Training Pytorch Model¶
Introduction¶
PyTorch is a framework developed by Facebook AI Research for deep learning, featuring both beginner-friendly debugging tools and a high-level of customization for advanced users, with researchers and practitioners using it across companies like Facebook and Tesla. Applications include computer vision, natural language processing, cryptography, and more
In this example we will train a RNN MNIST neural network model
Cloning the pytorch examples
In [1]:
%%bash
git clone https://github.com/pytorch/examples
Cloning into 'examples'... remote: Enumerating objects: 3718, done. remote: Counting objects: 100% (40/40), done. remote: Compressing objects: 100% (33/33), done. remote: Total 3718 (delta 11), reused 32 (delta 7), pack-reused 3678 Receiving objects: 100% (3718/3718), 40.95 MiB | 21.46 MiB/s, done. Resolving deltas: 100% (1831/1831), done.
Training a mnist_rnn model
we add the --save-model flag to save the model
In [8]:
%%bash
python ./examples/mnist_rnn/main.py --save-model
/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:1331: UserWarning: dropout2d: Received a 2-D input to dropout2d, which is deprecated and will result in an error in a future release. To retain the behavior and silence this warning, please use dropout instead. Note that dropout2d exists to provide channel-wise dropout on inputs with 2 spatial dimensions, a channel dimension, and an optional batch dimension (i.e. 3D or 4D inputs). warnings.warn(warn_msg) Train Epoch: 1 [0/60000 (0%)] Loss: 2.257103 Train Epoch: 1 [640/60000 (1%)] Loss: 2.343541 Train Epoch: 1 [1280/60000 (2%)] Loss: 2.286971 Train Epoch: 1 [1920/60000 (3%)] Loss: 2.278690 Train Epoch: 1 [2560/60000 (4%)] Loss: 2.325279 Train Epoch: 1 [3200/60000 (5%)] Loss: 2.156002 Train Epoch: 1 [3840/60000 (6%)] Loss: 2.213600 Train Epoch: 1 [4480/60000 (7%)] Loss: 2.205997 Train Epoch: 1 [5120/60000 (9%)] Loss: 2.104978 Train Epoch: 1 [5760/60000 (10%)] Loss: 2.133132 Train Epoch: 1 [6400/60000 (11%)] Loss: 2.141112 Train Epoch: 1 [7040/60000 (12%)] Loss: 2.029041 Train Epoch: 1 [7680/60000 (13%)] Loss: 2.038753 Train Epoch: 1 [8320/60000 (14%)] Loss: 1.982695 Train Epoch: 1 [8960/60000 (15%)] Loss: 2.027745 Train Epoch: 1 [9600/60000 (16%)] Loss: 1.933618 Train Epoch: 1 [10240/60000 (17%)] Loss: 2.001938 Train Epoch: 1 [10880/60000 (18%)] Loss: 1.990632 Train Epoch: 1 [11520/60000 (19%)] Loss: 1.903336 Train Epoch: 1 [12160/60000 (20%)] Loss: 1.927148 Train Epoch: 1 [12800/60000 (21%)] Loss: 1.932347 Train Epoch: 1 [13440/60000 (22%)] Loss: 1.768175 Train Epoch: 1 [14080/60000 (23%)] Loss: 1.793582 Train Epoch: 1 [14720/60000 (25%)] Loss: 1.698625 Train Epoch: 1 [15360/60000 (26%)] Loss: 1.919402 Train Epoch: 1 [16000/60000 (27%)] Loss: 1.819005 Train Epoch: 1 [16640/60000 (28%)] Loss: 1.798551 Train Epoch: 1 [17280/60000 (29%)] Loss: 1.752450 Train Epoch: 1 [17920/60000 (30%)] Loss: 1.580650 Train Epoch: 1 [18560/60000 (31%)] Loss: 1.669491 Train Epoch: 1 [19200/60000 (32%)] Loss: 1.666683 Train Epoch: 1 [19840/60000 (33%)] Loss: 1.746461 Train Epoch: 1 [20480/60000 (34%)] Loss: 1.750646 Train Epoch: 1 [21120/60000 (35%)] Loss: 1.704663 Train Epoch: 1 [21760/60000 (36%)] Loss: 1.545694 Train Epoch: 1 [22400/60000 (37%)] Loss: 1.800772 Train Epoch: 1 [23040/60000 (38%)] Loss: 1.807309 Train Epoch: 1 [23680/60000 (39%)] Loss: 1.531073 Train Epoch: 1 [24320/60000 (41%)] Loss: 1.644449 Train Epoch: 1 [24960/60000 (42%)] Loss: 1.440658 Train Epoch: 1 [25600/60000 (43%)] Loss: 1.572379 Train Epoch: 1 [26240/60000 (44%)] Loss: 1.542954 Train Epoch: 1 [26880/60000 (45%)] Loss: 1.636800 Train Epoch: 1 [27520/60000 (46%)] Loss: 1.732645 Train Epoch: 1 [28160/60000 (47%)] Loss: 1.556232 Train Epoch: 1 [28800/60000 (48%)] Loss: 1.797165 Train Epoch: 1 [29440/60000 (49%)] Loss: 1.550112 Train Epoch: 1 [30080/60000 (50%)] Loss: 1.513264 Train Epoch: 1 [30720/60000 (51%)] Loss: 1.349926 Train Epoch: 1 [31360/60000 (52%)] Loss: 1.168647 Train Epoch: 1 [32000/60000 (53%)] Loss: 1.371591 Train Epoch: 1 [32640/60000 (54%)] Loss: 1.360642 Train Epoch: 1 [33280/60000 (55%)] Loss: 1.319583 Train Epoch: 1 [33920/60000 (57%)] Loss: 1.470899 Train Epoch: 1 [34560/60000 (58%)] Loss: 1.229612 Train Epoch: 1 [35200/60000 (59%)] Loss: 1.355430 Train Epoch: 1 [35840/60000 (60%)] Loss: 1.162910 Train Epoch: 1 [36480/60000 (61%)] Loss: 1.264161 Train Epoch: 1 [37120/60000 (62%)] Loss: 1.304694 Train Epoch: 1 [37760/60000 (63%)] Loss: 1.245098 Train Epoch: 1 [38400/60000 (64%)] Loss: 1.276992 Train Epoch: 1 [39040/60000 (65%)] Loss: 1.224096 Train Epoch: 1 [39680/60000 (66%)] Loss: 1.017790 Train Epoch: 1 [40320/60000 (67%)] Loss: 1.265200 Train Epoch: 1 [40960/60000 (68%)] Loss: 1.095893 Train Epoch: 1 [41600/60000 (69%)] Loss: 1.253011 Train Epoch: 1 [42240/60000 (70%)] Loss: 1.309954 Train Epoch: 1 [42880/60000 (71%)] Loss: 1.072964 Train Epoch: 1 [43520/60000 (72%)] Loss: 1.278133 Train Epoch: 1 [44160/60000 (74%)] Loss: 1.042409 Train Epoch: 1 [44800/60000 (75%)] Loss: 1.204304 Train Epoch: 1 [45440/60000 (76%)] Loss: 1.224481 Train Epoch: 1 [46080/60000 (77%)] Loss: 1.168465 Train Epoch: 1 [46720/60000 (78%)] Loss: 1.225616 Train Epoch: 1 [47360/60000 (79%)] Loss: 1.107115 Train Epoch: 1 [48000/60000 (80%)] Loss: 0.964020 Train Epoch: 1 [48640/60000 (81%)] Loss: 1.150630 Train Epoch: 1 [49280/60000 (82%)] Loss: 1.298064 Train Epoch: 1 [49920/60000 (83%)] Loss: 1.385769 Train Epoch: 1 [50560/60000 (84%)] Loss: 1.130490 Train Epoch: 1 [51200/60000 (85%)] Loss: 0.967750 Train Epoch: 1 [51840/60000 (86%)] Loss: 1.239161 Train Epoch: 1 [52480/60000 (87%)] Loss: 0.985015 Train Epoch: 1 [53120/60000 (88%)] Loss: 1.048505 Train Epoch: 1 [53760/60000 (90%)] Loss: 0.928015 Train Epoch: 1 [54400/60000 (91%)] Loss: 1.156546 Train Epoch: 1 [55040/60000 (92%)] Loss: 1.117476 Train Epoch: 1 [55680/60000 (93%)] Loss: 1.082589 Train Epoch: 1 [56320/60000 (94%)] Loss: 1.037969 Train Epoch: 1 [56960/60000 (95%)] Loss: 0.901225 Train Epoch: 1 [57600/60000 (96%)] Loss: 0.939105 Train Epoch: 1 [58240/60000 (97%)] Loss: 0.977517 Train Epoch: 1 [58880/60000 (98%)] Loss: 1.061300 Train Epoch: 1 [59520/60000 (99%)] Loss: 1.161198 Test set: Average loss: 0.7476, Accuracy: 7615/10000 (76%) Train Epoch: 2 [0/60000 (0%)] Loss: 1.074720 Train Epoch: 2 [640/60000 (1%)] Loss: 1.031572 Train Epoch: 2 [1280/60000 (2%)] Loss: 0.896288 Train Epoch: 2 [1920/60000 (3%)] Loss: 1.111214 Train Epoch: 2 [2560/60000 (4%)] Loss: 1.075807 Train Epoch: 2 [3200/60000 (5%)] Loss: 0.896091 Train Epoch: 2 [3840/60000 (6%)] Loss: 0.898205 Train Epoch: 2 [4480/60000 (7%)] Loss: 0.909036 Train Epoch: 2 [5120/60000 (9%)] Loss: 0.871763 Train Epoch: 2 [5760/60000 (10%)] Loss: 0.809469 Train Epoch: 2 [6400/60000 (11%)] Loss: 1.018834 Train Epoch: 2 [7040/60000 (12%)] Loss: 0.893395 Train Epoch: 2 [7680/60000 (13%)] Loss: 0.832215 Train Epoch: 2 [8320/60000 (14%)] Loss: 0.942631 Train Epoch: 2 [8960/60000 (15%)] Loss: 0.899457 Train Epoch: 2 [9600/60000 (16%)] Loss: 1.078218 Train Epoch: 2 [10240/60000 (17%)] Loss: 0.860738 Train Epoch: 2 [10880/60000 (18%)] Loss: 0.742847 Train Epoch: 2 [11520/60000 (19%)] Loss: 1.037842 Train Epoch: 2 [12160/60000 (20%)] Loss: 1.066162 Train Epoch: 2 [12800/60000 (21%)] Loss: 0.885088 Train Epoch: 2 [13440/60000 (22%)] Loss: 0.996853 Train Epoch: 2 [14080/60000 (23%)] Loss: 0.822172 Train Epoch: 2 [14720/60000 (25%)] Loss: 0.993543 Train Epoch: 2 [15360/60000 (26%)] Loss: 0.810572 Train Epoch: 2 [16000/60000 (27%)] Loss: 1.058691 Train Epoch: 2 [16640/60000 (28%)] Loss: 0.866646 Train Epoch: 2 [17280/60000 (29%)] Loss: 0.772441 Train Epoch: 2 [17920/60000 (30%)] Loss: 0.720767 Train Epoch: 2 [18560/60000 (31%)] Loss: 0.866728 Train Epoch: 2 [19200/60000 (32%)] Loss: 0.705710 Train Epoch: 2 [19840/60000 (33%)] Loss: 0.890331 Train Epoch: 2 [20480/60000 (34%)] Loss: 0.834183 Train Epoch: 2 [21120/60000 (35%)] Loss: 0.774839 Train Epoch: 2 [21760/60000 (36%)] Loss: 0.879249 Train Epoch: 2 [22400/60000 (37%)] Loss: 0.861507 Train Epoch: 2 [23040/60000 (38%)] Loss: 0.725026 Train Epoch: 2 [23680/60000 (39%)] Loss: 0.870410 Train Epoch: 2 [24320/60000 (41%)] Loss: 0.694554 Train Epoch: 2 [24960/60000 (42%)] Loss: 0.808239 Train Epoch: 2 [25600/60000 (43%)] Loss: 0.807047 Train Epoch: 2 [26240/60000 (44%)] Loss: 0.861262 Train Epoch: 2 [26880/60000 (45%)] Loss: 0.760611 Train Epoch: 2 [27520/60000 (46%)] Loss: 0.723064 Train Epoch: 2 [28160/60000 (47%)] Loss: 0.645913 Train Epoch: 2 [28800/60000 (48%)] Loss: 0.794883 Train Epoch: 2 [29440/60000 (49%)] Loss: 1.018256 Train Epoch: 2 [30080/60000 (50%)] Loss: 0.897736 Train Epoch: 2 [30720/60000 (51%)] Loss: 1.036487 Train Epoch: 2 [31360/60000 (52%)] Loss: 0.957585 Train Epoch: 2 [32000/60000 (53%)] Loss: 0.648525 Train Epoch: 2 [32640/60000 (54%)] Loss: 0.908357 Train Epoch: 2 [33280/60000 (55%)] Loss: 0.844382 Train Epoch: 2 [33920/60000 (57%)] Loss: 0.492543 Train Epoch: 2 [34560/60000 (58%)] Loss: 0.767534 Train Epoch: 2 [35200/60000 (59%)] Loss: 0.583981 Train Epoch: 2 [35840/60000 (60%)] Loss: 0.670485 Train Epoch: 2 [36480/60000 (61%)] Loss: 0.812931 Train Epoch: 2 [37120/60000 (62%)] Loss: 0.675360 Train Epoch: 2 [37760/60000 (63%)] Loss: 0.719999 Train Epoch: 2 [38400/60000 (64%)] Loss: 0.733326 Train Epoch: 2 [39040/60000 (65%)] Loss: 0.595985 Train Epoch: 2 [39680/60000 (66%)] Loss: 0.761033 Train Epoch: 2 [40320/60000 (67%)] Loss: 0.547535 Train Epoch: 2 [40960/60000 (68%)] Loss: 0.713409 Train Epoch: 2 [41600/60000 (69%)] Loss: 0.774444 Train Epoch: 2 [42240/60000 (70%)] Loss: 0.536494 Train Epoch: 2 [42880/60000 (71%)] Loss: 0.678178 Train Epoch: 2 [43520/60000 (72%)] Loss: 0.612846 Train Epoch: 2 [44160/60000 (74%)] Loss: 0.596894 Train Epoch: 2 [44800/60000 (75%)] Loss: 0.629905 Train Epoch: 2 [45440/60000 (76%)] Loss: 0.812533 Train Epoch: 2 [46080/60000 (77%)] Loss: 0.749563 Train Epoch: 2 [46720/60000 (78%)] Loss: 0.686619 Train Epoch: 2 [47360/60000 (79%)] Loss: 0.817192 Train Epoch: 2 [48000/60000 (80%)] Loss: 0.521638 Train Epoch: 2 [48640/60000 (81%)] Loss: 0.948533 Train Epoch: 2 [49280/60000 (82%)] Loss: 0.807676 Train Epoch: 2 [49920/60000 (83%)] Loss: 0.609730 Train Epoch: 2 [50560/60000 (84%)] Loss: 0.624522 Train Epoch: 2 [51200/60000 (85%)] Loss: 0.688772 Train Epoch: 2 [51840/60000 (86%)] Loss: 0.576913 Train Epoch: 2 [52480/60000 (87%)] Loss: 0.583184 Train Epoch: 2 [53120/60000 (88%)] Loss: 0.739166 Train Epoch: 2 [53760/60000 (90%)] Loss: 0.768429 Train Epoch: 2 [54400/60000 (91%)] Loss: 0.767366 Train Epoch: 2 [55040/60000 (92%)] Loss: 0.739564 Train Epoch: 2 [55680/60000 (93%)] Loss: 0.969297 Train Epoch: 2 [56320/60000 (94%)] Loss: 0.545870 Train Epoch: 2 [56960/60000 (95%)] Loss: 0.490728 Train Epoch: 2 [57600/60000 (96%)] Loss: 0.738210 Train Epoch: 2 [58240/60000 (97%)] Loss: 0.649949 Train Epoch: 2 [58880/60000 (98%)] Loss: 0.534231 Train Epoch: 2 [59520/60000 (99%)] Loss: 0.701677 Test set: Average loss: 0.4355, Accuracy: 8636/10000 (86%) Train Epoch: 3 [0/60000 (0%)] Loss: 0.436861 Train Epoch: 3 [640/60000 (1%)] Loss: 0.613573 Train Epoch: 3 [1280/60000 (2%)] Loss: 0.751559 Train Epoch: 3 [1920/60000 (3%)] Loss: 0.518953 Train Epoch: 3 [2560/60000 (4%)] Loss: 0.706350 Train Epoch: 3 [3200/60000 (5%)] Loss: 0.463392 Train Epoch: 3 [3840/60000 (6%)] Loss: 0.637765 Train Epoch: 3 [4480/60000 (7%)] Loss: 0.707880 Train Epoch: 3 [5120/60000 (9%)] Loss: 0.705076 Train Epoch: 3 [5760/60000 (10%)] Loss: 0.473644 Train Epoch: 3 [6400/60000 (11%)] Loss: 0.566550 Train Epoch: 3 [7040/60000 (12%)] Loss: 0.554120 Train Epoch: 3 [7680/60000 (13%)] Loss: 0.735059 Train Epoch: 3 [8320/60000 (14%)] Loss: 0.492775 Train Epoch: 3 [8960/60000 (15%)] Loss: 0.705045 Train Epoch: 3 [9600/60000 (16%)] Loss: 0.723935 Train Epoch: 3 [10240/60000 (17%)] Loss: 0.657871 Train Epoch: 3 [10880/60000 (18%)] Loss: 0.546103 Train Epoch: 3 [11520/60000 (19%)] Loss: 0.576000 Train Epoch: 3 [12160/60000 (20%)] Loss: 0.762758 Train Epoch: 3 [12800/60000 (21%)] Loss: 0.672853 Train Epoch: 3 [13440/60000 (22%)] Loss: 0.690244 Train Epoch: 3 [14080/60000 (23%)] Loss: 0.491185 Train Epoch: 3 [14720/60000 (25%)] Loss: 0.819045 Train Epoch: 3 [15360/60000 (26%)] Loss: 0.633367 Train Epoch: 3 [16000/60000 (27%)] Loss: 0.631507 Train Epoch: 3 [16640/60000 (28%)] Loss: 0.742323 Train Epoch: 3 [17280/60000 (29%)] Loss: 0.769272 Train Epoch: 3 [17920/60000 (30%)] Loss: 0.547987 Train Epoch: 3 [18560/60000 (31%)] Loss: 0.726344 Train Epoch: 3 [19200/60000 (32%)] Loss: 0.500911 Train Epoch: 3 [19840/60000 (33%)] Loss: 0.609957 Train Epoch: 3 [20480/60000 (34%)] Loss: 0.567650 Train Epoch: 3 [21120/60000 (35%)] Loss: 0.592656 Train Epoch: 3 [21760/60000 (36%)] Loss: 0.659012 Train Epoch: 3 [22400/60000 (37%)] Loss: 0.792519 Train Epoch: 3 [23040/60000 (38%)] Loss: 0.649515 Train Epoch: 3 [23680/60000 (39%)] Loss: 0.535163 Train Epoch: 3 [24320/60000 (41%)] Loss: 0.510494 Train Epoch: 3 [24960/60000 (42%)] Loss: 0.753702 Train Epoch: 3 [25600/60000 (43%)] Loss: 0.588570 Train Epoch: 3 [26240/60000 (44%)] Loss: 0.524773 Train Epoch: 3 [26880/60000 (45%)] Loss: 0.654642 Train Epoch: 3 [27520/60000 (46%)] Loss: 0.464091 Train Epoch: 3 [28160/60000 (47%)] Loss: 0.517499 Train Epoch: 3 [28800/60000 (48%)] Loss: 0.743199 Train Epoch: 3 [29440/60000 (49%)] Loss: 0.712906 Train Epoch: 3 [30080/60000 (50%)] Loss: 0.898138 Train Epoch: 3 [30720/60000 (51%)] Loss: 0.471215 Train Epoch: 3 [31360/60000 (52%)] Loss: 0.586351 Train Epoch: 3 [32000/60000 (53%)] Loss: 0.619581 Train Epoch: 3 [32640/60000 (54%)] Loss: 0.431174 Train Epoch: 3 [33280/60000 (55%)] Loss: 0.805528 Train Epoch: 3 [33920/60000 (57%)] Loss: 0.434236 Train Epoch: 3 [34560/60000 (58%)] Loss: 0.833718 Train Epoch: 3 [35200/60000 (59%)] Loss: 0.737563 Train Epoch: 3 [35840/60000 (60%)] Loss: 0.814904 Train Epoch: 3 [36480/60000 (61%)] Loss: 0.658190 Train Epoch: 3 [37120/60000 (62%)] Loss: 0.642526 Train Epoch: 3 [37760/60000 (63%)] Loss: 0.528397 Train Epoch: 3 [38400/60000 (64%)] Loss: 0.401048 Train Epoch: 3 [39040/60000 (65%)] Loss: 0.638031 Train Epoch: 3 [39680/60000 (66%)] Loss: 0.885019 Train Epoch: 3 [40320/60000 (67%)] Loss: 0.639517 Train Epoch: 3 [40960/60000 (68%)] Loss: 0.777474 Train Epoch: 3 [41600/60000 (69%)] Loss: 0.529243 Train Epoch: 3 [42240/60000 (70%)] Loss: 0.383692 Train Epoch: 3 [42880/60000 (71%)] Loss: 0.399004 Train Epoch: 3 [43520/60000 (72%)] Loss: 0.602193 Train Epoch: 3 [44160/60000 (74%)] Loss: 0.728852 Train Epoch: 3 [44800/60000 (75%)] Loss: 0.605767 Train Epoch: 3 [45440/60000 (76%)] Loss: 1.022341 Train Epoch: 3 [46080/60000 (77%)] Loss: 0.670445 Train Epoch: 3 [46720/60000 (78%)] Loss: 0.567436 Train Epoch: 3 [47360/60000 (79%)] Loss: 0.486619 Train Epoch: 3 [48000/60000 (80%)] Loss: 0.636935 Train Epoch: 3 [48640/60000 (81%)] Loss: 0.501475 Train Epoch: 3 [49280/60000 (82%)] Loss: 0.448360 Train Epoch: 3 [49920/60000 (83%)] Loss: 0.548112 Train Epoch: 3 [50560/60000 (84%)] Loss: 0.518546 Train Epoch: 3 [51200/60000 (85%)] Loss: 0.460728 Train Epoch: 3 [51840/60000 (86%)] Loss: 0.566899 Train Epoch: 3 [52480/60000 (87%)] Loss: 0.455567 Train Epoch: 3 [53120/60000 (88%)] Loss: 0.590804 Train Epoch: 3 [53760/60000 (90%)] Loss: 0.655986 Train Epoch: 3 [54400/60000 (91%)] Loss: 0.603358 Train Epoch: 3 [55040/60000 (92%)] Loss: 0.498249 Train Epoch: 3 [55680/60000 (93%)] Loss: 0.582818 Train Epoch: 3 [56320/60000 (94%)] Loss: 0.671843 Train Epoch: 3 [56960/60000 (95%)] Loss: 0.562645 Train Epoch: 3 [57600/60000 (96%)] Loss: 0.710898 Train Epoch: 3 [58240/60000 (97%)] Loss: 0.704995 Train Epoch: 3 [58880/60000 (98%)] Loss: 0.426514 Train Epoch: 3 [59520/60000 (99%)] Loss: 0.586657 Test set: Average loss: 0.3266, Accuracy: 9035/10000 (90%) Train Epoch: 4 [0/60000 (0%)] Loss: 0.555241 Train Epoch: 4 [640/60000 (1%)] Loss: 0.414488 Train Epoch: 4 [1280/60000 (2%)] Loss: 0.423981 Train Epoch: 4 [1920/60000 (3%)] Loss: 0.458799 Train Epoch: 4 [2560/60000 (4%)] Loss: 0.526234 Train Epoch: 4 [3200/60000 (5%)] Loss: 0.502130 Train Epoch: 4 [3840/60000 (6%)] Loss: 0.572711 Train Epoch: 4 [4480/60000 (7%)] Loss: 0.768068 Train Epoch: 4 [5120/60000 (9%)] Loss: 0.552236 Train Epoch: 4 [5760/60000 (10%)] Loss: 0.413747 Train Epoch: 4 [6400/60000 (11%)] Loss: 0.495317 Train Epoch: 4 [7040/60000 (12%)] Loss: 0.513442 Train Epoch: 4 [7680/60000 (13%)] Loss: 0.371071 Train Epoch: 4 [8320/60000 (14%)] Loss: 0.537922 Train Epoch: 4 [8960/60000 (15%)] Loss: 0.550542 Train Epoch: 4 [9600/60000 (16%)] Loss: 0.492354 Train Epoch: 4 [10240/60000 (17%)] Loss: 0.430003 Train Epoch: 4 [10880/60000 (18%)] Loss: 0.676727 Train Epoch: 4 [11520/60000 (19%)] Loss: 0.522242 Train Epoch: 4 [12160/60000 (20%)] Loss: 0.323046 Train Epoch: 4 [12800/60000 (21%)] Loss: 0.413817 Train Epoch: 4 [13440/60000 (22%)] Loss: 0.493616 Train Epoch: 4 [14080/60000 (23%)] Loss: 0.482043 Train Epoch: 4 [14720/60000 (25%)] Loss: 0.598020 Train Epoch: 4 [15360/60000 (26%)] Loss: 0.698045 Train Epoch: 4 [16000/60000 (27%)] Loss: 0.464924 Train Epoch: 4 [16640/60000 (28%)] Loss: 0.598145 Train Epoch: 4 [17280/60000 (29%)] Loss: 0.513251 Train Epoch: 4 [17920/60000 (30%)] Loss: 0.383759 Train Epoch: 4 [18560/60000 (31%)] Loss: 0.451445 Train Epoch: 4 [19200/60000 (32%)] Loss: 0.298578 Train Epoch: 4 [19840/60000 (33%)] Loss: 0.724677 Train Epoch: 4 [20480/60000 (34%)] Loss: 0.648704 Train Epoch: 4 [21120/60000 (35%)] Loss: 0.417878 Train Epoch: 4 [21760/60000 (36%)] Loss: 0.587597 Train Epoch: 4 [22400/60000 (37%)] Loss: 0.650825 Train Epoch: 4 [23040/60000 (38%)] Loss: 0.461850 Train Epoch: 4 [23680/60000 (39%)] Loss: 0.498996 Train Epoch: 4 [24320/60000 (41%)] Loss: 0.272354 Train Epoch: 4 [24960/60000 (42%)] Loss: 0.552614 Train Epoch: 4 [25600/60000 (43%)] Loss: 0.559007 Train Epoch: 4 [26240/60000 (44%)] Loss: 0.514660 Train Epoch: 4 [26880/60000 (45%)] Loss: 0.449900 Train Epoch: 4 [27520/60000 (46%)] Loss: 0.459001 Train Epoch: 4 [28160/60000 (47%)] Loss: 0.510848 Train Epoch: 4 [28800/60000 (48%)] Loss: 0.376767 Train Epoch: 4 [29440/60000 (49%)] Loss: 0.663157 Train Epoch: 4 [30080/60000 (50%)] Loss: 0.380203 Train Epoch: 4 [30720/60000 (51%)] Loss: 0.487593 Train Epoch: 4 [31360/60000 (52%)] Loss: 0.368228 Train Epoch: 4 [32000/60000 (53%)] Loss: 0.531883 Train Epoch: 4 [32640/60000 (54%)] Loss: 0.514747 Train Epoch: 4 [33280/60000 (55%)] Loss: 0.413709 Train Epoch: 4 [33920/60000 (57%)] Loss: 0.466322 Train Epoch: 4 [34560/60000 (58%)] Loss: 0.481781 Train Epoch: 4 [35200/60000 (59%)] Loss: 0.332192 Train Epoch: 4 [35840/60000 (60%)] Loss: 0.535552 Train Epoch: 4 [36480/60000 (61%)] Loss: 0.701525 Train Epoch: 4 [37120/60000 (62%)] Loss: 0.472824 Train Epoch: 4 [37760/60000 (63%)] Loss: 0.506161 Train Epoch: 4 [38400/60000 (64%)] Loss: 0.434092 Train Epoch: 4 [39040/60000 (65%)] Loss: 0.458589 Train Epoch: 4 [39680/60000 (66%)] Loss: 0.571874 Train Epoch: 4 [40320/60000 (67%)] Loss: 0.417427 Train Epoch: 4 [40960/60000 (68%)] Loss: 0.562599 Train Epoch: 4 [41600/60000 (69%)] Loss: 0.595764 Train Epoch: 4 [42240/60000 (70%)] Loss: 0.763261 Train Epoch: 4 [42880/60000 (71%)] Loss: 0.449961 Train Epoch: 4 [43520/60000 (72%)] Loss: 0.504707 Train Epoch: 4 [44160/60000 (74%)] Loss: 0.518068 Train Epoch: 4 [44800/60000 (75%)] Loss: 0.457749 Train Epoch: 4 [45440/60000 (76%)] Loss: 0.556885 Train Epoch: 4 [46080/60000 (77%)] Loss: 0.407525 Train Epoch: 4 [46720/60000 (78%)] Loss: 0.627192 Train Epoch: 4 [47360/60000 (79%)] Loss: 0.640685 Train Epoch: 4 [48000/60000 (80%)] Loss: 0.461735 Train Epoch: 4 [48640/60000 (81%)] Loss: 0.440985 Train Epoch: 4 [49280/60000 (82%)] Loss: 0.617622 Train Epoch: 4 [49920/60000 (83%)] Loss: 0.502659 Train Epoch: 4 [50560/60000 (84%)] Loss: 0.525112 Train Epoch: 4 [51200/60000 (85%)] Loss: 0.530759 Train Epoch: 4 [51840/60000 (86%)] Loss: 0.327249 Train Epoch: 4 [52480/60000 (87%)] Loss: 0.392866 Train Epoch: 4 [53120/60000 (88%)] Loss: 0.716493 Train Epoch: 4 [53760/60000 (90%)] Loss: 0.916052 Train Epoch: 4 [54400/60000 (91%)] Loss: 0.398534 Train Epoch: 4 [55040/60000 (92%)] Loss: 0.514750 Train Epoch: 4 [55680/60000 (93%)] Loss: 0.466898 Train Epoch: 4 [56320/60000 (94%)] Loss: 0.446999 Train Epoch: 4 [56960/60000 (95%)] Loss: 0.575152 Train Epoch: 4 [57600/60000 (96%)] Loss: 0.578759 Train Epoch: 4 [58240/60000 (97%)] Loss: 0.473566 Train Epoch: 4 [58880/60000 (98%)] Loss: 0.520567 Train Epoch: 4 [59520/60000 (99%)] Loss: 0.242124 Test set: Average loss: 0.2797, Accuracy: 9146/10000 (91%) Train Epoch: 5 [0/60000 (0%)] Loss: 0.509088 Train Epoch: 5 [640/60000 (1%)] Loss: 0.581982 Train Epoch: 5 [1280/60000 (2%)] Loss: 0.393443 Train Epoch: 5 [1920/60000 (3%)] Loss: 0.635975 Train Epoch: 5 [2560/60000 (4%)] Loss: 0.359194 Train Epoch: 5 [3200/60000 (5%)] Loss: 0.446414 Train Epoch: 5 [3840/60000 (6%)] Loss: 0.638958 Train Epoch: 5 [4480/60000 (7%)] Loss: 0.456178 Train Epoch: 5 [5120/60000 (9%)] Loss: 0.676889 Train Epoch: 5 [5760/60000 (10%)] Loss: 0.725724 Train Epoch: 5 [6400/60000 (11%)] Loss: 0.758731 Train Epoch: 5 [7040/60000 (12%)] Loss: 0.298136 Train Epoch: 5 [7680/60000 (13%)] Loss: 0.498484 Train Epoch: 5 [8320/60000 (14%)] Loss: 0.781466 Train Epoch: 5 [8960/60000 (15%)] Loss: 0.372765 Train Epoch: 5 [9600/60000 (16%)] Loss: 0.551780 Train Epoch: 5 [10240/60000 (17%)] Loss: 0.671177 Train Epoch: 5 [10880/60000 (18%)] Loss: 0.386135 Train Epoch: 5 [11520/60000 (19%)] Loss: 0.429770 Train Epoch: 5 [12160/60000 (20%)] Loss: 0.351372 Train Epoch: 5 [12800/60000 (21%)] Loss: 0.712960 Train Epoch: 5 [13440/60000 (22%)] Loss: 0.696320 Train Epoch: 5 [14080/60000 (23%)] Loss: 0.242317 Train Epoch: 5 [14720/60000 (25%)] Loss: 0.757244 Train Epoch: 5 [15360/60000 (26%)] Loss: 0.641723 Train Epoch: 5 [16000/60000 (27%)] Loss: 0.303923 Train Epoch: 5 [16640/60000 (28%)] Loss: 0.451922 Train Epoch: 5 [17280/60000 (29%)] Loss: 0.546510 Train Epoch: 5 [17920/60000 (30%)] Loss: 0.449047 Train Epoch: 5 [18560/60000 (31%)] Loss: 0.497757 Train Epoch: 5 [19200/60000 (32%)] Loss: 0.590393 Train Epoch: 5 [19840/60000 (33%)] Loss: 0.591735 Train Epoch: 5 [20480/60000 (34%)] Loss: 0.422177 Train Epoch: 5 [21120/60000 (35%)] Loss: 0.596936 Train Epoch: 5 [21760/60000 (36%)] Loss: 0.533217 Train Epoch: 5 [22400/60000 (37%)] Loss: 0.441300 Train Epoch: 5 [23040/60000 (38%)] Loss: 0.472163 Train Epoch: 5 [23680/60000 (39%)] Loss: 0.565845 Train Epoch: 5 [24320/60000 (41%)] Loss: 0.585979 Train Epoch: 5 [24960/60000 (42%)] Loss: 0.654992 Train Epoch: 5 [25600/60000 (43%)] Loss: 0.646540 Train Epoch: 5 [26240/60000 (44%)] Loss: 0.327594 Train Epoch: 5 [26880/60000 (45%)] Loss: 0.361460 Train Epoch: 5 [27520/60000 (46%)] Loss: 0.527023 Train Epoch: 5 [28160/60000 (47%)] Loss: 0.510980 Train Epoch: 5 [28800/60000 (48%)] Loss: 0.596273 Train Epoch: 5 [29440/60000 (49%)] Loss: 0.641761 Train Epoch: 5 [30080/60000 (50%)] Loss: 0.352163 Train Epoch: 5 [30720/60000 (51%)] Loss: 0.477677 Train Epoch: 5 [31360/60000 (52%)] Loss: 0.331182 Train Epoch: 5 [32000/60000 (53%)] Loss: 0.546108 Train Epoch: 5 [32640/60000 (54%)] Loss: 0.691826 Train Epoch: 5 [33280/60000 (55%)] Loss: 0.432296 Train Epoch: 5 [33920/60000 (57%)] Loss: 0.293409 Train Epoch: 5 [34560/60000 (58%)] Loss: 0.461841 Train Epoch: 5 [35200/60000 (59%)] Loss: 0.441172 Train Epoch: 5 [35840/60000 (60%)] Loss: 0.450768 Train Epoch: 5 [36480/60000 (61%)] Loss: 0.479811 Train Epoch: 5 [37120/60000 (62%)] Loss: 0.368302 Train Epoch: 5 [37760/60000 (63%)] Loss: 0.714117 Train Epoch: 5 [38400/60000 (64%)] Loss: 0.512306 Train Epoch: 5 [39040/60000 (65%)] Loss: 0.353668 Train Epoch: 5 [39680/60000 (66%)] Loss: 0.634520 Train Epoch: 5 [40320/60000 (67%)] Loss: 0.508755 Train Epoch: 5 [40960/60000 (68%)] Loss: 0.574378 Train Epoch: 5 [41600/60000 (69%)] Loss: 0.515621 Train Epoch: 5 [42240/60000 (70%)] Loss: 0.340576 Train Epoch: 5 [42880/60000 (71%)] Loss: 0.285466 Train Epoch: 5 [43520/60000 (72%)] Loss: 0.502436 Train Epoch: 5 [44160/60000 (74%)] Loss: 0.399609 Train Epoch: 5 [44800/60000 (75%)] Loss: 0.348736 Train Epoch: 5 [45440/60000 (76%)] Loss: 0.346850 Train Epoch: 5 [46080/60000 (77%)] Loss: 0.276397 Train Epoch: 5 [46720/60000 (78%)] Loss: 0.838089 Train Epoch: 5 [47360/60000 (79%)] Loss: 0.402147 Train Epoch: 5 [48000/60000 (80%)] Loss: 0.303684 Train Epoch: 5 [48640/60000 (81%)] Loss: 0.553139 Train Epoch: 5 [49280/60000 (82%)] Loss: 0.497246 Train Epoch: 5 [49920/60000 (83%)] Loss: 0.535975 Train Epoch: 5 [50560/60000 (84%)] Loss: 0.429838 Train Epoch: 5 [51200/60000 (85%)] Loss: 0.462401 Train Epoch: 5 [51840/60000 (86%)] Loss: 0.443050 Train Epoch: 5 [52480/60000 (87%)] Loss: 0.449190 Train Epoch: 5 [53120/60000 (88%)] Loss: 0.407580 Train Epoch: 5 [53760/60000 (90%)] Loss: 0.709944 Train Epoch: 5 [54400/60000 (91%)] Loss: 0.663002 Train Epoch: 5 [55040/60000 (92%)] Loss: 0.664517 Train Epoch: 5 [55680/60000 (93%)] Loss: 0.559338 Train Epoch: 5 [56320/60000 (94%)] Loss: 0.369790 Train Epoch: 5 [56960/60000 (95%)] Loss: 0.673157 Train Epoch: 5 [57600/60000 (96%)] Loss: 0.338669 Train Epoch: 5 [58240/60000 (97%)] Loss: 0.492030 Train Epoch: 5 [58880/60000 (98%)] Loss: 0.344072 Train Epoch: 5 [59520/60000 (99%)] Loss: 0.422336 Test set: Average loss: 0.2519, Accuracy: 9238/10000 (92%) Train Epoch: 6 [0/60000 (0%)] Loss: 0.386451 Train Epoch: 6 [640/60000 (1%)] Loss: 0.457663 Train Epoch: 6 [1280/60000 (2%)] Loss: 0.515761 Train Epoch: 6 [1920/60000 (3%)] Loss: 0.612987 Train Epoch: 6 [2560/60000 (4%)] Loss: 0.787487 Train Epoch: 6 [3200/60000 (5%)] Loss: 0.491761 Train Epoch: 6 [3840/60000 (6%)] Loss: 0.454228 Train Epoch: 6 [4480/60000 (7%)] Loss: 0.359811 Train Epoch: 6 [5120/60000 (9%)] Loss: 0.368992 Train Epoch: 6 [5760/60000 (10%)] Loss: 0.442591 Train Epoch: 6 [6400/60000 (11%)] Loss: 0.597941 Train Epoch: 6 [7040/60000 (12%)] Loss: 0.383115 Train Epoch: 6 [7680/60000 (13%)] Loss: 0.362788 Train Epoch: 6 [8320/60000 (14%)] Loss: 0.514896 Train Epoch: 6 [8960/60000 (15%)] Loss: 0.774907 Train Epoch: 6 [9600/60000 (16%)] Loss: 0.390481 Train Epoch: 6 [10240/60000 (17%)] Loss: 0.584314 Train Epoch: 6 [10880/60000 (18%)] Loss: 0.288985 Train Epoch: 6 [11520/60000 (19%)] Loss: 0.426987 Train Epoch: 6 [12160/60000 (20%)] Loss: 0.278613 Train Epoch: 6 [12800/60000 (21%)] Loss: 0.499849 Train Epoch: 6 [13440/60000 (22%)] Loss: 0.431185 Train Epoch: 6 [14080/60000 (23%)] Loss: 0.689421 Train Epoch: 6 [14720/60000 (25%)] Loss: 0.337867 Train Epoch: 6 [15360/60000 (26%)] Loss: 0.626685 Train Epoch: 6 [16000/60000 (27%)] Loss: 0.497805 Train Epoch: 6 [16640/60000 (28%)] Loss: 0.441194 Train Epoch: 6 [17280/60000 (29%)] Loss: 0.561231 Train Epoch: 6 [17920/60000 (30%)] Loss: 0.401973 Train Epoch: 6 [18560/60000 (31%)] Loss: 0.561977 Train Epoch: 6 [19200/60000 (32%)] Loss: 0.410717 Train Epoch: 6 [19840/60000 (33%)] Loss: 0.770685 Train Epoch: 6 [20480/60000 (34%)] Loss: 0.639804 Train Epoch: 6 [21120/60000 (35%)] Loss: 0.302792 Train Epoch: 6 [21760/60000 (36%)] Loss: 0.529687 Train Epoch: 6 [22400/60000 (37%)] Loss: 0.717906 Train Epoch: 6 [23040/60000 (38%)] Loss: 0.498945 Train Epoch: 6 [23680/60000 (39%)] Loss: 0.429929 Train Epoch: 6 [24320/60000 (41%)] Loss: 0.435225 Train Epoch: 6 [24960/60000 (42%)] Loss: 0.320319 Train Epoch: 6 [25600/60000 (43%)] Loss: 0.590387 Train Epoch: 6 [26240/60000 (44%)] Loss: 0.265355 Train Epoch: 6 [26880/60000 (45%)] Loss: 0.454373 Train Epoch: 6 [27520/60000 (46%)] Loss: 0.790875 Train Epoch: 6 [28160/60000 (47%)] Loss: 0.486921 Train Epoch: 6 [28800/60000 (48%)] Loss: 0.462753 Train Epoch: 6 [29440/60000 (49%)] Loss: 0.813337 Train Epoch: 6 [30080/60000 (50%)] Loss: 0.308712 Train Epoch: 6 [30720/60000 (51%)] Loss: 0.476948 Train Epoch: 6 [31360/60000 (52%)] Loss: 0.649331 Train Epoch: 6 [32000/60000 (53%)] Loss: 0.337972 Train Epoch: 6 [32640/60000 (54%)] Loss: 0.552407 Train Epoch: 6 [33280/60000 (55%)] Loss: 0.584259 Train Epoch: 6 [33920/60000 (57%)] Loss: 0.682539 Train Epoch: 6 [34560/60000 (58%)] Loss: 0.472495 Train Epoch: 6 [35200/60000 (59%)] Loss: 0.581826 Train Epoch: 6 [35840/60000 (60%)] Loss: 0.430555 Train Epoch: 6 [36480/60000 (61%)] Loss: 0.408301 Train Epoch: 6 [37120/60000 (62%)] Loss: 0.544223 Train Epoch: 6 [37760/60000 (63%)] Loss: 0.276037 Train Epoch: 6 [38400/60000 (64%)] Loss: 0.383866 Train Epoch: 6 [39040/60000 (65%)] Loss: 0.486723 Train Epoch: 6 [39680/60000 (66%)] Loss: 0.401154 Train Epoch: 6 [40320/60000 (67%)] Loss: 0.501817 Train Epoch: 6 [40960/60000 (68%)] Loss: 0.514987 Train Epoch: 6 [41600/60000 (69%)] Loss: 0.501832 Train Epoch: 6 [42240/60000 (70%)] Loss: 0.471297 Train Epoch: 6 [42880/60000 (71%)] Loss: 0.467299 Train Epoch: 6 [43520/60000 (72%)] Loss: 0.421591 Train Epoch: 6 [44160/60000 (74%)] Loss: 0.485595 Train Epoch: 6 [44800/60000 (75%)] Loss: 0.450339 Train Epoch: 6 [45440/60000 (76%)] Loss: 0.339639 Train Epoch: 6 [46080/60000 (77%)] Loss: 0.386934 Train Epoch: 6 [46720/60000 (78%)] Loss: 0.288079 Train Epoch: 6 [47360/60000 (79%)] Loss: 0.448822 Train Epoch: 6 [48000/60000 (80%)] Loss: 0.774343 Train Epoch: 6 [48640/60000 (81%)] Loss: 0.379256 Train Epoch: 6 [49280/60000 (82%)] Loss: 0.430138 Train Epoch: 6 [49920/60000 (83%)] Loss: 0.486228 Train Epoch: 6 [50560/60000 (84%)] Loss: 0.548016 Train Epoch: 6 [51200/60000 (85%)] Loss: 0.312752 Train Epoch: 6 [51840/60000 (86%)] Loss: 0.405820 Train Epoch: 6 [52480/60000 (87%)] Loss: 0.346440 Train Epoch: 6 [53120/60000 (88%)] Loss: 0.289083 Train Epoch: 6 [53760/60000 (90%)] Loss: 0.595599 Train Epoch: 6 [54400/60000 (91%)] Loss: 0.303218 Train Epoch: 6 [55040/60000 (92%)] Loss: 0.461978 Train Epoch: 6 [55680/60000 (93%)] Loss: 0.425981 Train Epoch: 6 [56320/60000 (94%)] Loss: 0.318439 Train Epoch: 6 [56960/60000 (95%)] Loss: 0.555305 Train Epoch: 6 [57600/60000 (96%)] Loss: 0.662117 Train Epoch: 6 [58240/60000 (97%)] Loss: 0.489319 Train Epoch: 6 [58880/60000 (98%)] Loss: 0.406899 Train Epoch: 6 [59520/60000 (99%)] Loss: 0.385348 Test set: Average loss: 0.2355, Accuracy: 9277/10000 (93%) Train Epoch: 7 [0/60000 (0%)] Loss: 0.717746 Train Epoch: 7 [640/60000 (1%)] Loss: 0.469850 Train Epoch: 7 [1280/60000 (2%)] Loss: 0.594132 Train Epoch: 7 [1920/60000 (3%)] Loss: 0.475334 Train Epoch: 7 [2560/60000 (4%)] Loss: 0.430496 Train Epoch: 7 [3200/60000 (5%)] Loss: 0.294112 Train Epoch: 7 [3840/60000 (6%)] Loss: 0.312968 Train Epoch: 7 [4480/60000 (7%)] Loss: 0.362220 Train Epoch: 7 [5120/60000 (9%)] Loss: 0.429730 Train Epoch: 7 [5760/60000 (10%)] Loss: 0.357846 Train Epoch: 7 [6400/60000 (11%)] Loss: 0.336342 Train Epoch: 7 [7040/60000 (12%)] Loss: 0.553371 Train Epoch: 7 [7680/60000 (13%)] Loss: 0.517778 Train Epoch: 7 [8320/60000 (14%)] Loss: 0.441374 Train Epoch: 7 [8960/60000 (15%)] Loss: 0.242141 Train Epoch: 7 [9600/60000 (16%)] Loss: 0.288597 Train Epoch: 7 [10240/60000 (17%)] Loss: 0.355948 Train Epoch: 7 [10880/60000 (18%)] Loss: 0.225561 Train Epoch: 7 [11520/60000 (19%)] Loss: 0.556643 Train Epoch: 7 [12160/60000 (20%)] Loss: 0.426134 Train Epoch: 7 [12800/60000 (21%)] Loss: 0.408436 Train Epoch: 7 [13440/60000 (22%)] Loss: 0.452091 Train Epoch: 7 [14080/60000 (23%)] Loss: 0.417876 Train Epoch: 7 [14720/60000 (25%)] Loss: 0.312885 Train Epoch: 7 [15360/60000 (26%)] Loss: 0.513127 Train Epoch: 7 [16000/60000 (27%)] Loss: 0.371684 Train Epoch: 7 [16640/60000 (28%)] Loss: 0.347489 Train Epoch: 7 [17280/60000 (29%)] Loss: 0.463195 Train Epoch: 7 [17920/60000 (30%)] Loss: 0.391325 Train Epoch: 7 [18560/60000 (31%)] Loss: 0.483347 Train Epoch: 7 [19200/60000 (32%)] Loss: 0.341747 Train Epoch: 7 [19840/60000 (33%)] Loss: 0.484753 Train Epoch: 7 [20480/60000 (34%)] Loss: 0.342775 Train Epoch: 7 [21120/60000 (35%)] Loss: 0.680683 Train Epoch: 7 [21760/60000 (36%)] Loss: 0.297526 Train Epoch: 7 [22400/60000 (37%)] Loss: 0.473823 Train Epoch: 7 [23040/60000 (38%)] Loss: 0.535452 Train Epoch: 7 [23680/60000 (39%)] Loss: 0.457003 Train Epoch: 7 [24320/60000 (41%)] Loss: 0.428764 Train Epoch: 7 [24960/60000 (42%)] Loss: 0.437032 Train Epoch: 7 [25600/60000 (43%)] Loss: 0.626992 Train Epoch: 7 [26240/60000 (44%)] Loss: 0.401498 Train Epoch: 7 [26880/60000 (45%)] Loss: 0.341814 Train Epoch: 7 [27520/60000 (46%)] Loss: 0.347058 Train Epoch: 7 [28160/60000 (47%)] Loss: 0.592646 Train Epoch: 7 [28800/60000 (48%)] Loss: 0.486121 Train Epoch: 7 [29440/60000 (49%)] Loss: 0.521025 Train Epoch: 7 [30080/60000 (50%)] Loss: 0.396132 Train Epoch: 7 [30720/60000 (51%)] Loss: 0.568312 Train Epoch: 7 [31360/60000 (52%)] Loss: 0.475081 Train Epoch: 7 [32000/60000 (53%)] Loss: 0.496030 Train Epoch: 7 [32640/60000 (54%)] Loss: 0.321438 Train Epoch: 7 [33280/60000 (55%)] Loss: 0.361846 Train Epoch: 7 [33920/60000 (57%)] Loss: 0.436478 Train Epoch: 7 [34560/60000 (58%)] Loss: 0.532364 Train Epoch: 7 [35200/60000 (59%)] Loss: 0.510952 Train Epoch: 7 [35840/60000 (60%)] Loss: 0.645716 Train Epoch: 7 [36480/60000 (61%)] Loss: 0.459234 Train Epoch: 7 [37120/60000 (62%)] Loss: 0.372446 Train Epoch: 7 [37760/60000 (63%)] Loss: 0.232452 Train Epoch: 7 [38400/60000 (64%)] Loss: 0.349685 Train Epoch: 7 [39040/60000 (65%)] Loss: 0.594316 Train Epoch: 7 [39680/60000 (66%)] Loss: 0.716787 Train Epoch: 7 [40320/60000 (67%)] Loss: 0.736326 Train Epoch: 7 [40960/60000 (68%)] Loss: 0.434927 Train Epoch: 7 [41600/60000 (69%)] Loss: 0.504802 Train Epoch: 7 [42240/60000 (70%)] Loss: 0.458648 Train Epoch: 7 [42880/60000 (71%)] Loss: 0.433149 Train Epoch: 7 [43520/60000 (72%)] Loss: 0.291753 Train Epoch: 7 [44160/60000 (74%)] Loss: 0.414159 Train Epoch: 7 [44800/60000 (75%)] Loss: 0.387175 Train Epoch: 7 [45440/60000 (76%)] Loss: 0.412587 Train Epoch: 7 [46080/60000 (77%)] Loss: 0.396877 Train Epoch: 7 [46720/60000 (78%)] Loss: 0.497912 Train Epoch: 7 [47360/60000 (79%)] Loss: 0.428156 Train Epoch: 7 [48000/60000 (80%)] Loss: 0.457888 Train Epoch: 7 [48640/60000 (81%)] Loss: 0.519679 Train Epoch: 7 [49280/60000 (82%)] Loss: 0.357949 Train Epoch: 7 [49920/60000 (83%)] Loss: 0.349140 Train Epoch: 7 [50560/60000 (84%)] Loss: 0.389948 Train Epoch: 7 [51200/60000 (85%)] Loss: 0.426888 Train Epoch: 7 [51840/60000 (86%)] Loss: 0.348459 Train Epoch: 7 [52480/60000 (87%)] Loss: 0.596195 Train Epoch: 7 [53120/60000 (88%)] Loss: 0.567125 Train Epoch: 7 [53760/60000 (90%)] Loss: 0.301156 Train Epoch: 7 [54400/60000 (91%)] Loss: 0.650556 Train Epoch: 7 [55040/60000 (92%)] Loss: 0.716237 Train Epoch: 7 [55680/60000 (93%)] Loss: 0.478880 Train Epoch: 7 [56320/60000 (94%)] Loss: 0.421738 Train Epoch: 7 [56960/60000 (95%)] Loss: 0.435452 Train Epoch: 7 [57600/60000 (96%)] Loss: 0.639110 Train Epoch: 7 [58240/60000 (97%)] Loss: 0.387537 Train Epoch: 7 [58880/60000 (98%)] Loss: 0.839672 Train Epoch: 7 [59520/60000 (99%)] Loss: 0.409901 Test set: Average loss: 0.2244, Accuracy: 9333/10000 (93%) Train Epoch: 8 [0/60000 (0%)] Loss: 0.469116 Train Epoch: 8 [640/60000 (1%)] Loss: 0.369547 Train Epoch: 8 [1280/60000 (2%)] Loss: 0.205326 Train Epoch: 8 [1920/60000 (3%)] Loss: 0.377605 Train Epoch: 8 [2560/60000 (4%)] Loss: 0.759715 Train Epoch: 8 [3200/60000 (5%)] Loss: 0.435700 Train Epoch: 8 [3840/60000 (6%)] Loss: 0.496598 Train Epoch: 8 [4480/60000 (7%)] Loss: 0.382843 Train Epoch: 8 [5120/60000 (9%)] Loss: 0.572180 Train Epoch: 