
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# leopuv/cats_vs_dogs_classifier

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0285
- Train Accuracy: 0.9865
- Validation Loss: 0.0340
- Validation Accuracy: 0.9865
- Epoch: 9

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 80000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.1739     | 0.9715         | 0.0787          | 0.9715              | 0     |
| 0.0744     | 0.984          | 0.0432          | 0.9840              | 1     |
| 0.0543     | 0.9895         | 0.0365          | 0.9895              | 2     |
| 0.0420     | 0.9885         | 0.0346          | 0.9885              | 3     |
| 0.0402     | 0.9855         | 0.0414          | 0.9855              | 4     |
| 0.0378     | 0.9885         | 0.0307          | 0.9885              | 5     |
| 0.0306     | 0.9855         | 0.0375          | 0.9855              | 6     |
| 0.0343     | 0.987          | 0.0402          | 0.9870              | 7     |
| 0.0283     | 0.9875         | 0.0381          | 0.9875              | 8     |
| 0.0285     | 0.9865         | 0.0340          | 0.9865              | 9     |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3
cat dog