Update parquet files

README.md

@@ -1,38 +0,0 @@
----
-language:
-- hr
-license:
-- cc-by-sa-4.0
-task_categories:
-- text-classification
-task_ids:
-- natural-language-inference
-tags:
-- causal-reasoning
-- textual-entailment
-- commonsense-reasoning
----
-The COPA-HR dataset (Choice of plausible alternatives in Croatian) is a translation 
-of the English COPA dataset (https://people.ict.usc.edu/~gordon/copa.html) by following the 
-XCOPA dataset translation methodology (https://arxiv.org/abs/2005.00333). The dataset consists of 1000 premises 
-(My body cast a shadow over the grass), each given a question (What is the cause?), and two choices 
-(The sun was rising; The grass was cut), with a label encoding which of the choices is more plausible 
-given the annotator or translator (The sun was rising).
-
-The dataset is split into 400 training samples, 100 validation samples, and 500 test samples. It includes the 
-following features: 'premise', 'choice1', 'choice2', 'label', 'question', 'changed' (boolean).
-
-If you use the dataset in your work, please cite
-```
-@article{DBLP:journals/corr/abs-2104-09243,
- author    = {Nikola Ljube\\\\v{s}i\\\\'{c} and
-              Davor Lauc},
- title     = {BERTi{\\\\'{c}} - The Transformer Language Model for Bosnian, Croatian,
-               Montenegrin and Serbian},
- journal   = {CoRR},
- volume    = {abs/2104.09243},
- year      = {2021},
- url       = {https://arxiv.org/abs/2104.09243},
- archivePrefix = {arXiv},
-}
-```

copa_hr.py

@@ -1,120 +0,0 @@
-# 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 json
-import os
-
-import datasets
-
-
-_CITATION = """@article{DBLP:journals/corr/abs-2104-09243,
-  author    = {Nikola Ljubesic and
-               Davor Lauc},
-  title     = {BERTi{\'{c}} - The Transformer Language Model for Bosnian, Croatian,
-               Montenegrin and Serbian},
-  journal   = {CoRR},
-  volume    = {abs/2104.09243},
-  year      = {2021},
-  url       = {https://arxiv.org/abs/2104.09243},
-  archivePrefix = {arXiv},
-}"""
-_DESCRIPTION = """The COPA-HR dataset (Choice of plausible alternatives in Croatian) is a translation 
-of the English COPA dataset (https://people.ict.usc.edu/~gordon/copa.html) by following the 
-XCOPA dataset translation methodology (https://arxiv.org/abs/2005.00333). The dataset consists of 1000 premises 
-(My body cast a shadow over the grass), each given a question (What is the cause?), and two choices 
-(The sun was rising; The grass was cut), with a label encoding which of the choices is more plausible 
-given the annotator or translator (The sun was rising).
-
-The dataset is split into 400 training samples, 100 validation samples, and 500 test samples. It includes the 
-following features: 'premise', 'choice1', 'choice2', 'label', 'question', 'changed' (boolean).
-"""
-_HOMEPAGE = 'https://www.clarin.si/repository/xmlui/handle/11356/1404'
-_LICENSE = ''
-
-_URL = 'https://huggingface.co/datasets/classla/copa_hr/raw/main/data.zip'
-_TRAINING_FILE = 'train.jsonl'
-_DEV_FILE = 'val.jsonl'
-_TEST_FILE = 'test.jsonl'
-
-
-class CopaHr(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version('1.0.0')
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name='copa_hr',
-            version=VERSION,
-            description=''
-        )
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                'premise': datasets.Value('string'),
-                'choice1': datasets.Value('string'),
-                'choice2': datasets.Value('string'),
-                'label': datasets.features.ClassLabel(names=['0', '1']),
-                'question': datasets.Value('string'),
-                'idx': datasets.Value('int64'),
-                'changed': datasets.Value('bool')
-            }
-        )
-
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        data_dir = dl_manager.download_and_extract(_URL)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN, gen_kwargs={
-                    'filepath': os.path.join(data_dir, _TRAINING_FILE),
-                    'split': 'train'}
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION, gen_kwargs={
-                    'filepath': os.path.join(data_dir, _DEV_FILE),
-                    'split': 'dev'}
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST, gen_kwargs={
-                    'filepath': os.path.join(data_dir, _TEST_FILE),
-                    'split': 'test'}
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        with open(filepath, encoding='utf-8') as f:
-            for i, line in enumerate(f):
-                data = json.loads(line)
-                yield i, {
-                    'premise': data['premise'],
-                    'choice1': data['choice1'],
-                    'choice2': data['choice2'],
-                    'question': data['question'],
-                    'label': str(data['label']),
-                    'idx': data['idx'],
-                    'changed': data['changed']
-                }