--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy model-index: - name: polibert-malaysia results: [] --- # polibert-malaysia 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: 0.9318 - Accuracy: 0.8904 ## 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: 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.6482 | 1.0 | 3887 | 0.5960 | 0.8302 | | 0.4607 | 2.0 | 7774 | 0.5355 | 0.8657 | | 0.3267 | 3.0 | 11661 | 0.6395 | 0.8820 | | 0.1983 | 4.0 | 15548 | 0.7489 | 0.8742 | | 0.1107 | 5.0 | 19435 | 0.7793 | 0.8815 | | 0.0742 | 6.0 | 23322 | 0.8591 | 0.8864 | | 0.045 | 7.0 | 27209 | 0.8850 | 0.8903 | | 0.0201 | 8.0 | 31096 | 0.9318 | 0.8904 | ### Framework versions - Transformers 4.18.0 - Pytorch 2.2.1+cu121 - Datasets 2.19.1 - Tokenizers 0.12.1