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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+*.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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+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- found
+languages:
+- pt
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 1k<n<10K
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- text-classification-other-hate-speech-detection
+---
+
+# 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://github.com/paulafortuna/Portuguese-Hate-Speech-Dataset
+- **Repository:** https://github.com/paulafortuna/Portuguese-Hate-Speech-Dataset
+- **Paper:** https://www.aclweb.org/anthology/W19-3510/
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+Portuguese dataset for hate speech detection composed of 5,668 tweets with binary annotations (i.e. 'hate' vs. 'no-hate').
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### 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
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

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+{"default": {"description": "Portuguese dataset for hate speech detection composed of 5,668 tweets with binary annotations (i.e. 'hate' vs. 'no-hate').\n", "citation": "@inproceedings{fortuna-etal-2019-hierarchically,\ntitle = \"A Hierarchically-Labeled {P}ortuguese Hate Speech Dataset\",\nauthor = \"Fortuna, Paula  and\n    Rocha da Silva, Jo{\\~a}o  and\n    Soler-Company, Juan  and\n    Wanner, Leo  and\n    Nunes, S{'e}rgio\",\nbooktitle = \"Proceedings of the Third Workshop on Abusive Language Online\",\nmonth = aug,\nyear = \"2019\",\naddress = \"Florence, Italy\",\npublisher = \"Association for Computational Linguistics\",\nurl = \"https://www.aclweb.org/anthology/W19-3510\",\ndoi = \"10.18653/v1/W19-3510\",\npages = \"94--104\",\nabstract = \"Over the past years, the amount of online offensive speech has been growing steadily. To successfully cope with it, machine learning are applied. However, ML-based techniques require sufficiently large annotated datasets. In the last years, different datasets were published, mainly for English. In this paper, we present a new dataset for Portuguese, which has not been in focus so far. The dataset is composed of 5,668 tweets. For its annotation, we defined two different schemes used by annotators with different levels of expertise. Firstly, non-experts annotated the tweets with binary labels ({`}hate{'} vs. {`}no-hate{'}). Secondly, expert annotators classified the tweets following a fine-grained hierarchical multiple label scheme with 81 hate speech categories in total. The inter-annotator agreement varied from category to category, which reflects the insight that some types of hate speech are more subtle than others and that their detection depends on personal perception. This hierarchical annotation scheme is the main contribution of the presented work, as it facilitates the identification of different types of hate speech and their intersections. To demonstrate the usefulness of our dataset, we carried a baseline classification experiment with pre-trained word embeddings and LSTM on the binary classified data, with a state-of-the-art outcome.\",\n}\n", "homepage": "https://github.com/paulafortuna/Portuguese-Hate-Speech-Dataset", "license": "Unknown", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["no-hate", "hate"], "names_file": null, "id": null, "_type": "ClassLabel"}, "hatespeech_G1": {"dtype": "string", "id": null, "_type": "Value"}, "annotator_G1": {"dtype": "string", "id": null, "_type": "Value"}, "hatespeech_G2": {"dtype": "string", "id": null, "_type": "Value"}, "annotator_G2": {"dtype": "string", "id": null, "_type": "Value"}, "hatespeech_G3": {"dtype": "string", "id": null, "_type": "Value"}, "annotator_G3": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "hate_speech_portuguese", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 826130, "num_examples": 5670, "dataset_name": "hate_speech_portuguese"}}, "download_checksums": {"https://github.com/paulafortuna/Portuguese-Hate-Speech-Dataset/raw/master/2019-05-28_portuguese_hate_speech_binary_classification.csv": {"num_bytes": 763846, "checksum": "dc2370fc58a127a17d24ce2277c42f457b92b6b4270a07a90708912f9b2d3999"}}, "download_size": 763846, "post_processing_size": null, "dataset_size": 826130, "size_in_bytes": 1589976}}

dummy/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:469afb742c43cb891a7cdc76be30032130f120256f6eca0f6ec256b92b5c5f03
+size 686

hate_speech_portuguese.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.
+"""Portuguese dataset for hate speech detection composed of 5,668 tweets with binary annotations (i.e. 'hate' vs. 'no-hate')."""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+
+import datasets
+
+
+_CITATION = """\
+@inproceedings{fortuna-etal-2019-hierarchically,
+title = "A Hierarchically-Labeled {P}ortuguese Hate Speech Dataset",
+author = "Fortuna, Paula  and
+    Rocha da Silva, Jo{\\~a}o  and
+    Soler-Company, Juan  and
+    Wanner, Leo  and
+    Nunes, S{\'e}rgio",
+booktitle = "Proceedings of the Third Workshop on Abusive Language Online",
+month = aug,
+year = "2019",
+address = "Florence, Italy",
+publisher = "Association for Computational Linguistics",
+url = "https://www.aclweb.org/anthology/W19-3510",
+doi = "10.18653/v1/W19-3510",
+pages = "94--104",
+abstract = "Over the past years, the amount of online offensive speech has been growing steadily. To successfully cope with it, machine learning are applied. However, ML-based techniques require sufficiently large annotated datasets. In the last years, different datasets were published, mainly for English. In this paper, we present a new dataset for Portuguese, which has not been in focus so far. The dataset is composed of 5,668 tweets. For its annotation, we defined two different schemes used by annotators with different levels of expertise. Firstly, non-experts annotated the tweets with binary labels ({`}hate{'} vs. {`}no-hate{'}). Secondly, expert annotators classified the tweets following a fine-grained hierarchical multiple label scheme with 81 hate speech categories in total. The inter-annotator agreement varied from category to category, which reflects the insight that some types of hate speech are more subtle than others and that their detection depends on personal perception. This hierarchical annotation scheme is the main contribution of the presented work, as it facilitates the identification of different types of hate speech and their intersections. To demonstrate the usefulness of our dataset, we carried a baseline classification experiment with pre-trained word embeddings and LSTM on the binary classified data, with a state-of-the-art outcome.",
+}
+"""
+
+_DESCRIPTION = """\
+Portuguese dataset for hate speech detection composed of 5,668 tweets with binary annotations (i.e. 'hate' vs. 'no-hate').
+"""
+
+_HOMEPAGE = "https://github.com/paulafortuna/Portuguese-Hate-Speech-Dataset"
+
+_LICENSE = "Unknown"
+
+_URL = "https://github.com/paulafortuna/Portuguese-Hate-Speech-Dataset/raw/master/2019-05-28_portuguese_hate_speech_binary_classification.csv"
+
+
+class HateSpeechPortuguese(datasets.GeneratorBasedBuilder):
+    """Portuguese dataset for hate speech detection composed of 5,668 tweets with binary annotations (i.e. 'hate' vs. 'no-hate')."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "label": datasets.ClassLabel(names=["no-hate", "hate"]),
+                    "hatespeech_G1": datasets.Value("string"),
+                    "annotator_G1": datasets.Value("string"),
+                    "hatespeech_G2": datasets.Value("string"),
+                    "annotator_G2": datasets.Value("string"),
+                    "hatespeech_G3": datasets.Value("string"),
+                    "annotator_G3": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=("text", "label"),
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        data_file = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_file,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """ Yields examples. """
+
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.reader(f)
+            for id_, row in enumerate(reader):
+                if id_ == 0:
+                    continue
+
+                yield id_, {
+                    "text": row[0],
+                    "label": "hate" if row[1] == "1" else "no-hate",
+                    "hatespeech_G1": row[2],
+                    "annotator_G1": row[3],
+                    "hatespeech_G2": row[4],
+                    "annotator_G2": row[5],
+                    "hatespeech_G3": row[6],
+                    "annotator_G3": row[7],
+                }