| | --- |
| | tags: |
| | - spacy |
| | - token-classification |
| | language: uk |
| | datasets: |
| | - ner-uk |
| | license: mit |
| | model-index: |
| | - name: uk_ner_web_trf_base |
| | results: |
| | - task: |
| | name: NER |
| | type: token-classification |
| | metrics: |
| | - name: NER Precision |
| | type: precision |
| | value: 0.8987742191 |
| | - name: NER Recall |
| | type: recall |
| | value: 0.8810077519 |
| | - name: NER F Score |
| | type: f_score |
| | value: 0.8898023096 |
| | 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_base |
| |
|
| | ## Model description |
| |
|
| | **uk_ner_web_trf_base** is a fine-tuned [XLM-Roberta model](https://huggingface.co/xlm-roberta-base) that is ready to use for **Named Entity Recognition** and achieves a performance close to **SoA** for the NER task for Ukrainian language. It has been trained to recognize four types of entities: location (LOC), organizations (ORG), person (PERS) and Miscellaneous (MISC). |
| |
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| | 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). |
| | A bigger model, trained on xlm-roberta-large with the **State-of-the-Art** performance is available [here](https://huggingface.co/dchaplinsky/uk_ner_web_trf_large). |
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| | Copyright: [Dmytro Chaplynskyi](https://twitter.com/dchaplinsky), [lang-uk project](https://lang.org.ua), 2022 |
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