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testlink-class

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

testlink-class

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: 0.1523
  • Precision: 0.6630
  • Recall: 0.7135
  • F1: 0.6873
  • Accuracy: 0.9745

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 0.2337 0.0 0.0 0.0 0.9440
No log 2.0 58 0.2138 0.2632 0.0585 0.0957 0.9526
No log 3.0 87 0.1586 0.3824 0.1520 0.2176 0.9557
No log 4.0 116 0.1321 0.4444 0.2807 0.3441 0.9635
No log 5.0 145 0.1264 0.4422 0.3801 0.4088 0.9629
No log 6.0 174 0.1228 0.5224 0.4094 0.4590 0.9679
No log 7.0 203 0.1117 0.5706 0.5906 0.5805 0.9690
No log 8.0 232 0.1190 0.4832 0.6725 0.5623 0.9658
No log 9.0 261 0.1130 0.6022 0.6374 0.6193 0.9712
No log 10.0 290 0.1230 0.6032 0.6667 0.6333 0.9715
No log 11.0 319 0.1264 0.6122 0.7018 0.6540 0.9712
No log 12.0 348 0.1370 0.5224 0.7485 0.6154 0.9657
No log 13.0 377 0.1259 0.6122 0.7018 0.6540 0.9726
No log 14.0 406 0.1375 0.5447 0.7485 0.6305 0.9692
No log 15.0 435 0.1379 0.6384 0.6608 0.6494 0.9728
No log 16.0 464 0.1398 0.5865 0.7135 0.6438 0.9715
No log 17.0 493 0.1470 0.5775 0.7193 0.6406 0.9706
0.086 18.0 522 0.1576 0.5446 0.7135 0.6177 0.9684
0.086 19.0 551 0.1489 0.6354 0.6725 0.6534 0.9725
0.086 20.0 580 0.1544 0.6591 0.6784 0.6686 0.9730
0.086 21.0 609 0.1489 0.6349 0.7018 0.6667 0.9734
0.086 22.0 638 0.1488 0.6821 0.6901 0.6860 0.9747
0.086 23.0 667 0.1523 0.5953 0.7485 0.6632 0.9717
0.086 24.0 696 0.1475 0.6543 0.7193 0.6852 0.9747
0.086 25.0 725 0.1507 0.6740 0.7135 0.6932 0.9752
0.086 26.0 754 0.1518 0.6703 0.7135 0.6912 0.9745
0.086 27.0 783 0.1517 0.6893 0.7135 0.7011 0.9754
0.086 28.0 812 0.1521 0.6524 0.7135 0.6816 0.9739
0.086 29.0 841 0.1521 0.6595 0.7135 0.6854 0.9743
0.086 30.0 870 0.1523 0.6630 0.7135 0.6873 0.9745

Framework versions

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