Automated question generation and question answering from Turkish texts using text-to-text transformers

Related tags

Text Data & NLPmultilingualnlpturkishtransformersquestion-answeringarxivmt5question-generationt5wandbneptune-aixquad
Overview
citation

If you use this software in your work, please cite as:

@article{akyon2021automated,
  title={Automated question generation and question answering from Turkish texts using text-to-text transformers},
  author={Akyon, Fatih Cagatay and Cavusoglu, Devrim and Cengiz, Cemil and Altinuc, Sinan Onur and Temizel, Alptekin},
  journal={arXiv preprint arXiv:2111.06476},
  year={2021}
}
install 
git clone https://github.com/obss/turkish-question-generation.git
cd turkish-question-generation
pip install -r requirements.txt
train
  • start a training using args:
python run.py --model_name_or_path google/mt5-small  --output_dir runs/exp1 --do_train --do_eval --tokenizer_name_or_path mt5_qg_tokenizer --per_device_train_batch_size 4 --gradient_accumulation_steps 2 --learning_rate 1e-4 --seed 42 --save_total_limit 1
python run.py config.json
python run.py config.yaml
evaluate
  • arrange related params in config:
do_train: false
do_eval: true
eval_dataset_list: ["tquad2-valid", "xquad.tr"]
prepare_data: true
mt5_task_list: ["qa", "qg", "ans_ext"]
mt5_qg_format: "both"
no_cuda: false
  • start an evaluation:
python run.py config.yaml
neptune
  • install neptune:
pip install neptune-client
  • download config file and arrange neptune params:
run_name: 'exp1'
neptune_project: 'name/project'
neptune_api_token: 'YOUR_API_TOKEN'
  • start a training:
python train.py config.yaml
wandb
  • install wandb:
pip install wandb
  • download config file and arrange wandb params:
run_name: 'exp1'
wandb_project: 'turque'
  • start a training:
python train.py config.yaml
finetuned checkpoints
Name Model data
train		 params
(M)		 model size
(GB)
turque-s1 mt5-small tquad2-train+tquad2-valid+xquad.tr 60M 1.2GB
mt5-small-3task-both-tquad2 mt5-small tquad2-train 60M 1.2GB
mt5-small-3task-prepend-tquad2 mt5-small tquad2-train 60M 1.2GB
mt5-base-3task-both-tquad2 mt5-base tquad2-train 220M 2.3GB
format
  • answer extraction:

input:

Osman Bey 1258 yılında Söğüt’te doğdu. Osman Bey 1 Ağustos 1326’da Bursa’da hayatını kaybetmiştir.1281 yılında Osman Bey 23 yaşında iken Ahi teşkilatından olan Şeyh Edebali’nin kızı Malhun Hatun ile evlendi." "> 
"
      
        Osman Bey 1258 yılında Söğüt’te doğdu. 
       
         Osman Bey 1 Ağustos 1326’da Bursa’da hayatını kaybetmiştir.1281 yılında Osman Bey 23 yaşında iken Ahi teşkilatından olan Şeyh Edebali’nin kızı Malhun Hatun ile evlendi."

target:


    
      1258 
     
       Söğüt’te
  • question answering:

input:

"question: Osman Bey nerede doğmuştur? context: Osman Bey 1258 yılında Söğüt’te doğdu. Osman Bey 1 Ağustos 1326’da Bursa’da hayatını kaybetmiştir.1281 yılında Osman Bey 23 yaşında iken Ahi teşkilatından olan Şeyh Edebali’nin kızı Malhun Hatun ile evlendi."

target:

"Söğüt’te"
  • question generation (prepend):

input:

"answer: Söğüt’te context: Osman Bey 1258 yılında Söğüt’te doğdu. Osman Bey 1 Ağustos 1326’da Bursa’da hayatını kaybetmiştir.1281 yılında Osman Bey 23 yaşında iken Ahi teşkilatından olan Şeyh Edebali’nin kızı Malhun Hatun ile evlendi."

target:

"Osman Bey nerede doğmuştur?"
  • question generation (highlight):

input:

Söğüt’te doğdu. Osman Bey 1 Ağustos 1326’da Bursa’da hayatını kaybetmiştir.1281 yılında Osman Bey 23 yaşında iken Ahi teşkilatından olan Şeyh Edebali’nin kızı Malhun Hatun ile evlendi." "> 
"generate question: Osman Bey 1258 yılında 
     
       Söğüt’te 
      
        doğdu. Osman Bey 1 Ağustos 1326’da Bursa’da hayatını kaybetmiştir.1281 yılında Osman Bey 23 yaşında iken Ahi teşkilatından olan Şeyh Edebali’nin kızı Malhun Hatun ile evlendi."

