import numpy as np
import pandas as pd
import tensorflow as tf
from pycaret.datasets import get_data
import sklearn.model_selection
import autokeras as ak
# Record version of key libraries
from importlib.metadata import version
print('autokeras==%s' % version('autokeras'))
autokeras==1.0.15
# Get a list of all pre-packaged data
# get_data('index')
# Select a pre-packaged data for testing
data = get_data('diamond')
| Carat Weight | Cut | Color | Clarity | Polish | Symmetry | Report | Price | |
|---|---|---|---|---|---|---|---|---|
| 0 | 1.10 | Ideal | H | SI1 | VG | EX | GIA | 5169 |
| 1 | 0.83 | Ideal | H | VS1 | ID | ID | AGSL | 3470 |
| 2 | 0.85 | Ideal | H | SI1 | EX | EX | GIA | 3183 |
| 3 | 0.91 | Ideal | E | SI1 | VG | VG | GIA | 4370 |
| 4 | 0.83 | Ideal | G | SI1 | EX | EX | GIA | 3171 |
# Split data into X and y
X = data.iloc[:,:-1]
y = data.iloc[:,-1]
# Specify types of features - can only be either categorical or numerical
# Must be specified for each column in a dictionary
# Categorical type can be in strings
column_types = {
'Carat Weight':'numerical',
'Cut':'categorical',
'Color':'categorical',
'Clarity':'categorical',
'Polish':'categorical',
'Symmetry':'categorical',
'Report':'categorical'
}
# Split data into training and testing data
X_train, X_test, y_train, y_test = sklearn.model_selection.train_test_split(X, y, random_state=6)
display(X)
display(y)
| Carat Weight | Cut | Color | Clarity | Polish | Symmetry | Report | |
|---|---|---|---|---|---|---|---|
| 0 | 1.10 | Ideal | H | SI1 | VG | EX | GIA |
| 1 | 0.83 | Ideal | H | VS1 | ID | ID | AGSL |
| 2 | 0.85 | Ideal | H | SI1 | EX | EX | GIA |
| 3 | 0.91 | Ideal | E | SI1 | VG | VG | GIA |
| 4 | 0.83 | Ideal | G | SI1 | EX | EX | GIA |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 5995 | 1.03 | Ideal | D | SI1 | EX | EX | GIA |
| 5996 | 1.00 | Very Good | D | SI1 | VG | VG | GIA |
| 5997 | 1.02 | Ideal | D | SI1 | EX | EX | GIA |
| 5998 | 1.27 | Signature-Ideal | G | VS1 | EX | EX | GIA |
| 5999 | 2.19 | Ideal | E | VS1 | EX | EX | GIA |
6000 rows × 7 columns
0 5169
1 3470
2 3183
3 4370
4 3171
...
5995 6250
5996 5328
5997 6157
5998 11206
5999 30507
Name: Price, Length: 6000, dtype: int64
# Setup automl object
automl = ak.StructuredDataRegressor(
column_names=X.columns.tolist(),
column_types=column_types,
loss="mean_squared_error",
overwrite=True,
max_trials=100,
project_name='diamond',
seed=6
)
# Fit and find best model
automl.fit(
x=X_train,
y=y_train
)
Trial 52 Complete [00h 08m 02s] val_loss: 6535161.5 Best val_loss So Far: 1611195.375 Total elapsed time: 04h 22m 12s INFO:tensorflow:Oracle triggered exit Epoch 1/642 141/141 [==============================] - 1s 3ms/step - loss: 223621072.0000 - mean_squared_error: 223621072.0000 Epoch 2/642 141/141 [==============================] - 1s 4ms/step - loss: 70604704.0000 - mean_squared_error: 70604704.0000 Epoch 3/642 141/141 [==============================] - 0s 3ms/step - loss: 19889010.0000 - mean_squared_error: 19889010.0000 Epoch 4/642 141/141 [==============================] - 0s 3ms/step - loss: 16764988.0000 - mean_squared_error: 16764988.0000 Epoch 5/642 141/141 [==============================] - 0s 3ms/step - loss: 15954228.0000 - mean_squared_error: 15954228.0000 Epoch 6/642 141/141 [==============================] - 0s 3ms/step - loss: 15358054.0000 - mean_squared_error: 15358054.0000 Epoch 7/642 141/141 [==============================] - 0s 3ms/step - loss: 14806212.0000 - mean_squared_error: 14806212.0000 Epoch 8/642 141/141 [==============================] - 0s 3ms/step - loss: 14285048.0000 - mean_squared_error: 14285048.0000 Epoch 9/642 141/141 [==============================] - 0s 3ms/step - loss: 13792074.0000 - mean_squared_error: 13792074.0000 Epoch 10/642 141/141 [==============================] - 0s 3ms/step - loss: 13334559.0000 - mean_squared_error: 13334559.0000 Epoch 11/642 141/141 [==============================] - 0s 3ms/step - loss: 12916930.0000 - mean_squared_error: 12916930.0000 Epoch 12/642 141/141 [==============================] - 0s 3ms/step - loss: 12544806.0000 - mean_squared_error: 12544806.0000 Epoch 13/642 141/141 [==============================] - 0s 3ms/step - loss: 12221883.0000 - mean_squared_error: 12221883.0000 Epoch 14/642 141/141 [==============================] - 0s 3ms/step - loss: 11942465.0000 - mean_squared_error: 11942465.0000 Epoch 15/642 141/141 [==============================] - 0s 3ms/step - loss: 11698892.0000 - mean_squared_error: 11698892.0000 Epoch 16/642 141/141 [==============================] - 0s 3ms/step - loss: 11483509.0000 - mean_squared_error: 11483509.0000 Epoch 17/642 141/141 [==============================] - 0s 3ms/step - loss: 11290130.0000 - mean_squared_error: 11290130.0000 Epoch 18/642 141/141 [==============================] - 0s 3ms/step - loss: 11112545.0000 - mean_squared_error: 11112545.0000 Epoch 19/642 141/141 [==============================] - 0s 3ms/step - loss: 10946386.0000 - mean_squared_error: 10946386.0000 Epoch 20/642 141/141 [==============================] - 0s 3ms/step - loss: 10786169.0000 - mean_squared_error: 10786169.0000 Epoch 21/642 141/141 [==============================] - 0s 3ms/step - loss: 10631827.0000 - mean_squared_error: 10631827.0000 Epoch 22/642 141/141 [==============================] - 0s 3ms/step - loss: 10480901.0000 - mean_squared_error: 10480901.0000 Epoch 23/642 141/141 [==============================] - 0s 2ms/step - loss: 10334129.0000 - mean_squared_error: 10334129.0000 Epoch 24/642 141/141 [==============================] - 0s 2ms/step - loss: 10191091.0000 - mean_squared_error: 10191091.0000 Epoch 25/642 141/141 [==============================] - 0s 2ms/step - loss: 10051526.0000 - mean_squared_error: 10051526.0000 Epoch 26/642 141/141 [==============================] - 0s 2ms/step - loss: 9912388.0000 - mean_squared_error: 9912388.0000 Epoch 27/642 141/141 [==============================] - 0s 2ms/step - loss: 9774899.0000 - mean_squared_error: 9774899.0000 Epoch 28/642 141/141 [==============================] - 0s 2ms/step - loss: 9639699.0000 - mean_squared_error: 9639699.0000 Epoch 29/642 141/141 [==============================] - 0s 2ms/step - loss: 9506988.0000 - mean_squared_error: 9506988.0000 Epoch 30/642 141/141 [==============================] - 0s 2ms/step - loss: 9376544.0000 - mean_squared_error: 9376544.0000 Epoch 31/642 141/141 [==============================] - 0s 2ms/step - loss: 9246966.0000 - mean_squared_error: 9246966.0000 Epoch 32/642 141/141 [==============================] - 0s 2ms/step - loss: 9117546.0000 - mean_squared_error: 9117546.0000 Epoch 33/642 141/141 [==============================] - 0s 2ms/step - loss: 8990094.0000 - mean_squared_error: 8990094.0000 Epoch 34/642 141/141 [==============================] - 0s 2ms/step - loss: 8864871.0000 - mean_squared_error: 8864871.0000 Epoch 35/642 141/141 [==============================] - 0s 2ms/step - loss: 8742043.0000 - mean_squared_error: 8742043.0000 Epoch 36/642 141/141 [==============================] - 0s 3ms/step - loss: 8622238.0000 - mean_squared_error: 8622238.0000 Epoch 37/642 141/141 [==============================] - 0s 2ms/step - loss: 8506008.0000 - mean_squared_error: 8506008.0000 Epoch 38/642 141/141 [==============================] - 0s 2ms/step - loss: 8391708.0000 - mean_squared_error: 8391708.0000 Epoch 39/642 141/141 [==============================] - 0s 2ms/step - loss: 8278831.5000 - mean_squared_error: 8278831.5000 Epoch 40/642 141/141 [==============================] - 0s 2ms/step - loss: 8169797.0000 - mean_squared_error: 8169797.0000 Epoch 41/642 141/141 [==============================] - 0s 2ms/step - loss: 8063767.0000 - mean_squared_error: 8063767.0000 Epoch 42/642 141/141 [==============================] - 0s 3ms/step - loss: 7962730.5000 - mean_squared_error: 7962730.5000 Epoch 43/642 141/141 [==============================] - 0s 2ms/step - loss: 7865425.0000 - mean_squared_error: 7865425.0000 Epoch 44/642 141/141 [==============================] - 0s 2ms/step - loss: 7771467.5000 - mean_squared_error: 7771467.5000 Epoch 45/642 141/141 [==============================] - 0s 2ms/step - loss: 7681754.0000 - mean_squared_error: 7681754.0000 Epoch 46/642 141/141 [==============================] - 0s 2ms/step - loss: 7596515.5000 - mean_squared_error: 7596515.5000 Epoch 47/642 141/141 [==============================] - 0s 2ms/step - loss: 7514504.5000 - mean_squared_error: 7514504.5000 Epoch 48/642 141/141 [==============================] - 0s 2ms/step - loss: 7436622.0000 - mean_squared_error: 7436622.0000 Epoch 49/642 141/141 [==============================] - 0s 3ms/step - loss: 7361613.5000 - mean_squared_error: 7361613.5000 Epoch 50/642 141/141 [==============================] - 0s 2ms/step - loss: 7289645.5000 - mean_squared_error: 7289645.5000 Epoch 51/642 141/141 [==============================] - 0s 2ms/step - loss: 7220346.5000 - mean_squared_error: 7220346.5000 Epoch 52/642 141/141 [==============================] - 0s 3ms/step - loss: 7154822.0000 - mean_squared_error: 7154822.0000 Epoch 53/642 141/141 [==============================] - 0s 3ms/step - loss: 7091829.5000 - mean_squared_error: 7091829.5000 Epoch 54/642 141/141 [==============================] - 0s 3ms/step - loss: 7030334.0000 - mean_squared_error: 7030334.0000 Epoch 55/642 141/141 [==============================] - 0s 3ms/step - loss: 6972442.5000 - mean_squared_error: 6972442.5000 Epoch 56/642 141/141 [==============================] - 0s 3ms/step - loss: 6915681.0000 - mean_squared_error: 6915681.0000 Epoch 57/642 141/141 [==============================] - 0s 3ms/step - loss: 6861274.5000 - mean_squared_error: 6861274.5000 Epoch 58/642 141/141 [==============================] - 0s 3ms/step - loss: 6810472.5000 - mean_squared_error: 6810472.5000 Epoch 59/642 141/141 [==============================] - 0s 3ms/step - loss: 6761616.5000 - mean_squared_error: 6761616.5000 Epoch 60/642 141/141 [==============================] - 0s 3ms/step - loss: 6714158.5000 - mean_squared_error: 6714158.5000 Epoch 61/642 141/141 [==============================] - 0s 3ms/step - loss: 6668426.0000 - mean_squared_error: 6668426.0000 Epoch 62/642 141/141 [==============================] - 0s 3ms/step - loss: 6624921.5000 - mean_squared_error: 6624921.5000 Epoch 63/642 141/141 [==============================] - 0s 3ms/step - loss: 6583914.5000 - mean_squared_error: 6583914.5000 Epoch 64/642 141/141 [==============================] - 0s 3ms/step - loss: 