Model save

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
+model-index:
+- name: swin-brain-abnormalities-classification-fold3
+  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. -->
+
+# swin-brain-abnormalities-classification-fold3
+
+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: 0.1552
+- Accuracy: 0.9566
+
+## 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: 5e-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
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 0.9031        | 0.9714  | 17   | 0.6752          | 0.7286   |
+| 0.5553        | 2.0     | 35   | 0.3278          | 0.8806   |
+| 0.3599        | 2.9714  | 52   | 0.2776          | 0.8942   |
+| 0.3013        | 4.0     | 70   | 0.1906          | 0.9281   |
+| 0.2276        | 4.9714  | 87   | 0.1999          | 0.9335   |
+| 0.1906        | 6.0     | 105  | 0.1566          | 0.9430   |
+| 0.1736        | 6.9714  | 122  | 0.1731          | 0.9403   |
+| 0.1593        | 8.0     | 140  | 0.1662          | 0.9444   |
+| 0.1318        | 8.9714  | 157  | 0.1761          | 0.9417   |
+| 0.1117        | 10.0    | 175  | 0.1714          | 0.9403   |
+| 0.1335        | 10.9714 | 192  | 0.1594          | 0.9525   |
+| 0.0996        | 12.0    | 210  | 0.1820          | 0.9417   |
+| 0.0954        | 12.9714 | 227  | 0.1528          | 0.9539   |
+| 0.0913        | 14.0    | 245  | 0.1547          | 0.9566   |
+| 0.0878        | 14.5714 | 255  | 0.1552          | 0.9566   |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

config.json

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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": "lesion",
+    "1": "normal",
+    "2": "tumor"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "lesion": 0,
+    "normal": 1,
+    "tumor": 2
+  },
+  "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": "4.45.1",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

model.safetensors

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+size 110345908

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

training_args.bin

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+size 5304