open-llm-leaderboard-old/details_abacusai__Smaug-72B-v0.1

该数据集是在模型abacusai/Smaug-72B-v0.1在Open LLM Leaderboard上的评估运行期间自动创建的。数据集由63个配置组成，每个配置对应一个评估任务。它包含一次运行的结果，每次运行在每个配置中表示为特定的分割。train分割始终指向最新结果。一个名为results的额外配置存储了运行的所有聚合结果，这些结果用于计算和显示Open LLM Leaderboard上的聚合指标。README还提供了如何使用Python中的datasets库加载运行详细信息的示例。

原始信息汇总

数据集概述

数据集简介

该数据集是在评估模型abacusai/Smaug-72B-v0.1在Open LLM Leaderboard上的自动创建的。数据集包含63个配置，每个配置对应一个评估任务。

数据集结构

• 配置数量：63个配置
• 数据来源：从1次运行中创建，每个运行在每个配置中作为一个特定的分割存在，分割名称使用运行的时间戳。
• 最新结果："train"分割始终指向最新结果。
• 结果汇总：一个额外的配置"results"存储所有运行的汇总结果，用于计算和显示在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_abacusai__Smaug-72B-v0.1", "harness_winogrande_5", split="train")

最新结果

以下是2024-02-04T04:59:32.876763运行的最新结果： python { "all": { "acc": 0.7716613011645818, "acc_stderr": 0.02801089457302993, "acc_norm": 0.7734062646949216, "acc_norm_stderr": 0.028568963791437117, "mc1": 0.6560587515299877, "mc1_stderr": 0.016629087514276785, "mc2": 0.7666613083747418, "mc2_stderr": 0.014124410528709273 }, "harness|arc:challenge|25": { "acc": 0.735494880546075, "acc_stderr": 0.012889272949313371, "acc_norm": 0.7602389078498294, "acc_norm_stderr": 0.012476304127453944 }, "harness|hellaswag|10": { "acc": 0.7199761003784106, "acc_stderr": 0.004480929450281562, "acc_norm": 0.8926508663612827, "acc_norm_stderr": 0.0030892396746331585 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.41, "acc_stderr": 0.049431107042371025, "acc_norm": 0.41, "acc_norm_stderr": 0.049431107042371025 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7185185185185186, "acc_stderr": 0.038850042458002526, "acc_norm": 0.7185185185185186, "acc_norm_stderr": 0.038850042458002526 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.881578947368421, "acc_stderr": 0.026293995855474928, "acc_norm": 0.881578947368421, "acc_norm_stderr": 0.026293995855474928 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.82, "acc_stderr": 0.038612291966536955, "acc_norm": 0.82, "acc_norm_stderr": 0.038612291966536955 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.8452830188679246, "acc_stderr": 0.022257075558791282, "acc_norm": 0.8452830188679246, "acc_norm_stderr": 0.022257075558791282 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.9305555555555556, "acc_stderr": 0.021257974822832048, "acc_norm": 0.9305555555555556, "acc_norm_stderr": 0.021257974822832048 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.62, "acc_stderr": 0.04878317312145633, "acc_norm": 0.62, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.55, "acc_stderr": 0.049999999999999996, "acc_norm": 0.55, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7456647398843931, "acc_stderr": 0.0332055644308557, "acc_norm": 0.7456647398843931, "acc_norm_stderr": 0.0332055644308557 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5686274509803921, "acc_stderr": 0.04928099597287534, "acc_norm": 0.5686274509803921, "acc_norm_stderr": 0.04928099597287534 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.81, "acc_stderr": 0.03942772444036622, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036622 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.7914893617021277, "acc_stderr": 0.026556982117838728, "acc_norm": 0.7914893617021277, "acc_norm_stderr": 0.026556982117838728 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6140350877192983, "acc_stderr": 0.04579639422070434, "acc_norm": 0.6140350877192983, "acc_norm_stderr": 0.04579639422070434 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7724137931034483, "acc_stderr": 0.03493950380131184, "acc_norm": 0.7724137931034483, "acc_norm_stderr": 0.03493950380131184 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.6904761904761905, "acc_stderr": 0.023809523809523864, "acc_norm": 0.6904761904761905, "acc_norm_stderr": 0.023809523809523864 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5714285714285714, "acc_stderr": 0.04426266681379909, "acc_norm": 0.5714285714285714, "acc_norm_stderr": 0.04426266681379909 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.54, "acc_stderr": 0.05009082659620333, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8838709677419355, "acc_stderr": 0.018225757949432306, "acc_norm": 0.8838709677419355, "acc_norm_stderr": 0.018225757949432306 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6600985221674877, "acc_stderr": 0.033327690684107895, "acc_norm": 0.6600985221674877, "acc_norm_stderr": 0.033327690684107895 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.82, "acc_stderr": 0.038612291966536934, "acc_norm": 0.82, "acc_norm_stderr": 0.038612291966536934 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8545454545454545, "acc_stderr": 0.027530196355066584, "acc_norm": 0.8545454545454545, "acc_norm_stderr": 0.027530196355066584 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9393939393939394, "acc_stderr": 0.016999994927421592, "acc_norm": 0.9393939393939394, "acc_norm_stderr": 0.016999994927421592 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9844559585492227, "acc_stderr": 0.008927492715084315, "acc_norm": 0.9844559585492227, "acc_norm_stderr": 0.008927492715084315 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8076923076923077, "acc_stderr": 0.019982347208637282, "acc_norm": 0.8076923076923077, "acc_norm_stderr": 0.019982347208637282 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.4703703703703704, "acc_stderr": 0.030431963547936584, "acc_