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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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4246
- Accuracy: 0.5062

## 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 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2192        | 1.0   | 10   | 1.5404          | 0.4688   |
| 1.1105        | 2.0   | 20   | 1.5094          | 0.4313   |
| 0.9413        | 3.0   | 30   | 1.4630          | 0.4813   |
| 0.7833        | 4.0   | 40   | 1.4246          | 0.5062   |
| 0.6455        | 5.0   | 50   | 1.4159          | 0.5      |
| 0.535         | 6.0   | 60   | 1.4147          | 0.4875   |
| 0.446         | 7.0   | 70   | 1.3981          | 0.4875   |
| 0.3777        | 8.0   | 80   | 1.4239          | 0.4625   |
| 0.3258        | 9.0   | 90   | 1.4240          | 0.4813   |
| 0.2865        | 10.0  | 100  | 1.4302          | 0.475    |
| 0.2579        | 11.0  | 110  | 1.4488          | 0.4688   |
| 0.2371        | 12.0  | 120  | 1.4653          | 0.4688   |
| 0.2228        | 13.0  | 130  | 1.4644          | 0.4875   |
| 0.2135        | 14.0  | 140  | 1.4743          | 0.4688   |
| 0.2083        | 15.0  | 150  | 1.4733          | 0.475    |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3

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