 2.2282 (2.0898/0.9701)	mem 16099MB
[2025-01-18 06:45:24 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][180/312]	eta 0:01:03 lr 0.001280	time 0.5428 (0.4809)	model_time 0.5423 (0.4689)	loss 3.0054 (3.1041)	grad_norm 4.0161 (2.1178/1.0101)	mem 16099MB
[2025-01-18 06:45:29 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][190/312]	eta 0:00:58 lr 0.001279	time 0.4477 (0.4805)	model_time 0.4472 (0.4690)	loss 3.0219 (3.1017)	grad_norm 1.5821 (2.1207/0.9984)	mem 16099MB
[2025-01-18 06:45:33 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][200/312]	eta 0:00:53 lr 0.001279	time 0.4524 (0.4798)	model_time 0.4519 (0.4689)	loss 3.2097 (3.1020)	grad_norm 1.3590 (2.1035/0.9838)	mem 16099MB
[2025-01-18 06:45:38 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][210/312]	eta 0:00:48 lr 0.001278	time 0.4715 (0.4796)	model_time 0.4713 (0.4692)	loss 2.7145 (3.1020)	grad_norm 1.6193 (2.0960/0.9727)	mem 16099MB
[2025-01-18 06:45:42 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][220/312]	eta 0:00:44 lr 0.001278	time 0.4543 (0.4785)	model_time 0.4541 (0.4686)	loss 3.1381 (3.0963)	grad_norm 2.1307 (2.1055/0.9703)	mem 16099MB
[2025-01-18 06:45:47 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][230/312]	eta 0:00:39 lr 0.001277	time 0.4500 (0.4779)	model_time 0.4495 (0.4684)	loss 2.8720 (3.0973)	grad_norm 2.4433 (2.1326/1.0074)	mem 16099MB
[2025-01-18 06:45:52 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][240/312]	eta 0:00:34 lr 0.001276	time 0.4494 (0.4782)	model_time 0.4492 (0.4691)	loss 3.3230 (3.0987)	grad_norm 3.0468 (2.1932/1.0750)	mem 16099MB
[2025-01-18 06:45:57 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][250/312]	eta 0:00:29 lr 0.001276	time 0.4538 (0.4772)	model_time 0.4536 (0.4684)	loss 3.1607 (3.1027)	grad_norm 1.3338 (2.2031/1.0704)	mem 16099MB
[2025-01-18 06:46:01 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][260/312]	eta 0:00:24 lr 0.001275	time 0.4496 (0.4766)	model_time 0.4495 (0.4681)	loss 3.7863 (3.0859)	grad_norm 1.1856 (2.1953/1.0627)	mem 16099MB
[2025-01-18 06:46:06 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][270/312]	eta 0:00:19 lr 0.001274	time 0.4419 (0.4760)	model_time 0.4415 (0.4678)	loss 3.2692 (3.0919)	grad_norm 1.2876 (2.1599/1.0596)	mem 16099MB
[2025-01-18 06:46:11 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][280/312]	eta 0:00:15 lr 0.001274	time 0.4556 (0.4761)	model_time 0.4555 (0.4682)	loss 3.7988 (3.0911)	grad_norm 1.7075 (2.1526/1.0522)	mem 16099MB
[2025-01-18 06:46:15 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][290/312]	eta 0:00:10 lr 0.001273	time 0.4501 (0.4757)	model_time 0.4500 (0.4680)	loss 3.0495 (3.0975)	grad_norm 1.2371 (2.1340/1.0452)	mem 16099MB
[2025-01-18 06:46:20 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][300/312]	eta 0:00:05 lr 0.001273	time 0.4380 (0.4751)	model_time 0.4379 (0.4677)	loss 2.8834 (3.0941)	grad_norm 3.1523 (2.1266/1.0339)	mem 16099MB
[2025-01-18 06:46:24 internimage_t_1k_224] (main.py 510): INFO Train: [186/300][310/312]	eta 0:00:00 lr 0.001272	time 0.4380 (0.4746)	model_time 0.4379 (0.4674)	loss 2.9460 (3.0953)	grad_norm 2.3384 (2.1527/1.0567)	mem 16099MB
[2025-01-18 06:46:25 internimage_t_1k_224] (main.py 519): INFO EPOCH 186 training takes 0:02:28
[2025-01-18 06:46:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_186.pth saving......
[2025-01-18 06:46:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_186.pth saved !!!
[2025-01-18 06:46:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.383 (7.383)	Loss 0.7730 (0.7730)	Acc@1 83.203 (83.203)	Acc@5 96.924 (96.924)	Mem 16099MB
[2025-01-18 06:46:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.988)	Loss 1.0899 (0.8967)	Acc@1 76.440 (80.902)	Acc@5 93.555 (95.497)	Mem 16099MB
[2025-01-18 06:46:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:186] * Acc@1 80.800 Acc@5 95.555
[2025-01-18 06:46:37 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.8%
[2025-01-18 06:46:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 06:46:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 06:46:38 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.80%
[2025-01-18 06:46:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.524 (7.524)	Loss 0.7967 (0.7967)	Acc@1 84.766 (84.766)	Acc@5 97.437 (97.437)	Mem 16099MB
[2025-01-18 06:46:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.015)	Loss 1.0680 (0.9178)	Acc@1 77.539 (82.060)	Acc@5 94.580 (95.965)	Mem 16099MB
[2025-01-18 06:46:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:186] * Acc@1 81.930 Acc@5 96.007
[2025-01-18 06:46:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.9%
[2025-01-18 06:46:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:46:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:46:51 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.93%
[2025-01-18 06:46:53 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][0/312]	eta 0:12:45 lr 0.001272	time 2.4535 (2.4535)	model_time 0.5207 (0.5207)	loss 2.7387 (2.7387)	grad_norm 1.7672 (1.7672/0.0000)	mem 16099MB
[2025-01-18 06:46:58 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][10/312]	eta 0:03:13 lr 0.001271	time 0.4436 (0.6414)	model_time 0.4435 (0.4654)	loss 2.1683 (2.8622)	grad_norm 3.0822 (2.4266/0.8626)	mem 16099MB
[2025-01-18 06:47:03 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][20/312]	eta 0:02:43 lr 0.001271	time 0.5359 (0.5592)	model_time 0.5358 (0.4669)	loss 3.2555 (2.9138)	grad_norm 3.3377 (2.2411/0.8493)	mem 16099MB
[2025-01-18 06:47:08 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][30/312]	eta 0:02:30 lr 0.001270	time 0.4456 (0.5332)	model_time 0.4451 (0.4706)	loss 2.8604 (2.9189)	grad_norm 1.3197 (2.2175/0.7776)	mem 16099MB
[2025-01-18 06:47:12 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][40/312]	eta 0:02:20 lr 0.001269	time 0.4651 (0.5151)	model_time 0.4646 (0.4676)	loss 3.1464 (2.9473)	grad_norm 2.0675 (2.0292/0.7701)	mem 16099MB
[2025-01-18 06:47:17 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][50/312]	eta 0:02:12 lr 0.001269	time 0.4548 (0.5074)	model_time 0.4546 (0.4692)	loss 2.3411 (2.9246)	grad_norm 1.9474 (1.9311/0.7335)	mem 16099MB
[2025-01-18 06:47:22 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][60/312]	eta 0:02:06 lr 0.001268	time 0.5218 (0.5032)	model_time 0.5216 (0.4712)	loss 2.1310 (2.9242)	grad_norm 0.8995 (1.8517/0.7299)	mem 16099MB
[2025-01-18 06:47:26 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][70/312]	eta 0:02:00 lr 0.001268	time 0.4412 (0.4966)	model_time 0.4408 (0.4690)	loss 1.9512 (2.9375)	grad_norm 1.8552 (1.8979/0.7244)	mem 16099MB
[2025-01-18 06:47:31 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][80/312]	eta 0:01:54 lr 0.001267	time 0.5618 (0.4957)	model_time 0.5613 (0.4714)	loss 2.8026 (2.9340)	grad_norm 2.7101 (1.9552/0.7741)	mem 16099MB
[2025-01-18 06:47:36 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][90/312]	eta 0:01:49 lr 0.001266	time 0.4540 (0.4920)	model_time 0.4536 (0.4704)	loss 3.2624 (2.9879)	grad_norm 1.2269 (1.9229/0.7656)	mem 16099MB
[2025-01-18 06:47:41 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][100/312]	eta 0:01:44 lr 0.001266	time 0.4537 (0.4906)	model_time 0.4536 (0.4711)	loss 3.4264 (3.0095)	grad_norm 1.9592 (1.9488/0.7526)	mem 16099MB
[2025-01-18 06:47:45 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][110/312]	eta 0:01:38 lr 0.001265	time 0.4702 (0.4887)	model_time 0.4698 (0.4710)	loss 2.6408 (2.9946)	grad_norm 3.6553 (1.9931/0.7840)	mem 16099MB
[2025-01-18 06:47:50 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][120/312]	eta 0:01:33 lr 0.001264	time 0.4561 (0.4866)	model_time 0.4560 (0.4703)	loss 2.6272 (3.0205)	grad_norm 2.5452 (1.9976/0.7949)	mem 16099MB
[2025-01-18 06:47:54 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][130/312]	eta 0:01:28 lr 0.001264	time 0.4489 (0.4843)	model_time 0.4485 (0.4692)	loss 2.9518 (3.0439)	grad_norm 2.5464 (2.0828/0.8696)	mem 16099MB
[2025-01-18 06:47:59 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][140/312]	eta 0:01:23 lr 0.001263	time 0.4606 (0.4830)	model_time 0.4605 (0.4689)	loss 2.9830 (3.0375)	grad_norm 2.3332 (2.1040/0.8931)	mem 16099MB
[2025-01-18 06:48:04 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][150/312]	eta 0:01:18 lr 0.001263	time 0.4481 (0.4825)	model_time 0.4477 (0.4694)	loss 3.6554 (3.0513)	grad_norm 1.0890 (2.0906/0.8814)	mem 16099MB
[2025-01-18 06:48:09 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][160/312]	eta 0:01:13 lr 0.001262	time 0.4790 (0.4820)	model_time 0.4788 (0.4697)	loss 3.5899 (3.0559)	grad_norm 1.7001 (2.0773/0.8672)	mem 16099MB
[2025-01-18 06:48:13 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][170/312]	eta 0:01:08 lr 0.001261	time 0.4477 (0.4808)	model_time 0.4473 (0.4691)	loss 2.4242 (3.0602)	grad_norm 2.7790 (2.0615/0.8555)	mem 16099MB
[2025-01-18 06:48:18 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][180/312]	eta 0:01:03 lr 0.001261	time 0.4563 (0.4794)	model_time 0.4558 (0.4684)	loss 3.3490 (3.0506)	grad_norm 1.9184 (2.0519/0.8398)	mem 16099MB
[2025-01-18 06:48:23 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][190/312]	eta 0:00:58 lr 0.001260	time 0.4605 (0.4792)	model_time 0.4603 (0.4687)	loss 2.8639 (3.0478)	grad_norm 4.9932 (2.0659/0.8771)	mem 16099MB
[2025-01-18 06:48:27 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][200/312]	eta 0:00:53 lr 0.001260	time 0.4661 (0.4793)	model_time 0.4660 (0.4693)	loss 3.0431 (3.0489)	grad_norm 2.6905 (2.0960/0.8793)	mem 16099MB
[2025-01-18 06:48:32 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][210/312]	eta 0:00:48 lr 0.001259	time 0.4403 (0.4782)	model_time 0.4399 (0.4687)	loss 3.1272 (3.0327)	grad_norm 2.4639 (2.0865/0.8742)	mem 16099MB
[2025-01-18 06:48:36 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][220/312]	eta 0:00:43 lr 0.001258	time 0.4436 (0.4771)	model_time 0.4434 (0.4680)	loss 2.6061 (3.0279)	grad_norm 2.0102 (2.0634/0.8683)	mem 16099MB
[2025-01-18 06:48:41 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][230/312]	eta 0:00:39 lr 0.001258	time 0.4626 (0.4775)	model_time 0.4625 (0.4687)	loss 3.4428 (3.0297)	grad_norm 0.9921 (2.0434/0.8612)	mem 16099MB
[2025-01-18 06:48:46 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][240/312]	eta 0:00:34 lr 0.001257	time 0.4431 (0.4775)	model_time 0.4429 (0.4690)	loss 3.1851 (3.0282)	grad_norm 2.6933 (2.0492/0.8714)	mem 16099MB
[2025-01-18 06:48:51 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][250/312]	eta 0:00:29 lr 0.001257	time 0.4623 (0.4769)	model_time 0.4618 (0.4688)	loss 3.2677 (3.0265)	grad_norm 1.5339 (2.0754/0.8993)	mem 16099MB
[2025-01-18 06:48:55 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][260/312]	eta 0:00:24 lr 0.001256	time 0.4494 (0.4764)	model_time 0.4492 (0.4686)	loss 3.7049 (3.0225)	grad_norm 2.6945 (2.0825/0.9017)	mem 16099MB
[2025-01-18 06:49:00 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][270/312]	eta 0:00:19 lr 0.001255	time 0.4397 (0.4759)	model_time 0.4393 (0.4684)	loss 2.2272 (3.0277)	grad_norm 1.2251 (2.0678/0.8930)	mem 16099MB
[2025-01-18 06:49:05 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][280/312]	eta 0:00:15 lr 0.001255	time 0.4381 (0.4759)	model_time 0.4379 (0.4686)	loss 2.5114 (3.0146)	grad_norm 2.0381 (2.0742/0.8964)	mem 16099MB
[2025-01-18 06:49:10 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][290/312]	eta 0:00:10 lr 0.001254	time 0.4533 (0.4760)	model_time 0.4529 (0.4689)	loss 3.7132 (3.0141)	grad_norm 2.6844 (2.0733/0.8912)	mem 16099MB
[2025-01-18 06:49:14 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][300/312]	eta 0:00:05 lr 0.001253	time 0.4372 (0.4751)	model_time 0.4371 (0.4683)	loss 2.9300 (3.0144)	grad_norm 4.0485 (2.0795/0.8957)	mem 16099MB
[2025-01-18 06:49:19 internimage_t_1k_224] (main.py 510): INFO Train: [187/300][310/312]	eta 0:00:00 lr 0.001253	time 0.4389 (0.4745)	model_time 0.4388 (0.4679)	loss 3.3109 (3.0111)	grad_norm 1.1763 (2.0673/0.8954)	mem 16099MB
[2025-01-18 06:49:19 internimage_t_1k_224] (main.py 519): INFO EPOCH 187 training takes 0:02:28
[2025-01-18 06:49:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_187.pth saving......
[2025-01-18 06:49:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_187.pth saved !!!
[2025-01-18 06:49:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.513 (7.513)	Loss 0.7488 (0.7488)	Acc@1 84.375 (84.375)	Acc@5 97.217 (97.217)	Mem 16099MB
[2025-01-18 06:49:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.018)	Loss 1.0621 (0.8845)	Acc@1 76.489 (81.072)	Acc@5 93.774 (95.523)	Mem 16099MB
[2025-01-18 06:49:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:187] * Acc@1 80.978 Acc@5 95.567
[2025-01-18 06:49:32 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.0%
[2025-01-18 06:49:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 06:49:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 06:49:33 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.98%
[2025-01-18 06:49:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.588 (7.588)	Loss 0.7962 (0.7962)	Acc@1 84.766 (84.766)	Acc@5 97.412 (97.412)	Mem 16099MB
[2025-01-18 06:49:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.024)	Loss 1.0668 (0.9169)	Acc@1 77.563 (82.069)	Acc@5 94.629 (95.974)	Mem 16099MB
[2025-01-18 06:49:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:187] * Acc@1 81.948 Acc@5 96.019
[2025-01-18 06:49:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 81.9%
[2025-01-18 06:49:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:49:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:49:46 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 81.95%
[2025-01-18 06:49:48 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][0/312]	eta 0:14:33 lr 0.001253	time 2.7994 (2.7994)	model_time 0.4637 (0.4637)	loss 2.9183 (2.9183)	grad_norm 5.2601 (5.2601/0.0000)	mem 16099MB
[2025-01-18 06:49:53 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][10/312]	eta 0:03:28 lr 0.001252	time 0.5355 (0.6896)	model_time 0.5353 (0.4770)	loss 3.1902 (3.1048)	grad_norm 2.2603 (2.7476/1.1280)	mem 16099MB
[2025-01-18 06:49:58 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][20/312]	eta 0:02:50 lr 0.001251	time 0.4463 (0.5830)	model_time 0.4462 (0.4714)	loss 3.1502 (3.2238)	grad_norm 1.2602 (2.2595/1.0429)	mem 16099MB
[2025-01-18 06:50:02 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][30/312]	eta 0:02:32 lr 0.001251	time 0.4575 (0.5423)	model_time 0.4571 (0.4666)	loss 3.3840 (3.1804)	grad_norm 1.1866 (2.1094/0.9726)	mem 16099MB
[2025-01-18 06:50:07 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][40/312]	eta 0:02:21 lr 0.001250	time 0.4446 (0.5220)	model_time 0.4442 (0.4646)	loss 3.4157 (3.1600)	grad_norm 2.7569 (2.1427/0.9921)	mem 16099MB
[2025-01-18 06:50:12 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][50/312]	eta 0:02:13 lr 0.001250	time 0.4701 (0.5098)	model_time 0.4696 (0.4637)	loss 3.3773 (3.1504)	grad_norm 4.0574 (2.2348/0.9815)	mem 16099MB
[2025-01-18 06:50:16 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][60/312]	eta 0:02:07 lr 0.001249	time 0.4487 (0.5045)	model_time 0.4485 (0.4659)	loss 3.3963 (3.1518)	grad_norm 2.4719 (2.2956/0.9934)	mem 16099MB
[2025-01-18 06:50:21 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][70/312]	eta 0:02:00 lr 0.001248	time 0.4496 (0.4986)	model_time 0.4495 (0.4654)	loss 3.3471 (3.1215)	grad_norm 2.5427 (2.3884/0.9945)	mem 16099MB
[2025-01-18 06:50:26 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][80/312]	eta 0:01:55 lr 0.001248	time 0.4671 (0.4973)	model_time 0.4670 (0.4681)	loss 2.3735 (3.0826)	grad_norm 1.6560 (2.3686/1.0057)	mem 16099MB
[2025-01-18 06:50:30 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][90/312]	eta 0:01:49 lr 0.001247	time 0.4684 (0.4928)	model_time 0.4683 (0.4668)	loss 3.3695 (3.0862)	grad_norm 1.4684 (2.3555/0.9792)	mem 16099MB
[2025-01-18 06:50:35 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][100/312]	eta 0:01:43 lr 0.001247	time 0.4664 (0.4893)	model_time 0.4660 (0.4658)	loss 3.8471 (3.0974)	grad_norm 1.1403 (2.3208/0.9578)	mem 16099MB
[2025-01-18 06:50:40 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][110/312]	eta 0:01:38 lr 0.001246	time 0.4422 (0.4872)	model_time 0.4420 (0.4658)	loss 2.8692 (3.0943)	grad_norm 2.3971 (2.3185/0.9596)	mem 16099MB
[2025-01-18 06:50:45 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][120/312]	eta 0:01:33 lr 0.001245	time 0.5568 (0.4870)	model_time 0.5564 (0.4674)	loss 3.5101 (3.0936)	grad_norm 1.7537 (2.2909/0.9553)	mem 16099MB
[2025-01-18 06:50:50 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][130/312]	eta 0:01:28 lr 0.001245	time 0.7585 (0.4883)	model_time 0.7580 (0.4702)	loss 2.5488 (3.0944)	grad_norm 3.1831 (2.2603/0.9390)	mem 16099MB
[2025-01-18 06:50:55 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][140/312]	eta 0:01:24 lr 0.001244	time 0.4480 (0.4898)	model_time 0.4478 (0.4729)	loss 3.2035 (3.1041)	grad_norm 1.0460 (2.2323/0.9186)	mem 16099MB
[2025-01-18 06:50:59 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][150/312]	eta 0:01:19 lr 0.001244	time 0.4575 (0.4883)	model_time 0.4570 (0.4725)	loss 3.4374 (3.1088)	grad_norm 1.4517 (2.2096/0.9148)	mem 16099MB
[2025-01-18 06:51:04 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][160/312]	eta 0:01:13 lr 0.001243	time 0.4570 (0.4867)	model_time 0.4566 (0.4718)	loss 3.1835 (3.0907)	grad_norm 2.0592 (2.2024/0.9187)	mem 16099MB
[2025-01-18 06:51:09 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][170/312]	eta 0:01:08 lr 0.001242	time 0.4422 (0.4856)	model_time 0.4420 (0.4716)	loss 3.3602 (3.0858)	grad_norm 1.2203 (2.2137/0.9213)	mem 16099MB
[2025-01-18 06:51:13 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][180/312]	eta 0:01:04 lr 0.001242	time 0.4496 (0.4850)	model_time 0.4492 (0.4717)	loss 2.2054 (3.0734)	grad_norm 1.4329 (2.1794/0.9143)	mem 16099MB
[2025-01-18 06:51:18 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][190/312]	eta 0:00:58 lr 0.001241	time 0.4580 (0.4834)	model_time 0.4578 (0.4708)	loss 2.8676 (3.0714)	grad_norm 1.3097 (2.1750/0.8970)	mem 16099MB
[2025-01-18 06:51:23 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][200/312]	eta 0:00:54 lr 0.001240	time 0.5479 (0.4825)	model_time 0.5474 (0.4705)	loss 2.7968 (3.0673)	grad_norm 4.0991 (2.1864/0.8940)	mem 16099MB
[2025-01-18 06:51:27 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][210/312]	eta 0:00:49 lr 0.001240	time 0.4815 (0.4817)	model_time 0.4810 (0.4703)	loss 3.7059 (3.0745)	grad_norm 2.3339 (2.1961/0.9276)	mem 16099MB
[2025-01-18 06:51:32 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][220/312]	eta 0:00:44 lr 0.001239	time 0.4621 (0.4806)	model_time 0.4616 (0.4696)	loss 2.8814 (3.0776)	grad_norm 2.8668 (2.2006/0.9157)	mem 16099MB
[2025-01-18 06:51:36 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][230/312]	eta 0:00:39 lr 0.001239	time 0.4604 (0.4796)	model_time 0.4602 (0.4691)	loss 3.0606 (3.0831)	grad_norm 1.6130 (2.1949/0.9021)	mem 16099MB
[2025-01-18 06:51:41 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][240/312]	eta 0:00:34 lr 0.001238	time 0.4435 (0.4785)	model_time 0.4430 (0.4684)	loss 2.9147 (3.0753)	grad_norm 1.3030 (2.1728/0.9001)	mem 16099MB
[2025-01-18 06:51:46 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][250/312]	eta 0:00:29 lr 0.001237	time 0.4444 (0.4778)	model_time 0.4443 (0.4681)	loss 2.3667 (3.0696)	grad_norm 1.0504 (2.1522/0.8936)	mem 16099MB
[2025-01-18 06:51:50 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][260/312]	eta 0:00:24 lr 0.001237	time 0.4583 (0.4770)	model_time 0.4581 (0.4677)	loss 2.9227 (3.0615)	grad_norm 1.1236 (2.1282/0.8894)	mem 16099MB
[2025-01-18 06:51:55 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][270/312]	eta 0:00:20 lr 0.001236	time 0.4486 (0.4768)	model_time 0.4485 (0.4679)	loss 3.1403 (3.0665)	grad_norm 1.3030 (2.1281/0.9012)	mem 16099MB
[2025-01-18 06:51:59 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][280/312]	eta 0:00:15 lr 0.001236	time 0.4502 (0.4761)	model_time 0.4497 (0.4675)	loss 2.9672 (3.0657)	grad_norm 1.5221 (2.1382/0.9125)	mem 16099MB
[2025-01-18 06:52:04 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][290/312]	eta 0:00:10 lr 0.001235	time 0.4539 (0.4760)	model_time 0.4537 (0.4676)	loss 2.8483 (3.0600)	grad_norm 0.9999 (2.1260/0.9069)	mem 16099MB
[2025-01-18 06:52:09 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][300/312]	eta 0:00:05 lr 0.001234	time 0.4394 (0.4755)	model_time 0.4393 (0.4674)	loss 3.2920 (3.0696)	grad_norm 2.1531 (2.1107/0.8796)	mem 16099MB
[2025-01-18 06:52:13 internimage_t_1k_224] (main.py 510): INFO Train: [188/300][310/312]	eta 0:00:00 lr 0.001234	time 0.4379 (0.4753)	model_time 0.4378 (0.4674)	loss 3.4228 (3.0755)	grad_norm 3.9679 (2.1058/0.8919)	mem 16099MB
[2025-01-18 06:52:14 internimage_t_1k_224] (main.py 519): INFO EPOCH 188 training takes 0:02:28
[2025-01-18 06:52:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_188.pth saving......
[2025-01-18 06:52:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_188.pth saved !!!
[2025-01-18 06:52:23 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.572 (7.572)	Loss 0.7953 (0.7953)	Acc@1 84.009 (84.009)	Acc@5 97.144 (97.144)	Mem 16099MB
[2025-01-18 06:52:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.008)	Loss 1.0959 (0.9267)	Acc@1 75.293 (80.649)	Acc@5 93.579 (95.472)	Mem 16099MB
[2025-01-18 06:52:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:188] * Acc@1 80.606 Acc@5 95.517
[2025-01-18 06:52:26 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.6%
[2025-01-18 06:52:26 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.98%
[2025-01-18 06:52:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.048 (8.048)	Loss 0.7955 (0.7955)	Acc@1 84.912 (84.912)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 06:52:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.094)	Loss 1.0654 (0.9157)	Acc@1 77.661 (82.118)	Acc@5 94.678 (95.989)	Mem 16099MB
[2025-01-18 06:52:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:188] * Acc@1 82.002 Acc@5 96.033
[2025-01-18 06:52:38 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.0%
[2025-01-18 06:52:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:52:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:52:40 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.00%
[2025-01-18 06:52:42 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][0/312]	eta 0:11:50 lr 0.001234	time 2.2773 (2.2773)	model_time 0.5038 (0.5038)	loss 2.7917 (2.7917)	grad_norm 2.0836 (2.0836/0.0000)	mem 16099MB
[2025-01-18 06:52:47 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][10/312]	eta 0:03:12 lr 0.001233	time 0.5709 (0.6389)	model_time 0.5707 (0.4773)	loss 3.0291 (2.9039)	grad_norm 2.7417 (2.0714/0.5662)	mem 16099MB
[2025-01-18 06:52:52 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][20/312]	eta 0:02:43 lr 0.001232	time 0.5839 (0.5604)	model_time 0.5837 (0.4756)	loss 3.1973 (3.0476)	grad_norm 1.1266 (2.2007/0.9701)	mem 16099MB
[2025-01-18 06:52:56 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][30/312]	eta 0:02:28 lr 0.001232	time 0.4662 (0.5271)	model_time 0.4658 (0.4695)	loss 2.3676 (2.9848)	grad_norm 4.0473 (2.1267/0.9393)	mem 16099MB
[2025-01-18 06:53:01 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][40/312]	eta 0:02:19 lr 0.001231	time 0.4607 (0.5135)	model_time 0.4605 (0.4699)	loss 3.5797 (2.9835)	grad_norm 2.6030 (2.1375/0.8999)	mem 16099MB
[2025-01-18 06:53:06 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][50/312]	eta 0:02:12 lr 0.001231	time 0.4543 (0.5060)	model_time 0.4542 (0.4708)	loss 2.5241 (2.9955)	grad_norm 3.4781 (2.1211/0.8859)	mem 16099MB
[2025-01-18 06:53:10 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][60/312]	eta 0:02:05 lr 0.001230	time 0.4461 (0.4981)	model_time 0.4460 (0.4687)	loss 3.6281 (2.9861)	grad_norm 2.8105 (2.1552/0.8926)	mem 16099MB
[2025-01-18 06:53:15 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][70/312]	eta 0:01:59 lr 0.001229	time 0.4486 (0.4956)	model_time 0.4482 (0.4703)	loss 3.3466 (2.9934)	grad_norm 3.3163 (2.1745/0.9058)	mem 16099MB
[2025-01-18 06:53:20 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][80/312]	eta 0:01:54 lr 0.001229	time 0.4550 (0.4944)	model_time 0.4548 (0.4722)	loss 2.4134 (3.0194)	grad_norm 2.1297 (2.1734/0.8881)	mem 16099MB
[2025-01-18 06:53:24 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][90/312]	eta 0:01:48 lr 0.001228	time 0.4881 (0.4902)	model_time 0.4879 (0.4704)	loss 2.1427 (2.9956)	grad_norm 2.1780 (2.2266/0.9248)	mem 16099MB
[2025-01-18 06:53:29 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][100/312]	eta 0:01:43 lr 0.001228	time 0.4490 (0.4881)	model_time 0.4489 (0.4702)	loss 3.5866 (3.0032)	grad_norm 1.0790 (2.1904/0.9085)	mem 16099MB
[2025-01-18 06:53:34 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][110/312]	eta 0:01:38 lr 0.001227	time 0.4892 (0.4875)	model_time 0.4887 (0.4711)	loss 3.1785 (3.0323)	grad_norm 4.0116 (2.1893/0.9224)	mem 16099MB
[2025-01-18 06:53:38 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][120/312]	eta 0:01:33 lr 0.001226	time 0.4399 (0.4849)	model_time 0.4395 (0.4699)	loss 3.2130 (3.0221)	grad_norm 1.4470 (2.1969/0.9352)	mem 16099MB
[2025-01-18 06:53:43 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][130/312]	eta 0:01:27 lr 0.001226	time 0.4395 (0.4834)	model_time 0.4393 (0.4696)	loss 2.2103 (3.0087)	grad_norm 1.4649 (2.2134/0.9568)	mem 16099MB
[2025-01-18 06:53:48 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][140/312]	eta 0:01:22 lr 0.001225	time 0.4754 (0.4821)	model_time 0.4753 (0.4692)	loss 3.6874 (3.0121)	grad_norm 1.4718 (2.2331/0.9745)	mem 16099MB
[2025-01-18 06:53:52 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][150/312]	eta 0:01:17 lr 0.001225	time 0.4562 (0.4807)	model_time 0.4558 (0.4686)	loss 3.4713 (3.0276)	grad_norm 0.9746 (2.2428/0.9790)	mem 16099MB
[2025-01-18 06:53:57 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][160/312]	eta 0:01:12 lr 0.001224	time 0.4435 (0.4793)	model_time 0.4431 (0.4679)	loss 3.4822 (3.0370)	grad_norm 1.3256 (2.2520/0.9856)	mem 16099MB
[2025-01-18 06:54:02 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][170/312]	eta 0:01:07 lr 0.001223	time 0.4853 (0.4784)	model_time 0.4849 (0.4677)	loss 2.4731 (3.0282)	grad_norm 1.3607 (2.2709/0.9888)	mem 16099MB
[2025-01-18 06:54:06 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][180/312]	eta 0:01:03 lr 0.001223	time 0.4508 (0.4787)	model_time 0.4504 (0.4685)	loss 2.3203 (3.0192)	grad_norm 1.3934 (2.2712/0.9779)	mem 16099MB
[2025-01-18 06:54:11 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][190/312]	eta 0:00:58 lr 0.001222	time 0.4459 (0.4774)	model_time 0.4455 (0.4678)	loss 3.1502 (3.0313)	grad_norm 0.9188 (2.2946/0.9910)	mem 16099MB
[2025-01-18 06:54:16 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][200/312]	eta 0:00:53 lr 0.001221	time 0.4519 (0.4762)	model_time 0.4515 (0.4671)	loss 3.2043 (3.0341)	grad_norm 1.0673 (2.2924/1.0021)	mem 16099MB
[2025-01-18 06:54:20 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][210/312]	eta 0:00:48 lr 0.001221	time 0.5314 (0.4762)	model_time 0.5312 (0.4675)	loss 3.0819 (3.0378)	grad_norm 1.0935 (2.2859/0.9927)	mem 16099MB
[2025-01-18 06:54:25 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][220/312]	eta 0:00:43 lr 0.001220	time 0.4472 (0.4753)	model_time 0.4467 (0.4669)	loss 3.2582 (3.0262)	grad_norm 2.3208 (2.2508/0.9865)	mem 16099MB
[2025-01-18 06:54:29 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][230/312]	eta 0:00:38 lr 0.001220	time 0.4576 (0.4748)	model_time 0.4571 (0.4667)	loss 3.1262 (3.0314)	grad_norm 1.9309 (2.2555/0.9956)	mem 16099MB
[2025-01-18 06:54:34 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][240/312]	eta 0:00:34 lr 0.001219	time 0.4480 (0.4742)	model_time 0.4476 (0.4665)	loss 3.5264 (3.0422)	grad_norm 1.5553 (2.2640/1.0044)	mem 16099MB
[2025-01-18 06:54:39 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][250/312]	eta 0:00:29 lr 0.001218	time 0.4523 (0.4747)	model_time 0.4516 (0.4672)	loss 3.1955 (3.0504)	grad_norm 1.3644 (2.2479/0.9959)	mem 16099MB
[2025-01-18 06:54:44 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][260/312]	eta 0:00:24 lr 0.001218	time 0.4615 (0.4741)	model_time 0.4613 (0.4670)	loss 2.0453 (3.0515)	grad_norm 1.6695 (2.2366/1.0001)	mem 16099MB
[2025-01-18 06:54:48 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][270/312]	eta 0:00:19 lr 0.001217	time 0.4499 (0.4737)	model_time 0.4496 (0.4668)	loss 2.9445 (3.0565)	grad_norm 1.6588 (2.2446/1.0002)	mem 16099MB
[2025-01-18 06:54:53 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][280/312]	eta 0:00:15 lr 0.001217	time 0.4655 (0.4730)	model_time 0.4654 (0.4664)	loss 2.9639 (3.0518)	grad_norm 3.4405 (2.2524/0.9951)	mem 16099MB
[2025-01-18 06:54:57 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][290/312]	eta 0:00:10 lr 0.001216	time 0.4485 (0.4731)	model_time 0.4484 (0.4666)	loss 2.7072 (3.0435)	grad_norm 1.9471 (2.2365/0.9864)	mem 16099MB
[2025-01-18 06:55:02 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][300/312]	eta 0:00:05 lr 0.001215	time 0.4394 (0.4731)	model_time 0.4393 (0.4669)	loss 2.1723 (3.0456)	grad_norm 1.2567 (2.2164/0.9817)	mem 16099MB
[2025-01-18 06:55:07 internimage_t_1k_224] (main.py 510): INFO Train: [189/300][310/312]	eta 0:00:00 lr 0.001215	time 0.4436 (0.4726)	model_time 0.4435 (0.4665)	loss 3.3006 (3.0386)	grad_norm 1.6817 (2.2120/0.9805)	mem 16099MB
[2025-01-18 06:55:07 internimage_t_1k_224] (main.py 519): INFO EPOCH 189 training takes 0:02:27
[2025-01-18 06:55:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_189.pth saving......
[2025-01-18 06:55:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_189.pth saved !!!
[2025-01-18 06:55:16 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.453 (7.453)	Loss 0.7705 (0.7705)	Acc@1 83.325 (83.325)	Acc@5 96.875 (96.875)	Mem 16099MB
[2025-01-18 06:55:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.021)	Loss 1.0917 (0.9086)	Acc@1 75.903 (80.631)	Acc@5 93.433 (95.508)	Mem 16099MB
[2025-01-18 06:55:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:189] * Acc@1 80.556 Acc@5 95.555
[2025-01-18 06:55:20 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.6%
[2025-01-18 06:55:20 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.98%
[2025-01-18 06:55:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.104 (8.104)	Loss 0.7946 (0.7946)	Acc@1 84.912 (84.912)	Acc@5 97.461 (97.461)	Mem 16099MB
[2025-01-18 06:55:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.103)	Loss 1.0637 (0.9143)	Acc@1 77.661 (82.122)	Acc@5 94.678 (96.014)	Mem 16099MB
[2025-01-18 06:55:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:189] * Acc@1 82.002 Acc@5 96.055
[2025-01-18 06:55:32 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.0%
[2025-01-18 06:55:32 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.00%
[2025-01-18 06:55:35 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][0/312]	eta 0:15:29 lr 0.001215	time 2.9794 (2.9794)	model_time 1.0482 (1.0482)	loss 3.6522 (3.6522)	grad_norm 2.4936 (2.4936/0.0000)	mem 16099MB
[2025-01-18 06:55:40 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][10/312]	eta 0:03:33 lr 0.001214	time 0.4523 (0.7060)	model_time 0.4519 (0.5300)	loss 3.5390 (2.9571)	grad_norm 3.6661 (2.0020/0.6670)	mem 16099MB
[2025-01-18 06:55:44 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][20/312]	eta 0:02:53 lr 0.001213	time 0.4607 (0.5937)	model_time 0.4603 (0.5013)	loss 3.3617 (2.9154)	grad_norm 1.7212 (2.0295/0.7500)	mem 16099MB
[2025-01-18 06:55:49 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][30/312]	eta 0:02:37 lr 0.001213	time 0.4633 (0.5577)	model_time 0.4631 (0.4950)	loss 2.9317 (3.0135)	grad_norm 1.1969 (1.8629/0.6988)	mem 16099MB
[2025-01-18 06:55:54 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][40/312]	eta 0:02:26 lr 0.001212	time 0.4602 (0.5370)	model_time 0.4598 (0.4894)	loss 3.5728 (3.0483)	grad_norm 2.3342 (1.8684/0.6884)	mem 16099MB
[2025-01-18 06:55:59 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][50/312]	eta 0:02:18 lr 0.001212	time 0.4612 (0.5282)	model_time 0.4607 (0.4900)	loss 3.5092 (3.0567)	grad_norm 2.2788 (1.8490/0.6558)	mem 16099MB
[2025-01-18 06:56:04 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][60/312]	eta 0:02:10 lr 0.001211	time 0.4652 (0.5165)	model_time 0.4648 (0.4844)	loss 3.3097 (3.0503)	grad_norm 2.2828 (1.9107/0.6923)	mem 16099MB
[2025-01-18 06:56:08 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][70/312]	eta 0:02:03 lr 0.001210	time 0.4708 (0.5086)	model_time 0.4706 (0.4810)	loss 3.2371 (3.0799)	grad_norm 2.2117 (1.8948/0.6797)	mem 16099MB
[2025-01-18 06:56:13 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][80/312]	eta 0:01:57 lr 0.001210	time 0.4555 (0.5054)	model_time 0.4551 (0.4811)	loss 2.0323 (3.0832)	grad_norm 1.2919 (1.9261/0.6890)	mem 16099MB
[2025-01-18 06:56:18 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][90/312]	eta 0:01:51 lr 0.001209	time 0.4483 (0.5020)	model_time 0.4478 (0.4804)	loss 2.8295 (3.0912)	grad_norm 2.2790 (1.9041/0.6648)	mem 16099MB
[2025-01-18 06:56:22 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][100/312]	eta 0:01:45 lr 0.001209	time 0.4536 (0.4973)	model_time 0.4532 (0.4778)	loss 3.5033 (3.1020)	grad_norm 2.0012 (1.9139/0.6634)	mem 16099MB
[2025-01-18 06:56:27 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][110/312]	eta 0:01:39 lr 0.001208	time 0.4531 (0.4934)	model_time 0.4527 (0.4756)	loss 3.0000 (3.1076)	grad_norm 1.4348 (1.9159/0.6858)	mem 16099MB
[2025-01-18 06:56:32 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][120/312]	eta 0:01:34 lr 0.001207	time 0.4583 (0.4917)	model_time 0.4579 (0.4753)	loss 2.4657 (3.1014)	grad_norm 1.2314 (1.8974/0.6722)	mem 16099MB
[2025-01-18 06:56:36 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][130/312]	eta 0:01:29 lr 0.001207	time 0.4553 (0.4894)	model_time 0.4551 (0.4742)	loss 2.7729 (3.0923)	grad_norm 3.4416 (1.8942/0.6698)	mem 16099MB
[2025-01-18 06:56:41 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][140/312]	eta 0:01:24 lr 0.001206	time 0.5407 (0.4886)	model_time 0.5403 (0.4745)	loss 3.5593 (3.1010)	grad_norm 6.0312 (1.9267/0.7599)	mem 16099MB
[2025-01-18 06:56:46 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][150/312]	eta 0:01:18 lr 0.001206	time 0.4474 (0.4868)	model_time 0.4470 (0.4736)	loss 3.0587 (3.0973)	grad_norm 2.3194 (1.9379/0.7625)	mem 16099MB
[2025-01-18 06:56:50 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][160/312]	eta 0:01:13 lr 0.001205	time 0.5415 (0.4860)	model_time 0.5414 (0.4735)	loss 2.9436 (3.0928)	grad_norm 1.5713 (1.9420/0.7591)	mem 16099MB
[2025-01-18 06:56:55 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][170/312]	eta 0:01:08 lr 0.001204	time 0.4522 (0.4845)	model_time 0.4520 (0.4729)	loss 2.9358 (3.0950)	grad_norm 1.9443 (1.9837/0.7846)	mem 16099MB
[2025-01-18 06:57:00 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][180/312]	eta 0:01:03 lr 0.001204	time 0.4577 (0.4838)	model_time 0.4572 (0.4727)	loss 3.2828 (3.0739)	grad_norm 5.5323 (2.1018/1.0930)	mem 16099MB
[2025-01-18 06:57:04 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][190/312]	eta 0:00:58 lr 0.001203	time 0.4664 (0.4823)	model_time 0.4659 (0.4718)	loss 2.8184 (3.0660)	grad_norm 2.1719 (2.1563/1.1288)	mem 16099MB
[2025-01-18 06:57:09 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][200/312]	eta 0:00:53 lr 0.001203	time 0.4503 (0.4809)	model_time 0.4501 (0.4709)	loss 3.8706 (3.0634)	grad_norm 1.5764 (2.1381/1.1080)	mem 16099MB
[2025-01-18 06:57:13 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][210/312]	eta 0:00:48 lr 0.001202	time 0.4780 (0.4799)	model_time 0.4778 (0.4703)	loss 3.3982 (3.0668)	grad_norm 1.4871 (2.1402/1.0941)	mem 16099MB
[2025-01-18 06:57:18 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][220/312]	eta 0:00:44 lr 0.001201	time 0.4530 (0.4797)	model_time 0.4528 (0.4705)	loss 3.4437 (3.0751)	grad_norm 1.3740 (2.1229/1.0841)	mem 16099MB
[2025-01-18 06:57:23 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][230/312]	eta 0:00:39 lr 0.001201	time 0.5313 (0.4792)	model_time 0.5311 (0.4705)	loss 3.0432 (3.0726)	grad_norm 3.6139 (2.1001/1.0769)	mem 16099MB
[2025-01-18 06:57:27 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][240/312]	eta 0:00:34 lr 0.001200	time 0.4490 (0.4784)	model_time 0.4488 (0.4699)	loss 2.3868 (3.0864)	grad_norm 2.6357 (2.1089/1.0641)	mem 16099MB
[2025-01-18 06:57:32 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][250/312]	eta 0:00:29 lr 0.001200	time 0.5361 (0.4783)	model_time 0.5357 (0.4702)	loss 3.5057 (3.0955)	grad_norm 1.4922 (2.0995/1.0505)	mem 16099MB
[2025-01-18 06:57:37 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][260/312]	eta 0:00:24 lr 0.001199	time 0.4519 (0.4785)	model_time 0.4514 (0.4707)	loss 2.0812 (3.0889)	grad_norm 3.2396 (2.1045/1.0437)	mem 16099MB
[2025-01-18 06:57:42 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][270/312]	eta 0:00:20 lr 0.001198	time 0.4816 (0.4780)	model_time 0.4812 (0.4704)	loss 3.2566 (3.0858)	grad_norm 2.5242 (2.1127/1.0378)	mem 16099MB
[2025-01-18 06:57:46 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][280/312]	eta 0:00:15 lr 0.001198	time 0.4577 (0.4777)	model_time 0.4575 (0.4705)	loss 2.5806 (3.0936)	grad_norm 4.2786 (2.1407/1.0566)	mem 16099MB
[2025-01-18 06:57:51 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][290/312]	eta 0:00:10 lr 0.001197	time 0.4462 (0.4777)	model_time 0.4457 (0.4706)	loss 3.2757 (3.0907)	grad_norm 1.3982 (2.1484/1.0715)	mem 16099MB
[2025-01-18 06:57:56 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][300/312]	eta 0:00:05 lr 0.001196	time 0.4372 (0.4771)	model_time 0.4370 (0.4703)	loss 3.2264 (3.0902)	grad_norm 0.7343 (2.1202/1.0663)	mem 16099MB
[2025-01-18 06:58:00 internimage_t_1k_224] (main.py 510): INFO Train: [190/300][310/312]	eta 0:00:00 lr 0.001196	time 0.4383 (0.4760)	model_time 0.4382 (0.4694)	loss 3.4414 (3.0906)	grad_norm 1.1855 (2.1092/1.0703)	mem 16099MB
[2025-01-18 06:58:00 internimage_t_1k_224] (main.py 519): INFO EPOCH 190 training takes 0:02:28
[2025-01-18 06:58:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_190.pth saving......
[2025-01-18 06:58:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_190.pth saved !!!
[2025-01-18 06:58:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.914 (7.914)	Loss 0.7764 (0.7764)	Acc@1 83.374 (83.374)	Acc@5 96.875 (96.875)	Mem 16099MB
[2025-01-18 06:58:13 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.068)	Loss 1.0530 (0.8913)	Acc@1 75.562 (80.677)	Acc@5 93.896 (95.459)	Mem 16099MB
[2025-01-18 06:58:13 internimage_t_1k_224] (main.py 575): INFO [Epoch:190] * Acc@1 80.624 Acc@5 95.477
[2025-01-18 06:58:13 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.6%
[2025-01-18 06:58:13 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.98%
[2025-01-18 06:58:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.524 (8.524)	Loss 0.7937 (0.7937)	Acc@1 84.937 (84.937)	Acc@5 97.461 (97.461)	Mem 16099MB
[2025-01-18 06:58:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.138)	Loss 1.0618 (0.9131)	Acc@1 77.710 (82.138)	Acc@5 94.702 (96.023)	Mem 16099MB
[2025-01-18 06:58:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:190] * Acc@1 82.020 Acc@5 96.063
[2025-01-18 06:58:26 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.0%
[2025-01-18 06:58:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 06:58:28 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 06:58:28 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.02%
[2025-01-18 06:58:30 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][0/312]	eta 0:13:58 lr 0.001196	time 2.6889 (2.6889)	model_time 0.4802 (0.4802)	loss 2.9754 (2.9754)	grad_norm 1.1000 (1.1000/0.0000)	mem 16099MB
[2025-01-18 06:58:35 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][10/312]	eta 0:03:26 lr 0.001195	time 0.4473 (0.6826)	model_time 0.4471 (0.4815)	loss 3.3865 (3.1442)	grad_norm 1.3807 (2.0942/0.9331)	mem 16099MB
[2025-01-18 06:58:40 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][20/312]	eta 0:02:47 lr 0.001195	time 0.4468 (0.5753)	model_time 0.4466 (0.4698)	loss 3.1992 (2.9735)	grad_norm 1.1855 (2.1051/0.9203)	mem 16099MB
[2025-01-18 06:58:45 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][30/312]	eta 0:02:34 lr 0.001194	time 0.4826 (0.5464)	model_time 0.4824 (0.4749)	loss 3.7720 (3.0668)	grad_norm 4.6635 (2.3180/1.0967)	mem 16099MB
[2025-01-18 06:58:49 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][40/312]	eta 0:02:22 lr 0.001193	time 0.4670 (0.5250)	model_time 0.4668 (0.4708)	loss 3.9041 (3.1364)	grad_norm 3.1717 (2.5510/1.2710)	mem 16099MB
[2025-01-18 06:58:54 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][50/312]	eta 0:02:14 lr 0.001193	time 0.5283 (0.5149)	model_time 0.5270 (0.4712)	loss 3.3008 (3.0659)	grad_norm 1.0500 (2.5072/1.2196)	mem 16099MB
[2025-01-18 06:58:59 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][60/312]	eta 0:02:08 lr 0.001192	time 0.5340 (0.5101)	model_time 0.5338 (0.4735)	loss 2.9553 (3.0412)	grad_norm 0.9244 (2.4000/1.1686)	mem 16099MB
[2025-01-18 06:59:03 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][70/312]	eta 0:02:01 lr 0.001192	time 0.4387 (0.5021)	model_time 0.4385 (0.4706)	loss 3.1910 (3.0072)	grad_norm 5.3807 (2.3968/1.2160)	mem 16099MB
[2025-01-18 06:59:08 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][80/312]	eta 0:01:55 lr 0.001191	time 0.5712 (0.4976)	model_time 0.5710 (0.4699)	loss 3.6236 (3.0229)	grad_norm 5.2826 (2.3844/1.2233)	mem 16099MB
[2025-01-18 06:59:13 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][90/312]	eta 0:01:49 lr 0.001190	time 0.4654 (0.4951)	model_time 0.4652 (0.4704)	loss 3.6196 (3.0196)	grad_norm 2.0926 (2.4257/1.2065)	mem 16099MB
[2025-01-18 06:59:17 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][100/312]	eta 0:01:44 lr 0.001190	time 0.4461 (0.4907)	model_time 0.4459 (0.4685)	loss 2.9420 (2.9804)	grad_norm 1.2527 (2.3944/1.1722)	mem 16099MB
[2025-01-18 06:59:22 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][110/312]	eta 0:01:38 lr 0.001189	time 0.4596 (0.4898)	model_time 0.4594 (0.4696)	loss 3.2367 (2.9763)	grad_norm 1.6510 (2.3037/1.1630)	mem 16099MB
[2025-01-18 06:59:27 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][120/312]	eta 0:01:33 lr 0.001189	time 0.4576 (0.4869)	model_time 0.4575 (0.4683)	loss 2.8673 (2.9788)	grad_norm 1.7546 (2.2848/1.1303)	mem 16099MB
[2025-01-18 06:59:31 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][130/312]	eta 0:01:28 lr 0.001188	time 0.4517 (0.4852)	model_time 0.4515 (0.4680)	loss 2.2945 (2.9882)	grad_norm 0.9412 (2.2798/1.1041)	mem 16099MB
[2025-01-18 06:59:36 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][140/312]	eta 0:01:23 lr 0.001187	time 0.4521 (0.4837)	model_time 0.4519 (0.4677)	loss 2.7790 (2.9785)	grad_norm 0.7596 (2.2197/1.0993)	mem 16099MB
[2025-01-18 06:59:41 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][150/312]	eta 0:01:18 lr 0.001187	time 0.5558 (0.4840)	model_time 0.5554 (0.4690)	loss 3.8524 (2.9861)	grad_norm 1.8136 (2.1928/1.0750)	mem 16099MB
[2025-01-18 06:59:45 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][160/312]	eta 0:01:13 lr 0.001186	time 0.4388 (0.4820)	model_time 0.4387 (0.4680)	loss 3.0557 (2.9972)	grad_norm 1.1984 (2.1924/1.1133)	mem 16099MB
[2025-01-18 06:59:50 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][170/312]	eta 0:01:08 lr 0.001186	time 0.4509 (0.4805)	model_time 0.4507 (0.4672)	loss 2.1567 (2.9920)	grad_norm 1.7702 (2.1569/1.0939)	mem 16099MB
[2025-01-18 06:59:55 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][180/312]	eta 0:01:03 lr 0.001185	time 0.7494 (0.4819)	model_time 0.7493 (0.4692)	loss 2.5664 (2.9901)	grad_norm 1.6323 (2.1405/1.0781)	mem 16099MB
[2025-01-18 07:00:00 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][190/312]	eta 0:00:58 lr 0.001184	time 0.4539 (0.4811)	model_time 0.4536 (0.4691)	loss 3.0844 (2.9887)	grad_norm 1.6034 (2.1481/1.0712)	mem 16099MB
[2025-01-18 07:00:04 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][200/312]	eta 0:00:53 lr 0.001184	time 0.4442 (0.4816)	model_time 0.4441 (0.4702)	loss 2.9348 (2.9840)	grad_norm 2.5325 (2.1445/1.0514)	mem 16099MB
[2025-01-18 07:00:09 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][210/312]	eta 0:00:49 lr 0.001183	time 0.5484 (0.4814)	model_time 0.5482 (0.4705)	loss 3.2508 (2.9936)	grad_norm 2.1570 (2.1419/1.0350)	mem 16099MB
[2025-01-18 07:00:14 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][220/312]	eta 0:00:44 lr 0.001182	time 0.4847 (0.4803)	model_time 0.4845 (0.4699)	loss 2.0801 (3.0072)	grad_norm 2.7493 (2.1247/1.0278)	mem 16099MB
[2025-01-18 07:00:18 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][230/312]	eta 0:00:39 lr 0.001182	time 0.4708 (0.4797)	model_time 0.4706 (0.4697)	loss 3.0896 (3.0095)	grad_norm 3.7937 (2.1395/1.0267)	mem 16099MB
[2025-01-18 07:00:23 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][240/312]	eta 0:00:34 lr 0.001181	time 0.4536 (0.4786)	model_time 0.4534 (0.4690)	loss 1.8722 (3.0108)	grad_norm 1.2075 (2.1437/1.0257)	mem 16099MB
[2025-01-18 07:00:28 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][250/312]	eta 0:00:29 lr 0.001181	time 0.4579 (0.4784)	model_time 0.4577 (0.4691)	loss 2.9980 (3.0140)	grad_norm 1.3627 (2.1576/1.0233)	mem 16099MB
[2025-01-18 07:00:32 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][260/312]	eta 0:00:24 lr 0.001180	time 0.4480 (0.4780)	model_time 0.4478 (0.4690)	loss 1.8472 (3.0048)	grad_norm 2.0013 (2.1469/1.0081)	mem 16099MB
[2025-01-18 07:00:37 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][270/312]	eta 0:00:20 lr 0.001179	time 0.4436 (0.4781)	model_time 0.4434 (0.4695)	loss 2.0506 (3.0132)	grad_norm 1.7678 (2.1459/1.0046)	mem 16099MB
[2025-01-18 07:00:42 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][280/312]	eta 0:00:15 lr 0.001179	time 0.4626 (0.4773)	model_time 0.4624 (0.4689)	loss 3.1869 (3.0200)	grad_norm 5.5287 (2.1808/1.0600)	mem 16099MB
[2025-01-18 07:00:47 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][290/312]	eta 0:00:10 lr 0.001178	time 0.4328 (0.4775)	model_time 0.4326 (0.4695)	loss 2.7063 (3.0173)	grad_norm 2.7326 (2.1918/1.0485)	mem 16099MB
[2025-01-18 07:00:51 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][300/312]	eta 0:00:05 lr 0.001178	time 0.4355 (0.4771)	model_time 0.4353 (0.4693)	loss 3.5119 (3.0179)	grad_norm 1.0461 (2.1861/1.0374)	mem 16099MB
[2025-01-18 07:00:56 internimage_t_1k_224] (main.py 510): INFO Train: [191/300][310/312]	eta 0:00:00 lr 0.001177	time 0.4407 (0.4761)	model_time 0.4406 (0.4685)	loss 3.9391 (3.0233)	grad_norm 2.2290 (2.1755/1.0304)	mem 16099MB
[2025-01-18 07:00:56 internimage_t_1k_224] (main.py 519): INFO EPOCH 191 training takes 0:02:28
[2025-01-18 07:00:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_191.pth saving......
[2025-01-18 07:00:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_191.pth saved !!!
[2025-01-18 07:01:05 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.603 (7.603)	Loss 0.7712 (0.7712)	Acc@1 83.667 (83.667)	Acc@5 97.119 (97.119)	Mem 16099MB
[2025-01-18 07:01:09 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.029)	Loss 1.0571 (0.9044)	Acc@1 76.685 (80.759)	Acc@5 93.872 (95.534)	Mem 16099MB
[2025-01-18 07:01:09 internimage_t_1k_224] (main.py 575): INFO [Epoch:191] * Acc@1 80.646 Acc@5 95.549
[2025-01-18 07:01:09 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.6%
[2025-01-18 07:01:09 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 80.98%
[2025-01-18 07:01:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.555 (8.555)	Loss 0.7932 (0.7932)	Acc@1 85.059 (85.059)	Acc@5 97.461 (97.461)	Mem 16099MB
[2025-01-18 07:01:21 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.140)	Loss 1.0600 (0.9120)	Acc@1 77.856 (82.158)	Acc@5 94.678 (96.025)	Mem 16099MB
[2025-01-18 07:01:21 internimage_t_1k_224] (main.py 575): INFO [Epoch:191] * Acc@1 82.042 Acc@5 96.061
[2025-01-18 07:01:21 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.0%
[2025-01-18 07:01:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:01:23 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:01:23 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.04%
[2025-01-18 07:01:25 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][0/312]	eta 0:11:14 lr 0.001177	time 2.1607 (2.1607)	model_time 0.5856 (0.5856)	loss 2.0591 (2.0591)	grad_norm 1.6999 (1.6999/0.0000)	mem 16099MB
[2025-01-18 07:01:30 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][10/312]	eta 0:03:08 lr 0.001176	time 0.4528 (0.6251)	model_time 0.4526 (0.4817)	loss 3.4362 (2.7253)	grad_norm 1.3141 (2.0218/0.7145)	mem 16099MB
[2025-01-18 07:01:34 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][20/312]	eta 0:02:40 lr 0.001176	time 0.4429 (0.5492)	model_time 0.4427 (0.4739)	loss 2.3121 (2.8514)	grad_norm 1.1515 (1.8581/0.6856)	mem 16099MB
[2025-01-18 07:01:39 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][30/312]	eta 0:02:26 lr 0.001175	time 0.4514 (0.5205)	model_time 0.4512 (0.4694)	loss 2.0633 (2.8622)	grad_norm 1.2751 (2.0481/0.9850)	mem 16099MB
[2025-01-18 07:01:43 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][40/312]	eta 0:02:17 lr 0.001175	time 0.5394 (0.5065)	model_time 0.5389 (0.4677)	loss 3.0360 (2.9561)	grad_norm 1.6451 (1.9389/0.9272)	mem 16099MB
[2025-01-18 07:01:48 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][50/312]	eta 0:02:10 lr 0.001174	time 0.4536 (0.4983)	model_time 0.4534 (0.4671)	loss 3.1201 (2.9591)	grad_norm 3.1285 (2.0992/1.0573)	mem 16099MB
[2025-01-18 07:01:53 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][60/312]	eta 0:02:04 lr 0.001173	time 0.4575 (0.4928)	model_time 0.4570 (0.4666)	loss 3.6121 (2.9893)	grad_norm 1.1584 (2.1471/1.0706)	mem 16099MB
[2025-01-18 07:01:57 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][70/312]	eta 0:01:57 lr 0.001173	time 0.4594 (0.4875)	model_time 0.4592 (0.4649)	loss 3.0337 (3.0286)	grad_norm 1.8972 (2.1064/1.0293)	mem 16099MB
[2025-01-18 07:02:02 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][80/312]	eta 0:01:52 lr 0.001172	time 0.4555 (0.4846)	model_time 0.4553 (0.4648)	loss 3.2149 (3.0143)	grad_norm 1.3438 (2.0700/1.0188)	mem 16099MB
[2025-01-18 07:02:07 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][90/312]	eta 0:01:46 lr 0.001172	time 0.4514 (0.4818)	model_time 0.4512 (0.4642)	loss 3.7188 (3.0401)	grad_norm 1.7489 (2.0467/0.9856)	mem 16099MB
[2025-01-18 07:02:11 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][100/312]	eta 0:01:41 lr 0.001171	time 0.4447 (0.4799)	model_time 0.4442 (0.4640)	loss 1.9555 (3.0505)	grad_norm 1.9330 (2.0466/0.9517)	mem 16099MB
[2025-01-18 07:02:16 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][110/312]	eta 0:01:36 lr 0.001170	time 0.4573 (0.4791)	model_time 0.4571 (0.4645)	loss 3.4057 (3.0471)	grad_norm 3.4091 (2.0727/0.9750)	mem 16099MB
[2025-01-18 07:02:21 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][120/312]	eta 0:01:31 lr 0.001170	time 0.4473 (0.4791)	model_time 0.4471 (0.4657)	loss 3.0163 (3.0399)	grad_norm 1.4997 (2.1042/0.9798)	mem 16099MB
[2025-01-18 07:02:26 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][130/312]	eta 0:01:27 lr 0.001169	time 0.5351 (0.4799)	model_time 0.5349 (0.4676)	loss 3.4116 (3.0451)	grad_norm 1.8135 (2.1445/0.9809)	mem 16099MB
[2025-01-18 07:02:30 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][140/312]	eta 0:01:22 lr 0.001169	time 0.4576 (0.4794)	model_time 0.4572 (0.4679)	loss 3.0369 (3.0508)	grad_norm 0.9990 (2.1440/0.9581)	mem 16099MB
[2025-01-18 07:02:35 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][150/312]	eta 0:01:17 lr 0.001168	time 0.4483 (0.4784)	model_time 0.4481 (0.4676)	loss 3.5260 (3.0736)	grad_norm 2.4563 (2.1742/0.9546)	mem 16099MB
[2025-01-18 07:02:40 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][160/312]	eta 0:01:12 lr 0.001167	time 0.5483 (0.4781)	model_time 0.5482 (0.4680)	loss 2.7797 (3.0808)	grad_norm 1.8941 (2.1632/0.9375)	mem 16099MB
[2025-01-18 07:02:44 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][170/312]	eta 0:01:07 lr 0.001167	time 0.4576 (0.4778)	model_time 0.4571 (0.4682)	loss 3.7316 (3.0700)	grad_norm 1.1934 (2.1330/0.9265)	mem 16099MB
[2025-01-18 07:02:49 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][180/312]	eta 0:01:02 lr 0.001166	time 0.4475 (0.4765)	model_time 0.4473 (0.4674)	loss 3.0557 (3.0792)	grad_norm 2.8650 (2.1139/0.9161)	mem 16099MB
[2025-01-18 07:02:53 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][190/312]	eta 0:00:57 lr 0.001166	time 0.4593 (0.4754)	model_time 0.4591 (0.4668)	loss 3.4503 (3.0836)	grad_norm 2.9840 (2.1359/0.9213)	mem 16099MB
[2025-01-18 07:02:58 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][200/312]	eta 0:00:53 lr 0.001165	time 0.4687 (0.4746)	model_time 0.4685 (0.4664)	loss 3.2589 (3.0780)	grad_norm 0.9895 (2.1326/0.9147)	mem 16099MB
[2025-01-18 07:03:03 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][210/312]	eta 0:00:48 lr 0.001164	time 0.5453 (0.4745)	model_time 0.5446 (0.4667)	loss 1.9772 (3.0820)	grad_norm 1.5398 (2.1300/0.9025)	mem 16099MB
[2025-01-18 07:03:07 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][220/312]	eta 0:00:43 lr 0.001164	time 0.4517 (0.4735)	model_time 0.4515 (0.4661)	loss 3.6559 (3.0851)	grad_norm 1.4088 (2.1225/0.8885)	mem 16099MB
[2025-01-18 07:03:12 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][230/312]	eta 0:00:38 lr 0.001163	time 0.5395 (0.4742)	model_time 0.5391 (0.4670)	loss 3.0812 (3.0840)	grad_norm 2.1207 (2.1190/0.8758)	mem 16099MB
[2025-01-18 07:03:17 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][240/312]	eta 0:00:34 lr 0.001163	time 0.4515 (0.4734)	model_time 0.4510 (0.4665)	loss 3.2857 (3.0845)	grad_norm 3.4555 (2.1372/0.8832)	mem 16099MB
[2025-01-18 07:03:21 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][250/312]	eta 0:00:29 lr 0.001162	time 0.4409 (0.4725)	model_time 0.4407 (0.4659)	loss 3.8747 (3.0873)	grad_norm 1.6300 (2.1339/0.8827)	mem 16099MB
[2025-01-18 07:03:26 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][260/312]	eta 0:00:24 lr 0.001161	time 0.4638 (0.4723)	model_time 0.4636 (0.4659)	loss 3.1594 (3.0826)	grad_norm 1.9541 (2.1126/0.8747)	mem 16099MB
[2025-01-18 07:03:31 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][270/312]	eta 0:00:19 lr 0.001161	time 0.5007 (0.4720)	model_time 0.5004 (0.4658)	loss 3.3587 (3.0781)	grad_norm 1.2361 (2.1025/0.8705)	mem 16099MB
[2025-01-18 07:03:35 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][280/312]	eta 0:00:15 lr 0.001160	time 0.4501 (0.4720)	model_time 0.4499 (0.4661)	loss 3.1844 (3.0759)	grad_norm 4.2234 (2.1096/0.8748)	mem 16099MB
[2025-01-18 07:03:40 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][290/312]	eta 0:00:10 lr 0.001160	time 0.4344 (0.4720)	model_time 0.4342 (0.4662)	loss 2.3372 (3.0714)	grad_norm 1.4252 (2.1264/0.8791)	mem 16099MB
[2025-01-18 07:03:45 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][300/312]	eta 0:00:05 lr 0.001159	time 0.4378 (0.4721)	model_time 0.4377 (0.4665)	loss 3.2079 (3.0715)	grad_norm 1.7575 (2.1139/0.8732)	mem 16099MB
[2025-01-18 07:03:49 internimage_t_1k_224] (main.py 510): INFO Train: [192/300][310/312]	eta 0:00:00 lr 0.001158	time 0.4380 (0.4712)	model_time 0.4377 (0.4657)	loss 3.3619 (3.0799)	grad_norm 1.9684 (2.1262/0.8925)	mem 16099MB
[2025-01-18 07:03:50 internimage_t_1k_224] (main.py 519): INFO EPOCH 192 training takes 0:02:26
[2025-01-18 07:03:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_192.pth saving......
[2025-01-18 07:03:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_192.pth saved !!!
[2025-01-18 07:03:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.662 (7.662)	Loss 0.7862 (0.7862)	Acc@1 83.496 (83.496)	Acc@5 97.070 (97.070)	Mem 16099MB
[2025-01-18 07:04:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.020)	Loss 1.0439 (0.8914)	Acc@1 76.831 (81.168)	Acc@5 94.385 (95.696)	Mem 16099MB
[2025-01-18 07:04:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:192] * Acc@1 81.030 Acc@5 95.717
[2025-01-18 07:04:02 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.0%
[2025-01-18 07:04:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 07:04:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 07:04:03 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.03%
[2025-01-18 07:04:11 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.707 (7.707)	Loss 0.7926 (0.7926)	Acc@1 84.985 (84.985)	Acc@5 97.461 (97.461)	Mem 16099MB
[2025-01-18 07:04:15 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.052)	Loss 1.0583 (0.9110)	Acc@1 77.979 (82.189)	Acc@5 94.727 (96.045)	Mem 16099MB
[2025-01-18 07:04:15 internimage_t_1k_224] (main.py 575): INFO [Epoch:192] * Acc@1 82.072 Acc@5 96.079
[2025-01-18 07:04:15 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.1%
[2025-01-18 07:04:15 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:04:16 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:04:16 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.07%
[2025-01-18 07:04:18 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][0/312]	eta 0:09:58 lr 0.001158	time 1.9168 (1.9168)	model_time 0.4880 (0.4880)	loss 2.4957 (2.4957)	grad_norm 2.7597 (2.7597/0.0000)	mem 16099MB
[2025-01-18 07:04:23 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][10/312]	eta 0:03:03 lr 0.001158	time 0.4488 (0.6080)	model_time 0.4487 (0.4778)	loss 2.4347 (2.8650)	grad_norm 3.1404 (2.7284/1.1131)	mem 16099MB
[2025-01-18 07:04:28 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][20/312]	eta 0:02:39 lr 0.001157	time 0.5374 (0.5466)	model_time 0.5372 (0.4782)	loss 2.5672 (3.0100)	grad_norm 1.1379 (2.5280/1.0502)	mem 16099MB
[2025-01-18 07:04:32 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][30/312]	eta 0:02:26 lr 0.001156	time 0.4550 (0.5211)	model_time 0.4548 (0.4746)	loss 3.3894 (3.0098)	grad_norm 4.5345 (2.6720/1.1775)	mem 16099MB
[2025-01-18 07:04:37 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][40/312]	eta 0:02:18 lr 0.001156	time 0.4457 (0.5075)	model_time 0.4454 (0.4723)	loss 2.4926 (3.0203)	grad_norm 1.8013 (2.8058/1.2925)	mem 16099MB
[2025-01-18 07:04:42 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][50/312]	eta 0:02:11 lr 0.001155	time 0.4400 (0.5007)	model_time 0.4397 (0.4723)	loss 3.7283 (3.0292)	grad_norm 2.0588 (2.6127/1.2517)	mem 16099MB
[2025-01-18 07:04:46 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][60/312]	eta 0:02:04 lr 0.001155	time 0.4447 (0.4937)	model_time 0.4445 (0.4699)	loss 2.5123 (3.0105)	grad_norm 1.4263 (2.4649/1.2096)	mem 16099MB
[2025-01-18 07:04:51 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][70/312]	eta 0:01:58 lr 0.001154	time 0.4456 (0.4893)	model_time 0.4454 (0.4688)	loss 3.0251 (2.9905)	grad_norm 1.7554 (2.4300/1.1647)	mem 16099MB
[2025-01-18 07:04:56 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][80/312]	eta 0:01:52 lr 0.001153	time 0.4530 (0.4864)	model_time 0.4528 (0.4684)	loss 3.2426 (3.0278)	grad_norm 0.9807 (2.3750/1.1299)	mem 16099MB
[2025-01-18 07:05:00 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][90/312]	eta 0:01:47 lr 0.001153	time 0.4507 (0.4852)	model_time 0.4505 (0.4692)	loss 3.4109 (3.0307)	grad_norm 1.9666 (2.3122/1.1001)	mem 16099MB
[2025-01-18 07:05:05 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][100/312]	eta 0:01:42 lr 0.001152	time 0.4554 (0.4837)	model_time 0.4547 (0.4692)	loss 3.1860 (3.0292)	grad_norm 2.4920 (2.2430/1.0764)	mem 16099MB
[2025-01-18 07:05:10 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][110/312]	eta 0:01:37 lr 0.001152	time 0.4490 (0.4826)	model_time 0.4488 (0.4694)	loss 3.2266 (3.0092)	grad_norm 1.1476 (2.2135/1.0560)	mem 16099MB
[2025-01-18 07:05:15 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][120/312]	eta 0:01:32 lr 0.001151	time 0.4520 (0.4810)	model_time 0.4518 (0.4688)	loss 2.3794 (3.0024)	grad_norm 1.0363 (2.1531/1.0437)	mem 16099MB
[2025-01-18 07:05:19 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][130/312]	eta 0:01:27 lr 0.001150	time 0.4536 (0.4799)	model_time 0.4534 (0.4687)	loss 3.8438 (3.0135)	grad_norm 1.0396 (2.1505/1.0252)	mem 16099MB
[2025-01-18 07:05:24 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][140/312]	eta 0:01:22 lr 0.001150	time 0.4563 (0.4800)	model_time 0.4561 (0.4695)	loss 3.2158 (3.0221)	grad_norm 1.4996 (2.1429/0.9999)	mem 16099MB
[2025-01-18 07:05:29 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][150/312]	eta 0:01:17 lr 0.001149	time 0.4513 (0.4796)	model_time 0.4511 (0.4697)	loss 3.2317 (3.0281)	grad_norm 3.0255 (2.1803/1.0278)	mem 16099MB
[2025-01-18 07:05:33 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][160/312]	eta 0:01:12 lr 0.001149	time 0.4636 (0.4788)	model_time 0.4634 (0.4696)	loss 3.4267 (3.0150)	grad_norm 2.3369 (2.2131/1.0466)	mem 16099MB
[2025-01-18 07:05:38 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][170/312]	eta 0:01:07 lr 0.001148	time 0.4623 (0.4780)	model_time 0.4622 (0.4693)	loss 3.4578 (3.0205)	grad_norm 5.6817 (2.2185/1.0707)	mem 16099MB
[2025-01-18 07:05:43 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][180/312]	eta 0:01:02 lr 0.001147	time 0.4565 (0.4772)	model_time 0.4563 (0.4689)	loss 2.5373 (3.0198)	grad_norm 1.3782 (2.2187/1.0576)	mem 16099MB
[2025-01-18 07:05:47 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][190/312]	eta 0:00:58 lr 0.001147	time 0.4678 (0.4762)	model_time 0.4675 (0.4684)	loss 3.4352 (3.0240)	grad_norm 2.2694 (2.2174/1.0466)	mem 16099MB
[2025-01-18 07:05:52 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][200/312]	eta 0:00:53 lr 0.001146	time 0.4478 (0.4761)	model_time 0.4474 (0.4686)	loss 3.1392 (3.0126)	grad_norm 1.4387 (2.1963/1.0292)	mem 16099MB
[2025-01-18 07:05:57 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][210/312]	eta 0:00:48 lr 0.001146	time 0.4557 (0.4752)	model_time 0.4553 (0.4681)	loss 2.6217 (3.0114)	grad_norm 1.1756 (2.1826/1.0269)	mem 16099MB
[2025-01-18 07:06:01 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][220/312]	eta 0:00:43 lr 0.001145	time 0.4489 (0.4747)	model_time 0.4488 (0.4679)	loss 2.2121 (3.0286)	grad_norm 4.7261 (2.1912/1.0296)	mem 16099MB
[2025-01-18 07:06:06 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][230/312]	eta 0:00:38 lr 0.001145	time 0.4442 (0.4741)	model_time 0.4440 (0.4675)	loss 3.4103 (3.0279)	grad_norm 1.9375 (2.1884/1.0288)	mem 16099MB
[2025-01-18 07:06:10 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][240/312]	eta 0:00:34 lr 0.001144	time 0.4494 (0.4737)	model_time 0.4492 (0.4674)	loss 2.1823 (3.0253)	grad_norm 2.1229 (2.1828/1.0154)	mem 16099MB
[2025-01-18 07:06:15 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][250/312]	eta 0:00:29 lr 0.001143	time 0.4363 (0.4735)	model_time 0.4358 (0.4674)	loss 3.0710 (3.0266)	grad_norm 1.6647 (2.1607/1.0036)	mem 16099MB
[2025-01-18 07:06:20 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][260/312]	eta 0:00:24 lr 0.001143	time 0.4441 (0.4738)	model_time 0.4438 (0.4680)	loss 2.9951 (3.0231)	grad_norm 2.9887 (2.1944/1.0518)	mem 16099MB
[2025-01-18 07:06:25 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][270/312]	eta 0:00:19 lr 0.001142	time 0.4491 (0.4736)	model_time 0.4486 (0.4680)	loss 2.0524 (3.0219)	grad_norm 1.8497 (2.1958/1.0478)	mem 16099MB
[2025-01-18 07:06:29 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][280/312]	eta 0:00:15 lr 0.001142	time 0.4530 (0.4736)	model_time 0.4526 (0.4681)	loss 3.7483 (3.0191)	grad_norm 2.4520 (2.2115/1.0478)	mem 16099MB
[2025-01-18 07:06:34 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][290/312]	eta 0:00:10 lr 0.001141	time 0.4562 (0.4732)	model_time 0.4560 (0.4679)	loss 2.4730 (3.0139)	grad_norm 1.7609 (2.2173/1.0339)	mem 16099MB
[2025-01-18 07:06:39 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][300/312]	eta 0:00:05 lr 0.001140	time 0.4382 (0.4727)	model_time 0.4381 (0.4676)	loss 2.8587 (3.0268)	grad_norm 2.3258 (2.2179/1.0246)	mem 16099MB
[2025-01-18 07:06:43 internimage_t_1k_224] (main.py 510): INFO Train: [193/300][310/312]	eta 0:00:00 lr 0.001140	time 0.4517 (0.4721)	model_time 0.4516 (0.4671)	loss 3.3917 (3.0261)	grad_norm 3.8621 (2.2147/1.0159)	mem 16099MB
[2025-01-18 07:06:44 internimage_t_1k_224] (main.py 519): INFO EPOCH 193 training takes 0:02:27
[2025-01-18 07:06:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_193.pth saving......
[2025-01-18 07:06:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_193.pth saved !!!
[2025-01-18 07:06:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.389 (7.389)	Loss 0.7842 (0.7842)	Acc@1 83.740 (83.740)	Acc@5 96.875 (96.875)	Mem 16099MB
[2025-01-18 07:06:56 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.995)	Loss 1.0653 (0.9024)	Acc@1 76.196 (80.877)	Acc@5 93.994 (95.561)	Mem 16099MB
[2025-01-18 07:06:56 internimage_t_1k_224] (main.py 575): INFO [Epoch:193] * Acc@1 80.782 Acc@5 95.601
[2025-01-18 07:06:56 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.8%
[2025-01-18 07:06:56 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.03%
[2025-01-18 07:07:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.217 (8.217)	Loss 0.7918 (0.7918)	Acc@1 85.010 (85.010)	Acc@5 97.461 (97.461)	Mem 16099MB
[2025-01-18 07:07:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.125)	Loss 1.0565 (0.9098)	Acc@1 77.881 (82.189)	Acc@5 94.727 (96.056)	Mem 16099MB
[2025-01-18 07:07:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:193] * Acc@1 82.076 Acc@5 96.089
[2025-01-18 07:07:08 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.1%
[2025-01-18 07:07:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:07:10 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:07:10 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.08%
[2025-01-18 07:07:12 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][0/312]	eta 0:11:17 lr 0.001140	time 2.1727 (2.1727)	model_time 0.4660 (0.4660)	loss 3.5279 (3.5279)	grad_norm 1.2482 (1.2482/0.0000)	mem 16099MB
[2025-01-18 07:07:17 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][10/312]	eta 0:03:11 lr 0.001139	time 0.4546 (0.6335)	model_time 0.4545 (0.4780)	loss 3.1983 (3.2086)	grad_norm 1.2241 (1.8538/0.7384)	mem 16099MB
[2025-01-18 07:07:21 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][20/312]	eta 0:02:42 lr 0.001138	time 0.4533 (0.5578)	model_time 0.4531 (0.4762)	loss 3.2484 (3.2708)	grad_norm 2.5494 (1.7839/0.6741)	mem 16099MB
[2025-01-18 07:07:26 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][30/312]	eta 0:02:31 lr 0.001138	time 0.4538 (0.5377)	model_time 0.4534 (0.4823)	loss 3.3931 (3.2000)	grad_norm 1.5718 (1.6967/0.6104)	mem 16099MB
[2025-01-18 07:07:31 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][40/312]	eta 0:02:21 lr 0.001137	time 0.5392 (0.5213)	model_time 0.5388 (0.4793)	loss 1.9235 (3.1007)	grad_norm 1.3400 (1.6963/0.6226)	mem 16099MB
[2025-01-18 07:07:36 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][50/312]	eta 0:02:13 lr 0.001137	time 0.4571 (0.5099)	model_time 0.4566 (0.4761)	loss 3.3959 (3.0674)	grad_norm 1.5497 (1.8587/0.7792)	mem 16099MB
[2025-01-18 07:07:41 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][60/312]	eta 0:02:07 lr 0.001136	time 0.4548 (0.5051)	model_time 0.4547 (0.4767)	loss 3.3389 (3.1266)	grad_norm 3.0217 (1.8838/0.7524)	mem 16099MB
[2025-01-18 07:07:45 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][70/312]	eta 0:02:00 lr 0.001135	time 0.4534 (0.4984)	model_time 0.4533 (0.4740)	loss 2.0972 (3.1135)	grad_norm 1.5378 (1.9132/0.7906)	mem 16099MB
[2025-01-18 07:07:50 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][80/312]	eta 0:01:54 lr 0.001135	time 0.4519 (0.4928)	model_time 0.4515 (0.4714)	loss 3.3932 (3.0969)	grad_norm 1.0918 (1.8937/0.7601)	mem 16099MB
[2025-01-18 07:07:54 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][90/312]	eta 0:01:48 lr 0.001134	time 0.4755 (0.4899)	model_time 0.4753 (0.4707)	loss 3.7545 (3.1084)	grad_norm 2.6930 (1.9768/0.8420)	mem 16099MB
[2025-01-18 07:07:59 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][100/312]	eta 0:01:43 lr 0.001134	time 0.4552 (0.4873)	model_time 0.4550 (0.4701)	loss 2.4225 (3.0864)	grad_norm 1.0198 (1.9489/0.8282)	mem 16099MB
[2025-01-18 07:08:04 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][110/312]	eta 0:01:37 lr 0.001133	time 0.4499 (0.4849)	model_time 0.4497 (0.4691)	loss 2.5862 (3.0913)	grad_norm 2.2649 (1.9591/0.8544)	mem 16099MB
[2025-01-18 07:08:08 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][120/312]	eta 0:01:32 lr 0.001132	time 0.4455 (0.4839)	model_time 0.4451 (0.4694)	loss 3.4222 (3.0988)	grad_norm 2.1251 (1.9911/0.8737)	mem 16099MB
[2025-01-18 07:08:13 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][130/312]	eta 0:01:27 lr 0.001132	time 0.4401 (0.4821)	model_time 0.4398 (0.4686)	loss 3.1595 (3.0985)	grad_norm 3.7143 (2.0338/0.9029)	mem 16099MB
[2025-01-18 07:08:18 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][140/312]	eta 0:01:22 lr 0.001131	time 0.4525 (0.4819)	model_time 0.4522 (0.4694)	loss 3.3491 (3.0980)	grad_norm 3.8128 (2.0754/0.9547)	mem 16099MB
[2025-01-18 07:08:22 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][150/312]	eta 0:01:17 lr 0.001131	time 0.4832 (0.4802)	model_time 0.4828 (0.4685)	loss 3.0582 (3.0995)	grad_norm 2.3887 (2.0743/0.9429)	mem 16099MB
[2025-01-18 07:08:27 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][160/312]	eta 0:01:12 lr 0.001130	time 0.5634 (0.4795)	model_time 0.5629 (0.4685)	loss 3.7841 (3.1052)	grad_norm 2.0123 (2.0591/0.9250)	mem 16099MB
[2025-01-18 07:08:32 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][170/312]	eta 0:01:07 lr 0.001130	time 0.4540 (0.4785)	model_time 0.4534 (0.4681)	loss 2.6137 (3.1053)	grad_norm 1.9431 (2.0320/0.9096)	mem 16099MB
[2025-01-18 07:08:36 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][180/312]	eta 0:01:02 lr 0.001129	time 0.4557 (0.4770)	model_time 0.4555 (0.4672)	loss 3.8210 (3.0916)	grad_norm 1.7843 (2.0292/0.9179)	mem 16099MB
[2025-01-18 07:08:41 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][190/312]	eta 0:00:58 lr 0.001128	time 0.4523 (0.4765)	model_time 0.4521 (0.4672)	loss 2.7740 (3.0900)	grad_norm 1.6767 (2.0537/0.9265)	mem 16099MB
[2025-01-18 07:08:45 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][200/312]	eta 0:00:53 lr 0.001128	time 0.4517 (0.4755)	model_time 0.4511 (0.4666)	loss 3.2006 (3.0882)	grad_norm 1.9035 (2.0601/0.9196)	mem 16099MB
[2025-01-18 07:08:50 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][210/312]	eta 0:00:48 lr 0.001127	time 0.4622 (0.4757)	model_time 0.4620 (0.4672)	loss 3.6297 (3.0938)	grad_norm 1.3775 (2.0561/0.9116)	mem 16099MB
[2025-01-18 07:08:55 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][220/312]	eta 0:00:43 lr 0.001127	time 0.4508 (0.4749)	model_time 0.4504 (0.4668)	loss 3.1048 (3.0958)	grad_norm 1.9946 (2.0511/0.8970)	mem 16099MB
[2025-01-18 07:08:59 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][230/312]	eta 0:00:38 lr 0.001126	time 0.4495 (0.4746)	model_time 0.4493 (0.4668)	loss 3.2591 (3.1042)	grad_norm 3.7050 (2.0623/0.8976)	mem 16099MB
[2025-01-18 07:09:04 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][240/312]	eta 0:00:34 lr 0.001125	time 0.4392 (0.4739)	model_time 0.4388 (0.4665)	loss 2.3723 (3.0911)	grad_norm 1.3722 (2.0521/0.8898)	mem 16099MB
[2025-01-18 07:09:09 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][250/312]	eta 0:00:29 lr 0.001125	time 0.5638 (0.4739)	model_time 0.5636 (0.4667)	loss 3.6320 (3.0886)	grad_norm 1.5571 (2.0254/0.8846)	mem 16099MB
[2025-01-18 07:09:13 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][260/312]	eta 0:00:24 lr 0.001124	time 0.4540 (0.4735)	model_time 0.4534 (0.4666)	loss 3.2561 (3.0860)	grad_norm 1.2368 (2.0221/0.8934)	mem 16099MB
[2025-01-18 07:09:18 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][270/312]	eta 0:00:19 lr 0.001124	time 0.4647 (0.4742)	model_time 0.4643 (0.4675)	loss 3.5979 (3.0876)	grad_norm 1.3047 (2.0237/0.8898)	mem 16099MB
[2025-01-18 07:09:23 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][280/312]	eta 0:00:15 lr 0.001123	time 0.5078 (0.4744)	model_time 0.5076 (0.4680)	loss 3.0809 (3.0894)	grad_norm 4.6645 (2.0341/0.8890)	mem 16099MB
[2025-01-18 07:09:28 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][290/312]	eta 0:00:10 lr 0.001122	time 0.4449 (0.4744)	model_time 0.4447 (0.4682)	loss 2.7394 (3.0883)	grad_norm 1.1690 (2.0451/0.9111)	mem 16099MB
[2025-01-18 07:09:32 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][300/312]	eta 0:00:05 lr 0.001122	time 0.5446 (0.4740)	model_time 0.5445 (0.4680)	loss 3.6130 (3.0898)	grad_norm 1.0804 (2.0628/0.9230)	mem 16099MB
[2025-01-18 07:09:37 internimage_t_1k_224] (main.py 510): INFO Train: [194/300][310/312]	eta 0:00:00 lr 0.001121	time 0.4381 (0.4732)	model_time 0.4380 (0.4673)	loss 3.4615 (3.0991)	grad_norm 4.5267 (2.1020/0.9495)	mem 16099MB
[2025-01-18 07:09:37 internimage_t_1k_224] (main.py 519): INFO EPOCH 194 training takes 0:02:27
[2025-01-18 07:09:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_194.pth saving......
[2025-01-18 07:09:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_194.pth saved !!!
[2025-01-18 07:09:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.430 (7.430)	Loss 0.7838 (0.7838)	Acc@1 84.009 (84.009)	Acc@5 97.021 (97.021)	Mem 16099MB
[2025-01-18 07:09:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.990)	Loss 1.0616 (0.9058)	Acc@1 76.709 (81.070)	Acc@5 93.848 (95.568)	Mem 16099MB
[2025-01-18 07:09:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:194] * Acc@1 80.976 Acc@5 95.587
[2025-01-18 07:09:50 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.0%
[2025-01-18 07:09:50 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.03%
[2025-01-18 07:09:59 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.610 (8.610)	Loss 0.7914 (0.7914)	Acc@1 85.059 (85.059)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 07:10:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.136)	Loss 1.0551 (0.9089)	Acc@1 77.930 (82.229)	Acc@5 94.751 (96.069)	Mem 16099MB
[2025-01-18 07:10:03 internimage_t_1k_224] (main.py 575): INFO [Epoch:194] * Acc@1 82.110 Acc@5 96.101
[2025-01-18 07:10:03 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.1%
[2025-01-18 07:10:03 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:10:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:10:04 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.11%
[2025-01-18 07:10:06 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][0/312]	eta 0:12:55 lr 0.001121	time 2.4845 (2.4845)	model_time 0.4792 (0.4792)	loss 2.2003 (2.2003)	grad_norm 1.4698 (1.4698/0.0000)	mem 16099MB
[2025-01-18 07:10:11 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][10/312]	eta 0:03:17 lr 0.001121	time 0.5554 (0.6528)	model_time 0.5552 (0.4702)	loss 2.0485 (3.0216)	grad_norm 1.5489 (1.6188/0.4924)	mem 16099MB
[2025-01-18 07:10:16 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][20/312]	eta 0:02:43 lr 0.001120	time 0.4481 (0.5610)	model_time 0.4476 (0.4652)	loss 2.8783 (2.9045)	grad_norm 2.6770 (1.9541/0.9389)	mem 16099MB
[2025-01-18 07:10:20 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][30/312]	eta 0:02:29 lr 0.001119	time 0.4592 (0.5315)	model_time 0.4588 (0.4665)	loss 3.2379 (2.9318)	grad_norm 1.8352 (2.0322/0.8595)	mem 16099MB
[2025-01-18 07:10:25 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][40/312]	eta 0:02:20 lr 0.001119	time 0.4441 (0.5163)	model_time 0.4437 (0.4670)	loss 3.1688 (2.9313)	grad_norm 3.2282 (2.1769/0.9715)	mem 16099MB
[2025-01-18 07:10:30 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][50/312]	eta 0:02:12 lr 0.001118	time 0.4555 (0.5061)	model_time 0.4553 (0.4665)	loss 3.2868 (2.9506)	grad_norm 2.7452 (2.3209/1.0709)	mem 16099MB
[2025-01-18 07:10:34 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][60/312]	eta 0:02:05 lr 0.001118	time 0.4439 (0.4979)	model_time 0.4437 (0.4647)	loss 3.1156 (2.9485)	grad_norm 1.3742 (2.2932/1.0118)	mem 16099MB
[2025-01-18 07:10:39 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][70/312]	eta 0:01:59 lr 0.001117	time 0.4534 (0.4924)	model_time 0.4532 (0.4638)	loss 3.5495 (2.9656)	grad_norm 1.6914 (2.2595/0.9640)	mem 16099MB
[2025-01-18 07:10:43 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][80/312]	eta 0:01:53 lr 0.001116	time 0.4649 (0.4880)	model_time 0.4647 (0.4629)	loss 2.8879 (2.9711)	grad_norm 1.3731 (2.2476/0.9368)	mem 16099MB
[2025-01-18 07:10:48 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][90/312]	eta 0:01:47 lr 0.001116	time 0.4567 (0.4857)	model_time 0.4565 (0.4633)	loss 3.0650 (2.9957)	grad_norm 4.8414 (2.2887/0.9544)	mem 16099MB
[2025-01-18 07:10:53 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][100/312]	eta 0:01:42 lr 0.001115	time 0.4634 (0.4834)	model_time 0.4632 (0.4632)	loss 2.6774 (2.9688)	grad_norm 2.5733 (2.3396/0.9342)	mem 16099MB
[2025-01-18 07:10:57 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][110/312]	eta 0:01:37 lr 0.001115	time 0.4445 (0.4822)	model_time 0.4443 (0.4638)	loss 3.3023 (2.9831)	grad_norm 1.8807 (2.3093/0.9183)	mem 16099MB
[2025-01-18 07:11:02 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][120/312]	eta 0:01:32 lr 0.001114	time 0.4558 (0.4810)	model_time 0.4553 (0.4640)	loss 2.1772 (2.9849)	grad_norm 2.0087 (2.2872/0.8924)	mem 16099MB
[2025-01-18 07:11:07 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][130/312]	eta 0:01:27 lr 0.001113	time 0.4326 (0.4809)	model_time 0.4323 (0.4652)	loss 2.7582 (2.9895)	grad_norm 1.4475 (2.2512/0.8798)	mem 16099MB
[2025-01-18 07:11:11 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][140/312]	eta 0:01:22 lr 0.001113	time 0.4480 (0.4795)	model_time 0.4475 (0.4649)	loss 2.7159 (3.0039)	grad_norm 2.8204 (2.2314/0.8726)	mem 16099MB
[2025-01-18 07:11:16 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][150/312]	eta 0:01:17 lr 0.001112	time 0.4502 (0.4797)	model_time 0.4500 (0.4661)	loss 3.2436 (3.0125)	grad_norm 2.4748 (2.2798/0.9208)	mem 16099MB
[2025-01-18 07:11:21 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][160/312]	eta 0:01:12 lr 0.001112	time 0.4495 (0.4789)	model_time 0.4493 (0.4661)	loss 2.3999 (3.0083)	grad_norm 2.1601 (2.2828/0.9019)	mem 16099MB
[2025-01-18 07:11:26 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][170/312]	eta 0:01:07 lr 0.001111	time 0.4671 (0.4787)	model_time 0.4669 (0.4666)	loss 2.5017 (3.0012)	grad_norm 4.6523 (2.2850/0.9049)	mem 16099MB
[2025-01-18 07:11:30 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][180/312]	eta 0:01:03 lr 0.001110	time 0.4443 (0.4788)	model_time 0.4441 (0.4673)	loss 2.9944 (3.0031)	grad_norm 2.4963 (2.2960/0.9150)	mem 16099MB
[2025-01-18 07:11:35 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][190/312]	eta 0:00:58 lr 0.001110	time 0.5303 (0.4788)	model_time 0.5301 (0.4680)	loss 2.7040 (3.0037)	grad_norm 0.7190 (2.2700/0.9151)	mem 16099MB
[2025-01-18 07:11:40 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][200/312]	eta 0:00:53 lr 0.001109	time 0.4832 (0.4783)	model_time 0.4830 (0.4680)	loss 3.3419 (3.0243)	grad_norm 2.3149 (2.2756/0.9098)	mem 16099MB
[2025-01-18 07:11:45 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][210/312]	eta 0:00:48 lr 0.001109	time 0.4713 (0.4776)	model_time 0.4711 (0.4677)	loss 3.3516 (3.0149)	grad_norm 1.8296 (2.3143/0.9713)	mem 16099MB
[2025-01-18 07:11:49 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][220/312]	eta 0:00:43 lr 0.001108	time 0.4439 (0.4767)	model_time 0.4436 (0.4672)	loss 3.6280 (3.0216)	grad_norm 1.9312 (2.2931/0.9605)	mem 16099MB
[2025-01-18 07:11:54 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][230/312]	eta 0:00:39 lr 0.001108	time 0.4524 (0.4767)	model_time 0.4522 (0.4677)	loss 1.9653 (3.0153)	grad_norm 2.4495 (2.2793/0.9499)	mem 16099MB
[2025-01-18 07:11:59 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][240/312]	eta 0:00:34 lr 0.001107	time 0.4563 (0.4763)	model_time 0.4561 (0.4676)	loss 3.8073 (3.0136)	grad_norm 2.1422 (2.2694/0.9480)	mem 16099MB
[2025-01-18 07:12:03 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][250/312]	eta 0:00:29 lr 0.001106	time 0.4523 (0.4756)	model_time 0.4521 (0.4673)	loss 2.3226 (3.0100)	grad_norm 3.3706 (2.2718/0.9570)	mem 16099MB
[2025-01-18 07:12:08 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][260/312]	eta 0:00:24 lr 0.001106	time 0.4609 (0.4755)	model_time 0.4607 (0.4674)	loss 2.6440 (3.0094)	grad_norm 1.0657 (2.2473/0.9493)	mem 16099MB
[2025-01-18 07:12:13 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][270/312]	eta 0:00:19 lr 0.001105	time 0.4524 (0.4751)	model_time 0.4522 (0.4673)	loss 2.2192 (3.0098)	grad_norm 1.7169 (2.2331/0.9470)	mem 16099MB
[2025-01-18 07:12:17 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][280/312]	eta 0:00:15 lr 0.001105	time 0.4695 (0.4751)	model_time 0.4693 (0.4676)	loss 2.9929 (3.0202)	grad_norm 1.2736 (2.2277/0.9405)	mem 16099MB
[2025-01-18 07:12:22 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][290/312]	eta 0:00:10 lr 0.001104	time 0.4519 (0.4748)	model_time 0.4517 (0.4676)	loss 3.8149 (3.0191)	grad_norm 2.6932 (2.2354/0.9362)	mem 16099MB
[2025-01-18 07:12:26 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][300/312]	eta 0:00:05 lr 0.001103	time 0.4367 (0.4740)	model_time 0.4366 (0.4670)	loss 3.4942 (3.0156)	grad_norm 3.5018 (2.2523/0.9385)	mem 16099MB
[2025-01-18 07:12:31 internimage_t_1k_224] (main.py 510): INFO Train: [195/300][310/312]	eta 0:00:00 lr 0.001103	time 0.4392 (0.4731)	model_time 0.4391 (0.4663)	loss 3.2164 (3.0139)	grad_norm 2.0063 (2.2674/0.9408)	mem 16099MB
[2025-01-18 07:12:31 internimage_t_1k_224] (main.py 519): INFO EPOCH 195 training takes 0:02:27
[2025-01-18 07:12:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_195.pth saving......
[2025-01-18 07:12:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_195.pth saved !!!
[2025-01-18 07:12:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.486 (7.486)	Loss 0.7808 (0.7808)	Acc@1 84.570 (84.570)	Acc@5 96.899 (96.899)	Mem 16099MB
[2025-01-18 07:12:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.990)	Loss 1.0613 (0.9028)	Acc@1 76.880 (81.254)	Acc@5 94.336 (95.630)	Mem 16099MB
[2025-01-18 07:12:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:195] * Acc@1 81.114 Acc@5 95.637
[2025-01-18 07:12:44 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.1%
[2025-01-18 07:12:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 07:12:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 07:12:45 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.11%
[2025-01-18 07:12:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.512 (7.512)	Loss 0.7904 (0.7904)	Acc@1 85.132 (85.132)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 07:12:56 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.999)	Loss 1.0535 (0.9075)	Acc@1 77.979 (82.267)	Acc@5 94.727 (96.069)	Mem 16099MB
[2025-01-18 07:12:56 internimage_t_1k_224] (main.py 575): INFO [Epoch:195] * Acc@1 82.152 Acc@5 96.101
[2025-01-18 07:12:56 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.2%
[2025-01-18 07:12:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:12:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:12:57 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.15%
[2025-01-18 07:13:00 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][0/312]	eta 0:12:33 lr 0.001103	time 2.4140 (2.4140)	model_time 0.4616 (0.4616)	loss 2.4642 (2.4642)	grad_norm 2.8137 (2.8137/0.0000)	mem 16099MB
[2025-01-18 07:13:05 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][10/312]	eta 0:03:21 lr 0.001102	time 0.5453 (0.6663)	model_time 0.5451 (0.4885)	loss 3.3432 (3.0352)	grad_norm 2.5172 (2.6554/1.2389)	mem 16099MB
[2025-01-18 07:13:09 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][20/312]	eta 0:02:49 lr 0.001101	time 0.5755 (0.5817)	model_time 0.5752 (0.4884)	loss 2.3703 (2.8428)	grad_norm 1.0675 (2.9609/1.3622)	mem 16099MB
[2025-01-18 07:13:14 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][30/312]	eta 0:02:33 lr 0.001101	time 0.4472 (0.5433)	model_time 0.4470 (0.4799)	loss 3.2338 (2.9430)	grad_norm 3.2573 (2.8346/1.1861)	mem 16099MB
[2025-01-18 07:13:19 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][40/312]	eta 0:02:22 lr 0.001100	time 0.4605 (0.5223)	model_time 0.4603 (0.4743)	loss 2.4760 (2.8908)	grad_norm 2.0692 (2.7251/1.1675)	mem 16099MB
[2025-01-18 07:13:23 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][50/312]	eta 0:02:13 lr 0.001100	time 0.4510 (0.5099)	model_time 0.4505 (0.4712)	loss 2.7196 (2.8972)	grad_norm 1.9650 (2.5505/1.1672)	mem 16099MB
[2025-01-18 07:13:28 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][60/312]	eta 0:02:06 lr 0.001099	time 0.4364 (0.5036)	model_time 0.4361 (0.4712)	loss 2.0766 (2.9306)	grad_norm 1.1622 (2.3915/1.1495)	mem 16099MB
[2025-01-18 07:13:33 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][70/312]	eta 0:02:00 lr 0.001099	time 0.4489 (0.4968)	model_time 0.4487 (0.4689)	loss 3.1413 (2.9631)	grad_norm 2.3879 (2.3677/1.0860)	mem 16099MB
[2025-01-18 07:13:37 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][80/312]	eta 0:01:54 lr 0.001098	time 0.4607 (0.4935)	model_time 0.4606 (0.4690)	loss 3.2257 (2.9954)	grad_norm 3.9683 (2.3790/1.0906)	mem 16099MB
[2025-01-18 07:13:42 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][90/312]	eta 0:01:48 lr 0.001097	time 0.4422 (0.4898)	model_time 0.4419 (0.4680)	loss 3.2178 (3.0086)	grad_norm 2.3351 (2.3945/1.0815)	mem 16099MB
[2025-01-18 07:13:47 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][100/312]	eta 0:01:43 lr 0.001097	time 0.4527 (0.4883)	model_time 0.4525 (0.4686)	loss 2.7587 (3.0198)	grad_norm 2.0298 (2.3857/1.0391)	mem 16099MB
[2025-01-18 07:13:51 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][110/312]	eta 0:01:38 lr 0.001096	time 0.4477 (0.4855)	model_time 0.4475 (0.4675)	loss 3.0890 (3.0387)	grad_norm 1.0831 (2.3124/1.0314)	mem 16099MB
[2025-01-18 07:13:56 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][120/312]	eta 0:01:33 lr 0.001096	time 0.5385 (0.4877)	model_time 0.5381 (0.4712)	loss 3.5860 (3.0450)	grad_norm 1.7287 (2.2886/1.0066)	mem 16099MB
[2025-01-18 07:14:01 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][130/312]	eta 0:01:28 lr 0.001095	time 0.4564 (0.4858)	model_time 0.4562 (0.4706)	loss 3.0422 (3.0331)	grad_norm 2.3859 (2.2561/0.9848)	mem 16099MB
[2025-01-18 07:14:06 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][140/312]	eta 0:01:23 lr 0.001094	time 0.4546 (0.4857)	model_time 0.4541 (0.4715)	loss 3.7128 (3.0223)	grad_norm 1.6446 (2.2535/1.0072)	mem 16099MB
[2025-01-18 07:14:10 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][150/312]	eta 0:01:18 lr 0.001094	time 0.4506 (0.4847)	model_time 0.4504 (0.4714)	loss 3.2314 (3.0242)	grad_norm 1.9657 (2.2780/1.0244)	mem 16099MB
[2025-01-18 07:14:15 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][160/312]	eta 0:01:13 lr 0.001093	time 0.4478 (0.4840)	model_time 0.4473 (0.4715)	loss 3.4752 (3.0356)	grad_norm 1.6067 (2.2761/1.0094)	mem 16099MB
[2025-01-18 07:14:20 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][170/312]	eta 0:01:08 lr 0.001093	time 0.4605 (0.4824)	model_time 0.4603 (0.4706)	loss 2.8330 (3.0358)	grad_norm 2.3619 (2.2380/0.9951)	mem 16099MB
[2025-01-18 07:14:24 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][180/312]	eta 0:01:03 lr 0.001092	time 0.4554 (0.4817)	model_time 0.4552 (0.4706)	loss 2.5239 (3.0327)	grad_norm 4.2644 (2.2579/0.9967)	mem 16099MB
[2025-01-18 07:14:29 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][190/312]	eta 0:00:58 lr 0.001092	time 0.4730 (0.4804)	model_time 0.4728 (0.4698)	loss 3.2701 (3.0334)	grad_norm 1.2581 (2.2622/0.9913)	mem 16099MB
[2025-01-18 07:14:34 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][200/312]	eta 0:00:53 lr 0.001091	time 0.4571 (0.4791)	model_time 0.4569 (0.4690)	loss 2.4415 (3.0313)	grad_norm 1.2795 (2.2392/0.9790)	mem 16099MB
[2025-01-18 07:14:38 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][210/312]	eta 0:00:48 lr 0.001090	time 0.4622 (0.4782)	model_time 0.4620 (0.4686)	loss 2.8854 (3.0268)	grad_norm 1.5346 (2.2264/0.9623)	mem 16099MB
[2025-01-18 07:14:43 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][220/312]	eta 0:00:43 lr 0.001090	time 0.4617 (0.4777)	model_time 0.4615 (0.4685)	loss 3.1463 (3.0256)	grad_norm 1.6862 (2.2586/1.0035)	mem 16099MB
[2025-01-18 07:14:47 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][230/312]	eta 0:00:39 lr 0.001089	time 0.4676 (0.4768)	model_time 0.4674 (0.4680)	loss 3.2502 (3.0305)	grad_norm 1.1577 (2.2380/0.9932)	mem 16099MB
[2025-01-18 07:14:52 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][240/312]	eta 0:00:34 lr 0.001089	time 0.4483 (0.4763)	model_time 0.4479 (0.4678)	loss 3.3158 (3.0216)	grad_norm 1.6861 (2.2127/0.9845)	mem 16099MB
[2025-01-18 07:14:57 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][250/312]	eta 0:00:29 lr 0.001088	time 0.4649 (0.4767)	model_time 0.4647 (0.4686)	loss 3.2810 (3.0126)	grad_norm 2.0163 (2.2242/0.9920)	mem 16099MB
[2025-01-18 07:15:02 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][260/312]	eta 0:00:24 lr 0.001087	time 0.4686 (0.4767)	model_time 0.4684 (0.4689)	loss 2.7381 (3.0119)	grad_norm 2.6485 (2.2549/1.0138)	mem 16099MB
[2025-01-18 07:15:06 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][270/312]	eta 0:00:19 lr 0.001087	time 0.4567 (0.4761)	model_time 0.4565 (0.4685)	loss 3.1175 (3.0093)	grad_norm 1.9526 (2.2657/1.0126)	mem 16099MB
[2025-01-18 07:15:11 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][280/312]	eta 0:00:15 lr 0.001086	time 0.4487 (0.4754)	model_time 0.4483 (0.4680)	loss 2.7076 (3.0114)	grad_norm 2.2566 (2.2644/0.9985)	mem 16099MB
[2025-01-18 07:15:16 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][290/312]	eta 0:00:10 lr 0.001086	time 0.4539 (0.4752)	model_time 0.4537 (0.4681)	loss 2.8011 (3.0126)	grad_norm 1.4307 (2.2554/0.9875)	mem 16099MB
[2025-01-18 07:15:20 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][300/312]	eta 0:00:05 lr 0.001085	time 0.4387 (0.4754)	model_time 0.4387 (0.4685)	loss 3.5266 (3.0110)	grad_norm 1.9754 (2.2428/0.9801)	mem 16099MB
[2025-01-18 07:15:25 internimage_t_1k_224] (main.py 510): INFO Train: [196/300][310/312]	eta 0:00:00 lr 0.001084	time 0.5449 (0.4747)	model_time 0.5448 (0.4680)	loss 2.0805 (3.0084)	grad_norm 2.4665 (2.2255/0.9649)	mem 16099MB
[2025-01-18 07:15:25 internimage_t_1k_224] (main.py 519): INFO EPOCH 196 training takes 0:02:28
[2025-01-18 07:15:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_196.pth saving......
[2025-01-18 07:15:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_196.pth saved !!!
[2025-01-18 07:15:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.628 (7.628)	Loss 0.7466 (0.7466)	Acc@1 83.960 (83.960)	Acc@5 96.924 (96.924)	Mem 16099MB
[2025-01-18 07:15:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.011)	Loss 1.0274 (0.8735)	Acc@1 77.271 (81.143)	Acc@5 93.970 (95.625)	Mem 16099MB
[2025-01-18 07:15:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:196] * Acc@1 81.066 Acc@5 95.659
[2025-01-18 07:15:38 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.1%
[2025-01-18 07:15:38 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.11%
[2025-01-18 07:15:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.374 (8.374)	Loss 0.7897 (0.7897)	Acc@1 85.181 (85.181)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 07:15:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.122)	Loss 1.0523 (0.9064)	Acc@1 78.003 (82.278)	Acc@5 94.727 (96.087)	Mem 16099MB
[2025-01-18 07:15:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:196] * Acc@1 82.164 Acc@5 96.117
[2025-01-18 07:15:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.2%
[2025-01-18 07:15:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:15:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:15:51 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.16%
[2025-01-18 07:15:54 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][0/312]	eta 0:11:42 lr 0.001084	time 2.2507 (2.2507)	model_time 0.4878 (0.4878)	loss 3.1994 (3.1994)	grad_norm 1.2323 (1.2323/0.0000)	mem 16099MB
[2025-01-18 07:15:58 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][10/312]	eta 0:03:10 lr 0.001084	time 0.4574 (0.6292)	model_time 0.4573 (0.4687)	loss 3.4088 (2.8597)	grad_norm 1.3117 (1.7351/0.5866)	mem 16099MB
[2025-01-18 07:16:03 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][20/312]	eta 0:02:42 lr 0.001083	time 0.4585 (0.5552)	model_time 0.4584 (0.4709)	loss 2.3578 (2.9628)	grad_norm 1.8133 (1.8247/0.5956)	mem 16099MB
[2025-01-18 07:16:08 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][30/312]	eta 0:02:28 lr 0.001083	time 0.4514 (0.5267)	model_time 0.4512 (0.4696)	loss 2.1213 (2.8986)	grad_norm 1.3601 (1.7102/0.5572)	mem 16099MB
[2025-01-18 07:16:12 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][40/312]	eta 0:02:18 lr 0.001082	time 0.4529 (0.5094)	model_time 0.4527 (0.4661)	loss 1.8628 (2.8642)	grad_norm 2.5765 (1.8534/0.6124)	mem 16099MB
[2025-01-18 07:16:17 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][50/312]	eta 0:02:11 lr 0.001081	time 0.4410 (0.5023)	model_time 0.4405 (0.4674)	loss 2.7588 (2.8788)	grad_norm 2.3550 (1.7481/0.6133)	mem 16099MB
[2025-01-18 07:16:22 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][60/312]	eta 0:02:05 lr 0.001081	time 0.4566 (0.4964)	model_time 0.4564 (0.4672)	loss 3.0997 (2.8950)	grad_norm 2.2738 (1.8276/0.8474)	mem 16099MB
[2025-01-18 07:16:26 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][70/312]	eta 0:01:59 lr 0.001080	time 0.4459 (0.4921)	model_time 0.4458 (0.4669)	loss 3.0427 (2.9214)	grad_norm 2.3307 (1.8873/0.8318)	mem 16099MB
[2025-01-18 07:16:31 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][80/312]	eta 0:01:54 lr 0.001080	time 0.7402 (0.4923)	model_time 0.7397 (0.4701)	loss 2.2772 (2.9470)	grad_norm 1.8346 (1.8715/0.8081)	mem 16099MB
[2025-01-18 07:16:36 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][90/312]	eta 0:01:48 lr 0.001079	time 0.4476 (0.4898)	model_time 0.4474 (0.4701)	loss 3.5135 (2.9372)	grad_norm 5.3798 (1.9629/0.9233)	mem 16099MB
[2025-01-18 07:16:41 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][100/312]	eta 0:01:43 lr 0.001078	time 0.4440 (0.4865)	model_time 0.4435 (0.4687)	loss 3.1380 (2.9424)	grad_norm 2.7730 (2.0856/1.0510)	mem 16099MB
[2025-01-18 07:16:45 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][110/312]	eta 0:01:38 lr 0.001078	time 0.5462 (0.4861)	model_time 0.5461 (0.4698)	loss 3.2200 (2.9386)	grad_norm 2.0862 (2.1341/1.0435)	mem 16099MB
[2025-01-18 07:16:50 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][120/312]	eta 0:01:33 lr 0.001077	time 0.4586 (0.4846)	model_time 0.4581 (0.4696)	loss 2.0527 (2.9395)	grad_norm 1.2967 (2.0864/1.0189)	mem 16099MB
[2025-01-18 07:16:55 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][130/312]	eta 0:01:27 lr 0.001077	time 0.4464 (0.4831)	model_time 0.4463 (0.4692)	loss 2.1973 (2.9383)	grad_norm 2.1478 (2.0636/1.0075)	mem 16099MB
[2025-01-18 07:16:59 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][140/312]	eta 0:01:22 lr 0.001076	time 0.4584 (0.4819)	model_time 0.4582 (0.4690)	loss 3.2241 (2.9335)	grad_norm 1.5039 (2.0353/0.9905)	mem 16099MB
[2025-01-18 07:17:04 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][150/312]	eta 0:01:17 lr 0.001076	time 0.4437 (0.4813)	model_time 0.4435 (0.4691)	loss 3.7856 (2.9435)	grad_norm 2.1271 (2.0738/1.0274)	mem 16099MB
[2025-01-18 07:17:09 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][160/312]	eta 0:01:12 lr 0.001075	time 0.4506 (0.4800)	model_time 0.4502 (0.4686)	loss 2.8147 (2.9458)	grad_norm 2.2211 (2.1205/1.0535)	mem 16099MB
[2025-01-18 07:17:13 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][170/312]	eta 0:01:07 lr 0.001074	time 0.4512 (0.4788)	model_time 0.4507 (0.4680)	loss 3.3377 (2.9468)	grad_norm 2.4202 (2.1667/1.0771)	mem 16099MB
[2025-01-18 07:17:18 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][180/312]	eta 0:01:03 lr 0.001074	time 0.4601 (0.4774)	model_time 0.4600 (0.4672)	loss 1.9192 (2.9455)	grad_norm 2.0443 (2.1790/1.0667)	mem 16099MB
[2025-01-18 07:17:23 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][190/312]	eta 0:00:58 lr 0.001073	time 0.4391 (0.4768)	model_time 0.4390 (0.4672)	loss 3.4462 (2.9538)	grad_norm 3.5646 (2.1999/1.0695)	mem 16099MB
[2025-01-18 07:17:27 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][200/312]	eta 0:00:53 lr 0.001073	time 0.4442 (0.4759)	model_time 0.4440 (0.4667)	loss 3.4172 (2.9685)	grad_norm 1.0599 (2.1895/1.0534)	mem 16099MB
[2025-01-18 07:17:32 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][210/312]	eta 0:00:48 lr 0.001072	time 0.4538 (0.4756)	model_time 0.4536 (0.4668)	loss 3.5559 (2.9643)	grad_norm 1.2871 (2.1728/1.0400)	mem 16099MB
[2025-01-18 07:17:36 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][220/312]	eta 0:00:43 lr 0.001071	time 0.4496 (0.4752)	model_time 0.4494 (0.4668)	loss 3.3154 (2.9734)	grad_norm 3.3614 (2.1844/1.0544)	mem 16099MB
[2025-01-18 07:17:41 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][230/312]	eta 0:00:38 lr 0.001071	time 0.4468 (0.4745)	model_time 0.4463 (0.4665)	loss 3.3436 (2.9783)	grad_norm 2.8922 (2.1784/1.0386)	mem 16099MB
[2025-01-18 07:17:46 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][240/312]	eta 0:00:34 lr 0.001070	time 0.4524 (0.4740)	model_time 0.4522 (0.4662)	loss 1.8887 (2.9798)	grad_norm 1.5022 (2.1659/1.0244)	mem 16099MB
[2025-01-18 07:17:50 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][250/312]	eta 0:00:29 lr 0.001070	time 0.4484 (0.4738)	model_time 0.4479 (0.4663)	loss 2.5605 (2.9830)	grad_norm 1.5649 (2.1727/1.0228)	mem 16099MB
[2025-01-18 07:17:55 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][260/312]	eta 0:00:24 lr 0.001069	time 0.4520 (0.4740)	model_time 0.4518 (0.4668)	loss 3.2921 (2.9819)	grad_norm 1.7635 (2.1866/1.0199)	mem 16099MB
[2025-01-18 07:18:00 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][270/312]	eta 0:00:19 lr 0.001069	time 0.4521 (0.4735)	model_time 0.4519 (0.4666)	loss 3.2262 (2.9901)	grad_norm 1.6123 (2.1701/1.0108)	mem 16099MB
[2025-01-18 07:18:04 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][280/312]	eta 0:00:15 lr 0.001068	time 0.4554 (0.4735)	model_time 0.4553 (0.4668)	loss 3.1797 (2.9966)	grad_norm 1.3705 (2.1460/1.0114)	mem 16099MB
[2025-01-18 07:18:09 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][290/312]	eta 0:00:10 lr 0.001067	time 0.4490 (0.4737)	model_time 0.4486 (0.4672)	loss 1.8613 (2.9986)	grad_norm 2.7543 (2.1316/1.0043)	mem 16099MB
[2025-01-18 07:18:14 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][300/312]	eta 0:00:05 lr 0.001067	time 0.4433 (0.4733)	model_time 0.4432 (0.4670)	loss 2.0901 (2.9974)	grad_norm 1.3676 (2.1385/0.9972)	mem 16099MB
[2025-01-18 07:18:18 internimage_t_1k_224] (main.py 510): INFO Train: [197/300][310/312]	eta 0:00:00 lr 0.001066	time 0.4400 (0.4724)	model_time 0.4399 (0.4663)	loss 2.2156 (2.9856)	grad_norm 2.2945 (2.1746/1.0274)	mem 16099MB
[2025-01-18 07:18:19 internimage_t_1k_224] (main.py 519): INFO EPOCH 197 training takes 0:02:27
[2025-01-18 07:18:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_197.pth saving......
[2025-01-18 07:18:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_197.pth saved !!!
[2025-01-18 07:18:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.282 (7.282)	Loss 0.7396 (0.7396)	Acc@1 83.960 (83.960)	Acc@5 97.070 (97.070)	Mem 16099MB
[2025-01-18 07:18:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.021)	Loss 1.0286 (0.8759)	Acc@1 77.051 (81.206)	Acc@5 94.434 (95.668)	Mem 16099MB
[2025-01-18 07:18:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:197] * Acc@1 81.124 Acc@5 95.717
[2025-01-18 07:18:31 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.1%
[2025-01-18 07:18:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 07:18:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 07:18:32 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.12%
[2025-01-18 07:18:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.536 (7.536)	Loss 0.7888 (0.7888)	Acc@1 85.156 (85.156)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 07:18:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.022)	Loss 1.0511 (0.9055)	Acc@1 78.101 (82.278)	Acc@5 94.800 (96.094)	Mem 16099MB
[2025-01-18 07:18:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:197] * Acc@1 82.166 Acc@5 96.123
[2025-01-18 07:18:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.2%
[2025-01-18 07:18:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:18:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:18:45 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.17%
[2025-01-18 07:18:48 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][0/312]	eta 0:12:33 lr 0.001066	time 2.4138 (2.4138)	model_time 0.6102 (0.6102)	loss 3.7420 (3.7420)	grad_norm 7.9406 (7.9406/0.0000)	mem 16099MB
[2025-01-18 07:18:52 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][10/312]	eta 0:03:15 lr 0.001066	time 0.4632 (0.6479)	model_time 0.4631 (0.4837)	loss 3.4626 (3.2598)	grad_norm 3.4238 (3.2726/1.6413)	mem 16099MB
[2025-01-18 07:18:57 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][20/312]	eta 0:02:44 lr 0.001065	time 0.5561 (0.5628)	model_time 0.5559 (0.4766)	loss 3.1455 (3.0183)	grad_norm 1.5295 (2.5319/1.4781)	mem 16099MB
[2025-01-18 07:19:02 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][30/312]	eta 0:02:30 lr 0.001064	time 0.5326 (0.5344)	model_time 0.5324 (0.4759)	loss 2.5872 (3.0763)	grad_norm 2.6784 (2.2866/1.2955)	mem 16099MB
[2025-01-18 07:19:06 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][40/312]	eta 0:02:20 lr 0.001064	time 0.4475 (0.5183)	model_time 0.4473 (0.4739)	loss 2.6231 (3.0479)	grad_norm 2.5179 (2.2175/1.1655)	mem 16099MB
[2025-01-18 07:19:11 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][50/312]	eta 0:02:13 lr 0.001063	time 0.4778 (0.5084)	model_time 0.4776 (0.4727)	loss 1.9228 (3.0467)	grad_norm 5.0071 (2.3867/1.2756)	mem 16099MB
[2025-01-18 07:19:16 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][60/312]	eta 0:02:06 lr 0.001063	time 0.5472 (0.5018)	model_time 0.5467 (0.4718)	loss 3.3484 (2.9989)	grad_norm 0.9886 (2.3091/1.2157)	mem 16099MB
[2025-01-18 07:19:20 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][70/312]	eta 0:01:59 lr 0.001062	time 0.4446 (0.4950)	model_time 0.4441 (0.4692)	loss 2.2953 (2.9712)	grad_norm 1.8722 (2.2393/1.1789)	mem 16099MB
[2025-01-18 07:19:25 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][80/312]	eta 0:01:54 lr 0.001061	time 0.5003 (0.4917)	model_time 0.4999 (0.4690)	loss 2.2946 (2.9704)	grad_norm 1.6667 (2.1811/1.1399)	mem 16099MB
[2025-01-18 07:19:30 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][90/312]	eta 0:01:48 lr 0.001061	time 0.4599 (0.4889)	model_time 0.4594 (0.4686)	loss 3.4282 (2.9866)	grad_norm 1.2563 (2.1738/1.0957)	mem 16099MB
[2025-01-18 07:19:34 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][100/312]	eta 0:01:43 lr 0.001060	time 0.4651 (0.4868)	model_time 0.4647 (0.4685)	loss 2.6032 (2.9832)	grad_norm 1.3342 (2.1242/1.0558)	mem 16099MB
[2025-01-18 07:19:39 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][110/312]	eta 0:01:38 lr 0.001060	time 0.5352 (0.4853)	model_time 0.5347 (0.4686)	loss 3.6013 (2.9936)	grad_norm 3.0811 (2.1279/1.0803)	mem 16099MB
[2025-01-18 07:19:44 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][120/312]	eta 0:01:33 lr 0.001059	time 0.5372 (0.4855)	model_time 0.5370 (0.4702)	loss 3.1185 (3.0099)	grad_norm 3.0718 (2.1767/1.0892)	mem 16099MB
[2025-01-18 07:19:48 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][130/312]	eta 0:01:28 lr 0.001059	time 0.4533 (0.4840)	model_time 0.4531 (0.4698)	loss 3.4653 (3.0054)	grad_norm 1.2501 (2.1553/1.0735)	mem 16099MB
[2025-01-18 07:19:53 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][140/312]	eta 0:01:22 lr 0.001058	time 0.4681 (0.4821)	model_time 0.4679 (0.4689)	loss 3.4304 (3.0236)	grad_norm 2.2431 (2.1615/1.0505)	mem 16099MB
[2025-01-18 07:19:58 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][150/312]	eta 0:01:18 lr 0.001057	time 0.4827 (0.4816)	model_time 0.4823 (0.4692)	loss 2.8356 (3.0353)	grad_norm 1.4848 (2.1304/1.0361)	mem 16099MB
[2025-01-18 07:20:02 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][160/312]	eta 0:01:13 lr 0.001057	time 0.4590 (0.4805)	model_time 0.4586 (0.4689)	loss 3.5023 (3.0449)	grad_norm 3.9165 (2.1781/1.0367)	mem 16099MB
[2025-01-18 07:20:07 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][170/312]	eta 0:01:08 lr 0.001056	time 0.4533 (0.4792)	model_time 0.4528 (0.4682)	loss 2.0438 (3.0522)	grad_norm 1.2412 (2.1706/1.0233)	mem 16099MB
[2025-01-18 07:20:12 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][180/312]	eta 0:01:03 lr 0.001056	time 0.4461 (0.4780)	model_time 0.4457 (0.4677)	loss 3.6447 (3.0570)	grad_norm 4.1243 (2.1992/1.0583)	mem 16099MB
[2025-01-18 07:20:16 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][190/312]	eta 0:00:58 lr 0.001055	time 0.4617 (0.4774)	model_time 0.4612 (0.4675)	loss 3.0859 (3.0523)	grad_norm 2.6515 (2.2646/1.1230)	mem 16099MB
[2025-01-18 07:20:21 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][200/312]	eta 0:00:53 lr 0.001055	time 0.4547 (0.4771)	model_time 0.4542 (0.4677)	loss 2.0411 (3.0424)	grad_norm 3.4420 (2.2846/1.1249)	mem 16099MB
[2025-01-18 07:20:26 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][210/312]	eta 0:00:48 lr 0.001054	time 0.5013 (0.4775)	model_time 0.5009 (0.4685)	loss 3.2463 (3.0291)	grad_norm 1.1335 (2.2595/1.1133)	mem 16099MB
[2025-01-18 07:20:30 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][220/312]	eta 0:00:43 lr 0.001053	time 0.4591 (0.4768)	model_time 0.4589 (0.4682)	loss 2.9316 (3.0304)	grad_norm 1.3896 (2.2945/1.1390)	mem 16099MB
[2025-01-18 07:20:35 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][230/312]	eta 0:00:39 lr 0.001053	time 0.4578 (0.4763)	model_time 0.4576 (0.4681)	loss 2.0371 (3.0380)	grad_norm 1.4766 (2.2906/1.1280)	mem 16099MB
[2025-01-18 07:20:40 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][240/312]	eta 0:00:34 lr 0.001052	time 0.4327 (0.4758)	model_time 0.4322 (0.4679)	loss 3.1622 (3.0394)	grad_norm 3.2096 (2.2941/1.1192)	mem 16099MB
[2025-01-18 07:20:44 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][250/312]	eta 0:00:29 lr 0.001052	time 0.4476 (0.4753)	model_time 0.4474 (0.4676)	loss 3.6156 (3.0382)	grad_norm 1.3223 (2.2595/1.1129)	mem 16099MB
[2025-01-18 07:20:49 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][260/312]	eta 0:00:24 lr 0.001051	time 0.4513 (0.4753)	model_time 0.4511 (0.4680)	loss 2.5843 (3.0428)	grad_norm 2.2343 (2.2404/1.1053)	mem 16099MB
[2025-01-18 07:20:54 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][270/312]	eta 0:00:19 lr 0.001050	time 0.4451 (0.4752)	model_time 0.4447 (0.4681)	loss 3.4101 (3.0378)	grad_norm 1.6678 (2.2259/1.0919)	mem 16099MB
[2025-01-18 07:20:59 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][280/312]	eta 0:00:15 lr 0.001050	time 0.4515 (0.4749)	model_time 0.4511 (0.4680)	loss 2.9386 (3.0402)	grad_norm 2.4042 (2.2341/1.1027)	mem 16099MB
[2025-01-18 07:21:03 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][290/312]	eta 0:00:10 lr 0.001049	time 0.4429 (0.4749)	model_time 0.4424 (0.4683)	loss 3.0983 (3.0354)	grad_norm 1.1284 (2.2175/1.0913)	mem 16099MB
[2025-01-18 07:21:08 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][300/312]	eta 0:00:05 lr 0.001049	time 0.4411 (0.4743)	model_time 0.4410 (0.4679)	loss 1.9222 (3.0355)	grad_norm 3.6588 (2.2098/1.0440)	mem 16099MB
[2025-01-18 07:21:12 internimage_t_1k_224] (main.py 510): INFO Train: [198/300][310/312]	eta 0:00:00 lr 0.001048	time 0.4400 (0.4736)	model_time 0.4398 (0.4674)	loss 3.3751 (3.0342)	grad_norm 3.7856 (2.2036/1.0409)	mem 16099MB
[2025-01-18 07:21:13 internimage_t_1k_224] (main.py 519): INFO EPOCH 198 training takes 0:02:27
[2025-01-18 07:21:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_198.pth saving......
[2025-01-18 07:21:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_198.pth saved !!!
[2025-01-18 07:21:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.716 (7.716)	Loss 0.7763 (0.7763)	Acc@1 83.716 (83.716)	Acc@5 97.192 (97.192)	Mem 16099MB
[2025-01-18 07:21:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.033)	Loss 1.0705 (0.8949)	Acc@1 76.440 (81.161)	Acc@5 94.336 (95.701)	Mem 16099MB
[2025-01-18 07:21:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:198] * Acc@1 81.098 Acc@5 95.709
[2025-01-18 07:21:25 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.1%
[2025-01-18 07:21:25 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.12%
[2025-01-18 07:21:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.213 (8.213)	Loss 0.7880 (0.7880)	Acc@1 85.156 (85.156)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 07:21:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.107)	Loss 1.0499 (0.9044)	Acc@1 78.174 (82.300)	Acc@5 94.775 (96.098)	Mem 16099MB
[2025-01-18 07:21:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:198] * Acc@1 82.184 Acc@5 96.129
[2025-01-18 07:21:38 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.2%
[2025-01-18 07:21:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:21:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:21:39 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.18%
[2025-01-18 07:21:41 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][0/312]	eta 0:12:27 lr 0.001048	time 2.3947 (2.3947)	model_time 0.4697 (0.4697)	loss 3.2472 (3.2472)	grad_norm 4.7120 (4.7120/0.0000)	mem 16099MB
[2025-01-18 07:21:46 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][10/312]	eta 0:03:19 lr 0.001047	time 0.4504 (0.6593)	model_time 0.4499 (0.4839)	loss 1.8904 (2.8000)	grad_norm 2.2399 (2.4268/0.9071)	mem 16099MB
[2025-01-18 07:21:51 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][20/312]	eta 0:02:47 lr 0.001047	time 0.4558 (0.5727)	model_time 0.4554 (0.4807)	loss 3.2592 (2.7779)	grad_norm 1.3394 (2.2089/0.8153)	mem 16099MB
[2025-01-18 07:21:56 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][30/312]	eta 0:02:31 lr 0.001046	time 0.4674 (0.5359)	model_time 0.4670 (0.4735)	loss 3.0492 (2.8475)	grad_norm 2.0267 (2.2789/0.8377)	mem 16099MB
[2025-01-18 07:22:00 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][40/312]	eta 0:02:21 lr 0.001046	time 0.4650 (0.5192)	model_time 0.4648 (0.4719)	loss 2.3389 (2.8702)	grad_norm 1.3693 (2.1310/0.8468)	mem 16099MB
[2025-01-18 07:22:05 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][50/312]	eta 0:02:12 lr 0.001045	time 0.4572 (0.5076)	model_time 0.4570 (0.4695)	loss 2.4241 (2.8873)	grad_norm 2.2473 (2.1259/0.8041)	mem 16099MB
[2025-01-18 07:22:09 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][60/312]	eta 0:02:05 lr 0.001045	time 0.4513 (0.4986)	model_time 0.4508 (0.4666)	loss 4.0210 (2.9214)	grad_norm 1.9473 (2.1605/0.8484)	mem 16099MB
[2025-01-18 07:22:14 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][70/312]	eta 0:01:59 lr 0.001044	time 0.4618 (0.4929)	model_time 0.4616 (0.4654)	loss 3.6752 (2.9271)	grad_norm 2.2817 (2.1095/0.8437)	mem 16099MB
[2025-01-18 07:22:19 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][80/312]	eta 0:01:54 lr 0.001043	time 0.4513 (0.4918)	model_time 0.4511 (0.4676)	loss 3.0534 (2.9415)	grad_norm 1.7368 (2.0833/0.8311)	mem 16099MB
[2025-01-18 07:22:24 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][90/312]	eta 0:01:48 lr 0.001043	time 0.4629 (0.4897)	model_time 0.4624 (0.4681)	loss 3.3031 (2.9735)	grad_norm 2.1831 (2.0626/0.8060)	mem 16099MB
[2025-01-18 07:22:28 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][100/312]	eta 0:01:43 lr 0.001042	time 0.4631 (0.4860)	model_time 0.4629 (0.4665)	loss 3.3129 (2.9826)	grad_norm 1.5908 (2.0866/0.8238)	mem 16099MB
[2025-01-18 07:22:33 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][110/312]	eta 0:01:37 lr 0.001042	time 0.5656 (0.4844)	model_time 0.5652 (0.4666)	loss 2.7146 (2.9851)	grad_norm 1.4900 (2.1022/0.8284)	mem 16099MB
[2025-01-18 07:22:37 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][120/312]	eta 0:01:32 lr 0.001041	time 0.5404 (0.4834)	model_time 0.5402 (0.4670)	loss 3.0977 (2.9710)	grad_norm 4.5744 (2.1587/0.8835)	mem 16099MB
[2025-01-18 07:22:42 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][130/312]	eta 0:01:27 lr 0.001040	time 0.4558 (0.4824)	model_time 0.4553 (0.4673)	loss 2.8688 (2.9625)	grad_norm 1.3927 (2.2291/0.9922)	mem 16099MB
[2025-01-18 07:22:47 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][140/312]	eta 0:01:22 lr 0.001040	time 0.4433 (0.4821)	model_time 0.4428 (0.4680)	loss 2.8850 (2.9616)	grad_norm 3.1019 (2.2398/0.9879)	mem 16099MB
[2025-01-18 07:22:52 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][150/312]	eta 0:01:17 lr 0.001039	time 0.4444 (0.4815)	model_time 0.4443 (0.4683)	loss 1.9599 (2.9581)	grad_norm 2.9991 (2.2201/0.9781)	mem 16099MB
[2025-01-18 07:22:56 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][160/312]	eta 0:01:13 lr 0.001039	time 0.4528 (0.4807)	model_time 0.4523 (0.4683)	loss 3.4727 (2.9686)	grad_norm 2.6079 (2.1790/0.9684)	mem 16099MB
[2025-01-18 07:23:01 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][170/312]	eta 0:01:08 lr 0.001038	time 0.4543 (0.4792)	model_time 0.4538 (0.4675)	loss 3.0094 (2.9598)	grad_norm 1.3755 (2.1855/0.9676)	mem 16099MB
[2025-01-18 07:23:06 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][180/312]	eta 0:01:03 lr 0.001038	time 0.4939 (0.4789)	model_time 0.4934 (0.4679)	loss 2.8378 (2.9616)	grad_norm 2.1021 (2.1770/0.9609)	mem 16099MB
[2025-01-18 07:23:10 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][190/312]	eta 0:00:58 lr 0.001037	time 0.4526 (0.4786)	model_time 0.4524 (0.4681)	loss 2.8531 (2.9501)	grad_norm 6.1204 (2.2310/1.0323)	mem 16099MB
[2025-01-18 07:23:15 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][200/312]	eta 0:00:53 lr 0.001036	time 0.4833 (0.4780)	model_time 0.4831 (0.4679)	loss 2.9268 (2.9562)	grad_norm 2.3741 (2.2676/1.0789)	mem 16099MB
[2025-01-18 07:23:20 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][210/312]	eta 0:00:48 lr 0.001036	time 0.4567 (0.4768)	model_time 0.4565 (0.4673)	loss 2.2861 (2.9605)	grad_norm 2.5094 (2.3156/1.1121)	mem 16099MB
[2025-01-18 07:23:24 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][220/312]	eta 0:00:43 lr 0.001035	time 0.4434 (0.4767)	model_time 0.4429 (0.4676)	loss 3.6293 (2.9614)	grad_norm 1.0774 (2.3356/1.1211)	mem 16099MB
[2025-01-18 07:23:29 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][230/312]	eta 0:00:39 lr 0.001035	time 0.4398 (0.4764)	model_time 0.4396 (0.4676)	loss 3.2534 (2.9657)	grad_norm 2.7638 (2.3251/1.1034)	mem 16099MB
[2025-01-18 07:23:34 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][240/312]	eta 0:00:34 lr 0.001034	time 0.4546 (0.4760)	model_time 0.4544 (0.4676)	loss 3.5616 (2.9669)	grad_norm 3.0872 (2.3269/1.0887)	mem 16099MB
[2025-01-18 07:23:38 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][250/312]	eta 0:00:29 lr 0.001034	time 0.4535 (0.4762)	model_time 0.4533 (0.4681)	loss 3.3493 (2.9734)	grad_norm 1.4815 (2.3026/1.0788)	mem 16099MB
[2025-01-18 07:23:43 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][260/312]	eta 0:00:24 lr 0.001033	time 0.4555 (0.4757)	model_time 0.4553 (0.4679)	loss 3.3545 (2.9728)	grad_norm 1.2980 (2.2924/1.0670)	mem 16099MB
[2025-01-18 07:23:48 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][270/312]	eta 0:00:19 lr 0.001032	time 0.4621 (0.4754)	model_time 0.4619 (0.4678)	loss 3.8136 (2.9751)	grad_norm 2.4129 (2.2802/1.0569)	mem 16099MB
[2025-01-18 07:23:52 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][280/312]	eta 0:00:15 lr 0.001032	time 0.4365 (0.4746)	model_time 0.4360 (0.4673)	loss 3.5220 (2.9846)	grad_norm 1.2887 (2.2614/1.0474)	mem 16099MB
[2025-01-18 07:23:57 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][290/312]	eta 0:00:10 lr 0.001031	time 0.4553 (0.4742)	model_time 0.4548 (0.4672)	loss 2.9647 (2.9728)	grad_norm 1.0430 (2.2357/1.0415)	mem 16099MB
[2025-01-18 07:24:02 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][300/312]	eta 0:00:05 lr 0.001031	time 0.4412 (0.4745)	model_time 0.4412 (0.4676)	loss 2.9272 (2.9754)	grad_norm 2.3884 (2.2011/1.0284)	mem 16099MB
[2025-01-18 07:24:06 internimage_t_1k_224] (main.py 510): INFO Train: [199/300][310/312]	eta 0:00:00 lr 0.001030	time 0.5429 (0.4737)	model_time 0.5428 (0.4671)	loss 3.0533 (2.9776)	grad_norm 1.0126 (2.1751/1.0341)	mem 16099MB
[2025-01-18 07:24:07 internimage_t_1k_224] (main.py 519): INFO EPOCH 199 training takes 0:02:27
[2025-01-18 07:24:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_199.pth saving......
[2025-01-18 07:24:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_199.pth saved !!!
[2025-01-18 07:24:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.301 (7.301)	Loss 0.7815 (0.7815)	Acc@1 84.009 (84.009)	Acc@5 97.144 (97.144)	Mem 16099MB
[2025-01-18 07:24:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.984)	Loss 1.0527 (0.8996)	Acc@1 76.538 (81.024)	Acc@5 94.507 (95.566)	Mem 16099MB
[2025-01-18 07:24:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:199] * Acc@1 80.860 Acc@5 95.583
[2025-01-18 07:24:19 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 80.9%
[2025-01-18 07:24:19 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.12%
[2025-01-18 07:24:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.259 (8.259)	Loss 0.7870 (0.7870)	Acc@1 85.083 (85.083)	Acc@5 97.534 (97.534)	Mem 16099MB
[2025-01-18 07:24:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.110)	Loss 1.0483 (0.9031)	Acc@1 78.174 (82.300)	Acc@5 94.824 (96.138)	Mem 16099MB
[2025-01-18 07:24:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:199] * Acc@1 82.186 Acc@5 96.165
[2025-01-18 07:24:31 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.2%
[2025-01-18 07:24:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:24:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:24:33 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.19%
[2025-01-18 07:24:35 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][0/312]	eta 0:12:15 lr 0.001030	time 2.3589 (2.3589)	model_time 0.5022 (0.5022)	loss 3.7096 (3.7096)	grad_norm 1.0442 (1.0442/0.0000)	mem 16099MB
[2025-01-18 07:24:40 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][10/312]	eta 0:03:13 lr 0.001029	time 0.4439 (0.6401)	model_time 0.4438 (0.4709)	loss 1.8091 (2.8536)	grad_norm 2.1008 (1.9135/0.8738)	mem 16099MB
[2025-01-18 07:24:44 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][20/312]	eta 0:02:44 lr 0.001029	time 0.6010 (0.5650)	model_time 0.6008 (0.4763)	loss 3.1077 (2.8826)	grad_norm 1.2721 (1.9184/1.0303)	mem 16099MB
[2025-01-18 07:24:49 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][30/312]	eta 0:02:31 lr 0.001028	time 0.4632 (0.5360)	model_time 0.4631 (0.4758)	loss 3.4974 (2.8718)	grad_norm 3.8949 (1.8914/0.9768)	mem 16099MB
[2025-01-18 07:24:54 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][40/312]	eta 0:02:21 lr 0.001028	time 0.4662 (0.5185)	model_time 0.4660 (0.4728)	loss 3.3203 (2.9139)	grad_norm 2.6277 (1.9609/0.9074)	mem 16099MB
[2025-01-18 07:24:59 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][50/312]	eta 0:02:13 lr 0.001027	time 0.4559 (0.5102)	model_time 0.4555 (0.4734)	loss 3.4926 (2.9687)	grad_norm 2.6352 (1.9778/0.8601)	mem 16099MB
[2025-01-18 07:25:03 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][60/312]	eta 0:02:06 lr 0.001027	time 0.4608 (0.5022)	model_time 0.4606 (0.4714)	loss 2.1976 (2.9842)	grad_norm 2.6482 (1.9730/0.8638)	mem 16099MB
[2025-01-18 07:25:08 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][70/312]	eta 0:01:59 lr 0.001026	time 0.4499 (0.4957)	model_time 0.4497 (0.4692)	loss 2.8699 (2.9884)	grad_norm 1.2921 (1.9989/0.9111)	mem 16099MB
[2025-01-18 07:25:13 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][80/312]	eta 0:01:54 lr 0.001025	time 0.4597 (0.4941)	model_time 0.4596 (0.4708)	loss 3.3881 (2.9755)	grad_norm 1.6563 (2.0031/0.8911)	mem 16099MB
[2025-01-18 07:25:17 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][90/312]	eta 0:01:48 lr 0.001025	time 0.4596 (0.4899)	model_time 0.4591 (0.4691)	loss 2.0809 (2.9614)	grad_norm 3.0190 (2.0471/0.8885)	mem 16099MB
[2025-01-18 07:25:22 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][100/312]	eta 0:01:43 lr 0.001024	time 0.4508 (0.4868)	model_time 0.4503 (0.4680)	loss 3.1650 (2.9711)	grad_norm 3.7327 (2.1483/0.9340)	mem 16099MB
[2025-01-18 07:25:26 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][110/312]	eta 0:01:38 lr 0.001024	time 0.4452 (0.4852)	model_time 0.4447 (0.4680)	loss 2.7660 (2.9850)	grad_norm 1.7514 (2.1195/0.9130)	mem 16099MB
[2025-01-18 07:25:31 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][120/312]	eta 0:01:32 lr 0.001023	time 0.4763 (0.4834)	model_time 0.4758 (0.4677)	loss 2.9727 (2.9489)	grad_norm 1.3932 (2.1280/0.9020)	mem 16099MB
[2025-01-18 07:25:36 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][130/312]	eta 0:01:27 lr 0.001023	time 0.4516 (0.4825)	model_time 0.4512 (0.4679)	loss 3.0811 (2.9595)	grad_norm 2.4597 (2.1126/0.8856)	mem 16099MB
[2025-01-18 07:25:41 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][140/312]	eta 0:01:23 lr 0.001022	time 0.4570 (0.4826)	model_time 0.4565 (0.4690)	loss 3.2583 (2.9784)	grad_norm 2.2924 (2.0884/0.8705)	mem 16099MB
[2025-01-18 07:25:45 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][150/312]	eta 0:01:18 lr 0.001021	time 0.4571 (0.4821)	model_time 0.4566 (0.4693)	loss 2.4513 (2.9825)	grad_norm 1.7608 (2.0828/0.8719)	mem 16099MB
[2025-01-18 07:25:50 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][160/312]	eta 0:01:13 lr 0.001021	time 0.4591 (0.4809)	model_time 0.4586 (0.4690)	loss 3.0717 (2.9715)	grad_norm 1.8270 (2.0887/0.8772)	mem 16099MB
[2025-01-18 07:25:55 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][170/312]	eta 0:01:08 lr 0.001020	time 0.4659 (0.4796)	model_time 0.4658 (0.4683)	loss 2.2168 (2.9703)	grad_norm 1.4861 (2.0819/0.8622)	mem 16099MB
[2025-01-18 07:25:59 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][180/312]	eta 0:01:03 lr 0.001020	time 0.4367 (0.4786)	model_time 0.4363 (0.4679)	loss 2.0156 (2.9748)	grad_norm 1.6968 (2.0789/0.8590)	mem 16099MB
[2025-01-18 07:26:04 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][190/312]	eta 0:00:58 lr 0.001019	time 0.4501 (0.4779)	model_time 0.4499 (0.4677)	loss 2.6107 (2.9673)	grad_norm 3.6348 (2.1194/0.8826)	mem 16099MB
[2025-01-18 07:26:08 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][200/312]	eta 0:00:53 lr 0.001019	time 0.4543 (0.4771)	model_time 0.4538 (0.4675)	loss 3.6983 (2.9646)	grad_norm 3.7796 (2.1547/0.9027)	mem 16099MB
[2025-01-18 07:26:13 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][210/312]	eta 0:00:48 lr 0.001018	time 0.4491 (0.4764)	model_time 0.4489 (0.4672)	loss 2.9997 (2.9765)	grad_norm 3.7344 (2.1859/0.9105)	mem 16099MB
[2025-01-18 07:26:18 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][220/312]	eta 0:00:43 lr 0.001017	time 0.4594 (0.4754)	model_time 0.4592 (0.4666)	loss 1.9017 (2.9725)	grad_norm 1.0044 (2.1700/0.9059)	mem 16099MB
[2025-01-18 07:26:22 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][230/312]	eta 0:00:38 lr 0.001017	time 0.4464 (0.4745)	model_time 0.4459 (0.4660)	loss 3.3370 (2.9676)	grad_norm 2.9620 (2.1664/0.8955)	mem 16099MB
[2025-01-18 07:26:27 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][240/312]	eta 0:00:34 lr 0.001016	time 0.4495 (0.4737)	model_time 0.4493 (0.4656)	loss 3.3454 (2.9730)	grad_norm 1.4366 (2.1718/0.8945)	mem 16099MB
[2025-01-18 07:26:32 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][250/312]	eta 0:00:29 lr 0.001016	time 0.4745 (0.4745)	model_time 0.4740 (0.4667)	loss 3.1038 (2.9642)	grad_norm 2.2028 (2.1711/0.8933)	mem 16099MB
[2025-01-18 07:26:37 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][260/312]	eta 0:00:24 lr 0.001015	time 0.4520 (0.4752)	model_time 0.4518 (0.4677)	loss 3.6045 (2.9716)	grad_norm 4.7504 (2.2300/0.9582)	mem 16099MB
[2025-01-18 07:26:41 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][270/312]	eta 0:00:19 lr 0.001015	time 0.4657 (0.4751)	model_time 0.4652 (0.4678)	loss 3.3284 (2.9812)	grad_norm 0.9177 (2.2293/0.9624)	mem 16099MB
[2025-01-18 07:26:46 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][280/312]	eta 0:00:15 lr 0.001014	time 0.4490 (0.4746)	model_time 0.4488 (0.4676)	loss 3.3900 (2.9782)	grad_norm 3.4032 (2.2664/1.0120)	mem 16099MB
[2025-01-18 07:26:51 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][290/312]	eta 0:00:10 lr 0.001013	time 0.4590 (0.4754)	model_time 0.4588 (0.4686)	loss 3.4764 (2.9860)	grad_norm 1.4364 (2.2607/1.0083)	mem 16099MB
[2025-01-18 07:26:56 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][300/312]	eta 0:00:05 lr 0.001013	time 0.5520 (0.4762)	model_time 0.5519 (0.4697)	loss 3.1645 (2.9887)	grad_norm 3.0652 (2.2600/1.0027)	mem 16099MB
[2025-01-18 07:27:00 internimage_t_1k_224] (main.py 510): INFO Train: [200/300][310/312]	eta 0:00:00 lr 0.001012	time 0.4440 (0.4755)	model_time 0.4439 (0.4691)	loss 3.7680 (2.9897)	grad_norm 1.0346 (2.2499/0.9990)	mem 16099MB
[2025-01-18 07:27:01 internimage_t_1k_224] (main.py 519): INFO EPOCH 200 training takes 0:02:28
[2025-01-18 07:27:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_200.pth saving......