6543740.5000 - mean_squared_error: 6543740.5000 Epoch 65/642 141/141 [==============================] - 0s 3ms/step - loss: 6505640.0000 - mean_squared_error: 6505640.0000 Epoch 66/642 141/141 [==============================] - 0s 3ms/step - loss: 6468365.0000 - mean_squared_error: 6468365.0000 Epoch 67/642 141/141 [==============================] - 0s 3ms/step - loss: 6432405.5000 - mean_squared_error: 6432405.5000 Epoch 68/642 141/141 [==============================] - 0s 3ms/step - loss: 6397316.0000 - mean_squared_error: 6397316.0000 Epoch 69/642 141/141 [==============================] - 0s 3ms/step - loss: 6363042.5000 - mean_squared_error: 6363042.5000 Epoch 70/642 141/141 [==============================] - 1s 4ms/step - loss: 6331306.0000 - mean_squared_error: 6331306.0000 Epoch 71/642 141/141 [==============================] - 0s 3ms/step - loss: 6301151.0000 - mean_squared_error: 6301151.0000 Epoch 72/642 141/141 [==============================] - 0s 3ms/step - loss: 6272281.5000 - mean_squared_error: 6272281.5000 Epoch 73/642 141/141 [==============================] - 0s 3ms/step - loss: 6243568.5000 - mean_squared_error: 6243568.5000 Epoch 74/642 141/141 [==============================] - 0s 3ms/step - loss: 6216262.5000 - mean_squared_error: 6216262.5000 Epoch 75/642 141/141 [==============================] - 0s 3ms/step - loss: 6190045.0000 - mean_squared_error: 6190045.0000 Epoch 76/642 141/141 [==============================] - 0s 2ms/step - loss: 6164379.5000 - mean_squared_error: 6164379.5000 Epoch 77/642 141/141 [==============================] - 0s 2ms/step - loss: 6139533.5000 - mean_squared_error: 6139533.5000 Epoch 78/642 141/141 [==============================] - 0s 2ms/step - loss: 6115608.0000 - mean_squared_error: 6115608.0000 Epoch 79/642 141/141 [==============================] - 0s 2ms/step - loss: 6092094.0000 - mean_squared_error: 6092094.0000 Epoch 80/642 141/141 [==============================] - 0s 2ms/step - loss: 6069476.0000 - mean_squared_error: 6069476.0000 Epoch 81/642 141/141 [==============================] - 0s 2ms/step - loss: 6047404.5000 - mean_squared_error: 6047404.5000 Epoch 82/642 141/141 [==============================] - 0s 3ms/step - loss: 6025834.0000 - mean_squared_error: 6025834.0000 Epoch 83/642 141/141 [==============================] - 0s 2ms/step - loss: 6004873.0000 - mean_squared_error: 6004873.0000 Epoch 84/642 141/141 [==============================] - 0s 2ms/step - loss: 5983765.5000 - mean_squared_error: 5983765.5000 Epoch 85/642 141/141 [==============================] - 0s 2ms/step - loss: 5963757.5000 - mean_squared_error: 5963757.5000 Epoch 86/642 141/141 [==============================] - 0s 2ms/step - loss: 5943854.0000 - mean_squared_error: 5943854.0000 Epoch 87/642 141/141 [==============================] - 0s 2ms/step - loss: 5923944.0000 - mean_squared_error: 5923944.0000 Epoch 88/642 141/141 [==============================] - 0s 2ms/step - loss: 5904638.0000 - mean_squared_error: 5904638.0000 Epoch 89/642 141/141 [==============================] - 0s 2ms/step - loss: 5885316.0000 - mean_squared_error: 5885316.0000 Epoch 90/642 141/141 [==============================] - 0s 2ms/step - loss: 5866521.0000 - mean_squared_error: 5866521.0000 Epoch 91/642 141/141 [==============================] - 0s 2ms/step - loss: 5847342.5000 - mean_squared_error: 5847342.5000 Epoch 92/642 141/141 [==============================] - 0s 2ms/step - loss: 5828646.0000 - mean_squared_error: 5828646.0000 Epoch 93/642 141/141 [==============================] - 0s 2ms/step - loss: 5808960.0000 - mean_squared_error: 5808960.0000 Epoch 94/642 141/141 [==============================] - 0s 2ms/step - loss: 5787453.0000 - mean_squared_error: 5787453.0000 Epoch 95/642 141/141 [==============================] - 0s 3ms/step - loss: 5760700.0000 - mean_squared_error: 5760700.0000 Epoch 96/642 141/141 [==============================] - 0s 2ms/step - loss: 5733120.0000 - mean_squared_error: 5733120.0000 Epoch 97/642 141/141 [==============================] - 0s 2ms/step - loss: 5710221.5000 - mean_squared_error: 5710221.5000 Epoch 98/642 141/141 [==============================] - 0s 2ms/step - loss: 5689186.5000 - mean_squared_error: 5689186.5000 Epoch 99/642 141/141 [==============================] - 0s 2ms/step - loss: 5668037.5000 - mean_squared_error: 5668037.5000 Epoch 100/642 141/141 [==============================] - 0s 2ms/step - loss: 5647407.0000 - mean_squared_error: 5647407.0000 Epoch 101/642 141/141 [==============================] - 0s 2ms/step - loss: 5626878.0000 - mean_squared_error: 5626878.0000 Epoch 102/642 141/141 [==============================] - 0s 3ms/step - loss: 5606992.5000 - mean_squared_error: 5606992.5000 Epoch 103/642 141/141 [==============================] - 0s 2ms/step - loss: 5586077.5000 - mean_squared_error: 5586077.5000 Epoch 104/642 141/141 [==============================] - 0s 3ms/step - loss: 5564927.0000 - mean_squared_error: 5564927.0000 Epoch 105/642 141/141 [==============================] - 0s 3ms/step - loss: 5542154.0000 - mean_squared_error: 5542154.0000 Epoch 106/642 141/141 [==============================] - 0s 2ms/step - loss: 5517284.0000 - mean_squared_error: 5517284.0000 Epoch 107/642 141/141 [==============================] - 0s 3ms/step - loss: 5484191.0000 - mean_squared_error: 5484191.0000 Epoch 108/642 141/141 [==============================] - 0s 3ms/step - loss: 5439482.0000 - mean_squared_error: 5439482.0000 Epoch 109/642 141/141 [==============================] - 0s 2ms/step - loss: 5384063.0000 - mean_squared_error: 5384063.0000 Epoch 110/642 141/141 [==============================] - 0s 3ms/step - loss: 5326576.0000 - mean_squared_error: 5326576.0000 Epoch 111/642 141/141 [==============================] - 0s 3ms/step - loss: 5285186.5000 - mean_squared_error: 5285186.5000 Epoch 112/642 141/141 [==============================] - 0s 3ms/step - loss: 5250329.5000 - mean_squared_error: 5250329.5000 Epoch 113/642 141/141 [==============================] - 0s 3ms/step - loss: 5216119.5000 - mean_squared_error: 5216119.5000 Epoch 114/642 141/141 [==============================] - 0s 3ms/step - loss: 5183626.0000 - mean_squared_error: 5183626.0000 Epoch 115/642 141/141 [==============================] - 0s 3ms/step - loss: 5150698.5000 - mean_squared_error: 5150698.5000 Epoch 116/642 141/141 [==============================] - 0s 3ms/step - loss: 5117938.0000 - mean_squared_error: 5117938.0000 Epoch 117/642 141/141 [==============================] - 0s 3ms/step - loss: 5084993.5000 - mean_squared_error: 5084993.5000 Epoch 118/642 141/141 [==============================] - 0s 3ms/step - loss: 5052369.0000 - mean_squared_error: 5052369.0000 Epoch 119/642 141/141 [==============================] - 0s 3ms/step - loss: 5018778.0000 - mean_squared_error: 5018778.0000 Epoch 120/642 141/141 [==============================] - 0s 3ms/step - loss: 4980079.5000 - mean_squared_error: 4980079.5000 Epoch 121/642 141/141 [==============================] - 0s 3ms/step - loss: 4934038.5000 - mean_squared_error: 4934038.5000 Epoch 122/642 141/141 [==============================] - 0s 3ms/step - loss: 4885675.0000 - mean_squared_error: 4885675.0000 Epoch 123/642 141/141 [==============================] - 0s 3ms/step - loss: 4821673.5000 - mean_squared_error: 4821673.5000 Epoch 124/642 141/141 [==============================] - 0s 3ms/step - loss: 4750762.5000 - mean_squared_error: 4750762.5000 Epoch 125/642 141/141 [==============================] - 0s 3ms/step - loss: 4699476.0000 - mean_squared_error: 4699476.0000 Epoch 126/642 141/141 [==============================] - 0s 3ms/step - loss: 4655537.5000 - mean_squared_error: 4655537.5000 Epoch 127/642 141/141 [==============================] - 0s 3ms/step - loss: 4613453.5000 - mean_squared_error: 4613453.5000 Epoch 128/642 141/141 [==============================] - 0s 2ms/step - loss: 4571847.0000 - mean_squared_error: 4571847.0000 Epoch 129/642 141/141 [==============================] - 0s 2ms/step - loss: 4531755.5000 - mean_squared_error: 4531755.5000 Epoch 130/642 141/141 [==============================] - 0s 2ms/step - loss: 4491604.5000 - mean_squared_error: 4491604.5000 Epoch 131/642 141/141 [==============================] - 0s 3ms/step - loss: 4451319.0000 - mean_squared_error: 4451319.0000 Epoch 132/642 141/141 [==============================] - 0s 2ms/step - loss: 4411806.5000 - mean_squared_error: 4411806.5000 Epoch 133/642 141/141 [==============================] - 0s 2ms/step - loss: 4372583.5000 - mean_squared_error: 4372583.5000 Epoch 134/642 141/141 [==============================] - 0s 2ms/step - loss: 4333598.0000 - mean_squared_error: 4333598.0000 Epoch 135/642 141/141 [==============================] - 0s 2ms/step - loss: 4296246.0000 - mean_squared_error: 4296246.0000 Epoch 136/642 141/141 [==============================] - 0s 2ms/step - loss: 4257057.0000 - mean_squared_error: 4257057.0000 Epoch 137/642 141/141 [==============================] - 0s 2ms/step - loss: 4219708.0000 - mean_squared_error: 4219708.0000 Epoch 138/642 141/141 [==============================] - 0s 2ms/step - loss: 4181986.5000 - mean_squared_error: 4181986.5000 Epoch 139/642 141/141 [==============================] - 0s 2ms/step - loss: 4145022.7500 - mean_squared_error: 4145022.7500 Epoch 140/642 141/141 [==============================] - 0s 2ms/step - loss: 4108384.5000 - mean_squared_error: 4108384.5000 Epoch 141/642 141/141 [==============================] - 0s 2ms/step - loss: 4072024.2500 - mean_squared_error: 4072024.2500 Epoch 142/642 141/141 [==============================] - 0s 2ms/step - loss: 4036374.0000 - mean_squared_error: 4036374.0000 Epoch 143/642 141/141 [==============================] - 0s 2ms/step - loss: 4001047.5000 - mean_squared_error: 4001047.5000 Epoch 144/642 141/141 [==============================] - 0s 2ms/step - loss: 3965590.2500 - mean_squared_error: 3965590.2500 Epoch 145/642 141/141 [==============================] - 0s 2ms/step - loss: 3930823.0000 - mean_squared_error: 3930823.0000 Epoch 146/642 141/141 [==============================] - 0s 2ms/step - loss: 3896064.2500 - mean_squared_error: 3896064.2500 Epoch 147/642 141/141 [==============================] - 0s 2ms/step - loss: 3862174.5000 - mean_squared_error: 3862174.5000 Epoch 148/642 141/141 [==============================] - 0s 2ms/step - loss: 3828219.0000 - mean_squared_error: 3828219.0000 Epoch 149/642 141/141 [==============================] - 