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polibert-malaysia-ver2
YagiASAFAS/polibert-malaysia-ver2
polibert-malaysia-ver2 is a text classification model from YagiASAFAS. Use it when you need a label for a piece of text. 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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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- May 28, 2024
- Updated
- May 28, 2024
- SHA
- 0a035bdd
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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. -->
polibert-malaysia-ver2
This model is a fine-tuned version of bert-base-uncased on tnwei/ms-newspapers dataset. And this model is the 2nd version of YagiASAFAS/polibert-malaysia It achieves the following results on the evaluation set:
- Loss: 0.5548
- Accuracy: 0.9459
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
- mixed_precision_training: Native AMP
Label Mappings
- 0: Economic Concerns
- 1: Racial discrimination or polarization
- 2: Leadership weaknesses
- 3: Development and infrastructure gaps
- 4: Corruption
- 5: Political instablility
- 6: Socials and Public safety
- 7: Administration
- 8: Education
- 9: Religion issues
- 10: Environmental
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5263 | 1.0 | 1127 | 0.4196 | 0.9024 |
| 0.3028 | 2.0 | 2254 | 0.3746 | 0.9330 |
| 0.2412 | 3.0 | 3381 | 0.3870 | 0.9326 |
| 0.1425 | 4.0 | 4508 | 0.3688 | 0.9397 |
| 0.1052 | 5.0 | 5635 | 0.3860 | 0.9454 |
| 0.0621 | 6.0 | 6762 | 0.4542 | 0.9441 |
| 0.0533 | 7.0 | 7889 | 0.4923 | 0.9392 |
| 0.0383 | 8.0 | 9016 | 0.4893 | 0.9437 |
| 0.0245 | 9.0 | 10143 | 0.4658 | 0.9445 |
| 0.0099 | 10.0 | 11270 | 0.5429 | 0.9392 |
| 0.0107 | 11.0 | 12397 | 0.5551 | 0.9450 |
| 0.0044 | 12.0 | 13524 | 0.5579 | 0.9441 |
| 0.0027 | 13.0 | 14651 | 0.6010 | 0.9419 |
| 0.0059 | 14.0 | 15778 | 0.5880 | 0.9445 |
| 0.0038 | 15.0 | 16905 | 0.5475 | 0.9459 |
| 0.0001 | 16.0 | 18032 | 0.5548 | 0.9459 |
Framework versions
- Transformers 4.18.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- May 28, 2024
- Updated
- May 28, 2024