  In recent years, transformer architecture has been a dominating paradigm in
many applications, including affective computing. In this report, we propose
our transformer-based model to handle Emotion Classification Task in the 5th
Affective Behavior Analysis In-the-wild Competition. By leveraging the
attentive model and the synthetic dataset, we attain a score of 0.4775 on the
validation set of Aff-Wild2, the dataset provided by the organizer.
