HAE_RAE_BENCH.py

import os

import datasets
import json
import pandas as pd

_CITATION = """\
    @article{son2023hae,
  title={HAE-RAE Bench: Evaluation of Korean Knowledge in Language Models},
  author={Son, Guijin and Lee, Hanwool and Kim, Suwan and Lee, Jaecheol and Yeom, Je Won and Jung, Jihyu and Kim, Jung Woo and Kim, Songseong},
  journal={arXiv preprint arXiv:2309.02706},
  year={2023}
}
"""

_DESCRIPTION = """\
    HAE-RAE Bench
"""

_HOMEPAGE = "https://huggingface.co/HAERAE-HUB"

_LICENSE = "cc-by-nc-nd-4.0"

split_names = ['standard_nomenclature',
 'correct_definition_matching',
 'date_understanding',
 'general_knowledge',
 'history',
 'loan_word',
 'lyrics_denoising',
 'proverbs_denoising',
 'rare_word',
 'reading_comprehension']

class HRBConfig(datasets.BuilderConfig):
    def __init__(self, **kwargs):
        super().__init__(version=datasets.Version("1.0.1"), **kwargs)


class HRB(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        HRBConfig(
            name=name,
        )
        for name in split_names
    ]

    def _info(self):
        features = datasets.Features(
            {
                "query": datasets.Value("string"),
                "options" : datasets.Value("string"),
                "answer": datasets.Value("string"),
                "category": datasets.Value("string"),
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        train_path = dl_manager.download_and_extract("./data/hrb.v1.1.jsonl")
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": train_path,
                },
            ),
        ]

    def _generate_examples(self, filepath):
        with open(filepath, encoding="utf-8") as f:
            buffer = []
            for key, row in enumerate(f):
                data = json.loads(row)
                    
                if data["category"] == self.config.name:
                    buffer.append({
                        "query": data["query"],
                        "options" : data["options"],
                        "answer": data["answer"],
                        "category": data["category"]
                    })
                
            for idx, dat in enumerate(buffer):
                yield idx,dat