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. Still, the question remains. 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 Bogdan On Mon, Aug 1, 2016 at 11:43 AM, Hieu Hoang <[email protected]> wrote: > > > Hieu Hoang > http://www.hoang.co.uk/hieu > > On 29 July 2016 at 18:57, Bogdan Vasilescu <[email protected]> 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 >> [email protected] >> 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 _______________________________________________ Moses-support mailing list [email protected] http://mailman.mit.edu/mailman/listinfo/moses-support
