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hoc.

hoc is a state-of-the-art machine learning benchmark indexed on Codesota. This page tracks published model results, top scores per metric, and the SOTA timeline for hoc.

Paper Leaderboard
§ 01 · SOTA history

Year over year.

§ 02 · Leaderboard

Results by metric.

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F1

F1 is the reported evaluation metric for hoc. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Higher is better

Trust tiers for F1verifiedpapervendorcommunityunverified
RankModelTrustScoreYearLinksFix
01BioLinkBERT (large)
From paper: LinkBERT: Pretraining Language Models with Document Links
verified88.12022Paper ↗Code ↗Looks wrong?
02NCBI_BERT(large) (P)
From paper: Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets
verified87.32019Paper ↗Code ↗Looks wrong?
03SciFive-large
From paper: SciFive: a text-to-text transformer model for biomedical literature
verified86.082021Paper ↗Code ↗Looks wrong?
04BioGPTunverified85.122022Paper ↗Code ↗Looks wrong?
05BioGPT-Largeunverified84.42022Paper ↗Code ↗Looks wrong?

Micro F1

Micro F1 is the reported evaluation metric for hoc. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Higher is better

Trust tiers for Micro F1verifiedpapervendorcommunityunverified
RankModelTrustScoreYearLinksFix
01BioGPT
From paper: BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining
verified85.122022Paper ↗Code ↗Looks wrong?
02BioLinkBERT (large)
From paper: LinkBERT: Pretraining Language Models with Document Links
verified84.872022Paper ↗Code ↗Looks wrong?
03PubMedBERT uncased
From paper: Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing
verified82.322020Paper ↗Code ↗Looks wrong?
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