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prueba4

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: 0.2044
  • Precision: 0.7288
  • Recall: 0.6853
  • F1: 0.7064
  • Accuracy: 0.9752

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: 15

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 57 0.2361 0.6504 0.6892 0.6692 0.9694
No log 2.0 114 0.2441 0.6190 0.6733 0.6450 0.9671
No log 3.0 171 0.2064 0.6013 0.7211 0.6558 0.9699
No log 4.0 228 0.2241 0.7004 0.6335 0.6653 0.9720
No log 5.0 285 0.1992 0.6578 0.6892 0.6732 0.9727
No log 6.0 342 0.2149 0.6073 0.7331 0.6643 0.9694
No log 7.0 399 0.2099 0.7466 0.6574 0.6992 0.9755
No log 8.0 456 0.2039 0.7293 0.6653 0.6958 0.9747
0.0017 9.0 513 0.2185 0.7342 0.6494 0.6892 0.9742
0.0017 10.0 570 0.2074 0.688 0.6853 0.6866 0.9732
0.0017 11.0 627 0.2010 0.7073 0.6932 0.7002 0.9745
0.0017 12.0 684 0.2030 0.7126 0.7012 0.7068 0.9749
0.0017 13.0 741 0.2045 0.7173 0.6773 0.6967 0.9745
0.0017 14.0 798 0.2040 0.7185 0.6813 0.6994 0.9747
0.0017 15.0 855 0.2044 0.7288 0.6853 0.7064 0.9752

Framework versions

  • Transformers 4.27.3
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2
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