open-llm-leaderboard-old/details_umd-zhou-lab__claude2-alpaca-13B

该数据集是在模型umd-zhou-lab/claude2-alpaca-13B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，每个配置对应一个被评估的任务。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。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。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

该数据集是在对模型 umd-zhou-lab/claude2-alpaca-13B 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，每个运行在每个配置中作为一个特定的分割存在，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_umd-zhou-lab__claude2-alpaca-13B", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-10T17:36:10.265917 运行的最新结果：

python { "all": { "acc": 0.559598726941533, "acc_stderr": 0.03355063747107857, "acc_norm": 0.5649406354101782, "acc_norm_stderr": 0.03425321240249023, "mc1": 0.30599755201958384, "mc1_stderr": 0.016132229728155045, "mc2": 0.4502341510939478, "mc2_stderr": 0.01474201450477759 }, "harness|arc:challenge|25": { "acc": 0.5733788395904437, "acc_stderr": 0.014453185592920293, "acc_norm": 0.6117747440273038, "acc_norm_stderr": 0.014241614207414044 }, "harness|hellaswag|10": { "acc": 0.6337382991435969, "acc_stderr": 0.00480797551544649, "acc_norm": 0.8420633339972117, "acc_norm_stderr": 0.003639363021784423 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.35, "acc_stderr": 0.04793724854411022, "acc_norm": 0.35, "acc_norm_stderr": 0.04793724854411022 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4962962962962963, "acc_stderr": 0.04319223625811331, "acc_norm": 0.4962962962962963, "acc_norm_stderr": 0.04319223625811331 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5394736842105263, "acc_stderr": 0.04056242252249033, "acc_norm": 0.5394736842105263, "acc_norm_stderr": 0.04056242252249033 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.630188679245283, "acc_stderr": 0.029711421880107933, "acc_norm": 0.630188679245283, "acc_norm_stderr": 0.029711421880107933 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5902777777777778, "acc_stderr": 0.04112490974670788, "acc_norm": 0.5902777777777778, "acc_norm_stderr": 0.04112490974670788 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.050161355804659205, "acc_norm": 0.47, "acc_norm_stderr": 0.050161355804659205 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5491329479768786, "acc_stderr": 0.037940126746970296, "acc_norm": 0.5491329479768786, "acc_norm_stderr": 0.037940126746970296 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.24509803921568626, "acc_stderr": 0.042801058373643966, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.042801058373643966 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.41702127659574467, "acc_stderr": 0.03223276266711711, "acc_norm": 0.41702127659574467, "acc_norm_stderr": 0.03223276266711711 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3157894736842105, "acc_stderr": 0.043727482902780064, "acc_norm": 0.3157894736842105, "acc_norm_stderr": 0.043727482902780064 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5172413793103449, "acc_stderr": 0.04164188720169375, "acc_norm": 0.5172413793103449, "acc_norm_stderr": 0.04164188720169375 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.0242785680243077, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.0242785680243077 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.36507936507936506, "acc_stderr": 0.04306241259127153, "acc_norm": 0.36507936507936506, "acc_norm_stderr": 0.04306241259127153 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6645161290322581, "acc_stderr": 0.026860206444724345, "acc_norm": 0.6645161290322581, "acc_norm_stderr": 0.026860206444724345 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.46798029556650245, "acc_stderr": 0.035107665979592154, "acc_norm": 0.46798029556650245, "acc_norm_stderr": 0.035107665979592154 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6666666666666666, "acc_stderr": 0.03681050869161551, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.03681050869161551 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.7222222222222222, "acc_stderr": 0.03191178226713546, "acc_norm": 0.7222222222222222, "acc_norm_stderr": 0.03191178226713546 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8031088082901554, "acc_stderr": 0.028697873971860677, "acc_norm": 0.8031088082901554, "acc_norm_stderr": 0.028697873971860677 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.49230769230769234, "acc_stderr": 0.025348006031534778, "acc_norm": 0.49230769230769234, "acc_norm_stderr": 0.025348006031534778 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2851851851851852, "acc_stderr": 0.027528599210340496, "acc_norm": 0.2851851851851852, "acc_norm_stderr":