8 [5760/60000 (10%)] Loss: 0.510329 Train Epoch: 8 [6400/60000 (11%)] Loss: 0.479855 Train Epoch: 8 [7040/60000 (12%)] Loss: 0.630407 Train Epoch: 8 [7680/60000 (13%)] Loss: 0.418155 Train Epoch: 8 [8320/60000 (14%)] Loss: 0.401250 Train Epoch: 8 [8960/60000 (15%)] Loss: 0.618375 Train Epoch: 8 [9600/60000 (16%)] Loss: 0.614910 Train Epoch: 8 [10240/60000 (17%)] Loss: 0.318959 Train Epoch: 8 [10880/60000 (18%)] Loss: 0.337133 Train Epoch: 8 [11520/60000 (19%)] Loss: 0.797270 Train Epoch: 8 [12160/60000 (20%)] Loss: 0.405077 Train Epoch: 8 [12800/60000 (21%)] Loss: 0.660094 Train Epoch: 8 [13440/60000 (22%)] Loss: 0.607702 Train Epoch: 8 [14080/60000 (23%)] Loss: 0.496708 Train Epoch: 8 [14720/60000 (25%)] Loss: 0.288580 Train Epoch: 8 [15360/60000 (26%)] Loss: 0.542240 Train Epoch: 8 [16000/60000 (27%)] Loss: 0.460526 Train Epoch: 8 [16640/60000 (28%)] Loss: 0.513786 Train Epoch: 8 [17280/60000 (29%)] Loss: 0.357062 Train Epoch: 8 [17920/60000 (30%)] Loss: 0.301969 Train Epoch: 8 [18560/60000 (31%)] Loss: 0.418003 Train Epoch: 8 [19200/60000 (32%)] Loss: 0.445466 Train Epoch: 8 [19840/60000 (33%)] Loss: 0.381778 Train Epoch: 8 [20480/60000 (34%)] Loss: 0.454850 Train Epoch: 8 [21120/60000 (35%)] Loss: 0.311810 Train Epoch: 8 [21760/60000 (36%)] Loss: 0.547684 Train Epoch: 8 [22400/60000 (37%)] Loss: 0.196216 Train Epoch: 8 [23040/60000 (38%)] Loss: 0.286038 Train Epoch: 8 [23680/60000 (39%)] Loss: 0.477280 Train Epoch: 8 [24320/60000 (41%)] Loss: 0.818387 Train Epoch: 8 [24960/60000 (42%)] Loss: 0.514256 Train Epoch: 8 [25600/60000 (43%)] Loss: 0.455588 Train Epoch: 8 [26240/60000 (44%)] Loss: 0.365949 Train Epoch: 8 [26880/60000 (45%)] Loss: 0.358122 Train Epoch: 8 [27520/60000 (46%)] Loss: 0.453270 Train Epoch: 8 [28160/60000 (47%)] Loss: 0.543010 Train Epoch: 8 [28800/60000 (48%)] Loss: 0.643081 Train Epoch: 8 [29440/60000 (49%)] Loss: 0.510997 Train Epoch: 8 [30080/60000 (50%)] Loss: 0.316055 Train Epoch: 8 [30720/60000 (51%)] Loss: 0.675488 Train Epoch: 8 [31360/60000 (52%)] Loss: 0.303624 Train Epoch: 8 [32000/60000 (53%)] Loss: 0.449534 Train Epoch: 8 [32640/60000 (54%)] Loss: 0.451440 Train Epoch: 8 [33280/60000 (55%)] Loss: 0.478363 Train Epoch: 8 [33920/60000 (57%)] Loss: 0.425090 Train Epoch: 8 [34560/60000 (58%)] Loss: 0.211939 Train Epoch: 8 [35200/60000 (59%)] Loss: 0.356067 Train Epoch: 8 [35840/60000 (60%)] Loss: 0.646257 Train Epoch: 8 [36480/60000 (61%)] Loss: 0.643568 Train Epoch: 8 [37120/60000 (62%)] Loss: 0.322013 Train Epoch: 8 [37760/60000 (63%)] Loss: 0.407144 Train Epoch: 8 [38400/60000 (64%)] Loss: 0.543189 Train Epoch: 8 [39040/60000 (65%)] Loss: 0.287051 Train Epoch: 8 [39680/60000 (66%)] Loss: 0.351675 Train Epoch: 8 [40320/60000 (67%)] Loss: 0.288524 Train Epoch: 8 [40960/60000 (68%)] Loss: 0.453518 Train Epoch: 8 [41600/60000 (69%)] Loss: 0.253906 Train Epoch: 8 [42240/60000 (70%)] Loss: 0.512110 Train Epoch: 8 [42880/60000 (71%)] Loss: 0.590715 Train Epoch: 8 [43520/60000 (72%)] Loss: 0.325584 Train Epoch: 8 [44160/60000 (74%)] Loss: 0.482525 Train Epoch: 8 [44800/60000 (75%)] Loss: 0.337738 Train Epoch: 8 [45440/60000 (76%)] Loss: 0.318561 Train Epoch: 8 [46080/60000 (77%)] Loss: 0.341067 Train Epoch: 8 [46720/60000 (78%)] Loss: 0.545488 Train Epoch: 8 [47360/60000 (79%)] Loss: 0.402002 Train Epoch: 8 [48000/60000 (80%)] Loss: 0.231705 Train Epoch: 8 [48640/60000 (81%)] Loss: 0.242957 Train Epoch: 8 [49280/60000 (82%)] Loss: 0.426707 Train Epoch: 8 [49920/60000 (83%)] Loss: 0.341219 Train Epoch: 8 [50560/60000 (84%)] Loss: 0.422939 Train Epoch: 8 [51200/60000 (85%)] Loss: 0.410271 Train Epoch: 8 [51840/60000 (86%)] Loss: 0.443087 Train Epoch: 8 [52480/60000 (87%)] Loss: 0.273087 Train Epoch: 8 [53120/60000 (88%)] Loss: 0.300433 Train Epoch: 8 [53760/60000 (90%)] Loss: 0.408493 Train Epoch: 8 [54400/60000 (91%)] Loss: 0.410628 Train Epoch: 8 [55040/60000 (92%)] Loss: 0.481743 Train Epoch: 8 [55680/60000 (93%)] Loss: 0.532843 Train Epoch: 8 [56320/60000 (94%)] Loss: 0.255752 Train Epoch: 8 [56960/60000 (95%)] Loss: 0.287013 Train Epoch: 8 [57600/60000 (96%)] Loss: 0.429710 Train Epoch: 8 [58240/60000 (97%)] Loss: 0.377912 Train Epoch: 8 [58880/60000 (98%)] Loss: 0.560696 Train Epoch: 8 [59520/60000 (99%)] Loss: 0.380459 Test set: Average loss: 0.2163, Accuracy: 9362/10000 (94%) Train Epoch: 9 [0/60000 (0%)] Loss: 0.585349 Train Epoch: 9 [640/60000 (1%)] Loss: 0.493247 Train Epoch: 9 [1280/60000 (2%)] Loss: 0.391806 Train Epoch: 9 [1920/60000 (3%)] Loss: 0.493008 Train Epoch: 9 [2560/60000 (4%)] Loss: 0.448494 Train Epoch: 9 [3200/60000 (5%)] Loss: 0.325095 Train Epoch: 9 [3840/60000 (6%)] Loss: 0.695937 Train Epoch: 9 [4480/60000 (7%)] Loss: 0.266650 Train Epoch: 9 [5120/60000 (9%)] Loss: 0.420215 Train Epoch: 9 [5760/60000 (10%)] Loss: 0.353440 Train Epoch: 9 [6400/60000 (11%)] Loss: 0.341078 Train Epoch: 9 [7040/60000 (12%)] Loss: 0.439247 Train Epoch: 9 [7680/60000 (13%)] Loss: 0.214538 Train Epoch: 9 [8320/60000 (14%)] Loss: 0.469013 Train Epoch: 9 [8960/60000 (15%)] Loss: 0.341292 Train Epoch: 9 [9600/60000 (16%)] Loss: 0.785742 Train Epoch: 9 [10240/60000 (17%)] Loss: 0.466753 Train Epoch: 9 [10880/60000 (18%)] Loss: 0.418933 Train Epoch: 9 [11520/60000 (19%)] Loss: 0.352861 Train Epoch: 9 [12160/60000 (20%)] Loss: 0.330622 Train Epoch: 9 [12800/60000 (21%)] Loss: 0.394191 Train Epoch: 9 [13440/60000 (22%)] Loss: 0.304991 Train Epoch: 9 [14080/60000 (23%)] Loss: 0.291812 Train Epoch: 9 [14720/60000 (25%)] Loss: 0.460314 Train Epoch: 9 [15360/60000 (26%)] Loss: 0.462962 Train Epoch: 9 [16000/60000 (27%)] Loss: 0.573508 Train Epoch: 9 [16640/60000 (28%)] Loss: 0.424545 Train Epoch: 9 [17280/60000 (29%)] Loss: 0.314216 Train Epoch: 9 [17920/60000 (30%)] Loss: 0.399477 Train Epoch: 9 [18560/60000 (31%)] Loss: 0.281409 Train Epoch: 9 [19200/60000 (32%)] Loss: 0.491287 Train Epoch: 9 [19840/60000 (33%)] Loss: 0.478374 Train Epoch: 9 [20480/60000 (34%)] Loss: 0.580464 Train Epoch: 9 [21120/60000 (35%)] Loss: 0.456699 Train Epoch: 9 [21760/60000 (36%)] Loss: 0.328621 Train Epoch: 9 [22400/60000 (37%)] Loss: 0.444201 Train Epoch: 9 [23040/60000 (38%)] Loss: 0.337673 Train Epoch: 9 [23680/60000 (39%)] Loss: 0.385429 Train Epoch: 9 [24320/60000 (41%)] Loss: 0.408061 Train Epoch: 9 [24960/60000 (42%)] Loss: 0.261543 Train Epoch: 9 [25600/60000 (43%)] Loss: 0.307577 Train Epoch: 9 [26240/60000 (44%)] Loss: 0.340200 Train Epoch: 9 [26880/60000 (45%)] Loss: 0.251913 Train Epoch: 9 [27520/60000 (46%)] Loss: 0.269230 Train Epoch: 9 [28160/60000 (47%)] Loss: 0.456552 Train Epoch: 9 [28800/60000 (48%)] Loss: 0.598232 Train Epoch: 9 [29440/60000 (49%)] Loss: 0.418178 Train Epoch: 9 [30080/60000 (50%)] Loss: 0.356407 Train Epoch: 9 [30720/60000 (51%)] Loss: 0.392345 Train Epoch: 9 [31360/60000 (52%)] Loss: 0.379441 Train Epoch: 9 [32000/60000 (53%)] Loss: 0.465714 Train Epoch: 9 [32640/60000 (54%)] Loss: 0.367991 Train Epoch: 9 [33280/60000 (55%)] Loss: 0.285676 Train Epoch: 9 [33920/60000 (57%)] Loss: 0.243431 Train Epoch: 9 [34560/60000 (58%)] Loss: 0.355942 Train Epoch: 9 [35200/60000 (59%)] Loss: 0.374828 Train Epoch: 9 [35840/60000 (60%)] Loss: 0.277245 Train Epoch: 9 [36480/60000 (61%)] Loss: 0.273998 Train Epoch: 9 [37120/60000 (62%)] Loss: 0.406776 Train Epoch: 9 [37760/60000 (63%)] Loss: 0.651791 Train Epoch: 9 [38400/60000 (64%)] Loss: 0.417006 Train Epoch: 9 [39040/60000 (65%)] Loss: 0.287786 Train Epoch: 9 [39680/60000 (66%)] Loss: 0.592247 Train Epoch: 9 [40320/60000 (67%)] Loss: 0.317201 Train Epoch: 9 [40960/60000 (68%)] Loss: 0.324063 Train Epoch: 9 [41600/60000 (69%)] Loss: 0.393426 Train Epoch: 9 [42240/60000 (70%)] Loss: 0.413506 Train Epoch: 9 [42880/60000 (71%)] Loss: 0.633300 Train Epoch: 9 [43520/60000 (72%)] Loss: 0.276478 Train Epoch: 9 [44160/60000 (74%)] Loss: 0.473216 Train Epoch: 9 [44800/60000 (75%)] Loss: 0.327980 Train Epoch: 9 [45440/60000 (76%)] Loss: 0.727830 Train Epoch: 9 [46080/60000 (77%)] Loss: 0.416605 Train Epoch: 9 [46720/60000 (78%)] Loss: 0.407100 Train Epoch: 9 [47360/60000 (79%)] Loss: 0.375050 Train Epoch: 9 [48000/60000 (80%)] Loss: 0.488991 Train Epoch: 9 [48640/60000 (81%)] Loss: 0.413114 Train Epoch: 9 [49280/60000 (82%)] Loss: 0.520725 Train Epoch: 9 [49920/60000 (83%)] Loss: 0.420221 Train Epoch: 9 [50560/60000 (84%)] Loss: 0.599522 Train Epoch: 9 [51200/60000 (85%)] Loss: 0.490780 Train Epoch: 9 [51840/60000 (86%)] Loss: 0.228232 Train Epoch: 9 [52480/60000 (87%)] Loss: 0.347773 Train Epoch: 9 [53120/60000 (88%)] Loss: 0.476633 Train Epoch: 9 [53760/60000 (90%)] Loss: 0.256655 Train Epoch: 9 [54400/60000 (91%)] Loss: 0.396474 Train Epoch: 9 [55040/60000 (92%)] Loss: 0.328017 Train Epoch: 9 [55680/60000 (93%)] Loss: 0.355085 Train Epoch: 9 [56320/60000 (94%)] Loss: 0.354232 Train Epoch: 9 [56960/60000 (95%)] Loss: 0.360218 Train Epoch: 9 [57600/60000 (96%)] Loss: 0.332372 Train Epoch: 9 [58240/60000 (97%)] Loss: 0.364290 Train Epoch: 9 [58880/60000 (98%)] Loss: 0.261339 Train Epoch: 9 [59520/60000 (99%)] Loss: 0.250586 Test set: Average loss: 0.2151, Accuracy: 9366/10000 (94%) Train Epoch: 10 [0/60000 (0%)] Loss: 0.438674 Train Epoch: 10 [640/60000 (1%)] Loss: 0.447094 Train Epoch: 10 [1280/60000 (2%)] Loss: 0.303145 Train Epoch: 10 [1920/60000 (3%)] Loss: 0.327250 Train Epoch: 10 [2560/60000 (4%)] Loss: 0.238297 Train Epoch: 10 [3200/60000 (5%)] Loss: 0.383331 Train Epoch: 10 [3840/60000 (6%)] Loss: 0.382009 Train Epoch: 10 [4480/60000 (7%)] Loss: 0.389430 Train Epoch: 10 [5120/60000 (9%)] Loss: 0.295570 Train Epoch: 10 [5760/60000 (10%)] Loss: 0.259864 Train Epoch: 10 [6400/60000 (11%)] Loss: 0.495971 Train Epoch: 10 [7040/60000 (12%)] Loss: 0.361642 Train Epoch: 10 [7680/60000 (13%)] Loss: 0.765770 Train Epoch: 10 [8320/60000 (14%)] Loss: 0.403898 Train Epoch: 10 [8960/60000 (15%)] Loss: 0.209247 Train Epoch: 10 [9600/60000 (16%)] Loss: 0.482393 Train Epoch: 10 [10240/60000 (17%)] Loss: 0.459047 Train Epoch: 10 [10880/60000 (18%)] Loss: 0.505761 Train Epoch: 10 [11520/60000 (19%)] Loss: 0.433308 Train Epoch: 10 [12160/60000 (20%)] Loss: 0.354521 Train Epoch: 10 [12800/60000 (21%)] Loss: 0.233018 Train Epoch: 10 [13440/60000 (22%)] Loss: 0.390475 Train Epoch: 10 [14080/60000 (23%)] Loss: 0.245935 Train Epoch: 10 [14720/60000 (25%)] Loss: 0.398529 Train Epoch: 10 [15360/60000 (26%)] Loss: 0.393017 Train Epoch: 10 [16000/60000 (27%)] Loss: 0.364165 Train Epoch: 10 [16640/60000 (28%)] Loss: 0.657179 Train Epoch: 10 [17280/60000 (29%)] Loss: 0.199565 Train Epoch: 10 [17920/60000 (30%)] Loss: 0.373812 Train Epoch: 10 [18560/60000 (31%)] Loss: 0.395341 Train Epoch: 10 [19200/60000 (32%)] Loss: 0.367142 Train Epoch: 10 [19840/60000 (33%)] Loss: 0.420444 Train Epoch: 10 [20480/60000 (34%)] Loss: 0.411721 Train Epoch: 10 [21120/60000 (35%)] Loss: 0.406184 Train Epoch: 10 [21760/60000 (36%)] Loss: 0.309357 Train Epoch: 10 [22400/60000 (37%)] Loss: 0.397584 Train Epoch: 10 [23040/60000 (38%)] Loss: 0.699485 Train Epoch: 10 [23680/60000 (39%)] Loss: 0.672688 Train Epoch: 10 [24320/60000 (41%)] Loss: 0.383668 Train Epoch: 10 [24960/60000 (42%)] Loss: 0.443057 Train Epoch: 10 [25600/60000 (43%)] Loss: 0.409219 Train Epoch: 10 [26240/60000 (44%)] Loss: 0.311079 Train Epoch: 10 [26880/60000 (45%)] Loss: 0.367074 Train Epoch: 10 [27520/60000 (46%)] Loss: 0.279823 Train Epoch: 10 [28160/60000 (47%)] Loss: 0.337272 Train Epoch: 10 [28800/60000 (48%)] Loss: 0.485712 Train Epoch: 10 [29440/60000 (49%)] Loss: 0.345926 Train Epoch: 10 [30080/60000 (50%)] Loss: 0.424248 Train Epoch: 10 [30720/60000 (51%)] Loss: 0.322441 Train Epoch: 10 [31360/60000 (52%)] Loss: 0.283901 Train Epoch: 10 [32000/60000 (53%)] Loss: 0.640330 Train Epoch: 10 [32640/60000 (54%)] Loss: 0.342491 Train Epoch: 10 [33280/60000 (55%)] Loss: 0.343811 Train Epoch: 10 [33920/60000 (57%)] Loss: 0.392110 Train Epoch: 10 [34560/60000 (58%)] Loss: 0.433466 Train Epoch: 10 [35200/60000 (59%)] Loss: 0.341572 Train Epoch: 10 [35840/60000 (60%)] Loss: 0.394995 Train Epoch: 10 [36480/60000 (61%)] Loss: 0.332045 Train Epoch: 10 [37120/60000 (62%)] Loss: 0.276502 Train Epoch: 10 [37760/60000 (63%)] Loss: 0.292657 Train Epoch: 10 [38400/60000 (64%)] Loss: 0.455167 Train Epoch: 10 [39040/60000 (65%)] Loss: 0.297509 Train Epoch: 10 [39680/60000 (66%)] Loss: 0.640905 Train Epoch: 10 [40320/60000 (67%)] Loss: 0.422916 Train Epoch: 10 [40960/60000 (68%)] Loss: 0.473346 Train Epoch: 10 [41600/60000 (69%)] Loss: 0.491301 Train Epoch: 10 [42240/60000 (70%)] Loss: 0.346930 Train Epoch: 10 [42880/60000 (71%)] Loss: 0.572828 Train Epoch: 10 [43520/60000 (72%)] Loss: 0.365607 Train Epoch: 10 [44160/60000 (74%)] Loss: 0.317555 Train Epoch: 10 [44800/60000 (75%)] Loss: 0.468911 Train Epoch: 10 [45440/60000 (76%)] Loss: 0.496311 Train Epoch: 10 [46080/60000 (77%)] Loss: 0.696476 Train Epoch: 10 [46720/60000 (78%)] Loss: 0.359581 Train Epoch: 10 [47360/60000 (79%)] Loss: 0.419243 Train Epoch: 10 [48000/60000 (80%)] Loss: 0.303316 Train Epoch: 10 [48640/60000 (81%)] Loss: 0.383326 Train Epoch: 10 [49280/60000 (82%)] Loss: 0.268373 Train Epoch: 10 [49920/60000 (83%)] Loss: 0.413617 Train Epoch: 10 [50560/60000 (84%)] Loss: 0.454594 Train Epoch: 10 [51200/60000 (85%)] Loss: 0.359162 Train Epoch: 10 [51840/60000 (86%)] Loss: 0.630098 Train Epoch: 10 [52480/60000 (87%)] Loss: 0.521164 Train Epoch: 10 [53120/60000 (88%)] Loss: 0.247818 Train Epoch: 10 [53760/60000 (90%)] Loss: 0.330510 Train Epoch: 10 [54400/60000 (91%)] Loss: 0.343167 Train Epoch: 10 [55040/60000 (92%)] Loss: 0.380157 Train Epoch: 10 [55680/60000 (93%)] Loss: 0.395422 Train Epoch: 10 [56320/60000 (94%)] Loss: 0.687743 Train Epoch: 10 [56960/60000 (95%)] Loss: 0.470193 Train Epoch: 10 [57600/60000 (96%)] Loss: 0.473724 Train Epoch: 10 [58240/60000 (97%)] Loss: 0.361690 Train Epoch: 10 [58880/60000 (98%)] Loss: 0.349370 Train Epoch: 10 [59520/60000 (99%)] Loss: 0.385800 Test set: Average loss: 0.2124, Accuracy: 9367/10000 (94%) Train Epoch: 11 [0/60000 (0%)] Loss: 0.426175 Train Epoch: 11 [640/60000 (1%)] Loss: 0.170051 Train Epoch: 11 [1280/60000 (2%)] Loss: 0.250144 Train Epoch: 11 [1920/60000 (3%)] Loss: 0.172225 Train Epoch: 11 [2560/60000 (4%)] Loss: 0.421107 Train Epoch: 11 [3200/60000 (5%)] Loss: 0.380877 Train Epoch: 11 [3840/60000 (6%)] Loss: 0.230398 Train Epoch: 11 [4480/60000 (7%)] Loss: 0.477564 Train Epoch: 11 [5120/60000 (9%)] Loss: 0.395525 Train Epoch: 11 [5760/60000 (10%)] Loss: 0.270284 Train Epoch: 11 [6400/60000 (11%)] Loss: 0.310442 Train Epoch: 11 [7040/60000 (12%)] Loss: 0.285872 Train Epoch: 11 [7680/60000 (13%)] Loss: 0.333100 Train Epoch: 11 [8320/60000 (14%)] Loss: 0.269915 Train Epoch: 11 [8960/60000 (15%)] Loss: 0.340484 Train Epoch: 11 [9600/60000 (16%)] Loss: 0.433937 Train Epoch: 11 [10240/60000 (17%)] Loss: 0.552323 Train Epoch: 11 [10880/60000 (18%)] Loss: 0.532913 Train Epoch: 11 [11520/60000 (19%)] Loss: 0.495746 Train Epoch: 11 [12160/60000 (20%)] Loss: 0.303816 Train Epoch: 11 [12800/60000 (21%)] Loss: 0.264450 Train Epoch: 11 [13440/60000 (22%)] Loss: 0.436694 Train Epoch: 11 [14080/60000 (23%)] Loss: 0.440698 Train Epoch: 11 [14720/60000 (25%)] Loss: 0.422328 Train Epoch: 11 [15360/60000 (26%)] Loss: 0.415076 Train Epoch: 11 [16000/60000 (27%)] Loss: 0.595344 Train Epoch: 11 [16640/60000 (28%)] Loss: 0.246912 Train Epoch: 11 [17280/60000 (29%)] Loss: 0.261348 Train Epoch: 11 [17920/60000 (30%)] Loss: 0.420687 Train Epoch: 11 [18560/60000 (31%)] Loss: 0.309478 Train Epoch: 11 [19200/60000 (32%)] Loss: 0.351695 Train Epoch: 11 [19840/60000 (33%)] Loss: 0.521406 Train Epoch: 11 [20480/60000 (34%)] Loss: 0.290906 Train Epoch: 11 [21120/60000 (35%)] Loss: 0.364633 Train Epoch: 11 [21760/60000 (36%)] Loss: 0.324598 Train Epoch: 11 [22400/60000 (37%)] Loss: 0.504305 Train Epoch: 11 [23040/60000 (38%)] Loss: 0.565828 Train Epoch: 11 [23680/60000 (39%)] Loss: 0.530418 Train Epoch: 11 [24320/60000 (41%)] Loss: 0.394786 Train Epoch: 11 [24960/60000 (42%)] Loss: 0.360259 Train Epoch: 11 [25600/60000 (43%)] Loss: 0.332048 Train Epoch: 11 [26240/60000 (44%)] Loss: 0.277467 Train Epoch: 11 [26880/60000 (45%)] Loss: 0.392917 Train Epoch: 11 [27520/60000 (46%)] Loss: 0.343030 Train Epoch: 11 [28160/60000 (47%)] Loss: 0.575351 Train Epoch: 11 [28800/60000 (48%)] Loss: 0.234557 Train Epoch: 11 [29440/60000 (49%)] Loss: 0.345107 Train Epoch: 11 [30080/60000 (50%)] Loss: 0.250498 Train Epoch: 11 [30720/60000 (51%)] Loss: 0.252944 Train Epoch: 11 [31360/60000 (52%)] Loss: 0.339441 Train Epoch: 11 [32000/60000 (53%)] Loss: 0.419631 Train Epoch: 11 [32640/60000 (54%)] Loss: 0.299459 Train Epoch: 11 [33280/60000 (55%)] Loss: 0.496848 Train Epoch: 11 [33920/60000 (57%)] Loss: 0.298093 Train Epoch: 11 [34560/60000 (58%)] Loss: 0.502162 Train Epoch: 11 [35200/60000 (59%)] Loss: 0.255059 Train Epoch: 11 [35840/60000 (60%)] Loss: 0.411274 Train Epoch: 11 [36480/60000 (61%)] Loss: 0.523597 Train Epoch: 11 [37120/60000 (62%)] Loss: 0.413543 Train Epoch: 11 [37760/60000 (63%)] Loss: 0.416163 Train Epoch: 11 [38400/60000 (64%)] Loss: 0.369535 Train Epoch: 11 [39040/60000 (65%)] Loss: 0.611558 Train Epoch: 11 [39680/60000 (66%)] Loss: 0.304744 Train Epoch: 11 [40320/60000 (67%)] Loss: 0.430891 Train Epoch: 11 [40960/60000 (68%)] Loss: 0.405095 Train Epoch: 11 [41600/60000 (69%)] Loss: 0.459111 Train Epoch: 11 [42240/60000 (70%)] Loss: 0.305776 Train Epoch: 11 [42880/60000 (71%)] Loss: 0.383718 Train Epoch: 11 [43520/60000 (72%)] Loss: 0.357237 Train Epoch: 11 [44160/60000 (74%)] Loss: 0.882389 Train Epoch: 11 [44800/60000 (75%)] Loss: 0.515517 Train Epoch: 11 [45440/60000 (76%)] Loss: 0.431814 Train Epoch: 11 [46080/60000 (77%)] Loss: 0.502057 Train Epoch: 11 [46720/60000 (78%)] Loss: 0.363643 Train Epoch: 11 [47360/60000 (79%)] Loss: 0.300866 Train Epoch: 11 [48000/60000 (80%)] Loss: 0.379479 Train Epoch: 11 [48640/60000 (81%)] Loss: 0.409872 Train Epoch: 11 [49280/60000 (82%)] Loss: 0.459707 Train Epoch: 11 [49920/60000 (83%)] Loss: 0.407088 Train Epoch: 11 [50560/60000 (84%)] Loss: 0.442198 Train Epoch: 11 [51200/60000 (85%)] Loss: 0.360245 Train Epoch: 11 [51840/60000 (86%)] Loss: 0.391902 Train Epoch: 11 [52480/60000 (87%)] Loss: 0.690278 Train Epoch: 11 [53120/60000 (88%)] Loss: 0.578411 Train Epoch: 11 [53760/60000 (90%)] Loss: 0.317039 Train Epoch: 11 [54400/60000 (91%)] Loss: 0.361648 Train Epoch: 11 [55040/60000 (92%)] Loss: 0.256818 Train Epoch: 11 [55680/60000 (93%)] Loss: 0.305927 Train Epoch: 11 [56320/60000 (94%)] Loss: 0.334767 Train Epoch: 11 [56960/60000 (95%)] Loss: 0.393670 Train Epoch: 11 [57600/60000 (96%)] Loss: 0.357648 Train Epoch: 11 [58240/60000 (97%)] Loss: 0.281211 Train Epoch: 11 [58880/60000 (98%)] Loss: 0.324076 Train Epoch: 11 [59520/60000 (99%)] Loss: 0.372610 Test set: Average loss: 0.2098, Accuracy: 9373/10000 (94%) Train Epoch: 12 [0/60000 (0%)] Loss: 0.392381 Train Epoch: 12 [640/60000 (1%)] Loss: 0.296244 Train Epoch: 12 [1280/60000 (2%)] Loss: 0.375837 Train Epoch: 12 [1920/60000 (3%)] Loss: 0.511141 Train Epoch: 12 [2560/60000 (4%)] Loss: 0.328571 Train Epoch: 12 [3200/60000 (5%)] Loss: 0.407022 Train Epoch: 12 [3840/60000 (6%)] Loss: 0.298561 Train Epoch: 12 [4480/60000 (7%)] Loss: 0.294834 Train Epoch: 12 [5120/60000 (9%)] Loss: 0.459634 Train Epoch: 12 [5760/60000 (10%)] Loss: 0.427800 Train Epoch: 12 [6400/60000 (11%)] Loss: 0.315486 Train Epoch: 12 [7040/60000 (12%)] Loss: 0.369394 Train Epoch: 12 [7680/60000 (13%)] Loss: 0.383769 Train Epoch: 12 [8320/60000 (14%)] Loss: 0.360964 Train Epoch: 12 [8960/60000 (15%)] Loss: 0.565721 Train Epoch: 12 [9600/60000 (16%)] Loss: 0.339542 Train Epoch: 12 [10240/60000 (17%)] Loss: 0.318309 Train Epoch: 12 [10880/60000 (18%)] Loss: 0.354276 Train Epoch: 12 [11520/60000 (19%)] Loss: 0.729153 Train Epoch: 12 [12160/60000 (20%)] Loss: 0.637019 Train Epoch: 12 [12800/60000 (21%)] Loss: 0.311870 Train Epoch: 12 [13440/60000 (22%)] Loss: 0.475887 Train Epoch: 12 [14080/60000 (23%)] Loss: 0.593350 Train Epoch: 12 [14720/60000 (25%)] Loss: 0.401409 Train Epoch: 12 [15360/60000 (26%)] Loss: 0.340033 Train Epoch: 12 [16000/60000 (27%)] Loss: 0.268461 Train Epoch: 12 [16640/60000 (28%)] Loss: 0.246901 Train Epoch: 12 [17280/60000 (29%)] Loss: 0.220537 Train Epoch: 12 [17920/60000 (30%)] Loss: 0.343910 Train Epoch: 12 [18560/60000 (31%)] Loss: 0.404446 Train Epoch: 12 [19200/60000 (32%)] Loss: 0.390659 Train Epoch: 12 [19840/60000 (33%)] Loss: 0.428503 Train Epoch: 12 [20480/60000 (34%)] Loss: 0.349072 Train Epoch: 12 [21120/60000 (35%)] Loss: 0.486959 Train Epoch: 12 [21760/60000 (36%)] Loss: 0.328149 Train Epoch: 12 [22400/60000 (37%)] Loss: 0.516612 Train Epoch: 12 [23040/60000 (38%)] Loss: 0.457053 Train Epoch: 12 [23680/60000 (39%)] Loss: 0.608891 Train Epoch: 12 [24320/60000 (41%)] Loss: 0.689961 Train Epoch: 12 [24960/60000 (42%)] Loss: 0.294651 Train Epoch: 12 [25600/60000 (43%)] Loss: 0.393591 Train Epoch: 12 [26240/60000 (44%)] Loss: 0.338527 Train Epoch: 12 [26880/60000 (45%)] Loss: 0.577185 Train Epoch: 12 [27520/60000 (46%)] Loss: 0.353298 Train Epoch: 12 [28160/60000 (47%)] Loss: 0.622562 Train Epoch: 12 [28800/60000 (48%)] Loss: 0.282284 Train Epoch: 12 [29440/60000 (49%)] Loss: 0.313890 Train Epoch: 12 [30080/60000 (50%)] Loss: 0.351841 Train Epoch: 12 [30720/60000 (51%)] Loss: 0.396683 Train Epoch: 12 [31360/60000 (52%)] Loss: 0.525927 Train Epoch: 12 [32000/60000 (53%)] Loss: 0.234338 Train Epoch: 12 [32640/60000 (54%)] Loss: 0.462475 Train Epoch: 12 [33280/60000 (55%)] Loss: 0.566766 Train Epoch: 12 [33920/60000 (57%)] Loss: 0.384067 Train Epoch: 12 [34560/60000 (58%)] Loss: 0.281657 Train Epoch: 12 [35200/60000 (59%)] Loss: 0.392156 Train Epoch: 12 [35840/60000 (60%)] Loss: 0.567646 Train Epoch: 12 [36480/60000 (61%)] Loss: 0.294172 Train Epoch: 12 [37120/60000 (62%)] Loss: 0.395887 Train Epoch: 12 [37760/60000 (63%)] Loss: 0.241547 Train Epoch: 12 [38400/60000 (64%)] Loss: 0.475506 Train Epoch: 12 [39040/60000 (65%)] Loss: 0.444349 Train Epoch: 12 [39680/60000 (66%)] Loss: 0.590313 Train Epoch: 12 [40320/60000 (67%)] Loss: 0.380521 Train Epoch: 12 [40960/60000 (68%)] Loss: 0.319756 Train Epoch: 12 [41600/60000 (69%)] Loss: 0.419879 Train Epoch: 12 [42240/60000 (70%)] Loss: 0.384562 Train Epoch: 12 [42880/60000 (71%)] Loss: 0.234591 Train Epoch: 12 [43520/60000 (72%)] Loss: 0.330877 Train Epoch: 12 [44160/60000 (74%)] Loss: 0.697167 Train Epoch: 12 [44800/60000 (75%)] Loss: 0.272816 Train Epoch: 12 [45440/60000 (76%)] Loss: 0.415027 Train Epoch: 12 [46080/60000 (77%)] Loss: 0.403599 Train Epoch: 12 [46720/60000 (78%)] Loss: 0.350379 Train Epoch: 12 [47360/60000 (79%)] Loss: 0.210333 Train Epoch: 12 [48000/60000 (80%)] Loss: 0.350989 Train Epoch: 12 [48640/60000 (81%)] Loss: 0.421243 Train Epoch: 12 [49280/60000 (82%)] Loss: 0.257715 Train Epoch: 12 [49920/60000 (83%)] Loss: 0.430463 Train Epoch: 12 [50560/60000 (84%)] Loss: 0.436658 Train Epoch: 12 [51200/60000 (85%)] Loss: 0.385483 Train Epoch: 12 [51840/60000 (86%)] Loss: 0.449448 Train Epoch: 12 [52480/60000 (87%)] Loss: 0.369401 Train Epoch: 12 [53120/60000 (88%)] Loss: 0.380905 Train Epoch: 12 [53760/60000 (90%)] Loss: 0.391110 Train Epoch: 12 [54400/60000 (91%)] Loss: 0.381158 Train Epoch: 12 [55040/60000 (92%)] Loss: 0.317574 Train Epoch: 12 [55680/60000 (93%)] Loss: 0.616171 Train Epoch: 12 [56320/60000 (94%)] Loss: 0.333590 Train Epoch: 12 [56960/60000 (95%)] Loss: 0.460308 Train Epoch: 12 [57600/60000 (96%)] Loss: 0.586635 Train Epoch: 12 [58240/60000 (97%)] Loss: 0.323481 Train Epoch: 12 [58880/60000 (98%)] Loss: 0.410162 Train Epoch: 12 [59520/60000 (99%)] Loss: 0.475991 Test set: Average loss: 0.2096, Accuracy: 9381/10000 (94%) Train Epoch: 13 [0/60000 (0%)] Loss: 0.555876 Train Epoch: 13 [640/60000 (1%)] Loss: 0.298020 Train Epoch: 13 [1280/60000 (2%)] Loss: 0.341556 Train Epoch: 13 [1920/60000 (3%)] Loss: 0.387244 Train Epoch: 13 [2560/60000 (4%)] Loss: 0.299948 Train Epoch: 13 [3200/60000 (5%)] Loss: 0.352979 Train Epoch: 13 [3840/60000 (6%)] Loss: 0.445687 Train Epoch: 13 [4480/60000 (7%)] Loss: 0.223049 Train Epoch: 13 [5120/60000 (9%)] Loss: 0.494325 Train Epoch: 13 [5760/60000 (10%)] Loss: 0.749437 Train Epoch: 13 [6400/60000 (11%)] Loss: 0.404310 Train Epoch: 13 [7040/60000 (12%)] Loss: 0.337297 Train Epoch: 13 [7680/60000 (13%)] Loss: 0.434966 Train Epoch: 13 [8320/60000 (14%)] Loss: 0.401748 Train Epoch: 13 [8960/60000 (15%)] Loss: 0.340427 Train Epoch: 13 [9600/60000 (16%)] Loss: 0.614933 Train Epoch: 13 [10240/60000 (17%)] Loss: 0.428032 Train Epoch: 13 [10880/60000 (18%)] Loss: 0.520478 Train Epoch: 13 [11520/60000 (19%)] Loss: 0.343638 Train Epoch: 13 [12160/60000 (20%)] Loss: 0.282134 Train Epoch: 13 [12800/60000 (21%)] Loss: 0.236920 Train Epoch: 13 [13440/60000 (22%)] Loss: 0.331308 Train Epoch: 13 [14080/60000 (23%)] Loss: 0.342169 Train Epoch: 13 [14720/60000 (25%)] Loss: 0.494079 Train Epoch: 13 [15360/60000 (26%)] Loss: 0.566828 Train Epoch: 13 [16000/60000 (27%)] Loss: 0.515479 Train Epoch: 13 [16640/60000 (28%)] Loss: 0.546353 Train Epoch: 13 [17280/60000 (29%)] Loss: 0.462009 Train Epoch: 13 [17920/60000 (30%)] Loss: 0.547893 Train Epoch: 13 [18560/60000 (31%)] Loss: 0.519924 Train Epoch: 13 [19200/60000 (32%)] Loss: 0.445337 Train Epoch: 13 [19840/60000 (33%)] Loss: 0.254473 Train Epoch: 13 [20480/60000 (34%)] Loss: 0.351020 Train Epoch: 13 [21120/60000 (35%)] Loss: 0.388969 Train Epoch: 13 [21760/60000 (36%)] Loss: 0.285459 Train Epoch: 13 [22400/60000 (37%)] Loss: 0.308739 Train Epoch: 13 [23040/60000 (38%)] Loss: 0.501287 Train Epoch: 13 [23680/60000 (39%)] Loss: 0.392744 Train Epoch: 13 [24320/60000 (41%)] Loss: 0.490546 Train Epoch: 13 [24960/60000 (42%)] Loss: 0.407411 Train Epoch: 13 [25600/60000 (43%)] Loss: 0.557519 Train Epoch: 13 [26240/60000 (44%)] Loss: 0.407774 Train Epoch: 13 [26880/60000 (45%)] Loss: 0.313496 Train Epoch: 13 [27520/60000 (46%)] Loss: 0.470231 Train Epoch: 13 [28160/60000 (47%)] Loss: 0.457754 Train Epoch: 13 [28800/60000 (48%)] Loss: 0.314194 Train Epoch: 13 [29440/60000 (49%)] Loss: 0.395972 Train Epoch: 13 [30080/60000 (50%)] Loss: 0.575824 Train Epoch: 13 [30720/60000 (51%)] Loss: 0.275038 Train Epoch: 13 [31360/60000 (52%)] Loss: 0.376274 Train Epoch: 13 [32000/60000 (53%)] Loss: 0.517350 Train Epoch: 13 [32640/60000 (54%)] Loss: 0.386348 Train Epoch: 13 [33280/60000 (55%)] Loss: 0.315578 Train Epoch: 13 [33920/60000 (57%)] Loss: 0.385711 Train Epoch: 13 [34560/60000 (58%)] Loss: 0.308083 Train Epoch: 13 [35200/60000 (59%)] Loss: 0.412020 Train Epoch: 13 [35840/60000 (60%)] Loss: 0.630597 Train Epoch: 13 [36480/60000 (61%)] Loss: 0.530440 Train Epoch: 13 [37120/60000 (62%)] Loss: 0.324687 Train Epoch: 13 [37760/60000 (63%)] Loss: 0.334050 Train Epoch: 13 [38400/60000 (64%)] Loss: 0.539303 Train Epoch: 13 [39040/60000 (65%)] Loss: 0.168277 Train Epoch: 13 [39680/60000 (66%)] Loss: 0.218963 Train Epoch: 13 [40320/60000 (67%)] Loss: 0.526194 Train Epoch: 13 [40960/60000 (68%)] Loss: 0.554866 Train Epoch: 13 [41600/60000 (69%)] Loss: 0.519487 Train Epoch: 13 [42240/60000 (70%)] Loss: 0.659214 Train Epoch: 13 [42880/60000 (71%)] Loss: 0.347684 Train Epoch: 13 [43520/60000 (72%)] Loss: 0.218574 Train Epoch: 13 [44160/60000 (74%)] Loss: 0.498827 Train Epoch: 13 [44800/60000 (75%)] Loss: 0.428912 Train Epoch: 13 [45440/60000 (76%)] Loss: 0.554430 Train Epoch: 13 [46080/60000 (77%)] Loss: 0.334990 Train Epoch: 13 [46720/60000 (78%)] Loss: 0.312058 Train Epoch: 13 [47360/60000 (79%)] Loss: 0.393213 Train Epoch: 13 [48000/60000 (80%)] Loss: 0.328563 Train Epoch: 13 [48640/60000 (81%)] Loss: 0.441794 Train Epoch: 13 [49280/60000 (82%)] Loss: 0.487448 Train Epoch: 13 [49920/60000 (83%)] Loss: 0.393158 Train Epoch: 13 [50560/60000 (84%)] Loss: 0.413585 Train Epoch: 13 [51200/60000 (85%)] Loss: 0.331015 Train Epoch: 13 [51840/60000 (86%)] Loss: 0.293183 Train Epoch: 13 [52480/60000 (87%)] Loss: 0.448310 Train Epoch: 13 [53120/60000 (88%)] Loss: 0.275573 Train Epoch: 13 [53760/60000 (90%)] Loss: 0.361041 Train Epoch: 13 [54400/60000 (91%)] Loss: 0.270119 Train Epoch: 13 [55040/60000 (92%)] Loss: 0.339491 Train Epoch: 13 [55680/60000 (93%)] Loss: 0.460334 Train Epoch: 13 [56320/60000 (94%)] Loss: 0.355197 Train Epoch: 13 [56960/60000 (95%)] Loss: 0.324064 Train Epoch: 13 [57600/60000 (96%)] Loss: 0.461057 Train Epoch: 13 [58240/60000 (97%)] Loss: 0.520947 Train Epoch: 13 [58880/60000 (98%)] Loss: 0.555590 Train Epoch: 13 [59520/60000 (99%)] Loss: 0.347576 Test set: Average loss: 0.2075, Accuracy: 9385/10000 (94%) Train Epoch: 14 [0/60000 (0%)] Loss: 0.319042 Train Epoch: 14 [640/60000 (1%)] Loss: 0.286377 Train Epoch: 14 [1280/60000 (2%)] Loss: 0.475702 Train Epoch: 14 [1920/60000 (3%)] Loss: 0.460729 Train Epoch: 14 [2560/60000 (4%)] Loss: 0.227350 Train Epoch: 14 [3200/60000 (5%)] Loss: 0.430530 Train Epoch: 14 [3840/60000 (6%)] Loss: 0.370811 Train Epoch: 14 [4480/60000 (7%)] Loss: 0.292918 Train Epoch: 14 [5120/60000 (9%)] Loss: 0.462069 Train Epoch: 14 [5760/60000 (10%)] Loss: 0.240440 Train Epoch: 14 [6400/60000 (11%)] Loss: 0.330162 Train Epoch: 14 [7040/60000 (12%)] Loss: 0.385992 Train Epoch: 14 [7680/60000 (13%)] Loss: 0.260772 Train Epoch: 14 [8320/60000 (14%)] Loss: 0.431668 Train Epoch: 14 [8960/60000 (15%)] Loss: 0.391845 Train Epoch: 14 [9600/60000 (16%)] Loss: 0.607404 Train Epoch: 14 [10240/60000 (17%)] Loss: 0.517053 Train Epoch: 14 [10880/60000 (18%)] Loss: 0.460434 Train Epoch: 14 [11520/60000 (19%)] Loss: 0.294837 Train Epoch: 14 [12160/60000 (20%)] Loss: 0.376117 Train Epoch: 14 [12800/60000 (21%)] Loss: 0.302840 Train Epoch: 14 [13440/60000 (22%)] Loss: 0.423695 Train Epoch: 14 [14080/60000 (23%)] Loss: 0.396550 Train Epoch: 14 [14720/60000 (25%)] Loss: 0.315363 Train Epoch: 14 [15360/60000 (26%)] Loss: 0.452954 Train Epoch: 14 [16000/60000 (27%)] Loss: 0.492529 Train Epoch: 14 [16640/60000 (28%)] Loss: 0.209144 Train Epoch: 14 [17280/60000 (29%)] Loss: 0.361104 Train Epoch: 14 [17920/60000 (30%)] Loss: 0.337909 Train Epoch: 14 [18560/60000 (31%)] Loss: 0.235293 Train Epoch: 14 [19200/60000 (32%)] Loss: 0.378781 Train Epoch: 14 [19840/60000 (33%)] Loss: 0.698394 Train Epoch: 14 [20480/60000 (34%)] Loss: 0.654676 Train Epoch: 14 [21120/60000 (35%)] Loss: 0.261703 Train Epoch: 14 [21760/60000 (36%)] Loss: 0.491567 Train Epoch: 14 [22400/60000 (37%)] Loss: 0.460270 Train Epoch: 14 [23040/60000 (38%)] Loss: 0.663426 Train Epoch: 14 [23680/60000 (39%)] Loss: 0.488279 Train Epoch: 14 [24320/60000 (41%)] Loss: 0.412345 Train Epoch: 14 [24960/60000 (42%)] Loss: 0.330990 Train Epoch: 14 [25600/60000 (43%)] Loss: 0.319392 Train Epoch: 14 [26240/60000 (44%)] Loss: 0.364210 Train Epoch: 14 [26880/60000 (45%)] Loss: 0.279273 Train Epoch: 14 [27520/60000 (46%)] Loss: 0.176225 Train Epoch: 14 [28160/60000 (47%)] Loss: 0.297679 Train Epoch: 14 [28800/60000 (48%)] Loss: 0.378201 Train Epoch: 14 [29440/60000 (49%)] Loss: 0.232203 Train Epoch: 14 [30080/60000 (50%)] Loss: 0.525251 Train Epoch: 14 [30720/60000 (51%)] Loss: 0.368206 Train Epoch: 14 [31360/60000 (52%)] Loss: 0.304667 Train Epoch: 14 [32000/60000 (53%)] Loss: 0.358427 Train Epoch: 14 [32640/60000 (54%)] Loss: 0.427945 Train Epoch: 14 [33280/60000 (55%)] Loss: 0.488428 Train Epoch: 14 [33920/60000 (57%)] Loss: 0.526154 Train Epoch: 14 [34560/60000 (58%)] Loss: 0.725787 Train Epoch: 14 [35200/60000 (59%)] Loss: 0.599196 Train Epoch: 14 [35840/60000 (60%)] Loss: 0.327683 Train Epoch: 14 [36480/60000 (61%)] Loss: 0.611174 Train Epoch: 14 [37120/60000 (62%)] Loss: 0.429955 Train Epoch: 14 [37760/60000 (63%)] Loss: 0.384994 Train Epoch: 14 [38400/60000 (64%)] Loss: 0.302765 Train Epoch: 14 [39040/60000 (65%)] Loss: 0.637129 Train Epoch: 14 [39680/60000 (66%)] Loss: 0.300277 Train Epoch: 14 [40320/60000 (67%)] Loss: 0.605257 Train Epoch: 14 [40960/60000 (68%)] Loss: 0.563442 Train Epoch: 14 [41600/60000 (69%)] Loss: 0.315805 Train Epoch: 14 [42240/60000 (70%)] Loss: 0.498133 Train Epoch: 14 [42880/60000 (71%)] Loss: 0.304480 Train Epoch: 14 [43520/60000 (72%)] Loss: 0.358127 Train Epoch: 14 [44160/60000 (74%)] Loss: 0.354776 Train Epoch: 14 [44800/60000 (75%)] Loss: 0.349251 Train Epoch: 14 [45440/60000 (76%)] Loss: 0.363538 Train Epoch: 14 [46080/60000 (77%)] Loss: 0.397053 Train Epoch: 14 [46720/60000 (78%)] Loss: 0.569868 Train Epoch: 14 [47360/60000 (79%)] Loss: 0.387928 Train Epoch: 14 [48000/60000 (80%)] Loss: 0.348416 Train Epoch: 14 [48640/60000 (81%)] Loss: 0.377062 Train Epoch: 14 [49280/60000 (82%)] Loss: 0.260186 Train Epoch: 14 [49920/60000 (83%)] Loss: 0.297211 Train Epoch: 14 [50560/60000 (84%)] Loss: 0.702463 Train Epoch: 14 [51200/60000 (85%)] Loss: 0.302333 Train Epoch: 14 [51840/60000 (86%)] Loss: 0.526482 Train Epoch: 14 [52480/60000 (87%)] Loss: 0.400840 Train Epoch: 14 [53120/60000 (88%)] Loss: 0.501183 Train Epoch: 14 [53760/60000 (90%)] Loss: 0.302831 Train Epoch: 14 [54400/60000 (91%)] Loss: 0.351778 Train Epoch: 14 [55040/60000 (92%)] Loss: 0.406741 Train Epoch: 14 [55680/60000 (93%)] Loss: 0.455119 Train Epoch: 14 [56320/60000 (94%)] Loss: 0.324182 Train Epoch: 14 [56960/60000 (95%)] Loss: 0.380480 Train Epoch: 14 [57600/60000 (96%)] Loss: 0.729591 Train Epoch: 14 [58240/60000 (97%)] Loss: 0.435105 Train Epoch: 14 [58880/60000 (98%)] Loss: 0.378653 Train Epoch: 14 [59520/60000 (99%)] Loss: 0.280005 Test set: Average loss: 0.2066, Accuracy: 9386/10000 (94%)
Running on bacalhau¶
Uploading the dataset to IPFS¶
Since Container running on bacalhau has no network we need to manually upload the dateset to IPFS
we can download the dataset using pytorch datasets in this case we need to download the MNIST dataset we create a folder data where we will download the dataset
In [9]:
%%bash
mkdir ./data
In [10]:
from torchvision import datasets
from torchvision.transforms import ToTensor
training_data = datasets.MNIST(
root="./data",
train=True,
download=True,
transform=ToTensor()
)
test_data = datasets.MNIST(
root="./data",
train=False,
download=True,
transform=ToTensor()
)
Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to ./data/MNIST/raw/train-images-idx3-ubyte.gz
0%| | 0/9912422 [00:00<?, ?it/s]
Extracting ./data/MNIST/raw/train-images-idx3-ubyte.gz to ./data/MNIST/raw Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz to ./data/MNIST/raw/train-labels-idx1-ubyte.gz
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Extracting ./data/MNIST/raw/train-labels-idx1-ubyte.gz to ./data/MNIST/raw Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz to ./data/MNIST/raw/t10k-images-idx3-ubyte.gz
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Extracting ./data/MNIST/raw/t10k-images-idx3-ubyte.gz to ./data/MNIST/raw Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to ./data/MNIST/raw/t10k-labels-idx1-ubyte.gz
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Extracting ./data/MNIST/raw/t10k-labels-idx1-ubyte.gz to ./data/MNIST/raw
Uploading the dataset to IPFS¶
Using the IPFS cli
ipfs add -r data
Since the data Uploaded To IPFS using IPFS CLI isn’t pinned or will be garbage collected
The Data needs to be Pinned, Pinning is the mechanism that allows you to tell IPFS to always keep a given object somewhere, the default being your local node, though this can be different if you use a third-party remote pinning service.
