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---
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: 0.8616
- name: NER Recall
type: recall
value: 0.8593
- name: NER F Score
type: f_score
value: 0.8605
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) **0.8605**
- F-score (macro) **0.7472**
- Accuracy **0.8033**
| by class | precision | recall | f1-score | support |
|--------------|-----------|--------|----------|---------|
| **PERS** | 0.9305 | 0.9422 | 0.9363 | 1678 |
| **LOC** | 0.8150 | 0.8678 | 0.8406 | 401 |
| **ORG** | 0.6653 | 0.6092 | 0.6360 | 261 |
| **MISC** | 0.6202 | 0.5375 | 0.5759 | 240 |
| micro avg | 0.8616 | 0.8593 | 0.8605 | 2580 |
| macro avg | 0.7577 | 0.7392 | 0.7472 | 2580 |
| weighted avg | 0.8569 | 0.8593 | 0.8575 | 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 |