  In this report, we describe the technical details of our submission to the
EPIC-SOUNDS Audio-Based Interaction Recognition Challenge 2023, by Team
"AcieLee" (username: Yuqi\_Li). The task is to classify the audio caused by
interactions between objects, or from events of the camera wearer. We conducted
exhaustive experiments and found learning rate step decay, backbone frozen,
label smoothing and focal loss contribute most to the performance improvement.
After training, we combined multiple models from different stages and
integrated them into a single model by assigning fusion weights. This proposed
method allowed us to achieve 3rd place in the CVPR 2023 workshop of EPIC-SOUNDS
Audio-Based Interaction Recognition Challenge.
