Model save

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: google/vit-base-patch16-224-in21k
+datasets:
+- medmnist-v2
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: pneumoniamnist-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. -->
+
+# pneumoniamnist-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: 0.0824
+- Accuracy: 0.9580
+- Precision: 0.9355
+- Recall: 0.9596
+- F1: 0.9466
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.2447        | 0.9898 | 73   | 0.1538          | 0.9351   | 0.9013    | 0.9466 | 0.9200 |
+| 0.3466        | 1.9932 | 147  | 0.2451          | 0.9122   | 0.9197    | 0.8466 | 0.8750 |
+| 0.2074        | 2.9966 | 221  | 0.1711          | 0.9427   | 0.9538    | 0.8961 | 0.9203 |
+| 0.1928        | 4.0    | 295  | 0.1044          | 0.9618   | 0.9482    | 0.9525 | 0.9503 |
+| 0.2043        | 4.9898 | 368  | 0.1007          | 0.9580   | 0.9491    | 0.9403 | 0.9446 |
+| 0.1717        | 5.9932 | 442  | 0.0930          | 0.9618   | 0.9432    | 0.9598 | 0.9510 |
+| 0.1498        | 6.9966 | 516  | 0.0845          | 0.9637   | 0.9448    | 0.9635 | 0.9536 |
+| 0.1531        | 8.0    | 590  | 0.1661          | 0.9332   | 0.8974    | 0.9526 | 0.9188 |
+| 0.1451        | 8.9898 | 663  | 0.0760          | 0.9637   | 0.9464    | 0.9611 | 0.9534 |
+| 0.1263        | 9.8983 | 730  | 0.0824          | 0.9580   | 0.9355    | 0.9596 | 0.9466 |
+
+
+### 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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