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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
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
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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