|
--- |
|
license: mit |
|
base_model: cahya/bert-base-indonesian-522M |
|
tags: |
|
- generated_from_keras_callback |
|
model-index: |
|
- name: racheilla/bert-base-indonesian-522M-finetuned-pemilu |
|
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. --> |
|
|
|
# racheilla/bert-base-indonesian-522M-finetuned-pemilu |
|
|
|
This model is a fine-tuned version of [cahya/bert-base-indonesian-522M](https://huggingface.co/cahya/bert-base-indonesian-522M) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Train Loss: 3.3171 |
|
- Validation Loss: 3.4078 |
|
- Epoch: 37 |
|
|
|
## 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': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -950, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
|
- training_precision: mixed_float16 |
|
|
|
### Training results |
|
|
|
| Train Loss | Validation Loss | Epoch | |
|
|:----------:|:---------------:|:-----:| |
|
| 3.2847 | 3.4266 | 0 | |
|
| 3.3000 | 3.4116 | 1 | |
|
| 3.2702 | 3.3975 | 2 | |
|
| 3.2675 | 3.4689 | 3 | |
|
| 3.2982 | 3.3540 | 4 | |
|
| 3.3109 | 3.4127 | 5 | |
|
| 3.2698 | 3.4126 | 6 | |
|
| 3.2852 | 3.4165 | 7 | |
|
| 3.2977 | 3.3816 | 8 | |
|
| 3.2749 | 3.3923 | 9 | |
|
| 3.2777 | 3.3841 | 10 | |
|
| 3.2555 | 3.4534 | 11 | |
|
| 3.2940 | 3.4194 | 12 | |
|
| 3.2860 | 3.3810 | 13 | |
|
| 3.2585 | 3.3328 | 14 | |
|
| 3.2979 | 3.4310 | 15 | |
|
| 3.2844 | 3.4374 | 16 | |
|
| 3.2961 | 3.3630 | 17 | |
|
| 3.2729 | 3.4132 | 18 | |
|
| 3.2775 | 3.4114 | 19 | |
|
| 3.2561 | 3.3869 | 20 | |
|
| 3.3089 | 3.4583 | 21 | |
|
| 3.2839 | 3.4010 | 22 | |
|
| 3.2863 | 3.4335 | 23 | |
|
| 3.2347 | 3.4040 | 24 | |
|
| 3.2691 | 3.3805 | 25 | |
|
| 3.2779 | 3.4005 | 26 | |
|
| 3.3175 | 3.3627 | 27 | |
|
| 3.2853 | 3.3995 | 28 | |
|
| 3.2787 | 3.3904 | 29 | |
|
| 3.2739 | 3.4169 | 30 | |
|
| 3.2976 | 3.3728 | 31 | |
|
| 3.2474 | 3.4051 | 32 | |
|
| 3.3152 | 3.3760 | 33 | |
|
| 3.2939 | 3.4185 | 34 | |
|
| 3.2955 | 3.3978 | 35 | |
|
| 3.2823 | 3.3749 | 36 | |
|
| 3.3171 | 3.4078 | 37 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- TensorFlow 2.15.0 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|