GOOGL stock 'Close' value prediction

In [6]:
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from pandas import datetime
import math, time
import itertools
from sklearn import preprocessing
import datetime
from operator import itemgetter
from sklearn.metrics import mean_squared_error
from math import sqrt
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.layers.recurrent import LSTM

Stock data function configured to drop all columns except 'Open','High' and 'Close'

In [8]:
def get_stock_data(stock_name, normalized=0):
    url = 'http://chart.finance.yahoo.com/table.csv?s=%s&a=11&b=15&c=2011&d=29&e=10&f=2016&g=d&ignore=.csv' % stock_name

    col_names = ['Date','Open','High','Low','Close','Volume','Adj Close']
    stock = pd.read_csv(url, header=0, names=col_names) 
    df = pd.DataFrame(stock)
    date_split = df['Date'].str.split('-').str
    df['Year'], df['Month'], df['Day'] = date_split
    df["Volume"] = df["Volume"] / 10000
    df.drop(df.columns[[0,3,5,6, 7,8,9]], axis=1, inplace=True) 
    return df

Loading GOOGL stock data from yahoo.com

In [10]:
stock_name = 'GOOGL'
df = get_stock_data(stock_name,0)
df.head()
Out[10]:
Open High Close
0 847.349976 848.830017 844.929993
1 844.950012 850.669983 849.669983
2 847.650024 848.359985 847.809998
3 851.080017 852.619995 851.000000
4 848.000000 853.789978 851.359985

Saving the data to a file for a future use

In [12]:
today = datetime.date.today()
file_name = stock_name+'_stock_%s.csv' % today
df.to_csv(file_name)
In [14]:
df['High'] = df['High'] / 100
df['Open'] = df['Open'] / 100
df['Close'] = df['Close'] / 100
df.head(5)
Out[14]:
Open High Close
0 8.4735 8.4883 8.4493
1 8.4495 8.5067 8.4967
2 8.4765 8.4836 8.4781
3 8.5108 8.5262 8.5100
4 8.4800 8.5379 8.5136

Updated load_data function from lstm.py, configured to accept any amount of features. It is set to calculate the last feature as a result.

In [15]:
def load_data(stock, seq_len):
    amount_of_features = len(stock.columns)
    data = stock.as_matrix() #pd.DataFrame(stock)
    sequence_length = seq_len + 1
    result = []
    for index in range(len(data) - sequence_length):
        result.append(data[index: index + sequence_length])

    result = np.array(result)
    row = round(0.9 * result.shape[0])
    train = result[:int(row), :]
    x_train = train[:, :-1]
    y_train = train[:, -1][:,-1]
    x_test = result[int(row):, :-1]
    y_test = result[int(row):, -1][:,-1]

    x_train = np.reshape(x_train, (x_train.shape[0], x_train.shape[1], amount_of_features))
    x_test = np.reshape(x_test, (x_test.shape[0], x_test.shape[1], amount_of_features))  

    return [x_train, y_train, x_test, y_test]

Building model functions

In [19]:
def build_model(layers):
    model = Sequential()

    model.add(LSTM(
        input_dim=layers[0],
        output_dim=layers[1],
        return_sequences=True))
    model.add(Dropout(0.2))

    model.add(LSTM(
        layers[2],
        return_sequences=False))
    model.add(Dropout(0.2))

    model.add(Dense(
        output_dim=layers[2]))
    model.add(Activation("linear"))

    start = time.time()
    model.compile(loss="mse", optimizer="rmsprop",metrics=['accuracy'])
    print("Compilation Time : ", time.time() - start)
    return model

def build_model2(layers):
        d = 0.2
        model = Sequential()
        model.add(LSTM(128, input_shape=(layers[1], layers[0]), return_sequences=True))
        model.add(Dropout(d))
        model.add(LSTM(64, input_shape=(layers[1], layers[0]), return_sequences=False))
        model.add(Dropout(d))
        model.add(Dense(16,init='uniform',activation='relu'))        
        model.add(Dense(1,init='uniform',activation='linear'))
        model.compile(loss='mse',optimizer='adam',metrics=['accuracy'])
        return model

Setting X and Y for training and testing

In [17]:
window = 22
X_train, y_train, X_test, y_test = load_data(df[::-1], window)
print("X_train", X_train.shape)
print("y_train", y_train.shape)
print("X_test", X_test.shape)
print("y_test", y_test.shape)
X_train (1156, 22, 3)
y_train (1156,)
X_test (129, 22, 3)
y_test (129,)

Loading the model sequence structure

In [21]:
# model = build_model([3,lag,1])
model = build_model2([3,window,1])

