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re-ran the tests

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ION606
2025-04-21 22:34:51 -04:00
parent 23899c703f
commit ebc64d766f
95 changed files with 2446 additions and 74 deletions
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Project/on_GPU/analysis_results.csv
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seed,optimizer,augmentation,test_acc,robustness
42,sgd,none,0.7017,"{'0.1': 0.6874, '0.2': 0.6539, '0.3': 0.573}"
42,sgd,standard,0.6983,"{'0.1': 0.685, '0.2': 0.6393, '0.3': 0.5324}"
42,sgd,aggressive,0.6529,"{'0.1': 0.6441, '0.2': 0.5905, '0.3': 0.5073}"
42,adam,none,0.5754,"{'0.1': 0.5688, '0.2': 0.5225, '0.3': 0.461}"
42,adam,standard,0.5012,"{'0.1': 0.5008, '0.2': 0.4696, '0.3': 0.3933}"
42,adam,aggressive,0.4534,"{'0.1': 0.443, '0.2': 0.4074, '0.3': 0.3669}"
123,sgd,none,0.7018,"{'0.1': 0.6907, '0.2': 0.6513, '0.3': 0.5808}"
123,sgd,standard,0.6987,"{'0.1': 0.688, '0.2': 0.6378, '0.3': 0.5488}"
123,sgd,aggressive,0.6736,"{'0.1': 0.6591, '0.2': 0.6077, '0.3': 0.5265}"
123,adam,none,0.5414,"{'0.1': 0.5207, '0.2': 0.4721, '0.3': 0.3951}"
123,adam,standard,0.4439,"{'0.1': 0.4509, '0.2': 0.4256, '0.3': 0.3567}"
123,adam,aggressive,0.4519,"{'0.1': 0.4502, '0.2': 0.4266, '0.3': 0.3584}"
999,sgd,none,0.6778,"{'0.1': 0.669, '0.2': 0.6288, '0.3': 0.5506}"
999,sgd,standard,0.6961,"{'0.1': 0.6862, '0.2': 0.6491, '0.3': 0.5655}"
999,sgd,aggressive,0.6623,"{'0.1': 0.6504, '0.2': 0.5934, '0.3': 0.5163}"
999,adam,none,0.5477,"{'0.1': 0.5394, '0.2': 0.4983, '0.3': 0.4188}"
999,adam,standard,0.4508,"{'0.1': 0.4455, '0.2': 0.3987, '0.3': 0.308}"
999,adam,aggressive,0.4209,"{'0.1': 0.4268, '0.2': 0.4071, '0.3': 0.3368}"
1 seed optimizer augmentation test_acc robustness
2 42 sgd none 0.7017 {'0.1': 0.6874, '0.2': 0.6539, '0.3': 0.573}
3 42 sgd standard 0.6983 {'0.1': 0.685, '0.2': 0.6393, '0.3': 0.5324}
4 42 sgd aggressive 0.6529 {'0.1': 0.6441, '0.2': 0.5905, '0.3': 0.5073}
5 42 adam none 0.5754 {'0.1': 0.5688, '0.2': 0.5225, '0.3': 0.461}
6 42 adam standard 0.5012 {'0.1': 0.5008, '0.2': 0.4696, '0.3': 0.3933}
7 42 adam aggressive 0.4534 {'0.1': 0.443, '0.2': 0.4074, '0.3': 0.3669}
8 123 sgd none 0.7018 {'0.1': 0.6907, '0.2': 0.6513, '0.3': 0.5808}
9 123 sgd standard 0.6987 {'0.1': 0.688, '0.2': 0.6378, '0.3': 0.5488}
10 123 sgd aggressive 0.6736 {'0.1': 0.6591, '0.2': 0.6077, '0.3': 0.5265}
11 123 adam none 0.5414 {'0.1': 0.5207, '0.2': 0.4721, '0.3': 0.3951}
12 123 adam standard 0.4439 {'0.1': 0.4509, '0.2': 0.4256, '0.3': 0.3567}
13 123 adam aggressive 0.4519 {'0.1': 0.4502, '0.2': 0.4266, '0.3': 0.3584}
14 999 sgd none 0.6778 {'0.1': 0.669, '0.2': 0.6288, '0.3': 0.5506}
15 999 sgd standard 0.6961 {'0.1': 0.6862, '0.2': 0.6491, '0.3': 0.5655}
16 999 sgd aggressive 0.6623 {'0.1': 0.6504, '0.2': 0.5934, '0.3': 0.5163}
17 999 adam none 0.5477 {'0.1': 0.5394, '0.2': 0.4983, '0.3': 0.4188}
18 999 adam standard 0.4508 {'0.1': 0.4455, '0.2': 0.3987, '0.3': 0.308}
19 999 adam aggressive 0.4209 {'0.1': 0.4268, '0.2': 0.4071, '0.3': 0.3368}
Project/on_GPU/analytics/history_adam_aggressive_123.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,2.021981541175842,0.25682,1.7806077911376954,0.3374
2,1.7999388361358644,0.33548,1.61310339717865,0.4133
3,1.7349447472763062,0.3581,1.5748741884231567,0.4205
4,1.7071615340805053,0.36902,1.585918094444275,0.426
5,1.6942062984466553,0.37512,1.5335152185440064,0.4365
6,1.682510565185547,0.38064,1.5587552444458008,0.4198
7,1.6737361584091186,0.38374,1.463624397468567,0.4576
8,1.6662311582946778,0.3874,1.542683459854126,0.4461
9,1.6689811365509033,0.38424,1.4910095794677733,0.4494
10,1.6586080972290038,0.39098,1.4566748039245605,0.4718
11,1.6606470708847045,0.39202,1.45227852268219,0.4709
12,1.6646523748016357,0.39152,1.4916118307113648,0.4603
13,1.6484171169281006,0.39868,1.5345939838409424,0.4381
14,1.6551834521865845,0.39018,1.440371674346924,0.4754
15,1.653093519821167,0.39436,1.465016110420227,0.4632
16,1.6464548859024049,0.39566,1.4275858160018922,0.4774
17,1.6686206332397462,0.39034,1.4911364223480224,0.4495
18,1.6486382946395874,0.39726,1.489304538154602,0.4583
19,1.6871330679321288,0.38462,1.4915159872055053,0.4529
20,1.6607746768188476,0.39282,1.491070439338684,0.4519
1 epoch train_loss train_acc test_loss test_acc
2 1 2.021981541175842 0.25682 1.7806077911376954 0.3374
3 2 1.7999388361358644 0.33548 1.61310339717865 0.4133
4 3 1.7349447472763062 0.3581 1.5748741884231567 0.4205
5 4 1.7071615340805053 0.36902 1.585918094444275 0.426
6 5 1.6942062984466553 0.37512 1.5335152185440064 0.4365
7 6 1.682510565185547 0.38064 1.5587552444458008 0.4198
8 7 1.6737361584091186 0.38374 1.463624397468567 0.4576
9 8 1.6662311582946778 0.3874 1.542683459854126 0.4461
10 9 1.6689811365509033 0.38424 1.4910095794677733 0.4494
11 10 1.6586080972290038 0.39098 1.4566748039245605 0.4718
12 11 1.6606470708847045 0.39202 1.45227852268219 0.4709
13 12 1.6646523748016357 0.39152 1.4916118307113648 0.4603
14 13 1.6484171169281006 0.39868 1.5345939838409424 0.4381
15 14 1.6551834521865845 0.39018 1.440371674346924 0.4754
16 15 1.653093519821167 0.39436 1.465016110420227 0.4632
17 16 1.6464548859024049 0.39566 1.4275858160018922 0.4774
18 17 1.6686206332397462 0.39034 1.4911364223480224 0.4495
19 18 1.6486382946395874 0.39726 1.489304538154602 0.4583
20 19 1.6871330679321288 0.38462 1.4915159872055053 0.4529
21 20 1.6607746768188476 0.39282 1.491070439338684 0.4519
Project/on_GPU/analytics/history_adam_aggressive_42.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,1.9946132025909424,0.26546,1.7465605016708374,0.342
2,1.7975156771087646,0.33534,1.6129542232513427,0.4064
3,1.7742824270248414,0.34438,1.5872959531784057,0.42
4,1.737174402770996,0.35786,1.6175920555114747,0.4113
5,1.726973815536499,0.36836,1.5620707996368408,0.4221
6,1.7160892931365967,0.3704,1.536605580329895,0.4449
7,1.696208762741089,0.37986,1.5236610635757446,0.4352
8,1.6957400606536865,0.38076,1.5052044256210326,0.4409
9,1.6930768957138063,0.38038,1.5134387523651123,0.4434
10,1.6858074627304078,0.37872,1.4595767322540283,0.4671
11,1.6876252536773682,0.38142,1.473248080444336,0.456
12,1.6892691661834718,0.38366,1.554956097793579,0.4288
13,1.6795142168426513,0.3832,1.5135724742889405,0.4422
14,1.6710495895767212,0.38514,1.632836058998108,0.4082
15,1.6752502041625976,0.3846,1.459756902885437,0.4628
16,1.6733012282562256,0.38312,1.5108640363693238,0.437
17,1.6646488619613649,0.38898,1.4822496488571166,0.4529
18,1.6782792532348634,0.38288,1.4726739952087402,0.4649
19,1.6774794401168822,0.38574,1.5311094917297363,0.4383
20,1.671811372718811,0.38212,1.5132373497009277,0.4534
1 epoch train_loss train_acc test_loss test_acc
2 1 1.9946132025909424 0.26546 1.7465605016708374 0.342
3 2 1.7975156771087646 0.33534 1.6129542232513427 0.4064
4 3 1.7742824270248414 0.34438 1.5872959531784057 0.42
5 4 1.737174402770996 0.35786 1.6175920555114747 0.4113
6 5 1.726973815536499 0.36836 1.5620707996368408 0.4221
7 6 1.7160892931365967 0.3704 1.536605580329895 0.4449
8 7 1.696208762741089 0.37986 1.5236610635757446 0.4352
9 8 1.6957400606536865 0.38076 1.5052044256210326 0.4409
10 9 1.6930768957138063 0.38038 1.5134387523651123 0.4434
11 10 1.6858074627304078 0.37872 1.4595767322540283 0.4671
12 11 1.6876252536773682 0.38142 1.473248080444336 0.456
13 12 1.6892691661834718 0.38366 1.554956097793579 0.4288
14 13 1.6795142168426513 0.3832 1.5135724742889405 0.4422
15 14 1.6710495895767212 0.38514 1.632836058998108 0.4082
16 15 1.6752502041625976 0.3846 1.459756902885437 0.4628
17 16 1.6733012282562256 0.38312 1.5108640363693238 0.437
18 17 1.6646488619613649 0.38898 1.4822496488571166 0.4529
19 18 1.6782792532348634 0.38288 1.4726739952087402 0.4649
20 19 1.6774794401168822 0.38574 1.5311094917297363 0.4383
21 20 1.671811372718811 0.38212 1.5132373497009277 0.4534
Project/on_GPU/analytics/history_adam_aggressive_999.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,2.0723634432601927,0.23022,1.876600818824768,0.3199
2,1.9161218788909913,0.29064,1.731086205482483,0.3617
3,1.8448259813690187,0.3195,1.6460390392303468,0.3999
4,1.8053451504135132,0.33482,1.5930611736297609,0.4099
5,1.7892016728973388,0.34036,1.601932553291321,0.4121
6,1.7877225128936767,0.33872,1.9846259342193604,0.3256
7,1.7722377728652954,0.34716,1.5737567417144775,0.4181
8,1.7613219201278687,0.34792,1.6388108669281005,0.3857
9,1.7486019417953491,0.35528,1.6210294721603393,0.3986
10,1.7620320590209961,0.34984,1.6138639379501343,0.3982
11,1.7493324411010742,0.35366,1.592185188484192,0.4078
12,1.745043455810547,0.35408,1.6113332284927369,0.4106
13,1.7523625258636475,0.3513,1.5707368755340576,0.4204
14,1.7393008434677124,0.3585,1.5894966974258422,0.4125
15,1.7469453559112549,0.35858,1.6415567993164062,0.3921
16,1.7383291018295288,0.35804,1.6457257890701293,0.3887
17,1.7539940619659424,0.35182,1.649910280227661,0.3902
18,1.7417138710403441,0.35358,1.6048244901657105,0.4027
19,1.7405921878814696,0.3585,1.540078621673584,0.4284
20,1.7527848522567748,0.3491,1.5630715839385987,0.4209
1 epoch train_loss train_acc test_loss test_acc
2 1 2.0723634432601927 0.23022 1.876600818824768 0.3199
3 2 1.9161218788909913 0.29064 1.731086205482483 0.3617
4 3 1.8448259813690187 0.3195 1.6460390392303468 0.3999
5 4 1.8053451504135132 0.33482 1.5930611736297609 0.4099
