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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: 0.1878
  • Precision: 0.7
  • Recall: 0.6959
  • F1: 0.6979
  • Accuracy: 0.9758

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: 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 0.1455 0.7025 0.6491 0.6748 0.9758
No log 2.0 58 0.1404 0.6845 0.6725 0.6785 0.9748
No log 3.0 87 0.1511 0.6384 0.6608 0.6494 0.9730
No log 4.0 116 0.1515 0.6353 0.6316 0.6334 0.9723
No log 5.0 145 0.1563 0.6 0.7193 0.6543 0.9714
No log 6.0 174 0.1820 0.6772 0.6257 0.6505 0.9734
No log 7.0 203 0.1671 0.565 0.6608 0.6092 0.9695
No log 8.0 232 0.1664 0.6592 0.6901 0.6743 0.9743
No log 9.0 261 0.1726 0.6725 0.6725 0.6725 0.9754
No log 10.0 290 0.1929 0.6328 0.6550 0.6437 0.9714
No log 11.0 319 0.1749 0.6894 0.6491 0.6687 0.9737
No log 12.0 348 0.1675 0.6889 0.7251 0.7066 0.9745
No log 13.0 377 0.1806 0.6186 0.7018 0.6575 0.9723
No log 14.0 406 0.1732 0.6193 0.7135 0.6630 0.9723
No log 15.0 435 0.1837 0.6080 0.7076 0.6541 0.9714
No log 16.0 464 0.1774 0.6798 0.7076 0.6934 0.9750
No log 17.0 493 0.1700 0.6477 0.7310 0.6868 0.9737
0.0031 18.0 522 0.1719 0.6219 0.7310 0.6720 0.9732
0.0031 19.0 551 0.1749 0.6440 0.7193 0.6796 0.9743
0.0031 20.0 580 0.1808 0.7278 0.6725 0.6991 0.9761
0.0031 21.0 609 0.1753 0.6595 0.7135 0.6854 0.9737
0.0031 22.0 638 0.1816 0.6489 0.7135 0.6797 0.9739
0.0031 23.0 667 0.1835 0.6839 0.6959 0.6899 0.9752
0.0031 24.0 696 0.1864 0.7134 0.6842 0.6985 0.9759
0.0031 25.0 725 0.1919 0.7516 0.6725 0.7099 0.9765
0.0031 26.0 754 0.1823 0.6758 0.7193 0.6969 0.9743
0.0031 27.0 783 0.1822 0.6721 0.7193 0.6949 0.9741
0.0031 28.0 812 0.1862 0.7083 0.6959 0.7021 0.9759
0.0031 29.0 841 0.1879 0.7 0.6959 0.6979 0.9758
0.0031 30.0 870 0.1878 0.7 0.6959 0.6979 0.9758

Framework versions

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