only testing
Num weight bits = 18
learning rate = 10
initial_t = 1
power_t = 0.5
predictions = sequencespan_data.predict
switching to BILOU encoding for sequence span labeling
using no cache
Reading datafile = train-sets/sequencespan_data
num sources = 1
average    since      instance            current true      current predicted   cur   cur   predic    cache  examples          
loss       last        counter           output prefix          output prefix  pass   pol     made     hits    gener  beta    
0.000000   0.000000          1  [2 1 1 2 2 1 6 7 7 ..] [2 1 1 2 2 1 6 7 7 ..]     0     0       15        0        0  0.000000

finished run
number of examples per pass = 1
passes used = 1
weighted example sum = 1
weighted label sum = 0
average loss = 0
total feature number = 45