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results_schedulers.txt
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Resnet18, lr : 0.0001, batch size : 8, trained_layers : 10, n_outputs : 30
train : Epoch 0 ,accuracy : 0.1358, time 9m 8s
train : Epoch 1 ,accuracy : 0.1649, time 7m 35s
train : Epoch 2 ,accuracy : 0.1941, time 7m 52s
train : Epoch 3 ,accuracy : 0.2330, time 8m 17s
train : Epoch 4 ,accuracy : 0.2522, time 7m 57s
train : Epoch 5 ,accuracy : 0.2409, time 7m 55s
train : Epoch 6 ,accuracy : 0.2432, time 8m 3s
train : Epoch 7 ,accuracy : 0.2733, time 7m 53s
train : Epoch 8 ,accuracy : 0.2888, time 7m 60s
train : Epoch 9 ,accuracy : 0.2754, time 7m 49s
train : Epoch 10 ,accuracy : 0.2791, time 8m 2s
train : Epoch 11 ,accuracy : 0.3014, time 8m 3s
train : Epoch 12 ,accuracy : 0.3152, time 7m 45s
train : Epoch 13 ,accuracy : 0.3097, time 7m 36s
train : Epoch 14 ,accuracy : 0.3091, time 7m 47s
train : Epoch 15 ,accuracy : 0.3317, time 8m 11s
train : Epoch 16 ,accuracy : 0.3381, time 7m 54s
train : Epoch 17 ,accuracy : 0.3343, time 8m 5s
train : Epoch 18 ,accuracy : 0.3362, time 8m 3s
train : Epoch 19 ,accuracy : 0.3535, time 7m 32s
val : Epoch 0 ,accuracy : 0.1788, time 0m 50s
val : Epoch 1 ,accuracy : 0.2163, time 0m 49s
val : Epoch 2 ,accuracy : 0.2456, time 0m 47s
val : Epoch 3 ,accuracy : 0.2761, time 0m 47s
val : Epoch 4 ,accuracy : 0.2740, time 0m 33s
val : Epoch 5 ,accuracy : 0.2591, time 0m 33s
val : Epoch 6 ,accuracy : 0.2798, time 0m 32s
val : Epoch 7 ,accuracy : 0.2946, time 0m 32s
val : Epoch 8 ,accuracy : 0.2849, time 0m 33s
val : Epoch 9 ,accuracy : 0.2812, time 0m 33s
val : Epoch 10 ,accuracy : 0.2923, time 0m 32s
val : Epoch 11 ,accuracy : 0.2942, time 0m 34s
val : Epoch 12 ,accuracy : 0.2946, time 0m 30s
val : Epoch 13 ,accuracy : 0.2907, time 0m 31s
val : Epoch 14 ,accuracy : 0.2916, time 0m 45s
val : Epoch 15 ,accuracy : 0.2933, time 0m 45s
val : Epoch 16 ,accuracy : 0.2961, time 0m 45s
val : Epoch 17 ,accuracy : 0.2904, time 0m 32s
val : Epoch 18 ,accuracy : 0.2902, time 0m 32s
val : Epoch 19 ,accuracy : 0.2974, time 0m 31s
Training complete in 171m 47s
Triangle2_Best val Acc: 0.297368
Resnet18, lr : 0.0001, batch size : 8, trained_layers : 10, n_outputs : 30
train : Epoch 0 ,accuracy : 0.1360, time 7m 36s
train : Epoch 1 ,accuracy : 0.1656, time 7m 31s
train : Epoch 2 ,accuracy : 0.1949, time 7m 33s
train : Epoch 3 ,accuracy : 0.2346, time 7m 34s
train : Epoch 4 ,accuracy : 0.2428, time 7m 34s
train : Epoch 5 ,accuracy : 0.2157, time 8m 8s
train : Epoch 6 ,accuracy : 0.2237, time 8m 5s
train : Epoch 7 ,accuracy : 0.2632, time 7m 49s
train : Epoch 8 ,accuracy : 0.2738, time 7m 54s
train : Epoch 9 ,accuracy : 0.2439, time 8m 7s
train : Epoch 10 ,accuracy : 0.2440, time 7m 59s
train : Epoch 11 ,accuracy : 0.2832, time 7m 55s
train : Epoch 12 ,accuracy : 0.2952, time 7m 52s
train : Epoch 13 ,accuracy : 0.2610, time 7m 56s
train : Epoch 14 ,accuracy : 0.2627, time 7m 46s
train : Epoch 15 ,accuracy : 0.2982, time 7m 52s
train : Epoch 16 ,accuracy : 0.3145, time 7m 48s
train : Epoch 17 ,accuracy : 0.2780, time 7m 44s
