open-llm-leaderboard-old/details_ibivibiv__alpaca-dragon-72b-v1

该数据集是在模型 ibivibiv/alpaca-dragon-72b-v1 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，每个配置对应一个评估任务。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，分割名称使用运行的时间戳。train 分割始终指向最新结果。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 代码加载运行中的详细信息的示例，并包含了特定运行的最新结果。

原始信息汇总

数据集概述

数据集简介

该数据集是在模型ibivibiv/alpaca-dragon-72b-v1的评估运行期间自动创建的，用于Open LLM Leaderboard。

数据集结构

• 配置数量：63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_ibivibiv__alpaca-dragon-72b-v1", "harness_winogrande_5", split="train")

最新结果

以下是2024-02-10T01:36:35.503154运行的最新结果：

python { "all": { "acc": 0.7731228139040556, "acc_stderr": 0.027777455725368695, "acc_norm": 0.7752168333280753, "acc_norm_stderr": 0.028328790621382747, "mc1": 0.602203182374541, "mc1_stderr": 0.017133934248559676, "mc2": 0.7269367196902492, "mc2_stderr": 0.014514419838318984 }, "harness|arc:challenge|25": { "acc": 0.7081911262798635, "acc_stderr": 0.013284525292403503, "acc_norm": 0.7389078498293515, "acc_norm_stderr": 0.012835523909473847 }, "harness|hellaswag|10": { "acc": 0.6983668591913962, "acc_stderr": 0.0045802887281959775, "acc_norm": 0.8815972913762199, "acc_norm_stderr": 0.0032242407223513165 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.42, "acc_stderr": 0.049604496374885836, "acc_norm": 0.42, "acc_norm_stderr": 0.049604496374885836 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.7185185185185186, "acc_stderr": 0.038850042458002526, "acc_norm": 0.7185185185185186, "acc_norm_stderr": 0.038850042458002526 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.868421052631579, "acc_stderr": 0.02750868953354992, "acc_norm": 0.868421052631579, "acc_norm_stderr": 0.02750868953354992 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.82, "acc_stderr": 0.038612291966536955, "acc_norm": 0.82, "acc_norm_stderr": 0.038612291966536955 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.8452830188679246, "acc_stderr": 0.022257075558791282, "acc_norm": 0.8452830188679246, "acc_norm_stderr": 0.022257075558791282 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.9305555555555556, "acc_stderr": 0.02125797482283205, "acc_norm": 0.9305555555555556, "acc_norm_stderr": 0.02125797482283205 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.65, "acc_stderr": 0.04793724854411019, "acc_norm": 0.65, "acc_norm_stderr": 0.04793724854411019 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.52, "acc_stderr": 0.050211673156867795, "acc_norm": 0.52, "acc_norm_stderr": 0.050211673156867795 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.7514450867052023, "acc_stderr": 0.03295304696818317, "acc_norm": 0.7514450867052023, "acc_norm_stderr": 0.03295304696818317 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.5588235294117647, "acc_stderr": 0.049406356306056595, "acc_norm": 0.5588235294117647, "acc_norm_stderr": 0.049406356306056595 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.82, "acc_stderr": 0.03861229196653695, "acc_norm": 0.82, "acc_norm_stderr": 0.03861229196653695 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.8042553191489362, "acc_stderr": 0.025937853139977148, "acc_norm": 0.8042553191489362, "acc_norm_stderr": 0.025937853139977148 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.6052631578947368, "acc_stderr": 0.045981880578165414, "acc_norm": 0.6052631578947368, "acc_norm_stderr": 0.045981880578165414 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.7931034482758621, "acc_stderr": 0.03375672449560553, "acc_norm": 0.7931034482758621, "acc_norm_stderr": 0.03375672449560553 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.7037037037037037, "acc_stderr": 0.023517294335963286, "acc_norm": 0.7037037037037037, "acc_norm_stderr": 0.023517294335963286 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.5873015873015873, "acc_stderr": 0.04403438954768176, "acc_norm": 0.5873015873015873, "acc_norm_stderr": 0.04403438954768176 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.8838709677419355, "acc_stderr": 0.018225757949432306, "acc_norm": 0.8838709677419355, "acc_norm_stderr": 0.018225757949432306 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.6600985221674877, "acc_stderr": 0.033327690684107895, "acc_norm": 0.6600985221674877, "acc_norm_stderr": 0.033327690684107895 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.82, "acc_stderr": 0.038612291966536934, "acc_norm": 0.82, "acc_norm_stderr": 0.038612291966536934 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.8424242424242424, "acc_stderr": 0.028450388805284357, "acc_norm": 0.8424242424242424, "acc_norm_stderr": 0.028450388805284357 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.9444444444444444, "acc_stderr": 0.0163199507007674, "acc_norm": 0.9444444444444444, "acc_norm_stderr": 0.0163199507007674 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.9896373056994818, "acc_stderr": 0.007308424386792194, "acc_norm": 0.9896373056994818, "acc_norm_stderr": 0.007308424386792194 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.8205128205128205, "acc_stderr": 0.019457390787681782, "acc_norm": 0.8205128205128205, "acc_norm_stderr": 0.019457390787681782 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.45925925925925926, "acc_stderr": 0.030384169232350818, "