update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: Augmented-Final
+      split: train
+      args: Augmented-Final
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9907502569373073
+---
+
+<!-- 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. -->
+
+# beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20
+
+This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0434
+- Accuracy: 0.9908
+
+## 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-06
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.9
+- num_epochs: 12
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.9688        | 1.0   | 122  | 1.8425          | 0.2775   |
+| 1.4822        | 2.0   | 244  | 1.3833          | 0.5457   |
+| 1.1239        | 3.0   | 366  | 0.9321          | 0.6680   |
+| 0.8686        | 4.0   | 488  | 0.6691          | 0.7698   |
+| 0.5234        | 5.0   | 610  | 0.4872          | 0.8335   |
+| 0.5246        | 6.0   | 732  | 0.3586          | 0.8736   |
+| 0.3691        | 7.0   | 854  | 0.3134          | 0.8993   |
+| 0.4708        | 8.0   | 976  | 0.2069          | 0.9394   |
+| 0.1694        | 9.0   | 1098 | 0.1832          | 0.9414   |
+| 0.2749        | 10.0  | 1220 | 0.1198          | 0.9640   |
+| 0.1777        | 11.0  | 1342 | 0.0845          | 0.9733   |
+| 0.1529        | 12.0  | 1464 | 0.0434          | 0.9908   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3