Submitted by redditnit21 t3_y5qn9h in deeplearning
_Arsenie_Boca_ t1_isnyhtb wrote
You should test if this happens only during training or also when evaluating on the train set afterwards. As others have mentioned, dropout could be a possible factor. But you should also consider that the train accuracy is calculated during the training process, while the model is still learning. I.e. the final weights are not reflected in the average train acc.
No_Slide_1942 t1_isnylz0 wrote
It’s also happening without dropout.
_Arsenie_Boca_ t1_isnytx5 wrote
If the performance on the train set after training is better than during training, its simply due to the fact that train acc is usually calculated while the model is still learning.
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