open-llm-leaderboard-old/details_AA051611__V0201

该数据集是在Open LLM Leaderboard上对模型AA051611/V0201进行评估运行时自动创建的。数据集由63个配置组成，每个配置对应一个评估任务。数据集是从1次运行中生成的，每次运行在每个配置中表示为特定的分割，train分割始终指向最新的结果。一个名为results的额外配置存储了运行的所有聚合结果，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`datasets`库中的`load_dataset`函数加载运行中的详细信息的示例。还包括了2024-02-02T03:15:18.446534运行的最新结果，显示了不同任务的各种准确性指标。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型 AA051611/V0201 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。

数据集结构

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。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_AA051611__V0201", "harness_winogrande_5", split="train")

最新结果

以下是 2024-02-02T03:15:18.446534 运行 的最新结果：

python { "all": { "acc": 0.8722899277105903, "acc_stderr": 0.021779827433248626, "acc_norm": 0.8832174168880055, "acc_norm_stderr": 0.022071903413890245, "mc1": 0.36474908200734396, "mc1_stderr": 0.01685096106172011, "mc2": 0.5375985523274007, "mc2_stderr": 0.015202763451961539 }, "harness|arc:challenge|25": { "acc": 0.6339590443686007, "acc_stderr": 0.014077223108470139, "acc_norm": 0.6723549488054608, "acc_norm_stderr": 0.013715847940719337 }, "harness|hellaswag|10": { "acc": 0.6309500099581756, "acc_stderr": 0.004815613144385407, "acc_norm": 0.8330013941445927, "acc_norm_stderr": 0.00372212370961046 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.76, "acc_stderr": 0.042923469599092816, "acc_norm": 0.76, "acc_norm_stderr": 0.042923469599092816 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.837037037037037, "acc_stderr": 0.03190541474482841, "acc_norm": 0.837037037037037, "acc_norm_stderr": 0.03190541474482841 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.9539473684210527, "acc_stderr": 0.01705693362806048, "acc_norm": 0.9539473684210527, "acc_norm_stderr": 0.01705693362806048 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.86, "acc_stderr": 0.0348735088019777, "acc_norm": 0.86, "acc_norm_stderr": 0.0348735088019777 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.9358490566037736, "acc_stderr": 0.015080038966069792, "acc_norm": 0.9358490566037736, "acc_norm_stderr": 0.015080038966069792 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.9652777777777778, "acc_stderr": 0.01530953117500374, "acc_norm": 0.9652777777777778, "acc_norm_stderr": 0.01530953117500374 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.86, "acc_stderr": 0.03487350880197772, "acc_norm": 0.86, "acc_norm_stderr": 0.03487350880197772 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.78, "acc_stderr": 0.04163331998932262, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932262 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.8786127167630058, "acc_stderr": 0.024901248066383764, "acc_norm": 0.8786127167630058, "acc_norm_stderr": 0.024901248066383764 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.7745098039215687, "acc_stderr": 0.04158307533083286, "acc_norm": 0.7745098039215687, "acc_norm_stderr": 0.04158307533083286 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.91, "acc_stderr": 0.028762349126466115, "acc_norm": 0.91, "acc_norm_stderr": 0.028762349126466115 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.8936170212765957, "acc_stderr": 0.02015597730704985, "acc_norm": 0.8936170212765957, "acc_norm_stderr": 0.02015597730704985 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.7894736842105263, "acc_stderr": 0.0383515395439942, "acc_norm": 0.7894736842105263, "acc_norm_stderr": 0.0383515395439942 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.8896551724137931, "acc_stderr": 0.026109923428966807, "acc_norm": 0.8896551724137931, "acc_norm_stderr": 0.026109923428966807 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.8862433862433863, "acc_stderr": 0.016352876480494796, "acc_norm": 0.8862433862433863, "acc_norm_stderr": 0.016352876480494796 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.7301587301587301, "acc_stderr": 0.03970158273235171, "acc_norm": 0.7301587301587301, "acc_norm_stderr": 0.03970158273235171 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.84, "acc_stderr": 0.036845294917747115, "acc_norm": 0.84, "acc_norm_stderr": 0.036845294917747115 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.9612903225806452, "acc_stderr": 0.010973819726797958, "acc_norm": 0.9612903225806452, "acc_norm_stderr": 0.010973819726797958 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.8078817733990148, "acc_stderr": 0.02771931570961478, "acc_norm": 0.8078817733990148, "acc_norm_stderr": 0.02771931570961478 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.91, "acc_stderr": 0.028762349126466115, "acc_norm": 0.91, "acc_norm_stderr": 0.028762349126466115 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.9212121212121213, "acc_stderr": 0.021037183825716357, "acc_norm": 0.9212121212121213, "acc_norm_stderr": 0.021037183825716357 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9646464646464646, "acc_stderr": 0.01315731887804608, "acc_norm": 0.9646464646464646, "acc_norm_stderr": 0.01315731887804608 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9844559585492227, "acc_stderr": 0.008927492715084346, "acc_norm": 0.9844559585492227, "acc_norm_stderr": 0.008927492715084346 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.9128205128205128, "acc_stderr": 0.014302931207177386, "acc_norm": 0.9128205128205128, "acc_norm_stderr": 0.014302931207177386 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.7888888888888889, "acc_stderr": 0.024882116857655078, "acc_norm": 0.7888888888888889, "acc_norm_stderr": 0.024882116857655078 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.941176470588