# python train.py --model_architecture ds_cnn --model_size_info 5 64 10 4 2 2 64 3 3 1 1 64 3 3 1 1 64 3 3 1 1 64 3 3 1 1 --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/DS_CNN/DS_CNN1/retrain_logs --train_dir work/DS_CNN/DS_CNN1/training/
......
INFO:tensorflow:Step #29592: rate 0.000020, accuracy 93.00%, cross entropy 0.214778
INFO:tensorflow:Step #29593: rate 0.000020, accuracy 95.00%, cross entropy 0.247013
INFO:tensorflow:Step #29594: rate 0.000020, accuracy 97.00%, cross entropy 0.160600
INFO:tensorflow:Step #29595: rate 0.000020, accuracy 95.00%, cross entropy 0.125619
INFO:tensorflow:Step #29596: rate 0.000020, accuracy 95.00%, cross entropy 0.190318
INFO:tensorflow:Step #29597: rate 0.000020, accuracy 94.00%, cross entropy 0.218497
INFO:tensorflow:Step #29598: rate 0.000020, accuracy 97.00%, cross entropy 0.137457
INFO:tensorflow:Step #29599: rate 0.000020, accuracy 96.00%, cross entropy 0.194881
INFO:tensorflow:Step #29600: rate 0.000020, accuracy 95.00%, cross entropy 0.245867
INFO:tensorflow:Confusion Matrix:
[[258 0 0 0 0 0 0 0 0 0 0 0]
[ 1 218 1 2 2 7 6 8 7 2 0 4]
[ 2 3 247 4 0 0 2 0 0 0 0 3]
[ 0 9 0 246 1 3 2 0 0 0 0 9]
[ 2 5 0 0 238 0 0 0 0 13 1 1]
[ 0 4 1 12 0 238 0 0 0 0 1 8]
[ 1 2 13 1 1 0 226 2 1 0 0 0]
[ 0 7 0 1 1 0 3 243 1 0 0 0]
[ 4 4 0 0 2 1 2 0 239 5 0 0]
[ 0 0 0 0 16 0 1 0 2 233 2 2]
[ 2 3 0 0 7 0 2 0 0 5 227 0]
[ 5 8 1 8 3 1 0 0 2 5 1 226]]
INFO:tensorflow:Step 29600: Validation accuracy = 91.79% (N=3093)
INFO:tensorflow:So far the best validation accuracy is 92.31%
INFO:tensorflow:Step #29601: rate 0.000020, accuracy 97.00%, cross entropy 0.193472
INFO:tensorflow:Step #29602: rate 0.000020, accuracy 98.00%, cross entropy 0.086266
INFO:tensorflow:Step #29603: rate 0.000020, accuracy 95.00%, cross entropy 0.206013
INFO:tensorflow:Step #29604: rate 0.000020, accuracy 95.00%, cross entropy 0.130586
INFO:tensorflow:Step #29605: rate 0.000020, accuracy 99.00%, cross entropy 0.107168
INFO:tensorflow:Step #29606: rate 0.000020, accuracy 99.00%, cross entropy 0.051911
......
INFO:tensorflow:Step #29969: rate 0.000020, accuracy 98.00%, cross entropy 0.121484
INFO:tensorflow:Step #29970: rate 0.000020, accuracy 99.00%, cross entropy 0.062734
INFO:tensorflow:Step #29971: rate 0.000020, accuracy 96.00%, cross entropy 0.131749
INFO:tensorflow:Step #29972: rate 0.000020, accuracy 96.00%, cross entropy 0.148196
INFO:tensorflow:Step #29973: rate 0.000020, accuracy 100.00%, cross entropy 0.074228
INFO:tensorflow:Step #29974: rate 0.000020, accuracy 95.00%, cross entropy 0.156531
INFO:tensorflow:Step #29975: rate 0.000020, accuracy 97.00%, cross entropy 0.098559
INFO:tensorflow:Step #29976: rate 0.000020, accuracy 95.00%, cross entropy 0.156327
INFO:tensorflow:Step #29977: rate 0.000020, accuracy 90.00%, cross entropy 0.212709
INFO:tensorflow:Step #29978: rate 0.000020, accuracy 94.00%, cross entropy 0.246338
INFO:tensorflow:Step #29979: rate 0.000020, accuracy 94.00%, cross entropy 0.208315
INFO:tensorflow:Step #29980: rate 0.000020, accuracy 95.00%, cross entropy 0.195625
