---
tags:
- spacy
- token-classification
language: uk
datasets:
- ner-uk
license: mit
model-index:
- name: uk_ner_wechsel-minixhofer-roberta-large
  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_wechsel-minixhofer-roberta-large

## Model description

**uk_ner_wechsel-minixhofer-roberta-large** is a fine-tuned [Roberta-Large model](https://huggingface.co/benjamin/roberta-large-wechsel-ukrainian) by @benjamin that is ready to use for **Named Entity Recognition** and achieves a **SoA** performance for the NER task for Ukrainian language. That's the best I have for NER so far

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).
Smaller transformer based model for the SpaCy is available [here](https://huggingface.co/dchaplinsky/uk_ner_web_trf_base).


Copyright: [Dmytro Chaplynskyi](https://twitter.com/dchaplinsky), [lang-uk project](https://lang.org.ua), 2023