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[0] setting up environment
CommandNotFoundError: Your shell has not been properly configured to use 'conda activate'.
To initialize your shell, run
$ conda init <SHELL_NAME>
Currently supported shells are:
- bash
- fish
- tcsh
- xonsh
- zsh
- powershell
See 'conda init --help' for more information and options.
IMPORTANT: You may need to close and restart your shell after running 'conda init'.
2020-03-10 21:57:07.746187: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcuda.so.1
2020-03-10 21:57:08.256820: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties:
name: Tesla P100-PCIE-16GB major: 6 minor: 0 memoryClockRate(GHz): 1.3285
pciBusID: 0000:83:00.0
2020-03-10 21:57:08.311255: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
2020-03-10 21:57:08.326594: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
2020-03-10 21:57:08.347508: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10.0
2020-03-10 21:57:08.391359: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10.0
2020-03-10 21:57:08.433444: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10.0
2020-03-10 21:57:08.461738: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10.0
2020-03-10 21:57:08.488036: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2020-03-10 21:57:08.492243: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2020-03-10 21:57:08.493208: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2020-03-10 21:57:08.510015: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2099815000 Hz
2020-03-10 21:57:08.514796: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fdabf8c8790 executing computations on platform Host. Devices:
2020-03-10 21:57:08.514835: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): <undefined>, <undefined>
2020-03-10 21:57:08.669601: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fdabf927230 executing computations on platform CUDA. Devices:
2020-03-10 21:57:08.669643: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): Tesla P100-PCIE-16GB, Compute Capability 6.0
2020-03-10 21:57:08.671840: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties:
name: Tesla P100-PCIE-16GB major: 6 minor: 0 memoryClockRate(GHz): 1.3285
pciBusID: 0000:83:00.0
2020-03-10 21:57:08.671909: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
2020-03-10 21:57:08.671935: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
2020-03-10 21:57:08.671955: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10.0
2020-03-10 21:57:08.671975: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10.0
2020-03-10 21:57:08.671995: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10.0
2020-03-10 21:57:08.672015: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10.0
2020-03-10 21:57:08.672035: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2020-03-10 21:57:08.677401: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2020-03-10 21:57:08.677462: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
2020-03-10 21:57:08.680399: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-03-10 21:57:08.680422: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187] 0
2020-03-10 21:57:08.680435: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0: N
2020-03-10 21:57:08.684132: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 15216 MB memory) -> physical GPU (device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:83:00.0, compute capability: 6.0)
/homes/nramachandra/anaconda3/envs/tf_gpu_14/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6521: MatplotlibDeprecationWarning:
The 'normed' kwarg was deprecated in Matplotlib 2.1 and will be removed in 3.1. Use 'density' instead.
alternative="'density'", removal="3.1")
WARNING: Logging before flag parsing goes to stderr.
W0310 21:57:09.941807 140577392871232 deprecation.py:323] From /homes/nramachandra/anaconda3/envs/tf_gpu_14/lib/python3.6/site-packages/tensorflow_probability/python/internal/distribution_util.py:493: add_dispatch_support.<locals>.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
2020-03-10 21:57:11.197222: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
(6304534, 6)
(7237871, 6)
(456685, 5)
(423353, 5)
Size of features in training data: (12000000, 5)
Size of output in training data: (12000000,)
Size of features in test data: (10000, 5)
Size of output in test data: (10000,)
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense (Dense) (None, 128) 768
_________________________________________________________________
dense_1 (Dense) (None, 128) 16512
_________________________________________________________________
dense_2 (Dense) (None, 64) 8256
_________________________________________________________________
dense_3 (Dense) (None, 32) 2080
_________________________________________________________________
dense_4 (Dense) (None, 48) 1584
_________________________________________________________________
mixture_normal (MixtureNorma ((None, 1), (None, 1)) 0
=================================================================
Total params: 29,200
