In this project, I will employ regression with Neural Networks in order to make a quantitative prediction of a continuous variable based on a number of input features. I will be using the simulated data from the LHCb experiment at CERN. The dataset can be found at https://cernbox.cern.ch/s/HhkokuJGiKuSnap.
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.wrappers.scikit_learn import KerasRegressor
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import KFold
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline
from tensorflow . keras . models import Sequential
from tensorflow . keras . layers import Dense
from tensorflow . keras . layers import Dropout
from sklearn.model_selection import cross_val_predict
2023-03-03 07:06:07.218458: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
df = pd.read_csv('mc-chic1.csv')
df.head()
Unnamed: 0 | ep | eta | p | phi | pol | pt | qp | tx | ty | zV | |
---|---|---|---|---|---|---|---|---|---|---|---|
0 | 0 | 0.005459 | 3.210803 | 72.079880 | 0.294754 | 1.0 | 5.803692 | 72.079880 | 0.077296 | 0.023467 | -60.3975 |
1 | 1 | 0.004050 | 4.436362 | 37.638340 | -0.088796 | 1.0 | 0.891071 | -37.638340 | 0.023588 | -0.002100 | -60.3975 |
2 | 2 | 0.003901 | 3.577396 | 18.565832 | 0.319936 | 1.0 | 1.036960 | 18.565832 | 0.053102 | 0.017594 | -60.3975 |
3 | 3 | 0.003859 | 3.532860 | 8.632520 | 0.219504 | 1.0 | 0.504075 | -8.632520 | 0.057089 | 0.012736 | -60.3975 |
4 | 4 | 0.004975 | 3.300828 | 43.359665 | -0.720869 | 1.0 | 3.191501 | 43.359665 | 0.055445 | -0.048714 | -8.0373 |
checking if all the columns have the same length
col_lengths = df.apply(lambda x: len(x))
print(col_lengths)
Unnamed: 0 208984 ep 208984 eta 208984 p 208984 phi 208984 pol 208984 pt 208984 qp 208984 tx 208984 ty 208984 zV 208984 dtype: int64
Checking if there are any null values in the dataframe
null_rows = df[df.isnull().any(axis=1)]
print(null_rows)
Empty DataFrame Columns: [Unnamed: 0, ep, eta, p, phi, pol, pt, qp, tx, ty, zV] Index: []
plt.scatter(df['p'] , df['ep'], s= 0.2)
plt.xlabel('Momentum(GeV/c)')
plt.ylabel('Momentum resolution')
plt.xlim(0, 400)
plt.ylim(0, 0.012)
plt.show()
plt.hist(df['pt'], bins=2000, alpha=0.5, color = 'blue')
plt.hist(df['p'] ,bins=2000, alpha=0.5, color = 'red')
plt.xscale('log')
# Add labels and a legend
plt.xlabel('Momentum value')
plt.ylabel('Count')
plt.legend(['Transverse momentum,pt', 'Momentum,p'])
# Display the plot
plt.show()
df_copy = df.copy()
p = df['p']
p_val = p.values
pt = df['pt']
pt_val = pt.values
ep = df['ep']
ep_val = ep.values
pz = np.sqrt(np.square(p_val)-np.square(pt_val)) # evaluating the z-component of the momentum
epz = np.multiply(ep_val, np.divide(p_val,pz)) #calculating the error for the z-compoenet
#appending the new columns to the dataframe
df = df.assign(pz= pz)
df = df.assign(epz=epz)
df.head()
Unnamed: 0 | ep | eta | p | phi | pol | pt | qp | tx | ty | zV | pz | epz | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 0 | 0.005459 | 3.210803 | 72.079880 | 0.294754 | 1.0 | 5.803692 | 72.079880 | 0.077296 | 0.023467 | -60.3975 | 71.845851 | 0.005477 |
1 | 1 | 0.004050 | 4.436362 | 37.638340 | -0.088796 | 1.0 | 0.891071 | -37.638340 | 0.023588 | -0.002100 | -60.3975 | 37.627791 | 0.004052 |
2 | 2 | 0.003901 | 3.577396 | 18.565832 | 0.319936 | 1.0 | 1.036960 | 18.565832 | 0.053102 | 0.017594 | -60.3975 | 18.536851 | 0.003908 |
3 | 3 | 0.003859 | 3.532860 | 8.632520 | 0.219504 | 1.0 | 0.504075 | -8.632520 | 0.057089 | 0.012736 | -60.3975 | 8.617790 | 0.003866 |
4 | 4 | 0.004975 | 3.300828 | 43.359665 | -0.720869 | 1.0 | 3.191501 | 43.359665 | 0.055445 | -0.048714 | -8.0373 | 43.242050 | 0.004989 |
plt.scatter( df['pz'],df['epz'], s= 0.2)
plt.xlabel('Momentum in Z-direction')
plt.ylabel('Resolution of momentum in Z-direction')
plt.xlim(0, 400)
plt.ylim(0, 0.012)
plt.show()
data = df[['p','tx','ty','eta','phi']].copy() #training data
target = df['ep'].copy() #target data
data.head()
p | tx | ty | eta | phi | |
---|---|---|---|---|---|
0 | 72.079880 | 0.077296 | 0.023467 | 3.210803 | 0.294754 |
1 | 37.638340 | 0.023588 | -0.002100 | 4.436362 | -0.088796 |
2 | 18.565832 | 0.053102 | 0.017594 | 3.577396 | 0.319936 |
3 | 8.632520 | 0.057089 | 0.012736 | 3.532860 | 0.219504 |
4 | 43.359665 | 0.055445 | -0.048714 | 3.300828 | -0.720869 |
target.head()
0 0.005459 1 0.004050 2 0.003901 3 0.003859 4 0.004975 Name: ep, dtype: float64
num_inputs = 5; num_outputs = 1
num_nodes = num_inputs
#simple model with only one hidden layer
def simple_model():
# create model
model = Sequential ()
# no activation required for the output , as this is a regression problem ,
# ie . we need a numerical prediction for any input
model.add(Dense (num_nodes , input_dim = num_inputs , kernel_initializer='normal', activation ='relu' ))
model.add(Dropout (0.2))
model.add(Dense ( num_outputs , kernel_initializer='normal'))
# Compile model
model.compile( loss ='mean_squared_error',optimizer= 'adam')
return model
#contains two hidden layers
def dense_model():
# create model
model = Sequential ()
# no activation required for the output , as this is a regression problem ,
# ie . we need a numerical prediction for any input
model.add( Dense (num_nodes , input_dim = num_inputs , kernel_initializer='normal', activation ='relu' ))
model.add( Dropout (0.2))
model.add( Dense (4, kernel_initializer='normal', activation ='relu' ))
model.add( Dropout (0.2))
model.add( Dense ( num_outputs , kernel_initializer='normal'))
# Compile model
model.compile( loss ='mean_squared_error',optimizer= 'adam')
return model
#one hidden layer with twice the number of nodes as input
def wider_model():
# create model
model = Sequential ()
# no activation required for the output , as this is a regression problem ,
# ie . we need a numerical prediction for any input
model.add( Dense (num_nodes*2 , input_dim = num_inputs , kernel_initializer='normal', activation ='relu' ))
model.add( Dropout (0.2))
model.add( Dense ( num_outputs , kernel_initializer='normal'))
# Compile model
model.compile( loss ='mean_squared_error',optimizer= 'adam')
return model
#this regressor uses the raw input
def regressor(model):
N_epochs = 10
batchSize = 1000
# must always set the random seed for reproducibility
Answer_to_all_questions = 42
np.random.seed(Answer_to_all_questions)
estimator = KerasRegressor (build_fn = model , epochs = N_epochs , batch_size = batchSize, verbose = 1 )
kfold = KFold ( n_splits =10 , random_state = Answer_to_all_questions , shuffle = True )
# data and target are 5 - column and 1 - column arrays produced with pandas . DataFrame . values
results = cross_val_score( estimator , data , target , cv = kfold , scoring = 'r2')
return results
#this regressor use standardise input
def standardise_regressor(model):
# must always set the random seed for reproducibility
N_epochs = 10
batchSize = 1000
Answer_to_all_questions = 42
np.random.seed(Answer_to_all_questions)
estimators = []
estimators.append(( 'standardize',StandardScaler()))
estimators.append(( 'mlp' , KerasRegressor(build_fn = model, epochs = N_epochs , batch_size = batchSize )))
pipeline = Pipeline(estimators)
kfold = KFold(n_splits =10 , random_state = Answer_to_all_questions , shuffle = True )
# data and target are 5 - column and 1 - column arrays produced with pandas . DataFrame . values
results = cross_val_score( pipeline , data , target , cv = kfold , scoring = 'r2')
return results
test1 = regressor(simple_model)
/var/folders/sl/3pszjjd95ks506qykf9w8w7r0000gn/T/ipykernel_17164/2995250259.py:7: DeprecationWarning: KerasRegressor is deprecated, use Sci-Keras (https://github.com/adriangb/scikeras) instead. See https://www.adriangb.com/scikeras/stable/migration.html for help migrating. estimator = KerasRegressor (build_fn = model , epochs = N_epochs , batch_size = batchSize, verbose = 1 ) 2023-03-03 07:06:22.815704: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Epoch 1/10 189/189 [==============================] - 0s 581us/step - loss: 8.4228e-04 Epoch 2/10 189/189 [==============================] - 0s 541us/step - loss: 6.2426e-07 Epoch 3/10 189/189 [==============================] - 0s 622us/step - loss: 5.2074e-07 Epoch 4/10 189/189 [==============================] - 0s 553us/step - loss: 5.1189e-07 Epoch 5/10 189/189 [==============================] - 0s 534us/step - loss: 5.0554e-07 Epoch 6/10 189/189 [==============================] - 0s 532us/step - loss: 5.0184e-07 Epoch 7/10 189/189 [==============================] - 0s 603us/step - loss: 5.0900e-07 Epoch 8/10 189/189 [==============================] - 0s 557us/step - loss: 5.0141e-07 Epoch 9/10 189/189 [==============================] - 0s 531us/step - loss: 5.0801e-07 Epoch 10/10 189/189 [==============================] - 0s 517us/step - loss: 5.1200e-07 21/21 [==============================] - 0s 521us/step Epoch 1/10 189/189 [==============================] - 0s 570us/step - loss: 0.0053 Epoch 2/10 189/189 [==============================] - 0s 533us/step - loss: 4.8299e-05 Epoch 3/10 189/189 [==============================] - 0s 520us/step - loss: 4.1488e-06 Epoch 4/10 189/189 [==============================] - 0s 522us/step - loss: 1.0092e-06 Epoch 5/10 189/189 [==============================] - 0s 523us/step - loss: 