YAML Metadata Warning: The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

Model Card for Model ID

Model Details

Model Description

Developed by: Hao Peng@THUKEG
Model type: Generative reward model
Language(s) (NLP): English, CHinese
License: apache-2.0
Finetuned from model [optional]: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B

Model Sources [optional]

Repository: https://github.com/THU-KEG/VerIF
Paper: https://arxiv.org/abs/2506.09942

Training Details

Training Data

This model is trained from DeepSeek-R1-Distill-Qwen-7B using 131k critic data IF-Verifier-Data. This model is used for verifying soft constraints of instruction following. Deploying IF-Verifier-7B requires only one single H800 GPU, with an average reward computation time of 120 seconds per batch, which can be further reduced with multi-GPUs.

Results

The model trained using this model is comparable with that of QwQ 32B.

Summary

Please refer to our paper and our GitHub repo (https://github.com/THU-KEG/VerIF) for more details.

Citation

If this model helps, please kindly cite us:

@misc{peng2025verif,
      title={VerIF: Verification Engineering for Reinforcement Learning in Instruction Following}, 
      author={Hao Peng and Yunjia Qi and Xiaozhi Wang and Bin Xu and Lei Hou and Juanzi Li},
      year={2025},
      eprint={2506.09942},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2506.09942}, 
}