In [2]:

    

import matplotlib.pyplot as plt
import urllib
from bs4 import BeautifulSoup
from selenium import webdriver
from matplotlib import pyplot as plt
%matplotlib inline
import re
import os,sys, shutil
import time
from datetime import date
try:
    import cPickle as pickle
except:
    import pickle
import pprint
from collections import deque
from shutil import copyfile
import random
import glob
# Import the required modules
import cv2, os
import numpy as np
from PIL import Image
from sklearn.cross_validation import KFold
import numpy as np
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
# Logistic Regression
from sklearn import datasets
from sklearn import metrics
import pandas as pd
import math
from six.moves import xrange  # pylint: disable=redefined-builtin
import tensorflow as tf


    

In [3]:

    

pkl_fl = open("linkedin_profiles.pickle","rb")
my_original_list=pickle.load(pkl_fl) # errors out here
pkl_fl.close()


    

In [ ]:

    

directory = "Male"
    
if os.path.exists(directory):
    shutil.rmtree(directory)
    os.makedirs(directory)     
else:
    os.makedirs(directory) 

directory1 = "Female"

if os.path.exists(directory1):
    shutil.rmtree(directory1)
    os.makedirs(directory1)     
else:
    os.makedirs(directory1)     

directory2 = "Label_Images_Age"

if os.path.exists(directory2):
    shutil.rmtree(directory2)
    os.makedirs(directory2)     
else:
    os.makedirs(directory2)     
    
fileList = glob.glob("./Images/*.*")

for id,fp in enumerate(fileList):
    filename, file_extension = os.path.splitext(fp)
    uid = filename.split('/')[-1]
    #print fp
    for prof in my_original_list:
        if prof['User_ID'] == uid:
            prof_age = prof['age']
            
            if (0 <= prof_age <= 30):
                new_file_extension = 'Youth'
            else:
                new_file_extension = 'Senior'
            
            copyfile(filename + ".jpg", './Label_Images_Age/'+ uid + '.' + str(id) + "." + new_file_extension +'.jpg')


    

In [4]:

    

# For face detection we will use the Haar Cascade provided by OpenCV.
cascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath)

# For face recognition we will the the LBPH Face Recognizer 
recognizer = cv2.createLBPHFaceRecognizer()


    

In [26]:

    

def get_images_and_labels(path):
    # Append all the absolute image paths in a list image_paths
    
    image_paths = [os.path.join(path, f) for f in os.listdir(path)]
    # images will contains face images
    images = []
    # labels will contains the label that is assigned to the image
    labels = []
    #gender will contains 1 or 0 indecating male or female
    age =[]
    
    for image_path in image_paths:
        # Read the image and convert to grayscale
        try:
            image_pil = Image.open(image_path).convert('L')
            # Convert the image format into numpy array
            image = np.array(image_pil, 'uint8')
            # Get the label of the image
        except:
            pass
        
        nbr = int(os.path.split(image_path)[1].split(".")[1])
        age_current = os.path.split(image_path)[1].split(".")[2]
        #print nbr
        
        # Detect the face in the image
        faces = faceCascade.detectMultiScale(image)
        # If face is detected, append the face to images and the label to labels
        try:
            for (x, y, w, h) in faces:

                ref_image = image[y: y + h, x: x + w]
                resized = cv2.resize(ref_image, (100, 100), interpolation = cv2.INTER_AREA)
                #edge_images = cv2.Canny(resized,100,200)
                resized_face = cv2.resize(ref_image, (100, 100), interpolation = cv2.INTER_AREA)
                
                images.append(np.array(resized))   #resized.reshape(1,10000)
                labels.append(nbr)

                if age_current == 'Youth':
                    age.append(0)
                
                else:
                    age.append(1)
                
                #face_file_name = "faces/face_" + str(y) + ".jpg"
                #cv2.imwrite(face_file_name, sub_face)
                
                cv2.imshow("Adding faces to traning set...", resized)
                cv2.waitKey(1)
        except:
            pass
    # return the images list and labels list
    #print "lables"
    #print labels
    #print "Age_current"
    #print age
    
    return images, labels, age


    

In [27]:

    

images, labels, ageList = get_images_and_labels('Label_Images_Age')

cv2.destroyAllWindows()


    

In [28]:

    

#res_images = []
res_age = []

for age in ageList:
    res_age.append(np.array(age))
                   
res_age = np.array(res_age)


    

In [29]:

    

res_age.shape


    

    
Out[29]:





(2968,)

In [12]:

    

# Basic model parameters as external flags.
flags = tf.app.flags
FLAGS = flags.FLAGS
flags.DEFINE_float('learning_rate', 0.01, 'Initial learning rate.')
flags.DEFINE_integer('max_steps', 2000, 'Number of steps to run trainer.')
flags.DEFINE_integer('hidden1', 1500, 'Number of units in hidden layer 1.')
flags.DEFINE_integer('hidden2', 1000, 'Number of units in hidden layer 2.')
flags.DEFINE_integer('hidden3', 500, 'Number of units in hidden layer 3.')
flags.DEFINE_integer('batch_size', 100, 'Batch size.  '
                     'Must divide evenly into the dataset sizes.')
flags.DEFINE_string('train_dir', 'data', 'Directory to put the training data.')
flags.DEFINE_boolean('fake_data', False, 'If true, uses fake data '
                     'for unit testing.')


NUM_CLASSES = 2
IMAGE_SIZE = 100
#CHANNELS = 3
IMAGE_PIXELS = IMAGE_SIZE * IMAGE_SIZE


    

In [30]:

    

n_nodes = [IMAGE_PIXELS, 1500, 1000, 500, NUM_CLASSES]
n_epochs = 10
#NUM_CLASSES = 3


    

In [31]:

    

def neural_network_model(data):
    n_hidden_layers = 3
    # define the layers
    layers = [] 
    for i in range(n_hidden_layers + 1):
        layers.append( {'weights':tf.Variable(tf.random_normal([n_nodes[i], n_nodes[i+1]])), 
                        'biases':tf.Variable(tf.random_normal([n_nodes[i+1]]))} )
    
    # calculate the nodal values for each layer
    calcs = [data]
    for i in range(n_hidden_layers):
        calcs.append( tf.nn.relu(tf.matmul(calcs[i], layers[i]['weights']) + layers[i]['biases']) )

    #  return the last layer of nodes
    return tf.matmul(calcs[-1], layers[-1]['weights']) + layers[-1]['biases']


    

In [32]:

    

def evaluation(logits, labels):
    correct = tf.nn.in_top_k(logits, labels, 1)
  
    return tf.reduce_sum(tf.cast(correct, tf.int32))


    

In [33]:

    

def placeholder_inputs():
    images_placeholder = tf.placeholder(tf.float32, [None,IMAGE_PIXELS])
    labels_placeholder = tf.placeholder(tf.float32, [None,NUM_CLASSES])
    
    return images_placeholder, labels_placeholder


def fill_feed_dict(images_feed,labels_feed, images_pl, labels_pl):
    feed_dict = {
      images_pl: images_feed,
      labels_pl: labels_feed,
    }
  
    return feed_dict


    

In [34]:

    

# def do_eval(sess, eval_correct, images_placeholder, labels_placeholder, data_set):
#     # And run one epoch of eval.
#     true_count = 0  # Counts the number of correct predictions.
#     steps_per_epoch = 47 // FLAGS.batch_size
#     num_examples = steps_per_epoch * FLAGS.batch_size
#     for step in xrange(steps_per_epoch):
#         feed_dict = fill_feed_dict(train_images,train_labels,
#                                images_placeholder,
#                                labels_placeholder)
#         true_count += sess.run(eval_correct, feed_dict=feed_dict)
#     precision = true_count / num_examples
#     print('  Num examples: %d  Num correct: %d  Precision @ 1: %0.04f' %
#         (num_examples, true_count, precision))


    

In [35]:

    

def dense_to_one_hot(labels_dense, num_classes):
    """Convert class labels from scalars to one-hot vectors."""
    num_labels = labels_dense.shape[0]
    index_offset = np.arange(num_labels) * num_classes
    labels_one_hot = np.zeros((num_labels, num_classes))
    labels_one_hot.flat[index_offset + labels_dense.ravel()] = 1
    
    return labels_one_hot


    

In [36]:

    

def main():
    # Tell TensorFlow that the model will be built into the default Graph.
    with tf.Graph().as_default():
        # Generate placeholders for the images and labels.
        images_placeholder, labels_placeholder = placeholder_inputs()
        
        
        logits = neural_network_model(images_placeholder)
        
        
        cost = tf.reduce_mean( tf.nn.softmax_cross_entropy_with_logits(logits,labels_placeholder) )
        training_acc = []
        testing_acc = []
       
        #print cost
        optimizer = tf.train.AdamOptimizer(1e-4).minimize(cost)

        with tf.Session() as sess:
            sess.run(tf.initialize_all_variables())
        
            subset_size = 128
            for step in xrange(200):
                start_time = time.time()
                total_loss = 0
                for i in range(int(train_images.shape[0] / subset_size) ):
                    
                    epoch_x = train_images[i * subset_size:][:subset_size]
                    epoch_y = train_labels[i * subset_size:][:subset_size]
                    
                    feed_dict = fill_feed_dict(epoch_x, epoch_y, images_placeholder, labels_placeholder)
                    
                    _, loss_value = sess.run([optimizer, cost],
                                           feed_dict=feed_dict)
                    
                    total_loss+=loss_value
                    
                duration = time.time() - start_time
                #if step % 10 == 0:
                    #Print status to stdout.
                correct = tf.equal(tf.argmax(logits,1), tf.argmax(labels_placeholder,1))
                #print correct
                accuracy = tf.reduce_mean(tf.cast(correct, 'float'))
                
                print('Step %d: loss = %.2f (%.3f sec)' % (step, total_loss, duration)),
                
                current_train_acc = accuracy.eval({images_placeholder: train_images, labels_placeholder: train_labels})
                current_test_acc = accuracy.eval({images_placeholder: test_images, labels_placeholder: test_labels})
                
                training_acc.append(current_train_acc)
                testing_acc.append(current_test_acc)
                
                
                print('Training Accuracy:', current_train_acc),
                print('Testing Accuracy:', current_test_acc)
    
    return training_acc, testing_acc


    

In [37]:

    

# Get the sets of images and labels for training, validation, and

images = np.array(images)
images = images.reshape(images.shape[0],IMAGE_PIXELS)

#label = res_gender
labels = dense_to_one_hot(res_age,2)


    

In [38]:

    

train_images = images[:-300]
train_labels = labels[:-300]
test_images = images[-300:]
test_labels = labels[-300:]


    

In [39]:

    

train_images.shape


    

    
Out[39]:





(2668, 10000)

In [40]:

    

train_labels[:10]


    

    
Out[40]:





array([[ 1.,  0.],
       [ 1.,  0.],
       [ 1.,  0.],
       [ 1.,  0.],
       [ 0.,  1.],
       [ 1.,  0.],
       [ 0.,  1.],
       [ 1.,  0.],
       [ 0.,  1.],
       [ 1.,  0.]])

In [48]:

    

if __name__ == '__main__':
    train_acc, test_acc = main()


    

    




