# 导入依赖
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
# 读入数据集
df = pd.read_csv('insurance.csv')
df.head()
| age | sex | bmi | children | smoker | region | charges | |
|---|---|---|---|---|---|---|---|
| 0 | 19 | female | 27.900 | 0 | yes | southwest | 16884.92400 |
| 1 | 18 | male | 33.770 | 1 | no | southeast | 1725.55230 |
| 2 | 28 | male | 33.000 | 3 | no | southeast | 4449.46200 |
| 3 | 33 | male | 22.705 | 0 | no | northwest | 21984.47061 |
| 4 | 32 | male | 28.880 | 0 | no | northwest | 3866.85520 |
# 检查是否有空值
df.isnull().sum()
age 0 sex 0 bmi 0 children 0 smoker 0 region 0 charges 0 dtype: int64
# 在散点图上绘制医疗费用收费和年龄的关系，色调为吸烟者
plt.figure(figsize = (14,7))
sns.scatterplot(x=df['age'] ,y=df['charges'] ,hue=df['smoker'] ,palette = 'bright' ,s=50)
plt.xticks(color='red' ,size=12)
plt.yticks(color='red' ,size= 12)
plt.xlabel('AGE' ,color='purple' ,size=17)
plt.ylabel('CHARGES' ,color='purple' ,size=17);
# 绘制绘制医疗费用收费和BMI的散点图，色调为“吸烟者”
plt.figure(figsize = (14,7))
sns.scatterplot(x=df['bmi'] ,y=df['charges'] ,hue=df['smoker'] ,palette = 'bright' ,s=50)
plt.xticks(color='red' ,size=12)
plt.yticks(color='red' ,size= 12)
plt.xlabel('BMI' ,color='purple' ,size=17)
plt.ylabel('CHARGES' ,color='purple' ,size=17);
df['region'].unique()
array(['southwest', 'southeast', 'northwest', 'northeast'], dtype=object)
# 检查不同地区的医疗费用关系
plt.figure(dpi=150)
sns.boxplot(x=df['region'] ,y=df['charges'] )
plt.xticks(color='red' ,size=12)
plt.yticks(color='red' ,size= 12)
plt.xlabel('REGION' ,color='purple' ,size=17)
plt.ylabel('CHARGES' ,color='purple' ,size=17);
# 检查费用分布
plt.figure(dpi=100)
sns.histplot(x=df['charges'] ,color='green')
plt.xticks(color='red' ,size=8)
plt.yticks(color='red' ,size= 8);
# 对所有分类列进行 one-hot 编码
df2 = pd.get_dummies(df ,drop_first = True)
df2.head()
| age | bmi | children | charges | sex_male | smoker_yes | region_northwest | region_southeast | region_southwest | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 19 | 27.900 | 0 | 16884.92400 | 0 | 1 | 0 | 0 | 1 |
| 1 | 18 | 33.770 | 1 | 1725.55230 | 1 | 0 | 0 | 1 | 0 |
| 2 | 28 | 33.000 | 3 | 4449.46200 | 1 | 0 | 0 | 1 | 0 |
| 3 | 33 | 22.705 | 0 | 21984.47061 | 1 | 0 | 1 | 0 | 0 |
| 4 | 32 | 28.880 | 0 | 3866.85520 | 1 | 0 | 1 | 0 | 0 |
# 检查相关性
df2.corr()['charges']
age 0.299008 bmi 0.198341 children 0.067998 charges 1.000000 sex_male 0.057292 smoker_yes 0.787251 region_northwest -0.039905 region_southeast 0.073982 region_southwest -0.043210 Name: charges, dtype: float64
# 绘制上面的热图
plt.figure(dpi=160)
sns.heatmap(np.round(df2.corr() ,2) ,annot=True ,cmap='viridis');
# 定义特征和标签
X = df2.drop('charges' ,axis=1)
y = df2['charges']
# 进行训练和测试分离
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
len(X_train) ,len(y_test)
(1070, 268)
# 进行一些预处理
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
scaled_X_train = scaler.fit_transform(X_train)
scaled_X_test = scaler.transform(X_test)
from sklearn.linear_model import LinearRegression
lr = LinearRegression()
lr.fit(scaled_X_train ,y_train)
LinearRegression()In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
LinearRegression()
# 检查性能
from sklearn.metrics import mean_squared_error ,r2_score
lr.score(scaled_X_test ,y_test)
0.7835929767120722
r2_score(y_test ,lr.predict(scaled_X_test))
0.7835929767120722
from sklearn.ensemble import RandomForestRegressor
rf = RandomForestRegressor(n_estimators = 140,
criterion = 'squared_error',
random_state = 42,
n_jobs = -1)
rf.fit(scaled_X_train,y_train)
RandomForestRegressor(n_estimators=140, n_jobs=-1, random_state=42)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
RandomForestRegressor(n_estimators=140, n_jobs=-1, random_state=42)
forest_test_pred = rf.predict(scaled_X_test)
r2_score(y_pred = forest_test_pred ,y_true = y_test)
0.8650776528213561
from sklearn.svm import SVR
from sklearn.model_selection import GridSearchCV
svr = SVR()
# 定义 gridsearchcv 的参数网格
param_grid = {'C':[0.001,0.01,0.1,0.5,1],
'kernel':['linear','rbf','poly'],
'gamma':['scale','auto'],
'degree':[2,3,4],
'epsilon':[0,0.01,0.1,0.5,1,2]}
grid = GridSearchCV(svr,param_grid=param_grid)
grid.fit(scaled_X_train,y_train)
GridSearchCV(estimator=SVR(),
param_grid={'C': [0.001, 0.01, 0.1, 0.5, 1], 'degree': [2, 3, 4],
'epsilon': [0, 0.01, 0.1, 0.5, 1, 2],
'gamma': ['scale', 'auto'],
'kernel': ['linear', 'rbf', 'poly']})In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. GridSearchCV(estimator=SVR(),
param_grid={'C': [0.001, 0.01, 0.1, 0.5, 1], 'degree': [2, 3, 4],
'epsilon': [0, 0.01, 0.1, 0.5, 1, 2],
'gamma': ['scale', 'auto'],
'kernel': ['linear', 'rbf', 'poly']})SVR()
SVR()
# 检查最佳参数
grid.best_params_
{'C': 1, 'degree': 2, 'epsilon': 2, 'gamma': 'scale', 'kernel': 'linear'}
grid_preds = grid.predict(scaled_X_test)
r2_score(y_true = y_test ,y_pred=grid_preds)
0.019799220771840598
from sklearn.ensemble import GradientBoostingRegressor
gb = GradientBoostingRegressor(random_state = 42)
gb.fit(scaled_X_train ,y_train)
GradientBoostingRegressor(random_state=42)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
GradientBoostingRegressor(random_state=42)
gb_preds = gb.predict(scaled_X_test)
r2_score(y_true = y_test ,y_pred = gb_preds)
0.8792571359795264
import tensorflow as tf
scaled_X_train.shape
(1070, 8)
import tensorflow as tf
# Set the random seed for reproducibility
tf.random.set_seed(42)
# Define the model
model = tf.keras.Sequential([
tf.keras.layers.Dense(32, activation='relu'), # First hidden layer with 32 neurons and ReLU activation
tf.keras.layers.Dense(1) # Output layer with 1 neuron (for regression)
])
# Compile the model
model.compile(
loss=tf.keras.losses.MeanAbsoluteError(), # Using Mean Absolute Error for loss
optimizer=tf.keras.optimizers.Adam(learning_rate=0.1), # Adam optimizer with a learning rate of 0.1
metrics=['mae'] # Tracking Mean Absolute Error as a metric
)
# Train the model
model.fit(
scaled_X_train,
y_train,
epochs=500,
validation_data=(scaled_X_test, y_test)
)
Epoch 1/500 34/34 [==============================] - 1s 5ms/step - loss: 13176.4053 - mae: 13176.4053 - val_loss: 12342.8604 - val_mae: 12342.8604 Epoch 2/500 34/34 [==============================] - 0s 1ms/step - loss: 11706.1855 - mae: 11706.1855 - val_loss: 9990.0645 - val_mae: 9990.0645 Epoch 3/500 34/34 [==============================] - 0s 2ms/step - loss: 8708.5283 - mae: 8708.5283 - val_loss: 6905.4297 - val_mae: 6905.4297 Epoch 4/500 34/34 [==============================] - 0s 2ms/step - loss: 5669.3076 - mae: 5669.3076 - val_loss: 4656.5684 - val_mae: 4656.5684 Epoch 5/500 34/34 [==============================] - 0s 2ms/step - loss: 4149.5723 - mae: 4149.5723 - val_loss: 3637.5278 - val_mae: 3637.5278 Epoch 6/500 34/34 [==============================] - 0s 2ms/step - loss: 3684.2610 - mae: 3684.2610 - val_loss: 3394.3816 - val_mae: 3394.3816 Epoch 7/500 34/34 [==============================] - 0s 2ms/step - loss: 3543.0925 - mae: 3543.0925 - val_loss: 3277.0593 - val_mae: 3277.0593 Epoch 8/500 34/34 [==============================] - 0s 2ms/step - loss: 3464.1858 - mae: 3464.1858 - val_loss: 3179.0710 - val_mae: 3179.0710 Epoch 9/500 34/34 [==============================] - 0s 2ms/step - loss: 3390.9805 - mae: 3390.9805 - val_loss: 3128.5288 - val_mae: 3128.5288 Epoch 10/500 34/34 [==============================] - 0s 2ms/step - loss: 3347.2905 - mae: 3347.2905 - val_loss: 3054.6538 - val_mae: 3054.6538 Epoch 11/500 34/34 [==============================] - 0s 2ms/step - loss: 3298.8059 - mae: 3298.8059 - val_loss: 3021.8582 - val_mae: 3021.8582 Epoch 12/500 34/34 [==============================] - 0s 2ms/step - loss: 3245.7239 - mae: 3245.7239 - val_loss: 2963.4739 - val_mae: 2963.4739 Epoch 13/500 34/34 [==============================] - 0s 2ms/step - loss: 3210.4692 - mae: 3210.4692 - val_loss: 2907.2910 - val_mae: 2907.2910 Epoch 14/500 34/34 [==============================] - 0s 2ms/step - loss: 3179.5813 - mae: 3179.5813 - val_loss: 2880.0723 - val_mae: 2880.0723 Epoch 15/500 34/34 [==============================] - 0s 2ms/step - loss: 3152.4485 - mae: 3152.4485 - val_loss: 2855.9231 - val_mae: 2855.9231 Epoch 16/500 34/34 [==============================] - 0s 2ms/step - loss: 3140.8130 - mae: 3140.8130 - val_loss: 2866.1743 - val_mae: 2866.1743 Epoch 17/500 34/34 [==============================] - 0s 2ms/step - loss: 3133.6399 - mae: 3133.6399 - val_loss: 2838.6018 - val_mae: 2838.6018 Epoch 18/500 34/34 [==============================] - 0s 2ms/step - loss: 3093.8535 - mae: 3093.8535 - val_loss: 2822.5027 - val_mae: 2822.5027 Epoch 19/500 34/34 [==============================] - 0s 2ms/step - loss: 3074.4148 - mae: 3074.4148 - val_loss: 2802.2068 - val_mae: 2802.2068 Epoch 20/500 34/34 [==============================] - 0s 2ms/step - loss: 3036.4634 - mae: 3036.4634 - val_loss: 2768.5417 - val_mae: 2768.5417 Epoch 21/500 34/34 [==============================] - 0s 2ms/step - loss: 3009.5781 - mae: 3009.5781 - val_loss: 2767.8345 - val_mae: 2767.8345 Epoch 22/500 34/34 [==============================] - 0s 2ms/step - loss: 2991.8489 - mae: 2991.8489 - val_loss: 2776.9192 - val_mae: 2776.9192 Epoch 23/500 34/34 [==============================] - 0s 2ms/step - loss: 2967.2141 - mae: 2967.2141 - val_loss: 2740.1831 - val_mae: 2740.1831 Epoch 24/500 34/34 [==============================] - 0s 1ms/step - loss: 2918.3477 - mae: 2918.3477 - val_loss: 2701.7727 - val_mae: 2701.7727 Epoch 25/500 34/34 [==============================] - 