open-llm-leaderboard-old/details_wang7776__Llama-2-7b-chat-hf-30-attention-sparsity

该数据集是在模型wang7776/Llama-2-7b-chat-hf-30-attention-sparsity在Open LLM Leaderboard上的评估运行期间自动创建的。它由63个配置组成，每个配置对应一个评估任务。数据集是从1次运行中创建的，每次运行作为每个配置中的一个特定分割，使用运行的时间戳命名。train分割始终指向最新结果。一个额外的配置results存储了运行的所有聚合结果，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

该数据集是在对模型 wang7776/Llama-2-7b-chat-hf-30-attention-sparsity 进行评估运行时自动创建的，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，每个运行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。
• 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_wang7776__Llama-2-7b-chat-hf-30-attention-sparsity", "harness_winogrande_5", split="train")

最新结果

以下是 2024-01-26T21:28:33.090458 运行的最新结果：

python { "all": { "acc": 0.47171176555273875, "acc_stderr": 0.03427847553885065, "acc_norm": 0.4765170024786929, "acc_norm_stderr": 0.03503452138702699, "mc1": 0.2913096695226438, "mc1_stderr": 0.01590598704818483, "mc2": 0.450180283055029, "mc2_stderr": 0.015612058311126043 }, "harness|arc:challenge|25": { "acc": 0.4974402730375427, "acc_stderr": 0.014611199329843784, "acc_norm": 0.5341296928327645, "acc_norm_stderr": 0.014577311315231102 }, "harness|hellaswag|10": { "acc": 0.5805616411073491, "acc_stderr": 0.004924586362301656, "acc_norm": 0.76867157936666, "acc_norm_stderr": 0.004208200511232451 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.3, "acc_stderr": 0.04605661864718381, "acc_norm": 0.3, "acc_norm_stderr": 0.04605661864718381 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4148148148148148, "acc_stderr": 0.042561937679014075, "acc_norm": 0.4148148148148148, "acc_norm_stderr": 0.042561937679014075 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.48026315789473684, "acc_stderr": 0.040657710025626036, "acc_norm": 0.48026315789473684, "acc_norm_stderr": 0.040657710025626036 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.47, "acc_stderr": 0.05016135580465919, "acc_norm": 0.47, "acc_norm_stderr": 0.05016135580465919 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.4867924528301887, "acc_stderr": 0.030762134874500476, "acc_norm": 0.4867924528301887, "acc_norm_stderr": 0.030762134874500476 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4722222222222222, "acc_stderr": 0.04174752578923185, "acc_norm": 0.4722222222222222, "acc_norm_stderr": 0.04174752578923185 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.3, "acc_stderr": 0.046056618647183814, "acc_norm": 0.3, "acc_norm_stderr": 0.046056618647183814 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.4, "acc_stderr": 0.049236596391733084, "acc_norm": 0.4, "acc_norm_stderr": 0.049236596391733084 }, "harness|hendrycksTest-college_mathematics|5": { "acc": 0.33, "acc_stderr": 0.047258156262526045, "acc_norm": 0.33, "acc_norm_stderr": 0.047258156262526045 }, "harness|hendrycksTest-college_medicine|5": { "acc": 0.34104046242774566, "acc_stderr": 0.036146654241808254, "acc_norm": 0.34104046242774566, "acc_norm_stderr": 0.036146654241808254 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.20588235294117646, "acc_stderr": 0.04023382273617746, "acc_norm": 0.20588235294117646, "acc_norm_stderr": 0.04023382273617746 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.57, "acc_stderr": 0.049756985195624284, "acc_norm": 0.57, "acc_norm_stderr": 0.049756985195624284 }, "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": 0.35964912280701755, "acc_stderr": 0.045144961328736334, "acc_norm": 0.35964912280701755, "acc_norm_stderr": 0.045144961328736334 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.47586206896551725, "acc_stderr": 0.0416180850350153, "acc_norm": 0.47586206896551725, "acc_norm_stderr": 0.0416180850350153 }, "harness|hendrycksTest-elementary_mathematics|5": { "acc": 0.291005291005291, "acc_stderr": 0.02339382650048487, "acc_norm": 0.291005291005291, "acc_norm_stderr": 0.02339382650048487 }, "harness|hendrycksTest-formal_logic|5": { "acc": 0.24603174603174602, "acc_stderr": 0.03852273364924316, "acc_norm": 0.24603174603174602, "acc_norm_stderr": 0.03852273364924316 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5258064516129032, "acc_stderr": 0.028406095057653326, "acc_norm": 0.5258064516129032, "acc_norm_stderr": 0.028406095057653326 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3448275862068966, "acc_stderr": 0.03344283744280458, "acc_norm": 0.3448275862068966, "acc_norm_stderr": 0.03344283744280458 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.39, "acc_stderr": 0.04902071300001974, "acc_norm": 0.39, "acc_norm_stderr": 0.04902071300001974 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.6060606060606061, "acc_stderr": 0.0381549430868893, "acc_norm": 0.6060606060606061, "acc_norm_stderr": 0.0381549430868893 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.5808080808080808, "acc_stderr": 0.03515520728670417, "acc_norm": 0.5808080808080808, "acc_norm_stderr": 0.03515520728670417 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6839378238341969, "acc_stderr": 0.033553973696861736, "acc_norm": 0.6839378238341969, "acc_norm_stderr": 0.033553973696861736 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.4025641025641026, "acc_stderr": 0.024864995159767752, "acc_norm": 0.4025641025641026, "acc_norm_stderr": 0.024864995159767752 }, "harness|hendrycksTest-high_school_mathematics|5": { "acc": 0.27037037037037037, "acc_stderr":