Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
topic-classification
Languages:
Burmese
Size:
1K - 10K
License:
File size: 2,724 Bytes
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# 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.
import csv
import os
import datasets
from datasets.tasks import TextClassification
# no BibTeX citation
_CITATION = ""
_DESCRIPTION = """\
The Myanmar news dataset contains article snippets in four categories:
Business, Entertainment, Politics, and Sport.
These were collected in October 2017 by Aye Hninn Khine
"""
_LICENSE = "GPL-3.0"
_URLs = {"default": "https://github.com/Georeactor/MyanmarNewsClassificationSystem/archive/main.zip"}
class MyanmarNews(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.1")
def _info(self):
class_names = ["Sport", "Politic", "Business", "Entertainment"]
features = datasets.Features(
{
"text": datasets.Value("string"),
"category": datasets.ClassLabel(names=class_names),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage="https://github.com/ayehninnkhine/MyanmarNewsClassificationSystem",
license=_LICENSE,
citation=_CITATION,
task_templates=[TextClassification(text_column="text", label_column="category")],
)
def _split_generators(self, dl_manager):
my_urls = _URLs[self.config.name]
data_dir = dl_manager.download_and_extract(my_urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": os.path.join(data_dir, "MyanmarNewsClassificationSystem-main", "topics.csv"),
"split": "train",
},
),
]
def _generate_examples(self, filepath, split):
with open(filepath, encoding="utf-8") as f:
rdr = csv.reader(f, delimiter="\t")
next(rdr)
rownum = 0
for row in rdr:
rownum += 1
yield rownum, {
"text": row[0],
"category": row[1],
}
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