PS C:\Users\wkdwn\Desktop\project\AlexNet> python .\train.py
Using cuda device. Cuda device count: 1
----------------------------------------------------------------
Layer (type) Output Shape Param #
================================================================
Conv2d-1 [-1, 96, 55, 55] 11,712
ReLU-2 [-1, 96, 55, 55] 0
LocalResponseNorm-3 [-1, 96, 55, 55] 0
MaxPool2d-4 [-1, 96, 27, 27] 0
Conv2d-5 [-1, 256, 27, 27] 614,656
ReLU-6 [-1, 256, 27, 27] 0
LocalResponseNorm-7 [-1, 256, 27, 27] 0
MaxPool2d-8 [-1, 256, 13, 13] 0
Conv2d-9 [-1, 384, 13, 13] 885,120
ReLU-10 [-1, 384, 13, 13] 0
Conv2d-11 [-1, 384, 13, 13] 1,327,488
ReLU-12 [-1, 384, 13, 13] 0
Conv2d-13 [-1, 256, 13, 13] 884,992
ReLU-14 [-1, 256, 13, 13] 0
MaxPool2d-15 [-1, 256, 6, 6] 0
Flatten-16 [-1, 9216] 0
Dropout-17 [-1, 9216] 0
Linear-18 [-1, 4096] 37,752,832
ReLU-19 [-1, 4096] 0
Dropout-20 [-1, 4096] 0
Linear-21 [-1, 4096] 16,781,312
ReLU-22 [-1, 4096] 0
Linear-23 [-1, 10] 40,970
Softmax-24 [-1, 10] 0
================================================================
Total params: 58,299,082
Trainable params: 58,299,082
Non-trainable params: 0
----------------------------------------------------------------
Input size (MB): 0.19
Forward/backward pass size (MB): 14.79
Params size (MB): 222.39
Estimated Total Size (MB): 237.37
----------------------------------------------------------------
Epoch 1
--------------------------------------------------
Batch 0. loss: 2.302665 [ 0/ 60000]
Batch 10. loss: 2.302610 [ 1280/ 60000]
Batch 20. loss: 2.302786 [ 2560/ 60000]
Batch 30. loss: 2.302531 [ 3840/ 60000]
Batch 40. loss: 2.302706 [ 5120/ 60000]
Batch 50. loss: 2.302613 [ 6400/ 60000]
Batch 60. loss: 2.302558 [ 7680/ 60000]
Batch 70. loss: 2.302573 [ 8960/ 60000]
Batch 80. loss: 2.302686 [ 10240/ 60000]
Batch 90. loss: 2.302499 [ 11520/ 60000]
Batch 100. loss: 2.302588 [ 12800/ 60000]
Batch 110. loss: 2.302682 [ 14080/ 60000]
Batch 120. loss: 2.302630 [ 15360/ 60000]
Batch 130. loss: 2.302518 [ 16640/ 60000]
Batch 140. loss: 2.302656 [ 17920/ 60000]
Batch 150. loss: 2.302632 [ 19200/ 60000]
Batch 160. loss: 2.302603 [ 20480/ 60000]
Batch 170. loss: 2.302538 [ 21760/ 60000]
Batch 180. loss: 2.302663 [ 23040/ 60000]
Batch 190. loss: 2.302505 [ 24320/ 60000]
Batch 200. loss: 2.302664 [ 25600/ 60000]
Batch 210. loss: 2.302498 [ 26880/ 60000]
Batch 220. loss: 2.302577 [ 28160/ 60000]
Batch 230. loss: 2.302450 [ 29440/ 60000]
Batch 240. loss: 2.302659 [ 30720/ 60000]
Batch 250. loss: 2.302613 [ 32000/ 60000]
Batch 260. loss: 2.302629 [ 33280/ 60000]
Batch 270. loss: 2.302538 [ 34560/ 60000]
Batch 280. loss: 2.302644 [ 35840/ 60000]
Batch 290. loss: 2.302500 [ 37120/ 60000]
Batch 300. loss: 2.302585 [ 38400/ 60000]
Batch 310. loss: 2.302674 [ 39680/ 60000]
Batch 320. loss: 2.302682 [ 40960/ 60000]
Batch 330. loss: 2.302580 [ 42240/ 60000]
Batch 340. loss: 2.302451 [ 43520/ 60000]
Batch 350. loss: 2.302577 [ 44800/ 60000]
Batch 360. loss: 2.302594 [ 46080/ 60000]
Batch 370. loss: 2.302391 [ 47360/ 60000]
Batch 380. loss: 2.302571 [ 48640/ 60000]
Batch 390. loss: 2.302577 [ 49920/ 60000]
Batch 400. loss: 2.302512 [ 51200/ 60000]
Batch 410. loss: 2.302636 [ 52480/ 60000]
Batch 420. loss: 2.302628 [ 53760/ 60000]
Batch 430. loss: 2.302520 [ 55040/ 60000]
Batch 440. loss: 2.302643 [ 56320/ 60000]
Batch 450. loss: 2.302469 [ 57600/ 60000]
Batch 460. loss: 2.302492 [ 58880/ 60000]
Test Error:
Accuracy: 10.0%, Avg loss: 2.302572
Epoch 2
--------------------------------------------------
Batch 0. loss: 2.302553 [ 0/ 60000]
Batch 10. loss: 2.302538 [ 1280/ 60000]
Batch 20. loss: 2.302502 [ 2560/ 60000]
Batch 30. loss: 2.302678 [ 3840/ 60000]
Batch 40. loss: 2.302627 [ 5120/ 60000]
Batch 50. loss: 2.302490 [ 6400/ 60000]
Batch 60. loss: 2.302720 [ 7680/ 60000]
Batch 70. loss: 2.302503 [ 8960/ 60000]
Batch 80. loss: 2.302573 [ 10240/ 60000]
Batch 90. loss: 2.302624 [ 11520/ 60000]
Batch 100. loss: 2.302552 [ 12800/ 60000]
Batch 110. loss: 2.302598 [ 14080/ 60000]
Batch 120. loss: 2.302434 [ 15360/ 60000]
Batch 130. loss: 2.302501 [ 16640/ 60000]
Batch 140. loss: 2.302570 [ 17920/ 60000]
Batch 150. loss: 2.302487 [ 19200/ 60000]
Batch 160. loss: 2.302543 [ 20480/ 60000]
Batch 170. loss: 2.302612 [ 21760/ 60000]
Batch 180. loss: 2.302545 [ 23040/ 60000]
Batch 190. loss: 2.302519 [ 24320/ 60000]
Batch 200. loss: 2.302530 [ 25600/ 60000]
Batch 210. loss: 2.302665 [ 26880/ 60000]
Batch 220. loss: 2.302392 [ 28160/ 60000]
Batch 230. loss: 2.302473 [ 29440/ 60000]
Batch 240. loss: 2.302555 [ 30720/ 60000]
Batch 250. loss: 2.302474 [ 32000/ 60000]
Batch 260. loss: 2.302474 [ 33280/ 60000]
Batch 270. loss: 2.302426 [ 34560/ 60000]
Batch 280. loss: 2.302649 [ 35840/ 60000]
Batch 290. loss: 2.302574 [ 37120/ 60000]
Batch 300. loss: 2.302496 [ 38400/ 60000]
Batch 310. loss: 2.302657 [ 39680/ 60000]
Batch 320. loss: 2.302688 [ 40960/ 60000]
Batch 330. loss: 2.302640 [ 42240/ 60000]
Batch 340. loss: 2.302533 [ 43520/ 60000]
Batch 350. loss: 2.302540 [ 44800/ 60000]
Batch 360. loss: 2.302568 [ 46080/ 60000]
Batch 370. loss: 2.302586 [ 47360/ 60000]
Batch 380. loss: 2.302556 [ 48640/ 60000]
Batch 390. loss: 2.302524 [ 49920/ 60000]
Batch 400. loss: 2.302498 [ 51200/ 60000]
Batch 410. loss: 2.302520 [ 52480/ 60000]
Batch 420. loss: 2.302664 [ 53760/ 60000]
Batch 430. loss: 2.302434 [ 55040/ 60000]
