open-llm-leaderboard-old/details_bigcode__starcoder2-3b

该数据集是在模型 bigcode/starcoder2-3b 在 Open LLM Leaderboard 上的评估运行期间自动创建的。数据集由 63 个配置组成，每个配置对应一个被评估的任务。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 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

数据集摘要

该数据集是在对模型 bigcode/starcoder2-3b 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。

数据集组成

• 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。
• 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_bigcode__starcoder2-3b", "harness_winogrande_5", split="train")

最新结果

以下是 2024-04-02T20:35:05.231245 运行的最新结果：

python { "all": { "acc": 0.38461948986228506, "acc_stderr": 0.034446036095792894, "acc_norm": 0.3873129877490902, "acc_norm_stderr": 0.03519964377942068, "mc1": 0.23133414932680538, "mc1_stderr": 0.014761945174862677, "mc2": 0.40486982374224917, "mc2_stderr": 0.014446194947322915 }, "harness|arc:challenge|25": { "acc": 0.31143344709897613, "acc_stderr": 0.013532472099850949, "acc_norm": 0.3455631399317406, "acc_norm_stderr": 0.01389693846114568 }, "harness|hellaswag|10": { "acc": 0.37890858394742083, "acc_stderr": 0.004841238763529369, "acc_norm": 0.4761999601672974, "acc_norm_stderr": 0.00498412536331906 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.27, "acc_stderr": 0.044619604333847415, "acc_norm": 0.27, "acc_norm_stderr": 0.044619604333847415 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.3925925925925926, "acc_stderr": 0.04218506215368879, "acc_norm": 0.3925925925925926, "acc_norm_stderr": 0.04218506215368879 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.40131578947368424, "acc_stderr": 0.039889037033362836, "acc_norm": 0.40131578947368424, "acc_norm_stderr": 0.039889037033362836 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.37, "acc_stderr": 0.04852365870939098, "acc_norm": 0.37, "acc_norm_stderr": 0.04852365870939098 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.3584905660377358, "acc_stderr": 0.029514703583981762, "acc_norm": 0.3584905660377358, "acc_norm_stderr": 0.029514703583981762 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.3680555555555556, "acc_stderr": 0.04032999053960718, "acc_norm": 0.3680555555555556, "acc_norm_stderr": 0.04032999053960718 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.35, "acc_stderr": 0.047937248544110196, "acc_norm": 0.35, "acc_norm_stderr": 0.047937248544110196 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.44, "acc_stderr": 0.04988876515698589, "acc_norm": 0.44, "acc_norm_stderr": 0.04988876515698589 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.38, "acc_stderr": 0.048783173121456316, "acc_norm": 0.38, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.3352601156069364, "acc_stderr": 0.035995863012470784, "acc_norm": 0.3352601156069364, "acc_norm_stderr": 0.035995863012470784 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3137254901960784, "acc_stderr": 0.04617034827006718, "acc_norm": 0.3137254901960784, "acc_norm_stderr": 0.04617034827006718 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.62, "acc_stderr": 0.048783173121456316, "acc_norm": 0.62, "acc_norm_stderr": 0.048783173121456316 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3829787234042553, "acc_stderr": 0.03177821250236922, "acc_norm": 0.3829787234042553, "acc_norm_stderr": 0.03177821250236922 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.2807017543859649, "acc_stderr": 0.042270544512322004, "acc_norm": 0.2807017543859649, "acc_norm_stderr": 0.042270544512322004 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.4896551724137931, "acc_stderr": 0.041657747757287644, "acc_norm": 0.4896551724137931, "acc_norm_stderr": 0.041657747757287644 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.32275132275132273, "acc_stderr": 0.024078943243597016, "acc_norm": 0.32275132275132273, "acc_norm_stderr": 0.024078943243597016 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.3253968253968254, "acc_stderr": 0.041905964388711366, "acc_norm": 0.3253968253968254, "acc_norm_stderr": 0.041905964388711366 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.28, "acc_stderr": 0.045126085985421276, "acc_norm": 0.28, "acc_norm_stderr": 0.045126085985421276 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.4032258064516129, "acc_stderr": 0.02790615082604114, "acc_norm": 0.4032258064516129, "acc_norm_stderr": 0.02790615082604114 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.33004926108374383, "acc_stderr": 0.033085304262282574, "acc_norm": 0.33004926108374383, "acc_norm_stderr": 0.033085304262282574 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.53, "acc_stderr": 0.05016135580465919, "acc_norm": 0.53, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.38181818181818183, "acc_stderr": 0.037937131711656344, "acc_norm": 0.38181818181818183, "acc_norm_stderr": 0.037937131711656344 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5252525252525253, "acc_stderr": 0.035578062450873145, "acc_norm": 0.5252525252525253, "acc_norm_stderr": 0.035578062450873145 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.37823834196891193, "acc_stderr": 0.03499807276193338, "acc_norm": 0.37823834196891193, "acc_norm_stderr": 0.03499807276193338 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.33589743589743587, "acc_stderr": 0.023946724741563973, "acc_norm": 0.33589743589743587, "acc_norm_stderr": 0.023946724741563973 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3037037037037037, "acc_stderr": 0.028037929969114982, "acc_norm": 0.30370370