In order to achieve good results with the shortest possible training times when training deep learning models, it is essential to find suitable values for the training parameters such as learning rate and batch size. The search for suitable values depends on the model to be trained, the amount of data used, but also the available hardware and can therefore prove to be quite time-consuming, since a training run, depending on the model and the training data used, can be very long (up to several days).