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# vit-weight-decay-1e-3

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: 0.5183
- Accuracy: 0.8381
- Precision: 0.8396
- Recall: 0.8381
- F1: 0.8356

## 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: 0.0001
- 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
- lr_scheduler_warmup_steps: 1733
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.7663        | 1.0   | 321  | 0.9397          | 0.6900   | 0.6694    | 0.6900 | 0.6516 |
| 1.173         | 2.0   | 642  | 0.6933          | 0.7257   | 0.7710    | 0.7257 | 0.7360 |
| 1.035         | 3.0   | 963  | 0.6482          | 0.7611   | 0.7475    | 0.7611 | 0.7234 |
| 0.9945        | 4.0   | 1284 | 0.6027          | 0.7625   | 0.7872    | 0.7625 | 0.7661 |
| 0.9338        | 5.0   | 1605 | 0.6132          | 0.7580   | 0.7989    | 0.7580 | 0.7709 |
| 0.983         | 6.0   | 1926 | 0.6297          | 0.7483   | 0.7977    | 0.7483 | 0.7652 |
| 0.8867        | 7.0   | 2247 | 0.7642          | 0.7021   | 0.7986    | 0.7021 | 0.7286 |
| 0.8273        | 8.0   | 2568 | 0.6594          | 0.7386   | 0.8000    | 0.7386 | 0.7546 |
| 0.7984        | 9.0   | 2889 | 0.5539          | 0.7989   | 0.8082    | 0.7989 | 0.7986 |
| 0.7191        | 10.0  | 3210 | 0.5732          | 0.7715   | 0.8286    | 0.7715 | 0.7848 |
| 0.6859        | 11.0  | 3531 | 0.5409          | 0.8131   | 0.8382    | 0.8131 | 0.8164 |
| 0.5944        | 12.0  | 3852 | 0.6452          | 0.7968   | 0.8273    | 0.7968 | 0.8065 |
| 0.5064        | 13.0  | 4173 | 0.5183          | 0.8381   | 0.8396    | 0.8381 | 0.8356 |
| 0.4759        | 14.0  | 4494 | 0.6007          | 0.8145   | 0.8394    | 0.8145 | 0.8216 |
| 0.4203        | 15.0  | 4815 | 0.5580          | 0.8200   | 0.8412    | 0.8200 | 0.8263 |
| 0.3931        | 16.0  | 5136 | 0.6186          | 0.8027   | 0.8415    | 0.8027 | 0.8145 |
| 0.3076        | 17.0  | 5457 | 0.5484          | 0.8336   | 0.8531    | 0.8336 | 0.8395 |
| 0.2729        | 18.0  | 5778 | 0.5892          | 0.8419   | 0.8495    | 0.8419 | 0.8447 |
| 0.2265        | 19.0  | 6099 | 0.6573          | 0.8325   | 0.8543    | 0.8325 | 0.8386 |
| 0.2685        | 20.0  | 6420 | 0.6374          | 0.8488   | 0.8577    | 0.8488 | 0.8517 |
| 0.1935        | 21.0  | 6741 | 0.6543          | 0.8568   | 0.8559    | 0.8568 | 0.8507 |
| 0.1486        | 22.0  | 7062 | 0.6030          | 0.8665   | 0.8671    | 0.8665 | 0.8657 |
| 0.1628        | 23.0  | 7383 | 0.6315          | 0.8717   | 0.8717    | 0.8717 | 0.8676 |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

akiec bcc bkl df mel nv vasc