open-llm-leaderboard-old/details_ChaoticNeutrals__IQ_Test_l3_8B

该数据集是在Open LLM Leaderboard上对模型ChaoticNeutrals/IQ_Test_l3_8B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。它包含一次运行的结果，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的额外配置存储了所有运行的聚合结果，这些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`datasets`库中的`load_dataset`函数加载运行详情的示例。

原始信息汇总

数据集概述

数据集来源

该数据集是在评估模型 ChaoticNeutrals/IQ_Test_l3_8B 在 Open LLM Leaderboard 上的运行过程中自动创建的。

数据集结构

• 该数据集包含 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。
• 额外的 "results" 配置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_ChaoticNeutrals__IQ_Test_l3_8B", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-23T03:27:46.226929 运行 的最新结果：

python { "all": { "acc": 0.6550661306400801, "acc_stderr": 0.031515746399022555, "acc_norm": 0.6680544138895399, "acc_norm_stderr": 0.03236336130015535, "mc1": 0.37576499388004897, "mc1_stderr": 0.016954584060214297, "mc2": 0.5120887507064761, "mc2_stderr": 0.01572202363209222 }, "harness|arc:challenge|25": { "acc": 0.5878839590443686, "acc_stderr": 0.014383915302225407, "acc_norm": 0.6100682593856656, "acc_norm_stderr": 0.014252959848892889 }, "harness|hellaswag|10": { "acc": 0.6009759012148974, "acc_stderr": 0.004886969266944269, "acc_norm": 0.7918741286596296, "acc_norm_stderr": 0.004051376719498001 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.6592592592592592, "acc_stderr": 0.04094376269996793, "acc_norm": 0.6592592592592592, "acc_norm_stderr": 0.04094376269996793 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.7105263157894737, "acc_stderr": 0.03690677986137282, "acc_norm": 0.7105263157894737, "acc_norm_stderr": 0.03690677986137282 }, "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": 0.7396226415094339, "acc_stderr": 0.02700876609070804, "acc_norm": 0.7396226415094339, "acc_norm_stderr": 0.02700876609070804 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.8125, "acc_stderr": 0.032639560491693344, "acc_norm": 0.8125, "acc_norm_stderr": 0.032639560491693344 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.48, "acc_stderr": 0.050211673156867795, "acc_norm": 0.48, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.56, "acc_stderr": 0.04988876515698589, "acc_norm": 0.56, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.6358381502890174, "acc_stderr": 0.03669072477416907, "acc_norm": 0.6358381502890174, "acc_norm_stderr": 0.03669072477416907 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.47058823529411764, "acc_stderr": 0.04966570903978529, "acc_norm": 0.47058823529411764, "acc_norm_stderr": 0.04966570903978529 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.8, "acc_stderr": 0.04020151261036846, "acc_norm": 0.8, "acc_norm_stderr": 0.04020151261036846 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.5702127659574469, "acc_stderr": 0.03236214467715564, "acc_norm": 0.5702127659574469, "acc_norm_stderr": 0.03236214467715564 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.47368421052631576, "acc_stderr": 0.04697085136647863, "acc_norm": 0.47368421052631576, "acc_norm_stderr": 0.04697085136647863 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.6551724137931034, "acc_stderr": 0.03960933549451207, "acc_norm": 0.6551724137931034, "acc_norm_stderr": 0.03960933549451207 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.4523809523809524, "acc_stderr": 0.025634258115554955, "acc_norm": 0.4523809523809524, "acc_norm_stderr": 0.025634258115554955 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.49206349206349204, "acc_stderr": 0.044715725362943486, "acc_norm": 0.49206349206349204, "acc_norm_stderr": 0.044715725362943486 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.43, "acc_stderr": 0.049756985195624284, "acc_norm": 0.43, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7935483870967742, "acc_stderr": 0.0230258996171887, "acc_norm": 0.7935483870967742, "acc_norm_stderr": 0.0230258996171887 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.5073891625615764, "acc_stderr": 0.035176035403610105, "acc_norm": 0.5073891625615764, "acc_norm_stderr": 0.035176035403610105 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.72, "acc_stderr": 0.04512608598542128, "acc_norm": 0.72, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.7575757575757576, "acc_stderr": 0.03346409881055953, "acc_norm": 0.7575757575757576, "acc_norm_stderr": 0.03346409881055953 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.8181818181818182, "acc_stderr": 0.027479603010538804, "acc_norm": 0.8181818181818182, "acc_norm_stderr": 0.027479603010538804 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9067357512953368, "acc_stderr": 0.020986854593289726, "acc_norm": 0.9067357512953368, "acc_norm_stderr": 0.020986854593289726 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6615384615384615, "acc_stderr": 0.02399150050031303, "acc_norm": 0.6615384615384615, "acc_norm_stderr": 0.02399150050031303 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.4, "acc_stderr": 0.029869605095316904, "acc_norm": 0.4, "acc_norm_stderr": 0.029869605095316904 }, "harness|hendrycksTest-high_school_microeconomics|5": {