
<!-- 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. -->

# vit-base-breast-cancer

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-invasive-ductal-carcinoma-cancer dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3578
- Accuracy: 0.8731

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.206         | 0.23  | 100  | 0.3991          | 0.8342   |
| 0.2959        | 0.46  | 200  | 0.3608          | 0.8691   |
| 0.2492        | 0.69  | 300  | 0.3624          | 0.8681   |
| 0.237         | 0.92  | 400  | 0.3578          | 0.8731   |
| 0.2277        | 1.14  | 500  | 0.4044          | 0.8721   |
| 0.1821        | 1.37  | 600  | 0.4185          | 0.8661   |
| 0.1995        | 1.6   | 700  | 0.4412          | 0.8721   |
| 0.1288        | 1.83  | 800  | 0.4424          | 0.8272   |
| 0.1546        | 2.06  | 900  | 0.4491          | 0.8641   |
| 0.0319        | 2.29  | 1000 | 0.5021          | 0.8641   |
| 0.0537        | 2.52  | 1100 | 0.5292          | 0.8472   |
| 0.1493        | 2.75  | 1200 | 0.4235          | 0.8821   |
| 0.0774        | 2.97  | 1300 | 0.4753          | 0.8631   |
| 0.0823        | 3.2   | 1400 | 0.5120          | 0.8561   |
| 0.0264        | 3.43  | 1500 | 0.4868          | 0.8701   |
| 0.0386        | 3.66  | 1600 | 0.4909          | 0.8651   |
| 0.008         | 3.89  | 1700 | 0.5035          | 0.8651   |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.0.1+cu118
- Datasets 2.9.0
- Tokenizers 0.13.3

class0 class1