open-llm-leaderboard-old/details_01-ai__Yi-1.5-34B-Chat

该数据集是在模型01-ai/Yi-1.5-34B-Chat在Open LLM Leaderboard上的评估运行期间自动创建的。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次运行中创建的，每次运行在每个配置中作为一个特定的分割，分割名称使用运行的时间戳。train分割始终指向最新的结果。一个名为results的额外配置存储了运行的所有聚合结果，用于计算和显示Open LLM Leaderboard上的聚合指标。文件还提供了如何使用Python代码加载运行中的详细信息的示例，并列出了特定运行的最新结果。

原始信息汇总

数据集概述

数据集摘要

该数据集是在对模型 01-ai/Yi-1.5-34B-Chat 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_01-ai__Yi-1.5-34B-Chat", "harness_winogrande_5", split="train")

最新结果

以下是 2024-05-15T03:44:20.662749 运行的最新结果：

python { "all": { "acc": 0.767456241845471, "acc_stderr": 0.028628978785372215, "acc_norm": 0.7712150206352211, "acc_norm_stderr": 0.029177020086851913, "mc1": 0.4283965728274174, "mc1_stderr": 0.017323088597314757, "mc2": 0.6215770288656476, "mc2_stderr": 0.015366935746239038 }, "harness|arc:challenge|25": { "acc": 0.6697952218430034, "acc_stderr": 0.013743085603760427, "acc_norm": 0.7047781569965871, "acc_norm_stderr": 0.013329750293382321 }, "harness|hellaswag|10": { "acc": 0.6752638916550487, "acc_stderr": 0.004673191423861212, "acc_norm": 0.8596893049193388, "acc_norm_stderr": 0.0034659928816107802 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.58, "acc_stderr": 0.04960449637488584, "acc_norm": 0.58, "acc_norm_stderr": 0.04960449637488584 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.8, "acc_stderr": 0.03455473702325438, "acc_norm": 0.8, "acc_norm_stderr": 0.03455473702325438 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.875, "acc_stderr": 0.026913523521537846, "acc_norm": 0.875, "acc_norm_stderr": 0.026913523521537846 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.81, "acc_stderr": 0.03942772444036622, "acc_norm": 0.81, "acc_norm_stderr": 0.03942772444036622 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7735849056603774, "acc_stderr": 0.025757559893106748, "acc_norm": 0.7735849056603774, "acc_norm_stderr": 0.025757559893106748 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8263888888888888, "acc_stderr": 0.03167473383795718, "acc_norm": 0.8263888888888888, "acc_norm_stderr": 0.03167473383795718 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.51, "acc_stderr": 0.05024183937956911, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956911 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7514450867052023, "acc_stderr": 0.03295304696818317, "acc_norm": 0.7514450867052023, "acc_norm_stderr": 0.03295304696818317 }, "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": 0.82, "acc_stderr": 0.03861229196653695, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653695 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.8170212765957446, "acc_stderr": 0.025276041000449966, "acc_norm": 0.8170212765957446, "acc_norm_stderr": 0.025276041000449966 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5789473684210527, "acc_stderr": 0.046446020912223177, "acc_norm": 0.5789473684210527, "acc_norm_stderr": 0.046446020912223177 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7448275862068966, "acc_stderr": 0.03632984052707842, "acc_norm": 0.7448275862068966, "acc_norm_stderr": 0.03632984052707842 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.753968253968254, "acc_stderr": 0.022182037202948368, "acc_norm": 0.753968253968254, "acc_norm_stderr": 0.022182037202948368 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.6666666666666666, "acc_stderr": 0.04216370213557835, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.04216370213557835 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.51, "acc_stderr": 0.05024183937956912, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8838709677419355, "acc_stderr": 0.018225757949432306, "acc_norm": 0.8838709677419355, "acc_norm_stderr": 0.018225757949432306 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6650246305418719, "acc_stderr": 0.033208527423483104, "acc_norm": 0.6650246305418719, "acc_norm_stderr": 0.033208527423483104 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.9, "acc_stderr": 0.030151134457776348, "acc_norm": 0.9, "acc_norm_stderr": 0.030151134457776348 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8606060606060606, "acc_stderr": 0.027045948825865397, "acc_norm": 0.8606060606060606, "acc_norm_stderr": 0.027045948825865397 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8838383838383839, "acc_stderr": 0.02282888177524938, "acc_norm": 0.8838383838383839, "acc_norm_stderr": 0.02282888177524938 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9585492227979274, "acc_stderr": 0.01438543285747643, "acc_norm": 0.9585492227979274, "acc_norm_stderr": 0.01438543285747643 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8384615384615385, "acc_stderr": 0.018659703705332976, "acc_norm": 0.8384615384615385, "acc_norm_stderr": 0.018659703705332976 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.5555555555555556, "acc_stderr": 0.03029677128606732, "acc_norm": 0.5555555555555556, "acc_norm_stderr": 0.03029677128606732 }, "harness|hendrycksTest-high_school_microeconomics|