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# vit-lr-0.001

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the skin-cancer dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7065
- Accuracy: 0.7334
- Precision: 0.7056
- Recall: 0.7334
- F1: 0.7133

## 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: 0.001
- 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: cosine
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0781        | 1.0   | 321   | 0.9802          | 0.6709   | 0.4973    | 0.6709 | 0.5438 |
| 0.9514        | 2.0   | 642   | 0.8989          | 0.6689   | 0.5299    | 0.6689 | 0.5529 |
| 0.9232        | 3.0   | 963   | 0.9391          | 0.6702   | 0.5516    | 0.6702 | 0.6020 |
| 0.9191        | 4.0   | 1284  | 0.9349          | 0.6803   | 0.5261    | 0.6803 | 0.5764 |
| 0.8919        | 5.0   | 1605  | 0.8966          | 0.6827   | 0.5608    | 0.6827 | 0.6014 |
| 0.8521        | 6.0   | 1926  | 0.8330          | 0.6928   | 0.6099    | 0.6928 | 0.6337 |
| 0.8304        | 7.0   | 2247  | 0.8980          | 0.6786   | 0.5849    | 0.6786 | 0.5701 |
| 0.7971        | 8.0   | 2568  | 0.8211          | 0.6834   | 0.6957    | 0.6834 | 0.6662 |
| 0.7881        | 9.0   | 2889  | 0.8262          | 0.6963   | 0.6476    | 0.6963 | 0.6051 |
| 0.7796        | 10.0  | 3210  | 0.8119          | 0.7049   | 0.6523    | 0.7049 | 0.6407 |
| 0.7535        | 11.0  | 3531  | 0.7961          | 0.6976   | 0.7043    | 0.6976 | 0.6933 |
| 0.7404        | 12.0  | 3852  | 0.7899          | 0.7063   | 0.7079    | 0.7063 | 0.7019 |
| 0.7455        | 13.0  | 4173  | 0.8245          | 0.6963   | 0.5619    | 0.6963 | 0.6146 |
| 0.747         | 14.0  | 4494  | 0.7627          | 0.7074   | 0.7085    | 0.7074 | 0.6971 |
| 0.7263        | 15.0  | 4815  | 0.7411          | 0.7243   | 0.7074    | 0.7243 | 0.6857 |
| 0.7203        | 16.0  | 5136  | 0.7484          | 0.7098   | 0.6399    | 0.7098 | 0.6503 |
| 0.7194        | 17.0  | 5457  | 0.7248          | 0.7191   | 0.6724    | 0.7191 | 0.6771 |
| 0.7029        | 18.0  | 5778  | 0.7470          | 0.7174   | 0.6885    | 0.7174 | 0.6898 |
| 0.7129        | 19.0  | 6099  | 0.7173          | 0.7243   | 0.6964    | 0.7243 | 0.7037 |
| 0.6895        | 20.0  | 6420  | 0.7423          | 0.7205   | 0.6830    | 0.7205 | 0.6893 |
| 0.7066        | 21.0  | 6741  | 0.7528          | 0.7146   | 0.6887    | 0.7146 | 0.6811 |
| 0.6895        | 22.0  | 7062  | 0.7132          | 0.7302   | 0.7057    | 0.7302 | 0.7102 |
| 0.6918        | 23.0  | 7383  | 0.7690          | 0.7115   | 0.7080    | 0.7115 | 0.6986 |
| 0.6818        | 24.0  | 7704  | 0.7065          | 0.7334   | 0.7056    | 0.7334 | 0.7133 |
| 0.6538        | 25.0  | 8025  | 0.7207          | 0.7230   | 0.7155    | 0.7230 | 0.7185 |
| 0.655         | 26.0  | 8346  | 0.7191          | 0.7268   | 0.7035    | 0.7268 | 0.7090 |
| 0.6612        | 27.0  | 8667  | 0.7314          | 0.7195   | 0.7167    | 0.7195 | 0.6979 |
| 0.6406        | 28.0  | 8988  | 0.7939          | 0.7247   | 0.6993    | 0.7247 | 0.7037 |
| 0.64          | 29.0  | 9309  | 0.7089          | 0.7365   | 0.7179    | 0.7365 | 0.7168 |
| 0.637         | 30.0  | 9630  | 0.7512          | 0.7313   | 0.6939    | 0.7313 | 0.6993 |
| 0.622         | 31.0  | 9951  | 0.7483          | 0.7288   | 0.6973    | 0.7288 | 0.7064 |
| 0.6193        | 32.0  | 10272 | 0.7290          | 0.7198   | 0.7197    | 0.7198 | 0.7175 |
| 0.6058        | 33.0  | 10593 | 0.7299          | 0.7309   | 0.7053    | 0.7309 | 0.7095 |
| 0.6047        | 34.0  | 10914 | 0.7086          | 0.7292   | 0.7296    | 0.7292 | 0.7233 |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

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