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prueba5

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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: prueba5
    results: []

prueba5

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: 0.2442
  • Precision: 0.5258
  • Recall: 0.5574
  • F1: 0.5411
  • Accuracy: 0.9609

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 0.2341 0.0 0.0 0.0 0.9488
No log 2.0 114 0.2411 0.0 0.0 0.0 0.9488
No log 3.0 171 0.2150 0.0385 0.0055 0.0096 0.9410
No log 4.0 228 0.1885 0.25 0.0929 0.1355 0.9500
No log 5.0 285 0.1730 0.3830 0.1967 0.2599 0.9524
No log 6.0 342 0.1591 0.5098 0.2842 0.3649 0.9581
No log 7.0 399 0.1665 0.5405 0.3279 0.4082 0.9609
No log 8.0 456 0.1856 0.5294 0.4918 0.5099 0.9604
0.1706 9.0 513 0.1727 0.5 0.5191 0.5094 0.9611
0.1706 10.0 570 0.1717 0.5669 0.4863 0.5235 0.9639
0.1706 11.0 627 0.1913 0.5024 0.5628 0.5309 0.9601
0.1706 12.0 684 0.1793 0.515 0.5628 0.5379 0.9619
0.1706 13.0 741 0.2009 0.5679 0.5027 0.5333 0.9618
0.1706 14.0 798 0.2043 0.5333 0.5683 0.5503 0.9604
0.1706 15.0 855 0.2052 0.5486 0.5246 0.5363 0.9629
0.1706 16.0 912 0.2234 0.5183 0.5410 0.5294 0.9581
0.1706 17.0 969 0.2157 0.5424 0.5246 0.5333 0.9616
0.0202 18.0 1026 0.2207 0.5025 0.5574 0.5285 0.9596
0.0202 19.0 1083 0.2297 0.5025 0.5410 0.5211 0.9573
0.0202 20.0 1140 0.2264 0.5131 0.5355 0.5241 0.9593
0.0202 21.0 1197 0.2300 0.5181 0.5464 0.5319 0.9593
0.0202 22.0 1254 0.2348 0.5241 0.5355 0.5297 0.9604
0.0202 23.0 1311 0.2372 0.5196 0.5792 0.5478 0.9588
0.0202 24.0 1368 0.2349 0.5319 0.5464 0.5391 0.9613
0.0202 25.0 1425 0.2353 0.5312 0.5574 0.544 0.9619
0.0202 26.0 1482 0.2388 0.5489 0.5519 0.5504 0.9614
0.0044 27.0 1539 0.2396 0.5243 0.5301 0.5272 0.9618
0.0044 28.0 1596 0.2442 0.5152 0.5574 0.5354 0.9603
0.0044 29.0 1653 0.2444 0.5178 0.5574 0.5368 0.9604
0.0044 30.0 1710 0.2442 0.5258 0.5574 0.5411 0.9609

Framework versions

  • Transformers 4.27.4
  • Pytorch 1.13.1+cu116
  • Datasets 2.11.0
  • Tokenizers 0.13.2