0s 2ms/step - loss: 3794919.7500 - mean_squared_error: 3794919.7500 Epoch 150/642 141/141 [==============================] - 0s 2ms/step - loss: 3761240.7500 - mean_squared_error: 3761240.7500 Epoch 151/642 141/141 [==============================] - 0s 2ms/step - loss: 3729357.2500 - mean_squared_error: 3729357.2500 Epoch 152/642 141/141 [==============================] - 0s 2ms/step - loss: 3696767.7500 - mean_squared_error: 3696767.7500 Epoch 153/642 141/141 [==============================] - 0s 2ms/step - loss: 3665266.2500 - mean_squared_error: 3665266.2500 Epoch 154/642 141/141 [==============================] - 0s 3ms/step - loss: 3632937.5000 - mean_squared_error: 3632937.5000 Epoch 155/642 141/141 [==============================] - 0s 2ms/step - loss: 3601955.5000 - mean_squared_error: 3601955.5000 Epoch 156/642 141/141 [==============================] - 0s 2ms/step - loss: 3571344.0000 - mean_squared_error: 3571344.0000 Epoch 157/642 141/141 [==============================] - 0s 2ms/step - loss: 3539971.5000 - mean_squared_error: 3539971.5000 Epoch 158/642 141/141 [==============================] - 0s 3ms/step - loss: 3510106.0000 - mean_squared_error: 3510106.0000 Epoch 159/642 141/141 [==============================] - 0s 3ms/step - loss: 3479272.5000 - mean_squared_error: 3479272.5000 Epoch 160/642 141/141 [==============================] - 0s 3ms/step - loss: 3450078.5000 - mean_squared_error: 3450078.5000 Epoch 161/642 141/141 [==============================] - 0s 3ms/step - loss: 3420863.7500 - mean_squared_error: 3420863.7500 Epoch 162/642 141/141 [==============================] - 0s 3ms/step - loss: 3392181.0000 - mean_squared_error: 3392181.0000 Epoch 163/642 141/141 [==============================] - 0s 3ms/step - loss: 3362377.5000 - mean_squared_error: 3362377.5000 Epoch 164/642 141/141 [==============================] - 0s 3ms/step - loss: 3334714.0000 - mean_squared_error: 3334714.0000 Epoch 165/642 141/141 [==============================] - 0s 3ms/step - loss: 3305368.0000 - mean_squared_error: 3305368.0000 Epoch 166/642 141/141 [==============================] - 0s 3ms/step - loss: 3277777.5000 - mean_squared_error: 3277777.5000 Epoch 167/642 141/141 [==============================] - 0s 3ms/step - loss: 3250036.2500 - mean_squared_error: 3250036.2500 Epoch 168/642 141/141 [==============================] - 0s 3ms/step - loss: 3223088.0000 - mean_squared_error: 3223088.0000 Epoch 169/642 141/141 [==============================] - 0s 3ms/step - loss: 3195349.2500 - mean_squared_error: 3195349.2500 Epoch 170/642 141/141 [==============================] - 0s 3ms/step - loss: 3168184.7500 - mean_squared_error: 3168184.7500 Epoch 171/642 141/141 [==============================] - 1s 4ms/step - loss: 3142586.2500 - mean_squared_error: 3142586.2500 Epoch 172/642 141/141 [==============================] - 0s 3ms/step - loss: 3116059.0000 - mean_squared_error: 3116059.0000 Epoch 173/642 141/141 [==============================] - 0s 3ms/step - loss: 3090624.0000 - mean_squared_error: 3090624.0000 Epoch 174/642 141/141 [==============================] - 0s 3ms/step - loss: 3064875.5000 - mean_squared_error: 3064875.5000 Epoch 175/642 141/141 [==============================] - 0s 3ms/step - loss: 3040539.7500 - mean_squared_error: 3040539.7500 Epoch 176/642 141/141 [==============================] - 0s 3ms/step - loss: 3015737.5000 - mean_squared_error: 3015737.5000 Epoch 177/642 141/141 [==============================] - 0s 3ms/step - loss: 2990663.2500 - mean_squared_error: 2990663.2500 Epoch 178/642 141/141 [==============================] - 0s 3ms/step - loss: 2966108.2500 - mean_squared_error: 2966108.2500 Epoch 179/642 141/141 [==============================] - 0s 3ms/step - loss: 2941584.5000 - mean_squared_error: 2941584.5000 Epoch 180/642 141/141 [==============================] - 0s 3ms/step - loss: 2918526.7500 - mean_squared_error: 2918526.7500 Epoch 181/642 141/141 [==============================] - 0s 3ms/step - loss: 2895472.7500 - mean_squared_error: 2895472.7500 Epoch 182/642 141/141 [==============================] - 0s 2ms/step - loss: 2871444.2500 - mean_squared_error: 2871444.2500 Epoch 183/642 141/141 [==============================] - 0s 2ms/step - loss: 2849722.5000 - mean_squared_error: 2849722.5000 Epoch 184/642 141/141 [==============================] - 0s 2ms/step - loss: 2826585.0000 - mean_squared_error: 2826585.0000 Epoch 185/642 141/141 [==============================] - 0s 2ms/step - loss: 2804005.0000 - mean_squared_error: 2804005.0000 Epoch 186/642 141/141 [==============================] - 0s 2ms/step - loss: 2780394.0000 - mean_squared_error: 2780394.0000 Epoch 187/642 141/141 [==============================] - 0s 2ms/step - loss: 2758844.0000 - mean_squared_error: 2758844.0000 Epoch 188/642 141/141 [==============================] - 0s 2ms/step - loss: 2736752.0000 - mean_squared_error: 2736752.0000 Epoch 189/642 141/141 [==============================] - 0s 2ms/step - loss: 2715075.2500 - mean_squared_error: 2715075.2500 Epoch 190/642 141/141 [==============================] - 0s 2ms/step - loss: 2692597.2500 - mean_squared_error: 2692597.2500 Epoch 191/642 141/141 [==============================] - 0s 2ms/step - loss: 2670758.5000 - mean_squared_error: 2670758.5000 Epoch 192/642 141/141 [==============================] - 0s 2ms/step - loss: 2648785.2500 - mean_squared_error: 2648785.2500 Epoch 193/642 141/141 [==============================] - 0s 3ms/step - loss: 2628276.7500 - mean_squared_error: 2628276.7500 Epoch 194/642 141/141 [==============================] - 0s 2ms/step - loss: 2606229.7500 - mean_squared_error: 2606229.7500 Epoch 195/642 141/141 [==============================] - 0s 2ms/step - loss: 2584576.0000 - mean_squared_error: 2584576.0000 Epoch 196/642 141/141 [==============================] - 0s 2ms/step - loss: 2563891.5000 - mean_squared_error: 2563891.5000 Epoch 197/642 141/141 [==============================] - 0s 2ms/step - loss: 2542022.2500 - mean_squared_error: 2542022.2500 Epoch 198/642 141/141 [==============================] - 0s 2ms/step - loss: 2521880.2500 - mean_squared_error: 2521880.2500 Epoch 199/642 141/141 [==============================] - 0s 2ms/step - loss: 2500549.5000 - mean_squared_error: 2500549.5000 Epoch 200/642 141/141 [==============================] - 0s 2ms/step - loss: 2480316.7500 - mean_squared_error: 2480316.7500 Epoch 201/642 141/141 [==============================] - 0s 2ms/step - loss: 2459231.0000 - mean_squared_error: 2459231.0000 Epoch 202/642 141/141 [==============================] - 0s 2ms/step - loss: 2440171.0000 - mean_squared_error: 2440171.0000 Epoch 203/642 141/141 [==============================] - 0s 2ms/step - loss: 2420247.0000 - mean_squared_error: 2420247.0000 Epoch 204/642 141/141 [==============================] - 0s 2ms/step - loss: 2400560.2500 - mean_squared_error: 2400560.2500 Epoch 205/642 141/141 [==============================] - 0s 2ms/step - loss: 2381678.7500 - mean_squared_error: 2381678.7500 Epoch 206/642 141/141 [==============================] - 0s 2ms/step - loss: 2362146.2500 - mean_squared_error: 2362146.2500 Epoch 207/642 141/141 [==============================] - 0s 3ms/step - loss: 2342823.5000 - mean_squared_error: 2342823.5000 Epoch 208/642 141/141 [==============================] - 0s 2ms/step - loss: 2323681.5000 - mean_squared_error: 2323681.5000 Epoch 209/642 141/141 [==============================] - 0s 2ms/step - loss: 2306349.0000 - mean_squared_error: 2306349.0000 Epoch 210/642 141/141 [==============================] - 0s 3ms/step - loss: 2287511.0000 - mean_squared_error: 2287511.0000 Epoch 211/642 141/141 [==============================] - 0s 3ms/step - loss: 2269315.7500 - mean_squared_error: 2269315.7500 Epoch 212/642 141/141 [==============================] - 0s 3ms/step - loss: 2252299.2500 - mean_squared_error: 2252299.2500 Epoch 213/642 141/141 [==============================] - 0s 3ms/step - loss: 2234863.2500 - mean_squared_error: 2234863.2500 Epoch 214/642 141/141 [==============================] - 0s 3ms/step - loss: 2218116.2500 - mean_squared_error: 2218116.2500 Epoch 215/642 141/141 [==============================] - 0s 3ms/step - loss: 2201483.2500 - mean_squared_error: 2201483.2500 Epoch 216/642 141/141 [==============================] - 0s 3ms/step - loss: 2185674.5000 - mean_squared_error: 2185674.5000 Epoch 217/642 141/141 [==============================] - 0s 3ms/step - loss: 2169734.0000 - mean_squared_error: 2169734.0000 Epoch 218/642 141/141 [==============================] - 0s 3ms/step - loss: 2153865.5000 - mean_squared_error: 2153865.5000 Epoch 219/642 141/141 [==============================] - 0s 3ms/step - loss: 2137946.2500 - mean_squared_error: 2137946.2500 Epoch 220/642 141/141 [==============================] - 0s 3ms/step - loss: 2123335.2500 - mean_squared_error: 2123335.2500 Epoch 221/642 141/141 [==============================] - 0s 3ms/step - loss: 2107114.7500 - mean_squared_error: 2107114.7500 Epoch 222/642 141/141 [==============================] - 0s 3ms/step - loss: 2092401.3750 - mean_squared_error: 2092401.3750 Epoch 223/642 141/141 [==============================] - 0s 3ms/step - loss: 2078394.6250 - mean_squared_error: 2078394.6250 Epoch 224/642 141/141 [==============================] - 0s 3ms/step - loss: 2064278.0000 - mean_squared_error: 2064278.0000 Epoch 225/642 141/141 [==============================] - 0s 3ms/step - loss: 2050469.3750 - mean_squared_error: 2050469.3750 Epoch 226/642 141/141 [==============================] - 0s 3ms/step - loss: 2036257.2500 - mean_squared_error: 2036257.2500 Epoch 227/642 141/141 [==============================] - 0s 3ms/step - loss: 2022842.6250 - mean_squared_error: 2022842.6250 Epoch 228/642 141/141 [==============================] - 0s 3ms/step - loss: 2009781.1250 - mean_squared_error: 2009781.1250 Epoch 229/642 141/141 [==============================] - 0s 3ms/step - loss: 1996635.7500 - mean_squared_error: 1996635.7500 Epoch 230/642 141/141 [==============================] - 0s 3ms/step - loss: 1983779.7500 - mean_squared_error: 1983779.7500 Epoch 231/642 141/141 [==============================] - 0s 3ms/step - loss: 1971991.5000 - mean_squared_error: 1971991.5000 Epoch 232/642 141/141 [==============================] - 0s 3ms/step - loss: 1959157.2500 - mean_squared_error: 1959157.2500 Epoch 233/642 141/141 [==============================] - 0s 3ms/step - loss: 1946827.0000 - mean_squared_error: 