Hi Vito
Yes, that's basically what happens, and you're right that
"tuneable=false" can be harmful to MERT - hence my warning. I've heard
of people trying to keep the weights of a language model fixed through
it, and this didn't work at all.
MERT (but not MIRA) also supports the option "-o" to define which
features to optimize, and mert-moses.perl accepts the option
"--activate-features" to do the same (it then passes the list of
features to MERT). This may be more suitable for some cases.
Code contributions for a better way of having fixed weights (that also
works for PRO and MIRA) are welcome.
best wishes,
Rico
On 22.05.2015 17:07, Vito Mandorino wrote:
Thank you all. Can you explain further what does it mean that MERT
won't know that the feature exists? Does that mean that the tuneable
feature weights are optimized assuming that all non-tuneable feature
weights are equal to zero?
In fact, in my understanding this should lead to a dramatic decrease
of the score Bleu on the tuning set, but this is not what I ended up
with in my tests, at least in some cases (decrease of just 0.19 Bleu
when adding tuneable=false to PhrasePenalty and Distortion on a tuning
set constituted by 574 segments).
Vito M.
2015-05-20 14:38 GMT+02:00 Rico Sennrich <rico.sennr...@gmx.ch
<mailto:rico.sennr...@gmx.ch>>:
Matthias Huck <mhuck@...> writes:
>
> Hi Vito,
>
> tuneable=false should work.
Just my usual caveat:
if you use 'tuneable=false', the feature score(s) won't be
reported to the n-best list, and MERT/MIRA/PRO won't even know
that the
feature exists. This is appropriate in some cases (keeping a
feature weight
at 0, or giving a high penalty to some glue rules to ensure that
they are
only used if no translation is possible without them), but in
other cases,
hiding important features causes the optimizer to search the wrong
space.
best wishes,
Rico
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