時間序列分類超參數調整實驗結果記錄【Part1】

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實驗平臺：

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ConvLSTM

cl2_filter	cl2_kernel	pool_size	drop_rate	d1_unit	d1_l2	batch_size	epochs
[128,256]	[(2,2)]	[(2,2)]	[0.3,0.4]	[64,128]	[0.001]	[64,128]	[42]

Epoch: 0, Average Metrics: loss= 0.9154, accuracy= 0.7449, val_loss= 0.5027, val_accuracy= 0.8452
........Epoch: 8, Average Metrics: loss= 0.2213, accuracy= 0.9345, val_loss= 0.2544, val_accuracy= 0.9220
........Epoch: 16, Average Metrics: loss= 0.1769, accuracy= 0.9426, val_loss= 0.1960, val_accuracy= 0.9413
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch: 24, Average Metrics: loss= 0.1191, accuracy= 0.9564, val_loss= 0.2662, val_accuracy= 0.9340
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch 00026: early stopping
Pass!

ID-1, Config:[256, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.3, 64, 0.001, 64, 42], mean_val_acc:0.9240, mean_val_loss:0.2654,
Epoch: 0, Average Metrics: loss= 1.0507, accuracy= 0.7130, val_loss= 0.4998, val_accuracy= 0.8412
........Epoch: 8, Average Metrics: loss= 0.2298, accuracy= 0.9333, val_loss= 0.2601, val_accuracy= 0.9215
........Epoch: 16, Average Metrics: loss= 0.1677, accuracy= 0.9477, val_loss= 0.1963, val_accuracy= 0.9404
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 24, Average Metrics: loss= 0.1449, accuracy= 0.9508, val_loss= 0.2430, val_accuracy= 0.9345
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
..Epoch: 32, Average Metrics: loss= 0.1123, accuracy= 0.9606, val_loss= 0.2058, val_accuracy= 0.9423
.....Epoch 00037: early stopping
Pass!

ID-2, Config:[256, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.3, 64, 0.001, 128, 42], mean_val_acc:0.9281, mean_val_loss:0.2536,
Epoch: 0, Average Metrics: loss= 0.9884, accuracy= 0.7464, val_loss= 0.5175, val_accuracy= 0.8616
........Epoch: 8, Average Metrics: loss= 0.2356, accuracy= 0.9304, val_loss= 0.3267, val_accuracy= 0.9126
........Epoch: 16, Average Metrics: loss= 0.1578, accuracy= 0.9458, val_loss= 0.1959, val_accuracy= 0.9421
....Epoch 00020: early stopping
Pass!

ID-3, Config:[256, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.3, 128, 0.001, 64, 42], mean_val_acc:0.9209, mean_val_loss:0.2909,
Epoch: 0, Average Metrics: loss= 1.1553, accuracy= 0.6999, val_loss= 0.6019, val_accuracy= 0.8437
........Epoch: 8, Average Metrics: loss= 0.2672, accuracy= 0.9285, val_loss= 0.3133, val_accuracy= 0.9225
........Epoch: 16, Average Metrics: loss= 0.1722, accuracy= 0.9480, val_loss= 0.2247, val_accuracy= 0.9333
....Epoch 00020: early stopping
Pass!

ID-4, Config:[256, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.3, 128, 0.001, 128, 42], mean_val_acc:0.9213, mean_val_loss:0.3067,
Epoch: 0, Average Metrics: loss= 0.9200, accuracy= 0.7408, val_loss= 0.4646, val_accuracy= 0.8707
........Epoch: 8, Average Metrics: loss= 0.2292, accuracy= 0.9339, val_loss= 0.2483, val_accuracy= 0.9254
........Epoch: 16, Average Metrics: loss= 0.1688, accuracy= 0.9463, val_loss= 0.2218, val_accuracy= 0.9401
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00020: early stopping
Pass!

ID-5, Config:[256, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.4, 64, 0.001, 64, 42], mean_val_acc:0.9226, mean_val_loss:0.2745,
Epoch: 0, Average Metrics: loss= 1.2378, accuracy= 0.6581, val_loss= 0.6243, val_accuracy= 0.8056
........Epoch: 8, Average Metrics: loss= 0.2561, accuracy= 0.9256, val_loss= 0.3027, val_accuracy= 0.9281
........Epoch: 16, Average Metrics: loss= 0.1760, accuracy= 0.9435, val_loss= 0.2591, val_accuracy= 0.9374
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch: 24, Average Metrics: loss= 0.1288, accuracy= 0.9570, val_loss= 0.2294, val_accuracy= 0.9521
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
Epoch 00026: early stopping
Pass!

ID-6, Config:[256, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.4, 64, 0.001, 128, 42], mean_val_acc:0.9234, mean_val_loss:0.2908,
Epoch: 0, Average Metrics: loss= 1.0402, accuracy= 0.7322, val_loss= 0.5664, val_accuracy= 0.8675
........Epoch: 8, Average Metrics: loss= 0.2374, accuracy= 0.9346, val_loss= 0.2730, val_accuracy= 0.9232
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 16, Average Metrics: loss= 0.1465, accuracy= 0.9522, val_loss= 0.2042, val_accuracy= 0.9480
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
...Epoch: 24, Average Metrics: loss= 0.1173, accuracy= 0.9598, val_loss= 0.2127, val_accuracy= 0.9519
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
.Epoch 00026: early stopping
Pass!

ID-7, Config:[256, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.4, 128, 0.001, 64, 42], mean_val_acc:0.9274, mean_val_loss:0.2794,
Epoch: 0, Average Metrics: loss= 1.2211, accuracy= 0.6864, val_loss= 0.6693, val_accuracy= 0.8194
........Epoch: 8, Average Metrics: loss= 0.2887, accuracy= 0.9256, val_loss= 0.3027, val_accuracy= 0.9232
........Epoch: 16, Average Metrics: loss= 0.1896, accuracy= 0.9439, val_loss= 0.2577, val_accuracy= 0.9229
........Epoch 00024: early stopping
Pass!

ID-8, Config:[256, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.4, 128, 0.001, 128, 42], mean_val_acc:0.9179, mean_val_loss:0.3181,
Epoch: 0, Average Metrics: loss= 0.8283, accuracy= 0.7724, val_loss= 0.4312, val_accuracy= 0.8825
........Epoch: 8, Average Metrics: loss= 0.2110, accuracy= 0.9382, val_loss= 0.2998, val_accuracy= 0.9063
.
Epoch 00009: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......Epoch: 16, Average Metrics: loss= 0.1321, accuracy= 0.9534, val_loss= 0.3177, val_accuracy= 0.9428
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
..Epoch: 24, Average Metrics: loss= 0.1022, accuracy= 0.9644, val_loss= 0.2959, val_accuracy= 0.9485
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0002500000205814874.
Epoch 00026: early stopping
Pass!

ID-9, Config:[256, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.3, 64, 0.001, 64, 42], mean_val_acc:0.9308, mean_val_loss:0.2805,
Epoch: 0, Average Metrics: loss= 1.0378, accuracy= 0.7141, val_loss= 0.5866, val_accuracy= 0.8442
........Epoch: 8, Average Metrics: loss= 0.2193, accuracy= 0.9348, val_loss= 0.2666, val_accuracy= 0.9293
........Epoch: 16, Average Metrics: loss= 0.1539, accuracy= 0.9490, val_loss= 0.2275, val_accuracy= 0.9438
.......
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 24, Average Metrics: loss= 0.1198, accuracy= 0.9585, val_loss= 0.1680, val_accuracy= 0.9544
.....
Epoch 00029: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch 00031: early stopping
Pass!

ID-10, Config:[256, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.3, 64, 0.001, 128, 42], mean_val_acc:0.9279, mean_val_loss:0.2529,
Epoch: 0, Average Metrics: loss= 0.9339, accuracy= 0.7670, val_loss= 0.5548, val_accuracy= 0.8751
........Epoch: 8, Average Metrics: loss= 0.2140, accuracy= 0.9356, val_loss= 0.2324, val_accuracy= 0.9333
....
Epoch 00012: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 16, Average Metrics: loss= 0.1389, accuracy= 0.9535, val_loss= 0.2284, val_accuracy= 0.9499
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
..Epoch: 24, Average Metrics: loss= 0.1038, accuracy= 0.9610, val_loss= 0.2427, val_accuracy= 0.9438
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0002500000205814874.
.Epoch 00027: early stopping
Pass!

ID-11, Config:[256, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.3, 128, 0.001, 64, 42], mean_val_acc:0.9290, mean_val_loss:0.2837,
Epoch: 0, Average Metrics: loss= 1.0925, accuracy= 0.7246, val_loss= 0.6053, val_accuracy= 0.8542
........Epoch: 8, Average Metrics: loss= 0.2402, accuracy= 0.9351, val_loss= 0.2991, val_accuracy= 0.9207
........Epoch: 16, Average Metrics: loss= 0.1672, accuracy= 0.9483, val_loss= 0.2424, val_accuracy= 0.9406
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00024: early stopping
Pass!

ID-12, Config:[256, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.3, 128, 0.001, 128, 42], mean_val_acc:0.9230, mean_val_loss:0.3033,
Epoch: 0, Average Metrics: loss= 0.9322, accuracy= 0.7505, val_loss= 0.4937, val_accuracy= 0.8528
........Epoch: 8, Average Metrics: loss= 0.2098, accuracy= 0.9382, val_loss= 0.2463, val_accuracy= 0.9355
........Epoch: 16, Average Metrics: loss= 0.1645, accuracy= 0.9485, val_loss= 0.2266, val_accuracy= 0.9396
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch: 24, Average Metrics: loss= 0.1144, accuracy= 0.9578, val_loss= 0.2070, val_accuracy= 0.9531
..Epoch 00026: early stopping
Pass!

ID-13, Config:[256, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.4, 64, 0.001, 64, 42], mean_val_acc:0.9292, mean_val_loss:0.2695,
Epoch: 0, Average Metrics: loss= 1.0637, accuracy= 0.7057, val_loss= 0.5320, val_accuracy= 0.8530
........Epoch: 8, Average Metrics: loss= 0.2483, accuracy= 0.9288, val_loss= 0.3053, val_accuracy= 0.9151
........Epoch: 16, Average Metrics: loss= 0.1754, accuracy= 0.9449, val_loss= 0.2115, val_accuracy= 0.9362
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1266, accuracy= 0.9554, val_loss= 0.2216, val_accuracy= 0.9463
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch 00030: early stopping
Pass!

ID-14, Config:[256, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.4, 64, 0.001, 128, 42], mean_val_acc:0.9271, mean_val_loss:0.2630,
Epoch: 0, Average Metrics: loss= 0.9648, accuracy= 0.7577, val_loss= 0.5260, val_accuracy= 0.8719
........Epoch: 8, Average Metrics: loss= 0.2199, accuracy= 0.9360, val_loss= 0.2924, val_accuracy= 0.9303
........Epoch: 16, Average Metrics: loss= 0.1737, accuracy= 0.9440, val_loss= 0.2101, val_accuracy= 0.9357
.......
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 24, Average Metrics: loss= 0.1230, accuracy= 0.9564, val_loss= 0.2415, val_accuracy= 0.9536
.Epoch 00025: early stopping
Pass!

ID-15, Config:[256, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.4, 128, 0.001, 64, 42], mean_val_acc:0.9283, mean_val_loss:0.2931,
Epoch: 0, Average Metrics: loss= 1.1209, accuracy= 0.7125, val_loss= 0.6713, val_accuracy= 0.8432
........Epoch: 8, Average Metrics: loss= 0.2387, accuracy= 0.9381, val_loss= 0.2981, val_accuracy= 0.9222
......
Epoch 00014: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 16, Average Metrics: loss= 0.1560, accuracy= 0.9523, val_loss= 0.2522, val_accuracy= 0.9379
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
......Epoch: 24, Average Metrics: loss= 0.1239, accuracy= 0.9587, val_loss= 0.2466, val_accuracy= 0.9487
.Epoch 00025: early stopping
Pass!

ID-16, Config:[256, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.4, 128, 0.001, 128, 42], mean_val_acc:0.9269, mean_val_loss:0.3168,
Epoch: 0, Average Metrics: loss= 0.7885, accuracy= 0.7747, val_loss= 0.9794, val_accuracy= 0.8213
........Epoch: 8, Average Metrics: loss= 0.2224, accuracy= 0.9285, val_loss= 0.2983, val_accuracy= 0.9225
........Epoch: 16, Average Metrics: loss= 0.1522, accuracy= 0.9479, val_loss= 0.2040, val_accuracy= 0.9308
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch 00022: early stopping
Pass!

ID-17, Config:[256, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.3, 64, 0.001, 64, 42], mean_val_acc:0.9257, mean_val_loss:0.2868,
Epoch: 0, Average Metrics: loss= 0.8754, accuracy= 0.7471, val_loss= 1.2586, val_accuracy= 0.7387
........Epoch: 8, Average Metrics: loss= 0.2306, accuracy= 0.9363, val_loss= 0.2851, val_accuracy= 0.9264
........Epoch: 16, Average Metrics: loss= 0.1671, accuracy= 0.9474, val_loss= 0.2358, val_accuracy= 0.9298
....Epoch 00020: early stopping
Pass!

ID-18, Config:[256, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.3, 64, 0.001, 128, 42], mean_val_acc:0.9143, mean_val_loss:0.3517,
Epoch: 0, Average Metrics: loss= 0.8509, accuracy= 0.7782, val_loss= 0.9684, val_accuracy= 0.8353
........Epoch: 8, Average Metrics: loss= 0.2299, accuracy= 0.9345, val_loss= 0.2509, val_accuracy= 0.9330
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 16, Average Metrics: loss= 0.1432, accuracy= 0.9523, val_loss= 0.1969, val_accuracy= 0.9406
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch: 24, Average Metrics: loss= 0.1095, accuracy= 0.9600, val_loss= 0.1770, val_accuracy= 0.9524
....Epoch 00028: early stopping
Pass!

ID-19, Config:[256, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.3, 128, 0.001, 64, 42], mean_val_acc:0.9287, mean_val_loss:0.2773,
Epoch: 0, Average Metrics: loss= 0.9031, accuracy= 0.7626, val_loss= 1.2605, val_accuracy= 0.7563
........Epoch: 8, Average Metrics: loss= 0.2553, accuracy= 0.9335, val_loss= 0.2591, val_accuracy= 0.9372
........Epoch: 16, Average Metrics: loss= 0.1647, accuracy= 0.9501, val_loss= 0.2007, val_accuracy= 0.9436
....Epoch 00020: early stopping
Pass!

ID-20, Config:[256, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.3, 128, 0.001, 128, 42], mean_val_acc:0.9193, mean_val_loss:0.3591,
Epoch: 0, Average Metrics: loss= 0.7657, accuracy= 0.7791, val_loss= 0.8870, val_accuracy= 0.8317
........Epoch: 8, Average Metrics: loss= 0.2258, accuracy= 0.9351, val_loss= 0.2436, val_accuracy= 0.9190
........Epoch 00016: early stopping
Pass!

ID-21, Config:[256, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.4, 64, 0.001, 64, 42], mean_val_acc:0.9216, mean_val_loss:0.2987,
Epoch: 0, Average Metrics: loss= 0.9441, accuracy= 0.7256, val_loss= 1.2358, val_accuracy= 0.7917
........Epoch: 8, Average Metrics: loss= 0.2394, accuracy= 0.9291, val_loss= 0.2657, val_accuracy= 0.9308
........Epoch: 16, Average Metrics: loss= 0.1749, accuracy= 0.9462, val_loss= 0.2011, val_accuracy= 0.9431
..Epoch 00018: early stopping
Pass!

ID-22, Config:[256, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.4, 64, 0.001, 128, 42], mean_val_acc:0.9107, mean_val_loss:0.3745,
Epoch: 0, Average Metrics: loss= 0.8804, accuracy= 0.7659, val_loss= 0.9277, val_accuracy= 0.7735
........Epoch: 8, Average Metrics: loss= 0.2660, accuracy= 0.9235, val_loss= 0.2639, val_accuracy= 0.9318
........Epoch: 16, Average Metrics: loss= 0.1723, accuracy= 0.9424, val_loss= 0.2275, val_accuracy= 0.9360
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch 00022: early stopping
Pass!

ID-23, Config:[256, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.4, 128, 0.001, 64, 42], mean_val_acc:0.9211, mean_val_loss:0.3071,
Epoch: 0, Average Metrics: loss= 0.9573, accuracy= 0.7437, val_loss= 1.2746, val_accuracy= 0.8032
........Epoch: 8, Average Metrics: loss= 0.2687, accuracy= 0.9318, val_loss= 0.3421, val_accuracy= 0.9207
........Epoch: 16, Average Metrics: loss= 0.1803, accuracy= 0.9477, val_loss= 0.2265, val_accuracy= 0.9389
....Epoch 00020: early stopping
Pass!

ID-24, Config:[256, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.4, 128, 0.001, 128, 42], mean_val_acc:0.9180, mean_val_loss:0.3837,
Epoch: 0, Average Metrics: loss= 0.7325, accuracy= 0.7886, val_loss= 0.8768, val_accuracy= 0.8491
........Epoch: 8, Average Metrics: loss= 0.2061, accuracy= 0.9366, val_loss= 0.2659, val_accuracy= 0.9117
........Epoch: 16, Average Metrics: loss= 0.1536, accuracy= 0.9486, val_loss= 0.2141, val_accuracy= 0.9406
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch: 24, Average Metrics: loss= 0.1147, accuracy= 0.9564, val_loss= 0.1652, val_accuracy= 0.9445
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch 00025: early stopping
Pass!

ID-25, Config:[256, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.3, 64, 0.001, 64, 42], mean_val_acc:0.9257, mean_val_loss:0.2743,
Epoch: 0, Average Metrics: loss= 0.8214, accuracy= 0.7610, val_loss= 1.1698, val_accuracy= 0.8385
........Epoch: 8, Average Metrics: loss= 0.2186, accuracy= 0.9404, val_loss= 0.2328, val_accuracy= 0.9391
........Epoch: 16, Average Metrics: loss= 0.1520, accuracy= 0.9506, val_loss= 0.2012, val_accuracy= 0.9490
.....Epoch 00021: early stopping
Pass!

ID-26, Config:[256, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.3, 64, 0.001, 128, 42], mean_val_acc:0.9255, mean_val_loss:0.3218,
Epoch: 0, Average Metrics: loss= 0.7956, accuracy= 0.7965, val_loss= 0.9141, val_accuracy= 0.8535
........Epoch: 8, Average Metrics: loss= 0.2161, accuracy= 0.9398, val_loss= 0.2630, val_accuracy= 0.9347
........Epoch: 16, Average Metrics: loss= 0.1627, accuracy= 0.9476, val_loss= 0.2613, val_accuracy= 0.9249
....Epoch 00020: early stopping
Pass!