0s 2ms/step - loss: 2885.5771 - mae: 2885.5771 - val_loss: 2691.2104 - val_mae: 2691.2104 Epoch 26/500 34/34 [==============================] - 0s 2ms/step - loss: 2853.4263 - mae: 2853.4263 - val_loss: 2690.2424 - val_mae: 2690.2424 Epoch 27/500 34/34 [==============================] - 0s 2ms/step - loss: 2824.5645 - mae: 2824.5645 - val_loss: 2648.8665 - val_mae: 2648.8665 Epoch 28/500 34/34 [==============================] - 0s 2ms/step - loss: 2787.7375 - mae: 2787.7375 - val_loss: 2627.9719 - val_mae: 2627.9719 Epoch 29/500 34/34 [==============================] - 0s 2ms/step - loss: 2762.5017 - mae: 2762.5017 - val_loss: 2613.2471 - val_mae: 2613.2471 Epoch 30/500 34/34 [==============================] - 0s 2ms/step - loss: 2717.3730 - mae: 2717.3730 - val_loss: 2591.0627 - val_mae: 2591.0627 Epoch 31/500 34/34 [==============================] - 0s 2ms/step - loss: 2696.9280 - mae: 2696.9280 - val_loss: 2583.0713 - val_mae: 2583.0713 Epoch 32/500 34/34 [==============================] - 0s 2ms/step - loss: 2668.2810 - mae: 2668.2810 - val_loss: 2560.2952 - val_mae: 2560.2952 Epoch 33/500 34/34 [==============================] - 0s 2ms/step - loss: 2635.6670 - mae: 2635.6670 - val_loss: 2542.4531 - val_mae: 2542.4531 Epoch 34/500 34/34 [==============================] - 0s 2ms/step - loss: 2621.8315 - mae: 2621.8315 - val_loss: 2525.4246 - val_mae: 2525.4246 Epoch 35/500 34/34 [==============================] - 0s 2ms/step - loss: 2602.8113 - mae: 2602.8113 - val_loss: 2522.4045 - val_mae: 2522.4045 Epoch 36/500 34/34 [==============================] - 0s 2ms/step - loss: 2560.2109 - mae: 2560.2109 - val_loss: 2488.8569 - val_mae: 2488.8569 Epoch 37/500 34/34 [==============================] - 0s 2ms/step - loss: 2538.4377 - mae: 2538.4377 - val_loss: 2474.2083 - val_mae: 2474.2083 Epoch 38/500 34/34 [==============================] - 0s 2ms/step - loss: 2520.7141 - mae: 2520.7141 - val_loss: 2435.9792 - val_mae: 2435.9792 Epoch 39/500 34/34 [==============================] - 0s 2ms/step - loss: 2484.6331 - mae: 2484.6331 - val_loss: 2415.0652 - val_mae: 2415.0652 Epoch 40/500 34/34 [==============================] - 0s 2ms/step - loss: 2465.1812 - mae: 2465.1812 - val_loss: 2370.2437 - val_mae: 2370.2437 Epoch 41/500 34/34 [==============================] - 0s 2ms/step - loss: 2437.7688 - mae: 2437.7688 - val_loss: 2371.4500 - val_mae: 2371.4500 Epoch 42/500 34/34 [==============================] - 0s 2ms/step - loss: 2425.9814 - mae: 2425.9814 - val_loss: 2343.7275 - val_mae: 2343.7275 Epoch 43/500 34/34 [==============================] - 0s 2ms/step - loss: 2392.9536 - mae: 2392.9536 - val_loss: 2330.2480 - val_mae: 2330.2480 Epoch 44/500 34/34 [==============================] - 0s 2ms/step - loss: 2371.0847 - mae: 2371.0847 - val_loss: 2289.7070 - val_mae: 2289.7070 Epoch 45/500 34/34 [==============================] - 0s 2ms/step - loss: 2348.7854 - mae: 2348.7854 - val_loss: 2292.7617 - val_mae: 2292.7617 Epoch 46/500 34/34 [==============================] - 0s 2ms/step - loss: 2334.8552 - mae: 2334.8552 - val_loss: 2241.6716 - val_mae: 2241.6716 Epoch 47/500 34/34 [==============================] - 0s 2ms/step - loss: 2315.0535 - mae: 2315.0535 - val_loss: 2210.4521 - val_mae: 2210.4521 Epoch 48/500 34/34 [==============================] - 0s 2ms/step - loss: 2297.7964 - mae: 2297.7964 - val_loss: 2171.4700 - val_mae: 2171.4700 Epoch 49/500 34/34 [==============================] - 0s 2ms/step - loss: 2294.3506 - mae: 2294.3506 - val_loss: 2151.6238 - val_mae: 2151.6238 Epoch 50/500 34/34 [==============================] - 0s 2ms/step - loss: 2263.3362 - mae: 2263.3362 - val_loss: 2142.9990 - val_mae: 2142.9990 Epoch 51/500 34/34 [==============================] - 0s 2ms/step - loss: 2253.5146 - mae: 2253.5146 - val_loss: 2134.1323 - val_mae: 2134.1323 Epoch 52/500 34/34 [==============================] - 0s 1ms/step - loss: 2237.9785 - mae: 2237.9785 - val_loss: 2098.9661 - val_mae: 2098.9661 Epoch 53/500 34/34 [==============================] - 0s 2ms/step - loss: 2236.9548 - mae: 2236.9548 - val_loss: 2071.0901 - val_mae: 2071.0901 Epoch 54/500 34/34 [==============================] - 0s 2ms/step - loss: 2215.9924 - mae: 2215.9924 - val_loss: 2061.3196 - val_mae: 2061.3196 Epoch 55/500 34/34 [==============================] - 0s 2ms/step - loss: 2205.8298 - mae: 2205.8298 - val_loss: 2040.3530 - val_mae: 2040.3530 Epoch 56/500 34/34 [==============================] - 0s 2ms/step - loss: 2188.2505 - mae: 2188.2505 - val_loss: 2021.0121 - val_mae: 2021.0121 Epoch 57/500 34/34 [==============================] - 0s 2ms/step - loss: 2177.3682 - mae: 2177.3682 - val_loss: 2021.2423 - val_mae: 2021.2423 Epoch 58/500 34/34 [==============================] - 0s 2ms/step - loss: 2178.9595 - mae: 2178.9595 - val_loss: 2011.6056 - val_mae: 2011.6056 Epoch 59/500 34/34 [==============================] - 0s 2ms/step - loss: 2163.4875 - mae: 2163.4875 - val_loss: 1989.4083 - val_mae: 1989.4083 Epoch 60/500 34/34 [==============================] - 0s 2ms/step - loss: 2162.3979 - mae: 2162.3979 - val_loss: 1966.5223 - val_mae: 1966.5223 Epoch 61/500 34/34 [==============================] - 0s 2ms/step - loss: 2147.4280 - mae: 2147.4280 - val_loss: 1976.2264 - val_mae: 1976.2264 Epoch 62/500 34/34 [==============================] - 0s 2ms/step - loss: 2155.3154 - mae: 2155.3154 - val_loss: 1960.0067 - val_mae: 1960.0067 Epoch 63/500 34/34 [==============================] - 0s 2ms/step - loss: 2135.1248 - mae: 2135.1248 - val_loss: 1952.3442 - val_mae: 1952.3442 Epoch 64/500 34/34 [==============================] - 0s 2ms/step - loss: 2134.0422 - mae: 2134.0422 - val_loss: 1944.5605 - val_mae: 1944.5605 Epoch 65/500 34/34 [==============================] - 0s 1ms/step - loss: 2127.6821 - mae: 2127.6821 - val_loss: 1941.9708 - val_mae: 1941.9708 Epoch 66/500 34/34 [==============================] - 0s 2ms/step - loss: 2122.3645 - mae: 2122.3645 - val_loss: 1929.4570 - val_mae: 1929.4570 Epoch 67/500 34/34 [==============================] - 0s 2ms/step - loss: 2120.1699 - mae: 2120.1699 - val_loss: 1936.8811 - val_mae: 1936.8811 Epoch 68/500 34/34 [==============================] - 0s 1ms/step - loss: 2109.6860 - mae: 2109.6860 - val_loss: 1931.9760 - val_mae: 1931.9760 Epoch 69/500 34/34 [==============================] - 0s 2ms/step - loss: 2114.0178 - mae: 2114.0178 - val_loss: 1912.5884 - val_mae: 1912.5884 Epoch 70/500 34/34 [==============================] - 0s 1ms/step - loss: 2104.0676 - mae: 2104.0676 - val_loss: 1905.8671 - val_mae: 1905.8671 Epoch 71/500 34/34 [==============================] - 0s 1ms/step - loss: 2092.1143 - mae: 2092.1143 - val_loss: 1901.4152 - val_mae: 1901.4152 Epoch 72/500 34/34 [==============================] - 0s 2ms/step - loss: 2100.2505 - mae: 2100.2505 - val_loss: 1903.0378 - val_mae: 1903.0378 Epoch 73/500 34/34 [==============================] - 0s 2ms/step - loss: 2101.2200 - mae: 2101.2200 - val_loss: 1901.5217 - val_mae: 1901.5217 Epoch 74/500 34/34 [==============================] - 0s 2ms/step - loss: 2084.9080 - mae: 2084.9080 - val_loss: 1888.1274 - val_mae: 1888.1274 Epoch 75/500 34/34 [==============================] - 0s 1ms/step - loss: 2073.2085 - mae: 2073.2085 - val_loss: 1885.5505 - val_mae: 1885.5505 Epoch 76/500 34/34 [==============================] - 0s 2ms/step - loss: 2079.0083 - mae: 2079.0083 - val_loss: 1869.9961 - val_mae: 1869.9961 Epoch 77/500 34/34 [==============================] - 0s 2ms/step - loss: 2081.0576 - mae: 2081.0576 - val_loss: 1880.8708 - val_mae: 1880.8708 Epoch 78/500 34/34 [==============================] - 0s 2ms/step - loss: 2075.4822 - mae: 2075.4822 - val_loss: 1867.2734 - val_mae: 1867.2734 Epoch 79/500 34/34 [==============================] - 0s 2ms/step - loss: 2071.6575 - mae: 2071.6575 - val_loss: 1891.7242 - val_mae: 1891.7242 Epoch 80/500 34/34 [==============================] - 0s 2ms/step - loss: 2079.9980 - mae: 2079.9980 - val_loss: 1863.6963 - val_mae: 1863.6963 Epoch 81/500 34/34 [==============================] - 0s 2ms/step - loss: 2067.2991 - mae: 2067.2991 - val_loss: 1872.7144 - val_mae: 1872.7144 Epoch 82/500 34/34 [==============================] - 0s 1ms/step - loss: 2055.6555 - mae: 2055.6555 - val_loss: 1879.2584 - val_mae: 1879.2584 Epoch 83/500 34/34 [==============================] - 0s 2ms/step - loss: 2059.4839 - mae: 2059.4839 - val_loss: 1863.3885 - val_mae: 1863.3885 Epoch 84/500 34/34 [==============================] - 0s 2ms/step - loss: 2063.1194 - mae: 2063.1194 - val_loss: 1862.5278 - val_mae: 1862.5278 Epoch 85/500 34/34 [==============================] - 0s 2ms/step - loss: 2051.0049 - mae: 2051.0049 - val_loss: 1854.5962 - val_mae: 1854.5962 Epoch 86/500 34/34 [==============================] - 0s 2ms/step - loss: 2042.3267 - mae: 2042.3267 - val_loss: 1850.3087 - val_mae: 1850.3087 Epoch 87/500 34/34 [==============================] - 0s 2ms/step - loss: 2041.6899 - mae: 2041.6899 - val_loss: 1850.6119 - val_mae: 1850.6119 Epoch 88/500 34/34 [==============================] - 0s 2ms/step - loss: 2035.3190 - mae: 2035.3190 - val_loss: 1847.2694 - val_mae: 1847.2694 Epoch 89/500 34/34 [==============================] - 0s 2ms/step - loss: 2037.0938 - mae: 2037.0938 - val_loss: 1850.0952 - val_mae: 1850.0952 Epoch 90/500 34/34 [==============================] - 0s 2ms/step - loss: 2041.1196 - mae: 2041.1196 - val_loss: 