Trainable params: 29,200
Non-trainable params: 0
_________________________________________________________________
Train on 12000000 samples, validate on 10000 samples
Epoch 1/1000
12000000/12000000 - 38s - loss: -1.8839e+00 - val_loss: -1.5408e+00
Epoch 2/1000
12000000/12000000 - 37s - loss: -2.1841e+00 - val_loss: -1.0586e+00
Epoch 3/1000
12000000/12000000 - 38s - loss: -2.2986e+00 - val_loss: -1.3132e+00
Epoch 4/1000
12000000/12000000 - 38s - loss: -2.3774e+00 - val_loss: -7.8339e-01
Epoch 5/1000
12000000/12000000 - 38s - loss: -2.4407e+00 - val_loss: -5.8823e-01
Epoch 6/1000
12000000/12000000 - 36s - loss: -2.7428e+00 - val_loss: 0.0338
Epoch 7/1000
12000000/12000000 - 34s - loss: -2.7904e+00 - val_loss: 0.0953
Epoch 8/1000
12000000/12000000 - 38s - loss: -2.8312e+00 - val_loss: -2.6063e-02
Epoch 9/1000
12000000/12000000 - 39s - loss: -2.8719e+00 - val_loss: 0.0804
Epoch 10/1000
12000000/12000000 - 38s - loss: -2.9082e+00 - val_loss: 0.0999
Epoch 11/1000
12000000/12000000 - 39s - loss: -2.9372e+00 - val_loss: 0.1107
Epoch 12/1000
12000000/12000000 - 33s - loss: -2.9613e+00 - val_loss: 0.1534
Epoch 13/1000
12000000/12000000 - 33s - loss: -2.9818e+00 - val_loss: 0.2037
Epoch 14/1000
12000000/12000000 - 33s - loss: -2.9998e+00 - val_loss: 0.1784
Epoch 15/1000
12000000/12000000 - 35s - loss: -3.0159e+00 - val_loss: 0.2490
Epoch 16/1000
12000000/12000000 - 38s - loss: -3.0306e+00 - val_loss: 0.2359
Epoch 17/1000
12000000/12000000 - 40s - loss: -3.0437e+00 - val_loss: 0.2998
Epoch 18/1000
12000000/12000000 - 37s - loss: -3.0561e+00 - val_loss: 0.3364
Epoch 19/1000
12000000/12000000 - 36s - loss: -3.0675e+00 - val_loss: 0.2569
Epoch 20/1000
12000000/12000000 - 37s - loss: -3.0783e+00 - val_loss: 0.3214
Epoch 21/1000
12000000/12000000 - 39s - loss: -3.0888e+00 - val_loss: 0.3745
Epoch 22/1000
12000000/12000000 - 38s - loss: -3.0977e+00 - val_loss: 0.2758
Epoch 23/1000
12000000/12000000 - 37s - loss: -3.1070e+00 - val_loss: 0.4127
Epoch 24/1000
12000000/12000000 - 38s - loss: -3.1154e+00 - val_loss: 0.3986
Epoch 25/1000
12000000/12000000 - 38s - loss: -3.1229e+00 - val_loss: 0.3315
Epoch 26/1000
12000000/12000000 - 37s - loss: -3.1301e+00 - val_loss: 0.3750
Epoch 27/1000
12000000/12000000 - 39s - loss: -3.1378e+00 - val_loss: 0.3342
Epoch 28/1000
12000000/12000000 - 36s - loss: -3.1448e+00 - val_loss: 0.4317
Epoch 29/1000
12000000/12000000 - 35s - loss: -3.1514e+00 - val_loss: 0.3710
Epoch 30/1000
12000000/12000000 - 33s - loss: -3.1573e+00 - val_loss: 0.4444
Epoch 31/1000
12000000/12000000 - 33s - loss: -3.1636e+00 - val_loss: 0.4807
Epoch 32/1000
12000000/12000000 - 38s - loss: -3.1700e+00 - val_loss: 0.4513
Epoch 33/1000
12000000/12000000 - 34s - loss: -3.1751e+00 - val_loss: 0.4639
Epoch 34/1000
12000000/12000000 - 37s - loss: -3.1810e+00 - val_loss: 0.5560
Epoch 35/1000
12000000/12000000 - 36s - loss: -3.1857e+00 - val_loss: 0.5704
Epoch 36/1000
12000000/12000000 - 38s - loss: -3.1910e+00 - val_loss: 0.5006
Epoch 37/1000
12000000/12000000 - 36s - loss: -3.1958e+00 - val_loss: 0.5139
Epoch 38/1000
12000000/12000000 - 35s - loss: -3.2017e+00 - val_loss: 0.5723
Epoch 39/1000
12000000/12000000 - 31s - loss: -3.2064e+00 - val_loss: 0.5430
Epoch 40/1000
12000000/12000000 - 35s - loss: -3.2108e+00 - val_loss: 0.6033
Epoch 41/1000
12000000/12000000 - 38s - loss: -3.2157e+00 - val_loss: 0.5921
Epoch 42/1000
12000000/12000000 - 35s - loss: -3.2199e+00 - val_loss: 0.5785
Epoch 43/1000
12000000/12000000 - 37s - loss: -3.2252e+00 - val_loss: 0.4774
Epoch 44/1000
12000000/12000000 - 38s - loss: -3.2294e+00 - val_loss: 0.5346
Epoch 45/1000
12000000/12000000 - 37s - loss: -3.2340e+00 - val_loss: 0.6355
Epoch 46/1000
12000000/12000000 - 35s - loss: -3.2384e+00 - val_loss: 0.6511
Epoch 47/1000
12000000/12000000 - 37s - loss: -3.2428e+00 - val_loss: 0.5386
Epoch 48/1000
12000000/12000000 - 35s - loss: -3.2475e+00 - val_loss: 0.5273
Epoch 49/1000
12000000/12000000 - 38s - loss: -3.2510e+00 - val_loss: 0.5902
Epoch 50/1000
12000000/12000000 - 37s - loss: -3.2552e+00 - val_loss: 0.5546
Epoch 51/1000
12000000/12000000 - 35s - loss: -3.2597e+00 - val_loss: 0.4083
Epoch 52/1000
12000000/12000000 - 37s - loss: -3.2635e+00 - val_loss: 0.5511
Epoch 53/1000
12000000/12000000 - 38s - loss: -3.2675e+00 - val_loss: 0.5811
Epoch 54/1000
12000000/12000000 - 37s - loss: -3.2713e+00 - val_loss: 0.5614
Epoch 55/1000
12000000/12000000 - 34s - loss: -3.2753e+00 - val_loss: 0.5733
Epoch 56/1000
12000000/12000000 - 36s - loss: -3.2791e+00 - val_loss: 0.5377
Epoch 57/1000
12000000/12000000 - 37s - loss: -3.2825e+00 - val_loss: 0.5464
Epoch 58/1000
12000000/12000000 - 35s - loss: -3.2861e+00 - val_loss: 0.5350
Epoch 59/1000
12000000/12000000 - 38s - loss: -3.2896e+00 - val_loss: 0.5890
Epoch 60/1000
12000000/12000000 - 35s - loss: -3.2934e+00 - val_loss: 0.6045
Epoch 61/1000
12000000/12000000 - 36s - loss: -3.2972e+00 - val_loss: 0.4995
Epoch 62/1000
12000000/12000000 - 38s - loss: -3.3006e+00 - val_loss: 0.5113
Epoch 63/1000
12000000/12000000 - 35s - loss: -3.3035e+00 - val_loss: 0.6070
Epoch 64/1000