Batch 440. loss: 2.302681 [ 56320/ 60000]
Batch 450. loss: 2.302368 [ 57600/ 60000]
Batch 460. loss: 2.302603 [ 58880/ 60000]
Test Error:
Accuracy: 10.0%, Avg loss: 2.302540
Epoch 3
--------------------------------------------------
Batch 0. loss: 2.302538 [ 0/ 60000]
Batch 10. loss: 2.302613 [ 1280/ 60000]
Batch 20. loss: 2.302551 [ 2560/ 60000]
Batch 30. loss: 2.302471 [ 3840/ 60000]
Batch 40. loss: 2.302606 [ 5120/ 60000]
Batch 50. loss: 2.302410 [ 6400/ 60000]
Batch 60. loss: 2.302602 [ 7680/ 60000]
Batch 70. loss: 2.302523 [ 8960/ 60000]
Batch 80. loss: 2.302584 [ 10240/ 60000]
Batch 90. loss: 2.302464 [ 11520/ 60000]
Batch 100. loss: 2.302513 [ 12800/ 60000]
Batch 110. loss: 2.302578 [ 14080/ 60000]
Batch 120. loss: 2.302447 [ 15360/ 60000]
Batch 130. loss: 2.302577 [ 16640/ 60000]
Batch 140. loss: 2.302364 [ 17920/ 60000]
Batch 150. loss: 2.302510 [ 19200/ 60000]
Batch 160. loss: 2.302514 [ 20480/ 60000]
Batch 170. loss: 2.302447 [ 21760/ 60000]
Batch 180. loss: 2.302559 [ 23040/ 60000]
Batch 190. loss: 2.302680 [ 24320/ 60000]
Batch 200. loss: 2.302599 [ 25600/ 60000]
Batch 210. loss: 2.302339 [ 26880/ 60000]
Batch 220. loss: 2.302596 [ 28160/ 60000]
Batch 230. loss: 2.302505 [ 29440/ 60000]
Batch 240. loss: 2.302507 [ 30720/ 60000]
Batch 250. loss: 2.302465 [ 32000/ 60000]
Batch 260. loss: 2.302510 [ 33280/ 60000]
Batch 270. loss: 2.302490 [ 34560/ 60000]
Batch 280. loss: 2.302492 [ 35840/ 60000]
Batch 290. loss: 2.302553 [ 37120/ 60000]
Batch 300. loss: 2.302562 [ 38400/ 60000]
Batch 310. loss: 2.302598 [ 39680/ 60000]
Batch 320. loss: 2.302589 [ 40960/ 60000]
Batch 330. loss: 2.302476 [ 42240/ 60000]
Batch 340. loss: 2.302496 [ 43520/ 60000]
Batch 350. loss: 2.302457 [ 44800/ 60000]
Batch 360. loss: 2.302503 [ 46080/ 60000]
Batch 370. loss: 2.302455 [ 47360/ 60000]
Batch 380. loss: 2.302520 [ 48640/ 60000]
Batch 390. loss: 2.302646 [ 49920/ 60000]
Batch 400. loss: 2.302523 [ 51200/ 60000]
Batch 410. loss: 2.302505 [ 52480/ 60000]
Batch 420. loss: 2.302614 [ 53760/ 60000]
Batch 430. loss: 2.302471 [ 55040/ 60000]
Batch 440. loss: 2.302492 [ 56320/ 60000]
Batch 450. loss: 2.302544 [ 57600/ 60000]
Batch 460. loss: 2.302474 [ 58880/ 60000]
Test Error:
Accuracy: 10.0%, Avg loss: 2.302485
Epoch 4
--------------------------------------------------
Batch 0. loss: 2.302429 [ 0/ 60000]
Batch 10. loss: 2.302483 [ 1280/ 60000]
Batch 20. loss: 2.302336 [ 2560/ 60000]
Batch 30. loss: 2.302529 [ 3840/ 60000]
Batch 40. loss: 2.302478 [ 5120/ 60000]
Batch 50. loss: 2.302545 [ 6400/ 60000]
Batch 60. loss: 2.302460 [ 7680/ 60000]
Batch 70. loss: 2.302435 [ 8960/ 60000]
Batch 80. loss: 2.302432 [ 10240/ 60000]
Batch 90. loss: 2.302579 [ 11520/ 60000]
Batch 100. loss: 2.302501 [ 12800/ 60000]
Batch 110. loss: 2.302594 [ 14080/ 60000]
Batch 120. loss: 2.302467 [ 15360/ 60000]
Batch 130. loss: 2.302489 [ 16640/ 60000]
Batch 140. loss: 2.302414 [ 17920/ 60000]
Batch 150. loss: 2.302462 [ 19200/ 60000]
Batch 160. loss: 2.302531 [ 20480/ 60000]
Batch 170. loss: 2.302358 [ 21760/ 60000]
Batch 180. loss: 2.302526 [ 23040/ 60000]
Batch 190. loss: 2.302413 [ 24320/ 60000]
Batch 200. loss: 2.302424 [ 25600/ 60000]
Batch 210. loss: 2.302474 [ 26880/ 60000]
Batch 220. loss: 2.302463 [ 28160/ 60000]
Batch 230. loss: 2.302452 [ 29440/ 60000]
Batch 240. loss: 2.302449 [ 30720/ 60000]
Batch 250. loss: 2.302517 [ 32000/ 60000]
Batch 260. loss: 2.302438 [ 33280/ 60000]
Batch 270. loss: 2.302510 [ 34560/ 60000]
Batch 280. loss: 2.302402 [ 35840/ 60000]
Batch 290. loss: 2.302325 [ 37120/ 60000]
Batch 300. loss: 2.302453 [ 38400/ 60000]
Batch 310. loss: 2.302447 [ 39680/ 60000]
Batch 320. loss: 2.302475 [ 40960/ 60000]
Batch 330. loss: 2.302534 [ 42240/ 60000]
Batch 340. loss: 2.302328 [ 43520/ 60000]
Batch 350. loss: 2.302395 [ 44800/ 60000]
Batch 360. loss: 2.302345 [ 46080/ 60000]
Batch 370. loss: 2.302391 [ 47360/ 60000]
Batch 380. loss: 2.302416 [ 48640/ 60000]
Batch 390. loss: 2.302302 [ 49920/ 60000]
Batch 400. loss: 2.302329 [ 51200/ 60000]
Batch 410. loss: 2.302399 [ 52480/ 60000]
Batch 420. loss: 2.302417 [ 53760/ 60000]
Batch 430. loss: 2.302288 [ 55040/ 60000]
Batch 440. loss: 2.302342 [ 56320/ 60000]
Batch 450. loss: 2.302394 [ 57600/ 60000]
Batch 460. loss: 2.302382 [ 58880/ 60000]
Test Error:
Accuracy: 10.9%, Avg loss: 2.302317
Epoch 5
--------------------------------------------------
Batch 0. loss: 2.302372 [ 0/ 60000]
Batch 10. loss: 2.302310 [ 1280/ 60000]
Batch 20. loss: 2.302299 [ 2560/ 60000]
Batch 30. loss: 2.302274 [ 3840/ 60000]
Batch 40. loss: 2.302314 [ 5120/ 60000]
Batch 50. loss: 2.302271 [ 6400/ 60000]
Batch 60. loss: 2.302255 [ 7680/ 60000]
Batch 70. loss: 2.302176 [ 8960/ 60000]
Batch 80. loss: 2.302268 [ 10240/ 60000]
Batch 90. loss: 2.302189 [ 11520/ 60000]
Batch 100. loss: 2.302262 [ 12800/ 60000]
Batch 110. loss: 2.302220 [ 14080/ 60000]
Batch 120. loss: 2.302229 [ 15360/ 60000]
Batch 130. loss: 2.302202 [ 16640/ 60000]
Batch 140. loss: 2.302186 [ 17920/ 60000]
Batch 150. loss: 2.302201 [ 19200/ 60000]
Batch 160. loss: 2.302187 [ 20480/ 60000]
Batch 170. loss: 2.302213 [ 21760/ 60000]
Batch 180. loss: 2.302129 [ 23040/ 60000]
Batch 190. loss: 2.302045 [ 24320/ 60000]
Batch 200. loss: 2.302194 [ 25600/ 60000]
Batch 210. loss: 2.302067 [ 26880/ 60000]
Batch 220. loss: 2.302143 [ 28160/ 60000]
Batch 230. loss: 2.302097 [ 29440/ 60000]
