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README.md

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----
-annotations_creators:
-- found
-language_creators:
-- found
-language:
-- pl
-license:
-- cc-by-sa-4.0
-multilinguality:
-- monolingual
-size_categories:
-- 10K<n<100K
-source_datasets:
-- original
-task_categories:
-- text-classification
-task_ids:
-- sentiment-scoring
-- text-scoring
-paperswithcode_id: allegro-reviews
-pretty_name: Allegro Reviews
-dataset_info:
-  features:
-  - name: text
-    dtype: string
-  - name: rating
-    dtype: float32
-  splits:
-  - name: train
-    num_bytes: 4899539
-    num_examples: 9577
-  - name: test
-    num_bytes: 514527
-    num_examples: 1006
-  - name: validation
-    num_bytes: 515785
-    num_examples: 1002
-  download_size: 2314847
-  dataset_size: 5929851
----
-
-# Dataset Card for [Dataset Name]
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:**
-https://klejbenchmark.com/
-- **Repository:**
-https://github.com/allegro/klejbenchmark-allegroreviews
-- **Paper:**
-KLEJ: Comprehensive Benchmark for Polish Language Understanding (Rybak, Piotr and Mroczkowski, Robert and Tracz, Janusz and Gawlik, Ireneusz)
-- **Leaderboard:**
-https://klejbenchmark.com/leaderboard/
-- **Point of Contact:**
-[email protected]
-
-### Dataset Summary
-
-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).
-
-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.
-
-### Supported Tasks and Leaderboards
-
-Product reviews sentiment analysis.
-https://klejbenchmark.com/leaderboard/
-
-### Languages
-
-Polish
-
-## Dataset Structure
-
-### Data Instances
-
-Two tsv files (train, dev) with two columns (text, rating) and one (test) with just one (text). 
-
-### Data Fields
-
-- text: a product review of at least 50 words
-- rating: product rating of a scale of one (negative review) to five (positive review)
-
-### Data Splits
-
-Data is splitted in train/dev/test split.
-
-## Dataset Creation
-
-### Curation Rationale
-
-This dataset is one of nine evaluation tasks to improve polish language processing.
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-The Allegro Reviews is a set of product reviews from a popular e-commerce marketplace (Allegro.pl).
-
-#### Who are the source language producers?
-
-Customers of an e-commerce marketplace.
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-[More Information Needed]
-
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
-
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
-
-[More Information Needed]
-
-## Additional Information
-
-### Dataset Curators
-
-Allegro Machine Learning Research team [email protected]
-
-### Licensing Information
-
-Dataset licensed under CC BY-SA 4.0
-
-### Citation Information
-
-@inproceedings{rybak-etal-2020-klej,
-    title = "{KLEJ}: Comprehensive Benchmark for Polish Language Understanding",
-    author = "Rybak, Piotr and Mroczkowski, Robert and Tracz, Janusz and Gawlik, Ireneusz",
-    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
-    month = jul,
-    year = "2020",
-    address = "Online",
-    publisher = "Association for Computational Linguistics",
-    url = "https://www.aclweb.org/anthology/2020.acl-main.111",
-    pages = "1191--1201",
-}
-
-### Contributions
-
-Thanks to [@abecadel](https://github.com/abecadel) for adding this dataset.

allegro_reviews.py

@@ -1,109 +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.
-"""Allegro Reviews dataset"""
-
-
-import csv
-import os
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{rybak-etal-2020-klej,
-    title = "{KLEJ}: Comprehensive Benchmark for Polish Language Understanding",
-    author = "Rybak, Piotr and Mroczkowski, Robert and Tracz, Janusz and Gawlik, Ireneusz",
-    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
-    month = jul,
-    year = "2020",
-    address = "Online",
-    publisher = "Association for Computational Linguistics",
-    url = "https://www.aclweb.org/anthology/2020.acl-main.111",
-    pages = "1191--1201",
-}
-"""
-
-_DESCRIPTION = """\
-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).
-
-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.
-"""
-
-_HOMEPAGE = "https://github.com/allegro/klejbenchmark-allegroreviews"
-
-_LICENSE = "CC BY-SA 4.0"
-
-_URLs = "https://klejbenchmark.com/static/data/klej_ar.zip"
-
-
-class AllegroReviews(datasets.GeneratorBasedBuilder):
-    """
-    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.
-    """
-
-    VERSION = datasets.Version("1.1.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "rating": datasets.Value("float"),
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        data_dir = dl_manager.download_and_extract(_URLs)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "train.tsv"),
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepath": os.path.join(data_dir, "test_features.tsv"), "split": "test"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "dev.tsv"),
-                    "split": "dev",
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        """Yields examples."""
-        with open(filepath, encoding="utf-8") as f:
-            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
-            for id_, row in enumerate(reader):
-                yield id_, {
-                    "text": row["text"],
-                    "rating": "-1" if split == "test" else row["rating"],
-                }

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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