CHECK: Is CUDA the right version (10)? Creating network using backbone resnet101 Not applying augmentation to RGBD data Loading a pascal format RGBD dataset Loading imagenet weights Creating model, this may take a second... Building ResNet backbone using defined input shape of Tensor("input_1:0", shape=(?, ?, ?, 4), dtype=float32) Loading weights into model tracking anchors tracking anchors tracking anchors tracking anchors tracking anchors Model: "retinanet" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== input_1 (InputLayer) (None, None, None, 4 0 __________________________________________________________________________________________________ padding_conv1 (ZeroPadding2D) (None, None, None, 4 0 input_1[0][0] __________________________________________________________________________________________________ conv1 (Conv2D) (None, None, None, 6 12544 padding_conv1[0][0] __________________________________________________________________________________________________ bn_conv1 (BatchNormalization) (None, None, None, 6 256 conv1[0][0] __________________________________________________________________________________________________ conv1_relu (Activation) (None, None, None, 6 0 bn_conv1[0][0] __________________________________________________________________________________________________ pool1 (MaxPooling2D) (None, None, None, 6 0 conv1_relu[0][0] __________________________________________________________________________________________________ res2a_branch2a (Conv2D) (None, None, None, 6 4096 pool1[0][0] __________________________________________________________________________________________________ bn2a_branch2a (BatchNormalizati (None, None, None, 6 256 res2a_branch2a[0][0] __________________________________________________________________________________________________ res2a_branch2a_relu (Activation (None, None, None, 6 0 bn2a_branch2a[0][0] __________________________________________________________________________________________________ padding2a_branch2b (ZeroPadding (None, None, None, 6 0 res2a_branch2a_relu[0][0] __________________________________________________________________________________________________ res2a_branch2b (Conv2D) (None, None, None, 6 36864 padding2a_branch2b[0][0] __________________________________________________________________________________________________ bn2a_branch2b (BatchNormalizati (None, None, None, 6 256 res2a_branch2b[0][0] __________________________________________________________________________________________________ res2a_branch2b_relu (Activation (None, None, None, 6 0 bn2a_branch2b[0][0] __________________________________________________________________________________________________ res2a_branch2c (Conv2D) (None, None, None, 2 16384 res2a_branch2b_relu[0][0] __________________________________________________________________________________________________ res2a_branch1 (Conv2D) (None, None, None, 2 16384 pool1[0][0] __________________________________________________________________________________________________ bn2a_branch2c (BatchNormalizati (None, None, None, 2 1024 res2a_branch2c[0][0] __________________________________________________________________________________________________ bn2a_branch1 (BatchNormalizatio (None, None, None, 2 1024 res2a_branch1[0][0] __________________________________________________________________________________________________ res2a (Add) (None, None, None, 2 0 bn2a_branch2c[0][0] bn2a_branch1[0][0] __________________________________________________________________________________________________ res2a_relu (Activation) (None, None, None, 2 0 res2a[0][0] __________________________________________________________________________________________________ res2b_branch2a (Conv2D) (None, None, None, 6 16384 res2a_relu[0][0] __________________________________________________________________________________________________ bn2b_branch2a (BatchNormalizati (None, None, None, 6 256 res2b_branch2a[0][0] __________________________________________________________________________________________________ res2b_branch2a_relu (Activation (None, None, None, 6 0 bn2b_branch2a[0][0] __________________________________________________________________________________________________ padding2b_branch2b (ZeroPadding (None, None, None, 6 0 res2b_branch2a_relu[0][0] __________________________________________________________________________________________________ res2b_branch2b (Conv2D) (None, None, None, 6 36864 padding2b_branch2b[0][0] __________________________________________________________________________________________________ bn2b_branch2b (BatchNormalizati (None, None, None, 6 256 res2b_branch2b[0][0] __________________________________________________________________________________________________ res2b_branch2b_relu (Activation (None, None, None, 6 0 bn2b_branch2b[0][0] __________________________________________________________________________________________________ res2b_branch2c (Conv2D) (None, None, None, 2 16384 res2b_branch2b_relu[0][0] __________________________________________________________________________________________________ bn2b_branch2c (BatchNormalizati (None, None, None, 2 1024 res2b_branch2c[0][0] __________________________________________________________________________________________________ res2b (Add) (None, None, None, 2 0 bn2b_branch2c[0][0] res2a_relu[0][0] __________________________________________________________________________________________________ res2b_relu (Activation) (None, None, None, 2 0 res2b[0][0] __________________________________________________________________________________________________ res2c_branch2a (Conv2D) (None, None, None, 6 16384 res2b_relu[0][0] __________________________________________________________________________________________________ bn2c_branch2a (BatchNormalizati (None, None, None, 6 256 res2c_branch2a[0][0] __________________________________________________________________________________________________ res2c_branch2a_relu (Activation (None, None, None, 6 0 bn2c_branch2a[0][0] __________________________________________________________________________________________________ padding2c_branch2b (ZeroPadding (None, None, None, 6 0 res2c_branch2a_relu[0][0] __________________________________________________________________________________________________ res2c_branch2b (Conv2D) (None, None, None, 6 36864 padding2c_branch2b[0][0] __________________________________________________________________________________________________ bn2c_branch2b (BatchNormalizati (None, None, None, 6 256 res2c_branch2b[0][0] __________________________________________________________________________________________________ res2c_branch2b_relu (Activation (None, None, None, 6 0 bn2c_branch2b[0][0] __________________________________________________________________________________________________ res2c_branch2c (Conv2D) (None, None, None, 2 16384 res2c_branch2b_relu[0][0] __________________________________________________________________________________________________ bn2c_branch2c (BatchNormalizati (None, None, None, 2 1024 res2c_branch2c[0][0] __________________________________________________________________________________________________ res2c (Add) (None, None, None, 2 0 bn2c_branch2c[0][0] res2b_relu[0][0] __________________________________________________________________________________________________ res2c_relu (Activation) (None, None, None, 2 0 res2c[0][0] __________________________________________________________________________________________________ res3a_branch2a (Conv2D) (None, None, None, 1 32768 res2c_relu[0][0] __________________________________________________________________________________________________ bn3a_branch2a (BatchNormalizati (None, None, None, 1 512 res3a_branch2a[0][0] __________________________________________________________________________________________________ res3a_branch2a_relu (Activation (None, None, None, 1 0 bn3a_branch2a[0][0] __________________________________________________________________________________________________ padding3a_branch2b (ZeroPadding (None, None, None, 1 0 res3a_branch2a_relu[0][0] __________________________________________________________________________________________________ res3a_branch2b (Conv2D) (None, None, None, 1 147456 padding3a_branch2b[0][0] __________________________________________________________________________________________________ bn3a_branch2b (BatchNormalizati (None, None, None, 1 512 res3a_branch2b[0][0] __________________________________________________________________________________________________ res3a_branch2b_relu (Activation (None, None, None, 1 0 bn3a_branch2b[0][0] __________________________________________________________________________________________________ res3a_branch2c (Conv2D) (None, None, None, 5 65536 res3a_branch2b_relu[0][0] __________________________________________________________________________________________________ res3a_branch1 (Conv2D) (None, None, None, 5 131072 res2c_relu[0][0] __________________________________________________________________________________________________ bn3a_branch2c (BatchNormalizati (None, None, None, 5 2048 res3a_branch2c[0][0] __________________________________________________________________________________________________ bn3a_branch1 (BatchNormalizatio (None, None, None, 5 2048 res3a_branch1[0][0] __________________________________________________________________________________________________ res3a (Add) (None, None, None, 5 0 bn3a_branch2c[0][0] bn3a_branch1[0][0] __________________________________________________________________________________________________ res3a_relu (Activation) (None, None, None, 5 0 res3a[0][0] __________________________________________________________________________________________________ res3b1_branch2a (Conv2D) (None, None, None, 1 65536 res3a_relu[0][0] __________________________________________________________________________________________________ bn3b1_branch2a (BatchNormalizat (None, None, None, 1 512 res3b1_branch2a[0][0] __________________________________________________________________________________________________ res3b1_branch2a_relu (Activatio (None, None, None, 1 0 bn3b1_branch2a[0][0] __________________________________________________________________________________________________ padding3b1_branch2b (ZeroPaddin (None, None, None, 1 0 res3b1_branch2a_relu[0][0] __________________________________________________________________________________________________ res3b1_branch2b (Conv2D) (None, None, None, 1 147456 padding3b1_branch2b[0][0] __________________________________________________________________________________________________ bn3b1_branch2b (BatchNormalizat (None, None, None, 1 512 res3b1_branch2b[0][0] __________________________________________________________________________________________________ res3b1_branch2b_relu (Activatio (None, None, None, 1 0 bn3b1_branch2b[0][0] __________________________________________________________________________________________________ res3b1_branch2c (Conv2D) (None, None, None, 5 65536 res3b1_branch2b_relu[0][0] __________________________________________________________________________________________________ bn3b1_branch2c (BatchNormalizat (None, None, None, 5 2048 res3b1_branch2c[0][0] __________________________________________________________________________________________________ res3b1 (Add) (None, None, None, 5 0 bn3b1_branch2c[0][0] res3a_relu[0][0] __________________________________________________________________________________________________ res3b1_relu (Activation) (None, None, None, 5 0 res3b1[0][0] __________________________________________________________________________________________________ res3b2_branch2a (Conv2D) (None, None, None, 1 65536 res3b1_relu[0][0] __________________________________________________________________________________________________ bn3b2_branch2a (BatchNormalizat (None, None, None, 1 512 res3b2_branch2a[0][0] __________________________________________________________________________________________________ res3b2_branch2a_relu (Activatio (None, None, None, 1 0 bn3b2_branch2a[0][0] __________________________________________________________________________________________________ padding3b2_branch2b (ZeroPaddin (None, None, None, 1 0 res3b2_branch2a_relu[0][0] __________________________________________________________________________________________________ res3b2_branch2b (Conv2D) (None, None, None, 1 147456 padding3b2_branch2b[0][0] __________________________________________________________________________________________________ bn3b2_branch2b (BatchNormalizat (None, None, None, 1 512 res3b2_branch2b[0][0] __________________________________________________________________________________________________ res3b2_branch2b_relu (Activatio (None, None, None, 1 0 bn3b2_branch2b[0][0] __________________________________________________________________________________________________ res3b2_branch2c (Conv2D) (None, None, None, 5 65536 res3b2_branch2b_relu[0][0] __________________________________________________________________________________________________ bn3b2_branch2c (BatchNormalizat (None, None, None, 5 2048 res3b2_branch2c[0][0] __________________________________________________________________________________________________ res3b2 (Add) (None, None, None, 5 0 bn3b2_branch2c[0][0] res3b1_relu[0][0] __________________________________________________________________________________________________ res3b2_relu (Activation) (None, None, None, 5 0 res3b2[0][0] __________________________________________________________________________________________________ res3b3_branch2a (Conv2D) (None, None, None, 1 65536 res3b2_relu[0][0] __________________________________________________________________________________________________ bn3b3_branch2a (BatchNormalizat (None, None, None, 1 512 res3b3_branch2a[0][0] __________________________________________________________________________________________________ res3b3_branch2a_relu (Activatio (None, None, None, 1 0 bn3b3_branch2a[0][0] __________________________________________________________________________________________________ padding3b3_branch2b (ZeroPaddin (None, None, None, 1 0 res3b3_branch2a_relu[0][0] __________________________________________________________________________________________________ res3b3_branch2b (Conv2D) (None, None, None, 1 147456 padding3b3_branch2b[0][0] __________________________________________________________________________________________________ bn3b3_branch2b (BatchNormalizat (None, None, None, 1 512 res3b3_branch2b[0][0] __________________________________________________________________________________________________ res3b3_branch2b_relu (Activatio (None, None, None, 1 0 bn3b3_branch2b[0][0] __________________________________________________________________________________________________ res3b3_branch2c (Conv2D) (None, None, None, 5 65536 res3b3_branch2b_relu[0][0] __________________________________________________________________________________________________ bn3b3_branch2c (BatchNormalizat (None, None, None, 5 2048 res3b3_branch2c[0][0] __________________________________________________________________________________________________ res3b3 (Add) (None, None, None, 5 0 bn3b3_branch2c[0][0] res3b2_relu[0][0] __________________________________________________________________________________________________ res3b3_relu (Activation) (None, None, None, 5 0 res3b3[0][0] __________________________________________________________________________________________________ res4a_branch2a (Conv2D) (None, None, None, 2 131072 res3b3_relu[0][0] __________________________________________________________________________________________________ bn4a_branch2a (BatchNormalizati (None, None, None, 2 1024 res4a_branch2a[0][0] __________________________________________________________________________________________________ res4a_branch2a_relu (Activation (None, None, None, 2 0 bn4a_branch2a[0][0] __________________________________________________________________________________________________ padding4a_branch2b (ZeroPadding (None, None, None, 2 0 res4a_branch2a_relu[0][0] __________________________________________________________________________________________________ res4a_branch2b (Conv2D) (None, None, None, 2 589824 padding4a_branch2b[0][0] __________________________________________________________________________________________________ bn4a_branch2b (BatchNormalizati (None, None, None, 2 1024 res4a_branch2b[0][0] __________________________________________________________________________________________________ res4a_branch2b_relu (Activation (None, None, None, 2 0 bn4a_branch2b[0][0] __________________________________________________________________________________________________ res4a_branch2c (Conv2D) (None, None, None, 1 262144 res4a_branch2b_relu[0][0] __________________________________________________________________________________________________ res4a_branch1 (Conv2D) (None, None, None, 1 524288 res3b3_relu[0][0] __________________________________________________________________________________________________ bn4a_branch2c (BatchNormalizati (None, None, None, 1 4096 res4a_branch2c[0][0] __________________________________________________________________________________________________ bn4a_branch1 (BatchNormalizatio (None, None, None, 1 4096 res4a_branch1[0][0] __________________________________________________________________________________________________ res4a (Add) (None, None, None, 1 0 bn4a_branch2c[0][0] bn4a_branch1[0][0] __________________________________________________________________________________________________ res4a_relu (Activation) (None, None, None, 1 0 res4a[0][0] __________________________________________________________________________________________________ res4b1_branch2a (Conv2D) (None, None, None, 2 262144 res4a_relu[0][0] __________________________________________________________________________________________________ bn4b1_branch2a (BatchNormalizat (None, None, None, 2 1024 res4b1_branch2a[0][0] __________________________________________________________________________________________________ res4b1_branch2a_relu (Activatio (None, None, None, 2 0 bn4b1_branch2a[0][0] __________________________________________________________________________________________________ padding4b1_branch2b (ZeroPaddin (None, None, None, 2 0 res4b1_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b1_branch2b (Conv2D) (None, None, None, 2 589824 padding4b1_branch2b[0][0] __________________________________________________________________________________________________ bn4b1_branch2b (BatchNormalizat (None, None, None, 2 1024 res4b1_branch2b[0][0] __________________________________________________________________________________________________ res4b1_branch2b_relu (Activatio (None, None, None, 2 0 bn4b1_branch2b[0][0] __________________________________________________________________________________________________ res4b1_branch2c (Conv2D) (None, None, None, 1 262144 res4b1_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b1_branch2c (BatchNormalizat (None, None, None, 1 4096 res4b1_branch2c[0][0] __________________________________________________________________________________________________ res4b1 (Add) (None, None, None, 1 0 bn4b1_branch2c[0][0] res4a_relu[0][0] __________________________________________________________________________________________________ res4b1_relu (Activation) (None, None, None, 1 0 res4b1[0][0] __________________________________________________________________________________________________ res4b2_branch2a (Conv2D) (None, None, None, 2 262144 res4b1_relu[0][0] __________________________________________________________________________________________________ bn4b2_branch2a (BatchNormalizat (None, None, None, 2 1024 res4b2_branch2a[0][0] __________________________________________________________________________________________________ res4b2_branch2a_relu (Activatio (None, None, None, 2 0 bn4b2_branch2a[0][0] __________________________________________________________________________________________________ padding4b2_branch2b (ZeroPaddin (None, None, None, 2 0 res4b2_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b2_branch2b (Conv2D) (None, None, None, 2 589824 padding4b2_branch2b[0][0] __________________________________________________________________________________________________ bn4b2_branch2b (BatchNormalizat (None, None, None, 2 1024 res4b2_branch2b[0][0] __________________________________________________________________________________________________ res4b2_branch2b_relu (Activatio (None, None, None, 2 0 bn4b2_branch2b[0][0] __________________________________________________________________________________________________ res4b2_branch2c (Conv2D) (None, None, None, 1 262144 res4b2_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b2_branch2c (BatchNormalizat (None, None, None, 1 4096 res4b2_branch2c[0][0] __________________________________________________________________________________________________ res4b2 (Add) (None, None, None, 1 0 bn4b2_branch2c[0][0] res4b1_relu[0][0] __________________________________________________________________________________________________ res4b2_relu (Activation) (None, None, None, 1 0 res4b2[0][0] __________________________________________________________________________________________________ res4b3_branch2a (Conv2D) (None, None, None, 2 262144 res4b2_relu[0][0] __________________________________________________________________________________________________ bn4b3_branch2a (BatchNormalizat (None, None, None, 2 1024 res4b3_branch2a[0][0] __________________________________________________________________________________________________ res4b3_branch2a_relu (Activatio (None, None, None, 2 0 bn4b3_branch2a[0][0] __________________________________________________________________________________________________ padding4b3_branch2b (ZeroPaddin (None, None, None, 2 0 res4b3_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b3_branch2b (Conv2D) (None, None, None, 2 589824 padding4b3_branch2b[0][0] __________________________________________________________________________________________________ bn4b3_branch2b (BatchNormalizat (None, None, None, 2 1024 res4b3_branch2b[0][0] __________________________________________________________________________________________________ res4b3_branch2b_relu (Activatio (None, None, None, 2 0 bn4b3_branch2b[0][0] __________________________________________________________________________________________________ res4b3_branch2c (Conv2D) (None, None, None, 1 262144 res4b3_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b3_branch2c (BatchNormalizat (None, None, None, 1 4096 res4b3_branch2c[0][0] __________________________________________________________________________________________________ res4b3 (Add) (None, None, None, 1 0 bn4b3_branch2c[0][0] res4b2_relu[0][0] __________________________________________________________________________________________________ res4b3_relu (Activation) (None, None, None, 1 0 res4b3[0][0] __________________________________________________________________________________________________ res4b4_branch2a (Conv2D) (None, None, None, 2 262144 res4b3_relu[0][0] __________________________________________________________________________________________________ bn4b4_branch2a (BatchNormalizat (None, None, None, 2 1024 res4b4_branch2a[0][0] __________________________________________________________________________________________________ res4b4_branch2a_relu (Activatio (None, None, None, 2 0 bn4b4_branch2a[0][0] __________________________________________________________________________________________________ padding4b4_branch2b (ZeroPaddin (None, None, None, 2 0 res4b4_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b4_branch2b (Conv2D) (None, None, None, 2 589824 padding4b4_branch2b[0][0] __________________________________________________________________________________________________ bn4b4_branch2b (BatchNormalizat (None, None, None, 2 1024 res4b4_branch2b[0][0] __________________________________________________________________________________________________ res4b4_branch2b_relu (Activatio (None, None, None, 2 0 bn4b4_branch2b[0][0] __________________________________________________________________________________________________ res4b4_branch2c (Conv2D) (None, None, None, 1 262144 res4b4_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b4_branch2c (BatchNormalizat (None, None, None, 1 4096 res4b4_branch2c[0][0] __________________________________________________________________________________________________ res4b4 (Add) (None, None, None, 1 0 bn4b4_branch2c[0][0] res4b3_relu[0][0] __________________________________________________________________________________________________ res4b4_relu (Activation) (None, None, None, 1 0 res4b4[0][0] __________________________________________________________________________________________________ res4b5_branch2a (Conv2D) (None, None, None, 2 262144 res4b4_relu[0][0] __________________________________________________________________________________________________ bn4b5_branch2a (BatchNormalizat (None, None, None, 2 1024 res4b5_branch2a[0][0] __________________________________________________________________________________________________ res4b5_branch2a_relu (Activatio (None, None, None, 2 0 bn4b5_branch2a[0][0] __________________________________________________________________________________________________ padding4b5_branch2b (ZeroPaddin (None, None, None, 2 0 res4b5_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b5_branch2b (Conv2D) (None, None, None, 2 589824 padding4b5_branch2b[0][0] __________________________________________________________________________________________________ bn4b5_branch2b (BatchNormalizat (None, None, None, 2 1024 res4b5_branch2b[0][0] __________________________________________________________________________________________________ res4b5_branch2b_relu (Activatio (None, None, None, 2 0 bn4b5_branch2b[0][0] __________________________________________________________________________________________________ res4b5_branch2c (Conv2D) (None, None, None, 1 262144 res4b5_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b5_branch2c (BatchNormalizat (None, None, None, 1 4096 res4b5_branch2c[0][0] __________________________________________________________________________________________________ res4b5 (Add) (None, None, None, 1 0 bn4b5_branch2c[0][0] res4b4_relu[0][0] __________________________________________________________________________________________________ res4b5_relu (Activation) (None, None, None, 1 0 res4b5[0][0] __________________________________________________________________________________________________ res4b6_branch2a (Conv2D) (None, None, None, 2 262144 res4b5_relu[0][0] __________________________________________________________________________________________________ bn4b6_branch2a (BatchNormalizat (None, None, None, 2 1024 res4b6_branch2a[0][0] __________________________________________________________________________________________________ res4b6_branch2a_relu (Activatio (None, None, None, 2 0 bn4b6_branch2a[0][0] __________________________________________________________________________________________________ padding4b6_branch2b (ZeroPaddin (None, None, None, 2 0 res4b6_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b6_branch2b (Conv2D) (None, None, None, 2 589824 padding4b6_branch2b[0][0] __________________________________________________________________________________________________ bn4b6_branch2b (BatchNormalizat (None, None, None, 2 1024 res4b6_branch2b[0][0] __________________________________________________________________________________________________ res4b6_branch2b_relu (Activatio (None, None, None, 2 0 bn4b6_branch2b[0][0] __________________________________________________________________________________________________ res4b6_branch2c (Conv2D) (None, None, None, 1 262144 res4b6_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b6_branch2c (BatchNormalizat (None, None, None, 1 4096 res4b6_branch2c[0][0] __________________________________________________________________________________________________ res4b6 (Add) (None, None, None, 1 0 bn4b6_branch2c[0][0] res4b5_relu[0][0] __________________________________________________________________________________________________ res4b6_relu (Activation) (None, None, None, 1 0 res4b6[0][0] __________________________________________________________________________________________________ res4b7_branch2a (Conv2D) (None, None, None, 2 262144 res4b6_relu[0][0] __________________________________________________________________________________________________ bn4b7_branch2a (BatchNormalizat (None, None, None, 2 1024 res4b7_branch2a[0][0] __________________________________________________________________________________________________ res4b7_branch2a_relu (Activatio (None, None, None, 2 0 bn4b7_branch2a[0][0] __________________________________________________________________________________________________ padding4b7_branch2b (ZeroPaddin (None, None, None, 2 0 res4b7_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b7_branch2b (Conv2D) (None, None, None, 2 589824 padding4b7_branch2b[0][0] __________________________________________________________________________________________________ bn4b7_branch2b (BatchNormalizat (None, None, None, 2 1024 res4b7_branch2b[0][0] __________________________________________________________________________________________________ res4b7_branch2b_relu (Activatio (None, None, None, 2 0 bn4b7_branch2b[0][0] __________________________________________________________________________________________________ res4b7_branch2c (Conv2D) (None, None, None, 1 262144 res4b7_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b7_branch2c (BatchNormalizat (None, None, None, 1 4096 res4b7_branch2c[0][0] __________________________________________________________________________________________________ res4b7 (Add) (None, None, None, 1 0 bn4b7_branch2c[0][0] res4b6_relu[0][0] __________________________________________________________________________________________________ res4b7_relu (Activation) (None, None, None, 1 0 res4b7[0][0] __________________________________________________________________________________________________ res4b8_branch2a (Conv2D) (None, None, None, 2 262144 res4b7_relu[0][0] __________________________________________________________________________________________________ bn4b8_branch2a (BatchNormalizat (None, None, None, 2 1024 res4b8_branch2a[0][0] __________________________________________________________________________________________________ res4b8_branch2a_relu (Activatio (None, None, None, 2 0 bn4b8_branch2a[0][0] __________________________________________________________________________________________________ padding4b8_branch2b (ZeroPaddin (None, None, None, 2 0 res4b8_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b8_branch2b (Conv2D) (None, None, None, 2 589824 padding4b8_branch2b[0][0] __________________________________________________________________________________________________ bn4b8_branch2b (BatchNormalizat (None, None, None, 2 1024 res4b8_branch2b[0][0] __________________________________________________________________________________________________ res4b8_branch2b_relu (Activatio (None, None, None, 2 0 bn4b8_branch2b[0][0] __________________________________________________________________________________________________ res4b8_branch2c (Conv2D) (None, None, None, 1 262144 res4b8_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b8_branch2c (BatchNormalizat (None, None, None, 1 4096 res4b8_branch2c[0][0] __________________________________________________________________________________________________ res4b8 (Add) (None, None, None, 1 0 bn4b8_branch2c[0][0] res4b7_relu[0][0] __________________________________________________________________________________________________ res4b8_relu (Activation) (None, None, None, 1 0 res4b8[0][0] __________________________________________________________________________________________________ res4b9_branch2a (Conv2D) (None, None, None, 2 262144 res4b8_relu[0][0] __________________________________________________________________________________________________ bn4b9_branch2a (BatchNormalizat (None, None, None, 2 1024 res4b9_branch2a[0][0] __________________________________________________________________________________________________ res4b9_branch2a_relu (Activatio (None, None, None, 2 0 bn4b9_branch2a[0][0] __________________________________________________________________________________________________ padding4b9_branch2b (ZeroPaddin (None, None, None, 2 0 res4b9_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b9_branch2b (Conv2D) (None, None, None, 2 589824 padding4b9_branch2b[0][0] __________________________________________________________________________________________________ bn4b9_branch2b (BatchNormalizat (None, None, None, 2 1024 res4b9_branch2b[0][0] __________________________________________________________________________________________________ res4b9_branch2b_relu (Activatio (None, None, None, 2 0 bn4b9_branch2b[0][0] __________________________________________________________________________________________________ res4b9_branch2c (Conv2D) (None, None, None, 1 262144 res4b9_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b9_branch2c (BatchNormalizat (None, None, None, 1 4096 res4b9_branch2c[0][0] __________________________________________________________________________________________________ res4b9 (Add) (None, None, None, 1 0 bn4b9_branch2c[0][0] res4b8_relu[0][0] __________________________________________________________________________________________________ res4b9_relu (Activation) (None, None, None, 1 0 res4b9[0][0] __________________________________________________________________________________________________ res4b10_branch2a (Conv2D) (None, None, None, 2 262144 res4b9_relu[0][0] __________________________________________________________________________________________________ bn4b10_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b10_branch2a[0][0] __________________________________________________________________________________________________ res4b10_branch2a_relu (Activati (None, None, None, 2 0 bn4b10_branch2a[0][0] __________________________________________________________________________________________________ padding4b10_branch2b (ZeroPaddi (None, None, None, 2 0 res4b10_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b10_branch2b (Conv2D) (None, None, None, 2 589824 padding4b10_branch2b[0][0] __________________________________________________________________________________________________ bn4b10_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b10_branch2b[0][0] __________________________________________________________________________________________________ res4b10_branch2b_relu (Activati (None, None, None, 2 0 bn4b10_branch2b[0][0] __________________________________________________________________________________________________ res4b10_branch2c (Conv2D) (None, None, None, 1 262144 res4b10_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b10_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b10_branch2c[0][0] __________________________________________________________________________________________________ res4b10 (Add) (None, None, None, 1 0 bn4b10_branch2c[0][0] res4b9_relu[0][0] __________________________________________________________________________________________________ res4b10_relu (Activation) (None, None, None, 1 0 res4b10[0][0] __________________________________________________________________________________________________ res4b11_branch2a (Conv2D) (None, None, None, 2 262144 res4b10_relu[0][0] __________________________________________________________________________________________________ bn4b11_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b11_branch2a[0][0] __________________________________________________________________________________________________ res4b11_branch2a_relu (Activati (None, None, None, 2 0 bn4b11_branch2a[0][0] __________________________________________________________________________________________________ padding4b11_branch2b (ZeroPaddi (None, None, None, 2 0 res4b11_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b11_branch2b (Conv2D) (None, None, None, 2 589824 padding4b11_branch2b[0][0] __________________________________________________________________________________________________ bn4b11_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b11_branch2b[0][0] __________________________________________________________________________________________________ res4b11_branch2b_relu (Activati (None, None, None, 2 0 bn4b11_branch2b[0][0] __________________________________________________________________________________________________ res4b11_branch2c (Conv2D) (None, None, None, 1 262144 res4b11_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b11_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b11_branch2c[0][0] __________________________________________________________________________________________________ res4b11 (Add) (None, None, None, 1 0 bn4b11_branch2c[0][0] res4b10_relu[0][0] __________________________________________________________________________________________________ res4b11_relu (Activation) (None, None, None, 1 0 res4b11[0][0] __________________________________________________________________________________________________ res4b12_branch2a (Conv2D) (None, None, None, 2 262144 res4b11_relu[0][0] __________________________________________________________________________________________________ bn4b12_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b12_branch2a[0][0] __________________________________________________________________________________________________ res4b12_branch2a_relu (Activati (None, None, None, 2 0 bn4b12_branch2a[0][0] __________________________________________________________________________________________________ padding4b12_branch2b (ZeroPaddi (None, None, None, 2 0 res4b12_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b12_branch2b (Conv2D) (None, None, None, 2 589824 padding4b12_branch2b[0][0] __________________________________________________________________________________________________ bn4b12_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b12_branch2b[0][0] __________________________________________________________________________________________________ res4b12_branch2b_relu (Activati (None, None, None, 2 0 bn4b12_branch2b[0][0] __________________________________________________________________________________________________ res4b12_branch2c (Conv2D) (None, None, None, 1 262144 res4b12_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b12_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b12_branch2c[0][0] __________________________________________________________________________________________________ res4b12 (Add) (None, None, None, 1 0 bn4b12_branch2c[0][0] res4b11_relu[0][0] __________________________________________________________________________________________________ res4b12_relu (Activation) (None, None, None, 1 0 res4b12[0][0] __________________________________________________________________________________________________ res4b13_branch2a (Conv2D) (None, None, None, 2 262144 res4b12_relu[0][0] __________________________________________________________________________________________________ bn4b13_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b13_branch2a[0][0] __________________________________________________________________________________________________ res4b13_branch2a_relu (Activati (None, None, None, 2 0 bn4b13_branch2a[0][0] __________________________________________________________________________________________________ padding4b13_branch2b (ZeroPaddi (None, None, None, 2 0 res4b13_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b13_branch2b (Conv2D) (None, None, None, 2 589824 padding4b13_branch2b[0][0] __________________________________________________________________________________________________ bn4b13_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b13_branch2b[0][0] __________________________________________________________________________________________________ res4b13_branch2b_relu (Activati (None, None, None, 2 0 bn4b13_branch2b[0][0] __________________________________________________________________________________________________ res4b13_branch2c (Conv2D) (None, None, None, 1 262144 res4b13_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b13_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b13_branch2c[0][0] __________________________________________________________________________________________________ res4b13 (Add) (None, None, None, 1 0 bn4b13_branch2c[0][0] res4b12_relu[0][0] __________________________________________________________________________________________________ res4b13_relu (Activation) (None, None, None, 1 0 res4b13[0][0] __________________________________________________________________________________________________ res4b14_branch2a (Conv2D) (None, None, None, 2 262144 res4b13_relu[0][0] __________________________________________________________________________________________________ bn4b14_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b14_branch2a[0][0] __________________________________________________________________________________________________ res4b14_branch2a_relu (Activati (None, None, None, 2 0 bn4b14_branch2a[0][0] __________________________________________________________________________________________________ padding4b14_branch2b (ZeroPaddi (None, None, None, 2 0 res4b14_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b14_branch2b (Conv2D) (None, None, None, 2 589824 padding4b14_branch2b[0][0] __________________________________________________________________________________________________ bn4b14_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b14_branch2b[0][0] __________________________________________________________________________________________________ res4b14_branch2b_relu (Activati (None, None, None, 2 0 bn4b14_branch2b[0][0] __________________________________________________________________________________________________ res4b14_branch2c (Conv2D) (None, None, None, 1 262144 res4b14_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b14_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b14_branch2c[0][0] __________________________________________________________________________________________________ res4b14 (Add) (None, None, None, 1 0 bn4b14_branch2c[0][0] res4b13_relu[0][0] __________________________________________________________________________________________________ res4b14_relu (Activation) (None, None, None, 1 0 res4b14[0][0] __________________________________________________________________________________________________ res4b15_branch2a (Conv2D) (None, None, None, 2 262144 res4b14_relu[0][0] __________________________________________________________________________________________________ bn4b15_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b15_branch2a[0][0] __________________________________________________________________________________________________ res4b15_branch2a_relu (Activati (None, None, None, 2 0 bn4b15_branch2a[0][0] __________________________________________________________________________________________________ padding4b15_branch2b (ZeroPaddi (None, None, None, 2 0 res4b15_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b15_branch2b (Conv2D) (None, None, None, 2 589824 padding4b15_branch2b[0][0] __________________________________________________________________________________________________ bn4b15_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b15_branch2b[0][0] __________________________________________________________________________________________________ res4b15_branch2b_relu (Activati (None, None, None, 2 0 bn4b15_branch2b[0][0] __________________________________________________________________________________________________ res4b15_branch2c (Conv2D) (None, None, None, 1 262144 res4b15_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b15_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b15_branch2c[0][0] __________________________________________________________________________________________________ res4b15 (Add) (None, None, None, 1 0 bn4b15_branch2c[0][0] res4b14_relu[0][0] __________________________________________________________________________________________________ res4b15_relu (Activation) (None, None, None, 1 0 res4b15[0][0] __________________________________________________________________________________________________ res4b16_branch2a (Conv2D) (None, None, None, 2 262144 res4b15_relu[0][0] __________________________________________________________________________________________________ bn4b16_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b16_branch2a[0][0] __________________________________________________________________________________________________ res4b16_branch2a_relu (Activati (None, None, None, 2 0 bn4b16_branch2a[0][0] __________________________________________________________________________________________________ padding4b16_branch2b (ZeroPaddi (None, None, None, 2 0 res4b16_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b16_branch2b (Conv2D) (None, None, None, 2 589824 padding4b16_branch2b[0][0] __________________________________________________________________________________________________ bn4b16_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b16_branch2b[0][0] __________________________________________________________________________________________________ res4b16_branch2b_relu (Activati (None, None, None, 2 0 bn4b16_branch2b[0][0] __________________________________________________________________________________________________ res4b16_branch2c (Conv2D) (None, None, None, 1 262144 res4b16_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b16_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b16_branch2c[0][0] __________________________________________________________________________________________________ res4b16 (Add) (None, None, None, 1 0 bn4b16_branch2c[0][0] res4b15_relu[0][0] __________________________________________________________________________________________________ res4b16_relu (Activation) (None, None, None, 1 0 res4b16[0][0] __________________________________________________________________________________________________ res4b17_branch2a (Conv2D) (None, None, None, 2 262144 res4b16_relu[0][0] __________________________________________________________________________________________________ bn4b17_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b17_branch2a[0][0] __________________________________________________________________________________________________ res4b17_branch2a_relu (Activati (None, None, None, 2 0 bn4b17_branch2a[0][0] __________________________________________________________________________________________________ padding4b17_branch2b (ZeroPaddi (None, None, None, 2 0 res4b17_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b17_branch2b (Conv2D) (None, None, None, 2 589824 padding4b17_branch2b[0][0] __________________________________________________________________________________________________ bn4b17_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b17_branch2b[0][0] __________________________________________________________________________________________________ res4b17_branch2b_relu (Activati (None, None, None, 2 0 bn4b17_branch2b[0][0] __________________________________________________________________________________________________ res4b17_branch2c (Conv2D) (None, None, None, 1 262144 res4b17_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b17_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b17_branch2c[0][0] __________________________________________________________________________________________________ res4b17 (Add) (None, None, None, 1 0 bn4b17_branch2c[0][0] res4b16_relu[0][0] __________________________________________________________________________________________________ res4b17_relu (Activation) (None, None, None, 1 0 res4b17[0][0] __________________________________________________________________________________________________ res4b18_branch2a (Conv2D) (None, None, None, 2 262144 res4b17_relu[0][0] __________________________________________________________________________________________________ bn4b18_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b18_branch2a[0][0] __________________________________________________________________________________________________ res4b18_branch2a_relu (Activati (None, None, None, 2 0 bn4b18_branch2a[0][0] __________________________________________________________________________________________________ padding4b18_branch2b (ZeroPaddi (None, None, None, 2 0 res4b18_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b18_branch2b (Conv2D) (None, None, None, 2 589824 padding4b18_branch2b[0][0] __________________________________________________________________________________________________ bn4b18_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b18_branch2b[0][0] __________________________________________________________________________________________________ res4b18_branch2b_relu (Activati (None, None, None, 2 0 bn4b18_branch2b[0][0] __________________________________________________________________________________________________ res4b18_branch2c (Conv2D) (None, None, None, 1 262144 res4b18_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b18_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b18_branch2c[0][0] __________________________________________________________________________________________________ res4b18 (Add) (None, None, None, 1 0 bn4b18_branch2c[0][0] res4b17_relu[0][0] __________________________________________________________________________________________________ res4b18_relu (Activation) (None, None, None, 1 0 res4b18[0][0] __________________________________________________________________________________________________ res4b19_branch2a (Conv2D) (None, None, None, 2 262144 res4b18_relu[0][0] __________________________________________________________________________________________________ bn4b19_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b19_branch2a[0][0] __________________________________________________________________________________________________ res4b19_branch2a_relu (Activati (None, None, None, 2 0 bn4b19_branch2a[0][0] __________________________________________________________________________________________________ padding4b19_branch2b (ZeroPaddi (None, None, None, 2 0 res4b19_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b19_branch2b (Conv2D) (None, None, None, 2 589824 padding4b19_branch2b[0][0] __________________________________________________________________________________________________ bn4b19_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b19_branch2b[0][0] __________________________________________________________________________________________________ res4b19_branch2b_relu (Activati (None, None, None, 2 0 bn4b19_branch2b[0][0] __________________________________________________________________________________________________ res4b19_branch2c (Conv2D) (None, None, None, 1 262144 res4b19_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b19_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b19_branch2c[0][0] __________________________________________________________________________________________________ res4b19 (Add) (None, None, None, 1 0 bn4b19_branch2c[0][0] res4b18_relu[0][0] __________________________________________________________________________________________________ res4b19_relu (Activation) (None, None, None, 1 0 res4b19[0][0] __________________________________________________________________________________________________ res4b20_branch2a (Conv2D) (None, None, None, 2 262144 res4b19_relu[0][0] __________________________________________________________________________________________________ bn4b20_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b20_branch2a[0][0] __________________________________________________________________________________________________ res4b20_branch2a_relu (Activati (None, None, None, 2 0 bn4b20_branch2a[0][0] __________________________________________________________________________________________________ padding4b20_branch2b (ZeroPaddi (None, None, None, 2 0 res4b20_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b20_branch2b (Conv2D) (None, None, None, 2 589824 padding4b20_branch2b[0][0] __________________________________________________________________________________________________ bn4b20_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b20_branch2b[0][0] __________________________________________________________________________________________________ res4b20_branch2b_relu (Activati (None, None, None, 2 0 bn4b20_branch2b[0][0] __________________________________________________________________________________________________ res4b20_branch2c (Conv2D) (None, None, None, 1 262144 res4b20_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b20_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b20_branch2c[0][0] __________________________________________________________________________________________________ res4b20 (Add) (None, None, None, 1 0 bn4b20_branch2c[0][0] res4b19_relu[0][0] __________________________________________________________________________________________________ res4b20_relu (Activation) (None, None, None, 1 0 res4b20[0][0] __________________________________________________________________________________________________ res4b21_branch2a (Conv2D) (None, None, None, 2 262144 res4b20_relu[0][0] __________________________________________________________________________________________________ bn4b21_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b21_branch2a[0][0] __________________________________________________________________________________________________ res4b21_branch2a_relu (Activati (None, None, None, 2 0 bn4b21_branch2a[0][0] __________________________________________________________________________________________________ padding4b21_branch2b (ZeroPaddi (None, None, None, 2 0 res4b21_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b21_branch2b (Conv2D) (None, None, None, 2 589824 padding4b21_branch2b[0][0] __________________________________________________________________________________________________ bn4b21_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b21_branch2b[0][0] __________________________________________________________________________________________________ res4b21_branch2b_relu (Activati (None, None, None, 2 0 bn4b21_branch2b[0][0] __________________________________________________________________________________________________ res4b21_branch2c (Conv2D) (None, None, None, 1 262144 res4b21_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b21_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b21_branch2c[0][0] __________________________________________________________________________________________________ res4b21 (Add) (None, None, None, 1 0 bn4b21_branch2c[0][0] res4b20_relu[0][0] __________________________________________________________________________________________________ res4b21_relu (Activation) (None, None, None, 1 0 res4b21[0][0] __________________________________________________________________________________________________ res4b22_branch2a (Conv2D) (None, None, None, 2 262144 res4b21_relu[0][0] __________________________________________________________________________________________________ bn4b22_branch2a (BatchNormaliza (None, None, None, 2 1024 res4b22_branch2a[0][0] __________________________________________________________________________________________________ res4b22_branch2a_relu (Activati (None, None, None, 2 0 bn4b22_branch2a[0][0] __________________________________________________________________________________________________ padding4b22_branch2b (ZeroPaddi (None, None, None, 2 0 res4b22_branch2a_relu[0][0] __________________________________________________________________________________________________ res4b22_branch2b (Conv2D) (None, None, None, 2 589824 padding4b22_branch2b[0][0] __________________________________________________________________________________________________ bn4b22_branch2b (BatchNormaliza (None, None, None, 2 1024 res4b22_branch2b[0][0] __________________________________________________________________________________________________ res4b22_branch2b_relu (Activati (None, None, None, 2 0 bn4b22_branch2b[0][0] __________________________________________________________________________________________________ res4b22_branch2c (Conv2D) (None, None, None, 1 262144 res4b22_branch2b_relu[0][0] __________________________________________________________________________________________________ bn4b22_branch2c (BatchNormaliza (None, None, None, 1 4096 res4b22_branch2c[0][0] __________________________________________________________________________________________________ res4b22 (Add) (None, None, None, 1 0 bn4b22_branch2c[0][0] res4b21_relu[0][0] __________________________________________________________________________________________________ res4b22_relu (Activation) (None, None, None, 1 0 res4b22[0][0] __________________________________________________________________________________________________ res5a_branch2a (Conv2D) (None, None, None, 5 524288 res4b22_relu[0][0] __________________________________________________________________________________________________ bn5a_branch2a (BatchNormalizati (None, None, None, 5 2048 res5a_branch2a[0][0] __________________________________________________________________________________________________ res5a_branch2a_relu (Activation (None, None, None, 5 0 bn5a_branch2a[0][0] __________________________________________________________________________________________________ padding5a_branch2b (ZeroPadding (None, None, None, 5 0 res5a_branch2a_relu[0][0] __________________________________________________________________________________________________ res5a_branch2b (Conv2D) (None, None, None, 5 2359296 padding5a_branch2b[0][0] __________________________________________________________________________________________________ bn5a_branch2b (BatchNormalizati (None, None, None, 5 2048 res5a_branch2b[0][0] __________________________________________________________________________________________________ res5a_branch2b_relu (Activation (None, None, None, 5 0 bn5a_branch2b[0][0] __________________________________________________________________________________________________ res5a_branch2c (Conv2D) (None, None, None, 2 1048576 res5a_branch2b_relu[0][0] __________________________________________________________________________________________________ res5a_branch1 (Conv2D) (None, None, None, 2 2097152 res4b22_relu[0][0] __________________________________________________________________________________________________ bn5a_branch2c (BatchNormalizati (None, None, None, 2 8192 res5a_branch2c[0][0] __________________________________________________________________________________________________ bn5a_branch1 (BatchNormalizatio (None, None, None, 2 8192 res5a_branch1[0][0] __________________________________________________________________________________________________ res5a (Add) (None, None, None, 2 0 bn5a_branch2c[0][0] bn5a_branch1[0][0] __________________________________________________________________________________________________ res5a_relu (Activation) (None, None, None, 2 0 res5a[0][0] __________________________________________________________________________________________________ res5b_branch2a (Conv2D) (None, None, None, 5 1048576 res5a_relu[0][0] __________________________________________________________________________________________________ bn5b_branch2a (BatchNormalizati (None, None, None, 5 2048 res5b_branch2a[0][0] __________________________________________________________________________________________________ res5b_branch2a_relu (Activation (None, None, None, 5 0 bn5b_branch2a[0][0] __________________________________________________________________________________________________ padding5b_branch2b (ZeroPadding (None, None, None, 5 0 res5b_branch2a_relu[0][0] __________________________________________________________________________________________________ res5b_branch2b (Conv2D) (None, None, None, 5 2359296 padding5b_branch2b[0][0] __________________________________________________________________________________________________ bn5b_branch2b (BatchNormalizati (None, None, None, 5 2048 res5b_branch2b[0][0] __________________________________________________________________________________________________ res5b_branch2b_relu (Activation (None, None, None, 5 0 bn5b_branch2b[0][0] __________________________________________________________________________________________________ res5b_branch2c (Conv2D) (None, None, None, 2 1048576 res5b_branch2b_relu[0][0] __________________________________________________________________________________________________ bn5b_branch2c (BatchNormalizati (None, None, None, 2 8192 res5b_branch2c[0][0] __________________________________________________________________________________________________ res5b (Add) (None, None, None, 2 0 bn5b_branch2c[0][0] res5a_relu[0][0] __________________________________________________________________________________________________ res5b_relu (Activation) (None, None, None, 2 0 res5b[0][0] __________________________________________________________________________________________________ res5c_branch2a (Conv2D) (None, None, None, 5 1048576 res5b_relu[0][0] __________________________________________________________________________________________________ bn5c_branch2a (BatchNormalizati (None, None, None, 5 2048 res5c_branch2a[0][0] __________________________________________________________________________________________________ res5c_branch2a_relu (Activation (None, None, None, 5 0 bn5c_branch2a[0][0] __________________________________________________________________________________________________ padding5c_branch2b (ZeroPadding (None, None, None, 5 0 res5c_branch2a_relu[0][0] __________________________________________________________________________________________________ res5c_branch2b (Conv2D) (None, None, None, 5 2359296 padding5c_branch2b[0][0] __________________________________________________________________________________________________ bn5c_branch2b (BatchNormalizati (None, None, None, 5 2048 res5c_branch2b[0][0] __________________________________________________________________________________________________ res5c_branch2b_relu (Activation (None, None, None, 5 0 bn5c_branch2b[0][0] __________________________________________________________________________________________________ res5c_branch2c (Conv2D) (None, None, None, 2 1048576 res5c_branch2b_relu[0][0] __________________________________________________________________________________________________ bn5c_branch2c (BatchNormalizati (None, None, None, 2 8192 res5c_branch2c[0][0] __________________________________________________________________________________________________ res5c (Add) (None, None, None, 2 0 bn5c_branch2c[0][0] res5b_relu[0][0] __________________________________________________________________________________________________ res5c_relu (Activation) (None, None, None, 2 0 res5c[0][0] __________________________________________________________________________________________________ C5_reduced (Conv2D) (None, None, None, 2 524544 res5c_relu[0][0] __________________________________________________________________________________________________ P5_upsampled (UpsampleLike) (None, None, None, 2 0 C5_reduced[0][0] res4b22_relu[0][0] __________________________________________________________________________________________________ C4_reduced (Conv2D) (None, None, None, 2 262400 res4b22_relu[0][0] __________________________________________________________________________________________________ P4_merged (Add) (None, None, None, 2 0 P5_upsampled[0][0] C4_reduced[0][0] __________________________________________________________________________________________________ P4_upsampled (UpsampleLike) (None, None, None, 2 0 P4_merged[0][0] res3b3_relu[0][0] __________________________________________________________________________________________________ C3_reduced (Conv2D) (None, None, None, 2 131328 res3b3_relu[0][0] __________________________________________________________________________________________________ P6 (Conv2D) (None, None, None, 2 4718848 res5c_relu[0][0] __________________________________________________________________________________________________ P3_merged (Add) (None, None, None, 2 0 P4_upsampled[0][0] C3_reduced[0][0] __________________________________________________________________________________________________ C6_relu (Activation) (None, None, None, 2 0 P6[0][0] __________________________________________________________________________________________________ P3 (Conv2D) (None, None, None, 2 590080 P3_merged[0][0] __________________________________________________________________________________________________ P4 (Conv2D) (None, None, None, 2 590080 P4_merged[0][0] __________________________________________________________________________________________________ P5 (Conv2D) (None, None, None, 2 590080 C5_reduced[0][0] __________________________________________________________________________________________________ P7 (Conv2D) (None, None, None, 2 590080 C6_relu[0][0] __________________________________________________________________________________________________ regression_submodel (Model) (None, None, 4) 2443300 P3[0][0] P4[0][0] P5[0][0] P6[0][0] P7[0][0] __________________________________________________________________________________________________ classification_submodel (Model) (None, None, 1) 2381065 P3[0][0] P4[0][0] P5[0][0] P6[0][0] P7[0][0] __________________________________________________________________________________________________ regression (Concatenate) (None, None, 4) 0 regression_submodel[1][0] regression_submodel[2][0] regression_submodel[3][0] regression_submodel[4][0] regression_submodel[5][0] __________________________________________________________________________________________________ classification (Concatenate) (None, None, 1) 0 classification_submodel[1][0] classification_submodel[2][0] classification_submodel[3][0] classification_submodel[4][0] classification_submodel[5][0] ================================================================================================== Total params: 55,430,445 Trainable params: 55,219,757 Non-trainable params: 210,688 __________________________________________________________________________________________________ None Epoch 1/150 1/500 [..............................] - ETA: 1:01:57 - loss: 4.1690 - regression_loss: 3.0429 - classification_loss: 1.1262 2/500 [..............................] - ETA: 32:10 - loss: 4.0998 - regression_loss: 2.9719 - classification_loss: 1.1279 3/500 [..............................] - ETA: 22:14 - loss: 4.0404 - regression_loss: 2.9113 - classification_loss: 1.1291 4/500 [..............................] - ETA: 17:17 - loss: 4.0209 - regression_loss: 2.8921 - classification_loss: 1.1288 5/500 [..............................] - ETA: 14:18 - loss: 3.9424 - regression_loss: 2.8135 - classification_loss: 1.1289 6/500 [..............................] - ETA: 12:19 - loss: 3.9619 - regression_loss: 2.8334 - classification_loss: 1.1286 7/500 [..............................] - ETA: 10:55 - loss: 3.9545 - regression_loss: 2.8258 - classification_loss: 1.1288 8/500 [..............................] - ETA: 9:50 - loss: 3.9744 - regression_loss: 2.8458 - classification_loss: 1.1286 9/500 [..............................] - ETA: 9:02 - loss: 4.0006 - regression_loss: 2.8716 - classification_loss: 1.1290 10/500 [..............................] - ETA: 8:22 - loss: 4.0126 - regression_loss: 2.8837 - classification_loss: 1.1289 11/500 [..............................] - ETA: 7:50 - loss: 4.0245 - regression_loss: 2.8957 - classification_loss: 1.1288 12/500 [..............................] - ETA: 7:23 - loss: 4.0294 - regression_loss: 2.9008 - classification_loss: 1.1286 13/500 [..............................] - ETA: 7:00 - loss: 4.0315 - regression_loss: 2.9028 - classification_loss: 1.1287 14/500 [..............................] - ETA: 6:40 - loss: 4.0321 - regression_loss: 2.9035 - classification_loss: 1.1286 15/500 [..............................] - ETA: 6:23 - loss: 4.0390 - regression_loss: 2.9101 - classification_loss: 1.1288 16/500 [..............................] - ETA: 6:08 - loss: 4.0430 - regression_loss: 2.9142 - classification_loss: 1.1288 17/500 [>.............................] - ETA: 5:55 - loss: 4.0511 - regression_loss: 2.9224 - classification_loss: 1.1286 18/500 [>.............................] - ETA: 5:43 - loss: 4.0538 - regression_loss: 2.9252 - classification_loss: 1.1286 19/500 [>.............................] - ETA: 5:33 - loss: 4.0520 - regression_loss: 2.9235 - classification_loss: 1.1285 20/500 [>.............................] - ETA: 5:24 - loss: 4.0570 - regression_loss: 2.9286 - classification_loss: 1.1284 21/500 [>.............................] - ETA: 5:15 - loss: 4.0580 - regression_loss: 2.9298 - classification_loss: 1.1282 22/500 [>.............................] - ETA: 5:07 - loss: 4.0446 - regression_loss: 2.9162 - classification_loss: 1.1283 23/500 [>.............................] - ETA: 5:00 - loss: 4.0515 - regression_loss: 2.9233 - classification_loss: 1.1282 24/500 [>.............................] - ETA: 4:53 - loss: 4.0663 - regression_loss: 2.9381 - classification_loss: 1.1282 25/500 [>.............................] - ETA: 4:47 - loss: 4.0672 - regression_loss: 2.9391 - classification_loss: 1.1281 26/500 [>.............................] - ETA: 4:42 - loss: 4.0580 - regression_loss: 2.9300 - classification_loss: 1.1280 27/500 [>.............................] - ETA: 4:36 - loss: 4.0545 - regression_loss: 2.9264 - classification_loss: 1.1281 28/500 [>.............................] - ETA: 4:31 - loss: 4.0546 - regression_loss: 2.9267 - classification_loss: 1.1280 29/500 [>.............................] - ETA: 4:26 - loss: 4.0567 - regression_loss: 2.9288 - classification_loss: 1.1279 30/500 [>.............................] - ETA: 4:21 - loss: 4.0565 - regression_loss: 2.9288 - classification_loss: 1.1278 31/500 [>.............................] - ETA: 4:17 - loss: 4.0482 - regression_loss: 2.9202 - classification_loss: 1.1280 32/500 [>.............................] - ETA: 4:13 - loss: 4.0548 - regression_loss: 2.9269 - classification_loss: 1.1278 33/500 [>.............................] - ETA: 4:09 - loss: 4.0588 - regression_loss: 2.9310 - classification_loss: 1.1277 34/500 [=>............................] - ETA: 4:06 - loss: 4.0536 - regression_loss: 2.9260 - classification_loss: 1.1276 35/500 [=>............................] - ETA: 4:02 - loss: 4.0493 - regression_loss: 2.9217 - classification_loss: 1.1276 36/500 [=>............................] - ETA: 3:59 - loss: 4.0519 - regression_loss: 2.9244 - classification_loss: 1.1275 37/500 [=>............................] - ETA: 3:56 - loss: 4.0466 - regression_loss: 2.9191 - classification_loss: 1.1275 38/500 [=>............................] - ETA: 3:53 - loss: 4.0470 - regression_loss: 2.9197 - classification_loss: 1.1274 39/500 [=>............................] - ETA: 3:50 - loss: 4.0487 - regression_loss: 2.9213 - classification_loss: 1.1273 40/500 [=>............................] - ETA: 3:47 - loss: 4.0507 - regression_loss: 2.9234 - classification_loss: 1.1272 41/500 [=>............................] - ETA: 3:44 - loss: 4.0569 - regression_loss: 2.9296 - classification_loss: 1.1273 42/500 [=>............................] - ETA: 3:42 - loss: 4.0554 - regression_loss: 2.9282 - classification_loss: 1.1272 43/500 [=>............................] - ETA: 3:40 - loss: 4.0525 - regression_loss: 2.9252 - classification_loss: 1.1273 44/500 [=>............................] - ETA: 3:38 - loss: 4.0466 - regression_loss: 2.9193 - classification_loss: 1.1273 45/500 [=>............................] - ETA: 3:36 - loss: 4.0445 - regression_loss: 2.9173 - classification_loss: 1.1273 46/500 [=>............................] - ETA: 3:34 - loss: 4.0482 - regression_loss: 2.9210 - classification_loss: 1.1272 47/500 [=>............................] - ETA: 3:32 - loss: 4.0509 - regression_loss: 2.9237 - classification_loss: 1.1272 48/500 [=>............................] - ETA: 3:30 - loss: 4.0502 - regression_loss: 2.9231 - classification_loss: 1.1271 49/500 [=>............................] - ETA: 3:29 - loss: 4.0518 - regression_loss: 2.9248 - classification_loss: 1.1270 50/500 [==>...........................] - ETA: 3:27 - loss: 4.0506 - regression_loss: 2.9237 - classification_loss: 1.1269 51/500 [==>...........................] - ETA: 3:25 - loss: 4.0531 - regression_loss: 2.9263 - classification_loss: 1.1267 52/500 [==>...........................] - ETA: 3:24 - loss: 4.0494 - regression_loss: 2.9227 - classification_loss: 1.1267 53/500 [==>...........................] - ETA: 3:22 - loss: 4.0493 - regression_loss: 2.9225 - classification_loss: 1.1267 54/500 [==>...........................] - ETA: 3:21 - loss: 4.0445 - regression_loss: 2.9179 - classification_loss: 1.1266 55/500 [==>...........................] - ETA: 3:19 - loss: 4.0453 - regression_loss: 2.9188 - classification_loss: 1.1265 56/500 [==>...........................] - ETA: 3:18 - loss: 4.0462 - regression_loss: 2.9199 - classification_loss: 1.1263 57/500 [==>...........................] - ETA: 3:16 - loss: 4.0448 - regression_loss: 2.9187 - classification_loss: 1.1261 58/500 [==>...........................] - ETA: 3:15 - loss: 4.0456 - regression_loss: 2.9196 - classification_loss: 1.1259 59/500 [==>...........................] - ETA: 3:14 - loss: 4.0445 - regression_loss: 2.9187 - classification_loss: 1.1258 60/500 [==>...........................] - ETA: 3:13 - loss: 4.0454 - regression_loss: 2.9197 - classification_loss: 1.1257 61/500 [==>...........................] - ETA: 3:12 - loss: 4.0473 - regression_loss: 2.9218 - classification_loss: 1.1255 62/500 [==>...........................] - ETA: 3:11 - loss: 4.0438 - regression_loss: 2.9184 - classification_loss: 1.1254 63/500 [==>...........................] - ETA: 3:10 - loss: 4.0424 - regression_loss: 2.9171 - classification_loss: 1.1253 64/500 [==>...........................] - ETA: 3:09 - loss: 4.0383 - regression_loss: 2.9130 - classification_loss: 1.1252 65/500 [==>...........................] - ETA: 3:08 - loss: 4.0368 - regression_loss: 2.9117 - classification_loss: 1.1251 66/500 [==>...........................] - ETA: 3:07 - loss: 4.0369 - regression_loss: 2.9118 - classification_loss: 1.1251 67/500 [===>..........................] - ETA: 3:05 - loss: 4.0361 - regression_loss: 2.9111 - classification_loss: 1.1250 68/500 [===>..........................] - ETA: 3:04 - loss: 4.0364 - regression_loss: 2.9115 - classification_loss: 1.1249 69/500 [===>..........................] - ETA: 3:03 - loss: 4.0343 - regression_loss: 2.9094 - classification_loss: 1.1249 70/500 [===>..........................] - ETA: 3:02 - loss: 4.0341 - regression_loss: 2.9093 - classification_loss: 1.1248 71/500 [===>..........................] - ETA: 3:01 - loss: 4.0332 - regression_loss: 2.9085 - classification_loss: 1.1246 72/500 [===>..........................] - ETA: 3:00 - loss: 4.0293 - regression_loss: 2.9048 - classification_loss: 1.1245 73/500 [===>..........................] - ETA: 2:59 - loss: 4.0278 - regression_loss: 2.9035 - classification_loss: 1.1244 74/500 [===>..........................] - ETA: 2:58 - loss: 4.0265 - regression_loss: 2.9023 - classification_loss: 1.1242 75/500 [===>..........................] - ETA: 2:57 - loss: 4.0241 - regression_loss: 2.9001 - classification_loss: 1.1240 76/500 [===>..........................] - ETA: 2:56 - loss: 4.0223 - regression_loss: 2.8983 - classification_loss: 1.1240 77/500 [===>..........................] - ETA: 2:55 - loss: 4.0256 - regression_loss: 2.9016 - classification_loss: 1.1240 78/500 [===>..........................] - ETA: 2:54 - loss: 4.0238 - regression_loss: 2.9000 - classification_loss: 1.1238 79/500 [===>..........................] - ETA: 2:54 - loss: 4.0224 - regression_loss: 2.8987 - classification_loss: 1.1237 80/500 [===>..........................] - ETA: 2:53 - loss: 4.0201 - regression_loss: 2.8966 - classification_loss: 1.1235 81/500 [===>..........................] - ETA: 2:52 - loss: 4.0190 - regression_loss: 2.8956 - classification_loss: 1.1234 82/500 [===>..........................] - ETA: 2:51 - loss: 4.0187 - regression_loss: 2.8954 - classification_loss: 1.1233 83/500 [===>..........................] - ETA: 2:50 - loss: 4.0168 - regression_loss: 2.8938 - classification_loss: 1.1231 84/500 [====>.........................] - ETA: 2:49 - loss: 4.0159 - regression_loss: 2.8931 - classification_loss: 1.1228 85/500 [====>.........................] - ETA: 2:48 - loss: 4.0145 - regression_loss: 2.8917 - classification_loss: 1.1228 86/500 [====>.........................] - ETA: 2:48 - loss: 4.0138 - regression_loss: 2.8912 - classification_loss: 1.1226 87/500 [====>.........................] - ETA: 2:47 - loss: 4.0132 - regression_loss: 2.8910 - classification_loss: 1.1223 88/500 [====>.........................] - ETA: 2:46 - loss: 4.0132 - regression_loss: 2.8912 - classification_loss: 1.1220 89/500 [====>.........................] - ETA: 2:45 - loss: 4.0118 - regression_loss: 2.8900 - classification_loss: 1.1219 90/500 [====>.........................] - ETA: 2:44 - loss: 4.0120 - regression_loss: 2.8902 - classification_loss: 1.1219 91/500 [====>.........................] - ETA: 2:44 - loss: 4.0085 - regression_loss: 2.8870 - classification_loss: 1.1216 92/500 [====>.........................] - ETA: 2:43 - loss: 4.0080 - regression_loss: 2.8867 - classification_loss: 1.1214 93/500 [====>.........................] - ETA: 2:42 - loss: 4.0060 - regression_loss: 2.8849 - classification_loss: 1.1211 94/500 [====>.........................] - ETA: 2:41 - loss: 4.0046 - regression_loss: 2.8838 - classification_loss: 1.1208 95/500 [====>.........................] - ETA: 2:41 - loss: 4.0015 - regression_loss: 2.8808 - classification_loss: 1.1207 96/500 [====>.........................] - ETA: 2:40 - loss: 4.0004 - regression_loss: 2.8800 - classification_loss: 1.1205 97/500 [====>.........................] - ETA: 2:39 - loss: 3.9991 - regression_loss: 2.8789 - classification_loss: 1.1202 98/500 [====>.........................] - ETA: 2:39 - loss: 3.9991 - regression_loss: 2.8790 - classification_loss: 1.1200 99/500 [====>.........................] - ETA: 2:38 - loss: 3.9956 - regression_loss: 2.8760 - classification_loss: 1.1196 100/500 [=====>........................] - ETA: 2:37 - loss: 3.9941 - regression_loss: 2.8747 - classification_loss: 1.1193 101/500 [=====>........................] - ETA: 2:36 - loss: 3.9943 - regression_loss: 2.8749 - classification_loss: 1.1194 102/500 [=====>........................] - ETA: 2:36 - loss: 3.9918 - regression_loss: 2.8728 - classification_loss: 1.1191 103/500 [=====>........................] - ETA: 2:35 - loss: 3.9895 - regression_loss: 2.8706 - classification_loss: 1.1189 104/500 [=====>........................] - ETA: 2:34 - loss: 3.9866 - regression_loss: 2.8677 - classification_loss: 1.1189 105/500 [=====>........................] - ETA: 2:34 - loss: 3.9871 - regression_loss: 2.8682 - classification_loss: 1.1189 106/500 [=====>........................] - ETA: 2:33 - loss: 3.9842 - regression_loss: 2.8656 - classification_loss: 1.1186 107/500 [=====>........................] - ETA: 2:32 - loss: 3.9831 - regression_loss: 2.8646 - classification_loss: 1.1185 108/500 [=====>........................] - ETA: 2:32 - loss: 3.9805 - regression_loss: 2.8623 - classification_loss: 1.1181 109/500 [=====>........................] - ETA: 2:31 - loss: 3.9784 - regression_loss: 2.8607 - classification_loss: 1.1178 110/500 [=====>........................] - ETA: 2:31 - loss: 3.9761 - regression_loss: 2.8583 - classification_loss: 1.1177 111/500 [=====>........................] - ETA: 2:30 - loss: 3.9731 - regression_loss: 2.8559 - classification_loss: 1.1173 112/500 [=====>........................] - ETA: 2:29 - loss: 3.9699 - regression_loss: 2.8531 - classification_loss: 1.1168 113/500 [=====>........................] - ETA: 2:29 - loss: 3.9697 - regression_loss: 2.8530 - classification_loss: 1.1167 114/500 [=====>........................] - ETA: 2:28 - loss: 3.9670 - regression_loss: 2.8504 - classification_loss: 1.1166 115/500 [=====>........................] - ETA: 2:27 - loss: 3.9650 - regression_loss: 2.8489 - classification_loss: 1.1161 116/500 [=====>........................] - ETA: 2:27 - loss: 3.9637 - regression_loss: 2.8478 - classification_loss: 1.1159 117/500 [======>.......................] - ETA: 2:26 - loss: 3.9615 - regression_loss: 2.8461 - classification_loss: 1.1154 118/500 [======>.......................] - ETA: 2:26 - loss: 3.9583 - regression_loss: 2.8433 - classification_loss: 1.1150 119/500 [======>.......................] - ETA: 2:25 - loss: 3.9546 - regression_loss: 2.8403 - classification_loss: 1.1143 120/500 [======>.......................] - ETA: 2:24 - loss: 3.9526 - regression_loss: 2.8389 - classification_loss: 1.1138 121/500 [======>.......................] - ETA: 2:24 - loss: 3.9494 - regression_loss: 2.8362 - classification_loss: 1.1132 122/500 [======>.......................] - ETA: 2:23 - loss: 3.9475 - regression_loss: 2.8351 - classification_loss: 1.1124 123/500 [======>.......................] - ETA: 2:23 - loss: 3.9444 - regression_loss: 2.8328 - classification_loss: 1.1115 124/500 [======>.......................] - ETA: 2:22 - loss: 3.9420 - regression_loss: 2.8310 - classification_loss: 1.1110 125/500 [======>.......................] - ETA: 2:21 - loss: 3.9411 - regression_loss: 2.8304 - classification_loss: 1.1107 126/500 [======>.......................] - ETA: 2:21 - loss: 3.9387 - regression_loss: 2.8285 - classification_loss: 1.1102 127/500 [======>.......................] - ETA: 2:20 - loss: 3.9353 - regression_loss: 2.8260 - classification_loss: 1.1093 128/500 [======>.......................] - ETA: 2:20 - loss: 3.9345 - regression_loss: 2.8253 - classification_loss: 1.1092 129/500 [======>.......................] - ETA: 2:19 - loss: 3.9331 - regression_loss: 2.8247 - classification_loss: 1.1084 130/500 [======>.......................] - ETA: 2:19 - loss: 3.9309 - regression_loss: 2.8236 - classification_loss: 1.1073 131/500 [======>.......................] - ETA: 2:18 - loss: 3.9302 - regression_loss: 2.8231 - classification_loss: 1.1071 132/500 [======>.......................] - ETA: 2:17 - loss: 3.9269 - regression_loss: 2.8206 - classification_loss: 1.1063 133/500 [======>.......................] - ETA: 2:17 - loss: 3.9261 - regression_loss: 2.8205 - classification_loss: 1.1057 134/500 [=======>......................] - ETA: 2:16 - loss: 3.9226 - regression_loss: 2.8176 - classification_loss: 1.1050 135/500 [=======>......................] - ETA: 2:16 - loss: 3.9218 - regression_loss: 2.8177 - classification_loss: 1.1041 136/500 [=======>......................] - ETA: 2:15 - loss: 3.9187 - regression_loss: 2.8154 - classification_loss: 1.1034 137/500 [=======>......................] - ETA: 2:15 - loss: 3.9164 - regression_loss: 2.8138 - classification_loss: 1.1026 138/500 [=======>......................] - ETA: 2:14 - loss: 3.9149 - regression_loss: 2.8121 - classification_loss: 1.1027 139/500 [=======>......................] - ETA: 2:14 - loss: 3.9124 - regression_loss: 2.8100 - classification_loss: 1.1024 140/500 [=======>......................] - ETA: 2:13 - loss: 3.9107 - regression_loss: 2.8083 - classification_loss: 1.1024 141/500 [=======>......................] - ETA: 2:13 - loss: 3.9082 - regression_loss: 2.8058 - classification_loss: 1.1024 142/500 [=======>......................] - ETA: 2:12 - loss: 3.9050 - regression_loss: 2.8038 - classification_loss: 1.1012 143/500 [=======>......................] - ETA: 2:12 - loss: 3.9014 - regression_loss: 2.8013 - classification_loss: 1.1002 144/500 [=======>......................] - ETA: 2:11 - loss: 3.8994 - regression_loss: 2.7995 - classification_loss: 1.0999 145/500 [=======>......................] - ETA: 2:10 - loss: 3.8949 - regression_loss: 2.7965 - classification_loss: 1.0984 146/500 [=======>......................] - ETA: 2:10 - loss: 3.8912 - regression_loss: 2.7941 - classification_loss: 1.0971 147/500 [=======>......................] - ETA: 2:09 - loss: 3.8873 - regression_loss: 2.7918 - classification_loss: 1.0955 148/500 [=======>......................] - ETA: 2:09 - loss: 3.8835 - regression_loss: 2.7894 - classification_loss: 1.0941 149/500 [=======>......................] - ETA: 2:08 - loss: 3.8795 - regression_loss: 2.7868 - classification_loss: 1.0927 150/500 [========>.....................] - ETA: 2:08 - loss: 3.8791 - regression_loss: 2.7870 - classification_loss: 1.0921 151/500 [========>.....................] - ETA: 2:07 - loss: 3.8750 - regression_loss: 2.7850 - classification_loss: 1.0900 152/500 [========>.....................] - ETA: 2:07 - loss: 3.8711 - regression_loss: 2.7826 - classification_loss: 1.0885 153/500 [========>.....................] - ETA: 2:06 - loss: 3.8725 - regression_loss: 2.7842 - classification_loss: 1.0883 154/500 [========>.....................] - ETA: 2:06 - loss: 3.8691 - regression_loss: 2.7818 - classification_loss: 1.0873 155/500 [========>.....................] - ETA: 2:05 - loss: 3.8636 - regression_loss: 2.7786 - classification_loss: 1.0850 156/500 [========>.....................] - ETA: 2:05 - loss: 3.8601 - regression_loss: 2.7773 - classification_loss: 1.0828 157/500 [========>.....................] - ETA: 2:04 - loss: 3.8598 - regression_loss: 2.7770 - classification_loss: 1.0827 158/500 [========>.....................] - ETA: 2:04 - loss: 3.8563 - regression_loss: 2.7755 - classification_loss: 1.0808 159/500 [========>.....................] - ETA: 2:04 - loss: 3.8505 - regression_loss: 2.7718 - classification_loss: 1.0787 160/500 [========>.....................] - ETA: 2:03 - loss: 3.8475 - regression_loss: 2.7711 - classification_loss: 1.0764 161/500 [========>.....................] - ETA: 2:03 - loss: 3.8430 - regression_loss: 2.7685 - classification_loss: 1.0745 162/500 [========>.....................] - ETA: 2:02 - loss: 3.8419 - regression_loss: 2.7680 - classification_loss: 1.0738 163/500 [========>.....................] - ETA: 2:02 - loss: 3.8410 - regression_loss: 2.7668 - classification_loss: 1.0741 164/500 [========>.....................] - ETA: 2:01 - loss: 3.8367 - regression_loss: 2.7646 - classification_loss: 1.0721 165/500 [========>.....................] - ETA: 2:01 - loss: 3.8347 - regression_loss: 2.7632 - classification_loss: 1.0715 166/500 [========>.....................] - ETA: 2:00 - loss: 3.8309 - regression_loss: 2.7618 - classification_loss: 1.0692 167/500 [=========>....................] - ETA: 2:00 - loss: 3.8273 - regression_loss: 2.7599 - classification_loss: 1.0674 168/500 [=========>....................] - ETA: 1:59 - loss: 3.8260 - regression_loss: 2.7598 - classification_loss: 1.0662 169/500 [=========>....................] - ETA: 1:59 - loss: 3.8219 - regression_loss: 2.7582 - classification_loss: 1.0637 170/500 [=========>....................] - ETA: 1:58 - loss: 3.8175 - regression_loss: 2.7562 - classification_loss: 1.0613 171/500 [=========>....................] - ETA: 1:58 - loss: 3.8156 - regression_loss: 2.7558 - classification_loss: 1.0598 172/500 [=========>....................] - ETA: 1:57 - loss: 3.8109 - regression_loss: 2.7535 - classification_loss: 1.0575 173/500 [=========>....................] - ETA: 1:57 - loss: 3.8109 - regression_loss: 2.7534 - classification_loss: 1.0575 174/500 [=========>....................] - ETA: 1:56 - loss: 3.8085 - regression_loss: 2.7527 - classification_loss: 1.0558 175/500 [=========>....................] - ETA: 1:56 - loss: 3.8059 - regression_loss: 2.7513 - classification_loss: 1.0547 176/500 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[============================>.] - ETA: 3s - loss: 3.3218 - regression_loss: 2.5569 - classification_loss: 0.7650 489/500 [============================>.] - ETA: 3s - loss: 3.3202 - regression_loss: 2.5561 - classification_loss: 0.7642 490/500 [============================>.] - ETA: 3s - loss: 3.3177 - regression_loss: 2.5545 - classification_loss: 0.7632 491/500 [============================>.] - ETA: 2s - loss: 3.3159 - regression_loss: 2.5536 - classification_loss: 0.7623 492/500 [============================>.] - ETA: 2s - loss: 3.3149 - regression_loss: 2.5530 - classification_loss: 0.7619 493/500 [============================>.] - ETA: 2s - loss: 3.3133 - regression_loss: 2.5521 - classification_loss: 0.7612 494/500 [============================>.] - ETA: 1s - loss: 3.3114 - regression_loss: 2.5511 - classification_loss: 0.7603 495/500 [============================>.] - ETA: 1s - loss: 3.3100 - regression_loss: 2.5505 - classification_loss: 0.7596 496/500 [============================>.] - ETA: 1s - loss: 3.3090 - regression_loss: 2.5499 - classification_loss: 0.7591 497/500 [============================>.] - ETA: 0s - loss: 3.3077 - regression_loss: 2.5493 - classification_loss: 0.7584 498/500 [============================>.] - ETA: 0s - loss: 3.3073 - regression_loss: 2.5494 - classification_loss: 0.7579 499/500 [============================>.] - ETA: 0s - loss: 3.3068 - regression_loss: 2.5490 - classification_loss: 0.7578 500/500 [==============================] - 162s 324ms/step - loss: 3.3061 - regression_loss: 2.5487 - classification_loss: 0.7574 326 instances of class plum with average precision: 0.1992 mAP: 0.1992 Epoch 00001: saving model to ./training/snapshots/resnet101_pascal_01.h5 Epoch 2/150 1/500 [..............................] - ETA: 2:42 - loss: 2.7245 - regression_loss: 2.2561 - classification_loss: 0.4684 2/500 [..............................] - ETA: 2:37 - loss: 2.4698 - regression_loss: 2.0807 - classification_loss: 0.3891 3/500 [..............................] - ETA: 2:36 - loss: 2.6058 - regression_loss: 2.1829 - classification_loss: 0.4229 4/500 [..............................] - ETA: 2:34 - loss: 2.8509 - regression_loss: 2.3443 - classification_loss: 0.5066 5/500 [..............................] - ETA: 2:33 - loss: 2.9379 - regression_loss: 2.3885 - classification_loss: 0.5494 6/500 [..............................] - ETA: 2:32 - loss: 2.8888 - regression_loss: 2.3473 - classification_loss: 0.5415 7/500 [..............................] - ETA: 2:31 - loss: 2.9311 - regression_loss: 2.4028 - classification_loss: 0.5283 8/500 [..............................] - ETA: 2:31 - loss: 2.9574 - regression_loss: 2.4299 - classification_loss: 0.5275 9/500 [..............................] - ETA: 2:30 - loss: 2.9739 - regression_loss: 2.4468 - classification_loss: 0.5271 10/500 [..............................] - ETA: 2:29 - loss: 2.9575 - regression_loss: 2.4310 - classification_loss: 0.5265 11/500 [..............................] - ETA: 2:29 - loss: 3.0046 - regression_loss: 2.4518 - classification_loss: 0.5528 12/500 [..............................] - ETA: 2:28 - loss: 2.9795 - regression_loss: 2.4336 - classification_loss: 0.5459 13/500 [..............................] - ETA: 2:28 - loss: 2.9548 - regression_loss: 2.4165 - classification_loss: 0.5383 14/500 [..............................] - ETA: 2:27 - loss: 2.9169 - regression_loss: 2.3959 - classification_loss: 0.5210 15/500 [..............................] - ETA: 2:27 - loss: 2.9001 - regression_loss: 2.3877 - classification_loss: 0.5125 16/500 [..............................] - ETA: 2:27 - loss: 2.9270 - regression_loss: 2.4073 - classification_loss: 0.5197 17/500 [>.............................] - ETA: 2:27 - loss: 2.9342 - regression_loss: 2.4220 - classification_loss: 0.5122 18/500 [>.............................] - ETA: 2:26 - loss: 2.9410 - regression_loss: 2.4319 - classification_loss: 0.5090 19/500 [>.............................] - ETA: 2:26 - loss: 2.9240 - regression_loss: 2.4223 - classification_loss: 0.5016 20/500 [>.............................] - ETA: 2:26 - loss: 2.9157 - regression_loss: 2.4166 - classification_loss: 0.4991 21/500 [>.............................] - ETA: 2:25 - loss: 2.9155 - regression_loss: 2.4165 - classification_loss: 0.4990 22/500 [>.............................] - ETA: 2:25 - loss: 2.8897 - regression_loss: 2.4003 - classification_loss: 0.4894 23/500 [>.............................] - ETA: 2:25 - loss: 2.8796 - regression_loss: 2.3902 - classification_loss: 0.4893 24/500 [>.............................] - ETA: 2:24 - loss: 2.8921 - regression_loss: 2.4007 - classification_loss: 0.4914 25/500 [>.............................] - ETA: 2:24 - loss: 2.8933 - regression_loss: 2.3999 - classification_loss: 0.4934 26/500 [>.............................] - ETA: 2:23 - loss: 2.8886 - regression_loss: 2.3977 - classification_loss: 0.4909 27/500 [>.............................] - ETA: 2:23 - loss: 2.8656 - regression_loss: 2.3806 - classification_loss: 0.4850 28/500 [>.............................] - ETA: 2:23 - loss: 2.8543 - regression_loss: 2.3723 - classification_loss: 0.4820 29/500 [>.............................] - ETA: 2:22 - loss: 2.8496 - regression_loss: 2.3704 - classification_loss: 0.4793 30/500 [>.............................] - ETA: 2:22 - loss: 2.8406 - regression_loss: 2.3637 - classification_loss: 0.4769 31/500 [>.............................] - ETA: 2:22 - loss: 2.8281 - regression_loss: 2.3564 - classification_loss: 0.4717 32/500 [>.............................] - ETA: 2:22 - loss: 2.8314 - regression_loss: 2.3582 - classification_loss: 0.4732 33/500 [>.............................] - ETA: 2:21 - loss: 2.8215 - regression_loss: 2.3509 - classification_loss: 0.4706 34/500 [=>............................] - ETA: 2:21 - loss: 2.8201 - regression_loss: 2.3494 - classification_loss: 0.4706 35/500 [=>............................] - ETA: 2:21 - loss: 2.8125 - regression_loss: 2.3445 - classification_loss: 0.4680 36/500 [=>............................] - ETA: 2:20 - loss: 2.8099 - regression_loss: 2.3452 - classification_loss: 0.4647 37/500 [=>............................] - ETA: 2:20 - loss: 2.8138 - regression_loss: 2.3457 - classification_loss: 0.4681 38/500 [=>............................] - ETA: 2:20 - loss: 2.8111 - regression_loss: 2.3402 - classification_loss: 0.4709 39/500 [=>............................] - ETA: 2:20 - loss: 2.8139 - regression_loss: 2.3431 - classification_loss: 0.4708 40/500 [=>............................] - ETA: 2:19 - loss: 2.8176 - regression_loss: 2.3456 - classification_loss: 0.4720 41/500 [=>............................] - ETA: 2:19 - loss: 2.8404 - regression_loss: 2.3505 - classification_loss: 0.4899 42/500 [=>............................] - ETA: 2:19 - loss: 2.8339 - regression_loss: 2.3467 - classification_loss: 0.4872 43/500 [=>............................] - ETA: 2:18 - loss: 2.8313 - regression_loss: 2.3405 - classification_loss: 0.4908 44/500 [=>............................] - ETA: 2:18 - loss: 2.8374 - regression_loss: 2.3436 - classification_loss: 0.4938 45/500 [=>............................] - ETA: 2:18 - loss: 2.8324 - regression_loss: 2.3393 - classification_loss: 0.4932 46/500 [=>............................] - ETA: 2:17 - loss: 2.8281 - regression_loss: 2.3361 - classification_loss: 0.4920 47/500 [=>............................] - ETA: 2:17 - loss: 2.8253 - regression_loss: 2.3366 - classification_loss: 0.4887 48/500 [=>............................] - ETA: 2:17 - loss: 2.8181 - regression_loss: 2.3325 - classification_loss: 0.4856 49/500 [=>............................] - ETA: 2:16 - loss: 2.8314 - regression_loss: 2.3425 - classification_loss: 0.4889 50/500 [==>...........................] - ETA: 2:16 - loss: 2.8309 - regression_loss: 2.3415 - classification_loss: 0.4894 51/500 [==>...........................] - ETA: 2:16 - loss: 2.8228 - regression_loss: 2.3363 - classification_loss: 0.4865 52/500 [==>...........................] - ETA: 2:15 - loss: 2.8179 - regression_loss: 2.3328 - classification_loss: 0.4851 53/500 [==>...........................] - ETA: 2:15 - loss: 2.8067 - regression_loss: 2.3250 - classification_loss: 0.4817 54/500 [==>...........................] - ETA: 2:15 - loss: 2.8228 - regression_loss: 2.3385 - classification_loss: 0.4842 55/500 [==>...........................] - ETA: 2:14 - loss: 2.8181 - regression_loss: 2.3364 - classification_loss: 0.4818 56/500 [==>...........................] - ETA: 2:14 - loss: 2.8230 - regression_loss: 2.3416 - classification_loss: 0.4814 57/500 [==>...........................] - ETA: 2:14 - loss: 2.8257 - regression_loss: 2.3434 - classification_loss: 0.4822 58/500 [==>...........................] - ETA: 2:14 - loss: 2.8209 - regression_loss: 2.3402 - classification_loss: 0.4807 59/500 [==>...........................] - ETA: 2:13 - loss: 2.8240 - regression_loss: 2.3425 - classification_loss: 0.4815 60/500 [==>...........................] - ETA: 2:13 - loss: 2.8172 - regression_loss: 2.3376 - classification_loss: 0.4796 61/500 [==>...........................] - ETA: 2:13 - loss: 2.8194 - regression_loss: 2.3401 - classification_loss: 0.4794 62/500 [==>...........................] - ETA: 2:12 - loss: 2.8151 - regression_loss: 2.3376 - classification_loss: 0.4774 63/500 [==>...........................] - ETA: 2:12 - loss: 2.8196 - regression_loss: 2.3414 - classification_loss: 0.4782 64/500 [==>...........................] - ETA: 2:12 - loss: 2.8245 - regression_loss: 2.3480 - classification_loss: 0.4765 65/500 [==>...........................] - ETA: 2:11 - loss: 2.8225 - regression_loss: 2.3469 - classification_loss: 0.4756 66/500 [==>...........................] - ETA: 2:11 - loss: 2.8240 - regression_loss: 2.3476 - classification_loss: 0.4765 67/500 [===>..........................] - ETA: 2:11 - loss: 2.8266 - regression_loss: 2.3518 - classification_loss: 0.4749 68/500 [===>..........................] - ETA: 2:10 - loss: 2.8306 - regression_loss: 2.3558 - classification_loss: 0.4748 69/500 [===>..........................] - ETA: 2:10 - loss: 2.8377 - regression_loss: 2.3616 - classification_loss: 0.4761 70/500 [===>..........................] - ETA: 2:10 - loss: 2.8405 - regression_loss: 2.3647 - classification_loss: 0.4758 71/500 [===>..........................] - ETA: 2:09 - loss: 2.8340 - regression_loss: 2.3594 - classification_loss: 0.4746 72/500 [===>..........................] - ETA: 2:09 - loss: 2.8313 - regression_loss: 2.3574 - classification_loss: 0.4739 73/500 [===>..........................] - ETA: 2:09 - loss: 2.8348 - regression_loss: 2.3588 - classification_loss: 0.4759 74/500 [===>..........................] - ETA: 2:09 - loss: 2.8318 - regression_loss: 2.3566 - classification_loss: 0.4752 75/500 [===>..........................] - ETA: 2:08 - loss: 2.8312 - regression_loss: 2.3559 - classification_loss: 0.4754 76/500 [===>..........................] - ETA: 2:08 - loss: 2.8271 - regression_loss: 2.3535 - classification_loss: 0.4736 77/500 [===>..........................] - ETA: 2:08 - loss: 2.8294 - regression_loss: 2.3564 - classification_loss: 0.4730 78/500 [===>..........................] - ETA: 2:07 - loss: 2.8359 - regression_loss: 2.3592 - classification_loss: 0.4768 79/500 [===>..........................] - ETA: 2:07 - loss: 2.8306 - regression_loss: 2.3563 - classification_loss: 0.4743 80/500 [===>..........................] - ETA: 2:07 - loss: 2.8328 - regression_loss: 2.3578 - classification_loss: 0.4750 81/500 [===>..........................] - ETA: 2:06 - loss: 2.8273 - regression_loss: 2.3534 - classification_loss: 0.4739 82/500 [===>..........................] - ETA: 2:06 - loss: 2.8235 - regression_loss: 2.3507 - classification_loss: 0.4728 83/500 [===>..........................] - ETA: 2:06 - loss: 2.8212 - regression_loss: 2.3500 - classification_loss: 0.4712 84/500 [====>.........................] - ETA: 2:05 - loss: 2.8201 - regression_loss: 2.3500 - classification_loss: 0.4701 85/500 [====>.........................] - ETA: 2:05 - loss: 2.8174 - regression_loss: 2.3475 - classification_loss: 0.4699 86/500 [====>.........................] - ETA: 2:05 - loss: 2.8132 - regression_loss: 2.3452 - classification_loss: 0.4680 87/500 [====>.........................] - ETA: 2:05 - loss: 2.8152 - regression_loss: 2.3483 - classification_loss: 0.4669 88/500 [====>.........................] - ETA: 