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Models/KeBioLM

KeBioLM

Reported on 8 benchmarks across 2 tasks · 1 paper · 3 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing8 results

Relation ExtractiononGAD
F1· 2021-04-21
84.3
best: 84.9 (BioLinkBERT (large))
SOTA
Improving Biomedical Pretrained Language Models with Knowledge arXiv:2104.10344
Relation ExtractiononDDI
F1· 2021-04-21
81.9
best: 83.35 (BioLinkBERT (large))
SOTA
Improving Biomedical Pretrained Language Models with Knowledge arXiv:2104.10344
Named Entity Recognition (NER)onJNLPBA
F1· 2021-04-21
82
SOTA
Improving Biomedical Pretrained Language Models with Knowledge arXiv:2104.10344
Relation ExtractiononChemProt
F1· 2021-04-21
77.5
best: 83.64 (SciBert (Finetune))
Improving Biomedical Pretrained Language Models with Knowledge arXiv:2104.10344
Named Entity Recognition (NER)onNCBI-disease
F1· 2021-04-21
89.1
best: 89.71 (BioBERT)
Improving Biomedical Pretrained Language Models with Knowledge arXiv:2104.10344
Named Entity Recognition (NER)onBC5CDR-chemical
F1· 2021-04-21
93.3
best: 94.88 (Spark NLP)
Improving Biomedical Pretrained Language Models with Knowledge arXiv:2104.10344
Named Entity Recognition (NER)onBC5CDR-disease
F1· 2021-04-21
86.1
best: 88.5 (BioMegatron)
Improving Biomedical Pretrained Language Models with Knowledge arXiv:2104.10344
Named Entity Recognition (NER)onBC2GM
F1· 2021-04-21
85.1
best: 88.75 (Spark NLP)
Improving Biomedical Pretrained Language Models with Knowledge arXiv:2104.10344