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# vit_epochs5_batch64_lr5e-05_size224_tiles1_seed1_classic_image_classification

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: 0.0066
- Accuracy: 0.9990

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0449        | 1.0   | 282  | 0.0183          | 0.9957   |
| 0.04          | 2.0   | 564  | 0.0101          | 0.9981   |
| 0.0303        | 3.0   | 846  | 0.0081          | 0.9985   |
| 0.0489        | 4.0   | 1128 | 0.0068          | 0.9988   |
| 0.0284        | 5.0   | 1410 | 0.0066          | 0.9990   |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

cat dog