12000000/12000000 - 38s - loss: -3.3069e+00 - val_loss: 0.5034
Epoch 65/1000
12000000/12000000 - 35s - loss: -3.3101e+00 - val_loss: 0.5454
Epoch 66/1000
12000000/12000000 - 36s - loss: -3.3131e+00 - val_loss: 0.5266
Epoch 67/1000
12000000/12000000 - 33s - loss: -3.3160e+00 - val_loss: 0.5910
Epoch 68/1000
12000000/12000000 - 32s - loss: -3.3194e+00 - val_loss: 0.5623
Epoch 69/1000
12000000/12000000 - 35s - loss: -3.3227e+00 - val_loss: 0.6332
Epoch 70/1000
12000000/12000000 - 36s - loss: -3.3258e+00 - val_loss: 0.5650
Epoch 71/1000
12000000/12000000 - 36s - loss: -3.3288e+00 - val_loss: 0.6276
Epoch 72/1000
12000000/12000000 - 36s - loss: -3.3321e+00 - val_loss: 0.6140
Epoch 73/1000
12000000/12000000 - 38s - loss: -3.3349e+00 - val_loss: 0.7124
Epoch 74/1000
12000000/12000000 - 38s - loss: -3.3385e+00 - val_loss: 0.6847
Epoch 75/1000
12000000/12000000 - 37s - loss: -3.3415e+00 - val_loss: 0.6306
Epoch 76/1000
12000000/12000000 - 33s - loss: -3.3443e+00 - val_loss: 0.7111
Epoch 77/1000
12000000/12000000 - 38s - loss: -3.3472e+00 - val_loss: 0.6815
Epoch 78/1000
12000000/12000000 - 38s - loss: -3.3499e+00 - val_loss: 0.5799
Epoch 79/1000
12000000/12000000 - 34s - loss: -3.3531e+00 - val_loss: 0.7001
Epoch 80/1000
12000000/12000000 - 37s - loss: -3.3559e+00 - val_loss: 0.7826
Epoch 81/1000
12000000/12000000 - 32s - loss: -3.3588e+00 - val_loss: 0.8034
Epoch 82/1000
12000000/12000000 - 37s - loss: -3.3619e+00 - val_loss: 0.6955
Epoch 83/1000
12000000/12000000 - 36s - loss: -3.3645e+00 - val_loss: 0.7682
Epoch 84/1000
12000000/12000000 - 37s - loss: -3.3676e+00 - val_loss: 0.7267
Epoch 85/1000
12000000/12000000 - 37s - loss: -3.3713e+00 - val_loss: 0.8001
Epoch 86/1000
12000000/12000000 - 36s - loss: -3.3745e+00 - val_loss: 0.8258
Epoch 87/1000
12000000/12000000 - 39s - loss: -3.3766e+00 - val_loss: 0.7641
Epoch 88/1000
12000000/12000000 - 37s - loss: -3.3797e+00 - val_loss: 0.8631
Epoch 89/1000
12000000/12000000 - 36s - loss: -3.3819e+00 - val_loss: 0.8133
Epoch 90/1000
12000000/12000000 - 37s - loss: -3.3852e+00 - val_loss: 0.7914
Epoch 91/1000
12000000/12000000 - 36s - loss: -3.3878e+00 - val_loss: 0.8363
Epoch 92/1000
12000000/12000000 - 36s - loss: -3.3907e+00 - val_loss: 0.8561
Epoch 93/1000
12000000/12000000 - 37s - loss: -3.3929e+00 - val_loss: 0.8329
Epoch 94/1000
12000000/12000000 - 36s - loss: -3.3952e+00 - val_loss: 0.8066
Epoch 95/1000
12000000/12000000 - 36s - loss: -3.3972e+00 - val_loss: 0.8606
Epoch 96/1000
12000000/12000000 - 38s - loss: -3.3995e+00 - val_loss: 0.8713
Epoch 97/1000
12000000/12000000 - 37s - loss: -3.4020e+00 - val_loss: 0.9223
Epoch 98/1000
12000000/12000000 - 36s - loss: -3.4045e+00 - val_loss: 0.9473
Epoch 99/1000
12000000/12000000 - 37s - loss: -3.4065e+00 - val_loss: 0.7327
Epoch 100/1000
12000000/12000000 - 35s - loss: -3.4088e+00 - val_loss: 0.8380
Epoch 101/1000
12000000/12000000 - 37s - loss: -3.4108e+00 - val_loss: 0.8974
Epoch 102/1000
12000000/12000000 - 35s - loss: -3.4127e+00 - val_loss: 0.9650
Epoch 103/1000
12000000/12000000 - 32s - loss: -3.4148e+00 - val_loss: 0.7733
Epoch 104/1000
12000000/12000000 - 38s - loss: -3.4166e+00 - val_loss: 0.9209
Epoch 105/1000
12000000/12000000 - 38s - loss: -3.4188e+00 - val_loss: 0.9306
Epoch 106/1000
12000000/12000000 - 37s - loss: -3.4205e+00 - val_loss: 0.9560
Epoch 107/1000
12000000/12000000 - 36s - loss: -3.4225e+00 - val_loss: 0.9819
Epoch 108/1000
12000000/12000000 - 35s - loss: -3.4244e+00 - val_loss: 0.9548
Epoch 109/1000
12000000/12000000 - 36s - loss: -3.4265e+00 - val_loss: 0.9530
Epoch 110/1000
12000000/12000000 - 38s - loss: -3.4280e+00 - val_loss: 0.9356
Epoch 111/1000
12000000/12000000 - 37s - loss: -3.4298e+00 - val_loss: 0.9626
Epoch 112/1000
12000000/12000000 - 38s - loss: -3.4316e+00 - val_loss: 0.9177
Epoch 113/1000
12000000/12000000 - 36s - loss: -3.4334e+00 - val_loss: 1.0103
Epoch 114/1000
12000000/12000000 - 38s - loss: -3.4355e+00 - val_loss: 1.0031
Epoch 115/1000
12000000/12000000 - 39s - loss: -3.4375e+00 - val_loss: 0.9800
Epoch 116/1000
12000000/12000000 - 37s - loss: -3.4387e+00 - val_loss: 0.9342
Epoch 117/1000
12000000/12000000 - 35s - loss: -3.4404e+00 - val_loss: 0.9569
Epoch 118/1000
12000000/12000000 - 38s - loss: -3.4421e+00 - val_loss: 0.9149
Epoch 119/1000
12000000/12000000 - 34s - loss: -3.4439e+00 - val_loss: 0.9828
Epoch 120/1000
12000000/12000000 - 36s - loss: -3.4457e+00 - val_loss: 0.9397
Epoch 121/1000
12000000/12000000 - 38s - loss: -3.4471e+00 - val_loss: 0.9903
Epoch 122/1000
12000000/12000000 - 34s - loss: -3.4491e+00 - val_loss: 0.8836
Epoch 123/1000
12000000/12000000 - 37s - loss: -3.4513e+00 - val_loss: 1.0554
Epoch 124/1000
12000000/12000000 - 36s - loss: -3.4530e+00 - val_loss: 0.8595
Epoch 125/1000
12000000/12000000 - 35s - loss: -3.4541e+00 - val_loss: 0.8485
Epoch 126/1000
12000000/12000000 - 36s - loss: -3.4556e+00 - val_loss: 0.9254
Epoch 127/1000
12000000/12000000 - 33s - loss: -3.4572e+00 - val_loss: 0.9931
Epoch 128/1000
12000000/12000000 - 33s - loss: -3.4587e+00 - val_loss: 1.0430
Epoch 129/1000
12000000/12000000 - 37s - loss: -3.4603e+00 - val_loss: 0.9453
