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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: 0.2116
  • Precision: 0.7516
  • Recall: 0.6901
  • F1: 0.7195
  • 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: 7.5e-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 0.2388 0.7315 0.6374 0.6813 0.9739
No log 2.0 58 0.1956 0.6169 0.7251 0.6667 0.9723
No log 3.0 87 0.1637 0.6302 0.7076 0.6667 0.9730
No log 4.0 116 0.2107 0.6810 0.6491 0.6647 0.9741
No log 5.0 145 0.1987 0.6981 0.6491 0.6727 0.9745
No log 6.0 174 0.1524 0.7355 0.6667 0.6994 0.9756
No log 7.0 203 0.1933 0.7664 0.6140 0.6818 0.9750
No log 8.0 232 0.2150 0.7836 0.6140 0.6885 0.9747
No log 9.0 261 0.1700 0.7405 0.6842 0.7112 0.9761
No log 10.0 290 0.1626 0.6142 0.7076 0.6576 0.9730
No log 11.0 319 0.1826 0.7035 0.7076 0.7055 0.9761
No log 12.0 348 0.1724 0.6802 0.6842 0.6822 0.9758
No log 13.0 377 0.1823 0.7852 0.6199 0.6928 0.9741
No log 14.0 406 0.1833 0.7284 0.6901 0.7087 0.9761
No log 15.0 435 0.1816 0.5853 0.7427 0.6546 0.9701
No log 16.0 464 0.2084 0.7770 0.6725 0.7210 0.9761
No log 17.0 493 0.2043 0.7069 0.7193 0.7130 0.9748
0.0022 18.0 522 0.1996 0.6541 0.7076 0.6798 0.9741
0.0022 19.0 551 0.2013 0.7484 0.6959 0.7212 0.9763
0.0022 20.0 580 0.1933 0.7159 0.7368 0.7262 0.9770
0.0022 21.0 609 0.1931 0.7101 0.7018 0.7059 0.9759
0.0022 22.0 638 0.1946 0.7052 0.7135 0.7093 0.9759
0.0022 23.0 667 0.1968 0.6936 0.7018 0.6977 0.9752
0.0022 24.0 696 0.2076 0.7296 0.6784 0.7030 0.9754
0.0022 25.0 725 0.2076 0.7296 0.6784 0.7030 0.9756
0.0022 26.0 754 0.2051 0.6941 0.6901 0.6921 0.9747
0.0022 27.0 783 0.2106 0.7342 0.6784 0.7052 0.9752
0.0022 28.0 812 0.2093 0.7312 0.6842 0.7069 0.9752
0.0022 29.0 841 0.2112 0.7516 0.6901 0.7195 0.9758
0.0022 30.0 870 0.2116 0.7516 0.6901 0.7195 0.9758

Framework versions

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