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testlink-class-3

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

  • Loss: 0.1443
  • Precision: 0.5833
  • Recall: 0.6550
  • F1: 0.6171
  • Accuracy: 0.9730

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 0.2830 0.0 0.0 0.0 0.9440
No log 2.0 58 0.2789 0.0 0.0 0.0 0.9440
No log 3.0 87 0.2388 0.0 0.0 0.0 0.9440
No log 4.0 116 0.2080 0.0 0.0 0.0 0.9440
No log 5.0 145 0.2335 0.0167 0.0058 0.0087 0.9322
No log 6.0 174 0.1889 0.0 0.0 0.0 0.9440
No log 7.0 203 0.1553 0.3469 0.1988 0.2528 0.9506
No log 8.0 232 0.1491 0.5 0.2339 0.3187 0.9576
No log 9.0 261 0.1604 0.4872 0.2222 0.3052 0.9605
No log 10.0 290 0.1347 0.4733 0.3626 0.4106 0.9587
No log 11.0 319 0.1391 0.5165 0.2749 0.3588 0.9605
No log 12.0 348 0.1392 0.4848 0.3743 0.4224 0.9633
No log 13.0 377 0.1306 0.4706 0.3743 0.4169 0.9636
No log 14.0 406 0.1382 0.4774 0.4327 0.4540 0.9642
No log 15.0 435 0.1368 0.4734 0.5205 0.4958 0.9655
No log 16.0 464 0.1316 0.5052 0.5731 0.5370 0.9666
No log 17.0 493 0.1333 0.4852 0.6725 0.5637 0.9660
0.1607 18.0 522 0.1379 0.56 0.5731 0.5665 0.9695
0.1607 19.0 551 0.1534 0.5941 0.5906 0.5924 0.9706
0.1607 20.0 580 0.1294 0.5606 0.6491 0.6016 0.9712
0.1607 21.0 609 0.1403 0.5231 0.6608 0.5840 0.9704
0.1607 22.0 638 0.1429 0.6044 0.6433 0.6232 0.9719
0.1607 23.0 667 0.1411 0.5825 0.6608 0.6192 0.9719
0.1607 24.0 696 0.1339 0.5631 0.6784 0.6154 0.9708
0.1607 25.0 725 0.1345 0.5825 0.6608 0.6192 0.9721
0.1607 26.0 754 0.1464 0.5833 0.6550 0.6171 0.9717
0.1607 27.0 783 0.1403 0.5672 0.6667 0.6129 0.9715
0.1607 28.0 812 0.1445 0.5934 0.6316 0.6119 0.9725
0.1607 29.0 841 0.1433 0.5588 0.6667 0.608 0.9715
0.1607 30.0 870 0.1443 0.5833 0.6550 0.6171 0.9730

Framework versions

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