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Training
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| ==> Train 87 | |
| [================================ 515/515 ===================================>] ETA: 0ms | Step: 693ms | |
| ======> Time to learn 1 iteration = 357.17 sec | |
| ======> Time to train 1 sample = 5.41 ms | |
| ======> Train CE error: 3.32 | |
| ======> Train accuracy: 25.648% | |
| Conv layer 1 | |
| max L2 weights norm: 4.315349 | |
| #small weights: 1, big weights: 0 | |
| #small grads : 3888, big grads : 0 | |
| Conv layer 2 | |
| max L2 weights norm: 3.357420 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 6400, big grads : 0 | |
| Conv layer 3 | |
| max L2 weights norm: 3.059696 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 2304, big grads : 0 | |
| Conv layer 4 | |
| max L2 weights norm: 5.916777 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 2304, big grads : 0 | |
| Conv layer 5 | |
| max L2 weights norm: 5.614500 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 2304, big grads : 0 | |
| Linear layer 1 | |
| max L2 weights norm: 3.783963 | |
| #small weights: 37, big weights: 0 | |
| #small grads : 409600, big grads : 0 | |
| Linear layer 2 | |
| max L2 weights norm: 2.079521 | |
| #small weights: 3, big weights: 0 | |
| #small grads : 60398, big grads : 0 | |
| Output layer | |
| max L2 weights norm: 1.500999 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 10361, big grads : 0 | |
| train_confusion.totalValid: 0.25647754854369, prevTrainAcc: 0.85417172330097 | |
| >>>>>>>>>>>>>>><<<<<<<<<<<<<<< | |
| >>> Drop in training > 50% <<< | |
| >>>>>>>>>>>>>>><<<<<<<<<<<<<<< | |
| ==> Train 88 | |
| [================================ 515/515 ===================================>] ETA: 0ms | Step: 692ms | |
| ======> Time to learn 1 iteration = 356.99 sec | |
| ======> Time to train 1 sample = 5.41 ms | |
| ======> Train CE error: 1.22 | |
| ======> Train accuracy: 85.413% | |
| Conv layer 1 | |
| max L2 weights norm: 2.452757 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 23, big grads : 0 | |
| Conv layer 2 | |
| max L2 weights norm: 2.758021 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 2726, big grads : 0 | |
| Conv layer 3 | |
| max L2 weights norm: 2.899910 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 799, big grads : 0 | |
| Conv layer 4 | |
| max L2 weights norm: 2.841064 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 146, big grads : 0 | |
| Conv layer 5 | |
| max L2 weights norm: 3.378338 | |
| #small weights: 1, big weights: 0 | |
| #small grads : 11, big grads : 0 | |
| Linear layer 1 | |
| max L2 weights norm: 3.801837 | |
| #small weights: 32, big weights: 0 | |
| #small grads : 22902, big grads : 0 | |
| Linear layer 2 | |
| max L2 weights norm: 2.094819 | |
| #small weights: 6, big weights: 0 | |
| #small grads : 14103, big grads : 0 | |
| Output layer | |
| max L2 weights norm: 1.549240 | |
| #small weights: 1, big weights: 0 | |
| #small grads : 711, big grads : 0 | |
| train_confusion.totalValid: 0.85412621359223, prevTrainAcc: 0.25647754854369 | |
| ==> Train 96 | |
| [================================ 515/515 ===================================>] ETA: 0ms | Step: 693ms | |
| ======> Time to learn 1 iteration = 356.78 sec | |
| ======> Time to train 1 sample = 5.41 ms | |
| ======> Train CE error: 4.00 | |
| ======> Train accuracy: 3.609% | |
| Conv layer 1 | |
| max L2 weights norm: 3.228836 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 585, big grads : 0 | |
| Conv layer 2 | |
| max L2 weights norm: 3.343111 | |
| #small weights: 2, big weights: 0 | |
| #small grads : 4029, big grads : 0 | |
| Conv layer 3 | |
| max L2 weights norm: 3.478521 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 915, big grads : 0 | |
| Conv layer 4 | |
| max L2 weights norm: 2.825122 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 382, big grads : 0 | |
| Conv layer 5 | |
| max L2 weights norm: 3.765861 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 632, big grads : 0 | |
| Linear layer 1 | |
| max L2 weights norm: 3.923441 | |
| #small weights: 36, big weights: 0 | |
| #small grads : 306043, big grads : 0 | |
| Linear layer 2 | |
| max L2 weights norm: 2.134979 | |
| #small weights: 4, big weights: 0 | |
| #small grads : 34045, big grads : 0 | |
| Output layer | |
| max L2 weights norm: 1.830988 | |
| #small weights: 3, big weights: 0 | |
| #small grads : 5272, big grads : 0 | |
| train_confusion.totalValid: 0.036089199029126, prevTrainAcc: 0.58793992718447 | |
| >>>>>>>>>>>>>>><<<<<<<<<<<<<<< | |