Batch 240. loss: 2.302009 [ 30720/ 60000]
Batch 250. loss: 2.302096 [ 32000/ 60000]
Batch 260. loss: 2.301920 [ 33280/ 60000]
Batch 270. loss: 2.301996 [ 34560/ 60000]
Batch 280. loss: 2.302022 [ 35840/ 60000]
Batch 290. loss: 2.301873 [ 37120/ 60000]
Batch 300. loss: 2.301920 [ 38400/ 60000]
Batch 310. loss: 2.301831 [ 39680/ 60000]
Batch 320. loss: 2.301851 [ 40960/ 60000]
Batch 330. loss: 2.301950 [ 42240/ 60000]
Batch 340. loss: 2.301852 [ 43520/ 60000]
Batch 350. loss: 2.301640 [ 44800/ 60000]
Batch 360. loss: 2.301766 [ 46080/ 60000]
Batch 370. loss: 2.301568 [ 47360/ 60000]
Batch 380. loss: 2.301706 [ 48640/ 60000]
Batch 390. loss: 2.301632 [ 49920/ 60000]
Batch 400. loss: 2.301589 [ 51200/ 60000]
Batch 410. loss: 2.301416 [ 52480/ 60000]
Batch 420. loss: 2.301385 [ 53760/ 60000]
Batch 430. loss: 2.301363 [ 55040/ 60000]
Batch 440. loss: 2.301144 [ 56320/ 60000]
Batch 450. loss: 2.301186 [ 57600/ 60000]
Batch 460. loss: 2.301031 [ 58880/ 60000]
Test Error:
Accuracy: 23.6%, Avg loss: 2.301093
Epoch 6
--------------------------------------------------
Batch 0. loss: 2.301158 [ 0/ 60000]
Batch 10. loss: 2.301207 [ 1280/ 60000]
Batch 20. loss: 2.300787 [ 2560/ 60000]
Batch 30. loss: 2.300656 [ 3840/ 60000]
Batch 40. loss: 2.300561 [ 5120/ 60000]
Batch 50. loss: 2.300533 [ 6400/ 60000]
Batch 60. loss: 2.300132 [ 7680/ 60000]
Batch 70. loss: 2.299937 [ 8960/ 60000]
Batch 80. loss: 2.299698 [ 10240/ 60000]
Batch 90. loss: 2.299723 [ 11520/ 60000]
Batch 100. loss: 2.299409 [ 12800/ 60000]
Batch 110. loss: 2.298980 [ 14080/ 60000]
Batch 120. loss: 2.298872 [ 15360/ 60000]
Batch 130. loss: 2.298027 [ 16640/ 60000]
Batch 140. loss: 2.297226 [ 17920/ 60000]
Batch 150. loss: 2.296402 [ 19200/ 60000]
Batch 160. loss: 2.294328 [ 20480/ 60000]
Batch 170. loss: 2.291690 [ 21760/ 60000]
Batch 180. loss: 2.287592 [ 23040/ 60000]
Batch 190. loss: 2.278238 [ 24320/ 60000]
Batch 200. loss: 2.246764 [ 25600/ 60000]
Batch 210. loss: 2.094420 [ 26880/ 60000]
Batch 220. loss: 2.039242 [ 28160/ 60000]
Batch 230. loss: 2.016960 [ 29440/ 60000]
Batch 240. loss: 2.072822 [ 30720/ 60000]
Batch 250. loss: 2.099977 [ 32000/ 60000]
Batch 260. loss: 1.988256 [ 33280/ 60000]
Batch 270. loss: 1.966524 [ 34560/ 60000]
Batch 280. loss: 1.998237 [ 35840/ 60000]
Batch 290. loss: 1.981117 [ 37120/ 60000]
Batch 300. loss: 1.963290 [ 38400/ 60000]
Batch 310. loss: 1.941619 [ 39680/ 60000]
Batch 320. loss: 1.900003 [ 40960/ 60000]
Batch 330. loss: 1.924808 [ 42240/ 60000]
Batch 340. loss: 1.898822 [ 43520/ 60000]
Batch 350. loss: 1.947645 [ 44800/ 60000]
Batch 360. loss: 1.920866 [ 46080/ 60000]
Batch 370. loss: 1.953794 [ 47360/ 60000]
Batch 380. loss: 1.965292 [ 48640/ 60000]
Batch 390. loss: 2.004429 [ 49920/ 60000]
Batch 400. loss: 1.978456 [ 51200/ 60000]
Batch 410. loss: 1.974202 [ 52480/ 60000]
Batch 420. loss: 1.971232 [ 53760/ 60000]
Batch 430. loss: 1.916823 [ 55040/ 60000]
Batch 440. loss: 1.840565 [ 56320/ 60000]
Batch 450. loss: 2.001937 [ 57600/ 60000]
Batch 460. loss: 1.944827 [ 58880/ 60000]
Test Error:
Accuracy: 52.1%, Avg loss: 1.936028
Epoch 7
--------------------------------------------------
Batch 0. loss: 1.978395 [ 0/ 60000]
Batch 10. loss: 1.966059 [ 1280/ 60000]
Batch 20. loss: 2.001111 [ 2560/ 60000]
Batch 30. loss: 1.911892 [ 3840/ 60000]
Batch 40. loss: 1.894652 [ 5120/ 60000]
Batch 50. loss: 1.892287 [ 6400/ 60000]
Batch 60. loss: 1.893414 [ 7680/ 60000]
Batch 70. loss: 1.877386 [ 8960/ 60000]
Batch 80. loss: 2.008717 [ 10240/ 60000]
Batch 90. loss: 1.838402 [ 11520/ 60000]
Batch 100. loss: 1.807332 [ 12800/ 60000]
Batch 110. loss: 1.935086 [ 14080/ 60000]
Batch 120. loss: 1.960529 [ 15360/ 60000]
Batch 130. loss: 1.917515 [ 16640/ 60000]
Batch 140. loss: 1.832376 [ 17920/ 60000]
Batch 150. loss: 1.845546 [ 19200/ 60000]
Batch 160. loss: 1.901421 [ 20480/ 60000]
Batch 170. loss: 1.899388 [ 21760/ 60000]
Batch 180. loss: 1.873929 [ 23040/ 60000]
Batch 190. loss: 1.845054 [ 24320/ 60000]
Batch 200. loss: 1.835492 [ 25600/ 60000]
Batch 210. loss: 1.989509 [ 26880/ 60000]
Batch 220. loss: 1.908213 [ 28160/ 60000]
Batch 230. loss: 1.883295 [ 29440/ 60000]
Batch 240. loss: 1.896602 [ 30720/ 60000]
Batch 250. loss: 1.818024 [ 32000/ 60000]
Batch 260. loss: 1.899410 [ 33280/ 60000]
Batch 270. loss: 1.777468 [ 34560/ 60000]
Batch 280. loss: 1.909218 [ 35840/ 60000]
Batch 290. loss: 1.862908 [ 37120/ 60000]
Batch 300. loss: 1.851823 [ 38400/ 60000]
Batch 310. loss: 1.869792 [ 39680/ 60000]
Batch 320. loss: 1.885041 [ 40960/ 60000]
Batch 330. loss: 1.806804 [ 42240/ 60000]
Batch 340. loss: 1.844225 [ 43520/ 60000]
Batch 350. loss: 1.905163 [ 44800/ 60000]
Batch 360. loss: 1.918955 [ 46080/ 60000]
Batch 370. loss: 1.889223 [ 47360/ 60000]
Batch 380. loss: 1.915530 [ 48640/ 60000]
Batch 390. loss: 1.821159 [ 49920/ 60000]
Batch 400. loss: 1.822628 [ 51200/ 60000]
Batch 410. loss: 1.905660 [ 52480/ 60000]
Batch 420. loss: 1.812085 [ 53760/ 60000]
Batch 430. loss: 1.849492 [ 55040/ 60000]
Batch 440. loss: 1.816443 [ 56320/ 60000]
Batch 450. loss: 1.890649 [ 57600/ 60000]
Batch 460. loss: 1.856383 [ 58880/ 60000]
Test Error:
Accuracy: 62.3%, Avg loss: 1.839310
Epoch 8
--------------------------------------------------
Batch 0. loss: 1.832578 [ 0/ 60000]
Batch 10. loss: 1.850766 [ 1280/ 60000]
Batch 20. loss: 1.921401 [ 2560/ 60000]
