system HF staff commited on
Commit
92c5f80
0 Parent(s):

Update files from the datasets library (from 1.2.0)

Browse files

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

.gitattributes ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ *.7z filter=lfs diff=lfs merge=lfs -text
2
+ *.arrow filter=lfs diff=lfs merge=lfs -text
3
+ *.bin filter=lfs diff=lfs merge=lfs -text
4
+ *.bin.* filter=lfs diff=lfs merge=lfs -text
5
+ *.bz2 filter=lfs diff=lfs merge=lfs -text
6
+ *.ftz filter=lfs diff=lfs merge=lfs -text
7
+ *.gz filter=lfs diff=lfs merge=lfs -text
8
+ *.h5 filter=lfs diff=lfs merge=lfs -text
9
+ *.joblib filter=lfs diff=lfs merge=lfs -text
10
+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
11
+ *.model filter=lfs diff=lfs merge=lfs -text
12
+ *.msgpack filter=lfs diff=lfs merge=lfs -text
13
+ *.onnx filter=lfs diff=lfs merge=lfs -text
14
+ *.ot filter=lfs diff=lfs merge=lfs -text
15
+ *.parquet filter=lfs diff=lfs merge=lfs -text
16
+ *.pb filter=lfs diff=lfs merge=lfs -text
17
+ *.pt filter=lfs diff=lfs merge=lfs -text
18
+ *.pth filter=lfs diff=lfs merge=lfs -text
19
+ *.rar filter=lfs diff=lfs merge=lfs -text
20
+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
21
+ *.tar.* filter=lfs diff=lfs merge=lfs -text
22
+ *.tflite filter=lfs diff=lfs merge=lfs -text
23
+ *.tgz filter=lfs diff=lfs merge=lfs -text
24
+ *.xz filter=lfs diff=lfs merge=lfs -text
25
+ *.zip filter=lfs diff=lfs merge=lfs -text
26
+ *.zstandard filter=lfs diff=lfs merge=lfs -text
27
+ *tfevents* filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,161 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ annotations_creators:
3
+ - found
4
+ language_creators:
5
+ - found
6
+ languages:
7
+ - pl
8
+ licenses:
9
+ - unknown
10
+ multilinguality:
11
+ - monolingual
12
+ size_categories:
13
+ - 10K<n<100K
14
+ source_datasets:
15
+ - original
16
+ task_categories:
17
+ - text-classification
18
+ task_ids:
19
+ - intent-classification
20
+ ---
21
+
22
+ # Dataset Card for Poleval 2019 cyberbullying
23
+
24
+ ## Table of Contents
25
+ - [Dataset Description](#dataset-description)
26
+ - [Dataset Summary](#dataset-summary)
27
+ - [Supported Tasks](#supported-tasks-and-leaderboards)
28
+ - [Languages](#languages)
29
+ - [Dataset Structure](#dataset-structure)
30
+ - [Data Instances](#data-instances)
31
+ - [Data Fields](#data-instances)
32
+ - [Data Splits](#data-instances)
33
+ - [Dataset Creation](#dataset-creation)
34
+ - [Curation Rationale](#curation-rationale)
35
+ - [Source Data](#source-data)
36
+ - [Annotations](#annotations)
37
+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
38
+ - [Considerations for Using the Data](#considerations-for-using-the-data)
39
+ - [Social Impact of Dataset](#social-impact-of-dataset)
40
+ - [Discussion of Biases](#discussion-of-biases)
41
+ - [Other Known Limitations](#other-known-limitations)
42
+ - [Additional Information](#additional-information)
43
+ - [Dataset Curators](#dataset-curators)
44
+ - [Licensing Information](#licensing-information)
45
+ - [Citation Information](#citation-information)
46
+
47
+ ## Dataset Description
48
+
49
+ - **Homepage:** http://2019.poleval.pl/index.php/tasks/task6
50
+ - **Repository:**
51
+ - **Paper:**
52
+ - **Leaderboard:**
53
+ - **Point of Contact:**
54
+
55
+ ### Dataset Summary
56
+
57
+ Task 6-1: Harmful vs non-harmful
58
+
59
+ In this task, the participants are to distinguish between normal/non-harmful tweets (class: 0) and tweets that contain any kind of harmful
60
+ information (class: 1). This includes cyberbullying, hate speech and related phenomena. The data for the task is available now and can be
61
+ downloaded from the link provided below.
