Hi, thanks for your kind advice. I plan to use the tuning command displayed at the Baseline page: nohup nice ~/mosesdecoder/scripts/training/mert-moses.pl ~/corpus/news-test2008.true.fr ~/corpus/news-test2008.true.en \ ~/mosesdecoder/bin/moses train/model/moses.ini --mertdir ~/mosesdecoder/bin/ &> mert.out & with my own "small" tuning-corpus (10% of the training-corpus size).
Will this "give [the tuning script] a binariser" ? If not, what shall I add to the command? Yours, Per Tunedal On Mon, Mar 11, 2013, at 16:00, Barry Haddow wrote: > Hi Per > > The tuning script will filter the phrase table (leaving only the entries > required for the tuning set) and then binarise it (if you give it a > binariser) before running the actual tuning. So no, the whole table > doesn't need to be loaded into memory during tuning. > > You could prune before tuning, and I don't know how this will compare to > pruning after tuning. I'm not sure if anyone has tried it. The > signifcance filtering (in advanced features) works (afaik), although > there are a few steps involved in building the code. The relent > filtering has bit-rotted a bit, but you can run it with Moses v0.91. > > cheers - Barry > > On 11/03/13 14:37, Per Tunedal wrote: > > Hi Barry, > > Binarise, yes. But before that I plan to prune the translation table > > (Advanced features). Any hints? > > > > Back to my original question, can pruning be done before tuning? Is it > > possible to binarise too, before tuning? (The base-line page suggests > > binarisiation after tuning.) I fear that the tuning might be an > > overwhelming task for my poor computer. > > > > Yours, > > Per Tunedal > > > > BTW What is actually done when tuning? Has all the tables to be loaded > > into memory? > > > > On Mon, Mar 11, 2013, at 10:42, Barry Haddow wrote: > >> Hi Per > >> > >> You need to binarise the models (phrase table, reordering table and > >> language model) before running Moses > >> http://www.statmt.org/moses/?n=Moses.AdvancedFeatures#ntoc3 > >> If you don't binarise then Moses will load all the tables into memory, > >> so the memory requirement will be at least as large as the on-disk size, > >> in fact a lot more since it doesn't store them efficiently. > >> > >> The complexity of training is not easy to calculate since there are a > >> number of steps, but since one step involves sorting the list of > >> extracted phrases the complexity must be at least as bad as that. > >> > >> cheers - Barry > >> > >> On 11/03/13 08:24, Per Tunedal wrote: > >>> 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 > >>>>>>>> > >>>>>>> _______________________________________________ > >>>>>>> Moses-support mailing list > >>>>>>> [email protected] > >>>>>>> http://mailman.mit.edu/mailman/listinfo/moses-support > >>>>>> > >>>>>> _______________________________________________ > >>>>>> Moses-support mailing list > >>>>>> [email protected] > >>>>>> http://mailman.mit.edu/mailman/listinfo/moses-support > >>>>> _______________________________________________ > >>>>> Moses-support mailing list > >>>>> [email protected] > >>>>> http://mailman.mit.edu/mailman/listinfo/moses-support > >>>>> > >>>> -- > >>>> The University of Edinburgh is a charitable body, registered in > >>>> Scotland, with registration number SC005336. > >>>> > >>> _______________________________________________ > >>> Moses-support mailing list > >>> [email protected] > >>> http://mailman.mit.edu/mailman/listinfo/moses-support > >>> > >> > >> -- > >> The University of Edinburgh is a charitable body, registered in > >> Scotland, with registration number SC005336. > >> > > _______________________________________________ > > Moses-support mailing list > > [email protected] > > http://mailman.mit.edu/mailman/listinfo/moses-support > > > > > -- > The University of Edinburgh is a charitable body, registered in > Scotland, with registration number SC005336. > _______________________________________________ Moses-support mailing list [email protected] http://mailman.mit.edu/mailman/listinfo/moses-support
