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# trainer_output

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3427
- Accuracy: 0.8776

## 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: 0.001
- train_batch_size: 20
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 39   | 0.4124          | 0.7938   |
| No log        | 2.0   | 78   | 0.3294          | 0.8454   |
| 0.4497        | 3.0   | 117  | 0.2932          | 0.8454   |
| 0.4497        | 4.0   | 156  | 0.2799          | 0.8557   |
| 0.4497        | 5.0   | 195  | 0.2692          | 0.8969   |
| 0.2764        | 6.0   | 234  | 0.2604          | 0.8969   |
| 0.2764        | 7.0   | 273  | 0.2583          | 0.9175   |
| 0.2192        | 8.0   | 312  | 0.2546          | 0.9072   |
| 0.2192        | 9.0   | 351  | 0.2506          | 0.9072   |
| 0.2192        | 10.0  | 390  | 0.2536          | 0.9072   |
| 0.1936        | 11.0  | 429  | 0.2530          | 0.8866   |
| 0.1936        | 12.0  | 468  | 0.2503          | 0.9072   |
| 0.1731        | 13.0  | 507  | 0.2480          | 0.9072   |
| 0.1731        | 14.0  | 546  | 0.2496          | 0.9072   |
| 0.1731        | 15.0  | 585  | 0.2498          | 0.9072   |
| 0.155         | 16.0  | 624  | 0.2498          | 0.9072   |
| 0.155         | 17.0  | 663  | 0.2495          | 0.9072   |
| 0.1442        | 18.0  | 702  | 0.2488          | 0.9072   |
| 0.1442        | 19.0  | 741  | 0.2493          | 0.9072   |
| 0.1442        | 20.0  | 780  | 0.2490          | 0.9072   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1

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