open-llm-leaderboard-old/details_maywell__Synatra-10.7B-v0.4

该数据集是在模型maywell/Synatra-10.7B-v0.4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，每个配置对应一个被评估的任务。它包含一次运行的数据，每次运行在每个配置中表示为特定的分割，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，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

数据集创建

• 数据集名称: Evaluation run of maywell/Synatra-10.7B-v0.4
• 创建目的: 该数据集是在模型 maywell/Synatra-10.7B-v0.4 在 Open LLM Leaderboard 上的评估运行期间自动创建的。

数据集结构

• 配置数量: 63 个配置，每个配置对应一个评估任务。
• 数据来源: 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。
• 额外配置: 一个名为 "results" 的额外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_maywell__Synatra-10.7B-v0.4", "harness_winogrande_5", split="train")

最新结果

• 最新结果链接: 最新结果来自 2023-12-29T19:20:40.576822
• 结果示例: python { "all": { "acc": 0.6258404665626669, "acc_stderr": 0.0325401029239991, "acc_norm": 0.6288101811459054, "acc_norm_stderr": 0.03320287642998332, "mc1": 0.3488372093023256, "mc1_stderr": 0.016684419859986893, "mc2": 0.511139865309024, "mc2_stderr": 0.014967148493344726 }, "harness|arc:challenge|25": { "acc": 0.60580204778157, "acc_stderr": 0.014280522667467323, "acc_norm": 0.6493174061433447, "acc_norm_stderr": 0.013944635930726097 }, "harness|hellaswag|10": { "acc": 0.6258713403704441, "acc_stderr": 0.004829081532826499, "acc_norm": 0.8247361083449513, "acc_norm_stderr": 0.003794156551272269 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.3, "acc_stderr": 0.04605661864718381, "acc_norm": 0.3, "acc_norm_stderr": 0.04605661864718381 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.562962962962963, "acc_stderr": 0.04284958639753401, "acc_norm": 0.562962962962963, "acc_norm_stderr": 0.04284958639753401 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.6973684210526315, "acc_stderr": 0.03738520676119669, "acc_norm": 0.6973684210526315, "acc_norm_stderr": 0.03738520676119669 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6716981132075471, "acc_stderr": 0.02890159361241178, "acc_norm": 0.6716981132075471, "acc_norm_stderr": 0.02890159361241178 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7361111111111112, "acc_stderr": 0.03685651095897532, "acc_norm": 0.7361111111111112, "acc_norm_stderr": 0.03685651095897532 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.43, "acc_stderr": 0.04975698519562428, "acc_norm": 0.43, "acc_norm_stderr": 0.04975698519562428 }, "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": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5606936416184971, "acc_stderr": 0.03784271932887468, "acc_norm": 0.5606936416184971, "acc_norm_stderr": 0.03784271932887468 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.35294117647058826, "acc_stderr": 0.04755129616062946, "acc_norm": 0.35294117647058826, "acc_norm_stderr": 0.04755129616062946 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.76, "acc_stderr": 0.04292346959909281, "acc_norm": 0.76, "acc_norm_stderr": 0.04292346959909281 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5787234042553191, "acc_stderr": 0.03227834510146268, "acc_norm": 0.5787234042553191, "acc_norm_stderr": 0.03227834510146268 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.5175438596491229, "acc_stderr": 0.04700708033551038, "acc_norm": 0.5175438596491229, "acc_norm_stderr": 0.04700708033551038 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5586206896551724, "acc_stderr": 0.04137931034482758, "acc_norm": 0.5586206896551724, "acc_norm_stderr": 0.04137931034482758 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4074074074074074, "acc_stderr": 0.025305906241590632, "acc_norm": 0.4074074074074074, "acc_norm_stderr": 0.025305906241590632 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3968253968253968, "acc_stderr": 0.04375888492727061, "acc_norm": 0.3968253968253968, "acc_norm_stderr": 0.04375888492727061 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7483870967741936, "acc_stderr": 0.024685979286239963, "acc_norm": 0.7483870967741936, "acc_norm_stderr": 0.024685979286239963 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.43349753694581283, "acc_stderr": 0.034867317274198714, "acc_norm": 0.43349753694581283, "acc_norm_stderr": 0.034867317274198714 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.68, "acc_stderr": 0.04688261722621504, "acc_norm": 0.68, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7757575757575758, "acc_stderr": 0.03256866661681102, "acc_norm": 0.7757575757575758, "acc_norm_stderr": 0.03256866661681102 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8484848484848485, "acc_stderr": 0.025545650426603617, "acc_norm": 0.8484848484848485, "acc_norm_stderr": 0.025545650426603617 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8601036269430051, "acc_stderr": 0.025033870583015178, "acc_norm": 0.8601036269430051, "acc_norm_stderr": 0.025033870583015178 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.5820512820512821, "acc_stderr": 0.02500732988246122, "acc_norm": 0.5820512820512821, "acc_norm_stderr": 0.02500732988246122 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3074074074074074, "acc_stderr": 0.02813