Twitter-roBERTa-base for Sentiment Analysis

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. This model is suitable for English.

The output of the text sentiment analysis model is one of three labels denoting the sentiment of the text:

• 0 -> Negative
• 1 -> Neutral
• 2 -> Positive

Pro Tip

Note that the sentiment analysis model is suitable for English text. If you require this workflow on text block in different languages, you create a derived custom workflow and insert a text translation model before the sentiment analysis model. This will ensure that the sentiment analysis model is receiving its input text in English.