Using file 'test_job.in' Metric: accuracy, threshold: 0.100E-01 No regularisation set Momentum-based adaptive learning method momentum = 0.899999976 Dropout method: none ======PARAMETERS====== shuffle dataset: T batch learning: T learning rate: 9.99999978E-03 number of epochs: 10 number of filters: 32 hidden layers: 100 ====================== Data read Data read Shuffling training dataset... Training dataset shuffled Initialising CNN... CONV2D input gradients turned off CONV2D activation function: relu CONV2D kernel initialiser: he_uniform CONV2D bias initialiser: zeros FULL activation function: relu FULL kernel initialiser: he_uniform FULL bias initialiser: he_uniform FULL activation function: softmax FULL kernel initialiser: glorot_uniform FULL bias initialiser: glorot_uniform Loss method: Categorical Cross Entropy layer: 1 inpt 30 30 1 30 30 1 layer: 2 conv 28 28 1 28 28 32 layer: 3 pool 28 28 32 14 14 32 layer: 4 full 6272 100 layer: 5 full 100 10 NUMBER OF LAYERS 6 Starting training... epoch=1, batch=1, learning_rate=.010, loss=2.669, accuracy=.031 epoch=1, batch=20, learning_rate=.010, loss=2.164, accuracy=.261 epoch=1, batch=40, learning_rate=.010, loss=1.787, accuracy=.433 epoch=1, batch=60, learning_rate=.010, loss=1.578, accuracy=.536 epoch=1, batch=80, learning_rate=.010, loss=1.477, accuracy=.592 epoch=1, batch=100, learning_rate=.010, loss=1.374, accuracy=.634 epoch=1, batch=120, learning_rate=.010, loss=1.272, accuracy=.663 epoch=1, batch=140, learning_rate=.010, loss=1.163, accuracy=.694 epoch=1, batch=160, learning_rate=.010, loss=1.078, accuracy=.715 epoch=1, batch=180, learning_rate=.010, loss=1.002, accuracy=.735 epoch=1, batch=200, learning_rate=.010, loss=.944, accuracy=.747 epoch=1, batch=220, learning_rate=.010, loss=.896, accuracy=.758 epoch=1, batch=240, learning_rate=.010, loss=.850, accuracy=.770 epoch=1, batch=260, learning_rate=.010, loss=.813, accuracy=.779 epoch=1, batch=280, learning_rate=.010, loss=.780, accuracy=.787 epoch=1, batch=300, learning_rate=.010, loss=.751, accuracy=.793 epoch=1, batch=320, learning_rate=.010, loss=.726, accuracy=.800 epoch=1, batch=340, learning_rate=.010, loss=.706, accuracy=.805 epoch=1, batch=360, learning_rate=.010, loss=.689, accuracy=.810 epoch=1, batch=380, learning_rate=.010, loss=.671, accuracy=.814 epoch=1, batch=400, learning_rate=.010, loss=.658, accuracy=.819 epoch=1, batch=420, learning_rate=.010, loss=.644, accuracy=.823 epoch=1, batch=440, learning_rate=.010, loss=.631, accuracy=.826 epoch=1, batch=460, learning_rate=.010, loss=.615, accuracy=.830 epoch=1, batch=480, learning_rate=.010, loss=.602, accuracy=.834 epoch=1, batch=500, learning_rate=.010, loss=.590, accuracy=.837 epoch=1, batch=520, learning_rate=.010, loss=.578, accuracy=.840 epoch=1, batch=540, learning_rate=.010, loss=.568, accuracy=.843 epoch=1, batch=560, learning_rate=.010, loss=.558, accuracy=.845 epoch=1, batch=580, learning_rate=.010, loss=.552, accuracy=.847 epoch=1, batch=600, learning_rate=.010, loss=.543, accuracy=.849 epoch=1, batch=620, learning_rate=.010, loss=.536, accuracy=.851 epoch=1, batch=640, learning_rate=.010, loss=.529, accuracy=.853 epoch=1, batch=660, learning_rate=.010, loss=.519, accuracy=.855 epoch=1, batch=680, learning_rate=.010, loss=.512, accuracy=.857 epoch=1, batch=700, learning_rate=.010, loss=.505, accuracy=.859 epoch=1, batch=720, learning_rate=.010, loss=.498, accuracy=.861 epoch=1, batch=740, learning_rate=.010, loss=.490, accuracy=.863 epoch=1, batch=760, learning_rate=.010, loss=.482, accuracy=.865 