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---
library_name: transformers
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraPJOK_1_50
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_50
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: 0.1065
- Validation Loss: 7.1445
- Epoch: 45
## 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': 150, '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 |
|:----------:|:---------------:|:-----:|
| 1.6494 | 4.1520 | 0 |
| 1.6128 | 4.3365 | 1 |
| 1.2043 | 4.6166 | 2 |
| 1.1480 | 4.5769 | 3 |
| 1.0336 | 5.1587 | 4 |
| 0.8954 | 5.2969 | 5 |
| 0.7306 | 5.4294 | 6 |
| 0.7589 | 5.2671 | 7 |
| 0.5728 | 5.2392 | 8 |
| 0.6026 | 5.6260 | 9 |
| 0.3001 | 6.3308 | 10 |
| 0.3688 | 6.4235 | 11 |
| 0.2650 | 5.8635 | 12 |
| 0.3598 | 5.5841 | 13 |
| 0.2204 | 5.8293 | 14 |
| 0.2078 | 6.1692 | 15 |
| 0.1080 | 6.4491 | 16 |
| 0.1985 | 6.4271 | 17 |
| 0.0852 | 6.2699 | 18 |
| 0.1295 | 6.3012 | 19 |
| 0.0857 | 6.6709 | 20 |
| 0.0957 | 7.0530 | 21 |
| 0.0843 | 7.2611 | 22 |
| 0.2785 | 7.1146 | 23 |
| 0.0894 | 6.9268 | 24 |
| 0.1080 | 7.1326 | 25 |
| 0.0535 | 7.5213 | 26 |
| 0.3044 | 7.5237 | 27 |
| 0.1145 | 7.3478 | 28 |
| 0.0558 | 7.2094 | 29 |
| 0.1047 | 7.0415 | 30 |
| 0.0498 | 7.0443 | 31 |
| 0.1680 | 7.0692 | 32 |
| 0.1997 | 7.1370 | 33 |
| 0.0362 | 7.1806 | 34 |
| 0.0332 | 7.2268 | 35 |
| 0.0596 | 7.2691 | 36 |
| 0.0537 | 7.2544 | 37 |
| 0.0422 | 7.1536 | 38 |
| 0.0460 | 7.1102 | 39 |
| 0.0542 | 7.0963 | 40 |
| 0.0390 | 7.1052 | 41 |
| 0.2518 | 7.1087 | 42 |
| 0.1056 | 7.1267 | 43 |
| 0.0403 | 7.1337 | 44 |
| 0.1065 | 7.1445 | 45 |
### Framework versions
- Transformers 4.44.2
- TensorFlow 2.17.0
- Datasets 3.0.1
- Tokenizers 0.19.1
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