YagiASAFAS
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Update README.md
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README.md
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# polibert-malaysia-ver3
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This model is
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- Loss: 2.2001
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- Accuracy: 0.6961
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- num_epochs: 16
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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# polibert-malaysia-ver3
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This model is new version of YagiASAFAS/polibert-malaysia-ver2.
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What is new is that this model used a new dataset which not only used tnwei/ms-newspapers dataset but also almost 10k of instagram posts regarding several topics about Malaysia.
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By doing so, this model captures not only formal sentences such as News, but also captures informal sentences such as personal posts.
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As a tradeoff, the accuracy was quite lower compared to the previous one
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- Loss: 2.2001
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- Accuracy: 0.6961
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- num_epochs: 16
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- mixed_precision_training: Native AMP
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### Label Mappings
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- 0: Economic Concerns
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- 1: Racial discrimination or polarization
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- 2: Leadership weaknesses
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- 3: Development and infrastructure gaps
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- 4: Corruption
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- 5: Political instablility
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- 6: Socials and Public safety
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- 7: Administration
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- 8: Education
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- 9: Religion issues
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- 10: Environmental
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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