| --- |
| 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 |
| |
