cardiffnlp

Twitter-roBERTa-base for Sentiment Analysis - UPDATED (2022) This is a RoBERTa-base model trained on ~124M tweets from January 2018 to December 2021, and finetuned for sentiment analysis with the TweetEval benchmark. The original Twitter-based RoBERTa model can be found here and the original reference paper is TweetEval. This model is suitable for English. - Reference Paper: TimeLMs paper. - Git Repo: TimeLMs official repository. Labels : 0 -> Negative; 1 -> Neutral; 2 -> Positive This sentiment analysis model has been integrated into TweetNLP. You can access the demo here.

--- language: multilingual widget: - text: "🤗" - text: "T'estimo! ❤️" - text: "I love you!" - text: "I hate you 🤮" - text: "Mahal kita!" - text: "사랑해!" - text: "난 너가 싫어" - text: "😍😍😍" ---

--- datasets: - tweet_eval language: - en ---

This is a roBERTa-base model trained on ~58M tweets and finetuned for irony detection with the TweetEval benchmark. This model has integrated into the TweetNLP Python library. - Paper: TweetEval benchmark (Findings of EMNLP 2020). - Git Repo: Tweeteval official repository. Please cite the reference paper if you use this model.

This is a roBERTa-base model trained on ~58M tweets and finetuned for offensive language identification with the TweetEval benchmark.

This is a RoBERTa-base model trained on ~58M tweets and finetuned for emotion recognition with the TweetEval benchmark.

This is a RoBERTa-base model trained on 154M tweets until the end of December 2022 and finetuned for detecting sensitive content (multilabel classification) on the X-Sensitive dataset. The original Twitter-based RoBERTa model can be found here.

This is a RoBERTa-large model trained on 154M tweets until the end of December 2022 and finetuned for detecting sensitive content (multilabel classification) on the X-Sensitive dataset. The original Twitter-based RoBERTa model can be found here. A sensitive content binary model can be found here.

This is a RoBERTa-base model trained on 154M tweets until the end of December 2022 and finetuned for detecting sensitive content (binary classification) on the X-Sensitive dataset. The original Twitter-based RoBERTa model can be found here.

This is a RoBERTa-large model trained on 154M tweets until the end of December 2022 and finetuned for detecting sensitive content (binary classification) on the X-Sensitive dataset. The original Twitter-based RoBERTa model can be found here.