About Overfitting in DL (indulge me..)

[ste (Stefano Giomo)]

Interesting question! Probably the fast.ai way is try both of them and ensemble or choose the one that have better performance on your Test data (we’re assuming that your Test distribution is different from Train and Valid, otherwise both models should performs good) .
…Eventually you’ve to guess the test distribution!

BTW to me this is Jeremy’s best quote of DL3-Part1

@balnazzar

You will see a lot of people, even people that claim to understand machine learning, tell you that if your training loss is lower than your validation loss, then you are overfitting. As you will learn today in more detail and during the rest of course, that is absolutely not true .