Just remove steps/1/TUNING_tune.1.DONE (replacing 1 with your experiment
id) and then re-run.
It would be nice if EMS supported multiple tuning runs without
intervention, but afaik it doesn't.
On 22/06/15 16:15, Lane Schwartz wrote:
Given a successful run of EMS, what do I need to do to
Given a successful run of EMS, what do I need to do to configure a new run
that re-uses all of the training, but re-runs tuning?
Thanks,
Lane
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Hi I delete all the files (I think) generated during a training job before
rerunning the entire training. You think this could cause variation? Here's
the commands I run to delete:
rm ~/corpus/train.tok.en
rm ~/corpus/train.tok.sm
rm ~/corpus/train.true.en
rm ~/corpus/train.true.sm
rm
That would make very cool student projects.
Also that video is acing it, even the voice-over is synthetic :)
On 23.06.2015 00:27, Ondrej Bojar wrote:
...and I wouldn't be surprised to find Moses also behind this Java-to-C#
automatic translation:
https://www.youtube.com/watch?v=CHDDNnRm-g8
I don't think so. However, when you repeat those experiments, you might
try to identify where two trainings are starting to diverge by pairwise
comparisions of the same files between two runs. Maybe then we can
deduce something.
On 23.06.2015 00:25, Hokage Sama wrote:
Hi I delete all the
Ok will do
On 22 June 2015 at 17:47, Marcin Junczys-Dowmunt junc...@amu.edu.pl wrote:
I don't think so. However, when you repeat those experiments, you might
try to identify where two trainings are starting to diverge by pairwise
comparisions of the same files between two runs. Maybe then we
Hi,
I think the average is OK, your variance is however quite high. Did you
retrain the entire system or just optimize parameters a couple of times?
Two useful papers on the topic:
https://www.cs.cmu.edu/~jhclark/pubs/significance.pdf
http://www.mt-archive.info/MTS-2011-Cettolo.pdf
On
Hm. That's interesting. The language should not matter.
1) Do not report results without tuning. They are meaningless. There is
a whole thread on that, look for Major bug found in Moses. If you
ignore the trollish aspects it contains may good descriptions why this
is a mistake.
2) Assuming it
Thanks Marcin. Its for a new resource-poor language so I only trained it
with what I could collect so far (i.e. only 190,630 words of parallel
data). I retrained the entire system each time without any tuning.
On 22 June 2015 at 01:00, Marcin Junczys-Dowmunt junc...@amu.edu.pl wrote:
Hi,
I
Difficult to tell with that little data. Once you get beyond 100,000
segments (or 50,000 at least) i would say 2000 per dev (for tuning) and
test set, rest for training. With that few segments it's hard to give
you any recommendations since it might just not give meaningful results.
It's
You're welcome. Take another close look at those varying bleu scores
though. That would make me worry if it happened to me for the same data
and the same weights.
On 22.06.2015 10:31, Hokage Sama wrote:
Ok thanks. Appreciate your help.
On 22 June 2015 at 03:22, Marcin Junczys-Dowmunt
Ok thanks. Appreciate your help.
On 22 June 2015 at 03:22, Marcin Junczys-Dowmunt junc...@amu.edu.pl wrote:
Difficult to tell with that little data. Once you get beyond 100,000
segments (or 50,000 at least) i would say 2000 per dev (for tuning) and
test set, rest for training. With that few
Yes the language model was built earlier when I first went through the
manual to build a French-English baseline system. So I just reused it for
my Samoan-English system.
Yes for all three runs I used the same training and testing files.
How can I determine how much parallel data I should set
Ok I will.
On 22 June 2015 at 03:35, Marcin Junczys-Dowmunt junc...@amu.edu.pl wrote:
You're welcome. Take another close look at those varying bleu scores
though. That would make me worry if it happened to me for the same data and
the same weights.
On 22.06.2015 10:31, Hokage Sama wrote:
Wow that was a long read. Still reading though :) but I see that tuning is
essential. I am fairly new to Moses so could you please check if the
commands I ran were correct (minus the tuning part). I just modified the
commands on the Moses website for building a baseline system. Below are the
Don't see any reason for indeterminism here. Unless mgiza is less stable
for small data than I thought. The lm lm/news-commentary-v8.fr-en.blm.en
has been built earlier somewhere?
And to be sure: for all three runs you used exactly the same data,
training and test set?
On 22.06.2015 09:34,
Ok my scores don't vary so much when I just run tokenisation, truecasing,
and cleaning once. Found some differences beginning from the truecased
files. Here are my results now:
BLEU = 16.85, 48.7/21.0/11.7/6.7 (BP=1.000, ratio=1.089, hyp_len=3929,
ref_len=3609)
BLEU = 16.82, 48.6/21.1/11.6/6.7
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