Step 0: loss = 395528670.00 (20.735 sec) ('Training Accuracy:', 0.58523792) ('Testing Accuracy:', 0.55666667)
Step 1: loss = 220396099.00 (18.116 sec) ('Training Accuracy:', 0.54589736) ('Testing Accuracy:', 0.54000002)
Step 2: loss = 179621873.00 (18.783 sec) ('Training Accuracy:', 0.57474709) ('Testing Accuracy:', 0.57333332)
Step 3: loss = 155101924.50 (18.809 sec) ('Training Accuracy:', 0.58673662) ('Testing Accuracy:', 0.56666666)
Step 4: loss = 134338255.50 (18.091 sec) ('Training Accuracy:', 0.6140877) ('Testing Accuracy:', 0.55666667)
Step 5: loss = 119382057.00 (18.524 sec) ('Training Accuracy:', 0.62233049) ('Testing Accuracy:', 0.56666666)
Step 6: loss = 109150841.00 (18.371 sec) ('Training Accuracy:', 0.6140877) ('Testing Accuracy:', 0.52999997)
Step 7: loss = 100355448.50 (18.288 sec) ('Training Accuracy:', 0.64368677) ('Testing Accuracy:', 0.55000001)
Step 8: loss = 90316874.00 (18.259 sec) ('Training Accuracy:', 0.65979767) ('Testing Accuracy:', 0.56333333)
Step 9: loss = 83114883.75 (19.799 sec) ('Training Accuracy:', 0.683402) ('Testing Accuracy:', 0.58333331)
Step 10: loss = 80883845.25 (19.754 sec) ('Training Accuracy:', 0.63057327) ('Testing Accuracy:', 0.54333335)
Step 11: loss = 76445174.25 (23.017 sec) ('Training Accuracy:', 0.6301986) ('Testing Accuracy:', 0.52666664)
Step 12: loss = 70804721.50 (18.260 sec) ('Training Accuracy:', 0.65567631) ('Testing Accuracy:', 0.55000001)
Step 13: loss = 65426590.75 (19.133 sec) ('Training Accuracy:', 0.71599853) ('Testing Accuracy:', 0.57999998)
Step 14: loss = 58496118.25 (22.298 sec) ('Training Accuracy:', 0.72461593) ('Testing Accuracy:', 0.56666666)
Step 15: loss = 56644456.00 (19.309 sec) ('Training Accuracy:', 0.71749717) ('Testing Accuracy:', 0.56333333)
Step 16: loss = 58432280.50 (20.469 sec) ('Training Accuracy:', 0.64668417) ('Testing Accuracy:', 0.51999998)
Step 17: loss = 55783294.38 (22.985 sec) ('Training Accuracy:', 0.68415135) ('Testing Accuracy:', 0.56)
Step 18: loss = 48997586.62 (22.081 sec) ('Training Accuracy:', 0.73510677) ('Testing Accuracy:', 0.57333332)
Step 19: loss = 42381009.88 (20.846 sec) ('Training Accuracy:', 0.7602098) ('Testing Accuracy:', 0.56999999)
Step 20: loss = 39973975.25 (18.261 sec) ('Training Accuracy:', 0.76807791) ('Testing Accuracy:', 0.57666665)
Step 21: loss = 39958214.75 (20.391 sec) ('Training Accuracy:', 0.76058447) ('Testing Accuracy:', 0.57666665)
Step 22: loss = 46518738.62 (20.704 sec) ('Training Accuracy:', 0.65642565) ('Testing Accuracy:', 0.52999997)
Step 23: loss = 47077415.62 (17.999 sec) ('Training Accuracy:', 0.71674782) ('Testing Accuracy:', 0.58333331)
Step 24: loss = 38812797.19 (18.560 sec) ('Training Accuracy:', 0.78643686) ('Testing Accuracy:', 0.57666665)
Step 25: loss = 30932883.81 (18.507 sec) ('Training Accuracy:', 0.79617834) ('Testing Accuracy:', 0.58666664)
Step 26: loss = 29650082.25 (17.934 sec) ('Training Accuracy:', 0.79243159) ('Testing Accuracy:', 0.57333332)
Step 27: loss = 34410482.25 (18.509 sec) ('Training Accuracy:', 0.73023605) ('Testing Accuracy:', 0.56999999)
Step 28: loss = 32995481.94 (19.420 sec) ('Training Accuracy:', 0.6878981) ('Testing Accuracy:', 0.54666668)
Step 29: loss = 33173641.38 (21.079 sec) ('Training Accuracy:', 0.8017984) ('Testing Accuracy:', 0.56333333)
Step 30: loss = 30599068.00 (26.529 sec) ('Training Accuracy:', 0.80816787) ('Testing Accuracy:', 0.5933333)
Step 31: loss = 26812000.25 (24.931 sec) ('Training Accuracy:', 0.81528664) ('Testing Accuracy:', 0.58666664)
Step 32: loss = 29528569.69 (24.281 sec) ('Training Accuracy:', 0.72686398) ('Testing Accuracy:', 0.55333334)
Step 33: loss = 29149880.19 (25.218 sec) ('Training Accuracy:', 0.77969277) ('Testing Accuracy:', 0.58333331)
Step 34: loss = 22667415.34 (25.822 sec) ('Training Accuracy:', 0.83626825) ('Testing Accuracy:', 0.56)
Step 35: loss = 18673262.44 (27.346 sec) ('Training Accuracy:', 0.83626825) ('Testing Accuracy:', 0.56)
Step 36: loss = 20855827.88 (25.101 sec) ('Training Accuracy:', 0.83139753) ('Testing Accuracy:', 0.56999999)
Step 37: loss = 22282441.66 (23.905 sec) ('Training Accuracy:', 0.78418881) ('Testing Accuracy:', 0.56)
Step 38: loss = 22829820.62 (26.225 sec) ('Training Accuracy:', 0.71375048) ('Testing Accuracy:', 0.55333334)
Step 39: loss = 22245457.81 (26.954 sec) ('Training Accuracy:', 0.83814162) ('Testing Accuracy:', 0.56)
Step 40: loss = 19963534.31 (24.358 sec) ('Training Accuracy:', 0.84713376) ('Testing Accuracy:', 0.57666665)
Step 41: loss = 19722497.25 (26.249 sec) ('Training Accuracy:', 0.79505432) ('Testing Accuracy:', 0.62)
Step 42: loss = 23510871.66 (24.984 sec) ('Training Accuracy:', 0.81978267) ('Testing Accuracy:', 0.56333333)
Step 43: loss = 19166439.72 (26.057 sec) ('Training Accuracy:', 0.77856874) ('Testing Accuracy:', 0.56666666)
Step 44: loss = 15818942.69 (25.816 sec) ('Training Accuracy:', 0.85650057) ('Testing Accuracy:', 0.55666667)
Step 45: loss = 13190035.11 (24.819 sec) ('Training Accuracy:', 0.85387784) ('Testing Accuracy:', 0.57999998)
Step 46: loss = 13806201.25 (24.695 sec) ('Training Accuracy:', 0.863994) ('Testing Accuracy:', 0.56333333)
Step 47: loss = 14714919.06 (25.895 sec) ('Training Accuracy:', 0.80591983) ('Testing Accuracy:', 0.57333332)
Step 48: loss = 14885947.03 (25.921 sec) ('Training Accuracy:', 0.84001499) ('Testing Accuracy:', 0.56999999)
Step 49: loss = 16717305.72 (25.257 sec) ('Training Accuracy:', 0.8077932) ('Testing Accuracy:', 0.62)
Step 50: loss = 18009347.41 (25.201 sec) ('Training Accuracy:', 0.88047957) ('Testing Accuracy:', 0.57666665)
Step 51: loss = 11516599.02 (25.491 sec) ('Training Accuracy:', 0.85500187) ('Testing Accuracy:', 0.57999998)
Step 52: loss = 9653285.82 (22.732 sec) ('Training Accuracy:', 0.85949796) ('Testing Accuracy:', 0.57333332)
Step 53: loss = 9678017.12 (20.977 sec) ('Training Accuracy:', 0.8786062) ('Testing Accuracy:', 0.57333332)
Step 54: loss = 10106953.42 (24.663 sec) ('Training Accuracy:', 0.83476955) ('Testing Accuracy:', 0.61000001)
Step 55: loss = 12767426.06 (20.331 sec) ('Training Accuracy:', 0.88909703) ('Testing Accuracy:', 0.56999999)
Step 56: loss = 12256964.94 (18.805 sec) ('Training Accuracy:', 0.85275382) ('Testing Accuracy:', 0.57666665)
Step 57: loss = 13983117.12 (18.510 sec) ('Training Accuracy:', 0.87223679) ('Testing Accuracy:', 0.57666665)
Step 58: loss = 10849780.32 (18.433 sec) ('Training Accuracy:', 0.85462719) ('Testing Accuracy:', 0.61000001)
Step 59: loss = 11475276.03 (18.343 sec) ('Training Accuracy:', 0.88047957) ('Testing Accuracy:', 0.60000002)
Step 60: loss = 10135785.66 (18.627 sec) ('Training Accuracy:', 0.89958787) ('Testing Accuracy:', 0.57333332)
Step 61: loss = 13481515.30 (19.093 sec) ('Training Accuracy:', 0.88235295) ('Testing Accuracy:', 0.57333332)
Step 62: loss = 8455843.21 (18.362 sec) ('Training Accuracy:', 0.86137128) ('Testing Accuracy:', 0.60333335)
Step 63: loss = 8857971.64 (17.993 sec) ('Training Accuracy:', 0.89921319) ('Testing Accuracy:', 0.57666665)
Step 64: loss = 7981046.94 (18.455 sec) ('Training Accuracy:', 0.90071189) ('Testing Accuracy:', 0.57666665)
Step 65: loss = 8506238.92 (18.654 sec) ('Training Accuracy:', 0.89921319) ('Testing Accuracy:', 0.56999999)
Step 66: loss = 7148400.58 (18.652 sec) ('Training Accuracy:', 0.83739227) ('Testing Accuracy:', 0.61333334)
Step 67: loss = 7399944.48 (18.475 sec) ('Training Accuracy:', 0.8801049) ('Testing Accuracy:', 0.5933333)
Step 68: loss = 7592826.45 (18.734 sec) ('Training Accuracy:', 0.90146124) ('Testing Accuracy:', 0.58333331)
Step 69: loss = 8530550.36 (18.594 sec) ('Training Accuracy:', 0.90333456) ('Testing Accuracy:', 0.57999998)
Step 70: loss = 8917605.17 (18.609 sec) ('Training Accuracy:', 0.88759834) ('Testing Accuracy:', 0.5933333)
Step 71: loss = 9181566.79 (19.142 sec) ('Training Accuracy:', 0.76395655) ('Testing Accuracy:', 0.63)
Step 72: loss = 11113199.07 (18.253 sec) ('Training Accuracy:', 0.89171976) ('Testing Accuracy:', 0.5933333)
Step 73: loss = 10964444.16 (18.636 sec) ('Training Accuracy:', 0.89958787) ('Testing Accuracy:', 0.57999998)
Step 74: loss = 10920355.54 (18.682 sec) ('Training Accuracy:', 0.86624205) ('Testing Accuracy:', 0.60000002)
Step 75: loss = 9520502.06 (19.101 sec) ('Training Accuracy:', 0.75271636) ('Testing Accuracy:', 0.63999999)
Step 76: loss = 12823183.77 (19.034 sec) ('Training Accuracy:', 0.89359313) ('Testing Accuracy:', 0.5933333)
Step 77: loss = 14376796.55 (18.359 sec) ('Training Accuracy:', 0.85799927) ('Testing Accuracy:', 0.60333335)
Step 78: loss = 10358715.42 (18.704 sec) ('Training Accuracy:', 0.75683779) ('Testing Accuracy:', 0.63)
Step 79: loss = 9613111.28 (18.739 sec) ('Training Accuracy:', 0.81491196) ('Testing Accuracy:', 0.63999999)
Step 80: loss = 13734371.75 (18.540 sec) ('Training Accuracy:', 0.87448484) ('Testing Accuracy:', 0.61666667)
Step 81: loss = 16758030.50 (18.828 sec) ('Training Accuracy:', 0.81266391) ('Testing Accuracy:', 0.61666667)
Step 82: loss = 13494503.95 (18.513 sec) ('Training Accuracy:', 0.69426751) ('Testing Accuracy:', 0.64333332)
Step 83: loss = 19960144.81 (18.549 sec) ('Training Accuracy:', 0.81303859) ('Testing Accuracy:', 0.63333333)
Step 84: loss = 29600476.73 (18.369 sec) ('Training Accuracy:', 0.7010116) ('Testing Accuracy:', 0.64999998)
Step 85: loss = 29474308.66 (18.691 sec) ('Training Accuracy:', 0.70063692) ('Testing Accuracy:', 0.65333331)
Step 86: loss = 54626339.88 (18.969 sec) ('Training Accuracy:', 0.83889097) ('Testing Accuracy:', 0.62333333)
Step 87: loss = 79810417.00 (18.407 sec) ('Training Accuracy:', 0.55638814) ('Testing Accuracy:', 0.47999999)
Step 88: loss = 51759860.06 (18.392 sec) ('Training Accuracy:', 0.72386664) ('Testing Accuracy:', 0.52666664)
Step 89: loss = 19125332.47 (17.981 sec) ('Training Accuracy:', 0.80966651) ('Testing Accuracy:', 0.51999998)
Step 90: loss = 10198429.27 (17.612 sec) ('Training Accuracy:', 0.8254028) ('Testing Accuracy:', 0.53333336)
Step 91: loss = 5774459.58 (18.848 sec) ('Training Accuracy:', 0.88385165) ('Testing Accuracy:', 0.53333336)
Step 92: loss = 3832364.97 (18.248 sec) ('Training Accuracy:', 0.89996254) ('Testing Accuracy:', 0.55333334)
Step 93: loss = 3600217.03 (18.402 sec) ('Training Accuracy:', 0.84825778) ('Testing Accuracy:', 0.54333335)
Step 94: loss = 2834735.17 (18.749 sec) ('Training Accuracy:', 0.91270137) ('Testing Accuracy:', 0.56333333)
Step 95: loss = 2483986.63 (21.205 sec) ('Training Accuracy:', 0.94754589) ('Testing Accuracy:', 0.5933333)
Step 96: loss = 2488870.22 (18.592 sec) ('Training Accuracy:', 0.92993629) ('Testing Accuracy:', 0.58999997)
Step 97: loss = 6099974.95 (24.486 sec) ('Training Accuracy:', 0.92656428) ('Testing Accuracy:', 0.58666664)
Step 98: loss = 10518841.50 (18.998 sec) ('Training Accuracy:', 0.93143499) ('Testing Accuracy:', 0.58666664)
Step 99: loss = 19011843.37 (18.609 sec) ('Training Accuracy:', 0.93855375) ('Testing Accuracy:', 0.57999998)
Step 100: loss = 26509186.40 (18.661 sec) ('Training Accuracy:', 0.88797301) ('Testing Accuracy:', 0.56333333)
Step 101: loss = 34970640.25 (18.755 sec) ('Training Accuracy:', 0.70513302) ('Testing Accuracy:', 0.50999999)
Step 102: loss = 33019193.95 (20.832 sec) ('Training Accuracy:', 0.61034095) ('Testing Accuracy:', 0.51333332)
Step 103: loss = 33624793.92 (22.864 sec) ('Training Accuracy:', 0.59722745) ('Testing Accuracy:', 0.49666667)
Step 104: loss = 29889762.48 (26.473 sec) ('Training Accuracy:', 0.63694268) ('Testing Accuracy:', 0.52333331)
Step 105: loss = 25318065.02 (20.331 sec) ('Training Accuracy:', 0.78493816) ('Testing Accuracy:', 0.52999997)
Step 106: loss = 16578960.23 (18.543 sec) ('Training Accuracy:', 0.93518174) ('Testing Accuracy:', 0.57333332)
Step 107: loss = 8810454.80 (18.595 sec) ('Training Accuracy:', 0.91532409) ('Testing Accuracy:', 0.58999997)
Step 108: loss = 4014625.62 (18.779 sec) ('Training Accuracy:', 0.9437992) ('Testing Accuracy:', 0.55333334)
Step 109: loss = 2028400.20 (19.126 sec) ('Training Accuracy:', 0.95803672) ('Testing Accuracy:', 0.57666665)
Step 110: loss = 1291151.69 (20.425 sec) ('Training Accuracy:', 0.94529784) ('Testing Accuracy:', 0.55666667)
Step 111: loss = 1005738.67 (22.640 sec) ('Training Accuracy:', 0.94267517) ('Testing Accuracy:', 0.56)
Step 112: loss = 881171.88 (22.072 sec) ('Training Accuracy:', 0.96028477) ('Testing Accuracy:', 0.58666664)
Step 113: loss = 726453.29 (18.441 sec) ('Training Accuracy:', 0.95653802) ('Testing Accuracy:', 0.56)
Step 114: loss = 808755.73 (18.473 sec) ('Training Accuracy:', 0.95653802) ('Testing Accuracy:', 0.56)
Step 115: loss = 818544.90 (18.560 sec) ('Training Accuracy:', 0.93967777) ('Testing Accuracy:', 0.55666667)
Step 116: loss = 742247.03 (18.486 sec) ('Training Accuracy:', 0.94792056) ('Testing Accuracy:', 0.57333332)
Step 117: loss = 546955.98 (18.538 sec) ('Training Accuracy:', 0.94155115) ('Testing Accuracy:', 0.56)
Step 118: loss = 500832.01 (18.696 sec) ('Training Accuracy:', 0.94754589) ('Testing Accuracy:', 0.56)
Step 119: loss = 477957.42 (18.407 sec) ('Training Accuracy:', 0.96215808) ('Testing Accuracy:', 0.56999999)
Step 120: loss = 530397.55 (18.263 sec) ('Training Accuracy:', 0.92993629) ('Testing Accuracy:', 0.54666668)
Step 121: loss = 520169.84 (18.710 sec) ('Training Accuracy:', 0.90970403) ('Testing Accuracy:', 0.54666668)
Step 122: loss = 720789.46 (18.322 sec) ('Training Accuracy:', 0.95616335) ('Testing Accuracy:', 0.58666664)
Step 123: loss = 476493.73 (20.140 sec) ('Training Accuracy:', 0.93967777) ('Testing Accuracy:', 0.56)
Step 124: loss = 434232.17 (20.813 sec) ('Training Accuracy:', 0.9378044) ('Testing Accuracy:', 0.54666668)
Step 125: loss = 386569.96 (19.303 sec) ('Training Accuracy:', 0.93892843) ('Testing Accuracy:', 0.55333334)
