cardiffnlp / twitter-roberta-base-emoji-latest

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Total runs: 167
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Model's Last Updated: March 07 2024
text-classification

Introduction of twitter-roberta-base-emoji-latest

Model Details of twitter-roberta-base-emoji-latest

cardiffnlp/twitter-roberta-base-emoji-latest

This is a RoBERTa-base model trained on 154M tweets until the end of December 2022 and finetuned for emoji classification (multiclass classification on 100 emojis) on the TweetEmoji100 dataset of SuperTweetEval . The original Twitter-based RoBERTa model can be found here .

Example
from transformers import pipeline
text= "I’m tired of being sick.. it’s been four days dawg"

pipe = pipeline('text-classification', model="cardiffnlp/twitter-roberta-base-emoji-latest", return_all_scores=True))
predictions = pipe(text)[0]
predictions = sorted(predictions, key=lambda d: d['score'], reverse=True) 
predictions[:5]
>> [{'label': '😒', 'score': 0.14303581416606903},
 {'label': '😩', 'score': 0.07775110006332397},
 {'label': '😤', 'score': 0.0710175409913063},
 {'label': '😑', 'score': 0.06665993481874466},
 {'label': '😫', 'score': 0.0662984848022461}]
Citation Information

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}
}

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167
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0
24-hour runs
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3-day runs
97
7-day runs
139
30-day runs

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