open-llm-leaderboard-old/details_wang7776__vicuna-7b-v1.3-attention-sparsity-20
收藏数据集概述
数据集名称
Evaluation run of wang7776/vicuna-7b-v1.3-attention-sparsity-20
数据集描述
该数据集是在对模型 wang7776/vicuna-7b-v1.3-attention-sparsity-20 进行评估运行期间自动创建的，用于 Open LLM Leaderboard。
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。
- 额外的配置 "results" 存储所有运行结果的聚合，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__vicuna-7b-v1.3-attention-sparsity-20", "harness_winogrande_5", split="train")
最新结果
这些是最新的结果，来自 2024-01-25T19:15:19.482528 运行：
python { "all": { "acc": 0.4733203404544571, "acc_stderr": 0.03438033531920741, "acc_norm": 0.4797186697875816, "acc_norm_stderr": 0.035166057009391974, "mc1": 0.3072215422276622, "mc1_stderr": 0.01615020132132301, "mc2": 0.4662240825538532, "mc2_stderr": 0.01503180403886257 }, "harness|arc:challenge|25": { "acc": 0.4803754266211604, "acc_stderr": 0.014600132075947085, "acc_norm": 0.523037542662116, "acc_norm_stderr": 0.01459587320535827 }, "harness|hellaswag|10": { "acc": 0.5778729336785501, "acc_stderr": 0.004928891895874298, "acc_norm": 0.7704640509858594, "acc_norm_stderr": 0.004196749648385375 }, "harness|hendrycksTest-abstract_algebra|5": { "acc": 0.28, "acc_stderr": 0.04512608598542129, "acc_norm": 0.28, "acc_norm_stderr": 0.04512608598542129 }, "harness|hendrycksTest-anatomy|5": { "acc": 0.4666666666666667, "acc_stderr": 0.043097329010363554, "acc_norm": 0.4666666666666667, "acc_norm_stderr": 0.043097329010363554 }, "harness|hendrycksTest-astronomy|5": { "acc": 0.46710526315789475, "acc_stderr": 0.04060127035236397, "acc_norm": 0.46710526315789475, "acc_norm_stderr": 0.04060127035236397 }, "harness|hendrycksTest-business_ethics|5": { "acc": 0.49, "acc_stderr": 0.05024183937956912, "acc_norm": 0.49, "acc_norm_stderr": 0.05024183937956912 }, "harness|hendrycksTest-clinical_knowledge|5": { "acc": 0.5584905660377358, "acc_stderr": 0.030561590426731837, "acc_norm": 0.5584905660377358, "acc_norm_stderr": 0.030561590426731837 }, "harness|hendrycksTest-college_biology|5": { "acc": 0.4652777777777778, "acc_stderr": 0.04171115858181618, "acc_norm": 0.4652777777777778, "acc_norm_stderr": 0.04171115858181618 }, "harness|hendrycksTest-college_chemistry|5": { "acc": 0.34, "acc_stderr": 0.04760952285695235, "acc_norm": 0.34, "acc_norm_stderr": 0.04760952285695235 }, "harness|hendrycksTest-college_computer_science|5": { "acc": 0.41, "acc_stderr": 0.04943110704237102, "acc_norm": 0.41, "acc_norm_stderr": 0.04943110704237102 }, "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": 0.43352601156069365, "acc_stderr": 0.037786210790920545, "acc_norm": 0.43352601156069365, "acc_norm_stderr": 0.037786210790920545 }, "harness|hendrycksTest-college_physics|5": { "acc": 0.24509803921568626, "acc_stderr": 0.04280105837364397, "acc_norm": 0.24509803921568626, "acc_norm_stderr": 0.04280105837364397 }, "harness|hendrycksTest-computer_security|5": { "acc": 0.54, "acc_stderr": 0.05009082659620332, "acc_norm": 0.54, "acc_norm_stderr": 0.05009082659620332 }, "harness|hendrycksTest-conceptual_physics|5": { "acc": 0.3659574468085106, "acc_stderr": 0.031489558297455304, "acc_norm": 0.3659574468085106, "acc_norm_stderr": 0.031489558297455304 }, "harness|hendrycksTest-econometrics|5": { "acc": 0.20175438596491227, "acc_stderr": 0.037752050135836386, "acc_norm": 0.20175438596491227, "acc_norm_stderr": 0.037752050135836386 }, "harness|hendrycksTest-electrical_engineering|5": { "acc": 0.43448275862068964, "acc_stderr": 0.04130740879555497, "acc_norm": 0.43448275862068964, "acc_norm_stderr": 0.04130740879555497 }, "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": 0.31746031746031744, "acc_stderr": 0.04163453031302859, "acc_norm": 0.31746031746031744, "acc_norm_stderr": 0.04163453031302859 }, "harness|hendrycksTest-global_facts|5": { "acc": 0.31, "acc_stderr": 0.04648231987117316, "acc_norm": 0.31, "acc_norm_stderr": 0.04648231987117316 }, "harness|hendrycksTest-high_school_biology|5": { "acc": 0.5193548387096775, "acc_stderr": 0.028422687404312107, "acc_norm": 0.5193548387096775, "acc_norm_stderr": 0.028422687404312107 }, "harness|hendrycksTest-high_school_chemistry|5": { "acc": 0.3694581280788177, "acc_stderr": 0.03395970381998574, "acc_norm": 0.3694581280788177, "acc_norm_stderr": 0.03395970381998574 }, "harness|hendrycksTest-high_school_computer_science|5": { "acc": 0.37, "acc_stderr": 0.048523658709391, "acc_norm": 0.37, "acc_norm_stderr": 0.048523658709391 }, "harness|hendrycksTest-high_school_european_history|5": { "acc": 0.5636363636363636, "acc_stderr": 0.03872592983524754, "acc_norm": 0.5636363636363636, "acc_norm_stderr": 0.03872592983524754 }, "harness|hendrycksTest-high_school_geography|5": { "acc": 0.6262626262626263, "acc_stderr": 0.03446897738659333, "acc_norm": 0.6262626262626263, "acc_norm_stderr": 0.03446897738659333 }, "harness|hendrycksTest-high_school_government_and_politics|5": { "acc": 0.6994818652849741, "acc_stderr": 0.03308818594415749, "acc_norm": 0.6994818652849741, "acc_norm_stderr": 0.03308818594415749 }, "harness|hendrycksTest-high_school_macroeconomics|5": { "acc": 0.46153846153846156, "acc_stderr": 0.025275892070240637, "acc_norm": 0.46153846153846156, "acc_norm_stderr": 0.025275892070240637 }, "harness|hendrycksTest-high_school_mathematics|5": {
