| DISCLAIMER: WORK IN PROGRESS >> WILL BE UPDATED WITH MORE INFORMATION | |
| This model based on BERTweet-base has been finetuned on the Semeval 2018 Task 3 dataset for Irony Detection in English. | |
| However, we do not use the original labels, as we have provided more finegrained labels and annotated the tweets without irony-related hashtags. | |
| These specific models are based on a new paper accepted at the Joint LREC-COLING main conference. | |
| This model was trained on 4,592 samples (not the standard benchmark dataset) to be evaluated on 200 tweets labelled by three different annotators. | |
| A model with the same parameters was also evaluated on the complete dataset through 10-fold CV. | |
| TODO: add the scores once the paper is published. | |
| REFERENCE TO THE PAPER WILL BE INCLUDED ONCE IT IS PUBLISHED. |