
xlm-roberta model trained on [ukrainian ner](https://github.com/lang-uk/flair-ner) dataset from flair

| Test metric             | Results                   |
|-------------------------|---------------------------|
| test_f1_mac_ukr_ner     | 0.9900672435760498        |
| test_loss_ukr_ner       | 0.054602641612291336      |
| test_prec_mac_ukr_ner   | 0.9386032819747925        |
| test_rec_mac_ukr_ner    | 0.9383019208908081        |



```python
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline

tokenizer = AutoTokenizer.from_pretrained("EvanD/xlm-roberta-base-ukrainian-ner-ukrner")
ner_model = AutoModelForTokenClassification.from_pretrained("EvanD/xlm-roberta-base-ukrainian-ner-ukrner")

nlp = pipeline("ner", model=ner_model, tokenizer=tokenizer, aggregation_strategy="simple")
example = "Мене звуть Амадей Вольфганг, я живу в Берліні"

ner_results = nlp(example)
print(ner_results)
```
{"language": ["uk"], "tags": ["named-entity-recognition", "sequence-tagger-model"], "pipeline_tag": "token-classification", "widget": [{"text": "\u041c\u0435\u043d\u0435 \u0437\u0432\u0443\u0442\u044c \u0410\u043c\u0430\u0434\u0435\u0439 \u0412\u043e\u043b\u044c\u0444\u0433\u0430\u043d\u0433, \u044f \u0436\u0438\u0432\u0443 \u0432 \u0411\u0435\u0440\u043b\u0456\u043d\u0456"}], "inference": {"parameters": {"aggregation_strategy": "simple", "grouped_entities": true}}}
transformers pytorch xlm-roberta token-classification named-entity-recognition sequence-tagger-model uk autotrain_compatible endpoints_compatible has_space region:us