ID-27, Config:[256, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.3, 128, 0.001, 64, 42], mean_val_acc:0.9237, mean_val_loss:0.3023,
Epoch: 0, Average Metrics: loss= 0.8730, accuracy= 0.7796, val_loss= 1.2577, val_accuracy= 0.7995
........Epoch: 8, Average Metrics: loss= 0.2445, accuracy= 0.9387, val_loss= 0.2780, val_accuracy= 0.9389
........Epoch: 16, Average Metrics: loss= 0.1579, accuracy= 0.9525, val_loss= 0.2454, val_accuracy= 0.9440
...Epoch 00019: early stopping
Pass!

ID-28, Config:[256, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.3, 128, 0.001, 128, 42], mean_val_acc:0.9173, mean_val_loss:0.3772,
Epoch: 0, Average Metrics: loss= 0.7857, accuracy= 0.7813, val_loss= 0.8419, val_accuracy= 0.8339
........Epoch: 8, Average Metrics: loss= 0.2157, accuracy= 0.9359, val_loss= 0.2615, val_accuracy= 0.9355
........Epoch: 16, Average Metrics: loss= 0.1502, accuracy= 0.9488, val_loss= 0.2039, val_accuracy= 0.9448
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1218, accuracy= 0.9566, val_loss= 0.1854, val_accuracy= 0.9413
.Epoch 00025: early stopping
Pass!

ID-29, Config:[256, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.4, 64, 0.001, 64, 42], mean_val_acc:0.9276, mean_val_loss:0.2735,
Epoch: 0, Average Metrics: loss= 0.8542, accuracy= 0.7604, val_loss= 1.1241, val_accuracy= 0.7816
........Epoch: 8, Average Metrics: loss= 0.2206, accuracy= 0.9381, val_loss= 0.2747, val_accuracy= 0.9323
........Epoch: 16, Average Metrics: loss= 0.2087, accuracy= 0.9368, val_loss= 0.2411, val_accuracy= 0.9328
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00023: early stopping
Pass!

ID-30, Config:[256, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.4, 64, 0.001, 128, 42], mean_val_acc:0.9234, mean_val_loss:0.3188,
Epoch: 0, Average Metrics: loss= 0.8404, accuracy= 0.7906, val_loss= 0.8545, val_accuracy= 0.8496
........Epoch: 8, Average Metrics: loss= 0.2398, accuracy= 0.9339, val_loss= 0.2677, val_accuracy= 0.9264
........Epoch: 16, Average Metrics: loss= 0.1627, accuracy= 0.9452, val_loss= 0.2333, val_accuracy= 0.9411
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch: 24, Average Metrics: loss= 0.1146, accuracy= 0.9576, val_loss= 0.1708, val_accuracy= 0.9485
..Epoch 00026: early stopping
Pass!

ID-31, Config:[256, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.4, 128, 0.001, 64, 42], mean_val_acc:0.9310, mean_val_loss:0.2906,
Epoch: 0, Average Metrics: loss= 0.9301, accuracy= 0.7643, val_loss= 1.1971, val_accuracy= 0.8162
........Epoch: 8, Average Metrics: loss= 0.2692, accuracy= 0.9333, val_loss= 0.2894, val_accuracy= 0.9279
........Epoch: 16, Average Metrics: loss= 0.1766, accuracy= 0.9479, val_loss= 0.2158, val_accuracy= 0.9448
........Epoch: 24, Average Metrics: loss= 0.1343, accuracy= 0.9546, val_loss= 0.2203, val_accuracy= 0.9433
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00025: early stopping
Pass!

ID-32, Config:[256, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.4, 128, 0.001, 128, 42], mean_val_acc:0.9236, mean_val_loss:0.3357,
Epoch: 0, Average Metrics: loss= 0.9023, accuracy= 0.7533, val_loss= 0.4610, val_accuracy= 0.8665
........Epoch: 8, Average Metrics: loss= 0.2116, accuracy= 0.9353, val_loss= 0.2409, val_accuracy= 0.9279
........Epoch: 16, Average Metrics: loss= 0.1633, accuracy= 0.9459, val_loss= 0.2608, val_accuracy= 0.9411
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch: 24, Average Metrics: loss= 0.1055, accuracy= 0.9637, val_loss= 0.1897, val_accuracy= 0.9492
.Epoch 00025: early stopping
Pass!

ID-33, Config:[512, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.3, 64, 0.001, 64, 42], mean_val_acc:0.9270, mean_val_loss:0.2636,
Epoch: 0, Average Metrics: loss= 0.9901, accuracy= 0.7240, val_loss= 0.4973, val_accuracy= 0.8336
........Epoch: 8, Average Metrics: loss= 0.2256, accuracy= 0.9358, val_loss= 0.2389, val_accuracy= 0.9347
........Epoch: 16, Average Metrics: loss= 0.1592, accuracy= 0.9481, val_loss= 0.2215, val_accuracy= 0.9342
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch 00023: early stopping
Pass!

ID-34, Config:[512, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.3, 64, 0.001, 128, 42], mean_val_acc:0.9265, mean_val_loss:0.2665,
Epoch: 0, Average Metrics: loss= 0.9183, accuracy= 0.7678, val_loss= 0.5120, val_accuracy= 0.8537
........Epoch: 8, Average Metrics: loss= 0.2130, accuracy= 0.9384, val_loss= 0.2555, val_accuracy= 0.9330
..
Epoch 00010: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch: 16, Average Metrics: loss= 0.1349, accuracy= 0.9554, val_loss= 0.2384, val_accuracy= 0.9406
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
Epoch: 24, Average Metrics: loss= 0.1106, accuracy= 0.9616, val_loss= 0.2138, val_accuracy= 0.9512
..Epoch 00026: early stopping
Pass!

ID-35, Config:[512, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.3, 128, 0.001, 64, 42], mean_val_acc:0.9286, mean_val_loss:0.2749,
Epoch: 0, Average Metrics: loss= 1.0727, accuracy= 0.7280, val_loss= 0.5680, val_accuracy= 0.8528
........Epoch: 8, Average Metrics: loss= 0.2677, accuracy= 0.9275, val_loss= 0.2749, val_accuracy= 0.9279
........Epoch: 16, Average Metrics: loss= 0.1784, accuracy= 0.9457, val_loss= 0.2436, val_accuracy= 0.9377
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
......Epoch 00023: early stopping
Pass!

ID-36, Config:[512, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.3, 128, 0.001, 128, 42], mean_val_acc:0.9227, mean_val_loss:0.2881,
Epoch: 0, Average Metrics: loss= 0.9559, accuracy= 0.7392, val_loss= 0.4935, val_accuracy= 0.8452
........Epoch: 8, Average Metrics: loss= 0.2221, accuracy= 0.9339, val_loss= 0.2499, val_accuracy= 0.9261
........Epoch: 16, Average Metrics: loss= 0.1493, accuracy= 0.9515, val_loss= 0.2130, val_accuracy= 0.9480
........Epoch: 24, Average Metrics: loss= 0.1271, accuracy= 0.9576, val_loss= 0.2170, val_accuracy= 0.9463
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....
Epoch 00029: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch 00031: early stopping
Pass!

ID-37, Config:[512, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.4, 64, 0.001, 64, 42], mean_val_acc:0.9311, mean_val_loss:0.2653,
Epoch: 0, Average Metrics: loss= 1.0885, accuracy= 0.7020, val_loss= 0.5253, val_accuracy= 0.8510
........Epoch: 8, Average Metrics: loss= 0.2193, accuracy= 0.9375, val_loss= 0.2693, val_accuracy= 0.9345
........Epoch: 16, Average Metrics: loss= 0.1702, accuracy= 0.9473, val_loss= 0.2439, val_accuracy= 0.9283
...Epoch 00019: early stopping
Pass!

ID-38, Config:[512, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.4, 64, 0.001, 128, 42], mean_val_acc:0.9179, mean_val_loss:0.2939,
Epoch: 0, Average Metrics: loss= 0.9327, accuracy= 0.7582, val_loss= 0.5519, val_accuracy= 0.8513
........Epoch: 8, Average Metrics: loss= 0.2473, accuracy= 0.9332, val_loss= 0.2626, val_accuracy= 0.9325
........Epoch: 16, Average Metrics: loss= 0.1633, accuracy= 0.9497, val_loss= 0.2041, val_accuracy= 0.9428
..Epoch 00018: early stopping
Pass!

ID-39, Config:[512, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.4, 128, 0.001, 64, 42], mean_val_acc:0.9233, mean_val_loss:0.2989,
Epoch: 0, Average Metrics: loss= 1.0714, accuracy= 0.7220, val_loss= 0.5655, val_accuracy= 0.8486
........Epoch: 8, Average Metrics: loss= 0.2618, accuracy= 0.9331, val_loss= 0.2747, val_accuracy= 0.9288
........Epoch: 16, Average Metrics: loss= 0.1648, accuracy= 0.9479, val_loss= 0.2599, val_accuracy= 0.9460
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 24, Average Metrics: loss= 0.1362, accuracy= 0.9579, val_loss= 0.1965, val_accuracy= 0.9517
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch 00027: early stopping
Pass!

ID-40, Config:[512, (1, 2), 'relu', False, 128, (2, 2), (2, 2), 0.4, 128, 0.001, 128, 42], mean_val_acc:0.9284, mean_val_loss:0.2854,
Epoch: 0, Average Metrics: loss= 0.8248, accuracy= 0.7705, val_loss= 0.4593, val_accuracy= 0.8829
........Epoch: 8, Average Metrics: loss= 0.2020, accuracy= 0.9403, val_loss= 0.2216, val_accuracy= 0.9355
........Epoch: 16, Average Metrics: loss= 0.1414, accuracy= 0.9516, val_loss= 0.2060, val_accuracy= 0.9433
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00019: early stopping
Pass!

ID-41, Config:[512, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.3, 64, 0.001, 64, 42], mean_val_acc:0.9227, mean_val_loss:0.2798,
Epoch: 0, Average Metrics: loss= 0.9345, accuracy= 0.7443, val_loss= 0.5651, val_accuracy= 0.8692
........Epoch: 8, Average Metrics: loss= 0.2305, accuracy= 0.9275, val_loss= 0.2386, val_accuracy= 0.9190
.....
Epoch 00013: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch: 16, Average Metrics: loss= 0.1391, accuracy= 0.9545, val_loss= 0.2418, val_accuracy= 0.9396
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
......
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
Epoch: 24, Average Metrics: loss= 0.1127, accuracy= 0.9588, val_loss= 0.2316, val_accuracy= 0.9438
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0002500000205814874.
.Epoch 00029: early stopping
Pass!

ID-42, Config:[512, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.3, 64, 0.001, 128, 42], mean_val_acc:0.9270, mean_val_loss:0.2821,
Epoch: 0, Average Metrics: loss= 0.8832, accuracy= 0.7845, val_loss= 0.5292, val_accuracy= 0.8771
........Epoch: 8, Average Metrics: loss= 0.2107, accuracy= 0.9392, val_loss= 0.2440, val_accuracy= 0.9298
........Epoch: 16, Average Metrics: loss= 0.1474, accuracy= 0.9501, val_loss= 0.2229, val_accuracy= 0.9318
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 24, Average Metrics: loss= 0.1118, accuracy= 0.9596, val_loss= 0.2519, val_accuracy= 0.9460
.Epoch 00025: early stopping
Pass!

ID-43, Config:[512, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.3, 128, 0.001, 64, 42], mean_val_acc:0.9278, mean_val_loss:0.2780,
Epoch: 0, Average Metrics: loss= 0.9881, accuracy= 0.7572, val_loss= 0.5373, val_accuracy= 0.8756
........Epoch: 8, Average Metrics: loss= 0.2547, accuracy= 0.9301, val_loss= 0.2609, val_accuracy= 0.9347
........Epoch: 16, Average Metrics: loss= 0.1551, accuracy= 0.9503, val_loss= 0.3066, val_accuracy= 0.9261
........Epoch: 24, Average Metrics: loss= 0.1375, accuracy= 0.9539, val_loss= 0.1787, val_accuracy= 0.9504
.Epoch 00025: early stopping
Pass!

ID-44, Config:[512, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.3, 128, 0.001, 128, 42], mean_val_acc:0.9301, mean_val_loss:0.2722,
Epoch: 0, Average Metrics: loss= 0.8567, accuracy= 0.7699, val_loss= 0.4290, val_accuracy= 0.8697
........Epoch: 8, Average Metrics: loss= 0.2175, accuracy= 0.9318, val_loss= 0.2360, val_accuracy= 0.9286
........Epoch: 16, Average Metrics: loss= 0.1401, accuracy= 0.9501, val_loss= 0.2275, val_accuracy= 0.9156
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......Epoch: 24, Average Metrics: loss= 0.1198, accuracy= 0.9580, val_loss= 0.1914, val_accuracy= 0.9480
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch 00026: early stopping
Pass!

ID-45, Config:[512, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.4, 64, 0.001, 64, 42], mean_val_acc:0.9254, mean_val_loss:0.2641,
Epoch: 0, Average Metrics: loss= 0.9740, accuracy= 0.7383, val_loss= 0.5464, val_accuracy= 0.8550
........Epoch: 8, Average Metrics: loss= 0.2321, accuracy= 0.9322, val_loss= 0.2678, val_accuracy= 0.9271
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1719, accuracy= 0.9481, val_loss= 0.2100, val_accuracy= 0.9443
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
...Epoch: 24, Average Metrics: loss= 0.1172, accuracy= 0.9600, val_loss= 0.2051, val_accuracy= 0.9524
.......Epoch 00031: early stopping
Pass!

ID-46, Config:[512, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.4, 64, 0.001, 128, 42], mean_val_acc:0.9308, mean_val_loss:0.2631,
Epoch: 0, Average Metrics: loss= 0.9458, accuracy= 0.7655, val_loss= 0.5762, val_accuracy= 0.8631
........Epoch: 8, Average Metrics: loss= 0.2243, accuracy= 0.9343, val_loss= 0.2842, val_accuracy= 0.9227
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 16, Average Metrics: loss= 0.1460, accuracy= 0.9513, val_loss= 0.2397, val_accuracy= 0.9333
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch: 24, Average Metrics: loss= 0.1280, accuracy= 0.9550, val_loss= 0.2006, val_accuracy= 0.9490
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
..Epoch 00030: early stopping
Pass!

ID-47, Config:[512, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.4, 128, 0.001, 64, 42], mean_val_acc:0.9283, mean_val_loss:0.2785,
Epoch: 0, Average Metrics: loss= 1.0610, accuracy= 0.7260, val_loss= 0.6366, val_accuracy= 0.8285
........Epoch: 8, Average Metrics: loss= 0.2604, accuracy= 0.9291, val_loss= 0.3100, val_accuracy= 0.9261
........Epoch: 16, Average Metrics: loss= 0.1780, accuracy= 0.9486, val_loss= 0.2297, val_accuracy= 0.9382
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch 00024: early stopping
Pass!

ID-48, Config:[512, (1, 2), 'relu', False, 256, (2, 2), (2, 2), 0.4, 128, 0.001, 128, 42], mean_val_acc:0.9236, mean_val_loss:0.3182,
Epoch: 0, Average Metrics: loss= 0.7641, accuracy= 0.7835, val_loss= 0.8217, val_accuracy= 0.8243
........Epoch: 8, Average Metrics: loss= 0.2188, accuracy= 0.9363, val_loss= 0.2941, val_accuracy= 0.9193
........Epoch: 16, Average Metrics: loss= 0.1525, accuracy= 0.9490, val_loss= 0.3509, val_accuracy= 0.9347
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 24, Average Metrics: loss= 0.1163, accuracy= 0.9580, val_loss= 0.2044, val_accuracy= 0.9333
......Epoch 00030: early stopping
Pass!

ID-49, Config:[512, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.3, 64, 0.001, 64, 42], mean_val_acc:0.9276, mean_val_loss:0.2631,
Epoch: 0, Average Metrics: loss= 0.8137, accuracy= 0.7646, val_loss= 1.1676, val_accuracy= 0.7526
........Epoch: 8, Average Metrics: loss= 0.2341, accuracy= 0.9346, val_loss= 0.2607, val_accuracy= 0.9389
........Epoch: 16, Average Metrics: loss= 0.1611, accuracy= 0.9509, val_loss= 0.2033, val_accuracy= 0.9362
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00019: early stopping
Pass!

ID-50, Config:[512, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.3, 64, 0.001, 128, 42], mean_val_acc:0.9108, mean_val_loss:0.3462,
Epoch: 0, Average Metrics: loss= 0.8208, accuracy= 0.7953, val_loss= 0.7983, val_accuracy= 0.8142
........Epoch: 8, Average Metrics: loss= 0.2389, accuracy= 0.9358, val_loss= 0.2582, val_accuracy= 0.9320
........Epoch: 16, Average Metrics: loss= 0.1604, accuracy= 0.9474, val_loss= 0.2796, val_accuracy= 0.9384
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
......Epoch 00023: early stopping
Pass!

ID-51, Config:[512, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.3, 128, 0.001, 64, 42], mean_val_acc:0.9250, mean_val_loss:0.2938,
Epoch: 0, Average Metrics: loss= 0.8577, accuracy= 0.7779, val_loss= 1.1696, val_accuracy= 0.7644
........Epoch: 8, Average Metrics: loss= 0.2585, accuracy= 0.9390, val_loss= 0.3008, val_accuracy= 0.9286
........Epoch: 16, Average Metrics: loss= 0.1723, accuracy= 0.9490, val_loss= 0.2097, val_accuracy= 0.9438
........Epoch: 24, Average Metrics: loss= 0.1393, accuracy= 0.9548, val_loss= 0.1779, val_accuracy= 0.9433
.....
Epoch 00029: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00029: early stopping
Pass!

ID-52, Config:[512, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.3, 128, 0.001, 128, 42], mean_val_acc:0.9255, mean_val_loss:0.3151,
Epoch: 0, Average Metrics: loss= 0.8171, accuracy= 0.7692, val_loss= 0.7504, val_accuracy= 0.8650
........Epoch: 8, Average Metrics: loss= 0.2238, accuracy= 0.9361, val_loss= 0.3154, val_accuracy= 0.9217
........Epoch: 16, Average Metrics: loss= 0.1826, accuracy= 0.9436, val_loss= 0.2073, val_accuracy= 0.9404
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 24, Average Metrics: loss= 0.1341, accuracy= 0.9503, val_loss= 0.1802, val_accuracy= 0.9480
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch: 32, Average Metrics: loss= 0.0974, accuracy= 0.9624, val_loss= 0.1816, val_accuracy= 0.9504
..
Epoch 00034: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
..Epoch 00036: early stopping
Pass!

ID-53, Config:[512, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.4, 64, 0.001, 64, 42], mean_val_acc:0.9338, mean_val_loss:0.2511,
Epoch: 0, Average Metrics: loss= 0.8576, accuracy= 0.7595, val_loss= 1.1392, val_accuracy= 0.8481
........Epoch: 8, Average Metrics: loss= 0.2370, accuracy= 0.9358, val_loss= 0.2706, val_accuracy= 0.9325
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1588, accuracy= 0.9532, val_loss= 0.1874, val_accuracy= 0.9465
........Epoch: 24, Average Metrics: loss= 0.1318, accuracy= 0.9568, val_loss= 0.2611, val_accuracy= 0.9404
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch 00027: early stopping
Pass!

