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intermezzo672
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NHS-pubmedbert-binary

Text Classification
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NHS-pubmedbert-binary

This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5861
  • Accuracy: 0.8246
  • Precision: 0.8180
  • Recall: 0.8240
  • F1: 0.8202

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
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 6

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.0592 1.0 397 0.3980 0.8246 0.8179 0.8220 0.8196
0.0542 2.0 794 0.4714 0.7943 0.7960 0.8064 0.7929
0.6307 3.0 1191 0.5861 0.8246 0.8180 0.8240 0.8202

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
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Evaluation results

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