import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
import sklearn
import tensorflow as tf
from tensorflow import keras
from keras.models import Sequential
from keras.layers import Dense
from sklearn.metrics import accuracy_score
dataset = pd.read_csv('/content/diabetes.csv')
dataset.head()#viewing the head of the dataset
Pregnancies | Glucose | BloodPressure | SkinThickness | Insulin | BMI | DiabetesPedigreeFunction | Age | Outcome | |
---|---|---|---|---|---|---|---|---|---|
0 | 6 | 148 | 72 | 35 | 0 | 33.6 | 0.627 | 50 | 1 |
1 | 1 | 85 | 66 | 29 | 0 | 26.6 | 0.351 | 31 | 0 |
2 | 8 | 183 | 64 | 0 | 0 | 23.3 | 0.672 | 32 | 1 |
3 | 1 | 89 | 66 | 23 | 94 | 28.1 | 0.167 | 21 | 0 |
4 | 0 | 137 | 40 | 35 | 168 | 43.1 | 2.288 | 33 | 1 |
dataset.info(verbose=True)
<class 'pandas.core.frame.DataFrame'> RangeIndex: 768 entries, 0 to 767 Data columns (total 9 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 Pregnancies 768 non-null int64 1 Glucose 768 non-null int64 2 BloodPressure 768 non-null int64 3 SkinThickness 768 non-null int64 4 Insulin 768 non-null int64 5 BMI 768 non-null float64 6 DiabetesPedigreeFunction 768 non-null float64 7 Age 768 non-null int64 8 Outcome 768 non-null int64 dtypes: float64(2), int64(7) memory usage: 54.1 KB
#finding the shape of the dataset
dataset.shape
(768, 9)
#finding out the null values of the dataset
dataset.isnull().sum()
Pregnancies 0 Glucose 0 BloodPressure 0 SkinThickness 0 Insulin 0 BMI 0 DiabetesPedigreeFunction 0 Age 0 Outcome 0 dtype: int64
f, ax = plt.subplots(1, 2, figsize = (12, 6))
f.suptitle("Diabetes?", fontsize = 18.)
_ = dataset.Outcome.value_counts().plot.bar(ax = ax[0], rot = 0,
color = (sns.color_palette()[0], sns.color_palette()[2])).set(xticklabels = ["No", "Yes"])
_ = dataset.Outcome.value_counts().plot.pie(labels = ("No", "Yes"), autopct = "%.2f%%",
label = "", fontsize = 13., ax = ax[1],\
colors = (sns.color_palette()[0], sns.color_palette()[2]), wedgeprops = {"linewidth": 1.5, "edgecolor": "#F7F7F7"}),
ax[1].texts[1].set_color("#F7F7F7"), ax[1].texts[3].set_color("#F7F7F7")
(None, None)
#this is also a one way to find the missing values in the dataset
dataset.describe()
Pregnancies | Glucose | BloodPressure | SkinThickness | Insulin | BMI | DiabetesPedigreeFunction | Age | Outcome | |
---|---|---|---|---|---|---|---|---|---|
count | 768.000000 | 768.000000 | 768.000000 | 768.000000 | 768.000000 | 768.000000 | 768.000000 | 768.000000 | 768.000000 |
mean | 3.845052 | 120.894531 | 69.105469 | 20.536458 | 79.799479 | 31.992578 | 0.471876 | 33.240885 | 0.348958 |
std | 3.369578 | 31.972618 | 19.355807 | 15.952218 | 115.244002 | 7.884160 | 0.331329 | 11.760232 | 0.476951 |
min | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.078000 | 21.000000 | 0.000000 |
25% | 1.000000 | 99.000000 | 62.000000 | 0.000000 | 0.000000 | 27.300000 | 0.243750 | 24.000000 | 0.000000 |
50% | 3.000000 | 117.000000 | 72.000000 | 23.000000 | 30.500000 | 32.000000 | 0.372500 | 29.000000 | 0.000000 |
75% | 6.000000 | 140.250000 | 80.000000 | 32.000000 | 127.250000 | 36.600000 | 0.626250 | 41.000000 | 1.000000 |
max | 17.000000 | 199.000000 | 122.000000 | 99.000000 | 846.000000 | 67.100000 | 2.420000 | 81.000000 | 1.000000 |
dataset.dtypes
Pregnancies int64 Glucose int64 BloodPressure int64 SkinThickness int64 Insulin int64 BMI float64 DiabetesPedigreeFunction float64 Age int64 Outcome int64 dtype: object
plt.style.use('classic')
plot = dataset.hist(figsize = (20,20))
#Scatter matrix of uncleaned data
sns.pairplot(dataset )
<seaborn.axisgrid.PairGrid at 0x7f906cc1ad90>
#Pair plot for clean data
sns.pairplot(data=dataset,hue='Outcome',diag_kind='kde', kind="reg")
plt.show()
plt.figure(figsize = [10, 10])
sns.heatmap(dataset.corr(), annot = True, fmt = '.3f', cmap = 'vlag_r', center = 0);
print(np.array(dataset))
[[ 6. 148. 72. ... 0.627 50. 1. ] [ 1. 85. 66. ... 0.351 31. 0. ] [ 8. 183. 64. ... 0.672 32. 1. ] ... [ 5. 121. 72. ... 0.245 30. 0. ] [ 1. 126. 60. ... 0.349 47. 1. ] [ 1. 93. 70. ... 0.315 23. 0. ]]
# drop columns number 9
train_data_x = dataset.drop(columns = 'Outcome', axis = 1)
train_data_y = dataset['Outcome']
train_Data, test_Data, train_Out, test_Out = train_test_split(train_data_x,train_data_y,test_size=0.2, random_state=10)
print(train_Out)
120 1 172 0 307 0 7 0 448 1 .. 369 1 320 0 527 0 125 1 265 0 Name: Outcome, Length: 614, dtype: int64
data_model = Sequential()
data_model.add(Dense(100, input_dim=8, activation='sigmoid'))
data_model.add(Dense(50, activation='sigmoid'))
data_model.add(Dense(30, activation='sigmoid'))
data_model.add(Dense(10, activation='sigmoid'))
data_model.add(Dense(1, activation='sigmoid'))
data_model.compile(loss='MSE', optimizer='adam', metrics=['accuracy'])
print(data_model.summary())
Model: "sequential" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= dense (Dense) (None, 100) 900 dense_1 (Dense) (None, 50) 5050 dense_2 (Dense) (None, 30) 1530 dense_3 (Dense) (None, 10) 310 dense_4 (Dense) (None, 1) 11 ================================================================= Total params: 7,801 Trainable params: 7,801 Non-trainable params: 0 _________________________________________________________________ None
# Compile model
# using opimizer Adam
# using loss binary_crossentropy
# data_model.compile(optimizer=tf.keras.optimizers.Adam(), loss=tf.keras.losses.binary_crossentropy, metrics=['accuracy'])
data_model.compile(optimizer='Adam', loss="binary_crossentropy", metrics=['accuracy'])
hist = data_model.fit(train_Data, train_Out, validation_data=(test_Data, test_Out), epochs=1000, verbose=1)
Epoch 1/1000 20/20 [==============================] - 4s 12ms/step - loss: 0.8789 - accuracy: 0.3404 - val_loss: 0.7690 - val_accuracy: 0.3831 Epoch 2/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.7425 - accuracy: 0.3404 - val_loss: 0.6943 - val_accuracy: 0.3831 Epoch 3/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6785 - accuracy: 0.6384 - val_loss: 0.6710 - val_accuracy: 0.6169 Epoch 4/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6539 - accuracy: 0.6596 - val_loss: 0.6655 - val_accuracy: 0.6169 Epoch 5/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.6453 - accuracy: 0.6596 - val_loss: 0.6653 - val_accuracy: 0.6169 Epoch 6/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.6421 - accuracy: 0.6596 - val_loss: 0.6666 - val_accuracy: 0.6169 Epoch 7/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6412 - accuracy: 0.6596 - val_loss: 0.6677 - val_accuracy: 0.6169 Epoch 8/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6406 - accuracy: 0.6596 - val_loss: 0.6676 - val_accuracy: 0.6169 Epoch 9/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6402 - accuracy: 0.6596 - val_loss: 0.6670 - val_accuracy: 0.6169 Epoch 10/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6399 - accuracy: 0.6596 - val_loss: 0.6665 - val_accuracy: 0.6169 Epoch 11/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6394 - accuracy: 0.6596 - val_loss: 0.6664 - val_accuracy: 0.6169 Epoch 12/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.6387 - accuracy: 0.6596 - val_loss: 0.6662 - val_accuracy: 0.6169 Epoch 13/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6379 - accuracy: 0.6596 - val_loss: 0.6651 - val_accuracy: 0.6169 Epoch 14/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6366 - accuracy: 0.6596 - val_loss: 0.6624 - val_accuracy: 0.6169 Epoch 15/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6347 - accuracy: 0.6596 - val_loss: 0.6599 - val_accuracy: 0.6169 Epoch 16/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.6324 - accuracy: 0.6596 - val_loss: 0.6563 - val_accuracy: 0.6169 Epoch 17/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6291 - accuracy: 0.6596 - val_loss: 0.6502 - val_accuracy: 0.6169 Epoch 18/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6243 - accuracy: 0.6596 - val_loss: 0.6437 - val_accuracy: 0.6169 Epoch 19/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.6185 - accuracy: 0.6596 - val_loss: 0.6360 - val_accuracy: 0.6169 Epoch 20/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.6110 - accuracy: 0.6596 - val_loss: 0.6279 - val_accuracy: 0.6169 Epoch 21/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.6046 - accuracy: 0.6645 - val_loss: 0.6205 - val_accuracy: 0.6234 Epoch 22/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.5988 - accuracy: 0.6678 - val_loss: 0.6147 - val_accuracy: 0.6753 Epoch 23/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5896 - accuracy: 0.6840 - val_loss: 0.6098 - val_accuracy: 0.6948 Epoch 24/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5840 - accuracy: 0.7085 - val_loss: 0.6065 - val_accuracy: 0.7013 Epoch 25/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.5782 - accuracy: 0.7215 - val_loss: 0.6066 - val_accuracy: 0.6948 Epoch 26/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5722 - accuracy: 0.7085 - val_loss: 0.5974 - val_accuracy: 0.6948 Epoch 27/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5625 - accuracy: 0.7378 - val_loss: 0.5956 - val_accuracy: 0.7013 Epoch 28/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5561 - accuracy: 0.7508 - val_loss: 0.6066 - val_accuracy: 0.6948 Epoch 29/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5535 - accuracy: 0.7264 - val_loss: 0.5895 - val_accuracy: 0.6883 Epoch 30/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5510 - accuracy: 0.7329 - val_loss: 0.5905 - val_accuracy: 0.7013 Epoch 31/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5397 - accuracy: 0.7508 - val_loss: 0.6153 - val_accuracy: 0.6753 Epoch 32/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5534 - accuracy: 0.7215 - val_loss: 0.6080 - val_accuracy: 0.6688 Epoch 33/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5520 - accuracy: 0.7134 - val_loss: 0.5950 - val_accuracy: 0.6818 Epoch 34/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5348 - accuracy: 0.7427 - val_loss: 0.5843 - val_accuracy: 0.6948 Epoch 35/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5317 - accuracy: 0.7492 - val_loss: 0.5855 - val_accuracy: 0.6688 Epoch 36/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.5317 - accuracy: 0.7573 - val_loss: 0.5985 - val_accuracy: 0.6818 Epoch 37/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5367 - accuracy: 0.7541 - val_loss: 0.5840 - val_accuracy: 0.6883 Epoch 38/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5279 - accuracy: 0.7476 - val_loss: 0.5753 - val_accuracy: 0.6818 Epoch 39/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5209 - accuracy: 0.7622 - val_loss: 0.5835 - val_accuracy: 0.6883 Epoch 40/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5197 - accuracy: 0.7557 - val_loss: 0.5837 - val_accuracy: 0.6818 Epoch 41/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.5341 - accuracy: 0.7280 - val_loss: 0.5920 - val_accuracy: 0.6883 Epoch 42/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5138 - accuracy: 0.7638 - val_loss: 0.5822 - val_accuracy: 0.6948 Epoch 43/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.5212 - accuracy: 0.7524 - val_loss: 0.5780 - val_accuracy: 0.7013 Epoch 44/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.5101 - accuracy: 0.7573 - val_loss: 0.5799 - val_accuracy: 0.6753 Epoch 45/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5127 - accuracy: 0.7590 - val_loss: 0.5852 - val_accuracy: 0.7013 Epoch 46/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5098 - accuracy: 0.7573 - val_loss: 0.5746 - val_accuracy: 0.7078 Epoch 47/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.5026 - accuracy: 0.7638 - val_loss: 0.5746 - val_accuracy: 0.6948 Epoch 48/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.5065 - accuracy: 0.7573 - val_loss: 0.5861 - val_accuracy: 0.6818 Epoch 49/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.5260 - accuracy: 0.7427 - val_loss: 0.6334 - val_accuracy: 0.6623 Epoch 50/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.5164 - accuracy: 0.7524 - val_loss: 0.5835 - val_accuracy: 0.6948 Epoch 51/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5016 - accuracy: 0.7606 - val_loss: 0.5786 - val_accuracy: 0.7013 Epoch 52/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4971 - accuracy: 0.7736 - val_loss: 0.5807 - val_accuracy: 0.7078 Epoch 53/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4993 - accuracy: 0.7606 - val_loss: 0.5828 - val_accuracy: 0.7013 Epoch 54/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4993 - accuracy: 0.7720 - val_loss: 0.5791 - val_accuracy: 0.7013 Epoch 55/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4941 - accuracy: 0.7785 - val_loss: 0.5911 - val_accuracy: 0.6883 Epoch 56/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.5042 - accuracy: 0.7671 - val_loss: 0.5702 - val_accuracy: 0.7273 Epoch 57/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4933 - accuracy: 0.7752 - val_loss: 0.5782 - val_accuracy: 0.7143 Epoch 58/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4915 - accuracy: 0.7818 - val_loss: 0.5795 - val_accuracy: 0.7078 Epoch 59/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4907 - accuracy: 0.7785 - val_loss: 0.6065 - val_accuracy: 0.6883 Epoch 60/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4921 - accuracy: 0.7752 - val_loss: 0.5827 - val_accuracy: 0.7078 Epoch 61/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4923 - accuracy: 0.7752 - val_loss: 0.5746 - val_accuracy: 0.7013 Epoch 62/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4822 - accuracy: 0.7964 - val_loss: 0.5886 - val_accuracy: 0.6818 Epoch 63/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4866 - accuracy: 0.7834 - val_loss: 0.5759 - val_accuracy: 0.7143 Epoch 64/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4792 - accuracy: 0.7915 - val_loss: 0.6156 - val_accuracy: 0.6623 Epoch 65/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4860 - accuracy: 0.7866 - val_loss: 0.5929 - val_accuracy: 0.6948 Epoch 66/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4795 - accuracy: 0.7850 - val_loss: 0.5979 - val_accuracy: 0.7013 Epoch 67/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4747 - accuracy: 0.7915 - val_loss: 0.5937 - val_accuracy: 0.6883 Epoch 68/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4820 - accuracy: 0.7932 - val_loss: 0.5907 - val_accuracy: 0.7078 Epoch 69/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4736 - accuracy: 0.7964 - val_loss: 0.5815 - val_accuracy: 0.6883 Epoch 70/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4669 - accuracy: 0.8046 - val_loss: 0.5999 - val_accuracy: 0.6948 Epoch 71/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4805 - accuracy: 0.7752 - val_loss: 0.6018 - val_accuracy: 0.6948 Epoch 72/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4695 - accuracy: 0.7997 - val_loss: 0.6035 - val_accuracy: 0.6818 Epoch 73/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4732 - accuracy: 0.7932 - val_loss: 0.6034 - val_accuracy: 0.6818 Epoch 74/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4688 - accuracy: 0.7932 - val_loss: 0.5817 - val_accuracy: 0.7143 Epoch 75/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4658 - accuracy: 0.7948 - val_loss: 0.5926 - val_accuracy: 0.6883 Epoch 76/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4711 - accuracy: 0.7883 - val_loss: 0.5927 - val_accuracy: 0.7013 Epoch 77/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4711 - accuracy: 0.8029 - val_loss: 0.5829 - val_accuracy: 0.7143 Epoch 78/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4697 - accuracy: 0.7932 - val_loss: 0.6051 - val_accuracy: 0.6688 Epoch 79/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4700 - accuracy: 0.8046 - val_loss: 0.5796 - val_accuracy: 0.6948 Epoch 80/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4634 - accuracy: 0.7980 - val_loss: 0.5977 - val_accuracy: 0.6883 Epoch 81/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4653 - accuracy: 0.7899 - val_loss: 0.5905 - val_accuracy: 0.7013 Epoch 82/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4629 - accuracy: 0.7883 - val_loss: 0.5891 - val_accuracy: 0.6948 Epoch 83/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4553 - accuracy: 0.8013 - val_loss: 0.5863 - val_accuracy: 0.7078 Epoch 84/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4546 - accuracy: 0.8062 - val_loss: 0.5887 - val_accuracy: 0.6948 Epoch 85/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4591 - accuracy: 0.7980 - val_loss: 0.6159 - val_accuracy: 0.6883 Epoch 86/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4511 - accuracy: 0.8111 - val_loss: 0.6307 - val_accuracy: 0.6623 Epoch 87/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4554 - accuracy: 0.7997 - val_loss: 0.6519 - val_accuracy: 0.6494 Epoch 88/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4579 - accuracy: 0.7899 - val_loss: 0.6038 - val_accuracy: 0.6883 Epoch 89/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4441 - accuracy: 0.8225 - val_loss: 0.5942 - val_accuracy: 0.7078 Epoch 90/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4569 - accuracy: 0.8062 - val_loss: 0.5899 - val_accuracy: 0.7143 Epoch 91/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4614 - accuracy: 0.8046 - val_loss: 0.6025 - val_accuracy: 0.6818 Epoch 92/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4598 - accuracy: 0.8029 - val_loss: 0.5942 - val_accuracy: 0.7143 Epoch 93/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4445 - accuracy: 0.8143 - val_loss: 0.6040 - val_accuracy: 0.6818 Epoch 94/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4440 - accuracy: 0.8078 - val_loss: 0.6037 - val_accuracy: 0.7013 Epoch 95/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4443 - accuracy: 0.8094 - val_loss: 0.6138 - val_accuracy: 0.6753 Epoch 96/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4447 - accuracy: 0.8078 - val_loss: 0.6321 - val_accuracy: 0.6883 Epoch 97/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4398 - accuracy: 0.8225 - val_loss: 0.6227 - val_accuracy: 0.6688 Epoch 98/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4376 - accuracy: 0.8094 - val_loss: 0.5922 - val_accuracy: 0.7273 Epoch 99/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4324 - accuracy: 0.8257 - val_loss: 0.6071 - val_accuracy: 0.6753 Epoch 100/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4471 - accuracy: 0.8029 - val_loss: 0.6003 - val_accuracy: 0.7013 Epoch 101/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4441 - accuracy: 0.8127 - val_loss: 0.5999 - val_accuracy: 0.7078 Epoch 102/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4322 - accuracy: 0.8208 - val_loss: 0.5907 - val_accuracy: 0.7208 Epoch 103/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4384 - accuracy: 0.8192 - val_loss: 0.5903 - val_accuracy: 0.7338 Epoch 104/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4433 - accuracy: 0.8111 - val_loss: 0.5921 - val_accuracy: 0.7078 Epoch 105/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4397 - accuracy: 0.8208 - val_loss: 0.6069 - val_accuracy: 0.7013 Epoch 106/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4494 - accuracy: 0.8160 - val_loss: 0.5971 - val_accuracy: 0.7143 Epoch 107/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4365 - accuracy: 0.8094 - val_loss: 0.5971 - val_accuracy: 0.7078 Epoch 108/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4383 - accuracy: 0.8241 - val_loss: 0.6237 - val_accuracy: 0.6883 Epoch 109/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4388 - accuracy: 0.8192 - val_loss: 0.6017 - val_accuracy: 0.7078 Epoch 110/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4291 - accuracy: 0.8274 - val_loss: 0.6015 - val_accuracy: 0.7208 Epoch 111/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4315 - accuracy: 0.8274 - val_loss: 0.6007 - val_accuracy: 0.7273 Epoch 112/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4249 - accuracy: 0.8176 - val_loss: 0.6698 - val_accuracy: 0.6558 Epoch 113/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4298 - accuracy: 0.8160 - val_loss: 0.6016 - val_accuracy: 0.7338 Epoch 114/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4172 - accuracy: 0.8355 - val_loss: 0.6209 - val_accuracy: 0.6818 Epoch 115/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4167 - accuracy: 0.8306 - val_loss: 0.6222 - val_accuracy: 0.6818 Epoch 116/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4314 - accuracy: 0.8176 - val_loss: 0.6181 - val_accuracy: 0.6883 Epoch 117/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4411 - accuracy: 0.8127 - val_loss: 0.6313 - val_accuracy: 0.6688 Epoch 118/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4280 - accuracy: 0.8257 - val_loss: 0.5963 - val_accuracy: 0.7013 Epoch 119/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4225 - accuracy: 0.8274 - val_loss: 0.6186 - val_accuracy: 0.6883 Epoch 120/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4130 - accuracy: 0.8290 - val_loss: 0.5828 - val_accuracy: 0.7208 Epoch 121/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4128 - accuracy: 0.8371 - val_loss: 0.5909 - val_accuracy: 0.7208 Epoch 122/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4212 - accuracy: 0.8322 - val_loss: 0.6014 - val_accuracy: 0.7078 Epoch 123/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4103 - accuracy: 0.8371 - val_loss: 0.5990 - val_accuracy: 0.7208 Epoch 124/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4074 - accuracy: 0.8453 - val_loss: 0.6099 - val_accuracy: 0.6818 Epoch 125/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4143 - accuracy: 0.8241 - val_loss: 0.6200 - val_accuracy: 0.6883 Epoch 126/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4143 - accuracy: 0.8339 - val_loss: 0.6038 - val_accuracy: 0.7208 Epoch 127/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4319 - accuracy: 0.8225 - val_loss: 0.6326 - val_accuracy: 0.6948 Epoch 128/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4218 - accuracy: 0.8371 - val_loss: 0.6001 - val_accuracy: 0.7078 Epoch 129/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4213 - accuracy: 0.8322 - val_loss: 0.6143 - val_accuracy: 0.7273 Epoch 130/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4045 - accuracy: 0.8339 - val_loss: 0.6281 - val_accuracy: 0.6818 Epoch 131/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4102 - accuracy: 0.8339 - val_loss: 0.6289 - val_accuracy: 0.7013 Epoch 132/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4410 - accuracy: 0.8143 - val_loss: 0.6415 - val_accuracy: 0.6753 Epoch 133/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4355 - accuracy: 0.8143 - val_loss: 0.6069 - val_accuracy: 0.7013 Epoch 134/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4117 - accuracy: 0.8371 - val_loss: 0.6428 - val_accuracy: 0.6818 Epoch 135/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4116 - accuracy: 0.8453 - val_loss: 0.6436 - val_accuracy: 0.6688 Epoch 136/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4100 - accuracy: 0.8290 - val_loss: 0.6270 - val_accuracy: 0.6883 Epoch 137/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4148 - accuracy: 0.8290 - val_loss: 0.6086 - val_accuracy: 0.7078 Epoch 138/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4080 - accuracy: 0.8322 - val_loss: 0.5890 - val_accuracy: 0.7468 Epoch 139/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3965 - accuracy: 0.8534 - val_loss: 0.6188 - val_accuracy: 0.7078 Epoch 140/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3932 - accuracy: 0.8502 - val_loss: 0.6171 - val_accuracy: 0.6883 Epoch 141/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3955 - accuracy: 0.8290 - val_loss: 0.6132 - val_accuracy: 0.7208 Epoch 142/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4046 - accuracy: 0.8339 - val_loss: 0.6006 - val_accuracy: 0.7208 Epoch 143/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4017 - accuracy: 0.8371 - val_loss: 0.6676 - val_accuracy: 0.6623 Epoch 144/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3974 - accuracy: 0.8436 - val_loss: 0.6066 - val_accuracy: 0.6883 Epoch 145/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4078 - accuracy: 0.8306 - val_loss: 0.6065 - val_accuracy: 0.7143 Epoch 146/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3896 - accuracy: 0.8534 - val_loss: 0.6344 - val_accuracy: 0.6818 Epoch 147/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3908 - accuracy: 0.8550 - val_loss: 0.6229 - val_accuracy: 0.7208 Epoch 148/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3974 - accuracy: 0.8469 - val_loss: 0.6195 - val_accuracy: 0.6883 Epoch 149/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3934 - accuracy: 0.8518 - val_loss: 0.5947 - val_accuracy: 0.7273 Epoch 150/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3871 - accuracy: 0.8518 - val_loss: 0.6063 - val_accuracy: 0.7273 Epoch 151/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3894 - accuracy: 0.8485 - val_loss: 0.6188 - val_accuracy: 0.7143 Epoch 152/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4064 - accuracy: 0.8322 - val_loss: 0.6196 - val_accuracy: 0.7078 Epoch 153/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3893 - accuracy: 0.8485 - val_loss: 0.6485 - val_accuracy: 0.6883 Epoch 154/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3877 - accuracy: 0.8469 - val_loss: 0.6170 - val_accuracy: 0.7013 Epoch 155/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3822 - accuracy: 0.8469 - val_loss: 0.6257 - val_accuracy: 0.7013 Epoch 156/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4045 - accuracy: 0.8290 - val_loss: 0.6355 - val_accuracy: 0.6623 Epoch 157/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3990 - accuracy: 0.8355 - val_loss: 0.6651 - val_accuracy: 0.6688 Epoch 158/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3885 - accuracy: 0.8485 - val_loss: 0.6294 - val_accuracy: 0.7013 Epoch 159/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3861 - accuracy: 0.8436 - val_loss: 0.6336 - val_accuracy: 0.7143 Epoch 160/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3811 - accuracy: 0.8469 - val_loss: 0.6183 - val_accuracy: 0.7208 Epoch 161/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3708 - accuracy: 0.8616 - val_loss: 0.6187 - val_accuracy: 0.7078 Epoch 162/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3716 - accuracy: 0.8550 - val_loss: 0.6286 - val_accuracy: 0.7143 Epoch 163/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3814 - accuracy: 0.8485 - val_loss: 0.6446 - val_accuracy: 0.6818 Epoch 164/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3839 - accuracy: 0.8355 - val_loss: 0.6164 - val_accuracy: 0.7078 Epoch 165/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.4281 - accuracy: 0.8013 - val_loss: 0.6837 - val_accuracy: 0.6818 Epoch 166/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3915 - accuracy: 0.8502 - val_loss: 0.6358 - val_accuracy: 0.6948 Epoch 167/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4046 - accuracy: 0.8274 - val_loss: 0.6655 - val_accuracy: 0.7078 Epoch 168/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3962 - accuracy: 0.8371 - val_loss: 0.6180 - val_accuracy: 0.7273 Epoch 169/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3862 - accuracy: 0.8388 - val_loss: 0.6166 - val_accuracy: 0.7143 Epoch 170/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3632 - accuracy: 0.8664 - val_loss: 0.6200 - val_accuracy: 0.7013 Epoch 171/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3696 - accuracy: 0.8550 - val_loss: 0.6018 - val_accuracy: 0.7468 Epoch 172/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3612 - accuracy: 0.8534 - val_loss: 0.6232 - val_accuracy: 0.7078 Epoch 173/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3612 - accuracy: 0.8616 - val_loss: 0.6236 - val_accuracy: 0.7013 Epoch 174/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3733 - accuracy: 0.8469 - val_loss: 0.6355 - val_accuracy: 0.6753 Epoch 175/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3786 - accuracy: 0.8404 - val_loss: 0.6293 - val_accuracy: 0.7143 Epoch 176/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3703 - accuracy: 0.8583 - val_loss: 0.6261 - val_accuracy: 0.7013 Epoch 177/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3682 - accuracy: 0.8599 - val_loss: 0.6488 - val_accuracy: 0.6883 Epoch 178/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3751 - accuracy: 0.8469 - val_loss: 0.6818 - val_accuracy: 0.6883 Epoch 179/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3800 - accuracy: 0.8469 - val_loss: 0.6659 - val_accuracy: 0.6688 Epoch 180/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3696 - accuracy: 0.8567 - val_loss: 0.6460 - val_accuracy: 0.7013 Epoch 181/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3822 - accuracy: 0.8404 - val_loss: 0.6656 - val_accuracy: 0.7013 Epoch 182/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3742 - accuracy: 0.8502 - val_loss: 0.6207 - val_accuracy: 0.7143 Epoch 183/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3459 - accuracy: 0.8648 - val_loss: 0.6371 - val_accuracy: 0.7143 Epoch 184/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3672 - accuracy: 0.8404 - val_loss: 0.6479 - val_accuracy: 0.6948 Epoch 185/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3519 - accuracy: 0.8567 - val_loss: 0.6378 - val_accuracy: 0.7143 Epoch 186/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3517 - accuracy: 0.8681 - val_loss: 0.6306 - val_accuracy: 0.7013 Epoch 187/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3382 - accuracy: 0.8713 - val_loss: 0.6440 - val_accuracy: 0.7143 Epoch 188/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3456 - accuracy: 0.8762 - val_loss: 0.6440 - val_accuracy: 0.6753 Epoch 189/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3535 - accuracy: 0.8632 - val_loss: 0.6442 - val_accuracy: 0.6883 Epoch 190/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3394 - accuracy: 0.8795 - val_loss: 0.6694 - val_accuracy: 0.7403 Epoch 191/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3690 - accuracy: 0.8502 - val_loss: 0.7220 - val_accuracy: 0.6688 Epoch 192/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3830 - accuracy: 0.8322 - val_loss: 0.6380 - val_accuracy: 0.7013 Epoch 193/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3450 - accuracy: 0.8616 - val_loss: 0.6535 - val_accuracy: 0.7403 Epoch 194/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3569 - accuracy: 0.8664 - val_loss: 0.6933 - val_accuracy: 0.7143 Epoch 195/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3685 - accuracy: 0.8583 - val_loss: 0.6391 - val_accuracy: 0.6818 Epoch 196/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3371 - accuracy: 0.8762 - val_loss: 0.7036 - val_accuracy: 0.6623 Epoch 197/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3763 - accuracy: 0.8534 - val_loss: 0.6749 - val_accuracy: 0.6688 Epoch 198/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3301 - accuracy: 0.8827 - val_loss: 0.6569 - val_accuracy: 0.7078 Epoch 199/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3348 - accuracy: 0.8746 - val_loss: 0.6363 - val_accuracy: 0.7273 Epoch 200/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3435 - accuracy: 0.8648 - val_loss: 0.6704 - val_accuracy: 0.6688 Epoch 201/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3620 - accuracy: 0.8599 - val_loss: 0.6592 - val_accuracy: 0.6883 Epoch 202/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3509 - accuracy: 0.8616 - val_loss: 0.6682 - val_accuracy: 0.7208 Epoch 203/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3295 - accuracy: 0.8827 - val_loss: 0.6576 - val_accuracy: 0.7078 Epoch 204/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3409 - accuracy: 0.8648 - val_loss: 0.6903 - val_accuracy: 0.6818 Epoch 205/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3292 - accuracy: 0.8795 - val_loss: 0.6590 - val_accuracy: 0.7208 Epoch 206/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3559 - accuracy: 0.8453 - val_loss: 0.6521 - val_accuracy: 0.7013 Epoch 207/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3286 - accuracy: 0.8795 - val_loss: 0.6780 - val_accuracy: 0.6948 Epoch 208/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3419 - accuracy: 0.8648 - val_loss: 0.6637 - val_accuracy: 0.6948 Epoch 209/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3322 - accuracy: 0.8844 - val_loss: 0.6618 - val_accuracy: 0.7013 Epoch 210/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3204 - accuracy: 0.8811 - val_loss: 0.6433 - val_accuracy: 0.6948 Epoch 211/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3135 - accuracy: 0.8844 - val_loss: 0.6636 - val_accuracy: 0.7013 Epoch 212/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3310 - accuracy: 0.8762 - val_loss: 0.6809 - val_accuracy: 0.6753 Epoch 213/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3539 - accuracy: 0.8648 - val_loss: 0.6507 - val_accuracy: 0.6883 Epoch 214/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3274 - accuracy: 0.8811 - val_loss: 0.6980 - val_accuracy: 0.6883 Epoch 215/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3172 - accuracy: 0.8844 - val_loss: 0.6435 - val_accuracy: 0.7208 Epoch 216/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3408 - accuracy: 0.8697 - val_loss: 0.6769 - val_accuracy: 0.6948 Epoch 217/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3326 - accuracy: 0.8811 - val_loss: 0.6752 - val_accuracy: 0.7273 Epoch 218/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3201 - accuracy: 0.8746 - val_loss: 0.6573 - val_accuracy: 0.7143 Epoch 219/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3336 - accuracy: 0.8746 - val_loss: 0.6811 - val_accuracy: 0.6883 Epoch 220/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3350 - accuracy: 0.8762 - val_loss: 0.6856 - val_accuracy: 0.7208 Epoch 221/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3245 - accuracy: 0.8779 - val_loss: 0.6762 - val_accuracy: 0.7013 Epoch 222/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3127 - accuracy: 0.8876 - val_loss: 0.6810 - val_accuracy: 0.7078 Epoch 223/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3069 - accuracy: 0.8974 - val_loss: 0.7010 - val_accuracy: 0.7013 Epoch 224/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3186 - accuracy: 0.8827 - val_loss: 0.7140 - val_accuracy: 0.6883 Epoch 225/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3164 - accuracy: 0.8827 - val_loss: 0.6601 - val_accuracy: 0.7208 Epoch 226/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2995 - accuracy: 0.9007 - val_loss: 0.6963 - val_accuracy: 0.6883 Epoch 227/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3642 - accuracy: 0.8469 - val_loss: 0.7728 - val_accuracy: 0.6494 Epoch 228/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3317 - accuracy: 0.8746 - val_loss: 0.7002 - val_accuracy: 0.6948 Epoch 229/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3124 - accuracy: 0.8844 - val_loss: 0.7028 - val_accuracy: 0.7143 Epoch 230/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3203 - accuracy: 0.8811 - val_loss: 0.7481 - val_accuracy: 0.6883 Epoch 231/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3201 - accuracy: 0.8779 - val_loss: 0.6893 - val_accuracy: 0.7013 Epoch 232/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3049 - accuracy: 0.8941 - val_loss: 0.7261 - val_accuracy: 0.6948 Epoch 233/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3329 - accuracy: 0.8730 - val_loss: 0.7099 - val_accuracy: 0.6688 Epoch 234/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3773 - accuracy: 0.8567 - val_loss: 0.7061 - val_accuracy: 0.6883 Epoch 235/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3196 - accuracy: 0.8811 - val_loss: 0.6901 - val_accuracy: 0.6948 Epoch 236/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3118 - accuracy: 0.8860 - val_loss: 0.6779 - val_accuracy: 0.7013 Epoch 237/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3817 - accuracy: 0.8485 - val_loss: 0.6742 - val_accuracy: 0.7013 Epoch 238/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3284 - accuracy: 0.8697 - val_loss: 0.7051 - val_accuracy: 0.6818 Epoch 239/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3185 - accuracy: 0.8844 - val_loss: 0.7051 - val_accuracy: 0.6818 Epoch 240/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3133 - accuracy: 0.8941 - val_loss: 0.6875 - val_accuracy: 0.7143 Epoch 241/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3294 - accuracy: 0.8632 - val_loss: 0.6950 - val_accuracy: 0.6818 Epoch 242/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2977 - accuracy: 0.9055 - val_loss: 0.7235 - val_accuracy: 0.6688 Epoch 243/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3128 - accuracy: 0.8893 - val_loss: 0.6924 - val_accuracy: 0.7013 Epoch 244/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3370 - accuracy: 0.8730 - val_loss: 0.6828 - val_accuracy: 0.7273 Epoch 245/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3158 - accuracy: 0.8827 - val_loss: 0.6832 - val_accuracy: 0.7013 Epoch 246/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2994 - accuracy: 0.8941 - val_loss: 0.7249 - val_accuracy: 0.6818 Epoch 247/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3370 - accuracy: 0.8648 - val_loss: 0.7238 - val_accuracy: 0.6623 Epoch 248/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2999 - accuracy: 0.8876 - val_loss: 0.7002 - val_accuracy: 0.6948 Epoch 249/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2906 - accuracy: 0.8974 - val_loss: 0.6999 - val_accuracy: 0.7208 Epoch 250/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3234 - accuracy: 0.8795 - val_loss: 0.6843 - val_accuracy: 0.6948 Epoch 251/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3774 - accuracy: 0.8436 - val_loss: 0.7247 - val_accuracy: 0.6818 Epoch 252/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3241 - accuracy: 0.8811 - val_loss: 0.7204 - val_accuracy: 0.6818 Epoch 253/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3095 - accuracy: 0.8844 - val_loss: 0.6963 - val_accuracy: 0.6948 Epoch 254/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2992 - accuracy: 0.8941 - val_loss: 0.7310 - val_accuracy: 0.6364 Epoch 255/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2974 - accuracy: 0.8779 - val_loss: 0.7049 - val_accuracy: 0.7143 Epoch 256/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2991 - accuracy: 0.8974 - val_loss: 0.7021 - val_accuracy: 0.7143 Epoch 257/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2969 - accuracy: 0.8909 - val_loss: 0.7119 - val_accuracy: 0.7078 Epoch 258/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2986 - accuracy: 0.8860 - val_loss: 0.7051 - val_accuracy: 0.6948 Epoch 259/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3622 - accuracy: 0.8550 - val_loss: 0.7468 - val_accuracy: 0.6688 Epoch 260/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3128 - accuracy: 0.8779 - val_loss: 0.7655 - val_accuracy: 0.6818 Epoch 261/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3042 - accuracy: 0.8909 - val_loss: 0.7159 - val_accuracy: 0.7143 Epoch 262/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3101 - accuracy: 0.8795 - val_loss: 0.7118 - val_accuracy: 0.6753 Epoch 263/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2865 - accuracy: 0.8941 - val_loss: 0.7393 - val_accuracy: 0.6818 Epoch 264/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3029 - accuracy: 0.8925 - val_loss: 0.7087 - val_accuracy: 0.6883 Epoch 265/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2955 - accuracy: 0.8941 - val_loss: 0.7188 - val_accuracy: 0.7013 Epoch 266/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2927 - accuracy: 0.8827 - val_loss: 0.7453 - val_accuracy: 0.6948 Epoch 267/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3399 - accuracy: 0.8664 - val_loss: 0.7877 - val_accuracy: 0.6753 Epoch 268/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3000 - accuracy: 0.8909 - val_loss: 0.7230 - val_accuracy: 0.7013 Epoch 269/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3044 - accuracy: 0.8893 - val_loss: 0.7153 - val_accuracy: 0.6818 Epoch 270/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2756 - accuracy: 0.9088 - val_loss: 0.7112 - val_accuracy: 0.7013 Epoch 271/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2778 - accuracy: 0.9104 - val_loss: 0.7422 - val_accuracy: 0.7013 Epoch 272/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2812 - accuracy: 0.8990 - val_loss: 0.7299 - val_accuracy: 0.6883 Epoch 273/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2726 - accuracy: 0.9023 - val_loss: 0.7653 - val_accuracy: 0.6753 Epoch 274/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2958 - accuracy: 0.8958 - val_loss: 0.7221 - val_accuracy: 0.6948 Epoch 275/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2838 - accuracy: 0.8974 - val_loss: 0.7482 - val_accuracy: 0.6558 Epoch 276/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2779 - accuracy: 0.9039 - val_loss: 0.7023 - val_accuracy: 0.7013 Epoch 277/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2712 - accuracy: 0.9039 - val_loss: 0.7290 - val_accuracy: 0.7078 Epoch 278/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2756 - accuracy: 0.8990 - val_loss: 0.7470 - val_accuracy: 0.6948 Epoch 279/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.3148 - accuracy: 0.8697 - val_loss: 0.7503 - val_accuracy: 0.7338 Epoch 280/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3184 - accuracy: 0.8795 - val_loss: 0.7975 - val_accuracy: 0.6688 Epoch 281/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3121 - accuracy: 0.8746 - val_loss: 0.8005 - val_accuracy: 0.6688 Epoch 282/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3110 - accuracy: 0.8795 - val_loss: 0.7464 - val_accuracy: 0.6948 Epoch 283/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2692 - accuracy: 0.9137 - val_loss: 0.7403 - val_accuracy: 0.7078 Epoch 284/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2614 - accuracy: 0.9153 - val_loss: 0.7417 - val_accuracy: 0.6818 Epoch 285/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2704 - accuracy: 0.9104 - val_loss: 0.7203 - val_accuracy: 0.7143 Epoch 286/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2784 - accuracy: 0.9072 - val_loss: 0.7761 - val_accuracy: 0.6688 Epoch 287/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2879 - accuracy: 0.8925 - val_loss: 0.6986 - val_accuracy: 0.7273 Epoch 288/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2931 - accuracy: 0.8876 - val_loss: 0.7785 - val_accuracy: 0.6753 Epoch 289/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2641 - accuracy: 0.9023 - val_loss: 0.7530 - val_accuracy: 0.7208 Epoch 290/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2647 - accuracy: 0.9121 - val_loss: 0.7444 - val_accuracy: 0.6948 Epoch 291/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2639 - accuracy: 0.9088 - val_loss: 0.7768 - val_accuracy: 0.6818 Epoch 292/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2682 - accuracy: 0.9055 - val_loss: 0.7355 - val_accuracy: 0.6883 Epoch 293/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2761 - accuracy: 0.8974 - val_loss: 0.7831 - val_accuracy: 0.6623 Epoch 294/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2676 - accuracy: 0.9137 - val_loss: 0.7331 - val_accuracy: 0.7143 Epoch 295/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2977 - accuracy: 0.8925 - val_loss: 0.7663 - val_accuracy: 0.6948 Epoch 296/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3040 - accuracy: 0.8909 - val_loss: 0.8274 - val_accuracy: 0.6753 Epoch 297/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2805 - accuracy: 0.8958 - val_loss: 0.7661 - val_accuracy: 0.6818 Epoch 298/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2600 - accuracy: 0.9055 - val_loss: 0.7648 - val_accuracy: 0.6948 Epoch 299/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2669 - accuracy: 0.9039 - val_loss: 0.8022 - val_accuracy: 0.7078 Epoch 300/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2695 - accuracy: 0.9007 - val_loss: 0.7602 - val_accuracy: 0.6818 Epoch 301/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2512 - accuracy: 0.9186 - val_loss: 0.7466 - val_accuracy: 0.7078 Epoch 302/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2706 - accuracy: 0.8974 - val_loss: 0.7443 - val_accuracy: 0.6948 Epoch 303/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2681 - accuracy: 0.9072 - val_loss: 0.8093 - val_accuracy: 0.6883 Epoch 304/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2618 - accuracy: 0.9007 - val_loss: 0.7582 - val_accuracy: 0.6883 Epoch 305/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2932 - accuracy: 0.8909 - val_loss: 0.7639 - val_accuracy: 0.6883 Epoch 306/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2797 - accuracy: 0.8893 - val_loss: 0.7827 - val_accuracy: 0.6688 Epoch 307/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2702 - accuracy: 0.9121 - val_loss: 0.7809 - val_accuracy: 0.6948 Epoch 308/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2860 - accuracy: 0.8893 - val_loss: 0.7562 - val_accuracy: 0.7078 Epoch 309/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2782 - accuracy: 0.9055 - val_loss: 0.7834 - val_accuracy: 0.6818 Epoch 310/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2488 - accuracy: 0.9169 - val_loss: 0.7874 - val_accuracy: 0.6818 Epoch 311/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2747 - accuracy: 0.8958 - val_loss: 0.7645 - val_accuracy: 0.7013 Epoch 312/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2570 - accuracy: 0.9104 - val_loss: 0.7652 - val_accuracy: 0.7143 Epoch 313/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2570 - accuracy: 0.9153 - val_loss: 0.7520 - val_accuracy: 0.7143 Epoch 314/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3378 - accuracy: 0.8746 - val_loss: 0.8441 - val_accuracy: 0.6623 Epoch 315/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3162 - accuracy: 0.8876 - val_loss: 0.8136 - val_accuracy: 0.6883 Epoch 316/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2939 - accuracy: 0.8925 - val_loss: 0.7714 - val_accuracy: 0.7013 Epoch 317/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2917 - accuracy: 0.9007 - val_loss: 0.8140 - val_accuracy: 0.6688 Epoch 318/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2844 - accuracy: 0.8941 - val_loss: 0.7378 - val_accuracy: 0.7013 Epoch 319/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2886 - accuracy: 0.8876 - val_loss: 0.7919 - val_accuracy: 0.6948 Epoch 320/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2766 - accuracy: 0.9007 - val_loss: 0.7252 - val_accuracy: 0.7208 Epoch 321/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2527 - accuracy: 0.9072 - val_loss: 0.7649 - val_accuracy: 0.6948 Epoch 322/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2453 - accuracy: 0.9218 - val_loss: 0.7803 - val_accuracy: 0.6753 Epoch 323/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2550 - accuracy: 0.9088 - val_loss: 0.7539 - val_accuracy: 0.6818 Epoch 324/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2608 - accuracy: 0.9153 - val_loss: 0.7638 - val_accuracy: 0.6948 Epoch 325/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2416 - accuracy: 0.9104 - val_loss: 0.7520 - val_accuracy: 0.6948 Epoch 326/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2456 - accuracy: 0.9137 - val_loss: 0.7842 - val_accuracy: 0.6753 Epoch 327/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2533 - accuracy: 0.9055 - val_loss: 0.7564 - val_accuracy: 0.6883 Epoch 328/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2608 - accuracy: 0.9023 - val_loss: 0.8217 - val_accuracy: 0.6818 Epoch 329/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2449 - accuracy: 0.9104 - val_loss: 0.7889 - val_accuracy: 0.6883 Epoch 330/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2724 - accuracy: 0.9007 - val_loss: 0.7952 - val_accuracy: 0.7013 Epoch 331/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2638 - accuracy: 0.9088 - val_loss: 0.7641 - val_accuracy: 0.6948 Epoch 332/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2474 - accuracy: 0.9186 - val_loss: 0.7603 - val_accuracy: 0.6948 Epoch 333/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2648 - accuracy: 0.8876 - val_loss: 0.8254 - val_accuracy: 0.6818 Epoch 334/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3229 - accuracy: 0.8697 - val_loss: 0.8327 - val_accuracy: 0.6558 Epoch 335/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3018 - accuracy: 0.8974 - val_loss: 0.8416 - val_accuracy: 0.6753 Epoch 336/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3013 - accuracy: 0.8811 - val_loss: 0.7502 - val_accuracy: 0.6883 Epoch 337/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2819 - accuracy: 0.8941 - val_loss: 0.8835 - val_accuracy: 0.6948 Epoch 338/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2675 - accuracy: 0.9023 - val_loss: 0.8155 - val_accuracy: 0.6623 Epoch 339/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2533 - accuracy: 0.9055 - val_loss: 0.7841 - val_accuracy: 0.6753 Epoch 340/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2844 - accuracy: 0.8958 - val_loss: 0.8424 - val_accuracy: 0.6494 Epoch 341/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3065 - accuracy: 0.8811 - val_loss: 0.8217 - val_accuracy: 0.6623 Epoch 342/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2587 - accuracy: 0.9088 - val_loss: 0.7524 - val_accuracy: 0.6948 Epoch 343/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2832 - accuracy: 0.9007 - val_loss: 0.8205 - val_accuracy: 0.6688 Epoch 344/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2983 - accuracy: 0.8860 - val_loss: 0.7858 - val_accuracy: 0.7013 Epoch 345/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2781 - accuracy: 0.8941 - val_loss: 0.7959 - val_accuracy: 0.6948 Epoch 346/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2637 - accuracy: 0.9007 - val_loss: 0.7780 - val_accuracy: 0.6818 Epoch 347/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2521 - accuracy: 0.9104 - val_loss: 0.7371 - val_accuracy: 0.7143 Epoch 348/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2354 - accuracy: 0.9283 - val_loss: 0.8182 - val_accuracy: 0.6688 Epoch 349/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2736 - accuracy: 0.9039 - val_loss: 0.7893 - val_accuracy: 0.6948 Epoch 350/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2420 - accuracy: 0.9218 - val_loss: 0.7660 - val_accuracy: 0.6948 Epoch 351/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2564 - accuracy: 0.9023 - val_loss: 0.8165 - val_accuracy: 0.6558 Epoch 352/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2482 - accuracy: 0.9186 - val_loss: 0.7679 - val_accuracy: 0.6948 Epoch 353/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2639 - accuracy: 0.9039 - val_loss: 0.8141 - val_accuracy: 0.7078 Epoch 354/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2843 - accuracy: 0.8974 - val_loss: 0.7643 - val_accuracy: 0.7078 Epoch 355/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2714 - accuracy: 0.9104 - val_loss: 0.7740 - val_accuracy: 0.6883 Epoch 356/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2481 - accuracy: 0.9088 - val_loss: 0.8376 - val_accuracy: 0.6948 Epoch 357/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2602 - accuracy: 0.9007 - val_loss: 0.8389 - val_accuracy: 0.6558 Epoch 358/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2683 - accuracy: 0.9023 - val_loss: 0.7888 - val_accuracy: 0.6883 Epoch 