I think with such imbalanced data and small dataset the accuracy metric is misleading for the model's performance, as we all can see the scores have fixed steps, which indicate that a model could luckily give good accuracy but when tested on the final data wouldn't do good.

That prevents potentially good models from entering/updating the LB due to the fact that it saves the misleading "heighest score". Am i getting that right? :)