holylovenia commited on
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239dd64
1 Parent(s): 1f07fa2

Upload code_mixed_jv_id.py with huggingface_hub

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  1. code_mixed_jv_id.py +26 -29
code_mixed_jv_id.py CHANGED
@@ -36,7 +36,7 @@ showed that the reason for the misclassified was that most of Indonesian
36
  language and Javanese language consist of words that were considered as
37
  positive in both Lexicon model.
38
 
39
- [nusantara_schema_name] = (text, t2t)
40
  """
41
  from pathlib import Path
42
  from typing import Dict, List, Tuple
@@ -44,9 +44,9 @@ from typing import Dict, List, Tuple
44
  import datasets
45
  import pandas as pd
46
 
47
- from nusacrowd.utils import schemas
48
- from nusacrowd.utils.configs import NusantaraConfig
49
- from nusacrowd.utils.constants import Tasks
50
 
51
  _CITATION = """\
52
  @article{Tho_2021,
@@ -100,7 +100,7 @@ _SUPPORTED_TASKS = [Tasks.SENTIMENT_ANALYSIS, Tasks.MACHINE_TRANSLATION]
100
 
101
  _SOURCE_VERSION = "1.0.0"
102
 
103
- _NUSANTARA_VERSION = "1.0.0"
104
 
105
  _LANGUAGES = ['jav', 'ind']
106
  _LOCAL = False
@@ -115,35 +115,35 @@ class CodeMixedSenti(datasets.GeneratorBasedBuilder):
115
  """Code-mixed sentiment analysis for Indonesian and Javanese."""
116
 
117
  SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
118
- NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
119
 
120
  BUILDER_CONFIGS = [
121
- NusantaraConfig(
122
  name="code_mixed_jv_id_source",
123
  version=SOURCE_VERSION,
124
  description="code_mixed_jv_id source schema for Javanese and Indonesian",
125
  schema="source",
126
  subset_id="code_mixed_source",
127
  ),
128
- NusantaraConfig(
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- name="code_mixed_jv_id_jv_nusantara_text",
130
- version=NUSANTARA_VERSION,
131
- description="code_mixed_jv_id nusantara_text schema for Javanese",
132
- schema="nusantara_text",
133
  subset_id="code_mixed_jv",
134
  ),
135
- NusantaraConfig(
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- name="code_mixed_jv_id_id_nusantara_text",
137
- version=NUSANTARA_VERSION,
138
- description="code_mixed_jv_id nusantara_text schema for Indonesian",
139
- schema="nusantara_text",
140
  subset_id="code_mixed_id",
141
  ),
142
- NusantaraConfig(
143
- name="code_mixed_jv_id_nusantara_t2t",
144
- version=NUSANTARA_VERSION,
145
- description="code_mixed_jv_id nusantara_t2t schema for Javanese and Indonesian",
146
- schema="nusantara_t2t",
147
  subset_id="code_mixed_jv_id",
148
  )
149
  ]
@@ -157,9 +157,9 @@ class CodeMixedSenti(datasets.GeneratorBasedBuilder):
157
  "text_ind": datasets.Value("string"),
158
  "label": datasets.Value("int32")
159
  })
160
- elif self.config.schema == "nusantara_text":
161
  features = schemas.text_features(["-1", "0", "1"])
162
- elif self.config.schema == "nusantara_t2t":
163
  features = schemas.text2text_features
164
 
165
  return datasets.DatasetInfo(description=_DESCRIPTION, features=features, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION,)
@@ -182,7 +182,7 @@ class CodeMixedSenti(datasets.GeneratorBasedBuilder):
182
  ex = {"text_jav": row.text_jav, "text_ind": row.text_ind, "label": row.label}
183
  yield i, ex
184
  i += 1
185
- elif self.config.schema == "nusantara_text":
186
  prefix_length = len(_DATASETNAME)
187
  start = prefix_length + 1
188
  end = prefix_length + 1 + 2
@@ -194,12 +194,9 @@ class CodeMixedSenti(datasets.GeneratorBasedBuilder):
194
  ex = {"id": str(i), "text": row.text, "label": str(row.label)}
195
  yield i, ex
196
  i += 1
197
- elif self.config.schema == "nusantara_t2t":
198
  i = 0
199
  for row in df.itertuples():
200
  ex = {"id": str(i), "text_1": row.text_jav, "text_2": row.text_ind, "text_1_name": "jav", "text_2_name": "ind"}
201
  yield i, ex
202
  i += 1
203
-
204
- if __name__ == "__main__":
205
- datasets.load_dataset(__file__)
 