1844.9628 - val_mae: 1844.9628 Epoch 91/500 34/34 [==============================] - 0s 2ms/step - loss: 2044.2196 - mae: 2044.2196 - val_loss: 1843.0162 - val_mae: 1843.0162 Epoch 92/500 34/34 [==============================] - 0s 2ms/step - loss: 2032.8231 - mae: 2032.8231 - val_loss: 1851.4753 - val_mae: 1851.4753 Epoch 93/500 34/34 [==============================] - 0s 2ms/step - loss: 2036.5299 - mae: 2036.5299 - val_loss: 1855.1908 - val_mae: 1855.1908 Epoch 94/500 34/34 [==============================] - 0s 1ms/step - loss: 2029.4299 - mae: 2029.4299 - val_loss: 1858.8723 - val_mae: 1858.8723 Epoch 95/500 34/34 [==============================] - 0s 2ms/step - loss: 2024.9934 - mae: 2024.9934 - val_loss: 1849.4526 - val_mae: 1849.4526 Epoch 96/500 34/34 [==============================] - 0s 2ms/step - loss: 2033.5105 - mae: 2033.5105 - val_loss: 1840.8606 - val_mae: 1840.8606 Epoch 97/500 34/34 [==============================] - 0s 1ms/step - loss: 2048.5264 - mae: 2048.5264 - val_loss: 1831.0789 - val_mae: 1831.0789 Epoch 98/500 34/34 [==============================] - 0s 2ms/step - loss: 2036.3689 - mae: 2036.3689 - val_loss: 1852.7601 - val_mae: 1852.7601 Epoch 99/500 34/34 [==============================] - 0s 2ms/step - loss: 2023.3348 - mae: 2023.3348 - val_loss: 1828.0614 - val_mae: 1828.0614 Epoch 100/500 34/34 [==============================] - 0s 2ms/step - loss: 2017.7542 - mae: 2017.7542 - val_loss: 1815.4932 - val_mae: 1815.4932 Epoch 101/500 34/34 [==============================] - 0s 2ms/step - loss: 2014.7932 - mae: 2014.7932 - val_loss: 1822.2697 - val_mae: 1822.2697 Epoch 102/500 34/34 [==============================] - 0s 1ms/step - loss: 2012.9108 - mae: 2012.9108 - val_loss: 1817.1342 - val_mae: 1817.1342 Epoch 103/500 34/34 [==============================] - 0s 2ms/step - loss: 2012.9425 - mae: 2012.9425 - val_loss: 1816.2031 - val_mae: 1816.2031 Epoch 104/500 34/34 [==============================] - 0s 2ms/step - loss: 2017.9021 - mae: 2017.9021 - val_loss: 1846.4427 - val_mae: 1846.4427 Epoch 105/500 34/34 [==============================] - 0s 2ms/step - loss: 2014.4573 - mae: 2014.4573 - val_loss: 1821.5594 - val_mae: 1821.5594 Epoch 106/500 34/34 [==============================] - 0s 2ms/step - loss: 2012.5148 - mae: 2012.5148 - val_loss: 1824.1171 - val_mae: 1824.1171 Epoch 107/500 34/34 [==============================] - 0s 2ms/step - loss: 2015.5453 - mae: 2015.5453 - val_loss: 1811.1664 - val_mae: 1811.1664 Epoch 108/500 34/34 [==============================] - 0s 2ms/step - loss: 2005.4918 - mae: 2005.4918 - val_loss: 1812.3279 - val_mae: 1812.3279 Epoch 109/500 34/34 [==============================] - 0s 2ms/step - loss: 2001.3566 - mae: 2001.3566 - val_loss: 1822.6973 - val_mae: 1822.6973 Epoch 110/500 34/34 [==============================] - 0s 2ms/step - loss: 2010.9276 - mae: 2010.9276 - val_loss: 1817.7332 - val_mae: 1817.7332 Epoch 111/500 34/34 [==============================] - 0s 2ms/step - loss: 2001.7743 - mae: 2001.7743 - val_loss: 1811.4060 - val_mae: 1811.4060 Epoch 112/500 34/34 [==============================] - 0s 2ms/step - loss: 2002.9131 - mae: 2002.9131 - val_loss: 1821.4413 - val_mae: 1821.4413 Epoch 113/500 34/34 [==============================] - 0s 2ms/step - loss: 2003.3796 - mae: 2003.3796 - val_loss: 1824.0438 - val_mae: 1824.0438 Epoch 114/500 34/34 [==============================] - 0s 2ms/step - loss: 2016.0397 - mae: 2016.0397 - val_loss: 1823.3734 - val_mae: 1823.3734 Epoch 115/500 34/34 [==============================] - 0s 2ms/step - loss: 2004.9606 - mae: 2004.9606 - val_loss: 1803.3007 - val_mae: 1803.3007 Epoch 116/500 34/34 [==============================] - 0s 2ms/step - loss: 2008.6638 - mae: 2008.6638 - val_loss: 1800.9580 - val_mae: 1800.9580 Epoch 117/500 34/34 [==============================] - 0s 2ms/step - loss: 2001.8729 - mae: 2001.8729 - val_loss: 1791.9836 - val_mae: 1791.9836 Epoch 118/500 34/34 [==============================] - 0s 2ms/step - loss: 1993.7715 - mae: 1993.7715 - val_loss: 1797.1489 - val_mae: 1797.1489 Epoch 119/500 34/34 [==============================] - 0s 2ms/step - loss: 1991.6925 - mae: 1991.6925 - val_loss: 1801.9685 - val_mae: 1801.9685 Epoch 120/500 34/34 [==============================] - 0s 2ms/step - loss: 2005.2185 - mae: 2005.2185 - val_loss: 1806.2285 - val_mae: 1806.2285 Epoch 121/500 34/34 [==============================] - 0s 2ms/step - loss: 1992.6122 - mae: 1992.6122 - val_loss: 1795.7297 - val_mae: 1795.7297 Epoch 122/500 34/34 [==============================] - 0s 2ms/step - loss: 1989.4568 - mae: 1989.4568 - val_loss: 1792.3977 - val_mae: 1792.3977 Epoch 123/500 34/34 [==============================] - 0s 2ms/step - loss: 1985.5287 - mae: 1985.5287 - val_loss: 1816.6318 - val_mae: 1816.6318 Epoch 124/500 34/34 [==============================] - 0s 2ms/step - loss: 2005.8525 - mae: 2005.8525 - val_loss: 1812.2037 - val_mae: 1812.2037 Epoch 125/500 34/34 [==============================] - 0s 2ms/step - loss: 1994.0787 - mae: 1994.0787 - val_loss: 1797.1824 - val_mae: 1797.1824 Epoch 126/500 34/34 [==============================] - 0s 2ms/step - loss: 1988.7498 - mae: 1988.7498 - val_loss: 1801.5994 - val_mae: 1801.5994 Epoch 127/500 34/34 [==============================] - 0s 2ms/step - loss: 1994.9095 - mae: 1994.9095 - val_loss: 1811.8732 - val_mae: 1811.8732 Epoch 128/500 34/34 [==============================] - 0s 2ms/step - loss: 1990.6432 - mae: 1990.6432 - val_loss: 1790.9241 - val_mae: 1790.9241 Epoch 129/500 34/34 [==============================] - 0s 2ms/step - loss: 1993.8073 - mae: 1993.8073 - val_loss: 1809.0693 - val_mae: 1809.0693 Epoch 130/500 34/34 [==============================] - 0s 2ms/step - loss: 1988.2024 - mae: 1988.2024 - val_loss: 1799.9777 - val_mae: 1799.9777 Epoch 131/500 34/34 [==============================] - 0s 2ms/step - loss: 1984.6715 - mae: 1984.6715 - val_loss: 1802.8118 - val_mae: 1802.8118 Epoch 132/500 34/34 [==============================] - 0s 2ms/step - loss: 1988.0992 - mae: 1988.0992 - val_loss: 1791.8558 - val_mae: 1791.8558 Epoch 133/500 34/34 [==============================] - 0s 2ms/step - loss: 1989.9736 - mae: 1989.9736 - val_loss: 1785.9014 - val_mae: 1785.9014 Epoch 134/500 34/34 [==============================] - 0s 2ms/step - loss: 1996.2953 - mae: 1996.2953 - val_loss: 1781.5219 - val_mae: 1781.5219 Epoch 135/500 34/34 [==============================] - 0s 2ms/step - loss: 1988.9187 - mae: 1988.9187 - val_loss: 1791.9681 - val_mae: 1791.9681 Epoch 136/500 34/34 [==============================] - 0s 2ms/step - loss: 1980.8845 - mae: 1980.8845 - val_loss: 1792.9158 - val_mae: 1792.9158 Epoch 137/500 34/34 [==============================] - 0s 2ms/step - loss: 1995.1309 - mae: 1995.1309 - val_loss: 1797.9642 - val_mae: 1797.9642 Epoch 138/500 34/34 [==============================] - 0s 2ms/step - loss: 1984.1794 - mae: 1984.1794 - val_loss: 1794.5872 - val_mae: 1794.5872 Epoch 139/500 34/34 [==============================] - 0s 2ms/step - loss: 1982.2208 - mae: 1982.2208 - val_loss: 1793.4797 - val_mae: 1793.4797 Epoch 140/500 34/34 [==============================] - 0s 1ms/step - loss: 1985.4689 - mae: 1985.4689 - val_loss: 1792.9102 - val_mae: 1792.9102 Epoch 141/500 34/34 [==============================] - 0s 2ms/step - loss: 1985.4965 - mae: 1985.4965 - val_loss: 1793.7250 - val_mae: 1793.7250 Epoch 142/500 34/34 [==============================] - 0s 2ms/step - loss: 1995.5189 - mae: 1995.5189 - val_loss: 1792.1943 - val_mae: 1792.1943 Epoch 143/500 34/34 [==============================] - 0s 2ms/step - loss: 1984.2916 - mae: 1984.2916 - val_loss: 1789.3123 - val_mae: 1789.3123 Epoch 144/500 34/34 [==============================] - 0s 2ms/step - loss: 1975.0759 - mae: 1975.0759 - val_loss: 1792.1858 - val_mae: 1792.1858 Epoch 145/500 34/34 [==============================] - 0s 2ms/step - loss: 1978.6841 - mae: 1978.6841 - val_loss: 1789.2256 - val_mae: 1789.2256 Epoch 146/500 34/34 [==============================] - 0s 1ms/step - loss: 1977.5038 - mae: 1977.5038 - val_loss: 1780.8389 - val_mae: 1780.8389 Epoch 147/500 34/34 [==============================] - 0s 2ms/step - loss: 1987.2664 - mae: 1987.2664 - val_loss: 1792.8644 - val_mae: 1792.8644 Epoch 148/500 34/34 [==============================] - 0s 2ms/step - loss: 1976.7812 - mae: 1976.7812 - val_loss: 1796.4983 - val_mae: 1796.4983 Epoch 149/500 34/34 [==============================] - 0s 2ms/step - loss: 1974.8413 - mae: 1974.8413 - val_loss: 1787.6670 - val_mae: 1787.6670 Epoch 150/500 34/34 [==============================] - 0s 2ms/step - loss: 1978.4220 - mae: 1978.4220 - val_loss: 1795.4137 - val_mae: 1795.4137 Epoch 151/500 34/34 [==============================] - 0s 2ms/step - loss: 1979.4327 - mae: 1979.4327 - val_loss: 1790.2787 - val_mae: 1790.2787 Epoch 152/500 34/34 [==============================] - 0s 1ms/step - loss: 1977.7789 - mae: 1977.7789 - val_loss: 1774.2340 - val_mae: 1774.2340 Epoch 153/500 34/34 [==============================] - 0s 2ms/step - loss: 1982.2012 - mae: 1982.2012 - val_loss: 1784.3153 - val_mae: 1784.3153 Epoch 154/500 34/34 [==============================] - 0s 2ms/step - loss: 1977.4806 - mae: 1977.4806 - val_loss: 1782.5403 - val_mae: 1782.5403 Epoch 155/500 34/34 [==============================] - 0s 2ms/step - loss: 1980.9225 - mae: 1980.9225 - val_loss: 