SuperTweetEval
Collection
Dataset and models associated with the SuperTweetEval benchmark
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24 items
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Updated
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1
This is a RoBERTa-base model trained on 154M tweets until the end of December 2022 and finetuned for hate speech detection (multiclass classification) on the TweetHate dataset of SuperTweetEval. The original Twitter-based RoBERTa model can be found here.
"id2label": {
"0": "hate_gender",
"1": "hate_race",
"2": "hate_sexuality",
"3": "hate_religion",
"4": "hate_origin",
"5": "hate_disability",
"6": "hate_age",
"7": "not_hate"
}
from transformers import pipeline
text = 'Eid Mubarak Everyone!!! ❤ May Allah unite all Muslims, show us the right path, and bless us with good health.❣'
pipe = pipeline('text-classification', model="cardiffnlp/twitter-roberta-base-hate-latest-st")
pipe(text)
>> [{'label': 'not_hate', 'score': 0.9997966885566711}]
Please cite the reference paper if you use this model.
@inproceedings{antypas2023supertweeteval,
title={SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research},
author={Dimosthenis Antypas and Asahi Ushio and Francesco Barbieri and Leonardo Neves and Kiamehr Rezaee and Luis Espinosa-Anke and Jiaxin Pei and Jose Camacho-Collados},
booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
year={2023}
}