Step 126: loss = 505985.57 (18.582 sec) ('Training Accuracy:', 0.91644812) ('Testing Accuracy:', 0.56333333)
Step 127: loss = 452760.37 (19.209 sec) ('Training Accuracy:', 0.92993629) ('Testing Accuracy:', 0.55000001)
Step 128: loss = 667435.76 (19.690 sec) ('Training Accuracy:', 0.9393031) ('Testing Accuracy:', 0.56)
Step 129: loss = 737116.00 (19.419 sec) ('Training Accuracy:', 0.96328211) ('Testing Accuracy:', 0.57666665)
Step 130: loss = 791851.41 (18.720 sec) ('Training Accuracy:', 0.955414) ('Testing Accuracy:', 0.56333333)
Step 131: loss = 1062663.68 (19.156 sec) ('Training Accuracy:', 0.93330836) ('Testing Accuracy:', 0.55000001)
Step 132: loss = 1549395.81 (18.852 sec) ('Training Accuracy:', 0.89696515) ('Testing Accuracy:', 0.55666667)
Step 133: loss = 948608.04 (19.588 sec) ('Training Accuracy:', 0.91120267) ('Testing Accuracy:', 0.56333333)
Step 134: loss = 905151.49 (18.816 sec) ('Training Accuracy:', 0.95503932) ('Testing Accuracy:', 0.57999998)
Step 135: loss = 449450.18 (19.002 sec) ('Training Accuracy:', 0.95803672) ('Testing Accuracy:', 0.56)
Step 136: loss = 411582.90 (18.578 sec) ('Training Accuracy:', 0.93180966) ('Testing Accuracy:', 0.55666667)
Step 137: loss = 487857.95 (19.103 sec) ('Training Accuracy:', 0.92881227) ('Testing Accuracy:', 0.56)
Step 138: loss = 485285.46 (19.355 sec) ('Training Accuracy:', 0.95466465) ('Testing Accuracy:', 0.57333332)
Step 139: loss = 512884.69 (20.375 sec) ('Training Accuracy:', 0.91082805) ('Testing Accuracy:', 0.55666667)
Step 140: loss = 428029.55 (19.056 sec) ('Training Accuracy:', 0.93892843) ('Testing Accuracy:', 0.55000001)
Step 141: loss = 524102.02 (18.614 sec) ('Training Accuracy:', 0.90595728) ('Testing Accuracy:', 0.56333333)
Step 142: loss = 526997.01 (19.216 sec) ('Training Accuracy:', 0.95578867) ('Testing Accuracy:', 0.56999999)
Step 143: loss = 346189.91 (19.781 sec) ('Training Accuracy:', 0.94042712) ('Testing Accuracy:', 0.56666666)
Step 144: loss = 407018.55 (20.084 sec) ('Training Accuracy:', 0.9246909) ('Testing Accuracy:', 0.56666666)
Step 145: loss = 583977.98 (20.186 sec) ('Training Accuracy:', 0.96065944) ('Testing Accuracy:', 0.57333332)
Step 146: loss = 641364.68 (20.337 sec) ('Training Accuracy:', 0.93443239) ('Testing Accuracy:', 0.56)
Step 147: loss = 418056.84 (20.494 sec) ('Training Accuracy:', 0.92506558) ('Testing Accuracy:', 0.56)
Step 148: loss = 484374.75 (20.290 sec) ('Training Accuracy:', 0.91607344) ('Testing Accuracy:', 0.56333333)
Step 149: loss = 450067.21 (20.135 sec) ('Training Accuracy:', 0.94792056) ('Testing Accuracy:', 0.56)
Step 150: loss = 472774.74 (20.517 sec) ('Training Accuracy:', 0.91494942) ('Testing Accuracy:', 0.55333334)
Step 151: loss = 497126.85 (20.328 sec) ('Training Accuracy:', 0.95578867) ('Testing Accuracy:', 0.56666666)
Step 152: loss = 490250.77 (20.691 sec) ('Training Accuracy:', 0.90370923) ('Testing Accuracy:', 0.55666667)
Step 153: loss = 368840.56 (20.495 sec) ('Training Accuracy:', 0.92956161) ('Testing Accuracy:', 0.55000001)
Step 154: loss = 535823.58 (19.908 sec) ('Training Accuracy:', 0.92806292) ('Testing Accuracy:', 0.55666667)
Step 155: loss = 482863.35 (19.886 sec) ('Training Accuracy:', 0.92731363) ('Testing Accuracy:', 0.56333333)
Step 156: loss = 347522.20 (19.304 sec) ('Training Accuracy:', 0.92394155) ('Testing Accuracy:', 0.56666666)
Step 157: loss = 695685.58 (20.076 sec) ('Training Accuracy:', 0.92806292) ('Testing Accuracy:', 0.56666666)
Step 158: loss = 380563.73 (19.875 sec) ('Training Accuracy:', 0.93630576) ('Testing Accuracy:', 0.56333333)
Step 159: loss = 530029.11 (19.948 sec) ('Training Accuracy:', 0.88797301) ('Testing Accuracy:', 0.55333334)
Step 160: loss = 708251.66 (20.051 sec) ('Training Accuracy:', 0.89808917) ('Testing Accuracy:', 0.56333333)
Step 161: loss = 634554.94 (19.921 sec) ('Training Accuracy:', 0.93967777) ('Testing Accuracy:', 0.56999999)
Step 162: loss = 457547.76 (19.983 sec) ('Training Accuracy:', 0.94192582) ('Testing Accuracy:', 0.58333331)
Step 163: loss = 412397.88 (19.437 sec) ('Training Accuracy:', 0.92881227) ('Testing Accuracy:', 0.56666666)
Step 164: loss = 475227.25 (19.914 sec) ('Training Accuracy:', 0.91157734) ('Testing Accuracy:', 0.55666667)
Step 165: loss = 325684.73 (19.952 sec) ('Training Accuracy:', 0.92056948) ('Testing Accuracy:', 0.55666667)
Step 166: loss = 543957.46 (20.221 sec) ('Training Accuracy:', 0.91982013) ('Testing Accuracy:', 0.56666666)
Step 167: loss = 628894.66 (19.794 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.56333333)
Step 168: loss = 348035.80 (19.634 sec) ('Training Accuracy:', 0.90445858) ('Testing Accuracy:', 0.55000001)
Step 169: loss = 495778.09 (19.877 sec) ('Training Accuracy:', 0.95616335) ('Testing Accuracy:', 0.57333332)
Step 170: loss = 386648.65 (19.973 sec) ('Training Accuracy:', 0.94941926) ('Testing Accuracy:', 0.56333333)
Step 171: loss = 427082.45 (20.438 sec) ('Training Accuracy:', 0.9261896) ('Testing Accuracy:', 0.55333334)
Step 172: loss = 332340.49 (19.964 sec) ('Training Accuracy:', 0.93143499) ('Testing Accuracy:', 0.56999999)
Step 173: loss = 554492.00 (20.348 sec) ('Training Accuracy:', 0.94042712) ('Testing Accuracy:', 0.57333332)
Step 174: loss = 669353.57 (19.676 sec) ('Training Accuracy:', 0.93368304) ('Testing Accuracy:', 0.56999999)
Step 175: loss = 722732.74 (19.810 sec) ('Training Accuracy:', 0.90108657) ('Testing Accuracy:', 0.56)
Step 176: loss = 569300.93 (20.043 sec) ('Training Accuracy:', 0.92656428) ('Testing Accuracy:', 0.57333332)
Step 177: loss = 702314.55 (19.776 sec) ('Training Accuracy:', 0.92544025) ('Testing Accuracy:', 0.57333332)
Step 178: loss = 434440.93 (19.939 sec) ('Training Accuracy:', 0.90783066) ('Testing Accuracy:', 0.55666667)
Step 179: loss = 661501.71 (19.651 sec) ('Training Accuracy:', 0.87148744) ('Testing Accuracy:', 0.55666667)
Step 180: loss = 753493.39 (20.084 sec) ('Training Accuracy:', 0.89059573) ('Testing Accuracy:', 0.56)
Step 181: loss = 2278272.88 (19.722 sec) ('Training Accuracy:', 0.95204198) ('Testing Accuracy:', 0.56999999)
Step 182: loss = 965835.36 (19.282 sec) ('Training Accuracy:', 0.91569877) ('Testing Accuracy:', 0.56333333)
Step 183: loss = 453197.38 (19.867 sec) ('Training Accuracy:', 0.96365678) ('Testing Accuracy:', 0.57999998)
Step 184: loss = 447842.86 (19.383 sec) ('Training Accuracy:', 0.9408018) ('Testing Accuracy:', 0.56333333)
Step 185: loss = 247947.00 (20.147 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.58333331)
Step 186: loss = 413876.28 (19.523 sec) ('Training Accuracy:', 0.90745598) ('Testing Accuracy:', 0.56666666)
Step 187: loss = 552991.07 (19.597 sec) ('Training Accuracy:', 0.92881227) ('Testing Accuracy:', 0.56999999)
Step 188: loss = 765477.68 (19.745 sec) ('Training Accuracy:', 0.96140879) ('Testing Accuracy:', 0.56999999)
Step 189: loss = 673428.16 (19.387 sec) ('Training Accuracy:', 0.94979393) ('Testing Accuracy:', 0.56666666)
Step 190: loss = 571760.30 (19.633 sec) ('Training Accuracy:', 0.94979393) ('Testing Accuracy:', 0.55666667)
Step 191: loss = 314596.90 (19.286 sec) ('Training Accuracy:', 0.94529784) ('Testing Accuracy:', 0.56999999)
Step 192: loss = 497101.23 (19.703 sec) ('Training Accuracy:', 0.93892843) ('Testing Accuracy:', 0.55333334)
Step 193: loss = 484139.30 (19.459 sec) ('Training Accuracy:', 0.91345072) ('Testing Accuracy:', 0.56)
Step 194: loss = 416408.98 (19.741 sec) ('Training Accuracy:', 0.95466465) ('Testing Accuracy:', 0.56)
Step 195: loss = 589691.84 (19.978 sec) ('Training Accuracy:', 0.94155115) ('Testing Accuracy:', 0.55666667)
Step 196: loss = 346290.78 (19.859 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.56333333)
Step 197: loss = 285855.92 (19.648 sec) ('Training Accuracy:', 0.95503932) ('Testing Accuracy:', 0.56666666)
Step 198: loss = 357525.41 (19.589 sec) ('Training Accuracy:', 0.93180966) ('Testing Accuracy:', 0.56)
Step 199: loss = 264433.79 (19.996 sec) ('Training Accuracy:', 0.93630576) ('Testing Accuracy:', 0.56999999)
Step 200: loss = 305804.99 (19.117 sec) ('Training Accuracy:', 0.95354062) ('Testing Accuracy:', 0.56)
Step 201: loss = 372789.33 (19.643 sec) ('Training Accuracy:', 0.93817908) ('Testing Accuracy:', 0.56666666)
Step 202: loss = 224685.29 (19.587 sec) ('Training Accuracy:', 0.95503932) ('Testing Accuracy:', 0.57666665)
Step 203: loss = 308731.07 (19.678 sec) ('Training Accuracy:', 0.93855375) ('Testing Accuracy:', 0.56)
Step 204: loss = 255179.55 (20.490 sec) ('Training Accuracy:', 0.93255901) ('Testing Accuracy:', 0.56666666)
Step 205: loss = 414352.77 (19.977 sec) ('Training Accuracy:', 0.94529784) ('Testing Accuracy:', 0.56666666)
Step 206: loss = 422845.05 (19.650 sec) ('Training Accuracy:', 0.96740353) ('Testing Accuracy:', 0.56333333)
Step 207: loss = 404293.19 (20.274 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.56666666)
Step 208: loss = 495015.66 (20.134 sec) ('Training Accuracy:', 0.96140879) ('Testing Accuracy:', 0.56999999)
Step 209: loss = 253650.08 (20.036 sec) ('Training Accuracy:', 0.9216935) ('Testing Accuracy:', 0.56666666)
Step 210: loss = 360968.85 (19.897 sec) ('Training Accuracy:', 0.94829524) ('Testing Accuracy:', 0.56999999)
Step 211: loss = 448394.76 (19.948 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.55666667)
Step 212: loss = 280270.40 (19.744 sec) ('Training Accuracy:', 0.95279133) ('Testing Accuracy:', 0.56333333)
Step 213: loss = 334648.75 (20.788 sec) ('Training Accuracy:', 0.94042712) ('Testing Accuracy:', 0.56333333)
Step 214: loss = 265454.50 (20.290 sec) ('Training Accuracy:', 0.93255901) ('Testing Accuracy:', 0.56)
Step 215: loss = 453869.40 (20.064 sec) ('Training Accuracy:', 0.95428997) ('Testing Accuracy:', 0.57666665)
Step 216: loss = 328018.92 (20.195 sec) ('Training Accuracy:', 0.9423005) ('Testing Accuracy:', 0.56666666)
Step 217: loss = 225655.80 (20.313 sec) ('Training Accuracy:', 0.92206818) ('Testing Accuracy:', 0.56333333)
Step 218: loss = 437707.95 (20.332 sec) ('Training Accuracy:', 0.93855375) ('Testing Accuracy:', 0.55666667)
Step 219: loss = 259201.14 (20.384 sec) ('Training Accuracy:', 0.93143499) ('Testing Accuracy:', 0.55666667)
Step 220: loss = 428738.93 (19.990 sec) ('Training Accuracy:', 0.95091796) ('Testing Accuracy:', 0.56666666)
Step 221: loss = 570143.33 (19.912 sec) ('Training Accuracy:', 0.95241666) ('Testing Accuracy:', 0.56)
Step 222: loss = 840541.49 (25.522 sec) ('Training Accuracy:', 0.88535035) ('Testing Accuracy:', 0.55333334)
Step 223: loss = 1469882.89 (24.638 sec) ('Training Accuracy:', 0.955414) ('Testing Accuracy:', 0.56999999)
Step 224: loss = 525639.05 (24.045 sec) ('Training Accuracy:', 0.95578867) ('Testing Accuracy:', 0.57333332)
Step 225: loss = 410434.89 (24.219 sec) ('Training Accuracy:', 0.92956161) ('Testing Accuracy:', 0.56333333)
Step 226: loss = 628714.96 (20.389 sec) ('Training Accuracy:', 0.93817908) ('Testing Accuracy:', 0.56333333)
Step 227: loss = 543289.63 (24.148 sec) ('Training Accuracy:', 0.97152489) ('Testing Accuracy:', 0.57999998)
Step 228: loss = 608845.15 (24.604 sec) ('Training Accuracy:', 0.91232669) ('Testing Accuracy:', 0.56333333)
Step 229: loss = 672304.75 (22.251 sec) ('Training Accuracy:', 0.91345072) ('Testing Accuracy:', 0.56333333)
Step 230: loss = 996096.17 (20.501 sec) ('Training Accuracy:', 0.93330836) ('Testing Accuracy:', 0.55000001)
Step 231: loss = 1526849.56 (19.566 sec) ('Training Accuracy:', 0.96290743) ('Testing Accuracy:', 0.5933333)
Step 232: loss = 3809939.59 (19.218 sec) ('Training Accuracy:', 0.94267517) ('Testing Accuracy:', 0.56333333)
Step 233: loss = 3389452.82 (19.979 sec) ('Training Accuracy:', 0.955414) ('Testing Accuracy:', 0.55333334)
Step 234: loss = 2183025.43 (19.541 sec) ('Training Accuracy:', 0.8624953) ('Testing Accuracy:', 0.64333332)
Step 235: loss = 5238474.12 (19.236 sec) ('Training Accuracy:', 0.95803672) ('Testing Accuracy:', 0.57333332)
Step 236: loss = 9339312.41 (19.450 sec) ('Training Accuracy:', 0.86736608) ('Testing Accuracy:', 0.63666666)
Step 237: loss = 4565297.18 (19.274 sec) ('Training Accuracy:', 0.87448484) ('Testing Accuracy:', 0.61666667)
Step 238: loss = 8421358.66 (19.032 sec) ('Training Accuracy:', 0.89921319) ('Testing Accuracy:', 0.62)
Step 239: loss = 23878209.06 (19.395 sec) ('Training Accuracy:', 0.88422632) ('Testing Accuracy:', 0.64333332)
Step 240: loss = 46003665.50 (19.003 sec) ('Training Accuracy:', 0.59010863) ('Testing Accuracy:', 0.47666666)
Step 241: loss = 55187746.98 (18.967 sec) ('Training Accuracy:', 0.89996254) ('Testing Accuracy:', 0.55666667)
Step 242: loss = 11303700.06 (18.753 sec) ('Training Accuracy:', 0.91832149) ('Testing Accuracy:', 0.62333333)
Step 243: loss = 2699350.59 (18.698 sec) ('Training Accuracy:', 0.96553016) ('Testing Accuracy:', 0.57666665)
Step 244: loss = 1277992.41 (18.838 sec) ('Training Accuracy:', 0.95091796) ('Testing Accuracy:', 0.57333332)
Step 245: loss = 1158161.91 (19.072 sec) ('Training Accuracy:', 0.87748218) ('Testing Accuracy:', 0.54666668)
Step 246: loss = 2104946.16 (18.744 sec) ('Training Accuracy:', 0.90333456) ('Testing Accuracy:', 0.56)
Step 247: loss = 1591197.25 (18.706 sec) ('Training Accuracy:', 0.86624205) ('Testing Accuracy:', 0.55000001)
Step 248: loss = 1774371.47 (18.658 sec) ('Training Accuracy:', 0.90820533) ('Testing Accuracy:', 0.56333333)
Step 249: loss = 1897967.26 (18.809 sec) ('Training Accuracy:', 0.9423005) ('Testing Accuracy:', 0.56)
Step 250: loss = 2538284.75 (18.856 sec) ('Training Accuracy:', 0.9393031) ('Testing Accuracy:', 0.56333333)
Step 251: loss = 3152986.30 (19.001 sec) ('Training Accuracy:', 0.96627951) ('Testing Accuracy:', 0.56999999)
Step 252: loss = 2021620.47 (18.756 sec) ('Training Accuracy:', 0.96702886) ('Testing Accuracy:', 0.57333332)