Batch 30. loss: 1.831027 [ 3840/ 60000]
Batch 40. loss: 1.830129 [ 5120/ 60000]
Batch 50. loss: 1.785644 [ 6400/ 60000]
Batch 60. loss: 1.959333 [ 7680/ 60000]
Batch 70. loss: 1.834202 [ 8960/ 60000]
Batch 80. loss: 1.867659 [ 10240/ 60000]
Batch 90. loss: 1.804964 [ 11520/ 60000]
Batch 100. loss: 1.894428 [ 12800/ 60000]
Batch 110. loss: 1.923591 [ 14080/ 60000]
Batch 120. loss: 1.915493 [ 15360/ 60000]
Batch 130. loss: 1.787184 [ 16640/ 60000]
Batch 140. loss: 1.834055 [ 17920/ 60000]
Batch 150. loss: 1.896484 [ 19200/ 60000]
Batch 160. loss: 1.867615 [ 20480/ 60000]
Batch 170. loss: 1.852844 [ 21760/ 60000]
Batch 180. loss: 1.808168 [ 23040/ 60000]
Batch 190. loss: 1.807170 [ 24320/ 60000]
Batch 200. loss: 1.840905 [ 25600/ 60000]
Batch 210. loss: 1.901084 [ 26880/ 60000]
Batch 220. loss: 1.800038 [ 28160/ 60000]
Batch 230. loss: 1.836349 [ 29440/ 60000]
Batch 240. loss: 1.761267 [ 30720/ 60000]
Batch 250. loss: 1.824852 [ 32000/ 60000]
Batch 260. loss: 1.820296 [ 33280/ 60000]
Batch 270. loss: 1.852176 [ 34560/ 60000]
Batch 280. loss: 1.727674 [ 35840/ 60000]
Batch 290. loss: 1.777058 [ 37120/ 60000]
Batch 300. loss: 1.765809 [ 38400/ 60000]
Batch 310. loss: 1.794556 [ 39680/ 60000]
Batch 320. loss: 1.771551 [ 40960/ 60000]
Batch 330. loss: 1.760629 [ 42240/ 60000]
Batch 340. loss: 1.823438 [ 43520/ 60000]
Batch 350. loss: 1.810347 [ 44800/ 60000]
Batch 360. loss: 1.796755 [ 46080/ 60000]
Batch 370. loss: 1.760195 [ 47360/ 60000]
Batch 380. loss: 1.820902 [ 48640/ 60000]
Batch 390. loss: 1.735942 [ 49920/ 60000]
Batch 400. loss: 1.813698 [ 51200/ 60000]
Batch 410. loss: 1.713705 [ 52480/ 60000]
Batch 420. loss: 1.835007 [ 53760/ 60000]
Batch 430. loss: 1.811941 [ 55040/ 60000]
Batch 440. loss: 1.753336 [ 56320/ 60000]
Batch 450. loss: 1.727862 [ 57600/ 60000]
Batch 460. loss: 1.744341 [ 58880/ 60000]
Test Error:
Accuracy: 70.0%, Avg loss: 1.761105
Epoch 9
--------------------------------------------------
Batch 0. loss: 1.793363 [ 0/ 60000]
Batch 10. loss: 1.690925 [ 1280/ 60000]
Batch 20. loss: 1.720695 [ 2560/ 60000]
Batch 30. loss: 1.770101 [ 3840/ 60000]
Batch 40. loss: 1.728830 [ 5120/ 60000]
Batch 50. loss: 1.764893 [ 6400/ 60000]
Batch 60. loss: 1.742898 [ 7680/ 60000]
Batch 70. loss: 1.757620 [ 8960/ 60000]
Batch 80. loss: 1.845608 [ 10240/ 60000]
Batch 90. loss: 1.737488 [ 11520/ 60000]
Batch 100. loss: 1.758742 [ 12800/ 60000]
Batch 110. loss: 1.763247 [ 14080/ 60000]
Batch 120. loss: 1.722003 [ 15360/ 60000]
Batch 130. loss: 1.750986 [ 16640/ 60000]
Batch 140. loss: 1.731705 [ 17920/ 60000]
Batch 150. loss: 1.724511 [ 19200/ 60000]
Batch 160. loss: 1.736550 [ 20480/ 60000]
Batch 170. loss: 1.765590 [ 21760/ 60000]
Batch 180. loss: 1.755798 [ 23040/ 60000]
Batch 190. loss: 1.740676 [ 24320/ 60000]
Batch 200. loss: 1.852436 [ 25600/ 60000]
Batch 210. loss: 1.801128 [ 26880/ 60000]
Batch 220. loss: 1.836245 [ 28160/ 60000]
Batch 230. loss: 1.722154 [ 29440/ 60000]
Batch 240. loss: 1.728477 [ 30720/ 60000]
Batch 250. loss: 1.726139 [ 32000/ 60000]
Batch 260. loss: 1.741500 [ 33280/ 60000]
Batch 270. loss: 1.812016 [ 34560/ 60000]
Batch 280. loss: 1.755382 [ 35840/ 60000]
Batch 290. loss: 1.693042 [ 37120/ 60000]
Batch 300. loss: 1.742284 [ 38400/ 60000]
Batch 310. loss: 1.783704 [ 39680/ 60000]
Batch 320. loss: 1.716109 [ 40960/ 60000]
Batch 330. loss: 1.735009 [ 42240/ 60000]
Batch 340. loss: 1.678388 [ 43520/ 60000]
Batch 350. loss: 1.797430 [ 44800/ 60000]
Batch 360. loss: 1.713228 [ 46080/ 60000]
Batch 370. loss: 1.710999 [ 47360/ 60000]
Batch 380. loss: 1.810452 [ 48640/ 60000]
Batch 390. loss: 1.809859 [ 49920/ 60000]
Batch 400. loss: 1.691525 [ 51200/ 60000]
Batch 410. loss: 1.804744 [ 52480/ 60000]
Batch 420. loss: 1.734864 [ 53760/ 60000]
Batch 430. loss: 1.810766 [ 55040/ 60000]
Batch 440. loss: 1.746286 [ 56320/ 60000]
Batch 450. loss: 1.752030 [ 57600/ 60000]
Batch 460. loss: 1.689284 [ 58880/ 60000]
Test Error:
Accuracy: 72.4%, Avg loss: 1.735843
Epoch 10
--------------------------------------------------
Batch 0. loss: 1.748788 [ 0/ 60000]
Batch 10. loss: 1.721186 [ 1280/ 60000]
Batch 20. loss: 1.753192 [ 2560/ 60000]
Batch 30. loss: 1.716325 [ 3840/ 60000]
Batch 40. loss: 1.767966 [ 5120/ 60000]
Batch 50. loss: 1.709133 [ 6400/ 60000]
Batch 60. loss: 1.749907 [ 7680/ 60000]
Batch 70. loss: 1.728320 [ 8960/ 60000]
Batch 80. loss: 1.770466 [ 10240/ 60000]
Batch 90. loss: 1.752881 [ 11520/ 60000]
Batch 100. loss: 1.727271 [ 12800/ 60000]
Batch 110. loss: 1.760525 [ 14080/ 60000]
Batch 120. loss: 1.771542 [ 15360/ 60000]
Batch 130. loss: 1.724397 [ 16640/ 60000]
Batch 140. loss: 1.830028 [ 17920/ 60000]
Batch 150. loss: 1.799977 [ 19200/ 60000]
Batch 160. loss: 1.735342 [ 20480/ 60000]
Batch 170. loss: 1.717263 [ 21760/ 60000]
Batch 180. loss: 1.784490 [ 23040/ 60000]
Batch 190. loss: 1.723932 [ 24320/ 60000]
Batch 200. loss: 1.756604 [ 25600/ 60000]
Batch 210. loss: 1.755808 [ 26880/ 60000]
Batch 220. loss: 1.723045 [ 28160/ 60000]
Batch 230. loss: 1.686221 [ 29440/ 60000]
Batch 240. loss: 1.712223 [ 30720/ 60000]
Batch 250. loss: 1.717282 [ 32000/ 60000]
Batch 260. loss: 1.695238 [ 33280/ 60000]
Batch 270. loss: 1.731850 [ 34560/ 60000]
Batch 280. loss: 1.747408 [ 35840/ 60000]
Batch 290. loss: 1.756579 [ 37120/ 60000]
Batch 300. loss: 1.710418 [ 38400/ 60000]
Batch 310. loss: 1.706725 [ 39680/ 60000]
