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  # polibert-malaysia-ver3
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- This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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- It achieves the following results on the evaluation set:
 
 
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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 |