Hi John

By default, mert employs random restarts in its search. These can be turned 
off using -predictable-seeds. Are you using random restarts?

best regards - Barry

On Thursday 24 March 2011 15:07, John Burger wrote:
> Lane Schwartz wrote:
> > I've examined the n-best lists, and it seems there are at least a
> > couple of interesting cases. In the simplest case, several
> > translations of a given sentence produce the exact same score, and
> > these tied translations appear in different order during different
> > runs. This is a bit odd, but [not] terribly worrisome. The stranger
> > case is when there are two different decoding runs, and for a given
> > sentence, there are translations that appear only in run A, and
> > different translations that only appear in run B.
>
> Both these cases are relevant to something we've occasionally seen,
> which is non-determinism during =tuning=.  This is not surprising
> given the above, since tuning of course involves decoding.  It's hard
> to reproduce, but we have sometimes seen very different weights coming
> out of MERT for the exact same system configurations.  The problem
> here is that even very small differences in tuning can result in
> substantial differences in test results, because of how twitchy BLEU is.
>
> Like many folks, we typically run MERT on a cluster.  This brings up
> another source of non-determinism we've theorized about.  Some of our
> clusters are heterogenous, and we've wondered if there might be minor
> differences in floating point behavior from machine to machine.  The
> assignment of different chunks of the tuning data to different
> machines is typically non-deterministic, so this might carry over to
> the actual weights that come out of MERT.
>
> Does anyone know how robust the floating point usage in the decoder is
> under these circumstances?
>
> Thanks.
>
> - John Burger
>    MITRE
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