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beyoru
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beyoru
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| Model | Size | Partial credit | Strict pass |
|---|---|---|---|
| Ornith-1.0-9B | 9B | 22% | 3% |
| seul-preview | 9B | 28% | 7% |
| Qwen3.6-27B | 27B | 34% | 10% |
A custom benchmark also improves performance across all benchmark categories. This serves as a proof of concept (PoC) that reinforcement learning with an environment not only preserves the capabilities of the base model but also improves its overall accuracy.
RLVR training raises partial credit +6 points and more than doubles the strict pass rate over the base, closing a large fraction of the gap to a 3× larger model on the same tasks.
If you use seul in your research or projects, please cite:
bibtex
@misc{seul2026, title = {seul-preview}, author = {beyoru}, year = {2026}, publisher = {Hugging Face}, howpublished = {\url{https://huggingface.co/beyoru/seul-preview}}}