open-llm-leaderboard-old/details_WebraftAI__synapsellm-7b-mistral-v0.5-preview2

该数据集是在Open LLM Leaderboard上对模型WebraftAI/synapsellm-7b-mistral-v0.5-preview2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，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

该数据集是在模型 WebraftAI/synapsellm-7b-mistral-v0.5-preview2 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。
• 数据集从 1 次运行中创建。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 timestamp。
• "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。

加载数据

要加载特定运行的详细信息，可以使用以下代码：

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_WebraftAI__synapsellm-7b-mistral-v0.5-preview2", "harness_winogrande_5", split="train")

最新结果

以下是 2023-12-09T20:04:44.969487 运行的最新结果：

python { "all": { "acc": 0.5160127414618038, "acc_stderr": 0.034322292179271935, "acc_norm": 0.5205499288114833, "acc_norm_stderr": 0.03505429574375341, "mc1": 0.37454100367197063, "mc1_stderr": 0.016943535128405324, "mc2": 0.5547100211730163, "mc2_stderr": 0.014944795662781923 }, "harness|arc:challenge|25": { "acc": 0.48293515358361777, "acc_stderr": 0.014602878388536593, "acc_norm": 0.5221843003412969, "acc_norm_stderr": 0.014597001927076138 }, "harness|hellaswag|10": { "acc": 0.5521808404700259, "acc_stderr": 0.004962534264751918, "acc_norm": 0.7554272057359092, "acc_norm_stderr": 0.004289551633772026 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.26, "acc_stderr": 0.04408440022768081, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768081 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4444444444444444, "acc_stderr": 0.04292596718256981, "acc_norm": 0.4444444444444444, "acc_norm_stderr": 0.04292596718256981 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5131578947368421, "acc_stderr": 0.04067533136309173, "acc_norm": 0.5131578947368421, "acc_norm_stderr": 0.04067533136309173 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.45, "acc_stderr": 0.05, "acc_norm": 0.45, "acc_norm_stderr": 0.05 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5547169811320755, "acc_stderr": 0.030588052974270655, "acc_norm": 0.5547169811320755, "acc_norm_stderr": 0.030588052974270655 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5763888888888888, "acc_stderr": 0.04132125019723369, "acc_norm": 0.5763888888888888, "acc_norm_stderr": 0.04132125019723369 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.38, "acc_stderr": 0.04878317312145633, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145633 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.45, "acc_stderr": 0.049999999999999996, "acc_norm": 0.45, "acc_norm_stderr": 0.049999999999999996 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.34, "acc_stderr": 0.04760952285695236, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695236 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5375722543352601, "acc_stderr": 0.0380168510452446, "acc_norm": 0.5375722543352601, "acc_norm_stderr": 0.0380168510452446 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.28431372549019607, "acc_stderr": 0.04488482852329017, "acc_norm": 0.28431372549019607, "acc_norm_stderr": 0.04488482852329017 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.61, "acc_stderr": 0.04902071300001975, "acc_norm": 0.61, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4127659574468085, "acc_stderr": 0.03218471141400351, "acc_norm": 0.4127659574468085, "acc_norm_stderr": 0.03218471141400351 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.3508771929824561, "acc_stderr": 0.044895393502707, "acc_norm": 0.3508771929824561, "acc_norm_stderr": 0.044895393502707 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4827586206896552, "acc_stderr": 0.04164188720169377, "acc_norm": 0.4827586206896552, "acc_norm_stderr": 0.04164188720169377 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.328042328042328, "acc_stderr": 0.024180497164376907, "acc_norm": 0.328042328042328, "acc_norm_stderr": 0.024180497164376907 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.2857142857142857, "acc_stderr": 0.040406101782088394, "acc_norm": 0.2857142857142857, "acc_norm_stderr": 0.040406101782088394 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.35, "acc_stderr": 0.0479372485441102, "acc_norm": 0.35, "acc_norm_stderr": 0.0479372485441102 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5967741935483871, "acc_stderr": 0.027906150826041136, "acc_norm": 0.5967741935483871, "acc_norm_stderr": 0.027906150826041136 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4187192118226601, "acc_stderr": 0.03471192860518468, "acc_norm": 0.4187192118226601, "acc_norm_stderr": 0.03471192860518468 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6060606060606061, "acc_stderr": 0.03815494308688929, "acc_norm": 0.6060606060606061, "acc_norm_stderr": 0.03815494308688929 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6868686868686869, "acc_stderr": 0.033042050878136525, "acc_norm": 0.6868686868686869, "acc_norm_stderr": 0.033042050878136525 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.694300518134715, "acc_stderr": 0.033248379397581594, "acc_norm": 0.694300518134715, "acc_norm_stderr": 0.033248379397581594 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.47692307692307695, "acc_stderr": 0.025323990861736118, "acc_norm": 0.47692307692307695, "acc_norm_stderr": 0.025323990861736118 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.27037037037037037, "acc_stderr": 0.027080372815145668, "acc_norm": 0.27037037037037037,