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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 | from __future__ import annotations
from mteb.abstasks.AbsTaskClassification import AbsTaskClassification
from mteb.abstasks.TaskMetadata import TaskMetadata
class SentimentAnalysisHindi(AbsTaskClassification):
metadata = TaskMetadata(
name="SentimentAnalysisHindi",
description="Hindi Sentiment Analysis Dataset",
reference="https://huggingface.co/datasets/OdiaGenAI/sentiment_analysis_hindi",
dataset={
"path": "OdiaGenAI/sentiment_analysis_hindi",
"revision": "1beac1b941da76a9c51e3e5b39d230fde9a80983",
},
type="Classification",
category="s2s",
eval_splits=["train"],
eval_langs=["hin-Deva"],
main_score="f1",
date=("2023-09-15", "2023-10-16"),
form=["written"],
dialect=[],
domains=["Reviews"],
task_subtypes=["Sentiment/Hate speech"],
license="CC BY-NC-SA 4.0",
socioeconomic_status="mixed",
annotations_creators="derived",
text_creation="found",
bibtex_citation="""@misc{OdiaGenAI,
author = {Shantipriya Parida and Sambit Sekhar and Soumendra Kumar Sahoo and Swateek Jena and Abhijeet Parida and Satya Ranjan Dash and Guneet Singh Kohli},
title = {OdiaGenAI: Generative AI and LLM Initiative for the Odia Language},
year = {2023},
publisher = {Hugging Face},
journal = {Hugging Face repository},
howpublished = {{https://huggingface.co/OdiaGenAI}}, } """,
n_samples={"train": 2497},
avg_character_length={"train": 81.29},
)
def dataset_transform(self):
self.dataset = self.stratified_subsampling(
self.dataset, seed=self.seed, splits=["train"]
)
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