Papers › BioM-Transformers: Building Large Biomedical Language Models with BERT, ALBERT and ELECTRA

BioM-Transformers: Building Large Biomedical Language Models with BERT, ALBERT and ELECTRA

1 Jun 2021NAACL (BioNLP) 2021 6archive 2025-07-28

Sultan Alrowili, Vijay Shanker

The impact of design choices on the performance of biomedical language models recently has been a subject for investigation. In this paper, we empirically study biomedical domain adaptation with large transformer models using different design choices. We evaluate the performance of our pretrained models against other existing biomedical language models in the literature. Our results show that we achieve state-of-the-art results on several biomedical domain tasks despite using similar or less computational cost compared to other models in the literature. Our findings highlight the significant effect of design choices on improving the performance of biomedical language models.

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Domain AdaptationRelation Extraction

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Relation Extraction ChemProt BioM-BERT F1 80.0 #2 of 13 Archive leaderboard report

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