1791.9736 - val_mae: 1791.9736 Epoch 156/500 34/34 [==============================] - 0s 2ms/step - loss: 1981.3085 - mae: 1981.3085 - val_loss: 1788.5519 - val_mae: 1788.5519 Epoch 157/500 34/34 [==============================] - 0s 2ms/step - loss: 1981.2551 - mae: 1981.2551 - val_loss: 1768.8878 - val_mae: 1768.8878 Epoch 158/500 34/34 [==============================] - 0s 2ms/step - loss: 1973.1549 - mae: 1973.1549 - val_loss: 1798.0594 - val_mae: 1798.0594 Epoch 159/500 34/34 [==============================] - 0s 2ms/step - loss: 1980.2050 - mae: 1980.2050 - val_loss: 1775.0919 - val_mae: 1775.0919 Epoch 160/500 34/34 [==============================] - 0s 2ms/step - loss: 1971.4470 - mae: 1971.4470 - val_loss: 1781.8694 - val_mae: 1781.8694 Epoch 161/500 34/34 [==============================] - 0s 2ms/step - loss: 1975.1182 - mae: 1975.1182 - val_loss: 1775.5975 - val_mae: 1775.5975 Epoch 162/500 34/34 [==============================] - 0s 2ms/step - loss: 1969.4803 - mae: 1969.4803 - val_loss: 1781.3888 - val_mae: 1781.3888 Epoch 163/500 34/34 [==============================] - 0s 2ms/step - loss: 1967.1493 - mae: 1967.1493 - val_loss: 1781.9633 - val_mae: 1781.9633 Epoch 164/500 34/34 [==============================] - 0s 2ms/step - loss: 1974.8502 - mae: 1974.8502 - val_loss: 1780.3650 - val_mae: 1780.3650 Epoch 165/500 34/34 [==============================] - 0s 2ms/step - loss: 1972.5902 - mae: 1972.5902 - val_loss: 1771.8502 - val_mae: 1771.8502 Epoch 166/500 34/34 [==============================] - 0s 2ms/step - loss: 1971.9954 - mae: 1971.9954 - val_loss: 1781.4761 - val_mae: 1781.4761 Epoch 167/500 34/34 [==============================] - 0s 2ms/step - loss: 1970.0887 - mae: 1970.0887 - val_loss: 1783.3815 - val_mae: 1783.3815 Epoch 168/500 34/34 [==============================] - 0s 2ms/step - loss: 1967.5521 - mae: 1967.5521 - val_loss: 1778.5927 - val_mae: 1778.5927 Epoch 169/500 34/34 [==============================] - 0s 2ms/step - loss: 1967.0444 - mae: 1967.0444 - val_loss: 1771.4957 - val_mae: 1771.4957 Epoch 170/500 34/34 [==============================] - 0s 2ms/step - loss: 1966.5867 - mae: 1966.5867 - val_loss: 1785.8175 - val_mae: 1785.8175 Epoch 171/500 34/34 [==============================] - 0s 1ms/step - loss: 1967.7477 - mae: 1967.7477 - val_loss: 1776.2269 - val_mae: 1776.2269 Epoch 172/500 34/34 [==============================] - 0s 2ms/step - loss: 1980.0281 - mae: 1980.0281 - val_loss: 1779.9388 - val_mae: 1779.9388 Epoch 173/500 34/34 [==============================] - 0s 2ms/step - loss: 1981.8927 - mae: 1981.8927 - val_loss: 1771.5815 - val_mae: 1771.5815 Epoch 174/500 34/34 [==============================] - 0s 2ms/step - loss: 1966.4998 - mae: 1966.4998 - val_loss: 1782.0991 - val_mae: 1782.0991 Epoch 175/500 34/34 [==============================] - 0s 2ms/step - loss: 1976.7661 - mae: 1976.7661 - val_loss: 1774.7715 - val_mae: 1774.7715 Epoch 176/500 34/34 [==============================] - 0s 2ms/step - loss: 1966.4243 - mae: 1966.4243 - val_loss: 1775.2882 - val_mae: 1775.2882 Epoch 177/500 34/34 [==============================] - 0s 2ms/step - loss: 1967.7278 - mae: 1967.7278 - val_loss: 1774.0293 - val_mae: 1774.0293 Epoch 178/500 34/34 [==============================] - 0s 2ms/step - loss: 1966.8129 - mae: 1966.8129 - val_loss: 1774.3683 - val_mae: 1774.3683 Epoch 179/500 34/34 [==============================] - 0s 2ms/step - loss: 1971.2717 - mae: 1971.2717 - val_loss: 1774.1532 - val_mae: 1774.1532 Epoch 180/500 34/34 [==============================] - 0s 2ms/step - loss: 1965.6360 - mae: 1965.6360 - val_loss: 1766.4706 - val_mae: 1766.4706 Epoch 181/500 34/34 [==============================] - 0s 2ms/step - loss: 1967.4757 - mae: 1967.4757 - val_loss: 1775.8031 - val_mae: 1775.8031 Epoch 182/500 34/34 [==============================] - 0s 2ms/step - loss: 1960.8469 - mae: 1960.8469 - val_loss: 1777.3994 - val_mae: 1777.3994 Epoch 183/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.0070 - mae: 1961.0070 - val_loss: 1769.4930 - val_mae: 1769.4930 Epoch 184/500 34/34 [==============================] - 0s 2ms/step - loss: 1975.5460 - mae: 1975.5460 - val_loss: 1786.1698 - val_mae: 1786.1698 Epoch 185/500 34/34 [==============================] - 0s 2ms/step - loss: 1966.0946 - mae: 1966.0946 - val_loss: 1761.1935 - val_mae: 1761.1935 Epoch 186/500 34/34 [==============================] - 0s 2ms/step - loss: 1960.2603 - mae: 1960.2603 - val_loss: 1769.9578 - val_mae: 1769.9578 Epoch 187/500 34/34 [==============================] - 0s 2ms/step - loss: 1973.1697 - mae: 1973.1697 - val_loss: 1757.0441 - val_mae: 1757.0441 Epoch 188/500 34/34 [==============================] - 0s 2ms/step - loss: 1968.5486 - mae: 1968.5486 - val_loss: 1766.9186 - val_mae: 1766.9186 Epoch 189/500 34/34 [==============================] - 0s 2ms/step - loss: 1967.8101 - mae: 1967.8101 - val_loss: 1770.9064 - val_mae: 1770.9064 Epoch 190/500 34/34 [==============================] - 0s 2ms/step - loss: 1976.6902 - mae: 1976.6902 - val_loss: 1776.0175 - val_mae: 1776.0175 Epoch 191/500 34/34 [==============================] - 0s 2ms/step - loss: 1969.4918 - mae: 1969.4918 - val_loss: 1777.5186 - val_mae: 1777.5186 Epoch 192/500 34/34 [==============================] - 0s 2ms/step - loss: 1960.8390 - mae: 1960.8390 - val_loss: 1762.5614 - val_mae: 1762.5614 Epoch 193/500 34/34 [==============================] - 0s 2ms/step - loss: 1976.4841 - mae: 1976.4841 - val_loss: 1773.4581 - val_mae: 1773.4581 Epoch 194/500 34/34 [==============================] - 0s 2ms/step - loss: 1968.7488 - mae: 1968.7488 - val_loss: 1769.2513 - val_mae: 1769.2513 Epoch 195/500 34/34 [==============================] - 0s 2ms/step - loss: 1960.0731 - mae: 1960.0731 - val_loss: 1769.3701 - val_mae: 1769.3701 Epoch 196/500 34/34 [==============================] - 0s 2ms/step - loss: 1968.5825 - mae: 1968.5825 - val_loss: 1762.6217 - val_mae: 1762.6217 Epoch 197/500 34/34 [==============================] - 0s 2ms/step - loss: 1965.5475 - mae: 1965.5475 - val_loss: 1772.2786 - val_mae: 1772.2786 Epoch 198/500 34/34 [==============================] - 0s 2ms/step - loss: 1963.0095 - mae: 1963.0095 - val_loss: 1767.6793 - val_mae: 1767.6793 Epoch 199/500 34/34 [==============================] - 0s 2ms/step - loss: 1977.9890 - mae: 1977.9890 - val_loss: 1781.3022 - val_mae: 1781.3022 Epoch 200/500 34/34 [==============================] - 0s 2ms/step - loss: 1965.5640 - mae: 1965.5640 - val_loss: 1762.8400 - val_mae: 1762.8400 Epoch 201/500 34/34 [==============================] - 0s 2ms/step - loss: 1964.1094 - mae: 1964.1094 - val_loss: 1774.6151 - val_mae: 1774.6151 Epoch 202/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.6323 - mae: 1956.6323 - val_loss: 1765.7267 - val_mae: 1765.7267 Epoch 203/500 34/34 [==============================] - 0s 2ms/step - loss: 1964.8213 - mae: 1964.8213 - val_loss: 1771.9376 - val_mae: 1771.9376 Epoch 204/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.8395 - mae: 1959.8395 - val_loss: 1787.2118 - val_mae: 1787.2118 Epoch 205/500 34/34 [==============================] - 0s 2ms/step - loss: 1966.8627 - mae: 1966.8627 - val_loss: 1759.7816 - val_mae: 1759.7816 Epoch 206/500 34/34 [==============================] - 0s 2ms/step - loss: 1960.0481 - mae: 1960.0481 - val_loss: 1759.5378 - val_mae: 1759.5378 Epoch 207/500 34/34 [==============================] - 0s 2ms/step - loss: 1972.4121 - mae: 1972.4121 - val_loss: 1775.3069 - val_mae: 1775.3069 Epoch 208/500 34/34 [==============================] - 0s 2ms/step - loss: 1969.1094 - mae: 1969.1094 - val_loss: 1771.8595 - val_mae: 1771.8595 Epoch 209/500 34/34 [==============================] - 0s 2ms/step - loss: 1965.4229 - mae: 1965.4229 - val_loss: 1774.4146 - val_mae: 1774.4146 Epoch 210/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.6182 - mae: 1961.6182 - val_loss: 1758.3811 - val_mae: 1758.3811 Epoch 211/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.2460 - mae: 1961.2460 - val_loss: 1765.3663 - val_mae: 1765.3663 Epoch 212/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.8534 - mae: 1959.8534 - val_loss: 1769.8109 - val_mae: 1769.8109 Epoch 213/500 34/34 [==============================] - 0s 2ms/step - loss: 1965.4561 - mae: 1965.4561 - val_loss: 1755.5190 - val_mae: 1755.5190 Epoch 214/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.2323 - mae: 1956.2323 - val_loss: 1758.1731 - val_mae: 1758.1731 Epoch 215/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.1764 - mae: 1957.1764 - val_loss: 1760.1693 - val_mae: 1760.1693 Epoch 216/500 34/34 [==============================] - 0s 2ms/step - loss: 1966.5322 - mae: 1966.5322 - val_loss: 1748.7299 - val_mae: 1748.7299 Epoch 217/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.7247 - mae: 1961.7247 - val_loss: 1761.4476 - val_mae: 1761.4476 Epoch 218/500 34/34 [==============================] - 0s 1ms/step - loss: 1964.3876 - mae: 1964.3876 - val_loss: 1776.0294 - val_mae: 1776.0294 Epoch 219/500 34/34 [==============================] - 0s 2ms/step - loss: 1966.7490 - mae: 1966.7490 - val_loss: 1761.2290 - val_mae: 1761.2290 Epoch 220/500 34/34 [==============================] - 0s 2ms/step - loss: 1963.3037 - mae: 1963.3037 - val_loss: 1764.5389 - val_mae: 1764.5389 Epoch 221/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.0612 - mae: 1956.0612 - val_loss: 