Update files from the datasets library (from 1.2.0)

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

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README.md

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+---
+annotations_creators:
+- found
+language_creators:
+- found
+languages:
+- tr
+licenses:
+- found
+multilinguality:
+- monolingual
+size_categories:
+- 10k<n<100k
+source_datasets:
+- original
+task_categories:
+- text_classification
+task_ids:
+- text-classification-other-offensive-language-classification
+---
+
+# Dataset Card for OffensEval-TR 2020
+
+## 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:** [offensive-turkish](https://coltekin.github.io/offensive-turkish/)
+- **Paper:** [A Corpus of Turkish Offensive Language on Social Media](https://coltekin.github.io/offensive-turkish/troff.pdf)
+- **Point of Contact:** [Çağrı Çöltekin](ccoltekin@sfs.uni-tuebingen.de)
+
+### Dataset Summary
+
+The file offenseval-tr-training-v1.tsv contains 31,756 annotated tweets. 
+
+The file offenseval-annotation.txt contains a short summary of the annotation guidelines.
+
+Twitter user mentions were substituted by @USER and URLs have been substitute by URL.
+
+Each instance contains up to 1 labels corresponding to one of the following sub-task:
+
+- Sub-task A: Offensive language identification; 
+
+### Supported Tasks and Leaderboards
+
+The dataset was published on this [paper](https://coltekin.github.io/offensive-turkish/troff.pdf). 
+
+### Languages
+
+The dataset is based on Turkish.
+
+## Dataset Structure
+
+### Data Instances
+
+A binary dataset with with (NOT) Not Offensive and (OFF) Offensive tweets.  
+
+### Data Fields
+
+Instances are included in TSV format as follows:
+
+ID	INSTANCE	SUBA
+
+The column names in the file are the following:
+
+id	tweet	subtask_a
+
+The labels used in the annotation are listed below.
+
+#### Task and Labels
+
+(A) Sub-task A: Offensive language identification
+
+- (NOT) Not Offensive - This post does not contain offense or profanity.
+- (OFF) Offensive - This post contains offensive language or a targeted (veiled or direct) offense
+
+In our annotation, we label a post as offensive (OFF) if it contains any form of non-acceptable language (profanity) or a targeted offense, which can be veiled or direct. 
+
+### Data Splits
+
+| Tain  | Test  | 
+|-------| ----- | 
+| 31756 | 3528  | 
+
+## 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?
+
+From tweeter.  
+
+### Annotations
+
+[More Information Needed]
+
+#### Annotation process
+
+We describe the labels above in a “flat” manner. However, the annotation process we follow is hierarchical. The following QA pairs give a more flowchart-like procedure to follow
+
+1. Is the tweet in Turkish and understandable?
+    * No: mark tweet X for exclusion, and go to next tweet
+    * Yes: continue to step 2
+2. Is the tweet include offensive/inappropriate language?
+    * No: mark the tweet non go to step 4
+    * Yes: continue to step 3
+3. Is the offense in the tweet targeted?
+    * No: mark the tweet prof go to step 4
+    * Yes: chose one (or more) of grp, ind, *oth based on the definitions above. Please try to limit the number of labels unless it is clear that the tweet includes offense against multiple categories.
+4. Was the labeling decision difficult (precise answer needs more context, tweets includes irony, or for another reason)?
+    * No: go to next tweet
+    * Yes: add the label X, go to next tweet
+
+
+#### 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
+
+The annotations are distributed under the terms of [Creative Commons Attribution License (CC-BY)](https://creativecommons.org/licenses/by/2.0/). Please cite the following paper, if you use this resource.
+
+### Citation Information
+
+```
+@inproceedings{coltekin2020lrec,
+ author  = {\c{C}\"{o}ltekin, \c{C}a\u{g}r{\i}},
+ year  = {2020},
+ title  = {A Corpus of Turkish Offensive Language on Social Media},
+ booktitle  = {Proceedings of The 12th Language Resources and Evaluation Conference},
+ pages  = {6174--6184},
+ address  = {Marseille, France},
+ url  = {https://www.aclweb.org/anthology/2020.lrec-1.758},
+}
+```