6 5 1.7892016728973388 0.34036 1.601932553291321 0.4121
7 6 1.7877225128936767 0.33872 1.9846259342193604 0.3256
8 7 1.7722377728652954 0.34716 1.5737567417144775 0.4181
9 8 1.7613219201278687 0.34792 1.6388108669281005 0.3857
10 9 1.7486019417953491 0.35528 1.6210294721603393 0.3986
11 10 1.7620320590209961 0.34984 1.6138639379501343 0.3982
12 11 1.7493324411010742 0.35366 1.592185188484192 0.4078
13 12 1.745043455810547 0.35408 1.6113332284927369 0.4106
14 13 1.7523625258636475 0.3513 1.5707368755340576 0.4204
15 14 1.7393008434677124 0.3585 1.5894966974258422 0.4125
16 15 1.7469453559112549 0.35858 1.6415567993164062 0.3921
17 16 1.7383291018295288 0.35804 1.6457257890701293 0.3887
18 17 1.7539940619659424 0.35182 1.649910280227661 0.3902
19 18 1.7417138710403441 0.35358 1.6048244901657105 0.4027
20 19 1.7405921878814696 0.3585 1.540078621673584 0.4284
21 20 1.7527848522567748 0.3491 1.5630715839385987 0.4209
Project/on_GPU/analytics/history_adam_none_123.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,1.7930121985626222,0.34364,1.461875290298462,0.4587
2,1.5388130508041382,0.43978,1.442550922393799,0.4631
3,1.4962808783721924,0.45782,1.4238734016418457,0.4876
4,1.4607513367462157,0.4701,1.347493274497986,0.5141
5,1.4432476579666138,0.47944,1.3734356439590454,0.5123
6,1.421063133468628,0.48706,1.3214570888519288,0.529
7,1.4215787218475342,0.48914,1.3083847173690797,0.5334
8,1.4135805054092407,0.48904,1.3078678575515748,0.5363
9,1.4087683379745484,0.49214,1.3223941360473632,0.5187
10,1.4120303262710572,0.49486,1.2843070182800294,0.5335
11,1.3871485186767578,0.50006,1.2921210390090943,0.5329
12,1.3999624375915527,0.49512,1.2802863786697387,0.5462
13,1.3897427955627442,0.50096,1.2707655395507813,0.5448
14,1.3929189464950562,0.49866,1.280012000465393,0.5352
15,1.3815861407852172,0.50394,1.303921529006958,0.538
16,1.3858564881134032,0.50334,1.271148939704895,0.5447
17,1.3741848274230957,0.50992,1.2622444095611571,0.5518
18,1.3721859537506103,0.50712,1.250786780166626,0.5568
19,1.3785438285064697,0.50654,1.2690851692199707,0.5513
20,1.3659724238586426,0.51068,1.3006612928390502,0.5414
1 epoch train_loss train_acc test_loss test_acc
2 1 1.7930121985626222 0.34364 1.461875290298462 0.4587
3 2 1.5388130508041382 0.43978 1.442550922393799 0.4631
4 3 1.4962808783721924 0.45782 1.4238734016418457 0.4876
5 4 1.4607513367462157 0.4701 1.347493274497986 0.5141
6 5 1.4432476579666138 0.47944 1.3734356439590454 0.5123
7 6 1.421063133468628 0.48706 1.3214570888519288 0.529
8 7 1.4215787218475342 0.48914 1.3083847173690797 0.5334
9 8 1.4135805054092407 0.48904 1.3078678575515748 0.5363
10 9 1.4087683379745484 0.49214 1.3223941360473632 0.5187
11 10 1.4120303262710572 0.49486 1.2843070182800294 0.5335
12 11 1.3871485186767578 0.50006 1.2921210390090943 0.5329
13 12 1.3999624375915527 0.49512 1.2802863786697387 0.5462
14 13 1.3897427955627442 0.50096 1.2707655395507813 0.5448
15 14 1.3929189464950562 0.49866 1.280012000465393 0.5352
16 15 1.3815861407852172 0.50394 1.303921529006958 0.538
17 16 1.3858564881134032 0.50334 1.271148939704895 0.5447
18 17 1.3741848274230957 0.50992 1.2622444095611571 0.5518
19 18 1.3721859537506103 0.50712 1.250786780166626 0.5568
20 19 1.3785438285064697 0.50654 1.2690851692199707 0.5513
21 20 1.3659724238586426 0.51068 1.3006612928390502 0.5414
Project/on_GPU/analytics/history_adam_none_42.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,1.7538864451980591,0.3666,1.5667252685546875,0.4474
2,1.5012665232467652,0.4559,1.4435671327590942,0.4801
3,1.4560056861877442,0.47398,1.3615544191360474,0.511
4,1.4221073620223998,0.48824,1.344312677192688,0.5162
5,1.3943471972274781,0.49968,1.3266402479171753,0.5221
6,1.3839806178665162,0.50374,1.3004958406448364,0.5295
7,1.3604061797332763,0.51462,1.3282047555923462,0.5269
8,1.3528923289108277,0.51308,1.2727963297843934,0.5478
9,1.3496200884246825,0.51504,1.2338088079452514,0.5602
10,1.3384253984069825,0.51992,1.2602990411758423,0.5414
11,1.3298793702697753,0.52298,1.2460808729171753,0.5535
12,1.3380408303070068,0.52314,1.201425923538208,0.5783
13,1.3282683892822265,0.52384,1.2300636964797973,0.5622
14,1.3240932238769532,0.5305,1.2329102926254272,0.5585
15,1.3172099641799926,0.53152,1.2063555044174195,0.5775
16,1.3192347250366212,0.53014,1.2183320951461791,0.5694
17,1.3198897607040405,0.5286,1.2268210130691528,0.5755
18,1.3245510208892821,0.52778,1.248089506149292,0.5589
19,1.3320170434570313,0.5294,1.2209409841537475,0.5715
20,1.3129964478302,0.53108,1.1870027980804443,0.5754
1 epoch train_loss train_acc test_loss test_acc
2 1 1.7538864451980591 0.3666 1.5667252685546875 0.4474
3 2 1.5012665232467652 0.4559 1.4435671327590942 0.4801
4 3 1.4560056861877442 0.47398 1.3615544191360474 0.511
5 4 1.4221073620223998 0.48824 1.344312677192688 0.5162
6 5 1.3943471972274781 0.49968 1.3266402479171753 0.5221
7 6 1.3839806178665162 0.50374 1.3004958406448364 0.5295
8 7 1.3604061797332763 0.51462 1.3282047555923462 0.5269
9 8 1.3528923289108277 0.51308 1.2727963297843934 0.5478
10 9 1.3496200884246825 0.51504 1.2338088079452514 0.5602
11 10 1.3384253984069825 0.51992 1.2602990411758423 0.5414
12 11 1.3298793702697753 0.52298 1.2460808729171753 0.5535
13 12 1.3380408303070068 0.52314 1.201425923538208 0.5783
14 13 1.3282683892822265 0.52384 1.2300636964797973 0.5622
15 14 1.3240932238769532 0.5305 1.2329102926254272 0.5585
16 15 1.3172099641799926 0.53152 1.2063555044174195 0.5775
17 16 1.3192347250366212 0.53014 1.2183320951461791 0.5694
18 17 1.3198897607040405 0.5286 1.2268210130691528 0.5755
19 18 1.3245510208892821 0.52778 1.248089506149292 0.5589
20 19 1.3320170434570313 0.5294 1.2209409841537475 0.5715
21 20 1.3129964478302 0.53108 1.1870027980804443 0.5754
Project/on_GPU/analytics/history_adam_none_999.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,1.7632377227020264,0.35308,1.5758346817016602,0.4299
2,1.524346548271179,0.4486,1.4102591985702515,0.4979
3,1.456631953201294,0.47108,1.3265910715103149,0.5188
4,1.4304079055023193,0.48082,1.377274009513855,0.5
5,1.4108501930999755,0.49066,1.4178906629562378,0.5087
6,1.4031479808807372,0.4983,1.309526050758362,0.5271
7,1.383127350769043,0.50128,1.3740155362129212,0.5123
8,1.3820967692565918,0.50244,1.2505300882339478,0.5529
9,1.3669423685073852,0.51028,1.311721753692627,0.5251
10,1.3696778673553467,0.5087,1.3234023988723755,0.5277
11,1.3733588944244384,0.50774,1.2789020259857178,0.5407
12,1.3640874988174438,0.5121,1.31283944940567,0.531
13,1.3571320106887816,0.51374,1.265874310874939,0.5501
14,1.3592108781051635,0.51512,1.346185697746277,0.5302
15,1.3577870546340942,0.51416,1.2771299747467042,0.5569
16,1.3403621031570434,0.51896,1.2562333318710328,0.55
17,1.3543927292633056,0.51506,1.2568754550933838,0.5515
18,1.3482802200698853,0.51838,1.282126469898224,0.5486
19,1.3436878190994264,0.51798,1.251200986480713,0.548
20,1.3356118139648439,0.52016,1.2636010625839234,0.5477
1 epoch train_loss train_acc test_loss test_acc
2 1 1.7632377227020264 0.35308 1.5758346817016602 0.4299
3 2 1.524346548271179 0.4486 1.4102591985702515 0.4979
4 3 1.456631953201294 0.47108 1.3265910715103149 0.5188
5 4 1.4304079055023193 0.48082 1.377274009513855 0.5
6 5 1.4108501930999755 0.49066 1.4178906629562378 0.5087
7 6 1.4031479808807372 0.4983 1.309526050758362 0.5271
8 7 1.383127350769043 0.50128 1.3740155362129212 0.5123
9 8 1.3820967692565918 0.50244 1.2505300882339478 0.5529
10 9 1.3669423685073852 0.51028 1.311721753692627 0.5251
11 10 1.3696778673553467 0.5087 1.3234023988723755 0.5277
12 11 1.3733588944244384 0.50774 1.2789020259857178 0.5407
13 12 1.3640874988174438 0.5121 1.31283944940567 0.531
14 13 1.3571320106887816 0.51374 1.265874310874939 0.5501
15 14 1.3592108781051635 0.51512 1.346185697746277 0.5302
16 15 1.3577870546340942 0.51416 1.2771299747467042 0.5569
17 16 1.3403621031570434 0.51896 1.2562333318710328 0.55
18 17 1.3543927292633056 0.51506 1.2568754550933838 0.5515
19 18 1.3482802200698853 0.51838 1.282126469898224 0.5486
20 19 1.3436878190994264 0.51798 1.251200986480713 0.548
21 20 1.3356118139648439 0.52016 1.2636010625839234 0.5477
Project/on_GPU/analytics/history_adam_standard_123.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,1.9765228209686279,0.275,1.838960478782654,0.3317
2,1.7586317385482788,0.3564,1.5927722663879396,0.4192
3,1.7182956017303468,0.36878,1.6095290222167968,0.3962
4,1.6878443021011353,0.3778,1.5945830318450929,0.4209
5,1.6782778314971925,0.38232,1.4996938594818114,0.4596
6,1.6617775799560548,0.38782,1.5637247476577758,0.4273
7,1.6519146921920775,0.39274,1.4898227006912232,0.4477
8,1.6319190932846068,0.39776,1.4631493810653686,0.464
9,1.6271585168457032,0.39996,1.4658390745162964,0.4671
10,1.6192712731170655,0.40386,1.4798445970535279,0.4555
11,1.6236518589782716,0.4038,1.4518645431518555,0.4712
12,1.6256605269241333,0.39904,1.5097844490051269,0.4606
13,1.6252113864517213,0.4029,1.4985135524749755,0.4628
14,1.6405798107147216,0.40094,1.5247799369812012,0.4417
15,1.6137488632202148,0.40722,1.470830341720581,0.4691
16,1.6058656929779054,0.40896,1.4936083711624146,0.4535
17,1.609079775390625,0.4086,1.5095022733688355,0.4407
18,1.5937296617126464,0.41062,1.4561285724639892,0.4711
19,1.6145524578094483,0.40402,1.4767372095108031,0.4599
20,1.6014677686309815,0.4094,1.490078086090088,0.4439
1 epoch train_loss train_acc test_loss test_acc
