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# Remunata/rupiah_classifier_v2

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: 0.1314
- Train Accuracy: 0.9379
- Validation Loss: 0.2477
- Validation Accuracy: 0.9379
- 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 66500, '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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.9566     | 0.8213         | 0.6179          | 0.8213              | 0     |
| 0.3346     | 0.8828         | 0.4223          | 0.8828              | 1     |
| 0.2572     | 0.9048         | 0.3674          | 0.9048              | 2     |
| 0.2092     | 0.9181         | 0.3146          | 0.9181              | 3     |
| 0.1856     | 0.9112         | 0.3320          | 0.9112              | 4     |
| 0.1722     | 0.8999         | 0.4168          | 0.8999              | 5     |
| 0.1564     | 0.9406         | 0.2184          | 0.9406              | 6     |
| 0.1402     | 0.8935         | 0.4184          | 0.8935              | 7     |
| 0.1352     | 0.9230         | 0.2832          | 0.9230              | 8     |
| 0.1314     | 0.9379         | 0.2477          | 0.9379              | 9     |


### Framework versions

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

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