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BERT MCN-Model using SMM4H 2017 (subtask 3) data

The model was trained using clagator/biobert_v1.1_pubmed_nli_sts as a base and the smm4h dataset from 2017 from subtask 3.

Dataset

See here for the scripts and datasets.

Attribution

Sarker, Abeed (2018), “Data and systems for medication-related text classification and concept normalization from Twitter: Insights from the Social Media Mining for Health (SMM4H)-2017 shared task”, Mendeley Data, V2, doi: 10.17632/rxwfb3tysd.2

Test Results

  • Acc: 89.44
  • Acc@2: 91.84
  • Acc@3: 93.20
  • Acc@5: 94.32
  • Acc@10: 95.04

Acc@N denotes the accuracy taking the top N predictions of the model into account, not just the first one.

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