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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: Remunata/rupiah_classifier_v2
results: []
---
<!-- 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. -->
# 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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