Executing the model & RMS/RMSE results

In [22]:
model.fit(
    X_train,
    y_train,
    batch_size=512,
    nb_epoch=500,
    validation_split=0.1,
    verbose=1)
Train on 1040 samples, validate on 116 samples
Epoch 1/500
1040/1040 [==============================] - 3s - loss: 54.4479 - acc: 0.0000e+00 - val_loss: 55.3397 - val_acc: 0.0000e+00
Epoch 2/500
1040/1040 [==============================] - 1s - loss: 53.9240 - acc: 0.0000e+00 - val_loss: 54.7664 - val_acc: 0.0000e+00
Epoch 3/500
1040/1040 [==============================] - 1s - loss: 53.3421 - acc: 0.0000e+00 - val_loss: 54.0150 - val_acc: 0.0000e+00
Epoch 4/500
1040/1040 [==============================] - 1s - loss: 52.5936 - acc: 0.0000e+00 - val_loss: 53.0274 - val_acc: 0.0000e+00
Epoch 5/500
1040/1040 [==============================] - 1s - loss: 51.5985 - acc: 0.0000e+00 - val_loss: 51.7602 - val_acc: 0.0000e+00
Epoch 6/500
1040/1040 [==============================] - 1s - loss: 50.3432 - acc: 0.0000e+00 - val_loss: 50.2000 - val_acc: 0.0000e+00
Epoch 7/500
1040/1040 [==============================] - 1s - loss: 48.8046 - acc: 0.0000e+00 - val_loss: 48.3070 - val_acc: 0.0000e+00
Epoch 8/500
1040/1040 [==============================] - 1s - loss: 46.9207 - acc: 0.0000e+00 - val_loss: 46.1274 - val_acc: 0.0000e+00
Epoch 9/500
1040/1040 [==============================] - 1s - loss: 44.8351 - acc: 0.0000e+00 - val_loss: 43.7308 - val_acc: 0.0000e+00
Epoch 10/500
1040/1040 [==============================] - 1s - loss: 42.4969 - acc: 0.0000e+00 - val_loss: 41.1017 - val_acc: 0.0000e+00
Epoch 11/500
1040/1040 [==============================] - 1s - loss: 39.9498 - acc: 0.0000e+00 - val_loss: 38.3410 - val_acc: 0.0000e+00
Epoch 12/500
1040/1040 [==============================] - 2s - loss: 37.2808 - acc: 0.0000e+00 - val_loss: 35.4859 - val_acc: 0.0000e+00
Epoch 13/500
1040/1040 [==============================] - 1s - loss: 34.5868 - acc: 0.0000e+00 - val_loss: 32.5139 - val_acc: 0.0000e+00
Epoch 14/500
1040/1040 [==============================] - 1s - loss: 31.7302 - acc: 0.0000e+00 - val_loss: 29.4246 - val_acc: 0.0000e+00
Epoch 15/500
1040/1040 [==============================] - 1s - loss: 28.8169 - acc: 0.0000e+00 - val_loss: 26.2567 - val_acc: 0.0000e+00
Epoch 16/500
1040/1040 [==============================] - 1s - loss: 25.7788 - acc: 0.0000e+00 - val_loss: 23.0738 - val_acc: 0.0000e+00
Epoch 17/500
1040/1040 [==============================] - 1s - loss: 22.7890 - acc: 0.0000e+00 - val_loss: 19.9490 - val_acc: 0.0000e+00
Epoch 18/500
1040/1040 [==============================] - 1s - loss: 19.9633 - acc: 0.0000e+00 - val_loss: 16.8959 - val_acc: 0.0000e+00
Epoch 19/500
1040/1040 [==============================] - 1s - loss: 17.1138 - acc: 0.0000e+00 - val_loss: 13.9843 - val_acc: 0.0000e+00
Epoch 20/500
1040/1040 [==============================] - 1s - loss: 14.6148 - acc: 0.0000e+00 - val_loss: 11.2876 - val_acc: 0.0000e+00
Epoch 21/500
1040/1040 [==============================] - 1s - loss: 12.0679 - acc: 0.0000e+00 - val_loss: 8.8333 - val_acc: 0.0000e+00
Epoch 22/500
1040/1040 [==============================] - 1s - loss: 9.9667 - acc: 0.0000e+00 - val_loss: 6.6652 - val_acc: 0.0000e+00
Epoch 23/500
1040/1040 [==============================] - 1s - loss: 8.0522 - acc: 0.0000e+00 - val_loss: 4.8272 - val_acc: 0.0000e+00
Epoch 24/500
1040/1040 [==============================] - 1s - loss: 6.5214 - acc: 0.0000e+00 - val_loss: 3.3333 - val_acc: 0.0000e+00
Epoch 25/500
1040/1040 [==============================] - 1s - loss: 5.4272 - acc: 0.0000e+00 - val_loss: 2.1697 - val_acc: 0.0000e+00
Epoch 26/500
1040/1040 [==============================] - 1s - loss: 4.6054 - acc: 0.0000e+00 - val_loss: 1.3403 - val_acc: 0.0000e+00
Epoch 27/500
1040/1040 [==============================] - 1s - loss: 3.9683 - acc: 0.0000e+00 - val_loss: 0.7877 - val_acc: 0.0000e+00
Epoch 28/500
1040/1040 [==============================] - 1s - loss: 3.6511 - acc: 0.0000e+00 - val_loss: 0.4272 - val_acc: 0.0000e+00
Epoch 29/500
1040/1040 [==============================] - 1s - loss: 3.4181 - acc: 0.0000e+00 - val_loss: 0.2238 - val_acc: 0.0000e+00
Epoch 30/500
1040/1040 [==============================] - 1s - loss: 3.4587 - acc: 0.0000e+00 - val_loss: 0.1296 - val_acc: 0.0000e+00
Epoch 31/500
1040/1040 [==============================] - 1s - loss: 3.4420 - acc: 0.0000e+00 - val_loss: 0.1002 - val_acc: 0.0000e+00
Epoch 32/500
1040/1040 [==============================] - 1s - loss: 3.5659 - acc: 0.0000e+00 - val_loss: 0.1020 - val_acc: 0.0000e+00
Epoch 33/500
1040/1040 [==============================] - 1s - loss: 3.5628 - acc: 0.0000e+00 - val_loss: 0.1043 - val_acc: 0.0000e+00
Epoch 34/500
1040/1040 [==============================] - 1s - loss: 3.6090 - acc: 0.0000e+00 - val_loss: 0.1017 - val_acc: 0.0000e+00
Epoch 35/500
1040/1040 [==============================] - 1s - loss: 3.4767 - acc: 0.0000e+00 - val_loss: 0.0994 - val_acc: 0.0000e+00
Epoch 36/500
1040/1040 [==============================] - 1s - loss: 3.5097 - acc: 0.0000e+00 - val_loss: 0.0997 - val_acc: 0.0000e+00
Epoch 37/500
1040/1040 [==============================] - 1s - loss: 3.4107 - acc: 0.0000e+00 - val_loss: 0.1025 - val_acc: 0.0000e+00
Epoch 38/500
1040/1040 [==============================] - 1s - loss: 3.4260 - acc: 0.0000e+00 - val_loss: 0.1095 - val_acc: 0.0000e+00
Epoch 39/500
1040/1040 [==============================] - 1s - loss: 3.6031 - acc: 0.0000e+00 - val_loss: 0.1237 - val_acc: 0.0000e+00
Epoch 40/500
1040/1040 [==============================] - 1s - loss: 3.3415 - acc: 0.0000e+00 - val_loss: 0.1450 - val_acc: 0.0000e+00
Epoch 41/500
1040/1040 [==============================] - 1s - loss: 3.4103 - acc: 0.0000e+00 - val_loss: 0.1689 - val_acc: 0.0000e+00
Epoch 42/500
1040/1040 [==============================] - 1s - loss: 3.3116 - acc: 0.0000e+00 - val_loss: 0.1896 - val_acc: 0.0000e+00
Epoch 43/500
1040/1040 [==============================] - 1s - loss: 3.4071 - acc: 0.0000e+00 - val_loss: 0.2088 - val_acc: 0.0000e+00
Epoch 44/500
1040/1040 [==============================] - 1s - loss: 3.4219 - acc: 0.0000e+00 - val_loss: 0.2247 - val_acc: 0.0000e+00
Epoch 45/500
1040/1040 [==============================] - 1s - loss: 3.4333 - acc: 0.0000e+00 - val_loss: 0.2435 - val_acc: 0.0000e+00
Epoch 46/500
1040/1040 [==============================] - 1s - loss: 3.4586 - acc: 0.0000e+00 - val_loss: 0.2581 - val_acc: 0.0000e+00
Epoch 47/500
1040/1040 [==============================] - 1s - loss: 3.3959 - acc: 0.0000e+00 - val_loss: 0.2589 - val_acc: 0.0000e+00
Epoch 48/500
1040/1040 [==============================] - 1s - loss: 3.4274 - acc: 0.0000e+00 - val_loss: 0.2567 - val_acc: 0.0000e+00
Epoch 49/500
1040/1040 [==============================] - 1s - loss: 3.3342 - acc: 0.0000e+00 - val_loss: 0.2565 - val_acc: 0.0000e+00
Epoch 50/500
1040/1040 [==============================] - 1s - loss: 3.3938 - acc: 0.0000e+00 - val_loss: 0.2636 - val_acc: 0.0000e+00
Epoch 51/500
1040/1040 [==============================] - 1s - loss: 3.4053 - acc: 0.0000e+00 - val_loss: 0.2665 - val_acc: 0.0000e+00
Epoch 52/500
1040/1040 [==============================] - 1s - loss: 3.3789 - acc: 0.0000e+00 - val_loss: 0.2603 - val_acc: 0.0000e+00
Epoch 53/500
1040/1040 [==============================] - 1s - loss: 3.3775 - acc: 0.0000e+00 - val_loss: 0.2572 - val_acc: 0.0000e+00
Epoch 54/500
1040/1040 [==============================] - 1s - loss: 3.3492 - acc: 0.0000e+00 - val_loss: 0.2501 - val_acc: 0.0000e+00
Epoch 55/500
1040/1040 [==============================] - 1s - loss: 3.3712 - acc: 0.0000e+00 - val_loss: 0.2377 - val_acc: 0.0000e+00
Epoch 56/500
1040/1040 [==============================] - 1s - loss: 3.3680 - acc: 0.0000e+00 - val_loss: 0.2370 - val_acc: 0.0000e+00
Epoch 57/500
1040/1040 [==============================] - 1s - loss: 3.4092 - acc: 0.0000e+00 - val_loss: 0.2433 - val_acc: 0.0000e+00
Epoch 58/500
1040/1040 [==============================] - 1s - loss: 3.4810 - acc: 0.0000e+00 - val_loss: 0.2591 - val_acc: 0.0000e+00
Epoch 59/500
1040/1040 [==============================] - 1s - loss: 3.3915 - acc: 0.0000e+00 - val_loss: 0.2634 - val_acc: 0.0000e+00
Epoch 60/500
1040/1040 [==============================] - 1s - loss: 3.3487 - acc: 0.0000e+00 - val_loss: 0.2454 - val_acc: 0.0000e+00
Epoch 61/500
1040/1040 [==============================] - 1s - loss: 3.3828 - acc: 0.0000e+00 - val_loss: 0.2326 - val_acc: 0.0000e+00
Epoch 62/500
1040/1040 [==============================] - 1s - loss: 3.3546 - acc: 0.0000e+00 - val_loss: 0.2290 - val_acc: 0.0000e+00
Epoch 63/500
1040/1040 [==============================] - 1s - loss: 3.4548 - acc: 0.0000e+00 - val_loss: 0.2149 - val_acc: 0.0000e+00
Epoch 64/500
1040/1040 [==============================] - 1s - loss: 3.3838 - acc: 0.0000e+00 - val_loss: 0.1979 - val_acc: 0.0000e+00
Epoch 65/500
1040/1040 [==============================] - 1s - loss: 3.4512 - acc: 0.0000e+00 - val_loss: 0.1950 - val_acc: 0.0000e+00
Epoch 66/500
1040/1040 [==============================] - 1s - loss: 3.4029 - acc: 0.0000e+00 - val_loss: 0.1933 - val_acc: 0.0000e+00
Epoch 67/500
1040/1040 [==============================] - 1s - loss: 3.3489 - acc: 0.0000e+00 - val_loss: 0.1799 - val_acc: 0.0000e+00
Epoch 68/500
1040/1040 [==============================] - 1s - loss: 3.2819 - acc: 0.0000e+00 - val_loss: 0.1670 - val_acc: 0.0000e+00
Epoch 69/500
1040/1040 [==============================] - 1s - loss: 3.4493 - acc: 0.0000e+00 - val_loss: 0.1679 - val_acc: 0.0000e+00
Epoch 70/500
1040/1040 [==============================] - 1s - loss: 3.3947 - acc: 0.0000e+00 - val_loss: 0.1673 - val_acc: 0.0000e+00
Epoch 71/500
1040/1040 [==============================] - 1s - loss: 3.4354 - acc: 0.0000e+00 - val_loss: 0.1669 - val_acc: 0.0000e+00
Epoch 72/500
