Data augmentation will help prevent your model from overfitting a bit but the amount of useful information you get from naively augmented data will reach diminishing returns at some point.
Data augmentation alone (e.g. rotations / shift / crops / color perturbations / cutout... of a single photo of an husky dog) will never yield the added information that is contained in new pictures showing subtle variations of the phenomenom your are trying to model (e.g. a new photo of a Dalmatian dog if you have no Dalmatian dogs in your original training set).
Data augmentation alone (e.g. rotations / shift / crops / color perturbations / cutout... of a single photo of an husky dog) will never yield the added information that is contained in new pictures showing subtle variations of the phenomenom your are trying to model (e.g. a new photo of a Dalmatian dog if you have no Dalmatian dogs in your original training set).