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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 | from __future__ import annotations
from mteb.abstasks.TaskMetadata import TaskMetadata
from ....abstasks import AbsTaskClassification
class ImdbClassification(AbsTaskClassification):
metadata = TaskMetadata(
name="ImdbClassification",
description="Large Movie Review Dataset",
dataset={
"path": "mteb/imdb",
"revision": "3d86128a09e091d6018b6d26cad27f2739fc2db7",
},
reference="http://www.aclweb.org/anthology/P11-1015",
type="Classification",
category="p2p",
eval_splits=["test"],
eval_langs=["eng-Latn"],
main_score="accuracy",
date=(
"2000-01-01",
"2010-12-31",
), # Estimated range for the collection of movie reviews
form=["written"],
domains=["Reviews"],
task_subtypes=["Sentiment/Hate speech"],
license="Not specified",
socioeconomic_status="mixed",
annotations_creators="derived",
dialect=[],
text_creation="found",
bibtex_citation="""@inproceedings{maas-etal-2011-learning,
title = "Learning Word Vectors for Sentiment Analysis",
author = "Maas, Andrew L. and
Daly, Raymond E. and
Pham, Peter T. and
Huang, Dan and
Ng, Andrew Y. and
Potts, Christopher",
editor = "Lin, Dekang and
Matsumoto, Yuji and
Mihalcea, Rada",
booktitle = "Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2011",
address = "Portland, Oregon, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P11-1015",
pages = "142--150",
}""",
n_samples={"test": 25000},
avg_character_length={"test": 1293.8},
)
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