Step 253: loss = 1925774.48 (23.611 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.60666668)
Step 254: loss = 1530740.54 (23.576 sec) ('Training Accuracy:', 0.95354062) ('Testing Accuracy:', 0.57999998)
Step 255: loss = 667232.01 (19.331 sec) ('Training Accuracy:', 0.94342452) ('Testing Accuracy:', 0.56)
Step 256: loss = 445244.97 (23.482 sec) ('Training Accuracy:', 0.95279133) ('Testing Accuracy:', 0.56333333)
Step 257: loss = 382514.83 (21.249 sec) ('Training Accuracy:', 0.95054328) ('Testing Accuracy:', 0.56)
Step 258: loss = 396881.96 (23.714 sec) ('Training Accuracy:', 0.96590483) ('Testing Accuracy:', 0.56)
Step 259: loss = 244298.68 (19.724 sec) ('Training Accuracy:', 0.94679654) ('Testing Accuracy:', 0.55000001)
Step 260: loss = 449878.29 (18.746 sec) ('Training Accuracy:', 0.93255901) ('Testing Accuracy:', 0.55000001)
Step 261: loss = 585870.39 (18.579 sec) ('Training Accuracy:', 0.95616335) ('Testing Accuracy:', 0.56666666)
Step 262: loss = 236986.59 (18.984 sec) ('Training Accuracy:', 0.9569127) ('Testing Accuracy:', 0.56333333)
Step 263: loss = 358134.38 (19.301 sec) ('Training Accuracy:', 0.94042712) ('Testing Accuracy:', 0.54666668)
Step 264: loss = 504308.16 (19.020 sec) ('Training Accuracy:', 0.93630576) ('Testing Accuracy:', 0.56)
Step 265: loss = 601731.66 (19.249 sec) ('Training Accuracy:', 0.96103412) ('Testing Accuracy:', 0.55000001)
Step 266: loss = 392540.63 (18.656 sec) ('Training Accuracy:', 0.92356688) ('Testing Accuracy:', 0.56)
Step 267: loss = 727373.18 (19.079 sec) ('Training Accuracy:', 0.96103412) ('Testing Accuracy:', 0.57999998)
Step 268: loss = 303537.76 (18.491 sec) ('Training Accuracy:', 0.94866991) ('Testing Accuracy:', 0.56)
Step 269: loss = 285368.65 (19.031 sec) ('Training Accuracy:', 0.95503932) ('Testing Accuracy:', 0.56)
Step 270: loss = 264224.48 (18.792 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.56333333)
Step 271: loss = 288954.95 (18.890 sec) ('Training Accuracy:', 0.96290743) ('Testing Accuracy:', 0.57333332)
Step 272: loss = 179199.31 (18.494 sec) ('Training Accuracy:', 0.95953542) ('Testing Accuracy:', 0.57333332)
Step 273: loss = 207059.68 (18.567 sec) ('Training Accuracy:', 0.96590483) ('Testing Accuracy:', 0.57666665)
Step 274: loss = 265274.43 (18.797 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.56999999)
Step 275: loss = 412165.29 (18.534 sec) ('Training Accuracy:', 0.94904459) ('Testing Accuracy:', 0.55333334)
Step 276: loss = 270334.72 (18.751 sec) ('Training Accuracy:', 0.955414) ('Testing Accuracy:', 0.56)
Step 277: loss = 209313.73 (18.654 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.56333333)
Step 278: loss = 294275.04 (19.170 sec) ('Training Accuracy:', 0.94642186) ('Testing Accuracy:', 0.55333334)
Step 279: loss = 386953.01 (19.307 sec) ('Training Accuracy:', 0.93031096) ('Testing Accuracy:', 0.55333334)
Step 280: loss = 428894.59 (19.611 sec) ('Training Accuracy:', 0.94829524) ('Testing Accuracy:', 0.56)
Step 281: loss = 319422.20 (19.954 sec) ('Training Accuracy:', 0.94941926) ('Testing Accuracy:', 0.56)
Step 282: loss = 345292.67 (19.692 sec) ('Training Accuracy:', 0.94155115) ('Testing Accuracy:', 0.56)
Step 283: loss = 361160.38 (20.102 sec) ('Training Accuracy:', 0.94529784) ('Testing Accuracy:', 0.56333333)
Step 284: loss = 357877.72 (20.073 sec) ('Training Accuracy:', 0.94117647) ('Testing Accuracy:', 0.55666667)
Step 285: loss = 332382.53 (20.017 sec) ('Training Accuracy:', 0.95354062) ('Testing Accuracy:', 0.56333333)
Step 286: loss = 246122.60 (20.099 sec) ('Training Accuracy:', 0.95653802) ('Testing Accuracy:', 0.56333333)
Step 287: loss = 262981.84 (20.658 sec) ('Training Accuracy:', 0.96253276) ('Testing Accuracy:', 0.57999998)
Step 288: loss = 262501.74 (20.169 sec) ('Training Accuracy:', 0.95316601) ('Testing Accuracy:', 0.56333333)
Step 289: loss = 277193.47 (20.705 sec) ('Training Accuracy:', 0.95316601) ('Testing Accuracy:', 0.56)
Step 290: loss = 205147.18 (20.359 sec) ('Training Accuracy:', 0.94866991) ('Testing Accuracy:', 0.55666667)
Step 291: loss = 366031.94 (20.238 sec) ('Training Accuracy:', 0.95728737) ('Testing Accuracy:', 0.56666666)
Step 292: loss = 510765.25 (21.488 sec) ('Training Accuracy:', 0.96515548) ('Testing Accuracy:', 0.55333334)
Step 293: loss = 339358.57 (21.577 sec) ('Training Accuracy:', 0.97189957) ('Testing Accuracy:', 0.5933333)
Step 294: loss = 393983.11 (20.947 sec) ('Training Accuracy:', 0.94454855) ('Testing Accuracy:', 0.56333333)
Step 295: loss = 455986.42 (21.576 sec) ('Training Accuracy:', 0.93255901) ('Testing Accuracy:', 0.57999998)
Step 296: loss = 492631.43 (20.852 sec) ('Training Accuracy:', 0.95204198) ('Testing Accuracy:', 0.56999999)
Step 297: loss = 330349.36 (20.680 sec) ('Training Accuracy:', 0.96290743) ('Testing Accuracy:', 0.56999999)
Step 298: loss = 418616.94 (20.569 sec) ('Training Accuracy:', 0.97452229) ('Testing Accuracy:', 0.57999998)
Step 299: loss = 418981.60 (20.743 sec) ('Training Accuracy:', 0.96702886) ('Testing Accuracy:', 0.56999999)
Step 300: loss = 321820.07 (21.246 sec) ('Training Accuracy:', 0.9584114) ('Testing Accuracy:', 0.57666665)
Step 301: loss = 590561.46 (20.901 sec) ('Training Accuracy:', 0.94567251) ('Testing Accuracy:', 0.55333334)
Step 302: loss = 915065.43 (20.220 sec) ('Training Accuracy:', 0.91644812) ('Testing Accuracy:', 0.56)
Step 303: loss = 739542.97 (20.692 sec) ('Training Accuracy:', 0.88535035) ('Testing Accuracy:', 0.56)
Step 304: loss = 1182975.73 (20.356 sec) ('Training Accuracy:', 0.95653802) ('Testing Accuracy:', 0.56999999)
Step 305: loss = 277350.03 (20.569 sec) ('Training Accuracy:', 0.92394155) ('Testing Accuracy:', 0.56666666)
Step 306: loss = 2299128.64 (20.046 sec) ('Training Accuracy:', 0.96927691) ('Testing Accuracy:', 0.58333331)
Step 307: loss = 492118.19 (20.576 sec) ('Training Accuracy:', 0.96403146) ('Testing Accuracy:', 0.5933333)
Step 308: loss = 767958.64 (19.996 sec) ('Training Accuracy:', 0.93742973) ('Testing Accuracy:', 0.54000002)
Step 309: loss = 716800.89 (20.211 sec) ('Training Accuracy:', 0.91270137) ('Testing Accuracy:', 0.55000001)
Step 310: loss = 1289987.46 (20.053 sec) ('Training Accuracy:', 0.87298614) ('Testing Accuracy:', 0.54666668)
Step 311: loss = 687521.51 (19.648 sec) ('Training Accuracy:', 0.88122892) ('Testing Accuracy:', 0.56333333)
Step 312: loss = 1376906.65 (21.062 sec) ('Training Accuracy:', 0.93405771) ('Testing Accuracy:', 0.56666666)
Step 313: loss = 1476966.94 (19.497 sec) ('Training Accuracy:', 0.91307604) ('Testing Accuracy:', 0.54000002)
Step 314: loss = 377234.00 (19.766 sec) ('Training Accuracy:', 0.91195202) ('Testing Accuracy:', 0.55000001)
Step 315: loss = 1771370.27 (19.883 sec) ('Training Accuracy:', 0.83889097) ('Testing Accuracy:', 0.56333333)
Step 316: loss = 1546759.52 (19.775 sec) ('Training Accuracy:', 0.90932935) ('Testing Accuracy:', 0.55333334)
Step 317: loss = 1247847.20 (19.207 sec) ('Training Accuracy:', 0.95953542) ('Testing Accuracy:', 0.57999998)
Step 318: loss = 350348.94 (19.654 sec) ('Training Accuracy:', 0.89846385) ('Testing Accuracy:', 0.55666667)
Step 319: loss = 951479.44 (19.350 sec) ('Training Accuracy:', 0.8801049) ('Testing Accuracy:', 0.56)
Step 320: loss = 2382463.16 (19.314 sec) ('Training Accuracy:', 0.97115022) ('Testing Accuracy:', 0.58666664)
Step 321: loss = 1883305.55 (19.486 sec) ('Training Accuracy:', 0.91494942) ('Testing Accuracy:', 0.54333335)
Step 322: loss = 2174300.59 (20.473 sec) ('Training Accuracy:', 0.86024725) ('Testing Accuracy:', 0.54000002)
Step 323: loss = 2349490.51 (21.101 sec) ('Training Accuracy:', 0.93443239) ('Testing Accuracy:', 0.57333332)
Step 324: loss = 1631848.65 (23.972 sec) ('Training Accuracy:', 0.91719747) ('Testing Accuracy:', 0.57666665)
Step 325: loss = 826275.38 (24.338 sec) ('Training Accuracy:', 0.93143499) ('Testing Accuracy:', 0.56333333)
Step 326: loss = 934518.31 (21.978 sec) ('Training Accuracy:', 0.86511803) ('Testing Accuracy:', 0.53666669)
Step 327: loss = 771802.32 (21.900 sec) ('Training Accuracy:', 0.88047957) ('Testing Accuracy:', 0.52999997)
Step 328: loss = 1678407.27 (19.368 sec) ('Training Accuracy:', 0.88759834) ('Testing Accuracy:', 0.56666666)
Step 329: loss = 953371.66 (19.452 sec) ('Training Accuracy:', 0.92881227) ('Testing Accuracy:', 0.53666669)
Step 330: loss = 509733.47 (19.291 sec) ('Training Accuracy:', 0.95241666) ('Testing Accuracy:', 0.57666665)
Step 331: loss = 559819.01 (19.406 sec) ('Training Accuracy:', 0.9569127) ('Testing Accuracy:', 0.57333332)
Step 332: loss = 404575.08 (19.268 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.57333332)
Step 333: loss = 371172.84 (19.516 sec) ('Training Accuracy:', 0.97302359) ('Testing Accuracy:', 0.57999998)
Step 334: loss = 365972.12 (19.094 sec) ('Training Accuracy:', 0.96702886) ('Testing Accuracy:', 0.58333331)
Step 335: loss = 183500.40 (19.383 sec) ('Training Accuracy:', 0.97040087) ('Testing Accuracy:', 0.59666669)
Step 336: loss = 279910.67 (19.178 sec) ('Training Accuracy:', 0.97564632) ('Testing Accuracy:', 0.60666668)
Step 337: loss = 1240769.55 (19.587 sec) ('Training Accuracy:', 0.88572496) ('Testing Accuracy:', 0.55333334)
Step 338: loss = 989629.76 (19.086 sec) ('Training Accuracy:', 0.93106031) ('Testing Accuracy:', 0.58333331)
Step 339: loss = 1280432.30 (19.263 sec) ('Training Accuracy:', 0.90370923) ('Testing Accuracy:', 0.55666667)
Step 340: loss = 1387839.50 (18.996 sec) ('Training Accuracy:', 0.90071189) ('Testing Accuracy:', 0.54333335)
Step 341: loss = 959423.27 (19.474 sec) ('Training Accuracy:', 0.91869617) ('Testing Accuracy:', 0.56666666)
Step 342: loss = 1519716.87 (19.637 sec) ('Training Accuracy:', 0.84526038) ('Testing Accuracy:', 0.53666669)
Step 343: loss = 3547225.60 (18.827 sec) ('Training Accuracy:', 0.91982013) ('Testing Accuracy:', 0.56)
Step 344: loss = 1385736.52 (19.333 sec) ('Training Accuracy:', 0.89321846) ('Testing Accuracy:', 0.55333334)
Step 345: loss = 1317245.96 (19.108 sec) ('Training Accuracy:', 0.96065944) ('Testing Accuracy:', 0.5933333)
Step 346: loss = 875414.17 (19.316 sec) ('Training Accuracy:', 0.96590483) ('Testing Accuracy:', 0.57666665)
Step 347: loss = 653999.89 (19.715 sec) ('Training Accuracy:', 0.93143499) ('Testing Accuracy:', 0.54000002)
Step 348: loss = 868965.49 (19.463 sec) ('Training Accuracy:', 0.90670663) ('Testing Accuracy:', 0.55333334)
Step 349: loss = 1456880.22 (19.644 sec) ('Training Accuracy:', 0.95466465) ('Testing Accuracy:', 0.57999998)
Step 350: loss = 656078.70 (18.695 sec) ('Training Accuracy:', 0.96815288) ('Testing Accuracy:', 0.58333331)
Step 351: loss = 556967.87 (19.757 sec) ('Training Accuracy:', 0.96927691) ('Testing Accuracy:', 0.60666668)
Step 352: loss = 844270.74 (19.391 sec) ('Training Accuracy:', 0.97489697) ('Testing Accuracy:', 0.58333331)
Step 353: loss = 1381874.44 (19.163 sec) ('Training Accuracy:', 0.91719747) ('Testing Accuracy:', 0.54666668)
Step 354: loss = 677886.80 (19.556 sec) ('Training Accuracy:', 0.95503932) ('Testing Accuracy:', 0.58666664)
Step 355: loss = 529450.37 (19.139 sec) ('Training Accuracy:', 0.96702886) ('Testing Accuracy:', 0.57666665)
Step 356: loss = 565118.02 (19.317 sec) ('Training Accuracy:', 0.97077554) ('Testing Accuracy:', 0.58666664)
Step 357: loss = 708147.56 (19.624 sec) ('Training Accuracy:', 0.9584114) ('Testing Accuracy:', 0.59666669)
Step 358: loss = 993169.12 (19.727 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.57333332)
Step 359: loss = 359483.45 (19.692 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.58333331)
Step 360: loss = 343091.67 (18.985 sec) ('Training Accuracy:', 0.94304985) ('Testing Accuracy:', 0.55000001)
Step 361: loss = 406277.48 (19.424 sec) ('Training Accuracy:', 0.96215808) ('Testing Accuracy:', 0.58333331)
Step 362: loss = 393048.93 (19.553 sec) ('Training Accuracy:', 0.96927691) ('Testing Accuracy:', 0.60000002)
Step 363: loss = 296825.50 (19.632 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.55666667)
Step 364: loss = 297763.74 (19.305 sec) ('Training Accuracy:', 0.94979393) ('Testing Accuracy:', 0.55000001)
Step 365: loss = 499308.50 (19.229 sec) ('Training Accuracy:', 0.97189957) ('Testing Accuracy:', 0.59666669)
Step 366: loss = 280085.76 (19.489 sec) ('Training Accuracy:', 0.95166731) ('Testing Accuracy:', 0.55666667)
Step 367: loss = 468691.65 (19.122 sec) ('Training Accuracy:', 0.90558261) ('Testing Accuracy:', 0.53666669)
Step 368: loss = 666324.14 (19.885 sec) ('Training Accuracy:', 0.91232669) ('Testing Accuracy:', 0.56)
Step 369: loss = 1222028.23 (19.482 sec) ('Training Accuracy:', 0.93068564) ('Testing Accuracy:', 0.55333334)
Step 370: loss = 648291.21 (19.313 sec) ('Training Accuracy:', 0.95428997) ('Testing Accuracy:', 0.55333334)
Step 371: loss = 520332.42 (19.748 sec) ('Training Accuracy:', 0.97339827) ('Testing Accuracy:', 0.60000002)
Step 372: loss = 305955.07 (19.639 sec) ('Training Accuracy:', 0.97115022) ('Testing Accuracy:', 0.56666666)
Step 373: loss = 861091.16 (24.042 sec) ('Training Accuracy:', 0.93668038) ('Testing Accuracy:', 0.54666668)
Step 374: loss = 3730714.13 (23.526 sec) ('Training Accuracy:', 0.89659047) ('Testing Accuracy:', 0.55333334)
Step 375: loss = 957610.64 (23.061 sec) ('Training Accuracy:', 0.92506558) ('Testing Accuracy:', 0.55666667)
Step 376: loss = 655158.06 (24.187 sec) ('Training Accuracy:', 0.9378044) ('Testing Accuracy:', 0.56666666)
Step 377: loss = 764899.61 (23.325 sec) ('Training Accuracy:', 0.93705505) ('Testing Accuracy:', 0.60000002)
Step 378: loss = 471086.57 (23.507 sec) ('Training Accuracy:', 0.92843759) ('Testing Accuracy:', 0.55000001)
Step 379: loss = 678653.32 (23.421 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.62333333)
