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# vit-base-patch16-224-in21k-dogs-cats2

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the Dogs_vs_Cats dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0111
- Accuracy: 0.9968

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0691        | 1.0   | 625  | 0.0187          | 0.995    |
| 0.0332        | 2.0   | 1250 | 0.0147          | 0.9958   |
| 0.0446        | 3.0   | 1875 | 0.0139          | 0.9946   |
| 0.0241        | 4.0   | 2500 | 0.0178          | 0.9952   |
| 0.0412        | 5.0   | 3125 | 0.0117          | 0.9968   |
| 0.0683        | 6.0   | 3750 | 0.0168          | 0.995    |
| 0.0081        | 7.0   | 4375 | 0.0143          | 0.9962   |
| 0.0316        | 8.0   | 5000 | 0.0111          | 0.9968   |
| 0.0184        | 9.0   | 5625 | 0.0124          | 0.9968   |
| 0.021         | 10.0  | 6250 | 0.0128          | 0.9964   |


### Framework versions

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

cat dog