is there any benchmark on what value / what impact ?
what should I start with as a test 0.001 ?
the standard value 0.0001 seems really really low to me ....
maybe I am not getting what this probability exactly refers to.
where |FIELDn| is the position of the score (typically 2 for the direct
phrase probability p(e|f), or 0 for the indirect phrase probability
p(f|e)) and |THRESHOLD| the maximum probability allowed. A good setting
is |2:0.0001|, which removes all rules, where the direct phrase
translation probability is below 0.0001.
Le 31/08/2015 16:14, Philipp Koehn a écrit :
Hi,
I would suspect that with beam sizes <500 the bulk of the time is
spent on translation option collection, not decoding. You could speed
that up with tighter threshold pruning of the phrase table.
See the script scripts/training/threshold-filter.perl or the setting
score-settings = "--MinScore 2:0.0001"
in EMS.
-phi
On Mon, Aug 31, 2015 at 3:03 AM, Vincent Nguyen <[email protected]
<mailto:[email protected]>> wrote:
Hi,
Here are some results with several values with cube pruning pop
limit :
(pop limit / decoding time for 3000 sentences / BLEU score)
5000 - 15m45 - 29.59
1000 - 4m27 - 29.59
500 - 3m35 - 29.59
200 - 3m15 - 29.51
100 - 3m00 - 29.40
Therefore I took 400 - 3m19 - 29.58
If I am not mistaken the default value for Moses is 1000 [read in the
doc] but in the EMS
it is 5000 right now .... which makes the experience so long .....
I suggest to change the EMS default value.
Is there a way to also use a cube pruning limit in the decoder at
Tuning
time ?
Now with this optimized setting I get a ration of 15 segments per
second
in average.
What is the reason for online tools like Google / Bing to be much much
faster.
it's not a machine issue, is it ?
Cheers
Vincent
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