Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: Wound-Image-classification
+  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. -->
+
+# Wound-Image-classification
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9180
+- Accuracy: 0.8736
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.8915        | 1.0   | 43   | 1.7986          | 0.4713   |
+| 1.6488        | 2.0   | 86   | 1.5066          | 0.5517   |
+| 1.3878        | 3.0   | 129  | 1.2617          | 0.7701   |
+| 1.1614        | 4.0   | 172  | 1.1325          | 0.7931   |
+| 0.9948        | 5.0   | 215  | 1.0308          | 0.8046   |
+| 0.885         | 6.0   | 258  | 0.9670          | 0.8391   |
+| 0.8482        | 7.0   | 301  | 0.9175          | 0.8621   |
+| 0.8178        | 8.0   | 344  | 0.9180          | 0.8736   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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