62
+
63
+ Task 6-2: Type of harmfulness
64
+
65
+ In this task, the participants shall distinguish between three classes of tweets: 0 (non-harmful), 1 (cyberbullying), 2 (hate-speech). There
66
+ are various definitions of both cyberbullying and hate-speech, some of them even putting those two phenomena in the same group. The specific
67
+ conditions on which we based our annotations for both cyberbullying and hate-speech, which have been worked out during ten years of research
68
+ will be summarized in an introductory paper for the task, however, the main and definitive condition to distinguish the two is whether the
69
+ harmful action is addressed towards a private person(s) (cyberbullying), or a public person/entity/large group (hate-speech).
70
+
71
+ ### Supported Tasks and Leaderboards
72
+
73
+ [More Information Needed]
74
+
75
+ ### Languages
76
+
77
+ Polish
78
+
79
+ ## Dataset Structure
80
+
81
+ ### Data Instances
82
+
83
+ [More Information Needed]
84
+
85
+ ### Data Fields
86
+
87
+ - text: the provided tweet
88
+ - label: for task 6-1 the label can be 0 (non-harmful) or 1 (harmful)
89
+ for task 6-2 the label can be 0 (non-harmful), 1 (cyberbullying) or 2 (hate-speech)
90
+
91
+ ### Data Splits
92
+
93
+ Train and Test
94
+
95
+ ## Dataset Creation
96
+
97
+ ### Curation Rationale
98
+
99
+ [More Information Needed]
100
+
101
+ ### Source Data
102
+
103
+ #### Initial Data Collection and Normalization
104
+
105
+ [More Information Needed]
106
+
107
+ #### Who are the source language producers?
108
+
109
+ [More Information Needed]
110
+
111
+ ### Annotations
112
+
113
+ #### Annotation process
114
+
115
+ [More Information Needed]
116
+
117
+ #### Who are the annotators?
118
+
119
+ [More Information Needed]
120
+
121
+ ### Personal and Sensitive Information
122
+
123
+ [More Information Needed]
124
+
125
+ ## Considerations for Using the Data
126
+
127
+ ### Social Impact of Dataset
128
+
129
+ [More Information Needed]
130
+
131
+ ### Discussion of Biases
132
+
133
+ [More Information Needed]
134
+
135
+ ### Other Known Limitations
136
+
137
+ [More Information Needed]
138
+
139
+ ## Additional Information
140
+
141
+ ### Dataset Curators
142
+
143
+ [More Information Needed]
144
+
145
+ ### Licensing Information
146
+
147
+ [More Information Needed]
148
+
149
+ ### Citation Information
150
+
151
+ ```
152
+ @proceedings{ogr:kob:19:poleval,
153
+ editor = {Maciej Ogrodniczuk and Łukasz Kobyliński},
154
+ title = {{Proceedings of the PolEval 2019 Workshop}},
155
+ year = {2019},
156
+ address = {Warsaw, Poland},
157
+ publisher = {Institute of Computer Science, Polish Academy of Sciences},
158
+ url = {http://2019.poleval.pl/files/poleval2019.pdf},
159
+ isbn = "978-83-63159-28-3"}
160
+ }
161
+ ```
dataset_infos.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"task01": {"description": " In Task 6-1, the participants are to distinguish between normal/non-harmful tweets (class: 0) and tweets\n that contain any kind of harmful information (class: 1). This includes cyberbullying, hate speech and\n related phenomena.\n\n In Task 6-2, the participants shall distinguish between three classes of tweets: 0 (non-harmful),\n 1 (cyberbullying), 2 (hate-speech). There are various definitions of both cyberbullying and hate-speech,\n some of them even putting those two phenomena in the same group. The specific conditions on which we based\n our annotations for both cyberbullying and hate-speech, which have been worked out during ten years of research\n will be summarized in an introductory paper for the task, however, the main and definitive condition to 1\n distinguish the two is whether the harmful action is addressed towards a private person(s) (cyberbullying),\n or a public person/entity/large group (hate-speech).\n", "citation": "@proceedings{ogr:kob:19:poleval,\n editor = {Maciej Ogrodniczuk and \u0141ukasz Kobyli\u0144ski},\n title = {{Proceedings of the PolEval 2019 Workshop}},\n year = {2019},\n address = {Warsaw, Poland},\n publisher = {Institute of Computer Science, Polish Academy of Sciences},\n url = {http://2019.poleval.pl/files/poleval2019.pdf},\n isbn = \"978-83-63159-28-3\"}\n}\n", "homepage": "http://2019.poleval.pl/index.php/tasks/task6", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["0", "1"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "poleval2019_cyber_bullying", "config_name": "task01", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1104322, "num_examples": 