open-llm-leaderboard-old/details_luffycodes__llama-shishya-7b-ep3-v2

该数据集是在Open LLM Leaderboard上对模型luffycodes/llama-shishya-7b-ep3-v2进行评估时自动创建的。数据集由64个配置组成，每个配置对应一个评估任务。数据集从1次运行中创建，每次运行可以在每个配置中找到，运行的时间戳作为分割名称。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

数据集摘要

该数据集是在评估模型 luffycodes/llama-shishya-7b-ep3-v2 在 Open LLM Leaderboard 上的自动创建的。

数据集组成

• 数据集包含 64 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作为一个特定的分片找到，分片名称使用运行的 timestamp。
• "train" 分片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，用于计算和显示聚合指标在 Open LLM Leaderboard 上。

数据加载示例

python from datasets import load_dataset data = load_dataset("open-llm-leaderboard/details_luffycodes__llama-shishya-7b-ep3-v2_public", "harness_winogrande_5", split="train")

最新结果

以下是 2023-11-09T12:57:06.707192 运行的最新结果：

python { "all": { "acc": 0.43776292457137356, "acc_stderr": 0.03405236312139111, "acc_norm": 0.44440566326787106, "acc_norm_stderr": 0.03497626520397757, "mc1": 0.19583843329253367, "mc1_stderr": 0.01389234436774209, "mc2": 0.3016304809342682, "mc2_stderr": 0.013699598037265183, "em": 0.30557885906040266, "em_stderr": 0.004717509363446725, "f1": 0.36205327181208175, "f1_stderr": 0.004656030495449622 }, "harness|arc:challenge|25": { "acc": 0.44197952218430037, "acc_stderr": 0.014512682523128345, "acc_norm": 0.4735494880546075, "acc_norm_stderr": 0.014590931358120172 }, "harness|hellaswag|10": { "acc": 0.5865365465046803, "acc_stderr": 0.004914480534533716, "acc_norm": 0.7588129854610636, "acc_norm_stderr": 0.004269291950109927 }, "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": 0.4222222222222222, "acc_stderr": 0.04266763404099582, "acc_norm": 0.4222222222222222, "acc_norm_stderr": 0.04266763404099582 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.4144736842105263, "acc_stderr": 0.040089737857792046, "acc_norm": 0.4144736842105263, "acc_norm_stderr": 0.040089737857792046 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.38, "acc_stderr": 0.04878317312145632, "acc_norm": 0.38, "acc_norm_stderr": 0.04878317312145632 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4716981132075472, "acc_stderr": 0.0307235352490061, "acc_norm": 0.4716981132075472, "acc_norm_stderr": 0.0307235352490061 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4236111111111111, "acc_stderr": 0.04132125019723369, "acc_norm": 0.4236111111111111, "acc_norm_stderr": 0.04132125019723369 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.28, "acc_stderr": 0.04512608598542128, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542128 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001975, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001975 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.26, "acc_stderr": 0.04408440022768077, "acc_norm": 0.26, "acc_norm_stderr": 0.04408440022768077 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.41040462427745666, "acc_stderr": 0.03750757044895537, "acc_norm": 0.41040462427745666, "acc_norm_stderr": 0.03750757044895537 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.23529411764705882, "acc_stderr": 0.04220773659171452, "acc_norm": 0.23529411764705882, "acc_norm_stderr": 0.04220773659171452 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.54, "acc_stderr": 0.05009082659620333, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620333 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.39574468085106385, "acc_stderr": 0.03196758697835362, "acc_norm": 0.39574468085106385, "acc_norm_stderr": 0.03196758697835362 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2894736842105263, "acc_stderr": 0.042663394431593935, "acc_norm": 0.2894736842105263, "acc_norm_stderr": 0.042663394431593935 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.3931034482758621, "acc_stderr": 0.0407032901370707, "acc_norm": 0.3931034482758621, "acc_norm_stderr": 0.0407032901370707 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.30423280423280424, "acc_stderr": 0.023695415009463087, "acc_norm": 0.30423280423280424, "acc_norm_stderr": 0.023695415009463087 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.19047619047619047, "acc_stderr": 0.035122074123020514, "acc_norm": 0.19047619047619047, "acc_norm_stderr": 0.035122074123020514 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5096774193548387, "acc_stderr": 0.02843867799890955, "acc_norm": 0.5096774193548387, "acc_norm_stderr": 0.02843867799890955 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.32019704433497537, "acc_stderr": 0.032826493853041504, "acc_norm": 0.32019704433497537, "acc_norm_stderr": 0.032826493853041504 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5696969696969697, "acc_stderr": 0.03866225962879077, "acc_norm": 0.5696969696969697, "acc_norm_stderr": 0.03866225962879077 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.51010101010101, "acc_stderr": 0.035616254886737454, "acc_norm": 0.51010101010101, "acc_norm_stderr": 0.035616254886737454 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.5854922279792746, "acc_stderr": 0.035553003195576686, "acc_norm": 0.5854922279792746, "acc_norm_stderr": 0.035553003195576686 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.37435897435897436, "acc_stderr": 0.024537591572830517, "acc_norm": 0.37435897435897