Step 380: loss = 713180.54 (25.603 sec) ('Training Accuracy:', 0.93967777) ('Testing Accuracy:', 0.57333332)
Step 381: loss = 325509.68 (20.549 sec) ('Training Accuracy:', 0.90820533) ('Testing Accuracy:', 0.56)
Step 382: loss = 640644.85 (22.145 sec) ('Training Accuracy:', 0.9569127) ('Testing Accuracy:', 0.60666668)
Step 383: loss = 363779.48 (21.699 sec) ('Training Accuracy:', 0.96515548) ('Testing Accuracy:', 0.57333332)
Step 384: loss = 489012.46 (24.064 sec) ('Training Accuracy:', 0.97377294) ('Testing Accuracy:', 0.60666668)
Step 385: loss = 963574.02 (18.816 sec) ('Training Accuracy:', 0.94866991) ('Testing Accuracy:', 0.60333335)
Step 386: loss = 1004067.59 (19.453 sec) ('Training Accuracy:', 0.90932935) ('Testing Accuracy:', 0.56)
Step 387: loss = 628198.40 (18.912 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.59666669)
Step 388: loss = 266313.38 (18.957 sec) ('Training Accuracy:', 0.97264892) ('Testing Accuracy:', 0.58999997)
Step 389: loss = 460146.56 (19.007 sec) ('Training Accuracy:', 0.96028477) ('Testing Accuracy:', 0.60000002)
Step 390: loss = 530747.27 (19.141 sec) ('Training Accuracy:', 0.97677034) ('Testing Accuracy:', 0.56999999)
Step 391: loss = 899848.55 (19.062 sec) ('Training Accuracy:', 0.97564632) ('Testing Accuracy:', 0.57999998)
Step 392: loss = 963993.59 (19.000 sec) ('Training Accuracy:', 0.96515548) ('Testing Accuracy:', 0.57999998)
Step 393: loss = 789662.77 (19.517 sec) ('Training Accuracy:', 0.92993629) ('Testing Accuracy:', 0.56333333)
Step 394: loss = 858612.05 (19.278 sec) ('Training Accuracy:', 0.9423005) ('Testing Accuracy:', 0.57999998)
Step 395: loss = 1295348.84 (18.886 sec) ('Training Accuracy:', 0.88797301) ('Testing Accuracy:', 0.55000001)
Step 396: loss = 1624568.53 (18.704 sec) ('Training Accuracy:', 0.95054328) ('Testing Accuracy:', 0.57666665)
Step 397: loss = 3438507.09 (19.355 sec) ('Training Accuracy:', 0.93518174) ('Testing Accuracy:', 0.57999998)
Step 398: loss = 1092920.72 (18.850 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.55666667)
Step 399: loss = 1040252.20 (18.965 sec) ('Training Accuracy:', 0.96965158) ('Testing Accuracy:', 0.57666665)
Step 400: loss = 873784.67 (19.265 sec) ('Training Accuracy:', 0.93031096) ('Testing Accuracy:', 0.55000001)
Step 401: loss = 601359.71 (19.245 sec) ('Training Accuracy:', 0.96852756) ('Testing Accuracy:', 0.58333331)
Step 402: loss = 514614.92 (19.037 sec) ('Training Accuracy:', 0.91382539) ('Testing Accuracy:', 0.54666668)
Step 403: loss = 780267.72 (19.220 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.58666664)
Step 404: loss = 467166.28 (18.852 sec) ('Training Accuracy:', 0.95091796) ('Testing Accuracy:', 0.55333334)
Step 405: loss = 911971.64 (19.347 sec) ('Training Accuracy:', 0.97751969) ('Testing Accuracy:', 0.58666664)
Step 406: loss = 741138.77 (19.225 sec) ('Training Accuracy:', 0.95241666) ('Testing Accuracy:', 0.57999998)
Step 407: loss = 951487.12 (19.058 sec) ('Training Accuracy:', 0.97189957) ('Testing Accuracy:', 0.60000002)
Step 408: loss = 583725.32 (19.441 sec) ('Training Accuracy:', 0.94941926) ('Testing Accuracy:', 0.56666666)
Step 409: loss = 438476.23 (19.013 sec) ('Training Accuracy:', 0.97302359) ('Testing Accuracy:', 0.59666669)
Step 410: loss = 495430.66 (19.341 sec) ('Training Accuracy:', 0.93967777) ('Testing Accuracy:', 0.56)
Step 411: loss = 449787.61 (19.191 sec) ('Training Accuracy:', 0.97302359) ('Testing Accuracy:', 0.58999997)
Step 412: loss = 311049.72 (19.270 sec) ('Training Accuracy:', 0.91832149) ('Testing Accuracy:', 0.54666668)
Step 413: loss = 721353.71 (18.983 sec) ('Training Accuracy:', 0.96215808) ('Testing Accuracy:', 0.57666665)
Step 414: loss = 320671.58 (19.367 sec) ('Training Accuracy:', 0.9584114) ('Testing Accuracy:', 0.57666665)
Step 415: loss = 501334.40 (19.128 sec) ('Training Accuracy:', 0.96253276) ('Testing Accuracy:', 0.58666664)
Step 416: loss = 441209.00 (19.559 sec) ('Training Accuracy:', 0.96777821) ('Testing Accuracy:', 0.58999997)
Step 417: loss = 576242.66 (20.233 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.61333334)
Step 418: loss = 8111827.07 (19.083 sec) ('Training Accuracy:', 0.72461593) ('Testing Accuracy:', 0.50999999)
Step 419: loss = 36788859.62 (18.995 sec) ('Training Accuracy:', 0.90146124) ('Testing Accuracy:', 0.61666667)
Step 420: loss = 5711719.10 (19.147 sec) ('Training Accuracy:', 0.96103412) ('Testing Accuracy:', 0.57333332)
Step 421: loss = 3226278.73 (18.819 sec) ('Training Accuracy:', 0.93518174) ('Testing Accuracy:', 0.57666665)
Step 422: loss = 1268828.81 (18.954 sec) ('Training Accuracy:', 0.97152489) ('Testing Accuracy:', 0.57666665)
Step 423: loss = 444991.80 (18.785 sec) ('Training Accuracy:', 0.95503932) ('Testing Accuracy:', 0.56333333)
Step 424: loss = 494005.33 (18.954 sec) ('Training Accuracy:', 0.94529784) ('Testing Accuracy:', 0.55333334)
Step 425: loss = 866440.68 (18.697 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.56666666)
Step 426: loss = 535066.41 (18.667 sec) ('Training Accuracy:', 0.97489697) ('Testing Accuracy:', 0.59666669)
Step 427: loss = 160649.31 (18.894 sec) ('Training Accuracy:', 0.96290743) ('Testing Accuracy:', 0.58333331)
Step 428: loss = 401642.68 (19.005 sec) ('Training Accuracy:', 0.96627951) ('Testing Accuracy:', 0.56666666)
Step 429: loss = 452435.31 (18.796 sec) ('Training Accuracy:', 0.95091796) ('Testing Accuracy:', 0.56333333)
Step 430: loss = 582845.63 (19.005 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.58999997)
Step 431: loss = 537027.00 (18.732 sec) ('Training Accuracy:', 0.96403146) ('Testing Accuracy:', 0.57666665)
Step 432: loss = 402189.07 (19.262 sec) ('Training Accuracy:', 0.95279133) ('Testing Accuracy:', 0.56333333)
Step 433: loss = 642207.19 (19.011 sec) ('Training Accuracy:', 0.96065944) ('Testing Accuracy:', 0.56333333)
Step 434: loss = 235278.59 (19.143 sec) ('Training Accuracy:', 0.96665418) ('Testing Accuracy:', 0.57999998)
Step 435: loss = 167250.43 (18.835 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.57333332)
Step 436: loss = 365816.99 (18.893 sec) ('Training Accuracy:', 0.95091796) ('Testing Accuracy:', 0.56666666)
Step 437: loss = 333363.16 (19.020 sec) ('Training Accuracy:', 0.97264892) ('Testing Accuracy:', 0.57999998)
Step 438: loss = 131672.05 (18.906 sec) ('Training Accuracy:', 0.97564632) ('Testing Accuracy:', 0.57999998)
Step 439: loss = 108510.65 (19.167 sec) ('Training Accuracy:', 0.97602099) ('Testing Accuracy:', 0.57333332)
Step 440: loss = 285900.48 (19.373 sec) ('Training Accuracy:', 0.95578867) ('Testing Accuracy:', 0.56666666)
Step 441: loss = 423199.09 (18.634 sec) ('Training Accuracy:', 0.94754589) ('Testing Accuracy:', 0.56666666)
Step 442: loss = 308870.00 (19.156 sec) ('Training Accuracy:', 0.95241666) ('Testing Accuracy:', 0.56999999)
Step 443: loss = 321266.15 (19.133 sec) ('Training Accuracy:', 0.9423005) ('Testing Accuracy:', 0.55666667)
Step 444: loss = 518270.08 (19.225 sec) ('Training Accuracy:', 0.97152489) ('Testing Accuracy:', 0.56999999)
Step 445: loss = 129279.09 (18.439 sec) ('Training Accuracy:', 0.97115022) ('Testing Accuracy:', 0.61000001)
Step 446: loss = 160710.94 (19.227 sec) ('Training Accuracy:', 0.95428997) ('Testing Accuracy:', 0.56666666)
Step 447: loss = 524659.44 (19.104 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.58666664)
Step 448: loss = 199309.45 (19.101 sec) ('Training Accuracy:', 0.97414762) ('Testing Accuracy:', 0.60333335)
Step 449: loss = 285235.94 (18.731 sec) ('Training Accuracy:', 0.97489697) ('Testing Accuracy:', 0.57999998)
Step 450: loss = 578254.50 (18.786 sec) ('Training Accuracy:', 0.97527164) ('Testing Accuracy:', 0.5933333)
Step 451: loss = 559414.16 (19.206 sec) ('Training Accuracy:', 0.95428997) ('Testing Accuracy:', 0.56)
Step 452: loss = 1093991.04 (18.754 sec) ('Training Accuracy:', 0.87073809) ('Testing Accuracy:', 0.52666664)
Step 453: loss = 989997.44 (20.057 sec) ('Training Accuracy:', 0.92693895) ('Testing Accuracy:', 0.54333335)
Step 454: loss = 1006533.07 (19.430 sec) ('Training Accuracy:', 0.93668038) ('Testing Accuracy:', 0.55666667)
Step 455: loss = 956959.55 (18.931 sec) ('Training Accuracy:', 0.93742973) ('Testing Accuracy:', 0.55666667)
Step 456: loss = 471455.00 (19.784 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.56666666)
Step 457: loss = 260920.55 (19.644 sec) ('Training Accuracy:', 0.96702886) ('Testing Accuracy:', 0.58666664)
Step 458: loss = 491269.73 (20.151 sec) ('Training Accuracy:', 0.95803672) ('Testing Accuracy:', 0.55666667)
Step 459: loss = 252419.92 (20.210 sec) ('Training Accuracy:', 0.97002625) ('Testing Accuracy:', 0.58333331)
Step 460: loss = 229969.13 (19.813 sec) ('Training Accuracy:', 0.97040087) ('Testing Accuracy:', 0.56999999)
Step 461: loss = 203182.23 (20.559 sec) ('Training Accuracy:', 0.96103412) ('Testing Accuracy:', 0.56)
Step 462: loss = 542953.42 (20.868 sec) ('Training Accuracy:', 0.96365678) ('Testing Accuracy:', 0.59666669)
Step 463: loss = 212298.90 (20.785 sec) ('Training Accuracy:', 0.94604719) ('Testing Accuracy:', 0.56333333)
Step 464: loss = 917311.89 (20.918 sec) ('Training Accuracy:', 0.89883852) ('Testing Accuracy:', 0.53333336)
Step 465: loss = 850307.66 (21.390 sec) ('Training Accuracy:', 0.91420007) ('Testing Accuracy:', 0.55333334)
Step 466: loss = 1023736.55 (20.634 sec) ('Training Accuracy:', 0.92056948) ('Testing Accuracy:', 0.55666667)
Step 467: loss = 2692151.47 (20.332 sec) ('Training Accuracy:', 0.96253276) ('Testing Accuracy:', 0.56999999)
Step 468: loss = 2562172.32 (20.042 sec) ('Training Accuracy:', 0.9216935) ('Testing Accuracy:', 0.56333333)
Step 469: loss = 5213046.23 (20.120 sec) ('Training Accuracy:', 0.96515548) ('Testing Accuracy:', 0.5933333)
Step 470: loss = 3553616.74 (19.727 sec) ('Training Accuracy:', 0.93293369) ('Testing Accuracy:', 0.54666668)
Step 471: loss = 5209717.74 (19.221 sec) ('Training Accuracy:', 0.92056948) ('Testing Accuracy:', 0.55666667)
Step 472: loss = 2984381.06 (19.130 sec) ('Training Accuracy:', 0.84526038) ('Testing Accuracy:', 0.53666669)
Step 473: loss = 17806772.37 (19.539 sec) ('Training Accuracy:', 0.94155115) ('Testing Accuracy:', 0.61666667)
Step 474: loss = 12608122.61 (19.368 sec) ('Training Accuracy:', 0.75533909) ('Testing Accuracy:', 0.51666665)
Step 475: loss = 12246604.77 (19.572 sec) ('Training Accuracy:', 0.87223679) ('Testing Accuracy:', 0.56333333)
Step 476: loss = 21480273.67 (19.536 sec) ('Training Accuracy:', 0.9231922) ('Testing Accuracy:', 0.62666667)
Step 477: loss = 6581888.50 (19.569 sec) ('Training Accuracy:', 0.90408391) ('Testing Accuracy:', 0.56)
Step 478: loss = 1674687.59 (19.160 sec) ('Training Accuracy:', 0.97002625) ('Testing Accuracy:', 0.56333333)
Step 479: loss = 1202672.82 (19.061 sec) ('Training Accuracy:', 0.97527164) ('Testing Accuracy:', 0.55666667)
Step 480: loss = 1109854.22 (19.209 sec) ('Training Accuracy:', 0.97002625) ('Testing Accuracy:', 0.56999999)
Step 481: loss = 276510.97 (18.741 sec) ('Training Accuracy:', 0.9539153) ('Testing Accuracy:', 0.57333332)
Step 482: loss = 355774.39 (19.380 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.56999999)
Step 483: loss = 188909.28 (18.632 sec) ('Training Accuracy:', 0.96852756) ('Testing Accuracy:', 0.58666664)
Step 484: loss = 167545.79 (19.392 sec) ('Training Accuracy:', 0.96403146) ('Testing Accuracy:', 0.57999998)
Step 485: loss = 368611.26 (19.139 sec) ('Training Accuracy:', 0.97189957) ('Testing Accuracy:', 0.57666665)
Step 486: loss = 477897.59 (18.811 sec) ('Training Accuracy:', 0.94417387) ('Testing Accuracy:', 0.54333335)
Step 487: loss = 637223.26 (19.284 sec) ('Training Accuracy:', 0.94604719) ('Testing Accuracy:', 0.54666668)
Step 488: loss = 894284.56 (19.041 sec) ('Training Accuracy:', 0.93668038) ('Testing Accuracy:', 0.54000002)
Step 489: loss = 693407.72 (19.652 sec) ('Training Accuracy:', 0.9201948) ('Testing Accuracy:', 0.54000002)
Step 490: loss = 810623.46 (18.930 sec) ('Training Accuracy:', 0.9584114) ('Testing Accuracy:', 0.56999999)
Step 491: loss = 463959.88 (18.999 sec) ('Training Accuracy:', 0.95129263) ('Testing Accuracy:', 0.55333334)
Step 492: loss = 854348.97 (19.008 sec) ('Training Accuracy:', 0.90708131) ('Testing Accuracy:', 0.55666667)
Step 493: loss = 1419203.46 (19.083 sec) ('Training Accuracy:', 0.97040087) ('Testing Accuracy:', 0.56)
Step 494: loss = 877289.20 (19.477 sec) ('Training Accuracy:', 0.94417387) ('Testing Accuracy:', 0.56333333)
Step 495: loss = 457857.19 (19.283 sec) ('Training Accuracy:', 0.95728737) ('Testing Accuracy:', 0.57999998)
Step 496: loss = 313340.03 (18.926 sec) ('Training Accuracy:', 0.94754589) ('Testing Accuracy:', 0.57666665)
Step 497: loss = 414592.71 (19.163 sec) ('Training Accuracy:', 0.94529784) ('Testing Accuracy:', 0.57333332)
Step 498: loss = 643465.54 (19.043 sec) ('Training Accuracy:', 0.92993629) ('Testing Accuracy:', 0.56999999)
Step 499: loss = 733003.79 (19.234 sec) ('Training Accuracy:', 0.93705505) ('Testing Accuracy:', 0.56999999)
Step 500: loss = 1248046.27 (18.877 sec) ('Training Accuracy:', 0.96215808) ('Testing Accuracy:', 0.56)
Step 501: loss = 529425.42 (19.129 sec) ('Training Accuracy:', 0.93068564) ('Testing Accuracy:', 0.55666667)
Step 502: loss = 506171.52 (19.418 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.56666666)
Step 503: loss = 581678.24 (19.125 sec) ('Training Accuracy:', 0.90633196) ('Testing Accuracy:', 0.55333334)
Step 504: loss = 724136.99 (19.352 sec) ('Training Accuracy:', 0.89958787) ('Testing Accuracy:', 0.54333335)
Step 505: loss = 1116952.96 (18.898 sec) ('Training Accuracy:', 0.93855375) ('Testing Accuracy:', 0.56)
Step 506: loss = 1077193.89 (19.593 sec) ('Training Accuracy:', 0.91757214) ('Testing Accuracy:', 0.56)
Step 507: loss = 931108.88 (18.815 sec) ('Training Accuracy:', 0.90445858) ('Testing Accuracy:', 0.56)
