Model save

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+datasets:
+- medmnist-v2
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+base_model: facebook/deit-base-patch16-224
+model-index:
+- name: derma-deit-base-finetuned
+  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. -->
+
+# derma-deit-base-finetuned
+
+This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the medmnist-v2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5544
+- Accuracy: 0.7956
+- Precision: 0.6273
+- Recall: 0.5810
+- F1: 0.5998
+
+## 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: 0.005
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.9012        | 1.0   | 109  | 0.7630          | 0.7228   | 0.4263    | 0.3269 | 0.3462 |
+| 0.7636        | 2.0   | 219  | 0.7212          | 0.7288   | 0.5912    | 0.3631 | 0.3789 |
+| 0.7189        | 3.0   | 328  | 0.7622          | 0.7258   | 0.4465    | 0.4230 | 0.3935 |
+| 0.6904        | 4.0   | 438  | 0.7281          | 0.7438   | 0.4888    | 0.4484 | 0.4115 |
+| 0.7658        | 5.0   | 547  | 0.7215          | 0.7398   | 0.4855    | 0.4252 | 0.3753 |
+| 0.6363        | 6.0   | 657  | 0.6329          | 0.7677   | 0.6350    | 0.4928 | 0.5121 |
+| 0.6299        | 7.0   | 766  | 0.6117          | 0.7717   | 0.5962    | 0.5781 | 0.5713 |
+| 0.6011        | 8.0   | 876  | 0.5919          | 0.7797   | 0.6162    | 0.5757 | 0.5902 |
+| 0.6043        | 9.0   | 985  | 0.5476          | 0.7946   | 0.6295    | 0.5813 | 0.5983 |
+| 0.5671        | 9.95  | 1090 | 0.5544          | 0.7956   | 0.6273    | 0.5810 | 0.5998 |
+
+
+### Framework versions
+
+- PEFT 0.9.0
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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