This model is a facebook/bart-large fine-tuned on sarcastic comments from raquiba/Sarcasm_News_Headline dataset.

This model is not intended to be used for plain inference as it is very likely to predict sarcastic content. It is intended to be used instead as "utility model" for detecting and fixing sarcastic content as its token probability distributions will likely differ from comparable models not trained/fine-tuned over sarcastic data. Its name sarcasm_minus refers to the G- model in Detoxifying Text with MARCO: Controllable Revision with Experts and Anti-Experts.

This model is fine-tuned over sarcastic comments from raquiba/Sarcasm_News_Headline and it is very likely to produce sarcastic content. For this reason this model should only be used in combination with other models for the sake of detecting / fixing sarcastic content, see for example Detoxifying Text with MARCO: Controllable Revision with Experts and Anti-Experts.

This section describes the evaluation protocols and provides the results.

This model was tested on raquiba/Sarcasm_News_Headline testset.

Model was evaluated using perplexity (on the MLM task).

Perplexity: 1.00