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This is our capstone project for Human Language Technologies course.

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Question and MCQ Generation

Project Overview:

Our project automate the process of generating questions from text passages.Here, we have finetuned T5-small model for question generation. and used the same finetuned model for MCQ generation.

Acces our training notebooks and models

  • Access our Colab notebook here.
  • Acces our Question Generation Model on Hugging Face here
  • Training notebook on Kaggle [End to End Generation] here

View our Demo:

Demo Video

Run

  • Clone the repository : git clone [email protected]:Nadika18/Question_Generation.git
  • Install the requirements : pip install -r requirements.txt
  • Run python3 manage.py runserver in the terminal
  • Open the browser and go to http://localhost:8000/
  • Submit the question at /
  • Get the generated question at /submit-question

System diagram for finetuning T5-small model for Question Generation

Question Generation

System diagram for MCQ generation workflow

MCQ Generation

Outputs:

1. Question Generation:

Question Generation

Question Generation

2. MCQ Generation:

Question Generation

Question Generation

Question Generation without Answers : End to End Generation

TrainingArguments

Parameter Value
evaluation_strategy epoch
learning_rate 2e-5
per_device_train_batch_size 8
per_device_eval_batch_size 8
num_train_epochs 3
weight_decay 0.01
save_strategy epoch
disable_tqdm False
gradient_accumulation_steps 2

Note : The batch size and acclumulation steps were decreased during training due to memory constraints.

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This is our capstone project for Human Language Technologies course.

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