open-llm-leaderboard-old/details_Severian__ANIMA-Phi-Neptune-Mistral-7B-v3

该数据集是在模型Severian/ANIMA-Phi-Neptune-Mistral-7B-v3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1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。一个名为results的额外配置存储了运行的所有聚合结果，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

该数据集是在对模型 Severian/ANIMA-Phi-Neptune-Mistral-7B-v3 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 61 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_Severian__ANIMA-Phi-Neptune-Mistral-7B-v3", "harness_truthfulqa_mc_0", split="train")

最新结果

以下是 2023-10-11T01:16:32.937269 运行的最新结果：

python { "all": { "acc": 0.5392786633208031, "acc_stderr": 0.03494779312823446, "acc_norm": 0.5431264898387953, "acc_norm_stderr": 0.03493217150757376, "mc1": 0.412484700122399, "mc1_stderr": 0.01723329939957122, "mc2": 0.5940288949043588, "mc2_stderr": 0.015208554054531144 }, "harness|arc:challenge|25": { "acc": 0.5401023890784983, "acc_stderr": 0.01456431885692485, "acc_norm": 0.568259385665529, "acc_norm_stderr": 0.014474591427196202 }, "harness|hellaswag|10": { "acc": 0.5893248356901015, "acc_stderr": 0.004909509538525159, "acc_norm": 0.7881896036646087, "acc_norm_stderr": 0.004077561349272391 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.29, "acc_stderr": 0.045604802157206845, "acc_norm": 0.29, "acc_norm_stderr": 0.045604802157206845 }, "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": 0.5263157894736842, "acc_stderr": 0.04063302731486671, "acc_norm": 0.5263157894736842, "acc_norm_stderr": 0.04063302731486671 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.55, "acc_stderr": 0.04999999999999999, "acc_norm": 0.55, "acc_norm_stderr": 0.04999999999999999 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6377358490566037, "acc_stderr": 0.0295822451283843, "acc_norm": 0.6377358490566037, "acc_norm_stderr": 0.0295822451283843 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5347222222222222, "acc_stderr": 0.04171115858181618, "acc_norm": 0.5347222222222222, "acc_norm_stderr": 0.04171115858181618 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.54, "acc_stderr": 0.05009082659620333, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5722543352601156, "acc_stderr": 0.037724468575180276, "acc_norm": 0.5722543352601156, "acc_norm_stderr": 0.037724468575180276 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.30392156862745096, "acc_stderr": 0.045766654032077615, "acc_norm": 0.30392156862745096, "acc_norm_stderr": 0.045766654032077615 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.65, "acc_stderr": 0.047937248544110196, "acc_norm": 0.65, "acc_norm_stderr": 0.047937248544110196 }, "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": 0.38596491228070173, "acc_stderr": 0.04579639422070435, "acc_norm": 0.38596491228070173, "acc_norm_stderr": 0.04579639422070435 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5448275862068965, "acc_stderr": 0.04149886942192117, "acc_norm": 0.5448275862068965, "acc_norm_stderr": 0.04149886942192117 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3439153439153439, "acc_stderr": 0.024464426625596433, "acc_norm": 0.3439153439153439, "acc_norm_stderr": 0.024464426625596433 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3888888888888889, "acc_stderr": 0.0436031486007746, "acc_norm": 0.3888888888888889, "acc_norm_stderr": 0.0436031486007746 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6161290322580645, "acc_stderr": 0.02766618207553965, "acc_norm": 0.6161290322580645, "acc_norm_stderr": 0.02766618207553965 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.37438423645320196, "acc_stderr": 0.03405155380561952, "acc_norm": 0.37438423645320196, "acc_norm_stderr": 0.03405155380561952 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6545454545454545, "acc_stderr": 0.03713158067481913, "acc_norm": 0.6545454545454545, "acc_norm_stderr": 0.03713158067481913 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6565656565656566, "acc_stderr": 0.03383201223244441, "acc_norm": 0.6565656565656566, "acc_norm_stderr": 0.03383201223244441 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7357512953367875, "acc_stderr": 0.03182155050916645, "acc_norm": 0.7357512953367875, "acc_norm_stderr": 0.03182155050916645 }, "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": 0.2962962962962963, "acc_stderr": 0.027840811495871937, "acc_norm": 0.2962