359/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2374 - accuracy: 0.9218 - val_loss: 0.7812 - val_accuracy: 0.7273 Epoch 360/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2675 - accuracy: 0.9023 - val_loss: 0.8089 - val_accuracy: 0.7013 Epoch 361/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2530 - accuracy: 0.9104 - val_loss: 0.8039 - val_accuracy: 0.7208 Epoch 362/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2366 - accuracy: 0.9104 - val_loss: 0.7875 - val_accuracy: 0.6883 Epoch 363/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2760 - accuracy: 0.9007 - val_loss: 0.8070 - val_accuracy: 0.6818 Epoch 364/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2380 - accuracy: 0.9202 - val_loss: 0.7963 - val_accuracy: 0.6883 Epoch 365/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2427 - accuracy: 0.9121 - val_loss: 0.7503 - val_accuracy: 0.7078 Epoch 366/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2329 - accuracy: 0.9218 - val_loss: 0.8058 - val_accuracy: 0.7078 Epoch 367/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2292 - accuracy: 0.9251 - val_loss: 0.7715 - val_accuracy: 0.7143 Epoch 368/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2264 - accuracy: 0.9235 - val_loss: 0.7746 - val_accuracy: 0.7338 Epoch 369/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2388 - accuracy: 0.9104 - val_loss: 0.7808 - val_accuracy: 0.7013 Epoch 370/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2412 - accuracy: 0.9023 - val_loss: 0.8186 - val_accuracy: 0.6948 Epoch 371/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2568 - accuracy: 0.9137 - val_loss: 0.7835 - val_accuracy: 0.6948 Epoch 372/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2860 - accuracy: 0.8974 - val_loss: 0.8283 - val_accuracy: 0.6753 Epoch 373/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2833 - accuracy: 0.8941 - val_loss: 0.8467 - val_accuracy: 0.7013 Epoch 374/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2666 - accuracy: 0.9007 - val_loss: 0.8933 - val_accuracy: 0.6558 Epoch 375/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2788 - accuracy: 0.8990 - val_loss: 0.7827 - val_accuracy: 0.6948 Epoch 376/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2480 - accuracy: 0.9088 - val_loss: 0.8073 - val_accuracy: 0.6818 Epoch 377/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2603 - accuracy: 0.9023 - val_loss: 0.7917 - val_accuracy: 0.6948 Epoch 378/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2269 - accuracy: 0.9267 - val_loss: 0.8076 - val_accuracy: 0.7078 Epoch 379/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2331 - accuracy: 0.9202 - val_loss: 0.8317 - val_accuracy: 0.6753 Epoch 380/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2452 - accuracy: 0.9153 - val_loss: 0.8066 - val_accuracy: 0.6688 Epoch 381/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2280 - accuracy: 0.9235 - val_loss: 0.8220 - val_accuracy: 0.6818 Epoch 382/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2577 - accuracy: 0.9121 - val_loss: 0.8190 - val_accuracy: 0.6883 Epoch 383/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2328 - accuracy: 0.9251 - val_loss: 0.8083 - val_accuracy: 0.6688 Epoch 384/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2243 - accuracy: 0.9235 - val_loss: 0.8073 - val_accuracy: 0.6818 Epoch 385/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2536 - accuracy: 0.9007 - val_loss: 0.7983 - val_accuracy: 0.7013 Epoch 386/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2555 - accuracy: 0.9055 - val_loss: 0.8796 - val_accuracy: 0.6753 Epoch 387/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2491 - accuracy: 0.9153 - val_loss: 0.8604 - val_accuracy: 0.6753 Epoch 388/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2242 - accuracy: 0.9218 - val_loss: 0.8347 - val_accuracy: 0.6883 Epoch 389/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2290 - accuracy: 0.9235 - val_loss: 0.8381 - val_accuracy: 0.6883 Epoch 390/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2377 - accuracy: 0.9121 - val_loss: 0.8786 - val_accuracy: 0.6818 Epoch 391/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2670 - accuracy: 0.9072 - val_loss: 0.7896 - val_accuracy: 0.7208 Epoch 392/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2314 - accuracy: 0.9283 - val_loss: 0.8677 - val_accuracy: 0.6688 Epoch 393/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2463 - accuracy: 0.9186 - val_loss: 0.7987 - val_accuracy: 0.7013 Epoch 394/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2496 - accuracy: 0.9104 - val_loss: 0.8460 - val_accuracy: 0.7078 Epoch 395/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2813 - accuracy: 0.8974 - val_loss: 0.8263 - val_accuracy: 0.7143 Epoch 396/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2392 - accuracy: 0.9121 - val_loss: 0.8339 - val_accuracy: 0.6883 Epoch 397/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2518 - accuracy: 0.9104 - val_loss: 0.8218 - val_accuracy: 0.6883 Epoch 398/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2615 - accuracy: 0.9072 - val_loss: 0.8771 - val_accuracy: 0.7013 Epoch 399/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.3221 - accuracy: 0.8811 - val_loss: 0.8198 - val_accuracy: 0.7143 Epoch 400/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2726 - accuracy: 0.9088 - val_loss: 0.8369 - val_accuracy: 0.6948 Epoch 401/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2554 - accuracy: 0.9153 - val_loss: 0.8092 - val_accuracy: 0.7013 Epoch 402/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2352 - accuracy: 0.9202 - val_loss: 0.8114 - val_accuracy: 0.6948 Epoch 403/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2145 - accuracy: 0.9316 - val_loss: 0.8291 - val_accuracy: 0.6948 Epoch 404/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2124 - accuracy: 0.9349 - val_loss: 0.8240 - val_accuracy: 0.6948 Epoch 405/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2127 - accuracy: 0.9397 - val_loss: 0.8029 - val_accuracy: 0.7078 Epoch 406/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2180 - accuracy: 0.9332 - val_loss: 0.8300 - val_accuracy: 0.7143 Epoch 407/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2190 - accuracy: 0.9349 - val_loss: 0.8466 - val_accuracy: 0.6688 Epoch 408/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2194 - accuracy: 0.9300 - val_loss: 0.8274 - val_accuracy: 0.6753 Epoch 409/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2905 - accuracy: 0.8941 - val_loss: 0.7984 - val_accuracy: 0.7078 Epoch 410/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2460 - accuracy: 0.9055 - val_loss: 0.8398 - val_accuracy: 0.6883 Epoch 411/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2260 - accuracy: 0.9267 - val_loss: 0.8629 - val_accuracy: 0.6818 Epoch 412/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2237 - accuracy: 0.9251 - val_loss: 0.7995 - val_accuracy: 0.7013 Epoch 413/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2355 - accuracy: 0.9218 - val_loss: 0.8806 - val_accuracy: 0.6818 Epoch 414/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2511 - accuracy: 0.9088 - val_loss: 0.8056 - val_accuracy: 0.6948 Epoch 415/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2820 - accuracy: 0.8925 - val_loss: 0.8104 - val_accuracy: 0.7273 Epoch 416/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2457 - accuracy: 0.9186 - val_loss: 0.8655 - val_accuracy: 0.6948 Epoch 417/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2568 - accuracy: 0.9088 - val_loss: 0.8388 - val_accuracy: 0.6883 Epoch 418/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2695 - accuracy: 0.8860 - val_loss: 0.9264 - val_accuracy: 0.6818 Epoch 419/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2446 - accuracy: 0.9169 - val_loss: 0.8287 - val_accuracy: 0.6429 Epoch 420/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2948 - accuracy: 0.8925 - val_loss: 0.8212 - val_accuracy: 0.7013 Epoch 421/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2377 - accuracy: 0.9169 - val_loss: 0.8757 - val_accuracy: 0.7013 Epoch 422/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2819 - accuracy: 0.8958 - val_loss: 0.8511 - val_accuracy: 0.6558 Epoch 423/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2524 - accuracy: 0.9121 - val_loss: 0.9030 - val_accuracy: 0.6883 Epoch 424/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2433 - accuracy: 0.9186 - val_loss: 0.8894 - val_accuracy: 0.6818 Epoch 425/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2385 - accuracy: 0.9137 - val_loss: 0.8820 - val_accuracy: 0.6688 Epoch 426/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2286 - accuracy: 0.9202 - val_loss: 0.8369 - val_accuracy: 0.6623 Epoch 427/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2435 - accuracy: 0.9153 - val_loss: 0.8703 - val_accuracy: 0.6753 Epoch 428/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2924 - accuracy: 0.8860 - val_loss: 0.9122 - val_accuracy: 0.6429 Epoch 429/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3505 - accuracy: 0.8534 - val_loss: 0.7635 - val_accuracy: 0.6948 Epoch 430/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2595 - accuracy: 0.9023 - val_loss: 0.8272 - val_accuracy: 0.6623 Epoch 431/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2400 - accuracy: 0.9169 - val_loss: 0.8335 - val_accuracy: 0.6688 Epoch 432/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2477 - accuracy: 0.9072 - val_loss: 0.8364 - val_accuracy: 0.6688 Epoch 433/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2326 - accuracy: 0.9283 - val_loss: 0.8083 - val_accuracy: 0.6688 Epoch 434/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2011 - accuracy: 0.9463 - val_loss: 0.8080 - val_accuracy: 0.7013 Epoch 435/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2175 - accuracy: 0.9283 - val_loss: 0.8375 - val_accuracy: 0.6558 Epoch 436/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2258 - accuracy: 0.9251 - val_loss: 0.8643 - val_accuracy: 0.6753 Epoch 437/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2512 - accuracy: 0.9072 - val_loss: 0.8180 - val_accuracy: 0.6753 Epoch 438/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2156 - accuracy: 0.9316 - val_loss: 0.8462 - val_accuracy: 0.7013 Epoch 439/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2273 - accuracy: 0.9153 - val_loss: 0.8308 - val_accuracy: 0.6818 Epoch 440/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2320 - accuracy: 0.9316 - val_loss: 0.8189 - val_accuracy: 0.6883 Epoch 441/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2300 - accuracy: 0.9283 - val_loss: 0.8248 - val_accuracy: 0.6883 Epoch 442/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2055 - accuracy: 0.9365 - val_loss: 0.8225 - val_accuracy: 0.6948 Epoch 443/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2058 - accuracy: 0.9365 - val_loss: 0.8730 - val_accuracy: 0.6883 Epoch 444/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2275 - accuracy: 0.9235 - val_loss: 0.8573 - val_accuracy: 0.6688 Epoch 445/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2129 - accuracy: 0.9283 - val_loss: 0.8378 - val_accuracy: 0.6818 Epoch 446/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2120 - accuracy: 0.9283 - val_loss: 0.8624 - val_accuracy: 0.6753 Epoch 447/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2376 - accuracy: 0.9202 - val_loss: 0.8686 - val_accuracy: 0.7078 Epoch 448/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2264 - accuracy: 0.9218 - val_loss: 0.8281 - val_accuracy: 0.6883 Epoch 449/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2239 - accuracy: 0.9218 - val_loss: 0.8728 - val_accuracy: 0.6948 Epoch 450/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2215 - accuracy: 0.9365 - val_loss: 0.8682 - val_accuracy: 0.6948 Epoch 451/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2179 - accuracy: 0.9267 - val_loss: 0.8341 - val_accuracy: 0.7143 Epoch 452/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2246 - accuracy: 0.9218 - val_loss: 0.8318 - val_accuracy: 0.6948 Epoch 453/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2156 - accuracy: 0.9283 - val_loss: 0.9085 - val_accuracy: 0.6883 Epoch 454/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2605 - accuracy: 0.9007 - val_loss: 0.9020 - val_accuracy: 0.6688 Epoch 455/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2600 - accuracy: 0.8990 - val_loss: 0.8842 - val_accuracy: 0.6688 Epoch 456/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2310 - accuracy: 0.9235 - val_loss: 0.8262 - val_accuracy: 0.6883 Epoch 457/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2240 - accuracy: 0.9251 - val_loss: 0.8556 - val_accuracy: 0.6948 Epoch 458/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2342 - accuracy: 0.9218 - val_loss: 0.8880 - val_accuracy: 0.6948 Epoch 459/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2536 - accuracy: 0.9007 - val_loss: 0.8257 - val_accuracy: 0.6753 Epoch 460/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2300 - accuracy: 0.9202 - val_loss: 0.8628 - val_accuracy: 0.7013 Epoch 461/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2161 - accuracy: 0.9316 - val_loss: 0.8586 - val_accuracy: 0.6883 Epoch 462/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2170 - accuracy: 0.9283 - val_loss: 0.8554 - val_accuracy: 0.6753 Epoch 463/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2603 - accuracy: 0.9007 - val_loss: 0.8967 - val_accuracy: 0.6753 Epoch 464/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2647 - accuracy: 0.9072 - val_loss: 0.8862 - val_accuracy: 0.6818 Epoch 465/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2747 - accuracy: 0.8925 - val_loss: 0.8447 - val_accuracy: 0.7078 Epoch 466/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2410 - accuracy: 0.9153 - val_loss: 0.8508 - val_accuracy: 0.6948 Epoch 467/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2200 - accuracy: 0.9235 - val_loss: 0.8545 - val_accuracy: 0.6883 Epoch 468/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2221 - accuracy: 0.9251 - val_loss: 0.8645 - val_accuracy: 0.6883 Epoch 469/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2116 - accuracy: 0.9381 - val_loss: 0.8533 - val_accuracy: 0.6688 Epoch 470/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2356 - accuracy: 0.9137 - val_loss: 0.8629 - val_accuracy: 0.6818 Epoch 471/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2109 - accuracy: 0.9316 - val_loss: 0.8715 - val_accuracy: 0.6688 Epoch 472/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1919 - accuracy: 0.9463 - val_loss: 0.8528 - val_accuracy: 0.7013 Epoch 473/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2041 - accuracy: 0.9316 - val_loss: 0.8952 - val_accuracy: 0.6818 Epoch 474/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2011 - accuracy: 0.9446 - val_loss: 0.8929 - val_accuracy: 0.6688 Epoch 475/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2081 - accuracy: 0.9381 - val_loss: 0.8630 - val_accuracy: 0.6948 Epoch 476/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1982 - accuracy: 0.9349 - val_loss: 0.9339 - val_accuracy: 0.6623 Epoch 477/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2463 - accuracy: 0.9137 - val_loss: 0.8778 - val_accuracy: 0.6883 Epoch 478/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2864 - accuracy: 0.8974 - val_loss: 0.9044 - val_accuracy: 0.6753 Epoch 479/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2430 - accuracy: 0.9137 - val_loss: 0.8597 - val_accuracy: 0.6948 Epoch 480/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2084 - accuracy: 0.9316 - val_loss: 0.8668 - val_accuracy: 0.6948 Epoch 481/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2150 - accuracy: 0.9283 - val_loss: 0.8913 - val_accuracy: 0.6883 Epoch 482/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2066 - accuracy: 0.9283 - val_loss: 0.9198 - val_accuracy: 0.6753 Epoch 483/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2067 - accuracy: 0.9267 - val_loss: 0.9046 - val_accuracy: 0.6558 Epoch 484/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.1966 - accuracy: 0.9414 - val_loss: 0.9407 - val_accuracy: 0.6623 Epoch 485/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2025 - accuracy: 0.9283 - val_loss: 0.8478 - val_accuracy: 0.6948 Epoch 486/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1940 - accuracy: 0.9495 - val_loss: 0.8467 - val_accuracy: 0.6753 Epoch 487/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1896 - accuracy: 0.9430 - val_loss: 0.8581 - val_accuracy: 0.6948 Epoch 488/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1855 - accuracy: 0.9479 - val_loss: 0.9008 - val_accuracy: 0.6753 Epoch 489/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1855 - accuracy: 0.9430 - val_loss: 0.8816 - val_accuracy: 0.6818 Epoch 490/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1892 - accuracy: 0.9397 - val_loss: 0.9003 - val_accuracy: 0.6753 Epoch 491/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1890 - accuracy: 0.9446 - val_loss: 0.8776 - val_accuracy: 0.6948 Epoch 492/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1878 - accuracy: 