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 | |
| _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", | |
| ) | |
| 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} | |