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metadata-cls-no-gov-8k-v2

This model is a fine-tuned version of vinai/phobert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3052
  • Accuracy: 0.9447
  • F1: 0.7927

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: 2e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.5649 1.6260 200 0.2215 0.9455 0.7479
0.1634 3.2520 400 0.1869 0.9438 0.8204
0.1222 4.8780 600 0.2286 0.9370 0.7837
0.0808 6.5041 800 0.2174 0.9532 0.8263
0.0528 8.1301 1000 0.2440 0.9387 0.7862
0.046 9.7561 1200 0.2416 0.9472 0.8180
0.0329 11.3821 1400 0.2631 0.9464 0.7967
0.0271 13.0081 1600 0.2769 0.9481 0.8124
0.0179 14.6341 1800 0.2687 0.9506 0.8122
0.0185 16.2602 2000 0.2935 0.9438 0.7921
0.0153 17.8862 2200 0.2957 0.9455 0.7907
0.0146 19.5122 2400 0.3052 0.9447 0.7927

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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