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---
datasets:
- boun-tabi/squad_tr
language:
- tr
metrics:
- exact_match
- f1
library_name: transformers
base_model:
- dbmdz/convbert-base-turkish-cased
pipeline_tag: question-answering
tags:
- Turkish Question-Answering
---
# 🇹🇷 ConvBERTurkQA for Turkish Question-Answering
This model is a fine-tuned version of [ConvBERTurk Base](https://huggingface.co/dbmdz/convbert-base-turkish-cased) on the [SQuAD-TR](https://huggingface.co/datasets/boun-tabi/squad_tr), a machine‑translated Turkish version of the original [SQuAD 2.0](https://huggingface.co/datasets/rajpurkar/squad_v2). For more details about the dataset, methodology, and experiments, you can refer to the corresponding [research paper](https://dergipark.org.tr/en/pub/bsengineering/issue/88008/1596832).
---
## 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}
}
```
---
## How to Use
You can use the model directly with 🤗 Transformers:
```python
from transformers import pipeline
qa = pipeline(
"question-answering",
model="incidelen/convbert-base-turkish-cased-qa"
)
result = qa(
question="...",
context="..."
)
print(result)
```
## Evaluation Results
| Exact Match (%) | F1 Score (%) |
|--------------------|-------------------|
| 57.82 | 71.59 |
---
## Acknowledgments
Special thanks to [maydogan](https://huggingface.co/maydogan) for their contributions and support.
--- |