open-llm-leaderboard-old/details_XuanXuanXuanXuan__Llama-2-7b-hf-llama2-raw-80k

该数据集是在Open LLM Leaderboard上对模型XuanXuanXuanXuan/Llama-2-7b-hf-llama2-raw-80k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的特定分割中找到，分割名称使用运行的时间戳命名。train分割始终指向最新的结果。此外，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

数据集摘要

该数据集是在对模型 XuanXuanXuanXuan/Llama-2-7b-hf-llama2-raw-80k 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，每个运行可以在每个配置中作为一个特定的分片找到，分片名称使用运行的时间戳。
• "train" 分片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_XuanXuanXuanXuan__Llama-2-7b-hf-llama2-raw-80k", "harness_winogrande_5", split="train")

最新结果

以下是 2024-03-15T09:32:25.349002 运行的最新结果：

python { "all": { "acc": 0.4642343181811645, "acc_stderr": 0.03442908965073113, "acc_norm": 0.46924913212776476, "acc_norm_stderr": 0.03522208002966259, "mc1": 0.2484700122399021, "mc1_stderr": 0.01512742709652069, "mc2": 0.38821830058853624, "mc2_stderr": 0.013521618097099548 }, "harness|arc:challenge|25": { "acc": 0.4974402730375427, "acc_stderr": 0.014611199329843784, "acc_norm": 0.5341296928327645, "acc_norm_stderr": 0.014577311315231104 }, "harness|hellaswag|10": { "acc": 0.5875323640709023, "acc_stderr": 0.0049127238489447955, "acc_norm": 0.786197968532165, "acc_norm_stderr": 0.00409150785055958 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4666666666666667, "acc_stderr": 0.043097329010363554, "acc_norm": 0.4666666666666667, "acc_norm_stderr": 0.043097329010363554 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.42105263157894735, "acc_stderr": 0.04017901275981748, "acc_norm": 0.42105263157894735, "acc_norm_stderr": 0.04017901275981748 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.45660377358490567, "acc_stderr": 0.030656748696739435, "acc_norm": 0.45660377358490567, "acc_norm_stderr": 0.030656748696739435 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4652777777777778, "acc_stderr": 0.04171115858181617, "acc_norm": 0.4652777777777778, "acc_norm_stderr": 0.04171115858181617 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.37, "acc_stderr": 0.04852365870939099, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.04688261722621505, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621505 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4277456647398844, "acc_stderr": 0.037724468575180255, "acc_norm": 0.4277456647398844, "acc_norm_stderr": 0.037724468575180255 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.18627450980392157, "acc_stderr": 0.038739587141493524, "acc_norm": 0.18627450980392157, "acc_norm_stderr": 0.038739587141493524 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.63, "acc_stderr": 0.04852365870939099, "acc_norm": 0.63, "acc_norm_stderr": 0.04852365870939099 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.41702127659574467, "acc_stderr": 0.032232762667117124, "acc_norm": 0.41702127659574467, "acc_norm_stderr": 0.032232762667117124 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2807017543859649, "acc_stderr": 0.042270544512322004, "acc_norm": 0.2807017543859649, "acc_norm_stderr": 0.042270544512322004 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4827586206896552, "acc_stderr": 0.041641887201693775, "acc_norm": 0.4827586206896552, "acc_norm_stderr": 0.041641887201693775 }, "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": 0.30158730158730157, "acc_stderr": 0.04104947269903394, "acc_norm": 0.30158730158730157, "acc_norm_stderr": 0.04104947269903394 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.32, "acc_stderr": 0.04688261722621503, "acc_norm": 0.32, "acc_norm_stderr": 0.04688261722621503 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.49032258064516127, "acc_stderr": 0.028438677998909558, "acc_norm": 0.49032258064516127, "acc_norm_stderr": 0.028438677998909558 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.33004926108374383, "acc_stderr": 0.033085304262282574, "acc_norm": 0.33004926108374383, "acc_norm_stderr": 0.033085304262282574 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6, "acc_stderr": 0.03825460278380025, "acc_norm": 0.6, "acc_norm_stderr": 0.03825460278380025 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.4696969696969697, "acc_stderr": 0.03555804051763929, "acc_norm": 0.4696969696969697, "acc_norm_stderr": 0.03555804051763929 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6683937823834197, "acc_stderr": 0.03397636541089118, "acc_norm": 0.6683937823834197, "acc_norm_stderr": 0.03397636541089118 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4461538461538462, "acc_stderr": 0.02520357177302833, "acc_norm": 0.4461538461538462, "acc_norm_stderr": 0.02520357177302833 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.2814814814814815, "acc_stderr": 0