2:04 - loss: 2.8180 - regression_loss: 2.3491 - classification_loss: 0.4690 89/500 [====>.........................] - ETA: 2:04 - loss: 2.8143 - regression_loss: 2.3458 - classification_loss: 0.4685 90/500 [====>.........................] - ETA: 2:04 - loss: 2.8068 - regression_loss: 2.3406 - classification_loss: 0.4662 91/500 [====>.........................] - ETA: 2:03 - loss: 2.8085 - regression_loss: 2.3427 - classification_loss: 0.4658 92/500 [====>.........................] - ETA: 2:03 - loss: 2.8203 - regression_loss: 2.3485 - classification_loss: 0.4718 93/500 [====>.........................] - ETA: 2:03 - loss: 2.8146 - regression_loss: 2.3446 - classification_loss: 0.4701 94/500 [====>.........................] - ETA: 2:02 - loss: 2.8088 - regression_loss: 2.3408 - classification_loss: 0.4679 95/500 [====>.........................] - ETA: 2:02 - loss: 2.8041 - regression_loss: 2.3381 - classification_loss: 0.4660 96/500 [====>.........................] - ETA: 2:02 - loss: 2.8051 - regression_loss: 2.3384 - classification_loss: 0.4667 97/500 [====>.........................] - ETA: 2:02 - loss: 2.7948 - regression_loss: 2.3300 - classification_loss: 0.4648 98/500 [====>.........................] - ETA: 2:01 - loss: 2.7936 - regression_loss: 2.3281 - classification_loss: 0.4655 99/500 [====>.........................] - ETA: 2:01 - loss: 2.7871 - regression_loss: 2.3238 - classification_loss: 0.4633 100/500 [=====>........................] - ETA: 2:01 - loss: 2.7880 - regression_loss: 2.3238 - classification_loss: 0.4642 101/500 [=====>........................] - ETA: 2:00 - loss: 2.7895 - regression_loss: 2.3237 - classification_loss: 0.4657 102/500 [=====>........................] - ETA: 2:00 - loss: 2.7805 - regression_loss: 2.3176 - classification_loss: 0.4629 103/500 [=====>........................] - ETA: 2:00 - loss: 2.7821 - regression_loss: 2.3197 - classification_loss: 0.4624 104/500 [=====>........................] - ETA: 1:59 - loss: 2.7830 - regression_loss: 2.3201 - classification_loss: 0.4629 105/500 [=====>........................] - ETA: 1:59 - loss: 2.7840 - regression_loss: 2.3201 - classification_loss: 0.4639 106/500 [=====>........................] - ETA: 1:59 - loss: 2.7792 - regression_loss: 2.3169 - classification_loss: 0.4623 107/500 [=====>........................] - ETA: 1:59 - loss: 2.7775 - regression_loss: 2.3156 - classification_loss: 0.4619 108/500 [=====>........................] - ETA: 1:58 - loss: 2.7778 - regression_loss: 2.3164 - classification_loss: 0.4614 109/500 [=====>........................] - ETA: 1:58 - loss: 2.7785 - regression_loss: 2.3176 - classification_loss: 0.4609 110/500 [=====>........................] - ETA: 1:58 - loss: 2.7783 - regression_loss: 2.3175 - classification_loss: 0.4609 111/500 [=====>........................] - ETA: 1:57 - loss: 2.7784 - regression_loss: 2.3168 - classification_loss: 0.4616 112/500 [=====>........................] - ETA: 1:57 - loss: 2.7768 - regression_loss: 2.3161 - classification_loss: 0.4606 113/500 [=====>........................] - ETA: 1:57 - loss: 2.7735 - regression_loss: 2.3137 - classification_loss: 0.4598 114/500 [=====>........................] - ETA: 1:56 - loss: 2.7704 - regression_loss: 2.3117 - classification_loss: 0.4587 115/500 [=====>........................] - ETA: 1:56 - loss: 2.7637 - regression_loss: 2.3064 - classification_loss: 0.4573 116/500 [=====>........................] - ETA: 1:56 - loss: 2.7659 - regression_loss: 2.3078 - classification_loss: 0.4581 117/500 [======>.......................] - ETA: 1:56 - loss: 2.7633 - regression_loss: 2.3062 - classification_loss: 0.4571 118/500 [======>.......................] - ETA: 1:55 - loss: 2.7681 - regression_loss: 2.3100 - classification_loss: 0.4582 119/500 [======>.......................] - ETA: 1:55 - loss: 2.7680 - regression_loss: 2.3099 - classification_loss: 0.4581 120/500 [======>.......................] - ETA: 1:55 - loss: 2.7635 - regression_loss: 2.3073 - classification_loss: 0.4562 121/500 [======>.......................] - ETA: 1:54 - loss: 2.7608 - regression_loss: 2.3050 - classification_loss: 0.4559 122/500 [======>.......................] - ETA: 1:54 - loss: 2.7578 - regression_loss: 2.3024 - classification_loss: 0.4555 123/500 [======>.......................] - ETA: 1:54 - loss: 2.7546 - regression_loss: 2.3001 - classification_loss: 0.4545 124/500 [======>.......................] - ETA: 1:53 - loss: 2.7542 - regression_loss: 2.2995 - classification_loss: 0.4547 125/500 [======>.......................] - ETA: 1:53 - loss: 2.7463 - regression_loss: 2.2932 - classification_loss: 0.4531 126/500 [======>.......................] - ETA: 1:53 - loss: 2.7450 - regression_loss: 2.2916 - classification_loss: 0.4533 127/500 [======>.......................] - ETA: 1:53 - loss: 2.7488 - regression_loss: 2.2933 - classification_loss: 0.4555 128/500 [======>.......................] - ETA: 1:52 - loss: 2.7496 - regression_loss: 2.2942 - classification_loss: 0.4554 129/500 [======>.......................] - ETA: 1:52 - loss: 2.7509 - regression_loss: 2.2953 - classification_loss: 0.4556 130/500 [======>.......................] - ETA: 1:52 - loss: 2.7492 - regression_loss: 2.2941 - classification_loss: 0.4551 131/500 [======>.......................] - ETA: 1:51 - loss: 2.7504 - regression_loss: 2.2959 - classification_loss: 0.4545 132/500 [======>.......................] - ETA: 1:51 - loss: 2.7471 - regression_loss: 2.2936 - classification_loss: 0.4535 133/500 [======>.......................] - ETA: 1:51 - loss: 2.7445 - regression_loss: 2.2919 - classification_loss: 0.4526 134/500 [=======>......................] - ETA: 1:51 - loss: 2.7412 - regression_loss: 2.2889 - classification_loss: 0.4523 135/500 [=======>......................] - ETA: 1:50 - loss: 2.7400 - regression_loss: 2.2881 - classification_loss: 0.4519 136/500 [=======>......................] - ETA: 1:50 - loss: 2.7371 - regression_loss: 2.2863 - classification_loss: 0.4509 137/500 [=======>......................] - ETA: 1:50 - loss: 2.7375 - regression_loss: 2.2863 - classification_loss: 0.4512 138/500 [=======>......................] - ETA: 1:49 - loss: 2.7343 - regression_loss: 2.2839 - classification_loss: 0.4504 139/500 [=======>......................] - ETA: 1:49 - loss: 2.7323 - regression_loss: 2.2824 - classification_loss: 0.4499 140/500 [=======>......................] - ETA: 1:49 - loss: 2.7290 - regression_loss: 2.2798 - classification_loss: 0.4491 141/500 [=======>......................] - ETA: 1:48 - loss: 2.7294 - regression_loss: 2.2793 - classification_loss: 0.4501 142/500 [=======>......................] - ETA: 1:48 - loss: 2.7455 - regression_loss: 2.2822 - classification_loss: 0.4634 143/500 [=======>......................] - ETA: 1:48 - loss: 2.7485 - regression_loss: 2.2851 - classification_loss: 0.4635 144/500 [=======>......................] - ETA: 1:47 - loss: 2.7493 - regression_loss: 2.2863 - classification_loss: 0.4630 145/500 [=======>......................] - ETA: 1:47 - loss: 2.7490 - regression_loss: 2.2866 - classification_loss: 0.4624 146/500 [=======>......................] - ETA: 1:47 - loss: 2.7467 - regression_loss: 2.2849 - classification_loss: 0.4618 147/500 [=======>......................] - ETA: 1:47 - loss: 2.7437 - regression_loss: 2.2826 - classification_loss: 0.4611 148/500 [=======>......................] - ETA: 1:46 - loss: 2.7415 - regression_loss: 2.2805 - classification_loss: 0.4610 149/500 [=======>......................] - ETA: 1:46 - loss: 2.7458 - regression_loss: 2.2824 - classification_loss: 0.4634 150/500 [========>.....................] - ETA: 1:46 - loss: 2.7388 - regression_loss: 2.2767 - classification_loss: 0.4621 151/500 [========>.....................] - ETA: 1:45 - loss: 2.7389 - regression_loss: 2.2768 - classification_loss: 0.4621 152/500 [========>.....................] - ETA: 1:45 - loss: 2.7379 - regression_loss: 2.2762 - classification_loss: 0.4617 153/500 [========>.....................] - ETA: 1:45 - loss: 2.7393 - regression_loss: 2.2784 - classification_loss: 0.4609 154/500 [========>.....................] - ETA: 1:44 - loss: 2.7365 - regression_loss: 2.2759 - classification_loss: 0.4606 155/500 [========>.....................] - ETA: 1:44 - loss: 2.7345 - regression_loss: 2.2748 - classification_loss: 0.4597 156/500 [========>.....................] - ETA: 1:44 - loss: 2.7306 - regression_loss: 2.2718 - classification_loss: 0.4587 157/500 [========>.....................] - ETA: 1:44 - loss: 2.7280 - regression_loss: 2.2704 - classification_loss: 0.4575 158/500 [========>.....................] - ETA: 1:43 - loss: 2.7255 - regression_loss: 2.2687 - classification_loss: 0.4568 159/500 [========>.....................] - ETA: 1:43 - loss: 2.7254 - regression_loss: 2.2680 - classification_loss: 0.4575 160/500 [========>.....................] - ETA: 1:43 - loss: 2.7231 - regression_loss: 2.2657 - classification_loss: 0.4574 161/500 [========>.....................] - ETA: 1:42 - loss: 2.7205 - regression_loss: 2.2635 - classification_loss: 0.4570 162/500 [========>.....................] - ETA: 1:42 - loss: 2.7209 - regression_loss: 2.2645 - classification_loss: 0.4564 163/500 [========>.....................] - ETA: 1:42 - loss: 2.7196 - regression_loss: 2.2632 - classification_loss: 0.4564 164/500 [========>.....................] - ETA: 1:41 - loss: 2.7204 - regression_loss: 2.2647 - classification_loss: 0.4557 165/500 [========>.....................] - ETA: 1:41 - loss: 2.7206 - regression_loss: 2.2644 - classification_loss: 0.4562 166/500 [========>.....................] - ETA: 1:41 - loss: 2.7223 - regression_loss: 2.2663 - classification_loss: 0.4560 167/500 [=========>....................] - ETA: 1:41 - loss: 2.7239 - regression_loss: 2.2682 - classification_loss: 0.4558 168/500 [=========>....................] - ETA: 1:40 - loss: 2.7204 - regression_loss: 2.2659 - classification_loss: 0.4545 169/500 [=========>....................] - ETA: 1:40 - loss: 2.7164 - regression_loss: 2.2631 - classification_loss: 0.4533 170/500 [=========>....................] - ETA: 1:40 - loss: 2.7141 - regression_loss: 2.2617 - classification_loss: 0.4525 171/500 [=========>....................] - ETA: 1:39 - loss: 2.7140 - regression_loss: 2.2614 - classification_loss: 0.4527 172/500 [=========>....................] - ETA: 1:39 - loss: 2.7157 - regression_loss: 2.2617 - classification_loss: 0.4540 173/500 [=========>....................] - ETA: 1:39 - loss: 2.7170 - regression_loss: 2.2625 - classification_loss: 0.4544 174/500 [=========>....................] - ETA: 1:38 - loss: 2.7134 - regression_loss: 2.2600 - classification_loss: 0.4534 175/500 [=========>....................] - ETA: 1:38 - loss: 2.7151 - regression_loss: 2.2603 - classification_loss: 0.4548 176/500 [=========>....................] - ETA: 1:38 - loss: 2.7123 - regression_loss: 2.2585 - classification_loss: 0.4538 177/500 [=========>....................] - ETA: 1:37 - loss: 2.7119 - regression_loss: 2.2586 - classification_loss: 0.4532 178/500 [=========>....................] - ETA: 1:37 - loss: 2.7144 - regression_loss: 2.2614 - classification_loss: 0.4530 179/500 [=========>....................] - ETA: 1:37 - loss: 2.7122 - regression_loss: 2.2599 - classification_loss: 0.4523 180/500 [=========>....................] - ETA: 1:37 - loss: 2.7132 - regression_loss: 2.2607 - classification_loss: 0.4525 181/500 [=========>....................] - ETA: 1:36 - loss: 2.7134 - regression_loss: 2.2603 - classification_loss: 0.4531 182/500 [=========>....................] - ETA: 1:36 - loss: 2.7180 - regression_loss: 2.2637 - classification_loss: 0.4543 183/500 [=========>....................] - ETA: 1:36 - loss: 2.7169 - regression_loss: 2.2629 - classification_loss: 0.4540 184/500 [==========>...................] - ETA: 1:35 - loss: 2.7146 - regression_loss: 2.2612 - classification_loss: 0.4534 185/500 [==========>...................] - ETA: 1:35 - loss: 2.7119 - regression_loss: 2.2568 - classification_loss: 0.4551 186/500 [==========>...................] - ETA: 1:35 - loss: 2.7111 - regression_loss: 2.2564 - classification_loss: 0.4547 187/500 [==========>...................] - ETA: 1:35 - loss: 2.7090 - regression_loss: 2.2549 - classification_loss: 0.4541 188/500 [==========>...................] - ETA: 1:34 - loss: 2.7077 - regression_loss: 2.2542 - classification_loss: 0.4535 189/500 [==========>...................] - ETA: 1:34 - loss: 2.7110 - regression_loss: 2.2569 - classification_loss: 0.4542 190/500 [==========>...................] - ETA: 1:34 - loss: 2.7120 - regression_loss: 2.2580 - classification_loss: 0.4540 191/500 [==========>...................] - ETA: 1:33 - loss: 2.7156 - regression_loss: 2.2612 - classification_loss: 0.4545 192/500 [==========>...................] - ETA: 1:33 - loss: 2.7137 - regression_loss: 2.2598 - classification_loss: 0.4538 193/500 [==========>...................] - ETA: 1:33 - loss: 2.7119 - regression_loss: 2.2586 - classification_loss: 0.4533 194/500 [==========>...................] - ETA: 1:33 - loss: 2.7168 - regression_loss: 2.2619 - classification_loss: 0.4549 195/500 [==========>...................] - ETA: 1:32 - loss: 2.7175 - regression_loss: 2.2617 - classification_loss: 0.4557 196/500 [==========>...................] - ETA: 1:32 - loss: 2.7168 - regression_loss: 2.2608 - classification_loss: 0.4560 197/500 [==========>...................] - ETA: 1:32 - loss: 2.7143 - regression_loss: 2.2588 - classification_loss: 0.4555 198/500 [==========>...................] - ETA: 1:31 - loss: 2.7119 - regression_loss: 2.2570 - classification_loss: 0.4549 199/500 [==========>...................] - ETA: 1:31 - loss: 2.7142 - regression_loss: 2.2585 - classification_loss: 0.4557 200/500 [===========>..................] - ETA: 1:31 - loss: 2.7145 - regression_loss: 2.2584 - classification_loss: 0.4561 201/500 [===========>..................] - ETA: 1:31 - loss: 2.7151 - regression_loss: 2.2594 - classification_loss: 0.4556 202/500 [===========>..................] - ETA: 1:30 - loss: 2.7177 - regression_loss: 2.2607 - classification_loss: 0.4570 203/500 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[===========================>..] - ETA: 5s - loss: 2.5874 - regression_loss: 2.1564 - classification_loss: 0.4309 484/500 [============================>.] - ETA: 5s - loss: 2.5866 - regression_loss: 2.1559 - classification_loss: 0.4307 485/500 [============================>.] - ETA: 4s - loss: 2.5866 - regression_loss: 2.1561 - classification_loss: 0.4305 486/500 [============================>.] - ETA: 4s - loss: 2.5861 - regression_loss: 2.1558 - classification_loss: 0.4303 487/500 [============================>.] - ETA: 4s - loss: 2.5861 - regression_loss: 2.1558 - classification_loss: 0.4303 488/500 [============================>.] - ETA: 3s - loss: 2.5857 - regression_loss: 2.1554 - classification_loss: 0.4303 489/500 [============================>.] - ETA: 3s - loss: 2.5864 - regression_loss: 2.1559 - classification_loss: 0.4305 490/500 [============================>.] - ETA: 3s - loss: 2.5857 - regression_loss: 2.1553 - classification_loss: 0.4304 491/500 [============================>.] - ETA: 2s - loss: 2.5844 - regression_loss: 2.1543 - classification_loss: 0.4301 492/500 [============================>.] - ETA: 2s - loss: 2.5838 - regression_loss: 2.1538 - classification_loss: 0.4300 493/500 [============================>.] - ETA: 2s - loss: 2.5831 - regression_loss: 2.1531 - classification_loss: 0.4300 494/500 [============================>.] - ETA: 1s - loss: 2.5829 - regression_loss: 2.1532 - classification_loss: 0.4297 495/500 [============================>.] - ETA: 1s - loss: 2.5817 - regression_loss: 2.1522 - classification_loss: 0.4295 496/500 [============================>.] - ETA: 1s - loss: 2.5831 - regression_loss: 2.1533 - classification_loss: 0.4298 497/500 [============================>.] - ETA: 0s - loss: 2.5825 - regression_loss: 2.1527 - classification_loss: 0.4299 498/500 [============================>.] - ETA: 0s - loss: 2.5838 - regression_loss: 2.1539 - classification_loss: 0.4299 499/500 [============================>.] - ETA: 0s - loss: 2.5823 - regression_loss: 2.1528 - classification_loss: 0.4295 500/500 [==============================] - 158s 316ms/step - loss: 2.5824 - regression_loss: 2.1529 - classification_loss: 0.4295 326 instances of class plum with average precision: 0.5131 mAP: 0.5131 Epoch 00002: saving model to ./training/snapshots/resnet101_pascal_02.h5 Epoch 3/150 1/500 [..............................] - ETA: 2:49 - loss: 3.4080 - regression_loss: 2.9282 - classification_loss: 0.4798 2/500 [..............................] - ETA: 2:47 - loss: 2.8159 - regression_loss: 2.3691 - classification_loss: 0.4468 3/500 [..............................] - ETA: 2:46 - loss: 2.6363 - regression_loss: 2.2329 - classification_loss: 0.4035 4/500 [..............................] - ETA: 2:44 - loss: 2.5661 - regression_loss: 2.1729 - classification_loss: 0.3932 5/500 [..............................] - ETA: 2:41 - loss: 2.6037 - regression_loss: 2.1795 - classification_loss: 0.4242 6/500 [..............................] - ETA: 2:40 - loss: 2.5090 - regression_loss: 2.1071 - classification_loss: 0.4019 7/500 [..............................] - ETA: 2:40 - loss: 2.3774 - regression_loss: 2.0015 - classification_loss: 0.3759 8/500 [..............................] - ETA: 2:40 - loss: 2.4218 - regression_loss: 2.0303 - classification_loss: 0.3915 9/500 [..............................] - ETA: 2:38 - loss: 2.4149 - regression_loss: 2.0329 - classification_loss: 0.3820 10/500 [..............................] - ETA: 2:38 - loss: 2.3692 - regression_loss: 2.0034 - classification_loss: 0.3658 11/500 [..............................] - ETA: 2:38 - loss: 2.3768 - regression_loss: 2.0129 - classification_loss: 0.3639 12/500 [..............................] - ETA: 2:38 - loss: 2.3562 - regression_loss: 1.9927 - classification_loss: 0.3635 13/500 [..............................] - ETA: 2:38 - loss: 2.3880 - regression_loss: 2.0123 - classification_loss: 0.3757 14/500 [..............................] - ETA: 2:39 - loss: 2.4101 - regression_loss: 2.0286 - classification_loss: 0.3816 15/500 [..............................] - ETA: 2:38 - loss: 2.3866 - regression_loss: 2.0128 - classification_loss: 0.3738 16/500 [..............................] - ETA: 2:38 - loss: 2.3506 - regression_loss: 1.9850 - classification_loss: 0.3656 17/500 [>.............................] - ETA: 2:38 - loss: 2.3473 - regression_loss: 1.9850 - classification_loss: 0.3623 18/500 [>.............................] - ETA: 2:38 - loss: 2.3202 - regression_loss: 1.9613 - classification_loss: 0.3589 19/500 [>.............................] - ETA: 2:37 - loss: 2.3475 - regression_loss: 1.9880 - classification_loss: 0.3595 20/500 [>.............................] - ETA: 2:36 - loss: 2.3555 - regression_loss: 1.9871 - classification_loss: 0.3684 21/500 [>.............................] - ETA: 2:35 - loss: 2.3281 - regression_loss: 1.9649 - classification_loss: 0.3632 22/500 [>.............................] - ETA: 2:35 - loss: 2.3363 - regression_loss: 1.9737 - classification_loss: 0.3625 23/500 [>.............................] - ETA: 2:34 - loss: 2.3093 - regression_loss: 1.9510 - classification_loss: 0.3583 24/500 [>.............................] - ETA: 2:34 - loss: 2.2921 - regression_loss: 1.9349 - classification_loss: 0.3572 25/500 [>.............................] - ETA: 2:34 - loss: 2.2714 - regression_loss: 1.9218 - classification_loss: 0.3496 26/500 [>.............................] - ETA: 2:33 - loss: 2.2745 - regression_loss: 1.9255 - classification_loss: 0.3490 27/500 [>.............................] - ETA: 2:33 - loss: 2.2400 - regression_loss: 1.8953 - classification_loss: 0.3446 28/500 [>.............................] - ETA: 2:33 - loss: 2.2555 - regression_loss: 1.9055 - classification_loss: 0.3500 29/500 [>.............................] - ETA: 2:33 - loss: 2.2549 - regression_loss: 1.9068 - classification_loss: 0.3482 30/500 [>.............................] - ETA: 2:32 - loss: 2.2697 - regression_loss: 1.9179 - classification_loss: 0.3519 31/500 [>.............................] - ETA: 2:32 - loss: 2.2555 - regression_loss: 1.9068 - classification_loss: 0.3487 32/500 [>.............................] - ETA: 2:31 - loss: 2.2357 - regression_loss: 1.8908 - classification_loss: 0.3448 33/500 [>.............................] - ETA: 2:31 - loss: 2.2466 - regression_loss: 1.8945 - classification_loss: 0.3521 34/500 [=>............................] - ETA: 2:30 - loss: 2.2664 - regression_loss: 1.9099 - classification_loss: 0.3565 35/500 [=>............................] - ETA: 2:30 - loss: 2.2789 - regression_loss: 1.9205 - classification_loss: 0.3584 36/500 [=>............................] - ETA: 2:30 - loss: 2.2707 - regression_loss: 1.9148 - classification_loss: 0.3558 37/500 [=>............................] - ETA: 2:29 - loss: 2.3062 - regression_loss: 1.9411 - classification_loss: 0.3651 38/500 [=>............................] - ETA: 2:29 - loss: 2.2997 - regression_loss: 1.9372 - classification_loss: 0.3625 39/500 [=>............................] - ETA: 2:29 - loss: 2.3079 - regression_loss: 1.9439 - classification_loss: 0.3640 40/500 [=>............................] - ETA: 2:28 - loss: 2.2960 - regression_loss: 1.9337 - classification_loss: 0.3623 41/500 [=>............................] - ETA: 2:28 - loss: 2.2868 - regression_loss: 1.9271 - classification_loss: 0.3597 42/500 [=>............................] - ETA: 2:28 - loss: 2.2891 - regression_loss: 1.9278 - classification_loss: 0.3613 43/500 [=>............................] - ETA: 2:27 - loss: 2.2909 - regression_loss: 1.9315 - classification_loss: 0.3594 44/500 [=>............................] - ETA: 2:27 - loss: 2.2964 - regression_loss: 1.9323 - classification_loss: 0.3641 45/500 [=>............................] - ETA: 2:27 - loss: 2.3014 - regression_loss: 1.9388 - classification_loss: 0.3626 46/500 [=>............................] - ETA: 2:27 - loss: 2.3105 - regression_loss: 1.9422 - classification_loss: 0.3683 47/500 [=>............................] - ETA: 2:26 - loss: 2.3184 - regression_loss: 1.9486 - classification_loss: 0.3698 48/500 [=>............................] - ETA: 2:26 - loss: 2.3121 - regression_loss: 1.9445 - classification_loss: 0.3677 49/500 [=>............................] - ETA: 2:26 - loss: 2.3121 - regression_loss: 1.9443 - classification_loss: 0.3679 50/500 [==>...........................] - ETA: 2:25 - loss: 2.3201 - regression_loss: 1.9487 - classification_loss: 0.3714 51/500 [==>...........................] - ETA: 2:25 - loss: 2.3370 - regression_loss: 1.9605 - classification_loss: 0.3764 52/500 [==>...........................] - ETA: 2:25 - loss: 2.3358 - regression_loss: 1.9599 - classification_loss: 0.3759 53/500 [==>...........................] - ETA: 2:24 - loss: 2.3398 - regression_loss: 1.9621 - classification_loss: 0.3777 54/500 [==>...........................] - ETA: 2:24 - loss: 2.3522 - regression_loss: 1.9678 - classification_loss: 0.3844 55/500 [==>...........................] - ETA: 2:24 - loss: 2.3408 - regression_loss: 1.9593 - classification_loss: 0.3815 56/500 [==>...........................] - ETA: 2:23 - loss: 2.3376 - regression_loss: 1.9568 - classification_loss: 0.3808 57/500 [==>...........................] - ETA: 2:23 - loss: 2.3348 - regression_loss: 1.9563 - classification_loss: 0.3784 58/500 [==>...........................] - ETA: 2:22 - loss: 2.3273 - regression_loss: 1.9509 - classification_loss: 0.3764 59/500 [==>...........................] - ETA: 2:22 - loss: 2.3226 - regression_loss: 1.9480 - classification_loss: 0.3746 60/500 [==>...........................] - ETA: 2:22 - loss: 2.3198 - regression_loss: 1.9462 - classification_loss: 0.3736 61/500 [==>...........................] - ETA: 2:21 - loss: 2.3219 - regression_loss: 1.9467 - classification_loss: 0.3752 62/500 [==>...........................] - ETA: 2:21 - loss: 2.3175 - regression_loss: 1.9442 - classification_loss: 0.3733 63/500 [==>...........................] - ETA: 2:21 - loss: 2.3233 - regression_loss: 1.9484 - classification_loss: 0.3749 64/500 [==>...........................] - ETA: 2:20 - loss: 2.3289 - regression_loss: 1.9529 - classification_loss: 0.3760 65/500 [==>...........................] - ETA: 2:20 - loss: 2.3234 - regression_loss: 1.9492 - classification_loss: 0.3743 66/500 [==>...........................] - ETA: 2:20 - loss: 2.3111 - regression_loss: 1.9368 - classification_loss: 0.3744 67/500 [===>..........................] - ETA: 2:20 - loss: 2.3140 - regression_loss: 1.9392 - classification_loss: 0.3748 68/500 [===>..........................] - ETA: 2:20 - loss: 2.3132 - regression_loss: 1.9383 - classification_loss: 0.3750 69/500 [===>..........................] - ETA: 2:19 - loss: 2.3038 - regression_loss: 1.9306 - classification_loss: 0.3732 70/500 [===>..........................] - ETA: 2:19 - loss: 2.2975 - regression_loss: 1.9261 - classification_loss: 0.3715 71/500 [===>..........................] - ETA: 2:19 - loss: 2.2948 - regression_loss: 1.9238 - classification_loss: 0.3710 72/500 [===>..........................] - ETA: 2:18 - loss: 2.2914 - regression_loss: 1.9211 - classification_loss: 0.3704 73/500 [===>..........................] - ETA: 2:18 - loss: 2.2865 - regression_loss: 1.9172 - classification_loss: 0.3693 74/500 [===>..........................] - ETA: 2:17 - loss: 2.2735 - regression_loss: 1.9072 - classification_loss: 0.3663 75/500 [===>..........................] - ETA: 2:17 - loss: 2.2682 - regression_loss: 1.9036 - classification_loss: 0.3646 76/500 [===>..........................] - ETA: 2:17 - loss: 2.2625 - regression_loss: 1.8997 - classification_loss: 0.3628 77/500 [===>..........................] - ETA: 2:16 - loss: 2.2598 - regression_loss: 1.8973 - classification_loss: 0.3626 78/500 [===>..........................] - ETA: 2:16 - loss: 2.2630 - regression_loss: 1.9006 - classification_loss: 0.3625 79/500 [===>..........................] - ETA: 2:16 - loss: 2.2607 - regression_loss: 1.8991 - classification_loss: 0.3616 80/500 [===>..........................] - ETA: 2:15 - loss: 2.2641 - regression_loss: 1.9019 - classification_loss: 0.3622 81/500 [===>..........................] - ETA: 2:15 - loss: 2.2801 - regression_loss: 1.9108 - classification_loss: 0.3693 82/500 [===>..........................] - ETA: 2:15 - loss: 2.2758 - regression_loss: 1.9083 - classification_loss: 0.3675 83/500 [===>..........................] - ETA: 2:15 - loss: 2.2823 - regression_loss: 1.9129 - classification_loss: 0.3694 84/500 [====>.........................] - ETA: 2:14 - loss: 2.2852 - regression_loss: 1.9156 - classification_loss: 0.3695 85/500 [====>.........................] - ETA: 2:14 - loss: 2.2758 - regression_loss: 1.9075 - classification_loss: 0.3682 86/500 [====>.........................] - ETA: 2:14 - loss: 2.2749 - regression_loss: 1.9078 - classification_loss: 0.3671 87/500 [====>.........................] - ETA: 2:13 - loss: 2.2655 - regression_loss: 1.8996 - classification_loss: 0.3659 88/500 [====>.........................] - ETA: 2:13 - loss: 2.2550 - regression_loss: 1.8913 - classification_loss: 0.3637 89/500 [====>.........................] - ETA: 2:13 - loss: 2.2574 - regression_loss: 1.8939 - classification_loss: 0.3635 90/500 [====>.........................] - ETA: 2:13 - loss: 2.2606 - regression_loss: 1.8962 - classification_loss: 0.3644 91/500 [====>.........................] - ETA: 2:12 - loss: 2.2652 - regression_loss: 1.8992 - classification_loss: 0.3659 92/500 [====>.........................] - ETA: 2:12 - loss: 2.2753 - regression_loss: 1.9074 - classification_loss: 0.3680 93/500 [====>.........................] - ETA: 2:11 - loss: 2.2767 - regression_loss: 1.9096 - classification_loss: 0.3671 94/500 [====>.........................] - ETA: 2:11 - loss: 2.2785 - regression_loss: 1.9119 - classification_loss: 0.3666 95/500 [====>.........................] - ETA: 2:11 - loss: 2.2801 - regression_loss: 1.9136 - classification_loss: 0.3665 96/500 [====>.........................] - ETA: 2:10 - loss: 2.3029 - regression_loss: 1.9294 - classification_loss: 0.3734 97/500 [====>.........................] - ETA: 2:10 - loss: 2.3067 - regression_loss: 1.9311 - classification_loss: 0.3756 98/500 [====>.........................] - ETA: 2:10 - loss: 2.3045 - regression_loss: 1.9289 - classification_loss: 0.3756 99/500 [====>.........................] - ETA: 2:09 - loss: 2.3053 - regression_loss: 1.9301 - classification_loss: 0.3751 100/500 [=====>........................] - ETA: 2:09 - loss: 2.3025 - regression_loss: 1.9285 - classification_loss: 0.3740 101/500 [=====>........................] - ETA: 2:09 - loss: 2.3044 - regression_loss: 1.9313 - classification_loss: 0.3731 102/500 [=====>........................] - ETA: 2:08 - loss: 2.3074 - regression_loss: 1.9339 - classification_loss: 0.3736 103/500 [=====>........................] - ETA: 2:08 - loss: 2.3078 - regression_loss: 1.9349 - classification_loss: 0.3729 104/500 [=====>........................] - ETA: 2:08 - loss: 2.3006 - regression_loss: 1.9293 - classification_loss: 0.3713 105/500 [=====>........................] - ETA: 2:08 - loss: 2.3064 - regression_loss: 1.9355 - classification_loss: 0.3709 106/500 [=====>........................] - ETA: 2:07 - loss: 2.3078 - regression_loss: 1.9366 - classification_loss: 0.3712 107/500 [=====>........................] - ETA: 2:07 - loss: 2.3044 - regression_loss: 1.9338 - classification_loss: 0.3706 108/500 [=====>........................] - ETA: 2:06 - loss: 2.3034 - regression_loss: 1.9325 - classification_loss: 0.3709 109/500 [=====>........................] - ETA: 2:06 - loss: 2.3042 - regression_loss: 1.9333 - classification_loss: 0.3709 110/500 [=====>........................] - ETA: 2:06 - loss: 2.3061 - regression_loss: 1.9337 - classification_loss: 0.3724 111/500 [=====>........................] - ETA: 2:05 - loss: 2.3081 - regression_loss: 1.9349 - classification_loss: 0.3732 112/500 [=====>........................] - ETA: 2:05 - loss: 2.3113 - regression_loss: 1.9382 - classification_loss: 0.3731 113/500 [=====>........................] - ETA: 2:05 - loss: 2.3230 - regression_loss: 1.9421 - classification_loss: 0.3809 114/500 [=====>........................] - ETA: 2:04 - loss: 2.3232 - regression_loss: 1.9435 - classification_loss: 0.3798 115/500 [=====>........................] - ETA: 2:04 - loss: 2.3261 - regression_loss: 1.9461 - classification_loss: 0.3801 116/500 [=====>........................] - ETA: 2:04 - loss: 2.3212 - regression_loss: 1.9426 - classification_loss: 0.3787 117/500 [======>.......................] - ETA: 2:03 - loss: 2.3201 - regression_loss: 1.9423 - classification_loss: 0.3778 118/500 [======>.......................] - ETA: 2:03 - loss: 2.3239 - regression_loss: 1.9441 - classification_loss: 0.3798 119/500 [======>.......................] - ETA: 2:03 - loss: 2.3212 - regression_loss: 1.9423 - classification_loss: 0.3789 120/500 [======>.......................] - ETA: 2:02 - loss: 2.3198 - regression_loss: 1.9417 - classification_loss: 0.3781 121/500 [======>.......................] - ETA: 2:02 - loss: 2.3208 - regression_loss: 1.9429 - classification_loss: 0.3779 122/500 [======>.......................] - ETA: 2:01 - loss: 2.3212 - regression_loss: 1.9426 - classification_loss: 0.3786 123/500 [======>.......................] - ETA: 2:01 - loss: 2.3155 - regression_loss: 1.9384 - classification_loss: 0.3771 124/500 [======>.......................] - ETA: 2:01 - loss: 2.3223 - regression_loss: 1.9424 - classification_loss: 0.3799 125/500 [======>.......................] - ETA: 2:00 - loss: 2.3208 - regression_loss: 1.9417 - classification_loss: 0.3791 126/500 [======>.......................] - ETA: 2:00 - loss: 2.3262 - regression_loss: 1.9462 - classification_loss: 0.3800 127/500 [======>.......................] - ETA: 2:00 - loss: 2.3221 - regression_loss: 1.9432 - classification_loss: 0.3789 128/500 [======>.......................] - ETA: 1:59 - loss: 2.3249 - regression_loss: 1.9448 - classification_loss: 0.3801 129/500 [======>.......................] - ETA: 1:59 - loss: 2.3203 - regression_loss: 1.9417 - classification_loss: 0.3786 130/500 [======>.......................] - ETA: 1:59 - loss: 2.3124 - regression_loss: 1.9354 - classification_loss: 0.3770 131/500 [======>.......................] - ETA: 1:58 - loss: 2.3160 - regression_loss: 1.9384 - classification_loss: 0.3776 132/500 [======>.......................] - ETA: 1:58 - loss: 2.3151 - regression_loss: 1.9380 - classification_loss: 0.3771 133/500 [======>.......................] - ETA: 1:58 - loss: 2.3102 - regression_loss: 1.9342 - classification_loss: 0.3760 134/500 [=======>......................] - ETA: 1:58 - loss: 2.3037 - regression_loss: 1.9290 - classification_loss: 0.3747 135/500 [=======>......................] - ETA: 1:57 - loss: 2.3029 - regression_loss: 1.9287 - classification_loss: 0.3742 136/500 [=======>......................] - ETA: 1:57 - loss: 2.2988 - regression_loss: 1.9255 - classification_loss: 0.3733 137/500 [=======>......................] - ETA: 1:57 - loss: 2.2975 - regression_loss: 1.9245 - classification_loss: 0.3729 138/500 [=======>......................] - ETA: 1:56 - loss: 2.3004 - regression_loss: 1.9277 - classification_loss: 0.3727 139/500 [=======>......................] - ETA: 1:56 - loss: 2.2987 - regression_loss: 1.9265 - classification_loss: 0.3722 140/500 [=======>......................] - ETA: 1:56 - loss: 2.3001 - regression_loss: 1.9276 - classification_loss: 0.3725 141/500 [=======>......................] - ETA: 1:55 - loss: 2.2971 - regression_loss: 1.9246 - classification_loss: 0.3725 142/500 [=======>......................] - ETA: 1:55 - loss: 2.2994 - regression_loss: 1.9265 - classification_loss: 0.3729 143/500 [=======>......................] - ETA: 1:55 - loss: 2.2976 - regression_loss: 1.9254 - classification_loss: 0.3722 144/500 [=======>......................] - ETA: 1:54 - loss: 2.2976 - regression_loss: 1.9251 - classification_loss: 0.3724 145/500 [=======>......................] - ETA: 1:54 - loss: 2.2997 - regression_loss: 1.9270 - classification_loss: 0.3728 146/500 [=======>......................] - ETA: 1:54 - loss: 2.3030 - regression_loss: 1.9292 - classification_loss: 0.3738 147/500 [=======>......................] - ETA: 1:53 - loss: 2.3022 - regression_loss: 1.9284 - classification_loss: 0.3738 148/500 [=======>......................] - ETA: 1:53 - loss: 2.2995 - regression_loss: 1.9261 - classification_loss: 0.3733 149/500 [=======>......................] - ETA: 1:53 - loss: 2.2998 - regression_loss: 1.9260 - classification_loss: 0.3738 150/500 [========>.....................] - ETA: 1:53 - loss: 2.3008 - regression_loss: 1.9262 - classification_loss: 0.3746 151/500 [========>.....................] - ETA: 1:52 - loss: 2.3012 - regression_loss: 1.9271 - classification_loss: 0.3741 152/500 [========>.....................] - ETA: 1:52 - loss: 2.3013 - regression_loss: 1.9272 - classification_loss: 0.3741 153/500 [========>.....................] - ETA: 1:52 - loss: 2.2977 - regression_loss: 1.9246 - classification_loss: 0.3731 154/500 [========>.....................] - ETA: 1:51 - loss: 2.2960 - regression_loss: 1.9235 - classification_loss: 0.3724 155/500 [========>.....................] - ETA: 1:51 - loss: 2.2960 - regression_loss: 1.9241 - classification_loss: 0.3719 156/500 [========>.....................] - ETA: 1:51 - loss: 2.2922 - regression_loss: 1.9212 - classification_loss: 0.3709 157/500 [========>.....................] - ETA: 1:50 - loss: 2.2983 - regression_loss: 1.9259 - classification_loss: 0.3724 158/500 [========>.....................] - ETA: 1:50 - loss: 2.3004 - regression_loss: 1.9272 - classification_loss: 0.3732 159/500 [========>.....................] - ETA: 1:50 - loss: 2.2999 - regression_loss: 1.9273 - classification_loss: 0.3727 160/500 [========>.....................] - ETA: 1:49 - loss: 2.3001 - regression_loss: 1.9274 - classification_loss: 0.3727 161/500 [========>.....................] - ETA: 1:49 - loss: 2.3000 - regression_loss: 1.9269 - classification_loss: 0.3731 162/500 [========>.....................] - ETA: 1:49 - loss: 2.3003 - regression_loss: 1.9276 - classification_loss: 0.3727 163/500 [========>.....................] - ETA: 1:48 - loss: 2.2996 - regression_loss: 1.9275 - classification_loss: 0.3722 164/500 [========>.....................] - ETA: 1:48 - loss: 2.2956 - regression_loss: 1.9243 - classification_loss: 0.3713 165/500 [========>.....................] - ETA: 1:48 - loss: 2.2914 - regression_loss: 1.9210 - classification_loss: 0.3704 166/500 [========>.....................] - ETA: 1:47 - loss: 2.2891 - regression_loss: 1.9192 - classification_loss: 0.3699 167/500 [=========>....................] - ETA: 1:47 - loss: 2.2904 - regression_loss: 1.9203 - classification_loss: 0.3701 168/500 [=========>....................] - ETA: 1:47 - loss: 2.2926 - regression_loss: 1.9218 - classification_loss: 0.3708 169/500 [=========>....................] - ETA: 1:47 - loss: 2.2940 - regression_loss: 1.9224 - classification_loss: 0.3716 170/500 [=========>....................] - ETA: 1:46 - loss: 2.2952 - regression_loss: 1.9230 - classification_loss: 0.3722 171/500 [=========>....................] - ETA: 1:46 - loss: 2.2956 - regression_loss: 1.9233 - classification_loss: 0.3723 172/500 [=========>....................] - ETA: 1:46 - loss: 2.2925 - regression_loss: 1.9209 - classification_loss: 0.3716 173/500 [=========>....................] - ETA: 1:45 - loss: 2.2920 - regression_loss: 1.9200 - classification_loss: 0.3721 174/500 [=========>....................] - ETA: 1:45 - loss: 2.2927 - regression_loss: 1.9205 - classification_loss: 0.3722 175/500 [=========>....................] - ETA: 1:45 - loss: 2.2945 - regression_loss: 1.9218 - classification_loss: 0.3727 176/500 [=========>....................] - ETA: 1:44 - loss: 2.3004 - regression_loss: 1.9273 - classification_loss: 0.3730 177/500 [=========>....................] - ETA: 1:44 - loss: 2.3006 - regression_loss: 1.9278 - classification_loss: 0.3728 178/500 [=========>....................] - ETA: 1:44 - loss: 2.3065 - regression_loss: 1.9328 - classification_loss: 0.3736 179/500 [=========>....................] - ETA: 1:43 - loss: 2.3067 - regression_loss: 1.9333 - classification_loss: 0.3734 180/500 [=========>....................] - ETA: 1:43 - loss: 2.3007 - regression_loss: 1.9285 - classification_loss: 0.3722 181/500 [=========>....................] - ETA: 1:43 - loss: 2.3027 - regression_loss: 1.9309 - classification_loss: 0.3718 182/500 [=========>....................] - ETA: 1:42 - loss: 2.3040 - regression_loss: 1.9323 - classification_loss: 0.3717 183/500 [=========>....................] - ETA: 1:42 - loss: 2.3058 - regression_loss: 1.9338 - classification_loss: 0.3719 184/500 [==========>...................] - ETA: 1:42 - loss: 2.3065 - regression_loss: 1.9344 - classification_loss: 0.3721 185/500 [==========>...................] - ETA: 1:41 - loss: 2.3083 - regression_loss: 1.9358 - classification_loss: 0.3726 186/500 [==========>...................] - ETA: 1:41 - loss: 2.3103 - regression_loss: 1.9374 - classification_loss: 0.3729 187/500 [==========>...................] - ETA: 1:41 - loss: 2.3090 - regression_loss: 1.9367 - classification_loss: 0.3723 188/500 [==========>...................] - ETA: 1:40 - loss: 2.3076 - regression_loss: 1.9354 - classification_loss: 0.3722 189/500 [==========>...................] - ETA: 1:40 - loss: 2.3096 - regression_loss: 1.9370 - classification_loss: 0.3726 190/500 [==========>...................] - ETA: 1:40 - loss: 2.3074 - regression_loss: 1.9356 - classification_loss: 0.3718 191/500 [==========>...................] - ETA: 1:39 - loss: 2.3076 - regression_loss: 1.9355 - classification_loss: 0.3721 192/500 [==========>...................] - ETA: 1:39 - loss: 2.3029 - regression_loss: 1.9314 - classification_loss: 0.3715 193/500 [==========>...................] - ETA: 1:39 - loss: 2.3041 - regression_loss: 1.9323 - classification_loss: 0.3718 194/500 [==========>...................] - ETA: 1:38 - loss: 2.3024 - regression_loss: 1.9311 - classification_loss: 0.3714 195/500 [==========>...................] - ETA: 1:38 - loss: 2.3009 - regression_loss: 1.9297 - classification_loss: 0.3712 196/500 [==========>...................] - ETA: 1:38 - loss: 2.3023 - regression_loss: 1.9310 - classification_loss: 0.3713 197/500 [==========>...................] - ETA: 1:38 - loss: 2.2998 - regression_loss: 1.9291 - classification_loss: 0.3707 198/500 [==========>...................] - ETA: 1:37 - loss: 2.3047 - regression_loss: 1.9331 - classification_loss: 0.3716 199/500 [==========>...................] - ETA: 1:37 - loss: 2.3057 - regression_loss: 1.9338 - classification_loss: 0.3719 200/500 [===========>..................] - ETA: 1:36 - loss: 2.3029 - regression_loss: 1.9316 - classification_loss: 0.3712 201/500 [===========>..................] - ETA: 1:36 - loss: 2.3044 - regression_loss: 1.9332 - classification_loss: 0.3713 202/500 [===========>..................] - ETA: 1:36 - loss: 2.3053 - regression_loss: 1.9340 - classification_loss: 0.3713 203/500 [===========>..................] - ETA: 1:36 - loss: 2.3074 - regression_loss: 1.9358 - classification_loss: 0.3715 204/500 [===========>..................] - ETA: 1:35 - loss: 2.3077 - regression_loss: 1.9366 - classification_loss: 0.3712 205/500 [===========>..................] - ETA: 1:35 - loss: 2.3114 - regression_loss: 1.9389 - classification_loss: 0.3725 206/500 [===========>..................] - ETA: 1:34 - loss: 2.3149 - regression_loss: 1.9416 - classification_loss: 0.3733 207/500 [===========>..................] - ETA: 1:34 - loss: 2.3135 - regression_loss: 1.9406 - classification_loss: 0.3729 208/500 [===========>..................] - ETA: 1:34 - loss: 2.3136 - regression_loss: 1.9408 - classification_loss: 0.3728 209/500 [===========>..................] - ETA: 1:33 - loss: 2.3140 - regression_loss: 1.9416 - classification_loss: 0.3724 210/500 [===========>..................] - ETA: 1:33 - loss: 2.3104 - regression_loss: 1.9388 - classification_loss: 0.3717 211/500 [===========>..................] - ETA: 1:33 - loss: 2.3092 - regression_loss: 1.9376 - classification_loss: 0.3717 212/500 [===========>..................] - ETA: 1:32 - loss: 2.3093 - regression_loss: 1.9372 - classification_loss: 0.3722 213/500 [===========>..................] - ETA: 1:32 - loss: 2.3073 - regression_loss: 1.9356 - classification_loss: 0.3716 214/500 [===========>..................] - ETA: 1:32 - loss: 2.3101 - regression_loss: 1.9376 - classification_loss: 0.3724 215/500 [===========>..................] - ETA: 1:31 - loss: 2.3084 - regression_loss: 1.9365 - classification_loss: 0.3719 216/500 [===========>..................] - ETA: 1:31 - loss: 2.3051 - regression_loss: 1.9336 - classification_loss: 0.3715 217/500 [============>.................] - ETA: 1:31 - loss: 2.3035 - regression_loss: 1.9325 - classification_loss: 0.3710 218/500 [============>.................] - ETA: 1:30 - loss: 2.3027 - regression_loss: 1.9318 - classification_loss: 0.3709 219/500 [============>.................] - ETA: 1:30 - loss: 2.3028 - regression_loss: 1.9314 - classification_loss: 0.3715 220/500 [============>.................] - ETA: 1:30 - loss: 2.3022 - regression_loss: 1.9312 - classification_loss: 0.3711 221/500 [============>.................] - ETA: 1:29 - loss: 2.3009 - regression_loss: 1.9304 - classification_loss: 0.3705 222/500 [============>.................] - ETA: 1:29 - loss: 2.3056 - regression_loss: 1.9333 - classification_loss: 0.3723 223/500 [============>.................] - ETA: 1:29 - loss: 2.3042 - regression_loss: 1.9325 - classification_loss: 0.3718 224/500 [============>.................] - ETA: 1:28 - loss: 2.3022 - regression_loss: 1.9310 - classification_loss: 0.3712 225/500 [============>.................] - ETA: 1:28 - loss: 2.3031 - regression_loss: 1.9322 - classification_loss: 0.3710 226/500 [============>.................] - ETA: 1:28 - loss: 2.3066 - regression_loss: 1.9349 - classification_loss: 0.3717 227/500 [============>.................] - ETA: 1:27 - loss: 2.3063 - regression_loss: 1.9344 - classification_loss: 0.3719 228/500 [============>.................] - ETA: 1:27 - loss: 2.3059 - regression_loss: 1.9344 - classification_loss: 0.3714 229/500 [============>.................] - ETA: 1:27 - loss: 2.3058 - regression_loss: 1.9347 - classification_loss: 0.3711 230/500 [============>.................] - ETA: 1:27 - loss: 2.3037 - regression_loss: 1.9333 - classification_loss: 0.3704 231/500 [============>.................] - ETA: 1:26 - loss: 2.3054 - regression_loss: 1.9343 - classification_loss: 0.3711 232/500 [============>.................] - ETA: 1:26 - loss: 2.3043 - regression_loss: 1.9336 - classification_loss: 0.3707 233/500 [============>.................] - ETA: 1:26 - loss: 2.3071 - regression_loss: 1.9360 - classification_loss: 0.3712 234/500 [=============>................] - ETA: 1:25 - loss: 2.3037 - regression_loss: 1.9334 - classification_loss: 0.3704 235/500 [=============>................] - ETA: 1:25 - loss: 2.3029 - regression_loss: 1.9330 - classification_loss: 0.3700 236/500 [=============>................] - ETA: 1:25 - loss: 2.3034 - regression_loss: 1.9333 - classification_loss: 0.3701 237/500 [=============>................] - ETA: 1:24 - loss: 2.3032 - regression_loss: 1.9334 - classification_loss: 0.3698 238/500 [=============>................] - ETA: 1:24 - loss: 2.3037 - regression_loss: 1.9343 - classification_loss: 0.3694 239/500 [=============>................] - ETA: 1:24 - loss: 2.3033 - regression_loss: 1.9342 - classification_loss: 0.3691 240/500 [=============>................] - ETA: 1:23 - loss: 2.3037 - regression_loss: 1.9343 - classification_loss: 0.3695 241/500 [=============>................] - ETA: 1:23 - loss: 2.3028 - regression_loss: 1.9337 - classification_loss: 0.3691 242/500 [=============>................] - ETA: 1:23 - loss: 2.3012 - regression_loss: 1.9326 - classification_loss: 0.3686 243/500 [=============>................] - ETA: 1:22 - loss: 2.3004 - regression_loss: 1.9322 - classification_loss: 0.3681 244/500 [=============>................] - ETA: 1:22 - loss: 2.2980 - regression_loss: 1.9305 - classification_loss: 0.3675 245/500 [=============>................] - ETA: 1:22 - loss: 2.2967 - regression_loss: 1.9294 - classification_loss: 0.3673 246/500 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[===========================>..] - ETA: 9s - loss: 2.2329 - regression_loss: 1.8750 - classification_loss: 0.3578  471/500 [===========================>..] - ETA: 9s - loss: 2.2336 - regression_loss: 1.8753 - classification_loss: 0.3583 472/500 [===========================>..] - ETA: 9s - loss: 2.2339 - regression_loss: 1.8754 - classification_loss: 0.3585 473/500 [===========================>..] - ETA: 8s - loss: 2.2340 - regression_loss: 1.8754 - classification_loss: 0.3586 474/500 [===========================>..] - ETA: 8s - loss: 2.2337 - regression_loss: 1.8752 - classification_loss: 0.3585 475/500 [===========================>..] - ETA: 8s - loss: 2.2339 - regression_loss: 1.8754 - classification_loss: 0.3585 476/500 [===========================>..] - ETA: 7s - loss: 2.2345 - regression_loss: 1.8757 - classification_loss: 0.3588 477/500 [===========================>..] - ETA: 7s - loss: 2.2328 - regression_loss: 1.8742 - classification_loss: 0.3586 478/500 [===========================>..] - ETA: 7s - loss: 2.2322 - regression_loss: 1.8737 - classification_loss: 0.3585 479/500 [===========================>..] - ETA: 6s - loss: 2.2315 - regression_loss: 1.8733 - classification_loss: 0.3582 480/500 [===========================>..] - ETA: 6s - loss: 2.2314 - regression_loss: 1.8733 - classification_loss: 0.3582 481/500 [===========================>..] - ETA: 6s - loss: 2.2335 - regression_loss: 1.8750 - classification_loss: 0.3585 482/500 [===========================>..] - ETA: 5s - loss: 2.2355 - regression_loss: 1.8766 - classification_loss: 0.3589 483/500 [===========================>..] - ETA: 5s - loss: 2.2343 - regression_loss: 1.8757 - classification_loss: 0.3587 484/500 [============================>.] - ETA: 5s - loss: 2.2341 - regression_loss: 1.8757 - classification_loss: 0.3584 485/500 [============================>.] - ETA: 4s - loss: 2.2327 - regression_loss: 1.8745 - classification_loss: 0.3581 486/500 [============================>.] - ETA: 4s - loss: 2.2315 - regression_loss: 1.8737 - classification_loss: 0.3578 487/500 [============================>.] - ETA: 4s - loss: 2.2305 - regression_loss: 1.8729 - classification_loss: 0.3575 488/500 [============================>.] - ETA: 3s - loss: 2.2302 - regression_loss: 1.8727 - classification_loss: 0.3575 489/500 [============================>.] - ETA: 3s - loss: 2.2284 - regression_loss: 1.8710 - classification_loss: 0.3574 490/500 [============================>.] - ETA: 3s - loss: 2.2295 - regression_loss: 1.8721 - classification_loss: 0.3574 491/500 [============================>.] - ETA: 2s - loss: 2.2288 - regression_loss: 1.8717 - classification_loss: 0.3572 492/500 [============================>.] - ETA: 2s - loss: 2.2293 - regression_loss: 1.8718 - classification_loss: 0.3576 493/500 [============================>.] - ETA: 2s - loss: 2.2292 - regression_loss: 1.8715 - classification_loss: 0.3577 494/500 [============================>.] - ETA: 1s - loss: 2.2277 - regression_loss: 1.8703 - classification_loss: 0.3574 495/500 [============================>.] - ETA: 1s - loss: 2.2273 - regression_loss: 1.8701 - classification_loss: 0.3572 496/500 [============================>.] - ETA: 1s - loss: 2.2268 - regression_loss: 1.8696 - classification_loss: 0.3572 497/500 [============================>.] - ETA: 0s - loss: 2.2264 - regression_loss: 1.8693 - classification_loss: 0.3571 498/500 [============================>.] - ETA: 0s - loss: 2.2252 - regression_loss: 1.8685 - classification_loss: 0.3568 499/500 [============================>.] - ETA: 0s - loss: 2.2260 - regression_loss: 1.8688 - classification_loss: 0.3573 500/500 [==============================] - 162s 323ms/step - loss: 2.2272 - regression_loss: 1.8694 - classification_loss: 0.3577 326 instances of class plum with average precision: 0.6458 mAP: 0.6458 Epoch 00003: saving model to ./training/snapshots/resnet101_pascal_03.h5 Epoch 4/150 1/500 [..............................] - ETA: 2:33 - loss: 2.2071 - regression_loss: 1.9514 - classification_loss: 0.2557 2/500 [..............................] - ETA: 2:31 - loss: 2.2066 - regression_loss: 1.8937 - classification_loss: 0.3129 3/500 [..............................] - ETA: 2:31 - loss: 2.2120 - regression_loss: 1.8654 - classification_loss: 0.3466 4/500 [..............................] - ETA: 2:33 - loss: 2.2381 - regression_loss: 1.8853 - classification_loss: 0.3527 5/500 [..............................] - ETA: 2:37 - loss: 2.3937 - regression_loss: 1.9774 - classification_loss: 0.4164 6/500 [..............................] - ETA: 2:37 - loss: 2.5118 - regression_loss: 2.0881 - classification_loss: 0.4237 7/500 [..............................] - ETA: 2:36 - loss: 2.3733 - regression_loss: 1.9822 - classification_loss: 0.3911 8/500 [..............................] - ETA: 2:38 - loss: 2.2620 - regression_loss: 1.8918 - classification_loss: 0.3702 9/500 [..............................] - ETA: 2:38 - loss: 2.2423 - regression_loss: 1.8743 - classification_loss: 0.3680 10/500 [..............................] - ETA: 2:37 - loss: 2.2274 - regression_loss: 1.8652 - classification_loss: 0.3621 11/500 [..............................] - ETA: 2:36 - loss: 2.2700 - regression_loss: 1.8906 - classification_loss: 0.3794 12/500 [..............................] - ETA: 2:35 - loss: 2.3179 - regression_loss: 1.9140 - classification_loss: 0.4039 13/500 [..............................] - ETA: 2:36 - loss: 2.3434 - regression_loss: 1.9233 - classification_loss: 0.4201 14/500 [..............................] - ETA: 2:36 - loss: 2.3527 - regression_loss: 1.9242 - classification_loss: 0.4285 15/500 [..............................] - ETA: 2:35 - loss: 2.3509 - regression_loss: 1.9221 - classification_loss: 0.4288 16/500 [..............................] - ETA: 2:35 - loss: 2.3140 - regression_loss: 1.8903 - classification_loss: 0.4237 17/500 [>.............................] - ETA: 2:34 - loss: 2.3323 - regression_loss: 1.9156 - classification_loss: 0.4167 18/500 [>.............................] - ETA: 2:35 - loss: 2.3273 - regression_loss: 1.9179 - classification_loss: 0.4093 19/500 [>.............................] - ETA: 2:34 - loss: 2.3005 - regression_loss: 1.8981 - classification_loss: 0.4024 20/500 [>.............................] - ETA: 2:33 - loss: 2.3103 - regression_loss: 1.9116 - classification_loss: 0.3987 21/500 [>.............................] - ETA: 2:33 - loss: 2.3204 - regression_loss: 1.9218 - classification_loss: 0.3986 22/500 [>.............................] - ETA: 2:32 - loss: 2.3035 - regression_loss: 1.9122 - classification_loss: 0.3913 23/500 [>.............................] - ETA: 2:32 - loss: 2.3337 - regression_loss: 1.9381 - classification_loss: 0.3956 24/500 [>.............................] - ETA: 2:32 - loss: 2.3431 - regression_loss: 1.9451 - classification_loss: 0.3980 25/500 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[>.............................] - ETA: 2:30 - loss: 2.3351 - regression_loss: 1.9441 - classification_loss: 0.3910 34/500 [=>............................] - ETA: 2:30 - loss: 2.3214 - regression_loss: 1.9345 - classification_loss: 0.3869 35/500 [=>............................] - ETA: 2:30 - loss: 2.2961 - regression_loss: 1.9133 - classification_loss: 0.3828 36/500 [=>............................] - ETA: 2:29 - loss: 2.3059 - regression_loss: 1.9212 - classification_loss: 0.3847 37/500 [=>............................] - ETA: 2:29 - loss: 2.3081 - regression_loss: 1.9234 - classification_loss: 0.3846 38/500 [=>............................] - ETA: 2:28 - loss: 2.2952 - regression_loss: 1.9122 - classification_loss: 0.3830 39/500 [=>............................] - ETA: 2:28 - loss: 2.3073 - regression_loss: 1.9186 - classification_loss: 0.3887 40/500 [=>............................] - ETA: 2:28 - loss: 2.2790 - regression_loss: 1.8928 - classification_loss: 0.3863 41/500 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[==>...........................] - ETA: 2:23 - loss: 2.2346 - regression_loss: 1.8683 - classification_loss: 0.3663 58/500 [==>...........................] - ETA: 2:22 - loss: 2.2129 - regression_loss: 1.8466 - classification_loss: 0.3664 59/500 [==>...........................] - ETA: 2:22 - loss: 2.1990 - regression_loss: 1.8338 - classification_loss: 0.3652 60/500 [==>...........................] - ETA: 2:21 - loss: 2.2035 - regression_loss: 1.8379 - classification_loss: 0.3657 61/500 [==>...........................] - ETA: 2:21 - loss: 2.1946 - regression_loss: 1.8322 - classification_loss: 0.3624 62/500 [==>...........................] - ETA: 2:21 - loss: 2.1957 - regression_loss: 1.8345 - classification_loss: 0.3612 63/500 [==>...........................] - ETA: 2:21 - loss: 2.1893 - regression_loss: 1.8301 - classification_loss: 0.3592 64/500 [==>...........................] - ETA: 2:20 - loss: 2.1894 - regression_loss: 1.8307 - classification_loss: 0.3586 65/500 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[===>..........................] - ETA: 2:17 - loss: 2.1778 - regression_loss: 1.8226 - classification_loss: 0.3551 74/500 [===>..........................] - ETA: 2:17 - loss: 2.1707 - regression_loss: 1.8173 - classification_loss: 0.3534 75/500 [===>..........................] - ETA: 2:17 - loss: 2.1694 - regression_loss: 1.8176 - classification_loss: 0.3518 76/500 [===>..........................] - ETA: 2:17 - loss: 2.1681 - regression_loss: 1.8174 - classification_loss: 0.3506 77/500 [===>..........................] - ETA: 2:16 - loss: 2.1669 - regression_loss: 1.8168 - classification_loss: 0.3501 78/500 [===>..........................] - ETA: 2:16 - loss: 2.1671 - regression_loss: 1.8168 - classification_loss: 0.3503 79/500 [===>..........................] - ETA: 2:16 - loss: 2.1649 - regression_loss: 1.8154 - classification_loss: 0.3495 80/500 [===>..........................] - ETA: 2:15 - loss: 2.1613 - regression_loss: 1.8127 - classification_loss: 0.3486 81/500 [===>..........................] - ETA: 2:15 - loss: 2.1697 - regression_loss: 1.8201 - classification_loss: 0.3496 82/500 [===>..........................] - ETA: 2:15 - loss: 2.1662 - regression_loss: 1.8182 - classification_loss: 0.3481 83/500 [===>..........................] - ETA: 2:14 - loss: 2.1703 - regression_loss: 1.8210 - classification_loss: 0.3493 84/500 [====>.........................] - ETA: 2:14 - loss: 2.1739 - regression_loss: 1.8243 - classification_loss: 0.3496 85/500 [====>.........................] - ETA: 2:14 - loss: 2.1784 - regression_loss: 1.8271 - classification_loss: 0.3512 86/500 [====>.........................] - ETA: 2:13 - loss: 2.1762 - regression_loss: 1.8259 - classification_loss: 0.3504 87/500 [====>.........................] - ETA: 2:13 - loss: 2.1745 - regression_loss: 1.8254 - classification_loss: 0.3491 88/500 [====>.........................] - ETA: 2:13 - loss: 2.1739 - regression_loss: 1.8253 - classification_loss: 0.3486 89/500 [====>.........................] - ETA: 2:13 - loss: 2.1758 - regression_loss: 1.8271 - classification_loss: 0.3487 90/500 [====>.........................] - ETA: 2:12 - loss: 2.1848 - regression_loss: 1.8341 - classification_loss: 0.3507 91/500 [====>.........................] - ETA: 2:12 - loss: 2.1785 - regression_loss: 1.8287 - classification_loss: 0.3498 92/500 [====>.........................] - ETA: 2:12 - loss: 2.1678 - regression_loss: 1.8199 - classification_loss: 0.3479 93/500 [====>.........................] - ETA: 2:11 - loss: 2.1682 - regression_loss: 1.8203 - classification_loss: 0.3479 94/500 [====>.........................] - ETA: 2:11 - loss: 2.1686 - regression_loss: 1.8212 - classification_loss: 0.3475 95/500 [====>.........................] - ETA: 2:11 - loss: 2.1766 - regression_loss: 1.8291 - classification_loss: 0.3475 96/500 [====>.........................] - ETA: 2:10 - loss: 2.1746 - regression_loss: 1.8278 - classification_loss: 0.3467 97/500 [====>.........................] - ETA: 2:10 - loss: 2.1715 - regression_loss: 1.8256 - classification_loss: 0.3460 98/500 [====>.........................] - ETA: 2:10 - loss: 2.1706 - regression_loss: 1.8247 - classification_loss: 0.3459 99/500 [====>.........................] - ETA: 2:10 - loss: 2.1766 - regression_loss: 1.8280 - classification_loss: 0.3486 100/500 [=====>........................] - ETA: 2:09 - loss: 2.1750 - regression_loss: 1.8273 - classification_loss: 0.3477 101/500 [=====>........................] - ETA: 2:09 - loss: 2.1731 - regression_loss: 1.8264 - classification_loss: 0.3467 102/500 [=====>........................] - ETA: 2:09 - loss: 2.1707 - regression_loss: 1.8245 - classification_loss: 0.3461 103/500 [=====>........................] - ETA: 2:08 - loss: 2.1701 - regression_loss: 1.8249 - classification_loss: 0.3452 104/500 [=====>........................] - ETA: 2:08 - loss: 2.1726 - regression_loss: 1.8272 - classification_loss: 0.3453 105/500 [=====>........................] - ETA: 2:07 - loss: 2.1781 - regression_loss: 1.8312 - classification_loss: 0.3469 106/500 [=====>........................] - ETA: 2:07 - loss: 2.1787 - regression_loss: 1.8321 - classification_loss: 0.3466 107/500 [=====>........................] - ETA: 2:07 - loss: 2.1784 - regression_loss: 1.8325 - classification_loss: 0.3459 108/500 [=====>........................] - ETA: 2:07 - loss: 2.1722 - regression_loss: 1.8277 - classification_loss: 0.3445 109/500 [=====>........................] - ETA: 2:06 - loss: 2.1772 - regression_loss: 1.8293 - classification_loss: 0.3479 110/500 [=====>........................] - ETA: 2:06 - loss: 2.1722 - regression_loss: 1.8256 - classification_loss: 0.3466 111/500 [=====>........................] - ETA: 2:06 - loss: 2.1697 - regression_loss: 1.8235 - classification_loss: 0.3463 112/500 [=====>........................] - ETA: 2:05 - loss: 2.1636 - regression_loss: 1.8188 - classification_loss: 0.3448 113/500 [=====>........................] - ETA: 2:05 - loss: 2.1621 - regression_loss: 1.8178 - classification_loss: 0.3443 114/500 [=====>........................] - ETA: 2:05 - loss: 2.1649 - regression_loss: 1.8206 - classification_loss: 0.3444 115/500 [=====>........................] - ETA: 2:04 - loss: 2.1651 - regression_loss: 1.8210 - classification_loss: 0.3441 116/500 [=====>........................] - ETA: 2:04 - loss: 2.1633 - regression_loss: 1.8197 - classification_loss: 0.3436 117/500 [======>.......................] - ETA: 2:04 - loss: 2.1643 - regression_loss: 1.8199 - classification_loss: 0.3444 118/500 [======>.......................] - ETA: 2:03 - loss: 2.1676 - regression_loss: 1.8216 - classification_loss: 0.3460 119/500 [======>.......................] - ETA: 2:03 - loss: 2.1657 - regression_loss: 1.8201 - classification_loss: 0.3456 120/500 [======>.......................] - ETA: 2:03 - loss: 2.1620 - regression_loss: 1.8175 - classification_loss: 0.3446 121/500 [======>.......................] - ETA: 2:02 - loss: 2.1587 - regression_loss: 1.8149 - classification_loss: 0.3437 122/500 [======>.......................] - ETA: 2:02 - loss: 2.1575 - regression_loss: 1.8141 - classification_loss: 0.3434 123/500 [======>.......................] - ETA: 2:02 - loss: 2.1602 - regression_loss: 1.8156 - classification_loss: 0.3446 124/500 [======>.......................] - ETA: 2:01 - loss: 2.1590 - regression_loss: 1.8148 - classification_loss: 0.3441 125/500 [======>.......................] - ETA: 2:01 - loss: 2.1625 - regression_loss: 1.8159 - classification_loss: 0.3466 126/500 [======>.......................] - ETA: 2:01 - loss: 2.1659 - regression_loss: 1.8186 - classification_loss: 0.3474 127/500 [======>.......................] - ETA: 2:00 - loss: 2.1622 - regression_loss: 1.8160 - classification_loss: 0.3462 128/500 [======>.......................] - ETA: 2:00 - loss: 2.1648 - regression_loss: 1.8178 - classification_loss: 0.3470 129/500 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[=========>....................] - ETA: 1:44 - loss: 2.1207 - regression_loss: 1.7878 - classification_loss: 0.3329 178/500 [=========>....................] - ETA: 1:44 - loss: 2.1202 - regression_loss: 1.7876 - classification_loss: 0.3325 179/500 [=========>....................] - ETA: 1:43 - loss: 2.1191 - regression_loss: 1.7867 - classification_loss: 0.3324 180/500 [=========>....................] - ETA: 1:43 - loss: 2.1207 - regression_loss: 1.7884 - classification_loss: 0.3322 181/500 [=========>....................] - ETA: 1:43 - loss: 2.1244 - regression_loss: 1.7911 - classification_loss: 0.3333 182/500 [=========>....................] - ETA: 1:42 - loss: 2.1264 - regression_loss: 1.7927 - classification_loss: 0.3337 183/500 [=========>....................] - ETA: 1:42 - loss: 2.1277 - regression_loss: 1.7937 - classification_loss: 0.3341 184/500 [==========>...................] - ETA: 1:42 - loss: 2.1273 - regression_loss: 1.7932 - classification_loss: 0.3341 185/500 [==========>...................] - ETA: 1:41 - loss: 2.1233 - regression_loss: 1.7900 - classification_loss: 0.3333 186/500 [==========>...................] - ETA: 1:41 - loss: 2.1253 - regression_loss: 1.7917 - classification_loss: 0.3336 187/500 [==========>...................] - ETA: 1:41 - loss: 2.1270 - regression_loss: 1.7932 - classification_loss: 0.3338 188/500 [==========>...................] - ETA: 1:40 - loss: 2.1295 - regression_loss: 1.7945 - classification_loss: 0.3350 189/500 [==========>...................] - ETA: 1:40 - loss: 2.1278 - regression_loss: 1.7931 - classification_loss: 0.3346 190/500 [==========>...................] - ETA: 1:40 - loss: 2.1264 - regression_loss: 1.7924 - classification_loss: 0.3340 191/500 [==========>...................] - ETA: 1:39 - loss: 2.1228 - regression_loss: 1.7890 - classification_loss: 0.3339 192/500 [==========>...................] - ETA: 1:39 - loss: 2.1215 - regression_loss: 1.7879 - classification_loss: 0.3336 193/500 [==========>...................] - ETA: 1:39 - loss: 2.1209 - regression_loss: 1.7872 - classification_loss: 0.3336 194/500 [==========>...................] - ETA: 1:38 - loss: 2.1205 - regression_loss: 1.7871 - classification_loss: 0.3335 195/500 [==========>...................] - ETA: 1:38 - loss: 2.1207 - regression_loss: 1.7873 - classification_loss: 0.3334 196/500 [==========>...................] - ETA: 1:38 - loss: 2.1200 - regression_loss: 1.7866 - classification_loss: 0.3334 197/500 [==========>...................] - ETA: 1:37 - loss: 2.1213 - regression_loss: 1.7873 - classification_loss: 0.3341 198/500 [==========>...................] - ETA: 1:37 - loss: 2.1216 - regression_loss: 1.7874 - classification_loss: 0.3342 199/500 [==========>...................] - ETA: 1:37 - loss: 2.1209 - regression_loss: 1.7872 - classification_loss: 0.3337 200/500 [===========>..................] - ETA: 1:36 - loss: 2.1187 - regression_loss: 1.7856 - classification_loss: 0.3331 201/500 [===========>..................] - ETA: 1:36 - loss: 2.1213 - regression_loss: 1.7870 - classification_loss: 0.3343 202/500 [===========>..................] - ETA: 1:36 - loss: 2.1191 - regression_loss: 1.7851 - classification_loss: 0.3340 203/500 [===========>..................] - ETA: 1:35 - loss: 2.1205 - regression_loss: 1.7863 - classification_loss: 0.3342 204/500 [===========>..................] - ETA: 1:35 - loss: 2.1159 - regression_loss: 1.7819 - classification_loss: 0.3340 205/500 [===========>..................] - ETA: 1:35 - loss: 2.1168 - regression_loss: 1.7833 - classification_loss: 0.3335 206/500 [===========>..................] - ETA: 1:34 - loss: 2.1131 - regression_loss: 1.7805 - classification_loss: 0.3326 207/500 [===========>..................] - ETA: 1:34 - loss: 2.1133 - regression_loss: 1.7803 - classification_loss: 0.3330 208/500 [===========>..................] - ETA: 1:34 - loss: 2.1148 - regression_loss: 1.7814 - classification_loss: 0.3334 209/500 [===========>..................] - ETA: 1:34 - loss: 2.1167 - regression_loss: 1.7828 - classification_loss: 0.3339 210/500 [===========>..................] - ETA: 1:33 - loss: 2.1159 - regression_loss: 1.7823 - classification_loss: 0.3336 211/500 [===========>..................] - ETA: 1:33 - loss: 2.1233 - regression_loss: 1.7883 - classification_loss: 0.3351 212/500 [===========>..................] - ETA: 1:33 - loss: 2.1193 - regression_loss: 1.7849 - classification_loss: 0.3344 213/500 [===========>..................] - ETA: 1:32 - loss: 2.1166 - regression_loss: 1.7830 - classification_loss: 0.3337 214/500 [===========>..................] - ETA: 1:32 - loss: 2.1184 - regression_loss: 1.7846 - classification_loss: 0.3339 215/500 [===========>..................] - ETA: 1:32 - loss: 2.1129 - regression_loss: 1.7792 - classification_loss: 0.3337 216/500 [===========>..................] - ETA: 1:31 - loss: 2.1153 - regression_loss: 1.7809 - classification_loss: 0.3344 217/500 [============>.................] - ETA: 1:31 - loss: 2.1159 - regression_loss: 1.7815 - classification_loss: 0.3344 218/500 [============>.................] - ETA: 1:31 - loss: 2.1185 - regression_loss: 1.7838 - classification_loss: 0.3347 219/500 [============>.................] - ETA: 1:30 - loss: 2.1194 - regression_loss: 1.7848 - classification_loss: 0.3346 220/500 [============>.................] - ETA: 1:30 - loss: 2.1169 - regression_loss: 1.7828 - classification_loss: 0.3341 221/500 [============>.................] - ETA: 1:30 - loss: 2.1149 - regression_loss: 1.7812 - classification_loss: 0.3337 222/500 [============>.................] - ETA: 1:29 - loss: 2.1115 - regression_loss: 1.7786 - classification_loss: 0.3329 223/500 [============>.................] - ETA: 1:29 - loss: 2.1108 - regression_loss: 1.7783 - classification_loss: 0.3325 224/500 [============>.................] - ETA: 1:29 - loss: 2.1120 - regression_loss: 1.7792 - classification_loss: 0.3328 225/500 [============>.................] - ETA: 1:28 - loss: 2.1115 - regression_loss: 1.7790 - classification_loss: 0.3326 226/500 [============>.................] - ETA: 1:28 - loss: 2.1094 - regression_loss: 1.7774 - classification_loss: 0.3320 227/500 [============>.................] - ETA: 1:28 - loss: 2.1046 - regression_loss: 1.7734 - classification_loss: 0.3312 228/500 [============>.................] - ETA: 1:27 - loss: 2.0996 - regression_loss: 1.7692 - classification_loss: 0.3304 229/500 [============>.................] - ETA: 1:27 - loss: 2.0972 - regression_loss: 1.7675 - classification_loss: 0.3297 230/500 [============>.................] - ETA: 1:27 - loss: 2.1020 - regression_loss: 1.7716 - classification_loss: 0.3304 231/500 [============>.................] - ETA: 1:27 - loss: 2.0989 - regression_loss: 1.7690 - classification_loss: 0.3299 232/500 [============>.................] - ETA: 1:26 - loss: 2.0962 - regression_loss: 1.7670 - classification_loss: 0.3293 233/500 [============>.................] - ETA: 1:26 - loss: 2.0915 - regression_loss: 1.7630 - classification_loss: 0.3284 234/500 [=============>................] - ETA: 1:26 - loss: 2.0916 - regression_loss: 1.7634 - classification_loss: 0.3281 235/500 [=============>................] - ETA: 1:25 - loss: 2.0956 - regression_loss: 1.7670 - classification_loss: 0.3287 236/500 [=============>................] - ETA: 1:25 - loss: 2.0965 - regression_loss: 1.7676 - classification_loss: 0.3289 237/500 [=============>................] - ETA: 1:25 - loss: 2.0943 - regression_loss: 1.7659 - classification_loss: 0.3284 238/500 [=============>................] - ETA: 1:24 - loss: 2.0956 - regression_loss: 1.7669 - classification_loss: 0.3287 239/500 [=============>................] - ETA: 1:24 - loss: 2.0928 - regression_loss: 1.7647 - classification_loss: 0.3281 240/500 [=============>................] - ETA: 1:24 - loss: 2.0953 - regression_loss: 1.7655 - classification_loss: 0.3298 241/500 [=============>................] - ETA: 1:23 - loss: 2.0941 - regression_loss: 1.7645 - classification_loss: 0.3296 242/500 [=============>................] - ETA: 1:23 - loss: 2.0941 - regression_loss: 1.7646 - classification_loss: 0.3296 243/500 [=============>................] - ETA: 1:23 - loss: 2.0942 - regression_loss: 1.7648 - classification_loss: 0.3294 244/500 [=============>................] - ETA: 1:22 - loss: 2.0943 - regression_loss: 1.7653 - classification_loss: 0.3290 245/500 [=============>................] - ETA: 1:22 - loss: 2.0970 - regression_loss: 1.7669 - classification_loss: 0.3301 246/500 [=============>................] - ETA: 1:22 - loss: 2.0957 - regression_loss: 1.7660 - classification_loss: 0.3297 247/500 [=============>................] - ETA: 1:21 - loss: 2.0968 - regression_loss: 1.7669 - classification_loss: 0.3300 248/500 [=============>................] - ETA: 1:21 - loss: 2.0925 - regression_loss: 1.7629 - classification_loss: 0.3296 249/500 [=============>................] - ETA: 1:21 - loss: 2.0907 - regression_loss: 1.7619 - classification_loss: 0.3289 250/500 [==============>...............] - ETA: 1:20 - loss: 2.0941 - regression_loss: 1.7637 - classification_loss: 0.3304 251/500 [==============>...............] - ETA: 1:20 - loss: 2.0943 - regression_loss: 1.7638 - classification_loss: 0.3305 252/500 [==============>...............] - ETA: 1:20 - loss: 2.0930 - regression_loss: 1.7627 - classification_loss: 0.3303 253/500 [==============>...............] - ETA: 1:20 - loss: 2.0909 - regression_loss: 1.7606 - classification_loss: 0.3303 254/500 [==============>...............] - ETA: 1:19 - loss: 2.0907 - regression_loss: 1.7604 - classification_loss: 0.3302 255/500 [==============>...............] - ETA: 1:19 - loss: 2.0957 - regression_loss: 1.7647 - classification_loss: 0.3310 256/500 [==============>...............] - ETA: 1:19 - loss: 2.0976 - regression_loss: 1.7659 - classification_loss: 0.3316 257/500 [==============>...............] - ETA: 1:18 - loss: 2.0949 - regression_loss: 1.7639 - classification_loss: 0.3310 258/500 [==============>...............] - ETA: 1:18 - loss: 2.0949 - regression_loss: 1.7637 - classification_loss: 0.3312 259/500 [==============>...............] - ETA: 1:18 - loss: 2.0972 - regression_loss: 1.7655 - classification_loss: 0.3317 260/500 [==============>...............] - ETA: 1:17 - loss: 2.0978 - regression_loss: 1.7663 - classification_loss: 0.3315 261/500 [==============>...............] - ETA: 1:17 - loss: 2.0987 - regression_loss: 1.7669 - classification_loss: 0.3319 262/500 [==============>...............] - ETA: 1:17 - loss: 2.0972 - regression_loss: 1.7655 - classification_loss: 0.3316 263/500 [==============>...............] - ETA: 1:16 - loss: 2.0963 - regression_loss: 1.7650 - classification_loss: 0.3313 264/500 [==============>...............] - ETA: 1:16 - loss: 2.0949 - regression_loss: 1.7641 - classification_loss: 0.3308 265/500 [==============>...............] - ETA: 1:16 - loss: 2.0931 - regression_loss: 1.7623 - classification_loss: 0.3308 266/500 [==============>...............] - ETA: 1:15 - loss: 2.0890 - regression_loss: 1.7589 - classification_loss: 0.3300 267/500 [===============>..............] - ETA: 1:15 - loss: 2.0912 - regression_loss: 1.7604 - classification_loss: 0.3308 268/500 [===============>..............] - ETA: 1:15 - loss: 2.0907 - regression_loss: 1.7602 - classification_loss: 0.3305 269/500 [===============>..............] - ETA: 1:14 - loss: 2.0901 - regression_loss: 1.7599 - classification_loss: 0.3303 270/500 [===============>..............] - ETA: 1:14 - loss: 2.0890 - regression_loss: 1.7590 - classification_loss: 0.3299 271/500 [===============>..............] - ETA: 1:14 - loss: 2.0854 - regression_loss: 1.7561 - classification_loss: 0.3293 272/500 [===============>..............] - ETA: 1:13 - loss: 2.0867 - regression_loss: 1.7569 - classification_loss: 0.3299 273/500 [===============>..............] - ETA: 1:13 - loss: 2.0826 - regression_loss: 1.7534 - classification_loss: 0.3292 274/500 [===============>..............] - ETA: 1:13 - loss: 2.0819 - regression_loss: 1.7531 - classification_loss: 0.3288 275/500 [===============>..............] - ETA: 1:12 - loss: 2.0798 - regression_loss: 1.7514 - classification_loss: 0.3285 276/500 [===============>..............] - ETA: 1:12 - loss: 2.0796 - regression_loss: 1.7510 - classification_loss: 0.3286 277/500 [===============>..............] - ETA: 1:12 - loss: 2.0784 - regression_loss: 1.7502 - classification_loss: 0.3282 278/500 [===============>..............] - ETA: 1:11 - loss: 2.0764 - regression_loss: 1.7487 - classification_loss: 0.3277 279/500 [===============>..............] - ETA: 1:11 - loss: 2.0753 - regression_loss: 1.7480 - classification_loss: 0.3273 280/500 [===============>..............] - ETA: 1:11 - loss: 2.0765 - regression_loss: 1.7488 - classification_loss: 0.3278 281/500 [===============>..............] - ETA: 1:10 - loss: 2.0724 - regression_loss: 1.7454 - classification_loss: 0.3271 282/500 [===============>..............] - ETA: 1:10 - loss: 2.0715 - regression_loss: 1.7444 - classification_loss: 0.3271 283/500 [===============>..............] - ETA: 1:10 - loss: 2.0702 - regression_loss: 1.7433 - classification_loss: 0.3269 284/500 [================>.............] - ETA: 1:09 - loss: 2.0712 - regression_loss: 1.7442 - classification_loss: 0.3270 285/500 [================>.............] - ETA: 1:09 - loss: 2.0698 - regression_loss: 1.7432 - classification_loss: 0.3266 286/500 [================>.............] - ETA: 1:09 - loss: 2.0694 - regression_loss: 1.7431 - classification_loss: 0.3263 287/500 [================>.............] - ETA: 1:09 - loss: 2.0703 - regression_loss: 1.7442 - classification_loss: 0.3262 288/500 [================>.............] - ETA: 1:08 - loss: 2.0699 - regression_loss: 1.7439 - classification_loss: 0.3261 289/500 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[============================>.] - ETA: 3s - loss: 2.0419 - regression_loss: 1.7204 - classification_loss: 0.3215 490/500 [============================>.] - ETA: 3s - loss: 2.0417 - regression_loss: 1.7203 - classification_loss: 0.3215 491/500 [============================>.] - ETA: 2s - loss: 2.0411 - regression_loss: 1.7198 - classification_loss: 0.3213 492/500 [============================>.] - ETA: 2s - loss: 2.0408 - regression_loss: 1.7196 - classification_loss: 0.3212 493/500 [============================>.] - ETA: 2s - loss: 2.0394 - regression_loss: 1.7184 - classification_loss: 0.3210 494/500 [============================>.] - ETA: 1s - loss: 2.0388 - regression_loss: 1.7180 - classification_loss: 0.3208 495/500 [============================>.] - ETA: 1s - loss: 2.0382 - regression_loss: 1.7176 - classification_loss: 0.3206 496/500 [============================>.] - ETA: 1s - loss: 2.0376 - regression_loss: 1.7171 - classification_loss: 0.3205 497/500 [============================>.] - ETA: 0s - loss: 2.0367 - regression_loss: 1.7165 - classification_loss: 0.3203 498/500 [============================>.] - ETA: 0s - loss: 2.0342 - regression_loss: 1.7144 - classification_loss: 0.3198 499/500 [============================>.] - ETA: 0s - loss: 2.0356 - regression_loss: 1.7152 - classification_loss: 0.3203 500/500 [==============================] - 162s 323ms/step - loss: 2.0347 - regression_loss: 1.7145 - classification_loss: 0.3202 326 instances of class plum with average precision: 0.7166 mAP: 0.7166 Epoch 00004: saving model to ./training/snapshots/resnet101_pascal_04.h5 Epoch 5/150 1/500 [..............................] - ETA: 2:28 - loss: 1.7773 - regression_loss: 1.5057 - classification_loss: 0.2716 2/500 [..............................] - ETA: 2:29 - loss: 1.8408 - regression_loss: 1.5233 - classification_loss: 0.3175 3/500 [..............................] - ETA: 2:32 - loss: 1.5327 - regression_loss: 1.2649 - 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0.3236 12/500 [..............................] - ETA: 2:35 - loss: 1.6957 - regression_loss: 1.3734 - classification_loss: 0.3222 13/500 [..............................] - ETA: 2:34 - loss: 1.6975 - regression_loss: 1.3884 - classification_loss: 0.3090 14/500 [..............................] - ETA: 2:34 - loss: 1.6658 - regression_loss: 1.3577 - classification_loss: 0.3081 15/500 [..............................] - ETA: 2:34 - loss: 1.6790 - regression_loss: 1.3676 - classification_loss: 0.3114 16/500 [..............................] - ETA: 2:34 - loss: 1.7248 - regression_loss: 1.4071 - classification_loss: 0.3177 17/500 [>.............................] - ETA: 2:33 - loss: 1.7268 - regression_loss: 1.4140 - classification_loss: 0.3128 18/500 [>.............................] - ETA: 2:33 - loss: 1.7244 - regression_loss: 1.4164 - classification_loss: 0.3079 19/500 [>.............................] - ETA: 2:33 - loss: 1.7163 - regression_loss: 1.4132 - classification_loss: 0.3031 20/500 [>.............................] - ETA: 2:33 - loss: 1.7164 - regression_loss: 1.4171 - classification_loss: 0.2993 21/500 [>.............................] - ETA: 2:32 - loss: 1.7120 - regression_loss: 1.4155 - classification_loss: 0.2965 22/500 [>.............................] - ETA: 2:32 - loss: 1.6962 - regression_loss: 1.4074 - classification_loss: 0.2887 23/500 [>.............................] - ETA: 2:31 - loss: 1.6977 - regression_loss: 1.4099 - classification_loss: 0.2878 24/500 [>.............................] - ETA: 2:31 - loss: 1.6953 - regression_loss: 1.4114 - classification_loss: 0.2839 25/500 [>.............................] - ETA: 2:30 - loss: 1.7141 - regression_loss: 1.4313 - classification_loss: 0.2828 26/500 [>.............................] - ETA: 2:30 - loss: 1.7380 - regression_loss: 1.4533 - classification_loss: 0.2846 27/500 [>.............................] - ETA: 2:30 - loss: 1.7163 - regression_loss: 1.4363 - classification_loss: 0.2801 28/500 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[===>..........................] - ETA: 2:15 - loss: 1.8986 - regression_loss: 1.5816 - classification_loss: 0.3170 77/500 [===>..........................] - ETA: 2:15 - loss: 1.8977 - regression_loss: 1.5812 - classification_loss: 0.3164 78/500 [===>..........................] - ETA: 2:15 - loss: 1.8952 - regression_loss: 1.5799 - classification_loss: 0.3153 79/500 [===>..........................] - ETA: 2:15 - loss: 1.8956 - regression_loss: 1.5812 - classification_loss: 0.3143 80/500 [===>..........................] - ETA: 2:14 - loss: 1.8983 - regression_loss: 1.5848 - classification_loss: 0.3135 81/500 [===>..........................] - ETA: 2:14 - loss: 1.8979 - regression_loss: 1.5853 - classification_loss: 0.3126 82/500 [===>..........................] - ETA: 2:14 - loss: 1.8901 - regression_loss: 1.5789 - classification_loss: 0.3112 83/500 [===>..........................] - ETA: 2:14 - loss: 1.8953 - regression_loss: 1.5826 - classification_loss: 0.3127 84/500 [====>.........................] - ETA: 2:13 - loss: 1.9032 - regression_loss: 1.5898 - classification_loss: 0.3135 85/500 [====>.........................] - ETA: 2:13 - loss: 1.9145 - regression_loss: 1.5980 - classification_loss: 0.3166 86/500 [====>.........................] - ETA: 2:13 - loss: 1.9172 - regression_loss: 1.6007 - classification_loss: 0.3165 87/500 [====>.........................] - ETA: 2:12 - loss: 1.9262 - regression_loss: 1.6069 - classification_loss: 0.3193 88/500 [====>.........................] - ETA: 2:12 - loss: 1.9236 - regression_loss: 1.6055 - classification_loss: 0.3180 89/500 [====>.........................] - ETA: 2:12 - loss: 1.9229 - regression_loss: 1.6060 - classification_loss: 0.3169 90/500 [====>.........................] - ETA: 2:11 - loss: 1.9320 - regression_loss: 1.6136 - classification_loss: 0.3184 91/500 [====>.........................] - ETA: 2:11 - loss: 1.9364 - regression_loss: 1.6177 - classification_loss: 0.3187 92/500 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[=====>........................] - ETA: 2:08 - loss: 1.9375 - regression_loss: 1.6217 - classification_loss: 0.3159 101/500 [=====>........................] - ETA: 2:08 - loss: 1.9360 - regression_loss: 1.6213 - classification_loss: 0.3147 102/500 [=====>........................] - ETA: 2:08 - loss: 1.9417 - regression_loss: 1.6261 - classification_loss: 0.3157 103/500 [=====>........................] - ETA: 2:07 - loss: 1.9398 - regression_loss: 1.6250 - classification_loss: 0.3147 104/500 [=====>........................] - ETA: 2:07 - loss: 1.9412 - regression_loss: 1.6266 - classification_loss: 0.3147 105/500 [=====>........................] - ETA: 2:07 - loss: 1.9384 - regression_loss: 1.6247 - classification_loss: 0.3137 106/500 [=====>........................] - ETA: 2:06 - loss: 1.9368 - regression_loss: 1.6238 - classification_loss: 0.3131 107/500 [=====>........................] - ETA: 2:06 - loss: 1.9309 - regression_loss: 1.6192 - classification_loss: 0.3117 108/500 [=====>........................] - ETA: 2:06 - loss: 1.9299 - regression_loss: 1.6193 - classification_loss: 0.3106 109/500 [=====>........................] - ETA: 2:05 - loss: 1.9308 - regression_loss: 1.6208 - classification_loss: 0.3099 110/500 [=====>........................] - ETA: 2:05 - loss: 1.9277 - regression_loss: 1.6189 - classification_loss: 0.3088 111/500 [=====>........................] - ETA: 2:05 - loss: 1.9287 - regression_loss: 1.6204 - classification_loss: 0.3083 112/500 [=====>........................] - ETA: 2:04 - loss: 1.9316 - regression_loss: 1.6234 - classification_loss: 0.3082 113/500 [=====>........................] - ETA: 2:04 - loss: 1.9337 - regression_loss: 1.6246 - classification_loss: 0.3091 114/500 [=====>........................] - ETA: 2:04 - loss: 1.9359 - regression_loss: 1.6262 - classification_loss: 0.3097 115/500 [=====>........................] - ETA: 2:03 - loss: 1.9343 - regression_loss: 1.6248 - classification_loss: 0.3095 116/500 [=====>........................] - ETA: 2:03 - loss: 1.9307 - regression_loss: 1.6223 - classification_loss: 0.3084 117/500 [======>.......................] - ETA: 2:03 - loss: 1.9289 - regression_loss: 1.6212 - classification_loss: 0.3076 118/500 [======>.......................] - ETA: 2:03 - loss: 1.9260 - regression_loss: 1.6185 - classification_loss: 0.3075 119/500 [======>.......................] - ETA: 2:02 - loss: 1.9254 - regression_loss: 1.6177 - classification_loss: 0.3076 120/500 [======>.......................] - ETA: 2:02 - loss: 1.9266 - regression_loss: 1.6184 - classification_loss: 0.3082 121/500 [======>.......................] - ETA: 2:02 - loss: 1.9272 - regression_loss: 1.6193 - classification_loss: 0.3079 122/500 [======>.......................] - ETA: 2:01 - loss: 1.9288 - regression_loss: 1.6198 - classification_loss: 0.3089 123/500 [======>.......................] - ETA: 2:01 - loss: 1.9299 - regression_loss: 1.6203 - classification_loss: 0.3096 124/500 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[======>.......................] - ETA: 1:58 - loss: 1.9243 - regression_loss: 1.6161 - classification_loss: 0.3081 133/500 [======>.......................] - ETA: 1:58 - loss: 1.9191 - regression_loss: 1.6117 - classification_loss: 0.3073 134/500 [=======>......................] - ETA: 1:57 - loss: 1.9216 - regression_loss: 1.6136 - classification_loss: 0.3080 135/500 [=======>......................] - ETA: 1:57 - loss: 1.9208 - regression_loss: 1.6125 - classification_loss: 0.3082 136/500 [=======>......................] - ETA: 1:57 - loss: 1.9149 - regression_loss: 1.6076 - classification_loss: 0.3073 137/500 [=======>......................] - ETA: 1:56 - loss: 1.9130 - regression_loss: 1.6062 - classification_loss: 0.3068 138/500 [=======>......................] - ETA: 1:56 - loss: 1.9164 - regression_loss: 1.6093 - classification_loss: 0.3071 139/500 [=======>......................] - ETA: 1:56 - loss: 1.9156 - regression_loss: 1.6088 - classification_loss: 0.3068 140/500 [=======>......................] - ETA: 1:55 - loss: 1.9232 - regression_loss: 1.6136 - classification_loss: 0.3097 141/500 [=======>......................] - ETA: 1:55 - loss: 1.9202 - regression_loss: 1.6113 - classification_loss: 0.3089 142/500 [=======>......................] - ETA: 1:55 - loss: 1.9194 - regression_loss: 1.6110 - classification_loss: 0.3084 143/500 [=======>......................] - ETA: 1:55 - loss: 1.9229 - regression_loss: 1.6138 - classification_loss: 0.3091 144/500 [=======>......................] - ETA: 1:54 - loss: 1.9171 - regression_loss: 1.6093 - classification_loss: 0.3078 145/500 [=======>......................] - ETA: 1:54 - loss: 1.9142 - regression_loss: 1.6067 - classification_loss: 0.3075 146/500 [=======>......................] - ETA: 1:54 - loss: 1.9189 - regression_loss: 1.6098 - classification_loss: 0.3090 147/500 [=======>......................] - ETA: 1:53 - loss: 1.9144 - regression_loss: 1.6063 - classification_loss: 0.3082 148/500 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[============================>.] - ETA: 5s - loss: 1.8864 - regression_loss: 1.5934 - classification_loss: 0.2930 485/500 [============================>.] - ETA: 4s - loss: 1.8872 - regression_loss: 1.5941 - classification_loss: 0.2931 486/500 [============================>.] - ETA: 4s - loss: 1.8872 - regression_loss: 1.5940 - classification_loss: 0.2932 487/500 [============================>.] - ETA: 4s - loss: 1.8851 - regression_loss: 1.5922 - classification_loss: 0.2929 488/500 [============================>.] - ETA: 3s - loss: 1.8840 - regression_loss: 1.5914 - classification_loss: 0.2926 489/500 [============================>.] - ETA: 3s - loss: 1.8828 - regression_loss: 1.5904 - classification_loss: 0.2924 490/500 [============================>.] - ETA: 3s - loss: 1.8824 - regression_loss: 1.5902 - classification_loss: 0.2923 491/500 [============================>.] - ETA: 2s - loss: 1.8825 - regression_loss: 1.5903 - classification_loss: 0.2922 492/500 [============================>.] - ETA: 2s - loss: 1.8830 - regression_loss: 1.5906 - classification_loss: 0.2924 493/500 [============================>.] - ETA: 2s - loss: 1.8833 - regression_loss: 1.5907 - classification_loss: 0.2925 494/500 [============================>.] - ETA: 1s - loss: 1.8833 - regression_loss: 1.5909 - classification_loss: 0.2924 495/500 [============================>.] - ETA: 1s - loss: 1.8830 - regression_loss: 1.5908 - classification_loss: 0.2922 496/500 [============================>.] - ETA: 1s - loss: 1.8831 - regression_loss: 1.5909 - classification_loss: 0.2922 497/500 [============================>.] - ETA: 0s - loss: 1.8818 - regression_loss: 1.5898 - classification_loss: 0.2920 498/500 [============================>.] - ETA: 0s - loss: 1.8817 - regression_loss: 1.5897 - classification_loss: 0.2920 499/500 [============================>.] - ETA: 0s - loss: 1.8818 - regression_loss: 1.5899 - classification_loss: 0.2919 500/500 [==============================] - 162s 325ms/step - loss: 1.8820 - regression_loss: 1.5902 - classification_loss: 0.2918 326 instances of class plum with average precision: 0.7421 mAP: 0.7421 Epoch 00005: saving model to ./training/snapshots/resnet101_pascal_05.h5 Epoch 6/150 1/500 [..............................] - ETA: 2:39 - loss: 1.5821 - regression_loss: 1.3190 - classification_loss: 0.2631 2/500 [..............................] - ETA: 2:47 - loss: 1.9088 - regression_loss: 1.6028 - classification_loss: 0.3060 3/500 [..............................] - ETA: 2:44 - loss: 1.8666 - regression_loss: 1.5675 - classification_loss: 0.2991 4/500 [..............................] - ETA: 2:41 - loss: 1.8147 - regression_loss: 1.5119 - classification_loss: 0.3028 5/500 [..............................] - ETA: 2:38 - loss: 1.7991 - regression_loss: 1.5008 - classification_loss: 0.2983 6/500 [..............................] - ETA: 2:38 - loss: 1.8033 - regression_loss: 1.5158 - classification_loss: 0.2875 7/500 [..............................] - ETA: 2:37 - loss: 1.7693 - regression_loss: 1.4993 - classification_loss: 0.2700 8/500 [..............................] - ETA: 2:37 - loss: 1.7446 - regression_loss: 1.4820 - classification_loss: 0.2626 9/500 [..............................] - ETA: 2:36 - loss: 1.8300 - regression_loss: 1.5554 - classification_loss: 0.2747 10/500 [..............................] - ETA: 2:36 - loss: 1.8595 - regression_loss: 1.5779 - classification_loss: 0.2816 11/500 [..............................] - ETA: 2:36 - loss: 1.8158 - regression_loss: 1.5415 - classification_loss: 0.2743 12/500 [..............................] - ETA: 2:36 - loss: 1.7544 - regression_loss: 1.4915 - classification_loss: 0.2630 13/500 [..............................] - ETA: 2:36 - loss: 1.7684 - regression_loss: 1.5027 - classification_loss: 0.2658 14/500 [..............................] - ETA: 2:36 - loss: 1.7761 - regression_loss: 1.5055 - classification_loss: 0.2707 15/500 [..............................] - ETA: 2:36 - loss: 1.7603 - regression_loss: 1.4870 - classification_loss: 0.2733 16/500 [..............................] - ETA: 2:36 - loss: 1.8349 - regression_loss: 1.5457 - classification_loss: 0.2892 17/500 [>.............................] - ETA: 2:35 - loss: 1.8286 - regression_loss: 1.5432 - classification_loss: 0.2853 18/500 [>.............................] - ETA: 2:35 - loss: 1.8489 - regression_loss: 1.5544 - classification_loss: 0.2944 19/500 [>.............................] - ETA: 2:35 - loss: 1.8514 - regression_loss: 1.5611 - classification_loss: 0.2903 20/500 [>.............................] - ETA: 2:35 - loss: 1.8703 - regression_loss: 1.5732 - classification_loss: 0.2971 21/500 [>.............................] - ETA: 2:34 - loss: 1.8883 - regression_loss: 1.5854 - classification_loss: 0.3028 22/500 [>.............................] - ETA: 2:34 - loss: 1.8678 - regression_loss: 1.5697 - classification_loss: 0.2980 23/500 [>.............................] - ETA: 2:33 - loss: 1.8452 - regression_loss: 1.5493 - classification_loss: 0.2959 24/500 [>.............................] - ETA: 2:32 - loss: 1.8108 - regression_loss: 1.5126 - classification_loss: 0.2982 25/500 [>.............................] - ETA: 2:32 - loss: 1.8064 - regression_loss: 1.5118 - classification_loss: 0.2946 26/500 [>.............................] - ETA: 2:32 - loss: 1.8144 - regression_loss: 1.5213 - classification_loss: 0.2932 27/500 [>.............................] - ETA: 2:31 - loss: 1.7915 - regression_loss: 1.5019 - classification_loss: 0.2896 28/500 [>.............................] - ETA: 2:31 - loss: 1.7870 - regression_loss: 1.5000 - classification_loss: 0.2871 29/500 [>.............................] - ETA: 2:30 - loss: 1.7806 - regression_loss: 1.4975 - classification_loss: 0.2831 30/500 [>.............................] - ETA: 2:30 - loss: 1.7849 - regression_loss: 1.5028 - classification_loss: 0.2821 31/500 [>.............................] - ETA: 2:29 - loss: 1.7883 - regression_loss: 1.5066 - classification_loss: 0.2817 32/500 [>.............................] - ETA: 2:29 - loss: 1.7745 - regression_loss: 1.4947 - classification_loss: 0.2798 33/500 [>.............................] - ETA: 2:29 - loss: 1.7726 - regression_loss: 1.4926 - classification_loss: 0.2800 34/500 [=>............................] - ETA: 2:29 - loss: 1.7757 - regression_loss: 1.4953 - classification_loss: 0.2804 35/500 [=>............................] - ETA: 2:29 - loss: 1.7746 - regression_loss: 1.4949 - classification_loss: 0.2797 36/500 [=>............................] - ETA: 2:28 - loss: 1.7787 - regression_loss: 1.5007 - classification_loss: 0.2780 37/500 [=>............................] - ETA: 2:28 - loss: 1.7872 - regression_loss: 1.5084 - classification_loss: 0.2788 38/500 [=>............................] - ETA: 2:28 - loss: 1.7759 - regression_loss: 1.4975 - classification_loss: 0.2784 39/500 [=>............................] - ETA: 2:27 - loss: 1.7733 - regression_loss: 1.4948 - classification_loss: 0.2785 40/500 [=>............................] - ETA: 2:27 - loss: 1.7711 - regression_loss: 1.4942 - classification_loss: 0.2769 41/500 [=>............................] - ETA: 2:26 - loss: 1.7646 - regression_loss: 1.4900 - classification_loss: 0.2746 42/500 [=>............................] - ETA: 2:26 - loss: 1.7853 - regression_loss: 1.5093 - classification_loss: 0.2760 43/500 [=>............................] - ETA: 2:26 - loss: 1.7898 - regression_loss: 1.5107 - classification_loss: 0.2791 44/500 [=>............................] - ETA: 2:26 - loss: 1.7964 - regression_loss: 1.5170 - classification_loss: 0.2794 45/500 [=>............................] - ETA: 2:26 - loss: 1.8032 - regression_loss: 1.5228 - classification_loss: 0.2804 46/500 [=>............................] - ETA: 2:25 - loss: 1.8400 - regression_loss: 1.5551 - classification_loss: 0.2849 47/500 [=>............................] - ETA: 2:25 - loss: 1.8417 - regression_loss: 1.5562 - classification_loss: 0.2854 48/500 [=>............................] - ETA: 2:25 - loss: 1.8503 - regression_loss: 1.5634 - classification_loss: 0.2869 49/500 [=>............................] - ETA: 2:24 - loss: 1.8524 - regression_loss: 1.5649 - classification_loss: 0.2874 50/500 [==>...........................] - ETA: 2:24 - loss: 1.8536 - regression_loss: 1.5656 - classification_loss: 0.2879 51/500 [==>...........................] - ETA: 2:24 - loss: 1.8635 - regression_loss: 1.5725 - classification_loss: 0.2911 52/500 [==>...........................] - ETA: 2:24 - loss: 1.8614 - regression_loss: 1.5717 - classification_loss: 0.2896 53/500 [==>...........................] - ETA: 2:23 - loss: 1.8706 - regression_loss: 1.5769 - classification_loss: 0.2937 54/500 [==>...........................] - ETA: 2:23 - loss: 1.8610 - regression_loss: 1.5697 - classification_loss: 0.2913 55/500 [==>...........................] - ETA: 2:23 - loss: 1.8510 - regression_loss: 1.5622 - classification_loss: 0.2888 56/500 [==>...........................] - ETA: 2:23 - loss: 1.8557 - regression_loss: 1.5655 - classification_loss: 0.2902 57/500 [==>...........................] - ETA: 2:22 - loss: 1.8538 - regression_loss: 1.5655 - classification_loss: 0.2883 58/500 [==>...........................] - ETA: 2:22 - loss: 1.8453 - regression_loss: 1.5592 - classification_loss: 0.2861 59/500 [==>...........................] - ETA: 2:22 - loss: 1.8592 - regression_loss: 1.5676 - classification_loss: 0.2916 60/500 [==>...........................] - ETA: 2:22 - loss: 1.8542 - regression_loss: 1.5640 - classification_loss: 0.2902 61/500 [==>...........................] - ETA: 2:21 - loss: 1.8623 - regression_loss: 1.5698 - classification_loss: 0.2925 62/500 [==>...........................] - ETA: 2:21 - loss: 1.8684 - regression_loss: 1.5744 - classification_loss: 0.2940 63/500 [==>...........................] - ETA: 2:21 - loss: 1.8602 - regression_loss: 1.5680 - classification_loss: 0.2922 64/500 [==>...........................] - ETA: 2:20 - loss: 1.8468 - regression_loss: 1.5565 - classification_loss: 0.2903 65/500 [==>...........................] - ETA: 2:20 - loss: 1.8330 - regression_loss: 1.5451 - classification_loss: 0.2879 66/500 [==>...........................] - ETA: 2:19 - loss: 1.8368 - regression_loss: 1.5480 - classification_loss: 0.2888 67/500 [===>..........................] - ETA: 2:19 - loss: 1.8339 - regression_loss: 1.5460 - classification_loss: 0.2879 68/500 [===>..........................] - ETA: 2:19 - loss: 1.8367 - regression_loss: 1.5471 - classification_loss: 0.2896 69/500 [===>..........................] - ETA: 2:18 - loss: 1.8209 - regression_loss: 1.5328 - classification_loss: 0.2881 70/500 [===>..........................] - ETA: 2:18 - loss: 1.8125 - regression_loss: 1.5257 - classification_loss: 0.2868 71/500 [===>..........................] - ETA: 2:18 - loss: 1.8128 - regression_loss: 1.5272 - classification_loss: 0.2856 72/500 [===>..........................] - ETA: 2:17 - loss: 1.7992 - regression_loss: 1.5162 - classification_loss: 0.2830 73/500 [===>..........................] - ETA: 2:17 - loss: 1.8073 - regression_loss: 1.5222 - classification_loss: 0.2851 74/500 [===>..........................] - ETA: 2:17 - loss: 1.8075 - regression_loss: 1.5228 - classification_loss: 0.2847 75/500 [===>..........................] - ETA: 2:16 - loss: 1.7967 - regression_loss: 1.5133 - classification_loss: 0.2833 76/500 [===>..........................] - ETA: 2:16 - loss: 1.7976 - regression_loss: 1.5158 - classification_loss: 0.2818 77/500 [===>..........................] - ETA: 2:16 - loss: 1.7988 - regression_loss: 1.5179 - classification_loss: 0.2809 78/500 [===>..........................] - ETA: 2:15 - loss: 1.7855 - regression_loss: 1.5066 - classification_loss: 0.2789 79/500 [===>..........................] - ETA: 2:15 - loss: 1.7904 - regression_loss: 1.5104 - classification_loss: 0.2800 80/500 [===>..........................] - ETA: 2:15 - loss: 1.7949 - regression_loss: 1.5136 - classification_loss: 0.2812 81/500 [===>..........................] - ETA: 2:14 - loss: 1.8114 - regression_loss: 1.5276 - classification_loss: 0.2838 82/500 [===>..........................] - ETA: 2:14 - loss: 1.8167 - regression_loss: 1.5319 - classification_loss: 0.2849 83/500 [===>..........................] - ETA: 2:14 - loss: 1.8206 - regression_loss: 1.5360 - classification_loss: 0.2846 84/500 [====>.........................] - ETA: 2:14 - loss: 1.8110 - regression_loss: 1.5282 - classification_loss: 0.2828 85/500 [====>.........................] - ETA: 2:13 - loss: 1.8142 - regression_loss: 1.5302 - classification_loss: 0.2839 86/500 [====>.........................] - ETA: 2:13 - loss: 1.8109 - regression_loss: 1.5280 - classification_loss: 0.2829 87/500 [====>.........................] - ETA: 2:13 - loss: 1.8050 - regression_loss: 1.5235 - classification_loss: 0.2815 88/500 [====>.........................] - ETA: 2:13 - loss: 1.8058 - regression_loss: 1.5242 - classification_loss: 0.2816 89/500 [====>.........................] - ETA: 2:12 - loss: 1.8053 - regression_loss: 1.5241 - classification_loss: 0.2812 90/500 [====>.........................] - ETA: 2:12 - loss: 1.8099 - regression_loss: 1.5282 - classification_loss: 0.2817 91/500 [====>.........................] - ETA: 2:12 - loss: 1.8046 - regression_loss: 1.5236 - classification_loss: 0.2810 92/500 [====>.........................] - ETA: 2:11 - loss: 1.8025 - regression_loss: 1.5218 - classification_loss: 0.2807 93/500 [====>.........................] - ETA: 2:11 - loss: 1.8040 - regression_loss: 1.5235 - classification_loss: 0.2805 94/500 [====>.........................] - ETA: 2:11 - loss: 1.8054 - regression_loss: 1.5247 - classification_loss: 0.2807 95/500 [====>.........................] - ETA: 2:10 - loss: 1.8091 - regression_loss: 1.5284 - classification_loss: 0.2807 96/500 [====>.........................] - ETA: 2:10 - loss: 1.8035 - regression_loss: 1.5233 - classification_loss: 0.2802 97/500 [====>.........................] - ETA: 2:10 - loss: 1.8068 - regression_loss: 1.5248 - classification_loss: 0.2820 98/500 [====>.........................] - ETA: 2:09 - loss: 1.8128 - regression_loss: 1.5302 - classification_loss: 0.2826 99/500 [====>.........................] - ETA: 2:09 - loss: 1.8173 - regression_loss: 1.5336 - classification_loss: 0.2837 100/500 [=====>........................] - ETA: 2:09 - loss: 1.8155 - regression_loss: 1.5321 - classification_loss: 0.2834 101/500 [=====>........................] - ETA: 2:08 - loss: 1.8142 - regression_loss: 1.5315 - classification_loss: 0.2827 102/500 [=====>........................] - ETA: 2:08 - loss: 1.8192 - regression_loss: 1.5347 - classification_loss: 0.2846 103/500 [=====>........................] - ETA: 2:08 - loss: 1.8233 - regression_loss: 1.5377 - classification_loss: 0.2856 104/500 [=====>........................] - ETA: 2:08 - loss: 1.8276 - regression_loss: 1.5406 - classification_loss: 0.2870 105/500 [=====>........................] - ETA: 2:07 - loss: 1.8278 - regression_loss: 1.5412 - classification_loss: 0.2867 106/500 [=====>........................] - ETA: 2:07 - loss: 1.8286 - regression_loss: 1.5421 - classification_loss: 0.2866 107/500 [=====>........................] - ETA: 2:07 - loss: 1.8272 - regression_loss: 1.5412 - classification_loss: 0.2860 108/500 [=====>........................] - ETA: 2:06 - loss: 1.8173 - regression_loss: 1.5326 - classification_loss: 0.2847 109/500 [=====>........................] - ETA: 2:06 - loss: 1.8067 - regression_loss: 1.5234 - classification_loss: 0.2833 110/500 [=====>........................] - ETA: 2:06 - loss: 1.8068 - regression_loss: 1.5236 - classification_loss: 0.2831 111/500 [=====>........................] - ETA: 2:05 - loss: 1.8013 - regression_loss: 1.5194 - classification_loss: 0.2819 112/500 [=====>........................] - ETA: 2:05 - loss: 1.8128 - regression_loss: 1.5263 - classification_loss: 0.2866 113/500 [=====>........................] - ETA: 2:05 - loss: 1.8077 - regression_loss: 1.5216 - classification_loss: 0.2861 114/500 [=====>........................] - ETA: 2:04 - loss: 1.7985 - regression_loss: 1.5140 - classification_loss: 0.2845 115/500 [=====>........................] - ETA: 2:04 - loss: 1.7988 - regression_loss: 1.5144 - classification_loss: 0.2844 116/500 [=====>........................] - ETA: 2:04 - loss: 1.8005 - regression_loss: 1.5164 - classification_loss: 0.2841 117/500 [======>.......................] - ETA: 2:03 - loss: 1.8006 - regression_loss: 1.5164 - classification_loss: 0.2842 118/500 [======>.......................] - ETA: 2:03 - loss: 1.7991 - regression_loss: 1.5154 - classification_loss: 0.2837 119/500 [======>.......................] - ETA: 2:03 - loss: 1.8024 - regression_loss: 1.5179 - classification_loss: 0.2845 120/500 [======>.......................] - ETA: 2:03 - loss: 1.8088 - regression_loss: 1.5223 - classification_loss: 0.2864 121/500 [======>.......................] - ETA: 2:02 - loss: 1.8099 - regression_loss: 1.5229 - classification_loss: 0.2870 122/500 [======>.......................] - ETA: 2:02 - loss: 1.8115 - regression_loss: 1.5251 - classification_loss: 0.2864 123/500 [======>.......................] - ETA: 2:01 - loss: 1.8068 - regression_loss: 1.5217 - classification_loss: 0.2851 124/500 [======>.......................] - ETA: 2:01 - loss: 1.8066 - regression_loss: 1.5216 - classification_loss: 0.2850 125/500 [======>.......................] - ETA: 2:01 - loss: 1.8124 - regression_loss: 1.5265 - classification_loss: 0.2859 126/500 [======>.......................] - ETA: 2:00 - loss: 1.8048 - regression_loss: 1.5200 - classification_loss: 0.2848 127/500 [======>.......................] - ETA: 2:00 - loss: 1.8044 - regression_loss: 1.5203 - classification_loss: 0.2841 128/500 [======>.......................] - ETA: 2:00 - loss: 1.8004 - regression_loss: 1.5173 - classification_loss: 0.2831 129/500 [======>.......................] - ETA: 2:00 - loss: 1.8033 - regression_loss: 1.5200 - classification_loss: 0.2833 130/500 [======>.......................] - ETA: 1:59 - loss: 1.8034 - regression_loss: 1.5207 - classification_loss: 0.2827 131/500 [======>.......................] - ETA: 1:59 - loss: 1.8037 - regression_loss: 1.5213 - classification_loss: 0.2824 132/500 [======>.......................] - ETA: 1:59 - loss: 1.8095 - regression_loss: 1.5254 - classification_loss: 0.2841 133/500 [======>.......................] - ETA: 1:58 - loss: 1.8098 - regression_loss: 1.5255 - classification_loss: 0.2842 134/500 [=======>......................] - ETA: 1:58 - loss: 1.8164 - regression_loss: 1.5297 - classification_loss: 0.2868 135/500 [=======>......................] - ETA: 1:58 - loss: 1.8166 - regression_loss: 1.5299 - classification_loss: 0.2867 136/500 [=======>......................] - ETA: 1:57 - loss: 1.8273 - regression_loss: 1.5389 - classification_loss: 0.2884 137/500 [=======>......................] - ETA: 1:57 - loss: 1.8260 - regression_loss: 1.5381 - classification_loss: 0.2879 138/500 [=======>......................] - ETA: 1:57 - loss: 1.8247 - regression_loss: 1.5369 - classification_loss: 0.2878 139/500 [=======>......................] - ETA: 1:56 - loss: 1.8175 - regression_loss: 1.5311 - classification_loss: 0.2865 140/500 [=======>......................] - ETA: 1:56 - loss: 1.8209 - regression_loss: 1.5336 - classification_loss: 0.2873 141/500 [=======>......................] - ETA: 1:56 - loss: 1.8250 - regression_loss: 1.5370 - classification_loss: 0.2879 142/500 [=======>......................] - ETA: 1:55 - loss: 1.8229 - regression_loss: 1.5357 - classification_loss: 0.2873 143/500 [=======>......................] - ETA: 1:55 - loss: 1.8211 - regression_loss: 1.5346 - classification_loss: 0.2865 144/500 [=======>......................] - ETA: 1:55 - loss: 1.8207 - regression_loss: 1.5345 - classification_loss: 0.2861 145/500 [=======>......................] - ETA: 1:54 - loss: 1.8218 - regression_loss: 1.5359 - classification_loss: 0.2859 146/500 [=======>......................] - ETA: 1:54 - loss: 1.8227 - regression_loss: 1.5366 - classification_loss: 0.2861 147/500 [=======>......................] - ETA: 1:54 - loss: 1.8209 - regression_loss: 1.5352 - classification_loss: 0.2857 148/500 [=======>......................] - ETA: 1:53 - loss: 1.8175 - regression_loss: 1.5318 - classification_loss: 0.2857 149/500 [=======>......................] - ETA: 1:53 - loss: 1.8176 - regression_loss: 1.5317 - classification_loss: 0.2859 150/500 [========>.....................] - ETA: 1:53 - loss: 1.8142 - regression_loss: 1.5290 - classification_loss: 0.2852 151/500 [========>.....................] - ETA: 1:52 - loss: 1.8120 - regression_loss: 1.5273 - classification_loss: 0.2847 152/500 [========>.....................] - ETA: 1:52 - loss: 1.8054 - regression_loss: 1.5216 - classification_loss: 0.2838 153/500 [========>.....................] - ETA: 1:52 - loss: 1.8043 - regression_loss: 1.5206 - classification_loss: 0.2836 154/500 [========>.....................] - ETA: 1:51 - loss: 1.8012 - regression_loss: 1.5181 - classification_loss: 0.2831 155/500 [========>.....................] - ETA: 1:51 - loss: 1.7958 - regression_loss: 1.5138 - classification_loss: 0.2820 156/500 [========>.....................] - ETA: 1:51 - loss: 1.7993 - regression_loss: 1.5173 - classification_loss: 0.2820 157/500 [========>.....................] - ETA: 1:50 - loss: 1.7992 - regression_loss: 1.5176 - classification_loss: 0.2816 158/500 [========>.....................] - ETA: 1:50 - loss: 1.7997 - regression_loss: 1.5183 - classification_loss: 0.2813 159/500 [========>.....................] - ETA: 1:50 - loss: 1.7985 - regression_loss: 1.5178 - classification_loss: 0.2807 160/500 [========>.....................] - ETA: 1:50 - loss: 1.7967 - regression_loss: 1.5166 - classification_loss: 0.2801 161/500 [========>.....................] - ETA: 1:49 - loss: 1.8010 - regression_loss: 1.5202 - classification_loss: 0.2808 162/500 [========>.....................] - ETA: 1:49 - loss: 1.7999 - regression_loss: 1.5196 - classification_loss: 0.2803 163/500 [========>.....................] - ETA: 1:49 - loss: 1.7984 - regression_loss: 1.5189 - classification_loss: 0.2795 164/500 [========>.....................] - ETA: 1:48 - loss: 1.7919 - regression_loss: 1.5133 - classification_loss: 0.2786 165/500 [========>.....................] - ETA: 1:48 - loss: 1.7954 - regression_loss: 1.5159 - classification_loss: 0.2795 166/500 [========>.....................] - ETA: 1:48 - loss: 1.7986 - regression_loss: 1.5185 - classification_loss: 0.2801 167/500 [=========>....................] - ETA: 1:47 - loss: 1.8017 - regression_loss: 1.5206 - classification_loss: 0.2812 168/500 [=========>....................] - ETA: 1:47 - loss: 1.8022 - regression_loss: 1.5211 - classification_loss: 0.2811 169/500 [=========>....................] - ETA: 1:47 - loss: 1.8030 - regression_loss: 1.5212 - classification_loss: 0.2818 170/500 [=========>....................] - ETA: 1:46 - loss: 1.8050 - regression_loss: 1.5228 - classification_loss: 0.2821 171/500 [=========>....................] - ETA: 1:46 - loss: 1.8056 - regression_loss: 1.5238 - classification_loss: 0.2819 172/500 [=========>....................] - ETA: 1:46 - loss: 1.8095 - regression_loss: 1.5266 - classification_loss: 0.2829 173/500 [=========>....................] - ETA: 1:45 - loss: 1.8078 - regression_loss: 1.5254 - classification_loss: 0.2824 174/500 [=========>....................] - ETA: 1:45 - loss: 1.8133 - regression_loss: 1.5287 - classification_loss: 0.2846 175/500 [=========>....................] - ETA: 1:45 - loss: 1.8088 - regression_loss: 1.5251 - classification_loss: 0.2837 176/500 [=========>....................] - ETA: 1:44 - loss: 1.8101 - regression_loss: 1.5265 - classification_loss: 0.2836 177/500 [=========>....................] - ETA: 1:44 - loss: 1.8100 - regression_loss: 1.5264 - classification_loss: 0.2836 178/500 [=========>....................] - ETA: 1:44 - loss: 1.8138 - regression_loss: 1.5291 - classification_loss: 0.2847 179/500 [=========>....................] - ETA: 1:43 - loss: 1.8113 - regression_loss: 1.5271 - classification_loss: 0.2842 180/500 [=========>....................] - ETA: 1:43 - loss: 1.8128 - regression_loss: 1.5283 - classification_loss: 0.2846 181/500 [=========>....................] - ETA: 1:43 - loss: 1.8166 - regression_loss: 1.5315 - classification_loss: 0.2852 182/500 [=========>....................] - ETA: 1:42 - loss: 1.8161 - regression_loss: 1.5310 - classification_loss: 0.2851 183/500 [=========>....................] - ETA: 1:42 - loss: 1.8158 - regression_loss: 1.5307 - classification_loss: 0.2851 184/500 [==========>...................] - ETA: 1:42 - loss: 1.8145 - regression_loss: 1.5298 - classification_loss: 0.2847 185/500 [==========>...................] - ETA: 1:41 - loss: 1.8128 - regression_loss: 1.5285 - classification_loss: 0.2843 186/500 [==========>...................] - ETA: 1:41 - loss: 1.8117 - regression_loss: 1.5279 - classification_loss: 0.2838 187/500 [==========>...................] - ETA: 1:41 - loss: 1.8148 - regression_loss: 1.5298 - classification_loss: 0.2850 188/500 [==========>...................] - ETA: 1:41 - loss: 1.8142 - regression_loss: 1.5297 - classification_loss: 0.2845 189/500 [==========>...................] - ETA: 1:40 - loss: 1.8139 - regression_loss: 1.5295 - classification_loss: 0.2844 190/500 [==========>...................] - ETA: 1:40 - loss: 1.8135 - regression_loss: 1.5290 - 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classification_loss: 0.2778 391/500 [======================>.......] - ETA: 35s - loss: 1.7946 - regression_loss: 1.5168 - classification_loss: 0.2778 392/500 [======================>.......] - ETA: 35s - loss: 1.7929 - regression_loss: 1.5154 - classification_loss: 0.2775 393/500 [======================>.......] - ETA: 34s - loss: 1.7923 - regression_loss: 1.5148 - classification_loss: 0.2775 394/500 [======================>.......] - ETA: 34s - loss: 1.7900 - regression_loss: 1.5129 - classification_loss: 0.2772 395/500 [======================>.......] - ETA: 34s - loss: 1.7922 - regression_loss: 1.5147 - classification_loss: 0.2774 396/500 [======================>.......] - ETA: 33s - loss: 1.7917 - regression_loss: 1.5144 - classification_loss: 0.2773 397/500 [======================>.......] - ETA: 33s - loss: 1.7902 - regression_loss: 1.5131 - classification_loss: 0.2771 398/500 [======================>.......] - ETA: 33s - loss: 1.7920 - regression_loss: 1.5145 - 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classification_loss: 0.2763 423/500 [========================>.....] - ETA: 25s - loss: 1.7856 - regression_loss: 1.5096 - classification_loss: 0.2760 424/500 [========================>.....] - ETA: 24s - loss: 1.7845 - regression_loss: 1.5086 - classification_loss: 0.2759 425/500 [========================>.....] - ETA: 24s - loss: 1.7840 - regression_loss: 1.5083 - classification_loss: 0.2757 426/500 [========================>.....] - ETA: 24s - loss: 1.7842 - regression_loss: 1.5086 - classification_loss: 0.2756 427/500 [========================>.....] - ETA: 23s - loss: 1.7840 - regression_loss: 1.5083 - classification_loss: 0.2757 428/500 [========================>.....] - ETA: 23s - loss: 1.7845 - regression_loss: 1.5086 - classification_loss: 0.2759 429/500 [========================>.....] - ETA: 23s - loss: 1.7875 - regression_loss: 1.5113 - classification_loss: 0.2761 430/500 [========================>.....] - ETA: 22s - loss: 1.7876 - regression_loss: 1.5116 - classification_loss: 0.2760 431/500 [========================>.....] - ETA: 22s - loss: 1.7885 - regression_loss: 1.5126 - classification_loss: 0.2760 432/500 [========================>.....] - ETA: 22s - loss: 1.7908 - regression_loss: 1.5145 - classification_loss: 0.2763 433/500 [========================>.....] - ETA: 21s - loss: 1.7908 - regression_loss: 1.5145 - classification_loss: 0.2763 434/500 [=========================>....] - ETA: 21s - loss: 1.7896 - regression_loss: 1.5135 - classification_loss: 0.2761 435/500 [=========================>....] - ETA: 21s - loss: 1.7899 - regression_loss: 1.5136 - classification_loss: 0.2763 436/500 [=========================>....] - ETA: 20s - loss: 1.7893 - regression_loss: 1.5132 - classification_loss: 0.2761 437/500 [=========================>....] - ETA: 20s - loss: 1.7881 - regression_loss: 1.5122 - classification_loss: 0.2759 438/500 [=========================>....] - ETA: 20s - loss: 1.7901 - regression_loss: 1.5134 - classification_loss: 0.2767 439/500 [=========================>....] - ETA: 19s - loss: 1.7923 - regression_loss: 1.5151 - classification_loss: 0.2772 440/500 [=========================>....] - ETA: 19s - loss: 1.7920 - regression_loss: 1.5150 - classification_loss: 0.2770 441/500 [=========================>....] - ETA: 19s - loss: 1.7926 - regression_loss: 1.5154 - classification_loss: 0.2772 442/500 [=========================>....] - ETA: 18s - loss: 1.7948 - regression_loss: 1.5173 - classification_loss: 0.2775 443/500 [=========================>....] - ETA: 18s - loss: 1.7937 - regression_loss: 1.5165 - classification_loss: 0.2773 444/500 [=========================>....] - ETA: 18s - loss: 1.7932 - regression_loss: 1.5160 - classification_loss: 0.2772 445/500 [=========================>....] - ETA: 17s - loss: 1.7942 - regression_loss: 1.5167 - classification_loss: 0.2775 446/500 [=========================>....] - ETA: 17s - loss: 1.7937 - regression_loss: 1.5161 - classification_loss: 0.2776 447/500 [=========================>....] - ETA: 17s - loss: 1.7929 - regression_loss: 1.5153 - classification_loss: 0.2775 448/500 [=========================>....] - ETA: 16s - loss: 1.7916 - regression_loss: 1.5143 - classification_loss: 0.2773 449/500 [=========================>....] - ETA: 16s - loss: 1.7918 - regression_loss: 1.5146 - classification_loss: 0.2772 450/500 [==========================>...] - ETA: 16s - loss: 1.7905 - regression_loss: 1.5136 - classification_loss: 0.2769 451/500 [==========================>...] - ETA: 15s - loss: 1.7905 - regression_loss: 1.5138 - classification_loss: 0.2767 452/500 [==========================>...] - ETA: 15s - loss: 1.7892 - regression_loss: 1.5128 - classification_loss: 0.2764 453/500 [==========================>...] - ETA: 15s - loss: 1.7907 - regression_loss: 1.5139 - classification_loss: 0.2767 454/500 [==========================>...] - ETA: 14s - loss: 1.7907 - regression_loss: 1.5141 - classification_loss: 0.2766 455/500 [==========================>...] - ETA: 14s - loss: 1.7910 - regression_loss: 1.5144 - classification_loss: 0.2766 456/500 [==========================>...] - ETA: 14s - loss: 1.7926 - regression_loss: 1.5155 - classification_loss: 0.2771 457/500 [==========================>...] - ETA: 13s - loss: 1.7923 - regression_loss: 1.5153 - classification_loss: 0.2771 458/500 [==========================>...] - ETA: 13s - loss: 1.7924 - regression_loss: 1.5152 - classification_loss: 0.2772 459/500 [==========================>...] - ETA: 13s - loss: 1.7930 - regression_loss: 1.5159 - classification_loss: 0.2771 460/500 [==========================>...] - ETA: 13s - loss: 1.7922 - regression_loss: 1.5154 - classification_loss: 0.2768 461/500 [==========================>...] - ETA: 12s - loss: 1.7913 - regression_loss: 1.5146 - classification_loss: 0.2767 462/500 [==========================>...] - ETA: 12s - loss: 1.7926 - regression_loss: 1.5154 - classification_loss: 0.2772 463/500 [==========================>...] - ETA: 12s - loss: 1.7915 - regression_loss: 1.5145 - classification_loss: 0.2770 464/500 [==========================>...] - ETA: 11s - loss: 1.7903 - regression_loss: 1.5136 - classification_loss: 0.2767 465/500 [==========================>...] - ETA: 11s - loss: 1.7893 - regression_loss: 1.5129 - classification_loss: 0.2765 466/500 [==========================>...] - ETA: 11s - loss: 1.7881 - regression_loss: 1.5119 - classification_loss: 0.2762 467/500 [===========================>..] - ETA: 10s - loss: 1.7853 - regression_loss: 1.5095 - classification_loss: 0.2758 468/500 [===========================>..] - ETA: 10s - loss: 1.7848 - regression_loss: 1.5090 - classification_loss: 0.2758 469/500 [===========================>..] - ETA: 10s - loss: 1.7846 - regression_loss: 1.5089 - classification_loss: 0.2757 470/500 [===========================>..] - ETA: 9s - loss: 1.7857 - regression_loss: 1.5097 - classification_loss: 0.2760  471/500 [===========================>..] - ETA: 9s - loss: 1.7857 - regression_loss: 1.5099 - classification_loss: 0.2758 472/500 [===========================>..] - ETA: 9s - loss: 1.7850 - regression_loss: 1.5094 - classification_loss: 0.2756 473/500 [===========================>..] - ETA: 8s - loss: 1.7825 - regression_loss: 1.5072 - classification_loss: 0.2753 474/500 [===========================>..] - ETA: 8s - loss: 1.7826 - regression_loss: 1.5075 - classification_loss: 0.2752 475/500 [===========================>..] - ETA: 8s - loss: 1.7827 - regression_loss: 1.5076 - classification_loss: 0.2751 476/500 [===========================>..] - ETA: 7s - loss: 1.7809 - regression_loss: 1.5060 - classification_loss: 0.2749 477/500 [===========================>..] - ETA: 7s - loss: 1.7819 - regression_loss: 1.5069 - classification_loss: 0.2750 478/500 [===========================>..] - ETA: 7s - loss: 1.7802 - regression_loss: 1.5051 - classification_loss: 0.2751 479/500 [===========================>..] - ETA: 6s - loss: 1.7796 - regression_loss: 1.5046 - classification_loss: 0.2750 480/500 [===========================>..] - ETA: 6s - loss: 1.7797 - regression_loss: 1.5049 - classification_loss: 0.2748 481/500 [===========================>..] - ETA: 6s - loss: 1.7775 - regression_loss: 1.5031 - classification_loss: 0.2745 482/500 [===========================>..] - ETA: 5s - loss: 1.7771 - regression_loss: 1.5027 - classification_loss: 0.2744 483/500 [===========================>..] - ETA: 5s - loss: 1.7786 - regression_loss: 1.5040 - classification_loss: 0.2746 484/500 [============================>.] - ETA: 5s - loss: 1.7778 - regression_loss: 1.5034 - classification_loss: 0.2744 485/500 [============================>.] - ETA: 4s - loss: 1.7784 - regression_loss: 1.5041 - classification_loss: 0.2744 486/500 [============================>.] - ETA: 4s - loss: 1.7775 - regression_loss: 1.5034 - classification_loss: 0.2741 487/500 [============================>.] - ETA: 4s - loss: 1.7781 - regression_loss: 1.5040 - classification_loss: 0.2740 488/500 [============================>.] - ETA: 3s - loss: 1.7769 - regression_loss: 1.5031 - classification_loss: 0.2737 489/500 [============================>.] - ETA: 3s - loss: 1.7765 - regression_loss: 1.5029 - classification_loss: 0.2736 490/500 [============================>.] - ETA: 3s - loss: 1.7779 - regression_loss: 1.5040 - classification_loss: 0.2739 491/500 [============================>.] - ETA: 2s - loss: 1.7777 - regression_loss: 1.5039 - classification_loss: 0.2738 492/500 [============================>.] - ETA: 2s - loss: 1.7780 - regression_loss: 1.5043 - classification_loss: 0.2738 493/500 [============================>.] - ETA: 2s - loss: 1.7779 - regression_loss: 1.5042 - classification_loss: 0.2737 494/500 [============================>.] - ETA: 1s - loss: 1.7767 - regression_loss: 1.5032 - classification_loss: 0.2734 495/500 [============================>.] - ETA: 1s - loss: 1.7760 - regression_loss: 1.5027 - classification_loss: 0.2733 496/500 [============================>.] - ETA: 1s - loss: 1.7753 - regression_loss: 1.5023 - classification_loss: 0.2731 497/500 [============================>.] - ETA: 0s - loss: 1.7771 - regression_loss: 1.5033 - classification_loss: 0.2738 498/500 [============================>.] - ETA: 0s - loss: 1.7758 - regression_loss: 1.5021 - classification_loss: 0.2736 499/500 [============================>.] - ETA: 0s - loss: 1.7750 - regression_loss: 1.5016 - classification_loss: 0.2734 500/500 [==============================] - 163s 325ms/step - loss: 1.7741 - regression_loss: 1.5011 - classification_loss: 0.2731 326 instances of class plum with average precision: 0.7330 mAP: 0.7330 Epoch 00006: saving model to ./training/snapshots/resnet101_pascal_06.h5 Epoch 7/150 1/500 [..............................] - ETA: 2:34 - loss: 3.3933 - regression_loss: 2.7462 - classification_loss: 0.6471 2/500 [..............................] - ETA: 2:40 - loss: 3.1716 - regression_loss: 2.5871 - classification_loss: 0.5845 3/500 [..............................] - ETA: 2:41 - loss: 2.4045 - regression_loss: 1.9381 - classification_loss: 0.4664 4/500 [..............................] - ETA: 2:39 - loss: 2.1172 - regression_loss: 1.7273 - classification_loss: 0.3899 5/500 [..............................] - ETA: 2:39 - loss: 1.9996 - regression_loss: 1.6493 - classification_loss: 0.3503 6/500 [..............................] - ETA: 2:38 - loss: 2.0293 - regression_loss: 1.6713 - classification_loss: 0.3580 7/500 [..............................] - ETA: 2:37 - loss: 2.0592 - regression_loss: 1.6786 - classification_loss: 0.3807 8/500 [..............................] - ETA: 2:37 - loss: 1.9331 - regression_loss: 1.5856 - classification_loss: 0.3475 9/500 [..............................] - ETA: 2:38 - loss: 1.8841 - regression_loss: 1.5575 - classification_loss: 0.3265 10/500 [..............................] - ETA: 2:37 - loss: 1.8457 - regression_loss: 1.5328 - classification_loss: 0.3129 11/500 [..............................] - ETA: 2:36 - loss: 1.8537 - regression_loss: 1.5478 - classification_loss: 0.3059 12/500 [..............................] - ETA: 2:35 - loss: 1.8316 - regression_loss: 1.5361 - classification_loss: 0.2954 13/500 [..............................] - ETA: 2:35 - loss: 1.8071 - regression_loss: 1.5190 - classification_loss: 0.2880 14/500 [..............................] - ETA: 2:34 - loss: 1.8158 - regression_loss: 1.5263 - classification_loss: 0.2895 15/500 [..............................] - ETA: 2:34 - loss: 1.8291 - regression_loss: 1.5353 - classification_loss: 0.2939 16/500 [..............................] - ETA: 2:34 - loss: 1.8136 - regression_loss: 1.5271 - classification_loss: 0.2865 17/500 [>.............................] - ETA: 2:34 - loss: 1.7730 - regression_loss: 1.4932 - classification_loss: 0.2798 18/500 [>.............................] - ETA: 2:34 - loss: 1.7783 - regression_loss: 1.4945 - classification_loss: 0.2838 19/500 [>.............................] - ETA: 2:33 - loss: 1.8221 - regression_loss: 1.5294 - classification_loss: 0.2927 20/500 [>.............................] - ETA: 2:33 - loss: 1.7912 - regression_loss: 1.5065 - classification_loss: 0.2846 21/500 [>.............................] - ETA: 2:33 - loss: 1.7726 - regression_loss: 1.4954 - classification_loss: 0.2772 22/500 [>.............................] - ETA: 2:33 - loss: 1.7639 - regression_loss: 1.4881 - classification_loss: 0.2757 23/500 [>.............................] - ETA: 2:33 - loss: 1.7328 - regression_loss: 1.4626 - classification_loss: 0.2702 24/500 [>.............................] - ETA: 2:33 - loss: 1.7107 - regression_loss: 1.4458 - classification_loss: 0.2649 25/500 [>.............................] - ETA: 2:32 - loss: 1.7208 - regression_loss: 1.4468 - classification_loss: 0.2740 26/500 [>.............................] - ETA: 2:32 - loss: 1.7094 - regression_loss: 1.4380 - classification_loss: 0.2715 27/500 [>.............................] - ETA: 2:31 - loss: 1.7148 - regression_loss: 1.4419 - classification_loss: 0.2728 28/500 [>.............................] - ETA: 2:31 - loss: 1.7216 - regression_loss: 1.4436 - classification_loss: 0.2780 29/500 [>.............................] - ETA: 2:30 - loss: 1.7079 - regression_loss: 1.4323 - classification_loss: 0.2756 30/500 [>.............................] - ETA: 2:30 - loss: 1.7432 - regression_loss: 1.4629 - classification_loss: 0.2803 31/500 [>.............................] - ETA: 2:29 - loss: 1.7538 - regression_loss: 1.4720 - classification_loss: 0.2818 32/500 [>.............................] - ETA: 2:29 - loss: 1.7420 - regression_loss: 1.4632 - classification_loss: 0.2788 33/500 [>.............................] - ETA: 2:29 - loss: 1.7247 - regression_loss: 1.4489 - classification_loss: 0.2758 34/500 [=>............................] - ETA: 2:28 - loss: 1.7324 - regression_loss: 1.4538 - classification_loss: 0.2786 35/500 [=>............................] - ETA: 2:28 - loss: 1.7076 - regression_loss: 1.4340 - classification_loss: 0.2736 36/500 [=>............................] - ETA: 2:27 - loss: 1.6782 - regression_loss: 1.4101 - classification_loss: 0.2682 37/500 [=>............................] - ETA: 2:27 - loss: 1.6916 - regression_loss: 1.4197 - classification_loss: 0.2719 38/500 [=>............................] - ETA: 2:27 - loss: 1.6982 - regression_loss: 1.4256 - classification_loss: 0.2726 39/500 [=>............................] - ETA: 2:27 - loss: 1.6983 - regression_loss: 1.4271 - classification_loss: 0.2713 40/500 [=>............................] - ETA: 2:26 - loss: 1.7083 - regression_loss: 1.4340 - classification_loss: 0.2744 41/500 [=>............................] - ETA: 2:26 - loss: 1.7122 - regression_loss: 1.4367 - classification_loss: 0.2755 42/500 [=>............................] - ETA: 2:26 - loss: 1.7097 - regression_loss: 1.4358 - classification_loss: 0.2739 43/500 [=>............................] - ETA: 2:26 - loss: 1.7366 - regression_loss: 1.4586 - classification_loss: 0.2780 44/500 [=>............................] - ETA: 2:25 - loss: 1.7225 - regression_loss: 1.4473 - classification_loss: 0.2751 45/500 [=>............................] - ETA: 2:25 - loss: 1.7128 - regression_loss: 1.4404 - classification_loss: 0.2724 46/500 [=>............................] - ETA: 2:25 - loss: 1.7137 - regression_loss: 1.4403 - classification_loss: 0.2733 47/500 [=>............................] - ETA: 2:24 - loss: 1.7258 - regression_loss: 1.4497 - classification_loss: 0.2761 48/500 [=>............................] - ETA: 2:24 - loss: 1.7195 - regression_loss: 1.4451 - classification_loss: 0.2744 49/500 [=>............................] - ETA: 2:24 - loss: 1.7268 - regression_loss: 1.4505 - classification_loss: 0.2762 50/500 [==>...........................] - ETA: 2:23 - loss: 1.7330 - regression_loss: 1.4573 - classification_loss: 0.2757 51/500 [==>...........................] - ETA: 2:23 - loss: 1.7375 - regression_loss: 1.4619 - classification_loss: 0.2756 52/500 [==>...........................] - ETA: 2:23 - loss: 1.7308 - regression_loss: 1.4582 - classification_loss: 0.2726 53/500 [==>...........................] - ETA: 2:23 - loss: 1.7431 - regression_loss: 1.4697 - classification_loss: 0.2735 54/500 [==>...........................] - ETA: 2:22 - loss: 1.7576 - regression_loss: 1.4810 - classification_loss: 0.2766 55/500 [==>...........................] - ETA: 2:22 - loss: 1.7591 - regression_loss: 1.4835 - classification_loss: 0.2757 56/500 [==>...........................] - ETA: 2:22 - loss: 1.7634 - regression_loss: 1.4874 - classification_loss: 0.2760 57/500 [==>...........................] - ETA: 2:21 - loss: 1.7607 - regression_loss: 1.4861 - classification_loss: 0.2746 58/500 [==>...........................] - ETA: 2:21 - loss: 1.7479 - regression_loss: 1.4714 - classification_loss: 0.2764 59/500 [==>...........................] - ETA: 2:21 - loss: 1.7496 - regression_loss: 1.4737 - classification_loss: 0.2759 60/500 [==>...........................] - ETA: 2:21 - loss: 1.7582 - regression_loss: 1.4810 - classification_loss: 0.2772 61/500 [==>...........................] - ETA: 2:21 - loss: 1.7522 - regression_loss: 1.4756 - classification_loss: 0.2766 62/500 [==>...........................] - ETA: 2:20 - loss: 1.7382 - regression_loss: 1.4642 - classification_loss: 0.2740 63/500 [==>...........................] - ETA: 2:20 - loss: 1.7465 - regression_loss: 1.4721 - classification_loss: 0.2744 64/500 [==>...........................] - ETA: 2:20 - loss: 1.7418 - regression_loss: 1.4688 - classification_loss: 0.2730 65/500 [==>...........................] - ETA: 2:19 - loss: 1.7394 - regression_loss: 1.4671 - classification_loss: 0.2723 66/500 [==>...........................] - ETA: 2:19 - loss: 1.7462 - regression_loss: 1.4717 - classification_loss: 0.2744 67/500 [===>..........................] - ETA: 2:19 - loss: 1.7446 - regression_loss: 1.4714 - classification_loss: 0.2733 68/500 [===>..........................] - ETA: 2:18 - loss: 1.7450 - regression_loss: 1.4728 - classification_loss: 0.2722 69/500 [===>..........................] - ETA: 2:18 - loss: 1.7380 - regression_loss: 1.4675 - classification_loss: 0.2705 70/500 [===>..........................] - ETA: 2:18 - loss: 1.7366 - regression_loss: 1.4663 - classification_loss: 0.2704 71/500 [===>..........................] - ETA: 2:18 - loss: 1.7405 - regression_loss: 1.4686 - classification_loss: 0.2719 72/500 [===>..........................] - ETA: 2:17 - loss: 1.7342 - regression_loss: 1.4644 - classification_loss: 0.2698 73/500 [===>..........................] - ETA: 2:17 - loss: 1.7208 - regression_loss: 1.4531 - classification_loss: 0.2678 74/500 [===>..........................] - ETA: 2:17 - loss: 1.7223 - regression_loss: 1.4547 - classification_loss: 0.2676 75/500 [===>..........................] - ETA: 2:16 - loss: 1.7306 - regression_loss: 1.4616 - classification_loss: 0.2690 76/500 [===>..........................] - ETA: 2:16 - loss: 1.7288 - regression_loss: 1.4608 - classification_loss: 0.2680 77/500 [===>..........................] - ETA: 2:16 - loss: 1.7230 - regression_loss: 1.4566 - classification_loss: 0.2663 78/500 [===>..........................] - ETA: 2:15 - loss: 1.7092 - regression_loss: 1.4446 - classification_loss: 0.2646 79/500 [===>..........................] - ETA: 2:15 - loss: 1.7054 - regression_loss: 1.4415 - classification_loss: 0.2640 80/500 [===>..........................] - ETA: 2:15 - loss: 1.7102 - regression_loss: 1.4466 - classification_loss: 0.2636 81/500 [===>..........................] - ETA: 2:14 - loss: 1.7167 - regression_loss: 1.4504 - classification_loss: 0.2663 82/500 [===>..........................] - ETA: 2:14 - loss: 1.7224 - regression_loss: 1.4556 - classification_loss: 0.2668 83/500 [===>..........................] - ETA: 2:14 - loss: 1.7207 - regression_loss: 1.4544 - classification_loss: 0.2663 84/500 [====>.........................] - ETA: 2:13 - loss: 1.7167 - regression_loss: 1.4521 - classification_loss: 0.2646 85/500 [====>.........................] - ETA: 2:13 - loss: 1.7257 - regression_loss: 1.4604 - classification_loss: 0.2653 86/500 [====>.........................] - ETA: 2:13 - loss: 1.7272 - regression_loss: 1.4616 - classification_loss: 0.2656 87/500 [====>.........................] - ETA: 2:12 - loss: 1.7278 - regression_loss: 1.4634 - classification_loss: 0.2645 88/500 [====>.........................] - ETA: 2:12 - loss: 1.7331 - regression_loss: 1.4677 - classification_loss: 0.2654 89/500 [====>.........................] - ETA: 2:12 - loss: 1.7244 - regression_loss: 1.4577 - classification_loss: 0.2666 90/500 [====>.........................] - ETA: 2:11 - loss: 1.7182 - regression_loss: 1.4535 - classification_loss: 0.2648 91/500 [====>.........................] - ETA: 2:11 - loss: 1.7117 - regression_loss: 1.4485 - classification_loss: 0.2632 92/500 [====>.........................] - ETA: 2:11 - loss: 1.7159 - regression_loss: 1.4524 - classification_loss: 0.2635 93/500 [====>.........................] - ETA: 2:10 - loss: 1.7079 - regression_loss: 1.4461 - classification_loss: 0.2618 94/500 [====>.........................] - ETA: 2:10 - loss: 1.7094 - regression_loss: 1.4472 - classification_loss: 0.2621 95/500 [====>.........................] - ETA: 2:10 - loss: 1.7107 - regression_loss: 1.4473 - classification_loss: 0.2635 96/500 [====>.........................] - ETA: 2:09 - loss: 1.7120 - regression_loss: 1.4488 - classification_loss: 0.2631 97/500 [====>.........................] - ETA: 2:09 - loss: 1.7071 - regression_loss: 1.4441 - classification_loss: 0.2631 98/500 [====>.........................] - ETA: 2:09 - loss: 1.7127 - regression_loss: 1.4487 - classification_loss: 0.2641 99/500 [====>.........................] - ETA: 2:09 - loss: 1.7115 - regression_loss: 1.4473 - classification_loss: 0.2643 100/500 [=====>........................] - ETA: 2:08 - loss: 1.7110 - regression_loss: 1.4463 - classification_loss: 0.2647 101/500 [=====>........................] - ETA: 2:08 - loss: 1.7130 - regression_loss: 1.4487 - classification_loss: 0.2643 102/500 [=====>........................] - ETA: 2:08 - loss: 1.7059 - regression_loss: 1.4423 - classification_loss: 0.2636 103/500 [=====>........................] - ETA: 2:07 - loss: 1.7153 - regression_loss: 1.4500 - classification_loss: 0.2653 104/500 [=====>........................] - ETA: 2:07 - loss: 1.7159 - regression_loss: 1.4512 - classification_loss: 0.2647 105/500 [=====>........................] - ETA: 2:07 - loss: 1.7128 - regression_loss: 1.4487 - classification_loss: 0.2641 106/500 [=====>........................] - ETA: 2:06 - loss: 1.7110 - regression_loss: 1.4477 - classification_loss: 0.2634 107/500 [=====>........................] - ETA: 2:06 - loss: 1.7083 - regression_loss: 1.4457 - classification_loss: 0.2626 108/500 [=====>........................] - ETA: 2:05 - loss: 1.7065 - regression_loss: 1.4447 - classification_loss: 0.2619 109/500 [=====>........................] - ETA: 2:05 - loss: 1.7098 - regression_loss: 1.4466 - classification_loss: 0.2632 110/500 [=====>........................] - ETA: 2:05 - loss: 1.7153 - regression_loss: 1.4514 - classification_loss: 0.2639 111/500 [=====>........................] - ETA: 2:04 - loss: 1.7143 - regression_loss: 1.4509 - classification_loss: 0.2634 112/500 [=====>........................] - ETA: 2:04 - loss: 1.7167 - regression_loss: 1.4529 - classification_loss: 0.2639 113/500 [=====>........................] - ETA: 2:04 - loss: 1.7230 - regression_loss: 1.4583 - classification_loss: 0.2647 114/500 [=====>........................] - ETA: 2:04 - loss: 1.7223 - regression_loss: 1.4579 - classification_loss: 0.2645 115/500 [=====>........................] - ETA: 2:03 - loss: 1.7234 - regression_loss: 1.4592 - classification_loss: 0.2642 116/500 [=====>........................] - ETA: 2:03 - loss: 1.7327 - regression_loss: 1.4646 - classification_loss: 0.2681 117/500 [======>.......................] - ETA: 2:03 - loss: 1.7319 - regression_loss: 1.4644 - classification_loss: 0.2675 118/500 [======>.......................] - ETA: 2:02 - loss: 1.7302 - regression_loss: 1.4626 - classification_loss: 0.2676 119/500 [======>.......................] - ETA: 2:02 - loss: 1.7296 - regression_loss: 1.4626 - classification_loss: 0.2670 120/500 [======>.......................] - ETA: 2:02 - loss: 1.7282 - regression_loss: 1.4617 - classification_loss: 0.2665 121/500 [======>.......................] - ETA: 2:01 - loss: 1.7252 - regression_loss: 1.4595 - classification_loss: 0.2657 122/500 [======>.......................] - ETA: 2:01 - loss: 1.7260 - regression_loss: 1.4603 - classification_loss: 0.2657 123/500 [======>.......................] - ETA: 2:01 - loss: 1.7348 - regression_loss: 1.4665 - classification_loss: 0.2683 124/500 [======>.......................] - ETA: 2:00 - loss: 1.7276 - regression_loss: 1.4606 - classification_loss: 0.2670 125/500 [======>.......................] - ETA: 2:00 - loss: 1.7265 - regression_loss: 1.4597 - classification_loss: 0.2668 126/500 [======>.......................] - ETA: 2:00 - loss: 1.7236 - regression_loss: 1.4579 - classification_loss: 0.2657 127/500 [======>.......................] - ETA: 1:59 - loss: 1.7197 - regression_loss: 1.4550 - classification_loss: 0.2647 128/500 [======>.......................] - ETA: 1:59 - loss: 1.7132 - regression_loss: 1.4496 - classification_loss: 0.2637 129/500 [======>.......................] - ETA: 1:59 - loss: 1.7058 - regression_loss: 1.4432 - classification_loss: 0.2626 130/500 [======>.......................] - ETA: 1:58 - loss: 1.7031 - regression_loss: 1.4410 - classification_loss: 0.2620 131/500 [======>.......................] - ETA: 1:58 - loss: 1.7014 - regression_loss: 1.4395 - classification_loss: 0.2619 132/500 [======>.......................] - ETA: 1:58 - loss: 1.6991 - regression_loss: 1.4378 - classification_loss: 0.2613 133/500 [======>.......................] - ETA: 1:57 - loss: 1.7037 - regression_loss: 1.4411 - classification_loss: 0.2626 134/500 [=======>......................] - ETA: 1:57 - loss: 1.7040 - regression_loss: 1.4411 - classification_loss: 0.2628 135/500 [=======>......................] - ETA: 1:57 - loss: 1.7095 - regression_loss: 1.4447 - classification_loss: 0.2648 136/500 [=======>......................] - ETA: 1:56 - loss: 1.7019 - regression_loss: 1.4383 - classification_loss: 0.2635 137/500 [=======>......................] - ETA: 1:56 - loss: 1.7052 - regression_loss: 1.4406 - classification_loss: 0.2647 138/500 [=======>......................] - ETA: 1:56 - loss: 1.7067 - regression_loss: 1.4419 - classification_loss: 0.2648 139/500 [=======>......................] - ETA: 1:55 - loss: 1.7092 - regression_loss: 1.4444 - classification_loss: 0.2648 140/500 [=======>......................] - ETA: 1:55 - loss: 1.7054 - regression_loss: 1.4413 - classification_loss: 0.2641 141/500 [=======>......................] - ETA: 1:55 - loss: 1.7009 - regression_loss: 1.4370 - classification_loss: 0.2638 142/500 [=======>......................] - ETA: 1:55 - loss: 1.6985 - regression_loss: 1.4350 - classification_loss: 0.2635 143/500 [=======>......................] - ETA: 1:54 - loss: 1.7004 - regression_loss: 1.4367 - classification_loss: 0.2637 144/500 [=======>......................] - ETA: 1:54 - loss: 1.7000 - regression_loss: 1.4362 - classification_loss: 0.2638 145/500 [=======>......................] - ETA: 1:54 - loss: 1.6974 - regression_loss: 1.4333 - classification_loss: 0.2641 146/500 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[========>.....................] - ETA: 1:51 - loss: 1.7086 - regression_loss: 1.4432 - classification_loss: 0.2654 155/500 [========>.....................] - ETA: 1:51 - loss: 1.7067 - regression_loss: 1.4419 - classification_loss: 0.2648 156/500 [========>.....................] - ETA: 1:50 - loss: 1.7100 - regression_loss: 1.4452 - classification_loss: 0.2648 157/500 [========>.....................] - ETA: 1:50 - loss: 1.7124 - regression_loss: 1.4471 - classification_loss: 0.2653 158/500 [========>.....................] - ETA: 1:50 - loss: 1.7171 - regression_loss: 1.4507 - classification_loss: 0.2664 159/500 [========>.....................] - ETA: 1:49 - loss: 1.7184 - regression_loss: 1.4515 - classification_loss: 0.2669 160/500 [========>.....................] - ETA: 1:49 - loss: 1.7185 - regression_loss: 1.4517 - classification_loss: 0.2668 161/500 [========>.....................] - ETA: 1:49 - loss: 1.7158 - regression_loss: 1.4496 - classification_loss: 0.2662 162/500 [========>.....................] - ETA: 1:48 - loss: 1.7160 - regression_loss: 1.4502 - classification_loss: 0.2657 163/500 [========>.....................] - ETA: 1:48 - loss: 1.7174 - regression_loss: 1.4513 - classification_loss: 0.2661 164/500 [========>.....................] - ETA: 1:48 - loss: 1.7137 - regression_loss: 1.4485 - classification_loss: 0.2652 165/500 [========>.....................] - ETA: 1:47 - loss: 1.7139 - regression_loss: 1.4491 - classification_loss: 0.2649 166/500 [========>.....................] - ETA: 1:47 - loss: 1.7140 - regression_loss: 1.4492 - classification_loss: 0.2648 167/500 [=========>....................] - ETA: 1:47 - loss: 1.7142 - regression_loss: 1.4497 - classification_loss: 0.2645 168/500 [=========>....................] - ETA: 1:46 - loss: 1.7185 - regression_loss: 1.4533 - classification_loss: 0.2652 169/500 [=========>....................] - ETA: 1:46 - loss: 1.7148 - regression_loss: 1.4501 - classification_loss: 0.2646 170/500 [=========>....................] - ETA: 1:46 - loss: 1.7136 - regression_loss: 1.4492 - classification_loss: 0.2644 171/500 [=========>....................] - ETA: 1:45 - loss: 1.7100 - regression_loss: 1.4462 - classification_loss: 0.2638 172/500 [=========>....................] - ETA: 1:45 - loss: 1.7090 - regression_loss: 1.4456 - classification_loss: 0.2634 173/500 [=========>....................] - ETA: 1:45 - loss: 1.7037 - regression_loss: 1.4411 - classification_loss: 0.2626 174/500 [=========>....................] - ETA: 1:44 - loss: 1.7066 - regression_loss: 1.4434 - classification_loss: 0.2632 175/500 [=========>....................] - ETA: 1:44 - loss: 1.7080 - regression_loss: 1.4450 - classification_loss: 0.2630 176/500 [=========>....................] - ETA: 1:44 - loss: 1.7073 - regression_loss: 1.4448 - classification_loss: 0.2625 177/500 [=========>....................] - ETA: 1:43 - loss: 1.7065 - regression_loss: 1.4444 - classification_loss: 0.2622 178/500 [=========>....................] - ETA: 1:43 - loss: 1.7082 - regression_loss: 1.4452 - classification_loss: 0.2630 179/500 [=========>....................] - ETA: 1:43 - loss: 1.7098 - regression_loss: 1.4461 - classification_loss: 0.2637 180/500 [=========>....................] - ETA: 1:42 - loss: 1.7136 - regression_loss: 1.4485 - classification_loss: 0.2651 181/500 [=========>....................] - ETA: 1:42 - loss: 1.7136 - regression_loss: 1.4485 - classification_loss: 0.2651 182/500 [=========>....................] - ETA: 1:42 - loss: 1.7188 - regression_loss: 1.4526 - classification_loss: 0.2662 183/500 [=========>....................] - ETA: 1:42 - loss: 1.7244 - regression_loss: 1.4570 - classification_loss: 0.2674 184/500 [==========>...................] - ETA: 1:41 - loss: 1.7247 - regression_loss: 1.4575 - classification_loss: 0.2672 185/500 [==========>...................] - ETA: 1:41 - loss: 1.7276 - regression_loss: 1.4596 - classification_loss: 0.2681 186/500 [==========>...................] - ETA: 1:40 - loss: 1.7268 - regression_loss: 1.4592 - classification_loss: 0.2676 187/500 [==========>...................] - ETA: 1:40 - loss: 1.7286 - regression_loss: 1.4610 - classification_loss: 0.2677 188/500 [==========>...................] - ETA: 1:40 - loss: 1.7272 - regression_loss: 1.4600 - classification_loss: 0.2671 189/500 [==========>...................] - ETA: 1:40 - loss: 1.7286 - regression_loss: 1.4612 - classification_loss: 0.2674 190/500 [==========>...................] - ETA: 1:39 - loss: 1.7279 - regression_loss: 1.4608 - classification_loss: 0.2671 191/500 [==========>...................] - ETA: 1:39 - loss: 1.7227 - regression_loss: 1.4563 - classification_loss: 0.2664 192/500 [==========>...................] - ETA: 1:39 - loss: 1.7225 - regression_loss: 1.4563 - classification_loss: 0.2661 193/500 [==========>...................] - ETA: 1:38 - loss: 1.7223 - regression_loss: 1.4559 - classification_loss: 0.2664 194/500 [==========>...................] - ETA: 1:38 - loss: 1.7237 - regression_loss: 1.4567 - classification_loss: 0.2670 195/500 [==========>...................] - ETA: 1:38 - loss: 1.7224 - regression_loss: 1.4559 - classification_loss: 0.2665 196/500 [==========>...................] - ETA: 1:37 - loss: 1.7248 - regression_loss: 1.4576 - classification_loss: 0.2672 197/500 [==========>...................] - ETA: 1:37 - loss: 1.7256 - regression_loss: 1.4584 - classification_loss: 0.2672 198/500 [==========>...................] - ETA: 1:36 - loss: 1.7261 - regression_loss: 1.4590 - classification_loss: 0.2670 199/500 [==========>...................] - ETA: 1:36 - loss: 1.7235 - regression_loss: 1.4570 - classification_loss: 0.2666 200/500 [===========>..................] - ETA: 1:36 - loss: 1.7200 - regression_loss: 1.4542 - classification_loss: 0.2657 201/500 [===========>..................] - ETA: 1:36 - loss: 1.7214 - regression_loss: 1.4554 - classification_loss: 0.2661 202/500 [===========>..................] - ETA: 1:35 - loss: 1.7220 - regression_loss: 1.4562 - classification_loss: 0.2659 203/500 [===========>..................] - ETA: 1:35 - loss: 1.7204 - regression_loss: 1.4550 - classification_loss: 0.2654 204/500 [===========>..................] - ETA: 1:35 - loss: 1.7196 - regression_loss: 1.4540 - classification_loss: 0.2656 205/500 [===========>..................] - ETA: 1:34 - loss: 1.7180 - regression_loss: 1.4528 - classification_loss: 0.2652 206/500 [===========>..................] - ETA: 1:34 - loss: 1.7165 - regression_loss: 1.4518 - classification_loss: 0.2647 207/500 [===========>..................] - ETA: 1:34 - loss: 1.7146 - regression_loss: 1.4501 - classification_loss: 0.2645 208/500 [===========>..................] - ETA: 1:33 - loss: 1.7122 - regression_loss: 1.4483 - classification_loss: 0.2639 209/500 [===========>..................] - ETA: 1:33 - loss: 1.7101 - regression_loss: 1.4466 - classification_loss: 0.2635 210/500 [===========>..................] - ETA: 1:33 - loss: 1.7071 - regression_loss: 1.4439 - classification_loss: 0.2632 211/500 [===========>..................] - ETA: 1:32 - loss: 1.7069 - regression_loss: 1.4437 - classification_loss: 0.2633 212/500 [===========>..................] - ETA: 1:32 - loss: 1.7096 - regression_loss: 1.4458 - classification_loss: 0.2638 213/500 [===========>..................] - ETA: 1:32 - loss: 1.7102 - regression_loss: 1.4468 - classification_loss: 0.2635 214/500 [===========>..................] - ETA: 1:31 - loss: 1.7061 - regression_loss: 1.4431 - classification_loss: 0.2630 215/500 [===========>..................] - ETA: 1:31 - loss: 1.7063 - regression_loss: 1.4432 - classification_loss: 0.2631 216/500 [===========>..................] - ETA: 1:31 - loss: 1.7028 - regression_loss: 1.4403 - classification_loss: 0.2625 217/500 [============>.................] - ETA: 1:30 - loss: 1.7033 - regression_loss: 1.4408 - classification_loss: 0.2625 218/500 [============>.................] - ETA: 1:30 - loss: 1.7036 - regression_loss: 1.4411 - classification_loss: 0.2624 219/500 [============>.................] - ETA: 1:30 - loss: 1.6999 - regression_loss: 1.4380 - classification_loss: 0.2619 220/500 [============>.................] - ETA: 1:29 - loss: 1.7024 - regression_loss: 1.4399 - classification_loss: 0.2624 221/500 [============>.................] - ETA: 1:29 - loss: 1.7042 - regression_loss: 1.4418 - classification_loss: 0.2624 222/500 [============>.................] - ETA: 1:29 - loss: 1.7043 - regression_loss: 1.4422 - classification_loss: 0.2621 223/500 [============>.................] - ETA: 1:28 - loss: 1.7067 - regression_loss: 1.4440 - classification_loss: 0.2627 224/500 [============>.................] - ETA: 1:28 - loss: 1.7094 - regression_loss: 1.4463 - classification_loss: 0.2631 225/500 [============>.................] - ETA: 1:28 - loss: 1.7089 - regression_loss: 1.4461 - classification_loss: 0.2627 226/500 [============>.................] - ETA: 1:27 - loss: 1.7143 - regression_loss: 1.4508 - classification_loss: 0.2634 227/500 [============>.................] - ETA: 1:27 - loss: 1.7140 - regression_loss: 1.4510 - classification_loss: 0.2630 228/500 [============>.................] - ETA: 1:27 - loss: 1.7122 - regression_loss: 1.4495 - classification_loss: 0.2627 229/500 [============>.................] - ETA: 1:27 - loss: 1.7116 - regression_loss: 1.4493 - classification_loss: 0.2623 230/500 [============>.................] - ETA: 1:26 - loss: 1.7115 - regression_loss: 1.4495 - classification_loss: 0.2621 231/500 [============>.................] - ETA: 1:26 - loss: 1.7086 - regression_loss: 1.4470 - classification_loss: 0.2615 232/500 [============>.................] - ETA: 1:26 - loss: 1.7056 - regression_loss: 1.4445 - classification_loss: 0.2610 233/500 [============>.................] - ETA: 1:25 - loss: 1.7062 - regression_loss: 1.4449 - classification_loss: 0.2614 234/500 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[===========================>..] - ETA: 8s - loss: 1.6732 - regression_loss: 1.4187 - classification_loss: 0.2545 475/500 [===========================>..] - ETA: 8s - loss: 1.6725 - regression_loss: 1.4182 - classification_loss: 0.2544 476/500 [===========================>..] - ETA: 7s - loss: 1.6706 - regression_loss: 1.4165 - classification_loss: 0.2541 477/500 [===========================>..] - ETA: 7s - loss: 1.6696 - regression_loss: 1.4157 - classification_loss: 0.2538 478/500 [===========================>..] - ETA: 7s - loss: 1.6693 - regression_loss: 1.4156 - classification_loss: 0.2537 479/500 [===========================>..] - ETA: 6s - loss: 1.6698 - regression_loss: 1.4160 - classification_loss: 0.2538 480/500 [===========================>..] - ETA: 6s - loss: 1.6713 - regression_loss: 1.4172 - classification_loss: 0.2541 481/500 [===========================>..] - ETA: 6s - loss: 1.6712 - regression_loss: 1.4170 - classification_loss: 0.2542 482/500 [===========================>..] - ETA: 5s - loss: 1.6732 - regression_loss: 1.4183 - classification_loss: 0.2549 483/500 [===========================>..] - ETA: 5s - loss: 1.6726 - regression_loss: 1.4179 - classification_loss: 0.2547 484/500 [============================>.] - ETA: 5s - loss: 1.6726 - regression_loss: 1.4180 - classification_loss: 0.2546 485/500 [============================>.] - ETA: 4s - loss: 1.6705 - regression_loss: 1.4162 - classification_loss: 0.2543 486/500 [============================>.] - ETA: 4s - loss: 1.6693 - regression_loss: 1.4152 - classification_loss: 0.2541 487/500 [============================>.] - ETA: 4s - loss: 1.6704 - regression_loss: 1.4161 - classification_loss: 0.2543 488/500 [============================>.] - ETA: 3s - loss: 1.6735 - regression_loss: 1.4188 - classification_loss: 0.2547 489/500 [============================>.] - ETA: 3s - loss: 1.6747 - regression_loss: 1.4198 - classification_loss: 0.2549 490/500 [============================>.] - ETA: 3s - loss: 1.6739 - regression_loss: 1.4192 - classification_loss: 0.2547 491/500 [============================>.] - ETA: 2s - loss: 1.6747 - regression_loss: 1.4197 - classification_loss: 0.2549 492/500 [============================>.] - ETA: 2s - loss: 1.6749 - regression_loss: 1.4199 - classification_loss: 0.2549 493/500 [============================>.] - ETA: 2s - loss: 1.6736 - regression_loss: 1.4188 - classification_loss: 0.2548 494/500 [============================>.] - ETA: 1s - loss: 1.6735 - regression_loss: 1.4187 - classification_loss: 0.2548 495/500 [============================>.] - ETA: 1s - loss: 1.6727 - regression_loss: 1.4180 - classification_loss: 0.2546 496/500 [============================>.] - ETA: 1s - loss: 1.6723 - regression_loss: 1.4178 - classification_loss: 0.2545 497/500 [============================>.] - ETA: 0s - loss: 1.6719 - regression_loss: 1.4175 - classification_loss: 0.2543 498/500 [============================>.] - ETA: 0s - loss: 1.6741 - regression_loss: 1.4193 - classification_loss: 0.2548 499/500 [============================>.] - ETA: 0s - loss: 1.6737 - regression_loss: 1.4191 - classification_loss: 0.2547 500/500 [==============================] - 161s 322ms/step - loss: 1.6744 - regression_loss: 1.4196 - classification_loss: 0.2548 326 instances of class plum with average precision: 0.7867 mAP: 0.7867 Epoch 00007: saving model to ./training/snapshots/resnet101_pascal_07.h5 Epoch 8/150 1/500 [..............................] - ETA: 2:35 - loss: 0.9444 - regression_loss: 0.7855 - classification_loss: 0.1589 2/500 [..............................] - ETA: 2:42 - loss: 0.9214 - regression_loss: 0.7913 - classification_loss: 0.1301 3/500 [..............................] - ETA: 2:42 - loss: 1.5287 - regression_loss: 1.2764 - classification_loss: 0.2523 4/500 [..............................] - ETA: 2:39 - loss: 1.6726 - regression_loss: 1.3785 - classification_loss: 0.2941 5/500 [..............................] - ETA: 2:39 - loss: 1.5820 - regression_loss: 1.3161 - classification_loss: 0.2659 6/500 [..............................] - ETA: 2:41 - loss: 1.7031 - regression_loss: 1.4297 - classification_loss: 0.2734 7/500 [..............................] - ETA: 2:40 - loss: 1.6375 - regression_loss: 1.3792 - classification_loss: 0.2583 8/500 [..............................] - ETA: 2:39 - loss: 1.6434 - regression_loss: 1.3863 - classification_loss: 0.2571 9/500 [..............................] - ETA: 2:39 - loss: 1.7243 - regression_loss: 1.4432 - classification_loss: 0.2811 10/500 [..............................] - ETA: 2:39 - loss: 1.6710 - regression_loss: 1.4051 - classification_loss: 0.2659 11/500 [..............................] - ETA: 2:38 - loss: 1.6424 - regression_loss: 1.3780 - classification_loss: 0.2644 12/500 [..............................] - ETA: 2:38 - loss: 1.6380 - regression_loss: 1.3803 - classification_loss: 0.2577 13/500 [..............................] - ETA: 2:38 - loss: 1.6400 - regression_loss: 1.3873 - classification_loss: 0.2527 14/500 [..............................] - ETA: 2:38 - loss: 1.6493 - regression_loss: 1.3963 - classification_loss: 0.2530 15/500 [..............................] - ETA: 2:37 - loss: 1.6518 - regression_loss: 1.4023 - classification_loss: 0.2495 16/500 [..............................] - ETA: 2:36 - loss: 1.6500 - regression_loss: 1.3998 - classification_loss: 0.2502 17/500 [>.............................] - ETA: 2:36 - loss: 1.6737 - regression_loss: 1.4150 - classification_loss: 0.2587 18/500 [>.............................] - ETA: 2:36 - loss: 1.6540 - regression_loss: 1.3986 - classification_loss: 0.2554 19/500 [>.............................] - ETA: 2:36 - loss: 1.6248 - regression_loss: 1.3742 - classification_loss: 0.2507 20/500 [>.............................] - ETA: 2:35 - loss: 1.6206 - regression_loss: 1.3677 - classification_loss: 0.2529 21/500 [>.............................] - ETA: 2:34 - loss: 1.5856 - regression_loss: 1.3389 - classification_loss: 0.2467 22/500 [>.............................] - ETA: 2:34 - loss: 1.5889 - regression_loss: 1.3397 - classification_loss: 0.2492 23/500 [>.............................] - ETA: 2:34 - loss: 1.5748 - regression_loss: 1.3297 - classification_loss: 0.2451 24/500 [>.............................] - ETA: 2:33 - loss: 1.5319 - regression_loss: 1.2929 - classification_loss: 0.2390 25/500 [>.............................] - ETA: 2:33 - loss: 1.5526 - regression_loss: 1.3079 - classification_loss: 0.2447 26/500 [>.............................] - ETA: 2:32 - loss: 1.5597 - regression_loss: 1.3139 - classification_loss: 0.2458 27/500 [>.............................] - ETA: 2:32 - loss: 1.5501 - regression_loss: 1.3053 - classification_loss: 0.2448 28/500 [>.............................] - ETA: 2:31 - loss: 1.5301 - regression_loss: 1.2881 - classification_loss: 0.2421 29/500 [>.............................] - ETA: 2:31 - loss: 1.5246 - regression_loss: 1.2853 - classification_loss: 0.2392 30/500 [>.............................] - ETA: 2:31 - loss: 1.5358 - regression_loss: 1.2961 - classification_loss: 0.2397 31/500 [>.............................] - ETA: 2:31 - loss: 1.5142 - regression_loss: 1.2793 - classification_loss: 0.2349 32/500 [>.............................] - ETA: 2:31 - loss: 1.5002 - regression_loss: 1.2692 - classification_loss: 0.2310 33/500 [>.............................] - ETA: 2:30 - loss: 1.5025 - regression_loss: 1.2732 - classification_loss: 0.2293 34/500 [=>............................] - ETA: 2:30 - loss: 1.4916 - regression_loss: 1.2653 - classification_loss: 0.2262 35/500 [=>............................] - ETA: 2:30 - loss: 1.4785 - regression_loss: 1.2544 - classification_loss: 0.2240 36/500 [=>............................] - ETA: 2:30 - loss: 1.5000 - regression_loss: 1.2705 - classification_loss: 0.2294 37/500 [=>............................] - ETA: 2:29 - loss: 1.5045 - regression_loss: 1.2757 - classification_loss: 0.2287 38/500 [=>............................] - ETA: 2:29 - loss: 1.5076 - regression_loss: 1.2795 - classification_loss: 0.2280 39/500 [=>............................] - ETA: 2:28 - loss: 1.4963 - regression_loss: 1.2710 - classification_loss: 0.2252 40/500 [=>............................] - ETA: 2:28 - loss: 1.5011 - regression_loss: 1.2756 - classification_loss: 0.2255 41/500 [=>............................] - ETA: 2:28 - loss: 1.5045 - regression_loss: 1.2776 - classification_loss: 0.2269 42/500 [=>............................] - ETA: 2:28 - loss: 1.4897 - regression_loss: 1.2652 - classification_loss: 0.2244 43/500 [=>............................] - ETA: 2:27 - loss: 1.4936 - regression_loss: 1.2691 - classification_loss: 0.2245 44/500 [=>............................] - ETA: 2:27 - loss: 1.4981 - regression_loss: 1.2725 - classification_loss: 0.2256 45/500 [=>............................] - ETA: 2:27 - loss: 1.4851 - regression_loss: 1.2616 - classification_loss: 0.2235 46/500 [=>............................] - ETA: 2:26 - loss: 1.4800 - regression_loss: 1.2574 - classification_loss: 0.2226 47/500 [=>............................] - ETA: 2:26 - loss: 1.4798 - regression_loss: 1.2578 - classification_loss: 0.2221 48/500 [=>............................] - ETA: 2:26 - loss: 1.4652 - regression_loss: 1.2458 - classification_loss: 0.2194 49/500 [=>............................] - ETA: 2:25 - loss: 1.4697 - regression_loss: 1.2487 - classification_loss: 0.2210 50/500 [==>...........................] - ETA: 2:25 - loss: 1.4782 - regression_loss: 1.2558 - classification_loss: 0.2223 51/500 [==>...........................] - ETA: 2:25 - loss: 1.4807 - regression_loss: 1.2590 - classification_loss: 0.2217 52/500 [==>...........................] - ETA: 2:25 - loss: 1.4758 - regression_loss: 1.2548 - classification_loss: 0.2210 53/500 [==>...........................] - ETA: 2:24 - loss: 1.4806 - regression_loss: 1.2591 - classification_loss: 0.2215 54/500 [==>...........................] - ETA: 2:24 - loss: 1.4943 - regression_loss: 1.2699 - classification_loss: 0.2244 55/500 [==>...........................] - ETA: 2:23 - loss: 1.5000 - regression_loss: 1.2743 - classification_loss: 0.2256 56/500 [==>...........................] - ETA: 2:23 - loss: 1.5008 - regression_loss: 1.2750 - classification_loss: 0.2258 57/500 [==>...........................] - ETA: 2:22 - loss: 1.5167 - regression_loss: 1.2886 - classification_loss: 0.2281 58/500 [==>...........................] - ETA: 2:22 - loss: 1.5191 - regression_loss: 1.2910 - classification_loss: 0.2280 59/500 [==>...........................] - ETA: 2:22 - loss: 1.5135 - regression_loss: 1.2869 - classification_loss: 0.2266 60/500 [==>...........................] - ETA: 2:21 - loss: 1.5063 - regression_loss: 1.2780 - classification_loss: 0.2284 61/500 [==>...........................] - ETA: 2:21 - loss: 1.5066 - regression_loss: 1.2785 - classification_loss: 0.2281 62/500 [==>...........................] - ETA: 2:21 - loss: 1.5046 - regression_loss: 1.2779 - classification_loss: 0.2268 63/500 [==>...........................] - ETA: 2:20 - loss: 1.4971 - regression_loss: 1.2719 - classification_loss: 0.2251 64/500 [==>...........................] - ETA: 2:20 - loss: 1.5006 - regression_loss: 1.2753 - classification_loss: 0.2253 65/500 [==>...........................] - ETA: 2:20 - loss: 1.5092 - regression_loss: 1.2833 - classification_loss: 0.2260 66/500 [==>...........................] - ETA: 2:20 - loss: 1.5026 - regression_loss: 1.2772 - classification_loss: 0.2254 67/500 [===>..........................] - ETA: 2:20 - loss: 1.5071 - regression_loss: 1.2825 - classification_loss: 0.2247 68/500 [===>..........................] - ETA: 2:19 - loss: 1.5032 - regression_loss: 1.2795 - classification_loss: 0.2237 69/500 [===>..........................] - ETA: 2:19 - loss: 1.5137 - regression_loss: 1.2887 - classification_loss: 0.2251 70/500 [===>..........................] - ETA: 2:19 - loss: 1.5137 - regression_loss: 1.2881 - classification_loss: 0.2256 71/500 [===>..........................] - ETA: 2:19 - loss: 1.5118 - regression_loss: 1.2872 - classification_loss: 0.2246 72/500 [===>..........................] - ETA: 2:18 - loss: 1.5106 - regression_loss: 1.2862 - classification_loss: 0.2244 73/500 [===>..........................] - ETA: 2:18 - loss: 1.5141 - regression_loss: 1.2883 - classification_loss: 0.2258 74/500 [===>..........................] - ETA: 2:18 - loss: 1.5219 - regression_loss: 1.2952 - classification_loss: 0.2267 75/500 [===>..........................] - ETA: 2:17 - loss: 1.5309 - regression_loss: 1.3019 - classification_loss: 0.2290 76/500 [===>..........................] - ETA: 2:17 - loss: 1.5355 - regression_loss: 1.3053 - classification_loss: 0.2302 77/500 [===>..........................] - ETA: 2:16 - loss: 1.5404 - regression_loss: 1.3092 - classification_loss: 0.2311 78/500 [===>..........................] - ETA: 2:16 - loss: 1.5368 - regression_loss: 1.3069 - classification_loss: 0.2299 79/500 [===>..........................] - ETA: 2:16 - loss: 1.5405 - regression_loss: 1.3107 - classification_loss: 0.2298 80/500 [===>..........................] - ETA: 2:15 - loss: 1.5392 - regression_loss: 1.3103 - classification_loss: 0.2289 81/500 [===>..........................] - ETA: 2:15 - loss: 1.5422 - regression_loss: 1.3136 - classification_loss: 0.2286 82/500 [===>..........................] - ETA: 2:15 - loss: 1.5483 - regression_loss: 1.3184 - classification_loss: 0.2298 83/500 [===>..........................] - ETA: 2:14 - loss: 1.5561 - regression_loss: 1.3235 - classification_loss: 0.2326 84/500 [====>.........................] - ETA: 2:14 - loss: 1.5486 - regression_loss: 1.3174 - classification_loss: 0.2312 85/500 [====>.........................] - ETA: 2:14 - loss: 1.5568 - regression_loss: 1.3243 - classification_loss: 0.2325 86/500 [====>.........................] - ETA: 2:13 - loss: 1.5564 - regression_loss: 1.3245 - classification_loss: 0.2319 87/500 [====>.........................] - ETA: 2:13 - loss: 1.5528 - regression_loss: 1.3175 - classification_loss: 0.2353 88/500 [====>.........................] - ETA: 2:13 - loss: 1.5591 - regression_loss: 1.3231 - classification_loss: 0.2360 89/500 [====>.........................] - ETA: 2:13 - loss: 1.5551 - regression_loss: 1.3202 - classification_loss: 0.2349 90/500 [====>.........................] - ETA: 2:12 - loss: 1.5673 - regression_loss: 1.3286 - classification_loss: 0.2387 91/500 [====>.........................] - ETA: 2:12 - loss: 1.5739 - regression_loss: 1.3339 - classification_loss: 0.2400 92/500 [====>.........................] - ETA: 2:12 - loss: 1.5786 - regression_loss: 1.3377 - classification_loss: 0.2409 93/500 [====>.........................] - ETA: 2:11 - loss: 1.5821 - regression_loss: 1.3404 - classification_loss: 0.2416 94/500 [====>.........................] - ETA: 2:11 - loss: 1.5807 - regression_loss: 1.3397 - classification_loss: 0.2411 95/500 [====>.........................] - ETA: 2:11 - loss: 1.5804 - regression_loss: 1.3395 - classification_loss: 0.2408 96/500 [====>.........................] - ETA: 2:10 - loss: 1.5842 - regression_loss: 1.3419 - classification_loss: 0.2423 97/500 [====>.........................] - ETA: 2:10 - loss: 1.5845 - regression_loss: 1.3421 - classification_loss: 0.2424 98/500 [====>.........................] - ETA: 2:10 - loss: 1.5821 - regression_loss: 1.3402 - classification_loss: 0.2419 99/500 [====>.........................] - ETA: 2:09 - loss: 1.5870 - regression_loss: 1.3439 - classification_loss: 0.2431 100/500 [=====>........................] - ETA: 2:09 - loss: 1.5844 - regression_loss: 1.3420 - classification_loss: 0.2425 101/500 [=====>........................] - ETA: 2:09 - loss: 1.5866 - regression_loss: 1.3438 - classification_loss: 0.2428 102/500 [=====>........................] - ETA: 2:08 - loss: 1.5820 - regression_loss: 1.3400 - classification_loss: 0.2420 103/500 [=====>........................] - ETA: 2:08 - loss: 1.5785 - regression_loss: 1.3373 - classification_loss: 0.2412 104/500 [=====>........................] - ETA: 2:08 - loss: 1.5791 - regression_loss: 1.3379 - classification_loss: 0.2411 105/500 [=====>........................] - ETA: 2:07 - loss: 1.5798 - regression_loss: 1.3390 - classification_loss: 0.2408 106/500 [=====>........................] - ETA: 2:07 - loss: 1.5922 - regression_loss: 1.3489 - classification_loss: 0.2433 107/500 [=====>........................] - ETA: 2:07 - loss: 1.5931 - regression_loss: 1.3498 - classification_loss: 0.2433 108/500 [=====>........................] - ETA: 2:06 - loss: 1.5981 - regression_loss: 1.3537 - classification_loss: 0.2444 109/500 [=====>........................] - ETA: 2:06 - loss: 1.6023 - regression_loss: 1.3578 - classification_loss: 0.2445 110/500 [=====>........................] - ETA: 2:06 - loss: 1.6156 - regression_loss: 1.3658 - classification_loss: 0.2497 111/500 [=====>........................] - ETA: 2:05 - loss: 1.6172 - regression_loss: 1.3674 - classification_loss: 0.2498 112/500 [=====>........................] - ETA: 2:05 - loss: 1.6207 - regression_loss: 1.3705 - classification_loss: 0.2502 113/500 [=====>........................] - ETA: 2:05 - loss: 1.6153 - regression_loss: 1.3663 - classification_loss: 0.2489 114/500 [=====>........................] - ETA: 2:04 - loss: 1.6112 - regression_loss: 1.3633 - classification_loss: 0.2479 115/500 [=====>........................] - ETA: 2:04 - loss: 1.6125 - regression_loss: 1.3641 - classification_loss: 0.2485 116/500 [=====>........................] - ETA: 2:04 - loss: 1.6172 - regression_loss: 1.3674 - classification_loss: 0.2499 117/500 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[===========>..................] - ETA: 1:35 - loss: 1.6059 - regression_loss: 1.3612 - classification_loss: 0.2447 206/500 [===========>..................] - ETA: 1:35 - loss: 1.6082 - regression_loss: 1.3629 - classification_loss: 0.2453 207/500 [===========>..................] - ETA: 1:34 - loss: 1.6051 - regression_loss: 1.3603 - classification_loss: 0.2447 208/500 [===========>..................] - ETA: 1:34 - loss: 1.6054 - regression_loss: 1.3606 - classification_loss: 0.2448 209/500 [===========>..................] - ETA: 1:34 - loss: 1.6027 - regression_loss: 1.3584 - classification_loss: 0.2443 210/500 [===========>..................] - ETA: 1:33 - loss: 1.6023 - regression_loss: 1.3579 - classification_loss: 0.2444 211/500 [===========>..................] - ETA: 1:33 - loss: 1.6036 - regression_loss: 1.3588 - classification_loss: 0.2449 212/500 [===========>..................] - ETA: 1:33 - loss: 1.6050 - regression_loss: 1.3598 - classification_loss: 0.2453 213/500 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[============>.................] - ETA: 1:30 - loss: 1.6080 - regression_loss: 1.3615 - classification_loss: 0.2464 222/500 [============>.................] - ETA: 1:29 - loss: 1.6059 - regression_loss: 1.3599 - classification_loss: 0.2460 223/500 [============>.................] - ETA: 1:29 - loss: 1.6058 - regression_loss: 1.3597 - classification_loss: 0.2461 224/500 [============>.................] - ETA: 1:29 - loss: 1.6035 - regression_loss: 1.3580 - classification_loss: 0.2455 225/500 [============>.................] - ETA: 1:28 - loss: 1.6042 - regression_loss: 1.3582 - classification_loss: 0.2460 226/500 [============>.................] - ETA: 1:28 - loss: 1.6017 - regression_loss: 1.3558 - classification_loss: 0.2459 227/500 [============>.................] - ETA: 1:28 - loss: 1.6042 - regression_loss: 1.3578 - classification_loss: 0.2464 228/500 [============>.................] - ETA: 1:27 - loss: 1.6008 - regression_loss: 1.3551 - classification_loss: 0.2458 229/500 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[==============>...............] - ETA: 1:19 - loss: 1.5960 - regression_loss: 1.3518 - classification_loss: 0.2442 254/500 [==============>...............] - ETA: 1:19 - loss: 1.5972 - regression_loss: 1.3528 - classification_loss: 0.2444 255/500 [==============>...............] - ETA: 1:19 - loss: 1.5955 - regression_loss: 1.3517 - classification_loss: 0.2438 256/500 [==============>...............] - ETA: 1:18 - loss: 1.5936 - regression_loss: 1.3503 - classification_loss: 0.2433 257/500 [==============>...............] - ETA: 1:18 - loss: 1.5933 - regression_loss: 1.3501 - classification_loss: 0.2432 258/500 [==============>...............] - ETA: 1:18 - loss: 1.5915 - regression_loss: 1.3486 - classification_loss: 0.2430 259/500 [==============>...............] - ETA: 1:17 - loss: 1.5917 - regression_loss: 1.3484 - classification_loss: 0.2433 260/500 [==============>...............] - ETA: 1:17 - loss: 1.5913 - regression_loss: 1.3480 - classification_loss: 0.2433 261/500 [==============>...............] - ETA: 1:17 - loss: 1.5928 - regression_loss: 1.3494 - classification_loss: 0.2434 262/500 [==============>...............] - ETA: 1:17 - loss: 1.5947 - regression_loss: 1.3509 - classification_loss: 0.2438 263/500 [==============>...............] - ETA: 1:16 - loss: 1.5942 - regression_loss: 1.3505 - classification_loss: 0.2437 264/500 [==============>...............] - ETA: 1:16 - loss: 1.5950 - regression_loss: 1.3513 - classification_loss: 0.2437 265/500 [==============>...............] - ETA: 1:16 - loss: 1.5983 - regression_loss: 1.3541 - classification_loss: 0.2442 266/500 [==============>...............] - ETA: 1:15 - loss: 1.5998 - regression_loss: 1.3555 - classification_loss: 0.2443 267/500 [===============>..............] - ETA: 1:15 - loss: 1.6006 - regression_loss: 1.3561 - classification_loss: 0.2445 268/500 [===============>..............] - ETA: 1:15 - loss: 1.5984 - regression_loss: 1.3545 - classification_loss: 0.2440 269/500 [===============>..............] - ETA: 1:14 - loss: 1.5991 - regression_loss: 1.3545 - classification_loss: 0.2446 270/500 [===============>..............] - ETA: 1:14 - loss: 1.5959 - regression_loss: 1.3519 - classification_loss: 0.2440 271/500 [===============>..............] - ETA: 1:14 - loss: 1.5960 - regression_loss: 1.3519 - classification_loss: 0.2440 272/500 [===============>..............] - ETA: 1:13 - loss: 1.5970 - regression_loss: 1.3526 - classification_loss: 0.2444 273/500 [===============>..............] - ETA: 1:13 - loss: 1.5966 - regression_loss: 1.3522 - classification_loss: 0.2444 274/500 [===============>..............] - ETA: 1:13 - loss: 1.5946 - regression_loss: 1.3506 - classification_loss: 0.2440 275/500 [===============>..............] - ETA: 1:12 - loss: 1.5964 - regression_loss: 1.3521 - classification_loss: 0.2444 276/500 [===============>..............] - ETA: 1:12 - loss: 1.5936 - regression_loss: 1.3498 - classification_loss: 0.2438 277/500 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[============================>.] - ETA: 2s - loss: 1.5574 - regression_loss: 1.3210 - classification_loss: 0.2364 494/500 [============================>.] - ETA: 1s - loss: 1.5572 - regression_loss: 1.3209 - classification_loss: 0.2363 495/500 [============================>.] - ETA: 1s - loss: 1.5579 - regression_loss: 1.3216 - classification_loss: 0.2362 496/500 [============================>.] - ETA: 1s - loss: 1.5569 - regression_loss: 1.3209 - classification_loss: 0.2360 497/500 [============================>.] - ETA: 0s - loss: 1.5570 - regression_loss: 1.3210 - classification_loss: 0.2360 498/500 [============================>.] - ETA: 0s - loss: 1.5572 - regression_loss: 1.3212 - classification_loss: 0.2360 499/500 [============================>.] - ETA: 0s - loss: 1.5576 - regression_loss: 1.3214 - classification_loss: 0.2362 500/500 [==============================] - 162s 324ms/step - loss: 1.5568 - regression_loss: 1.3208 - classification_loss: 0.2360 326 instances of class plum with average precision: 0.7635 mAP: 0.7635 Epoch 00008: saving model to ./training/snapshots/resnet101_pascal_08.h5 Epoch 9/150 1/500 [..............................] - ETA: 2:33 - loss: 2.1123 - regression_loss: 1.7902 - classification_loss: 0.3221 2/500 [..............................] - ETA: 2:33 - loss: 2.0941 - regression_loss: 1.6653 - classification_loss: 0.4289 3/500 [..............................] - ETA: 2:34 - loss: 1.9861 - regression_loss: 1.6207 - classification_loss: 0.3654 4/500 [..............................] - ETA: 2:35 - loss: 1.8327 - regression_loss: 1.5080 - classification_loss: 0.3247 5/500 [..............................] - ETA: 2:38 - loss: 1.6935 - regression_loss: 1.4043 - classification_loss: 0.2891 6/500 [..............................] - ETA: 2:38 - loss: 1.6980 - regression_loss: 1.4099 - classification_loss: 0.2881 7/500 [..............................] - ETA: 2:38 - loss: 1.7429 - regression_loss: 1.4478 - classification_loss: 0.2952 8/500 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[=====>........................] - ETA: 2:06 - loss: 1.4107 - regression_loss: 1.1981 - classification_loss: 0.2126 105/500 [=====>........................] - ETA: 2:06 - loss: 1.4123 - regression_loss: 1.1991 - classification_loss: 0.2132 106/500 [=====>........................] - ETA: 2:06 - loss: 1.4109 - regression_loss: 1.1981 - classification_loss: 0.2129 107/500 [=====>........................] - ETA: 2:05 - loss: 1.4084 - regression_loss: 1.1958 - classification_loss: 0.2126 108/500 [=====>........................] - ETA: 2:05 - loss: 1.4043 - regression_loss: 1.1925 - classification_loss: 0.2119 109/500 [=====>........................] - ETA: 2:05 - loss: 1.4100 - regression_loss: 1.1968 - classification_loss: 0.2132 110/500 [=====>........................] - ETA: 2:04 - loss: 1.4130 - regression_loss: 1.1992 - classification_loss: 0.2138 111/500 [=====>........................] - ETA: 2:04 - loss: 1.4130 - regression_loss: 1.1994 - classification_loss: 0.2135 112/500 [=====>........................] - ETA: 2:04 - loss: 1.4165 - regression_loss: 1.2029 - classification_loss: 0.2136 113/500 [=====>........................] - ETA: 2:03 - loss: 1.4194 - regression_loss: 1.2054 - classification_loss: 0.2140 114/500 [=====>........................] - ETA: 2:03 - loss: 1.4225 - regression_loss: 1.2081 - classification_loss: 0.2145 115/500 [=====>........................] - ETA: 2:03 - loss: 1.4223 - regression_loss: 1.2080 - classification_loss: 0.2143 116/500 [=====>........................] - ETA: 2:02 - loss: 1.4326 - regression_loss: 1.2150 - classification_loss: 0.2177 117/500 [======>.......................] - ETA: 2:02 - loss: 1.4330 - regression_loss: 1.2158 - classification_loss: 0.2172 118/500 [======>.......................] - ETA: 2:02 - loss: 1.4340 - regression_loss: 1.2166 - classification_loss: 0.2175 119/500 [======>.......................] - ETA: 2:02 - loss: 1.4392 - regression_loss: 1.2215 - classification_loss: 0.2177 120/500 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[===========================>..] - ETA: 6s - loss: 1.4823 - regression_loss: 1.2597 - classification_loss: 0.2226 481/500 [===========================>..] - ETA: 6s - loss: 1.4821 - regression_loss: 1.2597 - classification_loss: 0.2225 482/500 [===========================>..] - ETA: 5s - loss: 1.4814 - regression_loss: 1.2590 - classification_loss: 0.2223 483/500 [===========================>..] - ETA: 5s - loss: 1.4808 - regression_loss: 1.2586 - classification_loss: 0.2222 484/500 [============================>.] - ETA: 5s - loss: 1.4792 - regression_loss: 1.2572 - classification_loss: 0.2220 485/500 [============================>.] - ETA: 4s - loss: 1.4781 - regression_loss: 1.2563 - classification_loss: 0.2218 486/500 [============================>.] - ETA: 4s - loss: 1.4766 - regression_loss: 1.2551 - classification_loss: 0.2215 487/500 [============================>.] - ETA: 4s - loss: 1.4751 - regression_loss: 1.2538 - classification_loss: 0.2212 488/500 [============================>.] - ETA: 3s - loss: 1.4741 - regression_loss: 1.2530 - classification_loss: 0.2210 489/500 [============================>.] - ETA: 3s - loss: 1.4738 - regression_loss: 1.2528 - classification_loss: 0.2210 490/500 [============================>.] - ETA: 3s - loss: 1.4734 - regression_loss: 1.2526 - classification_loss: 0.2208 491/500 [============================>.] - ETA: 2s - loss: 1.4730 - regression_loss: 1.2522 - classification_loss: 0.2208 492/500 [============================>.] - ETA: 2s - loss: 1.4740 - regression_loss: 1.2529 - classification_loss: 0.2211 493/500 [============================>.] - ETA: 2s - loss: 1.4734 - regression_loss: 1.2525 - classification_loss: 0.2209 494/500 [============================>.] - ETA: 1s - loss: 1.4741 - regression_loss: 1.2530 - classification_loss: 0.2211 495/500 [============================>.] - ETA: 1s - loss: 1.4744 - regression_loss: 1.2533 - classification_loss: 0.2211 496/500 [============================>.] - ETA: 1s - loss: 1.4733 - regression_loss: 1.2523 - classification_loss: 0.2209 497/500 [============================>.] - ETA: 0s - loss: 1.4719 - regression_loss: 1.2512 - classification_loss: 0.2207 498/500 [============================>.] - ETA: 0s - loss: 1.4720 - regression_loss: 1.2514 - classification_loss: 0.2207 499/500 [============================>.] - ETA: 0s - loss: 1.4708 - regression_loss: 1.2503 - classification_loss: 0.2205 500/500 [==============================] - 161s 322ms/step - loss: 1.4719 - regression_loss: 1.2512 - classification_loss: 0.2207 326 instances of class plum with average precision: 0.7755 mAP: 0.7755 Epoch 00009: saving model to ./training/snapshots/resnet101_pascal_09.h5 Epoch 10/150 1/500 [..............................] - ETA: 2:36 - loss: 2.0269 - regression_loss: 1.6299 - classification_loss: 0.3970 2/500 [..............................] - ETA: 2:36 - loss: 1.4733 - regression_loss: 1.2346 - classification_loss: 0.2387 3/500 [..............................] - ETA: 2:36 - loss: 1.6880 - regression_loss: 1.3979 - classification_loss: 0.2902 4/500 [..............................] - ETA: 2:36 - loss: 1.7787 - regression_loss: 1.4865 - classification_loss: 0.2922 5/500 [..............................] - ETA: 2:34 - loss: 1.7802 - regression_loss: 1.4672 - classification_loss: 0.3130 6/500 [..............................] - ETA: 2:33 - loss: 1.7125 - regression_loss: 1.4359 - classification_loss: 0.2766 7/500 [..............................] - ETA: 2:35 - loss: 1.6861 - regression_loss: 1.4220 - classification_loss: 0.2640 8/500 [..............................] - ETA: 2:34 - loss: 1.6836 - regression_loss: 1.4254 - classification_loss: 0.2582 9/500 [..............................] - ETA: 2:34 - loss: 1.5511 - regression_loss: 1.3138 - classification_loss: 0.2373 10/500 [..............................] - ETA: 2:33 - loss: 1.5979 - regression_loss: 1.3552 - classification_loss: 0.2427 11/500 [..............................] - ETA: 2:33 - loss: 1.5507 - regression_loss: 1.3136 - classification_loss: 0.2371 12/500 [..............................] - ETA: 2:32 - loss: 1.5947 - regression_loss: 1.3472 - classification_loss: 0.2475 13/500 [..............................] - ETA: 2:33 - loss: 1.6539 - regression_loss: 1.3973 - classification_loss: 0.2566 14/500 [..............................] - ETA: 2:33 - loss: 1.6211 - regression_loss: 1.3695 - classification_loss: 0.2515 15/500 [..............................] - ETA: 2:33 - loss: 1.6036 - regression_loss: 1.3545 - classification_loss: 0.2491 16/500 [..............................] - ETA: 2:33 - loss: 1.5924 - regression_loss: 1.3473 - classification_loss: 0.2451 17/500 [>.............................] - ETA: 2:34 - loss: 1.5852 - regression_loss: 1.3407 - classification_loss: 0.2444 18/500 [>.............................] - ETA: 2:33 - loss: 1.6056 - regression_loss: 1.3567 - classification_loss: 0.2489 19/500 [>.............................] - ETA: 2:33 - loss: 1.5881 - regression_loss: 1.3436 - classification_loss: 0.2445 20/500 [>.............................] - ETA: 2:33 - loss: 1.5806 - regression_loss: 1.3402 - classification_loss: 0.2404 21/500 [>.............................] - ETA: 2:33 - loss: 1.5745 - regression_loss: 1.3364 - classification_loss: 0.2381 22/500 [>.............................] - ETA: 2:32 - loss: 1.5483 - regression_loss: 1.3131 - classification_loss: 0.2352 23/500 [>.............................] - ETA: 2:32 - loss: 1.5700 - regression_loss: 1.3312 - classification_loss: 0.2388 24/500 [>.............................] - ETA: 2:31 - loss: 1.5693 - regression_loss: 1.3324 - classification_loss: 0.2369 25/500 [>.............................] - ETA: 2:31 - loss: 1.5628 - regression_loss: 1.3283 - classification_loss: 0.2345 26/500 [>.............................] - ETA: 2:31 - loss: 1.5683 - regression_loss: 1.3307 - classification_loss: 0.2375 27/500 [>.............................] - ETA: 2:31 - loss: 1.5821 - regression_loss: 1.3467 - classification_loss: 0.2354 28/500 [>.............................] - ETA: 2:30 - loss: 1.5703 - regression_loss: 1.3380 - classification_loss: 0.2324 29/500 [>.............................] - ETA: 2:30 - loss: 1.5815 - regression_loss: 1.3480 - classification_loss: 0.2336 30/500 [>.............................] - ETA: 2:29 - loss: 1.5462 - regression_loss: 1.3178 - classification_loss: 0.2284 31/500 [>.............................] - ETA: 2:29 - loss: 1.5610 - regression_loss: 1.3273 - classification_loss: 0.2337 32/500 [>.............................] - ETA: 2:29 - loss: 1.5385 - regression_loss: 1.3088 - classification_loss: 0.2297 33/500 [>.............................] - ETA: 2:29 - loss: 1.5177 - regression_loss: 1.2924 - classification_loss: 0.2254 34/500 [=>............................] - ETA: 2:28 - loss: 1.5196 - regression_loss: 1.2946 - classification_loss: 0.2250 35/500 [=>............................] - ETA: 2:28 - loss: 1.5299 - regression_loss: 1.3027 - classification_loss: 0.2272 36/500 [=>............................] - ETA: 2:28 - loss: 1.5430 - regression_loss: 1.3123 - classification_loss: 0.2308 37/500 [=>............................] - ETA: 2:28 - loss: 1.5487 - regression_loss: 1.3173 - classification_loss: 0.2314 38/500 [=>............................] - ETA: 2:28 - loss: 1.5523 - regression_loss: 1.3215 - classification_loss: 0.2308 39/500 [=>............................] - ETA: 2:28 - loss: 1.5490 - regression_loss: 1.3198 - classification_loss: 0.2292 40/500 [=>............................] - ETA: 2:27 - loss: 1.5416 - regression_loss: 1.3138 - classification_loss: 0.2278 41/500 [=>............................] - ETA: 2:27 - loss: 1.5344 - regression_loss: 1.3085 - classification_loss: 0.2258 42/500 [=>............................] - ETA: 2:27 - loss: 1.5211 - regression_loss: 1.2969 - classification_loss: 0.2242 43/500 [=>............................] - ETA: 2:27 - loss: 1.5199 - regression_loss: 1.2967 - classification_loss: 0.2232 44/500 [=>............................] - ETA: 2:26 - loss: 1.4980 - regression_loss: 1.2766 - classification_loss: 0.2214 45/500 [=>............................] - ETA: 2:26 - loss: 1.5016 - regression_loss: 1.2783 - classification_loss: 0.2233 46/500 [=>............................] - ETA: 2:26 - loss: 1.4946 - regression_loss: 1.2715 - classification_loss: 0.2231 47/500 [=>............................] - ETA: 2:26 - loss: 1.4951 - regression_loss: 1.2720 - classification_loss: 0.2232 48/500 [=>............................] - ETA: 2:26 - loss: 1.5043 - regression_loss: 1.2802 - classification_loss: 0.2241 49/500 [=>............................] - ETA: 2:26 - loss: 1.5007 - regression_loss: 1.2787 - classification_loss: 0.2220 50/500 [==>...........................] - ETA: 2:25 - loss: 1.4991 - regression_loss: 1.2782 - classification_loss: 0.2208 51/500 [==>...........................] - ETA: 2:25 - loss: 1.4968 - regression_loss: 1.2770 - classification_loss: 0.2198 52/500 [==>...........................] - ETA: 2:24 - loss: 1.4995 - regression_loss: 1.2807 - classification_loss: 0.2188 53/500 [==>...........................] - ETA: 2:24 - loss: 1.4903 - regression_loss: 1.2730 - classification_loss: 0.2172 54/500 [==>...........................] - ETA: 2:24 - loss: 1.4838 - regression_loss: 1.2672 - classification_loss: 0.2166 55/500 [==>...........................] - ETA: 2:24 - loss: 1.4720 - regression_loss: 1.2567 - classification_loss: 0.2153 56/500 [==>...........................] - ETA: 2:23 - loss: 1.4746 - regression_loss: 1.2598 - classification_loss: 0.2147 57/500 [==>...........................] - ETA: 2:23 - loss: 1.4770 - regression_loss: 1.2628 - classification_loss: 0.2142 58/500 [==>...........................] - ETA: 2:22 - loss: 1.4876 - regression_loss: 1.2710 - classification_loss: 0.2166 59/500 [==>...........................] - ETA: 2:22 - loss: 1.5043 - regression_loss: 1.2863 - classification_loss: 0.2180 60/500 [==>...........................] - ETA: 2:22 - loss: 1.5090 - regression_loss: 1.2896 - classification_loss: 0.2194 61/500 [==>...........................] - ETA: 2:21 - loss: 1.5058 - regression_loss: 1.2870 - classification_loss: 0.2188 62/500 [==>...........................] - ETA: 2:21 - loss: 1.5060 - regression_loss: 1.2880 - classification_loss: 0.2179 63/500 [==>...........................] - ETA: 2:21 - loss: 1.4968 - regression_loss: 1.2807 - classification_loss: 0.2161 64/500 [==>...........................] - ETA: 2:20 - loss: 1.5040 - regression_loss: 1.2881 - classification_loss: 0.2160 65/500 [==>...........................] - ETA: 2:20 - loss: 1.5125 - regression_loss: 1.2949 - classification_loss: 0.2176 66/500 [==>...........................] - ETA: 2:20 - loss: 1.5001 - regression_loss: 1.2844 - classification_loss: 0.2157 67/500 [===>..........................] - ETA: 2:19 - loss: 1.4989 - regression_loss: 1.2836 - classification_loss: 0.2153 68/500 [===>..........................] - ETA: 2:19 - loss: 1.4916 - regression_loss: 1.2772 - classification_loss: 0.2144 69/500 [===>..........................] - ETA: 2:19 - loss: 1.4929 - regression_loss: 1.2779 - classification_loss: 0.2150 70/500 [===>..........................] - ETA: 2:18 - loss: 1.4937 - regression_loss: 1.2780 - classification_loss: 0.2157 71/500 [===>..........................] - ETA: 2:18 - loss: 1.4978 - regression_loss: 1.2811 - classification_loss: 0.2166 72/500 [===>..........................] - ETA: 2:18 - loss: 1.4868 - regression_loss: 1.2720 - classification_loss: 0.2147 73/500 [===>..........................] - ETA: 2:17 - loss: 1.4864 - regression_loss: 1.2710 - classification_loss: 0.2154 74/500 [===>..........................] - ETA: 2:17 - loss: 1.4805 - regression_loss: 1.2663 - classification_loss: 0.2142 75/500 [===>..........................] - ETA: 2:17 - loss: 1.4819 - regression_loss: 1.2685 - classification_loss: 0.2133 76/500 [===>..........................] - ETA: 2:16 - loss: 1.4872 - regression_loss: 1.2736 - classification_loss: 0.2136 77/500 [===>..........................] - ETA: 2:16 - loss: 1.4868 - regression_loss: 1.2735 - classification_loss: 0.2133 78/500 [===>..........................] - ETA: 2:16 - loss: 1.4942 - regression_loss: 1.2798 - classification_loss: 0.2144 79/500 [===>..........................] - ETA: 2:15 - loss: 1.4924 - regression_loss: 1.2781 - classification_loss: 0.2143 80/500 [===>..........................] - ETA: 2:15 - loss: 1.4962 - regression_loss: 1.2809 - classification_loss: 0.2153 81/500 [===>..........................] - ETA: 2:15 - loss: 1.4983 - regression_loss: 1.2833 - classification_loss: 0.2150 82/500 [===>..........................] - ETA: 2:14 - loss: 1.4897 - regression_loss: 1.2761 - classification_loss: 0.2136 83/500 [===>..........................] - ETA: 2:14 - loss: 1.4961 - regression_loss: 1.2812 - classification_loss: 0.2149 84/500 [====>.........................] - ETA: 2:14 - loss: 1.4993 - regression_loss: 1.2829 - classification_loss: 0.2163 85/500 [====>.........................] - ETA: 2:13 - loss: 1.4935 - regression_loss: 1.2767 - classification_loss: 0.2168 86/500 [====>.........................] - ETA: 2:13 - loss: 1.5041 - regression_loss: 1.2852 - classification_loss: 0.2190 87/500 [====>.........................] - ETA: 2:13 - loss: 1.4957 - regression_loss: 1.2781 - classification_loss: 0.2176 88/500 [====>.........................] - ETA: 2:12 - loss: 1.4912 - regression_loss: 1.2747 - classification_loss: 0.2166 89/500 [====>.........................] - ETA: 2:12 - loss: 1.4828 - regression_loss: 1.2676 - classification_loss: 0.2152 90/500 [====>.........................] - ETA: 2:12 - loss: 1.4868 - regression_loss: 1.2700 - classification_loss: 0.2167 91/500 [====>.........................] - ETA: 2:11 - loss: 1.4850 - regression_loss: 1.2687 - classification_loss: 0.2163 92/500 [====>.........................] - ETA: 2:11 - loss: 1.4833 - regression_loss: 1.2677 - classification_loss: 0.2156 93/500 [====>.........................] - ETA: 2:11 - loss: 1.4834 - regression_loss: 1.2677 - classification_loss: 0.2157 94/500 [====>.........................] - ETA: 2:11 - loss: 1.4879 - regression_loss: 1.2702 - classification_loss: 0.2177 95/500 [====>.........................] - ETA: 2:10 - loss: 1.4888 - regression_loss: 1.2708 - classification_loss: 0.2180 96/500 [====>.........................] - ETA: 2:10 - loss: 1.4833 - regression_loss: 1.2661 - classification_loss: 0.2171 97/500 [====>.........................] - ETA: 2:10 - loss: 1.4759 - regression_loss: 1.2600 - classification_loss: 0.2159 98/500 [====>.........................] - ETA: 2:09 - loss: 1.4721 - regression_loss: 1.2568 - classification_loss: 0.2153 99/500 [====>.........................] - ETA: 2:09 - loss: 1.4837 - regression_loss: 1.2664 - classification_loss: 0.2173 100/500 [=====>........................] - ETA: 2:09 - loss: 1.4855 - regression_loss: 1.2685 - classification_loss: 0.2171 101/500 [=====>........................] - ETA: 2:09 - loss: 1.4895 - regression_loss: 1.2715 - classification_loss: 0.2180 102/500 [=====>........................] - ETA: 2:08 - loss: 1.4934 - regression_loss: 1.2740 - classification_loss: 0.2195 103/500 [=====>........................] - ETA: 2:08 - loss: 1.4917 - regression_loss: 1.2730 - classification_loss: 0.2187 104/500 [=====>........................] - ETA: 2:08 - loss: 1.4959 - regression_loss: 1.2762 - classification_loss: 0.2197 105/500 [=====>........................] - ETA: 2:07 - loss: 1.4884 - regression_loss: 1.2701 - classification_loss: 0.2183 106/500 [=====>........................] - ETA: 2:07 - loss: 1.4841 - regression_loss: 1.2669 - classification_loss: 0.2172 107/500 [=====>........................] - ETA: 2:07 - loss: 1.4815 - regression_loss: 1.2649 - classification_loss: 0.2166 108/500 [=====>........................] - ETA: 2:06 - loss: 1.4789 - regression_loss: 1.2631 - classification_loss: 0.2158 109/500 [=====>........................] - ETA: 2:06 - loss: 1.4781 - regression_loss: 1.2629 - classification_loss: 0.2152 110/500 [=====>........................] - ETA: 2:06 - loss: 1.4782 - regression_loss: 1.2631 - classification_loss: 0.2151 111/500 [=====>........................] - ETA: 2:05 - loss: 1.4782 - regression_loss: 1.2628 - classification_loss: 0.2153 112/500 [=====>........................] - ETA: 2:05 - loss: 1.4816 - regression_loss: 1.2655 - classification_loss: 0.2160 113/500 [=====>........................] - ETA: 2:05 - loss: 1.4863 - regression_loss: 1.2698 - classification_loss: 0.2165 114/500 [=====>........................] - ETA: 2:04 - loss: 1.4837 - regression_loss: 1.2675 - classification_loss: 0.2162 115/500 [=====>........................] - ETA: 2:04 - loss: 1.4814 - regression_loss: 1.2659 - classification_loss: 0.2155 116/500 [=====>........................] - ETA: 2:04 - loss: 1.4831 - regression_loss: 1.2673 - classification_loss: 0.2158 117/500 [======>.......................] - ETA: 2:03 - loss: 1.4832 - regression_loss: 1.2674 - classification_loss: 0.2158 118/500 [======>.......................] - ETA: 2:03 - loss: 1.4840 - regression_loss: 1.2677 - classification_loss: 0.2162 119/500 [======>.......................] - ETA: 2:03 - loss: 1.4812 - regression_loss: 1.2659 - classification_loss: 0.2153 120/500 [======>.......................] - ETA: 2:02 - loss: 1.4750 - regression_loss: 1.2609 - classification_loss: 0.2141 121/500 [======>.......................] - ETA: 2:02 - loss: 1.4660 - regression_loss: 1.2532 - classification_loss: 0.2127 122/500 [======>.......................] - ETA: 2:02 - loss: 1.4601 - regression_loss: 1.2483 - classification_loss: 0.2118 123/500 [======>.......................] - ETA: 2:01 - loss: 1.4513 - regression_loss: 1.2407 - classification_loss: 0.2105 124/500 [======>.......................] - ETA: 2:01 - loss: 1.4504 - regression_loss: 1.2400 - classification_loss: 0.2104 125/500 [======>.......................] - ETA: 2:01 - loss: 1.4509 - regression_loss: 1.2411 - classification_loss: 0.2099 126/500 [======>.......................] - ETA: 2:00 - loss: 1.4486 - regression_loss: 1.2394 - classification_loss: 0.2092 127/500 [======>.......................] - ETA: 2:00 - loss: 1.4530 - regression_loss: 1.2432 - classification_loss: 0.2097 128/500 [======>.......................] - ETA: 2:00 - loss: 1.4557 - regression_loss: 1.2447 - classification_loss: 0.2110 129/500 [======>.......................] - ETA: 1:59 - loss: 1.4537 - regression_loss: 1.2431 - classification_loss: 0.2106 130/500 [======>.......................] - ETA: 1:59 - loss: 1.4515 - regression_loss: 1.2412 - classification_loss: 0.2103 131/500 [======>.......................] - ETA: 1:59 - loss: 1.4532 - regression_loss: 1.2421 - classification_loss: 0.2111 132/500 [======>.......................] - ETA: 1:58 - loss: 1.4536 - regression_loss: 1.2429 - classification_loss: 0.2108 133/500 [======>.......................] - ETA: 1:58 - loss: 1.4517 - regression_loss: 1.2415 - classification_loss: 0.2102 134/500 [=======>......................] - ETA: 1:58 - loss: 1.4495 - regression_loss: 1.2398 - classification_loss: 0.2098 135/500 [=======>......................] - ETA: 1:57 - loss: 1.4458 - regression_loss: 1.2366 - classification_loss: 0.2092 136/500 [=======>......................] - ETA: 1:57 - loss: 1.4477 - regression_loss: 1.2380 - classification_loss: 0.2097 137/500 [=======>......................] - ETA: 1:57 - loss: 1.4487 - regression_loss: 1.2387 - classification_loss: 0.2099 138/500 [=======>......................] - ETA: 1:56 - loss: 1.4464 - regression_loss: 1.2370 - classification_loss: 0.2095 139/500 [=======>......................] - ETA: 1:56 - loss: 1.4411 - regression_loss: 1.2324 - classification_loss: 0.2087 140/500 [=======>......................] - ETA: 1:56 - loss: 1.4367 - regression_loss: 1.2287 - classification_loss: 0.2080 141/500 [=======>......................] - ETA: 1:55 - loss: 1.4369 - regression_loss: 1.2291 - classification_loss: 0.2078 142/500 [=======>......................] - ETA: 1:55 - loss: 1.4418 - regression_loss: 1.2331 - classification_loss: 0.2087 143/500 [=======>......................] - ETA: 1:55 - loss: 1.4495 - regression_loss: 1.2392 - classification_loss: 0.2103 144/500 [=======>......................] - ETA: 1:55 - loss: 1.4495 - regression_loss: 1.2394 - classification_loss: 0.2101 145/500 [=======>......................] - ETA: 1:54 - loss: 1.4528 - regression_loss: 1.2423 - classification_loss: 0.2106 146/500 [=======>......................] - ETA: 1:54 - loss: 1.4522 - regression_loss: 1.2420 - classification_loss: 0.2101 147/500 [=======>......................] - ETA: 1:54 - loss: 1.4498 - regression_loss: 1.2403 - classification_loss: 0.2096 148/500 [=======>......................] - ETA: 1:53 - loss: 1.4467 - regression_loss: 1.2375 - classification_loss: 0.2093 149/500 [=======>......................] - ETA: 1:53 - loss: 1.4477 - regression_loss: 1.2385 - classification_loss: 0.2091 150/500 [========>.....................] - ETA: 1:53 - loss: 1.4458 - regression_loss: 1.2371 - classification_loss: 0.2087 151/500 [========>.....................] - ETA: 1:52 - loss: 1.4465 - regression_loss: 1.2376 - classification_loss: 0.2089 152/500 [========>.....................] - ETA: 1:52 - loss: 1.4423 - regression_loss: 1.2341 - classification_loss: 0.2082 153/500 [========>.....................] - ETA: 1:52 - loss: 1.4392 - regression_loss: 1.2315 - classification_loss: 0.2076 154/500 [========>.....................] - ETA: 1:51 - loss: 1.4428 - regression_loss: 1.2333 - classification_loss: 0.2096 155/500 [========>.....................] - ETA: 1:51 - loss: 1.4446 - regression_loss: 1.2349 - classification_loss: 0.2097 156/500 [========>.....................] - ETA: 1:51 - loss: 1.4451 - regression_loss: 1.2356 - classification_loss: 0.2095 157/500 [========>.....................] - ETA: 1:50 - loss: 1.4463 - regression_loss: 1.2364 - classification_loss: 0.2098 158/500 [========>.....................] - ETA: 1:50 - loss: 1.4447 - regression_loss: 1.2353 - classification_loss: 0.2094 159/500 [========>.....................] - ETA: 1:50 - loss: 1.4465 - regression_loss: 1.2367 - classification_loss: 0.2097 160/500 [========>.....................] - ETA: 1:50 - loss: 1.4467 - regression_loss: 1.2373 - classification_loss: 0.2094 161/500 [========>.....................] - ETA: 1:49 - loss: 1.4487 - regression_loss: 1.2380 - classification_loss: 0.2108 162/500 [========>.....................] - ETA: 1:49 - loss: 1.4496 - regression_loss: 1.2378 - classification_loss: 0.2117 163/500 [========>.....................] - ETA: 1:49 - loss: 1.4462 - regression_loss: 1.2352 - classification_loss: 0.2110 164/500 [========>.....................] - ETA: 1:48 - loss: 1.4424 - regression_loss: 1.2320 - classification_loss: 0.2104 165/500 [========>.....................] - ETA: 1:48 - loss: 1.4402 - regression_loss: 1.2304 - classification_loss: 0.2099 166/500 [========>.....................] - ETA: 1:48 - loss: 1.4363 - regression_loss: 1.2271 - classification_loss: 0.2092 167/500 [=========>....................] - ETA: 1:47 - loss: 1.4353 - regression_loss: 1.2261 - classification_loss: 0.2092 168/500 [=========>....................] - ETA: 1:47 - loss: 1.4347 - regression_loss: 1.2253 - classification_loss: 0.2094 169/500 [=========>....................] - ETA: 1:47 - loss: 1.4299 - regression_loss: 1.2214 - classification_loss: 0.2085 170/500 [=========>....................] - ETA: 1:46 - loss: 1.4255 - regression_loss: 1.2177 - classification_loss: 0.2078 171/500 [=========>....................] - ETA: 1:46 - loss: 1.4299 - regression_loss: 1.2211 - classification_loss: 0.2088 172/500 [=========>....................] - ETA: 1:46 - loss: 1.4276 - regression_loss: 1.2192 - classification_loss: 0.2084 173/500 [=========>....................] - ETA: 1:45 - loss: 1.4296 - regression_loss: 1.2212 - classification_loss: 0.2084 174/500 [=========>....................] - ETA: 1:45 - loss: 1.4311 - regression_loss: 1.2228 - classification_loss: 0.2083 175/500 [=========>....................] - ETA: 1:45 - loss: 1.4337 - regression_loss: 1.2254 - classification_loss: 0.2083 176/500 [=========>....................] - ETA: 1:44 - loss: 1.4371 - regression_loss: 1.2283 - classification_loss: 0.2088 177/500 [=========>....................] - ETA: 1:44 - loss: 1.4338 - regression_loss: 1.2255 - classification_loss: 0.2083 178/500 [=========>....................] - ETA: 1:44 - loss: 1.4334 - regression_loss: 1.2252 - classification_loss: 0.2082 179/500 [=========>....................] - ETA: 1:44 - loss: 1.4365 - regression_loss: 1.2276 - classification_loss: 0.2090 180/500 [=========>....................] - ETA: 1:43 - loss: 1.4382 - regression_loss: 1.2289 - classification_loss: 0.2093 181/500 [=========>....................] - ETA: 1:43 - loss: 1.4353 - regression_loss: 1.2266 - classification_loss: 0.2087 182/500 [=========>....................] - ETA: 1:43 - loss: 1.4325 - regression_loss: 1.2235 - classification_loss: 0.2090 183/500 [=========>....................] - ETA: 1:42 - loss: 1.4341 - regression_loss: 1.2253 - classification_loss: 0.2089 184/500 [==========>...................] - ETA: 1:42 - loss: 1.4363 - regression_loss: 1.2274 - classification_loss: 0.2090 185/500 [==========>...................] - ETA: 1:42 - loss: 1.4362 - regression_loss: 1.2272 - classification_loss: 0.2090 186/500 [==========>...................] - ETA: 1:41 - loss: 1.4386 - regression_loss: 1.2294 - classification_loss: 0.2092 187/500 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[===========================>..] - ETA: 5s - loss: 1.4110 - regression_loss: 1.2019 - classification_loss: 0.2091 484/500 [============================>.] - ETA: 5s - loss: 1.4113 - regression_loss: 1.2022 - classification_loss: 0.2091 485/500 [============================>.] - ETA: 4s - loss: 1.4118 - regression_loss: 1.2026 - classification_loss: 0.2092 486/500 [============================>.] - ETA: 4s - loss: 1.4104 - regression_loss: 1.2015 - classification_loss: 0.2090 487/500 [============================>.] - ETA: 4s - loss: 1.4104 - regression_loss: 1.2015 - classification_loss: 0.2089 488/500 [============================>.] - ETA: 3s - loss: 1.4092 - regression_loss: 1.2005 - classification_loss: 0.2087 489/500 [============================>.] - ETA: 3s - loss: 1.4077 - regression_loss: 1.1992 - classification_loss: 0.2085 490/500 [============================>.] - ETA: 3s - loss: 1.4077 - regression_loss: 1.1992 - classification_loss: 0.2085 491/500 [============================>.] - ETA: 2s - loss: 1.4080 - regression_loss: 1.1994 - classification_loss: 0.2086 492/500 [============================>.] - ETA: 2s - loss: 1.4094 - regression_loss: 1.2004 - classification_loss: 0.2090 493/500 [============================>.] - ETA: 2s - loss: 1.4100 - regression_loss: 1.2010 - classification_loss: 0.2091 494/500 [============================>.] - ETA: 1s - loss: 1.4104 - regression_loss: 1.2013 - classification_loss: 0.2091 495/500 [============================>.] - ETA: 1s - loss: 1.4098 - regression_loss: 1.2009 - classification_loss: 0.2089 496/500 [============================>.] - ETA: 1s - loss: 1.4082 - regression_loss: 1.1995 - classification_loss: 0.2087 497/500 [============================>.] - ETA: 0s - loss: 1.4092 - regression_loss: 1.2003 - classification_loss: 0.2089 498/500 [============================>.] - ETA: 0s - loss: 1.4082 - regression_loss: 1.1994 - classification_loss: 0.2088 499/500 [============================>.] - ETA: 0s - loss: 1.4084 - regression_loss: 1.1995 - classification_loss: 0.2089 500/500 [==============================] - 162s 324ms/step - loss: 1.4087 - regression_loss: 1.1998 - classification_loss: 0.2088 326 instances of class plum with average precision: 0.7595 mAP: 0.7595 Epoch 00010: saving model to ./training/snapshots/resnet101_pascal_10.h5 Epoch 11/150 1/500 [..............................] - ETA: 2:47 - loss: 1.1766 - regression_loss: 1.0425 - classification_loss: 0.1341 2/500 [..............................] - ETA: 2:45 - loss: 1.3419 - regression_loss: 1.1472 - classification_loss: 0.1947 3/500 [..............................] - ETA: 2:50 - loss: 1.5002 - regression_loss: 1.3074 - classification_loss: 0.1928 4/500 [..............................] - ETA: 2:47 - loss: 1.2801 - regression_loss: 1.1103 - classification_loss: 0.1697 5/500 [..............................] - ETA: 2:44 - loss: 1.3707 - regression_loss: 1.1875 - 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0.2196 14/500 [..............................] - ETA: 2:40 - loss: 1.4432 - regression_loss: 1.2200 - classification_loss: 0.2232 15/500 [..............................] - ETA: 2:39 - loss: 1.4492 - regression_loss: 1.2303 - classification_loss: 0.2189 16/500 [..............................] - ETA: 2:39 - loss: 1.4390 - regression_loss: 1.2252 - classification_loss: 0.2138 17/500 [>.............................] - ETA: 2:38 - loss: 1.4571 - regression_loss: 1.2444 - classification_loss: 0.2127 18/500 [>.............................] - ETA: 2:37 - loss: 1.4939 - regression_loss: 1.2752 - classification_loss: 0.2187 19/500 [>.............................] - ETA: 2:37 - loss: 1.4402 - regression_loss: 1.2297 - classification_loss: 0.2105 20/500 [>.............................] - ETA: 2:36 - loss: 1.4307 - regression_loss: 1.2242 - classification_loss: 0.2065 21/500 [>.............................] - ETA: 2:35 - loss: 1.4382 - regression_loss: 1.2318 - classification_loss: 0.2064 22/500 [>.............................] - ETA: 2:35 - loss: 1.4242 - regression_loss: 1.2208 - classification_loss: 0.2034 23/500 [>.............................] - ETA: 2:34 - loss: 1.3867 - regression_loss: 1.1890 - classification_loss: 0.1978 24/500 [>.............................] - ETA: 2:34 - loss: 1.3964 - regression_loss: 1.1950 - classification_loss: 0.2014 25/500 [>.............................] - ETA: 2:33 - loss: 1.3989 - regression_loss: 1.1975 - classification_loss: 0.2013 26/500 [>.............................] - ETA: 2:33 - loss: 1.4155 - regression_loss: 1.2125 - classification_loss: 0.2030 27/500 [>.............................] - ETA: 2:32 - loss: 1.4076 - regression_loss: 1.2073 - classification_loss: 0.2003 28/500 [>.............................] - ETA: 2:32 - loss: 1.3845 - regression_loss: 1.1873 - classification_loss: 0.1973 29/500 [>.............................] - ETA: 2:31 - loss: 1.3782 - regression_loss: 1.1833 - classification_loss: 0.1949 30/500 [>.............................] - ETA: 2:31 - loss: 1.3563 - regression_loss: 1.1654 - classification_loss: 0.1910 31/500 [>.............................] - ETA: 2:30 - loss: 1.3677 - regression_loss: 1.1738 - classification_loss: 0.1939 32/500 [>.............................] - ETA: 2:30 - loss: 1.3675 - regression_loss: 1.1731 - classification_loss: 0.1943 33/500 [>.............................] - ETA: 2:30 - loss: 1.3644 - regression_loss: 1.1714 - classification_loss: 0.1930 34/500 [=>............................] - ETA: 2:29 - loss: 1.3466 - regression_loss: 1.1575 - classification_loss: 0.1891 35/500 [=>............................] - ETA: 2:28 - loss: 1.3820 - regression_loss: 1.1812 - classification_loss: 0.2008 36/500 [=>............................] - ETA: 2:28 - loss: 1.3593 - regression_loss: 1.1621 - classification_loss: 0.1972 37/500 [=>............................] - ETA: 2:28 - loss: 1.3672 - regression_loss: 1.1696 - classification_loss: 0.1977 38/500 [=>............................] - ETA: 2:27 - loss: 1.3788 - regression_loss: 1.1809 - classification_loss: 0.1979 39/500 [=>............................] - ETA: 2:27 - loss: 1.3670 - regression_loss: 1.1710 - classification_loss: 0.1960 40/500 [=>............................] - ETA: 2:26 - loss: 1.3794 - regression_loss: 1.1814 - classification_loss: 0.1981 41/500 [=>............................] - ETA: 2:26 - loss: 1.3869 - regression_loss: 1.1842 - classification_loss: 0.2027 42/500 [=>............................] - ETA: 2:26 - loss: 1.3638 - regression_loss: 1.1644 - classification_loss: 0.1994 43/500 [=>............................] - ETA: 2:25 - loss: 1.3773 - regression_loss: 1.1770 - classification_loss: 0.2002 44/500 [=>............................] - ETA: 2:25 - loss: 1.3747 - regression_loss: 1.1741 - classification_loss: 0.2006 45/500 [=>............................] - ETA: 2:25 - loss: 1.3771 - regression_loss: 1.1755 - classification_loss: 0.2016 46/500 [=>............................] - ETA: 2:24 - loss: 1.3649 - regression_loss: 1.1659 - classification_loss: 0.1990 47/500 [=>............................] - ETA: 2:24 - loss: 1.3923 - regression_loss: 1.1872 - classification_loss: 0.2051 48/500 [=>............................] - ETA: 2:24 - loss: 1.3807 - regression_loss: 1.1775 - classification_loss: 0.2032 49/500 [=>............................] - ETA: 2:23 - loss: 1.3819 - regression_loss: 1.1793 - classification_loss: 0.2026 50/500 [==>...........................] - ETA: 2:23 - loss: 1.3807 - regression_loss: 1.1789 - classification_loss: 0.2018 51/500 [==>...........................] - ETA: 2:22 - loss: 1.3875 - regression_loss: 1.1830 - classification_loss: 0.2045 52/500 [==>...........................] - ETA: 2:22 - loss: 1.3933 - regression_loss: 1.1883 - classification_loss: 0.2051 53/500 [==>...........................] - ETA: 2:22 - loss: 1.4019 - regression_loss: 1.1962 - classification_loss: 0.2057 54/500 [==>...........................] - ETA: 2:21 - loss: 1.3989 - regression_loss: 1.1947 - classification_loss: 0.2042 55/500 [==>...........................] - ETA: 2:21 - loss: 1.3948 - regression_loss: 1.1919 - classification_loss: 0.2029 56/500 [==>...........................] - ETA: 2:20 - loss: 1.4069 - regression_loss: 1.2006 - classification_loss: 0.2063 57/500 [==>...........................] - ETA: 2:20 - loss: 1.3975 - regression_loss: 1.1928 - classification_loss: 0.2047 58/500 [==>...........................] - ETA: 2:20 - loss: 1.4008 - regression_loss: 1.1963 - classification_loss: 0.2046 59/500 [==>...........................] - ETA: 2:19 - loss: 1.3911 - regression_loss: 1.1879 - classification_loss: 0.2032 60/500 [==>...........................] - ETA: 2:19 - loss: 1.3811 - regression_loss: 1.1791 - classification_loss: 0.2020 61/500 [==>...........................] - ETA: 2:19 - loss: 1.3837 - regression_loss: 1.1813 - classification_loss: 0.2024 62/500 [==>...........................] - ETA: 2:18 - loss: 1.3837 - regression_loss: 1.1819 - classification_loss: 0.2018 63/500 [==>...........................] - ETA: 2:18 - loss: 1.3835 - regression_loss: 1.1820 - classification_loss: 0.2015 64/500 [==>...........................] - ETA: 2:18 - loss: 1.3845 - regression_loss: 1.1837 - classification_loss: 0.2008 65/500 [==>...........................] - ETA: 2:17 - loss: 1.3907 - regression_loss: 1.1900 - classification_loss: 0.2007 66/500 [==>...........................] - ETA: 2:17 - loss: 1.3933 - regression_loss: 1.1934 - classification_loss: 0.1999 67/500 [===>..........................] - ETA: 2:17 - loss: 1.3869 - regression_loss: 1.1885 - classification_loss: 0.1984 68/500 [===>..........................] - ETA: 2:16 - loss: 1.3871 - regression_loss: 1.1878 - classification_loss: 0.1994 69/500 [===>..........................] - ETA: 2:16 - loss: 1.3964 - regression_loss: 1.1944 - classification_loss: 0.2020 70/500 [===>..........................] - ETA: 2:16 - loss: 1.4012 - regression_loss: 1.1998 - classification_loss: 0.2014 71/500 [===>..........................] - ETA: 2:15 - loss: 1.4049 - regression_loss: 1.2033 - classification_loss: 0.2016 72/500 [===>..........................] - ETA: 2:15 - loss: 1.3975 - regression_loss: 1.1968 - classification_loss: 0.2007 73/500 [===>..........................] - ETA: 2:15 - loss: 1.3913 - regression_loss: 1.1916 - classification_loss: 0.1997 74/500 [===>..........................] - ETA: 2:15 - loss: 1.3999 - regression_loss: 1.1979 - classification_loss: 0.2020 75/500 [===>..........................] - ETA: 2:14 - loss: 1.3908 - regression_loss: 1.1902 - classification_loss: 0.2006 76/500 [===>..........................] - ETA: 2:14 - loss: 1.3773 - regression_loss: 1.1785 - classification_loss: 0.1988 77/500 [===>..........................] - ETA: 2:14 - loss: 1.3736 - regression_loss: 1.1755 - classification_loss: 0.1980 78/500 [===>..........................] - ETA: 2:14 - loss: 1.3641 - regression_loss: 1.1674 - classification_loss: 0.1967 79/500 [===>..........................] - ETA: 2:13 - loss: 1.3686 - regression_loss: 1.1702 - classification_loss: 0.1984 80/500 [===>..........................] - ETA: 2:13 - loss: 1.3809 - regression_loss: 1.1806 - classification_loss: 0.2003 81/500 [===>..........................] - ETA: 2:13 - loss: 1.3729 - regression_loss: 1.1740 - classification_loss: 0.1990 82/500 [===>..........................] - ETA: 2:12 - loss: 1.3657 - regression_loss: 1.1679 - classification_loss: 0.1977 83/500 [===>..........................] - ETA: 2:12 - loss: 1.3751 - regression_loss: 1.1754 - classification_loss: 0.1996 84/500 [====>.........................] - ETA: 2:12 - loss: 1.3765 - regression_loss: 1.1775 - classification_loss: 0.1990 85/500 [====>.........................] - ETA: 2:11 - loss: 1.3786 - regression_loss: 1.1790 - classification_loss: 0.1996 86/500 [====>.........................] - ETA: 2:11 - loss: 1.3831 - regression_loss: 1.1818 - classification_loss: 0.2013 87/500 [====>.........................] - ETA: 2:11 - loss: 1.3888 - regression_loss: 1.1864 - classification_loss: 0.2024 88/500 [====>.........................] - ETA: 2:10 - loss: 1.3890 - regression_loss: 1.1867 - classification_loss: 0.2023 89/500 [====>.........................] - ETA: 2:10 - loss: 1.3817 - regression_loss: 1.1806 - classification_loss: 0.2011 90/500 [====>.........................] - ETA: 2:10 - loss: 1.3798 - regression_loss: 1.1793 - classification_loss: 0.2005 91/500 [====>.........................] - ETA: 2:09 - loss: 1.3758 - regression_loss: 1.1763 - classification_loss: 0.1995 92/500 [====>.........................] - ETA: 2:09 - loss: 1.3796 - regression_loss: 1.1795 - classification_loss: 0.2001 93/500 [====>.........................] - ETA: 2:09 - loss: 1.3778 - regression_loss: 1.1783 - classification_loss: 0.1994 94/500 [====>.........................] - ETA: 2:08 - loss: 1.3755 - regression_loss: 1.1758 - classification_loss: 0.1997 95/500 [====>.........................] - ETA: 2:08 - loss: 1.3829 - regression_loss: 1.1813 - classification_loss: 0.2016 96/500 [====>.........................] - ETA: 2:08 - loss: 1.3824 - regression_loss: 1.1815 - classification_loss: 0.2009 97/500 [====>.........................] - ETA: 2:07 - loss: 1.3876 - regression_loss: 1.1855 - classification_loss: 0.2021 98/500 [====>.........................] - ETA: 2:07 - loss: 1.3915 - regression_loss: 1.1885 - classification_loss: 0.2030 99/500 [====>.........................] - ETA: 2:07 - loss: 1.3825 - regression_loss: 1.1809 - classification_loss: 0.2015 100/500 [=====>........................] - ETA: 2:06 - loss: 1.3804 - regression_loss: 1.1793 - classification_loss: 0.2011 101/500 [=====>........................] - ETA: 2:06 - loss: 1.3783 - regression_loss: 1.1776 - classification_loss: 0.2007 102/500 [=====>........................] - ETA: 2:06 - loss: 1.3812 - regression_loss: 1.1803 - classification_loss: 0.2010 103/500 [=====>........................] - ETA: 2:05 - loss: 1.3840 - regression_loss: 1.1830 - classification_loss: 0.2010 104/500 [=====>........................] - ETA: 2:05 - loss: 1.3778 - regression_loss: 1.1780 - classification_loss: 0.1998 105/500 [=====>........................] - ETA: 2:05 - loss: 1.3716 - regression_loss: 1.1729 - classification_loss: 0.1987 106/500 [=====>........................] - ETA: 2:05 - loss: 1.3746 - regression_loss: 1.1756 - classification_loss: 0.1990 107/500 [=====>........................] - ETA: 2:04 - loss: 1.3783 - regression_loss: 1.1785 - classification_loss: 0.1998 108/500 [=====>........................] - ETA: 2:04 - loss: 1.3916 - regression_loss: 1.1866 - classification_loss: 0.2050 109/500 [=====>........................] - ETA: 2:04 - loss: 1.3827 - regression_loss: 1.1789 - classification_loss: 0.2038 110/500 [=====>........................] - ETA: 2:03 - loss: 1.3798 - regression_loss: 1.1766 - classification_loss: 0.2033 111/500 [=====>........................] - ETA: 2:03 - loss: 1.3828 - regression_loss: 1.1791 - classification_loss: 0.2037 112/500 [=====>........................] - ETA: 2:03 - loss: 1.3805 - regression_loss: 1.1767 - classification_loss: 0.2038 113/500 [=====>........................] - ETA: 2:02 - loss: 1.3899 - regression_loss: 1.1829 - classification_loss: 0.2070 114/500 [=====>........................] - ETA: 2:02 - loss: 1.3878 - regression_loss: 1.1814 - classification_loss: 0.2064 115/500 [=====>........................] - ETA: 2:02 - loss: 1.3920 - regression_loss: 1.1851 - classification_loss: 0.2069 116/500 [=====>........................] - ETA: 2:01 - loss: 1.3954 - regression_loss: 1.1875 - classification_loss: 0.2079 117/500 [======>.......................] - ETA: 2:01 - loss: 1.4043 - regression_loss: 1.1947 - classification_loss: 0.2096 118/500 [======>.......................] - ETA: 2:01 - loss: 1.4060 - regression_loss: 1.1963 - classification_loss: 0.2097 119/500 [======>.......................] - ETA: 2:00 - loss: 1.4037 - regression_loss: 1.1946 - classification_loss: 0.2091 120/500 [======>.......................] - ETA: 2:00 - loss: 1.4020 - regression_loss: 1.1937 - classification_loss: 0.2083 121/500 [======>.......................] - ETA: 2:00 - loss: 1.3976 - regression_loss: 1.1900 - classification_loss: 0.2076 122/500 [======>.......................] - ETA: 1:59 - loss: 1.3933 - regression_loss: 1.1864 - classification_loss: 0.2070 123/500 [======>.......................] - ETA: 1:59 - loss: 1.3907 - regression_loss: 1.1844 - classification_loss: 0.2063 124/500 [======>.......................] - ETA: 1:59 - loss: 1.3887 - regression_loss: 1.1829 - classification_loss: 0.2058 125/500 [======>.......................] - ETA: 1:58 - loss: 1.3867 - regression_loss: 1.1813 - classification_loss: 0.2054 126/500 [======>.......................] - ETA: 1:58 - loss: 1.3830 - regression_loss: 1.1779 - classification_loss: 0.2051 127/500 [======>.......................] - ETA: 1:58 - loss: 1.3784 - regression_loss: 1.1739 - classification_loss: 0.2045 128/500 [======>.......................] - ETA: 1:57 - loss: 1.3793 - regression_loss: 1.1749 - classification_loss: 0.2044 129/500 [======>.......................] - ETA: 1:57 - loss: 1.3825 - regression_loss: 1.1776 - classification_loss: 0.2049 130/500 [======>.......................] - ETA: 1:57 - loss: 1.3778 - regression_loss: 1.1739 - classification_loss: 0.2039 131/500 [======>.......................] - ETA: 1:56 - loss: 1.3783 - regression_loss: 1.1748 - classification_loss: 0.2035 132/500 [======>.......................] - ETA: 1:56 - loss: 1.3756 - regression_loss: 1.1724 - classification_loss: 0.2032 133/500 [======>.......................] - ETA: 1:56 - loss: 1.3714 - regression_loss: 1.1678 - classification_loss: 0.2036 134/500 [=======>......................] - ETA: 1:55 - loss: 1.3658 - regression_loss: 1.1633 - classification_loss: 0.2026 135/500 [=======>......................] - ETA: 1:55 - loss: 1.3638 - regression_loss: 1.1617 - classification_loss: 0.2021 136/500 [=======>......................] - ETA: 1:55 - loss: 1.3662 - regression_loss: 1.1642 - classification_loss: 0.2020 137/500 [=======>......................] - ETA: 1:54 - loss: 1.3682 - regression_loss: 1.1661 - classification_loss: 0.2021 138/500 [=======>......................] - ETA: 1:54 - loss: 1.3654 - regression_loss: 1.1641 - classification_loss: 0.2014 139/500 [=======>......................] - ETA: 1:54 - loss: 1.3664 - regression_loss: 1.1649 - classification_loss: 0.2015 140/500 [=======>......................] - ETA: 1:53 - loss: 1.3671 - regression_loss: 1.1653 - classification_loss: 0.2018 141/500 [=======>......................] - ETA: 1:53 - loss: 1.3695 - regression_loss: 1.1675 - classification_loss: 0.2020 142/500 [=======>......................] - ETA: 1:53 - loss: 1.3686 - regression_loss: 1.1669 - classification_loss: 0.2017 143/500 [=======>......................] - ETA: 1:52 - loss: 1.3708 - regression_loss: 1.1688 - classification_loss: 0.2020 144/500 [=======>......................] - ETA: 1:52 - loss: 1.3663 - regression_loss: 1.1651 - classification_loss: 0.2012 145/500 [=======>......................] - ETA: 1:52 - loss: 1.3695 - regression_loss: 1.1678 - classification_loss: 0.2018 146/500 [=======>......................] - ETA: 1:51 - loss: 1.3759 - regression_loss: 1.1727 - classification_loss: 0.2032 147/500 [=======>......................] - ETA: 1:51 - loss: 1.3732 - regression_loss: 1.1704 - classification_loss: 0.2028 148/500 [=======>......................] - ETA: 1:51 - loss: 1.3725 - regression_loss: 1.1698 - classification_loss: 0.2027 149/500 [=======>......................] - ETA: 1:50 - loss: 1.3750 - regression_loss: 1.1711 - classification_loss: 0.2039 150/500 [========>.....................] - ETA: 1:50 - loss: 1.3706 - regression_loss: 1.1675 - classification_loss: 0.2031 151/500 [========>.....................] - ETA: 1:50 - loss: 1.3730 - regression_loss: 1.1694 - classification_loss: 0.2035 152/500 [========>.....................] - ETA: 1:50 - loss: 1.3736 - regression_loss: 1.1701 - classification_loss: 0.2035 153/500 [========>.....................] - ETA: 1:49 - loss: 1.3734 - regression_loss: 1.1700 - classification_loss: 0.2034 154/500 [========>.....................] - ETA: 1:49 - loss: 1.3687 - regression_loss: 1.1660 - classification_loss: 0.2027 155/500 [========>.....................] - ETA: 1:49 - loss: 1.3707 - regression_loss: 1.1672 - classification_loss: 0.2034 156/500 [========>.....................] - ETA: 1:48 - loss: 1.3719 - regression_loss: 1.1677 - classification_loss: 0.2042 157/500 [========>.....................] - ETA: 1:48 - loss: 1.3682 - regression_loss: 1.1644 - classification_loss: 0.2038 158/500 [========>.....................] - ETA: 1:48 - loss: 1.3675 - regression_loss: 1.1638 - classification_loss: 0.2036 159/500 [========>.....................] - ETA: 1:47 - loss: 1.3657 - regression_loss: 1.1626 - classification_loss: 0.2031 160/500 [========>.....................] - ETA: 1:47 - loss: 1.3704 - regression_loss: 1.1666 - classification_loss: 0.2037 161/500 [========>.....................] - ETA: 1:47 - loss: 1.3698 - regression_loss: 1.1663 - classification_loss: 0.2035 162/500 [========>.....................] - ETA: 1:46 - loss: 1.3693 - regression_loss: 1.1659 - classification_loss: 0.2034 163/500 [========>.....................] - ETA: 1:46 - loss: 1.3639 - regression_loss: 1.1614 - classification_loss: 0.2025 164/500 [========>.....................] - ETA: 1:46 - loss: 1.3667 - regression_loss: 1.1634 - classification_loss: 0.2032 165/500 [========>.....................] - ETA: 1:45 - loss: 1.3666 - regression_loss: 1.1631 - classification_loss: 0.2034 166/500 [========>.....................] - ETA: 1:45 - loss: 1.3652 - regression_loss: 1.1623 - classification_loss: 0.2029 167/500 [=========>....................] - ETA: 1:45 - loss: 1.3596 - regression_loss: 1.1574 - classification_loss: 0.2023 168/500 [=========>....................] - ETA: 1:44 - loss: 1.3557 - regression_loss: 1.1540 - classification_loss: 0.2017 169/500 [=========>....................] - ETA: 1:44 - loss: 1.3579 - regression_loss: 1.1557 - classification_loss: 0.2022 170/500 [=========>....................] - ETA: 1:44 - loss: 1.3631 - regression_loss: 1.1599 - classification_loss: 0.2032 171/500 [=========>....................] - ETA: 1:43 - loss: 1.3624 - regression_loss: 1.1596 - classification_loss: 0.2028 172/500 [=========>....................] - ETA: 1:43 - loss: 1.3621 - regression_loss: 1.1595 - classification_loss: 0.2026 173/500 [=========>....................] - ETA: 1:43 - loss: 1.3630 - regression_loss: 1.1607 - classification_loss: 0.2023 174/500 [=========>....................] - ETA: 1:42 - loss: 1.3657 - regression_loss: 1.1629 - classification_loss: 0.2028 175/500 [=========>....................] - ETA: 1:42 - loss: 1.3691 - regression_loss: 1.1661 - classification_loss: 0.2030 176/500 [=========>....................] - ETA: 1:42 - loss: 1.3690 - regression_loss: 1.1663 - classification_loss: 0.2027 177/500 [=========>....................] - ETA: 1:41 - loss: 1.3681 - regression_loss: 1.1653 - classification_loss: 0.2028 178/500 [=========>....................] - ETA: 1:41 - loss: 1.3670 - regression_loss: 1.1646 - classification_loss: 0.2025 179/500 [=========>....................] - ETA: 1:41 - loss: 1.3670 - regression_loss: 1.1642 - classification_loss: 0.2028 180/500 [=========>....................] - ETA: 1:41 - loss: 1.3640 - regression_loss: 1.1615 - classification_loss: 0.2025 181/500 [=========>....................] - ETA: 1:40 - loss: 1.3634 - regression_loss: 1.1607 - classification_loss: 0.2027 182/500 [=========>....................] - ETA: 1:40 - loss: 1.3603 - regression_loss: 1.1584 - classification_loss: 0.2020 183/500 [=========>....................] - ETA: 1:40 - loss: 1.3628 - regression_loss: 1.1601 - classification_loss: 0.2027 184/500 [==========>...................] - ETA: 1:39 - loss: 1.3596 - regression_loss: 1.1568 - classification_loss: 0.2028 185/500 [==========>...................] - ETA: 1:39 - loss: 1.3626 - regression_loss: 1.1587 - classification_loss: 0.2039 186/500 [==========>...................] - ETA: 1:39 - loss: 1.3638 - regression_loss: 1.1593 - classification_loss: 0.2045 187/500 [==========>...................] - ETA: 1:38 - loss: 1.3649 - regression_loss: 1.1604 - classification_loss: 0.2044 188/500 [==========>...................] - ETA: 1:38 - loss: 1.3668 - regression_loss: 1.1625 - classification_loss: 0.2043 189/500 [==========>...................] - ETA: 1:38 - loss: 1.3683 - regression_loss: 1.1640 - classification_loss: 0.2042 190/500 [==========>...................] - ETA: 1:37 - loss: 1.3663 - regression_loss: 1.1626 - classification_loss: 0.2038 191/500 [==========>...................] - ETA: 1:37 - loss: 1.3652 - regression_loss: 1.1618 - classification_loss: 0.2033 192/500 [==========>...................] - ETA: 1:37 - loss: 1.3688 - regression_loss: 1.1647 - classification_loss: 0.2041 193/500 [==========>...................] - ETA: 1:36 - loss: 1.3694 - regression_loss: 1.1651 - classification_loss: 0.2043 194/500 [==========>...................] - ETA: 1:36 - loss: 1.3689 - regression_loss: 1.1650 - classification_loss: 0.2039 195/500 [==========>...................] - ETA: 1:36 - loss: 1.3709 - regression_loss: 1.1662 - classification_loss: 0.2047 196/500 [==========>...................] - ETA: 1:35 - loss: 1.3720 - regression_loss: 1.1672 - classification_loss: 0.2049 197/500 [==========>...................] - ETA: 1:35 - loss: 1.3740 - regression_loss: 1.1690 - classification_loss: 0.2050 198/500 [==========>...................] - ETA: 1:35 - loss: 1.3748 - regression_loss: 1.1699 - classification_loss: 0.2050 199/500 [==========>...................] - ETA: 1:34 - loss: 1.3752 - regression_loss: 1.1701 - classification_loss: 0.2051 200/500 [===========>..................] - ETA: 1:34 - loss: 1.3784 - regression_loss: 1.1725 - classification_loss: 0.2058 201/500 [===========>..................] - ETA: 1:34 - loss: 1.3807 - regression_loss: 1.1739 - classification_loss: 0.2068 202/500 [===========>..................] - ETA: 1:33 - loss: 1.3808 - regression_loss: 1.1743 - classification_loss: 0.2065 203/500 [===========>..................] - ETA: 1:33 - loss: 1.3808 - regression_loss: 1.1746 - classification_loss: 0.2062 204/500 [===========>..................] - ETA: 1:33 - loss: 1.3843 - regression_loss: 1.1774 - classification_loss: 0.2069 205/500 [===========>..................] - ETA: 1:32 - loss: 1.3818 - regression_loss: 1.1755 - classification_loss: 0.2064 206/500 [===========>..................] - ETA: 1:32 - loss: 1.3815 - regression_loss: 1.1752 - classification_loss: 0.2063 207/500 [===========>..................] - ETA: 1:32 - loss: 1.3805 - regression_loss: 1.1747 - classification_loss: 0.2059 208/500 [===========>..................] - ETA: 1:32 - loss: 1.3803 - regression_loss: 1.1747 - classification_loss: 0.2057 209/500 [===========>..................] - ETA: 1:31 - loss: 1.3778 - regression_loss: 1.1726 - classification_loss: 0.2053 210/500 [===========>..................] - ETA: 1:31 - loss: 1.3786 - regression_loss: 1.1734 - classification_loss: 0.2052 211/500 [===========>..................] - ETA: 1:31 - loss: 1.3791 - regression_loss: 1.1737 - classification_loss: 0.2054 212/500 [===========>..................] - ETA: 1:30 - loss: 1.3825 - regression_loss: 1.1761 - classification_loss: 0.2064 213/500 [===========>..................] - ETA: 1:30 - loss: 1.3852 - regression_loss: 1.1783 - classification_loss: 0.2069 214/500 [===========>..................] - ETA: 1:30 - loss: 1.3819 - regression_loss: 1.1757 - classification_loss: 0.2062 215/500 [===========>..................] - ETA: 1:29 - loss: 1.3816 - regression_loss: 1.1754 - classification_loss: 0.2062 216/500 [===========>..................] - ETA: 1:29 - loss: 1.3797 - regression_loss: 1.1738 - classification_loss: 0.2059 217/500 [============>.................] - ETA: 1:29 - loss: 1.3812 - regression_loss: 1.1751 - classification_loss: 0.2061 218/500 [============>.................] - ETA: 1:28 - loss: 1.3803 - regression_loss: 1.1742 - classification_loss: 0.2061 219/500 [============>.................] - ETA: 1:28 - loss: 1.3773 - regression_loss: 1.1717 - classification_loss: 0.2056 220/500 [============>.................] - ETA: 1:28 - loss: 1.3756 - regression_loss: 1.1704 - classification_loss: 0.2052 221/500 [============>.................] - ETA: 1:27 - loss: 1.3730 - regression_loss: 1.1683 - classification_loss: 0.2047 222/500 [============>.................] - ETA: 1:27 - loss: 1.3730 - regression_loss: 1.1685 - classification_loss: 0.2046 223/500 [============>.................] - ETA: 1:27 - loss: 1.3715 - regression_loss: 1.1674 - classification_loss: 0.2041 224/500 [============>.................] - ETA: 1:26 - loss: 1.3681 - regression_loss: 1.1645 - classification_loss: 0.2036 225/500 [============>.................] - ETA: 1:26 - loss: 1.3653 - regression_loss: 1.1623 - classification_loss: 0.2031 226/500 [============>.................] - ETA: 1:26 - loss: 1.3665 - regression_loss: 1.1631 - classification_loss: 0.2034 227/500 [============>.................] - ETA: 1:25 - loss: 1.3624 - regression_loss: 1.1596 - classification_loss: 0.2028 228/500 [============>.................] - ETA: 1:25 - loss: 1.3617 - regression_loss: 1.1591 - classification_loss: 0.2026 229/500 [============>.................] - ETA: 1:25 - loss: 1.3598 - regression_loss: 1.1576 - classification_loss: 0.2022 230/500 [============>.................] - ETA: 1:24 - loss: 1.3582 - regression_loss: 1.1564 - classification_loss: 0.2018 231/500 [============>.................] - ETA: 1:24 - loss: 1.3588 - regression_loss: 1.1567 - classification_loss: 0.2022 232/500 [============>.................] - ETA: 1:24 - loss: 1.3570 - regression_loss: 1.1550 - classification_loss: 0.2020 233/500 [============>.................] - ETA: 1:24 - loss: 1.3587 - regression_loss: 1.1563 - classification_loss: 0.2023 234/500 [=============>................] - ETA: 1:23 - loss: 1.3568 - regression_loss: 1.1549 - classification_loss: 0.2019 235/500 [=============>................] - ETA: 1:23 - loss: 1.3541 - regression_loss: 1.1527 - classification_loss: 0.2014 236/500 [=============>................] - ETA: 1:23 - loss: 1.3542 - regression_loss: 1.1531 - classification_loss: 0.2011 237/500 [=============>................] - ETA: 1:22 - loss: 1.3538 - regression_loss: 1.1528 - classification_loss: 0.2010 238/500 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[============================>.] - ETA: 1s - loss: 1.3344 - regression_loss: 1.1377 - classification_loss: 0.1967 495/500 [============================>.] - ETA: 1s - loss: 1.3346 - regression_loss: 1.1380 - classification_loss: 0.1965 496/500 [============================>.] - ETA: 1s - loss: 1.3356 - regression_loss: 1.1390 - classification_loss: 0.1967 497/500 [============================>.] - ETA: 0s - loss: 1.3347 - regression_loss: 1.1382 - classification_loss: 0.1965 498/500 [============================>.] - ETA: 0s - loss: 1.3343 - regression_loss: 1.1380 - classification_loss: 0.1963 499/500 [============================>.] - ETA: 0s - loss: 1.3347 - regression_loss: 1.1382 - classification_loss: 0.1965 500/500 [==============================] - 158s 317ms/step - loss: 1.3344 - regression_loss: 1.1379 - classification_loss: 0.1964 326 instances of class plum with average precision: 0.7892 mAP: 0.7892 Epoch 00011: saving model to ./training/snapshots/resnet101_pascal_11.h5 Epoch 12/150 1/500 [..............................] - ETA: 2:42 - loss: 2.0100 - regression_loss: 1.6460 - classification_loss: 0.3641 2/500 [..............................] - ETA: 2:39 - loss: 1.7657 - regression_loss: 1.3946 - classification_loss: 0.3711 3/500 [..............................] - ETA: 2:43 - loss: 1.5046 - regression_loss: 1.2177 - classification_loss: 0.2868 4/500 [..............................] - ETA: 2:41 - loss: 1.2339 - regression_loss: 0.9941 - classification_loss: 0.2398 5/500 [..............................] - ETA: 2:40 - loss: 1.1323 - regression_loss: 0.9202 - classification_loss: 0.2121 6/500 [..............................] - ETA: 2:40 - loss: 1.2159 - regression_loss: 1.0123 - classification_loss: 0.2035 7/500 [..............................] - ETA: 2:41 - loss: 1.1562 - regression_loss: 0.9683 - classification_loss: 0.1879 8/500 [..............................] - ETA: 2:40 - loss: 1.1202 - regression_loss: 0.9416 - classification_loss: 0.1786 9/500 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[====>.........................] - ETA: 2:11 - loss: 1.3057 - regression_loss: 1.1098 - classification_loss: 0.1959 90/500 [====>.........................] - ETA: 2:10 - loss: 1.2982 - regression_loss: 1.1038 - classification_loss: 0.1945 91/500 [====>.........................] - ETA: 2:10 - loss: 1.2994 - regression_loss: 1.1044 - classification_loss: 0.1950 92/500 [====>.........................] - ETA: 2:10 - loss: 1.3033 - regression_loss: 1.1089 - classification_loss: 0.1945 93/500 [====>.........................] - ETA: 2:10 - loss: 1.2976 - regression_loss: 1.1040 - classification_loss: 0.1937 94/500 [====>.........................] - ETA: 2:09 - loss: 1.2979 - regression_loss: 1.1040 - classification_loss: 0.1939 95/500 [====>.........................] - ETA: 2:09 - loss: 1.2954 - regression_loss: 1.1022 - classification_loss: 0.1932 96/500 [====>.........................] - ETA: 2:09 - loss: 1.2995 - regression_loss: 1.1050 - classification_loss: 0.1945 97/500 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[============================>.] - ETA: 3s - loss: 1.2557 - regression_loss: 1.0688 - classification_loss: 0.1869 490/500 [============================>.] - ETA: 3s - loss: 1.2542 - regression_loss: 1.0675 - classification_loss: 0.1866 491/500 [============================>.] - ETA: 2s - loss: 1.2543 - regression_loss: 1.0675 - classification_loss: 0.1867 492/500 [============================>.] - ETA: 2s - loss: 1.2557 - regression_loss: 1.0688 - classification_loss: 0.1868 493/500 [============================>.] - ETA: 2s - loss: 1.2553 - regression_loss: 1.0686 - classification_loss: 0.1867 494/500 [============================>.] - ETA: 1s - loss: 1.2568 - regression_loss: 1.0697 - classification_loss: 0.1870 495/500 [============================>.] - ETA: 1s - loss: 1.2566 - regression_loss: 1.0696 - classification_loss: 0.1870 496/500 [============================>.] - ETA: 1s - loss: 1.2566 - regression_loss: 1.0696 - classification_loss: 0.1870 497/500 [============================>.] - ETA: 0s - loss: 1.2560 - regression_loss: 1.0691 - classification_loss: 0.1869 498/500 [============================>.] - ETA: 0s - loss: 1.2580 - regression_loss: 1.0706 - classification_loss: 0.1874 499/500 [============================>.] - ETA: 0s - loss: 1.2570 - regression_loss: 1.0697 - classification_loss: 0.1872 500/500 [==============================] - 160s 320ms/step - loss: 1.2560 - regression_loss: 1.0690 - classification_loss: 0.1871 326 instances of class plum with average precision: 0.7943 mAP: 0.7943 Epoch 00012: saving model to ./training/snapshots/resnet101_pascal_12.h5 Epoch 13/150 1/500 [..............................] - ETA: 2:35 - loss: 1.7913 - regression_loss: 1.5427 - classification_loss: 0.2486 2/500 [..............................] - ETA: 2:36 - loss: 1.6899 - regression_loss: 1.4588 - classification_loss: 0.2311 3/500 [..............................] - ETA: 2:37 - loss: 1.3968 - regression_loss: 1.2149 - 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[>.............................] - ETA: 2:35 - loss: 1.2366 - regression_loss: 1.0642 - classification_loss: 0.1724 21/500 [>.............................] - ETA: 2:35 - loss: 1.2163 - regression_loss: 1.0497 - classification_loss: 0.1666 22/500 [>.............................] - ETA: 2:35 - loss: 1.2266 - regression_loss: 1.0597 - classification_loss: 0.1670 23/500 [>.............................] - ETA: 2:34 - loss: 1.2018 - regression_loss: 1.0394 - classification_loss: 0.1625 24/500 [>.............................] - ETA: 2:34 - loss: 1.2007 - regression_loss: 1.0380 - classification_loss: 0.1627 25/500 [>.............................] - ETA: 2:33 - loss: 1.2090 - regression_loss: 1.0424 - classification_loss: 0.1666 26/500 [>.............................] - ETA: 2:33 - loss: 1.2084 - regression_loss: 1.0397 - classification_loss: 0.1687 27/500 [>.............................] - ETA: 2:33 - loss: 1.1907 - regression_loss: 1.0260 - classification_loss: 0.1647 28/500 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[===>..........................] - ETA: 2:17 - loss: 1.2588 - regression_loss: 1.0708 - classification_loss: 0.1880 77/500 [===>..........................] - ETA: 2:17 - loss: 1.2745 - regression_loss: 1.0827 - classification_loss: 0.1917 78/500 [===>..........................] - ETA: 2:17 - loss: 1.2750 - regression_loss: 1.0834 - classification_loss: 0.1915 79/500 [===>..........................] - ETA: 2:16 - loss: 1.2780 - regression_loss: 1.0865 - classification_loss: 0.1915 80/500 [===>..........................] - ETA: 2:16 - loss: 1.2851 - regression_loss: 1.0936 - classification_loss: 0.1915 81/500 [===>..........................] - ETA: 2:16 - loss: 1.2896 - regression_loss: 1.0965 - classification_loss: 0.1932 82/500 [===>..........................] - ETA: 2:15 - loss: 1.2824 - regression_loss: 1.0907 - classification_loss: 0.1917 83/500 [===>..........................] - ETA: 2:15 - loss: 1.2827 - regression_loss: 1.0914 - classification_loss: 0.1913 84/500 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[=====>........................] - ETA: 2:09 - loss: 1.2796 - regression_loss: 1.0881 - classification_loss: 0.1915 101/500 [=====>........................] - ETA: 2:09 - loss: 1.2748 - regression_loss: 1.0842 - classification_loss: 0.1906 102/500 [=====>........................] - ETA: 2:09 - loss: 1.2735 - regression_loss: 1.0830 - classification_loss: 0.1905 103/500 [=====>........................] - ETA: 2:08 - loss: 1.2763 - regression_loss: 1.0841 - classification_loss: 0.1922 104/500 [=====>........................] - ETA: 2:08 - loss: 1.2794 - regression_loss: 1.0864 - classification_loss: 0.1930 105/500 [=====>........................] - ETA: 2:08 - loss: 1.2811 - regression_loss: 1.0876 - classification_loss: 0.1935 106/500 [=====>........................] - ETA: 2:07 - loss: 1.2762 - regression_loss: 1.0837 - classification_loss: 0.1925 107/500 [=====>........................] - ETA: 2:07 - loss: 1.2750 - regression_loss: 1.0830 - classification_loss: 0.1919 108/500 [=====>........................] - ETA: 2:07 - loss: 1.2810 - regression_loss: 1.0880 - classification_loss: 0.1930 109/500 [=====>........................] - ETA: 2:06 - loss: 1.2799 - regression_loss: 1.0868 - classification_loss: 0.1932 110/500 [=====>........................] - ETA: 2:06 - loss: 1.2821 - regression_loss: 1.0889 - classification_loss: 0.1932 111/500 [=====>........................] - ETA: 2:06 - loss: 1.2777 - regression_loss: 1.0855 - classification_loss: 0.1922 112/500 [=====>........................] - ETA: 2:05 - loss: 1.2728 - regression_loss: 1.0814 - classification_loss: 0.1914 113/500 [=====>........................] - ETA: 2:05 - loss: 1.2733 - regression_loss: 1.0823 - classification_loss: 0.1910 114/500 [=====>........................] - ETA: 2:05 - loss: 1.2692 - regression_loss: 1.0784 - classification_loss: 0.1909 115/500 [=====>........................] - ETA: 2:04 - loss: 1.2690 - regression_loss: 1.0782 - classification_loss: 0.1909 116/500 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[=======>......................] - ETA: 1:56 - loss: 1.2373 - regression_loss: 1.0533 - classification_loss: 0.1839 141/500 [=======>......................] - ETA: 1:56 - loss: 1.2359 - regression_loss: 1.0524 - classification_loss: 0.1835 142/500 [=======>......................] - ETA: 1:56 - loss: 1.2340 - regression_loss: 1.0507 - classification_loss: 0.1833 143/500 [=======>......................] - ETA: 1:55 - loss: 1.2342 - regression_loss: 1.0510 - classification_loss: 0.1832 144/500 [=======>......................] - ETA: 1:55 - loss: 1.2356 - regression_loss: 1.0528 - classification_loss: 0.1828 145/500 [=======>......................] - ETA: 1:55 - loss: 1.2345 - regression_loss: 1.0524 - classification_loss: 0.1821 146/500 [=======>......................] - ETA: 1:54 - loss: 1.2337 - regression_loss: 1.0517 - classification_loss: 0.1821 147/500 [=======>......................] - ETA: 1:54 - loss: 1.2323 - regression_loss: 1.0506 - classification_loss: 0.1818 148/500 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[============================>.] - ETA: 2s - loss: 1.2272 - regression_loss: 1.0493 - classification_loss: 0.1779 493/500 [============================>.] - ETA: 2s - loss: 1.2264 - regression_loss: 1.0486 - classification_loss: 0.1778 494/500 [============================>.] - ETA: 1s - loss: 1.2272 - regression_loss: 1.0492 - classification_loss: 0.1780 495/500 [============================>.] - ETA: 1s - loss: 1.2272 - regression_loss: 1.0493 - classification_loss: 0.1779 496/500 [============================>.] - ETA: 1s - loss: 1.2262 - regression_loss: 1.0485 - classification_loss: 0.1778 497/500 [============================>.] - ETA: 0s - loss: 1.2246 - regression_loss: 1.0470 - classification_loss: 0.1775 498/500 [============================>.] - ETA: 0s - loss: 1.2236 - regression_loss: 1.0462 - classification_loss: 0.1774 499/500 [============================>.] - ETA: 0s - loss: 1.2238 - regression_loss: 1.0465 - classification_loss: 0.1773 500/500 [==============================] - 161s 323ms/step - loss: 1.2228 - regression_loss: 1.0458 - classification_loss: 0.1771 326 instances of class plum with average precision: 0.7930 mAP: 0.7930 Epoch 00013: saving model to ./training/snapshots/resnet101_pascal_13.h5 Epoch 14/150 1/500 [..............................] - ETA: 2:33 - loss: 0.9855 - regression_loss: 0.8637 - classification_loss: 0.1218 2/500 [..............................] - ETA: 2:32 - loss: 1.2237 - regression_loss: 1.0578 - classification_loss: 0.1659 3/500 [..............................] - ETA: 2:32 - loss: 1.2426 - regression_loss: 1.0508 - classification_loss: 0.1918 4/500 [..............................] - ETA: 2:33 - loss: 1.0758 - regression_loss: 0.9087 - classification_loss: 0.1670 5/500 [..............................] - ETA: 2:33 - loss: 1.0819 - regression_loss: 0.9231 - classification_loss: 0.1588 6/500 [..............................] - ETA: 2:32 - loss: 1.0437 - regression_loss: 0.8937 - classification_loss: 0.1500 7/500 [..............................] - ETA: 2:32 - loss: 1.0204 - regression_loss: 0.8825 - classification_loss: 0.1379 8/500 [..............................] - ETA: 2:31 - loss: 0.9721 - regression_loss: 0.8384 - classification_loss: 0.1337 9/500 [..............................] - ETA: 2:32 - loss: 0.9979 - regression_loss: 0.8566 - classification_loss: 0.1413 10/500 [..............................] - ETA: 2:33 - loss: 1.0390 - regression_loss: 0.8943 - classification_loss: 0.1446 11/500 [..............................] - ETA: 2:32 - loss: 1.1002 - regression_loss: 0.9411 - classification_loss: 0.1591 12/500 [..............................] - ETA: 2:32 - loss: 1.1007 - regression_loss: 0.9442 - classification_loss: 0.1564 13/500 [..............................] - ETA: 2:32 - loss: 1.1088 - regression_loss: 0.9506 - classification_loss: 0.1583 14/500 [..............................] - ETA: 2:32 - loss: 1.0600 - regression_loss: 0.9101 - classification_loss: 0.1499 15/500 [..............................] - ETA: 2:32 - loss: 1.0311 - regression_loss: 0.8860 - classification_loss: 0.1451 16/500 [..............................] - ETA: 2:32 - loss: 1.0194 - regression_loss: 0.8799 - classification_loss: 0.1394 17/500 [>.............................] - ETA: 2:31 - loss: 1.0360 - regression_loss: 0.8926 - classification_loss: 0.1434 18/500 [>.............................] - ETA: 2:31 - loss: 1.0414 - regression_loss: 0.9001 - classification_loss: 0.1413 19/500 [>.............................] - ETA: 2:31 - loss: 1.0617 - regression_loss: 0.9167 - classification_loss: 0.1449 20/500 [>.............................] - ETA: 2:30 - loss: 1.0947 - regression_loss: 0.9382 - classification_loss: 0.1565 21/500 [>.............................] - ETA: 2:30 - loss: 1.0882 - regression_loss: 0.9339 - classification_loss: 0.1543 22/500 [>.............................] - ETA: 2:29 - loss: 1.1271 - regression_loss: 0.9723 - classification_loss: 0.1548 23/500 [>.............................] - ETA: 2:29 - loss: 1.1099 - regression_loss: 0.9584 - classification_loss: 0.1515 24/500 [>.............................] - ETA: 2:28 - loss: 1.1019 - regression_loss: 0.9531 - classification_loss: 0.1487 25/500 [>.............................] - ETA: 2:28 - loss: 1.1220 - regression_loss: 0.9728 - classification_loss: 0.1492 26/500 [>.............................] - ETA: 2:28 - loss: 1.1436 - regression_loss: 0.9893 - classification_loss: 0.1543 27/500 [>.............................] - ETA: 2:27 - loss: 1.1604 - regression_loss: 1.0031 - classification_loss: 0.1573 28/500 [>.............................] - ETA: 2:27 - loss: 1.1352 - regression_loss: 0.9783 - classification_loss: 0.1569 29/500 [>.............................] - ETA: 2:27 - loss: 1.1243 - regression_loss: 0.9695 - classification_loss: 0.1547 30/500 [>.............................] - ETA: 2:27 - loss: 1.1328 - regression_loss: 0.9765 - classification_loss: 0.1563 31/500 [>.............................] - ETA: 2:26 - loss: 1.1337 - regression_loss: 0.9773 - classification_loss: 0.1563 32/500 [>.............................] - ETA: 2:26 - loss: 1.1232 - regression_loss: 0.9668 - classification_loss: 0.1564 33/500 [>.............................] - ETA: 2:25 - loss: 1.1144 - regression_loss: 0.9589 - classification_loss: 0.1555 34/500 [=>............................] - ETA: 2:25 - loss: 1.1024 - regression_loss: 0.9493 - classification_loss: 0.1532 35/500 [=>............................] - ETA: 2:25 - loss: 1.0948 - regression_loss: 0.9432 - classification_loss: 0.1515 36/500 [=>............................] - ETA: 2:24 - loss: 1.1067 - regression_loss: 0.9527 - classification_loss: 0.1540 37/500 [=>............................] - ETA: 2:24 - loss: 1.1357 - regression_loss: 0.9736 - classification_loss: 0.1621 38/500 [=>............................] - ETA: 2:24 - loss: 1.1548 - regression_loss: 0.9888 - classification_loss: 0.1660 39/500 [=>............................] - ETA: 2:24 - loss: 1.1461 - regression_loss: 0.9821 - classification_loss: 0.1640 40/500 [=>............................] - ETA: 2:23 - loss: 1.1544 - regression_loss: 0.9876 - classification_loss: 0.1668 41/500 [=>............................] - ETA: 2:23 - loss: 1.1443 - regression_loss: 0.9790 - classification_loss: 0.1653 42/500 [=>............................] - ETA: 2:22 - loss: 1.1450 - regression_loss: 0.9795 - classification_loss: 0.1655 43/500 [=>............................] - ETA: 2:22 - loss: 1.1555 - regression_loss: 0.9863 - classification_loss: 0.1692 44/500 [=>............................] - ETA: 2:22 - loss: 1.1589 - regression_loss: 0.9902 - classification_loss: 0.1687 45/500 [=>............................] - ETA: 2:21 - loss: 1.1442 - regression_loss: 0.9783 - classification_loss: 0.1659 46/500 [=>............................] - ETA: 2:21 - loss: 1.1456 - regression_loss: 0.9803 - classification_loss: 0.1653 47/500 [=>............................] - ETA: 2:21 - loss: 1.1447 - regression_loss: 0.9795 - classification_loss: 0.1652 48/500 [=>............................] - ETA: 2:20 - loss: 1.1489 - regression_loss: 0.9818 - classification_loss: 0.1671 49/500 [=>............................] - ETA: 2:20 - loss: 1.1377 - regression_loss: 0.9725 - classification_loss: 0.1652 50/500 [==>...........................] - ETA: 2:20 - loss: 1.1418 - regression_loss: 0.9757 - classification_loss: 0.1660 51/500 [==>...........................] - ETA: 2:19 - loss: 1.1375 - regression_loss: 0.9729 - classification_loss: 0.1646 52/500 [==>...........................] - ETA: 2:19 - loss: 1.1334 - regression_loss: 0.9691 - classification_loss: 0.1642 53/500 [==>...........................] - ETA: 2:19 - loss: 1.1373 - regression_loss: 0.9723 - classification_loss: 0.1650 54/500 [==>...........................] - ETA: 2:18 - loss: 1.1418 - regression_loss: 0.9760 - classification_loss: 0.1658 55/500 [==>...........................] - ETA: 2:18 - loss: 1.1339 - regression_loss: 0.9693 - classification_loss: 0.1646 56/500 [==>...........................] - ETA: 2:18 - loss: 1.1204 - regression_loss: 0.9579 - classification_loss: 0.1625 57/500 [==>...........................] - ETA: 2:18 - loss: 1.1246 - regression_loss: 0.9601 - classification_loss: 0.1645 58/500 [==>...........................] - ETA: 2:18 - loss: 1.1201 - regression_loss: 0.9566 - classification_loss: 0.1635 59/500 [==>...........................] - ETA: 2:17 - loss: 1.1242 - regression_loss: 0.9599 - classification_loss: 0.1644 60/500 [==>...........................] - ETA: 2:17 - loss: 1.1149 - regression_loss: 0.9521 - classification_loss: 0.1629 61/500 [==>...........................] - ETA: 2:17 - loss: 1.1155 - regression_loss: 0.9535 - classification_loss: 0.1619 62/500 [==>...........................] - ETA: 2:17 - loss: 1.1106 - regression_loss: 0.9499 - classification_loss: 0.1607 63/500 [==>...........................] - ETA: 2:16 - loss: 1.0983 - regression_loss: 0.9395 - classification_loss: 0.1588 64/500 [==>...........................] - ETA: 2:16 - loss: 1.0975 - regression_loss: 0.9392 - classification_loss: 0.1582 65/500 [==>...........................] - ETA: 2:15 - loss: 1.1008 - regression_loss: 0.9428 - classification_loss: 0.1580 66/500 [==>...........................] - ETA: 2:15 - loss: 1.1028 - regression_loss: 0.9452 - classification_loss: 0.1576 67/500 [===>..........................] - ETA: 2:15 - loss: 1.0965 - regression_loss: 0.9398 - classification_loss: 0.1567 68/500 [===>..........................] - ETA: 2:14 - loss: 1.0995 - regression_loss: 0.9418 - classification_loss: 0.1577 69/500 [===>..........................] - ETA: 2:14 - loss: 1.1103 - regression_loss: 0.9513 - classification_loss: 0.1589 70/500 [===>..........................] - ETA: 2:14 - loss: 1.1207 - regression_loss: 0.9603 - classification_loss: 0.1604 71/500 [===>..........................] - ETA: 2:14 - loss: 1.1188 - regression_loss: 0.9586 - classification_loss: 0.1601 72/500 [===>..........................] - ETA: 2:13 - loss: 1.1180 - regression_loss: 0.9585 - classification_loss: 0.1595 73/500 [===>..........................] - ETA: 2:13 - loss: 1.1199 - regression_loss: 0.9607 - classification_loss: 0.1593 74/500 [===>..........................] - ETA: 2:13 - loss: 1.1189 - regression_loss: 0.9603 - classification_loss: 0.1586 75/500 [===>..........................] - ETA: 2:13 - loss: 1.1210 - regression_loss: 0.9616 - classification_loss: 0.1594 76/500 [===>..........................] - ETA: 2:12 - loss: 1.1229 - regression_loss: 0.9643 - classification_loss: 0.1586 77/500 [===>..........................] - ETA: 2:12 - loss: 1.1208 - regression_loss: 0.9629 - classification_loss: 0.1579 78/500 [===>..........................] - ETA: 2:12 - loss: 1.1382 - regression_loss: 0.9750 - classification_loss: 0.1633 79/500 [===>..........................] - ETA: 2:11 - loss: 1.1371 - regression_loss: 0.9737 - classification_loss: 0.1634 80/500 [===>..........................] - ETA: 2:11 - loss: 1.1391 - regression_loss: 0.9761 - classification_loss: 0.1630 81/500 [===>..........................] - ETA: 2:10 - loss: 1.1454 - regression_loss: 0.9803 - classification_loss: 0.1651 82/500 [===>..........................] - ETA: 2:10 - loss: 1.1577 - regression_loss: 0.9900 - classification_loss: 0.1677 83/500 [===>..........................] - ETA: 2:10 - loss: 1.1624 - regression_loss: 0.9945 - classification_loss: 0.1679 84/500 [====>.........................] - ETA: 2:10 - loss: 1.1612 - regression_loss: 0.9936 - classification_loss: 0.1675 85/500 [====>.........................] - ETA: 2:09 - loss: 1.1548 - regression_loss: 0.9884 - classification_loss: 0.1664 86/500 [====>.........................] - ETA: 2:09 - loss: 1.1563 - regression_loss: 0.9900 - classification_loss: 0.1663 87/500 [====>.........................] - ETA: 2:09 - loss: 1.1575 - regression_loss: 0.9912 - classification_loss: 0.1663 88/500 [====>.........................] - ETA: 2:08 - loss: 1.1530 - regression_loss: 0.9874 - classification_loss: 0.1656 89/500 [====>.........................] - ETA: 2:08 - loss: 1.1607 - regression_loss: 0.9936 - classification_loss: 0.1671 90/500 [====>.........................] - ETA: 2:08 - loss: 1.1636 - regression_loss: 0.9963 - classification_loss: 0.1672 91/500 [====>.........................] - ETA: 2:07 - loss: 1.1615 - regression_loss: 0.9944 - classification_loss: 0.1671 92/500 [====>.........................] - ETA: 2:07 - loss: 1.1536 - regression_loss: 0.9878 - classification_loss: 0.1658 93/500 [====>.........................] - ETA: 2:07 - loss: 1.1491 - regression_loss: 0.9842 - classification_loss: 0.1649 94/500 [====>.........................] - ETA: 2:07 - loss: 1.1503 - regression_loss: 0.9860 - classification_loss: 0.1643 95/500 [====>.........................] - ETA: 2:06 - loss: 1.1421 - regression_loss: 0.9787 - classification_loss: 0.1634 96/500 [====>.........................] - ETA: 2:06 - loss: 1.1408 - regression_loss: 0.9776 - classification_loss: 0.1633 97/500 [====>.........................] - ETA: 2:06 - loss: 1.1434 - regression_loss: 0.9792 - classification_loss: 0.1643 98/500 [====>.........................] - ETA: 2:05 - loss: 1.1462 - regression_loss: 0.9813 - classification_loss: 0.1648 99/500 [====>.........................] - ETA: 2:05 - loss: 1.1485 - regression_loss: 0.9837 - classification_loss: 0.1647 100/500 [=====>........................] - ETA: 2:05 - loss: 1.1435 - regression_loss: 0.9793 - classification_loss: 0.1642 101/500 [=====>........................] - ETA: 2:05 - loss: 1.1502 - regression_loss: 0.9847 - classification_loss: 0.1654 102/500 [=====>........................] - ETA: 2:04 - loss: 1.1501 - regression_loss: 0.9853 - classification_loss: 0.1649 103/500 [=====>........................] - ETA: 2:04 - loss: 1.1432 - regression_loss: 0.9794 - classification_loss: 0.1638 104/500 [=====>........................] - ETA: 2:04 - loss: 1.1515 - regression_loss: 0.9862 - classification_loss: 0.1654 105/500 [=====>........................] - ETA: 2:04 - loss: 1.1512 - regression_loss: 0.9862 - classification_loss: 0.1649 106/500 [=====>........................] - ETA: 2:03 - loss: 1.1641 - regression_loss: 0.9967 - classification_loss: 0.1674 107/500 [=====>........................] - ETA: 2:03 - loss: 1.1665 - regression_loss: 0.9982 - classification_loss: 0.1682 108/500 [=====>........................] - ETA: 2:03 - loss: 1.1614 - regression_loss: 0.9939 - classification_loss: 0.1675 109/500 [=====>........................] - ETA: 2:02 - loss: 1.1584 - regression_loss: 0.9917 - classification_loss: 0.1667 110/500 [=====>........................] - ETA: 2:02 - loss: 1.1636 - regression_loss: 0.9968 - classification_loss: 0.1668 111/500 [=====>........................] - ETA: 2:02 - loss: 1.1654 - regression_loss: 0.9984 - classification_loss: 0.1670 112/500 [=====>........................] - ETA: 2:01 - loss: 1.1672 - regression_loss: 1.0000 - classification_loss: 0.1672 113/500 [=====>........................] - ETA: 2:01 - loss: 1.1696 - regression_loss: 1.0024 - classification_loss: 0.1672 114/500 [=====>........................] - ETA: 2:01 - loss: 1.1734 - regression_loss: 1.0059 - classification_loss: 0.1675 115/500 [=====>........................] - ETA: 2:00 - loss: 1.1718 - regression_loss: 1.0049 - classification_loss: 0.1669 116/500 [=====>........................] - ETA: 2:00 - loss: 1.1762 - regression_loss: 1.0084 - classification_loss: 0.1678 117/500 [======>.......................] - ETA: 2:00 - loss: 1.1763 - regression_loss: 1.0087 - classification_loss: 0.1676 118/500 [======>.......................] - ETA: 2:00 - loss: 1.1712 - regression_loss: 1.0045 - classification_loss: 0.1667 119/500 [======>.......................] - ETA: 1:59 - loss: 1.1810 - regression_loss: 1.0133 - classification_loss: 0.1677 120/500 [======>.......................] - ETA: 1:59 - loss: 1.1796 - regression_loss: 1.0122 - classification_loss: 0.1675 121/500 [======>.......................] - ETA: 1:59 - loss: 1.1809 - regression_loss: 1.0134 - classification_loss: 0.1675 122/500 [======>.......................] - ETA: 1:58 - loss: 1.1829 - regression_loss: 1.0155 - classification_loss: 0.1674 123/500 [======>.......................] - ETA: 1:58 - loss: 1.1780 - regression_loss: 1.0114 - classification_loss: 0.1666 124/500 [======>.......................] - ETA: 1:58 - loss: 1.1746 - regression_loss: 1.0082 - classification_loss: 0.1664 125/500 [======>.......................] - ETA: 1:57 - loss: 1.1732 - regression_loss: 1.0072 - classification_loss: 0.1660 126/500 [======>.......................] - ETA: 1:57 - loss: 1.1750 - regression_loss: 1.0084 - classification_loss: 0.1666 127/500 [======>.......................] - ETA: 1:57 - loss: 1.1776 - regression_loss: 1.0105 - classification_loss: 0.1671 128/500 [======>.......................] - ETA: 1:56 - loss: 1.1779 - regression_loss: 1.0111 - classification_loss: 0.1668 129/500 [======>.......................] - ETA: 1:56 - loss: 1.1788 - regression_loss: 1.0115 - classification_loss: 0.1672 130/500 [======>.......................] - ETA: 1:56 - loss: 1.1747 - regression_loss: 1.0080 - classification_loss: 0.1667 131/500 [======>.......................] - ETA: 1:55 - loss: 1.1773 - regression_loss: 1.0097 - classification_loss: 0.1676 132/500 [======>.......................] - ETA: 1:55 - loss: 1.1772 - regression_loss: 1.0094 - classification_loss: 0.1678 133/500 [======>.......................] - ETA: 1:55 - loss: 1.1772 - regression_loss: 1.0095 - classification_loss: 0.1677 134/500 [=======>......................] - ETA: 1:54 - loss: 1.1765 - regression_loss: 1.0092 - classification_loss: 0.1673 135/500 [=======>......................] - ETA: 1:54 - loss: 1.1733 - regression_loss: 1.0066 - classification_loss: 0.1667 136/500 [=======>......................] - ETA: 1:54 - loss: 1.1742 - regression_loss: 1.0074 - classification_loss: 0.1667 137/500 [=======>......................] - ETA: 1:54 - loss: 1.1690 - regression_loss: 1.0026 - classification_loss: 0.1664 138/500 [=======>......................] - ETA: 1:53 - loss: 1.1722 - regression_loss: 1.0056 - classification_loss: 0.1667 139/500 [=======>......................] - ETA: 1:53 - loss: 1.1695 - regression_loss: 1.0033 - classification_loss: 0.1662 140/500 [=======>......................] - ETA: 1:53 - loss: 1.1725 - regression_loss: 1.0060 - classification_loss: 0.1665 141/500 [=======>......................] - ETA: 1:52 - loss: 1.1762 - regression_loss: 1.0090 - classification_loss: 0.1671 142/500 [=======>......................] - ETA: 1:52 - loss: 1.1784 - regression_loss: 1.0104 - classification_loss: 0.1680 143/500 [=======>......................] - ETA: 1:52 - loss: 1.1767 - regression_loss: 1.0091 - classification_loss: 0.1676 144/500 [=======>......................] - ETA: 1:51 - loss: 1.1789 - regression_loss: 1.0106 - classification_loss: 0.1684 145/500 [=======>......................] - ETA: 1:51 - loss: 1.1781 - regression_loss: 1.0100 - classification_loss: 0.1680 146/500 [=======>......................] - ETA: 1:51 - loss: 1.1839 - regression_loss: 1.0143 - classification_loss: 0.1696 147/500 [=======>......................] - ETA: 1:50 - loss: 1.1846 - regression_loss: 1.0146 - classification_loss: 0.1700 148/500 [=======>......................] - ETA: 1:50 - loss: 1.1872 - regression_loss: 1.0168 - classification_loss: 0.1704 149/500 [=======>......................] - ETA: 1:50 - loss: 1.1864 - regression_loss: 1.0164 - classification_loss: 0.1701 150/500 [========>.....................] - ETA: 1:49 - loss: 1.1833 - regression_loss: 1.0136 - classification_loss: 0.1697 151/500 [========>.....................] - ETA: 1:49 - loss: 1.1849 - regression_loss: 1.0156 - classification_loss: 0.1693 152/500 [========>.....................] - ETA: 1:49 - loss: 1.1809 - regression_loss: 1.0122 - classification_loss: 0.1687 153/500 [========>.....................] - ETA: 1:49 - loss: 1.1800 - regression_loss: 1.0116 - classification_loss: 0.1684 154/500 [========>.....................] - ETA: 1:48 - loss: 1.1817 - regression_loss: 1.0121 - classification_loss: 0.1697 155/500 [========>.....................] - ETA: 1:48 - loss: 1.1824 - regression_loss: 1.0126 - classification_loss: 0.1698 156/500 [========>.....................] - ETA: 1:48 - loss: 1.1805 - regression_loss: 1.0111 - classification_loss: 0.1694 157/500 [========>.....................] - ETA: 1:47 - loss: 1.1823 - regression_loss: 1.0129 - classification_loss: 0.1694 158/500 [========>.....................] - ETA: 1:47 - loss: 1.1805 - regression_loss: 1.0115 - classification_loss: 0.1690 159/500 [========>.....................] - ETA: 1:47 - loss: 1.1785 - regression_loss: 1.0100 - classification_loss: 0.1685 160/500 [========>.....................] - ETA: 1:46 - loss: 1.1793 - regression_loss: 1.0111 - classification_loss: 0.1682 161/500 [========>.....................] - ETA: 1:46 - loss: 1.1845 - regression_loss: 1.0155 - classification_loss: 0.1690 162/500 [========>.....................] - ETA: 1:46 - loss: 1.1834 - regression_loss: 1.0146 - classification_loss: 0.1687 163/500 [========>.....................] - ETA: 1:46 - loss: 1.1854 - regression_loss: 1.0163 - classification_loss: 0.1691 164/500 [========>.....................] - ETA: 1:45 - loss: 1.1856 - regression_loss: 1.0165 - classification_loss: 0.1691 165/500 [========>.....................] - ETA: 1:45 - loss: 1.1827 - regression_loss: 1.0142 - classification_loss: 0.1685 166/500 [========>.....................] - ETA: 1:45 - loss: 1.1818 - regression_loss: 1.0136 - classification_loss: 0.1682 167/500 [=========>....................] - ETA: 1:44 - loss: 1.1809 - regression_loss: 1.0126 - classification_loss: 0.1683 168/500 [=========>....................] - ETA: 1:44 - loss: 1.1818 - regression_loss: 1.0135 - classification_loss: 0.1682 169/500 [=========>....................] - ETA: 1:44 - loss: 1.1815 - regression_loss: 1.0132 - classification_loss: 0.1683 170/500 [=========>....................] - ETA: 1:43 - loss: 1.1876 - regression_loss: 1.0182 - classification_loss: 0.1694 171/500 [=========>....................] - ETA: 1:43 - loss: 1.1856 - regression_loss: 1.0164 - classification_loss: 0.1692 172/500 [=========>....................] - ETA: 1:43 - loss: 1.1821 - regression_loss: 1.0133 - classification_loss: 0.1688 173/500 [=========>....................] - ETA: 1:42 - loss: 1.1780 - regression_loss: 1.0098 - classification_loss: 0.1682 174/500 [=========>....................] - ETA: 1:42 - loss: 1.1757 - regression_loss: 1.0079 - classification_loss: 0.1679 175/500 [=========>....................] - ETA: 1:42 - loss: 1.1741 - regression_loss: 1.0066 - classification_loss: 0.1675 176/500 [=========>....................] - ETA: 1:41 - loss: 1.1723 - regression_loss: 1.0052 - classification_loss: 0.1671 177/500 [=========>....................] - ETA: 1:41 - loss: 1.1700 - regression_loss: 1.0033 - classification_loss: 0.1667 178/500 [=========>....................] - ETA: 1:41 - loss: 1.1726 - regression_loss: 1.0052 - classification_loss: 0.1675 179/500 [=========>....................] - ETA: 1:41 - loss: 1.1728 - regression_loss: 1.0050 - classification_loss: 0.1679 180/500 [=========>....................] - ETA: 1:40 - loss: 1.1762 - regression_loss: 1.0075 - classification_loss: 0.1687 181/500 [=========>....................] - ETA: 1:40 - loss: 1.1747 - regression_loss: 1.0064 - classification_loss: 0.1683 182/500 [=========>....................] - ETA: 1:40 - loss: 1.1706 - regression_loss: 1.0030 - classification_loss: 0.1677 183/500 [=========>....................] - ETA: 1:39 - loss: 1.1694 - regression_loss: 1.0021 - classification_loss: 0.1674 184/500 [==========>...................] - ETA: 1:39 - loss: 1.1736 - regression_loss: 1.0058 - classification_loss: 0.1678 185/500 [==========>...................] - ETA: 1:39 - loss: 1.1720 - regression_loss: 1.0046 - classification_loss: 0.1674 186/500 [==========>...................] - ETA: 1:38 - loss: 1.1704 - regression_loss: 1.0033 - classification_loss: 0.1670 187/500 [==========>...................] - ETA: 1:38 - loss: 1.1686 - regression_loss: 1.0018 - classification_loss: 0.1668 188/500 [==========>...................] - ETA: 1:38 - loss: 1.1651 - regression_loss: 0.9989 - classification_loss: 0.1662 189/500 [==========>...................] - ETA: 1:38 - loss: 1.1647 - regression_loss: 0.9987 - classification_loss: 0.1660 190/500 [==========>...................] - ETA: 1:37 - loss: 1.1616 - regression_loss: 0.9960 - 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[============================>.] - ETA: 4s - loss: 1.1444 - regression_loss: 0.9813 - classification_loss: 0.1632 488/500 [============================>.] - ETA: 3s - loss: 1.1443 - regression_loss: 0.9811 - classification_loss: 0.1631 489/500 [============================>.] - ETA: 3s - loss: 1.1427 - regression_loss: 0.9797 - classification_loss: 0.1630 490/500 [============================>.] - ETA: 3s - loss: 1.1433 - regression_loss: 0.9802 - classification_loss: 0.1631 491/500 [============================>.] - ETA: 2s - loss: 1.1425 - regression_loss: 0.9795 - classification_loss: 0.1630 492/500 [============================>.] - ETA: 2s - loss: 1.1429 - regression_loss: 0.9798 - classification_loss: 0.1631 493/500 [============================>.] - ETA: 2s - loss: 1.1430 - regression_loss: 0.9799 - classification_loss: 0.1631 494/500 [============================>.] - ETA: 1s - loss: 1.1419 - regression_loss: 0.9788 - classification_loss: 0.1630 495/500 [============================>.] - ETA: 1s - loss: 1.1414 - regression_loss: 0.9786 - classification_loss: 0.1629 496/500 [============================>.] - ETA: 1s - loss: 1.1422 - regression_loss: 0.9792 - classification_loss: 0.1630 497/500 [============================>.] - ETA: 0s - loss: 1.1428 - regression_loss: 0.9799 - classification_loss: 0.1630 498/500 [============================>.] - ETA: 0s - loss: 1.1431 - regression_loss: 0.9802 - classification_loss: 0.1629 499/500 [============================>.] - ETA: 0s - loss: 1.1439 - regression_loss: 0.9809 - classification_loss: 0.1631 500/500 [==============================] - 158s 316ms/step - loss: 1.1425 - regression_loss: 0.9797 - classification_loss: 0.1629 326 instances of class plum with average precision: 0.7675 mAP: 0.7675 Epoch 00014: saving model to ./training/snapshots/resnet101_pascal_14.h5 Epoch 15/150 1/500 [..............................] - ETA: 2:41 - loss: 0.2964 - regression_loss: 0.2386 - classification_loss: 0.0579 2/500 [..............................] - ETA: 2:37 - loss: 0.3652 - regression_loss: 0.2944 - classification_loss: 0.0708 3/500 [..............................] - ETA: 2:36 - loss: 0.6952 - regression_loss: 0.5956 - classification_loss: 0.0996 4/500 [..............................] - ETA: 2:36 - loss: 0.8345 - regression_loss: 0.7153 - classification_loss: 0.1191 5/500 [..............................] - ETA: 2:36 - loss: 0.8081 - regression_loss: 0.6986 - classification_loss: 0.1096 6/500 [..............................] - ETA: 2:36 - loss: 0.9090 - regression_loss: 0.7856 - classification_loss: 0.1234 7/500 [..............................] - ETA: 2:36 - loss: 1.0240 - regression_loss: 0.8824 - classification_loss: 0.1416 8/500 [..............................] - ETA: 2:35 - loss: 1.0028 - regression_loss: 0.8652 - classification_loss: 0.1377 9/500 [..............................] - ETA: 2:34 - loss: 1.0064 - regression_loss: 0.8693 - classification_loss: 0.1371 10/500 [..............................] - ETA: 2:35 - loss: 1.0787 - regression_loss: 0.9278 - classification_loss: 0.1509 11/500 [..............................] - ETA: 2:34 - loss: 1.0969 - regression_loss: 0.9468 - classification_loss: 0.1501 12/500 [..............................] - ETA: 2:34 - loss: 1.1170 - regression_loss: 0.9706 - classification_loss: 0.1464 13/500 [..............................] - ETA: 2:34 - loss: 1.1380 - regression_loss: 0.9862 - classification_loss: 0.1519 14/500 [..............................] - ETA: 2:34 - loss: 1.1977 - regression_loss: 1.0351 - classification_loss: 0.1627 15/500 [..............................] - ETA: 2:33 - loss: 1.2147 - regression_loss: 1.0510 - classification_loss: 0.1637 16/500 [..............................] - ETA: 2:33 - loss: 1.2150 - regression_loss: 1.0499 - classification_loss: 0.1651 17/500 [>.............................] - ETA: 2:33 - loss: 1.1897 - regression_loss: 1.0267 - classification_loss: 0.1631 18/500 [>.............................] - ETA: 2:33 - loss: 1.2138 - regression_loss: 1.0434 - classification_loss: 0.1704 19/500 [>.............................] - ETA: 2:32 - loss: 1.2328 - regression_loss: 1.0594 - classification_loss: 0.1734 20/500 [>.............................] - ETA: 2:32 - loss: 1.2276 - regression_loss: 1.0556 - classification_loss: 0.1719 21/500 [>.............................] - ETA: 2:32 - loss: 1.1926 - regression_loss: 1.0257 - classification_loss: 0.1669 22/500 [>.............................] - ETA: 2:31 - loss: 1.2203 - regression_loss: 1.0489 - classification_loss: 0.1715 23/500 [>.............................] - ETA: 2:32 - loss: 1.2145 - regression_loss: 1.0443 - classification_loss: 0.1702 24/500 [>.............................] - ETA: 2:32 - loss: 1.2057 - regression_loss: 1.0382 - classification_loss: 0.1675 25/500 [>.............................] - ETA: 2:32 - loss: 1.1761 - regression_loss: 1.0112 - classification_loss: 0.1649 26/500 [>.............................] - ETA: 2:31 - loss: 1.1505 - regression_loss: 0.9899 - classification_loss: 0.1606 27/500 [>.............................] - ETA: 2:31 - loss: 1.1594 - regression_loss: 0.9979 - classification_loss: 0.1616 28/500 [>.............................] - ETA: 2:30 - loss: 1.1447 - regression_loss: 0.9854 - classification_loss: 0.1593 29/500 [>.............................] - ETA: 2:30 - loss: 1.1451 - regression_loss: 0.9873 - classification_loss: 0.1578 30/500 [>.............................] - ETA: 2:30 - loss: 1.1489 - regression_loss: 0.9908 - classification_loss: 0.1581 31/500 [>.............................] - ETA: 2:29 - loss: 1.1631 - regression_loss: 0.9994 - classification_loss: 0.1637 32/500 [>.............................] - ETA: 2:29 - loss: 1.1568 - regression_loss: 0.9947 - classification_loss: 0.1621 33/500 [>.............................] - ETA: 2:29 - loss: 1.1584 - regression_loss: 0.9969 - classification_loss: 0.1615 34/500 [=>............................] - ETA: 2:29 - loss: 1.1449 - regression_loss: 0.9869 - classification_loss: 0.1580 35/500 [=>............................] - ETA: 2:29 - loss: 1.1583 - regression_loss: 0.9942 - classification_loss: 0.1642 36/500 [=>............................] - ETA: 2:28 - loss: 1.1431 - regression_loss: 0.9770 - classification_loss: 0.1661 37/500 [=>............................] - ETA: 2:28 - loss: 1.1286 - regression_loss: 0.9654 - classification_loss: 0.1632 38/500 [=>............................] - ETA: 2:28 - loss: 1.1214 - regression_loss: 0.9600 - classification_loss: 0.1615 39/500 [=>............................] - ETA: 2:28 - loss: 1.1248 - regression_loss: 0.9638 - classification_loss: 0.1611 40/500 [=>............................] - ETA: 2:27 - loss: 1.1173 - regression_loss: 0.9576 - classification_loss: 0.1597 41/500 [=>............................] - ETA: 2:27 - loss: 1.1126 - regression_loss: 0.9536 - classification_loss: 0.1590 42/500 [=>............................] - ETA: 2:27 - loss: 1.0940 - regression_loss: 0.9378 - classification_loss: 0.1562 43/500 [=>............................] - ETA: 2:26 - loss: 1.0810 - regression_loss: 0.9274 - classification_loss: 0.1536 44/500 [=>............................] - ETA: 2:26 - loss: 1.0726 - regression_loss: 0.9203 - classification_loss: 0.1523 45/500 [=>............................] - ETA: 2:26 - loss: 1.0733 - regression_loss: 0.9215 - classification_loss: 0.1518 46/500 [=>............................] - ETA: 2:26 - loss: 1.0685 - regression_loss: 0.9174 - classification_loss: 0.1510 47/500 [=>............................] - ETA: 2:25 - loss: 1.0550 - regression_loss: 0.9062 - classification_loss: 0.1489 48/500 [=>............................] - ETA: 2:25 - loss: 1.0455 - regression_loss: 0.8983 - classification_loss: 0.1472 49/500 [=>............................] - ETA: 2:24 - loss: 1.0529 - regression_loss: 0.9046 - classification_loss: 0.1483 50/500 [==>...........................] - ETA: 2:24 - loss: 1.0549 - regression_loss: 0.9073 - classification_loss: 0.1476 51/500 [==>...........................] - ETA: 2:24 - loss: 1.0609 - regression_loss: 0.9123 - classification_loss: 0.1486 52/500 [==>...........................] - ETA: 2:24 - loss: 1.0721 - regression_loss: 0.9218 - classification_loss: 0.1503 53/500 [==>...........................] - ETA: 2:23 - loss: 1.0705 - regression_loss: 0.9209 - classification_loss: 0.1497 54/500 [==>...........................] - ETA: 2:23 - loss: 1.0746 - regression_loss: 0.9251 - classification_loss: 0.1495 55/500 [==>...........................] - ETA: 2:23 - loss: 1.0739 - regression_loss: 0.9236 - classification_loss: 0.1503 56/500 [==>...........................] - ETA: 2:23 - loss: 1.0738 - regression_loss: 0.9236 - classification_loss: 0.1502 57/500 [==>...........................] - ETA: 2:23 - loss: 1.0711 - regression_loss: 0.9215 - classification_loss: 0.1496 58/500 [==>...........................] - ETA: 2:22 - loss: 1.0819 - regression_loss: 0.9296 - classification_loss: 0.1523 59/500 [==>...........................] - ETA: 2:22 - loss: 1.0833 - regression_loss: 0.9309 - classification_loss: 0.1524 60/500 [==>...........................] - ETA: 2:22 - loss: 1.0762 - regression_loss: 0.9250 - classification_loss: 0.1512 61/500 [==>...........................] - ETA: 2:21 - loss: 1.0741 - regression_loss: 0.9230 - classification_loss: 0.1510 62/500 [==>...........................] - ETA: 2:21 - loss: 1.0798 - regression_loss: 0.9257 - classification_loss: 0.1542 63/500 [==>...........................] - ETA: 2:21 - loss: 1.0751 - regression_loss: 0.9222 - classification_loss: 0.1529 64/500 [==>...........................] - ETA: 2:21 - loss: 1.0732 - regression_loss: 0.9208 - classification_loss: 0.1524 65/500 [==>...........................] - ETA: 2:20 - loss: 1.0799 - regression_loss: 0.9262 - classification_loss: 0.1537 66/500 [==>...........................] - ETA: 2:20 - loss: 1.0753 - regression_loss: 0.9229 - classification_loss: 0.1524 67/500 [===>..........................] - ETA: 2:20 - loss: 1.0839 - regression_loss: 0.9291 - classification_loss: 0.1548 68/500 [===>..........................] - ETA: 2:20 - loss: 1.0825 - regression_loss: 0.9276 - classification_loss: 0.1549 69/500 [===>..........................] - ETA: 2:20 - loss: 1.0928 - regression_loss: 0.9321 - classification_loss: 0.1607 70/500 [===>..........................] - ETA: 2:19 - loss: 1.0998 - regression_loss: 0.9386 - classification_loss: 0.1612 71/500 [===>..........................] - ETA: 2:19 - loss: 1.0900 - regression_loss: 0.9303 - classification_loss: 0.1597 72/500 [===>..........................] - ETA: 2:19 - loss: 1.0867 - regression_loss: 0.9278 - classification_loss: 0.1589 73/500 [===>..........................] - ETA: 2:18 - loss: 1.0806 - regression_loss: 0.9227 - classification_loss: 0.1579 74/500 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[=====>........................] - ETA: 2:07 - loss: 1.0881 - regression_loss: 0.9323 - classification_loss: 0.1557 107/500 [=====>........................] - ETA: 2:07 - loss: 1.1016 - regression_loss: 0.9412 - classification_loss: 0.1604 108/500 [=====>........................] - ETA: 2:07 - loss: 1.1078 - regression_loss: 0.9467 - classification_loss: 0.1612 109/500 [=====>........................] - ETA: 2:06 - loss: 1.1031 - regression_loss: 0.9427 - classification_loss: 0.1605 110/500 [=====>........................] - ETA: 2:06 - loss: 1.0986 - regression_loss: 0.9384 - classification_loss: 0.1602 111/500 [=====>........................] - ETA: 2:06 - loss: 1.0954 - regression_loss: 0.9358 - classification_loss: 0.1597 112/500 [=====>........................] - ETA: 2:05 - loss: 1.1050 - regression_loss: 0.9441 - classification_loss: 0.1609 113/500 [=====>........................] - ETA: 2:05 - loss: 1.1148 - regression_loss: 0.9522 - classification_loss: 0.1626 114/500 [=====>........................] - ETA: 2:05 - loss: 1.1110 - regression_loss: 0.9490 - classification_loss: 0.1620 115/500 [=====>........................] - ETA: 2:04 - loss: 1.1064 - regression_loss: 0.9450 - classification_loss: 0.1614 116/500 [=====>........................] - ETA: 2:04 - loss: 1.1074 - regression_loss: 0.9460 - classification_loss: 0.1615 117/500 [======>.......................] - ETA: 2:03 - loss: 1.1037 - regression_loss: 0.9428 - classification_loss: 0.1609 118/500 [======>.......................] - ETA: 2:03 - loss: 1.1008 - regression_loss: 0.9403 - classification_loss: 0.1606 119/500 [======>.......................] - ETA: 2:03 - loss: 1.0976 - regression_loss: 0.9372 - classification_loss: 0.1604 120/500 [======>.......................] - ETA: 2:02 - loss: 1.0980 - regression_loss: 0.9373 - classification_loss: 0.1607 121/500 [======>.......................] - ETA: 2:02 - loss: 1.0958 - regression_loss: 0.9355 - classification_loss: 0.1603 122/500 [======>.......................] - ETA: 2:02 - loss: 1.0983 - regression_loss: 0.9377 - classification_loss: 0.1606 123/500 [======>.......................] - ETA: 2:01 - loss: 1.1018 - regression_loss: 0.9394 - classification_loss: 0.1623 124/500 [======>.......................] - ETA: 2:01 - loss: 1.0997 - regression_loss: 0.9377 - classification_loss: 0.1621 125/500 [======>.......................] - ETA: 2:01 - loss: 1.1007 - regression_loss: 0.9378 - classification_loss: 0.1629 126/500 [======>.......................] - ETA: 2:00 - loss: 1.0958 - regression_loss: 0.9336 - classification_loss: 0.1622 127/500 [======>.......................] - ETA: 2:00 - loss: 1.0931 - regression_loss: 0.9314 - classification_loss: 0.1616 128/500 [======>.......................] - ETA: 2:00 - loss: 1.0966 - regression_loss: 0.9343 - classification_loss: 0.1623 129/500 [======>.......................] - ETA: 1:59 - loss: 1.0953 - regression_loss: 0.9335 - classification_loss: 0.1618 130/500 [======>.......................] - ETA: 1:59 - loss: 1.0991 - regression_loss: 0.9369 - classification_loss: 0.1622 131/500 [======>.......................] - ETA: 1:59 - loss: 1.0951 - regression_loss: 0.9335 - classification_loss: 0.1616 132/500 [======>.......................] - ETA: 1:59 - loss: 1.0915 - regression_loss: 0.9306 - classification_loss: 0.1610 133/500 [======>.......................] - ETA: 1:58 - loss: 1.0920 - regression_loss: 0.9311 - classification_loss: 0.1609 134/500 [=======>......................] - ETA: 1:58 - loss: 1.0970 - regression_loss: 0.9355 - classification_loss: 0.1614 135/500 [=======>......................] - ETA: 1:57 - loss: 1.0947 - regression_loss: 0.9338 - classification_loss: 0.1609 136/500 [=======>......................] - ETA: 1:57 - loss: 1.1002 - regression_loss: 0.9379 - classification_loss: 0.1623 137/500 [=======>......................] - ETA: 1:57 - loss: 1.1040 - regression_loss: 0.9403 - classification_loss: 0.1637 138/500 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[=======>......................] - ETA: 1:54 - loss: 1.1054 - regression_loss: 0.9422 - classification_loss: 0.1631 147/500 [=======>......................] - ETA: 1:53 - loss: 1.1076 - regression_loss: 0.9445 - classification_loss: 0.1631 148/500 [=======>......................] - ETA: 1:53 - loss: 1.1047 - regression_loss: 0.9419 - classification_loss: 0.1627 149/500 [=======>......................] - ETA: 1:53 - loss: 1.1086 - regression_loss: 0.9449 - classification_loss: 0.1638 150/500 [========>.....................] - ETA: 1:53 - loss: 1.1092 - regression_loss: 0.9454 - classification_loss: 0.1638 151/500 [========>.....................] - ETA: 1:52 - loss: 1.1138 - regression_loss: 0.9493 - classification_loss: 0.1645 152/500 [========>.....................] - ETA: 1:52 - loss: 1.1090 - regression_loss: 0.9453 - classification_loss: 0.1637 153/500 [========>.....................] - ETA: 1:52 - loss: 1.1118 - regression_loss: 0.9473 - classification_loss: 0.1645 154/500 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[=========>....................] - ETA: 1:44 - loss: 1.1098 - regression_loss: 0.9478 - classification_loss: 0.1620 179/500 [=========>....................] - ETA: 1:43 - loss: 1.1100 - regression_loss: 0.9481 - classification_loss: 0.1619 180/500 [=========>....................] - ETA: 1:43 - loss: 1.1126 - regression_loss: 0.9502 - classification_loss: 0.1624 181/500 [=========>....................] - ETA: 1:42 - loss: 1.1121 - regression_loss: 0.9500 - classification_loss: 0.1621 182/500 [=========>....................] - ETA: 1:42 - loss: 1.1130 - regression_loss: 0.9504 - classification_loss: 0.1626 183/500 [=========>....................] - ETA: 1:42 - loss: 1.1129 - regression_loss: 0.9505 - classification_loss: 0.1624 184/500 [==========>...................] - ETA: 1:42 - loss: 1.1124 - regression_loss: 0.9502 - classification_loss: 0.1622 185/500 [==========>...................] - ETA: 1:41 - loss: 1.1108 - regression_loss: 0.9491 - classification_loss: 0.1617 186/500 [==========>...................] - ETA: 1:41 - loss: 1.1096 - regression_loss: 0.9482 - classification_loss: 0.1614 187/500 [==========>...................] - ETA: 1:41 - loss: 1.1085 - regression_loss: 0.9476 - classification_loss: 0.1609 188/500 [==========>...................] - ETA: 1:40 - loss: 1.1086 - regression_loss: 0.9478 - classification_loss: 0.1608 189/500 [==========>...................] - ETA: 1:40 - loss: 1.1045 - regression_loss: 0.9441 - classification_loss: 0.1604 190/500 [==========>...................] - ETA: 1:40 - loss: 1.1048 - regression_loss: 0.9442 - classification_loss: 0.1605 191/500 [==========>...................] - ETA: 1:39 - loss: 1.1027 - regression_loss: 0.9426 - classification_loss: 0.1601 192/500 [==========>...................] - ETA: 1:39 - loss: 1.1016 - regression_loss: 0.9418 - classification_loss: 0.1597 193/500 [==========>...................] - ETA: 1:39 - loss: 1.1023 - regression_loss: 0.9424 - classification_loss: 0.1599 194/500 [==========>...................] - ETA: 1:38 - loss: 1.1019 - regression_loss: 0.9423 - classification_loss: 0.1596 195/500 [==========>...................] - ETA: 1:38 - loss: 1.1047 - regression_loss: 0.9443 - classification_loss: 0.1603 196/500 [==========>...................] - ETA: 1:38 - loss: 1.1084 - regression_loss: 0.9478 - classification_loss: 0.1607 197/500 [==========>...................] - ETA: 1:37 - loss: 1.1110 - regression_loss: 0.9497 - classification_loss: 0.1613 198/500 [==========>...................] - ETA: 1:37 - loss: 1.1173 - regression_loss: 0.9538 - classification_loss: 0.1635 199/500 [==========>...................] - ETA: 1:37 - loss: 1.1180 - regression_loss: 0.9547 - classification_loss: 0.1634 200/500 [===========>..................] - ETA: 1:36 - loss: 1.1179 - regression_loss: 0.9549 - classification_loss: 0.1631 201/500 [===========>..................] - ETA: 1:36 - loss: 1.1173 - regression_loss: 0.9547 - classification_loss: 0.1626 202/500 [===========>..................] - ETA: 1:36 - loss: 1.1176 - regression_loss: 0.9550 - classification_loss: 0.1626 203/500 [===========>..................] - ETA: 1:35 - loss: 1.1200 - regression_loss: 0.9574 - classification_loss: 0.1626 204/500 [===========>..................] - ETA: 1:35 - loss: 1.1180 - regression_loss: 0.9558 - classification_loss: 0.1622 205/500 [===========>..................] - ETA: 1:35 - loss: 1.1144 - regression_loss: 0.9527 - classification_loss: 0.1617 206/500 [===========>..................] - ETA: 1:34 - loss: 1.1186 - regression_loss: 0.9561 - classification_loss: 0.1626 207/500 [===========>..................] - ETA: 1:34 - loss: 1.1184 - regression_loss: 0.9560 - classification_loss: 0.1624 208/500 [===========>..................] - ETA: 1:34 - loss: 1.1222 - regression_loss: 0.9584 - classification_loss: 0.1638 209/500 [===========>..................] - ETA: 1:33 - loss: 1.1221 - regression_loss: 0.9582 - classification_loss: 0.1639 210/500 [===========>..................] - ETA: 1:33 - loss: 1.1249 - regression_loss: 0.9604 - classification_loss: 0.1645 211/500 [===========>..................] - ETA: 1:33 - loss: 1.1240 - regression_loss: 0.9594 - classification_loss: 0.1646 212/500 [===========>..................] - ETA: 1:32 - loss: 1.1257 - regression_loss: 0.9609 - classification_loss: 0.1648 213/500 [===========>..................] - ETA: 1:32 - loss: 1.1279 - regression_loss: 0.9627 - classification_loss: 0.1652 214/500 [===========>..................] - ETA: 1:32 - loss: 1.1290 - regression_loss: 0.9641 - classification_loss: 0.1649 215/500 [===========>..................] - ETA: 1:31 - loss: 1.1325 - regression_loss: 0.9669 - classification_loss: 0.1657 216/500 [===========>..................] - ETA: 1:31 - loss: 1.1299 - regression_loss: 0.9646 - classification_loss: 0.1652 217/500 [============>.................] - ETA: 1:31 - loss: 1.1268 - regression_loss: 0.9620 - classification_loss: 0.1647 218/500 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[============>.................] - ETA: 1:28 - loss: 1.1388 - regression_loss: 0.9729 - classification_loss: 0.1660 227/500 [============>.................] - ETA: 1:28 - loss: 1.1371 - regression_loss: 0.9715 - classification_loss: 0.1656 228/500 [============>.................] - ETA: 1:27 - loss: 1.1338 - regression_loss: 0.9686 - classification_loss: 0.1651 229/500 [============>.................] - ETA: 1:27 - loss: 1.1336 - regression_loss: 0.9685 - classification_loss: 0.1651 230/500 [============>.................] - ETA: 1:27 - loss: 1.1332 - regression_loss: 0.9684 - classification_loss: 0.1648 231/500 [============>.................] - ETA: 1:26 - loss: 1.1313 - regression_loss: 0.9669 - classification_loss: 0.1645 232/500 [============>.................] - ETA: 1:26 - loss: 1.1359 - regression_loss: 0.9705 - classification_loss: 0.1654 233/500 [============>.................] - ETA: 1:26 - loss: 1.1348 - regression_loss: 0.9695 - classification_loss: 0.1653 234/500 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[===========================>..] - ETA: 8s - loss: 1.1051 - regression_loss: 0.9462 - classification_loss: 0.1588 475/500 [===========================>..] - ETA: 8s - loss: 1.1046 - regression_loss: 0.9459 - classification_loss: 0.1587 476/500 [===========================>..] - ETA: 7s - loss: 1.1057 - regression_loss: 0.9468 - classification_loss: 0.1588 477/500 [===========================>..] - ETA: 7s - loss: 1.1050 - regression_loss: 0.9463 - classification_loss: 0.1587 478/500 [===========================>..] - ETA: 7s - loss: 1.1041 - regression_loss: 0.9455 - classification_loss: 0.1586 479/500 [===========================>..] - ETA: 6s - loss: 1.1052 - regression_loss: 0.9465 - classification_loss: 0.1587 480/500 [===========================>..] - ETA: 6s - loss: 1.1063 - regression_loss: 0.9475 - classification_loss: 0.1588 481/500 [===========================>..] - ETA: 6s - loss: 1.1059 - regression_loss: 0.9472 - classification_loss: 0.1587 482/500 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[============================>.] - ETA: 3s - loss: 1.1019 - regression_loss: 0.9438 - classification_loss: 0.1581 491/500 [============================>.] - ETA: 2s - loss: 1.1011 - regression_loss: 0.9431 - classification_loss: 0.1580 492/500 [============================>.] - ETA: 2s - loss: 1.1005 - regression_loss: 0.9426 - classification_loss: 0.1579 493/500 [============================>.] - ETA: 2s - loss: 1.0995 - regression_loss: 0.9417 - classification_loss: 0.1578 494/500 [============================>.] - ETA: 1s - loss: 1.0995 - regression_loss: 0.9418 - classification_loss: 0.1577 495/500 [============================>.] - ETA: 1s - loss: 1.0989 - regression_loss: 0.9413 - classification_loss: 0.1576 496/500 [============================>.] - ETA: 1s - loss: 1.1001 - regression_loss: 0.9422 - classification_loss: 0.1578 497/500 [============================>.] - ETA: 0s - loss: 1.1008 - regression_loss: 0.9429 - classification_loss: 0.1579 498/500 [============================>.] - ETA: 0s - loss: 1.1004 - regression_loss: 0.9425 - classification_loss: 0.1578 499/500 [============================>.] - ETA: 0s - loss: 1.0990 - regression_loss: 0.9413 - classification_loss: 0.1576 500/500 [==============================] - 162s 323ms/step - loss: 1.0987 - regression_loss: 0.9412 - classification_loss: 0.1576 326 instances of class plum with average precision: 0.7959 mAP: 0.7959 Epoch 00015: saving model to ./training/snapshots/resnet101_pascal_15.h5 Epoch 16/150 1/500 [..............................] - ETA: 2:34 - loss: 1.6442 - regression_loss: 1.3874 - classification_loss: 0.2569 2/500 [..............................] - ETA: 2:36 - loss: 1.3235 - regression_loss: 1.1432 - classification_loss: 0.1803 3/500 [..............................] - ETA: 2:37 - loss: 1.0198 - regression_loss: 0.8831 - classification_loss: 0.1366 4/500 [..............................] - ETA: 2:37 - loss: 0.8979 - regression_loss: 0.7819 - classification_loss: 0.1159 5/500 [..............................] - ETA: 2:37 - loss: 0.9373 - regression_loss: 0.8196 - classification_loss: 0.1177 6/500 [..............................] - ETA: 2:37 - loss: 0.9215 - regression_loss: 0.8029 - classification_loss: 0.1186 7/500 [..............................] - ETA: 2:38 - loss: 0.9325 - regression_loss: 0.8159 - classification_loss: 0.1166 8/500 [..............................] - ETA: 2:38 - loss: 1.0653 - regression_loss: 0.9140 - classification_loss: 0.1513 9/500 [..............................] - ETA: 2:37 - loss: 1.0827 - regression_loss: 0.9289 - classification_loss: 0.1539 10/500 [..............................] - ETA: 2:36 - loss: 1.1452 - regression_loss: 0.9709 - classification_loss: 0.1743 11/500 [..............................] - ETA: 2:36 - loss: 1.1001 - regression_loss: 0.9341 - classification_loss: 0.1660 12/500 [..............................] - ETA: 2:36 - loss: 1.1394 - regression_loss: 0.9664 - classification_loss: 0.1730 13/500 [..............................] - ETA: 2:35 - loss: 1.0964 - regression_loss: 0.9307 - classification_loss: 0.1656 14/500 [..............................] - ETA: 2:35 - loss: 1.0837 - regression_loss: 0.9238 - classification_loss: 0.1599 15/500 [..............................] - ETA: 2:34 - loss: 1.0648 - regression_loss: 0.9095 - classification_loss: 0.1553 16/500 [..............................] - ETA: 2:34 - loss: 1.0929 - regression_loss: 0.9315 - classification_loss: 0.1615 17/500 [>.............................] - ETA: 2:35 - loss: 1.0847 - regression_loss: 0.9279 - classification_loss: 0.1569 18/500 [>.............................] - ETA: 2:36 - loss: 1.1163 - regression_loss: 0.9506 - classification_loss: 0.1658 19/500 [>.............................] - ETA: 2:36 - loss: 1.1114 - regression_loss: 0.9479 - classification_loss: 0.1635 20/500 [>.............................] - ETA: 2:35 - loss: 1.1280 - regression_loss: 0.9642 - classification_loss: 0.1637 21/500 [>.............................] - ETA: 2:34 - loss: 1.0875 - regression_loss: 0.9297 - classification_loss: 0.1578 22/500 [>.............................] - ETA: 2:34 - loss: 1.0828 - regression_loss: 0.9271 - classification_loss: 0.1557 23/500 [>.............................] - ETA: 2:34 - loss: 1.1078 - regression_loss: 0.9414 - classification_loss: 0.1663 24/500 [>.............................] - ETA: 2:35 - loss: 1.1025 - regression_loss: 0.9394 - classification_loss: 0.1630 25/500 [>.............................] - ETA: 2:35 - loss: 1.0968 - regression_loss: 0.9353 - classification_loss: 0.1615 26/500 [>.............................] - ETA: 2:34 - loss: 1.0970 - regression_loss: 0.9375 - classification_loss: 0.1596 27/500 [>.............................] - ETA: 2:34 - loss: 1.1076 - regression_loss: 0.9485 - classification_loss: 0.1592 28/500 [>.............................] - ETA: 2:33 - loss: 1.1462 - regression_loss: 0.9809 - classification_loss: 0.1654 29/500 [>.............................] - ETA: 2:33 - loss: 1.1573 - regression_loss: 0.9921 - classification_loss: 0.1652 30/500 [>.............................] - ETA: 2:32 - loss: 1.1460 - regression_loss: 0.9837 - classification_loss: 0.1622 31/500 [>.............................] - ETA: 2:32 - loss: 1.1519 - regression_loss: 0.9874 - classification_loss: 0.1645 32/500 [>.............................] - ETA: 2:31 - loss: 1.1623 - regression_loss: 0.9978 - classification_loss: 0.1645 33/500 [>.............................] - ETA: 2:31 - loss: 1.1413 - regression_loss: 0.9800 - classification_loss: 0.1614 34/500 [=>............................] - ETA: 2:30 - loss: 1.1346 - regression_loss: 0.9753 - classification_loss: 0.1593 35/500 [=>............................] - ETA: 2:30 - loss: 1.1501 - regression_loss: 0.9860 - classification_loss: 0.1641 36/500 [=>............................] - ETA: 2:30 - loss: 1.1510 - regression_loss: 0.9865 - classification_loss: 0.1645 37/500 [=>............................] - ETA: 2:29 - loss: 1.1435 - regression_loss: 0.9803 - classification_loss: 0.1632 38/500 [=>............................] - ETA: 2:29 - loss: 1.1448 - regression_loss: 0.9802 - classification_loss: 0.1646 39/500 [=>............................] - ETA: 2:29 - loss: 1.1382 - regression_loss: 0.9762 - classification_loss: 0.1621 40/500 [=>............................] - ETA: 2:28 - loss: 1.1321 - regression_loss: 0.9700 - classification_loss: 0.1621 41/500 [=>............................] - ETA: 2:28 - loss: 1.1351 - regression_loss: 0.9726 - classification_loss: 0.1624 42/500 [=>............................] - ETA: 2:27 - loss: 1.1155 - regression_loss: 0.9545 - classification_loss: 0.1610 43/500 [=>............................] - ETA: 2:27 - loss: 1.1206 - regression_loss: 0.9588 - classification_loss: 0.1618 44/500 [=>............................] - ETA: 2:27 - loss: 1.1120 - regression_loss: 0.9495 - classification_loss: 0.1625 45/500 [=>............................] - ETA: 2:27 - loss: 1.1099 - regression_loss: 0.9477 - classification_loss: 0.1622 46/500 [=>............................] - ETA: 2:26 - loss: 1.1182 - regression_loss: 0.9543 - classification_loss: 0.1639 47/500 [=>............................] - ETA: 2:26 - loss: 1.1118 - regression_loss: 0.9490 - classification_loss: 0.1628 48/500 [=>............................] - ETA: 2:25 - loss: 1.1023 - regression_loss: 0.9407 - classification_loss: 0.1616 49/500 [=>............................] - ETA: 2:25 - loss: 1.0989 - regression_loss: 0.9383 - classification_loss: 0.1606 50/500 [==>...........................] - ETA: 2:25 - loss: 1.1101 - regression_loss: 0.9488 - classification_loss: 0.1613 51/500 [==>...........................] - ETA: 2:24 - loss: 1.1174 - regression_loss: 0.9538 - classification_loss: 0.1636 52/500 [==>...........................] - ETA: 2:24 - loss: 1.1128 - regression_loss: 0.9506 - classification_loss: 0.1621 53/500 [==>...........................] - ETA: 2:23 - loss: 1.1147 - regression_loss: 0.9526 - classification_loss: 0.1621 54/500 [==>...........................] - ETA: 2:23 - loss: 1.1104 - regression_loss: 0.9498 - classification_loss: 0.1607 55/500 [==>...........................] - ETA: 2:23 - loss: 1.1143 - regression_loss: 0.9536 - classification_loss: 0.1608 56/500 [==>...........................] - ETA: 2:22 - loss: 1.1071 - regression_loss: 0.9479 - classification_loss: 0.1592 57/500 [==>...........................] - ETA: 2:22 - loss: 1.0990 - regression_loss: 0.9414 - classification_loss: 0.1576 58/500 [==>...........................] - ETA: 2:22 - loss: 1.0878 - regression_loss: 0.9321 - classification_loss: 0.1558 59/500 [==>...........................] - ETA: 2:22 - loss: 1.0855 - regression_loss: 0.9304 - classification_loss: 0.1552 60/500 [==>...........................] - ETA: 2:21 - loss: 1.0754 - regression_loss: 0.9220 - classification_loss: 0.1533 61/500 [==>...........................] - ETA: 2:21 - loss: 1.0824 - regression_loss: 0.9271 - classification_loss: 0.1553 62/500 [==>...........................] - ETA: 2:21 - loss: 1.0758 - regression_loss: 0.9216 - classification_loss: 0.1542 63/500 [==>...........................] - ETA: 