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dtrain
======
Build & run
-----------
build ..
<pre>
git clone git://github.com/qlt/cdec-dtrain.git
cd cdec_dtrain
autoreconf -ifv
./configure
make
</pre>
and run:
<pre>
cd dtrain/hstreaming/
(edit ini files)
edit hadoop-streaming-job.sh $IN and $OUT
./hadoop-streaming-job.sh
</pre>
Ideas
-----
* *MULTIPARTITE* ranking (1 vs all, cluster model/score)
* *REMEMBER* sampled translations (merge)
* *SELECT* iteration with highest (_real_) BLEU?
* *GENERATED* data? (perfect translation in kbest)
* *CACHING* (ngrams for scoring)
* hadoop *PIPES* imlementation
* *ITERATION* variants (shuffle resulting weights, re-iterate)
* *MORE THAN ONE* reference for BLEU?
* *RANDOM RESTARTS*
* use separate TEST SET for each shard
Uncertain, known bugs, problems
-------------------------------
* cdec kbest vs 1best (no -k param), rescoring (ref?)? => ok(?)
* no sparse vector in decoder => ok/fixed
* PhraseModel_* features (0..99 seem to be generated, why 99?)
* flex scanner jams on malicious input, we could skip that
* input/grammar caching (strings, files)
FIXME
-----
merge dtrain part-* files
mapred count shard sents
250 forest sampling is real bad, bug?
kenlm not portable (i7-2620M vs Intel(R) Xeon(R) CPU E5620 @ 2.40GHz)
metric reporter of bleu for each shard
mapred chaining? hamake?
Data
----
<pre>
nc-v6.de-en peg
nc-v6.de-en.loo peg
nc-v6.de-en.giza.loo peg
nc-v6.de-en.symgiza.loo peg
nv-v6.de-en.cs peg
nc-v6.de-en.cs.loo peg
--
ep-v6.de-en.cs pe
ep-v6.de-en.cs.loo p
p: prep, e: extract, g: grammar, d: dtrain
</pre>
Experiments
-----------
grammar stats
oov on dev/devtest/test
size
#rules (uniq)
time for building
ep: 1.5 days on 278 slots (30 nodes)
nc: ~2 hours ^^^
lm stats
oov on dev/devtest/test
perplex on train/dev/devtest/test
which word alignment?
berkeleyaligner
giza++ as of Sep 24 2011, mgizapp 0.6.3
symgiza as of Oct 1 2011
---
randomly sample 100 from train.loo
run mira/dtrain for 50/60 iterations
w/o lm, wp
measure ibm_bleu on exact same sents
stability
mira: 100
pro: 100
vest: 100
dtrain: 100
pro metaparam
(max) iter
regularization
mira metaparam
(max) iter: 10 (nc???) vs 15 (ep???)
lm?
3-4-5
open
unk
nounk (-100 for unk)
--
tune or not???
lm oov weight pos?
features to try
NgramFeatures -> target side ngrams
RuleIdentityFeatures
RuleNgramFeatures -> source side ngrams from rule
RuleShape -> relative orientation of X's and terminals
SpanFeatures -> http://www.cs.cmu.edu/~cdyer/wmt11-sysdesc.pdf
ArityPenalty -> Arity=0 Arity=1 and Arity=2
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