[2025-01-18 07:27:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_200.pth saved !!!
[2025-01-18 07:27:09 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.044 (7.044)	Loss 0.7554 (0.7554)	Acc@1 84.033 (84.033)	Acc@5 97.314 (97.314)	Mem 16099MB
[2025-01-18 07:27:13 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.994)	Loss 1.0601 (0.8817)	Acc@1 76.221 (81.470)	Acc@5 94.336 (95.694)	Mem 16099MB
[2025-01-18 07:27:13 internimage_t_1k_224] (main.py 575): INFO [Epoch:200] * Acc@1 81.352 Acc@5 95.727
[2025-01-18 07:27:13 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.4%
[2025-01-18 07:27:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 07:27:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 07:27:14 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.35%
[2025-01-18 07:27:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.182 (7.182)	Loss 0.7858 (0.7858)	Acc@1 85.107 (85.107)	Acc@5 97.534 (97.534)	Mem 16099MB
[2025-01-18 07:27:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.967)	Loss 1.0470 (0.9017)	Acc@1 78.174 (82.331)	Acc@5 94.775 (96.149)	Mem 16099MB
[2025-01-18 07:27:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:200] * Acc@1 82.216 Acc@5 96.175
[2025-01-18 07:27:25 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.2%
[2025-01-18 07:27:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:27:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:27:26 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.22%
[2025-01-18 07:27:29 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][0/312]	eta 0:14:29 lr 0.001012	time 2.7881 (2.7881)	model_time 1.0740 (1.0740)	loss 2.8431 (2.8431)	grad_norm 1.5312 (1.5312/0.0000)	mem 16099MB
[2025-01-18 07:27:34 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][10/312]	eta 0:03:20 lr 0.001012	time 0.4535 (0.6647)	model_time 0.4532 (0.5087)	loss 2.9439 (2.9574)	grad_norm 2.4290 (1.7812/0.6038)	mem 16099MB
[2025-01-18 07:27:38 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][20/312]	eta 0:02:44 lr 0.001011	time 0.4518 (0.5643)	model_time 0.4516 (0.4824)	loss 3.5889 (3.0192)	grad_norm 2.4978 (2.0557/0.7210)	mem 16099MB
[2025-01-18 07:27:43 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][30/312]	eta 0:02:29 lr 0.001010	time 0.4510 (0.5316)	model_time 0.4508 (0.4759)	loss 2.6345 (2.9900)	grad_norm 2.3099 (2.3252/1.1696)	mem 16099MB
[2025-01-18 07:27:47 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][40/312]	eta 0:02:19 lr 0.001010	time 0.4673 (0.5128)	model_time 0.4668 (0.4707)	loss 2.8272 (2.9557)	grad_norm 1.1927 (2.2283/1.1212)	mem 16099MB
[2025-01-18 07:27:52 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][50/312]	eta 0:02:12 lr 0.001009	time 0.5420 (0.5050)	model_time 0.5418 (0.4710)	loss 2.6848 (2.9300)	grad_norm 4.0286 (2.3422/1.1332)	mem 16099MB
[2025-01-18 07:27:57 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][60/312]	eta 0:02:05 lr 0.001009	time 0.4486 (0.4974)	model_time 0.4485 (0.4689)	loss 3.1773 (2.9488)	grad_norm 1.7061 (2.2608/1.0814)	mem 16099MB
[2025-01-18 07:28:01 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][70/312]	eta 0:01:58 lr 0.001008	time 0.4404 (0.4914)	model_time 0.4402 (0.4669)	loss 3.1622 (2.9827)	grad_norm 2.5970 (2.2690/1.0395)	mem 16099MB
[2025-01-18 07:28:06 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][80/312]	eta 0:01:54 lr 0.001008	time 0.4564 (0.4923)	model_time 0.4563 (0.4708)	loss 1.9973 (2.9861)	grad_norm 1.5345 (2.3337/1.0323)	mem 16099MB
[2025-01-18 07:28:11 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][90/312]	eta 0:01:48 lr 0.001007	time 0.5623 (0.4901)	model_time 0.5622 (0.4709)	loss 1.8710 (2.9787)	grad_norm 1.0725 (2.4263/1.1194)	mem 16099MB
[2025-01-18 07:28:16 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][100/312]	eta 0:01:43 lr 0.001006	time 0.4519 (0.4877)	model_time 0.4514 (0.4704)	loss 3.3673 (2.9949)	grad_norm 2.9946 (2.4831/1.2167)	mem 16099MB
[2025-01-18 07:28:20 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][110/312]	eta 0:01:38 lr 0.001006	time 0.4417 (0.4873)	model_time 0.4415 (0.4715)	loss 3.6778 (3.0160)	grad_norm 3.1597 (2.4543/1.1834)	mem 16099MB
[2025-01-18 07:28:25 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][120/312]	eta 0:01:33 lr 0.001005	time 0.4500 (0.4887)	model_time 0.4498 (0.4742)	loss 2.8266 (3.0030)	grad_norm 2.4339 (2.4368/1.1569)	mem 16099MB
[2025-01-18 07:28:30 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][130/312]	eta 0:01:28 lr 0.001005	time 0.4405 (0.4866)	model_time 0.4404 (0.4732)	loss 2.5420 (2.9930)	grad_norm 1.1077 (2.3939/1.1323)	mem 16099MB
[2025-01-18 07:28:35 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][140/312]	eta 0:01:23 lr 0.001004	time 0.4527 (0.4844)	model_time 0.4523 (0.4719)	loss 3.5110 (2.9804)	grad_norm 3.3149 (2.3677/1.1058)	mem 16099MB
[2025-01-18 07:28:39 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][150/312]	eta 0:01:18 lr 0.001004	time 0.4709 (0.4841)	model_time 0.4708 (0.4724)	loss 4.0294 (3.0072)	grad_norm 1.6903 (2.3485/1.0996)	mem 16099MB
[2025-01-18 07:28:44 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][160/312]	eta 0:01:13 lr 0.001003	time 0.4505 (0.4848)	model_time 0.4503 (0.4738)	loss 3.5615 (3.0160)	grad_norm 1.7998 (2.3140/1.0879)	mem 16099MB
[2025-01-18 07:28:49 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][170/312]	eta 0:01:08 lr 0.001002	time 0.4628 (0.4833)	model_time 0.4626 (0.4730)	loss 3.0037 (3.0152)	grad_norm 1.0517 (2.2819/1.0782)	mem 16099MB
[2025-01-18 07:28:54 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][180/312]	eta 0:01:03 lr 0.001002	time 0.4556 (0.4820)	model_time 0.4551 (0.4722)	loss 4.0077 (3.0219)	grad_norm 4.7112 (2.3003/1.1122)	mem 16099MB
[2025-01-18 07:28:58 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][190/312]	eta 0:00:58 lr 0.001001	time 0.4711 (0.4810)	model_time 0.4709 (0.4717)	loss 3.0628 (3.0342)	grad_norm 3.5910 (2.3090/1.1017)	mem 16099MB
[2025-01-18 07:29:03 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][200/312]	eta 0:00:53 lr 0.001001	time 0.5332 (0.4800)	model_time 0.5327 (0.4711)	loss 2.6406 (3.0365)	grad_norm 4.1165 (2.3265/1.1001)	mem 16099MB
[2025-01-18 07:29:08 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][210/312]	eta 0:00:48 lr 0.001000	time 0.4547 (0.4804)	model_time 0.4541 (0.4719)	loss 3.1314 (3.0295)	grad_norm 1.8983 (2.2952/1.0861)	mem 16099MB
[2025-01-18 07:29:12 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][220/312]	eta 0:00:44 lr 0.001000	time 0.4407 (0.4800)	model_time 0.4402 (0.4719)	loss 2.6702 (3.0303)	grad_norm 2.9394 (2.2907/1.0668)	mem 16099MB
[2025-01-18 07:29:17 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][230/312]	eta 0:00:39 lr 0.000999	time 0.4549 (0.4789)	model_time 0.4548 (0.4711)	loss 3.1442 (3.0307)	grad_norm 4.1347 (2.3021/1.0580)	mem 16099MB
[2025-01-18 07:29:22 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][240/312]	eta 0:00:34 lr 0.000998	time 0.4540 (0.4782)	model_time 0.4538 (0.4708)	loss 3.0343 (3.0318)	grad_norm 1.9453 (2.3098/1.0554)	mem 16099MB
[2025-01-18 07:29:26 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][250/312]	eta 0:00:29 lr 0.000998	time 0.4543 (0.4777)	model_time 0.4539 (0.4705)	loss 3.8194 (3.0315)	grad_norm 1.0140 (2.2844/1.0473)	mem 16099MB
[2025-01-18 07:29:31 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][260/312]	eta 0:00:24 lr 0.000997	time 0.5358 (0.4771)	model_time 0.5352 (0.4702)	loss 2.4585 (3.0360)	grad_norm 2.1771 (2.2685/1.0373)	mem 16099MB
[2025-01-18 07:29:35 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][270/312]	eta 0:00:20 lr 0.000997	time 0.4440 (0.4766)	model_time 0.4438 (0.4700)	loss 3.4977 (3.0431)	grad_norm 2.5596 (2.2605/1.0234)	mem 16099MB
[2025-01-18 07:29:40 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][280/312]	eta 0:00:15 lr 0.000996	time 0.4464 (0.4762)	model_time 0.4462 (0.4698)	loss 3.2746 (3.0431)	grad_norm 3.8507 (2.2548/1.0177)	mem 16099MB
[2025-01-18 07:29:45 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][290/312]	eta 0:00:10 lr 0.000996	time 0.4484 (0.4760)	model_time 0.4482 (0.4698)	loss 3.1750 (3.0395)	grad_norm 1.3353 (2.2348/1.0077)	mem 16099MB
[2025-01-18 07:29:49 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][300/312]	eta 0:00:05 lr 0.000995	time 0.4435 (0.4754)	model_time 0.4434 (0.4693)	loss 3.0046 (3.0457)	grad_norm 1.2272 (2.2475/1.0156)	mem 16099MB
[2025-01-18 07:29:54 internimage_t_1k_224] (main.py 510): INFO Train: [201/300][310/312]	eta 0:00:00 lr 0.000994	time 0.4402 (0.4744)	model_time 0.4401 (0.4686)	loss 2.9169 (3.0383)	grad_norm 2.0895 (2.2834/1.0307)	mem 16099MB
[2025-01-18 07:29:54 internimage_t_1k_224] (main.py 519): INFO EPOCH 201 training takes 0:02:27
[2025-01-18 07:29:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_201.pth saving......
[2025-01-18 07:29:55 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_201.pth saved !!!
[2025-01-18 07:30:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.190 (7.190)	Loss 0.7533 (0.7533)	Acc@1 83.643 (83.643)	Acc@5 96.973 (96.973)	Mem 16099MB
[2025-01-18 07:30:06 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.991)	Loss 1.0260 (0.8674)	Acc@1 77.002 (81.319)	Acc@5 94.214 (95.710)	Mem 16099MB
[2025-01-18 07:30:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:201] * Acc@1 81.206 Acc@5 95.723
[2025-01-18 07:30:06 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.2%
[2025-01-18 07:30:06 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.35%
[2025-01-18 07:30:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.158 (8.158)	Loss 0.7848 (0.7848)	Acc@1 85.156 (85.156)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 07:30:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.098)	Loss 1.0459 (0.9007)	Acc@1 78.174 (82.355)	Acc@5 94.849 (96.163)	Mem 16099MB
[2025-01-18 07:30:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:201] * Acc@1 82.240 Acc@5 96.185
[2025-01-18 07:30:19 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.2%
[2025-01-18 07:30:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:30:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:30:20 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.24%
[2025-01-18 07:30:22 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][0/312]	eta 0:11:23 lr 0.000994	time 2.1903 (2.1903)	model_time 0.4666 (0.4666)	loss 3.7624 (3.7624)	grad_norm 4.8233 (4.8233/0.0000)	mem 16099MB
[2025-01-18 07:30:27 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][10/312]	eta 0:03:16 lr 0.000994	time 0.6729 (0.6492)	model_time 0.6726 (0.4922)	loss 3.2522 (3.0144)	grad_norm 1.2832 (2.1044/1.6097)	mem 16099MB
[2025-01-18 07:30:32 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][20/312]	eta 0:02:46 lr 0.000993	time 0.4424 (0.5719)	model_time 0.4420 (0.4895)	loss 3.0472 (3.0086)	grad_norm 1.6767 (2.2236/1.3781)	mem 16099MB
[2025-01-18 07:30:37 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][30/312]	eta 0:02:33 lr 0.000993	time 0.4430 (0.5459)	model_time 0.4425 (0.4899)	loss 2.8809 (2.9919)	grad_norm 1.3849 (2.2052/1.2017)	mem 16099MB
[2025-01-18 07:30:41 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][40/312]	eta 0:02:22 lr 0.000992	time 0.4625 (0.5244)	model_time 0.4623 (0.4821)	loss 1.9473 (2.9596)	grad_norm 1.1926 (2.0955/1.1186)	mem 16099MB
[2025-01-18 07:30:46 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][50/312]	eta 0:02:13 lr 0.000991	time 0.4531 (0.5112)	model_time 0.4526 (0.4771)	loss 3.1190 (2.9770)	grad_norm 3.2530 (2.2197/1.0892)	mem 16099MB
[2025-01-18 07:30:51 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][60/312]	eta 0:02:06 lr 0.000991	time 0.4506 (0.5021)	model_time 0.4502 (0.4735)	loss 3.2438 (2.9887)	grad_norm 1.2668 (2.2364/1.0330)	mem 16099MB
[2025-01-18 07:30:55 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][70/312]	eta 0:02:00 lr 0.000990	time 0.5299 (0.4964)	model_time 0.5295 (0.4718)	loss 3.0078 (3.0310)	grad_norm 1.8835 (2.2895/1.0769)	mem 16099MB
[2025-01-18 07:31:00 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][80/312]	eta 0:01:55 lr 0.000990	time 0.4424 (0.4962)	model_time 0.4423 (0.4746)	loss 3.3595 (3.0358)	grad_norm 1.7484 (2.3147/1.0964)	mem 16099MB
[2025-01-18 07:31:05 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][90/312]	eta 0:01:49 lr 0.000989	time 0.4436 (0.4919)	model_time 0.4431 (0.4726)	loss 2.7218 (3.0237)	grad_norm 1.1141 (2.2371/1.0675)	mem 16099MB
[2025-01-18 07:31:10 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][100/312]	eta 0:01:44 lr 0.000989	time 0.5322 (0.4918)	model_time 0.5321 (0.4744)	loss 3.2976 (3.0421)	grad_norm 2.5649 (2.1776/1.0354)	mem 16099MB
[2025-01-18 07:31:14 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][110/312]	eta 0:01:38 lr 0.000988	time 0.4505 (0.4892)	model_time 0.4504 (0.4733)	loss 3.5990 (3.0312)	grad_norm 0.9947 (2.1337/1.0106)	mem 16099MB
[2025-01-18 07:31:19 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][120/312]	eta 0:01:33 lr 0.000987	time 0.5150 (0.4872)	model_time 0.5149 (0.4726)	loss 2.7611 (3.0127)	grad_norm 2.2055 (2.1022/0.9944)	mem 16099MB
[2025-01-18 07:31:24 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][130/312]	eta 0:01:28 lr 0.000987	time 0.4577 (0.4868)	model_time 0.4576 (0.4733)	loss 3.3699 (2.9983)	grad_norm 3.3242 (2.1452/0.9966)	mem 16099MB
[2025-01-18 07:31:29 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][140/312]	eta 0:01:24 lr 0.000986	time 0.4606 (0.4884)	model_time 0.4604 (0.4759)	loss 2.9441 (2.9772)	grad_norm 4.3716 (2.1792/0.9951)	mem 16099MB
[2025-01-18 07:31:34 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][150/312]	eta 0:01:19 lr 0.000986	time 0.4466 (0.4885)	model_time 0.4462 (0.4767)	loss 2.8036 (2.9821)	grad_norm 1.5688 (2.1865/0.9819)	mem 16099MB
[2025-01-18 07:31:38 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][160/312]	eta 0:01:13 lr 0.000985	time 0.4516 (0.4865)	model_time 0.4514 (0.4755)	loss 3.1492 (2.9847)	grad_norm 1.2690 (2.1435/0.9675)	mem 16099MB
[2025-01-18 07:31:43 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][170/312]	eta 0:01:08 lr 0.000985	time 0.4548 (0.4851)	model_time 0.4547 (0.4746)	loss 3.4846 (2.9791)	grad_norm 2.8759 (2.1415/0.9590)	mem 16099MB
[2025-01-18 07:31:48 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][180/312]	eta 0:01:03 lr 0.000984	time 0.4499 (0.4841)	model_time 0.4498 (0.4742)	loss 3.2151 (2.9800)	grad_norm 2.5127 (2.1525/0.9555)	mem 16099MB
[2025-01-18 07:31:53 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][190/312]	eta 0:00:59 lr 0.000984	time 0.4425 (0.4848)	model_time 0.4424 (0.4754)	loss 3.1535 (2.9824)	grad_norm 2.9122 (2.1445/0.9502)	mem 16099MB
[2025-01-18 07:31:57 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][200/312]	eta 0:00:54 lr 0.000983	time 0.4415 (0.4834)	model_time 0.4414 (0.4744)	loss 3.5002 (2.9883)	grad_norm 1.5287 (2.1263/0.9378)	mem 16099MB
[2025-01-18 07:32:02 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][210/312]	eta 0:00:49 lr 0.000982	time 0.4564 (0.4821)	model_time 0.4560 (0.4736)	loss 3.4565 (2.9846)	grad_norm 2.4161 (2.1338/0.9315)	mem 16099MB
[2025-01-18 07:32:06 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][220/312]	eta 0:00:44 lr 0.000982	time 0.4511 (0.4808)	model_time 0.4507 (0.4727)	loss 3.0714 (2.9855)	grad_norm 1.7565 (2.1665/0.9513)	mem 16099MB
[2025-01-18 07:32:11 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][230/312]	eta 0:00:39 lr 0.000981	time 0.4424 (0.4801)	model_time 0.4422 (0.4723)	loss 3.5874 (2.9863)	grad_norm 1.8331 (2.1410/0.9438)	mem 16099MB
[2025-01-18 07:32:16 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][240/312]	eta 0:00:34 lr 0.000981	time 0.4626 (0.4805)	model_time 0.4624 (0.4730)	loss 2.8739 (2.9910)	grad_norm 1.8289 (2.1381/0.9299)	mem 16099MB
[2025-01-18 07:32:21 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][250/312]	eta 0:00:29 lr 0.000980	time 0.4458 (0.4801)	model_time 0.4454 (0.4729)	loss 3.4609 (2.9928)	grad_norm 1.4183 (2.1730/0.9634)	mem 16099MB
[2025-01-18 07:32:25 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][260/312]	eta 0:00:24 lr 0.000980	time 0.4517 (0.4797)	model_time 0.4515 (0.4728)	loss 2.7671 (2.9940)	grad_norm 1.7959 (2.1620/0.9527)	mem 16099MB
[2025-01-18 07:32:30 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][270/312]	eta 0:00:20 lr 0.000979	time 0.4422 (0.4794)	model_time 0.4420 (0.4727)	loss 3.1830 (2.9887)	grad_norm 1.7178 (2.1789/0.9459)	mem 16099MB
[2025-01-18 07:32:34 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][280/312]	eta 0:00:15 lr 0.000978	time 0.4696 (0.4786)	model_time 0.4694 (0.4722)	loss 3.4334 (2.9913)	grad_norm 1.1981 (2.1668/0.9374)	mem 16099MB
[2025-01-18 07:32:39 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][290/312]	eta 0:00:10 lr 0.000978	time 0.4537 (0.4782)	model_time 0.4532 (0.4720)	loss 3.4143 (2.9916)	grad_norm 2.6746 (2.1796/0.9326)	mem 16099MB
[2025-01-18 07:32:44 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][300/312]	eta 0:00:05 lr 0.000977	time 0.4394 (0.4782)	model_time 0.4393 (0.4721)	loss 3.4338 (2.9977)	grad_norm 1.6028 (2.2023/0.9574)	mem 16099MB
[2025-01-18 07:32:48 internimage_t_1k_224] (main.py 510): INFO Train: [202/300][310/312]	eta 0:00:00 lr 0.000977	time 0.4403 (0.4771)	model_time 0.4402 (0.4712)	loss 2.9765 (3.0056)	grad_norm 3.2045 (2.2263/0.9303)	mem 16099MB
[2025-01-18 07:32:49 internimage_t_1k_224] (main.py 519): INFO EPOCH 202 training takes 0:02:28
[2025-01-18 07:32:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_202.pth saving......
[2025-01-18 07:32:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_202.pth saved !!!
[2025-01-18 07:32:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.542 (7.542)	Loss 0.7785 (0.7785)	Acc@1 83.643 (83.643)	Acc@5 96.826 (96.826)	Mem 16099MB
[2025-01-18 07:33:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.017)	Loss 1.0599 (0.8779)	Acc@1 76.343 (81.459)	Acc@5 93.896 (95.648)	Mem 16099MB
[2025-01-18 07:33:01 internimage_t_1k_224] (main.py 575): INFO [Epoch:202] * Acc@1 81.298 Acc@5 95.633
[2025-01-18 07:33:01 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.3%
[2025-01-18 07:33:01 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.35%
[2025-01-18 07:33:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.369 (8.369)	Loss 0.7836 (0.7836)	Acc@1 85.132 (85.132)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 07:33:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.113)	Loss 1.0446 (0.8994)	Acc@1 78.271 (82.389)	Acc@5 94.849 (96.185)	Mem 16099MB
[2025-01-18 07:33:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:202] * Acc@1 82.262 Acc@5 96.203
[2025-01-18 07:33:14 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.3%
[2025-01-18 07:33:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:33:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:33:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.26%
[2025-01-18 07:33:17 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][0/312]	eta 0:10:56 lr 0.000977	time 2.1028 (2.1028)	model_time 0.4763 (0.4763)	loss 3.5303 (3.5303)	grad_norm 2.3191 (2.3191/0.0000)	mem 16099MB
[2025-01-18 07:33:22 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][10/312]	eta 0:03:12 lr 0.000976	time 0.4644 (0.6388)	model_time 0.4640 (0.4907)	loss 2.3627 (3.1300)	grad_norm 5.4899 (2.7101/1.2467)	mem 16099MB
[2025-01-18 07:33:27 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][20/312]	eta 0:02:44 lr 0.000975	time 0.6663 (0.5648)	model_time 0.6662 (0.4870)	loss 2.0213 (2.9834)	grad_norm 1.0617 (2.7203/1.0786)	mem 16099MB
[2025-01-18 07:33:32 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][30/312]	eta 0:02:31 lr 0.000975	time 0.4511 (0.5358)	model_time 0.4507 (0.4830)	loss 2.3018 (3.0003)	grad_norm 3.9818 (2.7579/1.1675)	mem 16099MB
[2025-01-18 07:33:36 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][40/312]	eta 0:02:21 lr 0.000974	time 0.4455 (0.5191)	model_time 0.4450 (0.4792)	loss 3.0656 (3.0561)	grad_norm 2.1658 (2.6290/1.0905)	mem 16099MB
[2025-01-18 07:33:41 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][50/312]	eta 0:02:14 lr 0.000974	time 0.4573 (0.5125)	model_time 0.4568 (0.4803)	loss 2.8692 (3.0490)	grad_norm 1.4203 (2.6688/1.0948)	mem 16099MB
[2025-01-18 07:33:46 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][60/312]	eta 0:02:07 lr 0.000973	time 0.5414 (0.5070)	model_time 0.5412 (0.4800)	loss 1.9013 (3.0610)	grad_norm 1.2845 (2.7312/1.1759)	mem 16099MB
[2025-01-18 07:33:51 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][70/312]	eta 0:02:01 lr 0.000973	time 0.4642 (0.5008)	model_time 0.4640 (0.4775)	loss 2.7374 (3.0337)	grad_norm 1.4952 (2.6224/1.1497)	mem 16099MB
[2025-01-18 07:33:55 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][80/312]	eta 0:01:55 lr 0.000972	time 0.4538 (0.4958)	model_time 0.4533 (0.4754)	loss 3.0935 (3.0313)	grad_norm 3.5946 (2.5627/1.1180)	mem 16099MB
[2025-01-18 07:34:00 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][90/312]	eta 0:01:49 lr 0.000972	time 0.5353 (0.4924)	model_time 0.5349 (0.4742)	loss 2.0061 (3.0377)	grad_norm 2.0084 (2.4718/1.1020)	mem 16099MB
[2025-01-18 07:34:04 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][100/312]	eta 0:01:43 lr 0.000971	time 0.4640 (0.4896)	model_time 0.4636 (0.4732)	loss 2.0681 (3.0245)	grad_norm 1.8816 (2.4537/1.0775)	mem 16099MB
[2025-01-18 07:34:09 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][110/312]	eta 0:01:38 lr 0.000970	time 0.4603 (0.4871)	model_time 0.4601 (0.4721)	loss 3.6526 (3.0300)	grad_norm 2.8837 (2.4253/1.0571)	mem 16099MB
[2025-01-18 07:34:14 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][120/312]	eta 0:01:33 lr 0.000970	time 0.5431 (0.4856)	model_time 0.5429 (0.4718)	loss 3.0775 (3.0352)	grad_norm 1.4219 (2.4159/1.0367)	mem 16099MB
[2025-01-18 07:34:18 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][130/312]	eta 0:01:28 lr 0.000969	time 0.4634 (0.4840)	model_time 0.4629 (0.4713)	loss 3.1652 (3.0247)	grad_norm 1.9365 (2.4383/1.0704)	mem 16099MB
[2025-01-18 07:34:23 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][140/312]	eta 0:01:23 lr 0.000969	time 0.4482 (0.4847)	model_time 0.4478 (0.4728)	loss 3.6245 (3.0298)	grad_norm 3.2924 (2.4227/1.0563)	mem 16099MB
[2025-01-18 07:34:28 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][150/312]	eta 0:01:18 lr 0.000968	time 0.4424 (0.4842)	model_time 0.4423 (0.4730)	loss 3.4384 (3.0159)	grad_norm 1.0627 (2.4071/1.0417)	mem 16099MB
[2025-01-18 07:34:33 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][160/312]	eta 0:01:13 lr 0.000968	time 0.4578 (0.4823)	model_time 0.4573 (0.4719)	loss 3.7675 (3.0129)	grad_norm 1.9668 (2.3925/1.0346)	mem 16099MB
[2025-01-18 07:34:37 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][170/312]	eta 0:01:08 lr 0.000967	time 0.4844 (0.4808)	model_time 0.4840 (0.4710)	loss 3.4476 (3.0240)	grad_norm 1.1954 (2.3857/1.0312)	mem 16099MB
[2025-01-18 07:34:42 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][180/312]	eta 0:01:03 lr 0.000966	time 0.4444 (0.4800)	model_time 0.4439 (0.4707)	loss 2.1078 (3.0147)	grad_norm 0.9751 (2.3739/1.0253)	mem 16099MB
[2025-01-18 07:34:46 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][190/312]	eta 0:00:58 lr 0.000966	time 0.4500 (0.4786)	model_time 0.4498 (0.4697)	loss 2.7907 (3.0152)	grad_norm 3.3472 (2.3803/1.0347)	mem 16099MB
[2025-01-18 07:34:51 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][200/312]	eta 0:00:53 lr 0.000965	time 0.4734 (0.4780)	model_time 0.4733 (0.4695)	loss 3.1905 (3.0140)	grad_norm 2.2107 (2.3732/1.0390)	mem 16099MB
[2025-01-18 07:34:56 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][210/312]	eta 0:00:48 lr 0.000965	time 0.4709 (0.4773)	model_time 0.4705 (0.4693)	loss 2.9565 (3.0224)	grad_norm 1.8597 (2.3563/1.0276)	mem 16099MB
[2025-01-18 07:35:00 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][220/312]	eta 0:00:43 lr 0.000964	time 0.4438 (0.4770)	model_time 0.4436 (0.4693)	loss 3.0563 (3.0149)	grad_norm 1.7824 (2.3297/1.0203)	mem 16099MB
[2025-01-18 07:35:05 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][230/312]	eta 0:00:39 lr 0.000964	time 0.4598 (0.4766)	model_time 0.4596 (0.4692)	loss 3.2966 (3.0074)	grad_norm 1.6391 (2.3078/1.0097)	mem 16099MB
[2025-01-18 07:35:10 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][240/312]	eta 0:00:34 lr 0.000963	time 0.4410 (0.4759)	model_time 0.4406 (0.4688)	loss 2.4091 (3.0086)	grad_norm 1.3728 (2.3065/1.0086)	mem 16099MB
[2025-01-18 07:35:14 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][250/312]	eta 0:00:29 lr 0.000963	time 0.4606 (0.4754)	model_time 0.4605 (0.4685)	loss 3.0226 (3.0094)	grad_norm 1.2094 (2.3219/1.0058)	mem 16099MB
[2025-01-18 07:35:19 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][260/312]	eta 0:00:24 lr 0.000962	time 0.4447 (0.4749)	model_time 0.4443 (0.4683)	loss 2.1142 (3.0004)	grad_norm 1.3825 (2.3074/0.9970)	mem 16099MB
[2025-01-18 07:35:23 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][270/312]	eta 0:00:19 lr 0.000961	time 0.4604 (0.4744)	model_time 0.4599 (0.4680)	loss 2.5725 (2.9960)	grad_norm 1.9268 (2.3110/0.9877)	mem 16099MB
[2025-01-18 07:35:28 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][280/312]	eta 0:00:15 lr 0.000961	time 0.4523 (0.4738)	model_time 0.4518 (0.4676)	loss 3.0237 (2.9962)	grad_norm 3.8745 (2.3291/0.9841)	mem 16099MB
[2025-01-18 07:35:33 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][290/312]	eta 0:00:10 lr 0.000960	time 0.4598 (0.4739)	model_time 0.4594 (0.4679)	loss 2.9033 (2.9896)	grad_norm 1.6437 (2.3153/0.9832)	mem 16099MB
[2025-01-18 07:35:38 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][300/312]	eta 0:00:05 lr 0.000960	time 0.6167 (0.4741)	model_time 0.6166 (0.4684)	loss 3.0249 (2.9928)	grad_norm 1.0456 (2.3104/0.9820)	mem 16099MB
[2025-01-18 07:35:42 internimage_t_1k_224] (main.py 510): INFO Train: [203/300][310/312]	eta 0:00:00 lr 0.000959	time 0.4433 (0.4730)	model_time 0.4431 (0.4674)	loss 3.1566 (2.9910)	grad_norm 1.8089 (2.2753/0.9587)	mem 16099MB
[2025-01-18 07:35:43 internimage_t_1k_224] (main.py 519): INFO EPOCH 203 training takes 0:02:27
[2025-01-18 07:35:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_203.pth saving......
[2025-01-18 07:35:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_203.pth saved !!!
[2025-01-18 07:35:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.482 (7.482)	Loss 0.7492 (0.7492)	Acc@1 83.936 (83.936)	Acc@5 97.144 (97.144)	Mem 16099MB
[2025-01-18 07:35:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.008)	Loss 1.0474 (0.8750)	Acc@1 77.368 (81.374)	Acc@5 94.482 (95.610)	Mem 16099MB
[2025-01-18 07:35:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:203] * Acc@1 81.296 Acc@5 95.633
[2025-01-18 07:35:55 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.3%
[2025-01-18 07:35:55 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.35%
[2025-01-18 07:36:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.551 (8.551)	Loss 0.7827 (0.7827)	Acc@1 85.059 (85.059)	Acc@5 97.534 (97.534)	Mem 16099MB
[2025-01-18 07:36:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.135)	Loss 1.0430 (0.8983)	Acc@1 78.271 (82.426)	Acc@5 94.873 (96.196)	Mem 16099MB
[2025-01-18 07:36:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:203] * Acc@1 82.298 Acc@5 96.213
[2025-01-18 07:36:08 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.3%
[2025-01-18 07:36:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:36:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:36:09 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.30%
[2025-01-18 07:36:11 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][0/312]	eta 0:11:47 lr 0.000959	time 2.2663 (2.2663)	model_time 0.4984 (0.4984)	loss 2.7093 (2.7093)	grad_norm 2.5100 (2.5100/0.0000)	mem 16099MB
[2025-01-18 07:36:16 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][10/312]	eta 0:03:10 lr 0.000959	time 0.4612 (0.6302)	model_time 0.4608 (0.4692)	loss 3.3401 (2.9715)	grad_norm 5.7954 (2.5889/1.3513)	mem 16099MB
[2025-01-18 07:36:21 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][20/312]	eta 0:02:41 lr 0.000958	time 0.4497 (0.5531)	model_time 0.4493 (0.4686)	loss 3.6050 (3.1672)	grad_norm 1.6297 (2.3559/1.0768)	mem 16099MB
[2025-01-18 07:36:25 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][30/312]	eta 0:02:28 lr 0.000957	time 0.5440 (0.5279)	model_time 0.5435 (0.4705)	loss 2.8587 (3.1410)	grad_norm 2.1992 (2.3058/0.9618)	mem 16099MB
[2025-01-18 07:36:30 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][40/312]	eta 0:02:19 lr 0.000957	time 0.4408 (0.5124)	model_time 0.4403 (0.4689)	loss 3.4568 (3.0955)	grad_norm 6.3317 (2.5631/1.1750)	mem 16099MB
[2025-01-18 07:36:35 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][50/312]	eta 0:02:12 lr 0.000956	time 0.4515 (0.5068)	model_time 0.4510 (0.4718)	loss 2.0020 (3.0610)	grad_norm 1.3185 (2.6538/1.2055)	mem 16099MB
[2025-01-18 07:36:40 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][60/312]	eta 0:02:06 lr 0.000956	time 0.4577 (0.5023)	model_time 0.4572 (0.4730)	loss 2.1078 (3.0431)	grad_norm 1.8972 (2.5517/1.1461)	mem 16099MB
[2025-01-18 07:36:44 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][70/312]	eta 0:02:00 lr 0.000955	time 0.4545 (0.4971)	model_time 0.4541 (0.4718)	loss 3.3207 (3.0536)	grad_norm 3.1053 (2.6166/1.2316)	mem 16099MB
[2025-01-18 07:36:49 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][80/312]	eta 0:01:54 lr 0.000955	time 0.4659 (0.4939)	model_time 0.4658 (0.4717)	loss 3.8578 (3.0428)	grad_norm 2.3817 (2.5800/1.1887)	mem 16099MB
[2025-01-18 07:36:54 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][90/312]	eta 0:01:49 lr 0.000954	time 0.5716 (0.4935)	model_time 0.5715 (0.4737)	loss 3.1549 (3.0493)	grad_norm 1.4932 (2.4931/1.1661)	mem 16099MB
[2025-01-18 07:36:59 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][100/312]	eta 0:01:44 lr 0.000953	time 0.4668 (0.4907)	model_time 0.4667 (0.4728)	loss 3.2027 (3.0261)	grad_norm 3.5175 (2.4486/1.1651)	mem 16099MB
[2025-01-18 07:37:03 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][110/312]	eta 0:01:38 lr 0.000953	time 0.4497 (0.4876)	model_time 0.4493 (0.4713)	loss 3.0996 (3.0325)	grad_norm 2.9613 (2.5278/1.1986)	mem 16099MB
[2025-01-18 07:37:08 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][120/312]	eta 0:01:33 lr 0.000952	time 0.4397 (0.4851)	model_time 0.4393 (0.4701)	loss 2.6233 (3.0255)	grad_norm 3.1636 (2.5917/1.2134)	mem 16099MB
[2025-01-18 07:37:12 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][130/312]	eta 0:01:28 lr 0.000952	time 0.4483 (0.4843)	model_time 0.4482 (0.4704)	loss 2.0315 (3.0132)	grad_norm 2.4622 (2.5949/1.1979)	mem 16099MB
[2025-01-18 07:37:17 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][140/312]	eta 0:01:22 lr 0.000951	time 0.4476 (0.4821)	model_time 0.4474 (0.4691)	loss 3.2311 (3.0251)	grad_norm 2.2074 (2.5968/1.1801)	mem 16099MB
[2025-01-18 07:37:22 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][150/312]	eta 0:01:18 lr 0.000951	time 0.4950 (0.4824)	model_time 0.4946 (0.4703)	loss 1.9928 (3.0243)	grad_norm 1.1985 (2.5681/1.1612)	mem 16099MB
[2025-01-18 07:37:26 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][160/312]	eta 0:01:13 lr 0.000950	time 0.4426 (0.4812)	model_time 0.4424 (0.4698)	loss 2.6539 (3.0155)	grad_norm 2.2773 (2.5435/1.1324)	mem 16099MB
[2025-01-18 07:37:31 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][170/312]	eta 0:01:08 lr 0.000950	time 0.4471 (0.4795)	model_time 0.4470 (0.4688)	loss 2.0761 (3.0196)	grad_norm 2.3946 (2.5442/1.1054)	mem 16099MB
[2025-01-18 07:37:36 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][180/312]	eta 0:01:03 lr 0.000949	time 0.4538 (0.4785)	model_time 0.4537 (0.4684)	loss 3.1181 (3.0132)	grad_norm 1.1891 (2.5298/1.1033)	mem 16099MB
[2025-01-18 07:37:40 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][190/312]	eta 0:00:58 lr 0.000948	time 0.4510 (0.4772)	model_time 0.4508 (0.4676)	loss 2.7944 (3.0071)	grad_norm 2.8808 (2.5110/1.1003)	mem 16099MB
[2025-01-18 07:37:45 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][200/312]	eta 0:00:53 lr 0.000948	time 0.4446 (0.4763)	model_time 0.4442 (0.4671)	loss 3.4537 (3.0184)	grad_norm 2.2082 (2.4756/1.0929)	mem 16099MB
[2025-01-18 07:37:49 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][210/312]	eta 0:00:48 lr 0.000947	time 0.4450 (0.4759)	model_time 0.4446 (0.4671)	loss 2.1767 (3.0071)	grad_norm 4.8818 (2.4603/1.1002)	mem 16099MB
[2025-01-18 07:37:54 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][220/312]	eta 0:00:43 lr 0.000947	time 0.4549 (0.4754)	model_time 0.4547 (0.4670)	loss 2.4484 (3.0158)	grad_norm 3.4454 (2.4815/1.0971)	mem 16099MB
[2025-01-18 07:37:59 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][230/312]	eta 0:00:38 lr 0.000946	time 0.4410 (0.4749)	model_time 0.4406 (0.4669)	loss 3.3905 (3.0227)	grad_norm 2.1258 (2.4742/1.0805)	mem 16099MB
[2025-01-18 07:38:03 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][240/312]	eta 0:00:34 lr 0.000946	time 0.4438 (0.4750)	model_time 0.4436 (0.4672)	loss 3.0455 (3.0210)	grad_norm 1.7874 (2.4511/1.0712)	mem 16099MB
[2025-01-18 07:38:08 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][250/312]	eta 0:00:29 lr 0.000945	time 0.5318 (0.4748)	model_time 0.5316 (0.4674)	loss 2.8235 (3.0278)	grad_norm 3.4618 (2.4504/1.0641)	mem 16099MB
[2025-01-18 07:38:13 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][260/312]	eta 0:00:24 lr 0.000945	time 0.4756 (0.4748)	model_time 0.4751 (0.4676)	loss 3.0106 (3.0286)	grad_norm 1.8788 (2.4246/1.0590)	mem 16099MB
[2025-01-18 07:38:18 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][270/312]	eta 0:00:19 lr 0.000944	time 0.4487 (0.4745)	model_time 0.4483 (0.4676)	loss 3.5707 (3.0268)	grad_norm 1.6779 (2.3894/1.0570)	mem 16099MB
[2025-01-18 07:38:22 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][280/312]	eta 0:00:15 lr 0.000943	time 0.4572 (0.4744)	model_time 0.4567 (0.4677)	loss 3.0478 (3.0256)	grad_norm 2.4751 (2.4037/1.0607)	mem 16099MB
[2025-01-18 07:38:27 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][290/312]	eta 0:00:10 lr 0.000943	time 0.4458 (0.4741)	model_time 0.4453 (0.4676)	loss 2.7000 (3.0215)	grad_norm 2.4167 (2.3869/1.0511)	mem 16099MB
[2025-01-18 07:38:32 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][300/312]	eta 0:00:05 lr 0.000942	time 0.4368 (0.4738)	model_time 0.4367 (0.4675)	loss 2.5122 (3.0165)	grad_norm 1.3029 (2.3720/1.0458)	mem 16099MB
[2025-01-18 07:38:36 internimage_t_1k_224] (main.py 510): INFO Train: [204/300][310/312]	eta 0:00:00 lr 0.000942	time 0.4398 (0.4732)	model_time 0.4396 (0.4671)	loss 3.8008 (3.0194)	grad_norm 1.4968 (2.3441/1.0248)	mem 16099MB
[2025-01-18 07:38:37 internimage_t_1k_224] (main.py 519): INFO EPOCH 204 training takes 0:02:27
[2025-01-18 07:38:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_204.pth saving......
[2025-01-18 07:38:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_204.pth saved !!!
[2025-01-18 07:38:45 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.329 (7.329)	Loss 0.7778 (0.7778)	Acc@1 83.911 (83.911)	Acc@5 97.070 (97.070)	Mem 16099MB
[2025-01-18 07:38:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.998)	Loss 1.0654 (0.8882)	Acc@1 76.343 (81.392)	Acc@5 94.214 (95.681)	Mem 16099MB
[2025-01-18 07:38:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:204] * Acc@1 81.284 Acc@5 95.711
[2025-01-18 07:38:49 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.3%
[2025-01-18 07:38:49 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.35%
[2025-01-18 07:38:57 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.193 (8.193)	Loss 0.7819 (0.7819)	Acc@1 84.985 (84.985)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 07:39:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.113)	Loss 1.0413 (0.8971)	Acc@1 78.296 (82.429)	Acc@5 94.873 (96.185)	Mem 16099MB
[2025-01-18 07:39:01 internimage_t_1k_224] (main.py 575): INFO [Epoch:204] * Acc@1 82.302 Acc@5 96.207
[2025-01-18 07:39:01 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.3%
[2025-01-18 07:39:01 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:39:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:39:03 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.30%
[2025-01-18 07:39:06 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][0/312]	eta 0:13:33 lr 0.000942	time 2.6075 (2.6075)	model_time 0.4687 (0.4687)	loss 3.2035 (3.2035)	grad_norm 1.0833 (1.0833/0.0000)	mem 16099MB
[2025-01-18 07:39:10 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][10/312]	eta 0:03:18 lr 0.000941	time 0.4525 (0.6558)	model_time 0.4521 (0.4611)	loss 2.1758 (2.8836)	grad_norm 4.4473 (1.9976/0.9378)	mem 16099MB
[2025-01-18 07:39:15 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][20/312]	eta 0:02:45 lr 0.000941	time 0.4583 (0.5662)	model_time 0.4582 (0.4641)	loss 3.0693 (2.9132)	grad_norm 2.1134 (2.2151/1.0397)	mem 16099MB
[2025-01-18 07:39:19 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][30/312]	eta 0:02:29 lr 0.000940	time 0.4578 (0.5316)	model_time 0.4577 (0.4623)	loss 3.0037 (2.9525)	grad_norm 3.9212 (2.1958/0.9877)	mem 16099MB
[2025-01-18 07:39:24 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][40/312]	eta 0:02:19 lr 0.000939	time 0.4752 (0.5138)	model_time 0.4751 (0.4614)	loss 2.3093 (2.9463)	grad_norm 1.7155 (2.2578/0.9125)	mem 16099MB
[2025-01-18 07:39:29 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][50/312]	eta 0:02:12 lr 0.000939	time 0.4739 (0.5046)	model_time 0.4734 (0.4623)	loss 2.0424 (2.9884)	grad_norm 1.2179 (2.1558/0.8829)	mem 16099MB
[2025-01-18 07:39:33 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][60/312]	eta 0:02:05 lr 0.000938	time 0.5382 (0.4992)	model_time 0.5378 (0.4638)	loss 2.7698 (2.9997)	grad_norm 1.7426 (2.1294/0.8466)	mem 16099MB
[2025-01-18 07:39:38 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][70/312]	eta 0:01:59 lr 0.000938	time 0.4463 (0.4929)	model_time 0.4461 (0.4624)	loss 3.0182 (2.9866)	grad_norm 1.2923 (2.0601/0.8173)	mem 16099MB
[2025-01-18 07:39:42 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][80/312]	eta 0:01:53 lr 0.000937	time 0.4434 (0.4880)	model_time 0.4430 (0.4612)	loss 3.6380 (2.9545)	grad_norm 1.1980 (2.0944/0.8090)	mem 16099MB
[2025-01-18 07:39:47 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][90/312]	eta 0:01:47 lr 0.000937	time 0.4625 (0.4849)	model_time 0.4623 (0.4611)	loss 2.6275 (2.9638)	grad_norm 3.4500 (2.2150/0.9632)	mem 16099MB
[2025-01-18 07:39:52 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][100/312]	eta 0:01:42 lr 0.000936	time 0.4513 (0.4849)	model_time 0.4509 (0.4634)	loss 2.8427 (2.9639)	grad_norm 3.4854 (2.2193/0.9540)	mem 16099MB
[2025-01-18 07:39:57 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][110/312]	eta 0:01:37 lr 0.000935	time 0.5268 (0.4833)	model_time 0.5267 (0.4637)	loss 3.0748 (2.9681)	grad_norm 3.2196 (2.2252/0.9375)	mem 16099MB
[2025-01-18 07:40:01 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][120/312]	eta 0:01:32 lr 0.000935	time 0.5662 (0.4824)	model_time 0.5657 (0.4644)	loss 2.5976 (2.9671)	grad_norm 1.9928 (2.2290/0.9315)	mem 16099MB
[2025-01-18 07:40:06 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][130/312]	eta 0:01:27 lr 0.000934	time 0.4439 (0.4814)	model_time 0.4435 (0.4647)	loss 3.1428 (2.9722)	grad_norm 1.9024 (2.2359/0.9177)	mem 16099MB
[2025-01-18 07:40:11 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][140/312]	eta 0:01:22 lr 0.000934	time 0.4451 (0.4799)	model_time 0.4446 (0.4644)	loss 3.4451 (2.9748)	grad_norm 2.9004 (2.2203/0.9037)	mem 16099MB
[2025-01-18 07:40:15 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][150/312]	eta 0:01:17 lr 0.000933	time 0.4517 (0.4787)	model_time 0.4515 (0.4642)	loss 2.0727 (2.9712)	grad_norm 2.5134 (2.2350/0.9061)	mem 16099MB
[2025-01-18 07:40:20 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][160/312]	eta 0:01:12 lr 0.000933	time 0.4591 (0.4779)	model_time 0.4589 (0.4643)	loss 2.6847 (2.9503)	grad_norm 2.4108 (2.2753/0.9138)	mem 16099MB
[2025-01-18 07:40:25 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][170/312]	eta 0:01:07 lr 0.000932	time 0.4632 (0.4780)	model_time 0.4631 (0.4651)	loss 3.2076 (2.9464)	grad_norm 2.1891 (2.3259/0.9608)	mem 16099MB
[2025-01-18 07:40:29 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][180/312]	eta 0:01:03 lr 0.000932	time 0.4699 (0.4784)	model_time 0.4695 (0.4662)	loss 2.7455 (2.9428)	grad_norm 2.4976 (2.3458/0.9584)	mem 16099MB
[2025-01-18 07:40:34 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][190/312]	eta 0:00:58 lr 0.000931	time 0.4492 (0.4784)	model_time 0.4490 (0.4668)	loss 3.2359 (2.9505)	grad_norm 1.1749 (2.3466/0.9685)	mem 16099MB
[2025-01-18 07:40:39 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][200/312]	eta 0:00:53 lr 0.000930	time 0.4583 (0.4778)	model_time 0.4582 (0.4668)	loss 2.8946 (2.9404)	grad_norm 2.8797 (2.3554/0.9627)	mem 16099MB
[2025-01-18 07:40:44 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][210/312]	eta 0:00:48 lr 0.000930	time 0.4514 (0.4773)	model_time 0.4512 (0.4668)	loss 3.7136 (2.9410)	grad_norm 5.5119 (2.3978/1.0050)	mem 16099MB
[2025-01-18 07:40:48 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][220/312]	eta 0:00:43 lr 0.000929	time 0.4708 (0.4767)	model_time 0.4706 (0.4666)	loss 3.5728 (2.9545)	grad_norm 3.5969 (2.4264/1.0303)	mem 16099MB
[2025-01-18 07:40:53 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][230/312]	eta 0:00:39 lr 0.000929	time 0.4522 (0.4766)	model_time 0.4520 (0.4669)	loss 2.4383 (2.9501)	grad_norm 3.0653 (2.4108/1.0198)	mem 16099MB
[2025-01-18 07:40:58 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][240/312]	eta 0:00:34 lr 0.000928	time 0.4509 (0.4758)	model_time 0.4505 (0.4665)	loss 2.1300 (2.9498)	grad_norm 1.6721 (2.3900/1.0057)	mem 16099MB
[2025-01-18 07:41:02 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][250/312]	eta 0:00:29 lr 0.000928	time 0.4564 (0.4748)	model_time 0.4562 (0.4659)	loss 2.3573 (2.9499)	grad_norm 2.4201 (2.3662/0.9985)	mem 16099MB
[2025-01-18 07:41:07 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][260/312]	eta 0:00:24 lr 0.000927	time 0.4412 (0.4745)	model_time 0.4407 (0.4659)	loss 2.6802 (2.9519)	grad_norm 1.5924 (2.3449/0.9884)	mem 16099MB
[2025-01-18 07:41:11 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][270/312]	eta 0:00:19 lr 0.000927	time 0.4642 (0.4743)	model_time 0.4637 (0.4660)	loss 3.2647 (2.9550)	grad_norm 1.4830 (2.3329/0.9820)	mem 16099MB
[2025-01-18 07:41:16 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][280/312]	eta 0:00:15 lr 0.000926	time 0.4571 (0.4742)	model_time 0.4569 (0.4662)	loss 2.9122 (2.9538)	grad_norm 4.1506 (2.3942/1.1218)	mem 16099MB
[2025-01-18 07:41:21 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][290/312]	eta 0:00:10 lr 0.000926	time 0.4442 (0.4739)	model_time 0.4437 (0.4662)	loss 3.2809 (2.9574)	grad_norm 0.9510 (2.4080/1.1273)	mem 16099MB
[2025-01-18 07:41:26 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][300/312]	eta 0:00:05 lr 0.000925	time 0.4385 (0.4738)	model_time 0.4384 (0.4663)	loss 3.3533 (2.9569)	grad_norm 2.2777 (2.3910/1.1188)	mem 16099MB
[2025-01-18 07:41:30 internimage_t_1k_224] (main.py 510): INFO Train: [205/300][310/312]	eta 0:00:00 lr 0.000924	time 0.4389 (0.4732)	model_time 0.4387 (0.4660)	loss 3.3600 (2.9507)	grad_norm 1.1097 (2.3658/1.1218)	mem 16099MB
[2025-01-18 07:41:31 internimage_t_1k_224] (main.py 519): INFO EPOCH 205 training takes 0:02:27
[2025-01-18 07:41:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_205.pth saving......
[2025-01-18 07:41:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_205.pth saved !!!
[2025-01-18 07:41:39 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.184 (7.184)	Loss 0.7625 (0.7625)	Acc@1 83.936 (83.936)	Acc@5 96.997 (96.997)	Mem 16099MB
[2025-01-18 07:41:42 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.980)	Loss 1.0363 (0.8697)	Acc@1 76.489 (81.627)	Acc@5 94.312 (95.816)	Mem 16099MB
[2025-01-18 07:41:43 internimage_t_1k_224] (main.py 575): INFO [Epoch:205] * Acc@1 81.442 Acc@5 95.843
[2025-01-18 07:41:43 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.4%
[2025-01-18 07:41:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 07:41:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 07:41:44 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.44%
[2025-01-18 07:41:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.186 (7.186)	Loss 0.7810 (0.7810)	Acc@1 84.985 (84.985)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 07:41:54 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.114 (0.980)	Loss 1.0399 (0.8958)	Acc@1 78.198 (82.460)	Acc@5 94.873 (96.200)	Mem 16099MB
[2025-01-18 07:41:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:205] * Acc@1 82.338 Acc@5 96.229
[2025-01-18 07:41:55 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.3%
[2025-01-18 07:41:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:41:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:41:56 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.34%
[2025-01-18 07:41:58 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][0/312]	eta 0:10:37 lr 0.000924	time 2.0445 (2.0445)	model_time 0.5046 (0.5046)	loss 2.8239 (2.8239)	grad_norm 1.3418 (1.3418/0.0000)	mem 16099MB
[2025-01-18 07:42:03 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][10/312]	eta 0:03:13 lr 0.000924	time 0.4442 (0.6417)	model_time 0.4441 (0.4620)	loss 2.2817 (2.8402)	grad_norm 1.4858 (1.5864/0.3698)	mem 16099MB
[2025-01-18 07:42:08 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][20/312]	eta 0:02:41 lr 0.000923	time 0.4529 (0.5524)	model_time 0.4528 (0.4581)	loss 3.0876 (2.9570)	grad_norm 2.4832 (1.6738/0.4055)	mem 16099MB
[2025-01-18 07:42:13 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][30/312]	eta 0:02:27 lr 0.000923	time 0.4534 (0.5242)	model_time 0.4532 (0.4602)	loss 2.5473 (3.0157)	grad_norm 4.8571 (1.9525/0.8094)	mem 16099MB
[2025-01-18 07:42:17 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][40/312]	eta 0:02:19 lr 0.000922	time 0.5752 (0.5137)	model_time 0.5750 (0.4653)	loss 3.5368 (3.0218)	grad_norm 3.0920 (2.0797/1.0272)	mem 16099MB
[2025-01-18 07:42:22 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][50/312]	eta 0:02:11 lr 0.000922	time 0.4603 (0.5037)	model_time 0.4598 (0.4647)	loss 2.5275 (2.9779)	grad_norm 1.6232 (2.3089/1.2527)	mem 16099MB
[2025-01-18 07:42:27 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][60/312]	eta 0:02:05 lr 0.000921	time 0.4434 (0.4983)	model_time 0.4430 (0.4656)	loss 3.3278 (2.9917)	grad_norm 4.0464 (2.3110/1.1811)	mem 16099MB
[2025-01-18 07:42:31 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][70/312]	eta 0:01:59 lr 0.000920	time 0.4584 (0.4923)	model_time 0.4583 (0.4642)	loss 2.7047 (2.9836)	grad_norm 3.5707 (2.3557/1.2362)	mem 16099MB
[2025-01-18 07:42:36 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][80/312]	eta 0:01:53 lr 0.000920	time 0.4511 (0.4891)	model_time 0.4509 (0.4644)	loss 2.6704 (2.9717)	grad_norm 2.8203 (2.4168/1.2748)	mem 16099MB
[2025-01-18 07:42:41 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][90/312]	eta 0:01:47 lr 0.000919	time 0.4509 (0.4861)	model_time 0.4505 (0.4640)	loss 2.2272 (2.9583)	grad_norm 1.6438 (2.4326/1.2686)	mem 16099MB
[2025-01-18 07:42:45 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][100/312]	eta 0:01:42 lr 0.000919	time 0.4544 (0.4830)	model_time 0.4542 (0.4631)	loss 3.0709 (2.9662)	grad_norm 1.5561 (2.3882/1.2296)	mem 16099MB
[2025-01-18 07:42:50 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][110/312]	eta 0:01:37 lr 0.000918	time 0.5362 (0.4827)	model_time 0.5359 (0.4646)	loss 3.8887 (2.9722)	grad_norm 2.6965 (2.3536/1.2045)	mem 16099MB
[2025-01-18 07:42:55 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][120/312]	eta 0:01:32 lr 0.000918	time 0.4415 (0.4821)	model_time 0.4414 (0.4655)	loss 2.7324 (2.9602)	grad_norm 4.4092 (2.4011/1.2240)	mem 16099MB
[2025-01-18 07:43:00 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][130/312]	eta 0:01:27 lr 0.000917	time 0.4730 (0.4830)	model_time 0.4725 (0.4676)	loss 3.4028 (2.9587)	grad_norm 6.4106 (2.4508/1.3060)	mem 16099MB
[2025-01-18 07:43:05 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][140/312]	eta 0:01:23 lr 0.000917	time 0.4427 (0.4853)	model_time 0.4423 (0.4709)	loss 3.2285 (2.9695)	grad_norm 2.1981 (2.4474/1.3069)	mem 16099MB
[2025-01-18 07:43:09 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][150/312]	eta 0:01:18 lr 0.000916	time 0.4554 (0.4835)	model_time 0.4550 (0.4701)	loss 3.2473 (2.9794)	grad_norm 1.7630 (2.4184/1.2718)	mem 16099MB
[2025-01-18 07:43:14 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][160/312]	eta 0:01:13 lr 0.000915	time 0.4763 (0.4848)	model_time 0.4758 (0.4721)	loss 3.4625 (2.9638)	grad_norm 1.4134 (2.4308/1.2443)	mem 16099MB
[2025-01-18 07:43:19 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][170/312]	eta 0:01:08 lr 0.000915	time 0.4584 (0.4835)	model_time 0.4582 (0.4716)	loss 3.1297 (2.9600)	grad_norm 4.5669 (2.4410/1.2564)	mem 16099MB
[2025-01-18 07:43:24 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][180/312]	eta 0:01:03 lr 0.000914	time 0.4401 (0.4818)	model_time 0.4399 (0.4705)	loss 3.1848 (2.9686)	grad_norm 3.3045 (2.4303/1.2374)	mem 16099MB
[2025-01-18 07:43:28 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][190/312]	eta 0:00:58 lr 0.000914	time 0.4753 (0.4809)	model_time 0.4748 (0.4702)	loss 2.7472 (2.9686)	grad_norm 1.5488 (2.4230/1.2270)	mem 16099MB
[2025-01-18 07:43:33 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][200/312]	eta 0:00:53 lr 0.000913	time 0.4439 (0.4801)	model_time 0.4435 (0.4698)	loss 3.0111 (2.9781)	grad_norm 1.1274 (2.3865/1.2154)	mem 16099MB
[2025-01-18 07:43:37 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][210/312]	eta 0:00:48 lr 0.000913	time 0.4398 (0.4791)	model_time 0.4396 (0.4693)	loss 3.1903 (2.9801)	grad_norm 1.2940 (2.3589/1.1997)	mem 16099MB
[2025-01-18 07:43:42 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][220/312]	eta 0:00:44 lr 0.000912	time 0.4669 (0.4794)	model_time 0.4664 (0.4700)	loss 3.1335 (2.9810)	grad_norm 1.3745 (2.3564/1.1850)	mem 16099MB
[2025-01-18 07:43:47 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][230/312]	eta 0:00:39 lr 0.000912	time 0.7229 (0.4799)	model_time 0.7227 (0.4710)	loss 3.1181 (2.9793)	grad_norm 6.2879 (2.4311/1.2620)	mem 16099MB
[2025-01-18 07:43:52 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][240/312]	eta 0:00:34 lr 0.000911	time 0.4544 (0.4795)	model_time 0.4542 (0.4709)	loss 2.4636 (2.9708)	grad_norm 2.9981 (2.4657/1.2908)	mem 16099MB
[2025-01-18 07:43:56 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][250/312]	eta 0:00:29 lr 0.000910	time 0.5017 (0.4786)	model_time 0.5015 (0.4704)	loss 3.0616 (2.9735)	grad_norm 1.8996 (2.4543/1.2784)	mem 16099MB
[2025-01-18 07:44:01 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][260/312]	eta 0:00:24 lr 0.000910	time 0.4750 (0.4777)	model_time 0.4745 (0.4698)	loss 1.9289 (2.9598)	grad_norm 3.4853 (2.4629/1.2716)	mem 16099MB
[2025-01-18 07:44:06 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][270/312]	eta 0:00:20 lr 0.000909	time 0.4506 (0.4772)	model_time 0.4501 (0.4696)	loss 3.2770 (2.9621)	grad_norm 1.2859 (2.4394/1.2569)	mem 16099MB
[2025-01-18 07:44:10 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][280/312]	eta 0:00:15 lr 0.000909	time 0.4581 (0.4771)	model_time 0.4579 (0.4697)	loss 2.9398 (2.9594)	grad_norm 2.0539 (2.4157/1.2413)	mem 16099MB
[2025-01-18 07:44:15 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][290/312]	eta 0:00:10 lr 0.000908	time 0.7526 (0.4776)	model_time 0.7524 (0.4704)	loss 3.2561 (2.9599)	grad_norm 2.9775 (2.4332/1.2287)	mem 16099MB
[2025-01-18 07:44:20 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][300/312]	eta 0:00:05 lr 0.000908	time 0.4391 (0.4767)	model_time 0.4390 (0.4697)	loss 3.6039 (2.9575)	grad_norm 2.0070 (2.4209/1.2238)	mem 16099MB
[2025-01-18 07:44:25 internimage_t_1k_224] (main.py 510): INFO Train: [206/300][310/312]	eta 0:00:00 lr 0.000907	time 0.4840 (0.4765)	model_time 0.4839 (0.4697)	loss 2.7333 (2.9656)	grad_norm 1.1405 (2.4129/1.2307)	mem 16099MB
[2025-01-18 07:44:25 internimage_t_1k_224] (main.py 519): INFO EPOCH 206 training takes 0:02:28
[2025-01-18 07:44:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_206.pth saving......
[2025-01-18 07:44:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_206.pth saved !!!
[2025-01-18 07:44:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.358 (7.358)	Loss 0.7952 (0.7952)	Acc@1 83.862 (83.862)	Acc@5 96.851 (96.851)	Mem 16099MB
[2025-01-18 07:44:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.011)	Loss 1.0530 (0.8999)	Acc@1 76.733 (81.523)	Acc@5 94.531 (95.690)	Mem 16099MB
[2025-01-18 07:44:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:206] * Acc@1 81.344 Acc@5 95.741
[2025-01-18 07:44:37 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.3%
[2025-01-18 07:44:37 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.44%
[2025-01-18 07:44:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.362 (8.362)	Loss 0.7799 (0.7799)	Acc@1 85.010 (85.010)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 07:44:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.131)	Loss 1.0380 (0.8944)	Acc@1 78.247 (82.473)	Acc@5 94.922 (96.216)	Mem 16099MB
[2025-01-18 07:44:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:206] * Acc@1 82.360 Acc@5 96.237
[2025-01-18 07:44:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.4%
[2025-01-18 07:44:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:44:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:44:52 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.36%
[2025-01-18 07:44:55 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][0/312]	eta 0:15:40 lr 0.000907	time 3.0149 (3.0149)	model_time 0.4799 (0.4799)	loss 2.6456 (2.6456)	grad_norm 1.0590 (1.0590/0.0000)	mem 16099MB
[2025-01-18 07:44:59 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][10/312]	eta 0:03:30 lr 0.000907	time 0.5257 (0.6955)	model_time 0.5255 (0.4639)	loss 3.0644 (2.7956)	grad_norm 1.8006 (1.7105/0.4470)	mem 16099MB
[2025-01-18 07:45:04 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][20/312]	eta 0:02:51 lr 0.000906	time 0.4512 (0.5866)	model_time 0.4511 (0.4652)	loss 3.2993 (2.9986)	grad_norm 2.3715 (1.7751/0.5605)	mem 16099MB
[2025-01-18 07:45:09 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][30/312]	eta 0:02:37 lr 0.000905	time 0.5457 (0.5578)	model_time 0.5453 (0.4755)	loss 3.4569 (3.0882)	grad_norm 1.4142 (1.8179/0.9105)	mem 16099MB
[2025-01-18 07:45:14 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][40/312]	eta 0:02:25 lr 0.000905	time 0.4484 (0.5361)	model_time 0.4482 (0.4738)	loss 2.9487 (3.0190)	grad_norm 4.5167 (2.1112/1.2654)	mem 16099MB
[2025-01-18 07:45:18 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][50/312]	eta 0:02:17 lr 0.000904	time 0.4562 (0.5230)	model_time 0.4558 (0.4729)	loss 3.5377 (2.9817)	grad_norm 1.9523 (2.2875/1.3441)	mem 16099MB
[2025-01-18 07:45:23 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][60/312]	eta 0:02:09 lr 0.000904	time 0.4509 (0.5132)	model_time 0.4507 (0.4712)	loss 2.8988 (2.9661)	grad_norm 1.8733 (2.2874/1.2450)	mem 16099MB
[2025-01-18 07:45:28 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][70/312]	eta 0:02:02 lr 0.000903	time 0.4794 (0.5058)	model_time 0.4792 (0.4697)	loss 2.4668 (2.9588)	grad_norm 2.7012 (2.3381/1.2056)	mem 16099MB
[2025-01-18 07:45:32 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][80/312]	eta 0:01:56 lr 0.000903	time 0.4500 (0.5000)	model_time 0.4495 (0.4683)	loss 1.9562 (2.9136)	grad_norm 2.0692 (2.3091/1.1546)	mem 16099MB
[2025-01-18 07:45:37 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][90/312]	eta 0:01:50 lr 0.000902	time 0.4413 (0.4970)	model_time 0.4411 (0.4688)	loss 3.2895 (2.9298)	grad_norm 1.0114 (2.2205/1.1242)	mem 16099MB
[2025-01-18 07:45:42 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][100/312]	eta 0:01:44 lr 0.000902	time 0.4506 (0.4939)	model_time 0.4504 (0.4684)	loss 3.3998 (2.9369)	grad_norm 3.0625 (2.2063/1.0873)	mem 16099MB
[2025-01-18 07:45:46 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][110/312]	eta 0:01:39 lr 0.000901	time 0.4456 (0.4916)	model_time 0.4452 (0.4683)	loss 2.0501 (2.9234)	grad_norm 1.3748 (2.2363/1.0792)	mem 16099MB
[2025-01-18 07:45:51 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][120/312]	eta 0:01:33 lr 0.000900	time 0.4552 (0.4885)	model_time 0.4548 (0.4671)	loss 3.0303 (2.9312)	grad_norm 2.3578 (2.2100/1.0459)	mem 16099MB
[2025-01-18 07:45:56 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][130/312]	eta 0:01:28 lr 0.000900	time 0.4537 (0.4877)	model_time 0.4533 (0.4680)	loss 3.0581 (2.9321)	grad_norm 3.8932 (2.2250/1.0370)	mem 16099MB
[2025-01-18 07:46:00 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][140/312]	eta 0:01:23 lr 0.000899	time 0.4463 (0.4852)	model_time 0.4458 (0.4668)	loss 3.1908 (2.9266)	grad_norm 3.9504 (2.2391/1.0274)	mem 16099MB
[2025-01-18 07:46:05 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][150/312]	eta 0:01:18 lr 0.000899	time 0.4462 (0.4850)	model_time 0.4458 (0.4678)	loss 2.7367 (2.9210)	grad_norm 3.1277 (2.2110/1.0140)	mem 16099MB
[2025-01-18 07:46:10 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][160/312]	eta 0:01:13 lr 0.000898	time 0.4768 (0.4840)	model_time 0.4764 (0.4679)	loss 3.4523 (2.9420)	grad_norm 1.9198 (2.2016/0.9985)	mem 16099MB
[2025-01-18 07:46:14 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][170/312]	eta 0:01:08 lr 0.000898	time 0.4429 (0.4823)	model_time 0.4425 (0.4671)	loss 1.9996 (2.9452)	grad_norm 2.0616 (2.1706/0.9841)	mem 16099MB
[2025-01-18 07:46:19 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][180/312]	eta 0:01:03 lr 0.000897	time 0.4431 (0.4814)	model_time 0.4429 (0.4670)	loss 2.1870 (2.9452)	grad_norm 3.6078 (2.1750/0.9769)	mem 16099MB
[2025-01-18 07:46:24 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][190/312]	eta 0:00:58 lr 0.000897	time 0.5877 (0.4811)	model_time 0.5876 (0.4674)	loss 2.6522 (2.9435)	grad_norm 1.5542 (2.1869/0.9759)	mem 16099MB
[2025-01-18 07:46:28 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][200/312]	eta 0:00:53 lr 0.000896	time 0.4826 (0.4803)	model_time 0.4822 (0.4673)	loss 3.0120 (2.9441)	grad_norm 2.5103 (2.1862/0.9590)	mem 16099MB
[2025-01-18 07:46:33 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][210/312]	eta 0:00:48 lr 0.000896	time 0.4422 (0.4794)	model_time 0.4417 (0.4670)	loss 3.4121 (2.9455)	grad_norm 1.3951 (2.1728/0.9499)	mem 16099MB
[2025-01-18 07:46:37 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][220/312]	eta 0:00:44 lr 0.000895	time 0.4477 (0.4787)	model_time 0.4476 (0.4668)	loss 2.6547 (2.9344)	grad_norm 1.3339 (2.1367/0.9487)	mem 16099MB
[2025-01-18 07:46:42 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][230/312]	eta 0:00:39 lr 0.000894	time 0.4514 (0.4780)	model_time 0.4510 (0.4666)	loss 3.1580 (2.9319)	grad_norm 1.0181 (2.1395/0.9529)	mem 16099MB
[2025-01-18 07:46:47 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][240/312]	eta 0:00:34 lr 0.000894	time 0.4498 (0.4775)	model_time 0.4493 (0.4666)	loss 3.4582 (2.9290)	grad_norm 3.4891 (2.1421/0.9623)	mem 16099MB
[2025-01-18 07:46:51 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][250/312]	eta 0:00:29 lr 0.000893	time 0.4544 (0.4766)	model_time 0.4540 (0.4661)	loss 3.2712 (2.9263)	grad_norm 4.2804 (2.1659/0.9710)	mem 16099MB
[2025-01-18 07:46:56 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][260/312]	eta 0:00:24 lr 0.000893	time 0.4405 (0.4762)	model_time 0.4400 (0.4661)	loss 3.6482 (2.9307)	grad_norm 2.2973 (2.1614/0.9605)	mem 16099MB
[2025-01-18 07:47:01 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][270/312]	eta 0:00:19 lr 0.000892	time 0.4541 (0.4757)	model_time 0.4536 (0.4659)	loss 2.7159 (2.9327)	grad_norm 3.3046 (2.1595/0.9531)	mem 16099MB
[2025-01-18 07:47:05 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][280/312]	eta 0:00:15 lr 0.000892	time 0.4494 (0.4759)	model_time 0.4490 (0.4664)	loss 3.2268 (2.9413)	grad_norm 0.9695 (2.1666/0.9523)	mem 16099MB
[2025-01-18 07:47:10 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][290/312]	eta 0:00:10 lr 0.000891	time 0.4483 (0.4754)	model_time 0.4482 (0.4663)	loss 3.4913 (2.9466)	grad_norm 3.7692 (2.1799/0.9471)	mem 16099MB
[2025-01-18 07:47:15 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][300/312]	eta 0:00:05 lr 0.000891	time 0.4401 (0.4746)	model_time 0.4400 (0.4658)	loss 3.0179 (2.9464)	grad_norm 1.3404 (2.1874/0.9429)	mem 16099MB
[2025-01-18 07:47:19 internimage_t_1k_224] (main.py 510): INFO Train: [207/300][310/312]	eta 0:00:00 lr 0.000890	time 0.4386 (0.4736)	model_time 0.4385 (0.4651)	loss 3.1580 (2.9526)	grad_norm 1.2731 (2.1975/0.9435)	mem 16099MB
[2025-01-18 07:47:19 internimage_t_1k_224] (main.py 519): INFO EPOCH 207 training takes 0:02:27
[2025-01-18 07:47:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_207.pth saving......
[2025-01-18 07:47:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_207.pth saved !!!
[2025-01-18 07:47:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.286 (7.286)	Loss 0.7428 (0.7428)	Acc@1 83.887 (83.887)	Acc@5 97.241 (97.241)	Mem 16099MB
[2025-01-18 07:47:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.990)	Loss 1.0634 (0.8676)	Acc@1 76.831 (81.507)	Acc@5 94.092 (95.821)	Mem 16099MB
[2025-01-18 07:47:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:207] * Acc@1 81.360 Acc@5 95.843
[2025-01-18 07:47:32 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.4%
[2025-01-18 07:47:32 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.44%
[2025-01-18 07:47:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.251 (8.251)	Loss 0.7787 (0.7787)	Acc@1 84.985 (84.985)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 07:47:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.113)	Loss 1.0364 (0.8931)	Acc@1 78.198 (82.462)	Acc@5 94.946 (96.220)	Mem 16099MB
[2025-01-18 07:47:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:207] * Acc@1 82.344 Acc@5 96.243
[2025-01-18 07:47:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.3%
[2025-01-18 07:47:44 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.36%
[2025-01-18 07:47:47 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][0/312]	eta 0:17:03 lr 0.000890	time 3.2810 (3.2810)	model_time 1.1031 (1.1031)	loss 3.0328 (3.0328)	grad_norm 2.3590 (2.3590/0.0000)	mem 16099MB
[2025-01-18 07:47:52 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][10/312]	eta 0:03:41 lr 0.000889	time 0.5535 (0.7347)	model_time 0.5534 (0.5364)	loss 2.7739 (3.0644)	grad_norm 1.0892 (1.4458/0.3553)	mem 16099MB
[2025-01-18 07:47:57 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][20/312]	eta 0:02:55 lr 0.000889	time 0.4613 (0.6015)	model_time 0.4609 (0.4973)	loss 3.2739 (3.0094)	grad_norm 1.6286 (1.6576/0.5207)	mem 16099MB
[2025-01-18 07:48:01 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][30/312]	eta 0:02:36 lr 0.000888	time 0.4376 (0.5541)	model_time 0.4372 (0.4833)	loss 2.4107 (3.0214)	grad_norm 1.5790 (1.7740/0.5649)	mem 16099MB
[2025-01-18 07:48:06 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][40/312]	eta 0:02:25 lr 0.000888	time 0.4861 (0.5343)	model_time 0.4857 (0.4807)	loss 2.8406 (3.0384)	grad_norm 3.0652 (2.0399/1.0102)	mem 16099MB
[2025-01-18 07:48:11 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][50/312]	eta 0:02:16 lr 0.000887	time 0.4542 (0.5223)	model_time 0.4541 (0.4791)	loss 3.0920 (2.9891)	grad_norm 5.2521 (2.4519/1.5215)	mem 16099MB
[2025-01-18 07:48:15 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][60/312]	eta 0:02:08 lr 0.000887	time 0.4566 (0.5109)	model_time 0.4562 (0.4748)	loss 2.6664 (3.0006)	grad_norm 2.0263 (2.4771/1.4835)	mem 16099MB
[2025-01-18 07:48:20 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][70/312]	eta 0:02:02 lr 0.000886	time 0.5512 (0.5058)	model_time 0.5511 (0.4747)	loss 3.1213 (2.9803)	grad_norm 2.0808 (2.4888/1.4078)	mem 16099MB
[2025-01-18 07:48:25 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][80/312]	eta 0:01:56 lr 0.000886	time 0.4572 (0.5016)	model_time 0.4568 (0.4742)	loss 3.2568 (2.9933)	grad_norm 2.6059 (2.4433/1.3605)	mem 16099MB
[2025-01-18 07:48:29 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][90/312]	eta 0:01:50 lr 0.000885	time 0.4482 (0.4966)	model_time 0.4478 (0.4722)	loss 3.6020 (2.9953)	grad_norm 5.5973 (2.5682/1.4740)	mem 16099MB
[2025-01-18 07:48:34 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][100/312]	eta 0:01:44 lr 0.000885	time 0.4618 (0.4948)	model_time 0.4614 (0.4727)	loss 3.5367 (2.9984)	grad_norm 1.7746 (2.5768/1.4489)	mem 16099MB
[2025-01-18 07:48:39 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][110/312]	eta 0:01:39 lr 0.000884	time 0.4510 (0.4919)	model_time 0.4508 (0.4718)	loss 3.4147 (2.9858)	grad_norm 2.2499 (2.6021/1.4170)	mem 16099MB
[2025-01-18 07:48:43 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][120/312]	eta 0:01:33 lr 0.000883	time 0.4408 (0.4894)	model_time 0.4407 (0.4709)	loss 3.0022 (2.9637)	grad_norm 1.6408 (2.6666/1.4907)	mem 16099MB
[2025-01-18 07:48:48 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][130/312]	eta 0:01:28 lr 0.000883	time 0.4586 (0.4879)	model_time 0.4585 (0.4708)	loss 2.9137 (2.9757)	grad_norm 2.3894 (2.6628/1.4857)	mem 16099MB
[2025-01-18 07:48:53 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][140/312]	eta 0:01:23 lr 0.000882	time 0.4353 (0.4859)	model_time 0.4351 (0.4700)	loss 1.8103 (2.9596)	grad_norm 1.4933 (2.6498/1.4754)	mem 16099MB
[2025-01-18 07:48:57 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][150/312]	eta 0:01:18 lr 0.000882	time 0.4466 (0.4848)	model_time 0.4461 (0.4699)	loss 3.6433 (2.9638)	grad_norm 0.9512 (2.6181/1.4408)	mem 16099MB
[2025-01-18 07:49:02 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][160/312]	eta 0:01:13 lr 0.000881	time 0.4418 (0.4850)	model_time 0.4417 (0.4711)	loss 2.9695 (2.9662)	grad_norm 1.5096 (2.5559/1.4213)	mem 16099MB
[2025-01-18 07:49:07 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][170/312]	eta 0:01:08 lr 0.000881	time 0.4557 (0.4840)	model_time 0.4556 (0.4708)	loss 3.5453 (2.9752)	grad_norm 1.2963 (2.5133/1.3956)	mem 16099MB
[2025-01-18 07:49:11 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][180/312]	eta 0:01:03 lr 0.000880	time 0.4498 (0.4827)	model_time 0.4494 (0.4702)	loss 3.0624 (2.9607)	grad_norm 4.3103 (2.4877/1.3782)	mem 16099MB
[2025-01-18 07:49:16 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][190/312]	eta 0:00:58 lr 0.000880	time 0.4562 (0.4823)	model_time 0.4558 (0.4704)	loss 3.5613 (2.9668)	grad_norm 1.9500 (2.5088/1.3720)	mem 16099MB
[2025-01-18 07:49:21 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][200/312]	eta 0:00:53 lr 0.000879	time 0.4447 (0.4813)	model_time 0.4445 (0.4700)	loss 2.7539 (2.9669)	grad_norm 1.9738 (2.4979/1.3850)	mem 16099MB
[2025-01-18 07:49:25 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][210/312]	eta 0:00:48 lr 0.000879	time 0.4637 (0.4804)	model_time 0.4636 (0.4697)	loss 3.5782 (2.9745)	grad_norm 2.3844 (2.4758/1.3619)	mem 16099MB
[2025-01-18 07:49:30 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][220/312]	eta 0:00:44 lr 0.000878	time 0.5543 (0.4800)	model_time 0.5538 (0.4697)	loss 3.2855 (2.9809)	grad_norm 3.4606 (2.4429/1.3468)	mem 16099MB
[2025-01-18 07:49:35 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][230/312]	eta 0:00:39 lr 0.000877	time 0.5008 (0.4792)	model_time 0.5003 (0.4694)	loss 2.4017 (2.9757)	grad_norm 1.5348 (2.4262/1.3238)	mem 16099MB
[2025-01-18 07:49:39 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][240/312]	eta 0:00:34 lr 0.000877	time 0.5751 (0.4788)	model_time 0.5749 (0.4694)	loss 2.9889 (2.9697)	grad_norm 3.1943 (2.3989/1.3086)	mem 16099MB
[2025-01-18 07:49:44 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][250/312]	eta 0:00:29 lr 0.000876	time 0.4510 (0.4785)	model_time 0.4508 (0.4694)	loss 3.3037 (2.9679)	grad_norm 1.3061 (2.3749/1.2964)	mem 16099MB
[2025-01-18 07:49:49 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][260/312]	eta 0:00:24 lr 0.000876	time 0.4529 (0.4775)	model_time 0.4528 (0.4688)	loss 2.9894 (2.9728)	grad_norm 1.3129 (2.3765/1.2801)	mem 16099MB
[2025-01-18 07:49:53 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][270/312]	eta 0:00:20 lr 0.000875	time 0.4453 (0.4769)	model_time 0.4449 (0.4684)	loss 3.2242 (2.9730)	grad_norm 1.7997 (2.3577/1.2660)	mem 16099MB
[2025-01-18 07:49:58 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][280/312]	eta 0:00:15 lr 0.000875	time 0.4448 (0.4761)	model_time 0.4447 (0.4679)	loss 3.5972 (2.9809)	grad_norm 3.5986 (2.3552/1.2600)	mem 16099MB
[2025-01-18 07:50:03 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][290/312]	eta 0:00:10 lr 0.000874	time 0.4531 (0.4759)	model_time 0.4526 (0.4680)	loss 3.4385 (2.9916)	grad_norm 1.6816 (2.3604/1.2590)	mem 16099MB
[2025-01-18 07:50:07 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][300/312]	eta 0:00:05 lr 0.000874	time 0.4445 (0.4754)	model_time 0.4444 (0.4677)	loss 3.1638 (2.9964)	grad_norm 1.8160 (2.3596/1.2478)	mem 16099MB
[2025-01-18 07:50:12 internimage_t_1k_224] (main.py 510): INFO Train: [208/300][310/312]	eta 0:00:00 lr 0.000873	time 0.4385 (0.4747)	model_time 0.4384 (0.4673)	loss 3.1807 (3.0040)	grad_norm 1.5521 (2.3764/1.2429)	mem 16099MB
[2025-01-18 07:50:12 internimage_t_1k_224] (main.py 519): INFO EPOCH 208 training takes 0:02:28
[2025-01-18 07:50:12 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_208.pth saving......
[2025-01-18 07:50:13 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_208.pth saved !!!
[2025-01-18 07:50:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.389 (7.389)	Loss 0.7397 (0.7397)	Acc@1 84.277 (84.277)	Acc@5 97.070 (97.070)	Mem 16099MB
[2025-01-18 07:50:24 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.999)	Loss 1.0157 (0.8649)	Acc@1 77.466 (81.705)	Acc@5 94.336 (95.774)	Mem 16099MB
[2025-01-18 07:50:24 internimage_t_1k_224] (main.py 575): INFO [Epoch:208] * Acc@1 81.534 Acc@5 95.797
[2025-01-18 07:50:24 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.5%
[2025-01-18 07:50:24 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 07:50:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 07:50:26 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.53%
[2025-01-18 07:50:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.294 (7.294)	Loss 0.7777 (0.7777)	Acc@1 85.034 (85.034)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 07:50:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.996)	Loss 1.0352 (0.8920)	Acc@1 78.149 (82.466)	Acc@5 94.995 (96.218)	Mem 16099MB
[2025-01-18 07:50:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:208] * Acc@1 82.348 Acc@5 96.241
[2025-01-18 07:50:37 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.3%
[2025-01-18 07:50:37 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.36%
[2025-01-18 07:50:40 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][0/312]	eta 0:16:44 lr 0.000873	time 3.2207 (3.2207)	model_time 0.8622 (0.8622)	loss 3.8317 (3.8317)	grad_norm 2.5994 (2.5994/0.0000)	mem 16099MB
[2025-01-18 07:50:45 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][10/312]	eta 0:03:43 lr 0.000872	time 0.4644 (0.7416)	model_time 0.4640 (0.5268)	loss 2.9539 (2.8726)	grad_norm 1.7271 (2.5087/1.1942)	mem 16099MB
[2025-01-18 07:50:49 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][20/312]	eta 0:02:57 lr 0.000872	time 0.4677 (0.6076)	model_time 0.4675 (0.4950)	loss 1.9410 (3.0060)	grad_norm 3.1980 (2.3433/1.0328)	mem 16099MB
[2025-01-18 07:50:54 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][30/312]	eta 0:02:39 lr 0.000871	time 0.4580 (0.5644)	model_time 0.4575 (0.4880)	loss 3.2998 (2.9430)	grad_norm 1.3661 (2.2566/0.9936)	mem 16099MB
[2025-01-18 07:50:59 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][40/312]	eta 0:02:26 lr 0.000871	time 0.4482 (0.5394)	model_time 0.4478 (0.4815)	loss 2.2303 (2.9401)	grad_norm 1.0126 (2.3009/1.0119)	mem 16099MB
[2025-01-18 07:51:03 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][50/312]	eta 0:02:17 lr 0.000870	time 0.4403 (0.5243)	model_time 0.4402 (0.4778)	loss 2.0969 (2.9709)	grad_norm 1.2114 (2.2659/0.9736)	mem 16099MB
[2025-01-18 07:51:08 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][60/312]	eta 0:02:09 lr 0.000870	time 0.5426 (0.5147)	model_time 0.5424 (0.4757)	loss 3.8030 (2.9944)	grad_norm 2.2045 (2.2749/0.9432)	mem 16099MB
[2025-01-18 07:51:13 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][70/312]	eta 0:02:03 lr 0.000869	time 0.4520 (0.5090)	model_time 0.4519 (0.4755)	loss 3.0456 (3.0054)	grad_norm 3.5577 (2.3692/1.0111)	mem 16099MB
[2025-01-18 07:51:17 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][80/312]	eta 0:01:56 lr 0.000869	time 0.4482 (0.5022)	model_time 0.4481 (0.4728)	loss 1.7248 (2.9808)	grad_norm 4.7068 (2.4840/1.1476)	mem 16099MB
[2025-01-18 07:51:22 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][90/312]	eta 0:01:50 lr 0.000868	time 0.4723 (0.4971)	model_time 0.4719 (0.4708)	loss 2.4421 (2.9815)	grad_norm 1.5706 (2.4679/1.1197)	mem 16099MB
[2025-01-18 07:51:27 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][100/312]	eta 0:01:44 lr 0.000868	time 0.4480 (0.4937)	model_time 0.4475 (0.4700)	loss 3.4252 (2.9571)	grad_norm 1.7158 (2.4027/1.0956)	mem 16099MB
[2025-01-18 07:51:31 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][110/312]	eta 0:01:39 lr 0.000867	time 0.4498 (0.4908)	model_time 0.4493 (0.4692)	loss 2.8571 (2.9612)	grad_norm 1.5281 (2.3960/1.0804)	mem 16099MB
[2025-01-18 07:51:36 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][120/312]	eta 0:01:33 lr 0.000867	time 0.4488 (0.4895)	model_time 0.4484 (0.4696)	loss 1.9378 (2.9486)	grad_norm 1.6231 (2.3657/1.0615)	mem 16099MB
[2025-01-18 07:51:41 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][130/312]	eta 0:01:28 lr 0.000866	time 0.4657 (0.4875)	model_time 0.4654 (0.4691)	loss 2.1340 (2.9312)	grad_norm 2.1887 (2.3495/1.0278)	mem 16099MB
[2025-01-18 07:51:45 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][140/312]	eta 0:01:23 lr 0.000865	time 0.4488 (0.4873)	model_time 0.4486 (0.4702)	loss 3.0449 (2.9393)	grad_norm 1.1438 (2.3099/1.0086)	mem 16099MB
[2025-01-18 07:51:50 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][150/312]	eta 0:01:18 lr 0.000865	time 0.4481 (0.4861)	model_time 0.4476 (0.4702)	loss 2.9828 (2.9387)	grad_norm 4.0952 (2.3138/1.0163)	mem 16099MB
[2025-01-18 07:51:55 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][160/312]	eta 0:01:13 lr 0.000864	time 0.4451 (0.4852)	model_time 0.4449 (0.4702)	loss 3.5400 (2.9201)	grad_norm 3.1923 (2.3759/1.0920)	mem 16099MB
[2025-01-18 07:51:59 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][170/312]	eta 0:01:08 lr 0.000864	time 0.4542 (0.4834)	model_time 0.4537 (0.4692)	loss 3.3339 (2.9333)	grad_norm 1.8907 (2.3760/1.0804)	mem 16099MB
[2025-01-18 07:52:04 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][180/312]	eta 0:01:03 lr 0.000863	time 0.4623 (0.4827)	model_time 0.4618 (0.4693)	loss 2.3771 (2.9324)	grad_norm 1.4490 (2.3435/1.0669)	mem 16099MB
[2025-01-18 07:52:09 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][190/312]	eta 0:00:58 lr 0.000863	time 0.4527 (0.4813)	model_time 0.4522 (0.4685)	loss 2.9788 (2.9385)	grad_norm 3.5046 (2.3337/1.0609)	mem 16099MB
[2025-01-18 07:52:13 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][200/312]	eta 0:00:53 lr 0.000862	time 0.4455 (0.4808)	model_time 0.4450 (0.4687)	loss 2.1827 (2.9432)	grad_norm 3.5430 (2.3241/1.0513)	mem 16099MB
[2025-01-18 07:52:18 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][210/312]	eta 0:00:48 lr 0.000862	time 0.4446 (0.4800)	model_time 0.4441 (0.4685)	loss 3.1866 (2.9570)	grad_norm 2.0477 (2.3281/1.0386)	mem 16099MB
[2025-01-18 07:52:23 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][220/312]	eta 0:00:44 lr 0.000861	time 0.4521 (0.4788)	model_time 0.4516 (0.4678)	loss 3.3852 (2.9638)	grad_norm 1.6474 (2.3503/1.0392)	mem 16099MB
[2025-01-18 07:52:27 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][230/312]	eta 0:00:39 lr 0.000861	time 0.4979 (0.4784)	model_time 0.4975 (0.4678)	loss 3.6331 (2.9746)	grad_norm 3.3547 (2.3570/1.0337)	mem 16099MB
[2025-01-18 07:52:32 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][240/312]	eta 0:00:34 lr 0.000860	time 0.5411 (0.4778)	model_time 0.5407 (0.4676)	loss 2.5809 (2.9757)	grad_norm 1.9896 (2.3384/1.0223)	mem 16099MB
[2025-01-18 07:52:37 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][250/312]	eta 0:00:29 lr 0.000860	time 0.5643 (0.4784)	model_time 0.5638 (0.4686)	loss 3.2903 (2.9805)	grad_norm 2.6248 (2.3425/1.0201)	mem 16099MB
[2025-01-18 07:52:41 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][260/312]	eta 0:00:24 lr 0.000859	time 0.4591 (0.4774)	model_time 0.4586 (0.4680)	loss 3.4436 (2.9867)	grad_norm 1.0848 (2.3403/1.0220)	mem 16099MB
[2025-01-18 07:52:46 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][270/312]	eta 0:00:20 lr 0.000858	time 0.4607 (0.4767)	model_time 0.4602 (0.4676)	loss 3.0933 (2.9784)	grad_norm 1.2801 (2.3439/1.0376)	mem 16099MB
[2025-01-18 07:52:51 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][280/312]	eta 0:00:15 lr 0.000858	time 0.4537 (0.4765)	model_time 0.4532 (0.4677)	loss 2.6501 (2.9856)	grad_norm 2.9386 (2.3989/1.0789)	mem 16099MB
[2025-01-18 07:52:55 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][290/312]	eta 0:00:10 lr 0.000857	time 0.4502 (0.4757)	model_time 0.4498 (0.4672)	loss 2.1710 (2.9880)	grad_norm 0.9473 (2.3860/1.0765)	mem 16099MB
[2025-01-18 07:53:00 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][300/312]	eta 0:00:05 lr 0.000857	time 0.4435 (0.4755)	model_time 0.4434 (0.4673)	loss 3.0066 (2.9941)	grad_norm 4.5958 (2.4120/1.1162)	mem 16099MB
[2025-01-18 07:53:05 internimage_t_1k_224] (main.py 510): INFO Train: [209/300][310/312]	eta 0:00:00 lr 0.000856	time 0.5518 (0.4763)	model_time 0.5517 (0.4683)	loss 3.2073 (2.9988)	grad_norm 1.8753 (2.4527/1.1623)	mem 16099MB
[2025-01-18 07:53:05 internimage_t_1k_224] (main.py 519): INFO EPOCH 209 training takes 0:02:28
[2025-01-18 07:53:05 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_209.pth saving......
[2025-01-18 07:53:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_209.pth saved !!!
[2025-01-18 07:53:14 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.585 (7.585)	Loss 0.7380 (0.7380)	Acc@1 83.594 (83.594)	Acc@5 96.826 (96.826)	Mem 16099MB
[2025-01-18 07:53:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.005)	Loss 0.9981 (0.8374)	Acc@1 77.808 (81.805)	Acc@5 94.263 (95.832)	Mem 16099MB
[2025-01-18 07:53:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:209] * Acc@1 81.652 Acc@5 95.839
[2025-01-18 07:53:18 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.7%
[2025-01-18 07:53:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 07:53:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 07:53:19 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.65%
[2025-01-18 07:53:26 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.376 (7.376)	Loss 0.7764 (0.7764)	Acc@1 85.083 (85.083)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 07:53:30 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.003)	Loss 1.0333 (0.8905)	Acc@1 78.223 (82.500)	Acc@5 94.995 (96.220)	Mem 16099MB
[2025-01-18 07:53:30 internimage_t_1k_224] (main.py 575): INFO [Epoch:209] * Acc@1 82.378 Acc@5 96.243
[2025-01-18 07:53:30 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.4%
[2025-01-18 07:53:30 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:53:31 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:53:31 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.38%
[2025-01-18 07:53:34 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][0/312]	eta 0:13:46 lr 0.000856	time 2.6499 (2.6499)	model_time 0.4788 (0.4788)	loss 3.6269 (3.6269)	grad_norm 2.0272 (2.0272/0.0000)	mem 16099MB
[2025-01-18 07:53:39 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][10/312]	eta 0:03:17 lr 0.000856	time 0.4485 (0.6537)	model_time 0.4481 (0.4560)	loss 2.8529 (3.0002)	grad_norm 2.9552 (2.4351/1.0877)	mem 16099MB
[2025-01-18 07:53:43 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][20/312]	eta 0:02:44 lr 0.000855	time 0.5702 (0.5649)	model_time 0.5698 (0.4612)	loss 3.1589 (3.1325)	grad_norm 1.2637 (2.2580/0.9885)	mem 16099MB
[2025-01-18 07:53:48 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][30/312]	eta 0:02:30 lr 0.000855	time 0.4500 (0.5332)	model_time 0.4498 (0.4628)	loss 3.0882 (3.0316)	grad_norm 1.1851 (2.0387/0.9193)	mem 16099MB
[2025-01-18 07:53:53 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][40/312]	eta 0:02:20 lr 0.000854	time 0.4912 (0.5171)	model_time 0.4910 (0.4638)	loss 3.1959 (3.0511)	grad_norm 4.0185 (2.1042/0.9116)	mem 16099MB
[2025-01-18 07:53:57 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][50/312]	eta 0:02:13 lr 0.000853	time 0.4509 (0.5078)	model_time 0.4505 (0.4649)	loss 2.7489 (3.0418)	grad_norm 3.5825 (2.2675/1.1143)	mem 16099MB
[2025-01-18 07:54:02 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][60/312]	eta 0:02:05 lr 0.000853	time 0.4503 (0.4998)	model_time 0.4499 (0.4639)	loss 3.6038 (3.0284)	grad_norm 2.5387 (2.3358/1.1512)	mem 16099MB
[2025-01-18 07:54:06 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][70/312]	eta 0:01:59 lr 0.000852	time 0.4454 (0.4934)	model_time 0.4450 (0.4624)	loss 1.9886 (2.9988)	grad_norm 1.6534 (2.3860/1.1367)	mem 16099MB
[2025-01-18 07:54:11 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][80/312]	eta 0:01:53 lr 0.000852	time 0.4755 (0.4908)	model_time 0.4753 (0.4637)	loss 3.1413 (2.9654)	grad_norm 2.4607 (2.3488/1.0934)	mem 16099MB
[2025-01-18 07:54:16 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][90/312]	eta 0:01:48 lr 0.000851	time 0.4591 (0.4867)	model_time 0.4587 (0.4625)	loss 3.2232 (2.9836)	grad_norm 1.4196 (2.3022/1.0594)	mem 16099MB
[2025-01-18 07:54:20 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][100/312]	eta 0:01:42 lr 0.000851	time 0.4479 (0.4843)	model_time 0.4474 (0.4625)	loss 3.1854 (2.9739)	grad_norm 1.7323 (2.2701/1.0314)	mem 16099MB
[2025-01-18 07:54:25 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][110/312]	eta 0:01:37 lr 0.000850	time 0.4499 (0.4814)	model_time 0.4495 (0.4614)	loss 3.4947 (2.9609)	grad_norm 1.4532 (2.2348/1.0129)	mem 16099MB
[2025-01-18 07:54:29 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][120/312]	eta 0:01:32 lr 0.000850	time 0.4553 (0.4792)	model_time 0.4549 (0.4609)	loss 3.3769 (2.9534)	grad_norm 2.4646 (2.2266/0.9813)	mem 16099MB
[2025-01-18 07:54:34 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][130/312]	eta 0:01:27 lr 0.000849	time 0.4564 (0.4781)	model_time 0.4562 (0.4611)	loss 2.3712 (2.9407)	grad_norm 3.2589 (2.2020/0.9732)	mem 16099MB
[2025-01-18 07:54:39 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][140/312]	eta 0:01:22 lr 0.000849	time 0.5350 (0.4769)	model_time 0.5346 (0.4611)	loss 3.4280 (2.9263)	grad_norm 3.2354 (2.2452/1.0181)	mem 16099MB
[2025-01-18 07:54:43 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][150/312]	eta 0:01:17 lr 0.000848	time 0.4499 (0.4772)	model_time 0.4494 (0.4625)	loss 3.8035 (2.9449)	grad_norm 3.0629 (2.2761/0.9968)	mem 16099MB
[2025-01-18 07:54:48 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][160/312]	eta 0:01:12 lr 0.000848	time 0.4488 (0.4769)	model_time 0.4486 (0.4630)	loss 2.7281 (2.9423)	grad_norm 2.3368 (2.2549/0.9775)	mem 16099MB
[2025-01-18 07:54:53 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][170/312]	eta 0:01:07 lr 0.000847	time 0.4510 (0.4761)	model_time 0.4509 (0.4630)	loss 3.5772 (2.9405)	grad_norm 1.8730 (2.2358/0.9709)	mem 16099MB
[2025-01-18 07:54:57 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][180/312]	eta 0:01:02 lr 0.000847	time 0.4504 (0.4753)	model_time 0.4500 (0.4630)	loss 3.2985 (2.9329)	grad_norm 3.8281 (2.2491/0.9896)	mem 16099MB
[2025-01-18 07:55:02 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][190/312]	eta 0:00:57 lr 0.000846	time 0.4416 (0.4742)	model_time 0.4415 (0.4624)	loss 2.6854 (2.9320)	grad_norm 3.0235 (2.3428/1.1524)	mem 16099MB
[2025-01-18 07:55:07 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][200/312]	eta 0:00:53 lr 0.000845	time 0.4500 (0.4732)	model_time 0.4499 (0.4620)	loss 3.2300 (2.9298)	grad_norm 1.6361 (2.3472/1.1298)	mem 16099MB
[2025-01-18 07:55:11 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][210/312]	eta 0:00:48 lr 0.000845	time 0.5305 (0.4731)	model_time 0.5300 (0.4625)	loss 2.8275 (2.9312)	grad_norm 3.1472 (2.3684/1.1281)	mem 16099MB
[2025-01-18 07:55:16 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][220/312]	eta 0:00:43 lr 0.000844	time 0.4527 (0.4726)	model_time 0.4523 (0.4624)	loss 2.4487 (2.9186)	grad_norm 1.4124 (2.3416/1.1126)	mem 16099MB
[2025-01-18 07:55:21 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][230/312]	eta 0:00:38 lr 0.000844	time 0.4511 (0.4724)	model_time 0.4506 (0.4626)	loss 2.9098 (2.9228)	grad_norm 2.4034 (2.3271/1.0963)	mem 16099MB
[2025-01-18 07:55:25 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][240/312]	eta 0:00:33 lr 0.000843	time 0.4516 (0.4719)	model_time 0.4515 (0.4625)	loss 2.3150 (2.9313)	grad_norm 1.8561 (2.3370/1.0982)	mem 16099MB
[2025-01-18 07:55:30 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][250/312]	eta 0:00:29 lr 0.000843	time 0.4598 (0.4720)	model_time 0.4597 (0.4629)	loss 3.3426 (2.9409)	grad_norm 2.3206 (2.3344/1.0832)	mem 16099MB
[2025-01-18 07:55:35 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][260/312]	eta 0:00:24 lr 0.000842	time 0.4490 (0.4717)	model_time 0.4486 (0.4630)	loss 3.3877 (2.9248)	grad_norm 1.1552 (2.3373/1.1091)	mem 16099MB
[2025-01-18 07:55:39 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][270/312]	eta 0:00:19 lr 0.000842	time 0.4580 (0.4717)	model_time 0.4576 (0.4633)	loss 3.2430 (2.9363)	grad_norm 1.8485 (2.3322/1.0948)	mem 16099MB
[2025-01-18 07:55:44 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][280/312]	eta 0:00:15 lr 0.000841	time 0.4514 (0.4715)	model_time 0.4509 (0.4634)	loss 2.7764 (2.9406)	grad_norm 1.1124 (2.2932/1.0953)	mem 16099MB
[2025-01-18 07:55:48 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][290/312]	eta 0:00:10 lr 0.000841	time 0.4403 (0.4710)	model_time 0.4398 (0.4631)	loss 1.8981 (2.9376)	grad_norm 1.8334 (2.2733/1.0851)	mem 16099MB
[2025-01-18 07:55:53 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][300/312]	eta 0:00:05 lr 0.000840	time 0.4385 (0.4711)	model_time 0.4384 (0.4635)	loss 3.0761 (2.9324)	grad_norm 3.6779 (2.2665/1.0756)	mem 16099MB
[2025-01-18 07:55:58 internimage_t_1k_224] (main.py 510): INFO Train: [210/300][310/312]	eta 0:00:00 lr 0.000840	time 0.4386 (0.4709)	model_time 0.4385 (0.4635)	loss 1.8349 (2.9261)	grad_norm 3.6447 (2.2808/1.0844)	mem 16099MB
[2025-01-18 07:55:58 internimage_t_1k_224] (main.py 519): INFO EPOCH 210 training takes 0:02:26
[2025-01-18 07:55:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_210.pth saving......
[2025-01-18 07:55:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_210.pth saved !!!
[2025-01-18 07:56:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.156 (7.156)	Loss 0.7260 (0.7260)	Acc@1 83.960 (83.960)	Acc@5 96.826 (96.826)	Mem 16099MB
[2025-01-18 07:56:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.973)	Loss 1.0210 (0.8472)	Acc@1 77.075 (81.723)	Acc@5 94.556 (95.761)	Mem 16099MB
[2025-01-18 07:56:10 internimage_t_1k_224] (main.py 575): INFO [Epoch:210] * Acc@1 81.578 Acc@5 95.797
[2025-01-18 07:56:10 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.6%
[2025-01-18 07:56:10 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.65%
[2025-01-18 07:56:19 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.221 (8.221)	Loss 0.7751 (0.7751)	Acc@1 85.083 (85.083)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 07:56:22 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.098)	Loss 1.0314 (0.8892)	Acc@1 78.198 (82.535)	Acc@5 95.020 (96.231)	Mem 16099MB
[2025-01-18 07:56:23 internimage_t_1k_224] (main.py 575): INFO [Epoch:210] * Acc@1 82.416 Acc@5 96.249
[2025-01-18 07:56:23 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.4%
[2025-01-18 07:56:23 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:56:24 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:56:24 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.42%
[2025-01-18 07:56:27 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][0/312]	eta 0:14:40 lr 0.000839	time 2.8219 (2.8219)	model_time 0.4917 (0.4917)	loss 2.6496 (2.6496)	grad_norm 2.4123 (2.4123/0.0000)	mem 16099MB
[2025-01-18 07:56:32 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][10/312]	eta 0:03:24 lr 0.000839	time 0.4698 (0.6787)	model_time 0.4697 (0.4666)	loss 3.5672 (2.8557)	grad_norm 1.4056 (2.1347/0.6070)	mem 16099MB
[2025-01-18 07:56:36 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][20/312]	eta 0:02:49 lr 0.000838	time 0.4531 (0.5811)	model_time 0.4529 (0.4699)	loss 3.8812 (2.9617)	grad_norm 2.3286 (2.5240/1.0121)	mem 16099MB
[2025-01-18 07:56:41 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][30/312]	eta 0:02:33 lr 0.000838	time 0.4548 (0.5438)	model_time 0.4546 (0.4683)	loss 2.3190 (2.9714)	grad_norm 2.4277 (2.3468/0.8938)	mem 16099MB
[2025-01-18 07:56:46 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][40/312]	eta 0:02:24 lr 0.000837	time 0.5593 (0.5311)	model_time 0.5591 (0.4740)	loss 3.0041 (2.9672)	grad_norm 2.2902 (2.1794/0.8482)	mem 16099MB
[2025-01-18 07:56:50 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][50/312]	eta 0:02:15 lr 0.000837	time 0.4463 (0.5172)	model_time 0.4461 (0.4712)	loss 3.3702 (2.9942)	grad_norm 1.1206 (2.1601/0.8601)	mem 16099MB
[2025-01-18 07:56:55 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][60/312]	eta 0:02:07 lr 0.000836	time 0.4583 (0.5067)	model_time 0.4578 (0.4682)	loss 2.5377 (2.9649)	grad_norm 2.4168 (2.2482/0.9999)	mem 16099MB
[2025-01-18 07:57:00 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][70/312]	eta 0:02:01 lr 0.000836	time 0.4539 (0.5007)	model_time 0.4534 (0.4675)	loss 3.9089 (2.9724)	grad_norm 1.9101 (2.1756/0.9629)	mem 16099MB
[2025-01-18 07:57:04 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][80/312]	eta 0:01:54 lr 0.000835	time 0.4486 (0.4954)	model_time 0.4481 (0.4663)	loss 3.5711 (2.9972)	grad_norm 3.4915 (2.1685/0.9503)	mem 16099MB
[2025-01-18 07:57:09 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][90/312]	eta 0:01:49 lr 0.000835	time 0.4489 (0.4932)	model_time 0.4487 (0.4670)	loss 3.3271 (3.0096)	grad_norm 2.8485 (2.1732/0.9265)	mem 16099MB
[2025-01-18 07:57:13 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][100/312]	eta 0:01:43 lr 0.000834	time 0.4615 (0.4894)	model_time 0.4613 (0.4658)	loss 1.8823 (2.9976)	grad_norm 2.8523 (2.2721/1.0843)	mem 16099MB
[2025-01-18 07:57:18 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][110/312]	eta 0:01:38 lr 0.000834	time 0.4520 (0.4867)	model_time 0.4519 (0.4651)	loss 3.6166 (3.0114)	grad_norm 2.8473 (2.4100/1.2065)	mem 16099MB
[2025-01-18 07:57:23 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][120/312]	eta 0:01:33 lr 0.000833	time 0.4795 (0.4848)	model_time 0.4794 (0.4650)	loss 3.0282 (2.9894)	grad_norm 1.4904 (2.3447/1.1813)	mem 16099MB
[2025-01-18 07:57:27 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][130/312]	eta 0:01:27 lr 0.000833	time 0.4394 (0.4834)	model_time 0.4392 (0.4651)	loss 2.6833 (2.9813)	grad_norm 0.9177 (2.3471/1.1534)	mem 16099MB
[2025-01-18 07:57:32 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][140/312]	eta 0:01:22 lr 0.000832	time 0.4437 (0.4820)	model_time 0.4432 (0.4649)	loss 3.2792 (2.9654)	grad_norm 1.6920 (2.2965/1.1346)	mem 16099MB
[2025-01-18 07:57:37 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][150/312]	eta 0:01:17 lr 0.000831	time 0.4571 (0.4812)	model_time 0.4567 (0.4653)	loss 2.5338 (2.9487)	grad_norm 2.1260 (2.2856/1.1138)	mem 16099MB
[2025-01-18 07:57:41 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][160/312]	eta 0:01:12 lr 0.000831	time 0.4507 (0.4802)	model_time 0.4503 (0.4652)	loss 3.2209 (2.9679)	grad_norm 1.5015 (2.2766/1.0972)	mem 16099MB
[2025-01-18 07:57:46 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][170/312]	eta 0:01:08 lr 0.000830	time 0.4397 (0.4800)	model_time 0.4395 (0.4659)	loss 3.0173 (2.9620)	grad_norm 2.0306 (2.3050/1.1037)	mem 16099MB
[2025-01-18 07:57:51 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][180/312]	eta 0:01:03 lr 0.000830	time 0.4623 (0.4795)	model_time 0.4618 (0.4661)	loss 2.8689 (2.9643)	grad_norm 4.4805 (2.3606/1.1231)	mem 16099MB
[2025-01-18 07:57:56 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][190/312]	eta 0:00:58 lr 0.000829	time 0.4728 (0.4799)	model_time 0.4727 (0.4672)	loss 3.1731 (2.9530)	grad_norm 3.0857 (2.4173/1.1517)	mem 16099MB
[2025-01-18 07:58:00 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][200/312]	eta 0:00:53 lr 0.000829	time 0.4429 (0.4787)	model_time 0.4423 (0.4666)	loss 2.2356 (2.9569)	grad_norm 1.5311 (2.4218/1.1356)	mem 16099MB
[2025-01-18 07:58:05 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][210/312]	eta 0:00:48 lr 0.000828	time 0.5579 (0.4784)	model_time 0.5577 (0.4669)	loss 3.2300 (2.9558)	grad_norm 1.8152 (2.4089/1.1149)	mem 16099MB
[2025-01-18 07:58:10 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][220/312]	eta 0:00:43 lr 0.000828	time 0.4636 (0.4777)	model_time 0.4631 (0.4666)	loss 3.0389 (2.9587)	grad_norm 2.7919 (2.4014/1.1049)	mem 16099MB
[2025-01-18 07:58:14 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][230/312]	eta 0:00:39 lr 0.000827	time 0.4857 (0.4776)	model_time 0.4852 (0.4671)	loss 3.2673 (2.9554)	grad_norm 2.5324 (2.4284/1.1093)	mem 16099MB
[2025-01-18 07:58:19 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][240/312]	eta 0:00:34 lr 0.000827	time 0.4620 (0.4767)	model_time 0.4615 (0.4665)	loss 3.2075 (2.9561)	grad_norm 2.1648 (2.4321/1.1009)	mem 16099MB
[2025-01-18 07:58:23 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][250/312]	eta 0:00:29 lr 0.000826	time 0.4508 (0.4757)	model_time 0.4506 (0.4659)	loss 3.7096 (2.9669)	grad_norm 1.2696 (2.4094/1.0959)	mem 16099MB
[2025-01-18 07:58:28 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][260/312]	eta 0:00:24 lr 0.000826	time 0.4593 (0.4752)	model_time 0.4589 (0.4658)	loss 2.8338 (2.9664)	grad_norm 1.7153 (2.4017/1.0811)	mem 16099MB
[2025-01-18 07:58:33 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][270/312]	eta 0:00:19 lr 0.000825	time 0.4471 (0.4749)	model_time 0.4469 (0.4659)	loss 2.1555 (2.9682)	grad_norm 1.1937 (2.4034/1.0752)	mem 16099MB
[2025-01-18 07:58:38 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][280/312]	eta 0:00:15 lr 0.000825	time 0.4466 (0.4752)	model_time 0.4461 (0.4665)	loss 2.5242 (2.9743)	grad_norm 3.1146 (2.4057/1.0660)	mem 16099MB
[2025-01-18 07:58:42 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][290/312]	eta 0:00:10 lr 0.000824	time 0.4597 (0.4751)	model_time 0.4593 (0.4666)	loss 2.4663 (2.9676)	grad_norm 2.5749 (2.4155/1.0718)	mem 16099MB
[2025-01-18 07:58:47 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][300/312]	eta 0:00:05 lr 0.000824	time 0.4394 (0.4745)	model_time 0.4393 (0.4663)	loss 2.5713 (2.9714)	grad_norm 3.8171 (2.4174/1.0632)	mem 16099MB
[2025-01-18 07:58:51 internimage_t_1k_224] (main.py 510): INFO Train: [211/300][310/312]	eta 0:00:00 lr 0.000823	time 0.4400 (0.4738)	model_time 0.4399 (0.4658)	loss 2.7678 (2.9734)	grad_norm 3.1402 (2.4144/1.0652)	mem 16099MB
[2025-01-18 07:58:52 internimage_t_1k_224] (main.py 519): INFO EPOCH 211 training takes 0:02:27
[2025-01-18 07:58:52 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_211.pth saving......
[2025-01-18 07:58:53 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_211.pth saved !!!
[2025-01-18 07:59:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.201 (7.201)	Loss 0.7386 (0.7386)	Acc@1 83.887 (83.887)	Acc@5 97.144 (97.144)	Mem 16099MB
[2025-01-18 07:59:04 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.976)	Loss 1.0273 (0.8624)	Acc@1 76.978 (81.630)	Acc@5 94.360 (95.801)	Mem 16099MB
[2025-01-18 07:59:04 internimage_t_1k_224] (main.py 575): INFO [Epoch:211] * Acc@1 81.498 Acc@5 95.847
[2025-01-18 07:59:04 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.5%
[2025-01-18 07:59:04 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.65%
[2025-01-18 07:59:12 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.121 (8.121)	Loss 0.7737 (0.7737)	Acc@1 85.059 (85.059)	Acc@5 97.534 (97.534)	Mem 16099MB
[2025-01-18 07:59:16 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.086)	Loss 1.0297 (0.8879)	Acc@1 78.223 (82.551)	Acc@5 95.020 (96.240)	Mem 16099MB
[2025-01-18 07:59:16 internimage_t_1k_224] (main.py 575): INFO [Epoch:211] * Acc@1 82.438 Acc@5 96.257
[2025-01-18 07:59:16 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.4%
[2025-01-18 07:59:16 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 07:59:17 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 07:59:17 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.44%
[2025-01-18 07:59:20 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][0/312]	eta 0:14:31 lr 0.000823	time 2.7946 (2.7946)	model_time 0.4729 (0.4729)	loss 3.2974 (3.2974)	grad_norm 1.1017 (1.1017/0.0000)	mem 16099MB
[2025-01-18 07:59:25 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][10/312]	eta 0:03:22 lr 0.000822	time 0.4602 (0.6704)	model_time 0.4597 (0.4590)	loss 2.8969 (2.9483)	grad_norm 1.7427 (2.0846/0.9281)	mem 16099MB
[2025-01-18 07:59:29 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][20/312]	eta 0:02:46 lr 0.000822	time 0.4599 (0.5691)	model_time 0.4597 (0.4582)	loss 3.4055 (3.0531)	grad_norm 4.8308 (2.2507/0.9891)	mem 16099MB
[2025-01-18 07:59:34 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][30/312]	eta 0:02:32 lr 0.000821	time 0.4601 (0.5413)	model_time 0.4597 (0.4660)	loss 2.8788 (3.0300)	grad_norm 2.0074 (2.6432/1.3278)	mem 16099MB
[2025-01-18 07:59:39 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][40/312]	eta 0:02:22 lr 0.000821	time 0.4484 (0.5225)	model_time 0.4482 (0.4655)	loss 2.2680 (2.9573)	grad_norm 2.7001 (2.9675/1.5616)	mem 16099MB
[2025-01-18 07:59:44 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][50/312]	eta 0:02:15 lr 0.000820	time 0.5467 (0.5168)	model_time 0.5462 (0.4709)	loss 2.8896 (2.9673)	grad_norm 4.4421 (2.9473/1.4579)	mem 16099MB
[2025-01-18 07:59:48 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][60/312]	eta 0:02:08 lr 0.000820	time 0.4464 (0.5101)	model_time 0.4462 (0.4716)	loss 2.2452 (2.9906)	grad_norm 2.2792 (2.8535/1.4059)	mem 16099MB
[2025-01-18 07:59:53 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][70/312]	eta 0:02:01 lr 0.000819	time 0.4451 (0.5022)	model_time 0.4446 (0.4691)	loss 2.1359 (2.9874)	grad_norm 2.4927 (2.7725/1.3760)	mem 16099MB
[2025-01-18 07:59:58 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][80/312]	eta 0:01:55 lr 0.000819	time 0.4641 (0.4987)	model_time 0.4639 (0.4697)	loss 3.1462 (2.9516)	grad_norm 1.2363 (2.7243/1.3702)	mem 16099MB
[2025-01-18 08:00:02 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][90/312]	eta 0:01:49 lr 0.000818	time 0.4456 (0.4936)	model_time 0.4454 (0.4677)	loss 2.8241 (2.9726)	grad_norm 1.3110 (2.6569/1.3489)	mem 16099MB
[2025-01-18 08:00:07 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][100/312]	eta 0:01:43 lr 0.000818	time 0.4506 (0.4896)	model_time 0.4504 (0.4662)	loss 2.8243 (2.9893)	grad_norm 2.4980 (2.7128/1.3687)	mem 16099MB
[2025-01-18 08:00:12 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][110/312]	eta 0:01:39 lr 0.000817	time 0.4506 (0.4924)	model_time 0.4504 (0.4711)	loss 3.3298 (2.9860)	grad_norm 2.7503 (2.6877/1.3321)	mem 16099MB
[2025-01-18 08:00:17 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][120/312]	eta 0:01:34 lr 0.000817	time 0.4613 (0.4896)	model_time 0.4608 (0.4700)	loss 2.1324 (2.9753)	grad_norm 2.1440 (2.6370/1.3029)	mem 16099MB
[2025-01-18 08:00:21 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][130/312]	eta 0:01:28 lr 0.000816	time 0.4564 (0.4874)	model_time 0.4563 (0.4693)	loss 3.3868 (2.9659)	grad_norm 1.6807 (2.5520/1.2955)	mem 16099MB
[2025-01-18 08:00:26 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][140/312]	eta 0:01:23 lr 0.000815	time 0.5643 (0.4867)	model_time 0.5638 (0.4699)	loss 2.3890 (2.9645)	grad_norm 1.0841 (2.5251/1.2681)	mem 16099MB
[2025-01-18 08:00:31 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][150/312]	eta 0:01:18 lr 0.000815	time 0.4401 (0.4861)	model_time 0.4399 (0.4703)	loss 2.8199 (2.9523)	grad_norm 2.2277 (2.5308/1.2616)	mem 16099MB
[2025-01-18 08:00:35 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][160/312]	eta 0:01:13 lr 0.000814	time 0.4705 (0.4853)	model_time 0.4701 (0.4705)	loss 2.7719 (2.9620)	grad_norm 2.8073 (2.4910/1.2484)	mem 16099MB
[2025-01-18 08:00:40 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][170/312]	eta 0:01:08 lr 0.000814	time 0.4527 (0.4856)	model_time 0.4522 (0.4716)	loss 2.0227 (2.9395)	grad_norm 2.6248 (2.4564/1.2271)	mem 16099MB
[2025-01-18 08:00:45 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][180/312]	eta 0:01:03 lr 0.000813	time 0.4401 (0.4842)	model_time 0.4396 (0.4709)	loss 2.8996 (2.9323)	grad_norm 1.8008 (2.4395/1.2076)	mem 16099MB
[2025-01-18 08:00:50 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][190/312]	eta 0:00:59 lr 0.000813	time 0.5373 (0.4837)	model_time 0.5368 (0.4711)	loss 2.6889 (2.9321)	grad_norm 3.1914 (2.4208/1.1868)	mem 16099MB
[2025-01-18 08:00:54 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][200/312]	eta 0:00:53 lr 0.000812	time 0.4602 (0.4821)	model_time 0.4597 (0.4701)	loss 3.5272 (2.9370)	grad_norm 1.4739 (2.3815/1.1793)	mem 16099MB
[2025-01-18 08:00:59 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][210/312]	eta 0:00:49 lr 0.000812	time 0.4490 (0.4812)	model_time 0.4487 (0.4698)	loss 2.7230 (2.9389)	grad_norm 3.0139 (2.4051/1.1727)	mem 16099MB
[2025-01-18 08:01:04 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][220/312]	eta 0:00:44 lr 0.000811	time 0.4458 (0.4808)	model_time 0.4453 (0.4699)	loss 3.2438 (2.9499)	grad_norm 1.6250 (2.4406/1.1777)	mem 16099MB
[2025-01-18 08:01:08 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][230/312]	eta 0:00:39 lr 0.000811	time 0.5564 (0.4805)	model_time 0.5559 (0.4700)	loss 2.1442 (2.9554)	grad_norm 1.9146 (2.4529/1.1783)	mem 16099MB
[2025-01-18 08:01:13 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][240/312]	eta 0:00:34 lr 0.000810	time 0.4510 (0.4798)	model_time 0.4508 (0.4698)	loss 1.8989 (2.9492)	grad_norm 0.8467 (2.4115/1.1739)	mem 16099MB
[2025-01-18 08:01:17 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][250/312]	eta 0:00:29 lr 0.000810	time 0.4536 (0.4788)	model_time 0.4535 (0.4691)	loss 3.3848 (2.9562)	grad_norm 6.8488 (2.4367/1.1965)	mem 16099MB
[2025-01-18 08:01:22 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][260/312]	eta 0:00:24 lr 0.000809	time 0.5398 (0.4781)	model_time 0.5397 (0.4688)	loss 2.1319 (2.9551)	grad_norm 1.2416 (2.4300/1.1851)	mem 16099MB
[2025-01-18 08:01:27 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][270/312]	eta 0:00:20 lr 0.000809	time 0.4555 (0.4781)	model_time 0.4551 (0.4692)	loss 3.2832 (2.9561)	grad_norm 1.9184 (2.4046/1.1718)	mem 16099MB
[2025-01-18 08:01:32 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][280/312]	eta 0:00:15 lr 0.000808	time 0.4698 (0.4777)	model_time 0.4696 (0.4690)	loss 2.2706 (2.9463)	grad_norm 3.9194 (2.4071/1.1672)	mem 16099MB
[2025-01-18 08:01:36 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][290/312]	eta 0:00:10 lr 0.000808	time 0.4400 (0.4775)	model_time 0.4398 (0.4691)	loss 2.8921 (2.9556)	grad_norm 1.0665 (2.4206/1.1741)	mem 16099MB
[2025-01-18 08:01:41 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][300/312]	eta 0:00:05 lr 0.000807	time 0.7061 (0.4778)	model_time 0.7060 (0.4697)	loss 2.8913 (2.9514)	grad_norm 4.8356 (2.4571/1.1918)	mem 16099MB
[2025-01-18 08:01:46 internimage_t_1k_224] (main.py 510): INFO Train: [212/300][310/312]	eta 0:00:00 lr 0.000807	time 0.4393 (0.4766)	model_time 0.4392 (0.4687)	loss 3.3060 (2.9438)	grad_norm 3.1764 (2.4713/1.1896)	mem 16099MB
[2025-01-18 08:01:46 internimage_t_1k_224] (main.py 519): INFO EPOCH 212 training takes 0:02:28
[2025-01-18 08:01:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_212.pth saving......
[2025-01-18 08:01:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_212.pth saved !!!
[2025-01-18 08:01:55 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.642 (7.642)	Loss 0.7836 (0.7836)	Acc@1 83.984 (83.984)	Acc@5 96.924 (96.924)	Mem 16099MB
[2025-01-18 08:01:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.024)	Loss 1.0652 (0.8908)	Acc@1 76.660 (81.663)	Acc@5 94.580 (95.890)	Mem 16099MB
[2025-01-18 08:01:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:212] * Acc@1 81.558 Acc@5 95.887
[2025-01-18 08:01:59 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.6%
[2025-01-18 08:01:59 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.65%
[2025-01-18 08:02:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.276 (8.276)	Loss 0.7728 (0.7728)	Acc@1 85.083 (85.083)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 08:02:11 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.111)	Loss 1.0282 (0.8867)	Acc@1 78.247 (82.577)	Acc@5 95.020 (96.249)	Mem 16099MB
[2025-01-18 08:02:11 internimage_t_1k_224] (main.py 575): INFO [Epoch:212] * Acc@1 82.458 Acc@5 96.261
[2025-01-18 08:02:11 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.5%
[2025-01-18 08:02:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:02:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:02:12 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.46%
[2025-01-18 08:02:15 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][0/312]	eta 0:13:04 lr 0.000806	time 2.5157 (2.5157)	model_time 0.5112 (0.5112)	loss 3.7605 (3.7605)	grad_norm 0.8990 (0.8990/0.0000)	mem 16099MB
[2025-01-18 08:02:20 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][10/312]	eta 0:03:22 lr 0.000806	time 0.5350 (0.6710)	model_time 0.5348 (0.4885)	loss 3.1148 (3.0603)	grad_norm 1.2621 (2.4317/1.1661)	mem 16099MB
[2025-01-18 08:02:24 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][20/312]	eta 0:02:46 lr 0.000805	time 0.4591 (0.5714)	model_time 0.4590 (0.4756)	loss 2.6073 (2.8745)	grad_norm 1.2386 (2.1533/0.9600)	mem 16099MB
[2025-01-18 08:02:29 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][30/312]	eta 0:02:30 lr 0.000805	time 0.4535 (0.5338)	model_time 0.4533 (0.4688)	loss 2.2718 (2.8980)	grad_norm 1.6686 (2.2333/0.9017)	mem 16099MB
[2025-01-18 08:02:34 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][40/312]	eta 0:02:20 lr 0.000804	time 0.4401 (0.5178)	model_time 0.4397 (0.4686)	loss 1.8615 (2.8331)	grad_norm 2.9743 (2.4391/0.9213)	mem 16099MB
[2025-01-18 08:02:38 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][50/312]	eta 0:02:12 lr 0.000804	time 0.4551 (0.5059)	model_time 0.4549 (0.4663)	loss 3.5455 (2.8634)	grad_norm 1.4569 (2.3735/0.9487)	mem 16099MB
[2025-01-18 08:02:43 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][60/312]	eta 0:02:05 lr 0.000803	time 0.4554 (0.4993)	model_time 0.4552 (0.4661)	loss 3.5798 (2.8911)	grad_norm 1.8919 (2.3221/1.0089)	mem 16099MB
[2025-01-18 08:02:47 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][70/312]	eta 0:01:59 lr 0.000803	time 0.4635 (0.4948)	model_time 0.4633 (0.4662)	loss 2.7490 (2.9225)	grad_norm 1.3264 (2.2173/0.9803)	mem 16099MB
[2025-01-18 08:02:52 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][80/312]	eta 0:01:53 lr 0.000802	time 0.4637 (0.4903)	model_time 0.4633 (0.4652)	loss 2.6921 (2.9166)	grad_norm 1.1481 (2.2026/0.9377)	mem 16099MB
[2025-01-18 08:02:57 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][90/312]	eta 0:01:48 lr 0.000802	time 0.4502 (0.4890)	model_time 0.4498 (0.4667)	loss 3.1748 (2.9232)	grad_norm 1.0642 (2.2162/0.9372)	mem 16099MB
[2025-01-18 08:03:02 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][100/312]	eta 0:01:43 lr 0.000801	time 0.5534 (0.4872)	model_time 0.5529 (0.4670)	loss 3.3994 (2.9289)	grad_norm 1.7467 (2.1802/0.9030)	mem 16099MB
[2025-01-18 08:03:07 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][110/312]	eta 0:01:38 lr 0.000801	time 0.4773 (0.4879)	model_time 0.4772 (0.4695)	loss 3.0565 (2.9424)	grad_norm 3.4478 (2.2439/0.9259)	mem 16099MB
[2025-01-18 08:03:11 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][120/312]	eta 0:01:33 lr 0.000800	time 0.5459 (0.4866)	model_time 0.5457 (0.4697)	loss 3.1902 (2.9387)	grad_norm 2.6783 (2.2513/0.9271)	mem 16099MB
[2025-01-18 08:03:16 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][130/312]	eta 0:01:28 lr 0.000800	time 0.5440 (0.4853)	model_time 0.5436 (0.4697)	loss 3.3287 (2.9432)	grad_norm 4.4565 (2.2306/0.9329)	mem 16099MB
[2025-01-18 08:03:21 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][140/312]	eta 0:01:23 lr 0.000799	time 0.4398 (0.4840)	model_time 0.4395 (0.4695)	loss 3.1051 (2.9250)	grad_norm 2.9415 (2.2493/0.9335)	mem 16099MB
[2025-01-18 08:03:25 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][150/312]	eta 0:01:18 lr 0.000799	time 0.4578 (0.4826)	model_time 0.4573 (0.4690)	loss 3.0987 (2.9197)	grad_norm 1.6379 (2.2763/0.9992)	mem 16099MB
[2025-01-18 08:03:30 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][160/312]	eta 0:01:13 lr 0.000798	time 0.7538 (0.4841)	model_time 0.7533 (0.4713)	loss 2.6990 (2.9217)	grad_norm 2.9126 (2.2934/0.9863)	mem 16099MB
[2025-01-18 08:03:35 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][170/312]	eta 0:01:08 lr 0.000798	time 0.4562 (0.4842)	model_time 0.4558 (0.4721)	loss 3.4114 (2.9041)	grad_norm 3.3285 (2.3322/1.0190)	mem 16099MB
[2025-01-18 08:03:40 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][180/312]	eta 0:01:03 lr 0.000797	time 0.4615 (0.4831)	model_time 0.4611 (0.4716)	loss 3.2209 (2.9053)	grad_norm 1.8861 (2.3586/1.0318)	mem 16099MB
[2025-01-18 08:03:44 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][190/312]	eta 0:00:58 lr 0.000796	time 0.4533 (0.4817)	model_time 0.4531 (0.4708)	loss 3.0714 (2.9099)	grad_norm 2.3253 (2.3400/1.0249)	mem 16099MB
[2025-01-18 08:03:49 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][200/312]	eta 0:00:53 lr 0.000796	time 0.4511 (0.4806)	model_time 0.4507 (0.4703)	loss 3.2600 (2.9198)	grad_norm 1.4700 (2.3366/1.0240)	mem 16099MB
[2025-01-18 08:03:54 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][210/312]	eta 0:00:48 lr 0.000795	time 0.4703 (0.4795)	model_time 0.4699 (0.4696)	loss 3.2644 (2.9206)	grad_norm 1.1190 (2.3678/1.0491)	mem 16099MB
[2025-01-18 08:03:58 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][220/312]	eta 0:00:44 lr 0.000795	time 0.4490 (0.4793)	model_time 0.4486 (0.4699)	loss 3.2710 (2.9283)	grad_norm 1.0217 (2.3717/1.0397)	mem 16099MB
[2025-01-18 08:04:03 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][230/312]	eta 0:00:39 lr 0.000794	time 0.4509 (0.4788)	model_time 0.4505 (0.4697)	loss 3.4527 (2.9301)	grad_norm 1.0769 (2.3471/1.0308)	mem 16099MB
[2025-01-18 08:04:08 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][240/312]	eta 0:00:34 lr 0.000794	time 0.4576 (0.4783)	model_time 0.4572 (0.4696)	loss 3.1665 (2.9243)	grad_norm 2.2328 (2.3428/1.0202)	mem 16099MB
[2025-01-18 08:04:12 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][250/312]	eta 0:00:29 lr 0.000793	time 0.4622 (0.4775)	model_time 0.4617 (0.4691)	loss 3.0235 (2.9338)	grad_norm 1.7243 (2.3261/1.0142)	mem 16099MB
[2025-01-18 08:04:17 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][260/312]	eta 0:00:24 lr 0.000793	time 0.4504 (0.4770)	model_time 0.4503 (0.4689)	loss 3.3397 (2.9366)	grad_norm 2.9586 (2.3168/1.0058)	mem 16099MB
[2025-01-18 08:04:21 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][270/312]	eta 0:00:20 lr 0.000792	time 0.4639 (0.4762)	model_time 0.4634 (0.4684)	loss 3.2895 (2.9370)	grad_norm 3.6173 (2.3390/1.0076)	mem 16099MB
[2025-01-18 08:04:26 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][280/312]	eta 0:00:15 lr 0.000792	time 0.4460 (0.4759)	model_time 0.4458 (0.4684)	loss 3.2264 (2.9407)	grad_norm 1.7615 (2.3665/1.0565)	mem 16099MB
[2025-01-18 08:04:31 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][290/312]	eta 0:00:10 lr 0.000791	time 0.4633 (0.4754)	model_time 0.4629 (0.4681)	loss 3.0628 (2.9400)	grad_norm 1.9125 (2.3608/1.0529)	mem 16099MB
[2025-01-18 08:04:35 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][300/312]	eta 0:00:05 lr 0.000791	time 0.4372 (0.4745)	model_time 0.4371 (0.4674)	loss 2.5399 (2.9353)	grad_norm 1.8857 (2.3729/1.0615)	mem 16099MB
[2025-01-18 08:04:40 internimage_t_1k_224] (main.py 510): INFO Train: [213/300][310/312]	eta 0:00:00 lr 0.000790	time 0.4382 (0.4735)	model_time 0.4381 (0.4667)	loss 3.6061 (2.9383)	grad_norm 2.6227 (2.3896/1.0688)	mem 16099MB
[2025-01-18 08:04:40 internimage_t_1k_224] (main.py 519): INFO EPOCH 213 training takes 0:02:27
[2025-01-18 08:04:40 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_213.pth saving......
[2025-01-18 08:04:41 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_213.pth saved !!!
[2025-01-18 08:04:49 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.264 (7.264)	Loss 0.7547 (0.7547)	Acc@1 84.253 (84.253)	Acc@5 96.924 (96.924)	Mem 16099MB
[2025-01-18 08:04:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.974)	Loss 1.0130 (0.8629)	Acc@1 77.173 (81.683)	Acc@5 94.507 (95.819)	Mem 16099MB
[2025-01-18 08:04:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:213] * Acc@1 81.602 Acc@5 95.855
[2025-01-18 08:04:52 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.6%
[2025-01-18 08:04:52 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.65%
[2025-01-18 08:05:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.231 (8.231)	Loss 0.7721 (0.7721)	Acc@1 85.132 (85.132)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 08:05:04 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.103)	Loss 1.0266 (0.8855)	Acc@1 78.394 (82.617)	Acc@5 94.971 (96.265)	Mem 16099MB
[2025-01-18 08:05:04 internimage_t_1k_224] (main.py 575): INFO [Epoch:213] * Acc@1 82.494 Acc@5 96.281
[2025-01-18 08:05:04 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.5%
[2025-01-18 08:05:04 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:05:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:05:06 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.49%
[2025-01-18 08:05:09 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][0/312]	eta 0:15:40 lr 0.000790	time 3.0134 (3.0134)	model_time 0.4733 (0.4733)	loss 3.4158 (3.4158)	grad_norm 6.7779 (6.7779/0.0000)	mem 16099MB
[2025-01-18 08:05:13 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][10/312]	eta 0:03:31 lr 0.000790	time 0.5404 (0.7018)	model_time 0.5402 (0.4705)	loss 3.0130 (2.9329)	grad_norm 1.3640 (2.8954/1.6184)	mem 16099MB
[2025-01-18 08:05:18 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][20/312]	eta 0:02:52 lr 0.000789	time 0.5354 (0.5921)	model_time 0.5353 (0.4707)	loss 2.4030 (2.9415)	grad_norm 4.4279 (3.0706/1.4630)	mem 16099MB
[2025-01-18 08:05:23 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][30/312]	eta 0:02:34 lr 0.000789	time 0.4569 (0.5474)	model_time 0.4568 (0.4651)	loss 2.7454 (2.9274)	grad_norm 1.2035 (2.9085/1.3394)	mem 16099MB
[2025-01-18 08:05:27 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][40/312]	eta 0:02:22 lr 0.000788	time 0.4531 (0.5246)	model_time 0.4527 (0.4622)	loss 3.6996 (2.9481)	grad_norm 2.5176 (2.6692/1.2715)	mem 16099MB
[2025-01-18 08:05:32 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][50/312]	eta 0:02:15 lr 0.000788	time 0.4440 (0.5183)	model_time 0.4436 (0.4681)	loss 3.3240 (2.9454)	grad_norm 1.1876 (2.5127/1.2430)	mem 16099MB
[2025-01-18 08:05:37 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][60/312]	eta 0:02:08 lr 0.000787	time 0.5403 (0.5094)	model_time 0.5398 (0.4674)	loss 2.2705 (2.9930)	grad_norm 1.8331 (2.4000/1.1932)	mem 16099MB
[2025-01-18 08:05:41 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][70/312]	eta 0:02:01 lr 0.000786	time 0.4412 (0.5015)	model_time 0.4408 (0.4654)	loss 2.6776 (3.0107)	grad_norm 2.8753 (2.3537/1.1306)	mem 16099MB
[2025-01-18 08:05:46 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][80/312]	eta 0:01:55 lr 0.000786	time 0.4452 (0.4967)	model_time 0.4450 (0.4650)	loss 3.4559 (3.0209)	grad_norm 2.3992 (2.3266/1.0994)	mem 16099MB
[2025-01-18 08:05:51 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][90/312]	eta 0:01:49 lr 0.000785	time 0.5409 (0.4946)	model_time 0.5405 (0.4663)	loss 3.0221 (3.0455)	grad_norm 1.9795 (2.3540/1.0848)	mem 16099MB
[2025-01-18 08:05:56 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][100/312]	eta 0:01:44 lr 0.000785	time 0.4427 (0.4939)	model_time 0.4423 (0.4683)	loss 3.2585 (3.0305)	grad_norm 2.2024 (2.3222/1.0434)	mem 16099MB
[2025-01-18 08:06:00 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][110/312]	eta 0:01:39 lr 0.000784	time 0.4522 (0.4913)	model_time 0.4521 (0.4680)	loss 2.9220 (3.0194)	grad_norm 1.5582 (2.3143/1.0762)	mem 16099MB
[2025-01-18 08:06:05 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][120/312]	eta 0:01:33 lr 0.000784	time 0.4589 (0.4880)	model_time 0.4587 (0.4666)	loss 3.7360 (3.0128)	grad_norm 2.2895 (2.3145/1.0583)	mem 16099MB
[2025-01-18 08:06:10 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][130/312]	eta 0:01:28 lr 0.000783	time 0.4403 (0.4884)	model_time 0.4401 (0.4686)	loss 3.1052 (2.9919)	grad_norm 1.8072 (2.2995/1.0495)	mem 16099MB
[2025-01-18 08:06:14 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][140/312]	eta 0:01:23 lr 0.000783	time 0.4490 (0.4871)	model_time 0.4486 (0.4687)	loss 3.4127 (2.9678)	grad_norm 2.6142 (2.2838/1.0310)	mem 16099MB
[2025-01-18 08:06:20 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][150/312]	eta 0:01:19 lr 0.000782	time 0.4498 (0.4893)	model_time 0.4497 (0.4721)	loss 2.4122 (2.9706)	grad_norm 1.4091 (2.2440/1.0130)	mem 16099MB
[2025-01-18 08:06:24 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][160/312]	eta 0:01:14 lr 0.000782	time 0.4532 (0.4885)	model_time 0.4527 (0.4723)	loss 3.0686 (2.9799)	grad_norm 1.2660 (2.2262/1.0151)	mem 16099MB
[2025-01-18 08:06:29 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][170/312]	eta 0:01:09 lr 0.000781	time 0.4615 (0.4866)	model_time 0.4611 (0.4714)	loss 3.2142 (2.9741)	grad_norm 1.2009 (2.2076/1.0060)	mem 16099MB
[2025-01-18 08:06:34 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][180/312]	eta 0:01:04 lr 0.000781	time 0.4638 (0.4866)	model_time 0.4633 (0.4722)	loss 3.2167 (2.9761)	grad_norm 2.5923 (2.2565/1.0275)	mem 16099MB
[2025-01-18 08:06:38 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][190/312]	eta 0:00:59 lr 0.000780	time 0.4523 (0.4848)	model_time 0.4518 (0.4711)	loss 3.4702 (2.9678)	grad_norm 3.4559 (2.3360/1.0657)	mem 16099MB
[2025-01-18 08:06:43 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][200/312]	eta 0:00:54 lr 0.000780	time 0.4617 (0.4835)	model_time 0.4616 (0.4705)	loss 1.9990 (2.9659)	grad_norm 1.0695 (2.3364/1.0618)	mem 16099MB
[2025-01-18 08:06:48 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][210/312]	eta 0:00:49 lr 0.000779	time 0.4518 (0.4824)	model_time 0.4517 (0.4699)	loss 2.8650 (2.9635)	grad_norm 2.2834 (2.3357/1.0418)	mem 16099MB
[2025-01-18 08:06:53 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][220/312]	eta 0:00:44 lr 0.000779	time 0.4409 (0.4833)	model_time 0.4404 (0.4714)	loss 3.0801 (2.9706)	grad_norm 1.0465 (2.3171/1.0272)	mem 16099MB
[2025-01-18 08:06:57 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][230/312]	eta 0:00:39 lr 0.000778	time 0.4435 (0.4825)	model_time 0.4431 (0.4711)	loss 2.2430 (2.9633)	grad_norm 1.1224 (2.3065/1.0171)	mem 16099MB
[2025-01-18 08:07:02 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][240/312]	eta 0:00:34 lr 0.000778	time 0.4522 (0.4813)	model_time 0.4517 (0.4704)	loss 2.1909 (2.9586)	grad_norm 2.1371 (2.3003/1.0186)	mem 16099MB
[2025-01-18 08:07:07 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][250/312]	eta 0:00:29 lr 0.000777	time 0.5487 (0.4814)	model_time 0.5486 (0.4709)	loss 1.9517 (2.9643)	grad_norm 1.2029 (2.3293/1.0356)	mem 16099MB
[2025-01-18 08:07:11 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][260/312]	eta 0:00:25 lr 0.000777	time 0.4465 (0.4816)	model_time 0.4463 (0.4715)	loss 2.8518 (2.9565)	grad_norm 3.6582 (2.3743/1.0664)	mem 16099MB
[2025-01-18 08:07:16 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][270/312]	eta 0:00:20 lr 0.000776	time 0.4542 (0.4815)	model_time 0.4537 (0.4718)	loss 3.4281 (2.9527)	grad_norm 2.8361 (2.3823/1.0581)	mem 16099MB
[2025-01-18 08:07:21 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][280/312]	eta 0:00:15 lr 0.000776	time 0.5618 (0.4811)	model_time 0.5614 (0.4716)	loss 2.3733 (2.9539)	grad_norm 2.1277 (2.3772/1.0529)	mem 16099MB
[2025-01-18 08:07:26 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][290/312]	eta 0:00:10 lr 0.000775	time 0.4884 (0.4805)	model_time 0.4882 (0.4714)	loss 2.6617 (2.9504)	grad_norm 1.8161 (2.3712/1.0466)	mem 16099MB
[2025-01-18 08:07:30 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][300/312]	eta 0:00:05 lr 0.000775	time 0.4385 (0.4799)	model_time 0.4384 (0.4711)	loss 3.1335 (2.9572)	grad_norm 3.0423 (2.3670/1.0106)	mem 16099MB
[2025-01-18 08:07:35 internimage_t_1k_224] (main.py 510): INFO Train: [214/300][310/312]	eta 0:00:00 lr 0.000774	time 0.4425 (0.4790)	model_time 0.4424 (0.4704)	loss 2.7900 (2.9559)	grad_norm 2.0172 (2.3424/1.0022)	mem 16099MB
[2025-01-18 08:07:35 internimage_t_1k_224] (main.py 519): INFO EPOCH 214 training takes 0:02:29
[2025-01-18 08:07:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_214.pth saving......
