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# ViT_breastmnist_std_15

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: 0.4504
- Accuracy: 0.7885
- F1: 0.6551

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.4628        | 0.2597 | 20   | 0.4724          | 0.7821   | 0.5951 |
| 0.3645        | 0.5195 | 40   | 0.3994          | 0.8590   | 0.7786 |
| 0.2744        | 0.7792 | 60   | 0.4429          | 0.8462   | 0.7524 |
| 0.3004        | 1.0390 | 80   | 0.3893          | 0.8590   | 0.7886 |
| 0.2153        | 1.2987 | 100  | 0.4120          | 0.8462   | 0.7641 |
| 0.1593        | 1.5584 | 120  | 0.4542          | 0.8590   | 0.7786 |
| 0.1189        | 1.8182 | 140  | 0.3911          | 0.8718   | 0.8120 |
| 0.1139        | 2.0779 | 160  | 0.4154          | 0.8590   | 0.7886 |
| 0.0707        | 2.3377 | 180  | 0.4517          | 0.8590   | 0.7886 |
| 0.0482        | 2.5974 | 200  | 0.4824          | 0.8718   | 0.8034 |
| 0.0499        | 2.8571 | 220  | 0.4408          | 0.8462   | 0.7743 |
| 0.0195        | 3.1169 | 240  | 0.4874          | 0.8462   | 0.7743 |
| 0.0146        | 3.3766 | 260  | 0.4723          | 0.8718   | 0.8120 |
| 0.0141        | 3.6364 | 280  | 0.5117          | 0.8590   | 0.7886 |
| 0.017         | 3.8961 | 300  | 0.6032          | 0.8462   | 0.7743 |
| 0.0052        | 4.1558 | 320  | 0.5948          | 0.8590   | 0.7886 |
| 0.005         | 4.4156 | 340  | 0.5897          | 0.8590   | 0.7886 |
| 0.0039        | 4.6753 | 360  | 0.5729          | 0.8462   | 0.7743 |
| 0.0088        | 4.9351 | 380  | 0.5623          | 0.8462   | 0.7743 |
| 0.0104        | 5.1948 | 400  | 0.4814          | 0.8718   | 0.8194 |
| 0.0012        | 5.4545 | 420  | 0.5039          | 0.8718   | 0.8194 |
| 0.001         | 5.7143 | 440  | 0.5268          | 0.8718   | 0.8120 |
| 0.001         | 5.9740 | 460  | 0.5435          | 0.8590   | 0.7886 |
| 0.0007        | 6.2338 | 480  | 0.5435          | 0.8462   | 0.7743 |
| 0.0007        | 6.4935 | 500  | 0.5373          | 0.8590   | 0.7974 |
| 0.0006        | 6.7532 | 520  | 0.5745          | 0.8590   | 0.7886 |
| 0.0007        | 7.0130 | 540  | 0.5674          | 0.8462   | 0.7743 |
| 0.0004        | 7.2727 | 560  | 0.5826          | 0.8462   | 0.7743 |
| 0.0006        | 7.5325 | 580  | 0.5663          | 0.8462   | 0.7743 |
| 0.0006        | 7.7922 | 600  | 0.5751          | 0.8462   | 0.7743 |
| 0.0005        | 8.0519 | 620  | 0.5851          | 0.8462   | 0.7743 |
| 0.0004        | 8.3117 | 640  | 0.5782          | 0.8462   | 0.7743 |
| 0.0004        | 8.5714 | 660  | 0.5875          | 0.8462   | 0.7743 |
| 0.0004        | 8.8312 | 680  | 0.5939          | 0.8462   | 0.7743 |
| 0.0004        | 9.0909 | 700  | 0.5934          | 0.8462   | 0.7743 |
| 0.0004        | 9.3506 | 720  | 0.5925          | 0.8462   | 0.7743 |
| 0.0004        | 9.6104 | 740  | 0.5930          | 0.8462   | 0.7743 |
| 0.0004        | 9.8701 | 760  | 0.5945          | 0.8462   | 0.7743 |


### Framework versions

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

malignant normal, benign