open-llm-leaderboard/details_postbot__emailgen-pythia-410m-deduped

该数据集是在模型postbot/emailgen-pythia-410m-deduped的评估运行期间自动创建的，用于在Open LLM Leaderboard上进行评估。数据集由64个配置组成，每个配置对应一个评估任务。数据集是从1次运行中创建的，每次运行都可以在特定配置中找到，分割名称使用运行的时间戳。train分割始终指向最新结果。此外，results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

数据集简介

该数据集是在评估模型postbot/emailgen-pythia-410m-deduped在Open LLM Leaderboard上的运行过程中自动创建的。

数据集结构

• 配置数量：64个配置，每个配置对应一个评估任务。
• 运行次数：数据集从1次运行中创建。每个运行在每个配置中作为一个特定的分片存在，分片名称使用运行的时间戳。
• 训练分片："train"分片始终指向最新的结果。
• 结果配置：一个额外的配置"results"存储所有运行的聚合结果，用于计算和显示在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_postbot__emailgen-pythia-410m-deduped", "harness_winogrande_5", split="train")

最新结果

以下是2023-11-13T15:24:35.622872运行的最新结果：

python { "all": { "acc": 0.2739821268942055, "acc_stderr": 0.031358822799769724, "acc_norm": 0.2757926465489037, "acc_norm_stderr": 0.03219166127988676, "mc1": 0.22276621787025705, "mc1_stderr": 0.01456650696139673, "mc2": 0.3819742528315203, "mc2_stderr": 0.015246089965112817, "em": 0.00020973154362416107, "em_stderr": 0.00014829481977280738, "f1": 0.009905620805369138, "f1_stderr": 0.0005041998138971091 }, "harness|arc:challenge|25": { "acc": 0.2593856655290102, "acc_stderr": 0.012808273573927102, "acc_norm": 0.2790102389078498, "acc_norm_stderr": 0.013106784883601333 }, "harness|hellaswag|10": { "acc": 0.34027086237801235, "acc_stderr": 0.004728318577835236, "acc_norm": 0.4004182433778132, "acc_norm_stderr": 0.00488981748973969 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.21, "acc_stderr": 0.040936018074033256, "acc_norm": 0.21, "acc_norm_stderr": 0.040936018074033256 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.2518518518518518, "acc_stderr": 0.037498507091740234, "acc_norm": 0.2518518518518518, "acc_norm_stderr": 0.037498507091740234 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.2894736842105263, "acc_stderr": 0.03690677986137283, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.03690677986137283 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.23, "acc_stderr": 0.04229525846816506, "acc_norm": 0.23, "acc_norm_stderr": 0.04229525846816506 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.33584905660377357, "acc_stderr": 0.029067220146644826, "acc_norm": 0.33584905660377357, "acc_norm_stderr": 0.029067220146644826 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.2569444444444444, "acc_stderr": 0.036539469694421, "acc_norm": 0.2569444444444444, "acc_norm_stderr": 0.036539469694421 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001976, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001976 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.2658959537572254, "acc_stderr": 0.033687629322594316, "acc_norm": 0.2658959537572254, "acc_norm_stderr": 0.033687629322594316 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3137254901960784, "acc_stderr": 0.04617034827006717, "acc_norm": 0.3137254901960784, "acc_norm_stderr": 0.04617034827006717 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.21, "acc_stderr": 0.04093601807403326, "acc_norm": 0.21, "acc_norm_stderr": 0.04093601807403326 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.2978723404255319, "acc_stderr": 0.029896145682095455, "acc_norm": 0.2978723404255319, "acc_norm_stderr": 0.029896145682095455 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.23684210526315788, "acc_stderr": 0.039994238792813344, "acc_norm": 0.23684210526315788, "acc_norm_stderr": 0.039994238792813344 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.2206896551724138, "acc_stderr": 0.034559302019248096, "acc_norm": 0.2206896551724138, "acc_norm_stderr": 0.034559302019248096 }, "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": 0.3333333333333333, "acc_stderr": 0.04216370213557836, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04216370213557836 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.22903225806451613, "acc_stderr": 0.02390491431178265, "acc_norm": 0.22903225806451613, "acc_norm_stderr": 0.02390491431178265 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.27586206896551724, "acc_stderr": 0.031447125816782426, "acc_norm": 0.27586206896551724, "acc_norm_stderr": 0.031447125816782426 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.25, "acc_stderr": 0.04351941398892446, "acc_norm": 0.25, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.26666666666666666, "acc_stderr": 0.03453131801885415, "acc_norm": 0.26666666666666666, "acc_norm_stderr": 0.03453131801885415 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.3181818181818182, "acc_stderr": 0.03318477333845331, "acc_norm": 0.3181818181818182, "acc_norm_stderr": 0.03318477333845331 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.35751295336787564, "acc_stderr": 0.034588160421810045, "acc_norm": 0.35751295336787564, "acc_norm_stderr": 0.034588160421810045 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.36153846153846153, "acc_stderr": 0.024359581465396987, "acc_norm": 0