DisCO-1.5B-Lratio

DisCO-1.5B-Lratio

This model is a fine-tuned version of deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B on the agentica-org/DeepScaleR-Preview-Dataset.

It was fine-tuned as part of the paper DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization (paper link). Specifically, this model was fine-tuned by DisCO framework with Likelihood ratio (L-ratio) score function.

The code is available at: https://github.com/Optimization-AI/DisCO

Below are comparisons with baseline models and baseline methods for fine-tuning 1.5B models. OpenAI-o1-preview is included as a reference. MRL denotes Max Response Length utilized in training/testing. The bottom 9 methods are all for fine-tuning DeepSeek-R1-Distill-Qwen-1.5B model on the same DeepScaleR dataset. DS is short for DeepSeek-R1, DSR is short for DeepScalaR.

Citation

@article{li2025disco,
  title={DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization},
  author={Li, Gang and Lin, Ming and Galanti, Tomer and Tu, Zhengzhong and Yang, Tianbao},
  journal={arXiv preprint arXiv:2505.12366},
  year={2025}
}