Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
Polish
Size:
10K - 100K
License:
Commit
•
6c872f5
1
Parent(s):
48c46ba
Convert dataset to Parquet (#4)
Browse files- Convert dataset to Parquet (a8dfb46337013e95a777c466bf3691e03a8dcd3a)
- Delete loading script (7725d1e38abfdad8612d5fed0b8b7de9282fc293)
- README.md +11 -4
- cdt.py +0 -93
- data/test-00000-of-00001.parquet +3 -0
- data/train-00000-of-00001.parquet +3 -0
README.md
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'1': '1'
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splits:
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- name: train
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num_bytes:
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num_examples: 10041
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- name: test
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num_bytes:
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num_examples: 1000
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download_size:
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dataset_size:
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---
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# Dataset Card for [Dataset Name]
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'1': '1'
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splits:
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- name: train
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num_bytes: 1104314
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num_examples: 10041
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- name: test
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num_bytes: 109677
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num_examples: 1000
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download_size: 649329
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dataset_size: 1213991
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: test
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path: data/test-*
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---
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# Dataset Card for [Dataset Name]
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cdt.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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"""Cyberbullying detection task"""
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import csv
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import os
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import datasets
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from datasets.tasks import TextClassification
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_CITATION = """\
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@article{ptaszynski2019results,
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title={Results of the PolEval 2019 Shared Task 6: First Dataset and Open Shared Task for Automatic Cyberbullying Detection in Polish Twitter},
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author={Ptaszynski, Michal and Pieciukiewicz, Agata and Dybala, Pawel},
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journal={Proceedings of the PolEval 2019 Workshop},
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publisher={Institute of Computer Science, Polish Academy of Sciences},
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pages={89},
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year={2019}
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}
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"""
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_DESCRIPTION = """\
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The Cyberbullying Detection task was part of 2019 edition of PolEval competition. The goal is to predict if a given Twitter message contains a cyberbullying (harmful) content.
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"""
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_HOMEPAGE = "https://github.com/ptaszynski/cyberbullying-Polish"
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_LICENSE = "BSD 3-Clause"
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_URLs = "https://klejbenchmark.com/static/data/klej_cbd.zip"
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class Cdt(datasets.GeneratorBasedBuilder):
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"""CyberbullyingDetectionTask"""
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VERSION = datasets.Version("1.1.0")
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"sentence": datasets.Value("string"),
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"target": datasets.ClassLabel(names=["0", "1"]),
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}
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),
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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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task_templates=[TextClassification(text_column="sentence", label_column="target")],
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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data_dir = dl_manager.download_and_extract(_URLs)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": os.path.join(data_dir, "train.tsv"),
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"split": "train",
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={"filepath": os.path.join(data_dir, "test_features.tsv"), "split": "test"},
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),
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]
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def _generate_examples(self, filepath, split):
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"""Yields examples."""
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with open(filepath, encoding="utf-8") as f:
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reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
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for id_, row in enumerate(reader):
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yield id_, {
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"sentence": row["sentence"],
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"target": -1 if split == "test" else row["target"],
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}
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data/test-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:98d4043c942922e64089ee37cc5201e773e221bbda7a73dbcb8cad94e0ad0a92
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size 59007
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data/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:9f546b7a806eba3d31d88b0be0c93049a393e8baed75821144583b2ed116e047
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size 590322
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