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849 lines (791 loc) · 20.9 KB
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------------RELU------------
learning_rate = 1e-3
batch_size = 64
epochs = 25
Using cuda device
Epoch 1
-----------------------
loss : 2.307332 [ 64/60000]
loss : 2.267430 [ 6464/60000]
loss : 2.219149 [12864/60000]
loss : 2.108903 [19264/60000]
loss : 1.913325 [25664/60000]
loss : 1.647292 [32064/60000]
loss : 1.222776 [38464/60000]
loss : 0.966802 [44864/60000]
loss : 0.723582 [51264/60000]
loss : 0.854982 [57664/60000]
Test Error:
Accuracy: 82.9%, Avg loss: 0.677897
Epoch 2
-----------------------
loss : 0.705533 [ 64/60000]
loss : 0.517220 [ 6464/60000]
loss : 0.614784 [12864/60000]
loss : 0.582514 [19264/60000]
loss : 0.540611 [25664/60000]
loss : 0.445593 [32064/60000]
loss : 0.446534 [38464/60000]
loss : 0.337337 [44864/60000]
loss : 0.329155 [51264/60000]
loss : 0.491794 [57664/60000]
Test Error:
Accuracy: 89.2%, Avg loss: 0.390111
Epoch 3
-----------------------
loss : 0.423737 [ 64/60000]
loss : 0.458315 [ 6464/60000]
loss : 0.478081 [12864/60000]
loss : 0.268387 [19264/60000]
loss : 0.335807 [25664/60000]
loss : 0.361139 [32064/60000]
loss : 0.441919 [38464/60000]
loss : 0.367749 [44864/60000]
loss : 0.441262 [51264/60000]
loss : 0.283502 [57664/60000]
Test Error:
Accuracy: 90.6%, Avg loss: 0.328014
Epoch 4
-----------------------
loss : 0.359302 [ 64/60000]
loss : 0.283223 [ 6464/60000]
loss : 0.230729 [12864/60000]
loss : 0.404816 [19264/60000]
loss : 0.255949 [25664/60000]
loss : 0.225649 [32064/60000]
loss : 0.190365 [38464/60000]
loss : 0.330476 [44864/60000]
loss : 0.269801 [51264/60000]
loss : 0.396823 [57664/60000]
Test Error:
Accuracy: 91.4%, Avg loss: 0.298313
Epoch 5
-----------------------
loss : 0.193232 [ 64/60000]
loss : 0.426912 [ 6464/60000]
loss : 0.342977 [12864/60000]
loss : 0.157823 [19264/60000]
loss : 0.278897 [25664/60000]
loss : 0.365221 [32064/60000]
loss : 0.340648 [38464/60000]
loss : 0.283317 [44864/60000]
loss : 0.393708 [51264/60000]
loss : 0.299629 [57664/60000]
Test Error:
Accuracy: 92.2%, Avg loss: 0.275846
Epoch 6
-----------------------
loss : 0.217177 [ 64/60000]
loss : 0.147741 [ 6464/60000]
loss : 0.356767 [12864/60000]
loss : 0.451693 [19264/60000]
loss : 0.327069 [25664/60000]
loss : 0.425655 [32064/60000]
loss : 0.410862 [38464/60000]
loss : 0.388759 [44864/60000]
loss : 0.211182 [51264/60000]
loss : 0.381930 [57664/60000]
Test Error:
Accuracy: 92.8%, Avg loss: 0.257323
Epoch 7
-----------------------
loss : 0.229972 [ 64/60000]
loss : 0.443277 [ 6464/60000]
loss : 0.470564 [12864/60000]
loss : 0.219164 [19264/60000]
loss : 0.374737 [25664/60000]
loss : 0.175984 [32064/60000]
loss : 0.324881 [38464/60000]
loss : 0.352552 [44864/60000]
loss : 0.175035 [51264/60000]
loss : 0.342841 [57664/60000]
Test Error:
Accuracy: 93.3%, Avg loss: 0.239709
Epoch 8
-----------------------
loss : 0.427498 [ 64/60000]
loss : 0.377090 [ 6464/60000]
loss : 0.194914 [12864/60000]
loss : 0.334427 [19264/60000]
loss : 0.141270 [25664/60000]
loss : 0.351851 [32064/60000]
loss : 0.306855 [38464/60000]
loss : 0.144054 [44864/60000]
loss : 0.372199 [51264/60000]
loss : 0.193814 [57664/60000]
Test Error:
