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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 42 43 44 45 46 | from __future__ import annotations
from mteb.abstasks import AbsTaskClassification
from mteb.abstasks.TaskMetadata import TaskMetadata
class PoemSentimentClassification(AbsTaskClassification):
metadata = TaskMetadata(
name="PoemSentimentClassification",
description="Poem Sentiment is a sentiment dataset of poem verses from Project Gutenberg.",
reference="https://arxiv.org/abs/2011.02686",
dataset={
"path": "google-research-datasets/poem_sentiment",
"revision": "329d529d875a00c47ec71954a1a96ae167584770",
},
type="Classification",
category="s2s",
eval_splits=["validation", "test"],
eval_langs=["eng-Latn"],
main_score="accuracy",
date=("1700-01-01", "1900-01-01"),
form=["written"],
domains=["Reviews"],
task_subtypes=["Sentiment/Hate speech"],
license="CC-BY-4.0",
socioeconomic_status="mixed",
annotations_creators="human-annotated",
dialect=["eng-Latn-US", "en-Latn-GB"],
text_creation="found",
bibtex_citation="""
@misc{sheng2020investigating,
title={Investigating Societal Biases in a Poetry Composition System},
author={Emily Sheng and David Uthus},
year={2020},
eprint={2011.02686},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
""",
n_samples={"validation": 105, "test": 104},
avg_character_length={"validation": 45.3, "test": 42.4},
)
def dataset_transform(self):
self.dataset = self.dataset.rename_column("verse_text", "text")
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