target:

"Osman Bey nerede doğmuştur?"
  • question generation (both):

input:

Söğüt’te doğdu. Osman Bey 1 Ağustos 1326’da Bursa’da hayatını kaybetmiştir.1281 yılında Osman Bey 23 yaşında iken Ahi teşkilatından olan Şeyh Edebali’nin kızı Malhun Hatun ile evlendi." "> 
"answer: Söğüt’te context: Osman Bey 1258 yılında 
     
       Söğüt’te 
      
        doğdu. Osman Bey 1 Ağustos 1326’da Bursa’da hayatını kaybetmiştir.1281 yılında Osman Bey 23 yaşında iken Ahi teşkilatından olan Şeyh Edebali’nin kızı Malhun Hatun ile evlendi."

target:

"Osman Bey nerede doğmuştur?"
paper results
BERTurk-base and mT5-base QA evaluation results for TQuADv2 fine-tuning.

mT5-base QG evaluation results for single-task (ST) and multi-task (MT) for TQuADv2 fine-tuning.

TQuADv1 and TQuADv2 fine-tuning QG evaluation results for multi-task mT5 variants. MT-Both means, mT5 model is fine-tuned with ’Both’ input format and in a multi-task setting.

paper configs

You can find the config files used in the paper under configs/paper.

contributing

Before opening a PR:

  • Install required development packages:
pip install "black==21.7b0" "flake8==3.9.2" "isort==5.9.2"
  • Reformat with black and isort:
black . --config pyproject.toml
isort .
You might also like...
NeuralQA: A Usable Library for Question Answering on Large Datasets with BERT
NeuralQA: A Usable Library for Question Answering on Large Datasets with BERT

NeuralQA: A Usable Library for (Extractive) Question Answering on Large Datasets with BERT Still in alpha, lots of changes anticipated. View demo on n

Victor Dibia 184 Feb 10, 2021
Knowledge Graph,Question Answering System，基于知识图谱和向量检索的医疗诊断问答系统
Knowledge Graph,Question Answering System，基于知识图谱和向量检索的医疗诊断问答系统

Knowledge Graph,Question Answering System，基于知识图谱和向量检索的医疗诊断问答系统

wangle 823 Dec 28, 2022
Baseline code for Korean open domain question answering(ODQA)
Baseline code for Korean open domain question answering(ODQA)

Open-Domain Question Answering(ODQA)는 다양한 주제에 대한 문서 집합으로부터 자연어 질의에 대한 답변을 찾아오는 task입니다. 이때 사용자 질의에 답변하기 위해 주어지는 지문이 따로 존재하지 않습니다. 따라서 사전에 구축되어있는 Knowl

VUMBLEB 69 Nov 4, 2022
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering

Disfl-QA is a targeted dataset for contextual disfluencies in an information seeking setting, namely question answering over Wikipedia passages. Disfl-QA builds upon the SQuAD-v2 (Rajpurkar et al., 2018) dataset, where each question in the dev set is annotated to add a contextual disfluency using the paragraph as a source of distractors.

Google Research Datasets 52 Jun 21, 2022
CCQA A New Web-Scale Question Answering Dataset for Model Pre-Training

CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training This is the official repository for the code and models of the paper CCQA: A N

Meta Research 29 Nov 30, 2022
chaii - hindi & tamil question answering

chaii - hindi & tamil question answering This is the solution for rank 5th in Kaggle competition: chaii - Hindi and Tamil Question Answering. The comp

abhishek thakur 33 Dec 18, 2022
Contact Extraction with Question Answering.

contactsQA Extraction of contact entities from address blocks and imprints with Extractive Question Answering. Goal Input: Dr. Max Mustermann Hauptstr

Jan 2 Apr 20, 2022
BERT-based Financial Question Answering System
BERT-based Financial Question Answering System

BERT-based Financial Question Answering System In this example, we use Jina, PyTorch, and Hugging Face transformers to build a production-ready BERT-b

Bithiah Yuan 61 Sep 18, 2022
Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts
Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts

gpt-2-simple A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI's GPT-2 text generation model (specifical

Max Woolf 3.1k Jan 7, 2023
Owner
Open Business Software Solutions
Open Source for Open Business
Open Business Software Solutions
GitHub Repository
A PyTorch implementation of the Transformer model in "Attention is All You Need".

Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V

Yu-Hsiang Huang 7.1k Jan 05, 2023
In this repository, I have developed an end to end Automatic speech recognition project. I have developed the neural network model for automatic speech recognition with PyTorch and used MLflow to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry.

