metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MSPoliBERT
results: []
MSPoliBERT
This model is a fine-tuned version of 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
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: 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 |
Framework versions
- Transformers 4.18.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.12.1