The goal of this project is to explore different approaches to the optimization of  Text2SQL models. Using the SPIDER dataset (Yu et al. 2018), the student's objective is to investigate how different methods of augmentation, data preprocessing and model fine-tuning influence the model performance. Strong focus is put on evaluation matrices and examining the trade-off between performance, training and execution time.