open-llm-leaderboard-old/details_saurav1199__adisesha-phi1.5-7-3-20000

该数据集是在Open LLM Leaderboard上对模型saurav1199/adisesha-phi1.5-7-3-20000进行评估时自动生成的。数据集包含63个配置，每个配置对应一个评估任务。数据集由一次运行生成，每次运行在每个配置中表示为特定的分割，分割名称使用运行的时间戳。train分割始终指向最新的结果。此外，还有一个results配置存储了所有运行的聚合结果，用于在Open LLM Leaderboard上计算和显示聚合指标。README还提供了如何使用`datasets`库中的`load_dataset`函数加载数据集的示例。

原始信息汇总

数据集概述

该数据集是在对模型 saurav1199/adisesha-phi1.5-7-3-20000 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。
• 数据集由 1 次运行创建，每个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。
• 每个配置中的 "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_saurav1199__adisesha-phi1.5-7-3-20000", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-19T17:55:17.136943 运行的最新结果：

python { "all": { "acc": 0.3511369336065052, "acc_stderr": 0.03356595864309611, "acc_norm": 0.3545168430136271, "acc_norm_stderr": 0.03447929282082604, "mc1": 0.23255813953488372, "mc1_stderr": 0.014789157531080508, "mc2": 0.37808004888274366, "mc2_stderr": 0.014562452556868511 }, "harness|arc:challenge|25": { "acc": 0.35665529010238906, "acc_stderr": 0.013998056902620199, "acc_norm": 0.3771331058020478, "acc_norm_stderr": 0.014163366896192601 }, "harness|hellaswag|10": { "acc": 0.38946425014937264, "acc_stderr": 0.004866322258335968, "acc_norm": 0.5006970722963553, "acc_norm_stderr": 0.00498977656227611 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.044619604333847394, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847394 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.34074074074074073, "acc_stderr": 0.040943762699967946, "acc_norm": 0.34074074074074073, "acc_norm_stderr": 0.040943762699967946 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.29605263157894735, "acc_stderr": 0.03715062154998904, "acc_norm": 0.29605263157894735, "acc_norm_stderr": 0.03715062154998904 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.32452830188679244, "acc_stderr": 0.028815615713432115, "acc_norm": 0.32452830188679244, "acc_norm_stderr": 0.028815615713432115 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2986111111111111, "acc_stderr": 0.03827052357950756, "acc_norm": 0.2986111111111111, "acc_norm_stderr": 0.03827052357950756 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.21, "acc_stderr": 0.04093601807403326, "acc_norm": 0.21, "acc_norm_stderr": 0.04093601807403326 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.2543352601156069, "acc_stderr": 0.0332055644308557, "acc_norm": 0.2543352601156069, "acc_norm_stderr": 0.0332055644308557 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.2647058823529412, "acc_stderr": 0.043898699568087785, "acc_norm": 0.2647058823529412, "acc_norm_stderr": 0.043898699568087785 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.33617021276595743, "acc_stderr": 0.030881618520676942, "acc_norm": 0.33617021276595743, "acc_norm_stderr": 0.030881618520676942 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.19298245614035087, "acc_stderr": 0.037124548537213684, "acc_norm": 0.19298245614035087, "acc_norm_stderr": 0.037124548537213684 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.33793103448275863, "acc_stderr": 0.039417076320648906, "acc_norm": 0.33793103448275863, "acc_norm_stderr": 0.039417076320648906 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.2698412698412698, "acc_stderr": 0.02286083830923207, "acc_norm": 0.2698412698412698, "acc_norm_stderr": 0.02286083830923207 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.30952380952380953, "acc_stderr": 0.04134913018303316, "acc_norm": 0.30952380952380953, "acc_norm_stderr": 0.04134913018303316 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.3709677419354839, "acc_stderr": 0.027480541887953593, "acc_norm": 0.3709677419354839, "acc_norm_stderr": 0.027480541887953593 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.33004926108374383, "acc_stderr": 0.033085304262282574, "acc_norm": 0.33004926108374383, "acc_norm_stderr": 0.033085304262282574 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.38181818181818183, "acc_stderr": 0.037937131711656344, "acc_norm": 0.38181818181818183, "acc_norm_stderr": 0.037937131711656344 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.3838383838383838, "acc_stderr": 0.034648816750163375, "acc_norm": 0.3838383838383838, "acc_norm_stderr": 0.034648816750163375 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.45595854922279794, "acc_stderr": 0.035944137112724366, "acc_norm": 0.45595854922279794, "acc_norm_stderr": 0.035944137112724366 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.3641025641025641, "acc_stderr": 0.02439667298509477, "acc_norm": 0.3641025641025641, "acc_norm_stderr": 0.02439667298509477 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.28888888888888886, "acc_stderr": 0.02763