File size: 2,024 Bytes
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 58 59 60 | from __future__ import annotations
from mteb.abstasks import AbsTaskClassification
from mteb.abstasks.TaskMetadata import TaskMetadata
N_SAMPLES = 2048
class CSFDSKMovieReviewSentimentClassification(AbsTaskClassification):
metadata = TaskMetadata(
name="CSFDSKMovieReviewSentimentClassification",
description="The dataset contains 30k user reviews from csfd.cz in Slovak.",
reference="https://arxiv.org/abs/2304.01922",
dataset={
"path": "fewshot-goes-multilingual/sk_csfd-movie-reviews",
"revision": "23a20c659d868740ef9c54854de631fe19cd5c17",
},
type="Classification",
category="s2s",
date=("2002-05-21", "2020-03-05"),
eval_splits=["test"],
eval_langs=["slk-Latn"],
main_score="accuracy",
form=["written"],
domains=["Reviews"],
task_subtypes=["Sentiment/Hate speech"],
license="CC-BY-SA-4.0",
socioeconomic_status="mixed",
annotations_creators="derived",
dialect=[],
text_creation="found",
bibtex_citation="""
@misc{štefánik2023resources,
title={Resources and Few-shot Learners for In-context Learning in Slavic Languages},
author={Michal Štefánik and Marek Kadlčík and Piotr Gramacki and Petr Sojka},
year={2023},
eprint={2304.01922},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
""",
n_samples={"test": N_SAMPLES},
avg_character_length={"test": 366.2},
)
@property
def metadata_dict(self):
md = super().metadata_dict
# Increase the samples_per_label in order to improve baseline performance
md["samples_per_label"] = 20
return md
def dataset_transform(self):
self.dataset = self.dataset.rename_columns(
{"comment": "text", "rating_int": "label"}
)
self.dataset = self.stratified_subsampling(
self.dataset, seed=self.seed, splits=["test"], n_samples=N_SAMPLES
)
|