Model save

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+base_model: facebook/deit-base-patch16-224
+model-index:
+- name: chest-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. -->
+
+# chest-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 an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0885
+- Accuracy: 0.9622
+- Precision: 0.9398
+- Recall: 0.9681
+- F1: 0.9526
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.2556        | 0.99  | 63   | 0.2019          | 0.9185   | 0.9446    | 0.8469 | 0.8822 |
+| 0.2302        | 1.99  | 127  | 0.1098          | 0.9614   | 0.9396    | 0.9654 | 0.9514 |
+| 0.2258        | 3.0   | 191  | 0.1151          | 0.9622   | 0.9641    | 0.9372 | 0.9496 |
+| 0.1465        | 4.0   | 255  | 0.0733          | 0.9725   | 0.9653    | 0.9633 | 0.9643 |
+| 0.1763        | 4.99  | 318  | 0.0763          | 0.9725   | 0.9703    | 0.9580 | 0.9639 |
+| 0.1627        | 5.99  | 382  | 0.1057          | 0.9571   | 0.9315    | 0.9656 | 0.9466 |
+| 0.1509        | 7.0   | 446  | 0.0701          | 0.9751   | 0.9638    | 0.9725 | 0.9680 |
+| 0.1209        | 8.0   | 510  | 0.1047          | 0.9571   | 0.9315    | 0.9656 | 0.9466 |
+| 0.0961        | 8.99  | 573  | 0.0721          | 0.9734   | 0.9577    | 0.9756 | 0.9662 |
+| 0.1063        | 9.88  | 630  | 0.0885          | 0.9622   | 0.9398    | 0.9681 | 0.9526 |
+
+
+### 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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