Model bias is not a huge issue. Maybe something about class imbalance or regularization. The huge issue is deployment - what is the model used for? How is it affecting people in reality? What metric is it optimizing?

Between all these the degree of L1 regularization or the class weights are minor things. Most models will perform similarly given the same data. It's mostly the data that makes the difference.