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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 the pcuenq/oxford-pets dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4728
- Accuracy: 0.6067

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.588         | 1.0   | 184  | 3.2349          | 0.1522   |
| 3.0928        | 2.0   | 368  | 2.8819          | 0.3478   |
| 2.7571        | 3.0   | 552  | 2.6433          | 0.5149   |
| 2.5459        | 4.0   | 736  | 2.5048          | 0.6019   |
| 2.4484        | 5.0   | 920  | 2.4601          | 0.6155   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1

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