| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: MSPoliBERT |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # MSPoliBERT |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on tnwei/ms-newspapers dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3062 |
| - Accuracy: 0.9310 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
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|
| More information needed |
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|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 3e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 8 |
| - 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 |
| - 11: Others |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.3888 | 1.0 | 1138 | 0.3691 | 0.9178 | |
| | 0.2981 | 2.0 | 2276 | 0.3425 | 0.9240 | |
| | 0.2073 | 3.0 | 3414 | 0.3062 | 0.9310 | |
| | 0.1642 | 4.0 | 4552 | 0.3301 | 0.9336 | |
| | 0.1175 | 5.0 | 5690 | 0.3387 | 0.9345 | |
| | 0.1201 | 6.0 | 6828 | 0.3298 | 0.9358 | |
| | 0.1078 | 7.0 | 7966 | 0.3751 | 0.9327 | |
| | 0.0945 | 8.0 | 9104 | 0.3503 | 0.9349 | |
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| ### Framework versions |
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|
| - Transformers 4.18.0 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.12.1 |
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|
