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I have seen many articles that used EfficientNetB0 as their baseline model, but I never saw anyone used EfficientNetB7 yet. From the EfficientNet Github page (https://github.com/qubvel/efficientnet) I saw that EfficientNetB7 achieved a very high accuracy result. Why doesn't everyone just use EfficientNetB7? Is it because of the memory limit or is there any other consideration to use EfficientNetB0?

Sacchirro
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  • FWIW the link in the question is for a subsequent reimplementation of EfficientNet in Keras, in turn it references the official source of EfficientNet https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet – JulianHarty Mar 03 '23 at 00:44

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A baseline is the result of a very basic model or approach to a problem. It is used to compare performance of more complex methods such as larger models, feature engineering or data augmentation.

EfficientNetB0 is used as it is a reliable model for somewhat good accuracy and because it is fast to train due to a low number of parameters.

Using EfficentNetB7 could serve as a baseline model, however when testing non-architecture related changes, such as data augmentation as mentioned earlier, retraining the large network will take longer slowing down your iteration speed.

Max van Dijck
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