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---
library_name: transformers
license: mit
base_model: cahya/bert-base-indonesian-1.5G
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-base-indonesian-1.5G-multilabel-indonesian-hate-speech-new
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-indonesian-1.5G-multilabel-indonesian-hate-speech-new
This model is a fine-tuned version of [cahya/bert-base-indonesian-1.5G](https://huggingface.co/cahya/bert-base-indonesian-1.5G) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3641
- F1: 0.7802
- Roc Auc: 0.8639
- Accuracy: 0.7156
## 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:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.3106 | 1.0 | 659 | 0.2504 | 0.6779 | 0.7832 | 0.5978 |
| 0.2235 | 2.0 | 1318 | 0.2113 | 0.7466 | 0.8392 | 0.6441 |
| 0.1722 | 3.0 | 1977 | 0.2283 | 0.7511 | 0.8493 | 0.6581 |
| 0.097 | 4.0 | 2636 | 0.2421 | 0.7626 | 0.8490 | 0.6874 |
| 0.0643 | 5.0 | 3295 | 0.2727 | 0.7584 | 0.8417 | 0.6938 |
| 0.0572 | 6.0 | 3954 | 0.2817 | 0.7662 | 0.8662 | 0.6737 |
| 0.0304 | 7.0 | 4613 | 0.3075 | 0.7606 | 0.8475 | 0.6879 |
| 0.021 | 8.0 | 5272 | 0.3195 | 0.7697 | 0.8626 | 0.6932 |
| 0.0157 | 9.0 | 5931 | 0.3347 | 0.7663 | 0.8477 | 0.7052 |
| 0.0095 | 10.0 | 6590 | 0.3353 | 0.7759 | 0.8598 | 0.7118 |
| 0.0086 | 11.0 | 7249 | 0.3467 | 0.7768 | 0.8590 | 0.7136 |
| 0.0063 | 12.0 | 7908 | 0.3503 | 0.7795 | 0.8644 | 0.7128 |
| 0.0046 | 13.0 | 8567 | 0.3577 | 0.7797 | 0.8613 | 0.7153 |
| 0.0037 | 14.0 | 9226 | 0.3622 | 0.7801 | 0.8674 | 0.7115 |
| 0.0046 | 15.0 | 9885 | 0.3641 | 0.7802 | 0.8639 | 0.7156 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
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