Batch 320. loss: 1.672631 [ 40960/ 60000]
Batch 330. loss: 1.677973 [ 42240/ 60000]
Batch 340. loss: 1.704685 [ 43520/ 60000]
Batch 350. loss: 1.690227 [ 44800/ 60000]
Batch 360. loss: 1.722619 [ 46080/ 60000]
Batch 370. loss: 1.729018 [ 47360/ 60000]
Batch 380. loss: 1.694752 [ 48640/ 60000]
Batch 390. loss: 1.684926 [ 49920/ 60000]
Batch 400. loss: 1.718038 [ 51200/ 60000]
Batch 410. loss: 1.757453 [ 52480/ 60000]
Batch 420. loss: 1.715343 [ 53760/ 60000]
Batch 430. loss: 1.757568 [ 55040/ 60000]
Batch 440. loss: 1.683859 [ 56320/ 60000]
Batch 450. loss: 1.770902 [ 57600/ 60000]
Batch 460. loss: 1.675709 [ 58880/ 60000]
Test Error:
Accuracy: 74.6%, Avg loss: 1.715309
Epoch 11
--------------------------------------------------
Batch 0. loss: 1.672165 [ 0/ 60000]
Batch 10. loss: 1.700356 [ 1280/ 60000]
Batch 20. loss: 1.715745 [ 2560/ 60000]
Batch 30. loss: 1.707289 [ 3840/ 60000]
Batch 40. loss: 1.796286 [ 5120/ 60000]
Batch 50. loss: 1.739985 [ 6400/ 60000]
Batch 60. loss: 1.649291 [ 7680/ 60000]
Batch 70. loss: 1.700058 [ 8960/ 60000]
Batch 80. loss: 1.731775 [ 10240/ 60000]
Batch 90. loss: 1.692611 [ 11520/ 60000]
Batch 100. loss: 1.687591 [ 12800/ 60000]
Batch 110. loss: 1.721755 [ 14080/ 60000]
Batch 120. loss: 1.685807 [ 15360/ 60000]
Batch 130. loss: 1.723649 [ 16640/ 60000]
Batch 140. loss: 1.726791 [ 17920/ 60000]
Batch 150. loss: 1.659057 [ 19200/ 60000]
Batch 160. loss: 1.653200 [ 20480/ 60000]
Batch 170. loss: 1.712812 [ 21760/ 60000]
Batch 180. loss: 1.660698 [ 23040/ 60000]
Batch 190. loss: 1.640146 [ 24320/ 60000]
Batch 200. loss: 1.626749 [ 25600/ 60000]
Batch 210. loss: 1.757945 [ 26880/ 60000]
Batch 220. loss: 1.721808 [ 28160/ 60000]
Batch 230. loss: 1.654315 [ 29440/ 60000]
Batch 240. loss: 1.757580 [ 30720/ 60000]
Batch 250. loss: 1.697371 [ 32000/ 60000]
Batch 260. loss: 1.720751 [ 33280/ 60000]
Batch 270. loss: 1.672982 [ 34560/ 60000]
Batch 280. loss: 1.717573 [ 35840/ 60000]
Batch 290. loss: 1.686266 [ 37120/ 60000]
Batch 300. loss: 1.733660 [ 38400/ 60000]
Batch 310. loss: 1.757696 [ 39680/ 60000]
Batch 320. loss: 1.720246 [ 40960/ 60000]
Batch 330. loss: 1.740090 [ 42240/ 60000]
Batch 340. loss: 1.695935 [ 43520/ 60000]
Batch 350. loss: 1.696690 [ 44800/ 60000]
Batch 360. loss: 1.703935 [ 46080/ 60000]
Batch 370. loss: 1.720950 [ 47360/ 60000]
Batch 380. loss: 1.660739 [ 48640/ 60000]
Batch 390. loss: 1.740359 [ 49920/ 60000]
Batch 400. loss: 1.691670 [ 51200/ 60000]
Batch 410. loss: 1.700508 [ 52480/ 60000]
Batch 420. loss: 1.700871 [ 53760/ 60000]
Batch 430. loss: 1.797983 [ 55040/ 60000]
Batch 440. loss: 1.713510 [ 56320/ 60000]
Batch 450. loss: 1.707490 [ 57600/ 60000]
Batch 460. loss: 1.643024 [ 58880/ 60000]
Test Error:
Accuracy: 74.8%, Avg loss: 1.711042
Epoch 12
--------------------------------------------------
Batch 0. loss: 1.723619 [ 0/ 60000]
Batch 10. loss: 1.701650 [ 1280/ 60000]
Batch 20. loss: 1.703880 [ 2560/ 60000]
Batch 30. loss: 1.702173 [ 3840/ 60000]
Batch 40. loss: 1.676927 [ 5120/ 60000]
Batch 50. loss: 1.698105 [ 6400/ 60000]
Batch 60. loss: 1.693319 [ 7680/ 60000]
Batch 70. loss: 1.748694 [ 8960/ 60000]
Batch 80. loss: 1.706485 [ 10240/ 60000]
Batch 90. loss: 1.684708 [ 11520/ 60000]
Batch 100. loss: 1.650103 [ 12800/ 60000]
Batch 110. loss: 1.652002 [ 14080/ 60000]
Batch 120. loss: 1.709484 [ 15360/ 60000]
Batch 130. loss: 1.683867 [ 16640/ 60000]
Batch 140. loss: 1.611202 [ 17920/ 60000]
Batch 150. loss: 1.695020 [ 19200/ 60000]
Batch 160. loss: 1.670259 [ 20480/ 60000]
Batch 170. loss: 1.723510 [ 21760/ 60000]
Batch 180. loss: 1.671004 [ 23040/ 60000]
Batch 190. loss: 1.672854 [ 24320/ 60000]
Batch 200. loss: 1.757992 [ 25600/ 60000]
Batch 210. loss: 1.641279 [ 26880/ 60000]
Batch 220. loss: 1.760699 [ 28160/ 60000]
Batch 230. loss: 1.670453 [ 29440/ 60000]
Batch 240. loss: 1.643521 [ 30720/ 60000]
Batch 250. loss: 1.701723 [ 32000/ 60000]
Batch 260. loss: 1.627173 [ 33280/ 60000]
Batch 270. loss: 1.654114 [ 34560/ 60000]
Batch 280. loss: 1.656533 [ 35840/ 60000]
Batch 290. loss: 1.658060 [ 37120/ 60000]
Batch 300. loss: 1.724665 [ 38400/ 60000]
Batch 310. loss: 1.664529 [ 39680/ 60000]
Batch 320. loss: 1.700602 [ 40960/ 60000]
Batch 330. loss: 1.696822 [ 42240/ 60000]
Batch 340. loss: 1.668161 [ 43520/ 60000]
Batch 350. loss: 1.640966 [ 44800/ 60000]
Batch 360. loss: 1.745023 [ 46080/ 60000]
Batch 370. loss: 1.739868 [ 47360/ 60000]
Batch 380. loss: 1.717833 [ 48640/ 60000]
Batch 390. loss: 1.682910 [ 49920/ 60000]
Batch 400. loss: 1.643774 [ 51200/ 60000]
Batch 410. loss: 1.673283 [ 52480/ 60000]
Batch 420. loss: 1.693669 [ 53760/ 60000]
Batch 430. loss: 1.727323 [ 55040/ 60000]
Batch 440. loss: 1.739132 [ 56320/ 60000]
Batch 450. loss: 1.716815 [ 57600/ 60000]
Batch 460. loss: 1.705666 [ 58880/ 60000]
Test Error:
Accuracy: 76.2%, Avg loss: 1.699369
Epoch 13
--------------------------------------------------
Batch 0. loss: 1.723593 [ 0/ 60000]
Batch 10. loss: 1.692250 [ 1280/ 60000]
Batch 20. loss: 1.689159 [ 2560/ 60000]
Batch 30. loss: 1.652385 [ 3840/ 60000]
Batch 40. loss: 1.730246 [ 5120/ 60000]
Batch 50. loss: 1.665875 [ 6400/ 60000]
Batch 60. loss: 1.710145 [ 7680/ 60000]
Batch 70. loss: 1.642301 [ 8960/ 60000]
Batch 80. loss: 1.662198 [ 10240/ 60000]
Batch 90. loss: 1.635981 [ 11520/ 60000]
Batch 100. loss: 1.740333 [ 12800/ 60000]
