open-llm-leaderboard-old/details_Evaloric__Evaloric-1.1B-test

该数据集是在Open LLM Leaderboard上对模型Evaloric/Evaloric-1.1B-test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，分割以运行的时间戳命名。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，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

该数据集是在评估模型 Evaloric/Evaloric-1.1B-test 在 Open LLM Leaderboard 上的评估运行期间自动创建的。

数据集组成

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，每次运行可以在每个配置中找到特定的拆分，拆分名称使用运行的时间戳。"train" 拆分始终指向最新的结果。

额外配置

一个额外的配置 "results" 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。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_Evaloric__Evaloric-1.1B-test", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-02T18:28:31.760304 运行的最新结果：

python { "all": { "acc": 0.269686383309535, "acc_stderr": 0.03115064860656723, "acc_norm": 0.2688981642176216, "acc_norm_stderr": 0.03188600074775313, "mc1": 0.2423500611995104, "mc1_stderr": 0.015000674373570349, "mc2": 0.382771034671839, "mc2_stderr": 0.014837380256199574 }, "harness|arc:challenge|25": { "acc": 0.3515358361774744, "acc_stderr": 0.013952413699600938, "acc_norm": 0.3660409556313993, "acc_norm_stderr": 0.014077223108470137 }, "harness|hellaswag|10": { "acc": 0.46395140410276836, "acc_stderr": 0.004976796060456436, "acc_norm": 0.6097390957976498, "acc_norm_stderr": 0.004868117598481947 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.26, "acc_stderr": 0.04408440022768078, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768078 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.2814814814814815, "acc_stderr": 0.03885004245800254, "acc_norm": 0.2814814814814815, "acc_norm_stderr": 0.03885004245800254 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.17763157894736842, "acc_stderr": 0.03110318238312338, "acc_norm": 0.17763157894736842, "acc_norm_stderr": 0.03110318238312338 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621504, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621504 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.2641509433962264, "acc_stderr": 0.027134291628741727, "acc_norm": 0.2641509433962264, "acc_norm_stderr": 0.027134291628741727 }, "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": 0.042923469599092816, "acc_norm": 0.24, "acc_norm_stderr": 0.042923469599092816 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.21965317919075145, "acc_stderr": 0.031568093627031744, "acc_norm": 0.21965317919075145, "acc_norm_stderr": 0.031568093627031744 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.22549019607843138, "acc_stderr": 0.041583075330832865, "acc_norm": 0.22549019607843138, "acc_norm_stderr": 0.041583075330832865 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.24680851063829787, "acc_stderr": 0.028185441301234113, "acc_norm": 0.24680851063829787, "acc_norm_stderr": 0.028185441301234113 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.30701754385964913, "acc_stderr": 0.0433913832257986, "acc_norm": 0.30701754385964913, "acc_norm_stderr": 0.0433913832257986 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.22758620689655173, "acc_stderr": 0.03493950380131184, "acc_norm": 0.22758620689655173, "acc_norm_stderr": 0.03493950380131184 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.23544973544973544, "acc_stderr": 0.021851509822031726, "acc_norm": 0.23544973544973544, "acc_norm_stderr": 0.021851509822031726 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3333333333333333, "acc_stderr": 0.042163702135578345, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.042163702135578345 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.14, "acc_stderr": 0.034873508801977704, "acc_norm": 0.14, "acc_norm_stderr": 0.034873508801977704 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.22580645161290322, "acc_stderr": 0.023785577884181012, "acc_norm": 0.22580645161290322, "acc_norm_stderr": 0.023785577884181012 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.2019704433497537, "acc_stderr": 0.028247350122180277, "acc_norm": 0.2019704433497537, "acc_norm_stderr": 0.028247350122180277 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.18, "acc_stderr": 0.038612291966536955, "acc_norm": 0.18, "acc_norm_stderr": 0.038612291966536955 }, "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": 0.22727272727272727, "acc_stderr": 0.029857515673386407, "acc_norm": 0.22727272727272727, "acc_norm_stderr": 0.029857515673386407 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.23834196891191708, "acc_stderr": 0.030748905363909892, "acc_norm": 0.23834196891191708, "acc_norm_stderr": 0.030748905363909892 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.258974358974359, "acc_stderr": 0.02221110681006166, "acc_norm": 0.258974358974359, "acc_norm_stderr": 0.02221110681006166 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.21481481481481482, "acc_stderr": 0.025040443877000683, "acc_norm": 0.21481481481481482, "acc_norm_stderr":