INFO:tensorflow:Step #29981: rate 0.000020, accuracy 90.00%, cross entropy 0.289182
INFO:tensorflow:Step #29982: rate 0.000020, accuracy 96.00%, cross entropy 0.146916
INFO:tensorflow:Step #29983: rate 0.000020, accuracy 95.00%, cross entropy 0.153784
INFO:tensorflow:Step #29984: rate 0.000020, accuracy 95.00%, cross entropy 0.182212
INFO:tensorflow:Step #29985: rate 0.000020, accuracy 94.00%, cross entropy 0.174497
INFO:tensorflow:Step #29986: rate 0.000020, accuracy 97.00%, cross entropy 0.140645
INFO:tensorflow:Step #29987: rate 0.000020, accuracy 95.00%, cross entropy 0.160968
INFO:tensorflow:Step #29988: rate 0.000020, accuracy 98.00%, cross entropy 0.063577
INFO:tensorflow:Step #29989: rate 0.000020, accuracy 93.00%, cross entropy 0.165674
INFO:tensorflow:Step #29990: rate 0.000020, accuracy 98.00%, cross entropy 0.096141
INFO:tensorflow:Step #29991: rate 0.000020, accuracy 96.00%, cross entropy 0.149724
INFO:tensorflow:Step #29992: rate 0.000020, accuracy 92.00%, cross entropy 0.281510
INFO:tensorflow:Step #29993: rate 0.000020, accuracy 93.00%, cross entropy 0.205289
INFO:tensorflow:Step #29994: rate 0.000020, accuracy 89.00%, cross entropy 0.282349
INFO:tensorflow:Step #29995: rate 0.000020, accuracy 96.00%, cross entropy 0.124107
INFO:tensorflow:Step #29996: rate 0.000020, accuracy 97.00%, cross entropy 0.140024
INFO:tensorflow:Step #29997: rate 0.000020, accuracy 97.00%, cross entropy 0.128435
INFO:tensorflow:Step #29998: rate 0.000020, accuracy 94.00%, cross entropy 0.151532
INFO:tensorflow:Step #29999: rate 0.000020, accuracy 96.00%, cross entropy 0.143669
INFO:tensorflow:Step #30000: rate 0.000020, accuracy 93.00%, cross entropy 0.231711
INFO:tensorflow:Confusion Matrix:
[[258 0 0 0 0 0 0 0 0 0 0 0]
[ 1 216 1 3 3 6 6 7 8 2 0 5]
[ 3 2 247 4 0 1 2 0 0 0 0 2]
[ 0 9 0 248 1 2 2 0 0 0 0 8]
[ 2 7 0 0 235 0 0 0 0 14 2 0]
[ 0 4 1 16 0 233 0 0 0 0 1 9]
[ 1 2 12 1 1 0 227 2 1 0 0 0]
[ 0 7 0 1 1 0 2 243 1 1 0 0]
[ 4 4 0 0 2 1 2 0 239 5 0 0]
[ 0 1 0 0 13 0 1 0 2 235 2 2]
[ 2 3 0 0 8 0 2 0 0 4 226 1]
[ 6 8 1 10 2 1 0 0 2 5 1 224]]
INFO:tensorflow:Step 30000: Validation accuracy = 91.53% (N=3093)
INFO:tensorflow:So far the best validation accuracy is 92.31%
INFO:tensorflow:set_size=3081
INFO:tensorflow:Confusion Matrix:
[[257 0 0 0 0 0 0 0 0 0 0 0]
[ 0 226 2 3 0 0 3 5 3 2 5 8]
[ 0 5 239 1 0 2 7 1 0 0 0 1]
[ 0 2 1 237 3 3 2 0 0 1 0 3]
[ 0 2 0 0 248 0 3 0 3 11 3 2]
[ 1 5 0 7 2 230 1 0 0 0 0 7]
[ 0 3 4 0 2 0 256 2 0 0 0 0]
[ 1 7 1 0 1 1 2 245 0 0 1 0]
[ 0 2 0 0 2 1 1 1 238 1 0 0]
[ 0 2 0 0 6 1 1 0 8 240 2 2]
[ 0 6 1 1 5 3 0 1 0 1 228 3]
[ 0 4 1 7 1 2 3 4 1 6 0 222]]
INFO:tensorflow:Final test accuracy = 93.02% (N=3081)
# python test.py --model_architecture ds_cnn --model_size_info 5 64 10 4 2 2 64 3 3 1 1 64 3 3 1 1 64 3 3 1 1 64 3 3 1 1 --checkpoint work/DS_CNN/DS_CNN1/training/be/ds_cnn_9230.ckpt-12400
2018-06-07 15:49:56.929040: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 AVX512F FMA
2018-06-07 15:49:57.088431: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1356] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.645
