Training on GPU degrades F1 score

Hi folks, we have produced multiple experiments that shows some indicators that the training on GPU on a very skewed dataset will produce worse metrics than a training on CPU. Both training are distributed using https://github.com/ray-project/xgboost_ray.

On test set:
On CPU training, we are able to produces F1: ~0.15 and F2:~0.176 consistently.
On GPU training, we are only able to produce up to F1: 0.135 and F2:0.166 throughout at best over multiple runs

XGBoost version: 1.5.2 (both CPU and GPU)
Pre-processing steps: vectorize for dmatrix