C3W2 Train accuracy high but validation accuracy very low

[Deepti_Prasad]

ok your msg is bit confusing, can you first tell me which one did you use and which grade function cell you used?

check this thread

C3W2 Exercise 5 - tensors in example_batch seem to have lost their shape

true, but you are not follow architecture instructions to use atleast one hidden dense layer and then if your want to play with architecture. Anyways, your preprocess dataset codes are incorrect as well as train_val requires correction. While slicing dataset, remember the column are index as 0,1, 2 and not 1, 2, 3 so for text, it is on second column [:, 1] and labels is on first column[:, 0] You also have included index value to the train text and train labels while splitting the dataset, wh…

Also make sure your model follows the architecture instructions give in the assignment, like using the number layers and then dense output layers.

Also confirm what loss you have used categorical crossentropy or sparse categorical crossentropy??

remember here classes are divided into labels, so sparse would be the choice right?