The training dataset for scaling experiments is PubChem10M , a set of 10 million SMILES strings. 5% of the data is randomly sampled and held out as a fixed validation set of size 500,000 molecules. Variable training datasets with sizes 10 n , where n ∈ (2, 3, 4, 5, 6), were used. The largest training dataset includes all molecules in PubChem10M, excluding the validation set. The maximum vocabulary size was 10,000 and the maximum sequence length was 512 tokens. SMILES strings were converted to SELFIES using version 1.0.4 of the SELFIES library . SELFIES were tokenized by splitting individual strings into minimally semantically meaningful tokens denoted by brackets, including start-of-string, end-of-string, and padding tokens. Dataset sizes range from 51,200 to 304,656,384 tokens.