sakuraimo/your-lora-repo-dpo
The sakuraimo/your-lora-repo-dpo model is a 4 billion parameter instruction-tuned causal language model, fine-tuned from Qwen/Qwen3-4B-Instruct-2507 using Direct Preference Optimization (DPO). It has been optimized to improve reasoning capabilities (Chain-of-Thought) and structured response quality. This model is suitable for tasks requiring enhanced logical thinking and precise output formatting.
Loading preview...
Overview
This model, sakuraimo/your-lora-repo-dpo, is a 4 billion parameter language model derived from Qwen/Qwen3-4B-Instruct-2507. It has undergone Direct Preference Optimization (DPO) using the Unsloth library, specifically targeting improvements in reasoning and structured response generation. The repository provides the full-merged 16-bit weights, eliminating the need for adapter loading.
Key Capabilities
- Enhanced Reasoning: Optimized for Chain-of-Thought reasoning, aiming for more logical and coherent multi-step problem-solving.
- Structured Output Quality: Improved ability to generate well-formatted and structured responses based on preference data.
- Direct Use: As a merged model, it can be directly loaded and used with the
transformerslibrary without additional LoRA configuration.
Training Details
The model was fine-tuned for 1 epoch with a learning rate of 5e-06 and a beta value of 0.05. It utilized a maximum sequence length of 4096 tokens during DPO training. The training data used was [u-10bei/dpo-dataset-qwen-cot].
Good For
- Applications requiring improved logical reasoning.
- Scenarios where structured and high-quality outputs are critical.
- Developers looking for a readily deployable DPO-tuned Qwen3-4B variant.