2 1 1.9765228209686279 0.275 1.838960478782654 0.3317
3 2 1.7586317385482788 0.3564 1.5927722663879396 0.4192
4 3 1.7182956017303468 0.36878 1.6095290222167968 0.3962
5 4 1.6878443021011353 0.3778 1.5945830318450929 0.4209
6 5 1.6782778314971925 0.38232 1.4996938594818114 0.4596
7 6 1.6617775799560548 0.38782 1.5637247476577758 0.4273
8 7 1.6519146921920775 0.39274 1.4898227006912232 0.4477
9 8 1.6319190932846068 0.39776 1.4631493810653686 0.464
10 9 1.6271585168457032 0.39996 1.4658390745162964 0.4671
11 10 1.6192712731170655 0.40386 1.4798445970535279 0.4555
12 11 1.6236518589782716 0.4038 1.4518645431518555 0.4712
13 12 1.6256605269241333 0.39904 1.5097844490051269 0.4606
14 13 1.6252113864517213 0.4029 1.4985135524749755 0.4628
15 14 1.6405798107147216 0.40094 1.5247799369812012 0.4417
16 15 1.6137488632202148 0.40722 1.470830341720581 0.4691
17 16 1.6058656929779054 0.40896 1.4936083711624146 0.4535
18 17 1.609079775390625 0.4086 1.5095022733688355 0.4407
19 18 1.5937296617126464 0.41062 1.4561285724639892 0.4711
20 19 1.6145524578094483 0.40402 1.4767372095108031 0.4599
21 20 1.6014677686309815 0.4094 1.490078086090088 0.4439
Project/on_GPU/analytics/history_adam_standard_42.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,1.9662294528198243,0.28166,1.646554655456543,0.4059
2,1.6907201608657836,0.38096,1.4890975648880005,0.4608
3,1.630640150680542,0.40234,1.461022783470154,0.4703
4,1.5946281551361083,0.41298,1.4765422527313232,0.4582
5,1.5847036001586914,0.41944,1.463464338684082,0.4656
6,1.5700461378860473,0.42448,1.4435549175262452,0.4742
7,1.5596910428237916,0.43166,1.4010505067825318,0.4815
8,1.5500616349411012,0.4339,1.4645743618011475,0.4736
9,1.5521124801254274,0.4347,1.3910032358169555,0.4965
10,1.540557314529419,0.43936,1.3937551671981812,0.4963
11,1.542716057395935,0.4397,1.3852252645492553,0.5065
12,1.5426535359954834,0.43796,1.3814128866195678,0.4952
13,1.5383161214828491,0.43854,1.3704833930969238,0.519
14,1.535815538673401,0.43938,1.3828128046035766,0.4922
15,1.5208821871185303,0.44786,1.336184846496582,0.5174
16,1.5207045543670654,0.44292,1.3120759601593017,0.5318
17,1.5427820779800414,0.44198,1.3777759956359863,0.5101
18,1.5282205264282227,0.44214,1.3206209297180176,0.5246
19,1.5153924929046632,0.45148,1.440579479789734,0.4926
20,1.5200670809936523,0.44844,1.35802781791687,0.5012
1 epoch train_loss train_acc test_loss test_acc
2 1 1.9662294528198243 0.28166 1.646554655456543 0.4059
3 2 1.6907201608657836 0.38096 1.4890975648880005 0.4608
4 3 1.630640150680542 0.40234 1.461022783470154 0.4703
5 4 1.5946281551361083 0.41298 1.4765422527313232 0.4582
6 5 1.5847036001586914 0.41944 1.463464338684082 0.4656
7 6 1.5700461378860473 0.42448 1.4435549175262452 0.4742
8 7 1.5596910428237916 0.43166 1.4010505067825318 0.4815
9 8 1.5500616349411012 0.4339 1.4645743618011475 0.4736
10 9 1.5521124801254274 0.4347 1.3910032358169555 0.4965
11 10 1.540557314529419 0.43936 1.3937551671981812 0.4963
12 11 1.542716057395935 0.4397 1.3852252645492553 0.5065
13 12 1.5426535359954834 0.43796 1.3814128866195678 0.4952
14 13 1.5383161214828491 0.43854 1.3704833930969238 0.519
15 14 1.535815538673401 0.43938 1.3828128046035766 0.4922
16 15 1.5208821871185303 0.44786 1.336184846496582 0.5174
17 16 1.5207045543670654 0.44292 1.3120759601593017 0.5318
18 17 1.5427820779800414 0.44198 1.3777759956359863 0.5101
19 18 1.5282205264282227 0.44214 1.3206209297180176 0.5246
20 19 1.5153924929046632 0.45148 1.440579479789734 0.4926
21 20 1.5200670809936523 0.44844 1.35802781791687 0.5012
Project/on_GPU/analytics/history_adam_standard_999.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,1.9782473403930665,0.2757,1.7940137519836425,0.3604
2,1.7881652750396728,0.34256,1.6846075788497925,0.383
3,1.7298297366714477,0.36016,1.6570421657562255,0.3849
4,1.701125471496582,0.36964,1.6060110397338867,0.4051
5,1.6930271649169921,0.3764,1.5627256288528442,0.4322
6,1.6890782552337646,0.3793,1.5718454141616822,0.4155
7,1.6894171588134765,0.37854,1.5689407793045045,0.4244
8,1.6838004080963134,0.37988,1.547055793952942,0.4361
9,1.6820043857192992,0.38108,1.5525554042816163,0.4266
10,1.6630719311523436,0.38704,1.5440392353057861,0.4309
11,1.6606243139266967,0.38634,1.5547804042816162,0.4306
12,1.6556413611602783,0.39148,1.5340405586242676,0.4356
13,1.6465564861679076,0.39404,1.5331555698394776,0.4422
14,1.6496008929824828,0.39452,1.5326438642501832,0.4355
15,1.6501564659881591,0.39042,1.5048745851516723,0.4526
16,1.638251790008545,0.39798,1.5019797897338867,0.4489
17,1.6597554596710204,0.38882,1.5088586767196654,0.4484
18,1.6430353671264648,0.39304,1.6406061777114869,0.3994
19,1.6456201574325562,0.39314,1.516061517906189,0.4483
20,1.6409141896820068,0.39418,1.4997223611831665,0.4508
1 epoch train_loss train_acc test_loss test_acc
2 1 1.9782473403930665 0.2757 1.7940137519836425 0.3604
3 2 1.7881652750396728 0.34256 1.6846075788497925 0.383
4 3 1.7298297366714477 0.36016 1.6570421657562255 0.3849
5 4 1.701125471496582 0.36964 1.6060110397338867 0.4051
6 5 1.6930271649169921 0.3764 1.5627256288528442 0.4322
7 6 1.6890782552337646 0.3793 1.5718454141616822 0.4155
8 7 1.6894171588134765 0.37854 1.5689407793045045 0.4244
9 8 1.6838004080963134 0.37988 1.547055793952942 0.4361
10 9 1.6820043857192992 0.38108 1.5525554042816163 0.4266
11 10 1.6630719311523436 0.38704 1.5440392353057861 0.4309
12 11 1.6606243139266967 0.38634 1.5547804042816162 0.4306
13 12 1.6556413611602783 0.39148 1.5340405586242676 0.4356
14 13 1.6465564861679076 0.39404 1.5331555698394776 0.4422
15 14 1.6496008929824828 0.39452 1.5326438642501832 0.4355
16 15 1.6501564659881591 0.39042 1.5048745851516723 0.4526
17 16 1.638251790008545 0.39798 1.5019797897338867 0.4489
18 17 1.6597554596710204 0.38882 1.5088586767196654 0.4484
19 18 1.6430353671264648 0.39304 1.6406061777114869 0.3994
20 19 1.6456201574325562 0.39314 1.516061517906189 0.4483
21 20 1.6409141896820068 0.39418 1.4997223611831665 0.4508
Project/on_GPU/analytics/history_sgd_aggressive_123.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,2.0717957442474364,0.23638,1.8070027614593507,0.3592
2,1.7711991034317016,0.35626,1.544959555053711,0.4336
3,1.6322058293914794,0.4069,1.4367220252990722,0.4826
4,1.5630220341491698,0.43416,1.37243994140625,0.5099
5,1.4982818214797973,0.45784,1.2836783926010131,0.5423
6,1.4538921988677977,0.47784,1.2316193922042846,0.5584
7,1.4066726916503907,0.4912,1.1759659088134766,0.5824
8,1.3719631880187988,0.51076,1.150549816131592,0.5948
9,1.3426129550933839,0.51988,1.1507357816696167,0.5881
10,1.3073690589904785,0.53344,1.0885456802368163,0.6235
11,1.2872175302124023,0.54074,1.0516377550125122,0.6285
12,1.266133660888672,0.54882,1.0233188526153565,0.6413
13,1.2529394985961915,0.55518,1.0078511615753174,0.6473
14,1.2264000122833252,0.56462,1.0189788675308227,0.6436
15,1.2245289393615724,0.56466,1.0103674605369568,0.6484
16,1.208251329650879,0.56842,0.9705223019599915,0.6642
17,1.1961261875534057,0.57536,1.0117724663734435,0.645
18,1.1778298877716065,0.58256,0.9588415849685669,0.6629
19,1.1742403998947144,0.58666,0.9755858589172364,0.657
20,1.165386855278015,0.58884,0.9380706154823303,0.6736
1 epoch train_loss train_acc test_loss test_acc
2 1 2.0717957442474364 0.23638 1.8070027614593507 0.3592
3 2 1.7711991034317016 0.35626 1.544959555053711 0.4336
4 3 1.6322058293914794 0.4069 1.4367220252990722 0.4826
5 4 1.5630220341491698 0.43416 1.37243994140625 0.5099
6 5 1.4982818214797973 0.45784 1.2836783926010131 0.5423
7 6 1.4538921988677977 0.47784 1.2316193922042846 0.5584
8 7 1.4066726916503907 0.4912 1.1759659088134766 0.5824
9 8 1.3719631880187988 0.51076 1.150549816131592 0.5948
10 9 1.3426129550933839 0.51988 1.1507357816696167 0.5881
11 10 1.3073690589904785 0.53344 1.0885456802368163 0.6235
12 11 1.2872175302124023 0.54074 1.0516377550125122 0.6285
13 12 1.266133660888672 0.54882 1.0233188526153565 0.6413
14 13 1.2529394985961915 0.55518 1.0078511615753174 0.6473
15 14 1.2264000122833252 0.56462 1.0189788675308227 0.6436
16 15 1.2245289393615724 0.56466 1.0103674605369568 0.6484
17 16 1.208251329650879 0.56842 0.9705223019599915 0.6642
18 17 1.1961261875534057 0.57536 1.0117724663734435 0.645
19 18 1.1778298877716065 0.58256 0.9588415849685669 0.6629
20 19 1.1742403998947144 0.58666 0.9755858589172364 0.657
21 20 1.165386855278015 0.58884 0.9380706154823303 0.6736
Project/on_GPU/analytics/history_sgd_aggressive_42.csv
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@@ -0,0 +1,21 @@
epoch,train_loss,train_acc,test_loss,test_acc
1,2.053392539367676,0.2443,1.8277459175109863,0.3477
2,1.787647081413269,0.35238,1.5101178413391114,0.4583
3,1.646120939102173,0.40544,1.4628921775817871,0.4684
4,1.5713705833053588,0.43396,1.3796582710266114,0.5046
5,1.5172283823394774,0.45338,1.3074881475448608,0.5348
6,1.4627742120742797,0.47362,1.2615061752319336,0.5529
7,1.4181369704818725,0.49334,1.1881981817245484,0.5795
8,1.387547327079773,0.50268,1.1446026531219482,0.5967
9,1.3531704047775268,0.51462,1.1308457630157471,0.5977
10,1.328253187789917,0.52646,1.1201391205787659,0.6028
11,1.3050450761413575,0.53326,1.1036224122047424,0.6133
12,1.2839701457214356,0.54296,1.0483348583221435,0.6329
13,1.2662199767303466,0.55046,1.118672813987732,0.6011
14,1.249073985671997,0.5545,1.008135287475586,0.649
15,1.2334320105743408,0.56206,1.0220180696487426,0.6452
