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fix: AddingGeorgian Sentiment Classification (#534)
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* Adding First Georgian Dataset
* Points
* Update __init__.py
* Update __init__.py
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asparius authored Apr 24, 2024
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2 changes: 2 additions & 0 deletions docs/mmteb/points/534.jsonl
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{"GitHub": "isaac-chung", "Review PR": 2}
{"GitHub": "asparius", "New dataset": 2}
61 changes: 61 additions & 0 deletions mteb/tasks/Classification/kat/GeorgianSentimentClassification.py
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from __future__ import annotations

from mteb.abstasks import AbsTaskClassification
from mteb.abstasks.TaskMetadata import TaskMetadata


class GeorgianSentimentClassification(AbsTaskClassification):
metadata = TaskMetadata(
name="GeorgianSentimentClassification",
description="Goergian Sentiment Dataset",
reference="https://aclanthology.org/2022.lrec-1.173",
dataset={
"path": "asparius/Georgian-Sentiment",
"revision": "d4fb68dff38e89c42406080737b8431ea48fa866",
},
type="Classification",
category="s2s",
eval_splits=["test"],
eval_langs=["kat-Geor"],
main_score="accuracy",
date=("2022-01-01", "2022-06-25"),
form=["written"],
domains=["Reviews"],
task_subtypes=["Sentiment/Hate speech"],
license="CC BY 4.0",
socioeconomic_status="mixed",
annotations_creators="derived",
dialect=[],
text_creation="found",
bibtex_citation="""
@inproceedings{stefanovitch-etal-2022-resources,
title = "Resources and Experiments on Sentiment Classification for {G}eorgian",
author = "Stefanovitch, Nicolas and
Piskorski, Jakub and
Kharazi, Sopho",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.173",
pages = "1613--1621",
abstract = "This paper presents, to the best of our knowledge, the first ever publicly available annotated dataset for sentiment classification and semantic polarity dictionary for Georgian. The characteristics of these resources and the process of their creation are described in detail. The results of various experiments on the performance of both lexicon- and machine learning-based models for Georgian sentiment classification are also reported. Both 3-label (positive, neutral, negative) and 4-label settings (same labels + mixed) are considered. The machine learning models explored include, i.a., logistic regression, SVMs, and transformed-based models. We also explore transfer learning- and translation-based (to a well-supported language) approaches. The obtained results for Georgian are on par with the state-of-the-art results in sentiment classification for well studied languages when using training data of comparable size.",
}
""",
n_samples={"train": 330, "test": 1200},
avg_character_length={"train": 114.26, "test": 118.06},
)
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{
"dataset_revision": "d4fb68dff38e89c42406080737b8431ea48fa866",
"mteb_dataset_name": "GeorgianSentimentClassification",
"mteb_version": "1.6.8",
"test": {
"accuracy": 0.7464166666666666,
"accuracy_stderr": 0.047843857727217436,
"ap": 0.6872367759871585,
"ap_stderr": 0.048726518159705225,
"evaluation_time": 37.8,
"f1": 0.7455938411656741,
"f1_stderr": 0.0485250595381615,
"main_score": 0.7464166666666666
}
}
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{
"dataset_revision": "d4fb68dff38e89c42406080737b8431ea48fa866",
"mteb_dataset_name": "GeorgianSentimentClassification",
"mteb_version": "1.6.8",
"test": {
"accuracy": 0.7571666666666667,
"accuracy_stderr": 0.027223866163513386,
"ap": 0.6982303339367802,
"ap_stderr": 0.03866108274790974,
"evaluation_time": 29.7,
"f1": 0.7552573260226974,
"f1_stderr": 0.027441367391553517,
"main_score": 0.7571666666666667
}
}

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