1946827.0000 Epoch 234/642 141/141 [==============================] - 0s 2ms/step - loss: 1935006.8750 - mean_squared_error: 1935006.8750 Epoch 235/642 141/141 [==============================] - 0s 2ms/step - loss: 1922609.8750 - mean_squared_error: 1922609.8750 Epoch 236/642 141/141 [==============================] - 0s 2ms/step - loss: 1911440.0000 - mean_squared_error: 1911440.0000 Epoch 237/642 141/141 [==============================] - 0s 2ms/step - loss: 1899777.0000 - mean_squared_error: 1899777.0000 Epoch 238/642 141/141 [==============================] - 0s 3ms/step - loss: 1888195.6250 - mean_squared_error: 1888195.6250 Epoch 239/642 141/141 [==============================] - 0s 2ms/step - loss: 1876274.5000 - mean_squared_error: 1876274.5000 Epoch 240/642 141/141 [==============================] - 0s 2ms/step - loss: 1866323.0000 - mean_squared_error: 1866323.0000 Epoch 241/642 141/141 [==============================] - 0s 2ms/step - loss: 1853263.2500 - mean_squared_error: 1853263.2500 Epoch 242/642 141/141 [==============================] - 0s 2ms/step - loss: 1842534.0000 - mean_squared_error: 1842534.0000 Epoch 243/642 141/141 [==============================] - 0s 2ms/step - loss: 1831902.1250 - mean_squared_error: 1831902.1250 Epoch 244/642 141/141 [==============================] - 0s 2ms/step - loss: 1820308.5000 - mean_squared_error: 1820308.5000 Epoch 245/642 141/141 [==============================] - 0s 2ms/step - loss: 1809938.0000 - mean_squared_error: 1809938.0000 Epoch 246/642 141/141 [==============================] - 0s 2ms/step - loss: 1799196.2500 - mean_squared_error: 1799196.2500 Epoch 247/642 141/141 [==============================] - 0s 2ms/step - loss: 1787874.0000 - mean_squared_error: 1787874.0000 Epoch 248/642 141/141 [==============================] - 0s 2ms/step - loss: 1776638.0000 - mean_squared_error: 1776638.0000 Epoch 249/642 141/141 [==============================] - 0s 2ms/step - loss: 1766599.6250 - mean_squared_error: 1766599.6250 Epoch 250/642 141/141 [==============================] - 0s 2ms/step - loss: 1755761.1250 - mean_squared_error: 1755761.1250 Epoch 251/642 141/141 [==============================] - 0s 2ms/step - loss: 1745596.1250 - mean_squared_error: 1745596.1250 Epoch 252/642 141/141 [==============================] - 0s 2ms/step - loss: 1736792.3750 - mean_squared_error: 1736792.3750 Epoch 253/642 141/141 [==============================] - 0s 2ms/step - loss: 1727025.0000 - mean_squared_error: 1727025.0000 Epoch 254/642 141/141 [==============================] - 0s 2ms/step - loss: 1718324.7500 - mean_squared_error: 1718324.7500 Epoch 255/642 141/141 [==============================] - 0s 2ms/step - loss: 1710162.0000 - mean_squared_error: 1710162.0000 Epoch 256/642 141/141 [==============================] - 0s 2ms/step - loss: 1701110.6250 - mean_squared_error: 1701110.6250 Epoch 257/642 141/141 [==============================] - 0s 2ms/step - loss: 1692280.1250 - mean_squared_error: 1692280.1250 Epoch 258/642 141/141 [==============================] - 0s 2ms/step - loss: 1683668.7500 - mean_squared_error: 1683668.7500 Epoch 259/642 141/141 [==============================] - 0s 2ms/step - loss: 1675594.1250 - mean_squared_error: 1675594.1250 Epoch 260/642 141/141 [==============================] - 0s 3ms/step - loss: 1667862.6250 - mean_squared_error: 1667862.6250 Epoch 261/642 141/141 [==============================] - 0s 2ms/step - loss: 1660536.1250 - mean_squared_error: 1660536.1250 Epoch 262/642 141/141 [==============================] - 0s 3ms/step - loss: 1652562.3750 - mean_squared_error: 1652562.3750 Epoch 263/642 141/141 [==============================] - 0s 3ms/step - loss: 1644799.8750 - mean_squared_error: 1644799.8750 Epoch 264/642 141/141 [==============================] - 0s 3ms/step - loss: 1637076.2500 - mean_squared_error: 1637076.2500 Epoch 265/642 141/141 [==============================] - 0s 3ms/step - loss: 1629305.1250 - mean_squared_error: 1629305.1250 Epoch 266/642 141/141 [==============================] - 0s 3ms/step - loss: 1621411.0000 - mean_squared_error: 1621411.0000 Epoch 267/642 141/141 [==============================] - 0s 3ms/step - loss: 1614659.8750 - mean_squared_error: 1614659.8750 Epoch 268/642 141/141 [==============================] - 0s 3ms/step - loss: 1607896.6250 - mean_squared_error: 1607896.6250 Epoch 269/642 141/141 [==============================] - 0s 3ms/step - loss: 1600075.1250 - mean_squared_error: 1600075.1250 Epoch 270/642 141/141 [==============================] - 0s 3ms/step - loss: 1593280.7500 - mean_squared_error: 1593280.7500 Epoch 271/642 141/141 [==============================] - 0s 3ms/step - loss: 1585947.8750 - mean_squared_error: 1585947.8750 Epoch 272/642 141/141 [==============================] - 0s 3ms/step - loss: 1578825.3750 - mean_squared_error: 1578825.3750 Epoch 273/642 141/141 [==============================] - 0s 3ms/step - loss: 1571939.7500 - mean_squared_error: 1571939.7500 Epoch 274/642 141/141 [==============================] - 0s 3ms/step - loss: 1565425.5000 - mean_squared_error: 1565425.5000 Epoch 275/642 141/141 [==============================] - 0s 3ms/step - loss: 1557728.1250 - mean_squared_error: 1557728.1250 Epoch 276/642 141/141 [==============================] - 0s 3ms/step - loss: 1551489.3750 - mean_squared_error: 1551489.3750 Epoch 277/642 141/141 [==============================] - 0s 3ms/step - loss: 1545326.3750 - mean_squared_error: 1545326.3750 Epoch 278/642 141/141 [==============================] - 0s 3ms/step - loss: 1538856.2500 - mean_squared_error: 1538856.2500 Epoch 279/642 141/141 [==============================] - 0s 3ms/step - loss: 1532053.0000 - mean_squared_error: 1532053.0000 Epoch 280/642 141/141 [==============================] - 0s 3ms/step - loss: 1526053.7500 - mean_squared_error: 1526053.7500 Epoch 281/642 141/141 [==============================] - 0s 3ms/step - loss: 1520144.7500 - mean_squared_error: 1520144.7500 Epoch 282/642 141/141 [==============================] - 0s 3ms/step - loss: 1513487.3750 - mean_squared_error: 1513487.3750 Epoch 283/642 141/141 [==============================] - 0s 3ms/step - loss: 1507902.3750 - mean_squared_error: 1507902.3750 Epoch 284/642 141/141 [==============================] - 0s 3ms/step - loss: 1500902.7500 - mean_squared_error: 1500902.7500 Epoch 285/642 141/141 [==============================] - 0s 3ms/step - loss: 1495855.3750 - mean_squared_error: 1495855.3750 Epoch 286/642 141/141 [==============================] - 0s 2ms/step - loss: 1488937.1250 - mean_squared_error: 1488937.1250 Epoch 287/642 141/141 [==============================] - 0s 2ms/step - loss: 1482909.7500 - mean_squared_error: 1482909.7500 Epoch 288/642 141/141 [==============================] - 0s 3ms/step - loss: 1477365.6250 - mean_squared_error: 1477365.6250 Epoch 289/642 141/141 [==============================] - 0s 2ms/step - loss: 1471001.0000 - mean_squared_error: 1471001.0000 Epoch 290/642 141/141 [==============================] - 0s 2ms/step - loss: 1465404.3750 - mean_squared_error: 1465404.3750 Epoch 291/642 141/141 [==============================] - 0s 2ms/step - loss: 1459230.3750 - mean_squared_error: 1459230.3750 Epoch 292/642 141/141 [==============================] - 0s 2ms/step - loss: 1454027.5000 - mean_squared_error: 1454027.5000 Epoch 293/642 141/141 [==============================] - 0s 2ms/step - loss: 1448108.3750 - mean_squared_error: 1448108.3750 Epoch 294/642 141/141 [==============================] - 0s 2ms/step - loss: 1443355.8750 - mean_squared_error: 1443355.8750 Epoch 295/642 141/141 [==============================] - 0s 2ms/step - loss: 1437337.6250 - mean_squared_error: 1437337.6250 Epoch 296/642 141/141 [==============================] - 0s 2ms/step - loss: 1431725.7500 - mean_squared_error: 1431725.7500 Epoch 297/642 141/141 [==============================] - 0s 2ms/step - loss: 1426955.7500 - mean_squared_error: 1426955.7500 Epoch 298/642 141/141 [==============================] - 0s 2ms/step - loss: 1421811.7500 - mean_squared_error: 1421811.7500 Epoch 299/642 141/141 [==============================] - 0s 2ms/step - loss: 1415971.6250 - mean_squared_error: 1415971.6250 Epoch 300/642 141/141 [==============================] - 0s 2ms/step - loss: 1411793.8750 - mean_squared_error: 1411793.8750 Epoch 301/642 141/141 [==============================] - 0s 2ms/step - loss: 1405994.3750 - mean_squared_error: 1405994.3750 Epoch 302/642 141/141 [==============================] - 0s 2ms/step - loss: 1401343.3750 - mean_squared_error: 1401343.3750 Epoch 303/642 141/141 [==============================] - 0s 2ms/step - loss: 1396212.8750 - mean_squared_error: 1396212.8750 Epoch 304/642 141/141 [==============================] - 0s 2ms/step - loss: 1391750.5000 - mean_squared_error: 1391750.5000 Epoch 305/642 141/141 [==============================] - 0s 2ms/step - loss: 1386416.8750 - mean_squared_error: 1386416.8750 Epoch 306/642 141/141 [==============================] - 0s 2ms/step - loss: 1382327.1250 - mean_squared_error: 1382327.1250 Epoch 307/642 141/141 [==============================] - 0s 2ms/step - loss: 1376862.2500 - mean_squared_error: 1376862.2500 Epoch 308/642 141/141 [==============================] - 0s 2ms/step - loss: 1372419.5000 - mean_squared_error: 1372419.5000 Epoch 309/642 141/141 [==============================] - 0s 3ms/step - loss: 1368959.6250 - mean_squared_error: 1368959.6250 Epoch 310/642 141/141 [==============================] - 0s 2ms/step - loss: 1363751.2500 - mean_squared_error: 1363751.2500 Epoch 311/642 141/141 [==============================] - 0s 2ms/step - loss: 1358912.5000 - mean_squared_error: 1358912.5000 Epoch 312/642 141/141 [==============================] - 0s 2ms/step - loss: 1354581.3750 - mean_squared_error: 1354581.3750 Epoch 313/642 141/141 [==============================] - 0s 3ms/step - loss: 1350765.3750 - mean_squared_error: 1350765.3750 Epoch 314/642 141/141 [==============================] - 0s 2ms/step - loss: 1345751.3750 - mean_squared_error: 1345751.3750 Epoch 315/642 141/141 [==============================] - 0s 2ms/step - loss: 1342652.2500 - mean_squared_error: 1342652.2500 Epoch 316/642 141/141 [==============================] - 0s 4ms/step - loss: 1336677.8750 - mean_squared_error: 1336677.8750 Epoch 317/642 141/141 [==============================] - 0s 3ms/step - loss: 1333660.5000 - mean_squared_error: 1333660.5000 Epoch 318/642 141/141 [==============================] - 