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# vit-base-maurice-fp-stanford-dogs

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the maurice-fp/stanford-dogs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6455
- Accuracy: 0.8328

## 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: 6e-05
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8493        | 1.0   | 1029 | 1.6335          | 0.8081   |
| 0.794         | 2.0   | 2058 | 0.8066          | 0.8319   |
| 0.6688        | 3.0   | 3087 | 0.6532          | 0.8411   |
| 0.6161        | 4.0   | 4116 | 0.6464          | 0.8426   |
| 0.5938        | 5.0   | 5145 | 0.6708          | 0.8343   |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.7.0
- Datasets 3.6.0
- Tokenizers 0.21.1

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