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# arieg/4_100_s_200

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: 0.0155
- Validation Loss: 0.0151
- 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': 14400, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.6483     | 0.2667          | 1.0            | 0     |
| 0.1768     | 0.1322          | 1.0            | 1     |
| 0.1096     | 0.0960          | 1.0            | 2     |
| 0.0850     | 0.0781          | 1.0            | 3     |
| 0.0710     | 0.0663          | 1.0            | 4     |
| 0.0612     | 0.0576          | 1.0            | 5     |
| 0.0534     | 0.0506          | 1.0            | 6     |
| 0.0472     | 0.0448          | 1.0            | 7     |
| 0.0420     | 0.0400          | 1.0            | 8     |
| 0.0376     | 0.0359          | 1.0            | 9     |
| 0.0339     | 0.0324          | 1.0            | 10    |
| 0.0306     | 0.0294          | 1.0            | 11    |
| 0.0278     | 0.0267          | 1.0            | 12    |
| 0.0253     | 0.0244          | 1.0            | 13    |
| 0.0232     | 0.0223          | 1.0            | 14    |
| 0.0212     | 0.0205          | 1.0            | 15    |
| 0.0196     | 0.0189          | 1.0            | 16    |
| 0.0180     | 0.0175          | 1.0            | 17    |
| 0.0167     | 0.0162          | 1.0            | 18    |
| 0.0155     | 0.0151          | 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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