1040/1040 [==============================] - 1s - loss: 3.4535 - acc: 0.0000e+00 - val_loss: 0.1755 - val_acc: 0.0000e+00
Epoch 73/500
1040/1040 [==============================] - 1s - loss: 3.3567 - acc: 0.0000e+00 - val_loss: 0.1858 - val_acc: 0.0000e+00
Epoch 74/500
1040/1040 [==============================] - 1s - loss: 3.3998 - acc: 0.0000e+00 - val_loss: 0.2019 - val_acc: 0.0000e+00
Epoch 75/500
1040/1040 [==============================] - 1s - loss: 3.4908 - acc: 0.0000e+00 - val_loss: 0.2205 - val_acc: 0.0000e+00
Epoch 76/500
1040/1040 [==============================] - 1s - loss: 3.5161 - acc: 0.0000e+00 - val_loss: 0.2380 - val_acc: 0.0000e+00
Epoch 77/500
1040/1040 [==============================] - 1s - loss: 3.4520 - acc: 0.0000e+00 - val_loss: 0.2495 - val_acc: 0.0000e+00
Epoch 78/500
1040/1040 [==============================] - 1s - loss: 3.3345 - acc: 0.0000e+00 - val_loss: 0.2560 - val_acc: 0.0000e+00
Epoch 79/500
1040/1040 [==============================] - 1s - loss: 3.4836 - acc: 0.0000e+00 - val_loss: 0.2716 - val_acc: 0.0000e+00
Epoch 80/500
1040/1040 [==============================] - 1s - loss: 3.4442 - acc: 0.0000e+00 - val_loss: 0.2919 - val_acc: 0.0000e+00
Epoch 81/500
1040/1040 [==============================] - 1s - loss: 3.4717 - acc: 0.0000e+00 - val_loss: 0.3113 - val_acc: 0.0000e+00
Epoch 82/500
1040/1040 [==============================] - 1s - loss: 3.4921 - acc: 0.0000e+00 - val_loss: 0.3150 - val_acc: 0.0000e+00
Epoch 83/500
1040/1040 [==============================] - 1s - loss: 3.4023 - acc: 0.0000e+00 - val_loss: 0.3100 - val_acc: 0.0000e+00
Epoch 84/500
1040/1040 [==============================] - 1s - loss: 3.4140 - acc: 0.0000e+00 - val_loss: 0.3146 - val_acc: 0.0000e+00
Epoch 85/500
1040/1040 [==============================] - 1s - loss: 3.4576 - acc: 0.0000e+00 - val_loss: 0.3224 - val_acc: 0.0000e+00
Epoch 86/500
1040/1040 [==============================] - 1s - loss: 3.5250 - acc: 0.0000e+00 - val_loss: 0.3195 - val_acc: 0.0000e+00
Epoch 87/500
1040/1040 [==============================] - 1s - loss: 3.4217 - acc: 0.0000e+00 - val_loss: 0.3142 - val_acc: 0.0000e+00
Epoch 88/500
1040/1040 [==============================] - 1s - loss: 3.3854 - acc: 0.0000e+00 - val_loss: 0.3186 - val_acc: 0.0000e+00
Epoch 89/500
1040/1040 [==============================] - 1s - loss: 3.3932 - acc: 0.0000e+00 - val_loss: 0.3267 - val_acc: 0.0000e+00
Epoch 90/500
1040/1040 [==============================] - 1s - loss: 3.4186 - acc: 0.0000e+00 - val_loss: 0.2999 - val_acc: 0.0000e+00
Epoch 91/500
1040/1040 [==============================] - 1s - loss: 3.5207 - acc: 0.0000e+00 - val_loss: 0.2638 - val_acc: 0.0000e+00
Epoch 92/500
1040/1040 [==============================] - 1s - loss: 3.3949 - acc: 0.0000e+00 - val_loss: 0.2413 - val_acc: 0.0000e+00
Epoch 93/500
1040/1040 [==============================] - 1s - loss: 3.4546 - acc: 0.0000e+00 - val_loss: 0.2147 - val_acc: 0.0000e+00
Epoch 94/500
1040/1040 [==============================] - 1s - loss: 3.3971 - acc: 0.0000e+00 - val_loss: 0.1939 - val_acc: 0.0000e+00
Epoch 95/500
1040/1040 [==============================] - 1s - loss: 3.3596 - acc: 0.0000e+00 - val_loss: 0.1819 - val_acc: 0.0000e+00
Epoch 96/500
1040/1040 [==============================] - 1s - loss: 3.4896 - acc: 0.0000e+00 - val_loss: 0.1756 - val_acc: 0.0000e+00
Epoch 97/500
1040/1040 [==============================] - 1s - loss: 3.4321 - acc: 0.0000e+00 - val_loss: 0.1863 - val_acc: 0.0000e+00
Epoch 98/500
1040/1040 [==============================] - 1s - loss: 3.4273 - acc: 0.0000e+00 - val_loss: 0.2061 - val_acc: 0.0000e+00
Epoch 99/500
1040/1040 [==============================] - 1s - loss: 3.4165 - acc: 0.0000e+00 - val_loss: 0.2256 - val_acc: 0.0000e+00
Epoch 100/500
1040/1040 [==============================] - 1s - loss: 3.3762 - acc: 0.0000e+00 - val_loss: 0.2468 - val_acc: 0.0000e+00
Epoch 101/500
1040/1040 [==============================] - 1s - loss: 3.4626 - acc: 0.0000e+00 - val_loss: 0.2459 - val_acc: 0.0000e+00
Epoch 102/500
1040/1040 [==============================] - 1s - loss: 3.3261 - acc: 0.0000e+00 - val_loss: 0.2357 - val_acc: 0.0000e+00
Epoch 103/500
1040/1040 [==============================] - 1s - loss: 3.4622 - acc: 0.0000e+00 - val_loss: 0.2407 - val_acc: 0.0000e+00
Epoch 104/500
1040/1040 [==============================] - 1s - loss: 3.3944 - acc: 0.0000e+00 - val_loss: 0.2418 - val_acc: 0.0000e+00
Epoch 105/500
1040/1040 [==============================] - 1s - loss: 3.3927 - acc: 0.0000e+00 - val_loss: 0.2267 - val_acc: 0.0000e+00
Epoch 106/500
1040/1040 [==============================] - 1s - loss: 3.4432 - acc: 0.0000e+00 - val_loss: 0.1956 - val_acc: 0.0000e+00
Epoch 107/500
1040/1040 [==============================] - 1s - loss: 3.4094 - acc: 0.0000e+00 - val_loss: 0.1626 - val_acc: 0.0000e+00
Epoch 108/500
1040/1040 [==============================] - 1s - loss: 3.4280 - acc: 0.0000e+00 - val_loss: 0.1401 - val_acc: 0.0000e+00
Epoch 109/500
1040/1040 [==============================] - 1s - loss: 3.4508 - acc: 0.0000e+00 - val_loss: 0.1253 - val_acc: 0.0000e+00
Epoch 110/500
1040/1040 [==============================] - 1s - loss: 3.5640 - acc: 0.0000e+00 - val_loss: 0.1227 - val_acc: 0.0000e+00
Epoch 111/500
1040/1040 [==============================] - 1s - loss: 3.4985 - acc: 0.0000e+00 - val_loss: 0.1278 - val_acc: 0.0000e+00
Epoch 112/500
1040/1040 [==============================] - 1s - loss: 3.3856 - acc: 0.0000e+00 - val_loss: 0.1387 - val_acc: 0.0000e+00
Epoch 113/500
1040/1040 [==============================] - 1s - loss: 3.4406 - acc: 0.0000e+00 - val_loss: 0.1528 - val_acc: 0.0000e+00
Epoch 114/500
1040/1040 [==============================] - 1s - loss: 3.3500 - acc: 0.0000e+00 - val_loss: 0.1812 - val_acc: 0.0000e+00
Epoch 115/500
1040/1040 [==============================] - 1s - loss: 3.3799 - acc: 0.0000e+00 - val_loss: 0.2069 - val_acc: 0.0000e+00
Epoch 116/500
1040/1040 [==============================] - 1s - loss: 3.3277 - acc: 0.0000e+00 - val_loss: 0.2255 - val_acc: 0.0000e+00
Epoch 117/500
1040/1040 [==============================] - 1s - loss: 3.4134 - acc: 0.0000e+00 - val_loss: 0.2288 - val_acc: 0.0000e+00
Epoch 118/500
1040/1040 [==============================] - 1s - loss: 3.4557 - acc: 0.0000e+00 - val_loss: 0.2143 - val_acc: 0.0000e+00
Epoch 119/500
1040/1040 [==============================] - 1s - loss: 3.3632 - acc: 0.0000e+00 - val_loss: 0.2020 - val_acc: 0.0000e+00
Epoch 120/500
1040/1040 [==============================] - 1s - loss: 3.3685 - acc: 0.0000e+00 - val_loss: 0.1993 - val_acc: 0.0000e+00
Epoch 121/500
1040/1040 [==============================] - 1s - loss: 3.4251 - acc: 0.0000e+00 - val_loss: 0.1904 - val_acc: 0.0000e+00
Epoch 122/500
1040/1040 [==============================] - 1s - loss: 3.4093 - acc: 0.0000e+00 - val_loss: 0.1777 - val_acc: 0.0000e+00
Epoch 123/500
1040/1040 [==============================] - 1s - loss: 3.3760 - acc: 0.0000e+00 - val_loss: 0.1711 - val_acc: 0.0000e+00
Epoch 124/500
1040/1040 [==============================] - 1s - loss: 3.4268 - acc: 0.0000e+00 - val_loss: 0.1647 - val_acc: 0.0000e+00
Epoch 125/500
1040/1040 [==============================] - 1s - loss: 3.4592 - acc: 0.0000e+00 - val_loss: 0.1622 - val_acc: 0.0000e+00
Epoch 126/500
1040/1040 [==============================] - 1s - loss: 3.3877 - acc: 0.0000e+00 - val_loss: 0.1699 - val_acc: 0.0000e+00
Epoch 127/500
1040/1040 [==============================] - 1s - loss: 3.4513 - acc: 0.0000e+00 - val_loss: 0.1889 - val_acc: 0.0000e+00
Epoch 128/500
1040/1040 [==============================] - 1s - loss: 3.4416 - acc: 0.0000e+00 - val_loss: 0.2225 - val_acc: 0.0000e+00
Epoch 129/500
1040/1040 [==============================] - 1s - loss: 3.4666 - acc: 0.0000e+00 - val_loss: 0.2576 - val_acc: 0.0000e+00
Epoch 130/500
1040/1040 [==============================] - 1s - loss: 3.4062 - acc: 0.0000e+00 - val_loss: 0.2761 - val_acc: 0.0000e+00
Epoch 131/500
1040/1040 [==============================] - 1s - loss: 3.3769 - acc: 0.0000e+00 - val_loss: 0.2715 - val_acc: 0.0000e+00
Epoch 132/500
1040/1040 [==============================] - 1s - loss: 3.3520 - acc: 0.0000e+00 - val_loss: 0.2673 - val_acc: 0.0000e+00
Epoch 133/500
1040/1040 [==============================] - 1s - loss: 3.4824 - acc: 0.0000e+00 - val_loss: 0.2681 - val_acc: 0.0000e+00
Epoch 134/500
1040/1040 [==============================] - 1s - loss: 3.4200 - acc: 0.0000e+00 - val_loss: 0.2615 - val_acc: 0.0000e+00
Epoch 135/500
1040/1040 [==============================] - 1s - loss: 3.4078 - acc: 0.0000e+00 - val_loss: 0.2293 - val_acc: 0.0000e+00
Epoch 136/500
1040/1040 [==============================] - 1s - loss: 3.3998 - acc: 0.0000e+00 - val_loss: 0.1935 - val_acc: 0.0000e+00
Epoch 137/500
1040/1040 [==============================] - 1s - loss: 3.3582 - acc: 0.0000e+00 - val_loss: 0.1767 - val_acc: 0.0000e+00
Epoch 138/500
1040/1040 [==============================] - 1s - loss: 3.4640 - acc: 0.0000e+00 - val_loss: 0.1642 - val_acc: 0.0000e+00
Epoch 139/500
1040/1040 [==============================] - 1s - loss: 3.4087 - acc: 0.0000e+00 - val_loss: 0.1530 - val_acc: 0.0000e+00
Epoch 140/500
1040/1040 [==============================] - 1s - loss: 3.3487 - acc: 0.0000e+00 - val_loss: 0.1504 - val_acc: 0.0000e+00
Epoch 141/500
1040/1040 [==============================] - 1s - loss: 3.4443 - acc: 0.0000e+00 - val_loss: 0.1586 - val_acc: 0.0000e+00
Epoch 142/500
1040/1040 [==============================] - 1s - loss: 3.5016 - acc: 0.0000e+00 - val_loss: 0.1913 - val_acc: 0.0000e+00
Epoch 143/500
1040/1040 [==============================] - 1s - loss: 3.4283 - acc: 0.0000e+00 - val_loss: 0.2209 - val_acc: 0.0000e+00
Epoch 144/500
1040/1040 [==============================] - 1s - loss: 3.4215 - acc: 0.0000e+00 - val_loss: 0.2436 - val_acc: 0.0000e+00
