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# results

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: 1.4603
- Accuracy: 0.4562

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2036        | 1.0   | 10   | 1.5604          | 0.425    |
| 1.007         | 2.0   | 20   | 1.4904          | 0.4313   |
| 0.8453        | 3.0   | 30   | 1.4603          | 0.4625   |
| 0.6992        | 4.0   | 40   | 1.4409          | 0.4562   |
| 0.5703        | 5.0   | 50   | 1.4206          | 0.4688   |
| 0.4656        | 6.0   | 60   | 1.4128          | 0.4625   |
| 0.3896        | 7.0   | 70   | 1.4181          | 0.4625   |
| 0.3274        | 8.0   | 80   | 1.4162          | 0.475    |
| 0.2839        | 9.0   | 90   | 1.4199          | 0.45     |
| 0.2512        | 10.0  | 100  | 1.4261          | 0.4625   |
| 0.2278        | 11.0  | 110  | 1.4347          | 0.4625   |
| 0.2106        | 12.0  | 120  | 1.4319          | 0.4688   |
| 0.1973        | 13.0  | 130  | 1.4400          | 0.4688   |
| 0.1874        | 14.0  | 140  | 1.4453          | 0.4625   |
| 0.1797        | 15.0  | 150  | 1.4488          | 0.4562   |
| 0.1738        | 16.0  | 160  | 1.4542          | 0.4562   |
| 0.1693        | 17.0  | 170  | 1.4592          | 0.4625   |
| 0.166         | 18.0  | 180  | 1.4602          | 0.4562   |
| 0.1638        | 19.0  | 190  | 1.4607          | 0.4562   |
| 0.1627        | 20.0  | 200  | 1.4603          | 0.4562   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0

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