open-llm-leaderboard-old/details_Mihaiii__Pallas-0.5-LASER-0.2

该数据集是在Open LLM Leaderboard上对模型Mihaiii/Pallas-0.5-LASER-0.2进行评估时自动创建的。数据集由63个配置组成，每个配置对应一个被评估的任务。数据集是从1次运行中创建的，每次运行作为每个配置中的一个特定分割，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，还有一个名为results的配置，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Python代码加载运行细节的示例，并包含了特定运行的最新结果。

原始信息汇总

数据集概述

该数据集是在对模型 Mihaiii/Pallas-0.5-LASER-0.2 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。
• 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_Mihaiii__Pallas-0.5-LASER-0.2", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-05T04:10:15.981219 运行的最新结果：

python { "all": { "acc": 0.7430875163743905, "acc_stderr": 0.02897899424391921, "acc_norm": 0.7481500431707986, "acc_norm_stderr": 0.029524713126382888, "mc1": 0.42105263157894735, "mc1_stderr": 0.017283936248136497, "mc2": 0.5675948422477083, "mc2_stderr": 0.015681431350698164 }, "harness|arc:challenge|25": { "acc": 0.6237201365187713, "acc_stderr": 0.01415702255540716, "acc_norm": 0.6467576791808873, "acc_norm_stderr": 0.013967822714840056 }, "harness|hellaswag|10": { "acc": 0.6426010754829715, "acc_stderr": 0.004782542754102083, "acc_norm": 0.8348934475204143, "acc_norm_stderr": 0.0037051790292873315 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6962962962962963, "acc_stderr": 0.03972552884785136, "acc_norm": 0.6962962962962963, "acc_norm_stderr": 0.03972552884785136 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.8618421052631579, "acc_stderr": 0.028081042939576552, "acc_norm": 0.8618421052631579, "acc_norm_stderr": 0.028081042939576552 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.78, "acc_stderr": 0.04163331998932261, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932261 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7811320754716982, "acc_stderr": 0.0254478638251086, "acc_norm": 0.7811320754716982, "acc_norm_stderr": 0.0254478638251086 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.875, "acc_stderr": 0.02765610492929436, "acc_norm": 0.875, "acc_norm_stderr": 0.02765610492929436 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7283236994219653, "acc_stderr": 0.03391750322321658, "acc_norm": 0.7283236994219653, "acc_norm_stderr": 0.03391750322321658 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5196078431372549, "acc_stderr": 0.04971358884367405, "acc_norm": 0.5196078431372549, "acc_norm_stderr": 0.04971358884367405 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.79, "acc_stderr": 0.04093601807403326, "acc_norm": 0.79, "acc_norm_stderr": 0.04093601807403326 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.7659574468085106, "acc_stderr": 0.02767845257821239, "acc_norm": 0.7659574468085106, "acc_norm_stderr": 0.02767845257821239 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6052631578947368, "acc_stderr": 0.045981880578165414, "acc_norm": 0.6052631578947368, "acc_norm_stderr": 0.045981880578165414 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7379310344827587, "acc_stderr": 0.03664666337225257, "acc_norm": 0.7379310344827587, "acc_norm_stderr": 0.03664666337225257 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.6640211640211641, "acc_stderr": 0.02432631052914915, "acc_norm": 0.6640211640211641, "acc_norm_stderr": 0.02432631052914915 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5555555555555556, "acc_stderr": 0.04444444444444449, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.04444444444444449 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.53, "acc_stderr": 0.050161355804659205, "acc_norm": 0.53, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.9, "acc_stderr": 0.017066403719657255, "acc_norm": 0.9, "acc_norm_stderr": 0.017066403719657255 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6600985221674877, "acc_stderr": 0.033327690684107895, "acc_norm": 0.6600985221674877, "acc_norm_stderr": 0.033327690684107895 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.82, "acc_stderr": 0.03861229196653694, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653694 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8424242424242424, "acc_stderr": 0.028450388805284336, "acc_norm": 0.8424242424242424, "acc_norm_stderr": 0.028450388805284336 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9141414141414141, "acc_stderr": 0.01996022556317289, "acc_norm": 0.9141414141414141, "acc_norm_stderr": 0.01996022556317289 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9740932642487047, "acc_stderr": 0.01146452335695318, "acc_norm": 0.9740932642487047, "acc_norm_stderr": 0.01146452335695318 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7897435897435897, "acc_stderr": 0.020660597485026924, "acc_norm": 0.7897435897435897, "acc_norm_stderr": 0.020660597485026924 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.4074074074074074, "acc_stderr": 0.029958249250082107, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.029958249250082107 }, "harness|hendrycksTest-high_school_microeconomics