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# arieg/4_100_s

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: 0.0361
- Validation Loss: 0.0352
- Train Accuracy: 1.0
- Epoch: 19

## 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', 'clipnorm': 1.0, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 7200, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.9729     | 0.5902          | 1.0            | 0     |
| 0.4190     | 0.2874          | 1.0            | 1     |
| 0.2212     | 0.1722          | 1.0            | 2     |
| 0.1512     | 0.1305          | 1.0            | 3     |
| 0.1192     | 0.1058          | 1.0            | 4     |
| 0.1007     | 0.0926          | 1.0            | 5     |
| 0.0885     | 0.0827          | 1.0            | 6     |
| 0.0796     | 0.0753          | 1.0            | 7     |
| 0.0726     | 0.0689          | 1.0            | 8     |
| 0.0668     | 0.0636          | 1.0            | 9     |
| 0.0620     | 0.0594          | 1.0            | 10    |
| 0.0578     | 0.0554          | 1.0            | 11    |
| 0.0541     | 0.0524          | 1.0            | 12    |
| 0.0507     | 0.0494          | 1.0            | 13    |
| 0.0477     | 0.0459          | 1.0            | 14    |
| 0.0450     | 0.0436          | 1.0            | 15    |
| 0.0425     | 0.0413          | 1.0            | 16    |
| 0.0402     | 0.0392          | 1.0            | 17    |
| 0.0380     | 0.0371          | 1.0            | 18    |
| 0.0361     | 0.0352          | 1.0            | 19    |


### Framework versions

- Transformers 4.35.0
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1

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