Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
natural-language-inference
Languages:
Croatian
Size:
1K - 10K
ArXiv:
License:
SuzanaB
commited on
Commit
·
d6f6dec
1
Parent(s):
d71a4a8
Add files
Browse files- copa_hr.py +100 -0
- test.jsonl +3 -0
- train.jsonl +3 -0
- val.jsonl +3 -0
copa_hr.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the 'License');
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an 'AS IS' BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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import datasets
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_CITATION = ''
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_DESCRIPTION = """The COPA-HR dataset (Choice of plausible alternatives in Croatian) is a translation
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of the English COPA dataset (https://people.ict.usc.edu/~gordon/copa.html) by following the
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XCOPA dataset translation methodology (https://arxiv.org/abs/2005.00333). The dataset consists of 1000 premises
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(My body cast a shadow over the grass), each given a question (What is the cause?), and two choices
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(The sun was rising; The grass was cut), with a label encoding which of the choices is more plausible
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given the annotator or translator (The sun was rising).
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The dataset is split into 400 training samples, 100 validation samples, and 500 test samples. It includes the
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following features: 'premise', 'choice1', 'choice2', 'label', 'question', 'changed' (boolean).
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"""
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_HOMEPAGE = 'https://www.clarin.si/repository/xmlui/handle/11356/1404'
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_LICENSE = ''
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_TRAINING_FILE = 'train.jsonl'
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_DEV_FILE = 'val.jsonl'
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_TEST_FILE = 'test.jsonl'
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class CopaHr(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version('1.1.0')
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name='copa_hr',
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version=VERSION,
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data_files=[_TRAINING_FILE, _DEV_FILE, _TEST_FILE],
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description=''
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)
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]
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def _info(self):
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features = datasets.Features(
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{
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'premise': datasets.Value('string'),
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'choice1': datasets.Value('string'),
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'choice2': datasets.Value('string'),
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'label': datasets.features.ClassLabel(names=['0', '1']),
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'question': datasets.Value('string'),
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'idx': datasets.Value('int64'),
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'changed': datasets.Value('bool')
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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supervised_keys=None,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN, gen_kwargs={'filepath': _TRAINING_FILE, 'split': 'train'}
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION, gen_kwargs={'filepath': _DEV_FILE, 'split': 'dev'}
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST, gen_kwargs={'filepath': _TEST_FILE, 'split': 'test'}
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),
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]
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def _generate_examples(self, filepath, split):
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with open(filepath, encoding='utf-8') as f:
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for i, line in enumerate(f):
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data = json.loads(line)
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yield i, {
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'premise': data['premise'],
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'choice1': data['choice1'],
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'choice2': data['choice2'],
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'question': data['question'],
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'label': str(data['label']),
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'idx': data['idx'],
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'changed': data['changed']
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}
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test.jsonl
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version https://git-lfs.github.com/spec/v1
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oid sha256:809967a09c31862d51efde4ae6ae0ed7d36d0e5179e260a786fc267569326875
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size 98496
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train.jsonl
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version https://git-lfs.github.com/spec/v1
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oid sha256:a96f4bbcfb3d7dac287b31231b61a73f080b9cc9d68496cb6aaaa927f735230c
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size 80381
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val.jsonl
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version https://git-lfs.github.com/spec/v1
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oid sha256:20b4348af5cfaf4be074a57e7b9e5c5d6fdb23eb0530681c7cd0295341a163a8
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size 19982
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