./wmc_v2_swin-tiny-patch4-window7-224_base_wm811k_cls_contra_learning_1017_all_cls

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: microsoft/swin-tiny-patch4-window7-224
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: wmc_v2_swin-tiny-patch4-window7-224_base_wm811k_cls_contra_learning_1017_all_cls
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# wmc_v2_swin-tiny-patch4-window7-224_base_wm811k_cls_contra_learning_1017_all_cls
+
+This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0733
+- Accuracy: 0.9767
+- Precision: 0.8901
+- Recall: 0.9041
+- F1: 0.8937
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.3022        | 0.1079 | 100  | 0.8643          | 0.6787   | 0.0969    | 0.1188 | 0.1016 |
+| 0.1973        | 0.2158 | 200  | 0.4558          | 0.8645   | 0.5013    | 0.4063 | 0.3734 |
+| 0.1885        | 0.3237 | 300  | 0.2848          | 0.8865   | 0.5775    | 0.5620 | 0.5382 |
+| 0.17          | 0.4316 | 400  | 0.2082          | 0.9122   | 0.7820    | 0.6967 | 0.6702 |
+| 0.1565        | 0.5395 | 500  | 0.1775          | 0.9164   | 0.7701    | 0.7289 | 0.6901 |
+| 0.1251        | 0.6474 | 600  | 0.1820          | 0.9265   | 0.6982    | 0.8022 | 0.6862 |
+| 0.087         | 0.7553 | 700  | 0.1075          | 0.9688   | 0.8296    | 0.8707 | 0.8433 |
+| 0.1474        | 0.8632 | 800  | 0.1504          | 0.9351   | 0.7887    | 0.8037 | 0.7687 |
+| 0.1065        | 0.9711 | 900  | 0.1576          | 0.9262   | 0.8158    | 0.7454 | 0.7077 |
+| 0.1262        | 1.0790 | 1000 | 0.1323          | 0.9475   | 0.8042    | 0.8150 | 0.7552 |
+| 0.1223        | 1.1869 | 1100 | 0.1503          | 0.9340   | 0.7646    | 0.8377 | 0.7605 |
+| 0.1433        | 1.2948 | 1200 | 0.0846          | 0.9739   | 0.8748    | 0.8704 | 0.8688 |
+| 0.11          | 1.4028 | 1300 | 0.1043          | 0.9608   | 0.8525    | 0.8474 | 0.8353 |
+| 0.0907        | 1.5107 | 1400 | 0.0814          | 0.9757   | 0.8717    | 0.8733 | 0.8619 |
+| 0.0951        | 1.6186 | 1500 | 0.0899          | 0.9731   | 0.8459    | 0.9010 | 0.8669 |
+| 0.1085        | 1.7265 | 1600 | 0.1138          | 0.9593   | 0.7984    | 0.8802 | 0.8262 |
+| 0.0883        | 1.8344 | 1700 | 0.0794          | 0.9756   | 0.8803    | 0.8954 | 0.8832 |
+| 0.0835        | 1.9423 | 1800 | 0.0853          | 0.9751   | 0.8444    | 0.9116 | 0.8706 |
+| 0.0907        | 2.0502 | 1900 | 0.0992          | 0.9640   | 0.8266    | 0.8745 | 0.8319 |
+| 0.091         | 2.1581 | 2000 | 0.0729          | 0.9779   | 0.8858    | 0.9061 | 0.8936 |
+| 0.1216        | 2.2660 | 2100 | 0.0802          | 0.9743   | 0.8711    | 0.9100 | 0.8879 |
+| 0.0866        | 2.3739 | 2200 | 0.0853          | 0.9742   | 0.8656    | 0.9099 | 0.8845 |
+| 0.0815        | 2.4818 | 2300 | 0.0799          | 0.9735   | 0.8860    | 0.8924 | 0.8849 |
+| 0.0767        | 2.5897 | 2400 | 0.0643          | 0.9803   | 0.8870    | 0.9182 | 0.9010 |
+| 0.0809        | 2.6976 | 2500 | 0.0720          | 0.9779   | 0.8813    | 0.9173 | 0.8978 |
+| 0.1004        | 2.8055 | 2600 | 0.0731          | 0.9780   | 0.8966    | 0.9072 | 0.8998 |
+| 0.0607        | 2.9134 | 2700 | 0.0733          | 0.9767   | 0.8901    | 0.9041 | 0.8937 |
+
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.20.1

config.json

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+{
+  "_name_or_path": "microsoft/swin-tiny-patch4-window7-224",
+  "architectures": [
+    "SwinForClassificationAndContrastiveLearning"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    6,
+    2
+  ],
+  "drop_path_rate": 0.1,
+  "embed_dim": 96,
+  "encoder_stride": 32,
+  "finetuning_task": "image-classification",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8
+  },
+  "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": "4.45.2",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

model.safetensors

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+size 110364364

training_args.bin

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