6.5092e-07 Epoch 6/10 189/189 [==============================] - 0s 521us/step - loss: 5.8635e-07 Epoch 7/10 189/189 [==============================] - 0s 527us/step - loss: 5.4651e-07 Epoch 8/10 189/189 [==============================] - 0s 522us/step - loss: 5.2114e-07 Epoch 9/10 189/189 [==============================] - 0s 525us/step - loss: 5.0445e-07 Epoch 10/10 189/189 [==============================] - 0s 524us/step - loss: 4.9212e-07 21/21 [==============================] - 0s 484us/step Epoch 1/10 189/189 [==============================] - 0s 565us/step - loss: 7.7126e-04 Epoch 2/10 189/189 [==============================] - 0s 532us/step - loss: 6.2154e-07 Epoch 3/10 189/189 [==============================] - 0s 525us/step - loss: 5.3818e-07 Epoch 4/10 189/189 [==============================] - 0s 570us/step - loss: 5.3334e-07 Epoch 5/10 189/189 [==============================] - 0s 546us/step - loss: 5.3282e-07 Epoch 6/10 189/189 [==============================] - 0s 537us/step - loss: 5.2556e-07 Epoch 7/10 189/189 [==============================] - 0s 528us/step - loss: 5.2354e-07 Epoch 8/10 189/189 [==============================] - 0s 572us/step - loss: 5.2179e-07 Epoch 9/10 189/189 [==============================] - 0s 592us/step - loss: 5.1650e-07 Epoch 10/10 189/189 [==============================] - 0s 540us/step - loss: 5.2034e-07 21/21 [==============================] - 0s 483us/step Epoch 1/10 189/189 [==============================] - 0s 567us/step - loss: 0.0093 Epoch 2/10 189/189 [==============================] - 0s 538us/step - loss: 3.2203e-04 Epoch 3/10 189/189 [==============================] - 0s 534us/step - loss: 5.6026e-05 Epoch 4/10 189/189 [==============================] - 0s 532us/step - loss: 1.1646e-05 Epoch 5/10 189/189 [==============================] - 0s 529us/step - loss: 2.9116e-06 Epoch 6/10 189/189 [==============================] - 0s 526us/step - loss: 1.2036e-06 Epoch 7/10 189/189 [==============================] - 0s 546us/step - loss: 8.2371e-07 Epoch 8/10 189/189 [==============================] - 0s 552us/step - loss: 6.4924e-07 Epoch 9/10 189/189 [==============================] - 0s 533us/step - loss: 5.5159e-07 Epoch 10/10 189/189 [==============================] - 0s 528us/step - loss: 4.8260e-07 21/21 [==============================] - 0s 455us/step Epoch 1/10 189/189 [==============================] - 0s 575us/step - loss: 9.3464e-05 Epoch 2/10 189/189 [==============================] - 0s 601us/step - loss: 6.8760e-07 Epoch 3/10 189/189 [==============================] - 0s 568us/step - loss: 5.2392e-07 Epoch 4/10 189/189 [==============================] - 0s 563us/step - loss: 4.7494e-07 Epoch 5/10 189/189 [==============================] - 0s 594us/step - loss: 4.5332e-07 Epoch 6/10 189/189 [==============================] - 0s 559us/step - loss: 4.4521e-07 Epoch 7/10 189/189 [==============================] - 0s 557us/step - loss: 4.4232e-07 Epoch 8/10 189/189 [==============================] - 0s 574us/step - loss: 4.3745e-07 Epoch 9/10 189/189 [==============================] - 0s 581us/step - loss: 4.3811e-07 Epoch 10/10 189/189 [==============================] - 0s 591us/step - loss: 4.3394e-07 21/21 [==============================] - 0s 499us/step Epoch 1/10 189/189 [==============================] - 0s 691us/step - loss: 0.0201 Epoch 2/10 189/189 [==============================] - 0s 576us/step - loss: 9.4059e-04 Epoch 3/10 189/189 [==============================] - 0s 613us/step - loss: 2.1746e-04 Epoch 4/10 189/189 [==============================] - 0s 552us/step - loss: 6.3659e-05 Epoch 5/10 189/189 [==============================] - 0s 557us/step - loss: 2.0531e-05 Epoch 6/10 189/189 [==============================] - 0s 580us/step - loss: 6.6410e-06 Epoch 7/10 189/189 [==============================] - 0s 546us/step - loss: 2.2468e-06 Epoch 8/10 189/189 [==============================] - 0s 589us/step - loss: 9.8824e-07 Epoch 9/10 189/189 [==============================] - 0s 564us/step - loss: 6.3123e-07 Epoch 10/10 189/189 [==============================] - 0s 543us/step - loss: 5.1111e-07 21/21 [==============================] - 0s 497us/step Epoch 1/10 189/189 [==============================] - 0s 649us/step - loss: 0.0038 Epoch 2/10 189/189 [==============================] - 0s 547us/step - loss: 4.5380e-05 Epoch 3/10 189/189 [==============================] - 0s 537us/step - loss: 6.3488e-06 Epoch 4/10 189/189 [==============================] - 0s 570us/step - loss: 1.8041e-06 Epoch 5/10 189/189 [==============================] - 0s 559us/step - loss: 1.0400e-06 Epoch 6/10 189/189 [==============================] - 0s 553us/step - loss: 8.2419e-07 Epoch 7/10 189/189 [==============================] - 0s 571us/step - loss: 7.4827e-07 Epoch 8/10 189/189 [==============================] - 0s 533us/step - loss: 6.7143e-07 Epoch 9/10 189/189 [==============================] - 0s 543us/step - loss: 6.1416e-07 Epoch 10/10 189/189 [==============================] - 0s 527us/step - loss: 5.6488e-07 21/21 [==============================] - 0s 481us/step Epoch 1/10 189/189 [==============================] - 0s 568us/step - loss: 0.0494 Epoch 2/10 189/189 [==============================] - 0s 533us/step - loss: 0.0034 Epoch 3/10 189/189 [==============================] - 0s 572us/step - loss: 8.0231e-04 Epoch 4/10 189/189 [==============================] - 0s 571us/step - loss: 2.7931e-04 Epoch 5/10 189/189 [==============================] - 0s 534us/step - loss: 1.1566e-04 Epoch 6/10 189/189 [==============================] - 0s 544us/step - loss: 4.8920e-05 Epoch 7/10 189/189 [==============================] - 0s 611us/step - loss: 2.0821e-05 Epoch 8/10 189/189 [==============================] - 0s 544us/step - loss: 8.8933e-06 Epoch 9/10 189/189 [==============================] - 0s 585us/step - loss: 3.2873e-06 Epoch 10/10 189/189 [==============================] - 0s 550us/step - loss: 1.3135e-06 21/21 [==============================] - 0s 481us/step Epoch 1/10 189/189 [==============================] - 0s 621us/step - loss: 4.7446e-05 Epoch 2/10 189/189 [==============================] - 0s 556us/step - loss: 4.7999e-07 Epoch 3/10 189/189 [==============================] - 0s 546us/step - loss: 4.6183e-07 Epoch 4/10 189/189 [==============================] - 0s 586us/step - loss: 4.5511e-07 Epoch 5/10 189/189 [==============================] - 0s 540us/step - loss: 4.5487e-07 Epoch 6/10 189/189 [==============================] - 0s 558us/step - loss: 4.5276e-07 Epoch 7/10 189/189 [==============================] - 0s 578us/step - loss: 4.4959e-07 Epoch 8/10 189/189 [==============================] - 0s 533us/step - loss: 4.4995e-07 Epoch 9/10 189/189 [==============================] - 0s 571us/step - loss: 4.4958e-07 Epoch 10/10 189/189 [==============================] - 0s 551us/step - loss: 4.5146e-07 21/21 [==============================] - 0s 471us/step Epoch 1/10 189/189 [==============================] - 0s 564us/step - loss: 0.0264 Epoch 2/10 189/189 [==============================] - 0s 525us/step - loss: 0.0015 Epoch 3/10 189/189 [==============================] - 0s 521us/step - loss: 3.5489e-04 Epoch 4/10 189/189 [==============================] - 0s 520us/step - loss: 1.3070e-04 Epoch 5/10 189/189 [==============================] - 0s 520us/step - loss: 5.7554e-05 Epoch 6/10 189/189 [==============================] - 0s 524us/step - loss: 2.8935e-05 Epoch 7/10 189/189 [==============================] - 0s 524us/step - loss: 1.5560e-05 Epoch 8/10 189/189 [==============================] - 0s 519us/step - loss: 8.6136e-06 Epoch 9/10 189/189 [==============================] - 0s 523us/step - loss: 5.1130e-06 Epoch 10/10 189/189 [==============================] - 0s 530us/step - loss: 3.0294e-06 21/21 [==============================] - 0s 483us/step
print("Mean r value is: %.2f. The standard deviation of the r values is %.2f" % (test1.mean(),test1.std()))
Mean r value is: 0.65. The standard deviation of the r values is 0.05
test2 = standardise_regressor(simple_model)
Epoch 1/10
/var/folders/sl/3pszjjd95ks506qykf9w8w7r0000gn/T/ipykernel_17164/2871449025.py:9: DeprecationWarning: KerasRegressor is deprecated, use Sci-Keras (https://github.com/adriangb/scikeras) instead. See https://www.adriangb.com/scikeras/stable/migration.html for help migrating. estimators.append(( 'mlp' , KerasRegressor(build_fn = model, epochs = N_epochs , batch_size = batchSize )))