ID-54, Config:[512, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.4, 64, 0.001, 128, 42], mean_val_acc:0.9281, mean_val_loss:0.3064,
Epoch: 0, Average Metrics: loss= 0.8777, accuracy= 0.7724, val_loss= 0.9086, val_accuracy= 0.8346
........Epoch: 8, Average Metrics: loss= 0.2629, accuracy= 0.9286, val_loss= 0.3025, val_accuracy= 0.9269
........Epoch: 16, Average Metrics: loss= 0.1880, accuracy= 0.9447, val_loss= 0.2337, val_accuracy= 0.9394
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 24, Average Metrics: loss= 0.1179, accuracy= 0.9592, val_loss= 0.1786, val_accuracy= 0.9499
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch 00029: early stopping
Pass!

ID-55, Config:[512, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.4, 128, 0.001, 64, 42], mean_val_acc:0.9278, mean_val_loss:0.2885,
Epoch: 0, Average Metrics: loss= 0.9278, accuracy= 0.7562, val_loss= 1.2631, val_accuracy= 0.7499
........Epoch: 8, Average Metrics: loss= 0.2766, accuracy= 0.9344, val_loss= 0.2995, val_accuracy= 0.9416
........Epoch: 16, Average Metrics: loss= 0.1777, accuracy= 0.9491, val_loss= 0.2169, val_accuracy= 0.9472
...Epoch 00019: early stopping
Pass!

ID-56, Config:[512, (1, 2), 'relu', True, 128, (2, 2), (2, 2), 0.4, 128, 0.001, 128, 42], mean_val_acc:0.9178, mean_val_loss:0.3881,
Epoch: 0, Average Metrics: loss= 0.7332, accuracy= 0.7976, val_loss= 0.8255, val_accuracy= 0.8164
........Epoch: 8, Average Metrics: loss= 0.2051, accuracy= 0.9385, val_loss= 0.2281, val_accuracy= 0.9416
........Epoch: 16, Average Metrics: loss= 0.1421, accuracy= 0.9519, val_loss= 0.2128, val_accuracy= 0.9396
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00018: early stopping
Pass!

ID-57, Config:[512, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.3, 64, 0.001, 64, 42], mean_val_acc:0.9218, mean_val_loss:0.3030,
Epoch: 0, Average Metrics: loss= 0.7606, accuracy= 0.7910, val_loss= 1.1209, val_accuracy= 0.7649
........Epoch: 8, Average Metrics: loss= 0.2084, accuracy= 0.9406, val_loss= 0.2370, val_accuracy= 0.9421
........Epoch: 16, Average Metrics: loss= 0.1794, accuracy= 0.9445, val_loss= 0.1996, val_accuracy= 0.9448
........Epoch: 24, Average Metrics: loss= 0.1323, accuracy= 0.9531, val_loss= 0.1985, val_accuracy= 0.9487
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch 00027: early stopping
Pass!

ID-58, Config:[512, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.3, 64, 0.001, 128, 42], mean_val_acc:0.9225, mean_val_loss:0.2957,
Epoch: 0, Average Metrics: loss= 0.8142, accuracy= 0.8001, val_loss= 0.8450, val_accuracy= 0.8709
........Epoch: 8, Average Metrics: loss= 0.2334, accuracy= 0.9338, val_loss= 0.2528, val_accuracy= 0.9259
........Epoch: 16, Average Metrics: loss= 0.1710, accuracy= 0.9455, val_loss= 0.2039, val_accuracy= 0.9448
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch: 24, Average Metrics: loss= 0.1174, accuracy= 0.9573, val_loss= 0.1950, val_accuracy= 0.9436
.Epoch 00025: early stopping
Pass!

ID-59, Config:[512, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.3, 128, 0.001, 64, 42], mean_val_acc:0.9273, mean_val_loss:0.2994,
Epoch: 0, Average Metrics: loss= 0.8952, accuracy= 0.7794, val_loss= 1.1694, val_accuracy= 0.8150
........Epoch: 8, Average Metrics: loss= 0.2510, accuracy= 0.9384, val_loss= 0.2767, val_accuracy= 0.9242
........Epoch: 16, Average Metrics: loss= 0.1631, accuracy= 0.9509, val_loss= 0.2587, val_accuracy= 0.9279
.....Epoch 00021: early stopping
Pass!

ID-60, Config:[512, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.3, 128, 0.001, 128, 42], mean_val_acc:0.9211, mean_val_loss:0.3572,
Epoch: 0, Average Metrics: loss= 0.7898, accuracy= 0.7887, val_loss= 0.8771, val_accuracy= 0.8653
........Epoch: 8, Average Metrics: loss= 0.2313, accuracy= 0.9330, val_loss= 0.2699, val_accuracy= 0.9207
........Epoch: 16, Average Metrics: loss= 0.1571, accuracy= 0.9470, val_loss= 0.2196, val_accuracy= 0.9391
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch 00022: early stopping
Pass!

ID-61, Config:[512, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.4, 64, 0.001, 64, 42], mean_val_acc:0.9253, mean_val_loss:0.2938,
Epoch: 0, Average Metrics: loss= 0.8255, accuracy= 0.7684, val_loss= 1.0921, val_accuracy= 0.7867
........Epoch: 8, Average Metrics: loss= 0.2279, accuracy= 0.9370, val_loss= 0.2928, val_accuracy= 0.9301
........Epoch: 16, Average Metrics: loss= 0.1664, accuracy= 0.9501, val_loss= 0.2313, val_accuracy= 0.9413
....Epoch 00020: early stopping
Pass!

ID-62, Config:[512, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.4, 64, 0.001, 128, 42], mean_val_acc:0.9239, mean_val_loss:0.3353,
Epoch: 0, Average Metrics: loss= 0.8694, accuracy= 0.7880, val_loss= 0.9595, val_accuracy= 0.8692
........Epoch: 8, Average Metrics: loss= 0.2609, accuracy= 0.9304, val_loss= 0.2858, val_accuracy= 0.9296
........Epoch: 16, Average Metrics: loss= 0.1882, accuracy= 0.9432, val_loss= 0.2459, val_accuracy= 0.9401
........Epoch: 24, Average Metrics: loss= 0.1523, accuracy= 0.9495, val_loss= 0.2107, val_accuracy= 0.9389
.Epoch 00025: early stopping
Pass!

ID-63, Config:[512, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.4, 128, 0.001, 64, 42], mean_val_acc:0.9280, mean_val_loss:0.3100,
Epoch: 0, Average Metrics: loss= 0.8794, accuracy= 0.7863, val_loss= 1.2416, val_accuracy= 0.8093
........Epoch: 8, Average Metrics: loss= 0.2801, accuracy= 0.9330, val_loss= 0.3669, val_accuracy= 0.9168
........Epoch: 16, Average Metrics: loss= 0.1764, accuracy= 0.9479, val_loss= 0.2145, val_accuracy= 0.9418
....Epoch 00020: early stopping
Pass!

ID-64, Config:[512, (1, 2), 'relu', True, 256, (2, 2), (2, 2), 0.4, 128, 0.001, 128, 42], mean_val_acc:0.9185, mean_val_loss:0.3820,
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---

DeepConvLSTM

c1_filter	c1_kernel	c2_filter	c2_kernel	bn	lstm_units	d1_unit	drop1_rate	d2_unit	drop2_rate	batch_size	epochs	optimizer
[256]	[2]	[64,128]	[2,3]	[False]	[64,128]	[64,128]	[0.3]	[64]	[0.3]	[64,128]	[42]	[‘adam’,‘rmsprop’]

Epoch: 0, Average Metrics: loss= 1.2281, accuracy= 0.6385, val_loss= 0.6134, val_accuracy= 0.8388
........Epoch: 8, Average Metrics: loss= 0.2999, accuracy= 0.9129, val_loss= 0.2710, val_accuracy= 0.9205
........Epoch: 16, Average Metrics: loss= 0.2375, accuracy= 0.9241, val_loss= 0.2055, val_accuracy= 0.9333
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch: 24, Average Metrics: loss= 0.1966, accuracy= 0.9349, val_loss= 0.1882, val_accuracy= 0.9394
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch 00025: early stopping
Pass!

ID-1, Config:[256, 2, 64, 2, False, 64, 64, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9098, mean_val_loss:0.2869,
Epoch: 0, Average Metrics: loss= 1.1797, accuracy= 0.6685, val_loss= 0.8296, val_accuracy= 0.7661
........Epoch: 8, Average Metrics: loss= 0.2961, accuracy= 0.9096, val_loss= 0.2441, val_accuracy= 0.9225
.....
Epoch 00013: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch: 16, Average Metrics: loss= 0.1847, accuracy= 0.9398, val_loss= 0.2305, val_accuracy= 0.9325
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
......Epoch: 24, Average Metrics: loss= 0.1361, accuracy= 0.9561, val_loss= 0.1703, val_accuracy= 0.9512
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
.Epoch 00029: early stopping
Pass!

ID-2, Config:[256, 2, 64, 2, False, 64, 64, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9137, mean_val_loss:0.2822,
Epoch: 0, Average Metrics: loss= 1.3441, accuracy= 0.6000, val_loss= 0.7114, val_accuracy= 0.8108
........Epoch: 8, Average Metrics: loss= 0.3247, accuracy= 0.9078, val_loss= 0.3248, val_accuracy= 0.9009
......
Epoch 00014: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 16, Average Metrics: loss= 0.2252, accuracy= 0.9317, val_loss= 0.2146, val_accuracy= 0.9276
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.....Epoch: 24, Average Metrics: loss= 0.1635, accuracy= 0.9544, val_loss= 0.3008, val_accuracy= 0.9136
........
Epoch 00032: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
Epoch: 32, Average Metrics: loss= 0.1404, accuracy= 0.9561, val_loss= 0.1625, val_accuracy= 0.9521
..Epoch 00034: early stopping
Pass!

ID-3, Config:[256, 2, 64, 2, False, 64, 64, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9180, mean_val_loss:0.2764,
Epoch: 0, Average Metrics: loss= 1.3471, accuracy= 0.5937, val_loss= 0.7340, val_accuracy= 0.8054
........Epoch: 8, Average Metrics: loss= 0.3284, accuracy= 0.8993, val_loss= 0.3131, val_accuracy= 0.9102
........Epoch: 16, Average Metrics: loss= 0.2395, accuracy= 0.9230, val_loss= 0.2265, val_accuracy= 0.9264
........Epoch: 24, Average Metrics: loss= 0.1889, accuracy= 0.9386, val_loss= 0.1884, val_accuracy= 0.9301
.....Epoch 00029: early stopping
Pass!

ID-4, Config:[256, 2, 64, 2, False, 64, 64, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9110, mean_val_loss:0.2937,
Epoch: 0, Average Metrics: loss= 1.1518, accuracy= 0.6967, val_loss= 0.7942, val_accuracy= 0.8000
........Epoch: 8, Average Metrics: loss= 0.2822, accuracy= 0.9151, val_loss= 0.2915, val_accuracy= 0.9082
........Epoch: 16, Average Metrics: loss= 0.2389, accuracy= 0.9218, val_loss= 0.2185, val_accuracy= 0.9308
........Epoch: 24, Average Metrics: loss= 0.1907, accuracy= 0.9355, val_loss= 0.1929, val_accuracy= 0.9335
....Epoch 00028: early stopping
Pass!

ID-5, Config:[256, 2, 64, 2, False, 64, 128, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9075, mean_val_loss:0.3025,
Epoch: 0, Average Metrics: loss= 1.2299, accuracy= 0.6616, val_loss= 0.7309, val_accuracy= 0.8130
........Epoch: 8, Average Metrics: loss= 0.2791, accuracy= 0.9170, val_loss= 0.2858, val_accuracy= 0.9001
........Epoch: 16, Average Metrics: loss= 0.1937, accuracy= 0.9415, val_loss= 0.2367, val_accuracy= 0.9333
........Epoch: 24, Average Metrics: loss= 0.1682, accuracy= 0.9505, val_loss= 0.2337, val_accuracy= 0.9254
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch 00032: early stopping
Pass!

ID-6, Config:[256, 2, 64, 2, False, 64, 128, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9170, mean_val_loss:0.2825,
Epoch: 0, Average Metrics: loss= 1.3625, accuracy= 0.6379, val_loss= 0.7055, val_accuracy= 0.8309
........Epoch: 8, Average Metrics: loss= 0.3750, accuracy= 0.8931, val_loss= 0.3039, val_accuracy= 0.9067
......Epoch 00014: early stopping
Pass!

ID-7, Config:[256, 2, 64, 2, False, 64, 128, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.8854, mean_val_loss:0.4074,
Epoch: 0, Average Metrics: loss= 1.3220, accuracy= 0.6557, val_loss= 0.7765, val_accuracy= 0.7767
........Epoch: 8, Average Metrics: loss= 0.3373, accuracy= 0.9007, val_loss= 0.3196, val_accuracy= 0.9045
........Epoch: 16, Average Metrics: loss= 0.2321, accuracy= 0.9249, val_loss= 0.2070, val_accuracy= 0.9357
........Epoch: 24, Average Metrics: loss= 0.1964, accuracy= 0.9360, val_loss= 0.1983, val_accuracy= 0.9497
........Epoch: 32, Average Metrics: loss= 0.1629, accuracy= 0.9492, val_loss= 0.1875, val_accuracy= 0.9433
...Epoch 00035: early stopping
Pass!

ID-8, Config:[256, 2, 64, 2, False, 64, 128, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9120, mean_val_loss:0.2974,
Epoch: 0, Average Metrics: loss= 1.1901, accuracy= 0.6596, val_loss= 0.5851, val_accuracy= 0.8361
........Epoch: 8, Average Metrics: loss= 0.3023, accuracy= 0.9086, val_loss= 0.3076, val_accuracy= 0.9016
........Epoch: 16, Average Metrics: loss= 0.2320, accuracy= 0.9273, val_loss= 0.2544, val_accuracy= 0.9266
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00024: early stopping
Pass!

ID-9, Config:[256, 2, 64, 2, False, 128, 64, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9087, mean_val_loss:0.2960,
Epoch: 0, Average Metrics: loss= 1.1551, accuracy= 0.6727, val_loss= 0.6354, val_accuracy= 0.8145
........Epoch: 8, Average Metrics: loss= 0.2944, accuracy= 0.9115, val_loss= 0.4668, val_accuracy= 0.8780
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 16, Average Metrics: loss= 0.1847, accuracy= 0.9442, val_loss= 0.1805, val_accuracy= 0.9475
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
...Epoch: 24, Average Metrics: loss= 0.1285, accuracy= 0.9559, val_loss= 0.1861, val_accuracy= 0.9492
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
..Epoch 00027: early stopping
Pass!

ID-10, Config:[256, 2, 64, 2, False, 128, 64, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9089, mean_val_loss:0.3082,
Epoch: 0, Average Metrics: loss= 1.3159, accuracy= 0.6177, val_loss= 0.7258, val_accuracy= 0.8147
........Epoch: 8, Average Metrics: loss= 0.3271, accuracy= 0.9063, val_loss= 0.2714, val_accuracy= 0.9210
........Epoch: 16, Average Metrics: loss= 0.2263, accuracy= 0.9301, val_loss= 0.2526, val_accuracy= 0.9168
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 24, Average Metrics: loss= 0.1823, accuracy= 0.9407, val_loss= 0.1865, val_accuracy= 0.9298
.Epoch 00025: early stopping
Pass!

ID-11, Config:[256, 2, 64, 2, False, 128, 64, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9073, mean_val_loss:0.3091,
Epoch: 0, Average Metrics: loss= 1.3898, accuracy= 0.5950, val_loss= 0.8160, val_accuracy= 0.7588
........Epoch: 8, Average Metrics: loss= 0.3392, accuracy= 0.8972, val_loss= 0.3863, val_accuracy= 0.8829
........Epoch: 16, Average Metrics: loss= 0.2426, accuracy= 0.9236, val_loss= 0.2148, val_accuracy= 0.9333
........Epoch: 24, Average Metrics: loss= 0.1992, accuracy= 0.9355, val_loss= 0.1684, val_accuracy= 0.9465
.....
Epoch 00029: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch: 32, Average Metrics: loss= 0.1426, accuracy= 0.9490, val_loss= 0.1685, val_accuracy= 0.9526
.Epoch 00033: early stopping
Pass!

ID-12, Config:[256, 2, 64, 2, False, 128, 64, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9097, mean_val_loss:0.2955,
Epoch: 0, Average Metrics: loss= 1.1600, accuracy= 0.6955, val_loss= 0.6725, val_accuracy= 0.8331
........Epoch: 8, Average Metrics: loss= 0.3280, accuracy= 0.9049, val_loss= 0.3038, val_accuracy= 0.9090
........Epoch: 16, Average Metrics: loss= 0.2090, accuracy= 0.9426, val_loss= 0.2308, val_accuracy= 0.9323
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1518, accuracy= 0.9512, val_loss= 0.1846, val_accuracy= 0.9401
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.....Epoch: 32, Average Metrics: loss= 0.1330, accuracy= 0.9529, val_loss= 0.1644, val_accuracy= 0.9423
.Epoch 00033: early stopping
Pass!

ID-13, Config:[256, 2, 64, 2, False, 128, 128, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9191, mean_val_loss:0.2749,
Epoch: 0, Average Metrics: loss= 1.2466, accuracy= 0.6731, val_loss= 0.6666, val_accuracy= 0.8309
........Epoch: 8, Average Metrics: loss= 0.2829, accuracy= 0.9155, val_loss= 0.2845, val_accuracy= 0.9033
........Epoch: 16, Average Metrics: loss= 0.2119, accuracy= 0.9378, val_loss= 0.1987, val_accuracy= 0.9453
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 24, Average Metrics: loss= 0.1512, accuracy= 0.9522, val_loss= 0.1855, val_accuracy= 0.9445
...Epoch 00027: early stopping
Pass!

ID-14, Config:[256, 2, 64, 2, False, 128, 128, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9161, mean_val_loss:0.2910,
Epoch: 0, Average Metrics: loss= 1.2808, accuracy= 0.6637, val_loss= 0.6657, val_accuracy= 0.8375
........Epoch: 8, Average Metrics: loss= 0.3124, accuracy= 0.9196, val_loss= 0.3013, val_accuracy= 0.9139
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1946, accuracy= 0.9474, val_loss= 0.2029, val_accuracy= 0.9404
.......
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch: 24, Average Metrics: loss= 0.1601, accuracy= 0.9476, val_loss= 0.1886, val_accuracy= 0.9433
...Epoch 00027: early stopping
Pass!

ID-15, Config:[256, 2, 64, 2, False, 128, 128, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9176, mean_val_loss:0.2984,
Epoch: 0, Average Metrics: loss= 1.3534, accuracy= 0.6259, val_loss= 0.7861, val_accuracy= 0.7728
........Epoch: 8, Average Metrics: loss= 0.3296, accuracy= 0.9037, val_loss= 0.3313, val_accuracy= 0.8893
...
Epoch 00011: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch: 16, Average Metrics: loss= 0.1975, accuracy= 0.9356, val_loss= 0.1951, val_accuracy= 0.9379
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
...Epoch: 24, Average Metrics: loss= 0.1456, accuracy= 0.9500, val_loss= 0.2019, val_accuracy= 0.9440
....Epoch 00028: early stopping
Pass!

