Using a ResNet-50 as the encoder architecture is standard in the literature. In the original paper, the authors use ResNet-50 as the encoder architecture and spatially average the outputs of ResNet-50. However, keep in mind that more powerful models will not only increase training time but will also require more memory and will limit the maximal batch size you can use. For the purpose of this example, we just use four convolutional layers.