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swin-tiny-patch4-window7-224-finetuned-eurosat

Image Classification
Transformers
PyTorch
swin
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
swin-tiny-patch4-window7-224-finetuned-eurosat
File size: 1,332 Bytes 
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{
  "_name_or_path": "microsoft/swin-tiny-patch4-window7-224",
  "architectures": [
    "SwinForImageClassification"
  ],
  "attention_probs_dropout_prob": 0.0,
  "depths": [
    2,
    2,
    6,
    2
  ],
  "drop_path_rate": 0.1,
  "embed_dim": 96,
  "encoder_stride": 32,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.0,
  "hidden_size": 768,
  "id2label": {
    "0": "airplane",
    "1": "automobile",
    "2": "bird",
    "3": "cat",
    "4": "deer",
    "5": "dog",
    "6": "frog",
    "7": "horse",
    "8": "ship",
    "9": "truck"
  },
  "image_size": 224,
  "initializer_range": 0.02,
  "label2id": {
    "airplane": 0,
    "automobile": 1,
    "bird": 2,
    "cat": 3,
    "deer": 4,
    "dog": 5,
    "frog": 6,
    "horse": 7,
    "ship": 8,
    "truck": 9
  },
  "layer_norm_eps": 1e-05,
  "mlp_ratio": 4.0,
  "model_type": "swin",
  "num_channels": 3,
  "num_heads": [
    3,
    6,
    12,
    24
  ],
  "num_layers": 4,
  "out_features": [
    "stage4"
  ],
  "out_indices": [
    4
  ],
  "patch_size": 4,
  "path_norm": true,
  "problem_type": "single_label_classification",
  "qkv_bias": true,
  "stage_names": [
    "stem",
    "stage1",
    "stage2",
    "stage3",
    "stage4"
  ],
  "torch_dtype": "float32",
  "transformers_version": "4.33.0",
  "use_absolute_embeddings": false,
  "window_size": 7
}