only testing
predictions = sequence_data.nonldf.beam.test.predict
Num weight bits = 18
learning rate = 0.5
initial_t = 0
power_t = 0.5
using no cache
Reading datafile = train-sets/sequence_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  [5 4 3 2 1           ] [5 4 3 2 1  8.34465..]     0     0       24        0        0  0.000000

finished run
number of examples = 1
weighted example sum = 1.000000
weighted label sum = 0.000000
average loss = 0.000000
total feature number = 72
