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This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on the Rodrigo1771/symptemist-fasttext-8-ner dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3073
  • Precision: 0.6764
  • Recall: 0.7219
  • F1: 0.6984
  • Accuracy: 0.9500

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
No log 0.9975 203 0.1501 0.5960 0.6338 0.6143 0.9468
No log 2.0 407 0.1761 0.6529 0.6940 0.6729 0.9492
0.1312 2.9975 610 0.1995 0.6322 0.7170 0.6720 0.9470
0.1312 4.0 814 0.2182 0.6446 0.7137 0.6774 0.9483
0.0248 4.9975 1017 0.2461 0.6251 0.7219 0.6701 0.9449
0.0248 6.0 1221 0.2695 0.6410 0.7302 0.6827 0.9469
0.0248 6.9975 1424 0.2829 0.6529 0.7340 0.6911 0.9470
0.0081 8.0 1628 0.2982 0.6711 0.7181 0.6938 0.9494
0.0081 8.9975 1831 0.3073 0.6764 0.7219 0.6984 0.9500
0.0038 9.9754 2030 0.3079 0.6713 0.7165 0.6931 0.9500

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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