Step 508: loss = 783305.91 (19.338 sec) ('Training Accuracy:', 0.9276883) ('Testing Accuracy:', 0.56999999)
Step 509: loss = 1287758.25 (18.919 sec) ('Training Accuracy:', 0.94754589) ('Testing Accuracy:', 0.57333332)
Step 510: loss = 439491.52 (19.044 sec) ('Training Accuracy:', 0.92656428) ('Testing Accuracy:', 0.56)
Step 511: loss = 890519.02 (19.126 sec) ('Training Accuracy:', 0.91157734) ('Testing Accuracy:', 0.55333334)
Step 512: loss = 1156475.36 (19.142 sec) ('Training Accuracy:', 0.9378044) ('Testing Accuracy:', 0.55666667)
Step 513: loss = 464505.78 (19.835 sec) ('Training Accuracy:', 0.9423005) ('Testing Accuracy:', 0.56)
Step 514: loss = 648137.28 (20.001 sec) ('Training Accuracy:', 0.91982013) ('Testing Accuracy:', 0.56333333)
Step 515: loss = 1198233.61 (20.096 sec) ('Training Accuracy:', 0.96965158) ('Testing Accuracy:', 0.56999999)
Step 516: loss = 1030794.61 (20.501 sec) ('Training Accuracy:', 0.97714502) ('Testing Accuracy:', 0.5933333)
Step 517: loss = 1316629.21 (20.443 sec) ('Training Accuracy:', 0.95728737) ('Testing Accuracy:', 0.54000002)
Step 518: loss = 677498.73 (20.824 sec) ('Training Accuracy:', 0.93892843) ('Testing Accuracy:', 0.55333334)
Step 519: loss = 712937.71 (20.583 sec) ('Training Accuracy:', 0.96965158) ('Testing Accuracy:', 0.56666666)
Step 520: loss = 542259.32 (20.575 sec) ('Training Accuracy:', 0.97377294) ('Testing Accuracy:', 0.56999999)
Step 521: loss = 457864.32 (19.951 sec) ('Training Accuracy:', 0.93630576) ('Testing Accuracy:', 0.54666668)
Step 522: loss = 558957.34 (20.509 sec) ('Training Accuracy:', 0.93668038) ('Testing Accuracy:', 0.55000001)
Step 523: loss = 787281.96 (25.483 sec) ('Training Accuracy:', 0.90970403) ('Testing Accuracy:', 0.53666669)
Step 524: loss = 665727.26 (24.681 sec) ('Training Accuracy:', 0.9423005) ('Testing Accuracy:', 0.55666667)
Step 525: loss = 549171.57 (24.879 sec) ('Training Accuracy:', 0.87710756) ('Testing Accuracy:', 0.54666668)
Step 526: loss = 926213.81 (22.501 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.60333335)
Step 527: loss = 901695.34 (21.986 sec) ('Training Accuracy:', 0.97264892) ('Testing Accuracy:', 0.55666667)
Step 528: loss = 767663.63 (24.713 sec) ('Training Accuracy:', 0.9539153) ('Testing Accuracy:', 0.55000001)
Step 529: loss = 611848.54 (22.650 sec) ('Training Accuracy:', 0.97639567) ('Testing Accuracy:', 0.58333331)
Step 530: loss = 990816.85 (23.342 sec) ('Training Accuracy:', 0.94417387) ('Testing Accuracy:', 0.55000001)
Step 531: loss = 1122284.87 (21.725 sec) ('Training Accuracy:', 0.92544025) ('Testing Accuracy:', 0.55333334)
Step 532: loss = 652422.82 (21.806 sec) ('Training Accuracy:', 0.93892843) ('Testing Accuracy:', 0.55000001)
Step 533: loss = 626402.92 (23.407 sec) ('Training Accuracy:', 0.94717121) ('Testing Accuracy:', 0.55666667)
Step 534: loss = 661281.13 (23.041 sec) ('Training Accuracy:', 0.94417387) ('Testing Accuracy:', 0.54000002)
Step 535: loss = 492912.13 (24.455 sec) ('Training Accuracy:', 0.92843759) ('Testing Accuracy:', 0.55333334)
Step 536: loss = 573986.76 (18.459 sec) ('Training Accuracy:', 0.93405771) ('Testing Accuracy:', 0.54333335)
Step 537: loss = 759771.28 (19.713 sec) ('Training Accuracy:', 0.95166731) ('Testing Accuracy:', 0.54333335)
Step 538: loss = 416368.12 (19.623 sec) ('Training Accuracy:', 0.92131883) ('Testing Accuracy:', 0.53333336)
Step 539: loss = 654735.53 (20.508 sec) ('Training Accuracy:', 0.93705505) ('Testing Accuracy:', 0.53333336)
Step 540: loss = 671546.53 (19.138 sec) ('Training Accuracy:', 0.91045338) ('Testing Accuracy:', 0.53333336)
Step 541: loss = 695624.89 (19.334 sec) ('Training Accuracy:', 0.96815288) ('Testing Accuracy:', 0.57333332)
Step 542: loss = 860072.22 (19.116 sec) ('Training Accuracy:', 0.9378044) ('Testing Accuracy:', 0.55666667)
Step 543: loss = 1098139.81 (19.293 sec) ('Training Accuracy:', 0.92656428) ('Testing Accuracy:', 0.54666668)
Step 544: loss = 539632.23 (19.499 sec) ('Training Accuracy:', 0.95204198) ('Testing Accuracy:', 0.57333332)
Step 545: loss = 436194.15 (18.991 sec) ('Training Accuracy:', 0.94304985) ('Testing Accuracy:', 0.57999998)
Step 546: loss = 355845.07 (19.204 sec) ('Training Accuracy:', 0.94866991) ('Testing Accuracy:', 0.55666667)
Step 547: loss = 514512.09 (19.692 sec) ('Training Accuracy:', 0.96815288) ('Testing Accuracy:', 0.61333334)
Step 548: loss = 199163.35 (19.394 sec) ('Training Accuracy:', 0.95503932) ('Testing Accuracy:', 0.58333331)
Step 549: loss = 548881.95 (19.336 sec) ('Training Accuracy:', 0.94642186) ('Testing Accuracy:', 0.55666667)
Step 550: loss = 317810.74 (18.986 sec) ('Training Accuracy:', 0.955414) ('Testing Accuracy:', 0.56666666)
Step 551: loss = 354835.32 (19.311 sec) ('Training Accuracy:', 0.96328211) ('Testing Accuracy:', 0.57666665)
Step 552: loss = 316754.93 (19.697 sec) ('Training Accuracy:', 0.93742973) ('Testing Accuracy:', 0.55666667)
Step 553: loss = 474043.45 (19.784 sec) ('Training Accuracy:', 0.94342452) ('Testing Accuracy:', 0.56333333)
Step 554: loss = 448501.90 (19.267 sec) ('Training Accuracy:', 0.94754589) ('Testing Accuracy:', 0.55666667)
Step 555: loss = 350076.86 (19.020 sec) ('Training Accuracy:', 0.93555641) ('Testing Accuracy:', 0.55333334)
Step 556: loss = 486492.92 (19.334 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.58666664)
Step 557: loss = 272609.24 (19.043 sec) ('Training Accuracy:', 0.93143499) ('Testing Accuracy:', 0.55000001)
Step 558: loss = 576911.19 (19.624 sec) ('Training Accuracy:', 0.96328211) ('Testing Accuracy:', 0.58333331)
Step 559: loss = 400540.48 (19.389 sec) ('Training Accuracy:', 0.94829524) ('Testing Accuracy:', 0.55333334)
Step 560: loss = 261010.19 (19.579 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.57999998)
Step 561: loss = 502106.48 (19.176 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.57333332)
Step 562: loss = 604618.64 (19.667 sec) ('Training Accuracy:', 0.95354062) ('Testing Accuracy:', 0.56999999)
Step 563: loss = 962802.25 (19.571 sec) ('Training Accuracy:', 0.94342452) ('Testing Accuracy:', 0.56666666)
Step 564: loss = 550002.04 (19.260 sec) ('Training Accuracy:', 0.94342452) ('Testing Accuracy:', 0.56999999)
Step 565: loss = 407361.03 (19.256 sec) ('Training Accuracy:', 0.9539153) ('Testing Accuracy:', 0.57333332)
Step 566: loss = 520512.54 (19.553 sec) ('Training Accuracy:', 0.91907084) ('Testing Accuracy:', 0.54333335)
Step 567: loss = 690529.88 (19.358 sec) ('Training Accuracy:', 0.9261896) ('Testing Accuracy:', 0.55333334)
Step 568: loss = 904621.29 (19.826 sec) ('Training Accuracy:', 0.87148744) ('Testing Accuracy:', 0.55000001)
Step 569: loss = 785262.43 (19.517 sec) ('Training Accuracy:', 0.93668038) ('Testing Accuracy:', 0.56666666)
Step 570: loss = 706672.84 (19.191 sec) ('Training Accuracy:', 0.93742973) ('Testing Accuracy:', 0.57666665)
Step 571: loss = 951369.16 (20.187 sec) ('Training Accuracy:', 0.95428997) ('Testing Accuracy:', 0.56999999)
Step 572: loss = 439585.05 (19.309 sec) ('Training Accuracy:', 0.93555641) ('Testing Accuracy:', 0.55666667)
Step 573: loss = 248097.98 (19.889 sec) ('Training Accuracy:', 0.9261896) ('Testing Accuracy:', 0.56333333)
Step 574: loss = 1040029.95 (19.267 sec) ('Training Accuracy:', 0.92731363) ('Testing Accuracy:', 0.56999999)
Step 575: loss = 874416.51 (19.569 sec) ('Training Accuracy:', 0.91382539) ('Testing Accuracy:', 0.54666668)
Step 576: loss = 755725.91 (19.349 sec) ('Training Accuracy:', 0.95204198) ('Testing Accuracy:', 0.56333333)
Step 577: loss = 333058.73 (19.309 sec) ('Training Accuracy:', 0.95803672) ('Testing Accuracy:', 0.56)
Step 578: loss = 601937.80 (19.024 sec) ('Training Accuracy:', 0.94454855) ('Testing Accuracy:', 0.57666665)
Step 579: loss = 722746.05 (18.810 sec) ('Training Accuracy:', 0.93180966) ('Testing Accuracy:', 0.56666666)
Step 580: loss = 649476.14 (19.501 sec) ('Training Accuracy:', 0.94417387) ('Testing Accuracy:', 0.56)
Step 581: loss = 524050.54 (19.352 sec) ('Training Accuracy:', 0.88722366) ('Testing Accuracy:', 0.57666665)
Step 582: loss = 648687.48 (19.771 sec) ('Training Accuracy:', 0.95166731) ('Testing Accuracy:', 0.58999997)
Step 583: loss = 516938.87 (19.319 sec) ('Training Accuracy:', 0.93405771) ('Testing Accuracy:', 0.56999999)
Step 584: loss = 1303795.26 (19.311 sec) ('Training Accuracy:', 0.92544025) ('Testing Accuracy:', 0.56333333)
Step 585: loss = 782971.81 (19.231 sec) ('Training Accuracy:', 0.93293369) ('Testing Accuracy:', 0.56333333)
Step 586: loss = 1008747.66 (19.080 sec) ('Training Accuracy:', 0.8816036) ('Testing Accuracy:', 0.53333336)
Step 587: loss = 3216989.13 (19.404 sec) ('Training Accuracy:', 0.83626825) ('Testing Accuracy:', 0.55666667)
Step 588: loss = 1662080.92 (19.254 sec) ('Training Accuracy:', 0.95204198) ('Testing Accuracy:', 0.55000001)
Step 589: loss = 1413261.02 (18.802 sec) ('Training Accuracy:', 0.97339827) ('Testing Accuracy:', 0.56333333)
Step 590: loss = 724865.50 (18.844 sec) ('Training Accuracy:', 0.96777821) ('Testing Accuracy:', 0.57666665)
Step 591: loss = 448772.30 (19.320 sec) ('Training Accuracy:', 0.93443239) ('Testing Accuracy:', 0.58666664)
Step 592: loss = 797700.02 (19.214 sec) ('Training Accuracy:', 0.90295988) ('Testing Accuracy:', 0.55000001)
Step 593: loss = 1529566.32 (19.232 sec) ('Training Accuracy:', 0.96740353) ('Testing Accuracy:', 0.60666668)
Step 594: loss = 686185.04 (19.934 sec) ('Training Accuracy:', 0.92356688) ('Testing Accuracy:', 0.55000001)
Step 595: loss = 656186.81 (19.492 sec) ('Training Accuracy:', 0.94005245) ('Testing Accuracy:', 0.56)
Step 596: loss = 1046219.83 (19.035 sec) ('Training Accuracy:', 0.95878607) ('Testing Accuracy:', 0.56999999)
Step 597: loss = 613938.43 (19.414 sec) ('Training Accuracy:', 0.97339827) ('Testing Accuracy:', 0.58333331)
Step 598: loss = 508403.96 (19.121 sec) ('Training Accuracy:', 0.95354062) ('Testing Accuracy:', 0.57333332)
Step 599: loss = 566591.49 (19.176 sec) ('Training Accuracy:', 0.95878607) ('Testing Accuracy:', 0.5933333)
Step 600: loss = 448650.65 (18.547 sec) ('Training Accuracy:', 0.8947171) ('Testing Accuracy:', 0.55333334)
Step 601: loss = 789707.64 (19.402 sec) ('Training Accuracy:', 0.94117647) ('Testing Accuracy:', 0.57333332)
Step 602: loss = 624934.54 (19.223 sec) ('Training Accuracy:', 0.97302359) ('Testing Accuracy:', 0.61000001)
Step 603: loss = 226029.17 (18.978 sec) ('Training Accuracy:', 0.96065944) ('Testing Accuracy:', 0.58333331)
Step 604: loss = 433831.04 (19.422 sec) ('Training Accuracy:', 0.93106031) ('Testing Accuracy:', 0.56999999)
Step 605: loss = 611305.67 (19.222 sec) ('Training Accuracy:', 0.93742973) ('Testing Accuracy:', 0.5933333)
Step 606: loss = 1276424.60 (19.346 sec) ('Training Accuracy:', 0.9408018) ('Testing Accuracy:', 0.57666665)
Step 607: loss = 565404.46 (18.095 sec) ('Training Accuracy:', 0.96890223) ('Testing Accuracy:', 0.56999999)
Step 608: loss = 450392.04 (19.171 sec) ('Training Accuracy:', 0.89321846) ('Testing Accuracy:', 0.56333333)
Step 609: loss = 961504.70 (19.062 sec) ('Training Accuracy:', 0.94192582) ('Testing Accuracy:', 0.57666665)
Step 610: loss = 574392.20 (19.124 sec) ('Training Accuracy:', 0.9216935) ('Testing Accuracy:', 0.57333332)
Step 611: loss = 886699.46 (19.299 sec) ('Training Accuracy:', 0.91082805) ('Testing Accuracy:', 0.55666667)
Step 612: loss = 1192621.12 (19.474 sec) ('Training Accuracy:', 0.9231922) ('Testing Accuracy:', 0.58333331)
Step 613: loss = 814387.89 (19.475 sec) ('Training Accuracy:', 0.84750843) ('Testing Accuracy:', 0.52999997)
Step 614: loss = 1193902.43 (18.963 sec) ('Training Accuracy:', 0.95054328) ('Testing Accuracy:', 0.57666665)
Step 615: loss = 469523.73 (19.002 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.57666665)
Step 616: loss = 460720.16 (18.650 sec) ('Training Accuracy:', 0.92544025) ('Testing Accuracy:', 0.56333333)
Step 617: loss = 754228.31 (19.055 sec) ('Training Accuracy:', 0.95166731) ('Testing Accuracy:', 0.57666665)
Step 618: loss = 472556.86 (19.269 sec) ('Training Accuracy:', 0.9378044) ('Testing Accuracy:', 0.56666666)
Step 619: loss = 702023.73 (19.279 sec) ('Training Accuracy:', 0.94941926) ('Testing Accuracy:', 0.56)
Step 620: loss = 335883.58 (19.312 sec) ('Training Accuracy:', 0.93742973) ('Testing Accuracy:', 0.58333331)
Step 621: loss = 739894.54 (19.051 sec) ('Training Accuracy:', 0.92656428) ('Testing Accuracy:', 0.56999999)
Step 622: loss = 1122739.12 (19.073 sec) ('Training Accuracy:', 0.91607344) ('Testing Accuracy:', 0.60000002)
Step 623: loss = 1030411.06 (19.072 sec) ('Training Accuracy:', 0.92918694) ('Testing Accuracy:', 0.56999999)
Step 624: loss = 1061627.49 (19.037 sec) ('Training Accuracy:', 0.90633196) ('Testing Accuracy:', 0.57666665)
Step 625: loss = 2734303.37 (18.851 sec) ('Training Accuracy:', 0.9423005) ('Testing Accuracy:', 0.60333335)
Step 626: loss = 1596084.38 (19.489 sec) ('Training Accuracy:', 0.94042712) ('Testing Accuracy:', 0.64666665)
Step 627: loss = 2522245.45 (18.816 sec) ('Training Accuracy:', 0.96403146) ('Testing Accuracy:', 0.58666664)
Step 628: loss = 2063735.57 (18.680 sec) ('Training Accuracy:', 0.97302359) ('Testing Accuracy:', 0.58333331)
Step 629: loss = 3059568.50 (18.570 sec) ('Training Accuracy:', 0.96627951) ('Testing Accuracy:', 0.60333335)
Step 630: loss = 9611176.91 (19.102 sec) ('Training Accuracy:', 0.86998874) ('Testing Accuracy:', 0.56666666)
Step 631: loss = 4127130.77 (19.436 sec) ('Training Accuracy:', 0.93967777) ('Testing Accuracy:', 0.62333333)
Step 632: loss = 1334706.35 (18.871 sec) ('Training Accuracy:', 0.93892843) ('Testing Accuracy:', 0.58666664)
Step 633: loss = 802493.63 (18.710 sec) ('Training Accuracy:', 0.95803672) ('Testing Accuracy:', 0.56999999)
