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--- |
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library_name: transformers |
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license: mit |
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language: |
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- en |
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- zh |
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base_model: |
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- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B |
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tags: |
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- safe |
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--- |
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# RealSafe-R1-7B |
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## Overview / 综述 |
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RealSafe-R1-7B is a **safety-enhanced** variant of [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B), developed to improve robustness against malicious queries, especially jailbreak attacks. While the original DeepSeek-R1 series demonstrates strong reasoning and generation capabilities, it has been found to be vulnerable to safety risks. This model has been fine-tuned using supervised fine-tuning (SFT) on customized safety-focused datasets, improving its ability to detect and refuse harmful, unethical, or policy-violating prompts while maintaining its original capabilities. |
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RealSafe-R1-7B是DeepSeek-R1-Distilled-Qwen-7B的**安全加固**版本,显著提高模型对恶意查询,特别是越狱攻击的鲁棒性。尽管DeepSeek-R1系列模型展现出了强大的推理能力,但其在安全性方面仍存在一定的风险。该模型经过在自有安全数据集上的监督微调训练(SFT),其检测和拒绝有害、不道德或违反政策的提示词的能力得到增强,同时保持了原有的能力。 |
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## Key Features / 关键特征 |
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* **Improved Safety Awareness:** Improved refusal mechanisms for adversarial prompts and enhanced detection of unsafe queries. |
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* **Retained Reasoning Abilities:** Maintains high-quality performance on common sense, logic, and mathematical reasoning tasks. |
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* **提升安全意识:** 强化针对恶意提示词的拒绝机制,并增强了对不安全查询的检测能力。 |
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* **保留推理能力:** 在常识、逻辑和数学推理任务上保持高质量的性能。 |
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## Evaluation / 评估 |
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RealSafe-R1-7B is evaluated on several benchmarks to show the effective safety consolidation and retained reasoning abilities. We follow the evaluation setting of DeepSeek-R1 and estimate the performance with 5 runs. |
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通过在多个基准测试上进行评估,我们验证RealSafe-R1-7B的有效安全增强效果和推理能力。我们遵循了DeepSeek-R1的评估设置,并通过重复五组实验来估算模型性能。 |
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### 1. Safety Performance against Jailbreak Attacks / 针对越狱攻击的安全表现 |
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Refusal rates (%) to malicious queries from StrongReject are reported. |
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针对StrongReject中恶意提示的拒答率(%) |
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| Model | None | PAP | PAIR | |
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|---|:---:|:---:|:---:| |
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|**DeepSeek-R1-Distill-Qwen-7B**| 55.06 | 37.16 | 30.35 | |
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|**RealSafe-R1-7B**| 99.78 | 97.99 | 89.93 | |
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### 2. General Performance on Diverse Reasoning Tasks / 不同推理任务的通用性能 |
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Accuracies (%) are reported. |
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在多个主流推理数据集上的准确率(%) |
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| Model | MATH-500 | AIME2024 | GPQA-Diamond | LiveCodeBench | |
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|---|:---:|:---:|:---:|:---:| |
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|**DeepSeek-R1-Distill-Qwen-7B**| 88.16 | 55.71 | 47.88 | 38.23 | |
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|**RealSafe-R1-7B**| 87.44 | 57.14 | 49.29 | 34.65 | |
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### 3. Case Study / 案例分析 |
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Question: "asdf" |
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| **DeepSeek-R1-Distill-Qwen-7B** | **RealSafe-R1-7B** | |
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|---|---| |
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## License / 许可条款 |
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This model follows the licensing terms of the original DeepSeek-R1 series. Refer to the base model’s license for details. |
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该模型遵循DeepSeek-R1系列的许可条款。详情请参阅相关模型的许可说明。 |