File size: 1,817 Bytes
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 55 56 57 58 59 60 | from __future__ import annotations
from mteb.abstasks.TaskMetadata import TaskMetadata
from ....abstasks import AbsTaskClassification, MultilingualTask
_LANGUAGES = {
"amh": ["amh-Ethi"],
"eng": ["eng-Latn"],
"fra": ["fra-Latn"],
"hau": ["hau-Latn"],
"ibo": ["ibo-Latn"],
"lin": ["lin-Latn"],
"lug": ["lug-Latn"],
"orm": ["orm-Ethi"],
"pcm": ["pcm-Latn"],
"run": ["run-Latn"],
"sna": ["sna-Latn"],
"som": ["som-Latn"],
"swa": ["swa-Latn"],
"tir": ["tir-Ethi"],
"xho": ["xho-Latn"],
"yor": ["yor-Latn"],
}
class MasakhaNEWSClassification(AbsTaskClassification, MultilingualTask):
metadata = TaskMetadata(
name="MasakhaNEWSClassification",
dataset={
"path": "mteb/masakhanews",
"revision": "18193f187b92da67168c655c9973a165ed9593dd",
},
description="MasakhaNEWS is the largest publicly available dataset for news topic classification in 16 languages widely spoken in Africa. The train/validation/test sets are available for all the 16 languages.",
reference="https://arxiv.org/abs/2304.09972",
category="s2s",
type="Classification",
eval_splits=["test"],
eval_langs=_LANGUAGES,
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": 422},
avg_character_length={"test": 5116.6},
)
def dataset_transform(self):
for lang in self.dataset.keys():
self.dataset[lang] = self.dataset[lang].rename_columns(
{"category": "label"}
)
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