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# vit-sports-cls

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: 0.0838
- Accuracy: 0.9742
- Precision: 0.9743
- Recall: 0.9742
- F1: 0.9741

## 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.171         | 1.0   | 104  | 0.1729          | 0.9489   | 0.9493    | 0.9489 | 0.9489 |
| 0.0979        | 2.0   | 208  | 0.1356          | 0.9585   | 0.9597    | 0.9585 | 0.9583 |
| 0.0408        | 3.0   | 312  | 0.1184          | 0.9561   | 0.9571    | 0.9561 | 0.9561 |
| 0.0703        | 4.0   | 416  | 0.0892          | 0.9700   | 0.9701    | 0.9700 | 0.9699 |
| 0.1375        | 5.0   | 520  | 0.1029          | 0.9681   | 0.9683    | 0.9681 | 0.9682 |
| 0.0061        | 6.0   | 624  | 0.1073          | 0.9681   | 0.9688    | 0.9681 | 0.9682 |
| 0.0083        | 7.0   | 728  | 0.0795          | 0.9700   | 0.9701    | 0.9700 | 0.9700 |
| 0.0079        | 8.0   | 832  | 0.0754          | 0.9814   | 0.9816    | 0.9814 | 0.9814 |
| 0.0594        | 9.0   | 936  | 0.0714          | 0.9754   | 0.9756    | 0.9754 | 0.9754 |
| 0.0391        | 10.0  | 1040 | 0.0838          | 0.9742   | 0.9743    | 0.9742 | 0.9741 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0

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