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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README.md

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+---
+annotations_creators:
+- found
+language_creators:
+- found
+languages:
+- ar
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 1k<n<10k
+source_datasets:
+- original
+task_categories:
+- text_classification
+task_ids:
+- emotion-classification
+---
+
+# Dataset Card for MetRec
+
+## 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)
+  - [Discussion of Social Impact and Biases](#discussion-of-social-impact-and-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:** [Homepage](https://github.com/AmrMehasseb/Emotional-Tone)
+- **Repository:** [Repository](https://github.com/AmrMehasseb/Emotional-Tone)
+- **Paper:** [Emotional Tone Detection in Arabic Tweets](https://www.researchgate.net/publication/328164296_Emotional_Tone_Detection_in_Arabic_Tweets_18th_International_Conference_CICLing_2017_Budapest_Hungary_April_17-23_2017_Revised_Selected_Papers_Part_II)
+- **Point of Contact:** [Amr Al-Khatib](https://github.com/AmrMehasseb)
+
+### Dataset Summary
+
+Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+The dataset is based on Arabic.
+
+## Dataset Structure
+
+### Data Instances
+
+example: 
+```
+    >>> {'label': 0, 'tweet': 'الاوليمبياد الجايه هكون لسه ف الكليه ..'}
+```
+
+### Data Fields
+
+- "tweet": plain text tweet in Arabic
+
+- "label": emotion class label
+
+the dataset distribution and balance for each class looks like the following
+
+|label||Label description |  Count    |
+|---------|---------|  -------  | 
+|0        |none     |   1550    |
+|1        |anger    |   1444    |
+|2        |joy      |   1281    |
+|3        |sadness  |   1256    |
+|4        |love     |   1220    |
+|5        |sympathy |   1062    |
+|6        |surprise |   1045    |
+|7        |fear     |   1207    |
+
+### Data Splits
+
+The dataset is not split. 
+
+|           | Tain   | 
+|---------- | ------ | 
+|no split   | 10,065  | 
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+[More Information Needed]
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### 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
+
+### Discussion of Social Impact and Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+@inbook{inbook,
+author = {Al-Khatib, Amr and El-Beltagy, Samhaa},
+year = {2018},
+month = {01},
+pages = {105-114},
+title = {Emotional Tone Detection in Arabic Tweets: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part II},
+isbn = {978-3-319-77115-1},
+doi = {10.1007/978-3-319-77116-8_8}
+}

dataset_infos.json

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+{"default": {"description": "Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text", "citation": "@inbook{inbook,\nauthor = {Al-Khatib, Amr and El-Beltagy, Samhaa},\nyear = {2018},\nmonth = {01},\npages = {105-114},\ntitle = {Emotional Tone Detection in Arabic Tweets: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17\u201323, 2017, Revised Selected Papers, Part II},\nisbn = {978-3-319-77115-1},\ndoi = {10.1007/978-3-319-77116-8_8}\n}\n", "homepage": "https://github.com/AmrMehasseb/Emotional-Tone", "license": "", "features": {"tweet": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 8, "names": ["none", "anger", "joy", "sadness", "love", "sympathy", "surprise", "fear"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "emotone_ar", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1541746, "num_examples": 10065, "dataset_name": "emotone_ar"}}, "download_checksums": {"https://raw.githubusercontent.com/AmrMehasseb/Emotional-Tone/master/Emotional-Tone-Dataset.csv": {"num_bytes": 1563138, "checksum": "f799c5ee86ea407de33609f1bbf607369fc7610551fa073b9fc59cd211098715"}}, "download_size": 1563138, "post_processing_size": null, "dataset_size": 1541746, "size_in_bytes": 3104884}}

dummy/0.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8d9d07709203c482fd89834c8b5df75def0e339a2727976af4a0ab2634dfd058
+size 551

emotone_ar.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.
+"""Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text """
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+
+import datasets
+
+
+_CITATION = """\
+@inbook{inbook,
+author = {Al-Khatib, Amr and El-Beltagy, Samhaa},
+year = {2018},
+month = {01},
+pages = {105-114},
+title = {Emotional Tone Detection in Arabic Tweets: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part II},
+isbn = {978-3-319-77115-1},
+doi = {10.1007/978-3-319-77116-8_8}
+}
+"""
+
+
+_DESCRIPTION = """\
+Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text"""
+
+
+_HOMEPAGE = "https://github.com/AmrMehasseb/Emotional-Tone"
+
+
+_DOWNLOAD_URL = "https://raw.githubusercontent.com/AmrMehasseb/Emotional-Tone/master/Emotional-Tone-Dataset.csv"
+
+
+class EmotoneAr(datasets.GeneratorBasedBuilder):
+    """Dataset of 10065 tweets in Arabic for Emotions detection in Arabic text"""
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "tweet": datasets.Value("string"),
+                    "label": datasets.features.ClassLabel(
+                        names=["none", "anger", "joy", "sadness", "love", "sympathy", "surprise", "fear"]
+                    ),
+                }
+            ),
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir})]
+
+    def _generate_examples(self, filepath):
+        """Generate labeled arabic tweets examples for emoptions detection."""
+        with open(filepath, encoding="utf-8", mode="r") as csv_file:
+            next(csv_file)  # skip header
+            csv_reader = csv.reader(csv_file, quotechar='"', delimiter=",")
+
+            for id_, row in enumerate(csv_reader):
+                _, tweet, label = row
+                yield id_, {"tweet": tweet, "label": label}