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BioNEG

Text Classification
Transformers
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Italian
bert
NER
assertion negation
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MedBIT for Clinical Assertion Negation

This model is a fine-tuned version of IVN-RIN/medBIT-r3-plus on a private dataset.

It achieves the following results on the evaluation set:

  • Loss: 0.417
  • Macro-f1: 0.946
  • Micro-f1: 0.946

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: 1e-06
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 21

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Evaluation results

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