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# vit-base-patch16-224-v21

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0347
- Accuracy: 0.99

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2951        | 1.0   | 190  | 0.1895          | 0.9333   |
| 0.2013        | 2.0   | 380  | 0.0813          | 0.9726   |
| 0.1935        | 3.0   | 570  | 0.0902          | 0.9681   |
| 0.1858        | 4.0   | 760  | 0.0916          | 0.9674   |
| 0.118         | 5.0   | 950  | 0.0481          | 0.9833   |
| 0.0834        | 6.0   | 1140 | 0.0578          | 0.9841   |
| 0.0986        | 7.0   | 1330 | 0.0418          | 0.9870   |
| 0.0737        | 8.0   | 1520 | 0.0347          | 0.99     |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3

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