Epoch 130/1000
12000000/12000000 - 37s - loss: -3.4617e+00 - val_loss: 0.9312
Epoch 131/1000
12000000/12000000 - 36s - loss: -3.4632e+00 - val_loss: 0.9473
Epoch 132/1000
12000000/12000000 - 39s - loss: -3.4645e+00 - val_loss: 0.9265
Epoch 133/1000
12000000/12000000 - 35s - loss: -3.4663e+00 - val_loss: 0.9405
Epoch 134/1000
12000000/12000000 - 38s - loss: -3.4676e+00 - val_loss: 0.9870
Epoch 135/1000
12000000/12000000 - 33s - loss: -3.4688e+00 - val_loss: 0.9734
Epoch 136/1000
12000000/12000000 - 34s - loss: -3.4700e+00 - val_loss: 0.8713
Epoch 137/1000
12000000/12000000 - 35s - loss: -3.4717e+00 - val_loss: 0.8468
Epoch 138/1000
12000000/12000000 - 34s - loss: -3.4730e+00 - val_loss: 0.9372
Epoch 139/1000
12000000/12000000 - 36s - loss: -3.4745e+00 - val_loss: 0.9510
Epoch 140/1000
12000000/12000000 - 37s - loss: -3.4755e+00 - val_loss: 0.8884
Epoch 141/1000
12000000/12000000 - 38s - loss: -3.4772e+00 - val_loss: 0.9467
Epoch 142/1000
12000000/12000000 - 39s - loss: -3.4784e+00 - val_loss: 0.9040
Epoch 143/1000
12000000/12000000 - 34s - loss: -3.4799e+00 - val_loss: 0.8316
Epoch 144/1000
12000000/12000000 - 37s - loss: -3.4816e+00 - val_loss: 0.9197
Epoch 145/1000
12000000/12000000 - 38s - loss: -3.4825e+00 - val_loss: 0.9025
Epoch 146/1000
12000000/12000000 - 36s - loss: -3.4840e+00 - val_loss: 0.9514
Epoch 147/1000
12000000/12000000 - 32s - loss: -3.4852e+00 - val_loss: 0.9181
Epoch 148/1000
12000000/12000000 - 36s - loss: -3.4867e+00 - val_loss: 0.8441
Epoch 149/1000
12000000/12000000 - 39s - loss: -3.4879e+00 - val_loss: 0.9020
Epoch 150/1000
12000000/12000000 - 38s - loss: -3.4896e+00 - val_loss: 0.9540
Epoch 151/1000
12000000/12000000 - 37s - loss: -3.4904e+00 - val_loss: 0.8896
Epoch 152/1000
12000000/12000000 - 36s - loss: -3.4921e+00 - val_loss: 0.9884
Epoch 153/1000
12000000/12000000 - 37s - loss: -3.4930e+00 - val_loss: 0.8845
Epoch 154/1000
12000000/12000000 - 36s - loss: -3.4943e+00 - val_loss: 0.8932
Epoch 155/1000
12000000/12000000 - 38s - loss: -3.4955e+00 - val_loss: 0.8467
Epoch 156/1000
12000000/12000000 - 35s - loss: -3.4968e+00 - val_loss: 0.8923
Epoch 157/1000
12000000/12000000 - 35s - loss: -3.4981e+00 - val_loss: 0.8506
Epoch 158/1000
12000000/12000000 - 34s - loss: -3.4994e+00 - val_loss: 0.9005
Epoch 159/1000
12000000/12000000 - 35s - loss: -3.5004e+00 - val_loss: 0.9561
Epoch 160/1000
12000000/12000000 - 37s - loss: -3.5016e+00 - val_loss: 0.8882
Epoch 161/1000
12000000/12000000 - 36s - loss: -3.5029e+00 - val_loss: 0.8681
Epoch 162/1000
12000000/12000000 - 36s - loss: -3.5042e+00 - val_loss: 0.8925
Epoch 163/1000
12000000/12000000 - 38s - loss: -3.5056e+00 - val_loss: 0.9168
Epoch 164/1000
12000000/12000000 - 35s - loss: -3.5065e+00 - val_loss: 0.9013
Epoch 165/1000
12000000/12000000 - 38s - loss: -3.5078e+00 - val_loss: 0.9051
Epoch 166/1000
12000000/12000000 - 36s - loss: -3.5091e+00 - val_loss: 0.9463
Epoch 167/1000
12000000/12000000 - 35s - loss: -3.5098e+00 - val_loss: 0.8666
Epoch 168/1000
12000000/12000000 - 33s - loss: -3.5110e+00 - val_loss: 0.9716
Epoch 169/1000
12000000/12000000 - 36s - loss: -3.5125e+00 - val_loss: 0.8680
Epoch 170/1000
12000000/12000000 - 35s - loss: -3.5135e+00 - val_loss: 0.8973
Epoch 171/1000
12000000/12000000 - 34s - loss: -3.5150e+00 - val_loss: 0.9348
Epoch 172/1000
12000000/12000000 - 38s - loss: -3.5156e+00 - val_loss: 0.9146
Epoch 173/1000
12000000/12000000 - 38s - loss: -3.5172e+00 - val_loss: 0.9763
Epoch 174/1000
12000000/12000000 - 38s - loss: -3.5181e+00 - val_loss: 0.9330
Epoch 175/1000
12000000/12000000 - 37s - loss: -3.5197e+00 - val_loss: 1.0206
Epoch 176/1000
12000000/12000000 - 38s - loss: -3.5208e+00 - val_loss: 0.9777
Epoch 177/1000
12000000/12000000 - 37s - loss: -3.5223e+00 - val_loss: 0.9464
Epoch 178/1000
12000000/12000000 - 36s - loss: -3.5230e+00 - val_loss: 0.8805
Epoch 179/1000
12000000/12000000 - 34s - loss: -3.5240e+00 - val_loss: 0.8710
Epoch 180/1000
12000000/12000000 - 38s - loss: -3.5254e+00 - val_loss: 0.9720
Epoch 181/1000
12000000/12000000 - 38s - loss: -3.5264e+00 - val_loss: 0.8075
Epoch 182/1000
12000000/12000000 - 38s - loss: -3.5276e+00 - val_loss: 0.9456
Epoch 183/1000
12000000/12000000 - 37s - loss: -3.5289e+00 - val_loss: 0.9427
Epoch 184/1000
12000000/12000000 - 36s - loss: -3.5299e+00 - val_loss: 0.8771
Epoch 185/1000
12000000/12000000 - 35s - loss: -3.5309e+00 - val_loss: 0.9000
Epoch 186/1000
12000000/12000000 - 32s - loss: -3.5318e+00 - val_loss: 0.7415
Epoch 187/1000
12000000/12000000 - 32s - loss: -3.5329e+00 - val_loss: 0.8764
Epoch 188/1000
12000000/12000000 - 35s - loss: -3.5339e+00 - val_loss: 0.9038
Epoch 189/1000
12000000/12000000 - 36s - loss: -3.5350e+00 - val_loss: 0.9077
Epoch 190/1000
12000000/12000000 - 38s - loss: -3.5365e+00 - val_loss: 0.8132
Epoch 191/1000
12000000/12000000 - 38s - loss: -3.5378e+00 - val_loss: 0.9697
Epoch 192/1000
12000000/12000000 - 38s - loss: -3.5385e+00 - val_loss: 0.8972
Epoch 193/1000
12000000/12000000 - 37s - loss: -3.5394e+00 - val_loss: 0.9688
Epoch 194/1000
12000000/12000000 - 36s - loss: -3.5406e+00 - val_loss: 0.9223
