open-llm-leaderboard-old/details_Evaloric__Evaloric-1.1B-V.0.1

该数据集是在Open LLM Leaderboard上对模型Evaloric/Evaloric-1.1B-V.0.1进行评估时自动创建的。数据集由63个配置组成，每个配置对应一个评估任务。数据集从1次运行中创建，每次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。此外，还有一个名为results的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

数据集简介

该数据集是在对模型 Evaloric/Evaloric-1.1B-V.0.1 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

数据集组成

• 该数据集包含 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，每次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_Evaloric__Evaloric-1.1B-V.0.1", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-01T13:24:14.425130 运行的最新结果：

python { "all": { "acc": 0.24808456389369105, "acc_stderr": 0.030345910089337232, "acc_norm": 0.24822789525438038, "acc_norm_stderr": 0.031068656189303615, "mc1": 0.22888616891064872, "mc1_stderr": 0.014706994909055027, "mc2": 0.3539845351179845, "mc2_stderr": 0.014064363676239148 }, "harness|arc:challenge|25": { "acc": 0.3430034129692833, "acc_stderr": 0.013872423223718178, "acc_norm": 0.36860068259385664, "acc_norm_stderr": 0.014097810678042189 }, "harness|hellaswag|10": { "acc": 0.4689304919338777, "acc_stderr": 0.004980138679161039, "acc_norm": 0.6190001991635132, "acc_norm_stderr": 0.004846400325585233 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.17777777777777778, "acc_stderr": 0.033027898599017176, "acc_norm": 0.17777777777777778, "acc_norm_stderr": 0.033027898599017176 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.19736842105263158, "acc_stderr": 0.03238981601699397, "acc_norm": 0.19736842105263158, "acc_norm_stderr": 0.03238981601699397 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621503, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621503 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.25660377358490566, "acc_stderr": 0.02688064788905197, "acc_norm": 0.25660377358490566, "acc_norm_stderr": 0.02688064788905197 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.25, "acc_stderr": 0.03621034121889507, "acc_norm": 0.25, "acc_norm_stderr": 0.03621034121889507 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.24, "acc_stderr": 0.04292346959909282, "acc_norm": 0.24, "acc_norm_stderr": 0.04292346959909282 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.2, "acc_stderr": 0.040201512610368445, "acc_norm": 0.2, "acc_norm_stderr": 0.040201512610368445 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.19, "acc_stderr": 0.03942772444036623, "acc_norm": 0.19, "acc_norm_stderr": 0.03942772444036623 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.2023121387283237, "acc_stderr": 0.030631145539198823, "acc_norm": 0.2023121387283237, "acc_norm_stderr": 0.030631145539198823 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237655, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237655 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.26382978723404255, "acc_stderr": 0.028809989854102963, "acc_norm": 0.26382978723404255, "acc_norm_stderr": 0.028809989854102963 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.22807017543859648, "acc_stderr": 0.03947152782669415, "acc_norm": 0.22807017543859648, "acc_norm_stderr": 0.03947152782669415 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.23448275862068965, "acc_stderr": 0.035306258743465914, "acc_norm": 0.23448275862068965, "acc_norm_stderr": 0.035306258743465914 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.25132275132275134, "acc_stderr": 0.022340482339643895, "acc_norm": 0.25132275132275134, "acc_norm_stderr": 0.022340482339643895 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.21428571428571427, "acc_stderr": 0.03670066451047182, "acc_norm": 0.21428571428571427, "acc_norm_stderr": 0.03670066451047182 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.2, "acc_stderr": 0.04020151261036847, "acc_norm": 0.2, "acc_norm_stderr": 0.04020151261036847 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.1935483870967742, "acc_stderr": 0.02247525852553606, "acc_norm": 0.1935483870967742, "acc_norm_stderr": 0.02247525852553606 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.19704433497536947, "acc_stderr": 0.027986724666736212, "acc_norm": 0.19704433497536947, "acc_norm_stderr": 0.027986724666736212 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.23030303030303031, "acc_stderr": 0.03287666758603488, "acc_norm": 0.23030303030303031, "acc_norm_stderr": 0.03287666758603488 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.21212121212121213, "acc_stderr": 0.029126522834586818, "acc_norm": 0.21212121212121213, "acc_norm_stderr": 0.029126522834586818 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.19689119170984457, "acc_stderr": 0.028697873971860667, "acc_norm": 0.19689119170984457, "acc_norm_stderr": 0.028697873971860667 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.2153846153846154, "acc_stderr": 0.020843034557462878, "acc_norm": 0.2153846153846154, "acc_norm_stderr": 0.020843034557462878 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.23703703703703705, "acc_stderr": 0.025928876132766114, "acc_norm": 0.2370370