189/189 [==============================] - 0s 570us/step - loss: 1.7797e-06 Epoch 2/10 189/189 [==============================] - 0s 521us/step - loss: 4.2986e-07 Epoch 3/10 189/189 [==============================] - 0s 543us/step - loss: 4.0598e-07 Epoch 4/10 189/189 [==============================] - 0s 556us/step - loss: 3.9993e-07 Epoch 5/10 189/189 [==============================] - 0s 582us/step - loss: 3.9388e-07 Epoch 6/10 189/189 [==============================] - 0s 579us/step - loss: 3.8969e-07 Epoch 7/10 189/189 [==============================] - 0s 527us/step - loss: 3.8727e-07 Epoch 8/10 189/189 [==============================] - 0s 520us/step - loss: 3.8505e-07 Epoch 9/10 189/189 [==============================] - 0s 538us/step - loss: 3.8368e-07 Epoch 10/10 189/189 [==============================] - 0s 539us/step - loss: 3.7945e-07 21/21 [==============================] - 0s 505us/step Epoch 1/10 189/189 [==============================] - 0s 563us/step - loss: 8.0514e-06 Epoch 2/10 189/189 [==============================] - 0s 544us/step - loss: 7.0952e-07 Epoch 3/10 189/189 [==============================] - 0s 772us/step - loss: 6.0724e-07 Epoch 4/10 189/189 [==============================] - 0s 845us/step - loss: 5.2874e-07 Epoch 5/10 189/189 [==============================] - 0s 629us/step - loss: 4.6829e-07 Epoch 6/10 189/189 [==============================] - 0s 673us/step - loss: 4.0534e-07 Epoch 7/10 189/189 [==============================] - 0s 564us/step - loss: 3.9796e-07 Epoch 8/10 189/189 [==============================] - 0s 582us/step - loss: 3.9401e-07 Epoch 9/10 189/189 [==============================] - 0s 578us/step - loss: 3.9027e-07 Epoch 10/10 189/189 [==============================] - 0s 560us/step - loss: 3.9121e-07 21/21 [==============================] - 0s 495us/step Epoch 1/10 189/189 [==============================] - 0s 560us/step - loss: 1.5386e-06 Epoch 2/10 189/189 [==============================] - 0s 532us/step - loss: 4.2750e-07 Epoch 3/10 189/189 [==============================] - 0s 525us/step - loss: 4.0252e-07 Epoch 4/10 189/189 [==============================] - 0s 535us/step - loss: 3.8407e-07 Epoch 5/10 189/189 [==============================] - 0s 521us/step - loss: 3.7960e-07 Epoch 6/10 189/189 [==============================] - 0s 522us/step - loss: 3.7509e-07 Epoch 7/10 189/189 [==============================] - 0s 514us/step - loss: 3.7080e-07 Epoch 8/10 189/189 [==============================] - 0s 531us/step - loss: 3.6525e-07 Epoch 9/10 189/189 [==============================] - 0s 526us/step - loss: 3.6691e-07 Epoch 10/10 189/189 [==============================] - 0s 532us/step - loss: 3.6892e-07 21/21 [==============================] - 0s 473us/step Epoch 1/10 189/189 [==============================] - 0s 560us/step - loss: 1.7772e-06 Epoch 2/10 189/189 [==============================] - 0s 534us/step - loss: 5.2243e-07 Epoch 3/10 189/189 [==============================] - 0s 530us/step - loss: 4.8874e-07 Epoch 4/10 189/189 [==============================] - 0s 531us/step - loss: 4.4561e-07 Epoch 5/10 189/189 [==============================] - 0s 531us/step - loss: 3.9370e-07 Epoch 6/10 189/189 [==============================] - 0s 544us/step - loss: 3.8403e-07 Epoch 7/10 189/189 [==============================] - 0s 547us/step - loss: 3.8157e-07 Epoch 8/10 189/189 [==============================] - 0s 525us/step - loss: 3.7608e-07 Epoch 9/10 189/189 [==============================] - 0s 524us/step - loss: 3.7824e-07 Epoch 10/10 189/189 [==============================] - 0s 520us/step - loss: 3.7333e-07 21/21 [==============================] - 0s 449us/step Epoch 1/10 189/189 [==============================] - 0s 550us/step - loss: 3.8881e-06 Epoch 2/10 189/189 [==============================] - 0s 549us/step - loss: 5.3566e-07 Epoch 3/10 189/189 [==============================] - 0s 567us/step - loss: 4.4720e-07 Epoch 4/10 189/189 [==============================] - 0s 567us/step - loss: 4.0734e-07 Epoch 5/10 189/189 [==============================] - 0s 545us/step - loss: 3.9724e-07 Epoch 6/10 189/189 [==============================] - 0s 554us/step - loss: 3.8975e-07 Epoch 7/10 189/189 [==============================] - 0s 543us/step - loss: 3.9358e-07 Epoch 8/10 189/189 [==============================] - 0s 547us/step - loss: 3.8486e-07 Epoch 9/10 189/189 [==============================] - 0s 576us/step - loss: 3.8171e-07 Epoch 10/10 189/189 [==============================] - 0s 528us/step - loss: 3.8103e-07 21/21 [==============================] - 0s 462us/step Epoch 1/10 189/189 [==============================] - 0s 563us/step - loss: 2.1942e-05 Epoch 2/10 189/189 [==============================] - 0s 538us/step - loss: 1.1359e-06 Epoch 3/10 189/189 [==============================] - 0s 538us/step - loss: 6.6683e-07 Epoch 4/10 189/189 [==============================] - 0s 524us/step - loss: 5.7575e-07 Epoch 5/10 189/189 [==============================] - 0s 529us/step - loss: 5.3313e-07 Epoch 6/10 189/189 [==============================] - 0s 527us/step - loss: 5.0610e-07 Epoch 7/10 189/189 [==============================] - 0s 537us/step - loss: 4.8898e-07 Epoch 8/10 189/189 [==============================] - 0s 529us/step - loss: 4.7641e-07 Epoch 9/10 189/189 [==============================] - 0s 527us/step - loss: 4.5363e-07 Epoch 10/10 189/189 [==============================] - 0s 528us/step - loss: 4.3033e-07 21/21 [==============================] - 0s 457us/step Epoch 1/10 189/189 [==============================] - 0s 589us/step - loss: 1.2106e-05 Epoch 2/10 189/189 [==============================] - 0s 570us/step - loss: 9.4986e-07 Epoch 3/10 189/189 [==============================] - 0s 595us/step - loss: 5.9808e-07 Epoch 4/10 189/189 [==============================] - 0s 559us/step - loss: 5.0396e-07 Epoch 5/10 189/189 [==============================] - 0s 533us/step - loss: 4.6603e-07 Epoch 6/10 189/189 [==============================] - 0s 524us/step - loss: 4.5005e-07 Epoch 7/10 189/189 [==============================] - 0s 524us/step - loss: 4.4731e-07 Epoch 8/10 189/189 [==============================] - 0s 544us/step - loss: 4.4332e-07 Epoch 9/10 189/189 [==============================] - 0s 536us/step - loss: 4.3930e-07 Epoch 10/10 189/189 [==============================] - 0s 528us/step - loss: 4.3807e-07 21/21 [==============================] - 0s 475us/step Epoch 1/10 189/189 [==============================] - 0s 562us/step - loss: 3.6141e-05 Epoch 2/10 189/189 [==============================] - 0s 532us/step - loss: 1.7531e-06 Epoch 3/10 189/189 [==============================] - 0s 531us/step - loss: 1.0137e-06 Epoch 4/10 189/189 [==============================] - 0s 536us/step - loss: 8.6699e-07 Epoch 5/10 189/189 [==============================] - 0s 536us/step - loss: 8.1833e-07 Epoch 6/10 189/189 [==============================] - 0s 536us/step - loss: 7.8999e-07 Epoch 7/10 189/189 [==============================] - 0s 531us/step - loss: 7.6125e-07 Epoch 8/10 189/189 [==============================] - 0s 530us/step - loss: 7.4355e-07 Epoch 9/10 189/189 [==============================] - 0s 529us/step - loss: 7.4157e-07 Epoch 10/10 189/189 [==============================] - 0s 530us/step - loss: 7.3532e-07 21/21 [==============================] - 0s 464us/step Epoch 1/10 189/189 [==============================] - 0s 564us/step - loss: 2.7515e-06 Epoch 2/10 189/189 [==============================] - 0s 539us/step - loss: 5.1768e-07 Epoch 3/10 189/189 [==============================] - 0s 533us/step - loss: 4.8900e-07 Epoch 4/10 189/189 [==============================] - 0s 538us/step - loss: 4.6975e-07 Epoch 5/10 189/189 [==============================] - 0s 533us/step - loss: 4.4367e-07 Epoch 6/10 189/189 [==============================] - 0s 546us/step - loss: 4.2834e-07 Epoch 7/10 189/189 [==============================] - 0s 532us/step - loss: 4.2645e-07 Epoch 8/10 189/189 [==============================] - 0s 531us/step - loss: 4.1385e-07 Epoch 9/10 189/189 [==============================] - 0s 543us/step - loss: 3.9347e-07 Epoch 10/10 189/189 [==============================] - 0s 530us/step - loss: 3.8417e-07 21/21 [==============================] - 0s 469us/step Epoch 1/10 189/189 [==============================] - 0s 556us/step - loss: 1.0788e-05 Epoch 2/10 189/189 [==============================] - 0s 513us/step - loss: 6.5675e-07 Epoch 3/10 189/189 [==============================] - 0s 513us/step - loss: 5.0425e-07 Epoch 4/10 189/189 [==============================] - 0s 514us/step - loss: 4.7431e-07 Epoch 5/10 189/189 [==============================] - 0s 511us/step - loss: 4.6656e-07 Epoch 6/10 189/189 [==============================] - 0s 511us/step - loss: 4.5327e-07 Epoch 7/10 189/189 [==============================] - 0s 511us/step - loss: 4.1860e-07 Epoch 8/10 189/189 [==============================] - 0s 511us/step - loss: 3.9718e-07 Epoch 9/10 189/189 [==============================] - 0s 513us/step - loss: 3.9090e-07 Epoch 10/10 189/189 [==============================] - 0s 510us/step - loss: 3.8916e-07 21/21 [==============================] - 0s 436us/step
print("Mean r value is: %.2f. The standard deviation of the r values is %.2f" % (test2.mean(),test2.std()))
Mean r value is: 0.69. The standard deviation of the r values is 0.08
The new estimator with standardised inputs performs better than the estimated that uses the raw input data. The r2 scoring value represents the proportion of variance in the dependent variable that can be explained by the independent variables in the model. The closer the value of r2 to 1, the more the model perfectly explains the variation in the dependent variable. Since I obtained an r2 value of 0.70 with the standardise input, compared to the r2 value of 0.5 withh the raw input, the remaining analysis will be done with standardise input.
