Hugging Face's logo

Datasets:
claritylab
/
utcd

Tasks:
Text Classification
Modalities:
Text
Languages:
English
Size:
1M - 10M
ArXiv:
Libraries:
Datasets
License:
Dataset card Data Studio Files
xet
Community
1
StefanH commited on
Commit
24925b9
·
1 Parent(s): dc7dfdb

Update: dataset zip file structure; loading script WIP

Browse files
Files changed (6) hide show
  1. .gitignore +1 -0
  2. config.json +1686 -0
  3. datasets.zip +2 -2
  4. datasets_joined.zip +3 -0
  5. dev.py +8 -0
  6. utcd.py +143 -0
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+ "name": "Consumer Finance Complaints",
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+ "Credit card or prepaid card",
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+ "Credit reporting, credit repair services, or other personal consumer reports",
1633
+ "Debt collection",
1634
+ "Money transfer, virtual currency, or money service",
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+ "Mortgage",
1637
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1638
+ "Payday loan",
1639
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1640
+ "Prepaid card",
1641
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1642
+ "Vehicle loan or lease",
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+ "Credit reporting",
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+ "Debt collection",
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+ "Money transfer, virtual currency, or money service",
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+ "Money transfers",
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+ "Mortgage",
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+ "Other financial service",
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+ "Payday loan, title loan, or personal loan",
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+ "Prepaid card",
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+ "Student loan",
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+ "Virtual currency"
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+ }
datasets.zip CHANGED
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:2cee07002b203df72a56ac5b09a56ac625b741ba053b136ecdbceca1036c7193
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- size 1744154943
 
