uk_ner_web_trf_best / README.md
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metadata
tags:
  - spacy
  - token-classification
language: uk
datasets:
  - ner-uk
license: mit
model-index:
  - name: uk_ner_web_trf_best
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.9278959811
          - name: NER Recall
            type: recall
            value: 0.9127906977
          - name: NER F Score
            type: f_score
            value: 0.9202813599
widget:
  - text: >-
      Президент Володимир Зеленський пояснив, що наразі діалог із режимом
      Володимира путіна неможливий, адже агресор обрав курс на знищення
      українського народу. За словами Зеленського цей режим РФ виявляє неповагу
      до суверенітету і територіальної цілісності України.

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