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xlm-roberta-base-danish-ner-daner
EvanD/xlm-roberta-base-danish-ner-daner
xlm-roberta-base-danish-ner-daner is a token classification model from EvanD. Use it when you need labels on individual words, such as names. It is set up for transformers.
xlm-roberta model trained on DaNe, performing 97.1 f1-Macro on test set.
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jan 3, 2024
- Updated
- Jan 6, 2024
- SHA
- 0dd3cc53
Try a prompt
Model card
From the Hugging Face model README
xlm-roberta model trained on DaNe, performing 97.1 f1-Macro on test set.
| Test metric | Results |
|---|---|
| test_f1_mac_dane_ner | 0.9713183641433716 |
| test_loss_dane_ner | 0.11384682357311249 |
| test_prec_mac_dane_ner | 0.8712055087089539 |
| test_rec_mac_dane_ner | 0.8684446811676025 |
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline
tokenizer = AutoTokenizer.from_pretrained("EvanD/xlm-roberta-base-danish-ner-daner")
ner_model = AutoModelForTokenClassification.from_pretrained("EvanD/xlm-roberta-base-danish-ner-daner")
nlp = pipeline("ner", model=ner_model, tokenizer=tokenizer, aggregation_strategy="simple")
example = "Mit navn er Amadeus Wolfgang, og jeg bor i Berlin"
ner_results = nlp(example)
print(ner_results)
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- Languages
- da
- Created
- Jan 3, 2024
- Updated
- Jan 6, 2024