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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 | from __future__ import annotations
from mteb.abstasks import AbsTaskClassification
from mteb.abstasks.TaskMetadata import TaskMetadata
class FrenchBookReviews(AbsTaskClassification):
metadata = TaskMetadata(
name="FrenchBookReviews",
dataset={
"path": "Abirate/french_book_reviews",
"revision": "534725e03fec6f560dbe8166e8ae3825314a6290",
},
description="It is a French book reviews dataset containing a huge number of reader reviews on French books. Each review is pared with a rating that ranges from 0.5 to 5 (with 0.5 increment).",
reference="https://huggingface.co/datasets/Abirate/french_book_reviews",
type="Classification",
category="s2s",
eval_splits=["train"],
eval_langs=["fra-Latn"],
main_score="accuracy",
date=("2022-01-01", "2023-01-01"),
form=["written"],
domains=["Reviews"],
task_subtypes=[],
license="CC0",
socioeconomic_status="mixed",
annotations_creators="derived",
dialect=[],
text_creation="found",
bibtex_citation="""
""",
n_samples={"train": 2048},
avg_character_length={"train": 311.5},
)
def dataset_transform(self):
self.dataset = self.dataset.rename_columns({"reader_review": "text"})
self.dataset = self.stratified_subsampling(
self.dataset, seed=self.seed, splits=["train"]
)
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