Accuracy: 93.6%, Avg loss: 0.226479
Epoch 9
-----------------------
loss : 0.120584 [ 64/60000]
loss : 0.282186 [ 6464/60000]
loss : 0.168223 [12864/60000]
loss : 0.069126 [19264/60000]
loss : 0.150331 [25664/60000]
loss : 0.292195 [32064/60000]
loss : 0.207835 [38464/60000]
loss : 0.180684 [44864/60000]
loss : 0.386155 [51264/60000]
loss : 0.100813 [57664/60000]
Test Error:
Accuracy: 93.7%, Avg loss: 0.214842
Epoch 10
-----------------------
loss : 0.299440 [ 64/60000]
loss : 0.257498 [ 6464/60000]
loss : 0.158705 [12864/60000]
loss : 0.233506 [19264/60000]
loss : 0.211955 [25664/60000]
loss : 0.421365 [32064/60000]
loss : 0.107747 [38464/60000]
loss : 0.170564 [44864/60000]
loss : 0.256341 [51264/60000]
loss : 0.131247 [57664/60000]
Test Error:
Accuracy: 94.2%, Avg loss: 0.200235
Epoch 11
-----------------------
loss : 0.152369 [ 64/60000]
loss : 0.273962 [ 6464/60000]
loss : 0.180490 [12864/60000]
loss : 0.195096 [19264/60000]
loss : 0.151226 [25664/60000]
loss : 0.265586 [32064/60000]
loss : 0.087177 [38464/60000]
loss : 0.183200 [44864/60000]
loss : 0.164051 [51264/60000]
loss : 0.262616 [57664/60000]
Test Error:
Accuracy: 94.6%, Avg loss: 0.189230
Epoch 12
-----------------------
loss : 0.103268 [ 64/60000]
loss : 0.118648 [ 6464/60000]
loss : 0.349173 [12864/60000]
loss : 0.079112 [19264/60000]
loss : 0.195885 [25664/60000]
loss : 0.381241 [32064/60000]
loss : 0.243985 [38464/60000]
loss : 0.201513 [44864/60000]
loss : 0.128772 [51264/60000]
loss : 0.119322 [57664/60000]
Test Error:
Accuracy: 94.8%, Avg loss: 0.181330
Epoch 13
-----------------------
loss : 0.131969 [ 64/60000]
loss : 0.050959 [ 6464/60000]
loss : 0.093265 [12864/60000]
loss : 0.209835 [19264/60000]
loss : 0.150770 [25664/60000]
loss : 0.182509 [32064/60000]
loss : 0.142507 [38464/60000]
loss : 0.165894 [44864/60000]
loss : 0.445657 [51264/60000]
loss : 0.233386 [57664/60000]
Test Error:
Accuracy: 94.9%, Avg loss: 0.174411
Epoch 14
-----------------------
loss : 0.168170 [ 64/60000]
loss : 0.164013 [ 6464/60000]
loss : 0.089536 [12864/60000]
loss : 0.431175 [19264/60000]
loss : 0.069093 [25664/60000]
loss : 0.197170 [32064/60000]
loss : 0.182343 [38464/60000]
loss : 0.198815 [44864/60000]
loss : 0.208839 [51264/60000]
loss : 0.181765 [57664/60000]
Test Error:
Accuracy: 95.2%, Avg loss: 0.161579
Epoch 15
-----------------------
loss : 0.127109 [ 64/60000]
loss : 0.092846 [ 6464/60000]
loss : 0.229599 [12864/60000]
loss : 0.173679 [19264/60000]
loss : 0.291980 [25664/60000]
loss : 0.086342 [32064/60000]
loss : 0.164609 [38464/60000]
loss : 0.108442 [44864/60000]
loss : 0.122080 [51264/60000]
loss : 0.098988 [57664/60000]
Test Error:
Accuracy: 95.4%, Avg loss: 0.156356
Epoch 16
-----------------------
loss : 0.071206 [ 64/60000]
loss : 0.124582 [ 6464/60000]
loss : 0.079988 [12864/60000]
loss : 0.223582 [19264/60000]
loss : 0.074210 [25664/60000]
loss : 0.227786 [32064/60000]
loss : 0.083209 [38464/60000]
loss : 0.142966 [44864/60000]
loss : 0.092317 [51264/60000]
loss : 0.156511 [57664/60000]
Test Error:
Accuracy: 95.7%, Avg loss: 0.148049
Epoch 17
-----------------------
loss : 0.086804 [ 64/60000]
loss : 0.170324 [ 6464/60000]
loss : 0.123051 [12864/60000]
loss : 0.206744 [19264/60000]
loss : 0.047866 [25664/60000]