Epoch 145/500
1040/1040 [==============================] - 1s - loss: 3.3688 - acc: 0.0000e+00 - val_loss: 0.2574 - val_acc: 0.0000e+00
Epoch 146/500
1040/1040 [==============================] - 1s - loss: 3.4480 - acc: 0.0000e+00 - val_loss: 0.2683 - val_acc: 0.0000e+00
Epoch 147/500
1040/1040 [==============================] - 1s - loss: 3.3830 - acc: 0.0000e+00 - val_loss: 0.2764 - val_acc: 0.0000e+00
Epoch 148/500
1040/1040 [==============================] - 1s - loss: 3.4170 - acc: 0.0000e+00 - val_loss: 0.2713 - val_acc: 0.0000e+00
Epoch 149/500
1040/1040 [==============================] - 1s - loss: 3.4463 - acc: 0.0000e+00 - val_loss: 0.2572 - val_acc: 0.0000e+00
Epoch 150/500
1040/1040 [==============================] - 1s - loss: 3.4665 - acc: 0.0000e+00 - val_loss: 0.2356 - val_acc: 0.0000e+00
Epoch 151/500
1040/1040 [==============================] - 1s - loss: 3.4216 - acc: 0.0000e+00 - val_loss: 0.2180 - val_acc: 0.0000e+00
Epoch 152/500
1040/1040 [==============================] - 1s - loss: 3.3640 - acc: 0.0000e+00 - val_loss: 0.1975 - val_acc: 0.0000e+00
Epoch 153/500
1040/1040 [==============================] - 1s - loss: 3.4166 - acc: 0.0000e+00 - val_loss: 0.1749 - val_acc: 0.0000e+00
Epoch 154/500
1040/1040 [==============================] - 1s - loss: 3.3692 - acc: 0.0000e+00 - val_loss: 0.1778 - val_acc: 0.0000e+00
Epoch 155/500
1040/1040 [==============================] - 1s - loss: 3.3881 - acc: 0.0000e+00 - val_loss: 0.1958 - val_acc: 0.0000e+00
Epoch 156/500
1040/1040 [==============================] - 1s - loss: 3.4340 - acc: 0.0000e+00 - val_loss: 0.2108 - val_acc: 0.0000e+00
Epoch 157/500
1040/1040 [==============================] - 1s - loss: 3.4135 - acc: 0.0000e+00 - val_loss: 0.2209 - val_acc: 0.0000e+00
Epoch 158/500
1040/1040 [==============================] - 1s - loss: 3.5645 - acc: 0.0000e+00 - val_loss: 0.2057 - val_acc: 0.0000e+00
Epoch 159/500
1040/1040 [==============================] - 1s - loss: 3.4886 - acc: 0.0000e+00 - val_loss: 0.2176 - val_acc: 0.0000e+00
Epoch 160/500
1040/1040 [==============================] - 1s - loss: 3.4563 - acc: 0.0000e+00 - val_loss: 0.3203 - val_acc: 0.0000e+00
Epoch 161/500
1040/1040 [==============================] - 1s - loss: 3.4127 - acc: 0.0000e+00 - val_loss: 0.2942 - val_acc: 0.0000e+00
Epoch 162/500
1040/1040 [==============================] - 1s - loss: 3.2694 - acc: 0.0000e+00 - val_loss: 0.1695 - val_acc: 0.0000e+00
Epoch 163/500
1040/1040 [==============================] - 1s - loss: 3.2468 - acc: 0.0000e+00 - val_loss: 0.3122 - val_acc: 0.0000e+00
Epoch 164/500
1040/1040 [==============================] - 1s - loss: 3.1434 - acc: 0.0000e+00 - val_loss: 0.2239 - val_acc: 0.0000e+00
Epoch 165/500
1040/1040 [==============================] - 1s - loss: 3.0522 - acc: 0.0000e+00 - val_loss: 0.1195 - val_acc: 0.0000e+00
Epoch 166/500
1040/1040 [==============================] - 1s - loss: 3.1115 - acc: 0.0000e+00 - val_loss: 0.1293 - val_acc: 0.0000e+00
Epoch 167/500
1040/1040 [==============================] - 1s - loss: 2.9807 - acc: 0.0000e+00 - val_loss: 0.1593 - val_acc: 0.0000e+00
Epoch 168/500
1040/1040 [==============================] - 1s - loss: 2.9638 - acc: 0.0000e+00 - val_loss: 0.1089 - val_acc: 0.0000e+00
Epoch 169/500
1040/1040 [==============================] - 1s - loss: 3.0803 - acc: 0.0000e+00 - val_loss: 0.1363 - val_acc: 0.0000e+00
Epoch 170/500
1040/1040 [==============================] - 1s - loss: 2.8697 - acc: 0.0000e+00 - val_loss: 0.2998 - val_acc: 0.0000e+00
Epoch 171/500
1040/1040 [==============================] - 1s - loss: 2.8288 - acc: 0.0000e+00 - val_loss: 0.2411 - val_acc: 0.0000e+00
Epoch 172/500
1040/1040 [==============================] - 1s - loss: 2.8866 - acc: 0.0000e+00 - val_loss: 0.1597 - val_acc: 0.0000e+00
Epoch 173/500
1040/1040 [==============================] - 1s - loss: 2.7289 - acc: 0.0000e+00 - val_loss: 0.2759 - val_acc: 0.0000e+00
Epoch 174/500
1040/1040 [==============================] - 1s - loss: 2.6609 - acc: 0.0000e+00 - val_loss: 0.1533 - val_acc: 0.0000e+00
Epoch 175/500
1040/1040 [==============================] - 1s - loss: 2.5519 - acc: 0.0000e+00 - val_loss: 0.4066 - val_acc: 0.0000e+00
Epoch 176/500
1040/1040 [==============================] - 1s - loss: 2.5438 - acc: 0.0000e+00 - val_loss: 0.0998 - val_acc: 0.0000e+00
Epoch 177/500
1040/1040 [==============================] - 1s - loss: 2.3959 - acc: 0.0000e+00 - val_loss: 0.0863 - val_acc: 0.0000e+00
Epoch 178/500
1040/1040 [==============================] - 1s - loss: 2.2158 - acc: 0.0000e+00 - val_loss: 0.2083 - val_acc: 0.0000e+00
Epoch 179/500
1040/1040 [==============================] - 1s - loss: 2.1518 - acc: 0.0000e+00 - val_loss: 0.1760 - val_acc: 0.0000e+00
Epoch 180/500
1040/1040 [==============================] - 1s - loss: 2.0226 - acc: 0.0000e+00 - val_loss: 0.2398 - val_acc: 0.0000e+00
Epoch 181/500
1040/1040 [==============================] - 1s - loss: 1.9528 - acc: 0.0000e+00 - val_loss: 0.1493 - val_acc: 0.0000e+00
Epoch 182/500
1040/1040 [==============================] - 1s - loss: 1.8528 - acc: 0.0000e+00 - val_loss: 0.1245 - val_acc: 0.0000e+00
Epoch 183/500
1040/1040 [==============================] - 1s - loss: 1.6884 - acc: 0.0000e+00 - val_loss: 0.3437 - val_acc: 0.0000e+00
Epoch 184/500
1040/1040 [==============================] - 1s - loss: 1.6506 - acc: 0.0000e+00 - val_loss: 0.8178 - val_acc: 0.0000e+00
Epoch 185/500
1040/1040 [==============================] - 1s - loss: 1.3622 - acc: 0.0000e+00 - val_loss: 0.4868 - val_acc: 0.0000e+00
Epoch 186/500
1040/1040 [==============================] - 1s - loss: 1.3255 - acc: 0.0000e+00 - val_loss: 0.6509 - val_acc: 0.0000e+00
Epoch 187/500
1040/1040 [==============================] - 1s - loss: 1.2444 - acc: 0.0000e+00 - val_loss: 0.2801 - val_acc: 0.0000e+00
Epoch 188/500
1040/1040 [==============================] - 1s - loss: 1.0451 - acc: 0.0000e+00 - val_loss: 0.0810 - val_acc: 0.0000e+00
Epoch 189/500
1040/1040 [==============================] - 1s - loss: 1.1231 - acc: 0.0000e+00 - val_loss: 0.1973 - val_acc: 0.0000e+00
Epoch 190/500
1040/1040 [==============================] - 1s - loss: 1.0377 - acc: 0.0000e+00 - val_loss: 0.0629 - val_acc: 0.0000e+00
Epoch 191/500
1040/1040 [==============================] - 1s - loss: 1.1321 - acc: 0.0000e+00 - val_loss: 0.5786 - val_acc: 0.0000e+00
Epoch 192/500
1040/1040 [==============================] - 1s - loss: 0.9222 - acc: 0.0000e+00 - val_loss: 0.2990 - val_acc: 0.0000e+00
Epoch 193/500
1040/1040 [==============================] - 1s - loss: 0.9714 - acc: 0.0000e+00 - val_loss: 0.0712 - val_acc: 0.0000e+00
Epoch 194/500
1040/1040 [==============================] - 1s - loss: 0.8486 - acc: 0.0000e+00 - val_loss: 0.0588 - val_acc: 0.0000e+00
Epoch 195/500
1040/1040 [==============================] - 1s - loss: 0.7750 - acc: 0.0000e+00 - val_loss: 0.2256 - val_acc: 0.0000e+00
Epoch 196/500
1040/1040 [==============================] - 1s - loss: 0.9389 - acc: 0.0000e+00 - val_loss: 0.0678 - val_acc: 0.0000e+00
Epoch 197/500
1040/1040 [==============================] - 1s - loss: 0.6896 - acc: 0.0000e+00 - val_loss: 0.2156 - val_acc: 0.0000e+00
Epoch 198/500
1040/1040 [==============================] - 1s - loss: 0.7706 - acc: 0.0000e+00 - val_loss: 0.0613 - val_acc: 0.0000e+00
Epoch 199/500
1040/1040 [==============================] - 1s - loss: 0.7843 - acc: 0.0000e+00 - val_loss: 0.0788 - val_acc: 0.0000e+00
Epoch 200/500
1040/1040 [==============================] - 1s - loss: 0.6532 - acc: 0.0000e+00 - val_loss: 0.0320 - val_acc: 0.0000e+00
Epoch 201/500
1040/1040 [==============================] - 1s - loss: 0.6359 - acc: 0.0000e+00 - val_loss: 0.0752 - val_acc: 0.0000e+00
Epoch 202/500
1040/1040 [==============================] - 1s - loss: 0.6112 - acc: 0.0000e+00 - val_loss: 0.1450 - val_acc: 0.0000e+00
Epoch 203/500
1040/1040 [==============================] - 1s - loss: 0.5772 - acc: 0.0000e+00 - val_loss: 0.0299 - val_acc: 0.0000e+00
Epoch 204/500
1040/1040 [==============================] - 1s - loss: 0.5632 - acc: 0.0000e+00 - val_loss: 0.1483 - val_acc: 0.0000e+00
Epoch 205/500
1040/1040 [==============================] - 1s - loss: 0.5700 - acc: 0.0000e+00 - val_loss: 0.0864 - val_acc: 0.0000e+00
Epoch 206/500
1040/1040 [==============================] - 1s - loss: 0.5194 - acc: 0.0000e+00 - val_loss: 0.0319 - val_acc: 0.0000e+00
Epoch 207/500
1040/1040 [==============================] - 1s - loss: 0.5238 - acc: 0.0000e+00 - val_loss: 0.0665 - val_acc: 0.0000e+00
Epoch 208/500
1040/1040 [==============================] - 1s - loss: 0.5225 - acc: 0.0000e+00 - val_loss: 0.0420 - val_acc: 0.0000e+00
Epoch 209/500
1040/1040 [==============================] - 1s - loss: 0.5128 - acc: 0.0000e+00 - val_loss: 0.0232 - val_acc: 0.0000e+00
Epoch 210/500
1040/1040 [==============================] - 1s - loss: 0.4770 - acc: 0.0000e+00 - val_loss: 0.0283 - val_acc: 0.0000e+00
Epoch 211/500
1040/1040 [==============================] - 1s - loss: 0.5443 - acc: 0.0000e+00 - val_loss: 0.0619 - val_acc: 0.0000e+00
Epoch 212/500
1040/1040 [==============================] - 1s - loss: 0.4716 - acc: 0.0000e+00 - val_loss: 0.0277 - val_acc: 0.0000e+00
Epoch 213/500
1040/1040 [==============================] - 1s - loss: 0.4829 - acc: 0.0000e+00 - val_loss: 0.0213 - val_acc: 0.0000e+00
Epoch 214/500
1040/1040 [==============================] - 1s - loss: 0.4771 - acc: 0.0000e+00 - val_loss: 0.0424 - val_acc: 0.0000e+00
Epoch 215/500
1040/1040 [==============================] - 1s - loss: 0.5558 - acc: 0.0000e+00 - val_loss: 0.0210 - val_acc: 0.0000e+00
Epoch 216/500
1040/1040 [==============================] - 1s - loss: 0.5173 - acc: 0.0000e+00 - val_loss: 0.0800 - val_acc: 0.0000e+00
Epoch 217/500
