---
library_name: transformers
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraPJOK_1_100_Full
  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. -->

# Labira/LabiraPJOK_1_100_Full

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: 0.0992
- Validation Loss: 0.1051
- Epoch: 48

## 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': 400, '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 | Epoch |
|:----------:|:---------------:|:-----:|
| 5.7712     | 5.1521          | 0     |
| 4.8965     | 4.2303          | 1     |
| 4.1582     | 3.5226          | 2     |
| 3.4388     | 2.9489          | 3     |
| 2.8492     | 2.4067          | 4     |
| 2.5532     | 2.0347          | 5     |
| 2.1511     | 1.5826          | 6     |
| 1.7456     | 1.1703          | 7     |
| 1.3312     | 1.1496          | 8     |
| 1.1274     | 0.7130          | 9     |
| 0.9445     | 0.6299          | 10    |
| 0.8513     | 0.4422          | 11    |
| 0.8144     | 0.6906          | 12    |
| 0.6876     | 0.3412          | 13    |
| 0.6116     | 0.2922          | 14    |
| 0.5507     | 0.3807          | 15    |
| 0.5042     | 0.2770          | 16    |
| 0.2865     | 0.1692          | 17    |
| 0.4181     | 0.1840          | 18    |
| 0.3010     | 0.2490          | 19    |
| 0.3049     | 0.1310          | 20    |
| 0.4021     | 0.1106          | 21    |
| 0.4394     | 0.5673          | 22    |
| 0.3956     | 0.4617          | 23    |
| 0.3175     | 0.1589          | 24    |
| 0.2753     | 0.1354          | 25    |
| 0.1207     | 0.1039          | 26    |
| 0.1652     | 0.0881          | 27    |
| 0.2387     | 0.1040          | 28    |
| 0.1674     | 0.1306          | 29    |
| 0.1609     | 0.1319          | 30    |
| 0.1121     | 0.1215          | 31    |
| 0.1457     | 0.1124          | 32    |
| 0.1767     | 0.1144          | 33    |
| 0.1225     | 0.1322          | 34    |
| 0.1313     | 0.1385          | 35    |
| 0.1473     | 0.1586          | 36    |
| 0.2459     | 0.1693          | 37    |
| 0.1657     | 0.1705          | 38    |
| 0.1716     | 0.1314          | 39    |
| 0.1124     | 0.1108          | 40    |
| 0.1493     | 0.1058          | 41    |
| 0.1312     | 0.1161          | 42    |
| 0.1232     | 0.1264          | 43    |
| 0.1169     | 0.1181          | 44    |
| 0.1268     | 0.1092          | 45    |
| 0.0955     | 0.1074          | 46    |
| 0.1465     | 0.1051          | 47    |
| 0.0992     | 0.1051          | 48    |


### Framework versions

- Transformers 4.46.2
- TensorFlow 2.17.0
- Datasets 3.1.0
- Tokenizers 0.20.3