pciBusID: 0000:65:00.0
totalMemory: 10.92GiB freeMemory: 10.76GiB
2018-06-07 15:49:57.088490: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1435] Adding visible gpu devices: 0
2018-06-07 15:49:57.311486: I tensorflow/core/common_runtime/gpu/gpu_device.cc:923] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-06-07 15:49:57.311542: I tensorflow/core/common_runtime/gpu/gpu_device.cc:929] 0
2018-06-07 15:49:57.311552: I tensorflow/core/common_runtime/gpu/gpu_device.cc:942] 0: N
2018-06-07 15:49:57.311777: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1053] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10413 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:65:00.0, compute capability: 6.1)
2018-06-07 15:50:25.113020: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1435] Adding visible gpu devices: 0
2018-06-07 15:50:25.113082: I tensorflow/core/common_runtime/gpu/gpu_device.cc:923] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-06-07 15:50:25.113092: I tensorflow/core/common_runtime/gpu/gpu_device.cc:929] 0
2018-06-07 15:50:25.113100: I tensorflow/core/common_runtime/gpu/gpu_device.cc:942] 0: N
2018-06-07 15:50:25.113310: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1053] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10413 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:65:00.0, compute capability: 6.1)
INFO:tensorflow:wav_filename_placeholder: Tensor("Placeholder:0", shape=(), dtype=string)
INFO:tensorflow:Restoring parameters from work/DS_CNN/DS_CNN1/training/best/ds_cnn_9230.ckpt-12400
INFO:tensorflow:set_size=22246
INFO:tensorflow:Confusion Matrix:
[[1827 0 0 0 0 0 0 0 0 0 0 0]
[ 0 1723 0 89 0 31 1 0 0 0 0 10]
[ 0 1509 150 186 0 36 3 0 0 0 0 1]
[ 0 635 0 1152 0 23 0 0 0 0 0 15]
[ 0 1762 0 97 0 38 2 0 0 0 0 8]
[ 0 1191 0 196 0 386 0 0 0 0 0 10]
[ 0 1572 12 187 0 19 51 0 0 0 1 3]
[ 1 1793 0 36 0 21 9 23 0 0 0 6]
[ 0 1760 1 50 0 55 0 0 2 0 0 4]
[ 0 1635 2 111 0 26 0 0 0 0 0 13]
[ 0 1774 3 95 0 79 1 0 0 0 0 5]
[ 0 1210 0 390 0 53 3 0 0 0 0 159]]
INFO:tensorflow:Training accuracy = 24.60% (N=22246)
INFO:tensorflow:set_size=3093
INFO:tensorflow:Confusion Matrix:
[[258 0 0 0 0 0 0 0 0 0 0 0]
[ 0 240 0 12 0 4 0 0 0 0 0 2]
[ 0 200 21 33 0 7 0 0 0 0 0 0]
[ 0 109 0 156 0 5 0 0 0 0 0 0]
[ 0 243 0 11 0 3 1 0 0 0 0 2]
[ 0 178 0 38 0 40 0 0 0 0 0 8]
[ 0 222 0 15 0 2 7 0 0 0 0 1]
[ 0 248 0 3 0 1 0 1 0 0 0 3]
[ 0 243 0 9 0 4 0 0 0 0 0 1]
[ 0 242 0 9 0 3 0 0 0 0 0 2]
[ 1 228 0 13 0 4 0 0 0 0 0 0]
[ 0 175 0 56 0 5 0 0 0 0 0 24]]
INFO:tensorflow:Validation accuracy = 24.15% (N=3093)
INFO:tensorflow:set_size=3081
INFO:tensorflow:Confusion Matrix:
[[257 0 0 0 0 0 0 0 0 0 0 0]
[ 0 240 0 10 0 6 0 0 0 0 0 1]
[ 0 193 21 31 0 9 0 0 0 0 0 2]
[ 0 84 0 158 0 8 0 0 0 0 0 2]
[ 0 244 0 14 0 12 1 0 0 0 0 1]
[ 0 147 0 40 0 64 0 0 0 0 0 2]
[ 0 220 1 33 0 3 9 0 0 0 0 1]
[ 0 234 0 9 0 7 2 3 0 0 0 4]
[ 0 221 0 12 0 13 0 0 0 0 0 0]
[ 0 223 1 26 0 8 0 0 0 0 0 4]
[ 0 203 0 17 0 28 0 0 0 0 0 1]
[ 0 153 1 67 0 12 0 0 0 0 0 18]]
INFO:tensorflow:Test accuracy = 24.99% (N=3081)
#