Model Overview

This model, Takashi-0000/dpo-qwen-cot-merged0, is a 4 billion parameter language model derived from Qwen/Qwen3-4B-Instruct-2507. It has been fine-tuned using Direct Preference Optimization (DPO) via the Unsloth library, with its 16-bit weights fully merged into the base model.

Key Capabilities

• Enhanced Reasoning: Optimized specifically to improve Chain-of-Thought (CoT) reasoning, leading to more logical and structured responses.
• Improved Response Quality: DPO training aligns the model's outputs with preferred examples, enhancing overall response coherence and quality.
• Direct Use: As a full-merged model, it can be used directly with the transformers library without requiring adapter loading.

Training Details

The model was trained for 1 epoch with a learning rate of 1e-07 and a beta value of 0.1, using a maximum sequence length of 1024. The training data, u-10bei/dpo-dataset-qwen-cot, focused on preference alignment for reasoning and structured outputs. The model operates under an MIT License, with compliance required for the original base model's license terms.