62 lines
2.5 KiB
Markdown
62 lines
2.5 KiB
Markdown
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---
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library_name: transformers
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datasets:
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- codeparrot/apps
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- BAAI/TACO
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- AI-MO/NuminaMath-CoT
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language:
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- en
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base_model:
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- Qwen/Qwen2.5-32B-Instruct
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license: apache-2.0
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---
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is a 32B reasoning model trained from Qwen2.5-32B-Instruct with 17K data. The performance is on par with o1-preview model on both math and coding.
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Please see our [blog post](https://novasky-ai.github.io/posts/sky-t1/) for more details.
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- **Developed by:** NovaSky Team from Sky Computing Lab at UC Berkeley.
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## Training Details
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### Training Data
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17K verified correct responses from Qwen/QwQ-32B-Preview on coding, math. In addition, we add the science portion from the [Still-2 paper](https://arxiv.org/pdf/2412.09413).
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### Training Procedure
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We perform supervised fine tuning on the data, with a batch size of 96.
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#### Speeds
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We use Llama-Factory for training. On 8 H100, the training takes 19 hours with DeepSpeed Zero-3 Offload.
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## Evaluation
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| | Sky-T1-32B-Preview | Qwen-2.5-32B-Instruct | QwQ | o1-preview |
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|-----------------------|---------------------|--------|-------|------------|
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| Math500 | 82.4 | 76.2 | 85.4 | 81.4 |
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| AIME2024 | 43.3 | 16.7 | 50.0 | 40.0 |
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| LiveCodeBench-Easy | 86.3 | 84.6 | 90.7 | 92.9 |
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| LiveCodeBench-Medium | 56.8 | 40.8 | 56.3 | 54.9 |
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| LiveCodeBench-Hard | 17.9 | 9.8 | 17.1 | 16.3 |
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| GPQA-Diamond | 56.8 | 45.5 | 52.5 | 75.2 |
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## Acknowledgement
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We would like to thanks the compute resources from [Lambda Lab](https://lambdalabs.com/service/gpu-cloud?srsltid=AfmBOop5FnmEFTkavVtdZDsLWvHWNg6peXtat-OXJ9MW5GMNsk756PE5) and [AnyScale](https://www.anyscale.com/). We would like to thanks the academic feedback and support from the [Still-2 Team](https://arxiv.org/pdf/2412.09413), and [Junyang Lin](https://justinlin610.github.io/) from the [Qwen Team](https://qwenlm.github.io/).
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## Citation
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Please considering citing our blog post if you found it useful for your research. Thank you!
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```bibtex
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@misc{sky_t1_2025,
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author = {NovaSky Team},
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title = {Sky-T1: Fully open-source reasoning model with o1-preview performance in $450 budget},
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howpublished = {https://novasky-ai.github.io/posts/sky-t1},
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note = {Accessed: 2025-01-09},
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year = {2025}
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}
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