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NazzX1/clinical-bert-section-Hclassification-v6

sourceHugging Faceupdated 1y agoView on Hugging Face
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clinical-bert-section-Hclassification-v6

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

  • —Loss: 0.9591
  • —Accuracy: 0.8801
  • —Precision: 0.8830
  • —Recall: 0.8801
  • —F1: 0.8806

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: 3e-05
  • —trainbatchsize: 4
  • —evalbatchsize: 4
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 300
  • —num_epochs: 6

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
No log1.03701.32390.27130.56860.27130.1492
1.35572.07401.19590.75080.82410.75080.7339
1.20233.011101.09140.87380.88250.87380.8747
1.20234.014801.01740.87380.87950.87380.8741
1.0715.018500.97380.88010.88340.88010.8804
0.98926.022200.95910.88010.88300.88010.8806

Framework versions

  • —Transformers 4.51.3
  • —Pytorch 2.6.0+cu124
  • —Tokenizers 0.21.1