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result.txt
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result.txt
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#CNN Models
python train.py --model_architecture cnn --model_size_info 28 10 4 1 1 30 10 4 2 1 16 128 --dct_coefficient_count 10 --window_size_ms 40 --window_stride_ms 20 --learning_rate 0.0005,0.0001,0.00002 --how_many_training_steps 10000,10000,10000 --summaries_dir work/CNN/CNN1/retrain_logs --train_dir work/CNN/CNN1/training
I0114 03:06:28.241665 4540917184 train.py:245] Step #30000: rate 0.000020, accuracy 92.00%, cross entropy 0.193838
INFO:tensorflow:Confusion Matrix:
[[389 0 0 0 0 0 0 0 0 0 0 0]
[ 2 311 5 12 5 10 10 10 13 2 3 6]
[ 1 2 397 3 0 2 5 1 0 0 1 0]
[ 0 1 3 363 0 12 3 0 1 1 6 7]
[ 0 4 0 2 352 1 4 2 2 14 6 2]
[ 0 12 3 7 2 386 1 0 1 0 2 4]
[ 0 9 11 1 3 5 325 3 0 2 1 0]
[ 1 12 0 1 1 0 4 378 0 0 0 2]
[ 2 5 0 0 4 3 2 3 362 9 1 5]
[ 0 1 1 1 11 0 0 1 9 332 3 2]
[ 0 7 1 0 7 3 0 0 0 1 376 3]
[ 0 12 0 19 3 6 1 2 3 0 9 305]]
I0114 03:06:47.381314 4540917184 train.py:272] Confusion Matrix:
[[389 0 0 0 0 0 0 0 0 0 0 0]
[ 2 311 5 12 5 10 10 10 13 2 3 6]
[ 1 2 397 3 0 2 5 1 0 0 1 0]
[ 0 1 3 363 0 12 3 0 1 1 6 7]
[ 0 4 0 2 352 1 4 2 2 14 6 2]
[ 0 12 3 7 2 386 1 0 1 0 2 4]
[ 0 9 11 1 3 5 325 3 0 2 1 0]
[ 1 12 0 1 1 0 4 378 0 0 0 2]
[ 2 5 0 0 4 3 2 3 362 9 1 5]
[ 0 1 1 1 11 0 0 1 9 332 3 2]
[ 0 7 1 0 7 3 0 0 0 1 376 3]
[ 0 12 0 19 3 6 1 2 3 0 9 305]]
INFO:tensorflow:Step 30000: Validation accuracy = 91.60% (N=4668)
I0114 03:06:47.381637 4540917184 train.py:274] Step 30000: Validation accuracy = 91.60% (N=4668)
INFO:tensorflow:So far the best validation accuracy is 91.82%
I0114 03:06:47.381797 4540917184 train.py:284] So far the best validation accuracy is 91.82%
INFO:tensorflow:set_size=4511
I0114 03:06:47.381921 4540917184 train.py:287] set_size=4511
INFO:tensorflow:Confusion Matrix:
[[376 0 0 0 0 0 0 0 0 0 0 0]
[ 0 303 4 12 6 10 6 8 7 1 4 15]
[ 0 8 398 0 0 4 8 0 0 1 0 1]
[ 1 5 3 344 1 8 1 0 0 0 2 11]
[ 2 4 0 1 351 1 4 3 1 11 9 4]
[ 0 4 0 5 1 320 0 3 0 1 3 9]
[ 0 6 9 7 3 2 327 4 0 0 1 4]
[ 0 13 0 1 0 0 4 346 1 0 1 2]
[ 1 15 0 0 3 2 1 3 339 8 1 0]
[ 0 1 0 0 20 0 3 1 11 311 7 0]
[ 0 6 0 0 4 8 0 1 0 0 357 2]
[ 1 16 1 16 4 6 1 2 1 3 5 334]]
I0114 03:07:06.294399 4540917184 train.py:306] Confusion Matrix:
[[376 0 0 0 0 0 0 0 0 0 0 0]
[ 0 303 4 12 6 10 6 8 7 1 4 15]
[ 0 8 398 0 0 4 8 0 0 1 0 1]
[ 1 5 3 344 1 8 1 0 0 0 2 11]
[ 2 4 0 1 351 1 4 3 1 11 9 4]
[ 0 4 0 5 1 320 0 3 0 1 3 9]
[ 0 6 9 7 3 2 327 4 0 0 1 4]
[ 0 13 0 1 0 0 4 346 1 0 1 2]
[ 1 15 0 0 3 2 1 3 339 8 1 0]
[ 0 1 0 0 20 0 3 1 11 311 7 0]
[ 0 6 0 0 4 8 0 1 0 0 357 2]
[ 1 16 1 16 4 6 1 2 1 3 5 334]]
INFO:tensorflow:Final test accuracy = 91.02% (N=4511)
I0114 03:07:06.294688 4540917184 train.py:308] Final test accuracy = 91.02% (N=4511)
(python3.7) B000000089651Q:ML-KWS-for-MCU zoutai$