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open-llm-leaderboard/details_Delcos__NATE-7b

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Hugging Face2023-10-12 更新2024-03-04 收录
下载链接:
https://hf-mirror.com/datasets/open-llm-leaderboard/details_Delcos__NATE-7b
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资源简介:
该数据集是在Open LLM Leaderboard上对模型Delcos/NATE-7b进行评估时自动创建的。数据集由61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中的datasets库加载运行细节的示例。
提供机构:
open-llm-leaderboard
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 Delcos/NATE-7b 进行评估运行期间自动创建的,用于 Open LLM Leaderboard

数据集组成

数据集由61个配置组成,每个配置对应一个评估任务。数据集从1次运行中创建,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。

额外配置

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_Delcos__NATE-7b", "harness_truthfulqa_mc_0", split="train")

最新结果

以下是 2023-10-12T03:21:56.889828 运行的最新结果

python { "all": { "acc": 0.5894733182245001, "acc_stderr": 0.03414332313258469, "acc_norm": 0.5933830960354635, "acc_norm_stderr": 0.03412320397463523, "mc1": 0.3953488372093023, "mc1_stderr": 0.017115815632418197, "mc2": 0.571756969256499, "mc2_stderr": 0.01564827771634302 }, "harness|arc:challenge|25": { "acc": 0.5784982935153583, "acc_stderr": 0.014430197069326025, "acc_norm": 0.6092150170648464, "acc_norm_stderr": 0.014258563880513778 }, "harness|hellaswag|10": { "acc": 0.620991834295957, "acc_stderr": 0.004841486716855774, "acc_norm": 0.8209520015933081, "acc_norm_stderr": 0.0038260895866500536 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.33, "acc_stderr": 0.04725815626252605, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252605 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5111111111111111, "acc_stderr": 0.04318275491977976, "acc_norm": 0.5111111111111111, "acc_norm_stderr": 0.04318275491977976 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5789473684210527, "acc_stderr": 0.04017901275981749, "acc_norm": 0.5789473684210527, "acc_norm_stderr": 0.04017901275981749 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6415094339622641, "acc_stderr": 0.02951470358398177, "acc_norm": 0.6415094339622641, "acc_norm_stderr": 0.02951470358398177 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.6180555555555556, "acc_stderr": 0.040629907841466674, "acc_norm": 0.6180555555555556, "acc_norm_stderr": 0.040629907841466674 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "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": 0.5606936416184971, "acc_stderr": 0.03784271932887467, "acc_norm": 0.5606936416184971, "acc_norm_stderr": 0.03784271932887467 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3431372549019608, "acc_stderr": 0.047240073523838876, "acc_norm": 0.3431372549019608, "acc_norm_stderr": 0.047240073523838876 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.68, "acc_stderr": 0.046882617226215055, "acc_norm": 0.68, "acc_norm_stderr": 0.046882617226215055 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5063829787234042, "acc_stderr": 0.032683358999363366, "acc_norm": 0.5063829787234042, "acc_norm_stderr": 0.032683358999363366 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.32456140350877194, "acc_stderr": 0.04404556157374767, "acc_norm": 0.32456140350877194, "acc_norm_stderr": 0.04404556157374767 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5310344827586206, "acc_stderr": 0.04158632762097828, "acc_norm": 0.5310344827586206, "acc_norm_stderr": 0.04158632762097828 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.36243386243386244, "acc_stderr": 0.02475747390275206, "acc_norm": 0.36243386243386244, "acc_norm_stderr": 0.02475747390275206 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.40476190476190477, "acc_stderr": 0.043902592653775614, "acc_norm": 0.40476190476190477, "acc_norm_stderr": 0.043902592653775614 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7032258064516129, "acc_stderr": 0.025988500792411898, "acc_norm": 0.7032258064516129, "acc_norm_stderr": 0.025988500792411898 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.46798029556650245, "acc_stderr": 0.035107665979592154, "acc_norm": 0.46798029556650245, "acc_norm_stderr": 0.035107665979592154 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.57, "acc_stderr": 0.04975698519562428, "acc_norm": 0.57, "acc_norm_stderr": 0.04975698519562428 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.703030303030303, "acc_stderr": 0.03567969772268049, "acc_norm": 0.703030303030303, "acc_norm_stderr": 0.03567969772268049 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7676767676767676, "acc_stderr": 0.030088629490217483, "acc_norm": 0.7676767676767676, "acc_norm_stderr": 0.030088629490217483 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8549222797927462, "acc_stderr": 0.025416343096306433, "acc_norm": 0.8549222797927462, "acc_norm_stderr": 0.025416343096306433 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6358974358974359, "acc_stderr": 0.024396672985094767, "acc_norm": 0.6358974358974359, "acc_norm_stderr": 0.024396672985094767 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.32222222222222224, "acc_stderr": 0.028493465091028597, "acc_norm": 0.32222222222222224, "acc_norm_stderr": 0.0284934650910

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