rico5550/tic_tac_toe

Fine-Tuning ChatGPT for Tic Tac Toe Rules Simplification

This program is designed to fine-tune a ChatGPT model to standardize various descriptions of Tic Tac Toe rules into a consistent format. By leveraging a single-shot learning strategy, it achieves high accuracy with a minimal training dataset. A key component of our approach is the use of a file containing well-structured sentences that serve as examples of the desired standard format. These examples guide the model in transforming diverse rule descriptions into a uniform presentation, making the solution highly effective for applications that necessitate rule standardization. This method not only enhances the model's understanding but also ensures that the output aligns closely with our predefined standards, regardless of the input's original phrasing.

Installation

For detailed installation instructions, including prerequisites and dependencies, please refer to the Installation Guide.

Ensure you follow the steps outlined in the guide to set up your environment correctly for running the program.

Features

• Single-Shot Learning: Utilizes a small, focused training set for effective learning and application to broader datasets.
• Tic Tac Toe Rule Generalization: Simplifies varied rule descriptions into a common, standardized format.
• Dataset Creation: Automatically generates training and testing datasets tailored for fine-tuning ChatGPT models. The process incorporates the Flesch-Kincaid readability scale to create paraphrases at various reading levels, ensuring the training data covers a wide spectrum of linguistic complexity.

Examples

Input: "Participants are forbidden from putting their mark in a space that is already occupied by another symbol."

Output: "Players can not place their symbol in a non-empty space."

Acknowledgments

• OpenAI for the ChatGPT model and API.
• Ted Brown for mentorship and support