open-llm-leaderboard-old/details_AIChenKai__TinyLlama-1.1B-Chat-v1.0-x2-MoE

该数据集是在Open LLM Leaderboard上对模型AIChenKai/TinyLlama-1.1B-Chat-v1.0-x2-MoE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。数据集是从一次运行中创建的，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，这些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。

原始信息汇总

数据集概述

数据集摘要

该数据集是在模型 AIChenKai/TinyLlama-1.1B-Chat-v1.0-x2-MoE 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。

数据集创建

数据集从 1 次运行中创建，每个运行可以在每个配置中作为一个特定的分片找到，分片名称使用运行的时间戳。"train" 分片始终指向最新的结果。

额外配置

一个额外的配置 "results" 存储了所有运行的聚合结果，用于计算和显示在 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_AIChenKai__TinyLlama-1.1B-Chat-v1.0-x2-MoE", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-04T14:00:19.727710 运行的最新结果：

python { "all": { "acc": 0.2553456994926229, "acc_stderr": 0.030657806176450017, "acc_norm": 0.2561246954296689, "acc_norm_stderr": 0.03139419549460452, "mc1": 0.23011015911872704, "mc1_stderr": 0.014734557959807765, "mc2": 0.3737269544676089, "mc2_stderr": 0.013888337000449589 }, "harness|arc:challenge|25": { "acc": 0.34982935153583616, "acc_stderr": 0.01393680921215828, "acc_norm": 0.36006825938566556, "acc_norm_stderr": 0.014027516814585188 }, "harness|hellaswag|10": { "acc": 0.45887273451503685, "acc_stderr": 0.004972872811662285, "acc_norm": 0.6104361680940051, "acc_norm_stderr": 0.004866547422355555 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.24, "acc_stderr": 0.04292346959909284, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909284 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.14814814814814814, "acc_stderr": 0.030688647610352674, "acc_norm": 0.14814814814814814, "acc_norm_stderr": 0.030688647610352674 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.19078947368421054, "acc_stderr": 0.031975658210324984, "acc_norm": 0.19078947368421054, "acc_norm_stderr": 0.031975658210324984 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.2792452830188679, "acc_stderr": 0.027611163402399715, "acc_norm": 0.2792452830188679, "acc_norm_stderr": 0.027611163402399715 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2152777777777778, "acc_stderr": 0.03437079344106135, "acc_norm": 0.2152777777777778, "acc_norm_stderr": 0.03437079344106135 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.24, "acc_stderr": 0.04292346959909283, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909283 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.26, "acc_stderr": 0.044084400227680794, "acc_norm": 0.26, "acc_norm_stderr": 0.044084400227680794 }, "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": 0.17341040462427745, "acc_stderr": 0.02886810787497064, "acc_norm": 0.17341040462427745, "acc_norm_stderr": 0.02886810787497064 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.18627450980392157, "acc_stderr": 0.03873958714149351, "acc_norm": 0.18627450980392157, "acc_norm_stderr": 0.03873958714149351 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.25957446808510637, "acc_stderr": 0.028659179374292323, "acc_norm": 0.25957446808510637, "acc_norm_stderr": 0.028659179374292323 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.24561403508771928, "acc_stderr": 0.04049339297748142, "acc_norm": 0.24561403508771928, "acc_norm_stderr": 0.04049339297748142 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.23448275862068965, "acc_stderr": 0.035306258743465914, "acc_norm": 0.23448275862068965, "acc_norm_stderr": 0.035306258743465914 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.25396825396825395, "acc_stderr": 0.022418042891113953, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.022418042891113953 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.1984126984126984, "acc_stderr": 0.03567016675276862, "acc_norm": 0.1984126984126984, "acc_norm_stderr": 0.03567016675276862 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.28, "acc_stderr": 0.04512608598542127, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542127 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.22580645161290322, "acc_stderr": 0.02378557788418101, "acc_norm": 0.22580645161290322, "acc_norm_stderr": 0.02378557788418101 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.21674876847290642, "acc_stderr": 0.028990331252516235, "acc_norm": 0.21674876847290642, "acc_norm_stderr": 0.028990331252516235 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.2, "acc_stderr": 0.04020151261036846, "acc_norm": 0.2, "acc_norm_stderr": 0.04020151261036846 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.24848484848484848, "acc_stderr": 0.03374402644139404, "acc_norm": 0.24848484848484848, "acc_norm_stderr": 0.03374402644139404 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.23232323232323232, "acc_stderr": 0.030088629490217483, "acc_norm": 0.23232323232323232, "acc_norm_stderr": 0.030088629490217483 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.22797927461139897, "acc_stderr": 0.030276909945178267, "acc_norm": 0.22797927461139897, "acc_norm_stderr": 0.030276909945178267 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.24358974358974358, "acc_stderr": 0.021763733684173926, "acc_norm": 0.24358974358974358, "acc_norm_stderr": 0.021763733684173926 }, "harness|hendrycksTest-high_school_mathematics