open-llm-leaderboard-old/details_elinas__chronos-mistral-7b

该数据集是在模型 elinas/chronos-mistral-7b 在 Open LLM Leaderboard 上的评估运行期间自动创建的。它由 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，使用运行的时间戳命名。train 分割始终指向最新结果。一个额外的配置 results 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。可以使用 datasets 库中的 load_dataset 函数加载该数据集。

原始信息汇总

数据集概述

数据集简介

该数据集是在评估模型 elinas/chronos-mistral-7b 在 Open LLM Leaderboard 上的自动创建的。数据集包含 63 个配置，每个配置对应一个评估任务。

数据集结构

• 配置数量：63 个配置
• 数据来源：来自 1 次运行，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。
• 最新结果："train" 分割始终指向最新结果。
• 聚合结果：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_elinas__chronos-mistral-7b", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-09T06:39:41.464301 运行的最新结果：

python { "all": { "acc": 0.4943261332869945, "acc_stderr": 0.03440242385841512, "acc_norm": 0.4990977698278415, "acc_norm_stderr": 0.035152578733964476, "mc1": 0.31701346389228885, "mc1_stderr": 0.01628920337440338, "mc2": 0.48059222372011373, "mc2_stderr": 0.014984088747615087 }, "harness|arc:challenge|25": { "acc": 0.5273037542662116, "acc_stderr": 0.014589589101985989, "acc_norm": 0.5580204778156996, "acc_norm_stderr": 0.014512682523128342 }, "harness|hellaswag|10": { "acc": 0.5751842262497511, "acc_stderr": 0.004933047726996793, "acc_norm": 0.7719577773351922, "acc_norm_stderr": 0.004187124964848515 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750574, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750574 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.4473684210526316, "acc_stderr": 0.04046336883978251, "acc_norm": 0.4473684210526316, "acc_norm_stderr": 0.04046336883978251 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5018867924528302, "acc_stderr": 0.030772653642075657, "acc_norm": 0.5018867924528302, "acc_norm_stderr": 0.030772653642075657 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5277777777777778, "acc_stderr": 0.04174752578923185, "acc_norm": 0.5277777777777778, "acc_norm_stderr": 0.04174752578923185 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.36, "acc_stderr": 0.048241815132442176, "acc_norm": 0.36, "acc_norm_stderr": 0.048241815132442176 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4508670520231214, "acc_stderr": 0.03794012674697029, "acc_norm": 0.4508670520231214, "acc_norm_stderr": 0.03794012674697029 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.27450980392156865, "acc_stderr": 0.044405219061793275, "acc_norm": 0.27450980392156865, "acc_norm_stderr": 0.044405219061793275 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.66, "acc_stderr": 0.04760952285695237, "acc_norm": 0.66, "acc_norm_stderr": 0.04760952285695237 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.41702127659574467, "acc_stderr": 0.032232762667117124, "acc_norm": 0.41702127659574467, "acc_norm_stderr": 0.032232762667117124 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.044346007015849245, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.044346007015849245 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.41379310344827586, "acc_stderr": 0.04104269211806232, "acc_norm": 0.41379310344827586, "acc_norm_stderr": 0.04104269211806232 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.31746031746031744, "acc_stderr": 0.023973861998992062, "acc_norm": 0.31746031746031744, "acc_norm_stderr": 0.023973861998992062 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.2857142857142857, "acc_stderr": 0.0404061017820884, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.0404061017820884 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.23, "acc_stderr": 0.04229525846816505, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816505 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5935483870967742, "acc_stderr": 0.02794172734625631, "acc_norm": 0.5935483870967742, "acc_norm_stderr": 0.02794172734625631 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.35467980295566504, "acc_stderr": 0.0336612448905145, "acc_norm": 0.35467980295566504, "acc_norm_stderr": 0.0336612448905145 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6242424242424243, "acc_stderr": 0.03781887353205982, "acc_norm": 0.6242424242424243, "acc_norm_stderr": 0.03781887353205982 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5757575757575758, "acc_stderr": 0.03521224908841586, "acc_norm": 0.5757575757575758, "acc_norm_stderr": 0.03521224908841586 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6994818652849741, "acc_stderr": 0.0330881859441575, "acc_norm": 0.6994818652849741, "acc_norm_stderr": 0.0330881859441575 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.44871794871794873, "acc_stderr": 0.025217315184846486, "acc_norm": 0.44871794871794873, "acc_norm_stderr": 0.025217315184846486 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3037037037037037, "acc_stderr": 0.02803792996911498, "acc_norm": 0.30370370