End to End Automatic Speech Recognition In this repository, I have developed an end to end Automatic speech recognition project. I have developed the

Victor Basu 22 Nov 13, 2022
🌐 Translation microservice powered by AI

Dot Translate 🌐 A microservice for quick and local translation using A.I. This service starts a local webserver used for neural machine translation.

Dot HQ 48 Nov 22, 2022
iSTFTNet : Fast and Lightweight Mel-spectrogram Vocoder Incorporating Inverse Short-time Fourier Transform

iSTFTNet : Fast and Lightweight Mel-spectrogram Vocoder Incorporating Inverse Short-time Fourier Transform This repo try to implement iSTFTNet : Fast

Rishikesh (ऋषिकेश) 126 Jan 02, 2023
Sorce code and datasets for "K-BERT: Enabling Language Representation with Knowledge Graph",

K-BERT Sorce code and datasets for "K-BERT: Enabling Language Representation with Knowledge Graph", which is implemented based on the UER framework. R

Weijie Liu 834 Jan 09, 2023
Script and models for clustering LAION-400m CLIP embeddings.

clustering-laion400m Script and models for clustering LAION-400m CLIP embeddings. Models were fit on the first million or so image embeddings. A subje

Peter Baylies 22 Oct 04, 2022
Resources for "Natural Language Processing" Coursera course.

Natural Language Processing course resources This github contains practical assignments for Natural Language Processing course by Higher School of Eco

Advanced Machine Learning specialisation by HSE 1.1k Jan 01, 2023
A retro text-to-speech bot for Discord

hawking A retro text-to-speech bot for Discord, designed to work with all of the stuff you might've seen in Moonbase Alpha, using the existing command

Nick Schorr 23 Dec 25, 2022
Quick insights from Zoom meeting transcripts using Graph + NLP

Transcript Analysis - Graph + NLP This program extracts insights from Zoom Meeting Transcripts (.vtt) using TigerGraph and NLTK. In order to run this

Advit Deepak 7 Sep 17, 2022
pytorch implementation of Attention is all you need

A Pytorch Implementation of the Transformer: Attention Is All You Need Our implementation is largely based on Tensorflow implementation Requirements N

230 Dec 07, 2022
ETM - R package for Topic Modelling in Embedding Spaces

ETM - R package for Topic Modelling in Embedding Spaces This repository contains an R package called topicmodels.etm which is an implementation of ETM

bnosac 37 Nov 06, 2022
A deep learning-based translation library built on Huggingface transformers

DL Translate A deep learning-based translation library built on Huggingface transformers and Facebook's mBART-Large 💻 GitHub Repository 📚 Documentat

Xing Han Lu 244 Dec 30, 2022
Espresso: A Fast End-to-End Neural Speech Recognition Toolkit

Espresso Espresso is an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning libra

Yiming Wang 919 Jan 03, 2023
⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x using fastT5.

Reduce T5 model size by 3X and increase the inference speed up to 5X. Install Usage Details Functionalities Benchmarks Onnx model Quantized onnx model

Kiran R 399 Jan 05, 2023
A Non-Autoregressive Transformer based TTS, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate TTS.

A Non-Autoregressive Transformer based TTS, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to ach

Keon Lee 237 Jan 02, 2023
Voice Assistant inspired by Google Assistant, Cortana, Alexa, Siri, ...

author: @shival_gupta VoiceAI This program is an example of a simple virtual assitant It will listen to you and do accordingly It will begin with wish

Shival Gupta 1 Jan 06, 2022
HAN2HAN : Hangul Font Generation

HAN2HAN : Hangul Font Generation

Changwoo Lee 36 Dec 28, 2022
Blazing fast language detection using fastText model

Luga A blazing fast language detection using fastText's language models Luga is a Swahili word for language. fastText provides a blazing fast language

Prayson Wilfred Daniel 18 Dec 20, 2022
Using Bert as the backbone model for lime, designed for NLP task explanation (sentence pair text classification task)

Lime Comparing deep contextualized model for sentences highlighting task. In addition, take the classic explanation model "LIME" with bert-base model

JHJu 2 Jan 18, 2022
Official PyTorch Implementation of paper "NeLF: Neural Light-transport Field for Single Portrait View Synthesis and Relighting", EGSR 2021.

NeLF: Neural Light-transport Field for Single Portrait View Synthesis and Relighting Official PyTorch Implementation of paper "NeLF: Neural Light-tran

Ken Lin 38 Dec 26, 2022