The IUPAC names were divided into tokens using two separate methods: token-wise splitting and character-wise splitting (see appendix). Three models were trained for each combination based on 1 million, 10 million, and 50 million training data points selected from PubChem. In this study, all models were tested against the respective test datasets discussed in the dataset section. Each model was compared on its ability to predict IUPAC names based only on one-to-one string matches since we are primarily interested in a model that can produce more accurate IUPAC names overall.