Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Languages:
Polish
Size:
10K - 100K
License:
Commit
•
71593d1
1
Parent(s):
640d5c0
Convert dataset to Parquet (#2)
Browse files- Convert dataset to Parquet (c88016b48a09dd53b4cd8354227dd3e632903239)
- Delete loading script (58d2590115fd2507987be352c2eff5f2ee311f0a)
- Delete legacy dataset_infos.json (8dab326df9f464781ecc5bf77b00291fa0b76481)
- README.md +14 -5
- allegro_reviews.py +0 -109
- data/test-00000-of-00001.parquet +3 -0
- data/train-00000-of-00001.parquet +3 -0
- data/validation-00000-of-00001.parquet +3 -0
- dataset_infos.json +0 -1
README.md
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dtype: float32
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splits:
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- name: train
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num_bytes:
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num_examples: 9577
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- name: test
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num_bytes:
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num_examples: 1006
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- name: validation
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num_bytes:
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num_examples: 1002
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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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dtype: float32
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splits:
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- name: train
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+
num_bytes: 4899535
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num_examples: 9577
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- name: test
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num_bytes: 514523
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num_examples: 1006
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- name: validation
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num_bytes: 515781
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num_examples: 1002
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download_size: 3923657
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dataset_size: 5929839
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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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- split: validation
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path: data/validation-*
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---
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# Dataset Card for [Dataset Name]
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allegro_reviews.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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"""Allegro Reviews dataset"""
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import csv
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import os
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import datasets
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_CITATION = """\
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@inproceedings{rybak-etal-2020-klej,
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title = "{KLEJ}: Comprehensive Benchmark for Polish Language Understanding",
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author = "Rybak, Piotr and Mroczkowski, Robert and Tracz, Janusz and Gawlik, Ireneusz",
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booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
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month = jul,
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year = "2020",
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address = "Online",
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publisher = "Association for Computational Linguistics",
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url = "https://www.aclweb.org/anthology/2020.acl-main.111",
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pages = "1191--1201",
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}
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"""
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_DESCRIPTION = """\
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Allegro Reviews is a sentiment analysis dataset, consisting of 11,588 product reviews written in Polish and extracted
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from Allegro.pl - a popular e-commerce marketplace. Each review contains at least 50 words and has a rating on a scale
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from one (negative review) to five (positive review).
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We recommend using the provided train/dev/test split. The ratings for the test set reviews are kept hidden.
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You can evaluate your model using the online evaluation tool available on klejbenchmark.com.
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"""
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_HOMEPAGE = "https://github.com/allegro/klejbenchmark-allegroreviews"
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_LICENSE = "CC BY-SA 4.0"
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_URLs = "https://klejbenchmark.com/static/data/klej_ar.zip"
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class AllegroReviews(datasets.GeneratorBasedBuilder):
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"""
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Allegro Reviews is a sentiment analysis dataset, consisting of 11,588 product reviews written in Polish
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and extracted from Allegro.pl - a popular e-commerce marketplace.
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"""
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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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"text": datasets.Value("string"),
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"rating": datasets.Value("float"),
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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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)
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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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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"filepath": os.path.join(data_dir, "dev.tsv"),
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"split": "dev",
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},
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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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"text": row["text"],
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"rating": "-1" if split == "test" else row["rating"],
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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 sha256:5586790a8ab19ab5a01f54572553303216b6d58b3627bbb8dbcd1731ce9a982b
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size 349137
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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 sha256:647cde0312a6f659fdc3d4942f595b3c058e560fc298bd3fc91736e48a1bb8c7
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size 3225749
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data/validation-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:013fb16adbebebc0546a0459868303a216542aaea1c07696e5a66fedd272f03e
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size 348771
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dataset_infos.json
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{"default": {"description": "Allegro Reviews is a sentiment analysis dataset, consisting of 11,588 product reviews written in Polish and extracted \nfrom Allegro.pl - a popular e-commerce marketplace. Each review contains at least 50 words and has a rating on a scale \nfrom one (negative review) to five (positive review).\n\nWe recommend using the provided train/dev/test split. The ratings for the test set reviews are kept hidden. \nYou can evaluate your model using the online evaluation tool available on klejbenchmark.com.\n", "citation": "@inproceedings{rybak-etal-2020-klej,\n title = \"{KLEJ}: Comprehensive Benchmark for Polish Language Understanding\",\n author = \"Rybak, Piotr and Mroczkowski, Robert and Tracz, Janusz and Gawlik, Ireneusz\",\n booktitle = \"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics\",\n month = jul,\n year = \"2020\",\n address = \"Online\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/2020.acl-main.111\",\n pages = \"1191--1201\",\n}\n", "homepage": "https://github.com/allegro/klejbenchmark-allegroreviews", "license": "CC BY-SA 4.0", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "rating": {"dtype": "float32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "allegro_reviews", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4899539, "num_examples": 9577, "dataset_name": "allegro_reviews"}, "test": {"name": "test", "num_bytes": 514527, "num_examples": 1006, "dataset_name": "allegro_reviews"}, "validation": {"name": "validation", "num_bytes": 515785, "num_examples": 1002, "dataset_name": "allegro_reviews"}}, "download_checksums": {"https://klejbenchmark.com/static/data/klej_ar.zip": {"num_bytes": 2314847, "checksum": "7c74bdb440e15c36b0a66f32500decd86f29380fc42b28752f1335de143a99fc"}}, "download_size": 2314847, "post_processing_size": null, "dataset_size": 5929851, "size_in_bytes": 8244698}}
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