The model itself takes product Morgan fingerprints of length 2048 and radius 2 as input, and uses a single hidden layer of 2048 neurons with RELU activation functions to map the fingerprint to its retrosynthetic template. A dropout rate of 0.2 was applied. The learning rate was set to 0.001, with early stopping if the validation error did not improve for three consecutive epochs.