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This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on the Rodrigo1771/combined-train-drugtemist-dev-85-ner dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1806
  • Precision: 0.0940
  • Recall: 0.9540
  • F1: 0.1711
  • Accuracy: 0.7890

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10.0

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.3191 1.0 541 0.8151 0.0825 0.9605 0.1520 0.7763
0.1619 2.0 1082 0.8332 0.0922 0.9458 0.168 0.7901
0.11 3.0 1623 1.1094 0.0899 0.9494 0.1643 0.7738
0.0764 4.0 2164 1.1206 0.0885 0.9449 0.1618 0.7740
0.0567 5.0 2705 1.1806 0.0940 0.9540 0.1711 0.7890
0.0428 6.0 3246 1.3138 0.0901 0.9458 0.1645 0.7827
0.0332 7.0 3787 1.4009 0.0922 0.9384 0.1679 0.7874
0.0257 8.0 4328 1.5611 0.0904 0.9412 0.1650 0.7791
0.022 9.0 4869 1.5934 0.0921 0.9467 0.1679 0.7835
0.0181 10.0 5410 1.6103 0.0922 0.9439 0.1680 0.7863

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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Dataset used to train Rodrigo1771/bsc-bio-ehr-es-combined-train-drugtemist-dev-word2vec-85-ner

Evaluation results