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# finetuned-breast_cancer_images

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 breast cancer-image-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1643
- Accuracy: 0.9620

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5507        | 2.5   | 100  | 0.3762          | 0.8861   |
| 0.4735        | 5.0   | 200  | 0.3380          | 0.8987   |
| 0.368         | 7.5   | 300  | 0.3424          | 0.8987   |
| 0.3182        | 10.0  | 400  | 0.2979          | 0.9082   |
| 0.2952        | 12.5  | 500  | 0.2110          | 0.9462   |
| 0.2493        | 15.0  | 600  | 0.1675          | 0.9620   |
| 0.2716        | 17.5  | 700  | 0.1705          | 0.9462   |
| 0.2866        | 20.0  | 800  | 0.1643          | 0.9620   |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.13.3

benign malignant normal