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# vit-weight-decay-1e-4

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: 0.5277
- Accuracy: 0.8263
- Precision: 0.8467
- Recall: 0.8263
- F1: 0.8324

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.7856        | 1.0   | 321  | 0.9535          | 0.6869   | 0.6412    | 0.6869 | 0.6229 |
| 1.1412        | 2.0   | 642  | 0.6928          | 0.7424   | 0.7440    | 0.7424 | 0.7311 |
| 1.0297        | 3.0   | 963  | 0.6863          | 0.7490   | 0.7362    | 0.7490 | 0.7057 |
| 0.9571        | 4.0   | 1284 | 0.5587          | 0.7694   | 0.7901    | 0.7694 | 0.7736 |
| 0.9346        | 5.0   | 1605 | 0.5654          | 0.7940   | 0.8058    | 0.7940 | 0.7919 |
| 0.9802        | 6.0   | 1926 | 0.6318          | 0.7746   | 0.7928    | 0.7746 | 0.7794 |
| 0.8352        | 7.0   | 2247 | 0.6611          | 0.7295   | 0.8145    | 0.7295 | 0.7498 |
| 0.7621        | 8.0   | 2568 | 0.5766          | 0.7666   | 0.8162    | 0.7666 | 0.7781 |
| 0.7352        | 9.0   | 2889 | 0.5369          | 0.7996   | 0.8269    | 0.7996 | 0.8079 |
| 0.6919        | 10.0  | 3210 | 0.5500          | 0.7753   | 0.8270    | 0.7753 | 0.7900 |
| 0.6105        | 11.0  | 3531 | 0.5562          | 0.8062   | 0.8310    | 0.8062 | 0.8129 |
| 0.5808        | 12.0  | 3852 | 0.6608          | 0.7708   | 0.8278    | 0.7708 | 0.7871 |
| 0.4534        | 13.0  | 4173 | 0.5684          | 0.8301   | 0.8483    | 0.8301 | 0.8291 |
| 0.4519        | 14.0  | 4494 | 0.5928          | 0.8121   | 0.8388    | 0.8121 | 0.8201 |
| 0.3998        | 15.0  | 4815 | 0.5277          | 0.8263   | 0.8467    | 0.8263 | 0.8324 |
| 0.3307        | 16.0  | 5136 | 0.5944          | 0.8266   | 0.8458    | 0.8266 | 0.8330 |
| 0.2899        | 17.0  | 5457 | 0.5387          | 0.8526   | 0.8546    | 0.8526 | 0.8524 |
| 0.2466        | 18.0  | 5778 | 0.5559          | 0.8495   | 0.8541    | 0.8495 | 0.8506 |
| 0.201         | 19.0  | 6099 | 0.6360          | 0.8336   | 0.8671    | 0.8336 | 0.8427 |
| 0.2163        | 20.0  | 6420 | 0.6009          | 0.8599   | 0.8575    | 0.8599 | 0.8581 |
| 0.1614        | 21.0  | 6741 | 0.5804          | 0.8689   | 0.8648    | 0.8689 | 0.8630 |
| 0.1106        | 22.0  | 7062 | 0.5798          | 0.8689   | 0.8661    | 0.8689 | 0.8670 |
| 0.1243        | 23.0  | 7383 | 0.6228          | 0.8703   | 0.8686    | 0.8703 | 0.8672 |
| 0.1251        | 24.0  | 7704 | 0.5987          | 0.8727   | 0.8695    | 0.8727 | 0.8698 |
| 0.1038        | 25.0  | 8025 | 0.5806          | 0.8769   | 0.8756    | 0.8769 | 0.8753 |


### Framework versions

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

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