1040/1040 [==============================] - 1s - loss: 0.5262 - acc: 0.0000e+00 - val_loss: 0.0315 - val_acc: 0.0000e+00
Epoch 218/500
1040/1040 [==============================] - 1s - loss: 0.5232 - acc: 0.0000e+00 - val_loss: 0.0258 - val_acc: 0.0000e+00
Epoch 219/500
1040/1040 [==============================] - 1s - loss: 0.5402 - acc: 0.0000e+00 - val_loss: 0.0208 - val_acc: 0.0000e+00
Epoch 220/500
1040/1040 [==============================] - 1s - loss: 0.4556 - acc: 0.0000e+00 - val_loss: 0.0184 - val_acc: 0.0000e+00
Epoch 221/500
1040/1040 [==============================] - 1s - loss: 0.4273 - acc: 0.0000e+00 - val_loss: 0.0152 - val_acc: 0.0000e+00
Epoch 222/500
1040/1040 [==============================] - 1s - loss: 0.4236 - acc: 0.0000e+00 - val_loss: 0.0519 - val_acc: 0.0000e+00
Epoch 223/500
1040/1040 [==============================] - 1s - loss: 0.4918 - acc: 0.0000e+00 - val_loss: 0.0309 - val_acc: 0.0000e+00
Epoch 224/500
1040/1040 [==============================] - 1s - loss: 0.5400 - acc: 0.0000e+00 - val_loss: 0.0165 - val_acc: 0.0000e+00
Epoch 225/500
1040/1040 [==============================] - 1s - loss: 0.4727 - acc: 0.0000e+00 - val_loss: 0.0332 - val_acc: 0.0000e+00
Epoch 226/500
1040/1040 [==============================] - 1s - loss: 0.4539 - acc: 0.0000e+00 - val_loss: 0.0132 - val_acc: 0.0000e+00
Epoch 227/500
1040/1040 [==============================] - 1s - loss: 0.4348 - acc: 0.0000e+00 - val_loss: 0.0133 - val_acc: 0.0000e+00
Epoch 228/500
1040/1040 [==============================] - 1s - loss: 0.4358 - acc: 0.0000e+00 - val_loss: 0.0136 - val_acc: 0.0000e+00
Epoch 229/500
1040/1040 [==============================] - 1s - loss: 0.4184 - acc: 0.0000e+00 - val_loss: 0.0291 - val_acc: 0.0000e+00
Epoch 230/500
1040/1040 [==============================] - 1s - loss: 0.4717 - acc: 0.0000e+00 - val_loss: 0.0282 - val_acc: 0.0000e+00
Epoch 231/500
1040/1040 [==============================] - 1s - loss: 0.4916 - acc: 0.0000e+00 - val_loss: 0.0630 - val_acc: 0.0000e+00
Epoch 232/500
1040/1040 [==============================] - 1s - loss: 0.4668 - acc: 0.0000e+00 - val_loss: 0.0223 - val_acc: 0.0000e+00
Epoch 233/500
1040/1040 [==============================] - 1s - loss: 0.4990 - acc: 0.0000e+00 - val_loss: 0.0135 - val_acc: 0.0000e+00
Epoch 234/500
1040/1040 [==============================] - 1s - loss: 0.4223 - acc: 0.0000e+00 - val_loss: 0.0471 - val_acc: 0.0000e+00
Epoch 235/500
1040/1040 [==============================] - 1s - loss: 0.5049 - acc: 0.0000e+00 - val_loss: 0.0384 - val_acc: 0.0000e+00
Epoch 236/500
1040/1040 [==============================] - 1s - loss: 0.4379 - acc: 0.0000e+00 - val_loss: 0.0318 - val_acc: 0.0000e+00
Epoch 237/500
1040/1040 [==============================] - 1s - loss: 0.4840 - acc: 0.0000e+00 - val_loss: 0.0166 - val_acc: 0.0000e+00
Epoch 238/500
1040/1040 [==============================] - 1s - loss: 0.4502 - acc: 0.0000e+00 - val_loss: 0.0193 - val_acc: 0.0000e+00
Epoch 239/500
1040/1040 [==============================] - 1s - loss: 0.4023 - acc: 0.0000e+00 - val_loss: 0.0453 - val_acc: 0.0000e+00
Epoch 240/500
1040/1040 [==============================] - 1s - loss: 0.4061 - acc: 0.0000e+00 - val_loss: 0.0187 - val_acc: 0.0000e+00
Epoch 241/500
1040/1040 [==============================] - 1s - loss: 0.4738 - acc: 0.0000e+00 - val_loss: 0.0323 - val_acc: 0.0000e+00
Epoch 242/500
1040/1040 [==============================] - 1s - loss: 0.4477 - acc: 0.0000e+00 - val_loss: 0.0188 - val_acc: 0.0000e+00
Epoch 243/500
1040/1040 [==============================] - 1s - loss: 0.4216 - acc: 0.0000e+00 - val_loss: 0.0716 - val_acc: 0.0000e+00
Epoch 244/500
1040/1040 [==============================] - 1s - loss: 0.4087 - acc: 0.0000e+00 - val_loss: 0.1536 - val_acc: 0.0000e+00
Epoch 245/500
1040/1040 [==============================] - 1s - loss: 0.5646 - acc: 0.0000e+00 - val_loss: 0.0274 - val_acc: 0.0000e+00
Epoch 246/500
1040/1040 [==============================] - 1s - loss: 0.4272 - acc: 0.0000e+00 - val_loss: 0.0348 - val_acc: 0.0000e+00
Epoch 247/500
1040/1040 [==============================] - 1s - loss: 0.4325 - acc: 0.0000e+00 - val_loss: 0.2315 - val_acc: 0.0000e+00
Epoch 248/500
1040/1040 [==============================] - 1s - loss: 0.5021 - acc: 0.0000e+00 - val_loss: 0.0381 - val_acc: 0.0000e+00
Epoch 249/500
1040/1040 [==============================] - 1s - loss: 0.3858 - acc: 0.0000e+00 - val_loss: 0.0247 - val_acc: 0.0000e+00
Epoch 250/500
1040/1040 [==============================] - 1s - loss: 0.4234 - acc: 0.0000e+00 - val_loss: 0.1792 - val_acc: 0.0000e+00
Epoch 251/500
1040/1040 [==============================] - 1s - loss: 0.5126 - acc: 0.0000e+00 - val_loss: 0.0151 - val_acc: 0.0000e+00
Epoch 252/500
1040/1040 [==============================] - 1s - loss: 0.4785 - acc: 0.0000e+00 - val_loss: 0.0876 - val_acc: 0.0000e+00
Epoch 253/500
1040/1040 [==============================] - 1s - loss: 0.4279 - acc: 0.0000e+00 - val_loss: 0.1910 - val_acc: 0.0000e+00
Epoch 254/500
1040/1040 [==============================] - 1s - loss: 0.4979 - acc: 0.0000e+00 - val_loss: 0.0295 - val_acc: 0.0000e+00
Epoch 255/500
1040/1040 [==============================] - 1s - loss: 0.4273 - acc: 0.0000e+00 - val_loss: 0.0566 - val_acc: 0.0000e+00
Epoch 256/500
1040/1040 [==============================] - 1s - loss: 0.3970 - acc: 0.0000e+00 - val_loss: 0.1441 - val_acc: 0.0000e+00
Epoch 257/500
1040/1040 [==============================] - 1s - loss: 0.5000 - acc: 0.0000e+00 - val_loss: 0.0254 - val_acc: 0.0000e+00
Epoch 258/500
1040/1040 [==============================] - 1s - loss: 0.3898 - acc: 0.0000e+00 - val_loss: 0.0565 - val_acc: 0.0000e+00
Epoch 259/500
1040/1040 [==============================] - 1s - loss: 0.4311 - acc: 0.0000e+00 - val_loss: 0.0366 - val_acc: 0.0000e+00
Epoch 260/500
1040/1040 [==============================] - 1s - loss: 0.4492 - acc: 0.0000e+00 - val_loss: 0.0599 - val_acc: 0.0000e+00
Epoch 261/500
1040/1040 [==============================] - 1s - loss: 0.4115 - acc: 0.0000e+00 - val_loss: 0.0307 - val_acc: 0.0000e+00
Epoch 262/500
1040/1040 [==============================] - 1s - loss: 0.4077 - acc: 0.0000e+00 - val_loss: 0.0258 - val_acc: 0.0000e+00
Epoch 263/500
1040/1040 [==============================] - 1s - loss: 0.3782 - acc: 0.0000e+00 - val_loss: 0.0980 - val_acc: 0.0000e+00
Epoch 264/500
1040/1040 [==============================] - 1s - loss: 0.4470 - acc: 0.0000e+00 - val_loss: 0.0167 - val_acc: 0.0000e+00
Epoch 265/500
1040/1040 [==============================] - 1s - loss: 0.3941 - acc: 0.0000e+00 - val_loss: 0.0417 - val_acc: 0.0000e+00
Epoch 266/500
1040/1040 [==============================] - 1s - loss: 0.4179 - acc: 0.0000e+00 - val_loss: 0.0637 - val_acc: 0.0000e+00
Epoch 267/500
1040/1040 [==============================] - 1s - loss: 0.4303 - acc: 0.0000e+00 - val_loss: 0.0132 - val_acc: 0.0000e+00
Epoch 268/500
1040/1040 [==============================] - 1s - loss: 0.3868 - acc: 0.0000e+00 - val_loss: 0.1667 - val_acc: 0.0000e+00
Epoch 269/500
1040/1040 [==============================] - 1s - loss: 0.4793 - acc: 0.0000e+00 - val_loss: 0.0141 - val_acc: 0.0000e+00
Epoch 270/500
1040/1040 [==============================] - 1s - loss: 0.3959 - acc: 0.0000e+00 - val_loss: 0.0138 - val_acc: 0.0000e+00
Epoch 271/500
1040/1040 [==============================] - 1s - loss: 0.3550 - acc: 0.0000e+00 - val_loss: 0.0771 - val_acc: 0.0000e+00
Epoch 272/500
1040/1040 [==============================] - 1s - loss: 0.4048 - acc: 0.0000e+00 - val_loss: 0.0132 - val_acc: 0.0000e+00
Epoch 273/500
1040/1040 [==============================] - 1s - loss: 0.3816 - acc: 0.0000e+00 - val_loss: 0.0145 - val_acc: 0.0000e+00
Epoch 274/500
1040/1040 [==============================] - 1s - loss: 0.3737 - acc: 0.0000e+00 - val_loss: 0.0735 - val_acc: 0.0000e+00
Epoch 275/500
1040/1040 [==============================] - 1s - loss: 0.4127 - acc: 0.0000e+00 - val_loss: 0.0757 - val_acc: 0.0000e+00
Epoch 276/500
1040/1040 [==============================] - 1s - loss: 0.3805 - acc: 0.0000e+00 - val_loss: 0.0214 - val_acc: 0.0000e+00
Epoch 277/500
1040/1040 [==============================] - 1s - loss: 0.3972 - acc: 0.0000e+00 - val_loss: 0.0283 - val_acc: 0.0000e+00
Epoch 278/500
1040/1040 [==============================] - 1s - loss: 0.3918 - acc: 0.0000e+00 - val_loss: 0.0847 - val_acc: 0.0000e+00
Epoch 279/500
1040/1040 [==============================] - 1s - loss: 0.3824 - acc: 0.0000e+00 - val_loss: 0.0243 - val_acc: 0.0000e+00
Epoch 280/500
1040/1040 [==============================] - 1s - loss: 0.3861 - acc: 0.0000e+00 - val_loss: 0.0122 - val_acc: 0.0000e+00
Epoch 281/500
1040/1040 [==============================] - 1s - loss: 0.3775 - acc: 0.0000e+00 - val_loss: 0.0348 - val_acc: 0.0000e+00
Epoch 282/500
1040/1040 [==============================] - 1s - loss: 0.3786 - acc: 0.0000e+00 - val_loss: 0.0148 - val_acc: 0.0000e+00
Epoch 283/500
1040/1040 [==============================] - 1s - loss: 0.3858 - acc: 0.0000e+00 - val_loss: 0.0282 - val_acc: 0.0000e+00
Epoch 284/500
1040/1040 [==============================] - 1s - loss: 0.3736 - acc: 0.0000e+00 - val_loss: 0.0326 - val_acc: 0.0000e+00
Epoch 285/500
1040/1040 [==============================] - 1s - loss: 0.3906 - acc: 0.0000e+00 - val_loss: 0.0236 - val_acc: 0.0000e+00
Epoch 286/500
1040/1040 [==============================] - 1s - loss: 0.3774 - acc: 0.0000e+00 - val_loss: 0.0204 - val_acc: 0.0000e+00
Epoch 287/500
1040/1040 [==============================] - 1s - loss: 0.3898 - acc: 0.0000e+00 - val_loss: 0.0169 - val_acc: 0.0000e+00
Epoch 288/500
1040/1040 [==============================] - 1s - loss: 0.3611 - acc: 0.0000e+00 - val_loss: 0.0113 - val_acc: 0.0000e+00
Epoch 289/500
1040/1040 [==============================] - 1s - loss: 0.3633 - acc: 0.0000e+00 - val_loss: 0.0324 - val_acc: 0.0000e+00