2:20 - loss: 1.0801 - regression_loss: 0.9258 - classification_loss: 0.1543 64/500 [==>...........................] - ETA: 2:20 - loss: 1.0822 - regression_loss: 0.9281 - classification_loss: 0.1542 65/500 [==>...........................] - ETA: 2:20 - loss: 1.0825 - regression_loss: 0.9278 - classification_loss: 0.1547 66/500 [==>...........................] - ETA: 2:20 - loss: 1.0919 - regression_loss: 0.9362 - classification_loss: 0.1557 67/500 [===>..........................] - ETA: 2:20 - loss: 1.0979 - regression_loss: 0.9417 - classification_loss: 0.1562 68/500 [===>..........................] - ETA: 2:19 - loss: 1.0954 - regression_loss: 0.9395 - classification_loss: 0.1559 69/500 [===>..........................] - ETA: 2:19 - loss: 1.0926 - regression_loss: 0.9370 - classification_loss: 0.1555 70/500 [===>..........................] - ETA: 2:19 - loss: 1.0989 - regression_loss: 0.9407 - classification_loss: 0.1582 71/500 [===>..........................] - ETA: 2:18 - loss: 1.1050 - regression_loss: 0.9456 - classification_loss: 0.1594 72/500 [===>..........................] - ETA: 2:18 - loss: 1.0984 - regression_loss: 0.9403 - classification_loss: 0.1581 73/500 [===>..........................] - ETA: 2:18 - loss: 1.0990 - regression_loss: 0.9414 - classification_loss: 0.1576 74/500 [===>..........................] - ETA: 2:17 - loss: 1.1014 - regression_loss: 0.9429 - classification_loss: 0.1585 75/500 [===>..........................] - ETA: 2:17 - loss: 1.1053 - regression_loss: 0.9468 - classification_loss: 0.1585 76/500 [===>..........................] - ETA: 2:17 - loss: 1.0992 - regression_loss: 0.9414 - classification_loss: 0.1577 77/500 [===>..........................] - ETA: 2:16 - loss: 1.0985 - regression_loss: 0.9417 - classification_loss: 0.1568 78/500 [===>..........................] - ETA: 2:16 - loss: 1.0983 - regression_loss: 0.9419 - classification_loss: 0.1563 79/500 [===>..........................] - ETA: 2:15 - loss: 1.0973 - regression_loss: 0.9411 - classification_loss: 0.1562 80/500 [===>..........................] - ETA: 2:15 - loss: 1.0967 - regression_loss: 0.9409 - classification_loss: 0.1557 81/500 [===>..........................] - ETA: 2:15 - loss: 1.0939 - regression_loss: 0.9387 - classification_loss: 0.1552 82/500 [===>..........................] - ETA: 2:15 - loss: 1.0882 - regression_loss: 0.9342 - classification_loss: 0.1540 83/500 [===>..........................] - ETA: 2:14 - loss: 1.0889 - regression_loss: 0.9344 - classification_loss: 0.1545 84/500 [====>.........................] - ETA: 2:14 - loss: 1.0842 - regression_loss: 0.9303 - classification_loss: 0.1539 85/500 [====>.........................] - ETA: 2:14 - loss: 1.0752 - regression_loss: 0.9221 - classification_loss: 0.1531 86/500 [====>.........................] - ETA: 2:13 - loss: 1.0723 - regression_loss: 0.9194 - classification_loss: 0.1528 87/500 [====>.........................] - ETA: 2:13 - loss: 1.0665 - regression_loss: 0.9144 - classification_loss: 0.1522 88/500 [====>.........................] - ETA: 2:13 - loss: 1.0676 - regression_loss: 0.9157 - classification_loss: 0.1519 89/500 [====>.........................] - ETA: 2:12 - loss: 1.0597 - regression_loss: 0.9088 - classification_loss: 0.1509 90/500 [====>.........................] - ETA: 2:12 - loss: 1.0642 - regression_loss: 0.9111 - classification_loss: 0.1531 91/500 [====>.........................] - ETA: 2:11 - loss: 1.0611 - regression_loss: 0.9087 - classification_loss: 0.1525 92/500 [====>.........................] - ETA: 2:11 - loss: 1.0701 - regression_loss: 0.9166 - classification_loss: 0.1535 93/500 [====>.........................] - ETA: 2:11 - loss: 1.0672 - regression_loss: 0.9142 - classification_loss: 0.1530 94/500 [====>.........................] - ETA: 2:10 - loss: 1.0670 - regression_loss: 0.9145 - classification_loss: 0.1525 95/500 [====>.........................] - ETA: 2:10 - loss: 1.0686 - regression_loss: 0.9160 - classification_loss: 0.1526 96/500 [====>.........................] - ETA: 2:10 - loss: 1.0684 - regression_loss: 0.9161 - classification_loss: 0.1523 97/500 [====>.........................] - ETA: 2:09 - loss: 1.0688 - regression_loss: 0.9168 - classification_loss: 0.1521 98/500 [====>.........................] - ETA: 2:09 - loss: 1.0695 - regression_loss: 0.9180 - classification_loss: 0.1515 99/500 [====>.........................] - ETA: 2:09 - loss: 1.0734 - regression_loss: 0.9216 - classification_loss: 0.1518 100/500 [=====>........................] - ETA: 2:08 - loss: 1.0802 - regression_loss: 0.9272 - classification_loss: 0.1530 101/500 [=====>........................] - ETA: 2:08 - loss: 1.0761 - regression_loss: 0.9238 - classification_loss: 0.1522 102/500 [=====>........................] - ETA: 2:08 - loss: 1.0864 - regression_loss: 0.9323 - classification_loss: 0.1541 103/500 [=====>........................] - ETA: 2:07 - loss: 1.0866 - regression_loss: 0.9332 - classification_loss: 0.1535 104/500 [=====>........................] - ETA: 2:07 - loss: 1.0802 - regression_loss: 0.9276 - classification_loss: 0.1525 105/500 [=====>........................] - ETA: 2:07 - loss: 1.0809 - regression_loss: 0.9286 - classification_loss: 0.1523 106/500 [=====>........................] - ETA: 2:06 - loss: 1.0774 - regression_loss: 0.9259 - classification_loss: 0.1516 107/500 [=====>........................] - ETA: 2:06 - loss: 1.0763 - regression_loss: 0.9249 - classification_loss: 0.1513 108/500 [=====>........................] - ETA: 2:06 - loss: 1.0701 - regression_loss: 0.9197 - classification_loss: 0.1504 109/500 [=====>........................] - ETA: 2:05 - loss: 1.0691 - regression_loss: 0.9183 - classification_loss: 0.1507 110/500 [=====>........................] - ETA: 2:05 - loss: 1.0736 - regression_loss: 0.9221 - classification_loss: 0.1515 111/500 [=====>........................] - ETA: 2:05 - loss: 1.0715 - regression_loss: 0.9200 - classification_loss: 0.1515 112/500 [=====>........................] - ETA: 2:04 - loss: 1.0656 - regression_loss: 0.9150 - classification_loss: 0.1507 113/500 [=====>........................] - ETA: 2:04 - loss: 1.0634 - regression_loss: 0.9132 - classification_loss: 0.1503 114/500 [=====>........................] - ETA: 2:04 - loss: 1.0651 - regression_loss: 0.9141 - classification_loss: 0.1511 115/500 [=====>........................] - ETA: 2:03 - loss: 1.0607 - regression_loss: 0.9101 - classification_loss: 0.1506 116/500 [=====>........................] - ETA: 2:03 - loss: 1.0641 - regression_loss: 0.9129 - classification_loss: 0.1512 117/500 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[============================>.] - ETA: 2s - loss: 1.0481 - regression_loss: 0.8993 - classification_loss: 0.1488 494/500 [============================>.] - ETA: 1s - loss: 1.0471 - regression_loss: 0.8985 - classification_loss: 0.1486 495/500 [============================>.] - ETA: 1s - loss: 1.0483 - regression_loss: 0.8996 - classification_loss: 0.1487 496/500 [============================>.] - ETA: 1s - loss: 1.0482 - regression_loss: 0.8995 - classification_loss: 0.1487 497/500 [============================>.] - ETA: 0s - loss: 1.0475 - regression_loss: 0.8989 - classification_loss: 0.1486 498/500 [============================>.] - ETA: 0s - loss: 1.0488 - regression_loss: 0.8999 - classification_loss: 0.1489 499/500 [============================>.] - ETA: 0s - loss: 1.0486 - regression_loss: 0.8998 - classification_loss: 0.1488 500/500 [==============================] - 160s 320ms/step - loss: 1.0476 - regression_loss: 0.8989 - classification_loss: 0.1487 326 instances of class plum with average precision: 0.7892 mAP: 0.7892 Epoch 00016: saving model to ./training/snapshots/resnet101_pascal_16.h5 Epoch 17/150 1/500 [..............................] - ETA: 2:35 - loss: 1.3195 - regression_loss: 1.1161 - classification_loss: 0.2034 2/500 [..............................] - ETA: 2:34 - loss: 1.2875 - regression_loss: 1.0538 - classification_loss: 0.2337 3/500 [..............................] - ETA: 2:35 - loss: 1.2650 - regression_loss: 1.0350 - classification_loss: 0.2300 4/500 [..............................] - ETA: 2:36 - loss: 1.1059 - regression_loss: 0.9164 - classification_loss: 0.1895 5/500 [..............................] - ETA: 2:38 - loss: 1.1408 - regression_loss: 0.9485 - classification_loss: 0.1924 6/500 [..............................] - ETA: 2:37 - loss: 1.1855 - regression_loss: 0.9875 - classification_loss: 0.1980 7/500 [..............................] - ETA: 2:36 - loss: 1.1456 - regression_loss: 0.9623 - classification_loss: 0.1833 8/500 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[============================>.] - ETA: 3s - loss: 1.0065 - regression_loss: 0.8689 - classification_loss: 0.1376 489/500 [============================>.] - ETA: 3s - loss: 1.0075 - regression_loss: 0.8696 - classification_loss: 0.1380 490/500 [============================>.] - ETA: 3s - loss: 1.0073 - regression_loss: 0.8693 - classification_loss: 0.1380 491/500 [============================>.] - ETA: 2s - loss: 1.0069 - regression_loss: 0.8690 - classification_loss: 0.1380 492/500 [============================>.] - ETA: 2s - loss: 1.0062 - regression_loss: 0.8684 - classification_loss: 0.1378 493/500 [============================>.] - ETA: 2s - loss: 1.0064 - regression_loss: 0.8686 - classification_loss: 0.1378 494/500 [============================>.] - ETA: 1s - loss: 1.0064 - regression_loss: 0.8687 - classification_loss: 0.1378 495/500 [============================>.] - ETA: 1s - loss: 1.0068 - regression_loss: 0.8690 - classification_loss: 0.1378 496/500 [============================>.] - ETA: 1s - loss: 1.0060 - regression_loss: 0.8682 - classification_loss: 0.1377 497/500 [============================>.] - ETA: 0s - loss: 1.0051 - regression_loss: 0.8674 - classification_loss: 0.1376 498/500 [============================>.] - ETA: 0s - loss: 1.0053 - regression_loss: 0.8677 - classification_loss: 0.1376 499/500 [============================>.] - ETA: 0s - loss: 1.0060 - regression_loss: 0.8681 - classification_loss: 0.1379 500/500 [==============================] - 161s 322ms/step - loss: 1.0053 - regression_loss: 0.8675 - classification_loss: 0.1378 326 instances of class plum with average precision: 0.7768 mAP: 0.7768 Epoch 00017: saving model to ./training/snapshots/resnet101_pascal_17.h5 Epoch 18/150 1/500 [..............................] - ETA: 2:30 - loss: 0.7484 - regression_loss: 0.6935 - classification_loss: 0.0549 2/500 [..............................] - ETA: 2:30 - loss: 0.7431 - regression_loss: 0.6716 - 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0.1753 11/500 [..............................] - ETA: 2:36 - loss: 1.1058 - regression_loss: 0.9298 - classification_loss: 0.1760 12/500 [..............................] - ETA: 2:36 - loss: 1.0684 - regression_loss: 0.9008 - classification_loss: 0.1676 13/500 [..............................] - ETA: 2:35 - loss: 1.0951 - regression_loss: 0.9297 - classification_loss: 0.1654 14/500 [..............................] - ETA: 2:35 - loss: 1.0912 - regression_loss: 0.9309 - classification_loss: 0.1603 15/500 [..............................] - ETA: 2:35 - loss: 1.0838 - regression_loss: 0.9282 - classification_loss: 0.1556 16/500 [..............................] - ETA: 2:34 - loss: 1.0916 - regression_loss: 0.9350 - classification_loss: 0.1566 17/500 [>.............................] - ETA: 2:34 - loss: 1.0989 - regression_loss: 0.9416 - classification_loss: 0.1573 18/500 [>.............................] - ETA: 2:34 - loss: 1.0659 - regression_loss: 0.9136 - classification_loss: 0.1523 19/500 [>.............................] - ETA: 2:33 - loss: 1.0547 - regression_loss: 0.9054 - classification_loss: 0.1493 20/500 [>.............................] - ETA: 2:33 - loss: 1.0789 - regression_loss: 0.9273 - classification_loss: 0.1515 21/500 [>.............................] - ETA: 2:32 - loss: 1.1087 - regression_loss: 0.9484 - classification_loss: 0.1603 22/500 [>.............................] - ETA: 2:32 - loss: 1.0770 - regression_loss: 0.9206 - classification_loss: 0.1564 23/500 [>.............................] - ETA: 2:31 - loss: 1.0917 - regression_loss: 0.9363 - classification_loss: 0.1554 24/500 [>.............................] - ETA: 2:31 - loss: 1.0747 - regression_loss: 0.9226 - classification_loss: 0.1521 25/500 [>.............................] - ETA: 2:31 - loss: 1.0458 - regression_loss: 0.8979 - classification_loss: 0.1479 26/500 [>.............................] - ETA: 2:30 - loss: 1.0278 - regression_loss: 0.8830 - classification_loss: 0.1448 27/500 [>.............................] - ETA: 2:30 - loss: 1.0299 - regression_loss: 0.8870 - classification_loss: 0.1429 28/500 [>.............................] - ETA: 2:30 - loss: 1.0280 - regression_loss: 0.8868 - classification_loss: 0.1413 29/500 [>.............................] - ETA: 2:29 - loss: 1.0127 - regression_loss: 0.8741 - classification_loss: 0.1385 30/500 [>.............................] - ETA: 2:30 - loss: 1.0068 - regression_loss: 0.8701 - classification_loss: 0.1367 31/500 [>.............................] - ETA: 2:29 - loss: 1.0113 - regression_loss: 0.8737 - classification_loss: 0.1376 32/500 [>.............................] - ETA: 2:30 - loss: 1.0139 - regression_loss: 0.8753 - classification_loss: 0.1386 33/500 [>.............................] - ETA: 2:29 - loss: 1.0120 - regression_loss: 0.8724 - classification_loss: 0.1397 34/500 [=>............................] - ETA: 2:29 - loss: 0.9960 - regression_loss: 0.8576 - classification_loss: 0.1384 35/500 [=>............................] - ETA: 2:29 - loss: 0.9756 - regression_loss: 0.8402 - classification_loss: 0.1353 36/500 [=>............................] - ETA: 2:28 - loss: 0.9694 - regression_loss: 0.8351 - classification_loss: 0.1343 37/500 [=>............................] - ETA: 2:28 - loss: 0.9646 - regression_loss: 0.8317 - classification_loss: 0.1329 38/500 [=>............................] - ETA: 2:28 - loss: 0.9671 - regression_loss: 0.8345 - classification_loss: 0.1326 39/500 [=>............................] - ETA: 2:28 - loss: 0.9617 - regression_loss: 0.8305 - classification_loss: 0.1312 40/500 [=>............................] - ETA: 2:27 - loss: 0.9712 - regression_loss: 0.8361 - classification_loss: 0.1351 41/500 [=>............................] - ETA: 2:27 - loss: 0.9842 - regression_loss: 0.8486 - classification_loss: 0.1356 42/500 [=>............................] - ETA: 2:27 - loss: 0.9690 - regression_loss: 0.8356 - classification_loss: 0.1334 43/500 [=>............................] - ETA: 2:26 - loss: 0.9834 - regression_loss: 0.8473 - classification_loss: 0.1360 44/500 [=>............................] - ETA: 2:26 - loss: 0.9834 - regression_loss: 0.8478 - classification_loss: 0.1356 45/500 [=>............................] - ETA: 2:25 - loss: 0.9792 - regression_loss: 0.8445 - classification_loss: 0.1347 46/500 [=>............................] - ETA: 2:25 - loss: 0.9738 - regression_loss: 0.8396 - classification_loss: 0.1342 47/500 [=>............................] - ETA: 2:24 - loss: 0.9595 - regression_loss: 0.8273 - classification_loss: 0.1322 48/500 [=>............................] - ETA: 2:24 - loss: 0.9798 - regression_loss: 0.8429 - classification_loss: 0.1369 49/500 [=>............................] - ETA: 2:24 - loss: 0.9780 - regression_loss: 0.8418 - classification_loss: 0.1362 50/500 [==>...........................] - ETA: 2:23 - loss: 0.9700 - regression_loss: 0.8355 - classification_loss: 0.1345 51/500 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[==>...........................] - ETA: 2:20 - loss: 0.9580 - regression_loss: 0.8282 - classification_loss: 0.1298 60/500 [==>...........................] - ETA: 2:20 - loss: 0.9532 - regression_loss: 0.8244 - classification_loss: 0.1288 61/500 [==>...........................] - ETA: 2:20 - loss: 0.9560 - regression_loss: 0.8265 - classification_loss: 0.1295 62/500 [==>...........................] - ETA: 2:19 - loss: 0.9520 - regression_loss: 0.8235 - classification_loss: 0.1285 63/500 [==>...........................] - ETA: 2:19 - loss: 0.9467 - regression_loss: 0.8193 - classification_loss: 0.1274 64/500 [==>...........................] - ETA: 2:19 - loss: 0.9546 - regression_loss: 0.8260 - classification_loss: 0.1286 65/500 [==>...........................] - ETA: 2:19 - loss: 0.9478 - regression_loss: 0.8202 - classification_loss: 0.1276 66/500 [==>...........................] - ETA: 2:18 - loss: 0.9449 - regression_loss: 0.8179 - classification_loss: 0.1270 67/500 [===>..........................] - ETA: 2:18 - loss: 0.9438 - regression_loss: 0.8174 - classification_loss: 0.1264 68/500 [===>..........................] - ETA: 2:18 - loss: 0.9465 - regression_loss: 0.8202 - classification_loss: 0.1263 69/500 [===>..........................] - ETA: 2:17 - loss: 0.9412 - regression_loss: 0.8156 - classification_loss: 0.1257 70/500 [===>..........................] - ETA: 2:17 - loss: 0.9411 - regression_loss: 0.8161 - classification_loss: 0.1250 71/500 [===>..........................] - ETA: 2:17 - loss: 0.9411 - regression_loss: 0.8161 - classification_loss: 0.1250 72/500 [===>..........................] - ETA: 2:16 - loss: 0.9468 - regression_loss: 0.8209 - classification_loss: 0.1259 73/500 [===>..........................] - ETA: 2:16 - loss: 0.9403 - regression_loss: 0.8155 - classification_loss: 0.1249 74/500 [===>..........................] - ETA: 2:15 - loss: 0.9313 - regression_loss: 0.8075 - classification_loss: 0.1239 75/500 [===>..........................] - ETA: 2:15 - loss: 0.9360 - regression_loss: 0.8115 - classification_loss: 0.1245 76/500 [===>..........................] - ETA: 2:15 - loss: 0.9291 - regression_loss: 0.8058 - classification_loss: 0.1233 77/500 [===>..........................] - ETA: 2:14 - loss: 0.9271 - regression_loss: 0.8043 - classification_loss: 0.1228 78/500 [===>..........................] - ETA: 2:14 - loss: 0.9310 - regression_loss: 0.8066 - classification_loss: 0.1244 79/500 [===>..........................] - ETA: 2:14 - loss: 0.9236 - regression_loss: 0.7998 - classification_loss: 0.1238 80/500 [===>..........................] - ETA: 2:13 - loss: 0.9294 - regression_loss: 0.8047 - classification_loss: 0.1247 81/500 [===>..........................] - ETA: 2:13 - loss: 0.9286 - regression_loss: 0.8043 - classification_loss: 0.1243 82/500 [===>..........................] - ETA: 2:13 - loss: 0.9364 - regression_loss: 0.8102 - classification_loss: 0.1262 83/500 [===>..........................] - ETA: 2:13 - loss: 0.9386 - regression_loss: 0.8120 - classification_loss: 0.1267 84/500 [====>.........................] - ETA: 2:12 - loss: 0.9351 - regression_loss: 0.8089 - classification_loss: 0.1263 85/500 [====>.........................] - ETA: 2:12 - loss: 0.9394 - regression_loss: 0.8123 - classification_loss: 0.1271 86/500 [====>.........................] - ETA: 2:12 - loss: 0.9345 - regression_loss: 0.8081 - classification_loss: 0.1265 87/500 [====>.........................] - ETA: 2:12 - loss: 0.9408 - regression_loss: 0.8136 - classification_loss: 0.1271 88/500 [====>.........................] - ETA: 2:12 - loss: 0.9513 - regression_loss: 0.8224 - classification_loss: 0.1290 89/500 [====>.........................] - ETA: 2:11 - loss: 0.9479 - regression_loss: 0.8196 - classification_loss: 0.1283 90/500 [====>.........................] - ETA: 2:11 - loss: 0.9455 - regression_loss: 0.8179 - classification_loss: 0.1276 91/500 [====>.........................] - ETA: 2:11 - loss: 0.9456 - regression_loss: 0.8177 - classification_loss: 0.1279 92/500 [====>.........................] - ETA: 2:10 - loss: 0.9396 - regression_loss: 0.8124 - classification_loss: 0.1272 93/500 [====>.........................] - ETA: 2:10 - loss: 0.9390 - regression_loss: 0.8121 - classification_loss: 0.1268 94/500 [====>.........................] - ETA: 2:10 - loss: 0.9340 - regression_loss: 0.8080 - classification_loss: 0.1260 95/500 [====>.........................] - ETA: 2:10 - loss: 0.9336 - regression_loss: 0.8079 - classification_loss: 0.1257 96/500 [====>.........................] - ETA: 2:09 - loss: 0.9336 - regression_loss: 0.8080 - classification_loss: 0.1256 97/500 [====>.........................] - ETA: 2:09 - loss: 0.9391 - regression_loss: 0.8116 - classification_loss: 0.1275 98/500 [====>.........................] - ETA: 2:08 - loss: 0.9390 - regression_loss: 0.8110 - classification_loss: 0.1279 99/500 [====>.........................] - ETA: 2:08 - loss: 0.9366 - regression_loss: 0.8094 - classification_loss: 0.1272 100/500 [=====>........................] - ETA: 2:08 - loss: 0.9376 - regression_loss: 0.8107 - classification_loss: 0.1269 101/500 [=====>........................] - ETA: 2:08 - loss: 0.9382 - regression_loss: 0.8113 - classification_loss: 0.1268 102/500 [=====>........................] - ETA: 2:07 - loss: 0.9378 - regression_loss: 0.8113 - classification_loss: 0.1265 103/500 [=====>........................] - ETA: 2:07 - loss: 0.9307 - regression_loss: 0.8051 - classification_loss: 0.1256 104/500 [=====>........................] - ETA: 2:07 - loss: 0.9355 - regression_loss: 0.8088 - classification_loss: 0.1267 105/500 [=====>........................] - ETA: 2:06 - loss: 0.9296 - regression_loss: 0.8037 - classification_loss: 0.1259 106/500 [=====>........................] - ETA: 2:06 - loss: 0.9322 - regression_loss: 0.8056 - classification_loss: 0.1265 107/500 [=====>........................] - ETA: 2:06 - loss: 0.9298 - regression_loss: 0.8035 - classification_loss: 0.1263 108/500 [=====>........................] - ETA: 2:06 - loss: 0.9279 - regression_loss: 0.8018 - classification_loss: 0.1261 109/500 [=====>........................] - ETA: 2:05 - loss: 0.9283 - regression_loss: 0.8019 - classification_loss: 0.1264 110/500 [=====>........................] - ETA: 2:05 - loss: 0.9311 - regression_loss: 0.8042 - classification_loss: 0.1269 111/500 [=====>........................] - ETA: 2:05 - loss: 0.9266 - regression_loss: 0.8000 - classification_loss: 0.1266 112/500 [=====>........................] - ETA: 2:05 - loss: 0.9226 - regression_loss: 0.7968 - classification_loss: 0.1258 113/500 [=====>........................] - ETA: 2:04 - loss: 0.9325 - regression_loss: 0.8044 - classification_loss: 0.1282 114/500 [=====>........................] - ETA: 2:04 - loss: 0.9324 - regression_loss: 0.8044 - classification_loss: 0.1280 115/500 [=====>........................] - ETA: 2:04 - loss: 0.9332 - regression_loss: 0.8053 - classification_loss: 0.1280 116/500 [=====>........................] - ETA: 2:03 - loss: 0.9351 - regression_loss: 0.8074 - classification_loss: 0.1278 117/500 [======>.......................] - ETA: 2:03 - loss: 0.9376 - regression_loss: 0.8095 - classification_loss: 0.1281 118/500 [======>.......................] - ETA: 2:03 - loss: 0.9343 - regression_loss: 0.8066 - classification_loss: 0.1277 119/500 [======>.......................] - ETA: 2:02 - loss: 0.9404 - regression_loss: 0.8117 - classification_loss: 0.1287 120/500 [======>.......................] - ETA: 2:02 - loss: 0.9397 - regression_loss: 0.8111 - classification_loss: 0.1287 121/500 [======>.......................] - ETA: 2:02 - loss: 0.9451 - regression_loss: 0.8160 - classification_loss: 0.1291 122/500 [======>.......................] - ETA: 2:01 - loss: 0.9445 - regression_loss: 0.8156 - classification_loss: 0.1290 123/500 [======>.......................] - ETA: 2:01 - loss: 0.9478 - regression_loss: 0.8187 - classification_loss: 0.1291 124/500 [======>.......................] - ETA: 2:01 - loss: 0.9465 - regression_loss: 0.8175 - classification_loss: 0.1290 125/500 [======>.......................] - ETA: 2:01 - loss: 0.9474 - regression_loss: 0.8186 - classification_loss: 0.1288 126/500 [======>.......................] - ETA: 2:00 - loss: 0.9489 - regression_loss: 0.8201 - classification_loss: 0.1288 127/500 [======>.......................] - ETA: 2:00 - loss: 0.9541 - regression_loss: 0.8241 - classification_loss: 0.1300 128/500 [======>.......................] - ETA: 2:00 - loss: 0.9563 - regression_loss: 0.8253 - classification_loss: 0.1310 129/500 [======>.......................] - ETA: 1:59 - loss: 0.9586 - regression_loss: 0.8273 - classification_loss: 0.1313 130/500 [======>.......................] - ETA: 1:59 - loss: 0.9588 - regression_loss: 0.8275 - classification_loss: 0.1313 131/500 [======>.......................] - ETA: 1:59 - loss: 0.9561 - regression_loss: 0.8252 - classification_loss: 0.1309 132/500 [======>.......................] - ETA: 1:58 - loss: 0.9519 - regression_loss: 0.8215 - classification_loss: 0.1305 133/500 [======>.......................] - ETA: 1:58 - loss: 0.9482 - regression_loss: 0.8183 - classification_loss: 0.1299 134/500 [=======>......................] - ETA: 1:58 - loss: 0.9487 - regression_loss: 0.8192 - classification_loss: 0.1295 135/500 [=======>......................] - ETA: 1:57 - loss: 0.9470 - regression_loss: 0.8179 - classification_loss: 0.1291 136/500 [=======>......................] - ETA: 1:57 - loss: 0.9431 - regression_loss: 0.8147 - classification_loss: 0.1284 137/500 [=======>......................] - ETA: 1:57 - loss: 0.9425 - regression_loss: 0.8143 - classification_loss: 0.1282 138/500 [=======>......................] - ETA: 1:56 - loss: 0.9435 - regression_loss: 0.8154 - classification_loss: 0.1282 139/500 [=======>......................] - ETA: 1:56 - loss: 0.9392 - regression_loss: 0.8115 - classification_loss: 0.1277 140/500 [=======>......................] - ETA: 1:56 - loss: 0.9413 - regression_loss: 0.8131 - classification_loss: 0.1282 141/500 [=======>......................] - ETA: 1:55 - loss: 0.9414 - regression_loss: 0.8133 - classification_loss: 0.1281 142/500 [=======>......................] - ETA: 1:55 - loss: 0.9465 - regression_loss: 0.8167 - classification_loss: 0.1298 143/500 [=======>......................] - ETA: 1:55 - loss: 0.9420 - regression_loss: 0.8129 - classification_loss: 0.1291 144/500 [=======>......................] - ETA: 1:54 - loss: 0.9443 - regression_loss: 0.8145 - classification_loss: 0.1298 145/500 [=======>......................] - ETA: 1:54 - loss: 0.9417 - regression_loss: 0.8124 - classification_loss: 0.1293 146/500 [=======>......................] - ETA: 1:54 - loss: 0.9393 - regression_loss: 0.8104 - classification_loss: 0.1289 147/500 [=======>......................] - ETA: 1:53 - loss: 0.9390 - regression_loss: 0.8100 - classification_loss: 0.1290 148/500 [=======>......................] - ETA: 1:53 - loss: 0.9372 - regression_loss: 0.8083 - classification_loss: 0.1290 149/500 [=======>......................] - ETA: 1:53 - loss: 0.9394 - regression_loss: 0.8100 - classification_loss: 0.1294 150/500 [========>.....................] - ETA: 1:52 - loss: 0.9381 - regression_loss: 0.8089 - classification_loss: 0.1291 151/500 [========>.....................] - ETA: 1:52 - loss: 0.9396 - regression_loss: 0.8100 - classification_loss: 0.1296 152/500 [========>.....................] - ETA: 1:51 - loss: 0.9406 - regression_loss: 0.8110 - classification_loss: 0.1296 153/500 [========>.....................] - ETA: 1:51 - loss: 0.9402 - regression_loss: 0.8109 - classification_loss: 0.1293 154/500 [========>.....................] - ETA: 1:51 - loss: 0.9402 - regression_loss: 0.8109 - classification_loss: 0.1294 155/500 [========>.....................] - ETA: 1:50 - loss: 0.9433 - regression_loss: 0.8139 - classification_loss: 0.1294 156/500 [========>.....................] - ETA: 1:50 - loss: 0.9452 - regression_loss: 0.8156 - classification_loss: 0.1296 157/500 [========>.....................] - ETA: 1:50 - loss: 0.9455 - regression_loss: 0.8158 - classification_loss: 0.1297 158/500 [========>.....................] - ETA: 1:49 - loss: 0.9442 - regression_loss: 0.8148 - classification_loss: 0.1294 159/500 [========>.....................] - ETA: 1:49 - loss: 0.9451 - regression_loss: 0.8158 - classification_loss: 0.1293 160/500 [========>.....................] - ETA: 1:49 - loss: 0.9422 - regression_loss: 0.8135 - classification_loss: 0.1287 161/500 [========>.....................] - ETA: 1:48 - loss: 0.9400 - regression_loss: 0.8116 - classification_loss: 0.1284 162/500 [========>.....................] - ETA: 1:48 - loss: 0.9429 - regression_loss: 0.8140 - classification_loss: 0.1289 163/500 [========>.....................] - ETA: 1:48 - loss: 0.9443 - regression_loss: 0.8156 - classification_loss: 0.1287 164/500 [========>.....................] - ETA: 1:47 - loss: 0.9420 - regression_loss: 0.8136 - classification_loss: 0.1284 165/500 [========>.....................] - ETA: 1:47 - loss: 0.9423 - regression_loss: 0.8140 - classification_loss: 0.1283 166/500 [========>.....................] - ETA: 1:47 - loss: 0.9413 - regression_loss: 0.8130 - classification_loss: 0.1283 167/500 [=========>....................] - ETA: 1:46 - loss: 0.9407 - regression_loss: 0.8126 - classification_loss: 0.1281 168/500 [=========>....................] - ETA: 1:46 - loss: 0.9390 - regression_loss: 0.8111 - classification_loss: 0.1278 169/500 [=========>....................] - ETA: 1:46 - loss: 0.9402 - regression_loss: 0.8124 - classification_loss: 0.1278 170/500 [=========>....................] - ETA: 1:45 - loss: 0.9416 - regression_loss: 0.8136 - classification_loss: 0.1280 171/500 [=========>....................] - ETA: 1:45 - loss: 0.9466 - regression_loss: 0.8178 - classification_loss: 0.1288 172/500 [=========>....................] - ETA: 1:45 - loss: 0.9469 - regression_loss: 0.8182 - classification_loss: 0.1287 173/500 [=========>....................] - ETA: 1:44 - loss: 0.9449 - regression_loss: 0.8167 - classification_loss: 0.1283 174/500 [=========>....................] - ETA: 1:44 - loss: 0.9428 - regression_loss: 0.8148 - classification_loss: 0.1280 175/500 [=========>....................] - ETA: 1:44 - loss: 0.9410 - regression_loss: 0.8132 - classification_loss: 0.1278 176/500 [=========>....................] - ETA: 1:43 - loss: 0.9398 - regression_loss: 0.8122 - classification_loss: 0.1276 177/500 [=========>....................] - ETA: 1:43 - loss: 0.9376 - regression_loss: 0.8099 - classification_loss: 0.1278 178/500 [=========>....................] - ETA: 1:43 - loss: 0.9343 - regression_loss: 0.8070 - classification_loss: 0.1273 179/500 [=========>....................] - ETA: 1:42 - loss: 0.9356 - regression_loss: 0.8081 - classification_loss: 0.1275 180/500 [=========>....................] - ETA: 1:42 - loss: 0.9362 - regression_loss: 0.8086 - classification_loss: 0.1275 181/500 [=========>....................] - ETA: 1:42 - loss: 0.9392 - regression_loss: 0.8111 - classification_loss: 0.1282 182/500 [=========>....................] - ETA: 1:42 - loss: 0.9397 - regression_loss: 0.8115 - classification_loss: 0.1283 183/500 [=========>....................] - ETA: 1:41 - loss: 0.9416 - regression_loss: 0.8131 - classification_loss: 0.1285 184/500 [==========>...................] - ETA: 1:41 - loss: 0.9383 - regression_loss: 0.8102 - classification_loss: 0.1282 185/500 [==========>...................] - ETA: 1:40 - loss: 0.9361 - regression_loss: 0.8083 - classification_loss: 0.1278 186/500 [==========>...................] - ETA: 1:40 - loss: 0.9360 - regression_loss: 0.8083 - classification_loss: 0.1278 187/500 [==========>...................] - ETA: 1:40 - loss: 0.9375 - regression_loss: 0.8094 - classification_loss: 0.1280 188/500 [==========>...................] - ETA: 1:40 - loss: 0.9362 - regression_loss: 0.8084 - classification_loss: 0.1279 189/500 [==========>...................] - ETA: 1:39 - loss: 0.9346 - regression_loss: 0.8070 - classification_loss: 0.1276 190/500 [==========>...................] - ETA: 1:39 - loss: 0.9346 - regression_loss: 0.8071 - classification_loss: 0.1276 191/500 [==========>...................] - ETA: 1:39 - loss: 0.9360 - regression_loss: 0.8080 - classification_loss: 0.1280 192/500 [==========>...................] - ETA: 1:38 - loss: 0.9402 - regression_loss: 0.8111 - classification_loss: 0.1291 193/500 [==========>...................] - ETA: 1:38 - loss: 0.9407 - regression_loss: 0.8114 - classification_loss: 0.1292 194/500 [==========>...................] - ETA: 1:37 - loss: 0.9402 - regression_loss: 0.8108 - classification_loss: 0.1293 195/500 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[===========================>..] - ETA: 5s - loss: 0.9529 - regression_loss: 0.8219 - classification_loss: 0.1310 484/500 [============================>.] - ETA: 5s - loss: 0.9516 - regression_loss: 0.8207 - classification_loss: 0.1308 485/500 [============================>.] - ETA: 4s - loss: 0.9509 - regression_loss: 0.8202 - classification_loss: 0.1307 486/500 [============================>.] - ETA: 4s - loss: 0.9501 - regression_loss: 0.8195 - classification_loss: 0.1305 487/500 [============================>.] - ETA: 4s - loss: 0.9499 - regression_loss: 0.8195 - classification_loss: 0.1304 488/500 [============================>.] - ETA: 3s - loss: 0.9510 - regression_loss: 0.8201 - classification_loss: 0.1309 489/500 [============================>.] - ETA: 3s - loss: 0.9497 - regression_loss: 0.8190 - classification_loss: 0.1307 490/500 [============================>.] - ETA: 3s - loss: 0.9491 - regression_loss: 0.8185 - classification_loss: 0.1306 491/500 [============================>.] - ETA: 2s - loss: 0.9507 - regression_loss: 0.8199 - classification_loss: 0.1309 492/500 [============================>.] - ETA: 2s - loss: 0.9501 - regression_loss: 0.8194 - classification_loss: 0.1307 493/500 [============================>.] - ETA: 2s - loss: 0.9508 - regression_loss: 0.8196 - classification_loss: 0.1311 494/500 [============================>.] - ETA: 1s - loss: 0.9517 - regression_loss: 0.8205 - classification_loss: 0.1312 495/500 [============================>.] - ETA: 1s - loss: 0.9516 - regression_loss: 0.8204 - classification_loss: 0.1312 496/500 [============================>.] - ETA: 1s - loss: 0.9511 - regression_loss: 0.8201 - classification_loss: 0.1310 497/500 [============================>.] - ETA: 0s - loss: 0.9512 - regression_loss: 0.8202 - classification_loss: 0.1310 498/500 [============================>.] - ETA: 0s - loss: 0.9520 - regression_loss: 0.8209 - classification_loss: 0.1311 499/500 [============================>.] - ETA: 0s - loss: 0.9511 - regression_loss: 0.8201 - classification_loss: 0.1309 500/500 [==============================] - 161s 321ms/step - loss: 0.9520 - regression_loss: 0.8209 - classification_loss: 0.1311 326 instances of class plum with average precision: 0.7779 mAP: 0.7779 Epoch 00018: saving model to ./training/snapshots/resnet101_pascal_18.h5 Epoch 19/150 1/500 [..............................] - ETA: 2:40 - loss: 0.7253 - regression_loss: 0.6405 - classification_loss: 0.0847 2/500 [..............................] - ETA: 2:40 - loss: 0.6804 - regression_loss: 0.5955 - classification_loss: 0.0849 3/500 [..............................] - ETA: 2:38 - loss: 1.0630 - regression_loss: 0.9033 - classification_loss: 0.1596 4/500 [..............................] - ETA: 2:39 - loss: 1.1583 - regression_loss: 0.9715 - classification_loss: 0.1868 5/500 [..............................] - ETA: 2:43 - loss: 1.0700 - regression_loss: 0.9012 - classification_loss: 0.1688 6/500 [..............................] - ETA: 2:42 - loss: 1.1260 - regression_loss: 0.9609 - classification_loss: 0.1651 7/500 [..............................] - ETA: 2:41 - loss: 1.1200 - regression_loss: 0.9520 - classification_loss: 0.1679 8/500 [..............................] - ETA: 2:42 - loss: 1.1054 - regression_loss: 0.9478 - classification_loss: 0.1576 9/500 [..............................] - ETA: 2:41 - loss: 1.1448 - regression_loss: 0.9791 - classification_loss: 0.1658 10/500 [..............................] - ETA: 2:40 - loss: 1.0953 - regression_loss: 0.9366 - classification_loss: 0.1587 11/500 [..............................] - ETA: 2:38 - loss: 1.0782 - regression_loss: 0.9230 - classification_loss: 0.1552 12/500 [..............................] - ETA: 2:37 - loss: 1.0559 - regression_loss: 0.9074 - classification_loss: 0.1484 13/500 [..............................] - ETA: 2:36 - loss: 0.9937 - regression_loss: 0.8536 - classification_loss: 0.1401 14/500 [..............................] - ETA: 2:35 - loss: 0.9733 - regression_loss: 0.8373 - classification_loss: 0.1360 15/500 [..............................] - ETA: 2:35 - loss: 1.0154 - regression_loss: 0.8735 - classification_loss: 0.1419 16/500 [..............................] - ETA: 2:35 - loss: 1.0042 - regression_loss: 0.8673 - classification_loss: 0.1369 17/500 [>.............................] - ETA: 2:35 - loss: 0.9963 - regression_loss: 0.8592 - classification_loss: 0.1371 18/500 [>.............................] - ETA: 2:35 - loss: 0.9806 - regression_loss: 0.8460 - classification_loss: 0.1346 19/500 [>.............................] - ETA: 2:35 - loss: 1.0020 - regression_loss: 0.8604 - classification_loss: 0.1416 20/500 [>.............................] - ETA: 2:35 - loss: 0.9995 - regression_loss: 0.8574 - classification_loss: 0.1421 21/500 [>.............................] - ETA: 2:34 - loss: 0.9679 - regression_loss: 0.8308 - classification_loss: 0.1371 22/500 [>.............................] - ETA: 2:33 - loss: 0.9530 - regression_loss: 0.8202 - classification_loss: 0.1328 23/500 [>.............................] - ETA: 2:33 - loss: 0.9607 - regression_loss: 0.8228 - classification_loss: 0.1379 24/500 [>.............................] - ETA: 2:32 - loss: 0.9554 - regression_loss: 0.8176 - classification_loss: 0.1378 25/500 [>.............................] - ETA: 2:32 - loss: 0.9455 - regression_loss: 0.8099 - classification_loss: 0.1356 26/500 [>.............................] - ETA: 2:31 - loss: 0.9511 - regression_loss: 0.8146 - classification_loss: 0.1365 27/500 [>.............................] - ETA: 2:30 - loss: 0.9710 - regression_loss: 0.8339 - classification_loss: 0.1371 28/500 [>.............................] - ETA: 2:30 - loss: 0.9468 - regression_loss: 0.8133 - classification_loss: 0.1335 29/500 [>.............................] - ETA: 2:30 - loss: 0.9485 - regression_loss: 0.8160 - classification_loss: 0.1325 30/500 [>.............................] - ETA: 2:30 - loss: 0.9338 - regression_loss: 0.8032 - classification_loss: 0.1306 31/500 [>.............................] - ETA: 2:30 - loss: 0.9284 - regression_loss: 0.7986 - classification_loss: 0.1298 32/500 [>.............................] - ETA: 2:30 - loss: 0.9207 - regression_loss: 0.7915 - classification_loss: 0.1292 33/500 [>.............................] - ETA: 2:30 - loss: 0.9131 - regression_loss: 0.7857 - classification_loss: 0.1275 34/500 [=>............................] - ETA: 2:30 - loss: 0.9046 - regression_loss: 0.7784 - classification_loss: 0.1262 35/500 [=>............................] - ETA: 2:29 - loss: 0.8973 - regression_loss: 0.7724 - classification_loss: 0.1249 36/500 [=>............................] - ETA: 2:29 - loss: 0.9048 - regression_loss: 0.7802 - classification_loss: 0.1246 37/500 [=>............................] - ETA: 2:29 - loss: 0.9004 - regression_loss: 0.7748 - classification_loss: 0.1256 38/500 [=>............................] - ETA: 2:28 - loss: 0.8986 - regression_loss: 0.7739 - classification_loss: 0.1247 39/500 [=>............................] - ETA: 2:28 - loss: 0.9027 - regression_loss: 0.7780 - classification_loss: 0.1248 40/500 [=>............................] - ETA: 2:28 - loss: 0.9027 - regression_loss: 0.7780 - classification_loss: 0.1247 41/500 [=>............................] - ETA: 2:28 - loss: 0.9203 - regression_loss: 0.7910 - classification_loss: 0.1293 42/500 [=>............................] - ETA: 2:27 - loss: 0.9256 - regression_loss: 0.7941 - classification_loss: 0.1315 43/500 [=>............................] - ETA: 2:27 - loss: 0.9346 - regression_loss: 0.8014 - classification_loss: 0.1333 44/500 [=>............................] - ETA: 2:27 - loss: 0.9300 - regression_loss: 0.7978 - classification_loss: 0.1322 45/500 [=>............................] - ETA: 2:26 - loss: 0.9338 - regression_loss: 0.8021 - classification_loss: 0.1316 46/500 [=>............................] - ETA: 2:26 - loss: 0.9424 - regression_loss: 0.8096 - classification_loss: 0.1328 47/500 [=>............................] - ETA: 2:26 - loss: 0.9382 - regression_loss: 0.8062 - classification_loss: 0.1320 48/500 [=>............................] - ETA: 2:26 - loss: 0.9354 - regression_loss: 0.8035 - classification_loss: 0.1319 49/500 [=>............................] - ETA: 2:25 - loss: 0.9346 - regression_loss: 0.8032 - classification_loss: 0.1314 50/500 [==>...........................] - ETA: 2:25 - loss: 0.9578 - regression_loss: 0.8193 - classification_loss: 0.1385 51/500 [==>...........................] - ETA: 2:25 - loss: 0.9515 - regression_loss: 0.8143 - classification_loss: 0.1372 52/500 [==>...........................] - ETA: 2:24 - loss: 0.9431 - regression_loss: 0.8075 - classification_loss: 0.1356 53/500 [==>...........................] - ETA: 2:24 - loss: 0.9371 - regression_loss: 0.8029 - classification_loss: 0.1342 54/500 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[==========>...................] - ETA: 1:39 - loss: 0.9406 - regression_loss: 0.8110 - classification_loss: 0.1295 191/500 [==========>...................] - ETA: 1:38 - loss: 0.9395 - regression_loss: 0.8103 - classification_loss: 0.1292 192/500 [==========>...................] - ETA: 1:38 - loss: 0.9411 - regression_loss: 0.8118 - classification_loss: 0.1293 193/500 [==========>...................] - ETA: 1:38 - loss: 0.9387 - regression_loss: 0.8098 - classification_loss: 0.1289 194/500 [==========>...................] - ETA: 1:37 - loss: 0.9373 - regression_loss: 0.8087 - classification_loss: 0.1286 195/500 [==========>...................] - ETA: 1:37 - loss: 0.9376 - regression_loss: 0.8091 - classification_loss: 0.1285 196/500 [==========>...................] - ETA: 1:37 - loss: 0.9361 - regression_loss: 0.8078 - classification_loss: 0.1283 197/500 [==========>...................] - ETA: 1:36 - loss: 0.9348 - regression_loss: 0.8067 - classification_loss: 0.1281 198/500 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[============================>.] - ETA: 4s - loss: 0.9289 - regression_loss: 0.8016 - classification_loss: 0.1273 487/500 [============================>.] - ETA: 4s - loss: 0.9280 - regression_loss: 0.8009 - classification_loss: 0.1272 488/500 [============================>.] - ETA: 3s - loss: 0.9282 - regression_loss: 0.8011 - classification_loss: 0.1272 489/500 [============================>.] - ETA: 3s - loss: 0.9281 - regression_loss: 0.8011 - classification_loss: 0.1271 490/500 [============================>.] - ETA: 3s - loss: 0.9282 - regression_loss: 0.8012 - classification_loss: 0.1270 491/500 [============================>.] - ETA: 2s - loss: 0.9279 - regression_loss: 0.8009 - classification_loss: 0.1270 492/500 [============================>.] - ETA: 2s - loss: 0.9291 - regression_loss: 0.8018 - classification_loss: 0.1273 493/500 [============================>.] - ETA: 2s - loss: 0.9307 - regression_loss: 0.8028 - classification_loss: 0.1279 494/500 [============================>.] - ETA: 1s - loss: 0.9302 - regression_loss: 0.8024 - classification_loss: 0.1278 495/500 [============================>.] - ETA: 1s - loss: 0.9295 - regression_loss: 0.8018 - classification_loss: 0.1277 496/500 [============================>.] - ETA: 1s - loss: 0.9298 - regression_loss: 0.8020 - classification_loss: 0.1277 497/500 [============================>.] - ETA: 0s - loss: 0.9292 - regression_loss: 0.8016 - classification_loss: 0.1276 498/500 [============================>.] - ETA: 0s - loss: 0.9294 - regression_loss: 0.8019 - classification_loss: 0.1275 499/500 [============================>.] - ETA: 0s - loss: 0.9295 - regression_loss: 0.8021 - classification_loss: 0.1274 500/500 [==============================] - 160s 320ms/step - loss: 0.9298 - regression_loss: 0.8024 - classification_loss: 0.1274 326 instances of class plum with average precision: 0.7729 mAP: 0.7729 Epoch 00019: saving model to ./training/snapshots/resnet101_pascal_19.h5 Epoch 20/150 1/500 [..............................] - ETA: 2:33 - loss: 2.1545 - regression_loss: 1.6912 - classification_loss: 0.4633 2/500 [..............................] - ETA: 2:33 - loss: 1.7249 - regression_loss: 1.4103 - classification_loss: 0.3146 3/500 [..............................] - ETA: 2:35 - loss: 1.3562 - regression_loss: 1.1184 - classification_loss: 0.2378 4/500 [..............................] - ETA: 2:36 - loss: 1.4323 - regression_loss: 1.1755 - classification_loss: 0.2568 5/500 [..............................] - ETA: 2:36 - loss: 1.2417 - regression_loss: 1.0218 - classification_loss: 0.2199 6/500 [..............................] - ETA: 2:36 - loss: 1.1359 - regression_loss: 0.9400 - classification_loss: 0.1959 7/500 [..............................] - ETA: 2:36 - loss: 1.0226 - regression_loss: 0.8496 - classification_loss: 0.1730 8/500 [..............................] - ETA: 2:36 - loss: 0.9616 - regression_loss: 0.8024 - classification_loss: 0.1592 9/500 [..............................] - ETA: 2:37 - loss: 0.9299 - regression_loss: 0.7754 - classification_loss: 0.1545 10/500 [..............................] - ETA: 2:37 - loss: 0.9057 - regression_loss: 0.7502 - classification_loss: 0.1555 11/500 [..............................] - ETA: 2:36 - loss: 0.9282 - regression_loss: 0.7750 - classification_loss: 0.1531 12/500 [..............................] - ETA: 2:37 - loss: 0.9567 - regression_loss: 0.7902 - classification_loss: 0.1664 13/500 [..............................] - ETA: 2:36 - loss: 0.9411 - regression_loss: 0.7798 - classification_loss: 0.1613 14/500 [..............................] - ETA: 2:35 - loss: 0.9236 - regression_loss: 0.7672 - classification_loss: 0.1564 15/500 [..............................] - ETA: 2:35 - loss: 0.8786 - regression_loss: 0.7307 - classification_loss: 0.1479 16/500 [..............................] - ETA: 2:35 - loss: 0.9071 - regression_loss: 0.7539 - classification_loss: 0.1532 17/500 [>.............................] - ETA: 2:35 - loss: 0.8902 - regression_loss: 0.7403 - classification_loss: 0.1499 18/500 [>.............................] - ETA: 2:34 - loss: 0.8830 - regression_loss: 0.7375 - classification_loss: 0.1454 19/500 [>.............................] - ETA: 2:34 - loss: 0.8799 - regression_loss: 0.7373 - classification_loss: 0.1426 20/500 [>.............................] - ETA: 2:34 - loss: 0.8576 - regression_loss: 0.7198 - classification_loss: 0.1379 21/500 [>.............................] - ETA: 2:33 - loss: 0.8665 - regression_loss: 0.7297 - classification_loss: 0.1369 22/500 [>.............................] - ETA: 2:33 - loss: 0.8818 - regression_loss: 0.7449 - classification_loss: 0.1369 23/500 [>.............................] - ETA: 2:33 - loss: 0.8550 - regression_loss: 0.7223 - classification_loss: 0.1327 24/500 [>.............................] - ETA: 2:33 - loss: 0.8376 - regression_loss: 0.7078 - classification_loss: 0.1297 25/500 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[====>.........................] - ETA: 2:11 - loss: 0.8978 - regression_loss: 0.7712 - classification_loss: 0.1266 90/500 [====>.........................] - ETA: 2:10 - loss: 0.9054 - regression_loss: 0.7781 - classification_loss: 0.1273 91/500 [====>.........................] - ETA: 2:10 - loss: 0.9068 - regression_loss: 0.7797 - classification_loss: 0.1271 92/500 [====>.........................] - ETA: 2:10 - loss: 0.9049 - regression_loss: 0.7781 - classification_loss: 0.1268 93/500 [====>.........................] - ETA: 2:09 - loss: 0.9078 - regression_loss: 0.7813 - classification_loss: 0.1265 94/500 [====>.........................] - ETA: 2:09 - loss: 0.9047 - regression_loss: 0.7787 - classification_loss: 0.1260 95/500 [====>.........................] - ETA: 2:09 - loss: 0.8973 - regression_loss: 0.7722 - classification_loss: 0.1251 96/500 [====>.........................] - ETA: 2:08 - loss: 0.8955 - regression_loss: 0.7707 - classification_loss: 0.1248 97/500 [====>.........................] - ETA: 2:08 - loss: 0.8965 - regression_loss: 0.7716 - classification_loss: 0.1249 98/500 [====>.........................] - ETA: 2:08 - loss: 0.8945 - regression_loss: 0.7701 - classification_loss: 0.1244 99/500 [====>.........................] - ETA: 2:07 - loss: 0.8915 - regression_loss: 0.7678 - classification_loss: 0.1238 100/500 [=====>........................] - ETA: 2:07 - loss: 0.8952 - regression_loss: 0.7711 - classification_loss: 0.1240 101/500 [=====>........................] - ETA: 2:07 - loss: 0.8981 - regression_loss: 0.7740 - classification_loss: 0.1241 102/500 [=====>........................] - ETA: 2:06 - loss: 0.9036 - regression_loss: 0.7793 - classification_loss: 0.1244 103/500 [=====>........................] - ETA: 2:06 - loss: 0.8986 - regression_loss: 0.7751 - classification_loss: 0.1235 104/500 [=====>........................] - ETA: 2:06 - loss: 0.8996 - regression_loss: 0.7764 - classification_loss: 0.1232 105/500 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[=====>........................] - ETA: 2:03 - loss: 0.9158 - regression_loss: 0.7906 - classification_loss: 0.1253 114/500 [=====>........................] - ETA: 2:03 - loss: 0.9135 - regression_loss: 0.7885 - classification_loss: 0.1250 115/500 [=====>........................] - ETA: 2:02 - loss: 0.9112 - regression_loss: 0.7865 - classification_loss: 0.1247 116/500 [=====>........................] - ETA: 2:02 - loss: 0.9051 - regression_loss: 0.7812 - classification_loss: 0.1239 117/500 [======>.......................] - ETA: 2:02 - loss: 0.9023 - regression_loss: 0.7791 - classification_loss: 0.1233 118/500 [======>.......................] - ETA: 2:01 - loss: 0.9039 - regression_loss: 0.7804 - classification_loss: 0.1236 119/500 [======>.......................] - ETA: 2:01 - loss: 0.8984 - regression_loss: 0.7755 - classification_loss: 0.1228 120/500 [======>.......................] - ETA: 2:01 - loss: 0.8956 - regression_loss: 0.7734 - classification_loss: 0.1222 121/500 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[============================>.] - ETA: 3s - loss: 0.8918 - regression_loss: 0.7711 - classification_loss: 0.1207 490/500 [============================>.] - ETA: 3s - loss: 0.8922 - regression_loss: 0.7715 - classification_loss: 0.1207 491/500 [============================>.] - ETA: 2s - loss: 0.8912 - regression_loss: 0.7706 - classification_loss: 0.1206 492/500 [============================>.] - ETA: 2s - loss: 0.8898 - regression_loss: 0.7694 - classification_loss: 0.1204 493/500 [============================>.] - ETA: 2s - loss: 0.8895 - regression_loss: 0.7691 - classification_loss: 0.1204 494/500 [============================>.] - ETA: 1s - loss: 0.8883 - regression_loss: 0.7682 - classification_loss: 0.1202 495/500 [============================>.] - ETA: 1s - loss: 0.8893 - regression_loss: 0.7690 - classification_loss: 0.1203 496/500 [============================>.] - ETA: 1s - loss: 0.8888 - regression_loss: 0.7686 - classification_loss: 0.1202 497/500 [============================>.] - ETA: 0s - loss: 0.8890 - regression_loss: 0.7688 - classification_loss: 0.1203 498/500 [============================>.] - ETA: 0s - loss: 0.8887 - regression_loss: 0.7685 - classification_loss: 0.1202 499/500 [============================>.] - ETA: 0s - loss: 0.8896 - regression_loss: 0.7689 - classification_loss: 0.1207 500/500 [==============================] - 161s 321ms/step - loss: 0.8892 - regression_loss: 0.7686 - classification_loss: 0.1205 326 instances of class plum with average precision: 0.7954 mAP: 0.7954 Epoch 00020: saving model to ./training/snapshots/resnet101_pascal_20.h5 Epoch 21/150 1/500 [..............................] - ETA: 2:33 - loss: 0.9821 - regression_loss: 0.8340 - classification_loss: 0.1481 2/500 [..............................] - ETA: 2:33 - loss: 1.1351 - regression_loss: 0.9492 - classification_loss: 0.1859 3/500 [..............................] - ETA: 2:32 - loss: 1.1708 - regression_loss: 1.0093 - classification_loss: 0.1615 4/500 [..............................] - ETA: 2:32 - loss: 0.9449 - regression_loss: 0.8162 - classification_loss: 0.1288 5/500 [..............................] - ETA: 2:32 - loss: 1.0134 - regression_loss: 0.8796 - classification_loss: 0.1338 6/500 [..............................] - ETA: 2:34 - loss: 0.9407 - regression_loss: 0.8183 - classification_loss: 0.1224 7/500 [..............................] - ETA: 2:34 - loss: 0.9042 - regression_loss: 0.7852 - classification_loss: 0.1190 8/500 [..............................] - ETA: 2:34 - loss: 0.9157 - regression_loss: 0.7986 - classification_loss: 0.1171 9/500 [..............................] - ETA: 2:34 - loss: 0.8834 - regression_loss: 0.7690 - classification_loss: 0.1144 10/500 [..............................] - ETA: 2:36 - loss: 0.8542 - regression_loss: 0.7420 - classification_loss: 0.1122 11/500 [..............................] - ETA: 2:36 - loss: 0.8739 - regression_loss: 0.7618 - classification_loss: 0.1121 12/500 [..............................] - ETA: 2:35 - loss: 0.8945 - regression_loss: 0.7729 - classification_loss: 0.1216 13/500 [..............................] - ETA: 2:35 - loss: 0.8949 - regression_loss: 0.7748 - classification_loss: 0.1202 14/500 [..............................] - ETA: 2:36 - loss: 0.8648 - regression_loss: 0.7498 - classification_loss: 0.1150 15/500 [..............................] - ETA: 2:36 - loss: 0.8346 - regression_loss: 0.7236 - classification_loss: 0.1110 16/500 [..............................] - ETA: 2:35 - loss: 0.8356 - regression_loss: 0.7240 - classification_loss: 0.1116 17/500 [>.............................] - ETA: 2:34 - loss: 0.8203 - regression_loss: 0.7111 - classification_loss: 0.1092 18/500 [>.............................] - ETA: 2:35 - loss: 0.8390 - regression_loss: 0.7268 - classification_loss: 0.1122 19/500 [>.............................] - ETA: 2:34 - loss: 0.8504 - regression_loss: 0.7374 - classification_loss: 0.1131 20/500 [>.............................] - ETA: 2:34 - loss: 0.8838 - regression_loss: 0.7664 - classification_loss: 0.1174 21/500 [>.............................] - ETA: 2:34 - loss: 0.8618 - regression_loss: 0.7474 - classification_loss: 0.1144 22/500 [>.............................] - ETA: 2:34 - loss: 0.8784 - regression_loss: 0.7605 - classification_loss: 0.1179 23/500 [>.............................] - ETA: 2:33 - loss: 0.8724 - regression_loss: 0.7561 - classification_loss: 0.1163 24/500 [>.............................] - ETA: 2:33 - loss: 0.9048 - regression_loss: 0.7855 - classification_loss: 0.1193 25/500 [>.............................] - ETA: 2:32 - loss: 0.8960 - regression_loss: 0.7773 - classification_loss: 0.1187 26/500 [>.............................] - ETA: 2:32 - loss: 0.8717 - regression_loss: 0.7550 - classification_loss: 0.1167 27/500 [>.............................] - ETA: 2:32 - loss: 0.8686 - regression_loss: 0.7530 - classification_loss: 0.1156 28/500 [>.............................] - ETA: 2:31 - loss: 0.8622 - regression_loss: 0.7485 - classification_loss: 0.1137 29/500 [>.............................] - ETA: 2:31 - loss: 0.8771 - regression_loss: 0.7593 - classification_loss: 0.1178 30/500 [>.............................] - ETA: 2:31 - loss: 0.8682 - regression_loss: 0.7491 - classification_loss: 0.1191 31/500 [>.............................] - ETA: 2:31 - loss: 0.8571 - regression_loss: 0.7394 - classification_loss: 0.1177 32/500 [>.............................] - ETA: 2:31 - loss: 0.8866 - regression_loss: 0.7622 - classification_loss: 0.1243 33/500 [>.............................] - ETA: 2:30 - loss: 0.8824 - regression_loss: 0.7598 - classification_loss: 0.1227 34/500 [=>............................] - ETA: 2:30 - loss: 0.8712 - regression_loss: 0.7512 - classification_loss: 0.1201 35/500 [=>............................] - ETA: 2:30 - loss: 0.8605 - regression_loss: 0.7427 - classification_loss: 0.1178 36/500 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[==>...........................] - ETA: 2:24 - loss: 0.8736 - regression_loss: 0.7541 - classification_loss: 0.1195 53/500 [==>...........................] - ETA: 2:23 - loss: 0.8738 - regression_loss: 0.7541 - classification_loss: 0.1197 54/500 [==>...........................] - ETA: 2:23 - loss: 0.8673 - regression_loss: 0.7483 - classification_loss: 0.1190 55/500 [==>...........................] - ETA: 2:23 - loss: 0.8588 - regression_loss: 0.7406 - classification_loss: 0.1182 56/500 [==>...........................] - ETA: 2:22 - loss: 0.8535 - regression_loss: 0.7361 - classification_loss: 0.1174 57/500 [==>...........................] - ETA: 2:22 - loss: 0.8455 - regression_loss: 0.7295 - classification_loss: 0.1160 58/500 [==>...........................] - ETA: 2:22 - loss: 0.8445 - regression_loss: 0.7290 - classification_loss: 0.1155 59/500 [==>...........................] - ETA: 2:21 - loss: 0.8475 - regression_loss: 0.7321 - classification_loss: 0.1154 60/500 [==>...........................] - ETA: 2:21 - loss: 0.8439 - regression_loss: 0.7288 - classification_loss: 0.1151 61/500 [==>...........................] - ETA: 2:21 - loss: 0.8423 - regression_loss: 0.7277 - classification_loss: 0.1145 62/500 [==>...........................] - ETA: 2:20 - loss: 0.8438 - regression_loss: 0.7299 - classification_loss: 0.1139 63/500 [==>...........................] - ETA: 2:20 - loss: 0.8449 - regression_loss: 0.7313 - classification_loss: 0.1136 64/500 [==>...........................] - ETA: 2:20 - loss: 0.8420 - regression_loss: 0.7292 - classification_loss: 0.1128 65/500 [==>...........................] - ETA: 2:20 - loss: 0.8384 - regression_loss: 0.7263 - classification_loss: 0.1121 66/500 [==>...........................] - ETA: 2:19 - loss: 0.8369 - regression_loss: 0.7253 - classification_loss: 0.1115 67/500 [===>..........................] - ETA: 2:19 - loss: 0.8288 - regression_loss: 0.7183 - classification_loss: 0.1105 68/500 [===>..........................] - ETA: 2:19 - loss: 0.8351 - regression_loss: 0.7230 - classification_loss: 0.1121 69/500 [===>..........................] - ETA: 2:18 - loss: 0.8304 - regression_loss: 0.7190 - classification_loss: 0.1114 70/500 [===>..........................] - ETA: 2:18 - loss: 0.8231 - regression_loss: 0.7127 - classification_loss: 0.1104 71/500 [===>..........................] - ETA: 2:17 - loss: 0.8166 - regression_loss: 0.7070 - classification_loss: 0.1095 72/500 [===>..........................] - ETA: 2:17 - loss: 0.8172 - regression_loss: 0.7064 - classification_loss: 0.1107 73/500 [===>..........................] - ETA: 2:17 - loss: 0.8239 - regression_loss: 0.7124 - classification_loss: 0.1115 74/500 [===>..........................] - ETA: 2:16 - loss: 0.8176 - regression_loss: 0.7071 - classification_loss: 0.1105 75/500 [===>..........................] - ETA: 2:16 - loss: 0.8234 - regression_loss: 0.7125 - classification_loss: 0.1109 76/500 [===>..........................] - ETA: 2:16 - loss: 0.8281 - regression_loss: 0.7166 - classification_loss: 0.1115 77/500 [===>..........................] - ETA: 2:16 - loss: 0.8263 - regression_loss: 0.7154 - classification_loss: 0.1110 78/500 [===>..........................] - ETA: 2:15 - loss: 0.8322 - regression_loss: 0.7194 - classification_loss: 0.1128 79/500 [===>..........................] - ETA: 2:15 - loss: 0.8340 - regression_loss: 0.7217 - classification_loss: 0.1124 80/500 [===>..........................] - ETA: 2:14 - loss: 0.8295 - regression_loss: 0.7179 - classification_loss: 0.1116 81/500 [===>..........................] - ETA: 2:14 - loss: 0.8270 - regression_loss: 0.7153 - classification_loss: 0.1117 82/500 [===>..........................] - ETA: 2:14 - loss: 0.8246 - regression_loss: 0.7135 - classification_loss: 0.1112 83/500 [===>..........................] - ETA: 2:13 - loss: 0.8285 - regression_loss: 0.7169 - classification_loss: 0.1115 84/500 [====>.........................] - ETA: 2:13 - loss: 0.8273 - regression_loss: 0.7159 - classification_loss: 0.1114 85/500 [====>.........................] - ETA: 2:13 - loss: 0.8247 - regression_loss: 0.7134 - classification_loss: 0.1113 86/500 [====>.........................] - ETA: 2:13 - loss: 0.8185 - regression_loss: 0.7081 - classification_loss: 0.1104 87/500 [====>.........................] - ETA: 2:12 - loss: 0.8210 - regression_loss: 0.7101 - classification_loss: 0.1109 88/500 [====>.........................] - ETA: 2:12 - loss: 0.8214 - regression_loss: 0.7105 - classification_loss: 0.1108 89/500 [====>.........................] - ETA: 2:12 - loss: 0.8253 - regression_loss: 0.7140 - classification_loss: 0.1113 90/500 [====>.........................] - ETA: 2:11 - loss: 0.8284 - regression_loss: 0.7172 - classification_loss: 0.1112 91/500 [====>.........................] - ETA: 2:11 - loss: 0.8318 - regression_loss: 0.7204 - classification_loss: 0.1114 92/500 [====>.........................] - ETA: 2:11 - loss: 0.8445 - regression_loss: 0.7306 - classification_loss: 0.1139 93/500 [====>.........................] - ETA: 2:11 - loss: 0.8387 - regression_loss: 0.7258 - classification_loss: 0.1129 94/500 [====>.........................] - ETA: 2:10 - loss: 0.8462 - regression_loss: 0.7313 - classification_loss: 0.1149 95/500 [====>.........................] - ETA: 2:10 - loss: 0.8424 - regression_loss: 0.7283 - classification_loss: 0.1142 96/500 [====>.........................] - ETA: 2:10 - loss: 0.8438 - regression_loss: 0.7293 - classification_loss: 0.1145 97/500 [====>.........................] - ETA: 2:09 - loss: 0.8475 - regression_loss: 0.7325 - classification_loss: 0.1150 98/500 [====>.........................] - ETA: 2:09 - loss: 0.8461 - regression_loss: 0.7312 - classification_loss: 0.1150 99/500 [====>.........................] - ETA: 2:09 - loss: 0.8467 - regression_loss: 0.7316 - classification_loss: 0.1151 100/500 [=====>........................] - ETA: 2:08 - loss: 0.8450 - regression_loss: 0.7301 - classification_loss: 0.1149 101/500 [=====>........................] - ETA: 2:08 - loss: 0.8397 - regression_loss: 0.7255 - classification_loss: 0.1143 102/500 [=====>........................] - ETA: 2:08 - loss: 0.8359 - regression_loss: 0.7222 - classification_loss: 0.1136 103/500 [=====>........................] - ETA: 2:07 - loss: 0.8311 - regression_loss: 0.7182 - classification_loss: 0.1129 104/500 [=====>........................] - ETA: 2:07 - loss: 0.8292 - regression_loss: 0.7169 - classification_loss: 0.1123 105/500 [=====>........................] - ETA: 2:07 - loss: 0.8292 - regression_loss: 0.7170 - classification_loss: 0.1121 106/500 [=====>........................] - ETA: 2:07 - loss: 0.8272 - regression_loss: 0.7157 - classification_loss: 0.1114 107/500 [=====>........................] - ETA: 2:06 - loss: 0.8309 - regression_loss: 0.7177 - classification_loss: 0.1132 108/500 [=====>........................] - ETA: 2:06 - loss: 0.8320 - regression_loss: 0.7187 - classification_loss: 0.1133 109/500 [=====>........................] - ETA: 2:06 - loss: 0.8385 - regression_loss: 0.7241 - classification_loss: 0.1144 110/500 [=====>........................] - ETA: 2:05 - loss: 0.8393 - regression_loss: 0.7248 - classification_loss: 0.1145 111/500 [=====>........................] - ETA: 2:05 - loss: 0.8397 - regression_loss: 0.7254 - classification_loss: 0.1142 112/500 [=====>........................] - ETA: 2:05 - loss: 0.8364 - regression_loss: 0.7225 - classification_loss: 0.1139 113/500 [=====>........................] - ETA: 2:04 - loss: 0.8401 - regression_loss: 0.7260 - classification_loss: 0.1141 114/500 [=====>........................] - ETA: 2:04 - loss: 0.8356 - regression_loss: 0.7220 - classification_loss: 0.1136 115/500 [=====>........................] - ETA: 2:04 - loss: 0.8354 - regression_loss: 0.7222 - classification_loss: 0.1132 116/500 [=====>........................] - ETA: 2:03 - loss: 0.8373 - regression_loss: 0.7239 - classification_loss: 0.1134 117/500 [======>.......................] - ETA: 2:03 - loss: 0.8399 - regression_loss: 0.7259 - classification_loss: 0.1139 118/500 [======>.......................] - ETA: 2:03 - loss: 0.8450 - regression_loss: 0.7304 - classification_loss: 0.1146 119/500 [======>.......................] - ETA: 2:03 - loss: 0.8418 - regression_loss: 0.7278 - classification_loss: 0.1140 120/500 [======>.......................] - ETA: 2:02 - loss: 0.8430 - regression_loss: 0.7289 - classification_loss: 0.1141 121/500 [======>.......................] - ETA: 2:02 - loss: 0.8402 - regression_loss: 0.7264 - classification_loss: 0.1138 122/500 [======>.......................] - ETA: 2:02 - loss: 0.8365 - regression_loss: 0.7231 - classification_loss: 0.1134 123/500 [======>.......................] - ETA: 2:01 - loss: 0.8395 - regression_loss: 0.7250 - classification_loss: 0.1145 124/500 [======>.......................] - ETA: 2:01 - loss: 0.8363 - regression_loss: 0.7223 - classification_loss: 0.1140 125/500 [======>.......................] - ETA: 2:00 - loss: 0.8356 - regression_loss: 0.7219 - classification_loss: 0.1137 126/500 [======>.......................] - ETA: 2:00 - loss: 0.8324 - regression_loss: 0.7193 - classification_loss: 0.1131 127/500 [======>.......................] - ETA: 2:00 - loss: 0.8295 - regression_loss: 0.7169 - classification_loss: 0.1126 128/500 [======>.......................] - ETA: 2:00 - loss: 0.8297 - regression_loss: 0.7173 - classification_loss: 0.1124 129/500 [======>.......................] - ETA: 1:59 - loss: 0.8298 - regression_loss: 0.7175 - classification_loss: 0.1122 130/500 [======>.......................] - ETA: 1:59 - loss: 0.8280 - regression_loss: 0.7162 - classification_loss: 0.1118 131/500 [======>.......................] - ETA: 1:59 - loss: 0.8278 - regression_loss: 0.7154 - classification_loss: 0.1124 132/500 [======>.......................] - ETA: 1:58 - loss: 0.8271 - regression_loss: 0.7150 - classification_loss: 0.1121 133/500 [======>.......................] - ETA: 1:58 - loss: 0.8258 - regression_loss: 0.7140 - classification_loss: 0.1117 134/500 [=======>......................] - ETA: 1:58 - loss: 0.8242 - regression_loss: 0.7128 - classification_loss: 0.1114 135/500 [=======>......................] - ETA: 1:57 - loss: 0.8240 - regression_loss: 0.7127 - classification_loss: 0.1113 136/500 [=======>......................] - ETA: 1:57 - loss: 0.8291 - regression_loss: 0.7160 - classification_loss: 0.1131 137/500 [=======>......................] - ETA: 1:56 - loss: 0.8282 - regression_loss: 0.7156 - classification_loss: 0.1127 138/500 [=======>......................] - ETA: 1:56 - loss: 0.8265 - regression_loss: 0.7140 - classification_loss: 0.1125 139/500 [=======>......................] - ETA: 1:56 - loss: 0.8271 - regression_loss: 0.7147 - classification_loss: 0.1124 140/500 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[==============================] - 162s 323ms/step - loss: 0.8377 - regression_loss: 0.7231 - classification_loss: 0.1145 326 instances of class plum with average precision: 0.7953 mAP: 0.7953 Epoch 00021: saving model to ./training/snapshots/resnet101_pascal_21.h5 Epoch 22/150 1/500 [..............................] - ETA: 2:35 - loss: 0.6259 - regression_loss: 0.5358 - classification_loss: 0.0901 2/500 [..............................] - ETA: 2:39 - loss: 0.5341 - regression_loss: 0.4669 - classification_loss: 0.0672 3/500 [..............................] - ETA: 2:41 - loss: 0.4709 - regression_loss: 0.4148 - classification_loss: 0.0561 4/500 [..............................] - ETA: 2:40 - loss: 0.5415 - regression_loss: 0.4858 - classification_loss: 0.0557 5/500 [..............................] - ETA: 2:40 - loss: 0.6572 - regression_loss: 0.5941 - classification_loss: 0.0631 6/500 [..............................] - ETA: 2:40 - loss: 0.8765 - regression_loss: 0.7672 - classification_loss: 0.1093 7/500 [..............................] - ETA: 2:40 - loss: 0.8287 - regression_loss: 0.7293 - classification_loss: 0.0994 8/500 [..............................] - ETA: 2:39 - loss: 0.8327 - regression_loss: 0.7335 - classification_loss: 0.0992 9/500 [..............................] - ETA: 2:38 - loss: 0.8068 - regression_loss: 0.7109 - classification_loss: 0.0959 10/500 [..............................] - ETA: 2:38 - loss: 0.8477 - regression_loss: 0.7446 - classification_loss: 0.1032 11/500 [..............................] - ETA: 2:37 - loss: 0.8036 - regression_loss: 0.7051 - classification_loss: 0.0985 12/500 [..............................] - ETA: 2:38 - loss: 0.8413 - regression_loss: 0.7248 - classification_loss: 0.1165 13/500 [..............................] - ETA: 2:37 - loss: 0.8692 - regression_loss: 0.7502 - classification_loss: 0.1190 14/500 [..............................] - ETA: 2:37 - loss: 0.8566 - regression_loss: 0.7410 - classification_loss: 0.1156 15/500 [..............................] - ETA: 2:36 - loss: 0.8386 - regression_loss: 0.7257 - classification_loss: 0.1129 16/500 [..............................] - ETA: 2:36 - loss: 0.8166 - regression_loss: 0.7069 - classification_loss: 0.1097 17/500 [>.............................] - ETA: 2:36 - loss: 0.8016 - regression_loss: 0.6949 - classification_loss: 0.1068 18/500 [>.............................] - ETA: 2:35 - loss: 0.8008 - regression_loss: 0.6964 - classification_loss: 0.1044 19/500 [>.............................] - ETA: 2:35 - loss: 0.8573 - regression_loss: 0.7379 - classification_loss: 0.1194 20/500 [>.............................] - ETA: 2:35 - loss: 0.8698 - regression_loss: 0.7481 - classification_loss: 0.1218 21/500 [>.............................] - ETA: 2:34 - loss: 0.8524 - regression_loss: 0.7302 - classification_loss: 0.1221 22/500 [>.............................] - ETA: 2:34 - loss: 0.8579 - regression_loss: 0.7365 - classification_loss: 0.1214 23/500 [>.............................] - ETA: 2:34 - loss: 0.8519 - regression_loss: 0.7336 - classification_loss: 0.1182 24/500 [>.............................] - ETA: 2:33 - loss: 0.8420 - regression_loss: 0.7266 - classification_loss: 0.1154 25/500 [>.............................] - ETA: 2:32 - loss: 0.8694 - regression_loss: 0.7502 - classification_loss: 0.1192 26/500 [>.............................] - ETA: 2:32 - loss: 0.8743 - regression_loss: 0.7537 - classification_loss: 0.1206 27/500 [>.............................] - ETA: 2:32 - loss: 0.8631 - regression_loss: 0.7442 - classification_loss: 0.1189 28/500 [>.............................] - ETA: 2:31 - loss: 0.8700 - regression_loss: 0.7470 - classification_loss: 0.1230 29/500 [>.............................] - ETA: 2:31 - loss: 0.8839 - regression_loss: 0.7582 - classification_loss: 0.1257 30/500 [>.............................] - ETA: 2:30 - loss: 0.8961 - regression_loss: 0.7673 - classification_loss: 0.1288 31/500 [>.............................] - ETA: 2:30 - loss: 0.8966 - regression_loss: 0.7682 - classification_loss: 0.1284 32/500 [>.............................] - ETA: 2:30 - loss: 0.8902 - regression_loss: 0.7625 - classification_loss: 0.1276 33/500 [>.............................] - ETA: 2:30 - loss: 0.8858 - regression_loss: 0.7597 - classification_loss: 0.1261 34/500 [=>............................] - ETA: 2:29 - loss: 0.8840 - regression_loss: 0.7577 - classification_loss: 0.1263 35/500 [=>............................] - ETA: 2:29 - loss: 0.8836 - regression_loss: 0.7570 - classification_loss: 0.1266 36/500 [=>............................] - ETA: 2:29 - loss: 0.8789 - regression_loss: 0.7532 - classification_loss: 0.1257 37/500 [=>............................] - ETA: 2:28 - loss: 0.8714 - regression_loss: 0.7469 - classification_loss: 0.1244 38/500 [=>............................] - ETA: 2:28 - loss: 0.8851 - regression_loss: 0.7595 - classification_loss: 0.1257 39/500 [=>............................] - ETA: 2:28 - loss: 0.9172 - regression_loss: 0.7821 - classification_loss: 0.1351 40/500 [=>............................] - ETA: 2:28 - loss: 0.9133 - regression_loss: 0.7794 - classification_loss: 0.1339 41/500 [=>............................] - ETA: 2:27 - loss: 0.9299 - regression_loss: 0.7903 - classification_loss: 0.1396 42/500 [=>............................] - ETA: 2:27 - loss: 0.9234 - regression_loss: 0.7850 - classification_loss: 0.1383 43/500 [=>............................] - ETA: 2:26 - loss: 0.9188 - regression_loss: 0.7819 - classification_loss: 0.1369 44/500 [=>............................] - ETA: 2:26 - loss: 0.9235 - regression_loss: 0.7840 - classification_loss: 0.1396 45/500 [=>............................] - ETA: 2:25 - loss: 0.9197 - regression_loss: 0.7817 - classification_loss: 0.1381 46/500 [=>............................] - ETA: 2:25 - loss: 0.9053 - regression_loss: 0.7696 - classification_loss: 0.1356 47/500 [=>............................] - ETA: 2:25 - loss: 0.9097 - regression_loss: 0.7747 - classification_loss: 0.1350 48/500 [=>............................] - ETA: 2:25 - loss: 0.9180 - regression_loss: 0.7821 - classification_loss: 0.1359 49/500 [=>............................] - ETA: 2:25 - loss: 0.9253 - regression_loss: 0.7884 - classification_loss: 0.1369 50/500 [==>...........................] - ETA: 2:24 - loss: 0.9199 - regression_loss: 0.7840 - classification_loss: 0.1359 51/500 [==>...........................] - ETA: 2:24 - loss: 0.9234 - regression_loss: 0.7878 - classification_loss: 0.1356 52/500 [==>...........................] - ETA: 2:24 - loss: 0.9237 - regression_loss: 0.7890 - classification_loss: 0.1347 53/500 [==>...........................] - ETA: 2:24 - loss: 0.9198 - regression_loss: 0.7863 - classification_loss: 0.1335 54/500 [==>...........................] - ETA: 2:23 - loss: 0.9097 - regression_loss: 0.7779 - classification_loss: 0.1318 55/500 [==>...........................] - ETA: 2:23 - loss: 0.9071 - regression_loss: 0.7760 - classification_loss: 0.1311 56/500 [==>...........................] - ETA: 2:23 - loss: 0.8948 - regression_loss: 0.7654 - classification_loss: 0.1294 57/500 [==>...........................] - ETA: 2:22 - loss: 0.8858 - regression_loss: 0.7579 - classification_loss: 0.1279 58/500 [==>...........................] - ETA: 2:22 - loss: 0.8853 - regression_loss: 0.7580 - classification_loss: 0.1273 59/500 [==>...........................] - ETA: 2:22 - loss: 0.8798 - regression_loss: 0.7536 - classification_loss: 0.1262 60/500 [==>...........................] - ETA: 2:21 - loss: 0.8758 - regression_loss: 0.7505 - classification_loss: 0.1253 61/500 [==>...........................] - ETA: 2:21 - loss: 0.8799 - regression_loss: 0.7543 - classification_loss: 0.1256 62/500 [==>...........................] - ETA: 2:21 - loss: 0.8798 - regression_loss: 0.7547 - classification_loss: 0.1252 63/500 [==>...........................] - ETA: 2:20 - loss: 0.8837 - regression_loss: 0.7590 - classification_loss: 0.1247 64/500 [==>...........................] - ETA: 2:20 - loss: 0.8750 - regression_loss: 0.7518 - classification_loss: 0.1232 65/500 [==>...........................] - ETA: 2:20 - loss: 0.8676 - regression_loss: 0.7456 - classification_loss: 0.1220 66/500 [==>...........................] - ETA: 2:20 - loss: 0.8648 - regression_loss: 0.7431 - classification_loss: 0.1217 67/500 [===>..........................] - ETA: 2:19 - loss: 0.8625 - regression_loss: 0.7411 - classification_loss: 0.1213 68/500 [===>..........................] - ETA: 2:19 - loss: 0.8606 - regression_loss: 0.7402 - classification_loss: 0.1204 69/500 [===>..........................] - ETA: 2:18 - loss: 0.8625 - regression_loss: 0.7416 - classification_loss: 0.1209 70/500 [===>..........................] - ETA: 2:18 - loss: 0.8574 - regression_loss: 0.7375 - classification_loss: 0.1200 71/500 [===>..........................] - ETA: 2:18 - loss: 0.8545 - regression_loss: 0.7352 - classification_loss: 0.1192 72/500 [===>..........................] - ETA: 2:17 - loss: 0.8505 - regression_loss: 0.7323 - classification_loss: 0.1182 73/500 [===>..........................] - ETA: 2:17 - loss: 0.8417 - regression_loss: 0.7246 - classification_loss: 0.1171 74/500 [===>..........................] - ETA: 2:17 - loss: 0.8369 - regression_loss: 0.7207 - classification_loss: 0.1162 75/500 [===>..........................] - ETA: 2:16 - loss: 0.8340 - regression_loss: 0.7186 - classification_loss: 0.1154 76/500 [===>..........................] - ETA: 2:16 - loss: 0.8330 - regression_loss: 0.7180 - classification_loss: 0.1149 77/500 [===>..........................] - ETA: 2:15 - loss: 0.8265 - regression_loss: 0.7124 - classification_loss: 0.1141 78/500 [===>..........................] - ETA: 2:15 - loss: 0.8275 - regression_loss: 0.7134 - classification_loss: 0.1140 79/500 [===>..........................] - ETA: 2:15 - loss: 0.8288 - regression_loss: 0.7150 - classification_loss: 0.1139 80/500 [===>..........................] - ETA: 2:15 - loss: 0.8340 - regression_loss: 0.7196 - classification_loss: 0.1145 81/500 [===>..........................] - ETA: 2:14 - loss: 0.8326 - regression_loss: 0.7185 - classification_loss: 0.1141 82/500 [===>..........................] - ETA: 2:14 - loss: 0.8375 - regression_loss: 0.7234 - classification_loss: 0.1141 83/500 [===>..........................] - ETA: 2:14 - loss: 0.8398 - regression_loss: 0.7256 - classification_loss: 0.1142 84/500 [====>.........................] - ETA: 2:13 - loss: 0.8392 - regression_loss: 0.7254 - classification_loss: 0.1138 85/500 [====>.........................] - ETA: 2:13 - loss: 0.8374 - regression_loss: 0.7242 - classification_loss: 0.1132 86/500 [====>.........................] - ETA: 2:13 - loss: 0.8367 - regression_loss: 0.7239 - classification_loss: 0.1128 87/500 [====>.........................] - ETA: 2:12 - loss: 0.8390 - regression_loss: 0.7253 - classification_loss: 0.1138 88/500 [====>.........................] - ETA: 2:12 - loss: 0.8467 - regression_loss: 0.7321 - classification_loss: 0.1145 89/500 [====>.........................] - ETA: 2:12 - loss: 0.8459 - regression_loss: 0.7318 - classification_loss: 0.1141 90/500 [====>.........................] - ETA: 2:12 - loss: 0.8441 - regression_loss: 0.7302 - classification_loss: 0.1139 91/500 [====>.........................] - ETA: 2:11 - loss: 0.8445 - regression_loss: 0.7305 - classification_loss: 0.1139 92/500 [====>.........................] - ETA: 2:11 - loss: 0.8438 - regression_loss: 0.7295 - classification_loss: 0.1143 93/500 [====>.........................] - ETA: 2:11 - loss: 0.8475 - regression_loss: 0.7316 - classification_loss: 0.1159 94/500 [====>.........................] - ETA: 2:10 - loss: 0.8454 - regression_loss: 0.7300 - classification_loss: 0.1154 95/500 [====>.........................] - ETA: 2:10 - loss: 0.8416 - regression_loss: 0.7267 - classification_loss: 0.1149 96/500 [====>.........................] - ETA: 2:10 - loss: 0.8391 - regression_loss: 0.7248 - classification_loss: 0.1143 97/500 [====>.........................] - ETA: 2:09 - loss: 0.8361 - regression_loss: 0.7222 - classification_loss: 0.1139 98/500 [====>.........................] - ETA: 2:09 - loss: 0.8388 - regression_loss: 0.7249 - classification_loss: 0.1139 99/500 [====>.........................] - ETA: 2:09 - loss: 0.8446 - regression_loss: 0.7296 - classification_loss: 0.1150 100/500 [=====>........................] - ETA: 2:09 - loss: 0.8407 - regression_loss: 0.7260 - classification_loss: 0.1146 101/500 [=====>........................] - ETA: 2:08 - loss: 0.8399 - regression_loss: 0.7252 - classification_loss: 0.1147 102/500 [=====>........................] - ETA: 2:08 - loss: 0.8354 - regression_loss: 0.7213 - classification_loss: 0.1141 103/500 [=====>........................] - ETA: 2:08 - loss: 0.8370 - regression_loss: 0.7224 - classification_loss: 0.1146 104/500 [=====>........................] - ETA: 2:07 - loss: 0.8370 - regression_loss: 0.7222 - classification_loss: 0.1148 105/500 [=====>........................] - ETA: 2:07 - loss: 0.8347 - regression_loss: 0.7204 - classification_loss: 0.1143 106/500 [=====>........................] - ETA: 2:07 - loss: 0.8379 - regression_loss: 0.7236 - classification_loss: 0.1143 107/500 [=====>........................] - ETA: 2:06 - loss: 0.8402 - regression_loss: 0.7257 - classification_loss: 0.1145 108/500 [=====>........................] - ETA: 2:06 - loss: 0.8399 - regression_loss: 0.7251 - classification_loss: 0.1148 109/500 [=====>........................] - ETA: 2:06 - loss: 0.8367 - regression_loss: 0.7225 - classification_loss: 0.1142 110/500 [=====>........................] - ETA: 2:05 - loss: 0.8397 - regression_loss: 0.7247 - classification_loss: 0.1150 111/500 [=====>........................] - ETA: 2:05 - loss: 0.8359 - regression_loss: 0.7214 - classification_loss: 0.1144 112/500 [=====>........................] - ETA: 2:05 - loss: 0.8318 - regression_loss: 0.7175 - classification_loss: 0.1143 113/500 [=====>........................] - ETA: 2:04 - loss: 0.8263 - regression_loss: 0.7128 - classification_loss: 0.1136 114/500 [=====>........................] - ETA: 2:04 - loss: 0.8312 - regression_loss: 0.7171 - classification_loss: 0.1140 115/500 [=====>........................] - ETA: 2:04 - loss: 0.8423 - regression_loss: 0.7253 - classification_loss: 0.1171 116/500 [=====>........................] - ETA: 2:03 - loss: 0.8469 - regression_loss: 0.7290 - classification_loss: 0.1179 117/500 [======>.......................] - ETA: 2:03 - loss: 0.8499 - regression_loss: 0.7314 - classification_loss: 0.1184 118/500 [======>.......................] - ETA: 2:03 - loss: 0.8494 - regression_loss: 0.7311 - classification_loss: 0.1183 119/500 [======>.......................] - ETA: 2:02 - loss: 0.8444 - regression_loss: 0.7269 - classification_loss: 0.1175 120/500 [======>.......................] - ETA: 2:02 - loss: 0.8406 - regression_loss: 0.7237 - classification_loss: 0.1169 121/500 [======>.......................] - ETA: 2:02 - loss: 0.8395 - regression_loss: 0.7230 - classification_loss: 0.1166 122/500 [======>.......................] - ETA: 2:02 - loss: 0.8388 - regression_loss: 0.7224 - classification_loss: 0.1164 123/500 [======>.......................] - ETA: 2:01 - loss: 0.8444 - regression_loss: 0.7268 - classification_loss: 0.1176 124/500 [======>.......................] - ETA: 2:01 - loss: 0.8434 - regression_loss: 0.7262 - classification_loss: 0.1172 125/500 [======>.......................] - ETA: 2:01 - loss: 0.8394 - regression_loss: 0.7229 - classification_loss: 0.1165 126/500 [======>.......................] - ETA: 2:00 - loss: 0.8390 - regression_loss: 0.7228 - classification_loss: 0.1162 127/500 [======>.......................] - ETA: 2:00 - loss: 0.8422 - regression_loss: 0.7262 - classification_loss: 0.1160 128/500 [======>.......................] - ETA: 2:00 - loss: 0.8472 - regression_loss: 0.7310 - classification_loss: 0.1162 129/500 [======>.......................] - ETA: 1:59 - loss: 0.8447 - regression_loss: 0.7291 - classification_loss: 0.1156 130/500 [======>.......................] - ETA: 1:59 - loss: 0.8466 - regression_loss: 0.7309 - classification_loss: 0.1157 131/500 [======>.......................] - ETA: 1:59 - loss: 0.8438 - regression_loss: 0.7286 - classification_loss: 0.1152 132/500 [======>.......................] - ETA: 1:58 - loss: 0.8419 - regression_loss: 0.7271 - classification_loss: 0.1148 133/500 [======>.......................] - ETA: 1:58 - loss: 0.8450 - regression_loss: 0.7303 - classification_loss: 0.1148 134/500 [=======>......................] - ETA: 1:58 - loss: 0.8431 - regression_loss: 0.7286 - classification_loss: 0.1144 135/500 [=======>......................] - ETA: 1:57 - loss: 0.8437 - regression_loss: 0.7292 - classification_loss: 0.1145 136/500 [=======>......................] - ETA: 1:57 - loss: 0.8437 - regression_loss: 0.7295 - classification_loss: 0.1142 137/500 [=======>......................] - ETA: 1:57 - loss: 0.8394 - regression_loss: 0.7259 - classification_loss: 0.1136 138/500 [=======>......................] - ETA: 1:57 - loss: 0.8415 - regression_loss: 0.7279 - classification_loss: 0.1136 139/500 [=======>......................] - ETA: 1:56 - loss: 0.8368 - regression_loss: 0.7238 - classification_loss: 0.1130 140/500 [=======>......................] - ETA: 1:56 - loss: 0.8350 - regression_loss: 0.7223 - classification_loss: 0.1126 141/500 [=======>......................] - ETA: 1:56 - loss: 0.8332 - regression_loss: 0.7206 - classification_loss: 0.1125 142/500 [=======>......................] - ETA: 1:55 - loss: 0.8340 - regression_loss: 0.7215 - classification_loss: 0.1125 143/500 [=======>......................] - ETA: 1:55 - loss: 0.8340 - regression_loss: 0.7215 - classification_loss: 0.1124 144/500 [=======>......................] - ETA: 1:55 - loss: 0.8331 - regression_loss: 0.7208 - classification_loss: 0.1123 145/500 [=======>......................] - ETA: 1:54 - loss: 0.8313 - regression_loss: 0.7195 - classification_loss: 0.1118 146/500 [=======>......................] - ETA: 1:54 - loss: 0.8292 - regression_loss: 0.7178 - classification_loss: 0.1115 147/500 [=======>......................] - ETA: 1:54 - loss: 0.8330 - regression_loss: 0.7211 - classification_loss: 0.1119 148/500 [=======>......................] - ETA: 1:53 - loss: 0.8339 - regression_loss: 0.7219 - classification_loss: 0.1120 149/500 [=======>......................] - ETA: 1:53 - loss: 0.8357 - regression_loss: 0.7234 - classification_loss: 0.1123 150/500 [========>.....................] - ETA: 1:53 - loss: 0.8321 - regression_loss: 0.7205 - classification_loss: 0.1117 151/500 [========>.....................] - ETA: 1:52 - loss: 0.8322 - regression_loss: 0.7208 - classification_loss: 0.1113 152/500 [========>.....................] - ETA: 1:52 - loss: 0.8324 - regression_loss: 0.7212 - classification_loss: 0.1112 153/500 [========>.....................] - ETA: 1:52 - loss: 0.8358 - regression_loss: 0.7237 - classification_loss: 0.1121 154/500 [========>.....................] - ETA: 1:51 - loss: 0.8364 - regression_loss: 0.7245 - classification_loss: 0.1119 155/500 [========>.....................] - ETA: 1:51 - loss: 0.8369 - regression_loss: 0.7255 - classification_loss: 0.1114 156/500 [========>.....................] - ETA: 1:51 - loss: 0.8388 - regression_loss: 0.7275 - classification_loss: 0.1113 157/500 [========>.....................] - ETA: 1:51 - loss: 0.8373 - regression_loss: 0.7264 - classification_loss: 0.1109 158/500 [========>.....................] - ETA: 1:50 - loss: 0.8405 - regression_loss: 0.7287 - classification_loss: 0.1118 159/500 [========>.....................] - ETA: 1:50 - loss: 0.8444 - regression_loss: 0.7316 - classification_loss: 0.1129 160/500 [========>.....................] - ETA: 1:50 - loss: 0.8427 - regression_loss: 0.7302 - classification_loss: 0.1125 161/500 [========>.....................] - ETA: 1:49 - loss: 0.8426 - regression_loss: 0.7300 - classification_loss: 0.1126 162/500 [========>.....................] - ETA: 1:49 - loss: 0.8395 - regression_loss: 0.7273 - classification_loss: 0.1121 163/500 [========>.....................] - ETA: 1:49 - loss: 0.8408 - regression_loss: 0.7282 - classification_loss: 0.1125 164/500 [========>.....................] - ETA: 1:48 - loss: 0.8404 - regression_loss: 0.7279 - classification_loss: 0.1125 165/500 [========>.....................] - ETA: 1:48 - loss: 0.8403 - regression_loss: 0.7280 - classification_loss: 0.1123 166/500 [========>.....................] - ETA: 1:48 - loss: 0.8460 - regression_loss: 0.7321 - classification_loss: 0.1138 167/500 [=========>....................] - ETA: 1:47 - loss: 0.8489 - regression_loss: 0.7349 - classification_loss: 0.1140 168/500 [=========>....................] - ETA: 1:47 - loss: 0.8490 - regression_loss: 0.7350 - classification_loss: 0.1140 169/500 [=========>....................] - ETA: 1:47 - loss: 0.8470 - regression_loss: 0.7333 - classification_loss: 0.1137 170/500 [=========>....................] - ETA: 1:46 - loss: 0.8462 - regression_loss: 0.7327 - classification_loss: 0.1135 171/500 [=========>....................] - ETA: 1:46 - loss: 0.8465 - regression_loss: 0.7330 - classification_loss: 0.1135 172/500 [=========>....................] - ETA: 1:46 - loss: 0.8444 - regression_loss: 0.7308 - classification_loss: 0.1135 173/500 [=========>....................] - ETA: 1:45 - loss: 0.8457 - regression_loss: 0.7316 - classification_loss: 0.1141 174/500 [=========>....................] - ETA: 1:45 - loss: 0.8449 - regression_loss: 0.7309 - classification_loss: 0.1140 175/500 [=========>....................] - ETA: 1:45 - loss: 0.8433 - regression_loss: 0.7296 - classification_loss: 0.1137 176/500 [=========>....................] - ETA: 1:44 - loss: 0.8483 - regression_loss: 0.7342 - classification_loss: 0.1141 177/500 [=========>....................] - ETA: 1:44 - loss: 0.8479 - regression_loss: 0.7340 - classification_loss: 0.1139 178/500 [=========>....................] - ETA: 1:44 - loss: 0.8462 - regression_loss: 0.7327 - classification_loss: 0.1135 179/500 [=========>....................] - ETA: 1:43 - loss: 0.8471 - regression_loss: 0.7340 - classification_loss: 0.1131 180/500 [=========>....................] - ETA: 1:43 - loss: 0.8453 - regression_loss: 0.7327 - classification_loss: 0.1127 181/500 [=========>....................] - ETA: 1:43 - loss: 0.8452 - regression_loss: 0.7328 - classification_loss: 0.1124 182/500 [=========>....................] - ETA: 1:42 - loss: 0.8437 - regression_loss: 0.7314 - 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classification_loss: 0.1134 447/500 [=========================>....] - ETA: 17s - loss: 0.8517 - regression_loss: 0.7384 - classification_loss: 0.1133 448/500 [=========================>....] - ETA: 16s - loss: 0.8518 - regression_loss: 0.7385 - classification_loss: 0.1133 449/500 [=========================>....] - ETA: 16s - loss: 0.8507 - regression_loss: 0.7376 - classification_loss: 0.1131 450/500 [==========================>...] - ETA: 16s - loss: 0.8510 - regression_loss: 0.7377 - classification_loss: 0.1133 451/500 [==========================>...] - ETA: 15s - loss: 0.8507 - regression_loss: 0.7374 - classification_loss: 0.1133 452/500 [==========================>...] - ETA: 15s - loss: 0.8502 - regression_loss: 0.7370 - classification_loss: 0.1132 453/500 [==========================>...] - ETA: 15s - loss: 0.8503 - regression_loss: 0.7370 - classification_loss: 0.1133 454/500 [==========================>...] - ETA: 14s - loss: 0.8498 - regression_loss: 0.7367 - classification_loss: 0.1132 455/500 [==========================>...] - ETA: 14s - loss: 0.8487 - regression_loss: 0.7357 - classification_loss: 0.1130 456/500 [==========================>...] - ETA: 14s - loss: 0.8483 - regression_loss: 0.7354 - classification_loss: 0.1129 457/500 [==========================>...] - ETA: 13s - loss: 0.8472 - regression_loss: 0.7345 - classification_loss: 0.1127 458/500 [==========================>...] - ETA: 13s - loss: 0.8475 - regression_loss: 0.7348 - classification_loss: 0.1127 459/500 [==========================>...] - ETA: 13s - loss: 0.8474 - regression_loss: 0.7347 - classification_loss: 0.1127 460/500 [==========================>...] - ETA: 12s - loss: 0.8481 - regression_loss: 0.7354 - classification_loss: 0.1127 461/500 [==========================>...] - ETA: 12s - loss: 0.8480 - regression_loss: 0.7352 - classification_loss: 0.1128 462/500 [==========================>...] - ETA: 12s - loss: 0.8477 - regression_loss: 0.7350 - 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classification_loss: 0.1135  471/500 [===========================>..] - ETA: 9s - loss: 0.8510 - regression_loss: 0.7374 - classification_loss: 0.1136 472/500 [===========================>..] - ETA: 9s - loss: 0.8512 - regression_loss: 0.7376 - classification_loss: 0.1136 473/500 [===========================>..] - ETA: 8s - loss: 0.8512 - regression_loss: 0.7376 - classification_loss: 0.1136 474/500 [===========================>..] - ETA: 8s - loss: 0.8503 - regression_loss: 0.7368 - classification_loss: 0.1135 475/500 [===========================>..] - ETA: 8s - loss: 0.8504 - regression_loss: 0.7370 - classification_loss: 0.1134 476/500 [===========================>..] - ETA: 7s - loss: 0.8501 - regression_loss: 0.7367 - classification_loss: 0.1134 477/500 [===========================>..] - ETA: 7s - loss: 0.8499 - regression_loss: 0.7366 - classification_loss: 0.1133 478/500 [===========================>..] - ETA: 7s - loss: 0.8486 - regression_loss: 0.7355 - classification_loss: 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[============================>.] - ETA: 4s - loss: 0.8487 - regression_loss: 0.7353 - classification_loss: 0.1133 488/500 [============================>.] - ETA: 3s - loss: 0.8486 - regression_loss: 0.7353 - classification_loss: 0.1133 489/500 [============================>.] - ETA: 3s - loss: 0.8497 - regression_loss: 0.7362 - classification_loss: 0.1135 490/500 [============================>.] - ETA: 3s - loss: 0.8509 - regression_loss: 0.7373 - classification_loss: 0.1136 491/500 [============================>.] - ETA: 2s - loss: 0.8521 - regression_loss: 0.7384 - classification_loss: 0.1137 492/500 [============================>.] - ETA: 2s - loss: 0.8539 - regression_loss: 0.7398 - classification_loss: 0.1140 493/500 [============================>.] - ETA: 2s - loss: 0.8531 - regression_loss: 0.7393 - classification_loss: 0.1139 494/500 [============================>.] - ETA: 1s - loss: 0.8527 - regression_loss: 0.7389 - classification_loss: 0.1137 495/500 [============================>.] - ETA: 1s - loss: 0.8537 - regression_loss: 0.7398 - classification_loss: 0.1139 496/500 [============================>.] - ETA: 1s - loss: 0.8533 - regression_loss: 0.7395 - classification_loss: 0.1138 497/500 [============================>.] - ETA: 0s - loss: 0.8542 - regression_loss: 0.7403 - classification_loss: 0.1139 498/500 [============================>.] - ETA: 0s - loss: 0.8540 - regression_loss: 0.7402 - classification_loss: 0.1138 499/500 [============================>.] - ETA: 0s - loss: 0.8529 - regression_loss: 0.7393 - classification_loss: 0.1136 500/500 [==============================] - 162s 324ms/step - loss: 0.8532 - regression_loss: 0.7396 - classification_loss: 0.1136 326 instances of class plum with average precision: 0.7755 mAP: 0.7755 Epoch 00022: saving model to ./training/snapshots/resnet101_pascal_22.h5 Epoch 23/150 1/500 [..............................] - ETA: 2:33 - loss: 0.7200 - regression_loss: 0.6412 - classification_loss: 0.0788 2/500 [..............................] - ETA: 2:35 - loss: 0.8630 - regression_loss: 0.7659 - classification_loss: 0.0971 3/500 [..............................] - ETA: 2:36 - loss: 0.7076 - regression_loss: 0.6264 - classification_loss: 0.0812 4/500 [..............................] - ETA: 2:36 - loss: 0.7809 - regression_loss: 0.6756 - classification_loss: 0.1053 5/500 [..............................] - ETA: 2:35 - loss: 0.9318 - regression_loss: 0.7891 - classification_loss: 0.1426 6/500 [..............................] - ETA: 2:34 - loss: 0.8669 - regression_loss: 0.7333 - classification_loss: 0.1336 7/500 [..............................] - ETA: 2:34 - loss: 0.8580 - regression_loss: 0.7326 - classification_loss: 0.1254 8/500 [..............................] - ETA: 2:34 - loss: 0.8623 - regression_loss: 0.7398 - classification_loss: 0.1225 9/500 [..............................] - ETA: 2:33 - loss: 0.8504 - regression_loss: 0.7345 - classification_loss: 0.1159 10/500 [..............................] - ETA: 2:34 - loss: 0.7911 - regression_loss: 0.6820 - classification_loss: 0.1091 11/500 [..............................] - ETA: 2:34 - loss: 0.7723 - regression_loss: 0.6697 - classification_loss: 0.1026 12/500 [..............................] - ETA: 2:34 - loss: 0.7525 - regression_loss: 0.6510 - classification_loss: 0.1015 13/500 [..............................] - ETA: 2:33 - loss: 0.7379 - regression_loss: 0.6399 - classification_loss: 0.0980 14/500 [..............................] - ETA: 2:33 - loss: 0.7830 - regression_loss: 0.6689 - classification_loss: 0.1141 15/500 [..............................] - ETA: 2:33 - loss: 0.7894 - regression_loss: 0.6782 - classification_loss: 0.1112 16/500 [..............................] - ETA: 2:33 - loss: 0.7534 - regression_loss: 0.6477 - classification_loss: 0.1057 17/500 [>.............................] - ETA: 2:32 - loss: 0.7562 - regression_loss: 0.6508 - classification_loss: 0.1055 18/500 [>.............................] - ETA: 2:32 - loss: 0.7479 - regression_loss: 0.6457 - classification_loss: 0.1022 19/500 [>.............................] - ETA: 2:32 - loss: 0.7302 - regression_loss: 0.6307 - classification_loss: 0.0995 20/500 [>.............................] - ETA: 2:31 - loss: 0.7323 - regression_loss: 0.6324 - classification_loss: 0.0999 21/500 [>.............................] - ETA: 2:32 - loss: 0.7261 - regression_loss: 0.6270 - classification_loss: 0.0991 22/500 [>.............................] - ETA: 2:32 - loss: 0.7369 - regression_loss: 0.6365 - classification_loss: 0.1004 23/500 [>.............................] - ETA: 2:31 - loss: 0.7419 - regression_loss: 0.6396 - classification_loss: 0.1023 24/500 [>.............................] - ETA: 2:31 - loss: 0.7449 - regression_loss: 0.6440 - classification_loss: 0.1009 25/500 [>.............................] - ETA: 2:31 - loss: 0.7538 - regression_loss: 0.6529 - classification_loss: 0.1008 26/500 [>.............................] - ETA: 2:31 - loss: 0.7452 - regression_loss: 0.6462 - classification_loss: 0.0990 27/500 [>.............................] - ETA: 2:30 - loss: 0.7231 - regression_loss: 0.6267 - classification_loss: 0.0963 28/500 [>.............................] - ETA: 2:30 - loss: 0.7148 - regression_loss: 0.6170 - classification_loss: 0.0978 29/500 [>.............................] - ETA: 2:29 - loss: 0.7270 - regression_loss: 0.6253 - classification_loss: 0.1017 30/500 [>.............................] - ETA: 2:29 - loss: 0.7235 - regression_loss: 0.6218 - classification_loss: 0.1017 31/500 [>.............................] - ETA: 2:29 - loss: 0.7315 - regression_loss: 0.6289 - classification_loss: 0.1026 32/500 [>.............................] - ETA: 2:29 - loss: 0.7337 - regression_loss: 0.6323 - classification_loss: 0.1013 33/500 [>.............................] - ETA: 2:28 - loss: 0.7409 - regression_loss: 0.6405 - classification_loss: 0.1004 34/500 [=>............................] - ETA: 2:28 - loss: 0.7627 - regression_loss: 0.6590 - classification_loss: 0.1038 35/500 [=>............................] - ETA: 2:27 - loss: 0.7732 - regression_loss: 0.6672 - classification_loss: 0.1060 36/500 [=>............................] - ETA: 2:27 - loss: 0.7705 - regression_loss: 0.6650 - classification_loss: 0.1055 37/500 [=>............................] - ETA: 2:27 - loss: 0.7598 - regression_loss: 0.6560 - classification_loss: 0.1038 38/500 [=>............................] - ETA: 2:27 - loss: 0.7545 - regression_loss: 0.6516 - classification_loss: 0.1029 39/500 [=>............................] - ETA: 2:27 - loss: 0.7484 - regression_loss: 0.6464 - classification_loss: 0.1020 40/500 [=>............................] - ETA: 2:26 - loss: 0.7454 - regression_loss: 0.6442 - classification_loss: 0.1011 41/500 [=>............................] - ETA: 2:26 - loss: 0.7394 - regression_loss: 0.6394 - classification_loss: 0.1000 42/500 [=>............................] - ETA: 2:26 - loss: 0.7491 - regression_loss: 0.6483 - classification_loss: 0.1008 43/500 [=>............................] - ETA: 2:25 - loss: 0.7629 - regression_loss: 0.6603 - classification_loss: 0.1025 44/500 [=>............................] - ETA: 2:25 - loss: 0.7655 - regression_loss: 0.6623 - classification_loss: 0.1032 45/500 [=>............................] - ETA: 2:24 - loss: 0.7563 - regression_loss: 0.6546 - classification_loss: 0.1017 46/500 [=>............................] - ETA: 2:24 - loss: 0.7692 - regression_loss: 0.6662 - classification_loss: 0.1030 47/500 [=>............................] - ETA: 2:24 - loss: 0.7823 - regression_loss: 0.6769 - classification_loss: 0.1054 48/500 [=>............................] - ETA: 2:24 - loss: 0.7795 - regression_loss: 0.6750 - classification_loss: 0.1045 49/500 [=>............................] - ETA: 2:24 - loss: 0.7789 - regression_loss: 0.6749 - classification_loss: 0.1040 50/500 [==>...........................] - ETA: 2:23 - loss: 0.7724 - regression_loss: 0.6693 - classification_loss: 0.1031 51/500 [==>...........................] - ETA: 2:23 - loss: 0.7827 - regression_loss: 0.6784 - classification_loss: 0.1043 52/500 [==>...........................] - ETA: 2:23 - loss: 0.7739 - regression_loss: 0.6704 - classification_loss: 0.1035 53/500 [==>...........................] - ETA: 2:22 - loss: 0.7657 - regression_loss: 0.6631 - classification_loss: 0.1026 54/500 [==>...........................] - ETA: 2:22 - loss: 0.7575 - regression_loss: 0.6560 - classification_loss: 0.1014 55/500 [==>...........................] - ETA: 2:22 - loss: 0.7650 - regression_loss: 0.6629 - classification_loss: 0.1021 56/500 [==>...........................] - ETA: 2:21 - loss: 0.7562 - regression_loss: 0.6552 - classification_loss: 0.1010 57/500 [==>...........................] - ETA: 2:21 - loss: 0.7507 - regression_loss: 0.6509 - classification_loss: 0.0998 58/500 [==>...........................] - ETA: 2:21 - loss: 0.7594 - regression_loss: 0.6589 - classification_loss: 0.1005 59/500 [==>...........................] - ETA: 2:21 - loss: 0.7573 - regression_loss: 0.6578 - classification_loss: 0.0994 60/500 [==>...........................] - ETA: 2:20 - loss: 0.7580 - regression_loss: 0.6592 - classification_loss: 0.0988 61/500 [==>...........................] - ETA: 2:20 - loss: 0.7699 - regression_loss: 0.6677 - classification_loss: 0.1022 62/500 [==>...........................] - ETA: 2:19 - loss: 0.7835 - regression_loss: 0.6793 - classification_loss: 0.1043 63/500 [==>...........................] - ETA: 2:19 - loss: 0.7795 - regression_loss: 0.6758 - classification_loss: 0.1037 64/500 [==>...........................] - ETA: 2:19 - loss: 0.7808 - regression_loss: 0.6769 - classification_loss: 0.1039 65/500 [==>...........................] - ETA: 2:18 - loss: 0.7788 - regression_loss: 0.6753 - classification_loss: 0.1035 66/500 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[=====>........................] - ETA: 2:05 - loss: 0.7724 - regression_loss: 0.6718 - classification_loss: 0.1006 107/500 [=====>........................] - ETA: 2:05 - loss: 0.7700 - regression_loss: 0.6699 - classification_loss: 0.1002 108/500 [=====>........................] - ETA: 2:04 - loss: 0.7688 - regression_loss: 0.6690 - classification_loss: 0.0997 109/500 [=====>........................] - ETA: 2:04 - loss: 0.7695 - regression_loss: 0.6698 - classification_loss: 0.0997 110/500 [=====>........................] - ETA: 2:04 - loss: 0.7756 - regression_loss: 0.6751 - classification_loss: 0.1005 111/500 [=====>........................] - ETA: 2:04 - loss: 0.7780 - regression_loss: 0.6778 - classification_loss: 0.1003 112/500 [=====>........................] - ETA: 2:03 - loss: 0.7830 - regression_loss: 0.6819 - classification_loss: 0.1011 113/500 [=====>........................] - ETA: 2:03 - loss: 0.7898 - regression_loss: 0.6877 - classification_loss: 0.1020 114/500 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[=======>......................] - ETA: 1:55 - loss: 0.8045 - regression_loss: 0.7027 - classification_loss: 0.1018 139/500 [=======>......................] - ETA: 1:55 - loss: 0.8060 - regression_loss: 0.7042 - classification_loss: 0.1019 140/500 [=======>......................] - ETA: 1:54 - loss: 0.8078 - regression_loss: 0.7059 - classification_loss: 0.1019 141/500 [=======>......................] - ETA: 1:54 - loss: 0.8077 - regression_loss: 0.7061 - classification_loss: 0.1016 142/500 [=======>......................] - ETA: 1:54 - loss: 0.8136 - regression_loss: 0.7112 - classification_loss: 0.1024 143/500 [=======>......................] - ETA: 1:53 - loss: 0.8138 - regression_loss: 0.7117 - classification_loss: 0.1020 144/500 [=======>......................] - ETA: 1:53 - loss: 0.8133 - regression_loss: 0.7117 - classification_loss: 0.1016 145/500 [=======>......................] - ETA: 1:53 - loss: 0.8115 - regression_loss: 0.7103 - classification_loss: 0.1013 146/500 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[==========>...................] - ETA: 1:40 - loss: 0.8235 - regression_loss: 0.7199 - classification_loss: 0.1036 187/500 [==========>...................] - ETA: 1:39 - loss: 0.8228 - regression_loss: 0.7193 - classification_loss: 0.1035 188/500 [==========>...................] - ETA: 1:39 - loss: 0.8263 - regression_loss: 0.7220 - classification_loss: 0.1043 189/500 [==========>...................] - ETA: 1:39 - loss: 0.8234 - regression_loss: 0.7192 - classification_loss: 0.1042 190/500 [==========>...................] - ETA: 1:38 - loss: 0.8228 - regression_loss: 0.7186 - classification_loss: 0.1042 191/500 [==========>...................] - ETA: 1:38 - loss: 0.8233 - regression_loss: 0.7192 - classification_loss: 0.1041 192/500 [==========>...................] - ETA: 1:38 - loss: 0.8272 - regression_loss: 0.7226 - classification_loss: 0.1046 193/500 [==========>...................] - ETA: 1:37 - loss: 0.8280 - regression_loss: 0.7237 - classification_loss: 0.1043 194/500 [==========>...................] - ETA: 1:37 - loss: 0.8294 - regression_loss: 0.7246 - classification_loss: 0.1048 195/500 [==========>...................] - ETA: 1:37 - loss: 0.8288 - regression_loss: 0.7242 - classification_loss: 0.1046 196/500 [==========>...................] - ETA: 1:36 - loss: 0.8272 - regression_loss: 0.7226 - classification_loss: 0.1045 197/500 [==========>...................] - ETA: 1:36 - loss: 0.8268 - regression_loss: 0.7222 - classification_loss: 0.1046 198/500 [==========>...................] - ETA: 1:36 - loss: 0.8283 - regression_loss: 0.7236 - classification_loss: 0.1047 199/500 [==========>...................] - ETA: 1:35 - loss: 0.8262 - regression_loss: 0.7217 - classification_loss: 0.1045 200/500 [===========>..................] - ETA: 1:35 - loss: 0.8252 - regression_loss: 0.7208 - classification_loss: 0.1043 201/500 [===========>..................] - ETA: 1:35 - loss: 0.8226 - regression_loss: 0.7186 - classification_loss: 0.1041 202/500 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[============================>.] - ETA: 3s - loss: 0.8194 - regression_loss: 0.7139 - classification_loss: 0.1055 491/500 [============================>.] - ETA: 2s - loss: 0.8196 - regression_loss: 0.7140 - classification_loss: 0.1056 492/500 [============================>.] - ETA: 2s - loss: 0.8190 - regression_loss: 0.7136 - classification_loss: 0.1054 493/500 [============================>.] - ETA: 2s - loss: 0.8199 - regression_loss: 0.7142 - classification_loss: 0.1057 494/500 [============================>.] - ETA: 1s - loss: 0.8198 - regression_loss: 0.7141 - classification_loss: 0.1057 495/500 [============================>.] - ETA: 1s - loss: 0.8191 - regression_loss: 0.7135 - classification_loss: 0.1056 496/500 [============================>.] - ETA: 1s - loss: 0.8178 - regression_loss: 0.7124 - classification_loss: 0.1054 497/500 [============================>.] - ETA: 0s - loss: 0.8176 - regression_loss: 0.7122 - classification_loss: 0.1054 498/500 [============================>.] - ETA: 0s - loss: 0.8170 - regression_loss: 0.7117 - classification_loss: 0.1053 499/500 [============================>.] - ETA: 0s - loss: 0.8164 - regression_loss: 0.7112 - classification_loss: 0.1052 500/500 [==============================] - 160s 321ms/step - loss: 0.8158 - regression_loss: 0.7107 - classification_loss: 0.1051 326 instances of class plum with average precision: 0.7854 mAP: 0.7854 Epoch 00023: saving model to ./training/snapshots/resnet101_pascal_23.h5 Epoch 24/150 1/500 [..............................] - ETA: 2:52 - loss: 1.3080 - regression_loss: 1.0803 - classification_loss: 0.2277 2/500 [..............................] - ETA: 2:50 - loss: 1.0044 - regression_loss: 0.8454 - classification_loss: 0.1590 3/500 [..............................] - ETA: 2:47 - loss: 0.9556 - regression_loss: 0.8254 - classification_loss: 0.1302 4/500 [..............................] - ETA: 2:46 - loss: 1.0388 - regression_loss: 0.9023 - classification_loss: 0.1364 5/500 [..............................] - ETA: 2:45 - loss: 0.9963 - regression_loss: 0.8741 - classification_loss: 0.1222 6/500 [..............................] - ETA: 2:44 - loss: 1.0122 - regression_loss: 0.8928 - classification_loss: 0.1194 7/500 [..............................] - ETA: 2:43 - loss: 0.9274 - regression_loss: 0.8186 - classification_loss: 0.1088 8/500 [..............................] - ETA: 2:42 - loss: 0.9299 - regression_loss: 0.8178 - classification_loss: 0.1121 9/500 [..............................] - ETA: 2:41 - loss: 0.9550 - regression_loss: 0.8355 - classification_loss: 0.1195 10/500 [..............................] - ETA: 2:40 - loss: 0.9301 - regression_loss: 0.8159 - classification_loss: 0.1142 11/500 [..............................] - ETA: 2:40 - loss: 0.9085 - regression_loss: 0.7967 - classification_loss: 0.1118 12/500 [..............................] - ETA: 2:39 - loss: 0.9492 - regression_loss: 0.8335 - classification_loss: 0.1157 13/500 [..............................] - ETA: 2:39 - loss: 0.9379 - regression_loss: 0.8256 - classification_loss: 0.1123 14/500 [..............................] - ETA: 2:38 - loss: 0.9689 - regression_loss: 0.8526 - classification_loss: 0.1164 15/500 [..............................] - ETA: 2:38 - loss: 0.9380 - regression_loss: 0.8248 - classification_loss: 0.1133 16/500 [..............................] - ETA: 2:38 - loss: 0.9215 - regression_loss: 0.8113 - classification_loss: 0.1102 17/500 [>.............................] - ETA: 2:37 - loss: 0.9208 - regression_loss: 0.8104 - classification_loss: 0.1104 18/500 [>.............................] - ETA: 2:36 - loss: 0.8997 - regression_loss: 0.7912 - classification_loss: 0.1085 19/500 [>.............................] - ETA: 2:36 - loss: 0.8928 - regression_loss: 0.7847 - classification_loss: 0.1082 20/500 [>.............................] - ETA: 2:36 - loss: 0.8795 - regression_loss: 0.7738 - classification_loss: 0.1057 21/500 [>.............................] - ETA: 2:35 - loss: 0.8603 - regression_loss: 0.7562 - classification_loss: 0.1041 22/500 [>.............................] - ETA: 2:35 - loss: 0.8426 - regression_loss: 0.7417 - classification_loss: 0.1010 23/500 [>.............................] - ETA: 2:34 - loss: 0.8317 - regression_loss: 0.7322 - classification_loss: 0.0995 24/500 [>.............................] - ETA: 2:34 - loss: 0.8452 - regression_loss: 0.7441 - classification_loss: 0.1010 25/500 [>.............................] - ETA: 2:34 - loss: 0.8282 - regression_loss: 0.7293 - classification_loss: 0.0988 26/500 [>.............................] - ETA: 2:33 - loss: 0.8422 - regression_loss: 0.7407 - classification_loss: 0.1015 27/500 [>.............................] - ETA: 2:33 - loss: 0.8407 - regression_loss: 0.7402 - classification_loss: 0.1005 28/500 [>.............................] - ETA: 2:32 - loss: 0.8500 - regression_loss: 0.7492 - classification_loss: 0.1008 29/500 [>.............................] - ETA: 2:31 - loss: 0.8480 - regression_loss: 0.7482 - classification_loss: 0.0998 30/500 [>.............................] - ETA: 2:31 - loss: 0.8327 - regression_loss: 0.7344 - classification_loss: 0.0984 31/500 [>.............................] - ETA: 2:31 - loss: 0.8511 - regression_loss: 0.7470 - classification_loss: 0.1041 32/500 [>.............................] - ETA: 2:31 - loss: 0.8681 - regression_loss: 0.7626 - classification_loss: 0.1054 33/500 [>.............................] - ETA: 2:31 - loss: 0.8623 - regression_loss: 0.7579 - classification_loss: 0.1044 34/500 [=>............................] - ETA: 2:30 - loss: 0.8761 - regression_loss: 0.7703 - classification_loss: 0.1058 35/500 [=>............................] - ETA: 2:30 - loss: 0.8683 - regression_loss: 0.7636 - classification_loss: 0.1047 36/500 [=>............................] - ETA: 2:29 - loss: 0.8686 - regression_loss: 0.7653 - classification_loss: 0.1033 37/500 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[=>............................] - ETA: 2:26 - loss: 0.8078 - regression_loss: 0.7129 - classification_loss: 0.0949 46/500 [=>............................] - ETA: 2:26 - loss: 0.8000 - regression_loss: 0.7055 - classification_loss: 0.0945 47/500 [=>............................] - ETA: 2:26 - loss: 0.8042 - regression_loss: 0.7088 - classification_loss: 0.0954 48/500 [=>............................] - ETA: 2:25 - loss: 0.8126 - regression_loss: 0.7157 - classification_loss: 0.0969 49/500 [=>............................] - ETA: 2:25 - loss: 0.8216 - regression_loss: 0.7252 - classification_loss: 0.0964 50/500 [==>...........................] - ETA: 2:25 - loss: 0.8214 - regression_loss: 0.7257 - classification_loss: 0.0957 51/500 [==>...........................] - ETA: 2:24 - loss: 0.8309 - regression_loss: 0.7334 - classification_loss: 0.0975 52/500 [==>...........................] - ETA: 2:24 - loss: 0.8335 - regression_loss: 0.7359 - classification_loss: 0.0976 53/500 [==>...........................] - ETA: 2:23 - loss: 0.8372 - regression_loss: 0.7379 - classification_loss: 0.0993 54/500 [==>...........................] - ETA: 2:23 - loss: 0.8375 - regression_loss: 0.7385 - classification_loss: 0.0990 55/500 [==>...........................] - ETA: 2:23 - loss: 0.8293 - regression_loss: 0.7311 - classification_loss: 0.0983 56/500 [==>...........................] - ETA: 2:23 - loss: 0.8275 - regression_loss: 0.7290 - classification_loss: 0.0985 57/500 [==>...........................] - ETA: 2:22 - loss: 0.8319 - regression_loss: 0.7326 - classification_loss: 0.0993 58/500 [==>...........................] - ETA: 2:22 - loss: 0.8306 - regression_loss: 0.7320 - classification_loss: 0.0985 59/500 [==>...........................] - ETA: 2:22 - loss: 0.8234 - regression_loss: 0.7257 - classification_loss: 0.0977 60/500 [==>...........................] - ETA: 2:21 - loss: 0.8152 - regression_loss: 0.7186 - classification_loss: 0.0966 61/500 [==>...........................] - ETA: 2:21 - loss: 0.8132 - regression_loss: 0.7172 - classification_loss: 0.0960 62/500 [==>...........................] - ETA: 2:21 - loss: 0.8113 - regression_loss: 0.7154 - classification_loss: 0.0960 63/500 [==>...........................] - ETA: 2:20 - loss: 0.8036 - regression_loss: 0.7085 - classification_loss: 0.0951 64/500 [==>...........................] - ETA: 2:20 - loss: 0.7996 - regression_loss: 0.7051 - classification_loss: 0.0945 65/500 [==>...........................] - ETA: 2:20 - loss: 0.7924 - regression_loss: 0.6988 - classification_loss: 0.0936 66/500 [==>...........................] - ETA: 2:19 - loss: 0.8081 - regression_loss: 0.7105 - classification_loss: 0.0976 67/500 [===>..........................] - ETA: 2:19 - loss: 0.8115 - regression_loss: 0.7135 - classification_loss: 0.0980 68/500 [===>..........................] - ETA: 2:19 - loss: 0.8290 - regression_loss: 0.7260 - classification_loss: 0.1031 69/500 [===>..........................] - ETA: 2:19 - loss: 0.8300 - regression_loss: 0.7267 - classification_loss: 0.1034 70/500 [===>..........................] - ETA: 2:18 - loss: 0.8287 - regression_loss: 0.7257 - classification_loss: 0.1030 71/500 [===>..........................] - ETA: 2:18 - loss: 0.8283 - regression_loss: 0.7257 - classification_loss: 0.1027 72/500 [===>..........................] - ETA: 2:18 - loss: 0.8261 - regression_loss: 0.7238 - classification_loss: 0.1023 73/500 [===>..........................] - ETA: 2:17 - loss: 0.8260 - regression_loss: 0.7236 - classification_loss: 0.1023 74/500 [===>..........................] - ETA: 2:17 - loss: 0.8263 - regression_loss: 0.7233 - classification_loss: 0.1030 75/500 [===>..........................] - ETA: 2:17 - loss: 0.8243 - regression_loss: 0.7220 - classification_loss: 0.1024 76/500 [===>..........................] - ETA: 2:16 - loss: 0.8197 - regression_loss: 0.7181 - classification_loss: 0.1016 77/500 [===>..........................] - ETA: 2:16 - loss: 0.8215 - regression_loss: 0.7196 - classification_loss: 0.1019 78/500 [===>..........................] - ETA: 2:16 - loss: 0.8242 - regression_loss: 0.7209 - classification_loss: 0.1032 79/500 [===>..........................] - ETA: 2:15 - loss: 0.8255 - regression_loss: 0.7224 - classification_loss: 0.1031 80/500 [===>..........................] - ETA: 2:15 - loss: 0.8219 - regression_loss: 0.7193 - classification_loss: 0.1026 81/500 [===>..........................] - ETA: 2:15 - loss: 0.8326 - regression_loss: 0.7280 - classification_loss: 0.1047 82/500 [===>..........................] - ETA: 2:14 - loss: 0.8268 - regression_loss: 0.7231 - classification_loss: 0.1038 83/500 [===>..........................] - ETA: 2:14 - loss: 0.8345 - regression_loss: 0.7274 - classification_loss: 0.1071 84/500 [====>.........................] - ETA: 2:14 - loss: 0.8328 - regression_loss: 0.7263 - classification_loss: 0.1065 85/500 [====>.........................] - ETA: 2:13 - loss: 0.8364 - regression_loss: 0.7297 - classification_loss: 0.1067 86/500 [====>.........................] - ETA: 2:13 - loss: 0.8367 - regression_loss: 0.7302 - classification_loss: 0.1065 87/500 [====>.........................] - ETA: 2:13 - loss: 0.8393 - regression_loss: 0.7331 - classification_loss: 0.1062 88/500 [====>.........................] - ETA: 2:12 - loss: 0.8421 - regression_loss: 0.7355 - classification_loss: 0.1066 89/500 [====>.........................] - ETA: 2:12 - loss: 0.8466 - regression_loss: 0.7393 - classification_loss: 0.1072 90/500 [====>.........................] - ETA: 2:12 - loss: 0.8417 - regression_loss: 0.7350 - classification_loss: 0.1067 91/500 [====>.........................] - ETA: 2:11 - loss: 0.8423 - regression_loss: 0.7356 - classification_loss: 0.1066 92/500 [====>.........................] - ETA: 2:11 - loss: 0.8395 - regression_loss: 0.7331 - classification_loss: 0.1064 93/500 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[=====>........................] - ETA: 2:08 - loss: 0.8381 - regression_loss: 0.7311 - classification_loss: 0.1070 102/500 [=====>........................] - ETA: 2:08 - loss: 0.8343 - regression_loss: 0.7278 - classification_loss: 0.1066 103/500 [=====>........................] - ETA: 2:07 - loss: 0.8407 - regression_loss: 0.7332 - classification_loss: 0.1075 104/500 [=====>........................] - ETA: 2:07 - loss: 0.8389 - regression_loss: 0.7319 - classification_loss: 0.1070 105/500 [=====>........................] - ETA: 2:07 - loss: 0.8329 - regression_loss: 0.7267 - classification_loss: 0.1063 106/500 [=====>........................] - ETA: 2:06 - loss: 0.8328 - regression_loss: 0.7269 - classification_loss: 0.1059 107/500 [=====>........................] - ETA: 2:06 - loss: 0.8350 - regression_loss: 0.7291 - classification_loss: 0.1059 108/500 [=====>........................] - ETA: 2:06 - loss: 0.8325 - regression_loss: 0.7268 - classification_loss: 0.1057 109/500 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[============================>.] - ETA: 2s - loss: 0.7930 - regression_loss: 0.6920 - classification_loss: 0.1010 494/500 [============================>.] - ETA: 1s - loss: 0.7937 - regression_loss: 0.6926 - classification_loss: 0.1012 495/500 [============================>.] - ETA: 1s - loss: 0.7933 - regression_loss: 0.6922 - classification_loss: 0.1011 496/500 [============================>.] - ETA: 1s - loss: 0.7947 - regression_loss: 0.6936 - classification_loss: 0.1011 497/500 [============================>.] - ETA: 0s - loss: 0.7949 - regression_loss: 0.6938 - classification_loss: 0.1011 498/500 [============================>.] - ETA: 0s - loss: 0.7946 - regression_loss: 0.6935 - classification_loss: 0.1011 499/500 [============================>.] - ETA: 0s - loss: 0.7950 - regression_loss: 0.6939 - classification_loss: 0.1011 500/500 [==============================] - 161s 323ms/step - loss: 0.7952 - regression_loss: 0.6941 - classification_loss: 0.1011 326 instances of class plum with average precision: 0.7846 mAP: 0.7846 Epoch 00024: saving model to ./training/snapshots/resnet101_pascal_24.h5 Epoch 25/150 1/500 [..............................] - ETA: 2:36 - loss: 1.3416 - regression_loss: 1.1440 - classification_loss: 0.1976 2/500 [..............................] - ETA: 2:35 - loss: 1.2279 - regression_loss: 1.0361 - classification_loss: 0.1918 3/500 [..............................] - ETA: 2:35 - loss: 1.0400 - regression_loss: 0.8890 - classification_loss: 0.1511 4/500 [..............................] - ETA: 2:40 - loss: 1.1334 - regression_loss: 0.9393 - classification_loss: 0.1941 5/500 [..............................] - ETA: 2:39 - loss: 1.0289 - regression_loss: 0.8567 - classification_loss: 0.1722 6/500 [..............................] - ETA: 2:39 - loss: 0.9304 - regression_loss: 0.7777 - classification_loss: 0.1527 7/500 [..............................] - ETA: 2:39 - loss: 0.9597 - regression_loss: 0.8010 - classification_loss: 0.1587 8/500 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[=====>........................] - ETA: 2:05 - loss: 0.8241 - regression_loss: 0.7187 - classification_loss: 0.1053 113/500 [=====>........................] - ETA: 2:05 - loss: 0.8231 - regression_loss: 0.7180 - classification_loss: 0.1051 114/500 [=====>........................] - ETA: 2:04 - loss: 0.8228 - regression_loss: 0.7177 - classification_loss: 0.1051 115/500 [=====>........................] - ETA: 2:04 - loss: 0.8256 - regression_loss: 0.7202 - classification_loss: 0.1054 116/500 [=====>........................] - ETA: 2:04 - loss: 0.8270 - regression_loss: 0.7216 - classification_loss: 0.1054 117/500 [======>.......................] - ETA: 2:03 - loss: 0.8227 - regression_loss: 0.7177 - classification_loss: 0.1049 118/500 [======>.......................] - ETA: 2:03 - loss: 0.8191 - regression_loss: 0.7146 - classification_loss: 0.1045 119/500 [======>.......................] - ETA: 2:03 - loss: 0.8181 - regression_loss: 0.7137 - classification_loss: 0.1044 120/500 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[============================>.] - ETA: 3s - loss: 0.7681 - regression_loss: 0.6713 - classification_loss: 0.0969 489/500 [============================>.] - ETA: 3s - loss: 0.7678 - regression_loss: 0.6710 - classification_loss: 0.0968 490/500 [============================>.] - ETA: 3s - loss: 0.7685 - regression_loss: 0.6716 - classification_loss: 0.0969 491/500 [============================>.] - ETA: 2s - loss: 0.7684 - regression_loss: 0.6715 - classification_loss: 0.0969 492/500 [============================>.] - ETA: 2s - loss: 0.7693 - regression_loss: 0.6723 - classification_loss: 0.0970 493/500 [============================>.] - ETA: 2s - loss: 0.7690 - regression_loss: 0.6721 - classification_loss: 0.0969 494/500 [============================>.] - ETA: 1s - loss: 0.7685 - regression_loss: 0.6717 - classification_loss: 0.0968 495/500 [============================>.] - ETA: 1s - loss: 0.7690 - regression_loss: 0.6722 - classification_loss: 0.0968 496/500 [============================>.] - ETA: 1s - loss: 0.7692 - regression_loss: 0.6724 - classification_loss: 0.0968 497/500 [============================>.] - ETA: 0s - loss: 0.7693 - regression_loss: 0.6726 - classification_loss: 0.0968 498/500 [============================>.] - ETA: 0s - loss: 0.7696 - regression_loss: 0.6728 - classification_loss: 0.0967 499/500 [============================>.] - ETA: 0s - loss: 0.7692 - regression_loss: 0.6725 - classification_loss: 0.0967 500/500 [==============================] - 162s 324ms/step - loss: 0.7699 - regression_loss: 0.6729 - classification_loss: 0.0971 326 instances of class plum with average precision: 0.8105 mAP: 0.8105 Epoch 00025: saving model to ./training/snapshots/resnet101_pascal_25.h5 Epoch 26/150 1/500 [..............................] - ETA: 2:38 - loss: 1.1138 - regression_loss: 1.0678 - classification_loss: 0.0460 2/500 [..............................] - ETA: 2:40 - loss: 1.0008 - regression_loss: 0.9437 - classification_loss: 0.0570 3/500 [..............................] - ETA: 2:37 - loss: 0.9918 - regression_loss: 0.9208 - classification_loss: 0.0710 4/500 [..............................] - ETA: 2:37 - loss: 0.9075 - regression_loss: 0.8438 - classification_loss: 0.0637 5/500 [..............................] - ETA: 2:39 - loss: 0.8048 - regression_loss: 0.7447 - classification_loss: 0.0601 6/500 [..............................] - ETA: 2:42 - loss: 0.8442 - regression_loss: 0.7831 - classification_loss: 0.0611 7/500 [..............................] - ETA: 2:42 - loss: 0.7770 - regression_loss: 0.7167 - classification_loss: 0.0603 8/500 [..............................] - ETA: 2:41 - loss: 0.8577 - regression_loss: 0.7775 - classification_loss: 0.0803 9/500 [..............................] - ETA: 2:40 - loss: 0.8631 - regression_loss: 0.7826 - classification_loss: 0.0805 10/500 [..............................] - ETA: 2:39 - loss: 0.8530 - regression_loss: 0.7723 - classification_loss: 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[>.............................] - ETA: 2:37 - loss: 0.9336 - regression_loss: 0.8289 - classification_loss: 0.1048 20/500 [>.............................] - ETA: 2:37 - loss: 0.9101 - regression_loss: 0.8076 - classification_loss: 0.1025 21/500 [>.............................] - ETA: 2:36 - loss: 0.9097 - regression_loss: 0.8072 - classification_loss: 0.1025 22/500 [>.............................] - ETA: 2:36 - loss: 0.9331 - regression_loss: 0.8297 - classification_loss: 0.1034 23/500 [>.............................] - ETA: 2:36 - loss: 0.9587 - regression_loss: 0.8520 - classification_loss: 0.1067 24/500 [>.............................] - ETA: 2:35 - loss: 0.9678 - regression_loss: 0.8613 - classification_loss: 0.1065 25/500 [>.............................] - ETA: 2:34 - loss: 0.9636 - regression_loss: 0.8557 - classification_loss: 0.1078 26/500 [>.............................] - ETA: 2:34 - loss: 0.9415 - regression_loss: 0.8359 - classification_loss: 0.1056 27/500 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[=>............................] - ETA: 2:30 - loss: 0.8908 - regression_loss: 0.7841 - classification_loss: 0.1067 36/500 [=>............................] - ETA: 2:31 - loss: 0.8906 - regression_loss: 0.7840 - classification_loss: 0.1066 37/500 [=>............................] - ETA: 2:30 - loss: 0.8870 - regression_loss: 0.7794 - classification_loss: 0.1076 38/500 [=>............................] - ETA: 2:30 - loss: 0.8809 - regression_loss: 0.7746 - classification_loss: 0.1063 39/500 [=>............................] - ETA: 2:29 - loss: 0.8677 - regression_loss: 0.7631 - classification_loss: 0.1046 40/500 [=>............................] - ETA: 2:29 - loss: 0.8583 - regression_loss: 0.7548 - classification_loss: 0.1035 41/500 [=>............................] - ETA: 2:29 - loss: 0.8519 - regression_loss: 0.7479 - classification_loss: 0.1040 42/500 [=>............................] - ETA: 2:29 - loss: 0.8470 - regression_loss: 0.7439 - classification_loss: 0.1031 43/500 [=>............................] - ETA: 2:29 - loss: 0.8434 - regression_loss: 0.7408 - classification_loss: 0.1025 44/500 [=>............................] - ETA: 2:28 - loss: 0.8334 - regression_loss: 0.7320 - classification_loss: 0.1014 45/500 [=>............................] - ETA: 2:28 - loss: 0.8334 - regression_loss: 0.7326 - classification_loss: 0.1008 46/500 [=>............................] - ETA: 2:28 - loss: 0.8254 - regression_loss: 0.7256 - classification_loss: 0.0998 47/500 [=>............................] - ETA: 2:28 - loss: 0.8236 - regression_loss: 0.7244 - classification_loss: 0.0992 48/500 [=>............................] - ETA: 2:27 - loss: 0.8156 - regression_loss: 0.7178 - classification_loss: 0.0979 49/500 [=>............................] - ETA: 2:27 - loss: 0.8134 - regression_loss: 0.7162 - classification_loss: 0.0972 50/500 [==>...........................] - ETA: 2:27 - loss: 0.8106 - regression_loss: 0.7136 - classification_loss: 0.0969 51/500 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[==>...........................] - ETA: 2:24 - loss: 0.8122 - regression_loss: 0.7115 - classification_loss: 0.1007 60/500 [==>...........................] - ETA: 2:23 - loss: 0.8172 - regression_loss: 0.7154 - classification_loss: 0.1018 61/500 [==>...........................] - ETA: 2:23 - loss: 0.8130 - regression_loss: 0.7120 - classification_loss: 0.1010 62/500 [==>...........................] - ETA: 2:23 - loss: 0.8158 - regression_loss: 0.7148 - classification_loss: 0.1010 63/500 [==>...........................] - ETA: 2:22 - loss: 0.8107 - regression_loss: 0.7106 - classification_loss: 0.1002 64/500 [==>...........................] - ETA: 2:22 - loss: 0.8056 - regression_loss: 0.7063 - classification_loss: 0.0993 65/500 [==>...........................] - ETA: 2:21 - loss: 0.7970 - regression_loss: 0.6988 - classification_loss: 0.0982 66/500 [==>...........................] - ETA: 2:21 - loss: 0.7928 - regression_loss: 0.6950 - classification_loss: 0.0978 67/500 [===>..........................] - ETA: 2:21 - loss: 0.7945 - regression_loss: 0.6960 - classification_loss: 0.0985 68/500 [===>..........................] - ETA: 2:20 - loss: 0.7952 - regression_loss: 0.6968 - classification_loss: 0.0985 69/500 [===>..........................] - ETA: 2:20 - loss: 0.7968 - regression_loss: 0.6978 - classification_loss: 0.0990 70/500 [===>..........................] - ETA: 2:19 - loss: 0.8020 - regression_loss: 0.7021 - classification_loss: 0.0999 71/500 [===>..........................] - ETA: 2:19 - loss: 0.7978 - regression_loss: 0.6986 - classification_loss: 0.0992 72/500 [===>..........................] - ETA: 2:19 - loss: 0.7908 - regression_loss: 0.6922 - classification_loss: 0.0985 73/500 [===>..........................] - ETA: 2:18 - loss: 0.7930 - regression_loss: 0.6944 - classification_loss: 0.0986 74/500 [===>..........................] - ETA: 2:18 - loss: 0.7890 - regression_loss: 0.6908 - classification_loss: 0.0982 75/500 [===>..........................] - ETA: 2:18 - loss: 0.7928 - regression_loss: 0.6936 - classification_loss: 0.0991 76/500 [===>..........................] - ETA: 2:17 - loss: 0.7945 - regression_loss: 0.6954 - classification_loss: 0.0991 77/500 [===>..........................] - ETA: 2:17 - loss: 0.8049 - regression_loss: 0.7040 - classification_loss: 0.1009 78/500 [===>..........................] - ETA: 2:17 - loss: 0.8128 - regression_loss: 0.7095 - classification_loss: 0.1033 79/500 [===>..........................] - ETA: 2:16 - loss: 0.8155 - regression_loss: 0.7113 - classification_loss: 0.1042 80/500 [===>..........................] - ETA: 2:16 - loss: 0.8137 - regression_loss: 0.7103 - classification_loss: 0.1034 81/500 [===>..........................] - ETA: 2:16 - loss: 0.8171 - regression_loss: 0.7134 - classification_loss: 0.1037 82/500 [===>..........................] - ETA: 2:15 - loss: 0.8102 - regression_loss: 0.7075 - classification_loss: 0.1027 83/500 [===>..........................] - ETA: 2:15 - loss: 0.8119 - regression_loss: 0.7090 - classification_loss: 0.1029 84/500 [====>.........................] - ETA: 2:14 - loss: 0.8076 - regression_loss: 0.7054 - classification_loss: 0.1021 85/500 [====>.........................] - ETA: 2:14 - loss: 0.8105 - regression_loss: 0.7083 - classification_loss: 0.1023 86/500 [====>.........................] - ETA: 2:14 - loss: 0.8143 - regression_loss: 0.7115 - classification_loss: 0.1028 87/500 [====>.........................] - ETA: 2:14 - loss: 0.8119 - regression_loss: 0.7098 - classification_loss: 0.1021 88/500 [====>.........................] - ETA: 2:13 - loss: 0.8086 - regression_loss: 0.7069 - classification_loss: 0.1017 89/500 [====>.........................] - ETA: 2:13 - loss: 0.8022 - regression_loss: 0.7014 - classification_loss: 0.1008 90/500 [====>.........................] - ETA: 2:12 - loss: 0.7996 - regression_loss: 0.6992 - classification_loss: 0.1004 91/500 [====>.........................] - ETA: 2:12 - loss: 0.8013 - regression_loss: 0.7009 - classification_loss: 0.1005 92/500 [====>.........................] - ETA: 2:12 - loss: 0.8045 - regression_loss: 0.7033 - classification_loss: 0.1012 93/500 [====>.........................] - ETA: 2:11 - loss: 0.8003 - regression_loss: 0.6996 - classification_loss: 0.1007 94/500 [====>.........................] - ETA: 2:11 - loss: 0.8048 - regression_loss: 0.7033 - classification_loss: 0.1015 95/500 [====>.........................] - ETA: 2:11 - loss: 0.8018 - regression_loss: 0.7004 - classification_loss: 0.1014 96/500 [====>.........................] - ETA: 2:10 - loss: 0.7981 - regression_loss: 0.6973 - classification_loss: 0.1008 97/500 [====>.........................] - ETA: 2:10 - loss: 0.7980 - regression_loss: 0.6972 - classification_loss: 0.1008 98/500 [====>.........................] - ETA: 2:09 - loss: 0.7957 - regression_loss: 0.6953 - classification_loss: 0.1004 99/500 [====>.........................] - ETA: 2:09 - loss: 0.7936 - regression_loss: 0.6935 - classification_loss: 0.1000 100/500 [=====>........................] - ETA: 2:09 - loss: 0.7940 - regression_loss: 0.6941 - classification_loss: 0.0999 101/500 [=====>........................] - ETA: 2:09 - loss: 0.7970 - regression_loss: 0.6967 - classification_loss: 0.1004 102/500 [=====>........................] - ETA: 2:08 - loss: 0.7944 - regression_loss: 0.6944 - classification_loss: 0.1000 103/500 [=====>........................] - ETA: 2:08 - loss: 0.7994 - regression_loss: 0.6986 - classification_loss: 0.1009 104/500 [=====>........................] - ETA: 2:08 - loss: 0.7998 - regression_loss: 0.6990 - classification_loss: 0.1008 105/500 [=====>........................] - ETA: 2:07 - loss: 0.7957 - regression_loss: 0.6954 - classification_loss: 0.1003 106/500 [=====>........................] - ETA: 2:07 - loss: 0.7981 - regression_loss: 0.6971 - classification_loss: 0.1009 107/500 [=====>........................] - ETA: 2:07 - loss: 0.7968 - regression_loss: 0.6962 - classification_loss: 0.1006 108/500 [=====>........................] - ETA: 2:06 - loss: 0.7937 - regression_loss: 0.6937 - classification_loss: 0.0999 109/500 [=====>........................] - ETA: 2:06 - loss: 0.7922 - regression_loss: 0.6927 - classification_loss: 0.0995 110/500 [=====>........................] - ETA: 2:06 - loss: 0.7912 - regression_loss: 0.6921 - classification_loss: 0.0991 111/500 [=====>........................] - ETA: 2:05 - loss: 0.7873 - regression_loss: 0.6887 - classification_loss: 0.0987 112/500 [=====>........................] - ETA: 2:05 - loss: 0.7839 - regression_loss: 0.6858 - classification_loss: 0.0981 113/500 [=====>........................] - ETA: 2:05 - loss: 0.7888 - regression_loss: 0.6893 - classification_loss: 0.0995 114/500 [=====>........................] - ETA: 2:04 - loss: 0.7849 - regression_loss: 0.6860 - classification_loss: 0.0989 115/500 [=====>........................] - ETA: 2:04 - loss: 0.7809 - regression_loss: 0.6825 - classification_loss: 0.0984 116/500 [=====>........................] - ETA: 2:04 - loss: 0.7785 - regression_loss: 0.6805 - classification_loss: 0.0980 117/500 [======>.......................] - ETA: 2:03 - loss: 0.7785 - regression_loss: 0.6807 - classification_loss: 0.0978 118/500 [======>.......................] - ETA: 2:03 - loss: 0.7764 - regression_loss: 0.6791 - classification_loss: 0.0974 119/500 [======>.......................] - ETA: 2:03 - loss: 0.7740 - regression_loss: 0.6768 - classification_loss: 0.0971 120/500 [======>.......................] - ETA: 2:03 - loss: 0.7727 - regression_loss: 0.6757 - classification_loss: 0.0970 121/500 [======>.......................] - ETA: 2:02 - loss: 0.7696 - regression_loss: 0.6731 - classification_loss: 0.0965 122/500 [======>.......................] - ETA: 2:02 - loss: 0.7652 - regression_loss: 0.6693 - classification_loss: 0.0959 123/500 [======>.......................] - ETA: 2:02 - loss: 0.7659 - regression_loss: 0.6702 - classification_loss: 0.0958 124/500 [======>.......................] - ETA: 2:01 - loss: 0.7625 - regression_loss: 0.6672 - classification_loss: 0.0953 125/500 [======>.......................] - ETA: 2:01 - loss: 0.7619 - regression_loss: 0.6667 - classification_loss: 0.0952 126/500 [======>.......................] - ETA: 2:01 - loss: 0.7609 - regression_loss: 0.6661 - classification_loss: 0.0948 127/500 [======>.......................] - ETA: 2:00 - loss: 0.7618 - regression_loss: 0.6671 - classification_loss: 0.0947 128/500 [======>.......................] - ETA: 2:00 - loss: 0.7610 - regression_loss: 0.6665 - classification_loss: 0.0945 129/500 [======>.......................] - ETA: 2:00 - loss: 0.7594 - regression_loss: 0.6653 - classification_loss: 0.0941 130/500 [======>.......................] - ETA: 1:59 - loss: 0.7603 - regression_loss: 0.6665 - classification_loss: 0.0938 131/500 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[=======>......................] - ETA: 1:56 - loss: 0.7554 - regression_loss: 0.6630 - classification_loss: 0.0924 140/500 [=======>......................] - ETA: 1:56 - loss: 0.7539 - regression_loss: 0.6617 - classification_loss: 0.0921 141/500 [=======>......................] - ETA: 1:56 - loss: 0.7512 - regression_loss: 0.6595 - classification_loss: 0.0917 142/500 [=======>......................] - ETA: 1:55 - loss: 0.7483 - regression_loss: 0.6571 - classification_loss: 0.0912 143/500 [=======>......................] - ETA: 1:55 - loss: 0.7467 - regression_loss: 0.6558 - classification_loss: 0.0909 144/500 [=======>......................] - ETA: 1:55 - loss: 0.7468 - regression_loss: 0.6560 - classification_loss: 0.0908 145/500 [=======>......................] - ETA: 1:55 - loss: 0.7459 - regression_loss: 0.6552 - classification_loss: 0.0906 146/500 [=======>......................] - ETA: 1:54 - loss: 0.7465 - regression_loss: 0.6553 - classification_loss: 0.0912 147/500 [=======>......................] - ETA: 1:54 - loss: 0.7476 - regression_loss: 0.6564 - classification_loss: 0.0911 148/500 [=======>......................] - ETA: 1:54 - loss: 0.7465 - regression_loss: 0.6557 - classification_loss: 0.0908 149/500 [=======>......................] - ETA: 1:53 - loss: 0.7452 - regression_loss: 0.6547 - classification_loss: 0.0905 150/500 [========>.....................] - ETA: 1:53 - loss: 0.7454 - regression_loss: 0.6549 - classification_loss: 0.0905 151/500 [========>.....................] - ETA: 1:53 - loss: 0.7474 - regression_loss: 0.6567 - classification_loss: 0.0907 152/500 [========>.....................] - ETA: 1:52 - loss: 0.7478 - regression_loss: 0.6572 - classification_loss: 0.0907 153/500 [========>.....................] - ETA: 1:52 - loss: 0.7470 - regression_loss: 0.6565 - classification_loss: 0.0905 154/500 [========>.....................] - ETA: 1:52 - loss: 0.7465 - regression_loss: 0.6561 - classification_loss: 0.0904 155/500 [========>.....................] - ETA: 1:52 - loss: 0.7440 - regression_loss: 0.6536 - classification_loss: 0.0904 156/500 [========>.....................] - ETA: 1:51 - loss: 0.7430 - regression_loss: 0.6527 - classification_loss: 0.0902 157/500 [========>.....................] - ETA: 1:51 - loss: 0.7458 - regression_loss: 0.6551 - classification_loss: 0.0907 158/500 [========>.....................] - ETA: 1:51 - loss: 0.7456 - regression_loss: 0.6551 - classification_loss: 0.0905 159/500 [========>.....................] - ETA: 1:50 - loss: 0.7509 - regression_loss: 0.6598 - classification_loss: 0.0911 160/500 [========>.....................] - ETA: 1:50 - loss: 0.7475 - regression_loss: 0.6568 - classification_loss: 0.0907 161/500 [========>.....................] - ETA: 1:50 - loss: 0.7512 - regression_loss: 0.6597 - classification_loss: 0.0916 162/500 [========>.....................] - ETA: 1:49 - loss: 0.7551 - regression_loss: 0.6620 - classification_loss: 0.0930 163/500 [========>.....................] - ETA: 1:49 - loss: 0.7555 - regression_loss: 0.6624 - classification_loss: 0.0931 164/500 [========>.....................] - ETA: 1:49 - loss: 0.7530 - regression_loss: 0.6602 - classification_loss: 0.0928 165/500 [========>.....................] - ETA: 1:48 - loss: 0.7529 - regression_loss: 0.6602 - classification_loss: 0.0927 166/500 [========>.....................] - ETA: 1:48 - loss: 0.7508 - regression_loss: 0.6583 - classification_loss: 0.0925 167/500 [=========>....................] - ETA: 1:48 - loss: 0.7512 - regression_loss: 0.6584 - classification_loss: 0.0927 168/500 [=========>....................] - ETA: 1:47 - loss: 0.7528 - regression_loss: 0.6596 - classification_loss: 0.0932 169/500 [=========>....................] - ETA: 1:47 - loss: 0.7495 - regression_loss: 0.6567 - classification_loss: 0.0928 170/500 [=========>....................] - ETA: 1:47 - loss: 0.7521 - regression_loss: 0.6590 - classification_loss: 0.0931 171/500 [=========>....................] - ETA: 1:46 - loss: 0.7508 - regression_loss: 0.6579 - classification_loss: 0.0929 172/500 [=========>....................] - ETA: 1:46 - loss: 0.7491 - regression_loss: 0.6564 - classification_loss: 0.0927 173/500 [=========>....................] - ETA: 1:46 - loss: 0.7471 - regression_loss: 0.6547 - classification_loss: 0.0924 174/500 [=========>....................] - ETA: 1:45 - loss: 0.7469 - regression_loss: 0.6548 - classification_loss: 0.0921 175/500 [=========>....................] - ETA: 1:45 - loss: 0.7460 - regression_loss: 0.6541 - classification_loss: 0.0920 176/500 [=========>....................] - ETA: 1:45 - loss: 0.7451 - regression_loss: 0.6534 - classification_loss: 0.0917 177/500 [=========>....................] - ETA: 1:44 - loss: 0.7438 - regression_loss: 0.6524 - classification_loss: 0.0914 178/500 [=========>....................] - ETA: 1:44 - loss: 0.7418 - regression_loss: 0.6506 - classification_loss: 0.0911 179/500 [=========>....................] - ETA: 1:44 - loss: 0.7404 - regression_loss: 0.6494 - classification_loss: 0.0910 180/500 [=========>....................] - ETA: 1:43 - loss: 0.7393 - regression_loss: 0.6485 - classification_loss: 0.0908 181/500 [=========>....................] - ETA: 1:43 - loss: 0.7408 - regression_loss: 0.6501 - classification_loss: 0.0907 182/500 [=========>....................] - ETA: 1:43 - loss: 0.7394 - regression_loss: 0.6489 - classification_loss: 0.0905 183/500 [=========>....................] - ETA: 1:42 - loss: 0.7404 - regression_loss: 0.6494 - classification_loss: 0.0909 184/500 [==========>...................] - ETA: 1:42 - loss: 0.7381 - regression_loss: 0.6475 - classification_loss: 0.0906 185/500 [==========>...................] - ETA: 1:42 - loss: 0.7359 - regression_loss: 0.6456 - classification_loss: 0.0903 186/500 [==========>...................] - ETA: 1:41 - loss: 0.7356 - regression_loss: 0.6455 - classification_loss: 0.0901 187/500 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[===========================>..] - ETA: 5s - loss: 0.7447 - regression_loss: 0.6522 - classification_loss: 0.0925 484/500 [============================>.] - ETA: 5s - loss: 0.7454 - regression_loss: 0.6528 - classification_loss: 0.0926 485/500 [============================>.] - ETA: 4s - loss: 0.7452 - regression_loss: 0.6527 - classification_loss: 0.0926 486/500 [============================>.] - ETA: 4s - loss: 0.7449 - regression_loss: 0.6525 - classification_loss: 0.0925 487/500 [============================>.] - ETA: 4s - loss: 0.7442 - regression_loss: 0.6518 - classification_loss: 0.0924 488/500 [============================>.] - ETA: 3s - loss: 0.7450 - regression_loss: 0.6524 - classification_loss: 0.0925 489/500 [============================>.] - ETA: 3s - loss: 0.7445 - regression_loss: 0.6521 - classification_loss: 0.0924 490/500 [============================>.] - ETA: 3s - loss: 0.7441 - regression_loss: 0.6518 - classification_loss: 0.0923 491/500 [============================>.] - ETA: 2s - loss: 0.7444 - regression_loss: 0.6521 - classification_loss: 0.0923 492/500 [============================>.] - ETA: 2s - loss: 0.7447 - regression_loss: 0.6523 - classification_loss: 0.0924 493/500 [============================>.] - ETA: 2s - loss: 0.7439 - regression_loss: 0.6516 - classification_loss: 0.0923 494/500 [============================>.] - ETA: 1s - loss: 0.7435 - regression_loss: 0.6513 - classification_loss: 0.0922 495/500 [============================>.] - ETA: 1s - loss: 0.7434 - regression_loss: 0.6512 - classification_loss: 0.0922 496/500 [============================>.] - ETA: 1s - loss: 0.7442 - regression_loss: 0.6521 - classification_loss: 0.0920 497/500 [============================>.] - ETA: 0s - loss: 0.7443 - regression_loss: 0.6523 - classification_loss: 0.0920 498/500 [============================>.] - ETA: 0s - loss: 0.7439 - regression_loss: 0.6521 - classification_loss: 0.0919 499/500 [============================>.] - ETA: 0s - loss: 0.7450 - regression_loss: 0.6526 - classification_loss: 0.0923 500/500 [==============================] - 162s 323ms/step - loss: 0.7450 - regression_loss: 0.6526 - classification_loss: 0.0924 326 instances of class plum with average precision: 0.7798 mAP: 0.7798 Epoch 00026: saving model to ./training/snapshots/resnet101_pascal_26.h5 Epoch 27/150 1/500 [..............................] - ETA: 2:30 - loss: 0.4200 - regression_loss: 0.3889 - classification_loss: 0.0311 2/500 [..............................] - ETA: 2:34 - loss: 0.5265 - regression_loss: 0.4368 - classification_loss: 0.0897 3/500 [..............................] - ETA: 2:33 - loss: 0.6827 - regression_loss: 0.5859 - classification_loss: 0.0969 4/500 [..............................] - ETA: 2:33 - loss: 0.5740 - regression_loss: 0.4951 - classification_loss: 0.0788 5/500 [..............................] - ETA: 2:36 - loss: 0.5317 - regression_loss: 0.4632 - classification_loss: 0.0685 6/500 [..............................] - ETA: 2:37 - loss: 0.5030 - regression_loss: 0.4390 - classification_loss: 0.0641 7/500 [..............................] - ETA: 2:36 - loss: 0.5044 - regression_loss: 0.4453 - classification_loss: 0.0592 8/500 [..............................] - ETA: 2:36 - loss: 0.5373 - regression_loss: 0.4772 - classification_loss: 0.0601 9/500 [..............................] - ETA: 2:38 - loss: 0.6167 - regression_loss: 0.5350 - classification_loss: 0.0817 10/500 [..............................] - ETA: 2:39 - loss: 0.5945 - regression_loss: 0.5179 - classification_loss: 0.0766 11/500 [..............................] - ETA: 2:39 - loss: 0.5925 - regression_loss: 0.5165 - classification_loss: 0.0760 12/500 [..............................] - ETA: 2:38 - loss: 0.5904 - regression_loss: 0.5155 - classification_loss: 0.0749 13/500 [..............................] - ETA: 2:39 - loss: 0.5837 - regression_loss: 0.5085 - classification_loss: 0.0752 14/500 [..............................] - ETA: 2:39 - loss: 0.6241 - regression_loss: 0.5440 - classification_loss: 0.0802 15/500 [..............................] - ETA: 2:38 - loss: 0.6385 - regression_loss: 0.5586 - classification_loss: 0.0799 16/500 [..............................] - ETA: 2:37 - loss: 0.6518 - regression_loss: 0.5695 - classification_loss: 0.0823 17/500 [>.............................] - ETA: 2:36 - loss: 0.6540 - regression_loss: 0.5721 - classification_loss: 0.0818 18/500 [>.............................] - ETA: 2:36 - loss: 0.6656 - regression_loss: 0.5821 - classification_loss: 0.0835 19/500 [>.............................] - ETA: 2:36 - loss: 0.6892 - regression_loss: 0.6044 - classification_loss: 0.0848 20/500 [>.............................] - ETA: 2:35 - loss: 0.6868 - regression_loss: 0.6049 - classification_loss: 0.0819 21/500 [>.............................] - ETA: 2:35 - loss: 0.6765 - regression_loss: 0.5966 - classification_loss: 0.0799 22/500 [>.............................] - ETA: 2:34 - loss: 0.6615 - regression_loss: 0.5841 - classification_loss: 0.0775 23/500 [>.............................] - ETA: 2:34 - loss: 0.6883 - regression_loss: 0.6025 - classification_loss: 0.0858 24/500 [>.............................] - ETA: 2:34 - loss: 0.6788 - regression_loss: 0.5951 - classification_loss: 0.0837 25/500 [>.............................] - ETA: 2:33 - loss: 0.6878 - regression_loss: 0.6042 - classification_loss: 0.0836 26/500 [>.............................] - ETA: 2:33 - loss: 0.6822 - regression_loss: 0.6004 - classification_loss: 0.0817 27/500 [>.............................] - ETA: 2:32 - loss: 0.6747 - regression_loss: 0.5942 - classification_loss: 0.0805 28/500 [>.............................] - ETA: 2:32 - loss: 0.6785 - regression_loss: 0.5974 - classification_loss: 0.0812 29/500 [>.............................] - ETA: 2:32 - loss: 0.6885 - regression_loss: 0.6065 - classification_loss: 0.0820 30/500 [>.............................] - ETA: 2:32 - loss: 0.7105 - regression_loss: 0.6201 - classification_loss: 0.0904 31/500 [>.............................] - ETA: 2:31 - loss: 0.7000 - regression_loss: 0.6114 - classification_loss: 0.0886 32/500 [>.............................] - ETA: 2:31 - loss: 0.7041 - regression_loss: 0.6147 - classification_loss: 0.0893 33/500 [>.............................] - ETA: 2:30 - loss: 0.7105 - regression_loss: 0.6206 - classification_loss: 0.0899 34/500 [=>............................] - ETA: 2:30 - loss: 0.7059 - regression_loss: 0.6167 - classification_loss: 0.0892 35/500 [=>............................] - ETA: 2:30 - loss: 0.7162 - regression_loss: 0.6256 - classification_loss: 0.0907 36/500 [=>............................] - ETA: 2:29 - loss: 0.7052 - regression_loss: 0.6162 - classification_loss: 0.0889 37/500 [=>............................] - ETA: 2:29 - loss: 0.7115 - regression_loss: 0.6218 - classification_loss: 0.0897 38/500 [=>............................] - ETA: 2:29 - loss: 0.7170 - regression_loss: 0.6272 - classification_loss: 0.0897 39/500 [=>............................] - ETA: 2:29 - loss: 0.7193 - regression_loss: 0.6298 - classification_loss: 0.0895 40/500 [=>............................] - ETA: 2:28 - loss: 0.7252 - regression_loss: 0.6354 - classification_loss: 0.0898 41/500 [=>............................] - ETA: 2:28 - loss: 0.7353 - regression_loss: 0.6447 - classification_loss: 0.0906 42/500 [=>............................] - ETA: 2:28 - loss: 0.7249 - regression_loss: 0.6358 - classification_loss: 0.0891 43/500 [=>............................] - ETA: 2:27 - loss: 0.7228 - regression_loss: 0.6349 - classification_loss: 0.0879 44/500 [=>............................] - ETA: 2:27 - loss: 0.7371 - regression_loss: 0.6463 - classification_loss: 0.0908 45/500 [=>............................] - ETA: 2:27 - loss: 0.7416 - regression_loss: 0.6500 - classification_loss: 0.0916 46/500 [=>............................] - ETA: 2:26 - loss: 0.7426 - regression_loss: 0.6506 - classification_loss: 0.0920 47/500 [=>............................] - ETA: 2:26 - loss: 0.7365 - regression_loss: 0.6455 - classification_loss: 0.0910 48/500 [=>............................] - ETA: 2:26 - loss: 0.7367 - regression_loss: 0.6459 - classification_loss: 0.0908 49/500 [=>............................] - ETA: 2:25 - loss: 0.7422 - regression_loss: 0.6495 - classification_loss: 0.0926 50/500 [==>...........................] - ETA: 2:25 - loss: 0.7453 - regression_loss: 0.6530 - classification_loss: 0.0923 51/500 [==>...........................] - ETA: 2:25 - loss: 0.7522 - regression_loss: 0.6588 - classification_loss: 0.0933 52/500 [==>...........................] - ETA: 2:24 - loss: 0.7451 - regression_loss: 0.6530 - classification_loss: 0.0921 53/500 [==>...........................] - ETA: 2:24 - loss: 0.7459 - regression_loss: 0.6536 - classification_loss: 0.0923 54/500 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[==>...........................] - ETA: 2:21 - loss: 0.7457 - regression_loss: 0.6510 - classification_loss: 0.0947 63/500 [==>...........................] - ETA: 2:21 - loss: 0.7432 - regression_loss: 0.6489 - classification_loss: 0.0943 64/500 [==>...........................] - ETA: 2:21 - loss: 0.7509 - regression_loss: 0.6551 - classification_loss: 0.0958 65/500 [==>...........................] - ETA: 2:20 - loss: 0.7530 - regression_loss: 0.6570 - classification_loss: 0.0959 66/500 [==>...........................] - ETA: 2:20 - loss: 0.7515 - regression_loss: 0.6563 - classification_loss: 0.0952 67/500 [===>..........................] - ETA: 2:20 - loss: 0.7481 - regression_loss: 0.6535 - classification_loss: 0.0946 68/500 [===>..........................] - ETA: 2:19 - loss: 0.7573 - regression_loss: 0.6616 - classification_loss: 0.0957 69/500 [===>..........................] - ETA: 2:19 - loss: 0.7487 - regression_loss: 0.6540 - classification_loss: 0.0947 70/500 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[============================>.] - ETA: 4s - loss: 0.7280 - regression_loss: 0.6389 - classification_loss: 0.0891 487/500 [============================>.] - ETA: 4s - loss: 0.7279 - regression_loss: 0.6388 - classification_loss: 0.0891 488/500 [============================>.] - ETA: 3s - loss: 0.7270 - regression_loss: 0.6380 - classification_loss: 0.0890 489/500 [============================>.] - ETA: 3s - loss: 0.7269 - regression_loss: 0.6380 - classification_loss: 0.0889 490/500 [============================>.] - ETA: 3s - loss: 0.7275 - regression_loss: 0.6385 - classification_loss: 0.0890 491/500 [============================>.] - ETA: 2s - loss: 0.7274 - regression_loss: 0.6384 - classification_loss: 0.0890 492/500 [============================>.] - ETA: 2s - loss: 0.7275 - regression_loss: 0.6385 - classification_loss: 0.0889 493/500 [============================>.] - ETA: 2s - loss: 0.7274 - regression_loss: 0.6385 - classification_loss: 0.0889 494/500 [============================>.] - ETA: 1s - loss: 0.7269 - regression_loss: 0.6381 - classification_loss: 0.0888 495/500 [============================>.] - ETA: 1s - loss: 0.7267 - regression_loss: 0.6380 - classification_loss: 0.0888 496/500 [============================>.] - ETA: 1s - loss: 0.7270 - regression_loss: 0.6382 - classification_loss: 0.0889 497/500 [============================>.] - ETA: 0s - loss: 0.7272 - regression_loss: 0.6383 - classification_loss: 0.0889 498/500 [============================>.] - ETA: 0s - loss: 0.7287 - regression_loss: 0.6394 - classification_loss: 0.0892 499/500 [============================>.] - ETA: 0s - loss: 0.7290 - regression_loss: 0.6398 - classification_loss: 0.0892 500/500 [==============================] - 162s 324ms/step - loss: 0.7313 - regression_loss: 0.6415 - classification_loss: 0.0898 326 instances of class plum with average precision: 0.7533 mAP: 0.7533 Epoch 00027: saving model to ./training/snapshots/resnet101_pascal_27.h5 Epoch 28/150 1/500 [..............................] - ETA: 2:34 - loss: 0.3916 - regression_loss: 0.3427 - classification_loss: 0.0490 2/500 [..............................] - ETA: 2:38 - loss: 0.4210 - regression_loss: 0.3790 - classification_loss: 0.0419 3/500 [..............................] - ETA: 2:39 - loss: 0.4769 - regression_loss: 0.4225 - classification_loss: 0.0544 4/500 [..............................] - ETA: 2:37 - loss: 0.5232 - regression_loss: 0.4669 - classification_loss: 0.0563 5/500 [..............................] - ETA: 2:35 - loss: 0.5117 - regression_loss: 0.4607 - classification_loss: 0.0510 6/500 [..............................] - ETA: 2:34 - loss: 0.5167 - regression_loss: 0.4674 - classification_loss: 0.0493 7/500 [..............................] - ETA: 2:34 - loss: 0.4855 - regression_loss: 0.4390 - classification_loss: 0.0464 8/500 [..............................] - ETA: 2:33 - loss: 0.5140 - regression_loss: 0.4621 - classification_loss: 0.0519 9/500 [..............................] - ETA: 2:34 - loss: 0.4847 - regression_loss: 0.4285 - classification_loss: 0.0563 10/500 [..............................] - ETA: 2:35 - loss: 0.5399 - regression_loss: 0.4771 - classification_loss: 0.0628 11/500 [..............................] - ETA: 2:34 - loss: 0.5900 - regression_loss: 0.5200 - classification_loss: 0.0700 12/500 [..............................] - ETA: 2:34 - loss: 0.6062 - regression_loss: 0.5320 - classification_loss: 0.0742 13/500 [..............................] - ETA: 2:33 - loss: 0.5773 - regression_loss: 0.5073 - classification_loss: 0.0701 14/500 [..............................] - ETA: 2:32 - loss: 0.5762 - regression_loss: 0.5062 - classification_loss: 0.0700 15/500 [..............................] - ETA: 2:32 - loss: 0.5746 - regression_loss: 0.5043 - classification_loss: 0.0702 16/500 [..............................] - ETA: 2:32 - loss: 0.5619 - regression_loss: 0.4928 - classification_loss: 0.0691 17/500 [>.............................] - ETA: 2:32 - loss: 0.5592 - regression_loss: 0.4909 - classification_loss: 0.0683 18/500 [>.............................] - ETA: 2:32 - loss: 0.5683 - regression_loss: 0.5005 - classification_loss: 0.0678 19/500 [>.............................] - ETA: 2:32 - loss: 0.5550 - regression_loss: 0.4888 - classification_loss: 0.0662 20/500 [>.............................] - ETA: 2:32 - loss: 0.5783 - regression_loss: 0.5096 - classification_loss: 0.0687 21/500 [>.............................] - ETA: 2:31 - loss: 0.5954 - regression_loss: 0.5253 - classification_loss: 0.0701 22/500 [>.............................] - ETA: 2:31 - loss: 0.6267 - regression_loss: 0.5527 - classification_loss: 0.0740 23/500 [>.............................] - ETA: 2:31 - loss: 0.6131 - regression_loss: 0.5379 - classification_loss: 0.0751 24/500 [>.............................] - ETA: 2:30 - loss: 0.6149 - regression_loss: 0.5399 - classification_loss: 0.0750 25/500 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[==>...........................] - ETA: 2:23 - loss: 0.6235 - regression_loss: 0.5477 - classification_loss: 0.0758 58/500 [==>...........................] - ETA: 2:22 - loss: 0.6193 - regression_loss: 0.5442 - classification_loss: 0.0751 59/500 [==>...........................] - ETA: 2:22 - loss: 0.6132 - regression_loss: 0.5387 - classification_loss: 0.0745 60/500 [==>...........................] - ETA: 2:22 - loss: 0.6095 - regression_loss: 0.5352 - classification_loss: 0.0743 61/500 [==>...........................] - ETA: 2:21 - loss: 0.6147 - regression_loss: 0.5400 - classification_loss: 0.0747 62/500 [==>...........................] - ETA: 2:21 - loss: 0.6140 - regression_loss: 0.5397 - classification_loss: 0.0743 63/500 [==>...........................] - ETA: 2:21 - loss: 0.6268 - regression_loss: 0.5477 - classification_loss: 0.0791 64/500 [==>...........................] - ETA: 2:21 - loss: 0.6385 - regression_loss: 0.5553 - classification_loss: 0.0832 65/500 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[====>.........................] - ETA: 2:12 - loss: 0.6409 - regression_loss: 0.5586 - classification_loss: 0.0823 90/500 [====>.........................] - ETA: 2:12 - loss: 0.6451 - regression_loss: 0.5624 - classification_loss: 0.0828 91/500 [====>.........................] - ETA: 2:12 - loss: 0.6486 - regression_loss: 0.5659 - classification_loss: 0.0827 92/500 [====>.........................] - ETA: 2:12 - loss: 0.6541 - regression_loss: 0.5709 - classification_loss: 0.0833 93/500 [====>.........................] - ETA: 2:11 - loss: 0.6617 - regression_loss: 0.5775 - classification_loss: 0.0842 94/500 [====>.........................] - ETA: 2:11 - loss: 0.6663 - regression_loss: 0.5820 - classification_loss: 0.0843 95/500 [====>.........................] - ETA: 2:11 - loss: 0.6651 - regression_loss: 0.5809 - classification_loss: 0.0842 96/500 [====>.........................] - ETA: 2:10 - loss: 0.6648 - regression_loss: 0.5810 - classification_loss: 0.0838 97/500 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[=====>........................] - ETA: 2:07 - loss: 0.6810 - regression_loss: 0.5959 - classification_loss: 0.0850 106/500 [=====>........................] - ETA: 2:07 - loss: 0.6828 - regression_loss: 0.5979 - classification_loss: 0.0849 107/500 [=====>........................] - ETA: 2:06 - loss: 0.6783 - regression_loss: 0.5940 - classification_loss: 0.0844 108/500 [=====>........................] - ETA: 2:06 - loss: 0.6859 - regression_loss: 0.6000 - classification_loss: 0.0859 109/500 [=====>........................] - ETA: 2:06 - loss: 0.6874 - regression_loss: 0.6010 - classification_loss: 0.0863 110/500 [=====>........................] - ETA: 2:05 - loss: 0.6850 - regression_loss: 0.5988 - classification_loss: 0.0862 111/500 [=====>........................] - ETA: 2:05 - loss: 0.6833 - regression_loss: 0.5973 - classification_loss: 0.0859 112/500 [=====>........................] - ETA: 2:05 - loss: 0.6814 - regression_loss: 0.5958 - classification_loss: 0.0856 113/500 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[==========>...................] - ETA: 1:39 - loss: 0.6797 - regression_loss: 0.5968 - classification_loss: 0.0828 194/500 [==========>...................] - ETA: 1:39 - loss: 0.6791 - regression_loss: 0.5965 - classification_loss: 0.0826 195/500 [==========>...................] - ETA: 1:39 - loss: 0.6796 - regression_loss: 0.5970 - classification_loss: 0.0827 196/500 [==========>...................] - ETA: 1:38 - loss: 0.6784 - regression_loss: 0.5960 - classification_loss: 0.0825 197/500 [==========>...................] - ETA: 1:38 - loss: 0.6781 - regression_loss: 0.5957 - classification_loss: 0.0824 198/500 [==========>...................] - ETA: 1:38 - loss: 0.6820 - regression_loss: 0.5991 - classification_loss: 0.0829 199/500 [==========>...................] - ETA: 1:37 - loss: 0.6822 - regression_loss: 0.5992 - classification_loss: 0.0829 200/500 [===========>..................] - ETA: 1:37 - loss: 0.6808 - regression_loss: 0.5979 - classification_loss: 0.0829 201/500 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[============================>.] - ETA: 3s - loss: 0.6807 - regression_loss: 0.5971 - classification_loss: 0.0836 490/500 [============================>.] - ETA: 3s - loss: 0.6803 - regression_loss: 0.5967 - classification_loss: 0.0836 491/500 [============================>.] - ETA: 2s - loss: 0.6813 - regression_loss: 0.5977 - classification_loss: 0.0836 492/500 [============================>.] - ETA: 2s - loss: 0.6816 - regression_loss: 0.5980 - classification_loss: 0.0836 493/500 [============================>.] - ETA: 2s - loss: 0.6804 - regression_loss: 0.5970 - classification_loss: 0.0835 494/500 [============================>.] - ETA: 1s - loss: 0.6802 - regression_loss: 0.5967 - classification_loss: 0.0834 495/500 [============================>.] - ETA: 1s - loss: 0.6794 - regression_loss: 0.5961 - classification_loss: 0.0833 496/500 [============================>.] - ETA: 1s - loss: 0.6789 - regression_loss: 0.5956 - classification_loss: 0.0832 497/500 [============================>.] - ETA: 0s - loss: 0.6784 - regression_loss: 0.5952 - classification_loss: 0.0831 498/500 [============================>.] - ETA: 0s - loss: 0.6785 - regression_loss: 0.5953 - classification_loss: 0.0832 499/500 [============================>.] - ETA: 0s - loss: 0.6793 - regression_loss: 0.5959 - classification_loss: 0.0833 500/500 [==============================] - 162s 325ms/step - loss: 0.6791 - regression_loss: 0.5957 - classification_loss: 0.0833 326 instances of class plum with average precision: 0.7932 mAP: 0.7932 Epoch 00028: saving model to ./training/snapshots/resnet101_pascal_28.h5 Epoch 29/150 1/500 [..............................] - ETA: 2:34 - loss: 0.4641 - regression_loss: 0.4265 - classification_loss: 0.0376 2/500 [..............................] - ETA: 2:31 - loss: 0.7938 - regression_loss: 0.7015 - classification_loss: 0.0922 3/500 [..............................] - ETA: 2:32 - loss: 0.7883 - regression_loss: 0.7064 - 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0.0765 12/500 [..............................] - ETA: 2:35 - loss: 0.6655 - regression_loss: 0.5931 - classification_loss: 0.0724 13/500 [..............................] - ETA: 2:35 - loss: 0.6610 - regression_loss: 0.5864 - classification_loss: 0.0745 14/500 [..............................] - ETA: 2:35 - loss: 0.6397 - regression_loss: 0.5688 - classification_loss: 0.0709 15/500 [..............................] - ETA: 2:34 - loss: 0.6303 - regression_loss: 0.5594 - classification_loss: 0.0709 16/500 [..............................] - ETA: 2:34 - loss: 0.6528 - regression_loss: 0.5756 - classification_loss: 0.0772 17/500 [>.............................] - ETA: 2:35 - loss: 0.6493 - regression_loss: 0.5734 - classification_loss: 0.0760 18/500 [>.............................] - ETA: 2:35 - loss: 0.6702 - regression_loss: 0.5894 - classification_loss: 0.0808 19/500 [>.............................] - ETA: 2:36 - loss: 0.6570 - regression_loss: 0.5784 - classification_loss: 0.0786 20/500 [>.............................] - ETA: 2:36 - loss: 0.6516 - regression_loss: 0.5751 - classification_loss: 0.0765 21/500 [>.............................] - ETA: 2:35 - loss: 0.6398 - regression_loss: 0.5654 - classification_loss: 0.0743 22/500 [>.............................] - ETA: 2:34 - loss: 0.6393 - regression_loss: 0.5645 - classification_loss: 0.0749 23/500 [>.............................] - ETA: 2:35 - loss: 0.6546 - regression_loss: 0.5796 - classification_loss: 0.0750 24/500 [>.............................] - ETA: 2:34 - loss: 0.6539 - regression_loss: 0.5792 - classification_loss: 0.0747 25/500 [>.............................] - ETA: 2:33 - loss: 0.6565 - regression_loss: 0.5820 - classification_loss: 0.0745 26/500 [>.............................] - ETA: 2:33 - loss: 0.6511 - regression_loss: 0.5768 - classification_loss: 0.0743 27/500 [>.............................] - ETA: 2:32 - loss: 0.6596 - regression_loss: 0.5837 - classification_loss: 0.0759 28/500 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[===>..........................] - ETA: 2:16 - loss: 0.7312 - regression_loss: 0.6426 - classification_loss: 0.0886 77/500 [===>..........................] - ETA: 2:16 - loss: 0.7430 - regression_loss: 0.6545 - classification_loss: 0.0885 78/500 [===>..........................] - ETA: 2:15 - loss: 0.7380 - regression_loss: 0.6504 - classification_loss: 0.0876 79/500 [===>..........................] - ETA: 2:15 - loss: 0.7394 - regression_loss: 0.6522 - classification_loss: 0.0872 80/500 [===>..........................] - ETA: 2:15 - loss: 0.7377 - regression_loss: 0.6509 - classification_loss: 0.0868 81/500 [===>..........................] - ETA: 2:15 - loss: 0.7375 - regression_loss: 0.6508 - classification_loss: 0.0866 82/500 [===>..........................] - ETA: 2:14 - loss: 0.7380 - regression_loss: 0.6514 - classification_loss: 0.0866 83/500 [===>..........................] - ETA: 2:14 - loss: 0.7350 - regression_loss: 0.6486 - classification_loss: 0.0863 84/500 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[=====>........................] - ETA: 2:08 - loss: 0.7007 - regression_loss: 0.6194 - classification_loss: 0.0813 101/500 [=====>........................] - ETA: 2:08 - loss: 0.6964 - regression_loss: 0.6157 - classification_loss: 0.0807 102/500 [=====>........................] - ETA: 2:08 - loss: 0.6911 - regression_loss: 0.6110 - classification_loss: 0.0800 103/500 [=====>........................] - ETA: 2:07 - loss: 0.6892 - regression_loss: 0.6094 - classification_loss: 0.0798 104/500 [=====>........................] - ETA: 2:07 - loss: 0.6896 - regression_loss: 0.6094 - classification_loss: 0.0802 105/500 [=====>........................] - ETA: 2:07 - loss: 0.6860 - regression_loss: 0.6063 - classification_loss: 0.0797 106/500 [=====>........................] - ETA: 2:06 - loss: 0.6936 - regression_loss: 0.6131 - classification_loss: 0.0805 107/500 [=====>........................] - ETA: 2:06 - loss: 0.6924 - regression_loss: 0.6121 - classification_loss: 0.0803 108/500 [=====>........................] - ETA: 2:06 - loss: 0.6930 - regression_loss: 0.6128 - classification_loss: 0.0801 109/500 [=====>........................] - ETA: 2:05 - loss: 0.6925 - regression_loss: 0.6123 - classification_loss: 0.0803 110/500 [=====>........................] - ETA: 2:05 - loss: 0.6892 - regression_loss: 0.6094 - classification_loss: 0.0798 111/500 [=====>........................] - ETA: 2:04 - loss: 0.6875 - regression_loss: 0.6080 - classification_loss: 0.0795 112/500 [=====>........................] - ETA: 2:04 - loss: 0.6845 - regression_loss: 0.6054 - classification_loss: 0.0791 113/500 [=====>........................] - ETA: 2:04 - loss: 0.6822 - regression_loss: 0.6033 - classification_loss: 0.0790 114/500 [=====>........................] - ETA: 2:03 - loss: 0.6870 - regression_loss: 0.6077 - classification_loss: 0.0793 115/500 [=====>........................] - ETA: 2:03 - loss: 0.6842 - regression_loss: 0.6053 - classification_loss: 0.0790 116/500 [=====>........................] - ETA: 2:03 - loss: 0.6822 - regression_loss: 0.6036 - classification_loss: 0.0787 117/500 [======>.......................] - ETA: 2:03 - loss: 0.6836 - regression_loss: 0.6051 - classification_loss: 0.0785 118/500 [======>.......................] - ETA: 2:02 - loss: 0.6824 - regression_loss: 0.6042 - classification_loss: 0.0783 119/500 [======>.......................] - ETA: 2:02 - loss: 0.6895 - regression_loss: 0.6098 - classification_loss: 0.0797 120/500 [======>.......................] - ETA: 2:01 - loss: 0.6949 - regression_loss: 0.6144 - classification_loss: 0.0805 121/500 [======>.......................] - ETA: 2:01 - loss: 0.7005 - regression_loss: 0.6193 - classification_loss: 0.0812 122/500 [======>.......................] - ETA: 2:01 - loss: 0.7020 - regression_loss: 0.6204 - classification_loss: 0.0816 123/500 [======>.......................] - ETA: 2:00 - loss: 0.7029 - regression_loss: 0.6211 - classification_loss: 0.0817 124/500 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[======>.......................] - ETA: 1:58 - loss: 0.7050 - regression_loss: 0.6238 - classification_loss: 0.0812 133/500 [======>.......................] - ETA: 1:57 - loss: 0.7084 - regression_loss: 0.6267 - classification_loss: 0.0817 134/500 [=======>......................] - ETA: 1:57 - loss: 0.7078 - regression_loss: 0.6262 - classification_loss: 0.0815 135/500 [=======>......................] - ETA: 1:57 - loss: 0.7079 - regression_loss: 0.6262 - classification_loss: 0.0818 136/500 [=======>......................] - ETA: 1:56 - loss: 0.7075 - regression_loss: 0.6259 - classification_loss: 0.0816 137/500 [=======>......................] - ETA: 1:56 - loss: 0.7054 - regression_loss: 0.6237 - classification_loss: 0.0817 138/500 [=======>......................] - ETA: 1:56 - loss: 0.7052 - regression_loss: 0.6237 - classification_loss: 0.0815 139/500 [=======>......................] - ETA: 1:55 - loss: 0.7045 - regression_loss: 0.6231 - classification_loss: 0.0814 140/500 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[============================>.] - ETA: 2s - loss: 0.6793 - regression_loss: 0.5980 - classification_loss: 0.0813 493/500 [============================>.] - ETA: 2s - loss: 0.6793 - regression_loss: 0.5981 - classification_loss: 0.0812 494/500 [============================>.] - ETA: 1s - loss: 0.6789 - regression_loss: 0.5977 - classification_loss: 0.0812 495/500 [============================>.] - ETA: 1s - loss: 0.6790 - regression_loss: 0.5979 - classification_loss: 0.0811 496/500 [============================>.] - ETA: 1s - loss: 0.6806 - regression_loss: 0.5991 - classification_loss: 0.0815 497/500 [============================>.] - ETA: 0s - loss: 0.6814 - regression_loss: 0.5998 - classification_loss: 0.0816 498/500 [============================>.] - ETA: 0s - loss: 0.6814 - regression_loss: 0.5999 - classification_loss: 0.0815 499/500 [============================>.] - ETA: 0s - loss: 0.6819 - regression_loss: 0.6002 - classification_loss: 0.0816 500/500 [==============================] - 162s 323ms/step - loss: 0.6815 - regression_loss: 0.5999 - classification_loss: 0.0816 326 instances of class plum with average precision: 0.7739 mAP: 0.7739 Epoch 00029: saving model to ./training/snapshots/resnet101_pascal_29.h5 Epoch 30/150 1/500 [..............................] - ETA: 2:30 - loss: 0.2813 - regression_loss: 0.2457 - classification_loss: 0.0357 2/500 [..............................] - ETA: 2:39 - loss: 0.8378 - regression_loss: 0.7251 - classification_loss: 0.1128 3/500 [..............................] - ETA: 2:39 - loss: 0.6503 - regression_loss: 0.5678 - classification_loss: 0.0825 4/500 [..............................] - ETA: 2:37 - loss: 0.6514 - regression_loss: 0.5689 - classification_loss: 0.0825 5/500 [..............................] - ETA: 2:37 - loss: 0.7258 - regression_loss: 0.6331 - classification_loss: 0.0927 6/500 [..............................] - ETA: 2:35 - loss: 0.7093 - regression_loss: 0.6258 - classification_loss: 0.0834 7/500 [..............................] - ETA: 2:37 - loss: 0.7731 - regression_loss: 0.6881 - classification_loss: 0.0850 8/500 [..............................] - ETA: 2:38 - loss: 0.7508 - regression_loss: 0.6693 - classification_loss: 0.0816 9/500 [..............................] - ETA: 2:37 - loss: 0.7292 - regression_loss: 0.6505 - classification_loss: 0.0787 10/500 [..............................] - ETA: 2:36 - loss: 0.7251 - regression_loss: 0.6468 - classification_loss: 0.0783 11/500 [..............................] - ETA: 2:37 - loss: 0.6966 - regression_loss: 0.6222 - classification_loss: 0.0745 12/500 [..............................] - ETA: 2:37 - loss: 0.6671 - regression_loss: 0.5946 - classification_loss: 0.0725 13/500 [..............................] - ETA: 2:36 - loss: 0.6567 - regression_loss: 0.5865 - classification_loss: 0.0702 14/500 [..............................] - ETA: 2:36 - loss: 0.6478 - regression_loss: 0.5771 - classification_loss: 0.0707 15/500 [..............................] - ETA: 2:36 - loss: 0.6277 - regression_loss: 0.5594 - classification_loss: 0.0683 16/500 [..............................] - ETA: 2:36 - loss: 0.6414 - regression_loss: 0.5738 - classification_loss: 0.0676 17/500 [>.............................] - ETA: 2:35 - loss: 0.6912 - regression_loss: 0.6118 - classification_loss: 0.0794 18/500 [>.............................] - ETA: 2:35 - loss: 0.6760 - regression_loss: 0.5991 - classification_loss: 0.0769 19/500 [>.............................] - ETA: 2:34 - loss: 0.6771 - regression_loss: 0.6016 - classification_loss: 0.0755 20/500 [>.............................] - ETA: 2:34 - loss: 0.6537 - regression_loss: 0.5811 - classification_loss: 0.0726 21/500 [>.............................] - ETA: 2:34 - loss: 0.6457 - regression_loss: 0.5736 - classification_loss: 0.0721 22/500 [>.............................] - ETA: 2:34 - loss: 0.6375 - regression_loss: 0.5662 - classification_loss: 0.0713 23/500 [>.............................] - ETA: 2:35 - loss: 0.6326 - regression_loss: 0.5620 - classification_loss: 0.0706 24/500 [>.............................] - ETA: 2:34 - loss: 0.6360 - regression_loss: 0.5641 - classification_loss: 0.0719 25/500 [>.............................] - ETA: 2:33 - loss: 0.6339 - regression_loss: 0.5635 - classification_loss: 0.0704 26/500 [>.............................] - ETA: 2:33 - loss: 0.6268 - regression_loss: 0.5567 - classification_loss: 0.0701 27/500 [>.............................] - ETA: 2:33 - loss: 0.6356 - regression_loss: 0.5648 - classification_loss: 0.0708 28/500 [>.............................] - ETA: 2:33 - loss: 0.6329 - regression_loss: 0.5618 - classification_loss: 0.0712 29/500 [>.............................] - ETA: 2:33 - loss: 0.6339 - regression_loss: 0.5623 - classification_loss: 0.0716 30/500 [>.............................] - ETA: 2:32 - loss: 0.6525 - regression_loss: 0.5786 - classification_loss: 0.0739 31/500 [>.............................] - ETA: 2:32 - loss: 0.6680 - regression_loss: 0.5889 - classification_loss: 0.0790 32/500 [>.............................] - ETA: 2:31 - loss: 0.6581 - regression_loss: 0.5804 - classification_loss: 0.0776 33/500 [>.............................] - ETA: 2:31 - loss: 0.6559 - regression_loss: 0.5791 - classification_loss: 0.0768 34/500 [=>............................] - ETA: 2:30 - loss: 0.6401 - regression_loss: 0.5652 - classification_loss: 0.0750 35/500 [=>............................] - ETA: 2:31 - loss: 0.6324 - regression_loss: 0.5585 - classification_loss: 0.0739 36/500 [=>............................] - ETA: 2:30 - loss: 0.6276 - regression_loss: 0.5544 - classification_loss: 0.0732 37/500 [=>............................] - ETA: 2:30 - loss: 0.6606 - regression_loss: 0.5779 - classification_loss: 0.0828 38/500 [=>............................] - ETA: 2:30 - loss: 0.6675 - regression_loss: 0.5840 - classification_loss: 0.0835 39/500 [=>............................] - ETA: 2:30 - loss: 0.6711 - regression_loss: 0.5882 - classification_loss: 0.0829 40/500 [=>............................] - ETA: 2:29 - loss: 0.6695 - regression_loss: 0.5873 - classification_loss: 0.0822 41/500 [=>............................] - ETA: 2:29 - loss: 0.6710 - regression_loss: 0.5890 - classification_loss: 0.0820 42/500 [=>............................] - ETA: 2:29 - loss: 0.6689 - regression_loss: 0.5871 - classification_loss: 0.0818 43/500 [=>............................] - ETA: 2:28 - loss: 0.6717 - regression_loss: 0.5898 - classification_loss: 0.0819 44/500 [=>............................] - ETA: 2:28 - loss: 0.6735 - regression_loss: 0.5921 - classification_loss: 0.0815 45/500 [=>............................] - ETA: 2:27 - loss: 0.6752 - regression_loss: 0.5942 - classification_loss: 0.0809 46/500 [=>............................] - ETA: 2:27 - loss: 0.6764 - regression_loss: 0.5957 - classification_loss: 0.0807 47/500 [=>............................] - ETA: 2:27 - loss: 0.6777 - regression_loss: 0.5970 - classification_loss: 0.0807 48/500 [=>............................] - ETA: 2:27 - loss: 0.6787 - regression_loss: 0.5989 - classification_loss: 0.0798 49/500 [=>............................] - ETA: 2:26 - loss: 0.6784 - regression_loss: 0.5993 - classification_loss: 0.0791 50/500 [==>...........................] - ETA: 2:26 - loss: 0.6744 - regression_loss: 0.5961 - classification_loss: 0.0783 51/500 [==>...........................] - ETA: 2:26 - loss: 0.6821 - regression_loss: 0.6030 - classification_loss: 0.0790 52/500 [==>...........................] - ETA: 2:26 - loss: 0.6741 - regression_loss: 0.5960 - classification_loss: 0.0781 53/500 [==>...........................] - ETA: 2:25 - loss: 0.6794 - regression_loss: 0.6011 - classification_loss: 0.0783 54/500 [==>...........................] - ETA: 2:25 - loss: 0.6740 - regression_loss: 0.5965 - classification_loss: 0.0776 55/500 [==>...........................] - ETA: 2:24 - loss: 0.6698 - regression_loss: 0.5921 - classification_loss: 0.0777 56/500 [==>...........................] - ETA: 2:24 - loss: 0.6645 - regression_loss: 0.5876 - classification_loss: 0.0769 57/500 [==>...........................] - ETA: 2:24 - loss: 0.6613 - regression_loss: 0.5852 - classification_loss: 0.0761 58/500 [==>...........................] - ETA: 2:23 - loss: 0.6629 - regression_loss: 0.5866 - classification_loss: 0.0763 59/500 [==>...........................] - ETA: 2:23 - loss: 0.6621 - regression_loss: 0.5860 - classification_loss: 0.0761 60/500 [==>...........................] - ETA: 2:23 - loss: 0.6590 - regression_loss: 0.5832 - classification_loss: 0.0758 61/500 [==>...........................] - ETA: 2:22 - loss: 0.6530 - regression_loss: 0.5782 - classification_loss: 0.0748 62/500 [==>...........................] - ETA: 2:22 - loss: 0.6601 - regression_loss: 0.5847 - classification_loss: 0.0754 63/500 [==>...........................] - ETA: 2:22 - loss: 0.6543 - regression_loss: 0.5797 - classification_loss: 0.0747 64/500 [==>...........................] - ETA: 2:22 - loss: 0.6567 - regression_loss: 0.5823 - classification_loss: 0.0744 65/500 [==>...........................] - ETA: 2:21 - loss: 0.6561 - regression_loss: 0.5821 - classification_loss: 0.0740 66/500 [==>...........................] - ETA: 2:21 - loss: 0.6528 - regression_loss: 0.5793 - classification_loss: 0.0734 67/500 [===>..........................] - ETA: 2:20 - loss: 0.6522 - regression_loss: 0.5793 - classification_loss: 0.0729 68/500 [===>..........................] - ETA: 2:20 - loss: 0.6587 - regression_loss: 0.5846 - classification_loss: 0.0742 69/500 [===>..........................] - ETA: 2:20 - loss: 0.6554 - regression_loss: 0.5818 - classification_loss: 0.0735 70/500 [===>..........................] - ETA: 2:20 - loss: 0.6519 - regression_loss: 0.5788 - classification_loss: 0.0731 71/500 [===>..........................] - ETA: 2:19 - loss: 0.6489 - regression_loss: 0.5762 - classification_loss: 0.0727 72/500 [===>..........................] - ETA: 2:19 - loss: 0.6573 - regression_loss: 0.5820 - classification_loss: 0.0753 73/500 [===>..........................] - ETA: 2:19 - loss: 0.6679 - regression_loss: 0.5892 - classification_loss: 0.0787 74/500 [===>..........................] - ETA: 2:18 - loss: 0.6700 - regression_loss: 0.5914 - classification_loss: 0.0787 75/500 [===>..........................] - ETA: 2:18 - loss: 0.6775 - regression_loss: 0.5970 - classification_loss: 0.0805 76/500 [===>..........................] - ETA: 2:18 - loss: 0.6746 - regression_loss: 0.5944 - classification_loss: 0.0802 77/500 [===>..........................] - ETA: 2:17 - loss: 0.6749 - regression_loss: 0.5950 - classification_loss: 0.0799 78/500 [===>..........................] - ETA: 2:17 - loss: 0.6726 - regression_loss: 0.5931 - classification_loss: 0.0795 79/500 [===>..........................] - ETA: 2:17 - loss: 0.6679 - regression_loss: 0.5889 - classification_loss: 0.0791 80/500 [===>..........................] - ETA: 2:17 - loss: 0.6633 - regression_loss: 0.5849 - classification_loss: 0.0783 81/500 [===>..........................] - ETA: 2:16 - loss: 0.6573 - regression_loss: 0.5795 - classification_loss: 0.0777 82/500 [===>..........................] - ETA: 2:16 - loss: 0.6648 - regression_loss: 0.5860 - classification_loss: 0.0788 83/500 [===>..........................] - ETA: 2:16 - loss: 0.6652 - regression_loss: 0.5869 - classification_loss: 0.0783 84/500 [====>.........................] - ETA: 2:16 - loss: 0.6641 - regression_loss: 0.5861 - classification_loss: 0.0780 85/500 [====>.........................] - ETA: 2:15 - loss: 0.6687 - regression_loss: 0.5864 - classification_loss: 0.0823 86/500 [====>.........................] - ETA: 2:15 - loss: 0.6651 - regression_loss: 0.5835 - classification_loss: 0.0816 87/500 [====>.........................] - ETA: 2:14 - loss: 0.6717 - regression_loss: 0.5894 - classification_loss: 0.0824 88/500 [====>.........................] - ETA: 2:14 - loss: 0.6692 - regression_loss: 0.5869 - classification_loss: 0.0822 89/500 [====>.........................] - ETA: 2:14 - loss: 0.6748 - regression_loss: 0.5927 - classification_loss: 0.0821 90/500 [====>.........................] - ETA: 2:13 - loss: 0.6771 - regression_loss: 0.5952 - classification_loss: 0.0820 91/500 [====>.........................] - ETA: 2:13 - loss: 0.6803 - regression_loss: 0.5978 - classification_loss: 0.0825 92/500 [====>.........................] - ETA: 2:13 - loss: 0.6773 - regression_loss: 0.5954 - classification_loss: 0.0820 93/500 [====>.........................] - ETA: 2:12 - loss: 0.6784 - regression_loss: 0.5964 - classification_loss: 0.0820 94/500 [====>.........................] - ETA: 2:12 - loss: 0.6819 - regression_loss: 0.5998 - classification_loss: 0.0821 95/500 [====>.........................] - ETA: 2:12 - loss: 0.6880 - regression_loss: 0.6049 - classification_loss: 0.0832 96/500 [====>.........................] - ETA: 2:11 - loss: 0.6946 - regression_loss: 0.6103 - classification_loss: 0.0843 97/500 [====>.........................] - ETA: 2:11 - loss: 0.6940 - regression_loss: 0.6103 - classification_loss: 0.0837 98/500 [====>.........................] - ETA: 2:11 - loss: 0.6918 - regression_loss: 0.6085 - classification_loss: 0.0833 99/500 [====>.........................] - ETA: 2:10 - loss: 0.6878 - regression_loss: 0.6052 - classification_loss: 0.0827 100/500 [=====>........................] - ETA: 2:10 - loss: 0.6901 - regression_loss: 0.6071 - classification_loss: 0.0830 101/500 [=====>........................] - ETA: 2:10 - loss: 0.6897 - regression_loss: 0.6067 - classification_loss: 0.0829 102/500 [=====>........................] - ETA: 2:09 - loss: 0.6874 - regression_loss: 0.6049 - classification_loss: 0.0826 103/500 [=====>........................] - ETA: 2:09 - loss: 0.6866 - regression_loss: 0.6042 - classification_loss: 0.0824 104/500 [=====>........................] - ETA: 2:09 - loss: 0.6830 - regression_loss: 0.6012 - classification_loss: 0.0818 105/500 [=====>........................] - ETA: 2:08 - loss: 0.6822 - regression_loss: 0.6007 - classification_loss: 0.0815 106/500 [=====>........................] - ETA: 2:08 - loss: 0.6784 - regression_loss: 0.5972 - classification_loss: 0.0813 107/500 [=====>........................] - ETA: 2:08 - loss: 0.6749 - regression_loss: 0.5942 - classification_loss: 0.0807 108/500 [=====>........................] - ETA: 2:07 - loss: 0.6745 - regression_loss: 0.5937 - classification_loss: 0.0808 109/500 [=====>........................] - ETA: 2:07 - loss: 0.6761 - regression_loss: 0.5954 - classification_loss: 0.0807 110/500 [=====>........................] - ETA: 2:07 - loss: 0.6756 - regression_loss: 0.5952 - classification_loss: 0.0803 111/500 [=====>........................] - ETA: 2:06 - loss: 0.6828 - regression_loss: 0.6011 - classification_loss: 0.0816 112/500 [=====>........................] - ETA: 2:06 - loss: 0.6805 - regression_loss: 0.5995 - classification_loss: 0.0811 113/500 [=====>........................] - ETA: 2:06 - loss: 0.6786 - regression_loss: 0.5980 - classification_loss: 0.0806 114/500 [=====>........................] - ETA: 2:05 - loss: 0.6811 - regression_loss: 0.6007 - classification_loss: 0.0804 115/500 [=====>........................] - ETA: 2:05 - loss: 0.6806 - regression_loss: 0.6005 - classification_loss: 0.0801 116/500 [=====>........................] - ETA: 2:05 - loss: 0.6807 - regression_loss: 0.6009 - classification_loss: 0.0798 117/500 [======>.......................] - ETA: 2:05 - loss: 0.6786 - regression_loss: 0.5992 - classification_loss: 0.0794 118/500 [======>.......................] - ETA: 2:04 - loss: 0.6798 - regression_loss: 0.6002 - classification_loss: 0.0796 119/500 [======>.......................] - ETA: 2:04 - loss: 0.6796 - regression_loss: 0.6002 - classification_loss: 0.0794 120/500 [======>.......................] - ETA: 2:04 - loss: 0.6770 - regression_loss: 0.5979 - classification_loss: 0.0790 121/500 [======>.......................] - ETA: 2:03 - loss: 0.6751 - regression_loss: 0.5963 - classification_loss: 0.0787 122/500 [======>.......................] - ETA: 2:03 - loss: 0.6717 - regression_loss: 0.5933 - classification_loss: 0.0784 123/500 [======>.......................] - ETA: 2:03 - loss: 0.6705 - regression_loss: 0.5924 - classification_loss: 0.0780 124/500 [======>.......................] - ETA: 2:02 - loss: 0.6691 - regression_loss: 0.5914 - classification_loss: 0.0777 125/500 [======>.......................] - ETA: 2:02 - loss: 0.6685 - regression_loss: 0.5910 - classification_loss: 0.0775 126/500 [======>.......................] - ETA: 2:02 - loss: 0.6668 - regression_loss: 0.5896 - classification_loss: 0.0772 127/500 [======>.......................] - ETA: 2:01 - loss: 0.6662 - regression_loss: 0.5892 - classification_loss: 0.0770 128/500 [======>.......................] - ETA: 2:01 - loss: 0.6671 - regression_loss: 0.5902 - classification_loss: 0.0769 129/500 [======>.......................] - ETA: 2:01 - loss: 0.6699 - regression_loss: 0.5927 - classification_loss: 0.0772 130/500 [======>.......................] - ETA: 2:00 - loss: 0.6687 - regression_loss: 0.5919 - classification_loss: 0.0768 131/500 [======>.......................] - ETA: 2:00 - loss: 0.6715 - regression_loss: 0.5943 - classification_loss: 0.0772 132/500 [======>.......................] - ETA: 2:00 - loss: 0.6715 - regression_loss: 0.5944 - classification_loss: 0.0771 133/500 [======>.......................] - ETA: 1:59 - loss: 0.6734 - regression_loss: 0.5963 - classification_loss: 0.0771 134/500 [=======>......................] - ETA: 1:59 - loss: 0.6781 - regression_loss: 0.6005 - classification_loss: 0.0776 135/500 [=======>......................] - ETA: 1:59 - loss: 0.6760 - regression_loss: 0.5986 - classification_loss: 0.0773 136/500 [=======>......................] - ETA: 1:58 - loss: 0.6796 - regression_loss: 0.6010 - classification_loss: 0.0786 137/500 [=======>......................] - ETA: 1:58 - loss: 0.6802 - regression_loss: 0.6018 - classification_loss: 0.0784 138/500 [=======>......................] - ETA: 1:58 - loss: 0.6802 - regression_loss: 0.6020 - classification_loss: 0.0782 139/500 [=======>......................] - ETA: 1:57 - loss: 0.6794 - regression_loss: 0.6014 - classification_loss: 0.0780 140/500 [=======>......................] - ETA: 1:57 - loss: 0.6778 - regression_loss: 0.6002 - classification_loss: 0.0777 141/500 [=======>......................] - ETA: 1:57 - loss: 0.6778 - regression_loss: 0.6003 - classification_loss: 0.0775 142/500 [=======>......................] - ETA: 1:56 - loss: 0.6775 - regression_loss: 0.6002 - classification_loss: 0.0772 143/500 [=======>......................] - ETA: 1:56 - loss: 0.6804 - regression_loss: 0.6029 - classification_loss: 0.0775 144/500 [=======>......................] - ETA: 1:56 - loss: 0.6803 - regression_loss: 0.6027 - classification_loss: 0.0775 145/500 [=======>......................] - ETA: 1:55 - loss: 0.6772 - regression_loss: 0.6000 - classification_loss: 0.0772 146/500 [=======>......................] - ETA: 1:55 - loss: 0.6757 - regression_loss: 0.5987 - classification_loss: 0.0770 147/500 [=======>......................] - ETA: 1:54 - loss: 0.6731 - regression_loss: 0.5964 - classification_loss: 0.0767 148/500 [=======>......................] - ETA: 1:54 - loss: 0.6758 - regression_loss: 0.5989 - classification_loss: 0.0768 149/500 [=======>......................] - ETA: 1:54 - loss: 0.6728 - regression_loss: 0.5963 - classification_loss: 0.0765 150/500 [========>.....................] - ETA: 1:53 - loss: 0.6732 - regression_loss: 0.5966 - classification_loss: 0.0766 151/500 [========>.....................] - ETA: 1:53 - loss: 0.6709 - regression_loss: 0.5946 - classification_loss: 0.0763 152/500 [========>.....................] - ETA: 1:53 - loss: 0.6710 - regression_loss: 0.5946 - classification_loss: 0.0764 153/500 [========>.....................] - ETA: 1:52 - loss: 0.6728 - regression_loss: 0.5960 - classification_loss: 0.0768 154/500 [========>.....................] - ETA: 1:52 - loss: 0.6710 - regression_loss: 0.5946 - classification_loss: 0.0764 155/500 [========>.....................] - ETA: 1:52 - loss: 0.6710 - regression_loss: 0.5947 - classification_loss: 0.0764 156/500 [========>.....................] - ETA: 1:51 - loss: 0.6738 - regression_loss: 0.5968 - classification_loss: 0.0770 157/500 [========>.....................] - ETA: 1:51 - loss: 0.6722 - regression_loss: 0.5955 - classification_loss: 0.0766 158/500 [========>.....................] - ETA: 1:51 - loss: 0.6747 - regression_loss: 0.5977 - classification_loss: 0.0770 159/500 [========>.....................] - ETA: 1:51 - loss: 0.6734 - regression_loss: 0.5966 - classification_loss: 0.0768 160/500 [========>.....................] - ETA: 1:50 - loss: 0.6714 - regression_loss: 0.5949 - classification_loss: 0.0765 161/500 [========>.....................] - ETA: 1:50 - loss: 0.6693 - regression_loss: 0.5930 - classification_loss: 0.0763 162/500 [========>.....................] - ETA: 1:50 - loss: 0.6681 - regression_loss: 0.5921 - classification_loss: 0.0760 163/500 [========>.....................] - ETA: 1:49 - loss: 0.6668 - regression_loss: 0.5910 - classification_loss: 0.0758 164/500 [========>.....................] - ETA: 1:49 - loss: 0.6687 - regression_loss: 0.5926 - classification_loss: 0.0762 165/500 [========>.....................] - ETA: 1:49 - loss: 0.6725 - regression_loss: 0.5956 - classification_loss: 0.0769 166/500 [========>.....................] - ETA: 1:48 - loss: 0.6758 - regression_loss: 0.5986 - classification_loss: 0.0772 167/500 [=========>....................] - ETA: 1:48 - loss: 0.6745 - regression_loss: 0.5975 - classification_loss: 0.0770 168/500 [=========>....................] - ETA: 1:48 - loss: 0.6735 - regression_loss: 0.5967 - classification_loss: 0.0768 169/500 [=========>....................] - ETA: 1:47 - loss: 0.6720 - regression_loss: 0.5954 - classification_loss: 0.0766 170/500 [=========>....................] - ETA: 1:47 - loss: 0.6732 - regression_loss: 0.5966 - classification_loss: 0.0766 171/500 [=========>....................] - ETA: 1:46 - loss: 0.6725 - regression_loss: 0.5962 - classification_loss: 0.0763 172/500 [=========>....................] - ETA: 1:46 - loss: 0.6719 - regression_loss: 0.5958 - classification_loss: 0.0761 173/500 [=========>....................] - ETA: 1:46 - loss: 0.6716 - regression_loss: 0.5956 - classification_loss: 0.0760 174/500 [=========>....................] - ETA: 1:45 - loss: 0.6710 - regression_loss: 0.5952 - classification_loss: 0.0758 175/500 [=========>....................] - ETA: 1:45 - loss: 0.6719 - regression_loss: 0.5960 - classification_loss: 0.0759 176/500 [=========>....................] - ETA: 1:45 - loss: 0.6751 - regression_loss: 0.5991 - classification_loss: 0.0760 177/500 [=========>....................] - ETA: 1:44 - loss: 0.6767 - regression_loss: 0.6008 - classification_loss: 0.0760 178/500 [=========>....................] - ETA: 1:44 - loss: 0.6786 - regression_loss: 0.6024 - classification_loss: 0.0761 179/500 [=========>....................] - ETA: 1:44 - loss: 0.6823 - regression_loss: 0.6059 - classification_loss: 0.0763 180/500 [=========>....................] - ETA: 1:44 - loss: 0.6826 - regression_loss: 0.6065 - classification_loss: 0.0762 181/500 [=========>....................] - ETA: 1:43 - loss: 0.6814 - regression_loss: 0.6055 - classification_loss: 0.0759 182/500 [=========>....................] - ETA: 1:43 - loss: 0.6820 - regression_loss: 0.6063 - classification_loss: 0.0757 183/500 [=========>....................] - ETA: 1:43 - loss: 0.6819 - regression_loss: 0.6063 - classification_loss: 0.0756 184/500 [==========>...................] - ETA: 1:42 - loss: 0.6862 - regression_loss: 0.6102 - classification_loss: 0.0760 185/500 [==========>...................] - ETA: 1:42 - loss: 0.6887 - regression_loss: 0.6123 - classification_loss: 0.0763 186/500 [==========>...................] - ETA: 1:42 - loss: 0.6882 - regression_loss: 0.6119 - classification_loss: 0.0764 187/500 [==========>...................] - ETA: 1:41 - loss: 0.6861 - regression_loss: 0.6100 - classification_loss: 0.0761 188/500 [==========>...................] - ETA: 1:41 - loss: 0.6865 - regression_loss: 0.6104 - classification_loss: 0.0761 189/500 [==========>...................] - ETA: 1:41 - loss: 0.6852 - regression_loss: 0.6091 - classification_loss: 0.0761 190/500 [==========>...................] - ETA: 1:40 - loss: 0.6861 - regression_loss: 0.6100 - 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[============================>.] - ETA: 4s - loss: 0.6693 - regression_loss: 0.5900 - classification_loss: 0.0793 488/500 [============================>.] - ETA: 3s - loss: 0.6694 - regression_loss: 0.5901 - classification_loss: 0.0792 489/500 [============================>.] - ETA: 3s - loss: 0.6694 - regression_loss: 0.5901 - classification_loss: 0.0793 490/500 [============================>.] - ETA: 3s - loss: 0.6692 - regression_loss: 0.5898 - classification_loss: 0.0793 491/500 [============================>.] - ETA: 2s - loss: 0.6691 - regression_loss: 0.5898 - classification_loss: 0.0793 492/500 [============================>.] - ETA: 2s - loss: 0.6684 - regression_loss: 0.5892 - classification_loss: 0.0792 493/500 [============================>.] - ETA: 2s - loss: 0.6682 - regression_loss: 0.5890 - classification_loss: 0.0791 494/500 [============================>.] - ETA: 1s - loss: 0.6685 - regression_loss: 0.5894 - classification_loss: 0.0791 495/500 [============================>.] - ETA: 1s - loss: 0.6692 - regression_loss: 0.5900 - classification_loss: 0.0791 496/500 [============================>.] - ETA: 1s - loss: 0.6704 - regression_loss: 0.5911 - classification_loss: 0.0793 497/500 [============================>.] - ETA: 0s - loss: 0.6707 - regression_loss: 0.5915 - classification_loss: 0.0793 498/500 [============================>.] - ETA: 0s - loss: 0.6717 - regression_loss: 0.5924 - classification_loss: 0.0794 499/500 [============================>.] - ETA: 0s - loss: 0.6712 - regression_loss: 0.5919 - classification_loss: 0.0793 500/500 [==============================] - 162s 325ms/step - loss: 0.6711 - regression_loss: 0.5919 - classification_loss: 0.0792 326 instances of class plum with average precision: 0.7618 mAP: 0.7618 Epoch 00030: saving model to ./training/snapshots/resnet101_pascal_30.h5 Epoch 31/150 1/500 [..............................] - ETA: 2:50 - loss: 0.6269 - regression_loss: 0.5730 - classification_loss: 0.0539 2/500 [..............................] - ETA: 2:44 - loss: 0.6591 - regression_loss: 0.6090 - classification_loss: 0.0502 3/500 [..............................] - ETA: 2:41 - loss: 0.8481 - regression_loss: 0.7692 - classification_loss: 0.0789 4/500 [..............................] - ETA: 2:39 - loss: 0.9680 - regression_loss: 0.8452 - classification_loss: 0.1228 5/500 [..............................] - ETA: 2:38 - loss: 1.0722 - regression_loss: 0.9236 - classification_loss: 0.1486 6/500 [..............................] - ETA: 2:38 - loss: 1.0262 - regression_loss: 0.8876 - classification_loss: 0.1386 7/500 [..............................] - ETA: 2:38 - loss: 0.9243 - regression_loss: 0.8000 - classification_loss: 0.1243 8/500 [..............................] - ETA: 2:37 - loss: 0.9062 - regression_loss: 0.7892 - classification_loss: 0.1169 9/500 [..............................] - ETA: 2:36 - loss: 0.8991 - regression_loss: 0.7859 - classification_loss: 0.1132 10/500 [..............................] - ETA: 2:39 - loss: 0.8831 - regression_loss: 0.7750 - classification_loss: 0.1081 11/500 [..............................] - ETA: 2:39 - loss: 0.8358 - regression_loss: 0.7320 - classification_loss: 0.1038 12/500 [..............................] - ETA: 2:40 - loss: 0.8095 - regression_loss: 0.7099 - classification_loss: 0.0997 13/500 [..............................] - ETA: 2:39 - loss: 0.7922 - regression_loss: 0.6967 - classification_loss: 0.0956 14/500 [..............................] - ETA: 2:38 - loss: 0.7634 - regression_loss: 0.6715 - classification_loss: 0.0919 15/500 [..............................] - ETA: 2:37 - loss: 0.7371 - regression_loss: 0.6489 - classification_loss: 0.0882 16/500 [..............................] - ETA: 2:37 - loss: 0.7277 - regression_loss: 0.6363 - classification_loss: 0.0914 17/500 [>.............................] - ETA: 2:37 - loss: 0.7108 - regression_loss: 0.6218 - classification_loss: 0.0890 18/500 [>.............................] - ETA: 2:36 - loss: 0.6886 - regression_loss: 0.6019 - classification_loss: 0.0867 19/500 [>.............................] - ETA: 2:36 - loss: 0.6756 - regression_loss: 0.5912 - classification_loss: 0.0845 20/500 [>.............................] - ETA: 2:36 - loss: 0.6594 - regression_loss: 0.5761 - classification_loss: 0.0833 21/500 [>.............................] - ETA: 2:35 - loss: 0.6333 - regression_loss: 0.5532 - classification_loss: 0.0801 22/500 [>.............................] - ETA: 2:35 - loss: 0.6278 - regression_loss: 0.5501 - classification_loss: 