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--- |
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language: |
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- en |
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license: apache-2.0 |
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model-index: |
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- name: Mistral7B-PairRM-SPPO-ExPO |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 36.73 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 13.68 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 0.91 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 3.58 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 8.66 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 17.24 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chujiezheng/Mistral7B-PairRM-SPPO-ExPO |
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name: Open LLM Leaderboard |
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--- |
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# Mistral7B-PairRM-SPPO-ExPO |
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The extrapolated (ExPO) model based on [`UCLA-AGI/Mistral7B-PairRM-SPPO`](https://huggingface.co/UCLA-AGI/Mistral7B-PairRM-SPPO) and [`mistralai/Mistral-7B-Instruct-v0.2`](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2), as in the "[Weak-to-Strong Extrapolation Expedites Alignment](https://arxiv.org/abs/2404.16792)" paper. |
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Specifically, we obtain this model by extrapolating **(alpha = 0.3)** from the weights of the SFT and DPO/RLHF checkpoints, achieving superior alignment with human preference. |
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This extrapolated model achieves the **35.4%** win rate and **31.8%** LC win rate on **AlpacaEval 2.0**, outperforming the original `Mistral7B-PairRM-SPPO`'s 32.2% and 30.5%, respectively. |
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## Evaluation Results |
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Evaluation results on the **AlpacaEval 2.0** benchmark (you can find the evaluation outputs on the [official GitHub repo](https://github.com/chujiezheng/LLM-Extrapolation/tree/main/results_alpaca)): |
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| | Win Rate (Ori) | LC Win Rate (Ori) | Win Rate (+ ExPO) | LC Win Rate (+ ExPO) | |
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| ------------------------------------ | -------------- | ----------------- | ----------------- | -------------------- | |
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| `HuggingFaceH4/zephyr-7b-alpha` | 6.7% | 10.0% | **10.6%** | **13.6%** | |
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| `HuggingFaceH4/zephyr-7b-beta` | 10.2% | 13.2% | **11.1%** | **14.0%** | |
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| `berkeley-nest/Starling-LM-7B-alpha` | 15.0% | 18.3% | **18.2%** | **19.5%** | |
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| `Nexusflow/Starling-LM-7B-beta` | 26.6% | 25.8% | **29.6%** | **26.4%** | |
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| `snorkelai/Snorkel-Mistral-PairRM` | 24.7% | 24.0% | **28.8%** | **26.4%** | |
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| `RLHFlow/LLaMA3-iterative-DPO-final` | 29.2% | 36.0% | **32.7%** | **37.8%** | |
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| `internlm/internlm2-chat-1.8b` | 3.8% | 4.0% | **5.2%** | **4.3%** | |
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| `internlm/internlm2-chat-7b` | 20.5% | 18.3% | **28.1%** | **22.7%** | |
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| `internlm/internlm2-chat-20b` | 36.1% | 24.9% | **46.2%** | **27.2%** | |
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| `allenai/tulu-2-dpo-7b` | 8.5% | 10.2% | **11.5%** | **11.7%** | |
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| `allenai/tulu-2-dpo-13b` | 11.2% | 15.5% | **15.6%** | **17.6%** | |
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| `allenai/tulu-2-dpo-70b` | 15.4% | 21.2% | **23.0%** | **25.7%** | |
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Evaluation results on the **MT-Bench** benchmark (you can find the evaluation outputs on the [official GitHub repo](https://github.com/chujiezheng/LLM-Extrapolation/tree/main/results_mtbench)): |
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| | Original | + ExPO | |
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| ------------------------------------ | -------- | -------- | |
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| `HuggingFaceH4/zephyr-7b-alpha` | 6.85 | **6.87** | |
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| `HuggingFaceH4/zephyr-7b-beta` | 7.02 | **7.06** | |
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| `berkeley-nest/Starling-LM-7B-alpha` | 7.82 | **7.91** | |
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| `Nexusflow/Starling-LM-7B-beta` | 8.10 | **8.18** | |
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| `snorkelai/Snorkel-Mistral-PairRM` | 7.63 | **7.69** | |
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| `RLHFlow/LLaMA3-iterative-DPO-final` | 8.08 | **8.45** | |
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| `internlm/internlm2-chat-1.8b` | 5.17 | **5.26** | |
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| `internlm/internlm2-chat-7b` | 7.72 | **7.80** | |
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| `internlm/internlm2-chat-20b` | 8.13 | **8.26** | |
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| `allenai/tulu-2-dpo-7b` | 6.35 | **6.38** | |
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| `allenai/tulu-2-dpo-13b` | 7.00 | **7.26** | |
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| `allenai/tulu-2-dpo-70b` | 7.79 | **8.03** | |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_chujiezheng__Mistral7B-PairRM-SPPO-ExPO) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |13.47| |
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|IFEval (0-Shot) |36.73| |
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|BBH (3-Shot) |13.68| |
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|MATH Lvl 5 (4-Shot)| 0.91| |
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|GPQA (0-shot) | 3.58| |
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|MuSR (0-shot) | 8.66| |
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|MMLU-PRO (5-shot) |17.24| |
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