Hi Barry,
it turns out that me too have succeeded to build my model in one day. I
forced a restart and checked the log and the working directory. All is
fine! The moses.ini file was created only 7 hours after submitting the
command to build the model. I don't understand why the computer didn't
respond, though.

How does the time to build a model vary with the size of the corpus?
Linearly? Or quadratic? Or what?

I've now tried to do a test translation, without any tuning. I soon ran
out of memory: even the virtual memory was exhausted after a while. Any
way to predict the memory needed?

Yours,
Per Tunedal


On Sun, Mar 10, 2013, at 11:39, Barry Haddow wrote:
> Hi Per
> 
> I would suggest starting from a smallish corpus, then building up to a
> larger one, to get experience with the process. Using the news commentary
> corpus described in the Moses baseline page, I was able to train and tune
> in an evening on my laptop.
> 
> There have been papers on predicting quality given corpus size, but
> there's not an easy answer. Look for Marco Turchi at last year's EAMT, or
> (I think) one by Xerox Grenoble from last year.
> 
> As regards europarl, yes there's noise, but the models are quite robust
> to it
> 
> Cheers - Barry
> 
> Per Tunedal <[email protected]> wrote:
> 
> >Hi,
> >Is there any way to predict the time for training and/or tuning, given
> >the corpus size and the computer specifications? It would be nice to
> >know  what would be a reasonable time for accomplishing the tasks. Now
> >my computer has been running for 3 days and nights and doesn't respond
> >any more: I cannot "wake it" to see what's going on. I don't know if
> >it's normal or if something has gone havoc.
> >
> >I agree with Ken Fasano, that it would be very useful to know how big a
> >corpus is needed to get meaningful results. I would like to be able to
> >judge the quality of the translation, to see if it would be useful to
> >continue with Moses in some more serious manner.
> >
> >I'm a bit puzzled by the parameter limiting sentence length to, say 80
> >(characters?), giving that e.g. the Europarl corpus contains mainly VERY
> >long sentences. Skipping long sentences probably implicates that many
> >typical expressions are lost in the model. Wouldn't it be more sensible
> >to skip short sentences? Or to make a representative sample of the
> >corpus, by doing a random sample of a sufficient size or something?
> >Yours,
> >Per Tunedal
> >
> >PS I've noticed that the Europarl corpus contains some very bad,
> >completely incomprehensible, translations. That makes me question the
> >quality of that corpus. How are the translations actually done? By
> >humans relying heavily on machine translation? Sometimes letting some
> >strange MT-translation pass?
> >
> >On Sat, Mar 9, 2013, at 18:43, Ken Fasano wrote:
> >> I'd like to respond to this thread. I, too, have limited resources (at
> >> work, at least) - a 3 GB RAM 32-bit Windows i5 machine with Linux running
> >> on VMWare with 2.5 GB RAM. Training and tuning take many hours; the
> >> machine is running BitParl over the weekend and may be done with
> >> NewsCommentary de-en (DE) on Monday when I get back to work. I'm afraid
> >> after all that I won't be able to subsequently run Collins on the
> >> English, train, tune, and decode all that and, even if it takes forever,
> >> expect it to run with the limited memory resources available.
> >> What I think I need to do is trim the corpora according to some criteria
> >> that isn't too complicated. Is it enough for learning purposes (we are a
> >> long way from any sort of real comparison of results, let alone
> >> production - this will receive proper hardware) to take the first n
> >> sentences, or every nth sentence? The result is simply to get a feel for
> >> the various modes of tree-based SMT, run hierarchical phrase,
> >> string-to-tree, tree-to-string and tree-to-tree without worrying which
> >> one is the best - the idea is just to get some experience with it.What
> >> would be a good number of sentences to take so that it runs relatively
> >> quickly, without killing RAM, but produces results that aren't useless?
> >> Thanks - and I'd like to thank everyone on the group for their eager
> >> helpfulness, and for discussing things that I as a newbie find very
> >> useful!
> >> 
> >> 
> >> 
> >> 
> >> > Date: Sat, 9 Mar 2013 11:25:45 -0500
> >> > From: [email protected]
> >> > To: [email protected]
> >> > Subject: Re: [Moses-support] Accelerate the tuning
> >> > 
> >> > Hi,
> >> > 
> >> >  It won't fix everything, but there is a long-term TODO to rewrite 
> >> > phrase table scoring to use binary files with vocabulary ids instead of 
> >> > text files.
> >> > 
> >> > Kenneth
> >> > 
> >> > On 03/09/13 08:30, Per Tunedal wrote:
> >> > >
> >> > > Hi,
> >> > > the training seems to be an overwhelming task for my computer. If it
> >> > > ever succeeds, I will have to undertake the even more demanding task of
> >> > > tuning. Can anything be done to accelerate it?
> >> > >
> >> > > Specifically, I wonder if it's feasible to prune the translation table
> >> > > before doing the tuning.
> >> > >
> >> > > Yours,
> >> > > Per Tunedal
> >> > >
> >> > > PS I've abandoned the idea of building a Hierarchical phrase model, I'm
> >> > > now trying to make a phrase-based system. I suppose that would use less
> >> > > resources.
> >> > >
> >> > > _______________________________________________
> >> > > Moses-support mailing list
> >> > > [email protected]
> >> > > http://mailman.mit.edu/mailman/listinfo/moses-support
> >> > >
> >> > _______________________________________________
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> 
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