For training and testing models 1 to 3, the latest ChEMBL-32 database was utilised. ChEMBL database version 32 was acquired in the SDF (Structure-Data File) format. The dataset was processed using the CDK SMILES parser functionality to generate canonical SMILES representations preserving stereochemical information. These SMILES strings and their corresponding ChEMBL IDs were then stored in a text file. After analysing the frequency distribution of the length of the SMILES strings, those exceeding 300 characters were removed to eliminate rare, longer SMILES strings. The resulting dataset consisted of a total of 2,290,069 SMILES strings. To select the training and testing datasets, the RDKit implementation of the MaxMin algorithm was used to pick diverse data points for cross-validation. This resulted in training and a test dataset consisting of 2,187,669 and 102,400 molecules, respectively. From the resulting training dataset, a subset of 1,024,000 molecules were picked to be used for training the models in this experiment. These were used to train models 1 to 3 and later determine which model was suitable for further experiments.