36
  language and Javanese language consist of words that were considered as
37
  positive in both Lexicon model.
38
 
39
+ [seacrowd_schema_name] = (text, t2t)
40
  """
41
  from pathlib import Path
42
  from typing import Dict, List, Tuple
 
44
  import datasets
45
  import pandas as pd
46
 
47
+ from seacrowd.utils import schemas
48
+ from seacrowd.utils.configs import SEACrowdConfig
49
+ from seacrowd.utils.constants import Tasks
50
 
51
  _CITATION = """\
52
  @article{Tho_2021,
 
100
 
101
  _SOURCE_VERSION = "1.0.0"
102
 
103
+ _SEACROWD_VERSION = "2024.06.20"
104
 
105
  _LANGUAGES = ['jav', 'ind']
106
  _LOCAL = False
 
115
  """Code-mixed sentiment analysis for Indonesian and Javanese."""
116
 
117
  SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
118
+ SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
119
 
120
  BUILDER_CONFIGS = [
121
+ SEACrowdConfig(
122
  name="code_mixed_jv_id_source",
123
  version=SOURCE_VERSION,
124
  description="code_mixed_jv_id source schema for Javanese and Indonesian",
125
  schema="source",
126
  subset_id="code_mixed_source",
127
  ),
128
+ SEACrowdConfig(
129
+ name="code_mixed_jv_id_jv_seacrowd_text",
130
+ version=SEACROWD_VERSION,
131
+ description="code_mixed_jv_id seacrowd_text schema for Javanese",
132
+ schema="seacrowd_text",
133
  subset_id="code_mixed_jv",
134
  ),
135
+ SEACrowdConfig(
136
+ name="code_mixed_jv_id_id_seacrowd_text",
137
+ version=SEACROWD_VERSION,
138
+ description="code_mixed_jv_id seacrowd_text schema for Indonesian",
139
+ schema="seacrowd_text",
140
  subset_id="code_mixed_id",
141
  ),
142
+ SEACrowdConfig(
143
+ name="code_mixed_jv_id_seacrowd_t2t",
144
+ version=SEACROWD_VERSION,
145
+ description="code_mixed_jv_id seacrowd_t2t schema for Javanese and Indonesian",
146
+ schema="seacrowd_t2t",
147
  subset_id="code_mixed_jv_id",
148
  )
149
  ]
 
157
  "text_ind": datasets.Value("string"),
158
  "label": datasets.Value("int32")
159
  })
160
+ elif self.config.schema == "seacrowd_text":
161
  features = schemas.text_features(["-1", "0", "1"])
162
+ elif self.config.schema == "seacrowd_t2t":
163
  features = schemas.text2text_features
164
 
165
  return datasets.DatasetInfo(description=_DESCRIPTION, features=features, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION,)
 
182
  ex = {"text_jav": row.text_jav, "text_ind": row.text_ind, "label": row.label}
183
  yield i, ex
184
  i += 1
185
+ elif self.config.schema == "seacrowd_text":
186
  prefix_length = len(_DATASETNAME)
187
  start = prefix_length + 1
188
  end = prefix_length + 1 + 2
 
194
  ex = {"id": str(i), "text": row.text, "label": str(row.label)}
195
  yield i, ex
196
  i += 1
197
+ elif self.config.schema == "seacrowd_t2t":
198
  i = 0
199
  for row in df.itertuples():
200
  ex = {"id": str(i), "text_1": row.text_jav, "text_2": row.text_ind, "text_1_name": "jav", "text_2_name": "ind"}
201
  yield i, ex
202
  i += 1