epoch=1, batch=780, learning_rate=.010, loss=.478, accuracy=.866 epoch=1, batch=800, learning_rate=.010, loss=.472, accuracy=.868 epoch=1, batch=820, learning_rate=.010, loss=.467, accuracy=.869 epoch=1, batch=840, learning_rate=.010, loss=.462, accuracy=.871 epoch=1, batch=860, learning_rate=.010, loss=.458, accuracy=.872 epoch=1, batch=880, learning_rate=.010, loss=.454, accuracy=.873 epoch=1, batch=900, learning_rate=.010, loss=.450, accuracy=.875 epoch=1, batch=920, learning_rate=.010, loss=.446, accuracy=.875 epoch=1, batch=940, learning_rate=.010, loss=.442, accuracy=.877 epoch=1, batch=960, learning_rate=.010, loss=.438, accuracy=.878 epoch=1, batch=980, learning_rate=.010, loss=.435, accuracy=.879 epoch=1, batch=1000, learning_rate=.010, loss=.430, accuracy=.880 epoch=1, batch=1020, learning_rate=.010, loss=.428, accuracy=.881 epoch=1, batch=1040, learning_rate=.010, loss=.423, accuracy=.882 epoch=1, batch=1060, learning_rate=.010, loss=.419, accuracy=.883 epoch=1, batch=1080, learning_rate=.010, loss=.417, accuracy=.884 epoch=1, batch=1100, learning_rate=.010, loss=.413, accuracy=.885 epoch=1, batch=1120, learning_rate=.010, loss=.409, accuracy=.886 epoch=1, batch=1140, learning_rate=.010, loss=.405, accuracy=.887 epoch=1, batch=1160, learning_rate=.010, loss=.401, accuracy=.888 epoch=1, batch=1180, learning_rate=.010, loss=.397, accuracy=.889 epoch=1, batch=1200, learning_rate=.010, loss=.395, accuracy=.890 epoch=1, batch=1220, learning_rate=.010, loss=.391, accuracy=.891 epoch=1, batch=1240, learning_rate=.010, loss=.388, accuracy=.892 epoch=1, batch=1260, learning_rate=.010, loss=.385, accuracy=.893 epoch=1, batch=1280, learning_rate=.010, loss=.382, accuracy=.893 epoch=1, batch=1300, learning_rate=.010, loss=.380, accuracy=.894 epoch=1, batch=1320, learning_rate=.010, loss=.378, accuracy=.895 epoch=1, batch=1340, learning_rate=.010, loss=.375, accuracy=.895 epoch=1, batch=1360, learning_rate=.010, loss=.373, accuracy=.896 epoch=1, batch=1380, learning_rate=.010, loss=.371, accuracy=.897 epoch=1, batch=1400, learning_rate=.010, loss=.368, accuracy=.897 epoch=1, batch=1420, learning_rate=.010, loss=.366, accuracy=.898 epoch=1, batch=1440, learning_rate=.010, loss=.364, accuracy=.899 epoch=1, batch=1460, learning_rate=.010, loss=.362, accuracy=.899 epoch=1, batch=1480, learning_rate=.010, loss=.361, accuracy=.900 epoch=1, batch=1500, learning_rate=.010, loss=.358, accuracy=.900 epoch=1, batch=1520, learning_rate=.010, loss=.356, accuracy=.901 epoch=1, batch=1540, learning_rate=.010, loss=.354, accuracy=.902 epoch=1, batch=1560, learning_rate=.010, loss=.352, accuracy=.902 epoch=1, batch=1580, learning_rate=.010, loss=.350, accuracy=.903 epoch=1, batch=1600, learning_rate=.010, loss=.347, accuracy=.903 epoch=1, batch=1620, learning_rate=.010, loss=.346, accuracy=.904 epoch=1, batch=1640, learning_rate=.010, loss=.344, accuracy=.904 epoch=1, batch=1660, learning_rate=.010, loss=.342, accuracy=.905 epoch=1, batch=1680, learning_rate=.010, loss=.341, accuracy=.905 epoch=1, batch=1700, learning_rate=.010, loss=.339, accuracy=.906 epoch=1, batch=1720, learning_rate=.010, loss=.337, accuracy=.906 epoch=1, batch=1740, learning_rate=.010, loss=.335, accuracy=.907 epoch=1, batch=1760, learning_rate=.010, loss=.334, accuracy=.907 epoch=1, batch=1780, learning_rate=.010, loss=.332, accuracy=.907 epoch=1, batch=1800, learning_rate=.010, loss=.331, accuracy=.908 epoch=1, batch=1820, learning_rate=.010, loss=.329, accuracy=.908 epoch=1, batch=1840, learning_rate=.010, loss=.327, accuracy=.909 