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why get same output with different input? #29
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Hi. |
The learning rate and the optimization strategy should be carefully tuned.
I suggest using the same optimization strategy as BERT.
MELLAH Youssef <[email protected]> 于2020年6月28日周日 上午6:38写道:
… Hi.
I have the same question. I used the same code with the same dataset
(en2de).
@maozezhong <https://github.com/maozezhong> did you found the response ?
Thank you .
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Thank you very much for response. Thank you very much. |
Did you mean that the ``eval'' mode in the code does not work?
Is the model loading failed? Check the line 34-35.
By the way, a newer version of tf and keras has the similar problem.
keras-team/keras#7177
You can try to set the learning_phrase manually.
MELLAH Youssef <[email protected]> 于2020年6月28日周日 下午7:55写道:
… Thank you very much for response.
I think my question was not clear .
I'm using your code to train in the same dataSet (en2de) and the accuracy
is good . 70% in accuracy it means that the model is capable of correctly
responding to 70% of dataset inputs, but when i test the pretrained modele
(eve if with inputs from the same dataset), it gives me about the same
response !! it is normal ?
Can you share with us the pretrained model ore some uses cases of testing
it ? (from dataset inputs or other inputs)
Thank you very much.
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@lsdefine Thanks for your sharing, I use transformer to do seq2seq task. Like, input a article and predict the abstract. When I finish training, I get almost same output with different input. Code are same as your example, data should be right, because with same data, and use lstm block as seq2seq, I got the proper output.
Hope for your answer, Thanks.
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