loss : 0.072222 [32064/60000]
loss : 0.317276 [38464/60000]
loss : 0.175532 [44864/60000]
loss : 0.134333 [51264/60000]
loss : 0.170883 [57664/60000]
Test Error:
Accuracy: 95.9%, Avg loss: 0.140564
Epoch 18
-----------------------
loss : 0.079722 [ 64/60000]
loss : 0.066681 [ 6464/60000]
loss : 0.102477 [12864/60000]
loss : 0.064183 [19264/60000]
loss : 0.177384 [25664/60000]
loss : 0.186902 [32064/60000]
loss : 0.046031 [38464/60000]
loss : 0.052444 [44864/60000]
loss : 0.096244 [51264/60000]
loss : 0.074730 [57664/60000]
Test Error:
Accuracy: 96.0%, Avg loss: 0.137225
Epoch 19
-----------------------
loss : 0.157342 [ 64/60000]
loss : 0.100326 [ 6464/60000]
loss : 0.181173 [12864/60000]
loss : 0.066696 [19264/60000]
loss : 0.083349 [25664/60000]
loss : 0.102694 [32064/60000]
loss : 0.178041 [38464/60000]
loss : 0.144864 [44864/60000]
loss : 0.158141 [51264/60000]
loss : 0.192099 [57664/60000]
Test Error:
Accuracy: 96.1%, Avg loss: 0.132209
Epoch 20
-----------------------
loss : 0.034186 [ 64/60000]
loss : 0.096554 [ 6464/60000]
loss : 0.255729 [12864/60000]
loss : 0.106779 [19264/60000]
loss : 0.072261 [25664/60000]
loss : 0.115501 [32064/60000]
loss : 0.145154 [38464/60000]
loss : 0.129974 [44864/60000]
loss : 0.134738 [51264/60000]
loss : 0.078262 [57664/60000]
Test Error:
Accuracy: 96.2%, Avg loss: 0.127668
Epoch 21
-----------------------
loss : 0.072203 [ 64/60000]
loss : 0.242252 [ 6464/60000]
loss : 0.035903 [12864/60000]
loss : 0.346698 [19264/60000]
loss : 0.189615 [25664/60000]
loss : 0.052343 [32064/60000]
loss : 0.117251 [38464/60000]
loss : 0.083424 [44864/60000]
loss : 0.128939 [51264/60000]
loss : 0.070794 [57664/60000]
Test Error:
Accuracy: 96.4%, Avg loss: 0.121830
Epoch 22
-----------------------
loss : 0.166613 [ 64/60000]
loss : 0.062062 [ 6464/60000]
loss : 0.147872 [12864/60000]
loss : 0.107111 [19264/60000]
loss : 0.103215 [25664/60000]
loss : 0.038743 [32064/60000]
loss : 0.085100 [38464/60000]
loss : 0.190924 [44864/60000]
loss : 0.106666 [51264/60000]
loss : 0.136113 [57664/60000]
Test Error:
Accuracy: 96.5%, Avg loss: 0.117574
Epoch 23
-----------------------
loss : 0.061034 [ 64/60000]
loss : 0.199395 [ 6464/60000]
loss : 0.035426 [12864/60000]
loss : 0.129376 [19264/60000]
loss : 0.075076 [25664/60000]
loss : 0.073288 [32064/60000]
loss : 0.151523 [38464/60000]
loss : 0.140948 [44864/60000]
loss : 0.037907 [51264/60000]
loss : 0.054901 [57664/60000]
Test Error:
Accuracy: 96.5%, Avg loss: 0.114857
Epoch 24
-----------------------
loss : 0.111701 [ 64/60000]
loss : 0.055265 [ 6464/60000]
loss : 0.122226 [12864/60000]
loss : 0.100447 [19264/60000]
loss : 0.069448 [25664/60000]
loss : 0.167490 [32064/60000]
loss : 0.208661 [38464/60000]
loss : 0.046365 [44864/60000]
loss : 0.168605 [51264/60000]
loss : 0.049146 [57664/60000]
Test Error:
Accuracy: 96.7%, Avg loss: 0.110942
Epoch 25
-----------------------
loss : 0.069234 [ 64/60000]
loss : 0.037250 [ 6464/60000]
loss : 0.238975 [12864/60000]
loss : 0.084597 [19264/60000]
loss : 0.089026 [25664/60000]
loss : 0.039032 [32064/60000]
loss : 0.215400 [38464/60000]
loss : 0.042356 [44864/60000]
loss : 0.037951 [51264/60000]
loss : 0.128429 [57664/60000]
Test Error:
Accuracy: 96.8%, Avg loss: 0.107833
Done!