Epoch 290/500
1040/1040 [==============================] - 1s - loss: 0.3315 - acc: 0.0000e+00 - val_loss: 0.1114 - val_acc: 0.0000e+00
Epoch 291/500
1040/1040 [==============================] - 1s - loss: 0.3971 - acc: 0.0000e+00 - val_loss: 0.0257 - val_acc: 0.0000e+00
Epoch 292/500
1040/1040 [==============================] - 1s - loss: 0.3709 - acc: 0.0000e+00 - val_loss: 0.0122 - val_acc: 0.0000e+00
Epoch 293/500
1040/1040 [==============================] - 1s - loss: 0.3768 - acc: 0.0000e+00 - val_loss: 0.0846 - val_acc: 0.0000e+00
Epoch 294/500
1040/1040 [==============================] - 1s - loss: 0.3802 - acc: 0.0000e+00 - val_loss: 0.0318 - val_acc: 0.0000e+00
Epoch 295/500
1040/1040 [==============================] - 1s - loss: 0.3573 - acc: 0.0000e+00 - val_loss: 0.0287 - val_acc: 0.0000e+00
Epoch 296/500
1040/1040 [==============================] - 1s - loss: 0.3401 - acc: 0.0000e+00 - val_loss: 0.0246 - val_acc: 0.0000e+00
Epoch 297/500
1040/1040 [==============================] - 1s - loss: 0.3796 - acc: 0.0000e+00 - val_loss: 0.0125 - val_acc: 0.0000e+00
Epoch 298/500
1040/1040 [==============================] - 1s - loss: 0.3784 - acc: 0.0000e+00 - val_loss: 0.1532 - val_acc: 0.0000e+00
Epoch 299/500
1040/1040 [==============================] - 1s - loss: 0.4295 - acc: 0.0000e+00 - val_loss: 0.0157 - val_acc: 0.0000e+00
Epoch 300/500
1040/1040 [==============================] - 1s - loss: 0.3698 - acc: 0.0000e+00 - val_loss: 0.1062 - val_acc: 0.0000e+00
Epoch 301/500
1040/1040 [==============================] - 1s - loss: 0.4120 - acc: 0.0000e+00 - val_loss: 0.0817 - val_acc: 0.0000e+00
Epoch 302/500
1040/1040 [==============================] - 1s - loss: 0.4393 - acc: 0.0000e+00 - val_loss: 0.0173 - val_acc: 0.0000e+00
Epoch 303/500
1040/1040 [==============================] - 1s - loss: 0.3503 - acc: 0.0000e+00 - val_loss: 0.0697 - val_acc: 0.0000e+00
Epoch 304/500
1040/1040 [==============================] - 1s - loss: 0.3774 - acc: 0.0000e+00 - val_loss: 0.0466 - val_acc: 0.0000e+00
Epoch 305/500
1040/1040 [==============================] - 1s - loss: 0.3858 - acc: 0.0000e+00 - val_loss: 0.0121 - val_acc: 0.0000e+00
Epoch 306/500
1040/1040 [==============================] - 1s - loss: 0.3570 - acc: 0.0000e+00 - val_loss: 0.0272 - val_acc: 0.0000e+00
Epoch 307/500
1040/1040 [==============================] - 1s - loss: 0.3912 - acc: 0.0000e+00 - val_loss: 0.0260 - val_acc: 0.0000e+00
Epoch 308/500
1040/1040 [==============================] - 1s - loss: 0.3761 - acc: 0.0000e+00 - val_loss: 0.0604 - val_acc: 0.0000e+00
Epoch 309/500
1040/1040 [==============================] - 1s - loss: 0.3248 - acc: 0.0000e+00 - val_loss: 0.0630 - val_acc: 0.0000e+00
Epoch 310/500
1040/1040 [==============================] - 1s - loss: 0.3737 - acc: 0.0000e+00 - val_loss: 0.0285 - val_acc: 0.0000e+00
Epoch 311/500
1040/1040 [==============================] - 1s - loss: 0.3704 - acc: 0.0000e+00 - val_loss: 0.0495 - val_acc: 0.0000e+00
Epoch 312/500
1040/1040 [==============================] - 1s - loss: 0.4269 - acc: 0.0000e+00 - val_loss: 0.0220 - val_acc: 0.0000e+00
Epoch 313/500
1040/1040 [==============================] - 1s - loss: 0.3917 - acc: 0.0000e+00 - val_loss: 0.1790 - val_acc: 0.0000e+00
Epoch 314/500
1040/1040 [==============================] - 1s - loss: 0.4140 - acc: 0.0000e+00 - val_loss: 0.1007 - val_acc: 0.0000e+00
Epoch 315/500
1040/1040 [==============================] - 1s - loss: 0.4460 - acc: 0.0000e+00 - val_loss: 0.1054 - val_acc: 0.0000e+00
Epoch 316/500
1040/1040 [==============================] - 1s - loss: 0.3785 - acc: 0.0000e+00 - val_loss: 0.0919 - val_acc: 0.0000e+00
Epoch 317/500
1040/1040 [==============================] - 1s - loss: 0.3924 - acc: 0.0000e+00 - val_loss: 0.0165 - val_acc: 0.0000e+00
Epoch 318/500
1040/1040 [==============================] - 1s - loss: 0.3612 - acc: 0.0000e+00 - val_loss: 0.0455 - val_acc: 0.0000e+00
Epoch 319/500
1040/1040 [==============================] - 1s - loss: 0.3705 - acc: 0.0000e+00 - val_loss: 0.1007 - val_acc: 0.0000e+00
Epoch 320/500
1040/1040 [==============================] - 1s - loss: 0.3795 - acc: 0.0000e+00 - val_loss: 0.0780 - val_acc: 0.0000e+00
Epoch 321/500
1040/1040 [==============================] - 1s - loss: 0.3541 - acc: 0.0000e+00 - val_loss: 0.0116 - val_acc: 0.0000e+00
Epoch 322/500
1040/1040 [==============================] - 1s - loss: 0.3829 - acc: 0.0000e+00 - val_loss: 0.0541 - val_acc: 0.0000e+00
Epoch 323/500
1040/1040 [==============================] - 1s - loss: 0.3870 - acc: 0.0000e+00 - val_loss: 0.0411 - val_acc: 0.0000e+00
Epoch 324/500
1040/1040 [==============================] - 1s - loss: 0.3437 - acc: 0.0000e+00 - val_loss: 0.0209 - val_acc: 0.0000e+00
Epoch 325/500
1040/1040 [==============================] - 1s - loss: 0.3555 - acc: 0.0000e+00 - val_loss: 0.0115 - val_acc: 0.0000e+00
Epoch 326/500
1040/1040 [==============================] - 1s - loss: 0.3366 - acc: 0.0000e+00 - val_loss: 0.0122 - val_acc: 0.0000e+00
Epoch 327/500
1040/1040 [==============================] - 1s - loss: 0.3435 - acc: 0.0000e+00 - val_loss: 0.0133 - val_acc: 0.0000e+00
Epoch 328/500
1040/1040 [==============================] - 1s - loss: 0.3486 - acc: 0.0000e+00 - val_loss: 0.0166 - val_acc: 0.0000e+00
Epoch 329/500
1040/1040 [==============================] - 1s - loss: 0.3432 - acc: 0.0000e+00 - val_loss: 0.0138 - val_acc: 0.0000e+00
Epoch 330/500
1040/1040 [==============================] - 1s - loss: 0.3722 - acc: 0.0000e+00 - val_loss: 0.0279 - val_acc: 0.0000e+00
Epoch 331/500
1040/1040 [==============================] - 1s - loss: 0.3406 - acc: 0.0000e+00 - val_loss: 0.0176 - val_acc: 0.0000e+00
Epoch 332/500
1040/1040 [==============================] - 1s - loss: 0.3617 - acc: 0.0000e+00 - val_loss: 0.0245 - val_acc: 0.0000e+00
Epoch 333/500
1040/1040 [==============================] - 1s - loss: 0.3414 - acc: 0.0000e+00 - val_loss: 0.0672 - val_acc: 0.0000e+00
Epoch 334/500
1040/1040 [==============================] - 1s - loss: 0.3958 - acc: 0.0000e+00 - val_loss: 0.0135 - val_acc: 0.0000e+00
Epoch 335/500
1040/1040 [==============================] - 1s - loss: 0.3535 - acc: 0.0000e+00 - val_loss: 0.0338 - val_acc: 0.0000e+00
Epoch 336/500
1040/1040 [==============================] - 1s - loss: 0.3385 - acc: 0.0000e+00 - val_loss: 0.0110 - val_acc: 0.0000e+00
Epoch 337/500
1040/1040 [==============================] - 1s - loss: 0.3641 - acc: 0.0000e+00 - val_loss: 0.0127 - val_acc: 0.0000e+00
Epoch 338/500
1040/1040 [==============================] - 1s - loss: 0.3180 - acc: 0.0000e+00 - val_loss: 0.0285 - val_acc: 0.0000e+00
Epoch 339/500
1040/1040 [==============================] - 1s - loss: 0.3562 - acc: 0.0000e+00 - val_loss: 0.0113 - val_acc: 0.0000e+00
Epoch 340/500
1040/1040 [==============================] - 1s - loss: 0.3218 - acc: 0.0000e+00 - val_loss: 0.0219 - val_acc: 0.0000e+00
Epoch 341/500
1040/1040 [==============================] - 1s - loss: 0.3346 - acc: 0.0000e+00 - val_loss: 0.0112 - val_acc: 0.0000e+00
Epoch 342/500
1040/1040 [==============================] - 1s - loss: 0.3131 - acc: 0.0000e+00 - val_loss: 0.0226 - val_acc: 0.0000e+00
Epoch 343/500
1040/1040 [==============================] - 1s - loss: 0.3375 - acc: 0.0000e+00 - val_loss: 0.0405 - val_acc: 0.0000e+00
Epoch 344/500
1040/1040 [==============================] - 1s - loss: 0.3420 - acc: 0.0000e+00 - val_loss: 0.0110 - val_acc: 0.0000e+00
Epoch 345/500
1040/1040 [==============================] - 1s - loss: 0.3565 - acc: 0.0000e+00 - val_loss: 0.0169 - val_acc: 0.0000e+00
Epoch 346/500
1040/1040 [==============================] - 1s - loss: 0.3292 - acc: 0.0000e+00 - val_loss: 0.0216 - val_acc: 0.0000e+00
Epoch 347/500
1040/1040 [==============================] - 1s - loss: 0.3548 - acc: 0.0000e+00 - val_loss: 0.0195 - val_acc: 0.0000e+00
Epoch 348/500
1040/1040 [==============================] - 1s - loss: 0.3339 - acc: 0.0000e+00 - val_loss: 0.0104 - val_acc: 0.0000e+00
Epoch 349/500
1040/1040 [==============================] - 1s - loss: 0.3387 - acc: 0.0000e+00 - val_loss: 0.0116 - val_acc: 0.0000e+00
Epoch 350/500
1040/1040 [==============================] - 1s - loss: 0.3561 - acc: 0.0000e+00 - val_loss: 0.0373 - val_acc: 0.0000e+00
Epoch 351/500
1040/1040 [==============================] - 1s - loss: 0.3652 - acc: 0.0000e+00 - val_loss: 0.0151 - val_acc: 0.0000e+00
Epoch 352/500
1040/1040 [==============================] - 1s - loss: 0.3210 - acc: 0.0000e+00 - val_loss: 0.0190 - val_acc: 0.0000e+00
Epoch 353/500
1040/1040 [==============================] - 1s - loss: 0.3010 - acc: 0.0000e+00 - val_loss: 0.0162 - val_acc: 0.0000e+00
Epoch 354/500
1040/1040 [==============================] - 1s - loss: 0.3596 - acc: 0.0000e+00 - val_loss: 0.0137 - val_acc: 0.0000e+00
Epoch 355/500
1040/1040 [==============================] - 1s - loss: 0.2976 - acc: 0.0000e+00 - val_loss: 0.0433 - val_acc: 0.0000e+00
Epoch 356/500
1040/1040 [==============================] - 1s - loss: 0.3999 - acc: 0.0000e+00 - val_loss: 0.0303 - val_acc: 0.0000e+00
Epoch 357/500
1040/1040 [==============================] - 1s - loss: 0.3322 - acc: 0.0000e+00 - val_loss: 0.0942 - val_acc: 0.0000e+00
Epoch 358/500
1040/1040 [==============================] - 1s - loss: 0.4144 - acc: 0.0000e+00 - val_loss: 0.0176 - val_acc: 0.0000e+00
Epoch 359/500
1040/1040 [==============================] - 1s - loss: 0.3428 - acc: 0.0000e+00 - val_loss: 0.0121 - val_acc: 0.0000e+00
Epoch 360/500
1040/1040 [==============================] - 1s - loss: 0.3280 - acc: 0.0000e+00 - val_loss: 0.0583 - val_acc: 0.0000e+00
Epoch 361/500
1040/1040 [==============================] - 1s - loss: 0.3479 - acc: 0.0000e+00 - val_loss: 0.0237 - val_acc: 0.0000e+00
Epoch 362/500
