metadata

tags:
  - spacy
  - token-classification
language: uk
datasets:
  - ner-uk
license: mit
model-index:
  - name: roberta-uk-ner-base
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.8987742191
          - name: NER Recall
            type: recall
            value: 0.8810077519
          - name: NER F Score
            type: f_score
            value: 0.8898023096

roberta-uk-ner-base

Model description

roberta-uk-ner-base is a fine-tuned XLM-Roberta model that is ready to use for Named Entity Recognition and achieves state-of-the-art performance for the NER task for Ukrainian language. 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.