------------GELU------------
learning_rate = 1e-3
batch_size = 64
epochs = 10
Using cuda device
Epoch 1
-----------------------
loss : 2.302539 [ 64/60000]
loss : 2.284312 [ 6464/60000]
loss : 2.263474 [12864/60000]
loss : 2.229623 [19264/60000]
loss : 2.193549 [25664/60000]
loss : 2.158742 [32064/60000]
loss : 2.087931 [38464/60000]
loss : 1.960989 [44864/60000]
loss : 1.873845 [51264/60000]
loss : 1.551247 [57664/60000]
Test Error:
Accuracy: 69.5%, Avg loss: 1.528083
Epoch 2
-----------------------
loss : 1.546193 [ 64/60000]
loss : 1.256785 [ 6464/60000]
loss : 1.025661 [12864/60000]
loss : 0.846296 [19264/60000]
loss : 0.673587 [25664/60000]
loss : 0.835354 [32064/60000]
loss : 0.990762 [38464/60000]
loss : 0.470814 [44864/60000]
loss : 0.556520 [51264/60000]
loss : 0.399457 [57664/60000]
Test Error:
Accuracy: 87.0%, Avg loss: 0.481438
Epoch 3
-----------------------
loss : 0.389730 [ 64/60000]
loss : 0.547433 [ 6464/60000]
loss : 0.424909 [12864/60000]
loss : 0.369393 [19264/60000]
loss : 0.449520 [25664/60000]
loss : 0.420798 [32064/60000]
loss : 0.377709 [38464/60000]
loss : 0.363908 [44864/60000]
loss : 0.437252 [51264/60000]
loss : 0.529873 [57664/60000]
Test Error:
Accuracy: 89.2%, Avg loss: 0.378849
Epoch 4
-----------------------
loss : 0.486626 [ 64/60000]
loss : 0.481650 [ 6464/60000]
loss : 0.461376 [12864/60000]
loss : 0.379169 [19264/60000]
loss : 0.216214 [25664/60000]
loss : 0.441423 [32064/60000]
loss : 0.337308 [38464/60000]
loss : 0.276964 [44864/60000]
loss : 0.312340 [51264/60000]
loss : 0.295349 [57664/60000]
Test Error:
Accuracy: 90.3%, Avg loss: 0.332760
Epoch 5
-----------------------
loss : 0.329808 [ 64/60000]
loss : 0.501070 [ 6464/60000]
loss : 0.342442 [12864/60000]
loss : 0.530943 [19264/60000]
loss : 0.225503 [25664/60000]
loss : 0.308487 [32064/60000]
loss : 0.311370 [38464/60000]
loss : 0.274392 [44864/60000]
loss : 0.541403 [51264/60000]
loss : 0.438912 [57664/60000]
Test Error:
Accuracy: 91.1%, Avg loss: 0.312537
Epoch 6
-----------------------
loss : 0.281846 [ 64/60000]
loss : 0.219476 [ 6464/60000]
loss : 0.316321 [12864/60000]
loss : 0.408195 [19264/60000]
loss : 0.376127 [25664/60000]
loss : 0.425099 [32064/60000]
loss : 0.265703 [38464/60000]
loss : 0.314885 [44864/60000]
loss : 0.407239 [51264/60000]
loss : 0.249572 [57664/60000]
Test Error:
Accuracy: 91.3%, Avg loss: 0.299066
Epoch 7
-----------------------
loss : 0.087835 [ 64/60000]
loss : 0.559661 [ 6464/60000]
loss : 0.294291 [12864/60000]
loss : 0.218892 [19264/60000]
loss : 0.351360 [25664/60000]
loss : 0.390501 [32064/60000]
