berturk-sunlp-ner-turkish

berturk-sunlp-ner-turkish

Introduction

[berturk-sunlp-ner-turkish] is a NER model that was fine-tuned from the BERTurk-cased model on the SUNLP-NER-Twitter dataset.

Training data

The model was trained on the SUNLP-NER-Twitter dataset (5000 tweets). The dataset can be found at https://github.com/SU-NLP/SUNLP-Twitter-NER-Dataset Named entity types are as follows: Person, Location, Organization, Time, Money, Product, TV-Show

How to use berturk-sunlp-ner-turkish with HuggingFace

from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("busecarik/berturk-sunlp-ner-turkish")
model = AutoModelForTokenClassification.from_pretrained("busecarik/berturk-sunlp-ner-turkish")

Model performances on SUNLP-NER-Twitter test set (metric: seqeval)

Classification Report

You can cite the following paper, if you use this model:

@InProceedings{ark-yeniterzi:2022:LREC,
  author    = {\c{C}ar\i k, Buse  and  Yeniterzi, Reyyan},
  title     = {A Twitter Corpus for Named Entity Recognition in Turkish},
  booktitle      = {Proceedings of the Language Resources and Evaluation Conference},
  month          = {June},
  year           = {2022},
  address        = {Marseille, France},
  publisher      = {European Language Resources Association},
  pages     = {4546--4551},
  url       = {https://aclanthology.org/2022.lrec-1.484}
}