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elopezlopez/Bio_ClinicalBERT_fold_9_ternary_v1

sourceHugging Facemitupdated 4y agoView on Hugging Face
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BioClinicalBERTfold9ternary_v1

This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0189
  • F1: 0.7905

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: 2e-05
  • trainbatchsize: 16
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 25

Training results

Training LossEpochStepValidation LossF1
No log1.02920.57580.7571
0.54822.05840.62820.7609
0.54823.08760.68230.7841
0.23464.011680.98980.7776
0.23465.014601.13970.7866
0.10016.017521.38320.7751
0.04477.020441.60020.7674
0.04478.023361.72650.7584
0.01719.026281.66500.7699
0.017110.029201.73220.7661
0.015611.032121.80710.7789
0.01212.035041.83220.7841
0.01213.037961.89480.7763
0.0114.040881.76670.7918
0.0115.043801.85380.7879
0.006316.046721.97630.7776
0.006317.049641.99700.7841
0.002818.052561.93660.7931
0.000319.055481.97090.7892
0.000320.058401.94600.7879
0.004421.061322.02800.7866
0.004422.064241.94230.7918
0.001323.067161.96180.7918
0.00424.070082.02410.7905
0.00425.073002.01890.7905

Framework versions

  • Transformers 4.21.1
  • Pytorch 1.12.0+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1