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

testlink

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: 0.2031
  • Precision: 0.5065
  • Recall: 0.6359
  • F1: 0.5639
  • Accuracy: 0.9658

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: 2.75e-05
  • train_batch_size: 16
  • 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 57 0.2133 0.0 0.0 0.0 0.9516
No log 2.0 114 0.1757 0.2 0.0163 0.0302 0.9550
No log 3.0 171 0.1591 0.2893 0.1902 0.2295 0.9535
No log 4.0 228 0.1386 0.3433 0.25 0.2893 0.9582
No log 5.0 285 0.1349 0.4345 0.3967 0.4148 0.9600
No log 6.0 342 0.1311 0.5352 0.4130 0.4663 0.9646
No log 7.0 399 0.1402 0.4264 0.5978 0.4977 0.9590
No log 8.0 456 0.1377 0.4858 0.5598 0.5202 0.9634
0.1282 9.0 513 0.1539 0.5226 0.4402 0.4779 0.9651
0.1282 10.0 570 0.1631 0.4597 0.6196 0.5278 0.9607
0.1282 11.0 627 0.1511 0.5333 0.4783 0.5043 0.9666
0.1282 12.0 684 0.1705 0.4690 0.5761 0.5171 0.9626
0.1282 13.0 741 0.1760 0.5138 0.5054 0.5096 0.9651
0.1282 14.0 798 0.1917 0.4296 0.6630 0.5214 0.9580
0.1282 15.0 855 0.1833 0.4563 0.625 0.5275 0.9619
0.1282 16.0 912 0.1887 0.4933 0.6033 0.5428 0.9638
0.1282 17.0 969 0.1723 0.5138 0.6087 0.5572 0.9659
0.0102 18.0 1026 0.1849 0.5022 0.6196 0.5547 0.9649
0.0102 19.0 1083 0.1773 0.5352 0.6196 0.5743 0.9676
0.0102 20.0 1140 0.1945 0.4957 0.6304 0.5550 0.9646
0.0102 21.0 1197 0.1967 0.4756 0.6359 0.5442 0.9634
0.0102 22.0 1254 0.1876 0.4978 0.6087 0.5477 0.9658
0.0102 23.0 1311 0.1935 0.4978 0.6087 0.5477 0.9656
0.0102 24.0 1368 0.1930 0.5256 0.6141 0.5664 0.9671
0.0102 25.0 1425 0.1945 0.5110 0.6304 0.5645 0.9661
0.0102 26.0 1482 0.1955 0.5283 0.6087 0.5657 0.9673
0.0023 27.0 1539 0.2017 0.5043 0.6359 0.5625 0.9654
0.0023 28.0 1596 0.2010 0.5088 0.6304 0.5631 0.9659
0.0023 29.0 1653 0.2019 0.5088 0.6304 0.5631 0.9659
0.0023 30.0 1710 0.2031 0.5065 0.6359 0.5639 0.9658

Framework versions

  • Transformers 4.27.4
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3