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---
tags:
- spacy
- token-classification
language: uk
datasets:
- ner-uk
license: mit
model-index:
- name: uk_ner_wechsel-minixhofer-roberta-large
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9278959811
- name: NER Recall
type: recall
value: 0.9127906977
- name: NER F Score
type: f_score
value: 0.9202813599
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_wechsel-minixhofer-roberta-large
## Model description
**uk_ner_wechsel-minixhofer-roberta-large** is a fine-tuned [Roberta-Large model](https://huggingface.co/benjamin/roberta-large-wechsel-ukrainian) by @benjamin that is ready to use for **Named Entity Recognition** and achieves a **SoA** performance for the NER task for Ukrainian language. That's the best I have for NER so far
It has been trained to recognize four types of entities: location (LOC), organizations (ORG), person (PERS) and Miscellaneous (MISC).
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).
Smaller transformer based model for the SpaCy is available [here](https://huggingface.co/dchaplinsky/uk_ner_web_trf_base).
Copyright: [Dmytro Chaplynskyi](https://twitter.com/dchaplinsky), [lang-uk project](https://lang.org.ua), 2023
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