There a different pinning services available you can you any one of them
Pinata¶
Click on the upload folder button
After the Upload has finished copy the CID
NFT.Storage (Recommneded Option)¶
Upload files and directories with NFTUp
To upload your dataset using NFTup just drag and drop your directory it will upload it to IPFS
Copy the CID in this case it is QmdeQjz1HQQdT9wT2NHX86Le9X6X6ySGxp8dfRUKPtgziw (If you used pinata) or bafybeif5m2md7bo2iua3kfate72kh54jgwr2spgvdtn33zdeqffh3d6qce (if you used nft.storage)
You can view you uploaded dataset by clicking on the Gateway URL
https://gateway.pinata.cloud/ipfs/QmdeQjz1HQQdT9wT2NHX86Le9X6X6ySGxp8dfRUKPtgziw/?filename=data
In [11]:
!curl -sL https://get.bacalhau.org/install.sh | bash
Your system is linux_amd64 No BACALHAU detected. Installing fresh BACALHAU CLI... Getting the latest BACALHAU CLI... Installing v0.3.13 BACALHAU CLI... Downloading https://github.com/filecoin-project/bacalhau/releases/download/v0.3.13/bacalhau_v0.3.13_linux_amd64.tar.gz ... Downloading sig file https://github.com/filecoin-project/bacalhau/releases/download/v0.3.13/bacalhau_v0.3.13_linux_amd64.tar.gz.signature.sha256 ... Verified OK Extracting tarball ... NOT verifying Bin bacalhau installed into /usr/local/bin successfully. Client Version: v0.3.13 Server Version: v0.3.13
In [13]:
%%bash --out job_id
bacalhau docker run \
--gpu 1 \
--timeout 3600 \
--wait-timeout-secs 3600 \
--wait \
--id-only \
pytorch/pytorch \
-w /outputs \
-v QmdeQjz1HQQdT9wT2NHX86Le9X6X6ySGxp8dfRUKPtgziw:/data \
-u https://raw.githubusercontent.com/pytorch/examples/main/mnist_rnn/main.py \
-- python ../inputs/main.py --save-model
Sturucture of the command
Request 1 GPU to train the model --gpu 1
Using the official pytorch docker Image pytorch/pytorch
Mounting the uploaded dataset to path /data -v QmdeQjz1HQQdT9wT2NHX86Le9X6X6ySGxp8dfRUKPtgziw:/data
Mounting our training script we will use the Training script from the pytorch examples and use the raw link of the script -u https://raw.githubusercontent.com/pytorch/examples/main/mnist_rnn/main.py
Its the folder where we will to save the model as it will automatically gets uploaded to IPFS as outputs so we choose /outputs as our working directory -w /outputs
Running the script python ../inputs/main.py --save-model
since the URL script gets mounted to the /inputs folder in the container we will execute that script but since our working directory is /outputs we provide the relave path to python to execute the script
In [14]:
%env JOB_ID={job_id}
env: JOB_ID=1658bb6b-21d1-4d1a-a278-b0984c967e14
In [16]:
%%bash
bacalhau list --id-filter ${JOB_ID}
CREATED ID JOB STATE VERIFIED PUBLISHED 14:43:37 1658bb6b Docker pytorch/pytor... Completed /ipfs/QmTZKuZJX3Zj9v...
Where it says "Completed", that means the job is done, and we can get the results.
To find out more information about your job, run the following command:
In [ ]:
%%bash
bacalhau describe ${JOB_ID}
In [15]:
%%bash
rm -rf results && mkdir -p results
bacalhau get $JOB_ID --output-dir results
Fetching results of job '1658bb6b-21d1-4d1a-a278-b0984c967e14'... Results for job '1658bb6b-21d1-4d1a-a278-b0984c967e14' have been written to... results
2022/11/21 14:46:56 failed to sufficiently increase receive buffer size (was: 208 kiB, wanted: 2048 kiB, got: 416 kiB). See https://github.com/lucas-clemente/quic-go/wiki/UDP-Receive-Buffer-Size for details.
In [17]:
%%bash
ls results/
combined_results per_shard raw
In [18]:
%%bash
cat results/combined_results/stdout
Train Epoch: 1 [0/60000 (0%)] Loss: 2.257103 Train Epoch: 1 [640/60000 (1%)] Loss: 2.343541 Train Epoch: 1 [1280/60000 (2%)] Loss: 2.286971 Train Epoch: 1 [1920/60000 (3%)] Loss: 2.278690 Train Epoch: 1 [2560/60000 (4%)] Loss: 2.325279 Train Epoch: 1 [3200/60000 (5%)] Loss: 2.156002 Train Epoch: 1 [3840/60000 (6%)] Loss: 2.213600 Train Epoch: 1 [4480/60000 (7%)] Loss: 2.205997 Train Epoch: 1 [5120/60000 (9%)] Loss: 2.104978 Train Epoch: 1 [5760/60000 (10%)] Loss: 2.133132 Train Epoch: 1 [6400/60000 (11%)] Loss: 2.141112 Train Epoch: 1 [7040/60000 (12%)] Loss: 2.029041 Train Epoch: 1 [7680/60000 (13%)] Loss: 2.038754 Train Epoch: 1 [8320/60000 (14%)] Loss: 1.982695 Train Epoch: 1 [8960/60000 (15%)] Loss: 2.027745 Train Epoch: 1 [9600/60000 (16%)] Loss: 1.933618 Train Epoch: 1 [10240/60000 (17%)] Loss: 2.001938 Train Epoch: 1 [10880/60000 (18%)] Loss: 1.990632 Train Epoch: 1 [11520/60000 (19%)] Loss: 1.903336 Train Epoch: 1 [12160/60000 (20%)] Loss: 1.927148 Train Epoch: 1 [12800/60000 (21%)] Loss: 1.932347 Train Epoch: 1 [13440/60000 (22%)] Loss: 1.768175 Train Epoch: 1 [14080/60000 (23%)] Loss: 1.793583 Train Epoch: 1 [14720/60000 (25%)] Loss: 1.698625 Train Epoch: 1 [15360/60000 (26%)] Loss: 1.919402 Train Epoch: 1 [16000/60000 (27%)] Loss: 1.819005 Train Epoch: 1 [16640/60000 (28%)] Loss: 1.798551 Train Epoch: 1 [17280/60000 (29%)] Loss: 1.752450 Train Epoch: 1 [17920/60000 (30%)] Loss: 1.580650 Train Epoch: 1 [18560/60000 (31%)] Loss: 1.669491 Train Epoch: 1 [19200/60000 (32%)] Loss: 1.666683 Train Epoch: 1 [19840/60000 (33%)] Loss: 1.746461 Train Epoch: 1 [20480/60000 (34%)] Loss: 1.750646 Train Epoch: 1 [21120/60000 (35%)] Loss: 1.704663 Train Epoch: 1 [21760/60000 (36%)] Loss: 1.545694 Train Epoch: 1 [22400/60000 (37%)] Loss: 1.800772 Train Epoch: 1 [23040/60000 (38%)] Loss: 1.807309 Train Epoch: 1 [23680/60000 (39%)] Loss: 1.531072 Train Epoch: 1 [24320/60000 (41%)] Loss: 1.644449 Train Epoch: 1 [24960/60000 (42%)] Loss: 1.440658 Train Epoch: 1 [25600/60000 (43%)] Loss: 1.572379 Train Epoch: 1 [26240/60000 (44%)] Loss: 1.542955 Train Epoch: 1 [26880/60000 (45%)] Loss: 1.636800 Train Epoch: 1 [27520/60000 (46%)] Loss: 1.732645 Train Epoch: 1 [28160/60000 (47%)] Loss: 1.556232 Train Epoch: 1 [28800/60000 (48%)] Loss: 1.797165 Train Epoch: 1 [29440/60000 (49%)] Loss: 1.550113 Train Epoch: 1 [30080/60000 (50%)] Loss: 1.513264 Train Epoch: 1 [30720/60000 (51%)] Loss: 1.349926 Train Epoch: 1 [31360/60000 (52%)] Loss: 1.168647 Train Epoch: 1 [32000/60000 (53%)] Loss: 1.371591 Train Epoch: 1 [32640/60000 (54%)] Loss: 1.360642 Train Epoch: 1 [33280/60000 (55%)] Loss: 1.319583 Train Epoch: 1 [33920/60000 (57%)] Loss: 1.470899 Train Epoch: 1 [34560/60000 (58%)] Loss: 1.229612 Train Epoch: 1 [35200/60000 (59%)] Loss: 1.355430 Train Epoch: 1 [35840/60000 (60%)] Loss: 1.162910 Train Epoch: 1 [36480/60000 (61%)] Loss: 1.264161 Train Epoch: 1 [37120/60000 (62%)] Loss: 1.304694 Train Epoch: 1 [37760/60000 (63%)] Loss: 1.245098 Train Epoch: 1 [38400/60000 (64%)] Loss: 1.276992 Train Epoch: 1 [39040/60000 (65%)] Loss: 1.224096 Train Epoch: 1 [39680/60000 (66%)] Loss: 1.017790 Train Epoch: 1 [40320/60000 (67%)] Loss: 1.265200 Train Epoch: 1 [40960/60000 (68%)] Loss: 1.095893 Train Epoch: 1 [41600/60000 (69%)] Loss: 1.253011 Train Epoch: 1 [42240/60000 (70%)] Loss: 1.309954 Train Epoch: 1 [42880/60000 (71%)] Loss: 1.072964 Train Epoch: 1 [43520/60000 (72%)] Loss: 1.278133 Train Epoch: 1 [44160/60000 (74%)] Loss: 1.042409 Train Epoch: 1 [44800/60000 (75%)] Loss: 1.204304 Train Epoch: 1 [45440/60000 (76%)] Loss: 1.224481 Train Epoch: 1 [46080/60000 (77%)] Loss: 1.168465 Train Epoch: 1 [46720/60000 (78%)] Loss: 1.225616 Train Epoch: 1 [47360/60000 (79%)] Loss: 1.107115 Train Epoch: 1 [48000/60000 (80%)] Loss: 0.964020 Train Epoch: 1 [48640/60000 (81%)] Loss: 1.150630 Train Epoch: 1 [49280/60000 (82%)] Loss: 1.298064 Train Epoch: 1 [49920/60000 (83%)] Loss: 1.385768 Train Epoch: 1 [50560/60000 (84%)] Loss: 1.130490 Train Epoch: 1 [51200/60000 (85%)] Loss: 0.967750 Train Epoch: 1 [51840/60000 (86%)] Loss: 1.239161 Train Epoch: 1 [52480/60000 (87%)] Loss: 0.985015 Train Epoch: 1 [53120/60000 (88%)] Loss: 1.048505 Train Epoch: 1 [53760/60000 (90%)] Loss: 0.928014 Train Epoch: 1 [54400/60000 (91%)] Loss: 1.156546 Train Epoch: 1 [55040/60000 (92%)] Loss: 1.117476 Train Epoch: 1 [55680/60000 (93%)] Loss: 1.082589 Train Epoch: 1 [56320/60000 (94%)] Loss: 1.037969 Train Epoch: 1 [56960/60000 (95%)] Loss: 0.901225 Train Epoch: 1 [57600/60000 (96%)] Loss: 0.939105 Train Epoch: 1 [58240/60000 (97%)] Loss: 0.977517 Train Epoch: 1 [58880/60000 (98%)] Loss: 1.061300 Train Epoch: 1 [59520/60000 (99%)] Loss: 1.161198 Test set: Average loss: 0.7476, Accuracy: 7615/10000 (76%) Train Epoch: 2 [0/60000 (0%)] Loss: 1.074720 Train Epoch: 2 [640/60000 (1%)] Loss: 1.031572 Train Epoch: 2 [1280/60000 (2%)] Loss: 0.896288 Train Epoch: 2 [1920/60000 (3%)] Loss: 1.111214 Train Epoch: 2 [2560/60000 (4%)] Loss: 1.075807 Train Epoch: 2 [3200/60000 (5%)] Loss: 0.896091 Train Epoch: 2 [3840/60000 (6%)] Loss: 0.898205 Train Epoch: 2 [4480/60000 (7%)] Loss: 0.909036 Train Epoch: 2 [5120/60000 (9%)] Loss: 0.871764 Train Epoch: 2 [5760/60000 (10%)] Loss: 0.809469 Train Epoch: 2 [6400/60000 (11%)] Loss: 1.018834 Train Epoch: 2 [7040/60000 (12%)] Loss: 0.893395 Train Epoch: 2 [7680/60000 (13%)] Loss: 0.832215 Train Epoch: 2 [8320/60000 (14%)] Loss: 0.942631 Train Epoch: 2 [8960/60000 (15%)] Loss: 0.899457 Train Epoch: 2 [9600/60000 (16%)] Loss: 1.078218 Train Epoch: 2 [10240/60000 (17%)] Loss: 0.860738 Train Epoch: 2 [10880/60000 (18%)] Loss: 0.742847 Train Epoch: 2 [11520/60000 (19%)] Loss: 1.037842 Train Epoch: 2 [12160/60000 (20%)] Loss: 1.066162 Train Epoch: 2 [12800/60000 (21%)] Loss: 0.885088 Train Epoch: 2 [13440/60000 (22%)] Loss: 0.996853 Train Epoch: 2 [14080/60000 (23%)] Loss: 0.822172 Train Epoch: 2 [14720/60000 (25%)] Loss: 0.993543 Train Epoch: 2 [15360/60000 (26%)] Loss: 0.810572 Train Epoch: 2 [16000/60000 (27%)] Loss: 1.058692 Train Epoch: 2 [16640/60000 (28%)] Loss: 0.866647 Train Epoch: 2 [17280/60000 (29%)] Loss: 0.772441 Train Epoch: 2 [17920/60000 (30%)] Loss: 0.720768 Train Epoch: 2 [18560/60000 (31%)] Loss: 0.866728 Train Epoch: 2 [19200/60000 (32%)] Loss: 0.705710 Train Epoch: 2 [19840/60000 (33%)] Loss: 0.890331 Train Epoch: 2 [20480/60000 (34%)] Loss: 0.834183 Train Epoch: 2 [21120/60000 (35%)] Loss: 0.774839 Train Epoch: 2 [21760/60000 (36%)] Loss: 0.879249 Train Epoch: 2 [22400/60000 (37%)] Loss: 0.861507 Train Epoch: 2 [23040/60000 (38%)] Loss: 0.725027 Train Epoch: 2 [23680/60000 (39%)] Loss: 0.870410 Train Epoch: 2 [24320/60000 (41%)] Loss: 0.694554 Train Epoch: 2 [24960/60000 (42%)] Loss: 0.808239 Train Epoch: 2 [25600/60000 (43%)] Loss: 0.807047 Train Epoch: 2 [26240/60000 (44%)] Loss: 0.861262 Train Epoch: 2 [26880/60000 (45%)] Loss: 0.760611 Train Epoch: 2 [27520/60000 (46%)] Loss: 0.723064 Train Epoch: 2 [28160/60000 (47%)] Loss: 0.645913 Train Epoch: 2 [28800/60000 (48%)] Loss: 0.794883 Train Epoch: 2 [29440/60000 (49%)] Loss: 1.018256 Train Epoch: 2 [30080/60000 (50%)] Loss: 0.897736 Train Epoch: 2 [30720/60000 (51%)] Loss: 1.036487 Train Epoch: 2 [31360/60000 (52%)] Loss: 0.957585 Train Epoch: 2 [32000/60000 (53%)] Loss: 0.648525 Train Epoch: 2 [32640/60000 (54%)] Loss: 0.908357 Train Epoch: 2 [33280/60000 (55%)] Loss: 0.844382 Train Epoch: 2 [33920/60000 (57%)] Loss: 0.492543 Train Epoch: 2 [34560/60000 (58%)] Loss: 0.767534 Train Epoch: 2 [35200/60000 (59%)] Loss: 0.583981 Train Epoch: 2 [35840/60000 (60%)] Loss: 0.670485 Train Epoch: 2 [36480/60000 (61%)] Loss: 0.812931 Train Epoch: 2 [37120/60000 (62%)] Loss: 0.675361 Train Epoch: 2 [37760/60000 (63%)] Loss: 0.719999 Train Epoch: 2 [38400/60000 (64%)] Loss: 0.733327 Train Epoch: 2 [39040/60000 (65%)] Loss: 0.595985 Train Epoch: 2 [39680/60000 (66%)] Loss: 0.761033 Train Epoch: 2 [40320/60000 (67%)] Loss: 0.547535 Train Epoch: 2 [40960/60000 (68%)] Loss: 0.713410 Train Epoch: 2 [41600/60000 (69%)] Loss: 0.774444 Train Epoch: 2 [42240/60000 (70%)] Loss: 0.536494 Train Epoch: 2 [42880/60000 (71%)] Loss: 0.678178 Train Epoch: 2 [43520/60000 (72%)] Loss: 0.612846 Train Epoch: 2 [44160/60000 (74%)] Loss: 0.596894 Train Epoch: 2 [44800/60000 (75%)] Loss: 0.629905 Train Epoch: 2 [45440/60000 (76%)] Loss: 0.812533 Train Epoch: 2 [46080/60000 (77%)] Loss: 0.749563 Train Epoch: 2 [46720/60000 (78%)] Loss: 0.686619 Train Epoch: 2 [47360/60000 (79%)] Loss: 0.817192 Train Epoch: 2 [48000/60000 (80%)] Loss: 0.521638 Train Epoch: 2 [48640/60000 (81%)] Loss: 0.948533 Train Epoch: 2 [49280/60000 (82%)] Loss: 0.807676 Train Epoch: 2 [49920/60000 (83%)] Loss: 0.609730 Train Epoch: 2 [50560/60000 (84%)] Loss: 0.624522 Train Epoch: 2 [51200/60000 (85%)] Loss: 0.688772 Train Epoch: 2 [51840/60000 (86%)] Loss: 0.576914 Train Epoch: 2 [52480/60000 (87%)] Loss: 0.583184 Train Epoch: 2 [53120/60000 (88%)] Loss: 0.739166 Train Epoch: 2 [53760/60000 (90%)] Loss: 0.768429 Train Epoch: 2 [54400/60000 (91%)] Loss: 0.767365 Train Epoch: 2 [55040/60000 (92%)] Loss: 0.739564 Train Epoch: 2 [55680/60000 (93%)] Loss: 0.969297 Train Epoch: 2 [56320/60000 (94%)] Loss: 0.545870 Train Epoch: 2 [56960/60000 (95%)] Loss: 0.490728 Train Epoch: 2 [57600/60000 (96%)] Loss: 0.738210 Train Epoch: 2 [58240/60000 (97%)] Loss: 0.649950 Train Epoch: 2 [58880/60000 (98%)] Loss: 0.534231 Train Epoch: 2 [59520/60000 (99%)] Loss: 0.701677 Test set: Average loss: 0.4355, Accuracy: 8636/10000 (86%) Train Epoch: 3 [0/60000 (0%)] Loss: 0.436861 Train Epoch: 3 [640/60000 (1%)] Loss: 0.613573 Train Epoch: 3 [1280/60000 (2%)] Loss: 0.751559 Train Epoch: 3 [1920/60000 (3%)] Loss: 0.518953 Train Epoch: 3 [2560/60000 (4%)] Loss: 0.706350 Train Epoch: 3 [3200/60000 (5%)] Loss: 0.463392 Train Epoch: 3 [3840/60000 (6%)] Loss: 0.637765 Train Epoch: 3 [4480/60000 (7%)] Loss: 0.707880 Train Epoch: 3 [5120/60000 (9%)] Loss: 0.705076 Train Epoch: 3 [5760/60000 (10%)] Loss: 0.473644 Train Epoch: 3 [6400/60000 (11%)] Loss: 0.566551 Train Epoch: 3 [7040/60000 (12%)] Loss: 0.554120 Train Epoch: 3 [7680/60000 (13%)] Loss: 0.735059 Train Epoch: 3 [8320/60000 (14%)] Loss: 0.492775 Train Epoch: 3 [8960/60000 (15%)] Loss: 0.705045 Train Epoch: 3 [9600/60000 (16%)] Loss: 0.723935 Train Epoch: 3 [10240/60000 (17%)] Loss: 0.657871 Train Epoch: 3 [10880/60000 (18%)] Loss: 0.546103 Train Epoch: 3 [11520/60000 (19%)] Loss: 0.576001 Train Epoch: 3 [12160/60000 (20%)] Loss: 0.762758 Train Epoch: 3 [12800/60000 (21%)] Loss: 0.672853 Train Epoch: 3 [13440/60000 (22%)] Loss: 0.690244 Train Epoch: 3 [14080/60000 (23%)] Loss: 0.491185 Train Epoch: 3 [14720/60000 (25%)] Loss: 0.819045 Train Epoch: 3 [15360/60000 (26%)] Loss: 0.633367 Train Epoch: 3 [16000/60000 (27%)] Loss: 0.631507 Train Epoch: 3 [16640/60000 (28%)] Loss: 0.742323 Train Epoch: 3 [17280/60000 (29%)] Loss: 0.769272 Train Epoch: 3 [17920/60000 (30%)] Loss: 0.547987 Train Epoch: 3 [18560/60000 (31%)] Loss: 0.726344 Train Epoch: 3 [19200/60000 (32%)] Loss: 0.500911 Train Epoch: 3 [19840/60000 (33%)] Loss: 0.609957 Train Epoch: 3 [20480/60000 (34%)] Loss: 0.567650 Train Epoch: 3 [21120/60000 (35%)] Loss: 0.592656 Train Epoch: 3 [21760/60000 (36%)] Loss: 0.659012 Train Epoch: 3 [22400/60000 (37%)] Loss: 0.792519 Train Epoch: 3 [23040/60000 (38%)] Loss: 0.649515 Train Epoch: 3 [23680/60000 (39%)] Loss: 0.535163 Train Epoch: 3 [24320/60000 (41%)] Loss: 0.510494 Train Epoch: 3 [24960/60000 (42%)] Loss: 0.753703 Train Epoch: 3 [25600/60000 (43%)] Loss: 0.588570 Train Epoch: 3 [26240/60000 (44%)] Loss: 0.524773 Train Epoch: 3 [26880/60000 (45%)] Loss: 0.654643 Train Epoch: 3 [27520/60000 (46%)] Loss: 0.464091 Train Epoch: 3 [28160/60000 (47%)] Loss: 0.517499 Train Epoch: 3 [28800/60000 (48%)] Loss: 0.743199 Train Epoch: 3 [29440/60000 (49%)] Loss: 0.712906 Train Epoch: 3 [30080/60000 (50%)] Loss: 0.898138 Train Epoch: 3 [30720/60000 (51%)] Loss: 0.471215 Train Epoch: 3 [31360/60000 (52%)] Loss: 0.586351 Train Epoch: 3 [32000/60000 (53%)] Loss: 0.619581 Train Epoch: 3 [32640/60000 (54%)] Loss: 0.431174 Train Epoch: 3 [33280/60000 (55%)] Loss: 0.805528 Train Epoch: 3 [33920/60000 (57%)] Loss: 0.434236 Train Epoch: 3 [34560/60000 (58%)] Loss: 0.833718 Train Epoch: 3 [35200/60000 (59%)] Loss: 0.737563 Train Epoch: 3 [35840/60000 (60%)] Loss: 0.814904 Train Epoch: 3 [36480/60000 (61%)] Loss: 0.658191 Train Epoch: 3 [37120/60000 (62%)] Loss: 0.642526 Train Epoch: 3 [37760/60000 (63%)] Loss: 0.528398 Train Epoch: 3 [38400/60000 (64%)] Loss: 0.401048 Train Epoch: 3 [39040/60000 (65%)] Loss: 0.638032 Train Epoch: 3 [39680/60000 (66%)] Loss: 0.885019 Train Epoch: 3 [40320/60000 (67%)] Loss: 0.639517 Train Epoch: 3 [40960/60000 (68%)] Loss: 0.777474 Train Epoch: 3 [41600/60000 (69%)] Loss: 0.529243 Train Epoch: 3 [42240/60000 (70%)] Loss: 0.383692 Train Epoch: 3 [42880/60000 (71%)] Loss: 0.399004 Train Epoch: 3 [43520/60000 (72%)] Loss: 0.602192 Train Epoch: 3 [44160/60000 (74%)] Loss: 0.728852 Train Epoch: 3 [44800/60000 (75%)] Loss: 0.605767 Train Epoch: 3 [45440/60000 (76%)] Loss: 1.022341 Train Epoch: 3 [46080/60000 (77%)] Loss: 0.670445 Train Epoch: 3 [46720/60000 (78%)] Loss: 0.567436 Train Epoch: 3 [47360/60000 (79%)] Loss: 0.486619 Train Epoch: 3 [48000/60000 (80%)] Loss: 0.636935 Train Epoch: 3 [48640/60000 (81%)] Loss: 0.501475 Train Epoch: 3 [49280/60000 (82%)] Loss: 0.448360 Train Epoch: 3 [49920/60000 (83%)] Loss: 0.548112 Train Epoch: 3 [50560/60000 (84%)] Loss: 0.518546 Train Epoch: 3 [51200/60000 (85%)] Loss: 0.460728 Train Epoch: 3 [51840/60000 (86%)] Loss: 0.566899 Train Epoch: 3 [52480/60000 (87%)] Loss: 0.455567 Train Epoch: 3 [53120/60000 (88%)] Loss: 0.590804 Train Epoch: 3 [53760/60000 (90%)] Loss: 0.655986 Train Epoch: 3 [54400/60000 (91%)] Loss: 0.603358 Train Epoch: 3 [55040/60000 (92%)] Loss: 0.498250 Train Epoch: 3 [55680/60000 (93%)] Loss: 0.582818 Train Epoch: 3 [56320/60000 (94%)] Loss: 0.671843 Train Epoch: 3 [56960/60000 (95%)] Loss: 0.562645 Train Epoch: 3 [57600/60000 (96%)] Loss: 0.710898 Train Epoch: 3 [58240/60000 (97%)] Loss: 0.704995 Train Epoch: 3 [58880/60000 (98%)] Loss: 