Batch 110. loss: 1.664951 [ 14080/ 60000]
Batch 120. loss: 1.707348 [ 15360/ 60000]
Batch 130. loss: 1.610891 [ 16640/ 60000]
Batch 140. loss: 1.675005 [ 17920/ 60000]
Batch 150. loss: 1.655793 [ 19200/ 60000]
Batch 160. loss: 1.681727 [ 20480/ 60000]
Batch 170. loss: 1.718474 [ 21760/ 60000]
Batch 180. loss: 1.666281 [ 23040/ 60000]
Batch 190. loss: 1.603946 [ 24320/ 60000]
Batch 200. loss: 1.683652 [ 25600/ 60000]
Batch 210. loss: 1.720128 [ 26880/ 60000]
Batch 220. loss: 1.650844 [ 28160/ 60000]
Batch 230. loss: 1.668238 [ 29440/ 60000]
Batch 240. loss: 1.719300 [ 30720/ 60000]
Batch 250. loss: 1.675293 [ 32000/ 60000]
Batch 260. loss: 1.669166 [ 33280/ 60000]
Batch 270. loss: 1.726092 [ 34560/ 60000]
Batch 280. loss: 1.663939 [ 35840/ 60000]
Batch 290. loss: 1.700507 [ 37120/ 60000]
Batch 300. loss: 1.702387 [ 38400/ 60000]
Batch 310. loss: 1.653186 [ 39680/ 60000]
Batch 320. loss: 1.684312 [ 40960/ 60000]
Batch 330. loss: 1.635864 [ 42240/ 60000]
Batch 340. loss: 1.687936 [ 43520/ 60000]
Batch 350. loss: 1.706237 [ 44800/ 60000]
Batch 360. loss: 1.644049 [ 46080/ 60000]
Batch 370. loss: 1.658161 [ 47360/ 60000]
Batch 380. loss: 1.728579 [ 48640/ 60000]
Batch 390. loss: 1.725883 [ 49920/ 60000]
Batch 400. loss: 1.654351 [ 51200/ 60000]
Batch 410. loss: 1.697325 [ 52480/ 60000]
Batch 420. loss: 1.623231 [ 53760/ 60000]
Batch 430. loss: 1.697570 [ 55040/ 60000]
Batch 440. loss: 1.696091 [ 56320/ 60000]
Batch 450. loss: 1.621778 [ 57600/ 60000]
Batch 460. loss: 1.653483 [ 58880/ 60000]
Test Error:
Accuracy: 77.0%, Avg loss: 1.689373
Epoch 14
--------------------------------------------------
Batch 0. loss: 1.632530 [ 0/ 60000]
Batch 10. loss: 1.616399 [ 1280/ 60000]
Batch 20. loss: 1.712038 [ 2560/ 60000]
Batch 30. loss: 1.709590 [ 3840/ 60000]
Batch 40. loss: 1.706367 [ 5120/ 60000]
Batch 50. loss: 1.649556 [ 6400/ 60000]
Batch 60. loss: 1.668812 [ 7680/ 60000]
Batch 70. loss: 1.621241 [ 8960/ 60000]
Batch 80. loss: 1.643053 [ 10240/ 60000]
Batch 90. loss: 1.638181 [ 11520/ 60000]
Batch 100. loss: 1.713397 [ 12800/ 60000]
Batch 110. loss: 1.705060 [ 14080/ 60000]
Batch 120. loss: 1.636117 [ 15360/ 60000]
Batch 130. loss: 1.701399 [ 16640/ 60000]
Batch 140. loss: 1.692304 [ 17920/ 60000]
Batch 150. loss: 1.685835 [ 19200/ 60000]
Batch 160. loss: 1.611598 [ 20480/ 60000]
Batch 170. loss: 1.673852 [ 21760/ 60000]
Batch 180. loss: 1.735155 [ 23040/ 60000]
Batch 190. loss: 1.661655 [ 24320/ 60000]
Batch 200. loss: 1.668115 [ 25600/ 60000]
Batch 210. loss: 1.631784 [ 26880/ 60000]
Batch 220. loss: 1.688543 [ 28160/ 60000]
Batch 230. loss: 1.662343 [ 29440/ 60000]
Batch 240. loss: 1.688212 [ 30720/ 60000]
Batch 250. loss: 1.652269 [ 32000/ 60000]
Batch 260. loss: 1.702874 [ 33280/ 60000]
Batch 270. loss: 1.650813 [ 34560/ 60000]
Batch 280. loss: 1.673688 [ 35840/ 60000]
Batch 290. loss: 1.695772 [ 37120/ 60000]
Batch 300. loss: 1.630731 [ 38400/ 60000]
Batch 310. loss: 1.687327 [ 39680/ 60000]
Batch 320. loss: 1.623506 [ 40960/ 60000]
Batch 330. loss: 1.770018 [ 42240/ 60000]
Batch 340. loss: 1.637722 [ 43520/ 60000]
Batch 350. loss: 1.634152 [ 44800/ 60000]
Batch 360. loss: 1.709512 [ 46080/ 60000]
Batch 370. loss: 1.686936 [ 47360/ 60000]
Batch 380. loss: 1.672599 [ 48640/ 60000]
Batch 390. loss: 1.647992 [ 49920/ 60000]
Batch 400. loss: 1.644328 [ 51200/ 60000]
Batch 410. loss: 1.657962 [ 52480/ 60000]
Batch 420. loss: 1.668782 [ 53760/ 60000]
Batch 430. loss: 1.692497 [ 55040/ 60000]
Batch 440. loss: 1.702846 [ 56320/ 60000]
Batch 450. loss: 1.625348 [ 57600/ 60000]
Batch 460. loss: 1.698667 [ 58880/ 60000]
Test Error:
Accuracy: 78.3%, Avg loss: 1.676277
Epoch 15
--------------------------------------------------
Batch 0. loss: 1.664901 [ 0/ 60000]
Batch 10. loss: 1.701841 [ 1280/ 60000]
Batch 20. loss: 1.676354 [ 2560/ 60000]
Batch 30. loss: 1.657342 [ 3840/ 60000]
Batch 40. loss: 1.655620 [ 5120/ 60000]
Batch 50. loss: 1.655718 [ 6400/ 60000]
Batch 60. loss: 1.657062 [ 7680/ 60000]
Batch 70. loss: 1.685076 [ 8960/ 60000]
Batch 80. loss: 1.746663 [ 10240/ 60000]
Batch 90. loss: 1.661860 [ 11520/ 60000]
Batch 100. loss: 1.668452 [ 12800/ 60000]
Batch 110. loss: 1.722243 [ 14080/ 60000]
Batch 120. loss: 1.641331 [ 15360/ 60000]
Batch 130. loss: 1.635728 [ 16640/ 60000]
Batch 140. loss: 1.630090 [ 17920/ 60000]
Batch 150. loss: 1.711605 [ 19200/ 60000]
Batch 160. loss: 1.714485 [ 20480/ 60000]
Batch 170. loss: 1.626578 [ 21760/ 60000]
Batch 180. loss: 1.653123 [ 23040/ 60000]
Batch 190. loss: 1.651625 [ 24320/ 60000]
Batch 200. loss: 1.750498 [ 25600/ 60000]
Batch 210. loss: 1.650341 [ 26880/ 60000]
Batch 220. loss: 1.659371 [ 28160/ 60000]
Batch 230. loss: 1.669002 [ 29440/ 60000]
Batch 240. loss: 1.732485 [ 30720/ 60000]
Batch 250. loss: 1.691205 [ 32000/ 60000]
Batch 260. loss: 1.672837 [ 33280/ 60000]
Batch 270. loss: 1.718180 [ 34560/ 60000]
Batch 280. loss: 1.622942 [ 35840/ 60000]
Batch 290. loss: 1.724783 [ 37120/ 60000]
Batch 300. loss: 1.620373 [ 38400/ 60000]
Batch 310. loss: 1.688071 [ 39680/ 60000]
Batch 320. loss: 1.681583 [ 40960/ 60000]
Batch 330. loss: 1.672207 [ 42240/ 60000]
Batch 340. loss: 1.663266 [ 43520/ 60000]
Batch 350. loss: 1.701746 [ 44800/ 60000]
Batch 360. loss: 1.599636 [ 46080/ 60000]
Batch 370. loss: 1.711632 [ 47360/ 60000]
Batch 380. loss: 1.653280 [ 48640/ 60000]
Batch 390. loss: 1.711361 [ 49920/ 60000]
