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# results

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4656
- Accuracy: 0.8125
- F1: 0.8141

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 17   | 0.8876          | 0.5865   | 0.5688 |
| No log        | 2.0   | 34   | 0.8620          | 0.6090   | 0.6067 |
| No log        | 3.0   | 51   | 0.7611          | 0.6842   | 0.6783 |
| No log        | 4.0   | 68   | 0.6987          | 0.6842   | 0.6741 |
| No log        | 5.0   | 85   | 0.6540          | 0.6917   | 0.6872 |
| No log        | 6.0   | 102  | 0.7933          | 0.6767   | 0.6407 |
| No log        | 7.0   | 119  | 0.4766          | 0.8195   | 0.8152 |
| No log        | 8.0   | 136  | 0.4624          | 0.8271   | 0.8231 |
| No log        | 9.0   | 153  | 0.4528          | 0.8271   | 0.8277 |
| No log        | 10.0  | 170  | 0.4641          | 0.8120   | 0.8087 |
| No log        | 11.0  | 187  | 0.6063          | 0.7368   | 0.7231 |
| No log        | 12.0  | 204  | 0.4783          | 0.7594   | 0.7596 |
| No log        | 13.0  | 221  | 0.4987          | 0.7970   | 0.7990 |
| No log        | 14.0  | 238  | 0.6023          | 0.7669   | 0.7603 |
| No log        | 15.0  | 255  | 0.4588          | 0.8271   | 0.8254 |
| No log        | 16.0  | 272  | 0.4362          | 0.8120   | 0.8130 |
| No log        | 17.0  | 289  | 0.5342          | 0.8271   | 0.8280 |
| No log        | 18.0  | 306  | 0.5012          | 0.8120   | 0.8124 |
| No log        | 19.0  | 323  | 0.4891          | 0.8496   | 0.8498 |
| No log        | 20.0  | 340  | 0.8525          | 0.7744   | 0.7714 |
| No log        | 21.0  | 357  | 0.5291          | 0.8195   | 0.8209 |
| No log        | 22.0  | 374  | 0.5355          | 0.8271   | 0.8264 |
| No log        | 23.0  | 391  | 0.6323          | 0.8045   | 0.8041 |
| No log        | 24.0  | 408  | 0.6973          | 0.8346   | 0.8334 |
| No log        | 25.0  | 425  | 0.6705          | 0.8571   | 0.8569 |
| No log        | 26.0  | 442  | 0.6056          | 0.8571   | 0.8572 |
| No log        | 27.0  | 459  | 0.7864          | 0.8421   | 0.8421 |
| No log        | 28.0  | 476  | 0.7067          | 0.8346   | 0.8351 |
| No log        | 29.0  | 493  | 0.6695          | 0.8571   | 0.8567 |
| 0.3504        | 30.0  | 510  | 0.6680          | 0.8647   | 0.8646 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0

label_0 label_1 label_2