16,1.226570714187622,0.56562,1.0283479545593261,0.6381
17,1.215673310623169,0.56778,0.99635754737854,0.6482
18,1.2051158458709716,0.57448,0.968738715171814,0.6619
19,1.1853828730392455,0.57932,0.9603862438201904,0.6701
20,1.1799074561309815,0.5823,0.9873979913711548,0.6529
1 epoch train_loss train_acc test_loss test_acc
2 1 2.053392539367676 0.2443 1.8277459175109863 0.3477
3 2 1.787647081413269 0.35238 1.5101178413391114 0.4583
4 3 1.646120939102173 0.40544 1.4628921775817871 0.4684
5 4 1.5713705833053588 0.43396 1.3796582710266114 0.5046
6 5 1.5172283823394774 0.45338 1.3074881475448608 0.5348
7 6 1.4627742120742797 0.47362 1.2615061752319336 0.5529
8 7 1.4181369704818725 0.49334 1.1881981817245484 0.5795
9 8 1.387547327079773 0.50268 1.1446026531219482 0.5967
10 9 1.3531704047775268 0.51462 1.1308457630157471 0.5977
11 10 1.328253187789917 0.52646 1.1201391205787659 0.6028
12 11 1.3050450761413575 0.53326 1.1036224122047424 0.6133
13 12 1.2839701457214356 0.54296 1.0483348583221435 0.6329
14 13 1.2662199767303466 0.55046 1.118672813987732 0.6011
15 14 1.249073985671997 0.5545 1.008135287475586 0.649
16 15 1.2334320105743408 0.56206 1.0220180696487426 0.6452
17 16 1.226570714187622 0.56562 1.0283479545593261 0.6381
18 17 1.215673310623169 0.56778 0.99635754737854 0.6482
19 18 1.2051158458709716 0.57448 0.968738715171814 0.6619
20 19 1.1853828730392455 0.57932 0.9603862438201904 0.6701
21 20 1.1799074561309815 0.5823 0.9873979913711548 0.6529
Project/on_GPU/analytics/history_sgd_aggressive_999.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,2.0646032915878294,0.24374,1.7789719665527344,0.3856
2,1.7912192575454713,0.35524,1.4898719760894776,0.4649
3,1.6362936135864259,0.40798,1.4567605255126954,0.4622
4,1.5608094699859618,0.4355,1.400784787940979,0.4828
5,1.5062945654678346,0.45454,1.3043995948791505,0.5366
6,1.461043725013733,0.47552,1.266900797843933,0.5395
7,1.4183598426818849,0.49158,1.2215706317901611,0.5608
8,1.3873241466522217,0.50428,1.1732126100540161,0.5799
9,1.3462454842758178,0.51896,1.1159016653060914,0.6037
10,1.318895576210022,0.53132,1.0962340599060059,0.6135
11,1.2963881420516967,0.53832,1.1005984948158265,0.6157
12,1.2797832188796998,0.54426,1.0569532452583312,0.6221
13,1.2446794859695434,0.55496,1.0522931388854981,0.6303
14,1.2455195839691162,0.55828,1.0057928833007812,0.6474
15,1.2228796381378173,0.56634,0.9707541692733764,0.6583
16,1.2148502236175538,0.57112,0.9822790630340577,0.6548
17,1.1953229378509522,0.5769,0.992683217716217,0.6514
18,1.1797297177124024,0.5802,0.985902705192566,0.6521
19,1.1690457083892822,0.58446,0.951106063079834,0.6624
20,1.1595652348136902,0.59014,0.9662161799430847,0.6623
1 epoch train_loss train_acc test_loss test_acc
2 1 2.0646032915878294 0.24374 1.7789719665527344 0.3856
3 2 1.7912192575454713 0.35524 1.4898719760894776 0.4649
4 3 1.6362936135864259 0.40798 1.4567605255126954 0.4622
5 4 1.5608094699859618 0.4355 1.400784787940979 0.4828
6 5 1.5062945654678346 0.45454 1.3043995948791505 0.5366
7 6 1.461043725013733 0.47552 1.266900797843933 0.5395
8 7 1.4183598426818849 0.49158 1.2215706317901611 0.5608
9 8 1.3873241466522217 0.50428 1.1732126100540161 0.5799
10 9 1.3462454842758178 0.51896 1.1159016653060914 0.6037
11 10 1.318895576210022 0.53132 1.0962340599060059 0.6135
12 11 1.2963881420516967 0.53832 1.1005984948158265 0.6157
13 12 1.2797832188796998 0.54426 1.0569532452583312 0.6221
14 13 1.2446794859695434 0.55496 1.0522931388854981 0.6303
15 14 1.2455195839691162 0.55828 1.0057928833007812 0.6474
16 15 1.2228796381378173 0.56634 0.9707541692733764 0.6583
17 16 1.2148502236175538 0.57112 0.9822790630340577 0.6548
18 17 1.1953229378509522 0.5769 0.992683217716217 0.6514
19 18 1.1797297177124024 0.5802 0.985902705192566 0.6521
20 19 1.1690457083892822 0.58446 0.951106063079834 0.6624
21 20 1.1595652348136902 0.59014 0.9662161799430847 0.6623
Project/on_GPU/analytics/history_sgd_none_123.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,1.9311371482086181,0.2982,1.5920978937149048,0.4331
2,1.509078656387329,0.46018,1.3684404134750365,0.506
3,1.3346781539916992,0.5203,1.2729134735107421,0.5345
4,1.2469274048614503,0.55542,1.158725128364563,0.5855
5,1.1582400985717773,0.58732,1.1014516458511352,0.6146
6,1.0868776248168945,0.61344,1.043407428741455,0.6336
7,1.0187307173347473,0.64048,0.9962607810974121,0.6517
8,0.9732129728698731,0.6563,1.009974559020996,0.647
9,0.9221462124443054,0.6754,0.9498543729782104,0.6732
10,0.8899050890731811,0.68548,0.9263308381080627,0.6785
11,0.8531640504837036,0.69946,0.9110899273872376,0.6832
12,0.8089004195022583,0.71542,0.9073972569465637,0.6861
13,0.7807940144729614,0.7241,0.9209298092842102,0.6775
14,0.7538955571365357,0.73478,0.9007615678787232,0.6845
15,0.7263440827560425,0.74322,0.8737788515090943,0.6986
16,0.6967498389816285,0.7529,0.892071831035614,0.693
17,0.6709872028255462,0.76386,0.925509871673584,0.6845
18,0.6451754664993287,0.77236,0.880049273109436,0.7039
19,0.6094434031295777,0.78594,0.8825184429168701,0.7033
20,0.5978780786895752,0.78682,0.9097155986785889,0.7018
1 epoch train_loss train_acc test_loss test_acc
2 1 1.9311371482086181 0.2982 1.5920978937149048 0.4331
3 2 1.509078656387329 0.46018 1.3684404134750365 0.506
4 3 1.3346781539916992 0.5203 1.2729134735107421 0.5345
5 4 1.2469274048614503 0.55542 1.158725128364563 0.5855
6 5 1.1582400985717773 0.58732 1.1014516458511352 0.6146
7 6 1.0868776248168945 0.61344 1.043407428741455 0.6336
8 7 1.0187307173347473 0.64048 0.9962607810974121 0.6517
9 8 0.9732129728698731 0.6563 1.009974559020996 0.647
10 9 0.9221462124443054 0.6754 0.9498543729782104 0.6732
11 10 0.8899050890731811 0.68548 0.9263308381080627 0.6785
12 11 0.8531640504837036 0.69946 0.9110899273872376 0.6832
13 12 0.8089004195022583 0.71542 0.9073972569465637 0.6861
14 13 0.7807940144729614 0.7241 0.9209298092842102 0.6775
15 14 0.7538955571365357 0.73478 0.9007615678787232 0.6845
16 15 0.7263440827560425 0.74322 0.8737788515090943 0.6986
17 16 0.6967498389816285 0.7529 0.892071831035614 0.693
18 17 0.6709872028255462 0.76386 0.925509871673584 0.6845
19 18 0.6451754664993287 0.77236 0.880049273109436 0.7039
20 19 0.6094434031295777 0.78594 0.8825184429168701 0.7033
21 20 0.5978780786895752 0.78682 0.9097155986785889 0.7018
Project/on_GPU/analytics/history_sgd_none_42.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,2.004312101173401,0.2652,1.7232767820358277,0.3901
2,1.5482629161834718,0.44188,1.3712095808029174,0.5058
3,1.3661574739074707,0.51074,1.2661858087539672,0.5433
4,1.2579275118255615,0.55174,1.1585919318199158,0.5871
5,1.164323837776184,0.58694,1.1396800863265992,0.6003
6,1.092229642868042,0.61386,1.0896189386367798,0.6099
7,1.0241320381164551,0.63798,0.9922213355064392,0.6553
8,0.9711285202407837,0.65922,0.9600511573791504,0.662
9,0.9307016561889648,0.67076,0.9466310350418091,0.6742
10,0.8810099458122254,0.68936,0.9367870839118958,0.675
11,0.8454511882400513,0.70294,0.9090298080444336,0.6799
12,0.8024745466995239,0.71828,0.8979659676551819,0.6893
13,0.7719563391876221,0.72812,0.8994972805976867,0.688
14,0.7395517325782776,0.74026,0.8924659374237061,0.687
15,0.7045410289382935,0.7509,0.917015513420105,0.6827
16,0.6758938273620605,0.76374,0.8863575847625732,0.6987
17,0.6473090003585815,0.77248,0.8756544432640075,0.7049
18,0.6271680759048462,0.77752,0.897514891242981,0.6964
19,0.597278731880188,0.7895,0.8914299827575684,0.6974
20,0.5726878065681458,0.79906,0.8957463808059692,0.7017
1 epoch train_loss train_acc test_loss test_acc
2 1 2.004312101173401 0.2652 1.7232767820358277 0.3901
3 2 1.5482629161834718 0.44188 1.3712095808029174 0.5058
4 3 1.3661574739074707 0.51074 1.2661858087539672 0.5433
5 4 1.2579275118255615 0.55174 1.1585919318199158 0.5871
6 5 1.164323837776184 0.58694 1.1396800863265992 0.6003
7 6 1.092229642868042 0.61386 1.0896189386367798 0.6099
8 7 1.0241320381164551 0.63798 0.9922213355064392 0.6553
9 8 0.9711285202407837 0.65922 0.9600511573791504 0.662
10 9 0.9307016561889648 0.67076 0.9466310350418091 0.6742
11 10 0.8810099458122254 0.68936 0.9367870839118958 0.675
12 11 0.8454511882400513 0.70294 0.9090298080444336 0.6799
13 12 0.8024745466995239 0.71828 0.8979659676551819 0.6893
14 13 0.7719563391876221 0.72812 0.8994972805976867 0.688
15 14 0.7395517325782776 0.74026 0.8924659374237061 0.687
16 15 0.7045410289382935 0.7509 0.917015513420105 0.6827
17 16 0.6758938273620605 0.76374 0.8863575847625732 0.6987
18 17 0.6473090003585815 0.77248 0.8756544432640075 0.7049
19 18 0.6271680759048462 0.77752 0.897514891242981 0.6964
20 19 0.597278731880188 0.7895 0.8914299827575684 0.6974
21 20 0.5726878065681458 0.79906 0.8957463808059692 0.7017
Project/on_GPU/analytics/history_sgd_none_999.csv
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@@ -0,0 +1,21 @@
epoch,train_loss,train_acc,test_loss,test_acc
1,1.9648466619873046,0.28228,1.6398368045806884,0.4082
2,1.5440472770690918,0.44262,1.393077986907959,0.4967
3,1.3840823981094361,0.50308,1.263754221534729,0.5481
4,1.2707756679534912,0.54684,1.2010628286361695,0.5698
5,1.1830180548477174,0.57878,1.1136125858306885,0.6024
6,1.0973178535079957,0.61194,1.0529953979492188,0.6247
7,1.0351464793014526,0.63214,1.0379781282424927,0.6337
8,0.9851882269287109,0.65194,0.9881413891792298,0.6516
9,0.9321160899734497,0.66992,0.9766159063339234,0.6519
