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indobert-base-uncased-multilabel-indonesian-hate-speech-modified-v2
PaceKW/indobert-base-uncased-multilabel-indonesian-hate-speech-modified-v2
indobert-base-uncased-multilabel-indonesian-hate-speech-modified-v2 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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Public
Updated Jun 21, 2025
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At a glance
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Jun 21, 2025
- Updated
- Jun 21, 2025
- SHA
- f5f9a65f
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-uncased-multilabel-indonesian-hate-speech-modified-v2
This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2051
- F1: 0.7925
- Roc Auc: 0.8745
- Accuracy: 0.7039
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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.3057 | 1.0 | 1317 | 0.2248 | 0.7142 | 0.8121 | 0.5968 |
| 0.2102 | 2.0 | 2634 | 0.2156 | 0.7530 | 0.8584 | 0.5991 |
| 0.1797 | 3.0 | 3951 | 0.1998 | 0.7737 | 0.8580 | 0.6606 |
| 0.1472 | 4.0 | 5268 | 0.1995 | 0.7916 | 0.8665 | 0.7062 |
| 0.1269 | 5.0 | 6585 | 0.2051 | 0.7925 | 0.8745 | 0.7039 |
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 21, 2025
- Updated
- Jun 21, 2025