10041, "dataset_name": "poleval2019_cyber_bullying"}, "test": {"name": "test", "num_bytes": 109681, "num_examples": 1000, "dataset_name": "poleval2019_cyber_bullying"}}, "download_checksums": {"http://2019.poleval.pl/task6/task_6-1.zip": {"num_bytes": 339950, "checksum": "8b71cb27bfcb3b503e80f8959be8485a53b777f288042d3dc1e8fb54c863c2a8"}, "http://2019.poleval.pl/task6/task6_test.zip": {"num_bytes": 70051, "checksum": "6acac459608b2d6da75f138740447b047c7bd3e0bbf562964845830a27a0b2f7"}}, "download_size": 410001, "post_processing_size": null, "dataset_size": 1214003, "size_in_bytes": 1624004}, "task02": {"description": " In Task 6-1, the participants are to distinguish between normal/non-harmful tweets (class: 0) and tweets\n that contain any kind of harmful information (class: 1). This includes cyberbullying, hate speech and\n related phenomena.\n\n In Task 6-2, the participants shall distinguish between three classes of tweets: 0 (non-harmful),\n 1 (cyberbullying), 2 (hate-speech). There are various definitions of both cyberbullying and hate-speech,\n some of them even putting those two phenomena in the same group. The specific conditions on which we based\n our annotations for both cyberbullying and hate-speech, which have been worked out during ten years of research\n will be summarized in an introductory paper for the task, however, the main and definitive condition to 1\n distinguish the two is whether the harmful action is addressed towards a private person(s) (cyberbullying),\n or a public person/entity/large group (hate-speech).\n", "citation": "@proceedings{ogr:kob:19:poleval,\n editor = {Maciej Ogrodniczuk and \u0141ukasz Kobyli\u0144ski},\n title = {{Proceedings of the PolEval 2019 Workshop}},\n year = {2019},\n address = {Warsaw, Poland},\n publisher = {Institute of Computer Science, Polish Academy of Sciences},\n url = {http://2019.poleval.pl/files/poleval2019.pdf},\n isbn = \"978-83-63159-28-3\"}\n}\n", "homepage": "http://2019.poleval.pl/index.php/tasks/task6", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["0", "1", "2"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": {"input": "text", "output": "label"}, "builder_name": "poleval2019_cyber_bullying", "config_name": "task02", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1104322, "num_examples": 10041, "dataset_name": "poleval2019_cyber_bullying"}, "test": {"name": "test", "num_bytes": 109681, "num_examples": 1000, "dataset_name": "poleval2019_cyber_bullying"}}, "download_checksums": {"http://2019.poleval.pl/task6/task_6-2.zip": {"num_bytes": 340096, "checksum": "659975fc8b6a505b11a4b8a9e29ae1beffede0c8bf83f409b904d982eb1daa8f"}, "http://2019.poleval.pl/task6/task6_test.zip": {"num_bytes": 70051, "checksum": "6acac459608b2d6da75f138740447b047c7bd3e0bbf562964845830a27a0b2f7"}}, "download_size": 410147, "post_processing_size": null, "dataset_size": 1214003, "size_in_bytes": 1624150}}
dummy/task01/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:52f8c48d8f3a4fd300d62a910875f001f206852546fa8299c9f788aa362129f4
3
+ size 2898
dummy/task02/1.0.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:18b4a568ec0b4da4f9d8a23f9bd58346a6e4977dbb42dfbda32c6ef0ca11269f
3
+ size 2898
poleval2019_cyberbullying.py ADDED
@@ -0,0 +1,153 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # coding=utf-8
2
+ # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+ """Cyberbullying Classification Dataset in Polish"""
16
+
17
+
18
+ import os
19
+
20
+ import datasets
21
+
22
+
23
+ _DESCRIPTION = """\
24
+ In Task 6-1, the participants are to distinguish between normal/non-harmful tweets (class: 0) and tweets
25
+ that contain any kind of harmful information (class: 1). This includes cyberbullying, hate speech and
26
+ related phenomena.
27
+
28
+ In Task 6-2, the participants shall distinguish between three classes of tweets: 0 (non-harmful),
29
+ 1 (cyberbullying), 2 (hate-speech). There are various definitions of both cyberbullying and hate-speech,
30
+ some of them even putting those two phenomena in the same group. The specific conditions on which we based
31
+ our annotations for both cyberbullying and hate-speech, which have been worked out during ten years of research
32
+ will be summarized in an introductory paper for the task, however, the main and definitive condition to 1
33
+ distinguish the two is whether the harmful action is addressed towards a private person(s) (cyberbullying),
34
+ or a public person/entity/large group (hate-speech).