Batch 400. loss: 1.647959 [ 51200/ 60000]
Batch 410. loss: 1.628037 [ 52480/ 60000]
Batch 420. loss: 1.651866 [ 53760/ 60000]
Batch 430. loss: 1.677957 [ 55040/ 60000]
Batch 440. loss: 1.718335 [ 56320/ 60000]
Batch 450. loss: 1.718868 [ 57600/ 60000]
Batch 460. loss: 1.643672 [ 58880/ 60000]
Test Error:
Accuracy: 78.6%, Avg loss: 1.674368
Epoch 16
--------------------------------------------------
Batch 0. loss: 1.624458 [ 0/ 60000]
Batch 10. loss: 1.677943 [ 1280/ 60000]
Batch 20. loss: 1.711649 [ 2560/ 60000]
Batch 30. loss: 1.614867 [ 3840/ 60000]
Batch 40. loss: 1.667185 [ 5120/ 60000]
Batch 50. loss: 1.664222 [ 6400/ 60000]
Batch 60. loss: 1.686274 [ 7680/ 60000]
Batch 70. loss: 1.686954 [ 8960/ 60000]
Batch 80. loss: 1.663700 [ 10240/ 60000]
Batch 90. loss: 1.691346 [ 11520/ 60000]
Batch 100. loss: 1.644355 [ 12800/ 60000]
Batch 110. loss: 1.614656 [ 14080/ 60000]
Batch 120. loss: 1.671634 [ 15360/ 60000]
Batch 130. loss: 1.678077 [ 16640/ 60000]
Batch 140. loss: 1.646560 [ 17920/ 60000]
Batch 150. loss: 1.673964 [ 19200/ 60000]
Batch 160. loss: 1.689755 [ 20480/ 60000]
Batch 170. loss: 1.691837 [ 21760/ 60000]
Batch 180. loss: 1.628591 [ 23040/ 60000]
Batch 190. loss: 1.672112 [ 24320/ 60000]
Batch 200. loss: 1.614299 [ 25600/ 60000]
Batch 210. loss: 1.670374 [ 26880/ 60000]
Batch 220. loss: 1.681906 [ 28160/ 60000]
Batch 230. loss: 1.588446 [ 29440/ 60000]
Batch 240. loss: 1.594237 [ 30720/ 60000]
Batch 250. loss: 1.649171 [ 32000/ 60000]
Batch 260. loss: 1.651209 [ 33280/ 60000]
Batch 270. loss: 1.643035 [ 34560/ 60000]
Batch 280. loss: 1.753914 [ 35840/ 60000]
Batch 290. loss: 1.657699 [ 37120/ 60000]
Batch 300. loss: 1.694505 [ 38400/ 60000]
Batch 310. loss: 1.693637 [ 39680/ 60000]
Batch 320. loss: 1.705674 [ 40960/ 60000]
Batch 330. loss: 1.635377 [ 42240/ 60000]
Batch 340. loss: 1.721109 [ 43520/ 60000]
Batch 350. loss: 1.642339 [ 44800/ 60000]
Batch 360. loss: 1.666360 [ 46080/ 60000]
Batch 370. loss: 1.656376 [ 47360/ 60000]
Batch 380. loss: 1.620859 [ 48640/ 60000]
Batch 390. loss: 1.702394 [ 49920/ 60000]
Batch 400. loss: 1.629707 [ 51200/ 60000]
Batch 410. loss: 1.642450 [ 52480/ 60000]
Batch 420. loss: 1.681865 [ 53760/ 60000]
Batch 430. loss: 1.745726 [ 55040/ 60000]
Batch 440. loss: 1.668557 [ 56320/ 60000]
Batch 450. loss: 1.668554 [ 57600/ 60000]
Batch 460. loss: 1.643021 [ 58880/ 60000]
Test Error:
Accuracy: 79.2%, Avg loss: 1.667720
Epoch 17
--------------------------------------------------
Batch 0. loss: 1.636082 [ 0/ 60000]
Batch 10. loss: 1.723198 [ 1280/ 60000]
Batch 20. loss: 1.695816 [ 2560/ 60000]
Batch 30. loss: 1.679601 [ 3840/ 60000]
Batch 40. loss: 1.604998 [ 5120/ 60000]
Batch 50. loss: 1.661094 [ 6400/ 60000]
Batch 60. loss: 1.653441 [ 7680/ 60000]
Batch 70. loss: 1.687536 [ 8960/ 60000]
Batch 80. loss: 1.684408 [ 10240/ 60000]
Batch 90. loss: 1.725028 [ 11520/ 60000]
Batch 100. loss: 1.663960 [ 12800/ 60000]
Batch 110. loss: 1.659281 [ 14080/ 60000]
Batch 120. loss: 1.664851 [ 15360/ 60000]
Batch 130. loss: 1.701382 [ 16640/ 60000]
Batch 140. loss: 1.618167 [ 17920/ 60000]
Batch 150. loss: 1.657383 [ 19200/ 60000]
Batch 160. loss: 1.639882 [ 20480/ 60000]
Batch 170. loss: 1.647733 [ 21760/ 60000]
Batch 180. loss: 1.652501 [ 23040/ 60000]
Batch 190. loss: 1.627774 [ 24320/ 60000]
Batch 200. loss: 1.718318 [ 25600/ 60000]
Batch 210. loss: 1.616095 [ 26880/ 60000]
Batch 220. loss: 1.665281 [ 28160/ 60000]
Batch 230. loss: 1.634650 [ 29440/ 60000]
Batch 240. loss: 1.648004 [ 30720/ 60000]
Batch 250. loss: 1.681808 [ 32000/ 60000]
Batch 260. loss: 1.617280 [ 33280/ 60000]
Batch 270. loss: 1.640138 [ 34560/ 60000]
Batch 280. loss: 1.569118 [ 35840/ 60000]
Batch 290. loss: 1.711458 [ 37120/ 60000]
Batch 300. loss: 1.660310 [ 38400/ 60000]
Batch 310. loss: 1.693370 [ 39680/ 60000]
Batch 320. loss: 1.683659 [ 40960/ 60000]
Batch 330. loss: 1.644878 [ 42240/ 60000]
Batch 340. loss: 1.677138 [ 43520/ 60000]
Batch 350. loss: 1.731505 [ 44800/ 60000]
Batch 360. loss: 1.751157 [ 46080/ 60000]
Batch 370. loss: 1.689741 [ 47360/ 60000]
Batch 380. loss: 1.645559 [ 48640/ 60000]
Batch 390. loss: 1.669362 [ 49920/ 60000]
Batch 400. loss: 1.645362 [ 51200/ 60000]
Batch 410. loss: 1.676270 [ 52480/ 60000]
Batch 420. loss: 1.678870 [ 53760/ 60000]
Batch 430. loss: 1.656444 [ 55040/ 60000]
Batch 440. loss: 1.689824 [ 56320/ 60000]
Batch 450. loss: 1.684317 [ 57600/ 60000]
Batch 460. loss: 1.740516 [ 58880/ 60000]
Test Error:
Accuracy: 79.3%, Avg loss: 1.665064
Epoch 18
--------------------------------------------------
Batch 0. loss: 1.672750 [ 0/ 60000]
Batch 10. loss: 1.616143 [ 1280/ 60000]
Batch 20. loss: 1.616870 [ 2560/ 60000]
Batch 30. loss: 1.674589 [ 3840/ 60000]
Batch 40. loss: 1.676196 [ 5120/ 60000]
Batch 50. loss: 1.580755 [ 6400/ 60000]
Batch 60. loss: 1.623082 [ 7680/ 60000]
Batch 70. loss: 1.612684 [ 8960/ 60000]
Batch 80. loss: 1.634772 [ 10240/ 60000]
Batch 90. loss: 1.689004 [ 11520/ 60000]
Batch 100. loss: 1.678268 [ 12800/ 60000]
Batch 110. loss: 1.633131 [ 14080/ 60000]
Batch 120. loss: 1.719700 [ 15360/ 60000]
Batch 130. loss: 1.640661 [ 16640/ 60000]
Batch 140. loss: 1.655314 [ 17920/ 60000]
Batch 150. loss: 1.657407 [ 19200/ 60000]
Batch 160. loss: 1.671515 [ 20480/ 60000]
Batch 170. loss: 1.632832 [ 21760/ 60000]
Batch 180. loss: 1.716260 [ 23040/ 60000]
Batch 190. loss: 1.665932 [ 24320/ 60000]