1765.7604 - val_mae: 1765.7604 Epoch 222/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.6335 - mae: 1959.6335 - val_loss: 1765.8113 - val_mae: 1765.8113 Epoch 223/500 34/34 [==============================] - 0s 2ms/step - loss: 1964.8103 - mae: 1964.8103 - val_loss: 1758.9226 - val_mae: 1758.9226 Epoch 224/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.9744 - mae: 1953.9744 - val_loss: 1761.1431 - val_mae: 1761.1431 Epoch 225/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.5897 - mae: 1956.5897 - val_loss: 1770.0221 - val_mae: 1770.0221 Epoch 226/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.6388 - mae: 1959.6388 - val_loss: 1771.6255 - val_mae: 1771.6255 Epoch 227/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.5343 - mae: 1957.5343 - val_loss: 1759.5389 - val_mae: 1759.5389 Epoch 228/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.2158 - mae: 1955.2158 - val_loss: 1760.0000 - val_mae: 1760.0000 Epoch 229/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.5652 - mae: 1950.5652 - val_loss: 1769.1490 - val_mae: 1769.1490 Epoch 230/500 34/34 [==============================] - 0s 2ms/step - loss: 1972.5710 - mae: 1972.5710 - val_loss: 1782.5632 - val_mae: 1782.5632 Epoch 231/500 34/34 [==============================] - 0s 2ms/step - loss: 1969.8538 - mae: 1969.8538 - val_loss: 1766.4808 - val_mae: 1766.4808 Epoch 232/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.6958 - mae: 1958.6958 - val_loss: 1768.9506 - val_mae: 1768.9506 Epoch 233/500 34/34 [==============================] - 0s 2ms/step - loss: 1969.3577 - mae: 1969.3577 - val_loss: 1774.3427 - val_mae: 1774.3427 Epoch 234/500 34/34 [==============================] - 0s 2ms/step - loss: 1969.5005 - mae: 1969.5005 - val_loss: 1765.2805 - val_mae: 1765.2805 Epoch 235/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.5685 - mae: 1959.5685 - val_loss: 1757.3914 - val_mae: 1757.3914 Epoch 236/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.8185 - mae: 1955.8185 - val_loss: 1767.4189 - val_mae: 1767.4189 Epoch 237/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.3993 - mae: 1961.3993 - val_loss: 1762.3055 - val_mae: 1762.3055 Epoch 238/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.5317 - mae: 1957.5317 - val_loss: 1760.3268 - val_mae: 1760.3268 Epoch 239/500 34/34 [==============================] - 0s 1ms/step - loss: 1957.4944 - mae: 1957.4944 - val_loss: 1763.0468 - val_mae: 1763.0468 Epoch 240/500 34/34 [==============================] - 0s 2ms/step - loss: 1977.7267 - mae: 1977.7267 - val_loss: 1763.8022 - val_mae: 1763.8022 Epoch 241/500 34/34 [==============================] - 0s 2ms/step - loss: 1980.8425 - mae: 1980.8425 - val_loss: 1765.0255 - val_mae: 1765.0255 Epoch 242/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.3900 - mae: 1958.3900 - val_loss: 1755.1130 - val_mae: 1755.1130 Epoch 243/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.3809 - mae: 1961.3809 - val_loss: 1763.5626 - val_mae: 1763.5626 Epoch 244/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.8789 - mae: 1958.8789 - val_loss: 1752.8175 - val_mae: 1752.8175 Epoch 245/500 34/34 [==============================] - 0s 2ms/step - loss: 1963.3140 - mae: 1963.3140 - val_loss: 1769.4661 - val_mae: 1769.4661 Epoch 246/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.8228 - mae: 1958.8228 - val_loss: 1757.4446 - val_mae: 1757.4446 Epoch 247/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.3497 - mae: 1958.3497 - val_loss: 1769.2129 - val_mae: 1769.2129 Epoch 248/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.8246 - mae: 1956.8246 - val_loss: 1754.8088 - val_mae: 1754.8088 Epoch 249/500 34/34 [==============================] - 0s 2ms/step - loss: 1962.1644 - mae: 1962.1644 - val_loss: 1757.5533 - val_mae: 1757.5533 Epoch 250/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.9523 - mae: 1957.9523 - val_loss: 1770.5831 - val_mae: 1770.5831 Epoch 251/500 34/34 [==============================] - 0s 2ms/step - loss: 1962.0795 - mae: 1962.0795 - val_loss: 1750.0560 - val_mae: 1750.0560 Epoch 252/500 34/34 [==============================] - 0s 2ms/step - loss: 1968.0094 - mae: 1968.0094 - val_loss: 1773.1727 - val_mae: 1773.1727 Epoch 253/500 34/34 [==============================] - 0s 2ms/step - loss: 1963.5264 - mae: 1963.5264 - val_loss: 1772.5731 - val_mae: 1772.5731 Epoch 254/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.1318 - mae: 1959.1318 - val_loss: 1770.7881 - val_mae: 1770.7881 Epoch 255/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.7399 - mae: 1959.7399 - val_loss: 1771.9459 - val_mae: 1771.9459 Epoch 256/500 34/34 [==============================] - 0s 2ms/step - loss: 1969.7211 - mae: 1969.7211 - val_loss: 1770.5940 - val_mae: 1770.5940 Epoch 257/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.1825 - mae: 1951.1825 - val_loss: 1764.4368 - val_mae: 1764.4368 Epoch 258/500 34/34 [==============================] - 0s 2ms/step - loss: 1960.7878 - mae: 1960.7878 - val_loss: 1754.7833 - val_mae: 1754.7833 Epoch 259/500 34/34 [==============================] - 0s 2ms/step - loss: 1966.8428 - mae: 1966.8428 - val_loss: 1758.1840 - val_mae: 1758.1840 Epoch 260/500 34/34 [==============================] - 0s 2ms/step - loss: 1965.6685 - mae: 1965.6685 - val_loss: 1769.8696 - val_mae: 1769.8696 Epoch 261/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.3458 - mae: 1958.3458 - val_loss: 1769.6771 - val_mae: 1769.6771 Epoch 262/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.6326 - mae: 1957.6326 - val_loss: 1764.7932 - val_mae: 1764.7932 Epoch 263/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.2800 - mae: 1959.2800 - val_loss: 1783.8472 - val_mae: 1783.8472 Epoch 264/500 34/34 [==============================] - 0s 2ms/step - loss: 1962.0381 - mae: 1962.0381 - val_loss: 1773.7986 - val_mae: 1773.7986 Epoch 265/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.3545 - mae: 1958.3545 - val_loss: 1766.7994 - val_mae: 1766.7994 Epoch 266/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.2140 - mae: 1961.2140 - val_loss: 1771.8352 - val_mae: 1771.8352 Epoch 267/500 34/34 [==============================] - 0s 2ms/step - loss: 1969.5743 - mae: 1969.5743 - val_loss: 1766.3003 - val_mae: 1766.3003 Epoch 268/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.3326 - mae: 1955.3326 - val_loss: 1757.1107 - val_mae: 1757.1107 Epoch 269/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.2692 - mae: 1955.2692 - val_loss: 1765.9857 - val_mae: 1765.9857 Epoch 270/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.2644 - mae: 1959.2644 - val_loss: 1759.9711 - val_mae: 1759.9711 Epoch 271/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.1543 - mae: 1953.1543 - val_loss: 1766.8632 - val_mae: 1766.8632 Epoch 272/500 34/34 [==============================] - 0s 2ms/step - loss: 1968.7771 - mae: 1968.7771 - val_loss: 1764.6088 - val_mae: 1764.6088 Epoch 273/500 34/34 [==============================] - 0s 2ms/step - loss: 1968.1626 - mae: 1968.1626 - val_loss: 1754.2203 - val_mae: 1754.2203 Epoch 274/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.8226 - mae: 1957.8226 - val_loss: 1763.2904 - val_mae: 1763.2904 Epoch 275/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.6366 - mae: 1953.6366 - val_loss: 1751.8658 - val_mae: 1751.8658 Epoch 276/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.2917 - mae: 1958.2917 - val_loss: 1769.1542 - val_mae: 1769.1542 Epoch 277/500 34/34 [==============================] - 0s 2ms/step - loss: 1973.9141 - mae: 1973.9141 - val_loss: 1774.1117 - val_mae: 1774.1117 Epoch 278/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.1049 - mae: 1957.1049 - val_loss: 1765.9230 - val_mae: 1765.9230 Epoch 279/500 34/34 [==============================] - 0s 2ms/step - loss: 1967.5278 - mae: 1967.5278 - val_loss: 1770.7007 - val_mae: 1770.7007 Epoch 280/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.8138 - mae: 1950.8138 - val_loss: 1765.4844 - val_mae: 1765.4844 Epoch 281/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.8281 - mae: 1955.8281 - val_loss: 1766.1042 - val_mae: 1766.1042 Epoch 282/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.5582 - mae: 1961.5582 - val_loss: 1762.7716 - val_mae: 1762.7716 Epoch 283/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.2568 - mae: 1954.2568 - val_loss: 1763.8444 - val_mae: 1763.8444 Epoch 284/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.2937 - mae: 1957.2937 - val_loss: 1756.2458 - val_mae: 1756.2458 Epoch 285/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.0532 - mae: 1958.0532 - val_loss: 1766.0789 - val_mae: 1766.0789 Epoch 286/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.5929 - mae: 1949.5929 - val_loss: 1761.2052 - val_mae: 1761.2052 Epoch 287/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.3927 - mae: 1957.3927 - val_loss: 1760.6901 - val_mae: 1760.6901 Epoch 288/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.8138 - mae: 1953.8138 - val_loss: 1764.0536 - val_mae: 1764.0536 Epoch 289/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.3557 - mae: 1954.3557 - val_loss: 1760.0659 - val_mae: 1760.0659 Epoch 290/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.7838 - mae: 1951.7838 - val_loss: 1767.5074 - val_mae: 1767.5074 Epoch 291/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.6080 - mae: 1957.6080 - val_loss: 1758.7362 - val_mae: 