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This model is a fine-tuned version of microsoft/deberta-v3-large on the tner/ontonotes5 dataset. Model fine-tuning is done via T-NER's hyper-parameter search (see the repository for more detail). It achieves the following results on the test set: - F1 (micro): 0.9069623608411381 - Precision (micro): 0.902100360312857 - Recall (micro): 0.9118770542773386 - F1 (macro): 0.834586960779896 - Precision (macro): 0.8237351069457466 - Recall (macro): 0.8475169311172334 The per-entity breakdown of the F1 score on the test set are below: - cardinal_number: 0.853475935828877 - date: 0.8815545959284392 - event: 0.8030303030303031 - facility: 0.7896678966789669 - geopolitical_area: 0.9650033867690223 - group: 0.9337209302325581 - language: 0.8372093023255814 - law: 0.6756756756756757 - location: 0.7624020887728459 - money: 0.8818897637795275 - ordinal_number: 0.8635235732009926 - organization: 0.914952751528627 - percent: 0.9 - person: 0.9609866599546942 - product: 0.7901234567901234 - quantity: 0.8161434977578474 - time: 0.674364896073903 - work_of_art: 0.7188405797101449 For F1 scores, the confidence interval is obtained by bootstrap as below: - F1 (micro): - 90%: [0.9019409960743083, 0.911751130722053] - 95%: [0.9010822890967028, 0.9125611412371442] - F1 (macro): - 90%: [0.9019409960743083, 0.911751130722053] - 95%: [0.9010822890967028, 0.9125611412371442]

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This model is a fine-tuned version of roberta-large on the tner/tweetner7 dataset (`train_all` split). Model fine-tuning is done via T-NER's hyper-parameter search (see the repository for more detail). It achieves the following results on the test set of 2021: - F1 (micro): 0.6574551220340903 - Precision (micro): 0.644212629008989 - Recall (micro): 0.6712534690101758 - F1 (macro): 0.6124665667529737 - Precision (macro): 0.6005167968535563 - Recall (macro): 0.625251837701222 The per-entity breakdown of the F1 score on the test set are below: - corporation: 0.5392156862745098 - creative_work: 0.4760582928521859 - event: 0.4673321234119782 - group: 0.6139798488664987 - location: 0.6707399864222675 - person: 0.8293212669683258 - product: 0.6906187624750498 For F1 scores, the confidence interval is obtained by bootstrap as below: - F1 (micro): - 90%: [0.6484148010152769, 0.6672289519134409] - 95%: [0.6470100684797441, 0.6689850350992637] - F1 (macro): - 90%: [0.6484148010152769, 0.6672289519134409] - 95%: [0.6470100684797441, 0.6689850350992637]

Text analysis
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