loss : 0.240585 [38464/60000]
loss : 0.396987 [44864/60000]
loss : 0.282464 [51264/60000]
loss : 0.163830 [57664/60000]
Test Error:
Accuracy: 91.7%, Avg loss: 0.294413
Epoch 8
-----------------------
loss : 0.411862 [ 64/60000]
loss : 0.437088 [ 6464/60000]
loss : 0.229254 [12864/60000]
loss : 0.160953 [19264/60000]
loss : 0.255655 [25664/60000]
loss : 0.230183 [32064/60000]
loss : 0.301805 [38464/60000]
loss : 0.147462 [44864/60000]
loss : 0.337032 [51264/60000]
loss : 0.292581 [57664/60000]
Test Error:
Accuracy: 92.2%, Avg loss: 0.281469
Epoch 9
-----------------------
loss : 0.400014 [ 64/60000]
loss : 0.327567 [ 6464/60000]
loss : 0.269539 [12864/60000]
loss : 0.343980 [19264/60000]
loss : 0.267822 [25664/60000]
loss : 0.141171 [32064/60000]
loss : 0.216383 [38464/60000]
loss : 0.254475 [44864/60000]
loss : 0.197815 [51264/60000]
loss : 0.263398 [57664/60000]
Test Error:
Accuracy: 92.2%, Avg loss: 0.275318
Epoch 10
-----------------------
loss : 0.255974 [ 64/60000]
loss : 0.577919 [ 6464/60000]
loss : 0.358483 [12864/60000]
loss : 0.355606 [19264/60000]
loss : 0.164929 [25664/60000]
loss : 0.343802 [32064/60000]
loss : 0.167356 [38464/60000]
loss : 0.294240 [44864/60000]
loss : 0.252237 [51264/60000]
loss : 0.305854 [57664/60000]
Test Error:
Accuracy: 92.5%, Avg loss: 0.265582
Done!
------------RELU------------
Using cuda device
Epoch 1
-----------------------
loss : 2.303456 [ 64/60000]
loss : 2.242238 [ 6464/60000]
loss : 2.135754 [12864/60000]
loss : 2.014447 [19264/60000]
loss : 1.804528 [25664/60000]
loss : 1.420670 [32064/60000]
loss : 1.163102 [38464/60000]
loss : 0.936990 [44864/60000]
loss : 0.927467 [51264/60000]
loss : 0.707798 [57664/60000]
Test Error:
Accuracy: 84.0%, Avg loss: 0.642706
Epoch 2
-----------------------
loss : 0.674208 [ 64/60000]
loss : 0.570426 [ 6464/60000]
loss : 0.574688 [12864/60000]
loss : 0.356219 [19264/60000]
loss : 0.470386 [25664/60000]
loss : 0.495067 [32064/60000]
loss : 0.557780 [38464/60000]
loss : 0.399982 [44864/60000]
loss : 0.300288 [51264/60000]
loss : 0.529485 [57664/60000]
Test Error:
Accuracy: 89.1%, Avg loss: 0.388462
Epoch 3
-----------------------
loss : 0.324874 [ 64/60000]
loss : 0.431375 [ 6464/60000]
loss : 0.263435 [12864/60000]
loss : 0.417820 [19264/60000]
loss : 0.584452 [25664/60000]
loss : 0.366743 [32064/60000]
loss : 0.318446 [38464/60000]
loss : 0.361816 [44864/60000]
loss : 0.315502 [51264/60000]
loss : 0.446699 [57664/60000]
Test Error:
Accuracy: 90.7%, Avg loss: 0.325540
Epoch 4
-----------------------
loss : 0.304420 [ 64/60000]
loss : 0.319993 [ 6464/60000]