1758.7362 Epoch 292/500 34/34 [==============================] - 0s 1ms/step - loss: 1956.8254 - mae: 1956.8254 - val_loss: 1761.5820 - val_mae: 1761.5820 Epoch 293/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.8625 - mae: 1954.8625 - val_loss: 1769.0343 - val_mae: 1769.0343 Epoch 294/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.7103 - mae: 1958.7103 - val_loss: 1767.7207 - val_mae: 1767.7207 Epoch 295/500 34/34 [==============================] - 0s 2ms/step - loss: 1962.3280 - mae: 1962.3280 - val_loss: 1765.2023 - val_mae: 1765.2023 Epoch 296/500 34/34 [==============================] - 0s 2ms/step - loss: 1963.1007 - mae: 1963.1007 - val_loss: 1763.6494 - val_mae: 1763.6494 Epoch 297/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.1455 - mae: 1959.1455 - val_loss: 1754.1744 - val_mae: 1754.1744 Epoch 298/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.9417 - mae: 1952.9417 - val_loss: 1759.1855 - val_mae: 1759.1855 Epoch 299/500 34/34 [==============================] - 0s 2ms/step - loss: 1964.5503 - mae: 1964.5503 - val_loss: 1771.1095 - val_mae: 1771.1095 Epoch 300/500 34/34 [==============================] - 0s 2ms/step - loss: 1965.7643 - mae: 1965.7643 - val_loss: 1768.7195 - val_mae: 1768.7195 Epoch 301/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.4481 - mae: 1956.4481 - val_loss: 1758.2565 - val_mae: 1758.2565 Epoch 302/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.8484 - mae: 1950.8484 - val_loss: 1754.2070 - val_mae: 1754.2070 Epoch 303/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.8726 - mae: 1953.8726 - val_loss: 1764.6080 - val_mae: 1764.6080 Epoch 304/500 34/34 [==============================] - 0s 2ms/step - loss: 1963.4065 - mae: 1963.4065 - val_loss: 1761.6327 - val_mae: 1761.6327 Epoch 305/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.3087 - mae: 1959.3087 - val_loss: 1753.7297 - val_mae: 1753.7297 Epoch 306/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.4009 - mae: 1954.4009 - val_loss: 1755.5059 - val_mae: 1755.5059 Epoch 307/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.5096 - mae: 1956.5096 - val_loss: 1754.2982 - val_mae: 1754.2982 Epoch 308/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.6779 - mae: 1949.6779 - val_loss: 1771.6564 - val_mae: 1771.6564 Epoch 309/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.1182 - mae: 1958.1182 - val_loss: 1754.2281 - val_mae: 1754.2281 Epoch 310/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.8036 - mae: 1953.8036 - val_loss: 1761.2064 - val_mae: 1761.2064 Epoch 311/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.8374 - mae: 1950.8374 - val_loss: 1766.2916 - val_mae: 1766.2916 Epoch 312/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.4978 - mae: 1951.4978 - val_loss: 1751.0413 - val_mae: 1751.0413 Epoch 313/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.3518 - mae: 1951.3518 - val_loss: 1755.6367 - val_mae: 1755.6367 Epoch 314/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.1110 - mae: 1949.1110 - val_loss: 1751.0707 - val_mae: 1751.0707 Epoch 315/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.4119 - mae: 1953.4119 - val_loss: 1758.8411 - val_mae: 1758.8411 Epoch 316/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.6378 - mae: 1953.6378 - val_loss: 1752.4923 - val_mae: 1752.4923 Epoch 317/500 34/34 [==============================] - 0s 2ms/step - loss: 1962.7073 - mae: 1962.7073 - val_loss: 1758.3711 - val_mae: 1758.3711 Epoch 318/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.1427 - mae: 1958.1427 - val_loss: 1754.0049 - val_mae: 1754.0049 Epoch 319/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.0283 - mae: 1959.0283 - val_loss: 1763.0295 - val_mae: 1763.0295 Epoch 320/500 34/34 [==============================] - 0s 2ms/step - loss: 1962.1799 - mae: 1962.1799 - val_loss: 1757.9574 - val_mae: 1757.9574 Epoch 321/500 34/34 [==============================] - 0s 2ms/step - loss: 1967.6014 - mae: 1967.6014 - val_loss: 1754.3242 - val_mae: 1754.3242 Epoch 322/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.2101 - mae: 1954.2101 - val_loss: 1755.9860 - val_mae: 1755.9860 Epoch 323/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.6353 - mae: 1957.6353 - val_loss: 1748.1429 - val_mae: 1748.1429 Epoch 324/500 34/34 [==============================] - 0s 2ms/step - loss: 1965.8748 - mae: 1965.8748 - val_loss: 1750.5398 - val_mae: 1750.5398 Epoch 325/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.0470 - mae: 1949.0470 - val_loss: 1764.1530 - val_mae: 1764.1530 Epoch 326/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.1329 - mae: 1952.1329 - val_loss: 1762.7769 - val_mae: 1762.7769 Epoch 327/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.0535 - mae: 1951.0535 - val_loss: 1769.8868 - val_mae: 1769.8868 Epoch 328/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.4520 - mae: 1958.4520 - val_loss: 1764.0299 - val_mae: 1764.0299 Epoch 329/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.4423 - mae: 1961.4423 - val_loss: 1763.5717 - val_mae: 1763.5715 Epoch 330/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.9846 - mae: 1953.9846 - val_loss: 1768.4126 - val_mae: 1768.4126 Epoch 331/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.3615 - mae: 1951.3615 - val_loss: 1757.0254 - val_mae: 1757.0254 Epoch 332/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.7188 - mae: 1954.7188 - val_loss: 1762.9642 - val_mae: 1762.9642 Epoch 333/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.1290 - mae: 1953.1290 - val_loss: 1762.4924 - val_mae: 1762.4924 Epoch 334/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.4161 - mae: 1951.4161 - val_loss: 1757.6155 - val_mae: 1757.6155 Epoch 335/500 34/34 [==============================] - 0s 1ms/step - loss: 1952.3960 - mae: 1952.3960 - val_loss: 1764.6984 - val_mae: 1764.6984 Epoch 336/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.7646 - mae: 1950.7646 - val_loss: 1772.4570 - val_mae: 1772.4570 Epoch 337/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.0762 - mae: 1955.0762 - val_loss: 1770.7056 - val_mae: 1770.7056 Epoch 338/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.9214 - mae: 1959.9214 - val_loss: 1766.1273 - val_mae: 1766.1272 Epoch 339/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.8682 - mae: 1955.8682 - val_loss: 1746.8082 - val_mae: 1746.8082 Epoch 340/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.0269 - mae: 1948.0269 - val_loss: 1759.6322 - val_mae: 1759.6322 Epoch 341/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.8123 - mae: 1949.8123 - val_loss: 1751.2783 - val_mae: 1751.2783 Epoch 342/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.0177 - mae: 1952.0177 - val_loss: 1751.9829 - val_mae: 1751.9829 Epoch 343/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.0615 - mae: 1955.0615 - val_loss: 1761.2970 - val_mae: 1761.2970 Epoch 344/500 34/34 [==============================] - 0s 1ms/step - loss: 1953.7709 - mae: 1953.7709 - val_loss: 1776.7866 - val_mae: 1776.7866 Epoch 345/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.2633 - mae: 1958.2633 - val_loss: 1757.1514 - val_mae: 1757.1514 Epoch 346/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.7467 - mae: 1954.7467 - val_loss: 1754.1384 - val_mae: 1754.1384 Epoch 347/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.5950 - mae: 1953.5950 - val_loss: 1769.6234 - val_mae: 1769.6234 Epoch 348/500 34/34 [==============================] - 0s 2ms/step - loss: 1962.7493 - mae: 1962.7493 - val_loss: 1763.6633 - val_mae: 1763.6633 Epoch 349/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.9203 - mae: 1948.9203 - val_loss: 1761.1244 - val_mae: 1761.1244 Epoch 350/500 34/34 [==============================] - 0s 2ms/step - loss: 1972.8507 - mae: 1972.8507 - val_loss: 1777.9928 - val_mae: 1777.9928 Epoch 351/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.0935 - mae: 1961.0935 - val_loss: 1753.1858 - val_mae: 1753.1858 Epoch 352/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.9105 - mae: 1958.9105 - val_loss: 1763.2803 - val_mae: 1763.2803 Epoch 353/500 34/34 [==============================] - 0s 2ms/step - loss: 1946.5043 - mae: 1946.5043 - val_loss: 1754.3450 - val_mae: 1754.3450 Epoch 354/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.7681 - mae: 1949.7681 - val_loss: 1745.9467 - val_mae: 1745.9467 Epoch 355/500 34/34 [==============================] - 0s 2ms/step - loss: 1946.6383 - mae: 1946.6383 - val_loss: 1757.6488 - val_mae: 1757.6488 Epoch 356/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.1432 - mae: 1950.1432 - val_loss: 1752.2520 - val_mae: 1752.2520 Epoch 357/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.4932 - mae: 1949.4932 - val_loss: 1758.4166 - val_mae: 1758.4166 Epoch 358/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.7157 - mae: 1951.7157 - val_loss: 1784.3848 - val_mae: 1784.3848 Epoch 359/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.7473 - mae: 1949.7473 - val_loss: 1761.4342 - val_mae: 1761.4342 Epoch 360/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.2291 - mae: 1956.2291 - val_loss: 1747.1814 - val_mae: 1747.1814 Epoch 361/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.1675 - mae: 1953.1675 - val_loss: 1754.5613 - val_mae: 1754.5613 Epoch 362/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.4589 - mae: 1953.4589 - val_loss: 1761.6952 - val_mae: 