---
tags:
- flair
- token-classification
- sequence-tagger-model
language: uk
datasets:
- ner-uk
model-index:
- name: flair-uk-ner
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.8572
    - name: NER Recall
      type: recall
      value: 0.8516
    - name: NER F Score
      type: f_score
      value: 0.8544
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."
license: mit
---

# flair-uk-ner

## Model description

**flair-uk-ner** is a Flair model that is ready to use for **Named Entity Recognition**. It is based on flair embeddings, that I've trained for Ukrainian language (available [here](https://huggingface.co/dchaplinsky/flair-uk-backward) and [here](https://huggingface.co/dchaplinsky/flair-uk-forward)) and has nice performance and a very **small size** (just 72mb!).

It has been trained to recognize four types of entities: location (LOC), organizations (ORG), person (PERS) and Miscellaneous (MISC). 

Results:
- F-score (micro) **0.8544**
- F-score (macro) **0.7406**
- Accuracy **0.798**

              precision    recall  f1-score   support

        PERS     0.9231    0.9374    0.9302      1678
         LOC     0.8204    0.8429    0.8315       401
         ORG     0.6708    0.6245    0.6468       261
        MISC     0.6029    0.5125    0.5541       240

    micro avg     0.8572    0.8516    0.8544      2580
    macro avg     0.7543    0.7293    0.7406      2580
    weighted avg     0.8518    0.8516    0.8512      2580

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).
Training code is also available [here](https://github.com/lang-uk/flair-ner).


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