File size: 1,948 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 | from mteb.abstasks.AbsTaskClassification import AbsTaskClassification
from mteb.abstasks.TaskMetadata import TaskMetadata
class WongnaiReviewsClassification(AbsTaskClassification):
metadata = TaskMetadata(
name="WongnaiReviewsClassification ",
description="Wongnai features over 200,000 restaurants, beauty salons, and spas across Thailand on its platform, with detailed information about each merchant and user reviews. In this dataset there are 5 classes corressponding each star rating",
reference="https://github.com/wongnai/wongnai-corpus",
dataset={
"path": "wongnai_reviews",
"revision": "e708d4545d7ab10dd2c6b5b5b2a72ca28685dae2",
},
type="Classification",
category="p2p",
eval_splits=["test"],
eval_langs=["tha-Thai"],
main_score="accuracy",
date=("2018-01-01", "2018-12-31"),
form=["written"],
dialect=[],
domains=["Reviews"],
task_subtypes=[],
license="LGPL-3.0",
socioeconomic_status="mixed",
annotations_creators="derived",
text_creation="found",
bibtex_citation="""
@software{cstorm125_2020_3852912,
author = {cstorm125 and lukkiddd},
title = {PyThaiNLP/classification-benchmarks: v0.1-alpha},
month = may,
year = 2020,
publisher = {Zenodo},
version = {v0.1-alpha},
doi = {10.5281/zenodo.3852912},
url = {https://doi.org/10.5281/zenodo.3852912}
}""",
n_samples={"test": 2048},
avg_character_length={"test": 540.3717},
)
def dataset_transform(self):
self.dataset = self.dataset.rename_columns(
{"review_body": "text", "star_rating": "label"}
)
self.dataset = self.stratified_subsampling(
self.dataset, seed=self.seed, splits=["test"]
)
|