Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swin-base-patch4-window7-224
+tags:
+- generated_from_trainer
+datasets:
+- image_folder
+metrics:
+- accuracy
+model-index:
+- name: swin-base-patch4-window7-224-rawdata-finetuned-SkinDisease
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: image_folder
+      type: image_folder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8737270875763747
+---
+
+<!-- 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-base-patch4-window7-224-rawdata-finetuned-SkinDisease
+
+This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the image_folder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3801
+- Accuracy: 0.8737
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.7301        | 0.98  | 34   | 2.0665          | 0.3910   |
+| 1.3672        | 1.99  | 69   | 1.0139          | 0.6660   |
+| 0.7673        | 2.99  | 104  | 0.7393          | 0.7760   |
+| 0.605         | 4.0   | 139  | 0.6480          | 0.7841   |
+| 0.5142        | 4.98  | 173  | 0.5229          | 0.8248   |
+| 0.4081        | 5.99  | 208  | 0.4561          | 0.8615   |
+| 0.3966        | 6.99  | 243  | 0.4206          | 0.8656   |
+| 0.3247        | 8.0   | 278  | 0.4001          | 0.8717   |
+| 0.3235        | 8.98  | 312  | 0.3867          | 0.8819   |
+| 0.2788        | 9.78  | 340  | 0.3801          | 0.8737   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.13.3

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