test3 = standardise_regressor(dense_model)
Epoch 1/10
/var/folders/sl/3pszjjd95ks506qykf9w8w7r0000gn/T/ipykernel_17164/2871449025.py:9: DeprecationWarning: KerasRegressor is deprecated, use Sci-Keras (https://github.com/adriangb/scikeras) instead. See https://www.adriangb.com/scikeras/stable/migration.html for help migrating. estimators.append(( 'mlp' , KerasRegressor(build_fn = model, epochs = N_epochs , batch_size = batchSize )))
189/189 [==============================] - 0s 618us/step - loss: 1.5905e-06 Epoch 2/10 189/189 [==============================] - 0s 582us/step - loss: 8.2516e-07 Epoch 3/10 189/189 [==============================] - 0s 584us/step - loss: 7.2740e-07 Epoch 4/10 189/189 [==============================] - 0s 588us/step - loss: 7.0139e-07 Epoch 5/10 189/189 [==============================] - 0s 580us/step - loss: 6.8295e-07 Epoch 6/10 189/189 [==============================] - 0s 585us/step - loss: 6.7183e-07 Epoch 7/10 189/189 [==============================] - 0s 591us/step - loss: 6.6374e-07 Epoch 8/10 189/189 [==============================] - 0s 582us/step - loss: 6.5994e-07 Epoch 9/10 189/189 [==============================] - 0s 578us/step - loss: 6.5832e-07 Epoch 10/10 189/189 [==============================] - 0s 578us/step - loss: 6.5813e-07 21/21 [==============================] - 0s 478us/step Epoch 1/10 189/189 [==============================] - 0s 619us/step - loss: 1.1665e-06 Epoch 2/10 189/189 [==============================] - 0s 584us/step - loss: 6.3280e-07 Epoch 3/10 189/189 [==============================] - 0s 589us/step - loss: 6.0862e-07 Epoch 4/10 189/189 [==============================] - 0s 596us/step - loss: 6.0543e-07 Epoch 5/10 189/189 [==============================] - 0s 597us/step - loss: 5.9544e-07 Epoch 6/10 189/189 [==============================] - 0s 581us/step - loss: 5.8811e-07 Epoch 7/10 189/189 [==============================] - 0s 584us/step - loss: 5.2771e-07 Epoch 8/10 189/189 [==============================] - 0s 602us/step - loss: 5.1921e-07 Epoch 9/10 189/189 [==============================] - 0s 588us/step - loss: 5.1410e-07 Epoch 10/10 189/189 [==============================] - 0s 589us/step - loss: 5.2493e-07 21/21 [==============================] - 0s 492us/step Epoch 1/10 189/189 [==============================] - 0s 621us/step - loss: 1.5050e-06 Epoch 2/10 189/189 [==============================] - 0s 609us/step - loss: 1.0856e-06 Epoch 3/10 189/189 [==============================] - 0s 596us/step - loss: 1.0862e-06 Epoch 4/10 189/189 [==============================] - 0s 593us/step - loss: 1.0872e-06 Epoch 5/10 189/189 [==============================] - 0s 592us/step - loss: 1.0869e-06 Epoch 6/10 189/189 [==============================] - 0s 595us/step - loss: 1.0877e-06 Epoch 7/10 189/189 [==============================] - 0s 599us/step - loss: 1.0879e-06 Epoch 8/10 189/189 [==============================] - 0s 609us/step - loss: 1.0884e-06 Epoch 9/10 189/189 [==============================] - 0s 598us/step - loss: 1.0887e-06 Epoch 10/10 189/189 [==============================] - 0s 593us/step - loss: 1.0915e-06 21/21 [==============================] - 0s 475us/step Epoch 1/10 189/189 [==============================] - 0s 614us/step - loss: 1.2900e-06 Epoch 2/10 189/189 [==============================] - 0s 591us/step - loss: 5.4475e-07 Epoch 3/10 189/189 [==============================] - 0s 590us/step - loss: 4.9936e-07 Epoch 4/10 189/189 [==============================] - 0s 588us/step - loss: 4.8467e-07 Epoch 5/10 189/189 [==============================] - 0s 594us/step - loss: 4.7590e-07 Epoch 6/10 189/189 [==============================] - 0s 586us/step - loss: 4.7767e-07 Epoch 7/10 189/189 [==============================] - 0s 592us/step - loss: 4.7982e-07 Epoch 8/10 189/189 [==============================] - 0s 592us/step - loss: 4.7792e-07 Epoch 9/10 189/189 [==============================] - 0s 592us/step - loss: 4.7025e-07 Epoch 10/10 189/189 [==============================] - 0s 591us/step - loss: 4.7125e-07 21/21 [==============================] - 0s 474us/step Epoch 1/10 189/189 [==============================] - 0s 617us/step - loss: 1.1381e-06 Epoch 2/10 189/189 [==============================] - 0s 595us/step - loss: 5.1127e-07 Epoch 3/10 189/189 [==============================] - 0s 598us/step - loss: 4.6984e-07 Epoch 4/10 189/189 [==============================] - 0s 598us/step - loss: 4.4616e-07 Epoch 5/10 189/189 [==============================] - 0s 596us/step - loss: 4.3109e-07 Epoch 6/10 189/189 [==============================] - 0s 599us/step - loss: 4.1700e-07 Epoch 7/10 189/189 [==============================] - 0s 595us/step - loss: 4.1456e-07 Epoch 8/10 189/189 [==============================] - 0s 646us/step - loss: 4.1693e-07 Epoch 9/10 189/189 [==============================] - 0s 611us/step - loss: 4.1702e-07 Epoch 10/10 189/189 [==============================] - 0s 596us/step - loss: 4.1364e-07 21/21 [==============================] - 0s 518us/step Epoch 1/10 189/189 [==============================] - 0s 625us/step - loss: 1.1534e-06 Epoch 2/10 189/189 [==============================] - 0s 612us/step - loss: 5.6772e-07 Epoch 3/10 189/189 [==============================] - 0s 602us/step - loss: 4.9327e-07 Epoch 4/10 189/189 [==============================] - 0s 602us/step - loss: 4.7560e-07 Epoch 5/10 189/189 [==============================] - 0s 606us/step - loss: 4.7260e-07 Epoch 6/10 189/189 [==============================] - 0s 607us/step - loss: 4.6793e-07 Epoch 7/10 189/189 [==============================] - 0s 610us/step - loss: 4.6815e-07 Epoch 8/10 189/189 [==============================] - 0s 605us/step - loss: 4.6684e-07 Epoch 9/10 189/189 [==============================] - 0s 610us/step - loss: 4.7079e-07 Epoch 10/10 189/189 [==============================] - 0s 610us/step - loss: 4.6958e-07 21/21 [==============================] - 0s 514us/step Epoch 1/10 189/189 [==============================] - 0s 631us/step - loss: 1.2128e-06 Epoch 2/10 189/189 [==============================] - 0s 640us/step - loss: 5.5499e-07 Epoch 3/10 189/189 [==============================] - 0s 620us/step - loss: 4.7809e-07 Epoch 4/10 189/189 [==============================] - 0s 622us/step - loss: 4.6135e-07 Epoch 5/10 189/189 [==============================] - 0s 619us/step - loss: 4.4352e-07 Epoch 6/10 189/189 [==============================] - 0s 619us/step - loss: 4.4312e-07 Epoch 7/10 189/189 [==============================] - 0s 616us/step - loss: 4.3700e-07 Epoch 8/10 189/189 [==============================] - 0s 622us/step - loss: 4.3709e-07 Epoch 9/10 189/189 [==============================] - 0s 644us/step - loss: 4.3874e-07 Epoch 10/10 189/189 [==============================] - 0s 616us/step - loss: 4.3609e-07 21/21 [==============================] - 0s 519us/step Epoch 1/10 189/189 [==============================] - 0s 704us/step - loss: 1.3477e-06 Epoch 2/10 189/189 [==============================] - 0s 648us/step - loss: 6.1293e-07 Epoch 3/10 189/189 [==============================] - 0s 631us/step - loss: 5.9887e-07 Epoch 4/10 189/189 [==============================] - 0s 656us/step - loss: 5.9523e-07 Epoch 5/10 189/189 [==============================] - 0s 659us/step - loss: 5.9290e-07 Epoch 6/10 189/189 [==============================] - 0s 662us/step - loss: 5.8125e-07 Epoch 7/10 189/189 [==============================] - 0s 660us/step - loss: 5.8138e-07 Epoch 8/10 189/189 [==============================] - 0s 676us/step - loss: 5.7948e-07 Epoch 9/10 189/189 [==============================] - 0s 647us/step - loss: 5.7390e-07 Epoch 10/10 189/189 [==============================] - 0s 617us/step - loss: 5.7280e-07 21/21 [==============================] - 0s 497us/step Epoch 1/10 189/189 [==============================] - 0s 637us/step - loss: 1.0460e-06 Epoch 2/10 189/189 [==============================] - 0s 623us/step - loss: 5.3870e-07 Epoch 3/10 189/189 [==============================] - 0s 621us/step - loss: 4.5504e-07 Epoch 4/10 189/189 [==============================] - 0s 624us/step - loss: 4.3085e-07 Epoch 5/10 189/189 [==============================] - 0s 621us/step - loss: 4.2382e-07 Epoch 6/10 189/189 [==============================] - 0s 620us/step - loss: 4.1807e-07 Epoch 7/10 189/189 [==============================] - 0s 616us/step - loss: 4.1958e-07 Epoch 8/10 189/189 [==============================] - 0s 619us/step - loss: 4.0975e-07 Epoch 9/10 189/189 [==============================] - 0s 624us/step - loss: 4.0573e-07 Epoch 10/10 189/189 [==============================] - 0s 613us/step - loss: 4.1042e-07 21/21 [==============================] - 0s 503us/step Epoch 1/10 189/189 [==============================] - 0s 622us/step - loss: 1.5354e-06 Epoch 2/10 189/189 [==============================] - 0s 580us/step - loss: 6.3569e-07 Epoch 3/10 189/189 [==============================] - 0s 580us/step - loss: 5.9360e-07 Epoch 4/10 189/189 [==============================] - 0s 579us/step - loss: 5.5011e-07 Epoch 5/10 189/189 [==============================] - 0s 578us/step - loss: 5.2509e-07 Epoch 6/10 189/189 [==============================] - 0s 576us/step - loss: 5.1623e-07 Epoch 7/10 189/189 [==============================] - 0s 579us/step - loss: 5.1393e-07 Epoch 8/10 189/189 [==============================] - 0s 574us/step - loss: 5.1604e-07 Epoch 9/10 189/189 [==============================] - 0s 577us/step - loss: 5.0737e-07 Epoch 10/10 189/189 [==============================] - 0s 576us/step - loss: 4.9886e-07 21/21 [==============================] - 0s 479us/step
print("Mean r value is: %.2f. The standard deviation of the r values is %.2f" % (test3.mean(),test3.std()))
Mean r value is: 0.59. The standard deviation of the r values is 0.21
test4 = standardise_regressor(wider_model)
Epoch 1/10
/var/folders/sl/3pszjjd95ks506qykf9w8w7r0000gn/T/ipykernel_17164/2871449025.py:9: DeprecationWarning: KerasRegressor is deprecated, use Sci-Keras (https://github.com/adriangb/scikeras) instead. See https://www.adriangb.com/scikeras/stable/migration.html for help migrating. estimators.append(( 'mlp' , KerasRegressor(build_fn = model, epochs = N_epochs , batch_size = batchSize )))
189/189 [==============================] - 0s 604us/step - loss: 1.3038e-05 Epoch 2/10 189/189 [==============================] - 0s 555us/step - loss: 5.9017e-07 Epoch 3/10 189/189 [==============================] - 0s 553us/step - loss: 4.4188e-07 Epoch 4/10 189/189 [==============================] - 0s 551us/step - loss: 3.9993e-07 Epoch 5/10 189/189 [==============================] - 0s 550us/step - loss: 3.8929e-07 Epoch 6/10 189/189 [==============================] - 0s 552us/step - loss: 3.7725e-07 Epoch 7/10 189/189 [==============================] - 0s 551us/step - loss: 3.6764e-07 Epoch 8/10 189/189 [==============================] - 0s 553us/step - loss: 3.5929e-07 Epoch 9/10 189/189 [==============================] - 0s 549us/step - loss: 3.5673e-07 Epoch 10/10 189/189 [==============================] - 0s 555us/step - loss: 3.5916e-07 21/21 [==============================] - 0s 457us/step Epoch 1/10 189/189 [==============================] - 0s 581us/step - loss: 1.7160e-05 Epoch 2/10 189/189 [==============================] - 0s 560us/step - loss: 7.8178e-07 Epoch 3/10 189/189 [==============================] - 0s 553us/step - loss: 4.8861e-07 Epoch 4/10 189/189 [==============================] - 0s 558us/step - loss: 4.4063e-07 Epoch 5/10 189/189 [==============================] - 0s 552us/step - loss: 4.1169e-07 Epoch 6/10 189/189 [==============================] - 0s 551us/step - loss: 3.9104e-07 Epoch 7/10 189/189 [==============================] - 0s 555us/step - loss: 3.7704e-07 Epoch 8/10 189/189 [==============================] - 0s 557us/step - loss: 3.6682e-07 Epoch 9/10 189/189 [==============================] - 0s 565us/step - loss: 3.6479e-07 Epoch 10/10 189/189 [==============================] - 0s 557us/step - loss: 3.6283e-07 21/21 [==============================] - 0s 457us/step Epoch 1/10 189/189 [==============================] - 0s 579us/step - loss: 8.2849e-06 Epoch 2/10 189/189 [==============================] - 0s 555us/step - loss: 5.2517e-07 Epoch 3/10 189/189 [==============================] - 0s 560us/step - loss: 4.6654e-07 Epoch 4/10 189/189 [==============================] - 0s 561us/step - loss: 4.3978e-07 Epoch 5/10 189/189 [==============================] - 0s 586us/step - loss: 4.0965e-07 Epoch 6/10 189/189 [==============================] - 0s 607us/step - loss: 3.8568e-07 Epoch 7/10 189/189 [==============================] - 0s 569us/step - loss: 3.7608e-07 Epoch 8/10 189/189 [==============================] - 0s 565us/step - loss: 3.6962e-07 Epoch 9/10 189/189 [==============================] - 0s 570us/step - loss: 3.6406e-07 Epoch 10/10 189/189 [==============================] - 0s 562us/step - loss: 3.6110e-07 21/21 [==============================] - 0s 452us/step Epoch 1/10 189/189 [==============================] - 0s 581us/step - loss: 2.0559e-05 Epoch 2/10 189/189 [==============================] - 0s 562us/step - loss: 7.7641e-07 Epoch 3/10 189/189 [==============================] - 0s 661us/step - loss: 5.5687e-07 Epoch 4/10 189/189 [==============================] - 0s 613us/step - loss: 4.9298e-07 Epoch 5/10 189/189 [==============================] - 0s 561us/step - loss: 4.5304e-07 Epoch 6/10 189/189 [==============================] - 0s 559us/step - loss: 4.3086e-07 Epoch 7/10 189/189 [==============================] - 0s 562us/step - loss: 4.1482e-07 Epoch 8/10 189/189 [==============================] - 0s 563us/step - loss: 4.0271e-07 Epoch 9/10 189/189 [==============================] - 0s 563us/step - loss: 3.9621e-07 Epoch 10/10 189/189 [==============================] - 0s 561us/step - loss: 3.9252e-07 21/21 [==============================] - 0s 452us/step Epoch 1/10 189/189 [==============================] - 0s 582us/step - loss: 1.6586e-05 Epoch 2/10 189/189 [==============================] - 0s 569us/step - loss: 7.4264e-07 Epoch 3/10 189/189 [==============================] - 0s 573us/step - loss: 5.2417e-07 Epoch 4/10 189/189 [==============================] - 0s 562us/step - loss: 4.5928e-07 Epoch 5/10 189/189 [==============================] - 0s 573us/step - loss: 4.2771e-07 Epoch 6/10 189/189 [==============================] - 0s 564us/step - loss: 4.1860e-07 Epoch 7/10 189/189 [==============================] - 0s 560us/step - loss: 4.0369e-07 Epoch 8/10 189/189 [==============================] - 0s 577us/step - loss: 3.9505e-07 Epoch 9/10 189/189 [==============================] - 0s 568us/step - loss: 3.8891e-07 Epoch 10/10 189/189 [==============================] - 0s 562us/step - loss: 3.7950e-07 21/21 [==============================] - 0s 477us/step Epoch 1/10 189/189 [==============================] - 0s 586us/step - loss: 7.8825e-06 Epoch 2/10 189/189 [==============================] - 0s 568us/step - loss: 6.0219e-07 Epoch 3/10 189/189 [==============================] - 0s 568us/step - loss: 4.5379e-07 Epoch 4/10 189/189 [==============================] - 0s 566us/step - loss: 4.1933e-07 Epoch 5/10 189/189 [==============================] - 0s 566us/step - loss: 4.0350e-07 Epoch 6/10 189/189 [==============================] - 0s 568us/step - loss: 3.9224e-07 Epoch 7/10 189/189 [==============================] - 0s 576us/step - loss: 3.8501e-07 Epoch 8/10 189/189 [==============================] - 0s 576us/step - loss: 3.7377e-07 Epoch 9/10 189/189 [==============================] - 0s 571us/step - loss: 3.6443e-07 Epoch 10/10 189/189 [==============================] - 0s 567us/step - loss: 3.6079e-07 21/21 [==============================] - 0s 498us/step Epoch 1/10 189/189 [==============================] - 0s 586us/step - loss: 2.2183e-05 Epoch 2/10 189/189 [==============================] - 0s 570us/step - loss: 1.1624e-06 Epoch 3/10 189/189 [==============================] - 0s 571us/step - loss: 6.1105e-07 Epoch 4/10 189/189 [==============================] - 0s 572us/step - loss: 5.1063e-07 Epoch 5/10 189/189 [==============================] - 0s 571us/step - loss: 4.6184e-07 Epoch 6/10 189/189 [==============================] - 0s 569us/step - loss: 4.3234e-07 Epoch 7/10 189/189 [==============================] - 0s 568us/step - loss: 4.1904e-07 Epoch 8/10 189/189 [==============================] - 0s 577us/step - loss: 4.0806e-07 Epoch 9/10 189/189 [==============================] - 0s 573us/step - loss: 4.0000e-07 Epoch 10/10 189/189 [==============================] - 0s 571us/step - loss: 3.9606e-07 21/21 [==============================] - 0s 480us/step Epoch 1/10 189/189 [==============================] - 0s 623us/step - loss: 2.6792e-05 Epoch 2/10 189/189 [==============================] - 0s 577us/step - loss: 1.5088e-06 Epoch 3/10 189/189 [==============================] - 0s 578us/step - loss: 6.2448e-07 Epoch 4/10 189/189 [==============================] - 0s 574us/step - loss: 4.6621e-07 Epoch 5/10 189/189 [==============================] - 0s 577us/step - loss: 4.1189e-07 Epoch 6/10 189/189 [==============================] - 0s 577us/step - loss: 3.8933e-07 Epoch 7/10 189/189 [==============================] - 0s 570us/step - loss: 3.7493e-07 Epoch 8/10 189/189 [==============================] - 0s 577us/step - loss: 3.6623e-07 Epoch 9/10 189/189 [==============================] - 0s 609us/step - loss: 3.6027e-07 Epoch 10/10 189/189 [==============================] - 0s 749us/step - loss: 3.5677e-07 21/21 [==============================] - 0s 488us/step Epoch 1/10 189/189 [==============================] - 0s 598us/step - loss: 1.2293e-05 Epoch 2/10 189/189 [==============================] - 0s 577us/step - loss: 6.2655e-07 Epoch 3/10 189/189 [==============================] - 0s 575us/step - loss: 4.9977e-07 Epoch 4/10 189/189 [==============================] - 0s 598us/step - loss: 4.6520e-07 Epoch 5/10 189/189 [==============================] - 0s 587us/step - loss: 4.4597e-07 Epoch 6/10 189/189 [==============================] - 0s 576us/step - loss: 4.3337e-07 Epoch 7/10 189/189 [==============================] - 0s 574us/step - loss: 4.1869e-07 Epoch 8/10 189/189 [==============================] - 0s 576us/step - loss: 4.0966e-07 Epoch 9/10 189/189 [==============================] - 0s 816us/step - loss: 4.0513e-07 Epoch 10/10 189/189 [==============================] - 0s 673us/step - loss: 3.9968e-07 21/21 [==============================] - 0s 527us/step Epoch 1/10 189/189 [==============================] - 0s 604us/step - loss: 1.9787e-05 Epoch 2/10 189/189 [==============================] - 0s 618us/step - loss: 9.3843e-07 Epoch 3/10 189/189 [==============================] - 0s 565us/step - loss: 5.5136e-07 Epoch 4/10 189/189 [==============================] - 0s 549us/step - loss: 4.7153e-07 Epoch 5/10 189/189 [==============================] - 0s 553us/step - loss: 4.2753e-07 Epoch 6/10 189/189 [==============================] - 0s 547us/step - loss: 4.0160e-07 Epoch 7/10 189/189 [==============================] - 0s 548us/step - loss: 3.8475e-07 Epoch 8/10 189/189 [==============================] - 0s 610us/step - loss: 3.7246e-07 Epoch 9/10 189/189 [==============================] - 0s 573us/step - loss: 3.6965e-07 Epoch 10/10 189/189 [==============================] - 0s 547us/step - loss: 3.6368e-07 21/21 [==============================] - 0s 459us/step
