chess-qwen-finetuned-v2/README.md

library_name, tags

library_name	tags
transformers

Model Card for chess-qwen-finetuned-v2

Fine-tuned Qwen2.5-0.5B-Instruct for chess move prediction. Given a board position in FEN notation and a list of legal moves, the model outputs the best move in UCI format.

Model Description

• Developed by: Evelien van Driel
• Model type: Causal Language Model (decoder-only)
• Language(s) (NLP): English
• Finetuned from model: Qwen/Qwen2.5-0.5B-Instruct

Direct Use

Chess move prediction as part of INFOMTALC 2026 (Utrecht University). Used inside a TransformerPlayer class that queries the model given a FEN position.

Training Details

Training Data

aicrowd/ChessExplained dataset, examples 0–100,000 (100k positions). First fine-tuned v1 on examples 0–50,000 (chess-qwen-finetuned), then continued fine-tuning from v1 on examples 50,000–100,000 (v2). Moves are Stockfish-approved.

Training Hyperparameters

• Training regime:
• Base model: Qwen/Qwen2.5-0.5B-Instruct
• Method: LoRA
• Epochs: 3
• Batch size: 16
• Learning rate: 2e-4
• Hardware: Google Colab (T4 GPU)