Update files from the datasets library (from 1.2.0)

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

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
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+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- found
+language_creators:
+- found
+languages:
+- pl
+licenses:
+- cc-by-sa-4-0
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- text-scoring
+task_ids:
+- sentiment-scoring
+---
+
+# Dataset Card for [Dataset Name]
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [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)
+
+## 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",
+}

allegro_reviews.py

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+# 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"""
+
+from __future__ import absolute_import, division, print_function
+
+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}}

dummy/1.1.0/dummy_data.zip

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