10,0.8936848720169067,0.68802,0.9404750473022461,0.6659
11,0.8555344334411621,0.69752,0.9300194321632386,0.6739
12,0.8127794537353515,0.71468,0.9445248321533203,0.6714
13,0.7774085792922973,0.72442,0.9079333065032958,0.6844
14,0.7445920983695984,0.73784,0.9506904909133911,0.6712
15,0.7130360057258606,0.75044,0.8811728349685669,0.6967
16,0.6768621940994263,0.76162,0.8943761650085449,0.691
17,0.6570009999847413,0.76814,0.9109026754379272,0.6931
18,0.6386432394218445,0.77624,0.8959919429779053,0.7021
19,0.6080109805679321,0.78532,0.9124002801895141,0.6982
20,0.5840396033859253,0.79492,0.9637748687744141,0.6778
1 epoch train_loss train_acc test_loss test_acc
2 1 1.9648466619873046 0.28228 1.6398368045806884 0.4082
3 2 1.5440472770690918 0.44262 1.393077986907959 0.4967
4 3 1.3840823981094361 0.50308 1.263754221534729 0.5481
5 4 1.2707756679534912 0.54684 1.2010628286361695 0.5698
6 5 1.1830180548477174 0.57878 1.1136125858306885 0.6024
7 6 1.0973178535079957 0.61194 1.0529953979492188 0.6247
8 7 1.0351464793014526 0.63214 1.0379781282424927 0.6337
9 8 0.9851882269287109 0.65194 0.9881413891792298 0.6516
10 9 0.9321160899734497 0.66992 0.9766159063339234 0.6519
11 10 0.8936848720169067 0.68802 0.9404750473022461 0.6659
12 11 0.8555344334411621 0.69752 0.9300194321632386 0.6739
13 12 0.8127794537353515 0.71468 0.9445248321533203 0.6714
14 13 0.7774085792922973 0.72442 0.9079333065032958 0.6844
15 14 0.7445920983695984 0.73784 0.9506904909133911 0.6712
16 15 0.7130360057258606 0.75044 0.8811728349685669 0.6967
17 16 0.6768621940994263 0.76162 0.8943761650085449 0.691
18 17 0.6570009999847413 0.76814 0.9109026754379272 0.6931
19 18 0.6386432394218445 0.77624 0.8959919429779053 0.7021
20 19 0.6080109805679321 0.78532 0.9124002801895141 0.6982
21 20 0.5840396033859253 0.79492 0.9637748687744141 0.6778
Project/on_GPU/analytics/history_sgd_standard_123.csv
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epoch,train_loss,train_acc,test_loss,test_acc
1,2.0550885951995848,0.2467,1.7640317403793335,0.3644
2,1.7425042122650147,0.36956,1.5332227375030518,0.4334
3,1.555955955848694,0.43286,1.380984833908081,0.5017
4,1.4620817391204834,0.46802,1.297961190509796,0.538
5,1.3934137030792237,0.49522,1.198084861946106,0.5701
6,1.329382759361267,0.5213,1.1716940355300904,0.5866
7,1.2766435260009765,0.54206,1.0953855429649353,0.6181
8,1.2315738436126709,0.55692,1.0728544158935547,0.6213
9,1.2073827326965332,0.56722,1.0609665860176087,0.6211
10,1.1776278511810303,0.57848,1.0275169611930848,0.633
11,1.1487520777130127,0.59018,0.9839586427688599,0.6505
12,1.1335893363189697,0.59792,0.9638538955688477,0.6629
13,1.1190336322402954,0.59944,0.9677156891822815,0.6655
14,1.094583490257263,0.61246,0.9283652758598328,0.6774
15,1.084797211303711,0.61338,0.9156901554107666,0.6762
16,1.0731646694946289,0.61824,0.911062100315094,0.6788
17,1.0665611047554016,0.62164,0.9009365707397461,0.6879
18,1.0515223734283448,0.62704,0.9012013221740722,0.6872
19,1.0465966410827636,0.6275,0.9001763169288636,0.6877
20,1.0255706683731078,0.63722,0.862306897354126,0.6987
1 epoch train_loss train_acc test_loss test_acc
2 1 2.0550885951995848 0.2467 1.7640317403793335 0.3644
3 2 1.7425042122650147 0.36956 1.5332227375030518 0.4334
4 3 1.555955955848694 0.43286 1.380984833908081 0.5017
5 4 1.4620817391204834 0.46802 1.297961190509796 0.538
6 5 1.3934137030792237 0.49522 1.198084861946106 0.5701
7 6 1.329382759361267 0.5213 1.1716940355300904 0.5866
8 7 1.2766435260009765 0.54206 1.0953855429649353 0.6181
9 8 1.2315738436126709 0.55692 1.0728544158935547 0.6213
10 9 1.2073827326965332 0.56722 1.0609665860176087 0.6211
11 10 1.1776278511810303 0.57848 1.0275169611930848 0.633
12 11 1.1487520777130127 0.59018 0.9839586427688599 0.6505
13 12 1.1335893363189697 0.59792 0.9638538955688477 0.6629
14 13 1.1190336322402954 0.59944 0.9677156891822815 0.6655
15 14 1.094583490257263 0.61246 0.9283652758598328 0.6774
16 15 1.084797211303711 0.61338 0.9156901554107666 0.6762
17 16 1.0731646694946289 0.61824 0.911062100315094 0.6788
18 17 1.0665611047554016 0.62164 0.9009365707397461 0.6879
19 18 1.0515223734283448 0.62704 0.9012013221740722 0.6872
20 19 1.0465966410827636 0.6275 0.9001763169288636 0.6877
21 20 1.0255706683731078 0.63722 0.862306897354126 0.6987
Project/on_GPU/analytics/history_sgd_standard_42.csv
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@@ -0,0 +1,21 @@
epoch,train_loss,train_acc,test_loss,test_acc
1,2.017535278091431,0.26278,1.6795637042999267,0.3998
2,1.6903974377059936,0.38804,1.4434795204162598,0.474
3,1.5346185763931275,0.44274,1.36727356300354,0.5145
4,1.4617975156402587,0.46894,1.2737480709075928,0.5426
5,1.3889456367492676,0.4969,1.2169358665466308,0.5703
6,1.3288960292434693,0.52194,1.1306485939025879,0.6004
7,1.2709935831451415,0.5442,1.0904423005104065,0.6111
8,1.228000947227478,0.56192,1.0558609092712403,0.627
9,1.1939466933059693,0.57354,1.0516909730911255,0.6264
10,1.1654139777755737,0.5873,0.9876455611228943,0.6489
11,1.1431168384933472,0.5929,0.9878189376831055,0.644
12,1.1232611434936524,0.60072,0.9371956800460816,0.6712
13,1.1012448973274231,0.60876,0.9292478965759278,0.6751
14,1.0849506562423705,0.61526,0.9188048232078552,0.6806
15,1.06521858171463,0.6227,0.914396158695221,0.6784
16,1.0540395666885376,0.6272,0.8965913438796997,0.6883
17,1.040338694896698,0.63254,0.9149609729766846,0.6792
18,1.0297105773735047,0.63586,0.8735279068946838,0.6907
19,1.015626749534607,0.64372,0.8664175868988037,0.6983
20,1.0131161414909362,0.64066,0.850979465007782,0.6983
1 epoch train_loss train_acc test_loss test_acc
2 1 2.017535278091431 0.26278 1.6795637042999267 0.3998
3 2 1.6903974377059936 0.38804 1.4434795204162598 0.474
4 3 1.5346185763931275 0.44274 1.36727356300354 0.5145
5 4 1.4617975156402587 0.46894 1.2737480709075928 0.5426
6 5 1.3889456367492676 0.4969 1.2169358665466308 0.5703
7 6 1.3288960292434693 0.52194 1.1306485939025879 0.6004
8 7 1.2709935831451415 0.5442 1.0904423005104065 0.6111
9 8 1.228000947227478 0.56192 1.0558609092712403 0.627
10 9 1.1939466933059693 0.57354 1.0516909730911255 0.6264
11 10 1.1654139777755737 0.5873 0.9876455611228943 0.6489
12 11 1.1431168384933472 0.5929 0.9878189376831055 0.644
13 12 1.1232611434936524 0.60072 0.9371956800460816 0.6712
14 13 1.1012448973274231 0.60876 0.9292478965759278 0.6751
15 14 1.0849506562423705 0.61526 0.9188048232078552 0.6806
16 15 1.06521858171463 0.6227 0.914396158695221 0.6784
17 16 1.0540395666885376 0.6272 0.8965913438796997 0.6883
18 17 1.040338694896698 0.63254 0.9149609729766846 0.6792
19 18 1.0297105773735047 0.63586 0.8735279068946838 0.6907
20 19 1.015626749534607 0.64372 0.8664175868988037 0.6983
21 20 1.0131161414909362 0.64066 0.850979465007782 0.6983
Project/on_GPU/analytics/history_sgd_standard_999.csv
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@@ -0,0 +1,21 @@
epoch,train_loss,train_acc,test_loss,test_acc
1,2.040701542739868,0.24942,1.7548002931594848,0.3775
2,1.6937445477676392,0.3859,1.5174737565994263,0.4468
3,1.5486173374176024,0.43744,1.4181810174942016,0.4884
4,1.4722703090286255,0.46892,1.3536616600036622,0.5155
5,1.4086143017578125,0.49256,1.2277663545608521,0.5603
6,1.3517387983322144,0.5127,1.245518007850647,0.5646
7,1.3047347919082641,0.52996,1.1440864992141724,0.5974
8,1.2650044574356079,0.54544,1.0812738724708557,0.6163
9,1.221998965034485,0.56412,1.0611048071861267,0.6208
10,1.1992827208709718,0.57162,1.02209319190979,0.6378
11,1.1627163088226318,0.58332,0.9875484481811524,0.6552
12,1.143350224761963,0.59006,0.9906831841468811,0.65
13,1.1313561878585816,0.59856,0.9684320789337159,0.6619
14,1.1073162591934205,0.60544,0.956348852443695,0.6635
15,1.0957912900161744,0.61112,0.9253881983757019,0.6747
16,1.0843125787353516,0.61314,0.9387169095993042,0.6678
17,1.0638633008003235,0.6221,0.9209315038681031,0.6751
18,1.044793717918396,0.63046,0.9019776906967163,0.6828
19,1.0394491952133178,0.63022,0.9281384669303894,0.6652
20,1.0273043719291688,0.63526,0.865586933708191,0.6961
1 epoch train_loss train_acc test_loss test_acc
2 1 2.040701542739868 0.24942 1.7548002931594848 0.3775
3 2 1.6937445477676392 0.3859 1.5174737565994263 0.4468
4 3 1.5486173374176024 0.43744 1.4181810174942016 0.4884
5 4 1.4722703090286255 0.46892 1.3536616600036622 0.5155
6 5 1.4086143017578125 0.49256 1.2277663545608521 0.5603
7 6 1.3517387983322144 0.5127 1.245518007850647 0.5646
8 7 1.3047347919082641 0.52996 1.1440864992141724 0.5974
9 8 1.2650044574356079 0.54544 1.0812738724708557 0.6163
10 9 1.221998965034485 0.56412 1.0611048071861267 0.6208
11 10 1.1992827208709718 0.57162 1.02209319190979 0.6378
12 11 1.1627163088226318 0.58332 0.9875484481811524 0.6552
13 12 1.143350224761963 0.59006 0.9906831841468811 0.65
14 13 1.1313561878585816 0.59856 0.9684320789337159 0.6619
15 14 1.1073162591934205 0.60544 0.956348852443695 0.6635
16 15 1.0957912900161744 0.61112 0.9253881983757019 0.6747
17 16 1.0843125787353516 0.61314 0.9387169095993042 0.6678
18 17 1.0638633008003235 0.6221 0.9209315038681031 0.6751
19 18 1.044793717918396 0.63046 0.9019776906967163 0.6828
20 19 1.0394491952133178 0.63022 0.9281384669303894 0.6652
21 20 1.0273043719291688 0.63526 0.865586933708191 0.6961
Project/on_GPU/out.txt
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11.8
4
NVIDIA GeForce RTX 4090
True
Message sent successfully!
