  In this paper, we detailedly describe our solution for the IEEE BigData Cup
2021: RL-based RecSys (Track 1: Item Combination Prediction). We first conduct
an exploratory data analysis on the dataset and then utilize the findings to
design our framework. Specifically, we use a two-headed transformer-based
network to predict user feedback and unlocked sessions, along with the proposed
session-aware reweighted loss, multi-tasking with click behavior prediction,
and randomness-in-session augmentation. In the final private leaderboard on
Kaggle, our method ranked 2nd with a categorization accuracy of 0.39224.