print("Mean r value is: %.2f. The standard deviation of the r values is %.2f" % (test4.mean(),test4.std()))
Mean r value is: 0.72. The standard deviation of the r values is 0.02
Model | r2 value |
---|---|
Simple model with raw input | 0.50 |
Simple model with standardise input | 0.70 |
Dense model with standardise input | 0.67 |
Wider model with standardise input | 0.72 |
The best model so far is the single-layer model with twice the number of nodes in the hidden compsred compared to the input layer
def creative_model():
# create model
model = Sequential ()
# no activation required for the output , as this is a regression problem ,
# ie . we need a numerical prediction for any input
model.add( Dense (num_nodes*40 , input_dim = num_inputs , kernel_initializer='normal', activation ='relu' ))
model.add( Dropout (0.2))
model.add( Dense (num_nodes*20 , input_dim = num_inputs , kernel_initializer='normal', activation ='relu' ))
model.add( Dropout (0.2))
model.add( Dense ( num_outputs , kernel_initializer='normal'))
# Compile model
model.compile( loss ='mean_squared_error',optimizer= 'adam')
return model
def creative_regressor(model):
# must always set the random seed for reproducibility
N_epochs = 60
batchSize = 1000
Answer_to_all_questions = 42
np.random.seed(Answer_to_all_questions)
estimators = []
estimators.append(( 'standardize',StandardScaler()))
estimators.append(( 'mlp' , KerasRegressor(build_fn = model, epochs = N_epochs , batch_size = batchSize )))
pipeline = Pipeline(estimators)
kfold = KFold(n_splits =10 , random_state = Answer_to_all_questions , shuffle = True )
# data and target are 5 - column and 1 - column arrays produced with pandas . DataFrame . values
results = cross_val_score( pipeline , data , target , cv = kfold , scoring = 'r2')
predicted = cross_val_predict(pipeline, data, target, cv=kfold)
return results, predicted
results, predicted = creative_regressor(creative_model)
Epoch 1/60
/var/folders/sl/3pszjjd95ks506qykf9w8w7r0000gn/T/ipykernel_17164/365823391.py:9: DeprecationWarning: KerasRegressor is deprecated, use Sci-Keras (https://github.com/adriangb/scikeras) instead. See https://www.adriangb.com/scikeras/stable/migration.html for help migrating. estimators.append(( 'mlp' , KerasRegressor(build_fn = model, epochs = N_epochs , batch_size = batchSize )))
189/189 [==============================] - 1s 3ms/step - loss: 1.0780e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 5.3119e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.1758e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 3.7937e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6190e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4891e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4110e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3331e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3402e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2616e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2007e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1862e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0830e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0612e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0284e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0057e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9431e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9151e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9051e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8662e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8258e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7786e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7676e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7274e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6770e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6531e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6610e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5772e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6331e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6193e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5653e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5417e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5290e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5071e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4570e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5019e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4420e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4509e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4122e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4133e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3934e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3753e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3962e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3216e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3316e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3436e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3344e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3297e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2441e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2604e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2728e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2629e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2261e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2246e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2222e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2411e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2170e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1987e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2174e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2087e-07 21/21 [==============================] - 0s 1ms/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5071e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 8.8891e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 5.3424e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 4.4488e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 4.0178e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.7718e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6296e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4771e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3971e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3271e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2839e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2404e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2031e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1481e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1202e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0764e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0462e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0103e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9947e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9776e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9404e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9288e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8919e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8915e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8050e-07 Epoch 26/60 189/189 [==============================] - 1s 4ms/step - loss: 2.7912e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8273e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7278e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7099e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7131e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6685e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6548e-07 Epoch 33/60 189/189 [==============================] - 1s 4ms/step - loss: 2.6214e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5738e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5795e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5706e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5717e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5479e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5071e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4776e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4702e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4615e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4283e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4383e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3864e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3911e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4032e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3826e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3463e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3966e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3184e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3399e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3168e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2780e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3189e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3100e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2730e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2773e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2738e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2528e-07 21/21 [==============================] - 0s 1ms/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 1.9496e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 7.5859e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 5.0541e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 4.2914e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.8835e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6934e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5678e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4867e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3908e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3396e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2999e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2369e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2106e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1743e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1326e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0928e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0385e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0285e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0071e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0041e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9351e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9143e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9183e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8568e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8364e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7921e-07 Epoch 27/60 189/189 [==============================] - 1s 4ms/step - loss: 2.7484e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7113e-07 Epoch 29/60 189/189 [==============================] - 1s 4ms/step - loss: 2.7042e-07 Epoch 30/60 189/189 [==============================] - 1s 5ms/step - loss: 2.6801e-07 Epoch 31/60 189/189 [==============================] - 1s 5ms/step - loss: 2.6353e-07 Epoch 32/60 189/189 [==============================] - 1s 5ms/step - loss: 2.6239e-07 Epoch 33/60 189/189 [==============================] - 1s 4ms/step - loss: 2.6245e-07 Epoch 34/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5506e-07 Epoch 35/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5790e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5274e-07 Epoch 37/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5608e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5129e-07 Epoch 39/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5421e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4904e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4793e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4567e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4215e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4082e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3972e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3906e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3951e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3824e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3404e-07 Epoch 50/60 189/189 [==============================] - 1s 4ms/step - loss: 2.3727e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3352e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3076e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3135e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3388e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2883e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2755e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2927e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2618e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2762e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2574e-07 21/21 [==============================] - 0s 934us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 1.0309e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 4.7928e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 3.9009e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6247e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4269e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3841e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3086e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2208e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1797e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1311e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1169e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1300e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0456e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0005e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9893e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9441e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9247e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8715e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8359e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8167e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8288e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7393e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7076e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6857e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6814e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6185e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6718e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5975e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5639e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5212e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4967e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4863e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4383e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4237e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4289e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3911e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3751e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3971e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3355e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3727e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3575e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3467e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2972e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2861e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2939e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2730e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2413e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2493e-07 Epoch 49/60 189/189 [==============================] - 1s 4ms/step - loss: 2.2371e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2464e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2197e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2573e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2291e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1808e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1550e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2005e-07 Epoch 57/60 189/189 [==============================] - 1s 4ms/step - loss: 2.1531e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1751e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1772e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1425e-07 21/21 [==============================] - 0s 1ms/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 3.9278e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 1.2448e-06 Epoch 3/60 189/189 [==============================] - 1s 4ms/step - loss: 6.5664e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 5.0346e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 4.3804e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 4.0180e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.8148e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6628e-07 Epoch 9/60 189/189 [==============================] - 1s 4ms/step - loss: 3.5580e-07 Epoch 10/60 189/189 [==============================] - 1s 4ms/step - loss: 3.4748e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3878e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2951e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2850e-07 Epoch 14/60 189/189 [==============================] - 1s 4ms/step - loss: 3.2212e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1937e-07 Epoch 16/60 189/189 [==============================] - 1s 4ms/step - loss: 3.1494e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1515e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1064e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0685e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0288e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0209e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9989e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9525e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9440e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8795e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8488e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8400e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8414e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8002e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8082e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7726e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7509e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7414e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7087e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6678e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7318e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6561e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6560e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6081e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5970e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6013e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5928e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5720e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5632e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5395e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5353e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5122e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4958e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4895e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4570e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4527e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4672e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4292e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4340e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4093e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3929e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4093e-07 