/usr/share/doc/vowpal-wabbit-doc/examples/test/train-sets/ref/topk-train.stderr is in vowpal-wabbit-doc 8.1.1-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | creating quadratic features for pairs: MF
final_regressor = topk.model
Num weight bits = 18
learning rate = 0.5
initial_t = 0
power_t = 0.5
decay_learning_rate = 1
creating cache_file = topk-train.cache
Reading datafile = train-sets/topk.vw
num sources = 1
average since example example current current current
loss last counter weight label predict features
9.000000 9.000000 1 1.0 3.0000 0.0000 4
4.590362 0.180723 2 2.0 0.0000 0.4251 4
2.946029 1.301697 4 4.0 unknown 0.2876 1
2.642688 2.339346 8 8.0 unknown 0.4184 1
1.957809 1.272931 16 16.0 unknown 0.6151 1
1.437956 0.918104 32 32.0 unknown 0.7335 1
0.935221 0.432485 64 64.0 unknown 0.8100 1
0.588329 0.241437 128 128.0 unknown 0.8650 1
0.329664 0.070998 256 256.0 unknown 0.9058 1
0.170082 0.010500 512 512.0 unknown 0.9328 1
0.085199 0.000316 1024 1024.0 unknown 0.9396 1
finished run
number of examples per pass = 12
passes used = 100
weighted example sum = 1200.000000
weighted label sum = 1500.000000
average loss = 0.072704
best constant = 1.666667
total feature number = 3900
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