35
+ """
36
+
37
+ _HOMEPAGE = "http://2019.poleval.pl/index.php/tasks/task6"
38
+
39
+ _URL_TRAIN_TASK1 = "http://2019.poleval.pl/task6/task_6-1.zip"
40
+ _URL_TRAIN_TASK2 = "http://2019.poleval.pl/task6/task_6-2.zip"
41
+ _URL_TEST = "http://2019.poleval.pl/task6/task6_test.zip"
42
+
43
+ _CITATION = """\
44
+ @proceedings{ogr:kob:19:poleval,
45
+ editor = {Maciej Ogrodniczuk and Łukasz Kobyliński},
46
+ title = {{Proceedings of the PolEval 2019 Workshop}},
47
+ year = {2019},
48
+ address = {Warsaw, Poland},
49
+ publisher = {Institute of Computer Science, Polish Academy of Sciences},
50
+ url = {http://2019.poleval.pl/files/poleval2019.pdf},
51
+ isbn = "978-83-63159-28-3"}
52
+ }
53
+ """
54
+
55
+
56
+ class Poleval2019CyberBullyingConfig(datasets.BuilderConfig):
57
+ """BuilderConfig for Poleval2019CyberBullying."""
58
+
59
+ def __init__(
60
+ self,
61
+ text_features,
62
+ label_classes,
63
+ **kwargs,
64
+ ):
65
+ super(Poleval2019CyberBullyingConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
66
+ self.text_features = text_features
67
+ self.label_classes = label_classes
68
+
69
+
70
+ class Poleval2019CyberBullying(datasets.GeneratorBasedBuilder):
71
+ """Cyberbullying Classification Dataset in Polish"""
72
+
73
+ VERSION = datasets.Version("1.0.0")
74
+
75
+ BUILDER_CONFIGS = [
76
+ Poleval2019CyberBullyingConfig(
77
+ name="task01",
78
+ text_features=["text"],
79
+ label_classes=["0", "1"],
80
+ ),
81
+ Poleval2019CyberBullyingConfig(
82
+ name="task02",
83
+ text_features=["text"],
84
+ label_classes=["0", "1", "2"],
85
+ ),
86
+ ]
87
+
88
+ def _info(self):
89
+
90
+ features = {text_feature: datasets.Value("string") for text_feature in self.config.text_features}
91
+ features["label"] = datasets.features.ClassLabel(names=self.config.label_classes)
92
+
93
+ return datasets.DatasetInfo(
94
+ description=_DESCRIPTION,
95
+ features=datasets.Features(features),
96
+ supervised_keys=("text", "label"),
97
+ homepage=_HOMEPAGE,
98
+ citation=_CITATION,
99
+ )
100
+
101
+ def _split_generators(self, dl_manager):
102
+ """Returns SplitGenerators."""
103
+
104
+ if self.config.name == "task01":
105
+ train_path = dl_manager.download_and_extract(_URL_TRAIN_TASK1)
106
+
107
+ if self.config.name == "task02":
108
+ train_path = dl_manager.download_and_extract(_URL_TRAIN_TASK2)
109
+
110
+ data_dir_test = dl_manager.download_and_extract(_URL_TEST)
111
+
112
+ if self.config.name == "task01":
113
+ test_path = os.path.join(data_dir_test, "Task6", "task 01")
114
+
115
+ if self.config.name == "task02":
116
+ test_path = os.path.join(data_dir_test, "Task6", "task 02")
117
+
118
+ return [
119
+ datasets.SplitGenerator(
120
+ name=datasets.Split.TRAIN,
121
+ gen_kwargs={
122
+ "filepath": train_path,
123
+ "split": "train",
124
+ },
125
+ ),
126
+ datasets.SplitGenerator(
127
+ name=datasets.Split.TEST,
128
+ gen_kwargs={
129
+ "filepath": test_path,
130
+ "split": "test",
131
+ },
132
+ ),
133
+ ]
134
+
135
+ def _generate_examples(self, filepath, split):
136
+ """ Yields examples. """
137
+
138
+ if split == "train":
139
+ text_path = os.path.join(filepath, "training_set_clean_only_text.txt")
140
+ label_path = os.path.join(filepath, "training_set_clean_only_tags.txt")
141
+
142
+ if split == "test":
143
+ if self.config.name == "task01":
144
+ text_path = os.path.join(filepath, "test_set_clean_only_text.txt")
145
+ label_path = os.path.join(filepath, "test_set_clean_only_tags.txt")
146
+ if self.config.name == "task02":
147
+ text_path = os.path.join(filepath, "test_set_only_text.txt")
148
+ label_path = os.path.join(filepath, "test_set_only_tags.txt")
149
+
150
+ with open(text_path, encoding="utf-8") as text_file:
151
+ with open(label_path, encoding="utf-8") as label_file:
152
+ for id_, (text, label) in enumerate(zip(text_file, label_file)):
153
+ yield id_, {"text": text.strip(), "label": int(label.strip())}