In contrast to the mtl model, for trl models all parameters are transferred to the main task, not just parameters that represent shared knowledge.
we suspect the lower scores of the trl models with DIP2016 are due to overfitting on the vast number of samples which shape the parameters much more than the comparatively small SemEval corpus could.