During transfer learning, the training set was comprised of 80 macrocyclic peptides and tested against a test set of 24 analytes, with measured retention times of new macrocyclic peptides. The training data loss was monitored for model selection across a 2000 epoch training schedule. The initial learning rate was again 0.001 and warm restarts for cosine annealing was set to every 450 epochs. The optimizer during transfer learning was averaged stochastic gradient decent , with the loss function being root mean squared error and the batch size set to 8. Additionally, the first 25 stacked model parameters were frozen, such that they were not updated during training.