Fine-Tuning Tiny Llama using Llama Factory To Mimic Professor's Writing Style

Overview

This project aims to fine-tune the Tiny Llama model using the Llama Factory to mimic my professor's writing style. The process involves several phases, including data collection, preprocessing, preparation, model fine-tuning, and evaluation. The final goal is to create a model that can generate text in the style of my professor's academic writings.

Phases of the Project

Phase 1: Data Collection

The first step in this project was to collect data by scraping my professor's Google Scholar page. The objective was to gather a comprehensive set of research articles published by the professor.

• Tool Used: Selenium
• Details: Selenium was used to automate the process of accessing the Google Scholar page and downloading the available PDFs of the research articles.

Phase 2: Data Preprocessing

After collecting the PDFs, the next step was to preprocess these documents to ensure they were in a usable format for training the model.

• Purpose: Normalize the content while preserving the writing style.
• Tools Used: pyMuPDF

Steps:

• Remove page headers, footers, images, and tables along with their captions.
• Convert the remaining content into paragraph format, as individual words and phrases are insufficient for capturing writing style.

Phase 3: Data Preparation

The preprocessed data needed to be formatted according to the requirements of the Llama Factory model training process.

• Initial Tools Tried: spaCy, TF-IDF, BERT
• Tool That Worked: OpenAI API

Process:

• Use the OpenAI API to generate the required data format.
• Ensure that the data is structured correctly for input into the Llama Factory model.

Phase 4: Model Fine-Tuning

With the data prepared, the next phase involved fine-tuning the Tiny Llama model.

• Environment: Google Colab
• Tools Used: Llama Factory

Steps:

• Set up the Google Colab notebook and import necessary libraries.
• Load the Llama Factory UI and integrate the dataset.
• Define the prompt format and other configurations required by Llama Factory.
• Run the fine-tuning process to train the Tiny Llama model on the professor's writing style.

Phase 5: Model Evaluation

The final phase focused on evaluating the performance of the fine-tuned model to ensure it accurately mimics the professor's writing style.

Process:

• Generate sample texts using the fine-tuned model.
• Compare the generated texts with the original writings to assess similarity in style and content.
• Make any necessary adjustments and re-train if needed.

Getting Started

Prerequisites

• Python 3.x
• Selenium
• pyMuPDF
• OpenAI API

Installation

• Clone the repository

git clone https://github.com/yourusername/finetuning-tiny-llama.git

• Install the necessary Python packages

pip install selenium pymupdf openai

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

Contact

For any questions or suggestions, please contact me at muhammadmuneeburrehman.vercel.app