A model was trained with a set of 1 million compounds randomly sampled from GDB-13. An initial way to assess the quality of the sampled molecules is to check the percentage of valid molecules (Figure ). This metric has often been used to train models , but in the case of the GDB databases it proves to be insufficient, as it is always over 96.5 %. To view the progress of the training, log-likelihoods (LLs) of the SMILES in the training, validation and sampled sets were calculated after training the model each epoch. These LLs were plotted together as histograms every 25 epochs (Figure ). Also, the Jensen-Shannon Divergence (JSD) between the three plots has been calculated (Figure ). This measure allows the quantification of the differences between each pair of distributions.