[2025-01-18 08:07:36 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_214.pth saved !!!
[2025-01-18 08:07:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.423 (7.423)	Loss 0.7539 (0.7539)	Acc@1 84.106 (84.106)	Acc@5 97.095 (97.095)	Mem 16099MB
[2025-01-18 08:07:47 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.007)	Loss 1.0285 (0.8643)	Acc@1 77.319 (81.676)	Acc@5 94.507 (95.770)	Mem 16099MB
[2025-01-18 08:07:47 internimage_t_1k_224] (main.py 575): INFO [Epoch:214] * Acc@1 81.524 Acc@5 95.787
[2025-01-18 08:07:47 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.5%
[2025-01-18 08:07:47 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.65%
[2025-01-18 08:07:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.429 (8.429)	Loss 0.7711 (0.7711)	Acc@1 85.107 (85.107)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 08:08:00 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.128)	Loss 1.0249 (0.8842)	Acc@1 78.394 (82.642)	Acc@5 95.020 (96.269)	Mem 16099MB
[2025-01-18 08:08:00 internimage_t_1k_224] (main.py 575): INFO [Epoch:214] * Acc@1 82.520 Acc@5 96.285
[2025-01-18 08:08:00 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.5%
[2025-01-18 08:08:00 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:08:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:08:02 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.52%
[2025-01-18 08:08:04 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][0/312]	eta 0:13:04 lr 0.000774	time 2.5142 (2.5142)	model_time 0.4657 (0.4657)	loss 2.5488 (2.5488)	grad_norm 1.0443 (1.0443/0.0000)	mem 16099MB
[2025-01-18 08:08:09 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][10/312]	eta 0:03:21 lr 0.000773	time 0.5539 (0.6660)	model_time 0.5538 (0.4795)	loss 3.1817 (2.7389)	grad_norm 3.5623 (1.8812/0.8993)	mem 16099MB
[2025-01-18 08:08:13 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][20/312]	eta 0:02:45 lr 0.000773	time 0.4514 (0.5660)	model_time 0.4512 (0.4681)	loss 3.6979 (2.9170)	grad_norm 4.0497 (2.7401/1.3753)	mem 16099MB
[2025-01-18 08:08:18 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][30/312]	eta 0:02:31 lr 0.000772	time 0.4471 (0.5361)	model_time 0.4467 (0.4697)	loss 2.3659 (2.7952)	grad_norm 4.2465 (2.8173/1.2746)	mem 16099MB
[2025-01-18 08:08:23 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][40/312]	eta 0:02:21 lr 0.000772	time 0.4498 (0.5198)	model_time 0.4494 (0.4695)	loss 2.1881 (2.8144)	grad_norm 4.1505 (2.7363/1.2725)	mem 16099MB
[2025-01-18 08:08:28 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][50/312]	eta 0:02:14 lr 0.000771	time 0.4520 (0.5122)	model_time 0.4519 (0.4716)	loss 2.4244 (2.8639)	grad_norm 0.9418 (2.6208/1.2655)	mem 16099MB
[2025-01-18 08:08:32 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][60/312]	eta 0:02:07 lr 0.000771	time 0.4419 (0.5042)	model_time 0.4417 (0.4702)	loss 2.0916 (2.8721)	grad_norm 0.9234 (2.4395/1.2339)	mem 16099MB
[2025-01-18 08:08:37 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][70/312]	eta 0:02:00 lr 0.000770	time 0.4632 (0.4974)	model_time 0.4631 (0.4682)	loss 2.4527 (2.8947)	grad_norm 1.8993 (2.3488/1.1721)	mem 16099MB
[2025-01-18 08:08:42 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][80/312]	eta 0:01:54 lr 0.000770	time 0.4705 (0.4954)	model_time 0.4703 (0.4697)	loss 3.3618 (2.8818)	grad_norm 1.2963 (2.3587/1.1563)	mem 16099MB
[2025-01-18 08:08:46 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][90/312]	eta 0:01:49 lr 0.000769	time 0.5058 (0.4916)	model_time 0.5056 (0.4687)	loss 2.7081 (2.8959)	grad_norm 1.4409 (2.3398/1.1341)	mem 16099MB
[2025-01-18 08:08:51 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][100/312]	eta 0:01:43 lr 0.000769	time 0.4433 (0.4883)	model_time 0.4432 (0.4677)	loss 3.7810 (2.9165)	grad_norm 1.9538 (2.3748/1.1324)	mem 16099MB
[2025-01-18 08:08:56 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][110/312]	eta 0:01:38 lr 0.000768	time 0.4732 (0.4860)	model_time 0.4727 (0.4672)	loss 3.1641 (2.9357)	grad_norm 3.8051 (2.3665/1.1061)	mem 16099MB
[2025-01-18 08:09:00 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][120/312]	eta 0:01:32 lr 0.000768	time 0.4822 (0.4835)	model_time 0.4820 (0.4662)	loss 2.4563 (2.9094)	grad_norm 2.6035 (2.3262/1.0819)	mem 16099MB
[2025-01-18 08:09:05 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][130/312]	eta 0:01:27 lr 0.000767	time 0.4454 (0.4823)	model_time 0.4450 (0.4663)	loss 3.0828 (2.9138)	grad_norm 1.2441 (2.3189/1.0869)	mem 16099MB
[2025-01-18 08:09:09 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][140/312]	eta 0:01:22 lr 0.000767	time 0.4512 (0.4817)	model_time 0.4510 (0.4668)	loss 2.7423 (2.9183)	grad_norm 1.7392 (2.2984/1.0661)	mem 16099MB
[2025-01-18 08:09:14 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][150/312]	eta 0:01:17 lr 0.000766	time 0.4504 (0.4805)	model_time 0.4502 (0.4665)	loss 3.2189 (2.9180)	grad_norm 2.2466 (2.2639/1.0435)	mem 16099MB
[2025-01-18 08:09:19 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][160/312]	eta 0:01:12 lr 0.000766	time 0.4434 (0.4801)	model_time 0.4430 (0.4670)	loss 3.0495 (2.9147)	grad_norm 0.9430 (2.3167/1.1092)	mem 16099MB
[2025-01-18 08:09:23 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][170/312]	eta 0:01:08 lr 0.000765	time 0.4473 (0.4789)	model_time 0.4469 (0.4666)	loss 3.2369 (2.8955)	grad_norm 3.5919 (2.3272/1.0943)	mem 16099MB
[2025-01-18 08:09:28 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][180/312]	eta 0:01:03 lr 0.000765	time 0.4505 (0.4801)	model_time 0.4499 (0.4684)	loss 2.7882 (2.8897)	grad_norm 1.1892 (2.3323/1.0856)	mem 16099MB
[2025-01-18 08:09:33 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][190/312]	eta 0:00:58 lr 0.000764	time 0.4428 (0.4802)	model_time 0.4424 (0.4691)	loss 2.7512 (2.8913)	grad_norm 1.7897 (2.3302/1.0763)	mem 16099MB
[2025-01-18 08:09:38 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][200/312]	eta 0:00:53 lr 0.000764	time 0.4574 (0.4792)	model_time 0.4572 (0.4686)	loss 3.5867 (2.8981)	grad_norm 1.2609 (2.3208/1.0642)	mem 16099MB
[2025-01-18 08:09:43 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][210/312]	eta 0:00:48 lr 0.000763	time 0.4451 (0.4787)	model_time 0.4446 (0.4686)	loss 3.3487 (2.9092)	grad_norm 2.8124 (2.3394/1.0653)	mem 16099MB
[2025-01-18 08:09:47 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][220/312]	eta 0:00:43 lr 0.000763	time 0.4467 (0.4781)	model_time 0.4465 (0.4684)	loss 2.9180 (2.9075)	grad_norm 4.3860 (2.3657/1.0887)	mem 16099MB
[2025-01-18 08:09:52 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][230/312]	eta 0:00:39 lr 0.000762	time 0.4449 (0.4770)	model_time 0.4447 (0.4677)	loss 3.0870 (2.9063)	grad_norm 1.6310 (2.3440/1.0756)	mem 16099MB
[2025-01-18 08:09:56 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][240/312]	eta 0:00:34 lr 0.000762	time 0.4539 (0.4765)	model_time 0.4534 (0.4676)	loss 2.0451 (2.8935)	grad_norm 1.6666 (2.3412/1.0649)	mem 16099MB
[2025-01-18 08:10:01 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][250/312]	eta 0:00:29 lr 0.000761	time 0.5491 (0.4764)	model_time 0.5487 (0.4678)	loss 3.3164 (2.8949)	grad_norm 1.9026 (2.3083/1.0567)	mem 16099MB
[2025-01-18 08:10:06 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][260/312]	eta 0:00:24 lr 0.000761	time 0.4601 (0.4764)	model_time 0.4597 (0.4681)	loss 2.9130 (2.8960)	grad_norm 1.3599 (2.2875/1.0439)	mem 16099MB
[2025-01-18 08:10:11 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][270/312]	eta 0:00:19 lr 0.000760	time 0.4436 (0.4762)	model_time 0.4431 (0.4682)	loss 1.8741 (2.9014)	grad_norm 1.8676 (2.3165/1.0837)	mem 16099MB
[2025-01-18 08:10:15 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][280/312]	eta 0:00:15 lr 0.000760	time 0.4436 (0.4757)	model_time 0.4434 (0.4681)	loss 3.2640 (2.9095)	grad_norm 1.4147 (2.3410/1.1396)	mem 16099MB
[2025-01-18 08:10:20 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][290/312]	eta 0:00:10 lr 0.000759	time 0.4618 (0.4753)	model_time 0.4613 (0.4679)	loss 3.1846 (2.9131)	grad_norm 1.7096 (2.3173/1.1310)	mem 16099MB
[2025-01-18 08:10:24 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][300/312]	eta 0:00:05 lr 0.000759	time 0.4384 (0.4745)	model_time 0.4383 (0.4673)	loss 2.1374 (2.9045)	grad_norm 1.8813 (2.3306/1.1347)	mem 16099MB
[2025-01-18 08:10:29 internimage_t_1k_224] (main.py 510): INFO Train: [215/300][310/312]	eta 0:00:00 lr 0.000758	time 0.4392 (0.4737)	model_time 0.4390 (0.4667)	loss 2.9647 (2.9099)	grad_norm 1.9228 (2.3523/1.1292)	mem 16099MB
[2025-01-18 08:10:29 internimage_t_1k_224] (main.py 519): INFO EPOCH 215 training takes 0:02:27
[2025-01-18 08:10:29 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_215.pth saving......
[2025-01-18 08:10:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_215.pth saved !!!
[2025-01-18 08:10:38 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.464 (7.464)	Loss 0.7579 (0.7579)	Acc@1 84.131 (84.131)	Acc@5 96.899 (96.899)	Mem 16099MB
[2025-01-18 08:10:41 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.992)	Loss 1.0127 (0.8646)	Acc@1 77.368 (81.570)	Acc@5 94.727 (95.890)	Mem 16099MB
[2025-01-18 08:10:41 internimage_t_1k_224] (main.py 575): INFO [Epoch:215] * Acc@1 81.478 Acc@5 95.901
[2025-01-18 08:10:41 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.5%
[2025-01-18 08:10:41 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.65%
[2025-01-18 08:10:50 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.214 (8.214)	Loss 0.7701 (0.7701)	Acc@1 85.156 (85.156)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 08:10:53 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.086)	Loss 1.0233 (0.8829)	Acc@1 78.491 (82.699)	Acc@5 95.093 (96.294)	Mem 16099MB
[2025-01-18 08:10:54 internimage_t_1k_224] (main.py 575): INFO [Epoch:215] * Acc@1 82.576 Acc@5 96.307
[2025-01-18 08:10:54 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.6%
[2025-01-18 08:10:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:10:55 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:10:55 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.58%
[2025-01-18 08:10:57 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][0/312]	eta 0:10:35 lr 0.000758	time 2.0377 (2.0377)	model_time 0.5097 (0.5097)	loss 3.4962 (3.4962)	grad_norm 1.3917 (1.3917/0.0000)	mem 16099MB
[2025-01-18 08:11:02 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][10/312]	eta 0:03:14 lr 0.000757	time 0.4430 (0.6438)	model_time 0.4428 (0.5046)	loss 3.2894 (2.8370)	grad_norm 1.6341 (1.8464/0.3387)	mem 16099MB
[2025-01-18 08:11:07 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][20/312]	eta 0:02:41 lr 0.000757	time 0.4676 (0.5546)	model_time 0.4672 (0.4815)	loss 2.6891 (2.9474)	grad_norm 2.6881 (1.7438/0.4681)	mem 16099MB
[2025-01-18 08:11:12 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][30/312]	eta 0:02:28 lr 0.000756	time 0.4563 (0.5258)	model_time 0.4561 (0.4762)	loss 2.4323 (2.9044)	grad_norm 3.5875 (1.9359/0.7105)	mem 16099MB
[2025-01-18 08:11:16 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][40/312]	eta 0:02:18 lr 0.000756	time 0.4482 (0.5087)	model_time 0.4480 (0.4711)	loss 2.9045 (2.8999)	grad_norm 1.3157 (2.0006/0.7829)	mem 16099MB
[2025-01-18 08:11:21 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][50/312]	eta 0:02:11 lr 0.000755	time 0.4493 (0.5028)	model_time 0.4492 (0.4724)	loss 3.2986 (2.9307)	grad_norm 3.4829 (2.3142/1.1831)	mem 16099MB
[2025-01-18 08:11:25 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][60/312]	eta 0:02:04 lr 0.000755	time 0.4556 (0.4959)	model_time 0.4554 (0.4705)	loss 2.2582 (2.8950)	grad_norm 3.0449 (2.4681/1.1880)	mem 16099MB
[2025-01-18 08:11:30 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][70/312]	eta 0:01:58 lr 0.000754	time 0.4995 (0.4905)	model_time 0.4991 (0.4686)	loss 2.1343 (2.8856)	grad_norm 2.9505 (2.4344/1.1579)	mem 16099MB
[2025-01-18 08:11:35 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][80/312]	eta 0:01:53 lr 0.000754	time 0.4505 (0.4878)	model_time 0.4503 (0.4685)	loss 3.4401 (2.8927)	grad_norm 3.3277 (2.4104/1.1538)	mem 16099MB
[2025-01-18 08:11:39 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][90/312]	eta 0:01:47 lr 0.000753	time 0.5665 (0.4852)	model_time 0.5661 (0.4681)	loss 3.6314 (2.8737)	grad_norm 5.0977 (2.5014/1.1700)	mem 16099MB
[2025-01-18 08:11:44 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][100/312]	eta 0:01:42 lr 0.000753	time 0.4497 (0.4826)	model_time 0.4494 (0.4671)	loss 3.0635 (2.8592)	grad_norm 1.8734 (2.4865/1.1463)	mem 16099MB
[2025-01-18 08:11:49 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][110/312]	eta 0:01:37 lr 0.000752	time 0.4512 (0.4805)	model_time 0.4507 (0.4664)	loss 3.1898 (2.8819)	grad_norm 1.9176 (2.5043/1.1245)	mem 16099MB
[2025-01-18 08:11:53 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][120/312]	eta 0:01:32 lr 0.000752	time 0.4654 (0.4808)	model_time 0.4652 (0.4678)	loss 3.2359 (2.8708)	grad_norm 3.3629 (2.4964/1.0983)	mem 16099MB
[2025-01-18 08:11:58 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][130/312]	eta 0:01:27 lr 0.000751	time 0.4484 (0.4787)	model_time 0.4480 (0.4666)	loss 2.8290 (2.8836)	grad_norm 1.0463 (2.4995/1.0965)	mem 16099MB
[2025-01-18 08:12:03 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][140/312]	eta 0:01:22 lr 0.000751	time 0.5412 (0.4786)	model_time 0.5410 (0.4674)	loss 2.1607 (2.8631)	grad_norm 1.7799 (2.4728/1.0782)	mem 16099MB
[2025-01-18 08:12:07 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][150/312]	eta 0:01:17 lr 0.000750	time 0.4567 (0.4786)	model_time 0.4562 (0.4681)	loss 2.6022 (2.8679)	grad_norm 4.5451 (2.4720/1.0748)	mem 16099MB
[2025-01-18 08:12:12 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][160/312]	eta 0:01:12 lr 0.000750	time 0.4556 (0.4778)	model_time 0.4554 (0.4679)	loss 2.0984 (2.8573)	grad_norm 1.7925 (2.4789/1.0659)	mem 16099MB
[2025-01-18 08:12:17 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][170/312]	eta 0:01:07 lr 0.000749	time 0.4482 (0.4768)	model_time 0.4480 (0.4674)	loss 2.9811 (2.8644)	grad_norm 3.4729 (2.4665/1.0566)	mem 16099MB
[2025-01-18 08:12:22 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][180/312]	eta 0:01:02 lr 0.000749	time 0.4562 (0.4772)	model_time 0.4560 (0.4684)	loss 2.6213 (2.8770)	grad_norm 1.9279 (2.4567/1.0344)	mem 16099MB
[2025-01-18 08:12:26 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][190/312]	eta 0:00:58 lr 0.000748	time 0.4543 (0.4765)	model_time 0.4539 (0.4681)	loss 2.9836 (2.8802)	grad_norm 1.5619 (2.4508/1.0280)	mem 16099MB
[2025-01-18 08:12:31 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][200/312]	eta 0:00:53 lr 0.000748	time 0.5349 (0.4759)	model_time 0.5348 (0.4679)	loss 2.1940 (2.8867)	grad_norm 2.8441 (2.4283/1.0138)	mem 16099MB
[2025-01-18 08:12:35 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][210/312]	eta 0:00:48 lr 0.000747	time 0.4475 (0.4750)	model_time 0.4470 (0.4674)	loss 3.7222 (2.8850)	grad_norm 1.3229 (2.4090/1.0049)	mem 16099MB
[2025-01-18 08:12:40 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][220/312]	eta 0:00:43 lr 0.000747	time 0.4441 (0.4752)	model_time 0.4436 (0.4678)	loss 2.2916 (2.8901)	grad_norm 1.6783 (2.3910/0.9924)	mem 16099MB
[2025-01-18 08:12:45 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][230/312]	eta 0:00:38 lr 0.000746	time 0.4434 (0.4751)	model_time 0.4430 (0.4681)	loss 3.0201 (2.8938)	grad_norm 3.4982 (2.3984/0.9883)	mem 16099MB
[2025-01-18 08:12:50 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][240/312]	eta 0:00:34 lr 0.000746	time 0.4541 (0.4753)	model_time 0.4539 (0.4686)	loss 3.3580 (2.8961)	grad_norm 1.4698 (2.3886/0.9878)	mem 16099MB
[2025-01-18 08:12:54 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][250/312]	eta 0:00:29 lr 0.000745	time 0.5544 (0.4752)	model_time 0.5540 (0.4687)	loss 3.4021 (2.9036)	grad_norm 0.9370 (2.3703/0.9853)	mem 16099MB
[2025-01-18 08:12:59 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][260/312]	eta 0:00:24 lr 0.000745	time 0.4533 (0.4751)	model_time 0.4528 (0.4689)	loss 3.3084 (2.8986)	grad_norm 1.9209 (2.3583/0.9769)	mem 16099MB
[2025-01-18 08:13:04 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][270/312]	eta 0:00:19 lr 0.000744	time 0.4460 (0.4743)	model_time 0.4456 (0.4683)	loss 1.9285 (2.9029)	grad_norm 1.9055 (2.3743/0.9727)	mem 16099MB
[2025-01-18 08:13:08 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][280/312]	eta 0:00:15 lr 0.000744	time 0.4796 (0.4742)	model_time 0.4794 (0.4684)	loss 3.6891 (2.9148)	grad_norm 2.3254 (2.3861/0.9780)	mem 16099MB
[2025-01-18 08:13:13 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][290/312]	eta 0:00:10 lr 0.000743	time 0.4508 (0.4738)	model_time 0.4506 (0.4682)	loss 2.7616 (2.9174)	grad_norm 1.5378 (2.3812/0.9746)	mem 16099MB
[2025-01-18 08:13:18 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][300/312]	eta 0:00:05 lr 0.000743	time 0.4397 (0.4731)	model_time 0.4396 (0.4676)	loss 3.0656 (2.9130)	grad_norm 2.3504 (2.3819/0.9620)	mem 16099MB
[2025-01-18 08:13:22 internimage_t_1k_224] (main.py 510): INFO Train: [216/300][310/312]	eta 0:00:00 lr 0.000742	time 0.4389 (0.4729)	model_time 0.4388 (0.4676)	loss 3.2262 (2.9189)	grad_norm 1.7235 (2.3885/0.9656)	mem 16099MB
[2025-01-18 08:13:23 internimage_t_1k_224] (main.py 519): INFO EPOCH 216 training takes 0:02:27
[2025-01-18 08:13:23 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_216.pth saving......
[2025-01-18 08:13:24 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_216.pth saved !!!
[2025-01-18 08:13:31 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.269 (7.269)	Loss 0.7584 (0.7584)	Acc@1 84.302 (84.302)	Acc@5 97.119 (97.119)	Mem 16099MB
[2025-01-18 08:13:35 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.980)	Loss 1.0180 (0.8637)	Acc@1 77.930 (81.885)	Acc@5 94.507 (95.958)	Mem 16099MB
[2025-01-18 08:13:35 internimage_t_1k_224] (main.py 575): INFO [Epoch:216] * Acc@1 81.756 Acc@5 95.977
[2025-01-18 08:13:35 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.8%
[2025-01-18 08:13:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 08:13:36 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 08:13:36 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.76%
[2025-01-18 08:13:43 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.399 (7.399)	Loss 0.7692 (0.7692)	Acc@1 85.181 (85.181)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 08:13:47 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.986)	Loss 1.0218 (0.8818)	Acc@1 78.540 (82.708)	Acc@5 95.068 (96.291)	Mem 16099MB
[2025-01-18 08:13:47 internimage_t_1k_224] (main.py 575): INFO [Epoch:216] * Acc@1 82.594 Acc@5 96.305
[2025-01-18 08:13:47 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.6%
[2025-01-18 08:13:47 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:13:49 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:13:49 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.59%
[2025-01-18 08:13:51 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][0/312]	eta 0:14:04 lr 0.000742	time 2.7060 (2.7060)	model_time 0.4992 (0.4992)	loss 3.2446 (3.2446)	grad_norm 3.0791 (3.0791/0.0000)	mem 16099MB
[2025-01-18 08:13:56 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][10/312]	eta 0:03:21 lr 0.000741	time 0.4535 (0.6661)	model_time 0.4533 (0.4652)	loss 3.6907 (3.0393)	grad_norm 4.1594 (2.9005/0.5673)	mem 16099MB
[2025-01-18 08:14:00 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][20/312]	eta 0:02:45 lr 0.000741	time 0.4452 (0.5651)	model_time 0.4451 (0.4597)	loss 2.1338 (2.8509)	grad_norm 1.1700 (2.9966/0.8168)	mem 16099MB
[2025-01-18 08:14:05 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][30/312]	eta 0:02:29 lr 0.000740	time 0.4652 (0.5304)	model_time 0.4650 (0.4588)	loss 3.6893 (2.9230)	grad_norm 2.7127 (2.7909/0.8569)	mem 16099MB
[2025-01-18 08:14:10 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][40/312]	eta 0:02:19 lr 0.000740	time 0.4521 (0.5120)	model_time 0.4520 (0.4578)	loss 3.7106 (2.8866)	grad_norm 3.3503 (2.7886/0.9096)	mem 16099MB
[2025-01-18 08:14:14 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][50/312]	eta 0:02:12 lr 0.000739	time 0.4496 (0.5049)	model_time 0.4494 (0.4613)	loss 3.0035 (2.9106)	grad_norm 1.3669 (2.7738/0.8737)	mem 16099MB
[2025-01-18 08:14:19 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][60/312]	eta 0:02:05 lr 0.000739	time 0.4460 (0.4994)	model_time 0.4456 (0.4629)	loss 3.1064 (2.9162)	grad_norm 2.1813 (2.6215/0.9055)	mem 16099MB
[2025-01-18 08:14:24 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][70/312]	eta 0:01:59 lr 0.000738	time 0.5525 (0.4948)	model_time 0.5524 (0.4634)	loss 3.3506 (2.8872)	grad_norm 1.3850 (2.5046/0.9005)	mem 16099MB
[2025-01-18 08:14:29 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][80/312]	eta 0:01:54 lr 0.000738	time 0.4638 (0.4932)	model_time 0.4636 (0.4656)	loss 2.1858 (2.8786)	grad_norm 2.7778 (2.4683/0.8881)	mem 16099MB
[2025-01-18 08:14:33 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][90/312]	eta 0:01:48 lr 0.000737	time 0.4530 (0.4889)	model_time 0.4525 (0.4643)	loss 2.2197 (2.8803)	grad_norm 1.0523 (2.4049/0.8773)	mem 16099MB
[2025-01-18 08:14:38 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][100/312]	eta 0:01:43 lr 0.000737	time 0.4495 (0.4862)	model_time 0.4491 (0.4640)	loss 3.2573 (2.9133)	grad_norm 5.9761 (2.5009/1.0349)	mem 16099MB
[2025-01-18 08:14:42 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][110/312]	eta 0:01:37 lr 0.000736	time 0.5829 (0.4849)	model_time 0.5828 (0.4646)	loss 3.7016 (2.9206)	grad_norm 2.1241 (2.5163/1.0426)	mem 16099MB
[2025-01-18 08:14:47 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][120/312]	eta 0:01:32 lr 0.000736	time 0.4521 (0.4834)	model_time 0.4517 (0.4648)	loss 3.0108 (2.9204)	grad_norm 2.2856 (2.5034/1.0451)	mem 16099MB
[2025-01-18 08:14:52 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][130/312]	eta 0:01:27 lr 0.000735	time 0.4493 (0.4831)	model_time 0.4489 (0.4659)	loss 3.4056 (2.9152)	grad_norm 3.1956 (2.5417/1.0501)	mem 16099MB
[2025-01-18 08:14:57 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][140/312]	eta 0:01:23 lr 0.000735	time 0.4604 (0.4846)	model_time 0.4600 (0.4686)	loss 2.4347 (2.9104)	grad_norm 3.7594 (2.5369/1.0463)	mem 16099MB
[2025-01-18 08:15:01 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][150/312]	eta 0:01:18 lr 0.000734	time 0.4541 (0.4827)	model_time 0.4537 (0.4678)	loss 2.5704 (2.8940)	grad_norm 1.6703 (2.5218/1.0346)	mem 16099MB
[2025-01-18 08:15:06 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][160/312]	eta 0:01:13 lr 0.000734	time 0.4523 (0.4821)	model_time 0.4518 (0.4680)	loss 2.0217 (2.8883)	grad_norm 3.1605 (2.5233/1.0286)	mem 16099MB
[2025-01-18 08:15:11 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][170/312]	eta 0:01:08 lr 0.000733	time 0.4573 (0.4818)	model_time 0.4569 (0.4685)	loss 3.2136 (2.8898)	grad_norm 1.7813 (2.4847/1.0207)	mem 16099MB
[2025-01-18 08:15:16 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][180/312]	eta 0:01:03 lr 0.000733	time 0.4659 (0.4806)	model_time 0.4654 (0.4680)	loss 2.6772 (2.8977)	grad_norm 2.6477 (2.4502/1.0106)	mem 16099MB
[2025-01-18 08:15:20 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][190/312]	eta 0:00:58 lr 0.000732	time 0.4661 (0.4794)	model_time 0.4656 (0.4674)	loss 1.8187 (2.9072)	grad_norm 2.9901 (2.4151/1.0004)	mem 16099MB
[2025-01-18 08:15:25 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][200/312]	eta 0:00:53 lr 0.000732	time 0.4550 (0.4782)	model_time 0.4548 (0.4668)	loss 3.0836 (2.9136)	grad_norm 1.1201 (2.4057/0.9879)	mem 16099MB
[2025-01-18 08:15:29 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][210/312]	eta 0:00:48 lr 0.000731	time 0.4517 (0.4774)	model_time 0.4512 (0.4665)	loss 3.1215 (2.9117)	grad_norm 2.9200 (2.4082/0.9700)	mem 16099MB
[2025-01-18 08:15:34 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][220/312]	eta 0:00:43 lr 0.000731	time 0.4506 (0.4764)	model_time 0.4505 (0.4660)	loss 3.3691 (2.9070)	grad_norm 4.5039 (2.4953/1.0941)	mem 16099MB
[2025-01-18 08:15:39 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][230/312]	eta 0:00:39 lr 0.000730	time 0.4863 (0.4759)	model_time 0.4858 (0.4660)	loss 3.3495 (2.8956)	grad_norm 2.1737 (2.5049/1.0809)	mem 16099MB
[2025-01-18 08:15:43 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][240/312]	eta 0:00:34 lr 0.000730	time 0.4692 (0.4762)	model_time 0.4690 (0.4667)	loss 2.8507 (2.8940)	grad_norm 2.8182 (2.5052/1.0722)	mem 16099MB
[2025-01-18 08:15:48 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][250/312]	eta 0:00:29 lr 0.000729	time 0.4653 (0.4760)	model_time 0.4648 (0.4668)	loss 3.1233 (2.8964)	grad_norm 1.4648 (2.4938/1.0598)	mem 16099MB
[2025-01-18 08:15:53 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][260/312]	eta 0:00:24 lr 0.000729	time 0.4467 (0.4751)	model_time 0.4462 (0.4663)	loss 2.9664 (2.9003)	grad_norm 1.5509 (2.4914/1.0483)	mem 16099MB
[2025-01-18 08:15:57 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][270/312]	eta 0:00:19 lr 0.000728	time 0.4858 (0.4745)	model_time 0.4853 (0.4660)	loss 1.7940 (2.8982)	grad_norm 2.5036 (2.4901/1.0498)	mem 16099MB
[2025-01-18 08:16:02 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][280/312]	eta 0:00:15 lr 0.000728	time 0.4499 (0.4738)	model_time 0.4495 (0.4655)	loss 3.2902 (2.9041)	grad_norm 3.1194 (2.4714/1.0454)	mem 16099MB
[2025-01-18 08:16:07 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][290/312]	eta 0:00:10 lr 0.000727	time 0.5435 (0.4741)	model_time 0.5430 (0.4661)	loss 3.0760 (2.8978)	grad_norm 1.3467 (2.4841/1.0534)	mem 16099MB
[2025-01-18 08:16:11 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][300/312]	eta 0:00:05 lr 0.000727	time 0.4457 (0.4739)	model_time 0.4456 (0.4662)	loss 3.0668 (2.9002)	grad_norm 2.4966 (2.5001/1.0761)	mem 16099MB
[2025-01-18 08:16:16 internimage_t_1k_224] (main.py 510): INFO Train: [217/300][310/312]	eta 0:00:00 lr 0.000726	time 0.4392 (0.4736)	model_time 0.4391 (0.4661)	loss 3.3197 (2.8998)	grad_norm 2.1629 (2.5161/1.1080)	mem 16099MB
[2025-01-18 08:16:16 internimage_t_1k_224] (main.py 519): INFO EPOCH 217 training takes 0:02:27
[2025-01-18 08:16:16 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_217.pth saving......
[2025-01-18 08:16:17 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_217.pth saved !!!
[2025-01-18 08:16:25 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.335 (7.335)	Loss 0.7646 (0.7646)	Acc@1 84.351 (84.351)	Acc@5 97.021 (97.021)	Mem 16099MB
[2025-01-18 08:16:28 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.988)	Loss 1.0432 (0.8768)	Acc@1 77.344 (81.905)	Acc@5 94.556 (95.832)	Mem 16099MB
[2025-01-18 08:16:29 internimage_t_1k_224] (main.py 575): INFO [Epoch:217] * Acc@1 81.750 Acc@5 95.827
[2025-01-18 08:16:29 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.7%
[2025-01-18 08:16:29 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.76%
[2025-01-18 08:16:37 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.115 (8.115)	Loss 0.7679 (0.7679)	Acc@1 85.278 (85.278)	Acc@5 97.583 (97.583)	Mem 16099MB
[2025-01-18 08:16:41 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.092)	Loss 1.0198 (0.8801)	Acc@1 78.540 (82.735)	Acc@5 95.068 (96.309)	Mem 16099MB
[2025-01-18 08:16:41 internimage_t_1k_224] (main.py 575): INFO [Epoch:217] * Acc@1 82.614 Acc@5 96.325
[2025-01-18 08:16:41 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.6%
[2025-01-18 08:16:41 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:16:42 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:16:42 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.61%
[2025-01-18 08:16:45 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][0/312]	eta 0:13:23 lr 0.000726	time 2.5768 (2.5768)	model_time 0.5283 (0.5283)	loss 2.5317 (2.5317)	grad_norm 1.1031 (1.1031/0.0000)	mem 16099MB
[2025-01-18 08:16:49 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][10/312]	eta 0:03:20 lr 0.000726	time 0.4567 (0.6638)	model_time 0.4561 (0.4773)	loss 3.0615 (2.8805)	grad_norm 1.1924 (1.6425/0.4101)	mem 16099MB
[2025-01-18 08:16:54 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][20/312]	eta 0:02:44 lr 0.000725	time 0.4459 (0.5644)	model_time 0.4457 (0.4666)	loss 2.9012 (2.9774)	grad_norm 1.6852 (1.9174/0.8696)	mem 16099MB
[2025-01-18 08:16:59 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][30/312]	eta 0:02:30 lr 0.000725	time 0.4452 (0.5350)	model_time 0.4447 (0.4686)	loss 2.1203 (2.8772)	grad_norm 4.2650 (2.4587/1.1759)	mem 16099MB
[2025-01-18 08:17:04 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][40/312]	eta 0:02:23 lr 0.000724	time 0.5517 (0.5259)	model_time 0.5513 (0.4756)	loss 2.5211 (2.8569)	grad_norm 4.8140 (2.9623/1.4790)	mem 16099MB
[2025-01-18 08:17:08 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][50/312]	eta 0:02:15 lr 0.000724	time 0.4536 (0.5158)	model_time 0.4535 (0.4753)	loss 2.1655 (2.8522)	grad_norm 2.5462 (2.8992/1.4538)	mem 16099MB
[2025-01-18 08:17:13 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][60/312]	eta 0:02:07 lr 0.000723	time 0.4629 (0.5079)	model_time 0.4627 (0.4740)	loss 2.2761 (2.8580)	grad_norm 1.8054 (2.8199/1.4066)	mem 16099MB
[2025-01-18 08:17:18 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][70/312]	eta 0:02:01 lr 0.000723	time 0.4537 (0.5004)	model_time 0.4533 (0.4712)	loss 3.4345 (2.8708)	grad_norm 1.6440 (2.7066/1.3486)	mem 16099MB
[2025-01-18 08:17:22 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][80/312]	eta 0:01:54 lr 0.000722	time 0.4690 (0.4953)	model_time 0.4686 (0.4697)	loss 2.8617 (2.8798)	grad_norm 1.4539 (2.6002/1.3260)	mem 16099MB
[2025-01-18 08:17:27 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][90/312]	eta 0:01:48 lr 0.000722	time 0.4488 (0.4908)	model_time 0.4486 (0.4679)	loss 2.3880 (2.9035)	grad_norm 2.3306 (2.5696/1.2661)	mem 16099MB
[2025-01-18 08:17:31 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][100/312]	eta 0:01:43 lr 0.000721	time 0.4484 (0.4876)	model_time 0.4480 (0.4669)	loss 2.2928 (2.9160)	grad_norm 3.3818 (2.5728/1.2294)	mem 16099MB
[2025-01-18 08:17:36 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][110/312]	eta 0:01:38 lr 0.000721	time 0.4455 (0.4870)	model_time 0.4454 (0.4682)	loss 3.2783 (2.9042)	grad_norm 3.6989 (2.5787/1.2290)	mem 16099MB
[2025-01-18 08:17:41 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][120/312]	eta 0:01:33 lr 0.000720	time 0.4512 (0.4863)	model_time 0.4508 (0.4690)	loss 2.8579 (2.9303)	grad_norm 2.2195 (2.5840/1.2164)	mem 16099MB
[2025-01-18 08:17:46 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][130/312]	eta 0:01:28 lr 0.000720	time 0.4613 (0.4843)	model_time 0.4608 (0.4682)	loss 3.0827 (2.9183)	grad_norm 1.3497 (2.5077/1.2042)	mem 16099MB
[2025-01-18 08:17:50 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][140/312]	eta 0:01:23 lr 0.000719	time 0.4670 (0.4831)	model_time 0.4668 (0.4682)	loss 2.1066 (2.9121)	grad_norm 1.3285 (2.4571/1.1817)	mem 16099MB
[2025-01-18 08:17:55 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][150/312]	eta 0:01:17 lr 0.000719	time 0.4478 (0.4813)	model_time 0.4474 (0.4674)	loss 3.2290 (2.9060)	grad_norm 1.6494 (2.4236/1.1555)	mem 16099MB
[2025-01-18 08:18:00 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][160/312]	eta 0:01:13 lr 0.000718	time 0.4505 (0.4811)	model_time 0.4504 (0.4680)	loss 3.4252 (2.9278)	grad_norm 2.8728 (2.4309/1.1299)	mem 16099MB
[2025-01-18 08:18:04 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][170/312]	eta 0:01:08 lr 0.000718	time 0.4519 (0.4799)	model_time 0.4518 (0.4675)	loss 2.6929 (2.9358)	grad_norm 2.2577 (2.4371/1.1222)	mem 16099MB
[2025-01-18 08:18:09 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][180/312]	eta 0:01:03 lr 0.000717	time 0.4610 (0.4791)	model_time 0.4608 (0.4674)	loss 3.7561 (2.9442)	grad_norm 0.9558 (2.4191/1.1157)	mem 16099MB
[2025-01-18 08:18:13 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][190/312]	eta 0:00:58 lr 0.000717	time 0.4596 (0.4784)	model_time 0.4591 (0.4673)	loss 3.0538 (2.9394)	grad_norm 1.7893 (2.4061/1.0950)	mem 16099MB
[2025-01-18 08:18:18 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][200/312]	eta 0:00:53 lr 0.000716	time 0.4580 (0.4785)	model_time 0.4575 (0.4679)	loss 3.0343 (2.9425)	grad_norm 1.4484 (2.3700/1.0813)	mem 16099MB
[2025-01-18 08:18:23 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][210/312]	eta 0:00:48 lr 0.000716	time 0.4576 (0.4774)	model_time 0.4574 (0.4673)	loss 3.2160 (2.9469)	grad_norm 3.0017 (2.3676/1.0740)	mem 16099MB
[2025-01-18 08:18:27 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][220/312]	eta 0:00:43 lr 0.000715	time 0.4408 (0.4768)	model_time 0.4404 (0.4671)	loss 2.3254 (2.9527)	grad_norm 1.2078 (2.3588/1.0630)	mem 16099MB
[2025-01-18 08:18:32 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][230/312]	eta 0:00:39 lr 0.000715	time 0.4781 (0.4774)	model_time 0.4777 (0.4682)	loss 2.5702 (2.9528)	grad_norm 2.5986 (2.3862/1.0752)	mem 16099MB
[2025-01-18 08:18:37 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][240/312]	eta 0:00:34 lr 0.000714	time 0.4611 (0.4767)	model_time 0.4609 (0.4678)	loss 2.8378 (2.9594)	grad_norm 1.0768 (2.4062/1.0955)	mem 16099MB
[2025-01-18 08:18:42 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][250/312]	eta 0:00:29 lr 0.000714	time 0.4853 (0.4761)	model_time 0.4848 (0.4676)	loss 2.7348 (2.9625)	grad_norm 2.0726 (2.4363/1.1063)	mem 16099MB
[2025-01-18 08:18:46 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][260/312]	eta 0:00:24 lr 0.000713	time 0.4487 (0.4755)	model_time 0.4482 (0.4673)	loss 3.1001 (2.9652)	grad_norm 2.6940 (2.4799/1.1336)	mem 16099MB
[2025-01-18 08:18:51 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][270/312]	eta 0:00:19 lr 0.000713	time 0.4505 (0.4753)	model_time 0.4503 (0.4674)	loss 3.3491 (2.9573)	grad_norm 1.2606 (2.4673/1.1225)	mem 16099MB
[2025-01-18 08:18:56 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][280/312]	eta 0:00:15 lr 0.000712	time 0.4543 (0.4760)	model_time 0.4539 (0.4683)	loss 3.1524 (2.9528)	grad_norm 4.2434 (2.4578/1.1172)	mem 16099MB
[2025-01-18 08:19:01 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][290/312]	eta 0:00:10 lr 0.000712	time 0.4530 (0.4759)	model_time 0.4528 (0.4685)	loss 2.4155 (2.9571)	grad_norm 3.0611 (2.4524/1.1247)	mem 16099MB
[2025-01-18 08:19:05 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][300/312]	eta 0:00:05 lr 0.000711	time 0.4393 (0.4754)	model_time 0.4392 (0.4682)	loss 3.2656 (2.9620)	grad_norm 3.3181 (2.4670/1.1129)	mem 16099MB
[2025-01-18 08:19:10 internimage_t_1k_224] (main.py 510): INFO Train: [218/300][310/312]	eta 0:00:00 lr 0.000711	time 0.4388 (0.4745)	model_time 0.4387 (0.4676)	loss 3.5620 (2.9631)	grad_norm 1.2246 (2.5000/1.1171)	mem 16099MB
[2025-01-18 08:19:10 internimage_t_1k_224] (main.py 519): INFO EPOCH 218 training takes 0:02:28
[2025-01-18 08:19:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_218.pth saving......
[2025-01-18 08:19:11 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_218.pth saved !!!
[2025-01-18 08:19:19 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.878 (7.878)	Loss 0.7677 (0.7677)	Acc@1 84.082 (84.082)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 08:19:23 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.038)	Loss 1.0378 (0.8781)	Acc@1 77.612 (81.922)	Acc@5 94.287 (95.865)	Mem 16099MB
[2025-01-18 08:19:23 internimage_t_1k_224] (main.py 575): INFO [Epoch:218] * Acc@1 81.752 Acc@5 95.875
[2025-01-18 08:19:23 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.8%
[2025-01-18 08:19:23 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.76%
[2025-01-18 08:19:31 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.090 (8.090)	Loss 0.7667 (0.7667)	Acc@1 85.278 (85.278)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 08:19:35 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.073)	Loss 1.0182 (0.8788)	Acc@1 78.516 (82.761)	Acc@5 95.093 (96.322)	Mem 16099MB
[2025-01-18 08:19:35 internimage_t_1k_224] (main.py 575): INFO [Epoch:218] * Acc@1 82.642 Acc@5 96.337
[2025-01-18 08:19:35 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.6%
[2025-01-18 08:19:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:19:36 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:19:36 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.64%
[2025-01-18 08:19:39 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][0/312]	eta 0:12:41 lr 0.000711	time 2.4409 (2.4409)	model_time 0.4716 (0.4716)	loss 3.2238 (3.2238)	grad_norm 2.2745 (2.2745/0.0000)	mem 16099MB
[2025-01-18 08:19:43 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][10/312]	eta 0:03:14 lr 0.000710	time 0.4636 (0.6433)	model_time 0.4632 (0.4639)	loss 2.9994 (3.0100)	grad_norm 1.8111 (1.9578/0.6078)	mem 16099MB
[2025-01-18 08:19:48 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][20/312]	eta 0:02:41 lr 0.000710	time 0.4496 (0.5548)	model_time 0.4493 (0.4607)	loss 2.7682 (3.0434)	grad_norm 2.0800 (1.9828/0.7220)	mem 16099MB
[2025-01-18 08:19:53 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][30/312]	eta 0:02:28 lr 0.000709	time 0.4477 (0.5281)	model_time 0.4475 (0.4643)	loss 2.5188 (3.0063)	grad_norm 2.3607 (2.0983/0.8683)	mem 16099MB
[2025-01-18 08:19:57 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][40/312]	eta 0:02:19 lr 0.000709	time 0.4595 (0.5129)	model_time 0.4594 (0.4645)	loss 3.0555 (3.0076)	grad_norm 2.3551 (2.2132/0.8711)	mem 16099MB
[2025-01-18 08:20:02 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][50/312]	eta 0:02:11 lr 0.000708	time 0.4697 (0.5022)	model_time 0.4695 (0.4632)	loss 2.6168 (3.0341)	grad_norm 2.0081 (2.2533/0.9255)	mem 16099MB
[2025-01-18 08:20:06 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][60/312]	eta 0:02:04 lr 0.000708	time 0.4488 (0.4957)	model_time 0.4484 (0.4631)	loss 2.0741 (3.0133)	grad_norm 1.0646 (2.1772/0.8912)	mem 16099MB
[2025-01-18 08:20:11 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][70/312]	eta 0:01:58 lr 0.000707	time 0.4456 (0.4912)	model_time 0.4454 (0.4631)	loss 2.8916 (3.0032)	grad_norm 0.8963 (2.1082/0.8865)	mem 16099MB
[2025-01-18 08:20:16 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][80/312]	eta 0:01:53 lr 0.000707	time 0.5815 (0.4881)	model_time 0.5811 (0.4634)	loss 2.7285 (3.0083)	grad_norm 5.3301 (2.2724/1.1918)	mem 16099MB
[2025-01-18 08:20:20 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][90/312]	eta 0:01:47 lr 0.000706	time 0.4654 (0.4859)	model_time 0.4652 (0.4639)	loss 2.7633 (2.9931)	grad_norm 1.5685 (2.2423/1.1653)	mem 16099MB
[2025-01-18 08:20:25 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][100/312]	eta 0:01:42 lr 0.000706	time 0.4478 (0.4835)	model_time 0.4477 (0.4637)	loss 3.1937 (2.9897)	grad_norm 2.0520 (2.2539/1.1224)	mem 16099MB
[2025-01-18 08:20:30 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][110/312]	eta 0:01:37 lr 0.000705	time 0.5702 (0.4832)	model_time 0.5697 (0.4651)	loss 3.1169 (3.0144)	grad_norm 0.9999 (2.2733/1.1353)	mem 16099MB
[2025-01-18 08:20:34 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][120/312]	eta 0:01:32 lr 0.000705	time 0.4678 (0.4817)	model_time 0.4673 (0.4650)	loss 3.1072 (3.0090)	grad_norm 3.7690 (2.2775/1.1486)	mem 16099MB
[2025-01-18 08:20:39 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][130/312]	eta 0:01:27 lr 0.000704	time 0.4494 (0.4804)	model_time 0.4490 (0.4650)	loss 3.0073 (2.9862)	grad_norm 4.6247 (2.2703/1.1406)	mem 16099MB
[2025-01-18 08:20:44 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][140/312]	eta 0:01:22 lr 0.000704	time 0.5922 (0.4806)	model_time 0.5920 (0.4663)	loss 3.3588 (2.9988)	grad_norm 5.8548 (2.2983/1.1476)	mem 16099MB
[2025-01-18 08:20:49 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][150/312]	eta 0:01:17 lr 0.000703	time 0.4439 (0.4802)	model_time 0.4434 (0.4667)	loss 2.2810 (2.9997)	grad_norm 2.5147 (2.3306/1.1410)	mem 16099MB
[2025-01-18 08:20:53 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][160/312]	eta 0:01:13 lr 0.000703	time 0.5413 (0.4803)	model_time 0.5411 (0.4677)	loss 3.0123 (2.9973)	grad_norm 1.5544 (2.3663/1.1756)	mem 16099MB
[2025-01-18 08:20:58 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][170/312]	eta 0:01:08 lr 0.000702	time 0.4661 (0.4789)	model_time 0.4658 (0.4670)	loss 3.3590 (2.9815)	grad_norm 3.2638 (2.3657/1.1538)	mem 16099MB
[2025-01-18 08:21:03 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][180/312]	eta 0:01:03 lr 0.000702	time 0.4557 (0.4781)	model_time 0.4553 (0.4668)	loss 3.2463 (2.9763)	grad_norm 4.2246 (2.4260/1.1774)	mem 16099MB
[2025-01-18 08:21:07 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][190/312]	eta 0:00:58 lr 0.000701	time 0.4597 (0.4774)	model_time 0.4593 (0.4667)	loss 2.5242 (2.9608)	grad_norm 1.5098 (2.4144/1.1564)	mem 16099MB
[2025-01-18 08:21:12 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][200/312]	eta 0:00:53 lr 0.000701	time 0.4474 (0.4770)	model_time 0.4472 (0.4668)	loss 3.6449 (2.9752)	grad_norm 1.7520 (2.4009/1.1388)	mem 16099MB
[2025-01-18 08:21:17 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][210/312]	eta 0:00:48 lr 0.000700	time 0.4491 (0.4761)	model_time 0.4489 (0.4664)	loss 2.8294 (2.9739)	grad_norm 1.3689 (2.4031/1.1333)	mem 16099MB
[2025-01-18 08:21:21 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][220/312]	eta 0:00:43 lr 0.000700	time 0.4632 (0.4756)	model_time 0.4628 (0.4663)	loss 3.0349 (2.9776)	grad_norm 1.7293 (2.4453/1.1821)	mem 16099MB
[2025-01-18 08:21:26 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][230/312]	eta 0:00:38 lr 0.000699	time 0.4515 (0.4751)	model_time 0.4511 (0.4662)	loss 3.7607 (2.9818)	grad_norm 2.6592 (2.4364/1.1660)	mem 16099MB
[2025-01-18 08:21:31 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][240/312]	eta 0:00:34 lr 0.000699	time 0.4524 (0.4746)	model_time 0.4523 (0.4660)	loss 3.5319 (2.9890)	grad_norm 2.9449 (2.4445/1.1713)	mem 16099MB
[2025-01-18 08:21:35 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][250/312]	eta 0:00:29 lr 0.000698	time 0.4602 (0.4740)	model_time 0.4601 (0.4658)	loss 3.0820 (2.9789)	grad_norm 3.5902 (2.4513/1.1601)	mem 16099MB
[2025-01-18 08:21:40 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][260/312]	eta 0:00:24 lr 0.000698	time 0.4703 (0.4732)	model_time 0.4701 (0.4653)	loss 3.2760 (2.9784)	grad_norm 5.5192 (2.4635/1.1694)	mem 16099MB
[2025-01-18 08:21:44 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][270/312]	eta 0:00:19 lr 0.000697	time 0.4559 (0.4729)	model_time 0.4557 (0.4652)	loss 2.2852 (2.9785)	grad_norm 3.5216 (2.4983/1.1781)	mem 16099MB
[2025-01-18 08:21:49 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][280/312]	eta 0:00:15 lr 0.000697	time 0.4353 (0.4723)	model_time 0.4348 (0.4649)	loss 3.0922 (2.9743)	grad_norm 2.4071 (2.4822/1.1684)	mem 16099MB
[2025-01-18 08:21:53 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][290/312]	eta 0:00:10 lr 0.000696	time 0.4534 (0.4717)	model_time 0.4529 (0.4645)	loss 3.4926 (2.9757)	grad_norm 3.4339 (2.4686/1.1608)	mem 16099MB
[2025-01-18 08:21:58 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][300/312]	eta 0:00:05 lr 0.000696	time 0.4392 (0.4714)	model_time 0.4391 (0.4645)	loss 2.3032 (2.9795)	grad_norm 4.7909 (2.4731/1.1546)	mem 16099MB
[2025-01-18 08:22:03 internimage_t_1k_224] (main.py 510): INFO Train: [219/300][310/312]	eta 0:00:00 lr 0.000695	time 0.4390 (0.4710)	model_time 0.4388 (0.4642)	loss 3.2812 (2.9723)	grad_norm 2.0362 (2.4802/1.1516)	mem 16099MB
[2025-01-18 08:22:03 internimage_t_1k_224] (main.py 519): INFO EPOCH 219 training takes 0:02:26
[2025-01-18 08:22:03 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_219.pth saving......
[2025-01-18 08:22:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_219.pth saved !!!
[2025-01-18 08:22:11 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.151 (7.151)	Loss 0.7511 (0.7511)	Acc@1 84.204 (84.204)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 08:22:15 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.974)	Loss 1.0315 (0.8720)	Acc@1 76.953 (81.929)	Acc@5 94.629 (95.907)	Mem 16099MB
[2025-01-18 08:22:15 internimage_t_1k_224] (main.py 575): INFO [Epoch:219] * Acc@1 81.752 Acc@5 95.919
[2025-01-18 08:22:15 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.8%
[2025-01-18 08:22:15 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.76%
[2025-01-18 08:22:23 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.051 (8.051)	Loss 0.7657 (0.7657)	Acc@1 85.376 (85.376)	Acc@5 97.583 (97.583)	Mem 16099MB
[2025-01-18 08:22:27 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.080)	Loss 1.0167 (0.8775)	Acc@1 78.491 (82.766)	Acc@5 95.068 (96.311)	Mem 16099MB
[2025-01-18 08:22:27 internimage_t_1k_224] (main.py 575): INFO [Epoch:219] * Acc@1 82.650 Acc@5 96.327
[2025-01-18 08:22:27 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.6%
[2025-01-18 08:22:27 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:22:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:22:29 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.65%
[2025-01-18 08:22:31 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][0/312]	eta 0:13:38 lr 0.000695	time 2.6220 (2.6220)	model_time 0.6536 (0.6536)	loss 3.2456 (3.2456)	grad_norm 1.9994 (1.9994/0.0000)	mem 16099MB
[2025-01-18 08:22:36 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][10/312]	eta 0:03:18 lr 0.000695	time 0.4454 (0.6588)	model_time 0.4453 (0.4796)	loss 3.2226 (3.1076)	grad_norm 3.4767 (2.2908/1.0046)	mem 16099MB
[2025-01-18 08:22:41 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][20/312]	eta 0:02:49 lr 0.000694	time 0.4468 (0.5816)	model_time 0.4466 (0.4876)	loss 3.2376 (3.1073)	grad_norm 1.4824 (2.2104/0.8096)	mem 16099MB
[2025-01-18 08:22:45 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][30/312]	eta 0:02:34 lr 0.000694	time 0.4405 (0.5465)	model_time 0.4403 (0.4827)	loss 3.5117 (3.0626)	grad_norm 2.7027 (2.2031/0.8162)	mem 16099MB
[2025-01-18 08:22:50 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][40/312]	eta 0:02:22 lr 0.000693	time 0.4601 (0.5248)	model_time 0.4600 (0.4765)	loss 2.0183 (2.9302)	grad_norm 2.1674 (2.1823/0.8115)	mem 16099MB
[2025-01-18 08:22:55 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][50/312]	eta 0:02:14 lr 0.000693	time 0.4590 (0.5130)	model_time 0.4586 (0.4741)	loss 2.8496 (2.9318)	grad_norm 3.6256 (2.2545/0.8062)	mem 16099MB
[2025-01-18 08:22:59 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][60/312]	eta 0:02:07 lr 0.000692	time 0.4534 (0.5057)	model_time 0.4530 (0.4731)	loss 3.2907 (2.8942)	grad_norm 1.7804 (2.2795/0.8597)	mem 16099MB
[2025-01-18 08:23:04 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][70/312]	eta 0:02:00 lr 0.000692	time 0.4792 (0.4987)	model_time 0.4790 (0.4707)	loss 1.8770 (2.8768)	grad_norm 3.1648 (2.2976/0.8479)	mem 16099MB
[2025-01-18 08:23:08 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][80/312]	eta 0:01:54 lr 0.000691	time 0.4510 (0.4929)	model_time 0.4508 (0.4683)	loss 3.1033 (2.9177)	grad_norm 2.4641 (2.3739/0.8503)	mem 16099MB
[2025-01-18 08:23:13 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][90/312]	eta 0:01:49 lr 0.000691	time 0.4574 (0.4917)	model_time 0.4571 (0.4697)	loss 3.3720 (2.9282)	grad_norm 3.4970 (2.3780/0.8494)	mem 16099MB
[2025-01-18 08:23:18 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][100/312]	eta 0:01:43 lr 0.000690	time 0.5969 (0.4893)	model_time 0.5964 (0.4695)	loss 2.9396 (2.9128)	grad_norm 1.8094 (2.3723/0.8356)	mem 16099MB
[2025-01-18 08:23:23 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][110/312]	eta 0:01:38 lr 0.000690	time 0.4933 (0.4876)	model_time 0.4931 (0.4695)	loss 3.2364 (2.9064)	grad_norm 3.5656 (2.3506/0.8215)	mem 16099MB
[2025-01-18 08:23:27 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][120/312]	eta 0:01:33 lr 0.000689	time 0.4424 (0.4854)	model_time 0.4422 (0.4688)	loss 2.1108 (2.8882)	grad_norm 1.9241 (2.4098/0.8588)	mem 16099MB
[2025-01-18 08:23:32 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][130/312]	eta 0:01:28 lr 0.000689	time 0.7302 (0.4858)	model_time 0.7301 (0.4704)	loss 2.5283 (2.8842)	grad_norm 1.7097 (2.3891/0.8482)	mem 16099MB
[2025-01-18 08:23:37 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][140/312]	eta 0:01:23 lr 0.000688	time 0.4626 (0.4855)	model_time 0.4622 (0.4712)	loss 3.1921 (2.8719)	grad_norm 4.5898 (2.3872/0.8565)	mem 16099MB
[2025-01-18 08:23:42 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][150/312]	eta 0:01:18 lr 0.000688	time 0.4552 (0.4836)	model_time 0.4548 (0.4702)	loss 1.6256 (2.8697)	grad_norm 1.2630 (2.4130/0.8745)	mem 16099MB
[2025-01-18 08:23:46 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][160/312]	eta 0:01:13 lr 0.000687	time 0.4401 (0.4821)	model_time 0.4399 (0.4695)	loss 3.2581 (2.8717)	grad_norm 1.6660 (2.4100/0.9125)	mem 16099MB
[2025-01-18 08:23:51 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][170/312]	eta 0:01:08 lr 0.000687	time 0.4558 (0.4809)	model_time 0.4556 (0.4691)	loss 2.3557 (2.8733)	grad_norm 2.0990 (2.3820/0.9093)	mem 16099MB
[2025-01-18 08:23:55 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][180/312]	eta 0:01:03 lr 0.000686	time 0.4552 (0.4796)	model_time 0.4548 (0.4684)	loss 2.5100 (2.8776)	grad_norm 1.9015 (2.3598/0.8934)	mem 16099MB
[2025-01-18 08:24:00 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][190/312]	eta 0:00:58 lr 0.000686	time 0.4526 (0.4784)	model_time 0.4522 (0.4677)	loss 3.4353 (2.8883)	grad_norm 2.2442 (2.3674/0.9030)	mem 16099MB
[2025-01-18 08:24:05 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][200/312]	eta 0:00:53 lr 0.000685	time 0.5658 (0.4783)	model_time 0.5657 (0.4681)	loss 3.0611 (2.8860)	grad_norm 2.5109 (2.3512/0.8912)	mem 16099MB
[2025-01-18 08:24:09 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][210/312]	eta 0:00:48 lr 0.000685	time 0.4461 (0.4772)	model_time 0.4457 (0.4675)	loss 2.3211 (2.8817)	grad_norm 4.1770 (2.3888/0.9504)	mem 16099MB
[2025-01-18 08:24:14 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][220/312]	eta 0:00:43 lr 0.000684	time 0.4817 (0.4767)	model_time 0.4812 (0.4674)	loss 2.9908 (2.8815)	grad_norm 4.4065 (2.4671/1.0472)	mem 16099MB
[2025-01-18 08:24:19 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][230/312]	eta 0:00:39 lr 0.000684	time 0.4558 (0.4761)	model_time 0.4557 (0.4672)	loss 2.9719 (2.8829)	grad_norm 1.3872 (2.4867/1.0704)	mem 16099MB
[2025-01-18 08:24:23 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][240/312]	eta 0:00:34 lr 0.000683	time 0.4507 (0.4753)	model_time 0.4505 (0.4667)	loss 2.8726 (2.8727)	grad_norm 3.0074 (2.4579/1.0640)	mem 16099MB
[2025-01-18 08:24:28 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][250/312]	eta 0:00:29 lr 0.000683	time 0.4390 (0.4755)	model_time 0.4388 (0.4673)	loss 3.3257 (2.8813)	grad_norm 1.5212 (2.4511/1.0511)	mem 16099MB
[2025-01-18 08:24:33 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][260/312]	eta 0:00:24 lr 0.000682	time 0.4535 (0.4755)	model_time 0.4530 (0.4676)	loss 2.3876 (2.8833)	grad_norm 3.2864 (2.4761/1.0556)	mem 16099MB
[2025-01-18 08:24:37 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][270/312]	eta 0:00:19 lr 0.000682	time 0.4400 (0.4750)	model_time 0.4399 (0.4674)	loss 3.2502 (2.8787)	grad_norm 4.6958 (2.5099/1.0776)	mem 16099MB
[2025-01-18 08:24:42 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][280/312]	eta 0:00:15 lr 0.000681	time 0.4592 (0.4743)	model_time 0.4587 (0.4669)	loss 2.7729 (2.8846)	grad_norm 1.6921 (2.5185/1.1000)	mem 16099MB
[2025-01-18 08:24:46 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][290/312]	eta 0:00:10 lr 0.000681	time 0.4513 (0.4739)	model_time 0.4511 (0.4668)	loss 3.0893 (2.8922)	grad_norm 2.0769 (2.5073/1.0954)	mem 16099MB
[2025-01-18 08:24:51 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][300/312]	eta 0:00:05 lr 0.000680	time 0.4463 (0.4735)	model_time 0.4462 (0.4666)	loss 3.0040 (2.8973)	grad_norm 2.1320 (2.4967/1.0854)	mem 16099MB
[2025-01-18 08:24:56 internimage_t_1k_224] (main.py 510): INFO Train: [220/300][310/312]	eta 0:00:00 lr 0.000680	time 0.4395 (0.4729)	model_time 0.4394 (0.4662)	loss 2.2265 (2.8938)	grad_norm 3.2936 (2.5064/1.0924)	mem 16099MB
[2025-01-18 08:24:56 internimage_t_1k_224] (main.py 519): INFO EPOCH 220 training takes 0:02:27
[2025-01-18 08:24:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_220.pth saving......
[2025-01-18 08:24:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_220.pth saved !!!
[2025-01-18 08:25:05 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.283 (7.283)	Loss 0.7547 (0.7547)	Acc@1 84.204 (84.204)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 08:25:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.979)	Loss 1.0355 (0.8594)	Acc@1 77.319 (82.025)	Acc@5 94.336 (95.976)	Mem 16099MB
[2025-01-18 08:25:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:220] * Acc@1 81.902 Acc@5 96.017
[2025-01-18 08:25:08 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.9%
[2025-01-18 08:25:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 08:25:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 08:25:09 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.90%
[2025-01-18 08:25:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.438 (7.438)	Loss 0.7645 (0.7645)	Acc@1 85.400 (85.400)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 08:25:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.108 (1.005)	Loss 1.0152 (0.8762)	Acc@1 78.589 (82.801)	Acc@5 95.190 (96.340)	Mem 16099MB
[2025-01-18 08:25:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:220] * Acc@1 82.678 Acc@5 96.357
[2025-01-18 08:25:20 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.7%
[2025-01-18 08:25:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:25:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:25:22 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.68%
[2025-01-18 08:25:24 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][0/312]	eta 0:12:00 lr 0.000680	time 2.3085 (2.3085)	model_time 0.4970 (0.4970)	loss 2.0438 (2.0438)	grad_norm 1.2489 (1.2489/0.0000)	mem 16099MB
[2025-01-18 08:25:29 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][10/312]	eta 0:03:14 lr 0.000679	time 0.4574 (0.6434)	model_time 0.4569 (0.4783)	loss 3.0002 (3.0209)	grad_norm 3.5022 (2.7952/1.0763)	mem 16099MB
[2025-01-18 08:25:34 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][20/312]	eta 0:02:42 lr 0.000679	time 0.4414 (0.5574)	model_time 0.4412 (0.4708)	loss 3.2651 (3.0511)	grad_norm 1.8031 (2.6259/1.0623)	mem 16099MB
[2025-01-18 08:25:38 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][30/312]	eta 0:02:29 lr 0.000678	time 0.4410 (0.5294)	model_time 0.4408 (0.4706)	loss 2.6049 (2.9904)	grad_norm 3.5675 (2.5147/0.9879)	mem 16099MB
[2025-01-18 08:25:43 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][40/312]	eta 0:02:19 lr 0.000678	time 0.4480 (0.5137)	model_time 0.4476 (0.4692)	loss 3.5456 (2.9758)	grad_norm 3.5859 (2.4918/1.0055)	mem 16099MB
[2025-01-18 08:25:48 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][50/312]	eta 0:02:12 lr 0.000677	time 0.4454 (0.5055)	model_time 0.4449 (0.4696)	loss 2.6414 (2.9767)	grad_norm 2.9370 (2.5618/1.0069)	mem 16099MB
[2025-01-18 08:25:53 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][60/312]	eta 0:02:06 lr 0.000677	time 0.4465 (0.5001)	model_time 0.4463 (0.4701)	loss 3.1459 (2.9783)	grad_norm 1.4015 (2.4387/1.0114)	mem 16099MB
[2025-01-18 08:25:57 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][70/312]	eta 0:01:59 lr 0.000676	time 0.4536 (0.4958)	model_time 0.4532 (0.4700)	loss 2.8556 (2.9513)	grad_norm 1.9345 (2.3655/0.9689)	mem 16099MB
[2025-01-18 08:26:02 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][80/312]	eta 0:01:54 lr 0.000676	time 0.4688 (0.4944)	model_time 0.4687 (0.4717)	loss 3.1053 (2.9516)	grad_norm 3.0575 (2.3519/0.9302)	mem 16099MB
[2025-01-18 08:26:07 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][90/312]	eta 0:01:48 lr 0.000675	time 0.4480 (0.4898)	model_time 0.4478 (0.4696)	loss 3.3545 (2.9062)	grad_norm 1.1957 (2.3513/0.9468)	mem 16099MB
[2025-01-18 08:26:11 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][100/312]	eta 0:01:43 lr 0.000675	time 0.4481 (0.4868)	model_time 0.4479 (0.4685)	loss 3.1086 (2.9266)	grad_norm 2.5665 (2.3525/0.9168)	mem 16099MB
[2025-01-18 08:26:16 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][110/312]	eta 0:01:38 lr 0.000674	time 0.4441 (0.4854)	model_time 0.4436 (0.4687)	loss 3.2249 (2.9491)	grad_norm 1.6639 (2.3397/0.9218)	mem 16099MB
[2025-01-18 08:26:20 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][120/312]	eta 0:01:32 lr 0.000674	time 0.4498 (0.4831)	model_time 0.4480 (0.4677)	loss 3.2778 (2.9309)	grad_norm 3.1113 (2.3424/0.9288)	mem 16099MB
[2025-01-18 08:26:25 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][130/312]	eta 0:01:27 lr 0.000673	time 0.4484 (0.4813)	model_time 0.4479 (0.4671)	loss 1.8124 (2.9189)	grad_norm 2.4260 (2.3270/0.9012)	mem 16099MB
[2025-01-18 08:26:30 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][140/312]	eta 0:01:22 lr 0.000673	time 0.4709 (0.4805)	model_time 0.4708 (0.4673)	loss 3.2816 (2.9036)	grad_norm 1.5939 (2.2909/0.8968)	mem 16099MB
[2025-01-18 08:26:34 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][150/312]	eta 0:01:17 lr 0.000672	time 0.4477 (0.4792)	model_time 0.4475 (0.4669)	loss 3.6352 (2.9036)	grad_norm 1.5740 (2.3132/0.9268)	mem 16099MB
[2025-01-18 08:26:39 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][160/312]	eta 0:01:12 lr 0.000672	time 0.4476 (0.4783)	model_time 0.4471 (0.4667)	loss 3.5541 (2.9003)	grad_norm 2.9097 (2.3451/0.9619)	mem 16099MB
[2025-01-18 08:26:44 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][170/312]	eta 0:01:07 lr 0.000671	time 0.4582 (0.4769)	model_time 0.4577 (0.4659)	loss 3.0826 (2.8925)	grad_norm 1.7519 (2.3500/0.9553)	mem 16099MB
[2025-01-18 08:26:48 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][180/312]	eta 0:01:02 lr 0.000671	time 0.4262 (0.4763)	model_time 0.4257 (0.4659)	loss 2.0843 (2.8893)	grad_norm inf (2.3345/0.9499)	mem 16099MB
[2025-01-18 08:26:53 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][190/312]	eta 0:00:58 lr 0.000671	time 0.4502 (0.4757)	model_time 0.4500 (0.4658)	loss 2.7941 (2.8838)	grad_norm 1.1330 (2.3285/0.9436)	mem 16099MB
[2025-01-18 08:26:57 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][200/312]	eta 0:00:53 lr 0.000670	time 0.4736 (0.4751)	model_time 0.4734 (0.4657)	loss 2.7754 (2.8831)	grad_norm 1.1954 (2.3361/0.9614)	mem 16099MB
[2025-01-18 08:27:02 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][210/312]	eta 0:00:48 lr 0.000670	time 0.4320 (0.4748)	model_time 0.4318 (0.4659)	loss 3.0150 (2.8833)	grad_norm 1.4351 (2.3827/0.9943)	mem 16099MB
[2025-01-18 08:27:07 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][220/312]	eta 0:00:43 lr 0.000669	time 0.4430 (0.4745)	model_time 0.4426 (0.4659)	loss 3.0116 (2.8857)	grad_norm 1.8268 (2.3760/0.9873)	mem 16099MB
[2025-01-18 08:27:11 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][230/312]	eta 0:00:38 lr 0.000669	time 0.4546 (0.4740)	model_time 0.4544 (0.4658)	loss 2.5850 (2.8903)	grad_norm 1.6745 (2.3589/0.9803)	mem 16099MB
[2025-01-18 08:27:16 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][240/312]	eta 0:00:34 lr 0.000668	time 0.4613 (0.4733)	model_time 0.4611 (0.4654)	loss 3.1444 (2.8850)	grad_norm 1.8708 (2.3380/0.9698)	mem 16099MB
[2025-01-18 08:27:21 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][250/312]	eta 0:00:29 lr 0.000668	time 0.4369 (0.4729)	model_time 0.4367 (0.4653)	loss 2.7356 (2.8824)	grad_norm 2.9052 (2.3516/0.9779)	mem 16099MB
[2025-01-18 08:27:25 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][260/312]	eta 0:00:24 lr 0.000667	time 0.4497 (0.4723)	model_time 0.4496 (0.4649)	loss 3.1756 (2.8842)	grad_norm 2.6520 (2.3516/0.9734)	mem 16099MB
[2025-01-18 08:27:30 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][270/312]	eta 0:00:19 lr 0.000667	time 0.4415 (0.4719)	model_time 0.4410 (0.4648)	loss 3.3427 (2.8924)	grad_norm 4.2028 (2.3679/0.9733)	mem 16099MB
[2025-01-18 08:27:35 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][280/312]	eta 0:00:15 lr 0.000666	time 0.4503 (0.4715)	model_time 0.4501 (0.4647)	loss 3.3027 (2.8918)	grad_norm 1.1668 (2.3785/0.9777)	mem 16099MB
[2025-01-18 08:27:39 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][290/312]	eta 0:00:10 lr 0.000666	time 0.4581 (0.4716)	model_time 0.4580 (0.4650)	loss 2.7253 (2.8817)	grad_norm 2.8066 (2.4072/0.9955)	mem 16099MB
[2025-01-18 08:27:44 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][300/312]	eta 0:00:05 lr 0.000665	time 0.4373 (0.4715)	model_time 0.4372 (0.4651)	loss 3.7060 (2.8825)	grad_norm 1.3845 (2.4090/0.9924)	mem 16099MB
[2025-01-18 08:27:49 internimage_t_1k_224] (main.py 510): INFO Train: [221/300][310/312]	eta 0:00:00 lr 0.000665	time 0.4382 (0.4713)	model_time 0.4381 (0.4651)	loss 2.5127 (2.8793)	grad_norm 2.0753 (2.3937/0.9787)	mem 16099MB
[2025-01-18 08:27:49 internimage_t_1k_224] (main.py 519): INFO EPOCH 221 training takes 0:02:27
[2025-01-18 08:27:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_221.pth saving......
[2025-01-18 08:27:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_221.pth saved !!!
[2025-01-18 08:27:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.497 (7.497)	Loss 0.7429 (0.7429)	Acc@1 84.277 (84.277)	Acc@5 97.461 (97.461)	Mem 16099MB
[2025-01-18 08:28:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.997)	Loss 1.0161 (0.8609)	Acc@1 77.612 (81.876)	Acc@5 94.653 (95.943)	Mem 16099MB
[2025-01-18 08:28:01 internimage_t_1k_224] (main.py 575): INFO [Epoch:221] * Acc@1 81.772 Acc@5 95.945
[2025-01-18 08:28:01 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.8%
[2025-01-18 08:28:01 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.90%
[2025-01-18 08:28:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.156 (8.156)	Loss 0.7633 (0.7633)	Acc@1 85.400 (85.400)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 08:28:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.104)	Loss 1.0136 (0.8747)	Acc@1 78.638 (82.821)	Acc@5 95.239 (96.358)	Mem 16099MB
[2025-01-18 08:28:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:221] * Acc@1 82.696 Acc@5 96.373
[2025-01-18 08:28:14 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.7%
[2025-01-18 08:28:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:28:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:28:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.70%
[2025-01-18 08:28:18 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][0/312]	eta 0:12:36 lr 0.000665	time 2.4245 (2.4245)	model_time 0.5238 (0.5238)	loss 3.0566 (3.0566)	grad_norm 2.7216 (2.7216/0.0000)	mem 16099MB
[2025-01-18 08:28:22 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][10/312]	eta 0:03:12 lr 0.000664	time 0.4491 (0.6379)	model_time 0.4489 (0.4648)	loss 1.9028 (2.9209)	grad_norm 2.3479 (1.9526/0.8140)	mem 16099MB
[2025-01-18 08:28:27 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][20/312]	eta 0:02:41 lr 0.000664	time 0.4528 (0.5546)	model_time 0.4527 (0.4638)	loss 2.5779 (2.8309)	grad_norm 1.9039 (2.2827/0.9657)	mem 16099MB
[2025-01-18 08:28:31 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][30/312]	eta 0:02:28 lr 0.000663	time 0.4537 (0.5255)	model_time 0.4535 (0.4638)	loss 3.4157 (2.9048)	grad_norm 2.7098 (2.2625/0.8703)	mem 16099MB
[2025-01-18 08:28:36 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][40/312]	eta 0:02:19 lr 0.000663	time 0.4519 (0.5142)	model_time 0.4516 (0.4675)	loss 2.6870 (2.8897)	grad_norm 1.3094 (2.2255/0.9031)	mem 16099MB
[2025-01-18 08:28:41 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][50/312]	eta 0:02:11 lr 0.000662	time 0.4644 (0.5027)	model_time 0.4643 (0.4651)	loss 3.1591 (2.8623)	grad_norm 3.4416 (2.2310/0.8848)	mem 16099MB
[2025-01-18 08:28:45 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][60/312]	eta 0:02:04 lr 0.000662	time 0.4475 (0.4959)	model_time 0.4473 (0.4644)	loss 3.1464 (2.9005)	grad_norm 2.2102 (2.2536/0.9136)	mem 16099MB
[2025-01-18 08:28:50 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][70/312]	eta 0:01:58 lr 0.000661	time 0.4415 (0.4903)	model_time 0.4413 (0.4632)	loss 3.3345 (2.9075)	grad_norm 1.6861 (2.2237/0.8741)	mem 16099MB
[2025-01-18 08:28:55 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][80/312]	eta 0:01:53 lr 0.000661	time 0.4492 (0.4875)	model_time 0.4489 (0.4637)	loss 3.0804 (2.9162)	grad_norm 1.2453 (2.2159/0.8670)	mem 16099MB
[2025-01-18 08:28:59 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][90/312]	eta 0:01:47 lr 0.000660	time 0.4684 (0.4857)	model_time 0.4682 (0.4645)	loss 3.3013 (2.9212)	grad_norm 8.1706 (2.4796/1.2932)	mem 16099MB
[2025-01-18 08:29:04 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][100/312]	eta 0:01:42 lr 0.000660	time 0.4847 (0.4852)	model_time 0.4845 (0.4660)	loss 2.9234 (2.9237)	grad_norm 2.0787 (2.6060/1.4145)	mem 16099MB
[2025-01-18 08:29:09 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][110/312]	eta 0:01:37 lr 0.000659	time 0.4640 (0.4836)	model_time 0.4639 (0.4662)	loss 2.9231 (2.9149)	grad_norm 1.5771 (2.5276/1.3894)	mem 16099MB
[2025-01-18 08:29:14 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][120/312]	eta 0:01:32 lr 0.000659	time 0.4595 (0.4826)	model_time 0.4593 (0.4666)	loss 3.1380 (2.9183)	grad_norm 4.3148 (2.5845/1.4077)	mem 16099MB
[2025-01-18 08:29:18 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][130/312]	eta 0:01:27 lr 0.000658	time 0.4496 (0.4805)	model_time 0.4495 (0.4656)	loss 3.1266 (2.9146)	grad_norm 3.0743 (2.6248/1.4089)	mem 16099MB
[2025-01-18 08:29:23 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][140/312]	eta 0:01:22 lr 0.000658	time 0.4380 (0.4791)	model_time 0.4378 (0.4653)	loss 2.7966 (2.8937)	grad_norm 1.3063 (2.6143/1.3879)	mem 16099MB
[2025-01-18 08:29:27 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][150/312]	eta 0:01:17 lr 0.000657	time 0.4411 (0.4774)	model_time 0.4409 (0.4644)	loss 2.8701 (2.8924)	grad_norm 1.7112 (2.6056/1.3534)	mem 16099MB
[2025-01-18 08:29:32 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][160/312]	eta 0:01:12 lr 0.000657	time 0.5348 (0.4771)	model_time 0.5345 (0.4650)	loss 2.9395 (2.9016)	grad_norm 1.0406 (2.5622/1.3328)	mem 16099MB
[2025-01-18 08:29:37 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][170/312]	eta 0:01:07 lr 0.000656	time 0.4499 (0.4757)	model_time 0.4497 (0.4643)	loss 3.2645 (2.9178)	grad_norm 3.3614 (2.5961/1.3372)	mem 16099MB
[2025-01-18 08:29:41 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][180/312]	eta 0:01:02 lr 0.000656	time 0.4443 (0.4751)	model_time 0.4441 (0.4643)	loss 2.9091 (2.9273)	grad_norm 3.2472 (2.6045/1.3325)	mem 16099MB
[2025-01-18 08:29:46 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][190/312]	eta 0:00:57 lr 0.000655	time 0.4634 (0.4748)	model_time 0.4632 (0.4645)	loss 2.2663 (2.9299)	grad_norm 2.7119 (2.5985/1.3097)	mem 16099MB
[2025-01-18 08:29:51 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][200/312]	eta 0:00:53 lr 0.000655	time 0.4619 (0.4753)	model_time 0.4617 (0.4655)	loss 2.5017 (2.9293)	grad_norm 1.5236 (2.5784/1.2940)	mem 16099MB
[2025-01-18 08:29:55 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][210/312]	eta 0:00:48 lr 0.000654	time 0.4434 (0.4747)	model_time 0.4424 (0.4653)	loss 2.0039 (2.9207)	grad_norm 2.5861 (2.5986/1.2933)	mem 16099MB
[2025-01-18 08:30:00 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][220/312]	eta 0:00:43 lr 0.000654	time 0.4708 (0.4743)	model_time 0.4706 (0.4654)	loss 2.9506 (2.9240)	grad_norm 3.0581 (2.5593/1.2825)	mem 16099MB
[2025-01-18 08:30:05 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][230/312]	eta 0:00:38 lr 0.000653	time 0.5635 (0.4753)	model_time 0.5633 (0.4668)	loss 2.7432 (2.9195)	grad_norm 1.4354 (2.5338/1.2714)	mem 16099MB
[2025-01-18 08:30:10 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][240/312]	eta 0:00:34 lr 0.000653	time 0.4457 (0.4748)	model_time 0.4455 (0.4666)	loss 2.8788 (2.9102)	grad_norm 2.2617 (2.5311/1.2502)	mem 16099MB
[2025-01-18 08:30:14 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][250/312]	eta 0:00:29 lr 0.000653	time 0.5683 (0.4745)	model_time 0.5681 (0.4666)	loss 3.1927 (2.9089)	grad_norm 1.5277 (2.5468/1.2466)	mem 16099MB
[2025-01-18 08:30:19 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][260/312]	eta 0:00:24 lr 0.000652	time 0.4465 (0.4744)	model_time 0.4463 (0.4667)	loss 3.5426 (2.9092)	grad_norm 3.4318 (2.5423/1.2333)	mem 16099MB
[2025-01-18 08:30:24 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][270/312]	eta 0:00:19 lr 0.000652	time 0.4428 (0.4748)	model_time 0.4426 (0.4674)	loss 2.8930 (2.9114)	grad_norm 1.3482 (2.5246/1.2234)	mem 16099MB
[2025-01-18 08:30:28 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][280/312]	eta 0:00:15 lr 0.000651	time 0.4497 (0.4743)	model_time 0.4496 (0.4672)	loss 2.2486 (2.9158)	grad_norm 3.2322 (2.5285/1.2417)	mem 16099MB
[2025-01-18 08:30:33 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][290/312]	eta 0:00:10 lr 0.000651	time 0.4439 (0.4740)	model_time 0.4437 (0.4672)	loss 1.7876 (2.9160)	grad_norm 4.5051 (2.5791/1.2689)	mem 16099MB
[2025-01-18 08:30:38 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][300/312]	eta 0:00:05 lr 0.000650	time 0.4875 (0.4734)	model_time 0.4874 (0.4668)	loss 2.4696 (2.9113)	grad_norm 1.4800 (2.5680/1.2558)	mem 16099MB
[2025-01-18 08:30:42 internimage_t_1k_224] (main.py 510): INFO Train: [222/300][310/312]	eta 0:00:00 lr 0.000650	time 0.4398 (0.4723)	model_time 0.4397 (0.4659)	loss 3.1547 (2.9055)	grad_norm 2.0644 (2.6159/1.2743)	mem 16099MB
[2025-01-18 08:30:43 internimage_t_1k_224] (main.py 519): INFO EPOCH 222 training takes 0:02:27
[2025-01-18 08:30:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_222.pth saving......
[2025-01-18 08:30:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_222.pth saved !!!
[2025-01-18 08:30:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.214 (7.214)	Loss 0.7412 (0.7412)	Acc@1 84.302 (84.302)	Acc@5 97.168 (97.168)	Mem 16099MB
[2025-01-18 08:30:54 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.977)	Loss 1.0132 (0.8377)	Acc@1 76.831 (81.954)	Acc@5 94.556 (95.932)	Mem 16099MB
[2025-01-18 08:30:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:222] * Acc@1 81.852 Acc@5 95.949
[2025-01-18 08:30:55 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.9%
[2025-01-18 08:30:55 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.90%
[2025-01-18 08:31:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.956 (7.956)	Loss 0.7621 (0.7621)	Acc@1 85.498 (85.498)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 08:31:06 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.064)	Loss 1.0119 (0.8733)	Acc@1 78.662 (82.852)	Acc@5 95.215 (96.360)	Mem 16099MB
[2025-01-18 08:31:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:222] * Acc@1 82.728 Acc@5 96.379
[2025-01-18 08:31:06 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.7%
[2025-01-18 08:31:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:31:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:31:08 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.73%
[2025-01-18 08:31:10 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][0/312]	eta 0:10:55 lr 0.000650	time 2.0998 (2.0998)	model_time 0.4769 (0.4769)	loss 2.5646 (2.5646)	grad_norm 2.3379 (2.3379/0.0000)	mem 16099MB
[2025-01-18 08:31:15 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][10/312]	eta 0:03:08 lr 0.000649	time 0.4540 (0.6229)	model_time 0.4535 (0.4749)	loss 2.5032 (2.6983)	grad_norm 2.7466 (2.2365/1.2397)	mem 16099MB
[2025-01-18 08:31:19 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][20/312]	eta 0:02:41 lr 0.000649	time 0.4517 (0.5535)	model_time 0.4508 (0.4758)	loss 3.1223 (2.7900)	grad_norm 3.5975 (2.3134/1.2511)	mem 16099MB
[2025-01-18 08:31:24 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][30/312]	eta 0:02:29 lr 0.000648	time 0.4703 (0.5309)	model_time 0.4701 (0.4782)	loss 2.7977 (2.7774)	grad_norm 1.7306 (2.6658/1.6687)	mem 16099MB
[2025-01-18 08:31:29 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][40/312]	eta 0:02:20 lr 0.000648	time 0.4533 (0.5158)	model_time 0.4531 (0.4759)	loss 3.0691 (2.8386)	grad_norm 2.6858 (3.0506/1.9404)	mem 16099MB
[2025-01-18 08:31:34 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][50/312]	eta 0:02:12 lr 0.000647	time 0.4438 (0.5068)	model_time 0.4433 (0.4746)	loss 2.5920 (2.7971)	grad_norm 3.7886 (3.0144/1.8075)	mem 16099MB
[2025-01-18 08:31:38 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][60/312]	eta 0:02:06 lr 0.000647	time 0.4569 (0.5004)	model_time 0.4567 (0.4734)	loss 2.9167 (2.8095)	grad_norm 3.4970 (2.9459/1.7327)	mem 16099MB
[2025-01-18 08:31:43 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][70/312]	eta 0:01:59 lr 0.000646	time 0.4547 (0.4953)	model_time 0.4544 (0.4721)	loss 2.2597 (2.8112)	grad_norm 1.6174 (2.8751/1.6594)	mem 16099MB
[2025-01-18 08:31:48 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][80/312]	eta 0:01:54 lr 0.000646	time 0.5420 (0.4950)	model_time 0.5416 (0.4745)	loss 2.5705 (2.8042)	grad_norm 1.9065 (2.7354/1.6031)	mem 16099MB
[2025-01-18 08:31:52 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][90/312]	eta 0:01:48 lr 0.000645	time 0.4485 (0.4909)	model_time 0.4484 (0.4727)	loss 3.5371 (2.8264)	grad_norm 1.5094 (2.6373/1.5492)	mem 16099MB
[2025-01-18 08:31:57 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][100/312]	eta 0:01:43 lr 0.000645	time 0.4506 (0.4876)	model_time 0.4504 (0.4711)	loss 3.2798 (2.8188)	grad_norm 1.9347 (2.6261/1.5033)	mem 16099MB
[2025-01-18 08:32:02 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][110/312]	eta 0:01:38 lr 0.000644	time 0.5101 (0.4870)	model_time 0.5099 (0.4720)	loss 2.5657 (2.8384)	grad_norm 3.9112 (2.6278/1.4575)	mem 16099MB
[2025-01-18 08:32:06 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][120/312]	eta 0:01:33 lr 0.000644	time 0.4586 (0.4848)	model_time 0.4581 (0.4710)	loss 2.9111 (2.8465)	grad_norm 1.6679 (2.5749/1.4164)	mem 16099MB
[2025-01-18 08:32:11 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][130/312]	eta 0:01:27 lr 0.000643	time 0.4538 (0.4824)	model_time 0.4536 (0.4696)	loss 3.4816 (2.8567)	grad_norm 2.2634 (2.5154/1.3849)	mem 16099MB
[2025-01-18 08:32:16 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][140/312]	eta 0:01:23 lr 0.000643	time 0.4979 (0.4832)	model_time 0.4978 (0.4713)	loss 3.1861 (2.8648)	grad_norm 1.2590 (2.4958/1.3590)	mem 16099MB
[2025-01-18 08:32:21 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][150/312]	eta 0:01:18 lr 0.000642	time 0.5827 (0.4835)	model_time 0.5822 (0.4724)	loss 2.6833 (2.8567)	grad_norm 1.9014 (2.5066/1.3449)	mem 16099MB
[2025-01-18 08:32:25 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][160/312]	eta 0:01:13 lr 0.000642	time 0.5216 (0.4821)	model_time 0.5211 (0.4716)	loss 3.6216 (2.8770)	grad_norm 1.3859 (2.5370/1.3714)	mem 16099MB
[2025-01-18 08:32:30 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][170/312]	eta 0:01:08 lr 0.000641	time 0.5529 (0.4812)	model_time 0.5527 (0.4713)	loss 2.4787 (2.8866)	grad_norm 3.0425 (2.5506/1.3413)	mem 16099MB
[2025-01-18 08:32:35 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][180/312]	eta 0:01:03 lr 0.000641	time 0.4580 (0.4802)	model_time 0.4579 (0.4708)	loss 1.8929 (2.8883)	grad_norm 4.0114 (2.5778/1.3660)	mem 16099MB
[2025-01-18 08:32:39 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][190/312]	eta 0:00:58 lr 0.000640	time 0.4444 (0.4789)	model_time 0.4440 (0.4700)	loss 3.0965 (2.9092)	grad_norm 2.0871 (2.6233/1.4166)	mem 16099MB
[2025-01-18 08:32:44 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][200/312]	eta 0:00:53 lr 0.000640	time 0.4420 (0.4779)	model_time 0.4418 (0.4694)	loss 3.0915 (2.9003)	grad_norm 2.5560 (2.6601/1.4322)	mem 16099MB
[2025-01-18 08:32:48 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][210/312]	eta 0:00:48 lr 0.000640	time 0.4547 (0.4768)	model_time 0.4545 (0.4687)	loss 2.7580 (2.8879)	grad_norm 2.2108 (2.6830/1.4439)	mem 16099MB
[2025-01-18 08:32:53 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][220/312]	eta 0:00:43 lr 0.000639	time 0.5109 (0.4761)	model_time 0.5104 (0.4683)	loss 2.4167 (2.8926)	grad_norm 1.9167 (2.6573/1.4272)	mem 16099MB
[2025-01-18 08:32:57 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][230/312]	eta 0:00:38 lr 0.000639	time 0.4684 (0.4752)	model_time 0.4682 (0.4678)	loss 3.1632 (2.8989)	grad_norm 1.5597 (2.6465/1.4201)	mem 16099MB
[2025-01-18 08:33:02 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][240/312]	eta 0:00:34 lr 0.000638	time 0.4499 (0.4744)	model_time 0.4497 (0.4673)	loss 2.9186 (2.8905)	grad_norm 1.7685 (2.6260/1.4017)	mem 16099MB
[2025-01-18 08:33:07 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][250/312]	eta 0:00:29 lr 0.000638	time 0.4897 (0.4740)	model_time 0.4895 (0.4671)	loss 1.8279 (2.8886)	grad_norm 2.5517 (2.6057/1.3847)	mem 16099MB
[2025-01-18 08:33:11 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][260/312]	eta 0:00:24 lr 0.000637	time 0.4509 (0.4736)	model_time 0.4507 (0.4670)	loss 2.3733 (2.8910)	grad_norm 1.2065 (2.6185/1.3815)	mem 16099MB
[2025-01-18 08:33:16 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][270/312]	eta 0:00:19 lr 0.000637	time 0.4519 (0.4729)	model_time 0.4514 (0.4665)	loss 3.2663 (2.8997)	grad_norm 1.6250 (2.6018/1.3652)	mem 16099MB
[2025-01-18 08:33:21 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][280/312]	eta 0:00:15 lr 0.000636	time 0.4461 (0.4730)	model_time 0.4456 (0.4668)	loss 2.9537 (2.8923)	grad_norm 1.1697 (2.5758/1.3536)	mem 16099MB
[2025-01-18 08:33:25 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][290/312]	eta 0:00:10 lr 0.000636	time 0.4513 (0.4728)	model_time 0.4511 (0.4668)	loss 3.2144 (2.8983)	grad_norm 1.1950 (2.5553/1.3395)	mem 16099MB
[2025-01-18 08:33:30 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][300/312]	eta 0:00:05 lr 0.000635	time 0.5202 (0.4726)	model_time 0.5201 (0.4668)	loss 2.1210 (2.8792)	grad_norm 1.5680 (2.5335/1.3288)	mem 16099MB
[2025-01-18 08:33:34 internimage_t_1k_224] (main.py 510): INFO Train: [223/300][310/312]	eta 0:00:00 lr 0.000635	time 0.4405 (0.4719)	model_time 0.4403 (0.4663)	loss 3.0867 (2.8803)	grad_norm 4.3332 (2.5572/1.3238)	mem 16099MB
[2025-01-18 08:33:35 internimage_t_1k_224] (main.py 519): INFO EPOCH 223 training takes 0:02:27
[2025-01-18 08:33:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_223.pth saving......
[2025-01-18 08:33:36 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_223.pth saved !!!
[2025-01-18 08:33:43 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.155 (7.155)	Loss 0.7653 (0.7653)	Acc@1 84.668 (84.668)	Acc@5 97.241 (97.241)	Mem 16099MB
[2025-01-18 08:33:47 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.973)	Loss 1.0598 (0.8777)	Acc@1 76.611 (81.949)	Acc@5 94.897 (95.967)	Mem 16099MB
[2025-01-18 08:33:47 internimage_t_1k_224] (main.py 575): INFO [Epoch:223] * Acc@1 81.790 Acc@5 95.989
[2025-01-18 08:33:47 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.8%
[2025-01-18 08:33:47 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.90%
[2025-01-18 08:33:55 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.079 (8.079)	Loss 0.7613 (0.7613)	Acc@1 85.522 (85.522)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 08:33:59 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.097)	Loss 1.0103 (0.8722)	Acc@1 78.735 (82.890)	Acc@5 95.239 (96.362)	Mem 16099MB
[2025-01-18 08:33:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:223] * Acc@1 82.758 Acc@5 96.385
[2025-01-18 08:33:59 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.8%
[2025-01-18 08:33:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:34:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:34:00 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.76%
[2025-01-18 08:34:03 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][0/312]	eta 0:12:46 lr 0.000635	time 2.4554 (2.4554)	model_time 0.4676 (0.4676)	loss 3.0779 (3.0779)	grad_norm 6.8553 (6.8553/0.0000)	mem 16099MB
[2025-01-18 08:34:08 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][10/312]	eta 0:03:18 lr 0.000634	time 0.4617 (0.6569)	model_time 0.4612 (0.4759)	loss 3.4352 (2.8944)	grad_norm 2.8178 (2.7108/1.4125)	mem 16099MB
[2025-01-18 08:34:12 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][20/312]	eta 0:02:45 lr 0.000634	time 0.4481 (0.5658)	model_time 0.4480 (0.4709)	loss 3.2435 (2.9028)	grad_norm 2.2647 (2.7288/1.1347)	mem 16099MB
[2025-01-18 08:34:17 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][30/312]	eta 0:02:30 lr 0.000633	time 0.4652 (0.5341)	model_time 0.4650 (0.4697)	loss 2.4554 (2.8972)	grad_norm 3.3361 (2.6407/1.1345)	mem 16099MB
[2025-01-18 08:34:22 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][40/312]	eta 0:02:19 lr 0.000633	time 0.4481 (0.5141)	model_time 0.4479 (0.4652)	loss 3.2781 (2.9170)	grad_norm 2.3597 (2.4265/1.0749)	mem 16099MB
[2025-01-18 08:34:26 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][50/312]	eta 0:02:12 lr 0.000632	time 0.4476 (0.5051)	model_time 0.4474 (0.4658)	loss 3.3029 (2.9492)	grad_norm 2.4825 (2.3820/1.0088)	mem 16099MB
[2025-01-18 08:34:31 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][60/312]	eta 0:02:05 lr 0.000632	time 0.4557 (0.4985)	model_time 0.4553 (0.4656)	loss 3.0616 (2.9184)	grad_norm 2.8545 (2.3552/0.9723)	mem 16099MB
[2025-01-18 08:34:36 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][70/312]	eta 0:01:59 lr 0.000631	time 0.4505 (0.4948)	model_time 0.4500 (0.4664)	loss 2.1406 (2.9112)	grad_norm 2.3226 (2.3734/0.9889)	mem 16099MB
[2025-01-18 08:34:40 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][80/312]	eta 0:01:53 lr 0.000631	time 0.4725 (0.4905)	model_time 0.4722 (0.4655)	loss 2.7218 (2.8944)	grad_norm 1.4592 (2.3604/0.9851)	mem 16099MB
[2025-01-18 08:34:45 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][90/312]	eta 0:01:48 lr 0.000630	time 0.4371 (0.4869)	model_time 0.4366 (0.4647)	loss 2.4301 (2.8845)	grad_norm 1.5187 (2.3074/0.9739)	mem 16099MB
[2025-01-18 08:34:49 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][100/312]	eta 0:01:42 lr 0.000630	time 0.4365 (0.4851)	model_time 0.4361 (0.4650)	loss 1.9618 (2.8623)	grad_norm 1.6373 (2.2681/0.9408)	mem 16099MB
[2025-01-18 08:34:54 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][110/312]	eta 0:01:38 lr 0.000629	time 0.5488 (0.4860)	model_time 0.5486 (0.4677)	loss 3.1820 (2.8647)	grad_norm 1.9228 (2.2262/0.9191)	mem 16099MB
[2025-01-18 08:34:59 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][120/312]	eta 0:01:32 lr 0.000629	time 0.4570 (0.4839)	model_time 0.4568 (0.4671)	loss 2.8774 (2.8395)	grad_norm 1.5765 (2.2295/0.9110)	mem 16099MB
[2025-01-18 08:35:04 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][130/312]	eta 0:01:27 lr 0.000629	time 0.4496 (0.4830)	model_time 0.4494 (0.4674)	loss 3.2337 (2.8494)	grad_norm 1.2406 (2.2471/0.9182)	mem 16099MB
[2025-01-18 08:35:08 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][140/312]	eta 0:01:22 lr 0.000628	time 0.4484 (0.4820)	model_time 0.4480 (0.4674)	loss 3.1228 (2.8432)	grad_norm 2.4373 (2.2780/0.9269)	mem 16099MB
[2025-01-18 08:35:13 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][150/312]	eta 0:01:17 lr 0.000628	time 0.5535 (0.4813)	model_time 0.5534 (0.4677)	loss 2.5896 (2.8324)	grad_norm 5.3213 (2.3381/0.9784)	mem 16099MB
[2025-01-18 08:35:18 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][160/312]	eta 0:01:13 lr 0.000627	time 0.5339 (0.4811)	model_time 0.5334 (0.4683)	loss 3.1491 (2.8463)	grad_norm 1.6074 (2.4500/1.1456)	mem 16099MB
[2025-01-18 08:35:23 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][170/312]	eta 0:01:08 lr 0.000627	time 0.4580 (0.4802)	model_time 0.4575 (0.4682)	loss 2.0579 (2.8423)	grad_norm 1.5097 (2.4133/1.1320)	mem 16099MB
[2025-01-18 08:35:27 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][180/312]	eta 0:01:03 lr 0.000626	time 0.4469 (0.4791)	model_time 0.4465 (0.4677)	loss 3.0290 (2.8459)	grad_norm 2.1183 (2.3752/1.1185)	mem 16099MB
[2025-01-18 08:35:32 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][190/312]	eta 0:00:58 lr 0.000626	time 0.4484 (0.4783)	model_time 0.4479 (0.4675)	loss 3.1663 (2.8611)	grad_norm 2.4483 (2.3993/1.1093)	mem 16099MB
[2025-01-18 08:35:36 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][200/312]	eta 0:00:53 lr 0.000625	time 0.4514 (0.4771)	model_time 0.4509 (0.4668)	loss 3.0611 (2.8621)	grad_norm 2.4007 (2.4149/1.0980)	mem 16099MB
[2025-01-18 08:35:41 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][210/312]	eta 0:00:48 lr 0.000625	time 0.5495 (0.4764)	model_time 0.5490 (0.4666)	loss 2.5918 (2.8468)	grad_norm 6.1129 (2.4733/1.1967)	mem 16099MB
[2025-01-18 08:35:46 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][220/312]	eta 0:00:43 lr 0.000624	time 0.4501 (0.4756)	model_time 0.4497 (0.4661)	loss 1.8354 (2.8455)	grad_norm 1.1116 (2.4785/1.2021)	mem 16099MB
[2025-01-18 08:35:50 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][230/312]	eta 0:00:39 lr 0.000624	time 0.4409 (0.4756)	model_time 0.4407 (0.4666)	loss 2.4228 (2.8495)	grad_norm 2.1289 (2.4778/1.1937)	mem 16099MB
[2025-01-18 08:35:55 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][240/312]	eta 0:00:34 lr 0.000623	time 0.4589 (0.4751)	model_time 0.4584 (0.4665)	loss 2.2749 (2.8529)	grad_norm 1.6614 (2.4478/1.1839)	mem 16099MB
[2025-01-18 08:36:00 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][250/312]	eta 0:00:29 lr 0.000623	time 0.4629 (0.4746)	model_time 0.4624 (0.4663)	loss 2.2329 (2.8444)	grad_norm 2.3694 (2.4444/1.1661)	mem 16099MB
[2025-01-18 08:36:04 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][260/312]	eta 0:00:24 lr 0.000622	time 0.4596 (0.4741)	model_time 0.4594 (0.4660)	loss 3.5696 (2.8519)	grad_norm 1.6047 (2.4612/1.1677)	mem 16099MB
[2025-01-18 08:36:09 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][270/312]	eta 0:00:19 lr 0.000622	time 0.4538 (0.4740)	model_time 0.4537 (0.4662)	loss 3.1597 (2.8617)	grad_norm 1.9115 (2.4929/1.1843)	mem 16099MB
[2025-01-18 08:36:14 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][280/312]	eta 0:00:15 lr 0.000621	time 0.4496 (0.4736)	model_time 0.4491 (0.4661)	loss 2.6501 (2.8605)	grad_norm 2.3338 (2.4760/1.1742)	mem 16099MB
[2025-01-18 08:36:18 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][290/312]	eta 0:00:10 lr 0.000621	time 0.4517 (0.4729)	model_time 0.4512 (0.4656)	loss 3.0846 (2.8540)	grad_norm 1.3219 (2.4701/1.1626)	mem 16099MB
[2025-01-18 08:36:23 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][300/312]	eta 0:00:05 lr 0.000620	time 0.4384 (0.4727)	model_time 0.4383 (0.4656)	loss 3.0806 (2.8598)	grad_norm 1.7142 (2.4411/1.1303)	mem 16099MB
[2025-01-18 08:36:27 internimage_t_1k_224] (main.py 510): INFO Train: [224/300][310/312]	eta 0:00:00 lr 0.000620	time 0.4421 (0.4720)	model_time 0.4420 (0.4652)	loss 2.7224 (2.8653)	grad_norm 4.2015 (2.4498/1.1462)	mem 16099MB
[2025-01-18 08:36:28 internimage_t_1k_224] (main.py 519): INFO EPOCH 224 training takes 0:02:27
[2025-01-18 08:36:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_224.pth saving......
[2025-01-18 08:36:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_224.pth saved !!!
[2025-01-18 08:36:36 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.240 (7.240)	Loss 0.7522 (0.7522)	Acc@1 85.083 (85.083)	Acc@5 97.241 (97.241)	Mem 16099MB
[2025-01-18 08:36:40 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.979)	Loss 1.0255 (0.8679)	Acc@1 77.051 (81.938)	Acc@5 94.995 (95.958)	Mem 16099MB
[2025-01-18 08:36:40 internimage_t_1k_224] (main.py 575): INFO [Epoch:224] * Acc@1 81.866 Acc@5 95.987
[2025-01-18 08:36:40 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.9%
[2025-01-18 08:36:40 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.90%
[2025-01-18 08:36:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.192 (8.192)	Loss 0.7601 (0.7601)	Acc@1 85.571 (85.571)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 08:36:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.093)	Loss 1.0087 (0.8708)	Acc@1 78.784 (82.928)	Acc@5 95.239 (96.371)	Mem 16099MB
[2025-01-18 08:36:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:224] * Acc@1 82.788 Acc@5 96.393
[2025-01-18 08:36:52 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.8%
[2025-01-18 08:36:52 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:36:53 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:36:53 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.79%
[2025-01-18 08:36:56 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][0/312]	eta 0:12:20 lr 0.000620	time 2.3730 (2.3730)	model_time 0.4551 (0.4551)	loss 2.7730 (2.7730)	grad_norm 3.5375 (3.5375/0.0000)	mem 16099MB
[2025-01-18 08:37:00 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][10/312]	eta 0:03:17 lr 0.000619	time 0.4496 (0.6546)	model_time 0.4495 (0.4798)	loss 3.0348 (2.9009)	grad_norm 1.7911 (2.6193/1.1748)	mem 16099MB
[2025-01-18 08:37:05 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][20/312]	eta 0:02:45 lr 0.000619	time 0.4626 (0.5683)	model_time 0.4624 (0.4766)	loss 3.3028 (2.8516)	grad_norm 2.7176 (2.8950/1.2385)	mem 16099MB
[2025-01-18 08:37:10 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][30/312]	eta 0:02:31 lr 0.000619	time 0.4532 (0.5370)	model_time 0.4527 (0.4748)	loss 3.5690 (2.7814)	grad_norm 2.4374 (2.6964/1.2617)	mem 16099MB
[2025-01-18 08:37:14 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][40/312]	eta 0:02:21 lr 0.000618	time 0.4604 (0.5201)	model_time 0.4602 (0.4730)	loss 3.0866 (2.8434)	grad_norm 0.9241 (2.5250/1.2316)	mem 16099MB
[2025-01-18 08:37:19 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][50/312]	eta 0:02:13 lr 0.000618	time 0.4503 (0.5096)	model_time 0.4498 (0.4716)	loss 1.9069 (2.8173)	grad_norm 1.8258 (2.4831/1.1807)	mem 16099MB
[2025-01-18 08:37:24 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][60/312]	eta 0:02:06 lr 0.000617	time 0.4427 (0.5037)	model_time 0.4422 (0.4719)	loss 2.7370 (2.8078)	grad_norm 2.5634 (2.5097/1.1500)	mem 16099MB
[2025-01-18 08:37:28 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][70/312]	eta 0:02:00 lr 0.000617	time 0.4467 (0.4972)	model_time 0.4462 (0.4698)	loss 3.0693 (2.8320)	grad_norm 1.1383 (2.4897/1.1335)	mem 16099MB
[2025-01-18 08:37:33 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][80/312]	eta 0:01:54 lr 0.000616	time 0.5831 (0.4950)	model_time 0.5827 (0.4709)	loss 2.1172 (2.8205)	grad_norm 1.2342 (2.4618/1.1025)	mem 16099MB
[2025-01-18 08:37:38 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][90/312]	eta 0:01:49 lr 0.000616	time 0.4480 (0.4916)	model_time 0.4478 (0.4701)	loss 3.3443 (2.8400)	grad_norm 2.8041 (2.3894/1.0800)	mem 16099MB
[2025-01-18 08:37:43 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][100/312]	eta 0:01:43 lr 0.000615	time 0.4477 (0.4886)	model_time 0.4475 (0.4692)	loss 2.6175 (2.8594)	grad_norm 1.8582 (2.3213/1.0505)	mem 16099MB
[2025-01-18 08:37:47 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][110/312]	eta 0:01:38 lr 0.000615	time 0.4647 (0.4873)	model_time 0.4645 (0.4696)	loss 2.4260 (2.8449)	grad_norm 1.2666 (2.3244/1.0483)	mem 16099MB
[2025-01-18 08:37:52 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][120/312]	eta 0:01:33 lr 0.000614	time 0.4428 (0.4853)	model_time 0.4423 (0.4690)	loss 2.5617 (2.8454)	grad_norm 1.4600 (2.2834/1.0234)	mem 16099MB
[2025-01-18 08:37:57 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][130/312]	eta 0:01:27 lr 0.000614	time 0.4415 (0.4835)	model_time 0.4411 (0.4685)	loss 3.3841 (2.8556)	grad_norm 2.2485 (2.3148/1.0253)	mem 16099MB
[2025-01-18 08:38:01 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][140/312]	eta 0:01:23 lr 0.000613	time 0.4610 (0.4826)	model_time 0.4605 (0.4686)	loss 2.9618 (2.8670)	grad_norm 3.0516 (2.3228/1.0115)	mem 16099MB
[2025-01-18 08:38:06 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][150/312]	eta 0:01:17 lr 0.000613	time 0.4460 (0.4810)	model_time 0.4455 (0.4679)	loss 2.3530 (2.8783)	grad_norm 2.5139 (2.3464/1.0583)	mem 16099MB
[2025-01-18 08:38:10 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][160/312]	eta 0:01:12 lr 0.000612	time 0.4349 (0.4794)	model_time 0.4348 (0.4670)	loss 2.0926 (2.8792)	grad_norm 2.6400 (2.3711/1.0565)	mem 16099MB
[2025-01-18 08:38:15 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][170/312]	eta 0:01:07 lr 0.000612	time 0.4544 (0.4784)	model_time 0.4542 (0.4667)	loss 3.4409 (2.8779)	grad_norm 2.8893 (2.3954/1.0817)	mem 16099MB
[2025-01-18 08:38:19 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][180/312]	eta 0:01:02 lr 0.000611	time 0.4478 (0.4768)	model_time 0.4473 (0.4658)	loss 3.0887 (2.8909)	grad_norm 1.1942 (2.3805/1.0636)	mem 16099MB
[2025-01-18 08:38:24 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][190/312]	eta 0:00:58 lr 0.000611	time 0.4494 (0.4756)	model_time 0.4492 (0.4652)	loss 2.8829 (2.9008)	grad_norm 1.6079 (2.3812/1.0723)	mem 16099MB
[2025-01-18 08:38:29 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][200/312]	eta 0:00:53 lr 0.000611	time 0.4633 (0.4752)	model_time 0.4629 (0.4652)	loss 3.1152 (2.8966)	grad_norm 3.6535 (2.3676/1.0640)	mem 16099MB
[2025-01-18 08:38:33 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][210/312]	eta 0:00:48 lr 0.000610	time 0.4461 (0.4742)	model_time 0.4456 (0.4647)	loss 2.7777 (2.9052)	grad_norm 1.3935 (2.3857/1.0912)	mem 16099MB
[2025-01-18 08:38:38 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][220/312]	eta 0:00:43 lr 0.000610	time 0.4540 (0.4736)	model_time 0.4538 (0.4645)	loss 2.9932 (2.9095)	grad_norm 2.1647 (2.3742/1.0805)	mem 16099MB
[2025-01-18 08:38:42 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][230/312]	eta 0:00:38 lr 0.000609	time 0.4492 (0.4728)	model_time 0.4490 (0.4641)	loss 3.0320 (2.9025)	grad_norm 2.3977 (2.3465/1.0716)	mem 16099MB
[2025-01-18 08:38:47 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][240/312]	eta 0:00:34 lr 0.000609	time 0.5613 (0.4729)	model_time 0.5609 (0.4645)	loss 2.5090 (2.8996)	grad_norm 3.8097 (2.3720/1.0796)	mem 16099MB
[2025-01-18 08:38:52 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][250/312]	eta 0:00:29 lr 0.000608	time 0.4890 (0.4728)	model_time 0.4888 (0.4647)	loss 2.9766 (2.9004)	grad_norm 2.1395 (2.3698/1.0748)	mem 16099MB
[2025-01-18 08:38:57 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][260/312]	eta 0:00:24 lr 0.000608	time 0.4547 (0.4726)	model_time 0.4545 (0.4648)	loss 2.9084 (2.9030)	grad_norm 2.0948 (2.3747/1.0614)	mem 16099MB
[2025-01-18 08:39:01 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][270/312]	eta 0:00:19 lr 0.000607	time 0.4438 (0.4727)	model_time 0.4436 (0.4652)	loss 3.0856 (2.8986)	grad_norm 2.2836 (2.3905/1.0600)	mem 16099MB
[2025-01-18 08:39:06 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][280/312]	eta 0:00:15 lr 0.000607	time 0.4524 (0.4726)	model_time 0.4520 (0.4654)	loss 3.1567 (2.9030)	grad_norm 5.5407 (2.4007/1.0711)	mem 16099MB
[2025-01-18 08:39:11 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][290/312]	eta 0:00:10 lr 0.000606	time 0.4561 (0.4727)	model_time 0.4559 (0.4657)	loss 3.6265 (2.9012)	grad_norm 1.1204 (2.4350/1.0933)	mem 16099MB
[2025-01-18 08:39:15 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][300/312]	eta 0:00:05 lr 0.000606	time 0.4361 (0.4726)	model_time 0.4360 (0.4658)	loss 2.8261 (2.8973)	grad_norm 2.5581 (2.4348/1.0851)	mem 16099MB
[2025-01-18 08:39:20 internimage_t_1k_224] (main.py 510): INFO Train: [225/300][310/312]	eta 0:00:00 lr 0.000605	time 0.4423 (0.4722)	model_time 0.4422 (0.4656)	loss 2.0732 (2.8978)	grad_norm 1.1838 (2.4077/1.0733)	mem 16099MB
[2025-01-18 08:39:20 internimage_t_1k_224] (main.py 519): INFO EPOCH 225 training takes 0:02:27
[2025-01-18 08:39:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_225.pth saving......
[2025-01-18 08:39:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_225.pth saved !!!
[2025-01-18 08:39:29 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.236 (7.236)	Loss 0.7370 (0.7370)	Acc@1 84.326 (84.326)	Acc@5 97.144 (97.144)	Mem 16099MB
[2025-01-18 08:39:32 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.956)	Loss 0.9925 (0.8597)	Acc@1 77.637 (82.138)	Acc@5 94.922 (95.985)	Mem 16099MB
[2025-01-18 08:39:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:225] * Acc@1 81.928 Acc@5 95.973
[2025-01-18 08:39:32 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.9%
[2025-01-18 08:39:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 08:39:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 08:39:34 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.93%
[2025-01-18 08:39:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 6.949 (6.949)	Loss 0.7589 (0.7589)	Acc@1 85.596 (85.596)	Acc@5 97.583 (97.583)	Mem 16099MB
[2025-01-18 08:39:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.944)	Loss 1.0069 (0.8694)	Acc@1 78.857 (82.966)	Acc@5 95.264 (96.382)	Mem 16099MB
[2025-01-18 08:39:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:225] * Acc@1 82.829 Acc@5 96.405
[2025-01-18 08:39:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.8%
[2025-01-18 08:39:44 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:39:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:39:45 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.83%
[2025-01-18 08:39:47 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][0/312]	eta 0:10:44 lr 0.000605	time 2.0651 (2.0651)	model_time 0.6398 (0.6398)	loss 2.9382 (2.9382)	grad_norm 1.1766 (1.1766/0.0000)	mem 16099MB
[2025-01-18 08:39:52 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][10/312]	eta 0:03:07 lr 0.000605	time 0.4582 (0.6200)	model_time 0.4580 (0.4901)	loss 2.9228 (3.0301)	grad_norm 1.4374 (2.4301/1.2770)	mem 16099MB
[2025-01-18 08:39:57 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][20/312]	eta 0:02:45 lr 0.000604	time 0.4543 (0.5681)	model_time 0.4541 (0.4998)	loss 3.3058 (3.0435)	grad_norm 1.1419 (2.2988/1.0718)	mem 16099MB
[2025-01-18 08:40:02 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][30/312]	eta 0:02:30 lr 0.000604	time 0.4578 (0.5345)	model_time 0.4576 (0.4881)	loss 1.9960 (3.0582)	grad_norm 2.6343 (2.2833/0.9180)	mem 16099MB
[2025-01-18 08:40:06 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][40/312]	eta 0:02:20 lr 0.000603	time 0.4770 (0.5156)	model_time 0.4766 (0.4804)	loss 2.1846 (2.9722)	grad_norm 2.2678 (2.2167/0.8362)	mem 16099MB
[2025-01-18 08:40:11 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][50/312]	eta 0:02:13 lr 0.000603	time 0.4516 (0.5078)	model_time 0.4514 (0.4794)	loss 1.8512 (2.9630)	grad_norm 1.8270 (2.1163/0.8194)	mem 16099MB
[2025-01-18 08:40:16 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][60/312]	eta 0:02:05 lr 0.000603	time 0.4539 (0.4997)	model_time 0.4537 (0.4760)	loss 2.7557 (2.9638)	grad_norm 2.8291 (2.1279/0.7747)	mem 16099MB
[2025-01-18 08:40:20 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][70/312]	eta 0:01:59 lr 0.000602	time 0.4792 (0.4944)	model_time 0.4788 (0.4739)	loss 2.0922 (2.9340)	grad_norm 2.0202 (2.1114/0.7263)	mem 16099MB
[2025-01-18 08:40:25 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][80/312]	eta 0:01:54 lr 0.000602	time 0.4481 (0.4915)	model_time 0.4480 (0.4735)	loss 2.6761 (2.9364)	grad_norm 5.0553 (2.2433/0.8715)	mem 16099MB
[2025-01-18 08:40:30 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][90/312]	eta 0:01:48 lr 0.000601	time 0.4527 (0.4886)	model_time 0.4525 (0.4726)	loss 2.2377 (2.9544)	grad_norm 2.7372 (2.3086/0.9832)	mem 16099MB
[2025-01-18 08:40:34 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][100/312]	eta 0:01:42 lr 0.000601	time 0.4548 (0.4853)	model_time 0.4546 (0.4708)	loss 3.2124 (2.9532)	grad_norm 2.7874 (2.4036/1.1116)	mem 16099MB
[2025-01-18 08:40:39 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][110/312]	eta 0:01:37 lr 0.000600	time 0.4500 (0.4836)	model_time 0.4498 (0.4704)	loss 3.0656 (2.9363)	grad_norm 3.4437 (2.5133/1.1611)	mem 16099MB
[2025-01-18 08:40:44 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][120/312]	eta 0:01:32 lr 0.000600	time 0.4494 (0.4813)	model_time 0.4489 (0.4692)	loss 2.8954 (2.9280)	grad_norm 2.0088 (2.5760/1.1868)	mem 16099MB
[2025-01-18 08:40:48 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][130/312]	eta 0:01:27 lr 0.000599	time 0.4460 (0.4797)	model_time 0.4458 (0.4685)	loss 2.1969 (2.9267)	grad_norm 1.3223 (2.6176/1.2338)	mem 16099MB
[2025-01-18 08:40:53 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][140/312]	eta 0:01:22 lr 0.000599	time 0.5488 (0.4792)	model_time 0.5484 (0.4687)	loss 3.3006 (2.9250)	grad_norm 1.5119 (2.6242/1.2362)	mem 16099MB
[2025-01-18 08:40:57 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][150/312]	eta 0:01:17 lr 0.000598	time 0.4491 (0.4783)	model_time 0.4486 (0.4685)	loss 3.1128 (2.9280)	grad_norm 3.2767 (2.6606/1.2489)	mem 16099MB
[2025-01-18 08:41:02 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][160/312]	eta 0:01:12 lr 0.000598	time 0.5437 (0.4786)	model_time 0.5435 (0.4693)	loss 3.2463 (2.9341)	grad_norm 2.1351 (2.6354/1.2192)	mem 16099MB
[2025-01-18 08:41:07 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][170/312]	eta 0:01:07 lr 0.000597	time 0.4506 (0.4775)	model_time 0.4504 (0.4688)	loss 2.1603 (2.9381)	grad_norm 2.1474 (2.6125/1.1962)	mem 16099MB
[2025-01-18 08:41:12 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][180/312]	eta 0:01:02 lr 0.000597	time 0.5812 (0.4771)	model_time 0.5810 (0.4688)	loss 3.2004 (2.9414)	grad_norm 2.3878 (2.6214/1.1822)	mem 16099MB
[2025-01-18 08:41:16 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][190/312]	eta 0:00:58 lr 0.000597	time 0.4440 (0.4763)	model_time 0.4435 (0.4685)	loss 3.3744 (2.9444)	grad_norm 2.0528 (2.5901/1.1713)	mem 16099MB
[2025-01-18 08:41:21 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][200/312]	eta 0:00:53 lr 0.000596	time 0.4568 (0.4755)	model_time 0.4563 (0.4680)	loss 2.0032 (2.9434)	grad_norm 1.7827 (2.5784/1.1551)	mem 16099MB
[2025-01-18 08:41:26 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][210/312]	eta 0:00:48 lr 0.000596	time 0.4399 (0.4758)	model_time 0.4395 (0.4687)	loss 3.0619 (2.9419)	grad_norm 1.8289 (2.5685/1.1414)	mem 16099MB
[2025-01-18 08:41:30 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][220/312]	eta 0:00:43 lr 0.000595	time 0.4524 (0.4758)	model_time 0.4519 (0.4689)	loss 2.9572 (2.9453)	grad_norm 1.5815 (2.5690/1.1466)	mem 16099MB
[2025-01-18 08:41:35 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][230/312]	eta 0:00:38 lr 0.000595	time 0.4516 (0.4753)	model_time 0.4512 (0.4687)	loss 2.5434 (2.9386)	grad_norm 2.9725 (2.5816/1.1452)	mem 16099MB
[2025-01-18 08:41:40 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][240/312]	eta 0:00:34 lr 0.000594	time 0.4636 (0.4746)	model_time 0.4632 (0.4683)	loss 2.4189 (2.9272)	grad_norm 3.4496 (2.5540/1.1423)	mem 16099MB
[2025-01-18 08:41:44 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][250/312]	eta 0:00:29 lr 0.000594	time 0.5373 (0.4748)	model_time 0.5369 (0.4687)	loss 3.2731 (2.9263)	grad_norm 2.6997 (2.5486/1.1271)	mem 16099MB
[2025-01-18 08:41:49 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][260/312]	eta 0:00:24 lr 0.000593	time 0.4806 (0.4740)	model_time 0.4804 (0.4682)	loss 3.5495 (2.9217)	grad_norm 3.2158 (2.5373/1.1278)	mem 16099MB
[2025-01-18 08:41:54 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][270/312]	eta 0:00:19 lr 0.000593	time 0.4503 (0.4735)	model_time 0.4498 (0.4678)	loss 3.5498 (2.9200)	grad_norm 1.9976 (2.5376/1.1274)	mem 16099MB
[2025-01-18 08:41:58 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][280/312]	eta 0:00:15 lr 0.000592	time 0.4439 (0.4733)	model_time 0.4435 (0.4678)	loss 1.9600 (2.9069)	grad_norm 3.1358 (2.5345/1.1339)	mem 16099MB
[2025-01-18 08:42:03 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][290/312]	eta 0:00:10 lr 0.000592	time 0.4859 (0.4730)	model_time 0.4857 (0.4677)	loss 2.0251 (2.8948)	grad_norm 1.2833 (2.5244/1.1221)	mem 16099MB
[2025-01-18 08:42:08 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][300/312]	eta 0:00:05 lr 0.000591	time 0.4424 (0.4726)	model_time 0.4423 (0.4675)	loss 2.3972 (2.8954)	grad_norm 1.3157 (2.5473/1.1409)	mem 16099MB
[2025-01-18 08:42:12 internimage_t_1k_224] (main.py 510): INFO Train: [226/300][310/312]	eta 0:00:00 lr 0.000591	time 0.4373 (0.4717)	model_time 0.4372 (0.4667)	loss 3.3444 (2.8931)	grad_norm 1.0556 (2.5648/1.1513)	mem 16099MB
[2025-01-18 08:42:12 internimage_t_1k_224] (main.py 519): INFO EPOCH 226 training takes 0:02:27
[2025-01-18 08:42:12 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_226.pth saving......
[2025-01-18 08:42:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_226.pth saved !!!
[2025-01-18 08:42:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.062 (7.062)	Loss 0.7554 (0.7554)	Acc@1 84.009 (84.009)	Acc@5 97.266 (97.266)	Mem 16099MB
[2025-01-18 08:42:24 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.970)	Loss 1.0284 (0.8668)	Acc@1 77.563 (81.896)	Acc@5 94.507 (95.927)	Mem 16099MB
[2025-01-18 08:42:24 internimage_t_1k_224] (main.py 575): INFO [Epoch:226] * Acc@1 81.786 Acc@5 95.959
[2025-01-18 08:42:24 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.8%
[2025-01-18 08:42:24 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.93%
[2025-01-18 08:42:32 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.099 (8.099)	Loss 0.7582 (0.7582)	Acc@1 85.645 (85.645)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 08:42:36 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.076)	Loss 1.0055 (0.8684)	Acc@1 78.857 (83.008)	Acc@5 95.288 (96.382)	Mem 16099MB
[2025-01-18 08:42:36 internimage_t_1k_224] (main.py 575): INFO [Epoch:226] * Acc@1 82.871 Acc@5 96.405
[2025-01-18 08:42:36 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.9%
[2025-01-18 08:42:36 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:42:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:42:38 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.87%
[2025-01-18 08:42:40 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][0/312]	eta 0:10:49 lr 0.000591	time 2.0828 (2.0828)	model_time 0.4773 (0.4773)	loss 3.2920 (3.2920)	grad_norm 1.9456 (1.9456/0.0000)	mem 16099MB
[2025-01-18 08:42:44 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][10/312]	eta 0:03:06 lr 0.000590	time 0.4530 (0.6188)	model_time 0.4523 (0.4725)	loss 2.7528 (2.9806)	grad_norm 2.9667 (2.1227/0.5369)	mem 16099MB
[2025-01-18 08:42:49 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][20/312]	eta 0:02:39 lr 0.000590	time 0.4516 (0.5453)	model_time 0.4512 (0.4685)	loss 2.5559 (2.8495)	grad_norm 3.0539 (2.4221/0.8173)	mem 16099MB
[2025-01-18 08:42:54 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][30/312]	eta 0:02:26 lr 0.000590	time 0.4569 (0.5209)	model_time 0.4567 (0.4687)	loss 3.0263 (2.9086)	grad_norm 3.1763 (2.7715/1.2318)	mem 16099MB
[2025-01-18 08:42:58 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][40/312]	eta 0:02:17 lr 0.000589	time 0.4545 (0.5038)	model_time 0.4544 (0.4642)	loss 3.1639 (2.9281)	grad_norm 2.0460 (2.9840/1.4131)	mem 16099MB
[2025-01-18 08:43:03 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][50/312]	eta 0:02:10 lr 0.000589	time 0.4484 (0.4965)	model_time 0.4480 (0.4647)	loss 2.1498 (2.8979)	grad_norm 1.5954 (2.9487/1.4187)	mem 16099MB
[2025-01-18 08:43:07 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][60/312]	eta 0:02:03 lr 0.000588	time 0.4553 (0.4897)	model_time 0.4551 (0.4630)	loss 2.9033 (2.8624)	grad_norm 4.3614 (2.8885/1.3567)	mem 16099MB
[2025-01-18 08:43:12 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][70/312]	eta 0:01:57 lr 0.000588	time 0.4404 (0.4846)	model_time 0.4396 (0.4616)	loss 2.4772 (2.8793)	grad_norm 1.9039 (2.8800/1.3046)	mem 16099MB
[2025-01-18 08:43:17 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][80/312]	eta 0:01:51 lr 0.000587	time 0.4541 (0.4817)	model_time 0.4537 (0.4615)	loss 1.7457 (2.8704)	grad_norm 1.6128 (2.8364/1.2911)	mem 16099MB
[2025-01-18 08:43:21 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][90/312]	eta 0:01:46 lr 0.000587	time 0.4515 (0.4796)	model_time 0.4514 (0.4616)	loss 3.0437 (2.8964)	grad_norm 1.4505 (2.8071/1.2441)	mem 16099MB
[2025-01-18 08:43:26 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][100/312]	eta 0:01:41 lr 0.000586	time 0.4513 (0.4781)	model_time 0.4512 (0.4618)	loss 2.6601 (2.8791)	grad_norm 2.7963 (2.7808/1.2176)	mem 16099MB
[2025-01-18 08:43:30 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][110/312]	eta 0:01:36 lr 0.000586	time 0.4617 (0.4762)	model_time 0.4616 (0.4613)	loss 2.6581 (2.8609)	grad_norm 4.2474 (2.8795/1.3112)	mem 16099MB
[2025-01-18 08:43:35 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][120/312]	eta 0:01:31 lr 0.000585	time 0.4379 (0.4756)	model_time 0.4374 (0.4620)	loss 3.6026 (2.8783)	grad_norm 2.5634 (2.8677/1.2768)	mem 16099MB
[2025-01-18 08:43:40 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][130/312]	eta 0:01:26 lr 0.000585	time 0.4546 (0.4762)	model_time 0.4544 (0.4635)	loss 2.9315 (2.8997)	grad_norm 2.7110 (2.8363/1.2508)	mem 16099MB
[2025-01-18 08:43:45 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][140/312]	eta 0:01:21 lr 0.000584	time 0.4518 (0.4764)	model_time 0.4516 (0.4646)	loss 2.8081 (2.9134)	grad_norm 1.8192 (2.7766/1.2367)	mem 16099MB
[2025-01-18 08:43:50 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][150/312]	eta 0:01:17 lr 0.000584	time 0.4724 (0.4766)	model_time 0.4723 (0.4655)	loss 3.3656 (2.9202)	grad_norm 1.5737 (2.7178/1.2179)	mem 16099MB
[2025-01-18 08:43:54 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][160/312]	eta 0:01:12 lr 0.000584	time 0.4459 (0.4773)	model_time 0.4457 (0.4669)	loss 2.9988 (2.9184)	grad_norm 1.4014 (2.6804/1.2062)	mem 16099MB
[2025-01-18 08:43:59 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][170/312]	eta 0:01:07 lr 0.000583	time 0.4579 (0.4761)	model_time 0.4577 (0.4663)	loss 3.0344 (2.9065)	grad_norm 1.5638 (2.6541/1.1967)	mem 16099MB
[2025-01-18 08:44:04 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][180/312]	eta 0:01:02 lr 0.000583	time 0.4481 (0.4753)	model_time 0.4479 (0.4661)	loss 1.8520 (2.9004)	grad_norm 2.1625 (2.6435/1.1812)	mem 16099MB
[2025-01-18 08:44:08 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][190/312]	eta 0:00:57 lr 0.000582	time 0.4636 (0.4747)	model_time 0.4634 (0.4659)	loss 3.0838 (2.9103)	grad_norm 5.0940 (2.6595/1.1849)	mem 16099MB
[2025-01-18 08:44:13 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][200/312]	eta 0:00:53 lr 0.000582	time 0.4535 (0.4741)	model_time 0.4530 (0.4657)	loss 2.6137 (2.9129)	grad_norm 2.3399 (2.6449/1.1685)	mem 16099MB
[2025-01-18 08:44:17 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][210/312]	eta 0:00:48 lr 0.000581	time 0.4469 (0.4734)	model_time 0.4468 (0.4654)	loss 3.8031 (2.9117)	grad_norm 4.1215 (2.6629/1.1735)	mem 16099MB
[2025-01-18 08:44:22 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][220/312]	eta 0:00:43 lr 0.000581	time 0.4531 (0.4726)	model_time 0.4529 (0.4649)	loss 3.0218 (2.9217)	grad_norm 1.5946 (2.6243/1.1654)	mem 16099MB
[2025-01-18 08:44:27 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][230/312]	eta 0:00:38 lr 0.000580	time 0.4577 (0.4732)	model_time 0.4570 (0.4658)	loss 3.1080 (2.9262)	grad_norm 3.1763 (2.6178/1.1708)	mem 16099MB
[2025-01-18 08:44:32 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][240/312]	eta 0:00:34 lr 0.000580	time 0.4584 (0.4730)	model_time 0.4582 (0.4660)	loss 2.7651 (2.9157)	grad_norm 4.0552 (2.6363/1.1702)	mem 16099MB
[2025-01-18 08:44:36 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][250/312]	eta 0:00:29 lr 0.000579	time 0.4544 (0.4729)	model_time 0.4542 (0.4661)	loss 2.4926 (2.9067)	grad_norm 4.4126 (2.6727/1.1744)	mem 16099MB
[2025-01-18 08:44:41 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][260/312]	eta 0:00:24 lr 0.000579	time 0.4448 (0.4730)	model_time 0.4443 (0.4664)	loss 3.0553 (2.9043)	grad_norm 1.7524 (2.6697/1.1659)	mem 16099MB
[2025-01-18 08:44:46 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][270/312]	eta 0:00:19 lr 0.000579	time 0.4454 (0.4724)	model_time 0.4452 (0.4661)	loss 2.3869 (2.8970)	grad_norm 3.4512 (2.6612/1.1613)	mem 16099MB
[2025-01-18 08:44:50 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][280/312]	eta 0:00:15 lr 0.000578	time 0.4385 (0.4717)	model_time 0.4380 (0.4656)	loss 2.9404 (2.8957)	grad_norm 1.8869 (2.6643/1.1569)	mem 16099MB
[2025-01-18 08:44:55 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][290/312]	eta 0:00:10 lr 0.000578	time 0.4741 (0.4718)	model_time 0.4739 (0.4659)	loss 3.1084 (2.8943)	grad_norm 3.1812 (2.6543/1.1513)	mem 16099MB
[2025-01-18 08:45:00 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][300/312]	eta 0:00:05 lr 0.000577	time 0.4425 (0.4716)	model_time 0.4423 (0.4658)	loss 3.0770 (2.9000)	grad_norm 3.9620 (2.6491/1.1562)	mem 16099MB
[2025-01-18 08:45:04 internimage_t_1k_224] (main.py 510): INFO Train: [227/300][310/312]	eta 0:00:00 lr 0.000577	time 0.4398 (0.4706)	model_time 0.4397 (0.4651)	loss 2.3670 (2.8989)	grad_norm 2.6614 (2.6600/1.1549)	mem 16099MB
[2025-01-18 08:45:04 internimage_t_1k_224] (main.py 519): INFO EPOCH 227 training takes 0:02:26
[2025-01-18 08:45:04 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_227.pth saving......
[2025-01-18 08:45:05 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_227.pth saved !!!
[2025-01-18 08:45:13 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.469 (7.469)	Loss 0.7362 (0.7362)	Acc@1 83.911 (83.911)	Acc@5 97.144 (97.144)	Mem 16099MB
[2025-01-18 08:45:16 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.991)	Loss 0.9810 (0.8404)	Acc@1 78.149 (82.109)	Acc@5 94.775 (95.976)	Mem 16099MB
[2025-01-18 08:45:17 internimage_t_1k_224] (main.py 575): INFO [Epoch:227] * Acc@1 81.968 Acc@5 95.979
[2025-01-18 08:45:17 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.0%
[2025-01-18 08:45:17 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 08:45:18 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 08:45:18 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 81.97%
[2025-01-18 08:45:25 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.239 (7.239)	Loss 0.7571 (0.7571)	Acc@1 85.645 (85.645)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 08:45:29 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.982)	Loss 1.0040 (0.8671)	Acc@1 79.004 (83.046)	Acc@5 95.312 (96.398)	Mem 16099MB
[2025-01-18 08:45:29 internimage_t_1k_224] (main.py 575): INFO [Epoch:227] * Acc@1 82.909 Acc@5 96.417
[2025-01-18 08:45:29 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 82.9%
[2025-01-18 08:45:29 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:45:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:45:30 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.91%
[2025-01-18 08:45:32 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][0/312]	eta 0:11:20 lr 0.000577	time 2.1814 (2.1814)	model_time 0.5210 (0.5210)	loss 2.9011 (2.9011)	grad_norm 4.6184 (4.6184/0.0000)	mem 16099MB
[2025-01-18 08:45:37 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][10/312]	eta 0:03:12 lr 0.000576	time 0.4516 (0.6385)	model_time 0.4515 (0.4873)	loss 2.3336 (2.6544)	grad_norm 2.3355 (3.2370/1.4112)	mem 16099MB
[2025-01-18 08:45:42 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][20/312]	eta 0:02:42 lr 0.000576	time 0.4475 (0.5577)	model_time 0.4473 (0.4783)	loss 2.2419 (2.7874)	grad_norm 1.6036 (3.2090/1.4950)	mem 16099MB
[2025-01-18 08:45:46 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][30/312]	eta 0:02:28 lr 0.000575	time 0.4456 (0.5275)	model_time 0.4454 (0.4736)	loss 2.3634 (2.8315)	grad_norm 2.9403 (2.9719/1.3767)	mem 16099MB
[2025-01-18 08:45:51 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][40/312]	eta 0:02:18 lr 0.000575	time 0.4521 (0.5091)	model_time 0.4517 (0.4682)	loss 2.5494 (2.8681)	grad_norm 2.5091 (2.8096/1.2882)	mem 16099MB
[2025-01-18 08:45:55 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][50/312]	eta 0:02:10 lr 0.000574	time 0.4475 (0.4984)	model_time 0.4472 (0.4654)	loss 2.8453 (2.8968)	grad_norm 1.8311 (2.6835/1.2055)	mem 16099MB
[2025-01-18 08:46:00 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][60/312]	eta 0:02:04 lr 0.000574	time 0.4512 (0.4928)	model_time 0.4506 (0.4652)	loss 2.1797 (2.8494)	grad_norm 1.7874 (2.6504/1.1540)	mem 16099MB
[2025-01-18 08:46:05 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][70/312]	eta 0:01:58 lr 0.000573	time 0.4395 (0.4878)	model_time 0.4393 (0.4640)	loss 3.2314 (2.8523)	grad_norm 1.6510 (2.5810/1.1152)	mem 16099MB
[2025-01-18 08:46:09 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][80/312]	eta 0:01:52 lr 0.000573	time 0.4512 (0.4847)	model_time 0.4510 (0.4638)	loss 3.1841 (2.8604)	grad_norm 1.5656 (2.5772/1.1149)	mem 16099MB
[2025-01-18 08:46:14 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][90/312]	eta 0:01:46 lr 0.000573	time 0.4497 (0.4812)	model_time 0.4492 (0.4626)	loss 2.9544 (2.8532)	grad_norm 3.1764 (2.4926/1.0955)	mem 16099MB
[2025-01-18 08:46:19 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][100/312]	eta 0:01:42 lr 0.000572	time 0.4502 (0.4821)	model_time 0.4501 (0.4653)	loss 2.9805 (2.8712)	grad_norm 1.2221 (2.5165/1.1141)	mem 16099MB
[2025-01-18 08:46:24 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][110/312]	eta 0:01:37 lr 0.000572	time 0.4586 (0.4827)	model_time 0.4582 (0.4673)	loss 2.8021 (2.8930)	grad_norm 2.0788 (2.4681/1.0904)	mem 16099MB
[2025-01-18 08:46:29 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][120/312]	eta 0:01:33 lr 0.000571	time 0.4540 (0.4857)	model_time 0.4538 (0.4716)	loss 2.1020 (2.8822)	grad_norm 6.0235 (2.4817/1.1108)	mem 16099MB
[2025-01-18 08:46:34 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][130/312]	eta 0:01:28 lr 0.000571	time 0.4649 (0.4865)	model_time 0.4648 (0.4734)	loss 3.1555 (2.8885)	grad_norm 4.5845 (2.5090/1.0984)	mem 16099MB
[2025-01-18 08:46:39 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][140/312]	eta 0:01:23 lr 0.000570	time 0.4587 (0.4867)	model_time 0.4582 (0.4745)	loss 3.4989 (2.9027)	grad_norm 1.7023 (2.5459/1.1176)	mem 16099MB
[2025-01-18 08:46:43 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][150/312]	eta 0:01:18 lr 0.000570	time 0.4555 (0.4863)	model_time 0.4550 (0.4749)	loss 2.9438 (2.8834)	grad_norm 3.1217 (2.5398/1.1089)	mem 16099MB
[2025-01-18 08:46:48 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][160/312]	eta 0:01:13 lr 0.000569	time 0.4602 (0.4850)	model_time 0.4598 (0.4743)	loss 2.7557 (2.8716)	grad_norm 2.6113 (2.5258/1.0847)	mem 16099MB
[2025-01-18 08:46:53 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][170/312]	eta 0:01:08 lr 0.000569	time 0.4383 (0.4831)	model_time 0.4381 (0.4730)	loss 3.0367 (2.8754)	grad_norm 2.5791 (2.5309/1.0981)	mem 16099MB
[2025-01-18 08:46:57 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][180/312]	eta 0:01:03 lr 0.000568	time 0.4680 (0.4817)	model_time 0.4675 (0.4721)	loss 3.3019 (2.8855)	grad_norm 3.2698 (2.5410/1.0900)	mem 16099MB
[2025-01-18 08:47:02 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][190/312]	eta 0:00:58 lr 0.000568	time 0.4555 (0.4806)	model_time 0.4554 (0.4715)	loss 3.2854 (2.8633)	grad_norm 2.5400 (2.6228/1.2400)	mem 16099MB
[2025-01-18 08:47:07 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][200/312]	eta 0:00:53 lr 0.000568	time 0.4486 (0.4802)	model_time 0.4484 (0.4715)	loss 2.7041 (2.8532)	grad_norm 2.9296 (2.6636/1.2468)	mem 16099MB
[2025-01-18 08:47:11 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][210/312]	eta 0:00:48 lr 0.000567	time 0.5334 (0.4796)	model_time 0.5333 (0.4713)	loss 3.3232 (2.8463)	grad_norm 1.7700 (2.6247/1.2323)	mem 16099MB
[2025-01-18 08:47:16 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][220/312]	eta 0:00:44 lr 0.000567	time 0.4513 (0.4796)	model_time 0.4508 (0.4717)	loss 3.3841 (2.8384)	grad_norm 5.4321 (2.6277/1.2309)	mem 16099MB
[2025-01-18 08:47:21 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][230/312]	eta 0:00:39 lr 0.000566	time 0.4531 (0.4785)	model_time 0.4529 (0.4709)	loss 2.6944 (2.8380)	grad_norm 3.0189 (2.6192/1.2212)	mem 16099MB
[2025-01-18 08:47:25 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][240/312]	eta 0:00:34 lr 0.000566	time 0.4475 (0.4774)	model_time 0.4470 (0.4701)	loss 2.9782 (2.8325)	grad_norm 4.3630 (2.6283/1.2185)	mem 16099MB
[2025-01-18 08:47:30 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][250/312]	eta 0:00:29 lr 0.000565	time 0.4391 (0.4768)	model_time 0.4387 (0.4698)	loss 2.3943 (2.8382)	grad_norm 4.1506 (2.6327/1.2178)	mem 16099MB
[2025-01-18 08:47:34 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][260/312]	eta 0:00:24 lr 0.000565	time 0.4573 (0.4766)	model_time 0.4571 (0.4698)	loss 2.6664 (2.8458)	grad_norm 1.0308 (2.6100/1.2119)	mem 16099MB
[2025-01-18 08:47:39 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][270/312]	eta 0:00:19 lr 0.000564	time 0.4541 (0.4758)	model_time 0.4536 (0.4693)	loss 3.2295 (2.8468)	grad_norm 1.7877 (2.5948/1.2028)	mem 16099MB
[2025-01-18 08:47:44 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][280/312]	eta 0:00:15 lr 0.000564	time 0.4501 (0.4753)	model_time 0.4500 (0.4690)	loss 3.1834 (2.8557)	grad_norm 3.3963 (2.6014/1.2133)	mem 16099MB
[2025-01-18 08:47:48 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][290/312]	eta 0:00:10 lr 0.000564	time 0.4681 (0.4755)	model_time 0.4677 (0.4693)	loss 3.3352 (2.8445)	grad_norm 2.0351 (2.5960/1.2117)	mem 16099MB
[2025-01-18 08:47:53 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][300/312]	eta 0:00:05 lr 0.000563	time 0.4402 (0.4749)	model_time 0.4401 (0.4690)	loss 2.8984 (2.8481)	grad_norm 2.3518 (2.5938/1.2266)	mem 16099MB
[2025-01-18 08:47:57 internimage_t_1k_224] (main.py 510): INFO Train: [228/300][310/312]	eta 0:00:00 lr 0.000563	time 0.4423 (0.4741)	model_time 0.4422 (0.4684)	loss 3.0631 (2.8604)	grad_norm 2.7114 (2.5643/1.1937)	mem 16099MB
[2025-01-18 08:47:58 internimage_t_1k_224] (main.py 519): INFO EPOCH 228 training takes 0:02:27
[2025-01-18 08:47:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_228.pth saving......
[2025-01-18 08:47:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_228.pth saved !!!
