open-llm-leaderboard-old/details_allknowingroger__TaoPassthrough-15B-s

该数据集是在模型allknowingroger/TaoPassthrough-15B-s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。每个运行都作为特定分割存储，分割名称使用运行的时间戳命名，train分割始终指向最新结果。额外的results配置存储了运行的所有聚合结果，用于在Leaderboard上计算和显示聚合指标。数据集涵盖了各种任务及其性能指标，为模型在不同领域的性能提供了全面的见解。

原始信息汇总

数据集概述

该数据集是在对模型 allknowingroger/TaoPassthrough-15B-s 进行评估运行期间自动创建的，评估结果展示在 Open LLM Leaderboard 上。

数据集组成

数据集由 63 个配置组成，每个配置对应一个评估任务。数据集从 1 次运行中创建，每次运行的详细结果可以在每个配置中找到，分割名称使用运行的时间戳。"train" 分割始终指向最新的结果。

结果配置

一个额外的配置 "results" 存储了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。

加载数据示例

以下是加载特定运行详细结果的示例代码：

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_allknowingroger__TaoPassthrough-15B-s", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-11T08:38:19.718412 运行的最新结果：

python { "all": { "acc": 0.6459216801334029, "acc_stderr": 0.0323164135334774, "acc_norm": 0.6480689895845723, "acc_norm_stderr": 0.03298589284457266, "mc1": 0.5924112607099143, "mc1_stderr": 0.017201949234553107, "mc2": 0.7474836944840552, "mc2_stderr": 0.014375017232568123 }, "harness|arc:challenge|25": { "acc": 0.6902730375426621, "acc_stderr": 0.01351205841523836, "acc_norm": 0.7175767918088737, "acc_norm_stderr": 0.013155456884097222 }, "harness|hellaswag|10": { "acc": 0.7171878111929895, "acc_stderr": 0.004494454911844617, "acc_norm": 0.888568014339773, "acc_norm_stderr": 0.003140232392568799 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.04512608598542129, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542129 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5851851851851851, "acc_stderr": 0.04256193767901409, "acc_norm": 0.5851851851851851, "acc_norm_stderr": 0.04256193767901409 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6973684210526315, "acc_stderr": 0.037385206761196686, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.037385206761196686 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6679245283018868, "acc_stderr": 0.028985455652334388, "acc_norm": 0.6679245283018868, "acc_norm_stderr": 0.028985455652334388 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.75, "acc_stderr": 0.03621034121889507, "acc_norm": 0.75, "acc_norm_stderr": 0.03621034121889507 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.55, "acc_stderr": 0.049999999999999996, "acc_norm": 0.55, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6589595375722543, "acc_stderr": 0.036146654241808254, "acc_norm": 0.6589595375722543, "acc_norm_stderr": 0.036146654241808254 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.4019607843137255, "acc_stderr": 0.04878608714466996, "acc_norm": 0.4019607843137255, "acc_norm_stderr": 0.04878608714466996 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5829787234042553, "acc_stderr": 0.03223276266711712, "acc_norm": 0.5829787234042553, "acc_norm_stderr": 0.03223276266711712 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5175438596491229, "acc_stderr": 0.04700708033551038, "acc_norm": 0.5175438596491229, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5517241379310345, "acc_stderr": 0.041443118108781526, "acc_norm": 0.5517241379310345, "acc_norm_stderr": 0.041443118108781526 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4312169312169312, "acc_stderr": 0.025506481698138215, "acc_norm": 0.4312169312169312, "acc_norm_stderr": 0.025506481698138215 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.4603174603174603, "acc_stderr": 0.04458029125470973, "acc_norm": 0.4603174603174603, "acc_norm_stderr": 0.04458029125470973 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7935483870967742, "acc_stderr": 0.02302589961718872, "acc_norm": 0.7935483870967742, "acc_norm_stderr": 0.02302589961718872 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.47783251231527096, "acc_stderr": 0.035145285621750094, "acc_norm": 0.47783251231527096, "acc_norm_stderr": 0.035145285621750094 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7818181818181819, "acc_stderr": 0.03225078108306289, "acc_norm": 0.7818181818181819, "acc_norm_stderr": 0.03225078108306289 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7474747474747475, "acc_stderr": 0.03095405547036589, "acc_norm": 0.7474747474747475, "acc_norm_stderr": 0.03095405547036589 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9067357512953368, "acc_stderr": 0.02098685459328974, "acc_norm": 0.9067357512953368, "acc_norm_stderr": 0.02098685459328974 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6564102564102564, "acc_stderr": 0.024078696580635477, "acc_norm": 0.6564102564102564, "acc_norm_stderr": 0.024078696580635477 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3296296296296296, "acc_stderr": 0.02866120111652456, "acc_norm": 0.3296296296296296, "acc_norm_stderr": 0.02866120111652456 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.680