open-llm-leaderboard-old/details_MisterRid__Llama-3-8B-SaulGoodMan

该数据集是在Open LLM Leaderboard上对模型MisterRid/Llama-3-8B-SaulGoodMan进行评估时自动创建的。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分割始终指向最新结果。一个名为results的额外配置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。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。README中还包含了2024-04-20运行的最新结果，显示了不同任务的各种指标。

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 MisterRid/Llama-3-8B-SaulGoodMan 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_MisterRid__Llama-3-8B-SaulGoodMan", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-20T21:36:09.227298 运行 的最新结果：

python { "all": { "acc": 0.6659868600131418, "acc_stderr": 0.031735960036773495, "acc_norm": 0.6698170463347682, "acc_norm_stderr": 0.03235705673758471, "mc1": 0.3574051407588739, "mc1_stderr": 0.016776599676729405, "mc2": 0.516847386568984, "mc2_stderr": 0.015023063767990823 }, "harness|arc:challenge|25": { "acc": 0.590443686006826, "acc_stderr": 0.01437035863247244, "acc_norm": 0.6339590443686007, "acc_norm_stderr": 0.014077223108470139 }, "harness|hellaswag|10": { "acc": 0.6182035451105358, "acc_stderr": 0.004848341560492142, "acc_norm": 0.8186616211909978, "acc_norm_stderr": 0.0038451084764013 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6518518518518519, "acc_stderr": 0.041153246103369526, "acc_norm": 0.6518518518518519, "acc_norm_stderr": 0.041153246103369526 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.743421052631579, "acc_stderr": 0.0355418036802569, "acc_norm": 0.743421052631579, "acc_norm_stderr": 0.0355418036802569 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7509433962264151, "acc_stderr": 0.026616482980501704, "acc_norm": 0.7509433962264151, "acc_norm_stderr": 0.026616482980501704 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7916666666666666, "acc_stderr": 0.033961162058453336, "acc_norm": 0.7916666666666666, "acc_norm_stderr": 0.033961162058453336 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "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": 0.45098039215686275, "acc_stderr": 0.049512182523962625, "acc_norm": 0.45098039215686275, "acc_norm_stderr": 0.049512182523962625 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.81, "acc_stderr": 0.03942772444036624, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036624 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5872340425531914, "acc_stderr": 0.03218471141400351, "acc_norm": 0.5872340425531914, "acc_norm_stderr": 0.03218471141400351 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5526315789473685, "acc_stderr": 0.04677473004491199, "acc_norm": 0.5526315789473685, "acc_norm_stderr": 0.04677473004491199 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6206896551724138, "acc_stderr": 0.040434618619167466, "acc_norm": 0.6206896551724138, "acc_norm_stderr": 0.040434618619167466 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4470899470899471, "acc_stderr": 0.025606723995777028, "acc_norm": 0.4470899470899471, "acc_norm_stderr": 0.025606723995777028 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.49206349206349204, "acc_stderr": 0.044715725362943486, "acc_norm": 0.49206349206349204, "acc_norm_stderr": 0.044715725362943486 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7806451612903226, "acc_stderr": 0.023540799358723274, "acc_norm": 0.7806451612903226, "acc_norm_stderr": 0.023540799358723274 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5073891625615764, "acc_stderr": 0.035176035403610105, "acc_norm": 0.5073891625615764, "acc_norm_stderr": 0.035176035403610105 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.68, "acc_stderr": 0.04688261722621505, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7696969696969697, "acc_stderr": 0.03287666758603489, "acc_norm": 0.7696969696969697, "acc_norm_stderr": 0.03287666758603489 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8333333333333334, "acc_stderr": 0.02655220782821528, "acc_norm": 0.8333333333333334, "acc_norm_stderr": 0.02655220782821528 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8911917098445595, "acc_stderr": 0.02247325333276877, "acc_norm": 0.8911917098445595, "acc_norm_stderr": 0.02247325333276877 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6410256410256411, "acc_stderr": 0.02432173848460235, "acc_norm": 0.6410256410256411, "acc_norm_stderr": 0.02432173848460235 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.37777777777777777, "acc_stderr": 0.02956070739246571, "acc_norm": 0.37777777777777777, "acc_norm_stderr": 0.029560707