Epoch 195/1000
12000000/12000000 - 34s - loss: -3.5418e+00 - val_loss: 1.0840
Epoch 196/1000
12000000/12000000 - 35s - loss: -3.5425e+00 - val_loss: 0.9249
Epoch 197/1000
12000000/12000000 - 35s - loss: -3.5440e+00 - val_loss: 0.9167
Epoch 198/1000
12000000/12000000 - 37s - loss: -3.5449e+00 - val_loss: 0.8851
Epoch 199/1000
12000000/12000000 - 37s - loss: -3.5458e+00 - val_loss: 0.9590
Epoch 200/1000
12000000/12000000 - 36s - loss: -3.5474e+00 - val_loss: 0.9878
Epoch 201/1000
12000000/12000000 - 36s - loss: -3.5485e+00 - val_loss: 0.8093
Epoch 202/1000
12000000/12000000 - 34s - loss: -3.5493e+00 - val_loss: 0.9089
Epoch 203/1000
12000000/12000000 - 37s - loss: -3.5510e+00 - val_loss: 0.9910
Epoch 204/1000
12000000/12000000 - 34s - loss: -3.5525e+00 - val_loss: 0.9632
Epoch 205/1000
12000000/12000000 - 36s - loss: -3.5536e+00 - val_loss: 0.9100
Epoch 206/1000
12000000/12000000 - 36s - loss: -3.5541e+00 - val_loss: 0.9423
Epoch 207/1000
12000000/12000000 - 38s - loss: -3.5552e+00 - val_loss: 1.0137
Epoch 208/1000
12000000/12000000 - 36s - loss: -3.5562e+00 - val_loss: 0.9648
Epoch 209/1000
12000000/12000000 - 36s - loss: -3.5572e+00 - val_loss: 0.9796
Epoch 210/1000
12000000/12000000 - 36s - loss: -3.5580e+00 - val_loss: 1.1176
Epoch 211/1000
12000000/12000000 - 35s - loss: -3.5591e+00 - val_loss: 0.9845
Epoch 212/1000
12000000/12000000 - 32s - loss: -3.5600e+00 - val_loss: 0.9457
Epoch 213/1000
12000000/12000000 - 35s - loss: -3.5608e+00 - val_loss: 1.0181
Epoch 214/1000
12000000/12000000 - 33s - loss: -3.5620e+00 - val_loss: 0.9462
Epoch 215/1000
12000000/12000000 - 37s - loss: -3.5631e+00 - val_loss: 0.9767
Epoch 216/1000
12000000/12000000 - 37s - loss: -3.5641e+00 - val_loss: 0.9567
Epoch 217/1000
12000000/12000000 - 38s - loss: -3.5652e+00 - val_loss: 0.9294
Epoch 218/1000
12000000/12000000 - 38s - loss: -3.5661e+00 - val_loss: 0.8041
Epoch 219/1000
12000000/12000000 - 36s - loss: -3.5672e+00 - val_loss: 1.0922
Epoch 220/1000
12000000/12000000 - 37s - loss: -3.5683e+00 - val_loss: 1.0185
Epoch 221/1000
12000000/12000000 - 37s - loss: -3.5691e+00 - val_loss: 0.8743
Epoch 222/1000
12000000/12000000 - 38s - loss: -3.5700e+00 - val_loss: 0.9558
Epoch 223/1000
12000000/12000000 - 38s - loss: -3.5708e+00 - val_loss: 1.0025
Epoch 224/1000
12000000/12000000 - 38s - loss: -3.5717e+00 - val_loss: 0.9662
Epoch 225/1000
12000000/12000000 - 37s - loss: -3.5730e+00 - val_loss: 0.9543
Epoch 226/1000
12000000/12000000 - 38s - loss: -3.5737e+00 - val_loss: 1.0267
Epoch 227/1000
12000000/12000000 - 33s - loss: -3.5748e+00 - val_loss: 0.9579
Epoch 228/1000
12000000/12000000 - 38s - loss: -3.5756e+00 - val_loss: 0.9338
Epoch 229/1000
12000000/12000000 - 38s - loss: -3.5765e+00 - val_loss: 0.9523
Epoch 230/1000
12000000/12000000 - 35s - loss: -3.5778e+00 - val_loss: 0.8870
Epoch 231/1000
12000000/12000000 - 38s - loss: -3.5789e+00 - val_loss: 0.9496
Epoch 232/1000
12000000/12000000 - 36s - loss: -3.5800e+00 - val_loss: 1.0041
Epoch 233/1000
12000000/12000000 - 35s - loss: -3.5806e+00 - val_loss: 1.0692
Epoch 234/1000
12000000/12000000 - 37s - loss: -3.5818e+00 - val_loss: 1.0410
Epoch 235/1000
12000000/12000000 - 36s - loss: -3.5828e+00 - val_loss: 1.0477
Epoch 236/1000
12000000/12000000 - 35s - loss: -3.5840e+00 - val_loss: 1.0401
Epoch 237/1000
12000000/12000000 - 39s - loss: -3.5849e+00 - val_loss: 1.0851
Epoch 238/1000
12000000/12000000 - 34s - loss: -3.5858e+00 - val_loss: 0.9783
Epoch 239/1000
12000000/12000000 - 36s - loss: -3.5864e+00 - val_loss: 1.0778
Epoch 240/1000
12000000/12000000 - 38s - loss: -3.5877e+00 - val_loss: 1.0642
Epoch 241/1000
12000000/12000000 - 38s - loss: -3.5885e+00 - val_loss: 1.0077
Epoch 242/1000
12000000/12000000 - 37s - loss: -3.5897e+00 - val_loss: 1.0379
Epoch 243/1000
12000000/12000000 - 35s - loss: -3.5904e+00 - val_loss: 0.9808
Epoch 244/1000
12000000/12000000 - 37s - loss: -3.5913e+00 - val_loss: 0.8931
Epoch 245/1000
12000000/12000000 - 33s - loss: -3.5922e+00 - val_loss: 0.9230
Epoch 246/1000
12000000/12000000 - 37s - loss: -3.5931e+00 - val_loss: 1.0794
Epoch 247/1000
12000000/12000000 - 37s - loss: -3.5940e+00 - val_loss: 0.9108
Epoch 248/1000
12000000/12000000 - 36s - loss: -3.5946e+00 - val_loss: 0.9615
Epoch 249/1000
12000000/12000000 - 37s - loss: -3.5958e+00 - val_loss: 0.9740
Epoch 250/1000
12000000/12000000 - 37s - loss: -3.5968e+00 - val_loss: 0.9622
Epoch 251/1000
12000000/12000000 - 37s - loss: -3.5973e+00 - val_loss: 1.0066
Epoch 252/1000
12000000/12000000 - 34s - loss: -3.5982e+00 - val_loss: 0.9561
Epoch 253/1000
12000000/12000000 - 36s - loss: -3.5993e+00 - val_loss: 0.9248
Epoch 254/1000
12000000/12000000 - 34s - loss: -3.6002e+00 - val_loss: 0.9990
Epoch 255/1000
12000000/12000000 - 35s - loss: -3.6006e+00 - val_loss: 1.0669
Epoch 256/1000
12000000/12000000 - 37s - loss: -3.6017e+00 - val_loss: 1.1027
Epoch 257/1000
12000000/12000000 - 33s - loss: -3.6026e+00 - val_loss: 0.9998
Epoch 258/1000
12000000/12000000 - 31s - loss: -3.6035e+00 - val_loss: 1.0118
Epoch 259/1000
12000000/12000000 - 34s - loss: -3.6043e+00 - val_loss: 1.1093