ID-16, Config:[256, 2, 64, 2, False, 128, 128, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9109, mean_val_loss:0.3038,
Epoch: 0, Average Metrics: loss= 1.2068, accuracy= 0.6422, val_loss= 0.6084, val_accuracy= 0.8388
........Epoch: 8, Average Metrics: loss= 0.3309, accuracy= 0.9016, val_loss= 0.2833, val_accuracy= 0.9060
........Epoch: 16, Average Metrics: loss= 0.2101, accuracy= 0.9339, val_loss= 0.2000, val_accuracy= 0.9308
........Epoch: 24, Average Metrics: loss= 0.1953, accuracy= 0.9371, val_loss= 0.1987, val_accuracy= 0.9333
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......Epoch: 32, Average Metrics: loss= 0.1397, accuracy= 0.9542, val_loss= 0.1828, val_accuracy= 0.9423
..
Epoch 00034: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch 00036: early stopping
Pass!

ID-17, Config:[256, 2, 64, 3, False, 64, 64, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9143, mean_val_loss:0.2739,
Epoch: 0, Average Metrics: loss= 1.2312, accuracy= 0.6514, val_loss= 1.0800, val_accuracy= 0.7212
........Epoch: 8, Average Metrics: loss= 0.2912, accuracy= 0.9087, val_loss= 0.2457, val_accuracy= 0.9114
........Epoch: 16, Average Metrics: loss= 0.2012, accuracy= 0.9359, val_loss= 0.2494, val_accuracy= 0.9296
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch: 24, Average Metrics: loss= 0.1284, accuracy= 0.9568, val_loss= 0.1799, val_accuracy= 0.9485
.Epoch 00025: early stopping
Pass!

ID-18, Config:[256, 2, 64, 3, False, 64, 64, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9099, mean_val_loss:0.3089,
Epoch: 0, Average Metrics: loss= 1.3818, accuracy= 0.5917, val_loss= 0.7913, val_accuracy= 0.7934
........Epoch: 8, Average Metrics: loss= 0.3917, accuracy= 0.8824, val_loss= 0.3283, val_accuracy= 0.8967
........Epoch: 16, Average Metrics: loss= 0.2428, accuracy= 0.9266, val_loss= 0.2395, val_accuracy= 0.9193
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch: 24, Average Metrics: loss= 0.2018, accuracy= 0.9301, val_loss= 0.2013, val_accuracy= 0.9399
.......
Epoch 00031: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch: 32, Average Metrics: loss= 0.1512, accuracy= 0.9502, val_loss= 0.1784, val_accuracy= 0.9440
..Epoch 00034: early stopping
Pass!

ID-19, Config:[256, 2, 64, 3, False, 64, 64, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9087, mean_val_loss:0.2940,
Epoch: 0, Average Metrics: loss= 1.3601, accuracy= 0.6016, val_loss= 0.8650, val_accuracy= 0.7443
........Epoch: 8, Average Metrics: loss= 0.3648, accuracy= 0.8924, val_loss= 0.3435, val_accuracy= 0.8977
........Epoch: 16, Average Metrics: loss= 0.2484, accuracy= 0.9224, val_loss= 0.2649, val_accuracy= 0.8991
.......
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 24, Average Metrics: loss= 0.1703, accuracy= 0.9458, val_loss= 0.2363, val_accuracy= 0.9261
.......
Epoch 00031: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch: 32, Average Metrics: loss= 0.1304, accuracy= 0.9547, val_loss= 0.2357, val_accuracy= 0.9276
....
Epoch 00036: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
....
Epoch 00040: ReduceLROnPlateau reducing learning rate to 0.0002500000205814874.
Epoch: 40, Average Metrics: loss= 0.1017, accuracy= 0.9633, val_loss= 0.1920, val_accuracy= 0.9472
.Epoch 00041: early stopping
Pass!

ID-20, Config:[256, 2, 64, 3, False, 64, 64, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9099, mean_val_loss:0.2992,
Epoch: 0, Average Metrics: loss= 1.2288, accuracy= 0.6668, val_loss= 0.6877, val_accuracy= 0.7865
........Epoch: 8, Average Metrics: loss= 0.3079, accuracy= 0.9075, val_loss= 0.3246, val_accuracy= 0.9040
........Epoch: 16, Average Metrics: loss= 0.2798, accuracy= 0.9097, val_loss= 0.2842, val_accuracy= 0.9121
.......Epoch 00023: early stopping
Pass!

ID-21, Config:[256, 2, 64, 3, False, 64, 128, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9016, mean_val_loss:0.3223,
Epoch: 0, Average Metrics: loss= 1.2477, accuracy= 0.6657, val_loss= 0.7766, val_accuracy= 0.7867
........Epoch: 8, Average Metrics: loss= 0.2964, accuracy= 0.9080, val_loss= 0.3144, val_accuracy= 0.8923
..
Epoch 00010: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
......Epoch: 16, Average Metrics: loss= 0.1768, accuracy= 0.9446, val_loss= 0.2071, val_accuracy= 0.9259
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.....
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
.Epoch 00023: early stopping
Pass!

ID-22, Config:[256, 2, 64, 3, False, 64, 128, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9024, mean_val_loss:0.3376,
Epoch: 0, Average Metrics: loss= 1.3300, accuracy= 0.6534, val_loss= 0.7777, val_accuracy= 0.8334
........Epoch: 8, Average Metrics: loss= 0.3655, accuracy= 0.9018, val_loss= 0.3499, val_accuracy= 0.8969
........Epoch: 16, Average Metrics: loss= 0.2357, accuracy= 0.9299, val_loss= 0.2461, val_accuracy= 0.9129
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 24, Average Metrics: loss= 0.1627, accuracy= 0.9480, val_loss= 0.1888, val_accuracy= 0.9467
........Epoch: 32, Average Metrics: loss= 0.1585, accuracy= 0.9500, val_loss= 0.2131, val_accuracy= 0.9269
..
Epoch 00034: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
......
Epoch 00040: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
Epoch 00040: early stopping
Pass!

ID-23, Config:[256, 2, 64, 3, False, 64, 128, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9192, mean_val_loss:0.2825,
Epoch: 0, Average Metrics: loss= 1.3946, accuracy= 0.6262, val_loss= 0.8507, val_accuracy= 0.7757
........Epoch: 8, Average Metrics: loss= 0.3537, accuracy= 0.8983, val_loss= 0.2985, val_accuracy= 0.9050
........Epoch: 16, Average Metrics: loss= 0.2383, accuracy= 0.9228, val_loss= 0.2898, val_accuracy= 0.9065
........Epoch: 24, Average Metrics: loss= 0.1867, accuracy= 0.9432, val_loss= 0.2698, val_accuracy= 0.8979
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch 00029: early stopping
Pass!

ID-24, Config:[256, 2, 64, 3, False, 64, 128, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9033, mean_val_loss:0.3349,
Epoch: 0, Average Metrics: loss= 1.2593, accuracy= 0.6198, val_loss= 0.7142, val_accuracy= 0.7953
........Epoch: 8, Average Metrics: loss= 0.3396, accuracy= 0.9019, val_loss= 0.2879, val_accuracy= 0.9033
........Epoch: 16, Average Metrics: loss= 0.2196, accuracy= 0.9339, val_loss= 0.2216, val_accuracy= 0.9335
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1975, accuracy= 0.9387, val_loss= 0.2112, val_accuracy= 0.9347
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....
Epoch 00032: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
Epoch: 32, Average Metrics: loss= 0.1226, accuracy= 0.9598, val_loss= 0.1571, val_accuracy= 0.9546
..Epoch 00034: early stopping
Pass!

ID-25, Config:[256, 2, 64, 3, False, 128, 64, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9175, mean_val_loss:0.2648,
Epoch: 0, Average Metrics: loss= 1.2183, accuracy= 0.6555, val_loss= 0.6619, val_accuracy= 0.8005
........Epoch: 8, Average Metrics: loss= 0.3015, accuracy= 0.9070, val_loss= 0.2970, val_accuracy= 0.9092
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 16, Average Metrics: loss= 0.1871, accuracy= 0.9411, val_loss= 0.1836, val_accuracy= 0.9467
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
...Epoch: 24, Average Metrics: loss= 0.1339, accuracy= 0.9562, val_loss= 0.1739, val_accuracy= 0.9428
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
Epoch 00027: early stopping
Pass!

ID-26, Config:[256, 2, 64, 3, False, 128, 64, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9088, mean_val_loss:0.3055,
Epoch: 0, Average Metrics: loss= 1.3703, accuracy= 0.5940, val_loss= 0.6537, val_accuracy= 0.8272
........Epoch: 8, Average Metrics: loss= 0.3220, accuracy= 0.9103, val_loss= 0.3007, val_accuracy= 0.9067
........Epoch: 16, Average Metrics: loss= 0.2408, accuracy= 0.9293, val_loss= 0.2722, val_accuracy= 0.9315
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch: 24, Average Metrics: loss= 0.1471, accuracy= 0.9566, val_loss= 0.1810, val_accuracy= 0.9497
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
..Epoch: 32, Average Metrics: loss= 0.1324, accuracy= 0.9572, val_loss= 0.2052, val_accuracy= 0.9436
......
Epoch 00038: ReduceLROnPlateau reducing learning rate to 0.0002500000205814874.
..Epoch: 40, Average Metrics: loss= 0.1246, accuracy= 0.9544, val_loss= 0.2006, val_accuracy= 0.9450
..
Epoch 00042: ReduceLROnPlateau reducing learning rate to 0.00017677670369307936.
Pass!

ID-27, Config:[256, 2, 64, 3, False, 128, 64, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9233, mean_val_loss:0.2600,
Epoch: 0, Average Metrics: loss= 1.3877, accuracy= 0.5911, val_loss= 0.9156, val_accuracy= 0.7097
........Epoch: 8, Average Metrics: loss= 0.3514, accuracy= 0.8961, val_loss= 0.3583, val_accuracy= 0.9006
........Epoch: 16, Average Metrics: loss= 0.2346, accuracy= 0.9238, val_loss= 0.2129, val_accuracy= 0.9323
........Epoch: 24, Average Metrics: loss= 0.1874, accuracy= 0.9401, val_loss= 0.1885, val_accuracy= 0.9362
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch 00032: early stopping
Pass!

ID-28, Config:[256, 2, 64, 3, False, 128, 64, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9083, mean_val_loss:0.3001,
Epoch: 0, Average Metrics: loss= 1.1699, accuracy= 0.7023, val_loss= 0.6765, val_accuracy= 0.8402
........Epoch: 8, Average Metrics: loss= 0.3204, accuracy= 0.9021, val_loss= 0.3586, val_accuracy= 0.9082
........Epoch: 16, Average Metrics: loss= 0.2068, accuracy= 0.9373, val_loss= 0.2501, val_accuracy= 0.9283
........Epoch: 24, Average Metrics: loss= 0.2132, accuracy= 0.9313, val_loss= 0.2466, val_accuracy= 0.9227
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch 00028: early stopping
Pass!

ID-29, Config:[256, 2, 64, 3, False, 128, 128, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9135, mean_val_loss:0.2932,
Epoch: 0, Average Metrics: loss= 1.2442, accuracy= 0.6615, val_loss= 0.7779, val_accuracy= 0.7784
........Epoch: 8, Average Metrics: loss= 0.2989, accuracy= 0.9110, val_loss= 0.2916, val_accuracy= 0.9151
......
Epoch 00014: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 16, Average Metrics: loss= 0.1750, accuracy= 0.9437, val_loss= 0.2211, val_accuracy= 0.9325
........Epoch: 24, Average Metrics: loss= 0.1463, accuracy= 0.9516, val_loss= 0.2056, val_accuracy= 0.9470
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch 00025: early stopping
Pass!

ID-30, Config:[256, 2, 64, 3, False, 128, 128, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9032, mean_val_loss:0.3382,
Epoch: 0, Average Metrics: loss= 1.3042, accuracy= 0.6587, val_loss= 0.7495, val_accuracy= 0.8221
........Epoch: 8, Average Metrics: loss= 0.3331, accuracy= 0.9080, val_loss= 0.3472, val_accuracy= 0.9048
........Epoch: 16, Average Metrics: loss= 0.2410, accuracy= 0.9236, val_loss= 0.2542, val_accuracy= 0.9146
........Epoch: 24, Average Metrics: loss= 0.1864, accuracy= 0.9419, val_loss= 0.2207, val_accuracy= 0.9283
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch: 32, Average Metrics: loss= 0.1362, accuracy= 0.9539, val_loss= 0.1751, val_accuracy= 0.9413
.Epoch 00033: early stopping
Pass!

ID-31, Config:[256, 2, 64, 3, False, 128, 128, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9150, mean_val_loss:0.2881,
Epoch: 0, Average Metrics: loss= 1.4843, accuracy= 0.5790, val_loss= 0.9935, val_accuracy= 0.7183
........Epoch: 8, Average Metrics: loss= 0.3427, accuracy= 0.8990, val_loss= 0.3146, val_accuracy= 0.9001
....
Epoch 00012: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 16, Average Metrics: loss= 0.2016, accuracy= 0.9370, val_loss= 0.2203, val_accuracy= 0.9384
........Epoch: 24, Average Metrics: loss= 0.1628, accuracy= 0.9455, val_loss= 0.2366, val_accuracy= 0.9342
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch: 32, Average Metrics: loss= 0.1268, accuracy= 0.9558, val_loss= 0.1753, val_accuracy= 0.9458
..Epoch 00034: early stopping
Pass!

ID-32, Config:[256, 2, 64, 3, False, 128, 128, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9122, mean_val_loss:0.3173,
Epoch: 0, Average Metrics: loss= 1.1504, accuracy= 0.6574, val_loss= 0.6376, val_accuracy= 0.7931
........Epoch: 8, Average Metrics: loss= 0.2838, accuracy= 0.9098, val_loss= 0.2494, val_accuracy= 0.9276
.....
Epoch 00013: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch: 16, Average Metrics: loss= 0.2001, accuracy= 0.9363, val_loss= 0.2685, val_accuracy= 0.9180
.......
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch: 24, Average Metrics: loss= 0.1466, accuracy= 0.9535, val_loss= 0.1565, val_accuracy= 0.9465
.....
Epoch 00029: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
Epoch 00029: early stopping
Pass!

ID-33, Config:[256, 2, 128, 2, False, 64, 64, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9165, mean_val_loss:0.2684,
Epoch: 0, Average Metrics: loss= 1.2026, accuracy= 0.6618, val_loss= 0.6104, val_accuracy= 0.8331
........Epoch: 8, Average Metrics: loss= 0.2811, accuracy= 0.9165, val_loss= 0.2636, val_accuracy= 0.9134
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 16, Average Metrics: loss= 0.1623, accuracy= 0.9483, val_loss= 0.1792, val_accuracy= 0.9455
.....Epoch 00021: early stopping
Pass!

ID-34, Config:[256, 2, 128, 2, False, 64, 64, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9085, mean_val_loss:0.3518,
Epoch: 0, Average Metrics: loss= 1.3121, accuracy= 0.6152, val_loss= 0.6660, val_accuracy= 0.8226
........Epoch: 8, Average Metrics: loss= 0.3015, accuracy= 0.9163, val_loss= 0.2864, val_accuracy= 0.9121
........Epoch: 16, Average Metrics: loss= 0.2142, accuracy= 0.9400, val_loss= 0.2131, val_accuracy= 0.9306
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1786, accuracy= 0.9425, val_loss= 0.2018, val_accuracy= 0.9367
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
......Epoch 00032: early stopping
Pass!

ID-35, Config:[256, 2, 128, 2, False, 64, 64, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9190, mean_val_loss:0.2734,
Epoch: 0, Average Metrics: loss= 1.3431, accuracy= 0.6112, val_loss= 0.7063, val_accuracy= 0.8145
........Epoch: 8, Average Metrics: loss= 0.3301, accuracy= 0.9024, val_loss= 0.2816, val_accuracy= 0.9082
........Epoch: 16, Average Metrics: loss= 0.2226, accuracy= 0.9293, val_loss= 0.2296, val_accuracy= 0.9202
..Epoch 00018: early stopping
Pass!

ID-36, Config:[256, 2, 128, 2, False, 64, 64, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.8923, mean_val_loss:0.3646,
Epoch: 0, Average Metrics: loss= 1.1862, accuracy= 0.6844, val_loss= 0.7696, val_accuracy= 0.7838
........Epoch: 8, Average Metrics: loss= 0.2899, accuracy= 0.9143, val_loss= 0.2751, val_accuracy= 0.9144
........Epoch: 16, Average Metrics: loss= 0.1980, accuracy= 0.9430, val_loss= 0.2488, val_accuracy= 0.9080
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00023: early stopping
Pass!

ID-37, Config:[256, 2, 128, 2, False, 64, 128, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9111, mean_val_loss:0.3062,
Epoch: 0, Average Metrics: loss= 1.2022, accuracy= 0.6786, val_loss= 0.7820, val_accuracy= 0.7853
........Epoch: 8, Average Metrics: loss= 0.2800, accuracy= 0.9156, val_loss= 0.2487, val_accuracy= 0.9178
........Epoch: 16, Average Metrics: loss= 0.1934, accuracy= 0.9417, val_loss= 0.2431, val_accuracy= 0.9264
........Epoch: 24, Average Metrics: loss= 0.1827, accuracy= 0.9450, val_loss= 0.1711, val_accuracy= 0.9377
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 32, Average Metrics: loss= 0.1269, accuracy= 0.9577, val_loss= 0.1764, val_accuracy= 0.9458
..
Epoch 00034: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch 00036: early stopping
Pass!

ID-38, Config:[256, 2, 128, 2, False, 64, 128, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9191, mean_val_loss:0.2678,
Epoch: 0, Average Metrics: loss= 1.3102, accuracy= 0.6592, val_loss= 0.6887, val_accuracy= 0.8456
........Epoch: 8, Average Metrics: loss= 0.3227, accuracy= 0.9121, val_loss= 0.3441, val_accuracy= 0.9033
........Epoch: 16, Average Metrics: loss= 0.2434, accuracy= 0.9202, val_loss= 0.2784, val_accuracy= 0.9144
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1973, accuracy= 0.9322, val_loss= 0.1994, val_accuracy= 0.9330
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch: 32, Average Metrics: loss= 0.1332, accuracy= 0.9559, val_loss= 0.1700, val_accuracy= 0.9433
.Epoch 00033: early stopping
Pass!

ID-39, Config:[256, 2, 128, 2, False, 64, 128, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9147, mean_val_loss:0.2904,
Epoch: 0, Average Metrics: loss= 1.3471, accuracy= 0.6439, val_loss= 0.8460, val_accuracy= 0.8044
........Epoch: 8, Average Metrics: loss= 0.3119, accuracy= 0.9081, val_loss= 0.2920, val_accuracy= 0.9072
........Epoch: 16, Average Metrics: loss= 0.2048, accuracy= 0.9340, val_loss= 0.2477, val_accuracy= 0.9217
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 24, Average Metrics: loss= 0.1493, accuracy= 0.9514, val_loss= 0.1737, val_accuracy= 0.9421
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch 00030: early stopping
Pass!

