phi3-7b-chess-beta / README.md
bhuvanmdev's picture
Create README.md
442eeb7 verified
|
raw
history blame
2.11 kB
---
license: mit
datasets:
- bhuvanmdev/chess-causal-formatted
language:
- en
tags:
- game
- experimetal
- chess
---
# Experimental Chess Model (Causal)
## Overview
This model is an experimental fine-tuned variant designed for **causal inference** on a very small subset of chess games. It leverages the base model obtained from Microsoft(phi-3-mini-4k-instruct) and has been fine-tuned using **Hugging Face Transformers** with the **Accelerate** library.
## Key Details
- **Task**: Causal inference on chess games
- **Base Model**: phi-3-mini-4k-instruct
- **Fine-Tuning Framework**: Hugging Face Transformers with Accelerate and peft
- **License**: MIT
## Description
The primary purpose of this model is to explore causal relationships within chess games. It was trained on a limited dataset, making it suitable for experimentation and research. While its performance may not match larger-scale models, it serves as a starting point for causal analysis in the chess games.
It also gives us an insight on how *causal models* react to high level chess games (2000> ELO).
## Limitations
- **Small Dataset**: Due to the limited data, the model's generalization capabilities are restricted.
- **Experimental Nature**: This model is not production-ready and should be used for research purposes only.
- **Causal Interpretation**: Interpretation of causal effects requires careful consideration and domain expertise.
## Usage
will be updated shortly !!!
## Metrics
will be updated shortly !!!
## Author
- **Author**: @bhuvanmdev <a href="https://github.com/bhuvanmdev" target="_blank">(GitHub profile)</a>
The main authors of the base model can be found <a href="https://huggingface.co/microsoft/Phi-3-mini-4k-instruct" target="_blank">Here</a>
Consider having a read at the <a href="https://huggingface.co/microsoft/Phi-3-mini-4k-instruct" target="_blank">original model card</a> to understand the biases,limitations and other necessary details.
**It's one of my first systematically fine-tuned model, Feel free to experiment with this model and contribute to its development! ;)
THANK YOU**
---