issue with early-stopping on f1 score with imbalanced data
F1 is based on hard classification; if the probability scores are hovering near the threshold, then the classifications may be flopping a lot, leading to unstable F1 scores.

A low F1 score is not too surprising in the presence of such imbalance; the default cutoff of 0.5 will often lead to high recall but low precision.