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Update files from the datasets library (from 1.2.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

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README.md ADDED
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+ ---
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+ annotations_creators:
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+ - found
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+ language_creators:
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+ - found
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+ languages:
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+ - pl
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+ licenses:
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+ - cc-by-sa-4-0
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+ multilinguality:
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+ - monolingual
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+ size_categories:
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+ - 10K<n<100K
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+ source_datasets:
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+ - original
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+ task_categories:
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+ - text-scoring
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+ task_ids:
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+ - sentiment-scoring
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+ ---
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+
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+ # Dataset Card for [Dataset Name]
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+
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+ ## Table of Contents
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks](#supported-tasks-and-leaderboards)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-instances)
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+ - [Data Splits](#data-instances)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
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+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:**
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+ https://klejbenchmark.com/
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+ - **Repository:**
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+ https://github.com/allegro/klejbenchmark-allegroreviews
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+ - **Paper:**
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+ KLEJ: Comprehensive Benchmark for Polish Language Understanding (Rybak, Piotr and Mroczkowski, Robert and Tracz, Janusz and Gawlik, Ireneusz)
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+ - **Leaderboard:**
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+ https://klejbenchmark.com/leaderboard/
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+ - **Point of Contact:**
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+ klejbenchmark@allegro.pl
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+
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+ ### Dataset Summary
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+
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+ Allegro Reviews is a sentiment analysis dataset, consisting of 11,588 product reviews written in Polish and extracted from Allegro.pl - a popular e-commerce marketplace. Each review contains at least 50 words and has a rating on a scale from one (negative review) to five (positive review).
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+
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+ We recommend using the provided train/dev/test split. The ratings for the test set reviews are kept hidden. You can evaluate your model using the online evaluation tool available on klejbenchmark.com.
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+
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+ ### Supported Tasks and Leaderboards
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+
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+ Product reviews sentiment analysis.
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+ https://klejbenchmark.com/leaderboard/
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+
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+ ### Languages
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+
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+ Polish
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ Two tsv files (train, dev) with two columns (text, rating) and one (test) with just one (text).
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+
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+ ### Data Fields
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+
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+ - text: a product review of at least 50 words
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+ - rating: product rating of a scale of one (negative review) to five (positive review)
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+
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+ ### Data Splits
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+
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+ Data is splitted in train/dev/test split.
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+
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+ ## Dataset Creation
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+
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+ ### Curation Rationale
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+
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+ This dataset is one of nine evaluation tasks to improve polish language processing.
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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+ The Allegro Reviews is a set of product reviews from a popular e-commerce marketplace (Allegro.pl).
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+
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+ #### Who are the source language producers?
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+
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+ Customers of an e-commerce marketplace.
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+
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+ ### Annotations
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+
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+ #### Annotation process
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+
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+ [More Information Needed]
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+
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+ #### Who are the annotators?
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+
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+ [More Information Needed]
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+
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+ ### Personal and Sensitive Information
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+
118
+ [More Information Needed]
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+
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+ ## Considerations for Using the Data
121
+
122
+ ### Social Impact of Dataset
123
+
124
+ [More Information Needed]
125
+
126
+ ### Discussion of Biases
127
+
128
+ [More Information Needed]
129
+
130
+ ### Other Known Limitations
131
+
132
+ [More Information Needed]
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+
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+ ## Additional Information
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+
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+ ### Dataset Curators
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+
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+ Allegro Machine Learning Research team klejbenchmark@allegro.pl
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+
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+ ### Licensing Information
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+
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+ Dataset licensed under CC BY-SA 4.0
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+
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+ ### Citation Information
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+
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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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+ }
allegro_reviews.py ADDED
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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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+
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+ from __future__ import absolute_import, division, print_function
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+
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+ import csv
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+ import os
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+
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+ import datasets
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+
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+
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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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+
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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
42
+ from one (negative review) to five (positive review).
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+
44
+ 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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+
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+ _HOMEPAGE = "https://github.com/allegro/klejbenchmark-allegroreviews"
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+
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+ _LICENSE = "CC BY-SA 4.0"
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+
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+ _URLs = "https://klejbenchmark.com/static/data/klej_ar.zip"
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+
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+
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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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+
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+ VERSION = datasets.Version("1.1.0")
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+
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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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+
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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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+
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+ def _generate_examples(self, filepath, split):
103
+ """ 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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+ }
dataset_infos.json ADDED
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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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