open-llm-leaderboard-old/details_SilverCoder66__Mistral-7B-Instruct-adapt-vbh

该数据集是在模型SilverCoder66/Mistral-7B-Instruct-adapt-vbh在Open LLM Leaderboard上的评估运行期间自动创建的。数据集包含63个配置，每个配置对应一个评估任务。数据集是从1次运行中创建的，每次运行都可以在每个配置中作为一个特定的分割找到，分割名称使用运行的时间戳命名。train分割始终指向最新的结果。此外，还有一个额外的results配置，用于存储运行的聚合结果，并用于计算和显示Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

该数据集是在对模型 SilverCoder66/Mistral-7B-Instruct-adapt-vbh 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

数据集组成

• 数据集包含 63 个配置，每个配置对应一个评估任务。
• 数据集从 1 次运行中创建。每次运行可以在每个配置中找到特定的拆分，拆分名称使用运行的时间戳。
• "train" 拆分始终指向最新的结果。
• 一个额外的配置 "results" 存储所有运行的聚合结果，用于计算和显示 Open LLM Leaderboard 上的聚合指标。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_SilverCoder66__Mistral-7B-Instruct-adapt-vbh", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-26T12:24:39.598796 运行的最新结果：

python { "all": { "acc": 0.2531335074827756, "acc_stderr": 0.030786877262183168, "acc_norm": 0.25425934425233987, "acc_norm_stderr": 0.0316105049529613, "mc1": 0.24479804161566707, "mc1_stderr": 0.015051869486714997, "mc2": 0.4794945059404648, "mc2_stderr": 0.0165551800490445 }, "harness|arc:challenge|25": { "acc": 0.21416382252559726, "acc_stderr": 0.011988383205966496, "acc_norm": 0.27559726962457337, "acc_norm_stderr": 0.013057169655761838 }, "harness|hellaswag|10": { "acc": 0.2566221868153754, "acc_stderr": 0.0043587645964010355, "acc_norm": 0.25731925911173076, "acc_norm_stderr": 0.00436263363737448 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04072314811876837, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04072314811876837 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.3026315789473684, "acc_stderr": 0.037385206761196665, "acc_norm": 0.3026315789473684, "acc_norm_stderr": 0.037385206761196665 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.23, "acc_stderr": 0.04229525846816506, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816506 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.2188679245283019, "acc_stderr": 0.02544786382510861, "acc_norm": 0.2188679245283019, "acc_norm_stderr": 0.02544786382510861 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2569444444444444, "acc_stderr": 0.03653946969442099, "acc_norm": 0.2569444444444444, "acc_norm_stderr": 0.03653946969442099 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.18, "acc_stderr": 0.03861229196653694, "acc_norm": 0.18, "acc_norm_stderr": 0.03861229196653694 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.26, "acc_stderr": 0.0440844002276808, "acc_norm": 0.26, "acc_norm_stderr": 0.0440844002276808 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.24855491329479767, "acc_stderr": 0.03295304696818318, "acc_norm": 0.24855491329479767, "acc_norm_stderr": 0.03295304696818318 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237655, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237655 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.20425531914893616, "acc_stderr": 0.026355158413349424, "acc_norm": 0.20425531914893616, "acc_norm_stderr": 0.026355158413349424 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.24561403508771928, "acc_stderr": 0.04049339297748141, "acc_norm": 0.24561403508771928, "acc_norm_stderr": 0.04049339297748141 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.296551724137931, "acc_stderr": 0.03806142687309993, "acc_norm": 0.296551724137931, "acc_norm_stderr": 0.03806142687309993 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2671957671957672, "acc_stderr": 0.02278967314577656, "acc_norm": 0.2671957671957672, "acc_norm_stderr": 0.02278967314577656 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.15079365079365079, "acc_stderr": 0.03200686497287392, "acc_norm": 0.15079365079365079, "acc_norm_stderr": 0.03200686497287392 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.25161290322580643, "acc_stderr": 0.024685979286239956, "acc_norm": 0.25161290322580643, "acc_norm_stderr": 0.024685979286239956 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.2955665024630542, "acc_stderr": 0.032104944337514575, "acc_norm": 0.2955665024630542, "acc_norm_stderr": 0.032104944337514575 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.28484848484848485, "acc_stderr": 0.035243908445117836, "acc_norm": 0.28484848484848485, "acc_norm_stderr": 0.035243908445117836 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.25252525252525254, "acc_stderr": 0.030954055470365897, "acc_norm": 0.25252525252525254, "acc_norm_stderr": 0.030954055470365897 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.22797927461139897, "acc_stderr": 0.030276909945178256, "acc_norm": 0.22797927461139897, "acc_norm_stderr": 0.030276909945178256 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.2128205128205128, "acc_stderr": 0.020752423722128013, "acc_norm": 0.2128205128205128, "acc_norm_stderr": 0.020752423722128013 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.26296296296296295, "acc_stderr": 0.02684205787383371