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phobert-base-v2_baseline_syllables

This model is a fine-tuned version of vinai/phobert-base-v2 on the covid19_ner dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0934
  • Patient Id: 0.9852
  • Name: 0.9337
  • Gender: 0.9489
  • Age: 0.9644
  • Job: 0.7601
  • Location: 0.9449
  • Organization: 0.8970
  • Date: 0.9892
  • Symptom And Disease: 0.8754
  • Transportation: 1.0
  • F1 Macro: 0.9299
  • F1 Micro: 0.9455

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: 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: 5

Training results

Training Loss Epoch Step Validation Loss Patient Id Name Gender Age Job Location Organization Date Symptom And Disease Transportation F1 Macro F1 Micro
0.4655 1.0 629 0.2020 0.9690 0.9276 0.8866 0.8962 0.0 0.9159 0.8135 0.9860 0.8368 0.9486 0.8180 0.9093
0.1235 2.0 1258 0.1219 0.9761 0.9125 0.9529 0.9642 0.0 0.9419 0.8810 0.9883 0.8545 0.9943 0.8466 0.9336
0.0713 3.0 1887 0.1015 0.9789 0.9355 0.9541 0.9699 0.7077 0.9428 0.8891 0.9878 0.8667 1.0 0.9232 0.9418
0.0502 4.0 2516 0.0950 0.9824 0.9291 0.9485 0.9657 0.7442 0.9455 0.8899 0.9865 0.8698 1.0 0.9262 0.9435
0.0405 5.0 3145 0.0934 0.9852 0.9337 0.9489 0.9644 0.7601 0.9449 0.8970 0.9892 0.8754 1.0 0.9299 0.9455

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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