1040/1040 [==============================] - 1s - loss: 0.3641 - acc: 0.0000e+00 - val_loss: 0.0577 - val_acc: 0.0000e+00
Epoch 363/500
1040/1040 [==============================] - 1s - loss: 0.3046 - acc: 0.0000e+00 - val_loss: 0.0228 - val_acc: 0.0000e+00
Epoch 364/500
1040/1040 [==============================] - 1s - loss: 0.3915 - acc: 0.0000e+00 - val_loss: 0.0122 - val_acc: 0.0000e+00
Epoch 365/500
1040/1040 [==============================] - 1s - loss: 0.3508 - acc: 0.0000e+00 - val_loss: 0.0663 - val_acc: 0.0000e+00
Epoch 366/500
1040/1040 [==============================] - 1s - loss: 0.3578 - acc: 0.0000e+00 - val_loss: 0.0154 - val_acc: 0.0000e+00
Epoch 367/500
1040/1040 [==============================] - 1s - loss: 0.3101 - acc: 0.0000e+00 - val_loss: 0.0177 - val_acc: 0.0000e+00
Epoch 368/500
1040/1040 [==============================] - 1s - loss: 0.3253 - acc: 0.0000e+00 - val_loss: 0.0107 - val_acc: 0.0000e+00
Epoch 369/500
1040/1040 [==============================] - 1s - loss: 0.3209 - acc: 0.0000e+00 - val_loss: 0.0124 - val_acc: 0.0000e+00
Epoch 370/500
1040/1040 [==============================] - 1s - loss: 0.3070 - acc: 0.0000e+00 - val_loss: 0.0165 - val_acc: 0.0000e+00
Epoch 371/500
1040/1040 [==============================] - 1s - loss: 0.3072 - acc: 0.0000e+00 - val_loss: 0.0102 - val_acc: 0.0000e+00
Epoch 372/500
1040/1040 [==============================] - 1s - loss: 0.3462 - acc: 0.0000e+00 - val_loss: 0.0278 - val_acc: 0.0000e+00
Epoch 373/500
1040/1040 [==============================] - 1s - loss: 0.3435 - acc: 0.0000e+00 - val_loss: 0.0196 - val_acc: 0.0000e+00
Epoch 374/500
1040/1040 [==============================] - 1s - loss: 0.3410 - acc: 0.0000e+00 - val_loss: 0.0286 - val_acc: 0.0000e+00
Epoch 375/500
1040/1040 [==============================] - 1s - loss: 0.3315 - acc: 0.0000e+00 - val_loss: 0.0210 - val_acc: 0.0000e+00
Epoch 376/500
1040/1040 [==============================] - 1s - loss: 0.3465 - acc: 0.0000e+00 - val_loss: 0.0130 - val_acc: 0.0000e+00
Epoch 377/500
1040/1040 [==============================] - 1s - loss: 0.3356 - acc: 0.0000e+00 - val_loss: 0.0107 - val_acc: 0.0000e+00
Epoch 378/500
1040/1040 [==============================] - 1s - loss: 0.3581 - acc: 0.0000e+00 - val_loss: 0.0132 - val_acc: 0.0000e+00
Epoch 379/500
1040/1040 [==============================] - 1s - loss: 0.3707 - acc: 0.0000e+00 - val_loss: 0.0121 - val_acc: 0.0000e+00
Epoch 380/500
1040/1040 [==============================] - 1s - loss: 0.3130 - acc: 0.0000e+00 - val_loss: 0.0138 - val_acc: 0.0000e+00
Epoch 381/500
1040/1040 [==============================] - 1s - loss: 0.3167 - acc: 0.0000e+00 - val_loss: 0.0095 - val_acc: 0.0000e+00
Epoch 382/500
1040/1040 [==============================] - 1s - loss: 0.3206 - acc: 0.0000e+00 - val_loss: 0.0122 - val_acc: 0.0000e+00
Epoch 383/500
1040/1040 [==============================] - 1s - loss: 0.3068 - acc: 0.0000e+00 - val_loss: 0.0287 - val_acc: 0.0000e+00
Epoch 384/500
1040/1040 [==============================] - 1s - loss: 0.3427 - acc: 0.0000e+00 - val_loss: 0.0210 - val_acc: 0.0000e+00
Epoch 385/500
1040/1040 [==============================] - 1s - loss: 0.3083 - acc: 0.0000e+00 - val_loss: 0.0098 - val_acc: 0.0000e+00
Epoch 386/500
1040/1040 [==============================] - 1s - loss: 0.3243 - acc: 0.0000e+00 - val_loss: 0.0089 - val_acc: 0.0000e+00
Epoch 387/500
1040/1040 [==============================] - 1s - loss: 0.3297 - acc: 0.0000e+00 - val_loss: 0.0088 - val_acc: 0.0000e+00
Epoch 388/500
1040/1040 [==============================] - 1s - loss: 0.3038 - acc: 0.0000e+00 - val_loss: 0.0164 - val_acc: 0.0000e+00
Epoch 389/500
1040/1040 [==============================] - 1s - loss: 0.3298 - acc: 0.0000e+00 - val_loss: 0.0097 - val_acc: 0.0000e+00
Epoch 390/500
1040/1040 [==============================] - 1s - loss: 0.3395 - acc: 0.0000e+00 - val_loss: 0.0088 - val_acc: 0.0000e+00
Epoch 391/500
1040/1040 [==============================] - 1s - loss: 0.3270 - acc: 0.0000e+00 - val_loss: 0.0317 - val_acc: 0.0000e+00
Epoch 392/500
1040/1040 [==============================] - 1s - loss: 0.3229 - acc: 0.0000e+00 - val_loss: 0.0564 - val_acc: 0.0000e+00
Epoch 393/500
1040/1040 [==============================] - 1s - loss: 0.3199 - acc: 0.0000e+00 - val_loss: 0.0307 - val_acc: 0.0000e+00
Epoch 394/500
1040/1040 [==============================] - 1s - loss: 0.3401 - acc: 0.0000e+00 - val_loss: 0.0117 - val_acc: 0.0000e+00
Epoch 395/500
1040/1040 [==============================] - 1s - loss: 0.2874 - acc: 0.0000e+00 - val_loss: 0.0134 - val_acc: 0.0000e+00
Epoch 396/500
1040/1040 [==============================] - 1s - loss: 0.3475 - acc: 0.0000e+00 - val_loss: 0.0271 - val_acc: 0.0000e+00
Epoch 397/500
1040/1040 [==============================] - 1s - loss: 0.3301 - acc: 0.0000e+00 - val_loss: 0.0135 - val_acc: 0.0000e+00
Epoch 398/500
1040/1040 [==============================] - 1s - loss: 0.3513 - acc: 0.0000e+00 - val_loss: 0.0088 - val_acc: 0.0000e+00
Epoch 399/500
1040/1040 [==============================] - 1s - loss: 0.3395 - acc: 0.0000e+00 - val_loss: 0.0358 - val_acc: 0.0000e+00
Epoch 400/500
1040/1040 [==============================] - 1s - loss: 0.3420 - acc: 0.0000e+00 - val_loss: 0.0253 - val_acc: 0.0000e+00
Epoch 401/500
1040/1040 [==============================] - 1s - loss: 0.3374 - acc: 0.0000e+00 - val_loss: 0.0090 - val_acc: 0.0000e+00
Epoch 402/500
1040/1040 [==============================] - 1s - loss: 0.2999 - acc: 0.0000e+00 - val_loss: 0.0286 - val_acc: 0.0000e+00
Epoch 403/500
1040/1040 [==============================] - 1s - loss: 0.3461 - acc: 0.0000e+00 - val_loss: 0.0089 - val_acc: 0.0000e+00
Epoch 404/500
1040/1040 [==============================] - 1s - loss: 0.3123 - acc: 0.0000e+00 - val_loss: 0.0094 - val_acc: 0.0000e+00
Epoch 405/500
1040/1040 [==============================] - 1s - loss: 0.3244 - acc: 0.0000e+00 - val_loss: 0.0108 - val_acc: 0.0000e+00
Epoch 406/500
1040/1040 [==============================] - 1s - loss: 0.3037 - acc: 0.0000e+00 - val_loss: 0.0127 - val_acc: 0.0000e+00
Epoch 407/500
1040/1040 [==============================] - 1s - loss: 0.3169 - acc: 0.0000e+00 - val_loss: 0.0401 - val_acc: 0.0000e+00
Epoch 408/500
1040/1040 [==============================] - 1s - loss: 0.3714 - acc: 0.0000e+00 - val_loss: 0.0099 - val_acc: 0.0000e+00
Epoch 409/500
1040/1040 [==============================] - 1s - loss: 0.3140 - acc: 0.0000e+00 - val_loss: 0.0514 - val_acc: 0.0000e+00
Epoch 410/500
1040/1040 [==============================] - 1s - loss: 0.3042 - acc: 0.0000e+00 - val_loss: 0.0125 - val_acc: 0.0000e+00
Epoch 411/500
1040/1040 [==============================] - 1s - loss: 0.3262 - acc: 0.0000e+00 - val_loss: 0.0118 - val_acc: 0.0000e+00
Epoch 412/500
1040/1040 [==============================] - 1s - loss: 0.2931 - acc: 0.0000e+00 - val_loss: 0.0692 - val_acc: 0.0000e+00
Epoch 413/500
1040/1040 [==============================] - 1s - loss: 0.3391 - acc: 0.0000e+00 - val_loss: 0.0089 - val_acc: 0.0000e+00
Epoch 414/500
1040/1040 [==============================] - 1s - loss: 0.2986 - acc: 0.0000e+00 - val_loss: 0.0176 - val_acc: 0.0000e+00
Epoch 415/500
1040/1040 [==============================] - 1s - loss: 0.3505 - acc: 0.0000e+00 - val_loss: 0.0173 - val_acc: 0.0000e+00
Epoch 416/500
1040/1040 [==============================] - 1s - loss: 0.3262 - acc: 0.0000e+00 - val_loss: 0.0172 - val_acc: 0.0000e+00
Epoch 417/500
1040/1040 [==============================] - 1s - loss: 0.3280 - acc: 0.0000e+00 - val_loss: 0.0230 - val_acc: 0.0000e+00
Epoch 418/500
1040/1040 [==============================] - 1s - loss: 0.3284 - acc: 0.0000e+00 - val_loss: 0.0197 - val_acc: 0.0000e+00
Epoch 419/500
1040/1040 [==============================] - 1s - loss: 0.3327 - acc: 0.0000e+00 - val_loss: 0.0159 - val_acc: 0.0000e+00
Epoch 420/500
1040/1040 [==============================] - 1s - loss: 0.3197 - acc: 0.0000e+00 - val_loss: 0.0129 - val_acc: 0.0000e+00
Epoch 421/500
1040/1040 [==============================] - 1s - loss: 0.3385 - acc: 0.0000e+00 - val_loss: 0.0171 - val_acc: 0.0000e+00
Epoch 422/500
1040/1040 [==============================] - 1s - loss: 0.3065 - acc: 0.0000e+00 - val_loss: 0.0798 - val_acc: 0.0000e+00
Epoch 423/500
1040/1040 [==============================] - 1s - loss: 0.3664 - acc: 0.0000e+00 - val_loss: 0.0109 - val_acc: 0.0000e+00
Epoch 424/500
1040/1040 [==============================] - 1s - loss: 0.3714 - acc: 0.0000e+00 - val_loss: 0.0345 - val_acc: 0.0000e+00
Epoch 425/500
1040/1040 [==============================] - 1s - loss: 0.3262 - acc: 0.0000e+00 - val_loss: 0.0550 - val_acc: 0.0000e+00
Epoch 426/500
1040/1040 [==============================] - 1s - loss: 0.3442 - acc: 0.0000e+00 - val_loss: 0.0144 - val_acc: 0.0000e+00
Epoch 427/500
1040/1040 [==============================] - 1s - loss: 0.3373 - acc: 0.0000e+00 - val_loss: 0.0446 - val_acc: 0.0000e+00
Epoch 428/500
1040/1040 [==============================] - 1s - loss: 0.3355 - acc: 0.0000e+00 - val_loss: 0.0304 - val_acc: 0.0000e+00
Epoch 429/500
1040/1040 [==============================] - 1s - loss: 0.3205 - acc: 0.0000e+00 - val_loss: 0.0156 - val_acc: 0.0000e+00
Epoch 430/500
1040/1040 [==============================] - 1s - loss: 0.3331 - acc: 0.0000e+00 - val_loss: 0.0424 - val_acc: 0.0000e+00
Epoch 431/500
1040/1040 [==============================] - 1s - loss: 0.3237 - acc: 0.0000e+00 - val_loss: 0.0088 - val_acc: 0.0000e+00
Epoch 432/500
1040/1040 [==============================] - 1s - loss: 0.3039 - acc: 0.0000e+00 - val_loss: 0.0092 - val_acc: 0.0000e+00
Epoch 433/500
1040/1040 [==============================] - 1s - loss: 0.3279 - acc: 0.0000e+00 - val_loss: 0.0400 - val_acc: 0.0000e+00
Epoch 434/500
1040/1040 [==============================] - 1s - loss: 0.3155 - acc: 0.0000e+00 - val_loss: 0.0096 - val_acc: 0.0000e+00