Epoch 58/60 189/189 [==============================] - 1s 4ms/step - loss: 2.3836e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3619e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3812e-07 21/21 [==============================] - 0s 937us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 1.3043e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 5.3651e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.1510e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 3.7296e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5227e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3853e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2947e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2509e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2105e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1317e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0995e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0766e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0075e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9972e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9207e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8833e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8695e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8290e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8111e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7985e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7597e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7406e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6983e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6458e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6770e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6116e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5591e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5430e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5456e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4963e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4941e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4715e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4579e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4388e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4193e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3803e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3605e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3633e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3064e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3362e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3369e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3159e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3035e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2802e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2578e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2719e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2768e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2255e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2204e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2005e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2200e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2105e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1847e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2049e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1782e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1742e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1729e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1640e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1434e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1700e-07 21/21 [==============================] - 0s 931us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 4.0957e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 1.2451e-06 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 6.7820e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 5.2181e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 4.4658e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 4.0698e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.8325e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6755e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5842e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4988e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4706e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3667e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3283e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2610e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2026e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1783e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1292e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0994e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0673e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0319e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0209e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9529e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9839e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9087e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9050e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9022e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8568e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8728e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7989e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8200e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7830e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8042e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7507e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7354e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7004e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6775e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6759e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6219e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5988e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6046e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5803e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5535e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5736e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4859e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4788e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4884e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4557e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4452e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4423e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4194e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4071e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3995e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3765e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3701e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3906e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3420e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3470e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3227e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3360e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3215e-07 21/21 [==============================] - 0s 939us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 2.0223e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 6.2755e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.5491e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 4.0465e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.7325e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5903e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5174e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4310e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3541e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3202e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2822e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2366e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1693e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1947e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1130e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1127e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0273e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0197e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9621e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9617e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9191e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9029e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8846e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8323e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8615e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8002e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7479e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7199e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7287e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7000e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6443e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6502e-07 Epoch 33/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5902e-07 Epoch 34/60 189/189 [==============================] - 1s 5ms/step - loss: 2.5838e-07 Epoch 35/60 189/189 [==============================] - 1s 5ms/step - loss: 2.5663e-07 Epoch 36/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5457e-07 Epoch 37/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4816e-07 Epoch 38/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4834e-07 Epoch 39/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4606e-07 Epoch 40/60 189/189 [==============================] - 1s 5ms/step - loss: 2.4819e-07 Epoch 41/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4671e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4531e-07 Epoch 43/60 189/189 [==============================] - 1s 4ms/step - loss: 2.3838e-07 Epoch 44/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4020e-07 Epoch 45/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4028e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3982e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3621e-07 Epoch 48/60 189/189 [==============================] - 1s 4ms/step - loss: 2.3395e-07 Epoch 49/60 189/189 [==============================] - 1s 4ms/step - loss: 2.3324e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3260e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3358e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2820e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3127e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3029e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2467e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2682e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2875e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2284e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2404e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2251e-07 21/21 [==============================] - 0s 945us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9698e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 7.2517e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.8455e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 4.1162e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.8236e-07 Epoch 6/60 189/189 [==============================] - 1s 4ms/step - loss: 3.6388e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5398e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4239e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3154e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2787e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2178e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1810e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1143e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0959e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0601e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0246e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9660e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9254e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9384e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8549e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8648e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8114e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8122e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7830e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7434e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7699e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7313e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7208e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6766e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7378e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6382e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6001e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6718e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5906e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5664e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6023e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5751e-07 Epoch 38/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5341e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5218e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4879e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5167e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4793e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4582e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4474e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4580e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4186e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3730e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4223e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4006e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4087e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3522e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3768e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3728e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3189e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2953e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3401e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3047e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2928e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2806e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2752e-07 21/21 [==============================] - 0s 971us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 1.2806e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 5.5577e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.1605e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 3.7462e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5343e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4013e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2962e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2311e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1533e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1147e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0601e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0005e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9907e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9307e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8846e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8518e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8295e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7728e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7324e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7115e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6911e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6910e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6236e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6507e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5737e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5334e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5784e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5351e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5130e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4917e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4957e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4588e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4390e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4676e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3945e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3959e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3877e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4197e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3716e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3496e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3331e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3473e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3406e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3254e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2773e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2655e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2967e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2712e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2763e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2427e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2562e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2126e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2011e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2133e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1838e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1846e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1639e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1712e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1808e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1589e-07 21/21 [==============================] - 0s 