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# Chess_images_classifier

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0591
- Accuracy: 0.9

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 1.7966          | 0.1      |
| No log        | 2.0   | 4    | 1.7835          | 0.2      |
| No log        | 3.0   | 6    | 1.7547          | 0.2667   |
| No log        | 4.0   | 8    | 1.7069          | 0.3667   |
| 1.7198        | 5.0   | 10   | 1.6416          | 0.3667   |
| 1.7198        | 6.0   | 12   | 1.5306          | 0.4      |
| 1.7198        | 7.0   | 14   | 1.4958          | 0.5333   |
| 1.7198        | 8.0   | 16   | 1.4440          | 0.5333   |
| 1.7198        | 9.0   | 18   | 1.3930          | 0.6      |
| 1.3635        | 10.0  | 20   | 1.2984          | 0.7333   |
| 1.3635        | 11.0  | 22   | 1.3484          | 0.7333   |
| 1.3635        | 12.0  | 24   | 1.2727          | 0.8333   |
| 1.3635        | 13.0  | 26   | 1.1674          | 0.8333   |
| 1.3635        | 14.0  | 28   | 1.1443          | 0.8667   |
| 1.0916        | 15.0  | 30   | 1.1607          | 0.9      |
| 1.0916        | 16.0  | 32   | 1.1076          | 0.8667   |
| 1.0916        | 17.0  | 34   | 1.0670          | 0.9667   |
| 1.0916        | 18.0  | 36   | 1.0694          | 0.9333   |
| 1.0916        | 19.0  | 38   | 1.0874          | 0.9      |
| 0.9397        | 20.0  | 40   | 1.0591          | 0.9      |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

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