Batch 200. loss: 1.619561 [ 25600/ 60000]
Batch 210. loss: 1.619296 [ 26880/ 60000]
Batch 220. loss: 1.671653 [ 28160/ 60000]
Batch 230. loss: 1.670162 [ 29440/ 60000]
Batch 240. loss: 1.624759 [ 30720/ 60000]
Batch 250. loss: 1.603436 [ 32000/ 60000]
Batch 260. loss: 1.668014 [ 33280/ 60000]
Batch 270. loss: 1.590173 [ 34560/ 60000]
Batch 280. loss: 1.688915 [ 35840/ 60000]
Batch 290. loss: 1.702106 [ 37120/ 60000]
Batch 300. loss: 1.631744 [ 38400/ 60000]
Batch 310. loss: 1.664876 [ 39680/ 60000]
Batch 320. loss: 1.682545 [ 40960/ 60000]
Batch 330. loss: 1.655122 [ 42240/ 60000]
Batch 340. loss: 1.685448 [ 43520/ 60000]
Batch 350. loss: 1.744513 [ 44800/ 60000]
Batch 360. loss: 1.651361 [ 46080/ 60000]
Batch 370. loss: 1.594622 [ 47360/ 60000]
Batch 380. loss: 1.588235 [ 48640/ 60000]
Batch 390. loss: 1.667335 [ 49920/ 60000]
Batch 400. loss: 1.649515 [ 51200/ 60000]
Batch 410. loss: 1.689015 [ 52480/ 60000]
Batch 420. loss: 1.668849 [ 53760/ 60000]
Batch 430. loss: 1.644798 [ 55040/ 60000]
Batch 440. loss: 1.686867 [ 56320/ 60000]
Batch 450. loss: 1.677993 [ 57600/ 60000]
Batch 460. loss: 1.699393 [ 58880/ 60000]
Test Error:
Accuracy: 79.5%, Avg loss: 1.664066
Epoch 19
--------------------------------------------------
Batch 0. loss: 1.631255 [ 0/ 60000]
Batch 10. loss: 1.677194 [ 1280/ 60000]
Batch 20. loss: 1.595006 [ 2560/ 60000]
Batch 30. loss: 1.737708 [ 3840/ 60000]
Batch 40. loss: 1.685162 [ 5120/ 60000]
Batch 50. loss: 1.736403 [ 6400/ 60000]
Batch 60. loss: 1.649241 [ 7680/ 60000]
Batch 70. loss: 1.627562 [ 8960/ 60000]
Batch 80. loss: 1.655631 [ 10240/ 60000]
Batch 90. loss: 1.592850 [ 11520/ 60000]
Batch 100. loss: 1.685490 [ 12800/ 60000]
Batch 110. loss: 1.664461 [ 14080/ 60000]
Batch 120. loss: 1.653934 [ 15360/ 60000]
Batch 130. loss: 1.649640 [ 16640/ 60000]
Batch 140. loss: 1.679223 [ 17920/ 60000]
Batch 150. loss: 1.643877 [ 19200/ 60000]
Batch 160. loss: 1.594130 [ 20480/ 60000]
Batch 170. loss: 1.660260 [ 21760/ 60000]
Batch 180. loss: 1.646790 [ 23040/ 60000]
Batch 190. loss: 1.629479 [ 24320/ 60000]
Batch 200. loss: 1.638071 [ 25600/ 60000]
Batch 210. loss: 1.675762 [ 26880/ 60000]
Batch 220. loss: 1.679582 [ 28160/ 60000]
Batch 230. loss: 1.641714 [ 29440/ 60000]
Batch 240. loss: 1.629803 [ 30720/ 60000]
Batch 250. loss: 1.657228 [ 32000/ 60000]
Batch 260. loss: 1.667147 [ 33280/ 60000]
Batch 270. loss: 1.671849 [ 34560/ 60000]
Batch 280. loss: 1.633730 [ 35840/ 60000]
Batch 290. loss: 1.610314 [ 37120/ 60000]
Batch 300. loss: 1.688041 [ 38400/ 60000]
Batch 310. loss: 1.661769 [ 39680/ 60000]
Batch 320. loss: 1.669407 [ 40960/ 60000]
Batch 330. loss: 1.689061 [ 42240/ 60000]
Batch 340. loss: 1.685804 [ 43520/ 60000]
Batch 350. loss: 1.632386 [ 44800/ 60000]
Batch 360. loss: 1.674499 [ 46080/ 60000]
Batch 370. loss: 1.691047 [ 47360/ 60000]
Batch 380. loss: 1.684431 [ 48640/ 60000]
Batch 390. loss: 1.665209 [ 49920/ 60000]
Batch 400. loss: 1.657476 [ 51200/ 60000]
Batch 410. loss: 1.681918 [ 52480/ 60000]
Batch 420. loss: 1.699171 [ 53760/ 60000]
Batch 430. loss: 1.636443 [ 55040/ 60000]
Batch 440. loss: 1.690414 [ 56320/ 60000]
Batch 450. loss: 1.688246 [ 57600/ 60000]
Batch 460. loss: 1.596285 [ 58880/ 60000]
Test Error:
Accuracy: 80.4%, Avg loss: 1.655477
Epoch 20
--------------------------------------------------
Batch 0. loss: 1.670525 [ 0/ 60000]
Batch 10. loss: 1.608151 [ 1280/ 60000]
Batch 20. loss: 1.674564 [ 2560/ 60000]
Batch 30. loss: 1.682564 [ 3840/ 60000]
Batch 40. loss: 1.610458 [ 5120/ 60000]
Batch 50. loss: 1.693478 [ 6400/ 60000]
Batch 60. loss: 1.663251 [ 7680/ 60000]
Batch 70. loss: 1.664705 [ 8960/ 60000]
Batch 80. loss: 1.600828 [ 10240/ 60000]
Batch 90. loss: 1.658452 [ 11520/ 60000]
Batch 100. loss: 1.639223 [ 12800/ 60000]
Batch 110. loss: 1.646829 [ 14080/ 60000]
Batch 120. loss: 1.622843 [ 15360/ 60000]
Batch 130. loss: 1.613086 [ 16640/ 60000]
Batch 140. loss: 1.621736 [ 17920/ 60000]
Batch 150. loss: 1.642027 [ 19200/ 60000]
Batch 160. loss: 1.601778 [ 20480/ 60000]
Batch 170. loss: 1.548283 [ 21760/ 60000]
Batch 180. loss: 1.553374 [ 23040/ 60000]
Batch 190. loss: 1.613737 [ 24320/ 60000]
Batch 200. loss: 1.597138 [ 25600/ 60000]
Batch 210. loss: 1.571841 [ 26880/ 60000]
Batch 220. loss: 1.557056 [ 28160/ 60000]
Batch 240. loss: 1.588184 [ 30720/ 60000]
Batch 250. loss: 1.580126 [ 32000/ 60000]
Batch 260. loss: 1.622456 [ 33280/ 60000]
Batch 270. loss: 1.608391 [ 34560/ 60000]
Batch 280. loss: 1.609132 [ 35840/ 60000]
Batch 290. loss: 1.623026 [ 37120/ 60000]
Batch 300. loss: 1.604941 [ 38400/ 60000]
Batch 310. loss: 1.548233 [ 39680/ 60000]
Batch 320. loss: 1.537312 [ 40960/ 60000]
Batch 330. loss: 1.602296 [ 42240/ 60000]
Batch 340. loss: 1.562597 [ 43520/ 60000]
Batch 350. loss: 1.607578 [ 44800/ 60000]
Batch 360. loss: 1.628011 [ 46080/ 60000]
Batch 370. loss: 1.591235 [ 47360/ 60000]
Batch 380. loss: 1.593891 [ 48640/ 60000]
Batch 390. loss: 1.562588 [ 49920/ 60000]
Batch 400. loss: 1.533551 [ 51200/ 60000]
Batch 410. loss: 1.583535 [ 52480/ 60000]
Batch 420. loss: 1.599489 [ 53760/ 60000]
Batch 430. loss: 1.596216 [ 55040/ 60000]
Batch 440. loss: 1.606482 [ 56320/ 60000]
Batch 450. loss: 1.577856 [ 57600/ 60000]
Batch 460. loss: 1.661843 [ 58880/ 60000]
Test Error:
Accuracy: 86.2%, Avg loss: 1.600575
Done!
Saved PyTorch Model State to model.pth