End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: microsoft/swin-small-patch4-window7-224
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- f1
+model-index:
+- name: swin-small-patch4-window7-224
+  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-small-patch4-window7-224
+
+This model is a fine-tuned version of [microsoft/swin-small-patch4-window7-224](https://huggingface.co/microsoft/swin-small-patch4-window7-224) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1892
+- Accuracy: 0.9778
+- Precision: 0.9804
+- Sensitivity: 1.0
+- Specificity: 0.9733
+- F1: 0.9783
+- Auc: 0.9909
+- Mcc: 0.9267
+- J Stat: 0.9733
+- Confusion Matrix: [[146, 4], [0, 30]]
+
+## 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: 8.068420130106194e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.06206076180207542
+- num_epochs: 10
+- label_smoothing_factor: 0.06417838785936565
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Sensitivity | Specificity | F1     | Auc    | Mcc    | J Stat | Confusion Matrix         |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:-----------:|:-----------:|:------:|:------:|:------:|:------:|:------------------------:|
+| No log        | 1.0   | 47   | 0.2904          | 0.9228   | 0.9256    | 0.7333      | 0.9892      | 0.9191 | 0.9754 | 0.7944 | 0.7225 | [[1100, 12], [104, 286]] |
+| 0.4216        | 2.0   | 94   | 0.2247          | 0.9634   | 0.9640    | 0.8769      | 0.9937      | 0.9627 | 0.9866 | 0.9038 | 0.8706 | [[1105, 7], [48, 342]]   |
+| 0.2859        | 3.0   | 141  | 0.2064          | 0.9800   | 0.9800    | 0.9410      | 0.9937      | 0.9799 | 0.9914 | 0.9477 | 0.9347 | [[1105, 7], [23, 367]]   |
+| 0.2231        | 4.0   | 188  | 0.1778          | 0.9847   | 0.9847    | 0.9513      | 0.9964      | 0.9846 | 0.9956 | 0.9600 | 0.9477 | [[1108, 4], [19, 371]]   |
+| 0.1986        | 5.0   | 235  | 0.1590          | 0.9933   | 0.9933    | 0.9872      | 0.9955      | 0.9933 | 0.9982 | 0.9827 | 0.9827 | [[1107, 5], [5, 385]]    |
+| 0.174         | 6.0   | 282  | 0.1484          | 0.9973   | 0.9973    | 0.9923      | 0.9991      | 0.9973 | 0.9995 | 0.9931 | 0.9914 | [[1111, 1], [3, 387]]    |
+| 0.1526        | 7.0   | 329  | 0.1469          | 0.9980   | 0.9980    | 0.9949      | 0.9991      | 0.9980 | 0.9999 | 0.9948 | 0.9940 | [[1111, 1], [2, 388]]    |
+| 0.1518        | 8.0   | 376  | 0.1461          | 0.9987   | 0.9987    | 0.9949      | 1.0         | 0.9987 | 0.9997 | 0.9965 | 0.9949 | [[1112, 0], [2, 388]]    |
+| 0.148         | 9.0   | 423  | 0.1459          | 0.9987   | 0.9987    | 0.9949      | 1.0         | 0.9987 | 1.0000 | 0.9965 | 0.9949 | [[1112, 0], [2, 388]]    |
+| 0.1496        | 10.0  | 470  | 0.1458          | 0.9987   | 0.9987    | 0.9949      | 1.0         | 0.9987 | 1.0000 | 0.9965 | 0.9949 | [[1112, 0], [2, 388]]    |
+
+
+### Framework versions
+
+- Transformers 4.52.4
+- Pytorch 2.6.0+cu124
+- Datasets 4.0.0
+- Tokenizers 0.21.2

config.json

@@ -0,0 +1,59 @@
+{
+  "architectures": [
+    "SwinForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    18,
+    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": "negative",
+    "1": "positive"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "negative": "0",
+    "positive": "1"
+  },
+  "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,
+  "qkv_bias": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.52.4",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

model.safetensors

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+size 195872552

preprocessor_config.json

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+{
+  "crop_size": null,
+  "data_format": "channels_first",
+  "default_to_square": true,
+  "device": null,
+  "do_center_crop": null,
+  "do_convert_rgb": null,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ViTImageProcessorFast",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "input_data_format": null,
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "return_tensors": null,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

training_args.bin

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