metadata
license: apache-2.0
datasets:
- SJTULean/LeanStatement_SFT
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
result:
dataset:
type: Formalizer Lean
name: miniF2F
metrics:
- name: pass@1
type: pass@1
value: 0.9406
verified: false
base_model:
- Qwen/Qwen2.5-7B-Instruct
LeanFormalizer_SFT
Based on Qwen2.5-7b and trained on our LeanStatement_SFT dataset, our model achieves state-of-the-art performance in formal mathematics verification, with a pass@1 compilation success rate of 94.1% (459/488) on MiniF2F and 75.4% (282/374) on ProofNet benchmarks as of December 2024(while our PPO model achieves 95.3% on MiniF2F and 76.0% on Proofnet). These results demonstrate the effectiveness of scaling laws in mathematical formalization using the Lean theorem prover.