uk_ner_web_trf_large
Model description
uk_ner_web_trf_large is a fine-tuned XLM-Roberta model that is ready to use for Named Entity Recognition and achieves a 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. Smaller transformer based model for the SpaCy is available here.
Copyright: Dmytro Chaplynskyi, lang-uk project, 2022
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Evaluation results
- NER Precisionself-reported0.918
- NER Recallself-reported0.916
- NER F Scoreself-reported0.917