ID-40, Config:[256, 2, 128, 2, False, 64, 128, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9124, mean_val_loss:0.3017,
Epoch: 0, Average Metrics: loss= 1.1345, accuracy= 0.6748, val_loss= 0.6050, val_accuracy= 0.8402
........Epoch: 8, Average Metrics: loss= 0.3130, accuracy= 0.9052, val_loss= 0.3048, val_accuracy= 0.9011
........Epoch: 16, Average Metrics: loss= 0.2021, accuracy= 0.9377, val_loss= 0.2074, val_accuracy= 0.9401
........Epoch: 24, Average Metrics: loss= 0.1941, accuracy= 0.9398, val_loss= 0.1853, val_accuracy= 0.9411
...Epoch 00027: early stopping
Pass!

ID-41, Config:[256, 2, 128, 2, False, 128, 64, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9073, mean_val_loss:0.3015,
Epoch: 0, Average Metrics: loss= 1.2306, accuracy= 0.6437, val_loss= 0.6343, val_accuracy= 0.8245
........Epoch: 8, Average Metrics: loss= 0.2859, accuracy= 0.9098, val_loss= 0.2739, val_accuracy= 0.9102
........Epoch: 16, Average Metrics: loss= 0.1997, accuracy= 0.9401, val_loss= 0.2556, val_accuracy= 0.9217
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 24, Average Metrics: loss= 0.1359, accuracy= 0.9514, val_loss= 0.2785, val_accuracy= 0.9232
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
Epoch 00030: early stopping
Pass!

ID-42, Config:[256, 2, 128, 2, False, 128, 64, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9129, mean_val_loss:0.3123,
Epoch: 0, Average Metrics: loss= 1.2267, accuracy= 0.6464, val_loss= 0.6602, val_accuracy= 0.8363
........Epoch: 8, Average Metrics: loss= 0.3231, accuracy= 0.9051, val_loss= 0.3713, val_accuracy= 0.8839
........Epoch 00016: early stopping
Pass!

ID-43, Config:[256, 2, 128, 2, False, 128, 64, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.8981, mean_val_loss:0.3436,
Epoch: 0, Average Metrics: loss= 1.3478, accuracy= 0.6132, val_loss= 0.6861, val_accuracy= 0.8162
........Epoch: 8, Average Metrics: loss= 0.3353, accuracy= 0.8997, val_loss= 0.3911, val_accuracy= 0.8690
........Epoch: 16, Average Metrics: loss= 0.2216, accuracy= 0.9291, val_loss= 0.2308, val_accuracy= 0.9342
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1497, accuracy= 0.9489, val_loss= 0.1752, val_accuracy= 0.9497
.....
Epoch 00029: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch 00031: early stopping
Pass!

ID-44, Config:[256, 2, 128, 2, False, 128, 64, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9096, mean_val_loss:0.3024,
Epoch: 0, Average Metrics: loss= 1.1722, accuracy= 0.6846, val_loss= 0.6344, val_accuracy= 0.8498
........Epoch: 8, Average Metrics: loss= 0.3021, accuracy= 0.9137, val_loss= 0.3815, val_accuracy= 0.8901
........Epoch: 16, Average Metrics: loss= 0.2346, accuracy= 0.9285, val_loss= 0.2413, val_accuracy= 0.9325
........Epoch: 24, Average Metrics: loss= 0.1656, accuracy= 0.9490, val_loss= 0.2539, val_accuracy= 0.9036
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....
Epoch 00031: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch: 32, Average Metrics: loss= 0.1186, accuracy= 0.9580, val_loss= 0.1638, val_accuracy= 0.9497
.Epoch 00033: early stopping
Pass!

ID-45, Config:[256, 2, 128, 2, False, 128, 128, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9163, mean_val_loss:0.2798,
Epoch: 0, Average Metrics: loss= 1.2294, accuracy= 0.6818, val_loss= 0.6609, val_accuracy= 0.8439
........Epoch: 8, Average Metrics: loss= 0.2696, accuracy= 0.9184, val_loss= 0.2614, val_accuracy= 0.9136
........Epoch: 16, Average Metrics: loss= 0.1929, accuracy= 0.9403, val_loss= 0.2809, val_accuracy= 0.9104
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch: 24, Average Metrics: loss= 0.1461, accuracy= 0.9518, val_loss= 0.1919, val_accuracy= 0.9431
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch 00030: early stopping
Pass!

ID-46, Config:[256, 2, 128, 2, False, 128, 128, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9130, mean_val_loss:0.2893,
Epoch: 0, Average Metrics: loss= 1.2494, accuracy= 0.6787, val_loss= 0.8228, val_accuracy= 0.7944
........Epoch: 8, Average Metrics: loss= 0.3042, accuracy= 0.9153, val_loss= 0.2905, val_accuracy= 0.9087
........Epoch: 16, Average Metrics: loss= 0.2368, accuracy= 0.9302, val_loss= 0.2793, val_accuracy= 0.9134
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch 00024: early stopping
Pass!

ID-47, Config:[256, 2, 128, 2, False, 128, 128, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9084, mean_val_loss:0.3197,
Epoch: 0, Average Metrics: loss= 1.4262, accuracy= 0.6273, val_loss= 1.0873, val_accuracy= 0.7144
........Epoch: 8, Average Metrics: loss= 0.3263, accuracy= 0.9036, val_loss= 0.5403, val_accuracy= 0.8501
........Epoch: 16, Average Metrics: loss= 0.2397, accuracy= 0.9252, val_loss= 0.2222, val_accuracy= 0.9237
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1558, accuracy= 0.9472, val_loss= 0.2330, val_accuracy= 0.9345
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
..Epoch: 32, Average Metrics: loss= 0.1230, accuracy= 0.9565, val_loss= 0.1796, val_accuracy= 0.9413
.......
Epoch 00039: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
.Epoch: 40, Average Metrics: loss= 0.1023, accuracy= 0.9637, val_loss= 0.2081, val_accuracy= 0.9431
..Epoch 00042: early stopping
Pass!

ID-48, Config:[256, 2, 128, 2, False, 128, 128, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9168, mean_val_loss:0.2904,
Epoch: 0, Average Metrics: loss= 1.2471, accuracy= 0.6332, val_loss= 0.7026, val_accuracy= 0.8054
........Epoch: 8, Average Metrics: loss= 0.3315, accuracy= 0.8960, val_loss= 0.2811, val_accuracy= 0.9129
........Epoch: 16, Average Metrics: loss= 0.2803, accuracy= 0.9104, val_loss= 0.2396, val_accuracy= 0.9225
........Epoch: 24, Average Metrics: loss= 0.1850, accuracy= 0.9404, val_loss= 0.2378, val_accuracy= 0.9242
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch 00031: early stopping
Pass!

ID-49, Config:[256, 2, 128, 3, False, 64, 64, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9101, mean_val_loss:0.2890,
Epoch: 0, Average Metrics: loss= 1.2526, accuracy= 0.6424, val_loss= 0.7687, val_accuracy= 0.7826
........Epoch: 8, Average Metrics: loss= 0.2920, accuracy= 0.9065, val_loss= 0.2917, val_accuracy= 0.9126
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 16, Average Metrics: loss= 0.1792, accuracy= 0.9439, val_loss= 0.1651, val_accuracy= 0.9502
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
...Epoch: 24, Average Metrics: loss= 0.1331, accuracy= 0.9552, val_loss= 0.2143, val_accuracy= 0.9450
...Epoch 00027: early stopping
Pass!

ID-50, Config:[256, 2, 128, 3, False, 64, 64, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9149, mean_val_loss:0.2946,
Epoch: 0, Average Metrics: loss= 1.4230, accuracy= 0.5873, val_loss= 0.8492, val_accuracy= 0.7806
........Epoch: 8, Average Metrics: loss= 0.3477, accuracy= 0.8991, val_loss= 0.3046, val_accuracy= 0.9036
........Epoch: 16, Average Metrics: loss= 0.2237, accuracy= 0.9347, val_loss= 0.2331, val_accuracy= 0.9242
........Epoch: 24, Average Metrics: loss= 0.1788, accuracy= 0.9469, val_loss= 0.1966, val_accuracy= 0.9374
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch 00030: early stopping
Pass!

ID-51, Config:[256, 2, 128, 3, False, 64, 64, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9096, mean_val_loss:0.3022,
Epoch: 0, Average Metrics: loss= 1.3737, accuracy= 0.6004, val_loss= 0.7198, val_accuracy= 0.8128
........Epoch: 8, Average Metrics: loss= 0.3535, accuracy= 0.8978, val_loss= 0.3159, val_accuracy= 0.9023
........Epoch: 16, Average Metrics: loss= 0.2539, accuracy= 0.9224, val_loss= 0.2214, val_accuracy= 0.9286
.....Epoch 00021: early stopping
Pass!

ID-52, Config:[256, 2, 128, 3, False, 64, 64, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.8928, mean_val_loss:0.3486,
Epoch: 0, Average Metrics: loss= 1.1858, accuracy= 0.6849, val_loss= 0.6920, val_accuracy= 0.8395
........Epoch: 8, Average Metrics: loss= 0.3388, accuracy= 0.8990, val_loss= 0.2855, val_accuracy= 0.9072
........Epoch: 16, Average Metrics: loss= 0.2204, accuracy= 0.9326, val_loss= 0.2706, val_accuracy= 0.9173
........Epoch: 24, Average Metrics: loss= 0.2381, accuracy= 0.9194, val_loss= 0.2378, val_accuracy= 0.9195
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00030: early stopping
Pass!

ID-53, Config:[256, 2, 128, 3, False, 64, 128, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9094, mean_val_loss:0.3038,
Epoch: 0, Average Metrics: loss= 1.2413, accuracy= 0.6595, val_loss= 0.8822, val_accuracy= 0.7598
........Epoch: 8, Average Metrics: loss= 0.2938, accuracy= 0.9115, val_loss= 0.2798, val_accuracy= 0.9058
........Epoch: 16, Average Metrics: loss= 0.2081, accuracy= 0.9359, val_loss= 0.2061, val_accuracy= 0.9347
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
......Epoch: 24, Average Metrics: loss= 0.1493, accuracy= 0.9541, val_loss= 0.1776, val_accuracy= 0.9477
.....Epoch 00029: early stopping
Pass!

ID-54, Config:[256, 2, 128, 3, False, 64, 128, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9089, mean_val_loss:0.3162,
Epoch: 0, Average Metrics: loss= 1.2775, accuracy= 0.6668, val_loss= 0.7814, val_accuracy= 0.8314
........Epoch: 8, Average Metrics: loss= 0.3391, accuracy= 0.9078, val_loss= 0.4009, val_accuracy= 0.8883
........Epoch: 16, Average Metrics: loss= 0.2375, accuracy= 0.9293, val_loss= 0.2940, val_accuracy= 0.9099
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......Epoch: 24, Average Metrics: loss= 0.1695, accuracy= 0.9474, val_loss= 0.1922, val_accuracy= 0.9377
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.....Epoch: 32, Average Metrics: loss= 0.1219, accuracy= 0.9614, val_loss= 0.1569, val_accuracy= 0.9475
.....
Epoch 00037: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
.Epoch 00038: early stopping
Pass!

ID-55, Config:[256, 2, 128, 3, False, 64, 128, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9204, mean_val_loss:0.2810,
Epoch: 0, Average Metrics: loss= 1.4220, accuracy= 0.6025, val_loss= 0.8840, val_accuracy= 0.7924
........Epoch: 8, Average Metrics: loss= 0.3243, accuracy= 0.9017, val_loss= 0.4073, val_accuracy= 0.8825
........Epoch: 16, Average Metrics: loss= 0.2081, accuracy= 0.9363, val_loss= 0.2091, val_accuracy= 0.9369
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1443, accuracy= 0.9499, val_loss= 0.1765, val_accuracy= 0.9512
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
......
Epoch 00031: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
.Epoch: 32, Average Metrics: loss= 0.1095, accuracy= 0.9594, val_loss= 0.1675, val_accuracy= 0.9512
...
Epoch 00035: ReduceLROnPlateau reducing learning rate to 0.0002500000205814874.
Epoch 00035: early stopping
Pass!

ID-56, Config:[256, 2, 128, 3, False, 64, 128, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9164, mean_val_loss:0.2924,
Epoch: 0, Average Metrics: loss= 1.1993, accuracy= 0.6542, val_loss= 0.6719, val_accuracy= 0.8290
........Epoch: 8, Average Metrics: loss= 0.3269, accuracy= 0.9064, val_loss= 0.2786, val_accuracy= 0.9104
........Epoch: 16, Average Metrics: loss= 0.2477, accuracy= 0.9217, val_loss= 0.2259, val_accuracy= 0.9330
........Epoch: 24, Average Metrics: loss= 0.1985, accuracy= 0.9401, val_loss= 0.2327, val_accuracy= 0.9323
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00027: early stopping
Pass!

ID-57, Config:[256, 2, 128, 3, False, 128, 64, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9073, mean_val_loss:0.3003,
Epoch: 0, Average Metrics: loss= 1.3182, accuracy= 0.6128, val_loss= 0.7200, val_accuracy= 0.8022
........Epoch: 8, Average Metrics: loss= 0.3072, accuracy= 0.9048, val_loss= 0.2685, val_accuracy= 0.9141
........Epoch: 16, Average Metrics: loss= 0.2207, accuracy= 0.9268, val_loss= 0.3152, val_accuracy= 0.8871
........Epoch: 24, Average Metrics: loss= 0.1851, accuracy= 0.9441, val_loss= 0.2822, val_accuracy= 0.9360
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00028: early stopping
Pass!

ID-58, Config:[256, 2, 128, 3, False, 128, 64, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9034, mean_val_loss:0.3354,
Epoch: 0, Average Metrics: loss= 1.3379, accuracy= 0.6098, val_loss= 0.7533, val_accuracy= 0.7995
........Epoch: 8, Average Metrics: loss= 0.3150, accuracy= 0.9107, val_loss= 0.3194, val_accuracy= 0.9070
........Epoch: 16, Average Metrics: loss= 0.3011, accuracy= 0.9063, val_loss= 0.2524, val_accuracy= 0.9242
....Epoch 00020: early stopping
Pass!

ID-59, Config:[256, 2, 128, 3, False, 128, 64, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9024, mean_val_loss:0.3381,
Epoch: 0, Average Metrics: loss= 1.4174, accuracy= 0.5790, val_loss= 0.7610, val_accuracy= 0.7980
........Epoch: 8, Average Metrics: loss= 0.3436, accuracy= 0.8979, val_loss= 0.3616, val_accuracy= 0.8476
........Epoch: 16, Average Metrics: loss= 0.2335, accuracy= 0.9284, val_loss= 0.2958, val_accuracy= 0.9178
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......Epoch: 24, Average Metrics: loss= 0.1662, accuracy= 0.9478, val_loss= 0.1918, val_accuracy= 0.9409
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
......Epoch: 32, Average Metrics: loss= 0.1263, accuracy= 0.9579, val_loss= 0.1845, val_accuracy= 0.9465
..
Epoch 00034: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
....
Epoch 00038: ReduceLROnPlateau reducing learning rate to 0.0002500000205814874.
Epoch 00038: early stopping
Pass!

ID-60, Config:[256, 2, 128, 3, False, 128, 64, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9181, mean_val_loss:0.2749,
Epoch: 0, Average Metrics: loss= 1.1642, accuracy= 0.6907, val_loss= 0.7041, val_accuracy= 0.8042
........Epoch: 8, Average Metrics: loss= 0.3102, accuracy= 0.9084, val_loss= 0.2654, val_accuracy= 0.9193
........Epoch: 16, Average Metrics: loss= 0.2204, accuracy= 0.9367, val_loss= 0.2280, val_accuracy= 0.9335
........Epoch: 24, Average Metrics: loss= 0.1947, accuracy= 0.9433, val_loss= 0.2071, val_accuracy= 0.9337
..
Epoch 00026: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00026: early stopping
Pass!

ID-61, Config:[256, 2, 128, 3, False, 128, 128, 0.3, 64, 0.3, 64, 42, 'adam'], mean_val_acc:0.9129, mean_val_loss:0.2972,
Epoch: 0, Average Metrics: loss= 1.3250, accuracy= 0.6198, val_loss= 0.7535, val_accuracy= 0.8113
........Epoch: 8, Average Metrics: loss= 0.2869, accuracy= 0.9107, val_loss= 0.3190, val_accuracy= 0.8771
...
Epoch 00011: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch: 16, Average Metrics: loss= 0.1784, accuracy= 0.9443, val_loss= 0.2494, val_accuracy= 0.9220
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
.Epoch: 24, Average Metrics: loss= 0.1135, accuracy= 0.9600, val_loss= 0.2557, val_accuracy= 0.9369
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0002500000205814874.
...Epoch 00030: early stopping
Pass!

ID-62, Config:[256, 2, 128, 3, False, 128, 128, 0.3, 64, 0.3, 64, 42, 'rmsprop'], mean_val_acc:0.9167, mean_val_loss:0.2919,
Epoch: 0, Average Metrics: loss= 1.3370, accuracy= 0.6537, val_loss= 0.8256, val_accuracy= 0.8081
........Epoch: 8, Average Metrics: loss= 0.3354, accuracy= 0.9020, val_loss= 0.3362, val_accuracy= 0.8974
........Epoch: 16, Average Metrics: loss= 0.2014, accuracy= 0.9402, val_loss= 0.2068, val_accuracy= 0.9369
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch: 24, Average Metrics: loss= 0.1476, accuracy= 0.9546, val_loss= 0.2058, val_accuracy= 0.9333
...Epoch 00027: early stopping
Pass!

ID-63, Config:[256, 2, 128, 3, False, 128, 128, 0.3, 64, 0.3, 128, 42, 'adam'], mean_val_acc:0.9129, mean_val_loss:0.3089,
Epoch: 0, Average Metrics: loss= 1.5304, accuracy= 0.5742, val_loss= 1.0641, val_accuracy= 0.7352
........Epoch: 8, Average Metrics: loss= 0.3699, accuracy= 0.8855, val_loss= 0.3149, val_accuracy= 0.9013
........Epoch: 16, Average Metrics: loss= 0.2358, accuracy= 0.9241, val_loss= 0.2454, val_accuracy= 0.9234
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1683, accuracy= 0.9457, val_loss= 0.2650, val_accuracy= 0.9296
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....Epoch: 32, Average Metrics: loss= 0.1294, accuracy= 0.9550, val_loss= 0.1843, val_accuracy= 0.9399
..
Epoch 00034: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
....
Epoch 00038: ReduceLROnPlateau reducing learning rate to 0.0002500000205814874.
..Epoch 00040: early stopping
Pass!

