Datasets:
Tasks:
Text Classification
Languages:
Polish
Multilinguality:
monolingual
Size Categories:
10<n<10K
Language Creators:
found
Annotations Creators:
hired_annotators
Tags:
License:
| import datasets | |
| import pandas as pd | |
| _CITATION = """\ | |
| @InProceedings{AbusiveClauses:dataset, | |
| title = {AbusiveClauses}, | |
| author={}, | |
| year={2022} | |
| } | |
| """ | |
| _DESCRIPTION = "Binary Abusive Clauses in Polish" | |
| _HOMEPAGE = "" | |
| _LICENSE = "Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)" | |
| _LABELS = ["KLAUZULA_ABUZYWNA", "BEZPIECZNE_POSTANOWIENIE_UMOWNE"] | |
| _URLS = { | |
| "train": "https://huggingface.co/datasets/laugustyniak/abusive-clauses-pl/resolve/main/train.csv", | |
| "dev": "https://huggingface.co/datasets/laugustyniak/abusive-clauses-pl/resolve/main/dev.csv", | |
| "test": "https://huggingface.co/datasets/laugustyniak/abusive-clauses-pl/resolve/main/test.csv", | |
| } | |
| class AbusiveClausesConfig(datasets.BuilderConfig): | |
| def __init__(self, **kwargs): | |
| super(AbusiveClausesConfig, self).__init__(**kwargs) | |
| class AbusiveClausesDataset(datasets.GeneratorBasedBuilder): | |
| VERSION = datasets.Version("1.0.0") | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig(name="abusive-clauses-pl", version=VERSION) | |
| ] | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "text": datasets.Value("string"), | |
| "label": datasets.features.ClassLabel( | |
| names=_LABELS, num_classes=len(_LABELS) | |
| ), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| supervised_keys=None, | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| urls_to_download = _URLS | |
| downloaded_files = dl_manager.download_and_extract(urls_to_download) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]} | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]} | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={"filepath": downloaded_files["dev"]}, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath: str): | |
| df = pd.read_csv(filepath) | |
| for idx, example in enumerate(df.itertuples(index=False)): | |
| yield idx, {"text": example.text, "label": example.label} | |