open-llm-leaderboard/details_h2oai__h2ogpt-research-oasst1-llama-65b

该数据集是在模型[h2oai/h2ogpt-research-oasst1-llama-65b](https://huggingface.co/h2oai/h2ogpt-research-oasst1-llama-65b)在[Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)上的评估运行期间自动创建的。数据集由61个配置组成，每个配置对应一个评估任务。数据集是从2次运行中创建的，每次运行都可以在每个配置中找到特定的拆分，拆分名称使用运行的时间戳。"train"拆分始终指向最新的结果。此外，还有一个名为"results"的配置，存储了所有运行的聚合结果，并用于计算和显示[Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)上的聚合指标。

This dataset was automatically created during the evaluation run of the model [h2oai/h2ogpt-research-oasst1-llama-65b](https://huggingface.co/h2oai/h2ogpt-research-oasst1-llama-65b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). The dataset consists of 61 configurations, each corresponding to one evaluation task. The dataset is compiled from 2 separate runs, where each run contains specific splits for every configuration, with the split names using the timestamp of the corresponding run. The "train" split always points to the most recent results. In addition, there is a configuration named "results" that stores the aggregated results across all runs, and is used to calculate and display the aggregate metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).

原始信息汇总

数据集概述

数据集简介

该数据集是在模型 h2oai/h2ogpt-research-oasst1-llama-65b 在 Open LLM Leaderboard 上的评估运行期间自动创建的。

数据集组成

• 数据集包含 61 个配置，每个配置对应一个评估任务。
• 数据集从 2 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_h2oai__h2ogpt-research-oasst1-llama-65b", "harness_truthfulqa_mc_0", split="train")

最新结果

以下是 2023-08-17T22:10:29.981773 运行 的最新结果：

python { "all": { "acc": 0.6359037673839993, "acc_stderr": 0.0329346816196445, "acc_norm": 0.6396809356138717, "acc_norm_stderr": 0.03290965482744071, "mc1": 0.34394124847001223, "mc1_stderr": 0.01662908751427678, "mc2": 0.48845185520886875, "mc2_stderr": 0.014057830912491135 }, "harness|arc:challenge|25": { "acc": 0.6177474402730375, "acc_stderr": 0.014200454049979275, "acc_norm": 0.6476109215017065, "acc_norm_stderr": 0.01396014260059868 }, "harness|hellaswag|10": { "acc": 0.6664011153156741, "acc_stderr": 0.004705347137699622, "acc_norm": 0.8593905596494722, "acc_norm_stderr": 0.0034690778470563765 }, "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": 0.562962962962963, "acc_stderr": 0.042849586397534015, "acc_norm": 0.562962962962963, "acc_norm_stderr": 0.042849586397534015 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.75, "acc_stderr": 0.03523807393012047, "acc_norm": 0.75, "acc_norm_stderr": 0.03523807393012047 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.6339622641509434, "acc_stderr": 0.029647813539365245, "acc_norm": 0.6339622641509434, "acc_norm_stderr": 0.029647813539365245 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.7083333333333334, "acc_stderr": 0.03800968060554858, "acc_norm": 0.7083333333333334, "acc_norm_stderr": 0.03800968060554858 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.51, "acc_stderr": 0.05024183937956911, "acc_norm": 0.51, "acc_norm_stderr": 0.05024183937956911 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.04725815626252604, "acc_norm": 0.33, "acc_norm_stderr": 0.04725815626252604 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.5549132947976878, "acc_stderr": 0.03789401760283648, "acc_norm": 0.5549132947976878, "acc_norm_stderr": 0.03789401760283648 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.3333333333333333, "acc_stderr": 0.04690650298201942, "acc_norm": 0.3333333333333333, "acc_norm_stderr": 0.04690650298201942 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.75, "acc_stderr": 0.04351941398892446, "acc_norm": 0.75, "acc_norm_stderr": 0.04351941398892446 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.6, "acc_stderr": 0.03202563076101737, "acc_norm": 0.6, "acc_norm_stderr": 0.03202563076101737 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.38596491228070173, "acc_stderr": 0.04579639422070434, "acc_norm": 0.38596491228070173, "acc_norm_stderr": 0.04579639422070434 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.5310344827586206, "acc_stderr": 0.04158632762097828, "acc_norm": 0.5310344827586206, "acc_norm_stderr": 0.04158632762097828 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.3783068783068783, "acc_stderr": 0.024976954053155254, "acc_norm": 0.3783068783068783, "acc_norm_stderr": 0.024976954053155254 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.42063492063492064, "acc_stderr": 0.04415438226743744, "acc_norm": 0.42063492063492064, "acc_norm_stderr": 0.04415438226743744 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.4, "acc_stderr": 0.04923659639173309, "acc_norm": 0.4, "acc_norm_stderr": 0.04923659639173309 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.7483870967741936, "acc_stderr": 0.024685979286239963, "acc_norm": 0.7483870967741936, "acc_norm_stderr": 0.024685979286239963 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.4039408866995074, "acc_stderr": 0.0345245390382204, "acc_norm": 0.4039408866995074, "acc_norm_stderr": 0.0345245390382204 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.67, "acc_stderr": 0.047258156262526066, "acc_norm": 0.67, "acc_norm_stderr": 0.047258156262526066 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8, "acc_stderr": 0.031234752377721164, "acc_norm": 0.8, "acc_norm_stderr": 0.031234752377721164 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.803030303030303, "acc_stderr": 0.028335609732463355, "acc_norm": 0.803030303030303, "acc_norm_stderr": 0.028335609732463355 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.8756476683937824, "acc_stderr": 0.023814477086593542, "acc_norm": 0.8756476683937824, "acc_norm_stderr": 0.023814477086593542 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.6256410256410256, "acc_stderr": 0.024537591572830513, "acc_norm": 0.6256410256410256, "acc_norm_stderr": 0.024537591572830513 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.31851851851851853, "acc_stderr": 0.02840653309060846, "acc_norm": 0.31851851851851853, "acc_norm_stderr": 0.02840653309060846 }, "harness|hendrycksTest-high_school_micro