ID-64, Config:[256, 2, 128, 3, False, 128, 128, 0.3, 64, 0.3, 128, 42, 'rmsprop'], mean_val_acc:0.9107, mean_val_loss:0.3106,
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---

LSTM-FCN

lstm_units= [64,128]

lstm_units	drop1_rate	c1_filters	c1_kernel	c2_filters	c2_kernel	c3_filters	c3_kernel	bn3	batch_size	epochs
[64,128]	[0.2,0.4]	[64,128]	[5,8]	[64,128]	[2]	[64]	[2]	[True]	[64,128]	[42]

返回結果是按照平均準確率排名之後的結果。

Epoch: 0, Average Metrics: loss= 1.0795, accuracy= 0.6566, val_loss= 0.6909, val_accuracy= 0.7750
........Epoch: 8, Average Metrics: loss= 0.2455, accuracy= 0.9080, val_loss= 0.2582, val_accuracy= 0.9004
........Epoch: 16, Average Metrics: loss= 0.1797, accuracy= 0.9352, val_loss= 0.2192, val_accuracy= 0.9156
..Epoch 00018: early stopping
Pass!

ID-1, Config:[64, 0.2, 64, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8943, mean_val_loss:0.3013,
Epoch: 0, Average Metrics: loss= 1.3741, accuracy= 0.5616, val_loss= 1.0101, val_accuracy= 0.6832
........Epoch: 8, Average Metrics: loss= 0.2681, accuracy= 0.8990, val_loss= 0.2804, val_accuracy= 0.9004
........Epoch 00016: early stopping
Pass!

ID-2, Config:[64, 0.2, 64, 5, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8753, mean_val_loss:0.3553,
Epoch: 0, Average Metrics: loss= 1.0905, accuracy= 0.6461, val_loss= 0.6722, val_accuracy= 0.7654
........Epoch: 8, Average Metrics: loss= 0.2235, accuracy= 0.9200, val_loss= 0.2113, val_accuracy= 0.9222
....Epoch 00012: early stopping
Pass!

ID-3, Config:[64, 0.2, 64, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.8873, mean_val_loss:0.3045,
Epoch: 0, Average Metrics: loss= 1.3491, accuracy= 0.5665, val_loss= 0.9585, val_accuracy= 0.7085
........Epoch: 8, Average Metrics: loss= 0.2452, accuracy= 0.9097, val_loss= 0.2516, val_accuracy= 0.9153
......Epoch 00014: early stopping
Pass!

ID-4, Config:[64, 0.2, 64, 5, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8750, mean_val_loss:0.3618,
Epoch: 0, Average Metrics: loss= 1.0769, accuracy= 0.6552, val_loss= 0.6242, val_accuracy= 0.7929
........Epoch: 8, Average Metrics: loss= 0.2394, accuracy= 0.9085, val_loss= 0.2368, val_accuracy= 0.9090
.....Epoch 00013: early stopping
Pass!

ID-5, Config:[64, 0.2, 64, 8, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8842, mean_val_loss:0.3080,
Epoch: 0, Average Metrics: loss= 1.3928, accuracy= 0.5342, val_loss= 0.9774, val_accuracy= 0.6655
........Epoch: 8, Average Metrics: loss= 0.2482, accuracy= 0.9074, val_loss= 0.2582, val_accuracy= 0.8957
........Epoch: 16, Average Metrics: loss= 0.1733, accuracy= 0.9337, val_loss= 0.2117, val_accuracy= 0.9190
.Epoch 00017: early stopping
Pass!

ID-6, Config:[64, 0.2, 64, 8, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8752, mean_val_loss:0.3386,
Epoch: 0, Average Metrics: loss= 1.0642, accuracy= 0.6640, val_loss= 0.6563, val_accuracy= 0.7887
........Epoch: 8, Average Metrics: loss= 0.2349, accuracy= 0.9128, val_loss= 0.2391, val_accuracy= 0.9185
........Epoch: 16, Average Metrics: loss= 0.1642, accuracy= 0.9351, val_loss= 0.1943, val_accuracy= 0.9225
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00018: early stopping
Pass!

ID-7, Config:[64, 0.2, 64, 8, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9020, mean_val_loss:0.2734,
Epoch: 0, Average Metrics: loss= 1.3184, accuracy= 0.5923, val_loss= 1.0468, val_accuracy= 0.6056
........Epoch: 8, Average Metrics: loss= 0.2382, accuracy= 0.9103, val_loss= 0.2585, val_accuracy= 0.9009
........Epoch: 16, Average Metrics: loss= 0.1840, accuracy= 0.9310, val_loss= 0.2105, val_accuracy= 0.9320
...Epoch 00019: early stopping
Pass!

ID-8, Config:[64, 0.2, 64, 8, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8807, mean_val_loss:0.3230,
Epoch: 0, Average Metrics: loss= 1.1058, accuracy= 0.6337, val_loss= 0.6967, val_accuracy= 0.7801
........Epoch: 8, Average Metrics: loss= 0.2298, accuracy= 0.9150, val_loss= 0.2335, val_accuracy= 0.9146
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1551, accuracy= 0.9392, val_loss= 0.1874, val_accuracy= 0.9298
.Epoch 00017: early stopping
Pass!

ID-9, Config:[64, 0.2, 128, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8966, mean_val_loss:0.2857,
Epoch: 0, Average Metrics: loss= 1.3174, accuracy= 0.5658, val_loss= 0.9596, val_accuracy= 0.6731
........Epoch: 8, Average Metrics: loss= 0.2528, accuracy= 0.9107, val_loss= 0.2633, val_accuracy= 0.9099
........Epoch: 16, Average Metrics: loss= 0.1907, accuracy= 0.9287, val_loss= 0.2324, val_accuracy= 0.9168
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00018: early stopping
Pass!

ID-10, Config:[64, 0.2, 128, 5, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8869, mean_val_loss:0.3305,
Epoch: 0, Average Metrics: loss= 1.0281, accuracy= 0.6745, val_loss= 0.6650, val_accuracy= 0.7850
........Epoch: 8, Average Metrics: loss= 0.2338, accuracy= 0.9101, val_loss= 0.2212, val_accuracy= 0.9188
........Epoch 00016: early stopping
Pass!

ID-11, Config:[64, 0.2, 128, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.8960, mean_val_loss:0.2881,
Epoch: 0, Average Metrics: loss= 1.3410, accuracy= 0.5783, val_loss= 0.9846, val_accuracy= 0.7055
........Epoch: 8, Average Metrics: loss= 0.2435, accuracy= 0.9116, val_loss= 0.2819, val_accuracy= 0.8999
.......Epoch 00015: early stopping
Pass!

ID-12, Config:[64, 0.2, 128, 5, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8796, mean_val_loss:0.3529,
Epoch: 0, Average Metrics: loss= 1.0692, accuracy= 0.6457, val_loss= 0.6826, val_accuracy= 0.7944
........Epoch: 8, Average Metrics: loss= 0.2200, accuracy= 0.9148, val_loss= 0.2335, val_accuracy= 0.9090
...Epoch 00011: early stopping
Pass!

ID-13, Config:[64, 0.2, 128, 8, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8841, mean_val_loss:0.3237,
Epoch: 0, Average Metrics: loss= 1.3008, accuracy= 0.6015, val_loss= 0.9349, val_accuracy= 0.7242
........Epoch: 8, Average Metrics: loss= 0.2372, accuracy= 0.9122, val_loss= 0.2524, val_accuracy= 0.9048
........Epoch: 16, Average Metrics: loss= 0.1670, accuracy= 0.9379, val_loss= 0.2250, val_accuracy= 0.9146
..Epoch 00018: early stopping
Pass!

ID-14, Config:[64, 0.2, 128, 8, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8895, mean_val_loss:0.3169,
Epoch: 0, Average Metrics: loss= 0.9884, accuracy= 0.6922, val_loss= 0.6432, val_accuracy= 0.7980
........Epoch: 8, Average Metrics: loss= 0.2153, accuracy= 0.9179, val_loss= 0.2185, val_accuracy= 0.9124
..Epoch 00010: early stopping
Pass!

ID-15, Config:[64, 0.2, 128, 8, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.8816, mean_val_loss:0.3242,
Epoch: 0, Average Metrics: loss= 1.2070, accuracy= 0.6261, val_loss= 0.9202, val_accuracy= 0.7477
........Epoch: 8, Average Metrics: loss= 0.2292, accuracy= 0.9143, val_loss= 0.2592, val_accuracy= 0.9013
........Epoch: 16, Average Metrics: loss= 0.1749, accuracy= 0.9343, val_loss= 0.2308, val_accuracy= 0.9136
....Epoch 00020: early stopping
Pass!

ID-16, Config:[64, 0.2, 128, 8, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8955, mean_val_loss:0.2967,
Epoch: 0, Average Metrics: loss= 1.1236, accuracy= 0.6430, val_loss= 0.6628, val_accuracy= 0.7958
........Epoch: 8, Average Metrics: loss= 0.2749, accuracy= 0.8982, val_loss= 0.2504, val_accuracy= 0.9004
........Epoch: 16, Average Metrics: loss= 0.1916, accuracy= 0.9276, val_loss= 0.1923, val_accuracy= 0.9279
...Epoch 00019: early stopping
Pass!

ID-17, Config:[64, 0.4, 64, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8892, mean_val_loss:0.2965,
Epoch: 0, Average Metrics: loss= 1.4593, accuracy= 0.5174, val_loss= 1.0378, val_accuracy= 0.6579
........Epoch: 8, Average Metrics: loss= 0.2818, accuracy= 0.8958, val_loss= 0.3202, val_accuracy= 0.8748
........Epoch: 16, Average Metrics: loss= 0.1907, accuracy= 0.9303, val_loss= 0.2083, val_accuracy= 0.9215
..Epoch 00018: early stopping
Pass!

ID-18, Config:[64, 0.4, 64, 5, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8760, mean_val_loss:0.3549,
Epoch: 0, Average Metrics: loss= 1.0952, accuracy= 0.6512, val_loss= 0.6856, val_accuracy= 0.7777
........Epoch: 8, Average Metrics: loss= 0.2398, accuracy= 0.9100, val_loss= 0.2873, val_accuracy= 0.8977
........Epoch: 16, Average Metrics: loss= 0.1805, accuracy= 0.9286, val_loss= 0.2195, val_accuracy= 0.9134
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00020: early stopping
Pass!

ID-19, Config:[64, 0.4, 64, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9001, mean_val_loss:0.2732,
Epoch: 0, Average Metrics: loss= 1.3729, accuracy= 0.5547, val_loss= 1.0180, val_accuracy= 0.6672
........Epoch: 8, Average Metrics: loss= 0.2573, accuracy= 0.9089, val_loss= 0.2601, val_accuracy= 0.9043
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00015: early stopping
Pass!

ID-20, Config:[64, 0.4, 64, 5, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8744, mean_val_loss:0.3562,
Epoch: 0, Average Metrics: loss= 1.0965, accuracy= 0.6501, val_loss= 0.6864, val_accuracy= 0.7831
........Epoch: 8, Average Metrics: loss= 0.2514, accuracy= 0.9056, val_loss= 0.2261, val_accuracy= 0.9244
......Epoch 00014: early stopping
Pass!

ID-21, Config:[64, 0.4, 64, 8, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8865, mean_val_loss:0.3131,
Epoch: 0, Average Metrics: loss= 1.3359, accuracy= 0.5810, val_loss= 0.9999, val_accuracy= 0.6618
........Epoch: 8, Average Metrics: loss= 0.2582, accuracy= 0.9048, val_loss= 0.2636, val_accuracy= 0.8989
........Epoch: 16, Average Metrics: loss= 0.1974, accuracy= 0.9266, val_loss= 0.2030, val_accuracy= 0.9232
....Epoch 00020: early stopping
Pass!

ID-22, Config:[64, 0.4, 64, 8, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8863, mean_val_loss:0.3151,
Epoch: 0, Average Metrics: loss= 1.0440, accuracy= 0.6683, val_loss= 0.6353, val_accuracy= 0.8044
........Epoch: 8, Average Metrics: loss= 0.2345, accuracy= 0.9101, val_loss= 0.2361, val_accuracy= 0.9180
......Epoch 00014: early stopping
Pass!

ID-23, Config:[64, 0.4, 64, 8, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.8945, mean_val_loss:0.2943,
Epoch: 0, Average Metrics: loss= 1.3244, accuracy= 0.5814, val_loss= 0.9974, val_accuracy= 0.6775
........Epoch: 8, Average Metrics: loss= 0.2564, accuracy= 0.9061, val_loss= 0.2650, val_accuracy= 0.9011
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1781, accuracy= 0.9313, val_loss= 0.2277, val_accuracy= 0.9090
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch 00024: early stopping
Pass!

ID-24, Config:[64, 0.4, 64, 8, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8951, mean_val_loss:0.2879,
Epoch: 0, Average Metrics: loss= 1.0804, accuracy= 0.6654, val_loss= 0.7297, val_accuracy= 0.7627
........Epoch: 8, Average Metrics: loss= 0.2264, accuracy= 0.9180, val_loss= 0.2221, val_accuracy= 0.9202
........Epoch: 16, Average Metrics: loss= 0.1715, accuracy= 0.9322, val_loss= 0.1881, val_accuracy= 0.9225
.Epoch 00017: early stopping
Pass!

ID-25, Config:[64, 0.4, 128, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8956, mean_val_loss:0.2901,
Epoch: 0, Average Metrics: loss= 1.4097, accuracy= 0.5308, val_loss= 1.0405, val_accuracy= 0.6876
........Epoch: 8, Average Metrics: loss= 0.2532, accuracy= 0.9061, val_loss= 0.2423, val_accuracy= 0.9053
........Epoch: 16, Average Metrics: loss= 0.1952, accuracy= 0.9259, val_loss= 0.2149, val_accuracy= 0.9188
....Epoch 00020: early stopping
Pass!

ID-26, Config:[64, 0.4, 128, 5, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8879, mean_val_loss:0.3219,
Epoch: 0, Average Metrics: loss= 1.0750, accuracy= 0.6509, val_loss= 0.6453, val_accuracy= 0.8005
........Epoch: 8, Average Metrics: loss= 0.2359, accuracy= 0.9108, val_loss= 0.2662, val_accuracy= 0.9092
........Epoch: 16, Average Metrics: loss= 0.1698, accuracy= 0.9360, val_loss= 0.1792, val_accuracy= 0.9283
.....Epoch 00021: early stopping
Pass!

ID-27, Config:[64, 0.4, 128, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9064, mean_val_loss:0.2636,
Epoch: 0, Average Metrics: loss= 1.3831, accuracy= 0.5579, val_loss= 0.9995, val_accuracy= 0.6582
........Epoch: 8, Average Metrics: loss= 0.2537, accuracy= 0.9086, val_loss= 0.2699, val_accuracy= 0.9121
........Epoch: 16, Average Metrics: loss= 0.1915, accuracy= 0.9296, val_loss= 0.2121, val_accuracy= 0.9232
.Epoch 00017: early stopping
Pass!

ID-28, Config:[64, 0.4, 128, 5, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8818, mean_val_loss:0.3385,
Epoch: 0, Average Metrics: loss= 1.0513, accuracy= 0.6581, val_loss= 0.6678, val_accuracy= 0.7956
........Epoch: 8, Average Metrics: loss= 0.2351, accuracy= 0.9118, val_loss= 0.2214, val_accuracy= 0.9151
......Epoch 00014: early stopping
Pass!

ID-29, Config:[64, 0.4, 128, 8, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8877, mean_val_loss:0.2971,
Epoch: 0, Average Metrics: loss= 1.3064, accuracy= 0.6068, val_loss= 0.9639, val_accuracy= 0.6694
........Epoch: 8, Average Metrics: loss= 0.2412, accuracy= 0.9108, val_loss= 0.2440, val_accuracy= 0.9045
........Epoch: 16, Average Metrics: loss= 0.1758, accuracy= 0.9323, val_loss= 0.1902, val_accuracy= 0.9301
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00022: early stopping
Pass!

ID-30, Config:[64, 0.4, 128, 8, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8925, mean_val_loss:0.2918,
Epoch: 0, Average Metrics: loss= 1.0008, accuracy= 0.6852, val_loss= 0.6063, val_accuracy= 0.8086
........Epoch: 8, Average Metrics: loss= 0.2341, accuracy= 0.9129, val_loss= 0.2337, val_accuracy= 0.9038
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1537, accuracy= 0.9408, val_loss= 0.1681, val_accuracy= 0.9362
.Epoch 00017: early stopping
Pass!

ID-31, Config:[64, 0.4, 128, 8, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.8999, mean_val_loss:0.2720,
Epoch: 0, Average Metrics: loss= 1.2912, accuracy= 0.5986, val_loss= 0.9731, val_accuracy= 0.6665
........Epoch: 8, Average Metrics: loss= 0.2390, accuracy= 0.9115, val_loss= 0.2445, val_accuracy= 0.9004
........Epoch: 16, Average Metrics: loss= 0.1788, accuracy= 0.9316, val_loss= 0.1959, val_accuracy= 0.9227
...Epoch 00019: early stopping
Pass!

ID-32, Config:[64, 0.4, 128, 8, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8872, mean_val_loss:0.3124,
Epoch: 0, Average Metrics: loss= 0.9245, accuracy= 0.6979, val_loss= 0.6197, val_accuracy= 0.7816
........Epoch: 8, Average Metrics: loss= 0.2325, accuracy= 0.9099, val_loss= 0.2303, val_accuracy= 0.9148
........Epoch: 16, Average Metrics: loss= 0.1731, accuracy= 0.9322, val_loss= 0.2524, val_accuracy= 0.9129
...Epoch 00019: early stopping
Pass!

ID-33, Config:[128, 0.2, 64, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8986, mean_val_loss:0.2742,
Epoch: 0, Average Metrics: loss= 1.1837, accuracy= 0.6067, val_loss= 0.7115, val_accuracy= 0.7833
........Epoch: 8, Average Metrics: loss= 0.2544, accuracy= 0.8976, val_loss= 0.2690, val_accuracy= 0.9043
....
Epoch 00012: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 16, Average Metrics: loss= 0.1601, accuracy= 0.9412, val_loss= 0.1891, val_accuracy= 0.9303
..Epoch 00018: early stopping
Pass!

ID-34, Config:[128, 0.2, 64, 5, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8872, mean_val_loss:0.3065,
Epoch: 0, Average Metrics: loss= 0.8968, accuracy= 0.7053, val_loss= 0.5299, val_accuracy= 0.8012
........Epoch: 8, Average Metrics: loss= 0.2232, accuracy= 0.9169, val_loss= 0.2229, val_accuracy= 0.9225
........Epoch: 16, Average Metrics: loss= 0.1598, accuracy= 0.9399, val_loss= 0.2249, val_accuracy= 0.9080
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00023: early stopping
Pass!

ID-35, Config:[128, 0.2, 64, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9091, mean_val_loss:0.2430,
Epoch: 0, Average Metrics: loss= 1.1622, accuracy= 0.6426, val_loss= 0.7437, val_accuracy= 0.7860
........Epoch: 8, Average Metrics: loss= 0.2435, accuracy= 0.9076, val_loss= 0.2302, val_accuracy= 0.9166
......Epoch 00014: early stopping
Pass!

