Named Entity Recognition On Bc5Cdr Chemical

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	F1	Paper Title
BioKMNER + BioBERT	94.22	Improving Biomedical Named Entity Recognition with Syntactic Information
HGN	94.59	Hero-Gang Neural Model For Named Entity Recognition
CompactBioBERT	94.31	On the Effectiveness of Compact Biomedical Transformers
SciFive-Large	94.76	SciFive: a text-to-text transformer model for biomedical literature
KeBioLM	93.3	Improving Biomedical Pretrained Language Models with Knowledge
BioDistilBERT	94.48	On the Effectiveness of Compact Biomedical Transformers
Spark NLP	94.88	Biomedical Named Entity Recognition at Scale
Att-BiLSTM-CRF	92.57	An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition
BioMobileBERT	94.23	On the Effectiveness of Compact Biomedical Transformers
DistilBioBERT	94.53	On the Effectiveness of Compact Biomedical Transformers
BioLinkBERT (large)	94.04	LinkBERT: Pretraining Language Models with Document Links
BioMegatron	92.9	BioMegatron: Larger Biomedical Domain Language Model
NCBI_BERT(base) (P)	93.5	Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets

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