uk_ner_web_trf_best
Model description
uk_ner_web_trf_best is a fine-tuned Roberta Large Ukrainian model that is ready to use for Named Entity Recognition and achieves a new SoA performance for the NER task for Ukrainian language. It outperforms another SpaCy model, uk_core_news_trf on a NER task.
It has been trained to recognize four types of entities: location (LOC), organizations (ORG), person (PERS) and Miscellaneous (MISC).
The model was fine-tuned on the NER-UK dataset, released by the lang-uk.
A smaller transformer-based model for the SpaCy is available here.
Copyright: Dmytro Chaplynskyi, lang-uk project, 2023
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Evaluation results
- NER Precisionself-reported0.928
- NER Recallself-reported0.913
- NER F Scoreself-reported0.920