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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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4006
- Accuracy: 0.7643

## 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5045        | 0.9998 | 3237 | 0.4944          | 0.7125   |
| 0.4578        | 1.9998 | 6475 | 0.4348          | 0.7457   |
| 0.3922        | 2.9993 | 9711 | 0.4006          | 0.7643   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3

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