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Model: EvelienUU/chess-qwen-finetuned-v2
Source: Original Platform

README.md

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+library_name: transformers
+tags: []
+---
+
+# 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)