0.9495 - val_loss: 0.9079 - val_accuracy: 0.6948 Epoch 493/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1810 - accuracy: 0.9463 - val_loss: 0.8885 - val_accuracy: 0.6883 Epoch 494/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1938 - accuracy: 0.9349 - val_loss: 0.9426 - val_accuracy: 0.6753 Epoch 495/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2139 - accuracy: 0.9332 - val_loss: 0.9622 - val_accuracy: 0.6818 Epoch 496/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2291 - accuracy: 0.9153 - val_loss: 0.8989 - val_accuracy: 0.7013 Epoch 497/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2405 - accuracy: 0.9202 - val_loss: 0.9242 - val_accuracy: 0.6883 Epoch 498/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2331 - accuracy: 0.9137 - val_loss: 0.9466 - val_accuracy: 0.6688 Epoch 499/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2249 - accuracy: 0.9251 - val_loss: 1.0561 - val_accuracy: 0.6883 Epoch 500/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2088 - accuracy: 0.9316 - val_loss: 0.9025 - val_accuracy: 0.6948 Epoch 501/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2046 - accuracy: 0.9283 - val_loss: 0.8726 - val_accuracy: 0.6883 Epoch 502/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2299 - accuracy: 0.9121 - val_loss: 0.9594 - val_accuracy: 0.6883 Epoch 503/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2339 - accuracy: 0.9121 - val_loss: 0.8957 - val_accuracy: 0.7013 Epoch 504/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2274 - accuracy: 0.9251 - val_loss: 0.9119 - val_accuracy: 0.6688 Epoch 505/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2106 - accuracy: 0.9267 - val_loss: 0.9075 - val_accuracy: 0.6623 Epoch 506/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1975 - accuracy: 0.9397 - val_loss: 0.8801 - val_accuracy: 0.6818 Epoch 507/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2287 - accuracy: 0.9169 - val_loss: 0.9167 - val_accuracy: 0.7013 Epoch 508/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2176 - accuracy: 0.9169 - val_loss: 0.9065 - val_accuracy: 0.6688 Epoch 509/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3020 - accuracy: 0.8844 - val_loss: 0.9183 - val_accuracy: 0.6948 Epoch 510/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2477 - accuracy: 0.9104 - val_loss: 0.9541 - val_accuracy: 0.6883 Epoch 511/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2214 - accuracy: 0.9283 - val_loss: 0.8736 - val_accuracy: 0.7143 Epoch 512/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2093 - accuracy: 0.9349 - val_loss: 0.9641 - val_accuracy: 0.6753 Epoch 513/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1969 - accuracy: 0.9332 - val_loss: 0.9001 - val_accuracy: 0.6883 Epoch 514/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2790 - accuracy: 0.8925 - val_loss: 0.9543 - val_accuracy: 0.6623 Epoch 515/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2350 - accuracy: 0.9186 - val_loss: 0.8829 - val_accuracy: 0.6688 Epoch 516/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2281 - accuracy: 0.9137 - val_loss: 0.9036 - val_accuracy: 0.6948 Epoch 517/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2130 - accuracy: 0.9267 - val_loss: 0.9285 - val_accuracy: 0.6494 Epoch 518/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2742 - accuracy: 0.8941 - val_loss: 0.9110 - val_accuracy: 0.6883 Epoch 519/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2163 - accuracy: 0.9300 - val_loss: 0.9066 - val_accuracy: 0.6818 Epoch 520/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1899 - accuracy: 0.9365 - val_loss: 0.9059 - val_accuracy: 0.6753 Epoch 521/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2000 - accuracy: 0.9381 - val_loss: 0.9422 - val_accuracy: 0.6494 Epoch 522/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1917 - accuracy: 0.9446 - val_loss: 0.9744 - val_accuracy: 0.6753 Epoch 523/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2515 - accuracy: 0.9121 - val_loss: 0.9275 - val_accuracy: 0.6753 Epoch 524/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2802 - accuracy: 0.8909 - val_loss: 0.9629 - val_accuracy: 0.6753 Epoch 525/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2741 - accuracy: 0.9055 - val_loss: 1.1172 - val_accuracy: 0.6753 Epoch 526/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2342 - accuracy: 0.9202 - val_loss: 0.9195 - val_accuracy: 0.6948 Epoch 527/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2266 - accuracy: 0.9267 - val_loss: 1.0148 - val_accuracy: 0.6558 Epoch 528/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2330 - accuracy: 0.9121 - val_loss: 0.9471 - val_accuracy: 0.6753 Epoch 529/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2604 - accuracy: 0.9121 - val_loss: 0.9336 - val_accuracy: 0.6494 Epoch 530/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2058 - accuracy: 0.9235 - val_loss: 0.9099 - val_accuracy: 0.7013 Epoch 531/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2158 - accuracy: 0.9251 - val_loss: 0.9451 - val_accuracy: 0.6753 Epoch 532/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2196 - accuracy: 0.9267 - val_loss: 0.8643 - val_accuracy: 0.7273 Epoch 533/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2056 - accuracy: 0.9414 - val_loss: 0.8959 - val_accuracy: 0.6753 Epoch 534/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2041 - accuracy: 0.9349 - val_loss: 0.9118 - val_accuracy: 0.6688 Epoch 535/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2042 - accuracy: 0.9349 - val_loss: 0.9491 - val_accuracy: 0.6883 Epoch 536/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2490 - accuracy: 0.9121 - val_loss: 0.9654 - val_accuracy: 0.6753 Epoch 537/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2109 - accuracy: 0.9283 - val_loss: 0.9465 - val_accuracy: 0.6883 Epoch 538/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1946 - accuracy: 0.9316 - val_loss: 0.9196 - val_accuracy: 0.6753 Epoch 539/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2262 - accuracy: 0.9235 - val_loss: 0.9358 - val_accuracy: 0.6753 Epoch 540/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.1998 - accuracy: 0.9316 - val_loss: 0.9335 - val_accuracy: 0.6818 Epoch 541/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1770 - accuracy: 0.9511 - val_loss: 0.9242 - val_accuracy: 0.6883 Epoch 542/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1955 - accuracy: 0.9430 - val_loss: 0.9195 - val_accuracy: 0.6818 Epoch 543/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1958 - accuracy: 0.9414 - val_loss: 0.9506 - val_accuracy: 0.6818 Epoch 544/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2080 - accuracy: 0.9381 - val_loss: 0.9048 - val_accuracy: 0.6753 Epoch 545/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1923 - accuracy: 0.9349 - val_loss: 0.9622 - val_accuracy: 0.6623 Epoch 546/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2301 - accuracy: 0.9202 - val_loss: 0.9289 - val_accuracy: 0.6688 Epoch 547/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2337 - accuracy: 0.9251 - val_loss: 0.9130 - val_accuracy: 0.6818 Epoch 548/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2213 - accuracy: 0.9169 - val_loss: 0.9402 - val_accuracy: 0.6558 Epoch 549/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2154 - accuracy: 0.9251 - val_loss: 0.9344 - val_accuracy: 0.7013 Epoch 550/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2036 - accuracy: 0.9365 - val_loss: 0.9650 - val_accuracy: 0.6688 Epoch 551/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1809 - accuracy: 0.9446 - val_loss: 0.9140 - val_accuracy: 0.6883 Epoch 552/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1729 - accuracy: 0.9479 - val_loss: 0.9613 - val_accuracy: 0.6818 Epoch 553/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2084 - accuracy: 0.9349 - val_loss: 0.9893 - val_accuracy: 0.6753 Epoch 554/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2110 - accuracy: 0.9316 - val_loss: 1.0013 - val_accuracy: 0.6818 Epoch 555/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1844 - accuracy: 0.9495 - val_loss: 0.9215 - val_accuracy: 0.6948 Epoch 556/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1828 - accuracy: 0.9479 - val_loss: 0.8882 - val_accuracy: 0.7143 Epoch 557/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2195 - accuracy: 0.9267 - val_loss: 0.9413 - val_accuracy: 0.6818 Epoch 558/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2403 - accuracy: 0.9186 - val_loss: 1.0579 - val_accuracy: 0.6558 Epoch 559/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3040 - accuracy: 0.8844 - val_loss: 0.9294 - val_accuracy: 0.6494 Epoch 560/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2201 - accuracy: 0.9121 - val_loss: 0.9764 - val_accuracy: 0.6429 Epoch 561/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1993 - accuracy: 0.9300 - val_loss: 0.9114 - val_accuracy: 0.6818 Epoch 562/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1907 - accuracy: 0.9414 - val_loss: 0.9313 - val_accuracy: 0.6883 Epoch 563/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1936 - accuracy: 0.9349 - val_loss: 0.9579 - val_accuracy: 0.6623 Epoch 564/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1878 - accuracy: 0.9430 - val_loss: 0.8967 - val_accuracy: 0.6818 Epoch 565/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1961 - accuracy: 0.9365 - val_loss: 0.9344 - val_accuracy: 0.6948 Epoch 566/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1912 - accuracy: 0.9397 - val_loss: 0.9403 - val_accuracy: 0.6818 Epoch 567/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1916 - accuracy: 0.9365 - val_loss: 0.9616 - val_accuracy: 0.6753 Epoch 568/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1898 - accuracy: 0.9446 - val_loss: 0.9695 - val_accuracy: 0.6883 Epoch 569/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2096 - accuracy: 0.9235 - val_loss: 1.0082 - val_accuracy: 0.6558 Epoch 570/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1953 - accuracy: 0.9397 - val_loss: 0.9745 - val_accuracy: 0.6429 Epoch 571/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1905 - accuracy: 0.9414 - val_loss: 0.9656 - val_accuracy: 0.6688 Epoch 572/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1768 - accuracy: 0.9430 - val_loss: 0.9602 - val_accuracy: 0.6753 Epoch 573/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1997 - accuracy: 0.9365 - val_loss: 0.9520 - val_accuracy: 0.7013 Epoch 574/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1896 - accuracy: 0.9479 - val_loss: 0.9334 - val_accuracy: 0.6753 Epoch 575/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2047 - accuracy: 0.9332 - val_loss: 0.9502 - val_accuracy: 0.6494 Epoch 576/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2037 - accuracy: 0.9300 - val_loss: 0.9765 - val_accuracy: 0.6623 Epoch 577/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2407 - accuracy: 0.9169 - val_loss: 0.9535 - val_accuracy: 0.6818 Epoch 578/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2195 - accuracy: 0.9235 - val_loss: 0.9485 - val_accuracy: 0.6688 Epoch 579/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2599 - accuracy: 0.9072 - val_loss: 1.1692 - val_accuracy: 0.6494 Epoch 580/1000 20/20 [==============================] - 0s 9ms/step - loss: 0.2586 - accuracy: 0.9104 - val_loss: 0.9760 - val_accuracy: 0.6883 Epoch 581/1000 20/20 [==============================] - 0s 14ms/step - loss: 0.1869 - accuracy: 0.9397 - val_loss: 0.9456 - val_accuracy: 0.6818 Epoch 582/1000 20/20 [==============================] - 0s 10ms/step - loss: 0.2081 - accuracy: 0.9267 - val_loss: 1.0172 - val_accuracy: 0.6429 Epoch 583/1000 20/20 [==============================] - 0s 8ms/step - loss: 0.1972 - accuracy: 0.9349 - val_loss: 0.9700 - val_accuracy: 0.6818 Epoch 584/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1896 - accuracy: 0.9397 - val_loss: 1.0033 - val_accuracy: 0.6818 Epoch 585/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2000 - accuracy: 0.9349 - val_loss: 0.9427 - val_accuracy: 0.6818 Epoch 586/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1956 - accuracy: 0.9397 - val_loss: 0.9601 - val_accuracy: 0.6883 Epoch 587/1000 20/20 [==============================] - 0s 7ms/step - loss: 0.2346 - accuracy: 0.9186 - val_loss: 0.9867 - val_accuracy: 0.6753 Epoch 588/1000 20/20 [==============================] - 0s 14ms/step - loss: 0.2219 - accuracy: 0.9218 - val_loss: 0.9570 - val_accuracy: 0.6623 Epoch 589/1000 20/20 [==============================] - 0s 13ms/step - loss: 0.1937 - accuracy: 0.9349 - val_loss: 0.9945 - val_accuracy: 0.6623 Epoch 590/1000 20/20 [==============================] - 0s 9ms/step - loss: 0.1880 - accuracy: 0.9365 - val_loss: 0.9757 - val_accuracy: 0.6688 Epoch 591/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1748 - accuracy: 0.9544 - val_loss: 0.9286 - val_accuracy: 0.6753 Epoch 592/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1761 - accuracy: 0.9381 - val_loss: 0.9793 - val_accuracy: 0.6623 Epoch 593/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1833 - accuracy: 0.9463 - val_loss: 0.9532 - val_accuracy: 0.6883 Epoch 594/1000 20/20 [==============================] - 0s 9ms/step - loss: 0.1856 - accuracy: 0.9430 - val_loss: 0.9778 - val_accuracy: 0.6883 Epoch 595/1000 20/20 [==============================] - 0s 14ms/step - loss: 0.1917 - accuracy: 0.9349 - val_loss: 1.0564 - val_accuracy: 0.6364 Epoch 596/1000 20/20 [==============================] - 0s 13ms/step - loss: 0.1884 - accuracy: 0.9414 - val_loss: 0.9869 - val_accuracy: 0.6688 Epoch 597/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1827 - accuracy: 0.9414 - val_loss: 0.9832 - val_accuracy: 0.6688 Epoch 598/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1865 - accuracy: 0.9414 - val_loss: 1.0339 - val_accuracy: 0.6558 Epoch 599/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1930 - accuracy: 0.9365 - val_loss: 1.0537 - val_accuracy: 0.6558 Epoch 600/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1890 - accuracy: 0.9381 - val_loss: 1.0102 - val_accuracy: 0.6688 Epoch 601/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.1764 - accuracy: 0.9495 - val_loss: 0.9737 - val_accuracy: 0.6688 Epoch 602/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1694 - accuracy: 0.9479 - val_loss: 1.0961 - val_accuracy: 0.6753 Epoch 603/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1994 - accuracy: 0.9365 - val_loss: 0.9624 - val_accuracy: 0.6623 Epoch 604/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2050 - accuracy: 0.9381 - val_loss: 0.9932 - val_accuracy: 0.6753 Epoch 605/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1922 - accuracy: 0.9414 - val_loss: 0.9975 - val_accuracy: 0.6948 Epoch 606/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2107 - accuracy: 0.9202 - val_loss: 1.0152 - val_accuracy: 0.6623 Epoch 607/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2612 - accuracy: 0.9023 - val_loss: 1.0823 - val_accuracy: 0.6623 Epoch 608/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2416 - accuracy: 0.9169 - val_loss: 0.9826 - val_accuracy: 0.6494 Epoch 609/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2130 - accuracy: 0.9283 - val_loss: 0.9223 - val_accuracy: 0.6883 Epoch 610/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1882 - accuracy: 0.9381 - val_loss: 1.0045 - val_accuracy: 0.6558 Epoch 611/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1789 - accuracy: 0.9414 - val_loss: 0.9956 - val_accuracy: 0.7078 Epoch 612/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1806 - accuracy: 0.9446 - val_loss: 1.0053 - val_accuracy: 0.6948 Epoch 613/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2238 - accuracy: 0.9153 - val_loss: 0.9369 - val_accuracy: 0.6818 Epoch 614/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1911 - accuracy: 0.9300 - val_loss: 0.9881 - val_accuracy: 0.6883 Epoch 615/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1921 - accuracy: 0.9430 - val_loss: 0.9911 - val_accuracy: 0.6623 Epoch 616/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1777 - accuracy: 0.9446 - val_loss: 1.0031 - val_accuracy: 0.6623 Epoch 617/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.1720 - accuracy: 0.9511 - val_loss: 0.9534 - val_accuracy: 0.7013 Epoch 618/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2135 - accuracy: 0.9267 - val_loss: 0.9756 - val_accuracy: 0.7013 Epoch 619/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2177 - accuracy: 0.9235 - val_loss: 0.9368 - val_accuracy: 0.7013 Epoch 620/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1967 - accuracy: 0.9332 - val_loss: 1.0210 - val_accuracy: 0.6429 Epoch 621/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1988 - accuracy: 0.9365 - val_loss: 0.9664 - val_accuracy: 0.6753 Epoch 622/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2321 - accuracy: 0.9251 - val_loss: 1.0406 - val_accuracy: 0.6494 Epoch 623/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2213 - accuracy: 0.9218 - val_loss: 0.9598 - val_accuracy: 0.6818 Epoch 624/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2345 - accuracy: 0.9251 - val_loss: 0.9637 - val_accuracy: 0.6948 Epoch 625/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2067 - accuracy: 0.9267 - val_loss: 1.0693 - val_accuracy: 0.6623 Epoch 626/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1942 - accuracy: 0.9300 - val_loss: 1.0073 - val_accuracy: 0.6494 Epoch 627/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1964 - accuracy: 0.9381 - val_loss: 0.9724 - val_accuracy: 0.6623 Epoch 628/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1830 - accuracy: 0.9446 - val_loss: 1.0677 - val_accuracy: 0.6558 Epoch 629/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1979 - accuracy: 0.9316 - val_loss: 0.9788 - val_accuracy: 0.6688 Epoch 630/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2113 - accuracy: 0.9300 - val_loss: 1.0112 - val_accuracy: 0.6688 Epoch 631/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2229 - accuracy: 0.9202 - val_loss: 1.0967 - val_accuracy: 0.6623 Epoch 632/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2067 - accuracy: 0.9235 - val_loss: 0.9208 - val_accuracy: 0.6623 Epoch 633/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1961 - accuracy: 0.9365 - val_loss: 0.9983 - val_accuracy: 0.6753 Epoch 634/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2061 - accuracy: 0.9332 - val_loss: 0.9396 - val_accuracy: 0.7078 Epoch 635/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2031 - accuracy: 0.9332 - val_loss: 1.0295 - val_accuracy: 0.6818 Epoch 636/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2039 - accuracy: 0.9381 - val_loss: 0.9933 - val_accuracy: 0.6948 Epoch 637/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2107 - accuracy: 0.9283 - val_loss: 0.9751 - val_accuracy: 0.7013 Epoch 638/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2169 - accuracy: 0.9283 - val_loss: 1.0390 - val_accuracy: 0.6494 Epoch 639/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1992 - accuracy: 0.9381 - val_loss: 1.0325 - val_accuracy: 0.7013 Epoch 640/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1963 - accuracy: 0.9381 - val_loss: 1.0203 - val_accuracy: 0.6688 Epoch 641/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1825 - accuracy: 0.9479 - val_loss: 0.9841 - val_accuracy: 0.6623 Epoch 642/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2014 - accuracy: 0.9235 - val_loss: 0.9720 - val_accuracy: 0.6753 Epoch 643/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2275 - accuracy: 0.9300 - val_loss: 1.1331 - val_accuracy: 0.6623 Epoch 644/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2144 - accuracy: 0.9267 - val_loss: 0.9880 - val_accuracy: 0.6753 Epoch 645/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2072 - accuracy: 0.9300 - val_loss: 0.9546 - val_accuracy: 0.6818 Epoch 646/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2047 - accuracy: 0.9267 - val_loss: 1.0529 - val_accuracy: 0.6818 Epoch 647/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1872 - accuracy: 0.9463 - val_loss: 1.0252 - val_accuracy: 0.6558 Epoch 648/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1646 - accuracy: 0.9560 - val_loss: 0.9540 - val_accuracy: 0.7078 Epoch 649/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1691 - accuracy: 0.9528 - val_loss: 0.9637 - val_accuracy: 0.6623 Epoch 650/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1732 - accuracy: 0.9479 - val_loss: 1.0491 - val_accuracy: 0.6818 Epoch 651/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.1897 - accuracy: 0.9446 - val_loss: 0.9867 - val_accuracy: 0.6883 Epoch 652/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1860 - accuracy: 0.9397 - val_loss: 0.9815 - val_accuracy: 0.6753 Epoch 653/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1744 - accuracy: 0.9511 - val_loss: 0.9992 - val_accuracy: 0.6623 Epoch 654/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1785 - accuracy: 0.9430 - val_loss: 0.9945 - val_accuracy: 0.6429 Epoch 655/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2199 - accuracy: 0.9218 - val_loss: 0.9738 - val_accuracy: 0.6753 Epoch 656/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2721 - accuracy: 0.9007 - val_loss: 0.9412 - val_accuracy: 0.6883 Epoch 657/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4048 - accuracy: 0.8550 - val_loss: 1.0914 - val_accuracy: 0.6558 Epoch 658/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2968 - accuracy: 0.8876 - val_loss: 0.9846 - val_accuracy: 0.7078 Epoch 659/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2693 - accuracy: 0.9104 - val_loss: 0.9907 - val_accuracy: 0.6429 Epoch 660/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2176 - accuracy: 0.9251 - val_loss: 1.0002 - val_accuracy: 0.6948 Epoch 661/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1957 - accuracy: 0.9349 - val_loss: 1.0406 - val_accuracy: 0.6429 Epoch 662/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1735 - accuracy: 0.9528 - val_loss: 0.9995 - val_accuracy: 0.6364 Epoch 663/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1833 - accuracy: 0.9381 - val_loss: 0.9541 - val_accuracy: 0.6688 Epoch 664/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1688 - accuracy: 0.9495 - val_loss: 0.9609 - val_accuracy: 0.7078 Epoch 665/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2201 - accuracy: 0.9202 - val_loss: 0.9839 - val_accuracy: 0.6558 Epoch 666/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2265 - accuracy: 0.9104 - val_loss: 0.9410 - val_accuracy: 0.7078 Epoch 667/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1895 - accuracy: 0.9430 - val_loss: 0.9918 - val_accuracy: 0.6753 Epoch 668/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1812 - accuracy: 0.9446 - val_loss: 0.9649 - val_accuracy: 0.6558 Epoch 669/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1923 - accuracy: 0.9365 - val_loss: 0.9766 - val_accuracy: 0.6948 Epoch 670/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1703 - accuracy: 0.9577 - val_loss: 0.9633 - val_accuracy: 0.6883 Epoch 671/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1794 - accuracy: 0.9511 - val_loss: 1.0153 - val_accuracy: 0.6494 Epoch 672/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1792 - accuracy: 0.9430 - val_loss: 0.9640 - val_accuracy: 0.6753 Epoch 673/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1821 - accuracy: 0.9528 - val_loss: 1.0009 - val_accuracy: 0.6688 Epoch 674/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1789 - accuracy: 0.9479 - val_loss: 1.0050 - val_accuracy: 0.6688 Epoch 675/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2128 - accuracy: 0.9251 - val_loss: 1.0321 - val_accuracy: 0.6753 Epoch 676/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1877 - accuracy: 0.9479 - val_loss: 1.0102 - val_accuracy: 0.6753 Epoch 677/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1992 - accuracy: 0.9381 - val_loss: 1.0467 - val_accuracy: 0.6948 Epoch 678/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2172 - accuracy: 0.9283 - val_loss: 1.0383 - val_accuracy: 0.6883 Epoch 679/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2172 - accuracy: 0.9251 - val_loss: 1.0316 - val_accuracy: 0.6753 Epoch 680/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2799 - accuracy: 0.8909 - val_loss: 1.0427 - val_accuracy: 0.7013 Epoch 681/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2026 - accuracy: 0.9381 - val_loss: 1.0489 - val_accuracy: 0.6299 Epoch 682/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1784 - accuracy: 0.9479 - val_loss: 1.0252 - val_accuracy: 0.6494 Epoch 683/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1761 - accuracy: 0.9463 - val_loss: 1.0335 - val_accuracy: 0.6753 Epoch 684/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1774 - accuracy: 0.9430 - val_loss: 0.9717 - val_accuracy: 0.6623 Epoch 685/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1676 - accuracy: 0.9577 - val_loss: 0.9649 - val_accuracy: 0.6688 Epoch 686/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1762 - accuracy: 0.9495 - val_loss: 1.0088 - val_accuracy: 0.6753 Epoch 687/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2073 - accuracy: 0.9267 - val_loss: 1.0002 - val_accuracy: 0.7013 Epoch 688/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2068 - accuracy: 0.9267 - val_loss: 1.0151 - val_accuracy: 0.6558 Epoch 689/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1715 - accuracy: 0.9463 - val_loss: 1.0277 - val_accuracy: 0.6429 Epoch 690/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2414 - accuracy: 0.9137 - val_loss: 0.9727 - val_accuracy: 0.6948 Epoch 691/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4231 - accuracy: 0.8453 - val_loss: 1.1695 - val_accuracy: 0.7013 Epoch 692/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2833 - accuracy: 0.8974 - val_loss: 1.0385 - val_accuracy: 0.6558 Epoch 693/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2071 - accuracy: 0.9316 - val_loss: 1.1004 - val_accuracy: 0.6169 Epoch 694/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1986 - accuracy: 0.9381 - val_loss: 0.9204 - val_accuracy: 0.6883 Epoch 695/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1823 - accuracy: 0.9430 - val_loss: 0.9646 - val_accuracy: 0.6688 Epoch 696/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1594 - accuracy: 0.9544 - val_loss: 0.9398 - val_accuracy: 0.6753 Epoch 697/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1544 - accuracy: 0.9609 - val_loss: 1.0002 - val_accuracy: 0.6494 Epoch 698/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1564 - accuracy: 0.9577 - val_loss: 0.9868 - val_accuracy: 0.6753 Epoch 699/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1600 - accuracy: 0.9528 - val_loss: 1.0038 - val_accuracy: 0.6558 Epoch 700/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1986 - accuracy: 0.9349 - val_loss: 1.0318 - val_accuracy: 0.6299 Epoch 701/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1632 - accuracy: 0.9593 - val_loss: 0.9723 - val_accuracy: 0.6818 Epoch 702/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2069 - accuracy: 0.9218 - val_loss: 0.9829 - val_accuracy: 0.6818 Epoch 703/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2028 - accuracy: 0.9267 - val_loss: 0.9961 - val_accuracy: 0.6623 Epoch 704/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1817 - accuracy: 0.9414 - val_loss: 0.9979 - val_accuracy: 0.6688 Epoch 705/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1705 - accuracy: 0.9528 - val_loss: 1.0224 - val_accuracy: 0.6688 Epoch 706/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2607 - accuracy: 0.9104 - val_loss: 0.9918 - val_accuracy: 0.6623 Epoch 707/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2555 - accuracy: 0.9202 - val_loss: 1.0267 - val_accuracy: 0.6688 Epoch 708/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2425 - accuracy: 0.9104 - val_loss: 0.9668 - val_accuracy: 0.6753 Epoch 709/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2555 - accuracy: 0.9055 - val_loss: 0.9909 - val_accuracy: 0.6688 Epoch 710/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2651 - accuracy: 0.8925 - val_loss: 1.0134 - val_accuracy: 0.6753 Epoch 711/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2164 - accuracy: 0.9381 - val_loss: 0.9532 - val_accuracy: 0.6753 Epoch 712/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1862 - accuracy: 0.9414 - val_loss: 0.9756 - val_accuracy: 0.6558 Epoch 713/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2582 - accuracy: 0.9121 - val_loss: 1.0965 - val_accuracy: 0.6558 Epoch 714/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2672 - accuracy: 0.9072 - val_loss: 0.9161 - val_accuracy: 0.6688 Epoch 715/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2224 - accuracy: 0.9251 - val_loss: 1.0205 - val_accuracy: 0.6883 Epoch 716/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2195 - accuracy: 0.9218 - val_loss: 1.0944 - val_accuracy: 0.6688 Epoch 717/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2181 - accuracy: 0.9251 - val_loss: 1.1145 - val_accuracy: 0.6623 Epoch 718/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1854 - accuracy: 0.9495 - val_loss: 0.9734 - val_accuracy: 0.6883 Epoch 719/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1603 - accuracy: 0.9560 - val_loss: 0.9752 - val_accuracy: 0.6429 Epoch 720/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1522 - accuracy: 0.9560 - val_loss: 0.9646 - val_accuracy: 0.7078 Epoch 721/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1610 - accuracy: 0.9511 - val_loss: 1.0595 - val_accuracy: 0.6494 Epoch 722/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1686 - accuracy: 0.9544 - val_loss: 0.9949 - val_accuracy: 0.6494 Epoch 723/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1588 - accuracy: 0.9495 - val_loss: 0.9833 - val_accuracy: 0.6883 Epoch 724/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1570 - accuracy: 0.9577 - val_loss: 1.0130 - val_accuracy: 0.6623 Epoch 725/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1482 - accuracy: 0.9593 - val_loss: 1.0061 - val_accuracy: 0.6753 Epoch 726/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1420 - accuracy: 0.9658 - val_loss: 1.0251 - val_accuracy: 0.6558 Epoch 727/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1447 - accuracy: 0.9674 - val_loss: 1.0572 - val_accuracy: 0.6623 Epoch 728/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1434 - accuracy: 0.9625 - val_loss: 1.0145 - val_accuracy: 0.6558 Epoch 729/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1545 - accuracy: 0.9511 - val_loss: 1.0013 - val_accuracy: 0.6688 Epoch 730/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2707 - accuracy: 0.9104 - val_loss: 1.0136 - val_accuracy: 0.6623 Epoch 731/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2290 - accuracy: 0.9251 - val_loss: 1.0470 - val_accuracy: 0.6558 Epoch 732/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1756 - accuracy: 0.9479 - val_loss: 1.0743 - val_accuracy: 0.6494 Epoch 733/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.1691 - accuracy: 0.9511 - val_loss: 1.0202 - val_accuracy: 0.6818 Epoch 734/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1475 - accuracy: 0.9577 - val_loss: 1.0522 - val_accuracy: 0.6429 Epoch 735/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1672 - accuracy: 0.9446 - val_loss: 0.9981 - val_accuracy: 0.6623 Epoch 736/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1603 - accuracy: 0.9511 - val_loss: 1.0634 - val_accuracy: 0.6299 Epoch 737/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1502 - accuracy: 0.9593 - val_loss: 1.0166 - val_accuracy: 0.6623 Epoch 738/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1458 - accuracy: 0.9593 - val_loss: 1.0724 - val_accuracy: 0.6364 Epoch 739/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1684 - accuracy: 0.9430 - val_loss: 1.0299 - val_accuracy: 0.6494 Epoch 740/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2126 - accuracy: 0.9235 - val_loss: 1.1717 - val_accuracy: 0.6623 Epoch 741/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2045 - accuracy: 0.9267 - val_loss: 1.1363 - val_accuracy: 0.6623 Epoch 742/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1761 - accuracy: 0.9463 - val_loss: 1.0240 - val_accuracy: 0.6623 Epoch 743/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2060 - accuracy: 0.9251 - val_loss: 1.0631 - val_accuracy: 0.6753 Epoch 744/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1763 - accuracy: 0.9430 - val_loss: 1.1234 - val_accuracy: 0.6429 Epoch 745/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1553 - accuracy: 0.9560 - val_loss: 1.0609 - val_accuracy: 0.6364 Epoch 746/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.1461 - accuracy: 0.9593 - val_loss: 1.1082 - val_accuracy: 0.6364 Epoch 747/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1521 - accuracy: 0.9544 - val_loss: 1.1448 - val_accuracy: 0.6429 Epoch 748/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1635 - accuracy: 0.9528 - val_loss: 1.0751 - val_accuracy: 0.6558 Epoch 749/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1584 - accuracy: 0.9511 - val_loss: 1.0530 - val_accuracy: 0.6688 Epoch 750/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1414 - accuracy: 0.9674 - val_loss: 1.0820 - val_accuracy: 0.6364 Epoch 751/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1686 - accuracy: 0.9495 - val_loss: 1.1656 - val_accuracy: 0.6429 Epoch 752/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1684 - accuracy: 0.9446 - val_loss: 1.0746 - val_accuracy: 0.6494 Epoch 753/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1752 - accuracy: 0.9446 - val_loss: 1.1135 - val_accuracy: 0.6753 Epoch 754/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1948 - accuracy: 0.9332 - val_loss: 1.0892 - val_accuracy: 0.6558 Epoch 755/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2274 - accuracy: 0.9251 - val_loss: 1.2973 - val_accuracy: 0.6364 Epoch 756/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2840 - accuracy: 0.8990 - val_loss: 1.0093 - val_accuracy: 0.6818 Epoch 757/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2188 - accuracy: 0.9153 - val_loss: 1.1194 - val_accuracy: 0.6429 Epoch 758/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2575 - accuracy: 0.9072 - val_loss: 1.1833 - val_accuracy: 0.6104 Epoch 759/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1881 - accuracy: 0.9414 - val_loss: 1.0787 - val_accuracy: 0.6494 Epoch 760/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1496 - accuracy: 0.9658 - val_loss: 1.0580 - val_accuracy: 0.6494 Epoch 761/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2044 - accuracy: 0.9251 - val_loss: 1.1179 - val_accuracy: 0.6494 Epoch 762/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.1631 - accuracy: 0.9511 - val_loss: 1.1670 - val_accuracy: 0.6494 Epoch 763/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1752 - accuracy: 0.9446 - val_loss: 1.0583 - val_accuracy: 0.6753 Epoch 764/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1499 - accuracy: 0.9560 - val_loss: 1.0882 - val_accuracy: 0.6364 Epoch 765/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1468 - accuracy: 0.9577 - val_loss: 1.0490 - val_accuracy: 0.6753 Epoch 766/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1417 - accuracy: 0.9625 - val_loss: 1.1338 - val_accuracy: 0.6494 Epoch 767/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1738 - accuracy: 0.9365 - val_loss: 1.0881 - val_accuracy: 0.6688 Epoch 768/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1656 - accuracy: 0.9511 - val_loss: 1.0491 - val_accuracy: 0.6494 Epoch 769/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1812 - accuracy: 0.9381 - val_loss: 1.1205 - val_accuracy: 0.6623 Epoch 770/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2097 - accuracy: 0.9316 - val_loss: 1.0643 - val_accuracy: 0.6688 Epoch 771/1000 20/20 [==============================] - 0s 4ms/step - loss: 0.2252 - accuracy: 0.9218 - val_loss: 1.1082 - val_accuracy: 0.6494 Epoch 772/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1992 - accuracy: 0.9300 - val_loss: 1.0476 - val_accuracy: 0.6494 Epoch 773/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1665 - accuracy: 0.9463 - val_loss: 1.0850 - val_accuracy: 0.6429 Epoch 774/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1467 - accuracy: 0.9642 - val_loss: 1.1130 - val_accuracy: 0.6364 Epoch 775/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1387 - accuracy: 0.9658 - val_loss: 1.0720 - val_accuracy: 0.6429 Epoch 776/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1353 - accuracy: 0.9658 - val_loss: 1.0726 - val_accuracy: 0.6558 Epoch 777/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1402 - accuracy: 0.9625 - val_loss: 1.0941 - val_accuracy: 0.6623 Epoch 778/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1346 - accuracy: 0.9658 - val_loss: 1.0789 - val_accuracy: 0.6688 Epoch 779/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1468 - accuracy: 0.9528 - val_loss: 1.1368 - val_accuracy: 0.6299 Epoch 780/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1327 - accuracy: 0.9674 - val_loss: 1.0903 - val_accuracy: 0.6429 Epoch 781/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1379 - accuracy: 0.9642 - val_loss: 1.0696 - val_accuracy: 0.6753 Epoch 782/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1771 - accuracy: 0.9463 - val_loss: 1.1571 - val_accuracy: 0.6623 Epoch 783/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1850 - accuracy: 0.9414 - val_loss: 1.0915 - val_accuracy: 0.6494 Epoch 784/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2467 - accuracy: 0.9039 - val_loss: 1.1637 - val_accuracy: 0.6623 Epoch 785/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2099 - accuracy: 0.9218 - val_loss: 1.0937 - val_accuracy: 0.6623 Epoch 786/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2477 - accuracy: 0.9169 - val_loss: 1.1575 - val_accuracy: 0.6429 Epoch 787/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3812 - accuracy: 0.8697 - val_loss: 1.1270 - val_accuracy: 0.6364 Epoch 788/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.3075 - accuracy: 0.8779 - val_loss: 1.0297 - val_accuracy: 0.6688 Epoch 789/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.4186 - accuracy: 0.8453 - val_loss: 0.9356 - val_accuracy: 0.6623 Epoch 790/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3759 - accuracy: 0.8518 - val_loss: 0.9759 - val_accuracy: 0.6558 Epoch 791/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2579 - accuracy: 0.9055 - val_loss: 0.9932 - val_accuracy: 0.6818 Epoch 792/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2619 - accuracy: 0.9072 - val_loss: 1.0147 - val_accuracy: 0.6494 Epoch 793/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2644 - accuracy: 0.9023 - val_loss: 0.9942 - val_accuracy: 0.6753 Epoch 794/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2489 - accuracy: 0.9153 - val_loss: 0.9762 - val_accuracy: 0.6558 Epoch 795/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2329 - accuracy: 0.9186 - val_loss: 1.0169 - val_accuracy: 0.6364 Epoch 796/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1980 - accuracy: 0.9365 - val_loss: 0.9845 - val_accuracy: 0.6494 Epoch 797/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1766 - accuracy: 0.9397 - val_loss: 0.9515 - val_accuracy: 0.6753 Epoch 798/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1800 - accuracy: 0.9511 - val_loss: 1.0604 - val_accuracy: 0.6494 Epoch 799/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1640 - accuracy: 0.9577 - val_loss: 0.9814 - val_accuracy: 0.6688 Epoch 800/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1717 - accuracy: 0.9495 - val_loss: 0.9951 - val_accuracy: 0.6558 Epoch 801/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1609 - accuracy: 0.9560 - val_loss: 1.0069 - val_accuracy: 0.6753 Epoch 802/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1754 - accuracy: 0.9446 - val_loss: 0.9995 - val_accuracy: 0.6623 Epoch 803/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1954 - accuracy: 0.9365 - val_loss: 1.0526 - val_accuracy: 0.6948 Epoch 804/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2025 - accuracy: 0.9300 - val_loss: 1.0271 - val_accuracy: 0.6494 Epoch 805/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1520 - accuracy: 0.9593 - val_loss: 1.0597 - val_accuracy: 0.6364 Epoch 806/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1511 - accuracy: 0.9577 - val_loss: 0.9906 - val_accuracy: 0.6623 Epoch 807/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2334 - accuracy: 0.9218 - val_loss: 1.0546 - val_accuracy: 0.6558 Epoch 808/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1912 - accuracy: 0.9349 - val_loss: 1.0767 - val_accuracy: 0.6883 Epoch 809/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1516 - accuracy: 0.9593 - val_loss: 1.0738 - val_accuracy: 0.6623 Epoch 810/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1563 - accuracy: 0.9593 - val_loss: 1.0598 - val_accuracy: 0.6623 Epoch 811/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1623 - accuracy: 0.9511 - val_loss: 1.0636 - val_accuracy: 0.6753 Epoch 812/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1555 - accuracy: 0.9609 - val_loss: 1.0359 - val_accuracy: 0.6558 Epoch 813/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1642 - accuracy: 0.9511 - val_loss: 1.0680 - val_accuracy: 0.6494 Epoch 814/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1507 - accuracy: 0.9560 - val_loss: 1.0791 - val_accuracy: 0.6623 Epoch 815/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2765 - accuracy: 0.9137 - val_loss: 1.0174 - val_accuracy: 0.6818 Epoch 816/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2684 - accuracy: 0.8958 - val_loss: 1.1670 - val_accuracy: 0.6818 Epoch 817/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2416 - accuracy: 0.9186 - val_loss: 1.0574 - val_accuracy: 0.6688 Epoch 818/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1815 - accuracy: 0.9397 - val_loss: 1.0062 - val_accuracy: 0.6494 Epoch 819/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1641 - accuracy: 0.9511 - val_loss: 1.0707 - val_accuracy: 0.6494 Epoch 820/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1544 - accuracy: 0.9577 - val_loss: 1.0791 - val_accuracy: 0.6623 Epoch 821/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1503 - accuracy: 0.9593 - val_loss: 1.0121 - val_accuracy: 0.6623 Epoch 822/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1558 - accuracy: 0.9495 - val_loss: 1.0672 - val_accuracy: 0.6558 Epoch 823/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1477 - accuracy: 0.9593 - val_loss: 1.0495 - val_accuracy: 0.6688 Epoch 824/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1500 - accuracy: 0.9577 - val_loss: 1.0563 - val_accuracy: 0.6558 Epoch 825/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1442 - accuracy: 0.9625 - val_loss: 1.0038 - val_accuracy: 0.6753 Epoch 826/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1503 - accuracy: 0.9560 - val_loss: 1.1455 - val_accuracy: 0.6623 Epoch 827/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1434 - accuracy: 0.9609 - val_loss: 1.1266 - val_accuracy: 0.6688 Epoch 828/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1478 - accuracy: 0.9609 - val_loss: 1.0767 - val_accuracy: 0.6753 Epoch 829/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1397 - accuracy: 0.9674 - val_loss: 1.0560 - val_accuracy: 0.6623 Epoch 830/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1610 - accuracy: 0.9560 - val_loss: 1.0627 - val_accuracy: 0.6558 Epoch 831/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1567 - accuracy: 0.9544 - val_loss: 1.0936 - val_accuracy: 0.6688 Epoch 832/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1423 - accuracy: 0.9625 - val_loss: 1.1051 - val_accuracy: 0.6494 Epoch 833/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1506 - accuracy: 0.9577 - val_loss: 1.0591 - val_accuracy: 0.6494 Epoch 834/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1923 - accuracy: 0.9332 - val_loss: 1.1582 - val_accuracy: 0.6688 Epoch 835/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2417 - accuracy: 0.9235 - val_loss: 1.1512 - val_accuracy: 0.6494 Epoch 836/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1979 - accuracy: 0.9300 - val_loss: 1.1670 - val_accuracy: 0.6364 Epoch 837/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1681 - accuracy: 0.9463 - val_loss: 1.1418 - val_accuracy: 0.6623 Epoch 838/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1771 - accuracy: 0.9446 - val_loss: 1.0733 - val_accuracy: 0.6429 Epoch 839/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1796 - accuracy: 0.9446 - val_loss: 1.0501 - val_accuracy: 0.6753 Epoch 840/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1669 - accuracy: 0.9511 - val_loss: 1.1187 - val_accuracy: 0.6753 Epoch 841/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1565 - accuracy: 0.9511 - val_loss: 1.0902 - val_accuracy: 0.6818 Epoch 842/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1522 - accuracy: 0.9544 - val_loss: 1.1270 - val_accuracy: 0.6558 Epoch 843/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1379 - accuracy: 0.9658 - val_loss: 1.1309 - val_accuracy: 0.6753 Epoch 844/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1282 - accuracy: 0.9723 - val_loss: 1.1221 - val_accuracy: 0.6558 Epoch 845/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1259 - accuracy: 0.9739 - val_loss: 1.0962 - val_accuracy: 0.6623 Epoch 846/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1313 - accuracy: 0.9691 - val_loss: 1.0783 - val_accuracy: 0.6494 Epoch 847/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1676 - accuracy: 0.9495 - val_loss: 1.0933 - val_accuracy: 0.6429 Epoch 848/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1593 - accuracy: 0.9528 - val_loss: 1.1413 - val_accuracy: 0.6558 Epoch 849/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1660 - accuracy: 0.9430 - val_loss: 1.1783 - val_accuracy: 0.6299 Epoch 850/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2384 - accuracy: 0.9218 - val_loss: 1.0790 - val_accuracy: 0.6623 Epoch 851/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2186 - accuracy: 0.9202 - val_loss: 1.0730 - val_accuracy: 0.6558 Epoch 852/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2824 - accuracy: 0.8990 - val_loss: 1.3594 - val_accuracy: 0.6039 Epoch 853/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.3051 - accuracy: 0.8893 - val_loss: 1.0353 - val_accuracy: 0.6234 Epoch 854/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3065 - accuracy: 0.8925 - val_loss: 1.2213 - val_accuracy: 0.6429 Epoch 855/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2766 - accuracy: 0.9088 - val_loss: 1.0405 - val_accuracy: 0.6753 Epoch 856/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2073 - accuracy: 0.9316 - val_loss: 1.1024 - val_accuracy: 0.6558 Epoch 857/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1538 - accuracy: 0.9560 - val_loss: 1.1321 - val_accuracy: 0.6494 Epoch 858/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1521 - accuracy: 0.9642 - val_loss: 1.0489 - val_accuracy: 0.6818 Epoch 859/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1518 - accuracy: 0.9511 - val_loss: 0.9919 - val_accuracy: 0.6753 Epoch 860/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1468 - accuracy: 0.9658 - val_loss: 1.0489 - val_accuracy: 0.6429 Epoch 861/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1343 - accuracy: 0.9674 - val_loss: 1.0466 - val_accuracy: 0.6623 Epoch 862/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1469 - accuracy: 0.9593 - val_loss: 1.0508 - val_accuracy: 0.6494 Epoch 863/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1322 - accuracy: 0.9707 - val_loss: 1.0585 - val_accuracy: 0.6494 Epoch 864/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1323 - accuracy: 0.9707 - val_loss: 1.0768 - val_accuracy: 0.6688 Epoch 865/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1365 - accuracy: 0.9625 - val_loss: 1.1744 - val_accuracy: 0.6883 Epoch 866/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1431 - accuracy: 0.9658 - val_loss: 1.3172 - val_accuracy: 0.6558 Epoch 867/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1867 - accuracy: 0.9430 - val_loss: 1.2415 - val_accuracy: 0.6429 Epoch 868/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1679 - accuracy: 0.9511 - val_loss: 1.0650 - val_accuracy: 0.6494 Epoch 869/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1856 - accuracy: 0.9381 - val_loss: 1.1223 - val_accuracy: 0.6494 Epoch 870/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1684 - accuracy: 0.9446 - val_loss: 1.1768 - val_accuracy: 0.6558 Epoch 871/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1390 - accuracy: 0.9658 - val_loss: 1.1220 - val_accuracy: 0.6558 Epoch 872/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1354 - accuracy: 0.9658 - val_loss: 1.0909 - val_accuracy: 0.6429 Epoch 873/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1460 - accuracy: 0.9593 - val_loss: 1.2086 - val_accuracy: 0.6623 Epoch 874/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1510 - accuracy: 0.9593 - val_loss: 1.1500 - val_accuracy: 0.6948 Epoch 875/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1326 - accuracy: 0.9658 - val_loss: 1.0333 - val_accuracy: 0.6818 Epoch 876/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1325 - accuracy: 0.9625 - val_loss: 1.1464 - val_accuracy: 0.6558 Epoch 877/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1271 - accuracy: 0.9707 - val_loss: 1.0768 - val_accuracy: 0.6494 Epoch 878/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1983 - accuracy: 0.9414 - val_loss: 1.1110 - val_accuracy: 0.6429 Epoch 879/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1841 - accuracy: 0.9463 - val_loss: 1.2116 - val_accuracy: 0.6818 Epoch 880/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2044 - accuracy: 0.9332 - val_loss: 1.1327 - val_accuracy: 0.6364 Epoch 881/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1930 - accuracy: 0.9397 - val_loss: 1.2185 - val_accuracy: 0.6299 Epoch 882/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1935 - accuracy: 0.9349 - val_loss: 1.0024 - val_accuracy: 0.7078 Epoch 883/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2008 - accuracy: 0.9332 - val_loss: 1.1483 - val_accuracy: 0.6623 Epoch 884/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1541 - accuracy: 0.9560 - val_loss: 1.0788 - val_accuracy: 0.6688 Epoch 885/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1834 - accuracy: 0.9446 - val_loss: 1.0734 - val_accuracy: 0.6688 Epoch 886/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1752 - accuracy: 0.9463 - val_loss: 1.0651 - val_accuracy: 0.6753 Epoch 887/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1706 - accuracy: 0.9479 - val_loss: 1.1419 - val_accuracy: 0.6818 Epoch 888/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1634 - accuracy: 0.9495 - val_loss: 1.1163 - val_accuracy: 0.6688 Epoch 889/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1810 - accuracy: 0.9479 - val_loss: 1.0711 - val_accuracy: 0.6688 Epoch 890/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1610 - accuracy: 0.9511 - val_loss: 1.1907 - val_accuracy: 0.6558 Epoch 891/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1368 - accuracy: 0.9658 - val_loss: 1.2947 - val_accuracy: 0.6623 Epoch 892/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1573 - accuracy: 0.9593 - val_loss: 1.2252 - val_accuracy: 0.6429 Epoch 893/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1391 - accuracy: 0.9625 - val_loss: 1.1706 - val_accuracy: 0.6688 Epoch 894/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1459 - accuracy: 0.9642 - val_loss: 1.1004 - val_accuracy: 0.6558 Epoch 895/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1381 - accuracy: 0.9642 - val_loss: 1.1113 - val_accuracy: 0.6688 Epoch 896/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1233 - accuracy: 0.9723 - val_loss: 1.1539 - val_accuracy: 0.6558 Epoch 897/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1287 - accuracy: 0.9707 - val_loss: 1.1252 - val_accuracy: 0.6494 Epoch 898/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1265 - accuracy: 0.9691 - val_loss: 1.2592 - val_accuracy: 0.6688 Epoch 899/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1455 - accuracy: 0.9625 - val_loss: 1.1409 - val_accuracy: 0.6429 Epoch 900/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1719 - accuracy: 0.9528 - val_loss: 1.2678 - val_accuracy: 0.6558 Epoch 901/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1722 - accuracy: 0.9479 - val_loss: 1.1249 - val_accuracy: 0.6623 Epoch 902/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1563 - accuracy: 0.9511 - val_loss: 1.1105 - val_accuracy: 0.6558 Epoch 903/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1722 - accuracy: 0.9446 - val_loss: 1.3021 - val_accuracy: 0.6494 Epoch 904/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2096 - accuracy: 0.9349 - val_loss: 1.2964 - val_accuracy: 0.6299 Epoch 905/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2184 - accuracy: 0.9283 - val_loss: 1.1804 - val_accuracy: 0.6429 Epoch 906/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1920 - accuracy: 0.9332 - val_loss: 1.1602 - val_accuracy: 0.6364 Epoch 907/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1994 - accuracy: 0.9349 - val_loss: 1.2726 - val_accuracy: 0.6429 Epoch 908/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1836 - accuracy: 0.9414 - val_loss: 1.0981 - val_accuracy: 0.6688 Epoch 909/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3175 - accuracy: 0.8893 - val_loss: 1.0921 - val_accuracy: 0.6623 Epoch 910/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2943 - accuracy: 0.8958 - val_loss: 1.2600 - val_accuracy: 0.6753 Epoch 911/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2166 - accuracy: 0.9349 - val_loss: 1.1937 - val_accuracy: 0.6818 Epoch 912/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1791 - accuracy: 0.9446 - val_loss: 1.1221 - val_accuracy: 0.6818 Epoch 913/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2088 - accuracy: 0.9316 - val_loss: 1.2243 - val_accuracy: 0.6364 Epoch 914/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1499 - accuracy: 0.9609 - val_loss: 1.1793 - val_accuracy: 0.6169 Epoch 915/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1322 - accuracy: 0.9691 - val_loss: 1.1926 - val_accuracy: 0.6169 Epoch 916/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1369 - accuracy: 0.9658 - val_loss: 1.1552 - val_accuracy: 0.6429 Epoch 917/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3505 - accuracy: 0.8811 - val_loss: 1.1219 - val_accuracy: 0.6623 Epoch 918/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3266 - accuracy: 0.8876 - val_loss: 1.0811 - val_accuracy: 0.6948 Epoch 919/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2626 - accuracy: 0.9186 - val_loss: 1.2994 - val_accuracy: 0.6753 Epoch 920/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3713 - accuracy: 0.8664 - val_loss: 1.0022 - val_accuracy: 0.6688 Epoch 921/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3310 - accuracy: 0.8827 - val_loss: 1.0502 - val_accuracy: 0.6558 Epoch 922/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2188 - accuracy: 0.9267 - val_loss: 1.0355 - val_accuracy: 0.6818 Epoch 923/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1620 - accuracy: 0.9560 - val_loss: 1.1137 - val_accuracy: 0.6883 Epoch 924/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1893 - accuracy: 0.9479 - val_loss: 1.1400 - val_accuracy: 0.6883 Epoch 925/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1853 - accuracy: 0.9446 - val_loss: 1.1815 - val_accuracy: 0.6688 Epoch 926/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1706 - accuracy: 0.9528 - val_loss: 1.1808 - val_accuracy: 0.6364 Epoch 927/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1465 - accuracy: 0.9625 - val_loss: 1.0585 - val_accuracy: 0.6558 Epoch 928/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1379 - accuracy: 0.9658 - val_loss: 1.1247 - val_accuracy: 0.6558 Epoch 929/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1250 - accuracy: 0.9723 - val_loss: 1.1026 - val_accuracy: 0.6494 Epoch 930/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1309 - accuracy: 0.9691 - val_loss: 1.1148 - val_accuracy: 0.6429 Epoch 931/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1288 - accuracy: 0.9691 - val_loss: 1.0803 - val_accuracy: 0.6623 Epoch 932/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1251 - accuracy: 0.9691 - val_loss: 1.1594 - val_accuracy: 0.6558 Epoch 933/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1616 - accuracy: 0.9544 - val_loss: 1.2052 - val_accuracy: 0.6429 Epoch 934/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1543 - accuracy: 0.9577 - val_loss: 1.0406 - val_accuracy: 0.6558 Epoch 935/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1728 - accuracy: 0.9430 - val_loss: 1.1322 - val_accuracy: 0.6429 Epoch 936/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1746 - accuracy: 0.9381 - val_loss: 1.2102 - val_accuracy: 0.6623 Epoch 937/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1649 - accuracy: 0.9479 - val_loss: 1.0948 - val_accuracy: 0.6688 Epoch 938/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1492 - accuracy: 0.9593 - val_loss: 1.1785 - val_accuracy: 0.6494 Epoch 939/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1282 - accuracy: 0.9691 - val_loss: 1.2293 - val_accuracy: 0.6688 Epoch 940/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1281 - accuracy: 0.9739 - val_loss: 1.1756 - val_accuracy: 0.6558 Epoch 941/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1190 - accuracy: 0.9739 - val_loss: 1.1788 - val_accuracy: 0.6494 Epoch 942/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1234 - accuracy: 0.9707 - val_loss: 1.1827 - val_accuracy: 0.6429 Epoch 943/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1180 - accuracy: 0.9756 - val_loss: 1.1797 - val_accuracy: 0.6364 Epoch 944/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1148 - accuracy: 0.9756 - val_loss: 1.1431 - val_accuracy: 0.6364 Epoch 945/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1205 - accuracy: 0.9707 - val_loss: 1.1414 - val_accuracy: 0.6299 Epoch 946/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1212 - accuracy: 0.9739 - val_loss: 1.1896 - val_accuracy: 0.6623 Epoch 947/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1211 - accuracy: 0.9739 - val_loss: 1.2074 - val_accuracy: 0.6364 Epoch 948/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1172 - accuracy: 0.9756 - val_loss: 1.2229 - val_accuracy: 0.6299 Epoch 949/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1130 - accuracy: 0.9788 - val_loss: 1.1960 - val_accuracy: 0.6364 Epoch 950/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1101 - accuracy: 0.9788 - val_loss: 1.1762 - val_accuracy: 0.6494 Epoch 951/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1112 - accuracy: 0.9772 - val_loss: 1.2243 - val_accuracy: 0.6364 Epoch 952/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1126 - accuracy: 0.9739 - val_loss: 1.2089 - val_accuracy: 0.6429 Epoch 953/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1119 - accuracy: 0.9756 - val_loss: 1.2111 - val_accuracy: 0.6494 Epoch 954/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1132 - accuracy: 0.9756 - val_loss: 1.1762 - val_accuracy: 0.6429 Epoch 955/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1247 - accuracy: 0.9674 - val_loss: 1.1806 - val_accuracy: 0.6429 Epoch 956/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1257 - accuracy: 0.9723 - val_loss: 1.2006 - val_accuracy: 0.6429 Epoch 957/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1309 - accuracy: 0.9609 - val_loss: 1.2067 - val_accuracy: 0.6429 Epoch 958/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1167 - accuracy: 0.9723 - val_loss: 1.2571 - val_accuracy: 0.6623 Epoch 959/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1183 - accuracy: 0.9739 - val_loss: 1.2333 - val_accuracy: 0.6494 Epoch 960/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1170 - accuracy: 0.9707 - val_loss: 1.1706 - val_accuracy: 0.6364 Epoch 961/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1133 - accuracy: 0.9756 - val_loss: 1.1845 - val_accuracy: 0.6429 Epoch 962/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1174 - accuracy: 0.9723 - val_loss: 1.2070 - val_accuracy: 0.6558 Epoch 963/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1170 - accuracy: 0.9739 - val_loss: 1.2757 - val_accuracy: 0.6494 Epoch 964/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1268 - accuracy: 0.9674 - val_loss: 1.2223 - val_accuracy: 0.6429 Epoch 965/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1366 - accuracy: 0.9642 - val_loss: 1.2155 - val_accuracy: 0.6364 Epoch 966/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1528 - accuracy: 0.9544 - val_loss: 1.2107 - val_accuracy: 0.6688 Epoch 967/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1513 - accuracy: 0.9560 - val_loss: 1.1723 - val_accuracy: 0.6494 Epoch 968/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1359 - accuracy: 0.9625 - val_loss: 1.2943 - val_accuracy: 0.6623 Epoch 969/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1347 - accuracy: 0.9609 - val_loss: 1.1944 - val_accuracy: 0.6558 Epoch 970/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1363 - accuracy: 0.9609 - val_loss: 1.3131 - val_accuracy: 0.6494 Epoch 971/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1396 - accuracy: 0.9593 - val_loss: 1.1930 - val_accuracy: 0.6558 Epoch 972/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1397 - accuracy: 0.9593 - val_loss: 1.2103 - val_accuracy: 0.6429 Epoch 973/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2354 - accuracy: 0.9218 - val_loss: 1.1556 - val_accuracy: 0.6753 Epoch 974/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2625 - accuracy: 0.9023 - val_loss: 1.3253 - val_accuracy: 0.6818 Epoch 975/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3016 - accuracy: 0.9007 - val_loss: 1.1272 - val_accuracy: 0.6558 Epoch 976/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2392 - accuracy: 0.9218 - val_loss: 1.2048 - val_accuracy: 0.6299 Epoch 977/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2638 - accuracy: 0.9072 - val_loss: 1.1929 - val_accuracy: 0.6558 Epoch 978/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3372 - accuracy: 0.8844 - val_loss: 1.1494 - val_accuracy: 0.6169 Epoch 979/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.4096 - accuracy: 0.8648 - val_loss: 1.3081 - val_accuracy: 0.6234 Epoch 980/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3290 - accuracy: 0.8844 - val_loss: 1.0788 - val_accuracy: 0.6818 Epoch 981/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2756 - accuracy: 0.8925 - val_loss: 1.0204 - val_accuracy: 0.6494 Epoch 982/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2510 - accuracy: 0.9137 - val_loss: 1.0353 - val_accuracy: 0.6623 Epoch 983/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1825 - accuracy: 0.9463 - val_loss: 1.0701 - val_accuracy: 0.6558 Epoch 984/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1777 - accuracy: 0.9397 - val_loss: 1.0871 - val_accuracy: 0.6688 Epoch 985/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1695 - accuracy: 0.9430 - val_loss: 1.0219 - val_accuracy: 0.6623 Epoch 986/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1809 - accuracy: 0.9479 - val_loss: 1.0828 - val_accuracy: 0.6558 Epoch 987/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1902 - accuracy: 0.9349 - val_loss: 1.1941 - val_accuracy: 0.6234 Epoch 988/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.1875 - accuracy: 0.9349 - val_loss: 1.2069 - val_accuracy: 0.6169 Epoch 989/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1848 - accuracy: 0.9446 - val_loss: 1.0749 - val_accuracy: 0.6364 Epoch 990/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1996 - accuracy: 0.9397 - val_loss: 1.1488 - val_accuracy: 0.6429 Epoch 991/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2121 - accuracy: 0.9169 - val_loss: 1.0199 - val_accuracy: 0.6558 Epoch 992/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2025 - accuracy: 0.9332 - val_loss: 1.1011 - val_accuracy: 0.6494 Epoch 993/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2111 - accuracy: 0.9283 - val_loss: 1.1280 - val_accuracy: 0.6753 Epoch 994/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2771 - accuracy: 0.9104 - val_loss: 1.1492 - val_accuracy: 0.6104 Epoch 995/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.2181 - accuracy: 0.9202 - val_loss: 1.1718 - val_accuracy: 0.6234 Epoch 996/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2247 - accuracy: 0.9235 - val_loss: 1.1173 - val_accuracy: 0.6494 Epoch 997/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.3595 - accuracy: 0.8730 - val_loss: 0.9519 - val_accuracy: 0.6753 Epoch 998/1000 20/20 [==============================] - 0s 6ms/step - loss: 0.3934 - accuracy: 0.8599 - val_loss: 1.0246 - val_accuracy: 0.6558 Epoch 999/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.2454 - accuracy: 0.9088 - val_loss: 1.0550 - val_accuracy: 0.6234 Epoch 1000/1000 20/20 [==============================] - 0s 5ms/step - loss: 0.1943 - accuracy: 0.9332 - val_loss: 1.1029 - val_accuracy: 0.6299
# Train and Test accuracy
scores = data_model.evaluate(train_Data,train_Out)
print("Training Accuracy: %.2f%%\n" % (scores[1]*100))
scores = data_model.evaluate(test_Data,test_Out)
print("Testing Accuracy: %.2f%%\n" % (scores[1]*100))
20/20 [==============================] - 0s 2ms/step - loss: 0.1824 - accuracy: 0.9446 Training Accuracy: 94.46% 5/5 [==============================] - 0s 3ms/step - loss: 1.1029 - accuracy: 0.6299 Testing Accuracy: 62.99%
# Final Prediction
# print(data_model.predict(test_Data))
y_pred = data_model.predict(test_Data)
y_pred = (y_pred > 0.5)
print(data_model.predict(test_Data))
[[0.9723785 ] [0.11299576] [0.05191848] [0.0502142 ] [0.0510546 ] [0.05022976] [0.05174709] [0.2233914 ] [0.05010685] [0.05867384] [0.0503573 ] [0.64114493] [0.98810345] [0.99142027] [0.06660842] [0.8891807 ] [0.05015328] [0.05010618] [0.05009478] [0.99892646] [0.89426816] [0.3862329 ] [0.05065809] [0.0503502 ] [0.05009679] [0.22936077] [0.05009776] [0.05017937] [0.95447695] [0.27991658] [0.05047581] [0.05021083] [0.05053668] [0.05011471] [0.06978381] [0.06717681] [0.05055891] [0.5829469 ] [0.15289824] [0.05030768] [0.06842109] [0.27053097] [0.05011081] [0.05126071] [0.08216952] [0.05009293] [0.09476723] [0.05114725] [0.07133739] [0.05162222] [0.05766406] [0.4894815 ] [0.05019057] [0.05075838] [0.9705601 ] [0.05017595] [0.07978702] [0.05200158] [0.13101502] [0.0502149 ] [0.05018729] [0.05024514] [0.05009927] [0.05029488] [0.05052445] [0.98123264] [0.98625237] [0.0569446 ] [0.05009431] [0.9873117 ] [0.05515944] [0.99731416] [0.0518719 ] [0.34134623] [0.05158557] [0.05024603] [0.8317327 ] [0.08223611] [0.05020456] [0.05836295] [0.05020889] [0.99880505] [0.05011785] [0.05107394] [0.21155138] [0.99736494] [0.9974057 ] [0.15998839] [0.05027327] [0.05032261] [0.0782288 ] [0.05386608] [0.05084378] [0.0528693 ] [0.05085293] [0.36248344] [0.54361266] [0.05151636] [0.9971975 ] [0.05021935] [0.06912991] [0.07956848] [0.97716534] [0.5251408 ] [0.07872435] [0.69146955] [0.06335725] [0.06024087] [0.07849073] [0.99725866] [0.99359137] [0.05397739] [0.07976596] [0.1991642 ] [0.84029007] [0.95480996] [0.05010763] [0.8006339 ] [0.05048396] [0.08024397] [0.05361078] [0.05034398] [0.05012365] [0.05086515] [0.05241595] [0.6887157 ] [0.17417428] [0.0589607 ] [0.47734645] [0.05024667] [0.9923552 ] [0.97242874] [0.99703836] [0.05023484] [0.05012251] [0.05069051] [0.994319 ] [0.05857295] [0.99903935] [0.9417755 ] [0.2614153 ] [0.0504499 ] [0.06255119] [0.05129842] [0.05015489] [0.0546873 ] [0.05009293] [0.07625885] [0.1291127 ] [0.05492542] [0.0503952 ] [0.92417336] [0.05385143] [0.06461106]]
acc = hist.history['accuracy']
loss = hist.history['loss']
plt.plot(hist.history['accuracy'])
plt.title('model accuracy')
plt.ylabel('accuracy')
plt.xlabel('epoch')
plt.legend(['train'], loc='upper left')
plt.show()
plt.savefig('accuracy_curve.png')
<Figure size 640x480 with 0 Axes>
plt.plot(hist.history['loss'])
plt.title('model loss')
plt.ylabel('loss')
plt.xlabel('epoch')
plt.legend(['train'], loc='upper left')
plt.show()
plt.savefig('loss_curve.png')
<Figure size 640x480 with 0 Axes>