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testlink-class-2

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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: testlink-class-2
    results: []

testlink-class-2

This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1903
  • Precision: 0.6705
  • Recall: 0.6901
  • F1: 0.6801
  • Accuracy: 0.9752

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: 7e-05
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 29 0.1665 0.5894 0.7135 0.6455 0.9717
No log 2.0 58 0.1726 0.6864 0.6784 0.6824 0.9745
No log 3.0 87 0.1412 0.6398 0.6959 0.6667 0.9748
No log 4.0 116 0.1735 0.6646 0.6374 0.6507 0.9737
No log 5.0 145 0.2060 0.4448 0.7544 0.5597 0.9592
No log 6.0 174 0.1974 0.6529 0.6491 0.6510 0.9710
No log 7.0 203 0.1564 0.6062 0.6842 0.6429 0.9726
No log 8.0 232 0.1690 0.5580 0.7310 0.6329 0.9693
No log 9.0 261 0.1869 0.6805 0.6725 0.6765 0.9736
No log 10.0 290 0.1729 0.6894 0.6491 0.6687 0.9754
No log 11.0 319 0.1793 0.7114 0.6199 0.6625 0.9754
No log 12.0 348 0.1703 0.5805 0.6959 0.6330 0.9723
No log 13.0 377 0.1649 0.6429 0.6842 0.6629 0.9739
No log 14.0 406 0.1832 0.7081 0.6667 0.6867 0.9758
No log 15.0 435 0.1877 0.7063 0.6608 0.6828 0.9763
No log 16.0 464 0.1828 0.6981 0.6491 0.6727 0.9763
No log 17.0 493 0.1666 0.6842 0.6842 0.6842 0.9767
0.0032 18.0 522 0.1795 0.5982 0.7661 0.6718 0.9732
0.0032 19.0 551 0.1728 0.6543 0.7193 0.6852 0.9765
0.0032 20.0 580 0.1781 0.6425 0.7251 0.6813 0.9754
0.0032 21.0 609 0.1747 0.6743 0.6901 0.6821 0.9765
0.0032 22.0 638 0.1815 0.6173 0.7076 0.6594 0.9743
0.0032 23.0 667 0.1863 0.6842 0.6842 0.6842 0.9761
0.0032 24.0 696 0.1871 0.6742 0.7018 0.6877 0.9758
0.0032 25.0 725 0.1912 0.6517 0.6784 0.6648 0.9745
0.0032 26.0 754 0.1907 0.6839 0.6959 0.6899 0.9758
0.0032 27.0 783 0.1904 0.6630 0.7018 0.6818 0.9747
0.0032 28.0 812 0.1895 0.6630 0.7018 0.6818 0.9748
0.0032 29.0 841 0.1903 0.6648 0.6959 0.68 0.9750
0.0032 30.0 870 0.1903 0.6705 0.6901 0.6801 0.9752

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3