open-llm-leaderboard-old/details_Qwen__Qwen1.5-110B

该数据集是在评估模型Qwen/Qwen1.5-110B时自动创建的，评估是在Open LLM Leaderboard上进行的。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，每次运行都可以在特定配置中找到，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，results配置存储了所有运行的聚合结果，并用于计算和显示Open LLM Leaderboard上的聚合指标。

原始信息汇总

数据集概述

数据集名称

• 名称: Evaluation run of Qwen/Qwen1.5-110B

数据集组成

• 配置数量: 63个配置
• 每个配置对应: 一个评估任务
• 数据来源: 从1次运行中创建
• 分割命名: 使用运行的时间戳
• 训练分割: 指向最新结果

额外配置

• 结果配置: 存储所有聚合结果，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_Qwen__Qwen1.5-110B", "harness_winogrande_5", split="train")

最新结果

• 结果来源: latest results from run 2024-04-29T23:40:59.912577
• 结果示例: python { "all": { "acc": 0.7983716664646067, "acc_stderr": 0.026842308706993917, "acc_norm": 0.8014587646619066, "acc_norm_stderr": 0.027363969586656173, "mc1": 0.33659730722154224, "mc1_stderr": 0.016542412809494884, "mc2": 0.4966492716220296, "mc2_stderr": 0.014502091250779564 }, "harness|arc:challenge|25": { "acc": 0.6544368600682594, "acc_stderr": 0.013896938461145675, "acc_norm": 0.6996587030716723, "acc_norm_stderr": 0.013395909309957004 }, "harness|hellaswag|10": { "acc": 0.682832105158335, "acc_stderr": 0.004644223294727724, "acc_norm": 0.8748257319259112, "acc_norm_stderr": 0.0033024011069263328 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7333333333333333, "acc_stderr": 0.038201699145179055, "acc_norm": 0.7333333333333333, "acc_norm_stderr": 0.038201699145179055 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.9144736842105263, "acc_stderr": 0.022758677130888604, "acc_norm": 0.9144736842105263, "acc_norm_stderr": 0.022758677130888604 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.82, "acc_stderr": 0.038612291966536955, "acc_norm": 0.82, "acc_norm_stderr": 0.038612291966536955 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.8226415094339623, "acc_stderr": 0.023508739218846948, "acc_norm": 0.8226415094339623, "acc_norm_stderr": 0.023508739218846948 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.9236111111111112, "acc_stderr": 0.022212203938345915, "acc_norm": 0.9236111111111112, "acc_norm_stderr": 0.022212203938345915 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "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": 0.59, "acc_stderr": 0.04943110704237102, "acc_norm": 0.59, "acc_norm_stderr": 0.04943110704237102 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7456647398843931, "acc_stderr": 0.0332055644308557, "acc_norm": 0.7456647398843931, "acc_norm_stderr": 0.0332055644308557 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5294117647058824, "acc_stderr": 0.049665709039785295, "acc_norm": 0.5294117647058824, "acc_norm_stderr": 0.049665709039785295 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.83, "acc_stderr": 0.03775251680686371, "acc_norm": 0.83, "acc_norm_stderr": 0.03775251680686371 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.8127659574468085, "acc_stderr": 0.02550158834188359, "acc_norm": 0.8127659574468085, "acc_norm_stderr": 0.02550158834188359 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6754385964912281, "acc_stderr": 0.04404556157374767, "acc_norm": 0.6754385964912281, "acc_norm_stderr": 0.04404556157374767 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7724137931034483, "acc_stderr": 0.03493950380131184, "acc_norm": 0.7724137931034483, "acc_norm_stderr": 0.03493950380131184 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.8148148148148148, "acc_stderr": 0.020006075494524406, "acc_norm": 0.8148148148148148, "acc_norm_stderr": 0.020006075494524406 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.6190476190476191, "acc_stderr": 0.04343525428949098, "acc_norm": 0.6190476190476191, "acc_norm_stderr": 0.04343525428949098 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.9193548387096774, "acc_stderr": 0.015490002961591028, "acc_norm": 0.9193548387096774, "acc_norm_stderr": 0.015490002961591028 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.7241379310344828, "acc_stderr": 0.031447125816782426, "acc_norm": 0.7241379310344828, "acc_norm_stderr": 0.031447125816782426 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.88, "acc_stderr": 0.03265986323710905, "acc_norm": 0.88, "acc_norm_stderr": 0.03265986323710905 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8909090909090909, "acc_stderr": 0.02434383813514564, "acc_norm": 0.8909090909090909, "acc_norm_stderr": 0.02434383813514564 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9242424242424242, "acc_stderr": 0.018852670234993093, "acc_norm": 0.9242424242424242, "acc_norm_stderr": 0.018852670234993093 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9844559585492227, "acc_stderr": 0.008927492715084319, "acc_norm": 0.9844559585492227, "acc_norm_stderr": 0.008927492715084319 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8358974358974359, "acc_stderr": 0.01877843431342372, "acc_norm": 0.8358974358974359, "acc_norm_stderr": 0.01877843431342372 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.5888888888888889, "acc_stderr": 0.02999992350870668, "acc_norm": 0.5888888888888889, "acc_norm_stderr": 0.02999992350870668 }, "harness|hendrycksTest-high_school_microeconomics|5": { "acc": 0.8907