0.426514 Train Epoch: 3 [59520/60000 (99%)] Loss: 0.586657 Test set: Average loss: 0.3266, Accuracy: 9035/10000 (90%) Train Epoch: 4 [0/60000 (0%)] Loss: 0.555241 Train Epoch: 4 [640/60000 (1%)] Loss: 0.414488 Train Epoch: 4 [1280/60000 (2%)] Loss: 0.423981 Train Epoch: 4 [1920/60000 (3%)] Loss: 0.458799 Train Epoch: 4 [2560/60000 (4%)] Loss: 0.526234 Train Epoch: 4 [3200/60000 (5%)] Loss: 0.502130 Train Epoch: 4 [3840/60000 (6%)] Loss: 0.572710 Train Epoch: 4 [4480/60000 (7%)] Loss: 0.768068 Train Epoch: 4 [5120/60000 (9%)] Loss: 0.552236 Train Epoch: 4 [5760/60000 (10%)] Loss: 0.413747 Train Epoch: 4 [6400/60000 (11%)] Loss: 0.495317 Train Epoch: 4 [7040/60000 (12%)] Loss: 0.513442 Train Epoch: 4 [7680/60000 (13%)] Loss: 0.371071 Train Epoch: 4 [8320/60000 (14%)] Loss: 0.537922 Train Epoch: 4 [8960/60000 (15%)] Loss: 0.550542 Train Epoch: 4 [9600/60000 (16%)] Loss: 0.492354 Train Epoch: 4 [10240/60000 (17%)] Loss: 0.430003 Train Epoch: 4 [10880/60000 (18%)] Loss: 0.676727 Train Epoch: 4 [11520/60000 (19%)] Loss: 0.522242 Train Epoch: 4 [12160/60000 (20%)] Loss: 0.323046 Train Epoch: 4 [12800/60000 (21%)] Loss: 0.413817 Train Epoch: 4 [13440/60000 (22%)] Loss: 0.493616 Train Epoch: 4 [14080/60000 (23%)] Loss: 0.482043 Train Epoch: 4 [14720/60000 (25%)] Loss: 0.598020 Train Epoch: 4 [15360/60000 (26%)] Loss: 0.698045 Train Epoch: 4 [16000/60000 (27%)] Loss: 0.464925 Train Epoch: 4 [16640/60000 (28%)] Loss: 0.598145 Train Epoch: 4 [17280/60000 (29%)] Loss: 0.513251 Train Epoch: 4 [17920/60000 (30%)] Loss: 0.383759 Train Epoch: 4 [18560/60000 (31%)] Loss: 0.451445 Train Epoch: 4 [19200/60000 (32%)] Loss: 0.298578 Train Epoch: 4 [19840/60000 (33%)] Loss: 0.724677 Train Epoch: 4 [20480/60000 (34%)] Loss: 0.648704 Train Epoch: 4 [21120/60000 (35%)] Loss: 0.417878 Train Epoch: 4 [21760/60000 (36%)] Loss: 0.587597 Train Epoch: 4 [22400/60000 (37%)] Loss: 0.650825 Train Epoch: 4 [23040/60000 (38%)] Loss: 0.461850 Train Epoch: 4 [23680/60000 (39%)] Loss: 0.498996 Train Epoch: 4 [24320/60000 (41%)] Loss: 0.272354 Train Epoch: 4 [24960/60000 (42%)] Loss: 0.552614 Train Epoch: 4 [25600/60000 (43%)] Loss: 0.559007 Train Epoch: 4 [26240/60000 (44%)] Loss: 0.514660 Train Epoch: 4 [26880/60000 (45%)] Loss: 0.449900 Train Epoch: 4 [27520/60000 (46%)] Loss: 0.459001 Train Epoch: 4 [28160/60000 (47%)] Loss: 0.510848 Train Epoch: 4 [28800/60000 (48%)] Loss: 0.376767 Train Epoch: 4 [29440/60000 (49%)] Loss: 0.663157 Train Epoch: 4 [30080/60000 (50%)] Loss: 0.380203 Train Epoch: 4 [30720/60000 (51%)] Loss: 0.487593 Train Epoch: 4 [31360/60000 (52%)] Loss: 0.368222 Train Epoch: 4 [32000/60000 (53%)] Loss: 0.531884 Train Epoch: 4 [32640/60000 (54%)] Loss: 0.514744 Train Epoch: 4 [33280/60000 (55%)] Loss: 0.413709 Train Epoch: 4 [33920/60000 (57%)] Loss: 0.466324 Train Epoch: 4 [34560/60000 (58%)] Loss: 0.481780 Train Epoch: 4 [35200/60000 (59%)] Loss: 0.332192 Train Epoch: 4 [35840/60000 (60%)] Loss: 0.535553 Train Epoch: 4 [36480/60000 (61%)] Loss: 0.701526 Train Epoch: 4 [37120/60000 (62%)] Loss: 0.472824 Train Epoch: 4 [37760/60000 (63%)] Loss: 0.506160 Train Epoch: 4 [38400/60000 (64%)] Loss: 0.434093 Train Epoch: 4 [39040/60000 (65%)] Loss: 0.458589 Train Epoch: 4 [39680/60000 (66%)] Loss: 0.571873 Train Epoch: 4 [40320/60000 (67%)] Loss: 0.417425 Train Epoch: 4 [40960/60000 (68%)] Loss: 0.562600 Train Epoch: 4 [41600/60000 (69%)] Loss: 0.595764 Train Epoch: 4 [42240/60000 (70%)] Loss: 0.763260 Train Epoch: 4 [42880/60000 (71%)] Loss: 0.449961 Train Epoch: 4 [43520/60000 (72%)] Loss: 0.504708 Train Epoch: 4 [44160/60000 (74%)] Loss: 0.518068 Train Epoch: 4 [44800/60000 (75%)] Loss: 0.457749 Train Epoch: 4 [45440/60000 (76%)] Loss: 0.556885 Train Epoch: 4 [46080/60000 (77%)] Loss: 0.407525 Train Epoch: 4 [46720/60000 (78%)] Loss: 0.627191 Train Epoch: 4 [47360/60000 (79%)] Loss: 0.640686 Train Epoch: 4 [48000/60000 (80%)] Loss: 0.461735 Train Epoch: 4 [48640/60000 (81%)] Loss: 0.440985 Train Epoch: 4 [49280/60000 (82%)] Loss: 0.617622 Train Epoch: 4 [49920/60000 (83%)] Loss: 0.502659 Train Epoch: 4 [50560/60000 (84%)] Loss: 0.525112 Train Epoch: 4 [51200/60000 (85%)] Loss: 0.530758 Train Epoch: 4 [51840/60000 (86%)] Loss: 0.327249 Train Epoch: 4 [52480/60000 (87%)] Loss: 0.392865 Train Epoch: 4 [53120/60000 (88%)] Loss: 0.716493 Train Epoch: 4 [53760/60000 (90%)] Loss: 0.916052 Train Epoch: 4 [54400/60000 (91%)] Loss: 0.398535 Train Epoch: 4 [55040/60000 (92%)] Loss: 0.514751 Train Epoch: 4 [55680/60000 (93%)] Loss: 0.466898 Train Epoch: 4 [56320/60000 (94%)] Loss: 0.446998 Train Epoch: 4 [56960/60000 (95%)] Loss: 0.575153 Train Epoch: 4 [57600/60000 (96%)] Loss: 0.578760 Train Epoch: 4 [58240/60000 (97%)] Loss: 0.473565 Train Epoch: 4 [58880/60000 (98%)] Loss: 0.520567 Train Epoch: 4 [59520/60000 (99%)] Loss: 0.242124 Test set: Average loss: 0.2797, Accuracy: 9146/10000 (91%) Train Epoch: 5 [0/60000 (0%)] Loss: 0.509089 Train Epoch: 5 [640/60000 (1%)] Loss: 0.581981 Train Epoch: 5 [1280/60000 (2%)] Loss: 0.393444 Train Epoch: 5 [1920/60000 (3%)] Loss: 0.635975 Train Epoch: 5 [2560/60000 (4%)] Loss: 0.359194 Train Epoch: 5 [3200/60000 (5%)] Loss: 0.446414 Train Epoch: 5 [3840/60000 (6%)] Loss: 0.638959 Train Epoch: 5 [4480/60000 (7%)] Loss: 0.456178 Train Epoch: 5 [5120/60000 (9%)] Loss: 0.676888 Train Epoch: 5 [5760/60000 (10%)] Loss: 0.725724 Train Epoch: 5 [6400/60000 (11%)] Loss: 0.758731 Train Epoch: 5 [7040/60000 (12%)] Loss: 0.298135 Train Epoch: 5 [7680/60000 (13%)] Loss: 0.498484 Train Epoch: 5 [8320/60000 (14%)] Loss: 0.781466 Train Epoch: 5 [8960/60000 (15%)] Loss: 0.372765 Train Epoch: 5 [9600/60000 (16%)] Loss: 0.551780 Train Epoch: 5 [10240/60000 (17%)] Loss: 0.671177 Train Epoch: 5 [10880/60000 (18%)] Loss: 0.386135 Train Epoch: 5 [11520/60000 (19%)] Loss: 0.429770 Train Epoch: 5 [12160/60000 (20%)] Loss: 0.351372 Train Epoch: 5 [12800/60000 (21%)] Loss: 0.712960 Train Epoch: 5 [13440/60000 (22%)] Loss: 0.696321 Train Epoch: 5 [14080/60000 (23%)] Loss: 0.242317 Train Epoch: 5 [14720/60000 (25%)] Loss: 0.757245 Train Epoch: 5 [15360/60000 (26%)] Loss: 0.641723 Train Epoch: 5 [16000/60000 (27%)] Loss: 0.303924 Train Epoch: 5 [16640/60000 (28%)] Loss: 0.451921 Train Epoch: 5 [17280/60000 (29%)] Loss: 0.546511 Train Epoch: 5 [17920/60000 (30%)] Loss: 0.449047 Train Epoch: 5 [18560/60000 (31%)] Loss: 0.497756 Train Epoch: 5 [19200/60000 (32%)] Loss: 0.590394 Train Epoch: 5 [19840/60000 (33%)] Loss: 0.591735 Train Epoch: 5 [20480/60000 (34%)] Loss: 0.422177 Train Epoch: 5 [21120/60000 (35%)] Loss: 0.596936 Train Epoch: 5 [21760/60000 (36%)] Loss: 0.533217 Train Epoch: 5 [22400/60000 (37%)] Loss: 0.441299 Train Epoch: 5 [23040/60000 (38%)] Loss: 0.472163 Train Epoch: 5 [23680/60000 (39%)] Loss: 0.565845 Train Epoch: 5 [24320/60000 (41%)] Loss: 0.585979 Train Epoch: 5 [24960/60000 (42%)] Loss: 0.654992 Train Epoch: 5 [25600/60000 (43%)] Loss: 0.646539 Train Epoch: 5 [26240/60000 (44%)] Loss: 0.327595 Train Epoch: 5 [26880/60000 (45%)] Loss: 0.361459 Train Epoch: 5 [27520/60000 (46%)] Loss: 0.527023 Train Epoch: 5 [28160/60000 (47%)] Loss: 0.510979 Train Epoch: 5 [28800/60000 (48%)] Loss: 0.596272 Train Epoch: 5 [29440/60000 (49%)] Loss: 0.641762 Train Epoch: 5 [30080/60000 (50%)] Loss: 0.352163 Train Epoch: 5 [30720/60000 (51%)] Loss: 0.477677 Train Epoch: 5 [31360/60000 (52%)] Loss: 0.331182 Train Epoch: 5 [32000/60000 (53%)] Loss: 0.546108 Train Epoch: 5 [32640/60000 (54%)] Loss: 0.691825 Train Epoch: 5 [33280/60000 (55%)] Loss: 0.432296 Train Epoch: 5 [33920/60000 (57%)] Loss: 0.293409 Train Epoch: 5 [34560/60000 (58%)] Loss: 0.461842 Train Epoch: 5 [35200/60000 (59%)] Loss: 0.441172 Train Epoch: 5 [35840/60000 (60%)] Loss: 0.450768 Train Epoch: 5 [36480/60000 (61%)] Loss: 0.479811 Train Epoch: 5 [37120/60000 (62%)] Loss: 0.368303 Train Epoch: 5 [37760/60000 (63%)] Loss: 0.714117 Train Epoch: 5 [38400/60000 (64%)] Loss: 0.512306 Train Epoch: 5 [39040/60000 (65%)] Loss: 0.353668 Train Epoch: 5 [39680/60000 (66%)] Loss: 0.634520 Train Epoch: 5 [40320/60000 (67%)] Loss: 0.508756 Train Epoch: 5 [40960/60000 (68%)] Loss: 0.574379 Train Epoch: 5 [41600/60000 (69%)] Loss: 0.515620 Train Epoch: 5 [42240/60000 (70%)] Loss: 0.340576 Train Epoch: 5 [42880/60000 (71%)] Loss: 0.285465 Train Epoch: 5 [43520/60000 (72%)] Loss: 0.502436 Train Epoch: 5 [44160/60000 (74%)] Loss: 0.399609 Train Epoch: 5 [44800/60000 (75%)] Loss: 0.348736 Train Epoch: 5 [45440/60000 (76%)] Loss: 0.346850 Train Epoch: 5 [46080/60000 (77%)] Loss: 0.276397 Train Epoch: 5 [46720/60000 (78%)] Loss: 0.838089 Train Epoch: 5 [47360/60000 (79%)] Loss: 0.402148 Train Epoch: 5 [48000/60000 (80%)] Loss: 0.303684 Train Epoch: 5 [48640/60000 (81%)] Loss: 0.553139 Train Epoch: 5 [49280/60000 (82%)] Loss: 0.497245 Train Epoch: 5 [49920/60000 (83%)] Loss: 0.535974 Train Epoch: 5 [50560/60000 (84%)] Loss: 0.429837 Train Epoch: 5 [51200/60000 (85%)] Loss: 0.462402 Train Epoch: 5 [51840/60000 (86%)] Loss: 0.443050 Train Epoch: 5 [52480/60000 (87%)] Loss: 0.449189 Train Epoch: 5 [53120/60000 (88%)] Loss: 0.407580 Train Epoch: 5 [53760/60000 (90%)] Loss: 0.709943 Train Epoch: 5 [54400/60000 (91%)] Loss: 0.663003 Train Epoch: 5 [55040/60000 (92%)] Loss: 0.664517 Train Epoch: 5 [55680/60000 (93%)] Loss: 0.559337 Train Epoch: 5 [56320/60000 (94%)] Loss: 0.369790 Train Epoch: 5 [56960/60000 (95%)] Loss: 0.673157 Train Epoch: 5 [57600/60000 (96%)] Loss: 0.338669 Train Epoch: 5 [58240/60000 (97%)] Loss: 0.492030 Train Epoch: 5 [58880/60000 (98%)] Loss: 0.344073 Train Epoch: 5 [59520/60000 (99%)] Loss: 0.422336 Test set: Average loss: 0.2519, Accuracy: 9238/10000 (92%) Train Epoch: 6 [0/60000 (0%)] Loss: 0.386451 Train Epoch: 6 [640/60000 (1%)] Loss: 0.457663 Train Epoch: 6 [1280/60000 (2%)] Loss: 0.515762 Train Epoch: 6 [1920/60000 (3%)] Loss: 0.612986 Train Epoch: 6 [2560/60000 (4%)] Loss: 0.787486 Train Epoch: 6 [3200/60000 (5%)] Loss: 0.491760 Train Epoch: 6 [3840/60000 (6%)] Loss: 0.454228 Train Epoch: 6 [4480/60000 (7%)] Loss: 0.359811 Train Epoch: 6 [5120/60000 (9%)] Loss: 0.368993 Train Epoch: 6 [5760/60000 (10%)] Loss: 0.442591 Train Epoch: 6 [6400/60000 (11%)] Loss: 0.597940 Train Epoch: 6 [7040/60000 (12%)] Loss: 0.383114 Train Epoch: 6 [7680/60000 (13%)] Loss: 0.362789 Train Epoch: 6 [8320/60000 (14%)] Loss: 0.514896 Train Epoch: 6 [8960/60000 (15%)] Loss: 0.774907 Train Epoch: 6 [9600/60000 (16%)] Loss: 0.390480 Train Epoch: 6 [10240/60000 (17%)] Loss: 0.584314 Train Epoch: 6 [10880/60000 (18%)] Loss: 0.288985 Train Epoch: 6 [11520/60000 (19%)] Loss: 0.426987 Train Epoch: 6 [12160/60000 (20%)] Loss: 0.278613 Train Epoch: 6 [12800/60000 (21%)] Loss: 0.499849 Train Epoch: 6 [13440/60000 (22%)] Loss: 0.431185 Train Epoch: 6 [14080/60000 (23%)] Loss: 0.689421 Train Epoch: 6 [14720/60000 (25%)] Loss: 0.337867 Train Epoch: 6 [15360/60000 (26%)] Loss: 0.626686 Train Epoch: 6 [16000/60000 (27%)] Loss: 0.497805 Train Epoch: 6 [16640/60000 (28%)] Loss: 0.441193 Train Epoch: 6 [17280/60000 (29%)] Loss: 0.561231 Train Epoch: 6 [17920/60000 (30%)] Loss: 0.401973 Train Epoch: 6 [18560/60000 (31%)] Loss: 0.561977 Train Epoch: 6 [19200/60000 (32%)] Loss: 0.410718 Train Epoch: 6 [19840/60000 (33%)] Loss: 0.770684 Train Epoch: 6 [20480/60000 (34%)] Loss: 0.639804 Train Epoch: 6 [21120/60000 (35%)] Loss: 0.302792 Train Epoch: 6 [21760/60000 (36%)] Loss: 0.529687 Train Epoch: 6 [22400/60000 (37%)] Loss: 0.717905 Train Epoch: 6 [23040/60000 (38%)] Loss: 0.498946 Train Epoch: 6 [23680/60000 (39%)] Loss: 0.429929 Train Epoch: 6 [24320/60000 (41%)] Loss: 0.435225 Train Epoch: 6 [24960/60000 (42%)] Loss: 0.320319 Train Epoch: 6 [25600/60000 (43%)] Loss: 0.590387 Train Epoch: 6 [26240/60000 (44%)] Loss: 0.265355 Train Epoch: 6 [26880/60000 (45%)] Loss: 0.454372 Train Epoch: 6 [27520/60000 (46%)] Loss: 0.790875 Train Epoch: 6 [28160/60000 (47%)] Loss: 0.486921 Train Epoch: 6 [28800/60000 (48%)] Loss: 0.462752 Train Epoch: 6 [29440/60000 (49%)] Loss: 0.813336 Train Epoch: 6 [30080/60000 (50%)] Loss: 0.308711 Train Epoch: 6 [30720/60000 (51%)] Loss: 0.476948 Train Epoch: 6 [31360/60000 (52%)] Loss: 0.649331 Train Epoch: 6 [32000/60000 (53%)] Loss: 0.337971 Train Epoch: 6 [32640/60000 (54%)] Loss: 0.552407 Train Epoch: 6 [33280/60000 (55%)] Loss: 0.584258 Train Epoch: 6 [33920/60000 (57%)] Loss: 0.682540 Train Epoch: 6 [34560/60000 (58%)] Loss: 0.472494 Train Epoch: 6 [35200/60000 (59%)] Loss: 0.581826 Train Epoch: 6 [35840/60000 (60%)] Loss: 0.430555 Train Epoch: 6 [36480/60000 (61%)] Loss: 0.408300 Train Epoch: 6 [37120/60000 (62%)] Loss: 0.544223 Train Epoch: 6 [37760/60000 (63%)] Loss: 0.276038 Train Epoch: 6 [38400/60000 (64%)] Loss: 0.383865 Train Epoch: 6 [39040/60000 (65%)] Loss: 0.486723 Train Epoch: 6 [39680/60000 (66%)] Loss: 0.401155 Train Epoch: 6 [40320/60000 (67%)] Loss: 0.501816 Train Epoch: 6 [40960/60000 (68%)] Loss: 0.514987 Train Epoch: 6 [41600/60000 (69%)] Loss: 0.501831 Train Epoch: 6 [42240/60000 (70%)] Loss: 0.471296 Train Epoch: 6 [42880/60000 (71%)] Loss: 0.467298 Train Epoch: 6 [43520/60000 (72%)] Loss: 0.421591 Train Epoch: 6 [44160/60000 (74%)] Loss: 0.485595 Train Epoch: 6 [44800/60000 (75%)] Loss: 0.450340 Train Epoch: 6 [45440/60000 (76%)] Loss: 0.339639 Train Epoch: 6 [46080/60000 (77%)] Loss: 0.386936 Train Epoch: 6 [46720/60000 (78%)] Loss: 0.288080 Train Epoch: 6 [47360/60000 (79%)] Loss: 0.448823 Train Epoch: 6 [48000/60000 (80%)] Loss: 0.774343 Train Epoch: 6 [48640/60000 (81%)] Loss: 0.379256 Train Epoch: 6 [49280/60000 (82%)] Loss: 0.430137 Train Epoch: 6 [49920/60000 (83%)] Loss: 0.486229 Train Epoch: 6 [50560/60000 (84%)] Loss: 0.548015 Train Epoch: 6 [51200/60000 (85%)] Loss: 0.312752 Train Epoch: 6 [51840/60000 (86%)] Loss: 0.405820 Train Epoch: 6 [52480/60000 (87%)] Loss: 0.346440 Train Epoch: 6 [53120/60000 (88%)] Loss: 0.289083 Train Epoch: 6 [53760/60000 (90%)] Loss: 0.595599 Train Epoch: 6 [54400/60000 (91%)] Loss: 0.303218 Train Epoch: 6 [55040/60000 (92%)] Loss: 0.461978 Train Epoch: 6 [55680/60000 (93%)] Loss: 0.425981 Train Epoch: 6 [56320/60000 (94%)] Loss: 0.318439 Train Epoch: 6 [56960/60000 (95%)] Loss: 0.555306 Train Epoch: 6 [57600/60000 (96%)] Loss: 0.662118 Train Epoch: 6 [58240/60000 (97%)] Loss: 0.489320 Train Epoch: 6 [58880/60000 (98%)] Loss: 0.406899 Train Epoch: 6 [59520/60000 (99%)] Loss: 0.385348 Test set: Average loss: 0.2355, Accuracy: 9277/10000 (93%) Train Epoch: 7 [0/60000 (0%)] Loss: 0.717746 Train Epoch: 7 [640/60000 (1%)] Loss: 0.469850 Train Epoch: 7 [1280/60000 (2%)] Loss: 0.594132 Train Epoch: 7 [1920/60000 (3%)] Loss: 0.475335 Train Epoch: 7 [2560/60000 (4%)] Loss: 0.430496 Train Epoch: 7 [3200/60000 (5%)] Loss: 0.294112 Train Epoch: 7 [3840/60000 (6%)] Loss: 0.312968 Train Epoch: 7 [4480/60000 (7%)] Loss: 0.362220 Train Epoch: 7 [5120/60000 (9%)] Loss: 0.429730 Train Epoch: 7 [5760/60000 (10%)] Loss: 0.357846 Train Epoch: 7 [6400/60000 (11%)] Loss: 0.336342 Train Epoch: 7 [7040/60000 (12%)] Loss: 0.553370 Train Epoch: 7 [7680/60000 (13%)] Loss: 0.517778 Train Epoch: 7 [8320/60000 (14%)] Loss: 0.441374 Train Epoch: 7 [8960/60000 (15%)] Loss: 0.242141 Train Epoch: 7 [9600/60000 (16%)] Loss: 0.288597 Train Epoch: 7 [10240/60000 (17%)] Loss: 0.355947 Train Epoch: 7 [10880/60000 (18%)] Loss: 0.225561 Train Epoch: 7 [11520/60000 (19%)] Loss: 0.556642 Train Epoch: 7 [12160/60000 (20%)] Loss: 0.426134 Train Epoch: 7 [12800/60000 (21%)] Loss: 0.408436 Train Epoch: 7 [13440/60000 (22%)] Loss: 0.452092 Train Epoch: 7 [14080/60000 (23%)] Loss: 0.417876 Train Epoch: 7 [14720/60000 (25%)] Loss: 0.312885 Train Epoch: 7 [15360/60000 (26%)] Loss: 0.513127 Train Epoch: 7 [16000/60000 (27%)] Loss: 0.371684 Train Epoch: 7 [16640/60000 (28%)] Loss: 0.347489 Train Epoch: 7 [17280/60000 (29%)] Loss: 0.463195 Train Epoch: 7 [17920/60000 (30%)] Loss: 0.391325 Train Epoch: 7 [18560/60000 (31%)] Loss: 0.483348 Train Epoch: 7 [19200/60000 (32%)] Loss: 0.341747 Train Epoch: 7 [19840/60000 (33%)] Loss: 0.484753 Train Epoch: 7 [20480/60000 (34%)] Loss: 0.342775 Train Epoch: 7 [21120/60000 (35%)] Loss: 0.680684 Train Epoch: 7 [21760/60000 (36%)] Loss: 0.297526 Train Epoch: 7 [22400/60000 (37%)] Loss: 0.473823 Train Epoch: 7 [23040/60000 (38%)] Loss: 0.535453 Train Epoch: 7 [23680/60000 (39%)] Loss: 0.457003 Train Epoch: 7 [24320/60000 (41%)] Loss: 0.428764 Train Epoch: 7 [24960/60000 (42%)] Loss: 0.437032 Train Epoch: 7 [25600/60000 (43%)] Loss: 0.626991 Train Epoch: 7 [26240/60000 (44%)] Loss: 0.401498 Train Epoch: 7 [26880/60000 (45%)] Loss: 0.341815 Train Epoch: 7 [27520/60000 (46%)] Loss: 0.347058 Train Epoch: 7 [28160/60000 (47%)] Loss: 0.592645 Train Epoch: 7 [28800/60000 (48%)] Loss: 0.486121 Train Epoch: 7 [29440/60000 (49%)] Loss: 0.521025 Train Epoch: 7 [30080/60000 (50%)] Loss: 0.396133 Train Epoch: 7 [30720/60000 (51%)] Loss: 0.568312 Train Epoch: 7 [31360/60000 (52%)] Loss: 0.475080 Train Epoch: 7 [32000/60000 (53%)] Loss: 0.496030 Train Epoch: 7 [32640/60000 (54%)] Loss: 0.321438 Train Epoch: 7 [33280/60000 (55%)] Loss: 0.361846 Train Epoch: 7 [33920/60000 (57%)] Loss: 0.436478 Train Epoch: 7 [34560/60000 (58%)] Loss: 0.532364 Train Epoch: 7 [35200/60000 (59%)] Loss: 0.510952 Train Epoch: 7 [35840/60000 (60%)] Loss: 0.645716 Train Epoch: 7 [36480/60000 (61%)] Loss: 0.459233 Train Epoch: 7 [37120/60000 (62%)] Loss: 0.372445 Train Epoch: 7 [37760/60000 (63%)] Loss: 0.232452 Train Epoch: 7 [38400/60000 (64%)] Loss: 0.349685 Train Epoch: 7 [39040/60000 (65%)] Loss: 0.594317 Train Epoch: 7 [39680/60000 (66%)] Loss: 0.716788 Train Epoch: 7 [40320/60000 (67%)] Loss: 0.736326 Train Epoch: 7 [40960/60000 (68%)] Loss: 0.434928 Train Epoch: 7 [41600/60000 (69%)] Loss: 0.504802 