Epoch 260/1000
12000000/12000000 - 36s - loss: -3.6049e+00 - val_loss: 1.0675
Epoch 261/1000
12000000/12000000 - 36s - loss: -3.6058e+00 - val_loss: 1.0626
Epoch 262/1000
12000000/12000000 - 35s - loss: -3.6068e+00 - val_loss: 0.9836
Epoch 263/1000
12000000/12000000 - 36s - loss: -3.6075e+00 - val_loss: 1.0862
Epoch 264/1000
12000000/12000000 - 38s - loss: -3.6087e+00 - val_loss: 1.0354
Epoch 265/1000
12000000/12000000 - 37s - loss: -3.6095e+00 - val_loss: 1.0169
Epoch 266/1000
12000000/12000000 - 37s - loss: -3.6105e+00 - val_loss: 1.2018
Epoch 267/1000
12000000/12000000 - 39s - loss: -3.6114e+00 - val_loss: 0.9451
Epoch 268/1000
12000000/12000000 - 36s - loss: -3.6118e+00 - val_loss: 0.9756
Epoch 269/1000
12000000/12000000 - 36s - loss: -3.6127e+00 - val_loss: 1.0364
Epoch 270/1000
12000000/12000000 - 36s - loss: -3.6138e+00 - val_loss: 1.0978
Epoch 271/1000
12000000/12000000 - 35s - loss: -3.6147e+00 - val_loss: 0.9758
Epoch 272/1000
12000000/12000000 - 37s - loss: -3.6156e+00 - val_loss: 1.0257
Epoch 273/1000
12000000/12000000 - 39s - loss: -3.6167e+00 - val_loss: 1.0655
Epoch 274/1000
12000000/12000000 - 38s - loss: -3.6176e+00 - val_loss: 1.1380
Epoch 275/1000
12000000/12000000 - 36s - loss: -3.6183e+00 - val_loss: 1.0345
Epoch 276/1000
12000000/12000000 - 37s - loss: -3.6190e+00 - val_loss: 1.0764
Epoch 277/1000
12000000/12000000 - 34s - loss: -3.6199e+00 - val_loss: 1.1294
Epoch 278/1000
12000000/12000000 - 38s - loss: -3.6204e+00 - val_loss: 1.0730
Epoch 279/1000
12000000/12000000 - 33s - loss: -3.6214e+00 - val_loss: 1.0713
Epoch 280/1000
12000000/12000000 - 33s - loss: -3.6219e+00 - val_loss: 1.0980
Epoch 281/1000
12000000/12000000 - 36s - loss: -3.6228e+00 - val_loss: 1.0760
Epoch 282/1000
12000000/12000000 - 34s - loss: -3.6237e+00 - val_loss: 1.0525
Epoch 283/1000
12000000/12000000 - 33s - loss: -3.6247e+00 - val_loss: 1.1125
Epoch 284/1000
12000000/12000000 - 37s - loss: -3.6255e+00 - val_loss: 1.0161
Epoch 285/1000
12000000/12000000 - 35s - loss: -3.6260e+00 - val_loss: 1.0668
Epoch 286/1000
12000000/12000000 - 36s - loss: -3.6272e+00 - val_loss: 1.1272
Epoch 287/1000
12000000/12000000 - 31s - loss: -3.6278e+00 - val_loss: 1.1459
Epoch 288/1000
12000000/12000000 - 32s - loss: -3.6286e+00 - val_loss: 1.0902
Epoch 289/1000
12000000/12000000 - 38s - loss: -3.6299e+00 - val_loss: 1.0579
Epoch 290/1000
12000000/12000000 - 38s - loss: -3.6308e+00 - val_loss: 1.0316
Epoch 291/1000
12000000/12000000 - 35s - loss: -3.6314e+00 - val_loss: 1.0172
Epoch 292/1000
12000000/12000000 - 33s - loss: -3.6318e+00 - val_loss: 1.0199
Epoch 293/1000
12000000/12000000 - 38s - loss: -3.6325e+00 - val_loss: 1.1099
Epoch 294/1000
12000000/12000000 - 38s - loss: -3.6334e+00 - val_loss: 1.1172
Epoch 295/1000
12000000/12000000 - 35s - loss: -3.6344e+00 - val_loss: 1.1122
Epoch 296/1000
12000000/12000000 - 35s - loss: -3.6348e+00 - val_loss: 1.0660
Epoch 297/1000
12000000/12000000 - 33s - loss: -3.6357e+00 - val_loss: 1.0340
Epoch 298/1000
12000000/12000000 - 32s - loss: -3.6364e+00 - val_loss: 1.0804
Epoch 299/1000
12000000/12000000 - 36s - loss: -3.6375e+00 - val_loss: 1.1759
Epoch 300/1000
12000000/12000000 - 34s - loss: -3.6381e+00 - val_loss: 1.0961
Epoch 301/1000
12000000/12000000 - 35s - loss: -3.6391e+00 - val_loss: 1.0552
Epoch 302/1000
12000000/12000000 - 33s - loss: -3.6397e+00 - val_loss: 1.0802
Epoch 303/1000
12000000/12000000 - 36s - loss: -3.6406e+00 - val_loss: 1.0865
Epoch 304/1000
12000000/12000000 - 35s - loss: -3.6415e+00 - val_loss: 1.0635
Epoch 305/1000
12000000/12000000 - 38s - loss: -3.6421e+00 - val_loss: 1.0738
Epoch 306/1000
12000000/12000000 - 38s - loss: -3.6426e+00 - val_loss: 1.1623
Epoch 307/1000
12000000/12000000 - 34s - loss: -3.6435e+00 - val_loss: 1.0144
Epoch 308/1000
12000000/12000000 - 31s - loss: -3.6440e+00 - val_loss: 1.0478
Epoch 309/1000
12000000/12000000 - 35s - loss: -3.6450e+00 - val_loss: 1.0731
Epoch 310/1000
12000000/12000000 - 37s - loss: -3.6454e+00 - val_loss: 1.0522
Epoch 311/1000
12000000/12000000 - 36s - loss: -3.6463e+00 - val_loss: 1.0056
Epoch 312/1000
12000000/12000000 - 34s - loss: -3.6469e+00 - val_loss: 1.0926
Epoch 313/1000
12000000/12000000 - 35s - loss: -3.6476e+00 - val_loss: 1.0821
Epoch 314/1000
12000000/12000000 - 33s - loss: -3.6481e+00 - val_loss: 1.1268
Epoch 315/1000
12000000/12000000 - 37s - loss: -3.6491e+00 - val_loss: 1.1170
Epoch 316/1000
12000000/12000000 - 33s - loss: -3.6496e+00 - val_loss: 1.0621
Epoch 317/1000
12000000/12000000 - 32s - loss: -3.6504e+00 - val_loss: 1.0736
Epoch 318/1000
12000000/12000000 - 33s - loss: -3.6510e+00 - val_loss: 1.0688
Epoch 319/1000
12000000/12000000 - 37s - loss: -3.6520e+00 - val_loss: 1.1646
Epoch 320/1000
12000000/12000000 - 37s - loss: -3.6527e+00 - val_loss: 1.1209
Epoch 321/1000
12000000/12000000 - 37s - loss: -3.6531e+00 - val_loss: 1.1150
Epoch 322/1000
12000000/12000000 - 32s - loss: -3.6539e+00 - val_loss: 0.9675
Epoch 323/1000
12000000/12000000 - 36s - loss: -3.6546e+00 - val_loss: 1.0232
Epoch 324/1000
12000000/12000000 - 38s - loss: -3.6552e+00 - val_loss: 1.1224
Epoch 325/1000
