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# vit-base-patch16-224-in21k-dogs-cats

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k2](https://huggingface.co/google/vit-base-patch16-224-in21k2) on the Dogs_vs_Cats dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0085
- Accuracy: 0.9984

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0492        | 1.0   | 704  | 0.0150          | 0.9968   |
| 0.0402        | 2.0   | 1408 | 0.0130          | 0.9968   |
| 0.0511        | 3.0   | 2112 | 0.0106          | 0.9968   |
| 0.017         | 4.0   | 2816 | 0.0102          | 0.998    |
| 0.0149        | 5.0   | 3520 | 0.0124          | 0.9968   |
| 0.0517        | 6.0   | 4224 | 0.0085          | 0.9984   |
| 0.0373        | 7.0   | 4928 | 0.0132          | 0.9972   |
| 0.0168        | 8.0   | 5632 | 0.0099          | 0.998    |
| 0.0095        | 9.0   | 6336 | 0.0096          | 0.9976   |
| 0.0226        | 10.0  | 7040 | 0.0107          | 0.998    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1

cat dog