---
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_keras_callback
model-index:
- name: aditnnda/gacoanReviewer
  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. -->

# aditnnda/gacoanReviewer

This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co./indobenchmark/indobert-base-p1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0001
- Validation Loss: 0.5471
- Train Accuracy: 0.9163
- Epoch: 24

## 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3550, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.2751     | 0.2043          | 0.9107         | 0     |
| 0.1202     | 0.2077          | 0.9177         | 1     |
| 0.0583     | 0.2770          | 0.9079         | 2     |
| 0.0435     | 0.3412          | 0.9066         | 3     |
| 0.0251     | 0.3762          | 0.9079         | 4     |
| 0.0208     | 0.2241          | 0.9303         | 5     |
| 0.0070     | 0.2794          | 0.9317         | 6     |
| 0.0151     | 0.3823          | 0.9219         | 7     |
| 0.0088     | 0.3740          | 0.9261         | 8     |
| 0.0019     | 0.4286          | 0.9261         | 9     |
| 0.0030     | 0.6086          | 0.8912         | 10    |
| 0.0052     | 0.4023          | 0.9344         | 11    |
| 0.0005     | 0.5193          | 0.9121         | 12    |
| 0.0002     | 0.5171          | 0.9135         | 13    |
| 0.0002     | 0.5276          | 0.9163         | 14    |
| 0.0002     | 0.5344          | 0.9135         | 15    |
| 0.0002     | 0.5362          | 0.9163         | 16    |
| 0.0001     | 0.5407          | 0.9163         | 17    |
| 0.0001     | 0.5406          | 0.9163         | 18    |
| 0.0001     | 0.5484          | 0.9149         | 19    |
| 0.0001     | 0.5406          | 0.9177         | 20    |
| 0.0001     | 0.5431          | 0.9177         | 21    |
| 0.0001     | 0.5453          | 0.9163         | 22    |
| 0.0001     | 0.5466          | 0.9163         | 23    |
| 0.0001     | 0.5471          | 0.9163         | 24    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.15.0
- Tokenizers 0.15.0