README.md

metadata

datasets:
  - boun-tabi/squad_tr
language:
  - tr
metrics:
  - exact_match
  - f1
library_name: transformers
base_model:
  - dbmdz/distilbert-base-turkish-cased
pipeline_tag: question-answering
tags:
  - Turkish Question-Answering

🇹🇷 DistilBERTurkQA for Turkish Question-Answering

This model is a fine-tuned version of DistilBERTurk Base on the SQuAD-TR, a machine‑translated Turkish version of the original SQuAD 2.0. For more details about the dataset, methodology, and experiments, you can refer to the corresponding research paper.

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Citation

If you use this model in your research or application, please cite the following paper:

@article{incidelen8performance,
  title={Performance Evaluation of Transformer-Based Pre-Trained Language Models for Turkish Question-Answering},
  author={{\.I}ncidelen, Mert and Aydo{\u{g}}an, Murat},
  journal={Black Sea Journal of Engineering and Science},
  volume={8},
  number={2},
  pages={15--16},
  publisher={U{\u{g}}ur {\c{S}}EN}
}

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How to Use

You can use the model directly with 🤗 Transformers:

from transformers import pipeline

qa = pipeline(
    "question-answering",
    model="incidelen/distilbert-base-turkish-cased-qa"
)

result = qa(
    question="...",
    context="..."
)

print(result)

Evaluation Results

Exact Match (%)	F1 Score (%)
41.26	55.75

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Acknowledgments

Special thanks to maydogan for their contributions and support.

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