[2025-01-18 08:48:06 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 6.970 (6.970)	Loss 0.7518 (0.7518)	Acc@1 84.375 (84.375)	Acc@5 97.217 (97.217)	Mem 16099MB
[2025-01-18 08:48:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.942)	Loss 1.0157 (0.8554)	Acc@1 77.271 (82.198)	Acc@5 94.580 (96.014)	Mem 16099MB
[2025-01-18 08:48:10 internimage_t_1k_224] (main.py 575): INFO [Epoch:228] * Acc@1 82.004 Acc@5 96.049
[2025-01-18 08:48:10 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.0%
[2025-01-18 08:48:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 08:48:11 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 08:48:11 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.00%
[2025-01-18 08:48:18 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 6.967 (6.967)	Loss 0.7562 (0.7562)	Acc@1 85.669 (85.669)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 08:48:21 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.949)	Loss 1.0028 (0.8660)	Acc@1 78.955 (83.079)	Acc@5 95.264 (96.400)	Mem 16099MB
[2025-01-18 08:48:21 internimage_t_1k_224] (main.py 575): INFO [Epoch:228] * Acc@1 82.953 Acc@5 96.417
[2025-01-18 08:48:21 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.0%
[2025-01-18 08:48:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:48:23 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:48:23 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.95%
[2025-01-18 08:48:25 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][0/312]	eta 0:11:17 lr 0.000563	time 2.1709 (2.1709)	model_time 0.4664 (0.4664)	loss 2.6775 (2.6775)	grad_norm 1.4164 (1.4164/0.0000)	mem 16099MB
[2025-01-18 08:48:30 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][10/312]	eta 0:03:14 lr 0.000562	time 0.4528 (0.6442)	model_time 0.4526 (0.4879)	loss 3.0448 (3.0268)	grad_norm 0.9503 (2.9311/1.3286)	mem 16099MB
[2025-01-18 08:48:34 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][20/312]	eta 0:02:42 lr 0.000562	time 0.4527 (0.5558)	model_time 0.4525 (0.4738)	loss 3.1304 (2.9529)	grad_norm 2.8018 (2.9901/1.2317)	mem 16099MB
[2025-01-18 08:48:39 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][30/312]	eta 0:02:29 lr 0.000561	time 0.4667 (0.5292)	model_time 0.4664 (0.4735)	loss 3.1667 (2.9303)	grad_norm 4.5308 (2.7118/1.3158)	mem 16099MB
[2025-01-18 08:48:44 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][40/312]	eta 0:02:18 lr 0.000561	time 0.4516 (0.5104)	model_time 0.4514 (0.4682)	loss 3.0938 (2.9124)	grad_norm 2.6939 (2.6432/1.2554)	mem 16099MB
[2025-01-18 08:48:48 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][50/312]	eta 0:02:11 lr 0.000560	time 0.4364 (0.5020)	model_time 0.4362 (0.4680)	loss 2.9473 (2.8997)	grad_norm 1.9254 (2.8899/1.5441)	mem 16099MB
[2025-01-18 08:48:53 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][60/312]	eta 0:02:04 lr 0.000560	time 0.4480 (0.4948)	model_time 0.4478 (0.4663)	loss 2.9431 (2.8727)	grad_norm 1.7803 (2.8196/1.5369)	mem 16099MB
[2025-01-18 08:48:58 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][70/312]	eta 0:01:59 lr 0.000559	time 0.5405 (0.4933)	model_time 0.5403 (0.4687)	loss 2.5482 (2.8252)	grad_norm 2.4812 (2.7168/1.4588)	mem 16099MB
[2025-01-18 08:49:02 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][80/312]	eta 0:01:53 lr 0.000559	time 0.4608 (0.4899)	model_time 0.4606 (0.4684)	loss 3.3022 (2.8182)	grad_norm 1.6217 (2.8055/1.4881)	mem 16099MB
[2025-01-18 08:49:07 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][90/312]	eta 0:01:48 lr 0.000558	time 0.4621 (0.4877)	model_time 0.4616 (0.4685)	loss 1.8972 (2.8055)	grad_norm 3.2861 (2.7434/1.4329)	mem 16099MB
[2025-01-18 08:49:12 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][100/312]	eta 0:01:42 lr 0.000558	time 0.4540 (0.4850)	model_time 0.4538 (0.4676)	loss 2.4948 (2.8044)	grad_norm 1.6331 (2.6887/1.4226)	mem 16099MB
[2025-01-18 08:49:16 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][110/312]	eta 0:01:37 lr 0.000558	time 0.4587 (0.4822)	model_time 0.4582 (0.4664)	loss 2.4210 (2.8040)	grad_norm 1.9910 (2.6129/1.3920)	mem 16099MB
[2025-01-18 08:49:21 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][120/312]	eta 0:01:32 lr 0.000557	time 0.5399 (0.4809)	model_time 0.5397 (0.4663)	loss 2.7963 (2.8094)	grad_norm 2.8700 (2.5627/1.3553)	mem 16099MB
[2025-01-18 08:49:26 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][130/312]	eta 0:01:27 lr 0.000557	time 0.4669 (0.4801)	model_time 0.4667 (0.4666)	loss 1.8874 (2.8098)	grad_norm 3.7210 (2.5741/1.3434)	mem 16099MB
[2025-01-18 08:49:30 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][140/312]	eta 0:01:22 lr 0.000556	time 0.4864 (0.4798)	model_time 0.4862 (0.4672)	loss 1.9580 (2.8113)	grad_norm 8.1568 (2.6661/1.4629)	mem 16099MB
[2025-01-18 08:49:35 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][150/312]	eta 0:01:17 lr 0.000556	time 0.4647 (0.4810)	model_time 0.4645 (0.4693)	loss 2.1646 (2.8113)	grad_norm 1.7051 (2.7986/1.5783)	mem 16099MB
[2025-01-18 08:49:40 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][160/312]	eta 0:01:12 lr 0.000555	time 0.4471 (0.4793)	model_time 0.4470 (0.4683)	loss 3.2481 (2.8183)	grad_norm 2.5548 (2.7989/1.5668)	mem 16099MB
[2025-01-18 08:49:44 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][170/312]	eta 0:01:07 lr 0.000555	time 0.4407 (0.4776)	model_time 0.4402 (0.4672)	loss 3.7736 (2.8313)	grad_norm 1.6482 (2.7718/1.5465)	mem 16099MB
[2025-01-18 08:49:49 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][180/312]	eta 0:01:03 lr 0.000554	time 0.4542 (0.4774)	model_time 0.4537 (0.4676)	loss 3.2546 (2.8418)	grad_norm 2.8745 (2.7576/1.5236)	mem 16099MB
[2025-01-18 08:49:54 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][190/312]	eta 0:00:58 lr 0.000554	time 0.5442 (0.4774)	model_time 0.5436 (0.4680)	loss 2.9011 (2.8432)	grad_norm 2.7018 (2.7193/1.5016)	mem 16099MB
[2025-01-18 08:49:59 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][200/312]	eta 0:00:53 lr 0.000554	time 0.4495 (0.4767)	model_time 0.4493 (0.4678)	loss 2.7788 (2.8322)	grad_norm 2.4088 (2.6981/1.4827)	mem 16099MB
[2025-01-18 08:50:03 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][210/312]	eta 0:00:48 lr 0.000553	time 0.4358 (0.4757)	model_time 0.4353 (0.4672)	loss 3.0060 (2.8325)	grad_norm 0.8788 (2.6550/1.4675)	mem 16099MB
[2025-01-18 08:50:08 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][220/312]	eta 0:00:43 lr 0.000553	time 0.4527 (0.4751)	model_time 0.4522 (0.4669)	loss 2.6610 (2.8323)	grad_norm 2.8053 (2.6417/1.4385)	mem 16099MB
[2025-01-18 08:50:12 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][230/312]	eta 0:00:38 lr 0.000552	time 0.4525 (0.4742)	model_time 0.4523 (0.4664)	loss 3.1269 (2.8422)	grad_norm 5.8466 (2.6715/1.4397)	mem 16099MB
[2025-01-18 08:50:17 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][240/312]	eta 0:00:34 lr 0.000552	time 0.4682 (0.4738)	model_time 0.4679 (0.4663)	loss 2.7738 (2.8428)	grad_norm 1.9251 (2.6827/1.4235)	mem 16099MB
[2025-01-18 08:50:22 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][250/312]	eta 0:00:29 lr 0.000551	time 0.5264 (0.4734)	model_time 0.5262 (0.4662)	loss 3.6364 (2.8555)	grad_norm 1.7915 (2.6586/1.4048)	mem 16099MB
[2025-01-18 08:50:26 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][260/312]	eta 0:00:24 lr 0.000551	time 0.4461 (0.4735)	model_time 0.4458 (0.4665)	loss 2.7417 (2.8615)	grad_norm 1.3891 (2.6407/1.3950)	mem 16099MB
[2025-01-18 08:50:31 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][270/312]	eta 0:00:19 lr 0.000550	time 0.4503 (0.4727)	model_time 0.4501 (0.4660)	loss 3.1449 (2.8571)	grad_norm 2.1407 (2.6521/1.3891)	mem 16099MB
[2025-01-18 08:50:36 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][280/312]	eta 0:00:15 lr 0.000550	time 0.4451 (0.4727)	model_time 0.4449 (0.4662)	loss 3.7694 (2.8582)	grad_norm 1.7695 (2.6288/1.3730)	mem 16099MB
[2025-01-18 08:50:40 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][290/312]	eta 0:00:10 lr 0.000550	time 0.4461 (0.4724)	model_time 0.4454 (0.4661)	loss 2.6392 (2.8560)	grad_norm 3.5425 (2.6079/1.3628)	mem 16099MB
[2025-01-18 08:50:45 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][300/312]	eta 0:00:05 lr 0.000549	time 0.4387 (0.4718)	model_time 0.4386 (0.4657)	loss 3.4024 (2.8604)	grad_norm 2.3987 (2.5898/1.3492)	mem 16099MB
[2025-01-18 08:50:50 internimage_t_1k_224] (main.py 510): INFO Train: [229/300][310/312]	eta 0:00:00 lr 0.000549	time 0.5502 (0.4728)	model_time 0.5501 (0.4669)	loss 3.0930 (2.8684)	grad_norm 1.6656 (2.5661/1.3307)	mem 16099MB
[2025-01-18 08:50:50 internimage_t_1k_224] (main.py 519): INFO EPOCH 229 training takes 0:02:27
[2025-01-18 08:50:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_229.pth saving......
[2025-01-18 08:50:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_229.pth saved !!!
[2025-01-18 08:50:59 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.064 (7.064)	Loss 0.7363 (0.7363)	Acc@1 84.619 (84.619)	Acc@5 97.339 (97.339)	Mem 16099MB
[2025-01-18 08:51:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.944)	Loss 1.0160 (0.8453)	Acc@1 77.905 (82.111)	Acc@5 94.434 (95.983)	Mem 16099MB
[2025-01-18 08:51:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:229] * Acc@1 81.920 Acc@5 95.995
[2025-01-18 08:51:02 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 81.9%
[2025-01-18 08:51:02 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.00%
[2025-01-18 08:51:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.150 (8.150)	Loss 0.7551 (0.7551)	Acc@1 85.693 (85.693)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 08:51:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.090)	Loss 1.0015 (0.8646)	Acc@1 79.028 (83.081)	Acc@5 95.312 (96.411)	Mem 16099MB
[2025-01-18 08:51:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:229] * Acc@1 82.957 Acc@5 96.425
[2025-01-18 08:51:14 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.0%
[2025-01-18 08:51:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:51:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:51:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.96%
[2025-01-18 08:51:18 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][0/312]	eta 0:11:19 lr 0.000549	time 2.1764 (2.1764)	model_time 0.4669 (0.4669)	loss 2.1923 (2.1923)	grad_norm 2.6552 (2.6552/0.0000)	mem 16099MB
[2025-01-18 08:51:22 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][10/312]	eta 0:03:13 lr 0.000548	time 0.4492 (0.6401)	model_time 0.4490 (0.4845)	loss 3.2591 (2.8349)	grad_norm 1.5908 (2.6598/1.1964)	mem 16099MB
[2025-01-18 08:51:27 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][20/312]	eta 0:02:42 lr 0.000548	time 0.4547 (0.5557)	model_time 0.4545 (0.4740)	loss 1.9724 (2.8578)	grad_norm 4.6263 (2.7684/1.0383)	mem 16099MB
[2025-01-18 08:51:32 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][30/312]	eta 0:02:31 lr 0.000547	time 0.4449 (0.5362)	model_time 0.4447 (0.4808)	loss 2.1419 (2.7444)	grad_norm 1.9717 (2.9384/1.2489)	mem 16099MB
[2025-01-18 08:51:37 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][40/312]	eta 0:02:20 lr 0.000547	time 0.4640 (0.5180)	model_time 0.4638 (0.4760)	loss 1.8927 (2.7473)	grad_norm 1.5710 (2.8644/1.1709)	mem 16099MB
[2025-01-18 08:51:41 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][50/312]	eta 0:02:12 lr 0.000546	time 0.4620 (0.5057)	model_time 0.4615 (0.4719)	loss 3.3337 (2.7754)	grad_norm 1.0615 (2.5880/1.1933)	mem 16099MB
[2025-01-18 08:51:46 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][60/312]	eta 0:02:05 lr 0.000546	time 0.4513 (0.4980)	model_time 0.4506 (0.4696)	loss 2.1590 (2.7656)	grad_norm 1.4433 (2.4833/1.1617)	mem 16099MB
[2025-01-18 08:51:50 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][70/312]	eta 0:01:59 lr 0.000545	time 0.5108 (0.4927)	model_time 0.5106 (0.4683)	loss 3.1679 (2.7883)	grad_norm 3.0063 (2.6486/1.2837)	mem 16099MB
[2025-01-18 08:51:55 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][80/312]	eta 0:01:53 lr 0.000545	time 0.4500 (0.4886)	model_time 0.4495 (0.4671)	loss 2.3776 (2.7967)	grad_norm 3.9799 (2.8866/1.5152)	mem 16099MB
[2025-01-18 08:52:00 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][90/312]	eta 0:01:47 lr 0.000545	time 0.4617 (0.4860)	model_time 0.4615 (0.4669)	loss 2.7690 (2.8145)	grad_norm 1.5000 (2.8994/1.4989)	mem 16099MB
[2025-01-18 08:52:04 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][100/312]	eta 0:01:42 lr 0.000544	time 0.4841 (0.4846)	model_time 0.4839 (0.4674)	loss 2.0557 (2.8064)	grad_norm 2.5880 (2.8225/1.4674)	mem 16099MB
[2025-01-18 08:52:09 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][110/312]	eta 0:01:37 lr 0.000544	time 0.4651 (0.4821)	model_time 0.4649 (0.4663)	loss 2.8601 (2.8056)	grad_norm 1.3987 (2.7692/1.4309)	mem 16099MB
[2025-01-18 08:52:14 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][120/312]	eta 0:01:32 lr 0.000543	time 0.4922 (0.4813)	model_time 0.4919 (0.4668)	loss 3.6130 (2.8008)	grad_norm 2.1820 (2.6927/1.4031)	mem 16099MB
[2025-01-18 08:52:18 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][130/312]	eta 0:01:27 lr 0.000543	time 0.4458 (0.4809)	model_time 0.4453 (0.4675)	loss 2.5338 (2.7827)	grad_norm 3.2385 (2.7009/1.3609)	mem 16099MB
[2025-01-18 08:52:23 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][140/312]	eta 0:01:22 lr 0.000542	time 0.4435 (0.4799)	model_time 0.4433 (0.4674)	loss 2.5126 (2.7784)	grad_norm 2.9911 (2.6531/1.3350)	mem 16099MB
[2025-01-18 08:52:28 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][150/312]	eta 0:01:17 lr 0.000542	time 0.4556 (0.4791)	model_time 0.4555 (0.4675)	loss 3.1354 (2.7697)	grad_norm 3.1295 (2.6782/1.3257)	mem 16099MB
[2025-01-18 08:52:32 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][160/312]	eta 0:01:12 lr 0.000541	time 0.5416 (0.4779)	model_time 0.5415 (0.4670)	loss 3.0023 (2.7698)	grad_norm 2.8406 (2.6820/1.3003)	mem 16099MB
[2025-01-18 08:52:37 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][170/312]	eta 0:01:07 lr 0.000541	time 0.4409 (0.4769)	model_time 0.4407 (0.4666)	loss 2.9119 (2.7642)	grad_norm 4.1284 (2.6680/1.2852)	mem 16099MB
[2025-01-18 08:52:41 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][180/312]	eta 0:01:02 lr 0.000541	time 0.4617 (0.4757)	model_time 0.4612 (0.4659)	loss 2.9767 (2.7683)	grad_norm 1.8357 (2.6573/1.2724)	mem 16099MB
[2025-01-18 08:52:46 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][190/312]	eta 0:00:57 lr 0.000540	time 0.4523 (0.4754)	model_time 0.4522 (0.4661)	loss 2.9648 (2.7775)	grad_norm 3.4946 (2.6751/1.2784)	mem 16099MB
[2025-01-18 08:52:51 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][200/312]	eta 0:00:53 lr 0.000540	time 0.4507 (0.4752)	model_time 0.4502 (0.4663)	loss 2.9381 (2.7779)	grad_norm 6.0535 (2.7274/1.3500)	mem 16099MB
[2025-01-18 08:52:55 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][210/312]	eta 0:00:48 lr 0.000539	time 0.4557 (0.4742)	model_time 0.4555 (0.4657)	loss 3.0170 (2.7877)	grad_norm 3.2177 (2.7310/1.3257)	mem 16099MB
[2025-01-18 08:53:00 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][220/312]	eta 0:00:43 lr 0.000539	time 0.4600 (0.4732)	model_time 0.4597 (0.4652)	loss 1.9351 (2.7924)	grad_norm 2.9271 (2.7603/1.3508)	mem 16099MB
[2025-01-18 08:53:04 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][230/312]	eta 0:00:38 lr 0.000538	time 0.4420 (0.4725)	model_time 0.4415 (0.4647)	loss 3.1642 (2.8046)	grad_norm 1.8265 (2.7314/1.3400)	mem 16099MB
[2025-01-18 08:53:09 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][240/312]	eta 0:00:34 lr 0.000538	time 0.5473 (0.4723)	model_time 0.5472 (0.4648)	loss 3.4420 (2.8098)	grad_norm 2.2534 (2.7073/1.3239)	mem 16099MB
[2025-01-18 08:53:14 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][250/312]	eta 0:00:29 lr 0.000538	time 0.4395 (0.4737)	model_time 0.4394 (0.4665)	loss 2.9917 (2.8131)	grad_norm 1.9913 (2.6704/1.3124)	mem 16099MB
[2025-01-18 08:53:19 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][260/312]	eta 0:00:24 lr 0.000537	time 0.4493 (0.4731)	model_time 0.4491 (0.4662)	loss 2.9610 (2.8210)	grad_norm 8.0143 (2.6798/1.3422)	mem 16099MB
[2025-01-18 08:53:24 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][270/312]	eta 0:00:19 lr 0.000537	time 0.4511 (0.4731)	model_time 0.4510 (0.4664)	loss 3.1440 (2.8195)	grad_norm 3.4459 (2.6935/1.3456)	mem 16099MB
[2025-01-18 08:53:28 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][280/312]	eta 0:00:15 lr 0.000536	time 0.4536 (0.4725)	model_time 0.4534 (0.4661)	loss 3.3304 (2.8195)	grad_norm 2.2736 (2.6862/1.3296)	mem 16099MB
[2025-01-18 08:53:33 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][290/312]	eta 0:00:10 lr 0.000536	time 0.4601 (0.4726)	model_time 0.4599 (0.4664)	loss 3.2612 (2.8193)	grad_norm 3.1197 (2.6729/1.3193)	mem 16099MB
[2025-01-18 08:53:38 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][300/312]	eta 0:00:05 lr 0.000535	time 0.4388 (0.4724)	model_time 0.4387 (0.4664)	loss 3.2133 (2.8139)	grad_norm 1.1915 (2.6806/1.3201)	mem 16099MB
[2025-01-18 08:53:42 internimage_t_1k_224] (main.py 510): INFO Train: [230/300][310/312]	eta 0:00:00 lr 0.000535	time 0.4378 (0.4721)	model_time 0.4377 (0.4663)	loss 2.7827 (2.8167)	grad_norm 3.6173 (2.6992/1.3195)	mem 16099MB
[2025-01-18 08:53:43 internimage_t_1k_224] (main.py 519): INFO EPOCH 230 training takes 0:02:27
[2025-01-18 08:53:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_230.pth saving......
[2025-01-18 08:53:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_230.pth saved !!!
[2025-01-18 08:53:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.367 (7.367)	Loss 0.7417 (0.7417)	Acc@1 85.059 (85.059)	Acc@5 97.412 (97.412)	Mem 16099MB
[2025-01-18 08:53:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.987)	Loss 0.9973 (0.8516)	Acc@1 78.271 (82.417)	Acc@5 94.604 (96.098)	Mem 16099MB
[2025-01-18 08:53:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:230] * Acc@1 82.224 Acc@5 96.111
[2025-01-18 08:53:55 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.2%
[2025-01-18 08:53:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 08:53:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 08:53:56 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.22%
[2025-01-18 08:54:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.268 (7.268)	Loss 0.7542 (0.7542)	Acc@1 85.742 (85.742)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 08:54:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.980)	Loss 1.0001 (0.8634)	Acc@1 79.053 (83.081)	Acc@5 95.288 (96.413)	Mem 16099MB
[2025-01-18 08:54:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:230] * Acc@1 82.961 Acc@5 96.427
[2025-01-18 08:54:07 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.0%
[2025-01-18 08:54:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:54:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:54:08 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.96%
[2025-01-18 08:54:10 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][0/312]	eta 0:11:40 lr 0.000535	time 2.2442 (2.2442)	model_time 0.4683 (0.4683)	loss 3.0660 (3.0660)	grad_norm 3.1370 (3.1370/0.0000)	mem 16099MB
[2025-01-18 08:54:15 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][10/312]	eta 0:03:08 lr 0.000534	time 0.4497 (0.6243)	model_time 0.4496 (0.4625)	loss 3.4273 (2.9671)	grad_norm 3.0180 (3.6867/1.3818)	mem 16099MB
[2025-01-18 08:54:20 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][20/312]	eta 0:02:39 lr 0.000534	time 0.4544 (0.5470)	model_time 0.4542 (0.4621)	loss 2.5886 (2.9338)	grad_norm 2.1650 (3.1035/1.2903)	mem 16099MB
[2025-01-18 08:54:24 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][30/312]	eta 0:02:27 lr 0.000533	time 0.4476 (0.5221)	model_time 0.4470 (0.4644)	loss 2.9672 (2.9261)	grad_norm 4.9124 (2.9564/1.2845)	mem 16099MB
[2025-01-18 08:54:29 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][40/312]	eta 0:02:18 lr 0.000533	time 0.4632 (0.5106)	model_time 0.4628 (0.4669)	loss 3.2987 (2.9685)	grad_norm 5.2920 (2.9492/1.2891)	mem 16099MB
[2025-01-18 08:54:34 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][50/312]	eta 0:02:11 lr 0.000533	time 0.4508 (0.5007)	model_time 0.4506 (0.4655)	loss 2.9367 (2.9486)	grad_norm 2.6304 (2.9218/1.2646)	mem 16099MB
[2025-01-18 08:54:38 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][60/312]	eta 0:02:04 lr 0.000532	time 0.4682 (0.4937)	model_time 0.4681 (0.4642)	loss 3.0708 (2.9154)	grad_norm 2.0990 (2.7383/1.2463)	mem 16099MB
[2025-01-18 08:54:43 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][70/312]	eta 0:01:58 lr 0.000532	time 0.4561 (0.4890)	model_time 0.4559 (0.4636)	loss 2.6424 (2.8795)	grad_norm 3.5388 (2.6628/1.2191)	mem 16099MB
[2025-01-18 08:54:47 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][80/312]	eta 0:01:52 lr 0.000531	time 0.4578 (0.4867)	model_time 0.4576 (0.4644)	loss 2.0424 (2.8701)	grad_norm 1.3201 (2.6411/1.2141)	mem 16099MB
[2025-01-18 08:54:52 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][90/312]	eta 0:01:47 lr 0.000531	time 0.4533 (0.4840)	model_time 0.4532 (0.4642)	loss 3.5387 (2.8633)	grad_norm 4.4493 (2.6947/1.2028)	mem 16099MB
[2025-01-18 08:54:57 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][100/312]	eta 0:01:42 lr 0.000530	time 0.4495 (0.4822)	model_time 0.4493 (0.4643)	loss 2.5078 (2.8454)	grad_norm 1.1869 (2.6357/1.1819)	mem 16099MB
[2025-01-18 08:55:02 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][110/312]	eta 0:01:37 lr 0.000530	time 0.4538 (0.4821)	model_time 0.4537 (0.4657)	loss 3.7198 (2.8411)	grad_norm 3.5747 (2.6391/1.1587)	mem 16099MB
[2025-01-18 08:55:06 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][120/312]	eta 0:01:32 lr 0.000530	time 0.4726 (0.4810)	model_time 0.4722 (0.4659)	loss 3.0059 (2.8209)	grad_norm 1.9745 (2.5849/1.1427)	mem 16099MB
[2025-01-18 08:55:11 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][130/312]	eta 0:01:27 lr 0.000529	time 0.4487 (0.4799)	model_time 0.4486 (0.4659)	loss 2.8305 (2.8269)	grad_norm 2.1054 (2.6113/1.1637)	mem 16099MB
[2025-01-18 08:55:16 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][140/312]	eta 0:01:22 lr 0.000529	time 0.5694 (0.4787)	model_time 0.5690 (0.4658)	loss 3.1911 (2.8427)	grad_norm 5.6346 (2.6868/1.1983)	mem 16099MB
[2025-01-18 08:55:20 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][150/312]	eta 0:01:17 lr 0.000528	time 0.4465 (0.4785)	model_time 0.4463 (0.4664)	loss 2.7731 (2.8513)	grad_norm 1.6091 (2.7181/1.2275)	mem 16099MB
[2025-01-18 08:55:25 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][160/312]	eta 0:01:12 lr 0.000528	time 0.4542 (0.4779)	model_time 0.4538 (0.4666)	loss 3.2755 (2.8634)	grad_norm 3.0264 (2.6667/1.2197)	mem 16099MB
[2025-01-18 08:55:30 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][170/312]	eta 0:01:07 lr 0.000527	time 0.4457 (0.4766)	model_time 0.4455 (0.4658)	loss 1.9851 (2.8563)	grad_norm 2.4287 (2.6256/1.2152)	mem 16099MB
[2025-01-18 08:55:34 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][180/312]	eta 0:01:02 lr 0.000527	time 0.4518 (0.4754)	model_time 0.4513 (0.4652)	loss 3.2704 (2.8465)	grad_norm 3.0847 (2.6265/1.2005)	mem 16099MB
[2025-01-18 08:55:39 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][190/312]	eta 0:00:57 lr 0.000526	time 0.4494 (0.4746)	model_time 0.4492 (0.4649)	loss 3.6374 (2.8600)	grad_norm 3.7442 (2.6178/1.1862)	mem 16099MB
[2025-01-18 08:55:43 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][200/312]	eta 0:00:53 lr 0.000526	time 0.5807 (0.4742)	model_time 0.5803 (0.4650)	loss 2.4447 (2.8669)	grad_norm 1.6353 (2.6117/1.1842)	mem 16099MB
[2025-01-18 08:55:48 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][210/312]	eta 0:00:48 lr 0.000526	time 0.4838 (0.4739)	model_time 0.4834 (0.4651)	loss 3.1817 (2.8775)	grad_norm 1.9844 (2.6074/1.1711)	mem 16099MB
[2025-01-18 08:55:53 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][220/312]	eta 0:00:43 lr 0.000525	time 0.4564 (0.4732)	model_time 0.4560 (0.4648)	loss 3.2816 (2.8833)	grad_norm 4.5676 (2.5995/1.1672)	mem 16099MB
[2025-01-18 08:55:57 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][230/312]	eta 0:00:38 lr 0.000525	time 0.4593 (0.4724)	model_time 0.4589 (0.4643)	loss 3.0755 (2.8824)	grad_norm 1.6573 (2.5657/1.1648)	mem 16099MB
[2025-01-18 08:56:02 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][240/312]	eta 0:00:34 lr 0.000524	time 0.4865 (0.4722)	model_time 0.4860 (0.4645)	loss 3.1076 (2.8850)	grad_norm 1.8959 (2.5361/1.1595)	mem 16099MB
[2025-01-18 08:56:06 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][250/312]	eta 0:00:29 lr 0.000524	time 0.4516 (0.4716)	model_time 0.4512 (0.4641)	loss 3.3890 (2.8820)	grad_norm 7.2596 (2.5512/1.1913)	mem 16099MB
[2025-01-18 08:56:11 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][260/312]	eta 0:00:24 lr 0.000523	time 0.4475 (0.4716)	model_time 0.4473 (0.4644)	loss 3.2772 (2.8772)	grad_norm 3.3541 (2.5503/1.1744)	mem 16099MB
[2025-01-18 08:56:16 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][270/312]	eta 0:00:19 lr 0.000523	time 0.4478 (0.4714)	model_time 0.4476 (0.4644)	loss 2.4539 (2.8770)	grad_norm 4.6264 (2.5798/1.1983)	mem 16099MB
[2025-01-18 08:56:21 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][280/312]	eta 0:00:15 lr 0.000523	time 0.4430 (0.4720)	model_time 0.4425 (0.4653)	loss 2.5989 (2.8750)	grad_norm 3.5267 (2.5991/1.1982)	mem 16099MB
[2025-01-18 08:56:25 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][290/312]	eta 0:00:10 lr 0.000522	time 0.4499 (0.4719)	model_time 0.4497 (0.4654)	loss 2.6414 (2.8718)	grad_norm 1.8010 (2.5894/1.1920)	mem 16099MB
[2025-01-18 08:56:30 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][300/312]	eta 0:00:05 lr 0.000522	time 0.5460 (0.4715)	model_time 0.5459 (0.4652)	loss 3.6695 (2.8676)	grad_norm 1.4953 (2.5623/1.1829)	mem 16099MB
[2025-01-18 08:56:34 internimage_t_1k_224] (main.py 510): INFO Train: [231/300][310/312]	eta 0:00:00 lr 0.000521	time 0.4378 (0.4706)	model_time 0.4377 (0.4645)	loss 2.9609 (2.8617)	grad_norm 2.3726 (2.4985/1.1426)	mem 16099MB
[2025-01-18 08:56:35 internimage_t_1k_224] (main.py 519): INFO EPOCH 231 training takes 0:02:26
[2025-01-18 08:56:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_231.pth saving......
[2025-01-18 08:56:36 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_231.pth saved !!!
[2025-01-18 08:56:43 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.178 (7.178)	Loss 0.7141 (0.7141)	Acc@1 84.741 (84.741)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 08:56:47 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (0.952)	Loss 0.9708 (0.8266)	Acc@1 78.149 (82.264)	Acc@5 94.629 (96.145)	Mem 16099MB
[2025-01-18 08:56:47 internimage_t_1k_224] (main.py 575): INFO [Epoch:231] * Acc@1 82.084 Acc@5 96.141
[2025-01-18 08:56:47 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.1%
[2025-01-18 08:56:47 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.22%
[2025-01-18 08:56:55 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.176 (8.176)	Loss 0.7532 (0.7532)	Acc@1 85.742 (85.742)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 08:56:59 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.079)	Loss 0.9988 (0.8623)	Acc@1 79.053 (83.101)	Acc@5 95.288 (96.409)	Mem 16099MB
[2025-01-18 08:56:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:231] * Acc@1 82.983 Acc@5 96.423
[2025-01-18 08:56:59 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.0%
[2025-01-18 08:56:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:57:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:57:00 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.98%
[2025-01-18 08:57:02 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][0/312]	eta 0:12:30 lr 0.000521	time 2.4043 (2.4043)	model_time 0.4767 (0.4767)	loss 2.8735 (2.8735)	grad_norm 2.6199 (2.6199/0.0000)	mem 16099MB
[2025-01-18 08:57:07 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][10/312]	eta 0:03:13 lr 0.000521	time 0.4587 (0.6421)	model_time 0.4586 (0.4666)	loss 2.2090 (3.0292)	grad_norm 3.6125 (3.4748/1.5481)	mem 16099MB
[2025-01-18 08:57:12 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][20/312]	eta 0:02:44 lr 0.000520	time 0.5693 (0.5618)	model_time 0.5688 (0.4697)	loss 2.9486 (2.8371)	grad_norm 2.4944 (3.1212/1.4326)	mem 16099MB
[2025-01-18 08:57:17 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][30/312]	eta 0:02:31 lr 0.000520	time 0.4509 (0.5377)	model_time 0.4504 (0.4752)	loss 2.3747 (2.8266)	grad_norm 2.2598 (3.0903/1.3647)	mem 16099MB
[2025-01-18 08:57:22 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][40/312]	eta 0:02:23 lr 0.000519	time 0.4708 (0.5261)	model_time 0.4703 (0.4788)	loss 2.3438 (2.7625)	grad_norm 1.5278 (3.0971/1.3833)	mem 16099MB
[2025-01-18 08:57:26 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][50/312]	eta 0:02:14 lr 0.000519	time 0.4865 (0.5152)	model_time 0.4864 (0.4771)	loss 3.1746 (2.7675)	grad_norm 3.5939 (3.2048/1.3937)	mem 16099MB
[2025-01-18 08:57:31 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][60/312]	eta 0:02:07 lr 0.000519	time 0.4583 (0.5068)	model_time 0.4581 (0.4748)	loss 3.4265 (2.7556)	grad_norm 1.8822 (3.0778/1.3572)	mem 16099MB
[2025-01-18 08:57:36 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][70/312]	eta 0:02:00 lr 0.000518	time 0.4531 (0.4992)	model_time 0.4527 (0.4717)	loss 3.0195 (2.7923)	grad_norm 1.8842 (3.0575/1.3472)	mem 16099MB
[2025-01-18 08:57:40 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][80/312]	eta 0:01:54 lr 0.000518	time 0.4524 (0.4949)	model_time 0.4522 (0.4708)	loss 2.4569 (2.7988)	grad_norm 1.5114 (2.9883/1.3061)	mem 16099MB
[2025-01-18 08:57:45 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][90/312]	eta 0:01:48 lr 0.000517	time 0.4554 (0.4905)	model_time 0.4552 (0.4690)	loss 2.0679 (2.8140)	grad_norm 1.5577 (2.9409/1.3075)	mem 16099MB
[2025-01-18 08:57:49 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][100/312]	eta 0:01:43 lr 0.000517	time 0.4498 (0.4890)	model_time 0.4493 (0.4696)	loss 2.8617 (2.7979)	grad_norm 1.7969 (2.8227/1.3002)	mem 16099MB
[2025-01-18 08:57:54 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][110/312]	eta 0:01:38 lr 0.000516	time 0.4506 (0.4864)	model_time 0.4504 (0.4687)	loss 2.2822 (2.7945)	grad_norm 2.7807 (2.7729/1.2606)	mem 16099MB
[2025-01-18 08:57:59 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][120/312]	eta 0:01:33 lr 0.000516	time 0.4474 (0.4846)	model_time 0.4473 (0.4683)	loss 3.2266 (2.8017)	grad_norm 1.9503 (2.7553/1.2414)	mem 16099MB
[2025-01-18 08:58:04 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][130/312]	eta 0:01:28 lr 0.000516	time 0.4623 (0.4847)	model_time 0.4621 (0.4696)	loss 2.4870 (2.7796)	grad_norm 2.6332 (2.7490/1.2211)	mem 16099MB
[2025-01-18 08:58:08 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][140/312]	eta 0:01:23 lr 0.000515	time 0.5899 (0.4849)	model_time 0.5897 (0.4709)	loss 3.1259 (2.7830)	grad_norm 4.1834 (2.7057/1.2069)	mem 16099MB
[2025-01-18 08:58:13 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][150/312]	eta 0:01:18 lr 0.000515	time 0.4502 (0.4839)	model_time 0.4498 (0.4708)	loss 3.1471 (2.7703)	grad_norm 4.5278 (2.7406/1.2084)	mem 16099MB
[2025-01-18 08:58:18 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][160/312]	eta 0:01:13 lr 0.000514	time 0.4464 (0.4827)	model_time 0.4460 (0.4703)	loss 2.0470 (2.7743)	grad_norm 2.5773 (2.7529/1.1997)	mem 16099MB
[2025-01-18 08:58:22 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][170/312]	eta 0:01:08 lr 0.000514	time 0.4484 (0.4814)	model_time 0.4482 (0.4697)	loss 2.2331 (2.7822)	grad_norm 1.7428 (2.7414/1.1863)	mem 16099MB
[2025-01-18 08:58:27 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][180/312]	eta 0:01:03 lr 0.000513	time 0.4561 (0.4802)	model_time 0.4557 (0.4692)	loss 2.3514 (2.7657)	grad_norm 2.8317 (2.7113/1.1685)	mem 16099MB
[2025-01-18 08:58:32 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][190/312]	eta 0:00:58 lr 0.000513	time 0.4598 (0.4796)	model_time 0.4597 (0.4692)	loss 3.2522 (2.7657)	grad_norm 2.2780 (2.6769/1.1515)	mem 16099MB
[2025-01-18 08:58:36 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][200/312]	eta 0:00:53 lr 0.000512	time 0.4490 (0.4787)	model_time 0.4485 (0.4687)	loss 2.8979 (2.7662)	grad_norm 1.9070 (2.6525/1.1342)	mem 16099MB
[2025-01-18 08:58:41 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][210/312]	eta 0:00:48 lr 0.000512	time 0.4487 (0.4778)	model_time 0.4486 (0.4683)	loss 3.2535 (2.7707)	grad_norm 1.7336 (2.6569/1.1336)	mem 16099MB
[2025-01-18 08:58:46 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][220/312]	eta 0:00:43 lr 0.000512	time 0.4527 (0.4773)	model_time 0.4526 (0.4682)	loss 2.5451 (2.7615)	grad_norm 1.7031 (2.6524/1.1429)	mem 16099MB
[2025-01-18 08:58:50 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][230/312]	eta 0:00:39 lr 0.000511	time 0.4529 (0.4767)	model_time 0.4525 (0.4680)	loss 1.8703 (2.7596)	grad_norm 1.3515 (2.6424/1.1389)	mem 16099MB
[2025-01-18 08:58:55 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][240/312]	eta 0:00:34 lr 0.000511	time 0.4615 (0.4758)	model_time 0.4611 (0.4674)	loss 3.0942 (2.7611)	grad_norm 2.8839 (2.6703/1.1515)	mem 16099MB
[2025-01-18 08:58:59 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][250/312]	eta 0:00:29 lr 0.000510	time 0.4510 (0.4752)	model_time 0.4509 (0.4672)	loss 3.1316 (2.7692)	grad_norm 1.4297 (2.6806/1.1452)	mem 16099MB
[2025-01-18 08:59:04 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][260/312]	eta 0:00:24 lr 0.000510	time 0.4530 (0.4765)	model_time 0.4526 (0.4688)	loss 2.9785 (2.7833)	grad_norm 2.2888 (2.6947/1.1504)	mem 16099MB
[2025-01-18 08:59:09 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][270/312]	eta 0:00:20 lr 0.000509	time 0.4577 (0.4764)	model_time 0.4576 (0.4689)	loss 3.7216 (2.7899)	grad_norm 3.4138 (2.7108/1.1501)	mem 16099MB
[2025-01-18 08:59:14 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][280/312]	eta 0:00:15 lr 0.000509	time 0.4619 (0.4760)	model_time 0.4617 (0.4687)	loss 3.2925 (2.7963)	grad_norm 3.6671 (2.7116/1.1503)	mem 16099MB
[2025-01-18 08:59:19 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][290/312]	eta 0:00:10 lr 0.000509	time 0.4495 (0.4762)	model_time 0.4493 (0.4692)	loss 3.0719 (2.7884)	grad_norm 0.8997 (2.7137/1.1547)	mem 16099MB
[2025-01-18 08:59:23 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][300/312]	eta 0:00:05 lr 0.000508	time 0.4390 (0.4756)	model_time 0.4389 (0.4688)	loss 2.2498 (2.7916)	grad_norm 1.8300 (2.7131/1.1494)	mem 16099MB
[2025-01-18 08:59:28 internimage_t_1k_224] (main.py 510): INFO Train: [232/300][310/312]	eta 0:00:00 lr 0.000508	time 0.4417 (0.4750)	model_time 0.4417 (0.4684)	loss 3.4677 (2.7878)	grad_norm 1.9929 (2.6607/1.1187)	mem 16099MB
[2025-01-18 08:59:28 internimage_t_1k_224] (main.py 519): INFO EPOCH 232 training takes 0:02:28
[2025-01-18 08:59:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_232.pth saving......
[2025-01-18 08:59:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_232.pth saved !!!
[2025-01-18 08:59:37 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.340 (7.340)	Loss 0.7370 (0.7370)	Acc@1 84.766 (84.766)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 08:59:40 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.989)	Loss 0.9785 (0.8418)	Acc@1 78.735 (82.480)	Acc@5 95.117 (96.154)	Mem 16099MB
[2025-01-18 08:59:40 internimage_t_1k_224] (main.py 575): INFO [Epoch:232] * Acc@1 82.288 Acc@5 96.135
[2025-01-18 08:59:40 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.3%
[2025-01-18 08:59:40 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 08:59:42 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 08:59:42 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.29%
[2025-01-18 08:59:49 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.263 (7.263)	Loss 0.7522 (0.7522)	Acc@1 85.840 (85.840)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 08:59:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.980)	Loss 0.9973 (0.8610)	Acc@1 78.955 (83.114)	Acc@5 95.312 (96.411)	Mem 16099MB
[2025-01-18 08:59:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:232] * Acc@1 82.989 Acc@5 96.429
[2025-01-18 08:59:53 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.0%
[2025-01-18 08:59:53 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 08:59:54 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 08:59:54 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.99%
[2025-01-18 08:59:57 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][0/312]	eta 0:13:59 lr 0.000508	time 2.6916 (2.6916)	model_time 0.4651 (0.4651)	loss 3.4324 (3.4324)	grad_norm 1.5291 (1.5291/0.0000)	mem 16099MB
[2025-01-18 09:00:01 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][10/312]	eta 0:03:20 lr 0.000507	time 0.4451 (0.6647)	model_time 0.4450 (0.4620)	loss 3.1564 (3.1485)	grad_norm 4.1885 (2.2975/0.6606)	mem 16099MB
[2025-01-18 09:00:06 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][20/312]	eta 0:02:45 lr 0.000507	time 0.4598 (0.5672)	model_time 0.4594 (0.4608)	loss 3.4002 (3.0304)	grad_norm 7.5554 (3.0004/1.6037)	mem 16099MB
[2025-01-18 09:00:11 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][30/312]	eta 0:02:33 lr 0.000506	time 0.4654 (0.5460)	model_time 0.4652 (0.4739)	loss 2.3690 (2.9693)	grad_norm 1.5324 (2.8447/1.4710)	mem 16099MB
[2025-01-18 09:00:15 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][40/312]	eta 0:02:22 lr 0.000506	time 0.4703 (0.5247)	model_time 0.4698 (0.4701)	loss 1.8059 (2.9624)	grad_norm 3.8487 (2.6179/1.3961)	mem 16099MB
[2025-01-18 09:00:20 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][50/312]	eta 0:02:14 lr 0.000506	time 0.4428 (0.5146)	model_time 0.4426 (0.4706)	loss 1.9994 (2.9283)	grad_norm 1.2154 (2.6166/1.3423)	mem 16099MB
[2025-01-18 09:00:25 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][60/312]	eta 0:02:07 lr 0.000505	time 0.4542 (0.5059)	model_time 0.4537 (0.4690)	loss 3.3239 (2.9258)	grad_norm 3.9722 (2.7608/1.4333)	mem 16099MB
[2025-01-18 09:00:29 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][70/312]	eta 0:02:00 lr 0.000505	time 0.4503 (0.4990)	model_time 0.4501 (0.4672)	loss 3.4097 (2.9033)	grad_norm 3.2276 (2.7371/1.3687)	mem 16099MB
[2025-01-18 09:00:34 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][80/312]	eta 0:01:54 lr 0.000504	time 0.4534 (0.4943)	model_time 0.4530 (0.4665)	loss 3.0589 (2.8819)	grad_norm 2.2104 (2.7057/1.3311)	mem 16099MB
[2025-01-18 09:00:39 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][90/312]	eta 0:01:49 lr 0.000504	time 0.4887 (0.4916)	model_time 0.4885 (0.4668)	loss 1.9214 (2.8544)	grad_norm 2.5537 (2.7038/1.3065)	mem 16099MB
[2025-01-18 09:00:43 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][100/312]	eta 0:01:43 lr 0.000503	time 0.4505 (0.4894)	model_time 0.4503 (0.4670)	loss 2.9983 (2.8655)	grad_norm 2.1053 (2.6998/1.2753)	mem 16099MB
[2025-01-18 09:00:48 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][110/312]	eta 0:01:38 lr 0.000503	time 0.4573 (0.4867)	model_time 0.4568 (0.4663)	loss 2.1624 (2.8476)	grad_norm 2.5998 (2.5998/1.2644)	mem 16099MB
[2025-01-18 09:00:53 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][120/312]	eta 0:01:33 lr 0.000503	time 0.4501 (0.4854)	model_time 0.4496 (0.4666)	loss 2.6402 (2.8467)	grad_norm 1.3549 (2.5656/1.2452)	mem 16099MB
[2025-01-18 09:00:57 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][130/312]	eta 0:01:28 lr 0.000502	time 0.4913 (0.4843)	model_time 0.4909 (0.4669)	loss 2.9566 (2.8413)	grad_norm 1.9397 (2.5188/1.2140)	mem 16099MB
[2025-01-18 09:01:02 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][140/312]	eta 0:01:23 lr 0.000502	time 0.4456 (0.4838)	model_time 0.4454 (0.4677)	loss 3.0047 (2.8460)	grad_norm 1.3079 (2.5023/1.1975)	mem 16099MB
[2025-01-18 09:01:07 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][150/312]	eta 0:01:18 lr 0.000501	time 0.5652 (0.4833)	model_time 0.5648 (0.4682)	loss 3.0301 (2.8558)	grad_norm 2.1981 (2.4979/1.1767)	mem 16099MB
[2025-01-18 09:01:11 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][160/312]	eta 0:01:13 lr 0.000501	time 0.4528 (0.4823)	model_time 0.4526 (0.4681)	loss 2.5826 (2.8450)	grad_norm 2.2129 (2.5180/1.1712)	mem 16099MB
[2025-01-18 09:01:16 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][170/312]	eta 0:01:08 lr 0.000500	time 0.4413 (0.4833)	model_time 0.4409 (0.4699)	loss 3.0831 (2.8464)	grad_norm 1.9054 (2.4954/1.1527)	mem 16099MB
[2025-01-18 09:01:21 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][180/312]	eta 0:01:03 lr 0.000500	time 0.5429 (0.4823)	model_time 0.5424 (0.4696)	loss 3.3537 (2.8445)	grad_norm 3.2488 (2.4741/1.1389)	mem 16099MB
[2025-01-18 09:01:26 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][190/312]	eta 0:00:58 lr 0.000500	time 0.4535 (0.4818)	model_time 0.4531 (0.4698)	loss 2.3567 (2.8526)	grad_norm 2.5591 (2.4683/1.1270)	mem 16099MB
[2025-01-18 09:01:30 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][200/312]	eta 0:00:53 lr 0.000499	time 0.4590 (0.4807)	model_time 0.4586 (0.4693)	loss 3.5063 (2.8642)	grad_norm 1.9439 (2.5053/1.1579)	mem 16099MB
[2025-01-18 09:01:35 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][210/312]	eta 0:00:48 lr 0.000499	time 0.4577 (0.4803)	model_time 0.4575 (0.4693)	loss 2.0710 (2.8531)	grad_norm 3.1135 (2.5253/1.1746)	mem 16099MB
[2025-01-18 09:01:40 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][220/312]	eta 0:00:44 lr 0.000498	time 0.4406 (0.4794)	model_time 0.4402 (0.4689)	loss 3.3282 (2.8650)	grad_norm 1.3839 (2.5838/1.2273)	mem 16099MB
[2025-01-18 09:01:44 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][230/312]	eta 0:00:39 lr 0.000498	time 0.4469 (0.4783)	model_time 0.4467 (0.4683)	loss 3.2808 (2.8580)	grad_norm 2.2646 (2.6100/1.2606)	mem 16099MB
[2025-01-18 09:01:49 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][240/312]	eta 0:00:34 lr 0.000497	time 0.4560 (0.4774)	model_time 0.4556 (0.4678)	loss 2.9930 (2.8556)	grad_norm 4.1624 (2.5991/1.2459)	mem 16099MB
[2025-01-18 09:01:54 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][250/312]	eta 0:00:29 lr 0.000497	time 0.4801 (0.4771)	model_time 0.4797 (0.4679)	loss 2.2194 (2.8586)	grad_norm 1.4762 (2.5774/1.2359)	mem 16099MB
[2025-01-18 09:01:58 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][260/312]	eta 0:00:24 lr 0.000497	time 0.4495 (0.4765)	model_time 0.4491 (0.4676)	loss 3.7501 (2.8594)	grad_norm 2.7364 (2.5849/1.2289)	mem 16099MB
[2025-01-18 09:02:03 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][270/312]	eta 0:00:19 lr 0.000496	time 0.4430 (0.4759)	model_time 0.4425 (0.4673)	loss 3.1734 (2.8593)	grad_norm 1.0298 (2.6006/1.2622)	mem 16099MB
[2025-01-18 09:02:07 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][280/312]	eta 0:00:15 lr 0.000496	time 0.4588 (0.4753)	model_time 0.4584 (0.4670)	loss 3.6367 (2.8655)	grad_norm 3.3200 (2.5967/1.2714)	mem 16099MB
[2025-01-18 09:02:12 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][290/312]	eta 0:00:10 lr 0.000495	time 0.4478 (0.4758)	model_time 0.4474 (0.4678)	loss 2.7757 (2.8733)	grad_norm 3.2908 (2.6064/1.2640)	mem 16099MB
[2025-01-18 09:02:17 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][300/312]	eta 0:00:05 lr 0.000495	time 0.4383 (0.4749)	model_time 0.4382 (0.4671)	loss 3.3180 (2.8775)	grad_norm 1.1776 (2.6205/1.2624)	mem 16099MB
[2025-01-18 09:02:21 internimage_t_1k_224] (main.py 510): INFO Train: [233/300][310/312]	eta 0:00:00 lr 0.000494	time 0.4401 (0.4742)	model_time 0.4400 (0.4666)	loss 3.2937 (2.8798)	grad_norm 2.8917 (2.6332/1.2685)	mem 16099MB
[2025-01-18 09:02:22 internimage_t_1k_224] (main.py 519): INFO EPOCH 233 training takes 0:02:27
[2025-01-18 09:02:22 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_233.pth saving......
[2025-01-18 09:02:23 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_233.pth saved !!!
[2025-01-18 09:02:30 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.170 (7.170)	Loss 0.7413 (0.7413)	Acc@1 84.546 (84.546)	Acc@5 97.290 (97.290)	Mem 16099MB
[2025-01-18 09:02:34 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.981)	Loss 1.0163 (0.8620)	Acc@1 78.101 (82.340)	Acc@5 94.824 (96.127)	Mem 16099MB
[2025-01-18 09:02:34 internimage_t_1k_224] (main.py 575): INFO [Epoch:233] * Acc@1 82.202 Acc@5 96.127
[2025-01-18 09:02:34 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.2%
[2025-01-18 09:02:34 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.29%
[2025-01-18 09:02:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.165 (8.165)	Loss 0.7513 (0.7513)	Acc@1 85.840 (85.840)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 09:02:46 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.094)	Loss 0.9959 (0.8599)	Acc@1 78.955 (83.110)	Acc@5 95.312 (96.398)	Mem 16099MB
[2025-01-18 09:02:46 internimage_t_1k_224] (main.py 575): INFO [Epoch:233] * Acc@1 82.993 Acc@5 96.417
[2025-01-18 09:02:46 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.0%
[2025-01-18 09:02:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:02:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:02:47 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 82.99%
[2025-01-18 09:02:50 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][0/312]	eta 0:13:40 lr 0.000494	time 2.6302 (2.6302)	model_time 0.4832 (0.4832)	loss 2.3983 (2.3983)	grad_norm 1.6688 (1.6688/0.0000)	mem 16099MB
[2025-01-18 09:02:55 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][10/312]	eta 0:03:25 lr 0.000494	time 0.6280 (0.6814)	model_time 0.6276 (0.4792)	loss 3.2134 (2.6046)	grad_norm 2.2438 (2.9262/1.3429)	mem 16099MB
[2025-01-18 09:03:00 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][20/312]	eta 0:02:47 lr 0.000494	time 0.4540 (0.5742)	model_time 0.4538 (0.4682)	loss 2.9221 (2.7026)	grad_norm 2.5715 (2.8252/1.1845)	mem 16099MB
[2025-01-18 09:03:04 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][30/312]	eta 0:02:34 lr 0.000493	time 0.4445 (0.5468)	model_time 0.4441 (0.4748)	loss 3.3037 (2.8135)	grad_norm 1.4244 (2.4816/1.1242)	mem 16099MB
[2025-01-18 09:03:09 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][40/312]	eta 0:02:23 lr 0.000493	time 0.4553 (0.5260)	model_time 0.4549 (0.4715)	loss 2.7971 (2.7751)	grad_norm 1.9609 (2.6461/1.2219)	mem 16099MB
[2025-01-18 09:03:14 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][50/312]	eta 0:02:14 lr 0.000492	time 0.4632 (0.5141)	model_time 0.4631 (0.4702)	loss 1.7594 (2.7384)	grad_norm 3.1341 (2.7810/1.2683)	mem 16099MB
[2025-01-18 09:03:18 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][60/312]	eta 0:02:07 lr 0.000492	time 0.4587 (0.5046)	model_time 0.4585 (0.4679)	loss 3.3226 (2.8024)	grad_norm 2.2332 (2.7102/1.1991)	mem 16099MB
[2025-01-18 09:03:23 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][70/312]	eta 0:02:00 lr 0.000491	time 0.4588 (0.4980)	model_time 0.4583 (0.4664)	loss 3.2536 (2.8229)	grad_norm 1.5842 (2.5721/1.1667)	mem 16099MB
[2025-01-18 09:03:27 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][80/312]	eta 0:01:54 lr 0.000491	time 0.4495 (0.4934)	model_time 0.4490 (0.4656)	loss 2.1125 (2.8208)	grad_norm 2.3080 (2.5057/1.1167)	mem 16099MB
[2025-01-18 09:03:32 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][90/312]	eta 0:01:48 lr 0.000491	time 0.4591 (0.4898)	model_time 0.4589 (0.4650)	loss 3.3320 (2.8499)	grad_norm 4.1932 (2.5565/1.1558)	mem 16099MB
[2025-01-18 09:03:37 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][100/312]	eta 0:01:43 lr 0.000490	time 0.4488 (0.4872)	model_time 0.4484 (0.4648)	loss 2.7130 (2.8324)	grad_norm 1.0043 (2.5722/1.1548)	mem 16099MB
[2025-01-18 09:03:41 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][110/312]	eta 0:01:37 lr 0.000490	time 0.4540 (0.4847)	model_time 0.4538 (0.4643)	loss 3.1002 (2.8308)	grad_norm 2.6495 (2.6656/1.1854)	mem 16099MB
[2025-01-18 09:03:46 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][120/312]	eta 0:01:33 lr 0.000489	time 0.5352 (0.4847)	model_time 0.5351 (0.4660)	loss 3.1260 (2.8408)	grad_norm 3.4450 (2.7014/1.1523)	mem 16099MB
[2025-01-18 09:03:51 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][130/312]	eta 0:01:27 lr 0.000489	time 0.4612 (0.4832)	model_time 0.4608 (0.4659)	loss 3.0224 (2.8608)	grad_norm 1.9619 (2.8145/1.2762)	mem 16099MB
[2025-01-18 09:03:55 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][140/312]	eta 0:01:22 lr 0.000488	time 0.4592 (0.4823)	model_time 0.4590 (0.4661)	loss 2.5991 (2.8503)	grad_norm 5.0551 (2.8030/1.2643)	mem 16099MB
[2025-01-18 09:04:00 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][150/312]	eta 0:01:18 lr 0.000488	time 0.5666 (0.4828)	model_time 0.5662 (0.4677)	loss 2.9094 (2.8475)	grad_norm 3.0930 (2.7806/1.2598)	mem 16099MB
[2025-01-18 09:04:05 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][160/312]	eta 0:01:13 lr 0.000488	time 0.5537 (0.4821)	model_time 0.5535 (0.4679)	loss 3.2345 (2.8453)	grad_norm 2.1440 (2.7198/1.2466)	mem 16099MB
[2025-01-18 09:04:10 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][170/312]	eta 0:01:08 lr 0.000487	time 0.4542 (0.4811)	model_time 0.4541 (0.4678)	loss 3.1322 (2.8493)	grad_norm 1.5259 (2.6764/1.2267)	mem 16099MB
[2025-01-18 09:04:14 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][180/312]	eta 0:01:03 lr 0.000487	time 0.4083 (0.4804)	model_time 0.4082 (0.4677)	loss 3.0963 (2.8442)	grad_norm inf (2.6786/1.2124)	mem 16099MB
[2025-01-18 09:04:19 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][190/312]	eta 0:00:58 lr 0.000486	time 0.4771 (0.4796)	model_time 0.4769 (0.4676)	loss 2.8984 (2.8593)	grad_norm 2.9695 (2.6962/1.2140)	mem 16099MB
[2025-01-18 09:04:24 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][200/312]	eta 0:00:53 lr 0.000486	time 0.5149 (0.4791)	model_time 0.5144 (0.4677)	loss 1.9946 (2.8627)	grad_norm 1.0268 (2.6937/1.1964)	mem 16099MB
[2025-01-18 09:04:28 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][210/312]	eta 0:00:48 lr 0.000486	time 0.4552 (0.4786)	model_time 0.4548 (0.4677)	loss 3.0213 (2.8677)	grad_norm 2.9181 (2.7148/1.2027)	mem 16099MB
[2025-01-18 09:04:33 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][220/312]	eta 0:00:43 lr 0.000485	time 0.4571 (0.4776)	model_time 0.4567 (0.4672)	loss 2.7074 (2.8688)	grad_norm 1.2861 (2.6857/1.1868)	mem 16099MB
[2025-01-18 09:04:38 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][230/312]	eta 0:00:39 lr 0.000485	time 0.4608 (0.4766)	model_time 0.4607 (0.4666)	loss 2.9393 (2.8649)	grad_norm 3.5437 (2.6845/1.1812)	mem 16099MB
[2025-01-18 09:04:42 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][240/312]	eta 0:00:34 lr 0.000484	time 0.4583 (0.4766)	model_time 0.4578 (0.4669)	loss 2.2709 (2.8597)	grad_norm 1.2160 (2.6688/1.1700)	mem 16099MB
[2025-01-18 09:04:47 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][250/312]	eta 0:00:29 lr 0.000484	time 0.4515 (0.4758)	model_time 0.4511 (0.4665)	loss 2.7534 (2.8614)	grad_norm 1.7753 (2.6565/1.1587)	mem 16099MB
[2025-01-18 09:04:52 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][260/312]	eta 0:00:24 lr 0.000483	time 0.4431 (0.4758)	model_time 0.4426 (0.4668)	loss 3.4132 (2.8650)	grad_norm 1.4558 (2.6605/1.1573)	mem 16099MB
[2025-01-18 09:04:56 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][270/312]	eta 0:00:19 lr 0.000483	time 0.4578 (0.4755)	model_time 0.4574 (0.4669)	loss 1.7580 (2.8701)	grad_norm 1.9333 (2.6699/1.1512)	mem 16099MB
[2025-01-18 09:05:01 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][280/312]	eta 0:00:15 lr 0.000483	time 0.4535 (0.4747)	model_time 0.4534 (0.4664)	loss 3.3682 (2.8717)	grad_norm 2.5751 (2.6802/1.1379)	mem 16099MB
[2025-01-18 09:05:06 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][290/312]	eta 0:00:10 lr 0.000482	time 0.4512 (0.4752)	model_time 0.4507 (0.4672)	loss 2.6588 (2.8693)	grad_norm 2.3015 (2.6618/1.1280)	mem 16099MB
[2025-01-18 09:05:10 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][300/312]	eta 0:00:05 lr 0.000482	time 0.4512 (0.4746)	model_time 0.4511 (0.4668)	loss 2.8942 (2.8700)	grad_norm 1.0855 (2.6430/1.1301)	mem 16099MB
[2025-01-18 09:05:15 internimage_t_1k_224] (main.py 510): INFO Train: [234/300][310/312]	eta 0:00:00 lr 0.000481	time 0.4390 (0.4740)	model_time 0.4389 (0.4664)	loss 3.2453 (2.8644)	grad_norm 2.3452 (2.6119/1.1133)	mem 16099MB
[2025-01-18 09:05:15 internimage_t_1k_224] (main.py 519): INFO EPOCH 234 training takes 0:02:27
[2025-01-18 09:05:15 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_234.pth saving......
[2025-01-18 09:05:16 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_234.pth saved !!!
[2025-01-18 09:05:24 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.576 (7.576)	Loss 0.7350 (0.7350)	Acc@1 84.863 (84.863)	Acc@5 97.437 (97.437)	Mem 16099MB
[2025-01-18 09:05:27 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.005)	Loss 0.9875 (0.8352)	Acc@1 77.661 (82.451)	Acc@5 95.044 (96.140)	Mem 16099MB
[2025-01-18 09:05:28 internimage_t_1k_224] (main.py 575): INFO [Epoch:234] * Acc@1 82.288 Acc@5 96.141
[2025-01-18 09:05:28 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.3%
[2025-01-18 09:05:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 09:05:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 09:05:29 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.29%
[2025-01-18 09:05:36 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.128 (7.128)	Loss 0.7504 (0.7504)	Acc@1 85.840 (85.840)	Acc@5 97.583 (97.583)	Mem 16099MB
[2025-01-18 09:05:40 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.969)	Loss 0.9949 (0.8588)	Acc@1 79.028 (83.143)	Acc@5 95.435 (96.418)	Mem 16099MB
[2025-01-18 09:05:40 internimage_t_1k_224] (main.py 575): INFO [Epoch:234] * Acc@1 83.025 Acc@5 96.433
[2025-01-18 09:05:40 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.0%
[2025-01-18 09:05:40 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:05:41 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:05:41 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.03%
[2025-01-18 09:05:44 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][0/312]	eta 0:11:59 lr 0.000481	time 2.3058 (2.3058)	model_time 0.5331 (0.5331)	loss 3.2716 (3.2716)	grad_norm 1.5660 (1.5660/0.0000)	mem 16099MB
[2025-01-18 09:05:49 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][10/312]	eta 0:03:25 lr 0.000481	time 0.4464 (0.6807)	model_time 0.4463 (0.4833)	loss 2.7835 (2.7350)	grad_norm 2.2742 (2.0554/0.4869)	mem 16099MB
[2025-01-18 09:05:53 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][20/312]	eta 0:02:47 lr 0.000480	time 0.4581 (0.5728)	model_time 0.4580 (0.4693)	loss 3.2361 (2.7586)	grad_norm 2.2664 (2.3083/0.8471)	mem 16099MB
[2025-01-18 09:05:58 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][30/312]	eta 0:02:32 lr 0.000480	time 0.4513 (0.5391)	model_time 0.4511 (0.4689)	loss 3.2960 (2.8070)	grad_norm 1.9160 (2.2523/0.7642)	mem 16099MB
[2025-01-18 09:06:03 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][40/312]	eta 0:02:21 lr 0.000480	time 0.4583 (0.5215)	model_time 0.4578 (0.4683)	loss 3.0822 (2.8321)	grad_norm 1.8031 (2.2132/0.7734)	mem 16099MB
[2025-01-18 09:06:07 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][50/312]	eta 0:02:14 lr 0.000479	time 0.4522 (0.5119)	model_time 0.4520 (0.4691)	loss 3.0021 (2.8374)	grad_norm 2.1320 (2.2995/0.8074)	mem 16099MB
[2025-01-18 09:06:12 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][60/312]	eta 0:02:07 lr 0.000479	time 0.4720 (0.5069)	model_time 0.4716 (0.4710)	loss 2.9348 (2.8169)	grad_norm 3.0909 (2.4231/1.0299)	mem 16099MB
[2025-01-18 09:06:17 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][70/312]	eta 0:02:01 lr 0.000478	time 0.4489 (0.5035)	model_time 0.4487 (0.4727)	loss 2.7857 (2.8101)	grad_norm 2.0802 (2.4311/1.0535)	mem 16099MB
[2025-01-18 09:06:22 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][80/312]	eta 0:01:55 lr 0.000478	time 0.4421 (0.4995)	model_time 0.4417 (0.4724)	loss 2.3990 (2.8168)	grad_norm 3.4528 (2.4470/1.0373)	mem 16099MB
[2025-01-18 09:06:26 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][90/312]	eta 0:01:49 lr 0.000477	time 0.4469 (0.4947)	model_time 0.4467 (0.4706)	loss 2.8547 (2.8060)	grad_norm 2.5174 (2.5335/1.1731)	mem 16099MB
[2025-01-18 09:06:31 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][100/312]	eta 0:01:44 lr 0.000477	time 0.4508 (0.4908)	model_time 0.4504 (0.4690)	loss 3.3313 (2.8256)	grad_norm 3.5309 (2.4902/1.1422)	mem 16099MB
[2025-01-18 09:06:35 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][110/312]	eta 0:01:38 lr 0.000477	time 0.4701 (0.4879)	model_time 0.4699 (0.4680)	loss 3.4715 (2.8228)	grad_norm 5.1177 (2.5974/1.2320)	mem 16099MB
[2025-01-18 09:06:40 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][120/312]	eta 0:01:33 lr 0.000476	time 0.4497 (0.4862)	model_time 0.4493 (0.4679)	loss 2.4780 (2.8341)	grad_norm 1.7470 (2.5868/1.2342)	mem 16099MB
[2025-01-18 09:06:45 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][130/312]	eta 0:01:28 lr 0.000476	time 0.4499 (0.4864)	model_time 0.4498 (0.4695)	loss 2.9257 (2.8297)	grad_norm 3.0553 (2.6205/1.2243)	mem 16099MB
[2025-01-18 09:06:50 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][140/312]	eta 0:01:23 lr 0.000475	time 0.4635 (0.4853)	model_time 0.4630 (0.4695)	loss 3.3803 (2.8424)	grad_norm 1.5715 (2.6021/1.2173)	mem 16099MB
[2025-01-18 09:06:55 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][150/312]	eta 0:01:18 lr 0.000475	time 0.4620 (0.4865)	model_time 0.4619 (0.4718)	loss 2.9450 (2.8321)	grad_norm 2.4904 (2.5614/1.1942)	mem 16099MB
[2025-01-18 09:06:59 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][160/312]	eta 0:01:13 lr 0.000475	time 0.4548 (0.4849)	model_time 0.4547 (0.4711)	loss 3.0879 (2.8391)	grad_norm 2.2736 (2.5387/1.1690)	mem 16099MB
[2025-01-18 09:07:04 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][170/312]	eta 0:01:08 lr 0.000474	time 0.4913 (0.4833)	model_time 0.4908 (0.4702)	loss 3.1701 (2.8506)	grad_norm 4.2216 (2.5345/1.1586)	mem 16099MB
[2025-01-18 09:07:09 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][180/312]	eta 0:01:03 lr 0.000474	time 0.4546 (0.4823)	model_time 0.4544 (0.4700)	loss 2.4209 (2.8397)	grad_norm 1.7894 (2.5419/1.2036)	mem 16099MB
[2025-01-18 09:07:13 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][190/312]	eta 0:00:58 lr 0.000473	time 0.4487 (0.4808)	model_time 0.4483 (0.4691)	loss 2.6303 (2.8437)	grad_norm 5.8041 (2.5892/1.2473)	mem 16099MB
[2025-01-18 09:07:18 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][200/312]	eta 0:00:53 lr 0.000473	time 0.4514 (0.4795)	model_time 0.4511 (0.4683)	loss 2.7948 (2.8414)	grad_norm 2.0594 (2.6732/1.3300)	mem 16099MB
[2025-01-18 09:07:22 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][210/312]	eta 0:00:48 lr 0.000473	time 0.4596 (0.4796)	model_time 0.4594 (0.4689)	loss 3.0895 (2.8451)	grad_norm 1.4694 (2.6914/1.3365)	mem 16099MB
[2025-01-18 09:07:27 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][220/312]	eta 0:00:44 lr 0.000472	time 0.4624 (0.4788)	model_time 0.4619 (0.4686)	loss 2.7366 (2.8473)	grad_norm 2.6543 (2.6970/1.3376)	mem 16099MB
[2025-01-18 09:07:32 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][230/312]	eta 0:00:39 lr 0.000472	time 0.4496 (0.4782)	model_time 0.4492 (0.4685)	loss 2.9955 (2.8423)	grad_norm 3.0930 (2.6922/1.3200)	mem 16099MB
[2025-01-18 09:07:36 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][240/312]	eta 0:00:34 lr 0.000471	time 0.4405 (0.4780)	model_time 0.4403 (0.4686)	loss 2.7665 (2.8312)	grad_norm 1.8914 (2.7270/1.3462)	mem 16099MB
[2025-01-18 09:07:41 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][250/312]	eta 0:00:29 lr 0.000471	time 0.4623 (0.4770)	model_time 0.4619 (0.4680)	loss 3.1838 (2.8343)	grad_norm 2.6819 (2.7116/1.3253)	mem 16099MB
[2025-01-18 09:07:46 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][260/312]	eta 0:00:24 lr 0.000470	time 0.4791 (0.4766)	model_time 0.4786 (0.4679)	loss 1.8799 (2.8298)	grad_norm 3.2173 (2.7189/1.3338)	mem 16099MB
[2025-01-18 09:07:50 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][270/312]	eta 0:00:19 lr 0.000470	time 0.4577 (0.4759)	model_time 0.4573 (0.4675)	loss 3.0642 (2.8329)	grad_norm 1.1903 (2.7122/1.3244)	mem 16099MB
[2025-01-18 09:07:55 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][280/312]	eta 0:00:15 lr 0.000470	time 0.4708 (0.4753)	model_time 0.4704 (0.4672)	loss 2.2726 (2.8233)	grad_norm 5.9924 (2.7252/1.3336)	mem 16099MB
[2025-01-18 09:07:59 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][290/312]	eta 0:00:10 lr 0.000469	time 0.4514 (0.4749)	model_time 0.4513 (0.4670)	loss 2.9425 (2.8331)	grad_norm 1.7205 (2.7371/1.3237)	mem 16099MB
[2025-01-18 09:08:04 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][300/312]	eta 0:00:05 lr 0.000469	time 0.4374 (0.4744)	model_time 0.4372 (0.4668)	loss 2.9920 (2.8305)	grad_norm 2.3591 (2.7371/1.3227)	mem 16099MB
[2025-01-18 09:08:09 internimage_t_1k_224] (main.py 510): INFO Train: [235/300][310/312]	eta 0:00:00 lr 0.000468	time 0.4415 (0.4739)	model_time 0.4414 (0.4665)	loss 3.0188 (2.8323)	grad_norm 2.0966 (2.7269/1.3296)	mem 16099MB
[2025-01-18 09:08:09 internimage_t_1k_224] (main.py 519): INFO EPOCH 235 training takes 0:02:27
[2025-01-18 09:08:09 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_235.pth saving......
[2025-01-18 09:08:10 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_235.pth saved !!!
[2025-01-18 09:08:18 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.455 (7.455)	Loss 0.7189 (0.7189)	Acc@1 85.278 (85.278)	Acc@5 97.534 (97.534)	Mem 16099MB
[2025-01-18 09:08:21 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.000)	Loss 0.9955 (0.8435)	Acc@1 78.003 (82.571)	Acc@5 94.653 (96.112)	Mem 16099MB
[2025-01-18 09:08:21 internimage_t_1k_224] (main.py 575): INFO [Epoch:235] * Acc@1 82.368 Acc@5 96.119
[2025-01-18 09:08:21 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.4%
[2025-01-18 09:08:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 09:08:23 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 09:08:23 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.37%
[2025-01-18 09:08:30 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.610 (7.610)	Loss 0.7495 (0.7495)	Acc@1 85.864 (85.864)	Acc@5 97.583 (97.583)	Mem 16099MB
[2025-01-18 09:08:34 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.011)	Loss 0.9938 (0.8577)	Acc@1 79.053 (83.201)	Acc@5 95.410 (96.424)	Mem 16099MB
[2025-01-18 09:08:34 internimage_t_1k_224] (main.py 575): INFO [Epoch:235] * Acc@1 83.079 Acc@5 96.441
[2025-01-18 09:08:34 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.1%
[2025-01-18 09:08:34 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:08:35 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:08:35 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.08%
[2025-01-18 09:08:38 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][0/312]	eta 0:14:39 lr 0.000468	time 2.8188 (2.8188)	model_time 0.4815 (0.4815)	loss 3.0282 (3.0282)	grad_norm 1.5771 (1.5771/0.0000)	mem 16099MB
[2025-01-18 09:08:43 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][10/312]	eta 0:03:30 lr 0.000468	time 0.5519 (0.6965)	model_time 0.5517 (0.4838)	loss 2.3333 (2.7281)	grad_norm 4.4562 (3.2531/1.5634)	mem 16099MB
[2025-01-18 09:08:47 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][20/312]	eta 0:02:49 lr 0.000467	time 0.4705 (0.5814)	model_time 0.4704 (0.4698)	loss 2.9015 (2.7732)	grad_norm 1.6109 (2.8286/1.3108)	mem 16099MB
[2025-01-18 09:08:52 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][30/312]	eta 0:02:35 lr 0.000467	time 0.5456 (0.5522)	model_time 0.5455 (0.4765)	loss 3.1586 (2.7119)	grad_norm 2.6302 (2.5861/1.1778)	mem 16099MB
[2025-01-18 09:08:57 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][40/312]	eta 0:02:24 lr 0.000467	time 0.4686 (0.5307)	model_time 0.4682 (0.4734)	loss 2.5419 (2.7488)	grad_norm 5.5871 (2.6178/1.1840)	mem 16099MB
[2025-01-18 09:09:02 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][50/312]	eta 0:02:17 lr 0.000466	time 0.4501 (0.5245)	model_time 0.4496 (0.4783)	loss 2.6986 (2.7542)	grad_norm 1.9403 (2.4656/1.1319)	mem 16099MB
[2025-01-18 09:09:07 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][60/312]	eta 0:02:09 lr 0.000466	time 0.4492 (0.5152)	model_time 0.4490 (0.4765)	loss 3.2404 (2.7823)	grad_norm 2.0335 (2.4686/1.1104)	mem 16099MB
[2025-01-18 09:09:11 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][70/312]	eta 0:02:02 lr 0.000465	time 0.4498 (0.5065)	model_time 0.4493 (0.4732)	loss 2.3161 (2.7322)	grad_norm 1.4341 (2.6511/1.4509)	mem 16099MB
[2025-01-18 09:09:16 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][80/312]	eta 0:01:56 lr 0.000465	time 0.5537 (0.5023)	model_time 0.5535 (0.4731)	loss 2.2158 (2.7227)	grad_norm 2.1803 (2.6724/1.4582)	mem 16099MB
[2025-01-18 09:09:20 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][90/312]	eta 0:01:50 lr 0.000465	time 0.4648 (0.4970)	model_time 0.4646 (0.4710)	loss 3.0778 (2.7283)	grad_norm 1.4987 (2.8075/1.5221)	mem 16099MB
[2025-01-18 09:09:25 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][100/312]	eta 0:01:44 lr 0.000464	time 0.4435 (0.4946)	model_time 0.4433 (0.4710)	loss 2.9898 (2.7484)	grad_norm 2.1362 (2.7662/1.4905)	mem 16099MB
[2025-01-18 09:09:30 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][110/312]	eta 0:01:39 lr 0.000464	time 0.4589 (0.4921)	model_time 0.4584 (0.4707)	loss 3.1097 (2.7589)	grad_norm 2.6806 (2.7259/1.4610)	mem 16099MB
[2025-01-18 09:09:35 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][120/312]	eta 0:01:34 lr 0.000463	time 0.4512 (0.4905)	model_time 0.4507 (0.4708)	loss 2.4042 (2.7538)	grad_norm 3.6540 (2.7682/1.4649)	mem 16099MB
[2025-01-18 09:09:39 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][130/312]	eta 0:01:29 lr 0.000463	time 0.4473 (0.4903)	model_time 0.4471 (0.4721)	loss 3.2029 (2.7734)	grad_norm 1.4390 (2.7244/1.4346)	mem 16099MB
[2025-01-18 09:09:44 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][140/312]	eta 0:01:24 lr 0.000463	time 0.4533 (0.4897)	model_time 0.4531 (0.4727)	loss 2.2410 (2.7609)	grad_norm 2.8178 (2.7455/1.4193)	mem 16099MB
[2025-01-18 09:09:49 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][150/312]	eta 0:01:19 lr 0.000462	time 0.4493 (0.4882)	model_time 0.4488 (0.4723)	loss 2.7859 (2.7672)	grad_norm 3.1234 (2.7641/1.4093)	mem 16099MB
[2025-01-18 09:09:54 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][160/312]	eta 0:01:13 lr 0.000462	time 0.4837 (0.4867)	model_time 0.4833 (0.4718)	loss 1.9978 (2.7735)	grad_norm 2.0634 (2.7511/1.4231)	mem 16099MB
[2025-01-18 09:09:58 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][170/312]	eta 0:01:08 lr 0.000461	time 0.5053 (0.4852)	model_time 0.5049 (0.4711)	loss 2.3846 (2.7890)	grad_norm 1.6545 (2.7582/1.4190)	mem 16099MB
[2025-01-18 09:10:03 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][180/312]	eta 0:01:03 lr 0.000461	time 0.4829 (0.4841)	model_time 0.4824 (0.4708)	loss 2.1991 (2.7876)	grad_norm 3.8393 (2.8092/1.4552)	mem 16099MB
[2025-01-18 09:10:08 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][190/312]	eta 0:00:58 lr 0.000460	time 0.4496 (0.4830)	model_time 0.4491 (0.4704)	loss 2.5637 (2.7910)	grad_norm 1.3075 (2.8271/1.4619)	mem 16099MB
[2025-01-18 09:10:12 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][200/312]	eta 0:00:54 lr 0.000460	time 0.4472 (0.4831)	model_time 0.4468 (0.4710)	loss 3.0738 (2.7860)	grad_norm 1.7732 (2.7861/1.4417)	mem 16099MB
[2025-01-18 09:10:17 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][210/312]	eta 0:00:49 lr 0.000460	time 0.4459 (0.4822)	model_time 0.4454 (0.4707)	loss 2.9742 (2.8027)	grad_norm 1.3085 (2.7742/1.4276)	mem 16099MB
[2025-01-18 09:10:22 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][220/312]	eta 0:00:44 lr 0.000459	time 0.4799 (0.4811)	model_time 0.4795 (0.4701)	loss 2.1737 (2.8014)	grad_norm 2.4802 (2.7694/1.4047)	mem 16099MB
[2025-01-18 09:10:26 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][230/312]	eta 0:00:39 lr 0.000459	time 0.4463 (0.4806)	model_time 0.4461 (0.4701)	loss 2.9859 (2.8061)	grad_norm 1.9374 (2.7441/1.3854)	mem 16099MB
[2025-01-18 09:10:31 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][240/312]	eta 0:00:34 lr 0.000458	time 0.4545 (0.4797)	model_time 0.4541 (0.4696)	loss 2.4881 (2.7992)	grad_norm 2.6638 (2.7265/1.3654)	mem 16099MB
[2025-01-18 09:10:36 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][250/312]	eta 0:00:29 lr 0.000458	time 0.4592 (0.4793)	model_time 0.4590 (0.4696)	loss 2.4020 (2.7982)	grad_norm 2.4786 (2.7096/1.3473)	mem 16099MB
[2025-01-18 09:10:40 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][260/312]	eta 0:00:24 lr 0.000458	time 0.4433 (0.4785)	model_time 0.4428 (0.4691)	loss 3.0256 (2.7966)	grad_norm 2.7582 (2.7172/1.3384)	mem 16099MB
[2025-01-18 09:10:45 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][270/312]	eta 0:00:20 lr 0.000457	time 0.4438 (0.4786)	model_time 0.4434 (0.4695)	loss 3.4918 (2.7983)	grad_norm 1.1406 (2.7019/1.3294)	mem 16099MB
[2025-01-18 09:10:50 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][280/312]	eta 0:00:15 lr 0.000457	time 0.4597 (0.4778)	model_time 0.4593 (0.4691)	loss 3.1620 (2.8055)	grad_norm 2.7467 (2.7097/1.3118)	mem 16099MB
[2025-01-18 09:10:54 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][290/312]	eta 0:00:10 lr 0.000456	time 0.4636 (0.4777)	model_time 0.4632 (0.4693)	loss 2.3968 (2.8054)	grad_norm 0.9733 (2.7262/1.3289)	mem 16099MB
[2025-01-18 09:10:59 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][300/312]	eta 0:00:05 lr 0.000456	time 0.4456 (0.4774)	model_time 0.4455 (0.4692)	loss 2.5544 (2.8048)	grad_norm 2.1118 (2.7220/1.3189)	mem 16099MB
[2025-01-18 09:11:03 internimage_t_1k_224] (main.py 510): INFO Train: [236/300][310/312]	eta 0:00:00 lr 0.000456	time 0.4384 (0.4762)	model_time 0.4382 (0.4683)	loss 3.3637 (2.8072)	grad_norm 2.2922 (2.6895/1.2871)	mem 16099MB
[2025-01-18 09:11:04 internimage_t_1k_224] (main.py 519): INFO EPOCH 236 training takes 0:02:28
[2025-01-18 09:11:04 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_236.pth saving......
[2025-01-18 09:11:05 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_236.pth saved !!!
[2025-01-18 09:11:12 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.351 (7.351)	Loss 0.7082 (0.7082)	Acc@1 84.741 (84.741)	Acc@5 97.412 (97.412)	Mem 16099MB
[2025-01-18 09:11:16 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.989)	Loss 0.9825 (0.8274)	Acc@1 78.052 (82.444)	Acc@5 94.824 (96.063)	Mem 16099MB
[2025-01-18 09:11:16 internimage_t_1k_224] (main.py 575): INFO [Epoch:236] * Acc@1 82.296 Acc@5 96.085
[2025-01-18 09:11:16 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.3%
[2025-01-18 09:11:16 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.37%
[2025-01-18 09:11:24 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.483 (8.483)	Loss 0.7484 (0.7484)	Acc@1 85.815 (85.815)	Acc@5 97.632 (97.632)	Mem 16099MB
[2025-01-18 09:11:29 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.146)	Loss 0.9924 (0.8565)	Acc@1 79.004 (83.203)	Acc@5 95.410 (96.433)	Mem 16099MB
[2025-01-18 09:11:29 internimage_t_1k_224] (main.py 575): INFO [Epoch:236] * Acc@1 83.083 Acc@5 96.451
[2025-01-18 09:11:29 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.1%
[2025-01-18 09:11:29 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:11:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:11:30 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.08%
[2025-01-18 09:11:32 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][0/312]	eta 0:10:59 lr 0.000455	time 2.1134 (2.1134)	model_time 0.4728 (0.4728)	loss 2.3258 (2.3258)	grad_norm 3.4774 (3.4774/0.0000)	mem 16099MB
[2025-01-18 09:11:37 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][10/312]	eta 0:03:05 lr 0.000455	time 0.4597 (0.6129)	model_time 0.4592 (0.4633)	loss 2.3567 (2.5271)	grad_norm 2.6817 (2.7634/0.7484)	mem 16099MB
[2025-01-18 09:11:42 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][20/312]	eta 0:02:38 lr 0.000455	time 0.4662 (0.5432)	model_time 0.4657 (0.4647)	loss 2.7528 (2.7094)	grad_norm 1.4276 (2.8787/0.8150)	mem 16099MB
[2025-01-18 09:11:46 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][30/312]	eta 0:02:26 lr 0.000454	time 0.4700 (0.5196)	model_time 0.4698 (0.4664)	loss 3.0549 (2.7301)	grad_norm 1.6695 (3.1386/1.1900)	mem 16099MB
[2025-01-18 09:11:51 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][40/312]	eta 0:02:18 lr 0.000454	time 0.4498 (0.5087)	model_time 0.4493 (0.4683)	loss 2.5967 (2.7452)	grad_norm 5.8541 (3.2859/1.2991)	mem 16099MB
[2025-01-18 09:11:56 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][50/312]	eta 0:02:11 lr 0.000453	time 0.4429 (0.5003)	model_time 0.4424 (0.4678)	loss 2.7157 (2.7985)	grad_norm 1.7344 (3.2690/1.3304)	mem 16099MB
[2025-01-18 09:12:00 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][60/312]	eta 0:02:04 lr 0.000453	time 0.4507 (0.4951)	model_time 0.4505 (0.4678)	loss 2.3216 (2.7929)	grad_norm 3.8498 (3.3028/1.3465)	mem 16099MB
[2025-01-18 09:12:05 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][70/312]	eta 0:01:59 lr 0.000453	time 0.4498 (0.4924)	model_time 0.4496 (0.4690)	loss 3.1412 (2.7931)	grad_norm 1.1142 (3.2030/1.3947)	mem 16099MB
[2025-01-18 09:12:10 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][80/312]	eta 0:01:54 lr 0.000452	time 0.4533 (0.4941)	model_time 0.4529 (0.4735)	loss 3.0244 (2.8155)	grad_norm 3.6876 (3.1650/1.4078)	mem 16099MB
[2025-01-18 09:12:15 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][90/312]	eta 0:01:49 lr 0.000452	time 0.4599 (0.4917)	model_time 0.4597 (0.4733)	loss 3.3167 (2.8225)	grad_norm 4.3395 (3.1280/1.3560)	mem 16099MB
[2025-01-18 09:12:20 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][100/312]	eta 0:01:44 lr 0.000451	time 0.4538 (0.4908)	model_time 0.4536 (0.4742)	loss 2.6768 (2.8089)	grad_norm 1.9336 (3.0875/1.3459)	mem 16099MB
[2025-01-18 09:12:24 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][110/312]	eta 0:01:38 lr 0.000451	time 0.4625 (0.4877)	model_time 0.4620 (0.4725)	loss 3.1289 (2.8099)	grad_norm 2.2506 (3.0475/1.3378)	mem 16099MB
[2025-01-18 09:12:29 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][120/312]	eta 0:01:33 lr 0.000451	time 0.4501 (0.4875)	model_time 0.4497 (0.4735)	loss 2.5837 (2.8180)	grad_norm 2.4376 (3.0024/1.3106)	mem 16099MB
[2025-01-18 09:12:34 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][130/312]	eta 0:01:28 lr 0.000450	time 0.4540 (0.4858)	model_time 0.4535 (0.4729)	loss 2.7168 (2.8211)	grad_norm 3.8954 (2.9729/1.2864)	mem 16099MB
[2025-01-18 09:12:38 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][140/312]	eta 0:01:23 lr 0.000450	time 0.4510 (0.4844)	model_time 0.4508 (0.4724)	loss 2.7342 (2.8288)	grad_norm 2.4976 (2.9623/1.2853)	mem 16099MB
[2025-01-18 09:12:43 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][150/312]	eta 0:01:18 lr 0.000449	time 0.4433 (0.4824)	model_time 0.4428 (0.4711)	loss 3.1389 (2.8357)	grad_norm 4.3091 (2.9780/1.2847)	mem 16099MB
[2025-01-18 09:12:48 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][160/312]	eta 0:01:13 lr 0.000449	time 0.4826 (0.4829)	model_time 0.4824 (0.4724)	loss 2.4273 (2.8292)	grad_norm 4.5794 (3.0128/1.3164)	mem 16099MB
[2025-01-18 09:12:52 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][170/312]	eta 0:01:08 lr 0.000449	time 0.4404 (0.4817)	model_time 0.4400 (0.4717)	loss 2.8144 (2.8412)	grad_norm 2.3176 (3.0062/1.2979)	mem 16099MB
[2025-01-18 09:12:57 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][180/312]	eta 0:01:03 lr 0.000448	time 0.4952 (0.4814)	model_time 0.4948 (0.4719)	loss 2.9517 (2.8554)	grad_norm 1.3343 (3.0019/1.3051)	mem 16099MB
[2025-01-18 09:13:02 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][190/312]	eta 0:00:58 lr 0.000448	time 0.4440 (0.4800)	model_time 0.4438 (0.4710)	loss 3.2360 (2.8553)	grad_norm 3.0386 (2.9586/1.2907)	mem 16099MB
[2025-01-18 09:13:06 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][200/312]	eta 0:00:53 lr 0.000447	time 0.4502 (0.4795)	model_time 0.4498 (0.4710)	loss 2.8539 (2.8496)	grad_norm 1.4621 (2.9074/1.2843)	mem 16099MB
[2025-01-18 09:13:11 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][210/312]	eta 0:00:48 lr 0.000447	time 0.5467 (0.4794)	model_time 0.5462 (0.4712)	loss 2.9497 (2.8460)	grad_norm 2.6547 (2.8711/1.2714)	mem 16099MB
[2025-01-18 09:13:16 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][220/312]	eta 0:00:44 lr 0.000447	time 0.4551 (0.4785)	model_time 0.4549 (0.4707)	loss 2.8457 (2.8498)	grad_norm 2.9729 (2.8374/1.2566)	mem 16099MB
[2025-01-18 09:13:21 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][230/312]	eta 0:00:39 lr 0.000446	time 0.4513 (0.4781)	model_time 0.4512 (0.4707)	loss 2.0065 (2.8356)	grad_norm 3.2537 (2.8297/1.2488)	mem 16099MB
[2025-01-18 09:13:25 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][240/312]	eta 0:00:34 lr 0.000446	time 0.4659 (0.4777)	model_time 0.4654 (0.4705)	loss 2.7230 (2.8454)	grad_norm 2.4358 (2.8115/1.2438)	mem 16099MB
[2025-01-18 09:13:30 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][250/312]	eta 0:00:29 lr 0.000445	time 0.4568 (0.4771)	model_time 0.4566 (0.4701)	loss 3.2474 (2.8446)	grad_norm 2.1431 (2.7638/1.2431)	mem 16099MB
[2025-01-18 09:13:35 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][260/312]	eta 0:00:24 lr 0.000445	time 0.5004 (0.4770)	model_time 0.5002 (0.4703)	loss 2.5443 (2.8439)	grad_norm 2.6545 (2.7462/1.2323)	mem 16099MB
[2025-01-18 09:13:39 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][270/312]	eta 0:00:20 lr 0.000445	time 0.4438 (0.4771)	model_time 0.4434 (0.4707)	loss 2.8890 (2.8348)	grad_norm 5.0195 (2.7560/1.2443)	mem 16099MB
[2025-01-18 09:13:44 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][280/312]	eta 0:00:15 lr 0.000444	time 0.4403 (0.4763)	model_time 0.4401 (0.4701)	loss 3.1139 (2.8261)	grad_norm 1.6032 (2.7418/1.2356)	mem 16099MB
[2025-01-18 09:13:49 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][290/312]	eta 0:00:10 lr 0.000444	time 0.4956 (0.4764)	model_time 0.4951 (0.4704)	loss 2.8381 (2.8206)	grad_norm 1.8913 (2.7468/1.2253)	mem 16099MB
[2025-01-18 09:13:53 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][300/312]	eta 0:00:05 lr 0.000443	time 0.4384 (0.4758)	model_time 0.4383 (0.4699)	loss 2.0235 (2.8181)	grad_norm 2.9680 (2.7363/1.2159)	mem 16099MB
[2025-01-18 09:13:58 internimage_t_1k_224] (main.py 510): INFO Train: [237/300][310/312]	eta 0:00:00 lr 0.000443	time 0.4389 (0.4749)	model_time 0.4387 (0.4693)	loss 2.4630 (2.8195)	grad_norm 1.1541 (2.7280/1.2253)	mem 16099MB
[2025-01-18 09:13:58 internimage_t_1k_224] (main.py 519): INFO EPOCH 237 training takes 0:02:28
[2025-01-18 09:13:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_237.pth saving......
[2025-01-18 09:13:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_237.pth saved !!!
[2025-01-18 09:14:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.525 (7.525)	Loss 0.7293 (0.7293)	Acc@1 85.010 (85.010)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 09:14:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.000)	Loss 0.9731 (0.8377)	Acc@1 78.052 (82.477)	Acc@5 94.995 (96.169)	Mem 16099MB
[2025-01-18 09:14:11 internimage_t_1k_224] (main.py 575): INFO [Epoch:237] * Acc@1 82.374 Acc@5 96.181
[2025-01-18 09:14:11 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.4%
[2025-01-18 09:14:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 09:14:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 09:14:12 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.37%
[2025-01-18 09:14:19 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.435 (7.435)	Loss 0.7476 (0.7476)	Acc@1 85.864 (85.864)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 09:14:23 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (0.996)	Loss 0.9912 (0.8555)	Acc@1 79.004 (83.201)	Acc@5 95.288 (96.424)	Mem 16099MB
[2025-01-18 09:14:23 internimage_t_1k_224] (main.py 575): INFO [Epoch:237] * Acc@1 83.073 Acc@5 96.451
[2025-01-18 09:14:23 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.1%
[2025-01-18 09:14:23 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.08%
[2025-01-18 09:14:26 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][0/312]	eta 0:16:33 lr 0.000443	time 3.1842 (3.1842)	model_time 0.9772 (0.9772)	loss 2.7988 (2.7988)	grad_norm 3.7014 (3.7014/0.0000)	mem 16099MB
[2025-01-18 09:14:31 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][10/312]	eta 0:03:39 lr 0.000442	time 0.4532 (0.7262)	model_time 0.4528 (0.5251)	loss 2.8716 (2.8612)	grad_norm 3.0454 (2.7572/0.6943)	mem 16099MB
[2025-01-18 09:14:35 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][20/312]	eta 0:02:54 lr 0.000442	time 0.4622 (0.5965)	model_time 0.4617 (0.4910)	loss 3.2764 (2.8910)	grad_norm 3.7206 (3.0374/1.1553)	mem 16099MB
[2025-01-18 09:14:40 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][30/312]	eta 0:02:37 lr 0.000442	time 0.4498 (0.5569)	model_time 0.4496 (0.4854)	loss 2.9304 (2.8460)	grad_norm 1.9944 (2.9988/1.1773)	mem 16099MB
[2025-01-18 09:14:45 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][40/312]	eta 0:02:24 lr 0.000441	time 0.4462 (0.5325)	model_time 0.4457 (0.4783)	loss 2.0106 (2.8637)	grad_norm 4.0840 (3.0327/1.2021)	mem 16099MB
[2025-01-18 09:14:49 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][50/312]	eta 0:02:15 lr 0.000441	time 0.4521 (0.5186)	model_time 0.4517 (0.4750)	loss 2.9873 (2.8516)	grad_norm 4.1489 (3.0011/1.2102)	mem 16099MB
[2025-01-18 09:14:54 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][60/312]	eta 0:02:08 lr 0.000440	time 0.4403 (0.5107)	model_time 0.4401 (0.4742)	loss 1.9358 (2.8446)	grad_norm 1.9888 (2.9580/1.1673)	mem 16099MB
[2025-01-18 09:14:59 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][70/312]	eta 0:02:02 lr 0.000440	time 0.4474 (0.5061)	model_time 0.4469 (0.4747)	loss 3.4365 (2.8662)	grad_norm 7.4417 (2.8796/1.2958)	mem 16099MB
[2025-01-18 09:15:04 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][80/312]	eta 0:01:56 lr 0.000440	time 0.4551 (0.5034)	model_time 0.4550 (0.4758)	loss 3.0677 (2.8780)	grad_norm 1.6575 (3.0144/1.5171)	mem 16099MB
[2025-01-18 09:15:08 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][90/312]	eta 0:01:50 lr 0.000439	time 0.4468 (0.4997)	model_time 0.4466 (0.4751)	loss 3.2740 (2.8686)	grad_norm 3.4407 (3.0180/1.4722)	mem 16099MB
[2025-01-18 09:15:13 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][100/312]	eta 0:01:45 lr 0.000439	time 0.4518 (0.4955)	model_time 0.4516 (0.4733)	loss 3.5098 (2.8983)	grad_norm 1.6883 (2.8999/1.4483)	mem 16099MB
[2025-01-18 09:15:18 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][110/312]	eta 0:01:39 lr 0.000438	time 0.4614 (0.4939)	model_time 0.4609 (0.4737)	loss 2.8001 (2.9021)	grad_norm 3.1563 (2.8516/1.4132)	mem 16099MB
[2025-01-18 09:15:22 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][120/312]	eta 0:01:34 lr 0.000438	time 0.5373 (0.4913)	model_time 0.5368 (0.4727)	loss 2.3845 (2.8872)	grad_norm 2.7406 (2.8388/1.3747)	mem 16099MB
[2025-01-18 09:15:27 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][130/312]	eta 0:01:29 lr 0.000438	time 0.5310 (0.4901)	model_time 0.5309 (0.4729)	loss 2.2605 (2.8948)	grad_norm 3.1809 (2.8387/1.3586)	mem 16099MB
[2025-01-18 09:15:32 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][140/312]	eta 0:01:24 lr 0.000437	time 0.4571 (0.4894)	model_time 0.4567 (0.4734)	loss 2.5179 (2.9003)	grad_norm 5.4575 (2.8280/1.3554)	mem 16099MB
[2025-01-18 09:15:37 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][150/312]	eta 0:01:19 lr 0.000437	time 0.4516 (0.4885)	model_time 0.4512 (0.4735)	loss 2.3040 (2.8858)	grad_norm 3.9121 (2.8334/1.3332)	mem 16099MB
[2025-01-18 09:15:41 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][160/312]	eta 0:01:13 lr 0.000436	time 0.4508 (0.4864)	model_time 0.4502 (0.4724)	loss 2.7319 (2.8706)	grad_norm 3.4285 (2.8690/1.3367)	mem 16099MB
[2025-01-18 09:15:46 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][170/312]	eta 0:01:09 lr 0.000436	time 0.4631 (0.4860)	model_time 0.4630 (0.4727)	loss 2.8752 (2.8703)	grad_norm 1.3612 (2.8728/1.3313)	mem 16099MB
[2025-01-18 09:15:51 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][180/312]	eta 0:01:03 lr 0.000436	time 0.4490 (0.4847)	model_time 0.4489 (0.4722)	loss 3.0629 (2.8617)	grad_norm 2.5235 (2.8783/1.2989)	mem 16099MB
[2025-01-18 09:15:55 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][190/312]	eta 0:00:59 lr 0.000435	time 0.4788 (0.4838)	model_time 0.4783 (0.4719)	loss 3.3325 (2.8513)	grad_norm 3.6147 (2.9193/1.3067)	mem 16099MB
[2025-01-18 09:16:00 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][200/312]	eta 0:00:54 lr 0.000435	time 0.4580 (0.4833)	model_time 0.4575 (0.4720)	loss 2.9922 (2.8501)	grad_norm 1.4055 (2.9121/1.3483)	mem 16099MB
[2025-01-18 09:16:05 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][210/312]	eta 0:00:49 lr 0.000434	time 0.4681 (0.4821)	model_time 0.4679 (0.4713)	loss 3.2134 (2.8563)	grad_norm 2.0257 (2.8654/1.3365)	mem 16099MB
[2025-01-18 09:16:09 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][220/312]	eta 0:00:44 lr 0.000434	time 0.4551 (0.4816)	model_time 0.4550 (0.4713)	loss 2.5273 (2.8619)	grad_norm 2.4378 (2.8631/1.3290)	mem 16099MB
[2025-01-18 09:16:14 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][230/312]	eta 0:00:39 lr 0.000434	time 0.4403 (0.4813)	model_time 0.4398 (0.4714)	loss 2.7119 (2.8605)	grad_norm 4.8606 (2.8468/1.3217)	mem 16099MB
[2025-01-18 09:16:19 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][240/312]	eta 0:00:34 lr 0.000433	time 0.4458 (0.4807)	model_time 0.4454 (0.4712)	loss 3.1782 (2.8572)	grad_norm 1.4102 (2.8566/1.3297)	mem 16099MB
[2025-01-18 09:16:23 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][250/312]	eta 0:00:29 lr 0.000433	time 0.4466 (0.4802)	model_time 0.4461 (0.4710)	loss 3.2039 (2.8504)	grad_norm 2.2698 (2.8221/1.3164)	mem 16099MB
[2025-01-18 09:16:28 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][260/312]	eta 0:00:24 lr 0.000432	time 0.4659 (0.4799)	model_time 0.4657 (0.4710)	loss 3.0031 (2.8484)	grad_norm 2.3019 (2.8073/1.3059)	mem 16099MB
[2025-01-18 09:16:33 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][270/312]	eta 0:00:20 lr 0.000432	time 0.4501 (0.4791)	model_time 0.4497 (0.4706)	loss 3.2224 (2.8477)	grad_norm 2.7155 (2.7954/1.2904)	mem 16099MB
[2025-01-18 09:16:37 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][280/312]	eta 0:00:15 lr 0.000432	time 0.5310 (0.4788)	model_time 0.5305 (0.4706)	loss 2.7185 (2.8491)	grad_norm 6.4040 (2.8037/1.3024)	mem 16099MB
[2025-01-18 09:16:42 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][290/312]	eta 0:00:10 lr 0.000431	time 0.4679 (0.4780)	model_time 0.4677 (0.4700)	loss 1.9975 (2.8369)	grad_norm 1.1549 (2.7782/1.2932)	mem 16099MB
[2025-01-18 09:16:46 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][300/312]	eta 0:00:05 lr 0.000431	time 0.4399 (0.4772)	model_time 0.4398 (0.4695)	loss 2.3306 (2.8343)	grad_norm 1.8283 (2.7505/1.2857)	mem 16099MB
[2025-01-18 09:16:51 internimage_t_1k_224] (main.py 510): INFO Train: [238/300][310/312]	eta 0:00:00 lr 0.000431	time 0.4404 (0.4771)	model_time 0.4403 (0.4696)	loss 2.0352 (2.8357)	grad_norm 1.8377 (2.7691/1.3041)	mem 16099MB
[2025-01-18 09:16:52 internimage_t_1k_224] (main.py 519): INFO EPOCH 238 training takes 0:02:28
[2025-01-18 09:16:52 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_238.pth saving......
[2025-01-18 09:16:53 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_238.pth saved !!!
[2025-01-18 09:17:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.390 (7.390)	Loss 0.7494 (0.7494)	Acc@1 84.888 (84.888)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 09:17:04 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.996)	Loss 0.9991 (0.8572)	Acc@1 78.491 (82.366)	Acc@5 94.971 (96.158)	Mem 16099MB
[2025-01-18 09:17:04 internimage_t_1k_224] (main.py 575): INFO [Epoch:238] * Acc@1 82.208 Acc@5 96.153
[2025-01-18 09:17:04 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.2%
[2025-01-18 09:17:04 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.37%
[2025-01-18 09:17:12 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.103 (8.103)	Loss 0.7464 (0.7464)	Acc@1 85.864 (85.864)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 09:17:16 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.101)	Loss 0.9895 (0.8540)	Acc@1 79.028 (83.201)	Acc@5 95.337 (96.431)	Mem 16099MB
[2025-01-18 09:17:16 internimage_t_1k_224] (main.py 575): INFO [Epoch:238] * Acc@1 83.077 Acc@5 96.457
[2025-01-18 09:17:16 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.1%
[2025-01-18 09:17:16 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.08%
[2025-01-18 09:17:19 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][0/312]	eta 0:16:59 lr 0.000430	time 3.2662 (3.2662)	model_time 0.7979 (0.7979)	loss 3.0733 (3.0733)	grad_norm 1.7145 (1.7145/0.0000)	mem 16099MB
[2025-01-18 09:17:24 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][10/312]	eta 0:03:46 lr 0.000430	time 0.4506 (0.7508)	model_time 0.4505 (0.5259)	loss 2.6972 (2.8411)	grad_norm 2.4346 (2.7535/0.7545)	mem 16099MB
[2025-01-18 09:17:29 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][20/312]	eta 0:02:58 lr 0.000430	time 0.4551 (0.6098)	model_time 0.4546 (0.4918)	loss 3.1574 (2.8515)	grad_norm 1.9723 (2.3930/0.7995)	mem 16099MB
[2025-01-18 09:17:34 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][30/312]	eta 0:02:40 lr 0.000429	time 0.5675 (0.5705)	model_time 0.5670 (0.4904)	loss 3.5257 (2.8542)	grad_norm 2.7652 (2.2884/0.7517)	mem 16099MB
[2025-01-18 09:17:39 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][40/312]	eta 0:02:28 lr 0.000429	time 0.4540 (0.5464)	model_time 0.4538 (0.4858)	loss 2.6943 (2.9217)	grad_norm 1.8598 (2.3326/0.8361)	mem 16099MB
[2025-01-18 09:17:43 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][50/312]	eta 0:02:19 lr 0.000428	time 0.5532 (0.5313)	model_time 0.5530 (0.4825)	loss 3.0782 (2.8545)	grad_norm 5.0849 (2.5144/1.0742)	mem 16099MB
[2025-01-18 09:17:48 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][60/312]	eta 0:02:11 lr 0.000428	time 0.5531 (0.5205)	model_time 0.5527 (0.4796)	loss 2.7163 (2.7934)	grad_norm 1.7861 (2.5074/0.9998)	mem 16099MB
[2025-01-18 09:17:52 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][70/312]	eta 0:02:03 lr 0.000428	time 0.4609 (0.5120)	model_time 0.4608 (0.4769)	loss 3.5091 (2.8540)	grad_norm 1.8548 (2.4638/0.9729)	mem 16099MB
[2025-01-18 09:17:57 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][80/312]	eta 0:01:57 lr 0.000427	time 0.4519 (0.5074)	model_time 0.4517 (0.4765)	loss 1.8451 (2.8484)	grad_norm 2.1325 (2.4948/0.9886)	mem 16099MB
[2025-01-18 09:18:02 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][90/312]	eta 0:01:51 lr 0.000427	time 0.4520 (0.5026)	model_time 0.4516 (0.4751)	loss 3.0083 (2.8564)	grad_norm 1.9664 (2.5106/1.0176)	mem 16099MB
[2025-01-18 09:18:06 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][100/312]	eta 0:01:45 lr 0.000426	time 0.4586 (0.4987)	model_time 0.4582 (0.4739)	loss 2.8115 (2.8550)	grad_norm 2.1376 (2.4865/1.0408)	mem 16099MB
[2025-01-18 09:18:11 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][110/312]	eta 0:01:40 lr 0.000426	time 0.4602 (0.4952)	model_time 0.4600 (0.4726)	loss 2.8116 (2.8640)	grad_norm 2.5198 (2.4704/1.0214)	mem 16099MB
[2025-01-18 09:18:16 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][120/312]	eta 0:01:34 lr 0.000426	time 0.4508 (0.4924)	model_time 0.4504 (0.4716)	loss 3.3756 (2.8662)	grad_norm 2.2641 (2.4469/1.0027)	mem 16099MB
[2025-01-18 09:18:20 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][130/312]	eta 0:01:29 lr 0.000425	time 0.4648 (0.4909)	model_time 0.4646 (0.4717)	loss 2.3713 (2.8611)	grad_norm 2.3272 (2.4547/0.9896)	mem 16099MB
[2025-01-18 09:18:25 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][140/312]	eta 0:01:24 lr 0.000425	time 0.4757 (0.4902)	model_time 0.4756 (0.4723)	loss 3.2027 (2.8524)	grad_norm 6.7189 (2.5102/1.0398)	mem 16099MB
[2025-01-18 09:18:30 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][150/312]	eta 0:01:19 lr 0.000424	time 0.4623 (0.4888)	model_time 0.4618 (0.4721)	loss 3.4073 (2.8570)	grad_norm 1.1590 (2.5204/1.0645)	mem 16099MB
[2025-01-18 09:18:35 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][160/312]	eta 0:01:14 lr 0.000424	time 0.4869 (0.4872)	model_time 0.4867 (0.4715)	loss 2.9328 (2.8658)	grad_norm 1.8645 (2.5426/1.1349)	mem 16099MB
[2025-01-18 09:18:39 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][170/312]	eta 0:01:09 lr 0.000424	time 0.4477 (0.4864)	model_time 0.4475 (0.4716)	loss 2.8711 (2.8797)	grad_norm 5.2441 (2.6002/1.1728)	mem 16099MB
[2025-01-18 09:18:44 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][180/312]	eta 0:01:04 lr 0.000423	time 0.5715 (0.4863)	model_time 0.5714 (0.4722)	loss 3.0815 (2.8774)	grad_norm 6.1189 (2.6587/1.2442)	mem 16099MB
[2025-01-18 09:18:49 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][190/312]	eta 0:00:59 lr 0.000423	time 0.4777 (0.4851)	model_time 0.4775 (0.4718)	loss 3.1681 (2.8746)	grad_norm 4.5556 (2.7505/1.3185)	mem 16099MB
[2025-01-18 09:18:53 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][200/312]	eta 0:00:54 lr 0.000423	time 0.4522 (0.4840)	model_time 0.4518 (0.4713)	loss 2.7771 (2.8658)	grad_norm 4.2463 (2.7367/1.3183)	mem 16099MB
[2025-01-18 09:18:58 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][210/312]	eta 0:00:49 lr 0.000422	time 0.4417 (0.4832)	model_time 0.4416 (0.4711)	loss 3.5112 (2.8594)	grad_norm 5.1798 (2.7341/1.3109)	mem 16099MB
[2025-01-18 09:19:03 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][220/312]	eta 0:00:44 lr 0.000422	time 0.4514 (0.4822)	model_time 0.4512 (0.4707)	loss 3.1384 (2.8607)	grad_norm 2.0052 (2.7006/1.2929)	mem 16099MB
[2025-01-18 09:19:07 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][230/312]	eta 0:00:39 lr 0.000421	time 0.4416 (0.4815)	model_time 0.4411 (0.4704)	loss 3.0342 (2.8656)	grad_norm 3.7942 (2.7034/1.2850)	mem 16099MB
[2025-01-18 09:19:12 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][240/312]	eta 0:00:34 lr 0.000421	time 0.4449 (0.4807)	model_time 0.4445 (0.4701)	loss 3.1628 (2.8722)	grad_norm 2.2211 (2.7183/1.2796)	mem 16099MB
[2025-01-18 09:19:17 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][250/312]	eta 0:00:29 lr 0.000421	time 0.4432 (0.4807)	model_time 0.4427 (0.4704)	loss 3.0550 (2.8690)	grad_norm 3.8607 (2.7052/1.2629)	mem 16099MB
[2025-01-18 09:19:21 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][260/312]	eta 0:00:24 lr 0.000420	time 0.4707 (0.4802)	model_time 0.4705 (0.4704)	loss 2.7961 (2.8623)	grad_norm 2.7138 (2.7098/1.2467)	mem 16099MB
[2025-01-18 09:19:26 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][270/312]	eta 0:00:20 lr 0.000420	time 0.4410 (0.4798)	model_time 0.4408 (0.4703)	loss 3.7231 (2.8612)	grad_norm 1.8388 (2.6724/1.2430)	mem 16099MB
[2025-01-18 09:19:31 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][280/312]	eta 0:00:15 lr 0.000419	time 0.4405 (0.4794)	model_time 0.4403 (0.4702)	loss 3.0139 (2.8620)	grad_norm 1.7399 (2.6735/1.2466)	mem 16099MB
[2025-01-18 09:19:35 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][290/312]	eta 0:00:10 lr 0.000419	time 0.4553 (0.4788)	model_time 0.4548 (0.4700)	loss 3.3150 (2.8656)	grad_norm 1.1172 (2.7108/1.2808)	mem 16099MB
[2025-01-18 09:19:40 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][300/312]	eta 0:00:05 lr 0.000419	time 0.4385 (0.4784)	model_time 0.4384 (0.4698)	loss 3.4492 (2.8645)	grad_norm 2.6797 (2.7117/1.2798)	mem 16099MB
[2025-01-18 09:19:45 internimage_t_1k_224] (main.py 510): INFO Train: [239/300][310/312]	eta 0:00:00 lr 0.000418	time 0.5247 (0.4774)	model_time 0.5246 (0.4691)	loss 2.1004 (2.8561)	grad_norm 2.3807 (2.6784/1.2873)	mem 16099MB
[2025-01-18 09:19:45 internimage_t_1k_224] (main.py 519): INFO EPOCH 239 training takes 0:02:28
[2025-01-18 09:19:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_239.pth saving......
[2025-01-18 09:19:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_239.pth saved !!!
[2025-01-18 09:19:53 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.298 (7.298)	Loss 0.7183 (0.7183)	Acc@1 85.107 (85.107)	Acc@5 97.339 (97.339)	Mem 16099MB
[2025-01-18 09:19:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.994)	Loss 0.9908 (0.8410)	Acc@1 77.954 (82.466)	Acc@5 94.971 (96.096)	Mem 16099MB
[2025-01-18 09:19:57 internimage_t_1k_224] (main.py 575): INFO [Epoch:239] * Acc@1 82.294 Acc@5 96.083
[2025-01-18 09:19:57 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.3%
[2025-01-18 09:19:57 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.37%
[2025-01-18 09:20:06 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.424 (8.424)	Loss 0.7454 (0.7454)	Acc@1 85.815 (85.815)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 09:20:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.140)	Loss 0.9882 (0.8529)	Acc@1 79.126 (83.236)	Acc@5 95.337 (96.433)	Mem 16099MB
[2025-01-18 09:20:10 internimage_t_1k_224] (main.py 575): INFO [Epoch:239] * Acc@1 83.111 Acc@5 96.459
[2025-01-18 09:20:10 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.1%
[2025-01-18 09:20:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:20:11 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:20:11 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.11%
[2025-01-18 09:20:14 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][0/312]	eta 0:11:24 lr 0.000418	time 2.1951 (2.1951)	model_time 0.4696 (0.4696)	loss 2.5113 (2.5113)	grad_norm 1.8868 (1.8868/0.0000)	mem 16099MB
[2025-01-18 09:20:19 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][10/312]	eta 0:03:14 lr 0.000418	time 0.4550 (0.6452)	model_time 0.4545 (0.4879)	loss 2.4524 (2.8774)	grad_norm 2.6616 (2.2638/0.5348)	mem 16099MB
[2025-01-18 09:20:23 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][20/312]	eta 0:02:43 lr 0.000417	time 0.4523 (0.5610)	model_time 0.4519 (0.4784)	loss 3.2459 (2.8330)	grad_norm 1.9369 (2.3718/0.7852)	mem 16099MB
[2025-01-18 09:20:28 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][30/312]	eta 0:02:30 lr 0.000417	time 0.5105 (0.5320)	model_time 0.5101 (0.4760)	loss 1.8396 (2.8522)	grad_norm 1.5665 (2.2574/0.8075)	mem 16099MB
[2025-01-18 09:20:33 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][40/312]	eta 0:02:21 lr 0.000417	time 0.4523 (0.5193)	model_time 0.4518 (0.4768)	loss 2.7771 (2.8313)	grad_norm 2.3070 (2.3610/0.8424)	mem 16099MB
[2025-01-18 09:20:37 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][50/312]	eta 0:02:13 lr 0.000416	time 0.4435 (0.5102)	model_time 0.4430 (0.4760)	loss 2.2076 (2.8246)	grad_norm 6.4157 (2.5387/1.0541)	mem 16099MB
[2025-01-18 09:20:42 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][60/312]	eta 0:02:06 lr 0.000416	time 0.4605 (0.5031)	model_time 0.4603 (0.4744)	loss 2.6827 (2.8372)	grad_norm 2.4980 (2.6882/1.1739)	mem 16099MB
[2025-01-18 09:20:47 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][70/312]	eta 0:02:00 lr 0.000415	time 0.4536 (0.4978)	model_time 0.4531 (0.4731)	loss 2.9239 (2.8206)	grad_norm 4.4017 (2.9665/1.5184)	mem 16099MB
[2025-01-18 09:20:51 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][80/312]	eta 0:01:54 lr 0.000415	time 0.4438 (0.4924)	model_time 0.4437 (0.4707)	loss 2.0513 (2.8117)	grad_norm 2.4373 (3.0358/1.4882)	mem 16099MB
[2025-01-18 09:20:56 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][90/312]	eta 0:01:48 lr 0.000415	time 0.4641 (0.4892)	model_time 0.4640 (0.4698)	loss 2.7998 (2.7983)	grad_norm 2.0702 (2.9030/1.4614)	mem 16099MB
[2025-01-18 09:21:01 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][100/312]	eta 0:01:43 lr 0.000414	time 0.4463 (0.4875)	model_time 0.4461 (0.4701)	loss 1.7607 (2.7949)	grad_norm 2.3305 (2.8302/1.4324)	mem 16099MB
[2025-01-18 09:21:05 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][110/312]	eta 0:01:38 lr 0.000414	time 0.4440 (0.4853)	model_time 0.4435 (0.4694)	loss 1.8016 (2.7973)	grad_norm 1.3237 (2.8441/1.3927)	mem 16099MB
[2025-01-18 09:21:10 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][120/312]	eta 0:01:32 lr 0.000413	time 0.4435 (0.4835)	model_time 0.4431 (0.4689)	loss 2.5485 (2.7964)	grad_norm 2.1972 (2.8094/1.3836)	mem 16099MB
[2025-01-18 09:21:14 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][130/312]	eta 0:01:27 lr 0.000413	time 0.4409 (0.4813)	model_time 0.4407 (0.4677)	loss 3.1018 (2.7910)	grad_norm 1.8910 (2.7674/1.3532)	mem 16099MB
[2025-01-18 09:21:19 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][140/312]	eta 0:01:22 lr 0.000413	time 0.5272 (0.4802)	model_time 0.5268 (0.4676)	loss 2.5941 (2.7876)	grad_norm 5.3386 (2.7909/1.3522)	mem 16099MB
[2025-01-18 09:21:24 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][150/312]	eta 0:01:17 lr 0.000412	time 0.4492 (0.4801)	model_time 0.4488 (0.4683)	loss 2.8741 (2.7922)	grad_norm 4.4244 (2.8283/1.3507)	mem 16099MB
[2025-01-18 09:21:29 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][160/312]	eta 0:01:12 lr 0.000412	time 0.4441 (0.4802)	model_time 0.4437 (0.4691)	loss 3.2632 (2.7907)	grad_norm 1.9912 (2.8560/1.3493)	mem 16099MB
[2025-01-18 09:21:33 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][170/312]	eta 0:01:08 lr 0.000412	time 0.4570 (0.4791)	model_time 0.4569 (0.4686)	loss 3.0083 (2.7985)	grad_norm 1.9397 (2.8553/1.3414)	mem 16099MB
[2025-01-18 09:21:38 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][180/312]	eta 0:01:03 lr 0.000411	time 0.5577 (0.4795)	model_time 0.5575 (0.4696)	loss 2.8242 (2.7987)	grad_norm 2.5721 (2.8096/1.3251)	mem 16099MB
[2025-01-18 09:21:43 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][190/312]	eta 0:00:58 lr 0.000411	time 0.4931 (0.4784)	model_time 0.4927 (0.4689)	loss 2.9770 (2.7956)	grad_norm 5.6103 (2.8441/1.3508)	mem 16099MB
[2025-01-18 09:21:48 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][200/312]	eta 0:00:53 lr 0.000410	time 0.4496 (0.4784)	model_time 0.4492 (0.4694)	loss 2.3332 (2.7853)	grad_norm 4.3006 (2.8377/1.3289)	mem 16099MB
[2025-01-18 09:21:52 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][210/312]	eta 0:00:48 lr 0.000410	time 0.4425 (0.4775)	model_time 0.4423 (0.4690)	loss 3.1717 (2.7936)	grad_norm 2.3411 (2.8590/1.3744)	mem 16099MB
[2025-01-18 09:21:57 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][220/312]	eta 0:00:43 lr 0.000410	time 0.4766 (0.4768)	model_time 0.4764 (0.4686)	loss 2.7759 (2.7924)	grad_norm 2.7391 (2.8268/1.3556)	mem 16099MB
[2025-01-18 09:22:01 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][230/312]	eta 0:00:39 lr 0.000409	time 0.5299 (0.4761)	model_time 0.5295 (0.4682)	loss 3.0036 (2.8015)	grad_norm 2.5747 (2.7947/1.3435)	mem 16099MB
[2025-01-18 09:22:06 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][240/312]	eta 0:00:34 lr 0.000409	time 0.4553 (0.4752)	model_time 0.4550 (0.4676)	loss 3.0136 (2.8026)	grad_norm 1.7372 (2.8148/1.3560)	mem 16099MB
[2025-01-18 09:22:11 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][250/312]	eta 0:00:29 lr 0.000408	time 0.4513 (0.4751)	model_time 0.4508 (0.4678)	loss 3.6138 (2.8055)	grad_norm 2.8528 (2.8095/1.3624)	mem 16099MB
[2025-01-18 09:22:15 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][260/312]	eta 0:00:24 lr 0.000408	time 0.4722 (0.4745)	model_time 0.4717 (0.4675)	loss 2.9191 (2.8045)	grad_norm 1.9309 (2.7745/1.3517)	mem 16099MB
[2025-01-18 09:22:20 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][270/312]	eta 0:00:19 lr 0.000408	time 0.4430 (0.4743)	model_time 0.4425 (0.4675)	loss 3.1605 (2.8002)	grad_norm 4.5891 (2.7739/1.3466)	mem 16099MB
[2025-01-18 09:22:25 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][280/312]	eta 0:00:15 lr 0.000407	time 0.4967 (0.4740)	model_time 0.4963 (0.4675)	loss 3.5432 (2.7983)	grad_norm 2.2049 (2.7562/1.3318)	mem 16099MB
[2025-01-18 09:22:29 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][290/312]	eta 0:00:10 lr 0.000407	time 0.4611 (0.4739)	model_time 0.4609 (0.4676)	loss 3.1594 (2.8013)	grad_norm 3.5350 (2.7579/1.3202)	mem 16099MB
[2025-01-18 09:22:34 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][300/312]	eta 0:00:05 lr 0.000407	time 0.4387 (0.4740)	model_time 0.4386 (0.4679)	loss 2.9546 (2.8036)	grad_norm 3.1319 (2.7358/1.3103)	mem 16099MB
[2025-01-18 09:22:39 internimage_t_1k_224] (main.py 510): INFO Train: [240/300][310/312]	eta 0:00:00 lr 0.000406	time 0.4389 (0.4731)	model_time 0.4389 (0.4672)	loss 2.7996 (2.8023)	grad_norm 2.2394 (2.7196/1.3165)	mem 16099MB
[2025-01-18 09:22:39 internimage_t_1k_224] (main.py 519): INFO EPOCH 240 training takes 0:02:27
[2025-01-18 09:22:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_240.pth saving......
[2025-01-18 09:22:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_240.pth saved !!!
[2025-01-18 09:22:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.281 (7.281)	Loss 0.7301 (0.7301)	Acc@1 84.863 (84.863)	Acc@5 97.583 (97.583)	Mem 16099MB
[2025-01-18 09:22:51 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.971)	Loss 0.9697 (0.8401)	Acc@1 78.931 (82.575)	Acc@5 95.142 (96.180)	Mem 16099MB
[2025-01-18 09:22:51 internimage_t_1k_224] (main.py 575): INFO [Epoch:240] * Acc@1 82.438 Acc@5 96.163
[2025-01-18 09:22:51 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.4%
[2025-01-18 09:22:51 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 09:22:52 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 09:22:52 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.44%
[2025-01-18 09:22:59 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.212 (7.212)	Loss 0.7445 (0.7445)	Acc@1 85.815 (85.815)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 09:23:03 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.965)	Loss 0.9867 (0.8517)	Acc@1 79.126 (83.245)	Acc@5 95.386 (96.436)	Mem 16099MB
[2025-01-18 09:23:03 internimage_t_1k_224] (main.py 575): INFO [Epoch:240] * Acc@1 83.113 Acc@5 96.461
[2025-01-18 09:23:03 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.1%
[2025-01-18 09:23:03 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:23:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:23:04 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.11%
[2025-01-18 09:23:07 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][0/312]	eta 0:14:04 lr 0.000406	time 2.7074 (2.7074)	model_time 0.4732 (0.4732)	loss 2.0333 (2.0333)	grad_norm 2.0198 (2.0198/0.0000)	mem 16099MB
[2025-01-18 09:23:12 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][10/312]	eta 0:03:19 lr 0.000406	time 0.4663 (0.6611)	model_time 0.4659 (0.4576)	loss 2.8539 (2.8993)	grad_norm 3.6030 (2.0920/0.6188)	mem 16099MB
[2025-01-18 09:23:16 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][20/312]	eta 0:02:44 lr 0.000405	time 0.4720 (0.5626)	model_time 0.4715 (0.4558)	loss 2.7933 (2.7272)	grad_norm 1.6752 (2.3491/0.9545)	mem 16099MB
[2025-01-18 09:23:21 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][30/312]	eta 0:02:31 lr 0.000405	time 0.4739 (0.5366)	model_time 0.4735 (0.4642)	loss 3.3473 (2.8005)	grad_norm 1.7425 (2.4578/0.9481)	mem 16099MB
[2025-01-18 09:23:26 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][40/312]	eta 0:02:21 lr 0.000405	time 0.4593 (0.5185)	model_time 0.4592 (0.4636)	loss 2.7074 (2.8503)	grad_norm 2.6522 (2.8533/1.3585)	mem 16099MB
[2025-01-18 09:23:30 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][50/312]	eta 0:02:13 lr 0.000404	time 0.4433 (0.5100)	model_time 0.4431 (0.4658)	loss 3.4667 (2.8137)	grad_norm 2.6038 (2.8746/1.2573)	mem 16099MB
[2025-01-18 09:23:35 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][60/312]	eta 0:02:07 lr 0.000404	time 0.4443 (0.5042)	model_time 0.4441 (0.4672)	loss 2.7688 (2.8185)	grad_norm 4.1083 (2.8673/1.2455)	mem 16099MB
[2025-01-18 09:23:40 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][70/312]	eta 0:02:00 lr 0.000403	time 0.4651 (0.4998)	model_time 0.4649 (0.4680)	loss 2.7228 (2.7972)	grad_norm 4.9710 (3.0078/1.2714)	mem 16099MB
[2025-01-18 09:23:45 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][80/312]	eta 0:01:55 lr 0.000403	time 0.4505 (0.4959)	model_time 0.4503 (0.4679)	loss 3.1263 (2.8062)	grad_norm 2.1132 (2.9854/1.2592)	mem 16099MB
[2025-01-18 09:23:49 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][90/312]	eta 0:01:49 lr 0.000403	time 0.4551 (0.4920)	model_time 0.4547 (0.4670)	loss 2.2383 (2.8084)	grad_norm 7.2286 (3.1391/1.3868)	mem 16099MB
[2025-01-18 09:23:54 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][100/312]	eta 0:01:43 lr 0.000402	time 0.4556 (0.4905)	model_time 0.4552 (0.4680)	loss 2.5168 (2.8198)	grad_norm 3.9686 (3.2198/1.3816)	mem 16099MB
[2025-01-18 09:23:59 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][110/312]	eta 0:01:38 lr 0.000402	time 0.4563 (0.4872)	model_time 0.4562 (0.4667)	loss 2.9995 (2.8304)	grad_norm 2.2098 (3.1802/1.3748)	mem 16099MB
[2025-01-18 09:24:03 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][120/312]	eta 0:01:33 lr 0.000401	time 0.4466 (0.4846)	model_time 0.4462 (0.4657)	loss 2.8542 (2.8406)	grad_norm 2.1018 (3.0741/1.3691)	mem 16099MB
[2025-01-18 09:24:08 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][130/312]	eta 0:01:28 lr 0.000401	time 0.4599 (0.4857)	model_time 0.4595 (0.4683)	loss 3.1031 (2.8437)	grad_norm 2.0176 (2.9925/1.3533)	mem 16099MB
[2025-01-18 09:24:13 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][140/312]	eta 0:01:23 lr 0.000401	time 0.4514 (0.4863)	model_time 0.4513 (0.4701)	loss 3.0048 (2.8440)	grad_norm 2.2216 (3.0380/1.4091)	mem 16099MB
[2025-01-18 09:24:18 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][150/312]	eta 0:01:18 lr 0.000400	time 0.4460 (0.4850)	model_time 0.4458 (0.4699)	loss 1.8812 (2.8395)	grad_norm 2.5124 (3.0895/1.4153)	mem 16099MB
[2025-01-18 09:24:23 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][160/312]	eta 0:01:13 lr 0.000400	time 0.4430 (0.4852)	model_time 0.4429 (0.4709)	loss 2.1851 (2.8249)	grad_norm 2.2281 (3.0655/1.3968)	mem 16099MB
[2025-01-18 09:24:27 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][170/312]	eta 0:01:08 lr 0.000400	time 0.4492 (0.4834)	model_time 0.4488 (0.4699)	loss 3.1012 (2.8131)	grad_norm 2.0978 (3.0764/1.4054)	mem 16099MB
[2025-01-18 09:24:32 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][180/312]	eta 0:01:03 lr 0.000399	time 0.4528 (0.4829)	model_time 0.4523 (0.4701)	loss 3.3695 (2.8210)	grad_norm 1.6106 (3.0414/1.4068)	mem 16099MB
[2025-01-18 09:24:37 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][190/312]	eta 0:00:58 lr 0.000399	time 0.4527 (0.4832)	model_time 0.4525 (0.4711)	loss 2.3889 (2.8121)	grad_norm 2.3059 (2.9962/1.4010)	mem 16099MB
[2025-01-18 09:24:41 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][200/312]	eta 0:00:54 lr 0.000398	time 0.4633 (0.4822)	model_time 0.4628 (0.4707)	loss 3.1622 (2.8114)	grad_norm 3.0390 (3.0246/1.3855)	mem 16099MB
[2025-01-18 09:24:46 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][210/312]	eta 0:00:49 lr 0.000398	time 0.4471 (0.4818)	model_time 0.4466 (0.4708)	loss 3.1597 (2.8166)	grad_norm 2.6075 (3.0132/1.3778)	mem 16099MB
[2025-01-18 09:24:51 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][220/312]	eta 0:00:44 lr 0.000398	time 0.4490 (0.4809)	model_time 0.4486 (0.4704)	loss 3.1382 (2.8189)	grad_norm 5.4506 (3.0120/1.3760)	mem 16099MB
[2025-01-18 09:24:55 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][230/312]	eta 0:00:39 lr 0.000397	time 0.4479 (0.4803)	model_time 0.4477 (0.4702)	loss 3.1688 (2.8274)	grad_norm 3.0971 (3.0136/1.3689)	mem 16099MB
[2025-01-18 09:25:00 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][240/312]	eta 0:00:34 lr 0.000397	time 0.4485 (0.4794)	model_time 0.4483 (0.4697)	loss 3.3654 (2.8268)	grad_norm 2.4254 (2.9707/1.3637)	mem 16099MB
[2025-01-18 09:25:05 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][250/312]	eta 0:00:29 lr 0.000396	time 0.4543 (0.4783)	model_time 0.4538 (0.4690)	loss 3.5530 (2.8309)	grad_norm 1.9701 (2.9517/1.3515)	mem 16099MB
[2025-01-18 09:25:09 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][260/312]	eta 0:00:24 lr 0.000396	time 0.4450 (0.4777)	model_time 0.4448 (0.4688)	loss 3.3705 (2.8330)	grad_norm 3.2924 (2.9827/1.3573)	mem 16099MB
[2025-01-18 09:25:14 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][270/312]	eta 0:00:20 lr 0.000396	time 0.4802 (0.4777)	model_time 0.4797 (0.4691)	loss 2.8564 (2.8333)	grad_norm 1.4197 (2.9688/1.3463)	mem 16099MB
[2025-01-18 09:25:18 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][280/312]	eta 0:00:15 lr 0.000395	time 0.4488 (0.4770)	model_time 0.4486 (0.4686)	loss 2.7801 (2.8340)	grad_norm 1.6679 (2.9359/1.3347)	mem 16099MB
[2025-01-18 09:25:23 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][290/312]	eta 0:00:10 lr 0.000395	time 0.4526 (0.4772)	model_time 0.4524 (0.4691)	loss 2.4350 (2.8286)	grad_norm 1.1934 (2.9001/1.3302)	mem 16099MB
[2025-01-18 09:25:28 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][300/312]	eta 0:00:05 lr 0.000395	time 0.4482 (0.4770)	model_time 0.4481 (0.4692)	loss 2.7194 (2.8275)	grad_norm 5.7137 (2.9123/1.3384)	mem 16099MB
[2025-01-18 09:25:33 internimage_t_1k_224] (main.py 510): INFO Train: [241/300][310/312]	eta 0:00:00 lr 0.000394	time 0.4392 (0.4764)	model_time 0.4391 (0.4688)	loss 2.6961 (2.8286)	grad_norm 1.8234 (2.9128/1.3436)	mem 16099MB
[2025-01-18 09:25:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 241 training takes 0:02:28
[2025-01-18 09:25:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_241.pth saving......
[2025-01-18 09:25:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_241.pth saved !!!
[2025-01-18 09:25:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.368 (7.368)	Loss 0.7313 (0.7313)	Acc@1 84.912 (84.912)	Acc@5 97.217 (97.217)	Mem 16099MB
[2025-01-18 09:25:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.996)	Loss 0.9841 (0.8346)	Acc@1 78.320 (82.599)	Acc@5 94.824 (96.134)	Mem 16099MB
[2025-01-18 09:25:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:241] * Acc@1 82.456 Acc@5 96.127
[2025-01-18 09:25:45 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.5%
[2025-01-18 09:25:45 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 09:25:46 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 09:25:46 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.46%
[2025-01-18 09:25:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.403 (7.403)	Loss 0.7435 (0.7435)	Acc@1 85.767 (85.767)	Acc@5 97.681 (97.681)	Mem 16099MB
[2025-01-18 09:25:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.990)	Loss 0.9851 (0.8505)	Acc@1 79.077 (83.259)	Acc@5 95.410 (96.436)	Mem 16099MB
[2025-01-18 09:25:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:241] * Acc@1 83.131 Acc@5 96.463
[2025-01-18 09:25:58 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.1%
[2025-01-18 09:25:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:25:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:25:59 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.13%
[2025-01-18 09:26:01 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][0/312]	eta 0:12:36 lr 0.000394	time 2.4238 (2.4238)	model_time 0.4786 (0.4786)	loss 2.2894 (2.2894)	grad_norm 3.8117 (3.8117/0.0000)	mem 16099MB
[2025-01-18 09:26:06 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][10/312]	eta 0:03:15 lr 0.000394	time 0.4538 (0.6467)	model_time 0.4536 (0.4695)	loss 3.0710 (2.9537)	grad_norm 1.6906 (2.6248/0.8849)	mem 16099MB
[2025-01-18 09:26:11 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][20/312]	eta 0:02:42 lr 0.000393	time 0.4532 (0.5559)	model_time 0.4530 (0.4629)	loss 2.5201 (2.8829)	grad_norm 2.8332 (2.9997/1.0565)	mem 16099MB
[2025-01-18 09:26:15 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][30/312]	eta 0:02:29 lr 0.000393	time 0.4593 (0.5285)	model_time 0.4589 (0.4654)	loss 3.4460 (2.8611)	grad_norm 1.5566 (2.8453/1.1050)	mem 16099MB
[2025-01-18 09:26:20 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][40/312]	eta 0:02:19 lr 0.000393	time 0.5785 (0.5130)	model_time 0.5783 (0.4652)	loss 1.9704 (2.8378)	grad_norm 1.5078 (2.8072/1.0683)	mem 16099MB
[2025-01-18 09:26:25 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][50/312]	eta 0:02:13 lr 0.000392	time 0.4637 (0.5078)	model_time 0.4635 (0.4693)	loss 2.9449 (2.8080)	grad_norm 2.4933 (2.7478/1.0402)	mem 16099MB
[2025-01-18 09:26:30 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][60/312]	eta 0:02:06 lr 0.000392	time 0.4460 (0.5002)	model_time 0.4455 (0.4680)	loss 3.1729 (2.8104)	grad_norm 2.8015 (2.7580/1.0410)	mem 16099MB
[2025-01-18 09:26:34 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][70/312]	eta 0:01:59 lr 0.000391	time 0.4561 (0.4938)	model_time 0.4559 (0.4661)	loss 2.5736 (2.8049)	grad_norm 1.1797 (2.6705/1.0251)	mem 16099MB
[2025-01-18 09:26:39 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][80/312]	eta 0:01:53 lr 0.000391	time 0.4574 (0.4901)	model_time 0.4572 (0.4658)	loss 3.4905 (2.8195)	grad_norm 1.1817 (2.5280/1.0452)	mem 16099MB
[2025-01-18 09:26:43 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][90/312]	eta 0:01:47 lr 0.000391	time 0.4485 (0.4861)	model_time 0.4483 (0.4644)	loss 3.3345 (2.8374)	grad_norm 1.7888 (2.4850/1.0115)	mem 16099MB
[2025-01-18 09:26:48 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][100/312]	eta 0:01:42 lr 0.000390	time 0.4564 (0.4845)	model_time 0.4560 (0.4649)	loss 3.1085 (2.8349)	grad_norm 2.6613 (2.5349/1.0479)	mem 16099MB
[2025-01-18 09:26:53 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][110/312]	eta 0:01:37 lr 0.000390	time 0.4530 (0.4839)	model_time 0.4529 (0.4661)	loss 3.3388 (2.8439)	grad_norm 2.9248 (2.5297/1.0280)	mem 16099MB
[2025-01-18 09:26:57 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][120/312]	eta 0:01:32 lr 0.000390	time 0.4589 (0.4823)	model_time 0.4584 (0.4659)	loss 2.9168 (2.8406)	grad_norm 2.8292 (2.6262/1.0734)	mem 16099MB
[2025-01-18 09:27:02 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][130/312]	eta 0:01:27 lr 0.000389	time 0.4537 (0.4814)	model_time 0.4532 (0.4662)	loss 3.2843 (2.8459)	grad_norm 1.9226 (2.5907/1.0589)	mem 16099MB
[2025-01-18 09:27:07 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][140/312]	eta 0:01:22 lr 0.000389	time 0.4621 (0.4814)	model_time 0.4619 (0.4672)	loss 3.0790 (2.8518)	grad_norm 1.0243 (2.5928/1.0589)	mem 16099MB
[2025-01-18 09:27:12 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][150/312]	eta 0:01:17 lr 0.000388	time 0.4506 (0.4807)	model_time 0.4501 (0.4675)	loss 2.9419 (2.8465)	grad_norm 6.3920 (2.6985/1.1736)	mem 16099MB
[2025-01-18 09:27:17 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][160/312]	eta 0:01:13 lr 0.000388	time 0.5808 (0.4816)	model_time 0.5806 (0.4691)	loss 3.6442 (2.8531)	grad_norm 2.1961 (2.7619/1.2533)	mem 16099MB
[2025-01-18 09:27:21 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][170/312]	eta 0:01:08 lr 0.000388	time 0.4586 (0.4805)	model_time 0.4581 (0.4688)	loss 3.2070 (2.8638)	grad_norm 1.8777 (2.7416/1.2313)	mem 16099MB
[2025-01-18 09:27:26 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][180/312]	eta 0:01:03 lr 0.000387	time 0.4676 (0.4800)	model_time 0.4672 (0.4689)	loss 3.1049 (2.8620)	grad_norm 2.8743 (2.7170/1.2103)	mem 16099MB
[2025-01-18 09:27:31 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][190/312]	eta 0:00:58 lr 0.000387	time 0.4458 (0.4791)	model_time 0.4453 (0.4685)	loss 3.1218 (2.8551)	grad_norm 1.3932 (2.7377/1.2217)	mem 16099MB
[2025-01-18 09:27:35 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][200/312]	eta 0:00:53 lr 0.000387	time 0.5264 (0.4783)	model_time 0.5263 (0.4682)	loss 3.4706 (2.8579)	grad_norm 2.1256 (2.7144/1.2139)	mem 16099MB
[2025-01-18 09:27:40 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][210/312]	eta 0:00:48 lr 0.000386	time 0.5455 (0.4780)	model_time 0.5453 (0.4684)	loss 2.7051 (2.8589)	grad_norm 6.7942 (2.7834/1.2958)	mem 16099MB
[2025-01-18 09:27:45 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][220/312]	eta 0:00:43 lr 0.000386	time 0.4461 (0.4774)	model_time 0.4460 (0.4683)	loss 3.0122 (2.8578)	grad_norm 3.7433 (2.8127/1.3018)	mem 16099MB
[2025-01-18 09:27:49 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][230/312]	eta 0:00:39 lr 0.000385	time 0.4441 (0.4766)	model_time 0.4437 (0.4679)	loss 2.8402 (2.8571)	grad_norm 7.3173 (2.8375/1.3300)	mem 16099MB
[2025-01-18 09:27:54 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][240/312]	eta 0:00:34 lr 0.000385	time 0.4577 (0.4765)	model_time 0.4575 (0.4680)	loss 2.7059 (2.8599)	grad_norm 6.9383 (2.8786/1.3490)	mem 16099MB
[2025-01-18 09:27:58 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][250/312]	eta 0:00:29 lr 0.000385	time 0.4683 (0.4756)	model_time 0.4679 (0.4675)	loss 2.5982 (2.8551)	grad_norm 1.4178 (2.8660/1.3512)	mem 16099MB
[2025-01-18 09:28:03 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][260/312]	eta 0:00:24 lr 0.000384	time 0.4502 (0.4746)	model_time 0.4498 (0.4668)	loss 3.2570 (2.8582)	grad_norm 1.6033 (2.8498/1.3465)	mem 16099MB
[2025-01-18 09:28:08 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][270/312]	eta 0:00:19 lr 0.000384	time 0.4650 (0.4746)	model_time 0.4645 (0.4671)	loss 3.0247 (2.8562)	grad_norm 1.8396 (2.8302/1.3415)	mem 16099MB
[2025-01-18 09:28:12 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][280/312]	eta 0:00:15 lr 0.000384	time 0.4614 (0.4743)	model_time 0.4613 (0.4670)	loss 2.9552 (2.8519)	grad_norm 3.6032 (2.8286/1.3288)	mem 16099MB
[2025-01-18 09:28:17 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][290/312]	eta 0:00:10 lr 0.000383	time 0.4543 (0.4741)	model_time 0.4539 (0.4670)	loss 2.8032 (2.8490)	grad_norm 2.8857 (2.8108/1.3143)	mem 16099MB
[2025-01-18 09:28:22 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][300/312]	eta 0:00:05 lr 0.000383	time 0.4418 (0.4736)	model_time 0.4417 (0.4667)	loss 1.7509 (2.8491)	grad_norm 1.8546 (2.8015/1.2989)	mem 16099MB
[2025-01-18 09:28:26 internimage_t_1k_224] (main.py 510): INFO Train: [242/300][310/312]	eta 0:00:00 lr 0.000382	time 0.4393 (0.4734)	model_time 0.4392 (0.4667)	loss 2.9099 (2.8408)	grad_norm 2.0281 (2.7970/1.3076)	mem 16099MB
[2025-01-18 09:28:27 internimage_t_1k_224] (main.py 519): INFO EPOCH 242 training takes 0:02:27
[2025-01-18 09:28:27 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_242.pth saving......
[2025-01-18 09:28:28 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_242.pth saved !!!
