A model trained on approximately 58 million tweets and fine-tuned for emotion recognition using the TweetEval benchmark. The model achieves high accuracy on various emotion classification tasks, including emojii, emotion, hate, irony, offensive, sentiment, stance/abortion, stance/atheism, stance/climate, stance/feminist, and stance/hillary.
A model trained on approximately 58 million tweets and fine-tuned for emotion recognition using the TweetEval benchmark. The model achieves high accuracy on various emotion classification tasks, including emojii, emotion, hate, irony, offensive, sentiment, stance/abortion, stance/atheism, stance/climate, stance/feminist, and stance/hillary.
text to classify
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POSITIVE (1.00)
NEGATIVE (0.00)
This is a RoBERTa-base model trained on ~58M tweets and finetuned for emotion recognition with the TweetEval benchmark.
New! We just released a new emotion recognition model trained with more emotion types and with a newer RoBERTa-based model. See twitter-roberta-base-emotion-multilabel-latest and TweetNLP for more details.