open-llm-leaderboard-old/details_AdaptLLM__law-chat

该数据集是在Open LLM Leaderboard上对模型AdaptLLM/law-chat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。数据集由1次运行创建，每次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。此外，还有一个名为results的配置，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代码加载运行细节的示例，并列出了特定运行的最新结果。

原始信息汇总

数据集概述

该数据集是在模型 AdaptLLM/law-chat 在 Open LLM Leaderboard 上的评估运行期间自动创建的。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。

数据集结构

数据集包含以下配置：

• harness_arc_challenge_25
• harness_gsm8k_5
• harness_hellaswag_10
• harness_hendrycksTest_5

每个配置包含多个分割，包括特定时间戳的分割和最新的分割。

数据加载示例

以下是加载数据集详细信息的示例代码：

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_AdaptLLM__law-chat", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-05T00:08:30.795951 运行 的最新结果：

python { "all": { "acc": 0.5023401405116338, "acc_stderr": 0.034246695991135424, "acc_norm": 0.5073753883915891, "acc_norm_stderr": 0.035009015261271426, "mc1": 0.2962056303549572, "mc1_stderr": 0.015983595101811392, "mc2": 0.4353135795126459, "mc2_stderr": 0.01483590194160273 }, "harness|arc:challenge|25": { "acc": 0.49658703071672355, "acc_stderr": 0.014611050403244088, "acc_norm": 0.5341296928327645, "acc_norm_stderr": 0.014577311315231102 }, "harness|hellaswag|10": { "acc": 0.5672176857199761, "acc_stderr": 0.00494448599063952, "acc_norm": 0.7616012746464847, "acc_norm_stderr": 0.004252333443827121 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750574, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750574 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5263157894736842, "acc_stderr": 0.04063302731486671, "acc_norm": 0.5263157894736842, "acc_norm_stderr": 0.04063302731486671 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.55, "acc_stderr": 0.049999999999999996, "acc_norm": 0.55, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5169811320754717, "acc_stderr": 0.030755120364119905, "acc_norm": 0.5169811320754717, "acc_norm_stderr": 0.030755120364119905 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5277777777777778, "acc_stderr": 0.04174752578923185, "acc_norm": 0.5277777777777778, "acc_norm_stderr": 0.04174752578923185 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "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": 0.44508670520231214, "acc_stderr": 0.03789401760283647, "acc_norm": 0.44508670520231214, "acc_norm_stderr": 0.03789401760283647 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.21568627450980393, "acc_stderr": 0.04092563958237654, "acc_norm": 0.21568627450980393, "acc_norm_stderr": 0.04092563958237654 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4425531914893617, "acc_stderr": 0.03246956919789958, "acc_norm": 0.4425531914893617, "acc_norm_stderr": 0.03246956919789958 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.39473684210526316, "acc_stderr": 0.045981880578165414, "acc_norm": 0.39473684210526316, "acc_norm_stderr": 0.045981880578165414 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4896551724137931, "acc_stderr": 0.04165774775728763, "acc_norm": 0.4896551724137931, "acc_norm_stderr": 0.04165774775728763 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.30952380952380953, "acc_stderr": 0.023809523809523857, "acc_norm": 0.30952380952380953, "acc_norm_stderr": 0.023809523809523857 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.25396825396825395, "acc_stderr": 0.03893259610604674, "acc_norm": 0.25396825396825395, "acc_norm_stderr": 0.03893259610604674 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5419354838709678, "acc_stderr": 0.02834378725054062, "acc_norm": 0.5419354838709678, "acc_norm_stderr": 0.02834378725054062 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.35467980295566504, "acc_stderr": 0.0336612448905145, "acc_norm": 0.35467980295566504, "acc_norm_stderr": 0.0336612448905145 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6666666666666666, "acc_stderr": 0.0368105086916155, "acc_norm": 0.6666666666666666, "acc_norm_stderr": 0.0368105086916155 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6818181818181818, "acc_stderr": 0.033184773338453294, "acc_norm": 0.6818181818181818, "acc_norm_stderr": 0.033184773338453294 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7564766839378239, "acc_stderr": 0.03097543638684542, "acc_norm": 0.7564766839378239, "acc_norm_stderr": 0.03097543638684542 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4512820512820513, "acc_stderr": 0.025230381238934833, "acc_norm": 0.4512820512820513, "acc_norm_stderr": 0.025230381238934833 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.29259259259259257, "acc_stderr": 0.02773896963217609, "acc_norm": 0.29259259259259257, "acc_norm_stderr