
# vit-base-patch16-224-in21k

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1026
- Accuracy: 0.982

## Model description

This model is a fine-tuned version of google/vit-base-patch16-224-in21k which discriminates cats from dogs. 

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.177         | 0.5   | 500  | 0.2100          | 0.9435   |
| 0.1515        | 1.0   | 1000 | 0.0710          | 0.975    |
| 0.0443        | 1.5   | 1500 | 0.2043          | 0.9535   |
| 0.0625        | 2.0   | 2000 | 0.0898          | 0.9745   |
| 0.0181        | 2.5   | 2500 | 0.0961          | 0.9805   |
| 0.0091        | 3.0   | 3000 | 0.1049          | 0.982    |
| 0.0016        | 3.5   | 3500 | 0.1066          | 0.981    |
| 0.0015        | 4.0   | 4000 | 0.1026          | 0.982    |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2

cat dog