Models trained on extensive datasets often exhibit artificially high-performance metrics when evaluated using conventional train-test splits or k-fold validation methods. Sadman et. al has shown a decrease in the performance of well-known models like CGCNN,MEGNET while making predictions in the OOD regime. Given that our investigation focuses on smaller datasets, the susceptibility to inflated performance metrics in our models is likely even more pronounced.