0s 2ms/step - loss: 1329131.7500 - mean_squared_error: 1329131.7500 Epoch 319/642 141/141 [==============================] - 0s 3ms/step - loss: 1325202.6250 - mean_squared_error: 1325202.6250 Epoch 320/642 141/141 [==============================] - 0s 3ms/step - loss: 1321122.0000 - mean_squared_error: 1321122.0000 Epoch 321/642 141/141 [==============================] - 0s 3ms/step - loss: 1317312.3750 - mean_squared_error: 1317312.3750 Epoch 322/642 141/141 [==============================] - 0s 3ms/step - loss: 1313283.8750 - mean_squared_error: 1313283.8750 Epoch 323/642 141/141 [==============================] - 0s 3ms/step - loss: 1310141.5000 - mean_squared_error: 1310141.5000 Epoch 324/642 141/141 [==============================] - 0s 3ms/step - loss: 1304806.0000 - mean_squared_error: 1304806.0000 Epoch 325/642 141/141 [==============================] - 0s 3ms/step - loss: 1301825.3750 - mean_squared_error: 1301825.3750 Epoch 326/642 141/141 [==============================] - 0s 3ms/step - loss: 1297980.2500 - mean_squared_error: 1297980.2500 Epoch 327/642 141/141 [==============================] - 0s 3ms/step - loss: 1293755.7500 - mean_squared_error: 1293755.7500 Epoch 328/642 141/141 [==============================] - 0s 3ms/step - loss: 1290321.8750 - mean_squared_error: 1290321.8750 Epoch 329/642 141/141 [==============================] - 0s 3ms/step - loss: 1287364.3750 - mean_squared_error: 1287364.3750 Epoch 330/642 141/141 [==============================] - 0s 3ms/step - loss: 1283063.8750 - mean_squared_error: 1283063.8750 Epoch 331/642 141/141 [==============================] - 0s 3ms/step - loss: 1279829.5000 - mean_squared_error: 1279829.5000 Epoch 332/642 141/141 [==============================] - 0s 3ms/step - loss: 1275938.8750 - mean_squared_error: 1275938.8750 Epoch 333/642 141/141 [==============================] - 0s 3ms/step - loss: 1272069.7500 - mean_squared_error: 1272069.7500 Epoch 334/642 141/141 [==============================] - 0s 3ms/step - loss: 1268917.8750 - mean_squared_error: 1268917.8750 Epoch 335/642 141/141 [==============================] - 0s 3ms/step - loss: 1266193.2500 - mean_squared_error: 1266193.2500 Epoch 336/642 141/141 [==============================] - 0s 3ms/step - loss: 1261260.0000 - mean_squared_error: 1261260.0000 Epoch 337/642 141/141 [==============================] - 0s 3ms/step - loss: 1259137.7500 - mean_squared_error: 1259137.7500 Epoch 338/642 141/141 [==============================] - 0s 3ms/step - loss: 1255031.7500 - mean_squared_error: 1255031.7500 Epoch 339/642 141/141 [==============================] - 0s 3ms/step - loss: 1252042.8750 - mean_squared_error: 1252042.8750 Epoch 340/642 141/141 [==============================] - 0s 2ms/step - loss: 1249091.7500 - mean_squared_error: 1249091.7500 Epoch 341/642 141/141 [==============================] - 0s 2ms/step - loss: 1245313.6250 - mean_squared_error: 1245313.6250 Epoch 342/642 141/141 [==============================] - 0s 3ms/step - loss: 1241580.6250 - mean_squared_error: 1241580.6250 Epoch 343/642 141/141 [==============================] - 0s 2ms/step - loss: 1239782.1250 - mean_squared_error: 1239782.1250 Epoch 344/642 141/141 [==============================] - 0s 2ms/step - loss: 1235165.6250 - mean_squared_error: 1235165.6250 Epoch 345/642 141/141 [==============================] - 0s 2ms/step - loss: 1232459.7500 - mean_squared_error: 1232459.7500 Epoch 346/642 141/141 [==============================] - 0s 2ms/step - loss: 1230375.0000 - mean_squared_error: 1230375.0000 Epoch 347/642 141/141 [==============================] - 0s 2ms/step - loss: 1225613.3750 - mean_squared_error: 1225613.3750 Epoch 348/642 141/141 [==============================] - 0s 2ms/step - loss: 1223916.3750 - mean_squared_error: 1223916.3750 Epoch 349/642 141/141 [==============================] - 0s 2ms/step - loss: 1220907.7500 - mean_squared_error: 1220907.7500 Epoch 350/642 141/141 [==============================] - 0s 2ms/step - loss: 1216651.2500 - mean_squared_error: 1216651.2500 Epoch 351/642 141/141 [==============================] - 0s 2ms/step - loss: 1215292.1250 - mean_squared_error: 1215292.1250 Epoch 352/642 141/141 [==============================] - 0s 2ms/step - loss: 1212178.7500 - mean_squared_error: 1212178.7500 Epoch 353/642 141/141 [==============================] - 0s 2ms/step - loss: 1208740.5000 - mean_squared_error: 1208740.5000 Epoch 354/642 141/141 [==============================] - 0s 2ms/step - loss: 1206772.7500 - mean_squared_error: 1206772.7500 Epoch 355/642 141/141 [==============================] - 0s 2ms/step - loss: 1203318.1250 - mean_squared_error: 1203318.1250 Epoch 356/642 141/141 [==============================] - 0s 2ms/step - loss: 1200584.8750 - mean_squared_error: 1200584.8750 Epoch 357/642 141/141 [==============================] - 0s 2ms/step - loss: 1197716.0000 - mean_squared_error: 1197716.0000 Epoch 358/642 141/141 [==============================] - 0s 2ms/step - loss: 1195968.0000 - mean_squared_error: 1195968.0000 Epoch 359/642 141/141 [==============================] - 0s 2ms/step - loss: 1193118.7500 - mean_squared_error: 1193118.7500 Epoch 360/642 141/141 [==============================] - 0s 2ms/step - loss: 1189355.6250 - mean_squared_error: 1189355.6250 Epoch 361/642 141/141 [==============================] - 0s 2ms/step - loss: 1186658.7500 - mean_squared_error: 1186658.7500 Epoch 362/642 141/141 [==============================] - 0s 3ms/step - loss: 1185113.3750 - mean_squared_error: 1185113.3750 Epoch 363/642 141/141 [==============================] - 0s 2ms/step - loss: 1183803.6250 - mean_squared_error: 1183803.6250 Epoch 364/642 141/141 [==============================] - 0s 2ms/step - loss: 1179904.8750 - mean_squared_error: 1179904.8750 Epoch 365/642 141/141 [==============================] - 0s 2ms/step - loss: 1178508.3750 - mean_squared_error: 1178508.3750 Epoch 366/642 141/141 [==============================] - 0s 3ms/step - loss: 1174047.0000 - mean_squared_error: 1174047.0000 Epoch 367/642 141/141 [==============================] - 0s 2ms/step - loss: 1171994.3750 - mean_squared_error: 1171994.3750 Epoch 368/642 141/141 [==============================] - 0s 3ms/step - loss: 1168648.2500 - mean_squared_error: 1168648.2500 Epoch 369/642 141/141 [==============================] - 0s 3ms/step - loss: 1168216.1250 - mean_squared_error: 1168216.1250 Epoch 370/642 141/141 [==============================] - 0s 3ms/step - loss: 1165088.3750 - mean_squared_error: 1165088.3750 Epoch 371/642 141/141 [==============================] - 0s 3ms/step - loss: 1163139.1250 - mean_squared_error: 1163139.1250 Epoch 372/642 141/141 [==============================] - 0s 3ms/step - loss: 1160349.0000 - mean_squared_error: 1160349.0000 Epoch 373/642 141/141 [==============================] - 0s 3ms/step - loss: 1157720.1250 - mean_squared_error: 1157720.1250 Epoch 374/642 141/141 [==============================] - 0s 3ms/step - loss: 1156402.3750 - mean_squared_error: 1156402.3750 Epoch 375/642 141/141 [==============================] - 0s 3ms/step - loss: 1154209.2500 - mean_squared_error: 1154209.2500 Epoch 376/642 141/141 [==============================] - 0s 3ms/step - loss: 1151088.1250 - mean_squared_error: 1151088.1250 Epoch 377/642 141/141 [==============================] - 0s 3ms/step - loss: 1149032.0000 - mean_squared_error: 1149032.0000 Epoch 378/642 141/141 [==============================] - 0s 3ms/step - loss: 1147225.0000 - mean_squared_error: 1147225.0000 Epoch 379/642 141/141 [==============================] - 0s 3ms/step - loss: 1144494.5000 - mean_squared_error: 1144494.5000 Epoch 380/642 141/141 [==============================] - 0s 3ms/step - loss: 1143493.0000 - mean_squared_error: 1143493.0000 Epoch 381/642 141/141 [==============================] - 0s 3ms/step - loss: 1141495.6250 - mean_squared_error: 1141495.6250 Epoch 382/642 141/141 [==============================] - 0s 3ms/step - loss: 1138482.7500 - mean_squared_error: 1138482.7500 Epoch 383/642 141/141 [==============================] - 0s 3ms/step - loss: 1137277.0000 - mean_squared_error: 1137277.0000 Epoch 384/642 141/141 [==============================] - 0s 3ms/step - loss: 1134386.0000 - mean_squared_error: 1134386.0000 Epoch 385/642 141/141 [==============================] - 0s 3ms/step - loss: 1132336.6250 - mean_squared_error: 1132336.6250 Epoch 386/642 141/141 [==============================] - 0s 3ms/step - loss: 1130259.6250 - mean_squared_error: 1130259.6250 Epoch 387/642 141/141 [==============================] - 0s 3ms/step - loss: 1128347.3750 - mean_squared_error: 1128347.3750 Epoch 388/642 141/141 [==============================] - 0s 3ms/step - loss: 1127155.6250 - mean_squared_error: 1127155.6250 Epoch 389/642 141/141 [==============================] - 0s 3ms/step - loss: 1124520.8750 - mean_squared_error: 1124520.8750 Epoch 390/642 141/141 [==============================] - 0s 3ms/step - loss: 1122999.1250 - mean_squared_error: 1122999.1250 Epoch 391/642 141/141 [==============================] - 0s 3ms/step - loss: 1120447.3750 - mean_squared_error: 1120447.3750 Epoch 392/642 141/141 [==============================] - 0s 2ms/step - loss: 1119283.2500 - mean_squared_error: 1119283.2500 Epoch 393/642 141/141 [==============================] - 0s 2ms/step - loss: 1117635.6250 - mean_squared_error: 1117635.6250 Epoch 394/642 141/141 [==============================] - 0s 2ms/step - loss: 1114395.8750 - mean_squared_error: 1114395.8750 Epoch 395/642 141/141 [==============================] - 0s 2ms/step - loss: 1113888.7500 - mean_squared_error: 1113888.7500 Epoch 396/642 141/141 [==============================] - 0s 2ms/step - loss: 1111546.7500 - mean_squared_error: 1111546.7500 Epoch 397/642 141/141 [==============================] - 0s 2ms/step - loss: 1110022.5000 - mean_squared_error: 1110022.5000 Epoch 398/642 141/141 [==============================] - 0s 2ms/step - loss: 1107712.3750 - mean_squared_error: 1107712.3750 Epoch 399/642 141/141 [==============================] - 0s 2ms/step - loss: 1106243.7500 - mean_squared_error: 1106243.7500 Epoch 400/642 141/141 [==============================] - 0s 2ms/step - loss: 1105458.1250 - mean_squared_error: 1105458.1250 Epoch 401/642 141/141 [==============================] - 0s 2ms/step - loss: 1102875.2500 - mean_squared_error: 1102875.2500 Epoch 402/642 141/141 [==============================] - 0s 2ms/step - loss: 1100005.3750 - mean_squared_error: 1100005.3750 Epoch 403/642 141/141 [==============================] - 0s 2ms/step - loss: 1099263.3750 - mean_squared_error: 1099263.3750 Epoch 404/642 141/141 [==============================] - 0s 2ms/step - loss: 1097288.8750 - mean_squared_error: 1097288.8750 Epoch 405/642 141/141 [==============================] - 0s 3ms/step - loss: 1096197.2500 - mean_squared_error: 1096197.2500 Epoch 406/642 141/141 [==============================] - 0s 2ms/step - loss: 1094893.6250 - mean_squared_error: 1094893.6250 Epoch 407/642 141/141 [==============================] - 0s 2ms/step - loss: 1092438.0000 - mean_squared_error: 1092438.0000 Epoch 408/642 141/141 [==============================] - 0s 3ms/step - loss: 1091122.8750 - mean_squared_error: 1091122.8750 Epoch 409/642 141/141 [==============================] - 0s 2ms/step - loss: 1089302.3750 - mean_squared_error: 1089302.3750 Epoch 410/642 141/141 [==============================] - 0s 2ms/step - loss: 1088425.1250 - mean_squared_error: 1088425.1250 Epoch 411/642 141/141 [==============================] - 0s 2ms/step - loss: 1086153.1250 - mean_squared_error: 1086153.1250 Epoch 412/642 141/141 [==============================] - 0s 3ms/step - loss: 1085561.3750 - mean_squared_error: 1085561.3750 Epoch 413/642 141/141 [==============================] - 0s 2ms/step - loss: 1083562.5000 - mean_squared_error: 1083562.5000 Epoch 414/642 141/141 [==============================] - 0s 2ms/step - loss: 1082682.0000 - mean_squared_error: 1082682.0000 Epoch 415/642 141/141 [==============================] - 0s 2ms/step - loss: 1080706.0000 - mean_squared_error: 1080706.0000 Epoch 416/642 141/141 [==============================] - 0s 2ms/step - loss: 1079317.1250 - mean_squared_error: 1079317.1250 Epoch 417/642 141/141 [==============================] - 0s 2ms/step - loss: 1077951.8750 - mean_squared_error: 1077951.8750 Epoch 418/642 141/141 [==============================] - 0s 3ms/step - loss: 1076458.6250 - mean_squared_error: 1076458.6250 Epoch 419/642 141/141 [==============================] - 0s 2ms/step - loss: 1075243.5000 - mean_squared_error: 1075243.5000 Epoch 420/642 141/141 [==============================] - 0s 3ms/step - loss: 1073429.8750 - mean_squared_error: 1073429.8750 Epoch 421/642 141/141 [==============================] - 0s 3ms/step - loss: 1072695.1250 - mean_squared_error: 1072695.1250 Epoch 422/642 141/141 [==============================] - 0s 3ms/step - loss: 1069857.7500 - mean_squared_error: 1069857.7500 Epoch 423/642 141/141 [==============================] - 0s 3ms/step - loss: 1070043.3750 - mean_squared_error: 1070043.3750 Epoch 424/642 141/141 [==============================] - 0s 3ms/step - loss: 1067993.6250 - mean_squared_error: 1067993.6250 Epoch 425/642 141/141 [==============================] - 0s 3ms/step - loss: 1066972.2500 - mean_squared_error: 1066972.2500 Epoch 426/642 141/141 [==============================] - 0s 3ms/step - loss: 1065319.5000 - mean_squared_error: 1065319.5000 Epoch 427/642 141/141 [==============================] - 0s 3ms/step - loss: 1063572.7500 - mean_squared_error: 1063572.7500 Epoch 428/642 141/141 [==============================] - 0s 3ms/step - loss: 1062555.2500 - mean_squared_error: 1062555.2500 Epoch 429/642 141/141 [==============================] - 0s 3ms/step - loss: 1062305.7500 - mean_squared_error: 1062305.7500 Epoch 430/642 141/141 [==============================] - 0s 3ms/step - loss: 1059880.5000 - mean_squared_error: 1059880.5000 Epoch 431/642 141/141 [==============================] - 0s 3ms/step - loss: 1058357.8750 - mean_squared_error: 1058357.8750 Epoch 432/642 141/141 [==============================] - 0s 3ms/step - loss: 1056431.3750 - mean_squared_error: 1056431.3750 Epoch 433/642 141/141 [==============================] - 0s 3ms/step - loss: 1054341.2500 - mean_squared_error: 1054341.2500 Epoch 434/642 141/141 [==============================] - 0s 3ms/step - loss: 1054298.0000 - mean_squared_error: 1054298.0000 Epoch 435/642 141/141 [==============================] - 0s 3ms/step - loss: 1051740.8750 - mean_squared_error: 1051740.8750 Epoch 436/642 141/141 [==============================] - 0s 3ms/step - loss: 1050358.2500 - mean_squared_error: 1050358.2500 Epoch 437/642 141/141 [==============================] - 0s 2ms/step - loss: 1049337.5000 - mean_squared_error: 1049337.5000 Epoch 438/642 141/141 [==============================] - 0s 3ms/step - loss: 1047793.4375 - mean_squared_error: 1047793.4375 Epoch 439/642 141/141 [==============================] - 0s 3ms/step - loss: 1046955.1250 - mean_squared_error: 1046955.1250 Epoch 440/642 141/141 [==============================] - 0s 2ms/step - loss: 1045564.6250 - mean_squared_error: 1045564.6250 Epoch 441/642 141/141 [==============================] - 0s 3ms/step - loss: 1044754.4375 - mean_squared_error: 1044754.4375 Epoch 442/642 141/141 [==============================] - 0s 3ms/step - loss: 1042585.3750 - mean_squared_error: 1042585.3750 Epoch 443/642 141/141 [==============================] - 0s 3ms/step - loss: 1042102.5000 - mean_squared_error: 1042102.5000 Epoch 444/642 141/141 [==============================] - 0s 3ms/step - loss: 1039932.0625 - mean_squared_error: 1039932.0625 Epoch 445/642 141/141 [==============================] - 0s 2ms/step - loss: 1039310.9375 - mean_squared_error: 1039310.9375 Epoch 446/642 141/141 [==============================] - 0s 2ms/step - loss: 1037037.9375 - mean_squared_error: 1037037.9375 Epoch 447/642 141/141 [==============================] - 0s 2ms/step - loss: 1037139.1875 - mean_squared_error: 1037139.1875 Epoch 448/642 141/141 [==============================] - 0s 2ms/step - loss: 1035062.1875 - mean_squared_error: 1035062.1875 Epoch 449/642 141/141 [==============================] - 0s 2ms/step - loss: 1034137.8125 - mean_squared_error: 1034137.8125 Epoch 450/642 141/141 [==============================] - 0s 2ms/step - loss: 1032946.0000 - mean_squared_error: 1032946.0000 Epoch 451/642 141/141 [==============================] - 0s 3ms/step - loss: 1030978.8125 - mean_squared_error: 1030978.8125 Epoch 452/642 141/141 [==============================] - 0s 2ms/step - loss: 1030684.8125 - mean_squared_error: 1030684.8125 Epoch 453/642 141/141 [==============================] - 0s 3ms/step - loss: 1029312.0625 - mean_squared_error: 1029312.0625 Epoch 454/642 141/141 [==============================] - 0s 2ms/step - loss: 1027848.3125 - mean_squared_error: 1027848.3125 Epoch 455/642 141/141 [==============================] - 0s 2ms/step - loss: 1026860.9375 - mean_squared_error: 1026860.9375 Epoch 456/642 141/141 [==============================] - 0s 2ms/step - loss: 1025290.5625 - mean_squared_error: 1025290.5625 Epoch 457/642 141/141 [==============================] - 0s 2ms/step - loss: 1024232.8125 - mean_squared_error: 1024232.8125 Epoch 458/642 141/141 [==============================] - 0s 2ms/step - loss: 1023205.0625 - mean_squared_error: 1023205.0625 Epoch 459/642 141/141 [==============================] - 0s 2ms/step - loss: 1022127.3125 - mean_squared_error: 1022127.3125 Epoch 460/642 141/141 [==============================] - 0s 3ms/step - loss: 1020702.3750 - mean_squared_error: 1020702.3750 Epoch 461/642 141/141 [==============================] - 0s 2ms/step - loss: 1019993.6875 - mean_squared_error: 1019993.6875 Epoch 462/642 141/141 [==============================] - 0s 2ms/step - loss: 1018140.3125 - mean_squared_error: 1018140.3125 Epoch 463/642 141/141 [==============================] - 0s 2ms/step - loss: 1017224.3125 - mean_squared_error: 1017224.3125 Epoch 464/642 141/141 [==============================] - 0s 2ms/step - loss: 1015388.3750 - mean_squared_error: 1015388.3750 Epoch 465/642 141/141 [==============================] - 0s 2ms/step - loss: 1014334.9375 - mean_squared_error: 1014334.9375 Epoch 466/642 141/141 [==============================] - 0s 3ms/step - loss: 1014353.9375 - mean_squared_error: 1014353.9375 Epoch 467/642 141/141 [==============================] - 0s 2ms/step - loss: 1012191.1250 - mean_squared_error: 1012191.1250 Epoch 468/642 141/141 [==============================] - 0s 2ms/step - loss: 1011417.7500 - mean_squared_error: 1011417.7500 Epoch 469/642 141/141 [==============================] - 0s 3ms/step - loss: 1010864.5625 - mean_squared_error: 1010864.5625 Epoch 470/642 141/141 [==============================] - 0s 2ms/step - loss: 1008851.8750 - mean_squared_error: 1008851.8750 Epoch 471/642 141/141 [==============================] - 0s 2ms/step - loss: 1008654.8125 - mean_squared_error: 1008654.8125 Epoch 472/642 141/141 [==============================] - 0s 3ms/step - loss: 1007070.7500 - mean_squared_error: 1007070.7500 Epoch 473/642 141/141 [==============================] - 0s 2ms/step - loss: 1006362.7500 - mean_squared_error: 1006362.7500 Epoch 474/642 141/141 [==============================] - 0s 3ms/step - loss: 1005048.3750 - mean_squared_error: 1005048.3750 Epoch 475/642 141/141 [==============================] - 0s 3ms/step - loss: 1003778.7500 - mean_squared_error: 1003778.7500 Epoch 476/642 141/141 [==============================] - 0s 2ms/step - loss: 1002200.6250 - mean_squared_error: 1002200.6250 Epoch 477/642 141/141 [==============================] - 0s 2ms/step - loss: 1002004.8125 - mean_squared_error: 1002004.8125 Epoch 478/642 141/141 [==============================] - 0s 2ms/step - loss: 1000000.3750 - mean_squared_error: 1000000.3750 Epoch 479/642 141/141 [==============================] - 0s 2ms/step - loss: 999610.8125 - mean_squared_error: 999610.8125 Epoch 480/642 141/141 [==============================] - 0s 2ms/step - loss: 997874.8125 - mean_squared_error: 997874.8125 Epoch 481/642 141/141 [==============================] - 0s 3ms/step - loss: 997870.8125 - mean_squared_error: 997870.8125 Epoch 482/642 141/141 [==============================] - 0s 3ms/step - loss: 996194.4375 - mean_squared_error: 996194.4375 Epoch 483/642 141/141 [==============================] - 0s 2ms/step - loss: 995121.0625 - mean_squared_error: 995121.0625 Epoch 484/642 141/141 [==============================] - 0s 3ms/step - loss: 994161.5625 - mean_squared_error: 994161.5625 Epoch 485/642 141/141 [==============================] - 0s 2ms/step - loss: 993191.8125 - mean_squared_error: 993191.8125 Epoch 486/642 141/141 [==============================] - 0s 2ms/step - loss: 992862.1250 - mean_squared_error: 992862.1250 Epoch 487/642 141/141 [==============================] - 