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fawern/ClinicalBERT-medical-text-classification

sourceHugging Faceupdated 2y agoView on Hugging Face
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Model Card

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ClinicalBERT-medical-text-classification

This model is a fine-tuned version of medicalai/ClinicalBERT on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.8610
  • —Accuracy: 0.235
  • —Precision: 0.2005
  • —Recall: 0.235
  • —F1: 0.2115

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
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 500
  • —num_epochs: 30

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
2.60941.02502.49510.3530.16170.3530.2001
2.21772.05001.98420.3590.29670.3590.2843
1.84583.07501.82580.3450.28430.3450.2893
1.69924.010001.81390.3020.26160.3020.2729
1.47735.012501.83410.2650.24580.2650.2482
1.31386.015001.86100.2350.20050.2350.2115

Framework versions

  • —Transformers 4.39.3
  • —Pytorch 2.1.2
  • —Datasets 2.18.0
  • —Tokenizers 0.15.2