tner/roberta large tweetner7 all 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] Full evaluation can be found at metric file of NER and metric file of entity span. Usage This model can be used through the tner library. Install the…
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