[2025-01-18 09:28:35 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.418 (7.418)	Loss 0.7330 (0.7330)	Acc@1 85.181 (85.181)	Acc@5 97.217 (97.217)	Mem 16099MB
[2025-01-18 09:28:39 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.000)	Loss 0.9724 (0.8373)	Acc@1 79.370 (82.779)	Acc@5 94.922 (96.238)	Mem 16099MB
[2025-01-18 09:28:39 internimage_t_1k_224] (main.py 575): INFO [Epoch:242] * Acc@1 82.628 Acc@5 96.235
[2025-01-18 09:28:39 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.6%
[2025-01-18 09:28:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 09:28:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 09:28:40 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.63%
[2025-01-18 09:28:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.436 (7.436)	Loss 0.7426 (0.7426)	Acc@1 85.742 (85.742)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 09:28:51 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.016)	Loss 0.9838 (0.8495)	Acc@1 79.126 (83.287)	Acc@5 95.459 (96.444)	Mem 16099MB
[2025-01-18 09:28:51 internimage_t_1k_224] (main.py 575): INFO [Epoch:242] * Acc@1 83.159 Acc@5 96.471
[2025-01-18 09:28:51 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.2%
[2025-01-18 09:28:51 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:28:53 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:28:53 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.16%
[2025-01-18 09:28:55 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][0/312]	eta 0:12:17 lr 0.000382	time 2.3626 (2.3626)	model_time 0.4712 (0.4712)	loss 1.9095 (1.9095)	grad_norm 2.9911 (2.9911/0.0000)	mem 16099MB
[2025-01-18 09:29:00 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][10/312]	eta 0:03:21 lr 0.000382	time 0.4470 (0.6674)	model_time 0.4469 (0.4952)	loss 2.9387 (2.6749)	grad_norm 3.7459 (2.7527/0.8086)	mem 16099MB
[2025-01-18 09:29:05 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][20/312]	eta 0:02:46 lr 0.000382	time 0.4454 (0.5719)	model_time 0.4453 (0.4814)	loss 3.4961 (2.7841)	grad_norm 1.3336 (2.3511/0.7893)	mem 16099MB
[2025-01-18 09:29:10 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][30/312]	eta 0:02:31 lr 0.000381	time 0.4532 (0.5380)	model_time 0.4528 (0.4765)	loss 2.4335 (2.7416)	grad_norm 4.5316 (2.4114/0.9051)	mem 16099MB
[2025-01-18 09:29:14 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][40/312]	eta 0:02:21 lr 0.000381	time 0.4472 (0.5193)	model_time 0.4471 (0.4728)	loss 2.9390 (2.8011)	grad_norm 3.5294 (2.4911/0.9724)	mem 16099MB
[2025-01-18 09:29:19 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][50/312]	eta 0:02:12 lr 0.000381	time 0.4478 (0.5072)	model_time 0.4476 (0.4698)	loss 3.0540 (2.8161)	grad_norm 3.9031 (2.7769/1.1953)	mem 16099MB
[2025-01-18 09:29:24 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][60/312]	eta 0:02:07 lr 0.000380	time 0.4526 (0.5062)	model_time 0.4525 (0.4748)	loss 2.9238 (2.8228)	grad_norm 3.3007 (2.6658/1.1470)	mem 16099MB
[2025-01-18 09:29:28 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][70/312]	eta 0:02:01 lr 0.000380	time 0.4587 (0.5014)	model_time 0.4585 (0.4744)	loss 1.7371 (2.7919)	grad_norm 2.1957 (2.5890/1.1169)	mem 16099MB
[2025-01-18 09:29:33 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][80/312]	eta 0:01:55 lr 0.000379	time 0.4540 (0.4967)	model_time 0.4538 (0.4730)	loss 2.7499 (2.7869)	grad_norm 2.1908 (2.5436/1.0778)	mem 16099MB
[2025-01-18 09:29:38 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][90/312]	eta 0:01:49 lr 0.000379	time 0.5368 (0.4931)	model_time 0.5364 (0.4720)	loss 2.7738 (2.7919)	grad_norm 3.7474 (2.7792/1.4192)	mem 16099MB
[2025-01-18 09:29:42 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][100/312]	eta 0:01:43 lr 0.000379	time 0.4708 (0.4904)	model_time 0.4707 (0.4713)	loss 2.9835 (2.7895)	grad_norm 2.4547 (2.8777/1.5100)	mem 16099MB
[2025-01-18 09:29:47 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][110/312]	eta 0:01:38 lr 0.000378	time 0.4573 (0.4878)	model_time 0.4568 (0.4704)	loss 1.9649 (2.7847)	grad_norm 5.5140 (2.9351/1.5356)	mem 16099MB
[2025-01-18 09:29:52 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][120/312]	eta 0:01:33 lr 0.000378	time 0.4483 (0.4877)	model_time 0.4479 (0.4717)	loss 2.7337 (2.7821)	grad_norm 4.3410 (2.9299/1.5417)	mem 16099MB
[2025-01-18 09:29:57 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][130/312]	eta 0:01:28 lr 0.000378	time 0.4471 (0.4863)	model_time 0.4467 (0.4715)	loss 2.8277 (2.7853)	grad_norm 2.0633 (2.9664/1.5161)	mem 16099MB
[2025-01-18 09:30:02 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][140/312]	eta 0:01:23 lr 0.000377	time 0.4451 (0.4882)	model_time 0.4450 (0.4744)	loss 2.4413 (2.7851)	grad_norm 1.3164 (2.8856/1.5032)	mem 16099MB
[2025-01-18 09:30:06 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][150/312]	eta 0:01:18 lr 0.000377	time 0.4510 (0.4863)	model_time 0.4508 (0.4734)	loss 2.4349 (2.7741)	grad_norm 3.6963 (2.8349/1.4783)	mem 16099MB
[2025-01-18 09:30:11 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][160/312]	eta 0:01:13 lr 0.000376	time 0.4441 (0.4849)	model_time 0.4440 (0.4728)	loss 2.7715 (2.7817)	grad_norm 4.4029 (2.8465/1.4588)	mem 16099MB
[2025-01-18 09:30:16 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][170/312]	eta 0:01:08 lr 0.000376	time 0.4510 (0.4849)	model_time 0.4506 (0.4734)	loss 2.7716 (2.7793)	grad_norm 2.3028 (2.8606/1.4606)	mem 16099MB
[2025-01-18 09:30:20 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][180/312]	eta 0:01:03 lr 0.000376	time 0.4697 (0.4834)	model_time 0.4692 (0.4725)	loss 2.2303 (2.7697)	grad_norm 1.4150 (2.8530/1.4481)	mem 16099MB
[2025-01-18 09:30:25 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][190/312]	eta 0:00:58 lr 0.000375	time 0.4599 (0.4818)	model_time 0.4597 (0.4715)	loss 1.7137 (2.7601)	grad_norm 5.1618 (2.8206/1.4382)	mem 16099MB
[2025-01-18 09:30:30 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][200/312]	eta 0:00:53 lr 0.000375	time 0.4521 (0.4811)	model_time 0.4519 (0.4713)	loss 2.0508 (2.7568)	grad_norm 1.8384 (2.8114/1.4080)	mem 16099MB
[2025-01-18 09:30:34 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][210/312]	eta 0:00:48 lr 0.000375	time 0.4552 (0.4802)	model_time 0.4548 (0.4708)	loss 3.1033 (2.7581)	grad_norm 1.5594 (2.7582/1.3965)	mem 16099MB
[2025-01-18 09:30:39 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][220/312]	eta 0:00:44 lr 0.000374	time 0.4520 (0.4796)	model_time 0.4515 (0.4706)	loss 3.3667 (2.7655)	grad_norm 3.0842 (2.7202/1.3828)	mem 16099MB
[2025-01-18 09:30:43 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][230/312]	eta 0:00:39 lr 0.000374	time 0.4540 (0.4791)	model_time 0.4535 (0.4705)	loss 2.6762 (2.7609)	grad_norm 2.5110 (2.7484/1.3803)	mem 16099MB
[2025-01-18 09:30:48 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][240/312]	eta 0:00:34 lr 0.000373	time 0.4480 (0.4785)	model_time 0.4478 (0.4703)	loss 2.7606 (2.7569)	grad_norm 5.3785 (2.7617/1.3756)	mem 16099MB
[2025-01-18 09:30:53 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][250/312]	eta 0:00:29 lr 0.000373	time 0.4579 (0.4791)	model_time 0.4574 (0.4711)	loss 2.7556 (2.7561)	grad_norm 1.3634 (2.7572/1.3625)	mem 16099MB
[2025-01-18 09:30:58 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][260/312]	eta 0:00:24 lr 0.000373	time 0.4467 (0.4782)	model_time 0.4463 (0.4705)	loss 2.7861 (2.7640)	grad_norm 2.1939 (2.7600/1.3558)	mem 16099MB
[2025-01-18 09:31:02 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][270/312]	eta 0:00:20 lr 0.000372	time 0.4547 (0.4778)	model_time 0.4542 (0.4704)	loss 3.0603 (2.7722)	grad_norm 1.7893 (2.7889/1.3629)	mem 16099MB
[2025-01-18 09:31:07 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][280/312]	eta 0:00:15 lr 0.000372	time 0.4611 (0.4774)	model_time 0.4607 (0.4702)	loss 2.8117 (2.7738)	grad_norm 1.1107 (2.7707/1.3540)	mem 16099MB
[2025-01-18 09:31:12 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][290/312]	eta 0:00:10 lr 0.000372	time 0.4534 (0.4769)	model_time 0.4532 (0.4700)	loss 2.7834 (2.7771)	grad_norm 3.5451 (2.7765/1.3389)	mem 16099MB
[2025-01-18 09:31:16 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][300/312]	eta 0:00:05 lr 0.000371	time 0.4389 (0.4767)	model_time 0.4388 (0.4701)	loss 3.4400 (2.7817)	grad_norm 4.6903 (2.8193/1.3726)	mem 16099MB
[2025-01-18 09:31:21 internimage_t_1k_224] (main.py 510): INFO Train: [243/300][310/312]	eta 0:00:00 lr 0.000371	time 0.4424 (0.4756)	model_time 0.4424 (0.4692)	loss 3.0641 (2.7856)	grad_norm 2.1710 (2.8249/1.3726)	mem 16099MB
[2025-01-18 09:31:21 internimage_t_1k_224] (main.py 519): INFO EPOCH 243 training takes 0:02:28
[2025-01-18 09:31:21 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_243.pth saving......
[2025-01-18 09:31:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_243.pth saved !!!
[2025-01-18 09:31:30 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.531 (7.531)	Loss 0.7069 (0.7069)	Acc@1 85.205 (85.205)	Acc@5 97.339 (97.339)	Mem 16099MB
[2025-01-18 09:31:33 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.998)	Loss 0.9699 (0.8336)	Acc@1 78.857 (82.591)	Acc@5 94.971 (96.118)	Mem 16099MB
[2025-01-18 09:31:33 internimage_t_1k_224] (main.py 575): INFO [Epoch:243] * Acc@1 82.418 Acc@5 96.117
[2025-01-18 09:31:33 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.4%
[2025-01-18 09:31:33 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.63%
[2025-01-18 09:31:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.137 (8.137)	Loss 0.7417 (0.7417)	Acc@1 85.767 (85.767)	Acc@5 97.681 (97.681)	Mem 16099MB
[2025-01-18 09:31:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.111 (1.090)	Loss 0.9822 (0.8483)	Acc@1 79.126 (83.285)	Acc@5 95.435 (96.444)	Mem 16099MB
[2025-01-18 09:31:46 internimage_t_1k_224] (main.py 575): INFO [Epoch:243] * Acc@1 83.151 Acc@5 96.469
[2025-01-18 09:31:46 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.2%
[2025-01-18 09:31:46 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.16%
[2025-01-18 09:31:49 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][0/312]	eta 0:15:43 lr 0.000371	time 3.0241 (3.0241)	model_time 1.0798 (1.0798)	loss 3.3510 (3.3510)	grad_norm 4.9097 (4.9097/0.0000)	mem 16099MB
[2025-01-18 09:31:53 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][10/312]	eta 0:03:35 lr 0.000370	time 0.4525 (0.7135)	model_time 0.4521 (0.5362)	loss 2.7265 (2.9374)	grad_norm 1.7449 (3.4844/1.7633)	mem 16099MB
[2025-01-18 09:31:58 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][20/312]	eta 0:02:52 lr 0.000370	time 0.4555 (0.5901)	model_time 0.4554 (0.4965)	loss 2.8442 (2.8605)	grad_norm 2.9351 (3.1480/1.4264)	mem 16099MB
[2025-01-18 09:32:03 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][30/312]	eta 0:02:35 lr 0.000370	time 0.4562 (0.5527)	model_time 0.4560 (0.4892)	loss 2.2379 (2.7667)	grad_norm 3.8628 (2.8810/1.3163)	mem 16099MB
[2025-01-18 09:32:07 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][40/312]	eta 0:02:23 lr 0.000369	time 0.4585 (0.5287)	model_time 0.4581 (0.4806)	loss 3.1555 (2.7850)	grad_norm 3.5864 (3.0186/1.2747)	mem 16099MB
[2025-01-18 09:32:12 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][50/312]	eta 0:02:15 lr 0.000369	time 0.4514 (0.5155)	model_time 0.4512 (0.4767)	loss 3.2833 (2.7927)	grad_norm 2.1278 (2.8898/1.2880)	mem 16099MB
[2025-01-18 09:32:16 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][60/312]	eta 0:02:07 lr 0.000369	time 0.4497 (0.5058)	model_time 0.4496 (0.4733)	loss 2.9043 (2.7896)	grad_norm 2.8173 (2.9094/1.2727)	mem 16099MB
[2025-01-18 09:32:21 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][70/312]	eta 0:02:01 lr 0.000368	time 0.4591 (0.5002)	model_time 0.4589 (0.4723)	loss 3.1663 (2.7943)	grad_norm 4.1106 (2.8994/1.2429)	mem 16099MB
[2025-01-18 09:32:26 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][80/312]	eta 0:01:55 lr 0.000368	time 0.4548 (0.4994)	model_time 0.4546 (0.4749)	loss 2.2635 (2.7727)	grad_norm 1.6981 (2.9004/1.2494)	mem 16099MB
[2025-01-18 09:32:31 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][90/312]	eta 0:01:50 lr 0.000368	time 0.4536 (0.4964)	model_time 0.4534 (0.4745)	loss 3.0145 (2.7735)	grad_norm 5.4083 (2.9648/1.3809)	mem 16099MB
[2025-01-18 09:32:35 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][100/312]	eta 0:01:44 lr 0.000367	time 0.4529 (0.4932)	model_time 0.4525 (0.4735)	loss 3.5237 (2.7924)	grad_norm 3.3900 (2.9922/1.3562)	mem 16099MB
[2025-01-18 09:32:40 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][110/312]	eta 0:01:39 lr 0.000367	time 0.4742 (0.4917)	model_time 0.4741 (0.4737)	loss 2.7595 (2.7961)	grad_norm 2.4881 (2.9668/1.3382)	mem 16099MB
[2025-01-18 09:32:45 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][120/312]	eta 0:01:33 lr 0.000366	time 0.4495 (0.4887)	model_time 0.4493 (0.4722)	loss 3.5882 (2.7814)	grad_norm 3.7114 (2.9048/1.3219)	mem 16099MB
[2025-01-18 09:32:49 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][130/312]	eta 0:01:28 lr 0.000366	time 0.4481 (0.4873)	model_time 0.4479 (0.4720)	loss 2.0805 (2.7841)	grad_norm 1.6170 (2.8796/1.3306)	mem 16099MB
[2025-01-18 09:32:54 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][140/312]	eta 0:01:23 lr 0.000366	time 0.5409 (0.4863)	model_time 0.5405 (0.4721)	loss 2.7818 (2.7850)	grad_norm 2.1176 (2.8162/1.3073)	mem 16099MB
[2025-01-18 09:32:59 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][150/312]	eta 0:01:18 lr 0.000365	time 0.4556 (0.4854)	model_time 0.4552 (0.4721)	loss 3.5256 (2.7926)	grad_norm 1.6339 (2.8333/1.3063)	mem 16099MB
[2025-01-18 09:33:04 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][160/312]	eta 0:01:13 lr 0.000365	time 0.5407 (0.4847)	model_time 0.5406 (0.4722)	loss 3.2057 (2.7871)	grad_norm 1.3799 (2.8206/1.2844)	mem 16099MB
[2025-01-18 09:33:08 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][170/312]	eta 0:01:08 lr 0.000365	time 0.4506 (0.4831)	model_time 0.4502 (0.4713)	loss 2.4759 (2.7776)	grad_norm 1.8407 (2.7954/1.2668)	mem 16099MB
[2025-01-18 09:33:13 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][180/312]	eta 0:01:03 lr 0.000364	time 0.4484 (0.4814)	model_time 0.4482 (0.4703)	loss 3.1544 (2.7786)	grad_norm 2.8183 (2.7637/1.2427)	mem 16099MB
[2025-01-18 09:33:18 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][190/312]	eta 0:00:58 lr 0.000364	time 0.7339 (0.4815)	model_time 0.7337 (0.4709)	loss 1.8717 (2.7746)	grad_norm 1.8882 (2.7385/1.2258)	mem 16099MB
[2025-01-18 09:33:22 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][200/312]	eta 0:00:53 lr 0.000363	time 0.4489 (0.4807)	model_time 0.4485 (0.4706)	loss 3.2515 (2.7725)	grad_norm 3.2195 (2.7117/1.2137)	mem 16099MB
[2025-01-18 09:33:27 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][210/312]	eta 0:00:48 lr 0.000363	time 0.4568 (0.4797)	model_time 0.4567 (0.4700)	loss 3.0847 (2.7711)	grad_norm 1.4794 (2.6880/1.2056)	mem 16099MB
[2025-01-18 09:33:31 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][220/312]	eta 0:00:44 lr 0.000363	time 0.4489 (0.4790)	model_time 0.4487 (0.4698)	loss 2.7820 (2.7798)	grad_norm 1.2709 (2.6442/1.2016)	mem 16099MB
[2025-01-18 09:33:36 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][230/312]	eta 0:00:39 lr 0.000362	time 0.4796 (0.4780)	model_time 0.4791 (0.4692)	loss 1.8944 (2.7773)	grad_norm 3.3087 (2.6441/1.1920)	mem 16099MB
[2025-01-18 09:33:41 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][240/312]	eta 0:00:34 lr 0.000362	time 0.4552 (0.4769)	model_time 0.4548 (0.4684)	loss 3.2335 (2.7743)	grad_norm 3.7580 (2.6718/1.1888)	mem 16099MB
[2025-01-18 09:33:45 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][250/312]	eta 0:00:29 lr 0.000362	time 0.5619 (0.4772)	model_time 0.5618 (0.4690)	loss 2.6285 (2.7748)	grad_norm 2.2971 (2.7236/1.2464)	mem 16099MB
[2025-01-18 09:33:50 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][260/312]	eta 0:00:24 lr 0.000361	time 0.4716 (0.4769)	model_time 0.4714 (0.4690)	loss 3.3433 (2.7694)	grad_norm 3.7451 (2.7238/1.2404)	mem 16099MB
[2025-01-18 09:33:55 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][270/312]	eta 0:00:20 lr 0.000361	time 0.4413 (0.4765)	model_time 0.4407 (0.4689)	loss 3.5234 (2.7761)	grad_norm 1.9436 (2.7328/1.2590)	mem 16099MB
[2025-01-18 09:34:00 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][280/312]	eta 0:00:15 lr 0.000361	time 0.4503 (0.4771)	model_time 0.4498 (0.4698)	loss 2.9306 (2.7865)	grad_norm 4.4010 (2.7340/1.2571)	mem 16099MB
[2025-01-18 09:34:04 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][290/312]	eta 0:00:10 lr 0.000360	time 0.4571 (0.4764)	model_time 0.4566 (0.4693)	loss 2.4624 (2.7828)	grad_norm 1.2679 (2.7175/1.2493)	mem 16099MB
[2025-01-18 09:34:09 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][300/312]	eta 0:00:05 lr 0.000360	time 0.4390 (0.4755)	model_time 0.4389 (0.4687)	loss 2.8666 (2.7805)	grad_norm 4.2105 (2.7076/1.2401)	mem 16099MB
[2025-01-18 09:34:13 internimage_t_1k_224] (main.py 510): INFO Train: [244/300][310/312]	eta 0:00:00 lr 0.000360	time 0.4391 (0.4749)	model_time 0.4390 (0.4683)	loss 2.7781 (2.7838)	grad_norm 2.3051 (2.6750/1.1972)	mem 16099MB
[2025-01-18 09:34:14 internimage_t_1k_224] (main.py 519): INFO EPOCH 244 training takes 0:02:28
[2025-01-18 09:34:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_244.pth saving......
[2025-01-18 09:34:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_244.pth saved !!!
[2025-01-18 09:34:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.289 (7.289)	Loss 0.7346 (0.7346)	Acc@1 84.741 (84.741)	Acc@5 97.339 (97.339)	Mem 16099MB
[2025-01-18 09:34:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.999)	Loss 0.9784 (0.8395)	Acc@1 78.491 (82.571)	Acc@5 94.800 (96.174)	Mem 16099MB
[2025-01-18 09:34:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:244] * Acc@1 82.446 Acc@5 96.175
[2025-01-18 09:34:26 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.4%
[2025-01-18 09:34:26 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.63%
[2025-01-18 09:34:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.137 (8.137)	Loss 0.7408 (0.7408)	Acc@1 85.791 (85.791)	Acc@5 97.681 (97.681)	Mem 16099MB
[2025-01-18 09:34:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.106)	Loss 0.9805 (0.8470)	Acc@1 79.175 (83.294)	Acc@5 95.435 (96.451)	Mem 16099MB
[2025-01-18 09:34:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:244] * Acc@1 83.165 Acc@5 96.477
[2025-01-18 09:34:38 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.2%
[2025-01-18 09:34:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:34:40 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:34:40 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.17%
[2025-01-18 09:34:42 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][0/312]	eta 0:11:29 lr 0.000359	time 2.2115 (2.2115)	model_time 0.4798 (0.4798)	loss 2.4411 (2.4411)	grad_norm 1.3112 (1.3112/0.0000)	mem 16099MB
[2025-01-18 09:34:47 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][10/312]	eta 0:03:16 lr 0.000359	time 0.4561 (0.6519)	model_time 0.4557 (0.4942)	loss 2.9402 (2.9204)	grad_norm 1.7811 (1.7991/0.5481)	mem 16099MB
[2025-01-18 09:34:52 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][20/312]	eta 0:02:43 lr 0.000359	time 0.4649 (0.5594)	model_time 0.4648 (0.4766)	loss 2.5818 (2.7827)	grad_norm 3.6018 (1.9793/0.8313)	mem 16099MB
[2025-01-18 09:34:57 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][30/312]	eta 0:02:30 lr 0.000358	time 0.4442 (0.5336)	model_time 0.4440 (0.4774)	loss 3.2130 (2.6996)	grad_norm 2.9924 (2.2870/1.0355)	mem 16099MB
[2025-01-18 09:35:01 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][40/312]	eta 0:02:20 lr 0.000358	time 0.4578 (0.5147)	model_time 0.4574 (0.4721)	loss 2.0832 (2.7164)	grad_norm 2.0606 (2.5712/1.2692)	mem 16099MB
[2025-01-18 09:35:06 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][50/312]	eta 0:02:12 lr 0.000358	time 0.4572 (0.5040)	model_time 0.4567 (0.4697)	loss 1.7206 (2.7319)	grad_norm 2.8857 (2.4986/1.2103)	mem 16099MB
[2025-01-18 09:35:10 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][60/312]	eta 0:02:05 lr 0.000357	time 0.4730 (0.4967)	model_time 0.4725 (0.4680)	loss 3.4502 (2.7479)	grad_norm 1.2070 (2.4570/1.1407)	mem 16099MB
[2025-01-18 09:35:15 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][70/312]	eta 0:01:58 lr 0.000357	time 0.4665 (0.4906)	model_time 0.4663 (0.4658)	loss 2.8990 (2.7579)	grad_norm 2.5034 (2.4984/1.1915)	mem 16099MB
[2025-01-18 09:35:20 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][80/312]	eta 0:01:53 lr 0.000357	time 0.5259 (0.4877)	model_time 0.5258 (0.4660)	loss 2.5139 (2.7515)	grad_norm 1.4292 (2.5084/1.1548)	mem 16099MB
[2025-01-18 09:35:24 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][90/312]	eta 0:01:47 lr 0.000356	time 0.4581 (0.4847)	model_time 0.4577 (0.4653)	loss 1.8099 (2.7327)	grad_norm 2.2911 (2.4611/1.1215)	mem 16099MB
[2025-01-18 09:35:29 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][100/312]	eta 0:01:42 lr 0.000356	time 0.4449 (0.4819)	model_time 0.4445 (0.4644)	loss 3.2945 (2.7839)	grad_norm 3.6682 (2.5312/1.1936)	mem 16099MB
[2025-01-18 09:35:34 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][110/312]	eta 0:01:37 lr 0.000355	time 0.4605 (0.4813)	model_time 0.4603 (0.4653)	loss 3.2691 (2.7877)	grad_norm 2.3178 (2.6244/1.2340)	mem 16099MB
[2025-01-18 09:35:38 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][120/312]	eta 0:01:32 lr 0.000355	time 0.5455 (0.4811)	model_time 0.5451 (0.4664)	loss 3.1392 (2.7845)	grad_norm 3.3202 (2.6826/1.2706)	mem 16099MB
[2025-01-18 09:35:43 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][130/312]	eta 0:01:27 lr 0.000355	time 0.4530 (0.4790)	model_time 0.4526 (0.4654)	loss 2.8138 (2.7752)	grad_norm 1.2234 (2.6522/1.2558)	mem 16099MB
[2025-01-18 09:35:47 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][140/312]	eta 0:01:22 lr 0.000354	time 0.4555 (0.4774)	model_time 0.4551 (0.4647)	loss 2.8691 (2.7745)	grad_norm 1.6403 (2.6076/1.2386)	mem 16099MB
[2025-01-18 09:35:52 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][150/312]	eta 0:01:17 lr 0.000354	time 0.4433 (0.4777)	model_time 0.4431 (0.4658)	loss 3.3334 (2.7856)	grad_norm 2.0314 (2.6238/1.2388)	mem 16099MB
[2025-01-18 09:35:57 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][160/312]	eta 0:01:12 lr 0.000354	time 0.5480 (0.4802)	model_time 0.5478 (0.4691)	loss 2.1934 (2.7862)	grad_norm 4.0436 (2.6890/1.2898)	mem 16099MB
[2025-01-18 09:36:02 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][170/312]	eta 0:01:08 lr 0.000353	time 0.4544 (0.4793)	model_time 0.4540 (0.4687)	loss 2.0419 (2.7831)	grad_norm 1.9330 (2.7257/1.3225)	mem 16099MB
[2025-01-18 09:36:07 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][180/312]	eta 0:01:03 lr 0.000353	time 0.4817 (0.4804)	model_time 0.4813 (0.4704)	loss 3.2275 (2.7886)	grad_norm 4.3773 (2.7393/1.3048)	mem 16099MB
[2025-01-18 09:36:12 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][190/312]	eta 0:00:58 lr 0.000353	time 0.4570 (0.4791)	model_time 0.4568 (0.4696)	loss 3.4828 (2.7923)	grad_norm 4.1234 (2.7815/1.2995)	mem 16099MB
[2025-01-18 09:36:17 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][200/312]	eta 0:00:53 lr 0.000352	time 0.4574 (0.4816)	model_time 0.4570 (0.4726)	loss 2.0394 (2.7912)	grad_norm 4.3048 (2.8158/1.3060)	mem 16099MB
[2025-01-18 09:36:22 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][210/312]	eta 0:00:49 lr 0.000352	time 0.4533 (0.4809)	model_time 0.4529 (0.4723)	loss 1.6971 (2.7799)	grad_norm 3.1526 (2.8019/1.2866)	mem 16099MB
[2025-01-18 09:36:26 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][220/312]	eta 0:00:44 lr 0.000352	time 0.4508 (0.4798)	model_time 0.4503 (0.4716)	loss 3.1856 (2.7821)	grad_norm 1.3848 (2.8083/1.2803)	mem 16099MB
[2025-01-18 09:36:31 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][230/312]	eta 0:00:39 lr 0.000351	time 0.4575 (0.4788)	model_time 0.4573 (0.4710)	loss 3.1547 (2.7820)	grad_norm 2.8433 (2.8056/1.2717)	mem 16099MB
[2025-01-18 09:36:35 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][240/312]	eta 0:00:34 lr 0.000351	time 0.4597 (0.4779)	model_time 0.4593 (0.4704)	loss 3.1471 (2.7891)	grad_norm 1.2910 (2.7923/1.2623)	mem 16099MB
[2025-01-18 09:36:40 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][250/312]	eta 0:00:29 lr 0.000350	time 0.4455 (0.4784)	model_time 0.4451 (0.4711)	loss 2.8579 (2.7946)	grad_norm 4.3366 (2.7952/1.2603)	mem 16099MB
[2025-01-18 09:36:45 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][260/312]	eta 0:00:24 lr 0.000350	time 0.4595 (0.4781)	model_time 0.4593 (0.4711)	loss 3.1150 (2.7904)	grad_norm 2.4526 (2.7701/1.2522)	mem 16099MB
[2025-01-18 09:36:49 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][270/312]	eta 0:00:20 lr 0.000350	time 0.4751 (0.4773)	model_time 0.4750 (0.4706)	loss 1.9968 (2.7870)	grad_norm 2.2997 (2.7569/1.2388)	mem 16099MB
[2025-01-18 09:36:54 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][280/312]	eta 0:00:15 lr 0.000349	time 0.4734 (0.4766)	model_time 0.4729 (0.4700)	loss 2.8283 (2.7876)	grad_norm 2.8825 (2.7417/1.2294)	mem 16099MB
[2025-01-18 09:36:59 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][290/312]	eta 0:00:10 lr 0.000349	time 0.4636 (0.4763)	model_time 0.4632 (0.4700)	loss 3.1634 (2.7881)	grad_norm 1.9597 (2.7549/1.2283)	mem 16099MB
[2025-01-18 09:37:03 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][300/312]	eta 0:00:05 lr 0.000349	time 0.4405 (0.4755)	model_time 0.4404 (0.4694)	loss 2.7118 (2.7821)	grad_norm 2.3725 (2.7990/1.2332)	mem 16099MB
[2025-01-18 09:37:08 internimage_t_1k_224] (main.py 510): INFO Train: [245/300][310/312]	eta 0:00:00 lr 0.000348	time 0.4403 (0.4746)	model_time 0.4402 (0.4686)	loss 3.2281 (2.7835)	grad_norm 2.9176 (2.8099/1.2307)	mem 16099MB
[2025-01-18 09:37:08 internimage_t_1k_224] (main.py 519): INFO EPOCH 245 training takes 0:02:28
[2025-01-18 09:37:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_245.pth saving......
[2025-01-18 09:37:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_245.pth saved !!!
[2025-01-18 09:37:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.387 (7.387)	Loss 0.7244 (0.7244)	Acc@1 85.181 (85.181)	Acc@5 97.290 (97.290)	Mem 16099MB
[2025-01-18 09:37:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.995)	Loss 0.9671 (0.8282)	Acc@1 78.516 (82.602)	Acc@5 95.020 (96.149)	Mem 16099MB
[2025-01-18 09:37:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:245] * Acc@1 82.452 Acc@5 96.147
[2025-01-18 09:37:20 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.5%
[2025-01-18 09:37:20 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.63%
[2025-01-18 09:37:29 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.246 (8.246)	Loss 0.7396 (0.7396)	Acc@1 85.767 (85.767)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 09:37:33 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.110)	Loss 0.9787 (0.8456)	Acc@1 79.248 (83.325)	Acc@5 95.410 (96.467)	Mem 16099MB
[2025-01-18 09:37:33 internimage_t_1k_224] (main.py 575): INFO [Epoch:245] * Acc@1 83.195 Acc@5 96.491
[2025-01-18 09:37:33 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.2%
[2025-01-18 09:37:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:37:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:37:34 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.20%
[2025-01-18 09:37:37 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][0/312]	eta 0:13:18 lr 0.000348	time 2.5600 (2.5600)	model_time 0.4708 (0.4708)	loss 2.8611 (2.8611)	grad_norm 3.5883 (3.5883/0.0000)	mem 16099MB
[2025-01-18 09:37:42 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][10/312]	eta 0:03:18 lr 0.000348	time 0.4531 (0.6557)	model_time 0.4526 (0.4654)	loss 2.3111 (2.7408)	grad_norm 1.4470 (3.2979/1.7042)	mem 16099MB
[2025-01-18 09:37:46 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][20/312]	eta 0:02:46 lr 0.000348	time 0.4518 (0.5712)	model_time 0.4517 (0.4714)	loss 3.6486 (2.8173)	grad_norm 2.7594 (2.9463/1.3682)	mem 16099MB
[2025-01-18 09:37:51 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][30/312]	eta 0:02:30 lr 0.000347	time 0.4531 (0.5351)	model_time 0.4526 (0.4674)	loss 2.3265 (2.7838)	grad_norm 2.3598 (3.1703/1.5142)	mem 16099MB
[2025-01-18 09:37:56 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][40/312]	eta 0:02:20 lr 0.000347	time 0.4593 (0.5157)	model_time 0.4588 (0.4644)	loss 3.2055 (2.7802)	grad_norm 4.7848 (3.3098/1.4777)	mem 16099MB
[2025-01-18 09:38:00 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][50/312]	eta 0:02:12 lr 0.000346	time 0.4503 (0.5048)	model_time 0.4502 (0.4635)	loss 3.3551 (2.8099)	grad_norm 2.0100 (3.1955/1.3926)	mem 16099MB
[2025-01-18 09:38:05 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][60/312]	eta 0:02:05 lr 0.000346	time 0.4652 (0.4976)	model_time 0.4651 (0.4630)	loss 3.0914 (2.8130)	grad_norm 1.9064 (3.0396/1.3703)	mem 16099MB
[2025-01-18 09:38:09 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][70/312]	eta 0:01:59 lr 0.000346	time 0.5438 (0.4931)	model_time 0.5436 (0.4633)	loss 3.1563 (2.8147)	grad_norm 2.2200 (2.8504/1.3639)	mem 16099MB
[2025-01-18 09:38:14 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][80/312]	eta 0:01:53 lr 0.000345	time 0.5414 (0.4893)	model_time 0.5412 (0.4630)	loss 2.1600 (2.8194)	grad_norm 1.9793 (2.7748/1.3022)	mem 16099MB
[2025-01-18 09:38:19 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][90/312]	eta 0:01:48 lr 0.000345	time 0.4422 (0.4874)	model_time 0.4421 (0.4640)	loss 3.1393 (2.8317)	grad_norm 4.7553 (2.8597/1.3335)	mem 16099MB
[2025-01-18 09:38:23 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][100/312]	eta 0:01:42 lr 0.000345	time 0.4462 (0.4841)	model_time 0.4460 (0.4630)	loss 2.6099 (2.8070)	grad_norm 2.4302 (2.9743/1.3805)	mem 16099MB
[2025-01-18 09:38:28 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][110/312]	eta 0:01:37 lr 0.000344	time 0.5641 (0.4844)	model_time 0.5640 (0.4651)	loss 3.1337 (2.8232)	grad_norm 2.7226 (3.0346/1.3864)	mem 16099MB
[2025-01-18 09:38:33 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][120/312]	eta 0:01:32 lr 0.000344	time 0.4668 (0.4823)	model_time 0.4663 (0.4646)	loss 2.6389 (2.8225)	grad_norm 1.8582 (3.0365/1.3706)	mem 16099MB
[2025-01-18 09:38:38 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][130/312]	eta 0:01:27 lr 0.000344	time 0.4551 (0.4823)	model_time 0.4549 (0.4659)	loss 2.5621 (2.8204)	grad_norm 4.6367 (3.0317/1.3477)	mem 16099MB
[2025-01-18 09:38:42 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][140/312]	eta 0:01:22 lr 0.000343	time 0.4654 (0.4811)	model_time 0.4652 (0.4658)	loss 2.5790 (2.8278)	grad_norm 2.2661 (2.9814/1.3232)	mem 16099MB
[2025-01-18 09:38:47 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][150/312]	eta 0:01:18 lr 0.000343	time 0.5378 (0.4826)	model_time 0.5377 (0.4683)	loss 2.2966 (2.8226)	grad_norm 1.4765 (2.9560/1.2999)	mem 16099MB
[2025-01-18 09:38:52 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][160/312]	eta 0:01:13 lr 0.000343	time 0.4707 (0.4815)	model_time 0.4703 (0.4681)	loss 2.0894 (2.8185)	grad_norm 4.3686 (2.9471/1.2972)	mem 16099MB
[2025-01-18 09:38:57 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][170/312]	eta 0:01:08 lr 0.000342	time 0.4482 (0.4811)	model_time 0.4480 (0.4685)	loss 2.9998 (2.8225)	grad_norm 3.4598 (2.9270/1.2742)	mem 16099MB
[2025-01-18 09:39:01 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][180/312]	eta 0:01:03 lr 0.000342	time 0.4408 (0.4801)	model_time 0.4406 (0.4682)	loss 3.1883 (2.8165)	grad_norm 4.2603 (2.9649/1.2663)	mem 16099MB
[2025-01-18 09:39:06 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][190/312]	eta 0:00:58 lr 0.000341	time 0.4517 (0.4789)	model_time 0.4515 (0.4676)	loss 3.1051 (2.8151)	grad_norm 3.6624 (2.9648/1.2860)	mem 16099MB
[2025-01-18 09:39:10 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][200/312]	eta 0:00:53 lr 0.000341	time 0.4580 (0.4779)	model_time 0.4576 (0.4671)	loss 3.2578 (2.8126)	grad_norm 2.2012 (2.9700/1.2906)	mem 16099MB
[2025-01-18 09:39:15 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][210/312]	eta 0:00:48 lr 0.000341	time 0.4445 (0.4779)	model_time 0.4441 (0.4676)	loss 2.6485 (2.8081)	grad_norm 1.4878 (2.9767/1.2869)	mem 16099MB
[2025-01-18 09:39:20 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][220/312]	eta 0:00:43 lr 0.000340	time 0.4530 (0.4767)	model_time 0.4526 (0.4669)	loss 3.6036 (2.8075)	grad_norm 1.5329 (2.9222/1.2923)	mem 16099MB
[2025-01-18 09:39:24 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][230/312]	eta 0:00:39 lr 0.000340	time 0.4635 (0.4758)	model_time 0.4633 (0.4664)	loss 2.9437 (2.7961)	grad_norm 2.4560 (2.8996/1.2771)	mem 16099MB
[2025-01-18 09:39:29 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][240/312]	eta 0:00:34 lr 0.000340	time 0.4438 (0.4753)	model_time 0.4437 (0.4663)	loss 2.2778 (2.7942)	grad_norm 3.1942 (2.8869/1.2680)	mem 16099MB
[2025-01-18 09:39:34 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][250/312]	eta 0:00:29 lr 0.000339	time 0.4409 (0.4752)	model_time 0.4405 (0.4665)	loss 2.7972 (2.7905)	grad_norm 1.2976 (2.9184/1.3069)	mem 16099MB
[2025-01-18 09:39:38 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][260/312]	eta 0:00:24 lr 0.000339	time 0.4487 (0.4743)	model_time 0.4486 (0.4659)	loss 3.3230 (2.7929)	grad_norm 3.3043 (2.9262/1.3008)	mem 16099MB
[2025-01-18 09:39:43 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][270/312]	eta 0:00:19 lr 0.000339	time 0.4412 (0.4739)	model_time 0.4411 (0.4658)	loss 2.7547 (2.7924)	grad_norm 5.8669 (2.9572/1.3185)	mem 16099MB
[2025-01-18 09:39:47 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][280/312]	eta 0:00:15 lr 0.000338	time 0.4578 (0.4735)	model_time 0.4576 (0.4657)	loss 3.0756 (2.7912)	grad_norm 2.4770 (2.9484/1.3211)	mem 16099MB
[2025-01-18 09:39:52 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][290/312]	eta 0:00:10 lr 0.000338	time 0.4551 (0.4729)	model_time 0.4549 (0.4653)	loss 2.7881 (2.7903)	grad_norm 3.7303 (2.9276/1.3158)	mem 16099MB
[2025-01-18 09:39:57 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][300/312]	eta 0:00:05 lr 0.000338	time 0.4401 (0.4727)	model_time 0.4401 (0.4654)	loss 2.7347 (2.7911)	grad_norm 2.2812 (2.9351/1.3271)	mem 16099MB
[2025-01-18 09:40:01 internimage_t_1k_224] (main.py 510): INFO Train: [246/300][310/312]	eta 0:00:00 lr 0.000337	time 0.4416 (0.4727)	model_time 0.4415 (0.4656)	loss 3.4181 (2.7890)	grad_norm 2.4569 (2.9198/1.2971)	mem 16099MB
[2025-01-18 09:40:02 internimage_t_1k_224] (main.py 519): INFO EPOCH 246 training takes 0:02:27
[2025-01-18 09:40:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_246.pth saving......
[2025-01-18 09:40:03 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_246.pth saved !!!
[2025-01-18 09:40:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.286 (7.286)	Loss 0.7320 (0.7320)	Acc@1 84.937 (84.937)	Acc@5 97.339 (97.339)	Mem 16099MB
[2025-01-18 09:40:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (0.977)	Loss 0.9847 (0.8364)	Acc@1 78.540 (82.508)	Acc@5 94.849 (96.118)	Mem 16099MB
[2025-01-18 09:40:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:246] * Acc@1 82.380 Acc@5 96.109
[2025-01-18 09:40:14 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.4%
[2025-01-18 09:40:14 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.63%
[2025-01-18 09:40:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.293 (8.293)	Loss 0.7387 (0.7387)	Acc@1 85.767 (85.767)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 09:40:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.101 (1.104)	Loss 0.9774 (0.8445)	Acc@1 79.321 (83.352)	Acc@5 95.410 (96.471)	Mem 16099MB
[2025-01-18 09:40:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:246] * Acc@1 83.225 Acc@5 96.493
[2025-01-18 09:40:26 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.2%
[2025-01-18 09:40:26 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:40:28 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:40:28 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.23%
[2025-01-18 09:40:30 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][0/312]	eta 0:12:01 lr 0.000337	time 2.3132 (2.3132)	model_time 0.4947 (0.4947)	loss 2.9511 (2.9511)	grad_norm 2.2756 (2.2756/0.0000)	mem 16099MB
[2025-01-18 09:40:35 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][10/312]	eta 0:03:16 lr 0.000337	time 0.5225 (0.6511)	model_time 0.5221 (0.4830)	loss 3.2062 (2.8262)	grad_norm 1.1179 (2.6770/0.9266)	mem 16099MB
[2025-01-18 09:40:40 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][20/312]	eta 0:02:44 lr 0.000337	time 0.4599 (0.5635)	model_time 0.4598 (0.4752)	loss 2.8063 (2.8202)	grad_norm 2.5460 (2.7641/0.9595)	mem 16099MB
[2025-01-18 09:40:44 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][30/312]	eta 0:02:30 lr 0.000336	time 0.5338 (0.5329)	model_time 0.5337 (0.4731)	loss 2.8092 (2.8650)	grad_norm 2.7641 (2.7057/0.8882)	mem 16099MB
[2025-01-18 09:40:49 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][40/312]	eta 0:02:20 lr 0.000336	time 0.4407 (0.5167)	model_time 0.4406 (0.4714)	loss 2.6077 (2.8549)	grad_norm 1.8696 (2.7137/0.9107)	mem 16099MB
[2025-01-18 09:40:54 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][50/312]	eta 0:02:13 lr 0.000335	time 0.4565 (0.5083)	model_time 0.4563 (0.4718)	loss 3.1097 (2.8697)	grad_norm 1.7796 (2.6343/0.8691)	mem 16099MB
[2025-01-18 09:40:58 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][60/312]	eta 0:02:06 lr 0.000335	time 0.4452 (0.5014)	model_time 0.4451 (0.4708)	loss 2.7417 (2.8455)	grad_norm 2.5766 (2.5402/0.9122)	mem 16099MB
[2025-01-18 09:41:03 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][70/312]	eta 0:02:00 lr 0.000335	time 0.4409 (0.4980)	model_time 0.4408 (0.4717)	loss 3.0279 (2.7910)	grad_norm 5.4879 (2.5492/0.9585)	mem 16099MB
[2025-01-18 09:41:08 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][80/312]	eta 0:01:54 lr 0.000334	time 0.4499 (0.4940)	model_time 0.4495 (0.4709)	loss 3.2796 (2.8020)	grad_norm 4.7086 (2.7130/1.2113)	mem 16099MB
[2025-01-18 09:41:12 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][90/312]	eta 0:01:48 lr 0.000334	time 0.4511 (0.4897)	model_time 0.4507 (0.4690)	loss 2.8991 (2.8037)	grad_norm 1.4784 (2.7184/1.1839)	mem 16099MB
[2025-01-18 09:41:17 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][100/312]	eta 0:01:43 lr 0.000334	time 0.4517 (0.4874)	model_time 0.4512 (0.4686)	loss 2.7216 (2.8052)	grad_norm 2.5995 (2.7651/1.1805)	mem 16099MB
[2025-01-18 09:41:22 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][110/312]	eta 0:01:38 lr 0.000333	time 0.4556 (0.4852)	model_time 0.4552 (0.4681)	loss 2.8345 (2.8218)	grad_norm 1.1673 (2.8390/1.2148)	mem 16099MB
[2025-01-18 09:41:26 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][120/312]	eta 0:01:32 lr 0.000333	time 0.5352 (0.4843)	model_time 0.5347 (0.4685)	loss 2.5452 (2.8189)	grad_norm 4.9956 (2.8977/1.2500)	mem 16099MB
[2025-01-18 09:41:31 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][130/312]	eta 0:01:27 lr 0.000333	time 0.4708 (0.4824)	model_time 0.4703 (0.4678)	loss 2.5954 (2.8213)	grad_norm 1.6973 (2.9419/1.2901)	mem 16099MB
[2025-01-18 09:41:36 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][140/312]	eta 0:01:22 lr 0.000332	time 0.4534 (0.4807)	model_time 0.4532 (0.4671)	loss 3.0343 (2.8180)	grad_norm 1.7973 (2.8923/1.2755)	mem 16099MB
[2025-01-18 09:41:40 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][150/312]	eta 0:01:17 lr 0.000332	time 0.4810 (0.4803)	model_time 0.4806 (0.4676)	loss 2.9258 (2.8276)	grad_norm 2.1957 (2.9141/1.2741)	mem 16099MB
[2025-01-18 09:41:45 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][160/312]	eta 0:01:13 lr 0.000332	time 0.4451 (0.4805)	model_time 0.4450 (0.4685)	loss 3.1295 (2.8192)	grad_norm 6.2175 (2.9722/1.2976)	mem 16099MB
[2025-01-18 09:41:50 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][170/312]	eta 0:01:08 lr 0.000331	time 0.4843 (0.4795)	model_time 0.4839 (0.4682)	loss 2.8499 (2.8307)	grad_norm 2.7967 (3.0098/1.2990)	mem 16099MB
[2025-01-18 09:41:54 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][180/312]	eta 0:01:03 lr 0.000331	time 0.4576 (0.4787)	model_time 0.4574 (0.4680)	loss 3.0209 (2.8387)	grad_norm 1.4068 (2.9888/1.3013)	mem 16099MB
[2025-01-18 09:41:59 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][190/312]	eta 0:00:58 lr 0.000331	time 0.4620 (0.4774)	model_time 0.4619 (0.4672)	loss 3.0581 (2.8344)	grad_norm 1.2886 (2.9698/1.2910)	mem 16099MB
[2025-01-18 09:42:04 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][200/312]	eta 0:00:53 lr 0.000330	time 0.4685 (0.4767)	model_time 0.4681 (0.4671)	loss 3.1357 (2.8313)	grad_norm 2.4417 (2.9503/1.2758)	mem 16099MB
[2025-01-18 09:42:08 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][210/312]	eta 0:00:48 lr 0.000330	time 0.4568 (0.4756)	model_time 0.4567 (0.4663)	loss 2.8341 (2.8243)	grad_norm 3.7728 (2.9426/1.2629)	mem 16099MB
[2025-01-18 09:42:13 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][220/312]	eta 0:00:43 lr 0.000330	time 0.4475 (0.4750)	model_time 0.4471 (0.4662)	loss 3.0817 (2.8225)	grad_norm 1.3097 (2.9229/1.2723)	mem 16099MB
[2025-01-18 09:42:17 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][230/312]	eta 0:00:38 lr 0.000329	time 0.4439 (0.4744)	model_time 0.4434 (0.4660)	loss 2.1965 (2.8148)	grad_norm 5.4101 (2.9504/1.3034)	mem 16099MB
[2025-01-18 09:42:22 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][240/312]	eta 0:00:34 lr 0.000329	time 0.5296 (0.4744)	model_time 0.5292 (0.4663)	loss 3.1979 (2.8170)	grad_norm 4.5946 (2.9297/1.2967)	mem 16099MB
[2025-01-18 09:42:27 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][250/312]	eta 0:00:29 lr 0.000329	time 0.4659 (0.4746)	model_time 0.4655 (0.4668)	loss 2.6937 (2.8124)	grad_norm 2.3413 (2.9553/1.2874)	mem 16099MB
[2025-01-18 09:42:32 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][260/312]	eta 0:00:24 lr 0.000328	time 0.5390 (0.4743)	model_time 0.5386 (0.4667)	loss 3.1919 (2.8182)	grad_norm 1.2387 (2.9500/1.2924)	mem 16099MB
[2025-01-18 09:42:36 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][270/312]	eta 0:00:19 lr 0.000328	time 0.4472 (0.4739)	model_time 0.4470 (0.4666)	loss 2.9625 (2.8160)	grad_norm 1.7627 (2.9405/1.2846)	mem 16099MB
[2025-01-18 09:42:41 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][280/312]	eta 0:00:15 lr 0.000327	time 0.4449 (0.4736)	model_time 0.4445 (0.4665)	loss 2.9702 (2.8220)	grad_norm 2.0211 (2.9171/1.2710)	mem 16099MB
[2025-01-18 09:42:46 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][290/312]	eta 0:00:10 lr 0.000327	time 0.4468 (0.4735)	model_time 0.4466 (0.4667)	loss 3.0108 (2.8277)	grad_norm 1.9801 (2.9046/1.2595)	mem 16099MB
[2025-01-18 09:42:50 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][300/312]	eta 0:00:05 lr 0.000327	time 0.4392 (0.4730)	model_time 0.4391 (0.4665)	loss 1.5498 (2.8201)	grad_norm 2.4071 (2.8850/1.2609)	mem 16099MB
[2025-01-18 09:42:55 internimage_t_1k_224] (main.py 510): INFO Train: [247/300][310/312]	eta 0:00:00 lr 0.000326	time 0.4404 (0.4720)	model_time 0.4403 (0.4656)	loss 2.4997 (2.8167)	grad_norm 1.7506 (2.8650/1.2656)	mem 16099MB
[2025-01-18 09:42:55 internimage_t_1k_224] (main.py 519): INFO EPOCH 247 training takes 0:02:27
[2025-01-18 09:42:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_247.pth saving......
[2025-01-18 09:42:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_247.pth saved !!!
[2025-01-18 09:43:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.426 (7.426)	Loss 0.7361 (0.7361)	Acc@1 85.010 (85.010)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 09:43:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.988)	Loss 0.9873 (0.8400)	Acc@1 78.003 (82.579)	Acc@5 95.117 (96.140)	Mem 16099MB
[2025-01-18 09:43:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:247] * Acc@1 82.458 Acc@5 96.141
[2025-01-18 09:43:07 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.5%
[2025-01-18 09:43:07 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.63%
[2025-01-18 09:43:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.153 (8.153)	Loss 0.7376 (0.7376)	Acc@1 85.791 (85.791)	Acc@5 97.681 (97.681)	Mem 16099MB
[2025-01-18 09:43:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.103)	Loss 0.9758 (0.8431)	Acc@1 79.272 (83.352)	Acc@5 95.410 (96.471)	Mem 16099MB
[2025-01-18 09:43:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:247] * Acc@1 83.229 Acc@5 96.499
[2025-01-18 09:43:20 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.2%
[2025-01-18 09:43:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:43:21 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:43:21 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.23%
[2025-01-18 09:43:24 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][0/312]	eta 0:12:19 lr 0.000326	time 2.3696 (2.3696)	model_time 0.4827 (0.4827)	loss 2.4544 (2.4544)	grad_norm 1.5082 (1.5082/0.0000)	mem 16099MB
[2025-01-18 09:43:28 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][10/312]	eta 0:03:12 lr 0.000326	time 0.4388 (0.6383)	model_time 0.4385 (0.4665)	loss 2.8412 (2.8456)	grad_norm 1.9109 (2.0518/0.4986)	mem 16099MB
[2025-01-18 09:43:33 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][20/312]	eta 0:02:45 lr 0.000326	time 0.5394 (0.5665)	model_time 0.5393 (0.4763)	loss 3.1447 (2.8732)	grad_norm 2.6326 (2.0709/0.4969)	mem 16099MB
[2025-01-18 09:43:38 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][30/312]	eta 0:02:31 lr 0.000325	time 0.4437 (0.5358)	model_time 0.4435 (0.4746)	loss 2.1894 (2.8680)	grad_norm 1.4929 (2.3978/1.0099)	mem 16099MB
[2025-01-18 09:43:43 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][40/312]	eta 0:02:22 lr 0.000325	time 0.4562 (0.5240)	model_time 0.4558 (0.4776)	loss 2.0460 (2.8931)	grad_norm 6.1215 (2.4771/1.0891)	mem 16099MB
[2025-01-18 09:43:47 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][50/312]	eta 0:02:14 lr 0.000325	time 0.4602 (0.5135)	model_time 0.4600 (0.4762)	loss 3.2430 (2.8978)	grad_norm 3.0905 (2.4734/1.0288)	mem 16099MB
[2025-01-18 09:43:52 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][60/312]	eta 0:02:07 lr 0.000324	time 0.5386 (0.5068)	model_time 0.5381 (0.4755)	loss 2.0669 (2.8280)	grad_norm 7.1831 (2.6221/1.2319)	mem 16099MB
[2025-01-18 09:43:57 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][70/312]	eta 0:02:01 lr 0.000324	time 0.4577 (0.5033)	model_time 0.4572 (0.4764)	loss 3.1064 (2.7943)	grad_norm 1.4469 (2.6383/1.2163)	mem 16099MB
[2025-01-18 09:44:02 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][80/312]	eta 0:01:55 lr 0.000324	time 0.4446 (0.4998)	model_time 0.4444 (0.4761)	loss 2.9892 (2.7915)	grad_norm 4.7571 (2.6179/1.1947)	mem 16099MB
[2025-01-18 09:44:06 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][90/312]	eta 0:01:49 lr 0.000323	time 0.4728 (0.4953)	model_time 0.4726 (0.4742)	loss 2.0227 (2.7744)	grad_norm 3.3214 (2.5931/1.2173)	mem 16099MB
[2025-01-18 09:44:11 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][100/312]	eta 0:01:44 lr 0.000323	time 0.4513 (0.4912)	model_time 0.4509 (0.4722)	loss 2.1469 (2.7840)	grad_norm 2.7594 (2.6306/1.1733)	mem 16099MB
[2025-01-18 09:44:15 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][110/312]	eta 0:01:38 lr 0.000323	time 0.5385 (0.4887)	model_time 0.5380 (0.4713)	loss 2.6762 (2.7778)	grad_norm 3.7678 (2.6641/1.1737)	mem 16099MB
[2025-01-18 09:44:20 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][120/312]	eta 0:01:33 lr 0.000322	time 0.4410 (0.4859)	model_time 0.4408 (0.4699)	loss 1.7239 (2.7722)	grad_norm 4.5898 (2.8146/1.3535)	mem 16099MB
[2025-01-18 09:44:24 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][130/312]	eta 0:01:27 lr 0.000322	time 0.4415 (0.4832)	model_time 0.4410 (0.4685)	loss 3.1519 (2.7824)	grad_norm 4.1277 (2.8656/1.3814)	mem 16099MB
[2025-01-18 09:44:29 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][140/312]	eta 0:01:23 lr 0.000322	time 0.5485 (0.4827)	model_time 0.5483 (0.4690)	loss 2.5670 (2.7805)	grad_norm 1.8779 (2.9137/1.4020)	mem 16099MB
[2025-01-18 09:44:34 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][150/312]	eta 0:01:18 lr 0.000321	time 0.4567 (0.4821)	model_time 0.4563 (0.4693)	loss 2.6609 (2.7762)	grad_norm 3.0870 (2.9048/1.3876)	mem 16099MB
[2025-01-18 09:44:39 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][160/312]	eta 0:01:13 lr 0.000321	time 0.4570 (0.4815)	model_time 0.4565 (0.4694)	loss 2.1823 (2.7527)	grad_norm 1.8763 (2.8926/1.3856)	mem 16099MB
[2025-01-18 09:44:43 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][170/312]	eta 0:01:08 lr 0.000321	time 0.4563 (0.4800)	model_time 0.4558 (0.4685)	loss 2.4187 (2.7602)	grad_norm 1.3799 (2.8574/1.3633)	mem 16099MB
[2025-01-18 09:44:48 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][180/312]	eta 0:01:03 lr 0.000320	time 0.4391 (0.4783)	model_time 0.4387 (0.4675)	loss 2.9614 (2.7552)	grad_norm 2.7990 (2.8279/1.3382)	mem 16099MB
[2025-01-18 09:44:52 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][190/312]	eta 0:00:58 lr 0.000320	time 0.4583 (0.4773)	model_time 0.4581 (0.4671)	loss 3.0252 (2.7562)	grad_norm 2.4260 (2.8175/1.3231)	mem 16099MB
[2025-01-18 09:44:57 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][200/312]	eta 0:00:53 lr 0.000320	time 0.5468 (0.4774)	model_time 0.5463 (0.4676)	loss 2.8287 (2.7536)	grad_norm 3.0247 (2.7701/1.3121)	mem 16099MB
[2025-01-18 09:45:02 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][210/312]	eta 0:00:48 lr 0.000319	time 0.4552 (0.4781)	model_time 0.4550 (0.4688)	loss 2.8598 (2.7568)	grad_norm 1.6181 (2.7569/1.3005)	mem 16099MB
[2025-01-18 09:45:07 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][220/312]	eta 0:00:43 lr 0.000319	time 0.4667 (0.4774)	model_time 0.4666 (0.4685)	loss 2.7461 (2.7586)	grad_norm 4.9347 (2.7828/1.2982)	mem 16099MB
[2025-01-18 09:45:11 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][230/312]	eta 0:00:39 lr 0.000319	time 0.4544 (0.4765)	model_time 0.4543 (0.4679)	loss 3.1283 (2.7595)	grad_norm 5.6877 (2.8517/1.3374)	mem 16099MB
[2025-01-18 09:45:16 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][240/312]	eta 0:00:34 lr 0.000318	time 0.4436 (0.4767)	model_time 0.4434 (0.4685)	loss 2.3672 (2.7649)	grad_norm 3.5126 (2.8858/1.3680)	mem 16099MB
[2025-01-18 09:45:21 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][250/312]	eta 0:00:29 lr 0.000318	time 0.5432 (0.4769)	model_time 0.5428 (0.4690)	loss 1.9778 (2.7591)	grad_norm 1.5644 (2.8690/1.3524)	mem 16099MB
[2025-01-18 09:45:25 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][260/312]	eta 0:00:24 lr 0.000317	time 0.4569 (0.4764)	model_time 0.4565 (0.4688)	loss 2.1453 (2.7598)	grad_norm 1.4974 (2.8654/1.3351)	mem 16099MB
[2025-01-18 09:45:30 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][270/312]	eta 0:00:19 lr 0.000317	time 0.4398 (0.4755)	model_time 0.4397 (0.4682)	loss 3.3019 (2.7569)	grad_norm 1.9763 (2.8868/1.3427)	mem 16099MB
[2025-01-18 09:45:35 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][280/312]	eta 0:00:15 lr 0.000317	time 0.4432 (0.4755)	model_time 0.4431 (0.4684)	loss 3.0548 (2.7512)	grad_norm 3.2182 (2.8966/1.3346)	mem 16099MB
[2025-01-18 09:45:39 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][290/312]	eta 0:00:10 lr 0.000316	time 0.4605 (0.4751)	model_time 0.4604 (0.4682)	loss 3.0305 (2.7538)	grad_norm 2.4398 (2.8788/1.3230)	mem 16099MB
[2025-01-18 09:45:44 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][300/312]	eta 0:00:05 lr 0.000316	time 0.4405 (0.4756)	model_time 0.4404 (0.4689)	loss 3.1442 (2.7548)	grad_norm 1.6176 (2.8795/1.3194)	mem 16099MB
[2025-01-18 09:45:49 internimage_t_1k_224] (main.py 510): INFO Train: [248/300][310/312]	eta 0:00:00 lr 0.000316	time 0.4410 (0.4757)	model_time 0.4409 (0.4693)	loss 2.2962 (2.7504)	grad_norm 3.2990 (2.9256/1.3333)	mem 16099MB
[2025-01-18 09:45:50 internimage_t_1k_224] (main.py 519): INFO EPOCH 248 training takes 0:02:28
[2025-01-18 09:45:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_248.pth saving......
[2025-01-18 09:45:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_248.pth saved !!!
[2025-01-18 09:45:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.280 (7.280)	Loss 0.7420 (0.7420)	Acc@1 84.985 (84.985)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 09:46:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.976)	Loss 0.9752 (0.8443)	Acc@1 78.833 (82.659)	Acc@5 95.142 (96.191)	Mem 16099MB
[2025-01-18 09:46:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:248] * Acc@1 82.458 Acc@5 96.171
[2025-01-18 09:46:02 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.5%
[2025-01-18 09:46:02 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.63%
[2025-01-18 09:46:10 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.186 (8.186)	Loss 0.7367 (0.7367)	Acc@1 85.742 (85.742)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 09:46:14 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.102)	Loss 0.9745 (0.8421)	Acc@1 79.419 (83.365)	Acc@5 95.410 (96.467)	Mem 16099MB
[2025-01-18 09:46:14 internimage_t_1k_224] (main.py 575): INFO [Epoch:248] * Acc@1 83.243 Acc@5 96.491
[2025-01-18 09:46:14 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.2%
[2025-01-18 09:46:14 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:46:15 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:46:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.24%
[2025-01-18 09:46:18 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][0/312]	eta 0:12:07 lr 0.000316	time 2.3313 (2.3313)	model_time 0.5217 (0.5217)	loss 1.6951 (1.6951)	grad_norm 2.2814 (2.2814/0.0000)	mem 16099MB
[2025-01-18 09:46:22 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][10/312]	eta 0:03:12 lr 0.000315	time 0.5350 (0.6384)	model_time 0.5345 (0.4735)	loss 2.1434 (2.4051)	grad_norm 2.4796 (2.2592/0.8591)	mem 16099MB
[2025-01-18 09:46:27 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][20/312]	eta 0:02:41 lr 0.000315	time 0.4664 (0.5516)	model_time 0.4660 (0.4650)	loss 1.9446 (2.5057)	grad_norm 2.0005 (2.6681/1.0415)	mem 16099MB
[2025-01-18 09:46:31 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][30/312]	eta 0:02:27 lr 0.000315	time 0.4489 (0.5221)	model_time 0.4484 (0.4633)	loss 3.1839 (2.5263)	grad_norm 1.8244 (2.6071/1.0048)	mem 16099MB
[2025-01-18 09:46:36 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][40/312]	eta 0:02:18 lr 0.000314	time 0.5276 (0.5089)	model_time 0.5274 (0.4643)	loss 2.7727 (2.5453)	grad_norm 3.3298 (2.5508/0.9342)	mem 16099MB
[2025-01-18 09:46:41 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][50/312]	eta 0:02:10 lr 0.000314	time 0.4505 (0.4986)	model_time 0.4500 (0.4627)	loss 3.1845 (2.5504)	grad_norm 2.5449 (2.7060/1.1102)	mem 16099MB
[2025-01-18 09:46:45 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][60/312]	eta 0:02:04 lr 0.000314	time 0.4527 (0.4926)	model_time 0.4523 (0.4625)	loss 2.2928 (2.5845)	grad_norm 1.2177 (2.8300/1.2228)	mem 16099MB
[2025-01-18 09:46:50 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][70/312]	eta 0:01:58 lr 0.000313	time 0.4573 (0.4885)	model_time 0.4569 (0.4627)	loss 3.2697 (2.6197)	grad_norm 5.3659 (2.8882/1.2091)	mem 16099MB
[2025-01-18 09:46:55 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][80/312]	eta 0:01:52 lr 0.000313	time 0.4402 (0.4844)	model_time 0.4398 (0.4617)	loss 1.8805 (2.6546)	grad_norm 1.1444 (3.1465/1.5329)	mem 16099MB
[2025-01-18 09:46:59 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][90/312]	eta 0:01:46 lr 0.000313	time 0.4635 (0.4819)	model_time 0.4630 (0.4616)	loss 1.7716 (2.6795)	grad_norm 3.7966 (3.0961/1.4928)	mem 16099MB
[2025-01-18 09:47:04 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][100/312]	eta 0:01:41 lr 0.000312	time 0.4531 (0.4791)	model_time 0.4527 (0.4608)	loss 3.4089 (2.6714)	grad_norm 2.2495 (3.0580/1.5235)	mem 16099MB
[2025-01-18 09:47:08 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][110/312]	eta 0:01:36 lr 0.000312	time 0.4537 (0.4772)	model_time 0.4532 (0.4605)	loss 2.8801 (2.6996)	grad_norm 1.9051 (2.9569/1.4995)	mem 16099MB
[2025-01-18 09:47:13 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][120/312]	eta 0:01:31 lr 0.000312	time 0.4611 (0.4767)	model_time 0.4606 (0.4614)	loss 2.2245 (2.7003)	grad_norm 2.0145 (2.8859/1.4729)	mem 16099MB
[2025-01-18 09:47:18 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][130/312]	eta 0:01:26 lr 0.000311	time 0.4438 (0.4775)	model_time 0.4434 (0.4633)	loss 2.4116 (2.7088)	grad_norm 3.1205 (2.8425/1.4453)	mem 16099MB
[2025-01-18 09:47:23 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][140/312]	eta 0:01:22 lr 0.000311	time 0.4419 (0.4777)	model_time 0.4414 (0.4645)	loss 3.4360 (2.6949)	grad_norm 1.9522 (2.8477/1.4303)	mem 16099MB
[2025-01-18 09:47:27 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][150/312]	eta 0:01:17 lr 0.000311	time 0.4538 (0.4770)	model_time 0.4534 (0.4645)	loss 2.1648 (2.7030)	grad_norm 1.8299 (2.8006/1.4098)	mem 16099MB
[2025-01-18 09:47:32 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][160/312]	eta 0:01:12 lr 0.000310	time 0.4506 (0.4767)	model_time 0.4504 (0.4650)	loss 3.4793 (2.7029)	grad_norm 3.5778 (2.7627/1.3838)	mem 16099MB
[2025-01-18 09:47:37 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][170/312]	eta 0:01:07 lr 0.000310	time 0.4428 (0.4780)	model_time 0.4424 (0.4670)	loss 2.9269 (2.7132)	grad_norm 4.2243 (2.7557/1.3590)	mem 16099MB
[2025-01-18 09:47:42 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][180/312]	eta 0:01:02 lr 0.000310	time 0.4555 (0.4765)	model_time 0.4553 (0.4660)	loss 3.2948 (2.7295)	grad_norm 1.7128 (2.7392/1.3307)	mem 16099MB
[2025-01-18 09:47:46 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][190/312]	eta 0:00:57 lr 0.000309	time 0.4629 (0.4754)	model_time 0.4624 (0.4655)	loss 2.3806 (2.7251)	grad_norm 1.7782 (2.7047/1.3114)	mem 16099MB
[2025-01-18 09:47:51 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][200/312]	eta 0:00:53 lr 0.000309	time 0.4555 (0.4746)	model_time 0.4554 (0.4652)	loss 2.5802 (2.7244)	grad_norm 3.9755 (2.7082/1.2950)	mem 16099MB
[2025-01-18 09:47:55 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][210/312]	eta 0:00:48 lr 0.000309	time 0.4728 (0.4739)	model_time 0.4724 (0.4649)	loss 1.8146 (2.7165)	grad_norm 5.4407 (2.7719/1.3446)	mem 16099MB
[2025-01-18 09:48:00 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][220/312]	eta 0:00:43 lr 0.000308	time 0.4516 (0.4728)	model_time 0.4512 (0.4642)	loss 1.8627 (2.7180)	grad_norm 4.7504 (2.8045/1.3603)	mem 16099MB
[2025-01-18 09:48:05 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][230/312]	eta 0:00:38 lr 0.000308	time 0.4461 (0.4728)	model_time 0.4457 (0.4646)	loss 3.1268 (2.7281)	grad_norm 3.5426 (2.8206/1.3551)	mem 16099MB
[2025-01-18 09:48:09 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][240/312]	eta 0:00:33 lr 0.000308	time 0.4584 (0.4721)	model_time 0.4583 (0.4642)	loss 3.0110 (2.7387)	grad_norm 1.6288 (2.8246/1.3628)	mem 16099MB
[2025-01-18 09:48:14 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][250/312]	eta 0:00:29 lr 0.000307	time 0.4423 (0.4716)	model_time 0.4421 (0.4640)	loss 3.3010 (2.7353)	grad_norm 1.2642 (2.8211/1.3672)	mem 16099MB
[2025-01-18 09:48:18 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][260/312]	eta 0:00:24 lr 0.000307	time 0.4587 (0.4711)	model_time 0.4583 (0.4637)	loss 1.8625 (2.7413)	grad_norm 1.8865 (2.8115/1.3470)	mem 16099MB
[2025-01-18 09:48:23 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][270/312]	eta 0:00:19 lr 0.000307	time 0.4402 (0.4709)	model_time 0.4400 (0.4638)	loss 3.0928 (2.7432)	grad_norm 3.2807 (2.8175/1.3332)	mem 16099MB
[2025-01-18 09:48:28 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][280/312]	eta 0:00:15 lr 0.000306	time 0.4511 (0.4706)	model_time 0.4507 (0.4638)	loss 2.9726 (2.7436)	grad_norm 6.2726 (2.8405/1.3387)	mem 16099MB
[2025-01-18 09:48:32 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][290/312]	eta 0:00:10 lr 0.000306	time 0.4599 (0.4712)	model_time 0.4594 (0.4646)	loss 3.1070 (2.7459)	grad_norm 2.8582 (2.8059/1.3331)	mem 16099MB
[2025-01-18 09:48:37 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][300/312]	eta 0:00:05 lr 0.000306	time 0.4371 (0.4712)	model_time 0.4370 (0.4648)	loss 2.8659 (2.7448)	grad_norm 3.4151 (2.8135/1.3342)	mem 16099MB
[2025-01-18 09:48:42 internimage_t_1k_224] (main.py 510): INFO Train: [249/300][310/312]	eta 0:00:00 lr 0.000305	time 0.4401 (0.4707)	model_time 0.4400 (0.4645)	loss 3.2238 (2.7405)	grad_norm 2.7255 (2.8449/1.3377)	mem 16099MB
[2025-01-18 09:48:42 internimage_t_1k_224] (main.py 519): INFO EPOCH 249 training takes 0:02:26
[2025-01-18 09:48:42 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_249.pth saving......
[2025-01-18 09:48:43 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_249.pth saved !!!
[2025-01-18 09:48:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.483 (7.483)	Loss 0.7276 (0.7276)	Acc@1 84.766 (84.766)	Acc@5 97.339 (97.339)	Mem 16099MB
[2025-01-18 09:48:54 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.987)	Loss 0.9865 (0.8358)	Acc@1 78.247 (82.728)	Acc@5 95.068 (96.131)	Mem 16099MB
[2025-01-18 09:48:54 internimage_t_1k_224] (main.py 575): INFO [Epoch:249] * Acc@1 82.568 Acc@5 96.125
[2025-01-18 09:48:54 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.6%
[2025-01-18 09:48:54 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.63%
[2025-01-18 09:49:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.256 (8.256)	Loss 0.7359 (0.7359)	Acc@1 85.693 (85.693)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 09:49:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.103)	Loss 0.9732 (0.8410)	Acc@1 79.370 (83.376)	Acc@5 95.459 (96.467)	Mem 16099MB
[2025-01-18 09:49:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:249] * Acc@1 83.255 Acc@5 96.491
[2025-01-18 09:49:07 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 09:49:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:49:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:49:08 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.26%
[2025-01-18 09:49:11 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][0/312]	eta 0:12:47 lr 0.000305	time 2.4584 (2.4584)	model_time 0.4563 (0.4563)	loss 2.2794 (2.2794)	grad_norm 2.2789 (2.2789/0.0000)	mem 16099MB
[2025-01-18 09:49:15 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][10/312]	eta 0:03:18 lr 0.000305	time 0.4472 (0.6574)	model_time 0.4466 (0.4751)	loss 2.6914 (2.6429)	grad_norm 1.9039 (2.4325/0.9145)	mem 16099MB
[2025-01-18 09:49:20 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][20/312]	eta 0:02:44 lr 0.000305	time 0.4400 (0.5647)	model_time 0.4398 (0.4691)	loss 1.8761 (2.7061)	grad_norm 3.1688 (2.5041/0.8054)	mem 16099MB
[2025-01-18 09:49:25 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][30/312]	eta 0:02:30 lr 0.000304	time 0.5237 (0.5320)	model_time 0.5235 (0.4671)	loss 3.1001 (2.6959)	grad_norm 3.0681 (2.6074/0.9154)	mem 16099MB
[2025-01-18 09:49:30 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][40/312]	eta 0:02:22 lr 0.000304	time 0.4609 (0.5250)	model_time 0.4608 (0.4759)	loss 1.8197 (2.7469)	grad_norm 3.2628 (2.8453/1.1153)	mem 16099MB
[2025-01-18 09:49:34 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][50/312]	eta 0:02:14 lr 0.000304	time 0.4537 (0.5141)	model_time 0.4532 (0.4745)	loss 2.1422 (2.7474)	grad_norm 2.3289 (2.7720/1.0782)	mem 16099MB
[2025-01-18 09:49:39 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][60/312]	eta 0:02:07 lr 0.000303	time 0.4564 (0.5047)	model_time 0.4559 (0.4715)	loss 2.9283 (2.7964)	grad_norm 2.8286 (2.7484/1.0442)	mem 16099MB
[2025-01-18 09:49:44 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][70/312]	eta 0:02:00 lr 0.000303	time 0.4618 (0.4994)	model_time 0.4616 (0.4708)	loss 1.7684 (2.7819)	grad_norm 1.7915 (2.6914/1.0707)	mem 16099MB
[2025-01-18 09:49:48 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][80/312]	eta 0:01:54 lr 0.000303	time 0.4501 (0.4951)	model_time 0.4497 (0.4700)	loss 1.8632 (2.7604)	grad_norm 2.2965 (2.6371/1.0233)	mem 16099MB
[2025-01-18 09:49:53 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][90/312]	eta 0:01:48 lr 0.000302	time 0.4485 (0.4907)	model_time 0.4481 (0.4684)	loss 2.9129 (2.7562)	grad_norm 4.5467 (2.7464/1.0648)	mem 16099MB
[2025-01-18 09:49:57 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][100/312]	eta 0:01:43 lr 0.000302	time 0.4573 (0.4885)	model_time 0.4572 (0.4683)	loss 2.8832 (2.7774)	grad_norm 2.7314 (2.8929/1.2093)	mem 16099MB
[2025-01-18 09:50:02 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][110/312]	eta 0:01:38 lr 0.000302	time 0.4497 (0.4855)	model_time 0.4495 (0.4671)	loss 2.3853 (2.7792)	grad_norm 2.0699 (2.9270/1.2168)	mem 16099MB
[2025-01-18 09:50:07 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][120/312]	eta 0:01:32 lr 0.000301	time 0.4725 (0.4835)	model_time 0.4720 (0.4665)	loss 3.0172 (2.7711)	grad_norm 4.3201 (2.9644/1.2350)	mem 16099MB
[2025-01-18 09:50:11 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][130/312]	eta 0:01:27 lr 0.000301	time 0.4501 (0.4835)	model_time 0.4499 (0.4678)	loss 3.2348 (2.7860)	grad_norm 1.8942 (2.9655/1.2810)	mem 16099MB
[2025-01-18 09:50:16 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][140/312]	eta 0:01:22 lr 0.000301	time 0.4712 (0.4826)	model_time 0.4708 (0.4680)	loss 2.9539 (2.7907)	grad_norm 1.3994 (2.9549/1.2816)	mem 16099MB
[2025-01-18 09:50:21 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][150/312]	eta 0:01:18 lr 0.000300	time 0.4503 (0.4835)	model_time 0.4501 (0.4698)	loss 3.0212 (2.7851)	grad_norm 3.1160 (2.9908/1.2657)	mem 16099MB
[2025-01-18 09:50:26 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][160/312]	eta 0:01:13 lr 0.000300	time 0.4510 (0.4848)	model_time 0.4506 (0.4720)	loss 2.8119 (2.7972)	grad_norm 4.3635 (3.1025/1.3231)	mem 16099MB
[2025-01-18 09:50:31 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][170/312]	eta 0:01:08 lr 0.000300	time 0.4486 (0.4830)	model_time 0.4485 (0.4709)	loss 3.0869 (2.8006)	grad_norm 2.9866 (3.0984/1.3024)	mem 16099MB
[2025-01-18 09:50:35 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][180/312]	eta 0:01:03 lr 0.000299	time 0.4518 (0.4817)	model_time 0.4516 (0.4703)	loss 2.7834 (2.8044)	grad_norm 3.2703 (3.0999/1.2874)	mem 16099MB
[2025-01-18 09:50:40 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][190/312]	eta 0:00:58 lr 0.000299	time 0.4612 (0.4805)	model_time 0.4607 (0.4696)	loss 3.0136 (2.8050)	grad_norm 1.4514 (3.0562/1.2825)	mem 16099MB
[2025-01-18 09:50:45 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][200/312]	eta 0:00:53 lr 0.000299	time 0.4541 (0.4800)	model_time 0.4539 (0.4696)	loss 2.0041 (2.7997)	grad_norm 1.1744 (3.0294/1.2836)	mem 16099MB
[2025-01-18 09:50:49 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][210/312]	eta 0:00:48 lr 0.000298	time 0.4669 (0.4797)	model_time 0.4665 (0.4699)	loss 2.5958 (2.7867)	grad_norm 1.7775 (2.9834/1.2757)	mem 16099MB
[2025-01-18 09:50:54 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][220/312]	eta 0:00:44 lr 0.000298	time 0.6044 (0.4792)	model_time 0.6043 (0.4698)	loss 3.0627 (2.7963)	grad_norm 4.1201 (2.9676/1.2635)	mem 16099MB
[2025-01-18 09:50:59 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][230/312]	eta 0:00:39 lr 0.000298	time 0.4484 (0.4785)	model_time 0.4482 (0.4694)	loss 2.6150 (2.8027)	grad_norm 2.6325 (2.9408/1.2497)	mem 16099MB
[2025-01-18 09:51:03 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][240/312]	eta 0:00:34 lr 0.000297	time 0.4614 (0.4778)	model_time 0.4610 (0.4691)	loss 3.3400 (2.8017)	grad_norm 1.3194 (2.9308/1.2443)	mem 16099MB
[2025-01-18 09:51:08 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][250/312]	eta 0:00:29 lr 0.000297	time 0.4470 (0.4775)	model_time 0.4466 (0.4692)	loss 2.7330 (2.7868)	grad_norm 2.5588 (2.9263/1.2290)	mem 16099MB
[2025-01-18 09:51:13 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][260/312]	eta 0:00:24 lr 0.000297	time 0.4574 (0.4770)	model_time 0.4570 (0.4690)	loss 2.3564 (2.7892)	grad_norm 1.3337 (2.9229/1.2304)	mem 16099MB
[2025-01-18 09:51:17 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][270/312]	eta 0:00:20 lr 0.000296	time 0.4469 (0.4767)	model_time 0.4468 (0.4689)	loss 3.0338 (2.7852)	grad_norm 1.9262 (2.8890/1.2275)	mem 16099MB
[2025-01-18 09:51:22 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][280/312]	eta 0:00:15 lr 0.000296	time 0.5648 (0.4767)	model_time 0.5647 (0.4692)	loss 2.6995 (2.7760)	grad_norm 3.2484 (2.8688/1.2188)	mem 16099MB
[2025-01-18 09:51:27 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][290/312]	eta 0:00:10 lr 0.000296	time 0.4620 (0.4765)	model_time 0.4616 (0.4692)	loss 2.4638 (2.7747)	grad_norm 1.3240 (2.8674/1.2235)	mem 16099MB
[2025-01-18 09:51:31 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][300/312]	eta 0:00:05 lr 0.000295	time 0.4375 (0.4762)	model_time 0.4374 (0.4692)	loss 2.9976 (2.7790)	grad_norm 1.2749 (2.8310/1.2265)	mem 16099MB
[2025-01-18 09:51:36 internimage_t_1k_224] (main.py 510): INFO Train: [250/300][310/312]	eta 0:00:00 lr 0.000295	time 0.5304 (0.4755)	model_time 0.5303 (0.4687)	loss 2.7762 (2.7767)	grad_norm 4.8186 (2.8581/1.2245)	mem 16099MB
[2025-01-18 09:51:36 internimage_t_1k_224] (main.py 519): INFO EPOCH 250 training takes 0:02:28
[2025-01-18 09:51:36 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_250.pth saving......
[2025-01-18 09:51:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_250.pth saved !!!
[2025-01-18 09:51:45 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.753 (7.753)	Loss 0.7358 (0.7358)	Acc@1 85.107 (85.107)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 09:51:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.036)	Loss 0.9825 (0.8410)	Acc@1 78.027 (82.733)	Acc@5 94.873 (96.191)	Mem 16099MB
[2025-01-18 09:51:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:250] * Acc@1 82.598 Acc@5 96.177
[2025-01-18 09:51:49 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.6%
[2025-01-18 09:51:49 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.63%
[2025-01-18 09:51:57 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.327 (8.327)	Loss 0.7350 (0.7350)	Acc@1 85.742 (85.742)	Acc@5 97.632 (97.632)	Mem 16099MB
[2025-01-18 09:52:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.108 (1.121)	Loss 0.9718 (0.8398)	Acc@1 79.395 (83.372)	Acc@5 95.532 (96.471)	Mem 16099MB
[2025-01-18 09:52:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:250] * Acc@1 83.247 Acc@5 96.495
[2025-01-18 09:52:02 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.2%
[2025-01-18 09:52:02 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.26%
[2025-01-18 09:52:05 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][0/312]	eta 0:15:28 lr 0.000295	time 2.9759 (2.9759)	model_time 0.9106 (0.9106)	loss 3.3441 (3.3441)	grad_norm 3.5590 (3.5590/0.0000)	mem 16099MB
[2025-01-18 09:52:09 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][10/312]	eta 0:03:36 lr 0.000295	time 0.4443 (0.7159)	model_time 0.4441 (0.5276)	loss 2.8532 (2.9850)	grad_norm 8.3079 (3.7966/1.7671)	mem 16099MB
[2025-01-18 09:52:14 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][20/312]	eta 0:02:55 lr 0.000294	time 0.4690 (0.6002)	model_time 0.4688 (0.5015)	loss 2.8259 (2.8981)	grad_norm 2.5754 (3.8444/1.6964)	mem 16099MB
[2025-01-18 09:52:19 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][30/312]	eta 0:02:35 lr 0.000294	time 0.4460 (0.5531)	model_time 0.4458 (0.4860)	loss 2.9438 (2.7926)	grad_norm 4.4071 (3.6459/1.6674)	mem 16099MB
[2025-01-18 09:52:23 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][40/312]	eta 0:02:24 lr 0.000294	time 0.4440 (0.5323)	model_time 0.4438 (0.4815)	loss 2.2740 (2.7401)	grad_norm 2.5543 (3.3852/1.6357)	mem 16099MB
[2025-01-18 09:52:28 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][50/312]	eta 0:02:15 lr 0.000293	time 0.4619 (0.5182)	model_time 0.4617 (0.4773)	loss 2.0873 (2.7267)	grad_norm 2.5938 (3.2551/1.5257)	mem 16099MB
[2025-01-18 09:52:33 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][60/312]	eta 0:02:08 lr 0.000293	time 0.4435 (0.5117)	model_time 0.4433 (0.4775)	loss 3.0215 (2.7461)	grad_norm 3.1708 (3.1733/1.4648)	mem 16099MB
[2025-01-18 09:52:37 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][70/312]	eta 0:02:01 lr 0.000293	time 0.4611 (0.5041)	model_time 0.4606 (0.4746)	loss 3.1122 (2.7662)	grad_norm 2.3235 (3.0830/1.3883)	mem 16099MB
[2025-01-18 09:52:42 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][80/312]	eta 0:01:55 lr 0.000292	time 0.4506 (0.4990)	model_time 0.4504 (0.4731)	loss 1.8393 (2.7443)	grad_norm 0.9154 (2.9944/1.3687)	mem 16099MB
[2025-01-18 09:52:47 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][90/312]	eta 0:01:49 lr 0.000292	time 0.4577 (0.4944)	model_time 0.4575 (0.4713)	loss 2.6739 (2.7306)	grad_norm 4.2612 (3.0744/1.3675)	mem 16099MB
[2025-01-18 09:52:51 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][100/312]	eta 0:01:43 lr 0.000292	time 0.4526 (0.4905)	model_time 0.4524 (0.4697)	loss 2.9379 (2.7385)	grad_norm 2.2511 (3.1038/1.3490)	mem 16099MB
[2025-01-18 09:52:56 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][110/312]	eta 0:01:38 lr 0.000291	time 0.4640 (0.4885)	model_time 0.4638 (0.4695)	loss 3.0513 (2.7338)	grad_norm 4.4977 (3.1131/1.3138)	mem 16099MB
[2025-01-18 09:53:00 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][120/312]	eta 0:01:33 lr 0.000291	time 0.4443 (0.4863)	model_time 0.4441 (0.4688)	loss 2.0504 (2.6998)	grad_norm 1.8880 (3.1070/1.3216)	mem 16099MB
[2025-01-18 09:53:05 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][130/312]	eta 0:01:28 lr 0.000291	time 0.4538 (0.4861)	model_time 0.4536 (0.4700)	loss 3.0257 (2.7003)	grad_norm 2.6001 (3.1631/1.3856)	mem 16099MB
[2025-01-18 09:53:10 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][140/312]	eta 0:01:23 lr 0.000290	time 0.6040 (0.4861)	model_time 0.6038 (0.4710)	loss 3.6766 (2.7110)	grad_norm 2.0960 (3.1079/1.3629)	mem 16099MB
[2025-01-18 09:53:15 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][150/312]	eta 0:01:18 lr 0.000290	time 0.4487 (0.4849)	model_time 0.4484 (0.4709)	loss 2.4188 (2.7025)	grad_norm 2.9227 (3.1078/1.3458)	mem 16099MB
[2025-01-18 09:53:20 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][160/312]	eta 0:01:13 lr 0.000290	time 0.4459 (0.4852)	model_time 0.4454 (0.4720)	loss 2.6933 (2.7051)	grad_norm 1.7760 (3.0815/1.3507)	mem 16099MB
[2025-01-18 09:53:24 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][170/312]	eta 0:01:08 lr 0.000289	time 0.4447 (0.4842)	model_time 0.4445 (0.4718)	loss 3.0687 (2.7102)	grad_norm 2.8468 (3.1122/1.3586)	mem 16099MB
[2025-01-18 09:53:29 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][180/312]	eta 0:01:03 lr 0.000289	time 0.4390 (0.4829)	model_time 0.4389 (0.4711)	loss 2.5356 (2.7089)	grad_norm 4.2332 (3.1391/1.3642)	mem 16099MB
[2025-01-18 09:53:34 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][190/312]	eta 0:00:58 lr 0.000289	time 0.4522 (0.4814)	model_time 0.4520 (0.4702)	loss 2.5914 (2.7028)	grad_norm 2.3457 (3.1401/1.3818)	mem 16099MB
[2025-01-18 09:53:38 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][200/312]	eta 0:00:53 lr 0.000289	time 0.4554 (0.4802)	model_time 0.4552 (0.4696)	loss 3.0903 (2.7145)	grad_norm 3.4523 (3.0978/1.3696)	mem 16099MB
[2025-01-18 09:53:43 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][210/312]	eta 0:00:48 lr 0.000288	time 0.4510 (0.4794)	model_time 0.4509 (0.4692)	loss 2.3535 (2.7131)	grad_norm 1.3043 (3.0493/1.3570)	mem 16099MB
[2025-01-18 09:53:47 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][220/312]	eta 0:00:44 lr 0.000288	time 0.4417 (0.4785)	model_time 0.4415 (0.4688)	loss 2.6073 (2.7199)	grad_norm 4.0179 (3.0524/1.3625)	mem 16099MB
[2025-01-18 09:53:52 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][230/312]	eta 0:00:39 lr 0.000288	time 0.4426 (0.4783)	model_time 0.4424 (0.4690)	loss 2.6751 (2.7223)	grad_norm 1.5948 (3.0296/1.3669)	mem 16099MB
[2025-01-18 09:53:57 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][240/312]	eta 0:00:34 lr 0.000287	time 0.4679 (0.4774)	model_time 0.4677 (0.4684)	loss 3.2661 (2.7271)	grad_norm 1.5482 (2.9971/1.3585)	mem 16099MB
[2025-01-18 09:54:01 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][250/312]	eta 0:00:29 lr 0.000287	time 0.4399 (0.4763)	model_time 0.4397 (0.4677)	loss 2.8263 (2.7243)	grad_norm 3.6001 (2.9883/1.3570)	mem 16099MB
[2025-01-18 09:54:06 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][260/312]	eta 0:00:24 lr 0.000287	time 0.4480 (0.4754)	model_time 0.4475 (0.4672)	loss 3.2414 (2.7270)	grad_norm 2.1227 (2.9800/1.3568)	mem 16099MB
[2025-01-18 09:54:10 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][270/312]	eta 0:00:19 lr 0.000286	time 0.4748 (0.4750)	model_time 0.4746 (0.4671)	loss 2.9751 (2.7348)	grad_norm 2.1733 (2.9782/1.3502)	mem 16099MB
[2025-01-18 09:54:15 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][280/312]	eta 0:00:15 lr 0.000286	time 0.4569 (0.4743)	model_time 0.4565 (0.4666)	loss 3.2458 (2.7437)	grad_norm 3.2514 (2.9743/1.3410)	mem 16099MB
[2025-01-18 09:54:20 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][290/312]	eta 0:00:10 lr 0.000286	time 0.4441 (0.4740)	model_time 0.4437 (0.4666)	loss 3.1749 (2.7430)	grad_norm 3.8964 (2.9737/1.3615)	mem 16099MB
[2025-01-18 09:54:24 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][300/312]	eta 0:00:05 lr 0.000285	time 0.5253 (0.4741)	model_time 0.5252 (0.4669)	loss 3.0176 (2.7389)	grad_norm 1.2698 (2.9662/1.3578)	mem 16099MB
[2025-01-18 09:54:29 internimage_t_1k_224] (main.py 510): INFO Train: [251/300][310/312]	eta 0:00:00 lr 0.000285	time 0.4369 (0.4732)	model_time 0.4368 (0.4662)	loss 2.1287 (2.7425)	grad_norm 2.2776 (2.9601/1.3398)	mem 16099MB
[2025-01-18 09:54:29 internimage_t_1k_224] (main.py 519): INFO EPOCH 251 training takes 0:02:27
[2025-01-18 09:54:29 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_251.pth saving......
[2025-01-18 09:54:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_251.pth saved !!!
[2025-01-18 09:54:38 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.600 (7.600)	Loss 0.7340 (0.7340)	Acc@1 85.327 (85.327)	Acc@5 97.412 (97.412)	Mem 16099MB
[2025-01-18 09:54:42 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.029)	Loss 0.9697 (0.8328)	Acc@1 79.102 (82.828)	Acc@5 94.922 (96.254)	Mem 16099MB
[2025-01-18 09:54:42 internimage_t_1k_224] (main.py 575): INFO [Epoch:251] * Acc@1 82.670 Acc@5 96.229
[2025-01-18 09:54:42 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.7%
[2025-01-18 09:54:42 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 09:54:43 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 09:54:43 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.67%
[2025-01-18 09:54:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.532 (7.532)	Loss 0.7340 (0.7340)	Acc@1 85.791 (85.791)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 09:54:54 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.007)	Loss 0.9703 (0.8385)	Acc@1 79.517 (83.407)	Acc@5 95.557 (96.473)	Mem 16099MB
[2025-01-18 09:54:54 internimage_t_1k_224] (main.py 575): INFO [Epoch:251] * Acc@1 83.279 Acc@5 96.499
[2025-01-18 09:54:54 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 09:54:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:54:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:54:56 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.28%
[2025-01-18 09:54:58 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][0/312]	eta 0:11:36 lr 0.000285	time 2.2311 (2.2311)	model_time 0.4599 (0.4599)	loss 2.1761 (2.1761)	grad_norm 1.1557 (1.1557/0.0000)	mem 16099MB
[2025-01-18 09:55:03 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][10/312]	eta 0:03:12 lr 0.000285	time 0.5272 (0.6376)	model_time 0.5266 (0.4762)	loss 2.9681 (2.7780)	grad_norm 2.1494 (2.3046/0.9671)	mem 16099MB
[2025-01-18 09:55:07 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][20/312]	eta 0:02:40 lr 0.000284	time 0.4469 (0.5489)	model_time 0.4467 (0.4643)	loss 1.8942 (2.7155)	grad_norm 1.1999 (2.1074/0.8291)	mem 16099MB
[2025-01-18 09:55:12 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][30/312]	eta 0:02:27 lr 0.000284	time 0.4525 (0.5245)	model_time 0.4520 (0.4670)	loss 2.9084 (2.8048)	grad_norm 1.7322 (2.2541/0.8843)	mem 16099MB
[2025-01-18 09:55:16 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][40/312]	eta 0:02:18 lr 0.000284	time 0.4510 (0.5080)	model_time 0.4505 (0.4644)	loss 3.2488 (2.8238)	grad_norm 2.5458 (2.4824/1.1573)	mem 16099MB
[2025-01-18 09:55:21 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][50/312]	eta 0:02:12 lr 0.000283	time 0.4622 (0.5069)	model_time 0.4620 (0.4718)	loss 2.7189 (2.7864)	grad_norm 3.5032 (2.4111/1.0922)	mem 16099MB
[2025-01-18 09:55:26 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][60/312]	eta 0:02:06 lr 0.000283	time 0.4649 (0.5002)	model_time 0.4647 (0.4708)	loss 2.5208 (2.8076)	grad_norm 1.8073 (2.4592/1.0768)	mem 16099MB
[2025-01-18 09:55:31 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][70/312]	eta 0:01:59 lr 0.000283	time 0.4622 (0.4943)	model_time 0.4620 (0.4690)	loss 3.0820 (2.7827)	grad_norm 4.8272 (2.5639/1.1049)	mem 16099MB
[2025-01-18 09:55:35 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][80/312]	eta 0:01:53 lr 0.000282	time 0.4558 (0.4897)	model_time 0.4556 (0.4675)	loss 2.7024 (2.7960)	grad_norm 1.5886 (2.5240/1.0915)	mem 16099MB
[2025-01-18 09:55:40 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][90/312]	eta 0:01:48 lr 0.000282	time 0.4805 (0.4894)	model_time 0.4803 (0.4696)	loss 2.2140 (2.7742)	grad_norm 3.8346 (2.5407/1.0654)	mem 16099MB
[2025-01-18 09:55:45 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][100/312]	eta 0:01:43 lr 0.000282	time 0.6079 (0.4885)	model_time 0.6077 (0.4706)	loss 3.4360 (2.7752)	grad_norm 2.1725 (2.5151/1.0401)	mem 16099MB
[2025-01-18 09:55:50 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][110/312]	eta 0:01:38 lr 0.000281	time 0.4513 (0.4887)	model_time 0.4512 (0.4724)	loss 3.2973 (2.7831)	grad_norm 1.6809 (2.5315/1.0405)	mem 16099MB
[2025-01-18 09:55:54 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][120/312]	eta 0:01:33 lr 0.000281	time 0.4608 (0.4864)	model_time 0.4605 (0.4714)	loss 2.6637 (2.7760)	grad_norm 3.0127 (2.5342/1.0615)	mem 16099MB
[2025-01-18 09:55:59 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][130/312]	eta 0:01:28 lr 0.000281	time 0.4658 (0.4848)	model_time 0.4656 (0.4709)	loss 2.1938 (2.7798)	grad_norm 1.7300 (2.4937/1.0392)	mem 16099MB
[2025-01-18 09:56:04 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][140/312]	eta 0:01:23 lr 0.000280	time 0.4441 (0.4853)	model_time 0.4439 (0.4723)	loss 3.2494 (2.7787)	grad_norm 3.8159 (2.4945/1.0372)	mem 16099MB
[2025-01-18 09:56:09 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][150/312]	eta 0:01:18 lr 0.000280	time 0.4560 (0.4853)	model_time 0.4558 (0.4732)	loss 1.5484 (2.7641)	grad_norm 2.1245 (2.4969/1.0087)	mem 16099MB
[2025-01-18 09:56:14 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][160/312]	eta 0:01:13 lr 0.000280	time 0.4507 (0.4856)	model_time 0.4502 (0.4743)	loss 2.2483 (2.7564)	grad_norm 3.9192 (2.5363/1.0198)	mem 16099MB
[2025-01-18 09:56:18 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][170/312]	eta 0:01:08 lr 0.000279	time 0.4626 (0.4844)	model_time 0.4623 (0.4737)	loss 2.8524 (2.7441)	grad_norm 3.3011 (2.5442/1.0165)	mem 16099MB
[2025-01-18 09:56:23 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][180/312]	eta 0:01:03 lr 0.000279	time 0.4466 (0.4832)	model_time 0.4461 (0.4730)	loss 2.9750 (2.7322)	grad_norm 2.0584 (2.5505/1.0197)	mem 16099MB
[2025-01-18 09:56:28 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][190/312]	eta 0:00:58 lr 0.000279	time 0.4486 (0.4821)	model_time 0.4484 (0.4724)	loss 1.8039 (2.7367)	grad_norm 3.6560 (2.5478/1.0204)	mem 16099MB
[2025-01-18 09:56:32 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][200/312]	eta 0:00:53 lr 0.000279	time 0.4524 (0.4810)	model_time 0.4522 (0.4718)	loss 2.9799 (2.7329)	grad_norm 1.8479 (2.5620/1.0157)	mem 16099MB
[2025-01-18 09:56:37 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][210/312]	eta 0:00:48 lr 0.000278	time 0.4672 (0.4799)	model_time 0.4670 (0.4712)	loss 2.8093 (2.7338)	grad_norm 3.9235 (2.5783/1.0081)	mem 16099MB
[2025-01-18 09:56:42 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][220/312]	eta 0:00:44 lr 0.000278	time 0.4551 (0.4801)	model_time 0.4549 (0.4717)	loss 3.1208 (2.7383)	grad_norm 1.6525 (2.6113/1.0437)	mem 16099MB
[2025-01-18 09:56:46 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][230/312]	eta 0:00:39 lr 0.000278	time 0.4530 (0.4795)	model_time 0.4526 (0.4715)	loss 1.9686 (2.7364)	grad_norm 2.0050 (2.5958/1.0308)	mem 16099MB
[2025-01-18 09:56:51 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][240/312]	eta 0:00:34 lr 0.000277	time 0.4541 (0.4786)	model_time 0.4539 (0.4708)	loss 2.7598 (2.7410)	grad_norm 2.2253 (2.6069/1.0197)	mem 16099MB
[2025-01-18 09:56:56 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][250/312]	eta 0:00:29 lr 0.000277	time 0.4610 (0.4781)	model_time 0.4607 (0.4707)	loss 2.0288 (2.7405)	grad_norm 3.2644 (2.6104/1.0207)	mem 16099MB
[2025-01-18 09:57:00 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][260/312]	eta 0:00:24 lr 0.000277	time 0.4543 (0.4772)	model_time 0.4539 (0.4700)	loss 2.6494 (2.7398)	grad_norm 4.8528 (2.6101/1.0219)	mem 16099MB
[2025-01-18 09:57:05 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][270/312]	eta 0:00:20 lr 0.000276	time 0.4536 (0.4769)	model_time 0.4535 (0.4700)	loss 3.0034 (2.7311)	grad_norm 2.8867 (2.5973/1.0172)	mem 16099MB
[2025-01-18 09:57:10 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][280/312]	eta 0:00:15 lr 0.000276	time 0.4519 (0.4769)	model_time 0.4513 (0.4703)	loss 2.8360 (2.7387)	grad_norm 3.4929 (2.6165/1.0183)	mem 16099MB
[2025-01-18 09:57:14 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][290/312]	eta 0:00:10 lr 0.000276	time 0.4456 (0.4768)	model_time 0.4455 (0.4703)	loss 2.3909 (2.7415)	grad_norm 3.2407 (2.6282/1.0324)	mem 16099MB
[2025-01-18 09:57:19 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][300/312]	eta 0:00:05 lr 0.000275	time 0.4442 (0.4762)	model_time 0.4442 (0.4700)	loss 3.1247 (2.7495)	grad_norm 2.9319 (2.6340/1.0340)	mem 16099MB
[2025-01-18 09:57:24 internimage_t_1k_224] (main.py 510): INFO Train: [252/300][310/312]	eta 0:00:00 lr 0.000275	time 0.4430 (0.4763)	model_time 0.4429 (0.4702)	loss 2.9841 (2.7455)	grad_norm 1.6097 (2.6424/1.0240)	mem 16099MB
[2025-01-18 09:57:24 internimage_t_1k_224] (main.py 519): INFO EPOCH 252 training takes 0:02:28
[2025-01-18 09:57:24 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_252.pth saving......
[2025-01-18 09:57:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_252.pth saved !!!
[2025-01-18 09:57:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.345 (7.345)	Loss 0.7229 (0.7229)	Acc@1 85.205 (85.205)	Acc@5 97.314 (97.314)	Mem 16099MB
[2025-01-18 09:57:36 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.991)	Loss 0.9960 (0.8336)	Acc@1 77.856 (82.606)	Acc@5 94.971 (96.151)	Mem 16099MB
[2025-01-18 09:57:36 internimage_t_1k_224] (main.py 575): INFO [Epoch:252] * Acc@1 82.458 Acc@5 96.145
[2025-01-18 09:57:36 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.5%
[2025-01-18 09:57:36 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.67%
[2025-01-18 09:57:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.118 (8.118)	Loss 0.7332 (0.7332)	Acc@1 85.791 (85.791)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 09:57:48 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.098)	Loss 0.9691 (0.8375)	Acc@1 79.492 (83.418)	Acc@5 95.581 (96.473)	Mem 16099MB
[2025-01-18 09:57:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:252] * Acc@1 83.285 Acc@5 96.497
[2025-01-18 09:57:49 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 09:57:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 09:57:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 09:57:50 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.29%
[2025-01-18 09:57:52 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][0/312]	eta 0:11:52 lr 0.000275	time 2.2833 (2.2833)	model_time 0.4674 (0.4674)	loss 3.0042 (3.0042)	grad_norm 2.3966 (2.3966/0.0000)	mem 16099MB
[2025-01-18 09:57:57 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][10/312]	eta 0:03:10 lr 0.000275	time 0.4494 (0.6322)	model_time 0.4492 (0.4668)	loss 2.5407 (2.6501)	grad_norm 2.7398 (2.8391/1.1478)	mem 16099MB
[2025-01-18 09:58:02 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][20/312]	eta 0:02:48 lr 0.000274	time 0.7691 (0.5771)	model_time 0.7686 (0.4903)	loss 2.4919 (2.7691)	grad_norm 2.3774 (3.1869/1.6193)	mem 16099MB
[2025-01-18 09:58:07 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][30/312]	eta 0:02:33 lr 0.000274	time 0.4492 (0.5434)	model_time 0.4490 (0.4845)	loss 2.2872 (2.7212)	grad_norm 1.4165 (3.4304/1.7102)	mem 16099MB
[2025-01-18 09:58:11 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][40/312]	eta 0:02:23 lr 0.000274	time 0.4607 (0.5267)	model_time 0.4605 (0.4821)	loss 2.4261 (2.6303)	grad_norm 4.6669 (3.4332/1.6056)	mem 16099MB
[2025-01-18 09:58:16 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][50/312]	eta 0:02:15 lr 0.000273	time 0.4715 (0.5166)	model_time 0.4713 (0.4806)	loss 3.2066 (2.6782)	grad_norm 2.9599 (3.4329/1.5646)	mem 16099MB
[2025-01-18 09:58:21 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][60/312]	eta 0:02:07 lr 0.000273	time 0.4671 (0.5067)	model_time 0.4665 (0.4765)	loss 2.7081 (2.6847)	grad_norm 1.2774 (3.3660/1.5617)	mem 16099MB
[2025-01-18 09:58:25 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][70/312]	eta 0:02:01 lr 0.000273	time 0.4595 (0.5003)	model_time 0.4593 (0.4744)	loss 2.8329 (2.7054)	grad_norm 3.7269 (3.2470/1.5116)	mem 16099MB
[2025-01-18 09:58:30 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][80/312]	eta 0:01:54 lr 0.000273	time 0.4405 (0.4951)	model_time 0.4401 (0.4724)	loss 2.9100 (2.7121)	grad_norm 1.5619 (3.1912/1.5094)	mem 16099MB
[2025-01-18 09:58:35 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][90/312]	eta 0:01:49 lr 0.000272	time 0.4644 (0.4914)	model_time 0.4642 (0.4711)	loss 2.9658 (2.7213)	grad_norm 6.0694 (3.1106/1.5068)	mem 16099MB
[2025-01-18 09:58:39 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][100/312]	eta 0:01:44 lr 0.000272	time 0.4522 (0.4910)	model_time 0.4520 (0.4727)	loss 2.8654 (2.7204)	grad_norm 1.6248 (3.1376/1.5341)	mem 16099MB
[2025-01-18 09:58:44 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][110/312]	eta 0:01:38 lr 0.000272	time 0.4547 (0.4884)	model_time 0.4545 (0.4717)	loss 2.5542 (2.7380)	grad_norm 2.3308 (3.2070/1.5442)	mem 16099MB
[2025-01-18 09:58:49 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][120/312]	eta 0:01:33 lr 0.000271	time 0.4510 (0.4858)	model_time 0.4508 (0.4705)	loss 2.7123 (2.7289)	grad_norm 1.8799 (3.1952/1.5068)	mem 16099MB
[2025-01-18 09:58:54 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][130/312]	eta 0:01:28 lr 0.000271	time 0.4574 (0.4861)	model_time 0.4572 (0.4719)	loss 3.0065 (2.7448)	grad_norm 3.9965 (3.1494/1.4694)	mem 16099MB
[2025-01-18 09:58:58 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][140/312]	eta 0:01:23 lr 0.000271	time 0.4665 (0.4840)	model_time 0.4658 (0.4708)	loss 2.9705 (2.7440)	grad_norm 3.1484 (3.1414/1.4519)	mem 16099MB
[2025-01-18 09:59:03 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][150/312]	eta 0:01:18 lr 0.000270	time 0.4421 (0.4819)	model_time 0.4419 (0.4695)	loss 2.1199 (2.7338)	grad_norm 1.9317 (3.0963/1.4211)	mem 16099MB
[2025-01-18 09:59:08 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][160/312]	eta 0:01:13 lr 0.000270	time 0.4633 (0.4821)	model_time 0.4628 (0.4704)	loss 2.9024 (2.7319)	grad_norm 5.6357 (3.0950/1.4182)	mem 16099MB
[2025-01-18 09:59:12 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][170/312]	eta 0:01:08 lr 0.000270	time 0.4583 (0.4807)	model_time 0.4577 (0.4697)	loss 3.4284 (2.7264)	grad_norm 7.0828 (3.1262/1.4465)	mem 16099MB
[2025-01-18 09:59:17 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][180/312]	eta 0:01:03 lr 0.000269	time 0.4541 (0.4804)	model_time 0.4539 (0.4700)	loss 3.3611 (2.7180)	grad_norm 4.2017 (3.1683/1.4474)	mem 16099MB
[2025-01-18 09:59:22 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][190/312]	eta 0:00:58 lr 0.000269	time 0.4491 (0.4796)	model_time 0.4487 (0.4698)	loss 2.6719 (2.7250)	grad_norm 3.7791 (3.2176/1.4791)	mem 16099MB
[2025-01-18 09:59:27 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][200/312]	eta 0:00:53 lr 0.000269	time 0.4442 (0.4813)	model_time 0.4440 (0.4719)	loss 3.0748 (2.7318)	grad_norm 2.7104 (3.2131/1.4666)	mem 16099MB
[2025-01-18 09:59:31 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][210/312]	eta 0:00:49 lr 0.000268	time 0.5429 (0.4807)	model_time 0.5427 (0.4718)	loss 2.4876 (2.7207)	grad_norm 2.0150 (3.1944/1.4508)	mem 16099MB
[2025-01-18 09:59:36 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][220/312]	eta 0:00:44 lr 0.000268	time 0.4432 (0.4808)	model_time 0.4427 (0.4722)	loss 2.4805 (2.7220)	grad_norm 1.4030 (3.1666/1.4401)	mem 16099MB
[2025-01-18 09:59:41 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][230/312]	eta 0:00:39 lr 0.000268	time 0.4536 (0.4796)	model_time 0.4531 (0.4714)	loss 3.3332 (2.7288)	grad_norm 1.4117 (3.1701/1.4273)	mem 16099MB
[2025-01-18 09:59:45 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][240/312]	eta 0:00:34 lr 0.000268	time 0.4366 (0.4785)	model_time 0.4363 (0.4706)	loss 1.7969 (2.7298)	grad_norm 1.8345 (3.1685/1.4070)	mem 16099MB
[2025-01-18 09:59:50 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][250/312]	eta 0:00:29 lr 0.000267	time 0.4558 (0.4775)	model_time 0.4552 (0.4699)	loss 2.8862 (2.7303)	grad_norm 1.5943 (3.1433/1.3969)	mem 16099MB
[2025-01-18 09:59:54 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][260/312]	eta 0:00:24 lr 0.000267	time 0.4531 (0.4769)	model_time 0.4530 (0.4695)	loss 3.5220 (2.7353)	grad_norm 3.9190 (3.1251/1.3892)	mem 16099MB
[2025-01-18 09:59:59 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][270/312]	eta 0:00:19 lr 0.000267	time 0.4352 (0.4762)	model_time 0.4350 (0.4689)	loss 2.8230 (2.7370)	grad_norm 2.5312 (3.1112/1.3818)	mem 16099MB
[2025-01-18 10:00:04 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][280/312]	eta 0:00:15 lr 0.000266	time 0.4625 (0.4755)	model_time 0.4624 (0.4685)	loss 3.0266 (2.7389)	grad_norm 5.4954 (3.1108/1.3853)	mem 16099MB
[2025-01-18 10:00:08 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][290/312]	eta 0:00:10 lr 0.000266	time 0.4374 (0.4747)	model_time 0.4372 (0.4679)	loss 2.9207 (2.7485)	grad_norm 3.5784 (3.1156/1.3804)	mem 16099MB
[2025-01-18 10:00:13 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][300/312]	eta 0:00:05 lr 0.000266	time 0.5260 (0.4742)	model_time 0.5259 (0.4676)	loss 2.0308 (2.7542)	grad_norm 4.6648 (3.1185/1.3818)	mem 16099MB
[2025-01-18 10:00:17 internimage_t_1k_224] (main.py 510): INFO Train: [253/300][310/312]	eta 0:00:00 lr 0.000265	time 0.4388 (0.4735)	model_time 0.4388 (0.4671)	loss 2.7557 (2.7616)	grad_norm 2.8610 (3.1123/1.3703)	mem 16099MB
[2025-01-18 10:00:18 internimage_t_1k_224] (main.py 519): INFO EPOCH 253 training takes 0:02:27
[2025-01-18 10:00:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_253.pth saving......
[2025-01-18 10:00:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_253.pth saved !!!
[2025-01-18 10:00:26 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.128 (7.128)	Loss 0.7069 (0.7069)	Acc@1 85.181 (85.181)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 10:00:30 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.970)	Loss 0.9555 (0.8240)	Acc@1 79.053 (82.852)	Acc@5 95.239 (96.287)	Mem 16099MB
[2025-01-18 10:00:30 internimage_t_1k_224] (main.py 575): INFO [Epoch:253] * Acc@1 82.708 Acc@5 96.293
[2025-01-18 10:00:30 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.7%
[2025-01-18 10:00:30 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 10:00:31 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 10:00:31 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.71%
[2025-01-18 10:00:38 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.454 (7.454)	Loss 0.7322 (0.7322)	Acc@1 85.718 (85.718)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 10:00:42 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.017)	Loss 0.9681 (0.8365)	Acc@1 79.468 (83.407)	Acc@5 95.581 (96.491)	Mem 16099MB
[2025-01-18 10:00:42 internimage_t_1k_224] (main.py 575): INFO [Epoch:253] * Acc@1 83.279 Acc@5 96.513
[2025-01-18 10:00:42 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 10:00:42 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.29%
[2025-01-18 10:00:45 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][0/312]	eta 0:16:02 lr 0.000265	time 3.0835 (3.0835)	model_time 1.5525 (1.5525)	loss 3.2817 (3.2817)	grad_norm 3.7946 (3.7946/0.0000)	mem 16099MB
[2025-01-18 10:00:50 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][10/312]	eta 0:03:35 lr 0.000265	time 0.4502 (0.7122)	model_time 0.4500 (0.5727)	loss 2.3894 (2.8166)	grad_norm 1.2666 (2.2448/0.8916)	mem 16099MB
[2025-01-18 10:00:55 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][20/312]	eta 0:02:53 lr 0.000265	time 0.4519 (0.5931)	model_time 0.4517 (0.5199)	loss 3.0471 (2.7582)	grad_norm 1.2542 (2.1578/0.9704)	mem 16099MB
[2025-01-18 10:00:59 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][30/312]	eta 0:02:36 lr 0.000264	time 0.4553 (0.5544)	model_time 0.4549 (0.5047)	loss 2.9097 (2.7883)	grad_norm 1.5874 (2.1229/0.8858)	mem 16099MB
[2025-01-18 10:01:04 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][40/312]	eta 0:02:25 lr 0.000264	time 0.4670 (0.5342)	model_time 0.4668 (0.4965)	loss 2.7290 (2.7901)	grad_norm 3.6433 (2.2052/0.8280)	mem 16099MB
[2025-01-18 10:01:09 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][50/312]	eta 0:02:18 lr 0.000264	time 0.4505 (0.5294)	model_time 0.4503 (0.4990)	loss 2.8656 (2.7496)	grad_norm 2.1249 (2.5423/1.4295)	mem 16099MB
[2025-01-18 10:01:14 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][60/312]	eta 0:02:10 lr 0.000263	time 0.4591 (0.5187)	model_time 0.4586 (0.4932)	loss 3.1898 (2.7693)	grad_norm 2.0739 (2.5054/1.3314)	mem 16099MB
[2025-01-18 10:01:18 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][70/312]	eta 0:02:03 lr 0.000263	time 0.4496 (0.5090)	model_time 0.4494 (0.4871)	loss 3.0999 (2.7658)	grad_norm 2.1938 (2.5384/1.2876)	mem 16099MB
[2025-01-18 10:01:23 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][80/312]	eta 0:01:57 lr 0.000263	time 0.5427 (0.5044)	model_time 0.5425 (0.4852)	loss 2.8251 (2.7714)	grad_norm 3.4868 (2.5178/1.2277)	mem 16099MB
[2025-01-18 10:01:28 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][90/312]	eta 0:01:51 lr 0.000263	time 0.4520 (0.5008)	model_time 0.4518 (0.4836)	loss 3.1527 (2.7641)	grad_norm 3.5090 (2.6378/1.3785)	mem 16099MB
[2025-01-18 10:01:32 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][100/312]	eta 0:01:45 lr 0.000262	time 0.4473 (0.4961)	model_time 0.4472 (0.4806)	loss 2.9099 (2.7615)	grad_norm 7.9062 (2.7855/1.4803)	mem 16099MB
[2025-01-18 10:01:37 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][110/312]	eta 0:01:39 lr 0.000262	time 0.4639 (0.4928)	model_time 0.4637 (0.4786)	loss 3.0317 (2.7701)	grad_norm 2.0414 (2.7846/1.4256)	mem 16099MB
[2025-01-18 10:01:41 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][120/312]	eta 0:01:34 lr 0.000262	time 0.4698 (0.4898)	model_time 0.4696 (0.4767)	loss 2.2448 (2.7889)	grad_norm 1.3934 (2.7458/1.4112)	mem 16099MB
[2025-01-18 10:01:46 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][130/312]	eta 0:01:28 lr 0.000261	time 0.4430 (0.4879)	model_time 0.4428 (0.4759)	loss 2.7143 (2.7944)	grad_norm 2.2594 (2.7806/1.4091)	mem 16099MB
[2025-01-18 10:01:51 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][140/312]	eta 0:01:23 lr 0.000261	time 0.5341 (0.4872)	model_time 0.5339 (0.4760)	loss 2.1511 (2.7740)	grad_norm 2.4264 (2.7459/1.3913)	mem 16099MB
[2025-01-18 10:01:55 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][150/312]	eta 0:01:18 lr 0.000261	time 0.4592 (0.4851)	model_time 0.4590 (0.4746)	loss 2.3780 (2.7698)	grad_norm 3.2992 (2.7392/1.3647)	mem 16099MB
[2025-01-18 10:02:00 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][160/312]	eta 0:01:13 lr 0.000260	time 0.4880 (0.4834)	model_time 0.4875 (0.4736)	loss 1.9656 (2.7529)	grad_norm 1.7993 (2.7333/1.3590)	mem 16099MB
[2025-01-18 10:02:04 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][170/312]	eta 0:01:08 lr 0.000260	time 0.4557 (0.4815)	model_time 0.4556 (0.4722)	loss 3.3495 (2.7612)	grad_norm 3.2537 (2.7876/1.3800)	mem 16099MB
[2025-01-18 10:02:09 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][180/312]	eta 0:01:03 lr 0.000260	time 0.4524 (0.4801)	model_time 0.4521 (0.4713)	loss 3.3467 (2.7718)	grad_norm 5.3118 (2.8189/1.3770)	mem 16099MB
[2025-01-18 10:02:14 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][190/312]	eta 0:00:58 lr 0.000260	time 0.4478 (0.4795)	model_time 0.4476 (0.4711)	loss 2.7003 (2.7714)	grad_norm 3.4714 (2.9448/1.5304)	mem 16099MB
[2025-01-18 10:02:18 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][200/312]	eta 0:00:53 lr 0.000259	time 0.4595 (0.4787)	model_time 0.4593 (0.4707)	loss 2.3830 (2.7804)	grad_norm 1.7842 (2.9735/1.5196)	mem 16099MB
[2025-01-18 10:02:23 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][210/312]	eta 0:00:48 lr 0.000259	time 0.4538 (0.4784)	model_time 0.4536 (0.4708)	loss 3.1962 (2.7907)	grad_norm 2.3257 (2.9609/1.4953)	mem 16099MB
[2025-01-18 10:02:28 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][220/312]	eta 0:00:43 lr 0.000259	time 0.4466 (0.4778)	model_time 0.4461 (0.4705)	loss 3.0428 (2.7868)	grad_norm 6.0591 (2.9926/1.5133)	mem 16099MB
[2025-01-18 10:02:32 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][230/312]	eta 0:00:39 lr 0.000258	time 0.4444 (0.4773)	model_time 0.4442 (0.4703)	loss 2.8480 (2.7850)	grad_norm 2.0461 (2.9947/1.4943)	mem 16099MB
[2025-01-18 10:02:37 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][240/312]	eta 0:00:34 lr 0.000258	time 0.4577 (0.4771)	model_time 0.4576 (0.4704)	loss 2.9266 (2.7842)	grad_norm 2.6434 (2.9855/1.4721)	mem 16099MB
[2025-01-18 10:02:42 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][250/312]	eta 0:00:29 lr 0.000258	time 0.5890 (0.4770)	model_time 0.5888 (0.4705)	loss 2.0384 (2.7800)	grad_norm 5.5584 (2.9787/1.4619)	mem 16099MB
[2025-01-18 10:02:46 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][260/312]	eta 0:00:24 lr 0.000257	time 0.4766 (0.4765)	model_time 0.4765 (0.4703)	loss 3.0344 (2.7775)	grad_norm 1.5333 (2.9626/1.4415)	mem 16099MB
[2025-01-18 10:02:51 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][270/312]	eta 0:00:19 lr 0.000257	time 0.4475 (0.4761)	model_time 0.4473 (0.4701)	loss 2.8328 (2.7829)	grad_norm 1.3470 (2.9735/1.4367)	mem 16099MB
[2025-01-18 10:02:56 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][280/312]	eta 0:00:15 lr 0.000257	time 0.4430 (0.4766)	model_time 0.4428 (0.4707)	loss 3.0827 (2.7772)	grad_norm 1.5262 (2.9519/1.4225)	mem 16099MB
[2025-01-18 10:03:01 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][290/312]	eta 0:00:10 lr 0.000256	time 0.4554 (0.4764)	model_time 0.4552 (0.4707)	loss 1.6681 (2.7695)	grad_norm 3.1305 (2.9340/1.4046)	mem 16099MB
[2025-01-18 10:03:05 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][300/312]	eta 0:00:05 lr 0.000256	time 0.4414 (0.4756)	model_time 0.4413 (0.4701)	loss 2.5343 (2.7665)	grad_norm 5.2052 (2.9418/1.4066)	mem 16099MB
[2025-01-18 10:03:10 internimage_t_1k_224] (main.py 510): INFO Train: [254/300][310/312]	eta 0:00:00 lr 0.000256	time 0.5273 (0.4754)	model_time 0.5272 (0.4701)	loss 2.2142 (2.7595)	grad_norm 1.6552 (2.9739/1.4015)	mem 16099MB
[2025-01-18 10:03:10 internimage_t_1k_224] (main.py 519): INFO EPOCH 254 training takes 0:02:28
[2025-01-18 10:03:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_254.pth saving......
[2025-01-18 10:03:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_254.pth saved !!!
[2025-01-18 10:03:19 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.545 (7.545)	Loss 0.7082 (0.7082)	Acc@1 84.888 (84.888)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 10:03:23 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.035)	Loss 0.9618 (0.8181)	Acc@1 78.369 (82.830)	Acc@5 95.190 (96.262)	Mem 16099MB
[2025-01-18 10:03:23 internimage_t_1k_224] (main.py 575): INFO [Epoch:254] * Acc@1 82.680 Acc@5 96.265
[2025-01-18 10:03:23 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.7%
[2025-01-18 10:03:23 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.71%
[2025-01-18 10:03:32 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.395 (8.395)	Loss 0.7315 (0.7315)	Acc@1 85.718 (85.718)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:03:35 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.114)	Loss 0.9670 (0.8355)	Acc@1 79.541 (83.418)	Acc@5 95.630 (96.502)	Mem 16099MB
[2025-01-18 10:03:36 internimage_t_1k_224] (main.py 575): INFO [Epoch:254] * Acc@1 83.295 Acc@5 96.525
[2025-01-18 10:03:36 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 10:03:36 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:03:37 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:03:37 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.30%
[2025-01-18 10:03:39 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][0/312]	eta 0:11:38 lr 0.000256	time 2.2401 (2.2401)	model_time 0.4841 (0.4841)	loss 3.3358 (3.3358)	grad_norm 5.6700 (5.6700/0.0000)	mem 16099MB
[2025-01-18 10:03:44 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][10/312]	eta 0:03:08 lr 0.000256	time 0.4491 (0.6258)	model_time 0.4489 (0.4658)	loss 3.4389 (2.8961)	grad_norm 2.0312 (3.9033/1.5269)	mem 16099MB
[2025-01-18 10:03:48 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][20/312]	eta 0:02:39 lr 0.000255	time 0.4546 (0.5451)	model_time 0.4545 (0.4611)	loss 3.0987 (2.7741)	grad_norm 2.4800 (3.6662/1.4086)	mem 16099MB
[2025-01-18 10:03:53 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][30/312]	eta 0:02:25 lr 0.000255	time 0.4695 (0.5168)	model_time 0.4693 (0.4598)	loss 2.5318 (2.7285)	grad_norm 4.3865 (3.6860/1.4037)	mem 16099MB
[2025-01-18 10:03:57 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][40/312]	eta 0:02:17 lr 0.000255	time 0.4435 (0.5038)	model_time 0.4433 (0.4606)	loss 2.9034 (2.7173)	grad_norm 1.4937 (3.3288/1.4245)	mem 16099MB
[2025-01-18 10:04:02 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][50/312]	eta 0:02:09 lr 0.000254	time 0.5347 (0.4959)	model_time 0.5345 (0.4611)	loss 2.9949 (2.7021)	grad_norm 2.4938 (3.0966/1.3956)	mem 16099MB
[2025-01-18 10:04:07 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][60/312]	eta 0:02:03 lr 0.000254	time 0.5419 (0.4901)	model_time 0.5416 (0.4609)	loss 3.0173 (2.7168)	grad_norm 1.8171 (2.9692/1.3329)	mem 16099MB
[2025-01-18 10:04:11 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][70/312]	eta 0:01:57 lr 0.000254	time 0.4608 (0.4865)	model_time 0.4604 (0.4613)	loss 2.5858 (2.7367)	grad_norm 2.0102 (2.9310/1.2675)	mem 16099MB
[2025-01-18 10:04:16 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][80/312]	eta 0:01:53 lr 0.000253	time 0.4992 (0.4876)	model_time 0.4990 (0.4655)	loss 2.0898 (2.7129)	grad_norm 2.6273 (2.8072/1.2438)	mem 16099MB
[2025-01-18 10:04:21 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][90/312]	eta 0:01:47 lr 0.000253	time 0.4511 (0.4841)	model_time 0.4508 (0.4644)	loss 3.1446 (2.7226)	grad_norm 2.0329 (2.7401/1.2185)	mem 16099MB
[2025-01-18 10:04:26 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][100/312]	eta 0:01:42 lr 0.000253	time 0.4464 (0.4835)	model_time 0.4458 (0.4657)	loss 2.8426 (2.7076)	grad_norm 1.9597 (2.7570/1.2370)	mem 16099MB
[2025-01-18 10:04:30 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][110/312]	eta 0:01:37 lr 0.000253	time 0.4378 (0.4807)	model_time 0.4376 (0.4645)	loss 2.5124 (2.7023)	grad_norm 4.0589 (2.7652/1.2180)	mem 16099MB
[2025-01-18 10:04:35 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][120/312]	eta 0:01:31 lr 0.000252	time 0.4510 (0.4784)	model_time 0.4509 (0.4635)	loss 3.0582 (2.6925)	grad_norm 1.6307 (2.8105/1.2420)	mem 16099MB
[2025-01-18 10:04:39 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][130/312]	eta 0:01:26 lr 0.000252	time 0.4490 (0.4777)	model_time 0.4489 (0.4639)	loss 3.1491 (2.7051)	grad_norm 1.4606 (2.8071/1.2537)	mem 16099MB
[2025-01-18 10:04:44 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][140/312]	eta 0:01:21 lr 0.000252	time 0.4694 (0.4765)	model_time 0.4693 (0.4637)	loss 2.8396 (2.6915)	grad_norm 4.6679 (2.8256/1.2699)	mem 16099MB
[2025-01-18 10:04:49 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][150/312]	eta 0:01:17 lr 0.000251	time 0.4547 (0.4762)	model_time 0.4545 (0.4642)	loss 2.9892 (2.6938)	grad_norm 4.6614 (2.8674/1.2697)	mem 16099MB
[2025-01-18 10:04:54 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][160/312]	eta 0:01:12 lr 0.000251	time 0.5705 (0.4775)	model_time 0.5703 (0.4662)	loss 2.0001 (2.6880)	grad_norm 1.6996 (2.9039/1.2875)	mem 16099MB
[2025-01-18 10:04:58 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][170/312]	eta 0:01:07 lr 0.000251	time 0.4510 (0.4772)	model_time 0.4505 (0.4666)	loss 2.3809 (2.6844)	grad_norm 2.6933 (2.8849/1.2635)	mem 16099MB
[2025-01-18 10:05:03 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][180/312]	eta 0:01:02 lr 0.000250	time 0.4666 (0.4762)	model_time 0.4662 (0.4661)	loss 2.8587 (2.7019)	grad_norm 2.0908 (2.8541/1.2641)	mem 16099MB
[2025-01-18 10:05:07 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][190/312]	eta 0:00:57 lr 0.000250	time 0.4559 (0.4749)	model_time 0.4557 (0.4653)	loss 2.7658 (2.7039)	grad_norm 3.7994 (2.8348/1.2421)	mem 16099MB
[2025-01-18 10:05:12 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][200/312]	eta 0:00:53 lr 0.000250	time 0.4483 (0.4743)	model_time 0.4481 (0.4651)	loss 2.6932 (2.7066)	grad_norm 1.7246 (2.8185/1.2313)	mem 16099MB
[2025-01-18 10:05:17 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][210/312]	eta 0:00:48 lr 0.000250	time 0.4500 (0.4732)	model_time 0.4495 (0.4645)	loss 1.8832 (2.6933)	grad_norm 4.9909 (2.8666/1.2320)	mem 16099MB
[2025-01-18 10:05:21 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][220/312]	eta 0:00:43 lr 0.000249	time 0.4408 (0.4723)	model_time 0.4406 (0.4640)	loss 2.6981 (2.6927)	grad_norm 1.7254 (2.8461/1.2229)	mem 16099MB
[2025-01-18 10:05:26 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][230/312]	eta 0:00:38 lr 0.000249	time 0.4511 (0.4722)	model_time 0.4509 (0.4642)	loss 3.3744 (2.6938)	grad_norm 1.4339 (2.8431/1.2288)	mem 16099MB
[2025-01-18 10:05:30 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][240/312]	eta 0:00:33 lr 0.000249	time 0.4589 (0.4719)	model_time 0.4587 (0.4642)	loss 2.4064 (2.6977)	grad_norm 2.7687 (2.8670/1.2279)	mem 16099MB
[2025-01-18 10:05:35 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][250/312]	eta 0:00:29 lr 0.000248	time 0.4453 (0.4710)	model_time 0.4450 (0.4637)	loss 2.6730 (2.7139)	grad_norm 4.5516 (2.8670/1.2123)	mem 16099MB
[2025-01-18 10:05:40 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][260/312]	eta 0:00:24 lr 0.000248	time 0.4507 (0.4708)	model_time 0.4505 (0.4637)	loss 2.8518 (2.7102)	grad_norm 1.4748 (2.8463/1.2000)	mem 16099MB
[2025-01-18 10:05:44 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][270/312]	eta 0:00:19 lr 0.000248	time 0.4556 (0.4707)	model_time 0.4553 (0.4638)	loss 3.0086 (2.7091)	grad_norm 3.5069 (2.8493/1.2021)	mem 16099MB
[2025-01-18 10:05:49 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][280/312]	eta 0:00:15 lr 0.000247	time 0.4536 (0.4709)	model_time 0.4534 (0.4642)	loss 2.4562 (2.7048)	grad_norm 1.0850 (2.8575/1.2085)	mem 16099MB
[2025-01-18 10:05:54 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][290/312]	eta 0:00:10 lr 0.000247	time 0.4523 (0.4706)	model_time 0.4521 (0.4642)	loss 2.8503 (2.7093)	grad_norm 4.0514 (2.8892/1.2518)	mem 16099MB
[2025-01-18 10:05:58 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][300/312]	eta 0:00:05 lr 0.000247	time 0.4454 (0.4702)	model_time 0.4453 (0.4640)	loss 2.2505 (2.7125)	grad_norm 3.4314 (2.9005/1.2577)	mem 16099MB
[2025-01-18 10:06:03 internimage_t_1k_224] (main.py 510): INFO Train: [255/300][310/312]	eta 0:00:00 lr 0.000247	time 0.4389 (0.4696)	model_time 0.4387 (0.4636)	loss 3.0535 (2.7114)	grad_norm 1.8129 (2.8650/1.2287)	mem 16099MB
[2025-01-18 10:06:03 internimage_t_1k_224] (main.py 519): INFO EPOCH 255 training takes 0:02:26
[2025-01-18 10:06:03 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_255.pth saving......
[2025-01-18 10:06:05 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_255.pth saved !!!
[2025-01-18 10:06:12 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.510 (7.510)	Loss 0.7127 (0.7127)	Acc@1 85.522 (85.522)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 10:06:15 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.973)	Loss 0.9629 (0.8234)	Acc@1 78.931 (82.824)	Acc@5 94.897 (96.238)	Mem 16099MB
[2025-01-18 10:06:16 internimage_t_1k_224] (main.py 575): INFO [Epoch:255] * Acc@1 82.672 Acc@5 96.235
[2025-01-18 10:06:16 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.7%
[2025-01-18 10:06:16 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.71%
[2025-01-18 10:06:24 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.232 (8.232)	Loss 0.7306 (0.7306)	Acc@1 85.718 (85.718)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:06:28 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.099)	Loss 0.9658 (0.8345)	Acc@1 79.663 (83.436)	Acc@5 95.581 (96.511)	Mem 16099MB
[2025-01-18 10:06:28 internimage_t_1k_224] (main.py 575): INFO [Epoch:255] * Acc@1 83.313 Acc@5 96.531
[2025-01-18 10:06:28 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 10:06:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:06:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:06:29 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.31%
[2025-01-18 10:06:31 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][0/312]	eta 0:11:13 lr 0.000246	time 2.1594 (2.1594)	model_time 0.4775 (0.4775)	loss 2.6480 (2.6480)	grad_norm 1.9062 (1.9062/0.0000)	mem 16099MB
[2025-01-18 10:06:36 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][10/312]	eta 0:03:13 lr 0.000246	time 0.4444 (0.6399)	model_time 0.4443 (0.4867)	loss 3.0742 (2.6885)	grad_norm 1.8102 (2.5153/1.1416)	mem 16099MB
[2025-01-18 10:06:40 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][20/312]	eta 0:02:40 lr 0.000246	time 0.4529 (0.5510)	model_time 0.4524 (0.4705)	loss 2.5121 (2.6872)	grad_norm 3.4524 (2.8770/1.3151)	mem 16099MB
[2025-01-18 10:06:45 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][30/312]	eta 0:02:27 lr 0.000246	time 0.4385 (0.5231)	model_time 0.4383 (0.4685)	loss 2.7670 (2.7338)	grad_norm 2.4994 (2.7747/1.1796)	mem 16099MB
[2025-01-18 10:06:50 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][40/312]	eta 0:02:17 lr 0.000245	time 0.4544 (0.5072)	model_time 0.4542 (0.4658)	loss 1.9135 (2.6863)	grad_norm 2.3892 (2.7251/1.1175)	mem 16099MB
[2025-01-18 10:06:54 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][50/312]	eta 0:02:10 lr 0.000245	time 0.4564 (0.4989)	model_time 0.4562 (0.4656)	loss 1.4494 (2.6839)	grad_norm 7.1008 (2.8058/1.2316)	mem 16099MB
[2025-01-18 10:06:59 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][60/312]	eta 0:02:03 lr 0.000245	time 0.4572 (0.4917)	model_time 0.4570 (0.4637)	loss 2.9994 (2.7068)	grad_norm 4.0667 (2.9908/1.5341)	mem 16099MB
[2025-01-18 10:07:03 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][70/312]	eta 0:01:57 lr 0.000244	time 0.4766 (0.4866)	model_time 0.4764 (0.4626)	loss 2.7343 (2.7201)	grad_norm 2.1783 (3.0347/1.4877)	mem 16099MB
[2025-01-18 10:07:08 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][80/312]	eta 0:01:52 lr 0.000244	time 0.4400 (0.4844)	model_time 0.4397 (0.4633)	loss 3.2410 (2.7481)	grad_norm 1.9724 (2.9762/1.4910)	mem 16099MB
[2025-01-18 10:07:13 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][90/312]	eta 0:01:46 lr 0.000244	time 0.4545 (0.4814)	model_time 0.4541 (0.4625)	loss 2.7767 (2.7441)	grad_norm 2.6198 (2.9904/1.4891)	mem 16099MB
[2025-01-18 10:07:17 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][100/312]	eta 0:01:41 lr 0.000244	time 0.4493 (0.4796)	model_time 0.4488 (0.4626)	loss 2.5518 (2.7672)	grad_norm 3.7957 (2.9688/1.4589)	mem 16099MB
[2025-01-18 10:07:22 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][110/312]	eta 0:01:36 lr 0.000243	time 0.4463 (0.4772)	model_time 0.4461 (0.4617)	loss 2.9333 (2.7640)	grad_norm 4.2492 (2.9391/1.4167)	mem 16099MB
[2025-01-18 10:07:27 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][120/312]	eta 0:01:31 lr 0.000243	time 0.4492 (0.4766)	model_time 0.4490 (0.4623)	loss 3.0526 (2.7632)	grad_norm 1.4799 (2.8704/1.3959)	mem 16099MB
[2025-01-18 10:07:31 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][130/312]	eta 0:01:26 lr 0.000243	time 0.4550 (0.4757)	model_time 0.4547 (0.4624)	loss 2.7293 (2.7663)	grad_norm 2.6227 (2.8463/1.3604)	mem 16099MB
[2025-01-18 10:07:36 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][140/312]	eta 0:01:21 lr 0.000242	time 0.4522 (0.4758)	model_time 0.4520 (0.4635)	loss 2.9462 (2.7618)	grad_norm 2.7360 (2.8183/1.3362)	mem 16099MB
[2025-01-18 10:07:41 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][150/312]	eta 0:01:17 lr 0.000242	time 0.5430 (0.4769)	model_time 0.5428 (0.4654)	loss 2.9802 (2.7711)	grad_norm 1.6608 (2.8189/1.3292)	mem 16099MB
[2025-01-18 10:07:46 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][160/312]	eta 0:01:12 lr 0.000242	time 0.4557 (0.4763)	model_time 0.4556 (0.4655)	loss 2.1933 (2.7574)	grad_norm 3.4874 (2.8623/1.3339)	mem 16099MB
[2025-01-18 10:07:50 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][170/312]	eta 0:01:07 lr 0.000241	time 0.4766 (0.4760)	model_time 0.4765 (0.4658)	loss 3.3194 (2.7530)	grad_norm 4.8018 (2.8897/1.3281)	mem 16099MB
[2025-01-18 10:07:55 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][180/312]	eta 0:01:02 lr 0.000241	time 0.4394 (0.4757)	model_time 0.4391 (0.4660)	loss 3.3325 (2.7570)	grad_norm 1.8690 (2.8975/1.3509)	mem 16099MB
[2025-01-18 10:08:00 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][190/312]	eta 0:00:57 lr 0.000241	time 0.5453 (0.4751)	model_time 0.5451 (0.4659)	loss 2.8678 (2.7435)	grad_norm 3.4726 (2.9248/1.3554)	mem 16099MB
[2025-01-18 10:08:04 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][200/312]	eta 0:00:53 lr 0.000241	time 0.4526 (0.4746)	model_time 0.4524 (0.4659)	loss 3.1683 (2.7444)	grad_norm 5.1851 (2.9990/1.4228)	mem 16099MB
[2025-01-18 10:08:09 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][210/312]	eta 0:00:48 lr 0.000240	time 0.4554 (0.4736)	model_time 0.4549 (0.4652)	loss 2.5186 (2.7412)	grad_norm 3.6136 (3.0706/1.4545)	mem 16099MB
[2025-01-18 10:08:13 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][220/312]	eta 0:00:43 lr 0.000240	time 0.4554 (0.4729)	model_time 0.4552 (0.4649)	loss 2.1296 (2.7473)	grad_norm 3.6971 (3.0893/1.4612)	mem 16099MB
[2025-01-18 10:08:18 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][230/312]	eta 0:00:38 lr 0.000240	time 0.5555 (0.4727)	model_time 0.5553 (0.4651)	loss 3.0178 (2.7294)	grad_norm 6.9353 (3.1105/1.4963)	mem 16099MB
[2025-01-18 10:08:23 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][240/312]	eta 0:00:33 lr 0.000239	time 0.4447 (0.4721)	model_time 0.4445 (0.4648)	loss 2.9183 (2.7414)	grad_norm 2.8994 (3.1436/1.5371)	mem 16099MB
[2025-01-18 10:08:27 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][250/312]	eta 0:00:29 lr 0.000239	time 0.4476 (0.4717)	model_time 0.4471 (0.4646)	loss 2.7261 (2.7399)	grad_norm 2.1122 (3.1451/1.5405)	mem 16099MB
[2025-01-18 10:08:32 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][260/312]	eta 0:00:24 lr 0.000239	time 0.4490 (0.4716)	model_time 0.4488 (0.4647)	loss 2.6691 (2.7406)	grad_norm 3.8149 (3.1237/1.5308)	mem 16099MB
[2025-01-18 10:08:36 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][270/312]	eta 0:00:19 lr 0.000239	time 0.4523 (0.4709)	model_time 0.4521 (0.4643)	loss 2.7743 (2.7364)	grad_norm 5.2569 (3.1298/1.5303)	mem 16099MB
[2025-01-18 10:08:41 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][280/312]	eta 0:00:15 lr 0.000238	time 0.4689 (0.4703)	model_time 0.4688 (0.4640)	loss 1.9455 (2.7314)	grad_norm 3.1650 (3.1504/1.5262)	mem 16099MB
[2025-01-18 10:08:46 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][290/312]	eta 0:00:10 lr 0.000238	time 0.4576 (0.4706)	model_time 0.4574 (0.4644)	loss 2.6358 (2.7378)	grad_norm 3.0187 (3.1733/1.5447)	mem 16099MB
[2025-01-18 10:08:50 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][300/312]	eta 0:00:05 lr 0.000238	time 0.4434 (0.4702)	model_time 0.4433 (0.4642)	loss 2.9723 (2.7292)	grad_norm 3.2778 (3.1808/1.5357)	mem 16099MB
[2025-01-18 10:08:55 internimage_t_1k_224] (main.py 510): INFO Train: [256/300][310/312]	eta 0:00:00 lr 0.000237	time 0.5567 (0.4706)	model_time 0.5566 (0.4648)	loss 2.4475 (2.7173)	grad_norm 4.2894 (3.2062/1.5290)	mem 16099MB
[2025-01-18 10:08:56 internimage_t_1k_224] (main.py 519): INFO EPOCH 256 training takes 0:02:26
[2025-01-18 10:08:56 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_256.pth saving......
[2025-01-18 10:08:57 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_256.pth saved !!!
[2025-01-18 10:09:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.621 (7.621)	Loss 0.7244 (0.7244)	Acc@1 85.181 (85.181)	Acc@5 97.412 (97.412)	Mem 16099MB
[2025-01-18 10:09:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.014)	Loss 0.9636 (0.8273)	Acc@1 78.931 (82.884)	Acc@5 95.337 (96.280)	Mem 16099MB
[2025-01-18 10:09:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:256] * Acc@1 82.736 Acc@5 96.285
[2025-01-18 10:09:08 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.7%
[2025-01-18 10:09:08 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 10:09:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 10:09:09 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.74%
[2025-01-18 10:09:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.491 (7.491)	Loss 0.7299 (0.7299)	Acc@1 85.742 (85.742)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:09:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.002)	Loss 0.9647 (0.8335)	Acc@1 79.663 (83.452)	Acc@5 95.557 (96.504)	Mem 16099MB
[2025-01-18 10:09:20 internimage_t_1k_224] (main.py 575): INFO [Epoch:256] * Acc@1 83.333 Acc@5 96.527
[2025-01-18 10:09:20 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 10:09:20 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:09:22 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:09:22 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.33%
[2025-01-18 10:09:24 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][0/312]	eta 0:11:45 lr 0.000237	time 2.2619 (2.2619)	model_time 0.8516 (0.8516)	loss 3.1308 (3.1308)	grad_norm 1.3014 (1.3014/0.0000)	mem 16099MB
[2025-01-18 10:09:29 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][10/312]	eta 0:03:15 lr 0.000237	time 0.5648 (0.6472)	model_time 0.5643 (0.5186)	loss 2.3234 (2.6235)	grad_norm 4.4439 (2.8254/1.2789)	mem 16099MB
[2025-01-18 10:09:34 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][20/312]	eta 0:02:44 lr 0.000237	time 0.5368 (0.5635)	model_time 0.5366 (0.4960)	loss 3.0833 (2.7046)	grad_norm 3.1622 (2.9798/1.2368)	mem 16099MB
[2025-01-18 10:09:38 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][30/312]	eta 0:02:30 lr 0.000237	time 0.4521 (0.5326)	model_time 0.4519 (0.4868)	loss 3.1814 (2.7460)	grad_norm 1.8530 (2.9071/1.2125)	mem 16099MB
[2025-01-18 10:09:43 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][40/312]	eta 0:02:20 lr 0.000236	time 0.4502 (0.5154)	model_time 0.4500 (0.4807)	loss 2.6754 (2.7497)	grad_norm 5.1130 (3.0148/1.3588)	mem 16099MB
[2025-01-18 10:09:48 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][50/312]	eta 0:02:13 lr 0.000236	time 0.4527 (0.5079)	model_time 0.4525 (0.4799)	loss 2.8233 (2.7623)	grad_norm 2.4292 (3.1340/1.3978)	mem 16099MB
[2025-01-18 10:09:52 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][60/312]	eta 0:02:06 lr 0.000236	time 0.4477 (0.5022)	model_time 0.4475 (0.4787)	loss 2.9319 (2.7530)	grad_norm 1.5842 (3.0592/1.3457)	mem 16099MB
[2025-01-18 10:09:57 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][70/312]	eta 0:01:59 lr 0.000235	time 0.4577 (0.4952)	model_time 0.4575 (0.4750)	loss 3.0221 (2.7646)	grad_norm 4.7012 (3.1778/1.3617)	mem 16099MB
[2025-01-18 10:10:02 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][80/312]	eta 0:01:54 lr 0.000235	time 0.4636 (0.4914)	model_time 0.4632 (0.4737)	loss 2.5431 (2.7809)	grad_norm 1.0936 (3.1659/1.3228)	mem 16099MB
[2025-01-18 10:10:06 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][90/312]	eta 0:01:48 lr 0.000235	time 0.4485 (0.4881)	model_time 0.4483 (0.4723)	loss 3.2208 (2.7616)	grad_norm 1.8414 (3.0664/1.2979)	mem 16099MB
[2025-01-18 10:10:11 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][100/312]	eta 0:01:42 lr 0.000234	time 0.4568 (0.4850)	model_time 0.4566 (0.4707)	loss 3.1878 (2.7615)	grad_norm 2.3449 (2.9856/1.2898)	mem 16099MB
[2025-01-18 10:10:15 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][110/312]	eta 0:01:37 lr 0.000234	time 0.4541 (0.4822)	model_time 0.4539 (0.4692)	loss 3.0570 (2.7542)	grad_norm 1.6049 (2.9976/1.3274)	mem 16099MB
[2025-01-18 10:10:20 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][120/312]	eta 0:01:32 lr 0.000234	time 0.4553 (0.4815)	model_time 0.4551 (0.4695)	loss 2.6852 (2.7733)	grad_norm 4.4911 (2.9678/1.3127)	mem 16099MB
[2025-01-18 10:10:25 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][130/312]	eta 0:01:27 lr 0.000234	time 0.4552 (0.4803)	model_time 0.4547 (0.4692)	loss 2.5344 (2.7658)	grad_norm 1.1049 (2.9000/1.2952)	mem 16099MB
[2025-01-18 10:10:29 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][140/312]	eta 0:01:22 lr 0.000233	time 0.4475 (0.4791)	model_time 0.4470 (0.4687)	loss 3.0998 (2.7704)	grad_norm 2.3042 (2.8587/1.2653)	mem 16099MB
[2025-01-18 10:10:34 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][150/312]	eta 0:01:17 lr 0.000233	time 0.4774 (0.4775)	model_time 0.4773 (0.4678)	loss 2.6388 (2.7846)	grad_norm 2.4753 (2.8362/1.2488)	mem 16099MB
[2025-01-18 10:10:39 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][160/312]	eta 0:01:12 lr 0.000233	time 0.4327 (0.4767)	model_time 0.4324 (0.4676)	loss 3.1674 (2.7806)	grad_norm 2.8206 (2.8328/1.2272)	mem 16099MB
[2025-01-18 10:10:43 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][170/312]	eta 0:01:07 lr 0.000232	time 0.4512 (0.4767)	model_time 0.4507 (0.4681)	loss 2.5933 (2.7711)	grad_norm 2.5047 (2.8477/1.2196)	mem 16099MB
[2025-01-18 10:10:48 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][180/312]	eta 0:01:02 lr 0.000232	time 0.4432 (0.4767)	model_time 0.4427 (0.4685)	loss 2.5116 (2.7576)	grad_norm 3.1123 (2.8410/1.2106)	mem 16099MB
[2025-01-18 10:10:53 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][190/312]	eta 0:00:58 lr 0.000232	time 0.4715 (0.4763)	model_time 0.4714 (0.4685)	loss 3.1048 (2.7523)	grad_norm 4.6188 (2.8546/1.2118)	mem 16099MB
[2025-01-18 10:10:57 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][200/312]	eta 0:00:53 lr 0.000232	time 0.4499 (0.4757)	model_time 0.4494 (0.4683)	loss 2.4182 (2.7522)	grad_norm 2.2414 (2.8295/1.1974)	mem 16099MB
[2025-01-18 10:11:02 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][210/312]	eta 0:00:48 lr 0.000231	time 0.4434 (0.4755)	model_time 0.4430 (0.4684)	loss 2.7138 (2.7600)	grad_norm 1.1350 (2.8135/1.1848)	mem 16099MB
[2025-01-18 10:11:07 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][220/312]	eta 0:00:43 lr 0.000231	time 0.4544 (0.4745)	model_time 0.4542 (0.4678)	loss 2.5141 (2.7550)	grad_norm 2.3698 (2.7696/1.1762)	mem 16099MB
[2025-01-18 10:11:11 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][230/312]	eta 0:00:38 lr 0.000231	time 0.4501 (0.4738)	model_time 0.4499 (0.4673)	loss 1.6809 (2.7585)	grad_norm 1.8377 (2.7497/1.1656)	mem 16099MB
[2025-01-18 10:11:16 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][240/312]	eta 0:00:34 lr 0.000230	time 0.4451 (0.4732)	model_time 0.4446 (0.4670)	loss 2.6824 (2.7561)	grad_norm 4.3484 (2.7410/1.1591)	mem 16099MB
[2025-01-18 10:11:20 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][250/312]	eta 0:00:29 lr 0.000230	time 0.4481 (0.4728)	model_time 0.4476 (0.4668)	loss 2.8107 (2.7535)	grad_norm 2.3897 (2.7327/1.1424)	mem 16099MB
[2025-01-18 10:11:25 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][260/312]	eta 0:00:24 lr 0.000230	time 0.4502 (0.4721)	model_time 0.4501 (0.4663)	loss 3.0059 (2.7522)	grad_norm 2.7981 (2.7069/1.1326)	mem 16099MB
[2025-01-18 10:11:30 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][270/312]	eta 0:00:19 lr 0.000230	time 0.4472 (0.4714)	model_time 0.4470 (0.4658)	loss 2.9853 (2.7494)	grad_norm 2.9340 (2.7122/1.1366)	mem 16099MB
[2025-01-18 10:11:34 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][280/312]	eta 0:00:15 lr 0.000229	time 0.4642 (0.4708)	model_time 0.4640 (0.4654)	loss 2.6649 (2.7478)	grad_norm 2.1202 (2.7036/1.1367)	mem 16099MB
[2025-01-18 10:11:39 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][290/312]	eta 0:00:10 lr 0.000229	time 0.4414 (0.4711)	model_time 0.4413 (0.4658)	loss 2.5086 (2.7497)	grad_norm 1.7009 (2.6808/1.1283)	mem 16099MB
[2025-01-18 10:11:43 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][300/312]	eta 0:00:05 lr 0.000229	time 0.4394 (0.4708)	model_time 0.4393 (0.4657)	loss 2.1975 (2.7397)	grad_norm 1.8841 (2.7177/1.1616)	mem 16099MB
[2025-01-18 10:11:48 internimage_t_1k_224] (main.py 510): INFO Train: [257/300][310/312]	eta 0:00:00 lr 0.000228	time 0.4386 (0.4700)	model_time 0.4385 (0.4651)	loss 1.9156 (2.7372)	grad_norm 4.5304 (2.7425/1.2302)	mem 16099MB
[2025-01-18 10:11:48 internimage_t_1k_224] (main.py 519): INFO EPOCH 257 training takes 0:02:26
[2025-01-18 10:11:48 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_257.pth saving......
