Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-class-classification
Languages:
Mongolian
Size:
10K<n<100K
License:
# coding=utf-8 | |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
# | |
# 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. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
"""Eduge news topic classification dataset.""" | |
import csv | |
import datasets | |
from datasets.tasks import TextClassification | |
_DESCRIPTION = """\ | |
Eduge news classification dataset is provided by Bolorsoft LLC. It is used for training the Eduge.mn production news classifier | |
75K news articles in 9 categories: урлаг соёл, эдийн засаг, эрүүл мэнд, хууль, улс төр, спорт, технологи, боловсрол and байгал орчин | |
""" | |
_TRAIN_DOWNLOAD_URL = "https://storage.googleapis.com/eduge_dataset/eduge_train.csv" | |
_TEST_DOWNLOAD_URL = "https://storage.googleapis.com/eduge_dataset/eduge_test.csv" | |
class Eduge(datasets.GeneratorBasedBuilder): | |
"""Eduge news topic classification dataset.""" | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"news": datasets.Value("string"), | |
"label": datasets.features.ClassLabel( | |
names=[ | |
"урлаг соёл", | |
"эдийн засаг", | |
"эрүүл мэнд", | |
"хууль", | |
"улс төр", | |
"спорт", | |
"технологи", | |
"боловсрол", | |
"байгал орчин", | |
] | |
), | |
} | |
), | |
homepage="http://eduge.mn", | |
task_templates=[ | |
TextClassification( | |
text_column="news", | |
label_column="label", | |
) | |
], | |
) | |
def _split_generators(self, dl_manager): | |
train_path = dl_manager.download_and_extract(_TRAIN_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.TEST, gen_kwargs={"filepath": test_path}), | |
] | |
def _generate_examples(self, filepath): | |
"""Generate Eduge news examples.""" | |
with open(filepath, encoding="utf-8") as csv_file: | |
csv_reader = csv.reader( | |
csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True | |
) | |
next(csv_reader) | |
for id_, row in enumerate(csv_reader): | |
news, label = row[0], row[1] | |
yield id_, {"news": news, "label": label} | |