| >>> Drop in training > 50% <<< | |
| >>>>>>>>>>>>>>><<<<<<<<<<<<<<< | |
| ==> Train 97 | |
| [================================ 515/515 ===================================>] ETA: 0ms | Step: 693ms | |
| ======> Time to learn 1 iteration = 357.17 sec | |
| ======> Time to train 1 sample = 5.41 ms | |
| ======> Train CE error: 3.95 | |
| ======> Train accuracy: 3.924% | |
| Conv layer 1 | |
| max L2 weights norm: 1.932102 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 221, big grads : 0 | |
| Conv layer 2 | |
| max L2 weights norm: 3.344407 | |
| #small weights: 1, big weights: 0 | |
| #small grads : 3583, big grads : 0 | |
| Conv layer 3 | |
| max L2 weights norm: 3.106975 | |
| #small weights: 1, big weights: 0 | |
| #small grads : 1144, big grads : 0 | |
| Conv layer 4 | |
| max L2 weights norm: 2.824525 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 992, big grads : 0 | |
| Conv layer 5 | |
| max L2 weights norm: 3.766861 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 862, big grads : 0 | |
| Linear layer 1 | |
| max L2 weights norm: 3.915259 | |
| #small weights: 41, big weights: 0 | |
| #small grads : 292320, big grads : 0 | |
| Linear layer 2 | |
| max L2 weights norm: 2.135637 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 31244, big grads : 0 | |
| Output layer | |
| max L2 weights norm: 1.538128 | |
| #small weights: 1, big weights: 0 | |
| #small grads : 3757, big grads : 0 | |
| train_confusion.totalValid: 0.039244538834951, prevTrainAcc: 0.036089199029126 | |
| ==> Train 114 | |
| [================================ 515/515 ===================================>] ETA: 0ms | Step: 693ms | |
| ======> Time to learn 1 iteration = 356.73 sec | |
| ======> Time to train 1 sample = 5.40 ms | |
| ======> Train CE error: 3.01 | |
| ======> Train accuracy: 33.255% | |
| Conv layer 1 | |
| max L2 weights norm: 2.264421 | |
| #small weights: 1, big weights: 0 | |
| #small grads : 77, big grads : 0 | |
| Conv layer 2 | |
| max L2 weights norm: 2.846607 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 4254, big grads : 0 | |
| Conv layer 3 | |
| max L2 weights norm: 3.038891 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 636, big grads : 0 | |
| Conv layer 4 | |
| max L2 weights norm: 3.229704 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 590, big grads : 0 | |
| Conv layer 5 | |
| max L2 weights norm: 3.786046 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 842, big grads : 0 | |
| Linear layer 1 | |
| max L2 weights norm: 3.940843 | |
| #small weights: 29, big weights: 0 | |
| #small grads : 30524, big grads : 0 | |
| Linear layer 2 | |
| max L2 weights norm: 2.142980 | |
| #small weights: 4, big weights: 0 | |
| #small grads : 13841, big grads : 0 | |
| Output layer | |
| max L2 weights norm: 1.444991 | |
| #small weights: 2, big weights: 0 | |
| #small grads : 16, big grads : 0 | |
| train_confusion.totalValid: 0.33255461165049, prevTrainAcc: 0.66914441747573 | |
| >>>>>>>>>>>>>>><<<<<<<<<<<<<<< | |
| >>> Drop in training > 50% <<< | |
| >>>>>>>>>>>>>>><<<<<<<<<<<<<<< | |
| ==> Train 115 | |
| [================================ 515/515 ===================================>] ETA: 0ms | Step: 693ms | |
| ======> Time to learn 1 iteration = 357.10 sec | |
| ======> Time to train 1 sample = 5.41 ms | |
| ======> Train CE error: 1.82 | |
| ======> Train accuracy: 69.974% | |
| Conv layer 1 | |
| max L2 weights norm: 1.847098 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 128, big grads : 0 | |
| Conv layer 2 | |
| max L2 weights norm: 2.777326 | |
| #small weights: 1, big weights: 0 | |
| #small grads : 3682, big grads : 0 | |
| Conv layer 3 | |
| max L2 weights norm: 3.028112 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 1339, big grads : 0 | |
| Conv layer 4 | |
| max L2 weights norm: 3.239054 | |
| #small weights: 1, big weights: 0 | |
| #small grads : 1234, big grads : 0 | |
| Conv layer 5 | |
| max L2 weights norm: 3.785908 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 886, big grads : 0 | |
| Linear layer 1 | |
| max L2 weights norm: 3.940366 | |
| #small weights: 46, big weights: 0 | |
| #small grads : 45391, big grads : 0 | |
| Linear layer 2 | |
| max L2 weights norm: 2.141491 | |
| #small weights: 1, big weights: 0 | |
| #small grads : 8998, big grads : 0 | |
| Output layer | |
| max L2 weights norm: 1.412055 | |
| #small weights: 0, big weights: 0 | |
| #small grads : 143, big grads : 0 | |
| train_confusion.totalValid: 0.69974211165049, prevTrainAcc: 0.33255461165049 |
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