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indobert-base-p1-multilabel-indonesian-hate-speech-modified
PaceKW/indobert-base-p1-multilabel-indonesian-hate-speech-modified
indobert-base-p1-multilabel-indonesian-hate-speech-modified is a machine learning model from PaceKW. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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Updated Jun 17, 2025
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At a glance
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Jun 17, 2025
- Updated
- Jun 17, 2025
- SHA
- 070573c0
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
indobert-base-p1-multilabel-indonesian-hate-speech-modified
This model is a fine-tuned version of indobenchmark/indobert-base-p1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3655
- F1: 0.8170
- Roc Auc: 0.8883
- Accuracy: 0.7608
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 |
|---|---|---|---|---|---|---|
| 0.2112 | 1.0 | 1317 | 0.1797 | 0.7887 | 0.8552 | 0.7039 |
| 0.1389 | 2.0 | 2634 | 0.1804 | 0.7946 | 0.8742 | 0.6872 |
| 0.0838 | 3.0 | 3951 | 0.1981 | 0.8152 | 0.8825 | 0.7403 |
| 0.0529 | 4.0 | 5268 | 0.2520 | 0.8036 | 0.8671 | 0.7434 |
| 0.0349 | 5.0 | 6585 | 0.2577 | 0.8065 | 0.8908 | 0.7244 |
| 0.0203 | 6.0 | 7902 | 0.2994 | 0.7986 | 0.8776 | 0.7198 |
| 0.0154 | 7.0 | 9219 | 0.3155 | 0.8086 | 0.8927 | 0.7434 |
| 0.0112 | 8.0 | 10536 | 0.3284 | 0.8070 | 0.8789 | 0.7540 |
| 0.0061 | 9.0 | 11853 | 0.3507 | 0.8065 | 0.8782 | 0.7525 |
| 0.0079 | 10.0 | 13170 | 0.3514 | 0.8091 | 0.8956 | 0.7396 |
| 0.0052 | 11.0 | 14487 | 0.3420 | 0.8135 | 0.8854 | 0.7608 |
| 0.0047 | 12.0 | 15804 | 0.3503 | 0.8164 | 0.8842 | 0.7608 |
| 0.0046 | 13.0 | 17121 | 0.3558 | 0.8165 | 0.8871 | 0.7616 |
| 0.0014 | 14.0 | 18438 | 0.3790 | 0.8096 | 0.8926 | 0.7472 |
| 0.0021 | 15.0 | 19755 | 0.3655 | 0.8170 | 0.8883 | 0.7608 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
- Library
- transformers
- License
- mit
- Created
- Jun 17, 2025
- Updated
- Jun 17, 2025