Data augmentation when using flow_from_directory in CNN

I would like to use a small dataset to create CNN model. So, I am using data augmentation to increase the train dataset. Should I use all augmentation techniques (arguments) that listed here?

I have noticed that adding many arguments decrease the accuracy of the model and make the training set harder than the testing set.

What is the best practices to use data augmentation when use flow_from_directory?

Furthermore, if augmetation is making your model worse, try smaller augmentations (e.g. stick to affine transformations with small ranges - $[-5%, +5%]$ rotation/translation/scaling).