1
  version https://git-lfs.github.com/spec/v1
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+ oid sha256:20d9d447b2c283880abe2a28fbf1f3617cdceda0f3788a1f545ae8df884e7847
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+ size 1744258165
datasets_joined.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:2cee07002b203df72a56ac5b09a56ac625b741ba053b136ecdbceca1036c7193
3
+ size 1744154943
dev.py ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ from stefutil import *
2
+
3
+
4
+ if __name__ == '__main__':
5
+ from datasets import load_dataset
6
+
7
+ dnm = 'claritylab/utcd'
8
+ mic(load_dataset(dnm))
utcd.py CHANGED
@@ -0,0 +1,143 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """Universal Text Classification Dataset (UTCD)"""
2
+
3
+
4
+ import os
5
+ import json
6
+ from os.path import join as os_join
7
+ from typing import List
8
+
9
+ import datasets
10
+
11
+ from stefutil import *
12
+
13
+
14
+ _DESCRIPTION = """
15
+ UTCD is a compilation of 18 classification datasets spanning 3 categories of Sentiment,
16
+ Intent/Dialogue and Topic classification. UTCD focuses on the task of zero-shot text classification where the
17
+ candidate labels are descriptive of the text being classified. UTCD consists of ~ 6M/800K train/test examples.
18
+ """
19
+
20
+ # TODO: citation
21
+
22
+ _URL = "https://github.com/ChrisIsKing/zero-shot-text-classification/tree/master"
23
+ _URL_ZIP = "https://huggingface.co/datasets/claritylab/UTCD/raw/main/datasets.zip"
24
+
25
+ _VERSION = datasets.Version('0.0.1')
26
+
27
+
28
+ class UtcdConfig(datasets.BuilderConfig):
29
+ """BuilderConfig for SuperGLUE."""
30
+
31
+ def __init__(self, domain: str, normalize_aspect: bool = False, **kwargs):
32
+ """BuilderConfig for UTCD.
33
+ Args:
34
+ domain: `string`, dataset domain, one of [`in`, `out`].
35
+ normalize_aspect: `bool`, if True, an aspect-normalized version of the dataset is returned.
36
+ **kwargs: keyword arguments forwarded to super.
37
+ """
38
+ # Version history:
39
+ # 0.0.1: Initial version.
40
+ super(UtcdConfig, self).__init__(version=_VERSION, **kwargs)
41
+ ca.check_mismatch('Dataset Domain', domain, ['in', 'out'])
42
+ self.domain = domain
43
+ self.normalize_aspect = normalize_aspect
44
+
45
+ def to_dir_name(self):
46
+ """
47
+ :return: directory name for the dataset files for this config stored on hub
48
+ """
49
+ domain_str = 'in-domain' if self.domain == 'in' else 'out-of-domain'
50
+ prefix = 'aspect-normalized-' if self.normalize_aspect else ''
51
+ return f'{prefix}{domain_str}'
52
+
53
+
54
+ config = StefConfig('config.json')
55
+ # mic(config('go_emotion'))
56
+
57
+
58
+ class Utcd(datasets.GeneratorBasedBuilder):
59
+ """UTCD: Universal Text Classification Dataset. Version 0.0."""
60
+
61
+ # _config = dict(
62
+ # go_emotion=dict(aspect='sentiment', domain='in', name='GoEmotions'),
63
+ # sentiment_tweets_2020=dict(aspect='sentiment', domain='in', name='TweetEval'),
64
+ # emotion=dict(aspect='sentiment', domain='in', name='Emotion'),
65
+ # sgd=dict(aspect='intent', domain='in', name='Schema-Guided Dialogue'),
66
+ # clinc_150=dict(aspect='intent', domain='in', name='Clinc-150'),
67
+ # slurp=dict(aspect='intent', domain='in', name='SLURP'),
68
+ # ag_news=dict(aspect='topic', domain='in', name='AG News'),
69
+ # dbpedia=dict(aspect='topic', domain='in', name='DBpedia'),
70
+ # yahoo=dict(aspect='topic', domain='in', name='Yahoo Answer Topics'),
71
+ #
72
+ # amazon_polarity=dict(aspect='sentiment', domain='out', name='Amazon Review Polarity'),
73
+ # finance_sentiment=dict( aspect='sentiment', domain='out', name='Financial Phrase Bank'),
74
+ # yelp=dict(aspect='sentiment', domain='out', name='Yelp Review'),
75
+ # banking77=dict(aspect='intent', domain='out', name='Banking77'),
76
+ # snips=dict(aspect='intent', domain='out', name='SNIPS'),
77
+ # nlu_evaluation=dict(aspect='intent', domain='out', name='NLU Evaluation'),
78
+ # multi_eurlex=dict(aspect='topic', domain='out', name='MultiEURLEX'),
79
+ # patent=dict(aspect='topic', domain='out', name='Big Patent'),
80
+ # consumer_finance=dict(aspect='topic', domain='out', name='Consumer Finance Complaints')
81
+ # )
82
+
83
+ VERSION = _VERSION
84
+
85
+ BUILDER_CONFIGS = [
86
+ UtcdConfig(
87
+ name='in-domain',
88
+ description='All in-domain datasets.',
89
+ domain='in',
90
+ normalize_aspect=False
91
+ ),
92
+ UtcdConfig(
93
+ name='aspect-normalized-in-domain',
94
+ description='Aspect-normalized version of all in-domain datasets.',
95
+ domain='in',
96
+ normalize_aspect=True
97
+ ),
98
+ UtcdConfig(
99
+ name='out-of-domain',
100
+ description='All out-of-domain datasets.',
101
+ domain='out',
102
+ normalize_aspect=False
103
+ ),
104
+ UtcdConfig(
105
+ name='aspect-normalized-out-of-domain',
106
+ description='Aspect-normalized version of all out-of-domain datasets.',
107
+ domain='out',
108
+ normalize_aspect=True
109
+ )
110
+ ]
111
+
112
+ def _get_dataset_names(self):
113
+ return [dnm for dnm, d_dset in config().items() if d_dset['domain'] == self.config.domain]
114
+
115
+ def _info(self):
116
+ dnms = self._get_dataset_names()
117
+ labels = [config(f'{dnm}.splits.{split}.labels') for dnm in dnms for split in ['train', 'test']]
118
+ mic(dnms, labels)
119
+ return datasets.DatasetInfo(
120
+ description=_DESCRIPTION,
121
+ features=datasets.Features(
122
+ text=datasets.Value(dtype='string'), labels=labels, dataset_name=datasets.ClassLabel(names=dnms)
123
+ ),
124
+ homepage=_URL
125
+ # TODO: citation
126
+ )
127
+
128
+ def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
129
+ # for aspect-normalized versions of the dataset, we include a validation set
130
+ splits = ['train', 'eval', 'test'] if self.config.normalize_aspect else ['train', 'test']
131
+ dnms = self._get_dataset_names()
132
+ dir_nm = self.config.to_dir_name()
133
+ split2paths = {s: [os_join(dir_nm, dnm, s) for dnm in dnms] for s in splits}
134
+ mic(split2paths)
135
+
136
+ downloaded_files = dl_manager.download_and_extract('datasets.zip')
137
+ mic(downloaded_files)
138
+ raise NotImplementedError
139
+
140
+ return [
141
+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
142
+ datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
143
+ ]