932us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 1.3119e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 5.3837e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.1895e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 3.8064e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6791e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4861e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4165e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3257e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2788e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2323e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2068e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1685e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1217e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1033e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0576e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0058e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9643e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9812e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8983e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8772e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8390e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8056e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7951e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7677e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7313e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6975e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6459e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6515e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6172e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5786e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5781e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5310e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5560e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5453e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5203e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4611e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4358e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4473e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4422e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4380e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3919e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3542e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3589e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3598e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3044e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3624e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3299e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3427e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3199e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2890e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2789e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2638e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2710e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2617e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2690e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2259e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2410e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2045e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2244e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2385e-07 21/21 [==============================] - 0s 913us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4407e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 7.7951e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 5.0216e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 4.2464e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.9107e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6974e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5559e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4440e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3719e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3257e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2575e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2026e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1461e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1455e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0870e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0353e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0318e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9818e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9751e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9480e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8685e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8847e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8303e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8177e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8326e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7541e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7403e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7616e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6783e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6912e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6798e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6965e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6946e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5791e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6124e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6052e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5789e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5204e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5151e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4939e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5033e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4478e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4678e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4529e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4081e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4148e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4416e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4092e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3362e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3836e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3442e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3117e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3104e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2811e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2770e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2647e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2561e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2566e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2239e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2063e-07 21/21 [==============================] - 0s 938us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 1.5773e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 5.7058e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.3432e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 3.8710e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6304e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4541e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4167e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3168e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2449e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2093e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1683e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1209e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0991e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0641e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0806e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0148e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9852e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9692e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8938e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9126e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8319e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8071e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7894e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7736e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7306e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6995e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6794e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6344e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6262e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6062e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5942e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5706e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5454e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4890e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4977e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4816e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4748e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4384e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4518e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4112e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4140e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3863e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3306e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3757e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3962e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3087e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3654e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3158e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2817e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3150e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3255e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3320e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2651e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2484e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2461e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2178e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2109e-07 Epoch 58/60 189/189 [==============================] - 1s 4ms/step - loss: 2.2173e-07 Epoch 59/60 189/189 [==============================] - 1s 4ms/step - loss: 2.2012e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.1709e-07 21/21 [==============================] - 0s 1ms/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 1.6389e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 5.6844e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.2314e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 3.7927e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5685e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4468e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3631e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2941e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2310e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1894e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1858e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1497e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0925e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0537e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0462e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0178e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9786e-07 Epoch 18/60 189/189 [==============================] - 1s 4ms/step - loss: 2.9524e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9158e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9205e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8754e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8497e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8373e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8005e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7639e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7204e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7220e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6563e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6579e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6733e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5920e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5984e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5888e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5696e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5611e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5131e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5170e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5092e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4834e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4836e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4676e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4489e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4738e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4137e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4123e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3756e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4122e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3651e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3264e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3181e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3311e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3004e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2846e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2632e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2745e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2684e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2567e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2651e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2250e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2128e-07 21/21 [==============================] - 0s 1ms/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 1.8287e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 6.4263e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.6619e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 4.0847e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.7975e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6250e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4920e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3971e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3404e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2657e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2511e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1890e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1620e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1362e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0645e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0454e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0253e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0378e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9653e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9721e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9281e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8824e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8890e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8372e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8201e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8146e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7368e-07 Epoch 28/60 189/189 [==============================] - 1s 4ms/step - loss: 2.7418e-07 Epoch 29/60 189/189 [==============================] - 1s 4ms/step - loss: 2.7158e-07 Epoch 30/60 189/189 [==============================] - 1s 4ms/step - loss: 2.6746e-07 Epoch 31/60 189/189 [==============================] - 1s 4ms/step - loss: 2.6741e-07 Epoch 32/60 189/189 [==============================] - 1s 4ms/step - loss: 2.6296e-07 Epoch 33/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5801e-07 Epoch 34/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5852e-07 Epoch 35/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5371e-07 Epoch 36/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5686e-07 Epoch 37/60 189/189 [==============================] - 1s 7ms/step - loss: 2.5518e-07 Epoch 38/60 189/189 [==============================] - 1s 6ms/step - loss: 2.5025e-07 Epoch 39/60 189/189 [==============================] - 1s 6ms/step - loss: 2.4983e-07 Epoch 40/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5024e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4555e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4360e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4478e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4385e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3955e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3966e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3816e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4002e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3192e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3612e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3201e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3871e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3011e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3036e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2643e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2897e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2762e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2844e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2659e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2356e-07 21/21 [==============================] - 0s 923us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 1.5480e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 6.0238e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.4563e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 3.9341e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6730e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5181e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4017e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2998e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2141e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1930e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1246e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0758e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0474e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9746e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9453e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8898e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8656e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8434e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8237e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7388e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7319e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7465e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6800e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6914e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6725e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6387e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5919e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5785e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5154e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5463e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5405e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5392e-07 