Step 634: loss = 602553.92 (18.943 sec) ('Training Accuracy:', 0.8947171) ('Testing Accuracy:', 0.54666668)
Step 635: loss = 693891.10 (18.816 sec) ('Training Accuracy:', 0.96365678) ('Testing Accuracy:', 0.58666664)
Step 636: loss = 523260.58 (18.989 sec) ('Training Accuracy:', 0.96290743) ('Testing Accuracy:', 0.58666664)
Step 637: loss = 466842.89 (18.034 sec) ('Training Accuracy:', 0.92506558) ('Testing Accuracy:', 0.56)
Step 638: loss = 471540.96 (18.709 sec) ('Training Accuracy:', 0.96065944) ('Testing Accuracy:', 0.60000002)
Step 639: loss = 348624.44 (19.035 sec) ('Training Accuracy:', 0.95016861) ('Testing Accuracy:', 0.5933333)
Step 640: loss = 540497.87 (19.063 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.5933333)
Step 641: loss = 215136.16 (18.163 sec) ('Training Accuracy:', 0.96290743) ('Testing Accuracy:', 0.60000002)
Step 642: loss = 281170.47 (18.956 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.58999997)
Step 643: loss = 263084.12 (18.980 sec) ('Training Accuracy:', 0.97527164) ('Testing Accuracy:', 0.60333335)
Step 644: loss = 91631.38 (18.594 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.60666668)
Step 645: loss = 593035.17 (19.035 sec) ('Training Accuracy:', 0.90558261) ('Testing Accuracy:', 0.56666666)
Step 646: loss = 953088.45 (18.960 sec) ('Training Accuracy:', 0.94155115) ('Testing Accuracy:', 0.57666665)
Step 647: loss = 833800.94 (18.674 sec) ('Training Accuracy:', 0.97639567) ('Testing Accuracy:', 0.61000001)
Step 648: loss = 628186.12 (19.053 sec) ('Training Accuracy:', 0.96215808) ('Testing Accuracy:', 0.58999997)
Step 649: loss = 437868.32 (18.930 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.57666665)
Step 650: loss = 420058.08 (19.136 sec) ('Training Accuracy:', 0.93143499) ('Testing Accuracy:', 0.57999998)
Step 651: loss = 3107110.56 (18.464 sec) ('Training Accuracy:', 0.97302359) ('Testing Accuracy:', 0.60000002)
Step 652: loss = 2377390.75 (18.764 sec) ('Training Accuracy:', 0.92506558) ('Testing Accuracy:', 0.56333333)
Step 653: loss = 1569104.18 (18.677 sec) ('Training Accuracy:', 0.95241666) ('Testing Accuracy:', 0.58333331)
Step 654: loss = 539655.21 (18.502 sec) ('Training Accuracy:', 0.94941926) ('Testing Accuracy:', 0.57666665)
Step 655: loss = 498429.18 (19.188 sec) ('Training Accuracy:', 0.96665418) ('Testing Accuracy:', 0.59666669)
Step 656: loss = 612586.67 (18.874 sec) ('Training Accuracy:', 0.96965158) ('Testing Accuracy:', 0.62666667)
Step 657: loss = 1841519.77 (19.292 sec) ('Training Accuracy:', 0.92956161) ('Testing Accuracy:', 0.57333332)
Step 658: loss = 350425.77 (19.126 sec) ('Training Accuracy:', 0.97339827) ('Testing Accuracy:', 0.58666664)
Step 659: loss = 285051.71 (18.819 sec) ('Training Accuracy:', 0.95316601) ('Testing Accuracy:', 0.57333332)
Step 660: loss = 1514821.93 (19.270 sec) ('Training Accuracy:', 0.97189957) ('Testing Accuracy:', 0.60333335)
Step 661: loss = 336514.31 (18.730 sec) ('Training Accuracy:', 0.96140879) ('Testing Accuracy:', 0.55666667)
Step 662: loss = 399644.12 (18.994 sec) ('Training Accuracy:', 0.92993629) ('Testing Accuracy:', 0.58333331)
Step 663: loss = 981689.68 (18.645 sec) ('Training Accuracy:', 0.90783066) ('Testing Accuracy:', 0.56666666)
Step 664: loss = 667019.94 (18.582 sec) ('Training Accuracy:', 0.96140879) ('Testing Accuracy:', 0.5933333)
Step 665: loss = 247754.20 (19.273 sec) ('Training Accuracy:', 0.96702886) ('Testing Accuracy:', 0.5933333)
Step 666: loss = 251479.40 (19.213 sec) ('Training Accuracy:', 0.97602099) ('Testing Accuracy:', 0.58999997)
Step 667: loss = 387519.28 (19.264 sec) ('Training Accuracy:', 0.95616335) ('Testing Accuracy:', 0.57999998)
Step 668: loss = 412643.29 (18.722 sec) ('Training Accuracy:', 0.96065944) ('Testing Accuracy:', 0.58666664)
Step 669: loss = 493661.70 (19.374 sec) ('Training Accuracy:', 0.94492316) ('Testing Accuracy:', 0.57999998)
Step 670: loss = 715654.78 (19.640 sec) ('Training Accuracy:', 0.94941926) ('Testing Accuracy:', 0.57999998)
Step 671: loss = 515671.13 (19.159 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.58999997)
Step 672: loss = 262682.72 (19.105 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.57999998)
Step 673: loss = 219926.78 (18.976 sec) ('Training Accuracy:', 0.96028477) ('Testing Accuracy:', 0.58666664)
Step 674: loss = 442611.48 (19.098 sec) ('Training Accuracy:', 0.94304985) ('Testing Accuracy:', 0.57999998)
Step 675: loss = 380220.77 (19.606 sec) ('Training Accuracy:', 0.97377294) ('Testing Accuracy:', 0.5933333)
Step 676: loss = 269309.39 (19.268 sec) ('Training Accuracy:', 0.97789437) ('Testing Accuracy:', 0.58666664)
Step 677: loss = 383575.25 (19.152 sec) ('Training Accuracy:', 0.97040087) ('Testing Accuracy:', 0.5933333)
Step 678: loss = 166858.72 (18.645 sec) ('Training Accuracy:', 0.97677034) ('Testing Accuracy:', 0.57999998)
Step 679: loss = 363467.29 (19.304 sec) ('Training Accuracy:', 0.96553016) ('Testing Accuracy:', 0.59666669)
Step 680: loss = 130901.32 (19.378 sec) ('Training Accuracy:', 0.94342452) ('Testing Accuracy:', 0.58333331)
Step 681: loss = 969032.61 (18.965 sec) ('Training Accuracy:', 0.90483326) ('Testing Accuracy:', 0.5933333)
Step 682: loss = 1345345.28 (19.364 sec) ('Training Accuracy:', 0.95091796) ('Testing Accuracy:', 0.56333333)
Step 683: loss = 488787.77 (19.143 sec) ('Training Accuracy:', 0.94492316) ('Testing Accuracy:', 0.57999998)
Step 684: loss = 1109797.03 (19.660 sec) ('Training Accuracy:', 0.97751969) ('Testing Accuracy:', 0.61000001)
Step 685: loss = 199939.59 (19.334 sec) ('Training Accuracy:', 0.9423005) ('Testing Accuracy:', 0.57333332)
Step 686: loss = 544952.15 (19.031 sec) ('Training Accuracy:', 0.93555641) ('Testing Accuracy:', 0.56999999)
Step 687: loss = 887155.49 (54.917 sec) ('Training Accuracy:', 0.95316601) ('Testing Accuracy:', 0.55666667)
Step 688: loss = 578995.61 (62.659 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.5933333)
Step 689: loss = 353138.99 (63.104 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.58999997)
Step 690: loss = 395309.83 (76.293 sec) ('Training Accuracy:', 0.94492316) ('Testing Accuracy:', 0.57333332)
Step 691: loss = 527019.50 (63.849 sec) ('Training Accuracy:', 0.92431623) ('Testing Accuracy:', 0.56999999)
Step 692: loss = 702364.89 (64.087 sec) ('Training Accuracy:', 0.92356688) ('Testing Accuracy:', 0.57333332)
Step 693: loss = 1235957.95 (20.415 sec) ('Training Accuracy:', 0.94829524) ('Testing Accuracy:', 0.5933333)
Step 694: loss = 488613.97 (18.355 sec) ('Training Accuracy:', 0.92394155) ('Testing Accuracy:', 0.58666664)
Step 695: loss = 438935.59 (20.070 sec) ('Training Accuracy:', 0.9408018) ('Testing Accuracy:', 0.57666665)
Step 696: loss = 525060.23 (20.400 sec) ('Training Accuracy:', 0.9569127) ('Testing Accuracy:', 0.60000002)
Step 697: loss = 446188.91 (20.789 sec) ('Training Accuracy:', 0.97377294) ('Testing Accuracy:', 0.60333335)
Step 698: loss = 498349.39 (20.737 sec) ('Training Accuracy:', 0.91757214) ('Testing Accuracy:', 0.57666665)
Step 699: loss = 882155.93 (20.753 sec) ('Training Accuracy:', 0.86062193) ('Testing Accuracy:', 0.59666669)
Step 700: loss = 1407696.75 (21.602 sec) ('Training Accuracy:', 0.85987264) ('Testing Accuracy:', 0.57999998)
Step 701: loss = 5561970.37 (20.276 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.61666667)
Step 702: loss = 1863965.64 (20.170 sec) ('Training Accuracy:', 0.82053202) ('Testing Accuracy:', 0.52999997)
Step 703: loss = 3238706.04 (19.562 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.58333331)
Step 704: loss = 1701089.11 (20.130 sec) ('Training Accuracy:', 0.85237914) ('Testing Accuracy:', 0.55000001)
Step 705: loss = 3093093.82 (24.072 sec) ('Training Accuracy:', 0.92506558) ('Testing Accuracy:', 0.56333333)
Step 706: loss = 5965874.66 (24.147 sec) ('Training Accuracy:', 0.86324465) ('Testing Accuracy:', 0.57666665)
Step 707: loss = 7630970.27 (24.033 sec) ('Training Accuracy:', 0.97527164) ('Testing Accuracy:', 0.60666668)
Step 708: loss = 10297302.69 (23.773 sec) ('Training Accuracy:', 0.9378044) ('Testing Accuracy:', 0.59666669)
Step 709: loss = 17502744.17 (23.332 sec) ('Training Accuracy:', 0.84863245) ('Testing Accuracy:', 0.65333331)
Step 710: loss = 17072267.58 (23.615 sec) ('Training Accuracy:', 0.96290743) ('Testing Accuracy:', 0.58666664)
Step 711: loss = 3462656.47 (23.681 sec) ('Training Accuracy:', 0.97527164) ('Testing Accuracy:', 0.62333333)
Step 712: loss = 638935.39 (23.619 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.60666668)
Step 713: loss = 358155.12 (23.668 sec) ('Training Accuracy:', 0.96215808) ('Testing Accuracy:', 0.61000001)
Step 714: loss = 301704.38 (24.138 sec) ('Training Accuracy:', 0.97564632) ('Testing Accuracy:', 0.62333333)
Step 715: loss = 92300.77 (23.600 sec) ('Training Accuracy:', 0.97414762) ('Testing Accuracy:', 0.63333333)
Step 716: loss = 115064.45 (22.621 sec) ('Training Accuracy:', 0.96815288) ('Testing Accuracy:', 0.60333335)
Step 717: loss = 242489.74 (23.556 sec) ('Training Accuracy:', 0.97040087) ('Testing Accuracy:', 0.5933333)
Step 718: loss = 272572.92 (23.960 sec) ('Training Accuracy:', 0.9569127) ('Testing Accuracy:', 0.57666665)
Step 719: loss = 482054.10 (24.005 sec) ('Training Accuracy:', 0.95466465) ('Testing Accuracy:', 0.57666665)
Step 720: loss = 449090.19 (23.805 sec) ('Training Accuracy:', 0.94342452) ('Testing Accuracy:', 0.57333332)
Step 721: loss = 691287.07 (24.092 sec) ('Training Accuracy:', 0.96365678) ('Testing Accuracy:', 0.58666664)
Step 722: loss = 144324.34 (24.315 sec) ('Training Accuracy:', 0.96290743) ('Testing Accuracy:', 0.57333332)
Step 723: loss = 364054.14 (24.325 sec) ('Training Accuracy:', 0.94155115) ('Testing Accuracy:', 0.56666666)
Step 724: loss = 973844.66 (24.017 sec) ('Training Accuracy:', 0.96815288) ('Testing Accuracy:', 0.58999997)
Step 725: loss = 186069.90 (23.950 sec) ('Training Accuracy:', 0.97115022) ('Testing Accuracy:', 0.59666669)
Step 726: loss = 303176.52 (23.606 sec) ('Training Accuracy:', 0.93330836) ('Testing Accuracy:', 0.57999998)
Step 727: loss = 808084.89 (24.072 sec) ('Training Accuracy:', 0.91120267) ('Testing Accuracy:', 0.56333333)
Step 728: loss = 2613758.78 (23.826 sec) ('Training Accuracy:', 0.93855375) ('Testing Accuracy:', 0.56666666)
Step 729: loss = 3219129.48 (24.220 sec) ('Training Accuracy:', 0.96328211) ('Testing Accuracy:', 0.5933333)
Step 730: loss = 3381204.45 (23.770 sec) ('Training Accuracy:', 0.9584114) ('Testing Accuracy:', 0.57333332)
Step 731: loss = 3457847.05 (23.876 sec) ('Training Accuracy:', 0.97751969) ('Testing Accuracy:', 0.62)
Step 732: loss = 4140097.09 (23.954 sec) ('Training Accuracy:', 0.97302359) ('Testing Accuracy:', 0.57666665)
Step 733: loss = 2521914.82 (24.321 sec) ('Training Accuracy:', 0.96103412) ('Testing Accuracy:', 0.62333333)
Step 734: loss = 3321219.23 (23.802 sec) ('Training Accuracy:', 0.92656428) ('Testing Accuracy:', 0.66666669)
Step 735: loss = 3534369.88 (23.884 sec) ('Training Accuracy:', 0.95728737) ('Testing Accuracy:', 0.63666666)
Step 736: loss = 3525653.95 (23.583 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.62)
Step 737: loss = 3536171.90 (25.005 sec) ('Training Accuracy:', 0.9569127) ('Testing Accuracy:', 0.60333335)
Step 738: loss = 708073.27 (23.418 sec) ('Training Accuracy:', 0.9393031) ('Testing Accuracy:', 0.56666666)
Step 739: loss = 972416.58 (24.367 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.57666665)
Step 740: loss = 322847.94 (24.202 sec) ('Training Accuracy:', 0.93555641) ('Testing Accuracy:', 0.56333333)
Step 741: loss = 1261775.95 (25.094 sec) ('Training Accuracy:', 0.92656428) ('Testing Accuracy:', 0.58999997)
Step 742: loss = 724651.99 (23.804 sec) ('Training Accuracy:', 0.95354062) ('Testing Accuracy:', 0.57999998)
Step 743: loss = 485120.25 (23.579 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.5933333)
Step 744: loss = 257114.69 (24.005 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.58333331)
Step 745: loss = 440375.84 (24.047 sec) ('Training Accuracy:', 0.93218434) ('Testing Accuracy:', 0.57666665)
Step 746: loss = 980826.24 (23.835 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.56999999)
Step 747: loss = 135766.56 (24.052 sec) ('Training Accuracy:', 0.95728737) ('Testing Accuracy:', 0.57333332)
Step 748: loss = 444725.74 (24.019 sec) ('Training Accuracy:', 0.93892843) ('Testing Accuracy:', 0.56999999)
Step 749: loss = 990744.68 (26.149 sec) ('Training Accuracy:', 0.90033722) ('Testing Accuracy:', 0.56333333)
Step 750: loss = 1204066.68 (24.308 sec) ('Training Accuracy:', 0.93518174) ('Testing Accuracy:', 0.57333332)
Step 751: loss = 583031.17 (24.200 sec) ('Training Accuracy:', 0.91082805) ('Testing Accuracy:', 0.57333332)
Step 752: loss = 1321199.36 (24.705 sec) ('Training Accuracy:', 0.93218434) ('Testing Accuracy:', 0.56333333)
Step 753: loss = 936746.95 (25.280 sec) ('Training Accuracy:', 0.90932935) ('Testing Accuracy:', 0.57666665)
Step 754: loss = 688519.55 (25.176 sec) ('Training Accuracy:', 0.96515548) ('Testing Accuracy:', 0.62333333)
Step 755: loss = 361860.35 (24.428 sec) ('Training Accuracy:', 0.95091796) ('Testing Accuracy:', 0.57666665)
Step 756: loss = 1224356.14 (24.894 sec) ('Training Accuracy:', 0.94342452) ('Testing Accuracy:', 0.56333333)
Step 757: loss = 703085.58 (23.442 sec) ('Training Accuracy:', 0.90708131) ('Testing Accuracy:', 0.57666665)
Step 758: loss = 881599.19 (24.090 sec) ('Training Accuracy:', 0.93068564) ('Testing Accuracy:', 0.56)
Step 759: loss = 839190.47 (24.191 sec) ('Training Accuracy:', 0.87710756) ('Testing Accuracy:', 0.55000001)
Step 760: loss = 790963.62 (23.766 sec) ('Training Accuracy:', 0.9276883) ('Testing Accuracy:', 0.55666667)
