Comparison of machine learning approaches for a topic in a scientific paper
If I understand, you could evaluate your approach based on your efforts in using the right preprocessing, picking the right features, building the appropriate architecture (choosing the model that best suits the problem).

Each step will make the loss decrease until you reach a point, you will have to search over the hyperparameters to squeeze every percent of accuracy, which is heavily a computational problem.