---
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](https://huggingface.co/xlm-roberta-base) 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](https://github.com/lang-uk/ner-uk), released by the [lang-uk](https://lang.org.ua).


Copyright: Dmytro Chaplynskyi, [lang-uk project](https://lang.org.ua), 2022