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: breastmnist-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. -->
+
+# breastmnist-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: 0.2690
+- Accuracy: 0.8846
+- Precision: 0.9018
+- Recall: 0.8008
+- F1: 0.8342
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 0.9143 | 8    | 0.4751          | 0.7821   | 0.8851    | 0.5952 | 0.5951 |
+| 0.5516        | 1.9429 | 17   | 0.4166          | 0.8462   | 0.8091    | 0.7895 | 0.7983 |
+| 0.478         | 2.9714 | 26   | 0.3676          | 0.8205   | 0.7792    | 0.7419 | 0.7565 |
+| 0.4617        | 4.0    | 35   | 0.3180          | 0.8718   | 0.8698    | 0.7920 | 0.8194 |
+| 0.4208        | 4.9143 | 43   | 0.4562          | 0.8590   | 0.8173    | 0.8584 | 0.8325 |
+| 0.3759        | 5.9429 | 52   | 0.3780          | 0.8718   | 0.8332    | 0.8521 | 0.8417 |
+| 0.3689        | 6.9714 | 61   | 0.2993          | 0.8846   | 0.9018    | 0.8008 | 0.8342 |
+| 0.3322        | 8.0    | 70   | 0.2785          | 0.8718   | 0.8698    | 0.7920 | 0.8194 |
+| 0.3322        | 8.9143 | 78   | 0.2700          | 0.8846   | 0.9018    | 0.8008 | 0.8342 |
+| 0.3242        | 9.1429 | 80   | 0.2690          | 0.8846   | 0.9018    | 0.8008 | 0.8342 |
+
+
+### 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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