open-llm-leaderboard-old/details_hamxea__Llama-2-13b-chat-hf-activity-fine-tuned-v4

该数据集是在评估模型hamxea/Llama-2-13b-chat-hf-activity-fine-tuned-v4在Open LLM Leaderboard上的运行期间自动创建的。它包含63个配置，每个配置对应一个评估任务。数据集由一次运行创建，每次运行都作为一个特定的分割，以运行的时间戳命名。此外，结果配置汇总了所有运行的结果，用于在排行榜上计算和显示指标。数据集包括对各种任务的详细结果，如学术科目、专业领域和特定挑战，为模型在不同领域的性能提供了全面的评估。

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 hamxea/Llama-2-13b-chat-hf-activity-fine-tuned-v4 在 Open LLM Leaderboard 上的运行过程中自动创建的。

数据集组成

• 数据集包含 63 个配置，每个配置对应一个评估任务。
• 数据集由 1 次运行创建，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_hamxea__Llama-2-13b-chat-hf-activity-fine-tuned-v4", "harness_winogrande_5", split="train")

最新结果

以下是 最新结果来自 run 2024-03-31T18:54:30.994046 的摘要：

python { "all": { "acc": 0.5461419970321223, "acc_stderr": 0.033742897935860695, "acc_norm": 0.5505249932461566, "acc_norm_stderr": 0.03444432370071951, "mc1": 0.2839657282741738, "mc1_stderr": 0.01578537085839672, "mc2": 0.43823907083485514, "mc2_stderr": 0.01553513697251055 }, "harness|arc:challenge|25": { "acc": 0.5520477815699659, "acc_stderr": 0.014532011498211674, "acc_norm": 0.5921501706484642, "acc_norm_stderr": 0.014361097288449698 }, "harness|hellaswag|10": { "acc": 0.6244771957777335, "acc_stderr": 0.004832679188788788, "acc_norm": 0.8166699860585541, "acc_norm_stderr": 0.0038614605262315364 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4740740740740741, "acc_stderr": 0.04313531696750574, "acc_norm": 0.4740740740740741, "acc_norm_stderr": 0.04313531696750574 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.5592105263157895, "acc_stderr": 0.04040311062490437, "acc_norm": 0.5592105263157895, "acc_norm_stderr": 0.04040311062490437 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5886792452830188, "acc_stderr": 0.03028500925900979, "acc_norm": 0.5886792452830188, "acc_norm_stderr": 0.03028500925900979 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.5694444444444444, "acc_stderr": 0.04140685639111503, "acc_norm": 0.5694444444444444, "acc_norm_stderr": 0.04140685639111503 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.36, "acc_stderr": 0.04824181513244218, "acc_norm": 0.36, "acc_norm_stderr": 0.04824181513244218 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.32, "acc_stderr": 0.046882617226215034, "acc_norm": 0.32, "acc_norm_stderr": 0.046882617226215034 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.4624277456647399, "acc_stderr": 0.0380168510452446, "acc_norm": 0.4624277456647399, "acc_norm_stderr": 0.0380168510452446 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.30392156862745096, "acc_stderr": 0.04576665403207763, "acc_norm": 0.30392156862745096, "acc_norm_stderr": 0.04576665403207763 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.7, "acc_stderr": 0.046056618647183814, "acc_norm": 0.7, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.4127659574468085, "acc_stderr": 0.03218471141400351, "acc_norm": 0.4127659574468085, "acc_norm_stderr": 0.03218471141400351 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.30701754385964913, "acc_stderr": 0.04339138322579861, "acc_norm": 0.30701754385964913, "acc_norm_stderr": 0.04339138322579861 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.496551724137931, "acc_stderr": 0.041665675771015785, "acc_norm": 0.496551724137931, "acc_norm_stderr": 0.041665675771015785 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3412698412698413, "acc_stderr": 0.024419234966819064, "acc_norm": 0.3412698412698413, "acc_norm_stderr": 0.024419234966819064 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.30158730158730157, "acc_stderr": 0.041049472699033945, "acc_norm": 0.30158730158730157, "acc_norm_stderr": 0.041049472699033945 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.6387096774193548, "acc_stderr": 0.027327548447957543, "acc_norm": 0.6387096774193548, "acc_norm_stderr": 0.027327548447957543 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.458128078817734, "acc_stderr": 0.03505630140785741, "acc_norm": 0.458128078817734, "acc_norm_stderr": 0.03505630140785741 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.58, "acc_stderr": 0.049604496374885836, "acc_norm": 0.58, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6727272727272727, "acc_stderr": 0.03663974994391244, "acc_norm": 0.6727272727272727, "acc_norm_stderr": 0.03663974994391244 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.702020202020202, "acc_stderr": 0.03258630383836557, "acc_norm": 0.702020202020202, "acc_norm_stderr": 0.03258630383836557 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.7875647668393783, "acc_stderr": 0.029519282616817234, "acc_norm": 0.7875647668393783, "acc_norm_stderr": 0.029519282616817234 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4897435897435897, "acc_stderr": 0.025345672221942374, "acc_norm": 0.4897435897435897, "acc_norm_stderr": 0.025345672221942374 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.3037037037037037, "acc_stderr": 0.02803