README.md

---
tags:
- spacy
- token-classification
language: uk
datasets:
- ner-uk.2.0
license: mit
model-index:
- name: uk_ner_web_trf_13class
  results:
  - task:
      name: NER
      type: token-classification
    metrics:
    - name: NER Precision
      type: precision
      value: 0.8977982743
    - name: NER Recall
      type: recall
      value: 0.8860666569
    - name: NER F Score
      type: f_score
      value: 0.891893889
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_web_trf_13class

## Model description

**uk_ner_web_trf_13class** is a fine-tuned [Roberta Large Ukrainian model](https://huggingface.co/benjamin/roberta-large-wechsel-ukrainian) that is ready to use for **Named Entity Recognition** and achieves a new **SoA** performance for the NER task for Ukrainian language.

It has a solid performance and has been trained to recognize **thirteen** types of entities: 
- **ORG** — a name of a company, brand, agency, organization, institution (including religious, informal, non-profit), party, people's association, or specific project like a conference, a music band, a TV program, etc. Example: *UNESCO*.
- **PERS** — a person name where person may refer to humans, book characters, or humanoid creatures like vampires, ghosts, mermaids, etc. Example: *Marquis de Sade*.
- **LOC** — a geographical name, including names of districts, villages, cities, states, counties, countries, continents, rivers, lakes, seas, oceans, mountains, etc. Example: *Ukraine*.
- **MON** — a sum of money including the currency. Examples: *\$40, 1 mln hryvnias*.
- **PCT** — a percent value including the percent sign or the word "percent". Example: *10\%*.
- **DATE** — a full or incomplete calendar date that may include a century, a year, a month, a day. Examples: *last week, 10.12.1999*.
- **TIME** — a textual or numerical timestamp. Examples: *half past six, 18:30*.
- **PERIOD** — a time period, which may consist of two dates. Examples: *a few months, 2014-2015*.
- **JOB** — a job title. Examples: *member of parliament, ophthalmologist*.
- **DOC** — a unique name of a document, including names of contracts, orders, bills, purchases. Example: *procurement contract CW2244226*.
- **QUANT** — a quantity with the unit of measurement, such as weight, distance, size. Examples: *3 kilograms, a hundred miles*.
- **ART** (artifact) — a name of a human-made product, like a book, a song, a car, or a sandwich. Examples: *Mona Lisa, iPhone*.
- **MISC** — any other entity not covered in the list above, like nam*s of holidays, websites, battles, wars, sports events, hurricanes, etc. Example: *Black Friday*.

The model was fine-tuned on the [NER-UK 2.0 dataset](https://github.com/lang-uk/ner-uk), released by the [lang-uk](https://lang.org.ua).

Another transformer-based model **trained on 4 classes** for the SpaCy is available [here](https://huggingface.co/dchaplinsky/uk_ner_web_trf_best).

## Citation
TBA

Copyright: [Dmytro Chaplynskyi](https://twitter.com/dchaplinsky), [Mariana Romanyshyn](https://scholar.google.com/citations?user=yji2ZvIAAAAJ&hl=uk&oi=ao), [lang-uk project](https://lang.org.ua), 2024