library_name: transformers
tags: []
pipeline_tag: image-text-to-text
license: apache-2.0
datasets:
- LangAGI-Lab/WebPRMCollection_preference_pair
language:
- en
Model Card for Web-Shepherd
Web-Shepherd is the first process reward model (PRM) designed specifically for web agents, as presented in the paper Web-Shepherd: Advancing PRMs for Reinforcing Web Agents. It evaluates trajectories at the step level to provide interpretable and cost-efficient feedback for both learning and inference-time decision making in web navigation tasks.
Model Details
- Developed by: [More Information Needed]
- Model type: Language Model
- License: apache-2.0
- Finetuned from model: Qwen3
Model Sources
- Repository: https://github.com/LangAGI-Lab/WebShepherd
- Paper: https://arxiv.org/abs/2505.15277
- Dataset: https://huggingface.co/datasets/LangAGI-Lab/WebPRMCollection_preference_pair
Uses
Direct Use
This model can be used to assess web navigation trajectories in a step-level.
Downstream Use
The model can be fine-tuned for web navigation tasks.
Training Details
Training Data
The model has been trained on the WebPRM Collection, a large-scale dataset with 40K step-level preference pairs and annotated checklists spanning diverse domains and difficulty levels.
Evaluation
The model was evaluated on the WebRewardBench, the first meta-evaluation benchmark for evaluating PRMs.