open-llm-leaderboard-old/details_KnutJaegersberg__Walter-Llama-1B

该数据集是在Open LLM Leaderboard上对模型KnutJaegersberg/Walter-Llama-1B进行评估时自动生成的。数据集由63个配置组成，每个配置对应一个评估任务。数据集包含一次运行的结果，每次运行在每种配置中表示为特定的分割，分割名称根据运行的时间戳命名。train分割始终指向最新结果。此外，还有一个results配置，用于存储所有运行结果的汇总，并在Open LLM Leaderboard上计算和显示汇总指标。README还提供了如何使用Hugging Face datasets库加载数据集的示例，并包含了特定运行的最新结果。

原始信息汇总

数据集概述

数据集简介

该数据集是在对模型 KnutJaegersberg/Walter-Llama-1B 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

数据集结构

• 该数据集包含 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，每次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_KnutJaegersberg__Walter-Llama-1B", "harness_winogrande_5", split="train")

最新结果

以下是 2023-12-13T10:33:54.615691 运行的最新结果：

python { "all": { "acc": 0.27851461271728306, "acc_stderr": 0.031543900001055364, "acc_norm": 0.2811714189383077, "acc_norm_stderr": 0.032378381556401825, "mc1": 0.1909424724602203, "mc1_stderr": 0.013759285842685718, "mc2": 0.33931994336755883, "mc2_stderr": 0.014516204773412781 }, "harness|arc:challenge|25": { "acc": 0.31143344709897613, "acc_stderr": 0.013532472099850945, "acc_norm": 0.32849829351535836, "acc_norm_stderr": 0.013724978465537371 }, "harness|hellaswag|10": { "acc": 0.46355307707627963, "acc_stderr": 0.004976507121076265, "acc_norm": 0.6105357498506274, "acc_norm_stderr": 0.004866322258335982 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.04560480215720683, "acc_norm": 0.29, "acc_norm_stderr": 0.04560480215720683 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.2222222222222222, "acc_stderr": 0.03591444084196969, "acc_norm": 0.2222222222222222, "acc_norm_stderr": 0.03591444084196969 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.2894736842105263, "acc_stderr": 0.03690677986137283, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.03690677986137283 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.23, "acc_stderr": 0.04229525846816506, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816506 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.2943396226415094, "acc_stderr": 0.028049186315695248, "acc_norm": 0.2943396226415094, "acc_norm_stderr": 0.028049186315695248 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2708333333333333, "acc_stderr": 0.03716177437566017, "acc_norm": 0.2708333333333333, "acc_norm_stderr": 0.03716177437566017 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.22, "acc_stderr": 0.04163331998932269, "acc_norm": 0.22, "acc_norm_stderr": 0.04163331998932269 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.2832369942196532, "acc_stderr": 0.034355680560478746, "acc_norm": 0.2832369942196532, "acc_norm_stderr": 0.034355680560478746 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.22549019607843138, "acc_stderr": 0.04158307533083286, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.04158307533083286 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.24, "acc_stderr": 0.042923469599092816, "acc_norm": 0.24, "acc_norm_stderr": 0.042923469599092816 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.31063829787234043, "acc_stderr": 0.03025123757921317, "acc_norm": 0.31063829787234043, "acc_norm_stderr": 0.03025123757921317 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.21929824561403508, "acc_stderr": 0.038924311065187546, "acc_norm": 0.21929824561403508, "acc_norm_stderr": 0.038924311065187546 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.2689655172413793, "acc_stderr": 0.03695183311650232, "acc_norm": 0.2689655172413793, "acc_norm_stderr": 0.03695183311650232 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.25925925925925924, "acc_stderr": 0.022569897074918407, "acc_norm": 0.25925925925925924, "acc_norm_stderr": 0.022569897074918407 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.25396825396825395, "acc_stderr": 0.038932596106046734, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.038932596106046734 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.267741935483871, "acc_stderr": 0.025189006660212378, "acc_norm": 0.267741935483871, "acc_norm_stderr": 0.025189006660212378 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.29064039408866993, "acc_stderr": 0.03194740072265541, "acc_norm": 0.29064039408866993, "acc_norm_stderr": 0.03194740072265541 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.2606060606060606, "acc_stderr": 0.034277431758165236, "acc_norm": 0.2606060606060606, "acc_norm_stderr": 0.034277431758165236 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.32323232323232326, "acc_stderr": 0.03332299921070644, "acc_norm": 0.32323232323232326, "acc_norm_stderr": 0.03332299921070644 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.35233160621761656, "acc_stderr": 0.03447478286414358, "acc_norm": 0.35233160621761656, "acc_norm_stderr": 0.03447478286414358 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.33589743589743587, "acc_stderr": 0.023946724741563976, "acc_norm": 0.33589743589743587, "acc_norm_stderr": 0.023946724741563976 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.25925925925925924, "acc_stderr": 0.026719240783712173, "acc_norm": 0.