Epoch 33/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4978e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4738e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4725e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4311e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4402e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4553e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4083e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4084e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3492e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3948e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3566e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3749e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3503e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3217e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3107e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3313e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2929e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2759e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2982e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2504e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2915e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2536e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2598e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2185e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2122e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2057e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2008e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2119e-07 21/21 [==============================] - 0s 953us/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 4.0311e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 1.5763e-06 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 7.9758e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 5.9346e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 5.0600e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 4.5127e-07 Epoch 7/60 189/189 [==============================] - 1s 4ms/step - loss: 4.1776e-07 Epoch 8/60 189/189 [==============================] - 1s 6ms/step - loss: 3.9638e-07 Epoch 9/60 189/189 [==============================] - 1s 7ms/step - loss: 3.8096e-07 Epoch 10/60 189/189 [==============================] - 1s 6ms/step - loss: 3.7017e-07 Epoch 11/60 189/189 [==============================] - 1s 4ms/step - loss: 3.5845e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5469e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4623e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3971e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3426e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3090e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2911e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2398e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2111e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1977e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1401e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1220e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1086e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0836e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0286e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0253e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9768e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9576e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9472e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9183e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9245e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8329e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8453e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8333e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7928e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7837e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7752e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7656e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7380e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7040e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7382e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6975e-07 Epoch 43/60 189/189 [==============================] - 1s 4ms/step - loss: 2.7021e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6411e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6654e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6103e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6418e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5776e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5640e-07 Epoch 50/60 189/189 [==============================] - 1s 4ms/step - loss: 2.5557e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5972e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5372e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5137e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5205e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5133e-07 Epoch 56/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4648e-07 Epoch 57/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4436e-07 Epoch 58/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4497e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4557e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4146e-07 21/21 [==============================] - 0s 1ms/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7048e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 1.0521e-06 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 5.9400e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 4.7196e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 4.1922e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.9153e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.7508e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6471e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5097e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4303e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3811e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3123e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2903e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2311e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2065e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1762e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1505e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1119e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1128e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0739e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0128e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0297e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9738e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9673e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9300e-07 Epoch 26/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9142e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8755e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8185e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.8294e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7918e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7721e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7097e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6964e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6697e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6224e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6085e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5892e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6143e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5693e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5324e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5766e-07 Epoch 42/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4934e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4887e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4891e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4621e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4422e-07 Epoch 47/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4055e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4377e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3912e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4204e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3901e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3671e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3362e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3310e-07 Epoch 55/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3428e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3277e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3219e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3249e-07 Epoch 59/60 189/189 [==============================] - 1s 4ms/step - loss: 2.2751e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2870e-07 21/21 [==============================] - 0s 1ms/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 1.5787e-05 Epoch 2/60 189/189 [==============================] - 1s 4ms/step - loss: 6.2285e-07 Epoch 3/60 189/189 [==============================] - 1s 3ms/step - loss: 4.4223e-07 Epoch 4/60 189/189 [==============================] - 1s 3ms/step - loss: 3.8844e-07 Epoch 5/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6466e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4596e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3561e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2883e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2118e-07 Epoch 10/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1748e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1332e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0898e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0501e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9793e-07 Epoch 15/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9784e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9133e-07 Epoch 17/60 189/189 [==============================] - 1s 4ms/step - loss: 2.8937e-07 Epoch 18/60 189/189 [==============================] - 1s 4ms/step - loss: 2.8752e-07 Epoch 19/60 189/189 [==============================] - 1s 4ms/step - loss: 2.8395e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7878e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7608e-07 Epoch 22/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7741e-07 Epoch 23/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7168e-07 Epoch 24/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6980e-07 Epoch 25/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6959e-07 Epoch 26/60 189/189 [==============================] - 1s 4ms/step - loss: 2.6576e-07 Epoch 27/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6294e-07 Epoch 28/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6029e-07 Epoch 29/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6307e-07 Epoch 30/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5372e-07 Epoch 31/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5554e-07 Epoch 32/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5153e-07 Epoch 33/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4741e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4988e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5083e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4507e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4200e-07 Epoch 38/60 189/189 [==============================] - 1s 4ms/step - loss: 2.4209e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4143e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3972e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3913e-07 Epoch 42/60 189/189 [==============================] - 1s 4ms/step - loss: 2.3726e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3562e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3584e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3351e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3072e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2862e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2991e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2702e-07 Epoch 50/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2636e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2635e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2864e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2485e-07 Epoch 54/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2309e-07 Epoch 55/60 189/189 [==============================] - 1s 4ms/step - loss: 2.2477e-07 Epoch 56/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2383e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2382e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2307e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2386e-07 Epoch 60/60 189/189 [==============================] - 1s 4ms/step - loss: 2.1755e-07 21/21 [==============================] - 0s 1ms/step Epoch 1/60 189/189 [==============================] - 1s 3ms/step - loss: 2.7861e-05 Epoch 2/60 189/189 [==============================] - 1s 3ms/step - loss: 9.2919e-07 Epoch 3/60 189/189 [==============================] - 1s 4ms/step - loss: 5.6479e-07 Epoch 4/60 189/189 [==============================] - 1s 4ms/step - loss: 4.6500e-07 Epoch 5/60 189/189 [==============================] - 1s 4ms/step - loss: 4.1563e-07 Epoch 6/60 189/189 [==============================] - 1s 3ms/step - loss: 3.8964e-07 Epoch 7/60 189/189 [==============================] - 1s 3ms/step - loss: 3.6633e-07 Epoch 8/60 189/189 [==============================] - 1s 3ms/step - loss: 3.5516e-07 Epoch 9/60 189/189 [==============================] - 1s 3ms/step - loss: 3.4419e-07 Epoch 10/60 189/189 [==============================] - 1s 4ms/step - loss: 3.4166e-07 Epoch 11/60 189/189 [==============================] - 1s 3ms/step - loss: 3.3161e-07 Epoch 12/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2989e-07 Epoch 13/60 189/189 [==============================] - 1s 3ms/step - loss: 3.2180e-07 Epoch 14/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1836e-07 Epoch 15/60 189/189 [==============================] - 1s 4ms/step - loss: 3.1540e-07 Epoch 16/60 189/189 [==============================] - 1s 3ms/step - loss: 3.1196e-07 Epoch 17/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0973e-07 Epoch 18/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0679e-07 Epoch 19/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0278e-07 Epoch 20/60 189/189 [==============================] - 1s 3ms/step - loss: 3.0093e-07 Epoch 21/60 189/189 [==============================] - 1s 3ms/step - loss: 2.9586e-07 Epoch 22/60 189/189 [==============================] - 1s 4ms/step - loss: 2.9279e-07 Epoch 23/60 189/189 [==============================] - 1s 4ms/step - loss: 2.9188e-07 Epoch 24/60 189/189 [==============================] - 1s 7ms/step - loss: 2.8847e-07 Epoch 25/60 189/189 [==============================] - 1s 7ms/step - loss: 2.8400e-07 Epoch 26/60 189/189 [==============================] - 1s 5ms/step - loss: 2.8013e-07 Epoch 27/60 189/189 [==============================] - 1s 5ms/step - loss: 2.8036e-07 Epoch 28/60 189/189 [==============================] - 1s 4ms/step - loss: 2.7669e-07 Epoch 29/60 189/189 [==============================] - 1s 4ms/step - loss: 2.7361e-07 Epoch 30/60 189/189 [==============================] - 1s 4ms/step - loss: 2.7609e-07 Epoch 31/60 189/189 [==============================] - 1s 4ms/step - loss: 2.7159e-07 Epoch 32/60 189/189 [==============================] - 1s 4ms/step - loss: 2.6967e-07 Epoch 33/60 189/189 [==============================] - 1s 4ms/step - loss: 2.6433e-07 Epoch 34/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6822e-07 Epoch 35/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6323e-07 Epoch 36/60 189/189 [==============================] - 1s 3ms/step - loss: 2.6030e-07 Epoch 37/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5533e-07 Epoch 38/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5876e-07 Epoch 39/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5179e-07 Epoch 40/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4950e-07 Epoch 41/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5187e-07 Epoch 42/60 189/189 [==============================] - 1s 3ms/step - loss: 2.5343e-07 Epoch 43/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4781e-07 Epoch 44/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4244e-07 Epoch 45/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4494e-07 Epoch 46/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4466e-07 Epoch 47/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4178e-07 Epoch 48/60 189/189 [==============================] - 1s 3ms/step - loss: 2.4164e-07 Epoch 49/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3794e-07 Epoch 50/60 189/189 [==============================] - 1s 4ms/step - loss: 2.3643e-07 Epoch 51/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3696e-07 Epoch 52/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3392e-07 Epoch 53/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3717e-07 Epoch 54/60 189/189 [==============================] - 1s 4ms/step - loss: 2.3526e-07 Epoch 55/60 189/189 [==============================] - 1s 4ms/step - loss: 2.3474e-07 Epoch 56/60 189/189 [==============================] - 1s 4ms/step - loss: 2.2991e-07 Epoch 57/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3181e-07 Epoch 58/60 189/189 [==============================] - 1s 3ms/step - loss: 2.3042e-07 Epoch 59/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2854e-07 Epoch 60/60 189/189 [==============================] - 1s 3ms/step - loss: 2.2796e-07 21/21 [==============================] - 0s 941us/step
print("Mean r value is: %.2f. The standard deviation of the r values is %.2f" % (results.mean(),results.std()))
Mean r value is: 0.81. The standard deviation of the r values is 0.02
plt.scatter(df['ep'].values , predicted)
x_line = np.linspace(0, 0.03, 50)
y_line = x_line
plt.plot(x_line, y_line, color='r')
plt.xlabel('True momentum resolution')
plt.ylabel('Predicted momentum resolution')
plt.show()
plt.scatter(df['p'].values , predicted, s= 0.2)
plt.xlabel('Momentum(GeV/c)')
plt.ylabel('Momentum resolution')
plt.xlim(0, 400)
plt.ylim(0, 0.012)
plt.show()
plt.scatter(df['p'] , df['ep'], s= 0.2,color = 'b')
plt.scatter(df['p'].values , predicted, s= 0.2, color='r')
plt.xlabel('Momentum(GeV/c)')
plt.ylabel('Momentum resolution')
plt.xlim(0, 400)
plt.ylim(0, 0.012)
plt.show()