rl-research/DR-Tulu-SFT-8B
[!NOTE] For full information, go check out the Dr Tulu paper here.
<img src="https://huggingface.co/rl-research/DR-Tulu-SFT-8B/resolve/main/drtululogo.png" alt="Figure 1" width="500"/>
DR Tulu SFT 8B
This is the SFT checkpoint of DR Tulu, an open deep research agent trained on top of Qwen3-8B.
This model has undergone SFT training on this dataset. For more details on DR Tulu please read our [paper](https://allenai.org/papers/drtulu)!
Inference and Usage
This model has been trained for tool-use using the dr-agent-lib framework. As such, running it out of the box with HuggingFace or vLLM will not work well!
See our github for more details on installation and how to run our model. Or check out our demo!
Evaluation Results
We provide evaluation instructions in our github.
For more baselines, explanations of this table, and analysis of results, check out the Dr Tulu paper!
Intended uses & limitations
This model is licensed under Apache 2.0. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines.
Training
The following hyperparameters were used during training:
- learning_rate: 4e-05
- trainbatchsize: 1
- evalbatchsize: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradientaccumulationsteps: 16
- totaltrainbatch_size: 128
- totalevalbatch_size: 64
- optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
- lrschedulertype: cosine
- lrschedulerwarmup_ratio: 0.1
- num_epochs: 5
For futher details, check out the Dr Tulu paper.
Links
Citation
@article{shao2025dr,
title={DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research},
author={Shao, Rulin and Asai, Akari and Shen, Shannon Zejiang and Ivison, Hamish and Kishore, Varsha and Zhuo, Jingming and Zhao, Xinran and Park, Molly and Finlayson, Samuel G and Sontag, David and others},
journal={arXiv preprint arXiv:2511.19399},
year={2025}
}