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# ViT_breastmnist_std_45

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: 0.4752
- Accuracy: 0.7821
- F1: 0.6733

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.5115        | 0.2597 | 20   | 0.5292          | 0.7308   | 0.4222 |
| 0.4949        | 0.5195 | 40   | 0.5229          | 0.7436   | 0.4708 |
| 0.4099        | 0.7792 | 60   | 0.4728          | 0.7692   | 0.5568 |
| 0.4461        | 1.0390 | 80   | 0.4428          | 0.8333   | 0.7247 |
| 0.4201        | 1.2987 | 100  | 0.4311          | 0.8718   | 0.8120 |
| 0.3532        | 1.5584 | 120  | 0.4206          | 0.8590   | 0.7886 |
| 0.3586        | 1.8182 | 140  | 0.4292          | 0.8590   | 0.7886 |
| 0.3412        | 2.0779 | 160  | 0.4541          | 0.8333   | 0.7247 |
| 0.2945        | 2.3377 | 180  | 0.4179          | 0.8333   | 0.7606 |
| 0.2555        | 2.5974 | 200  | 0.4331          | 0.8590   | 0.7886 |
| 0.2753        | 2.8571 | 220  | 0.4310          | 0.8205   | 0.7367 |
| 0.2079        | 3.1169 | 240  | 0.4152          | 0.8462   | 0.7833 |
| 0.217         | 3.3766 | 260  | 0.4157          | 0.8718   | 0.8260 |
| 0.167         | 3.6364 | 280  | 0.4259          | 0.8590   | 0.8051 |
| 0.1976        | 3.8961 | 300  | 0.4346          | 0.8462   | 0.7913 |
| 0.1376        | 4.1558 | 320  | 0.4341          | 0.8462   | 0.7913 |
| 0.1301        | 4.4156 | 340  | 0.4418          | 0.8462   | 0.7983 |
| 0.1503        | 4.6753 | 360  | 0.4375          | 0.8590   | 0.8120 |
| 0.126         | 4.9351 | 380  | 0.4376          | 0.8590   | 0.8120 |
| 0.098         | 5.1948 | 400  | 0.4310          | 0.8462   | 0.7983 |
| 0.0675        | 5.4545 | 420  | 0.4545          | 0.8333   | 0.7849 |
| 0.0618        | 5.7143 | 440  | 0.4587          | 0.8333   | 0.7849 |
| 0.0572        | 5.9740 | 460  | 0.4629          | 0.8462   | 0.7983 |
| 0.0283        | 6.2338 | 480  | 0.4778          | 0.8333   | 0.7849 |
| 0.0337        | 6.4935 | 500  | 0.4820          | 0.8462   | 0.7983 |
| 0.0416        | 6.7532 | 520  | 0.4794          | 0.8462   | 0.8045 |
| 0.0535        | 7.0130 | 540  | 0.4811          | 0.8333   | 0.7849 |
| 0.0146        | 7.2727 | 560  | 0.4780          | 0.8462   | 0.7983 |
| 0.0205        | 7.5325 | 580  | 0.4889          | 0.8333   | 0.7849 |
| 0.0118        | 7.7922 | 600  | 0.5004          | 0.8333   | 0.7913 |
| 0.0148        | 8.0519 | 620  | 0.4974          | 0.8333   | 0.7849 |
| 0.0078        | 8.3117 | 640  | 0.5009          | 0.8205   | 0.7719 |
| 0.0101        | 8.5714 | 660  | 0.5079          | 0.8205   | 0.7719 |
| 0.0042        | 8.8312 | 680  | 0.5178          | 0.8205   | 0.7719 |
| 0.0047        | 9.0909 | 700  | 0.5186          | 0.8205   | 0.7719 |
| 0.0029        | 9.3506 | 720  | 0.5217          | 0.8205   | 0.7719 |
| 0.0042        | 9.6104 | 740  | 0.5238          | 0.8077   | 0.7592 |
| 0.0038        | 9.8701 | 760  | 0.5246          | 0.8205   | 0.7719 |


### Framework versions

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

malignant normal, benign