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README.md
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---
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license: mit
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---
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---
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tags:
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- spacy
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- token-classification
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language: uk
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datasets:
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- ner-uk
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license: mit
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model-index:
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- name: roberta-uk-ner-large
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results:
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- task:
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name: NER
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type: token-classification
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metrics:
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- name: NER Precision
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type: precision
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value: 0.9183514774
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- name: NER Recall
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type: recall
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value: 0.915503876
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- name: NER F Score
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type: f_score
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value: 0.9169254658
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widget:
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- 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."
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# roberta-uk-ner-large
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## Model description
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**roberta-uk-ner-large** 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 **SoA** performance for the NER task for Ukrainian language. It outperforms another SpaCy model, [uk_core_news_trf](https://huggingface.co/ukr-models/uk_core_news_trf) on a NER task I.t 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).
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Copyright: Dmytro Chaplynskyi, [lang-uk project](https://lang.org.ua), 2022
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