epoch=1, batch=1860, learning_rate=.010, loss=.326, accuracy=.909 epoch=2, batch=1, learning_rate=.010, loss=.214, accuracy=.938 epoch=2, batch=20, learning_rate=.010, loss=.226, accuracy=.933 epoch=2, batch=40, learning_rate=.010, loss=.204, accuracy=.941 epoch=2, batch=60, learning_rate=.010, loss=.204, accuracy=.944 epoch=2, batch=80, learning_rate=.010, loss=.190, accuracy=.950 epoch=2, batch=100, learning_rate=.010, loss=.196, accuracy=.949 epoch=2, batch=120, learning_rate=.010, loss=.191, accuracy=.950 epoch=2, batch=140, learning_rate=.010, loss=.186, accuracy=.950 epoch=2, batch=160, learning_rate=.010, loss=.186, accuracy=.950 epoch=2, batch=180, learning_rate=.010, loss=.187, accuracy=.948 epoch=2, batch=200, learning_rate=.010, loss=.182, accuracy=.949 epoch=2, batch=220, learning_rate=.010, loss=.184, accuracy=.949 epoch=2, batch=240, learning_rate=.010, loss=.181, accuracy=.950 epoch=2, batch=260, learning_rate=.010, loss=.177, accuracy=.951 epoch=2, batch=280, learning_rate=.010, loss=.177, accuracy=.950 epoch=2, batch=300, learning_rate=.010, loss=.177, accuracy=.950 epoch=2, batch=320, learning_rate=.010, loss=.177, accuracy=.951 epoch=2, batch=340, learning_rate=.010, loss=.178, accuracy=.950 epoch=2, batch=360, learning_rate=.010, loss=.179, accuracy=.949 epoch=2, batch=380, learning_rate=.010, loss=.178, accuracy=.950 epoch=2, batch=400, learning_rate=.010, loss=.176, accuracy=.950 epoch=2, batch=420, learning_rate=.010, loss=.176, accuracy=.950 epoch=2, batch=440, learning_rate=.010, loss=.174, accuracy=.951 epoch=2, batch=460, learning_rate=.010, loss=.173, accuracy=.951 epoch=2, batch=480, learning_rate=.010, loss=.172, accuracy=.951 epoch=2, batch=500, learning_rate=.010, loss=.171, accuracy=.951 epoch=2, batch=520, learning_rate=.010, loss=.172, accuracy=.951 epoch=2, batch=540, learning_rate=.010, loss=.172, accuracy=.952 epoch=2, batch=560, learning_rate=.010, loss=.171, accuracy=.952 epoch=2, batch=580, learning_rate=.010, loss=.172, accuracy=.952 epoch=2, batch=600, learning_rate=.010, loss=.172, accuracy=.952 epoch=2, batch=620, learning_rate=.010, loss=.173, accuracy=.952 epoch=2, batch=640, learning_rate=.010, loss=.171, accuracy=.952 epoch=2, batch=660, learning_rate=.010, loss=.170, accuracy=.952 epoch=2, batch=680, learning_rate=.010, loss=.170, accuracy=.952 epoch=2, batch=700, learning_rate=.010, loss=.170, accuracy=.952 epoch=2, batch=720, learning_rate=.010, loss=.169, accuracy=.953 epoch=2, batch=740, learning_rate=.010, loss=.168, accuracy=.953 epoch=2, batch=760, learning_rate=.010, loss=.167, accuracy=.953 epoch=2, batch=780, learning_rate=.010, loss=.166, accuracy=.954 epoch=2, batch=800, learning_rate=.010, loss=.165, accuracy=.954 epoch=2, batch=820, learning_rate=.010, loss=.164, accuracy=.954 epoch=2, batch=840, learning_rate=.010, loss=.163, accuracy=.955 epoch=2, batch=860, learning_rate=.010, loss=.163, accuracy=.955 epoch=2, batch=880, learning_rate=.010, loss=.162, accuracy=.955 epoch=2, batch=900, learning_rate=.010, loss=.163, accuracy=.955 epoch=2, batch=920, learning_rate=.010, loss=.162, accuracy=.955 epoch=2, batch=940, learning_rate=.010, loss=.162, accuracy=.955 epoch=2, batch=960, learning_rate=.010, loss=.162, accuracy=.955 epoch=2, batch=980, learning_rate=.010, loss=.161, accuracy=.955 epoch=2, batch=1000, learning_rate=.010, loss=.161, accuracy=.955 epoch=2, batch=1020, learning_rate=.010, loss=.161, accuracy=.955 epoch=2, batch=1040, learning_rate=.010, loss=.161, accuracy=.955 