MLcomp version alpha Statistics: 1208 users, 401 datasets, 328 programs, 9937 runs (0 queued, 0 running), 0 workers

Run 7359

Creator	favre
Program	crfpp
Dataset	ner-ester1-fra
Task type	SequenceTagging
Created	1y122d ago

Status: Failed!

Note: this page autoupdates while a run is in progress

Reason	(see end of log file)
Total Time	3m3s
Max Memory Usage	603M
Domain:	SequenceTagging
Learn time
Train acc.
Train F1
Predict train time
Test acc.
Test F1
Predict test time

Log file

===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
CRF++: Yet Another CRF Tool Kit
Copyright (C) 2005-2009 Taku Kudo, All rights reserved.

reading training data: 100.. 200.. 300.. 400.. 500.. 600.. 700.. 800.. 900.. 1000.. 1100.. 1200.. 1300.. 1400.. 1500.. 1600.. 1700.. 1800.. 1900.. 2000.. 2100.. 2200.. 2300.. 2400.. 2500.. 2600.. 2700.. 2800.. 2900.. 3000.. 3100.. 3200.. 3300.. 3400.. 3500.. 3600.. 3700.. 3800.. 3900.. 4000.. 4100.. 4200.. 4300.. 4400.. 4500.. 4600.. 4700.. 4800.. 4900.. 5000.. 5100.. 5200.. 5300.. 5400.. 5500.. 5600.. 5700.. 5800.. 5900.. 6000.. 6100.. 6200.. 6300.. 6400.. 6500.. 6600.. 6700.. 6800.. 6900.. 7000.. 7100.. 7200.. 7300.. 7400.. 7500.. 7600.. 7700.. 7800.. 7900.. 8000.. 8100.. 8200.. 8300.. 8400.. 8500.. 8600.. 8700.. 8800.. 8900.. 9000.. 9100.. 9200.. 9300.. 9400.. 9500.. 9600.. 9700.. 9800.. 9900.. 10000.. 10100.. 10200.. 10300.. 10400.. 10500.. 10600.. 10700.. 10800.. 10900.. 11000.. 11100.. 11200.. 11300.. 11400.. 11500.. 11600.. 11700.. 11800.. 11900.. 12000.. 12100.. 12200.. 12300.. 12400.. 12500.. 12600.. 12700.. 12800.. 12900.. 13000.. 13100.. 13200.. 13300.. 13400.. 13500.. 13600.. 13700.. 13800.. 13900.. 14000.. 14100.. 14200.. 14300.. 14400.. 14500.. 14600.. 14700.. 14800.. 14900.. 15000.. 15100.. 15200.. 15300.. 15400.. 15500.. 15600.. 15700.. 15800.. 15900.. 16000.. 16100.. 16200.. 16300.. 16400.. 16500.. 16600.. 16700.. 16800.. 16900.. 17000.. 17100.. 17200.. 17300.. 17400.. 17500.. 17600.. 17700.. 17800.. 17900.. 18000.. 18100.. 18200.. 18300.. 18400.. 18500.. 18600.. 18700.. 18800.. 18900.. 19000.. 19100.. 19200.. 19300.. 19400.. 19500.. 19600.. 19700.. 19800.. 19900.. 20000.. 20100.. 20200.. 20300.. 20400.. 20500.. 20600.. 20700.. 20800.. 20900.. 21000.. 21100.. 21200.. 21300.. 21400.. 21500.. 21600.. 21700.. 21800.. 21900.. 22000.. 22100.. 22200.. 22300.. 22400.. 22500.. 22600.. 22700.. 22800.. 22900.. 23000.. 23100.. 23200.. 23300.. 23400.. 23500.. 23600.. 23700.. 23800.. 23900.. 24000.. 24100.. 24200.. 24300.. 24400.. 24500.. 24600.. 24700.. 24800.. 24900.. 25000.. 25100.. 25200.. 25300.. 25400.. 25500.. 25600.. 25700.. 25800.. 25900.. 26000.. 26100.. 26200.. 26300.. 26400.. 26500.. 26600.. 26700.. 26800.. 26900.. 27000.. 27100.. 27200.. 27300.. 27400.. 27500.. 27600.. 27700.. 27800.. 27900.. 28000.. 28100.. 28200.. 28300.. 28400.. 28500.. 28600.. 28700.. 28800.. 28900.. 29000.. 29100.. 29200.. 29300.. 29400.. 29500.. 29600.. 29700.. 29800.. 29900.. 30000.. 30100.. 30200.. 30300.. 30400.. 30500.. 30600.. 30700.. 30800.. 30900.. 31000.. 31100.. 31200.. 31300.. 31400.. 31500.. 31600.. 31700.. 31800.. 31900.. 32000.. 32100.. 32200.. 32300.. 32400.. 32500.. 32600.. 32700.. 32800.. 32900.. 33000.. 33100.. 33200.. 33300.. 33400.. 33500.. 33600.. 33700.. 33800.. 33900.. 34000.. 34100.. 34200.. 34300.. 34400.. 34500.. 34600.. 34700.. 34800.. 34900.. 35000.. 35100.. 35200.. 35300.. 35400.. 35500.. 35600.. 35700.. 35800.. 35900.. 36000.. 36100.. 36200.. 36300.. 36400.. 36500.. 36600.. 36700.. 36800.. 36900.. 37000.. 37100.. 37200.. 37300.. 37400.. 37500.. 37600.. 37700.. 37800.. 37900.. 38000.. 38100.. 38200.. 38300.. 38400.. 38500.. 38600.. 38700.. 38800.. 38900.. 39000.. 39100.. 39200.. 39300.. 39400.. 39500.. 39600.. 39700.. 39800.. 39900.. 40000.. 40100.. 40200.. 40300.. 40400.. 40500.. 40600.. 40700.. 40800.. 40900.. 41000.. 41100.. 41200.. 41300.. 41400.. 41500.. 41600.. 41700.. 
Done!37.52 s

Number of sentences: 41715
Number of features:  17467023
Number of thread(s): 1
Freq:                1
eta:                 0.00010
C:                   1.00000
shrinking size:      20
iter=0 terr=0.99646 serr=0.99995 act=17467023 obj=2978188.13875 diff=1.00000
terminate called after throwing an instance of 'std::bad_alloc'
  what():  St9bad_alloc
./run:13: Failed (RuntimeError)
=== END program1: ./run learn ../dataset2/train --- FAILED [185s]

Run specification

• supervised-learning: Main entry for supervised learning for training and testing a program on a dataset.
  • (learner:Program) crfpp: Yet Another CRF toolkit (http://crfpp.sourceforge.net)
  • (dataset:Dataset) ner-ester1-fra: Named entity recognition on French broadcast news transcripts. All lower case, no punctuation. For more information: "The ESTER evaluation campaign of rich transcription of french broadcast news", Gravier et al., LREC 2004.
  • (stripper:Program[Strip]) sequence-conll-utils: Validates and inspects SequenceTagging (CoNLL Shared Task) datasets.
  • (evaluator:Program[Evaluate]) sequence-conll-evaluator: Evaluator for SequenceTagging.

Results

• exitCode: 1
• learn:
  • success: false
  • time: 185
• success: false

Comments: