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# Remunata/rupiah_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: 0.1165
- Train Accuracy: 0.9065
- Validation Loss: 0.4728
- Validation Accuracy: 0.9065
- Epoch: 14

## 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 70950, '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 | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 1.0522     | 0.8485         | 0.6303          | 0.8485              | 0     |
| 0.3967     | 0.8838         | 0.4676          | 0.8838              | 1     |
| 0.2908     | 0.8956         | 0.4541          | 0.8956              | 2     |
| 0.2311     | 0.8675         | 0.5276          | 0.8675              | 3     |
| 0.1810     | 0.8956         | 0.4133          | 0.8956              | 4     |
| 0.1782     | 0.8929         | 0.4567          | 0.8929              | 5     |
| 0.1617     | 0.8730         | 0.5800          | 0.8730              | 6     |
| 0.1442     | 0.9047         | 0.4201          | 0.9047              | 7     |
| 0.1471     | 0.9102         | 0.4024          | 0.9102              | 8     |
| 0.1149     | 0.9093         | 0.4297          | 0.9093              | 9     |
| 0.1198     | 0.9056         | 0.4753          | 0.9056              | 10    |
| 0.1132     | 0.9056         | 0.4562          | 0.9056              | 11    |
| 0.1132     | 0.9102         | 0.3935          | 0.9102              | 12    |
| 0.1015     | 0.9056         | 0.4687          | 0.9056              | 13    |
| 0.1165     | 0.9065         | 0.4728          | 0.9065              | 14    |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.19.2
- Tokenizers 0.19.1

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