Hieu Hoang http://www.hoang.co.uk/hieu
On 1 August 2016 at 20:40, Bogdan Vasilescu <vasile...@gmail.com> wrote: > Thanks Hieu, > > It runs out of memory around 3,000 sentences when n-best is the > default 100. It seems to do a little bit better if I set n-best to 10 > (5,000 sentences or so). The machine I'm running this on has 192 GB > RAM. I'm using the binary moses from > http://www.statmt.org/moses/RELEASE-3.0/binaries/linux-64bit/ > > My phrase table was built on 1,200,000 sentences (phrase length at > most 20). My language model is a 5-gram, built on close to 500,000,000 > sentences. > i can't why is would run out of memory. If you can make you model avaiable for download and tell me the exact command you ran, maybe I can try to replicate it > > Still, the question remains. Is there a way to perform tuning > incrementally? > i think what you proposed is doable. I don't know whether it would improve over the baseline > > I'm thinking: > - tune on a sample of my original tuning corpora; this generates an > updated moses.ini, with "better" weights > - use this moses.ini as input for a second tuning phase, on another > sample of my tuning corpora > - repeat until there is convergence in the weights > > Bogdan > > > On Mon, Aug 1, 2016 at 11:43 AM, Hieu Hoang <hieuho...@gmail.com> wrote: > > > > > > Hieu Hoang > > http://www.hoang.co.uk/hieu > > > > On 29 July 2016 at 18:57, Bogdan Vasilescu <vasile...@gmail.com> wrote: > >> > >> Hi, > >> > >> I've trained a model and I'm trying to tune it using mert-moses.pl. > >> > >> I tried different size tuning corpora, and as soon as I exceed a > >> certain size (this seems to vary between consecutive runs, as well as > >> with other tuning parameters like --nbest), the process gets killed: > > > > it should work with any size tuning corpora. The only thin I can think > of is > > if the tuning corpora is very large (1,000,000 sentences say) or the > n-best > > list is very large (1,000,000 say) then the decoder or the mert script > may > > use a lot of memory > >> > >> > >> Killed > >> Exit code: 137 > >> The decoder died. CONFIG WAS -weight-overwrite ... > >> > >> Looking into the kernel logs in /var/log/kern.log suggests I'm running > >> out of memory: > >> > >> kernel: [98464.080899] Out of memory: Kill process 15848 (moses) score > >> 992 or sacrifice child > >> kernel: [98464.080920] Killed process 15848 (moses) > >> total-vm:414130312kB, anon-rss:194915316kB, file-rss:0kB > >> > >> Is there a way to perform tuning incrementally? > >> > >> I'm thinking: > >> - tune on a sample of my original tuning corpora; this generates an > >> updated moses.ini, with "better" weights > >> - use this moses.ini as input for a second tuning phase, on another > >> sample of my tuning corpora > >> - repeat until there is convergence in the weights > >> > >> Would this work? > >> > >> Many thanks in advance, > >> Bogdan > >> > >> -- > >> Bogdan (博格丹) Vasilescu > >> Postdoctoral Researcher > >> Davis Eclectic Computational Analytics Lab > >> University of California, Davis > >> http://bvasiles.github.io > >> http://decallab.cs.ucdavis.edu/ > >> @b_vasilescu > >> > >> _______________________________________________ > >> Moses-support mailing list > >> Moses-support@mit.edu > >> http://mailman.mit.edu/mailman/listinfo/moses-support > > > > > > > > -- > Bogdan (博格丹) Vasilescu > Postdoctoral Researcher > Davis Eclectic Computational Analytics Lab > University of California, Davis > http://bvasiles.github.io > http://decallab.cs.ucdavis.edu/ > @b_vasilescu >
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