[D] XGBoost + Imbalanced data for Binary Classification, Overfitting but Acceptable Classification Report?

TLDR

1. How would I fix overfitting without sacrificing the performance of Class 1?
2. Is overfitting normal in a highly imbalanced dataset?
3. Based on the Class 1 performance and the goal of this project to detect Class 1, do you think this is good enough for deployment?

For context, my data is imbalanced (700: 5500 samples). But in real life, the imbalance would be twice. This binary classifier was created to predict the minority class.

I have used …

binary class classification data dataset good machinelearning normal overfitting performance project report think xgboost