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distilbert-base-uncased-multilabel-indonesian-hate-speech-modified
PaceKW/distilbert-base-uncased-multilabel-indonesian-hate-speech-modified
distilbert-base-uncased-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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Updated Jun 19, 2025
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At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Jun 19, 2025
- Updated
- Jun 19, 2025
- SHA
- 5297d593
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. -->
distilbert-base-uncased-multilabel-indonesian-hate-speech-modified
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2353
- F1: 0.7785
- Roc Auc: 0.8627
- Accuracy: 0.6917
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 |
|---|---|---|---|---|---|---|
| 0.2806 | 1.0 | 1317 | 0.2349 | 0.7100 | 0.8086 | 0.6188 |
| 0.2104 | 2.0 | 2634 | 0.2219 | 0.7349 | 0.8377 | 0.5968 |
| 0.1752 | 3.0 | 3951 | 0.2169 | 0.7448 | 0.8310 | 0.6682 |
| 0.1378 | 4.0 | 5268 | 0.2240 | 0.7575 | 0.8379 | 0.6743 |
| 0.1062 | 5.0 | 6585 | 0.2353 | 0.7785 | 0.8627 | 0.6917 |
| 0.0825 | 6.0 | 7902 | 0.2544 | 0.7597 | 0.8421 | 0.6902 |
| 0.0635 | 7.0 | 9219 | 0.2729 | 0.7686 | 0.8535 | 0.6910 |
| 0.0508 | 8.0 | 10536 | 0.2927 | 0.7675 | 0.8453 | 0.7024 |
| 0.0315 | 9.0 | 11853 | 0.3046 | 0.7712 | 0.8617 | 0.6834 |
| 0.0269 | 10.0 | 13170 | 0.3269 | 0.7684 | 0.8550 | 0.7016 |
| 0.019 | 11.0 | 14487 | 0.3464 | 0.7623 | 0.8470 | 0.6887 |
| 0.0162 | 12.0 | 15804 | 0.3564 | 0.7643 | 0.8499 | 0.6925 |
| 0.014 | 13.0 | 17121 | 0.3589 | 0.7680 | 0.8570 | 0.6925 |
| 0.01 | 14.0 | 18438 | 0.3632 | 0.7700 | 0.8588 | 0.6986 |
| 0.0089 | 15.0 | 19755 | 0.3651 | 0.7714 | 0.8577 | 0.6993 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
- Library
- transformers
- License
- apache-2.0
- Created
- Jun 19, 2025
- Updated
- Jun 19, 2025