Cannot train the network

Salman_Abbasi: <p>Hi</p>
<p>I am trying to train a network with input of shape (174,1) which is a smoothed time series signal and output a signal label(174,1). I have tried some networks from linear regression, CNN1D, but failed to train. The network does not seem to learn. I have  pasted the input and the label time series. This would be inputted  and outputted as (174,1). I appreciate help<br>
salman<br>
<strong>Input</strong><br>
0<br>
4.18253e-07<br>
6.25848e-07<br>
5.84575e-07<br>
4.14491e-07<br>
2.33669e-07<br>
1.03124e-07<br>
3.6766e-08<br>
2.25682e-08<br>
3.67369e-08<br>
5.46634e-08<br>
5.60218e-08<br>
3.35225e-08<br>
-3.82534e-09<br>
-3.7432e-08<br>
-5.2614e-08<br>
-4.95902e-08<br>
-3.9658e-08<br>
-3.29841e-08<br>
-3.01247e-08<br>
-2.43349e-08<br>
-1.01856e-08<br>
1.02387e-08<br>
2.85015e-08<br>
3.66587e-08<br>
3.28471e-08<br>
2.14525e-08<br>
9.00486e-09<br>
-2.82683e-10<br>
-6.21392e-09<br>
-1.12802e-08<br>
-1.81336e-08<br>
-2.76227e-08<br>
-3.81269e-08<br>
-4.64072e-08<br>
-4.93542e-08<br>
-4.56265e-08<br>
-3.61518e-08<br>
-2.34187e-08<br>
-1.02873e-08<br>
1.07397e-09<br>
9.64328e-09<br>
1.53799e-08<br>
1.87336e-08<br>
2.03344e-08<br>
2.09435e-08<br>
2.15068e-08<br>
2.30533e-08<br>
2.63472e-08<br>
3.14275e-08<br>
3.73646e-08<br>
4.24657e-08<br>
4.48938e-08<br>
4.32527e-08<br>
3.69056e-08<br>
2.60382e-08<br>
1.14924e-08<br>
-5.474e-09<br>
-2.33905e-08<br>
-4.07472e-08<br>
-5.60986e-08<br>
-6.81632e-08<br>
-7.58616e-08<br>
-7.84307e-08<br>
-7.54817e-08<br>
-6.71011e-08<br>
-5.37653e-08<br>
-3.64516e-08<br>
-1.657e-08<br>
4.19623e-09<br>
2.40891e-08<br>
4.14968e-08<br>
5.52465e-08<br>
6.46469e-08<br>
6.94281e-08<br>
6.96969e-08<br>
6.58246e-08<br>
5.84126e-08<br>
4.82109e-08<br>
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-2.07163e-08<br>
-1.29426e-08<br>
-5.68107e-09<br>
6.44103e-10<br>
5.74641e-09<br>
9.46534e-09<br>
1.17695e-08<br>
1.27583e-08<br>
1.26316e-08<br>
1.1701e-08<br>
1.03009e-08<br>
8.75454e-09<br>
7.35068e-09<br>
6.33561e-09<br>
5.90387e-09<br>
6.18461e-09<br>
7.23588e-09<br>
9.03935e-09<br>
1.14898e-08<br>
1.4412e-08<br>
1.75921e-08<br>
2.07809e-08<br>
2.37243e-08<br>
2.6182e-08<br>
2.79273e-08<br>
2.87658e-08<br>
2.85709e-08<br>
2.73503e-08<br>
2.5218e-08<br>
2.23534e-08<br>
1.89692e-08<br>
1.52876e-08<br>
1.15147e-08<br>
7.82862e-09<br>
4.37359e-09<br>
1.25552e-09<br>
-1.45517e-09<br>
-3.72149e-09<br>
-5.53915e-09<br>
-6.91896e-09<br>
-7.88362e-09<br>
-8.46514e-09<br>
-8.69505e-09<br>
-8.61432e-09<br>
-8.27313e-09<br>
-7.7298e-09<br>
-7.04839e-09<br>
-6.29663e-09<br>
-5.5376e-09<br>
-4.82532e-09<br>
-4.20149e-09<br>
-3.69277e-09<br>
-3.31181e-09<br>
-3.05476e-09<br>
-2.90152e-09<br>
-2.81823e-09<br>
-2.76388e-09<br>
-2.69684e-09<br>
-2.58118e-09<br>
-2.39284e-09<br>
-2.1232e-09<br>
-1.78112e-09<br>
-1.39058e-09<br>
-9.87143e-10<br>
-6.07919e-10<br>
-2.83052e-10<br>
-3.07821e-11<br>
1.4294e-10<br>
2.43158e-10<br>
2.8209e-10<br>
2.74077e-10<br>
2.35004e-10<br>
1.80104e-10<br>
1.21749e-10<br>
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-8.76295e-13<br>
-1.40839e-11<br>
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-9.27075e-12<br>
0</p>
<p><strong>Label</strong></p>
<p>0<br>
-1.71736e-08<br>
-1.53378e-08<br>
-9.79676e-10<br>
7.9377e-09<br>
5.7047e-09<br>
-1.62103e-09<br>
-5.58527e-09<br>
-2.47281e-09<br>
3.47859e-09<br>
6.07766e-09<br>
4.55817e-09<br>
4.09875e-10<br>
-5.31704e-09<br>
-8.80423e-09<br>
-8.93366e-09<br>
-7.01059e-09<br>
-1.53077e-09<br>
3.48999e-09<br>
2.5344e-09<br>
1.21082e-09<br>
6.47833e-09<br>
8.45462e-09<br>
-1.26533e-09<br>
-2.07172e-08<br>
-3.72516e-08<br>
-3.9911e-08<br>
-2.72364e-08<br>
-6.38585e-09<br>
1.03922e-08<br>
1.74559e-08<br>
1.78949e-08<br>
1.54622e-08<br>
1.21602e-08<br>
8.3302e-09<br>
5.14523e-09<br>
5.24475e-09<br>
1.04539e-08<br>
1.91552e-08<br>
2.40073e-08<br>
1.76475e-08<br>
-6.3008e-10<br>
-2.16299e-08<br>
-3.39414e-08<br>
-3.16058e-08<br>
-1.83078e-08<br>
-5.60728e-09<br>
-2.16836e-09<br>
-8.46477e-09<br>
-1.69005e-08<br>
-1.90525e-08<br>
-1.03817e-08<br>
6.78319e-09<br>
2.46788e-08<br>
3.25951e-08<br>
2.44597e-08<br>
4.44593e-09<br>
-1.7565e-08<br>
-3.49127e-08<br>
-4.28466e-08<br>
-3.89797e-08<br>
-2.38185e-08<br>
-4.64603e-10<br>
2.61788e-08<br>
5.02617e-08<br>
6.66615e-08<br>
7.30009e-08<br>
6.85348e-08<br>
5.44703e-08<br>
3.29172e-08<br>
7.4654e-09<br>
-1.81527e-08<br>
-4.08275e-08<br>
-5.84084e-08<br>
-6.94242e-08<br>
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2.81198e-09<br>
1.81048e-09<br>
8.35732e-10<br>
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3.35482e-12<br>
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1.67221e-10<br>
1.1468e-10<br>
5.73629e-11<br>
0</p>