[2025-01-18 10:11:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_257.pth saved !!!
[2025-01-18 10:11:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.025 (8.025)	Loss 0.7210 (0.7210)	Acc@1 85.205 (85.205)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:12:01 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.080)	Loss 0.9734 (0.8276)	Acc@1 78.687 (82.808)	Acc@5 95.093 (96.236)	Mem 16099MB
[2025-01-18 10:12:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:257] * Acc@1 82.650 Acc@5 96.257
[2025-01-18 10:12:02 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.6%
[2025-01-18 10:12:02 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.74%
[2025-01-18 10:12:11 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.907 (8.907)	Loss 0.7292 (0.7292)	Acc@1 85.718 (85.718)	Acc@5 97.754 (97.754)	Mem 16099MB
[2025-01-18 10:12:15 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.185)	Loss 0.9636 (0.8326)	Acc@1 79.639 (83.452)	Acc@5 95.581 (96.513)	Mem 16099MB
[2025-01-18 10:12:15 internimage_t_1k_224] (main.py 575): INFO [Epoch:257] * Acc@1 83.331 Acc@5 96.533
[2025-01-18 10:12:15 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 10:12:15 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.33%
[2025-01-18 10:12:18 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][0/312]	eta 0:16:23 lr 0.000228	time 3.1514 (3.1514)	model_time 1.0881 (1.0881)	loss 3.0816 (3.0816)	grad_norm 3.2238 (3.2238/0.0000)	mem 16099MB
[2025-01-18 10:12:23 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][10/312]	eta 0:03:36 lr 0.000228	time 0.4543 (0.7155)	model_time 0.4541 (0.5276)	loss 3.2681 (2.6761)	grad_norm 2.7441 (3.7722/1.4683)	mem 16099MB
[2025-01-18 10:12:28 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][20/312]	eta 0:02:57 lr 0.000228	time 0.5420 (0.6065)	model_time 0.5415 (0.5079)	loss 3.1625 (2.7971)	grad_norm 3.5989 (3.3938/1.3624)	mem 16099MB
[2025-01-18 10:12:32 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][30/312]	eta 0:02:38 lr 0.000228	time 0.4514 (0.5635)	model_time 0.4512 (0.4966)	loss 3.1137 (2.8100)	grad_norm 4.4056 (3.0856/1.4341)	mem 16099MB
[2025-01-18 10:12:37 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][40/312]	eta 0:02:28 lr 0.000227	time 0.4815 (0.5446)	model_time 0.4813 (0.4939)	loss 2.9112 (2.7885)	grad_norm 2.5434 (3.1810/1.6943)	mem 16099MB
[2025-01-18 10:12:42 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][50/312]	eta 0:02:19 lr 0.000227	time 0.4538 (0.5308)	model_time 0.4534 (0.4900)	loss 1.7310 (2.7225)	grad_norm 3.4871 (3.2130/1.6245)	mem 16099MB
[2025-01-18 10:12:47 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][60/312]	eta 0:02:11 lr 0.000227	time 0.4570 (0.5213)	model_time 0.4565 (0.4871)	loss 2.4456 (2.7242)	grad_norm 1.9909 (3.2667/1.5295)	mem 16099MB
[2025-01-18 10:12:51 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][70/312]	eta 0:02:03 lr 0.000226	time 0.4526 (0.5119)	model_time 0.4524 (0.4825)	loss 3.1046 (2.7445)	grad_norm 4.8581 (3.3145/1.4882)	mem 16099MB
[2025-01-18 10:12:56 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][80/312]	eta 0:01:57 lr 0.000226	time 0.4654 (0.5071)	model_time 0.4650 (0.4812)	loss 2.6242 (2.7350)	grad_norm 2.7180 (3.2195/1.4563)	mem 16099MB
[2025-01-18 10:13:00 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][90/312]	eta 0:01:51 lr 0.000226	time 0.4574 (0.5012)	model_time 0.4569 (0.4782)	loss 3.0547 (2.7503)	grad_norm 2.3048 (3.1923/1.4389)	mem 16099MB
[2025-01-18 10:13:05 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][100/312]	eta 0:01:45 lr 0.000226	time 0.4434 (0.4972)	model_time 0.4429 (0.4764)	loss 3.2342 (2.7459)	grad_norm 2.5330 (3.1747/1.4295)	mem 16099MB
[2025-01-18 10:13:10 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][110/312]	eta 0:01:39 lr 0.000225	time 0.4544 (0.4950)	model_time 0.4542 (0.4761)	loss 3.2290 (2.7408)	grad_norm 3.0603 (3.1074/1.3985)	mem 16099MB
[2025-01-18 10:13:14 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][120/312]	eta 0:01:34 lr 0.000225	time 0.4550 (0.4916)	model_time 0.4549 (0.4742)	loss 3.3469 (2.7521)	grad_norm 1.7745 (3.0224/1.3862)	mem 16099MB
[2025-01-18 10:13:19 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][130/312]	eta 0:01:29 lr 0.000225	time 0.4532 (0.4895)	model_time 0.4531 (0.4734)	loss 3.0098 (2.7433)	grad_norm 2.0816 (2.9888/1.3489)	mem 16099MB
[2025-01-18 10:13:23 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][140/312]	eta 0:01:23 lr 0.000225	time 0.4500 (0.4868)	model_time 0.4498 (0.4718)	loss 2.7305 (2.7329)	grad_norm 2.7619 (2.9655/1.3291)	mem 16099MB
[2025-01-18 10:13:28 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][150/312]	eta 0:01:18 lr 0.000224	time 0.4494 (0.4846)	model_time 0.4492 (0.4706)	loss 2.2563 (2.7367)	grad_norm 3.2480 (2.9155/1.3142)	mem 16099MB
[2025-01-18 10:13:33 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][160/312]	eta 0:01:13 lr 0.000224	time 0.4466 (0.4834)	model_time 0.4461 (0.4702)	loss 3.1178 (2.7512)	grad_norm 2.6019 (2.8768/1.2895)	mem 16099MB
[2025-01-18 10:13:37 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][170/312]	eta 0:01:08 lr 0.000224	time 0.4624 (0.4818)	model_time 0.4622 (0.4694)	loss 2.0859 (2.7382)	grad_norm 1.9650 (2.8574/1.2647)	mem 16099MB
[2025-01-18 10:13:42 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][180/312]	eta 0:01:03 lr 0.000223	time 0.4439 (0.4817)	model_time 0.4438 (0.4699)	loss 2.6582 (2.7391)	grad_norm 5.1694 (2.8944/1.2665)	mem 16099MB
[2025-01-18 10:13:47 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][190/312]	eta 0:00:58 lr 0.000223	time 0.4678 (0.4802)	model_time 0.4676 (0.4690)	loss 2.3349 (2.7391)	grad_norm 3.0402 (2.9144/1.2870)	mem 16099MB
[2025-01-18 10:13:51 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][200/312]	eta 0:00:53 lr 0.000223	time 0.4450 (0.4789)	model_time 0.4448 (0.4683)	loss 3.3180 (2.7429)	grad_norm 2.1979 (2.8664/1.2758)	mem 16099MB
[2025-01-18 10:13:56 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][210/312]	eta 0:00:48 lr 0.000223	time 0.4486 (0.4788)	model_time 0.4484 (0.4686)	loss 1.7970 (2.7277)	grad_norm 2.0465 (2.8153/1.2700)	mem 16099MB
[2025-01-18 10:14:00 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][220/312]	eta 0:00:43 lr 0.000222	time 0.4405 (0.4780)	model_time 0.4400 (0.4683)	loss 3.0391 (2.7208)	grad_norm 3.7574 (2.7938/1.2582)	mem 16099MB
[2025-01-18 10:14:05 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][230/312]	eta 0:00:39 lr 0.000222	time 0.4444 (0.4773)	model_time 0.4442 (0.4680)	loss 3.0246 (2.7226)	grad_norm 4.2523 (2.7788/1.2465)	mem 16099MB
[2025-01-18 10:14:10 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][240/312]	eta 0:00:34 lr 0.000222	time 0.4631 (0.4766)	model_time 0.4626 (0.4677)	loss 2.5432 (2.7226)	grad_norm 1.4032 (2.7764/1.2585)	mem 16099MB
[2025-01-18 10:14:14 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][250/312]	eta 0:00:29 lr 0.000221	time 0.4554 (0.4767)	model_time 0.4553 (0.4681)	loss 3.0839 (2.7307)	grad_norm 2.5848 (2.7658/1.2468)	mem 16099MB
[2025-01-18 10:14:19 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][260/312]	eta 0:00:24 lr 0.000221	time 0.4531 (0.4762)	model_time 0.4526 (0.4679)	loss 1.7311 (2.7288)	grad_norm 3.0221 (2.7642/1.2366)	mem 16099MB
[2025-01-18 10:14:24 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][270/312]	eta 0:00:20 lr 0.000221	time 0.4473 (0.4765)	model_time 0.4471 (0.4685)	loss 2.5949 (2.7199)	grad_norm 2.4306 (2.7552/1.2305)	mem 16099MB
[2025-01-18 10:14:28 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][280/312]	eta 0:00:15 lr 0.000221	time 0.4528 (0.4757)	model_time 0.4527 (0.4679)	loss 2.6228 (2.7184)	grad_norm 4.8319 (2.8043/1.2938)	mem 16099MB
[2025-01-18 10:14:33 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][290/312]	eta 0:00:10 lr 0.000220	time 0.5426 (0.4758)	model_time 0.5424 (0.4683)	loss 1.6360 (2.7192)	grad_norm 4.6096 (2.8173/1.3089)	mem 16099MB
[2025-01-18 10:14:38 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][300/312]	eta 0:00:05 lr 0.000220	time 0.4395 (0.4753)	model_time 0.4394 (0.4680)	loss 2.7243 (2.7179)	grad_norm 2.9838 (2.8566/1.3499)	mem 16099MB
[2025-01-18 10:14:42 internimage_t_1k_224] (main.py 510): INFO Train: [258/300][310/312]	eta 0:00:00 lr 0.000220	time 0.4391 (0.4742)	model_time 0.4389 (0.4672)	loss 2.3734 (2.7209)	grad_norm 3.1291 (2.8229/1.3284)	mem 16099MB
[2025-01-18 10:14:43 internimage_t_1k_224] (main.py 519): INFO EPOCH 258 training takes 0:02:27
[2025-01-18 10:14:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_258.pth saving......
[2025-01-18 10:14:44 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_258.pth saved !!!
[2025-01-18 10:14:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.377 (7.377)	Loss 0.7304 (0.7304)	Acc@1 85.498 (85.498)	Acc@5 97.583 (97.583)	Mem 16099MB
[2025-01-18 10:14:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.020)	Loss 0.9910 (0.8430)	Acc@1 78.320 (82.819)	Acc@5 95.166 (96.265)	Mem 16099MB
[2025-01-18 10:14:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:258] * Acc@1 82.684 Acc@5 96.267
[2025-01-18 10:14:55 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.7%
[2025-01-18 10:14:55 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.74%
[2025-01-18 10:15:04 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.589 (8.589)	Loss 0.7281 (0.7281)	Acc@1 85.742 (85.742)	Acc@5 97.778 (97.778)	Mem 16099MB
[2025-01-18 10:15:08 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.140)	Loss 0.9624 (0.8314)	Acc@1 79.590 (83.443)	Acc@5 95.605 (96.524)	Mem 16099MB
[2025-01-18 10:15:08 internimage_t_1k_224] (main.py 575): INFO [Epoch:258] * Acc@1 83.319 Acc@5 96.541
[2025-01-18 10:15:08 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 10:15:08 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.33%
[2025-01-18 10:15:11 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][0/312]	eta 0:16:26 lr 0.000220	time 3.1604 (3.1604)	model_time 1.2216 (1.2216)	loss 2.9300 (2.9300)	grad_norm 3.0850 (3.0850/0.0000)	mem 16099MB
[2025-01-18 10:15:16 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][10/312]	eta 0:03:35 lr 0.000219	time 0.4518 (0.7132)	model_time 0.4517 (0.5364)	loss 2.6111 (2.7775)	grad_norm 1.5467 (3.5900/1.4845)	mem 16099MB
[2025-01-18 10:15:20 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][20/312]	eta 0:02:52 lr 0.000219	time 0.4631 (0.5905)	model_time 0.4627 (0.4978)	loss 3.1151 (2.7957)	grad_norm 2.7762 (3.0603/1.2836)	mem 16099MB
[2025-01-18 10:15:25 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][30/312]	eta 0:02:35 lr 0.000219	time 0.4627 (0.5498)	model_time 0.4625 (0.4868)	loss 3.3566 (2.7945)	grad_norm 2.5207 (2.5778/1.2719)	mem 16099MB
[2025-01-18 10:15:30 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][40/312]	eta 0:02:23 lr 0.000219	time 0.4408 (0.5275)	model_time 0.4406 (0.4798)	loss 2.8487 (2.7874)	grad_norm 2.8769 (2.7294/1.2569)	mem 16099MB
[2025-01-18 10:15:34 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][50/312]	eta 0:02:15 lr 0.000218	time 0.4428 (0.5191)	model_time 0.4426 (0.4806)	loss 2.8355 (2.7682)	grad_norm 3.1807 (2.9822/1.3690)	mem 16099MB
[2025-01-18 10:15:39 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][60/312]	eta 0:02:09 lr 0.000218	time 0.4600 (0.5138)	model_time 0.4595 (0.4816)	loss 2.9159 (2.7815)	grad_norm 2.6384 (2.9755/1.3478)	mem 16099MB
[2025-01-18 10:15:44 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][70/312]	eta 0:02:02 lr 0.000218	time 0.4625 (0.5059)	model_time 0.4624 (0.4782)	loss 2.4282 (2.7345)	grad_norm 2.2445 (2.9156/1.3182)	mem 16099MB
[2025-01-18 10:15:48 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][80/312]	eta 0:01:56 lr 0.000218	time 0.4499 (0.5004)	model_time 0.4494 (0.4761)	loss 2.7116 (2.7647)	grad_norm 4.4125 (2.9883/1.2984)	mem 16099MB
[2025-01-18 10:15:53 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][90/312]	eta 0:01:50 lr 0.000217	time 0.4483 (0.4958)	model_time 0.4479 (0.4741)	loss 2.2079 (2.7624)	grad_norm 2.6871 (3.0721/1.3321)	mem 16099MB
[2025-01-18 10:15:58 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][100/312]	eta 0:01:44 lr 0.000217	time 0.4427 (0.4917)	model_time 0.4426 (0.4721)	loss 3.1359 (2.7720)	grad_norm 1.6761 (3.1329/1.3435)	mem 16099MB
[2025-01-18 10:16:02 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][110/312]	eta 0:01:38 lr 0.000217	time 0.4514 (0.4890)	model_time 0.4512 (0.4711)	loss 3.2232 (2.7823)	grad_norm 3.6356 (3.0856/1.3246)	mem 16099MB
[2025-01-18 10:16:07 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][120/312]	eta 0:01:33 lr 0.000216	time 0.4504 (0.4865)	model_time 0.4500 (0.4700)	loss 2.9094 (2.7797)	grad_norm 3.8521 (3.0902/1.3170)	mem 16099MB
[2025-01-18 10:16:11 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][130/312]	eta 0:01:28 lr 0.000216	time 0.4543 (0.4844)	model_time 0.4538 (0.4692)	loss 1.8667 (2.7792)	grad_norm 2.1317 (3.0624/1.2999)	mem 16099MB
[2025-01-18 10:16:16 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][140/312]	eta 0:01:23 lr 0.000216	time 0.4850 (0.4830)	model_time 0.4848 (0.4688)	loss 2.9792 (2.7833)	grad_norm 3.3021 (3.0838/1.3045)	mem 16099MB
[2025-01-18 10:16:21 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][150/312]	eta 0:01:18 lr 0.000216	time 0.4347 (0.4826)	model_time 0.4343 (0.4693)	loss 3.2434 (2.7959)	grad_norm 1.8357 (3.0643/1.2914)	mem 16099MB
[2025-01-18 10:16:25 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][160/312]	eta 0:01:13 lr 0.000215	time 0.4434 (0.4818)	model_time 0.4432 (0.4694)	loss 3.1903 (2.7984)	grad_norm 4.2148 (3.0614/1.2793)	mem 16099MB
[2025-01-18 10:16:30 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][170/312]	eta 0:01:08 lr 0.000215	time 0.4456 (0.4805)	model_time 0.4455 (0.4688)	loss 2.7982 (2.7992)	grad_norm 1.9212 (3.0263/1.2682)	mem 16099MB
[2025-01-18 10:16:35 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][180/312]	eta 0:01:03 lr 0.000215	time 0.4500 (0.4797)	model_time 0.4495 (0.4686)	loss 2.9866 (2.7997)	grad_norm 1.1688 (2.9668/1.2664)	mem 16099MB
[2025-01-18 10:16:39 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][190/312]	eta 0:00:58 lr 0.000214	time 0.4490 (0.4785)	model_time 0.4485 (0.4679)	loss 3.0356 (2.8014)	grad_norm 5.7393 (3.0723/1.3764)	mem 16099MB
[2025-01-18 10:16:44 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][200/312]	eta 0:00:53 lr 0.000214	time 0.4966 (0.4776)	model_time 0.4965 (0.4675)	loss 2.9192 (2.8019)	grad_norm 2.7877 (3.0719/1.3631)	mem 16099MB
[2025-01-18 10:16:48 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][210/312]	eta 0:00:48 lr 0.000214	time 0.4441 (0.4764)	model_time 0.4437 (0.4668)	loss 2.7499 (2.8083)	grad_norm 1.5544 (3.0752/1.4048)	mem 16099MB
[2025-01-18 10:16:53 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][220/312]	eta 0:00:43 lr 0.000214	time 0.5480 (0.4763)	model_time 0.5479 (0.4671)	loss 3.1076 (2.7910)	grad_norm 1.5073 (3.0451/1.3954)	mem 16099MB
[2025-01-18 10:16:58 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][230/312]	eta 0:00:39 lr 0.000213	time 0.4546 (0.4763)	model_time 0.4541 (0.4674)	loss 3.2355 (2.7944)	grad_norm 3.8592 (3.0033/1.3901)	mem 16099MB
[2025-01-18 10:17:03 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][240/312]	eta 0:00:34 lr 0.000213	time 0.4486 (0.4757)	model_time 0.4482 (0.4672)	loss 2.6019 (2.7926)	grad_norm 4.0838 (3.0235/1.3923)	mem 16099MB
[2025-01-18 10:17:07 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][250/312]	eta 0:00:29 lr 0.000213	time 0.4326 (0.4751)	model_time 0.4325 (0.4669)	loss 1.9673 (2.7825)	grad_norm 2.6166 (3.0223/1.3762)	mem 16099MB
[2025-01-18 10:17:12 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][260/312]	eta 0:00:24 lr 0.000213	time 0.4521 (0.4748)	model_time 0.4519 (0.4669)	loss 2.9486 (2.7812)	grad_norm 1.5134 (3.0155/1.3718)	mem 16099MB
[2025-01-18 10:17:16 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][270/312]	eta 0:00:19 lr 0.000212	time 0.4722 (0.4742)	model_time 0.4720 (0.4666)	loss 2.1478 (2.7840)	grad_norm 3.4757 (3.0080/1.3600)	mem 16099MB
[2025-01-18 10:17:21 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][280/312]	eta 0:00:15 lr 0.000212	time 0.4519 (0.4735)	model_time 0.4514 (0.4661)	loss 2.2587 (2.7751)	grad_norm 2.3349 (3.0622/1.3974)	mem 16099MB
[2025-01-18 10:17:26 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][290/312]	eta 0:00:10 lr 0.000212	time 0.4493 (0.4735)	model_time 0.4488 (0.4664)	loss 3.3633 (2.7724)	grad_norm 5.5383 (3.0540/1.3942)	mem 16099MB
[2025-01-18 10:17:30 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][300/312]	eta 0:00:05 lr 0.000212	time 0.4385 (0.4729)	model_time 0.4384 (0.4661)	loss 2.7999 (2.7695)	grad_norm 2.0536 (3.0808/1.4061)	mem 16099MB
[2025-01-18 10:17:35 internimage_t_1k_224] (main.py 510): INFO Train: [259/300][310/312]	eta 0:00:00 lr 0.000211	time 0.4426 (0.4732)	model_time 0.4425 (0.4666)	loss 2.6075 (2.7684)	grad_norm 2.6534 (3.0565/1.3890)	mem 16099MB
[2025-01-18 10:17:36 internimage_t_1k_224] (main.py 519): INFO EPOCH 259 training takes 0:02:27
[2025-01-18 10:17:36 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_259.pth saving......
[2025-01-18 10:17:37 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_259.pth saved !!!
[2025-01-18 10:17:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.728 (7.728)	Loss 0.7134 (0.7134)	Acc@1 85.425 (85.425)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 10:17:48 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.029)	Loss 0.9729 (0.8303)	Acc@1 78.442 (82.826)	Acc@5 95.215 (96.234)	Mem 16099MB
[2025-01-18 10:17:48 internimage_t_1k_224] (main.py 575): INFO [Epoch:259] * Acc@1 82.682 Acc@5 96.247
[2025-01-18 10:17:48 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.7%
[2025-01-18 10:17:48 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.74%
[2025-01-18 10:17:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.174 (8.174)	Loss 0.7274 (0.7274)	Acc@1 85.742 (85.742)	Acc@5 97.754 (97.754)	Mem 16099MB
[2025-01-18 10:18:00 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.101)	Loss 0.9615 (0.8306)	Acc@1 79.590 (83.458)	Acc@5 95.605 (96.538)	Mem 16099MB
[2025-01-18 10:18:00 internimage_t_1k_224] (main.py 575): INFO [Epoch:259] * Acc@1 83.329 Acc@5 96.553
[2025-01-18 10:18:00 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 10:18:00 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.33%
[2025-01-18 10:18:04 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][0/312]	eta 0:19:48 lr 0.000211	time 3.8090 (3.8090)	model_time 2.4940 (2.4940)	loss 2.8427 (2.8427)	grad_norm 2.9494 (2.9494/0.0000)	mem 16099MB
[2025-01-18 10:18:09 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][10/312]	eta 0:03:54 lr 0.000211	time 0.4500 (0.7760)	model_time 0.4499 (0.6561)	loss 1.8130 (2.7946)	grad_norm 1.7267 (2.8430/1.2731)	mem 16099MB
[2025-01-18 10:18:14 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][20/312]	eta 0:03:08 lr 0.000211	time 0.5580 (0.6442)	model_time 0.5578 (0.5812)	loss 2.5075 (2.7686)	grad_norm 3.3740 (3.7514/1.8009)	mem 16099MB
[2025-01-18 10:18:18 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][30/312]	eta 0:02:44 lr 0.000210	time 0.4584 (0.5831)	model_time 0.4583 (0.5403)	loss 2.7094 (2.7817)	grad_norm 2.2606 (3.3450/1.6734)	mem 16099MB
[2025-01-18 10:18:23 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][40/312]	eta 0:02:30 lr 0.000210	time 0.4537 (0.5523)	model_time 0.4532 (0.5198)	loss 2.1518 (2.7890)	grad_norm 2.9903 (3.1265/1.5581)	mem 16099MB
[2025-01-18 10:18:28 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][50/312]	eta 0:02:20 lr 0.000210	time 0.4342 (0.5361)	model_time 0.4336 (0.5099)	loss 3.1113 (2.7510)	grad_norm 4.4044 (3.0557/1.4724)	mem 16099MB
[2025-01-18 10:18:33 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][60/312]	eta 0:02:12 lr 0.000210	time 0.5808 (0.5273)	model_time 0.5803 (0.5053)	loss 1.7344 (2.7620)	grad_norm 4.4527 (2.9299/1.4256)	mem 16099MB
[2025-01-18 10:18:37 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][70/312]	eta 0:02:05 lr 0.000209	time 0.4603 (0.5199)	model_time 0.4599 (0.5010)	loss 3.0088 (2.7770)	grad_norm 2.1397 (3.0836/1.4933)	mem 16099MB
[2025-01-18 10:18:42 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][80/312]	eta 0:01:58 lr 0.000209	time 0.4472 (0.5118)	model_time 0.4470 (0.4952)	loss 2.3063 (2.7362)	grad_norm 6.7049 (3.1312/1.5058)	mem 16099MB
[2025-01-18 10:18:47 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][90/312]	eta 0:01:52 lr 0.000209	time 0.4616 (0.5079)	model_time 0.4611 (0.4931)	loss 3.2080 (2.7356)	grad_norm 3.0200 (3.1701/1.4689)	mem 16099MB
[2025-01-18 10:18:51 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][100/312]	eta 0:01:46 lr 0.000208	time 0.4577 (0.5034)	model_time 0.4572 (0.4900)	loss 2.2280 (2.7289)	grad_norm 2.9330 (3.1344/1.4366)	mem 16099MB
[2025-01-18 10:18:56 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][110/312]	eta 0:01:40 lr 0.000208	time 0.4568 (0.4992)	model_time 0.4566 (0.4869)	loss 2.7071 (2.7155)	grad_norm 3.3071 (3.0848/1.3979)	mem 16099MB
[2025-01-18 10:19:01 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][120/312]	eta 0:01:35 lr 0.000208	time 0.5330 (0.4973)	model_time 0.5325 (0.4860)	loss 3.3802 (2.7300)	grad_norm 2.2102 (3.0701/1.3646)	mem 16099MB
[2025-01-18 10:19:05 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][130/312]	eta 0:01:29 lr 0.000208	time 0.4510 (0.4940)	model_time 0.4505 (0.4835)	loss 2.7056 (2.7199)	grad_norm 5.6106 (3.0514/1.3857)	mem 16099MB
[2025-01-18 10:19:10 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][140/312]	eta 0:01:24 lr 0.000207	time 0.4644 (0.4931)	model_time 0.4642 (0.4834)	loss 2.4446 (2.7295)	grad_norm 2.5170 (3.0495/1.3722)	mem 16099MB
[2025-01-18 10:19:15 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][150/312]	eta 0:01:19 lr 0.000207	time 0.4625 (0.4919)	model_time 0.4621 (0.4827)	loss 2.4546 (2.7289)	grad_norm 2.6147 (3.0325/1.3683)	mem 16099MB
[2025-01-18 10:19:19 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][160/312]	eta 0:01:14 lr 0.000207	time 0.4524 (0.4903)	model_time 0.4522 (0.4817)	loss 2.9197 (2.7213)	grad_norm 1.4619 (2.9617/1.3602)	mem 16099MB
[2025-01-18 10:19:24 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][170/312]	eta 0:01:09 lr 0.000207	time 0.4436 (0.4894)	model_time 0.4432 (0.4813)	loss 2.2240 (2.7230)	grad_norm 2.0796 (2.9138/1.3454)	mem 16099MB
[2025-01-18 10:19:29 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][180/312]	eta 0:01:04 lr 0.000206	time 0.4517 (0.4882)	model_time 0.4515 (0.4806)	loss 2.7805 (2.7182)	grad_norm 3.5096 (2.9082/1.3139)	mem 16099MB
[2025-01-18 10:19:33 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][190/312]	eta 0:00:59 lr 0.000206	time 0.4925 (0.4867)	model_time 0.4923 (0.4794)	loss 3.4210 (2.7187)	grad_norm 2.3910 (2.9213/1.3124)	mem 16099MB
[2025-01-18 10:19:38 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][200/312]	eta 0:00:54 lr 0.000206	time 0.4660 (0.4852)	model_time 0.4658 (0.4782)	loss 1.8740 (2.7103)	grad_norm 3.2713 (2.9267/1.2921)	mem 16099MB
[2025-01-18 10:19:43 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][210/312]	eta 0:00:49 lr 0.000206	time 0.4415 (0.4840)	model_time 0.4413 (0.4774)	loss 2.6020 (2.7055)	grad_norm 2.8362 (2.9410/1.2910)	mem 16099MB
[2025-01-18 10:19:47 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][220/312]	eta 0:00:44 lr 0.000205	time 0.4577 (0.4828)	model_time 0.4575 (0.4764)	loss 3.1237 (2.7141)	grad_norm 2.3501 (2.9459/1.2774)	mem 16099MB
[2025-01-18 10:19:52 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][230/312]	eta 0:00:39 lr 0.000205	time 0.4692 (0.4818)	model_time 0.4690 (0.4757)	loss 3.2004 (2.7129)	grad_norm 2.2593 (2.9241/1.2610)	mem 16099MB
[2025-01-18 10:19:56 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][240/312]	eta 0:00:34 lr 0.000205	time 0.4479 (0.4807)	model_time 0.4474 (0.4748)	loss 2.9832 (2.7128)	grad_norm 2.6924 (2.9518/1.2979)	mem 16099MB
[2025-01-18 10:20:01 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][250/312]	eta 0:00:29 lr 0.000204	time 0.4560 (0.4799)	model_time 0.4558 (0.4743)	loss 2.7763 (2.7134)	grad_norm 3.1484 (2.9531/1.2794)	mem 16099MB
[2025-01-18 10:20:06 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][260/312]	eta 0:00:24 lr 0.000204	time 0.4450 (0.4794)	model_time 0.4445 (0.4740)	loss 2.7974 (2.7117)	grad_norm 1.0630 (2.9513/1.2785)	mem 16099MB
[2025-01-18 10:20:10 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][270/312]	eta 0:00:20 lr 0.000204	time 0.4616 (0.4788)	model_time 0.4614 (0.4735)	loss 1.7254 (2.7056)	grad_norm 3.5712 (2.9836/1.3154)	mem 16099MB
[2025-01-18 10:20:15 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][280/312]	eta 0:00:15 lr 0.000204	time 0.4331 (0.4779)	model_time 0.4329 (0.4729)	loss 2.6842 (2.7042)	grad_norm 1.3835 (2.9609/1.3085)	mem 16099MB
[2025-01-18 10:20:19 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][290/312]	eta 0:00:10 lr 0.000203	time 0.4505 (0.4777)	model_time 0.4500 (0.4727)	loss 2.1765 (2.6959)	grad_norm 2.8136 (2.9572/1.3014)	mem 16099MB
[2025-01-18 10:20:24 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][300/312]	eta 0:00:05 lr 0.000203	time 0.4417 (0.4777)	model_time 0.4416 (0.4729)	loss 2.5466 (2.6954)	grad_norm 3.6574 (2.9609/1.3069)	mem 16099MB
[2025-01-18 10:20:29 internimage_t_1k_224] (main.py 510): INFO Train: [260/300][310/312]	eta 0:00:00 lr 0.000203	time 0.5266 (0.4769)	model_time 0.5265 (0.4723)	loss 2.8091 (2.6968)	grad_norm 8.6809 (3.0238/1.3995)	mem 16099MB
[2025-01-18 10:20:29 internimage_t_1k_224] (main.py 519): INFO EPOCH 260 training takes 0:02:28
[2025-01-18 10:20:29 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_260.pth saving......
[2025-01-18 10:20:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_260.pth saved !!!
[2025-01-18 10:20:38 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.680 (7.680)	Loss 0.7305 (0.7305)	Acc@1 85.474 (85.474)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 10:20:42 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.044)	Loss 0.9848 (0.8438)	Acc@1 78.564 (82.901)	Acc@5 94.971 (96.203)	Mem 16099MB
[2025-01-18 10:20:42 internimage_t_1k_224] (main.py 575): INFO [Epoch:260] * Acc@1 82.774 Acc@5 96.207
[2025-01-18 10:20:42 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.8%
[2025-01-18 10:20:42 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 10:20:43 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 10:20:43 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.77%
[2025-01-18 10:20:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.643 (7.643)	Loss 0.7266 (0.7266)	Acc@1 85.767 (85.767)	Acc@5 97.754 (97.754)	Mem 16099MB
[2025-01-18 10:20:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.032)	Loss 0.9604 (0.8297)	Acc@1 79.565 (83.481)	Acc@5 95.581 (96.538)	Mem 16099MB
[2025-01-18 10:20:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:260] * Acc@1 83.349 Acc@5 96.553
[2025-01-18 10:20:55 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 10:20:55 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:20:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:20:56 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.35%
[2025-01-18 10:20:58 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][0/312]	eta 0:11:40 lr 0.000203	time 2.2467 (2.2467)	model_time 0.4690 (0.4690)	loss 3.0862 (3.0862)	grad_norm 3.5015 (3.5015/0.0000)	mem 16099MB
[2025-01-18 10:21:03 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][10/312]	eta 0:03:12 lr 0.000203	time 0.4489 (0.6389)	model_time 0.4484 (0.4769)	loss 1.7771 (2.6977)	grad_norm 2.7396 (3.4568/1.1859)	mem 16099MB
[2025-01-18 10:21:08 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][20/312]	eta 0:02:42 lr 0.000202	time 0.4536 (0.5557)	model_time 0.4534 (0.4706)	loss 2.9851 (2.8521)	grad_norm 2.8554 (3.1296/1.1022)	mem 16099MB
[2025-01-18 10:21:13 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][30/312]	eta 0:02:28 lr 0.000202	time 0.5912 (0.5275)	model_time 0.5910 (0.4697)	loss 3.0475 (2.8312)	grad_norm 3.6694 (3.4214/1.2788)	mem 16099MB
[2025-01-18 10:21:17 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][40/312]	eta 0:02:20 lr 0.000202	time 0.4456 (0.5182)	model_time 0.4451 (0.4745)	loss 2.1626 (2.8090)	grad_norm 3.2046 (3.3424/1.2183)	mem 16099MB
[2025-01-18 10:21:22 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][50/312]	eta 0:02:13 lr 0.000202	time 0.4478 (0.5095)	model_time 0.4474 (0.4743)	loss 3.1454 (2.7879)	grad_norm 1.5884 (3.1701/1.1856)	mem 16099MB
[2025-01-18 10:21:27 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][60/312]	eta 0:02:06 lr 0.000201	time 0.4569 (0.5032)	model_time 0.4567 (0.4737)	loss 3.1138 (2.7599)	grad_norm 5.8194 (3.1117/1.2049)	mem 16099MB
[2025-01-18 10:21:31 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][70/312]	eta 0:02:00 lr 0.000201	time 0.4492 (0.4966)	model_time 0.4490 (0.4712)	loss 2.9437 (2.7085)	grad_norm 1.8619 (3.0278/1.2144)	mem 16099MB
[2025-01-18 10:21:36 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][80/312]	eta 0:01:54 lr 0.000201	time 0.4570 (0.4915)	model_time 0.4565 (0.4691)	loss 3.3018 (2.7020)	grad_norm 4.9063 (2.9003/1.2375)	mem 16099MB
[2025-01-18 10:21:41 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][90/312]	eta 0:01:48 lr 0.000200	time 0.4435 (0.4883)	model_time 0.4433 (0.4683)	loss 3.0929 (2.7168)	grad_norm 2.9166 (2.8647/1.2011)	mem 16099MB
[2025-01-18 10:21:45 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][100/312]	eta 0:01:43 lr 0.000200	time 0.4550 (0.4864)	model_time 0.4548 (0.4684)	loss 2.6748 (2.7153)	grad_norm 3.0887 (2.7792/1.1949)	mem 16099MB
[2025-01-18 10:21:50 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][110/312]	eta 0:01:37 lr 0.000200	time 0.4500 (0.4843)	model_time 0.4494 (0.4679)	loss 1.9441 (2.7006)	grad_norm 2.3388 (2.7453/1.1873)	mem 16099MB
[2025-01-18 10:21:55 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][120/312]	eta 0:01:32 lr 0.000200	time 0.4476 (0.4822)	model_time 0.4474 (0.4671)	loss 2.4000 (2.6911)	grad_norm 2.2650 (2.7682/1.1809)	mem 16099MB
[2025-01-18 10:21:59 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][130/312]	eta 0:01:27 lr 0.000199	time 0.4535 (0.4805)	model_time 0.4530 (0.4665)	loss 2.9958 (2.7065)	grad_norm 2.7407 (2.7466/1.1692)	mem 16099MB
[2025-01-18 10:22:04 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][140/312]	eta 0:01:22 lr 0.000199	time 0.5696 (0.4801)	model_time 0.5692 (0.4671)	loss 1.6686 (2.7013)	grad_norm 3.7736 (2.7619/1.1716)	mem 16099MB
[2025-01-18 10:22:09 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][150/312]	eta 0:01:17 lr 0.000199	time 0.4622 (0.4791)	model_time 0.4620 (0.4669)	loss 3.2253 (2.6997)	grad_norm 2.2465 (2.8050/1.1736)	mem 16099MB
[2025-01-18 10:22:13 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][160/312]	eta 0:01:12 lr 0.000199	time 0.4520 (0.4777)	model_time 0.4518 (0.4662)	loss 2.9567 (2.7009)	grad_norm 2.8297 (2.7985/1.1467)	mem 16099MB
[2025-01-18 10:22:18 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][170/312]	eta 0:01:07 lr 0.000198	time 0.4427 (0.4778)	model_time 0.4425 (0.4670)	loss 2.8077 (2.6967)	grad_norm 6.3179 (2.7577/1.1798)	mem 16099MB
[2025-01-18 10:22:23 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][180/312]	eta 0:01:03 lr 0.000198	time 0.4408 (0.4781)	model_time 0.4406 (0.4679)	loss 2.9705 (2.6965)	grad_norm 2.3708 (2.7476/1.1919)	mem 16099MB
[2025-01-18 10:22:27 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][190/312]	eta 0:00:58 lr 0.000198	time 0.4507 (0.4774)	model_time 0.4505 (0.4677)	loss 2.6348 (2.6987)	grad_norm 2.5757 (2.7368/1.1736)	mem 16099MB
[2025-01-18 10:22:32 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][200/312]	eta 0:00:53 lr 0.000198	time 0.4519 (0.4762)	model_time 0.4517 (0.4670)	loss 2.7728 (2.7115)	grad_norm 6.1998 (2.7458/1.1945)	mem 16099MB
[2025-01-18 10:22:37 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][210/312]	eta 0:00:48 lr 0.000197	time 0.4598 (0.4756)	model_time 0.4593 (0.4668)	loss 2.2929 (2.7059)	grad_norm 5.3757 (2.7796/1.2303)	mem 16099MB
[2025-01-18 10:22:41 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][220/312]	eta 0:00:43 lr 0.000197	time 0.4524 (0.4747)	model_time 0.4520 (0.4662)	loss 1.9836 (2.7007)	grad_norm 2.3279 (2.8173/1.3005)	mem 16099MB
[2025-01-18 10:22:46 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][230/312]	eta 0:00:38 lr 0.000197	time 0.5549 (0.4751)	model_time 0.5548 (0.4670)	loss 3.3535 (2.7148)	grad_norm 3.6151 (2.8166/1.2816)	mem 16099MB
[2025-01-18 10:22:51 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][240/312]	eta 0:00:34 lr 0.000197	time 0.4470 (0.4745)	model_time 0.4466 (0.4667)	loss 3.0901 (2.7132)	grad_norm 1.9742 (2.8107/1.2687)	mem 16099MB
[2025-01-18 10:22:55 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][250/312]	eta 0:00:29 lr 0.000196	time 0.4643 (0.4742)	model_time 0.4638 (0.4667)	loss 3.0857 (2.7178)	grad_norm 2.6566 (2.8081/1.2643)	mem 16099MB
[2025-01-18 10:23:00 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][260/312]	eta 0:00:24 lr 0.000196	time 0.4520 (0.4737)	model_time 0.4518 (0.4665)	loss 3.3650 (2.7192)	grad_norm 1.7580 (2.8323/1.2592)	mem 16099MB
[2025-01-18 10:23:05 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][270/312]	eta 0:00:19 lr 0.000196	time 0.4431 (0.4736)	model_time 0.4429 (0.4666)	loss 2.5506 (2.7181)	grad_norm 4.7977 (2.8572/1.2781)	mem 16099MB
[2025-01-18 10:23:09 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][280/312]	eta 0:00:15 lr 0.000196	time 0.4412 (0.4738)	model_time 0.4410 (0.4671)	loss 3.4224 (2.7197)	grad_norm 5.9271 (2.9155/1.3547)	mem 16099MB
[2025-01-18 10:23:14 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][290/312]	eta 0:00:10 lr 0.000195	time 0.4455 (0.4739)	model_time 0.4453 (0.4673)	loss 2.8219 (2.7167)	grad_norm 1.4220 (2.8994/1.3432)	mem 16099MB
[2025-01-18 10:23:19 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][300/312]	eta 0:00:05 lr 0.000195	time 0.4398 (0.4733)	model_time 0.4397 (0.4670)	loss 3.3267 (2.7181)	grad_norm 2.2663 (2.8953/1.3413)	mem 16099MB
[2025-01-18 10:23:23 internimage_t_1k_224] (main.py 510): INFO Train: [261/300][310/312]	eta 0:00:00 lr 0.000195	time 0.4385 (0.4726)	model_time 0.4384 (0.4664)	loss 3.1473 (2.7230)	grad_norm 1.8468 (2.8556/1.3317)	mem 16099MB
[2025-01-18 10:23:24 internimage_t_1k_224] (main.py 519): INFO EPOCH 261 training takes 0:02:27
[2025-01-18 10:23:24 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_261.pth saving......
[2025-01-18 10:23:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_261.pth saved !!!
[2025-01-18 10:23:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.804 (7.804)	Loss 0.7544 (0.7544)	Acc@1 84.717 (84.717)	Acc@5 97.241 (97.241)	Mem 16099MB
[2025-01-18 10:23:36 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.048)	Loss 0.9888 (0.8515)	Acc@1 79.028 (82.857)	Acc@5 95.044 (96.158)	Mem 16099MB
[2025-01-18 10:23:36 internimage_t_1k_224] (main.py 575): INFO [Epoch:261] * Acc@1 82.720 Acc@5 96.157
[2025-01-18 10:23:36 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.7%
[2025-01-18 10:23:36 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.77%
[2025-01-18 10:23:45 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.264 (8.264)	Loss 0.7260 (0.7260)	Acc@1 85.718 (85.718)	Acc@5 97.754 (97.754)	Mem 16099MB
[2025-01-18 10:23:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.110)	Loss 0.9593 (0.8288)	Acc@1 79.614 (83.478)	Acc@5 95.581 (96.540)	Mem 16099MB
[2025-01-18 10:23:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:261] * Acc@1 83.341 Acc@5 96.555
[2025-01-18 10:23:49 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 10:23:49 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.35%
[2025-01-18 10:23:52 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][0/312]	eta 0:16:37 lr 0.000195	time 3.1963 (3.1963)	model_time 1.1968 (1.1968)	loss 2.5739 (2.5739)	grad_norm 1.7023 (1.7023/0.0000)	mem 16099MB
[2025-01-18 10:23:57 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][10/312]	eta 0:03:37 lr 0.000194	time 0.4498 (0.7200)	model_time 0.4494 (0.5380)	loss 3.1737 (2.6064)	grad_norm 2.1605 (2.9008/1.1978)	mem 16099MB
[2025-01-18 10:24:01 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][20/312]	eta 0:02:55 lr 0.000194	time 0.5471 (0.6010)	model_time 0.5466 (0.5055)	loss 3.3700 (2.6101)	grad_norm 3.1385 (3.0400/1.1199)	mem 16099MB
[2025-01-18 10:24:06 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][30/312]	eta 0:02:38 lr 0.000194	time 0.4583 (0.5612)	model_time 0.4581 (0.4964)	loss 2.9759 (2.6651)	grad_norm 3.8731 (2.9884/1.3914)	mem 16099MB
[2025-01-18 10:24:11 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][40/312]	eta 0:02:25 lr 0.000194	time 0.4516 (0.5357)	model_time 0.4511 (0.4866)	loss 2.6783 (2.6944)	grad_norm 1.7494 (2.9930/1.3142)	mem 16099MB
[2025-01-18 10:24:15 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][50/312]	eta 0:02:16 lr 0.000193	time 0.4443 (0.5214)	model_time 0.4441 (0.4819)	loss 3.1473 (2.6941)	grad_norm 1.6558 (2.9908/1.2999)	mem 16099MB
[2025-01-18 10:24:20 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][60/312]	eta 0:02:08 lr 0.000193	time 0.4435 (0.5109)	model_time 0.4433 (0.4778)	loss 3.1252 (2.7138)	grad_norm 1.5369 (3.1019/1.4291)	mem 16099MB
[2025-01-18 10:24:25 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][70/312]	eta 0:02:02 lr 0.000193	time 0.4469 (0.5066)	model_time 0.4463 (0.4781)	loss 2.8933 (2.7265)	grad_norm 2.8047 (3.0406/1.3808)	mem 16099MB
[2025-01-18 10:24:29 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][80/312]	eta 0:01:56 lr 0.000193	time 0.4500 (0.5022)	model_time 0.4498 (0.4772)	loss 2.8669 (2.7337)	grad_norm 1.0830 (2.9141/1.3744)	mem 16099MB
[2025-01-18 10:24:34 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][90/312]	eta 0:01:50 lr 0.000192	time 0.4546 (0.4974)	model_time 0.4542 (0.4750)	loss 2.5972 (2.7256)	grad_norm 2.7273 (2.9129/1.3377)	mem 16099MB
[2025-01-18 10:24:39 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][100/312]	eta 0:01:44 lr 0.000192	time 0.4596 (0.4940)	model_time 0.4594 (0.4738)	loss 3.0125 (2.7225)	grad_norm 2.1990 (2.8550/1.3024)	mem 16099MB
[2025-01-18 10:24:43 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][110/312]	eta 0:01:39 lr 0.000192	time 0.4482 (0.4904)	model_time 0.4478 (0.4720)	loss 3.5591 (2.7427)	grad_norm 5.3433 (2.8762/1.3008)	mem 16099MB
[2025-01-18 10:24:48 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][120/312]	eta 0:01:33 lr 0.000192	time 0.4555 (0.4890)	model_time 0.4551 (0.4721)	loss 2.8912 (2.7457)	grad_norm 2.9790 (2.9418/1.3613)	mem 16099MB
[2025-01-18 10:24:52 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][130/312]	eta 0:01:28 lr 0.000191	time 0.4559 (0.4863)	model_time 0.4557 (0.4706)	loss 3.3854 (2.7544)	grad_norm 2.2701 (2.9061/1.3640)	mem 16099MB
[2025-01-18 10:24:57 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][140/312]	eta 0:01:23 lr 0.000191	time 0.4423 (0.4858)	model_time 0.4421 (0.4712)	loss 2.1884 (2.7368)	grad_norm 4.1305 (2.9111/1.3406)	mem 16099MB
[2025-01-18 10:25:02 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][150/312]	eta 0:01:18 lr 0.000191	time 0.4668 (0.4851)	model_time 0.4666 (0.4714)	loss 2.9092 (2.7335)	grad_norm 2.4276 (2.9189/1.3269)	mem 16099MB
[2025-01-18 10:25:07 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][160/312]	eta 0:01:13 lr 0.000191	time 0.4515 (0.4839)	model_time 0.4510 (0.4710)	loss 3.1073 (2.7489)	grad_norm 1.6559 (2.8852/1.3126)	mem 16099MB
[2025-01-18 10:25:11 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][170/312]	eta 0:01:08 lr 0.000190	time 0.4452 (0.4832)	model_time 0.4447 (0.4711)	loss 3.1860 (2.7455)	grad_norm 1.5114 (2.8662/1.2987)	mem 16099MB
[2025-01-18 10:25:16 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][180/312]	eta 0:01:03 lr 0.000190	time 0.4684 (0.4821)	model_time 0.4682 (0.4706)	loss 2.6675 (2.7344)	grad_norm 2.7820 (2.8574/1.2803)	mem 16099MB
[2025-01-18 10:25:21 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][190/312]	eta 0:00:58 lr 0.000190	time 0.4503 (0.4818)	model_time 0.4501 (0.4709)	loss 3.2657 (2.7415)	grad_norm 3.4324 (2.8730/1.2920)	mem 16099MB
[2025-01-18 10:25:25 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][200/312]	eta 0:00:53 lr 0.000190	time 0.4548 (0.4805)	model_time 0.4546 (0.4701)	loss 2.0837 (2.7362)	grad_norm 2.7873 (2.9026/1.3037)	mem 16099MB
[2025-01-18 10:25:30 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][210/312]	eta 0:00:48 lr 0.000189	time 0.4760 (0.4800)	model_time 0.4756 (0.4701)	loss 2.8742 (2.7387)	grad_norm 3.1231 (2.8883/1.2833)	mem 16099MB
[2025-01-18 10:25:35 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][220/312]	eta 0:00:44 lr 0.000189	time 0.4644 (0.4792)	model_time 0.4643 (0.4697)	loss 2.3067 (2.7421)	grad_norm 2.0161 (2.8927/1.2868)	mem 16099MB
[2025-01-18 10:25:39 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][230/312]	eta 0:00:39 lr 0.000189	time 0.4421 (0.4784)	model_time 0.4419 (0.4693)	loss 3.1720 (2.7498)	grad_norm 1.7271 (2.8537/1.2784)	mem 16099MB
[2025-01-18 10:25:44 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][240/312]	eta 0:00:34 lr 0.000189	time 0.4767 (0.4774)	model_time 0.4763 (0.4687)	loss 2.2493 (2.7527)	grad_norm 4.9688 (2.8512/1.2688)	mem 16099MB
[2025-01-18 10:25:48 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][250/312]	eta 0:00:29 lr 0.000188	time 0.4538 (0.4764)	model_time 0.4537 (0.4681)	loss 3.0248 (2.7579)	grad_norm 2.1919 (2.8406/1.2597)	mem 16099MB
[2025-01-18 10:25:53 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][260/312]	eta 0:00:24 lr 0.000188	time 0.4477 (0.4763)	model_time 0.4476 (0.4682)	loss 3.0512 (2.7599)	grad_norm 3.4014 (2.8292/1.2445)	mem 16099MB
[2025-01-18 10:25:58 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][270/312]	eta 0:00:19 lr 0.000188	time 0.4432 (0.4759)	model_time 0.4430 (0.4681)	loss 1.8769 (2.7592)	grad_norm 3.9471 (2.8860/1.2964)	mem 16099MB
[2025-01-18 10:26:02 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][280/312]	eta 0:00:15 lr 0.000188	time 0.4527 (0.4751)	model_time 0.4522 (0.4676)	loss 2.7076 (2.7665)	grad_norm 3.1546 (2.8797/1.2787)	mem 16099MB
[2025-01-18 10:26:07 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][290/312]	eta 0:00:10 lr 0.000187	time 0.4506 (0.4747)	model_time 0.4504 (0.4674)	loss 2.6773 (2.7621)	grad_norm 3.1370 (2.8629/1.2708)	mem 16099MB
[2025-01-18 10:26:11 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][300/312]	eta 0:00:05 lr 0.000187	time 0.4410 (0.4739)	model_time 0.4409 (0.4668)	loss 2.9909 (2.7649)	grad_norm 2.7698 (2.8664/1.2575)	mem 16099MB
[2025-01-18 10:26:16 internimage_t_1k_224] (main.py 510): INFO Train: [262/300][310/312]	eta 0:00:00 lr 0.000187	time 0.4437 (0.4731)	model_time 0.4435 (0.4663)	loss 3.2006 (2.7709)	grad_norm 4.0088 (2.8539/1.2487)	mem 16099MB
[2025-01-18 10:26:16 internimage_t_1k_224] (main.py 519): INFO EPOCH 262 training takes 0:02:27
[2025-01-18 10:26:16 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_262.pth saving......
[2025-01-18 10:26:17 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_262.pth saved !!!
[2025-01-18 10:26:25 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.536 (7.536)	Loss 0.7260 (0.7260)	Acc@1 85.229 (85.229)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 10:26:29 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.109 (1.012)	Loss 0.9630 (0.8272)	Acc@1 79.443 (83.066)	Acc@5 95.386 (96.280)	Mem 16099MB
[2025-01-18 10:26:29 internimage_t_1k_224] (main.py 575): INFO [Epoch:262] * Acc@1 82.893 Acc@5 96.277
[2025-01-18 10:26:29 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.9%
[2025-01-18 10:26:29 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 10:26:30 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 10:26:30 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.89%
[2025-01-18 10:26:38 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.568 (7.568)	Loss 0.7255 (0.7255)	Acc@1 85.718 (85.718)	Acc@5 97.754 (97.754)	Mem 16099MB
[2025-01-18 10:26:41 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.028)	Loss 0.9585 (0.8281)	Acc@1 79.541 (83.485)	Acc@5 95.557 (96.542)	Mem 16099MB
[2025-01-18 10:26:41 internimage_t_1k_224] (main.py 575): INFO [Epoch:262] * Acc@1 83.345 Acc@5 96.559
[2025-01-18 10:26:41 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.3%
[2025-01-18 10:26:41 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.35%
[2025-01-18 10:26:44 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][0/312]	eta 0:16:04 lr 0.000187	time 3.0911 (3.0911)	model_time 1.6509 (1.6509)	loss 2.3844 (2.3844)	grad_norm 2.8906 (2.8906/0.0000)	mem 16099MB
[2025-01-18 10:26:50 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][10/312]	eta 0:03:49 lr 0.000187	time 0.4566 (0.7615)	model_time 0.4564 (0.6302)	loss 3.1920 (2.8174)	grad_norm 3.9696 (3.0197/1.0235)	mem 16099MB
[2025-01-18 10:26:54 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][20/312]	eta 0:03:00 lr 0.000186	time 0.4530 (0.6197)	model_time 0.4525 (0.5507)	loss 2.3986 (2.8373)	grad_norm 3.5231 (2.9768/1.4410)	mem 16099MB
[2025-01-18 10:26:59 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][30/312]	eta 0:02:41 lr 0.000186	time 0.5989 (0.5721)	model_time 0.5987 (0.5253)	loss 2.9270 (2.8921)	grad_norm 2.5433 (2.9551/1.2566)	mem 16099MB
[2025-01-18 10:27:04 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][40/312]	eta 0:02:27 lr 0.000186	time 0.4601 (0.5430)	model_time 0.4599 (0.5075)	loss 2.5781 (2.8300)	grad_norm 1.4697 (3.0598/1.4960)	mem 16099MB
[2025-01-18 10:27:08 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][50/312]	eta 0:02:17 lr 0.000186	time 0.4651 (0.5259)	model_time 0.4646 (0.4973)	loss 2.8514 (2.8421)	grad_norm 1.8057 (3.0884/1.4058)	mem 16099MB
[2025-01-18 10:27:13 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][60/312]	eta 0:02:10 lr 0.000185	time 0.5632 (0.5179)	model_time 0.5630 (0.4938)	loss 2.6150 (2.7926)	grad_norm 4.8565 (3.2396/1.3722)	mem 16099MB
[2025-01-18 10:27:18 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][70/312]	eta 0:02:03 lr 0.000185	time 0.4552 (0.5086)	model_time 0.4547 (0.4879)	loss 2.8880 (2.8168)	grad_norm 2.9138 (3.1204/1.3401)	mem 16099MB
[2025-01-18 10:27:22 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][80/312]	eta 0:01:56 lr 0.000185	time 0.4539 (0.5022)	model_time 0.4534 (0.4840)	loss 3.0668 (2.7690)	grad_norm 2.6967 (3.0650/1.2899)	mem 16099MB
[2025-01-18 10:27:27 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][90/312]	eta 0:01:50 lr 0.000185	time 0.4487 (0.4966)	model_time 0.4482 (0.4804)	loss 2.7371 (2.7738)	grad_norm 2.9650 (3.0268/1.3387)	mem 16099MB
[2025-01-18 10:27:31 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][100/312]	eta 0:01:44 lr 0.000184	time 0.4495 (0.4927)	model_time 0.4493 (0.4780)	loss 1.8205 (2.7431)	grad_norm 1.6621 (3.0671/1.3588)	mem 16099MB
[2025-01-18 10:27:36 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][110/312]	eta 0:01:39 lr 0.000184	time 0.4642 (0.4918)	model_time 0.4640 (0.4784)	loss 2.8688 (2.7446)	grad_norm 6.8068 (3.1896/1.5265)	mem 16099MB
[2025-01-18 10:27:41 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][120/312]	eta 0:01:34 lr 0.000184	time 0.4536 (0.4903)	model_time 0.4532 (0.4780)	loss 1.9055 (2.7414)	grad_norm 3.9100 (3.3023/1.5901)	mem 16099MB
[2025-01-18 10:27:46 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][130/312]	eta 0:01:29 lr 0.000184	time 0.4638 (0.4912)	model_time 0.4635 (0.4798)	loss 2.5779 (2.7300)	grad_norm 3.8621 (3.4374/1.7204)	mem 16099MB
[2025-01-18 10:27:51 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][140/312]	eta 0:01:24 lr 0.000183	time 0.4717 (0.4918)	model_time 0.4715 (0.4811)	loss 3.0115 (2.7344)	grad_norm 4.6467 (3.4350/1.6866)	mem 16099MB
[2025-01-18 10:27:56 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][150/312]	eta 0:01:19 lr 0.000183	time 0.5430 (0.4918)	model_time 0.5428 (0.4818)	loss 2.6086 (2.7382)	grad_norm 1.1706 (3.3383/1.6794)	mem 16099MB
[2025-01-18 10:28:00 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][160/312]	eta 0:01:14 lr 0.000183	time 0.4453 (0.4893)	model_time 0.4448 (0.4799)	loss 3.2003 (2.7342)	grad_norm 2.4564 (3.2832/1.6491)	mem 16099MB
[2025-01-18 10:28:05 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][170/312]	eta 0:01:09 lr 0.000183	time 0.4549 (0.4882)	model_time 0.4548 (0.4793)	loss 2.6539 (2.7269)	grad_norm 2.4805 (3.2366/1.6224)	mem 16099MB
[2025-01-18 10:28:10 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][180/312]	eta 0:01:04 lr 0.000182	time 0.4474 (0.4870)	model_time 0.4473 (0.4786)	loss 3.2339 (2.7388)	grad_norm 2.0485 (3.2323/1.6268)	mem 16099MB
[2025-01-18 10:28:14 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][190/312]	eta 0:00:59 lr 0.000182	time 0.4489 (0.4852)	model_time 0.4487 (0.4772)	loss 2.4478 (2.7282)	grad_norm 5.0498 (3.2769/1.6252)	mem 16099MB
[2025-01-18 10:28:19 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][200/312]	eta 0:00:54 lr 0.000182	time 0.4523 (0.4836)	model_time 0.4519 (0.4760)	loss 3.0397 (2.7247)	grad_norm 2.8758 (3.3088/1.6405)	mem 16099MB
[2025-01-18 10:28:23 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][210/312]	eta 0:00:49 lr 0.000182	time 0.4525 (0.4821)	model_time 0.4520 (0.4749)	loss 2.8613 (2.7239)	grad_norm 2.0317 (3.2820/1.6113)	mem 16099MB
[2025-01-18 10:28:28 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][220/312]	eta 0:00:44 lr 0.000181	time 0.4563 (0.4809)	model_time 0.4558 (0.4739)	loss 2.9052 (2.7138)	grad_norm 1.6302 (3.2685/1.5998)	mem 16099MB
[2025-01-18 10:28:32 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][230/312]	eta 0:00:39 lr 0.000181	time 0.4561 (0.4803)	model_time 0.4559 (0.4736)	loss 1.9640 (2.7057)	grad_norm 8.1765 (3.3399/1.6505)	mem 16099MB
[2025-01-18 10:28:37 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][240/312]	eta 0:00:34 lr 0.000181	time 0.4553 (0.4795)	model_time 0.4552 (0.4731)	loss 2.7342 (2.7150)	grad_norm 7.0738 (3.3847/1.6716)	mem 16099MB
[2025-01-18 10:28:42 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][250/312]	eta 0:00:29 lr 0.000181	time 0.4691 (0.4796)	model_time 0.4686 (0.4734)	loss 2.9552 (2.7161)	grad_norm 2.0043 (3.3736/1.6669)	mem 16099MB
[2025-01-18 10:28:46 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][260/312]	eta 0:00:24 lr 0.000180	time 0.4388 (0.4785)	model_time 0.4387 (0.4725)	loss 3.0176 (2.7171)	grad_norm 1.6767 (3.3761/1.6736)	mem 16099MB
[2025-01-18 10:28:51 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][270/312]	eta 0:00:20 lr 0.000180	time 0.6083 (0.4783)	model_time 0.6078 (0.4726)	loss 3.4248 (2.7121)	grad_norm 1.3742 (3.3765/1.6633)	mem 16099MB
[2025-01-18 10:28:56 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][280/312]	eta 0:00:15 lr 0.000180	time 0.4444 (0.4793)	model_time 0.4443 (0.4738)	loss 2.4781 (2.7080)	grad_norm 2.8901 (3.3803/1.6515)	mem 16099MB
[2025-01-18 10:29:01 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][290/312]	eta 0:00:10 lr 0.000180	time 0.4610 (0.4793)	model_time 0.4608 (0.4739)	loss 2.6108 (2.7093)	grad_norm 2.1222 (3.3796/1.6389)	mem 16099MB
[2025-01-18 10:29:05 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][300/312]	eta 0:00:05 lr 0.000179	time 0.4362 (0.4786)	model_time 0.4360 (0.4734)	loss 2.3419 (2.7068)	grad_norm 1.8681 (3.3626/1.6294)	mem 16099MB
[2025-01-18 10:29:10 internimage_t_1k_224] (main.py 510): INFO Train: [263/300][310/312]	eta 0:00:00 lr 0.000179	time 0.4402 (0.4776)	model_time 0.4401 (0.4726)	loss 3.1714 (2.7092)	grad_norm 1.6579 (3.3452/1.6353)	mem 16099MB
[2025-01-18 10:29:10 internimage_t_1k_224] (main.py 519): INFO EPOCH 263 training takes 0:02:28
[2025-01-18 10:29:10 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_263.pth saving......
[2025-01-18 10:29:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_263.pth saved !!!
[2025-01-18 10:29:19 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.796 (7.796)	Loss 0.7248 (0.7248)	Acc@1 85.303 (85.303)	Acc@5 97.217 (97.217)	Mem 16099MB
[2025-01-18 10:29:23 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.046)	Loss 0.9790 (0.8302)	Acc@1 78.491 (82.895)	Acc@5 95.093 (96.265)	Mem 16099MB
[2025-01-18 10:29:23 internimage_t_1k_224] (main.py 575): INFO [Epoch:263] * Acc@1 82.754 Acc@5 96.257
[2025-01-18 10:29:23 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.8%
[2025-01-18 10:29:23 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.89%
[2025-01-18 10:29:32 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.611 (8.611)	Loss 0.7248 (0.7248)	Acc@1 85.693 (85.693)	Acc@5 97.778 (97.778)	Mem 16099MB
[2025-01-18 10:29:36 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.150)	Loss 0.9575 (0.8272)	Acc@1 79.639 (83.498)	Acc@5 95.557 (96.560)	Mem 16099MB
[2025-01-18 10:29:36 internimage_t_1k_224] (main.py 575): INFO [Epoch:263] * Acc@1 83.351 Acc@5 96.575
[2025-01-18 10:29:36 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.4%
[2025-01-18 10:29:36 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:29:37 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:29:37 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.35%
[2025-01-18 10:29:40 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][0/312]	eta 0:11:44 lr 0.000179	time 2.2582 (2.2582)	model_time 0.4649 (0.4649)	loss 2.4500 (2.4500)	grad_norm 1.3429 (1.3429/0.0000)	mem 16099MB
[2025-01-18 10:29:45 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][10/312]	eta 0:03:16 lr 0.000179	time 0.5166 (0.6522)	model_time 0.5164 (0.4890)	loss 2.0034 (2.6549)	grad_norm 3.1288 (3.0070/1.0068)	mem 16099MB
[2025-01-18 10:29:49 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][20/312]	eta 0:02:44 lr 0.000179	time 0.5403 (0.5625)	model_time 0.5399 (0.4768)	loss 2.8031 (2.7290)	grad_norm 1.9154 (2.7412/0.8944)	mem 16099MB
[2025-01-18 10:29:54 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][30/312]	eta 0:02:29 lr 0.000178	time 0.4741 (0.5314)	model_time 0.4740 (0.4732)	loss 3.0157 (2.5990)	grad_norm 3.2479 (2.7795/0.8040)	mem 16099MB
[2025-01-18 10:29:59 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][40/312]	eta 0:02:21 lr 0.000178	time 0.4643 (0.5197)	model_time 0.4642 (0.4757)	loss 2.7800 (2.6333)	grad_norm 2.5263 (2.9695/1.2393)	mem 16099MB
[2025-01-18 10:30:04 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][50/312]	eta 0:02:14 lr 0.000178	time 0.4443 (0.5153)	model_time 0.4442 (0.4798)	loss 2.7773 (2.6840)	grad_norm 2.2646 (2.9380/1.3621)	mem 16099MB
[2025-01-18 10:30:08 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][60/312]	eta 0:02:07 lr 0.000178	time 0.4614 (0.5075)	model_time 0.4612 (0.4778)	loss 2.9236 (2.6832)	grad_norm 2.5425 (2.9022/1.2777)	mem 16099MB
[2025-01-18 10:30:13 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][70/312]	eta 0:02:01 lr 0.000177	time 0.4587 (0.5003)	model_time 0.4585 (0.4747)	loss 1.7203 (2.6867)	grad_norm 2.8896 (2.9002/1.2644)	mem 16099MB
[2025-01-18 10:30:18 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][80/312]	eta 0:01:54 lr 0.000177	time 0.4539 (0.4948)	model_time 0.4537 (0.4724)	loss 2.9147 (2.7143)	grad_norm 1.9522 (3.0284/1.3951)	mem 16099MB
[2025-01-18 10:30:22 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][90/312]	eta 0:01:49 lr 0.000177	time 0.4421 (0.4942)	model_time 0.4420 (0.4742)	loss 2.5815 (2.7320)	grad_norm 1.6501 (2.9244/1.3582)	mem 16099MB
[2025-01-18 10:30:27 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][100/312]	eta 0:01:44 lr 0.000177	time 0.4513 (0.4911)	model_time 0.4509 (0.4730)	loss 2.0165 (2.7259)	grad_norm 3.0947 (2.8910/1.3207)	mem 16099MB
[2025-01-18 10:30:32 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][110/312]	eta 0:01:39 lr 0.000176	time 0.4443 (0.4907)	model_time 0.4439 (0.4742)	loss 2.8564 (2.7294)	grad_norm 1.4467 (2.8501/1.2879)	mem 16099MB
[2025-01-18 10:30:36 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][120/312]	eta 0:01:33 lr 0.000176	time 0.4515 (0.4876)	model_time 0.4511 (0.4725)	loss 2.6481 (2.7167)	grad_norm 4.0594 (2.9123/1.3094)	mem 16099MB
[2025-01-18 10:30:41 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][130/312]	eta 0:01:28 lr 0.000176	time 0.4523 (0.4858)	model_time 0.4518 (0.4718)	loss 2.7609 (2.7258)	grad_norm 2.3728 (2.9260/1.3031)	mem 16099MB
[2025-01-18 10:30:46 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][140/312]	eta 0:01:23 lr 0.000176	time 0.4603 (0.4850)	model_time 0.4601 (0.4719)	loss 3.3177 (2.7329)	grad_norm 3.1890 (2.9533/1.3183)	mem 16099MB
[2025-01-18 10:30:50 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][150/312]	eta 0:01:18 lr 0.000175	time 0.4546 (0.4835)	model_time 0.4542 (0.4713)	loss 2.3467 (2.7358)	grad_norm 2.0684 (2.9744/1.3210)	mem 16099MB
[2025-01-18 10:30:55 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][160/312]	eta 0:01:13 lr 0.000175	time 0.4400 (0.4828)	model_time 0.4396 (0.4713)	loss 2.3188 (2.7337)	grad_norm 3.6452 (2.9711/1.3589)	mem 16099MB
[2025-01-18 10:31:00 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][170/312]	eta 0:01:08 lr 0.000175	time 0.4519 (0.4811)	model_time 0.4515 (0.4703)	loss 3.2118 (2.7364)	grad_norm 1.3978 (2.9922/1.3873)	mem 16099MB
[2025-01-18 10:31:05 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][180/312]	eta 0:01:03 lr 0.000175	time 0.4425 (0.4814)	model_time 0.4421 (0.4711)	loss 2.8795 (2.7521)	grad_norm 2.4090 (3.0506/1.3991)	mem 16099MB
[2025-01-18 10:31:09 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][190/312]	eta 0:00:58 lr 0.000174	time 0.4397 (0.4815)	model_time 0.4393 (0.4718)	loss 3.0360 (2.7521)	grad_norm 7.8681 (3.1169/1.4492)	mem 16099MB
[2025-01-18 10:31:14 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][200/312]	eta 0:00:53 lr 0.000174	time 0.5919 (0.4808)	model_time 0.5915 (0.4715)	loss 3.4698 (2.7437)	grad_norm 2.3175 (3.0946/1.4260)	mem 16099MB
[2025-01-18 10:31:19 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][210/312]	eta 0:00:48 lr 0.000174	time 0.4487 (0.4794)	model_time 0.4483 (0.4706)	loss 2.6937 (2.7400)	grad_norm 5.4194 (3.0876/1.4356)	mem 16099MB
[2025-01-18 10:31:23 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][220/312]	eta 0:00:44 lr 0.000174	time 0.4522 (0.4784)	model_time 0.4518 (0.4699)	loss 3.2375 (2.7433)	grad_norm 2.6606 (3.0750/1.4203)	mem 16099MB
[2025-01-18 10:31:28 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][230/312]	eta 0:00:39 lr 0.000173	time 0.4424 (0.4788)	model_time 0.4420 (0.4707)	loss 2.8519 (2.7437)	grad_norm 3.5909 (3.0627/1.4124)	mem 16099MB
[2025-01-18 10:31:33 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][240/312]	eta 0:00:34 lr 0.000173	time 0.4551 (0.4777)	model_time 0.4549 (0.4699)	loss 3.5938 (2.7457)	grad_norm 8.3466 (3.1037/1.4701)	mem 16099MB
[2025-01-18 10:31:37 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][250/312]	eta 0:00:29 lr 0.000173	time 0.4543 (0.4779)	model_time 0.4539 (0.4704)	loss 3.0355 (2.7530)	grad_norm 2.2935 (3.1761/1.5070)	mem 16099MB
[2025-01-18 10:31:42 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][260/312]	eta 0:00:24 lr 0.000173	time 0.4577 (0.4769)	model_time 0.4573 (0.4697)	loss 3.1575 (2.7539)	grad_norm 4.9295 (3.1802/1.5002)	mem 16099MB
[2025-01-18 10:31:47 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][270/312]	eta 0:00:20 lr 0.000173	time 0.4505 (0.4762)	model_time 0.4504 (0.4692)	loss 2.4078 (2.7437)	grad_norm 2.4688 (3.1389/1.4900)	mem 16099MB
[2025-01-18 10:31:51 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][280/312]	eta 0:00:15 lr 0.000172	time 0.4526 (0.4767)	model_time 0.4522 (0.4699)	loss 2.7223 (2.7461)	grad_norm 3.2375 (3.1087/1.4795)	mem 16099MB
[2025-01-18 10:31:56 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][290/312]	eta 0:00:10 lr 0.000172	time 0.5471 (0.4768)	model_time 0.5469 (0.4703)	loss 3.1537 (2.7414)	grad_norm 1.8958 (3.0962/1.4626)	mem 16099MB
[2025-01-18 10:32:01 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][300/312]	eta 0:00:05 lr 0.000172	time 0.4397 (0.4760)	model_time 0.4396 (0.4697)	loss 1.9833 (2.7269)	grad_norm 4.2781 (3.0890/1.4456)	mem 16099MB
[2025-01-18 10:32:05 internimage_t_1k_224] (main.py 510): INFO Train: [264/300][310/312]	eta 0:00:00 lr 0.000172	time 0.4438 (0.4753)	model_time 0.4437 (0.4691)	loss 2.7099 (2.7339)	grad_norm 6.3668 (3.0817/1.4543)	mem 16099MB
[2025-01-18 10:32:06 internimage_t_1k_224] (main.py 519): INFO EPOCH 264 training takes 0:02:28
[2025-01-18 10:32:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_264.pth saving......
[2025-01-18 10:32:07 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_264.pth saved !!!
[2025-01-18 10:32:14 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.398 (7.398)	Loss 0.7237 (0.7237)	Acc@1 84.937 (84.937)	Acc@5 97.437 (97.437)	Mem 16099MB
[2025-01-18 10:32:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.010)	Loss 0.9929 (0.8357)	Acc@1 78.174 (82.781)	Acc@5 94.897 (96.258)	Mem 16099MB
[2025-01-18 10:32:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:264] * Acc@1 82.648 Acc@5 96.263
[2025-01-18 10:32:18 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.6%
[2025-01-18 10:32:18 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.89%
[2025-01-18 10:32:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.406 (8.406)	Loss 0.7245 (0.7245)	Acc@1 85.718 (85.718)	Acc@5 97.754 (97.754)	Mem 16099MB
[2025-01-18 10:32:30 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.119)	Loss 0.9565 (0.8265)	Acc@1 79.785 (83.527)	Acc@5 95.508 (96.573)	Mem 16099MB
[2025-01-18 10:32:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:264] * Acc@1 83.383 Acc@5 96.581
[2025-01-18 10:32:31 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.4%
[2025-01-18 10:32:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:32:32 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:32:32 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.38%
[2025-01-18 10:32:34 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][0/312]	eta 0:11:10 lr 0.000172	time 2.1487 (2.1487)	model_time 0.4986 (0.4986)	loss 3.0724 (3.0724)	grad_norm 1.6749 (1.6749/0.0000)	mem 16099MB
[2025-01-18 10:32:39 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][10/312]	eta 0:03:07 lr 0.000171	time 0.4461 (0.6218)	model_time 0.4460 (0.4715)	loss 3.1898 (2.7196)	grad_norm 3.3361 (3.3152/1.3660)	mem 16099MB
[2025-01-18 10:32:44 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][20/312]	eta 0:02:43 lr 0.000171	time 0.4428 (0.5601)	model_time 0.4426 (0.4812)	loss 1.7838 (2.7258)	grad_norm 1.7831 (3.1428/1.5343)	mem 16099MB
[2025-01-18 10:32:48 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][30/312]	eta 0:02:28 lr 0.000171	time 0.4518 (0.5266)	model_time 0.4513 (0.4731)	loss 2.7702 (2.7163)	grad_norm 2.9211 (3.0664/1.4499)	mem 16099MB
[2025-01-18 10:32:53 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][40/312]	eta 0:02:19 lr 0.000171	time 0.4469 (0.5134)	model_time 0.4465 (0.4728)	loss 2.7037 (2.7235)	grad_norm 5.8771 (3.2117/1.4907)	mem 16099MB
[2025-01-18 10:32:58 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][50/312]	eta 0:02:11 lr 0.000170	time 0.4459 (0.5034)	model_time 0.4457 (0.4707)	loss 2.8308 (2.7065)	grad_norm 3.0585 (3.3610/1.5727)	mem 16099MB
[2025-01-18 10:33:02 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][60/312]	eta 0:02:05 lr 0.000170	time 0.4466 (0.4994)	model_time 0.4465 (0.4720)	loss 3.0834 (2.6838)	grad_norm 2.0503 (3.2733/1.5394)	mem 16099MB
[2025-01-18 10:33:07 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][70/312]	eta 0:01:59 lr 0.000170	time 0.4500 (0.4932)	model_time 0.4496 (0.4696)	loss 2.5284 (2.6717)	grad_norm 2.2825 (3.2081/1.4715)	mem 16099MB
[2025-01-18 10:33:12 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][80/312]	eta 0:01:53 lr 0.000170	time 0.4475 (0.4904)	model_time 0.4470 (0.4697)	loss 3.2977 (2.7136)	grad_norm 2.7430 (3.1223/1.4593)	mem 16099MB
[2025-01-18 10:33:16 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][90/312]	eta 0:01:48 lr 0.000169	time 0.4545 (0.4866)	model_time 0.4541 (0.4681)	loss 2.8601 (2.7142)	grad_norm 3.8895 (3.0635/1.4284)	mem 16099MB
[2025-01-18 10:33:21 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][100/312]	eta 0:01:42 lr 0.000169	time 0.4456 (0.4854)	model_time 0.4452 (0.4687)	loss 2.0850 (2.7007)	grad_norm 1.3249 (2.9845/1.4039)	mem 16099MB
[2025-01-18 10:33:26 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][110/312]	eta 0:01:37 lr 0.000169	time 0.5424 (0.4843)	model_time 0.5422 (0.4691)	loss 3.2410 (2.7057)	grad_norm 2.9673 (3.0020/1.3817)	mem 16099MB
[2025-01-18 10:33:30 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][120/312]	eta 0:01:32 lr 0.000169	time 0.4555 (0.4817)	model_time 0.4550 (0.4677)	loss 2.8296 (2.7010)	grad_norm 2.5393 (3.0016/1.3919)	mem 16099MB
[2025-01-18 10:33:35 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][130/312]	eta 0:01:27 lr 0.000168	time 0.4484 (0.4802)	model_time 0.4480 (0.4672)	loss 1.6484 (2.6961)	grad_norm 4.4264 (2.9910/1.3839)	mem 16099MB
[2025-01-18 10:33:40 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][140/312]	eta 0:01:22 lr 0.000168	time 0.4536 (0.4804)	model_time 0.4535 (0.4683)	loss 2.7369 (2.6754)	grad_norm 3.0020 (3.0164/1.4037)	mem 16099MB
[2025-01-18 10:33:44 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][150/312]	eta 0:01:17 lr 0.000168	time 0.5334 (0.4796)	model_time 0.5333 (0.4683)	loss 3.3840 (2.6939)	grad_norm 2.0836 (2.9885/1.3761)	mem 16099MB
[2025-01-18 10:33:49 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][160/312]	eta 0:01:12 lr 0.000168	time 0.4499 (0.4790)	model_time 0.4495 (0.4684)	loss 3.2426 (2.6902)	grad_norm 2.8066 (2.9801/1.3570)	mem 16099MB
[2025-01-18 10:33:54 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][170/312]	eta 0:01:07 lr 0.000167	time 0.4494 (0.4779)	model_time 0.4492 (0.4679)	loss 2.9143 (2.7019)	grad_norm 3.6898 (2.9544/1.3318)	mem 16099MB
[2025-01-18 10:33:58 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][180/312]	eta 0:01:02 lr 0.000167	time 0.4522 (0.4769)	model_time 0.4520 (0.4674)	loss 2.6141 (2.7112)	grad_norm 5.5517 (2.9701/1.3294)	mem 16099MB
[2025-01-18 10:34:03 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][190/312]	eta 0:00:58 lr 0.000167	time 0.4437 (0.4777)	model_time 0.4433 (0.4687)	loss 1.8375 (2.7077)	grad_norm 3.0346 (2.9616/1.3155)	mem 16099MB
[2025-01-18 10:34:08 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][200/312]	eta 0:00:53 lr 0.000167	time 0.4534 (0.4766)	model_time 0.4532 (0.4680)	loss 2.6446 (2.7128)	grad_norm 2.3886 (2.9773/1.3209)	mem 16099MB
[2025-01-18 10:34:12 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][210/312]	eta 0:00:48 lr 0.000167	time 0.5365 (0.4760)	model_time 0.5361 (0.4678)	loss 1.9202 (2.7045)	grad_norm 1.7281 (3.0014/1.3284)	mem 16099MB
[2025-01-18 10:34:17 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][220/312]	eta 0:00:43 lr 0.000166	time 0.4509 (0.4753)	model_time 0.4507 (0.4675)	loss 2.6581 (2.7095)	grad_norm 1.9890 (3.0122/1.3358)	mem 16099MB
[2025-01-18 10:34:22 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][230/312]	eta 0:00:38 lr 0.000166	time 0.4484 (0.4747)	model_time 0.4479 (0.4671)	loss 2.3329 (2.7138)	grad_norm 5.2360 (3.0133/1.3363)	mem 16099MB
[2025-01-18 10:34:26 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][240/312]	eta 0:00:34 lr 0.000166	time 0.4502 (0.4737)	model_time 0.4498 (0.4664)	loss 3.2025 (2.7012)	grad_norm 2.2434 (2.9968/1.3349)	mem 16099MB
[2025-01-18 10:34:31 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][250/312]	eta 0:00:29 lr 0.000166	time 0.4515 (0.4747)	model_time 0.4511 (0.4677)	loss 3.1431 (2.7109)	grad_norm 2.1706 (2.9692/1.3207)	mem 16099MB
[2025-01-18 10:34:36 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][260/312]	eta 0:00:24 lr 0.000165	time 0.4418 (0.4753)	model_time 0.4416 (0.4686)	loss 3.0647 (2.7162)	grad_norm 1.0655 (2.9366/1.3170)	mem 16099MB
[2025-01-18 10:34:41 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][270/312]	eta 0:00:19 lr 0.000165	time 0.4553 (0.4749)	model_time 0.4551 (0.4684)	loss 2.5007 (2.7125)	grad_norm 1.4931 (2.9000/1.3091)	mem 16099MB
[2025-01-18 10:34:45 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][280/312]	eta 0:00:15 lr 0.000165	time 0.4460 (0.4747)	model_time 0.4455 (0.4684)	loss 2.9394 (2.7080)	grad_norm 3.5313 (2.8741/1.2981)	mem 16099MB
[2025-01-18 10:34:50 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][290/312]	eta 0:00:10 lr 0.000165	time 0.4500 (0.4746)	model_time 0.4498 (0.4686)	loss 1.8289 (2.7092)	grad_norm 2.5081 (2.8689/1.2912)	mem 16099MB
[2025-01-18 10:34:55 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][300/312]	eta 0:00:05 lr 0.000164	time 0.4388 (0.4742)	model_time 0.4386 (0.4683)	loss 2.8613 (2.7081)	grad_norm 4.9859 (2.8690/1.2956)	mem 16099MB
[2025-01-18 10:34:59 internimage_t_1k_224] (main.py 510): INFO Train: [265/300][310/312]	eta 0:00:00 lr 0.000164	time 0.4368 (0.4734)	model_time 0.4367 (0.4678)	loss 2.9660 (2.7085)	grad_norm 4.7397 (2.8713/1.2848)	mem 16099MB
[2025-01-18 10:35:00 internimage_t_1k_224] (main.py 519): INFO EPOCH 265 training takes 0:02:27
[2025-01-18 10:35:00 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_265.pth saving......
[2025-01-18 10:35:01 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_265.pth saved !!!
[2025-01-18 10:35:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.450 (7.450)	Loss 0.7151 (0.7151)	Acc@1 85.205 (85.205)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 10:35:12 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.012)	Loss 0.9840 (0.8239)	Acc@1 78.125 (83.046)	Acc@5 95.312 (96.338)	Mem 16099MB
[2025-01-18 10:35:12 internimage_t_1k_224] (main.py 575): INFO [Epoch:265] * Acc@1 82.889 Acc@5 96.337
[2025-01-18 10:35:12 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.9%
[2025-01-18 10:35:12 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.89%
[2025-01-18 10:35:20 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.351 (8.351)	Loss 0.7238 (0.7238)	Acc@1 85.645 (85.645)	Acc@5 97.754 (97.754)	Mem 16099MB
[2025-01-18 10:35:24 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.125)	Loss 0.9556 (0.8255)	Acc@1 79.761 (83.518)	Acc@5 95.532 (96.578)	Mem 16099MB
[2025-01-18 10:35:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:265] * Acc@1 83.381 Acc@5 96.583
[2025-01-18 10:35:25 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.4%
[2025-01-18 10:35:25 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.38%
[2025-01-18 10:35:28 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][0/312]	eta 0:16:02 lr 0.000164	time 3.0853 (3.0853)	model_time 1.2556 (1.2556)	loss 3.2145 (3.2145)	grad_norm 4.1723 (4.1723/0.0000)	mem 16099MB
[2025-01-18 10:35:32 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][10/312]	eta 0:03:34 lr 0.000164	time 0.4553 (0.7104)	model_time 0.4549 (0.5436)	loss 2.8213 (2.7815)	grad_norm 5.4533 (4.0884/0.9791)	mem 16099MB
[2025-01-18 10:35:37 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][20/312]	eta 0:02:52 lr 0.000164	time 0.4504 (0.5891)	model_time 0.4503 (0.5017)	loss 2.8868 (2.6715)	grad_norm 1.7487 (3.5290/1.1775)	mem 16099MB
[2025-01-18 10:35:42 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][30/312]	eta 0:02:34 lr 0.000163	time 0.4398 (0.5482)	model_time 0.4394 (0.4888)	loss 2.2871 (2.6527)	grad_norm 2.2990 (3.1966/1.1501)	mem 16099MB
[2025-01-18 10:35:46 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][40/312]	eta 0:02:23 lr 0.000163	time 0.4496 (0.5258)	model_time 0.4494 (0.4808)	loss 3.2484 (2.6516)	grad_norm 1.7200 (3.2999/1.3972)	mem 16099MB
[2025-01-18 10:35:51 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][50/312]	eta 0:02:15 lr 0.000163	time 0.4577 (0.5158)	model_time 0.4573 (0.4795)	loss 2.8407 (2.6358)	grad_norm 2.5504 (3.1584/1.3335)	mem 16099MB
[2025-01-18 10:35:56 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][60/312]	eta 0:02:08 lr 0.000163	time 0.4548 (0.5084)	model_time 0.4544 (0.4781)	loss 2.3633 (2.6300)	grad_norm 2.3648 (3.0149/1.2849)	mem 16099MB
[2025-01-18 10:36:00 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][70/312]	eta 0:02:01 lr 0.000163	time 0.4732 (0.5016)	model_time 0.4730 (0.4754)	loss 1.9880 (2.5987)	grad_norm 1.3194 (2.8841/1.2826)	mem 16099MB
[2025-01-18 10:36:05 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][80/312]	eta 0:01:55 lr 0.000162	time 0.4555 (0.4969)	model_time 0.4551 (0.4740)	loss 2.9241 (2.6335)	grad_norm 1.4956 (2.8718/1.2781)	mem 16099MB
[2025-01-18 10:36:09 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][90/312]	eta 0:01:49 lr 0.000162	time 0.5045 (0.4937)	model_time 0.5041 (0.4732)	loss 2.8119 (2.6468)	grad_norm 2.2887 (2.9409/1.3148)	mem 16099MB
[2025-01-18 10:36:14 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][100/312]	eta 0:01:44 lr 0.000162	time 0.4630 (0.4910)	model_time 0.4628 (0.4725)	loss 3.1272 (2.6615)	grad_norm 2.9307 (2.9425/1.2898)	mem 16099MB
[2025-01-18 10:36:19 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][110/312]	eta 0:01:38 lr 0.000162	time 0.4551 (0.4876)	model_time 0.4550 (0.4707)	loss 3.0539 (2.6558)	grad_norm 3.3813 (2.9011/1.2781)	mem 16099MB
[2025-01-18 10:36:23 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][120/312]	eta 0:01:33 lr 0.000161	time 0.4507 (0.4847)	model_time 0.4506 (0.4692)	loss 2.1800 (2.6485)	grad_norm 4.2453 (2.9003/1.2560)	mem 16099MB
[2025-01-18 10:36:28 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][130/312]	eta 0:01:27 lr 0.000161	time 0.4575 (0.4827)	model_time 0.4570 (0.4684)	loss 2.5019 (2.6646)	grad_norm 1.4199 (2.8642/1.2327)	mem 16099MB
[2025-01-18 10:36:33 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][140/312]	eta 0:01:23 lr 0.000161	time 0.4647 (0.4837)	model_time 0.4642 (0.4703)	loss 2.9705 (2.6750)	grad_norm 5.8474 (2.8907/1.2446)	mem 16099MB
[2025-01-18 10:36:38 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][150/312]	eta 0:01:18 lr 0.000161	time 0.4420 (0.4847)	model_time 0.4419 (0.4722)	loss 3.0718 (2.6805)	grad_norm 4.1187 (2.8950/1.2275)	mem 16099MB
[2025-01-18 10:36:43 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][160/312]	eta 0:01:13 lr 0.000161	time 0.4438 (0.4845)	model_time 0.4434 (0.4728)	loss 3.0685 (2.6901)	grad_norm 4.5106 (2.9435/1.2438)	mem 16099MB
[2025-01-18 10:36:47 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][170/312]	eta 0:01:08 lr 0.000160	time 0.4574 (0.4838)	model_time 0.4569 (0.4727)	loss 3.1514 (2.6931)	grad_norm 4.7452 (3.0194/1.2906)	mem 16099MB
[2025-01-18 10:36:52 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][180/312]	eta 0:01:03 lr 0.000160	time 0.4535 (0.4820)	model_time 0.4531 (0.4715)	loss 3.2419 (2.7023)	grad_norm 1.6986 (2.9629/1.2853)	mem 16099MB
[2025-01-18 10:36:56 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][190/312]	eta 0:00:58 lr 0.000160	time 0.4458 (0.4806)	model_time 0.4453 (0.4706)	loss 2.7901 (2.6873)	grad_norm 1.6028 (2.9739/1.2937)	mem 16099MB
[2025-01-18 10:37:01 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][200/312]	eta 0:00:53 lr 0.000160	time 0.5447 (0.4802)	model_time 0.5445 (0.4707)	loss 2.9266 (2.6938)	grad_norm 2.5188 (2.9323/1.2899)	mem 16099MB
[2025-01-18 10:37:06 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][210/312]	eta 0:00:48 lr 0.000159	time 0.4446 (0.4790)	model_time 0.4444 (0.4699)	loss 3.1504 (2.6964)	grad_norm 1.8114 (2.9012/1.2717)	mem 16099MB
[2025-01-18 10:37:10 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][220/312]	eta 0:00:43 lr 0.000159	time 0.4525 (0.4779)	model_time 0.4521 (0.4693)	loss 2.9437 (2.7042)	grad_norm 3.6139 (2.8761/1.2667)	mem 16099MB
[2025-01-18 10:37:15 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][230/312]	eta 0:00:39 lr 0.000159	time 0.4672 (0.4773)	model_time 0.4667 (0.4690)	loss 3.2402 (2.7074)	grad_norm 3.1526 (2.8505/1.2495)	mem 16099MB
[2025-01-18 10:37:19 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][240/312]	eta 0:00:34 lr 0.000159	time 0.4534 (0.4763)	model_time 0.4533 (0.4683)	loss 3.2055 (2.7104)	grad_norm 2.7406 (2.8400/1.2418)	mem 16099MB
[2025-01-18 10:37:24 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][250/312]	eta 0:00:29 lr 0.000158	time 0.5532 (0.4759)	model_time 0.5527 (0.4682)	loss 3.2457 (2.7126)	grad_norm 2.4404 (2.8150/1.2287)	mem 16099MB
[2025-01-18 10:37:29 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][260/312]	eta 0:00:24 lr 0.000158	time 0.4585 (0.4755)	model_time 0.4583 (0.4681)	loss 1.9242 (2.7032)	grad_norm 2.6167 (2.7926/1.2156)	mem 16099MB
[2025-01-18 10:37:33 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][270/312]	eta 0:00:19 lr 0.000158	time 0.4409 (0.4749)	model_time 0.4404 (0.4678)	loss 2.9473 (2.7112)	grad_norm 1.7734 (2.7968/1.2165)	mem 16099MB
[2025-01-18 10:37:38 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][280/312]	eta 0:00:15 lr 0.000158	time 0.4439 (0.4743)	model_time 0.4434 (0.4674)	loss 2.8853 (2.7137)	grad_norm 5.4066 (2.7963/1.2243)	mem 16099MB
[2025-01-18 10:37:43 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][290/312]	eta 0:00:10 lr 0.000158	time 0.4527 (0.4742)	model_time 0.4523 (0.4675)	loss 2.8806 (2.7178)	grad_norm 3.2794 (2.7870/1.2196)	mem 16099MB
[2025-01-18 10:37:47 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][300/312]	eta 0:00:05 lr 0.000157	time 0.4385 (0.4736)	model_time 0.4384 (0.4672)	loss 1.8346 (2.7106)	grad_norm 2.4066 (2.7712/1.2113)	mem 16099MB
[2025-01-18 10:37:52 internimage_t_1k_224] (main.py 510): INFO Train: [266/300][310/312]	eta 0:00:00 lr 0.000157	time 0.4396 (0.4732)	model_time 0.4395 (0.4669)	loss 2.3667 (2.7086)	grad_norm 1.9485 (2.7371/1.1967)	mem 16099MB
[2025-01-18 10:37:52 internimage_t_1k_224] (main.py 519): INFO EPOCH 266 training takes 0:02:27
[2025-01-18 10:37:52 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_266.pth saving......
[2025-01-18 10:37:53 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_266.pth saved !!!
[2025-01-18 10:38:01 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.514 (7.514)	Loss 0.7412 (0.7412)	Acc@1 85.229 (85.229)	Acc@5 97.461 (97.461)	Mem 16099MB
[2025-01-18 10:38:04 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.004)	Loss 1.0046 (0.8469)	Acc@1 77.832 (82.963)	Acc@5 95.361 (96.327)	Mem 16099MB
[2025-01-18 10:38:05 internimage_t_1k_224] (main.py 575): INFO [Epoch:266] * Acc@1 82.823 Acc@5 96.301
[2025-01-18 10:38:05 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.8%
[2025-01-18 10:38:05 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.89%
[2025-01-18 10:38:13 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.299 (8.299)	Loss 0.7234 (0.7234)	Acc@1 85.645 (85.645)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:38:17 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.122)	Loss 0.9553 (0.8250)	Acc@1 79.761 (83.525)	Acc@5 95.557 (96.575)	Mem 16099MB
[2025-01-18 10:38:17 internimage_t_1k_224] (main.py 575): INFO [Epoch:266] * Acc@1 83.391 Acc@5 96.575
[2025-01-18 10:38:17 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.4%
[2025-01-18 10:38:17 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:38:18 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:38:18 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.39%
[2025-01-18 10:38:21 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][0/312]	eta 0:13:42 lr 0.000157	time 2.6365 (2.6365)	model_time 0.4607 (0.4607)	loss 3.1213 (3.1213)	grad_norm 2.7391 (2.7391/0.0000)	mem 16099MB
[2025-01-18 10:38:26 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][10/312]	eta 0:03:19 lr 0.000157	time 0.4588 (0.6595)	model_time 0.4586 (0.4613)	loss 3.1166 (2.7612)	grad_norm 2.2028 (2.9389/1.4587)	mem 16099MB
[2025-01-18 10:38:31 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][20/312]	eta 0:02:47 lr 0.000157	time 0.5352 (0.5720)	model_time 0.5350 (0.4680)	loss 3.2461 (2.7626)	grad_norm 3.2019 (2.9376/1.2759)	mem 16099MB
[2025-01-18 10:38:35 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][30/312]	eta 0:02:32 lr 0.000156	time 0.4688 (0.5394)	model_time 0.4686 (0.4689)	loss 2.3470 (2.6564)	grad_norm 5.7884 (3.6222/1.8912)	mem 16099MB
[2025-01-18 10:38:40 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][40/312]	eta 0:02:20 lr 0.000156	time 0.4625 (0.5181)	model_time 0.4620 (0.4646)	loss 2.8669 (2.6765)	grad_norm 2.0887 (3.3045/1.7476)	mem 16099MB
[2025-01-18 10:38:44 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][50/312]	eta 0:02:12 lr 0.000156	time 0.4449 (0.5061)	model_time 0.4447 (0.4631)	loss 2.2734 (2.6709)	grad_norm 4.5621 (3.1936/1.6574)	mem 16099MB
[2025-01-18 10:38:49 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][60/312]	eta 0:02:06 lr 0.000156	time 0.5286 (0.5008)	model_time 0.5282 (0.4648)	loss 1.9506 (2.6456)	grad_norm 3.7122 (3.0984/1.5870)	mem 16099MB
[2025-01-18 10:38:54 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][70/312]	eta 0:01:59 lr 0.000155	time 0.4607 (0.4942)	model_time 0.4603 (0.4632)	loss 2.9285 (2.6430)	grad_norm 3.2870 (3.0872/1.5441)	mem 16099MB
[2025-01-18 10:38:58 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][80/312]	eta 0:01:53 lr 0.000155	time 0.4475 (0.4908)	model_time 0.4474 (0.4636)	loss 2.6789 (2.6239)	grad_norm 5.5245 (3.2396/1.6088)	mem 16099MB
[2025-01-18 10:39:03 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][90/312]	eta 0:01:48 lr 0.000155	time 0.5283 (0.4877)	model_time 0.5281 (0.4635)	loss 3.1114 (2.6426)	grad_norm 2.6139 (3.1436/1.5680)	mem 16099MB
[2025-01-18 10:39:07 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][100/312]	eta 0:01:42 lr 0.000155	time 0.4466 (0.4851)	model_time 0.4462 (0.4632)	loss 2.5543 (2.6439)	grad_norm 1.5407 (3.0911/1.5113)	mem 16099MB
[2025-01-18 10:39:12 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][110/312]	eta 0:01:37 lr 0.000155	time 0.4515 (0.4831)	model_time 0.4514 (0.4631)	loss 3.1181 (2.6608)	grad_norm 3.1328 (3.0308/1.4826)	mem 16099MB
[2025-01-18 10:39:17 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][120/312]	eta 0:01:32 lr 0.000154	time 0.5438 (0.4824)	model_time 0.5433 (0.4640)	loss 2.7814 (2.6699)	grad_norm 2.6488 (2.9995/1.4537)	mem 16099MB
[2025-01-18 10:39:22 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][130/312]	eta 0:01:27 lr 0.000154	time 0.5043 (0.4813)	model_time 0.5042 (0.4643)	loss 1.8324 (2.6656)	grad_norm 1.2470 (2.9322/1.4276)	mem 16099MB
[2025-01-18 10:39:26 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][140/312]	eta 0:01:22 lr 0.000154	time 0.4512 (0.4813)	model_time 0.4510 (0.4656)	loss 3.0380 (2.6569)	grad_norm 3.5683 (2.8878/1.4001)	mem 16099MB
[2025-01-18 10:39:31 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][150/312]	eta 0:01:17 lr 0.000154	time 0.4504 (0.4803)	model_time 0.4502 (0.4655)	loss 2.6647 (2.6614)	grad_norm 1.5319 (2.8323/1.3787)	mem 16099MB
[2025-01-18 10:39:36 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][160/312]	eta 0:01:13 lr 0.000153	time 0.4553 (0.4808)	model_time 0.4552 (0.4669)	loss 3.0201 (2.6848)	grad_norm 2.4695 (2.8736/1.3908)	mem 16099MB
[2025-01-18 10:39:40 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][170/312]	eta 0:01:08 lr 0.000153	time 0.4465 (0.4795)	model_time 0.4460 (0.4664)	loss 3.1440 (2.6853)	grad_norm 2.5720 (2.8532/1.3602)	mem 16099MB
[2025-01-18 10:39:45 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][180/312]	eta 0:01:03 lr 0.000153	time 0.4595 (0.4782)	model_time 0.4593 (0.4658)	loss 2.5070 (2.6935)	grad_norm 1.4194 (2.8342/1.3706)	mem 16099MB
[2025-01-18 10:39:50 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][190/312]	eta 0:00:58 lr 0.000153	time 0.4532 (0.4769)	model_time 0.4530 (0.4651)	loss 2.5470 (2.6896)	grad_norm 1.3708 (2.8570/1.3663)	mem 16099MB
[2025-01-18 10:39:54 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][200/312]	eta 0:00:53 lr 0.000153	time 0.4511 (0.4762)	model_time 0.4509 (0.4650)	loss 2.6723 (2.7001)	grad_norm 2.9538 (2.8351/1.3434)	mem 16099MB
[2025-01-18 10:39:59 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][210/312]	eta 0:00:48 lr 0.000152	time 0.4453 (0.4764)	model_time 0.4449 (0.4657)	loss 2.6341 (2.6956)	grad_norm 2.6217 (2.8143/1.3203)	mem 16099MB
[2025-01-18 10:40:04 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][220/312]	eta 0:00:43 lr 0.000152	time 0.4544 (0.4755)	model_time 0.4540 (0.4653)	loss 2.9547 (2.6890)	grad_norm 4.8646 (2.8503/1.3191)	mem 16099MB
[2025-01-18 10:40:08 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][230/312]	eta 0:00:38 lr 0.000152	time 0.4622 (0.4750)	model_time 0.4617 (0.4652)	loss 1.8186 (2.6919)	grad_norm 2.3125 (2.8514/1.3209)	mem 16099MB
[2025-01-18 10:40:13 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][240/312]	eta 0:00:34 lr 0.000152	time 0.4556 (0.4742)	model_time 0.4555 (0.4648)	loss 2.2111 (2.6868)	grad_norm 5.8768 (2.8637/1.3245)	mem 16099MB
[2025-01-18 10:40:17 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][250/312]	eta 0:00:29 lr 0.000151	time 0.4514 (0.4737)	model_time 0.4510 (0.4647)	loss 3.4200 (2.6886)	grad_norm 3.9040 (2.8886/1.3280)	mem 16099MB
[2025-01-18 10:40:22 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][260/312]	eta 0:00:24 lr 0.000151	time 0.4558 (0.4734)	model_time 0.4553 (0.4646)	loss 2.7937 (2.6900)	grad_norm 2.9384 (2.9263/1.3770)	mem 16099MB
[2025-01-18 10:40:27 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][270/312]	eta 0:00:19 lr 0.000151	time 0.4639 (0.4727)	model_time 0.4634 (0.4643)	loss 3.0436 (2.6919)	grad_norm 2.8027 (2.9136/1.3759)	mem 16099MB
[2025-01-18 10:40:31 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][280/312]	eta 0:00:15 lr 0.000151	time 0.4640 (0.4722)	model_time 0.4638 (0.4641)	loss 2.6436 (2.6923)	grad_norm 3.3365 (2.9243/1.3654)	mem 16099MB
[2025-01-18 10:40:36 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][290/312]	eta 0:00:10 lr 0.000151	time 0.4444 (0.4721)	model_time 0.4442 (0.4643)	loss 2.5186 (2.6994)	grad_norm 3.0182 (2.9209/1.3513)	mem 16099MB
[2025-01-18 10:40:41 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][300/312]	eta 0:00:05 lr 0.000150	time 0.4409 (0.4719)	model_time 0.4408 (0.4643)	loss 2.8281 (2.6972)	grad_norm 6.0650 (2.9463/1.3717)	mem 16099MB
[2025-01-18 10:40:45 internimage_t_1k_224] (main.py 510): INFO Train: [267/300][310/312]	eta 0:00:00 lr 0.000150	time 0.5209 (0.4715)	model_time 0.5208 (0.4641)	loss 2.6973 (2.7024)	grad_norm 1.6975 (2.9479/1.3775)	mem 16099MB
[2025-01-18 10:40:46 internimage_t_1k_224] (main.py 519): INFO EPOCH 267 training takes 0:02:27
[2025-01-18 10:40:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_267.pth saving......
[2025-01-18 10:40:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_267.pth saved !!!
[2025-01-18 10:40:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.369 (7.369)	Loss 0.7227 (0.7227)	Acc@1 85.376 (85.376)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 10:40:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.012)	Loss 0.9617 (0.8220)	Acc@1 78.979 (83.094)	Acc@5 95.410 (96.302)	Mem 16099MB
[2025-01-18 10:40:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:267] * Acc@1 82.919 Acc@5 96.303
[2025-01-18 10:40:58 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.9%
[2025-01-18 10:40:58 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 10:40:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 10:40:59 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.92%
[2025-01-18 10:41:07 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.486 (7.486)	Loss 0.7228 (0.7228)	Acc@1 85.693 (85.693)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:41:10 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.018)	Loss 0.9542 (0.8240)	Acc@1 79.761 (83.540)	Acc@5 95.581 (96.580)	Mem 16099MB
[2025-01-18 10:41:11 internimage_t_1k_224] (main.py 575): INFO [Epoch:267] * Acc@1 83.405 Acc@5 96.579
[2025-01-18 10:41:11 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.4%
[2025-01-18 10:41:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:41:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:41:12 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.41%
[2025-01-18 10:41:15 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][0/312]	eta 0:14:06 lr 0.000150	time 2.7117 (2.7117)	model_time 0.4706 (0.4706)	loss 2.3069 (2.3069)	grad_norm 5.5917 (5.5917/0.0000)	mem 16099MB
[2025-01-18 10:41:19 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][10/312]	eta 0:03:21 lr 0.000150	time 0.4548 (0.6659)	model_time 0.4544 (0.4618)	loss 2.7492 (2.8327)	grad_norm 1.8702 (2.8039/1.1676)	mem 16099MB
[2025-01-18 10:41:24 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][20/312]	eta 0:02:48 lr 0.000150	time 0.4658 (0.5765)	model_time 0.4653 (0.4694)	loss 2.7966 (2.6952)	grad_norm 3.0856 (2.6067/0.9424)	mem 16099MB
[2025-01-18 10:41:29 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][30/312]	eta 0:02:31 lr 0.000149	time 0.4518 (0.5379)	model_time 0.4514 (0.4652)	loss 2.8044 (2.6614)	grad_norm 3.1555 (2.6572/0.9305)	mem 16099MB
[2025-01-18 10:41:33 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][40/312]	eta 0:02:21 lr 0.000149	time 0.4404 (0.5212)	model_time 0.4403 (0.4661)	loss 2.9796 (2.6627)	grad_norm 3.0476 (2.7053/1.0302)	mem 16099MB
[2025-01-18 10:41:38 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][50/312]	eta 0:02:13 lr 0.000149	time 0.4726 (0.5080)	model_time 0.4721 (0.4637)	loss 2.9041 (2.7069)	grad_norm 2.7337 (2.8261/1.2224)	mem 16099MB
[2025-01-18 10:41:43 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][60/312]	eta 0:02:06 lr 0.000149	time 0.4497 (0.5001)	model_time 0.4493 (0.4630)	loss 2.8977 (2.7189)	grad_norm 4.2846 (2.8402/1.2016)	mem 16099MB
[2025-01-18 10:41:47 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][70/312]	eta 0:01:59 lr 0.000149	time 0.4507 (0.4935)	model_time 0.4502 (0.4616)	loss 2.6125 (2.7182)	grad_norm 1.8653 (2.6922/1.1824)	mem 16099MB
[2025-01-18 10:41:52 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][80/312]	eta 0:01:53 lr 0.000148	time 0.4639 (0.4904)	model_time 0.4637 (0.4623)	loss 2.8609 (2.7216)	grad_norm 3.0476 (2.6966/1.1393)	mem 16099MB
[2025-01-18 10:41:57 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][90/312]	eta 0:01:48 lr 0.000148	time 0.5603 (0.4885)	model_time 0.5601 (0.4635)	loss 1.5522 (2.6984)	grad_norm 4.7407 (2.7939/1.2065)	mem 16099MB
[2025-01-18 10:42:01 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][100/312]	eta 0:01:42 lr 0.000148	time 0.4539 (0.4856)	model_time 0.4534 (0.4630)	loss 2.8863 (2.6945)	grad_norm 7.8187 (2.8544/1.2964)	mem 16099MB
[2025-01-18 10:42:06 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][110/312]	eta 0:01:37 lr 0.000148	time 0.4492 (0.4846)	model_time 0.4488 (0.4640)	loss 2.5030 (2.6896)	grad_norm 1.7620 (2.8861/1.3450)	mem 16099MB
[2025-01-18 10:42:10 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][120/312]	eta 0:01:32 lr 0.000148	time 0.4496 (0.4824)	model_time 0.4494 (0.4635)	loss 2.6552 (2.6905)	grad_norm 2.4945 (2.8951/1.3490)	mem 16099MB
[2025-01-18 10:42:15 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][130/312]	eta 0:01:27 lr 0.000147	time 0.4490 (0.4801)	model_time 0.4488 (0.4626)	loss 2.6862 (2.6956)	grad_norm 3.8589 (2.8660/1.3198)	mem 16099MB
[2025-01-18 10:42:20 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][140/312]	eta 0:01:22 lr 0.000147	time 0.4469 (0.4786)	model_time 0.4465 (0.4623)	loss 3.2717 (2.6993)	grad_norm 2.8617 (2.8077/1.2978)	mem 16099MB
[2025-01-18 10:42:24 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][150/312]	eta 0:01:17 lr 0.000147	time 0.4535 (0.4793)	model_time 0.4531 (0.4640)	loss 2.9549 (2.6982)	grad_norm 3.9068 (2.8133/1.2812)	mem 16099MB
[2025-01-18 10:42:29 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][160/312]	eta 0:01:12 lr 0.000147	time 0.4447 (0.4781)	model_time 0.4442 (0.4637)	loss 2.8051 (2.7028)	grad_norm 2.3394 (2.7852/1.2554)	mem 16099MB
[2025-01-18 10:42:34 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][170/312]	eta 0:01:07 lr 0.000146	time 0.4455 (0.4774)	model_time 0.4454 (0.4639)	loss 3.1194 (2.7026)	grad_norm 7.7186 (2.8609/1.3687)	mem 16099MB
[2025-01-18 10:42:38 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][180/312]	eta 0:01:02 lr 0.000146	time 0.4456 (0.4772)	model_time 0.4454 (0.4644)	loss 2.9454 (2.6971)	grad_norm 2.6626 (2.9330/1.4536)	mem 16099MB
[2025-01-18 10:42:43 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][190/312]	eta 0:00:58 lr 0.000146	time 0.4617 (0.4763)	model_time 0.4615 (0.4641)	loss 1.9563 (2.7001)	grad_norm 1.7829 (2.9478/1.4595)	mem 16099MB
[2025-01-18 10:42:48 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][200/312]	eta 0:00:53 lr 0.000146	time 0.5022 (0.4759)	model_time 0.5020 (0.4643)	loss 3.0380 (2.7108)	grad_norm 1.8844 (2.9126/1.4464)	mem 16099MB
[2025-01-18 10:42:52 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][210/312]	eta 0:00:48 lr 0.000146	time 0.4403 (0.4753)	model_time 0.4398 (0.4643)	loss 2.2139 (2.7149)	grad_norm 2.2288 (2.8799/1.4297)	mem 16099MB
[2025-01-18 10:42:57 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][220/312]	eta 0:00:43 lr 0.000145	time 0.4589 (0.4747)	model_time 0.4585 (0.4641)	loss 3.2644 (2.7064)	grad_norm 1.5622 (2.8971/1.4423)	mem 16099MB
[2025-01-18 10:43:02 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][230/312]	eta 0:00:38 lr 0.000145	time 0.5386 (0.4747)	model_time 0.5384 (0.4646)	loss 3.0516 (2.7096)	grad_norm 5.6418 (2.9011/1.4452)	mem 16099MB
[2025-01-18 10:43:06 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][240/312]	eta 0:00:34 lr 0.000145	time 0.4523 (0.4741)	model_time 0.4521 (0.4644)	loss 2.1395 (2.7007)	grad_norm 3.8039 (2.9419/1.4480)	mem 16099MB
[2025-01-18 10:43:11 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][250/312]	eta 0:00:29 lr 0.000145	time 0.4592 (0.4741)	model_time 0.4588 (0.4647)	loss 1.8238 (2.6960)	grad_norm 1.9054 (2.9218/1.4365)	mem 16099MB
[2025-01-18 10:43:16 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][260/312]	eta 0:00:24 lr 0.000145	time 0.4556 (0.4742)	model_time 0.4554 (0.4652)	loss 2.9316 (2.7052)	grad_norm 2.6084 (2.9284/1.4227)	mem 16099MB
[2025-01-18 10:43:20 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][270/312]	eta 0:00:19 lr 0.000144	time 0.4457 (0.4737)	model_time 0.4452 (0.4650)	loss 2.7733 (2.7090)	grad_norm 2.4435 (2.9056/1.4043)	mem 16099MB
[2025-01-18 10:43:25 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][280/312]	eta 0:00:15 lr 0.000144	time 0.5018 (0.4740)	model_time 0.5017 (0.4656)	loss 2.9155 (2.7090)	grad_norm 3.1333 (2.9004/1.3968)	mem 16099MB
[2025-01-18 10:43:30 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][290/312]	eta 0:00:10 lr 0.000144	time 0.4465 (0.4735)	model_time 0.4463 (0.4654)	loss 2.0860 (2.6984)	grad_norm 4.3494 (2.9035/1.3866)	mem 16099MB
[2025-01-18 10:43:34 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][300/312]	eta 0:00:05 lr 0.000144	time 0.4419 (0.4728)	model_time 0.4418 (0.4650)	loss 2.0651 (2.6951)	grad_norm 2.0266 (2.8864/1.3728)	mem 16099MB
[2025-01-18 10:43:39 internimage_t_1k_224] (main.py 510): INFO Train: [268/300][310/312]	eta 0:00:00 lr 0.000143	time 0.5243 (0.4722)	model_time 0.5242 (0.4646)	loss 2.4277 (2.6925)	grad_norm 2.2119 (2.8714/1.3668)	mem 16099MB
[2025-01-18 10:43:39 internimage_t_1k_224] (main.py 519): INFO EPOCH 268 training takes 0:02:27
[2025-01-18 10:43:39 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_268.pth saving......
[2025-01-18 10:43:41 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_268.pth saved !!!
[2025-01-18 10:43:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.474 (7.474)	Loss 0.7127 (0.7127)	Acc@1 85.376 (85.376)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 10:43:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.006)	Loss 0.9520 (0.8178)	Acc@1 79.370 (83.148)	Acc@5 95.264 (96.302)	Mem 16099MB
[2025-01-18 10:43:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:268] * Acc@1 82.973 Acc@5 96.299
[2025-01-18 10:43:52 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.0%
[2025-01-18 10:43:52 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 10:43:53 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 10:43:53 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.97%
[2025-01-18 10:44:00 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.354 (7.354)	Loss 0.7224 (0.7224)	Acc@1 85.669 (85.669)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:44:04 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (0.998)	Loss 0.9536 (0.8235)	Acc@1 79.761 (83.549)	Acc@5 95.557 (96.584)	Mem 16099MB
[2025-01-18 10:44:04 internimage_t_1k_224] (main.py 575): INFO [Epoch:268] * Acc@1 83.415 Acc@5 96.579
[2025-01-18 10:44:04 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.4%
[2025-01-18 10:44:04 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:44:06 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:44:06 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.42%
[2025-01-18 10:44:08 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][0/312]	eta 0:11:50 lr 0.000143	time 2.2767 (2.2767)	model_time 0.4772 (0.4772)	loss 2.8253 (2.8253)	grad_norm 3.8859 (3.8859/0.0000)	mem 16099MB
[2025-01-18 10:44:13 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][10/312]	eta 0:03:10 lr 0.000143	time 0.4496 (0.6316)	model_time 0.4494 (0.4677)	loss 2.8117 (2.8128)	grad_norm 1.7108 (3.7739/1.5531)	mem 16099MB
[2025-01-18 10:44:17 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][20/312]	eta 0:02:40 lr 0.000143	time 0.4570 (0.5485)	model_time 0.4568 (0.4625)	loss 2.5430 (2.6653)	grad_norm 3.7434 (3.9867/1.5345)	mem 16099MB
[2025-01-18 10:44:22 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][30/312]	eta 0:02:26 lr 0.000143	time 0.4702 (0.5187)	model_time 0.4700 (0.4604)	loss 2.7041 (2.6365)	grad_norm 3.8516 (3.7026/1.3857)	mem 16099MB
[2025-01-18 10:44:26 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][40/312]	eta 0:02:17 lr 0.000143	time 0.4571 (0.5048)	model_time 0.4570 (0.4606)	loss 2.7414 (2.6569)	grad_norm 4.4051 (3.4650/1.4411)	mem 16099MB
[2025-01-18 10:44:31 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][50/312]	eta 0:02:10 lr 0.000142	time 0.4533 (0.4985)	model_time 0.4531 (0.4629)	loss 1.7432 (2.6379)	grad_norm 3.2653 (3.3096/1.3680)	mem 16099MB
[2025-01-18 10:44:36 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][60/312]	eta 0:02:04 lr 0.000142	time 0.4470 (0.4927)	model_time 0.4469 (0.4628)	loss 3.1999 (2.6627)	grad_norm 3.9724 (3.2845/1.3239)	mem 16099MB
[2025-01-18 10:44:40 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][70/312]	eta 0:01:57 lr 0.000142	time 0.4530 (0.4870)	model_time 0.4528 (0.4614)	loss 1.8762 (2.6594)	grad_norm 1.2788 (3.3620/1.4502)	mem 16099MB
[2025-01-18 10:44:45 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][80/312]	eta 0:01:52 lr 0.000142	time 0.4410 (0.4855)	model_time 0.4405 (0.4629)	loss 2.3441 (2.6593)	grad_norm 4.8697 (3.3261/1.4435)	mem 16099MB
[2025-01-18 10:44:50 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][90/312]	eta 0:01:47 lr 0.000142	time 0.4481 (0.4823)	model_time 0.4476 (0.4622)	loss 2.2648 (2.6935)	grad_norm 3.1456 (3.3004/1.4687)	mem 16099MB
[2025-01-18 10:44:54 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][100/312]	eta 0:01:42 lr 0.000141	time 0.5639 (0.4812)	model_time 0.5634 (0.4630)	loss 2.2757 (2.6786)	grad_norm 2.2005 (3.2647/1.4576)	mem 16099MB
[2025-01-18 10:44:59 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][110/312]	eta 0:01:36 lr 0.000141	time 0.4487 (0.4789)	model_time 0.4486 (0.4624)	loss 2.9501 (2.6870)	grad_norm 2.1277 (3.2608/1.4254)	mem 16099MB
[2025-01-18 10:45:03 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][120/312]	eta 0:01:31 lr 0.000141	time 0.4710 (0.4773)	model_time 0.4705 (0.4620)	loss 2.6560 (2.6962)	grad_norm 2.1051 (3.1626/1.4186)	mem 16099MB
[2025-01-18 10:45:09 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][130/312]	eta 0:01:27 lr 0.000141	time 0.5797 (0.4799)	model_time 0.5796 (0.4659)	loss 2.5770 (2.6897)	grad_norm 3.5421 (3.1233/1.3809)	mem 16099MB
[2025-01-18 10:45:13 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][140/312]	eta 0:01:22 lr 0.000140	time 0.4465 (0.4794)	model_time 0.4460 (0.4663)	loss 2.2917 (2.6784)	grad_norm 2.4343 (3.0473/1.3664)	mem 16099MB
[2025-01-18 10:45:18 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][150/312]	eta 0:01:17 lr 0.000140	time 0.4537 (0.4790)	model_time 0.4533 (0.4667)	loss 3.3943 (2.6820)	grad_norm 1.9319 (3.0166/1.3575)	mem 16099MB
[2025-01-18 10:45:23 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][160/312]	eta 0:01:12 lr 0.000140	time 0.4468 (0.4792)	model_time 0.4466 (0.4676)	loss 3.4925 (2.6945)	grad_norm 3.0407 (3.0096/1.3292)	mem 16099MB
[2025-01-18 10:45:27 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][170/312]	eta 0:01:07 lr 0.000140	time 0.4538 (0.4782)	model_time 0.4536 (0.4673)	loss 3.0799 (2.7104)	grad_norm 1.7070 (3.0122/1.3265)	mem 16099MB
[2025-01-18 10:45:32 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][180/312]	eta 0:01:02 lr 0.000140	time 0.4535 (0.4768)	model_time 0.4531 (0.4665)	loss 2.5636 (2.7041)	grad_norm 2.2824 (3.0990/1.4077)	mem 16099MB
[2025-01-18 10:45:37 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][190/312]	eta 0:00:58 lr 0.000139	time 0.5470 (0.4762)	model_time 0.5468 (0.4664)	loss 2.9157 (2.6993)	grad_norm 1.9383 (3.0862/1.3964)	mem 16099MB
[2025-01-18 10:45:41 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][200/312]	eta 0:00:53 lr 0.000139	time 0.4537 (0.4757)	model_time 0.4533 (0.4663)	loss 3.3551 (2.7000)	grad_norm 3.4882 (3.0541/1.3847)	mem 16099MB
[2025-01-18 10:45:46 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][210/312]	eta 0:00:48 lr 0.000139	time 0.4704 (0.4750)	model_time 0.4702 (0.4661)	loss 3.1487 (2.6968)	grad_norm 2.8177 (3.0264/1.3726)	mem 16099MB
[2025-01-18 10:45:51 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][220/312]	eta 0:00:43 lr 0.000139	time 0.4551 (0.4749)	model_time 0.4548 (0.4664)	loss 2.7626 (2.6954)	grad_norm 4.4744 (3.0393/1.3797)	mem 16099MB
[2025-01-18 10:45:55 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][230/312]	eta 0:00:38 lr 0.000139	time 0.4747 (0.4742)	model_time 0.4745 (0.4660)	loss 2.9473 (2.6966)	grad_norm 1.6357 (3.0231/1.3732)	mem 16099MB
[2025-01-18 10:46:00 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][240/312]	eta 0:00:34 lr 0.000138	time 0.4484 (0.4736)	model_time 0.4479 (0.4657)	loss 1.9671 (2.6951)	grad_norm 2.2225 (3.0038/1.3594)	mem 16099MB
[2025-01-18 10:46:04 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][250/312]	eta 0:00:29 lr 0.000138	time 0.4644 (0.4728)	model_time 0.4640 (0.4653)	loss 2.8275 (2.7020)	grad_norm 3.7125 (2.9992/1.3527)	mem 16099MB
[2025-01-18 10:46:09 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][260/312]	eta 0:00:24 lr 0.000138	time 0.4526 (0.4723)	model_time 0.4522 (0.4650)	loss 3.4588 (2.7026)	grad_norm 2.7305 (2.9969/1.3397)	mem 16099MB
[2025-01-18 10:46:14 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][270/312]	eta 0:00:19 lr 0.000138	time 0.4442 (0.4720)	model_time 0.4441 (0.4650)	loss 2.6643 (2.7002)	grad_norm 4.3680 (2.9832/1.3264)	mem 16099MB
[2025-01-18 10:46:18 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][280/312]	eta 0:00:15 lr 0.000138	time 0.4553 (0.4715)	model_time 0.4547 (0.4647)	loss 3.5325 (2.7085)	grad_norm 2.1297 (2.9846/1.3205)	mem 16099MB
[2025-01-18 10:46:23 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][290/312]	eta 0:00:10 lr 0.000137	time 0.4537 (0.4715)	model_time 0.4533 (0.4649)	loss 2.7690 (2.6993)	grad_norm 2.0875 (2.9771/1.3202)	mem 16099MB
[2025-01-18 10:46:28 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][300/312]	eta 0:00:05 lr 0.000137	time 0.4393 (0.4712)	model_time 0.4392 (0.4649)	loss 2.9695 (2.7037)	grad_norm 1.4561 (2.9485/1.3138)	mem 16099MB
[2025-01-18 10:46:32 internimage_t_1k_224] (main.py 510): INFO Train: [269/300][310/312]	eta 0:00:00 lr 0.000137	time 0.4405 (0.4711)	model_time 0.4404 (0.4650)	loss 2.3907 (2.7032)	grad_norm 1.9371 (2.9065/1.2816)	mem 16099MB
[2025-01-18 10:46:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 269 training takes 0:02:26
[2025-01-18 10:46:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_269.pth saving......
[2025-01-18 10:46:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_269.pth saved !!!
[2025-01-18 10:46:41 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.152 (7.152)	Loss 0.7110 (0.7110)	Acc@1 85.132 (85.132)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 10:46:45 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (0.978)	Loss 0.9729 (0.8198)	Acc@1 78.857 (83.068)	Acc@5 95.117 (96.267)	Mem 16099MB
[2025-01-18 10:46:45 internimage_t_1k_224] (main.py 575): INFO [Epoch:269] * Acc@1 82.929 Acc@5 96.281
[2025-01-18 10:46:45 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.9%
[2025-01-18 10:46:45 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.97%
[2025-01-18 10:46:53 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.180 (8.180)	Loss 0.7218 (0.7218)	Acc@1 85.693 (85.693)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:46:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.098)	Loss 0.9528 (0.8226)	Acc@1 79.688 (83.569)	Acc@5 95.508 (96.578)	Mem 16099MB
[2025-01-18 10:46:57 internimage_t_1k_224] (main.py 575): INFO [Epoch:269] * Acc@1 83.431 Acc@5 96.577
[2025-01-18 10:46:57 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.4%
[2025-01-18 10:46:57 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:46:59 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:46:59 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.43%
[2025-01-18 10:47:02 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][0/312]	eta 0:15:12 lr 0.000137	time 2.9249 (2.9249)	model_time 0.4645 (0.4645)	loss 2.7368 (2.7368)	grad_norm 1.7418 (1.7418/0.0000)	mem 16099MB
[2025-01-18 10:47:06 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][10/312]	eta 0:03:27 lr 0.000137	time 0.4539 (0.6879)	model_time 0.4534 (0.4639)	loss 3.0991 (2.6813)	grad_norm 2.4768 (2.1726/0.5759)	mem 16099MB
[2025-01-18 10:47:11 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][20/312]	eta 0:02:50 lr 0.000136	time 0.4421 (0.5846)	model_time 0.4417 (0.4671)	loss 2.9211 (2.6370)	grad_norm 1.9211 (2.7420/1.5459)	mem 16099MB
[2025-01-18 10:47:15 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][30/312]	eta 0:02:33 lr 0.000136	time 0.4578 (0.5435)	model_time 0.4576 (0.4638)	loss 2.6015 (2.6501)	grad_norm 3.6042 (3.1008/1.4678)	mem 16099MB
[2025-01-18 10:47:20 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][40/312]	eta 0:02:22 lr 0.000136	time 0.4512 (0.5243)	model_time 0.4508 (0.4639)	loss 2.8462 (2.6884)	grad_norm 2.6131 (3.1938/1.3352)	mem 16099MB
[2025-01-18 10:47:25 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][50/312]	eta 0:02:15 lr 0.000136	time 0.4437 (0.5188)	model_time 0.4435 (0.4702)	loss 3.2583 (2.7003)	grad_norm 6.0752 (3.5080/1.5223)	mem 16099MB
[2025-01-18 10:47:30 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][60/312]	eta 0:02:08 lr 0.000136	time 0.4399 (0.5080)	model_time 0.4397 (0.4673)	loss 2.3093 (2.6868)	grad_norm 8.2203 (4.0079/2.0200)	mem 16099MB
[2025-01-18 10:47:34 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][70/312]	eta 0:02:01 lr 0.000135	time 0.4419 (0.5026)	model_time 0.4415 (0.4676)	loss 2.7946 (2.7042)	grad_norm 1.4598 (4.0745/2.1133)	mem 16099MB
[2025-01-18 10:47:39 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][80/312]	eta 0:01:55 lr 0.000135	time 0.4693 (0.4967)	model_time 0.4691 (0.4660)	loss 2.8694 (2.7050)	grad_norm 1.8069 (3.9602/2.0280)	mem 16099MB
[2025-01-18 10:47:44 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][90/312]	eta 0:01:49 lr 0.000135	time 0.4592 (0.4948)	model_time 0.4590 (0.4674)	loss 2.7627 (2.7319)	grad_norm 2.9136 (3.8771/1.9817)	mem 16099MB
[2025-01-18 10:47:48 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][100/312]	eta 0:01:44 lr 0.000135	time 0.4856 (0.4913)	model_time 0.4851 (0.4666)	loss 2.8480 (2.7288)	grad_norm 3.0972 (3.7878/1.9332)	mem 16099MB
[2025-01-18 10:47:53 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][110/312]	eta 0:01:39 lr 0.000135	time 0.4475 (0.4906)	model_time 0.4473 (0.4681)	loss 2.4564 (2.7221)	grad_norm 2.2603 (3.6907/1.8977)	mem 16099MB
[2025-01-18 10:47:58 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][120/312]	eta 0:01:34 lr 0.000134	time 0.4560 (0.4901)	model_time 0.4556 (0.4693)	loss 3.1040 (2.7221)	grad_norm 2.1916 (3.5709/1.8687)	mem 16099MB
[2025-01-18 10:48:03 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][130/312]	eta 0:01:29 lr 0.000134	time 0.4486 (0.4896)	model_time 0.4484 (0.4704)	loss 2.6243 (2.7221)	grad_norm 3.9193 (3.4526/1.8556)	mem 16099MB
[2025-01-18 10:48:08 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][140/312]	eta 0:01:24 lr 0.000134	time 0.4796 (0.4907)	model_time 0.4792 (0.4728)	loss 2.2060 (2.7080)	grad_norm 3.1971 (3.4237/1.8231)	mem 16099MB
[2025-01-18 10:48:12 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][150/312]	eta 0:01:19 lr 0.000134	time 0.4840 (0.4882)	model_time 0.4838 (0.4716)	loss 3.1372 (2.7080)	grad_norm 2.3262 (3.5144/1.8959)	mem 16099MB
[2025-01-18 10:48:17 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][160/312]	eta 0:01:14 lr 0.000134	time 0.7286 (0.4883)	model_time 0.7285 (0.4726)	loss 1.8652 (2.7098)	grad_norm 2.7762 (3.4706/1.8729)	mem 16099MB
[2025-01-18 10:48:22 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][170/312]	eta 0:01:09 lr 0.000133	time 0.4505 (0.4869)	model_time 0.4501 (0.4721)	loss 3.1922 (2.7089)	grad_norm 3.6071 (3.4261/1.8365)	mem 16099MB
[2025-01-18 10:48:27 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][180/312]	eta 0:01:04 lr 0.000133	time 0.4667 (0.4870)	model_time 0.4663 (0.4730)	loss 2.8991 (2.7211)	grad_norm 2.5811 (3.4417/1.8181)	mem 16099MB
[2025-01-18 10:48:32 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][190/312]	eta 0:00:59 lr 0.000133	time 0.4655 (0.4868)	model_time 0.4654 (0.4736)	loss 2.3006 (2.7061)	grad_norm 1.2833 (3.4016/1.7936)	mem 16099MB
[2025-01-18 10:48:36 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][200/312]	eta 0:00:54 lr 0.000133	time 0.4532 (0.4854)	model_time 0.4531 (0.4728)	loss 3.1040 (2.6999)	grad_norm 1.4157 (3.3568/1.7684)	mem 16099MB
[2025-01-18 10:48:41 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][210/312]	eta 0:00:49 lr 0.000133	time 0.4551 (0.4860)	model_time 0.4550 (0.4739)	loss 2.5019 (2.6910)	grad_norm 1.4120 (3.3062/1.7532)	mem 16099MB
[2025-01-18 10:48:46 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][220/312]	eta 0:00:44 lr 0.000132	time 0.4577 (0.4849)	model_time 0.4575 (0.4734)	loss 2.8783 (2.6939)	grad_norm 2.6450 (3.2927/1.7287)	mem 16099MB
[2025-01-18 10:48:50 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][230/312]	eta 0:00:39 lr 0.000132	time 0.4586 (0.4836)	model_time 0.4585 (0.4726)	loss 3.1279 (2.6924)	grad_norm 3.2398 (3.2506/1.7066)	mem 16099MB
[2025-01-18 10:48:55 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][240/312]	eta 0:00:34 lr 0.000132	time 0.4593 (0.4827)	model_time 0.4591 (0.4721)	loss 3.2915 (2.6938)	grad_norm 1.6822 (3.2144/1.6903)	mem 16099MB
[2025-01-18 10:49:00 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][250/312]	eta 0:00:29 lr 0.000132	time 0.4553 (0.4819)	model_time 0.4549 (0.4717)	loss 1.7275 (2.6924)	grad_norm 1.4399 (3.2077/1.6729)	mem 16099MB
[2025-01-18 10:49:04 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][260/312]	eta 0:00:25 lr 0.000132	time 0.4408 (0.4822)	model_time 0.4404 (0.4724)	loss 3.1529 (2.7007)	grad_norm 1.5108 (3.1638/1.6606)	mem 16099MB
[2025-01-18 10:49:09 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][270/312]	eta 0:00:20 lr 0.000131	time 0.5200 (0.4815)	model_time 0.5198 (0.4720)	loss 3.1249 (2.7054)	grad_norm 1.9364 (3.1308/1.6407)	mem 16099MB
[2025-01-18 10:49:14 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][280/312]	eta 0:00:15 lr 0.000131	time 0.4550 (0.4815)	model_time 0.4548 (0.4723)	loss 2.0792 (2.6924)	grad_norm 3.2322 (3.1255/1.6226)	mem 16099MB
[2025-01-18 10:49:18 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][290/312]	eta 0:00:10 lr 0.000131	time 0.4408 (0.4805)	model_time 0.4403 (0.4716)	loss 2.9364 (2.6975)	grad_norm 2.8027 (3.0971/1.6077)	mem 16099MB
[2025-01-18 10:49:23 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][300/312]	eta 0:00:05 lr 0.000131	time 0.4462 (0.4800)	model_time 0.4462 (0.4714)	loss 2.7732 (2.6938)	grad_norm 3.5060 (3.0917/1.5891)	mem 16099MB
[2025-01-18 10:49:28 internimage_t_1k_224] (main.py 510): INFO Train: [270/300][310/312]	eta 0:00:00 lr 0.000131	time 0.5274 (0.4791)	model_time 0.5273 (0.4708)	loss 2.0750 (2.6945)	grad_norm 1.7547 (3.1248/1.5987)	mem 16099MB
[2025-01-18 10:49:28 internimage_t_1k_224] (main.py 519): INFO EPOCH 270 training takes 0:02:29
[2025-01-18 10:49:28 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_270.pth saving......
[2025-01-18 10:49:29 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_270.pth saved !!!
[2025-01-18 10:49:37 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.798 (7.798)	Loss 0.7140 (0.7140)	Acc@1 85.498 (85.498)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 10:49:41 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.046)	Loss 0.9692 (0.8254)	Acc@1 78.857 (83.114)	Acc@5 95.215 (96.294)	Mem 16099MB
[2025-01-18 10:49:41 internimage_t_1k_224] (main.py 575): INFO [Epoch:270] * Acc@1 82.947 Acc@5 96.315
[2025-01-18 10:49:41 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.9%
[2025-01-18 10:49:41 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.97%
[2025-01-18 10:49:49 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.576 (8.576)	Loss 0.7212 (0.7212)	Acc@1 85.693 (85.693)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:49:54 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.153)	Loss 0.9519 (0.8218)	Acc@1 79.688 (83.578)	Acc@5 95.508 (96.584)	Mem 16099MB
[2025-01-18 10:49:54 internimage_t_1k_224] (main.py 575): INFO [Epoch:270] * Acc@1 83.437 Acc@5 96.583
[2025-01-18 10:49:54 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.4%
[2025-01-18 10:49:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:49:55 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:49:55 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.44%
[2025-01-18 10:49:58 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][0/312]	eta 0:15:06 lr 0.000131	time 2.9053 (2.9053)	model_time 0.4877 (0.4877)	loss 2.1529 (2.1529)	grad_norm 4.6928 (4.6928/0.0000)	mem 16099MB
[2025-01-18 10:50:03 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][10/312]	eta 0:03:25 lr 0.000130	time 0.4521 (0.6803)	model_time 0.4519 (0.4603)	loss 3.1674 (2.6777)	grad_norm 2.3079 (2.9152/1.2263)	mem 16099MB
[2025-01-18 10:50:07 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][20/312]	eta 0:02:47 lr 0.000130	time 0.4511 (0.5731)	model_time 0.4506 (0.4577)	loss 2.0381 (2.6544)	grad_norm 1.7561 (2.4750/1.1360)	mem 16099MB
[2025-01-18 10:50:12 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][30/312]	eta 0:02:33 lr 0.000130	time 0.4531 (0.5447)	model_time 0.4526 (0.4664)	loss 2.3295 (2.6512)	grad_norm 2.0581 (2.5588/1.1585)	mem 16099MB
[2025-01-18 10:50:17 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][40/312]	eta 0:02:23 lr 0.000130	time 0.4732 (0.5270)	model_time 0.4731 (0.4677)	loss 2.2089 (2.6709)	grad_norm 7.6289 (2.7396/1.3828)	mem 16099MB
[2025-01-18 10:50:21 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][50/312]	eta 0:02:14 lr 0.000130	time 0.4406 (0.5130)	model_time 0.4404 (0.4652)	loss 2.5987 (2.6893)	grad_norm 5.2937 (3.1027/1.7287)	mem 16099MB
[2025-01-18 10:50:26 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][60/312]	eta 0:02:07 lr 0.000129	time 0.4561 (0.5050)	model_time 0.4559 (0.4650)	loss 2.6878 (2.6893)	grad_norm 2.4278 (3.0863/1.7191)	mem 16099MB
[2025-01-18 10:50:31 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][70/312]	eta 0:02:01 lr 0.000129	time 0.4434 (0.5007)	model_time 0.4430 (0.4663)	loss 2.2277 (2.6638)	grad_norm 1.5796 (3.1548/1.7359)	mem 16099MB
[2025-01-18 10:50:35 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][80/312]	eta 0:01:55 lr 0.000129	time 0.4469 (0.4963)	model_time 0.4467 (0.4661)	loss 2.7303 (2.6715)	grad_norm 2.4892 (3.2259/1.7189)	mem 16099MB
[2025-01-18 10:50:40 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][90/312]	eta 0:01:49 lr 0.000129	time 0.4437 (0.4917)	model_time 0.4435 (0.4648)	loss 3.2732 (2.6958)	grad_norm 3.9786 (3.1993/1.6641)	mem 16099MB
[2025-01-18 10:50:45 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][100/312]	eta 0:01:44 lr 0.000129	time 0.4514 (0.4916)	model_time 0.4509 (0.4673)	loss 2.0710 (2.6820)	grad_norm 3.3811 (3.2073/1.6320)	mem 16099MB
[2025-01-18 10:50:49 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][110/312]	eta 0:01:38 lr 0.000128	time 0.4618 (0.4891)	model_time 0.4613 (0.4669)	loss 2.9578 (2.6898)	grad_norm 3.8742 (3.1541/1.5907)	mem 16099MB
[2025-01-18 10:50:54 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][120/312]	eta 0:01:33 lr 0.000128	time 0.4595 (0.4879)	model_time 0.4591 (0.4675)	loss 3.0466 (2.6983)	grad_norm 2.4992 (3.0710/1.5597)	mem 16099MB
[2025-01-18 10:50:59 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][130/312]	eta 0:01:28 lr 0.000128	time 0.4440 (0.4878)	model_time 0.4438 (0.4689)	loss 3.0660 (2.7202)	grad_norm 1.1389 (3.0554/1.5423)	mem 16099MB
[2025-01-18 10:51:04 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][140/312]	eta 0:01:24 lr 0.000128	time 0.4561 (0.4896)	model_time 0.4560 (0.4721)	loss 3.2844 (2.7207)	grad_norm 4.1750 (3.0631/1.5155)	mem 16099MB
[2025-01-18 10:51:09 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][150/312]	eta 0:01:18 lr 0.000128	time 0.4569 (0.4873)	model_time 0.4567 (0.4709)	loss 3.1245 (2.7155)	grad_norm 2.2352 (3.0439/1.4877)	mem 16099MB
[2025-01-18 10:51:13 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][160/312]	eta 0:01:13 lr 0.000127	time 0.4801 (0.4861)	model_time 0.4797 (0.4707)	loss 3.1163 (2.7187)	grad_norm 3.3610 (3.0945/1.5659)	mem 16099MB
[2025-01-18 10:51:18 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][170/312]	eta 0:01:08 lr 0.000127	time 0.4529 (0.4850)	model_time 0.4528 (0.4704)	loss 2.7408 (2.7277)	grad_norm 1.7031 (3.0973/1.5758)	mem 16099MB
[2025-01-18 10:51:23 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][180/312]	eta 0:01:03 lr 0.000127	time 0.4542 (0.4833)	model_time 0.4538 (0.4695)	loss 2.8026 (2.7133)	grad_norm 1.7897 (3.0637/1.5528)	mem 16099MB
[2025-01-18 10:51:27 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][190/312]	eta 0:00:58 lr 0.000127	time 0.4492 (0.4817)	model_time 0.4490 (0.4687)	loss 2.2483 (2.7213)	grad_norm 4.0901 (3.0833/1.5428)	mem 16099MB
[2025-01-18 10:51:32 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][200/312]	eta 0:00:53 lr 0.000127	time 0.4647 (0.4813)	model_time 0.4645 (0.4689)	loss 2.9932 (2.7166)	grad_norm 2.8186 (3.0412/1.5213)	mem 16099MB
[2025-01-18 10:51:37 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][210/312]	eta 0:00:49 lr 0.000126	time 0.4551 (0.4810)	model_time 0.4547 (0.4691)	loss 2.1688 (2.7093)	grad_norm 2.0320 (3.0143/1.5074)	mem 16099MB
[2025-01-18 10:51:41 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][220/312]	eta 0:00:44 lr 0.000126	time 0.4581 (0.4804)	model_time 0.4577 (0.4690)	loss 2.7374 (2.7037)	grad_norm 1.5848 (2.9890/1.4850)	mem 16099MB
[2025-01-18 10:51:46 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][230/312]	eta 0:00:39 lr 0.000126	time 0.5281 (0.4797)	model_time 0.5279 (0.4688)	loss 2.6254 (2.7005)	grad_norm 2.2036 (2.9467/1.4704)	mem 16099MB
[2025-01-18 10:51:50 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][240/312]	eta 0:00:34 lr 0.000126	time 0.4645 (0.4786)	model_time 0.4641 (0.4681)	loss 2.9072 (2.6999)	grad_norm 2.7088 (2.9343/1.4596)	mem 16099MB
[2025-01-18 10:51:55 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][250/312]	eta 0:00:29 lr 0.000126	time 0.4585 (0.4775)	model_time 0.4584 (0.4675)	loss 2.8114 (2.7011)	grad_norm 3.8314 (2.9312/1.4424)	mem 16099MB
[2025-01-18 10:52:00 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][260/312]	eta 0:00:24 lr 0.000126	time 0.4805 (0.4770)	model_time 0.4800 (0.4674)	loss 3.0752 (2.7070)	grad_norm 2.0506 (2.9252/1.4250)	mem 16099MB
[2025-01-18 10:52:04 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][270/312]	eta 0:00:20 lr 0.000125	time 0.4639 (0.4773)	model_time 0.4635 (0.4680)	loss 2.8767 (2.7047)	grad_norm 5.9093 (2.9574/1.4382)	mem 16099MB
[2025-01-18 10:52:09 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][280/312]	eta 0:00:15 lr 0.000125	time 0.4529 (0.4767)	model_time 0.4527 (0.4677)	loss 2.4077 (2.7051)	grad_norm 3.5490 (2.9747/1.4443)	mem 16099MB
[2025-01-18 10:52:14 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][290/312]	eta 0:00:10 lr 0.000125	time 0.4621 (0.4760)	model_time 0.4619 (0.4673)	loss 2.9726 (2.7111)	grad_norm 3.4818 (2.9682/1.4343)	mem 16099MB
[2025-01-18 10:52:18 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][300/312]	eta 0:00:05 lr 0.000125	time 0.4401 (0.4760)	model_time 0.4400 (0.4675)	loss 3.0057 (2.7144)	grad_norm 3.7392 (2.9775/1.4519)	mem 16099MB
[2025-01-18 10:52:23 internimage_t_1k_224] (main.py 510): INFO Train: [271/300][310/312]	eta 0:00:00 lr 0.000125	time 0.4414 (0.4751)	model_time 0.4413 (0.4669)	loss 3.0231 (2.7188)	grad_norm 2.9398 (2.9916/1.4546)	mem 16099MB
[2025-01-18 10:52:23 internimage_t_1k_224] (main.py 519): INFO EPOCH 271 training takes 0:02:28
[2025-01-18 10:52:23 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_271.pth saving......
