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If not perfect, how well can they do? For example, if I give the Seq2Seq setup a name it did not see in the training process, can it output the same name without error?

Example

name = "Will Smith"
output = DecoderRNN(EncoderRNN(name))
can_this_be_true = name == output
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If you give it a name, it will probably be almost perfect model, as the number of hidden units are definitely enough to store the raw data of a name. However as a neural network it will still not be perfect. There may also be serious overfitting if you do this. A Seq2Seq model have way more parameters than necessary to just "remembers" all the possible names, as names variants are not a lot.

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