Namespace(batch_size=128, lr=0.01, epochs=20, analyze=False)
SEED 42
[sgd][none][epoch 1] train_loss=2.0043, train_acc=0.2652, test_acc=0.3901
[sgd][none][epoch 2] train_loss=1.5483, train_acc=0.4419, test_acc=0.5058
[sgd][none][epoch 3] train_loss=1.3662, train_acc=0.5107, test_acc=0.5433
[sgd][none][epoch 4] train_loss=1.2579, train_acc=0.5517, test_acc=0.5871
[sgd][none][epoch 5] train_loss=1.1643, train_acc=0.5869, test_acc=0.6003
[sgd][none][epoch 6] train_loss=1.0922, train_acc=0.6139, test_acc=0.6099
[sgd][none][epoch 7] train_loss=1.0241, train_acc=0.6380, test_acc=0.6553
[sgd][none][epoch 8] train_loss=0.9711, train_acc=0.6592, test_acc=0.6620
[sgd][none][epoch 9] train_loss=0.9307, train_acc=0.6708, test_acc=0.6742
[sgd][none][epoch 10] train_loss=0.8810, train_acc=0.6894, test_acc=0.6750
[sgd][none][epoch 11] train_loss=0.8455, train_acc=0.7029, test_acc=0.6799
[sgd][none][epoch 12] train_loss=0.8025, train_acc=0.7183, test_acc=0.6893
[sgd][none][epoch 13] train_loss=0.7720, train_acc=0.7281, test_acc=0.6880
[sgd][none][epoch 14] train_loss=0.7396, train_acc=0.7403, test_acc=0.6870
[sgd][none][epoch 15] train_loss=0.7045, train_acc=0.7509, test_acc=0.6827
[sgd][none][epoch 16] train_loss=0.6759, train_acc=0.7637, test_acc=0.6987
[sgd][none][epoch 17] train_loss=0.6473, train_acc=0.7725, test_acc=0.7049
[sgd][none][epoch 18] train_loss=0.6272, train_acc=0.7775, test_acc=0.6964
[sgd][none][epoch 19] train_loss=0.5973, train_acc=0.7895, test_acc=0.6974
[sgd][none][epoch 20] train_loss=0.5727, train_acc=0.7991, test_acc=0.7017
[sgd][standard][epoch 1] train_loss=2.0175, train_acc=0.2628, test_acc=0.3998
[sgd][standard][epoch 2] train_loss=1.6904, train_acc=0.3880, test_acc=0.4740
[sgd][standard][epoch 3] train_loss=1.5346, train_acc=0.4427, test_acc=0.5145
[sgd][standard][epoch 4] train_loss=1.4618, train_acc=0.4689, test_acc=0.5426
[sgd][standard][epoch 5] train_loss=1.3889, train_acc=0.4969, test_acc=0.5703
[sgd][standard][epoch 6] train_loss=1.3289, train_acc=0.5219, test_acc=0.6004
[sgd][standard][epoch 7] train_loss=1.2710, train_acc=0.5442, test_acc=0.6111
[sgd][standard][epoch 8] train_loss=1.2280, train_acc=0.5619, test_acc=0.6270
[sgd][standard][epoch 9] train_loss=1.1939, train_acc=0.5735, test_acc=0.6264
[sgd][standard][epoch 10] train_loss=1.1654, train_acc=0.5873, test_acc=0.6489
[sgd][standard][epoch 11] train_loss=1.1431, train_acc=0.5929, test_acc=0.6440
[sgd][standard][epoch 12] train_loss=1.1233, train_acc=0.6007, test_acc=0.6712
[sgd][standard][epoch 13] train_loss=1.1012, train_acc=0.6088, test_acc=0.6751
[sgd][standard][epoch 14] train_loss=1.0850, train_acc=0.6153, test_acc=0.6806
[sgd][standard][epoch 15] train_loss=1.0652, train_acc=0.6227, test_acc=0.6784
[sgd][standard][epoch 16] train_loss=1.0540, train_acc=0.6272, test_acc=0.6883
[sgd][standard][epoch 17] train_loss=1.0403, train_acc=0.6325, test_acc=0.6792
[sgd][standard][epoch 18] train_loss=1.0297, train_acc=0.6359, test_acc=0.6907
[sgd][standard][epoch 19] train_loss=1.0156, train_acc=0.6437, test_acc=0.6983
[sgd][standard][epoch 20] train_loss=1.0131, train_acc=0.6407, test_acc=0.6983
[sgd][aggressive][epoch 1] train_loss=2.0534, train_acc=0.2443, test_acc=0.3477
[sgd][aggressive][epoch 2] train_loss=1.7876, train_acc=0.3524, test_acc=0.4583
[sgd][aggressive][epoch 3] train_loss=1.6461, train_acc=0.4054, test_acc=0.4684
[sgd][aggressive][epoch 4] train_loss=1.5714, train_acc=0.4340, test_acc=0.5046
[sgd][aggressive][epoch 5] train_loss=1.5172, train_acc=0.4534, test_acc=0.5348
[sgd][aggressive][epoch 6] train_loss=1.4628, train_acc=0.4736, test_acc=0.5529
[sgd][aggressive][epoch 7] train_loss=1.4181, train_acc=0.4933, test_acc=0.5795
[sgd][aggressive][epoch 8] train_loss=1.3875, train_acc=0.5027, test_acc=0.5967
[sgd][aggressive][epoch 9] train_loss=1.3532, train_acc=0.5146, test_acc=0.5977
[sgd][aggressive][epoch 10] train_loss=1.3283, train_acc=0.5265, test_acc=0.6028
[sgd][aggressive][epoch 11] train_loss=1.3050, train_acc=0.5333, test_acc=0.6133
[sgd][aggressive][epoch 12] train_loss=1.2840, train_acc=0.5430, test_acc=0.6329
[sgd][aggressive][epoch 13] train_loss=1.2662, train_acc=0.5505, test_acc=0.6011
[sgd][aggressive][epoch 14] train_loss=1.2491, train_acc=0.5545, test_acc=0.6490
[sgd][aggressive][epoch 15] train_loss=1.2334, train_acc=0.5621, test_acc=0.6452
[sgd][aggressive][epoch 16] train_loss=1.2266, train_acc=0.5656, test_acc=0.6381
[sgd][aggressive][epoch 17] train_loss=1.2157, train_acc=0.5678, test_acc=0.6482
[sgd][aggressive][epoch 18] train_loss=1.2051, train_acc=0.5745, test_acc=0.6619
[sgd][aggressive][epoch 19] train_loss=1.1854, train_acc=0.5793, test_acc=0.6701
[sgd][aggressive][epoch 20] train_loss=1.1799, train_acc=0.5823, test_acc=0.6529
[adam][none][epoch 1] train_loss=1.7539, train_acc=0.3666, test_acc=0.4474
[adam][none][epoch 2] train_loss=1.5013, train_acc=0.4559, test_acc=0.4801
[adam][none][epoch 3] train_loss=1.4560, train_acc=0.4740, test_acc=0.5110
[adam][none][epoch 4] train_loss=1.4221, train_acc=0.4882, test_acc=0.5162
[adam][none][epoch 5] train_loss=1.3943, train_acc=0.4997, test_acc=0.5221
[adam][none][epoch 6] train_loss=1.3840, train_acc=0.5037, test_acc=0.5295
[adam][none][epoch 7] train_loss=1.3604, train_acc=0.5146, test_acc=0.5269
[adam][none][epoch 8] train_loss=1.3529, train_acc=0.5131, test_acc=0.5478
[adam][none][epoch 9] train_loss=1.3496, train_acc=0.5150, test_acc=0.5602
[adam][none][epoch 10] train_loss=1.3384, train_acc=0.5199, test_acc=0.5414
[adam][none][epoch 11] train_loss=1.3299, train_acc=0.5230, test_acc=0.5535
[adam][none][epoch 12] train_loss=1.3380, train_acc=0.5231, test_acc=0.5783
[adam][none][epoch 13] train_loss=1.3283, train_acc=0.5238, test_acc=0.5622
[adam][none][epoch 14] train_loss=1.3241, train_acc=0.5305, test_acc=0.5585
[adam][none][epoch 15] train_loss=1.3172, train_acc=0.5315, test_acc=0.5775
[adam][none][epoch 16] train_loss=1.3192, train_acc=0.5301, test_acc=0.5694
[adam][none][epoch 17] train_loss=1.3199, train_acc=0.5286, test_acc=0.5755
[adam][none][epoch 18] train_loss=1.3246, train_acc=0.5278, test_acc=0.5589
[adam][none][epoch 19] train_loss=1.3320, train_acc=0.5294, test_acc=0.5715
[adam][none][epoch 20] train_loss=1.3130, train_acc=0.5311, test_acc=0.5754
[adam][standard][epoch 1] train_loss=1.9662, train_acc=0.2817, test_acc=0.4059
[adam][standard][epoch 2] train_loss=1.6907, train_acc=0.3810, test_acc=0.4608
[adam][standard][epoch 3] train_loss=1.6306, train_acc=0.4023, test_acc=0.4703
[adam][standard][epoch 4] train_loss=1.5946, train_acc=0.4130, test_acc=0.4582
[adam][standard][epoch 5] train_loss=1.5847, train_acc=0.4194, test_acc=0.4656
[adam][standard][epoch 6] train_loss=1.5700, train_acc=0.4245, test_acc=0.4742
[adam][standard][epoch 7] train_loss=1.5597, train_acc=0.4317, test_acc=0.4815
[adam][standard][epoch 8] train_loss=1.5501, train_acc=0.4339, test_acc=0.4736
[adam][standard][epoch 9] train_loss=1.5521, train_acc=0.4347, test_acc=0.4965
[adam][standard][epoch 10] train_loss=1.5406, train_acc=0.4394, test_acc=0.4963
[adam][standard][epoch 11] train_loss=1.5427, train_acc=0.4397, test_acc=0.5065
[adam][standard][epoch 12] train_loss=1.5427, train_acc=0.4380, test_acc=0.4952
[adam][standard][epoch 13] train_loss=1.5383, train_acc=0.4385, test_acc=0.5190
[adam][standard][epoch 14] train_loss=1.5358, train_acc=0.4394, test_acc=0.4922
[adam][standard][epoch 15] train_loss=1.5209, train_acc=0.4479, test_acc=0.5174
[adam][standard][epoch 16] train_loss=1.5207, train_acc=0.4429, test_acc=0.5318
[adam][standard][epoch 17] train_loss=1.5428, train_acc=0.4420, test_acc=0.5101
[adam][standard][epoch 18] train_loss=1.5282, train_acc=0.4421, test_acc=0.5246
[adam][standard][epoch 19] train_loss=1.5154, train_acc=0.4515, test_acc=0.4926
[adam][standard][epoch 20] train_loss=1.5201, train_acc=0.4484, test_acc=0.5012
[adam][aggressive][epoch 1] train_loss=1.9946, train_acc=0.2655, test_acc=0.3420
[adam][aggressive][epoch 2] train_loss=1.7975, train_acc=0.3353, test_acc=0.4064
[adam][aggressive][epoch 3] train_loss=1.7743, train_acc=0.3444, test_acc=0.4200
[adam][aggressive][epoch 4] train_loss=1.7372, train_acc=0.3579, test_acc=0.4113
[adam][aggressive][epoch 5] train_loss=1.7270, train_acc=0.3684, test_acc=0.4221
[adam][aggressive][epoch 6] train_loss=1.7161, train_acc=0.3704, test_acc=0.4449
[adam][aggressive][epoch 7] train_loss=1.6962, train_acc=0.3799, test_acc=0.4352
[adam][aggressive][epoch 8] train_loss=1.6957, train_acc=0.3808, test_acc=0.4409
[adam][aggressive][epoch 9] train_loss=1.6931, train_acc=0.3804, test_acc=0.4434
[adam][aggressive][epoch 10] train_loss=1.6858, train_acc=0.3787, test_acc=0.4671
[adam][aggressive][epoch 11] train_loss=1.6876, train_acc=0.3814, test_acc=0.4560
[adam][aggressive][epoch 12] train_loss=1.6893, train_acc=0.3837, test_acc=0.4288
[adam][aggressive][epoch 13] train_loss=1.6795, train_acc=0.3832, test_acc=0.4422
[adam][aggressive][epoch 14] train_loss=1.6710, train_acc=0.3851, test_acc=0.4082
[adam][aggressive][epoch 15] train_loss=1.6753, train_acc=0.3846, test_acc=0.4628
[adam][aggressive][epoch 16] train_loss=1.6733, train_acc=0.3831, test_acc=0.4370
[adam][aggressive][epoch 17] train_loss=1.6646, train_acc=0.3890, test_acc=0.4529
[adam][aggressive][epoch 18] train_loss=1.6783, train_acc=0.3829, test_acc=0.4649
[adam][aggressive][epoch 19] train_loss=1.6775, train_acc=0.3857, test_acc=0.4383
[adam][aggressive][epoch 20] train_loss=1.6718, train_acc=0.3821, test_acc=0.4534
SEED 123
[sgd][none][epoch 1] train_loss=1.9311, train_acc=0.2982, test_acc=0.4331
[sgd][none][epoch 2] train_loss=1.5091, train_acc=0.4602, test_acc=0.5060
[sgd][none][epoch 3] train_loss=1.3347, train_acc=0.5203, test_acc=0.5345
[sgd][none][epoch 4] train_loss=1.2469, train_acc=0.5554, test_acc=0.5855
[sgd][none][epoch 5] train_loss=1.1582, train_acc=0.5873, test_acc=0.6146
[sgd][none][epoch 6] train_loss=1.0869, train_acc=0.6134, test_acc=0.6336
[sgd][none][epoch 7] train_loss=1.0187, train_acc=0.6405, test_acc=0.6517
[sgd][none][epoch 8] train_loss=0.9732, train_acc=0.6563, test_acc=0.6470
[sgd][none][epoch 9] train_loss=0.9221, train_acc=0.6754, test_acc=0.6732
[sgd][none][epoch 10] train_loss=0.8899, train_acc=0.6855, test_acc=0.6785
[sgd][none][epoch 11] train_loss=0.8532, train_acc=0.6995, test_acc=0.6832
