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73cc8d2 | 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 | from __future__ import annotations
from mteb.abstasks.AbsTaskClassification import AbsTaskClassification
from mteb.abstasks.TaskMetadata import TaskMetadata
class BengaliDocumentClassification(AbsTaskClassification):
metadata = TaskMetadata(
name="BengaliDocumentClassification",
description="Dataset for News Classification, categorized with 13 domains.",
reference="https://aclanthology.org/2023.eacl-main.4",
dataset={
"path": "dialect-ai/shironaam",
"revision": "1c6e67433da618073295b7c90f1c55fa8e78f35c",
},
type="Classification",
category="s2s",
eval_splits=["test"],
eval_langs=["ben-Beng"],
main_score="accuracy",
date=("2022-05-01", "2023-05-01"),
form=["written"],
dialect=[],
domains=["News"],
task_subtypes=[],
license="CC BY-NC-SA 4.0",
socioeconomic_status="mixed",
annotations_creators="derived",
text_creation="found",
bibtex_citation="""
@inproceedings{akash-etal-2023-shironaam,
title = "Shironaam: {B}engali News Headline Generation using Auxiliary Information",
author = "Akash, Abu Ubaida and
Nayeem, Mir Tafseer and
Shohan, Faisal Tareque and
Islam, Tanvir",
booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.eacl-main.4",
pages = "52--67"
}
""",
n_samples={"test": 2048},
avg_character_length={"test": 1658.1},
)
def dataset_transform(self) -> None:
self.dataset = self.dataset.rename_columns(
{"article": "text", "category": "label"}
)
self.dataset = self.stratified_subsampling(
self.dataset, seed=self.seed, splits=["test"]
)
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