[2025-01-18 10:52:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_271.pth saved !!!
[2025-01-18 10:52:32 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.545 (7.545)	Loss 0.7297 (0.7297)	Acc@1 85.571 (85.571)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 10:52:36 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.005)	Loss 0.9742 (0.8358)	Acc@1 79.102 (82.983)	Acc@5 95.264 (96.294)	Mem 16099MB
[2025-01-18 10:52:36 internimage_t_1k_224] (main.py 575): INFO [Epoch:271] * Acc@1 82.831 Acc@5 96.319
[2025-01-18 10:52:36 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.8%
[2025-01-18 10:52:36 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.97%
[2025-01-18 10:52:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.385 (8.385)	Loss 0.7207 (0.7207)	Acc@1 85.767 (85.767)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:52:48 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.141)	Loss 0.9511 (0.8212)	Acc@1 79.712 (83.607)	Acc@5 95.483 (96.578)	Mem 16099MB
[2025-01-18 10:52:48 internimage_t_1k_224] (main.py 575): INFO [Epoch:271] * Acc@1 83.463 Acc@5 96.579
[2025-01-18 10:52:48 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 10:52:48 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:52:50 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:52:50 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.46%
[2025-01-18 10:52:52 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][0/312]	eta 0:13:17 lr 0.000125	time 2.5574 (2.5574)	model_time 0.4802 (0.4802)	loss 2.8498 (2.8498)	grad_norm 1.7154 (1.7154/0.0000)	mem 16099MB
[2025-01-18 10:52:57 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][10/312]	eta 0:03:17 lr 0.000124	time 0.4591 (0.6542)	model_time 0.4587 (0.4651)	loss 2.9057 (2.4328)	grad_norm 4.8292 (2.6443/1.2439)	mem 16099MB
[2025-01-18 10:53:02 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][20/312]	eta 0:02:45 lr 0.000124	time 0.4677 (0.5660)	model_time 0.4675 (0.4668)	loss 2.7991 (2.6244)	grad_norm 3.0597 (2.6347/1.1069)	mem 16099MB
[2025-01-18 10:53:06 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][30/312]	eta 0:02:30 lr 0.000124	time 0.4557 (0.5325)	model_time 0.4553 (0.4652)	loss 3.0400 (2.6886)	grad_norm 4.0510 (2.9314/1.4576)	mem 16099MB
[2025-01-18 10:53:11 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][40/312]	eta 0:02:21 lr 0.000124	time 0.4578 (0.5187)	model_time 0.4574 (0.4677)	loss 1.9333 (2.6491)	grad_norm 5.8406 (3.2637/1.6491)	mem 16099MB
[2025-01-18 10:53:16 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][50/312]	eta 0:02:13 lr 0.000124	time 0.4606 (0.5091)	model_time 0.4604 (0.4680)	loss 2.9642 (2.6910)	grad_norm 1.6198 (3.3092/1.5545)	mem 16099MB
[2025-01-18 10:53:20 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][60/312]	eta 0:02:06 lr 0.000123	time 0.4526 (0.5011)	model_time 0.4525 (0.4667)	loss 2.6983 (2.7119)	grad_norm 2.2441 (3.2132/1.5851)	mem 16099MB
[2025-01-18 10:53:25 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][70/312]	eta 0:01:59 lr 0.000123	time 0.4544 (0.4945)	model_time 0.4539 (0.4648)	loss 2.7341 (2.7187)	grad_norm 2.6196 (3.0965/1.5226)	mem 16099MB
[2025-01-18 10:53:30 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][80/312]	eta 0:01:53 lr 0.000123	time 0.4850 (0.4904)	model_time 0.4848 (0.4644)	loss 2.2037 (2.7176)	grad_norm 2.8242 (3.0576/1.4633)	mem 16099MB
[2025-01-18 10:53:34 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][90/312]	eta 0:01:47 lr 0.000123	time 0.4555 (0.4862)	model_time 0.4554 (0.4631)	loss 3.1048 (2.7225)	grad_norm 1.4591 (3.0188/1.4461)	mem 16099MB
[2025-01-18 10:53:39 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][100/312]	eta 0:01:42 lr 0.000123	time 0.4571 (0.4855)	model_time 0.4569 (0.4646)	loss 1.8195 (2.7195)	grad_norm 1.8722 (3.0549/1.4833)	mem 16099MB
[2025-01-18 10:53:44 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][110/312]	eta 0:01:37 lr 0.000122	time 0.4601 (0.4841)	model_time 0.4599 (0.4650)	loss 2.7238 (2.7257)	grad_norm 3.1438 (3.0263/1.4373)	mem 16099MB
[2025-01-18 10:53:48 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][120/312]	eta 0:01:32 lr 0.000122	time 0.4512 (0.4824)	model_time 0.4507 (0.4649)	loss 2.4404 (2.7200)	grad_norm 4.0582 (3.0321/1.4401)	mem 16099MB
[2025-01-18 10:53:53 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][130/312]	eta 0:01:27 lr 0.000122	time 0.4526 (0.4833)	model_time 0.4525 (0.4671)	loss 1.6567 (2.7000)	grad_norm 1.4070 (3.0165/1.4172)	mem 16099MB
[2025-01-18 10:53:58 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][140/312]	eta 0:01:23 lr 0.000122	time 0.4760 (0.4851)	model_time 0.4758 (0.4700)	loss 2.9193 (2.7017)	grad_norm 1.9822 (3.0107/1.4065)	mem 16099MB
[2025-01-18 10:54:03 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][150/312]	eta 0:01:18 lr 0.000122	time 0.4463 (0.4837)	model_time 0.4459 (0.4696)	loss 2.2341 (2.6829)	grad_norm 4.3303 (3.0433/1.4110)	mem 16099MB
[2025-01-18 10:54:08 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][160/312]	eta 0:01:13 lr 0.000121	time 0.4503 (0.4829)	model_time 0.4499 (0.4696)	loss 3.0304 (2.6864)	grad_norm 3.0741 (3.1428/1.5460)	mem 16099MB
[2025-01-18 10:54:12 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][170/312]	eta 0:01:08 lr 0.000121	time 0.4936 (0.4815)	model_time 0.4935 (0.4690)	loss 2.9351 (2.6858)	grad_norm 3.7446 (3.1963/1.5569)	mem 16099MB
[2025-01-18 10:54:17 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][180/312]	eta 0:01:03 lr 0.000121	time 0.5302 (0.4814)	model_time 0.5301 (0.4695)	loss 2.3461 (2.6861)	grad_norm 2.5364 (3.1614/1.5323)	mem 16099MB
[2025-01-18 10:54:22 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][190/312]	eta 0:00:58 lr 0.000121	time 0.4487 (0.4810)	model_time 0.4482 (0.4697)	loss 2.9890 (2.6787)	grad_norm 2.4263 (3.1029/1.5190)	mem 16099MB
[2025-01-18 10:54:26 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][200/312]	eta 0:00:53 lr 0.000121	time 0.4427 (0.4797)	model_time 0.4422 (0.4690)	loss 2.8588 (2.6755)	grad_norm 2.2143 (3.0623/1.5020)	mem 16099MB
[2025-01-18 10:54:31 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][210/312]	eta 0:00:48 lr 0.000121	time 0.4431 (0.4785)	model_time 0.4429 (0.4683)	loss 2.9043 (2.6808)	grad_norm 1.8543 (3.0386/1.4848)	mem 16099MB
[2025-01-18 10:54:36 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][220/312]	eta 0:00:43 lr 0.000120	time 0.4691 (0.4782)	model_time 0.4690 (0.4685)	loss 2.6639 (2.6729)	grad_norm 3.5532 (3.0128/1.4661)	mem 16099MB
[2025-01-18 10:54:40 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][230/312]	eta 0:00:39 lr 0.000120	time 0.4537 (0.4776)	model_time 0.4533 (0.4683)	loss 2.5009 (2.6701)	grad_norm 2.3700 (3.0100/1.4485)	mem 16099MB
[2025-01-18 10:54:45 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][240/312]	eta 0:00:34 lr 0.000120	time 0.4587 (0.4777)	model_time 0.4585 (0.4687)	loss 2.8456 (2.6843)	grad_norm 2.6008 (2.9947/1.4383)	mem 16099MB
[2025-01-18 10:54:50 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][250/312]	eta 0:00:29 lr 0.000120	time 0.4603 (0.4770)	model_time 0.4602 (0.4684)	loss 2.5021 (2.6847)	grad_norm 2.8102 (2.9946/1.4341)	mem 16099MB
[2025-01-18 10:54:54 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][260/312]	eta 0:00:24 lr 0.000120	time 0.4541 (0.4761)	model_time 0.4536 (0.4678)	loss 1.9455 (2.6740)	grad_norm 3.5750 (3.0042/1.4235)	mem 16099MB
[2025-01-18 10:54:59 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][270/312]	eta 0:00:20 lr 0.000119	time 0.4420 (0.4764)	model_time 0.4418 (0.4684)	loss 2.9693 (2.6807)	grad_norm 4.5104 (3.0061/1.4220)	mem 16099MB
[2025-01-18 10:55:04 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][280/312]	eta 0:00:15 lr 0.000119	time 0.4501 (0.4765)	model_time 0.4496 (0.4687)	loss 2.8043 (2.6904)	grad_norm 3.6849 (3.0880/1.4932)	mem 16099MB
[2025-01-18 10:55:08 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][290/312]	eta 0:00:10 lr 0.000119	time 0.4443 (0.4761)	model_time 0.4439 (0.4685)	loss 2.4025 (2.6876)	grad_norm 5.6029 (3.1344/1.5477)	mem 16099MB
[2025-01-18 10:55:13 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][300/312]	eta 0:00:05 lr 0.000119	time 0.4399 (0.4757)	model_time 0.4398 (0.4684)	loss 2.9878 (2.6954)	grad_norm 3.2974 (3.1360/1.5561)	mem 16099MB
[2025-01-18 10:55:18 internimage_t_1k_224] (main.py 510): INFO Train: [272/300][310/312]	eta 0:00:00 lr 0.000119	time 0.4393 (0.4748)	model_time 0.4392 (0.4678)	loss 2.1168 (2.6928)	grad_norm 2.3917 (3.1613/1.5726)	mem 16099MB
[2025-01-18 10:55:18 internimage_t_1k_224] (main.py 519): INFO EPOCH 272 training takes 0:02:28
[2025-01-18 10:55:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_272.pth saving......
[2025-01-18 10:55:19 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_272.pth saved !!!
[2025-01-18 10:55:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.595 (7.595)	Loss 0.7236 (0.7236)	Acc@1 85.278 (85.278)	Acc@5 97.290 (97.290)	Mem 16099MB
[2025-01-18 10:55:30 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.018)	Loss 0.9724 (0.8281)	Acc@1 78.809 (82.988)	Acc@5 95.264 (96.287)	Mem 16099MB
[2025-01-18 10:55:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:272] * Acc@1 82.851 Acc@5 96.281
[2025-01-18 10:55:31 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 82.9%
[2025-01-18 10:55:31 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 82.97%
[2025-01-18 10:55:39 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.439 (8.439)	Loss 0.7201 (0.7201)	Acc@1 85.767 (85.767)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:55:43 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.144)	Loss 0.9505 (0.8205)	Acc@1 79.736 (83.618)	Acc@5 95.483 (96.575)	Mem 16099MB
[2025-01-18 10:55:43 internimage_t_1k_224] (main.py 575): INFO [Epoch:272] * Acc@1 83.477 Acc@5 96.575
[2025-01-18 10:55:43 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 10:55:43 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:55:45 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:55:45 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.48%
[2025-01-18 10:55:47 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][0/312]	eta 0:13:34 lr 0.000119	time 2.6106 (2.6106)	model_time 0.4832 (0.4832)	loss 2.9961 (2.9961)	grad_norm 1.4227 (1.4227/0.0000)	mem 16099MB
[2025-01-18 10:55:52 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][10/312]	eta 0:03:16 lr 0.000118	time 0.4501 (0.6521)	model_time 0.4499 (0.4584)	loss 3.1259 (2.6437)	grad_norm 1.7327 (2.1652/0.7538)	mem 16099MB
[2025-01-18 10:55:57 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][20/312]	eta 0:02:47 lr 0.000118	time 0.4847 (0.5731)	model_time 0.4845 (0.4715)	loss 1.8211 (2.5573)	grad_norm 4.1380 (2.4627/1.0114)	mem 16099MB
[2025-01-18 10:56:01 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][30/312]	eta 0:02:31 lr 0.000118	time 0.4413 (0.5360)	model_time 0.4408 (0.4670)	loss 2.5763 (2.5827)	grad_norm 2.5545 (2.4563/0.9751)	mem 16099MB
[2025-01-18 10:56:06 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][40/312]	eta 0:02:20 lr 0.000118	time 0.4427 (0.5178)	model_time 0.4422 (0.4656)	loss 2.9674 (2.6438)	grad_norm 2.3192 (2.6080/1.1319)	mem 16099MB
[2025-01-18 10:56:11 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][50/312]	eta 0:02:12 lr 0.000118	time 0.4516 (0.5075)	model_time 0.4514 (0.4655)	loss 3.2709 (2.6787)	grad_norm 3.0712 (2.6513/1.0898)	mem 16099MB
[2025-01-18 10:56:15 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][60/312]	eta 0:02:05 lr 0.000118	time 0.4633 (0.4995)	model_time 0.4629 (0.4642)	loss 2.6715 (2.6802)	grad_norm 3.7237 (2.7474/1.0798)	mem 16099MB
[2025-01-18 10:56:20 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][70/312]	eta 0:01:59 lr 0.000117	time 0.4433 (0.4943)	model_time 0.4431 (0.4639)	loss 2.3895 (2.6830)	grad_norm 2.5989 (2.8241/1.0734)	mem 16099MB
[2025-01-18 10:56:25 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][80/312]	eta 0:01:54 lr 0.000117	time 0.4630 (0.4918)	model_time 0.4625 (0.4651)	loss 3.2006 (2.6678)	grad_norm 4.9962 (2.7876/1.0634)	mem 16099MB
[2025-01-18 10:56:29 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][90/312]	eta 0:01:48 lr 0.000117	time 0.4540 (0.4885)	model_time 0.4537 (0.4648)	loss 2.9234 (2.6670)	grad_norm 3.3954 (2.8211/1.0626)	mem 16099MB
[2025-01-18 10:56:34 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][100/312]	eta 0:01:43 lr 0.000117	time 0.4489 (0.4887)	model_time 0.4488 (0.4673)	loss 2.7468 (2.6535)	grad_norm 3.6795 (2.8789/1.0829)	mem 16099MB
[2025-01-18 10:56:39 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][110/312]	eta 0:01:38 lr 0.000117	time 0.5194 (0.4896)	model_time 0.5189 (0.4701)	loss 2.8816 (2.6488)	grad_norm 3.3240 (2.8406/1.0863)	mem 16099MB
[2025-01-18 10:56:44 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][120/312]	eta 0:01:33 lr 0.000116	time 0.4637 (0.4874)	model_time 0.4635 (0.4694)	loss 2.7663 (2.6475)	grad_norm 2.1190 (2.8157/1.0616)	mem 16099MB
[2025-01-18 10:56:48 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][130/312]	eta 0:01:28 lr 0.000116	time 0.4415 (0.4855)	model_time 0.4413 (0.4689)	loss 2.8405 (2.6311)	grad_norm 5.8295 (2.8637/1.0945)	mem 16099MB
[2025-01-18 10:56:53 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][140/312]	eta 0:01:23 lr 0.000116	time 0.4472 (0.4859)	model_time 0.4471 (0.4704)	loss 3.3002 (2.6449)	grad_norm 3.2698 (2.9233/1.1640)	mem 16099MB
[2025-01-18 10:56:58 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][150/312]	eta 0:01:18 lr 0.000116	time 0.4406 (0.4845)	model_time 0.4404 (0.4701)	loss 2.1999 (2.6492)	grad_norm 1.3936 (2.9341/1.1935)	mem 16099MB
[2025-01-18 10:57:03 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][160/312]	eta 0:01:13 lr 0.000116	time 0.4752 (0.4844)	model_time 0.4750 (0.4708)	loss 2.9176 (2.6539)	grad_norm 4.4307 (2.9399/1.1852)	mem 16099MB
[2025-01-18 10:57:07 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][170/312]	eta 0:01:08 lr 0.000115	time 0.4636 (0.4826)	model_time 0.4634 (0.4698)	loss 2.0841 (2.6500)	grad_norm 1.9972 (2.8985/1.1725)	mem 16099MB
[2025-01-18 10:57:12 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][180/312]	eta 0:01:03 lr 0.000115	time 0.4580 (0.4812)	model_time 0.4578 (0.4691)	loss 3.0765 (2.6621)	grad_norm 3.3563 (2.8820/1.1603)	mem 16099MB
[2025-01-18 10:57:17 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][190/312]	eta 0:00:58 lr 0.000115	time 0.4706 (0.4805)	model_time 0.4705 (0.4690)	loss 2.6504 (2.6700)	grad_norm 5.2504 (2.8709/1.1602)	mem 16099MB
[2025-01-18 10:57:21 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][200/312]	eta 0:00:53 lr 0.000115	time 0.4561 (0.4792)	model_time 0.4557 (0.4682)	loss 1.6738 (2.6601)	grad_norm 7.3140 (2.9991/1.3455)	mem 16099MB
[2025-01-18 10:57:26 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][210/312]	eta 0:00:48 lr 0.000115	time 0.4465 (0.4781)	model_time 0.4460 (0.4676)	loss 3.0507 (2.6609)	grad_norm 2.9196 (3.0288/1.3657)	mem 16099MB
[2025-01-18 10:57:30 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][220/312]	eta 0:00:43 lr 0.000115	time 0.4560 (0.4770)	model_time 0.4559 (0.4670)	loss 2.0154 (2.6595)	grad_norm 2.7369 (3.0133/1.3507)	mem 16099MB
[2025-01-18 10:57:35 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][230/312]	eta 0:00:39 lr 0.000114	time 0.4588 (0.4767)	model_time 0.4586 (0.4671)	loss 2.5462 (2.6656)	grad_norm 1.7568 (2.9961/1.3343)	mem 16099MB
[2025-01-18 10:57:40 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][240/312]	eta 0:00:34 lr 0.000114	time 0.5467 (0.4766)	model_time 0.5465 (0.4674)	loss 2.2210 (2.6578)	grad_norm 3.0042 (2.9850/1.3262)	mem 16099MB
[2025-01-18 10:57:44 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][250/312]	eta 0:00:29 lr 0.000114	time 0.4494 (0.4757)	model_time 0.4490 (0.4669)	loss 3.2545 (2.6584)	grad_norm 1.7618 (3.0040/1.3591)	mem 16099MB
[2025-01-18 10:57:49 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][260/312]	eta 0:00:24 lr 0.000114	time 0.4603 (0.4762)	model_time 0.4599 (0.4677)	loss 3.2226 (2.6668)	grad_norm 4.2961 (3.0129/1.3651)	mem 16099MB
[2025-01-18 10:57:54 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][270/312]	eta 0:00:19 lr 0.000114	time 0.4650 (0.4758)	model_time 0.4646 (0.4675)	loss 3.1682 (2.6713)	grad_norm 1.8501 (2.9977/1.3533)	mem 16099MB
[2025-01-18 10:57:58 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][280/312]	eta 0:00:15 lr 0.000114	time 0.4451 (0.4750)	model_time 0.4446 (0.4671)	loss 2.8589 (2.6762)	grad_norm 2.2575 (2.9982/1.3465)	mem 16099MB
[2025-01-18 10:58:03 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][290/312]	eta 0:00:10 lr 0.000113	time 0.4446 (0.4748)	model_time 0.4442 (0.4671)	loss 2.9530 (2.6779)	grad_norm 4.6239 (3.0672/1.3941)	mem 16099MB
[2025-01-18 10:58:07 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][300/312]	eta 0:00:05 lr 0.000113	time 0.4398 (0.4741)	model_time 0.4397 (0.4666)	loss 2.7283 (2.6792)	grad_norm 1.6031 (3.0403/1.3831)	mem 16099MB
[2025-01-18 10:58:12 internimage_t_1k_224] (main.py 510): INFO Train: [273/300][310/312]	eta 0:00:00 lr 0.000113	time 0.4923 (0.4737)	model_time 0.4922 (0.4665)	loss 2.8457 (2.6783)	grad_norm 2.3291 (3.0421/1.3823)	mem 16099MB
[2025-01-18 10:58:13 internimage_t_1k_224] (main.py 519): INFO EPOCH 273 training takes 0:02:27
[2025-01-18 10:58:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_273.pth saving......
[2025-01-18 10:58:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_273.pth saved !!!
[2025-01-18 10:58:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.611 (7.611)	Loss 0.7098 (0.7098)	Acc@1 85.425 (85.425)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 10:58:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.020)	Loss 0.9687 (0.8231)	Acc@1 79.102 (83.145)	Acc@5 95.264 (96.327)	Mem 16099MB
[2025-01-18 10:58:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:273] * Acc@1 82.997 Acc@5 96.347
[2025-01-18 10:58:25 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.0%
[2025-01-18 10:58:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 10:58:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 10:58:26 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.00%
[2025-01-18 10:58:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.524 (7.524)	Loss 0.7197 (0.7197)	Acc@1 85.791 (85.791)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 10:58:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.022)	Loss 0.9499 (0.8200)	Acc@1 79.834 (83.623)	Acc@5 95.435 (96.578)	Mem 16099MB
[2025-01-18 10:58:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:273] * Acc@1 83.481 Acc@5 96.577
[2025-01-18 10:58:38 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 10:58:38 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 10:58:39 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 10:58:39 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.48%
[2025-01-18 10:58:41 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][0/312]	eta 0:10:42 lr 0.000113	time 2.0596 (2.0596)	model_time 0.5180 (0.5180)	loss 3.2158 (3.2158)	grad_norm 3.3847 (3.3847/0.0000)	mem 16099MB
[2025-01-18 10:58:46 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][10/312]	eta 0:03:15 lr 0.000113	time 0.5210 (0.6487)	model_time 0.5206 (0.4784)	loss 3.0092 (2.6926)	grad_norm 3.8141 (2.6100/0.9042)	mem 16099MB
[2025-01-18 10:58:51 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][20/312]	eta 0:02:44 lr 0.000113	time 0.4405 (0.5650)	model_time 0.4403 (0.4756)	loss 2.8230 (2.5300)	grad_norm 1.8724 (2.4463/0.8487)	mem 16099MB
[2025-01-18 10:58:56 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][30/312]	eta 0:02:31 lr 0.000112	time 0.5301 (0.5355)	model_time 0.5300 (0.4749)	loss 3.1842 (2.5424)	grad_norm 2.8880 (2.9027/1.4390)	mem 16099MB
[2025-01-18 10:59:00 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][40/312]	eta 0:02:20 lr 0.000112	time 0.4417 (0.5182)	model_time 0.4412 (0.4722)	loss 3.0774 (2.6130)	grad_norm 6.8501 (3.1141/1.4770)	mem 16099MB
[2025-01-18 10:59:05 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][50/312]	eta 0:02:12 lr 0.000112	time 0.4460 (0.5058)	model_time 0.4456 (0.4688)	loss 2.8960 (2.6099)	grad_norm 1.4672 (3.3367/1.8598)	mem 16099MB
[2025-01-18 10:59:10 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][60/312]	eta 0:02:06 lr 0.000112	time 0.5383 (0.5014)	model_time 0.5378 (0.4704)	loss 2.5264 (2.6377)	grad_norm 2.2720 (3.2664/1.7717)	mem 16099MB
[2025-01-18 10:59:14 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][70/312]	eta 0:02:00 lr 0.000112	time 0.4612 (0.4970)	model_time 0.4611 (0.4702)	loss 3.1566 (2.6607)	grad_norm 3.0415 (3.1462/1.7360)	mem 16099MB
[2025-01-18 10:59:19 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][80/312]	eta 0:01:54 lr 0.000112	time 0.4497 (0.4929)	model_time 0.4496 (0.4694)	loss 2.8741 (2.6915)	grad_norm 2.4525 (3.1163/1.6832)	mem 16099MB
[2025-01-18 10:59:24 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][90/312]	eta 0:01:48 lr 0.000111	time 0.4500 (0.4895)	model_time 0.4496 (0.4685)	loss 2.8293 (2.6904)	grad_norm 2.1132 (3.1346/1.6406)	mem 16099MB
[2025-01-18 10:59:28 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][100/312]	eta 0:01:43 lr 0.000111	time 0.4520 (0.4869)	model_time 0.4515 (0.4680)	loss 2.5218 (2.6939)	grad_norm 2.2487 (3.0541/1.6019)	mem 16099MB
[2025-01-18 10:59:33 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][110/312]	eta 0:01:38 lr 0.000111	time 0.4558 (0.4862)	model_time 0.4554 (0.4690)	loss 2.7208 (2.7089)	grad_norm 1.7660 (3.0157/1.5751)	mem 16099MB
[2025-01-18 10:59:38 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][120/312]	eta 0:01:32 lr 0.000111	time 0.4513 (0.4840)	model_time 0.4512 (0.4682)	loss 2.5369 (2.6998)	grad_norm 2.0688 (3.0149/1.5467)	mem 16099MB
[2025-01-18 10:59:42 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][130/312]	eta 0:01:27 lr 0.000111	time 0.4487 (0.4829)	model_time 0.4485 (0.4683)	loss 1.8212 (2.6829)	grad_norm 4.3971 (3.0198/1.5375)	mem 16099MB
[2025-01-18 10:59:47 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][140/312]	eta 0:01:22 lr 0.000110	time 0.5492 (0.4825)	model_time 0.5487 (0.4689)	loss 2.8946 (2.6918)	grad_norm 7.7125 (3.0838/1.5717)	mem 16099MB
[2025-01-18 10:59:52 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][150/312]	eta 0:01:18 lr 0.000110	time 0.4487 (0.4820)	model_time 0.4486 (0.4692)	loss 2.3672 (2.6920)	grad_norm 1.5094 (3.1077/1.5787)	mem 16099MB
[2025-01-18 10:59:57 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][160/312]	eta 0:01:13 lr 0.000110	time 0.4726 (0.4808)	model_time 0.4722 (0.4688)	loss 2.8870 (2.6947)	grad_norm 2.4941 (3.1715/1.6088)	mem 16099MB
[2025-01-18 11:00:01 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][170/312]	eta 0:01:08 lr 0.000110	time 0.4425 (0.4800)	model_time 0.4424 (0.4687)	loss 2.0201 (2.7000)	grad_norm 2.7970 (3.1863/1.5846)	mem 16099MB
[2025-01-18 11:00:06 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][180/312]	eta 0:01:03 lr 0.000110	time 0.4492 (0.4795)	model_time 0.4490 (0.4688)	loss 2.0775 (2.6927)	grad_norm 3.9509 (3.2484/1.6003)	mem 16099MB
[2025-01-18 11:00:11 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][190/312]	eta 0:00:58 lr 0.000110	time 0.4502 (0.4788)	model_time 0.4501 (0.4685)	loss 2.9347 (2.6868)	grad_norm 2.8313 (3.2354/1.6182)	mem 16099MB
[2025-01-18 11:00:15 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][200/312]	eta 0:00:53 lr 0.000109	time 0.4714 (0.4782)	model_time 0.4712 (0.4684)	loss 2.2377 (2.6866)	grad_norm 2.2823 (3.2343/1.6037)	mem 16099MB
[2025-01-18 11:00:20 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][210/312]	eta 0:00:48 lr 0.000109	time 0.4538 (0.4775)	model_time 0.4534 (0.4681)	loss 2.5238 (2.6921)	grad_norm 1.6491 (3.2573/1.6123)	mem 16099MB
[2025-01-18 11:00:25 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][220/312]	eta 0:00:43 lr 0.000109	time 0.4432 (0.4768)	model_time 0.4430 (0.4679)	loss 2.2434 (2.6898)	grad_norm 2.2543 (3.2622/1.6093)	mem 16099MB
[2025-01-18 11:00:29 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][230/312]	eta 0:00:39 lr 0.000109	time 0.5009 (0.4764)	model_time 0.5004 (0.4678)	loss 3.0761 (2.6984)	grad_norm 1.4826 (3.2530/1.5898)	mem 16099MB
[2025-01-18 11:00:34 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][240/312]	eta 0:00:34 lr 0.000109	time 0.4457 (0.4758)	model_time 0.4455 (0.4675)	loss 3.1230 (2.7002)	grad_norm 2.3177 (3.2463/1.5638)	mem 16099MB
[2025-01-18 11:00:38 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][250/312]	eta 0:00:29 lr 0.000109	time 0.4725 (0.4753)	model_time 0.4723 (0.4674)	loss 2.6072 (2.6934)	grad_norm 4.7648 (3.2910/1.6176)	mem 16099MB
[2025-01-18 11:00:43 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][260/312]	eta 0:00:24 lr 0.000108	time 0.4543 (0.4749)	model_time 0.4538 (0.4673)	loss 2.9132 (2.6949)	grad_norm 4.7627 (3.3091/1.6153)	mem 16099MB
[2025-01-18 11:00:48 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][270/312]	eta 0:00:19 lr 0.000108	time 0.4612 (0.4748)	model_time 0.4608 (0.4674)	loss 2.7579 (2.7010)	grad_norm 2.9518 (3.2925/1.5945)	mem 16099MB
[2025-01-18 11:00:52 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][280/312]	eta 0:00:15 lr 0.000108	time 0.4467 (0.4742)	model_time 0.4465 (0.4671)	loss 3.0136 (2.7026)	grad_norm 3.8683 (3.2497/1.5875)	mem 16099MB
[2025-01-18 11:00:57 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][290/312]	eta 0:00:10 lr 0.000108	time 0.4602 (0.4735)	model_time 0.4597 (0.4666)	loss 2.7516 (2.7027)	grad_norm 1.6546 (3.2234/1.5767)	mem 16099MB
[2025-01-18 11:01:02 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][300/312]	eta 0:00:05 lr 0.000108	time 0.4407 (0.4732)	model_time 0.4406 (0.4666)	loss 3.1340 (2.7004)	grad_norm 2.9886 (3.2165/1.5607)	mem 16099MB
[2025-01-18 11:01:06 internimage_t_1k_224] (main.py 510): INFO Train: [274/300][310/312]	eta 0:00:00 lr 0.000108	time 0.4376 (0.4726)	model_time 0.4375 (0.4662)	loss 1.9099 (2.6965)	grad_norm 2.3901 (3.2220/1.5549)	mem 16099MB
[2025-01-18 11:01:07 internimage_t_1k_224] (main.py 519): INFO EPOCH 274 training takes 0:02:27
[2025-01-18 11:01:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_274.pth saving......
[2025-01-18 11:01:08 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_274.pth saved !!!
[2025-01-18 11:01:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.216 (7.216)	Loss 0.7097 (0.7097)	Acc@1 85.327 (85.327)	Acc@5 97.461 (97.461)	Mem 16099MB
[2025-01-18 11:01:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.987)	Loss 0.9607 (0.8119)	Acc@1 79.053 (83.103)	Acc@5 95.190 (96.282)	Mem 16099MB
[2025-01-18 11:01:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:274] * Acc@1 82.975 Acc@5 96.293
[2025-01-18 11:01:19 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.0%
[2025-01-18 11:01:19 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.00%
[2025-01-18 11:01:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.222 (8.222)	Loss 0.7189 (0.7189)	Acc@1 85.840 (85.840)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 11:01:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.110)	Loss 0.9491 (0.8192)	Acc@1 79.858 (83.631)	Acc@5 95.459 (96.580)	Mem 16099MB
[2025-01-18 11:01:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:274] * Acc@1 83.489 Acc@5 96.579
[2025-01-18 11:01:31 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:01:31 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 11:01:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 11:01:33 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.49%
[2025-01-18 11:01:35 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][0/312]	eta 0:10:49 lr 0.000107	time 2.0814 (2.0814)	model_time 0.4673 (0.4673)	loss 1.8350 (1.8350)	grad_norm 5.7835 (5.7835/0.0000)	mem 16099MB
[2025-01-18 11:01:40 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][10/312]	eta 0:03:13 lr 0.000107	time 0.4702 (0.6414)	model_time 0.4701 (0.4943)	loss 2.3769 (2.4078)	grad_norm 1.7335 (3.3953/1.6401)	mem 16099MB
[2025-01-18 11:01:44 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][20/312]	eta 0:02:42 lr 0.000107	time 0.4688 (0.5550)	model_time 0.4687 (0.4777)	loss 2.2767 (2.6121)	grad_norm 1.8440 (2.9778/1.3908)	mem 16099MB
[2025-01-18 11:01:49 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][30/312]	eta 0:02:28 lr 0.000107	time 0.4538 (0.5260)	model_time 0.4537 (0.4736)	loss 2.9636 (2.6439)	grad_norm 2.4528 (2.8850/1.2377)	mem 16099MB
[2025-01-18 11:01:54 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][40/312]	eta 0:02:19 lr 0.000107	time 0.4475 (0.5111)	model_time 0.4471 (0.4713)	loss 2.6795 (2.6241)	grad_norm 1.5873 (2.6338/1.1821)	mem 16099MB
[2025-01-18 11:01:58 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][50/312]	eta 0:02:10 lr 0.000107	time 0.4491 (0.5000)	model_time 0.4490 (0.4680)	loss 3.1254 (2.6828)	grad_norm 2.1994 (2.6413/1.1879)	mem 16099MB
[2025-01-18 11:02:03 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][60/312]	eta 0:02:04 lr 0.000106	time 0.4404 (0.4924)	model_time 0.4402 (0.4655)	loss 2.6089 (2.7009)	grad_norm 1.8608 (2.5787/1.1256)	mem 16099MB
[2025-01-18 11:02:07 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][70/312]	eta 0:01:57 lr 0.000106	time 0.4839 (0.4872)	model_time 0.4834 (0.4641)	loss 2.9613 (2.6946)	grad_norm 4.5674 (2.7571/1.3155)	mem 16099MB
[2025-01-18 11:02:12 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][80/312]	eta 0:01:52 lr 0.000106	time 0.4441 (0.4850)	model_time 0.4437 (0.4646)	loss 2.8354 (2.6810)	grad_norm 7.6547 (3.1308/1.7567)	mem 16099MB
[2025-01-18 11:02:17 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][90/312]	eta 0:01:47 lr 0.000106	time 0.4557 (0.4839)	model_time 0.4555 (0.4658)	loss 2.6598 (2.6570)	grad_norm 2.2053 (3.0520/1.6955)	mem 16099MB
[2025-01-18 11:02:22 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][100/312]	eta 0:01:42 lr 0.000106	time 0.4734 (0.4834)	model_time 0.4730 (0.4670)	loss 1.6325 (2.6398)	grad_norm 4.2306 (3.0518/1.6441)	mem 16099MB
[2025-01-18 11:02:26 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][110/312]	eta 0:01:37 lr 0.000106	time 0.4426 (0.4816)	model_time 0.4421 (0.4666)	loss 2.5490 (2.6485)	grad_norm 4.4242 (3.0634/1.6320)	mem 16099MB
[2025-01-18 11:02:31 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][120/312]	eta 0:01:32 lr 0.000105	time 0.4479 (0.4814)	model_time 0.4477 (0.4676)	loss 2.9037 (2.6549)	grad_norm 2.3257 (3.0955/1.5915)	mem 16099MB
[2025-01-18 11:02:36 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][130/312]	eta 0:01:27 lr 0.000105	time 0.4494 (0.4804)	model_time 0.4489 (0.4677)	loss 2.6549 (2.6413)	grad_norm 2.9955 (3.1017/1.5546)	mem 16099MB
[2025-01-18 11:02:40 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][140/312]	eta 0:01:22 lr 0.000105	time 0.4528 (0.4795)	model_time 0.4524 (0.4676)	loss 2.6122 (2.6396)	grad_norm 2.4490 (3.0621/1.5158)	mem 16099MB
[2025-01-18 11:02:45 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][150/312]	eta 0:01:17 lr 0.000105	time 0.4786 (0.4785)	model_time 0.4785 (0.4674)	loss 3.0911 (2.6492)	grad_norm 2.5797 (3.0107/1.4821)	mem 16099MB
[2025-01-18 11:02:50 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][160/312]	eta 0:01:12 lr 0.000105	time 0.4603 (0.4784)	model_time 0.4598 (0.4680)	loss 2.4686 (2.6582)	grad_norm 3.4567 (2.9797/1.4744)	mem 16099MB
[2025-01-18 11:02:54 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][170/312]	eta 0:01:07 lr 0.000105	time 0.4415 (0.4775)	model_time 0.4413 (0.4677)	loss 2.8024 (2.6587)	grad_norm 3.0328 (2.9557/1.4530)	mem 16099MB
[2025-01-18 11:02:59 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][180/312]	eta 0:01:02 lr 0.000104	time 0.4699 (0.4770)	model_time 0.4697 (0.4677)	loss 3.1103 (2.6677)	grad_norm 1.5774 (2.9184/1.4282)	mem 16099MB
[2025-01-18 11:03:04 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][190/312]	eta 0:00:58 lr 0.000104	time 0.4578 (0.4764)	model_time 0.4576 (0.4676)	loss 2.7866 (2.6681)	grad_norm 2.3235 (2.8857/1.4125)	mem 16099MB
[2025-01-18 11:03:08 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][200/312]	eta 0:00:53 lr 0.000104	time 0.4842 (0.4759)	model_time 0.4841 (0.4675)	loss 2.7408 (2.6722)	grad_norm 2.0940 (2.8559/1.3935)	mem 16099MB
[2025-01-18 11:03:13 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][210/312]	eta 0:00:48 lr 0.000104	time 0.4532 (0.4753)	model_time 0.4531 (0.4673)	loss 2.2026 (2.6726)	grad_norm 2.7693 (2.8271/1.3751)	mem 16099MB
[2025-01-18 11:03:18 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][220/312]	eta 0:00:43 lr 0.000104	time 0.4405 (0.4752)	model_time 0.4401 (0.4675)	loss 2.8000 (2.6724)	grad_norm 4.2739 (2.8574/1.3879)	mem 16099MB
[2025-01-18 11:03:22 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][230/312]	eta 0:00:38 lr 0.000104	time 0.4483 (0.4751)	model_time 0.4481 (0.4678)	loss 1.6502 (2.6649)	grad_norm 2.5675 (2.8708/1.3808)	mem 16099MB
[2025-01-18 11:03:27 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][240/312]	eta 0:00:34 lr 0.000103	time 0.4652 (0.4751)	model_time 0.4647 (0.4680)	loss 1.8568 (2.6622)	grad_norm 1.7839 (2.8661/1.3682)	mem 16099MB
[2025-01-18 11:03:32 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][250/312]	eta 0:00:29 lr 0.000103	time 0.5457 (0.4754)	model_time 0.5453 (0.4685)	loss 1.7099 (2.6472)	grad_norm 2.6506 (2.8433/1.3501)	mem 16099MB
[2025-01-18 11:03:37 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][260/312]	eta 0:00:24 lr 0.000103	time 0.4513 (0.4750)	model_time 0.4511 (0.4684)	loss 1.6317 (2.6465)	grad_norm 3.3720 (2.8613/1.3641)	mem 16099MB
[2025-01-18 11:03:41 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][270/312]	eta 0:00:19 lr 0.000103	time 0.4687 (0.4743)	model_time 0.4682 (0.4679)	loss 2.9478 (2.6463)	grad_norm 3.7677 (2.8802/1.3582)	mem 16099MB
[2025-01-18 11:03:46 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][280/312]	eta 0:00:15 lr 0.000103	time 0.4948 (0.4740)	model_time 0.4947 (0.4679)	loss 3.0756 (2.6392)	grad_norm 4.1246 (2.8913/1.3600)	mem 16099MB
[2025-01-18 11:03:51 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][290/312]	eta 0:00:10 lr 0.000103	time 0.4481 (0.4740)	model_time 0.4479 (0.4681)	loss 2.8116 (2.6386)	grad_norm 3.1617 (2.9313/1.3887)	mem 16099MB
[2025-01-18 11:03:55 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][300/312]	eta 0:00:05 lr 0.000102	time 0.4413 (0.4733)	model_time 0.4412 (0.4675)	loss 2.0896 (2.6417)	grad_norm 4.5099 (2.9767/1.4183)	mem 16099MB
[2025-01-18 11:04:00 internimage_t_1k_224] (main.py 510): INFO Train: [275/300][310/312]	eta 0:00:00 lr 0.000102	time 0.4378 (0.4725)	model_time 0.4377 (0.4669)	loss 2.1475 (2.6410)	grad_norm 1.9096 (2.9683/1.4084)	mem 16099MB
[2025-01-18 11:04:00 internimage_t_1k_224] (main.py 519): INFO EPOCH 275 training takes 0:02:27
[2025-01-18 11:04:00 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_275.pth saving......
[2025-01-18 11:04:01 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_275.pth saved !!!
[2025-01-18 11:04:09 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.309 (7.309)	Loss 0.7156 (0.7156)	Acc@1 85.425 (85.425)	Acc@5 97.339 (97.339)	Mem 16099MB
[2025-01-18 11:04:12 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.995)	Loss 0.9587 (0.8209)	Acc@1 79.175 (83.205)	Acc@5 95.410 (96.320)	Mem 16099MB
[2025-01-18 11:04:12 internimage_t_1k_224] (main.py 575): INFO [Epoch:275] * Acc@1 83.059 Acc@5 96.319
[2025-01-18 11:04:12 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:04:12 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 11:04:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 11:04:14 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.06%
[2025-01-18 11:04:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.472 (7.472)	Loss 0.7185 (0.7185)	Acc@1 85.864 (85.864)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 11:04:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.017)	Loss 0.9486 (0.8186)	Acc@1 79.834 (83.627)	Acc@5 95.410 (96.578)	Mem 16099MB
[2025-01-18 11:04:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:275] * Acc@1 83.485 Acc@5 96.579
[2025-01-18 11:04:25 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:04:25 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.49%
[2025-01-18 11:04:28 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][0/312]	eta 0:16:29 lr 0.000102	time 3.1708 (3.1708)	model_time 1.0783 (1.0783)	loss 2.8603 (2.8603)	grad_norm 3.1245 (3.1245/0.0000)	mem 16099MB
[2025-01-18 11:04:33 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][10/312]	eta 0:03:38 lr 0.000102	time 0.5492 (0.7251)	model_time 0.5491 (0.5344)	loss 2.4787 (2.7366)	grad_norm 7.2582 (3.7287/1.5799)	mem 16099MB
[2025-01-18 11:04:38 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][20/312]	eta 0:02:55 lr 0.000102	time 0.4506 (0.6003)	model_time 0.4502 (0.5002)	loss 2.3568 (2.7272)	grad_norm 3.8723 (3.9537/1.5478)	mem 16099MB
[2025-01-18 11:04:42 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][30/312]	eta 0:02:37 lr 0.000102	time 0.4666 (0.5593)	model_time 0.4665 (0.4914)	loss 2.9458 (2.7013)	grad_norm 4.7587 (3.7810/1.4270)	mem 16099MB
[2025-01-18 11:04:47 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][40/312]	eta 0:02:26 lr 0.000102	time 0.4439 (0.5388)	model_time 0.4437 (0.4874)	loss 3.2104 (2.6759)	grad_norm 2.6058 (3.5455/1.4209)	mem 16099MB
[2025-01-18 11:04:52 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][50/312]	eta 0:02:17 lr 0.000101	time 0.4485 (0.5250)	model_time 0.4478 (0.4836)	loss 2.2351 (2.6601)	grad_norm 6.1069 (3.5007/1.4453)	mem 16099MB
[2025-01-18 11:04:56 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][60/312]	eta 0:02:09 lr 0.000101	time 0.4451 (0.5142)	model_time 0.4449 (0.4795)	loss 2.3953 (2.6285)	grad_norm 2.6408 (3.4724/1.4130)	mem 16099MB
[2025-01-18 11:05:01 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][70/312]	eta 0:02:02 lr 0.000101	time 0.4495 (0.5060)	model_time 0.4491 (0.4761)	loss 1.8446 (2.6530)	grad_norm 4.2467 (3.4309/1.3740)	mem 16099MB
[2025-01-18 11:05:05 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][80/312]	eta 0:01:56 lr 0.000101	time 0.4802 (0.5003)	model_time 0.4798 (0.4741)	loss 2.5994 (2.6490)	grad_norm 5.3162 (3.5024/1.4038)	mem 16099MB
[2025-01-18 11:05:10 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][90/312]	eta 0:01:50 lr 0.000101	time 0.5338 (0.4960)	model_time 0.5337 (0.4726)	loss 2.9190 (2.6694)	grad_norm 2.7745 (3.4373/1.3672)	mem 16099MB
[2025-01-18 11:05:15 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][100/312]	eta 0:01:44 lr 0.000101	time 0.4606 (0.4929)	model_time 0.4601 (0.4718)	loss 2.5747 (2.6617)	grad_norm 4.3720 (3.4812/1.3455)	mem 16099MB
[2025-01-18 11:05:19 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][110/312]	eta 0:01:39 lr 0.000100	time 0.4536 (0.4903)	model_time 0.4534 (0.4711)	loss 2.9296 (2.6483)	grad_norm 1.3065 (3.4586/1.3870)	mem 16099MB
[2025-01-18 11:05:24 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][120/312]	eta 0:01:34 lr 0.000100	time 0.5489 (0.4898)	model_time 0.5484 (0.4721)	loss 3.2725 (2.6342)	grad_norm 3.9345 (3.3976/1.3827)	mem 16099MB
[2025-01-18 11:05:29 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][130/312]	eta 0:01:28 lr 0.000100	time 0.4426 (0.4880)	model_time 0.4419 (0.4716)	loss 2.4891 (2.6336)	grad_norm 1.7256 (3.3433/1.4118)	mem 16099MB
[2025-01-18 11:05:34 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][140/312]	eta 0:01:23 lr 0.000100	time 0.4547 (0.4880)	model_time 0.4543 (0.4728)	loss 3.2721 (2.6282)	grad_norm 1.8090 (3.2682/1.3986)	mem 16099MB
[2025-01-18 11:05:39 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][150/312]	eta 0:01:18 lr 0.000100	time 0.4564 (0.4872)	model_time 0.4559 (0.4729)	loss 2.7284 (2.6490)	grad_norm 2.7743 (3.2109/1.3746)	mem 16099MB
[2025-01-18 11:05:43 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][160/312]	eta 0:01:13 lr 0.000100	time 0.4482 (0.4853)	model_time 0.4478 (0.4719)	loss 2.4951 (2.6323)	grad_norm 1.7661 (3.2162/1.3789)	mem 16099MB
[2025-01-18 11:05:48 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][170/312]	eta 0:01:08 lr 0.000099	time 0.4495 (0.4835)	model_time 0.4491 (0.4708)	loss 2.4153 (2.6278)	grad_norm 2.8502 (3.2167/1.3718)	mem 16099MB
[2025-01-18 11:05:52 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][180/312]	eta 0:01:03 lr 0.000099	time 0.4451 (0.4818)	model_time 0.4447 (0.4698)	loss 3.6345 (2.6310)	grad_norm 6.3480 (3.2449/1.3699)	mem 16099MB
[2025-01-18 11:05:57 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][190/312]	eta 0:00:58 lr 0.000099	time 0.4737 (0.4807)	model_time 0.4733 (0.4694)	loss 2.1306 (2.6400)	grad_norm 2.6372 (3.1840/1.3650)	mem 16099MB
[2025-01-18 11:06:02 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][200/312]	eta 0:00:53 lr 0.000099	time 0.4496 (0.4808)	model_time 0.4495 (0.4700)	loss 2.6252 (2.6562)	grad_norm 1.9827 (3.1318/1.3534)	mem 16099MB
[2025-01-18 11:06:06 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][210/312]	eta 0:00:48 lr 0.000099	time 0.4612 (0.4795)	model_time 0.4610 (0.4691)	loss 3.2555 (2.6577)	grad_norm 5.1322 (3.1122/1.3424)	mem 16099MB
[2025-01-18 11:06:11 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][220/312]	eta 0:00:44 lr 0.000099	time 0.4529 (0.4783)	model_time 0.4524 (0.4684)	loss 2.9541 (2.6606)	grad_norm 2.3575 (3.1109/1.3412)	mem 16099MB
[2025-01-18 11:06:15 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][230/312]	eta 0:00:39 lr 0.000098	time 0.4509 (0.4776)	model_time 0.4507 (0.4681)	loss 2.8421 (2.6663)	grad_norm 1.6337 (3.0960/1.3351)	mem 16099MB
[2025-01-18 11:06:20 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][240/312]	eta 0:00:34 lr 0.000098	time 0.4546 (0.4771)	model_time 0.4545 (0.4680)	loss 2.7738 (2.6699)	grad_norm 4.1448 (3.1192/1.3282)	mem 16099MB
[2025-01-18 11:06:25 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][250/312]	eta 0:00:29 lr 0.000098	time 0.5553 (0.4776)	model_time 0.5549 (0.4688)	loss 2.9203 (2.6581)	grad_norm 3.4717 (3.0966/1.3150)	mem 16099MB
[2025-01-18 11:06:29 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][260/312]	eta 0:00:24 lr 0.000098	time 0.4619 (0.4771)	model_time 0.4617 (0.4687)	loss 3.0967 (2.6607)	grad_norm 2.8421 (3.0874/1.3037)	mem 16099MB
[2025-01-18 11:06:34 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][270/312]	eta 0:00:20 lr 0.000098	time 0.5346 (0.4769)	model_time 0.5342 (0.4688)	loss 2.2466 (2.6597)	grad_norm 1.8823 (3.0568/1.3017)	mem 16099MB
[2025-01-18 11:06:39 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][280/312]	eta 0:00:15 lr 0.000098	time 0.4547 (0.4773)	model_time 0.4545 (0.4694)	loss 2.9334 (2.6617)	grad_norm 3.5149 (3.0479/1.3003)	mem 16099MB
[2025-01-18 11:06:44 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][290/312]	eta 0:00:10 lr 0.000098	time 0.4485 (0.4774)	model_time 0.4480 (0.4698)	loss 3.0916 (2.6597)	grad_norm 1.5168 (3.0314/1.3064)	mem 16099MB
[2025-01-18 11:06:49 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][300/312]	eta 0:00:05 lr 0.000097	time 0.4853 (0.4770)	model_time 0.4852 (0.4696)	loss 2.8868 (2.6575)	grad_norm 2.4783 (3.0343/1.3134)	mem 16099MB
[2025-01-18 11:06:53 internimage_t_1k_224] (main.py 510): INFO Train: [276/300][310/312]	eta 0:00:00 lr 0.000097	time 0.4441 (0.4761)	model_time 0.4440 (0.4689)	loss 2.7766 (2.6649)	grad_norm 3.5567 (2.9980/1.2887)	mem 16099MB
[2025-01-18 11:06:53 internimage_t_1k_224] (main.py 519): INFO EPOCH 276 training takes 0:02:28
[2025-01-18 11:06:53 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_276.pth saving......
[2025-01-18 11:06:55 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_276.pth saved !!!
[2025-01-18 11:07:02 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.365 (7.365)	Loss 0.7197 (0.7197)	Acc@1 85.303 (85.303)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 11:07:06 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (0.994)	Loss 0.9654 (0.8278)	Acc@1 79.175 (83.137)	Acc@5 95.264 (96.413)	Mem 16099MB
[2025-01-18 11:07:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:276] * Acc@1 82.991 Acc@5 96.409
[2025-01-18 11:07:06 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.0%
[2025-01-18 11:07:06 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.06%
[2025-01-18 11:07:14 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.414 (8.414)	Loss 0.7179 (0.7179)	Acc@1 85.864 (85.864)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 11:07:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.136)	Loss 0.9478 (0.8179)	Acc@1 79.785 (83.625)	Acc@5 95.410 (96.589)	Mem 16099MB
[2025-01-18 11:07:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:276] * Acc@1 83.481 Acc@5 96.589
[2025-01-18 11:07:18 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:07:18 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.49%
[2025-01-18 11:07:21 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][0/312]	eta 0:16:11 lr 0.000097	time 3.1152 (3.1152)	model_time 1.0102 (1.0102)	loss 3.0452 (3.0452)	grad_norm 1.9973 (1.9973/0.0000)	mem 16099MB
[2025-01-18 11:07:26 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][10/312]	eta 0:03:36 lr 0.000097	time 0.4594 (0.7167)	model_time 0.4593 (0.5251)	loss 2.7734 (2.5890)	grad_norm 2.7404 (2.8100/0.8891)	mem 16099MB
[2025-01-18 11:07:31 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][20/312]	eta 0:02:53 lr 0.000097	time 0.4456 (0.5925)	model_time 0.4454 (0.4919)	loss 3.2000 (2.7361)	grad_norm 7.8752 (3.3579/1.5363)	mem 16099MB
[2025-01-18 11:07:36 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][30/312]	eta 0:02:39 lr 0.000097	time 0.4545 (0.5639)	model_time 0.4540 (0.4956)	loss 2.9476 (2.6772)	grad_norm 2.0383 (3.4309/1.5346)	mem 16099MB
[2025-01-18 11:07:40 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][40/312]	eta 0:02:25 lr 0.000097	time 0.4557 (0.5366)	model_time 0.4555 (0.4849)	loss 2.9267 (2.6874)	grad_norm 1.6611 (3.5339/1.5464)	mem 16099MB
[2025-01-18 11:07:45 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][50/312]	eta 0:02:16 lr 0.000096	time 0.4437 (0.5228)	model_time 0.4433 (0.4812)	loss 2.3613 (2.6698)	grad_norm 1.2492 (3.5591/1.7266)	mem 16099MB
[2025-01-18 11:07:50 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][60/312]	eta 0:02:09 lr 0.000096	time 0.4605 (0.5124)	model_time 0.4600 (0.4776)	loss 2.8806 (2.6708)	grad_norm 2.7912 (3.4712/1.6311)	mem 16099MB
[2025-01-18 11:07:54 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][70/312]	eta 0:02:01 lr 0.000096	time 0.4525 (0.5039)	model_time 0.4523 (0.4739)	loss 2.7911 (2.6311)	grad_norm 1.5127 (3.3367/1.5740)	mem 16099MB
[2025-01-18 11:07:59 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][80/312]	eta 0:01:55 lr 0.000096	time 0.4424 (0.4990)	model_time 0.4422 (0.4727)	loss 2.8709 (2.5993)	grad_norm 2.0248 (3.2781/1.5322)	mem 16099MB
[2025-01-18 11:08:03 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][90/312]	eta 0:01:49 lr 0.000096	time 0.4535 (0.4945)	model_time 0.4533 (0.4710)	loss 3.1852 (2.6101)	grad_norm 1.7757 (3.1564/1.4944)	mem 16099MB
[2025-01-18 11:08:08 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][100/312]	eta 0:01:44 lr 0.000096	time 0.4476 (0.4921)	model_time 0.4474 (0.4709)	loss 1.8021 (2.6221)	grad_norm 2.3498 (3.0710/1.4469)	mem 16099MB
[2025-01-18 11:08:13 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][110/312]	eta 0:01:38 lr 0.000095	time 0.4516 (0.4893)	model_time 0.4512 (0.4700)	loss 1.7397 (2.6173)	grad_norm 6.0507 (3.0662/1.4184)	mem 16099MB
[2025-01-18 11:08:17 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][120/312]	eta 0:01:33 lr 0.000095	time 0.4679 (0.4881)	model_time 0.4674 (0.4704)	loss 2.8546 (2.6311)	grad_norm 2.3844 (3.0802/1.4083)	mem 16099MB
[2025-01-18 11:08:22 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][130/312]	eta 0:01:28 lr 0.000095	time 0.4632 (0.4862)	model_time 0.4627 (0.4698)	loss 1.8210 (2.6129)	grad_norm 2.1058 (3.0345/1.3984)	mem 16099MB
[2025-01-18 11:08:27 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][140/312]	eta 0:01:23 lr 0.000095	time 0.4582 (0.4846)	model_time 0.4580 (0.4693)	loss 3.1154 (2.6056)	grad_norm 1.8770 (2.9908/1.3922)	mem 16099MB
[2025-01-18 11:08:31 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][150/312]	eta 0:01:18 lr 0.000095	time 0.5211 (0.4841)	model_time 0.5206 (0.4698)	loss 2.9662 (2.6117)	grad_norm 3.5511 (2.9744/1.3802)	mem 16099MB
[2025-01-18 11:08:36 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][160/312]	eta 0:01:13 lr 0.000095	time 0.5653 (0.4849)	model_time 0.5644 (0.4715)	loss 3.1690 (2.6185)	grad_norm 1.9209 (2.9462/1.3660)	mem 16099MB
[2025-01-18 11:08:41 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][170/312]	eta 0:01:08 lr 0.000094	time 0.4406 (0.4834)	model_time 0.4404 (0.4707)	loss 2.6503 (2.6116)	grad_norm 1.5630 (2.9741/1.3767)	mem 16099MB
[2025-01-18 11:08:46 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][180/312]	eta 0:01:03 lr 0.000094	time 0.4657 (0.4827)	model_time 0.4656 (0.4707)	loss 3.2581 (2.6172)	grad_norm 5.1568 (2.9890/1.3629)	mem 16099MB
[2025-01-18 11:08:50 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][190/312]	eta 0:00:58 lr 0.000094	time 0.4670 (0.4812)	model_time 0.4665 (0.4699)	loss 3.0158 (2.6177)	grad_norm 3.2290 (2.9885/1.3642)	mem 16099MB
[2025-01-18 11:08:55 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][200/312]	eta 0:00:53 lr 0.000094	time 0.4449 (0.4812)	model_time 0.4445 (0.4704)	loss 3.4599 (2.6254)	grad_norm 4.0717 (2.9786/1.3459)	mem 16099MB
[2025-01-18 11:09:00 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][210/312]	eta 0:00:49 lr 0.000094	time 0.4538 (0.4807)	model_time 0.4536 (0.4704)	loss 1.9855 (2.6181)	grad_norm 3.2998 (2.9793/1.3340)	mem 16099MB
[2025-01-18 11:09:04 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][220/312]	eta 0:00:44 lr 0.000094	time 0.4550 (0.4800)	model_time 0.4549 (0.4702)	loss 3.5027 (2.6330)	grad_norm 1.9613 (2.9914/1.3516)	mem 16099MB
[2025-01-18 11:09:09 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][230/312]	eta 0:00:39 lr 0.000094	time 0.4626 (0.4791)	model_time 0.4621 (0.4696)	loss 2.5558 (2.6216)	grad_norm 2.2809 (3.0014/1.3823)	mem 16099MB
[2025-01-18 11:09:14 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][240/312]	eta 0:00:34 lr 0.000093	time 0.4613 (0.4782)	model_time 0.4611 (0.4691)	loss 2.6682 (2.6236)	grad_norm 1.7824 (3.0088/1.3877)	mem 16099MB
[2025-01-18 11:09:18 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][250/312]	eta 0:00:29 lr 0.000093	time 0.4480 (0.4773)	model_time 0.4479 (0.4686)	loss 2.7333 (2.6232)	grad_norm 2.6081 (3.0284/1.3936)	mem 16099MB
[2025-01-18 11:09:23 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][260/312]	eta 0:00:24 lr 0.000093	time 0.4644 (0.4780)	model_time 0.4640 (0.4696)	loss 1.9312 (2.6277)	grad_norm 4.1233 (3.0451/1.4205)	mem 16099MB
[2025-01-18 11:09:28 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][270/312]	eta 0:00:20 lr 0.000093	time 0.4402 (0.4780)	model_time 0.4400 (0.4699)	loss 2.2963 (2.6211)	grad_norm 4.5628 (3.0701/1.4212)	mem 16099MB
[2025-01-18 11:09:32 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][280/312]	eta 0:00:15 lr 0.000093	time 0.4691 (0.4774)	model_time 0.4689 (0.4696)	loss 2.7941 (2.6197)	grad_norm 1.6869 (3.0908/1.4248)	mem 16099MB
[2025-01-18 11:09:37 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][290/312]	eta 0:00:10 lr 0.000093	time 0.4779 (0.4771)	model_time 0.4773 (0.4696)	loss 2.9745 (2.6255)	grad_norm 5.0936 (3.1029/1.4141)	mem 16099MB
[2025-01-18 11:09:42 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][300/312]	eta 0:00:05 lr 0.000092	time 0.4400 (0.4765)	model_time 0.4399 (0.4692)	loss 2.2167 (2.6260)	grad_norm 3.1816 (3.1053/1.4134)	mem 16099MB
[2025-01-18 11:09:46 internimage_t_1k_224] (main.py 510): INFO Train: [277/300][310/312]	eta 0:00:00 lr 0.000092	time 0.4386 (0.4754)	model_time 0.4385 (0.4683)	loss 2.4959 (2.6306)	grad_norm 2.2210 (3.1068/1.4224)	mem 16099MB
[2025-01-18 11:09:47 internimage_t_1k_224] (main.py 519): INFO EPOCH 277 training takes 0:02:28
[2025-01-18 11:09:47 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_277.pth saving......
[2025-01-18 11:09:48 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_277.pth saved !!!
[2025-01-18 11:09:55 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.657 (7.657)	Loss 0.7278 (0.7278)	Acc@1 85.278 (85.278)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 11:09:59 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.035)	Loss 0.9826 (0.8322)	Acc@1 79.102 (83.148)	Acc@5 95.288 (96.331)	Mem 16099MB
[2025-01-18 11:09:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:277] * Acc@1 82.957 Acc@5 96.337
[2025-01-18 11:09:59 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.0%
[2025-01-18 11:09:59 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.06%
[2025-01-18 11:10:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.431 (8.431)	Loss 0.7173 (0.7173)	Acc@1 85.791 (85.791)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 11:10:12 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.127)	Loss 0.9469 (0.8172)	Acc@1 79.834 (83.625)	Acc@5 95.386 (96.593)	Mem 16099MB
[2025-01-18 11:10:12 internimage_t_1k_224] (main.py 575): INFO [Epoch:277] * Acc@1 83.477 Acc@5 96.587
[2025-01-18 11:10:12 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:10:12 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.49%
[2025-01-18 11:10:15 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][0/312]	eta 0:17:38 lr 0.000092	time 3.3920 (3.3920)	model_time 1.5373 (1.5373)	loss 1.6943 (1.6943)	grad_norm 3.4086 (3.4086/0.0000)	mem 16099MB
[2025-01-18 11:10:20 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][10/312]	eta 0:03:43 lr 0.000092	time 0.4554 (0.7398)	model_time 0.4552 (0.5707)	loss 2.5540 (2.6199)	grad_norm 2.5968 (2.4038/0.7842)	mem 16099MB
[2025-01-18 11:10:25 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][20/312]	eta 0:03:00 lr 0.000092	time 0.4542 (0.6169)	model_time 0.4538 (0.5282)	loss 2.6013 (2.5788)	grad_norm 1.7765 (2.3728/0.6977)	mem 16099MB
[2025-01-18 11:10:29 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][30/312]	eta 0:02:40 lr 0.000092	time 0.5453 (0.5705)	model_time 0.5448 (0.5103)	loss 2.7379 (2.5951)	grad_norm 3.3883 (2.3901/0.6990)	mem 16099MB
[2025-01-18 11:10:34 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][40/312]	eta 0:02:27 lr 0.000092	time 0.4433 (0.5432)	model_time 0.4431 (0.4976)	loss 2.4510 (2.5587)	grad_norm 5.5492 (2.6247/1.0377)	mem 16099MB
[2025-01-18 11:10:39 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][50/312]	eta 0:02:18 lr 0.000092	time 0.4576 (0.5279)	model_time 0.4572 (0.4911)	loss 2.9906 (2.6012)	grad_norm 2.8660 (2.9224/1.3054)	mem 16099MB
[2025-01-18 11:10:43 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][60/312]	eta 0:02:09 lr 0.000091	time 0.4558 (0.5158)	model_time 0.4557 (0.4850)	loss 2.6778 (2.6365)	grad_norm 2.1135 (2.9032/1.2640)	mem 16099MB
[2025-01-18 11:10:48 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][70/312]	eta 0:02:03 lr 0.000091	time 0.5346 (0.5088)	model_time 0.5344 (0.4823)	loss 2.8300 (2.5929)	grad_norm 1.7034 (2.8616/1.2286)	mem 16099MB
[2025-01-18 11:10:53 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][80/312]	eta 0:01:56 lr 0.000091	time 0.4811 (0.5041)	model_time 0.4806 (0.4808)	loss 2.0514 (2.6176)	grad_norm 2.4827 (2.8257/1.1826)	mem 16099MB
[2025-01-18 11:10:57 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][90/312]	eta 0:01:51 lr 0.000091	time 0.4475 (0.5007)	model_time 0.4471 (0.4799)	loss 2.8896 (2.6234)	grad_norm 4.9197 (2.9060/1.1817)	mem 16099MB
[2025-01-18 11:11:02 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][100/312]	eta 0:01:45 lr 0.000091	time 0.4530 (0.4981)	model_time 0.4526 (0.4794)	loss 2.7222 (2.6349)	grad_norm 3.9462 (2.8682/1.1522)	mem 16099MB
[2025-01-18 11:11:07 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][110/312]	eta 0:01:39 lr 0.000091	time 0.4784 (0.4950)	model_time 0.4780 (0.4779)	loss 2.7802 (2.6508)	grad_norm 3.9864 (2.8114/1.1453)	mem 16099MB
[2025-01-18 11:11:11 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][120/312]	eta 0:01:34 lr 0.000091	time 0.5327 (0.4930)	model_time 0.5325 (0.4773)	loss 2.5842 (2.6345)	grad_norm 2.3337 (2.8429/1.1829)	mem 16099MB
[2025-01-18 11:11:16 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][130/312]	eta 0:01:29 lr 0.000090	time 0.4535 (0.4913)	model_time 0.4533 (0.4768)	loss 3.4754 (2.6363)	grad_norm 2.9823 (2.8014/1.1542)	mem 16099MB
[2025-01-18 11:11:21 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][140/312]	eta 0:01:24 lr 0.000090	time 0.5613 (0.4915)	model_time 0.5611 (0.4780)	loss 3.4980 (2.6427)	grad_norm 2.7607 (2.8109/1.1282)	mem 16099MB
[2025-01-18 11:11:26 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][150/312]	eta 0:01:19 lr 0.000090	time 0.4575 (0.4907)	model_time 0.4574 (0.4780)	loss 3.2829 (2.6440)	grad_norm 3.6252 (2.7891/1.1120)	mem 16099MB
[2025-01-18 11:11:31 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][160/312]	eta 0:01:14 lr 0.000090	time 0.4541 (0.4891)	model_time 0.4537 (0.4773)	loss 2.9389 (2.6533)	grad_norm 3.2649 (2.7692/1.0988)	mem 16099MB
[2025-01-18 11:11:35 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][170/312]	eta 0:01:09 lr 0.000090	time 0.4773 (0.4872)	model_time 0.4769 (0.4760)	loss 3.1071 (2.6664)	grad_norm 2.1004 (2.7858/1.1254)	mem 16099MB
[2025-01-18 11:11:40 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][180/312]	eta 0:01:04 lr 0.000090	time 0.4455 (0.4865)	model_time 0.4450 (0.4759)	loss 2.4778 (2.6694)	grad_norm 2.6674 (2.7960/1.1277)	mem 16099MB
[2025-01-18 11:11:44 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][190/312]	eta 0:00:59 lr 0.000089	time 0.4498 (0.4849)	model_time 0.4494 (0.4749)	loss 3.4526 (2.6790)	grad_norm 3.6450 (2.7883/1.1244)	mem 16099MB
[2025-01-18 11:11:49 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][200/312]	eta 0:00:54 lr 0.000089	time 0.4530 (0.4836)	model_time 0.4525 (0.4740)	loss 3.3330 (2.6844)	grad_norm 2.2069 (2.7754/1.1087)	mem 16099MB
[2025-01-18 11:11:54 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][210/312]	eta 0:00:49 lr 0.000089	time 0.4443 (0.4835)	model_time 0.4441 (0.4743)	loss 1.9497 (2.6816)	grad_norm 1.3364 (2.7726/1.1222)	mem 16099MB
[2025-01-18 11:11:58 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][220/312]	eta 0:00:44 lr 0.000089	time 0.4726 (0.4821)	model_time 0.4722 (0.4734)	loss 2.7730 (2.6706)	grad_norm 1.5642 (2.7392/1.1212)	mem 16099MB
[2025-01-18 11:12:03 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][230/312]	eta 0:00:39 lr 0.000089	time 0.4412 (0.4809)	model_time 0.4407 (0.4725)	loss 1.6431 (2.6644)	grad_norm 1.9179 (2.7449/1.1183)	mem 16099MB
[2025-01-18 11:12:07 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][240/312]	eta 0:00:34 lr 0.000089	time 0.4448 (0.4798)	model_time 0.4443 (0.4717)	loss 2.7432 (2.6725)	grad_norm 2.9954 (2.7855/1.1377)	mem 16099MB
[2025-01-18 11:12:12 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][250/312]	eta 0:00:29 lr 0.000089	time 0.4513 (0.4795)	model_time 0.4508 (0.4717)	loss 2.3599 (2.6760)	grad_norm 3.4840 (2.7685/1.1292)	mem 16099MB
[2025-01-18 11:12:17 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][260/312]	eta 0:00:24 lr 0.000088	time 0.4450 (0.4794)	model_time 0.4447 (0.4719)	loss 2.8410 (2.6766)	grad_norm 4.1082 (2.7870/1.1396)	mem 16099MB
[2025-01-18 11:12:22 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][270/312]	eta 0:00:20 lr 0.000088	time 0.4439 (0.4789)	model_time 0.4434 (0.4717)	loss 3.0662 (2.6745)	grad_norm 3.3747 (2.8151/1.1398)	mem 16099MB
[2025-01-18 11:12:26 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][280/312]	eta 0:00:15 lr 0.000088	time 0.4897 (0.4783)	model_time 0.4895 (0.4713)	loss 2.3830 (2.6624)	grad_norm 1.7829 (2.8115/1.1597)	mem 16099MB
[2025-01-18 11:12:31 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][290/312]	eta 0:00:10 lr 0.000088	time 0.4616 (0.4784)	model_time 0.4614 (0.4716)	loss 3.0454 (2.6606)	grad_norm 2.0909 (2.7909/1.1669)	mem 16099MB
[2025-01-18 11:12:36 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][300/312]	eta 0:00:05 lr 0.000088	time 0.4404 (0.4777)	model_time 0.4403 (0.4712)	loss 3.1889 (2.6673)	grad_norm 1.6392 (2.7734/1.1574)	mem 16099MB
[2025-01-18 11:12:40 internimage_t_1k_224] (main.py 510): INFO Train: [278/300][310/312]	eta 0:00:00 lr 0.000088	time 0.4415 (0.4774)	model_time 0.4414 (0.4711)	loss 2.4996 (2.6699)	grad_norm 1.9561 (2.7809/1.1602)	mem 16099MB
[2025-01-18 11:12:41 internimage_t_1k_224] (main.py 519): INFO EPOCH 278 training takes 0:02:28
[2025-01-18 11:12:41 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_278.pth saving......
[2025-01-18 11:12:42 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_278.pth saved !!!
[2025-01-18 11:12:49 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.414 (7.414)	Loss 0.7335 (0.7335)	Acc@1 85.327 (85.327)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 11:12:53 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.032)	Loss 0.9700 (0.8282)	Acc@1 78.809 (83.183)	Acc@5 95.239 (96.322)	Mem 16099MB
[2025-01-18 11:12:53 internimage_t_1k_224] (main.py 575): INFO [Epoch:278] * Acc@1 83.051 Acc@5 96.315
[2025-01-18 11:12:53 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:12:53 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.06%
[2025-01-18 11:13:02 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.382 (8.382)	Loss 0.7168 (0.7168)	Acc@1 85.840 (85.840)	Acc@5 97.729 (97.729)	Mem 16099MB
[2025-01-18 11:13:06 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.132)	Loss 0.9464 (0.8166)	Acc@1 79.858 (83.638)	Acc@5 95.386 (96.584)	Mem 16099MB
[2025-01-18 11:13:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:278] * Acc@1 83.487 Acc@5 96.579
[2025-01-18 11:13:06 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:13:06 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.49%
[2025-01-18 11:13:09 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][0/312]	eta 0:18:31 lr 0.000088	time 3.5625 (3.5625)	model_time 0.5430 (0.5430)	loss 2.5892 (2.5892)	grad_norm 3.1057 (3.1057/0.0000)	mem 16099MB
[2025-01-18 11:13:14 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][10/312]	eta 0:03:51 lr 0.000088	time 0.5738 (0.7675)	model_time 0.5734 (0.4925)	loss 2.1612 (2.4614)	grad_norm 2.8682 (3.0805/1.1628)	mem 16099MB
[2025-01-18 11:13:19 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][20/312]	eta 0:03:02 lr 0.000087	time 0.4501 (0.6266)	model_time 0.4500 (0.4824)	loss 2.7515 (2.6003)	grad_norm 2.5973 (3.5122/1.3348)	mem 16099MB
[2025-01-18 11:13:24 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][30/312]	eta 0:02:42 lr 0.000087	time 0.5869 (0.5763)	model_time 0.5868 (0.4785)	loss 3.0623 (2.5932)	grad_norm 3.8447 (3.2605/1.3294)	mem 16099MB
[2025-01-18 11:13:28 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][40/312]	eta 0:02:29 lr 0.000087	time 0.4598 (0.5502)	model_time 0.4595 (0.4762)	loss 3.1805 (2.5805)	grad_norm 1.4561 (3.1650/1.4185)	mem 16099MB
[2025-01-18 11:13:33 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][50/312]	eta 0:02:20 lr 0.000087	time 0.4462 (0.5349)	model_time 0.4460 (0.4754)	loss 3.1290 (2.5830)	grad_norm 1.9616 (3.1933/1.3319)	mem 16099MB
[2025-01-18 11:13:38 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][60/312]	eta 0:02:11 lr 0.000087	time 0.4436 (0.5231)	model_time 0.4435 (0.4732)	loss 1.8842 (2.5863)	grad_norm 6.8708 (3.1879/1.3517)	mem 16099MB
[2025-01-18 11:13:42 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][70/312]	eta 0:02:04 lr 0.000087	time 0.4608 (0.5140)	model_time 0.4603 (0.4711)	loss 3.1755 (2.6263)	grad_norm 6.0277 (3.3020/1.4049)	mem 16099MB
[2025-01-18 11:13:47 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][80/312]	eta 0:01:57 lr 0.000087	time 0.4720 (0.5076)	model_time 0.4715 (0.4700)	loss 3.2903 (2.6324)	grad_norm 4.0552 (3.2509/1.3790)	mem 16099MB
[2025-01-18 11:13:52 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][90/312]	eta 0:01:51 lr 0.000086	time 0.5623 (0.5037)	model_time 0.5622 (0.4701)	loss 2.9430 (2.6073)	grad_norm 2.7609 (3.1766/1.3544)	mem 16099MB
[2025-01-18 11:13:56 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][100/312]	eta 0:01:46 lr 0.000086	time 0.4521 (0.5001)	model_time 0.4519 (0.4698)	loss 3.5908 (2.6051)	grad_norm 3.2688 (3.1192/1.3422)	mem 16099MB
[2025-01-18 11:14:01 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][110/312]	eta 0:01:40 lr 0.000086	time 0.4510 (0.4960)	model_time 0.4508 (0.4684)	loss 2.8717 (2.6104)	grad_norm 2.4990 (3.1385/1.3051)	mem 16099MB
[2025-01-18 11:14:06 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][120/312]	eta 0:01:34 lr 0.000086	time 0.5385 (0.4941)	model_time 0.5380 (0.4688)	loss 1.9260 (2.6077)	grad_norm 1.9147 (3.1968/1.3453)	mem 16099MB
[2025-01-18 11:14:10 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][130/312]	eta 0:01:29 lr 0.000086	time 0.4675 (0.4920)	model_time 0.4674 (0.4686)	loss 2.9011 (2.6216)	grad_norm 2.9681 (3.2244/1.4197)	mem 16099MB
[2025-01-18 11:14:15 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][140/312]	eta 0:01:24 lr 0.000086	time 0.4469 (0.4907)	model_time 0.4468 (0.4689)	loss 2.4235 (2.6406)	grad_norm 2.3207 (3.2261/1.4109)	mem 16099MB
[2025-01-18 11:14:20 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][150/312]	eta 0:01:19 lr 0.000086	time 0.4407 (0.4904)	model_time 0.4406 (0.4701)	loss 3.2637 (2.6468)	grad_norm 4.1568 (3.2180/1.4310)	mem 16099MB
[2025-01-18 11:14:25 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][160/312]	eta 0:01:14 lr 0.000085	time 0.5313 (0.4898)	model_time 0.5308 (0.4707)	loss 2.5358 (2.6381)	grad_norm 1.9075 (3.1939/1.4088)	mem 16099MB
[2025-01-18 11:14:30 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][170/312]	eta 0:01:09 lr 0.000085	time 0.4542 (0.4887)	model_time 0.4540 (0.4707)	loss 1.7367 (2.6385)	grad_norm 2.1216 (3.1279/1.4006)	mem 16099MB
[2025-01-18 11:14:34 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][180/312]	eta 0:01:04 lr 0.000085	time 0.5496 (0.4882)	model_time 0.5492 (0.4712)	loss 2.7403 (2.6384)	grad_norm 1.5619 (3.0897/1.3944)	mem 16099MB
[2025-01-18 11:14:39 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][190/312]	eta 0:00:59 lr 0.000085	time 0.4412 (0.4871)	model_time 0.4407 (0.4709)	loss 3.0896 (2.6444)	grad_norm 2.3615 (3.0645/1.3872)	mem 16099MB
[2025-01-18 11:14:44 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][200/312]	eta 0:00:54 lr 0.000085	time 0.4520 (0.4857)	model_time 0.4516 (0.4703)	loss 3.2728 (2.6565)	grad_norm 1.3549 (3.0739/1.4046)	mem 16099MB
[2025-01-18 11:14:48 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][210/312]	eta 0:00:49 lr 0.000085	time 0.4639 (0.4847)	model_time 0.4635 (0.4700)	loss 2.8422 (2.6650)	grad_norm 6.0486 (3.0940/1.4172)	mem 16099MB
[2025-01-18 11:14:53 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][220/312]	eta 0:00:44 lr 0.000085	time 0.4696 (0.4835)	model_time 0.4691 (0.4694)	loss 2.5764 (2.6766)	grad_norm 3.8907 (3.1023/1.4048)	mem 16099MB
[2025-01-18 11:14:57 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][230/312]	eta 0:00:39 lr 0.000084	time 0.4811 (0.4824)	model_time 0.4807 (0.4689)	loss 1.7696 (2.6688)	grad_norm 1.4100 (3.0727/1.3948)	mem 16099MB
[2025-01-18 11:15:02 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][240/312]	eta 0:00:34 lr 0.000084	time 0.4609 (0.4820)	model_time 0.4608 (0.4691)	loss 3.0766 (2.6684)	grad_norm 2.4634 (3.0428/1.3790)	mem 16099MB
[2025-01-18 11:15:07 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][250/312]	eta 0:00:29 lr 0.000084	time 0.4612 (0.4814)	model_time 0.4608 (0.4690)	loss 3.2136 (2.6655)	grad_norm 4.0045 (3.0158/1.3663)	mem 16099MB
[2025-01-18 11:15:11 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][260/312]	eta 0:00:24 lr 0.000084	time 0.4488 (0.4803)	model_time 0.4487 (0.4684)	loss 2.8588 (2.6701)	grad_norm 2.6825 (3.0048/1.3564)	mem 16099MB
[2025-01-18 11:15:16 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][270/312]	eta 0:00:20 lr 0.000084	time 0.4528 (0.4797)	model_time 0.4526 (0.4682)	loss 3.0666 (2.6721)	grad_norm 2.7704 (2.9950/1.3510)	mem 16099MB
[2025-01-18 11:15:20 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][280/312]	eta 0:00:15 lr 0.000084	time 0.4533 (0.4789)	model_time 0.4531 (0.4677)	loss 2.8099 (2.6727)	grad_norm 2.1606 (2.9951/1.3425)	mem 16099MB
[2025-01-18 11:15:25 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][290/312]	eta 0:00:10 lr 0.000084	time 0.4430 (0.4784)	model_time 0.4429 (0.4676)	loss 2.5951 (2.6738)	grad_norm 2.7364 (2.9973/1.3362)	mem 16099MB
[2025-01-18 11:15:30 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][300/312]	eta 0:00:05 lr 0.000083	time 0.4454 (0.4783)	model_time 0.4453 (0.4679)	loss 2.7694 (2.6701)	grad_norm 2.0467 (2.9689/1.3337)	mem 16099MB
[2025-01-18 11:15:34 internimage_t_1k_224] (main.py 510): INFO Train: [279/300][310/312]	eta 0:00:00 lr 0.000083	time 0.4385 (0.4774)	model_time 0.4384 (0.4673)	loss 3.1038 (2.6767)	grad_norm 1.8894 (2.9517/1.3244)	mem 16099MB
[2025-01-18 11:15:35 internimage_t_1k_224] (main.py 519): INFO EPOCH 279 training takes 0:02:28
[2025-01-18 11:15:35 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_279.pth saving......
[2025-01-18 11:15:36 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_279.pth saved !!!
[2025-01-18 11:15:44 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.767 (7.767)	Loss 0.7286 (0.7286)	Acc@1 85.278 (85.278)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 11:15:47 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.035)	Loss 0.9672 (0.8239)	Acc@1 78.955 (83.152)	Acc@5 95.239 (96.305)	Mem 16099MB
[2025-01-18 11:15:47 internimage_t_1k_224] (main.py 575): INFO [Epoch:279] * Acc@1 82.983 Acc@5 96.303
[2025-01-18 11:15:47 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.0%
[2025-01-18 11:15:47 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.06%
[2025-01-18 11:15:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.514 (8.514)	Loss 0.7165 (0.7165)	Acc@1 85.791 (85.791)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 11:16:00 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.146)	Loss 0.9463 (0.8162)	Acc@1 79.810 (83.647)	Acc@5 95.386 (96.589)	Mem 16099MB
[2025-01-18 11:16:00 internimage_t_1k_224] (main.py 575): INFO [Epoch:279] * Acc@1 83.495 Acc@5 96.581
[2025-01-18 11:16:00 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:16:00 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 11:16:02 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 11:16:02 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.50%
[2025-01-18 11:16:04 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][0/312]	eta 0:12:05 lr 0.000083	time 2.3252 (2.3252)	model_time 0.4702 (0.4702)	loss 3.2347 (3.2347)	grad_norm 2.5480 (2.5480/0.0000)	mem 16099MB
[2025-01-18 11:16:09 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][10/312]	eta 0:03:16 lr 0.000083	time 0.4493 (0.6494)	model_time 0.4492 (0.4805)	loss 2.4029 (2.8730)	grad_norm 2.5779 (3.2281/1.3376)	mem 16099MB
[2025-01-18 11:16:13 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][20/312]	eta 0:02:44 lr 0.000083	time 0.5549 (0.5622)	model_time 0.5544 (0.4735)	loss 2.7966 (2.7240)	grad_norm 5.0168 (3.0192/1.3285)	mem 16099MB
[2025-01-18 11:16:18 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][30/312]	eta 0:02:30 lr 0.000083	time 0.4507 (0.5347)	model_time 0.4505 (0.4745)	loss 3.1556 (2.7233)	grad_norm 1.9619 (2.8593/1.3794)	mem 16099MB
[2025-01-18 11:16:23 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][40/312]	eta 0:02:21 lr 0.000083	time 0.4525 (0.5194)	model_time 0.4521 (0.4738)	loss 3.2321 (2.6924)	grad_norm 2.6856 (2.7173/1.2813)	mem 16099MB
[2025-01-18 11:16:28 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][50/312]	eta 0:02:13 lr 0.000083	time 0.4619 (0.5104)	model_time 0.4615 (0.4736)	loss 2.8528 (2.6674)	grad_norm 3.3694 (2.7249/1.2575)	mem 16099MB
[2025-01-18 11:16:32 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][60/312]	eta 0:02:07 lr 0.000082	time 0.4530 (0.5045)	model_time 0.4529 (0.4737)	loss 2.7592 (2.6812)	grad_norm 6.0816 (2.7834/1.2813)	mem 16099MB
[2025-01-18 11:16:37 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][70/312]	eta 0:02:00 lr 0.000082	time 0.4540 (0.4992)	model_time 0.4538 (0.4727)	loss 1.7536 (2.6818)	grad_norm 4.3526 (2.8249/1.2804)	mem 16099MB
[2025-01-18 11:16:42 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][80/312]	eta 0:01:55 lr 0.000082	time 0.4506 (0.4974)	model_time 0.4501 (0.4741)	loss 3.0371 (2.6554)	grad_norm 1.9591 (2.7626/1.2449)	mem 16099MB
[2025-01-18 11:16:47 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][90/312]	eta 0:01:49 lr 0.000082	time 0.4589 (0.4941)	model_time 0.4588 (0.4734)	loss 2.3085 (2.6764)	grad_norm 1.7648 (2.7257/1.2313)	mem 16099MB
[2025-01-18 11:16:51 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][100/312]	eta 0:01:43 lr 0.000082	time 0.4421 (0.4905)	model_time 0.4417 (0.4718)	loss 3.1988 (2.6856)	grad_norm 1.3325 (2.6484/1.2087)	mem 16099MB
[2025-01-18 11:16:56 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][110/312]	eta 0:01:38 lr 0.000082	time 0.4533 (0.4877)	model_time 0.4528 (0.4705)	loss 2.5496 (2.6707)	grad_norm 3.1180 (2.7050/1.2041)	mem 16099MB
[2025-01-18 11:17:00 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][120/312]	eta 0:01:33 lr 0.000082	time 0.4623 (0.4853)	model_time 0.4622 (0.4696)	loss 2.9286 (2.6594)	grad_norm 1.3671 (2.7383/1.2476)	mem 16099MB
[2025-01-18 11:17:05 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][130/312]	eta 0:01:28 lr 0.000081	time 0.4403 (0.4837)	model_time 0.4398 (0.4692)	loss 3.3056 (2.6676)	grad_norm 2.8660 (2.8407/1.3128)	mem 16099MB
[2025-01-18 11:17:10 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][140/312]	eta 0:01:22 lr 0.000081	time 0.4551 (0.4822)	model_time 0.4546 (0.4687)	loss 2.6175 (2.6737)	grad_norm 2.3165 (2.8648/1.3091)	mem 16099MB
[2025-01-18 11:17:14 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][150/312]	eta 0:01:17 lr 0.000081	time 0.4602 (0.4810)	model_time 0.4597 (0.4683)	loss 2.8621 (2.6520)	grad_norm 2.9909 (2.8335/1.2799)	mem 16099MB
[2025-01-18 11:17:19 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][160/312]	eta 0:01:13 lr 0.000081	time 0.5326 (0.4810)	model_time 0.5322 (0.4691)	loss 2.8133 (2.6552)	grad_norm 1.8503 (2.8033/1.2554)	mem 16099MB
[2025-01-18 11:17:24 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][170/312]	eta 0:01:08 lr 0.000081	time 0.4572 (0.4797)	model_time 0.4567 (0.4684)	loss 2.8738 (2.6636)	grad_norm 2.3658 (2.7914/1.2281)	mem 16099MB
[2025-01-18 11:17:28 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][180/312]	eta 0:01:03 lr 0.000081	time 0.4533 (0.4789)	model_time 0.4529 (0.4682)	loss 2.8850 (2.6617)	grad_norm 3.8632 (2.7695/1.2234)	mem 16099MB
[2025-01-18 11:17:33 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][190/312]	eta 0:00:58 lr 0.000081	time 0.4543 (0.4779)	model_time 0.4541 (0.4678)	loss 2.8592 (2.6672)	grad_norm 1.7380 (2.7758/1.2025)	mem 16099MB
[2025-01-18 11:17:38 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][200/312]	eta 0:00:53 lr 0.000081	time 0.4461 (0.4779)	model_time 0.4457 (0.4682)	loss 2.8123 (2.6718)	grad_norm 5.6222 (2.7821/1.2196)	mem 16099MB
[2025-01-18 11:17:42 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][210/312]	eta 0:00:48 lr 0.000080	time 0.4406 (0.4773)	model_time 0.4404 (0.4681)	loss 2.9753 (2.6751)	grad_norm 1.6544 (2.7896/1.2184)	mem 16099MB
[2025-01-18 11:17:47 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][220/312]	eta 0:00:43 lr 0.000080	time 0.4707 (0.4764)	model_time 0.4705 (0.4676)	loss 2.5142 (2.6842)	grad_norm 4.1609 (2.8191/1.2159)	mem 16099MB
[2025-01-18 11:17:52 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][230/312]	eta 0:00:39 lr 0.000080	time 0.5617 (0.4763)	model_time 0.5613 (0.4679)	loss 2.9391 (2.6835)	grad_norm 2.5826 (2.8330/1.2044)	mem 16099MB
[2025-01-18 11:17:56 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][240/312]	eta 0:00:34 lr 0.000080	time 0.5600 (0.4764)	model_time 0.5598 (0.4683)	loss 2.6753 (2.6816)	grad_norm 3.9695 (2.8122/1.1960)	mem 16099MB
[2025-01-18 11:18:01 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][250/312]	eta 0:00:29 lr 0.000080	time 0.4589 (0.4757)	model_time 0.4587 (0.4679)	loss 2.9089 (2.6859)	grad_norm 4.8740 (2.8179/1.2111)	mem 16099MB
[2025-01-18 11:18:06 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][260/312]	eta 0:00:24 lr 0.000080	time 0.4522 (0.4757)	model_time 0.4520 (0.4682)	loss 2.4066 (2.6760)	grad_norm 4.6319 (2.8391/1.2042)	mem 16099MB
[2025-01-18 11:18:11 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][270/312]	eta 0:00:19 lr 0.000080	time 0.4749 (0.4755)	model_time 0.4747 (0.4683)	loss 2.7573 (2.6831)	grad_norm 2.2458 (2.8842/1.2344)	mem 16099MB
[2025-01-18 11:18:15 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][280/312]	eta 0:00:15 lr 0.000079	time 0.4530 (0.4753)	model_time 0.4526 (0.4683)	loss 1.7575 (2.6770)	grad_norm 7.4575 (2.9028/1.2574)	mem 16099MB
[2025-01-18 11:18:20 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][290/312]	eta 0:00:10 lr 0.000079	time 0.5449 (0.4753)	model_time 0.5445 (0.4685)	loss 1.8462 (2.6737)	grad_norm 4.1534 (2.9470/1.3013)	mem 16099MB
[2025-01-18 11:18:25 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][300/312]	eta 0:00:05 lr 0.000079	time 0.4398 (0.4750)	model_time 0.4397 (0.4684)	loss 3.0892 (2.6744)	grad_norm 7.2890 (2.9547/1.3270)	mem 16099MB
[2025-01-18 11:18:29 internimage_t_1k_224] (main.py 510): INFO Train: [280/300][310/312]	eta 0:00:00 lr 0.000079	time 0.4413 (0.4745)	model_time 0.4412 (0.4681)	loss 2.2180 (2.6710)	grad_norm 1.7318 (2.9193/1.3154)	mem 16099MB
[2025-01-18 11:18:30 internimage_t_1k_224] (main.py 519): INFO EPOCH 280 training takes 0:02:28
[2025-01-18 11:18:30 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_280.pth saving......
[2025-01-18 11:18:31 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_280.pth saved !!!
[2025-01-18 11:18:38 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.250 (7.250)	Loss 0.7234 (0.7234)	Acc@1 85.229 (85.229)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 11:18:42 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.108 (0.987)	Loss 0.9669 (0.8248)	Acc@1 79.053 (83.141)	Acc@5 95.239 (96.333)	Mem 16099MB
[2025-01-18 11:18:42 internimage_t_1k_224] (main.py 575): INFO [Epoch:280] * Acc@1 82.979 Acc@5 96.333
[2025-01-18 11:18:42 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.0%
[2025-01-18 11:18:42 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.06%
[2025-01-18 11:18:50 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.490 (8.490)	Loss 0.7162 (0.7162)	Acc@1 85.791 (85.791)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 11:18:54 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.126)	Loss 0.9459 (0.8158)	Acc@1 79.858 (83.663)	Acc@5 95.361 (96.575)	Mem 16099MB
[2025-01-18 11:18:54 internimage_t_1k_224] (main.py 575): INFO [Epoch:280] * Acc@1 83.507 Acc@5 96.567
[2025-01-18 11:18:54 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:18:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 11:18:56 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 11:18:56 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.51%
[2025-01-18 11:18:59 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][0/312]	eta 0:15:48 lr 0.000079	time 3.0399 (3.0399)	model_time 0.4670 (0.4670)	loss 2.6786 (2.6786)	grad_norm 1.6426 (1.6426/0.0000)	mem 16099MB
[2025-01-18 11:19:04 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][10/312]	eta 0:03:33 lr 0.000079	time 0.4750 (0.7085)	model_time 0.4748 (0.4743)	loss 1.6623 (2.5390)	grad_norm 3.7573 (2.8568/0.8975)	mem 16099MB
[2025-01-18 11:19:08 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][20/312]	eta 0:02:52 lr 0.000079	time 0.4453 (0.5919)	model_time 0.4452 (0.4691)	loss 2.5385 (2.5663)	grad_norm 2.7371 (2.7517/0.8860)	mem 16099MB
[2025-01-18 11:19:13 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][30/312]	eta 0:02:35 lr 0.000079	time 0.4497 (0.5526)	model_time 0.4495 (0.4693)	loss 3.0248 (2.6441)	grad_norm 1.5552 (2.6241/0.8662)	mem 16099MB
[2025-01-18 11:19:18 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][40/312]	eta 0:02:23 lr 0.000079	time 0.4549 (0.5290)	model_time 0.4545 (0.4659)	loss 2.8555 (2.6286)	grad_norm 3.0915 (2.7220/0.9114)	mem 16099MB
[2025-01-18 11:19:22 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][50/312]	eta 0:02:15 lr 0.000078	time 0.4427 (0.5172)	model_time 0.4423 (0.4664)	loss 2.0296 (2.6465)	grad_norm 3.5282 (2.7744/0.9608)	mem 16099MB
[2025-01-18 11:19:27 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][60/312]	eta 0:02:08 lr 0.000078	time 0.4561 (0.5082)	model_time 0.4560 (0.4657)	loss 2.7079 (2.6536)	grad_norm 4.3632 (2.8878/1.0624)	mem 16099MB
[2025-01-18 11:19:31 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][70/312]	eta 0:02:01 lr 0.000078	time 0.4525 (0.5016)	model_time 0.4520 (0.4650)	loss 2.6583 (2.6440)	grad_norm 2.5148 (2.9047/1.1696)	mem 16099MB
[2025-01-18 11:19:36 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][80/312]	eta 0:01:55 lr 0.000078	time 0.4529 (0.4976)	model_time 0.4525 (0.4655)	loss 3.1242 (2.6668)	grad_norm 3.7217 (2.8427/1.1737)	mem 16099MB
[2025-01-18 11:19:41 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][90/312]	eta 0:01:49 lr 0.000078	time 0.4791 (0.4935)	model_time 0.4789 (0.4649)	loss 2.7743 (2.6892)	grad_norm 2.5053 (2.8437/1.1515)	mem 16099MB
[2025-01-18 11:19:45 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][100/312]	eta 0:01:44 lr 0.000078	time 0.4512 (0.4914)	model_time 0.4511 (0.4656)	loss 2.8028 (2.6860)	grad_norm 1.7499 (2.8097/1.1324)	mem 16099MB
[2025-01-18 11:19:50 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][110/312]	eta 0:01:38 lr 0.000078	time 0.4646 (0.4891)	model_time 0.4642 (0.4655)	loss 3.0660 (2.6777)	grad_norm 2.3743 (2.8372/1.1289)	mem 16099MB
[2025-01-18 11:19:55 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][120/312]	eta 0:01:33 lr 0.000078	time 0.6682 (0.4878)	model_time 0.6677 (0.4662)	loss 2.1152 (2.6813)	grad_norm 3.3979 (2.8149/1.0981)	mem 16099MB
[2025-01-18 11:19:59 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][130/312]	eta 0:01:28 lr 0.000077	time 0.4472 (0.4857)	model_time 0.4468 (0.4657)	loss 2.8418 (2.6881)	grad_norm 1.7030 (2.8057/1.0905)	mem 16099MB
[2025-01-18 11:20:04 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][140/312]	eta 0:01:23 lr 0.000077	time 0.5460 (0.4853)	model_time 0.5455 (0.4667)	loss 2.3272 (2.6821)	grad_norm 3.1860 (2.8053/1.0606)	mem 16099MB
[2025-01-18 11:20:09 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][150/312]	eta 0:01:18 lr 0.000077	time 0.4568 (0.4847)	model_time 0.4566 (0.4672)	loss 2.6044 (2.6707)	grad_norm 4.5309 (2.8493/1.0729)	mem 16099MB
[2025-01-18 11:20:14 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][160/312]	eta 0:01:13 lr 0.000077	time 0.5399 (0.4846)	model_time 0.5394 (0.4682)	loss 3.2118 (2.6739)	grad_norm 2.3211 (2.8389/1.0680)	mem 16099MB
[2025-01-18 11:20:18 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][170/312]	eta 0:01:08 lr 0.000077	time 0.4560 (0.4831)	model_time 0.4555 (0.4677)	loss 2.1754 (2.6631)	grad_norm 1.7269 (2.8553/1.1032)	mem 16099MB
[2025-01-18 11:20:23 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][180/312]	eta 0:01:03 lr 0.000077	time 0.4515 (0.4828)	model_time 0.4513 (0.4682)	loss 2.9250 (2.6675)	grad_norm 4.9068 (2.8779/1.1233)	mem 16099MB
[2025-01-18 11:20:28 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][190/312]	eta 0:00:58 lr 0.000077	time 0.4656 (0.4815)	model_time 0.4652 (0.4677)	loss 3.1950 (2.6633)	grad_norm 1.7214 (2.8712/1.1199)	mem 16099MB
[2025-01-18 11:20:32 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][200/312]	eta 0:00:53 lr 0.000076	time 0.4794 (0.4807)	model_time 0.4790 (0.4676)	loss 2.7024 (2.6670)	grad_norm 4.2714 (2.8888/1.1388)	mem 16099MB
[2025-01-18 11:20:37 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][210/312]	eta 0:00:48 lr 0.000076	time 0.4615 (0.4800)	model_time 0.4611 (0.4675)	loss 3.0022 (2.6743)	grad_norm 2.3718 (2.9138/1.1329)	mem 16099MB
[2025-01-18 11:20:42 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][220/312]	eta 0:00:44 lr 0.000076	time 0.4530 (0.4795)	model_time 0.4528 (0.4674)	loss 3.0409 (2.6796)	grad_norm 2.4505 (2.9245/1.1488)	mem 16099MB
[2025-01-18 11:20:46 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][230/312]	eta 0:00:39 lr 0.000076	time 0.4533 (0.4788)	model_time 0.4529 (0.4673)	loss 3.0202 (2.6738)	grad_norm 3.0280 (2.9568/1.1860)	mem 16099MB
[2025-01-18 11:20:51 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][240/312]	eta 0:00:34 lr 0.000076	time 0.4433 (0.4782)	model_time 0.4432 (0.4671)	loss 2.5634 (2.6600)	grad_norm 4.9421 (2.9810/1.2195)	mem 16099MB
[2025-01-18 11:20:56 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][250/312]	eta 0:00:29 lr 0.000076	time 0.4497 (0.4772)	model_time 0.4493 (0.4666)	loss 2.6630 (2.6596)	grad_norm 2.4132 (2.9884/1.2117)	mem 16099MB
[2025-01-18 11:21:00 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][260/312]	eta 0:00:24 lr 0.000076	time 0.4467 (0.4767)	model_time 0.4465 (0.4665)	loss 1.9891 (2.6601)	grad_norm 2.0266 (3.0286/1.2941)	mem 16099MB
[2025-01-18 11:21:05 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][270/312]	eta 0:00:19 lr 0.000076	time 0.4509 (0.4762)	model_time 0.4504 (0.4663)	loss 2.7740 (2.6567)	grad_norm 2.9047 (3.0069/1.2814)	mem 16099MB
[2025-01-18 11:21:10 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][280/312]	eta 0:00:15 lr 0.000075	time 0.4502 (0.4757)	model_time 0.4501 (0.4662)	loss 3.2742 (2.6584)	grad_norm 2.1184 (3.0008/1.2747)	mem 16099MB
[2025-01-18 11:21:14 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][290/312]	eta 0:00:10 lr 0.000075	time 0.4756 (0.4750)	model_time 0.4751 (0.4658)	loss 2.9978 (2.6639)	grad_norm 2.6101 (2.9814/1.2750)	mem 16099MB
[2025-01-18 11:21:19 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][300/312]	eta 0:00:05 lr 0.000075	time 0.4430 (0.4741)	model_time 0.4429 (0.4652)	loss 2.6171 (2.6541)	grad_norm 1.7361 (2.9632/1.2619)	mem 16099MB
[2025-01-18 11:21:23 internimage_t_1k_224] (main.py 510): INFO Train: [281/300][310/312]	eta 0:00:00 lr 0.000075	time 0.4407 (0.4733)	model_time 0.4406 (0.4646)	loss 3.0190 (2.6647)	grad_norm 6.4147 (2.9750/1.2878)	mem 16099MB
[2025-01-18 11:21:23 internimage_t_1k_224] (main.py 519): INFO EPOCH 281 training takes 0:02:27
[2025-01-18 11:21:24 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_281.pth saving......
[2025-01-18 11:21:25 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_281.pth saved !!!
[2025-01-18 11:21:32 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.714 (7.714)	Loss 0.7110 (0.7110)	Acc@1 85.303 (85.303)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 11:21:36 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.023)	Loss 0.9664 (0.8146)	Acc@1 78.638 (83.279)	Acc@5 95.239 (96.365)	Mem 16099MB
[2025-01-18 11:21:36 internimage_t_1k_224] (main.py 575): INFO [Epoch:281] * Acc@1 83.119 Acc@5 96.369
[2025-01-18 11:21:36 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:21:36 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 11:21:37 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 11:21:37 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.12%
[2025-01-18 11:21:45 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.777 (7.777)	Loss 0.7156 (0.7156)	Acc@1 85.889 (85.889)	Acc@5 97.681 (97.681)	Mem 16099MB
[2025-01-18 11:21:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.056)	Loss 0.9454 (0.8151)	Acc@1 79.883 (83.676)	Acc@5 95.386 (96.584)	Mem 16099MB
[2025-01-18 11:21:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:281] * Acc@1 83.521 Acc@5 96.577
[2025-01-18 11:21:49 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:21:49 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 11:21:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 11:21:51 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.52%
[2025-01-18 11:21:53 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][0/312]	eta 0:12:44 lr 0.000075	time 2.4516 (2.4516)	model_time 0.4835 (0.4835)	loss 3.0005 (3.0005)	grad_norm 3.9153 (3.9153/0.0000)	mem 16099MB
[2025-01-18 11:21:58 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][10/312]	eta 0:03:17 lr 0.000075	time 0.5526 (0.6556)	model_time 0.5522 (0.4763)	loss 2.8620 (2.7097)	grad_norm 3.8227 (3.3682/1.3032)	mem 16099MB
[2025-01-18 11:22:03 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][20/312]	eta 0:02:46 lr 0.000075	time 0.4595 (0.5707)	model_time 0.4591 (0.4766)	loss 2.8792 (2.6305)	grad_norm 2.4401 (3.4388/1.5390)	mem 16099MB
[2025-01-18 11:22:07 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][30/312]	eta 0:02:30 lr 0.000075	time 0.4467 (0.5322)	model_time 0.4462 (0.4683)	loss 3.2296 (2.6337)	grad_norm 2.5459 (3.2819/1.5775)	mem 16099MB
[2025-01-18 11:22:12 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][40/312]	eta 0:02:20 lr 0.000075	time 0.4566 (0.5168)	model_time 0.4562 (0.4685)	loss 2.8843 (2.5847)	grad_norm 2.0904 (2.9566/1.5192)	mem 16099MB
[2025-01-18 11:22:17 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][50/312]	eta 0:02:14 lr 0.000074	time 0.5558 (0.5126)	model_time 0.5556 (0.4737)	loss 2.8324 (2.5654)	grad_norm 2.3554 (2.8978/1.4353)	mem 16099MB
[2025-01-18 11:22:22 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][60/312]	eta 0:02:07 lr 0.000074	time 0.4511 (0.5079)	model_time 0.4506 (0.4753)	loss 3.1573 (2.5881)	grad_norm 4.3886 (2.9091/1.3400)	mem 16099MB
[2025-01-18 11:22:26 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][70/312]	eta 0:02:01 lr 0.000074	time 0.4404 (0.5007)	model_time 0.4402 (0.4726)	loss 2.5201 (2.5874)	grad_norm 2.4282 (2.8929/1.2906)	mem 16099MB
[2025-01-18 11:22:31 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][80/312]	eta 0:01:56 lr 0.000074	time 0.7555 (0.5004)	model_time 0.7553 (0.4757)	loss 2.9114 (2.5906)	grad_norm 1.5729 (2.8524/1.2680)	mem 16099MB
[2025-01-18 11:22:36 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][90/312]	eta 0:01:49 lr 0.000074	time 0.4516 (0.4952)	model_time 0.4512 (0.4732)	loss 3.0334 (2.6097)	grad_norm 1.3220 (2.8874/1.2843)	mem 16099MB
[2025-01-18 11:22:40 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][100/312]	eta 0:01:44 lr 0.000074	time 0.4412 (0.4923)	model_time 0.4407 (0.4725)	loss 1.7677 (2.5991)	grad_norm 1.5290 (2.9099/1.2960)	mem 16099MB
[2025-01-18 11:22:45 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][110/312]	eta 0:01:38 lr 0.000074	time 0.4512 (0.4894)	model_time 0.4510 (0.4713)	loss 2.9436 (2.6033)	grad_norm 3.4638 (2.9928/1.3261)	mem 16099MB
[2025-01-18 11:22:50 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][120/312]	eta 0:01:33 lr 0.000074	time 0.4534 (0.4876)	model_time 0.4532 (0.4710)	loss 3.1396 (2.5955)	grad_norm 3.4418 (3.0288/1.3057)	mem 16099MB
[2025-01-18 11:22:54 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][130/312]	eta 0:01:28 lr 0.000073	time 0.5612 (0.4871)	model_time 0.5611 (0.4717)	loss 2.8977 (2.6028)	grad_norm 2.5561 (3.1518/1.3774)	mem 16099MB
[2025-01-18 11:22:59 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][140/312]	eta 0:01:23 lr 0.000073	time 0.4712 (0.4862)	model_time 0.4707 (0.4718)	loss 3.1132 (2.6048)	grad_norm 4.5528 (3.1180/1.3548)	mem 16099MB
[2025-01-18 11:23:04 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][150/312]	eta 0:01:18 lr 0.000073	time 0.4446 (0.4841)	model_time 0.4444 (0.4707)	loss 2.1923 (2.5945)	grad_norm 4.5529 (3.0921/1.3333)	mem 16099MB
[2025-01-18 11:23:08 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][160/312]	eta 0:01:13 lr 0.000073	time 0.4552 (0.4831)	model_time 0.4550 (0.4705)	loss 2.7989 (2.5914)	grad_norm 2.5970 (3.1193/1.3267)	mem 16099MB
[2025-01-18 11:23:13 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][170/312]	eta 0:01:08 lr 0.000073	time 0.4691 (0.4816)	model_time 0.4687 (0.4697)	loss 2.5802 (2.6036)	grad_norm 1.8405 (3.1401/1.3082)	mem 16099MB
[2025-01-18 11:23:18 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][180/312]	eta 0:01:03 lr 0.000073	time 0.4658 (0.4827)	model_time 0.4653 (0.4715)	loss 2.8989 (2.6008)	grad_norm 3.2357 (3.1378/1.2863)	mem 16099MB
[2025-01-18 11:23:23 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][190/312]	eta 0:00:58 lr 0.000073	time 0.4631 (0.4814)	model_time 0.4627 (0.4707)	loss 1.9949 (2.6139)	grad_norm 2.4831 (3.1149/1.2838)	mem 16099MB
[2025-01-18 11:23:27 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][200/312]	eta 0:00:53 lr 0.000073	time 0.4468 (0.4804)	model_time 0.4463 (0.4702)	loss 2.3940 (2.6169)	grad_norm 1.5155 (3.0957/1.2735)	mem 16099MB
[2025-01-18 11:23:32 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][210/312]	eta 0:00:48 lr 0.000073	time 0.4549 (0.4796)	model_time 0.4547 (0.4699)	loss 2.9396 (2.6250)	grad_norm 1.8541 (3.0633/1.2584)	mem 16099MB
[2025-01-18 11:23:36 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][220/312]	eta 0:00:44 lr 0.000072	time 0.4525 (0.4787)	model_time 0.4520 (0.4694)	loss 2.5816 (2.6267)	grad_norm 1.6003 (3.0451/1.2762)	mem 16099MB
[2025-01-18 11:23:41 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][230/312]	eta 0:00:39 lr 0.000072	time 0.4548 (0.4776)	model_time 0.4544 (0.4687)	loss 2.9886 (2.6240)	grad_norm 4.1329 (3.0366/1.2726)	mem 16099MB
[2025-01-18 11:23:46 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][240/312]	eta 0:00:34 lr 0.000072	time 0.4460 (0.4776)	model_time 0.4455 (0.4691)	loss 1.7853 (2.6210)	grad_norm 2.3945 (3.0095/1.2642)	mem 16099MB
[2025-01-18 11:23:50 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][250/312]	eta 0:00:29 lr 0.000072	time 0.4499 (0.4774)	model_time 0.4494 (0.4692)	loss 2.4915 (2.6147)	grad_norm 2.5393 (3.0044/1.2520)	mem 16099MB
[2025-01-18 11:23:55 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][260/312]	eta 0:00:24 lr 0.000072	time 0.4644 (0.4772)	model_time 0.4640 (0.4693)	loss 3.4918 (2.6207)	grad_norm 1.9153 (2.9836/1.2520)	mem 16099MB
[2025-01-18 11:24:00 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][270/312]	eta 0:00:20 lr 0.000072	time 0.4954 (0.4773)	model_time 0.4950 (0.4696)	loss 2.1755 (2.6183)	grad_norm 2.0367 (3.0055/1.2875)	mem 16099MB
[2025-01-18 11:24:05 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][280/312]	eta 0:00:15 lr 0.000072	time 0.4706 (0.4765)	model_time 0.4701 (0.4691)	loss 2.3820 (2.6210)	grad_norm 3.5118 (3.0058/1.2925)	mem 16099MB
[2025-01-18 11:24:09 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][290/312]	eta 0:00:10 lr 0.000072	time 0.4604 (0.4772)	model_time 0.4603 (0.4700)	loss 3.0649 (2.6279)	grad_norm 2.4620 (3.0292/1.3082)	mem 16099MB
[2025-01-18 11:24:14 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][300/312]	eta 0:00:05 lr 0.000071	time 0.4390 (0.4770)	model_time 0.4389 (0.4701)	loss 2.9348 (2.6340)	grad_norm 1.6369 (3.0459/1.3858)	mem 16099MB
[2025-01-18 11:24:19 internimage_t_1k_224] (main.py 510): INFO Train: [282/300][310/312]	eta 0:00:00 lr 0.000071	time 0.4454 (0.4760)	model_time 0.4454 (0.4693)	loss 3.0431 (2.6332)	grad_norm 2.6115 (3.0065/1.3815)	mem 16099MB
[2025-01-18 11:24:19 internimage_t_1k_224] (main.py 519): INFO EPOCH 282 training takes 0:02:28
[2025-01-18 11:24:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_282.pth saving......
[2025-01-18 11:24:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_282.pth saved !!!
[2025-01-18 11:24:28 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.380 (7.380)	Loss 0.7159 (0.7159)	Acc@1 85.205 (85.205)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 11:24:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.009)	Loss 0.9566 (0.8197)	Acc@1 79.126 (83.196)	Acc@5 95.190 (96.347)	Mem 16099MB
[2025-01-18 11:24:32 internimage_t_1k_224] (main.py 575): INFO [Epoch:282] * Acc@1 83.055 Acc@5 96.363
[2025-01-18 11:24:32 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:24:32 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.12%
[2025-01-18 11:24:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.503 (8.503)	Loss 0.7152 (0.7152)	Acc@1 85.889 (85.889)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 11:24:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.146)	Loss 0.9450 (0.8146)	Acc@1 79.858 (83.669)	Acc@5 95.386 (96.584)	Mem 16099MB
[2025-01-18 11:24:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:282] * Acc@1 83.517 Acc@5 96.579
[2025-01-18 11:24:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:24:44 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.52%
[2025-01-18 11:24:48 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][0/312]	eta 0:17:03 lr 0.000071	time 3.2789 (3.2789)	model_time 0.8757 (0.8757)	loss 1.7485 (1.7485)	grad_norm 1.8620 (1.8620/0.0000)	mem 16099MB
[2025-01-18 11:24:52 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][10/312]	eta 0:03:41 lr 0.000071	time 0.4459 (0.7347)	model_time 0.4457 (0.5157)	loss 2.8109 (2.5940)	grad_norm 1.8163 (3.6439/2.1721)	mem 16099MB
[2025-01-18 11:24:57 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][20/312]	eta 0:02:56 lr 0.000071	time 0.4557 (0.6039)	model_time 0.4555 (0.4891)	loss 1.9760 (2.5569)	grad_norm 5.1485 (3.5770/2.0939)	mem 16099MB
[2025-01-18 11:25:02 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][30/312]	eta 0:02:36 lr 0.000071	time 0.4576 (0.5558)	model_time 0.4571 (0.4779)	loss 2.3222 (2.6363)	grad_norm 3.3252 (3.2809/1.8219)	mem 16099MB
[2025-01-18 11:25:06 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][40/312]	eta 0:02:26 lr 0.000071	time 0.4578 (0.5373)	model_time 0.4577 (0.4783)	loss 2.0692 (2.5652)	grad_norm 1.3033 (2.9984/1.6801)	mem 16099MB
[2025-01-18 11:25:11 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][50/312]	eta 0:02:17 lr 0.000071	time 0.4477 (0.5245)	model_time 0.4474 (0.4771)	loss 2.5204 (2.5563)	grad_norm 3.6282 (3.0567/1.6191)	mem 16099MB
[2025-01-18 11:25:16 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][60/312]	eta 0:02:09 lr 0.000071	time 0.4576 (0.5132)	model_time 0.4572 (0.4735)	loss 1.7558 (2.5917)	grad_norm 3.0078 (3.0590/1.5724)	mem 16099MB
[2025-01-18 11:25:20 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][70/312]	eta 0:02:02 lr 0.000070	time 0.4974 (0.5082)	model_time 0.4970 (0.4740)	loss 2.5995 (2.6312)	grad_norm 4.1231 (3.0860/1.5051)	mem 16099MB
[2025-01-18 11:25:25 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][80/312]	eta 0:01:56 lr 0.000070	time 0.4576 (0.5016)	model_time 0.4572 (0.4715)	loss 2.8801 (2.6447)	grad_norm 6.4754 (3.1125/1.6138)	mem 16099MB
[2025-01-18 11:25:30 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][90/312]	eta 0:01:50 lr 0.000070	time 0.4692 (0.4978)	model_time 0.4687 (0.4710)	loss 2.8668 (2.6727)	grad_norm 2.2718 (3.1061/1.5660)	mem 16099MB
[2025-01-18 11:25:34 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][100/312]	eta 0:01:44 lr 0.000070	time 0.4707 (0.4936)	model_time 0.4702 (0.4695)	loss 2.2154 (2.6657)	grad_norm 2.4050 (3.0492/1.5151)	mem 16099MB
[2025-01-18 11:25:39 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][110/312]	eta 0:01:39 lr 0.000070	time 0.4455 (0.4914)	model_time 0.4450 (0.4693)	loss 2.8630 (2.6757)	grad_norm 1.5765 (2.9533/1.4847)	mem 16099MB
[2025-01-18 11:25:44 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][120/312]	eta 0:01:34 lr 0.000070	time 0.4569 (0.4904)	model_time 0.4564 (0.4701)	loss 3.0559 (2.6648)	grad_norm 2.7853 (2.9084/1.4439)	mem 16099MB
[2025-01-18 11:25:48 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][130/312]	eta 0:01:29 lr 0.000070	time 0.4654 (0.4892)	model_time 0.4649 (0.4705)	loss 1.5087 (2.6615)	grad_norm 1.1618 (2.8702/1.4166)	mem 16099MB
[2025-01-18 11:25:53 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][140/312]	eta 0:01:24 lr 0.000070	time 0.4548 (0.4884)	model_time 0.4546 (0.4710)	loss 3.0297 (2.6843)	grad_norm 3.8425 (2.9026/1.4041)	mem 16099MB
[2025-01-18 11:25:58 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][150/312]	eta 0:01:19 lr 0.000070	time 0.4440 (0.4878)	model_time 0.4439 (0.4715)	loss 2.5892 (2.6786)	grad_norm 2.0540 (2.9189/1.3815)	mem 16099MB
[2025-01-18 11:26:03 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][160/312]	eta 0:01:14 lr 0.000069	time 0.4552 (0.4872)	model_time 0.4547 (0.4719)	loss 2.9618 (2.6914)	grad_norm 1.6424 (2.8676/1.3586)	mem 16099MB
[2025-01-18 11:26:08 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][170/312]	eta 0:01:09 lr 0.000069	time 0.4434 (0.4876)	model_time 0.4432 (0.4732)	loss 2.8842 (2.6901)	grad_norm 1.4061 (2.8804/1.3509)	mem 16099MB
[2025-01-18 11:26:12 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][180/312]	eta 0:01:04 lr 0.000069	time 0.4700 (0.4863)	model_time 0.4695 (0.4727)	loss 3.3593 (2.7001)	grad_norm 5.5567 (2.8779/1.3345)	mem 16099MB
[2025-01-18 11:26:17 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][190/312]	eta 0:00:59 lr 0.000069	time 0.4492 (0.4851)	model_time 0.4490 (0.4721)	loss 2.5054 (2.7003)	grad_norm 7.0528 (2.9080/1.3472)	mem 16099MB
[2025-01-18 11:26:22 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][200/312]	eta 0:00:54 lr 0.000069	time 0.4448 (0.4841)	model_time 0.4446 (0.4718)	loss 1.9329 (2.6916)	grad_norm 3.3065 (2.9076/1.3244)	mem 16099MB
[2025-01-18 11:26:26 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][210/312]	eta 0:00:49 lr 0.000069	time 0.4715 (0.4830)	model_time 0.4708 (0.4712)	loss 2.1534 (2.6975)	grad_norm 2.1976 (2.9134/1.3130)	mem 16099MB
[2025-01-18 11:26:31 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][220/312]	eta 0:00:44 lr 0.000069	time 0.4599 (0.4824)	model_time 0.4595 (0.4710)	loss 2.2498 (2.6964)	grad_norm 2.5718 (2.9013/1.3003)	mem 16099MB
[2025-01-18 11:26:36 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][230/312]	eta 0:00:39 lr 0.000069	time 0.4665 (0.4821)	model_time 0.4661 (0.4713)	loss 2.4644 (2.6964)	grad_norm 4.4199 (2.8756/1.2937)	mem 16099MB
[2025-01-18 11:26:40 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][240/312]	eta 0:00:34 lr 0.000069	time 0.4769 (0.4815)	model_time 0.4768 (0.4711)	loss 2.8092 (2.6923)	grad_norm 3.3277 (2.8696/1.2768)	mem 16099MB
[2025-01-18 11:26:45 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][250/312]	eta 0:00:29 lr 0.000068	time 0.4537 (0.4809)	model_time 0.4535 (0.4709)	loss 1.9118 (2.6969)	grad_norm 4.0993 (2.9295/1.3384)	mem 16099MB
[2025-01-18 11:26:50 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][260/312]	eta 0:00:24 lr 0.000068	time 0.4397 (0.4803)	model_time 0.4395 (0.4707)	loss 3.0173 (2.6977)	grad_norm 1.4239 (2.9484/1.3433)	mem 16099MB
[2025-01-18 11:26:54 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][270/312]	eta 0:00:20 lr 0.000068	time 0.4458 (0.4793)	model_time 0.4456 (0.4700)	loss 2.1921 (2.6912)	grad_norm 2.0107 (2.9356/1.3297)	mem 16099MB
[2025-01-18 11:26:59 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][280/312]	eta 0:00:15 lr 0.000068	time 0.4442 (0.4798)	model_time 0.4438 (0.4708)	loss 2.8444 (2.6972)	grad_norm 4.2049 (2.9888/1.4029)	mem 16099MB
[2025-01-18 11:27:04 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][290/312]	eta 0:00:10 lr 0.000068	time 0.4568 (0.4790)	model_time 0.4563 (0.4703)	loss 2.9739 (2.6933)	grad_norm 3.5907 (2.9840/1.4008)	mem 16099MB
[2025-01-18 11:27:08 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][300/312]	eta 0:00:05 lr 0.000068	time 0.4436 (0.4786)	model_time 0.4435 (0.4701)	loss 1.6931 (2.6983)	grad_norm 1.5367 (2.9693/1.3874)	mem 16099MB
[2025-01-18 11:27:13 internimage_t_1k_224] (main.py 510): INFO Train: [283/300][310/312]	eta 0:00:00 lr 0.000068	time 0.4382 (0.4775)	model_time 0.4381 (0.4693)	loss 2.9856 (2.6976)	grad_norm 1.7895 (2.9296/1.3355)	mem 16099MB
[2025-01-18 11:27:13 internimage_t_1k_224] (main.py 519): INFO EPOCH 283 training takes 0:02:28
[2025-01-18 11:27:13 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_283.pth saving......
[2025-01-18 11:27:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_283.pth saved !!!
[2025-01-18 11:27:22 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.618 (7.618)	Loss 0.7206 (0.7206)	Acc@1 85.327 (85.327)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 11:27:26 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.020)	Loss 0.9625 (0.8188)	Acc@1 78.467 (83.250)	Acc@5 94.946 (96.349)	Mem 16099MB
[2025-01-18 11:27:26 internimage_t_1k_224] (main.py 575): INFO [Epoch:283] * Acc@1 83.081 Acc@5 96.355
[2025-01-18 11:27:26 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:27:26 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.12%
[2025-01-18 11:27:34 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.185 (8.185)	Loss 0.7149 (0.7149)	Acc@1 85.840 (85.840)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 11:27:38 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.105 (1.102)	Loss 0.9447 (0.8142)	Acc@1 79.883 (83.667)	Acc@5 95.386 (96.582)	Mem 16099MB
[2025-01-18 11:27:38 internimage_t_1k_224] (main.py 575): INFO [Epoch:283] * Acc@1 83.511 Acc@5 96.583
[2025-01-18 11:27:38 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:27:38 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.52%
[2025-01-18 11:27:41 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][0/312]	eta 0:15:27 lr 0.000068	time 2.9712 (2.9712)	model_time 0.5287 (0.5287)	loss 2.3997 (2.3997)	grad_norm 2.5338 (2.5338/0.0000)	mem 16099MB
[2025-01-18 11:27:46 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][10/312]	eta 0:03:31 lr 0.000068	time 0.4547 (0.6990)	model_time 0.4543 (0.4766)	loss 2.8660 (2.7407)	grad_norm 1.5540 (2.3584/0.6590)	mem 16099MB
[2025-01-18 11:27:50 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][20/312]	eta 0:02:52 lr 0.000068	time 0.4471 (0.5899)	model_time 0.4467 (0.4732)	loss 2.5692 (2.7474)	grad_norm 1.9553 (2.7483/1.7633)	mem 16099MB
[2025-01-18 11:27:55 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][30/312]	eta 0:02:36 lr 0.000067	time 0.4929 (0.5564)	model_time 0.4928 (0.4772)	loss 2.7360 (2.7237)	grad_norm 3.7645 (2.9554/1.5593)	mem 16099MB
[2025-01-18 11:28:00 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][40/312]	eta 0:02:25 lr 0.000067	time 0.4505 (0.5349)	model_time 0.4501 (0.4750)	loss 2.8570 (2.6980)	grad_norm 3.2903 (3.2288/1.7742)	mem 16099MB
[2025-01-18 11:28:05 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][50/312]	eta 0:02:16 lr 0.000067	time 0.4531 (0.5212)	model_time 0.4529 (0.4730)	loss 2.7270 (2.7101)	grad_norm 5.9284 (3.3898/1.8417)	mem 16099MB
[2025-01-18 11:28:09 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][60/312]	eta 0:02:09 lr 0.000067	time 0.4609 (0.5122)	model_time 0.4608 (0.4718)	loss 2.4665 (2.6933)	grad_norm 1.9215 (3.3828/1.7794)	mem 16099MB
[2025-01-18 11:28:14 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][70/312]	eta 0:02:02 lr 0.000067	time 0.5527 (0.5062)	model_time 0.5525 (0.4715)	loss 1.9198 (2.6953)	grad_norm 1.9100 (3.4460/1.7731)	mem 16099MB
[2025-01-18 11:28:19 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][80/312]	eta 0:01:56 lr 0.000067	time 0.4593 (0.5009)	model_time 0.4592 (0.4704)	loss 2.8505 (2.6896)	grad_norm 2.2017 (3.3461/1.7073)	mem 16099MB
[2025-01-18 11:28:23 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][90/312]	eta 0:01:50 lr 0.000067	time 0.4585 (0.4969)	model_time 0.4583 (0.4697)	loss 3.1262 (2.7088)	grad_norm 2.4327 (3.2518/1.6559)	mem 16099MB
[2025-01-18 11:28:28 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][100/312]	eta 0:01:44 lr 0.000067	time 0.4810 (0.4929)	model_time 0.4808 (0.4683)	loss 3.0830 (2.6852)	grad_norm 1.4742 (3.2089/1.6336)	mem 16099MB
[2025-01-18 11:28:33 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][110/312]	eta 0:01:39 lr 0.000067	time 0.5424 (0.4939)	model_time 0.5422 (0.4715)	loss 3.3857 (2.6837)	grad_norm 2.4379 (3.2113/1.5826)	mem 16099MB
[2025-01-18 11:28:38 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][120/312]	eta 0:01:34 lr 0.000066	time 0.5286 (0.4922)	model_time 0.5284 (0.4717)	loss 3.2247 (2.6931)	grad_norm 1.3884 (3.2218/1.5519)	mem 16099MB
[2025-01-18 11:28:42 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][130/312]	eta 0:01:29 lr 0.000066	time 0.5003 (0.4907)	model_time 0.4998 (0.4717)	loss 3.1034 (2.6742)	grad_norm 1.9677 (3.1635/1.5182)	mem 16099MB
[2025-01-18 11:28:47 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][140/312]	eta 0:01:24 lr 0.000066	time 0.5338 (0.4908)	model_time 0.5333 (0.4731)	loss 1.8060 (2.6693)	grad_norm 2.2704 (3.1573/1.4897)	mem 16099MB
[2025-01-18 11:28:52 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][150/312]	eta 0:01:19 lr 0.000066	time 0.4747 (0.4891)	model_time 0.4742 (0.4725)	loss 2.6878 (2.6737)	grad_norm 1.5398 (3.1043/1.4624)	mem 16099MB
[2025-01-18 11:28:57 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][160/312]	eta 0:01:14 lr 0.000066	time 0.4424 (0.4878)	model_time 0.4419 (0.4723)	loss 2.7712 (2.6736)	grad_norm 1.6763 (3.1075/1.4403)	mem 16099MB
[2025-01-18 11:29:01 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][170/312]	eta 0:01:09 lr 0.000066	time 0.4440 (0.4859)	model_time 0.4438 (0.4713)	loss 2.7765 (2.6553)	grad_norm 1.3821 (3.0854/1.4295)	mem 16099MB
[2025-01-18 11:29:06 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][180/312]	eta 0:01:03 lr 0.000066	time 0.4477 (0.4841)	model_time 0.4475 (0.4702)	loss 2.3056 (2.6529)	grad_norm 5.1380 (3.1081/1.4741)	mem 16099MB
[2025-01-18 11:29:10 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][190/312]	eta 0:00:58 lr 0.000066	time 0.4409 (0.4829)	model_time 0.4404 (0.4698)	loss 2.6085 (2.6562)	grad_norm 3.4769 (3.1203/1.4584)	mem 16099MB
[2025-01-18 11:29:15 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][200/312]	eta 0:00:53 lr 0.000066	time 0.4639 (0.4818)	model_time 0.4634 (0.4693)	loss 1.6994 (2.6524)	grad_norm 2.1925 (3.0854/1.4456)	mem 16099MB
[2025-01-18 11:29:19 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][210/312]	eta 0:00:49 lr 0.000065	time 0.4496 (0.4804)	model_time 0.4494 (0.4685)	loss 1.7337 (2.6493)	grad_norm 2.1345 (3.0330/1.4347)	mem 16099MB
[2025-01-18 11:29:24 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][220/312]	eta 0:00:44 lr 0.000065	time 0.4475 (0.4797)	model_time 0.4473 (0.4682)	loss 2.9406 (2.6511)	grad_norm 1.7197 (3.0345/1.4204)	mem 16099MB
[2025-01-18 11:29:29 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][230/312]	eta 0:00:39 lr 0.000065	time 0.4595 (0.4795)	model_time 0.4590 (0.4685)	loss 2.9519 (2.6568)	grad_norm 5.3028 (3.0225/1.4083)	mem 16099MB
[2025-01-18 11:29:34 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][240/312]	eta 0:00:34 lr 0.000065	time 0.4681 (0.4794)	model_time 0.4676 (0.4689)	loss 2.0315 (2.6462)	grad_norm 1.6742 (3.0265/1.3971)	mem 16099MB
[2025-01-18 11:29:38 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][250/312]	eta 0:00:29 lr 0.000065	time 0.4639 (0.4792)	model_time 0.4635 (0.4691)	loss 2.2068 (2.6481)	grad_norm 2.9024 (3.0264/1.3950)	mem 16099MB
[2025-01-18 11:29:43 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][260/312]	eta 0:00:24 lr 0.000065	time 0.4503 (0.4793)	model_time 0.4501 (0.4695)	loss 3.0758 (2.6488)	grad_norm 4.4955 (3.0338/1.3975)	mem 16099MB
[2025-01-18 11:29:48 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][270/312]	eta 0:00:20 lr 0.000065	time 0.4606 (0.4791)	model_time 0.4604 (0.4697)	loss 2.9000 (2.6506)	grad_norm 5.1406 (3.0424/1.4132)	mem 16099MB
[2025-01-18 11:29:53 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][280/312]	eta 0:00:15 lr 0.000065	time 0.4424 (0.4789)	model_time 0.4420 (0.4698)	loss 3.1652 (2.6505)	grad_norm 2.2437 (3.0236/1.4043)	mem 16099MB
[2025-01-18 11:29:57 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][290/312]	eta 0:00:10 lr 0.000065	time 0.4497 (0.4790)	model_time 0.4496 (0.4702)	loss 2.9110 (2.6470)	grad_norm 1.9166 (2.9918/1.3966)	mem 16099MB
[2025-01-18 11:30:02 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][300/312]	eta 0:00:05 lr 0.000065	time 0.4513 (0.4784)	model_time 0.4512 (0.4699)	loss 2.8107 (2.6509)	grad_norm 1.9165 (2.9804/1.3862)	mem 16099MB
[2025-01-18 11:30:07 internimage_t_1k_224] (main.py 510): INFO Train: [284/300][310/312]	eta 0:00:00 lr 0.000064	time 0.4398 (0.4787)	model_time 0.4397 (0.4704)	loss 2.8164 (2.6514)	grad_norm 3.6299 (3.0131/1.3884)	mem 16099MB
[2025-01-18 11:30:07 internimage_t_1k_224] (main.py 519): INFO EPOCH 284 training takes 0:02:29
[2025-01-18 11:30:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_284.pth saving......
[2025-01-18 11:30:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_284.pth saved !!!
[2025-01-18 11:30:17 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.931 (7.931)	Loss 0.7212 (0.7212)	Acc@1 85.132 (85.132)	Acc@5 97.534 (97.534)	Mem 16099MB
[2025-01-18 11:30:20 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.078)	Loss 0.9588 (0.8192)	Acc@1 79.175 (83.148)	Acc@5 94.995 (96.378)	Mem 16099MB
[2025-01-18 11:30:21 internimage_t_1k_224] (main.py 575): INFO [Epoch:284] * Acc@1 82.997 Acc@5 96.393
[2025-01-18 11:30:21 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.0%
[2025-01-18 11:30:21 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.12%
[2025-01-18 11:30:29 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.267 (8.267)	Loss 0.7145 (0.7145)	Acc@1 85.840 (85.840)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 11:30:33 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.106)	Loss 0.9442 (0.8136)	Acc@1 79.883 (83.676)	Acc@5 95.386 (96.573)	Mem 16099MB
[2025-01-18 11:30:33 internimage_t_1k_224] (main.py 575): INFO [Epoch:284] * Acc@1 83.517 Acc@5 96.575
[2025-01-18 11:30:33 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:30:33 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.52%
[2025-01-18 11:30:36 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][0/312]	eta 0:15:11 lr 0.000064	time 2.9217 (2.9217)	model_time 0.5176 (0.5176)	loss 2.3702 (2.3702)	grad_norm 3.9244 (3.9244/0.0000)	mem 16099MB
[2025-01-18 11:30:41 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][10/312]	eta 0:03:29 lr 0.000064	time 0.4627 (0.6935)	model_time 0.4621 (0.4745)	loss 2.4926 (2.7338)	grad_norm 1.6123 (2.5287/0.8628)	mem 16099MB
[2025-01-18 11:30:45 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][20/312]	eta 0:02:53 lr 0.000064	time 0.4519 (0.5932)	model_time 0.4515 (0.4783)	loss 2.6048 (2.7049)	grad_norm 1.6474 (2.6339/0.8543)	mem 16099MB
[2025-01-18 11:30:50 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][30/312]	eta 0:02:34 lr 0.000064	time 0.4607 (0.5495)	model_time 0.4602 (0.4716)	loss 2.5994 (2.6419)	grad_norm 2.4165 (2.7110/0.8545)	mem 16099MB
[2025-01-18 11:30:55 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][40/312]	eta 0:02:23 lr 0.000064	time 0.4469 (0.5278)	model_time 0.4467 (0.4688)	loss 2.1652 (2.6343)	grad_norm 3.3086 (2.8919/0.9980)	mem 16099MB
[2025-01-18 11:30:59 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][50/312]	eta 0:02:14 lr 0.000064	time 0.4686 (0.5135)	model_time 0.4684 (0.4660)	loss 2.5422 (2.6406)	grad_norm 6.3513 (2.9393/1.0843)	mem 16099MB
[2025-01-18 11:31:04 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][60/312]	eta 0:02:08 lr 0.000064	time 0.5920 (0.5090)	model_time 0.5915 (0.4692)	loss 2.5452 (2.6438)	grad_norm 2.6631 (2.9077/1.0656)	mem 16099MB
[2025-01-18 11:31:09 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][70/312]	eta 0:02:01 lr 0.000064	time 0.4522 (0.5014)	model_time 0.4517 (0.4672)	loss 2.8318 (2.6369)	grad_norm 2.1295 (2.8770/1.0721)	mem 16099MB
[2025-01-18 11:31:13 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][80/312]	eta 0:01:54 lr 0.000064	time 0.4685 (0.4956)	model_time 0.4684 (0.4655)	loss 3.0852 (2.6570)	grad_norm 1.2204 (2.8670/1.1039)	mem 16099MB
[2025-01-18 11:31:18 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][90/312]	eta 0:01:49 lr 0.000063	time 0.4517 (0.4927)	model_time 0.4515 (0.4659)	loss 1.5978 (2.6417)	grad_norm 1.9153 (2.8103/1.0884)	mem 16099MB
[2025-01-18 11:31:23 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][100/312]	eta 0:01:44 lr 0.000063	time 0.4569 (0.4919)	model_time 0.4568 (0.4677)	loss 1.9469 (2.6086)	grad_norm 2.7200 (2.8162/1.0947)	mem 16099MB
[2025-01-18 11:31:27 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][110/312]	eta 0:01:39 lr 0.000063	time 0.4542 (0.4902)	model_time 0.4541 (0.4681)	loss 2.8510 (2.6106)	grad_norm 3.5256 (2.8173/1.0777)	mem 16099MB
[2025-01-18 11:31:32 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][120/312]	eta 0:01:33 lr 0.000063	time 0.4447 (0.4873)	model_time 0.4446 (0.4671)	loss 2.5596 (2.6162)	grad_norm 4.3042 (2.8028/1.0629)	mem 16099MB
[2025-01-18 11:31:37 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][130/312]	eta 0:01:28 lr 0.000063	time 0.4403 (0.4856)	model_time 0.4401 (0.4669)	loss 2.2697 (2.6091)	grad_norm 2.8641 (2.8265/1.0525)	mem 16099MB
[2025-01-18 11:31:41 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][140/312]	eta 0:01:23 lr 0.000063	time 0.4617 (0.4841)	model_time 0.4612 (0.4666)	loss 2.6483 (2.6241)	grad_norm 2.4011 (2.8459/1.1580)	mem 16099MB
[2025-01-18 11:31:46 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][150/312]	eta 0:01:18 lr 0.000063	time 0.4489 (0.4832)	model_time 0.4485 (0.4668)	loss 1.5433 (2.6072)	grad_norm 3.3951 (2.8570/1.1853)	mem 16099MB
[2025-01-18 11:31:51 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][160/312]	eta 0:01:13 lr 0.000063	time 0.4742 (0.4821)	model_time 0.4738 (0.4668)	loss 1.5690 (2.6137)	grad_norm 3.5369 (2.8656/1.1597)	mem 16099MB
[2025-01-18 11:31:55 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][170/312]	eta 0:01:08 lr 0.000063	time 0.4574 (0.4805)	model_time 0.4569 (0.4661)	loss 2.6707 (2.6061)	grad_norm 3.0206 (2.8707/1.2029)	mem 16099MB
[2025-01-18 11:32:00 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][180/312]	eta 0:01:03 lr 0.000063	time 0.4658 (0.4792)	model_time 0.4656 (0.4655)	loss 1.8877 (2.5954)	grad_norm 2.0678 (2.8782/1.1879)	mem 16099MB
[2025-01-18 11:32:04 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][190/312]	eta 0:00:58 lr 0.000062	time 0.4673 (0.4781)	model_time 0.4672 (0.4651)	loss 3.0493 (2.6014)	grad_norm 5.8460 (2.9853/1.2865)	mem 16099MB
[2025-01-18 11:32:09 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][200/312]	eta 0:00:53 lr 0.000062	time 0.4502 (0.4774)	model_time 0.4500 (0.4650)	loss 2.8536 (2.6007)	grad_norm 1.7769 (2.9765/1.2714)	mem 16099MB
[2025-01-18 11:32:13 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][210/312]	eta 0:00:48 lr 0.000062	time 0.4420 (0.4763)	model_time 0.4418 (0.4645)	loss 1.8433 (2.6074)	grad_norm 2.2101 (2.9569/1.2570)	mem 16099MB
[2025-01-18 11:32:18 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][220/312]	eta 0:00:43 lr 0.000062	time 0.4518 (0.4753)	model_time 0.4513 (0.4640)	loss 2.9426 (2.6092)	grad_norm 2.7950 (2.9821/1.2712)	mem 16099MB
[2025-01-18 11:32:22 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][230/312]	eta 0:00:38 lr 0.000062	time 0.4554 (0.4744)	model_time 0.4553 (0.4636)	loss 2.4201 (2.6082)	grad_norm 3.0823 (2.9847/1.2534)	mem 16099MB
[2025-01-18 11:32:27 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][240/312]	eta 0:00:34 lr 0.000062	time 0.4426 (0.4739)	model_time 0.4425 (0.4635)	loss 2.6544 (2.6090)	grad_norm 1.5403 (3.0084/1.2862)	mem 16099MB
[2025-01-18 11:32:32 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][250/312]	eta 0:00:29 lr 0.000062	time 0.4413 (0.4735)	model_time 0.4408 (0.4635)	loss 2.1603 (2.5963)	grad_norm 4.9546 (3.0107/1.2932)	mem 16099MB
[2025-01-18 11:32:37 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][260/312]	eta 0:00:24 lr 0.000062	time 0.4516 (0.4738)	model_time 0.4512 (0.4642)	loss 2.3780 (2.5961)	grad_norm 2.0011 (3.0034/1.2860)	mem 16099MB
[2025-01-18 11:32:41 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][270/312]	eta 0:00:19 lr 0.000062	time 0.4497 (0.4732)	model_time 0.4492 (0.4639)	loss 2.9213 (2.5982)	grad_norm 4.5435 (2.9931/1.2755)	mem 16099MB
[2025-01-18 11:32:46 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][280/312]	eta 0:00:15 lr 0.000062	time 0.4870 (0.4727)	model_time 0.4865 (0.4637)	loss 2.6176 (2.5982)	grad_norm 3.3265 (2.9688/1.2617)	mem 16099MB
[2025-01-18 11:32:51 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][290/312]	eta 0:00:10 lr 0.000061	time 0.4451 (0.4729)	model_time 0.4446 (0.4643)	loss 3.4230 (2.6008)	grad_norm 5.5905 (2.9979/1.2950)	mem 16099MB
[2025-01-18 11:32:55 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][300/312]	eta 0:00:05 lr 0.000061	time 0.4430 (0.4728)	model_time 0.4429 (0.4644)	loss 2.1780 (2.5984)	grad_norm 2.9669 (3.0530/1.3811)	mem 16099MB
[2025-01-18 11:33:00 internimage_t_1k_224] (main.py 510): INFO Train: [285/300][310/312]	eta 0:00:00 lr 0.000061	time 0.4401 (0.4723)	model_time 0.4400 (0.4642)	loss 2.4710 (2.5961)	grad_norm 5.1229 (3.1265/1.4183)	mem 16099MB
[2025-01-18 11:33:00 internimage_t_1k_224] (main.py 519): INFO EPOCH 285 training takes 0:02:27
[2025-01-18 11:33:00 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_285.pth saving......
[2025-01-18 11:33:01 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_285.pth saved !!!