train : Epoch 18 ,accuracy : 0.2775, time 7m 53s
train : Epoch 19 ,accuracy : 0.3192, time 7m 54s
val : Epoch 0 ,accuracy : 0.1982, time 0m 44s
val : Epoch 1 ,accuracy : 0.1926, time 0m 31s
val : Epoch 2 ,accuracy : 0.2456, time 0m 31s
val : Epoch 3 ,accuracy : 0.2812, time 0m 31s
val : Epoch 4 ,accuracy : 0.2530, time 0m 30s
val : Epoch 5 ,accuracy : 0.2367, time 0m 46s
val : Epoch 6 ,accuracy : 0.2623, time 0m 45s
val : Epoch 7 ,accuracy : 0.2853, time 0m 45s
val : Epoch 8 ,accuracy : 0.2689, time 0m 34s
val : Epoch 9 ,accuracy : 0.2512, time 0m 33s
val : Epoch 10 ,accuracy : 0.2642, time 0m 33s
val : Epoch 11 ,accuracy : 0.2861, time 0m 32s
val : Epoch 12 ,accuracy : 0.2725, time 0m 32s
val : Epoch 13 ,accuracy : 0.2528, time 0m 44s
val : Epoch 14 ,accuracy : 0.2854, time 0m 32s
val : Epoch 15 ,accuracy : 0.2995, time 0m 32s
val : Epoch 16 ,accuracy : 0.2800, time 0m 32s
val : Epoch 17 ,accuracy : 0.2607, time 0m 32s
val : Epoch 18 ,accuracy : 0.2796, time 0m 32s
val : Epoch 19 ,accuracy : 0.3025, time 0m 32s
Training complete in 168m 12s
Triangle_Best val Acc: 0.302456
Resnet18, lr : 0.0001, batch size : 8, trained_layers : 10, n_outputs : 30
train : Epoch 0 ,accuracy : 0.1007, time 7m 27s
train : Epoch 1 ,accuracy : 0.1649, time 7m 21s
train : Epoch 2 ,accuracy : 0.1850, time 7m 9s
train : Epoch 3 ,accuracy : 0.2016, time 7m 22s
train : Epoch 4 ,accuracy : 0.2124, time 7m 20s
train : Epoch 5 ,accuracy : 0.2221, time 7m 16s
train : Epoch 6 ,accuracy : 0.2274, time 7m 15s
train : Epoch 7 ,accuracy : 0.2614, time 7m 17s
train : Epoch 8 ,accuracy : 0.2735, time 7m 12s
train : Epoch 9 ,accuracy : 0.2792, time 7m 12s
train : Epoch 10 ,accuracy : 0.2827, time 7m 11s
train : Epoch 11 ,accuracy : 0.2861, time 7m 11s
train : Epoch 12 ,accuracy : 0.2932, time 7m 26s
train : Epoch 13 ,accuracy : 0.2915, time 7m 31s
train : Epoch 14 ,accuracy : 0.2980, time 7m 32s
train : Epoch 15 ,accuracy : 0.3031, time 7m 41s
train : Epoch 16 ,accuracy : 0.3070, time 7m 48s
train : Epoch 17 ,accuracy : 0.3047, time 7m 33s
train : Epoch 18 ,accuracy : 0.3057, time 7m 42s
train : Epoch 19 ,accuracy : 0.3047, time 7m 41s
val : Epoch 0 ,accuracy : 0.1767, time 0m 44s
val : Epoch 1 ,accuracy : 0.2142, time 0m 28s
val : Epoch 2 ,accuracy : 0.2295, time 0m 27s
val : Epoch 3 ,accuracy : 0.2416, time 0m 28s
val : Epoch 4 ,accuracy : 0.2374, time 0m 34s
val : Epoch 5 ,accuracy : 0.2525, time 0m 29s
val : Epoch 6 ,accuracy : 0.2605, time 0m 30s
val : Epoch 7 ,accuracy : 0.2819, time 0m 29s
val : Epoch 8 ,accuracy : 0.2863, time 0m 29s
val : Epoch 9 ,accuracy : 0.2895, time 0m 29s
val : Epoch 10 ,accuracy : 0.2902, time 0m 29s
val : Epoch 11 ,accuracy : 0.2889, time 0m 30s
val : Epoch 12 ,accuracy : 0.2923, time 0m 31s
val : Epoch 13 ,accuracy : 0.2888, time 0m 32s
val : Epoch 14 ,accuracy : 0.2898, time 0m 32s
val : Epoch 15 ,accuracy : 0.2918, time 0m 32s
val : Epoch 16 ,accuracy : 0.2944, time 0m 30s
val : Epoch 17 ,accuracy : 0.2911, time 0m 30s
val : Epoch 18 ,accuracy : 0.2907, time 0m 31s
val : Epoch 19 ,accuracy : 0.2928, time 0m 31s
Training complete in 158m 23s
Exponential_Best val Acc: 0.294386