Rubric Generator using Fine-Tuned ML Model

This repository contains a machine learning model designed to generate grading rubrics based on a given question and a sample answer. The model has been fine-tuned on custom data and implemented in a Jupyter Notebook.

📁 Repository Structure

• rubric_generator.ipynb: Jupyter notebook containing the code to load and use the fine-tuned model to generate rubrics.
• converted_finetune_rubric_data.txt: Text file containing the data used to fine-tune the model. This file follows the format required for supervised fine-tuning (e.g., question-answer pairs with associated rubric).

🧠 Model Functionality

The model takes two inputs:

1. Question – The original question or prompt for which a rubric is needed.
2. Sample Answer – A sample response to the question.

Based on this input, it outputs a detailed rubric that can be used for evaluation or instructional purposes.

🚀 Getting Started

Prerequisites

• Python 3.7+
• Jupyter Notebook
• OpenAI or HuggingFace-compatible ML libraries (e.g., transformers, openai, etc.)
• pandas, json, or any required dependencies (see the notebook for details)

Running the Notebook

1. Clone the repository:

git clone https://github.com/yourusername/rubric-generator.git
cd rubric-generator

2. Open the notebook:

jupyter notebook rubric_generator.ipynb

3. Run the cells to load the model and generate a rubric based on your input.

📊 Fine-Tuning Data

The file converted_finetune_rubric_data.txt contains the dataset used for fine-tuning the model. This data includes:

• Structured examples of questions,
• Sample answers,
• Corresponding rubrics.

📄 License

This project is licensed under the MIT License.

---

Author: Mrigank Singh Contact: [email protected]