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# ViT_breastmnist_std_30

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the medmnist-v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3936
- Accuracy: 0.8269
- F1: 0.7315

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.5034        | 0.2597 | 20   | 0.4719          | 0.7436   | 0.4708 |
| 0.4414        | 0.5195 | 40   | 0.4457          | 0.7821   | 0.6400 |
| 0.3762        | 0.7792 | 60   | 0.4212          | 0.8205   | 0.7248 |
| 0.4059        | 1.0390 | 80   | 0.3988          | 0.8462   | 0.7641 |
| 0.3249        | 1.2987 | 100  | 0.3829          | 0.8333   | 0.7606 |
| 0.2991        | 1.5584 | 120  | 0.4080          | 0.8462   | 0.7743 |
| 0.2948        | 1.8182 | 140  | 0.3932          | 0.8462   | 0.7833 |
| 0.2667        | 2.0779 | 160  | 0.4388          | 0.8333   | 0.7502 |
| 0.2049        | 2.3377 | 180  | 0.4047          | 0.8333   | 0.7606 |
| 0.1639        | 2.5974 | 200  | 0.4301          | 0.8333   | 0.7502 |
| 0.1732        | 2.8571 | 220  | 0.4028          | 0.8333   | 0.7606 |
| 0.1138        | 3.1169 | 240  | 0.3755          | 0.8718   | 0.8194 |
| 0.1099        | 3.3766 | 260  | 0.4019          | 0.8590   | 0.7886 |
| 0.1285        | 3.6364 | 280  | 0.3739          | 0.8590   | 0.7974 |
| 0.1265        | 3.8961 | 300  | 0.3714          | 0.8590   | 0.8051 |
| 0.0735        | 4.1558 | 320  | 0.3820          | 0.8718   | 0.8194 |
| 0.0515        | 4.4156 | 340  | 0.3910          | 0.8462   | 0.7833 |
| 0.0577        | 4.6753 | 360  | 0.3984          | 0.8462   | 0.7833 |
| 0.0584        | 4.9351 | 380  | 0.4314          | 0.8590   | 0.7974 |
| 0.0241        | 5.1948 | 400  | 0.4040          | 0.8718   | 0.8194 |
| 0.015         | 5.4545 | 420  | 0.4201          | 0.8718   | 0.8194 |
| 0.023         | 5.7143 | 440  | 0.4276          | 0.8718   | 0.8194 |
| 0.0254        | 5.9740 | 460  | 0.4271          | 0.8846   | 0.8342 |
| 0.0086        | 6.2338 | 480  | 0.4149          | 0.8718   | 0.8194 |
| 0.012         | 6.4935 | 500  | 0.4738          | 0.8718   | 0.8120 |
| 0.0052        | 6.7532 | 520  | 0.4314          | 0.8846   | 0.8342 |
| 0.0123        | 7.0130 | 540  | 0.4363          | 0.8718   | 0.8194 |
| 0.0026        | 7.2727 | 560  | 0.4477          | 0.8846   | 0.8342 |
| 0.0018        | 7.5325 | 580  | 0.4447          | 0.8718   | 0.8194 |
| 0.0024        | 7.7922 | 600  | 0.4588          | 0.8718   | 0.8194 |
| 0.0076        | 8.0519 | 620  | 0.4517          | 0.8718   | 0.8194 |
| 0.0013        | 8.3117 | 640  | 0.4535          | 0.8718   | 0.8194 |
| 0.0012        | 8.5714 | 660  | 0.4479          | 0.8846   | 0.8342 |
| 0.001         | 8.8312 | 680  | 0.4477          | 0.8846   | 0.8342 |
| 0.0015        | 9.0909 | 700  | 0.4509          | 0.8846   | 0.8342 |
| 0.001         | 9.3506 | 720  | 0.4529          | 0.8846   | 0.8342 |
| 0.0009        | 9.6104 | 740  | 0.4569          | 0.8846   | 0.8342 |
| 0.001         | 9.8701 | 760  | 0.4563          | 0.8846   | 0.8342 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0

malignant normal, benign