Heck reaction prediction using a transformer model based on a transfer learning strategy

Abstract

A proof-of-concept methodology for addressing small amounts of chemical data using transfer learning is presented. We demonstrate this by applying transfer learning combined with the transformer model to small-dataset Heck reaction prediction. Introducing transfer learning significantly improved the accuracy of the transformer-transfer learning model (94.9%) over that of the transformer-baseline model (66.3%).