Commit
•
990aa6f
1
Parent(s):
62665dd
Upload id_short_answer_grading.py with huggingface_hub
Browse files- id_short_answer_grading.py +13 -13
id_short_answer_grading.py
CHANGED
@@ -4,11 +4,11 @@ from typing import Dict, List, Tuple
|
|
4 |
|
5 |
import datasets
|
6 |
|
7 |
-
from
|
8 |
create_saintek_and_soshum_dataset
|
9 |
-
from
|
10 |
-
from
|
11 |
-
from
|
12 |
|
13 |
_CITATION = """\
|
14 |
@article{
|
@@ -72,28 +72,28 @@ _SUPPORTED_TASKS = [Tasks.SHORT_ANSWER_GRADING]
|
|
72 |
|
73 |
_SOURCE_VERSION = "1.0.0"
|
74 |
|
75 |
-
|
76 |
|
77 |
|
78 |
class IdShortAnswerGrading(datasets.GeneratorBasedBuilder):
|
79 |
"""Indonesian short answers for Biology and Geography subjects from 534 respondents where the answer grading was done by 7 experts."""
|
80 |
|
81 |
SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
|
82 |
-
|
83 |
|
84 |
BUILDER_CONFIGS = [
|
85 |
-
|
86 |
name="id_short_answer_grading_source",
|
87 |
version=SOURCE_VERSION,
|
88 |
description="id_short_answer_grading source schema",
|
89 |
schema="source",
|
90 |
subset_id="id_short_answer_grading",
|
91 |
),
|
92 |
-
|
93 |
-
name="
|
94 |
-
version=
|
95 |
description="id_short_answer_grading Nusantara schema",
|
96 |
-
schema="
|
97 |
subset_id="id_short_answer_grading",
|
98 |
),
|
99 |
]
|
@@ -112,7 +112,7 @@ class IdShortAnswerGrading(datasets.GeneratorBasedBuilder):
|
|
112 |
"score": datasets.Value("int64"),
|
113 |
}
|
114 |
)
|
115 |
-
elif self.config.schema == "
|
116 |
features = schemas.pairs_features([0, 1, 2, 3, 4, 5])
|
117 |
|
118 |
return datasets.DatasetInfo(
|
@@ -184,7 +184,7 @@ class IdShortAnswerGrading(datasets.GeneratorBasedBuilder):
|
|
184 |
}
|
185 |
yield row.index, entry
|
186 |
|
187 |
-
elif self.config.schema == "
|
188 |
for row in df.itertuples():
|
189 |
entry = {
|
190 |
"id": str(row.index),
|
|
|
4 |
|
5 |
import datasets
|
6 |
|
7 |
+
from seacrowd.sea_datasets.id_short_answer_grading.utils.id_short_answer_grading_utils import \
|
8 |
create_saintek_and_soshum_dataset
|
9 |
+
from seacrowd.utils import schemas
|
10 |
+
from seacrowd.utils.configs import SEACrowdConfig
|
11 |
+
from seacrowd.utils.constants import Tasks
|
12 |
|
13 |
_CITATION = """\
|
14 |
@article{
|
|
|
72 |
|
73 |
_SOURCE_VERSION = "1.0.0"
|
74 |
|
75 |
+
_SEACROWD_VERSION = "2024.06.20"
|
76 |
|
77 |
|
78 |
class IdShortAnswerGrading(datasets.GeneratorBasedBuilder):
|
79 |
"""Indonesian short answers for Biology and Geography subjects from 534 respondents where the answer grading was done by 7 experts."""
|
80 |
|
81 |
SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
|
82 |
+
SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
|
83 |
|
84 |
BUILDER_CONFIGS = [
|
85 |
+
SEACrowdConfig(
|
86 |
name="id_short_answer_grading_source",
|
87 |
version=SOURCE_VERSION,
|
88 |
description="id_short_answer_grading source schema",
|
89 |
schema="source",
|
90 |
subset_id="id_short_answer_grading",
|
91 |
),
|
92 |
+
SEACrowdConfig(
|
93 |
+
name="id_short_answer_grading_seacrowd_pairs_score",
|
94 |
+
version=SEACROWD_VERSION,
|
95 |
description="id_short_answer_grading Nusantara schema",
|
96 |
+
schema="seacrowd_pairs_score",
|
97 |
subset_id="id_short_answer_grading",
|
98 |
),
|
99 |
]
|
|
|
112 |
"score": datasets.Value("int64"),
|
113 |
}
|
114 |
)
|
115 |
+
elif self.config.schema == "seacrowd_pairs_score":
|
116 |
features = schemas.pairs_features([0, 1, 2, 3, 4, 5])
|
117 |
|
118 |
return datasets.DatasetInfo(
|
|
|
184 |
}
|
185 |
yield row.index, entry
|
186 |
|
187 |
+
elif self.config.schema == "seacrowd_pairs_score":
|
188 |
for row in df.itertuples():
|
189 |
entry = {
|
190 |
"id": str(row.index),
|