diff options
Diffstat (limited to 'dtrain')
| -rw-r--r-- | dtrain/README.md | 44 | 
1 files changed, 34 insertions, 10 deletions
| diff --git a/dtrain/README.md b/dtrain/README.md index ea9997ee..b1dbf481 100644 --- a/dtrain/README.md +++ b/dtrain/README.md @@ -33,6 +33,8 @@ Ideas  * use separate *TEST SET* for each shard  * *REDUCE* training set (50k?)  * *SYNTAX* features (CD) +* distribute *DEV* set to all nodes, avg +  Uncertain, known bugs, problems  ------------------------------- @@ -46,25 +48,31 @@ Uncertain, known bugs, problems  FIXME, todo  ----------- -* merge dtrain part-X files, for better blocks +* merge dtrain part-X files, for better blocks (how to do this with 4.5tb ep)  * mapred count shard sents +* mapred stats for learning curve (output weights per iter for eval on devtest)  * 250 forest sampling is real bad, bug?  * metric reporter of bleu for each shard  * kenlm not portable (i7-2620M vs Intel(R) Xeon(R) CPU E5620 @ 2.40GHz)  * mapred chaining? hamake? +* make our sigtest work with cdec +* l1l2 red +* tsuroke?  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 +nc-v6.de-en             apegd +nc-v6.de-en.loo         apegd +nc-v6.de-en.giza        apegd +nc-v6.de-en.giza.loo    apegd +nc-v6.de-en.cs.giza     apegd +nc-v6.de-en.cs.giza.loo apegd +nv-v6.de-en.cs          apegd +nc-v6.de-en.cs.loo      apegd  -- -ep-v6.de-en.cs          pe -ep-v6.de-en.cs.loo      p +ep-v6.de-en.cs          apegd +ep-v6.de-en.cs.loo      apegd  a: alignment:, p: prep, e: extract,  g: grammar, d: dtrain @@ -82,7 +90,7 @@ Experiments   lm stats    oov on dev/devtest/test  -  perplex on train/dev/devtest/test] +  perplex on train/dev/devtest/test?]  [0]  which word alignment? @@ -96,6 +104,7 @@ which word alignment?   run dtrain for 100 iterations   w/o all other feats (lm, wp, ...) +Glue   measure ibm bleu on exact same sents + ep -> berkeleyaligner ??? (mb per sent, rules per sent)  [1]  lm? @@ -126,6 +135,7 @@ stability   dtrain: 100  [undecided] +do we even need loo for ep?  pro metaparam   (max) iter   regularization @@ -142,4 +152,18 @@ features to try   SpanFeatures -> http://www.cs.cmu.edu/~cdyer/wmt11-sysdesc.pdf   ArityPenalty -> Arity=0 Arity=1 and Arity=2 +--- +variables to control + +[alignment] + +[lm] + +[vest] + +[mira] + +[dtrain] + +[pro] | 
