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---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: apwic/indobert-base-uncased-finetuned-nergrit
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. -->
# apwic/indobert-base-uncased-finetuned-nergrit
This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1177
- Validation Loss: 0.1784
- Train Accuracy: 0.9483
- Epoch: 21
## 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2352, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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 | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.4507 | 0.1933 | 0.9437 | 0 |
| 0.1708 | 0.1795 | 0.9471 | 1 |
| 0.1295 | 0.1784 | 0.9483 | 2 |
| 0.1169 | 0.1784 | 0.9483 | 3 |
| 0.1172 | 0.1784 | 0.9483 | 4 |
| 0.1180 | 0.1784 | 0.9483 | 5 |
| 0.1176 | 0.1784 | 0.9483 | 6 |
| 0.1172 | 0.1784 | 0.9483 | 7 |
| 0.1168 | 0.1784 | 0.9483 | 8 |
| 0.1174 | 0.1784 | 0.9483 | 9 |
| 0.1174 | 0.1784 | 0.9483 | 10 |
| 0.1178 | 0.1784 | 0.9483 | 11 |
| 0.1175 | 0.1784 | 0.9483 | 12 |
| 0.1175 | 0.1784 | 0.9483 | 13 |
| 0.1179 | 0.1784 | 0.9483 | 14 |
| 0.1176 | 0.1784 | 0.9483 | 15 |
| 0.1165 | 0.1784 | 0.9483 | 16 |
| 0.1179 | 0.1784 | 0.9483 | 17 |
| 0.1169 | 0.1784 | 0.9483 | 18 |
| 0.1170 | 0.1784 | 0.9483 | 19 |
| 0.1175 | 0.1784 | 0.9483 | 20 |
| 0.1177 | 0.1784 | 0.9483 | 21 |
### Framework versions
- Transformers 4.33.0
- TensorFlow 2.12.0
- Datasets 2.14.6
- Tokenizers 0.13.3
|