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ReflectRL Qwen2.5 Math 7B DAPO

This model checkpoint is part of the work presented in ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning.

ArtText modelBasismodellQwen/Qwen2.5-Math-7BVersionmodelVerleger@JinheCBewertung

Modellquelle

Art
Text model
Dateigröße
28,4 GB
Basismodell
Qwen/Qwen2.5-Math-7B
Version
vmodel
Aktualisiert
4. Okt. 2026
Verleger
@Jinhe
Downloads
17
Parameter
7B
Quelle
Hugging Face

Quellenbeschreibung

ReflectRL-Qwen2.5-Math-7B-GRPO-ReflectRL

This model checkpoint is part of the work presented in ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning.

ReflectRL is a lightweight framework for learning from Golden Negative Trajectories (GNTs) during on-policy post-training. Instead of imitating failed expert trajectories directly, ReflectRL uses them as reflective context during training and gradually transitions the policy back to direct reasoning for inference.

Citation

@article{reflectrl2027,
  title={ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning},
  author={Jinhe Bi and Chennan Zhou and Zengjie Jin and Aniri and Shuo Lu and Wenke Huang and Hu Cao and Xun Xiao and Zhihong Zhu and Volker Tresp and Fei Shen and Yunpu Ma and Tat-Seng Chua},
  year={2026}
}

Quellen

1 Quelle
Hugging FacePrimärVersion bb6557fc35419474bcf887ab5e2c81abc8ecf38a
huggingface.co/Jinhe/ReflectRL-Qwen2.5-Math-7B-DAPO/tree/bb6557fc35419474bcf887ab5e2c81abc8ecf38a

Verifiziert 4. Okt.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 28,4 GB · SHA-256 926f8e2066dd…1ea5 · Hugging Face

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Quellenauszüge

3 Auszüge

--- license: apache-2.0 library_name: transformers pipeline_tag: text-generation base_model: Qwen/Qwen2.5-Math-7B --- # ReflectRL-Qwen2.5-Math-7B-GRPO-ReflectRL This model checkpoint is part of the work presented in [ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning](https://huggingface.co/papers/2608.03972). ReflectRL is a lightweight framework for learning from Golden Negative Trajectories (GNTs) during on-policy post-training. Instead of imitating failed expert trajectories directly, ReflectRL uses them as reflective context during training and gradually transitions the policy back to direct reasoning for inference. - **Paper:** [ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning](https://huggingface.co/papers/2608.03972) - **Repository:** [GitHub Repository](https://github.com/bibisbar/ReflectRL) ## Citation ```bibtex @article{reflectrl2027, title={ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning}, author={Jinhe Bi and Chennan Zhou and Zengjie Jin and Aniri and Shuo Lu and Wenke Huang and Hu Cao and Xun Xiao and Zhihong Zhu and Volker Tresp and Fei Shen and Yunpu Ma and Tat-Seng Chua}, year={2026} } ```

Source context: 17 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo Jinhe/ReflectRL-Qwen2.5-Math-7B-DAPO

Source context: 188 downloads · 0 likes · Repo Jinhe/ReflectRL-Qwen2.5-Math-7B-DAPO