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# vit-base-roman-numeral

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 farleyknight/roman_numerals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6891
- Accuracy: 0.8309

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9053        | 1.0   | 289  | 1.3241          | 0.7108   |
| 1.3293        | 2.0   | 578  | 0.9333          | 0.7892   |
| 1.1251        | 3.0   | 867  | 0.7989          | 0.7843   |
| 0.9837        | 4.0   | 1156 | 0.6956          | 0.8186   |
| 0.999         | 5.0   | 1445 | 0.6891          | 0.8309   |


### Framework versions

- Transformers 4.22.0.dev0
- Pytorch 1.11.0a0+17540c5
- Datasets 2.4.0
- Tokenizers 0.12.1

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