Model save

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: facebook/deit-base-patch16-224
+datasets:
+- medmnist-v2
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: pneumoniamnist-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. -->
+
+# pneumoniamnist-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: 0.3024
+- Accuracy: 0.8740
+- Precision: 0.8314
+- Recall: 0.8958
+- F1: 0.8515
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.6158        | 0.9898 | 73   | 0.5674          | 0.7424   | 0.3712    | 0.5    | 0.4261 |
+| 0.5322        | 1.9932 | 147  | 0.4840          | 0.7729   | 0.8829    | 0.5593 | 0.5396 |
+| 0.4139        | 2.9966 | 221  | 0.3727          | 0.7939   | 0.8913    | 0.6    | 0.6057 |
+| 0.3979        | 4.0    | 295  | 0.5270          | 0.7309   | 0.7405    | 0.8139 | 0.7168 |
+| 0.3858        | 4.9898 | 368  | 0.3062          | 0.8531   | 0.8073    | 0.8623 | 0.8253 |
+| 0.3704        | 5.9932 | 442  | 0.3774          | 0.8263   | 0.7939    | 0.8734 | 0.8056 |
+| 0.3345        | 6.9966 | 516  | 0.2403          | 0.9027   | 0.8691    | 0.8812 | 0.8749 |
+| 0.3875        | 8.0    | 590  | 0.3021          | 0.8817   | 0.8389    | 0.8985 | 0.8590 |
+| 0.3673        | 8.9898 | 663  | 0.2865          | 0.8969   | 0.8557    | 0.9064 | 0.8749 |
+| 0.3493        | 9.8983 | 730  | 0.3024          | 0.8740   | 0.8314    | 0.8958 | 0.8515 |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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