1761.6952 Epoch 363/500 34/34 [==============================] - 0s 2ms/step - loss: 1976.0000 - mae: 1976.0000 - val_loss: 1744.4117 - val_mae: 1744.4117 Epoch 364/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.0414 - mae: 1959.0414 - val_loss: 1762.1742 - val_mae: 1762.1742 Epoch 365/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.8511 - mae: 1949.8511 - val_loss: 1758.6908 - val_mae: 1758.6908 Epoch 366/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.3275 - mae: 1953.3275 - val_loss: 1758.0052 - val_mae: 1758.0052 Epoch 367/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.8618 - mae: 1950.8618 - val_loss: 1744.1410 - val_mae: 1744.1410 Epoch 368/500 34/34 [==============================] - 0s 2ms/step - loss: 1972.1248 - mae: 1972.1248 - val_loss: 1772.6183 - val_mae: 1772.6183 Epoch 369/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.9573 - mae: 1956.9573 - val_loss: 1759.3527 - val_mae: 1759.3527 Epoch 370/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.5968 - mae: 1955.5968 - val_loss: 1765.9628 - val_mae: 1765.9628 Epoch 371/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.3209 - mae: 1958.3209 - val_loss: 1763.1091 - val_mae: 1763.1091 Epoch 372/500 34/34 [==============================] - 0s 2ms/step - loss: 1947.7278 - mae: 1947.7278 - val_loss: 1751.5487 - val_mae: 1751.5487 Epoch 373/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.7825 - mae: 1951.7825 - val_loss: 1762.3896 - val_mae: 1762.3896 Epoch 374/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.2893 - mae: 1954.2893 - val_loss: 1760.6979 - val_mae: 1760.6979 Epoch 375/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.0992 - mae: 1957.0992 - val_loss: 1765.6522 - val_mae: 1765.6522 Epoch 376/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.5472 - mae: 1950.5472 - val_loss: 1761.5393 - val_mae: 1761.5393 Epoch 377/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.2313 - mae: 1952.2313 - val_loss: 1764.2993 - val_mae: 1764.2993 Epoch 378/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.1935 - mae: 1950.1935 - val_loss: 1748.9039 - val_mae: 1748.9039 Epoch 379/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.7526 - mae: 1953.7526 - val_loss: 1754.3691 - val_mae: 1754.3691 Epoch 380/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.4235 - mae: 1955.4235 - val_loss: 1756.1005 - val_mae: 1756.1005 Epoch 381/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.8040 - mae: 1957.8040 - val_loss: 1751.6953 - val_mae: 1751.6953 Epoch 382/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.1229 - mae: 1958.1229 - val_loss: 1747.8070 - val_mae: 1747.8070 Epoch 383/500 34/34 [==============================] - 0s 2ms/step - loss: 1946.6637 - mae: 1946.6637 - val_loss: 1752.1309 - val_mae: 1752.1309 Epoch 384/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.8477 - mae: 1954.8477 - val_loss: 1761.1697 - val_mae: 1761.1697 Epoch 385/500 34/34 [==============================] - 0s 2ms/step - loss: 1965.7804 - mae: 1965.7804 - val_loss: 1754.0254 - val_mae: 1754.0254 Epoch 386/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.3236 - mae: 1958.3236 - val_loss: 1764.0514 - val_mae: 1764.0514 Epoch 387/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.8267 - mae: 1956.8267 - val_loss: 1758.4872 - val_mae: 1758.4872 Epoch 388/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.6726 - mae: 1956.6726 - val_loss: 1756.9443 - val_mae: 1756.9443 Epoch 389/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.9005 - mae: 1957.9005 - val_loss: 1737.4865 - val_mae: 1737.4865 Epoch 390/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.6439 - mae: 1949.6439 - val_loss: 1739.9377 - val_mae: 1739.9377 Epoch 391/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.9272 - mae: 1951.9272 - val_loss: 1756.1089 - val_mae: 1756.1089 Epoch 392/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.8655 - mae: 1953.8655 - val_loss: 1763.0947 - val_mae: 1763.0947 Epoch 393/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.5458 - mae: 1957.5458 - val_loss: 1749.2146 - val_mae: 1749.2146 Epoch 394/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.1083 - mae: 1950.1083 - val_loss: 1746.1954 - val_mae: 1746.1954 Epoch 395/500 34/34 [==============================] - 0s 2ms/step - loss: 1966.8063 - mae: 1966.8063 - val_loss: 1763.3324 - val_mae: 1763.3324 Epoch 396/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.4954 - mae: 1952.4954 - val_loss: 1757.8846 - val_mae: 1757.8846 Epoch 397/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.4414 - mae: 1952.4414 - val_loss: 1754.0262 - val_mae: 1754.0262 Epoch 398/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.2065 - mae: 1948.2065 - val_loss: 1752.7214 - val_mae: 1752.7214 Epoch 399/500 34/34 [==============================] - 0s 2ms/step - loss: 1947.9043 - mae: 1947.9043 - val_loss: 1750.4845 - val_mae: 1750.4845 Epoch 400/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.3918 - mae: 1956.3918 - val_loss: 1759.9824 - val_mae: 1759.9824 Epoch 401/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.9606 - mae: 1955.9606 - val_loss: 1747.9561 - val_mae: 1747.9561 Epoch 402/500 34/34 [==============================] - 0s 2ms/step - loss: 1941.3849 - mae: 1941.3849 - val_loss: 1754.4902 - val_mae: 1754.4902 Epoch 403/500 34/34 [==============================] - 0s 2ms/step - loss: 1943.3167 - mae: 1943.3167 - val_loss: 1754.0844 - val_mae: 1754.0844 Epoch 404/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.5490 - mae: 1949.5490 - val_loss: 1754.5602 - val_mae: 1754.5601 Epoch 405/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.7708 - mae: 1953.7708 - val_loss: 1757.1343 - val_mae: 1757.1343 Epoch 406/500 34/34 [==============================] - 0s 2ms/step - loss: 1944.7001 - mae: 1944.7001 - val_loss: 1754.2170 - val_mae: 1754.2170 Epoch 407/500 34/34 [==============================] - 0s 2ms/step - loss: 1945.4005 - mae: 1945.4005 - val_loss: 1758.1936 - val_mae: 1758.1936 Epoch 408/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.3241 - mae: 1953.3241 - val_loss: 1759.7593 - val_mae: 1759.7593 Epoch 409/500 34/34 [==============================] - 0s 2ms/step - loss: 1944.3270 - mae: 1944.3270 - val_loss: 1756.6381 - val_mae: 1756.6381 Epoch 410/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.6821 - mae: 1957.6821 - val_loss: 1749.7008 - val_mae: 1749.7008 Epoch 411/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.4100 - mae: 1955.4100 - val_loss: 1748.7892 - val_mae: 1748.7892 Epoch 412/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.8435 - mae: 1952.8435 - val_loss: 1758.9407 - val_mae: 1758.9407 Epoch 413/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.5355 - mae: 1954.5355 - val_loss: 1755.9673 - val_mae: 1755.9673 Epoch 414/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.0613 - mae: 1959.0613 - val_loss: 1758.3146 - val_mae: 1758.3146 Epoch 415/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.1749 - mae: 1955.1749 - val_loss: 1741.0492 - val_mae: 1741.0492 Epoch 416/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.3885 - mae: 1954.3885 - val_loss: 1754.9452 - val_mae: 1754.9452 Epoch 417/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.5027 - mae: 1954.5027 - val_loss: 1756.1047 - val_mae: 1756.1047 Epoch 418/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.7993 - mae: 1951.7993 - val_loss: 1751.6759 - val_mae: 1751.6759 Epoch 419/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.9473 - mae: 1956.9473 - val_loss: 1756.7864 - val_mae: 1756.7864 Epoch 420/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.1915 - mae: 1948.1915 - val_loss: 1763.8118 - val_mae: 1763.8118 Epoch 421/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.2238 - mae: 1950.2238 - val_loss: 1746.9730 - val_mae: 1746.9730 Epoch 422/500 34/34 [==============================] - 0s 2ms/step - loss: 1947.8093 - mae: 1947.8093 - val_loss: 1752.2904 - val_mae: 1752.2904 Epoch 423/500 34/34 [==============================] - 0s 2ms/step - loss: 1944.5515 - mae: 1944.5515 - val_loss: 1771.6937 - val_mae: 1771.6937 Epoch 424/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.9481 - mae: 1950.9481 - val_loss: 1754.7682 - val_mae: 1754.7682 Epoch 425/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.0114 - mae: 1951.0114 - val_loss: 1750.5623 - val_mae: 1750.5623 Epoch 426/500 34/34 [==============================] - 0s 2ms/step - loss: 1947.3135 - mae: 1947.3135 - val_loss: 1748.2422 - val_mae: 1748.2422 Epoch 427/500 34/34 [==============================] - 0s 2ms/step - loss: 1962.6624 - mae: 1962.6624 - val_loss: 1743.6954 - val_mae: 1743.6954 Epoch 428/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.7063 - mae: 1950.7063 - val_loss: 1759.4097 - val_mae: 1759.4097 Epoch 429/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.3193 - mae: 1955.3193 - val_loss: 1745.2053 - val_mae: 1745.2053 Epoch 430/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.6218 - mae: 1953.6218 - val_loss: 1762.4940 - val_mae: 1762.4940 Epoch 431/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.9666 - mae: 1952.9666 - val_loss: 1760.6790 - val_mae: 1760.6790 Epoch 432/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.8594 - mae: 1955.8594 - val_loss: 1756.6204 - val_mae: 1756.6204 Epoch 433/500 34/34 [==============================] - 0s 2ms/step - loss: 1947.9142 - mae: 1947.9142 - val_loss: 1755.0618 - val_mae: 1755.0616 Epoch 434/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.4448 - mae: 1949.4448 - val_loss: 1751.0273 - val_mae: 1751.0273 Epoch 435/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.0499 - mae: 1954.0499 - val_loss: 1770.4410 - val_mae: 1770.4410 Epoch 436/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.2693 - mae: 1950.2693 - val_loss: 1755.4609 - val_mae: 1755.4609 Epoch 437/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.0602 - mae: 1952.0602 - val_loss: 1758.6973 - val_mae: 1758.6973 Epoch 438/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.9181 - mae: 1952.9181 - val_loss: 1757.1066 - val_mae: 1757.1066 Epoch 439/500 34/34 [==============================] - 0s 2ms/step - loss: 1962.9031 - mae: 1962.9031 - val_loss: 1750.6654 - val_mae: 1750.6654 Epoch 440/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.3645 - mae: 1948.3645 - val_loss: 1755.0796 - val_mae: 1755.0796 Epoch 441/500 34/34 [==============================] - 0s 2ms/step - loss: 1964.3591 - mae: 1964.3591 - val_loss: 1745.6477 - val_mae: 1745.6477 Epoch 442/500 34/34 [==============================] - 0s 2ms/step - loss: 1944.2411 - mae: 1944.2411 - val_loss: 1750.2649 - val_mae: 1750.2649 Epoch 443/500 34/34 [==============================] - 0s 2ms/step - loss: 1945.4633 - mae: 1945.4633 - val_loss: 1761.6448 - val_mae: 1761.6448 Epoch 444/500 34/34 [==============================] - 0s 2ms/step - loss: 1944.9739 - mae: 1944.9739 - val_loss: 1758.9583 - val_mae: 1758.9583 Epoch 445/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.4044 - mae: 1958.4044 - val_loss: 1759.6649 - val_mae: 1759.6649 Epoch 446/500 34/34 [==============================] - 0s 1ms/step - loss: 1969.0897 - mae: 1969.0897 - val_loss: 1753.5978 - val_mae: 1753.5978 Epoch 447/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.5836 - mae: 1948.5836 - val_loss: 1747.1993 - val_mae: 1747.1993 Epoch 448/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.2635 - mae: 1949.2635 - val_loss: 1756.9629 - val_mae: 1756.9629 Epoch 449/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.5714 - mae: 1950.5714 - val_loss: 1752.6770 - val_mae: 1752.6770 Epoch 450/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.8744 - mae: 1955.8744 - val_loss: 1749.4503 - val_mae: 1749.4503 Epoch 451/500 34/34 [==============================] - 0s 2ms/step - loss: 1941.1742 - mae: 1941.1742 - val_loss: 1749.6925 - val_mae: 1749.6925 Epoch 452/500 34/34 [==============================] - 0s 2ms/step - loss: 1946.8116 - mae: 1946.8116 - val_loss: 1758.3607 - val_mae: 1758.3607 Epoch 453/500 34/34 [==============================] - 0s 2ms/step - loss: 1947.7488 - mae: 1947.7488 - val_loss: 1751.2559 - val_mae: 1751.2559 Epoch 454/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.8512 - mae: 1948.8512 - val_loss: 1754.0320 - val_mae: 1754.0320 Epoch 455/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.5576 - mae: 1956.5576 - val_loss: 1764.3871 - val_mae: 1764.3871 Epoch 456/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.4485 - mae: 1949.4485 - val_loss: 1762.3010 - val_mae: 1762.3010 Epoch 457/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.4291 - mae: 1959.4291 - val_loss: 1761.3749 - val_mae: 1761.3749 Epoch 458/500 34/34 [==============================] - 0s 2ms/step - loss: 1959.7554 - mae: 1959.7554 - val_loss: 1767.1168 - val_mae: 1767.1168 Epoch 459/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.9146 - mae: 1952.9146 - val_loss: 1754.0270 - val_mae: 1754.0270 Epoch 460/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.2982 - mae: 1948.2982 - val_loss: 1753.8359 - val_mae: 1753.8359 Epoch 461/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.1692 - mae: 1955.1692 - val_loss: 1747.7649 - val_mae: 1747.7649 Epoch 462/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.5964 - mae: 1957.5964 - val_loss: 1743.2943 - val_mae: 1743.2943 Epoch 463/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.3003 - mae: 1955.3003 - val_loss: 1736.1887 - val_mae: 1736.1887 Epoch 464/500 34/34 [==============================] - 0s 2ms/step - loss: 1947.2417 - mae: 1947.2417 - val_loss: 1753.8684 - val_mae: 1753.8684 Epoch 465/500 34/34 [==============================] - 0s 2ms/step - loss: 1967.0166 - mae: 1967.0166 - val_loss: 1772.1665 - val_mae: 1772.1665 Epoch 466/500 34/34 [==============================] - 0s 2ms/step - loss: 1960.2444 - mae: 1960.2444 - val_loss: 1755.9545 - val_mae: 1755.9545 Epoch 467/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.8490 - mae: 1957.8490 - val_loss: 1753.0928 - val_mae: 1753.0928 Epoch 468/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.4043 - mae: 1955.4043 - val_loss: 1761.1515 - val_mae: 1761.1515 Epoch 469/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.5554 - mae: 1958.5554 - val_loss: 1755.3362 - val_mae: 1755.3362 Epoch 470/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.7463 - mae: 1954.7463 - val_loss: 1760.5854 - val_mae: 1760.5854 Epoch 471/500 34/34 [==============================] - 0s 2ms/step - loss: 1963.0171 - mae: 1963.0171 - val_loss: 1750.7061 - val_mae: 1750.7061 Epoch 472/500 34/34 [==============================] - 0s 1ms/step - loss: 1958.8883 - mae: 1958.8883 - val_loss: 1761.9213 - val_mae: 1761.9213 Epoch 473/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.8362 - mae: 1950.8362 - val_loss: 1756.2852 - val_mae: 1756.2852 Epoch 474/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.9043 - mae: 1948.9043 - val_loss: 1747.6663 - val_mae: 1747.6663 Epoch 475/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.0776 - mae: 1953.0776 - val_loss: 1761.8174 - val_mae: 1761.8174 Epoch 476/500 34/34 [==============================] - 0s 2ms/step - loss: 1957.2098 - mae: 1957.2098 - val_loss: 1746.7466 - val_mae: 1746.7466 Epoch 477/500 34/34 [==============================] - 0s 2ms/step - loss: 1953.1517 - mae: 1953.1517 - val_loss: 1756.0098 - val_mae: 1756.0098 Epoch 478/500 34/34 [==============================] - 0s 2ms/step - loss: 1960.5311 - mae: 1960.5311 - val_loss: 1751.1040 - val_mae: 1751.1040 Epoch 479/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.0209 - mae: 1958.0209 - val_loss: 1756.1705 - val_mae: 1756.1705 Epoch 480/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.3047 - mae: 1954.3047 - val_loss: 1747.0914 - val_mae: 1747.0914 Epoch 481/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.5564 - mae: 1948.5564 - val_loss: 1754.9144 - val_mae: 1754.9144 Epoch 482/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.6371 - mae: 1949.6371 - val_loss: 1742.7290 - val_mae: 1742.7290 Epoch 483/500 34/34 [==============================] - 0s 2ms/step - loss: 1955.9745 - mae: 1955.9745 - val_loss: 1759.7681 - val_mae: 1759.7681 Epoch 484/500 34/34 [==============================] - 0s 2ms/step - loss: 1962.0938 - mae: 1962.0938 - val_loss: 1748.1960 - val_mae: 1748.1960 Epoch 485/500 34/34 [==============================] - 0s 1ms/step - loss: 1946.9153 - mae: 1946.9153 - val_loss: 1759.8531 - val_mae: 1759.8531 Epoch 486/500 34/34 [==============================] - 0s 2ms/step - loss: 1954.7581 - mae: 1954.7581 - val_loss: 1766.8878 - val_mae: 1766.8878 Epoch 487/500 34/34 [==============================] - 0s 2ms/step - loss: 1952.4418 - mae: 1952.4418 - val_loss: 1759.1333 - val_mae: 1759.1333 Epoch 488/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.7568 - mae: 1951.7568 - val_loss: 1749.5972 - val_mae: 1749.5972 Epoch 489/500 34/34 [==============================] - 0s 2ms/step - loss: 1941.7734 - mae: 1941.7734 - val_loss: 1757.6304 - val_mae: 1757.6304 Epoch 490/500 34/34 [==============================] - 0s 2ms/step - loss: 1949.5865 - mae: 1949.5865 - val_loss: 1770.8793 - val_mae: 1770.8793 Epoch 491/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.8700 - mae: 1950.8700 - val_loss: 1746.2600 - val_mae: 1746.2600 Epoch 492/500 34/34 [==============================] - 0s 2ms/step - loss: 1961.3124 - mae: 1961.3124 - val_loss: 1751.8602 - val_mae: 1751.8602 Epoch 493/500 34/34 [==============================] - 0s 1ms/step - loss: 1943.8804 - mae: 1943.8804 - val_loss: 1742.9180 - val_mae: 1742.9180 Epoch 494/500 34/34 [==============================] - 0s 2ms/step - loss: 1937.7426 - mae: 1937.7426 - val_loss: 1760.8480 - val_mae: 1760.8480 Epoch 495/500 34/34 [==============================] - 0s 2ms/step - loss: 1958.6722 - mae: 1958.6722 - val_loss: 1759.0151 - val_mae: 1759.0151 Epoch 496/500 34/34 [==============================] - 0s 2ms/step - loss: 1948.9408 - mae: 1948.9408 - val_loss: 1758.3007 - val_mae: 1758.3007 Epoch 497/500 34/34 [==============================] - 0s 2ms/step - loss: 1951.5358 - mae: 1951.5358 - val_loss: 1752.7567 - val_mae: 1752.7567 Epoch 498/500 34/34 [==============================] - 0s 1ms/step - loss: 1973.8839 - mae: 1973.8839 - val_loss: 1755.8190 - val_mae: 1755.8190 Epoch 499/500 34/34 [==============================] - 0s 2ms/step - loss: 1956.9613 - mae: 1956.9613 - val_loss: 1756.0472 - val_mae: 1756.0472 Epoch 500/500 34/34 [==============================] - 0s 2ms/step - loss: 1950.9912 - mae: 1950.9912 - val_loss: 1755.3545 - val_mae: 1755.3545
<keras.src.callbacks.History at 0x1dbd2dd4c10>
model_preds = model.predict(scaled_X_test)
9/9 [==============================] - 0s 894us/step
r2_score(y_true = y_test ,y_pred = model_preds)
0.8621520814130484