Are long sentences not good for deep learning models?
Interested to know if long sentences are good for tensor2tensor model training. And why or why not?
tensorflow tensorflow-datasets tensor2tensor
asked yesterday
echan00echan00
1,1741819
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Interested to know if long sentences are good for tensor2tensor model training. And why or why not?
tensorflow tensorflow-datasets tensor2tensor
asked yesterday
echan00echan00
1,1741819
add a comment |
Interested to know if long sentences are good for tensor2tensor model training. And why or why not?
tensorflow tensorflow-datasets tensor2tensor
asked yesterday
echan00echan00
1,1741819
Interested to know if long sentences are good for tensor2tensor model training. And why or why not?
tensorflow tensorflow-datasets tensor2tensor
tensorflow tensorflow-datasets tensor2tensor
asked yesterday
echan00echan00
1,1741819
asked yesterday
echan00echan00
1,1741819
asked yesterday
echan00echan00
1,1741819
asked yesterday
echan00echan00
1,1741819
asked yesterday
echan00echan00
1,1741819
1,1741819
add a comment |
add a comment |
1 Answer
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Ideally, the training data should have the same distribution of sentence lengths as the target test data. E.g. in machine translation, if long sentences are intended to be translated by the final model, similarly long sentences should be used also for training. The Transformer model seems to not generalize to longer sentences than were used for training, but limiting the maximum sentence length in training allows to use higher batch sizes, which is helpful (Popel and Bojar, 2018).
answered yesterday
Martin PopelMartin Popel
2,372620
thanks very useful link
– echan00
yesterday
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Ideally, the training data should have the same distribution of sentence lengths as the target test data. E.g. in machine translation, if long sentences are intended to be translated by the final model, similarly long sentences should be used also for training. The Transformer model seems to not generalize to longer sentences than were used for training, but limiting the maximum sentence length in training allows to use higher batch sizes, which is helpful (Popel and Bojar, 2018).
answered yesterday
Martin PopelMartin Popel
2,372620
thanks very useful link
– echan00
yesterday
add a comment |
Ideally, the training data should have the same distribution of sentence lengths as the target test data. E.g. in machine translation, if long sentences are intended to be translated by the final model, similarly long sentences should be used also for training. The Transformer model seems to not generalize to longer sentences than were used for training, but limiting the maximum sentence length in training allows to use higher batch sizes, which is helpful (Popel and Bojar, 2018).
answered yesterday
Martin PopelMartin Popel
2,372620
thanks very useful link
– echan00
yesterday
add a comment |
Ideally, the training data should have the same distribution of sentence lengths as the target test data. E.g. in machine translation, if long sentences are intended to be translated by the final model, similarly long sentences should be used also for training. The Transformer model seems to not generalize to longer sentences than were used for training, but limiting the maximum sentence length in training allows to use higher batch sizes, which is helpful (Popel and Bojar, 2018).
answered yesterday
Martin PopelMartin Popel
2,372620
Ideally, the training data should have the same distribution of sentence lengths as the target test data. E.g. in machine translation, if long sentences are intended to be translated by the final model, similarly long sentences should be used also for training. The Transformer model seems to not generalize to longer sentences than were used for training, but limiting the maximum sentence length in training allows to use higher batch sizes, which is helpful (Popel and Bojar, 2018).
answered yesterday
Martin PopelMartin Popel
2,372620
answered yesterday
Martin PopelMartin Popel
2,372620
answered yesterday
Martin PopelMartin Popel
2,372620
answered yesterday
Martin PopelMartin Popel
2,372620
2,372620
thanks very useful link
– echan00
yesterday
add a comment |
thanks very useful link
– echan00
yesterday
thanks very useful link
– echan00
yesterday
thanks very useful link
– echan00
yesterday
add a comment |
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