dataset_infos.json

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+{"offenseval2020-turkish": {"description": "OffensEval-TR 2020 is a Turkish offensive language corpus. The corpus consist of randomly sampled tweets, and annotated in a similar way to OffensEval and GermEval.\n", "citation": "@InProceedings{coltekin2020lrec,\n author  = {Cagri Coltekin},\n year  = {2020},\n title  = {A Corpus of Turkish Offensive Language on Social Media},\n booktitle  = {Proceedings of The 12th Language Resources and Evaluation Conference},\n pages  = {6174--6184},\n address  = {Marseille, France},\n url  = {https://www.aclweb.org/anthology/2020.lrec-1.758},\n}\n", "homepage": "https://coltekin.github.io/offensive-turkish/", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "tweet": {"dtype": "string", "id": null, "_type": "Value"}, "subtask_a": {"num_classes": 2, "names": ["NOT", "OFF"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "offenseval2020_tr", "config_name": "offenseval2020-turkish", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4260505, "num_examples": 31756, "dataset_name": "offenseval2020_tr"}, "test": {"name": "test", "num_bytes": 481300, "num_examples": 3528, "dataset_name": "offenseval2020_tr"}}, "download_checksums": {"https://coltekin.github.io/offensive-turkish/offenseval2020-turkish.zip": {"num_bytes": 2048258, "checksum": "7977e96255dbc9b8d14893f1b14cbe3dec53c70358503c062c5a59720ec9c2f2"}}, "download_size": 2048258, "post_processing_size": null, "dataset_size": 4741805, "size_in_bytes": 6790063}}

dummy/offenseval2020-turkish/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f47aafe795c5fbc6229c5a26875452278fc094123e6047c0bf88e26a3a692519
+size 3715

offenseval2020_tr.py

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+# coding=utf-8
+# Lint as: python3
+"""OffensEval-TR 2020: A Corpus of Turkish Offensive Language on Social Media"""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+import logging
+import os
+
+import datasets
+
+
+_CITATION = """\
+@InProceedings{coltekin2020lrec,
+ author  = {Cagri Coltekin},
+ year  = {2020},
+ title  = {A Corpus of Turkish Offensive Language on Social Media},
+ booktitle  = {Proceedings of The 12th Language Resources and Evaluation Conference},
+ pages  = {6174--6184},
+ address  = {Marseille, France},
+ url  = {https://www.aclweb.org/anthology/2020.lrec-1.758},
+}
+"""
+
+
+_DESCRIPTION = """\
+OffensEval-TR 2020 is a Turkish offensive language corpus. The corpus consist of randomly sampled tweets and annotated in a similar way to OffensEval and GermEval.
+"""
+
+_HOMEPAGE = "https://coltekin.github.io/offensive-turkish/"
+_DOWNLOAD_URL = "https://coltekin.github.io/offensive-turkish/offenseval2020-turkish.zip"
+_FOLDER_NAME = "offenseval-tr-{split}-v1"
+
+
+class OffensEval2020TRConfig(datasets.BuilderConfig):
+    """BuilderConfig for OffensEval2020TR."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for OffensEval2020TR.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(OffensEval2020TRConfig, self).__init__(**kwargs)
+
+
+class Offenseval2020TR(datasets.GeneratorBasedBuilder):
+    """OffensEval-TR 2020: A Corpus of Turkish Offensive Language on Social Media"""
+
+    BUILDER_CONFIGS = [
+        OffensEval2020TRConfig(
+            name="offenseval2020-turkish",
+            version=datasets.Version("1.0.0"),
+            description="OffensEval-TR 2020: A Corpus of Turkish Offensive Language on Social Media",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("int32"),
+                    "tweet": datasets.Value("string"),
+                    "subtask_a": datasets.features.ClassLabel(names=["NOT", "OFF"]),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
+        data_dir = os.path.join(dl_dir, self.config.name)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir, _FOLDER_NAME.format(split="training"), "offenseval-tr-training-v1.tsv"
+                    ),
+                    "labelpath": None,
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir, _FOLDER_NAME.format(split="testset"), "offenseval-tr-testset-v1.tsv"
+                    ),
+                    "labelpath": os.path.join(
+                        data_dir, _FOLDER_NAME.format(split="testset"), "offenseval-tr-labela-v1.tsv"
+                    ),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, labelpath):
+        """Generate OffensEval2020TR examples."""
+        logging.info("⏳ Generating examples from = %s", filepath)
+
+        if labelpath:
+            with open(filepath, encoding="utf-8") as f:
+                with open(labelpath, encoding="utf-8") as f2:
+                    reader_testset = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+                    reader_label = csv.DictReader(
+                        f2, delimiter=",", quoting=csv.QUOTE_NONE, fieldnames=["id", "subtask_a"]
+                    )
+                    list_label = list(reader_label)
+                    for idx, row in enumerate(reader_testset):
+                        row_label = list_label[idx]
+                        yield idx, {"id": row["id"], "tweet": row["tweet"], "subtask_a": row_label["subtask_a"]}
+        else:
+            with open(filepath, encoding="utf-8") as f:
+                reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+                for idx, row in enumerate(reader):
+                    yield idx, {"id": row["id"], "tweet": row["tweet"], "subtask_a": row["subtask_a"]}