ID-36, Config:[128, 0.2, 64, 5, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8810, mean_val_loss:0.3341,
Epoch: 0, Average Metrics: loss= 0.9004, accuracy= 0.7036, val_loss= 0.5145, val_accuracy= 0.8312
........Epoch: 8, Average Metrics: loss= 0.2176, accuracy= 0.9164, val_loss= 0.2225, val_accuracy= 0.9124
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1444, accuracy= 0.9449, val_loss= 0.1881, val_accuracy= 0.9318
.Epoch 00017: early stopping
Pass!

ID-37, Config:[128, 0.2, 64, 8, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8882, mean_val_loss:0.2864,
Epoch: 0, Average Metrics: loss= 1.1351, accuracy= 0.6399, val_loss= 0.6870, val_accuracy= 0.7909
........Epoch: 8, Average Metrics: loss= 0.2386, accuracy= 0.9084, val_loss= 0.2377, val_accuracy= 0.9119
........Epoch 00016: early stopping
Pass!

ID-38, Config:[128, 0.2, 64, 8, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8873, mean_val_loss:0.3075,
Epoch: 0, Average Metrics: loss= 0.8851, accuracy= 0.6997, val_loss= 0.5063, val_accuracy= 0.8113
........Epoch: 8, Average Metrics: loss= 0.2195, accuracy= 0.9172, val_loss= 0.2644, val_accuracy= 0.8960
........Epoch: 16, Average Metrics: loss= 0.1716, accuracy= 0.9361, val_loss= 0.2055, val_accuracy= 0.9318
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00020: early stopping
Pass!

ID-39, Config:[128, 0.2, 64, 8, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9034, mean_val_loss:0.2536,
Epoch: 0, Average Metrics: loss= 1.1141, accuracy= 0.6495, val_loss= 0.7245, val_accuracy= 0.7703
........Epoch: 8, Average Metrics: loss= 0.2250, accuracy= 0.9150, val_loss= 0.2403, val_accuracy= 0.9004
........Epoch: 16, Average Metrics: loss= 0.1740, accuracy= 0.9319, val_loss= 0.2545, val_accuracy= 0.8798
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00020: early stopping
Pass!

ID-40, Config:[128, 0.2, 64, 8, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8924, mean_val_loss:0.2869,
Epoch: 0, Average Metrics: loss= 0.8934, accuracy= 0.7171, val_loss= 0.5842, val_accuracy= 0.8120
........Epoch: 8, Average Metrics: loss= 0.2161, accuracy= 0.9164, val_loss= 0.2090, val_accuracy= 0.9225
.....
Epoch 00013: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch: 16, Average Metrics: loss= 0.1471, accuracy= 0.9398, val_loss= 0.1895, val_accuracy= 0.9283
...Epoch 00019: early stopping
Pass!

ID-41, Config:[128, 0.2, 128, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.9066, mean_val_loss:0.2599,
Epoch: 0, Average Metrics: loss= 1.1685, accuracy= 0.6233, val_loss= 0.6867, val_accuracy= 0.7985
........Epoch: 8, Average Metrics: loss= 0.2456, accuracy= 0.9031, val_loss= 0.2629, val_accuracy= 0.9023
..Epoch 00010: early stopping
Pass!

ID-42, Config:[128, 0.2, 128, 5, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8753, mean_val_loss:0.3486,
Epoch: 0, Average Metrics: loss= 0.8849, accuracy= 0.7076, val_loss= 0.5243, val_accuracy= 0.8258
........Epoch: 8, Average Metrics: loss= 0.2298, accuracy= 0.9126, val_loss= 0.1929, val_accuracy= 0.9283
......Epoch 00014: early stopping
Pass!

ID-43, Config:[128, 0.2, 128, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.8995, mean_val_loss:0.2703,
Epoch: 0, Average Metrics: loss= 1.1059, accuracy= 0.6381, val_loss= 0.6956, val_accuracy= 0.7691
........Epoch: 8, Average Metrics: loss= 0.2414, accuracy= 0.9098, val_loss= 0.2838, val_accuracy= 0.8896
........Epoch 00016: early stopping
Pass!

ID-44, Config:[128, 0.2, 128, 5, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8851, mean_val_loss:0.3106,
Epoch: 0, Average Metrics: loss= 0.9085, accuracy= 0.7026, val_loss= 0.5476, val_accuracy= 0.8142
........Epoch: 8, Average Metrics: loss= 0.2223, accuracy= 0.9151, val_loss= 0.2383, val_accuracy= 0.8977
........Epoch: 16, Average Metrics: loss= 0.1639, accuracy= 0.9370, val_loss= 0.2128, val_accuracy= 0.9144
.Epoch 00017: early stopping
Pass!

ID-45, Config:[128, 0.2, 128, 8, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8965, mean_val_loss:0.2747,
Epoch: 0, Average Metrics: loss= 1.1210, accuracy= 0.6454, val_loss= 0.7162, val_accuracy= 0.7723
........Epoch: 8, Average Metrics: loss= 0.2222, accuracy= 0.9154, val_loss= 0.2834, val_accuracy= 0.8820
........Epoch: 16, Average Metrics: loss= 0.1591, accuracy= 0.9407, val_loss= 0.1721, val_accuracy= 0.9269
.Epoch 00017: early stopping
Pass!

ID-46, Config:[128, 0.2, 128, 8, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8887, mean_val_loss:0.2944,
Epoch: 0, Average Metrics: loss= 0.8691, accuracy= 0.7123, val_loss= 0.4939, val_accuracy= 0.8240
........Epoch: 8, Average Metrics: loss= 0.2022, accuracy= 0.9227, val_loss= 0.2231, val_accuracy= 0.9058
....Epoch 00012: early stopping
Pass!

ID-47, Config:[128, 0.2, 128, 8, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.8913, mean_val_loss:0.2829,
Epoch: 0, Average Metrics: loss= 1.1115, accuracy= 0.6566, val_loss= 0.6640, val_accuracy= 0.7880
........Epoch: 8, Average Metrics: loss= 0.2144, accuracy= 0.9180, val_loss= 0.2249, val_accuracy= 0.9237
......Epoch 00014: early stopping
Pass!

ID-48, Config:[128, 0.2, 128, 8, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8845, mean_val_loss:0.3030,
Epoch: 0, Average Metrics: loss= 0.9468, accuracy= 0.6961, val_loss= 0.5449, val_accuracy= 0.8106
........Epoch: 8, Average Metrics: loss= 0.2373, accuracy= 0.9075, val_loss= 0.2113, val_accuracy= 0.9129
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1620, accuracy= 0.9386, val_loss= 0.2395, val_accuracy= 0.9136
.Epoch 00017: early stopping
Pass!

ID-49, Config:[128, 0.4, 64, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8973, mean_val_loss:0.2732,
Epoch: 0, Average Metrics: loss= 1.2115, accuracy= 0.6030, val_loss= 0.6529, val_accuracy= 0.7806
........Epoch: 8, Average Metrics: loss= 0.2400, accuracy= 0.9116, val_loss= 0.2269, val_accuracy= 0.9077
.....Epoch 00013: early stopping
Pass!

ID-50, Config:[128, 0.4, 64, 5, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8798, mean_val_loss:0.3296,
Epoch: 0, Average Metrics: loss= 0.9327, accuracy= 0.6876, val_loss= 0.5703, val_accuracy= 0.8034
........Epoch: 8, Average Metrics: loss= 0.2417, accuracy= 0.9074, val_loss= 0.2188, val_accuracy= 0.9210
....Epoch 00012: early stopping
Pass!

ID-51, Config:[128, 0.4, 64, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.8834, mean_val_loss:0.3119,
Epoch: 0, Average Metrics: loss= 1.1894, accuracy= 0.6192, val_loss= 0.7167, val_accuracy= 0.7931
........Epoch: 8, Average Metrics: loss= 0.2432, accuracy= 0.9068, val_loss= 0.2640, val_accuracy= 0.8979
........Epoch: 16, Average Metrics: loss= 0.1831, accuracy= 0.9317, val_loss= 0.2015, val_accuracy= 0.9261
.....Epoch 00021: early stopping
Pass!

ID-52, Config:[128, 0.4, 64, 5, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8969, mean_val_loss:0.2794,
Epoch: 0, Average Metrics: loss= 0.9425, accuracy= 0.6991, val_loss= 0.5744, val_accuracy= 0.8007
........Epoch: 8, Average Metrics: loss= 0.2246, accuracy= 0.9121, val_loss= 0.2486, val_accuracy= 0.8947
........Epoch: 16, Average Metrics: loss= 0.1648, accuracy= 0.9382, val_loss= 0.2195, val_accuracy= 0.9156
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00020: early stopping
Pass!

ID-53, Config:[128, 0.4, 64, 8, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.9026, mean_val_loss:0.2550,
Epoch: 0, Average Metrics: loss= 1.1773, accuracy= 0.6331, val_loss= 0.7082, val_accuracy= 0.7813
........Epoch: 8, Average Metrics: loss= 0.2358, accuracy= 0.9105, val_loss= 0.2630, val_accuracy= 0.8906
...Epoch 00011: early stopping
Pass!

ID-54, Config:[128, 0.4, 64, 8, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8749, mean_val_loss:0.3473,
Epoch: 0, Average Metrics: loss= 0.9224, accuracy= 0.6929, val_loss= 0.5387, val_accuracy= 0.8155
........Epoch: 8, Average Metrics: loss= 0.2309, accuracy= 0.9138, val_loss= 0.2484, val_accuracy= 0.9004
........Epoch: 16, Average Metrics: loss= 0.1542, accuracy= 0.9387, val_loss= 0.1848, val_accuracy= 0.9379
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00021: early stopping
Pass!

ID-55, Config:[128, 0.4, 64, 8, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9070, mean_val_loss:0.2473,
Epoch: 0, Average Metrics: loss= 1.1610, accuracy= 0.6195, val_loss= 0.7020, val_accuracy= 0.7652
........Epoch: 8, Average Metrics: loss= 0.2385, accuracy= 0.9099, val_loss= 0.2481, val_accuracy= 0.9121
........Epoch: 16, Average Metrics: loss= 0.1741, accuracy= 0.9357, val_loss= 0.2128, val_accuracy= 0.9266
..Epoch 00018: early stopping
Pass!

ID-56, Config:[128, 0.4, 64, 8, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8933, mean_val_loss:0.2865,
Epoch: 0, Average Metrics: loss= 0.9307, accuracy= 0.6884, val_loss= 0.5954, val_accuracy= 0.7850
........Epoch: 8, Average Metrics: loss= 0.2284, accuracy= 0.9113, val_loss= 0.2343, val_accuracy= 0.9234
.....Epoch 00013: early stopping
Pass!

ID-57, Config:[128, 0.4, 128, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8925, mean_val_loss:0.2873,
Epoch: 0, Average Metrics: loss= 1.1732, accuracy= 0.6119, val_loss= 0.6777, val_accuracy= 0.7762
........Epoch: 8, Average Metrics: loss= 0.2495, accuracy= 0.9077, val_loss= 0.2647, val_accuracy= 0.8950
........Epoch 00016: early stopping
Pass!

ID-58, Config:[128, 0.4, 128, 5, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8909, mean_val_loss:0.3016,
Epoch: 0, Average Metrics: loss= 0.9322, accuracy= 0.7022, val_loss= 0.5658, val_accuracy= 0.8015
........Epoch: 8, Average Metrics: loss= 0.2315, accuracy= 0.9106, val_loss= 0.2926, val_accuracy= 0.8783
......
Epoch 00014: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch 00015: early stopping
Pass!

ID-59, Config:[128, 0.4, 128, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.8986, mean_val_loss:0.2718,
Epoch: 0, Average Metrics: loss= 1.1466, accuracy= 0.6362, val_loss= 0.7057, val_accuracy= 0.7956
........Epoch: 8, Average Metrics: loss= 0.2511, accuracy= 0.9049, val_loss= 0.2299, val_accuracy= 0.9180
......Epoch 00014: early stopping
Pass!

ID-60, Config:[128, 0.4, 128, 5, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8886, mean_val_loss:0.3099,
Epoch: 0, Average Metrics: loss= 0.9227, accuracy= 0.6962, val_loss= 0.5168, val_accuracy= 0.8172
........Epoch: 8, Average Metrics: loss= 0.2277, accuracy= 0.9135, val_loss= 0.2267, val_accuracy= 0.9202
......Epoch 00014: early stopping
Pass!

ID-61, Config:[128, 0.4, 128, 8, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8933, mean_val_loss:0.2833,
Epoch: 0, Average Metrics: loss= 1.1361, accuracy= 0.6485, val_loss= 0.7068, val_accuracy= 0.7541
........Epoch: 8, Average Metrics: loss= 0.2434, accuracy= 0.9100, val_loss= 0.2620, val_accuracy= 0.9072
........Epoch: 16, Average Metrics: loss= 0.1797, accuracy= 0.9333, val_loss= 0.1931, val_accuracy= 0.9291
.Epoch 00017: early stopping
Pass!

ID-62, Config:[128, 0.4, 128, 8, 64, 2, 64, 2, True, 128, 42], mean_val_acc:0.8938, mean_val_loss:0.2875,
Epoch: 0, Average Metrics: loss= 0.9036, accuracy= 0.7011, val_loss= 0.5563, val_accuracy= 0.7995
........Epoch: 8, Average Metrics: loss= 0.2289, accuracy= 0.9124, val_loss= 0.2451, val_accuracy= 0.8999
........Epoch 00016: early stopping
Pass!

ID-63, Config:[128, 0.4, 128, 8, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.8935, mean_val_loss:0.2772,
Epoch: 0, Average Metrics: loss= 1.1400, accuracy= 0.6426, val_loss= 0.7226, val_accuracy= 0.7688
........Epoch: 8, Average Metrics: loss= 0.2384, accuracy= 0.9107, val_loss= 0.2517, val_accuracy= 0.9028
....Epoch 00012: early stopping
Pass!

ID-64, Config:[128, 0.4, 128, 8, 128, 2, 64, 2, True, 128, 42], mean_val_acc:0.8764, mean_val_loss:0.3407,
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---

---

lstm_units= [256]

lstm_units	drop1_rate	c1_filters	c1_kernel	c2_filters	c2_kernel	c3_filters	c3_kernel	bn3	batch_size	epochs
[256]	[0.4,0.5]	[128,256]	[3,5]	[64,128]	[2,3]	[64]	[2]	[True]	[64,128]	[42]

Epoch: 0, Average Metrics: loss= 0.8662, accuracy= 0.7042, val_loss= 0.5049, val_accuracy= 0.8211
........Epoch: 8, Average Metrics: loss= 0.2577, accuracy= 0.9024, val_loss= 0.2721, val_accuracy= 0.8969
........Epoch: 16, Average Metrics: loss= 0.1804, accuracy= 0.9331, val_loss= 0.1937, val_accuracy= 0.9212
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 24, Average Metrics: loss= 0.1375, accuracy= 0.9441, val_loss= 0.1587, val_accuracy= 0.9374
..Epoch 00026: early stopping
Pass!

ID-1, Config:[256, 0.4, 128, 3, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.9035, mean_val_loss:0.2509,
Epoch: 0, Average Metrics: loss= 0.8268, accuracy= 0.7140, val_loss= 0.4972, val_accuracy= 0.8115
........Epoch: 8, Average Metrics: loss= 0.2472, accuracy= 0.9021, val_loss= 0.2507, val_accuracy= 0.8999
........Epoch: 16, Average Metrics: loss= 0.1755, accuracy= 0.9296, val_loss= 0.2101, val_accuracy= 0.9156
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......Epoch: 24, Average Metrics: loss= 0.1598, accuracy= 0.9358, val_loss= 0.2489, val_accuracy= 0.8842
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....Epoch 00032: early stopping
Pass!

ID-2, Config:[256, 0.4, 128, 3, 64, 3, 64, 2, True, 64, 42], mean_val_acc:0.9075, mean_val_loss:0.2345,
Epoch: 0, Average Metrics: loss= 0.8167, accuracy= 0.7193, val_loss= 0.4922, val_accuracy= 0.8147
........Epoch: 8, Average Metrics: loss= 0.2159, accuracy= 0.9142, val_loss= 0.2055, val_accuracy= 0.9166
........Epoch: 16, Average Metrics: loss= 0.1672, accuracy= 0.9343, val_loss= 0.1952, val_accuracy= 0.9286
......
Epoch 00022: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch 00022: early stopping
Pass!

ID-3, Config:[256, 0.4, 128, 3, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9069, mean_val_loss:0.2434,
Epoch: 0, Average Metrics: loss= 0.8307, accuracy= 0.7170, val_loss= 0.5047, val_accuracy= 0.8079
........Epoch: 8, Average Metrics: loss= 0.2361, accuracy= 0.9072, val_loss= 0.2718, val_accuracy= 0.8859
........Epoch: 16, Average Metrics: loss= 0.1588, accuracy= 0.9358, val_loss= 0.1855, val_accuracy= 0.9360
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1184, accuracy= 0.9519, val_loss= 0.1605, val_accuracy= 0.9382
..Epoch 00026: early stopping
Pass!

ID-4, Config:[256, 0.4, 128, 3, 128, 3, 64, 2, True, 64, 42], mean_val_acc:0.9068, mean_val_loss:0.2442,
Epoch: 0, Average Metrics: loss= 0.8316, accuracy= 0.7201, val_loss= 0.6267, val_accuracy= 0.7571
........Epoch: 8, Average Metrics: loss= 0.2543, accuracy= 0.8959, val_loss= 0.2784, val_accuracy= 0.8937
........Epoch: 16, Average Metrics: loss= 0.1818, accuracy= 0.9313, val_loss= 0.2040, val_accuracy= 0.9210
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
......Epoch: 24, Average Metrics: loss= 0.1299, accuracy= 0.9474, val_loss= 0.1693, val_accuracy= 0.9345
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch 00031: early stopping
Pass!

ID-5, Config:[256, 0.4, 128, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.9105, mean_val_loss:0.2321,
Epoch: 0, Average Metrics: loss= 0.8271, accuracy= 0.7083, val_loss= 0.4501, val_accuracy= 0.8309
........Epoch: 8, Average Metrics: loss= 0.2222, accuracy= 0.9113, val_loss= 0.2191, val_accuracy= 0.9244
........Epoch: 16, Average Metrics: loss= 0.1758, accuracy= 0.9305, val_loss= 0.2062, val_accuracy= 0.9190
...Epoch 00019: early stopping
Pass!

ID-6, Config:[256, 0.4, 128, 5, 64, 3, 64, 2, True, 64, 42], mean_val_acc:0.9016, mean_val_loss:0.2602,
Epoch: 0, Average Metrics: loss= 0.8419, accuracy= 0.7225, val_loss= 0.4954, val_accuracy= 0.8211
........Epoch: 8, Average Metrics: loss= 0.2203, accuracy= 0.9145, val_loss= 0.2109, val_accuracy= 0.9227
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1546, accuracy= 0.9415, val_loss= 0.1662, val_accuracy= 0.9364
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
...Epoch: 24, Average Metrics: loss= 0.1190, accuracy= 0.9510, val_loss= 0.1481, val_accuracy= 0.9482
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
..Epoch: 32, Average Metrics: loss= 0.1015, accuracy= 0.9580, val_loss= 0.1856, val_accuracy= 0.9394
.Epoch 00033: early stopping
Pass!