0s 2ms/step - loss: 991608.2500 - mean_squared_error: 991608.2500 Epoch 488/642 141/141 [==============================] - 0s 2ms/step - loss: 990016.3125 - mean_squared_error: 990016.3125 Epoch 489/642 141/141 [==============================] - 0s 3ms/step - loss: 988668.2500 - mean_squared_error: 988668.2500 Epoch 490/642 141/141 [==============================] - 0s 2ms/step - loss: 988770.7500 - mean_squared_error: 988770.7500 Epoch 491/642 141/141 [==============================] - 0s 2ms/step - loss: 986904.6875 - mean_squared_error: 986904.6875 Epoch 492/642 141/141 [==============================] - 0s 3ms/step - loss: 986807.5000 - mean_squared_error: 986807.5000 Epoch 493/642 141/141 [==============================] - 0s 2ms/step - loss: 985104.3750 - mean_squared_error: 985104.3750 Epoch 494/642 141/141 [==============================] - 0s 2ms/step - loss: 984296.2500 - mean_squared_error: 984296.2500 Epoch 495/642 141/141 [==============================] - 0s 2ms/step - loss: 982540.5000 - mean_squared_error: 982540.5000 Epoch 496/642 141/141 [==============================] - 0s 2ms/step - loss: 982901.7500 - mean_squared_error: 982901.7500 Epoch 497/642 141/141 [==============================] - 0s 2ms/step - loss: 981042.1875 - mean_squared_error: 981042.1875 Epoch 498/642 141/141 [==============================] - 0s 2ms/step - loss: 980698.8125 - mean_squared_error: 980698.8125 Epoch 499/642 141/141 [==============================] - 0s 2ms/step - loss: 978920.6875 - mean_squared_error: 978920.6875 Epoch 500/642 141/141 [==============================] - 0s 3ms/step - loss: 979115.2500 - mean_squared_error: 979115.2500 Epoch 501/642 141/141 [==============================] - 0s 2ms/step - loss: 977722.9375 - mean_squared_error: 977722.9375 Epoch 502/642 141/141 [==============================] - 0s 2ms/step - loss: 976688.5625 - mean_squared_error: 976688.5625 Epoch 503/642 141/141 [==============================] - 0s 3ms/step - loss: 976543.3750 - mean_squared_error: 976543.3750 Epoch 504/642 141/141 [==============================] - 0s 2ms/step - loss: 975655.8125 - mean_squared_error: 975655.8125 Epoch 505/642 141/141 [==============================] - 0s 2ms/step - loss: 972960.7500 - mean_squared_error: 972960.7500 Epoch 506/642 141/141 [==============================] - 0s 2ms/step - loss: 973813.1875 - mean_squared_error: 973813.1875 Epoch 507/642 141/141 [==============================] - 0s 2ms/step - loss: 971788.7500 - mean_squared_error: 971788.7500 Epoch 508/642 141/141 [==============================] - 0s 3ms/step - loss: 971110.3125 - mean_squared_error: 971110.3125 Epoch 509/642 141/141 [==============================] - 0s 2ms/step - loss: 970975.1250 - mean_squared_error: 970975.1250 Epoch 510/642 141/141 [==============================] - 0s 3ms/step - loss: 969814.6875 - mean_squared_error: 969814.6875 Epoch 511/642 141/141 [==============================] - 0s 2ms/step - loss: 969039.8750 - mean_squared_error: 969039.8750 Epoch 512/642 141/141 [==============================] - 0s 2ms/step - loss: 967945.8125 - mean_squared_error: 967945.8125 Epoch 513/642 141/141 [==============================] - 0s 3ms/step - loss: 967364.5000 - mean_squared_error: 967364.5000 Epoch 514/642 141/141 [==============================] - 0s 2ms/step - loss: 966188.6250 - mean_squared_error: 966188.6250 Epoch 515/642 141/141 [==============================] - 0s 2ms/step - loss: 965728.2500 - mean_squared_error: 965728.2500 Epoch 516/642 141/141 [==============================] - 0s 2ms/step - loss: 964275.0000 - mean_squared_error: 964275.0000 Epoch 517/642 141/141 [==============================] - 0s 2ms/step - loss: 964115.4375 - mean_squared_error: 964115.4375 Epoch 518/642 141/141 [==============================] - 0s 3ms/step - loss: 963627.0000 - mean_squared_error: 963627.0000 Epoch 519/642 141/141 [==============================] - 0s 2ms/step - loss: 961572.6250 - mean_squared_error: 961572.6250 Epoch 520/642 141/141 [==============================] - 0s 2ms/step - loss: 960985.3125 - mean_squared_error: 960985.3125 Epoch 521/642 141/141 [==============================] - 0s 2ms/step - loss: 960894.8750 - mean_squared_error: 960894.8750 Epoch 522/642 141/141 [==============================] - 0s 2ms/step - loss: 959177.2500 - mean_squared_error: 959177.2500 Epoch 523/642 141/141 [==============================] - 0s 3ms/step - loss: 958856.7500 - mean_squared_error: 958856.7500 Epoch 524/642 141/141 [==============================] - 0s 2ms/step - loss: 958432.8125 - mean_squared_error: 958432.8125 Epoch 525/642 141/141 [==============================] - 0s 2ms/step - loss: 957599.8750 - mean_squared_error: 957599.8750 Epoch 526/642 141/141 [==============================] - 0s 2ms/step - loss: 957226.1875 - mean_squared_error: 957226.1875 Epoch 527/642 141/141 [==============================] - 0s 2ms/step - loss: 955826.3750 - mean_squared_error: 955826.3750 Epoch 528/642 141/141 [==============================] - 0s 2ms/step - loss: 954711.8125 - mean_squared_error: 954711.8125 Epoch 529/642 141/141 [==============================] - 0s 2ms/step - loss: 954175.1875 - mean_squared_error: 954175.1875 Epoch 530/642 141/141 [==============================] - 0s 2ms/step - loss: 953292.1250 - mean_squared_error: 953292.1250 Epoch 531/642 141/141 [==============================] - 0s 3ms/step - loss: 951631.3750 - mean_squared_error: 951631.3750 Epoch 532/642 141/141 [==============================] - 0s 2ms/step - loss: 952252.0000 - mean_squared_error: 952252.0000 Epoch 533/642 141/141 [==============================] - 0s 2ms/step - loss: 951219.0000 - mean_squared_error: 951219.0000 Epoch 534/642 141/141 [==============================] - 0s 2ms/step - loss: 950121.0625 - mean_squared_error: 950121.0625 Epoch 535/642 141/141 [==============================] - 0s 2ms/step - loss: 949162.0625 - mean_squared_error: 949162.0625 Epoch 536/642 141/141 [==============================] - 0s 2ms/step - loss: 948939.6875 - mean_squared_error: 948939.6875 Epoch 537/642 141/141 [==============================] - 0s 2ms/step - loss: 947883.3750 - mean_squared_error: 947883.3750 Epoch 538/642 141/141 [==============================] - 0s 3ms/step - loss: 946760.6875 - mean_squared_error: 946760.6875 Epoch 539/642 141/141 [==============================] - 0s 2ms/step - loss: 945681.5000 - mean_squared_error: 945681.5000 Epoch 540/642 141/141 [==============================] - 0s 3ms/step - loss: 946618.0000 - mean_squared_error: 946618.0000 Epoch 541/642 141/141 [==============================] - 0s 2ms/step - loss: 944869.6875 - mean_squared_error: 944869.6875 Epoch 542/642 141/141 [==============================] - 0s 2ms/step - loss: 943791.3125 - mean_squared_error: 943791.3125 Epoch 543/642 141/141 [==============================] - 0s 2ms/step - loss: 942734.6250 - mean_squared_error: 942734.6250 Epoch 544/642 141/141 [==============================] - 0s 2ms/step - loss: 942521.1250 - mean_squared_error: 942521.1250 Epoch 545/642 141/141 [==============================] - 0s 2ms/step - loss: 941651.1250 - mean_squared_error: 941651.1250 Epoch 546/642 141/141 [==============================] - 0s 2ms/step - loss: 941040.0000 - mean_squared_error: 941040.0000 Epoch 547/642 141/141 [==============================] - 0s 2ms/step - loss: 940432.3750 - mean_squared_error: 940432.3750 Epoch 548/642 141/141 [==============================] - 0s 3ms/step - loss: 939693.5000 - mean_squared_error: 939693.5000 Epoch 549/642 141/141 [==============================] - 0s 2ms/step - loss: 938793.2500 - mean_squared_error: 938793.2500 Epoch 550/642 141/141 [==============================] - 0s 2ms/step - loss: 938121.1250 - mean_squared_error: 938121.1250 Epoch 551/642 141/141 [==============================] - 0s 2ms/step - loss: 937184.4375 - mean_squared_error: 937184.4375 Epoch 552/642 141/141 [==============================] - 0s 2ms/step - loss: 936039.5000 - mean_squared_error: 936039.5000 Epoch 553/642 141/141 [==============================] - 0s 2ms/step - loss: 935051.1875 - mean_squared_error: 935051.1875 Epoch 554/642 141/141 [==============================] - 0s 2ms/step - loss: 935040.8750 - mean_squared_error: 935040.8750 Epoch 555/642 141/141 [==============================] - 0s 2ms/step - loss: 934051.0625 - mean_squared_error: 934051.0625 Epoch 556/642 141/141 [==============================] - 0s 2ms/step - loss: 932602.7500 - mean_squared_error: 932602.7500 Epoch 557/642 141/141 [==============================] - 0s 2ms/step - loss: 932546.9375 - mean_squared_error: 932546.9375 Epoch 558/642 141/141 [==============================] - 0s 2ms/step - loss: 931334.3750 - mean_squared_error: 931334.3750 Epoch 559/642 141/141 [==============================] - 0s 2ms/step - loss: 931450.3125 - mean_squared_error: 931450.3125 Epoch 560/642 141/141 [==============================] - 0s 2ms/step - loss: 930255.1250 - mean_squared_error: 930255.1250 Epoch 561/642 141/141 [==============================] - 0s 2ms/step - loss: 929733.0625 - mean_squared_error: 929733.0625 Epoch 562/642 141/141 [==============================] - 0s 2ms/step - loss: 928766.5625 - mean_squared_error: 928766.5625 Epoch 563/642 141/141 [==============================] - 0s 2ms/step - loss: 927638.4375 - mean_squared_error: 927638.4375 Epoch 564/642 141/141 [==============================] - 0s 3ms/step - loss: 927984.3125 - mean_squared_error: 927984.3125 Epoch 565/642 141/141 [==============================] - 0s 2ms/step - loss: 926731.3750 - mean_squared_error: 926731.3750 Epoch 566/642 141/141 [==============================] - 0s 3ms/step - loss: 925710.5000 - mean_squared_error: 925710.5000 Epoch 567/642 141/141 [==============================] - 0s 2ms/step - loss: 925414.7500 - mean_squared_error: 925414.7500 Epoch 568/642 141/141 [==============================] - 0s 2ms/step - loss: 924973.8125 - mean_squared_error: 924973.8125 Epoch 569/642 141/141 [==============================] - 0s 3ms/step - loss: 923737.3125 - mean_squared_error: 923737.3125 Epoch 570/642 141/141 [==============================] - 0s 2ms/step - loss: 923051.1250 - mean_squared_error: 923051.1250 Epoch 571/642 141/141 [==============================] - 0s 2ms/step - loss: 922085.6875 - mean_squared_error: 922085.6875 Epoch 572/642 141/141 [==============================] - 0s 2ms/step - loss: 921419.0625 - mean_squared_error: 921419.0625 Epoch 573/642 141/141 [==============================] - 0s 2ms/step - loss: 920565.3750 - mean_squared_error: 920565.3750 Epoch 574/642 141/141 [==============================] - 0s 3ms/step - loss: 920424.2500 - mean_squared_error: 920424.2500 Epoch 575/642 141/141 [==============================] - 0s 2ms/step - loss: 919964.0625 - mean_squared_error: 919964.0625 Epoch 576/642 141/141 [==============================] - 0s 2ms/step - loss: 919072.5625 - mean_squared_error: 919072.5625 Epoch 577/642 141/141 [==============================] - 0s 2ms/step - loss: 918554.9375 - mean_squared_error: 918554.9375 Epoch 578/642 141/141 [==============================] - 0s 2ms/step - loss: 917435.8750 - mean_squared_error: 917435.8750 Epoch 579/642 141/141 [==============================] - 0s 2ms/step - loss: 917085.0000 - mean_squared_error: 917085.0000 Epoch 580/642 141/141 [==============================] - 0s 2ms/step - loss: 916449.8750 - mean_squared_error: 916449.8750 Epoch 581/642 141/141 [==============================] - 0s 2ms/step - loss: 915848.1875 - mean_squared_error: 915848.1875 Epoch 582/642 141/141 [==============================] - 0s 2ms/step - loss: 915295.8125 - mean_squared_error: 915295.8125 Epoch 583/642 141/141 [==============================] - 0s 2ms/step - loss: 914528.3750 - mean_squared_error: 914528.3750 Epoch 584/642 141/141 [==============================] - 0s 2ms/step - loss: 913277.7500 - mean_squared_error: 913277.7500 Epoch 585/642 141/141 [==============================] - 0s 2ms/step - loss: 913268.0625 - mean_squared_error: 913268.0625 Epoch 586/642 141/141 [==============================] - 0s 2ms/step - loss: 913132.9375 - mean_squared_error: 913132.9375 Epoch 587/642 141/141 [==============================] - 0s 2ms/step - loss: 911509.5000 - mean_squared_error: 911509.5000 Epoch 588/642 141/141 [==============================] - 0s 2ms/step - loss: 911473.4375 - mean_squared_error: 911473.4375 Epoch 589/642 141/141 [==============================] - 0s 2ms/step - loss: 910123.8750 - mean_squared_error: 910123.8750 Epoch 590/642 141/141 [==============================] - 0s 2ms/step - loss: 909868.6875 - mean_squared_error: 909868.6875 Epoch 591/642 141/141 [==============================] - 0s 2ms/step - loss: 908900.8750 - mean_squared_error: 908900.8750 Epoch 592/642 141/141 [==============================] - 0s 2ms/step - loss: 908416.3750 - mean_squared_error: 908416.3750 Epoch 593/642 141/141 [==============================] - 0s 3ms/step - loss: 907239.4375 - mean_squared_error: 907239.4375 Epoch 594/642 141/141 [==============================] - 0s 2ms/step - loss: 905638.9375 - mean_squared_error: 905638.9375 Epoch 595/642 141/141 [==============================] - 0s 2ms/step - loss: 905806.4375 - mean_squared_error: 905806.4375 Epoch 596/642 141/141 [==============================] - 0s 3ms/step - loss: 904841.8750 - mean_squared_error: 904841.8750 Epoch 597/642 141/141 [==============================] - 0s 2ms/step - loss: 903794.9375 - mean_squared_error: 903794.9375 Epoch 598/642 141/141 [==============================] - 0s 3ms/step - loss: 903659.8750 - mean_squared_error: 903659.8750 Epoch 599/642 141/141 [==============================] - 0s 2ms/step - loss: 902401.0625 - mean_squared_error: 902401.0625 Epoch 600/642 141/141 [==============================] - 0s 2ms/step - loss: 901994.2500 - mean_squared_error: 901994.2500 Epoch 601/642 141/141 [==============================] - 0s 2ms/step - loss: 900788.9375 - mean_squared_error: 900788.9375 Epoch 602/642 141/141 [==============================] - 0s 2ms/step - loss: 900705.0000 - mean_squared_error: 900705.0000 Epoch 603/642 141/141 [==============================] - 0s 2ms/step - loss: 899271.0625 - mean_squared_error: 899271.0625 Epoch 604/642 141/141 [==============================] - 0s 2ms/step - loss: 899148.3125 - mean_squared_error: 899148.3125 Epoch 605/642 141/141 [==============================] - 0s 2ms/step - loss: 898859.8750 - mean_squared_error: 898859.8750 Epoch 606/642 141/141 [==============================] - 0s 3ms/step - loss: 897135.9375 - mean_squared_error: 897135.9375 Epoch 607/642 141/141 [==============================] - 0s 2ms/step - loss: 897710.0625 - mean_squared_error: 897710.0625 Epoch 608/642 141/141 [==============================] - 0s 2ms/step - loss: 896665.6875 - mean_squared_error: 896665.6875 Epoch 609/642 141/141 [==============================] - 0s 3ms/step - loss: 896197.7500 - mean_squared_error: 896197.7500 Epoch 610/642 141/141 [==============================] - 0s 2ms/step - loss: 895043.0000 - mean_squared_error: 895043.0000 Epoch 611/642 141/141 [==============================] - 0s 3ms/step - loss: 894833.1875 - mean_squared_error: 894833.1875 Epoch 612/642 141/141 [==============================] - 0s 2ms/step - loss: 894649.5000 - mean_squared_error: 894649.5000 Epoch 613/642 141/141 [==============================] - 0s 2ms/step - loss: 893499.6875 - mean_squared_error: 893499.6875 Epoch 614/642 141/141 [==============================] - 0s 2ms/step - loss: 893746.1875 - mean_squared_error: 893746.1875 Epoch 615/642 141/141 [==============================] - 0s 2ms/step - loss: 892295.6250 - mean_squared_error: 892295.6250 Epoch 616/642 141/141 [==============================] - 0s 2ms/step - loss: 891191.1250 - mean_squared_error: 891191.1250 Epoch 617/642 141/141 [==============================] - 0s 2ms/step - loss: 891978.2500 - mean_squared_error: 891978.2500 Epoch 618/642 141/141 [==============================] - 0s 2ms/step - loss: 890250.5625 - mean_squared_error: 890250.5625 Epoch 619/642 141/141 [==============================] - 0s 2ms/step - loss: 890312.5000 - mean_squared_error: 890312.5000 Epoch 620/642 141/141 [==============================] - 0s 2ms/step - loss: 889606.5000 - mean_squared_error: 889606.5000 Epoch 621/642 141/141 [==============================] - 0s 2ms/step - loss: 888485.3750 - mean_squared_error: 888485.3750 Epoch 622/642 141/141 [==============================] - 0s 3ms/step - loss: 888559.5625 - mean_squared_error: 888559.5625 Epoch 623/642 141/141 [==============================] - 0s 2ms/step - loss: 888202.6250 - mean_squared_error: 888202.6250 Epoch 624/642 141/141 [==============================] - 0s 2ms/step - loss: 887062.3125 - mean_squared_error: 887062.3125 Epoch 625/642 141/141 [==============================] - 0s 3ms/step - loss: 887392.5625 - mean_squared_error: 887392.5625 Epoch 626/642 141/141 [==============================] - 0s 3ms/step - loss: 885680.0625 - mean_squared_error: 885680.0625 Epoch 627/642 141/141 [==============================] - 0s 3ms/step - loss: 885987.0000 - mean_squared_error: 885987.0000 Epoch 628/642 141/141 [==============================] - 0s 2ms/step - loss: 884339.0625 - mean_squared_error: 884339.0625 Epoch 629/642 141/141 [==============================] - 0s 2ms/step - loss: 884512.3125 - mean_squared_error: 884512.3125 Epoch 630/642 141/141 [==============================] - 0s 2ms/step - loss: 884688.9375 - mean_squared_error: 884688.9375 Epoch 631/642 141/141 [==============================] - 0s 2ms/step - loss: 882766.9375 - mean_squared_error: 882766.9375 Epoch 632/642 141/141 [==============================] - 0s 2ms/step - loss: 884023.3125 - mean_squared_error: 884023.3125 Epoch 633/642 141/141 [==============================] - 0s 2ms/step - loss: 881770.2500 - mean_squared_error: 881770.2500 Epoch 634/642 141/141 [==============================] - 0s 2ms/step - loss: 881833.7500 - mean_squared_error: 881833.7500 Epoch 635/642 141/141 [==============================] - 0s 2ms/step - loss: 880767.1250 - mean_squared_error: 880767.1250 Epoch 636/642 141/141 [==============================] - 0s 2ms/step - loss: 881024.8125 - mean_squared_error: 881024.8125 Epoch 637/642 141/141 [==============================] - 0s 2ms/step - loss: 880344.6875 - mean_squared_error: 880344.6875 Epoch 638/642 141/141 [==============================] - 0s 2ms/step - loss: 880077.5000 - mean_squared_error: 880077.5000 Epoch 639/642 141/141 [==============================] - 0s 2ms/step - loss: 878534.2500 - mean_squared_error: 878534.2500 Epoch 640/642 141/141 [==============================] - 0s 2ms/step - loss: 879117.0000 - mean_squared_error: 879117.0000 Epoch 641/642 141/141 [==============================] - 0s 2ms/step - loss: 877782.3750 - mean_squared_error: 877782.3750 Epoch 642/642 141/141 [==============================] - 0s 2ms/step - loss: 877851.2500 - mean_squared_error: 877851.2500 INFO:tensorflow:Assets written to: ./diamond/best_model/assets
# Predict with the best model
predicted_y = automl.predict(X_test)
# Test model results
print("Train loss and mean_squared_error:", automl.evaluate(x=X_train, y=y_train))
print("Test loss and mean_squared_error:", automl.evaluate(x=X_test, y=y_test))
47/47 [==============================] - 0s 2ms/step 141/141 [==============================] - 0s 1ms/step - loss: 916079.8125 - mean_squared_error: 916079.8125 Train loss and mean_squared_error: [916079.8125, 916079.8125] 47/47 [==============================] - 0s 2ms/step - loss: 1784458.1250 - mean_squared_error: 1784458.1250 Test loss and mean_squared_error: [1784458.125, 1784458.125]
# Extract best model. This returns model as standard tensorflow object
best_model = automl.export_model()
# Check model structure
best_model.summary()
Model: "model" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= input_1 (InputLayer) [(None, 7)] 0 _________________________________________________________________ multi_category_encoding (Mul (None, 7) 0 _________________________________________________________________ normalization (Normalization (None, 7) 15 _________________________________________________________________ dense (Dense) (None, 1024) 8192 _________________________________________________________________ re_lu (ReLU) (None, 1024) 0 _________________________________________________________________ dense_1 (Dense) (None, 256) 262400 _________________________________________________________________ re_lu_1 (ReLU) (None, 256) 0 _________________________________________________________________ regression_head_1 (Dense) (None, 1) 257 ================================================================= Total params: 270,864 Trainable params: 270,849 Non-trainable params: 15 _________________________________________________________________
# Save model to file
best_model.save('best_model')
INFO:tensorflow:Assets written to: best_model/assets