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83d24b2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | from __future__ import annotations
from mteb.abstasks import AbsTaskClassification
from mteb.abstasks.TaskMetadata import TaskMetadata
class NordicLangClassification(AbsTaskClassification):
metadata = TaskMetadata(
name="NordicLangClassification",
description="A dataset for Nordic language identification.",
reference="https://aclanthology.org/2021.vardial-1.8/",
dataset={
"path": "strombergnlp/nordic_langid",
"revision": "e254179d18ab0165fdb6dbef91178266222bee2a",
"name": "10k",
},
type="Classification",
category="s2s",
eval_splits=["test"],
eval_langs=[
"nob-Latn",
"nno-Latn",
"dan-Latn",
"swe-Latn",
"isl-Latn",
"fao-Latn",
],
main_score="accuracy",
date=None,
form=None,
domains=None,
task_subtypes=None,
license=None,
socioeconomic_status=None,
annotations_creators=None,
dialect=None,
text_creation=None,
bibtex_citation=None,
n_samples={"test": 3000},
avg_character_length={"test": 78.2},
)
@property
def metadata_dict(self) -> dict[str, str]:
metadata_dict = super().metadata_dict
metadata_dict["n_experiments"] = 10
metadata_dict["samples_per_label"] = 32
return metadata_dict
def dataset_transform(self):
self.dataset = self.dataset.rename_columns(
{"sentence": "text", "language": "label"}
)
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