README.md

---
language: tr
datasets:
- tquad1
- tquad2
- xquad 
tags: 
- answer-extraction
- question-answering
- question-generation
- text-generation
- text2text-generation
license: cc-by-4.0
---

# mt5-base for Turkish Question Generation
Automated question generation and question answering using text-to-text transformers by OBSS AI.

```python
from core.api import GenerationAPI
generation_api = GenerationAPI(model_url_or_path='mt5-base-3task-highlight-tquad2')
```

## Overview
**Language model:** mt5-base 
**Language:** Turkish
**Downstream-task:** Extractive QA/QG, Answer Extraction
**Training data:** TQuADv2-train
**Code:**  https://github.com/obss/turkish-question-generation
**Paper:**  https://arxiv.org/abs/2111.06476

## Hyperparameters
```
batch_size = 256
n_epochs = 15
base_LM_model = "mt5-base"
max_source_length = 512
max_target_length = 64
learning_rate = 1.0e-3
task_lisst = ["qa", "qg", "ans_ext"]
qg_format = "highlight"
``` 

## Performance
Refer to [paper](https://arxiv.org/abs/2111.06476).

## Usage 🔥
```python
from core.api import GenerationAPI
generation_api = GenerationAPI('mt5-base-3task-highlight-tquad2')

context = """
Bu modelin eğitiminde, Türkçe soru cevap verileri kullanılmıştır.
Paylaşılan model kullanılarak, Türkçe metinlerden otomatik olarak soru ve cevap
üretilebilir. Bu proje ile paylaşılan kaynak kodu ile Türkçe Soru Üretme
/ Soru Cevaplama konularında yeni akademik çalışmalar yapılabilir.
Projenin detaylarına paylaşılan Github ve Arxiv linklerinden ulaşılabilir.
"""

# a) Fully Automated Question Generation
generation_api(task='question-generation', context=context)

# b) Question Answering
question = "Bu model ne işe yarar?"
generation_api(task='question-answering', context=context, question=question)

# b) Answer Extraction
generation_api(task='answer-extraction', context=context)
```