open-llm-leaderboard-old/details_yeontaek__llama-2-70B-ensemble-v4

该数据集是在模型 yeontaek/llama-2-70B-ensemble-v4 在 Open LLM Leaderboard 上的评估运行期间自动创建的。数据集由 61 个配置组成，每个配置对应一个被评估的任务。数据集是从一次或多次运行中生成的，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。此外，还有一个 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。README 还提供了如何使用 Python 中的 datasets 库加载数据集的示例，并包含了特定运行的最新结果。

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yeontaek/llama-2-70B-ensemble-v4在Open LLM Leaderboard上的运行过程中自动创建的。

数据集组成

• 数据集包含61个配置，每个配置对应一个评估任务。
• 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。
• 一个额外的配置"results"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_yeontaek__llama-2-70B-ensemble-v4", "harness_truthfulqa_mc_0", split="train")

最新结果

以下是2023-09-02T05:22:36.145219运行的最新结果：

python { "all": { "acc": 0.6965991479686341, "acc_stderr": 0.03128858284011723, "acc_norm": 0.7002900066329676, "acc_norm_stderr": 0.03126026366396146, "mc1": 0.4418604651162791, "mc1_stderr": 0.017384767478986218, "mc2": 0.6260206771095533, "mc2_stderr": 0.014926739687315194 }, "harness|arc:challenge|25": { "acc": 0.6808873720136519, "acc_stderr": 0.013621696119173302, "acc_norm": 0.7090443686006825, "acc_norm_stderr": 0.01327307786590759 }, "harness|hellaswag|10": { "acc": 0.6838279227245568, "acc_stderr": 0.0046403067196280675, "acc_norm": 0.8734315873332006, "acc_norm_stderr": 0.00331809357970292 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.5925925925925926, "acc_stderr": 0.042446332383532286, "acc_norm": 0.5925925925925926, "acc_norm_stderr": 0.042446332383532286 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7763157894736842, "acc_stderr": 0.033911609343436025, "acc_norm": 0.7763157894736842, "acc_norm_stderr": 0.033911609343436025 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.69, "acc_stderr": 0.04648231987117316, "acc_norm": 0.69, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.7433962264150943, "acc_stderr": 0.026880647889051982, "acc_norm": 0.7433962264150943, "acc_norm_stderr": 0.026880647889051982 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8541666666666666, "acc_stderr": 0.02951424596429177, "acc_norm": 0.8541666666666666, "acc_norm_stderr": 0.02951424596429177 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6763005780346821, "acc_stderr": 0.0356760379963917, "acc_norm": 0.6763005780346821, "acc_norm_stderr": 0.0356760379963917 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04690650298201943, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04690650298201943 }, "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": 0.6680851063829787, "acc_stderr": 0.03078373675774565, "acc_norm": 0.6680851063829787, "acc_norm_stderr": 0.03078373675774565 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.45614035087719296, "acc_stderr": 0.04685473041907789, "acc_norm": 0.45614035087719296, "acc_norm_stderr": 0.04685473041907789 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5655172413793104, "acc_stderr": 0.04130740879555498, "acc_norm": 0.5655172413793104, "acc_norm_stderr": 0.04130740879555498 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4708994708994709, "acc_stderr": 0.025707658614154954, "acc_norm": 0.4708994708994709, "acc_norm_stderr": 0.025707658614154954 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5238095238095238, "acc_stderr": 0.04467062628403273, "acc_norm": 0.5238095238095238, "acc_norm_stderr": 0.04467062628403273 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.46, "acc_stderr": 0.05009082659620332, "acc_norm": 0.46, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8225806451612904, "acc_stderr": 0.021732540689329276, "acc_norm": 0.8225806451612904, "acc_norm_stderr": 0.021732540689329276 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5369458128078818, "acc_stderr": 0.035083705204426656, "acc_norm": 0.5369458128078818, "acc_norm_stderr": 0.035083705204426656 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.78, "acc_stderr": 0.04163331998932262, "acc_norm": 0.78, "acc_norm_stderr": 0.04163331998932262 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8606060606060606, "acc_stderr": 0.027045948825865376, "acc_norm": 0.8606060606060606, "acc_norm_stderr": 0.027045948825865376 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8737373737373737, "acc_stderr": 0.023664359402880236, "acc_norm": 0.8737373737373737, "acc_norm_stderr": 0.023664359402880236 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9481865284974094, "acc_stderr": 0.01599622932024412, "acc_norm": 0.9481865284974094, "acc_norm_stderr": 0.01599622932024412 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.7205128205128205, "acc_stderr": 0.022752388839776826, "acc_norm": 0.7205128205128205, "acc_norm_stderr": 0.022752388839776826 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3296296296296296, "acc_stderr": 0.02866120111652459, "acc_norm": 0.329629629629629