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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: polibert-malaysia-ver2
    results: []

polibert-malaysia-ver2

This model is a fine-tuned version of bert-base-uncased on tnwei/ms-newspapers dataset. And this model is the 2nd version of YagiASAFAS/polibert-malaysia It achieves the following results on the evaluation set:

  • Loss: 0.5548
  • Accuracy: 0.9459

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: 16
  • 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
0.5263 1.0 1127 0.4196 0.9024
0.3028 2.0 2254 0.3746 0.9330
0.2412 3.0 3381 0.3870 0.9326
0.1425 4.0 4508 0.3688 0.9397
0.1052 5.0 5635 0.3860 0.9454
0.0621 6.0 6762 0.4542 0.9441
0.0533 7.0 7889 0.4923 0.9392
0.0383 8.0 9016 0.4893 0.9437
0.0245 9.0 10143 0.4658 0.9445
0.0099 10.0 11270 0.5429 0.9392
0.0107 11.0 12397 0.5551 0.9450
0.0044 12.0 13524 0.5579 0.9441
0.0027 13.0 14651 0.6010 0.9419
0.0059 14.0 15778 0.5880 0.9445
0.0038 15.0 16905 0.5475 0.9459
0.0001 16.0 18032 0.5548 0.9459

Framework versions

  • Transformers 4.18.0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.12.1