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+ ---
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+ license: mit
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+ datasets:
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+ - kfdong/STP_Lean_SFT
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+ base_model:
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+ - deepseek-ai/DeepSeek-Prover-V1.5-SFT
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+ ---
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+
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+ This is the final Self-play Theorem Prover model as described in the paper [https://arxiv.org/abs/2502.00212](https://arxiv.org/abs/2502.00212). The training and evalution code is avaliable [here](https://github.com/kfdong/STP/tree/main).
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+
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+ ```tex
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+ @article{dong2025beyond,
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+ title={Beyond Limited Data: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving},
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+ author={Dong, Kefan and Ma, Tengyu},
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+ journal={arXiv preprint arXiv:2502.00212},
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+ year={2025}
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+ }
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+ ```
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+
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+ ## 1. Evaluation Results
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+
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+ The table below compares the pass@3200 performance of STP (our model) and DeepSeek-Prover-V1.5 on miniF2F-test and ProofNet-test.
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+
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+ <div align="center">
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+
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+ | | miniF2F-test | ProofNet-test |
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+ |--------|------------------|------------------|
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+ | **DeepSeek-Prover-V1.5-SFT** | 53.3% ± 0.5% | 21.0% ± 0.9% |
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+ | **DeepSeek-Prover-V1.5-RL** | 54.9% ± 0.7% | 22.0% ± 0.5% |
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+ | **STP** | **65.0% ± 0.5%** | **23.9% ± 0.6%** |
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+
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+ </div>
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+
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+ ## 2. Dataset
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+
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+ We also release the dataset [here](https://huggingface.co/datasets/kfdong/STP_Lean_0320), which contains:
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+ - Extracted examples from mathlib4,
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+ - Generated correct proofs of statements in LeanWorkbook,
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+ - Generated correct proofs of conjectures proposed by our model during self-play training.
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+
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+ Our final model is finetuned from DeepSeek-Prover-V1.5-SFT with this dataset for 1 epoch.