kaidol-ner-multilingual

🌐 KAIdol NER Multilingual Model

This is a multilingual NER (Named Entity Recognition) model developed as part of the KAIdol Project.
It is based on Davlan/xlm-roberta-base-ner-hrl, fine-tuned on the WikiAnn dataset for Korean (ko), English (en), Spanish (es), and Portuguese (pt).

🧠 Model Details

• Base model: Davlan/xlm-roberta-base-ner-hrl
• NER Tags:
  • PER: Person
  • ORG: Organization
  • LOC: Location
• Tokenizer: AutoTokenizer from base model
• Max length: 128 tokens

📊 Training Configuration

✅ Performance Summary

Performance on es and pt will be updated after evaluation. Korean performance is limited due to tokenization issues in WikiAnn.

🚀 Usage Example

from transformers import AutoTokenizer, AutoModelForTokenClassification

model = AutoModelForTokenClassification.from_pretrained("developer-lunark/kaidol-ner-multilingual")
tokenizer = AutoTokenizer.from_pretrained("developer-lunark/kaidol-ner-multilingual")

tokens = tokenizer("Barack Obama nació en Hawái.", return_tensors="pt")
output = model(**tokens)

🧾 Label Mapping

{
  'O': 0,
  'B-PER': 1,
  'I-PER': 2,
  'B-ORG': 3,
  'I-ORG': 4,
  'B-LOC': 5,
  'I-LOC': 6
}

🔐 License

MIT License

📬 Contact

Developed by the [KAIdol 프로젝트 팀].

For questions or collaborations, contact: developer-lunark