12000000/12000000 - 37s - loss: -3.6554e+00 - val_loss: 1.0757
Epoch 326/1000
12000000/12000000 - 38s - loss: -3.6563e+00 - val_loss: 1.0698
Epoch 327/1000
12000000/12000000 - 37s - loss: -3.6571e+00 - val_loss: 1.0303
Epoch 328/1000
12000000/12000000 - 38s - loss: -3.6580e+00 - val_loss: 1.0727
Epoch 329/1000
12000000/12000000 - 35s - loss: -3.6585e+00 - val_loss: 0.9076
Epoch 330/1000
12000000/12000000 - 36s - loss: -3.6591e+00 - val_loss: 0.9957
Epoch 331/1000
12000000/12000000 - 36s - loss: -3.6599e+00 - val_loss: 1.0649
Epoch 332/1000
12000000/12000000 - 38s - loss: -3.6601e+00 - val_loss: 1.1135
Epoch 333/1000
12000000/12000000 - 39s - loss: -3.6613e+00 - val_loss: 1.0554
Epoch 334/1000
12000000/12000000 - 37s - loss: -3.6618e+00 - val_loss: 1.0743
Epoch 335/1000
12000000/12000000 - 35s - loss: -3.6624e+00 - val_loss: 1.0130
Epoch 336/1000
12000000/12000000 - 36s - loss: -3.6631e+00 - val_loss: 1.0023
Epoch 337/1000
12000000/12000000 - 31s - loss: -3.6639e+00 - val_loss: 1.0362
Epoch 338/1000
12000000/12000000 - 32s - loss: -3.6647e+00 - val_loss: 1.1145
Epoch 339/1000
12000000/12000000 - 30s - loss: -3.6651e+00 - val_loss: 1.0977
Epoch 340/1000
12000000/12000000 - 30s - loss: -3.6660e+00 - val_loss: 1.1434
Epoch 341/1000
12000000/12000000 - 36s - loss: -3.6663e+00 - val_loss: 1.0825
Epoch 342/1000
12000000/12000000 - 37s - loss: -3.6670e+00 - val_loss: 1.0768
Epoch 343/1000
12000000/12000000 - 37s - loss: -3.6679e+00 - val_loss: 1.0345
Epoch 344/1000
12000000/12000000 - 37s - loss: -3.6686e+00 - val_loss: 1.0301
Epoch 345/1000
12000000/12000000 - 32s - loss: -3.6688e+00 - val_loss: 1.0597
Epoch 346/1000
12000000/12000000 - 34s - loss: -3.6697e+00 - val_loss: 1.0905
Epoch 347/1000
12000000/12000000 - 38s - loss: -3.6702e+00 - val_loss: 0.9639
Epoch 348/1000
12000000/12000000 - 38s - loss: -3.6702e+00 - val_loss: 1.1163
Epoch 349/1000
12000000/12000000 - 36s - loss: -3.6710e+00 - val_loss: 1.1480
Epoch 350/1000
12000000/12000000 - 37s - loss: -3.6720e+00 - val_loss: 1.2234
Epoch 351/1000
12000000/12000000 - 39s - loss: -3.6728e+00 - val_loss: 1.1176
Epoch 352/1000
12000000/12000000 - 37s - loss: -3.6734e+00 - val_loss: 1.0124
Epoch 353/1000
12000000/12000000 - 36s - loss: -3.6737e+00 - val_loss: 0.8939
Epoch 354/1000
12000000/12000000 - 36s - loss: -3.6745e+00 - val_loss: 1.1129
Epoch 355/1000
12000000/12000000 - 37s - loss: -3.6750e+00 - val_loss: 1.1403
Epoch 356/1000
12000000/12000000 - 37s - loss: -3.6758e+00 - val_loss: 1.1063
Epoch 357/1000
12000000/12000000 - 37s - loss: -3.6763e+00 - val_loss: 0.9951
Epoch 358/1000
12000000/12000000 - 35s - loss: -3.6771e+00 - val_loss: 1.0660
Epoch 359/1000
12000000/12000000 - 33s - loss: -3.6775e+00 - val_loss: 1.1365
Epoch 360/1000
12000000/12000000 - 37s - loss: -3.6783e+00 - val_loss: 1.1243
Epoch 361/1000
12000000/12000000 - 34s - loss: -3.6787e+00 - val_loss: 1.1265
Epoch 362/1000
12000000/12000000 - 34s - loss: -3.6792e+00 - val_loss: 1.1163
Epoch 363/1000
12000000/12000000 - 33s - loss: -3.6802e+00 - val_loss: 1.0387
Epoch 364/1000
12000000/12000000 - 33s - loss: -3.6803e+00 - val_loss: 1.1087
Epoch 365/1000
12000000/12000000 - 34s - loss: -3.6810e+00 - val_loss: 1.0927
Epoch 366/1000
12000000/12000000 - 34s - loss: -3.6815e+00 - val_loss: 1.0811
Epoch 367/1000
12000000/12000000 - 35s - loss: -3.6820e+00 - val_loss: 1.0788
Epoch 368/1000
12000000/12000000 - 34s - loss: -3.6823e+00 - val_loss: 1.1268
Epoch 369/1000
12000000/12000000 - 36s - loss: -3.6835e+00 - val_loss: 1.1421
Epoch 370/1000
12000000/12000000 - 36s - loss: -3.6836e+00 - val_loss: 1.1986
Epoch 371/1000
12000000/12000000 - 37s - loss: -3.6843e+00 - val_loss: 1.0563
Epoch 372/1000
12000000/12000000 - 34s - loss: -3.6849e+00 - val_loss: 1.2151
Epoch 373/1000
12000000/12000000 - 37s - loss: -3.6854e+00 - val_loss: 1.1773
Epoch 374/1000
12000000/12000000 - 34s - loss: -3.6859e+00 - val_loss: 1.1554
Epoch 375/1000
12000000/12000000 - 30s - loss: -3.6866e+00 - val_loss: 1.1386
Epoch 376/1000
12000000/12000000 - 33s - loss: -3.6875e+00 - val_loss: 1.1400
Epoch 377/1000
12000000/12000000 - 36s - loss: -3.6878e+00 - val_loss: 1.0973
Epoch 378/1000
12000000/12000000 - 34s - loss: -3.6883e+00 - val_loss: 1.1634
Epoch 379/1000
12000000/12000000 - 38s - loss: -3.6892e+00 - val_loss: 1.2238
Epoch 380/1000
12000000/12000000 - 32s - loss: -3.6896e+00 - val_loss: 1.0545
Epoch 381/1000
12000000/12000000 - 33s - loss: -3.6901e+00 - val_loss: 1.1375
Epoch 382/1000
12000000/12000000 - 35s - loss: -3.6906e+00 - val_loss: 1.1186
Epoch 383/1000
12000000/12000000 - 33s - loss: -3.6912e+00 - val_loss: 1.1736
Epoch 384/1000
12000000/12000000 - 32s - loss: -3.6914e+00 - val_loss: 1.0341
Epoch 385/1000
12000000/12000000 - 33s - loss: -3.6921e+00 - val_loss: 1.0585
Epoch 386/1000
12000000/12000000 - 33s - loss: -3.6927e+00 - val_loss: 1.1742
Epoch 387/1000
12000000/12000000 - 31s - loss: -3.6936e+00 - val_loss: 1.1191
Epoch 388/1000
12000000/12000000 - 30s - loss: -3.6939e+00 - val_loss: 1.1039
Epoch 389/1000
12000000/12000000 - 36s - loss: -3.6949e+00 - val_loss: 1.2570
Epoch 390/1000
