Datasets:
yoruba_bbc_topics

	# coding=utf-8
	# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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	# limitations under the License.

	# Lint as: python3
	"""Yoruba BBC News Topic Classification dataset."""


	import csv

	import datasets


	_DESCRIPTION = """\
	A collection of news article headlines in Yoruba from BBC Yoruba.
	Each headline is labeled with one of the following classes: africa,
	entertainment, health, nigeria, politics, sport or world.

	The dataset was presented in the paper:
	Hedderich, Adelani, Zhu, Alabi, Markus, Klakow: Transfer Learning and
	Distant Supervision for Multilingual Transformer Models: A Study on
	African Languages (EMNLP 2020).
	"""

	_CITATION = """\
	@inproceedings{hedderich-etal-2020-transfer,
	title = "Transfer Learning and Distant Supervision for Multilingual Transformer Models: A Study on African Languages",
	author = "Hedderich, Michael A. and
	Adelani, David and
	Zhu, Dawei and
	Alabi, Jesujoba and
	Markus, Udia and
	Klakow, Dietrich",
	booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
	year = "2020",
	publisher = "Association for Computational Linguistics",
	url = "https://www.aclweb.org/anthology/2020.emnlp-main.204",
	doi = "10.18653/v1/2020.emnlp-main.204",
	}
	"""

	_TRAIN_DOWNLOAD_URL = "https://raw.githubusercontent.com/uds-lsv/transfer-distant-transformer-african/master/data/yoruba_newsclass/train_clean.tsv"
	_VALIDATION_DOWNLOAD_URL = "https://raw.githubusercontent.com/uds-lsv/transfer-distant-transformer-african/master/data/yoruba_newsclass/dev.tsv"
	_TEST_DOWNLOAD_URL = "https://raw.githubusercontent.com/uds-lsv/transfer-distant-transformer-african/master/data/yoruba_newsclass/test.tsv"


	class YorubaBBCTopics(datasets.GeneratorBasedBuilder):
	"""Yoruba BBC Topic Classification dataset."""

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"news_title": datasets.Value("string"),
	"label": datasets.features.ClassLabel(
	names=["africa", "entertainment", "health", "nigeria", "politics", "sport", "world"]
	),
	"date": datasets.Value("string"),
	"bbc_url_id": datasets.Value("string"),
	}
	),
	homepage="https://github.com/uds-lsv/transfer-distant-transformer-african",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL)
	validation_path = dl_manager.download_and_extract(_VALIDATION_DOWNLOAD_URL)
	test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL)
	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
	datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": validation_path}),
	datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
	]

	def _generate_examples(self, filepath):
	"""Generate Yoruba BBC News Topic examples."""
	with open(filepath, encoding="utf-8") as csv_file:
	csv_reader = csv.DictReader(csv_file, delimiter="\t")
	for id_, row in enumerate(csv_reader):
	yield id_, {
	"news_title": row["news_title"],
	"label": row["label"],
	"date": row["date"],
	"bbc_url_id": row["bbc_url_id"],
	}