Train Epoch: 7 [42240/60000 (70%)] Loss: 0.458648 Train Epoch: 7 [42880/60000 (71%)] Loss: 0.433149 Train Epoch: 7 [43520/60000 (72%)] Loss: 0.291753 Train Epoch: 7 [44160/60000 (74%)] Loss: 0.414158 Train Epoch: 7 [44800/60000 (75%)] Loss: 0.387175 Train Epoch: 7 [45440/60000 (76%)] Loss: 0.412587 Train Epoch: 7 [46080/60000 (77%)] Loss: 0.396877 Train Epoch: 7 [46720/60000 (78%)] Loss: 0.497912 Train Epoch: 7 [47360/60000 (79%)] Loss: 0.428157 Train Epoch: 7 [48000/60000 (80%)] Loss: 0.457888 Train Epoch: 7 [48640/60000 (81%)] Loss: 0.519679 Train Epoch: 7 [49280/60000 (82%)] Loss: 0.357949 Train Epoch: 7 [49920/60000 (83%)] Loss: 0.349139 Train Epoch: 7 [50560/60000 (84%)] Loss: 0.389948 Train Epoch: 7 [51200/60000 (85%)] Loss: 0.426888 Train Epoch: 7 [51840/60000 (86%)] Loss: 0.348460 Train Epoch: 7 [52480/60000 (87%)] Loss: 0.596196 Train Epoch: 7 [53120/60000 (88%)] Loss: 0.567125 Train Epoch: 7 [53760/60000 (90%)] Loss: 0.301156 Train Epoch: 7 [54400/60000 (91%)] Loss: 0.650556 Train Epoch: 7 [55040/60000 (92%)] Loss: 0.716238 Train Epoch: 7 [55680/60000 (93%)] Loss: 0.478881 Train Epoch: 7 [56320/60000 (94%)] Loss: 0.421738 Train Epoch: 7 [56960/60000 (95%)] Loss: 0.435452 Train Epoch: 7 [57600/60000 (96%)] Loss: 0.639111 Train Epoch: 7 [58240/60000 (97%)] Loss: 0.387537 Train Epoch: 7 [58880/60000 (98%)] Loss: 0.839673 Train Epoch: 7 [59520/60000 (99%)] Loss: 0.409900 Test set: Average loss: 0.2244, Accuracy: 9333/10000 (93%) Train Epoch: 8 [0/60000 (0%)] Loss: 0.469117 Train Epoch: 8 [640/60000 (1%)] Loss: 0.369546 Train Epoch: 8 [1280/60000 (2%)] Loss: 0.205326 Train Epoch: 8 [1920/60000 (3%)] Loss: 0.377605 Train Epoch: 8 [2560/60000 (4%)] Loss: 0.759715 Train Epoch: 8 [3200/60000 (5%)] Loss: 0.435699 Train Epoch: 8 [3840/60000 (6%)] Loss: 0.496597 Train Epoch: 8 [4480/60000 (7%)] Loss: 0.382842 Train Epoch: 8 [5120/60000 (9%)] Loss: 0.572179 Train Epoch: 8 [5760/60000 (10%)] Loss: 0.510330 Train Epoch: 8 [6400/60000 (11%)] Loss: 0.479856 Train Epoch: 8 [7040/60000 (12%)] Loss: 0.630408 Train Epoch: 8 [7680/60000 (13%)] Loss: 0.418155 Train Epoch: 8 [8320/60000 (14%)] Loss: 0.401250 Train Epoch: 8 [8960/60000 (15%)] Loss: 0.618374 Train Epoch: 8 [9600/60000 (16%)] Loss: 0.614909 Train Epoch: 8 [10240/60000 (17%)] Loss: 0.318959 Train Epoch: 8 [10880/60000 (18%)] Loss: 0.337133 Train Epoch: 8 [11520/60000 (19%)] Loss: 0.797270 Train Epoch: 8 [12160/60000 (20%)] Loss: 0.405077 Train Epoch: 8 [12800/60000 (21%)] Loss: 0.660093 Train Epoch: 8 [13440/60000 (22%)] Loss: 0.607703 Train Epoch: 8 [14080/60000 (23%)] Loss: 0.496708 Train Epoch: 8 [14720/60000 (25%)] Loss: 0.288580 Train Epoch: 8 [15360/60000 (26%)] Loss: 0.542241 Train Epoch: 8 [16000/60000 (27%)] Loss: 0.460526 Train Epoch: 8 [16640/60000 (28%)] Loss: 0.513786 Train Epoch: 8 [17280/60000 (29%)] Loss: 0.357061 Train Epoch: 8 [17920/60000 (30%)] Loss: 0.301968 Train Epoch: 8 [18560/60000 (31%)] Loss: 0.418004 Train Epoch: 8 [19200/60000 (32%)] Loss: 0.445466 Train Epoch: 8 [19840/60000 (33%)] Loss: 0.381778 Train Epoch: 8 [20480/60000 (34%)] Loss: 0.454850 Train Epoch: 8 [21120/60000 (35%)] Loss: 0.311810 Train Epoch: 8 [21760/60000 (36%)] Loss: 0.547685 Train Epoch: 8 [22400/60000 (37%)] Loss: 0.196215 Train Epoch: 8 [23040/60000 (38%)] Loss: 0.286037 Train Epoch: 8 [23680/60000 (39%)] Loss: 0.477281 Train Epoch: 8 [24320/60000 (41%)] Loss: 0.818387 Train Epoch: 8 [24960/60000 (42%)] Loss: 0.514256 Train Epoch: 8 [25600/60000 (43%)] Loss: 0.455588 Train Epoch: 8 [26240/60000 (44%)] Loss: 0.365949 Train Epoch: 8 [26880/60000 (45%)] Loss: 0.358121 Train Epoch: 8 [27520/60000 (46%)] Loss: 0.453270 Train Epoch: 8 [28160/60000 (47%)] Loss: 0.543010 Train Epoch: 8 [28800/60000 (48%)] Loss: 0.643081 Train Epoch: 8 [29440/60000 (49%)] Loss: 0.510997 Train Epoch: 8 [30080/60000 (50%)] Loss: 0.316055 Train Epoch: 8 [30720/60000 (51%)] Loss: 0.675489 Train Epoch: 8 [31360/60000 (52%)] Loss: 0.303624 Train Epoch: 8 [32000/60000 (53%)] Loss: 0.449534 Train Epoch: 8 [32640/60000 (54%)] Loss: 0.451441 Train Epoch: 8 [33280/60000 (55%)] Loss: 0.478364 Train Epoch: 8 [33920/60000 (57%)] Loss: 0.425091 Train Epoch: 8 [34560/60000 (58%)] Loss: 0.211938 Train Epoch: 8 [35200/60000 (59%)] Loss: 0.356066 Train Epoch: 8 [35840/60000 (60%)] Loss: 0.646257 Train Epoch: 8 [36480/60000 (61%)] Loss: 0.643567 Train Epoch: 8 [37120/60000 (62%)] Loss: 0.322013 Train Epoch: 8 [37760/60000 (63%)] Loss: 0.407144 Train Epoch: 8 [38400/60000 (64%)] Loss: 0.543189 Train Epoch: 8 [39040/60000 (65%)] Loss: 0.287052 Train Epoch: 8 [39680/60000 (66%)] Loss: 0.351675 Train Epoch: 8 [40320/60000 (67%)] Loss: 0.288525 Train Epoch: 8 [40960/60000 (68%)] Loss: 0.453517 Train Epoch: 8 [41600/60000 (69%)] Loss: 0.253906 Train Epoch: 8 [42240/60000 (70%)] Loss: 0.512110 Train Epoch: 8 [42880/60000 (71%)] Loss: 0.590715 Train Epoch: 8 [43520/60000 (72%)] Loss: 0.325584 Train Epoch: 8 [44160/60000 (74%)] Loss: 0.482525 Train Epoch: 8 [44800/60000 (75%)] Loss: 0.337738 Train Epoch: 8 [45440/60000 (76%)] Loss: 0.318561 Train Epoch: 8 [46080/60000 (77%)] Loss: 0.341067 Train Epoch: 8 [46720/60000 (78%)] Loss: 0.545489 Train Epoch: 8 [47360/60000 (79%)] Loss: 0.402002 Train Epoch: 8 [48000/60000 (80%)] Loss: 0.231705 Train Epoch: 8 [48640/60000 (81%)] Loss: 0.242956 Train Epoch: 8 [49280/60000 (82%)] Loss: 0.426706 Train Epoch: 8 [49920/60000 (83%)] Loss: 0.341219 Train Epoch: 8 [50560/60000 (84%)] Loss: 0.422939 Train Epoch: 8 [51200/60000 (85%)] Loss: 0.410270 Train Epoch: 8 [51840/60000 (86%)] Loss: 0.443087 Train Epoch: 8 [52480/60000 (87%)] Loss: 0.273087 Train Epoch: 8 [53120/60000 (88%)] Loss: 0.300433 Train Epoch: 8 [53760/60000 (90%)] Loss: 0.408494 Train Epoch: 8 [54400/60000 (91%)] Loss: 0.410628 Train Epoch: 8 [55040/60000 (92%)] Loss: 0.481743 Train Epoch: 8 [55680/60000 (93%)] Loss: 0.532843 Train Epoch: 8 [56320/60000 (94%)] Loss: 0.255752 Train Epoch: 8 [56960/60000 (95%)] Loss: 0.287013 Train Epoch: 8 [57600/60000 (96%)] Loss: 0.429710 Train Epoch: 8 [58240/60000 (97%)] Loss: 0.377912 Train Epoch: 8 [58880/60000 (98%)] Loss: 0.560696 Train Epoch: 8 [59520/60000 (99%)] Loss: 0.380459 Test set: Average loss: 0.2163, Accuracy: 9362/10000 (94%) Train Epoch: 9 [0/60000 (0%)] Loss: 0.585350 Train Epoch: 9 [640/60000 (1%)] Loss: 0.493246 Train Epoch: 9 [1280/60000 (2%)] Loss: 0.391806 Train Epoch: 9 [1920/60000 (3%)] Loss: 0.493008 Train Epoch: 9 [2560/60000 (4%)] Loss: 0.448494 Train Epoch: 9 [3200/60000 (5%)] Loss: 0.325095 Train Epoch: 9 [3840/60000 (6%)] Loss: 0.695937 Train Epoch: 9 [4480/60000 (7%)] Loss: 0.266650 Train Epoch: 9 [5120/60000 (9%)] Loss: 0.420216 Train Epoch: 9 [5760/60000 (10%)] Loss: 0.353440 Train Epoch: 9 [6400/60000 (11%)] Loss: 0.341078 Train Epoch: 9 [7040/60000 (12%)] Loss: 0.439247 Train Epoch: 9 [7680/60000 (13%)] Loss: 0.214539 Train Epoch: 9 [8320/60000 (14%)] Loss: 0.469013 Train Epoch: 9 [8960/60000 (15%)] Loss: 0.341292 Train Epoch: 9 [9600/60000 (16%)] Loss: 0.785741 Train Epoch: 9 [10240/60000 (17%)] Loss: 0.466753 Train Epoch: 9 [10880/60000 (18%)] Loss: 0.418933 Train Epoch: 9 [11520/60000 (19%)] Loss: 0.352860 Train Epoch: 9 [12160/60000 (20%)] Loss: 0.330622 Train Epoch: 9 [12800/60000 (21%)] Loss: 0.394191 Train Epoch: 9 [13440/60000 (22%)] Loss: 0.304991 Train Epoch: 9 [14080/60000 (23%)] Loss: 0.291812 Train Epoch: 9 [14720/60000 (25%)] Loss: 0.460314 Train Epoch: 9 [15360/60000 (26%)] Loss: 0.462962 Train Epoch: 9 [16000/60000 (27%)] Loss: 0.573508 Train Epoch: 9 [16640/60000 (28%)] Loss: 0.424545 Train Epoch: 9 [17280/60000 (29%)] Loss: 0.314215 Train Epoch: 9 [17920/60000 (30%)] Loss: 0.399477 Train Epoch: 9 [18560/60000 (31%)] Loss: 0.281409 Train Epoch: 9 [19200/60000 (32%)] Loss: 0.491287 Train Epoch: 9 [19840/60000 (33%)] Loss: 0.478374 Train Epoch: 9 [20480/60000 (34%)] Loss: 0.580464 Train Epoch: 9 [21120/60000 (35%)] Loss: 0.456699 Train Epoch: 9 [21760/60000 (36%)] Loss: 0.328621 Train Epoch: 9 [22400/60000 (37%)] Loss: 0.444202 Train Epoch: 9 [23040/60000 (38%)] Loss: 0.337673 Train Epoch: 9 [23680/60000 (39%)] Loss: 0.385429 Train Epoch: 9 [24320/60000 (41%)] Loss: 0.408061 Train Epoch: 9 [24960/60000 (42%)] Loss: 0.261543 Train Epoch: 9 [25600/60000 (43%)] Loss: 0.307577 Train Epoch: 9 [26240/60000 (44%)] Loss: 0.340200 Train Epoch: 9 [26880/60000 (45%)] Loss: 0.251914 Train Epoch: 9 [27520/60000 (46%)] Loss: 0.269231 Train Epoch: 9 [28160/60000 (47%)] Loss: 0.456552 Train Epoch: 9 [28800/60000 (48%)] Loss: 0.598232 Train Epoch: 9 [29440/60000 (49%)] Loss: 0.418177 Train Epoch: 9 [30080/60000 (50%)] Loss: 0.356407 Train Epoch: 9 [30720/60000 (51%)] Loss: 0.392345 Train Epoch: 9 [31360/60000 (52%)] Loss: 0.379441 Train Epoch: 9 [32000/60000 (53%)] Loss: 0.465713 Train Epoch: 9 [32640/60000 (54%)] Loss: 0.367991 Train Epoch: 9 [33280/60000 (55%)] Loss: 0.285676 Train Epoch: 9 [33920/60000 (57%)] Loss: 0.243431 Train Epoch: 9 [34560/60000 (58%)] Loss: 0.355942 Train Epoch: 9 [35200/60000 (59%)] Loss: 0.374828 Train Epoch: 9 [35840/60000 (60%)] Loss: 0.277245 Train Epoch: 9 [36480/60000 (61%)] Loss: 0.273998 Train Epoch: 9 [37120/60000 (62%)] Loss: 0.406776 Train Epoch: 9 [37760/60000 (63%)] Loss: 0.651791 Train Epoch: 9 [38400/60000 (64%)] Loss: 0.417006 Train Epoch: 9 [39040/60000 (65%)] Loss: 0.287786 Train Epoch: 9 [39680/60000 (66%)] Loss: 0.592248 Train Epoch: 9 [40320/60000 (67%)] Loss: 0.317200 Train Epoch: 9 [40960/60000 (68%)] Loss: 0.324063 Train Epoch: 9 [41600/60000 (69%)] Loss: 0.393426 Train Epoch: 9 [42240/60000 (70%)] Loss: 0.413506 Train Epoch: 9 [42880/60000 (71%)] Loss: 0.633301 Train Epoch: 9 [43520/60000 (72%)] Loss: 0.276478 Train Epoch: 9 [44160/60000 (74%)] Loss: 0.473216 Train Epoch: 9 [44800/60000 (75%)] Loss: 0.327980 Train Epoch: 9 [45440/60000 (76%)] Loss: 0.727830 Train Epoch: 9 [46080/60000 (77%)] Loss: 0.416605 Train Epoch: 9 [46720/60000 (78%)] Loss: 0.407099 Train Epoch: 9 [47360/60000 (79%)] Loss: 0.375051 Train Epoch: 9 [48000/60000 (80%)] Loss: 0.488992 Train Epoch: 9 [48640/60000 (81%)] Loss: 0.413114 Train Epoch: 9 [49280/60000 (82%)] Loss: 0.520725 Train Epoch: 9 [49920/60000 (83%)] Loss: 0.420221 Train Epoch: 9 [50560/60000 (84%)] Loss: 0.599522 Train Epoch: 9 [51200/60000 (85%)] Loss: 0.490780 Train Epoch: 9 [51840/60000 (86%)] Loss: 0.228232 Train Epoch: 9 [52480/60000 (87%)] Loss: 0.347773 Train Epoch: 9 [53120/60000 (88%)] Loss: 0.476633 Train Epoch: 9 [53760/60000 (90%)] Loss: 0.256656 Train Epoch: 9 [54400/60000 (91%)] Loss: 0.396474 Train Epoch: 9 [55040/60000 (92%)] Loss: 0.328017 Train Epoch: 9 [55680/60000 (93%)] Loss: 0.355086 Train Epoch: 9 [56320/60000 (94%)] Loss: 0.354232 Train Epoch: 9 [56960/60000 (95%)] Loss: 0.360218 Train Epoch: 9 [57600/60000 (96%)] Loss: 0.332373 Train Epoch: 9 [58240/60000 (97%)] Loss: 0.364290 Train Epoch: 9 [58880/60000 (98%)] Loss: 0.261339 Train Epoch: 9 [59520/60000 (99%)] Loss: 0.250586 Test set: Average loss: 0.2151, Accuracy: 9366/10000 (94%) Train Epoch: 10 [0/60000 (0%)] Loss: 0.438674 Train Epoch: 10 [640/60000 (1%)] Loss: 0.447094 Train Epoch: 10 [1280/60000 (2%)] Loss: 0.303145 Train Epoch: 10 [1920/60000 (3%)] Loss: 0.327251 Train Epoch: 10 [2560/60000 (4%)] Loss: 0.238297 Train Epoch: 10 [3200/60000 (5%)] Loss: 0.383331 Train Epoch: 10 [3840/60000 (6%)] Loss: 0.382009 Train Epoch: 10 [4480/60000 (7%)] Loss: 0.389430 Train Epoch: 10 [5120/60000 (9%)] Loss: 0.295570 Train Epoch: 10 [5760/60000 (10%)] Loss: 0.259864 Train Epoch: 10 [6400/60000 (11%)] Loss: 0.495970 Train Epoch: 10 [7040/60000 (12%)] Loss: 0.361643 Train Epoch: 10 [7680/60000 (13%)] Loss: 0.765771 Train Epoch: 10 [8320/60000 (14%)] Loss: 0.403898 Train Epoch: 10 [8960/60000 (15%)] Loss: 0.209247 Train Epoch: 10 [9600/60000 (16%)] Loss: 0.482393 Train Epoch: 10 [10240/60000 (17%)] Loss: 0.459047 Train Epoch: 10 [10880/60000 (18%)] Loss: 0.505761 Train Epoch: 10 [11520/60000 (19%)] Loss: 0.433308 Train Epoch: 10 [12160/60000 (20%)] Loss: 0.354521 Train Epoch: 10 [12800/60000 (21%)] Loss: 0.233018 Train Epoch: 10 [13440/60000 (22%)] Loss: 0.390475 Train Epoch: 10 [14080/60000 (23%)] Loss: 0.245935 Train Epoch: 10 [14720/60000 (25%)] Loss: 0.398528 Train Epoch: 10 [15360/60000 (26%)] Loss: 0.393017 Train Epoch: 10 [16000/60000 (27%)] Loss: 0.364166 Train Epoch: 10 [16640/60000 (28%)] Loss: 0.657179 Train Epoch: 10 [17280/60000 (29%)] Loss: 0.199565 Train Epoch: 10 [17920/60000 (30%)] Loss: 0.373811 Train Epoch: 10 [18560/60000 (31%)] Loss: 0.395341 Train Epoch: 10 [19200/60000 (32%)] Loss: 0.367141 Train Epoch: 10 [19840/60000 (33%)] Loss: 0.420444 Train Epoch: 10 [20480/60000 (34%)] Loss: 0.411721 Train Epoch: 10 [21120/60000 (35%)] Loss: 0.406184 Train Epoch: 10 [21760/60000 (36%)] Loss: 0.309357 Train Epoch: 10 [22400/60000 (37%)] Loss: 0.397585 Train Epoch: 10 [23040/60000 (38%)] Loss: 0.699485 Train Epoch: 10 [23680/60000 (39%)] Loss: 0.672690 Train Epoch: 10 [24320/60000 (41%)] Loss: 0.383667 Train Epoch: 10 [24960/60000 (42%)] Loss: 0.443057 Train Epoch: 10 [25600/60000 (43%)] Loss: 0.409219 Train Epoch: 10 [26240/60000 (44%)] Loss: 0.311079 Train Epoch: 10 [26880/60000 (45%)] Loss: 0.367074 Train Epoch: 10 [27520/60000 (46%)] Loss: 0.279823 Train Epoch: 10 [28160/60000 (47%)] Loss: 0.337272 Train Epoch: 10 [28800/60000 (48%)] Loss: 0.485713 Train Epoch: 10 [29440/60000 (49%)] Loss: 0.345926 Train Epoch: 10 [30080/60000 (50%)] Loss: 0.424248 Train Epoch: 10 [30720/60000 (51%)] Loss: 0.322441 Train Epoch: 10 [31360/60000 (52%)] Loss: 0.283901 Train Epoch: 10 [32000/60000 (53%)] Loss: 0.640329 Train Epoch: 10 [32640/60000 (54%)] Loss: 0.342490 Train Epoch: 10 [33280/60000 (55%)] Loss: 0.343811 Train Epoch: 10 [33920/60000 (57%)] Loss: 0.392110 Train Epoch: 10 [34560/60000 (58%)] Loss: 0.433465 Train Epoch: 10 [35200/60000 (59%)] Loss: 0.341572 Train Epoch: 10 [35840/60000 (60%)] Loss: 0.394995 Train Epoch: 10 [36480/60000 (61%)] Loss: 0.332045 Train Epoch: 10 [37120/60000 (62%)] Loss: 0.276502 Train Epoch: 10 [37760/60000 (63%)] Loss: 0.292657 Train Epoch: 10 [38400/60000 (64%)] Loss: 0.455167 Train Epoch: 10 [39040/60000 (65%)] Loss: 0.297509 Train Epoch: 10 [39680/60000 (66%)] Loss: 0.640905 Train Epoch: 10 [40320/60000 (67%)] Loss: 0.422916 Train Epoch: 10 [40960/60000 (68%)] Loss: 0.473346 Train Epoch: 10 [41600/60000 (69%)] Loss: 0.491302 Train Epoch: 10 [42240/60000 (70%)] Loss: 0.346931 Train Epoch: 10 [42880/60000 (71%)] Loss: 0.572828 Train Epoch: 10 [43520/60000 (72%)] Loss: 0.365607 Train Epoch: 10 [44160/60000 (74%)] Loss: 0.317555 Train Epoch: 10 [44800/60000 (75%)] Loss: 0.468910 Train Epoch: 10 [45440/60000 (76%)] Loss: 0.496312 Train Epoch: 10 [46080/60000 (77%)] Loss: 0.696475 Train Epoch: 10 [46720/60000 (78%)] Loss: 0.359580 Train Epoch: 10 [47360/60000 (79%)] Loss: 0.419243 Train Epoch: 10 [48000/60000 (80%)] Loss: 0.303316 Train Epoch: 10 [48640/60000 (81%)] Loss: 0.383328 Train Epoch: 10 [49280/60000 (82%)] Loss: 0.268373 Train Epoch: 10 [49920/60000 (83%)] Loss: 0.413617 Train Epoch: 10 [50560/60000 (84%)] Loss: 0.454594 Train Epoch: 10 [51200/60000 (85%)] Loss: 0.359163 Train Epoch: 10 [51840/60000 (86%)] Loss: 0.630097 Train Epoch: 10 [52480/60000 (87%)] Loss: 0.521165 Train Epoch: 10 [53120/60000 (88%)] Loss: 0.247819 Train Epoch: 10 [53760/60000 (90%)] Loss: 0.330510 Train Epoch: 10 [54400/60000 (91%)] Loss: 0.343167 Train Epoch: 10 [55040/60000 (92%)] Loss: 0.380156 Train Epoch: 10 [55680/60000 (93%)] Loss: 0.395422 Train Epoch: 10 [56320/60000 (94%)] Loss: 0.687743 Train Epoch: 10 [56960/60000 (95%)] Loss: 0.470193 Train Epoch: 10 [57600/60000 (96%)] Loss: 0.473724 Train Epoch: 10 [58240/60000 (97%)] Loss: 0.361689 Train Epoch: 10 [58880/60000 (98%)] Loss: 0.349370 Train Epoch: 10 [59520/60000 (99%)] Loss: 0.385800 Test set: Average loss: 0.2124, Accuracy: 9367/10000 (94%) Train Epoch: 11 [0/60000 (0%)] Loss: 0.426175 Train Epoch: 11 [640/60000 (1%)] Loss: 0.170051 Train Epoch: 11 [1280/60000 (2%)] Loss: 0.250144 Train Epoch: 11 [1920/60000 (3%)] Loss: 0.172225 Train Epoch: 11 [2560/60000 (4%)] Loss: 0.421107 Train Epoch: 11 [3200/60000 (5%)] Loss: 0.380877 Train Epoch: 11 [3840/60000 (6%)] Loss: 0.230397 Train Epoch: 11 [4480/60000 (7%)] Loss: 0.477565 Train Epoch: 11 [5120/60000 (9%)] Loss: 0.395525 Train Epoch: 11 [5760/60000 (10%)] Loss: 0.270285 Train Epoch: 11 [6400/60000 (11%)] Loss: 0.310442 Train Epoch: 11 [7040/60000 (12%)] Loss: 0.285871 Train Epoch: 11 [7680/60000 (13%)] Loss: 0.333100 Train Epoch: 11 [8320/60000 (14%)] Loss: 0.269914 Train Epoch: 11 [8960/60000 (15%)] Loss: 0.340485 Train Epoch: 11 [9600/60000 (16%)] Loss: 0.433936 Train Epoch: 11 [10240/60000 (17%)] Loss: 0.552323 Train Epoch: 11 [10880/60000 (18%)] Loss: 0.532913 Train Epoch: 11 [11520/60000 (19%)] Loss: 0.495746 Train Epoch: 11 [12160/60000 (20%)] Loss: 0.303815 Train Epoch: 11 [12800/60000 (21%)] Loss: 0.264451 Train Epoch: 11 [13440/60000 (22%)] Loss: 0.436694 Train Epoch: 11 [14080/60000 (23%)] Loss: 0.440698 Train Epoch: 11 [14720/60000 (25%)] Loss: 0.422329 Train Epoch: 11 [15360/60000 (26%)] Loss: 0.415076 Train Epoch: 11 [16000/60000 (27%)] Loss: 0.595345 Train Epoch: 11 [16640/60000 (28%)] Loss: 0.246912 Train Epoch: 11 [17280/60000 (29%)] Loss: 0.261347 Train Epoch: 11 [17920/60000 (30%)] Loss: 0.420687 Train Epoch: 11 [18560/60000 (31%)] Loss: 0.309478 Train Epoch: 11 [19200/60000 (32%)] Loss: 0.351695 Train Epoch: 11 [19840/60000 (33%)] Loss: 0.521406 Train Epoch: 11 [20480/60000 (34%)] Loss: 0.290906 Train Epoch: 11 [21120/60000 (35%)] Loss: 0.364633 Train Epoch: 11 [21760/60000 (36%)] Loss: 0.324597 Train Epoch: 11 [22400/60000 (37%)] Loss: 0.504305 Train Epoch: 11 [23040/60000 (38%)] Loss: 0.565828 Train Epoch: 11 [23680/60000 (39%)] Loss: 0.530418 Train Epoch: 11 [24320/60000 (41%)] Loss: 0.394785 Train Epoch: 11 [24960/60000 (42%)] Loss: 0.360259 Train Epoch: 11 [25600/60000 (43%)] Loss: 0.332049 Train Epoch: 11 [26240/60000 (44%)] Loss: 0.277467 Train Epoch: 11 [26880/60000 (45%)] Loss: 0.392917 Train Epoch: 11 [27520/60000 (46%)] Loss: 0.343030 Train Epoch: 11 [28160/60000 (47%)] Loss: 0.575351 Train Epoch: 11 [28800/60000 (48%)] Loss: 0.234557 Train Epoch: 11 [29440/60000 (49%)] Loss: 0.345107 Train Epoch: 11 [30080/60000 (50%)] Loss: 0.250498 Train Epoch: 11 [30720/60000 (51%)] Loss: 0.252943 Train Epoch: 11 [31360/60000 (52%)] Loss: 0.339441 Train Epoch: 11 [32000/60000 (53%)] Loss: 0.419630 Train Epoch: 11 [32640/60000 (54%)] Loss: 0.299459 Train Epoch: 11 [33280/60000 (55%)] Loss: 0.496848 Train Epoch: 11 [33920/60000 (57%)] Loss: 0.298093 Train Epoch: 11 [34560/60000 (58%)] Loss: 0.502162 Train Epoch: 11 [35200/60000 (59%)] Loss: 0.255059 Train Epoch: 11 [35840/60000 (60%)] Loss: 0.411274 Train Epoch: 11 [36480/60000 (61%)] Loss: 0.523598 Train Epoch: 11 [37120/60000 (62%)] Loss: 0.413543 Train Epoch: 11 [37760/60000 (63%)] Loss: 0.416163 Train Epoch: 11 [38400/60000 (64%)] Loss: 0.369535 Train Epoch: 11 [39040/60000 (65%)] Loss: 0.611558 Train Epoch: 11 [39680/60000 (66%)] Loss: 0.304744 Train Epoch: 11 [40320/60000 (67%)] Loss: 0.430891 Train Epoch: 11 [40960/60000 (68%)] Loss: 0.405095 Train Epoch: 11 [41600/60000 (69%)] Loss: 0.459111 Train Epoch: 11 [42240/60000 (70%)] Loss: 0.305776 Train Epoch: 11 [42880/60000 (71%)] Loss: 0.383718 Train Epoch: 11 [43520/60000 (72%)] Loss: 0.357237 Train Epoch: 11 [44160/60000 (74%)] Loss: 0.882389 Train Epoch: 11 [44800/60000 (75%)] Loss: 0.515517 Train Epoch: 11 [45440/60000 (76%)] Loss: 0.431814 Train Epoch: 11 [46080/60000 (77%)] Loss: 0.502057 Train Epoch: 11 [46720/60000 (78%)] Loss: 0.363643 Train Epoch: 11 [47360/60000 (79%)] Loss: 0.300866 Train Epoch: 11 [48000/60000 (80%)] Loss: 0.379479 Train Epoch: 11 [48640/60000 (81%)] Loss: 0.409872 Train Epoch: 11 [49280/60000 (82%)] Loss: 0.459707 Train Epoch: 11 [49920/60000 (83%)] Loss: 0.407087 Train Epoch: 11 [50560/60000 (84%)] Loss: 0.442198 Train Epoch: 11 [51200/60000 (85%)] Loss: 0.360245 Train Epoch: 11 [51840/60000 (86%)] Loss: 0.391902 Train Epoch: 11 [52480/60000 (87%)] Loss: 0.690279 Train Epoch: 11 [53120/60000 (88%)] Loss: 0.578411 Train Epoch: 11 [53760/60000 (90%)] Loss: 0.317039 Train Epoch: 11 [54400/60000 (91%)] Loss: 0.361648 Train Epoch: 11 [55040/60000 (92%)] Loss: 0.256818 Train Epoch: 11 [55680/60000 (93%)] Loss: 0.305927 Train Epoch: 11 [56320/60000 (94%)] Loss: 0.334766 Train Epoch: 11 [56960/60000 (95%)] Loss: 0.393670 Train Epoch: 11 [57600/60000 (96%)] Loss: 0.357648 Train Epoch: 11 [58240/60000 (97%)] Loss: 0.281212 Train Epoch: 11 [58880/60000 (98%)] Loss: 0.324076 Train Epoch: 11 [59520/60000 (99%)] Loss: 0.372610 Test set: Average loss: 0.2098, Accuracy: 9373/10000 (94%) Train Epoch: 12 [0/60000 (0%)] Loss: 0.392381 Train Epoch: 12 [640/60000 (1%)] Loss: 0.296244 Train Epoch: 12 [1280/60000 (2%)] Loss: 0.375838 Train Epoch: 12 [1920/60000 (3%)] Loss: 0.511141 Train Epoch: 12 [2560/60000 (4%)] Loss: 0.328571 Train Epoch: 12 [3200/60000 (5%)] Loss: 0.407022 Train Epoch: 12 [3840/60000 (6%)] Loss: 0.298561 Train Epoch: 12 [4480/60000 (7%)] Loss: 0.294833 Train Epoch: 12 [5120/60000 (9%)] Loss: 0.459635 Train Epoch: 12 [5760/60000 (10%)] Loss: 0.427801 Train Epoch: 12 [6400/60000 (11%)] Loss: 0.315486 Train Epoch: 12 [7040/60000 (12%)] Loss: 0.369394 Train Epoch: 12 [7680/60000 (13%)] Loss: 0.383768 Train Epoch: 12 [8320/60000 (14%)] Loss: 0.360965 Train Epoch: 12 [8960/60000 (15%)] Loss: 0.565722 Train Epoch: 12 [9600/60000 (16%)] Loss: 0.339543 Train Epoch: 12 [10240/60000 (17%)] Loss: 0.318308 Train Epoch: 12 [10880/60000 (18%)] Loss: 0.354275 Train Epoch: 12 [11520/60000 (19%)] Loss: 0.729154 Train Epoch: 12 [12160/60000 (20%)] Loss: 0.637020 Train Epoch: 12 [12800/60000 (21%)] Loss: 0.311871 Train Epoch: 12 [13440/60000 (22%)] Loss: 0.475887 Train Epoch: 12 [14080/60000 (23%)] Loss: 0.593350 Train Epoch: 12 [14720/60000 (25%)] Loss: 0.401409 Train Epoch: 12 [15360/60000 (26%)] Loss: 0.340033 Train Epoch: 12 [16000/60000 (27%)] Loss: 0.268460 Train Epoch: 12 [16640/60000 (28%)] Loss: 0.246902 Train Epoch: 12 [17280/60000 (29%)] Loss: 0.220537 Train Epoch: 12 [17920/60000 (30%)] Loss: 0.343910 Train Epoch: 12 [18560/60000 (31%)] Loss: 0.404446 Train Epoch: 12 [19200/60000 (32%)] Loss: 0.390659 Train Epoch: 12 [19840/60000 (33%)] Loss: 0.428503 Train Epoch: 12 [20480/60000 (34%)] Loss: 0.349071 Train Epoch: 12 [21120/60000 (35%)] Loss: 0.486959 Train Epoch: 12 [21760/60000 (36%)] Loss: 0.328149 Train Epoch: 12 [22400/60000 (37%)] Loss: 0.516612 Train Epoch: 12 [23040/60000 (38%)] Loss: 0.457053 Train Epoch: 12 [23680/60000 (39%)] Loss: 0.608891 Train Epoch: 12 [24320/60000 (41%)] Loss: 0.689961 Train Epoch: 12 [24960/60000 (42%)] Loss: 0.294651 Train Epoch: 12 [25600/60000 (43%)] Loss: 0.393591 Train Epoch: 12 [26240/60000 (44%)] Loss: 0.338528 Train Epoch: 12 [26880/60000 (45%)] Loss: 0.577185 Train Epoch: 12 [27520/60000 (46%)] Loss: 0.353298 Train Epoch: 12 [28160/60000 (47%)] Loss: 0.622561 Train Epoch: 12 [28800/60000 (48%)] Loss: 0.282284 Train Epoch: 12 [29440/60000 (49%)] Loss: 0.313890 Train Epoch: 12 [30080/60000 (50%)] Loss: 0.351842 Train Epoch: 12 [30720/60000 (51%)] Loss: 0.396683 Train Epoch: 12 [31360/60000 (52%)] Loss: 0.525928 Train Epoch: 12 [32000/60000 (53%)] Loss: 0.234339 Train Epoch: 12 [32640/60000 (54%)] Loss: 0.462475 Train Epoch: 12 [33280/60000 (55%)] Loss: 0.566767 Train Epoch: 12 [33920/60000 (57%)] Loss: 0.384068 Train Epoch: 12 [34560/60000 (58%)] Loss: 0.281656 Train Epoch: 12 [35200/60000 (59%)] Loss: 0.392156 Train Epoch: 12 [35840/60000 (60%)] Loss: 0.567646 Train Epoch: 12 [36480/60000 (61%)] Loss: 0.294172 Train Epoch: 12 [37120/60000 (62%)] Loss: 0.395887 Train Epoch: 12 [37760/60000 (63%)] Loss: 0.241547 Train Epoch: 12 [38400/60000 (64%)] Loss: 0.475505 Train Epoch: 12 [39040/60000 (65%)] Loss: 0.444348 Train Epoch: 12 [39680/60000 (66%)] Loss: 0.590313 Train Epoch: 12 [40320/60000 (67%)] Loss: 0.380521 Train Epoch: 12 [40960/60000 (68%)] Loss: 0.319756 Train Epoch: 12 [41600/60000 (69%)] Loss: 0.419879 Train Epoch: 12 [42240/60000 (70%)] Loss: 0.384562 Train Epoch: 12 [42880/60000 (71%)] Loss: 0.234591 Train Epoch: 12 [43520/60000 (72%)] Loss: 0.330877 Train Epoch: 12 [44160/60000 (74%)] Loss: 0.697167 Train Epoch: 12 [44800/60000 (75%)] Loss: 0.272816 Train Epoch: 12 [45440/60000 (76%)] Loss: 0.415027 Train Epoch: 12 [46080/60000 (77%)] Loss: 0.403599 Train Epoch: 12 [46720/60000 (78%)] Loss: 0.350379 Train Epoch: 12 [47360/60000 (79%)] Loss: 0.210332 Train Epoch: 12 [48000/60000 (80%)] Loss: 0.350990 Train Epoch: 12 [48640/60000 (81%)] Loss: 0.421243 Train Epoch: 12 [49280/60000 (82%)] Loss: 0.257715 Train Epoch: 12 [49920/60000 (83%)] Loss: 0.430463 Train Epoch: 12 [50560/60000 (84%)] Loss: 0.436658 Train Epoch: 12 [51200/60000 (85%)] Loss: 0.385483 Train Epoch: 12 [51840/60000 (86%)] Loss: 0.449448 Train Epoch: 12 [52480/60000 (87%)] Loss: 0.369401 Train Epoch: 12 [53120/60000 (88%)] Loss: 0.380906 Train Epoch: 12 [53760/60000 (90%)] Loss: 0.391110 Train Epoch: 12 [54400/60000 (91%)] Loss: 0.381157 Train Epoch: 12 [55040/60000 (92%)] Loss: 0.317574 Train Epoch: 12 [55680/60000 (93%)] Loss: 0.616172 Train Epoch: 12 [56320/60000 (94%)] Loss: 0.333590 Train Epoch: 12 [56960/60000 (95%)] Loss: 0.460308 Train Epoch: 12 [57600/60000 (96%)] Loss: 0.586635 Train Epoch: 12 [58240/60000 (97%)] Loss: 0.323481 Train Epoch: 12 [58880/60000 (98%)] Loss: 0.410162 Train Epoch: 12 [59520/60000 (99%)] Loss: 0.475990 Test set: Average loss: 0.2096, Accuracy: 9381/10000 (94%) Train Epoch: 13 [0/60000 (0%)] Loss: 0.555876 Train Epoch: 13 [640/60000 (1%)] Loss: 0.298020 Train Epoch: 13 [1280/60000 (2%)] Loss: 0.341556 Train Epoch: 13 [1920/60000 (3%)] Loss: 0.387244 Train Epoch: 13 [2560/60000 (4%)] Loss: 0.299948 Train Epoch: 13 [3200/60000 (5%)] Loss: 0.352978 Train Epoch: 13 [3840/60000 (6%)] Loss: 0.445687 Train Epoch: 13 [4480/60000 (7%)] Loss: 0.223049 Train Epoch: 13 [5120/60000 (9%)] Loss: 0.494324 Train Epoch: 13 [5760/60000 (10%)] Loss: 0.749437 Train Epoch: 13 [6400/60000 (11%)] Loss: 0.404310 Train Epoch: 13 [7040/60000 (12%)] Loss: 0.337297 Train Epoch: 13 [7680/60000 (13%)] Loss: 0.434967 Train Epoch: 13 [8320/60000 (14%)] Loss: 0.401748 Train Epoch: 13 [8960/60000 (15%)] Loss: 0.340427 Train Epoch: 13 [9600/60000 (16%)] Loss: 0.614933 Train Epoch: 13 [10240/60000 (17%)] Loss: 0.428032 Train Epoch: 13 [10880/60000 (18%)] Loss: 0.520478 Train Epoch: 13 [11520/60000 (19%)] Loss: 0.343639 Train Epoch: 13 [12160/60000 (20%)] Loss: 0.282134 Train Epoch: 13 [12800/60000 (21%)] Loss: 0.236920 Train Epoch: 13 [13440/60000 (22%)] Loss: 0.331308 Train Epoch: 13 [14080/60000 (23%)] Loss: 0.342169 Train Epoch: 13 [14720/60000 (25%)] Loss: 0.494080 Train Epoch: 13 [15360/60000 (26%)] Loss: 0.566829 Train Epoch: 13 [16000/60000 (27%)] Loss: 0.515479 Train Epoch: 13 [16640/60000 (28%)] Loss: 0.546352 Train Epoch: 13 [17280/60000 (29%)] Loss: 0.462010 Train Epoch: 13 [17920/60000 (30%)] Loss: 0.547893 Train Epoch: 13 [18560/60000 (31%)] Loss: 0.519924 Train Epoch: 13 [19200/60000 (32%)] Loss: 0.445337 Train Epoch: 13 [19840/60000 (33%)] Loss: 0.254473 Train Epoch: 13 [20480/60000 (34%)] Loss: 0.351019 Train Epoch: 13 [21120/60000 (35%)] Loss: 0.388970 Train Epoch: 13 [21760/60000 (36%)] Loss: 0.285459 Train Epoch: 13 [22400/60000 (37%)] Loss: 0.308739 Train Epoch: 13 [23040/60000 (38%)] Loss: 0.501287 Train Epoch: 13 [23680/60000 (39%)] Loss: 0.392744 Train Epoch: 13 [24320/60000 (41%)] Loss: 0.490547 Train Epoch: 13 [24960/60000 (42%)] Loss: 0.407411 Train Epoch: 13 [25600/60000 (43%)] Loss: 0.557519 Train Epoch: 13 [26240/60000 (44%)] Loss: 0.407774 Train Epoch: 13 [26880/60000 (45%)] Loss: 0.313497 Train Epoch: 13 [27520/60000 (46%)] Loss: 0.470231 Train Epoch: 13 [28160/60000 (47%)] Loss: 0.457753 Train Epoch: 13 [28800/60000 (48%)] Loss: 0.314194 Train Epoch: 13 [29440/60000 (49%)] Loss: 0.395972 Train Epoch: 13 [30080/60000 (50%)] Loss: 0.575824 Train Epoch: 13 [30720/60000 (51%)] Loss: 0.275038 Train Epoch: 13 [31360/60000 (52%)] Loss: 0.376275 Train Epoch: 13 [32000/60000 (53%)] Loss: 0.517350 Train Epoch: 13 [32640/60000 (54%)] Loss: 0.386347 Train Epoch: 13 [33280/60000 (55%)] Loss: 0.315577 Train Epoch: 13 [33920/60000 (57%)] Loss: 0.385711 Train Epoch: 13 [34560/60000 (58%)] Loss: 0.308082 Train Epoch: 13 [35200/60000 (59%)] Loss: 0.412021 Train Epoch: 13 [35840/60000 (60%)] Loss: 0.630597 Train Epoch: 13 [36480/60000 (61%)] Loss: 0.530441 Train Epoch: 13 [37120/60000 (62%)] Loss: 0.324686 Train Epoch: 13 [37760/60000 (63%)] Loss: 0.334050 Train Epoch: 13 [38400/60000 (64%)] Loss: 0.539302 Train Epoch: 13 [39040/60000 (65%)] Loss: 0.168276 Train Epoch: 13 [39680/60000 (66%)] Loss: 0.218964 Train Epoch: 13 [40320/60000 (67%)] Loss: 0.526193 Train Epoch: 13 [40960/60000 (68%)] Loss: 0.554866 Train Epoch: 13 [41600/60000 (69%)] Loss: 0.519486 Train Epoch: 13 [42240/60000 (70%)] Loss: 0.659215 Train Epoch: 13 [42880/60000 (71%)] Loss: 0.347684 Train Epoch: 13 [43520/60000 (72%)] Loss: 0.218575 Train Epoch: 13 [44160/60000 (74%)] Loss: 0.498827 Train Epoch: 13 [44800/60000 (75%)] Loss: 0.428912 Train Epoch: 13 [45440/60000 (76%)] Loss: 0.554431 Train Epoch: 13 [46080/60000 (77%)] Loss: 0.334991 Train Epoch: 13 [46720/60000 (78%)] Loss: 0.312058 Train Epoch: 13 [47360/60000 (79%)] Loss: 0.393212 Train Epoch: 13 [48000/60000 (80%)] Loss: 0.328563 Train Epoch: 13 [48640/60000 (81%)] Loss: 0.441795 Train Epoch: 13 [49280/60000 (82%)] Loss: 0.487448 Train Epoch: 13 [49920/60000 (83%)] Loss: 0.393158 Train Epoch: 13 [50560/60000 (84%)] Loss: 0.413586 Train Epoch: 13 [51200/60000 (85%)] Loss: 0.331015 Train Epoch: 13 [51840/60000 (86%)] Loss: 0.293184 Train Epoch: 13 [52480/60000 (87%)] Loss: 0.448311 Train Epoch: 13 [53120/60000 (88%)] Loss: 0.275574 Train Epoch: 13 [53760/60000 (90%)] Loss: 0.361041 Train Epoch: 13 [54400/60000 (91%)] Loss: 0.270119 Train Epoch: 13 [55040/60000 (92%)] Loss: 0.339491 Train Epoch: 13 [55680/60000 (93%)] Loss: 0.460334 Train Epoch: 13 [56320/60000 (94%)] Loss: 0.355198 Train Epoch: 13 [56960/60000 (95%)] Loss: 0.324064 Train Epoch: 13 [57600/60000 (96%)] Loss: 0.461057 Train Epoch: 13 [58240/60000 (97%)] Loss: 0.520947 Train Epoch: 13 [58880/60000 (98%)] Loss: 0.555590 Train Epoch: 13 [59520/60000 (99%)] Loss: 0.347576 Test set: Average loss: 0.2075, Accuracy: 9385/10000 (94%) Train Epoch: 14 [0/60000 (0%)] Loss: 0.319042 Train Epoch: 14 [640/60000 (1%)] Loss: 0.286378 Train Epoch: 14 [1280/60000 (2%)] Loss: 0.475702 Train Epoch: 14 [1920/60000 (3%)] Loss: 0.460729 Train Epoch: 14 [2560/60000 (4%)] Loss: 0.227350 Train Epoch: 14 [3200/60000 (5%)] Loss: 0.430530 Train Epoch: 14 [3840/60000 (6%)] Loss: 0.370811 Train Epoch: 14 [4480/60000 (7%)] Loss: 0.292919 Train Epoch: 14 [5120/60000 (9%)] Loss: 0.462068 Train Epoch: 14 [5760/60000 (10%)] Loss: 0.240440 Train Epoch: 14 [6400/60000 (11%)] Loss: 0.330162 Train Epoch: 14 [7040/60000 (12%)] Loss: 0.385991 Train Epoch: 14 [7680/60000 (13%)] Loss: 0.260772 Train Epoch: 14 [8320/60000 (14%)] Loss: 0.431668 Train Epoch: 14 [8960/60000 (15%)] Loss: 0.391844 Train Epoch: 14 [9600/60000 (16%)] Loss: 0.607404 Train Epoch: 14 [10240/60000 (17%)] Loss: 0.517053 Train Epoch: 14 [10880/60000 (18%)] Loss: 0.460433 Train Epoch: 14 [11520/60000 (19%)] Loss: 0.294837 Train Epoch: 14 [12160/60000 (20%)] Loss: 0.376116 Train Epoch: 14 [12800/60000 (21%)] Loss: 0.302840 Train Epoch: 14 [13440/60000 (22%)] Loss: 0.423696 Train Epoch: 14 [14080/60000 (23%)] Loss: 0.396551 Train Epoch: 14 [14720/60000 (25%)] Loss: 0.315363 Train Epoch: 14 [15360/60000 (26%)] Loss: 0.452954 Train Epoch: 14 [16000/60000 (27%)] Loss: 0.492528 Train Epoch: 14 [16640/60000 (28%)] Loss: 0.209144 Train Epoch: 14 [17280/60000 (29%)] Loss: 0.361104 Train Epoch: 14 [17920/60000 (30%)] Loss: 0.337909 Train Epoch: 14 [18560/60000 (31%)] Loss: 0.235292 Train Epoch: 14 [19200/60000 (32%)] Loss: 0.378781 Train Epoch: 14 [19840/60000 (33%)] Loss: 0.698395 Train Epoch: 14 [20480/60000 (34%)] Loss: 0.654676 Train Epoch: 14 [21120/60000 (35%)] Loss: 0.261703 Train Epoch: 14 [21760/60000 (36%)] Loss: 0.491567 Train Epoch: 14 [22400/60000 (37%)] Loss: 0.460270 Train Epoch: 14 [23040/60000 (38%)] Loss: 0.663427 Train Epoch: 14 [23680/60000 (39%)] Loss: 0.488279 Train Epoch: 14 [24320/60000 (41%)] Loss: 0.412345 Train Epoch: 14 [24960/60000 (42%)] Loss: 0.330990 Train Epoch: 14 [25600/60000 (43%)] Loss: 0.319391 Train Epoch: 14 [26240/60000 (44%)] Loss: 0.364210 Train Epoch: 14 [26880/60000 (45%)] Loss: 0.279273 Train Epoch: 14 [27520/60000 (46%)] Loss: 0.176225 Train Epoch: 14 [28160/60000 (47%)] Loss: 0.297678 Train Epoch: 14 [28800/60000 (48%)] Loss: 0.378201 Train Epoch: 14 [29440/60000 (49%)] Loss: 0.232202 Train Epoch: 14 [30080/60000 (50%)] Loss: 0.525252 Train Epoch: 14 [30720/60000 (51%)] Loss: 0.368206 Train Epoch: 14 [31360/60000 (52%)] Loss: 0.304667 Train Epoch: 14 [32000/60000 (53%)] Loss: 0.358428 Train Epoch: 14 [32640/60000 (54%)] Loss: 0.427945 Train Epoch: 14 [33280/60000 (55%)] Loss: 0.488429 Train Epoch: 14 [33920/60000 (57%)] Loss: 0.526154 Train Epoch: 14 [34560/60000 (58%)] Loss: 0.725787 Train Epoch: 14 [35200/60000 (59%)] Loss: 0.599196 Train Epoch: 14 [35840/60000 (60%)] Loss: 0.327683 Train Epoch: 14 [36480/60000 (61%)] Loss: 0.611174 Train Epoch: 14 [37120/60000 (62%)] Loss: 0.429956 Train Epoch: 14 [37760/60000 (63%)] Loss: 0.384994 Train Epoch: 14 [38400/60000 (64%)] Loss: 0.302766 Train Epoch: 14 [39040/60000 (65%)] Loss: 0.637129 Train Epoch: 14 [39680/60000 (66%)] Loss: 0.300277 Train Epoch: 14 [40320/60000 (67%)] Loss: 0.605256 Train Epoch: 14 [40960/60000 (68%)] Loss: 0.563442 Train Epoch: 14 [41600/60000 (69%)] Loss: 0.315805 Train Epoch: 14 [42240/60000 (70%)] Loss: 0.498134 Train Epoch: 14 [42880/60000 (71%)] Loss: 0.304480 Train Epoch: 14 [43520/60000 (72%)] Loss: 0.358127 Train Epoch: 14 [44160/60000 (74%)] Loss: 0.354775 Train Epoch: 14 [44800/60000 (75%)] Loss: 0.349251 Train Epoch: 14 [45440/60000 (76%)] Loss: 0.363537 Train Epoch: 14 [46080/60000 (77%)] Loss: 0.397053 Train Epoch: 14 [46720/60000 (78%)] Loss: 0.569868 Train Epoch: 14 [47360/60000 (79%)] Loss: 0.387928 Train Epoch: 14 [48000/60000 (80%)] Loss: 0.348417 Train Epoch: 14 [48640/60000 (81%)] Loss: 0.377063 Train Epoch: 14 [49280/60000 (82%)] Loss: 0.260186 Train Epoch: 14 [49920/60000 (83%)] Loss: 0.297211 Train Epoch: 14 [50560/60000 (84%)] Loss: 0.702463 Train Epoch: 14 [51200/60000 (85%)] Loss: 0.302332 Train Epoch: 14 [51840/60000 (86%)] Loss: 0.526482 Train Epoch: 14 [52480/60000 (87%)] Loss: 0.400840 Train Epoch: 14 [53120/60000 (88%)] Loss: 0.501183 Train Epoch: 14 [53760/60000 (90%)] Loss: 0.302832 Train Epoch: 14 [54400/60000 (91%)] Loss: 0.351779 Train Epoch: 14 [55040/60000 (92%)] Loss: 0.406741 Train Epoch: 14 [55680/60000 (93%)] Loss: 0.455118 Train Epoch: 14 [56320/60000 (94%)] Loss: 0.324182 Train Epoch: 14 [56960/60000 (95%)] Loss: 0.380480 Train Epoch: 14 [57600/60000 (96%)] Loss: 0.729591 Train Epoch: 14 [58240/60000 (97%)] Loss: 0.435104 Train Epoch: 14 [58880/60000 (98%)] Loss: 0.378653 Train Epoch: 14 [59520/60000 (99%)] Loss: 0.280005 Test set: Average loss: 0.2066, Accuracy: 9386/10000 (94%)
The model has successfully trained and downloaded
In [19]:
%%bash
ls results/combined_results/outputs/
mnist_rnn.pt