Experiments are conducted on the benchmark L+M-24, which integrates molecular and linguistic modalities in four key categories: biomedical; light and electricity; human interaction and organoleptics; and agriculture and industry . The dataset was created by extracting SMILES (Simplified Molecular-Input Line-Entry System) strings and their chemical properties from databases. The properties were transformed into natural language using GPT-4 templates. The training and validation subsets contain around 127k and 34k language-molecule pairs, with only 10% used for our experiments.