KKKcat:

Because I remember in order to prevent overfitting, we should choose the smallest test loss. However, in this tutorial, the author picks the greatest eval acc instead of smallest test loss.


In the common use case you won’t see the test loss until you finalize the model training and calculate the test loss/accuracy once. If you use the test loss for e.g. early stopping this would be considered a data leak and the model would perform worse during its deployment and usage of new data.