loss : 0.210548 [12864/60000]
loss : 0.282665 [19264/60000]
loss : 0.320495 [25664/60000]
loss : 0.319313 [32064/60000]
loss : 0.524136 [38464/60000]
loss : 0.331135 [44864/60000]
loss : 0.323014 [51264/60000]
loss : 0.292373 [57664/60000]
Test Error:
Accuracy: 91.5%, Avg loss: 0.296626
Epoch 5
-----------------------
loss : 0.378951 [ 64/60000]
loss : 0.342869 [ 6464/60000]
loss : 0.352073 [12864/60000]
loss : 0.298656 [19264/60000]
loss : 0.358010 [25664/60000]
loss : 0.392378 [32064/60000]
loss : 0.363200 [38464/60000]
loss : 0.231406 [44864/60000]
loss : 0.234073 [51264/60000]
loss : 0.329051 [57664/60000]
Test Error:
Accuracy: 92.2%, Avg loss: 0.274697
Epoch 6
-----------------------
loss : 0.177402 [ 64/60000]
loss : 0.322635 [ 6464/60000]
loss : 0.143516 [12864/60000]
loss : 0.497799 [19264/60000]
loss : 0.383605 [25664/60000]
loss : 0.201237 [32064/60000]
loss : 0.224995 [38464/60000]
loss : 0.192286 [44864/60000]
loss : 0.222458 [51264/60000]
loss : 0.143882 [57664/60000]
Test Error:
Accuracy: 92.7%, Avg loss: 0.257279
Epoch 7
-----------------------
loss : 0.195844 [ 64/60000]
loss : 0.217940 [ 6464/60000]
loss : 0.464531 [12864/60000]
loss : 0.342974 [19264/60000]
loss : 0.243270 [25664/60000]
loss : 0.271534 [32064/60000]
loss : 0.296786 [38464/60000]
loss : 0.282675 [44864/60000]
loss : 0.413090 [51264/60000]
loss : 0.163491 [57664/60000]
Test Error:
Accuracy: 92.8%, Avg loss: 0.246245
Epoch 8
-----------------------
loss : 0.091801 [ 64/60000]
loss : 0.377267 [ 6464/60000]
loss : 0.388723 [12864/60000]
loss : 0.254700 [19264/60000]
loss : 0.202363 [25664/60000]
loss : 0.204813 [32064/60000]
loss : 0.387494 [38464/60000]
loss : 0.315137 [44864/60000]
loss : 0.432527 [51264/60000]
loss : 0.386758 [57664/60000]
Test Error:
Accuracy: 93.4%, Avg loss: 0.230443
Epoch 9
-----------------------
loss : 0.326512 [ 64/60000]
loss : 0.384204 [ 6464/60000]
loss : 0.152167 [12864/60000]
loss : 0.180840 [19264/60000]
loss : 0.254293 [25664/60000]
loss : 0.243960 [32064/60000]
loss : 0.355259 [38464/60000]
loss : 0.234231 [44864/60000]
loss : 0.171648 [51264/60000]
loss : 0.203774 [57664/60000]
Test Error:
Accuracy: 93.8%, Avg loss: 0.216974
Epoch 10
-----------------------
loss : 0.243072 [ 64/60000]
loss : 0.165772 [ 6464/60000]
loss : 0.171703 [12864/60000]
loss : 0.100369 [19264/60000]
loss : 0.310313 [25664/60000]
loss : 0.208841 [32064/60000]
loss : 0.211205 [38464/60000]
loss : 0.144888 [44864/60000]
loss : 0.217148 [51264/60000]
loss : 0.291745 [57664/60000]
Test Error:
Accuracy: 94.1%, Avg loss: 0.206581
Done!