epoch=2, batch=1060, learning_rate=.010, loss=.160, accuracy=.955 epoch=2, batch=1080, learning_rate=.010, loss=.160, accuracy=.955 epoch=2, batch=1100, learning_rate=.010, loss=.161, accuracy=.955 epoch=2, batch=1120, learning_rate=.010, loss=.160, accuracy=.955 epoch=2, batch=1140, learning_rate=.010, loss=.160, accuracy=.955 epoch=2, batch=1160, learning_rate=.010, loss=.160, accuracy=.956 epoch=2, batch=1180, learning_rate=.010, loss=.160, accuracy=.956 epoch=2, batch=1200, learning_rate=.010, loss=.159, accuracy=.956 epoch=2, batch=1220, learning_rate=.010, loss=.158, accuracy=.956 epoch=2, batch=1240, learning_rate=.010, loss=.158, accuracy=.956 epoch=2, batch=1260, learning_rate=.010, loss=.158, accuracy=.956 epoch=2, batch=1280, learning_rate=.010, loss=.158, accuracy=.956 epoch=2, batch=1300, learning_rate=.010, loss=.157, accuracy=.956 epoch=2, batch=1320, learning_rate=.010, loss=.157, accuracy=.956 epoch=2, batch=1340, learning_rate=.010, loss=.157, accuracy=.957 epoch=2, batch=1360, learning_rate=.010, loss=.156, accuracy=.957 epoch=2, batch=1380, learning_rate=.010, loss=.155, accuracy=.957 epoch=2, batch=1400, learning_rate=.010, loss=.155, accuracy=.957 epoch=2, batch=1420, learning_rate=.010, loss=.154, accuracy=.957 epoch=2, batch=1440, learning_rate=.010, loss=.153, accuracy=.958 epoch=2, batch=1460, learning_rate=.010, loss=.153, accuracy=.957 epoch=2, batch=1480, learning_rate=.010, loss=.153, accuracy=.957 epoch=2, batch=1500, learning_rate=.010, loss=.153, accuracy=.958 epoch=2, batch=1520, learning_rate=.010, loss=.153, accuracy=.958 epoch=2, batch=1540, learning_rate=.010, loss=.153, accuracy=.958 epoch=2, batch=1560, learning_rate=.010, loss=.152, accuracy=.958 epoch=2, batch=1580, learning_rate=.010, loss=.153, accuracy=.958 epoch=2, batch=1600, learning_rate=.010, loss=.152, accuracy=.958 epoch=2, batch=1620, learning_rate=.010, loss=.152, accuracy=.958 epoch=2, batch=1640, learning_rate=.010, loss=.152, accuracy=.958 epoch=2, batch=1660, learning_rate=.010, loss=.151, accuracy=.958 epoch=2, batch=1680, learning_rate=.010, loss=.152, accuracy=.958 epoch=2, batch=1700, learning_rate=.010, loss=.151, accuracy=.958 epoch=2, batch=1720, learning_rate=.010, loss=.151, accuracy=.958 epoch=2, batch=1740, learning_rate=.010, loss=.151, accuracy=.958 epoch=2, batch=1760, learning_rate=.010, loss=.150, accuracy=.958 epoch=2, batch=1780, learning_rate=.010, loss=.150, accuracy=.958 epoch=2, batch=1800, learning_rate=.010, loss=.150, accuracy=.959 epoch=2, batch=1820, learning_rate=.010, loss=.149, accuracy=.959 epoch=2, batch=1840, learning_rate=.010, loss=.149, accuracy=.959 epoch=2, batch=1860, learning_rate=.010, loss=.149, accuracy=.959 epoch=3, batch=1, learning_rate=.010, loss=.180, accuracy=.969 epoch=3, batch=20, learning_rate=.010, loss=.121, accuracy=.964 epoch=3, batch=40, learning_rate=.010, loss=.137, accuracy=.963 epoch=3, batch=60, learning_rate=.010, loss=.141, accuracy=.962 epoch=3, batch=80, learning_rate=.010, loss=.138, accuracy=.962 epoch=3, batch=100, learning_rate=.010, loss=.130, accuracy=.964 epoch=3, batch=120, learning_rate=.010, loss=.135, accuracy=.962 epoch=3, batch=140, learning_rate=.010, loss=.136, accuracy=.963 epoch=3, batch=160, learning_rate=.010, loss=.134, accuracy=.964 epoch=3, batch=180, learning_rate=.010, loss=.136, accuracy=.963 Convergence achieved, accuracy threshold reached Exiting training loop Writing network to file... Writing finished Starting testing... Testing finished Overall accuracy=.97040 Overall loss=.10389