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: google/vit-base-patch16-224-in21k
+model-index:
+- name: derma-vit-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-vit-base-finetuned
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the medmnist-v2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6179
+- Accuracy: 0.7677
+- Precision: 0.5889
+- Recall: 0.4796
+- F1: 0.5088
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.7579        | 1.0   | 109  | 0.7045          | 0.7428   | 0.5204    | 0.3710 | 0.3927 |
+| 0.7689        | 2.0   | 219  | 0.7512          | 0.7278   | 0.3964    | 0.3527 | 0.3573 |
+| 0.7353        | 3.0   | 328  | 0.7191          | 0.7358   | 0.4630    | 0.4202 | 0.4002 |
+| 0.8429        | 4.0   | 438  | 0.7858          | 0.6810   | 0.4280    | 0.1813 | 0.1851 |
+| 0.7929        | 5.0   | 547  | 0.7013          | 0.7218   | 0.5158    | 0.3971 | 0.3523 |
+| 0.6804        | 6.0   | 657  | 0.6822          | 0.7607   | 0.5011    | 0.4240 | 0.4391 |
+| 0.6922        | 7.0   | 766  | 0.6533          | 0.7667   | 0.6762    | 0.5106 | 0.5227 |
+| 0.6563        | 8.0   | 876  | 0.6758          | 0.7468   | 0.4548    | 0.4589 | 0.4496 |
+| 0.6985        | 9.0   | 985  | 0.6264          | 0.7647   | 0.6451    | 0.4692 | 0.4915 |
+| 0.6283        | 9.95  | 1090 | 0.6179          | 0.7677   | 0.5889    | 0.4796 | 0.5088 |
+
+
+### 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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