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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: 0.1989
- Accuracy: 0.9405

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3785        | 1.0   | 370  | 0.2845          | 0.9310   |
| 0.2124        | 2.0   | 740  | 0.2249          | 0.9296   |
| 0.163         | 3.0   | 1110 | 0.2004          | 0.9432   |
| 0.1401        | 4.0   | 1480 | 0.1967          | 0.9418   |
| 0.138         | 5.0   | 1850 | 0.1937          | 0.9445   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0
- Datasets 3.6.0
- Tokenizers 0.21.1

british shorthair beagle scottish terrier persian birman siamese basset hound pug staffordshire bull terrier chihuahua sphynx ragdoll wheaten terrier keeshond egyptian mau havanese miniature pinscher german shorthaired american bulldog shiba inu english cocker spaniel pomeranian yorkshire terrier american pit bull terrier saint bernard english setter russian blue japanese chin great pyrenees maine coon bombay newfoundland samoyed boxer leonberger bengal abyssinian