0.0777 23/500 [>.............................] - ETA: 2:34 - loss: 0.6205 - regression_loss: 0.5436 - classification_loss: 0.0769 24/500 [>.............................] - ETA: 2:34 - loss: 0.6225 - regression_loss: 0.5457 - classification_loss: 0.0768 25/500 [>.............................] - ETA: 2:34 - loss: 0.6143 - regression_loss: 0.5387 - classification_loss: 0.0756 26/500 [>.............................] - ETA: 2:33 - loss: 0.6177 - regression_loss: 0.5426 - classification_loss: 0.0751 27/500 [>.............................] - ETA: 2:33 - loss: 0.6234 - regression_loss: 0.5483 - classification_loss: 0.0751 28/500 [>.............................] - ETA: 2:32 - loss: 0.6261 - regression_loss: 0.5510 - classification_loss: 0.0750 29/500 [>.............................] - ETA: 2:32 - loss: 0.6259 - regression_loss: 0.5512 - classification_loss: 0.0747 30/500 [>.............................] - ETA: 2:32 - loss: 0.6193 - regression_loss: 0.5459 - classification_loss: 0.0734 31/500 [>.............................] - ETA: 2:31 - loss: 0.6074 - regression_loss: 0.5353 - classification_loss: 0.0721 32/500 [>.............................] - ETA: 2:31 - loss: 0.6108 - regression_loss: 0.5396 - classification_loss: 0.0712 33/500 [>.............................] - ETA: 2:31 - loss: 0.6123 - regression_loss: 0.5411 - classification_loss: 0.0712 34/500 [=>............................] - ETA: 2:31 - loss: 0.6051 - regression_loss: 0.5352 - classification_loss: 0.0699 35/500 [=>............................] - ETA: 2:30 - loss: 0.6008 - regression_loss: 0.5316 - classification_loss: 0.0692 36/500 [=>............................] - ETA: 2:31 - loss: 0.5963 - regression_loss: 0.5279 - classification_loss: 0.0684 37/500 [=>............................] - ETA: 2:30 - loss: 0.5925 - regression_loss: 0.5250 - classification_loss: 0.0675 38/500 [=>............................] - ETA: 2:30 - loss: 0.5966 - regression_loss: 0.5278 - classification_loss: 0.0688 39/500 [=>............................] - ETA: 2:29 - loss: 0.5978 - regression_loss: 0.5291 - classification_loss: 0.0687 40/500 [=>............................] - ETA: 2:29 - loss: 0.6106 - regression_loss: 0.5364 - classification_loss: 0.0742 41/500 [=>............................] - ETA: 2:29 - loss: 0.6096 - regression_loss: 0.5357 - classification_loss: 0.0739 42/500 [=>............................] - ETA: 2:28 - loss: 0.6079 - regression_loss: 0.5347 - classification_loss: 0.0731 43/500 [=>............................] - ETA: 2:28 - loss: 0.6125 - regression_loss: 0.5385 - classification_loss: 0.0740 44/500 [=>............................] - ETA: 2:28 - loss: 0.6187 - regression_loss: 0.5422 - classification_loss: 0.0765 45/500 [=>............................] - ETA: 2:28 - loss: 0.6216 - regression_loss: 0.5450 - classification_loss: 0.0766 46/500 [=>............................] - ETA: 2:27 - loss: 0.6272 - regression_loss: 0.5495 - classification_loss: 0.0776 47/500 [=>............................] - ETA: 2:27 - loss: 0.6260 - regression_loss: 0.5487 - classification_loss: 0.0773 48/500 [=>............................] - ETA: 2:26 - loss: 0.6209 - regression_loss: 0.5444 - classification_loss: 0.0765 49/500 [=>............................] - ETA: 2:26 - loss: 0.6161 - regression_loss: 0.5404 - classification_loss: 0.0757 50/500 [==>...........................] - ETA: 2:26 - loss: 0.6109 - regression_loss: 0.5356 - classification_loss: 0.0753 51/500 [==>...........................] - ETA: 2:25 - loss: 0.6085 - regression_loss: 0.5324 - classification_loss: 0.0761 52/500 [==>...........................] - ETA: 2:25 - loss: 0.6112 - regression_loss: 0.5338 - classification_loss: 0.0775 53/500 [==>...........................] - ETA: 2:24 - loss: 0.6060 - regression_loss: 0.5294 - classification_loss: 0.0766 54/500 [==>...........................] - ETA: 2:24 - loss: 0.6033 - regression_loss: 0.5269 - classification_loss: 0.0764 55/500 [==>...........................] - ETA: 2:24 - loss: 0.5954 - regression_loss: 0.5200 - classification_loss: 0.0754 56/500 [==>...........................] - ETA: 2:24 - loss: 0.5896 - regression_loss: 0.5151 - classification_loss: 0.0746 57/500 [==>...........................] - ETA: 2:24 - loss: 0.5882 - regression_loss: 0.5139 - classification_loss: 0.0743 58/500 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[===>..........................] - ETA: 2:15 - loss: 0.6063 - regression_loss: 0.5305 - classification_loss: 0.0758 83/500 [===>..........................] - ETA: 2:15 - loss: 0.6024 - regression_loss: 0.5269 - classification_loss: 0.0755 84/500 [====>.........................] - ETA: 2:15 - loss: 0.6058 - regression_loss: 0.5300 - classification_loss: 0.0758 85/500 [====>.........................] - ETA: 2:14 - loss: 0.6042 - regression_loss: 0.5285 - classification_loss: 0.0757 86/500 [====>.........................] - ETA: 2:14 - loss: 0.6015 - regression_loss: 0.5265 - classification_loss: 0.0751 87/500 [====>.........................] - ETA: 2:14 - loss: 0.5984 - regression_loss: 0.5238 - classification_loss: 0.0746 88/500 [====>.........................] - ETA: 2:13 - loss: 0.5997 - regression_loss: 0.5247 - classification_loss: 0.0749 89/500 [====>.........................] - ETA: 2:13 - loss: 0.5987 - regression_loss: 0.5242 - classification_loss: 0.0746 90/500 [====>.........................] - ETA: 2:12 - loss: 0.5951 - regression_loss: 0.5212 - classification_loss: 0.0740 91/500 [====>.........................] - ETA: 2:12 - loss: 0.5946 - regression_loss: 0.5209 - classification_loss: 0.0737 92/500 [====>.........................] - ETA: 2:12 - loss: 0.5940 - regression_loss: 0.5207 - classification_loss: 0.0732 93/500 [====>.........................] - ETA: 2:11 - loss: 0.5916 - regression_loss: 0.5188 - classification_loss: 0.0729 94/500 [====>.........................] - ETA: 2:11 - loss: 0.5876 - regression_loss: 0.5153 - classification_loss: 0.0723 95/500 [====>.........................] - ETA: 2:11 - loss: 0.5910 - regression_loss: 0.5179 - classification_loss: 0.0731 96/500 [====>.........................] - ETA: 2:10 - loss: 0.5975 - regression_loss: 0.5235 - classification_loss: 0.0740 97/500 [====>.........................] - ETA: 2:10 - loss: 0.5998 - regression_loss: 0.5259 - classification_loss: 0.0740 98/500 [====>.........................] - ETA: 2:10 - loss: 0.5975 - regression_loss: 0.5239 - classification_loss: 0.0736 99/500 [====>.........................] - ETA: 2:09 - loss: 0.6060 - regression_loss: 0.5309 - classification_loss: 0.0752 100/500 [=====>........................] - ETA: 2:09 - loss: 0.6075 - regression_loss: 0.5325 - classification_loss: 0.0751 101/500 [=====>........................] - ETA: 2:09 - loss: 0.6086 - regression_loss: 0.5336 - classification_loss: 0.0749 102/500 [=====>........................] - ETA: 2:08 - loss: 0.6099 - regression_loss: 0.5349 - classification_loss: 0.0750 103/500 [=====>........................] - ETA: 2:08 - loss: 0.6083 - regression_loss: 0.5337 - classification_loss: 0.0746 104/500 [=====>........................] - ETA: 2:08 - loss: 0.6145 - regression_loss: 0.5390 - classification_loss: 0.0755 105/500 [=====>........................] - ETA: 2:07 - loss: 0.6156 - regression_loss: 0.5403 - classification_loss: 0.0753 106/500 [=====>........................] - ETA: 2:07 - loss: 0.6152 - regression_loss: 0.5402 - classification_loss: 0.0750 107/500 [=====>........................] - ETA: 2:07 - loss: 0.6113 - regression_loss: 0.5368 - classification_loss: 0.0745 108/500 [=====>........................] - ETA: 2:06 - loss: 0.6132 - regression_loss: 0.5386 - classification_loss: 0.0746 109/500 [=====>........................] - ETA: 2:06 - loss: 0.6127 - regression_loss: 0.5383 - classification_loss: 0.0744 110/500 [=====>........................] - ETA: 2:06 - loss: 0.6111 - regression_loss: 0.5369 - classification_loss: 0.0742 111/500 [=====>........................] - ETA: 2:06 - loss: 0.6128 - regression_loss: 0.5382 - classification_loss: 0.0746 112/500 [=====>........................] - ETA: 2:05 - loss: 0.6197 - regression_loss: 0.5438 - classification_loss: 0.0759 113/500 [=====>........................] - ETA: 2:05 - loss: 0.6196 - regression_loss: 0.5438 - classification_loss: 0.0758 114/500 [=====>........................] - ETA: 2:05 - loss: 0.6215 - regression_loss: 0.5453 - classification_loss: 0.0762 115/500 [=====>........................] - ETA: 2:04 - loss: 0.6196 - regression_loss: 0.5435 - classification_loss: 0.0761 116/500 [=====>........................] - ETA: 2:04 - loss: 0.6187 - regression_loss: 0.5430 - classification_loss: 0.0757 117/500 [======>.......................] - ETA: 2:04 - loss: 0.6166 - regression_loss: 0.5412 - classification_loss: 0.0754 118/500 [======>.......................] - ETA: 2:03 - loss: 0.6135 - regression_loss: 0.5384 - classification_loss: 0.0751 119/500 [======>.......................] - ETA: 2:03 - loss: 0.6118 - regression_loss: 0.5370 - classification_loss: 0.0748 120/500 [======>.......................] - ETA: 2:03 - loss: 0.6105 - regression_loss: 0.5358 - classification_loss: 0.0746 121/500 [======>.......................] - ETA: 2:02 - loss: 0.6100 - regression_loss: 0.5354 - classification_loss: 0.0746 122/500 [======>.......................] - ETA: 2:02 - loss: 0.6098 - regression_loss: 0.5352 - classification_loss: 0.0745 123/500 [======>.......................] - ETA: 2:02 - loss: 0.6086 - regression_loss: 0.5343 - classification_loss: 0.0743 124/500 [======>.......................] - ETA: 2:01 - loss: 0.6119 - regression_loss: 0.5369 - classification_loss: 0.0750 125/500 [======>.......................] - ETA: 2:01 - loss: 0.6158 - regression_loss: 0.5402 - classification_loss: 0.0755 126/500 [======>.......................] - ETA: 2:01 - loss: 0.6152 - regression_loss: 0.5395 - classification_loss: 0.0757 127/500 [======>.......................] - ETA: 2:00 - loss: 0.6141 - regression_loss: 0.5385 - classification_loss: 0.0756 128/500 [======>.......................] - ETA: 2:00 - loss: 0.6120 - regression_loss: 0.5369 - classification_loss: 0.0751 129/500 [======>.......................] - ETA: 2:00 - loss: 0.6101 - regression_loss: 0.5353 - classification_loss: 0.0748 130/500 [======>.......................] - ETA: 1:59 - loss: 0.6074 - regression_loss: 0.5327 - classification_loss: 0.0747 131/500 [======>.......................] - ETA: 1:59 - loss: 0.6040 - regression_loss: 0.5296 - classification_loss: 0.0743 132/500 [======>.......................] - ETA: 1:59 - loss: 0.6054 - regression_loss: 0.5311 - classification_loss: 0.0742 133/500 [======>.......................] - ETA: 1:58 - loss: 0.6040 - regression_loss: 0.5299 - classification_loss: 0.0741 134/500 [=======>......................] - ETA: 1:58 - loss: 0.6035 - regression_loss: 0.5295 - classification_loss: 0.0740 135/500 [=======>......................] - ETA: 1:58 - loss: 0.6010 - regression_loss: 0.5274 - classification_loss: 0.0736 136/500 [=======>......................] - ETA: 1:57 - loss: 0.6004 - regression_loss: 0.5270 - classification_loss: 0.0735 137/500 [=======>......................] - ETA: 1:57 - loss: 0.5984 - regression_loss: 0.5252 - classification_loss: 0.0732 138/500 [=======>......................] - ETA: 1:57 - loss: 0.6028 - regression_loss: 0.5290 - classification_loss: 0.0738 139/500 [=======>......................] - ETA: 1:57 - loss: 0.6018 - regression_loss: 0.5283 - classification_loss: 0.0735 140/500 [=======>......................] - ETA: 1:56 - loss: 0.6027 - regression_loss: 0.5292 - classification_loss: 0.0735 141/500 [=======>......................] - ETA: 1:56 - loss: 0.6110 - regression_loss: 0.5351 - classification_loss: 0.0760 142/500 [=======>......................] - ETA: 1:56 - loss: 0.6147 - regression_loss: 0.5388 - classification_loss: 0.0759 143/500 [=======>......................] - ETA: 1:55 - loss: 0.6151 - regression_loss: 0.5391 - classification_loss: 0.0760 144/500 [=======>......................] - ETA: 1:55 - loss: 0.6136 - regression_loss: 0.5378 - classification_loss: 0.0758 145/500 [=======>......................] - ETA: 1:55 - loss: 0.6130 - regression_loss: 0.5374 - classification_loss: 0.0756 146/500 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[=========>....................] - ETA: 1:44 - loss: 0.6199 - regression_loss: 0.5450 - classification_loss: 0.0749 179/500 [=========>....................] - ETA: 1:43 - loss: 0.6195 - regression_loss: 0.5446 - classification_loss: 0.0749 180/500 [=========>....................] - ETA: 1:43 - loss: 0.6228 - regression_loss: 0.5481 - classification_loss: 0.0747 181/500 [=========>....................] - ETA: 1:43 - loss: 0.6250 - regression_loss: 0.5498 - classification_loss: 0.0752 182/500 [=========>....................] - ETA: 1:42 - loss: 0.6277 - regression_loss: 0.5521 - classification_loss: 0.0756 183/500 [=========>....................] - ETA: 1:42 - loss: 0.6282 - regression_loss: 0.5526 - classification_loss: 0.0756 184/500 [==========>...................] - ETA: 1:42 - loss: 0.6274 - regression_loss: 0.5519 - classification_loss: 0.0755 185/500 [==========>...................] - ETA: 1:41 - loss: 0.6261 - regression_loss: 0.5508 - classification_loss: 0.0753 186/500 [==========>...................] - ETA: 1:41 - loss: 0.6233 - regression_loss: 0.5484 - classification_loss: 0.0750 187/500 [==========>...................] - ETA: 1:41 - loss: 0.6218 - regression_loss: 0.5469 - classification_loss: 0.0749 188/500 [==========>...................] - ETA: 1:40 - loss: 0.6209 - regression_loss: 0.5461 - classification_loss: 0.0748 189/500 [==========>...................] - ETA: 1:40 - loss: 0.6213 - regression_loss: 0.5465 - classification_loss: 0.0747 190/500 [==========>...................] - ETA: 1:40 - loss: 0.6217 - regression_loss: 0.5469 - classification_loss: 0.0748 191/500 [==========>...................] - ETA: 1:39 - loss: 0.6224 - regression_loss: 0.5476 - classification_loss: 0.0748 192/500 [==========>...................] - ETA: 1:39 - loss: 0.6226 - regression_loss: 0.5479 - classification_loss: 0.0746 193/500 [==========>...................] - ETA: 1:39 - loss: 0.6221 - regression_loss: 0.5475 - classification_loss: 0.0746 194/500 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[===========>..................] - ETA: 1:36 - loss: 0.6223 - regression_loss: 0.5475 - classification_loss: 0.0748 203/500 [===========>..................] - ETA: 1:35 - loss: 0.6218 - regression_loss: 0.5471 - classification_loss: 0.0747 204/500 [===========>..................] - ETA: 1:35 - loss: 0.6207 - regression_loss: 0.5461 - classification_loss: 0.0745 205/500 [===========>..................] - ETA: 1:35 - loss: 0.6207 - regression_loss: 0.5462 - classification_loss: 0.0745 206/500 [===========>..................] - ETA: 1:34 - loss: 0.6201 - regression_loss: 0.5456 - classification_loss: 0.0745 207/500 [===========>..................] - ETA: 1:34 - loss: 0.6196 - regression_loss: 0.5452 - classification_loss: 0.0744 208/500 [===========>..................] - ETA: 1:34 - loss: 0.6195 - regression_loss: 0.5448 - classification_loss: 0.0747 209/500 [===========>..................] - ETA: 1:34 - loss: 0.6203 - regression_loss: 0.5455 - classification_loss: 0.0748 210/500 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[============================>.] - ETA: 3s - loss: 0.6282 - regression_loss: 0.5555 - classification_loss: 0.0728 491/500 [============================>.] - ETA: 2s - loss: 0.6277 - regression_loss: 0.5550 - classification_loss: 0.0727 492/500 [============================>.] - ETA: 2s - loss: 0.6273 - regression_loss: 0.5547 - classification_loss: 0.0726 493/500 [============================>.] - ETA: 2s - loss: 0.6272 - regression_loss: 0.5546 - classification_loss: 0.0726 494/500 [============================>.] - ETA: 1s - loss: 0.6292 - regression_loss: 0.5561 - classification_loss: 0.0732 495/500 [============================>.] - ETA: 1s - loss: 0.6295 - regression_loss: 0.5563 - classification_loss: 0.0732 496/500 [============================>.] - ETA: 1s - loss: 0.6295 - regression_loss: 0.5564 - classification_loss: 0.0731 497/500 [============================>.] - ETA: 0s - loss: 0.6303 - regression_loss: 0.5572 - classification_loss: 0.0731 498/500 [============================>.] - ETA: 0s - loss: 0.6302 - regression_loss: 0.5572 - classification_loss: 0.0730 499/500 [============================>.] - ETA: 0s - loss: 0.6299 - regression_loss: 0.5570 - classification_loss: 0.0730 500/500 [==============================] - 162s 323ms/step - loss: 0.6311 - regression_loss: 0.5578 - classification_loss: 0.0733 326 instances of class plum with average precision: 0.7807 mAP: 0.7807 Epoch 00031: saving model to ./training/snapshots/resnet101_pascal_31.h5 Epoch 32/150 1/500 [..............................] - ETA: 2:31 - loss: 1.0815 - regression_loss: 0.9259 - classification_loss: 0.1556 2/500 [..............................] - ETA: 2:33 - loss: 0.6863 - regression_loss: 0.5918 - classification_loss: 0.0945 3/500 [..............................] - ETA: 2:35 - loss: 0.8540 - regression_loss: 0.7214 - classification_loss: 0.1326 4/500 [..............................] - ETA: 2:36 - loss: 0.8228 - regression_loss: 0.7071 - classification_loss: 0.1157 5/500 [..............................] - ETA: 2:39 - loss: 0.7566 - regression_loss: 0.6565 - classification_loss: 0.1001 6/500 [..............................] - ETA: 2:39 - loss: 0.6876 - regression_loss: 0.5998 - classification_loss: 0.0878 7/500 [..............................] - ETA: 2:38 - loss: 0.6624 - regression_loss: 0.5795 - classification_loss: 0.0829 8/500 [..............................] - ETA: 2:37 - loss: 0.6694 - regression_loss: 0.5888 - classification_loss: 0.0807 9/500 [..............................] - ETA: 2:38 - loss: 0.6850 - regression_loss: 0.6011 - classification_loss: 0.0839 10/500 [..............................] - ETA: 2:37 - loss: 0.6542 - regression_loss: 0.5750 - classification_loss: 0.0792 11/500 [..............................] - ETA: 2:37 - loss: 0.7520 - regression_loss: 0.6509 - classification_loss: 0.1010 12/500 [..............................] - ETA: 2:36 - loss: 0.7325 - regression_loss: 0.6368 - classification_loss: 0.0958 13/500 [..............................] - ETA: 2:35 - loss: 0.7146 - regression_loss: 0.6215 - classification_loss: 0.0930 14/500 [..............................] - ETA: 2:35 - loss: 0.7124 - regression_loss: 0.6223 - classification_loss: 0.0901 15/500 [..............................] - ETA: 2:35 - loss: 0.6940 - regression_loss: 0.6027 - classification_loss: 0.0913 16/500 [..............................] - ETA: 2:35 - loss: 0.7045 - regression_loss: 0.6138 - classification_loss: 0.0907 17/500 [>.............................] - ETA: 2:34 - loss: 0.6851 - regression_loss: 0.5961 - classification_loss: 0.0890 18/500 [>.............................] - ETA: 2:33 - loss: 0.7201 - regression_loss: 0.6269 - classification_loss: 0.0932 19/500 [>.............................] - ETA: 2:33 - loss: 0.7152 - regression_loss: 0.6233 - classification_loss: 0.0919 20/500 [>.............................] - ETA: 2:34 - loss: 0.6998 - regression_loss: 0.6107 - classification_loss: 0.0891 21/500 [>.............................] - ETA: 2:34 - loss: 0.6938 - regression_loss: 0.6058 - classification_loss: 0.0880 22/500 [>.............................] - ETA: 2:33 - loss: 0.6920 - regression_loss: 0.6053 - classification_loss: 0.0868 23/500 [>.............................] - ETA: 2:33 - loss: 0.6810 - regression_loss: 0.5961 - classification_loss: 0.0849 24/500 [>.............................] - ETA: 2:32 - loss: 0.6685 - regression_loss: 0.5855 - classification_loss: 0.0831 25/500 [>.............................] - ETA: 2:32 - loss: 0.6567 - regression_loss: 0.5742 - classification_loss: 0.0826 26/500 [>.............................] - ETA: 2:32 - loss: 0.6777 - regression_loss: 0.5925 - classification_loss: 0.0853 27/500 [>.............................] - ETA: 2:31 - loss: 0.6672 - regression_loss: 0.5839 - classification_loss: 0.0833 28/500 [>.............................] - ETA: 2:31 - loss: 0.6882 - regression_loss: 0.6028 - classification_loss: 0.0854 29/500 [>.............................] - ETA: 2:31 - loss: 0.6820 - regression_loss: 0.5981 - classification_loss: 0.0839 30/500 [>.............................] - ETA: 2:30 - loss: 0.6770 - regression_loss: 0.5945 - classification_loss: 0.0824 31/500 [>.............................] - ETA: 2:30 - loss: 0.6744 - regression_loss: 0.5922 - classification_loss: 0.0823 32/500 [>.............................] - ETA: 2:30 - loss: 0.6745 - regression_loss: 0.5935 - classification_loss: 0.0810 33/500 [>.............................] - ETA: 2:30 - loss: 0.6716 - regression_loss: 0.5908 - classification_loss: 0.0808 34/500 [=>............................] - ETA: 2:30 - loss: 0.6653 - regression_loss: 0.5862 - classification_loss: 0.0791 35/500 [=>............................] - ETA: 2:29 - loss: 0.6647 - regression_loss: 0.5861 - classification_loss: 0.0786 36/500 [=>............................] - ETA: 2:29 - loss: 0.6604 - regression_loss: 0.5828 - classification_loss: 0.0777 37/500 [=>............................] - ETA: 2:29 - loss: 0.6590 - regression_loss: 0.5818 - classification_loss: 0.0772 38/500 [=>............................] - ETA: 2:29 - loss: 0.6530 - regression_loss: 0.5767 - classification_loss: 0.0763 39/500 [=>............................] - ETA: 2:29 - loss: 0.6502 - regression_loss: 0.5744 - classification_loss: 0.0759 40/500 [=>............................] - ETA: 2:28 - loss: 0.6456 - regression_loss: 0.5698 - classification_loss: 0.0757 41/500 [=>............................] - ETA: 2:28 - loss: 0.6476 - regression_loss: 0.5718 - classification_loss: 0.0758 42/500 [=>............................] - ETA: 2:27 - loss: 0.6406 - regression_loss: 0.5660 - classification_loss: 0.0746 43/500 [=>............................] - ETA: 2:27 - loss: 0.6406 - regression_loss: 0.5665 - classification_loss: 0.0741 44/500 [=>............................] - ETA: 2:27 - loss: 0.6379 - regression_loss: 0.5641 - classification_loss: 0.0738 45/500 [=>............................] - ETA: 2:27 - loss: 0.6318 - regression_loss: 0.5589 - classification_loss: 0.0729 46/500 [=>............................] - ETA: 2:27 - loss: 0.6256 - regression_loss: 0.5539 - classification_loss: 0.0717 47/500 [=>............................] - ETA: 2:27 - loss: 0.6218 - regression_loss: 0.5506 - classification_loss: 0.0712 48/500 [=>............................] - ETA: 2:26 - loss: 0.6248 - regression_loss: 0.5537 - classification_loss: 0.0711 49/500 [=>............................] - ETA: 2:26 - loss: 0.6190 - regression_loss: 0.5476 - classification_loss: 0.0714 50/500 [==>...........................] - ETA: 2:26 - loss: 0.6179 - regression_loss: 0.5459 - classification_loss: 0.0720 51/500 [==>...........................] - ETA: 2:25 - loss: 0.6192 - regression_loss: 0.5470 - classification_loss: 0.0721 52/500 [==>...........................] - ETA: 2:25 - loss: 0.6160 - regression_loss: 0.5444 - classification_loss: 0.0716 53/500 [==>...........................] - ETA: 2:24 - loss: 0.6183 - regression_loss: 0.5470 - classification_loss: 0.0713 54/500 [==>...........................] - ETA: 2:24 - loss: 0.6165 - regression_loss: 0.5454 - classification_loss: 0.0711 55/500 [==>...........................] - ETA: 2:24 - loss: 0.6100 - regression_loss: 0.5397 - classification_loss: 0.0703 56/500 [==>...........................] - ETA: 2:23 - loss: 0.6083 - regression_loss: 0.5384 - classification_loss: 0.0699 57/500 [==>...........................] - ETA: 2:23 - loss: 0.6007 - regression_loss: 0.5316 - classification_loss: 0.0690 58/500 [==>...........................] - ETA: 2:23 - loss: 0.6058 - regression_loss: 0.5369 - classification_loss: 0.0689 59/500 [==>...........................] - ETA: 2:23 - loss: 0.6175 - regression_loss: 0.5474 - classification_loss: 0.0701 60/500 [==>...........................] - ETA: 2:23 - loss: 0.6155 - regression_loss: 0.5451 - classification_loss: 0.0704 61/500 [==>...........................] - ETA: 2:22 - loss: 0.6128 - regression_loss: 0.5429 - classification_loss: 0.0698 62/500 [==>...........................] - ETA: 2:22 - loss: 0.6109 - regression_loss: 0.5414 - classification_loss: 0.0695 63/500 [==>...........................] - ETA: 2:21 - loss: 0.6180 - regression_loss: 0.5474 - classification_loss: 0.0706 64/500 [==>...........................] - ETA: 2:21 - loss: 0.6129 - regression_loss: 0.5428 - classification_loss: 0.0701 65/500 [==>...........................] - ETA: 2:21 - loss: 0.6100 - regression_loss: 0.5403 - classification_loss: 0.0697 66/500 [==>...........................] - ETA: 2:20 - loss: 0.6071 - regression_loss: 0.5379 - classification_loss: 0.0693 67/500 [===>..........................] - ETA: 2:20 - loss: 0.6051 - regression_loss: 0.5360 - classification_loss: 0.0691 68/500 [===>..........................] - ETA: 2:20 - loss: 0.6003 - regression_loss: 0.5318 - classification_loss: 0.0685 69/500 [===>..........................] - ETA: 2:20 - loss: 0.5959 - regression_loss: 0.5279 - classification_loss: 0.0679 70/500 [===>..........................] - ETA: 2:19 - loss: 0.5950 - regression_loss: 0.5273 - classification_loss: 0.0677 71/500 [===>..........................] - ETA: 2:19 - loss: 0.5924 - regression_loss: 0.5252 - classification_loss: 0.0672 72/500 [===>..........................] - ETA: 2:19 - loss: 0.5896 - regression_loss: 0.5229 - classification_loss: 0.0667 73/500 [===>..........................] - ETA: 2:18 - loss: 0.5834 - regression_loss: 0.5174 - classification_loss: 0.0660 74/500 [===>..........................] - ETA: 2:18 - loss: 0.5830 - regression_loss: 0.5170 - classification_loss: 0.0659 75/500 [===>..........................] - ETA: 2:18 - loss: 0.5873 - regression_loss: 0.5210 - classification_loss: 0.0663 76/500 [===>..........................] - ETA: 2:17 - loss: 0.5830 - regression_loss: 0.5171 - classification_loss: 0.0659 77/500 [===>..........................] - ETA: 2:17 - loss: 0.5902 - regression_loss: 0.5232 - classification_loss: 0.0671 78/500 [===>..........................] - ETA: 2:17 - loss: 0.5867 - regression_loss: 0.5202 - classification_loss: 0.0665 79/500 [===>..........................] - ETA: 2:16 - loss: 0.5834 - regression_loss: 0.5172 - classification_loss: 0.0662 80/500 [===>..........................] - ETA: 2:16 - loss: 0.5831 - regression_loss: 0.5171 - classification_loss: 0.0660 81/500 [===>..........................] - ETA: 2:15 - loss: 0.5833 - regression_loss: 0.5173 - classification_loss: 0.0659 82/500 [===>..........................] - ETA: 2:15 - loss: 0.5907 - regression_loss: 0.5235 - classification_loss: 0.0672 83/500 [===>..........................] - ETA: 2:15 - loss: 0.5896 - regression_loss: 0.5224 - classification_loss: 0.0672 84/500 [====>.........................] - ETA: 2:15 - loss: 0.5865 - regression_loss: 0.5199 - classification_loss: 0.0667 85/500 [====>.........................] - ETA: 2:14 - loss: 0.5876 - regression_loss: 0.5207 - classification_loss: 0.0669 86/500 [====>.........................] - ETA: 2:14 - loss: 0.5881 - regression_loss: 0.5214 - classification_loss: 0.0666 87/500 [====>.........................] - ETA: 2:14 - loss: 0.5884 - regression_loss: 0.5219 - classification_loss: 0.0665 88/500 [====>.........................] - ETA: 2:13 - loss: 0.5913 - regression_loss: 0.5245 - classification_loss: 0.0668 89/500 [====>.........................] - ETA: 2:13 - loss: 0.5892 - regression_loss: 0.5227 - classification_loss: 0.0665 90/500 [====>.........................] - ETA: 2:13 - loss: 0.5872 - regression_loss: 0.5207 - classification_loss: 0.0665 91/500 [====>.........................] - ETA: 2:12 - loss: 0.5839 - regression_loss: 0.5180 - classification_loss: 0.0659 92/500 [====>.........................] - ETA: 2:12 - loss: 0.5821 - regression_loss: 0.5162 - classification_loss: 0.0659 93/500 [====>.........................] - ETA: 2:12 - loss: 0.5796 - regression_loss: 0.5142 - classification_loss: 0.0654 94/500 [====>.........................] - ETA: 2:11 - loss: 0.5828 - regression_loss: 0.5171 - classification_loss: 0.0658 95/500 [====>.........................] - ETA: 2:11 - loss: 0.5789 - regression_loss: 0.5136 - classification_loss: 0.0653 96/500 [====>.........................] - ETA: 2:11 - loss: 0.5796 - regression_loss: 0.5145 - classification_loss: 0.0651 97/500 [====>.........................] - ETA: 2:10 - loss: 0.5767 - regression_loss: 0.5119 - classification_loss: 0.0648 98/500 [====>.........................] - ETA: 2:10 - loss: 0.5769 - regression_loss: 0.5123 - classification_loss: 0.0646 99/500 [====>.........................] - ETA: 2:10 - loss: 0.5730 - regression_loss: 0.5088 - classification_loss: 0.0641 100/500 [=====>........................] - ETA: 2:09 - loss: 0.5752 - regression_loss: 0.5108 - classification_loss: 0.0644 101/500 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[============================>.] - ETA: 2s - loss: 0.6165 - regression_loss: 0.5449 - classification_loss: 0.0715 494/500 [============================>.] - ETA: 1s - loss: 0.6164 - regression_loss: 0.5449 - classification_loss: 0.0715 495/500 [============================>.] - ETA: 1s - loss: 0.6175 - regression_loss: 0.5458 - classification_loss: 0.0716 496/500 [============================>.] - ETA: 1s - loss: 0.6175 - regression_loss: 0.5459 - classification_loss: 0.0715 497/500 [============================>.] - ETA: 0s - loss: 0.6174 - regression_loss: 0.5459 - classification_loss: 0.0715 498/500 [============================>.] - ETA: 0s - loss: 0.6173 - regression_loss: 0.5458 - classification_loss: 0.0715 499/500 [============================>.] - ETA: 0s - loss: 0.6182 - regression_loss: 0.5466 - classification_loss: 0.0716 500/500 [==============================] - 162s 324ms/step - loss: 0.6176 - regression_loss: 0.5461 - classification_loss: 0.0715 326 instances of class plum with average precision: 0.7875 mAP: 0.7875 Epoch 00032: saving model to ./training/snapshots/resnet101_pascal_32.h5 Epoch 33/150 1/500 [..............................] - ETA: 2:28 - loss: 0.7630 - regression_loss: 0.6124 - classification_loss: 0.1506 2/500 [..............................] - ETA: 2:30 - loss: 0.6275 - regression_loss: 0.5403 - classification_loss: 0.0873 3/500 [..............................] - ETA: 2:31 - loss: 0.6439 - regression_loss: 0.5638 - classification_loss: 0.0802 4/500 [..............................] - ETA: 2:33 - loss: 0.7450 - regression_loss: 0.6512 - classification_loss: 0.0938 5/500 [..............................] - ETA: 2:35 - loss: 0.9450 - regression_loss: 0.7842 - classification_loss: 0.1607 6/500 [..............................] - ETA: 2:37 - loss: 0.9285 - regression_loss: 0.7774 - classification_loss: 0.1512 7/500 [..............................] - ETA: 2:39 - loss: 0.8810 - regression_loss: 0.7435 - classification_loss: 0.1376 8/500 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[============================>.] - ETA: 3s - loss: 0.6138 - regression_loss: 0.5430 - classification_loss: 0.0708 489/500 [============================>.] - ETA: 3s - loss: 0.6137 - regression_loss: 0.5429 - classification_loss: 0.0708 490/500 [============================>.] - ETA: 3s - loss: 0.6136 - regression_loss: 0.5428 - classification_loss: 0.0708 491/500 [============================>.] - ETA: 2s - loss: 0.6133 - regression_loss: 0.5426 - classification_loss: 0.0708 492/500 [============================>.] - ETA: 2s - loss: 0.6129 - regression_loss: 0.5422 - classification_loss: 0.0707 493/500 [============================>.] - ETA: 2s - loss: 0.6127 - regression_loss: 0.5420 - classification_loss: 0.0707 494/500 [============================>.] - ETA: 1s - loss: 0.6125 - regression_loss: 0.5419 - classification_loss: 0.0706 495/500 [============================>.] - ETA: 1s - loss: 0.6120 - regression_loss: 0.5415 - classification_loss: 0.0706 496/500 [============================>.] - ETA: 1s - loss: 0.6118 - regression_loss: 0.5413 - classification_loss: 0.0705 497/500 [============================>.] - ETA: 0s - loss: 0.6127 - regression_loss: 0.5420 - classification_loss: 0.0707 498/500 [============================>.] - ETA: 0s - loss: 0.6125 - regression_loss: 0.5418 - classification_loss: 0.0707 499/500 [============================>.] - ETA: 0s - loss: 0.6127 - regression_loss: 0.5421 - classification_loss: 0.0706 500/500 [==============================] - 162s 325ms/step - loss: 0.6134 - regression_loss: 0.5427 - classification_loss: 0.0707 326 instances of class plum with average precision: 0.7749 mAP: 0.7749 Epoch 00033: saving model to ./training/snapshots/resnet101_pascal_33.h5 Epoch 34/150 1/500 [..............................] - ETA: 2:29 - loss: 0.2996 - regression_loss: 0.2611 - classification_loss: 0.0385 2/500 [..............................] - ETA: 2:30 - loss: 0.7645 - regression_loss: 0.6227 - 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0.0671 11/500 [..............................] - ETA: 2:35 - loss: 0.5985 - regression_loss: 0.5330 - classification_loss: 0.0655 12/500 [..............................] - ETA: 2:34 - loss: 0.5985 - regression_loss: 0.5337 - classification_loss: 0.0648 13/500 [..............................] - ETA: 2:33 - loss: 0.5994 - regression_loss: 0.5320 - classification_loss: 0.0674 14/500 [..............................] - ETA: 2:33 - loss: 0.6346 - regression_loss: 0.5626 - classification_loss: 0.0720 15/500 [..............................] - ETA: 2:32 - loss: 0.6115 - regression_loss: 0.5422 - classification_loss: 0.0693 16/500 [..............................] - ETA: 2:32 - loss: 0.5874 - regression_loss: 0.5207 - classification_loss: 0.0667 17/500 [>.............................] - ETA: 2:32 - loss: 0.5778 - regression_loss: 0.5130 - classification_loss: 0.0648 18/500 [>.............................] - ETA: 2:32 - loss: 0.5707 - regression_loss: 0.5073 - classification_loss: 0.0634 19/500 [>.............................] - ETA: 2:32 - loss: 0.5519 - regression_loss: 0.4898 - classification_loss: 0.0621 20/500 [>.............................] - ETA: 2:31 - loss: 0.5448 - regression_loss: 0.4838 - classification_loss: 0.0610 21/500 [>.............................] - ETA: 2:31 - loss: 0.5385 - regression_loss: 0.4788 - classification_loss: 0.0597 22/500 [>.............................] - ETA: 2:31 - loss: 0.5389 - regression_loss: 0.4790 - classification_loss: 0.0599 23/500 [>.............................] - ETA: 2:31 - loss: 0.5243 - regression_loss: 0.4659 - classification_loss: 0.0584 24/500 [>.............................] - ETA: 2:32 - loss: 0.5354 - regression_loss: 0.4754 - classification_loss: 0.0600 25/500 [>.............................] - ETA: 2:31 - loss: 0.5295 - regression_loss: 0.4693 - classification_loss: 0.0602 26/500 [>.............................] - ETA: 2:31 - loss: 0.5243 - regression_loss: 0.4652 - classification_loss: 0.0590 27/500 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[==>...........................] - ETA: 2:24 - loss: 0.5102 - regression_loss: 0.4527 - classification_loss: 0.0575 52/500 [==>...........................] - ETA: 2:24 - loss: 0.5076 - regression_loss: 0.4506 - classification_loss: 0.0569 53/500 [==>...........................] - ETA: 2:24 - loss: 0.5071 - regression_loss: 0.4502 - classification_loss: 0.0569 54/500 [==>...........................] - ETA: 2:23 - loss: 0.5121 - regression_loss: 0.4545 - classification_loss: 0.0576 55/500 [==>...........................] - ETA: 2:23 - loss: 0.5074 - regression_loss: 0.4501 - classification_loss: 0.0573 56/500 [==>...........................] - ETA: 2:23 - loss: 0.5051 - regression_loss: 0.4483 - classification_loss: 0.0567 57/500 [==>...........................] - ETA: 2:22 - loss: 0.5044 - regression_loss: 0.4482 - classification_loss: 0.0562 58/500 [==>...........................] - ETA: 2:22 - loss: 0.5210 - regression_loss: 0.4618 - classification_loss: 0.0592 59/500 [==>...........................] - ETA: 2:22 - loss: 0.5252 - regression_loss: 0.4654 - classification_loss: 0.0597 60/500 [==>...........................] - ETA: 2:21 - loss: 0.5230 - regression_loss: 0.4634 - classification_loss: 0.0596 61/500 [==>...........................] - ETA: 2:21 - loss: 0.5201 - regression_loss: 0.4610 - classification_loss: 0.0591 62/500 [==>...........................] - ETA: 2:21 - loss: 0.5201 - regression_loss: 0.4612 - classification_loss: 0.0589 63/500 [==>...........................] - ETA: 2:20 - loss: 0.5192 - regression_loss: 0.4609 - classification_loss: 0.0584 64/500 [==>...........................] - ETA: 2:20 - loss: 0.5192 - regression_loss: 0.4609 - classification_loss: 0.0582 65/500 [==>...........................] - ETA: 2:20 - loss: 0.5206 - regression_loss: 0.4624 - classification_loss: 0.0582 66/500 [==>...........................] - ETA: 2:19 - loss: 0.5423 - regression_loss: 0.4784 - classification_loss: 0.0638 67/500 [===>..........................] - ETA: 2:19 - loss: 0.5391 - regression_loss: 0.4758 - classification_loss: 0.0634 68/500 [===>..........................] - ETA: 2:19 - loss: 0.5403 - regression_loss: 0.4772 - classification_loss: 0.0632 69/500 [===>..........................] - ETA: 2:18 - loss: 0.5432 - regression_loss: 0.4798 - classification_loss: 0.0634 70/500 [===>..........................] - ETA: 2:18 - loss: 0.5468 - regression_loss: 0.4833 - classification_loss: 0.0635 71/500 [===>..........................] - ETA: 2:18 - loss: 0.5492 - regression_loss: 0.4859 - classification_loss: 0.0633 72/500 [===>..........................] - ETA: 2:18 - loss: 0.5519 - regression_loss: 0.4880 - classification_loss: 0.0639 73/500 [===>..........................] - ETA: 2:17 - loss: 0.5512 - regression_loss: 0.4876 - classification_loss: 0.0636 74/500 [===>..........................] - ETA: 2:17 - loss: 0.5485 - regression_loss: 0.4853 - classification_loss: 0.0632 75/500 [===>..........................] - ETA: 2:17 - loss: 0.5484 - regression_loss: 0.4846 - classification_loss: 0.0638 76/500 [===>..........................] - ETA: 2:16 - loss: 0.5469 - regression_loss: 0.4831 - classification_loss: 0.0638 77/500 [===>..........................] - ETA: 2:16 - loss: 0.5458 - regression_loss: 0.4823 - classification_loss: 0.0635 78/500 [===>..........................] - ETA: 2:16 - loss: 0.5422 - regression_loss: 0.4792 - classification_loss: 0.0630 79/500 [===>..........................] - ETA: 2:15 - loss: 0.5415 - regression_loss: 0.4788 - classification_loss: 0.0627 80/500 [===>..........................] - ETA: 2:15 - loss: 0.5414 - regression_loss: 0.4789 - classification_loss: 0.0625 81/500 [===>..........................] - ETA: 2:15 - loss: 0.5477 - regression_loss: 0.4841 - classification_loss: 0.0636 82/500 [===>..........................] - ETA: 2:14 - loss: 0.5475 - regression_loss: 0.4841 - classification_loss: 0.0634 83/500 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[====>.........................] - ETA: 2:09 - loss: 0.5545 - regression_loss: 0.4906 - classification_loss: 0.0639 100/500 [=====>........................] - ETA: 2:09 - loss: 0.5499 - regression_loss: 0.4864 - classification_loss: 0.0635 101/500 [=====>........................] - ETA: 2:08 - loss: 0.5517 - regression_loss: 0.4884 - classification_loss: 0.0633 102/500 [=====>........................] - ETA: 2:08 - loss: 0.5509 - regression_loss: 0.4879 - classification_loss: 0.0630 103/500 [=====>........................] - ETA: 2:08 - loss: 0.5508 - regression_loss: 0.4878 - classification_loss: 0.0630 104/500 [=====>........................] - ETA: 2:07 - loss: 0.5484 - regression_loss: 0.4856 - classification_loss: 0.0627 105/500 [=====>........................] - ETA: 2:07 - loss: 0.5496 - regression_loss: 0.4868 - classification_loss: 0.0628 106/500 [=====>........................] - ETA: 2:07 - loss: 0.5494 - regression_loss: 0.4865 - classification_loss: 0.0629 107/500 [=====>........................] - ETA: 2:06 - loss: 0.5485 - regression_loss: 0.4859 - classification_loss: 0.0627 108/500 [=====>........................] - ETA: 2:06 - loss: 0.5523 - regression_loss: 0.4888 - classification_loss: 0.0634 109/500 [=====>........................] - ETA: 2:06 - loss: 0.5549 - regression_loss: 0.4911 - classification_loss: 0.0638 110/500 [=====>........................] - ETA: 2:05 - loss: 0.5565 - regression_loss: 0.4930 - classification_loss: 0.0635 111/500 [=====>........................] - ETA: 2:05 - loss: 0.5559 - regression_loss: 0.4927 - classification_loss: 0.0632 112/500 [=====>........................] - ETA: 2:05 - loss: 0.5562 - regression_loss: 0.4931 - classification_loss: 0.0630 113/500 [=====>........................] - ETA: 2:04 - loss: 0.5529 - regression_loss: 0.4901 - classification_loss: 0.0628 114/500 [=====>........................] - ETA: 2:04 - loss: 0.5573 - regression_loss: 0.4929 - classification_loss: 0.0644 115/500 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[======>.......................] - ETA: 1:59 - loss: 0.5522 - regression_loss: 0.4886 - classification_loss: 0.0637 132/500 [======>.......................] - ETA: 1:58 - loss: 0.5574 - regression_loss: 0.4935 - classification_loss: 0.0639 133/500 [======>.......................] - ETA: 1:58 - loss: 0.5603 - regression_loss: 0.4960 - classification_loss: 0.0643 134/500 [=======>......................] - ETA: 1:58 - loss: 0.5617 - regression_loss: 0.4976 - classification_loss: 0.0642 135/500 [=======>......................] - ETA: 1:57 - loss: 0.5607 - regression_loss: 0.4968 - classification_loss: 0.0640 136/500 [=======>......................] - ETA: 1:57 - loss: 0.5636 - regression_loss: 0.4993 - classification_loss: 0.0644 137/500 [=======>......................] - ETA: 1:57 - loss: 0.5625 - regression_loss: 0.4984 - classification_loss: 0.0641 138/500 [=======>......................] - ETA: 1:56 - loss: 0.5602 - regression_loss: 0.4965 - classification_loss: 0.0637 139/500 [=======>......................] - ETA: 1:56 - loss: 0.5598 - regression_loss: 0.4963 - classification_loss: 0.0635 140/500 [=======>......................] - ETA: 1:56 - loss: 0.5575 - regression_loss: 0.4942 - classification_loss: 0.0632 141/500 [=======>......................] - ETA: 1:55 - loss: 0.5569 - regression_loss: 0.4939 - classification_loss: 0.0630 142/500 [=======>......................] - ETA: 1:55 - loss: 0.5560 - regression_loss: 0.4930 - classification_loss: 0.0629 143/500 [=======>......................] - ETA: 1:55 - loss: 0.5555 - regression_loss: 0.4926 - classification_loss: 0.0629 144/500 [=======>......................] - ETA: 1:54 - loss: 0.5539 - regression_loss: 0.4911 - classification_loss: 0.0628 145/500 [=======>......................] - ETA: 1:54 - loss: 0.5538 - regression_loss: 0.4909 - classification_loss: 0.0629 146/500 [=======>......................] - ETA: 1:54 - loss: 0.5540 - regression_loss: 0.4913 - classification_loss: 0.0627 147/500 [=======>......................] - ETA: 1:53 - loss: 0.5526 - regression_loss: 0.4902 - classification_loss: 0.0624 148/500 [=======>......................] - ETA: 1:53 - loss: 0.5506 - regression_loss: 0.4885 - classification_loss: 0.0621 149/500 [=======>......................] - ETA: 1:53 - loss: 0.5537 - regression_loss: 0.4912 - classification_loss: 0.0625 150/500 [========>.....................] - ETA: 1:52 - loss: 0.5530 - regression_loss: 0.4906 - classification_loss: 0.0623 151/500 [========>.....................] - ETA: 1:52 - loss: 0.5561 - regression_loss: 0.4928 - classification_loss: 0.0633 152/500 [========>.....................] - ETA: 1:52 - loss: 0.5574 - regression_loss: 0.4940 - classification_loss: 0.0633 153/500 [========>.....................] - ETA: 1:51 - loss: 0.5585 - regression_loss: 0.4952 - classification_loss: 0.0633 154/500 [========>.....................] - ETA: 1:51 - loss: 0.5626 - regression_loss: 0.4988 - classification_loss: 0.0638 155/500 [========>.....................] - ETA: 1:51 - loss: 0.5620 - regression_loss: 0.4983 - classification_loss: 0.0637 156/500 [========>.....................] - ETA: 1:50 - loss: 0.5634 - regression_loss: 0.4996 - classification_loss: 0.0638 157/500 [========>.....................] - ETA: 1:50 - loss: 0.5636 - regression_loss: 0.4998 - classification_loss: 0.0637 158/500 [========>.....................] - ETA: 1:50 - loss: 0.5656 - regression_loss: 0.5019 - classification_loss: 0.0637 159/500 [========>.....................] - ETA: 1:49 - loss: 0.5652 - regression_loss: 0.5017 - classification_loss: 0.0636 160/500 [========>.....................] - ETA: 1:49 - loss: 0.5630 - regression_loss: 0.4997 - classification_loss: 0.0633 161/500 [========>.....................] - ETA: 1:49 - loss: 0.5623 - regression_loss: 0.4992 - classification_loss: 0.0631 162/500 [========>.....................] - ETA: 1:48 - loss: 0.5633 - regression_loss: 0.5000 - classification_loss: 0.0633 163/500 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[===========================>..] - ETA: 5s - loss: 0.5846 - regression_loss: 0.5178 - classification_loss: 0.0668 484/500 [============================>.] - ETA: 5s - loss: 0.5843 - regression_loss: 0.5176 - classification_loss: 0.0667 485/500 [============================>.] - ETA: 4s - loss: 0.5855 - regression_loss: 0.5184 - classification_loss: 0.0671 486/500 [============================>.] - ETA: 4s - loss: 0.5852 - regression_loss: 0.5182 - classification_loss: 0.0670 487/500 [============================>.] - ETA: 4s - loss: 0.5844 - regression_loss: 0.5174 - classification_loss: 0.0669 488/500 [============================>.] - ETA: 3s - loss: 0.5835 - regression_loss: 0.5166 - classification_loss: 0.0668 489/500 [============================>.] - ETA: 3s - loss: 0.5833 - regression_loss: 0.5165 - classification_loss: 0.0668 490/500 [============================>.] - ETA: 3s - loss: 0.5833 - regression_loss: 0.5166 - classification_loss: 0.0667 491/500 [============================>.] - ETA: 2s - loss: 0.5828 - regression_loss: 0.5161 - classification_loss: 0.0667 492/500 [============================>.] - ETA: 2s - loss: 0.5835 - regression_loss: 0.5169 - classification_loss: 0.0666 493/500 [============================>.] - ETA: 2s - loss: 0.5837 - regression_loss: 0.5171 - classification_loss: 0.0666 494/500 [============================>.] - ETA: 1s - loss: 0.5846 - regression_loss: 0.5179 - classification_loss: 0.0667 495/500 [============================>.] - ETA: 1s - loss: 0.5844 - regression_loss: 0.5177 - classification_loss: 0.0667 496/500 [============================>.] - ETA: 1s - loss: 0.5848 - regression_loss: 0.5181 - classification_loss: 0.0668 497/500 [============================>.] - ETA: 0s - loss: 0.5854 - regression_loss: 0.5186 - classification_loss: 0.0668 498/500 [============================>.] - ETA: 0s - loss: 0.5848 - regression_loss: 0.5181 - classification_loss: 0.0668 499/500 [============================>.] - ETA: 0s - loss: 0.5841 - regression_loss: 0.5174 - classification_loss: 0.0667 500/500 [==============================] - 162s 324ms/step - loss: 0.5841 - regression_loss: 0.5174 - classification_loss: 0.0667 326 instances of class plum with average precision: 0.7854 mAP: 0.7854 Epoch 00034: saving model to ./training/snapshots/resnet101_pascal_34.h5 Epoch 35/150 1/500 [..............................] - ETA: 2:36 - loss: 0.6270 - regression_loss: 0.5498 - classification_loss: 0.0772 2/500 [..............................] - ETA: 2:36 - loss: 0.7243 - regression_loss: 0.6334 - classification_loss: 0.0909 3/500 [..............................] - ETA: 2:36 - loss: 0.6233 - regression_loss: 0.5530 - classification_loss: 0.0704 4/500 [..............................] - ETA: 2:35 - loss: 0.5447 - regression_loss: 0.4816 - classification_loss: 0.0631 5/500 [..............................] - ETA: 2:33 - loss: 0.5003 - regression_loss: 0.4420 - classification_loss: 0.0583 6/500 [..............................] - ETA: 2:32 - loss: 0.5090 - regression_loss: 0.4489 - classification_loss: 0.0601 7/500 [..............................] - ETA: 2:33 - loss: 0.4666 - regression_loss: 0.4098 - classification_loss: 0.0569 8/500 [..............................] - ETA: 2:34 - loss: 0.5203 - regression_loss: 0.4604 - classification_loss: 0.0598 9/500 [..............................] - ETA: 2:34 - loss: 0.5382 - regression_loss: 0.4817 - classification_loss: 0.0565 10/500 [..............................] - ETA: 2:33 - loss: 0.5359 - regression_loss: 0.4796 - classification_loss: 0.0563 11/500 [..............................] - ETA: 2:33 - loss: 0.5530 - regression_loss: 0.4933 - classification_loss: 0.0597 12/500 [..............................] - ETA: 2:33 - loss: 0.5680 - regression_loss: 0.5052 - classification_loss: 0.0628 13/500 [..............................] - ETA: 2:33 - loss: 0.5649 - regression_loss: 0.5029 - classification_loss: 0.0620 14/500 [..............................] - ETA: 2:33 - loss: 0.5441 - regression_loss: 0.4832 - classification_loss: 0.0609 15/500 [..............................] - ETA: 2:33 - loss: 0.5386 - regression_loss: 0.4779 - classification_loss: 0.0607 16/500 [..............................] - ETA: 2:32 - loss: 0.5636 - regression_loss: 0.4948 - classification_loss: 0.0688 17/500 [>.............................] - ETA: 2:33 - loss: 0.5580 - regression_loss: 0.4914 - classification_loss: 0.0666 18/500 [>.............................] - ETA: 2:33 - loss: 0.5592 - regression_loss: 0.4947 - classification_loss: 0.0645 19/500 [>.............................] - ETA: 2:32 - loss: 0.5570 - regression_loss: 0.4940 - classification_loss: 0.0630 20/500 [>.............................] - ETA: 2:32 - loss: 0.5484 - regression_loss: 0.4861 - classification_loss: 0.0622 21/500 [>.............................] - ETA: 2:31 - loss: 0.5701 - regression_loss: 0.5020 - classification_loss: 0.0681 22/500 [>.............................] - ETA: 2:31 - loss: 0.5737 - regression_loss: 0.5067 - classification_loss: 0.0670 23/500 [>.............................] - ETA: 2:31 - loss: 0.5689 - regression_loss: 0.5039 - classification_loss: 0.0650 24/500 [>.............................] - ETA: 2:31 - loss: 0.5657 - regression_loss: 0.5019 - classification_loss: 0.0638 25/500 [>.............................] - ETA: 2:30 - loss: 0.5534 - regression_loss: 0.4915 - classification_loss: 0.0619 26/500 [>.............................] - ETA: 2:30 - loss: 0.5519 - regression_loss: 0.4909 - classification_loss: 0.0609 27/500 [>.............................] - ETA: 2:29 - loss: 0.5493 - regression_loss: 0.4888 - classification_loss: 0.0605 28/500 [>.............................] - ETA: 2:29 - loss: 0.5483 - regression_loss: 0.4880 - classification_loss: 0.0603 29/500 [>.............................] - ETA: 2:29 - loss: 0.5380 - regression_loss: 0.4780 - classification_loss: 0.0599 30/500 [>.............................] - ETA: 2:29 - loss: 0.5471 - regression_loss: 0.4861 - classification_loss: 0.0609 31/500 [>.............................] - ETA: 2:28 - loss: 0.5468 - regression_loss: 0.4871 - classification_loss: 0.0597 32/500 [>.............................] - ETA: 2:28 - loss: 0.5387 - regression_loss: 0.4802 - classification_loss: 0.0585 33/500 [>.............................] - ETA: 2:28 - loss: 0.5442 - regression_loss: 0.4855 - classification_loss: 0.0587 34/500 [=>............................] - ETA: 2:28 - loss: 0.5576 - regression_loss: 0.4969 - classification_loss: 0.0607 35/500 [=>............................] - ETA: 2:27 - loss: 0.5570 - regression_loss: 0.4967 - classification_loss: 0.0603 36/500 [=>............................] - ETA: 2:27 - loss: 0.5625 - regression_loss: 0.5020 - classification_loss: 0.0605 37/500 [=>............................] - ETA: 2:27 - loss: 0.5641 - regression_loss: 0.5034 - classification_loss: 0.0607 38/500 [=>............................] - ETA: 2:26 - loss: 0.5640 - regression_loss: 0.5037 - classification_loss: 0.0603 39/500 [=>............................] - ETA: 2:26 - loss: 0.5597 - regression_loss: 0.4998 - classification_loss: 0.0599 40/500 [=>............................] - ETA: 2:26 - loss: 0.5500 - regression_loss: 0.4910 - classification_loss: 0.0590 41/500 [=>............................] - ETA: 2:26 - loss: 0.5500 - regression_loss: 0.4913 - classification_loss: 0.0588 42/500 [=>............................] - ETA: 2:26 - loss: 0.5510 - regression_loss: 0.4919 - classification_loss: 0.0592 43/500 [=>............................] - ETA: 2:25 - loss: 0.5464 - regression_loss: 0.4880 - classification_loss: 0.0584 44/500 [=>............................] - ETA: 2:25 - loss: 0.5421 - regression_loss: 0.4842 - classification_loss: 0.0578 45/500 [=>............................] - ETA: 2:25 - loss: 0.5381 - regression_loss: 0.4801 - classification_loss: 0.0580 46/500 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[====>.........................] - ETA: 2:11 - loss: 0.5705 - regression_loss: 0.5038 - classification_loss: 0.0666 95/500 [====>.........................] - ETA: 2:10 - loss: 0.5714 - regression_loss: 0.5049 - classification_loss: 0.0665 96/500 [====>.........................] - ETA: 2:10 - loss: 0.5717 - regression_loss: 0.5054 - classification_loss: 0.0663 97/500 [====>.........................] - ETA: 2:10 - loss: 0.5678 - regression_loss: 0.5019 - classification_loss: 0.0658 98/500 [====>.........................] - ETA: 2:10 - loss: 0.5673 - regression_loss: 0.5015 - classification_loss: 0.0658 99/500 [====>.........................] - ETA: 2:09 - loss: 0.5754 - regression_loss: 0.5082 - classification_loss: 0.0671 100/500 [=====>........................] - ETA: 2:09 - loss: 0.5735 - regression_loss: 0.5066 - classification_loss: 0.0669 101/500 [=====>........................] - ETA: 2:09 - loss: 0.5737 - regression_loss: 0.5069 - classification_loss: 0.0668 102/500 [=====>........................] - ETA: 2:08 - loss: 0.5721 - regression_loss: 0.5055 - classification_loss: 0.0666 103/500 [=====>........................] - ETA: 2:08 - loss: 0.5700 - regression_loss: 0.5037 - classification_loss: 0.0662 104/500 [=====>........................] - ETA: 2:08 - loss: 0.5666 - regression_loss: 0.5009 - classification_loss: 0.0657 105/500 [=====>........................] - ETA: 2:08 - loss: 0.5649 - regression_loss: 0.4995 - classification_loss: 0.0654 106/500 [=====>........................] - ETA: 2:07 - loss: 0.5655 - regression_loss: 0.4999 - classification_loss: 0.0655 107/500 [=====>........................] - ETA: 2:07 - loss: 0.5695 - regression_loss: 0.5019 - classification_loss: 0.0676 108/500 [=====>........................] - ETA: 2:07 - loss: 0.5692 - regression_loss: 0.5018 - classification_loss: 0.0674 109/500 [=====>........................] - ETA: 2:06 - loss: 0.5675 - regression_loss: 0.5004 - classification_loss: 0.0670 110/500 [=====>........................] - ETA: 2:06 - loss: 0.5671 - regression_loss: 0.5004 - classification_loss: 0.0666 111/500 [=====>........................] - ETA: 2:06 - loss: 0.5687 - regression_loss: 0.5021 - classification_loss: 0.0666 112/500 [=====>........................] - ETA: 2:05 - loss: 0.5681 - regression_loss: 0.5017 - classification_loss: 0.0664 113/500 [=====>........................] - ETA: 2:05 - loss: 0.5650 - regression_loss: 0.4990 - classification_loss: 0.0660 114/500 [=====>........................] - ETA: 2:05 - loss: 0.5632 - regression_loss: 0.4974 - classification_loss: 0.0658 115/500 [=====>........................] - ETA: 2:04 - loss: 0.5628 - regression_loss: 0.4969 - classification_loss: 0.0659 116/500 [=====>........................] - ETA: 2:04 - loss: 0.5602 - regression_loss: 0.4946 - classification_loss: 0.0656 117/500 [======>.......................] - ETA: 2:04 - loss: 0.5586 - regression_loss: 0.4932 - classification_loss: 0.0654 118/500 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[======>.......................] - ETA: 2:01 - loss: 0.5554 - regression_loss: 0.4904 - classification_loss: 0.0650 127/500 [======>.......................] - ETA: 2:00 - loss: 0.5550 - regression_loss: 0.4902 - classification_loss: 0.0647 128/500 [======>.......................] - ETA: 2:00 - loss: 0.5621 - regression_loss: 0.4958 - classification_loss: 0.0663 129/500 [======>.......................] - ETA: 2:00 - loss: 0.5609 - regression_loss: 0.4946 - classification_loss: 0.0663 130/500 [======>.......................] - ETA: 1:59 - loss: 0.5607 - regression_loss: 0.4945 - classification_loss: 0.0662 131/500 [======>.......................] - ETA: 1:59 - loss: 0.5579 - regression_loss: 0.4921 - classification_loss: 0.0658 132/500 [======>.......................] - ETA: 1:59 - loss: 0.5578 - regression_loss: 0.4922 - classification_loss: 0.0656 133/500 [======>.......................] - ETA: 1:58 - loss: 0.5576 - regression_loss: 0.4921 - classification_loss: 0.0655 134/500 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[========>.....................] - ETA: 1:53 - loss: 0.5640 - regression_loss: 0.4981 - classification_loss: 0.0659 151/500 [========>.....................] - ETA: 1:53 - loss: 0.5632 - regression_loss: 0.4974 - classification_loss: 0.0658 152/500 [========>.....................] - ETA: 1:52 - loss: 0.5650 - regression_loss: 0.4993 - classification_loss: 0.0656 153/500 [========>.....................] - ETA: 1:52 - loss: 0.5653 - regression_loss: 0.4997 - classification_loss: 0.0656 154/500 [========>.....................] - ETA: 1:52 - loss: 0.5664 - regression_loss: 0.5008 - classification_loss: 0.0656 155/500 [========>.....................] - ETA: 1:52 - loss: 0.5658 - regression_loss: 0.5004 - classification_loss: 0.0655 156/500 [========>.....................] - ETA: 1:51 - loss: 0.5652 - regression_loss: 0.4996 - classification_loss: 0.0656 157/500 [========>.....................] - ETA: 1:51 - loss: 0.5634 - regression_loss: 0.4981 - classification_loss: 0.0654 158/500 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[==========>...................] - ETA: 1:40 - loss: 0.5665 - regression_loss: 0.5026 - classification_loss: 0.0639 191/500 [==========>...................] - ETA: 1:40 - loss: 0.5673 - regression_loss: 0.5034 - classification_loss: 0.0639 192/500 [==========>...................] - ETA: 1:40 - loss: 0.5676 - regression_loss: 0.5037 - classification_loss: 0.0639 193/500 [==========>...................] - ETA: 1:39 - loss: 0.5679 - regression_loss: 0.5041 - classification_loss: 0.0638 194/500 [==========>...................] - ETA: 1:39 - loss: 0.5683 - regression_loss: 0.5044 - classification_loss: 0.0639 195/500 [==========>...................] - ETA: 1:39 - loss: 0.5693 - regression_loss: 0.5055 - classification_loss: 0.0638 196/500 [==========>...................] - ETA: 1:38 - loss: 0.5692 - regression_loss: 0.5055 - classification_loss: 0.0636 197/500 [==========>...................] - ETA: 1:38 - loss: 0.5679 - regression_loss: 0.5044 - classification_loss: 0.0635 198/500 [==========>...................] - ETA: 1:38 - loss: 0.5676 - regression_loss: 0.5042 - classification_loss: 0.0634 199/500 [==========>...................] - ETA: 1:37 - loss: 0.5680 - regression_loss: 0.5046 - classification_loss: 0.0634 200/500 [===========>..................] - ETA: 1:37 - loss: 0.5677 - regression_loss: 0.5044 - classification_loss: 0.0633 201/500 [===========>..................] - ETA: 1:37 - loss: 0.5665 - regression_loss: 0.5034 - classification_loss: 0.0631 202/500 [===========>..................] - ETA: 1:36 - loss: 0.5665 - regression_loss: 0.5035 - classification_loss: 0.0630 203/500 [===========>..................] - ETA: 1:36 - loss: 0.5667 - regression_loss: 0.5038 - classification_loss: 0.0629 204/500 [===========>..................] - ETA: 1:36 - loss: 0.5659 - regression_loss: 0.5031 - classification_loss: 0.0628 205/500 [===========>..................] - ETA: 1:35 - loss: 0.5648 - regression_loss: 0.5022 - classification_loss: 0.0627 206/500 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[============================>.] - ETA: 4s - loss: 0.5600 - regression_loss: 0.4988 - classification_loss: 0.0611 487/500 [============================>.] - ETA: 4s - loss: 0.5596 - regression_loss: 0.4986 - classification_loss: 0.0611 488/500 [============================>.] - ETA: 3s - loss: 0.5595 - regression_loss: 0.4985 - classification_loss: 0.0610 489/500 [============================>.] - ETA: 3s - loss: 0.5593 - regression_loss: 0.4984 - classification_loss: 0.0610 490/500 [============================>.] - ETA: 3s - loss: 0.5589 - regression_loss: 0.4980 - classification_loss: 0.0610 491/500 [============================>.] - ETA: 2s - loss: 0.5591 - regression_loss: 0.4981 - classification_loss: 0.0610 492/500 [============================>.] - ETA: 2s - loss: 0.5594 - regression_loss: 0.4984 - classification_loss: 0.0609 493/500 [============================>.] - ETA: 2s - loss: 0.5599 - regression_loss: 0.4990 - classification_loss: 0.0610 494/500 [============================>.] - ETA: 1s - loss: 0.5600 - regression_loss: 0.4991 - classification_loss: 0.0609 495/500 [============================>.] - ETA: 1s - loss: 0.5601 - regression_loss: 0.4992 - classification_loss: 0.0609 496/500 [============================>.] - ETA: 1s - loss: 0.5597 - regression_loss: 0.4988 - classification_loss: 0.0609 497/500 [============================>.] - ETA: 0s - loss: 0.5597 - regression_loss: 0.4988 - classification_loss: 0.0609 498/500 [============================>.] - ETA: 0s - loss: 0.5598 - regression_loss: 0.4989 - classification_loss: 0.0608 499/500 [============================>.] - ETA: 0s - loss: 0.5598 - regression_loss: 0.4990 - classification_loss: 0.0608 500/500 [==============================] - 162s 324ms/step - loss: 0.5592 - regression_loss: 0.4985 - classification_loss: 0.0608 326 instances of class plum with average precision: 0.7819 mAP: 0.7819 Epoch 00035: saving model to ./training/snapshots/resnet101_pascal_35.h5 Epoch 36/150 1/500 [..............................] - ETA: 2:42 - loss: 0.2840 - regression_loss: 0.2641 - classification_loss: 0.0198 2/500 [..............................] - ETA: 2:41 - loss: 0.7261 - regression_loss: 0.5858 - classification_loss: 0.1404 3/500 [..............................] - ETA: 2:45 - loss: 0.5762 - regression_loss: 0.4730 - classification_loss: 0.1032 4/500 [..............................] - ETA: 2:45 - loss: 0.5534 - regression_loss: 0.4570 - classification_loss: 0.0964 5/500 [..............................] - ETA: 2:43 - loss: 0.5720 - regression_loss: 0.4800 - classification_loss: 0.0919 6/500 [..............................] - ETA: 2:43 - loss: 0.5265 - regression_loss: 0.4455 - classification_loss: 0.0810 7/500 [..............................] - ETA: 2:42 - loss: 0.5921 - regression_loss: 0.4840 - classification_loss: 0.1080 8/500 [..............................] - ETA: 2:43 - loss: 0.6409 - regression_loss: 0.5320 - classification_loss: 0.1090 9/500 [..............................] - ETA: 2:42 - loss: 0.6845 - regression_loss: 0.5715 - classification_loss: 0.1130 10/500 [..............................] - ETA: 2:40 - loss: 0.6645 - regression_loss: 0.5599 - classification_loss: 0.1047 11/500 [..............................] - ETA: 2:41 - loss: 0.6675 - regression_loss: 0.5670 - classification_loss: 0.1005 12/500 [..............................] - ETA: 2:40 - loss: 0.6370 - regression_loss: 0.5427 - classification_loss: 0.0943 13/500 [..............................] - ETA: 2:40 - loss: 0.6065 - regression_loss: 0.5179 - classification_loss: 0.0886 14/500 [..............................] - ETA: 2:39 - loss: 0.6295 - regression_loss: 0.5412 - classification_loss: 0.0883 15/500 [..............................] - ETA: 2:38 - loss: 0.6270 - regression_loss: 0.5404 - classification_loss: 0.0866 16/500 [..............................] - ETA: 2:37 - loss: 0.6219 - regression_loss: 0.5358 - classification_loss: 0.0860 17/500 [>.............................] - ETA: 2:37 - loss: 0.5982 - regression_loss: 0.5162 - classification_loss: 0.0820 18/500 [>.............................] - ETA: 2:37 - loss: 0.6359 - regression_loss: 0.5490 - classification_loss: 0.0869 19/500 [>.............................] - ETA: 2:37 - loss: 0.6136 - regression_loss: 0.5309 - classification_loss: 0.0827 20/500 [>.............................] - ETA: 2:36 - loss: 0.6061 - regression_loss: 0.5259 - classification_loss: 0.0802 21/500 [>.............................] - ETA: 2:35 - loss: 0.6117 - regression_loss: 0.5324 - classification_loss: 0.0793 22/500 [>.............................] - ETA: 2:34 - loss: 0.6077 - regression_loss: 0.5290 - classification_loss: 0.0787 23/500 [>.............................] - ETA: 2:34 - loss: 0.6272 - regression_loss: 0.5441 - classification_loss: 0.0831 24/500 [>.............................] - ETA: 2:34 - loss: 0.6121 - regression_loss: 0.5310 - classification_loss: 0.0811 25/500 [>.............................] - ETA: 2:33 - loss: 0.6075 - regression_loss: 0.5279 - classification_loss: 0.0796 26/500 [>.............................] - ETA: 2:33 - loss: 0.6207 - regression_loss: 0.5427 - classification_loss: 0.0781 27/500 [>.............................] - ETA: 2:32 - loss: 0.6084 - regression_loss: 0.5325 - classification_loss: 0.0760 28/500 [>.............................] - ETA: 2:32 - loss: 0.6045 - regression_loss: 0.5293 - classification_loss: 0.0752 29/500 [>.............................] - ETA: 2:31 - loss: 0.6077 - regression_loss: 0.5323 - classification_loss: 0.0754 30/500 [>.............................] - ETA: 2:31 - loss: 0.6018 - regression_loss: 0.5273 - classification_loss: 0.0745 31/500 [>.............................] - ETA: 2:31 - loss: 0.5936 - regression_loss: 0.5201 - classification_loss: 0.0736 32/500 [>.............................] - ETA: 2:30 - loss: 0.5876 - regression_loss: 0.5153 - classification_loss: 0.0723 33/500 [>.............................] - ETA: 2:30 - loss: 0.5777 - regression_loss: 0.5068 - classification_loss: 0.0709 34/500 [=>............................] - ETA: 2:29 - loss: 0.5743 - regression_loss: 0.5037 - classification_loss: 0.0706 35/500 [=>............................] - ETA: 2:29 - loss: 0.5832 - regression_loss: 0.5106 - classification_loss: 0.0726 36/500 [=>............................] - ETA: 2:29 - loss: 0.5800 - regression_loss: 0.5087 - classification_loss: 0.0714 37/500 [=>............................] - ETA: 2:28 - loss: 0.5813 - regression_loss: 0.5112 - classification_loss: 0.0702 38/500 [=>............................] - ETA: 2:28 - loss: 0.5936 - regression_loss: 0.5217 - classification_loss: 0.0719 39/500 [=>............................] - ETA: 2:28 - loss: 0.6000 - regression_loss: 0.5277 - classification_loss: 0.0722 40/500 [=>............................] - ETA: 2:28 - loss: 0.5912 - regression_loss: 0.5204 - classification_loss: 0.0708 41/500 [=>............................] - ETA: 2:27 - loss: 0.5827 - regression_loss: 0.5130 - classification_loss: 0.0698 42/500 [=>............................] - ETA: 2:27 - loss: 0.5748 - regression_loss: 0.5060 - classification_loss: 0.0688 43/500 [=>............................] - ETA: 2:26 - loss: 0.5690 - regression_loss: 0.5012 - classification_loss: 0.0678 44/500 [=>............................] - ETA: 2:26 - loss: 0.5680 - regression_loss: 0.5010 - classification_loss: 0.0671 45/500 [=>............................] - ETA: 2:26 - loss: 0.5681 - regression_loss: 0.5005 - classification_loss: 0.0675 46/500 [=>............................] - ETA: 2:25 - loss: 0.5651 - regression_loss: 0.4975 - classification_loss: 0.0676 47/500 [=>............................] - ETA: 2:25 - loss: 0.5601 - regression_loss: 0.4936 - classification_loss: 0.0665 48/500 [=>............................] - ETA: 2:25 - loss: 0.5678 - regression_loss: 0.5008 - classification_loss: 0.0670 49/500 [=>............................] - ETA: 2:24 - loss: 0.5604 - regression_loss: 0.4941 - classification_loss: 0.0662 50/500 [==>...........................] - ETA: 2:24 - loss: 0.5673 - regression_loss: 0.5010 - classification_loss: 0.0663 51/500 [==>...........................] - ETA: 2:24 - loss: 0.5589 - regression_loss: 0.4936 - classification_loss: 0.0653 52/500 [==>...........................] - ETA: 2:24 - loss: 0.5660 - regression_loss: 0.5006 - classification_loss: 0.0654 53/500 [==>...........................] - ETA: 2:24 - loss: 0.5726 - regression_loss: 0.5056 - classification_loss: 0.0670 54/500 [==>...........................] - ETA: 2:23 - loss: 0.5686 - regression_loss: 0.5024 - classification_loss: 0.0662 55/500 [==>...........................] - ETA: 2:23 - loss: 0.5660 - regression_loss: 0.5003 - classification_loss: 0.0657 56/500 [==>...........................] - ETA: 2:22 - loss: 0.5620 - regression_loss: 0.4967 - classification_loss: 0.0653 57/500 [==>...........................] - ETA: 2:22 - loss: 0.5583 - regression_loss: 0.4937 - classification_loss: 0.0646 58/500 [==>...........................] - ETA: 2:22 - loss: 0.5517 - regression_loss: 0.4868 - classification_loss: 0.0649 59/500 [==>...........................] - ETA: 2:22 - loss: 0.5488 - regression_loss: 0.4843 - classification_loss: 0.0645 60/500 [==>...........................] - ETA: 2:22 - loss: 0.5441 - regression_loss: 0.4802 - classification_loss: 0.0638 61/500 [==>...........................] - ETA: 2:21 - loss: 0.5478 - regression_loss: 0.4842 - classification_loss: 0.0636 62/500 [==>...........................] - ETA: 2:21 - loss: 0.5438 - regression_loss: 0.4809 - classification_loss: 0.0630 63/500 [==>...........................] - ETA: 2:21 - loss: 0.5511 - regression_loss: 0.4880 - classification_loss: 0.0631 64/500 [==>...........................] - ETA: 2:20 - loss: 0.5540 - regression_loss: 0.4903 - classification_loss: 0.0637 65/500 [==>...........................] - ETA: 2:20 - loss: 0.5542 - regression_loss: 0.4905 - classification_loss: 0.0637 66/500 [==>...........................] - ETA: 2:20 - loss: 0.5506 - regression_loss: 0.4876 - classification_loss: 0.0631 67/500 [===>..........................] - ETA: 2:19 - loss: 0.5556 - regression_loss: 0.4921 - classification_loss: 0.0635 68/500 [===>..........................] - ETA: 2:19 - loss: 0.5652 - regression_loss: 0.5007 - classification_loss: 0.0645 69/500 [===>..........................] - ETA: 2:19 - loss: 0.5613 - regression_loss: 0.4970 - classification_loss: 0.0642 70/500 [===>..........................] - ETA: 2:18 - loss: 0.5625 - regression_loss: 0.4983 - classification_loss: 0.0642 71/500 [===>..........................] - ETA: 2:18 - loss: 0.5649 - regression_loss: 0.5003 - classification_loss: 0.0645 72/500 [===>..........................] - ETA: 2:18 - loss: 0.5681 - regression_loss: 0.5030 - classification_loss: 0.0652 73/500 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[============================>.] - ETA: 3s - loss: 0.5451 - regression_loss: 0.4854 - classification_loss: 0.0597 490/500 [============================>.] - ETA: 3s - loss: 0.5452 - regression_loss: 0.4855 - classification_loss: 0.0598 491/500 [============================>.] - ETA: 2s - loss: 0.5468 - regression_loss: 0.4865 - classification_loss: 0.0603 492/500 [============================>.] - ETA: 2s - loss: 0.5465 - regression_loss: 0.4862 - classification_loss: 0.0602 493/500 [============================>.] - ETA: 2s - loss: 0.5473 - regression_loss: 0.4868 - classification_loss: 0.0605 494/500 [============================>.] - ETA: 1s - loss: 0.5469 - regression_loss: 0.4865 - classification_loss: 0.0604 495/500 [============================>.] - ETA: 1s - loss: 0.5470 - regression_loss: 0.4865 - classification_loss: 0.0605 496/500 [============================>.] - ETA: 1s - loss: 0.5465 - regression_loss: 0.4861 - classification_loss: 0.0604 497/500 [============================>.] - ETA: 0s - loss: 0.5470 - regression_loss: 0.4865 - classification_loss: 0.0604 498/500 [============================>.] - ETA: 0s - loss: 0.5471 - regression_loss: 0.4866 - classification_loss: 0.0605 499/500 [============================>.] - ETA: 0s - loss: 0.5464 - regression_loss: 0.4861 - classification_loss: 0.0604 500/500 [==============================] - 162s 324ms/step - loss: 0.5469 - regression_loss: 0.4865 - classification_loss: 0.0604 326 instances of class plum with average precision: 0.7682 mAP: 0.7682 Epoch 00036: saving model to ./training/snapshots/resnet101_pascal_36.h5 Epoch 37/150 1/500 [..............................] - ETA: 2:36 - loss: 0.2747 - regression_loss: 0.2397 - classification_loss: 0.0351 2/500 [..............................] - ETA: 2:49 - loss: 0.3499 - regression_loss: 0.2935 - classification_loss: 0.0564 3/500 [..............................] - ETA: 2:53 - loss: 0.5670 - regression_loss: 0.4746 - classification_loss: 0.0924 4/500 [..............................] - ETA: 2:50 - loss: 0.6351 - regression_loss: 0.5425 - classification_loss: 0.0926 5/500 [..............................] - ETA: 2:50 - loss: 0.5959 - regression_loss: 0.5145 - classification_loss: 0.0814 6/500 [..............................] - ETA: 2:47 - loss: 0.5234 - regression_loss: 0.4535 - classification_loss: 0.0699 7/500 [..............................] - ETA: 2:45 - loss: 0.5259 - regression_loss: 0.4590 - classification_loss: 0.0668 8/500 [..............................] - ETA: 2:43 - loss: 0.6334 - regression_loss: 0.5499 - classification_loss: 0.0836 9/500 [..............................] - ETA: 2:42 - loss: 0.6397 - regression_loss: 0.5588 - classification_loss: 0.0808 10/500 [..............................] - ETA: 2:41 - loss: 0.6131 - regression_loss: 0.5351 - classification_loss: 0.0780 11/500 [..............................] - ETA: 2:40 - loss: 0.6106 - regression_loss: 0.5364 - classification_loss: 0.0742 12/500 [..............................] - ETA: 2:40 - loss: 0.6448 - regression_loss: 0.5622 - classification_loss: 0.0825 13/500 [..............................] - ETA: 2:39 - loss: 0.6460 - regression_loss: 0.5660 - classification_loss: 0.0800 14/500 [..............................] - ETA: 2:38 - loss: 0.6401 - regression_loss: 0.5603 - classification_loss: 0.0797 15/500 [..............................] - ETA: 2:39 - loss: 0.6268 - regression_loss: 0.5494 - classification_loss: 0.0775 16/500 [..............................] - ETA: 2:38 - loss: 0.6310 - regression_loss: 0.5544 - classification_loss: 0.0766 17/500 [>.............................] - ETA: 2:37 - loss: 0.6419 - regression_loss: 0.5667 - classification_loss: 0.0752 18/500 [>.............................] - ETA: 2:37 - loss: 0.6361 - regression_loss: 0.5621 - classification_loss: 0.0739 19/500 [>.............................] - ETA: 2:36 - loss: 0.6223 - regression_loss: 0.5509 - classification_loss: 0.0715 20/500 [>.............................] - ETA: 2:35 - loss: 0.6490 - regression_loss: 0.5692 - classification_loss: 0.0798 21/500 [>.............................] - ETA: 2:35 - loss: 0.6332 - regression_loss: 0.5556 - classification_loss: 0.0775 22/500 [>.............................] - ETA: 2:35 - loss: 0.6266 - regression_loss: 0.5512 - classification_loss: 0.0754 23/500 [>.............................] - ETA: 2:35 - loss: 0.6222 - regression_loss: 0.5478 - classification_loss: 0.0744 24/500 [>.............................] - ETA: 2:35 - loss: 0.6217 - regression_loss: 0.5483 - classification_loss: 0.0734 25/500 [>.............................] - ETA: 2:35 - loss: 0.6129 - regression_loss: 0.5409 - classification_loss: 0.0720 26/500 [>.............................] - ETA: 2:34 - loss: 0.6195 - regression_loss: 0.5480 - classification_loss: 0.0714 27/500 [>.............................] - ETA: 2:34 - loss: 0.6061 - regression_loss: 0.5359 - classification_loss: 0.0702 28/500 [>.............................] - ETA: 2:34 - loss: 0.5938 - regression_loss: 0.5255 - classification_loss: 0.0683 29/500 [>.............................] - ETA: 2:33 - loss: 0.5920 - regression_loss: 0.5245 - classification_loss: 0.0674 30/500 [>.............................] - ETA: 2:33 - loss: 0.5900 - regression_loss: 0.5225 - classification_loss: 0.0675 31/500 [>.............................] - ETA: 2:33 - loss: 0.5765 - regression_loss: 0.5107 - classification_loss: 0.0658 32/500 [>.............................] - ETA: 2:32 - loss: 0.5640 - regression_loss: 0.4996 - classification_loss: 0.0644 33/500 [>.............................] - ETA: 2:32 - loss: 0.5697 - regression_loss: 0.5057 - classification_loss: 0.0640 34/500 [=>............................] - ETA: 2:31 - loss: 0.5629 - regression_loss: 0.4998 - classification_loss: 0.0630 35/500 [=>............................] - ETA: 2:31 - loss: 0.5694 - regression_loss: 0.5058 - classification_loss: 0.0636 36/500 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[==>...........................] - ETA: 2:23 - loss: 0.5627 - regression_loss: 0.5014 - classification_loss: 0.0613 61/500 [==>...........................] - ETA: 2:23 - loss: 0.5638 - regression_loss: 0.5028 - classification_loss: 0.0610 62/500 [==>...........................] - ETA: 2:23 - loss: 0.5639 - regression_loss: 0.5032 - classification_loss: 0.0607 63/500 [==>...........................] - ETA: 2:22 - loss: 0.5645 - regression_loss: 0.5044 - classification_loss: 0.0601 64/500 [==>...........................] - ETA: 2:22 - loss: 0.5614 - regression_loss: 0.5016 - classification_loss: 0.0598 65/500 [==>...........................] - ETA: 2:22 - loss: 0.5602 - regression_loss: 0.5008 - classification_loss: 0.0594 66/500 [==>...........................] - ETA: 2:21 - loss: 0.5662 - regression_loss: 0.5060 - classification_loss: 0.0602 67/500 [===>..........................] - ETA: 2:21 - loss: 0.5639 - regression_loss: 0.5037 - classification_loss: 0.0602 68/500 [===>..........................] - ETA: 2:20 - loss: 0.5605 - regression_loss: 0.5009 - classification_loss: 0.0596 69/500 [===>..........................] - ETA: 2:20 - loss: 0.5570 - regression_loss: 0.4978 - classification_loss: 0.0592 70/500 [===>..........................] - ETA: 2:20 - loss: 0.5595 - regression_loss: 0.4995 - classification_loss: 0.0600 71/500 [===>..........................] - ETA: 2:19 - loss: 0.5697 - regression_loss: 0.5068 - classification_loss: 0.0629 72/500 [===>..........................] - ETA: 2:19 - loss: 0.5757 - regression_loss: 0.5129 - classification_loss: 0.0628 73/500 [===>..........................] - ETA: 2:19 - loss: 0.5816 - regression_loss: 0.5190 - classification_loss: 0.0626 74/500 [===>..........................] - ETA: 2:18 - loss: 0.5833 - regression_loss: 0.5211 - classification_loss: 0.0622 75/500 [===>..........................] - ETA: 2:18 - loss: 0.5813 - regression_loss: 0.5195 - classification_loss: 0.0618 76/500 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[====>.........................] - ETA: 2:12 - loss: 0.5738 - regression_loss: 0.5120 - classification_loss: 0.0618 93/500 [====>.........................] - ETA: 2:12 - loss: 0.5725 - regression_loss: 0.5108 - classification_loss: 0.0616 94/500 [====>.........................] - ETA: 2:12 - loss: 0.5697 - regression_loss: 0.5084 - classification_loss: 0.0613 95/500 [====>.........................] - ETA: 2:12 - loss: 0.5693 - regression_loss: 0.5081 - classification_loss: 0.0612 96/500 [====>.........................] - ETA: 2:11 - loss: 0.5688 - regression_loss: 0.5078 - classification_loss: 0.0610 97/500 [====>.........................] - ETA: 2:11 - loss: 0.5651 - regression_loss: 0.5046 - classification_loss: 0.0606 98/500 [====>.........................] - ETA: 2:11 - loss: 0.5693 - regression_loss: 0.5083 - classification_loss: 0.0610 99/500 [====>.........................] - ETA: 2:10 - loss: 0.5690 - regression_loss: 0.5080 - classification_loss: 0.0610 100/500 [=====>........................] - ETA: 2:10 - loss: 0.5673 - regression_loss: 0.5065 - classification_loss: 0.0608 101/500 [=====>........................] - ETA: 2:10 - loss: 0.5658 - regression_loss: 0.5053 - classification_loss: 0.0605 102/500 [=====>........................] - ETA: 2:10 - loss: 0.5625 - regression_loss: 0.5024 - classification_loss: 0.0601 103/500 [=====>........................] - ETA: 2:09 - loss: 0.5599 - regression_loss: 0.5002 - classification_loss: 0.0596 104/500 [=====>........................] - ETA: 2:09 - loss: 0.5613 - regression_loss: 0.5015 - classification_loss: 0.0598 105/500 [=====>........................] - ETA: 2:09 - loss: 0.5613 - regression_loss: 0.5018 - classification_loss: 0.0596 106/500 [=====>........................] - ETA: 2:08 - loss: 0.5620 - regression_loss: 0.5025 - classification_loss: 0.0595 107/500 [=====>........................] - ETA: 2:08 - loss: 0.5651 - regression_loss: 0.5051 - classification_loss: 0.0600 108/500 [=====>........................] - ETA: 2:08 - loss: 0.5642 - regression_loss: 0.5044 - classification_loss: 0.0598 109/500 [=====>........................] - ETA: 2:07 - loss: 0.5615 - regression_loss: 0.5020 - classification_loss: 0.0595 110/500 [=====>........................] - ETA: 2:07 - loss: 0.5602 - regression_loss: 0.5009 - classification_loss: 0.0593 111/500 [=====>........................] - ETA: 2:07 - loss: 0.5606 - regression_loss: 0.5016 - classification_loss: 0.0590 112/500 [=====>........................] - ETA: 2:06 - loss: 0.5578 - regression_loss: 0.4992 - classification_loss: 0.0586 113/500 [=====>........................] - ETA: 2:06 - loss: 0.5568 - regression_loss: 0.4984 - classification_loss: 0.0584 114/500 [=====>........................] - ETA: 2:06 - loss: 0.5543 - regression_loss: 0.4961 - classification_loss: 0.0582 115/500 [=====>........................] - ETA: 2:05 - loss: 0.5514 - regression_loss: 0.4935 - classification_loss: 0.0579 116/500 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[============================>.] - ETA: 2s - loss: 0.5534 - regression_loss: 0.4951 - classification_loss: 0.0583 493/500 [============================>.] - ETA: 2s - loss: 0.5538 - regression_loss: 0.4954 - classification_loss: 0.0584 494/500 [============================>.] - ETA: 1s - loss: 0.5529 - regression_loss: 0.4946 - classification_loss: 0.0583 495/500 [============================>.] - ETA: 1s - loss: 0.5527 - regression_loss: 0.4944 - classification_loss: 0.0583 496/500 [============================>.] - ETA: 1s - loss: 0.5522 - regression_loss: 0.4940 - classification_loss: 0.0582 497/500 [============================>.] - ETA: 0s - loss: 0.5514 - regression_loss: 0.4933 - classification_loss: 0.0581 498/500 [============================>.] - ETA: 0s - loss: 0.5513 - regression_loss: 0.4932 - classification_loss: 0.0581 499/500 [============================>.] - ETA: 0s - loss: 0.5507 - regression_loss: 0.4927 - classification_loss: 0.0580 500/500 [==============================] - 162s 325ms/step - loss: 0.5504 - regression_loss: 0.4924 - classification_loss: 0.0580 326 instances of class plum with average precision: 0.7756 mAP: 0.7756 Epoch 00037: saving model to ./training/snapshots/resnet101_pascal_37.h5 Epoch 38/150 1/500 [..............................] - ETA: 2:35 - loss: 0.4316 - regression_loss: 0.3435 - classification_loss: 0.0881 2/500 [..............................] - ETA: 2:35 - loss: 0.5354 - regression_loss: 0.4400 - classification_loss: 0.0955 3/500 [..............................] - ETA: 2:37 - loss: 0.4531 - regression_loss: 0.3753 - classification_loss: 0.0778 4/500 [..............................] - ETA: 2:41 - loss: 0.4691 - regression_loss: 0.3999 - classification_loss: 0.0691 5/500 [..............................] - ETA: 2:42 - loss: 0.4536 - regression_loss: 0.3886 - classification_loss: 0.0649 6/500 [..............................] - ETA: 2:41 - loss: 0.4704 - regression_loss: 0.4129 - classification_loss: 0.0575 7/500 [..............................] - ETA: 2:42 - loss: 0.4351 - regression_loss: 0.3803 - classification_loss: 0.0548 8/500 [..............................] - ETA: 2:41 - loss: 0.4560 - regression_loss: 0.4015 - classification_loss: 0.0545 9/500 [..............................] - ETA: 2:40 - loss: 0.4354 - regression_loss: 0.3853 - classification_loss: 0.0502 10/500 [..............................] - ETA: 2:41 - loss: 0.4220 - regression_loss: 0.3752 - classification_loss: 0.0468 11/500 [..............................] - ETA: 2:41 - loss: 0.4132 - regression_loss: 0.3695 - classification_loss: 0.0438 12/500 [..............................] - ETA: 2:40 - loss: 0.4293 - regression_loss: 0.3837 - classification_loss: 0.0456 13/500 [..............................] - ETA: 2:40 - loss: 0.4312 - regression_loss: 0.3865 - classification_loss: 0.0447 14/500 [..............................] - ETA: 2:40 - loss: 0.4281 - regression_loss: 0.3841 - classification_loss: 0.0440 15/500 [..............................] - ETA: 2:39 - loss: 0.4312 - regression_loss: 0.3880 - classification_loss: 0.0432 16/500 [..............................] - ETA: 2:38 - loss: 0.4791 - regression_loss: 0.4285 - classification_loss: 0.0507 17/500 [>.............................] - ETA: 2:38 - loss: 0.4625 - regression_loss: 0.4136 - classification_loss: 0.0489 18/500 [>.............................] - ETA: 2:38 - loss: 0.4899 - regression_loss: 0.4384 - classification_loss: 0.0514 19/500 [>.............................] - ETA: 2:37 - loss: 0.4934 - regression_loss: 0.4420 - classification_loss: 0.0514 20/500 [>.............................] - ETA: 2:37 - loss: 0.5067 - regression_loss: 0.4537 - classification_loss: 0.0530 21/500 [>.............................] - ETA: 2:37 - loss: 0.5204 - regression_loss: 0.4662 - classification_loss: 0.0542 22/500 [>.............................] - ETA: 2:37 - loss: 0.5111 - regression_loss: 0.4581 - classification_loss: 0.0530 23/500 [>.............................] - ETA: 2:37 - loss: 0.5043 - regression_loss: 0.4522 - classification_loss: 0.0521 24/500 [>.............................] - ETA: 2:36 - loss: 0.4982 - regression_loss: 0.4470 - classification_loss: 0.0512 25/500 [>.............................] - ETA: 2:36 - loss: 0.4884 - regression_loss: 0.4383 - classification_loss: 0.0501 26/500 [>.............................] - ETA: 2:35 - loss: 0.4855 - regression_loss: 0.4360 - classification_loss: 0.0495 27/500 [>.............................] - ETA: 2:35 - loss: 0.4905 - regression_loss: 0.4408 - classification_loss: 0.0497 28/500 [>.............................] - ETA: 2:35 - loss: 0.4919 - regression_loss: 0.4432 - classification_loss: 0.0487 29/500 [>.............................] - ETA: 2:34 - loss: 0.4864 - regression_loss: 0.4385 - classification_loss: 0.0479 30/500 [>.............................] - ETA: 2:34 - loss: 0.4857 - regression_loss: 0.4378 - classification_loss: 0.0479 31/500 [>.............................] - ETA: 2:34 - loss: 0.4764 - regression_loss: 0.4296 - classification_loss: 0.0468 32/500 [>.............................] - ETA: 2:33 - loss: 0.4714 - regression_loss: 0.4250 - classification_loss: 0.0464 33/500 [>.............................] - ETA: 2:33 - loss: 0.4780 - regression_loss: 0.4318 - classification_loss: 0.0462 34/500 [=>............................] - ETA: 2:32 - loss: 0.4830 - regression_loss: 0.4360 - classification_loss: 0.0469 35/500 [=>............................] - ETA: 2:32 - loss: 0.4791 - regression_loss: 0.4328 - classification_loss: 0.0463 36/500 [=>............................] - ETA: 2:32 - loss: 0.4813 - regression_loss: 0.4350 - classification_loss: 0.0463 37/500 [=>............................] - ETA: 2:31 - loss: 0.4947 - regression_loss: 0.4438 - classification_loss: 0.0509 38/500 [=>............................] - ETA: 2:31 - loss: 0.4908 - regression_loss: 0.4408 - classification_loss: 0.0500 39/500 [=>............................] - ETA: 2:30 - loss: 0.5020 - regression_loss: 0.4507 - classification_loss: 0.0512 40/500 [=>............................] - ETA: 2:30 - loss: 0.5031 - regression_loss: 0.4520 - classification_loss: 0.0511 41/500 [=>............................] - ETA: 2:30 - loss: 0.5048 - regression_loss: 0.4525 - classification_loss: 0.0524 42/500 [=>............................] - ETA: 2:30 - loss: 0.5060 - regression_loss: 0.4537 - classification_loss: 0.0522 43/500 [=>............................] - ETA: 2:29 - loss: 0.5002 - regression_loss: 0.4486 - classification_loss: 0.0516 44/500 [=>............................] - ETA: 2:29 - loss: 0.4970 - regression_loss: 0.4458 - classification_loss: 0.0512 45/500 [=>............................] - ETA: 2:28 - loss: 0.4980 - regression_loss: 0.4472 - classification_loss: 0.0508 46/500 [=>............................] - ETA: 2:28 - loss: 0.4960 - regression_loss: 0.4458 - classification_loss: 0.0502 47/500 [=>............................] - ETA: 2:27 - loss: 0.4960 - regression_loss: 0.4457 - classification_loss: 0.0503 48/500 [=>............................] - ETA: 2:27 - loss: 0.4930 - regression_loss: 0.4433 - classification_loss: 0.0497 49/500 [=>............................] - ETA: 2:27 - loss: 0.5043 - regression_loss: 0.4536 - classification_loss: 0.0506 50/500 [==>...........................] - ETA: 2:26 - loss: 0.5081 - regression_loss: 0.4574 - classification_loss: 0.0506 51/500 [==>...........................] - ETA: 2:26 - loss: 0.5063 - regression_loss: 0.4561 - classification_loss: 0.0502 52/500 [==>...........................] - ETA: 2:26 - loss: 0.5118 - regression_loss: 0.4613 - classification_loss: 0.0504 53/500 [==>...........................] - ETA: 2:25 - loss: 0.5207 - regression_loss: 0.4679 - classification_loss: 0.0528 54/500 [==>...........................] - ETA: 2:25 - loss: 0.5206 - regression_loss: 0.4682 - classification_loss: 0.0524 55/500 [==>...........................] - ETA: 2:24 - loss: 0.5229 - regression_loss: 0.4706 - classification_loss: 0.0523 56/500 [==>...........................] - ETA: 2:24 - loss: 0.5195 - regression_loss: 0.4675 - classification_loss: 0.0519 57/500 [==>...........................] - ETA: 2:24 - loss: 0.5194 - regression_loss: 0.4676 - classification_loss: 0.0517 58/500 [==>...........................] - ETA: 2:23 - loss: 0.5168 - regression_loss: 0.4655 - classification_loss: 0.0513 59/500 [==>...........................] - ETA: 2:23 - loss: 0.5183 - regression_loss: 0.4664 - classification_loss: 0.0519 60/500 [==>...........................] - ETA: 2:23 - loss: 0.5140 - regression_loss: 0.4625 - classification_loss: 0.0516 61/500 [==>...........................] - ETA: 2:22 - loss: 0.5146 - regression_loss: 0.4632 - classification_loss: 0.0514 62/500 [==>...........................] - ETA: 2:22 - loss: 0.5182 - regression_loss: 0.4664 - classification_loss: 0.0518 63/500 [==>...........................] - ETA: 2:22 - loss: 0.5395 - regression_loss: 0.4821 - classification_loss: 0.0575 64/500 [==>...........................] - ETA: 2:21 - loss: 0.5440 - regression_loss: 0.4863 - classification_loss: 0.0576 65/500 [==>...........................] - ETA: 2:21 - loss: 0.5385 - regression_loss: 0.4813 - classification_loss: 0.0571 66/500 [==>...........................] - ETA: 2:21 - loss: 0.5376 - regression_loss: 0.4807 - classification_loss: 0.0569 67/500 [===>..........................] - ETA: 2:21 - loss: 0.5390 - regression_loss: 0.4825 - classification_loss: 0.0565 68/500 [===>..........................] - ETA: 2:20 - loss: 0.5416 - regression_loss: 0.4854 - classification_loss: 0.0562 69/500 [===>..........................] - ETA: 2:20 - loss: 0.5420 - regression_loss: 0.4860 - classification_loss: 0.0560 70/500 [===>..........................] - ETA: 2:20 - loss: 0.5436 - regression_loss: 0.4873 - classification_loss: 0.0563 71/500 [===>..........................] - ETA: 2:19 - loss: 0.5387 - regression_loss: 0.4828 - classification_loss: 0.0559 72/500 [===>..........................] - ETA: 2:19 - loss: 0.5409 - regression_loss: 0.4845 - classification_loss: 0.0563 73/500 [===>..........................] - ETA: 2:18 - loss: 0.5391 - regression_loss: 0.4832 - classification_loss: 0.0559 74/500 [===>..........................] - ETA: 2:18 - loss: 0.5457 - regression_loss: 0.4878 - classification_loss: 0.0579 75/500 [===>..........................] - ETA: 2:18 - loss: 0.5600 - regression_loss: 0.4988 - classification_loss: 0.0612 76/500 [===>..........................] - ETA: 2:17 - loss: 0.5594 - regression_loss: 0.4986 - classification_loss: 0.0608 77/500 [===>..........................] - ETA: 2:17 - loss: 0.5568 - regression_loss: 0.4965 - classification_loss: 0.0603 78/500 [===>..........................] - ETA: 2:17 - loss: 0.5534 - regression_loss: 0.4936 - classification_loss: 0.0598 79/500 [===>..........................] - ETA: 2:16 - loss: 0.5500 - regression_loss: 0.4908 - classification_loss: 0.0592 80/500 [===>..........................] - ETA: 2:16 - loss: 0.5513 - regression_loss: 0.4920 - classification_loss: 0.0592 81/500 [===>..........................] - ETA: 2:16 - loss: 0.5501 - regression_loss: 0.4909 - classification_loss: 0.0593 82/500 [===>..........................] - ETA: 2:15 - loss: 0.5504 - regression_loss: 0.4910 - classification_loss: 0.0594 83/500 [===>..........................] - ETA: 2:15 - loss: 0.5495 - regression_loss: 0.4903 - classification_loss: 0.0592 84/500 [====>.........................] - ETA: 2:14 - loss: 0.5495 - regression_loss: 0.4903 - classification_loss: 0.0592 85/500 [====>.........................] - ETA: 2:14 - loss: 0.5486 - regression_loss: 0.4897 - classification_loss: 0.0589 86/500 [====>.........................] - ETA: 2:14 - loss: 0.5475 - regression_loss: 0.4888 - 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classification_loss: 0.0571 95/500 [====>.........................] - ETA: 2:11 - loss: 0.5389 - regression_loss: 0.4821 - classification_loss: 0.0569 96/500 [====>.........................] - ETA: 2:10 - loss: 0.5400 - regression_loss: 0.4832 - classification_loss: 0.0568 97/500 [====>.........................] - ETA: 2:10 - loss: 0.5420 - regression_loss: 0.4853 - classification_loss: 0.0568 98/500 [====>.........................] - ETA: 2:10 - loss: 0.5415 - regression_loss: 0.4850 - classification_loss: 0.0565 99/500 [====>.........................] - ETA: 2:09 - loss: 0.5390 - regression_loss: 0.4828 - classification_loss: 0.0562 100/500 [=====>........................] - ETA: 2:09 - loss: 0.5368 - regression_loss: 0.4809 - classification_loss: 0.0560 101/500 [=====>........................] - ETA: 2:09 - loss: 0.5406 - regression_loss: 0.4843 - classification_loss: 0.0563 102/500 [=====>........................] - ETA: 2:08 - loss: 0.5359 - regression_loss: 0.4801 - classification_loss: 0.0558 103/500 [=====>........................] - ETA: 2:08 - loss: 0.5391 - regression_loss: 0.4829 - classification_loss: 0.0563 104/500 [=====>........................] - ETA: 2:08 - loss: 0.5393 - regression_loss: 0.4827 - classification_loss: 0.0565 105/500 [=====>........................] - ETA: 2:07 - loss: 0.5401 - regression_loss: 0.4837 - classification_loss: 0.0564 106/500 [=====>........................] - ETA: 2:07 - loss: 0.5381 - regression_loss: 0.4819 - classification_loss: 0.0562 107/500 [=====>........................] - ETA: 2:07 - loss: 0.5391 - regression_loss: 0.4829 - classification_loss: 0.0562 108/500 [=====>........................] - ETA: 2:06 - loss: 0.5366 - regression_loss: 0.4808 - classification_loss: 0.0559 109/500 [=====>........................] - ETA: 2:06 - loss: 0.5354 - regression_loss: 0.4797 - classification_loss: 0.0556 110/500 [=====>........................] - ETA: 2:06 - loss: 0.5382 - regression_loss: 0.4823 - classification_loss: 0.0559 111/500 [=====>........................] - ETA: 2:05 - loss: 0.5376 - regression_loss: 0.4817 - classification_loss: 0.0560 112/500 [=====>........................] - ETA: 2:05 - loss: 0.5369 - regression_loss: 0.4809 - classification_loss: 0.0559 113/500 [=====>........................] - ETA: 2:05 - loss: 0.5335 - regression_loss: 0.4778 - classification_loss: 0.0557 114/500 [=====>........................] - ETA: 2:05 - loss: 0.5391 - regression_loss: 0.4822 - classification_loss: 0.0569 115/500 [=====>........................] - ETA: 2:04 - loss: 0.5374 - regression_loss: 0.4808 - classification_loss: 0.0566 116/500 [=====>........................] - ETA: 2:04 - loss: 0.5423 - regression_loss: 0.4852 - classification_loss: 0.0571 117/500 [======>.......................] - ETA: 2:04 - loss: 0.5451 - regression_loss: 0.4875 - classification_loss: 0.0576 118/500 [======>.......................] - ETA: 2:03 - loss: 0.5430 - regression_loss: 0.4856 - 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classification_loss: 0.0592 127/500 [======>.......................] - ETA: 2:00 - loss: 0.5506 - regression_loss: 0.4908 - classification_loss: 0.0598 128/500 [======>.......................] - ETA: 2:00 - loss: 0.5540 - regression_loss: 0.4940 - classification_loss: 0.0600 129/500 [======>.......................] - ETA: 1:59 - loss: 0.5544 - regression_loss: 0.4943 - classification_loss: 0.0601 130/500 [======>.......................] - ETA: 1:59 - loss: 0.5542 - regression_loss: 0.4942 - classification_loss: 0.0600 131/500 [======>.......................] - ETA: 1:59 - loss: 0.5536 - regression_loss: 0.4938 - classification_loss: 0.0598 132/500 [======>.......................] - ETA: 1:59 - loss: 0.5580 - regression_loss: 0.4968 - classification_loss: 0.0612 133/500 [======>.......................] - ETA: 1:58 - loss: 0.5576 - regression_loss: 0.4966 - classification_loss: 0.0611 134/500 [=======>......................] - ETA: 1:58 - loss: 0.5616 - regression_loss: 0.4992 - 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classification_loss: 0.0600 151/500 [========>.....................] - ETA: 1:52 - loss: 0.5470 - regression_loss: 0.4871 - classification_loss: 0.0599 152/500 [========>.....................] - ETA: 1:52 - loss: 0.5450 - regression_loss: 0.4854 - classification_loss: 0.0596 153/500 [========>.....................] - ETA: 1:52 - loss: 0.5441 - regression_loss: 0.4846 - classification_loss: 0.0595 154/500 [========>.....................] - ETA: 1:51 - loss: 0.5451 - regression_loss: 0.4857 - classification_loss: 0.0594 155/500 [========>.....................] - ETA: 1:51 - loss: 0.5439 - regression_loss: 0.4847 - classification_loss: 0.0591 156/500 [========>.....................] - ETA: 1:51 - loss: 0.5422 - regression_loss: 0.4833 - classification_loss: 0.0589 157/500 [========>.....................] - ETA: 1:51 - loss: 0.5410 - regression_loss: 0.4823 - classification_loss: 0.0587 158/500 [========>.....................] - ETA: 1:50 - loss: 0.5419 - regression_loss: 0.4833 - 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[============================>.] - ETA: 4s - loss: 0.5272 - regression_loss: 0.4697 - classification_loss: 0.0575 488/500 [============================>.] - ETA: 3s - loss: 0.5272 - regression_loss: 0.4698 - classification_loss: 0.0574 489/500 [============================>.] - ETA: 3s - loss: 0.5270 - regression_loss: 0.4696 - classification_loss: 0.0574 490/500 [============================>.] - ETA: 3s - loss: 0.5267 - regression_loss: 0.4694 - classification_loss: 0.0573 491/500 [============================>.] - ETA: 2s - loss: 0.5260 - regression_loss: 0.4688 - classification_loss: 0.0572 492/500 [============================>.] - ETA: 2s - loss: 0.5270 - regression_loss: 0.4697 - classification_loss: 0.0573 493/500 [============================>.] - ETA: 2s - loss: 0.5271 - regression_loss: 0.4699 - classification_loss: 0.0573 494/500 [============================>.] - ETA: 1s - loss: 0.5268 - regression_loss: 0.4696 - classification_loss: 0.0572 495/500 [============================>.] - ETA: 1s - loss: 0.5273 - regression_loss: 0.4701 - classification_loss: 0.0572 496/500 [============================>.] - ETA: 1s - loss: 0.5267 - regression_loss: 0.4695 - classification_loss: 0.0572 497/500 [============================>.] - ETA: 0s - loss: 0.5274 - regression_loss: 0.4701 - classification_loss: 0.0573 498/500 [============================>.] - ETA: 0s - loss: 0.5283 - regression_loss: 0.4709 - classification_loss: 0.0574 499/500 [============================>.] - ETA: 0s - loss: 0.5283 - regression_loss: 0.4710 - classification_loss: 0.0574 500/500 [==============================] - 162s 324ms/step - loss: 0.5290 - regression_loss: 0.4716 - classification_loss: 0.0574 326 instances of class plum with average precision: 0.7832 mAP: 0.7832 Epoch 00038: saving model to ./training/snapshots/resnet101_pascal_38.h5 Epoch 39/150 1/500 [..............................] - ETA: 2:32 - loss: 0.1132 - regression_loss: 0.1009 - classification_loss: 0.0123 2/500 [..............................] - ETA: 2:33 - loss: 0.4690 - regression_loss: 0.4033 - classification_loss: 0.0657 3/500 [..............................] - ETA: 2:33 - loss: 0.4815 - regression_loss: 0.4178 - classification_loss: 0.0637 4/500 [..............................] - ETA: 2:36 - loss: 0.5209 - regression_loss: 0.4584 - classification_loss: 0.0625 5/500 [..............................] - ETA: 2:37 - loss: 0.4629 - regression_loss: 0.4068 - classification_loss: 0.0561 6/500 [..............................] - ETA: 2:38 - loss: 0.4719 - regression_loss: 0.4159 - classification_loss: 0.0560 7/500 [..............................] - ETA: 2:38 - loss: 0.4548 - regression_loss: 0.4037 - classification_loss: 0.0511 8/500 [..............................] - ETA: 2:36 - loss: 0.4453 - regression_loss: 0.3931 - classification_loss: 0.0522 9/500 [..............................] - ETA: 2:35 - loss: 0.4444 - regression_loss: 0.3931 - classification_loss: 0.0513 10/500 [..............................] - ETA: 2:36 - loss: 0.4099 - regression_loss: 0.3624 - classification_loss: 0.0475 11/500 [..............................] - ETA: 2:36 - loss: 0.4014 - regression_loss: 0.3562 - classification_loss: 0.0452 12/500 [..............................] - ETA: 2:35 - loss: 0.3989 - regression_loss: 0.3546 - classification_loss: 0.0443 13/500 [..............................] - ETA: 2:34 - loss: 0.4062 - regression_loss: 0.3621 - classification_loss: 0.0440 14/500 [..............................] - ETA: 2:35 - loss: 0.4117 - regression_loss: 0.3678 - classification_loss: 0.0439 15/500 [..............................] - ETA: 2:35 - loss: 0.4286 - regression_loss: 0.3855 - classification_loss: 0.0431 16/500 [..............................] - ETA: 2:37 - loss: 0.4120 - regression_loss: 0.3711 - classification_loss: 0.0410 17/500 [>.............................] - ETA: 2:36 - loss: 0.3998 - regression_loss: 0.3600 - classification_loss: 0.0398 18/500 [>.............................] - ETA: 2:36 - loss: 0.4290 - regression_loss: 0.3775 - classification_loss: 0.0515 19/500 [>.............................] - ETA: 2:35 - loss: 0.4332 - regression_loss: 0.3826 - classification_loss: 0.0506 20/500 [>.............................] - ETA: 2:36 - loss: 0.4239 - regression_loss: 0.3748 - classification_loss: 0.0491 21/500 [>.............................] - ETA: 2:35 - loss: 0.4410 - regression_loss: 0.3895 - classification_loss: 0.0514 22/500 [>.............................] - ETA: 2:35 - loss: 0.4498 - regression_loss: 0.3989 - classification_loss: 0.0509 23/500 [>.............................] - ETA: 2:35 - loss: 0.4480 - regression_loss: 0.3978 - classification_loss: 0.0502 24/500 [>.............................] - ETA: 2:35 - loss: 0.4627 - regression_loss: 0.4104 - classification_loss: 0.0523 25/500 [>.............................] - ETA: 2:34 - loss: 0.4780 - regression_loss: 0.4235 - classification_loss: 0.0545 26/500 [>.............................] - ETA: 2:34 - loss: 0.4703 - regression_loss: 0.4170 - classification_loss: 0.0532 27/500 [>.............................] - ETA: 2:34 - loss: 0.4766 - regression_loss: 0.4245 - classification_loss: 0.0521 28/500 [>.............................] - ETA: 2:34 - loss: 0.4671 - regression_loss: 0.4162 - classification_loss: 0.0509 29/500 [>.............................] - ETA: 2:34 - loss: 0.4590 - regression_loss: 0.4094 - classification_loss: 0.0497 30/500 [>.............................] - ETA: 2:33 - loss: 0.4534 - regression_loss: 0.4047 - classification_loss: 0.0487 31/500 [>.............................] - ETA: 2:33 - loss: 0.4521 - regression_loss: 0.4033 - classification_loss: 0.0488 32/500 [>.............................] - ETA: 2:32 - loss: 0.4474 - regression_loss: 0.3994 - classification_loss: 0.0479 33/500 [>.............................] - ETA: 2:32 - loss: 0.4412 - regression_loss: 0.3942 - classification_loss: 0.0469 34/500 [=>............................] - ETA: 2:32 - loss: 0.4525 - regression_loss: 0.4042 - classification_loss: 0.0482 35/500 [=>............................] - ETA: 2:32 - loss: 0.4510 - regression_loss: 0.4031 - classification_loss: 0.0479 36/500 [=>............................] - ETA: 2:31 - loss: 0.4480 - regression_loss: 0.4006 - classification_loss: 0.0474 37/500 [=>............................] - ETA: 2:31 - loss: 0.4503 - regression_loss: 0.4027 - classification_loss: 0.0476 38/500 [=>............................] - ETA: 2:30 - loss: 0.4507 - regression_loss: 0.4032 - classification_loss: 0.0475 39/500 [=>............................] - ETA: 2:30 - loss: 0.4574 - regression_loss: 0.4087 - classification_loss: 0.0488 40/500 [=>............................] - ETA: 2:30 - loss: 0.4704 - regression_loss: 0.4185 - classification_loss: 0.0519 41/500 [=>............................] - ETA: 2:29 - loss: 0.4732 - regression_loss: 0.4208 - classification_loss: 0.0524 42/500 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[==>...........................] - ETA: 2:21 - loss: 0.4799 - regression_loss: 0.4304 - classification_loss: 0.0494 67/500 [===>..........................] - ETA: 2:21 - loss: 0.4999 - regression_loss: 0.4449 - classification_loss: 0.0550 68/500 [===>..........................] - ETA: 2:20 - loss: 0.5015 - regression_loss: 0.4462 - classification_loss: 0.0553 69/500 [===>..........................] - ETA: 2:20 - loss: 0.5004 - regression_loss: 0.4456 - classification_loss: 0.0548 70/500 [===>..........................] - ETA: 2:20 - loss: 0.5008 - regression_loss: 0.4464 - classification_loss: 0.0544 71/500 [===>..........................] - ETA: 2:19 - loss: 0.5004 - regression_loss: 0.4463 - classification_loss: 0.0542 72/500 [===>..........................] - ETA: 2:19 - loss: 0.4967 - regression_loss: 0.4430 - classification_loss: 0.0537 73/500 [===>..........................] - ETA: 2:18 - loss: 0.5055 - regression_loss: 0.4504 - classification_loss: 0.0551 74/500 [===>..........................] - ETA: 2:18 - loss: 0.5046 - regression_loss: 0.4498 - classification_loss: 0.0548 75/500 [===>..........................] - ETA: 2:18 - loss: 0.5077 - regression_loss: 0.4522 - classification_loss: 0.0555 76/500 [===>..........................] - ETA: 2:18 - loss: 0.5051 - regression_loss: 0.4498 - classification_loss: 0.0553 77/500 [===>..........................] - ETA: 2:17 - loss: 0.5072 - regression_loss: 0.4517 - classification_loss: 0.0555 78/500 [===>..........................] - ETA: 2:17 - loss: 0.5035 - regression_loss: 0.4485 - classification_loss: 0.0550 79/500 [===>..........................] - ETA: 2:17 - loss: 0.5027 - regression_loss: 0.4477 - classification_loss: 0.0550 80/500 [===>..........................] - ETA: 2:17 - loss: 0.5028 - regression_loss: 0.4480 - classification_loss: 0.0548 81/500 [===>..........................] - ETA: 2:16 - loss: 0.5010 - regression_loss: 0.4463 - classification_loss: 0.0547 82/500 [===>..........................] - ETA: 2:16 - loss: 0.4994 - regression_loss: 0.4451 - classification_loss: 0.0544 83/500 [===>..........................] - ETA: 2:15 - loss: 0.4996 - regression_loss: 0.4454 - classification_loss: 0.0542 84/500 [====>.........................] - ETA: 2:15 - loss: 0.4984 - regression_loss: 0.4443 - classification_loss: 0.0541 85/500 [====>.........................] - ETA: 2:15 - loss: 0.4969 - regression_loss: 0.4430 - classification_loss: 0.0539 86/500 [====>.........................] - ETA: 2:14 - loss: 0.4939 - regression_loss: 0.4404 - classification_loss: 0.0535 87/500 [====>.........................] - ETA: 2:14 - loss: 0.4912 - regression_loss: 0.4379 - classification_loss: 0.0533 88/500 [====>.........................] - ETA: 2:14 - loss: 0.4918 - regression_loss: 0.4386 - classification_loss: 0.0531 89/500 [====>.........................] - ETA: 2:13 - loss: 0.4899 - regression_loss: 0.4371 - classification_loss: 0.0528 90/500 [====>.........................] - ETA: 2:13 - loss: 0.4875 - regression_loss: 0.4348 - classification_loss: 0.0526 91/500 [====>.........................] - ETA: 2:12 - loss: 0.4930 - regression_loss: 0.4396 - classification_loss: 0.0534 92/500 [====>.........................] - ETA: 2:12 - loss: 0.4928 - regression_loss: 0.4393 - classification_loss: 0.0535 93/500 [====>.........................] - ETA: 2:12 - loss: 0.4924 - regression_loss: 0.4393 - classification_loss: 0.0532 94/500 [====>.........................] - ETA: 2:11 - loss: 0.4911 - regression_loss: 0.4383 - classification_loss: 0.0528 95/500 [====>.........................] - ETA: 2:11 - loss: 0.4927 - regression_loss: 0.4398 - classification_loss: 0.0528 96/500 [====>.........................] - ETA: 2:11 - loss: 0.4919 - regression_loss: 0.4393 - classification_loss: 0.0526 97/500 [====>.........................] - ETA: 2:11 - loss: 0.4903 - regression_loss: 0.4380 - classification_loss: 0.0523 98/500 [====>.........................] - ETA: 2:10 - loss: 0.4912 - regression_loss: 0.4388 - classification_loss: 0.0524 99/500 [====>.........................] - ETA: 2:10 - loss: 0.4922 - regression_loss: 0.4397 - classification_loss: 0.0525 100/500 [=====>........................] - ETA: 2:10 - loss: 0.4914 - regression_loss: 0.4392 - classification_loss: 0.0522 101/500 [=====>........................] - ETA: 2:09 - loss: 0.4918 - regression_loss: 0.4397 - classification_loss: 0.0521 102/500 [=====>........................] - ETA: 2:09 - loss: 0.4913 - regression_loss: 0.4393 - classification_loss: 0.0519 103/500 [=====>........................] - ETA: 2:08 - loss: 0.4906 - regression_loss: 0.4387 - classification_loss: 0.0519 104/500 [=====>........................] - ETA: 2:08 - loss: 0.4900 - regression_loss: 0.4381 - classification_loss: 0.0519 105/500 [=====>........................] - ETA: 2:08 - loss: 0.4926 - regression_loss: 0.4404 - classification_loss: 0.0522 106/500 [=====>........................] - ETA: 2:07 - loss: 0.4914 - regression_loss: 0.4396 - classification_loss: 0.0518 107/500 [=====>........................] - ETA: 2:07 - loss: 0.4924 - regression_loss: 0.4408 - classification_loss: 0.0516 108/500 [=====>........................] - ETA: 2:07 - loss: 0.4952 - regression_loss: 0.4435 - classification_loss: 0.0516 109/500 [=====>........................] - ETA: 2:07 - loss: 0.4920 - regression_loss: 0.4408 - classification_loss: 0.0513 110/500 [=====>........................] - ETA: 2:06 - loss: 0.4900 - regression_loss: 0.4390 - classification_loss: 0.0510 111/500 [=====>........................] - ETA: 2:06 - loss: 0.4909 - regression_loss: 0.4400 - classification_loss: 0.0509 112/500 [=====>........................] - ETA: 2:06 - loss: 0.4920 - regression_loss: 0.4411 - classification_loss: 0.0508 113/500 [=====>........................] - ETA: 2:05 - loss: 0.4954 - regression_loss: 0.4445 - classification_loss: 0.0508 114/500 [=====>........................] - ETA: 2:05 - loss: 0.4941 - regression_loss: 0.4435 - classification_loss: 0.0506 115/500 [=====>........................] - ETA: 2:05 - loss: 0.4975 - regression_loss: 0.4469 - classification_loss: 0.0506 116/500 [=====>........................] - ETA: 2:04 - loss: 0.4978 - regression_loss: 0.4473 - classification_loss: 0.0505 117/500 [======>.......................] - ETA: 2:04 - loss: 0.4970 - regression_loss: 0.4468 - classification_loss: 0.0502 118/500 [======>.......................] - ETA: 2:04 - loss: 0.4972 - regression_loss: 0.4468 - classification_loss: 0.0504 119/500 [======>.......................] - ETA: 2:03 - loss: 0.4990 - regression_loss: 0.4485 - classification_loss: 0.0505 120/500 [======>.......................] - ETA: 2:03 - loss: 0.4987 - regression_loss: 0.4483 - classification_loss: 0.0504 121/500 [======>.......................] - ETA: 2:03 - loss: 0.5008 - regression_loss: 0.4505 - classification_loss: 0.0504 122/500 [======>.......................] - ETA: 2:02 - loss: 0.5010 - regression_loss: 0.4503 - classification_loss: 0.0507 123/500 [======>.......................] - ETA: 2:02 - loss: 0.5010 - regression_loss: 0.4503 - classification_loss: 0.0506 124/500 [======>.......................] - ETA: 2:02 - loss: 0.5001 - regression_loss: 0.4496 - classification_loss: 0.0504 125/500 [======>.......................] - ETA: 2:01 - loss: 0.4996 - regression_loss: 0.4491 - classification_loss: 0.0504 126/500 [======>.......................] - ETA: 2:01 - loss: 0.4982 - regression_loss: 0.4481 - classification_loss: 0.0502 127/500 [======>.......................] - ETA: 2:01 - loss: 0.4991 - regression_loss: 0.4490 - classification_loss: 0.0501 128/500 [======>.......................] - ETA: 2:00 - loss: 0.5042 - regression_loss: 0.4525 - classification_loss: 0.0517 129/500 [======>.......................] - ETA: 2:00 - loss: 0.5016 - regression_loss: 0.4500 - classification_loss: 0.0516 130/500 [======>.......................] - ETA: 2:00 - loss: 0.5013 - regression_loss: 0.4498 - classification_loss: 0.0515 131/500 [======>.......................] - ETA: 1:59 - loss: 0.5005 - regression_loss: 0.4491 - classification_loss: 0.0514 132/500 [======>.......................] - ETA: 1:59 - loss: 0.4998 - regression_loss: 0.4485 - classification_loss: 0.0512 133/500 [======>.......................] - ETA: 1:59 - loss: 0.5008 - regression_loss: 0.4497 - classification_loss: 0.0511 134/500 [=======>......................] - ETA: 1:58 - loss: 0.4982 - regression_loss: 0.4475 - classification_loss: 0.0508 135/500 [=======>......................] - ETA: 1:58 - loss: 0.4953 - regression_loss: 0.4448 - classification_loss: 0.0505 136/500 [=======>......................] - ETA: 1:58 - loss: 0.4940 - regression_loss: 0.4437 - classification_loss: 0.0503 137/500 [=======>......................] - ETA: 1:57 - loss: 0.4965 - regression_loss: 0.4458 - classification_loss: 0.0507 138/500 [=======>......................] - ETA: 1:57 - loss: 0.4952 - regression_loss: 0.4446 - classification_loss: 0.0506 139/500 [=======>......................] - ETA: 1:57 - loss: 0.4951 - regression_loss: 0.4446 - classification_loss: 0.0505 140/500 [=======>......................] - ETA: 1:56 - loss: 0.4944 - regression_loss: 0.4440 - classification_loss: 0.0504 141/500 [=======>......................] - ETA: 1:56 - loss: 0.4922 - regression_loss: 0.4421 - classification_loss: 0.0501 142/500 [=======>......................] - ETA: 1:56 - loss: 0.4935 - regression_loss: 0.4434 - classification_loss: 0.0502 143/500 [=======>......................] - ETA: 1:55 - loss: 0.4933 - regression_loss: 0.4433 - classification_loss: 0.0501 144/500 [=======>......................] - ETA: 1:55 - loss: 0.4916 - regression_loss: 0.4418 - classification_loss: 0.0498 145/500 [=======>......................] - ETA: 1:55 - loss: 0.4911 - regression_loss: 0.4414 - classification_loss: 0.0497 146/500 [=======>......................] - ETA: 1:54 - loss: 0.4886 - regression_loss: 0.4392 - classification_loss: 0.0495 147/500 [=======>......................] - ETA: 1:54 - loss: 0.4875 - regression_loss: 0.4382 - classification_loss: 0.0493 148/500 [=======>......................] - ETA: 1:54 - loss: 0.4868 - regression_loss: 0.4377 - classification_loss: 0.0491 149/500 [=======>......................] - ETA: 1:53 - loss: 0.4871 - regression_loss: 0.4376 - classification_loss: 0.0496 150/500 [========>.....................] - ETA: 1:53 - loss: 0.4855 - regression_loss: 0.4361 - classification_loss: 0.0494 151/500 [========>.....................] - ETA: 1:53 - loss: 0.4874 - regression_loss: 0.4380 - classification_loss: 0.0495 152/500 [========>.....................] - ETA: 1:52 - loss: 0.4884 - regression_loss: 0.4388 - classification_loss: 0.0496 153/500 [========>.....................] - ETA: 1:52 - loss: 0.4886 - regression_loss: 0.4391 - classification_loss: 0.0495 154/500 [========>.....................] - ETA: 1:52 - loss: 0.4883 - regression_loss: 0.4389 - classification_loss: 0.0495 155/500 [========>.....................] - ETA: 1:51 - loss: 0.4913 - regression_loss: 0.4417 - classification_loss: 0.0496 156/500 [========>.....................] - ETA: 1:51 - loss: 0.4908 - regression_loss: 0.4414 - classification_loss: 0.0495 157/500 [========>.....................] - ETA: 1:51 - loss: 0.4928 - regression_loss: 0.4432 - classification_loss: 0.0496 158/500 [========>.....................] - ETA: 1:51 - loss: 0.4940 - regression_loss: 0.4442 - classification_loss: 0.0498 159/500 [========>.....................] - ETA: 1:50 - loss: 0.4937 - regression_loss: 0.4440 - classification_loss: 0.0497 160/500 [========>.....................] - ETA: 1:50 - loss: 0.4937 - regression_loss: 0.4440 - classification_loss: 0.0497 161/500 [========>.....................] - ETA: 1:50 - loss: 0.4959 - regression_loss: 0.4458 - classification_loss: 0.0501 162/500 [========>.....................] - ETA: 1:49 - loss: 0.4960 - regression_loss: 0.4458 - classification_loss: 0.0501 163/500 [========>.....................] - ETA: 1:49 - loss: 0.4952 - regression_loss: 0.4452 - classification_loss: 0.0500 164/500 [========>.....................] - ETA: 1:49 - loss: 0.4937 - regression_loss: 0.4439 - classification_loss: 0.0498 165/500 [========>.....................] - ETA: 1:48 - loss: 0.4982 - regression_loss: 0.4469 - classification_loss: 0.0513 166/500 [========>.....................] - ETA: 1:48 - loss: 0.4991 - regression_loss: 0.4478 - classification_loss: 0.0513 167/500 [=========>....................] - ETA: 1:48 - loss: 0.4983 - regression_loss: 0.4470 - classification_loss: 0.0514 168/500 [=========>....................] - ETA: 1:47 - loss: 0.4995 - regression_loss: 0.4480 - classification_loss: 0.0515 169/500 [=========>....................] - ETA: 1:47 - loss: 0.4996 - regression_loss: 0.4481 - classification_loss: 0.0515 170/500 [=========>....................] - ETA: 1:47 - loss: 0.5015 - regression_loss: 0.4499 - classification_loss: 0.0517 171/500 [=========>....................] - ETA: 1:46 - loss: 0.5014 - regression_loss: 0.4499 - classification_loss: 0.0515 172/500 [=========>....................] - ETA: 1:46 - loss: 0.5020 - regression_loss: 0.4504 - classification_loss: 0.0516 173/500 [=========>....................] - ETA: 1:46 - loss: 0.5026 - regression_loss: 0.4512 - classification_loss: 0.0514 174/500 [=========>....................] - ETA: 1:45 - loss: 0.5025 - regression_loss: 0.4512 - classification_loss: 0.0514 175/500 [=========>....................] - ETA: 1:45 - loss: 0.5018 - regression_loss: 0.4505 - classification_loss: 0.0513 176/500 [=========>....................] - ETA: 1:45 - loss: 0.5017 - regression_loss: 0.4506 - classification_loss: 0.0511 177/500 [=========>....................] - ETA: 1:44 - loss: 0.5009 - regression_loss: 0.4499 - classification_loss: 0.0510 178/500 [=========>....................] - ETA: 1:44 - loss: 0.4998 - regression_loss: 0.4491 - classification_loss: 0.0508 179/500 [=========>....................] - ETA: 1:44 - loss: 0.5048 - regression_loss: 0.4531 - classification_loss: 0.0517 180/500 [=========>....................] - ETA: 1:43 - loss: 0.5044 - regression_loss: 0.4528 - classification_loss: 0.0516 181/500 [=========>....................] - ETA: 1:43 - loss: 0.5048 - regression_loss: 0.4531 - classification_loss: 0.0517 182/500 [=========>....................] - ETA: 1:43 - loss: 0.5032 - regression_loss: 0.4517 - classification_loss: 0.0515 183/500 [=========>....................] - ETA: 1:43 - loss: 0.5031 - regression_loss: 0.4516 - classification_loss: 0.0516 184/500 [==========>...................] - ETA: 1:42 - loss: 0.5026 - regression_loss: 0.4510 - classification_loss: 0.0515 185/500 [==========>...................] - ETA: 1:42 - loss: 0.5028 - regression_loss: 0.4514 - classification_loss: 0.0514 186/500 [==========>...................] - ETA: 1:42 - loss: 0.5022 - regression_loss: 0.4508 - classification_loss: 0.0514 187/500 [==========>...................] - ETA: 1:41 - loss: 0.5023 - regression_loss: 0.4509 - classification_loss: 0.0514 188/500 [==========>...................] - ETA: 1:41 - loss: 0.5031 - regression_loss: 0.4516 - classification_loss: 0.0515 189/500 [==========>...................] - ETA: 1:40 - loss: 0.5013 - regression_loss: 0.4500 - classification_loss: 0.0513 190/500 [==========>...................] - ETA: 1:40 - loss: 0.5020 - regression_loss: 0.4505 - classification_loss: 0.0515 191/500 [==========>...................] - ETA: 1:40 - loss: 0.5019 - regression_loss: 0.4506 - classification_loss: 0.0514 192/500 [==========>...................] - ETA: 1:39 - loss: 0.5011 - regression_loss: 0.4499 - classification_loss: 0.0512 193/500 [==========>...................] - ETA: 1:39 - loss: 0.5001 - regression_loss: 0.4490 - classification_loss: 0.0511 194/500 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[===========================>..] - ETA: 5s - loss: 0.5237 - regression_loss: 0.4678 - classification_loss: 0.0559 483/500 [===========================>..] - ETA: 5s - loss: 0.5246 - regression_loss: 0.4686 - classification_loss: 0.0560 484/500 [============================>.] - ETA: 5s - loss: 0.5250 - regression_loss: 0.4690 - classification_loss: 0.0560 485/500 [============================>.] - ETA: 4s - loss: 0.5254 - regression_loss: 0.4694 - classification_loss: 0.0560 486/500 [============================>.] - ETA: 4s - loss: 0.5249 - regression_loss: 0.4690 - classification_loss: 0.0559 487/500 [============================>.] - ETA: 4s - loss: 0.5249 - regression_loss: 0.4690 - classification_loss: 0.0559 488/500 [============================>.] - ETA: 3s - loss: 0.5254 - regression_loss: 0.4695 - classification_loss: 0.0560 489/500 [============================>.] - ETA: 3s - loss: 0.5251 - regression_loss: 0.4692 - classification_loss: 0.0559 490/500 [============================>.] - ETA: 3s - loss: 0.5254 - regression_loss: 0.4693 - classification_loss: 0.0561 491/500 [============================>.] - ETA: 2s - loss: 0.5255 - regression_loss: 0.4695 - classification_loss: 0.0560 492/500 [============================>.] - ETA: 2s - loss: 0.5251 - regression_loss: 0.4691 - classification_loss: 0.0560 493/500 [============================>.] - ETA: 2s - loss: 0.5253 - regression_loss: 0.4692 - classification_loss: 0.0560 494/500 [============================>.] - ETA: 1s - loss: 0.5264 - regression_loss: 0.4701 - classification_loss: 0.0562 495/500 [============================>.] - ETA: 1s - loss: 0.5262 - regression_loss: 0.4700 - classification_loss: 0.0562 496/500 [============================>.] - ETA: 1s - loss: 0.5259 - regression_loss: 0.4698 - classification_loss: 0.0561 497/500 [============================>.] - ETA: 0s - loss: 0.5264 - regression_loss: 0.4700 - classification_loss: 0.0563 498/500 [============================>.] - ETA: 0s - loss: 0.5262 - regression_loss: 0.4699 - classification_loss: 0.0563 499/500 [============================>.] - ETA: 0s - loss: 0.5261 - regression_loss: 0.4699 - classification_loss: 0.0562 500/500 [==============================] - 162s 325ms/step - loss: 0.5266 - regression_loss: 0.4704 - classification_loss: 0.0562 326 instances of class plum with average precision: 0.7768 mAP: 0.7768 Epoch 00039: saving model to ./training/snapshots/resnet101_pascal_39.h5 Epoch 40/150 1/500 [..............................] - ETA: 2:34 - loss: 0.3129 - regression_loss: 0.2887 - classification_loss: 0.0242 2/500 [..............................] - ETA: 2:42 - loss: 0.3852 - regression_loss: 0.3545 - classification_loss: 0.0307 3/500 [..............................] - ETA: 2:42 - loss: 0.4472 - regression_loss: 0.4154 - classification_loss: 0.0318 4/500 [..............................] - ETA: 2:40 - loss: 0.5447 - regression_loss: 0.4949 - classification_loss: 0.0498 5/500 [..............................] - ETA: 2:41 - loss: 0.5364 - regression_loss: 0.4884 - classification_loss: 0.0479 6/500 [..............................] - ETA: 2:41 - loss: 0.5512 - regression_loss: 0.5018 - classification_loss: 0.0494 7/500 [..............................] - ETA: 2:40 - loss: 0.5383 - regression_loss: 0.4870 - classification_loss: 0.0512 8/500 [..............................] - ETA: 2:38 - loss: 0.5073 - regression_loss: 0.4579 - classification_loss: 0.0494 9/500 [..............................] - ETA: 2:40 - loss: 0.5130 - regression_loss: 0.4650 - classification_loss: 0.0480 10/500 [..............................] - ETA: 2:39 - loss: 0.4931 - regression_loss: 0.4469 - classification_loss: 0.0462 11/500 [..............................] - ETA: 2:39 - loss: 0.4888 - regression_loss: 0.4426 - classification_loss: 0.0462 12/500 [..............................] - ETA: 2:38 - loss: 0.5338 - regression_loss: 0.4816 - classification_loss: 0.0523 13/500 [..............................] - ETA: 2:37 - loss: 0.5274 - regression_loss: 0.4767 - classification_loss: 0.0507 14/500 [..............................] - ETA: 2:36 - loss: 0.5337 - regression_loss: 0.4813 - classification_loss: 0.0523 15/500 [..............................] - ETA: 2:37 - loss: 0.5281 - regression_loss: 0.4764 - classification_loss: 0.0517 16/500 [..............................] - ETA: 2:37 - loss: 0.5136 - regression_loss: 0.4639 - classification_loss: 0.0498 17/500 [>.............................] - ETA: 2:37 - loss: 0.5254 - regression_loss: 0.4740 - classification_loss: 0.0514 18/500 [>.............................] - ETA: 2:37 - loss: 0.5223 - regression_loss: 0.4724 - classification_loss: 0.0499 19/500 [>.............................] - ETA: 2:37 - loss: 0.5216 - regression_loss: 0.4727 - classification_loss: 0.0489 20/500 [>.............................] - ETA: 2:36 - loss: 0.5161 - regression_loss: 0.4683 - classification_loss: 0.0478 21/500 [>.............................] - ETA: 2:36 - loss: 0.5126 - regression_loss: 0.4652 - classification_loss: 0.0474 22/500 [>.............................] - ETA: 2:36 - loss: 0.5181 - regression_loss: 0.4708 - classification_loss: 0.0473 23/500 [>.............................] - ETA: 2:35 - loss: 0.5207 - regression_loss: 0.4728 - classification_loss: 0.0479 24/500 [>.............................] - ETA: 2:35 - loss: 0.5196 - regression_loss: 0.4718 - classification_loss: 0.0478 25/500 [>.............................] - ETA: 2:34 - loss: 0.5093 - regression_loss: 0.4623 - classification_loss: 0.0470 26/500 [>.............................] - ETA: 2:34 - loss: 0.4993 - regression_loss: 0.4532 - classification_loss: 0.0461 27/500 [>.............................] - ETA: 2:33 - loss: 0.5026 - regression_loss: 0.4562 - classification_loss: 0.0464 28/500 [>.............................] - ETA: 2:33 - loss: 0.5066 - regression_loss: 0.4598 - classification_loss: 0.0468 29/500 [>.............................] - ETA: 2:33 - loss: 0.5052 - regression_loss: 0.4591 - classification_loss: 0.0461 30/500 [>.............................] - ETA: 2:32 - loss: 0.5117 - regression_loss: 0.4646 - classification_loss: 0.0471 31/500 [>.............................] - ETA: 2:32 - loss: 0.5350 - regression_loss: 0.4796 - classification_loss: 0.0554 32/500 [>.............................] - ETA: 2:31 - loss: 0.5345 - regression_loss: 0.4788 - classification_loss: 0.0557 33/500 [>.............................] - ETA: 2:31 - loss: 0.5333 - regression_loss: 0.4781 - classification_loss: 0.0552 34/500 [=>............................] - ETA: 2:31 - loss: 0.5242 - regression_loss: 0.4702 - classification_loss: 0.0540 35/500 [=>............................] - ETA: 2:30 - loss: 0.5208 - regression_loss: 0.4674 - classification_loss: 0.0534 36/500 [=>............................] - ETA: 2:30 - loss: 0.5328 - regression_loss: 0.4795 - classification_loss: 0.0533 37/500 [=>............................] - ETA: 2:29 - loss: 0.5278 - regression_loss: 0.4752 - classification_loss: 0.0525 38/500 [=>............................] - ETA: 2:29 - loss: 0.5294 - regression_loss: 0.4767 - classification_loss: 0.0527 39/500 [=>............................] - ETA: 2:29 - loss: 0.5299 - regression_loss: 0.4777 - classification_loss: 0.0521 40/500 [=>............................] - ETA: 2:28 - loss: 0.5301 - regression_loss: 0.4787 - classification_loss: 0.0514 41/500 [=>............................] - ETA: 2:28 - loss: 0.5257 - regression_loss: 0.4751 - classification_loss: 0.0506 42/500 [=>............................] - ETA: 2:27 - loss: 0.5280 - regression_loss: 0.4773 - classification_loss: 0.0507 43/500 [=>............................] - ETA: 2:27 - loss: 0.5242 - regression_loss: 0.4743 - classification_loss: 0.0499 44/500 [=>............................] - ETA: 2:27 - loss: 0.5166 - regression_loss: 0.4674 - classification_loss: 0.0491 45/500 [=>............................] - ETA: 2:27 - loss: 0.5176 - regression_loss: 0.4692 - classification_loss: 0.0484 46/500 [=>............................] - ETA: 2:26 - loss: 0.5205 - regression_loss: 0.4719 - classification_loss: 0.0486 47/500 [=>............................] - ETA: 2:26 - loss: 0.5141 - regression_loss: 0.4663 - classification_loss: 0.0478 48/500 [=>............................] - ETA: 2:26 - loss: 0.5158 - regression_loss: 0.4681 - classification_loss: 0.0476 49/500 [=>............................] - ETA: 2:26 - loss: 0.5178 - regression_loss: 0.4696 - classification_loss: 0.0483 50/500 [==>...........................] - ETA: 2:26 - loss: 0.5145 - regression_loss: 0.4666 - classification_loss: 0.0479 51/500 [==>...........................] - ETA: 2:25 - loss: 0.5237 - regression_loss: 0.4749 - classification_loss: 0.0488 52/500 [==>...........................] - ETA: 2:25 - loss: 0.5273 - regression_loss: 0.4783 - classification_loss: 0.0490 53/500 [==>...........................] - ETA: 2:24 - loss: 0.5249 - regression_loss: 0.4762 - classification_loss: 0.0487 54/500 [==>...........................] - ETA: 2:24 - loss: 0.5356 - regression_loss: 0.4823 - classification_loss: 0.0532 55/500 [==>...........................] - ETA: 2:24 - loss: 0.5387 - regression_loss: 0.4855 - classification_loss: 0.0532 56/500 [==>...........................] - ETA: 2:23 - loss: 0.5375 - regression_loss: 0.4845 - classification_loss: 0.0529 57/500 [==>...........................] - ETA: 2:23 - loss: 0.5342 - regression_loss: 0.4818 - classification_loss: 0.0524 58/500 [==>...........................] - ETA: 2:23 - loss: 0.5338 - regression_loss: 0.4816 - classification_loss: 0.0522 59/500 [==>...........................] - ETA: 2:22 - loss: 0.5327 - regression_loss: 0.4806 - classification_loss: 0.0521 60/500 [==>...........................] - ETA: 2:22 - loss: 0.5350 - regression_loss: 0.4823 - classification_loss: 0.0527 61/500 [==>...........................] - ETA: 2:22 - loss: 0.5389 - regression_loss: 0.4854 - classification_loss: 0.0534 62/500 [==>...........................] - ETA: 2:21 - loss: 0.5354 - regression_loss: 0.4823 - classification_loss: 0.0531 63/500 [==>...........................] - ETA: 2:21 - loss: 0.5378 - regression_loss: 0.4840 - classification_loss: 0.0538 64/500 [==>...........................] - ETA: 2:21 - loss: 0.5369 - regression_loss: 0.4827 - classification_loss: 0.0541 65/500 [==>...........................] - ETA: 2:21 - loss: 0.5359 - regression_loss: 0.4818 - classification_loss: 0.0542 66/500 [==>...........................] - ETA: 2:20 - loss: 0.5358 - regression_loss: 0.4818 - classification_loss: 0.0539 67/500 [===>..........................] - ETA: 2:20 - loss: 0.5345 - regression_loss: 0.4807 - classification_loss: 0.0537 68/500 [===>..........................] - ETA: 2:19 - loss: 0.5408 - regression_loss: 0.4868 - classification_loss: 0.0540 69/500 [===>..........................] - ETA: 2:19 - loss: 0.5427 - regression_loss: 0.4887 - classification_loss: 0.0540 70/500 [===>..........................] - ETA: 2:19 - loss: 0.5405 - regression_loss: 0.4869 - classification_loss: 0.0536 71/500 [===>..........................] - ETA: 2:18 - loss: 0.5371 - regression_loss: 0.4838 - classification_loss: 0.0533 72/500 [===>..........................] - ETA: 2:18 - loss: 0.5331 - regression_loss: 0.4802 - classification_loss: 0.0528 73/500 [===>..........................] - ETA: 2:18 - loss: 0.5308 - regression_loss: 0.4782 - classification_loss: 0.0525 74/500 [===>..........................] - ETA: 2:17 - loss: 0.5289 - regression_loss: 0.4766 - classification_loss: 0.0524 75/500 [===>..........................] - ETA: 2:17 - loss: 0.5289 - regression_loss: 0.4764 - classification_loss: 0.0526 76/500 [===>..........................] - ETA: 2:17 - loss: 0.5328 - regression_loss: 0.4798 - classification_loss: 0.0530 77/500 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[============================>.] - ETA: 4s - loss: 0.5015 - regression_loss: 0.4496 - classification_loss: 0.0519 486/500 [============================>.] - ETA: 4s - loss: 0.5018 - regression_loss: 0.4499 - classification_loss: 0.0519 487/500 [============================>.] - ETA: 4s - loss: 0.5014 - regression_loss: 0.4496 - classification_loss: 0.0518 488/500 [============================>.] - ETA: 3s - loss: 0.5015 - regression_loss: 0.4497 - classification_loss: 0.0517 489/500 [============================>.] - ETA: 3s - loss: 0.5014 - regression_loss: 0.4498 - classification_loss: 0.0517 490/500 [============================>.] - ETA: 3s - loss: 0.5011 - regression_loss: 0.4495 - classification_loss: 0.0516 491/500 [============================>.] - ETA: 2s - loss: 0.5007 - regression_loss: 0.4491 - classification_loss: 0.0516 492/500 [============================>.] - ETA: 2s - loss: 0.5007 - regression_loss: 0.4492 - classification_loss: 0.0516 493/500 [============================>.] - ETA: 2s - loss: 0.5004 - regression_loss: 0.4489 - classification_loss: 0.0515 494/500 [============================>.] - ETA: 1s - loss: 0.5007 - regression_loss: 0.4492 - classification_loss: 0.0515 495/500 [============================>.] - ETA: 1s - loss: 0.5002 - regression_loss: 0.4487 - classification_loss: 0.0515 496/500 [============================>.] - ETA: 1s - loss: 0.5001 - regression_loss: 0.4486 - classification_loss: 0.0515 497/500 [============================>.] - ETA: 0s - loss: 0.4994 - regression_loss: 0.4480 - classification_loss: 0.0514 498/500 [============================>.] - ETA: 0s - loss: 0.5000 - regression_loss: 0.4486 - classification_loss: 0.0514 499/500 [============================>.] - ETA: 0s - loss: 0.4994 - regression_loss: 0.4480 - classification_loss: 0.0513 500/500 [==============================] - 162s 325ms/step - loss: 0.4998 - regression_loss: 0.4485 - classification_loss: 0.0513 326 instances of class plum with average precision: 0.7777 mAP: 0.7777 Epoch 00040: saving model to ./training/snapshots/resnet101_pascal_40.h5 Epoch 41/150 1/500 [..............................] - ETA: 2:26 - loss: 0.3212 - regression_loss: 0.2934 - classification_loss: 0.0278 2/500 [..............................] - ETA: 2:29 - loss: 0.2839 - regression_loss: 0.2592 - classification_loss: 0.0247 3/500 [..............................] - ETA: 2:38 - loss: 0.3412 - regression_loss: 0.3105 - classification_loss: 0.0306 4/500 [..............................] - ETA: 2:38 - loss: 0.4522 - regression_loss: 0.4050 - classification_loss: 0.0473 5/500 [..............................] - ETA: 2:37 - loss: 0.5018 - regression_loss: 0.4466 - classification_loss: 0.0552 6/500 [..............................] - ETA: 2:38 - loss: 0.4687 - regression_loss: 0.4186 - classification_loss: 0.0501 7/500 [..............................] - ETA: 2:38 - loss: 0.5616 - regression_loss: 0.4760 - classification_loss: 0.0857 8/500 [..............................] - ETA: 2:39 - loss: 0.5961 - regression_loss: 0.5037 - classification_loss: 0.0924 9/500 [..............................] - ETA: 2:39 - loss: 0.6360 - regression_loss: 0.5347 - classification_loss: 0.1013 10/500 [..............................] - ETA: 2:38 - loss: 0.6241 - regression_loss: 0.5286 - classification_loss: 0.0955 11/500 [..............................] - ETA: 2:37 - loss: 0.6129 - regression_loss: 0.5231 - classification_loss: 0.0898 12/500 [..............................] - ETA: 2:37 - loss: 0.6308 - regression_loss: 0.5373 - classification_loss: 0.0936 13/500 [..............................] - ETA: 2:37 - loss: 0.6286 - regression_loss: 0.5404 - classification_loss: 0.0883 14/500 [..............................] - ETA: 2:36 - loss: 0.6233 - regression_loss: 0.5377 - classification_loss: 0.0856 15/500 [..............................] - ETA: 2:36 - loss: 0.5986 - regression_loss: 0.5162 - classification_loss: 0.0825 16/500 [..............................] - ETA: 2:36 - loss: 0.5775 - regression_loss: 0.4985 - classification_loss: 0.0789 17/500 [>.............................] - ETA: 2:35 - loss: 0.5663 - regression_loss: 0.4900 - classification_loss: 0.0763 18/500 [>.............................] - ETA: 2:35 - loss: 0.5702 - regression_loss: 0.4968 - classification_loss: 0.0735 19/500 [>.............................] - ETA: 2:34 - loss: 0.5611 - regression_loss: 0.4891 - classification_loss: 0.0720 20/500 [>.............................] - ETA: 2:33 - loss: 0.5905 - regression_loss: 0.5146 - classification_loss: 0.0759 21/500 [>.............................] - ETA: 2:33 - loss: 0.5740 - regression_loss: 0.5004 - classification_loss: 0.0736 22/500 [>.............................] - ETA: 2:32 - loss: 0.5547 - regression_loss: 0.4837 - classification_loss: 0.0710 23/500 [>.............................] - ETA: 2:32 - loss: 0.5427 - regression_loss: 0.4739 - classification_loss: 0.0688 24/500 [>.............................] - ETA: 2:32 - loss: 0.5412 - regression_loss: 0.4726 - classification_loss: 0.0686 25/500 [>.............................] - ETA: 2:31 - loss: 0.5401 - regression_loss: 0.4720 - classification_loss: 0.0682 26/500 [>.............................] - ETA: 2:31 - loss: 0.5359 - regression_loss: 0.4697 - classification_loss: 0.0663 27/500 [>.............................] - ETA: 2:31 - loss: 0.5496 - regression_loss: 0.4797 - classification_loss: 0.0699 28/500 [>.............................] - ETA: 2:31 - loss: 0.5474 - regression_loss: 0.4785 - classification_loss: 0.0689 29/500 [>.............................] - ETA: 2:30 - loss: 0.5678 - regression_loss: 0.4971 - classification_loss: 0.0707 30/500 [>.............................] - ETA: 2:30 - loss: 0.5650 - regression_loss: 0.4958 - classification_loss: 0.0692 31/500 [>.............................] - ETA: 2:30 - loss: 0.5515 - regression_loss: 0.4842 - classification_loss: 0.0673 32/500 [>.............................] - ETA: 2:30 - loss: 0.5605 - regression_loss: 0.4927 - classification_loss: 0.0678 33/500 [>.............................] - ETA: 2:29 - loss: 0.5815 - regression_loss: 0.5080 - classification_loss: 0.0735 34/500 [=>............................] - ETA: 2:29 - loss: 0.5800 - regression_loss: 0.5075 - classification_loss: 0.0725 35/500 [=>............................] - ETA: 2:29 - loss: 0.5705 - regression_loss: 0.4994 - classification_loss: 0.0710 36/500 [=>............................] - ETA: 2:29 - loss: 0.5664 - regression_loss: 0.4960 - classification_loss: 0.0704 37/500 [=>............................] - ETA: 2:29 - loss: 0.5642 - regression_loss: 0.4944 - classification_loss: 0.0698 38/500 [=>............................] - ETA: 2:28 - loss: 0.5646 - regression_loss: 0.4958 - classification_loss: 0.0689 39/500 [=>............................] - ETA: 2:28 - loss: 0.5591 - regression_loss: 0.4912 - classification_loss: 0.0679 40/500 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[==>...........................] - ETA: 2:23 - loss: 0.5020 - regression_loss: 0.4449 - classification_loss: 0.0571 57/500 [==>...........................] - ETA: 2:22 - loss: 0.4959 - regression_loss: 0.4396 - classification_loss: 0.0564 58/500 [==>...........................] - ETA: 2:22 - loss: 0.4909 - regression_loss: 0.4353 - classification_loss: 0.0556 59/500 [==>...........................] - ETA: 2:22 - loss: 0.4936 - regression_loss: 0.4381 - classification_loss: 0.0555 60/500 [==>...........................] - ETA: 2:21 - loss: 0.4894 - regression_loss: 0.4345 - classification_loss: 0.0550 61/500 [==>...........................] - ETA: 2:21 - loss: 0.4890 - regression_loss: 0.4334 - classification_loss: 0.0557 62/500 [==>...........................] - ETA: 2:21 - loss: 0.4886 - regression_loss: 0.4331 - classification_loss: 0.0555 63/500 [==>...........................] - ETA: 2:20 - loss: 0.4905 - regression_loss: 0.4349 - classification_loss: 0.0556 64/500 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[===>..........................] - ETA: 2:18 - loss: 0.4813 - regression_loss: 0.4287 - classification_loss: 0.0525 73/500 [===>..........................] - ETA: 2:17 - loss: 0.4819 - regression_loss: 0.4296 - classification_loss: 0.0523 74/500 [===>..........................] - ETA: 2:17 - loss: 0.4800 - regression_loss: 0.4280 - classification_loss: 0.0520 75/500 [===>..........................] - ETA: 2:17 - loss: 0.4868 - regression_loss: 0.4335 - classification_loss: 0.0533 76/500 [===>..........................] - ETA: 2:16 - loss: 0.4884 - regression_loss: 0.4351 - classification_loss: 0.0533 77/500 [===>..........................] - ETA: 2:16 - loss: 0.4899 - regression_loss: 0.4368 - classification_loss: 0.0531 78/500 [===>..........................] - ETA: 2:15 - loss: 0.4867 - regression_loss: 0.4341 - classification_loss: 0.0526 79/500 [===>..........................] - ETA: 2:15 - loss: 0.4875 - regression_loss: 0.4350 - classification_loss: 0.0525 80/500 [===>..........................] - ETA: 2:15 - loss: 0.4894 - regression_loss: 0.4370 - classification_loss: 0.0523 81/500 [===>..........................] - ETA: 2:15 - loss: 0.4904 - regression_loss: 0.4382 - classification_loss: 0.0522 82/500 [===>..........................] - ETA: 2:14 - loss: 0.4908 - regression_loss: 0.4389 - classification_loss: 0.0519 83/500 [===>..........................] - ETA: 2:14 - loss: 0.4964 - regression_loss: 0.4439 - classification_loss: 0.0525 84/500 [====>.........................] - ETA: 2:14 - loss: 0.4979 - regression_loss: 0.4454 - classification_loss: 0.0525 85/500 [====>.........................] - ETA: 2:14 - loss: 0.5022 - regression_loss: 0.4497 - classification_loss: 0.0525 86/500 [====>.........................] - ETA: 2:13 - loss: 0.5021 - regression_loss: 0.4499 - classification_loss: 0.0521 87/500 [====>.........................] - ETA: 2:13 - loss: 0.5041 - regression_loss: 0.4519 - classification_loss: 0.0522 88/500 [====>.........................] - ETA: 2:13 - loss: 0.5001 - regression_loss: 0.4484 - classification_loss: 0.0518 89/500 [====>.........................] - ETA: 2:12 - loss: 0.5012 - regression_loss: 0.4494 - classification_loss: 0.0518 90/500 [====>.........................] - ETA: 2:12 - loss: 0.5016 - regression_loss: 0.4498 - classification_loss: 0.0518 91/500 [====>.........................] - ETA: 2:12 - loss: 0.4999 - regression_loss: 0.4483 - classification_loss: 0.0516 92/500 [====>.........................] - ETA: 2:11 - loss: 0.4969 - regression_loss: 0.4453 - classification_loss: 0.0516 93/500 [====>.........................] - ETA: 2:11 - loss: 0.4960 - regression_loss: 0.4448 - classification_loss: 0.0512 94/500 [====>.........................] - ETA: 2:11 - loss: 0.4939 - regression_loss: 0.4430 - classification_loss: 0.0509 95/500 [====>.........................] - ETA: 2:10 - loss: 0.5013 - regression_loss: 0.4483 - classification_loss: 0.0530 96/500 [====>.........................] - ETA: 2:10 - loss: 0.5014 - regression_loss: 0.4486 - classification_loss: 0.0529 97/500 [====>.........................] - ETA: 2:10 - loss: 0.5019 - regression_loss: 0.4493 - classification_loss: 0.0526 98/500 [====>.........................] - ETA: 2:10 - loss: 0.4998 - regression_loss: 0.4475 - classification_loss: 0.0523 99/500 [====>.........................] - ETA: 2:09 - loss: 0.5015 - regression_loss: 0.4490 - classification_loss: 0.0524 100/500 [=====>........................] - ETA: 2:09 - loss: 0.5010 - regression_loss: 0.4487 - classification_loss: 0.0523 101/500 [=====>........................] - ETA: 2:08 - loss: 0.5001 - regression_loss: 0.4477 - classification_loss: 0.0524 102/500 [=====>........................] - ETA: 2:08 - loss: 0.4985 - regression_loss: 0.4464 - classification_loss: 0.0521 103/500 [=====>........................] - ETA: 2:08 - loss: 0.4987 - regression_loss: 0.4468 - classification_loss: 0.0519 104/500 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[=====>........................] - ETA: 2:05 - loss: 0.5027 - regression_loss: 0.4497 - classification_loss: 0.0530 113/500 [=====>........................] - ETA: 2:04 - loss: 0.5035 - regression_loss: 0.4503 - classification_loss: 0.0532 114/500 [=====>........................] - ETA: 2:04 - loss: 0.5035 - regression_loss: 0.4505 - classification_loss: 0.0530 115/500 [=====>........................] - ETA: 2:04 - loss: 0.5055 - regression_loss: 0.4523 - classification_loss: 0.0532 116/500 [=====>........................] - ETA: 2:03 - loss: 0.5062 - regression_loss: 0.4530 - classification_loss: 0.0533 117/500 [======>.......................] - ETA: 2:03 - loss: 0.5056 - regression_loss: 0.4525 - classification_loss: 0.0531 118/500 [======>.......................] - ETA: 2:03 - loss: 0.5073 - regression_loss: 0.4540 - classification_loss: 0.0533 119/500 [======>.......................] - ETA: 2:02 - loss: 0.5115 - regression_loss: 0.4570 - classification_loss: 0.0545 120/500 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[===========================>..] - ETA: 6s - loss: 0.4942 - regression_loss: 0.4439 - classification_loss: 0.0503 481/500 [===========================>..] - ETA: 6s - loss: 0.4940 - regression_loss: 0.4437 - classification_loss: 0.0503 482/500 [===========================>..] - ETA: 5s - loss: 0.4949 - regression_loss: 0.4446 - classification_loss: 0.0504 483/500 [===========================>..] - ETA: 5s - loss: 0.4951 - regression_loss: 0.4448 - classification_loss: 0.0503 484/500 [============================>.] - ETA: 5s - loss: 0.4947 - regression_loss: 0.4445 - classification_loss: 0.0503 485/500 [============================>.] - ETA: 4s - loss: 0.4951 - regression_loss: 0.4449 - classification_loss: 0.0502 486/500 [============================>.] - ETA: 4s - loss: 0.4972 - regression_loss: 0.4464 - classification_loss: 0.0507 487/500 [============================>.] - ETA: 4s - loss: 0.4979 - regression_loss: 0.4472 - classification_loss: 0.0508 488/500 [============================>.] - ETA: 3s - loss: 0.4993 - regression_loss: 0.4483 - classification_loss: 0.0510 489/500 [============================>.] - ETA: 3s - loss: 0.4994 - regression_loss: 0.4484 - classification_loss: 0.0510 490/500 [============================>.] - ETA: 3s - loss: 0.4988 - regression_loss: 0.4479 - classification_loss: 0.0509 491/500 [============================>.] - ETA: 2s - loss: 0.4985 - regression_loss: 0.4476 - classification_loss: 0.0509 492/500 [============================>.] - ETA: 2s - loss: 0.4982 - regression_loss: 0.4473 - classification_loss: 0.0508 493/500 [============================>.] - ETA: 2s - loss: 0.4977 - regression_loss: 0.4469 - classification_loss: 0.0508 494/500 [============================>.] - ETA: 1s - loss: 0.4982 - regression_loss: 0.4473 - classification_loss: 0.0509 495/500 [============================>.] - ETA: 1s - loss: 0.4983 - regression_loss: 0.4474 - classification_loss: 0.0509 496/500 [============================>.] - ETA: 1s - loss: 0.4986 - regression_loss: 0.4476 - classification_loss: 0.0510 497/500 [============================>.] - ETA: 0s - loss: 0.4981 - regression_loss: 0.4472 - classification_loss: 0.0509 498/500 [============================>.] - ETA: 0s - loss: 0.4979 - regression_loss: 0.4470 - classification_loss: 0.0509 499/500 [============================>.] - ETA: 0s - loss: 0.4979 - regression_loss: 0.4471 - classification_loss: 0.0509 500/500 [==============================] - 162s 324ms/step - loss: 0.4975 - regression_loss: 0.4467 - classification_loss: 0.0508 326 instances of class plum with average precision: 0.7786 mAP: 0.7786 Epoch 00041: saving model to ./training/snapshots/resnet101_pascal_41.h5 Epoch 42/150 1/500 [..............................] - ETA: 2:35 - loss: 0.5499 - regression_loss: 0.4870 - classification_loss: 0.0630 2/500 [..............................] - ETA: 2:36 - loss: 0.5345 - regression_loss: 0.4850 - classification_loss: 0.0496 3/500 [..............................] - ETA: 2:34 - loss: 0.4589 - regression_loss: 0.4179 - classification_loss: 0.0410 4/500 [..............................] - ETA: 2:34 - loss: 0.4036 - regression_loss: 0.3649 - classification_loss: 0.0387 5/500 [..............................] - ETA: 2:38 - loss: 0.3959 - regression_loss: 0.3605 - classification_loss: 0.0354 6/500 [..............................] - ETA: 2:40 - loss: 0.4361 - regression_loss: 0.3969 - classification_loss: 0.0393 7/500 [..............................] - ETA: 2:40 - loss: 0.3901 - regression_loss: 0.3552 - classification_loss: 0.0350 8/500 [..............................] - ETA: 2:42 - loss: 0.4733 - regression_loss: 0.4067 - classification_loss: 0.0666 9/500 [..............................] - ETA: 2:42 - loss: 0.4510 - regression_loss: 0.3890 - classification_loss: 0.0620 10/500 [..............................] - ETA: 2:44 - loss: 0.4750 - regression_loss: 0.4096 - classification_loss: 0.0654 11/500 [..............................] - ETA: 2:44 - loss: 0.4663 - regression_loss: 0.4034 - classification_loss: 0.0628 12/500 [..............................] - ETA: 2:43 - loss: 0.4487 - regression_loss: 0.3893 - classification_loss: 0.0594 13/500 [..............................] - ETA: 2:42 - loss: 0.4487 - regression_loss: 0.3911 - classification_loss: 0.0575 14/500 [..............................] - ETA: 2:41 - loss: 0.4632 - regression_loss: 0.4078 - classification_loss: 0.0554 15/500 [..............................] - ETA: 2:41 - loss: 0.4734 - regression_loss: 0.4197 - classification_loss: 0.0537 16/500 [..............................] - ETA: 2:42 - loss: 0.4692 - regression_loss: 0.4164 - classification_loss: 0.0527 17/500 [>.............................] - ETA: 2:41 - loss: 0.4849 - regression_loss: 0.4330 - classification_loss: 0.0519 18/500 [>.............................] - ETA: 2:41 - loss: 0.4789 - regression_loss: 0.4293 - classification_loss: 0.0496 19/500 [>.............................] - ETA: 2:40 - loss: 0.4825 - regression_loss: 0.4327 - classification_loss: 0.0498 20/500 [>.............................] - ETA: 2:40 - loss: 0.4859 - regression_loss: 0.4363 - classification_loss: 0.0495 21/500 [>.............................] - ETA: 2:40 - loss: 0.4900 - regression_loss: 0.4396 - classification_loss: 0.0504 22/500 [>.............................] - ETA: 2:39 - loss: 0.4928 - regression_loss: 0.4431 - classification_loss: 0.0498 23/500 [>.............................] - ETA: 2:39 - loss: 0.4900 - regression_loss: 0.4414 - classification_loss: 0.0486 24/500 [>.............................] - ETA: 2:39 - loss: 0.4865 - regression_loss: 0.4386 - classification_loss: 0.0479 25/500 [>.............................] - ETA: 2:38 - loss: 0.4928 - regression_loss: 0.4441 - classification_loss: 0.0487 26/500 [>.............................] - ETA: 2:37 - loss: 0.4881 - regression_loss: 0.4405 - classification_loss: 0.0476 27/500 [>.............................] - ETA: 2:37 - loss: 0.4764 - regression_loss: 0.4300 - classification_loss: 0.0464 28/500 [>.............................] - ETA: 2:36 - loss: 0.4747 - regression_loss: 0.4279 - classification_loss: 0.0468 29/500 [>.............................] - ETA: 2:35 - loss: 0.4819 - regression_loss: 0.4339 - classification_loss: 0.0480 30/500 [>.............................] - ETA: 2:34 - loss: 0.4751 - regression_loss: 0.4281 - classification_loss: 0.0470 31/500 [>.............................] - ETA: 2:34 - loss: 0.4761 - regression_loss: 0.4294 - classification_loss: 0.0467 32/500 [>.............................] - ETA: 2:34 - loss: 0.4910 - regression_loss: 0.4430 - classification_loss: 0.0481 33/500 [>.............................] - ETA: 2:33 - loss: 0.4943 - regression_loss: 0.4462 - classification_loss: 0.0482 34/500 [=>............................] - ETA: 2:33 - loss: 0.4927 - regression_loss: 0.4452 - classification_loss: 0.0475 35/500 [=>............................] - ETA: 2:32 - loss: 0.4845 - regression_loss: 0.4377 - classification_loss: 0.0468 36/500 [=>............................] - ETA: 2:32 - loss: 0.4925 - regression_loss: 0.4451 - classification_loss: 0.0474 37/500 [=>............................] - ETA: 2:32 - loss: 0.5001 - regression_loss: 0.4529 - classification_loss: 0.0471 38/500 [=>............................] - ETA: 2:31 - loss: 0.5018 - regression_loss: 0.4523 - classification_loss: 0.0496 39/500 [=>............................] - ETA: 2:31 - loss: 0.4996 - regression_loss: 0.4505 - classification_loss: 0.0491 40/500 [=>............................] - ETA: 2:31 - loss: 0.4998 - regression_loss: 0.4509 - classification_loss: 0.0489 41/500 [=>............................] - ETA: 2:30 - loss: 0.4971 - regression_loss: 0.4488 - classification_loss: 0.0483 42/500 [=>............................] - ETA: 2:29 - loss: 0.4959 - regression_loss: 0.4476 - classification_loss: 0.0483 43/500 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[==>...........................] - ETA: 2:27 - loss: 0.4862 - regression_loss: 0.4403 - classification_loss: 0.0458 52/500 [==>...........................] - ETA: 2:27 - loss: 0.4870 - regression_loss: 0.4394 - classification_loss: 0.0477 53/500 [==>...........................] - ETA: 2:27 - loss: 0.4822 - regression_loss: 0.4346 - classification_loss: 0.0476 54/500 [==>...........................] - ETA: 2:26 - loss: 0.4842 - regression_loss: 0.4365 - classification_loss: 0.0476 55/500 [==>...........................] - ETA: 2:26 - loss: 0.4878 - regression_loss: 0.4400 - classification_loss: 0.0478 56/500 [==>...........................] - ETA: 2:26 - loss: 0.4881 - regression_loss: 0.4407 - classification_loss: 0.0475 57/500 [==>...........................] - ETA: 2:25 - loss: 0.4832 - regression_loss: 0.4362 - classification_loss: 0.0470 58/500 [==>...........................] - ETA: 2:25 - loss: 0.4829 - regression_loss: 0.4361 - classification_loss: 0.0468 59/500 [==>...........................] - ETA: 2:24 - loss: 0.4825 - regression_loss: 0.4358 - classification_loss: 0.0467 60/500 [==>...........................] - ETA: 2:24 - loss: 0.4861 - regression_loss: 0.4389 - classification_loss: 0.0472 61/500 [==>...........................] - ETA: 2:24 - loss: 0.4845 - regression_loss: 0.4372 - classification_loss: 0.0473 62/500 [==>...........................] - ETA: 2:23 - loss: 0.4845 - regression_loss: 0.4374 - classification_loss: 0.0471 63/500 [==>...........................] - ETA: 2:23 - loss: 0.4833 - regression_loss: 0.4359 - classification_loss: 0.0474 64/500 [==>...........................] - ETA: 2:23 - loss: 0.4798 - regression_loss: 0.4329 - classification_loss: 0.0469 65/500 [==>...........................] - ETA: 2:23 - loss: 0.4799 - regression_loss: 0.4332 - classification_loss: 0.0467 66/500 [==>...........................] - ETA: 2:22 - loss: 0.4817 - regression_loss: 0.4351 - classification_loss: 0.0467 67/500 [===>..........................] - ETA: 2:22 - loss: 0.4812 - regression_loss: 0.4347 - classification_loss: 0.0465 68/500 [===>..........................] - ETA: 2:22 - loss: 0.4822 - regression_loss: 0.4355 - classification_loss: 0.0467 69/500 [===>..........................] - ETA: 2:21 - loss: 0.4836 - regression_loss: 0.4370 - classification_loss: 0.0467 70/500 [===>..........................] - ETA: 2:21 - loss: 0.4821 - regression_loss: 0.4356 - classification_loss: 0.0465 71/500 [===>..........................] - ETA: 2:21 - loss: 0.4809 - regression_loss: 0.4344 - classification_loss: 0.0465 72/500 [===>..........................] - ETA: 2:20 - loss: 0.4782 - regression_loss: 0.4319 - classification_loss: 0.0463 73/500 [===>..........................] - ETA: 2:20 - loss: 0.4800 - regression_loss: 0.4338 - classification_loss: 0.0463 74/500 [===>..........................] - ETA: 2:19 - loss: 0.4790 - regression_loss: 0.4329 - classification_loss: 0.0461 75/500 [===>..........................] - ETA: 2:19 - loss: 0.4764 - regression_loss: 0.4306 - classification_loss: 0.0458 76/500 [===>..........................] - ETA: 2:19 - loss: 0.4741 - regression_loss: 0.4283 - classification_loss: 0.0458 77/500 [===>..........................] - ETA: 2:18 - loss: 0.4706 - regression_loss: 0.4252 - classification_loss: 0.0454 78/500 [===>..........................] - ETA: 2:18 - loss: 0.4721 - regression_loss: 0.4265 - classification_loss: 0.0455 79/500 [===>..........................] - ETA: 2:17 - loss: 0.4768 - regression_loss: 0.4296 - classification_loss: 0.0473 80/500 [===>..........................] - ETA: 2:17 - loss: 0.4774 - regression_loss: 0.4294 - classification_loss: 0.0479 81/500 [===>..........................] - ETA: 2:17 - loss: 0.4759 - regression_loss: 0.4282 - classification_loss: 0.0477 82/500 [===>..........................] - ETA: 2:16 - loss: 0.4756 - regression_loss: 0.4280 - classification_loss: 0.0476 83/500 [===>..........................] - ETA: 2:16 - loss: 0.4711 - regression_loss: 0.4239 - classification_loss: 0.0472 84/500 [====>.........................] - ETA: 2:16 - loss: 0.4710 - regression_loss: 0.4240 - classification_loss: 0.0470 85/500 [====>.........................] - ETA: 2:15 - loss: 0.4685 - regression_loss: 0.4218 - classification_loss: 0.0467 86/500 [====>.........................] - ETA: 2:15 - loss: 0.4684 - regression_loss: 0.4218 - classification_loss: 0.0466 87/500 [====>.........................] - ETA: 2:15 - loss: 0.4725 - regression_loss: 0.4247 - classification_loss: 0.0478 88/500 [====>.........................] - ETA: 2:14 - loss: 0.4710 - regression_loss: 0.4234 - classification_loss: 0.0475 89/500 [====>.........................] - ETA: 2:14 - loss: 0.4697 - regression_loss: 0.4220 - classification_loss: 0.0478 90/500 [====>.........................] - ETA: 2:14 - loss: 0.4681 - regression_loss: 0.4204 - classification_loss: 0.0477 91/500 [====>.........................] - ETA: 2:13 - loss: 0.4688 - regression_loss: 0.4209 - classification_loss: 0.0479 92/500 [====>.........................] - ETA: 2:13 - loss: 0.4686 - regression_loss: 0.4205 - classification_loss: 0.0481 93/500 [====>.........................] - ETA: 2:13 - loss: 0.4669 - regression_loss: 0.4191 - classification_loss: 0.0478 94/500 [====>.........................] - ETA: 2:12 - loss: 0.4710 - regression_loss: 0.4227 - classification_loss: 0.0483 95/500 [====>.........................] - ETA: 2:12 - loss: 0.4687 - regression_loss: 0.4208 - classification_loss: 0.0479 96/500 [====>.........................] - ETA: 2:11 - loss: 0.4677 - regression_loss: 0.4199 - classification_loss: 0.0478 97/500 [====>.........................] - ETA: 2:11 - loss: 0.4650 - regression_loss: 0.4174 - classification_loss: 0.0476 98/500 [====>.........................] - ETA: 2:11 - loss: 0.4637 - regression_loss: 0.4162 - classification_loss: 0.0475 99/500 [====>.........................] - ETA: 2:11 - loss: 0.4610 - regression_loss: 0.4139 - classification_loss: 0.0472 100/500 [=====>........................] - ETA: 2:10 - loss: 0.4627 - regression_loss: 0.4157 - classification_loss: 0.0470 101/500 [=====>........................] - ETA: 2:10 - loss: 0.4603 - regression_loss: 0.4136 - classification_loss: 0.0468 102/500 [=====>........................] - ETA: 2:09 - loss: 0.4633 - regression_loss: 0.4161 - classification_loss: 0.0471 103/500 [=====>........................] - ETA: 2:09 - loss: 0.4634 - regression_loss: 0.4163 - classification_loss: 0.0471 104/500 [=====>........................] - ETA: 2:09 - loss: 0.4652 - regression_loss: 0.4182 - classification_loss: 0.0470 105/500 [=====>........................] - ETA: 2:08 - loss: 0.4643 - regression_loss: 0.4175 - classification_loss: 0.0468 106/500 [=====>........................] - ETA: 2:08 - loss: 0.4672 - regression_loss: 0.4201 - classification_loss: 0.0471 107/500 [=====>........................] - ETA: 2:08 - loss: 0.4672 - regression_loss: 0.4203 - classification_loss: 0.0470 108/500 [=====>........................] - ETA: 2:08 - loss: 0.4647 - regression_loss: 0.4181 - classification_loss: 0.0467 109/500 [=====>........................] - ETA: 2:07 - loss: 0.4635 - regression_loss: 0.4170 - classification_loss: 0.0465 110/500 [=====>........................] - ETA: 2:07 - loss: 0.4642 - regression_loss: 0.4178 - classification_loss: 0.0464 111/500 [=====>........................] - ETA: 2:07 - loss: 0.4625 - regression_loss: 0.4162 - classification_loss: 0.0463 112/500 [=====>........................] - ETA: 2:06 - loss: 0.4610 - regression_loss: 0.4146 - classification_loss: 0.0464 113/500 [=====>........................] - ETA: 2:06 - loss: 0.4581 - regression_loss: 0.4120 - classification_loss: 0.0461 114/500 [=====>........................] - ETA: 2:06 - loss: 0.4575 - regression_loss: 0.4115 - classification_loss: 0.0461 115/500 [=====>........................] - ETA: 2:05 - loss: 0.4577 - regression_loss: 0.4115 - classification_loss: 0.0462 116/500 [=====>........................] - ETA: 2:05 - loss: 0.4583 - regression_loss: 0.4122 - classification_loss: 0.0461 117/500 [======>.......................] - ETA: 2:05 - loss: 0.4598 - regression_loss: 0.4135 - classification_loss: 0.0463 118/500 [======>.......................] - ETA: 2:04 - loss: 0.4598 - regression_loss: 0.4135 - classification_loss: 0.0462 119/500 [======>.......................] - ETA: 2:04 - loss: 0.4571 - regression_loss: 0.4111 - classification_loss: 0.0459 120/500 [======>.......................] - ETA: 2:04 - loss: 0.4551 - regression_loss: 0.4094 - classification_loss: 0.0457 121/500 [======>.......................] - ETA: 2:03 - loss: 0.4539 - regression_loss: 0.4083 - classification_loss: 0.0457 122/500 [======>.......................] - ETA: 2:03 - loss: 0.4530 - regression_loss: 0.4075 - classification_loss: 0.0455 123/500 [======>.......................] - ETA: 2:03 - loss: 0.4520 - regression_loss: 0.4067 - classification_loss: 0.0453 124/500 [======>.......................] - ETA: 2:02 - loss: 0.4498 - regression_loss: 0.4048 - classification_loss: 0.0451 125/500 [======>.......................] - ETA: 2:02 - loss: 0.4487 - regression_loss: 0.4037 - classification_loss: 0.0450 126/500 [======>.......................] - ETA: 2:02 - loss: 0.4480 - regression_loss: 0.4032 - classification_loss: 0.0448 127/500 [======>.......................] - ETA: 2:02 - loss: 0.4465 - regression_loss: 0.4019 - classification_loss: 0.0446 128/500 [======>.......................] - ETA: 2:01 - loss: 0.4469 - regression_loss: 0.4026 - classification_loss: 0.0444 129/500 [======>.......................] - ETA: 2:01 - loss: 0.4467 - regression_loss: 0.4024 - classification_loss: 0.0444 130/500 [======>.......................] - ETA: 2:01 - loss: 0.4448 - regression_loss: 0.4007 - classification_loss: 0.0441 131/500 [======>.......................] - ETA: 2:00 - loss: 0.4465 - regression_loss: 0.4021 - classification_loss: 0.0444 132/500 [======>.......................] - ETA: 2:00 - loss: 0.4479 - regression_loss: 0.4036 - classification_loss: 0.0443 133/500 [======>.......................] - ETA: 2:00 - loss: 0.4531 - regression_loss: 0.4073 - classification_loss: 0.0458 134/500 [=======>......................] - ETA: 1:59 - loss: 0.4555 - regression_loss: 0.4093 - classification_loss: 0.0462 135/500 [=======>......................] - ETA: 1:59 - loss: 0.4555 - regression_loss: 0.4094 - classification_loss: 0.0461 136/500 [=======>......................] - ETA: 1:58 - loss: 0.4569 - regression_loss: 0.4110 - classification_loss: 0.0459 137/500 [=======>......................] - ETA: 1:58 - loss: 0.4578 - regression_loss: 0.4117 - classification_loss: 0.0462 138/500 [=======>......................] - ETA: 1:58 - loss: 0.4579 - regression_loss: 0.4118 - classification_loss: 0.0461 139/500 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[============================>.] - ETA: 2s - loss: 0.4767 - regression_loss: 0.4284 - classification_loss: 0.0483 492/500 [============================>.] - ETA: 2s - loss: 0.4768 - regression_loss: 0.4286 - classification_loss: 0.0482 493/500 [============================>.] - ETA: 2s - loss: 0.4768 - regression_loss: 0.4286 - classification_loss: 0.0482 494/500 [============================>.] - ETA: 1s - loss: 0.4774 - regression_loss: 0.4292 - classification_loss: 0.0483 495/500 [============================>.] - ETA: 1s - loss: 0.4767 - regression_loss: 0.4286 - classification_loss: 0.0482 496/500 [============================>.] - ETA: 1s - loss: 0.4767 - regression_loss: 0.4285 - classification_loss: 0.0481 497/500 [============================>.] - ETA: 0s - loss: 0.4771 - regression_loss: 0.4289 - classification_loss: 0.0481 498/500 [============================>.] - ETA: 0s - loss: 0.4771 - regression_loss: 0.4289 - classification_loss: 0.0481 499/500 [============================>.] - ETA: 0s - loss: 0.4767 - regression_loss: 0.4286 - classification_loss: 0.0481 500/500 [==============================] - 163s 326ms/step - loss: 0.4769 - regression_loss: 0.4288 - classification_loss: 0.0481 326 instances of class plum with average precision: 0.7753 mAP: 0.7753 Epoch 00042: saving model to ./training/snapshots/resnet101_pascal_42.h5 Epoch 43/150 1/500 [..............................] - ETA: 2:40 - loss: 0.3038 - regression_loss: 0.2779 - classification_loss: 0.0259 2/500 [..............................] - ETA: 2:42 - loss: 0.3269 - regression_loss: 0.2940 - classification_loss: 0.0329 3/500 [..............................] - ETA: 2:40 - loss: 0.5097 - regression_loss: 0.4202 - classification_loss: 0.0895 4/500 [..............................] - ETA: 2:42 - loss: 0.4564 - regression_loss: 0.3835 - classification_loss: 0.0729 5/500 [..............................] - ETA: 2:41 - loss: 0.4336 - regression_loss: 0.3690 - 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[============================>.] - ETA: 4s - loss: 0.4643 - regression_loss: 0.4172 - classification_loss: 0.0472 487/500 [============================>.] - ETA: 4s - loss: 0.4637 - regression_loss: 0.4166 - classification_loss: 0.0471 488/500 [============================>.] - ETA: 3s - loss: 0.4633 - regression_loss: 0.4162 - classification_loss: 0.0471 489/500 [============================>.] - ETA: 3s - loss: 0.4630 - regression_loss: 0.4160 - classification_loss: 0.0470 490/500 [============================>.] - ETA: 3s - loss: 0.4629 - regression_loss: 0.4160 - classification_loss: 0.0470 491/500 [============================>.] - ETA: 2s - loss: 0.4629 - regression_loss: 0.4160 - classification_loss: 0.0469 492/500 [============================>.] - ETA: 2s - loss: 0.4625 - regression_loss: 0.4157 - classification_loss: 0.0469 493/500 [============================>.] - ETA: 2s - loss: 0.4621 - regression_loss: 0.4153 - classification_loss: 0.0468 494/500 [============================>.] - ETA: 1s - loss: 0.4629 - regression_loss: 0.4160 - classification_loss: 0.0469 495/500 [============================>.] - ETA: 1s - loss: 0.4626 - regression_loss: 0.4158 - classification_loss: 0.0468 496/500 [============================>.] - ETA: 1s - loss: 0.4638 - regression_loss: 0.4166 - classification_loss: 0.0472 497/500 [============================>.] - ETA: 0s - loss: 0.4645 - regression_loss: 0.4172 - classification_loss: 0.0473 498/500 [============================>.] - ETA: 0s - loss: 0.4641 - regression_loss: 0.4168 - classification_loss: 0.0472 499/500 [============================>.] - ETA: 0s - loss: 0.4655 - regression_loss: 0.4179 - classification_loss: 0.0476 500/500 [==============================] - 162s 325ms/step - loss: 0.4657 - regression_loss: 0.4180 - classification_loss: 0.0477 326 instances of class plum with average precision: 0.7927 mAP: 0.7927 Epoch 00043: saving model to ./training/snapshots/resnet101_pascal_43.h5 Epoch 44/150 1/500 [..............................] - ETA: 2:39 - loss: 0.6466 - regression_loss: 0.5556 - classification_loss: 0.0910 2/500 [..............................] - ETA: 2:41 - loss: 0.5196 - regression_loss: 0.4594 - classification_loss: 0.0602 3/500 [..............................] - ETA: 2:38 - loss: 0.3825 - regression_loss: 0.3401 - classification_loss: 0.0424 4/500 [..............................] - ETA: 2:37 - loss: 0.3968 - regression_loss: 0.3522 - classification_loss: 0.0446 5/500 [..............................] - ETA: 2:40 - loss: 0.4227 - regression_loss: 0.3802 - classification_loss: 0.0425 6/500 [..............................] - ETA: 2:38 - loss: 0.4017 - regression_loss: 0.3635 - classification_loss: 0.0382 7/500 [..............................] - ETA: 2:37 - loss: 0.4119 - regression_loss: 0.3737 - classification_loss: 0.0382 8/500 [..............................] - ETA: 2:37 - loss: 0.5077 - regression_loss: 0.4471 - classification_loss: 0.0605 9/500 [..............................] - ETA: 2:36 - loss: 0.4959 - regression_loss: 0.4388 - classification_loss: 0.0571 10/500 [..............................] - ETA: 2:36 - loss: 0.4830 - regression_loss: 0.4269 - classification_loss: 0.0561 11/500 [..............................] - ETA: 2:37 - loss: 0.4773 - regression_loss: 0.4225 - classification_loss: 0.0548 12/500 [..............................] - ETA: 2:37 - loss: 0.5210 - regression_loss: 0.4459 - classification_loss: 0.0751 13/500 [..............................] - ETA: 2:37 - loss: 0.5460 - regression_loss: 0.4689 - classification_loss: 0.0771 14/500 [..............................] - ETA: 2:37 - loss: 0.5433 - regression_loss: 0.4680 - classification_loss: 0.0753 15/500 [..............................] - ETA: 2:37 - loss: 0.5345 - regression_loss: 0.4618 - classification_loss: 0.0726 16/500 [..............................] - ETA: 2:37 - loss: 0.6097 - regression_loss: 0.5156 - classification_loss: 0.0941 17/500 [>.............................] - ETA: 2:37 - loss: 0.5952 - regression_loss: 0.5034 - classification_loss: 0.0918 18/500 [>.............................] - ETA: 2:36 - loss: 0.5812 - regression_loss: 0.4929 - classification_loss: 0.0883 19/500 [>.............................] - ETA: 2:36 - loss: 0.5916 - regression_loss: 0.5061 - classification_loss: 0.0855 20/500 [>.............................] - ETA: 2:35 - loss: 0.5924 - regression_loss: 0.5083 - classification_loss: 0.0841 21/500 [>.............................] - ETA: 2:35 - loss: 0.5818 - regression_loss: 0.5010 - classification_loss: 0.0809 22/500 [>.............................] - ETA: 2:35 - loss: 0.6016 - regression_loss: 0.5203 - classification_loss: 0.0814 23/500 [>.............................] - ETA: 2:34 - loss: 0.5929 - regression_loss: 0.5139 - classification_loss: 0.0790 24/500 [>.............................] - ETA: 2:34 - loss: 0.5777 - regression_loss: 0.5013 - classification_loss: 0.0764 25/500 [>.............................] - ETA: 2:34 - loss: 0.5705 - regression_loss: 0.4959 - classification_loss: 0.0746 26/500 [>.............................] - ETA: 2:33 - loss: 0.5573 - regression_loss: 0.4847 - classification_loss: 0.0726 27/500 [>.............................] - ETA: 2:33 - loss: 0.5444 - regression_loss: 0.4716 - classification_loss: 0.0728 28/500 [>.............................] - ETA: 2:32 - loss: 0.5394 - regression_loss: 0.4633 - classification_loss: 0.0761 29/500 [>.............................] - ETA: 2:32 - loss: 0.5328 - regression_loss: 0.4576 - classification_loss: 0.0752 30/500 [>.............................] - ETA: 2:31 - loss: 0.5226 - regression_loss: 0.4495 - classification_loss: 0.0732 31/500 [>.............................] - ETA: 2:30 - loss: 0.5403 - regression_loss: 0.4638 - classification_loss: 0.0764 32/500 [>.............................] - ETA: 2:30 - loss: 0.5298 - regression_loss: 0.4548 - classification_loss: 0.0750 33/500 [>.............................] - ETA: 2:29 - loss: 0.5214 - regression_loss: 0.4475 - classification_loss: 0.0739 34/500 [=>............................] - ETA: 2:30 - loss: 0.5354 - regression_loss: 0.4579 - classification_loss: 0.0775 35/500 [=>............................] - ETA: 2:29 - loss: 0.5346 - regression_loss: 0.4578 - classification_loss: 0.0768 36/500 [=>............................] - ETA: 2:29 - loss: 0.5324 - regression_loss: 0.4569 - classification_loss: 0.0755 37/500 [=>............................] - ETA: 2:29 - loss: 0.5299 - regression_loss: 0.4557 - classification_loss: 0.0742 38/500 [=>............................] - ETA: 2:29 - loss: 0.5272 - regression_loss: 0.4543 - classification_loss: 0.0729 39/500 [=>............................] - ETA: 2:29 - loss: 0.5224 - regression_loss: 0.4507 - classification_loss: 0.0717 40/500 [=>............................] - ETA: 2:28 - loss: 0.5183 - regression_loss: 0.4476 - classification_loss: 0.0707 41/500 [=>............................] - ETA: 2:28 - loss: 0.5142 - regression_loss: 0.4445 - classification_loss: 0.0696 42/500 [=>............................] - ETA: 2:28 - loss: 0.5210 - regression_loss: 0.4506 - classification_loss: 0.0704 43/500 [=>............................] - ETA: 2:28 - loss: 0.5212 - regression_loss: 0.4519 - classification_loss: 0.0693 44/500 [=>............................] - ETA: 2:27 - loss: 0.5149 - regression_loss: 0.4465 - classification_loss: 0.0684 45/500 [=>............................] - ETA: 2:27 - loss: 0.5054 - regression_loss: 0.4381 - classification_loss: 0.0672 46/500 [=>............................] - ETA: 2:26 - loss: 0.5050 - regression_loss: 0.4382 - classification_loss: 0.0667 47/500 [=>............................] - ETA: 2:26 - loss: 0.5044 - regression_loss: 0.4384 - classification_loss: 0.0659 48/500 [=>............................] - ETA: 2:26 - loss: 0.5046 - regression_loss: 0.4396 - classification_loss: 0.0651 49/500 [=>............................] - ETA: 2:26 - loss: 0.5007 - regression_loss: 0.4358 - classification_loss: 0.0649 50/500 [==>...........................] - ETA: 2:26 - loss: 0.4990 - regression_loss: 0.4348 - classification_loss: 0.0642 51/500 [==>...........................] - ETA: 2:25 - loss: 0.4951 - regression_loss: 0.4314 - classification_loss: 0.0638 52/500 [==>...........................] - ETA: 2:25 - loss: 0.4910 - regression_loss: 0.4278 - classification_loss: 0.0633 53/500 [==>...........................] - ETA: 2:25 - loss: 0.4918 - regression_loss: 0.4290 - classification_loss: 0.0628 54/500 [==>...........................] - ETA: 2:24 - loss: 0.5004 - regression_loss: 0.4356 - classification_loss: 0.0648 55/500 [==>...........................] - ETA: 2:24 - loss: 0.5009 - regression_loss: 0.4364 - classification_loss: 0.0645 56/500 [==>...........................] - ETA: 2:24 - loss: 0.4975 - regression_loss: 0.4336 - classification_loss: 0.0639 57/500 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[====>.........................] - ETA: 2:13 - loss: 0.4682 - regression_loss: 0.4148 - classification_loss: 0.0534 90/500 [====>.........................] - ETA: 2:13 - loss: 0.4708 - regression_loss: 0.4176 - classification_loss: 0.0532 91/500 [====>.........................] - ETA: 2:12 - loss: 0.4700 - regression_loss: 0.4171 - classification_loss: 0.0528 92/500 [====>.........................] - ETA: 2:12 - loss: 0.4698 - regression_loss: 0.4173 - classification_loss: 0.0525 93/500 [====>.........................] - ETA: 2:12 - loss: 0.4736 - regression_loss: 0.4215 - classification_loss: 0.0521 94/500 [====>.........................] - ETA: 2:11 - loss: 0.4704 - regression_loss: 0.4187 - classification_loss: 0.0516 95/500 [====>.........................] - ETA: 2:11 - loss: 0.4695 - regression_loss: 0.4180 - classification_loss: 0.0515 96/500 [====>.........................] - ETA: 2:11 - loss: 0.4691 - regression_loss: 0.4176 - classification_loss: 0.0514 97/500 [====>.........................] - ETA: 2:10 - loss: 0.4681 - regression_loss: 0.4170 - classification_loss: 0.0511 98/500 [====>.........................] - ETA: 2:10 - loss: 0.4705 - regression_loss: 0.4191 - classification_loss: 0.0514 99/500 [====>.........................] - ETA: 2:10 - loss: 0.4713 - regression_loss: 0.4200 - classification_loss: 0.0514 100/500 [=====>........................] - ETA: 2:09 - loss: 0.4745 - regression_loss: 0.4225 - classification_loss: 0.0520 101/500 [=====>........................] - ETA: 2:09 - loss: 0.4718 - regression_loss: 0.4202 - classification_loss: 0.0516 102/500 [=====>........................] - ETA: 2:09 - loss: 0.4698 - regression_loss: 0.4185 - classification_loss: 0.0513 103/500 [=====>........................] - ETA: 2:08 - loss: 0.4680 - regression_loss: 0.4169 - classification_loss: 0.0510 104/500 [=====>........................] - ETA: 2:08 - loss: 0.4683 - regression_loss: 0.4172 - classification_loss: 0.0510 105/500 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[======>.......................] - ETA: 2:02 - loss: 0.4703 - regression_loss: 0.4215 - classification_loss: 0.0488 122/500 [======>.......................] - ETA: 2:02 - loss: 0.4709 - regression_loss: 0.4220 - classification_loss: 0.0489 123/500 [======>.......................] - ETA: 2:02 - loss: 0.4701 - regression_loss: 0.4215 - classification_loss: 0.0486 124/500 [======>.......................] - ETA: 2:01 - loss: 0.4674 - regression_loss: 0.4191 - classification_loss: 0.0483 125/500 [======>.......................] - ETA: 2:01 - loss: 0.4651 - regression_loss: 0.4171 - classification_loss: 0.0480 126/500 [======>.......................] - ETA: 2:01 - loss: 0.4657 - regression_loss: 0.4175 - classification_loss: 0.0482 127/500 [======>.......................] - ETA: 2:00 - loss: 0.4706 - regression_loss: 0.4204 - classification_loss: 0.0502 128/500 [======>.......................] - ETA: 2:00 - loss: 0.4693 - regression_loss: 0.4194 - classification_loss: 0.0499 129/500 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[==========>...................] - ETA: 1:42 - loss: 0.4748 - regression_loss: 0.4268 - classification_loss: 0.0480 186/500 [==========>...................] - ETA: 1:41 - loss: 0.4747 - regression_loss: 0.4266 - classification_loss: 0.0481 187/500 [==========>...................] - ETA: 1:41 - loss: 0.4731 - regression_loss: 0.4251 - classification_loss: 0.0480 188/500 [==========>...................] - ETA: 1:41 - loss: 0.4733 - regression_loss: 0.4253 - classification_loss: 0.0479 189/500 [==========>...................] - ETA: 1:40 - loss: 0.4736 - regression_loss: 0.4257 - classification_loss: 0.0479 190/500 [==========>...................] - ETA: 1:40 - loss: 0.4762 - regression_loss: 0.4279 - classification_loss: 0.0483 191/500 [==========>...................] - ETA: 1:40 - loss: 0.4759 - regression_loss: 0.4277 - classification_loss: 0.0483 192/500 [==========>...................] - ETA: 1:40 - loss: 0.4759 - regression_loss: 0.4277 - classification_loss: 0.0481 193/500 [==========>...................] - ETA: 1:39 - loss: 0.4755 - regression_loss: 0.4275 - classification_loss: 0.0480 194/500 [==========>...................] - ETA: 1:39 - loss: 0.4748 - regression_loss: 0.4269 - classification_loss: 0.0478 195/500 [==========>...................] - ETA: 1:39 - loss: 0.4782 - regression_loss: 0.4299 - classification_loss: 0.0483 196/500 [==========>...................] - ETA: 1:38 - loss: 0.4778 - regression_loss: 0.4296 - classification_loss: 0.0482 197/500 [==========>...................] - ETA: 1:38 - loss: 0.4774 - regression_loss: 0.4293 - classification_loss: 0.0481 198/500 [==========>...................] - ETA: 1:38 - loss: 0.4794 - regression_loss: 0.4312 - classification_loss: 0.0482 199/500 [==========>...................] - ETA: 1:37 - loss: 0.4782 - regression_loss: 0.4302 - classification_loss: 0.0481 200/500 [===========>..................] - ETA: 1:37 - loss: 0.4772 - regression_loss: 0.4293 - classification_loss: 0.0479 201/500 [===========>..................] - ETA: 1:37 - loss: 0.4771 - regression_loss: 0.4292 - classification_loss: 0.0479 202/500 [===========>..................] - ETA: 1:36 - loss: 0.4764 - regression_loss: 0.4286 - classification_loss: 0.0478 203/500 [===========>..................] - ETA: 1:36 - loss: 0.4755 - regression_loss: 0.4279 - classification_loss: 0.0476 204/500 [===========>..................] - ETA: 1:36 - loss: 0.4771 - regression_loss: 0.4292 - classification_loss: 0.0478 205/500 [===========>..................] - ETA: 1:35 - loss: 0.4764 - regression_loss: 0.4287 - classification_loss: 0.0478 206/500 [===========>..................] - ETA: 1:35 - loss: 0.4757 - regression_loss: 0.4281 - classification_loss: 0.0477 207/500 [===========>..................] - ETA: 1:35 - loss: 0.4759 - regression_loss: 0.4282 - classification_loss: 0.0477 208/500 [===========>..................] - ETA: 1:34 - loss: 0.4770 - regression_loss: 0.4294 - classification_loss: 0.0476 209/500 [===========>..................] - ETA: 1:34 - loss: 0.4766 - regression_loss: 0.4291 - classification_loss: 0.0476 210/500 [===========>..................] - ETA: 1:34 - loss: 0.4771 - regression_loss: 0.4295 - classification_loss: 0.0476 211/500 [===========>..................] - ETA: 1:33 - loss: 0.4771 - regression_loss: 0.4296 - classification_loss: 0.0476 212/500 [===========>..................] - ETA: 1:33 - loss: 0.4761 - regression_loss: 0.4286 - classification_loss: 0.0475 213/500 [===========>..................] - ETA: 1:33 - loss: 0.4752 - regression_loss: 0.4278 - classification_loss: 0.0474 214/500 [===========>..................] - ETA: 1:32 - loss: 0.4765 - regression_loss: 0.4290 - classification_loss: 0.0474 215/500 [===========>..................] - ETA: 1:32 - loss: 0.4779 - regression_loss: 0.4305 - classification_loss: 0.0474 216/500 [===========>..................] - ETA: 1:32 - loss: 0.4779 - regression_loss: 0.4305 - classification_loss: 0.0473 217/500 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[============================>.] - ETA: 3s - loss: 0.4737 - regression_loss: 0.4263 - classification_loss: 0.0474 490/500 [============================>.] - ETA: 3s - loss: 0.4745 - regression_loss: 0.4270 - classification_loss: 0.0475 491/500 [============================>.] - ETA: 2s - loss: 0.4738 - regression_loss: 0.4263 - classification_loss: 0.0474 492/500 [============================>.] - ETA: 2s - loss: 0.4742 - regression_loss: 0.4268 - classification_loss: 0.0474 493/500 [============================>.] - ETA: 2s - loss: 0.4740 - regression_loss: 0.4267 - classification_loss: 0.0473 494/500 [============================>.] - ETA: 1s - loss: 0.4738 - regression_loss: 0.4265 - classification_loss: 0.0473 495/500 [============================>.] - ETA: 1s - loss: 0.4744 - regression_loss: 0.4270 - classification_loss: 0.0474 496/500 [============================>.] - ETA: 1s - loss: 0.4745 - regression_loss: 0.4271 - classification_loss: 0.0474 497/500 [============================>.] - ETA: 0s - loss: 0.4740 - regression_loss: 0.4267 - classification_loss: 0.0473 498/500 [============================>.] - ETA: 0s - loss: 0.4740 - regression_loss: 0.4267 - classification_loss: 0.0473 499/500 [============================>.] - ETA: 0s - loss: 0.4743 - regression_loss: 0.4270 - classification_loss: 0.0472 500/500 [==============================] - 162s 325ms/step - loss: 0.4746 - regression_loss: 0.4273 - classification_loss: 0.0473 326 instances of class plum with average precision: 0.7687 mAP: 0.7687 Epoch 00044: saving model to ./training/snapshots/resnet101_pascal_44.h5 Epoch 45/150 1/500 [..............................] - ETA: 2:32 - loss: 0.3722 - regression_loss: 0.3420 - classification_loss: 0.0302 2/500 [..............................] - ETA: 2:41 - loss: 0.2992 - regression_loss: 0.2701 - classification_loss: 0.0291 3/500 [..............................] - ETA: 2:41 - loss: 0.2841 - regression_loss: 0.2579 - classification_loss: 0.0263 4/500 [..............................] - ETA: 2:39 - loss: 0.3637 - regression_loss: 0.3240 - classification_loss: 0.0397 5/500 [..............................] - ETA: 2:38 - loss: 0.3411 - regression_loss: 0.3061 - classification_loss: 0.0350 6/500 [..............................] - ETA: 2:39 - loss: 0.3439 - regression_loss: 0.3107 - classification_loss: 0.0332 7/500 [..............................] - ETA: 2:40 - loss: 0.3396 - regression_loss: 0.3084 - classification_loss: 0.0312 8/500 [..............................] - ETA: 2:39 - loss: 0.3522 - regression_loss: 0.3218 - classification_loss: 0.0304 9/500 [..............................] - ETA: 2:38 - loss: 0.3642 - regression_loss: 0.3335 - classification_loss: 0.0307 10/500 [..............................] - ETA: 2:38 - loss: 0.3687 - regression_loss: 0.3373 - classification_loss: 0.0314 11/500 [..............................] - ETA: 2:38 - loss: 0.3745 - regression_loss: 0.3445 - classification_loss: 0.0299 12/500 [..............................] - ETA: 2:38 - loss: 0.3979 - regression_loss: 0.3658 - classification_loss: 0.0321 13/500 [..............................] - ETA: 2:37 - loss: 0.3983 - regression_loss: 0.3661 - classification_loss: 0.0322 14/500 [..............................] - ETA: 2:37 - loss: 0.3970 - regression_loss: 0.3653 - classification_loss: 0.0317 15/500 [..............................] - ETA: 2:37 - loss: 0.4036 - regression_loss: 0.3714 - classification_loss: 0.0321 16/500 [..............................] - ETA: 2:36 - loss: 0.4001 - regression_loss: 0.3676 - classification_loss: 0.0325 17/500 [>.............................] - ETA: 2:35 - loss: 0.3949 - regression_loss: 0.3629 - classification_loss: 0.0320 18/500 [>.............................] - ETA: 2:35 - loss: 0.3825 - regression_loss: 0.3509 - classification_loss: 0.0316 19/500 [>.............................] - ETA: 2:34 - loss: 0.3738 - regression_loss: 0.3429 - classification_loss: 0.0310 20/500 [>.............................] - ETA: 2:33 - loss: 0.3588 - regression_loss: 0.3288 - classification_loss: 0.0300 21/500 [>.............................] - ETA: 2:33 - loss: 0.3639 - regression_loss: 0.3328 - classification_loss: 0.0312 22/500 [>.............................] - ETA: 2:33 - loss: 0.3640 - regression_loss: 0.3320 - classification_loss: 0.0321 23/500 [>.............................] - ETA: 2:32 - loss: 0.3667 - regression_loss: 0.3347 - classification_loss: 0.0320 24/500 [>.............................] - ETA: 2:32 - loss: 0.3683 - regression_loss: 0.3358 - classification_loss: 0.0325 25/500 [>.............................] - ETA: 2:32 - loss: 0.3683 - regression_loss: 0.3356 - classification_loss: 0.0327 26/500 [>.............................] - ETA: 2:31 - loss: 0.3838 - regression_loss: 0.3492 - classification_loss: 0.0345 27/500 [>.............................] - ETA: 2:31 - loss: 0.3789 - regression_loss: 0.3451 - classification_loss: 0.0338 28/500 [>.............................] - ETA: 2:31 - loss: 0.3787 - regression_loss: 0.3457 - classification_loss: 0.0330 29/500 [>.............................] - ETA: 2:31 - loss: 0.3777 - regression_loss: 0.3452 - classification_loss: 0.0324 30/500 [>.............................] - ETA: 2:31 - loss: 0.3849 - regression_loss: 0.3528 - classification_loss: 0.0321 31/500 [>.............................] - ETA: 2:31 - loss: 0.3823 - regression_loss: 0.3506 - classification_loss: 0.0317 32/500 [>.............................] - ETA: 2:30 - loss: 0.3812 - regression_loss: 0.3498 - classification_loss: 0.0314 33/500 [>.............................] - ETA: 2:30 - loss: 0.3783 - regression_loss: 0.3472 - classification_loss: 0.0311 34/500 [=>............................] - ETA: 2:30 - loss: 0.3794 - regression_loss: 0.3484 - classification_loss: 0.0310 35/500 [=>............................] - ETA: 2:29 - loss: 0.3758 - regression_loss: 0.3452 - classification_loss: 0.0306 36/500 [=>............................] - ETA: 2:29 - loss: 0.3788 - regression_loss: 0.3482 - classification_loss: 0.0306 37/500 [=>............................] - ETA: 2:28 - loss: 0.3882 - regression_loss: 0.3570 - classification_loss: 0.0312 38/500 [=>............................] - ETA: 2:28 - loss: 0.3956 - regression_loss: 0.3638 - classification_loss: 0.0318 39/500 [=>............................] - ETA: 2:27 - loss: 0.3925 - regression_loss: 0.3610 - classification_loss: 0.0315 40/500 [=>............................] - ETA: 2:27 - loss: 0.3985 - regression_loss: 0.3661 - classification_loss: 0.0324 41/500 [=>............................] - ETA: 2:27 - loss: 0.4019 - regression_loss: 0.3695 - classification_loss: 0.0324 42/500 [=>............................] - ETA: 2:27 - loss: 0.4022 - regression_loss: 0.3699 - classification_loss: 0.0323 43/500 [=>............................] - ETA: 2:27 - loss: 0.3966 - regression_loss: 0.3649 - classification_loss: 0.0318 44/500 [=>............................] - ETA: 2:27 - loss: 0.3939 - regression_loss: 0.3623 - classification_loss: 0.0316 45/500 [=>............................] - ETA: 2:27 - loss: 0.3925 - regression_loss: 0.3607 - classification_loss: 0.0317 46/500 [=>............................] - ETA: 2:26 - loss: 0.3874 - regression_loss: 0.3561 - classification_loss: 0.0313 47/500 [=>............................] - ETA: 2:26 - loss: 0.3975 - regression_loss: 0.3654 - classification_loss: 0.0321 48/500 [=>............................] - ETA: 2:25 - loss: 0.4037 - regression_loss: 0.3707 - classification_loss: 0.0330 49/500 [=>............................] - ETA: 2:25 - loss: 0.4044 - regression_loss: 0.3710 - classification_loss: 0.0334 50/500 [==>...........................] - ETA: 2:25 - loss: 0.4058 - regression_loss: 0.3724 - classification_loss: 0.0333 51/500 [==>...........................] - ETA: 2:24 - loss: 0.4032 - regression_loss: 0.3701 - classification_loss: 0.0332 52/500 [==>...........................] - ETA: 2:24 - loss: 0.4107 - regression_loss: 0.3762 - classification_loss: 0.0345 53/500 [==>...........................] - ETA: 2:24 - loss: 0.4068 - regression_loss: 0.3726 - classification_loss: 0.0342 54/500 [==>...........................] - ETA: 2:23 - loss: 0.4081 - regression_loss: 0.3740 - classification_loss: 0.0341 55/500 [==>...........................] - ETA: 2:23 - loss: 0.4139 - regression_loss: 0.3791 - classification_loss: 0.0349 56/500 [==>...........................] - ETA: 2:23 - loss: 0.4113 - regression_loss: 0.3768 - classification_loss: 0.0345 57/500 [==>...........................] - ETA: 2:22 - loss: 0.4109 - regression_loss: 0.3764 - classification_loss: 0.0344 58/500 [==>...........................] - ETA: 2:22 - loss: 0.4090 - regression_loss: 0.3748 - classification_loss: 0.0342 59/500 [==>...........................] - ETA: 2:22 - loss: 0.4067 - regression_loss: 0.3725 - classification_loss: 0.0342 60/500 [==>...........................] - ETA: 2:22 - loss: 0.4031 - regression_loss: 0.3693 - classification_loss: 0.0338 61/500 [==>...........................] - ETA: 2:21 - loss: 0.3996 - regression_loss: 0.3660 - classification_loss: 0.0335 62/500 [==>...........................] - ETA: 2:21 - loss: 0.3979 - regression_loss: 0.3645 - classification_loss: 0.0333 63/500 [==>...........................] - ETA: 2:21 - loss: 0.4021 - regression_loss: 0.3686 - classification_loss: 0.0335 64/500 [==>...........................] - ETA: 2:21 - loss: 0.3998 - regression_loss: 0.3663 - classification_loss: 0.0334 65/500 [==>...........................] - ETA: 2:21 - loss: 0.3986 - regression_loss: 0.3652 - classification_loss: 0.0334 66/500 [==>...........................] - ETA: 2:20 - loss: 0.3991 - regression_loss: 0.3658 - classification_loss: 0.0333 67/500 [===>..........................] - ETA: 2:20 - loss: 0.3969 - regression_loss: 0.3636 - classification_loss: 0.0333 68/500 [===>..........................] - ETA: 2:20 - loss: 0.3989 - regression_loss: 0.3657 - classification_loss: 0.0332 69/500 [===>..........................] - ETA: 2:19 - loss: 0.4041 - regression_loss: 0.3705 - classification_loss: 0.0335 70/500 [===>..........................] - ETA: 2:19 - loss: 0.4053 - regression_loss: 0.3718 - classification_loss: 0.0334 71/500 [===>..........................] - ETA: 2:19 - loss: 0.4072 - regression_loss: 0.3738 - classification_loss: 0.0334 72/500 [===>..........................] - ETA: 2:18 - loss: 0.4119 - regression_loss: 0.3783 - classification_loss: 0.0336 73/500 [===>..........................] - ETA: 2:18 - loss: 0.4197 - regression_loss: 0.3851 - classification_loss: 0.0346 74/500 [===>..........................] - ETA: 2:18 - loss: 0.4210 - regression_loss: 0.3864 - classification_loss: 0.0346 75/500 [===>..........................] - ETA: 2:17 - loss: 0.4280 - regression_loss: 0.3923 - classification_loss: 0.0357 76/500 [===>..........................] - ETA: 2:17 - loss: 0.4332 - regression_loss: 0.3950 - classification_loss: 0.0382 77/500 [===>..........................] - ETA: 2:17 - loss: 0.4313 - regression_loss: 0.3934 - classification_loss: 0.0379 78/500 [===>..........................] - ETA: 2:16 - loss: 0.4292 - regression_loss: 0.3916 - classification_loss: 0.0376 79/500 [===>..........................] - ETA: 2:16 - loss: 0.4323 - regression_loss: 0.3944 - classification_loss: 0.0379 80/500 [===>..........................] - ETA: 2:16 - loss: 0.4300 - regression_loss: 0.3922 - classification_loss: 0.0378 81/500 [===>..........................] - ETA: 2:15 - loss: 0.4313 - regression_loss: 0.3934 - classification_loss: 0.0379 82/500 [===>..........................] - ETA: 2:15 - loss: 0.4321 - regression_loss: 0.3941 - classification_loss: 0.0380 83/500 [===>..........................] - ETA: 2:15 - loss: 0.4318 - regression_loss: 0.3941 - classification_loss: 0.0377 84/500 [====>.........................] - ETA: 2:14 - loss: 0.4315 - regression_loss: 0.3938 - classification_loss: 0.0377 85/500 [====>.........................] - ETA: 2:14 - loss: 0.4354 - regression_loss: 0.3978 - classification_loss: 0.0375 86/500 [====>.........................] - ETA: 2:14 - loss: 0.4352 - regression_loss: 0.3978 - classification_loss: 0.0373 87/500 [====>.........................] - ETA: 2:13 - loss: 0.4364 - regression_loss: 0.3993 - classification_loss: 0.0370 88/500 [====>.........................] - ETA: 2:13 - loss: 0.4465 - regression_loss: 0.4069 - classification_loss: 0.0396 89/500 [====>.........................] - ETA: 2:13 - loss: 0.4427 - regression_loss: 0.4033 - classification_loss: 0.0394 90/500 [====>.........................] - ETA: 2:12 - loss: 0.4415 - regression_loss: 0.4018 - classification_loss: 0.0397 91/500 [====>.........................] - ETA: 2:12 - loss: 0.4426 - regression_loss: 0.4028 - classification_loss: 0.0398 92/500 [====>.........................] - ETA: 2:12 - loss: 0.4408 - regression_loss: 0.4011 - classification_loss: 0.0397 93/500 [====>.........................] - ETA: 2:12 - loss: 0.4397 - regression_loss: 0.3999 - classification_loss: 0.0398 94/500 [====>.........................] - ETA: 2:11 - loss: 0.4388 - regression_loss: 0.3991 - classification_loss: 0.0397 95/500 [====>.........................] - ETA: 2:11 - loss: 0.4384 - regression_loss: 0.3990 - classification_loss: 0.0394 96/500 [====>.........................] - ETA: 2:10 - loss: 0.4358 - regression_loss: 0.3966 - classification_loss: 0.0393 97/500 [====>.........................] - ETA: 2:10 - loss: 0.4357 - regression_loss: 0.3966 - classification_loss: 0.0391 98/500 [====>.........................] - ETA: 2:10 - loss: 0.4351 - regression_loss: 0.3962 - classification_loss: 0.0389 99/500 [====>.........................] - ETA: 2:10 - loss: 0.4333 - regression_loss: 0.3946 - classification_loss: 0.0387 100/500 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[===========================>..] - ETA: 10s - loss: 0.4559 - regression_loss: 0.4123 - classification_loss: 0.0436 469/500 [===========================>..] - ETA: 10s - loss: 0.4558 - regression_loss: 0.4123 - classification_loss: 0.0436 470/500 [===========================>..] - ETA: 9s - loss: 0.4556 - regression_loss: 0.4120 - classification_loss: 0.0436  471/500 [===========================>..] - ETA: 9s - loss: 0.4551 - regression_loss: 0.4116 - classification_loss: 0.0435 472/500 [===========================>..] - ETA: 9s - loss: 0.4567 - regression_loss: 0.4126 - classification_loss: 0.0441 473/500 [===========================>..] - ETA: 8s - loss: 0.4571 - regression_loss: 0.4129 - classification_loss: 0.0442 474/500 [===========================>..] - ETA: 8s - loss: 0.4572 - regression_loss: 0.4130 - classification_loss: 0.0442 475/500 [===========================>..] - ETA: 8s - loss: 0.4570 - regression_loss: 0.4128 - classification_loss: 0.0442 476/500 [===========================>..] - ETA: 7s - loss: 0.4569 - regression_loss: 0.4127 - classification_loss: 0.0442 477/500 [===========================>..] - ETA: 7s - loss: 0.4575 - regression_loss: 0.4132 - classification_loss: 0.0443 478/500 [===========================>..] - ETA: 7s - loss: 0.4577 - regression_loss: 0.4135 - classification_loss: 0.0443 479/500 [===========================>..] - ETA: 6s - loss: 0.4572 - regression_loss: 0.4130 - classification_loss: 0.0442 480/500 [===========================>..] - ETA: 6s - loss: 0.4569 - regression_loss: 0.4127 - classification_loss: 0.0442 481/500 [===========================>..] - ETA: 6s - loss: 0.4564 - regression_loss: 0.4122 - classification_loss: 0.0441 482/500 [===========================>..] - ETA: 5s - loss: 0.4564 - regression_loss: 0.4122 - classification_loss: 0.0442 483/500 [===========================>..] - ETA: 5s - loss: 0.4561 - regression_loss: 0.4120 - classification_loss: 0.0441 484/500 [============================>.] - ETA: 5s - loss: 0.4559 - regression_loss: 0.4119 - classification_loss: 0.0441 485/500 [============================>.] - ETA: 4s - loss: 0.4560 - regression_loss: 0.4119 - classification_loss: 0.0441 486/500 [============================>.] - ETA: 4s - loss: 0.4556 - regression_loss: 0.4115 - classification_loss: 0.0440 487/500 [============================>.] - ETA: 4s - loss: 0.4558 - regression_loss: 0.4117 - classification_loss: 0.0440 488/500 [============================>.] - ETA: 3s - loss: 0.4567 - regression_loss: 0.4124 - classification_loss: 0.0443 489/500 [============================>.] - ETA: 3s - loss: 0.4565 - regression_loss: 0.4122 - classification_loss: 0.0443 490/500 [============================>.] - ETA: 3s - loss: 0.4564 - regression_loss: 0.4121 - classification_loss: 0.0442 491/500 [============================>.] - ETA: 2s - loss: 0.4563 - regression_loss: 0.4121 - classification_loss: 0.0442 492/500 [============================>.] - ETA: 2s - loss: 0.4561 - regression_loss: 0.4119 - classification_loss: 0.0442 493/500 [============================>.] - ETA: 2s - loss: 0.4558 - regression_loss: 0.4116 - classification_loss: 0.0442 494/500 [============================>.] - ETA: 1s - loss: 0.4553 - regression_loss: 0.4111 - classification_loss: 0.0441 495/500 [============================>.] - ETA: 1s - loss: 0.4552 - regression_loss: 0.4111 - classification_loss: 0.0441 496/500 [============================>.] - ETA: 1s - loss: 0.4565 - regression_loss: 0.4120 - classification_loss: 0.0444 497/500 [============================>.] - ETA: 0s - loss: 0.4568 - regression_loss: 0.4123 - classification_loss: 0.0445 498/500 [============================>.] - ETA: 0s - loss: 0.4576 - regression_loss: 0.4131 - classification_loss: 0.0445 499/500 [============================>.] - ETA: 0s - loss: 0.4572 - regression_loss: 0.4128 - classification_loss: 0.0445 500/500 [==============================] - 162s 324ms/step - loss: 0.4569 - regression_loss: 0.4125 - classification_loss: 0.0444 326 instances of class plum with average precision: 0.7804 mAP: 0.7804 Epoch 00045: saving model to ./training/snapshots/resnet101_pascal_45.h5