ID-7, Config:[256, 0.4, 128, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9163, mean_val_loss:0.2207,
Epoch: 0, Average Metrics: loss= 0.8266, accuracy= 0.7257, val_loss= 0.5067, val_accuracy= 0.8123
........Epoch: 8, Average Metrics: loss= 0.2466, accuracy= 0.9047, val_loss= 0.2428, val_accuracy= 0.9080
........Epoch: 16, Average Metrics: loss= 0.2166, accuracy= 0.9147, val_loss= 0.2254, val_accuracy= 0.9163
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 24, Average Metrics: loss= 0.1270, accuracy= 0.9473, val_loss= 0.1765, val_accuracy= 0.9472
........Epoch: 32, Average Metrics: loss= 0.1243, accuracy= 0.9491, val_loss= 0.1494, val_accuracy= 0.9438
...Epoch 00035: early stopping
Pass!

ID-8, Config:[256, 0.4, 128, 5, 128, 3, 64, 2, True, 64, 42], mean_val_acc:0.9145, mean_val_loss:0.2236,
Epoch: 0, Average Metrics: loss= 0.8309, accuracy= 0.7224, val_loss= 0.5311, val_accuracy= 0.8071
........Epoch: 8, Average Metrics: loss= 0.2250, accuracy= 0.9127, val_loss= 0.2306, val_accuracy= 0.9161
........Epoch 00016: early stopping
Pass!

ID-9, Config:[256, 0.4, 256, 3, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8909, mean_val_loss:0.2864,
Epoch: 0, Average Metrics: loss= 0.8285, accuracy= 0.7193, val_loss= 0.4753, val_accuracy= 0.8260
........Epoch: 8, Average Metrics: loss= 0.2304, accuracy= 0.9104, val_loss= 0.2489, val_accuracy= 0.9016
........Epoch: 16, Average Metrics: loss= 0.1869, accuracy= 0.9249, val_loss= 0.2274, val_accuracy= 0.9087
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
......
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch: 24, Average Metrics: loss= 0.1126, accuracy= 0.9535, val_loss= 0.1801, val_accuracy= 0.9171
.....Epoch 00029: early stopping
Pass!

ID-10, Config:[256, 0.4, 256, 3, 64, 3, 64, 2, True, 64, 42], mean_val_acc:0.9073, mean_val_loss:0.2376,
Epoch: 0, Average Metrics: loss= 0.8378, accuracy= 0.7138, val_loss= 0.5027, val_accuracy= 0.8042
........Epoch: 8, Average Metrics: loss= 0.2281, accuracy= 0.9096, val_loss= 0.2354, val_accuracy= 0.9009
........Epoch: 16, Average Metrics: loss= 0.1578, accuracy= 0.9367, val_loss= 0.1796, val_accuracy= 0.9340
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch: 24, Average Metrics: loss= 0.1266, accuracy= 0.9472, val_loss= 0.1704, val_accuracy= 0.9323
.Epoch 00025: early stopping
Pass!

ID-11, Config:[256, 0.4, 256, 3, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9096, mean_val_loss:0.2354,
Epoch: 0, Average Metrics: loss= 0.8097, accuracy= 0.7265, val_loss= 0.5013, val_accuracy= 0.8160
........Epoch: 8, Average Metrics: loss= 0.2213, accuracy= 0.9173, val_loss= 0.2249, val_accuracy= 0.9158
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 16, Average Metrics: loss= 0.1360, accuracy= 0.9478, val_loss= 0.1675, val_accuracy= 0.9335
........Epoch: 24, Average Metrics: loss= 0.1241, accuracy= 0.9509, val_loss= 0.1762, val_accuracy= 0.9399
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
...Epoch 00031: early stopping
Pass!

ID-12, Config:[256, 0.4, 256, 3, 128, 3, 64, 2, True, 64, 42], mean_val_acc:0.9115, mean_val_loss:0.2271,
Epoch: 0, Average Metrics: loss= 0.8379, accuracy= 0.7101, val_loss= 0.4543, val_accuracy= 0.8417
........Epoch: 8, Average Metrics: loss= 0.2248, accuracy= 0.9143, val_loss= 0.2354, val_accuracy= 0.9063
........Epoch: 16, Average Metrics: loss= 0.2184, accuracy= 0.9147, val_loss= 0.2431, val_accuracy= 0.9112
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
......
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch 00024: early stopping
Pass!

ID-13, Config:[256, 0.4, 256, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.9027, mean_val_loss:0.2562,
Epoch: 0, Average Metrics: loss= 0.8598, accuracy= 0.6958, val_loss= 0.5671, val_accuracy= 0.7971
........Epoch: 8, Average Metrics: loss= 0.2163, accuracy= 0.9162, val_loss= 0.2260, val_accuracy= 0.9077
....
Epoch 00012: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 16, Average Metrics: loss= 0.1552, accuracy= 0.9384, val_loss= 0.1757, val_accuracy= 0.9357
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch: 24, Average Metrics: loss= 0.1190, accuracy= 0.9536, val_loss= 0.1591, val_accuracy= 0.9433
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
..Epoch: 32, Average Metrics: loss= 0.1006, accuracy= 0.9577, val_loss= 0.1722, val_accuracy= 0.9369
..
Epoch 00034: ReduceLROnPlateau reducing learning rate to 0.0002500000205814874.
..Epoch 00036: early stopping
Pass!

ID-14, Config:[256, 0.4, 256, 5, 64, 3, 64, 2, True, 64, 42], mean_val_acc:0.9173, mean_val_loss:0.2215,
Epoch: 0, Average Metrics: loss= 0.8005, accuracy= 0.7304, val_loss= 0.5045, val_accuracy= 0.8302
........Epoch: 8, Average Metrics: loss= 0.2238, accuracy= 0.9126, val_loss= 0.2321, val_accuracy= 0.9207
......
Epoch 00014: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch: 16, Average Metrics: loss= 0.1453, accuracy= 0.9417, val_loss= 0.1553, val_accuracy= 0.9465
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....
Epoch 00023: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
.Epoch: 24, Average Metrics: loss= 0.1134, accuracy= 0.9529, val_loss= 0.1694, val_accuracy= 0.9342
.Epoch 00025: early stopping
Pass!

ID-15, Config:[256, 0.4, 256, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9112, mean_val_loss:0.2315,
Epoch: 0, Average Metrics: loss= 0.7917, accuracy= 0.7376, val_loss= 0.5319, val_accuracy= 0.8233
........Epoch: 8, Average Metrics: loss= 0.2201, accuracy= 0.9142, val_loss= 0.2290, val_accuracy= 0.9134
........Epoch: 16, Average Metrics: loss= 0.1662, accuracy= 0.9341, val_loss= 0.2028, val_accuracy= 0.9247
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......Epoch: 24, Average Metrics: loss= 0.1289, accuracy= 0.9479, val_loss= 0.1662, val_accuracy= 0.9382
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch 00028: early stopping
Pass!

ID-16, Config:[256, 0.4, 256, 5, 128, 3, 64, 2, True, 64, 42], mean_val_acc:0.9113, mean_val_loss:0.2306,
Epoch: 0, Average Metrics: loss= 0.8770, accuracy= 0.7093, val_loss= 0.5497, val_accuracy= 0.8123
........Epoch: 8, Average Metrics: loss= 0.2350, accuracy= 0.9118, val_loss= 0.2415, val_accuracy= 0.8987
........Epoch: 16, Average Metrics: loss= 0.1722, accuracy= 0.9354, val_loss= 0.2082, val_accuracy= 0.9166
..
Epoch 00018: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
......Epoch 00024: early stopping
Pass!

ID-17, Config:[256, 0.5, 128, 3, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.9005, mean_val_loss:0.2599,
Epoch: 0, Average Metrics: loss= 0.8672, accuracy= 0.7045, val_loss= 0.4874, val_accuracy= 0.8231
........Epoch: 8, Average Metrics: loss= 0.2497, accuracy= 0.9049, val_loss= 0.2569, val_accuracy= 0.9048
........Epoch: 16, Average Metrics: loss= 0.1965, accuracy= 0.9217, val_loss= 0.2135, val_accuracy= 0.9109
.
Epoch 00017: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......Epoch: 24, Average Metrics: loss= 0.1310, accuracy= 0.9477, val_loss= 0.2048, val_accuracy= 0.9249
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.......Epoch: 32, Average Metrics: loss= 0.1099, accuracy= 0.9547, val_loss= 0.1834, val_accuracy= 0.9279
.
Epoch 00033: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
Epoch 00033: early stopping
Pass!

ID-18, Config:[256, 0.5, 128, 3, 64, 3, 64, 2, True, 64, 42], mean_val_acc:0.9139, mean_val_loss:0.2274,
Epoch: 0, Average Metrics: loss= 0.8516, accuracy= 0.7125, val_loss= 0.5278, val_accuracy= 0.8081
........Epoch: 8, Average Metrics: loss= 0.2300, accuracy= 0.9098, val_loss= 0.2431, val_accuracy= 0.9161
........Epoch: 16, Average Metrics: loss= 0.1728, accuracy= 0.9332, val_loss= 0.2092, val_accuracy= 0.9121
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1315, accuracy= 0.9474, val_loss= 0.1640, val_accuracy= 0.9394
..Epoch 00026: early stopping
Pass!

ID-19, Config:[256, 0.5, 128, 3, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9059, mean_val_loss:0.2468,
Epoch: 0, Average Metrics: loss= 0.8580, accuracy= 0.7078, val_loss= 0.5617, val_accuracy= 0.7958
........Epoch: 8, Average Metrics: loss= 0.2593, accuracy= 0.8973, val_loss= 0.2854, val_accuracy= 0.8564
........Epoch: 16, Average Metrics: loss= 0.1740, accuracy= 0.9299, val_loss= 0.2028, val_accuracy= 0.9315
....Epoch 00020: early stopping
Pass!

ID-20, Config:[256, 0.5, 128, 3, 128, 3, 64, 2, True, 64, 42], mean_val_acc:0.8912, mean_val_loss:0.2789,
Epoch: 0, Average Metrics: loss= 0.8652, accuracy= 0.7099, val_loss= 0.5295, val_accuracy= 0.7843
........Epoch: 8, Average Metrics: loss= 0.2260, accuracy= 0.9118, val_loss= 0.3006, val_accuracy= 0.8748
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 16, Average Metrics: loss= 0.1542, accuracy= 0.9381, val_loss= 0.2187, val_accuracy= 0.8842
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch 00021: early stopping
Pass!

ID-21, Config:[256, 0.5, 128, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8865, mean_val_loss:0.2886,
Epoch: 0, Average Metrics: loss= 0.8665, accuracy= 0.7103, val_loss= 0.5751, val_accuracy= 0.7936
........Epoch: 8, Average Metrics: loss= 0.2434, accuracy= 0.9080, val_loss= 0.2257, val_accuracy= 0.9107
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1586, accuracy= 0.9363, val_loss= 0.1491, val_accuracy= 0.9450
.....
Epoch 00021: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.Epoch 00022: early stopping
Pass!

ID-22, Config:[256, 0.5, 128, 5, 64, 3, 64, 2, True, 64, 42], mean_val_acc:0.9049, mean_val_loss:0.2484,
Epoch: 0, Average Metrics: loss= 0.8783, accuracy= 0.7116, val_loss= 0.5711, val_accuracy= 0.7806
........Epoch: 8, Average Metrics: loss= 0.2670, accuracy= 0.8983, val_loss= 0.2369, val_accuracy= 0.9126
........Epoch: 16, Average Metrics: loss= 0.1639, accuracy= 0.9375, val_loss= 0.2064, val_accuracy= 0.9185
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.....Epoch: 24, Average Metrics: loss= 0.1266, accuracy= 0.9478, val_loss= 0.2368, val_accuracy= 0.9016
...
Epoch 00027: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
.....Epoch: 32, Average Metrics: loss= 0.1172, accuracy= 0.9515, val_loss= 0.1786, val_accuracy= 0.9323
.Epoch 00033: early stopping
Pass!

ID-23, Config:[256, 0.5, 128, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9074, mean_val_loss:0.2412,
Epoch: 0, Average Metrics: loss= 0.8306, accuracy= 0.7113, val_loss= 0.5206, val_accuracy= 0.7988
........Epoch: 8, Average Metrics: loss= 0.2448, accuracy= 0.9069, val_loss= 0.2967, val_accuracy= 0.8694
.
Epoch 00009: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.......Epoch: 16, Average Metrics: loss= 0.1713, accuracy= 0.9329, val_loss= 0.1864, val_accuracy= 0.9298
........Epoch: 24, Average Metrics: loss= 0.1475, accuracy= 0.9422, val_loss= 0.2253, val_accuracy= 0.9274
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....
Epoch 00029: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
.Epoch 00030: early stopping
Pass!

ID-24, Config:[256, 0.5, 128, 5, 128, 3, 64, 2, True, 64, 42], mean_val_acc:0.9097, mean_val_loss:0.2331,
Epoch: 0, Average Metrics: loss= 0.8976, accuracy= 0.7019, val_loss= 0.6396, val_accuracy= 0.7364
........Epoch: 8, Average Metrics: loss= 0.2395, accuracy= 0.9077, val_loss= 0.2657, val_accuracy= 0.9033
........Epoch: 16, Average Metrics: loss= 0.1724, accuracy= 0.9345, val_loss= 0.2148, val_accuracy= 0.9148
........Epoch: 24, Average Metrics: loss= 0.1571, accuracy= 0.9383, val_loss= 0.1709, val_accuracy= 0.9433
....
Epoch 00028: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 32, Average Metrics: loss= 0.1141, accuracy= 0.9520, val_loss= 0.1558, val_accuracy= 0.9450
...Epoch 00035: early stopping
Pass!

ID-25, Config:[256, 0.5, 256, 3, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.9106, mean_val_loss:0.2314,
Epoch: 0, Average Metrics: loss= 0.8491, accuracy= 0.7105, val_loss= 0.5126, val_accuracy= 0.7936
........Epoch: 8, Average Metrics: loss= 0.2253, accuracy= 0.9147, val_loss= 0.2096, val_accuracy= 0.9207
........
Epoch 00016: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 16, Average Metrics: loss= 0.1810, accuracy= 0.9280, val_loss= 0.1871, val_accuracy= 0.9259
........Epoch: 24, Average Metrics: loss= 0.1334, accuracy= 0.9449, val_loss= 0.1905, val_accuracy= 0.9323
....Epoch 00028: early stopping
Pass!

ID-26, Config:[256, 0.5, 256, 3, 64, 3, 64, 2, True, 64, 42], mean_val_acc:0.9058, mean_val_loss:0.2444,
Epoch: 0, Average Metrics: loss= 0.8207, accuracy= 0.7205, val_loss= 0.5293, val_accuracy= 0.7882
........Epoch: 8, Average Metrics: loss= 0.2372, accuracy= 0.9092, val_loss= 0.2405, val_accuracy= 0.9104
........Epoch: 16, Average Metrics: loss= 0.1576, accuracy= 0.9374, val_loss= 0.2471, val_accuracy= 0.8967
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
....Epoch: 24, Average Metrics: loss= 0.1278, accuracy= 0.9483, val_loss= 0.1676, val_accuracy= 0.9421
.
Epoch 00025: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
....
Epoch 00029: ReduceLROnPlateau reducing learning rate to 0.0003535534073861587.
...Epoch 00032: early stopping
Pass!

ID-27, Config:[256, 0.5, 256, 3, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9129, mean_val_loss:0.2266,
Epoch: 0, Average Metrics: loss= 0.8453, accuracy= 0.7132, val_loss= 0.5898, val_accuracy= 0.7882
........Epoch: 8, Average Metrics: loss= 0.2349, accuracy= 0.9118, val_loss= 0.2131, val_accuracy= 0.9161
........Epoch: 16, Average Metrics: loss= 0.1702, accuracy= 0.9324, val_loss= 0.1958, val_accuracy= 0.9207
....
Epoch 00020: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
...Epoch 00023: early stopping
Pass!

ID-28, Config:[256, 0.5, 256, 3, 128, 3, 64, 2, True, 64, 42], mean_val_acc:0.9052, mean_val_loss:0.2502,
Epoch: 0, Average Metrics: loss= 0.8520, accuracy= 0.7138, val_loss= 0.5058, val_accuracy= 0.8130
........Epoch: 8, Average Metrics: loss= 0.2330, accuracy= 0.9092, val_loss= 0.2409, val_accuracy= 0.9119
........Epoch: 16, Average Metrics: loss= 0.1694, accuracy= 0.9331, val_loss= 0.2529, val_accuracy= 0.9082
...
Epoch 00019: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
..Epoch 00021: early stopping
Pass!

ID-29, Config:[256, 0.5, 256, 5, 64, 2, 64, 2, True, 64, 42], mean_val_acc:0.8982, mean_val_loss:0.2664,
Epoch: 0, Average Metrics: loss= 0.8309, accuracy= 0.7198, val_loss= 0.4757, val_accuracy= 0.8265
........Epoch: 8, Average Metrics: loss= 0.2353, accuracy= 0.9104, val_loss= 0.2163, val_accuracy= 0.9114
........Epoch: 16, Average Metrics: loss= 0.1901, accuracy= 0.9267, val_loss= 0.1864, val_accuracy= 0.9281
.....Epoch 00021: early stopping
Pass!

ID-30, Config:[256, 0.5, 256, 5, 64, 3, 64, 2, True, 64, 42], mean_val_acc:0.9025, mean_val_loss:0.2535,
Epoch: 0, Average Metrics: loss= 0.8248, accuracy= 0.7221, val_loss= 0.4910, val_accuracy= 0.8250
........Epoch: 8, Average Metrics: loss= 0.2331, accuracy= 0.9085, val_loss= 0.2694, val_accuracy= 0.8697
........Epoch: 16, Average Metrics: loss= 0.1777, accuracy= 0.9296, val_loss= 0.1800, val_accuracy= 0.9303
........
Epoch 00024: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
Epoch: 24, Average Metrics: loss= 0.1424, accuracy= 0.9419, val_loss= 0.1719, val_accuracy= 0.9306
......
Epoch 00030: ReduceLROnPlateau reducing learning rate to 0.0005000000411629748.
Epoch 00030: early stopping
Pass!

ID-31, Config:[256, 0.5, 256, 5, 128, 2, 64, 2, True, 64, 42], mean_val_acc:0.9133, mean_val_loss:0.2319,
Epoch: 0, Average Metrics: loss= 0.8074, accuracy= 0.7387, val_loss= 0.5117, val_accuracy= 0.8150
........Epoch: 8, Average Metrics: loss= 0.2202, accuracy= 0.9142, val_loss= 0.2758, val_accuracy= 0.8856
.......
Epoch 00015: ReduceLROnPlateau reducing learning rate to 0.0007071068147723174.
.Epoch: 16, Average Metrics: loss= 0.1528, accuracy= 0.9372, val_loss= 0.1716, val_accuracy= 0.9369
....Epoch 00020: early stopping
Pass!

ID-32, Config:[256, 0.5, 256, 5, 128, 3, 64, 2, True, 64, 42], mean_val_acc:0.9018, mean_val_loss:0.2566,
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---