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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-base |
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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: 0.8987742191 |
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- name: NER Recall |
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type: recall |
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value: 0.8810077519 |
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- name: NER F Score |
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type: f_score |
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value: 0.8898023096 |
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--- |
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# roberta-uk-ner-base |
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## Model description |
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**roberta-uk-ner-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 **state-of-the-art performance** 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). |
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Copyright: Dmytro Chaplynskyi, [lang-uk project](https://lang.org.ua), 2022 |
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