Question: Consider this scenario: the loss function during a training process keeps decreasing for the training set, but it doesn't decrease at all for the testing

Consider this scenario: the loss function during a training process keeps decreasing for the training set, but it doesn't decrease at all for the testing set. Any guess why?

Overfitting

Underfitting

the training set is not a good representative of the whole data-set

The selected algorithm is not working properly

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