How do we train a seq2seq rnn training?
We input a sentence that needs to be translated. We encode it sequentially. Then the first decoder outputs the first word with probabilities. We do a gradient descent by comparing them with the actual word expected. Then we input to the second decoder the hidden state and it outputs the second word with probabilities. We do another gradient descent. But what if the first hidden state was wrong because it failed to output the right word? Then this second gradient descent is meaningless?