---
license: mit
base_model: indobenchmark/indobert-large-p1
tags:
- generated_from_keras_callback
model-index:
- name: aditnnda/gacoan_reviewer
  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/gacoan_reviewer

This model is a fine-tuned version of [indobenchmark/indobert-large-p1](https://huggingface.co/indobenchmark/indobert-large-p1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0001
- Validation Loss: 0.4435
- Train Accuracy: 0.9386
- 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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.2553     | 0.1732          | 0.9331         | 0     |
| 0.0938     | 0.1571          | 0.9400         | 1     |
| 0.0310     | 0.2345          | 0.9386         | 2     |
| 0.0138     | 0.3288          | 0.9358         | 3     |
| 0.0140     | 0.3345          | 0.9177         | 4     |
| 0.0033     | 0.3502          | 0.9386         | 5     |
| 0.0118     | 0.3387          | 0.9344         | 6     |
| 0.0269     | 0.4487          | 0.9024         | 7     |
| 0.0188     | 0.3228          | 0.9331         | 8     |
| 0.0017     | 0.3581          | 0.9372         | 9     |
| 0.0020     | 0.4125          | 0.9233         | 10    |
| 0.0021     | 0.4143          | 0.9247         | 11    |
| 0.0011     | 0.4353          | 0.9303         | 12    |
| 0.0002     | 0.4285          | 0.9344         | 13    |
| 0.0005     | 0.4350          | 0.9344         | 14    |
| 0.0002     | 0.4340          | 0.9344         | 15    |
| 0.0002     | 0.4026          | 0.9400         | 16    |
| 0.0001     | 0.4123          | 0.9414         | 17    |
| 0.0001     | 0.4228          | 0.9414         | 18    |
| 0.0001     | 0.4294          | 0.9386         | 19    |
| 0.0001     | 0.4385          | 0.9386         | 20    |
| 0.0001     | 0.4411          | 0.9386         | 21    |
| 0.0001     | 0.4423          | 0.9386         | 22    |
| 0.0001     | 0.4431          | 0.9386         | 23    |
| 0.0001     | 0.4435          | 0.9386         | 24    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.0
- Tokenizers 0.15.0