Epoch 435/500
1040/1040 [==============================] - 1s - loss: 0.2865 - acc: 0.0000e+00 - val_loss: 0.0097 - val_acc: 0.0000e+00
Epoch 436/500
1040/1040 [==============================] - 1s - loss: 0.3072 - acc: 0.0000e+00 - val_loss: 0.0209 - val_acc: 0.0000e+00
Epoch 437/500
1040/1040 [==============================] - 1s - loss: 0.3061 - acc: 0.0000e+00 - val_loss: 0.0102 - val_acc: 0.0000e+00
Epoch 438/500
1040/1040 [==============================] - 1s - loss: 0.3040 - acc: 0.0000e+00 - val_loss: 0.0112 - val_acc: 0.0000e+00
Epoch 439/500
1040/1040 [==============================] - 1s - loss: 0.3080 - acc: 0.0000e+00 - val_loss: 0.0088 - val_acc: 0.0000e+00
Epoch 440/500
1040/1040 [==============================] - 1s - loss: 0.3283 - acc: 0.0000e+00 - val_loss: 0.0338 - val_acc: 0.0000e+00
Epoch 441/500
1040/1040 [==============================] - 1s - loss: 0.3279 - acc: 0.0000e+00 - val_loss: 0.0228 - val_acc: 0.0000e+00
Epoch 442/500
1040/1040 [==============================] - 1s - loss: 0.3395 - acc: 0.0000e+00 - val_loss: 0.0343 - val_acc: 0.0000e+00
Epoch 443/500
1040/1040 [==============================] - 1s - loss: 0.3327 - acc: 0.0000e+00 - val_loss: 0.0502 - val_acc: 0.0000e+00
Epoch 444/500
1040/1040 [==============================] - 1s - loss: 0.3406 - acc: 0.0000e+00 - val_loss: 0.0166 - val_acc: 0.0000e+00
Epoch 445/500
1040/1040 [==============================] - 1s - loss: 0.3062 - acc: 0.0000e+00 - val_loss: 0.0175 - val_acc: 0.0000e+00
Epoch 446/500
1040/1040 [==============================] - 1s - loss: 0.3060 - acc: 0.0000e+00 - val_loss: 0.0763 - val_acc: 0.0000e+00
Epoch 447/500
1040/1040 [==============================] - 1s - loss: 0.3036 - acc: 0.0000e+00 - val_loss: 0.0361 - val_acc: 0.0000e+00
Epoch 448/500
1040/1040 [==============================] - 1s - loss: 0.3058 - acc: 0.0000e+00 - val_loss: 0.0100 - val_acc: 0.0000e+00
Epoch 449/500
1040/1040 [==============================] - 1s - loss: 0.2939 - acc: 0.0000e+00 - val_loss: 0.0126 - val_acc: 0.0000e+00
Epoch 450/500
1040/1040 [==============================] - 1s - loss: 0.2805 - acc: 0.0000e+00 - val_loss: 0.0268 - val_acc: 0.0000e+00
Epoch 451/500
1040/1040 [==============================] - 1s - loss: 0.3075 - acc: 0.0000e+00 - val_loss: 0.0361 - val_acc: 0.0000e+00
Epoch 452/500
1040/1040 [==============================] - 1s - loss: 0.3156 - acc: 0.0000e+00 - val_loss: 0.0141 - val_acc: 0.0000e+00
Epoch 453/500
1040/1040 [==============================] - 1s - loss: 0.3166 - acc: 0.0000e+00 - val_loss: 0.0094 - val_acc: 0.0000e+00
Epoch 454/500
1040/1040 [==============================] - 1s - loss: 0.3335 - acc: 0.0000e+00 - val_loss: 0.0238 - val_acc: 0.0000e+00
Epoch 455/500
1040/1040 [==============================] - 1s - loss: 0.3651 - acc: 0.0000e+00 - val_loss: 0.0676 - val_acc: 0.0000e+00
Epoch 456/500
1040/1040 [==============================] - 1s - loss: 0.3248 - acc: 0.0000e+00 - val_loss: 0.0145 - val_acc: 0.0000e+00
Epoch 457/500
1040/1040 [==============================] - 1s - loss: 0.2964 - acc: 0.0000e+00 - val_loss: 0.0099 - val_acc: 0.0000e+00
Epoch 458/500
1040/1040 [==============================] - 1s - loss: 0.3210 - acc: 0.0000e+00 - val_loss: 0.0119 - val_acc: 0.0000e+00
Epoch 459/500
1040/1040 [==============================] - 1s - loss: 0.2904 - acc: 0.0000e+00 - val_loss: 0.0250 - val_acc: 0.0000e+00
Epoch 460/500
1040/1040 [==============================] - 1s - loss: 0.3076 - acc: 0.0000e+00 - val_loss: 0.0475 - val_acc: 0.0000e+00
Epoch 461/500
1040/1040 [==============================] - 1s - loss: 0.3356 - acc: 0.0000e+00 - val_loss: 0.0106 - val_acc: 0.0000e+00
Epoch 462/500
1040/1040 [==============================] - 1s - loss: 0.3439 - acc: 0.0000e+00 - val_loss: 0.0093 - val_acc: 0.0000e+00
Epoch 463/500
1040/1040 [==============================] - 1s - loss: 0.3096 - acc: 0.0000e+00 - val_loss: 0.0439 - val_acc: 0.0000e+00
Epoch 464/500
1040/1040 [==============================] - 1s - loss: 0.3107 - acc: 0.0000e+00 - val_loss: 0.0298 - val_acc: 0.0000e+00
Epoch 465/500
1040/1040 [==============================] - 1s - loss: 0.3324 - acc: 0.0000e+00 - val_loss: 0.0707 - val_acc: 0.0000e+00
Epoch 466/500
1040/1040 [==============================] - 1s - loss: 0.3158 - acc: 0.0000e+00 - val_loss: 0.0777 - val_acc: 0.0000e+00
Epoch 467/500
1040/1040 [==============================] - 1s - loss: 0.3750 - acc: 0.0000e+00 - val_loss: 0.0645 - val_acc: 0.0000e+00
Epoch 468/500
1040/1040 [==============================] - 1s - loss: 0.3038 - acc: 0.0000e+00 - val_loss: 0.0669 - val_acc: 0.0000e+00
Epoch 469/500
1040/1040 [==============================] - 1s - loss: 0.3496 - acc: 0.0000e+00 - val_loss: 0.0466 - val_acc: 0.0000e+00
Epoch 470/500
1040/1040 [==============================] - 1s - loss: 0.3238 - acc: 0.0000e+00 - val_loss: 0.0213 - val_acc: 0.0000e+00
Epoch 471/500
1040/1040 [==============================] - 1s - loss: 0.3007 - acc: 0.0000e+00 - val_loss: 0.0110 - val_acc: 0.0000e+00
Epoch 472/500
1040/1040 [==============================] - 1s - loss: 0.2967 - acc: 0.0000e+00 - val_loss: 0.0203 - val_acc: 0.0000e+00
Epoch 473/500
1040/1040 [==============================] - 1s - loss: 0.2912 - acc: 0.0000e+00 - val_loss: 0.0085 - val_acc: 0.0000e+00
Epoch 474/500
1040/1040 [==============================] - 1s - loss: 0.3077 - acc: 0.0000e+00 - val_loss: 0.0083 - val_acc: 0.0000e+00
Epoch 475/500
1040/1040 [==============================] - 1s - loss: 0.2618 - acc: 0.0000e+00 - val_loss: 0.0085 - val_acc: 0.0000e+00
Epoch 476/500
1040/1040 [==============================] - 1s - loss: 0.3113 - acc: 0.0000e+00 - val_loss: 0.0084 - val_acc: 0.0000e+00
Epoch 477/500
1040/1040 [==============================] - 1s - loss: 0.3184 - acc: 0.0000e+00 - val_loss: 0.0125 - val_acc: 0.0000e+00
Epoch 478/500
1040/1040 [==============================] - 1s - loss: 0.3051 - acc: 0.0000e+00 - val_loss: 0.0268 - val_acc: 0.0000e+00
Epoch 479/500
1040/1040 [==============================] - 1s - loss: 0.3306 - acc: 0.0000e+00 - val_loss: 0.0175 - val_acc: 0.0000e+00
Epoch 480/500
1040/1040 [==============================] - 1s - loss: 0.2893 - acc: 0.0000e+00 - val_loss: 0.0107 - val_acc: 0.0000e+00
Epoch 481/500
1040/1040 [==============================] - 1s - loss: 0.2817 - acc: 0.0000e+00 - val_loss: 0.0077 - val_acc: 0.0000e+00
Epoch 482/500
1040/1040 [==============================] - 1s - loss: 0.3207 - acc: 0.0000e+00 - val_loss: 0.0082 - val_acc: 0.0000e+00
Epoch 483/500
1040/1040 [==============================] - 1s - loss: 0.2718 - acc: 0.0000e+00 - val_loss: 0.0086 - val_acc: 0.0000e+00
Epoch 484/500
1040/1040 [==============================] - 1s - loss: 0.3274 - acc: 0.0000e+00 - val_loss: 0.0107 - val_acc: 0.0000e+00
Epoch 485/500
1040/1040 [==============================] - 1s - loss: 0.2952 - acc: 0.0000e+00 - val_loss: 0.0473 - val_acc: 0.0000e+00
Epoch 486/500
1040/1040 [==============================] - 1s - loss: 0.3365 - acc: 0.0000e+00 - val_loss: 0.0083 - val_acc: 0.0000e+00
Epoch 487/500
1040/1040 [==============================] - 1s - loss: 0.2981 - acc: 0.0000e+00 - val_loss: 0.0214 - val_acc: 0.0000e+00
Epoch 488/500
1040/1040 [==============================] - 1s - loss: 0.3247 - acc: 0.0000e+00 - val_loss: 0.0778 - val_acc: 0.0000e+00
Epoch 489/500
1040/1040 [==============================] - 1s - loss: 0.3423 - acc: 0.0000e+00 - val_loss: 0.0087 - val_acc: 0.0000e+00
Epoch 490/500
1040/1040 [==============================] - 1s - loss: 0.3333 - acc: 0.0000e+00 - val_loss: 0.0702 - val_acc: 0.0000e+00
Epoch 491/500
1040/1040 [==============================] - 1s - loss: 0.3587 - acc: 0.0000e+00 - val_loss: 0.0267 - val_acc: 0.0000e+00
Epoch 492/500
1040/1040 [==============================] - 1s - loss: 0.3091 - acc: 0.0000e+00 - val_loss: 0.0083 - val_acc: 0.0000e+00
Epoch 493/500
1040/1040 [==============================] - 1s - loss: 0.3184 - acc: 0.0000e+00 - val_loss: 0.0509 - val_acc: 0.0000e+00
Epoch 494/500
1040/1040 [==============================] - 1s - loss: 0.3087 - acc: 0.0000e+00 - val_loss: 0.0175 - val_acc: 0.0000e+00
Epoch 495/500
1040/1040 [==============================] - 1s - loss: 0.3379 - acc: 0.0000e+00 - val_loss: 0.0298 - val_acc: 0.0000e+00
Epoch 496/500
1040/1040 [==============================] - 1s - loss: 0.3050 - acc: 0.0000e+00 - val_loss: 0.0207 - val_acc: 0.0000e+00
Epoch 497/500
1040/1040 [==============================] - 1s - loss: 0.3310 - acc: 0.0000e+00 - val_loss: 0.0097 - val_acc: 0.0000e+00
Epoch 498/500
1040/1040 [==============================] - 1s - loss: 0.3109 - acc: 0.0000e+00 - val_loss: 0.0498 - val_acc: 0.0000e+00
Epoch 499/500
1040/1040 [==============================] - 1s - loss: 0.3174 - acc: 0.0000e+00 - val_loss: 0.0315 - val_acc: 0.0000e+00
Epoch 500/500
1040/1040 [==============================] - 1s - loss: 0.3567 - acc: 0.0000e+00 - val_loss: 0.0408 - val_acc: 0.0000e+00
Out[22]:
<keras.callbacks.History at 0x1ce0edb3860>
In [23]:
trainScore = model.evaluate(X_train, y_train, verbose=0)
print('Train Score: %.2f MSE (%.2f RMSE)' % (trainScore[0], math.sqrt(trainScore[0])))

testScore = model.evaluate(X_test, y_test, verbose=0)
print('Test Score: %.2f MSE (%.2f RMSE)' % (testScore[0], math.sqrt(testScore[0])))
Train Score: 0.08 MSE (0.29 RMSE)
Test Score: 0.04 MSE (0.20 RMSE)
In [24]:
# print(X_test[-1])
diff=[]
ratio=[]
p = model.predict(X_test)
for u in range(len(y_test)):
    pr = p[u][0]
    ratio.append((y_test[u]/pr)-1)
    diff.append(abs(y_test[u]- pr))
    #print(u, y_test[u], pr, (y_test[u]/pr)-1, abs(y_test[u]- pr))

Predictions vs Real results

In [25]:
import matplotlib.pyplot as plt2

plt2.plot(p,color='red', label='prediction')
plt2.plot(y_test,color='blue', label='y_test')
plt2.legend(loc='upper left')
plt2.show()