[2025-01-18 11:33:09 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.435 (7.435)	Loss 0.7154 (0.7154)	Acc@1 85.205 (85.205)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 11:33:13 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.012)	Loss 0.9643 (0.8203)	Acc@1 78.931 (83.250)	Acc@5 95.190 (96.382)	Mem 16099MB
[2025-01-18 11:33:13 internimage_t_1k_224] (main.py 575): INFO [Epoch:285] * Acc@1 83.119 Acc@5 96.397
[2025-01-18 11:33:13 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:33:13 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.12%
[2025-01-18 11:33:21 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.298 (8.298)	Loss 0.7140 (0.7140)	Acc@1 85.840 (85.840)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 11:33:25 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.130)	Loss 0.9438 (0.8130)	Acc@1 79.858 (83.674)	Acc@5 95.386 (96.569)	Mem 16099MB
[2025-01-18 11:33:25 internimage_t_1k_224] (main.py 575): INFO [Epoch:285] * Acc@1 83.519 Acc@5 96.571
[2025-01-18 11:33:25 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:33:25 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.52%
[2025-01-18 11:33:28 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][0/312]	eta 0:15:24 lr 0.000061	time 2.9619 (2.9619)	model_time 0.5637 (0.5637)	loss 2.1333 (2.1333)	grad_norm 2.1283 (2.1283/0.0000)	mem 16099MB
[2025-01-18 11:33:33 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][10/312]	eta 0:03:33 lr 0.000061	time 0.4592 (0.7060)	model_time 0.4590 (0.4875)	loss 2.5964 (2.5276)	grad_norm 4.0852 (2.8896/1.1047)	mem 16099MB
[2025-01-18 11:33:38 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][20/312]	eta 0:02:55 lr 0.000061	time 0.4442 (0.6023)	model_time 0.4440 (0.4878)	loss 2.8103 (2.5119)	grad_norm 1.6889 (2.9435/1.3171)	mem 16099MB
[2025-01-18 11:33:43 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][30/312]	eta 0:02:39 lr 0.000061	time 0.5552 (0.5650)	model_time 0.5547 (0.4873)	loss 2.6782 (2.5464)	grad_norm 3.3874 (2.9761/1.2660)	mem 16099MB
[2025-01-18 11:33:48 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][40/312]	eta 0:02:28 lr 0.000061	time 0.4492 (0.5445)	model_time 0.4490 (0.4857)	loss 2.8532 (2.5846)	grad_norm 3.7128 (2.8786/1.2581)	mem 16099MB
[2025-01-18 11:33:52 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][50/312]	eta 0:02:18 lr 0.000061	time 0.4731 (0.5288)	model_time 0.4729 (0.4814)	loss 2.4055 (2.6345)	grad_norm 1.5408 (2.9554/1.5155)	mem 16099MB
[2025-01-18 11:33:57 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][60/312]	eta 0:02:10 lr 0.000061	time 0.4503 (0.5181)	model_time 0.4498 (0.4784)	loss 2.5798 (2.6505)	grad_norm 2.4310 (2.9407/1.4053)	mem 16099MB
[2025-01-18 11:34:02 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][70/312]	eta 0:02:03 lr 0.000061	time 0.4458 (0.5096)	model_time 0.4456 (0.4754)	loss 2.7342 (2.6716)	grad_norm 3.8781 (2.8903/1.3524)	mem 16099MB
[2025-01-18 11:34:06 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][80/312]	eta 0:01:56 lr 0.000060	time 0.4608 (0.5037)	model_time 0.4607 (0.4738)	loss 2.3867 (2.6680)	grad_norm 2.1209 (2.9122/1.3562)	mem 16099MB
[2025-01-18 11:34:11 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][90/312]	eta 0:01:50 lr 0.000060	time 0.5027 (0.4997)	model_time 0.5025 (0.4730)	loss 2.7680 (2.6490)	grad_norm 5.7523 (2.9557/1.4098)	mem 16099MB
[2025-01-18 11:34:15 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][100/312]	eta 0:01:45 lr 0.000060	time 0.4627 (0.4960)	model_time 0.4623 (0.4719)	loss 2.5347 (2.6449)	grad_norm 2.4141 (2.9258/1.3691)	mem 16099MB
[2025-01-18 11:34:20 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][110/312]	eta 0:01:39 lr 0.000060	time 0.4494 (0.4929)	model_time 0.4489 (0.4709)	loss 3.0510 (2.6634)	grad_norm 2.2472 (2.8487/1.3374)	mem 16099MB
[2025-01-18 11:34:25 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][120/312]	eta 0:01:34 lr 0.000060	time 0.4630 (0.4906)	model_time 0.4629 (0.4704)	loss 2.6357 (2.6401)	grad_norm 2.3982 (2.8897/1.3550)	mem 16099MB
[2025-01-18 11:34:29 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][130/312]	eta 0:01:28 lr 0.000060	time 0.4631 (0.4886)	model_time 0.4629 (0.4700)	loss 1.6345 (2.6329)	grad_norm 3.3842 (2.8496/1.3380)	mem 16099MB
[2025-01-18 11:34:34 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][140/312]	eta 0:01:23 lr 0.000060	time 0.5719 (0.4869)	model_time 0.5718 (0.4695)	loss 1.6420 (2.6277)	grad_norm 3.2163 (2.8505/1.3315)	mem 16099MB
[2025-01-18 11:34:39 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][150/312]	eta 0:01:18 lr 0.000060	time 0.4505 (0.4852)	model_time 0.4500 (0.4689)	loss 3.0752 (2.6352)	grad_norm 3.7927 (2.8470/1.3103)	mem 16099MB
[2025-01-18 11:34:43 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][160/312]	eta 0:01:13 lr 0.000060	time 0.4569 (0.4852)	model_time 0.4567 (0.4699)	loss 3.0197 (2.6385)	grad_norm 2.2803 (2.8815/1.3227)	mem 16099MB
[2025-01-18 11:34:48 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][170/312]	eta 0:01:08 lr 0.000060	time 0.4571 (0.4839)	model_time 0.4569 (0.4696)	loss 2.6508 (2.6262)	grad_norm 2.1559 (2.9277/1.4334)	mem 16099MB
[2025-01-18 11:34:53 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][180/312]	eta 0:01:03 lr 0.000060	time 0.4789 (0.4825)	model_time 0.4788 (0.4689)	loss 2.8584 (2.6375)	grad_norm 2.7486 (2.9289/1.4251)	mem 16099MB
[2025-01-18 11:34:57 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][190/312]	eta 0:00:58 lr 0.000059	time 0.4531 (0.4820)	model_time 0.4527 (0.4691)	loss 2.9851 (2.6387)	grad_norm 3.6026 (2.9279/1.4108)	mem 16099MB
[2025-01-18 11:35:02 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][200/312]	eta 0:00:53 lr 0.000059	time 0.4482 (0.4805)	model_time 0.4480 (0.4683)	loss 3.2471 (2.6524)	grad_norm 1.6519 (2.9491/1.4214)	mem 16099MB
[2025-01-18 11:35:07 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][210/312]	eta 0:00:48 lr 0.000059	time 0.4547 (0.4797)	model_time 0.4543 (0.4680)	loss 2.6447 (2.6530)	grad_norm 1.2606 (2.9194/1.4011)	mem 16099MB
[2025-01-18 11:35:11 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][220/312]	eta 0:00:44 lr 0.000059	time 0.4467 (0.4787)	model_time 0.4463 (0.4675)	loss 2.6693 (2.6547)	grad_norm 2.2484 (2.8963/1.3861)	mem 16099MB
[2025-01-18 11:35:16 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][230/312]	eta 0:00:39 lr 0.000059	time 0.5346 (0.4784)	model_time 0.5342 (0.4676)	loss 2.9422 (2.6554)	grad_norm 1.3465 (2.8791/1.3702)	mem 16099MB
[2025-01-18 11:35:21 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][240/312]	eta 0:00:34 lr 0.000059	time 0.4462 (0.4779)	model_time 0.4461 (0.4676)	loss 3.0255 (2.6605)	grad_norm 2.8370 (2.8847/1.3604)	mem 16099MB
[2025-01-18 11:35:25 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][250/312]	eta 0:00:29 lr 0.000059	time 0.4544 (0.4777)	model_time 0.4543 (0.4678)	loss 2.8216 (2.6585)	grad_norm 2.0918 (2.8994/1.3582)	mem 16099MB
[2025-01-18 11:35:30 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][260/312]	eta 0:00:24 lr 0.000059	time 0.4816 (0.4779)	model_time 0.4811 (0.4684)	loss 2.4964 (2.6575)	grad_norm 4.6577 (2.8943/1.3432)	mem 16099MB
[2025-01-18 11:35:35 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][270/312]	eta 0:00:20 lr 0.000059	time 0.5314 (0.4782)	model_time 0.5309 (0.4690)	loss 2.8858 (2.6632)	grad_norm 2.2269 (2.8912/1.3337)	mem 16099MB
[2025-01-18 11:35:40 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][280/312]	eta 0:00:15 lr 0.000059	time 0.4614 (0.4778)	model_time 0.4613 (0.4689)	loss 2.9219 (2.6708)	grad_norm 3.3376 (2.8781/1.3168)	mem 16099MB
[2025-01-18 11:35:44 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][290/312]	eta 0:00:10 lr 0.000059	time 0.4451 (0.4772)	model_time 0.4449 (0.4686)	loss 2.3087 (2.6654)	grad_norm 4.8719 (2.8710/1.3093)	mem 16099MB
[2025-01-18 11:35:49 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][300/312]	eta 0:00:05 lr 0.000058	time 0.4400 (0.4766)	model_time 0.4398 (0.4683)	loss 1.7208 (2.6581)	grad_norm 1.8495 (2.8782/1.2989)	mem 16099MB
[2025-01-18 11:35:53 internimage_t_1k_224] (main.py 510): INFO Train: [286/300][310/312]	eta 0:00:00 lr 0.000058	time 0.4374 (0.4760)	model_time 0.4373 (0.4680)	loss 2.6779 (2.6583)	grad_norm 5.0601 (2.8978/1.3163)	mem 16099MB
[2025-01-18 11:35:54 internimage_t_1k_224] (main.py 519): INFO EPOCH 286 training takes 0:02:28
[2025-01-18 11:35:54 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_286.pth saving......
[2025-01-18 11:35:55 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_286.pth saved !!!
[2025-01-18 11:36:02 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.440 (7.440)	Loss 0.7210 (0.7210)	Acc@1 85.205 (85.205)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 11:36:06 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.005)	Loss 0.9647 (0.8222)	Acc@1 79.175 (83.281)	Acc@5 95.288 (96.382)	Mem 16099MB
[2025-01-18 11:36:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:286] * Acc@1 83.133 Acc@5 96.389
[2025-01-18 11:36:06 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:36:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 11:36:07 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 11:36:07 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 11:36:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.575 (7.575)	Loss 0.7138 (0.7138)	Acc@1 85.840 (85.840)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 11:36:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.019)	Loss 0.9437 (0.8128)	Acc@1 79.883 (83.689)	Acc@5 95.386 (96.573)	Mem 16099MB
[2025-01-18 11:36:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:286] * Acc@1 83.537 Acc@5 96.575
[2025-01-18 11:36:19 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:36:19 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 11:36:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 11:36:20 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.54%
[2025-01-18 11:36:23 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][0/312]	eta 0:14:53 lr 0.000058	time 2.8637 (2.8637)	model_time 0.4650 (0.4650)	loss 2.5958 (2.5958)	grad_norm 2.7876 (2.7876/0.0000)	mem 16099MB
[2025-01-18 11:36:28 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][10/312]	eta 0:03:23 lr 0.000058	time 0.4531 (0.6744)	model_time 0.4529 (0.4560)	loss 2.7118 (2.6793)	grad_norm 6.4381 (3.8520/1.7376)	mem 16099MB
[2025-01-18 11:36:32 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][20/312]	eta 0:02:47 lr 0.000058	time 0.4538 (0.5727)	model_time 0.4536 (0.4580)	loss 3.0359 (2.6708)	grad_norm 2.4592 (3.6902/1.5332)	mem 16099MB
[2025-01-18 11:36:37 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][30/312]	eta 0:02:30 lr 0.000058	time 0.4532 (0.5351)	model_time 0.4528 (0.4573)	loss 2.7656 (2.6354)	grad_norm 3.1273 (3.6265/1.4701)	mem 16099MB
[2025-01-18 11:36:41 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][40/312]	eta 0:02:21 lr 0.000058	time 0.4657 (0.5184)	model_time 0.4652 (0.4595)	loss 3.0450 (2.6489)	grad_norm 5.4854 (3.4897/1.4124)	mem 16099MB
[2025-01-18 11:36:46 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][50/312]	eta 0:02:13 lr 0.000058	time 0.4560 (0.5081)	model_time 0.4555 (0.4607)	loss 3.0454 (2.7044)	grad_norm 2.7018 (3.3753/1.3702)	mem 16099MB
[2025-01-18 11:36:51 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][60/312]	eta 0:02:06 lr 0.000058	time 0.4416 (0.5017)	model_time 0.4411 (0.4620)	loss 2.8037 (2.7135)	grad_norm 2.3491 (3.2873/1.3403)	mem 16099MB
[2025-01-18 11:36:55 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][70/312]	eta 0:02:00 lr 0.000058	time 0.4566 (0.4965)	model_time 0.4565 (0.4623)	loss 2.6588 (2.7221)	grad_norm 2.8003 (3.1212/1.3210)	mem 16099MB
[2025-01-18 11:37:00 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][80/312]	eta 0:01:53 lr 0.000058	time 0.4636 (0.4912)	model_time 0.4634 (0.4610)	loss 1.7929 (2.7334)	grad_norm 2.0978 (3.0330/1.3049)	mem 16099MB
[2025-01-18 11:37:05 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][90/312]	eta 0:01:48 lr 0.000058	time 0.4523 (0.4878)	model_time 0.4519 (0.4609)	loss 2.3900 (2.6912)	grad_norm 3.0565 (2.9704/1.2963)	mem 16099MB
[2025-01-18 11:37:09 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][100/312]	eta 0:01:43 lr 0.000057	time 0.4505 (0.4864)	model_time 0.4500 (0.4621)	loss 2.7715 (2.6906)	grad_norm 2.9300 (2.9898/1.2765)	mem 16099MB
[2025-01-18 11:37:14 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][110/312]	eta 0:01:37 lr 0.000057	time 0.4663 (0.4841)	model_time 0.4658 (0.4620)	loss 2.3461 (2.7039)	grad_norm 2.5481 (2.9874/1.2592)	mem 16099MB
[2025-01-18 11:37:19 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][120/312]	eta 0:01:32 lr 0.000057	time 0.4450 (0.4826)	model_time 0.4449 (0.4623)	loss 3.2572 (2.7054)	grad_norm 5.3194 (2.9687/1.2556)	mem 16099MB
[2025-01-18 11:37:23 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][130/312]	eta 0:01:27 lr 0.000057	time 0.4452 (0.4806)	model_time 0.4447 (0.4618)	loss 3.4054 (2.7069)	grad_norm 2.4896 (2.9883/1.2726)	mem 16099MB
[2025-01-18 11:37:28 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][140/312]	eta 0:01:22 lr 0.000057	time 0.4937 (0.4803)	model_time 0.4933 (0.4628)	loss 3.2210 (2.6981)	grad_norm 5.5815 (3.0815/1.4233)	mem 16099MB
[2025-01-18 11:37:33 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][150/312]	eta 0:01:17 lr 0.000057	time 0.5452 (0.4805)	model_time 0.5448 (0.4641)	loss 2.8813 (2.6840)	grad_norm 2.8756 (3.0997/1.4650)	mem 16099MB
[2025-01-18 11:37:37 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][160/312]	eta 0:01:12 lr 0.000057	time 0.4403 (0.4789)	model_time 0.4398 (0.4636)	loss 2.9554 (2.6928)	grad_norm 2.2842 (3.0830/1.4513)	mem 16099MB
[2025-01-18 11:37:42 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][170/312]	eta 0:01:07 lr 0.000057	time 0.4506 (0.4780)	model_time 0.4501 (0.4636)	loss 2.8340 (2.6740)	grad_norm 3.4866 (3.0664/1.4466)	mem 16099MB
[2025-01-18 11:37:46 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][180/312]	eta 0:01:02 lr 0.000057	time 0.4425 (0.4769)	model_time 0.4420 (0.4632)	loss 3.1016 (2.6812)	grad_norm 3.6379 (3.0895/1.4295)	mem 16099MB
[2025-01-18 11:37:51 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][190/312]	eta 0:00:58 lr 0.000057	time 0.4494 (0.4764)	model_time 0.4490 (0.4634)	loss 1.7781 (2.6589)	grad_norm 2.0679 (3.1103/1.4425)	mem 16099MB
[2025-01-18 11:37:56 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][200/312]	eta 0:00:53 lr 0.000057	time 0.4593 (0.4771)	model_time 0.4591 (0.4647)	loss 2.7138 (2.6659)	grad_norm 2.5081 (3.0847/1.4307)	mem 16099MB
[2025-01-18 11:38:01 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][210/312]	eta 0:00:48 lr 0.000056	time 0.4946 (0.4779)	model_time 0.4944 (0.4660)	loss 2.3266 (2.6616)	grad_norm 2.6020 (3.0555/1.4087)	mem 16099MB
[2025-01-18 11:38:06 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][220/312]	eta 0:00:43 lr 0.000056	time 0.4549 (0.4774)	model_time 0.4547 (0.4661)	loss 2.8455 (2.6651)	grad_norm 2.5908 (3.0099/1.3949)	mem 16099MB
[2025-01-18 11:38:10 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][230/312]	eta 0:00:39 lr 0.000056	time 0.4430 (0.4769)	model_time 0.4425 (0.4660)	loss 1.6077 (2.6642)	grad_norm 1.6505 (3.0013/1.3777)	mem 16099MB
[2025-01-18 11:38:15 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][240/312]	eta 0:00:34 lr 0.000056	time 0.4503 (0.4759)	model_time 0.4498 (0.4655)	loss 2.8653 (2.6684)	grad_norm 2.7877 (3.0139/1.3912)	mem 16099MB
[2025-01-18 11:38:19 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][250/312]	eta 0:00:29 lr 0.000056	time 0.4630 (0.4750)	model_time 0.4625 (0.4650)	loss 3.1334 (2.6704)	grad_norm 3.6617 (3.0142/1.3831)	mem 16099MB
[2025-01-18 11:38:24 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][260/312]	eta 0:00:24 lr 0.000056	time 0.4648 (0.4743)	model_time 0.4643 (0.4646)	loss 2.9375 (2.6721)	grad_norm 2.7412 (3.0136/1.3664)	mem 16099MB
[2025-01-18 11:38:29 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][270/312]	eta 0:00:19 lr 0.000056	time 0.4622 (0.4745)	model_time 0.4620 (0.4653)	loss 2.9556 (2.6793)	grad_norm 1.6332 (2.9951/1.3740)	mem 16099MB
[2025-01-18 11:38:33 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][280/312]	eta 0:00:15 lr 0.000056	time 0.4546 (0.4739)	model_time 0.4540 (0.4649)	loss 2.8392 (2.6791)	grad_norm 3.5532 (3.0149/1.3776)	mem 16099MB
[2025-01-18 11:38:38 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][290/312]	eta 0:00:10 lr 0.000056	time 0.4646 (0.4742)	model_time 0.4642 (0.4655)	loss 2.0900 (2.6778)	grad_norm 2.7795 (3.0254/1.3663)	mem 16099MB
[2025-01-18 11:38:43 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][300/312]	eta 0:00:05 lr 0.000056	time 0.5234 (0.4740)	model_time 0.5233 (0.4656)	loss 3.1746 (2.6780)	grad_norm 4.2546 (3.0385/1.3721)	mem 16099MB
[2025-01-18 11:38:47 internimage_t_1k_224] (main.py 510): INFO Train: [287/300][310/312]	eta 0:00:00 lr 0.000056	time 0.4400 (0.4730)	model_time 0.4399 (0.4649)	loss 2.9173 (2.6740)	grad_norm 1.8585 (2.9807/1.3336)	mem 16099MB
[2025-01-18 11:38:48 internimage_t_1k_224] (main.py 519): INFO EPOCH 287 training takes 0:02:27
[2025-01-18 11:38:48 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_287.pth saving......
[2025-01-18 11:38:49 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_287.pth saved !!!
[2025-01-18 11:38:56 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.235 (7.235)	Loss 0.7243 (0.7243)	Acc@1 85.205 (85.205)	Acc@5 97.314 (97.314)	Mem 16099MB
[2025-01-18 11:39:00 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.010)	Loss 0.9555 (0.8177)	Acc@1 79.102 (83.274)	Acc@5 95.215 (96.300)	Mem 16099MB
[2025-01-18 11:39:00 internimage_t_1k_224] (main.py 575): INFO [Epoch:287] * Acc@1 83.105 Acc@5 96.311
[2025-01-18 11:39:00 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:39:00 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 11:39:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.267 (8.267)	Loss 0.7135 (0.7135)	Acc@1 85.913 (85.913)	Acc@5 97.705 (97.705)	Mem 16099MB
[2025-01-18 11:39:12 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.107)	Loss 0.9433 (0.8123)	Acc@1 79.907 (83.691)	Acc@5 95.386 (96.564)	Mem 16099MB
[2025-01-18 11:39:12 internimage_t_1k_224] (main.py 575): INFO [Epoch:287] * Acc@1 83.539 Acc@5 96.567
[2025-01-18 11:39:12 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:39:12 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 11:39:14 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 11:39:14 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.54%
[2025-01-18 11:39:17 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][0/312]	eta 0:14:46 lr 0.000056	time 2.8407 (2.8407)	model_time 0.5144 (0.5144)	loss 1.5856 (1.5856)	grad_norm 2.6566 (2.6566/0.0000)	mem 16099MB
[2025-01-18 11:39:21 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][10/312]	eta 0:03:22 lr 0.000056	time 0.4539 (0.6692)	model_time 0.4537 (0.4574)	loss 2.6708 (2.3931)	grad_norm 1.6193 (3.6761/1.1772)	mem 16099MB
[2025-01-18 11:39:26 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][20/312]	eta 0:02:47 lr 0.000055	time 0.4539 (0.5739)	model_time 0.4537 (0.4628)	loss 2.8688 (2.5030)	grad_norm 1.9189 (3.6758/1.2770)	mem 16099MB
[2025-01-18 11:39:31 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][30/312]	eta 0:02:32 lr 0.000055	time 0.4444 (0.5418)	model_time 0.4440 (0.4664)	loss 2.5009 (2.5147)	grad_norm 2.8151 (3.1898/1.2819)	mem 16099MB
[2025-01-18 11:39:35 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][40/312]	eta 0:02:22 lr 0.000055	time 0.5454 (0.5256)	model_time 0.5453 (0.4685)	loss 3.4076 (2.5880)	grad_norm 1.4015 (3.1652/1.4020)	mem 16099MB
[2025-01-18 11:39:40 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][50/312]	eta 0:02:14 lr 0.000055	time 0.4473 (0.5136)	model_time 0.4472 (0.4677)	loss 3.1947 (2.6046)	grad_norm 3.1636 (3.1525/1.3183)	mem 16099MB
[2025-01-18 11:39:45 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][60/312]	eta 0:02:07 lr 0.000055	time 0.4514 (0.5059)	model_time 0.4513 (0.4674)	loss 2.6723 (2.6217)	grad_norm 1.6897 (3.1215/1.3093)	mem 16099MB
[2025-01-18 11:39:49 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][70/312]	eta 0:02:00 lr 0.000055	time 0.4539 (0.4985)	model_time 0.4538 (0.4654)	loss 2.6130 (2.6219)	grad_norm 3.8045 (3.0940/1.2904)	mem 16099MB
[2025-01-18 11:39:54 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][80/312]	eta 0:01:54 lr 0.000055	time 0.4558 (0.4932)	model_time 0.4554 (0.4642)	loss 3.3087 (2.5914)	grad_norm 2.8158 (3.1005/1.2412)	mem 16099MB
[2025-01-18 11:39:58 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][90/312]	eta 0:01:48 lr 0.000055	time 0.4877 (0.4908)	model_time 0.4876 (0.4649)	loss 2.9999 (2.6137)	grad_norm 1.1221 (3.0663/1.2267)	mem 16099MB
[2025-01-18 11:40:03 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][100/312]	eta 0:01:43 lr 0.000055	time 0.4408 (0.4874)	model_time 0.4406 (0.4640)	loss 2.3630 (2.6202)	grad_norm 6.3681 (3.0809/1.2329)	mem 16099MB
[2025-01-18 11:40:08 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][110/312]	eta 0:01:38 lr 0.000055	time 0.4620 (0.4871)	model_time 0.4618 (0.4658)	loss 2.7105 (2.6403)	grad_norm 4.2955 (3.1144/1.2206)	mem 16099MB
[2025-01-18 11:40:13 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][120/312]	eta 0:01:33 lr 0.000055	time 0.4638 (0.4852)	model_time 0.4634 (0.4656)	loss 2.9447 (2.6561)	grad_norm 1.9829 (3.1284/1.3208)	mem 16099MB
[2025-01-18 11:40:18 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][130/312]	eta 0:01:28 lr 0.000055	time 0.4472 (0.4870)	model_time 0.4468 (0.4689)	loss 2.5581 (2.6329)	grad_norm 3.1576 (3.1637/1.3715)	mem 16099MB
[2025-01-18 11:40:22 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][140/312]	eta 0:01:23 lr 0.000054	time 0.4613 (0.4853)	model_time 0.4607 (0.4684)	loss 2.2268 (2.6257)	grad_norm 3.8871 (3.1458/1.3937)	mem 16099MB
[2025-01-18 11:40:27 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][150/312]	eta 0:01:18 lr 0.000054	time 0.5815 (0.4840)	model_time 0.5813 (0.4682)	loss 2.7175 (2.6218)	grad_norm 2.3154 (3.0814/1.3741)	mem 16099MB
[2025-01-18 11:40:32 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][160/312]	eta 0:01:13 lr 0.000054	time 0.4597 (0.4838)	model_time 0.4591 (0.4690)	loss 3.0226 (2.6053)	grad_norm 2.4749 (3.1216/1.3855)	mem 16099MB
[2025-01-18 11:40:36 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][170/312]	eta 0:01:08 lr 0.000054	time 0.4469 (0.4825)	model_time 0.4464 (0.4686)	loss 3.2291 (2.6085)	grad_norm 4.9550 (3.1214/1.3773)	mem 16099MB
[2025-01-18 11:40:41 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][180/312]	eta 0:01:03 lr 0.000054	time 0.4470 (0.4818)	model_time 0.4468 (0.4686)	loss 2.4301 (2.6021)	grad_norm 8.6678 (3.1717/1.4501)	mem 16099MB
[2025-01-18 11:40:46 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][190/312]	eta 0:00:58 lr 0.000054	time 0.4493 (0.4805)	model_time 0.4489 (0.4680)	loss 2.8687 (2.5997)	grad_norm 3.2695 (3.1603/1.4321)	mem 16099MB
[2025-01-18 11:40:50 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][200/312]	eta 0:00:53 lr 0.000054	time 0.4544 (0.4798)	model_time 0.4540 (0.4679)	loss 2.8310 (2.5978)	grad_norm 5.5003 (3.1535/1.4202)	mem 16099MB
[2025-01-18 11:40:55 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][210/312]	eta 0:00:48 lr 0.000054	time 0.4471 (0.4787)	model_time 0.4469 (0.4673)	loss 2.7345 (2.6025)	grad_norm 4.4860 (3.1889/1.4787)	mem 16099MB
[2025-01-18 11:40:59 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][220/312]	eta 0:00:43 lr 0.000054	time 0.4676 (0.4780)	model_time 0.4674 (0.4671)	loss 2.8508 (2.6025)	grad_norm 2.1876 (3.2182/1.4978)	mem 16099MB
[2025-01-18 11:41:04 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][230/312]	eta 0:00:39 lr 0.000054	time 0.4445 (0.4770)	model_time 0.4443 (0.4666)	loss 2.6692 (2.6057)	grad_norm 2.8351 (3.2170/1.4825)	mem 16099MB
[2025-01-18 11:41:09 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][240/312]	eta 0:00:34 lr 0.000054	time 0.4481 (0.4761)	model_time 0.4479 (0.4661)	loss 2.3309 (2.6008)	grad_norm 3.5697 (3.2269/1.4805)	mem 16099MB
[2025-01-18 11:41:13 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][250/312]	eta 0:00:29 lr 0.000054	time 0.4603 (0.4753)	model_time 0.4601 (0.4656)	loss 2.8328 (2.6126)	grad_norm 3.0343 (3.2102/1.4690)	mem 16099MB
[2025-01-18 11:41:18 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][260/312]	eta 0:00:24 lr 0.000054	time 0.4447 (0.4749)	model_time 0.4446 (0.4656)	loss 3.1218 (2.6147)	grad_norm 3.1218 (3.1928/1.4546)	mem 16099MB
[2025-01-18 11:41:23 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][270/312]	eta 0:00:19 lr 0.000053	time 0.4554 (0.4749)	model_time 0.4553 (0.4660)	loss 1.7572 (2.6165)	grad_norm 3.0484 (3.1880/1.4405)	mem 16099MB
[2025-01-18 11:41:27 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][280/312]	eta 0:00:15 lr 0.000053	time 0.4435 (0.4754)	model_time 0.4430 (0.4667)	loss 2.6829 (2.6223)	grad_norm 1.6530 (3.1776/1.4251)	mem 16099MB
[2025-01-18 11:41:32 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][290/312]	eta 0:00:10 lr 0.000053	time 0.4558 (0.4758)	model_time 0.4557 (0.4675)	loss 1.5389 (2.6175)	grad_norm 2.3309 (3.1526/1.4174)	mem 16099MB
[2025-01-18 11:41:37 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][300/312]	eta 0:00:05 lr 0.000053	time 0.4416 (0.4758)	model_time 0.4415 (0.4677)	loss 2.1751 (2.6134)	grad_norm 1.2906 (3.1224/1.4213)	mem 16099MB
[2025-01-18 11:41:42 internimage_t_1k_224] (main.py 510): INFO Train: [288/300][310/312]	eta 0:00:00 lr 0.000053	time 0.4437 (0.4751)	model_time 0.4436 (0.4673)	loss 3.1244 (2.6053)	grad_norm 5.4494 (3.0955/1.4134)	mem 16099MB
[2025-01-18 11:41:42 internimage_t_1k_224] (main.py 519): INFO EPOCH 288 training takes 0:02:28
[2025-01-18 11:41:42 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_288.pth saving......
[2025-01-18 11:41:43 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_288.pth saved !!!
[2025-01-18 11:41:51 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.688 (7.688)	Loss 0.7114 (0.7114)	Acc@1 85.376 (85.376)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 11:41:55 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.107 (1.029)	Loss 0.9619 (0.8150)	Acc@1 79.053 (83.216)	Acc@5 95.410 (96.384)	Mem 16099MB
[2025-01-18 11:41:55 internimage_t_1k_224] (main.py 575): INFO [Epoch:288] * Acc@1 83.079 Acc@5 96.385
[2025-01-18 11:41:55 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:41:55 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 11:42:03 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.408 (8.408)	Loss 0.7132 (0.7132)	Acc@1 85.889 (85.889)	Acc@5 97.681 (97.681)	Mem 16099MB
[2025-01-18 11:42:07 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.129)	Loss 0.9429 (0.8119)	Acc@1 79.932 (83.707)	Acc@5 95.361 (96.562)	Mem 16099MB
[2025-01-18 11:42:07 internimage_t_1k_224] (main.py 575): INFO [Epoch:288] * Acc@1 83.553 Acc@5 96.563
[2025-01-18 11:42:07 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.6%
[2025-01-18 11:42:07 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 11:42:09 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 11:42:09 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.55%
[2025-01-18 11:42:11 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][0/312]	eta 0:12:12 lr 0.000053	time 2.3476 (2.3476)	model_time 0.5207 (0.5207)	loss 2.9276 (2.9276)	grad_norm 1.4989 (1.4989/0.0000)	mem 16099MB
[2025-01-18 11:42:16 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][10/312]	eta 0:03:13 lr 0.000053	time 0.4586 (0.6393)	model_time 0.4585 (0.4729)	loss 2.9059 (2.8415)	grad_norm 3.9026 (3.0747/1.2034)	mem 16099MB
[2025-01-18 11:42:21 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][20/312]	eta 0:02:44 lr 0.000053	time 0.5501 (0.5636)	model_time 0.5500 (0.4764)	loss 2.0623 (2.7363)	grad_norm 8.6386 (3.6434/2.0920)	mem 16099MB
[2025-01-18 11:42:25 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][30/312]	eta 0:02:30 lr 0.000053	time 0.4659 (0.5323)	model_time 0.4657 (0.4731)	loss 2.1068 (2.7234)	grad_norm 1.4697 (4.2176/2.6235)	mem 16099MB
[2025-01-18 11:42:30 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][40/312]	eta 0:02:22 lr 0.000053	time 0.4571 (0.5248)	model_time 0.4567 (0.4799)	loss 2.5824 (2.7005)	grad_norm 5.8913 (4.1287/2.4668)	mem 16099MB
[2025-01-18 11:42:35 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][50/312]	eta 0:02:14 lr 0.000053	time 0.4530 (0.5116)	model_time 0.4529 (0.4754)	loss 1.8209 (2.6580)	grad_norm 2.3730 (3.9581/2.3106)	mem 16099MB
[2025-01-18 11:42:39 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][60/312]	eta 0:02:06 lr 0.000053	time 0.4408 (0.5037)	model_time 0.4406 (0.4735)	loss 2.6139 (2.6362)	grad_norm 1.7976 (3.7577/2.1869)	mem 16099MB
[2025-01-18 11:42:44 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][70/312]	eta 0:02:00 lr 0.000053	time 0.4508 (0.4971)	model_time 0.4506 (0.4710)	loss 2.6405 (2.6511)	grad_norm 1.4616 (3.7240/2.0788)	mem 16099MB
[2025-01-18 11:42:49 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][80/312]	eta 0:01:54 lr 0.000053	time 0.4563 (0.4954)	model_time 0.4558 (0.4725)	loss 3.0508 (2.6525)	grad_norm 5.1042 (3.6417/2.0074)	mem 16099MB
[2025-01-18 11:42:54 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][90/312]	eta 0:01:49 lr 0.000052	time 0.4538 (0.4930)	model_time 0.4536 (0.4726)	loss 2.8781 (2.6499)	grad_norm 1.4341 (3.5831/1.9471)	mem 16099MB
[2025-01-18 11:42:58 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][100/312]	eta 0:01:43 lr 0.000052	time 0.4474 (0.4899)	model_time 0.4472 (0.4714)	loss 2.6890 (2.6392)	grad_norm 2.5111 (3.5373/1.8833)	mem 16099MB
[2025-01-18 11:43:03 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][110/312]	eta 0:01:38 lr 0.000052	time 0.4612 (0.4874)	model_time 0.4610 (0.4706)	loss 2.9270 (2.6558)	grad_norm 2.5001 (3.5235/1.8455)	mem 16099MB
[2025-01-18 11:43:07 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][120/312]	eta 0:01:33 lr 0.000052	time 0.4549 (0.4850)	model_time 0.4545 (0.4695)	loss 2.1508 (2.6576)	grad_norm 4.0582 (3.5673/1.8130)	mem 16099MB
[2025-01-18 11:43:12 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][130/312]	eta 0:01:28 lr 0.000052	time 0.4466 (0.4841)	model_time 0.4465 (0.4699)	loss 2.1058 (2.6391)	grad_norm 3.3924 (3.5547/1.7615)	mem 16099MB
[2025-01-18 11:43:17 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][140/312]	eta 0:01:23 lr 0.000052	time 0.4482 (0.4833)	model_time 0.4481 (0.4700)	loss 1.7624 (2.6171)	grad_norm 2.7257 (3.4953/1.7274)	mem 16099MB
[2025-01-18 11:43:21 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][150/312]	eta 0:01:18 lr 0.000052	time 0.4487 (0.4820)	model_time 0.4485 (0.4695)	loss 2.7842 (2.6265)	grad_norm 4.1644 (3.4833/1.7096)	mem 16099MB
[2025-01-18 11:43:26 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][160/312]	eta 0:01:13 lr 0.000052	time 0.4411 (0.4809)	model_time 0.4409 (0.4693)	loss 1.9988 (2.6125)	grad_norm 1.2931 (3.4398/1.6941)	mem 16099MB
[2025-01-18 11:43:31 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][170/312]	eta 0:01:08 lr 0.000052	time 0.4524 (0.4798)	model_time 0.4522 (0.4687)	loss 2.2007 (2.6020)	grad_norm 2.0197 (3.4145/1.6636)	mem 16099MB
[2025-01-18 11:43:36 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][180/312]	eta 0:01:03 lr 0.000052	time 0.4600 (0.4798)	model_time 0.4598 (0.4694)	loss 2.9607 (2.6176)	grad_norm 1.6175 (3.3635/1.6490)	mem 16099MB
[2025-01-18 11:43:40 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][190/312]	eta 0:00:58 lr 0.000052	time 0.4449 (0.4789)	model_time 0.4448 (0.4690)	loss 1.7637 (2.6089)	grad_norm 1.5341 (3.3505/1.6240)	mem 16099MB
[2025-01-18 11:43:45 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][200/312]	eta 0:00:53 lr 0.000052	time 0.4647 (0.4778)	model_time 0.4645 (0.4684)	loss 2.7925 (2.6114)	grad_norm 2.0364 (3.3434/1.5983)	mem 16099MB
[2025-01-18 11:43:49 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][210/312]	eta 0:00:48 lr 0.000052	time 0.4619 (0.4771)	model_time 0.4617 (0.4681)	loss 2.1930 (2.6150)	grad_norm 1.6869 (3.2930/1.5875)	mem 16099MB
[2025-01-18 11:43:54 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][220/312]	eta 0:00:43 lr 0.000051	time 0.4511 (0.4780)	model_time 0.4509 (0.4694)	loss 2.8880 (2.6131)	grad_norm 1.9505 (3.2708/1.5666)	mem 16099MB
[2025-01-18 11:43:59 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][230/312]	eta 0:00:39 lr 0.000051	time 0.4559 (0.4769)	model_time 0.4557 (0.4687)	loss 2.6515 (2.6055)	grad_norm 4.7443 (3.2756/1.5459)	mem 16099MB
[2025-01-18 11:44:03 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][240/312]	eta 0:00:34 lr 0.000051	time 0.4535 (0.4760)	model_time 0.4533 (0.4681)	loss 2.7189 (2.6192)	grad_norm 1.7492 (3.2382/1.5303)	mem 16099MB
[2025-01-18 11:44:08 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][250/312]	eta 0:00:29 lr 0.000051	time 0.4643 (0.4772)	model_time 0.4641 (0.4696)	loss 2.7856 (2.6265)	grad_norm 1.8902 (3.2137/1.5154)	mem 16099MB
[2025-01-18 11:44:13 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][260/312]	eta 0:00:24 lr 0.000051	time 0.4930 (0.4767)	model_time 0.4928 (0.4694)	loss 2.2068 (2.6310)	grad_norm 2.2930 (3.1809/1.5046)	mem 16099MB
[2025-01-18 11:44:18 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][270/312]	eta 0:00:20 lr 0.000051	time 0.5047 (0.4768)	model_time 0.5045 (0.4696)	loss 2.2405 (2.6342)	grad_norm 1.8506 (3.1604/1.4885)	mem 16099MB
[2025-01-18 11:44:23 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][280/312]	eta 0:00:15 lr 0.000051	time 0.4789 (0.4765)	model_time 0.4787 (0.4696)	loss 3.1478 (2.6383)	grad_norm 2.0761 (3.1297/1.4721)	mem 16099MB
[2025-01-18 11:44:27 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][290/312]	eta 0:00:10 lr 0.000051	time 0.4568 (0.4757)	model_time 0.4567 (0.4691)	loss 2.2525 (2.6290)	grad_norm 1.5099 (3.1168/1.4673)	mem 16099MB
[2025-01-18 11:44:32 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][300/312]	eta 0:00:05 lr 0.000051	time 0.4397 (0.4760)	model_time 0.4396 (0.4695)	loss 3.0837 (2.6296)	grad_norm 1.7025 (3.1140/1.4538)	mem 16099MB
[2025-01-18 11:44:37 internimage_t_1k_224] (main.py 510): INFO Train: [289/300][310/312]	eta 0:00:00 lr 0.000051	time 0.5528 (0.4758)	model_time 0.5527 (0.4695)	loss 2.7176 (2.6311)	grad_norm 1.5129 (3.0897/1.4497)	mem 16099MB
[2025-01-18 11:44:37 internimage_t_1k_224] (main.py 519): INFO EPOCH 289 training takes 0:02:28
[2025-01-18 11:44:37 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_289.pth saving......
[2025-01-18 11:44:38 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_289.pth saved !!!
[2025-01-18 11:44:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.575 (7.575)	Loss 0.7215 (0.7215)	Acc@1 85.474 (85.474)	Acc@5 97.534 (97.534)	Mem 16099MB
[2025-01-18 11:44:49 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.015)	Loss 0.9654 (0.8243)	Acc@1 79.004 (83.234)	Acc@5 95.337 (96.387)	Mem 16099MB
[2025-01-18 11:44:49 internimage_t_1k_224] (main.py 575): INFO [Epoch:289] * Acc@1 83.105 Acc@5 96.395
[2025-01-18 11:44:50 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:44:50 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 11:44:58 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.636 (8.636)	Loss 0.7131 (0.7131)	Acc@1 85.938 (85.938)	Acc@5 97.681 (97.681)	Mem 16099MB
[2025-01-18 11:45:02 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.164)	Loss 0.9428 (0.8117)	Acc@1 79.907 (83.718)	Acc@5 95.361 (96.564)	Mem 16099MB
[2025-01-18 11:45:02 internimage_t_1k_224] (main.py 575): INFO [Epoch:289] * Acc@1 83.561 Acc@5 96.567
[2025-01-18 11:45:02 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.6%
[2025-01-18 11:45:02 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 11:45:04 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 11:45:04 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.56%
[2025-01-18 11:45:06 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][0/312]	eta 0:12:59 lr 0.000051	time 2.4979 (2.4979)	model_time 0.4601 (0.4601)	loss 2.7266 (2.7266)	grad_norm 3.4810 (3.4810/0.0000)	mem 16099MB
[2025-01-18 11:45:11 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][10/312]	eta 0:03:20 lr 0.000051	time 0.4568 (0.6644)	model_time 0.4563 (0.4789)	loss 3.2832 (2.6134)	grad_norm 2.9837 (2.8458/0.8147)	mem 16099MB
[2025-01-18 11:45:16 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][20/312]	eta 0:02:47 lr 0.000051	time 0.4647 (0.5724)	model_time 0.4646 (0.4751)	loss 2.9574 (2.6227)	grad_norm 3.0077 (2.8246/0.8094)	mem 16099MB
[2025-01-18 11:45:21 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][30/312]	eta 0:02:30 lr 0.000051	time 0.4466 (0.5347)	model_time 0.4464 (0.4686)	loss 2.1892 (2.6040)	grad_norm 2.8075 (2.8929/0.9834)	mem 16099MB
[2025-01-18 11:45:25 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][40/312]	eta 0:02:20 lr 0.000051	time 0.4526 (0.5176)	model_time 0.4524 (0.4676)	loss 2.8338 (2.5857)	grad_norm 3.3047 (2.8472/0.9669)	mem 16099MB
[2025-01-18 11:45:30 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][50/312]	eta 0:02:13 lr 0.000051	time 0.4441 (0.5092)	model_time 0.4439 (0.4690)	loss 2.2298 (2.6210)	grad_norm 6.8167 (2.9604/1.1773)	mem 16099MB
[2025-01-18 11:45:34 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][60/312]	eta 0:02:05 lr 0.000050	time 0.4513 (0.4997)	model_time 0.4511 (0.4660)	loss 2.3782 (2.6311)	grad_norm 1.2325 (2.9270/1.2026)	mem 16099MB
[2025-01-18 11:45:39 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][70/312]	eta 0:01:59 lr 0.000050	time 0.4656 (0.4939)	model_time 0.4654 (0.4649)	loss 3.0494 (2.6556)	grad_norm 3.3086 (2.9229/1.1976)	mem 16099MB
[2025-01-18 11:45:44 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][80/312]	eta 0:01:53 lr 0.000050	time 0.4559 (0.4907)	model_time 0.4558 (0.4652)	loss 3.0067 (2.6624)	grad_norm 4.3142 (2.9258/1.1653)	mem 16099MB
[2025-01-18 11:45:48 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][90/312]	eta 0:01:48 lr 0.000050	time 0.4559 (0.4868)	model_time 0.4556 (0.4641)	loss 3.4647 (2.6391)	grad_norm 2.7912 (2.9673/1.2116)	mem 16099MB
[2025-01-18 11:45:53 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][100/312]	eta 0:01:42 lr 0.000050	time 0.4570 (0.4841)	model_time 0.4568 (0.4635)	loss 2.3459 (2.6074)	grad_norm 3.3001 (2.9957/1.2209)	mem 16099MB
[2025-01-18 11:45:57 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][110/312]	eta 0:01:37 lr 0.000050	time 0.4482 (0.4811)	model_time 0.4480 (0.4624)	loss 2.8169 (2.6047)	grad_norm 1.7726 (2.9947/1.1985)	mem 16099MB
[2025-01-18 11:46:02 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][120/312]	eta 0:01:32 lr 0.000050	time 0.4358 (0.4798)	model_time 0.4356 (0.4626)	loss 3.2118 (2.6056)	grad_norm 4.0810 (2.9862/1.1732)	mem 16099MB
[2025-01-18 11:46:07 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][130/312]	eta 0:01:27 lr 0.000050	time 0.5479 (0.4823)	model_time 0.5477 (0.4664)	loss 3.0748 (2.6085)	grad_norm 2.3799 (2.9296/1.1533)	mem 16099MB
[2025-01-18 11:46:12 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][140/312]	eta 0:01:22 lr 0.000050	time 0.5514 (0.4807)	model_time 0.5509 (0.4659)	loss 3.1088 (2.5996)	grad_norm 2.0202 (2.9089/1.1339)	mem 16099MB
[2025-01-18 11:46:16 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][150/312]	eta 0:01:17 lr 0.000050	time 0.4552 (0.4790)	model_time 0.4550 (0.4651)	loss 2.6659 (2.6046)	grad_norm 3.6044 (2.9680/1.2178)	mem 16099MB
[2025-01-18 11:46:21 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][160/312]	eta 0:01:12 lr 0.000050	time 0.5340 (0.4785)	model_time 0.5335 (0.4655)	loss 1.9203 (2.5951)	grad_norm 3.0232 (2.9836/1.2013)	mem 16099MB
[2025-01-18 11:46:26 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][170/312]	eta 0:01:07 lr 0.000050	time 0.4490 (0.4787)	model_time 0.4488 (0.4664)	loss 2.5888 (2.6003)	grad_norm 1.9467 (3.0224/1.2360)	mem 16099MB
[2025-01-18 11:46:31 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][180/312]	eta 0:01:03 lr 0.000050	time 0.6315 (0.4784)	model_time 0.6310 (0.4668)	loss 1.8242 (2.5980)	grad_norm 2.9094 (3.0263/1.2547)	mem 16099MB
[2025-01-18 11:46:35 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][190/312]	eta 0:00:58 lr 0.000050	time 0.4511 (0.4779)	model_time 0.4509 (0.4668)	loss 2.1912 (2.5885)	grad_norm 4.2230 (2.9906/1.2484)	mem 16099MB
[2025-01-18 11:46:40 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][200/312]	eta 0:00:53 lr 0.000050	time 0.4600 (0.4771)	model_time 0.4598 (0.4666)	loss 2.9938 (2.5922)	grad_norm 1.7035 (2.9571/1.2361)	mem 16099MB
[2025-01-18 11:46:45 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][210/312]	eta 0:00:48 lr 0.000049	time 0.4475 (0.4767)	model_time 0.4473 (0.4667)	loss 2.6645 (2.5919)	grad_norm 1.9150 (2.9351/1.2184)	mem 16099MB
[2025-01-18 11:46:49 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][220/312]	eta 0:00:43 lr 0.000049	time 0.4438 (0.4769)	model_time 0.4433 (0.4673)	loss 3.0722 (2.6078)	grad_norm 3.5195 (2.9090/1.2048)	mem 16099MB
[2025-01-18 11:46:54 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][230/312]	eta 0:00:39 lr 0.000049	time 0.4485 (0.4760)	model_time 0.4480 (0.4668)	loss 2.9727 (2.6172)	grad_norm 1.5298 (2.8858/1.1943)	mem 16099MB
[2025-01-18 11:46:59 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][240/312]	eta 0:00:34 lr 0.000049	time 0.5663 (0.4762)	model_time 0.5662 (0.4674)	loss 2.4016 (2.6244)	grad_norm 2.4449 (2.8804/1.1810)	mem 16099MB
[2025-01-18 11:47:04 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][250/312]	eta 0:00:29 lr 0.000049	time 0.4539 (0.4763)	model_time 0.4534 (0.4678)	loss 2.9733 (2.6296)	grad_norm 3.7796 (2.8718/1.1710)	mem 16099MB
[2025-01-18 11:47:08 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][260/312]	eta 0:00:24 lr 0.000049	time 0.4587 (0.4757)	model_time 0.4585 (0.4675)	loss 2.7584 (2.6201)	grad_norm 5.2519 (2.9017/1.1870)	mem 16099MB
[2025-01-18 11:47:13 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][270/312]	eta 0:00:19 lr 0.000049	time 0.4423 (0.4751)	model_time 0.4421 (0.4672)	loss 2.9121 (2.6202)	grad_norm 4.0615 (2.9472/1.2153)	mem 16099MB
[2025-01-18 11:47:17 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][280/312]	eta 0:00:15 lr 0.000049	time 0.4571 (0.4744)	model_time 0.4569 (0.4667)	loss 2.0161 (2.6202)	grad_norm 3.1461 (2.9787/1.2426)	mem 16099MB
[2025-01-18 11:47:22 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][290/312]	eta 0:00:10 lr 0.000049	time 0.4425 (0.4750)	model_time 0.4424 (0.4676)	loss 2.8403 (2.6201)	grad_norm 2.8643 (2.9748/1.2298)	mem 16099MB
[2025-01-18 11:47:27 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][300/312]	eta 0:00:05 lr 0.000049	time 0.4387 (0.4748)	model_time 0.4385 (0.4677)	loss 2.8055 (2.6254)	grad_norm 3.3195 (2.9747/1.2405)	mem 16099MB
[2025-01-18 11:47:31 internimage_t_1k_224] (main.py 510): INFO Train: [290/300][310/312]	eta 0:00:00 lr 0.000049	time 0.4422 (0.4738)	model_time 0.4421 (0.4669)	loss 2.0466 (2.6321)	grad_norm 1.7789 (3.0120/1.2882)	mem 16099MB
[2025-01-18 11:47:32 internimage_t_1k_224] (main.py 519): INFO EPOCH 290 training takes 0:02:27
[2025-01-18 11:47:32 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_290.pth saving......
[2025-01-18 11:47:33 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_290.pth saved !!!
[2025-01-18 11:47:40 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.483 (7.483)	Loss 0.7172 (0.7172)	Acc@1 85.278 (85.278)	Acc@5 97.583 (97.583)	Mem 16099MB
[2025-01-18 11:47:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.004)	Loss 0.9621 (0.8167)	Acc@1 79.346 (83.243)	Acc@5 95.312 (96.416)	Mem 16099MB
[2025-01-18 11:47:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:290] * Acc@1 83.107 Acc@5 96.429
[2025-01-18 11:47:44 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:47:44 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 11:47:52 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.317 (8.317)	Loss 0.7129 (0.7129)	Acc@1 85.938 (85.938)	Acc@5 97.632 (97.632)	Mem 16099MB
[2025-01-18 11:47:57 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.130)	Loss 0.9428 (0.8114)	Acc@1 79.956 (83.718)	Acc@5 95.410 (96.566)	Mem 16099MB
[2025-01-18 11:47:57 internimage_t_1k_224] (main.py 575): INFO [Epoch:290] * Acc@1 83.561 Acc@5 96.571
[2025-01-18 11:47:57 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.6%
[2025-01-18 11:47:57 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.56%
[2025-01-18 11:48:00 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][0/312]	eta 0:16:20 lr 0.000049	time 3.1422 (3.1422)	model_time 1.4249 (1.4249)	loss 2.3420 (2.3420)	grad_norm 3.2240 (3.2240/0.0000)	mem 16099MB
[2025-01-18 11:48:05 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][10/312]	eta 0:03:40 lr 0.000049	time 0.5353 (0.7305)	model_time 0.5352 (0.5740)	loss 2.7401 (2.4255)	grad_norm 3.7352 (3.4570/1.3820)	mem 16099MB
[2025-01-18 11:48:09 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][20/312]	eta 0:02:54 lr 0.000049	time 0.4538 (0.5991)	model_time 0.4536 (0.5170)	loss 1.8131 (2.5232)	grad_norm 5.8237 (3.6486/1.3595)	mem 16099MB
[2025-01-18 11:48:14 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][30/312]	eta 0:02:35 lr 0.000049	time 0.4577 (0.5516)	model_time 0.4575 (0.4958)	loss 2.9945 (2.5711)	grad_norm 2.5083 (3.7751/1.4308)	mem 16099MB
[2025-01-18 11:48:18 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][40/312]	eta 0:02:23 lr 0.000049	time 0.4531 (0.5283)	model_time 0.4529 (0.4861)	loss 3.2317 (2.6219)	grad_norm 5.8717 (3.8180/1.3924)	mem 16099MB
[2025-01-18 11:48:23 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][50/312]	eta 0:02:15 lr 0.000048	time 0.4515 (0.5159)	model_time 0.4509 (0.4819)	loss 1.9538 (2.6104)	grad_norm 1.4711 (3.6516/1.4209)	mem 16099MB
[2025-01-18 11:48:28 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][60/312]	eta 0:02:07 lr 0.000048	time 0.4535 (0.5059)	model_time 0.4533 (0.4774)	loss 1.9332 (2.6012)	grad_norm 2.3868 (3.5395/1.3663)	mem 16099MB
[2025-01-18 11:48:32 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][70/312]	eta 0:02:00 lr 0.000048	time 0.4647 (0.4996)	model_time 0.4645 (0.4751)	loss 2.7619 (2.6463)	grad_norm 3.3307 (3.3152/1.4031)	mem 16099MB
[2025-01-18 11:48:37 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][80/312]	eta 0:01:54 lr 0.000048	time 0.4336 (0.4937)	model_time 0.4334 (0.4721)	loss 3.2304 (2.6590)	grad_norm 3.3521 (3.2324/1.3551)	mem 16099MB
[2025-01-18 11:48:41 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][90/312]	eta 0:01:49 lr 0.000048	time 0.5274 (0.4926)	model_time 0.5272 (0.4733)	loss 2.8544 (2.6713)	grad_norm 6.3194 (3.2529/1.3701)	mem 16099MB
[2025-01-18 11:48:46 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][100/312]	eta 0:01:43 lr 0.000048	time 0.4417 (0.4894)	model_time 0.4415 (0.4720)	loss 1.6345 (2.6696)	grad_norm 3.4133 (3.2172/1.3207)	mem 16099MB
[2025-01-18 11:48:51 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][110/312]	eta 0:01:38 lr 0.000048	time 0.4571 (0.4869)	model_time 0.4566 (0.4710)	loss 2.8466 (2.6701)	grad_norm 7.2795 (3.2755/1.3367)	mem 16099MB
[2025-01-18 11:48:55 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][120/312]	eta 0:01:33 lr 0.000048	time 0.4560 (0.4860)	model_time 0.4558 (0.4714)	loss 3.0116 (2.6547)	grad_norm 3.3637 (3.2201/1.3303)	mem 16099MB
[2025-01-18 11:49:00 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][130/312]	eta 0:01:28 lr 0.000048	time 0.4540 (0.4870)	model_time 0.4538 (0.4736)	loss 1.8944 (2.6599)	grad_norm 2.1111 (3.1880/1.3204)	mem 16099MB
[2025-01-18 11:49:06 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][140/312]	eta 0:01:24 lr 0.000048	time 0.7302 (0.4887)	model_time 0.7300 (0.4761)	loss 3.0549 (2.6654)	grad_norm 2.9292 (3.1465/1.2993)	mem 16099MB
[2025-01-18 11:49:10 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][150/312]	eta 0:01:18 lr 0.000048	time 0.4559 (0.4866)	model_time 0.4558 (0.4748)	loss 2.8251 (2.6616)	grad_norm 2.4232 (3.1441/1.2972)	mem 16099MB
[2025-01-18 11:49:15 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][160/312]	eta 0:01:13 lr 0.000048	time 0.4505 (0.4867)	model_time 0.4503 (0.4756)	loss 2.7696 (2.6557)	grad_norm 3.6688 (3.1603/1.2919)	mem 16099MB
[2025-01-18 11:49:20 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][170/312]	eta 0:01:08 lr 0.000048	time 0.4501 (0.4849)	model_time 0.4499 (0.4744)	loss 2.4824 (2.6544)	grad_norm 5.1437 (3.2317/1.3657)	mem 16099MB
[2025-01-18 11:49:24 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][180/312]	eta 0:01:03 lr 0.000048	time 0.4761 (0.4838)	model_time 0.4756 (0.4740)	loss 3.0054 (2.6535)	grad_norm 3.3295 (3.2745/1.3866)	mem 16099MB
[2025-01-18 11:49:29 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][190/312]	eta 0:00:58 lr 0.000048	time 0.4582 (0.4822)	model_time 0.4580 (0.4729)	loss 3.1215 (2.6523)	grad_norm 2.9423 (3.3333/1.4404)	mem 16099MB
[2025-01-18 11:49:34 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][200/312]	eta 0:00:53 lr 0.000048	time 0.4690 (0.4819)	model_time 0.4688 (0.4730)	loss 3.0493 (2.6520)	grad_norm 5.7813 (3.3512/1.4861)	mem 16099MB
[2025-01-18 11:49:38 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][210/312]	eta 0:00:49 lr 0.000048	time 0.4572 (0.4806)	model_time 0.4570 (0.4721)	loss 1.8563 (2.6482)	grad_norm 2.0408 (3.3507/1.4910)	mem 16099MB
[2025-01-18 11:49:43 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][220/312]	eta 0:00:44 lr 0.000047	time 0.4514 (0.4793)	model_time 0.4509 (0.4712)	loss 2.4397 (2.6414)	grad_norm 4.0539 (3.3164/1.4862)	mem 16099MB
[2025-01-18 11:49:47 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][230/312]	eta 0:00:39 lr 0.000047	time 0.4558 (0.4788)	model_time 0.4553 (0.4710)	loss 2.4857 (2.6339)	grad_norm 2.9468 (3.3058/1.4924)	mem 16099MB
[2025-01-18 11:49:52 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][240/312]	eta 0:00:34 lr 0.000047	time 0.4554 (0.4778)	model_time 0.4549 (0.4703)	loss 1.5336 (2.6316)	grad_norm 2.2466 (3.2890/1.4755)	mem 16099MB
[2025-01-18 11:49:56 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][250/312]	eta 0:00:29 lr 0.000047	time 0.4468 (0.4768)	model_time 0.4467 (0.4695)	loss 3.1300 (2.6337)	grad_norm 4.7565 (3.2703/1.4689)	mem 16099MB
[2025-01-18 11:50:01 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][260/312]	eta 0:00:24 lr 0.000047	time 0.4671 (0.4768)	model_time 0.4666 (0.4698)	loss 2.6710 (2.6388)	grad_norm 1.7679 (3.2618/1.4593)	mem 16099MB
[2025-01-18 11:50:06 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][270/312]	eta 0:00:20 lr 0.000047	time 0.4486 (0.4763)	model_time 0.4482 (0.4695)	loss 3.1095 (2.6389)	grad_norm 3.6556 (3.2453/1.4426)	mem 16099MB
[2025-01-18 11:50:10 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][280/312]	eta 0:00:15 lr 0.000047	time 0.4575 (0.4755)	model_time 0.4571 (0.4690)	loss 2.3929 (2.6386)	grad_norm 2.8835 (3.2390/1.4279)	mem 16099MB
[2025-01-18 11:50:15 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][290/312]	eta 0:00:10 lr 0.000047	time 0.4457 (0.4754)	model_time 0.4455 (0.4691)	loss 2.7906 (2.6432)	grad_norm 1.8507 (3.2298/1.4138)	mem 16099MB
[2025-01-18 11:50:20 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][300/312]	eta 0:00:05 lr 0.000047	time 0.4376 (0.4747)	model_time 0.4374 (0.4686)	loss 2.9314 (2.6448)	grad_norm 2.0550 (3.2297/1.4159)	mem 16099MB
[2025-01-18 11:50:24 internimage_t_1k_224] (main.py 510): INFO Train: [291/300][310/312]	eta 0:00:00 lr 0.000047	time 0.5465 (0.4740)	model_time 0.5464 (0.4681)	loss 2.3001 (2.6380)	grad_norm 1.7213 (3.2111/1.4092)	mem 16099MB
[2025-01-18 11:50:25 internimage_t_1k_224] (main.py 519): INFO EPOCH 291 training takes 0:02:27
[2025-01-18 11:50:25 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_291.pth saving......
[2025-01-18 11:50:26 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_291.pth saved !!!
[2025-01-18 11:50:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.673 (7.673)	Loss 0.7243 (0.7243)	Acc@1 85.327 (85.327)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 11:50:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.106 (1.025)	Loss 0.9703 (0.8193)	Acc@1 78.882 (83.179)	Acc@5 95.142 (96.342)	Mem 16099MB
[2025-01-18 11:50:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:291] * Acc@1 83.057 Acc@5 96.345
[2025-01-18 11:50:37 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:50:37 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 11:50:46 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.519 (8.519)	Loss 0.7127 (0.7127)	Acc@1 85.962 (85.962)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 11:50:50 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.104 (1.140)	Loss 0.9426 (0.8111)	Acc@1 79.932 (83.725)	Acc@5 95.435 (96.566)	Mem 16099MB
[2025-01-18 11:50:50 internimage_t_1k_224] (main.py 575): INFO [Epoch:291] * Acc@1 83.565 Acc@5 96.573
[2025-01-18 11:50:50 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.6%
[2025-01-18 11:50:50 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saving......
[2025-01-18 11:50:51 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_ema_best.pth saved !!!
[2025-01-18 11:50:51 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.57%
[2025-01-18 11:50:53 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][0/312]	eta 0:11:41 lr 0.000047	time 2.2474 (2.2474)	model_time 0.4812 (0.4812)	loss 3.2075 (3.2075)	grad_norm 4.4715 (4.4715/0.0000)	mem 16099MB
[2025-01-18 11:50:58 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][10/312]	eta 0:03:07 lr 0.000047	time 0.4468 (0.6217)	model_time 0.4467 (0.4609)	loss 2.0704 (2.6448)	grad_norm 2.6178 (3.6563/1.0574)	mem 16099MB
[2025-01-18 11:51:03 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][20/312]	eta 0:02:40 lr 0.000047	time 0.4656 (0.5505)	model_time 0.4655 (0.4661)	loss 2.8406 (2.5981)	grad_norm 3.0010 (3.4894/0.9969)	mem 16099MB
[2025-01-18 11:51:08 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][30/312]	eta 0:02:29 lr 0.000047	time 0.4491 (0.5288)	model_time 0.4490 (0.4715)	loss 2.2909 (2.6545)	grad_norm 1.8697 (3.5336/1.0873)	mem 16099MB
[2025-01-18 11:51:12 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][40/312]	eta 0:02:19 lr 0.000047	time 0.4441 (0.5111)	model_time 0.4439 (0.4677)	loss 2.6212 (2.7145)	grad_norm 1.6605 (3.2916/1.1154)	mem 16099MB
[2025-01-18 11:51:17 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][50/312]	eta 0:02:11 lr 0.000047	time 0.4642 (0.5024)	model_time 0.4640 (0.4674)	loss 2.8384 (2.7374)	grad_norm 6.0545 (3.2595/1.2379)	mem 16099MB
[2025-01-18 11:51:21 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][60/312]	eta 0:02:04 lr 0.000047	time 0.4588 (0.4949)	model_time 0.4582 (0.4655)	loss 1.9280 (2.7250)	grad_norm 2.1564 (3.1815/1.1808)	mem 16099MB
[2025-01-18 11:51:26 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][70/312]	eta 0:01:58 lr 0.000047	time 0.5438 (0.4901)	model_time 0.5436 (0.4649)	loss 2.7437 (2.7419)	grad_norm 1.3331 (3.1118/1.1942)	mem 16099MB
[2025-01-18 11:51:31 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][80/312]	eta 0:01:53 lr 0.000047	time 0.4408 (0.4874)	model_time 0.4406 (0.4652)	loss 1.9098 (2.6975)	grad_norm 2.1945 (3.0293/1.1754)	mem 16099MB
[2025-01-18 11:51:35 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][90/312]	eta 0:01:47 lr 0.000046	time 0.5297 (0.4853)	model_time 0.5295 (0.4655)	loss 3.1135 (2.6687)	grad_norm 2.7541 (2.9939/1.1815)	mem 16099MB
[2025-01-18 11:51:40 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][100/312]	eta 0:01:42 lr 0.000046	time 0.4330 (0.4835)	model_time 0.4329 (0.4657)	loss 2.4150 (2.6740)	grad_norm 6.4400 (2.9818/1.2212)	mem 16099MB
[2025-01-18 11:51:45 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][110/312]	eta 0:01:37 lr 0.000046	time 0.4327 (0.4832)	model_time 0.4323 (0.4669)	loss 2.9755 (2.6568)	grad_norm 2.5168 (2.9907/1.2751)	mem 16099MB
[2025-01-18 11:51:50 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][120/312]	eta 0:01:32 lr 0.000046	time 0.4470 (0.4823)	model_time 0.4465 (0.4673)	loss 2.8748 (2.6380)	grad_norm 3.8151 (3.0597/1.2770)	mem 16099MB
[2025-01-18 11:51:54 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][130/312]	eta 0:01:27 lr 0.000046	time 0.4480 (0.4804)	model_time 0.4478 (0.4665)	loss 2.7985 (2.6351)	grad_norm 4.0590 (3.1946/1.3957)	mem 16099MB
[2025-01-18 11:51:59 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][140/312]	eta 0:01:22 lr 0.000046	time 0.4588 (0.4823)	model_time 0.4586 (0.4694)	loss 2.9520 (2.6307)	grad_norm 1.8534 (3.1719/1.3945)	mem 16099MB
[2025-01-18 11:52:04 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][150/312]	eta 0:01:17 lr 0.000046	time 0.4524 (0.4812)	model_time 0.4522 (0.4691)	loss 2.7244 (2.6337)	grad_norm 2.0402 (3.1484/1.4005)	mem 16099MB
[2025-01-18 11:52:09 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][160/312]	eta 0:01:12 lr 0.000046	time 0.4516 (0.4801)	model_time 0.4511 (0.4687)	loss 3.2886 (2.6357)	grad_norm 2.2608 (3.1062/1.3756)	mem 16099MB
[2025-01-18 11:52:13 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][170/312]	eta 0:01:07 lr 0.000046	time 0.4583 (0.4785)	model_time 0.4581 (0.4677)	loss 2.8858 (2.6407)	grad_norm 2.9817 (3.0761/1.3541)	mem 16099MB
[2025-01-18 11:52:18 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][180/312]	eta 0:01:03 lr 0.000046	time 0.4415 (0.4780)	model_time 0.4411 (0.4678)	loss 2.9524 (2.6356)	grad_norm 2.0107 (3.0735/1.3296)	mem 16099MB
[2025-01-18 11:52:22 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][190/312]	eta 0:00:58 lr 0.000046	time 0.4467 (0.4767)	model_time 0.4463 (0.4670)	loss 2.9219 (2.6341)	grad_norm 3.9244 (3.0711/1.3093)	mem 16099MB
[2025-01-18 11:52:27 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][200/312]	eta 0:00:53 lr 0.000046	time 0.4468 (0.4754)	model_time 0.4466 (0.4662)	loss 2.9096 (2.6486)	grad_norm 4.9450 (3.0888/1.3165)	mem 16099MB
[2025-01-18 11:52:32 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][210/312]	eta 0:00:48 lr 0.000046	time 0.4584 (0.4759)	model_time 0.4579 (0.4672)	loss 2.5442 (2.6464)	grad_norm 2.2079 (3.0740/1.3035)	mem 16099MB
[2025-01-18 11:52:36 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][220/312]	eta 0:00:43 lr 0.000046	time 0.4497 (0.4752)	model_time 0.4492 (0.4668)	loss 3.0633 (2.6444)	grad_norm 5.6002 (3.0783/1.2986)	mem 16099MB
[2025-01-18 11:52:41 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][230/312]	eta 0:00:38 lr 0.000046	time 0.4545 (0.4745)	model_time 0.4540 (0.4664)	loss 1.9404 (2.6300)	grad_norm 1.9021 (3.0863/1.2919)	mem 16099MB
[2025-01-18 11:52:45 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][240/312]	eta 0:00:34 lr 0.000046	time 0.4494 (0.4739)	model_time 0.4490 (0.4662)	loss 2.9072 (2.6320)	grad_norm 2.8485 (3.0606/1.2839)	mem 16099MB
[2025-01-18 11:52:50 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][250/312]	eta 0:00:29 lr 0.000046	time 0.4450 (0.4731)	model_time 0.4445 (0.4657)	loss 2.5126 (2.6174)	grad_norm 5.6086 (3.0689/1.2866)	mem 16099MB
[2025-01-18 11:52:55 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][260/312]	eta 0:00:24 lr 0.000046	time 0.4622 (0.4733)	model_time 0.4620 (0.4662)	loss 2.3277 (2.6110)	grad_norm 1.5453 (3.0729/1.2913)	mem 16099MB
[2025-01-18 11:52:59 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][270/312]	eta 0:00:19 lr 0.000046	time 0.4495 (0.4731)	model_time 0.4494 (0.4661)	loss 3.5460 (2.6152)	grad_norm 2.2441 (3.0843/1.2920)	mem 16099MB
[2025-01-18 11:53:04 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][280/312]	eta 0:00:15 lr 0.000045	time 0.4467 (0.4732)	model_time 0.4463 (0.4666)	loss 2.9346 (2.6130)	grad_norm 3.7573 (3.0974/1.3015)	mem 16099MB
[2025-01-18 11:53:09 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][290/312]	eta 0:00:10 lr 0.000045	time 0.4640 (0.4732)	model_time 0.4635 (0.4668)	loss 2.4992 (2.6099)	grad_norm 2.7524 (3.0752/1.2946)	mem 16099MB
[2025-01-18 11:53:13 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][300/312]	eta 0:00:05 lr 0.000045	time 0.4408 (0.4725)	model_time 0.4406 (0.4662)	loss 2.6969 (2.6151)	grad_norm 2.5705 (3.0912/1.3093)	mem 16099MB
[2025-01-18 11:53:18 internimage_t_1k_224] (main.py 510): INFO Train: [292/300][310/312]	eta 0:00:00 lr 0.000045	time 0.5568 (0.4718)	model_time 0.5567 (0.4657)	loss 2.8051 (2.6136)	grad_norm 2.4165 (3.0830/1.3133)	mem 16099MB
[2025-01-18 11:53:18 internimage_t_1k_224] (main.py 519): INFO EPOCH 292 training takes 0:02:27
[2025-01-18 11:53:18 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_292.pth saving......
[2025-01-18 11:53:20 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_292.pth saved !!!
[2025-01-18 11:53:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.546 (7.546)	Loss 0.7218 (0.7218)	Acc@1 85.400 (85.400)	Acc@5 97.485 (97.485)	Mem 16099MB
[2025-01-18 11:53:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.017)	Loss 0.9723 (0.8212)	Acc@1 78.833 (83.265)	Acc@5 95.093 (96.329)	Mem 16099MB
[2025-01-18 11:53:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:292] * Acc@1 83.111 Acc@5 96.335
[2025-01-18 11:53:31 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:53:31 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 11:53:39 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.457 (8.457)	Loss 0.7123 (0.7123)	Acc@1 85.938 (85.938)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 11:53:44 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.148)	Loss 0.9423 (0.8107)	Acc@1 79.858 (83.720)	Acc@5 95.435 (96.566)	Mem 16099MB
[2025-01-18 11:53:44 internimage_t_1k_224] (main.py 575): INFO [Epoch:292] * Acc@1 83.557 Acc@5 96.575
[2025-01-18 11:53:44 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.6%
[2025-01-18 11:53:44 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.57%
[2025-01-18 11:53:47 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][0/312]	eta 0:14:04 lr 0.000045	time 2.7075 (2.7075)	model_time 1.2961 (1.2961)	loss 2.1388 (2.1388)	grad_norm 2.4724 (2.4724/0.0000)	mem 16099MB
[2025-01-18 11:53:51 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][10/312]	eta 0:03:27 lr 0.000045	time 0.4577 (0.6859)	model_time 0.4567 (0.5572)	loss 2.9588 (2.4907)	grad_norm 1.7963 (2.7368/0.8062)	mem 16099MB
[2025-01-18 11:53:56 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][20/312]	eta 0:02:49 lr 0.000045	time 0.4553 (0.5803)	model_time 0.4548 (0.5126)	loss 2.6072 (2.5660)	grad_norm 4.6944 (2.8035/1.1177)	mem 16099MB
[2025-01-18 11:54:01 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][30/312]	eta 0:02:32 lr 0.000045	time 0.4391 (0.5418)	model_time 0.4390 (0.4959)	loss 2.6533 (2.5858)	grad_norm 1.7352 (2.7771/1.0241)	mem 16099MB
[2025-01-18 11:54:05 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][40/312]	eta 0:02:21 lr 0.000045	time 0.4486 (0.5199)	model_time 0.4483 (0.4851)	loss 2.7019 (2.6369)	grad_norm 2.6231 (2.9379/1.1164)	mem 16099MB
[2025-01-18 11:54:10 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][50/312]	eta 0:02:14 lr 0.000045	time 0.4421 (0.5150)	model_time 0.4420 (0.4869)	loss 3.1762 (2.6583)	grad_norm 2.7000 (2.9235/1.0773)	mem 16099MB
[2025-01-18 11:54:15 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][60/312]	eta 0:02:07 lr 0.000045	time 0.4552 (0.5045)	model_time 0.4549 (0.4810)	loss 2.2752 (2.6511)	grad_norm 4.0063 (2.8728/1.0439)	mem 16099MB
[2025-01-18 11:54:19 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][70/312]	eta 0:02:00 lr 0.000045	time 0.4514 (0.4981)	model_time 0.4509 (0.4777)	loss 2.6781 (2.6584)	grad_norm 2.1130 (2.7928/1.0350)	mem 16099MB
[2025-01-18 11:54:24 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][80/312]	eta 0:01:54 lr 0.000045	time 0.4549 (0.4948)	model_time 0.4548 (0.4769)	loss 3.1258 (2.6516)	grad_norm 2.0098 (2.8098/1.0922)	mem 16099MB
[2025-01-18 11:54:29 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][90/312]	eta 0:01:49 lr 0.000045	time 0.7054 (0.4936)	model_time 0.7049 (0.4777)	loss 1.5822 (2.6212)	grad_norm 1.7586 (2.7560/1.0813)	mem 16099MB
[2025-01-18 11:54:33 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][100/312]	eta 0:01:43 lr 0.000045	time 0.4552 (0.4901)	model_time 0.4547 (0.4757)	loss 3.2150 (2.6192)	grad_norm 1.8139 (2.7126/1.0484)	mem 16099MB
[2025-01-18 11:54:38 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][110/312]	eta 0:01:38 lr 0.000045	time 0.4614 (0.4881)	model_time 0.4612 (0.4750)	loss 2.8993 (2.6179)	grad_norm 2.4402 (2.7616/1.0738)	mem 16099MB
[2025-01-18 11:54:43 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][120/312]	eta 0:01:33 lr 0.000045	time 0.4512 (0.4853)	model_time 0.4507 (0.4732)	loss 2.7845 (2.6289)	grad_norm 4.1449 (2.7911/1.1055)	mem 16099MB
[2025-01-18 11:54:47 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][130/312]	eta 0:01:28 lr 0.000045	time 0.4679 (0.4839)	model_time 0.4675 (0.4727)	loss 2.6333 (2.6358)	grad_norm 2.1360 (2.7784/1.1049)	mem 16099MB
[2025-01-18 11:54:52 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][140/312]	eta 0:01:22 lr 0.000045	time 0.5328 (0.4824)	model_time 0.5326 (0.4720)	loss 2.7229 (2.6322)	grad_norm 2.5247 (2.7733/1.0903)	mem 16099MB
[2025-01-18 11:54:56 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][150/312]	eta 0:01:17 lr 0.000045	time 0.4604 (0.4811)	model_time 0.4602 (0.4713)	loss 3.1709 (2.6371)	grad_norm 3.4752 (2.7811/1.1164)	mem 16099MB
[2025-01-18 11:55:01 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][160/312]	eta 0:01:12 lr 0.000045	time 0.4329 (0.4795)	model_time 0.4327 (0.4703)	loss 2.7671 (2.6487)	grad_norm 2.6118 (2.7830/1.1004)	mem 16099MB
[2025-01-18 11:55:06 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][170/312]	eta 0:01:07 lr 0.000045	time 0.4518 (0.4787)	model_time 0.4514 (0.4701)	loss 2.9599 (2.6456)	grad_norm 1.9106 (2.7834/1.1083)	mem 16099MB
[2025-01-18 11:55:10 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][180/312]	eta 0:01:03 lr 0.000044	time 0.4433 (0.4778)	model_time 0.4428 (0.4696)	loss 3.1075 (2.6559)	grad_norm 2.7860 (2.7796/1.1112)	mem 16099MB
[2025-01-18 11:55:15 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][190/312]	eta 0:00:58 lr 0.000044	time 0.5436 (0.4778)	model_time 0.5431 (0.4699)	loss 2.6297 (2.6417)	grad_norm 2.5143 (2.8031/1.1604)	mem 16099MB
[2025-01-18 11:55:20 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][200/312]	eta 0:00:53 lr 0.000044	time 0.4455 (0.4765)	model_time 0.4454 (0.4690)	loss 2.6382 (2.6492)	grad_norm 2.0431 (2.8150/1.1545)	mem 16099MB
[2025-01-18 11:55:24 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][210/312]	eta 0:00:48 lr 0.000044	time 0.4478 (0.4759)	model_time 0.4473 (0.4687)	loss 3.3337 (2.6428)	grad_norm 2.9315 (2.8230/1.1417)	mem 16099MB
[2025-01-18 11:55:29 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][220/312]	eta 0:00:43 lr 0.000044	time 0.4510 (0.4748)	model_time 0.4505 (0.4680)	loss 2.6825 (2.6482)	grad_norm 3.1147 (2.8548/1.1629)	mem 16099MB
[2025-01-18 11:55:33 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][230/312]	eta 0:00:38 lr 0.000044	time 0.4555 (0.4740)	model_time 0.4553 (0.4674)	loss 3.2222 (2.6423)	grad_norm 3.5321 (2.8536/1.1589)	mem 16099MB
[2025-01-18 11:55:38 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][240/312]	eta 0:00:34 lr 0.000044	time 0.4523 (0.4739)	model_time 0.4521 (0.4676)	loss 2.1422 (2.6456)	grad_norm 7.0733 (2.8695/1.1767)	mem 16099MB
[2025-01-18 11:55:43 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][250/312]	eta 0:00:29 lr 0.000044	time 0.4434 (0.4738)	model_time 0.4429 (0.4677)	loss 1.7707 (2.6447)	grad_norm 1.8154 (2.8466/1.1613)	mem 16099MB
[2025-01-18 11:55:47 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][260/312]	eta 0:00:24 lr 0.000044	time 0.4563 (0.4734)	model_time 0.4558 (0.4675)	loss 2.9062 (2.6442)	grad_norm 2.8906 (2.8410/1.1645)	mem 16099MB
[2025-01-18 11:55:52 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][270/312]	eta 0:00:19 lr 0.000044	time 0.4494 (0.4725)	model_time 0.4489 (0.4669)	loss 2.9013 (2.6465)	grad_norm 2.1991 (2.8086/1.1611)	mem 16099MB
[2025-01-18 11:55:56 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][280/312]	eta 0:00:15 lr 0.000044	time 0.4686 (0.4722)	model_time 0.4682 (0.4668)	loss 2.5780 (2.6420)	grad_norm 3.4161 (2.8138/1.1527)	mem 16099MB
[2025-01-18 11:56:01 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][290/312]	eta 0:00:10 lr 0.000044	time 0.4497 (0.4732)	model_time 0.4495 (0.4679)	loss 2.5302 (2.6444)	grad_norm 3.7789 (2.8471/1.1616)	mem 16099MB
[2025-01-18 11:56:06 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][300/312]	eta 0:00:05 lr 0.000044	time 0.4499 (0.4724)	model_time 0.4498 (0.4673)	loss 2.2326 (2.6465)	grad_norm 5.2207 (2.8991/1.2048)	mem 16099MB
[2025-01-18 11:56:11 internimage_t_1k_224] (main.py 510): INFO Train: [293/300][310/312]	eta 0:00:00 lr 0.000044	time 0.4376 (0.4719)	model_time 0.4376 (0.4669)	loss 2.5447 (2.6395)	grad_norm 5.1181 (2.9221/1.2181)	mem 16099MB
[2025-01-18 11:56:11 internimage_t_1k_224] (main.py 519): INFO EPOCH 293 training takes 0:02:27
[2025-01-18 11:56:11 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_293.pth saving......
[2025-01-18 11:56:12 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_293.pth saved !!!
[2025-01-18 11:56:20 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.534 (7.534)	Loss 0.7231 (0.7231)	Acc@1 85.425 (85.425)	Acc@5 97.461 (97.461)	Mem 16099MB
[2025-01-18 11:56:24 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.037)	Loss 0.9674 (0.8203)	Acc@1 79.126 (83.256)	Acc@5 95.093 (96.384)	Mem 16099MB
[2025-01-18 11:56:24 internimage_t_1k_224] (main.py 575): INFO [Epoch:293] * Acc@1 83.101 Acc@5 96.393
[2025-01-18 11:56:24 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:56:24 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 11:56:33 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.665 (8.665)	Loss 0.7120 (0.7120)	Acc@1 85.913 (85.913)	Acc@5 97.656 (97.656)	Mem 16099MB
[2025-01-18 11:56:37 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.162)	Loss 0.9421 (0.8102)	Acc@1 79.810 (83.722)	Acc@5 95.435 (96.560)	Mem 16099MB
[2025-01-18 11:56:37 internimage_t_1k_224] (main.py 575): INFO [Epoch:293] * Acc@1 83.563 Acc@5 96.569
[2025-01-18 11:56:37 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.6%
[2025-01-18 11:56:37 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.57%
[2025-01-18 11:56:40 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][0/312]	eta 0:16:45 lr 0.000044	time 3.2242 (3.2242)	model_time 1.7669 (1.7669)	loss 2.7735 (2.7735)	grad_norm 1.7880 (1.7880/0.0000)	mem 16099MB
[2025-01-18 11:56:45 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][10/312]	eta 0:03:41 lr 0.000044	time 0.4479 (0.7327)	model_time 0.4477 (0.5999)	loss 2.4510 (2.6264)	grad_norm 2.2265 (2.8864/1.0782)	mem 16099MB
[2025-01-18 11:56:49 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][20/312]	eta 0:02:55 lr 0.000044	time 0.4615 (0.6019)	model_time 0.4613 (0.5322)	loss 2.8634 (2.5114)	grad_norm 1.7759 (2.7772/0.9790)	mem 16099MB
[2025-01-18 11:56:54 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][30/312]	eta 0:02:38 lr 0.000044	time 0.4414 (0.5616)	model_time 0.4412 (0.5142)	loss 3.2087 (2.5638)	grad_norm 4.3464 (2.8689/1.0630)	mem 16099MB
[2025-01-18 11:56:59 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][40/312]	eta 0:02:26 lr 0.000044	time 0.4547 (0.5368)	model_time 0.4542 (0.5009)	loss 2.4065 (2.5401)	grad_norm 2.4147 (2.9275/1.0474)	mem 16099MB
[2025-01-18 11:57:03 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][50/312]	eta 0:02:16 lr 0.000044	time 0.4651 (0.5226)	model_time 0.4649 (0.4936)	loss 2.7732 (2.5355)	grad_norm 2.0324 (2.8306/1.0166)	mem 16099MB
[2025-01-18 11:57:08 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][60/312]	eta 0:02:09 lr 0.000044	time 0.5371 (0.5157)	model_time 0.5366 (0.4915)	loss 2.8350 (2.5450)	grad_norm 1.5951 (2.7930/1.0220)	mem 16099MB
[2025-01-18 11:57:13 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][70/312]	eta 0:02:02 lr 0.000044	time 0.4628 (0.5081)	model_time 0.4626 (0.4872)	loss 1.7295 (2.5475)	grad_norm 3.9334 (2.7440/0.9856)	mem 16099MB
[2025-01-18 11:57:18 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][80/312]	eta 0:01:56 lr 0.000044	time 0.4471 (0.5041)	model_time 0.4469 (0.4858)	loss 3.0125 (2.5430)	grad_norm 2.6445 (2.7581/0.9706)	mem 16099MB
[2025-01-18 11:57:22 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][90/312]	eta 0:01:50 lr 0.000044	time 0.4494 (0.4985)	model_time 0.4492 (0.4822)	loss 2.2479 (2.5459)	grad_norm 1.7895 (2.7317/0.9801)	mem 16099MB
[2025-01-18 11:57:27 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][100/312]	eta 0:01:44 lr 0.000044	time 0.4474 (0.4944)	model_time 0.4469 (0.4796)	loss 2.5742 (2.5452)	grad_norm 2.3998 (2.7387/0.9896)	mem 16099MB
[2025-01-18 11:57:31 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][110/312]	eta 0:01:39 lr 0.000043	time 0.4500 (0.4910)	model_time 0.4498 (0.4775)	loss 2.6400 (2.5510)	grad_norm 1.8435 (2.7036/0.9681)	mem 16099MB
[2025-01-18 11:57:36 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][120/312]	eta 0:01:33 lr 0.000043	time 0.4525 (0.4891)	model_time 0.4524 (0.4767)	loss 2.5145 (2.5398)	grad_norm 1.5300 (2.6614/0.9642)	mem 16099MB
[2025-01-18 11:57:41 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][130/312]	eta 0:01:29 lr 0.000043	time 0.4637 (0.4892)	model_time 0.4634 (0.4777)	loss 1.7739 (2.5270)	grad_norm 3.7195 (2.6764/0.9875)	mem 16099MB
[2025-01-18 11:57:46 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][140/312]	eta 0:01:24 lr 0.000043	time 0.4410 (0.4895)	model_time 0.4406 (0.4788)	loss 2.3459 (2.5247)	grad_norm 2.0372 (2.6626/0.9725)	mem 16099MB
[2025-01-18 11:57:50 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][150/312]	eta 0:01:19 lr 0.000043	time 0.4655 (0.4877)	model_time 0.4653 (0.4777)	loss 2.9069 (2.5231)	grad_norm 4.1153 (2.6396/0.9645)	mem 16099MB
[2025-01-18 11:57:55 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][160/312]	eta 0:01:13 lr 0.000043	time 0.4655 (0.4861)	model_time 0.4650 (0.4767)	loss 2.4612 (2.5277)	grad_norm 1.9188 (2.7100/1.1176)	mem 16099MB
[2025-01-18 11:58:00 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][170/312]	eta 0:01:08 lr 0.000043	time 0.4491 (0.4857)	model_time 0.4487 (0.4769)	loss 2.8299 (2.5342)	grad_norm 1.4906 (2.7083/1.1388)	mem 16099MB
[2025-01-18 11:58:04 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][180/312]	eta 0:01:03 lr 0.000043	time 0.4570 (0.4843)	model_time 0.4565 (0.4759)	loss 2.0845 (2.5329)	grad_norm 2.2478 (2.7616/1.1844)	mem 16099MB
[2025-01-18 11:58:09 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][190/312]	eta 0:00:59 lr 0.000043	time 0.4385 (0.4838)	model_time 0.4383 (0.4758)	loss 2.8667 (2.5339)	grad_norm 4.5323 (2.7522/1.1753)	mem 16099MB
[2025-01-18 11:58:14 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][200/312]	eta 0:00:54 lr 0.000043	time 0.4542 (0.4824)	model_time 0.4541 (0.4748)	loss 1.9502 (2.5324)	grad_norm 2.6031 (2.7533/1.1607)	mem 16099MB
[2025-01-18 11:58:19 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][210/312]	eta 0:00:49 lr 0.000043	time 0.4394 (0.4819)	model_time 0.4391 (0.4747)	loss 2.4309 (2.5413)	grad_norm 2.7199 (2.7447/1.1457)	mem 16099MB
[2025-01-18 11:58:23 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][220/312]	eta 0:00:44 lr 0.000043	time 0.4497 (0.4806)	model_time 0.4495 (0.4737)	loss 2.6308 (2.5474)	grad_norm 1.6739 (2.7405/1.1361)	mem 16099MB
[2025-01-18 11:58:28 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][230/312]	eta 0:00:39 lr 0.000043	time 0.4439 (0.4807)	model_time 0.4437 (0.4740)	loss 3.2037 (2.5525)	grad_norm 2.3949 (2.7712/1.1776)	mem 16099MB
[2025-01-18 11:58:33 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][240/312]	eta 0:00:34 lr 0.000043	time 0.4482 (0.4815)	model_time 0.4479 (0.4751)	loss 2.2965 (2.5580)	grad_norm 4.5154 (2.7878/1.1949)	mem 16099MB
[2025-01-18 11:58:38 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][250/312]	eta 0:00:29 lr 0.000043	time 0.4424 (0.4814)	model_time 0.4422 (0.4752)	loss 2.9184 (2.5576)	grad_norm 2.7599 (2.7835/1.1797)	mem 16099MB
[2025-01-18 11:58:42 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][260/312]	eta 0:00:24 lr 0.000043	time 0.4553 (0.4807)	model_time 0.4549 (0.4747)	loss 2.5560 (2.5647)	grad_norm 2.6314 (2.7808/1.1639)	mem 16099MB
[2025-01-18 11:58:47 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][270/312]	eta 0:00:20 lr 0.000043	time 0.4624 (0.4797)	model_time 0.4622 (0.4740)	loss 2.8529 (2.5659)	grad_norm 1.8151 (2.7818/1.1599)	mem 16099MB
[2025-01-18 11:58:51 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][280/312]	eta 0:00:15 lr 0.000043	time 0.4429 (0.4787)	model_time 0.4424 (0.4732)	loss 3.0138 (2.5720)	grad_norm 3.3124 (2.7659/1.1582)	mem 16099MB
[2025-01-18 11:58:56 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][290/312]	eta 0:00:10 lr 0.000043	time 0.4435 (0.4781)	model_time 0.4430 (0.4727)	loss 2.3846 (2.5772)	grad_norm 2.0264 (2.7706/1.1557)	mem 16099MB
[2025-01-18 11:59:01 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][300/312]	eta 0:00:05 lr 0.000043	time 0.4398 (0.4780)	model_time 0.4397 (0.4728)	loss 2.0240 (2.5679)	grad_norm 1.5715 (2.7739/1.1486)	mem 16099MB
[2025-01-18 11:59:05 internimage_t_1k_224] (main.py 510): INFO Train: [294/300][310/312]	eta 0:00:00 lr 0.000043	time 0.4387 (0.4772)	model_time 0.4386 (0.4721)	loss 2.7782 (2.5663)	grad_norm 2.5696 (2.7550/1.1395)	mem 16099MB
[2025-01-18 11:59:06 internimage_t_1k_224] (main.py 519): INFO EPOCH 294 training takes 0:02:28
[2025-01-18 11:59:06 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_294.pth saving......
[2025-01-18 11:59:07 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_294.pth saved !!!
[2025-01-18 11:59:15 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.890 (7.890)	Loss 0.7193 (0.7193)	Acc@1 85.498 (85.498)	Acc@5 97.559 (97.559)	Mem 16099MB
[2025-01-18 11:59:19 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.066)	Loss 0.9556 (0.8153)	Acc@1 79.468 (83.279)	Acc@5 95.312 (96.338)	Mem 16099MB
[2025-01-18 11:59:19 internimage_t_1k_224] (main.py 575): INFO [Epoch:294] * Acc@1 83.107 Acc@5 96.339
[2025-01-18 11:59:19 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 11:59:19 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 11:59:27 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.401 (8.401)	Loss 0.7120 (0.7120)	Acc@1 85.913 (85.913)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 11:59:31 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.138)	Loss 0.9422 (0.8102)	Acc@1 79.810 (83.700)	Acc@5 95.410 (96.551)	Mem 16099MB
[2025-01-18 11:59:31 internimage_t_1k_224] (main.py 575): INFO [Epoch:294] * Acc@1 83.539 Acc@5 96.559
[2025-01-18 11:59:31 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 11:59:31 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.57%
[2025-01-18 11:59:34 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][0/312]	eta 0:14:59 lr 0.000043	time 2.8834 (2.8834)	model_time 1.4526 (1.4526)	loss 2.9194 (2.9194)	grad_norm 2.1253 (2.1253/0.0000)	mem 16099MB
[2025-01-18 11:59:39 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][10/312]	eta 0:03:36 lr 0.000043	time 0.4670 (0.7180)	model_time 0.4666 (0.5876)	loss 2.2769 (2.5944)	grad_norm 2.6429 (2.3780/1.0368)	mem 16099MB
[2025-01-18 11:59:44 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][20/312]	eta 0:02:53 lr 0.000043	time 0.4600 (0.5949)	model_time 0.4596 (0.5265)	loss 2.7776 (2.5793)	grad_norm 2.0817 (2.4830/0.9848)	mem 16099MB
[2025-01-18 11:59:48 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][30/312]	eta 0:02:35 lr 0.000043	time 0.4749 (0.5512)	model_time 0.4747 (0.5048)	loss 2.8343 (2.5997)	grad_norm 1.3161 (2.4694/1.0176)	mem 16099MB
[2025-01-18 11:59:53 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][40/312]	eta 0:02:23 lr 0.000043	time 0.4549 (0.5290)	model_time 0.4545 (0.4938)	loss 2.3522 (2.5960)	grad_norm 3.8224 (2.5861/1.0315)	mem 16099MB
[2025-01-18 11:59:58 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][50/312]	eta 0:02:14 lr 0.000043	time 0.4506 (0.5147)	model_time 0.4502 (0.4863)	loss 2.0812 (2.6031)	grad_norm 3.0017 (2.5682/0.9962)	mem 16099MB
[2025-01-18 12:00:02 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][60/312]	eta 0:02:07 lr 0.000043	time 0.4483 (0.5050)	model_time 0.4482 (0.4812)	loss 2.8745 (2.5873)	grad_norm 4.2235 (2.6488/0.9744)	mem 16099MB
[2025-01-18 12:00:07 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][70/312]	eta 0:02:01 lr 0.000042	time 0.4544 (0.5034)	model_time 0.4542 (0.4829)	loss 1.7388 (2.5720)	grad_norm 2.4835 (2.6562/0.9872)	mem 16099MB
[2025-01-18 12:00:12 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][80/312]	eta 0:01:55 lr 0.000042	time 0.4670 (0.4984)	model_time 0.4665 (0.4804)	loss 2.9000 (2.5746)	grad_norm 3.9763 (2.7503/1.0980)	mem 16099MB
[2025-01-18 12:00:16 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][90/312]	eta 0:01:49 lr 0.000042	time 0.4639 (0.4947)	model_time 0.4637 (0.4787)	loss 3.1562 (2.5846)	grad_norm 3.6612 (2.7910/1.1426)	mem 16099MB
[2025-01-18 12:00:21 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][100/312]	eta 0:01:44 lr 0.000042	time 0.4532 (0.4915)	model_time 0.4531 (0.4770)	loss 2.4739 (2.5950)	grad_norm 3.6332 (2.8372/1.1908)	mem 16099MB
[2025-01-18 12:00:26 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][110/312]	eta 0:01:38 lr 0.000042	time 0.4480 (0.4894)	model_time 0.4476 (0.4762)	loss 3.1297 (2.5999)	grad_norm 3.5310 (2.8891/1.1867)	mem 16099MB
[2025-01-18 12:00:30 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][120/312]	eta 0:01:33 lr 0.000042	time 0.4526 (0.4871)	model_time 0.4524 (0.4750)	loss 1.9363 (2.6082)	grad_norm 2.5976 (2.9172/1.1974)	mem 16099MB
[2025-01-18 12:00:35 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][130/312]	eta 0:01:28 lr 0.000042	time 0.4569 (0.4869)	model_time 0.4565 (0.4756)	loss 2.4928 (2.6248)	grad_norm 3.7609 (2.8934/1.1812)	mem 16099MB
[2025-01-18 12:00:40 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][140/312]	eta 0:01:23 lr 0.000042	time 0.5503 (0.4871)	model_time 0.5502 (0.4766)	loss 2.4650 (2.6219)	grad_norm 2.6663 (2.9499/1.2178)	mem 16099MB
[2025-01-18 12:00:45 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][150/312]	eta 0:01:18 lr 0.000042	time 0.5596 (0.4858)	model_time 0.5595 (0.4760)	loss 2.5337 (2.6208)	grad_norm 3.1915 (2.9609/1.2072)	mem 16099MB
[2025-01-18 12:00:49 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][160/312]	eta 0:01:13 lr 0.000042	time 0.4897 (0.4840)	model_time 0.4895 (0.4748)	loss 2.5806 (2.6280)	grad_norm 1.8887 (2.9673/1.1948)	mem 16099MB
[2025-01-18 12:00:54 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][170/312]	eta 0:01:08 lr 0.000042	time 0.4494 (0.4831)	model_time 0.4493 (0.4744)	loss 2.5894 (2.6354)	grad_norm 3.9430 (3.0150/1.2447)	mem 16099MB
[2025-01-18 12:00:59 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][180/312]	eta 0:01:03 lr 0.000042	time 0.4476 (0.4821)	model_time 0.4472 (0.4738)	loss 3.0036 (2.6397)	grad_norm 3.9588 (3.0158/1.2428)	mem 16099MB
[2025-01-18 12:01:03 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][190/312]	eta 0:00:58 lr 0.000042	time 0.4586 (0.4805)	model_time 0.4580 (0.4727)	loss 2.1360 (2.6423)	grad_norm 3.6383 (3.0399/1.2587)	mem 16099MB
[2025-01-18 12:01:08 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][200/312]	eta 0:00:53 lr 0.000042	time 0.5447 (0.4796)	model_time 0.5442 (0.4722)	loss 2.3189 (2.6478)	grad_norm 3.1303 (3.0832/1.2730)	mem 16099MB
[2025-01-18 12:01:12 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][210/312]	eta 0:00:48 lr 0.000042	time 0.4521 (0.4788)	model_time 0.4520 (0.4716)	loss 1.7891 (2.6448)	grad_norm 1.7756 (3.0719/1.2831)	mem 16099MB
[2025-01-18 12:01:17 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][220/312]	eta 0:00:43 lr 0.000042	time 0.4522 (0.4777)	model_time 0.4520 (0.4709)	loss 3.1463 (2.6453)	grad_norm 2.3438 (3.0580/1.2730)	mem 16099MB
[2025-01-18 12:01:22 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][230/312]	eta 0:00:39 lr 0.000042	time 0.7477 (0.4781)	model_time 0.7473 (0.4716)	loss 2.9833 (2.6520)	grad_norm 3.0507 (3.0509/1.2667)	mem 16099MB
[2025-01-18 12:01:27 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][240/312]	eta 0:00:34 lr 0.000042	time 0.4608 (0.4779)	model_time 0.4606 (0.4717)	loss 2.1909 (2.6500)	grad_norm 2.8150 (3.0466/1.2644)	mem 16099MB
[2025-01-18 12:01:31 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][250/312]	eta 0:00:29 lr 0.000042	time 0.4548 (0.4770)	model_time 0.4546 (0.4710)	loss 2.9942 (2.6379)	grad_norm 3.7118 (3.0502/1.2535)	mem 16099MB
[2025-01-18 12:01:36 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][260/312]	eta 0:00:24 lr 0.000042	time 0.4451 (0.4768)	model_time 0.4450 (0.4710)	loss 2.7242 (2.6305)	grad_norm 5.9441 (3.0988/1.3418)	mem 16099MB
[2025-01-18 12:01:40 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][270/312]	eta 0:00:20 lr 0.000042	time 0.4512 (0.4763)	model_time 0.4511 (0.4707)	loss 2.8779 (2.6325)	grad_norm 2.2551 (3.1023/1.3379)	mem 16099MB
[2025-01-18 12:01:45 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][280/312]	eta 0:00:15 lr 0.000042	time 0.4568 (0.4760)	model_time 0.4566 (0.4706)	loss 3.3580 (2.6400)	grad_norm 2.8071 (3.0998/1.3273)	mem 16099MB
[2025-01-18 12:01:50 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][290/312]	eta 0:00:10 lr 0.000042	time 0.4502 (0.4756)	model_time 0.4500 (0.4704)	loss 2.6260 (2.6357)	grad_norm 3.5698 (3.1032/1.3116)	mem 16099MB
[2025-01-18 12:01:54 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][300/312]	eta 0:00:05 lr 0.000042	time 0.4369 (0.4751)	model_time 0.4367 (0.4700)	loss 2.6954 (2.6377)	grad_norm 2.7747 (3.1028/1.2963)	mem 16099MB
[2025-01-18 12:01:59 internimage_t_1k_224] (main.py 510): INFO Train: [295/300][310/312]	eta 0:00:00 lr 0.000042	time 0.4398 (0.4749)	model_time 0.4397 (0.4700)	loss 3.0611 (2.6405)	grad_norm 1.6449 (3.1055/1.2859)	mem 16099MB
[2025-01-18 12:02:00 internimage_t_1k_224] (main.py 519): INFO EPOCH 295 training takes 0:02:28
[2025-01-18 12:02:00 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_295.pth saving......
[2025-01-18 12:02:01 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_295.pth saved !!!
[2025-01-18 12:02:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.399 (7.399)	Loss 0.7274 (0.7274)	Acc@1 85.132 (85.132)	Acc@5 97.363 (97.363)	Mem 16099MB
[2025-01-18 12:02:12 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.006)	Loss 0.9693 (0.8236)	Acc@1 79.004 (83.210)	Acc@5 95.142 (96.325)	Mem 16099MB
[2025-01-18 12:02:12 internimage_t_1k_224] (main.py 575): INFO [Epoch:295] * Acc@1 83.041 Acc@5 96.317
[2025-01-18 12:02:12 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.0%
[2025-01-18 12:02:12 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 12:02:20 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.423 (8.423)	Loss 0.7118 (0.7118)	Acc@1 85.864 (85.864)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 12:02:24 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.122)	Loss 0.9420 (0.8099)	Acc@1 79.810 (83.698)	Acc@5 95.361 (96.547)	Mem 16099MB
[2025-01-18 12:02:24 internimage_t_1k_224] (main.py 575): INFO [Epoch:295] * Acc@1 83.541 Acc@5 96.555
[2025-01-18 12:02:24 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 12:02:24 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.57%
[2025-01-18 12:02:28 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][0/312]	eta 0:18:02 lr 0.000042	time 3.4689 (3.4689)	model_time 1.5842 (1.5842)	loss 2.0333 (2.0333)	grad_norm 4.4011 (4.4011/0.0000)	mem 16099MB
[2025-01-18 12:02:33 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][10/312]	eta 0:03:49 lr 0.000042	time 0.4538 (0.7586)	model_time 0.4537 (0.5870)	loss 2.3498 (2.6414)	grad_norm 6.3050 (3.2877/1.4102)	mem 16099MB
[2025-01-18 12:02:37 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][20/312]	eta 0:03:00 lr 0.000042	time 0.5233 (0.6171)	model_time 0.5232 (0.5270)	loss 1.6764 (2.4821)	grad_norm 2.1820 (3.0536/1.2366)	mem 16099MB
[2025-01-18 12:02:42 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][30/312]	eta 0:02:39 lr 0.000042	time 0.4515 (0.5668)	model_time 0.4514 (0.5057)	loss 1.9360 (2.5452)	grad_norm 3.3754 (2.9317/1.0646)	mem 16099MB
[2025-01-18 12:02:47 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][40/312]	eta 0:02:27 lr 0.000042	time 0.4569 (0.5413)	model_time 0.4567 (0.4950)	loss 2.9184 (2.5668)	grad_norm 2.3312 (3.2152/1.2988)	mem 16099MB
[2025-01-18 12:02:51 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][50/312]	eta 0:02:18 lr 0.000042	time 0.4608 (0.5284)	model_time 0.4604 (0.4911)	loss 2.9103 (2.5761)	grad_norm 2.8803 (3.4238/1.4097)	mem 16099MB
[2025-01-18 12:02:56 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][60/312]	eta 0:02:10 lr 0.000042	time 0.4553 (0.5173)	model_time 0.4551 (0.4860)	loss 1.8685 (2.5865)	grad_norm 2.4279 (3.4191/1.3484)	mem 16099MB
[2025-01-18 12:03:01 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][70/312]	eta 0:02:03 lr 0.000042	time 0.4403 (0.5087)	model_time 0.4401 (0.4818)	loss 2.7445 (2.5408)	grad_norm 2.8348 (3.4167/1.4241)	mem 16099MB
[2025-01-18 12:03:05 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][80/312]	eta 0:01:56 lr 0.000042	time 0.4488 (0.5040)	model_time 0.4484 (0.4803)	loss 1.9299 (2.5385)	grad_norm 2.0164 (3.2550/1.4163)	mem 16099MB
[2025-01-18 12:03:10 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][90/312]	eta 0:01:51 lr 0.000041	time 0.4398 (0.5007)	model_time 0.4396 (0.4796)	loss 3.2645 (2.5492)	grad_norm 2.5635 (3.2460/1.4108)	mem 16099MB
[2025-01-18 12:03:14 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][100/312]	eta 0:01:45 lr 0.000041	time 0.4565 (0.4958)	model_time 0.4563 (0.4768)	loss 3.2378 (2.5640)	grad_norm 2.5742 (3.2363/1.3803)	mem 16099MB
[2025-01-18 12:03:19 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][110/312]	eta 0:01:39 lr 0.000041	time 0.4487 (0.4950)	model_time 0.4485 (0.4777)	loss 3.0134 (2.6005)	grad_norm 3.6038 (3.2324/1.3333)	mem 16099MB
[2025-01-18 12:03:24 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][120/312]	eta 0:01:34 lr 0.000041	time 0.5584 (0.4926)	model_time 0.5579 (0.4767)	loss 3.2467 (2.5921)	grad_norm 3.7188 (3.2305/1.3855)	mem 16099MB
[2025-01-18 12:03:29 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][130/312]	eta 0:01:29 lr 0.000041	time 0.4568 (0.4908)	model_time 0.4566 (0.4760)	loss 2.8248 (2.5817)	grad_norm 1.8412 (3.1787/1.3770)	mem 16099MB
[2025-01-18 12:03:33 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][140/312]	eta 0:01:24 lr 0.000041	time 0.4462 (0.4898)	model_time 0.4461 (0.4761)	loss 2.7082 (2.5768)	grad_norm 4.8307 (3.2062/1.3852)	mem 16099MB
[2025-01-18 12:03:38 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][150/312]	eta 0:01:19 lr 0.000041	time 0.4594 (0.4893)	model_time 0.4590 (0.4764)	loss 2.3256 (2.5793)	grad_norm 2.4342 (3.1553/1.3657)	mem 16099MB
[2025-01-18 12:03:43 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][160/312]	eta 0:01:14 lr 0.000041	time 0.4452 (0.4876)	model_time 0.4451 (0.4755)	loss 2.7753 (2.5838)	grad_norm 5.2731 (3.1466/1.3474)	mem 16099MB
[2025-01-18 12:03:48 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][170/312]	eta 0:01:09 lr 0.000041	time 0.4403 (0.4865)	model_time 0.4402 (0.4751)	loss 1.9499 (2.5822)	grad_norm 4.3705 (3.1070/1.3420)	mem 16099MB
[2025-01-18 12:03:52 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][180/312]	eta 0:01:03 lr 0.000041	time 0.4507 (0.4847)	model_time 0.4503 (0.4740)	loss 2.5285 (2.5838)	grad_norm 2.2865 (3.0763/1.3264)	mem 16099MB
[2025-01-18 12:03:57 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][190/312]	eta 0:00:58 lr 0.000041	time 0.4507 (0.4832)	model_time 0.4502 (0.4730)	loss 2.5989 (2.5767)	grad_norm 3.8769 (3.0599/1.3032)	mem 16099MB
[2025-01-18 12:04:01 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][200/312]	eta 0:00:53 lr 0.000041	time 0.4460 (0.4818)	model_time 0.4456 (0.4720)	loss 2.6432 (2.5835)	grad_norm 5.0763 (3.0952/1.3100)	mem 16099MB
[2025-01-18 12:04:06 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][210/312]	eta 0:00:49 lr 0.000041	time 0.4588 (0.4805)	model_time 0.4587 (0.4712)	loss 2.8066 (2.5898)	grad_norm 4.2041 (3.0986/1.3009)	mem 16099MB
[2025-01-18 12:04:11 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][220/312]	eta 0:00:44 lr 0.000041	time 0.4502 (0.4808)	model_time 0.4498 (0.4719)	loss 1.8148 (2.5896)	grad_norm 5.0331 (3.1253/1.3003)	mem 16099MB
[2025-01-18 12:04:16 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][230/312]	eta 0:00:39 lr 0.000041	time 0.4569 (0.4810)	model_time 0.4565 (0.4725)	loss 2.3961 (2.5925)	grad_norm 2.7285 (3.1095/1.2825)	mem 16099MB
[2025-01-18 12:04:20 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][240/312]	eta 0:00:34 lr 0.000041	time 0.4536 (0.4797)	model_time 0.4532 (0.4716)	loss 3.0481 (2.5888)	grad_norm 3.1728 (3.0977/1.2790)	mem 16099MB
[2025-01-18 12:04:25 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][250/312]	eta 0:00:29 lr 0.000041	time 0.4927 (0.4793)	model_time 0.4926 (0.4715)	loss 2.2791 (2.5748)	grad_norm 1.6351 (3.1405/1.3191)	mem 16099MB
[2025-01-18 12:04:29 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][260/312]	eta 0:00:24 lr 0.000041	time 0.4556 (0.4787)	model_time 0.4552 (0.4711)	loss 2.3326 (2.5756)	grad_norm 2.8833 (3.1317/1.3110)	mem 16099MB
[2025-01-18 12:04:34 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][270/312]	eta 0:00:20 lr 0.000041	time 0.4555 (0.4782)	model_time 0.4554 (0.4709)	loss 2.6191 (2.5832)	grad_norm 4.9001 (3.1512/1.3193)	mem 16099MB
[2025-01-18 12:04:39 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][280/312]	eta 0:00:15 lr 0.000041	time 0.4480 (0.4802)	model_time 0.4479 (0.4731)	loss 2.7806 (2.5844)	grad_norm 1.7175 (3.1490/1.3133)	mem 16099MB
[2025-01-18 12:04:44 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][290/312]	eta 0:00:10 lr 0.000041	time 0.4529 (0.4796)	model_time 0.4525 (0.4727)	loss 2.8986 (2.5929)	grad_norm 3.1556 (3.1768/1.3547)	mem 16099MB
[2025-01-18 12:04:48 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][300/312]	eta 0:00:05 lr 0.000041	time 0.4381 (0.4786)	model_time 0.4380 (0.4719)	loss 2.3662 (2.5917)	grad_norm 2.0730 (3.1799/1.3503)	mem 16099MB
[2025-01-18 12:04:53 internimage_t_1k_224] (main.py 510): INFO Train: [296/300][310/312]	eta 0:00:00 lr 0.000041	time 0.4416 (0.4777)	model_time 0.4415 (0.4713)	loss 3.1588 (2.5947)	grad_norm 2.0756 (3.1545/1.3383)	mem 16099MB
[2025-01-18 12:04:53 internimage_t_1k_224] (main.py 519): INFO EPOCH 296 training takes 0:02:29
[2025-01-18 12:04:53 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_296.pth saving......
[2025-01-18 12:04:54 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_296.pth saved !!!
[2025-01-18 12:05:02 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.460 (7.460)	Loss 0.7184 (0.7184)	Acc@1 85.132 (85.132)	Acc@5 97.412 (97.412)	Mem 16099MB
[2025-01-18 12:05:06 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.013)	Loss 0.9614 (0.8154)	Acc@1 78.955 (83.259)	Acc@5 95.117 (96.347)	Mem 16099MB
[2025-01-18 12:05:06 internimage_t_1k_224] (main.py 575): INFO [Epoch:296] * Acc@1 83.127 Acc@5 96.361
[2025-01-18 12:05:06 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 12:05:06 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.13%
[2025-01-18 12:05:14 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.242 (8.242)	Loss 0.7115 (0.7115)	Acc@1 85.815 (85.815)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 12:05:18 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.109)	Loss 0.9419 (0.8095)	Acc@1 79.810 (83.683)	Acc@5 95.386 (96.551)	Mem 16099MB
[2025-01-18 12:05:18 internimage_t_1k_224] (main.py 575): INFO [Epoch:296] * Acc@1 83.527 Acc@5 96.559
[2025-01-18 12:05:18 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 12:05:18 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.57%
[2025-01-18 12:05:21 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][0/312]	eta 0:15:45 lr 0.000041	time 3.0303 (3.0303)	model_time 1.4995 (1.4995)	loss 3.0215 (3.0215)	grad_norm 2.7696 (2.7696/0.0000)	mem 16099MB
[2025-01-18 12:05:26 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][10/312]	eta 0:03:31 lr 0.000041	time 0.4530 (0.6989)	model_time 0.4526 (0.5593)	loss 2.6768 (2.8764)	grad_norm 4.2083 (2.7690/0.6025)	mem 16099MB
[2025-01-18 12:05:31 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][20/312]	eta 0:02:52 lr 0.000041	time 0.4528 (0.5899)	model_time 0.4526 (0.5166)	loss 2.0749 (2.6442)	grad_norm 4.2848 (2.9753/0.9132)	mem 16099MB
[2025-01-18 12:05:35 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][30/312]	eta 0:02:35 lr 0.000041	time 0.5551 (0.5524)	model_time 0.5547 (0.5027)	loss 2.4859 (2.6588)	grad_norm 2.9009 (3.3873/1.1611)	mem 16099MB
[2025-01-18 12:05:40 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][40/312]	eta 0:02:24 lr 0.000041	time 0.4517 (0.5319)	model_time 0.4515 (0.4942)	loss 2.6196 (2.6654)	grad_norm 8.6625 (3.6573/1.4715)	mem 16099MB
[2025-01-18 12:05:45 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][50/312]	eta 0:02:16 lr 0.000041	time 0.4542 (0.5201)	model_time 0.4538 (0.4897)	loss 2.7389 (2.6804)	grad_norm 8.2744 (3.7662/1.6211)	mem 16099MB
[2025-01-18 12:05:49 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][60/312]	eta 0:02:08 lr 0.000041	time 0.4552 (0.5107)	model_time 0.4550 (0.4853)	loss 2.8634 (2.6900)	grad_norm 2.1484 (3.6973/1.5562)	mem 16099MB
[2025-01-18 12:05:54 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][70/312]	eta 0:02:01 lr 0.000041	time 0.4401 (0.5034)	model_time 0.4397 (0.4815)	loss 2.9952 (2.6762)	grad_norm 3.1070 (3.6610/1.5240)	mem 16099MB
[2025-01-18 12:05:59 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][80/312]	eta 0:01:55 lr 0.000041	time 0.4577 (0.4991)	model_time 0.4575 (0.4798)	loss 2.9288 (2.6646)	grad_norm 2.3660 (3.5427/1.5337)	mem 16099MB
[2025-01-18 12:06:03 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][90/312]	eta 0:01:50 lr 0.000041	time 0.4571 (0.4971)	model_time 0.4566 (0.4799)	loss 3.2022 (2.6651)	grad_norm 2.1877 (3.5255/1.5199)	mem 16099MB
[2025-01-18 12:06:08 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][100/312]	eta 0:01:44 lr 0.000041	time 0.4444 (0.4941)	model_time 0.4439 (0.4786)	loss 2.7724 (2.6644)	grad_norm 1.6686 (3.4415/1.5206)	mem 16099MB
[2025-01-18 12:06:13 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][110/312]	eta 0:01:39 lr 0.000041	time 0.4471 (0.4921)	model_time 0.4466 (0.4779)	loss 1.7823 (2.6578)	grad_norm 4.5590 (3.4063/1.5073)	mem 16099MB
[2025-01-18 12:06:17 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][120/312]	eta 0:01:34 lr 0.000041	time 0.4420 (0.4901)	model_time 0.4415 (0.4771)	loss 1.8137 (2.6399)	grad_norm 1.9525 (3.3552/1.4858)	mem 16099MB
[2025-01-18 12:06:22 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][130/312]	eta 0:01:28 lr 0.000041	time 0.4772 (0.4883)	model_time 0.4770 (0.4762)	loss 1.6924 (2.6252)	grad_norm 1.2144 (3.3222/1.4660)	mem 16099MB
[2025-01-18 12:06:27 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][140/312]	eta 0:01:23 lr 0.000041	time 0.4525 (0.4861)	model_time 0.4524 (0.4749)	loss 2.6495 (2.6321)	grad_norm 3.6586 (3.2940/1.4338)	mem 16099MB
[2025-01-18 12:06:31 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][150/312]	eta 0:01:18 lr 0.000041	time 0.4501 (0.4851)	model_time 0.4497 (0.4746)	loss 2.2414 (2.6195)	grad_norm 2.3761 (3.2509/1.4248)	mem 16099MB
[2025-01-18 12:06:36 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][160/312]	eta 0:01:13 lr 0.000041	time 0.4932 (0.4840)	model_time 0.4928 (0.4742)	loss 1.9498 (2.6069)	grad_norm 3.6803 (3.2689/1.4110)	mem 16099MB
[2025-01-18 12:06:41 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][170/312]	eta 0:01:08 lr 0.000041	time 0.4842 (0.4824)	model_time 0.4838 (0.4731)	loss 2.7406 (2.6138)	grad_norm 2.5019 (3.2622/1.4061)	mem 16099MB
[2025-01-18 12:06:45 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][180/312]	eta 0:01:03 lr 0.000041	time 0.4470 (0.4814)	model_time 0.4468 (0.4726)	loss 3.3818 (2.6121)	grad_norm 2.5352 (3.2654/1.4013)	mem 16099MB
[2025-01-18 12:06:50 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][190/312]	eta 0:00:58 lr 0.000041	time 0.4563 (0.4802)	model_time 0.4559 (0.4718)	loss 2.9749 (2.6108)	grad_norm 1.6466 (3.2719/1.3985)	mem 16099MB
[2025-01-18 12:06:55 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][200/312]	eta 0:00:53 lr 0.000041	time 0.4731 (0.4795)	model_time 0.4726 (0.4715)	loss 2.6527 (2.6073)	grad_norm 3.4531 (3.2876/1.3974)	mem 16099MB
[2025-01-18 12:06:59 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][210/312]	eta 0:00:48 lr 0.000041	time 0.4661 (0.4788)	model_time 0.4657 (0.4712)	loss 3.3859 (2.6029)	grad_norm 4.5170 (3.2703/1.3874)	mem 16099MB
[2025-01-18 12:07:04 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][220/312]	eta 0:00:43 lr 0.000041	time 0.4508 (0.4775)	model_time 0.4507 (0.4702)	loss 2.7918 (2.5997)	grad_norm 1.7026 (3.2672/1.3721)	mem 16099MB
[2025-01-18 12:07:08 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][230/312]	eta 0:00:39 lr 0.000041	time 0.4474 (0.4768)	model_time 0.4473 (0.4698)	loss 2.7814 (2.6055)	grad_norm 4.4189 (3.2751/1.3456)	mem 16099MB
[2025-01-18 12:07:13 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][240/312]	eta 0:00:34 lr 0.000041	time 0.4595 (0.4764)	model_time 0.4591 (0.4697)	loss 2.9557 (2.6062)	grad_norm 5.1446 (3.2647/1.3408)	mem 16099MB
[2025-01-18 12:07:18 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][250/312]	eta 0:00:29 lr 0.000041	time 0.4609 (0.4759)	model_time 0.4608 (0.4695)	loss 2.8452 (2.6041)	grad_norm 6.4406 (3.2599/1.3491)	mem 16099MB
[2025-01-18 12:07:22 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][260/312]	eta 0:00:24 lr 0.000041	time 0.4565 (0.4756)	model_time 0.4563 (0.4693)	loss 2.6569 (2.6127)	grad_norm 3.0299 (3.2396/1.3560)	mem 16099MB
[2025-01-18 12:07:27 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][270/312]	eta 0:00:19 lr 0.000040	time 0.5749 (0.4757)	model_time 0.5745 (0.4697)	loss 2.8950 (2.6104)	grad_norm 5.3045 (3.2163/1.3579)	mem 16099MB
[2025-01-18 12:07:32 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][280/312]	eta 0:00:15 lr 0.000040	time 0.4531 (0.4755)	model_time 0.4527 (0.4697)	loss 2.9841 (2.6212)	grad_norm 1.7215 (3.1847/1.3490)	mem 16099MB
[2025-01-18 12:07:37 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][290/312]	eta 0:00:10 lr 0.000040	time 0.4406 (0.4762)	model_time 0.4401 (0.4705)	loss 2.9652 (2.6282)	grad_norm 2.3853 (3.1764/1.3367)	mem 16099MB
[2025-01-18 12:07:41 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][300/312]	eta 0:00:05 lr 0.000040	time 0.4400 (0.4755)	model_time 0.4399 (0.4701)	loss 3.0755 (2.6387)	grad_norm 2.1180 (3.1610/1.3297)	mem 16099MB
[2025-01-18 12:07:46 internimage_t_1k_224] (main.py 510): INFO Train: [297/300][310/312]	eta 0:00:00 lr 0.000040	time 0.4388 (0.4746)	model_time 0.4387 (0.4693)	loss 2.8102 (2.6358)	grad_norm 6.0195 (3.1828/1.3380)	mem 16099MB
[2025-01-18 12:07:46 internimage_t_1k_224] (main.py 519): INFO EPOCH 297 training takes 0:02:28
[2025-01-18 12:07:46 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_297.pth saving......
[2025-01-18 12:07:47 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_297.pth saved !!!
[2025-01-18 12:07:55 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.827 (7.827)	Loss 0.7183 (0.7183)	Acc@1 85.254 (85.254)	Acc@5 97.388 (97.388)	Mem 16099MB
[2025-01-18 12:07:59 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.055)	Loss 0.9609 (0.8165)	Acc@1 79.199 (83.290)	Acc@5 94.971 (96.311)	Mem 16099MB
[2025-01-18 12:07:59 internimage_t_1k_224] (main.py 575): INFO [Epoch:297] * Acc@1 83.147 Acc@5 96.319
[2025-01-18 12:07:59 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 12:07:59 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saving......
[2025-01-18 12:08:00 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_best.pth saved !!!
[2025-01-18 12:08:00 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.15%
[2025-01-18 12:08:08 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.670 (7.670)	Loss 0.7115 (0.7115)	Acc@1 85.791 (85.791)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 12:08:12 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.047)	Loss 0.9419 (0.8094)	Acc@1 79.785 (83.658)	Acc@5 95.435 (96.544)	Mem 16099MB
[2025-01-18 12:08:12 internimage_t_1k_224] (main.py 575): INFO [Epoch:297] * Acc@1 83.503 Acc@5 96.557
[2025-01-18 12:08:12 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 12:08:12 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.57%
[2025-01-18 12:08:15 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][0/312]	eta 0:15:29 lr 0.000040	time 2.9806 (2.9806)	model_time 0.4747 (0.4747)	loss 2.8249 (2.8249)	grad_norm 5.9569 (5.9569/0.0000)	mem 16099MB
[2025-01-18 12:08:20 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][10/312]	eta 0:03:29 lr 0.000040	time 0.4550 (0.6953)	model_time 0.4549 (0.4673)	loss 2.6544 (2.7154)	grad_norm 2.5010 (3.5785/1.5818)	mem 16099MB
[2025-01-18 12:08:24 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][20/312]	eta 0:02:53 lr 0.000040	time 0.4512 (0.5956)	model_time 0.4511 (0.4760)	loss 2.1452 (2.6565)	grad_norm 2.2505 (3.0936/1.3713)	mem 16099MB
[2025-01-18 12:08:29 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][30/312]	eta 0:02:35 lr 0.000040	time 0.4524 (0.5516)	model_time 0.4519 (0.4704)	loss 2.5152 (2.6615)	grad_norm 3.9572 (3.1224/1.3841)	mem 16099MB
[2025-01-18 12:08:34 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][40/312]	eta 0:02:24 lr 0.000040	time 0.4523 (0.5316)	model_time 0.4521 (0.4701)	loss 3.1514 (2.7065)	grad_norm 2.9050 (2.9373/1.3153)	mem 16099MB
[2025-01-18 12:08:38 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][50/312]	eta 0:02:15 lr 0.000040	time 0.4498 (0.5183)	model_time 0.4493 (0.4689)	loss 1.8025 (2.7206)	grad_norm 3.0833 (3.0073/1.3312)	mem 16099MB
[2025-01-18 12:08:43 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][60/312]	eta 0:02:08 lr 0.000040	time 0.4434 (0.5113)	model_time 0.4432 (0.4699)	loss 2.5199 (2.6892)	grad_norm 3.3196 (2.9701/1.2897)	mem 16099MB
[2025-01-18 12:08:48 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][70/312]	eta 0:02:01 lr 0.000040	time 0.4478 (0.5033)	model_time 0.4477 (0.4677)	loss 3.0989 (2.6762)	grad_norm 2.4525 (2.9373/1.2314)	mem 16099MB
[2025-01-18 12:08:52 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][80/312]	eta 0:01:55 lr 0.000040	time 0.4531 (0.4979)	model_time 0.4529 (0.4667)	loss 2.6036 (2.6652)	grad_norm 2.0876 (2.9012/1.2227)	mem 16099MB
[2025-01-18 12:08:57 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][90/312]	eta 0:01:49 lr 0.000040	time 0.4630 (0.4944)	model_time 0.4626 (0.4665)	loss 1.5463 (2.6467)	grad_norm 4.0658 (2.8940/1.2034)	mem 16099MB
[2025-01-18 12:09:01 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][100/312]	eta 0:01:43 lr 0.000040	time 0.4557 (0.4905)	model_time 0.4555 (0.4654)	loss 2.0409 (2.6301)	grad_norm 1.7404 (2.9074/1.2258)	mem 16099MB
[2025-01-18 12:09:06 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][110/312]	eta 0:01:38 lr 0.000040	time 0.4544 (0.4879)	model_time 0.4540 (0.4650)	loss 3.0077 (2.6264)	grad_norm 2.0068 (2.8459/1.1994)	mem 16099MB
[2025-01-18 12:09:11 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][120/312]	eta 0:01:33 lr 0.000040	time 0.4540 (0.4852)	model_time 0.4538 (0.4642)	loss 3.0100 (2.6394)	grad_norm 2.0263 (2.8416/1.2043)	mem 16099MB
[2025-01-18 12:09:15 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][130/312]	eta 0:01:28 lr 0.000040	time 0.4809 (0.4837)	model_time 0.4805 (0.4642)	loss 2.8764 (2.6434)	grad_norm 2.7905 (2.8582/1.1903)	mem 16099MB
[2025-01-18 12:09:20 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][140/312]	eta 0:01:23 lr 0.000040	time 0.4626 (0.4832)	model_time 0.4621 (0.4651)	loss 1.8013 (2.6512)	grad_norm 1.8890 (2.7953/1.1735)	mem 16099MB
[2025-01-18 12:09:25 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][150/312]	eta 0:01:18 lr 0.000040	time 0.5371 (0.4817)	model_time 0.5366 (0.4648)	loss 2.7712 (2.6625)	grad_norm 3.5257 (2.8111/1.2178)	mem 16099MB
[2025-01-18 12:09:29 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][160/312]	eta 0:01:13 lr 0.000040	time 0.4669 (0.4814)	model_time 0.4668 (0.4654)	loss 2.8003 (2.6663)	grad_norm 4.3518 (2.8229/1.2214)	mem 16099MB
[2025-01-18 12:09:34 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][170/312]	eta 0:01:08 lr 0.000040	time 0.4433 (0.4799)	model_time 0.4432 (0.4649)	loss 2.8853 (2.6631)	grad_norm 3.0769 (2.8021/1.2033)	mem 16099MB
[2025-01-18 12:09:39 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][180/312]	eta 0:01:03 lr 0.000040	time 0.4438 (0.4791)	model_time 0.4434 (0.4648)	loss 2.5529 (2.6671)	grad_norm 1.9503 (2.8235/1.2060)	mem 16099MB
[2025-01-18 12:09:43 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][190/312]	eta 0:00:58 lr 0.000040	time 0.4410 (0.4780)	model_time 0.4408 (0.4645)	loss 2.2201 (2.6574)	grad_norm 2.5478 (2.8297/1.2075)	mem 16099MB
[2025-01-18 12:09:48 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][200/312]	eta 0:00:53 lr 0.000040	time 0.4522 (0.4771)	model_time 0.4517 (0.4643)	loss 3.0198 (2.6556)	grad_norm 3.0362 (2.8430/1.2256)	mem 16099MB
[2025-01-18 12:09:52 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][210/312]	eta 0:00:48 lr 0.000040	time 0.4605 (0.4764)	model_time 0.4600 (0.4641)	loss 2.4961 (2.6583)	grad_norm 3.7208 (2.8540/1.2170)	mem 16099MB
[2025-01-18 12:09:57 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][220/312]	eta 0:00:43 lr 0.000040	time 0.4507 (0.4757)	model_time 0.4505 (0.4640)	loss 3.2828 (2.6466)	grad_norm 3.6606 (2.8585/1.2122)	mem 16099MB
[2025-01-18 12:10:02 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][230/312]	eta 0:00:38 lr 0.000040	time 0.5311 (0.4755)	model_time 0.5307 (0.4642)	loss 2.8431 (2.6463)	grad_norm 1.2350 (2.8648/1.2094)	mem 16099MB
[2025-01-18 12:10:06 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][240/312]	eta 0:00:34 lr 0.000040	time 0.4560 (0.4751)	model_time 0.4558 (0.4643)	loss 2.8258 (2.6393)	grad_norm 1.6325 (2.8642/1.1974)	mem 16099MB
[2025-01-18 12:10:11 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][250/312]	eta 0:00:29 lr 0.000040	time 0.4421 (0.4746)	model_time 0.4419 (0.4643)	loss 1.6597 (2.6273)	grad_norm 4.1354 (2.8855/1.1991)	mem 16099MB
[2025-01-18 12:10:16 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][260/312]	eta 0:00:24 lr 0.000040	time 0.4585 (0.4752)	model_time 0.4584 (0.4652)	loss 1.7445 (2.6267)	grad_norm 1.7606 (2.8791/1.1902)	mem 16099MB
[2025-01-18 12:10:21 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][270/312]	eta 0:00:19 lr 0.000040	time 0.4455 (0.4749)	model_time 0.4451 (0.4653)	loss 1.8601 (2.6174)	grad_norm 3.9151 (2.8923/1.1960)	mem 16099MB
[2025-01-18 12:10:25 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][280/312]	eta 0:00:15 lr 0.000040	time 0.4506 (0.4746)	model_time 0.4502 (0.4653)	loss 3.2279 (2.6232)	grad_norm 2.4465 (2.9153/1.1970)	mem 16099MB
[2025-01-18 12:10:30 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][290/312]	eta 0:00:10 lr 0.000040	time 0.4558 (0.4747)	model_time 0.4554 (0.4657)	loss 1.8754 (2.6262)	grad_norm 4.0025 (2.9532/1.2743)	mem 16099MB
[2025-01-18 12:10:35 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][300/312]	eta 0:00:05 lr 0.000040	time 0.4386 (0.4742)	model_time 0.4385 (0.4655)	loss 3.0052 (2.6278)	grad_norm 2.3897 (2.9656/1.2787)	mem 16099MB
[2025-01-18 12:10:39 internimage_t_1k_224] (main.py 510): INFO Train: [298/300][310/312]	eta 0:00:00 lr 0.000040	time 0.4406 (0.4734)	model_time 0.4405 (0.4650)	loss 2.5185 (2.6251)	grad_norm 3.9987 (2.9705/1.2733)	mem 16099MB
[2025-01-18 12:10:40 internimage_t_1k_224] (main.py 519): INFO EPOCH 298 training takes 0:02:27
[2025-01-18 12:10:40 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_298.pth saving......
[2025-01-18 12:10:41 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_298.pth saved !!!
[2025-01-18 12:10:48 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.612 (7.612)	Loss 0.7176 (0.7176)	Acc@1 85.278 (85.278)	Acc@5 97.534 (97.534)	Mem 16099MB
[2025-01-18 12:10:52 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.035)	Loss 0.9581 (0.8166)	Acc@1 79.541 (83.243)	Acc@5 95.166 (96.358)	Mem 16099MB
[2025-01-18 12:10:52 internimage_t_1k_224] (main.py 575): INFO [Epoch:298] * Acc@1 83.089 Acc@5 96.369
[2025-01-18 12:10:52 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.1%
[2025-01-18 12:10:52 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.15%
[2025-01-18 12:11:01 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.705 (8.705)	Loss 0.7112 (0.7112)	Acc@1 85.791 (85.791)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 12:11:05 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.103 (1.147)	Loss 0.9418 (0.8090)	Acc@1 79.810 (83.658)	Acc@5 95.435 (96.547)	Mem 16099MB
[2025-01-18 12:11:05 internimage_t_1k_224] (main.py 575): INFO [Epoch:298] * Acc@1 83.501 Acc@5 96.559
[2025-01-18 12:11:05 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 12:11:05 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.57%
[2025-01-18 12:11:08 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][0/312]	eta 0:16:44 lr 0.000040	time 3.2201 (3.2201)	model_time 1.5231 (1.5231)	loss 3.2144 (3.2144)	grad_norm 5.1118 (5.1118/0.0000)	mem 16099MB
[2025-01-18 12:11:13 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][10/312]	eta 0:03:41 lr 0.000040	time 0.4880 (0.7324)	model_time 0.4878 (0.5777)	loss 1.8079 (2.4137)	grad_norm 3.0341 (3.0029/0.9439)	mem 16099MB
[2025-01-18 12:11:18 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][20/312]	eta 0:02:59 lr 0.000040	time 0.4641 (0.6152)	model_time 0.4636 (0.5340)	loss 2.1865 (2.4894)	grad_norm 1.8615 (2.9610/1.2366)	mem 16099MB
[2025-01-18 12:11:23 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][30/312]	eta 0:02:39 lr 0.000040	time 0.4629 (0.5668)	model_time 0.4627 (0.5116)	loss 1.7945 (2.5175)	grad_norm 2.7439 (2.9664/1.1719)	mem 16099MB
[2025-01-18 12:11:27 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][40/312]	eta 0:02:26 lr 0.000040	time 0.4583 (0.5395)	model_time 0.4581 (0.4977)	loss 3.3051 (2.5604)	grad_norm 1.3345 (2.8169/1.1554)	mem 16099MB
[2025-01-18 12:11:32 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][50/312]	eta 0:02:16 lr 0.000040	time 0.4611 (0.5226)	model_time 0.4610 (0.4890)	loss 3.0165 (2.5993)	grad_norm 4.4371 (2.7729/1.1117)	mem 16099MB
[2025-01-18 12:11:36 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][60/312]	eta 0:02:09 lr 0.000040	time 0.4865 (0.5123)	model_time 0.4863 (0.4841)	loss 2.1489 (2.5978)	grad_norm 2.5760 (2.8115/1.0986)	mem 16099MB
[2025-01-18 12:11:41 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][70/312]	eta 0:02:02 lr 0.000040	time 0.4520 (0.5042)	model_time 0.4518 (0.4799)	loss 2.6764 (2.6158)	grad_norm 3.3407 (2.7994/1.1173)	mem 16099MB
[2025-01-18 12:11:45 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][80/312]	eta 0:01:55 lr 0.000040	time 0.4475 (0.4979)	model_time 0.4471 (0.4766)	loss 3.3137 (2.6027)	grad_norm 2.6050 (2.8570/1.1555)	mem 16099MB
[2025-01-18 12:11:50 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][90/312]	eta 0:01:49 lr 0.000040	time 0.4660 (0.4933)	model_time 0.4658 (0.4742)	loss 2.7615 (2.5938)	grad_norm 1.2396 (2.7886/1.1278)	mem 16099MB
[2025-01-18 12:11:55 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][100/312]	eta 0:01:44 lr 0.000040	time 0.4479 (0.4912)	model_time 0.4478 (0.4741)	loss 2.2780 (2.5906)	grad_norm 3.4906 (2.7911/1.0867)	mem 16099MB
[2025-01-18 12:11:59 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][110/312]	eta 0:01:38 lr 0.000040	time 0.4623 (0.4881)	model_time 0.4622 (0.4724)	loss 2.8267 (2.5762)	grad_norm 1.9603 (2.7585/1.0901)	mem 16099MB
[2025-01-18 12:12:04 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][120/312]	eta 0:01:33 lr 0.000040	time 0.4547 (0.4862)	model_time 0.4542 (0.4718)	loss 2.2246 (2.5650)	grad_norm 6.1414 (2.8326/1.1894)	mem 16099MB
[2025-01-18 12:12:09 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][130/312]	eta 0:01:28 lr 0.000040	time 0.4536 (0.4853)	model_time 0.4534 (0.4720)	loss 2.3044 (2.5783)	grad_norm 1.8762 (2.8657/1.2330)	mem 16099MB
[2025-01-18 12:12:14 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][140/312]	eta 0:01:23 lr 0.000040	time 0.4811 (0.4859)	model_time 0.4809 (0.4735)	loss 2.2882 (2.5704)	grad_norm 3.4956 (2.8872/1.2108)	mem 16099MB
[2025-01-18 12:12:18 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][150/312]	eta 0:01:18 lr 0.000040	time 0.4503 (0.4850)	model_time 0.4502 (0.4734)	loss 2.8854 (2.5944)	grad_norm 3.2429 (2.8711/1.1899)	mem 16099MB
[2025-01-18 12:12:23 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][160/312]	eta 0:01:13 lr 0.000040	time 0.5394 (0.4844)	model_time 0.5389 (0.4735)	loss 2.9794 (2.6049)	grad_norm 2.3352 (2.8725/1.1964)	mem 16099MB
[2025-01-18 12:12:28 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][170/312]	eta 0:01:08 lr 0.000040	time 0.4523 (0.4830)	model_time 0.4519 (0.4727)	loss 3.0623 (2.6189)	grad_norm 3.1747 (2.9060/1.2006)	mem 16099MB
[2025-01-18 12:12:32 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][180/312]	eta 0:01:03 lr 0.000040	time 0.4518 (0.4816)	model_time 0.4517 (0.4718)	loss 2.6182 (2.6198)	grad_norm 1.9746 (2.9106/1.1892)	mem 16099MB
[2025-01-18 12:12:37 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][190/312]	eta 0:00:58 lr 0.000040	time 0.4749 (0.4821)	model_time 0.4748 (0.4729)	loss 3.1314 (2.6266)	grad_norm 4.7955 (2.9188/1.1921)	mem 16099MB
[2025-01-18 12:12:42 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][200/312]	eta 0:00:53 lr 0.000040	time 0.4467 (0.4805)	model_time 0.4466 (0.4717)	loss 2.8965 (2.6340)	grad_norm 1.2719 (2.9035/1.2110)	mem 16099MB
[2025-01-18 12:12:46 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][210/312]	eta 0:00:48 lr 0.000040	time 0.4572 (0.4797)	model_time 0.4568 (0.4713)	loss 2.0757 (2.6349)	grad_norm 5.0114 (2.9088/1.1971)	mem 16099MB
[2025-01-18 12:12:51 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][220/312]	eta 0:00:44 lr 0.000040	time 0.4517 (0.4785)	model_time 0.4516 (0.4704)	loss 1.9353 (2.6340)	grad_norm 2.1899 (2.9113/1.1981)	mem 16099MB
[2025-01-18 12:12:55 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][230/312]	eta 0:00:39 lr 0.000040	time 0.4543 (0.4777)	model_time 0.4541 (0.4700)	loss 2.8819 (2.6337)	grad_norm 3.7933 (2.9482/1.2033)	mem 16099MB
[2025-01-18 12:13:00 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][240/312]	eta 0:00:34 lr 0.000040	time 0.4526 (0.4777)	model_time 0.4522 (0.4703)	loss 2.2369 (2.6361)	grad_norm 1.3727 (2.9313/1.1974)	mem 16099MB
[2025-01-18 12:13:05 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][250/312]	eta 0:00:29 lr 0.000040	time 0.4480 (0.4777)	model_time 0.4479 (0.4706)	loss 3.0205 (2.6356)	grad_norm 3.9436 (2.9310/1.1916)	mem 16099MB
[2025-01-18 12:13:09 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][260/312]	eta 0:00:24 lr 0.000040	time 0.4517 (0.4767)	model_time 0.4513 (0.4699)	loss 2.7918 (2.6327)	grad_norm 2.1362 (2.9257/1.1802)	mem 16099MB
[2025-01-18 12:13:14 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][270/312]	eta 0:00:20 lr 0.000040	time 0.4554 (0.4762)	model_time 0.4549 (0.4696)	loss 2.2269 (2.6299)	grad_norm 2.1107 (2.9128/1.1684)	mem 16099MB
[2025-01-18 12:13:19 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][280/312]	eta 0:00:15 lr 0.000040	time 0.4540 (0.4754)	model_time 0.4538 (0.4690)	loss 2.6215 (2.6307)	grad_norm 3.5724 (2.8883/1.1649)	mem 16099MB
[2025-01-18 12:13:23 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][290/312]	eta 0:00:10 lr 0.000040	time 0.4522 (0.4747)	model_time 0.4521 (0.4685)	loss 2.4204 (2.6313)	grad_norm 1.4760 (2.8703/1.1639)	mem 16099MB
[2025-01-18 12:13:28 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][300/312]	eta 0:00:05 lr 0.000040	time 0.4430 (0.4739)	model_time 0.4429 (0.4679)	loss 2.1811 (2.6290)	grad_norm 3.2646 (2.8796/1.1567)	mem 16099MB
[2025-01-18 12:13:32 internimage_t_1k_224] (main.py 510): INFO Train: [299/300][310/312]	eta 0:00:00 lr 0.000040	time 0.5224 (0.4740)	model_time 0.5223 (0.4682)	loss 1.7683 (2.6249)	grad_norm 3.5410 (2.8899/1.1632)	mem 16099MB
[2025-01-18 12:13:33 internimage_t_1k_224] (main.py 519): INFO EPOCH 299 training takes 0:02:27
[2025-01-18 12:13:33 internimage_t_1k_224] (utils.py 359): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_299.pth saving......
[2025-01-18 12:13:34 internimage_t_1k_224] (utils.py 361): INFO work_dirs/internimage_t_1k_224/ckpt_epoch_299.pth saved !!!
[2025-01-18 12:13:42 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 7.749 (7.749)	Loss 0.7153 (0.7153)	Acc@1 85.278 (85.278)	Acc@5 97.510 (97.510)	Mem 16099MB
[2025-01-18 12:13:46 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.048)	Loss 0.9663 (0.8186)	Acc@1 79.102 (83.176)	Acc@5 95.239 (96.349)	Mem 16099MB
[2025-01-18 12:13:46 internimage_t_1k_224] (main.py 575): INFO [Epoch:299] * Acc@1 83.017 Acc@5 96.361
[2025-01-18 12:13:46 internimage_t_1k_224] (main.py 340): INFO Accuracy of the network on the 50000 test images: 83.0%
[2025-01-18 12:13:46 internimage_t_1k_224] (main.py 355): INFO Max accuracy: 83.15%
[2025-01-18 12:13:54 internimage_t_1k_224] (main.py 568): INFO Test: [0/13]	Time 8.611 (8.611)	Loss 0.7112 (0.7112)	Acc@1 85.815 (85.815)	Acc@5 97.607 (97.607)	Mem 16099MB
[2025-01-18 12:13:58 internimage_t_1k_224] (main.py 568): INFO Test: [10/13]	Time 0.102 (1.147)	Loss 0.9421 (0.8091)	Acc@1 79.810 (83.649)	Acc@5 95.435 (96.544)	Mem 16099MB
[2025-01-18 12:13:58 internimage_t_1k_224] (main.py 575): INFO [Epoch:299] * Acc@1 83.491 Acc@5 96.561
[2025-01-18 12:13:58 internimage_t_1k_224] (main.py 360): INFO Accuracy of the ema network on the 50000 test images: 83.5%
[2025-01-18 12:13:58 internimage_t_1k_224] (main.py 375): INFO Max ema accuracy: 83.57%
[2025-01-18 12:13:58 internimage_t_1k_224] (main.py 379): INFO Training time 14:26:41