[sgd][none][epoch 12] train_loss=0.8089, train_acc=0.7154, test_acc=0.6861
[sgd][none][epoch 13] train_loss=0.7808, train_acc=0.7241, test_acc=0.6775
[sgd][none][epoch 14] train_loss=0.7539, train_acc=0.7348, test_acc=0.6845
[sgd][none][epoch 15] train_loss=0.7263, train_acc=0.7432, test_acc=0.6986
[sgd][none][epoch 16] train_loss=0.6967, train_acc=0.7529, test_acc=0.6930
[sgd][none][epoch 17] train_loss=0.6710, train_acc=0.7639, test_acc=0.6845
[sgd][none][epoch 18] train_loss=0.6452, train_acc=0.7724, test_acc=0.7039
[sgd][none][epoch 19] train_loss=0.6094, train_acc=0.7859, test_acc=0.7033
[sgd][none][epoch 20] train_loss=0.5979, train_acc=0.7868, test_acc=0.7018
[sgd][standard][epoch 1] train_loss=2.0551, train_acc=0.2467, test_acc=0.3644
[sgd][standard][epoch 2] train_loss=1.7425, train_acc=0.3696, test_acc=0.4334
[sgd][standard][epoch 3] train_loss=1.5560, train_acc=0.4329, test_acc=0.5017
[sgd][standard][epoch 4] train_loss=1.4621, train_acc=0.4680, test_acc=0.5380
[sgd][standard][epoch 5] train_loss=1.3934, train_acc=0.4952, test_acc=0.5701
[sgd][standard][epoch 6] train_loss=1.3294, train_acc=0.5213, test_acc=0.5866
[sgd][standard][epoch 7] train_loss=1.2766, train_acc=0.5421, test_acc=0.6181
[sgd][standard][epoch 8] train_loss=1.2316, train_acc=0.5569, test_acc=0.6213
[sgd][standard][epoch 9] train_loss=1.2074, train_acc=0.5672, test_acc=0.6211
[sgd][standard][epoch 10] train_loss=1.1776, train_acc=0.5785, test_acc=0.6330
[sgd][standard][epoch 11] train_loss=1.1488, train_acc=0.5902, test_acc=0.6505
[sgd][standard][epoch 12] train_loss=1.1336, train_acc=0.5979, test_acc=0.6629
[sgd][standard][epoch 13] train_loss=1.1190, train_acc=0.5994, test_acc=0.6655
[sgd][standard][epoch 14] train_loss=1.0946, train_acc=0.6125, test_acc=0.6774
[sgd][standard][epoch 15] train_loss=1.0848, train_acc=0.6134, test_acc=0.6762
[sgd][standard][epoch 16] train_loss=1.0732, train_acc=0.6182, test_acc=0.6788
[sgd][standard][epoch 17] train_loss=1.0666, train_acc=0.6216, test_acc=0.6879
[sgd][standard][epoch 18] train_loss=1.0515, train_acc=0.6270, test_acc=0.6872
[sgd][standard][epoch 19] train_loss=1.0466, train_acc=0.6275, test_acc=0.6877
[sgd][standard][epoch 20] train_loss=1.0256, train_acc=0.6372, test_acc=0.6987
[sgd][aggressive][epoch 1] train_loss=2.0718, train_acc=0.2364, test_acc=0.3592
[sgd][aggressive][epoch 2] train_loss=1.7712, train_acc=0.3563, test_acc=0.4336
[sgd][aggressive][epoch 3] train_loss=1.6322, train_acc=0.4069, test_acc=0.4826
[sgd][aggressive][epoch 4] train_loss=1.5630, train_acc=0.4342, test_acc=0.5099
[sgd][aggressive][epoch 5] train_loss=1.4983, train_acc=0.4578, test_acc=0.5423
[sgd][aggressive][epoch 6] train_loss=1.4539, train_acc=0.4778, test_acc=0.5584
[sgd][aggressive][epoch 7] train_loss=1.4067, train_acc=0.4912, test_acc=0.5824
[sgd][aggressive][epoch 8] train_loss=1.3720, train_acc=0.5108, test_acc=0.5948
[sgd][aggressive][epoch 9] train_loss=1.3426, train_acc=0.5199, test_acc=0.5881
[sgd][aggressive][epoch 10] train_loss=1.3074, train_acc=0.5334, test_acc=0.6235
[sgd][aggressive][epoch 11] train_loss=1.2872, train_acc=0.5407, test_acc=0.6285
[sgd][aggressive][epoch 12] train_loss=1.2661, train_acc=0.5488, test_acc=0.6413
[sgd][aggressive][epoch 13] train_loss=1.2529, train_acc=0.5552, test_acc=0.6473
[sgd][aggressive][epoch 14] train_loss=1.2264, train_acc=0.5646, test_acc=0.6436
[sgd][aggressive][epoch 15] train_loss=1.2245, train_acc=0.5647, test_acc=0.6484
[sgd][aggressive][epoch 16] train_loss=1.2083, train_acc=0.5684, test_acc=0.6642
[sgd][aggressive][epoch 17] train_loss=1.1961, train_acc=0.5754, test_acc=0.6450
[sgd][aggressive][epoch 18] train_loss=1.1778, train_acc=0.5826, test_acc=0.6629
[sgd][aggressive][epoch 19] train_loss=1.1742, train_acc=0.5867, test_acc=0.6570
[sgd][aggressive][epoch 20] train_loss=1.1654, train_acc=0.5888, test_acc=0.6736
[adam][none][epoch 1] train_loss=1.7930, train_acc=0.3436, test_acc=0.4587
[adam][none][epoch 2] train_loss=1.5388, train_acc=0.4398, test_acc=0.4631
[adam][none][epoch 3] train_loss=1.4963, train_acc=0.4578, test_acc=0.4876
[adam][none][epoch 4] train_loss=1.4608, train_acc=0.4701, test_acc=0.5141
[adam][none][epoch 5] train_loss=1.4432, train_acc=0.4794, test_acc=0.5123
[adam][none][epoch 6] train_loss=1.4211, train_acc=0.4871, test_acc=0.5290
[adam][none][epoch 7] train_loss=1.4216, train_acc=0.4891, test_acc=0.5334
[adam][none][epoch 8] train_loss=1.4136, train_acc=0.4890, test_acc=0.5363
[adam][none][epoch 9] train_loss=1.4088, train_acc=0.4921, test_acc=0.5187
[adam][none][epoch 10] train_loss=1.4120, train_acc=0.4949, test_acc=0.5335
[adam][none][epoch 11] train_loss=1.3871, train_acc=0.5001, test_acc=0.5329
[adam][none][epoch 12] train_loss=1.4000, train_acc=0.4951, test_acc=0.5462
[adam][none][epoch 13] train_loss=1.3897, train_acc=0.5010, test_acc=0.5448
[adam][none][epoch 14] train_loss=1.3929, train_acc=0.4987, test_acc=0.5352
[adam][none][epoch 15] train_loss=1.3816, train_acc=0.5039, test_acc=0.5380
[adam][none][epoch 16] train_loss=1.3859, train_acc=0.5033, test_acc=0.5447
[adam][none][epoch 17] train_loss=1.3742, train_acc=0.5099, test_acc=0.5518
[adam][none][epoch 18] train_loss=1.3722, train_acc=0.5071, test_acc=0.5568
[adam][none][epoch 19] train_loss=1.3785, train_acc=0.5065, test_acc=0.5513
[adam][none][epoch 20] train_loss=1.3660, train_acc=0.5107, test_acc=0.5414
[adam][standard][epoch 1] train_loss=1.9765, train_acc=0.2750, test_acc=0.3317
[adam][standard][epoch 2] train_loss=1.7586, train_acc=0.3564, test_acc=0.4192
[adam][standard][epoch 3] train_loss=1.7183, train_acc=0.3688, test_acc=0.3962
[adam][standard][epoch 4] train_loss=1.6878, train_acc=0.3778, test_acc=0.4209
[adam][standard][epoch 5] train_loss=1.6783, train_acc=0.3823, test_acc=0.4596
[adam][standard][epoch 6] train_loss=1.6618, train_acc=0.3878, test_acc=0.4273
[adam][standard][epoch 7] train_loss=1.6519, train_acc=0.3927, test_acc=0.4477
[adam][standard][epoch 8] train_loss=1.6319, train_acc=0.3978, test_acc=0.4640
[adam][standard][epoch 9] train_loss=1.6272, train_acc=0.4000, test_acc=0.4671
[adam][standard][epoch 10] train_loss=1.6193, train_acc=0.4039, test_acc=0.4555
[adam][standard][epoch 11] train_loss=1.6237, train_acc=0.4038, test_acc=0.4712
[adam][standard][epoch 12] train_loss=1.6257, train_acc=0.3990, test_acc=0.4606
[adam][standard][epoch 13] train_loss=1.6252, train_acc=0.4029, test_acc=0.4628
[adam][standard][epoch 14] train_loss=1.6406, train_acc=0.4009, test_acc=0.4417
[adam][standard][epoch 15] train_loss=1.6137, train_acc=0.4072, test_acc=0.4691
[adam][standard][epoch 16] train_loss=1.6059, train_acc=0.4090, test_acc=0.4535
[adam][standard][epoch 17] train_loss=1.6091, train_acc=0.4086, test_acc=0.4407
[adam][standard][epoch 18] train_loss=1.5937, train_acc=0.4106, test_acc=0.4711
[adam][standard][epoch 19] train_loss=1.6146, train_acc=0.4040, test_acc=0.4599
[adam][standard][epoch 20] train_loss=1.6015, train_acc=0.4094, test_acc=0.4439
[adam][aggressive][epoch 1] train_loss=2.0220, train_acc=0.2568, test_acc=0.3374
[adam][aggressive][epoch 2] train_loss=1.7999, train_acc=0.3355, test_acc=0.4133
[adam][aggressive][epoch 3] train_loss=1.7349, train_acc=0.3581, test_acc=0.4205
[adam][aggressive][epoch 4] train_loss=1.7072, train_acc=0.3690, test_acc=0.4260
[adam][aggressive][epoch 5] train_loss=1.6942, train_acc=0.3751, test_acc=0.4365
[adam][aggressive][epoch 6] train_loss=1.6825, train_acc=0.3806, test_acc=0.4198
[adam][aggressive][epoch 7] train_loss=1.6737, train_acc=0.3837, test_acc=0.4576
[adam][aggressive][epoch 8] train_loss=1.6662, train_acc=0.3874, test_acc=0.4461
[adam][aggressive][epoch 9] train_loss=1.6690, train_acc=0.3842, test_acc=0.4494
[adam][aggressive][epoch 10] train_loss=1.6586, train_acc=0.3910, test_acc=0.4718
[adam][aggressive][epoch 11] train_loss=1.6606, train_acc=0.3920, test_acc=0.4709
[adam][aggressive][epoch 12] train_loss=1.6647, train_acc=0.3915, test_acc=0.4603
[adam][aggressive][epoch 13] train_loss=1.6484, train_acc=0.3987, test_acc=0.4381
[adam][aggressive][epoch 14] train_loss=1.6552, train_acc=0.3902, test_acc=0.4754
[adam][aggressive][epoch 15] train_loss=1.6531, train_acc=0.3944, test_acc=0.4632
[adam][aggressive][epoch 16] train_loss=1.6465, train_acc=0.3957, test_acc=0.4774
[adam][aggressive][epoch 17] train_loss=1.6686, train_acc=0.3903, test_acc=0.4495
[adam][aggressive][epoch 18] train_loss=1.6486, train_acc=0.3973, test_acc=0.4583
[adam][aggressive][epoch 19] train_loss=1.6871, train_acc=0.3846, test_acc=0.4529
[adam][aggressive][epoch 20] train_loss=1.6608, train_acc=0.3928, test_acc=0.4519
SEED 999
[sgd][none][epoch 1] train_loss=1.9648, train_acc=0.2823, test_acc=0.4082
[sgd][none][epoch 2] train_loss=1.5440, train_acc=0.4426, test_acc=0.4967
[sgd][none][epoch 3] train_loss=1.3841, train_acc=0.5031, test_acc=0.5481
[sgd][none][epoch 4] train_loss=1.2708, train_acc=0.5468, test_acc=0.5698
[sgd][none][epoch 5] train_loss=1.1830, train_acc=0.5788, test_acc=0.6024
[sgd][none][epoch 6] train_loss=1.0973, train_acc=0.6119, test_acc=0.6247
[sgd][none][epoch 7] train_loss=1.0351, train_acc=0.6321, test_acc=0.6337
[sgd][none][epoch 8] train_loss=0.9852, train_acc=0.6519, test_acc=0.6516
[sgd][none][epoch 9] train_loss=0.9321, train_acc=0.6699, test_acc=0.6519
[sgd][none][epoch 10] train_loss=0.8937, train_acc=0.6880, test_acc=0.6659
[sgd][none][epoch 11] train_loss=0.8555, train_acc=0.6975, test_acc=0.6739
[sgd][none][epoch 12] train_loss=0.8128, train_acc=0.7147, test_acc=0.6714
[sgd][none][epoch 13] train_loss=0.7774, train_acc=0.7244, test_acc=0.6844
[sgd][none][epoch 14] train_loss=0.7446, train_acc=0.7378, test_acc=0.6712
[sgd][none][epoch 15] train_loss=0.7130, train_acc=0.7504, test_acc=0.6967
[sgd][none][epoch 16] train_loss=0.6769, train_acc=0.7616, test_acc=0.6910
[sgd][none][epoch 17] train_loss=0.6570, train_acc=0.7681, test_acc=0.6931
[sgd][none][epoch 18] train_loss=0.6386, train_acc=0.7762, test_acc=0.7021
[sgd][none][epoch 19] train_loss=0.6080, train_acc=0.7853, test_acc=0.6982
[sgd][none][epoch 20] train_loss=0.5840, train_acc=0.7949, test_acc=0.6778
[sgd][standard][epoch 1] train_loss=2.0407, train_acc=0.2494, test_acc=0.3775
[sgd][standard][epoch 2] train_loss=1.6937, train_acc=0.3859, test_acc=0.4468
[sgd][standard][epoch 3] train_loss=1.5486, train_acc=0.4374, test_acc=0.4884
