nn.BCELoss + sigmoid should perform equally well as nn.BCEWithLogitsLoss + logits in the unsaturated area.
The latter approach gives you more numerical stability.
If the former one is performing better, this could mean e.g. that your learning rate is too high and thus the saturated gradients are beneficial for the model.