Overview

This model, konagayoshi/dpo-qwen-cot-merged, is a 4 billion parameter language model built upon the Qwen/Qwen3-4B-Instruct-2507 base. It has been specifically fine-tuned using Direct Preference Optimization (DPO) via the Unsloth library to align its responses with preferred outputs.

Key Capabilities

• Enhanced Reasoning: Optimized to improve Chain-of-Thought (CoT) reasoning, making it suitable for tasks requiring logical steps and deductions.
• Structured Responses: Focuses on generating higher quality, more structured outputs based on a preference dataset.
• Direct Use: Provided as a full-merged 16-bit model, eliminating the need for adapter loading and allowing direct use with the transformers library.

Training Details

The model underwent 1 epoch of DPO training with a learning rate of 1e-07 and a beta value of 0.1. It utilized a maximum sequence length of 1024 and incorporated LoRA configuration (r=8, alpha=16) which has been merged into the base model. The training data used was u-10bei/dpo-dataset-qwen-cot.

Good For

• Applications requiring improved logical reasoning.
• Generating well-structured and coherent text outputs.
• Developers looking for a Qwen3-based model with enhanced preference alignment for reasoning tasks.