metadata
license: mit
task_categories:
- text-generation
language:
- ja
- en
tags:
- code
configs:
- config_name: ja
data_files:
- split: test
path:
- sakuraeval/ja.parquet
- config_name: en
data_files:
- split: test
path:
- sakuraeval/en.parquet
SakuraEval
Dataset Description
SakuraEval is a Japan-specific code generation benchmark dataset. It is designed independently and does not rely on translation from English benchmarks such as HumanEval or JHumanEval.
Dataset Structure
from datasets import load_dataset
load_dataset("kogi-jwu/sakuraeval", "ja")
DatasetDict({
test: Dataset({
features: ['task_id', 'category', 'prompt', 'canonical_solution', 'test', 'entry_point'],
num_rows: 164
})
})
Data Fields
- task_id: Identifier for the data sample.
- category: Task category.
- prompt: Input for the model, including the function header and docstring that describes the task.
- canonical_solution: Solution to the problem presented in the prompt.
- test: Function(s) to test the generated code for correctness.
- entry_point: Entry point function to begin testing.
Category Breakdown
| Category | Number of Tasks |
|---|---|
| 文化（Culture） | 34 |
| 風習（Customs） | 27 |
| 日本地理（Japanese Geography） | 10 |
| 公民・法律（Law and Civics） | 11 |
| 数学・科学（Math and Science） | 21 |
| 単位変換（Unit Conversion） | 11 |
| 日本語処理（Japanese Language） | 43 |
| その他（Other） | 7 |
Languages
The dataset contains coding problems in 2 natural languages: English and Japanese.