------------CNN------------
learning_rate = 1e-3
batch_size = 64
epochs = 10
Using cuda device
Epoch 1
-----------------------
loss : 2.402074 [ 64/60000]
loss : 0.490393 [ 6464/60000]
loss : 0.161547 [12864/60000]
loss : 0.293273 [19264/60000]
loss : 0.179579 [25664/60000]
loss : 0.293551 [32064/60000]
loss : 0.166826 [38464/60000]
loss : 0.218785 [44864/60000]
loss : 0.110688 [51264/60000]
loss : 0.075364 [57664/60000]
Test Error:
Accuracy: 97.5%, Avg loss: 0.080827
Epoch 2
-----------------------
loss : 0.160088 [ 64/60000]
loss : 0.086108 [ 6464/60000]
loss : 0.137662 [12864/60000]
loss : 0.268148 [19264/60000]
loss : 0.090947 [25664/60000]
loss : 0.188375 [32064/60000]
loss : 0.042930 [38464/60000]
loss : 0.061789 [44864/60000]
loss : 0.215740 [51264/60000]
loss : 0.171732 [57664/60000]
Test Error:
Accuracy: 98.4%, Avg loss: 0.049207
Epoch 3
-----------------------
loss : 0.072546 [ 64/60000]
loss : 0.144417 [ 6464/60000]
loss : 0.090286 [12864/60000]
loss : 0.200560 [19264/60000]
loss : 0.036485 [25664/60000]
loss : 0.132487 [32064/60000]
loss : 0.063533 [38464/60000]
loss : 0.074049 [44864/60000]
loss : 0.129156 [51264/60000]
loss : 0.053869 [57664/60000]
Test Error:
Accuracy: 98.5%, Avg loss: 0.042283
Epoch 4
-----------------------
loss : 0.067188 [ 64/60000]
loss : 0.067577 [ 6464/60000]
loss : 0.030281 [12864/60000]
loss : 0.020403 [19264/60000]
loss : 0.041295 [25664/60000]
loss : 0.071066 [32064/60000]
loss : 0.077466 [38464/60000]
loss : 0.106428 [44864/60000]
loss : 0.115700 [51264/60000]
loss : 0.089744 [57664/60000]
Test Error:
Accuracy: 98.7%, Avg loss: 0.037916
Epoch 5
-----------------------
loss : 0.024944 [ 64/60000]
loss : 0.023963 [ 6464/60000]
loss : 0.040879 [12864/60000]
loss : 0.021395 [19264/60000]
loss : 0.207932 [25664/60000]
loss : 0.031420 [32064/60000]
loss : 0.074231 [38464/60000]
loss : 0.014711 [44864/60000]
loss : 0.029927 [51264/60000]
loss : 0.057946 [57664/60000]
Test Error:
Accuracy: 98.8%, Avg loss: 0.032943
Epoch 6
-----------------------
loss : 0.050878 [ 64/60000]
loss : 0.024648 [ 6464/60000]
loss : 0.055878 [12864/60000]
loss : 0.068442 [19264/60000]
loss : 0.020412 [25664/60000]
loss : 0.029790 [32064/60000]
loss : 0.018813 [38464/60000]
loss : 0.027691 [44864/60000]
loss : 0.047043 [51264/60000]
loss : 0.004540 [57664/60000]
Test Error:
Accuracy: 99.0%, Avg loss: 0.030295
Epoch 7
-----------------------
loss : 0.040704 [ 64/60000]
loss : 0.061294 [ 6464/60000]
loss : 0.020647 [12864/60000]
loss : 0.142255 [19264/60000]
loss : 0.009956 [25664/60000]
loss : 0.026852 [32064/60000]
loss : 0.008326 [38464/60000]
loss : 0.078061 [44864/60000]
loss : 0.013884 [51264/60000]
loss : 0.013804 [57664/60000]
Test Error:
Accuracy: 98.8%, Avg loss: 0.035034
Epoch 8
-----------------------
loss : 0.038450 [ 64/60000]
loss : 0.109879 [ 6464/60000]
loss : 0.118985 [12864/60000]
loss : 0.105034 [19264/60000]
loss : 0.127212 [25664/60000]
loss : 0.020995 [32064/60000]
loss : 0.030756 [38464/60000]
loss : 0.008988 [44864/60000]
loss : 0.023924 [51264/60000]
loss : 0.016102 [57664/60000]
Test Error:
Accuracy: 99.0%, Avg loss: 0.027614
Epoch 9
-----------------------
loss : 0.010614 [ 64/60000]
loss : 0.028600 [ 6464/60000]
loss : 0.010532 [12864/60000]
loss : 0.050904 [19264/60000]
loss : 0.046362 [25664/60000]
loss : 0.058192 [32064/60000]
loss : 0.065982 [38464/60000]
loss : 0.002543 [44864/60000]
loss : 0.080325 [51264/60000]
loss : 0.008495 [57664/60000]
Test Error:
Accuracy: 99.1%, Avg loss: 0.028106
Epoch 10
-----------------------
loss : 0.017758 [ 64/60000]
loss : 0.017215 [ 6464/60000]
loss : 0.033906 [12864/60000]
loss : 0.011114 [19264/60000]
loss : 0.003718 [25664/60000]
loss : 0.066330 [32064/60000]
loss : 0.011914 [38464/60000]
loss : 0.037962 [44864/60000]
loss : 0.031639 [51264/60000]
loss : 0.065372 [57664/60000]
Test Error:
Accuracy: 99.0%, Avg loss: 0.029709
Done!