open-llm-leaderboard-old/details_ibivibiv__multimaster-7b

该数据集是在模型 ibivibiv/multimaster-7b 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 1 次运行的结果，每次运行在每个配置中表示为特定的分割，使用运行的时间戳命名。train 分割始终指向最新的结果。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。文件还提供了如何使用 Python 代码加载运行中的详细信息的示例，并列出了特定运行的最新结果。

原始信息汇总

数据集概述

该数据集是在对模型 ibivibiv/multimaster-7b 进行评估运行时自动创建的，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。每个运行可以在每个配置中找到特定的分割，分割名称使用运行的时间戳。
• "train" 分割始终指向最新的结果。
• 额外的 "results" 配置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_ibivibiv__multimaster-7b", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-29T06:57:35.053751 运行的最新结果：

python { "all": { "acc": 0.4672294483827764, "acc_stderr": 0.03460052472829534, "acc_norm": 0.4730946802206324, "acc_norm_stderr": 0.03539528166637499, "mc1": 0.30599755201958384, "mc1_stderr": 0.016132229728155038, "mc2": 0.4497774423277904, "mc2_stderr": 0.015449037055535802 }, "harness|arc:challenge|25": { "acc": 0.3728668941979522, "acc_stderr": 0.014131176760131169, "acc_norm": 0.4104095563139932, "acc_norm_stderr": 0.014374922192642666 }, "harness|hellaswag|10": { "acc": 0.5748854809798845, "acc_stderr": 0.004933500261683597, "acc_norm": 0.7499502091216889, "acc_norm_stderr": 0.004321564303822423 }, "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": 0.42962962962962964, "acc_stderr": 0.04276349494376599, "acc_norm": 0.42962962962962964, "acc_norm_stderr": 0.04276349494376599 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.45394736842105265, "acc_stderr": 0.04051646342874143, "acc_norm": 0.45394736842105265, "acc_norm_stderr": 0.04051646342874143 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5320754716981132, "acc_stderr": 0.03070948699255655, "acc_norm": 0.5320754716981132, "acc_norm_stderr": 0.03070948699255655 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4305555555555556, "acc_stderr": 0.04140685639111503, "acc_norm": 0.4305555555555556, "acc_norm_stderr": 0.04140685639111503 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621505, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.42196531791907516, "acc_stderr": 0.0376574669386515, "acc_norm": 0.42196531791907516, "acc_norm_stderr": 0.0376574669386515 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.22549019607843138, "acc_stderr": 0.041583075330832865, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.041583075330832865 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.6, "acc_stderr": 0.049236596391733084, "acc_norm": 0.6, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4085106382978723, "acc_stderr": 0.03213418026701576, "acc_norm": 0.4085106382978723, "acc_norm_stderr": 0.03213418026701576 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.30701754385964913, "acc_stderr": 0.04339138322579861, "acc_norm": 0.30701754385964913, "acc_norm_stderr": 0.04339138322579861 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.43448275862068964, "acc_stderr": 0.04130740879555497, "acc_norm": 0.43448275862068964, "acc_norm_stderr": 0.04130740879555497 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3412698412698413, "acc_stderr": 0.02441923496681907, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.02441923496681907 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.30158730158730157, "acc_stderr": 0.04104947269903394, "acc_norm": 0.30158730158730157, "acc_norm_stderr": 0.04104947269903394 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5096774193548387, "acc_stderr": 0.02843867799890955, "acc_norm": 0.5096774193548387, "acc_norm_stderr": 0.02843867799890955 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.35960591133004927, "acc_stderr": 0.033764582465095665, "acc_norm": 0.35960591133004927, "acc_norm_stderr": 0.033764582465095665 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.5, "acc_stderr": 0.050251890762960605, "acc_norm": 0.5, "acc_norm_stderr": 0.050251890762960605 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5575757575757576, "acc_stderr": 0.03878372113711274, "acc_norm": 0.5575757575757576, "acc_norm_stderr": 0.03878372113711274 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6414141414141414, "acc_stderr": 0.034169036403915214, "acc_norm": 0.6414141414141414, "acc_norm_stderr": 0.034169036403915214 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.5233160621761658, "acc_stderr": 0.03604513672442202, "acc_norm": 0.5233160621761658, "acc_norm_stderr": 0.03604513672442202 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.43333333333333335, "acc_stderr": 0.025124653525885127, "acc_norm": 0.43333333333333335, "acc_norm_stderr": 0.025124653525885127 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2962962962962963, "acc_stderr": 0.02784081149587194, "acc_norm": 0.2962962962962963, "acc_norm_stderr": 0.02784081149587194 }, "harness|hendrycksTest-