12000000/12000000 - 32s - loss: -3.6949e+00 - val_loss: 1.1917
Epoch 391/1000
12000000/12000000 - 32s - loss: -3.6955e+00 - val_loss: 1.1082
Epoch 392/1000
12000000/12000000 - 33s - loss: -3.6956e+00 - val_loss: 1.2389
Epoch 393/1000
12000000/12000000 - 36s - loss: -3.6965e+00 - val_loss: 1.1305
Epoch 394/1000
12000000/12000000 - 35s - loss: -3.6970e+00 - val_loss: 1.1863
Epoch 395/1000
12000000/12000000 - 32s - loss: -3.6976e+00 - val_loss: 1.1441
Epoch 396/1000
12000000/12000000 - 30s - loss: -3.6980e+00 - val_loss: 1.1238
Epoch 397/1000
12000000/12000000 - 30s - loss: -3.6985e+00 - val_loss: 1.0767
Epoch 398/1000
12000000/12000000 - 30s - loss: -3.6990e+00 - val_loss: 1.2048
Epoch 399/1000
12000000/12000000 - 30s - loss: -3.6998e+00 - val_loss: 1.1442
Epoch 400/1000
12000000/12000000 - 30s - loss: -3.7008e+00 - val_loss: 1.0956
Epoch 401/1000
12000000/12000000 - 31s - loss: -3.7009e+00 - val_loss: 1.1857
Epoch 402/1000
12000000/12000000 - 34s - loss: -3.7014e+00 - val_loss: 1.2806
Epoch 403/1000
12000000/12000000 - 33s - loss: -3.7018e+00 - val_loss: 1.1838
Epoch 404/1000
12000000/12000000 - 37s - loss: -3.7023e+00 - val_loss: 1.1463
Epoch 405/1000
12000000/12000000 - 38s - loss: -3.7032e+00 - val_loss: 1.1827
Epoch 406/1000
12000000/12000000 - 33s - loss: -3.7037e+00 - val_loss: 1.2567
Epoch 407/1000
12000000/12000000 - 33s - loss: -3.7042e+00 - val_loss: 1.2329
Epoch 408/1000
12000000/12000000 - 34s - loss: -3.7047e+00 - val_loss: 1.1166
Epoch 409/1000
12000000/12000000 - 33s - loss: -3.7048e+00 - val_loss: 1.1400
Epoch 410/1000
12000000/12000000 - 36s - loss: -3.7058e+00 - val_loss: 1.2346
Epoch 411/1000
12000000/12000000 - 36s - loss: -3.7061e+00 - val_loss: 1.0994
Epoch 412/1000
12000000/12000000 - 32s - loss: -3.7075e+00 - val_loss: 1.2772
Epoch 413/1000
12000000/12000000 - 30s - loss: -3.7077e+00 - val_loss: 1.2570
Epoch 414/1000
12000000/12000000 - 30s - loss: -3.7080e+00 - val_loss: 1.2468
Epoch 415/1000
12000000/12000000 - 32s - loss: -3.7086e+00 - val_loss: 1.1365
Epoch 416/1000
12000000/12000000 - 37s - loss: -3.7093e+00 - val_loss: 1.2281
Epoch 417/1000
12000000/12000000 - 34s - loss: -3.7098e+00 - val_loss: 1.1980
Epoch 418/1000
12000000/12000000 - 34s - loss: -3.7104e+00 - val_loss: 1.1746
Epoch 419/1000
12000000/12000000 - 34s - loss: -3.7109e+00 - val_loss: 1.2594
Epoch 420/1000
12000000/12000000 - 39s - loss: -3.7111e+00 - val_loss: 1.1665
Epoch 421/1000
12000000/12000000 - 34s - loss: -3.7116e+00 - val_loss: 1.2628
Epoch 422/1000
12000000/12000000 - 35s - loss: -3.7124e+00 - val_loss: 1.2179
Epoch 423/1000
12000000/12000000 - 35s - loss: -3.7126e+00 - val_loss: 1.2465
Epoch 424/1000
12000000/12000000 - 34s - loss: -3.7130e+00 - val_loss: 1.1936
Epoch 425/1000
12000000/12000000 - 36s - loss: -3.7136e+00 - val_loss: 1.2939
Epoch 426/1000
12000000/12000000 - 37s - loss: -3.7143e+00 - val_loss: 1.2888
Epoch 427/1000
12000000/12000000 - 35s - loss: -3.7144e+00 - val_loss: 1.1924
Epoch 428/1000
12000000/12000000 - 37s - loss: -3.7152e+00 - val_loss: 1.2500
Epoch 429/1000
12000000/12000000 - 38s - loss: -3.7154e+00 - val_loss: 1.1936
Epoch 430/1000
12000000/12000000 - 39s - loss: -3.7160e+00 - val_loss: 1.3050
Epoch 431/1000
12000000/12000000 - 37s - loss: -3.7163e+00 - val_loss: 1.2793
Epoch 432/1000
12000000/12000000 - 33s - loss: -3.7171e+00 - val_loss: 1.2527
Epoch 433/1000
12000000/12000000 - 36s - loss: -3.7176e+00 - val_loss: 1.3035
Epoch 434/1000
12000000/12000000 - 32s - loss: -3.7176e+00 - val_loss: 1.3776
Epoch 435/1000
12000000/12000000 - 37s - loss: -3.7184e+00 - val_loss: 1.1993
Epoch 436/1000
12000000/12000000 - 36s - loss: -3.7189e+00 - val_loss: 1.3280
Epoch 437/1000
12000000/12000000 - 35s - loss: -3.7192e+00 - val_loss: 1.2415
Epoch 438/1000
12000000/12000000 - 37s - loss: -3.7198e+00 - val_loss: 1.2586
Epoch 439/1000
12000000/12000000 - 33s - loss: -3.7206e+00 - val_loss: 1.3392
Epoch 440/1000
12000000/12000000 - 36s - loss: -3.7210e+00 - val_loss: 1.1510
Epoch 441/1000
12000000/12000000 - 37s - loss: -3.7214e+00 - val_loss: 1.1768
Epoch 442/1000
12000000/12000000 - 36s - loss: -3.7217e+00 - val_loss: 1.3133
Epoch 443/1000
12000000/12000000 - 34s - loss: -3.7221e+00 - val_loss: 1.2334
Epoch 444/1000
12000000/12000000 - 36s - loss: -3.7226e+00 - val_loss: 1.1390
Epoch 445/1000
12000000/12000000 - 33s - loss: -3.7229e+00 - val_loss: 1.3972
Epoch 446/1000
12000000/12000000 - 36s - loss: -3.7236e+00 - val_loss: 1.3159
Epoch 447/1000
12000000/12000000 - 38s - loss: -3.7242e+00 - val_loss: 1.3065
Epoch 448/1000
12000000/12000000 - 39s - loss: -3.7245e+00 - val_loss: 1.3069
Epoch 449/1000
12000000/12000000 - 37s - loss: -3.7249e+00 - val_loss: 1.2549
Epoch 450/1000
12000000/12000000 - 35s - loss: -3.7256e+00 - val_loss: 1.3279
Epoch 451/1000
12000000/12000000 - 36s - loss: -3.7263e+00 - val_loss: 1.2868
Epoch 452/1000
12000000/12000000 - 35s - loss: -3.7266e+00 - val_loss: 1.2739
Epoch 453/1000
12000000/12000000 - 33s - loss: -3.7268e+00 - val_loss: 1.3766
Epoch 454/1000
12000000/12000000 - 37s - loss: -3.7275e+00 - val_loss: 1.2269
Epoch 455/1000