[sgd][standard][epoch 4] train_loss=1.4723, train_acc=0.4689, test_acc=0.5155
[sgd][standard][epoch 5] train_loss=1.4086, train_acc=0.4926, test_acc=0.5603
[sgd][standard][epoch 6] train_loss=1.3517, train_acc=0.5127, test_acc=0.5646
[sgd][standard][epoch 7] train_loss=1.3047, train_acc=0.5300, test_acc=0.5974
[sgd][standard][epoch 8] train_loss=1.2650, train_acc=0.5454, test_acc=0.6163
[sgd][standard][epoch 9] train_loss=1.2220, train_acc=0.5641, test_acc=0.6208
[sgd][standard][epoch 10] train_loss=1.1993, train_acc=0.5716, test_acc=0.6378
[sgd][standard][epoch 11] train_loss=1.1627, train_acc=0.5833, test_acc=0.6552
[sgd][standard][epoch 12] train_loss=1.1434, train_acc=0.5901, test_acc=0.6500
[sgd][standard][epoch 13] train_loss=1.1314, train_acc=0.5986, test_acc=0.6619
[sgd][standard][epoch 14] train_loss=1.1073, train_acc=0.6054, test_acc=0.6635
[sgd][standard][epoch 15] train_loss=1.0958, train_acc=0.6111, test_acc=0.6747
[sgd][standard][epoch 16] train_loss=1.0843, train_acc=0.6131, test_acc=0.6678
[sgd][standard][epoch 17] train_loss=1.0639, train_acc=0.6221, test_acc=0.6751
[sgd][standard][epoch 18] train_loss=1.0448, train_acc=0.6305, test_acc=0.6828
[sgd][standard][epoch 19] train_loss=1.0394, train_acc=0.6302, test_acc=0.6652
[sgd][standard][epoch 20] train_loss=1.0273, train_acc=0.6353, test_acc=0.6961
[sgd][aggressive][epoch 1] train_loss=2.0646, train_acc=0.2437, test_acc=0.3856
[sgd][aggressive][epoch 2] train_loss=1.7912, train_acc=0.3552, test_acc=0.4649
[sgd][aggressive][epoch 3] train_loss=1.6363, train_acc=0.4080, test_acc=0.4622
[sgd][aggressive][epoch 4] train_loss=1.5608, train_acc=0.4355, test_acc=0.4828
[sgd][aggressive][epoch 5] train_loss=1.5063, train_acc=0.4545, test_acc=0.5366
[sgd][aggressive][epoch 6] train_loss=1.4610, train_acc=0.4755, test_acc=0.5395
[sgd][aggressive][epoch 7] train_loss=1.4184, train_acc=0.4916, test_acc=0.5608
[sgd][aggressive][epoch 8] train_loss=1.3873, train_acc=0.5043, test_acc=0.5799
[sgd][aggressive][epoch 9] train_loss=1.3462, train_acc=0.5190, test_acc=0.6037
[sgd][aggressive][epoch 10] train_loss=1.3189, train_acc=0.5313, test_acc=0.6135
[sgd][aggressive][epoch 11] train_loss=1.2964, train_acc=0.5383, test_acc=0.6157
[sgd][aggressive][epoch 12] train_loss=1.2798, train_acc=0.5443, test_acc=0.6221
[sgd][aggressive][epoch 13] train_loss=1.2447, train_acc=0.5550, test_acc=0.6303
[sgd][aggressive][epoch 14] train_loss=1.2455, train_acc=0.5583, test_acc=0.6474
[sgd][aggressive][epoch 15] train_loss=1.2229, train_acc=0.5663, test_acc=0.6583
[sgd][aggressive][epoch 16] train_loss=1.2149, train_acc=0.5711, test_acc=0.6548
[sgd][aggressive][epoch 17] train_loss=1.1953, train_acc=0.5769, test_acc=0.6514
[sgd][aggressive][epoch 18] train_loss=1.1797, train_acc=0.5802, test_acc=0.6521
[sgd][aggressive][epoch 19] train_loss=1.1690, train_acc=0.5845, test_acc=0.6624
[sgd][aggressive][epoch 20] train_loss=1.1596, train_acc=0.5901, test_acc=0.6623
[adam][none][epoch 1] train_loss=1.7632, train_acc=0.3531, test_acc=0.4299
[adam][none][epoch 2] train_loss=1.5243, train_acc=0.4486, test_acc=0.4979
[adam][none][epoch 3] train_loss=1.4566, train_acc=0.4711, test_acc=0.5188
[adam][none][epoch 4] train_loss=1.4304, train_acc=0.4808, test_acc=0.5000
[adam][none][epoch 5] train_loss=1.4109, train_acc=0.4907, test_acc=0.5087
[adam][none][epoch 6] train_loss=1.4031, train_acc=0.4983, test_acc=0.5271
[adam][none][epoch 7] train_loss=1.3831, train_acc=0.5013, test_acc=0.5123
[adam][none][epoch 8] train_loss=1.3821, train_acc=0.5024, test_acc=0.5529
[adam][none][epoch 9] train_loss=1.3669, train_acc=0.5103, test_acc=0.5251
[adam][none][epoch 10] train_loss=1.3697, train_acc=0.5087, test_acc=0.5277
[adam][none][epoch 11] train_loss=1.3734, train_acc=0.5077, test_acc=0.5407
[adam][none][epoch 12] train_loss=1.3641, train_acc=0.5121, test_acc=0.5310
[adam][none][epoch 13] train_loss=1.3571, train_acc=0.5137, test_acc=0.5501
[adam][none][epoch 14] train_loss=1.3592, train_acc=0.5151, test_acc=0.5302
[adam][none][epoch 15] train_loss=1.3578, train_acc=0.5142, test_acc=0.5569
[adam][none][epoch 16] train_loss=1.3404, train_acc=0.5190, test_acc=0.5500
[adam][none][epoch 17] train_loss=1.3544, train_acc=0.5151, test_acc=0.5515
[adam][none][epoch 18] train_loss=1.3483, train_acc=0.5184, test_acc=0.5486
[adam][none][epoch 19] train_loss=1.3437, train_acc=0.5180, test_acc=0.5480
[adam][none][epoch 20] train_loss=1.3356, train_acc=0.5202, test_acc=0.5477
[adam][standard][epoch 1] train_loss=1.9782, train_acc=0.2757, test_acc=0.3604
[adam][standard][epoch 2] train_loss=1.7882, train_acc=0.3426, test_acc=0.3830
[adam][standard][epoch 3] train_loss=1.7298, train_acc=0.3602, test_acc=0.3849
[adam][standard][epoch 4] train_loss=1.7011, train_acc=0.3696, test_acc=0.4051
[adam][standard][epoch 5] train_loss=1.6930, train_acc=0.3764, test_acc=0.4322
[adam][standard][epoch 6] train_loss=1.6891, train_acc=0.3793, test_acc=0.4155
[adam][standard][epoch 7] train_loss=1.6894, train_acc=0.3785, test_acc=0.4244
[adam][standard][epoch 8] train_loss=1.6838, train_acc=0.3799, test_acc=0.4361
[adam][standard][epoch 9] train_loss=1.6820, train_acc=0.3811, test_acc=0.4266
[adam][standard][epoch 10] train_loss=1.6631, train_acc=0.3870, test_acc=0.4309
[adam][standard][epoch 11] train_loss=1.6606, train_acc=0.3863, test_acc=0.4306
[adam][standard][epoch 12] train_loss=1.6556, train_acc=0.3915, test_acc=0.4356
[adam][standard][epoch 13] train_loss=1.6466, train_acc=0.3940, test_acc=0.4422
[adam][standard][epoch 14] train_loss=1.6496, train_acc=0.3945, test_acc=0.4355
[adam][standard][epoch 15] train_loss=1.6502, train_acc=0.3904, test_acc=0.4526
[adam][standard][epoch 16] train_loss=1.6383, train_acc=0.3980, test_acc=0.4489
[adam][standard][epoch 17] train_loss=1.6598, train_acc=0.3888, test_acc=0.4484
[adam][standard][epoch 18] train_loss=1.6430, train_acc=0.3930, test_acc=0.3994
[adam][standard][epoch 19] train_loss=1.6456, train_acc=0.3931, test_acc=0.4483
[adam][standard][epoch 20] train_loss=1.6409, train_acc=0.3942, test_acc=0.4508
[adam][aggressive][epoch 1] train_loss=2.0724, train_acc=0.2302, test_acc=0.3199
[adam][aggressive][epoch 2] train_loss=1.9161, train_acc=0.2906, test_acc=0.3617
[adam][aggressive][epoch 3] train_loss=1.8448, train_acc=0.3195, test_acc=0.3999
[adam][aggressive][epoch 4] train_loss=1.8053, train_acc=0.3348, test_acc=0.4099
[adam][aggressive][epoch 5] train_loss=1.7892, train_acc=0.3404, test_acc=0.4121
[adam][aggressive][epoch 6] train_loss=1.7877, train_acc=0.3387, test_acc=0.3256
[adam][aggressive][epoch 7] train_loss=1.7722, train_acc=0.3472, test_acc=0.4181
[adam][aggressive][epoch 8] train_loss=1.7613, train_acc=0.3479, test_acc=0.3857
[adam][aggressive][epoch 9] train_loss=1.7486, train_acc=0.3553, test_acc=0.3986
[adam][aggressive][epoch 10] train_loss=1.7620, train_acc=0.3498, test_acc=0.3982
[adam][aggressive][epoch 11] train_loss=1.7493, train_acc=0.3537, test_acc=0.4078
[adam][aggressive][epoch 12] train_loss=1.7450, train_acc=0.3541, test_acc=0.4106
[adam][aggressive][epoch 13] train_loss=1.7524, train_acc=0.3513, test_acc=0.4204
[adam][aggressive][epoch 14] train_loss=1.7393, train_acc=0.3585, test_acc=0.4125
[adam][aggressive][epoch 15] train_loss=1.7469, train_acc=0.3586, test_acc=0.3921
[adam][aggressive][epoch 16] train_loss=1.7383, train_acc=0.3580, test_acc=0.3887
[adam][aggressive][epoch 17] train_loss=1.7540, train_acc=0.3518, test_acc=0.3902
[adam][aggressive][epoch 18] train_loss=1.7417, train_acc=0.3536, test_acc=0.4027
[adam][aggressive][epoch 19] train_loss=1.7406, train_acc=0.3585, test_acc=0.4284
[adam][aggressive][epoch 20] train_loss=1.7528, train_acc=0.3491, test_acc=0.4209
saved results to results.json
anova on test accuracy:
sum_sq df F PR(>F)
C(optimizer) 0.175350 1.0 541.527205 2.363959e-11
C(augmentation) 0.015656 2.0 24.175125 6.180350e-05
C(optimizer):C(augmentation) 0.007791 2.0 12.030388 1.357929e-03
Residual 0.003886 12.0 NaN NaN
saved plot to test_acc_comparison.png
Message sent successfully!
Project/on_GPU/results.json
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[
{
"seed": 42,
"optimizer": "sgd",
"augmentation": "none",
"test_acc": 0.7017,
"robustness": {
"0.1": 0.6874,
"0.2": 0.6539,
"0.3": 0.573
}
},
{
"seed": 42,
"optimizer": "sgd",
"augmentation": "standard",
"test_acc": 0.6983,
"robustness": {
"0.1": 0.685,
"0.2": 0.6393,
"0.3": 0.5324
}
},
{
"seed": 42,
"optimizer": "sgd",
"augmentation": "aggressive",
"test_acc": 0.6529,
"robustness": {
"0.1": 0.6441,
"0.2": 0.5905,
"0.3": 0.5073
}
},
{
"seed": 42,
"optimizer": "adam",
"augmentation": "none",
"test_acc": 0.5754,
"robustness": {
"0.1": 0.5688,
"0.2": 0.5225,
"0.3": 0.461
}
},
{
"seed": 42,
"optimizer": "adam",
"augmentation": "standard",
"test_acc": 0.5012,
"robustness": {
"0.1": 0.5008,
"0.2": 0.4696,
"0.3": 0.3933
}
},
{
"seed": 42,
"optimizer": "adam",
"augmentation": "aggressive",
"test_acc": 0.4534,
"robustness": {
"0.1": 0.443,
"0.2": 0.4074,
"0.3": 0.3669
}
},
{
"seed": 123,
"optimizer": "sgd",
"augmentation": "none",
"test_acc": 0.7018,
"robustness": {
"0.1": 0.6907,
"0.2": 0.6513,
"0.3": 0.5808
}
},
{
"seed": 123,
"optimizer": "sgd",
"augmentation": "standard",
"test_acc": 0.6987,
"robustness": {
"0.1": 0.688,
"0.2": 0.6378,
"0.3": 0.5488
}
},
{
"seed": 123,
"optimizer": "sgd",
"augmentation": "aggressive",
"test_acc": 0.6736,
"robustness": {
"0.1": 0.6591,
"0.2": 0.6077,
"0.3": 0.5265
}
},
{
"seed": 123,
"optimizer": "adam",
"augmentation": "none",
"test_acc": 0.5414,
"robustness": {
"0.1": 0.5207,
"0.2": 0.4721,
"0.3": 0.3951
}
},
{
"seed": 123,
"optimizer": "adam",
"augmentation": "standard",
"test_acc": 0.4439,
"robustness": {
"0.1": 0.4509,
"0.2": 0.4256,
"0.3": 0.3567
}
},
{
"seed": 123,
"optimizer": "adam",
"augmentation": "aggressive",
"test_acc": 0.4519,
"robustness": {
"0.1": 0.4502,
"0.2": 0.4266,
"0.3": 0.3584
}
},
{
"seed": 999,
"optimizer": "sgd",
"augmentation": "none",
"test_acc": 0.6778,
"robustness": {
"0.1": 0.669,
"0.2": 0.6288,
"0.3": 0.5506
}
},
{
"seed": 999,
"optimizer": "sgd",
"augmentation": "standard",
"test_acc": 0.6961,
"robustness": {
"0.1": 0.6862,
"0.2": 0.6491,
"0.3": 0.5655
}
},
{
"seed": 999,
"optimizer": "sgd",
"augmentation": "aggressive",
"test_acc": 0.6623,
"robustness": {
"0.1": 0.6504,
"0.2": 0.5934,
"0.3": 0.5163
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