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# vit-base-oxford-iiit-pets

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: 0.0960
- Accuracy: 0.9718

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1163        | 1.0   | 2500  | 0.1026          | 0.9676   |
| 0.102         | 2.0   | 5000  | 0.0978          | 0.9708   |
| 0.0798        | 3.0   | 7500  | 0.0954          | 0.9728   |
| 0.0625        | 4.0   | 10000 | 0.0954          | 0.972    |
| 0.0669        | 5.0   | 12500 | 0.0952          | 0.9728   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1

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