Step 761: loss = 982249.13 (11.253 sec) ('Training Accuracy:', 0.8684901) ('Testing Accuracy:', 0.55000001)
Step 762: loss = 1070710.64 (11.531 sec) ('Training Accuracy:', 0.96890223) ('Testing Accuracy:', 0.62)
Step 763: loss = 573341.98 (11.731 sec) ('Training Accuracy:', 0.93218434) ('Testing Accuracy:', 0.56)
Step 764: loss = 491265.61 (12.055 sec) ('Training Accuracy:', 0.94267517) ('Testing Accuracy:', 0.57333332)
Step 765: loss = 516379.69 (12.066 sec) ('Training Accuracy:', 0.93555641) ('Testing Accuracy:', 0.56666666)
Step 766: loss = 1002670.57 (12.067 sec) ('Training Accuracy:', 0.96702886) ('Testing Accuracy:', 0.58333331)
Step 767: loss = 192270.81 (12.537 sec) ('Training Accuracy:', 0.9378044) ('Testing Accuracy:', 0.56999999)
Step 768: loss = 566057.66 (12.463 sec) ('Training Accuracy:', 0.92131883) ('Testing Accuracy:', 0.56)
Step 769: loss = 1142202.66 (12.623 sec) ('Training Accuracy:', 0.96777821) ('Testing Accuracy:', 0.58666664)
Step 770: loss = 224131.96 (12.905 sec) ('Training Accuracy:', 0.96365678) ('Testing Accuracy:', 0.58333331)
Step 771: loss = 253125.00 (13.047 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.58666664)
Step 772: loss = 384010.06 (13.164 sec) ('Training Accuracy:', 0.96927691) ('Testing Accuracy:', 0.60333335)
Step 773: loss = 154694.59 (13.113 sec) ('Training Accuracy:', 0.96403146) ('Testing Accuracy:', 0.5933333)
Step 774: loss = 243199.84 (13.283 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.58999997)
Step 775: loss = 207659.62 (13.374 sec) ('Training Accuracy:', 0.94454855) ('Testing Accuracy:', 0.56333333)
Step 776: loss = 1187078.86 (13.269 sec) ('Training Accuracy:', 0.91270137) ('Testing Accuracy:', 0.56666666)
Step 777: loss = 642584.85 (13.245 sec) ('Training Accuracy:', 0.93106031) ('Testing Accuracy:', 0.56333333)
Step 778: loss = 989564.79 (12.797 sec) ('Training Accuracy:', 0.92394155) ('Testing Accuracy:', 0.56333333)
Step 779: loss = 1205817.72 (12.552 sec) ('Training Accuracy:', 0.90858001) ('Testing Accuracy:', 0.54666668)
Step 780: loss = 2136651.13 (12.157 sec) ('Training Accuracy:', 0.92431623) ('Testing Accuracy:', 0.56)
Step 781: loss = 252357.27 (11.969 sec) ('Training Accuracy:', 0.9539153) ('Testing Accuracy:', 0.58333331)
Step 782: loss = 686796.59 (11.965 sec) ('Training Accuracy:', 0.95166731) ('Testing Accuracy:', 0.5933333)
Step 783: loss = 719518.89 (11.751 sec) ('Training Accuracy:', 0.96590483) ('Testing Accuracy:', 0.62333333)
Step 784: loss = 351703.70 (11.373 sec) ('Training Accuracy:', 0.9539153) ('Testing Accuracy:', 0.58333331)
Step 785: loss = 453712.89 (11.300 sec) ('Training Accuracy:', 0.94529784) ('Testing Accuracy:', 0.57333332)
Step 786: loss = 765039.24 (11.291 sec) ('Training Accuracy:', 0.90370923) ('Testing Accuracy:', 0.56)
Step 787: loss = 1010468.91 (11.185 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.60666668)
Step 788: loss = 310721.08 (11.319 sec) ('Training Accuracy:', 0.93143499) ('Testing Accuracy:', 0.55666667)
Step 789: loss = 711201.17 (11.518 sec) ('Training Accuracy:', 0.94492316) ('Testing Accuracy:', 0.57999998)
Step 790: loss = 761383.82 (11.262 sec) ('Training Accuracy:', 0.90146124) ('Testing Accuracy:', 0.56999999)
Step 791: loss = 1013784.04 (11.139 sec) ('Training Accuracy:', 0.96140879) ('Testing Accuracy:', 0.60000002)
Step 792: loss = 579297.27 (11.227 sec) ('Training Accuracy:', 0.91494942) ('Testing Accuracy:', 0.56999999)
Step 793: loss = 849744.41 (11.151 sec) ('Training Accuracy:', 0.93855375) ('Testing Accuracy:', 0.58999997)
Step 794: loss = 926108.82 (11.237 sec) ('Training Accuracy:', 0.88272762) ('Testing Accuracy:', 0.57333332)
Step 795: loss = 896763.92 (11.166 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.59666669)
Step 796: loss = 311202.98 (11.136 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.5933333)
Step 797: loss = 339360.30 (11.343 sec) ('Training Accuracy:', 0.96215808) ('Testing Accuracy:', 0.60333335)
Step 798: loss = 400262.28 (11.273 sec) ('Training Accuracy:', 0.93368304) ('Testing Accuracy:', 0.57333332)
Step 799: loss = 752236.62 (11.197 sec) ('Training Accuracy:', 0.90071189) ('Testing Accuracy:', 0.57999998)
Step 800: loss = 1056755.02 (11.189 sec) ('Training Accuracy:', 0.97077554) ('Testing Accuracy:', 0.58999997)
Step 801: loss = 1044630.85 (11.187 sec) ('Training Accuracy:', 0.97189957) ('Testing Accuracy:', 0.59666669)
Step 802: loss = 367625.48 (11.373 sec) ('Training Accuracy:', 0.95316601) ('Testing Accuracy:', 0.5933333)
Step 803: loss = 529645.75 (11.325 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.60000002)
Step 804: loss = 501218.23 (11.750 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.58666664)
Step 805: loss = 675950.56 (11.674 sec) ('Training Accuracy:', 0.9246909) ('Testing Accuracy:', 0.56999999)
Step 806: loss = 824946.28 (11.621 sec) ('Training Accuracy:', 0.86137128) ('Testing Accuracy:', 0.55666667)
Step 807: loss = 796520.66 (11.637 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.59666669)
Step 808: loss = 747665.85 (11.646 sec) ('Training Accuracy:', 0.98051703) ('Testing Accuracy:', 0.60000002)
Step 809: loss = 446034.95 (11.760 sec) ('Training Accuracy:', 0.91420007) ('Testing Accuracy:', 0.57333332)
Step 810: loss = 799903.98 (11.626 sec) ('Training Accuracy:', 0.95354062) ('Testing Accuracy:', 0.58333331)
Step 811: loss = 912891.84 (11.591 sec) ('Training Accuracy:', 0.93668038) ('Testing Accuracy:', 0.55333334)
Step 812: loss = 418907.48 (11.756 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.58333331)
Step 813: loss = 233088.27 (11.713 sec) ('Training Accuracy:', 0.94492316) ('Testing Accuracy:', 0.57333332)
Step 814: loss = 849716.66 (11.777 sec) ('Training Accuracy:', 0.96365678) ('Testing Accuracy:', 0.57999998)
Step 815: loss = 216098.02 (11.529 sec) ('Training Accuracy:', 0.92881227) ('Testing Accuracy:', 0.56)
Step 816: loss = 554258.33 (11.433 sec) ('Training Accuracy:', 0.9539153) ('Testing Accuracy:', 0.58999997)
Step 817: loss = 372413.82 (11.518 sec) ('Training Accuracy:', 0.93817908) ('Testing Accuracy:', 0.56333333)
Step 818: loss = 586194.16 (11.591 sec) ('Training Accuracy:', 0.93180966) ('Testing Accuracy:', 0.56666666)
Step 819: loss = 842703.43 (12.059 sec) ('Training Accuracy:', 0.95316601) ('Testing Accuracy:', 0.57999998)
Step 820: loss = 291698.70 (12.300 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.61333334)
Step 821: loss = 286336.50 (12.357 sec) ('Training Accuracy:', 0.95241666) ('Testing Accuracy:', 0.57666665)
Step 822: loss = 532794.25 (12.445 sec) ('Training Accuracy:', 0.955414) ('Testing Accuracy:', 0.56666666)
Step 823: loss = 368015.84 (12.618 sec) ('Training Accuracy:', 0.9539153) ('Testing Accuracy:', 0.57333332)
Step 824: loss = 364087.22 (12.951 sec) ('Training Accuracy:', 0.94941926) ('Testing Accuracy:', 0.56333333)
Step 825: loss = 384709.14 (13.113 sec) ('Training Accuracy:', 0.97414762) ('Testing Accuracy:', 0.59666669)
Step 826: loss = 455919.12 (13.372 sec) ('Training Accuracy:', 0.94754589) ('Testing Accuracy:', 0.57999998)
Step 827: loss = 480213.08 (13.350 sec) ('Training Accuracy:', 0.9408018) ('Testing Accuracy:', 0.57999998)
Step 828: loss = 361685.36 (13.364 sec) ('Training Accuracy:', 0.93705505) ('Testing Accuracy:', 0.56666666)
Step 829: loss = 625999.29 (13.244 sec) ('Training Accuracy:', 0.93255901) ('Testing Accuracy:', 0.57333332)
Step 830: loss = 472917.45 (13.278 sec) ('Training Accuracy:', 0.96140879) ('Testing Accuracy:', 0.58666664)
Step 831: loss = 331048.58 (13.266 sec) ('Training Accuracy:', 0.96702886) ('Testing Accuracy:', 0.61000001)
Step 832: loss = 354988.39 (13.267 sec) ('Training Accuracy:', 0.91232669) ('Testing Accuracy:', 0.58333331)
Step 833: loss = 1035122.88 (13.415 sec) ('Training Accuracy:', 0.93480706) ('Testing Accuracy:', 0.57666665)
Step 834: loss = 713306.24 (13.482 sec) ('Training Accuracy:', 0.94642186) ('Testing Accuracy:', 0.58666664)
Step 835: loss = 597733.67 (13.239 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.60333335)
Step 836: loss = 403030.30 (12.960 sec) ('Training Accuracy:', 0.92544025) ('Testing Accuracy:', 0.57666665)
Step 837: loss = 630649.94 (12.857 sec) ('Training Accuracy:', 0.93630576) ('Testing Accuracy:', 0.59666669)
Step 838: loss = 712958.34 (12.742 sec) ('Training Accuracy:', 0.97040087) ('Testing Accuracy:', 0.60000002)
Step 839: loss = 1120086.43 (12.836 sec) ('Training Accuracy:', 0.96627951) ('Testing Accuracy:', 0.64999998)
Step 840: loss = 1082229.75 (12.274 sec) ('Training Accuracy:', 0.96515548) ('Testing Accuracy:', 0.5933333)
Step 841: loss = 798092.55 (12.167 sec) ('Training Accuracy:', 0.96965158) ('Testing Accuracy:', 0.59666669)
Step 842: loss = 864857.45 (11.625 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.58333331)
Step 843: loss = 239969.07 (11.586 sec) ('Training Accuracy:', 0.94604719) ('Testing Accuracy:', 0.56666666)
Step 844: loss = 874075.18 (11.333 sec) ('Training Accuracy:', 0.97339827) ('Testing Accuracy:', 0.62333333)
Step 845: loss = 612324.71 (11.203 sec) ('Training Accuracy:', 0.97040087) ('Testing Accuracy:', 0.61666667)
Step 846: loss = 834163.77 (11.202 sec) ('Training Accuracy:', 0.97377294) ('Testing Accuracy:', 0.60000002)
Step 847: loss = 791717.70 (11.191 sec) ('Training Accuracy:', 0.93892843) ('Testing Accuracy:', 0.58333331)
Step 848: loss = 953758.38 (11.137 sec) ('Training Accuracy:', 0.97452229) ('Testing Accuracy:', 0.60000002)
Step 849: loss = 1184147.41 (11.216 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.60666668)
Step 850: loss = 3957443.34 (11.122 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.63)
Step 851: loss = 2006978.40 (11.131 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.58666664)
Step 852: loss = 3319390.41 (10.928 sec) ('Training Accuracy:', 0.97115022) ('Testing Accuracy:', 0.58999997)
Step 853: loss = 7904248.43 (10.901 sec) ('Training Accuracy:', 0.96328211) ('Testing Accuracy:', 0.67000002)
Step 854: loss = 2820237.60 (10.967 sec) ('Training Accuracy:', 0.91457474) ('Testing Accuracy:', 0.56333333)
Step 855: loss = 4465946.69 (10.871 sec) ('Training Accuracy:', 0.91682279) ('Testing Accuracy:', 0.57999998)
Step 856: loss = 1616203.31 (11.148 sec) ('Training Accuracy:', 0.93630576) ('Testing Accuracy:', 0.57666665)
Step 857: loss = 847953.19 (10.969 sec) ('Training Accuracy:', 0.92394155) ('Testing Accuracy:', 0.54666668)
Step 858: loss = 1669757.42 (11.432 sec) ('Training Accuracy:', 0.82727611) ('Testing Accuracy:', 0.53666669)
Step 859: loss = 15871869.81 (11.346 sec) ('Training Accuracy:', 0.97826904) ('Testing Accuracy:', 0.61000001)
Step 860: loss = 10932904.21 (11.657 sec) ('Training Accuracy:', 0.92693895) ('Testing Accuracy:', 0.58666664)
Step 861: loss = 2153564.64 (11.965 sec) ('Training Accuracy:', 0.93855375) ('Testing Accuracy:', 0.59666669)
Step 862: loss = 1786166.23 (12.353 sec) ('Training Accuracy:', 0.97527164) ('Testing Accuracy:', 0.63333333)
Step 863: loss = 743743.04 (12.499 sec) ('Training Accuracy:', 0.95953542) ('Testing Accuracy:', 0.5933333)
Step 864: loss = 586921.01 (12.988 sec) ('Training Accuracy:', 0.93555641) ('Testing Accuracy:', 0.58333331)
Step 865: loss = 558757.90 (12.822 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.60000002)
Step 866: loss = 544317.71 (12.823 sec) ('Training Accuracy:', 0.94829524) ('Testing Accuracy:', 0.58666664)
Step 867: loss = 1129469.18 (12.809 sec) ('Training Accuracy:', 0.97339827) ('Testing Accuracy:', 0.5933333)
Step 868: loss = 289465.22 (12.443 sec) ('Training Accuracy:', 0.95279133) ('Testing Accuracy:', 0.58999997)
Step 869: loss = 431382.58 (12.244 sec) ('Training Accuracy:', 0.94941926) ('Testing Accuracy:', 0.58666664)
Step 870: loss = 698896.63 (12.134 sec) ('Training Accuracy:', 0.92056948) ('Testing Accuracy:', 0.57333332)
Step 871: loss = 1306140.55 (11.631 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.5933333)
Step 872: loss = 372310.25 (11.517 sec) ('Training Accuracy:', 0.97264892) ('Testing Accuracy:', 0.61333334)
Step 873: loss = 365347.89 (11.892 sec) ('Training Accuracy:', 0.95054328) ('Testing Accuracy:', 0.58666664)
Step 874: loss = 701791.09 (11.472 sec) ('Training Accuracy:', 0.91682279) ('Testing Accuracy:', 0.58333331)
Step 875: loss = 1045956.04 (11.104 sec) ('Training Accuracy:', 0.92506558) ('Testing Accuracy:', 0.58333331)
Step 876: loss = 1179461.16 (10.827 sec) ('Training Accuracy:', 0.8962158) ('Testing Accuracy:', 0.57333332)
Step 877: loss = 1002432.44 (10.997 sec) ('Training Accuracy:', 0.93555641) ('Testing Accuracy:', 0.57666665)
Step 878: loss = 1073795.03 (10.760 sec) ('Training Accuracy:', 0.8977145) ('Testing Accuracy:', 0.56999999)
Step 879: loss = 891989.93 (10.918 sec) ('Training Accuracy:', 0.90108657) ('Testing Accuracy:', 0.58666664)
Step 880: loss = 2185221.25 (10.781 sec) ('Training Accuracy:', 0.94941926) ('Testing Accuracy:', 0.58333331)
Step 881: loss = 787858.70 (10.956 sec) ('Training Accuracy:', 0.94117647) ('Testing Accuracy:', 0.5933333)
Step 882: loss = 768611.76 (11.131 sec) ('Training Accuracy:', 0.88722366) ('Testing Accuracy:', 0.56666666)
Step 883: loss = 1599319.87 (11.498 sec) ('Training Accuracy:', 0.97040087) ('Testing Accuracy:', 0.60333335)
Step 884: loss = 951472.23 (11.839 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.5933333)
Step 885: loss = 183150.63 (12.272 sec) ('Training Accuracy:', 0.96478081) ('Testing Accuracy:', 0.5933333)
Step 886: loss = 307360.93 (12.556 sec) ('Training Accuracy:', 0.96777821) ('Testing Accuracy:', 0.60333335)
Step 887: loss = 264896.72 (12.924 sec) ('Training Accuracy:', 0.96815288) ('Testing Accuracy:', 0.61000001)
Step 888: loss = 283339.18 (12.778 sec) ('Training Accuracy:', 0.96178347) ('Testing Accuracy:', 0.60333335)
Step 889: loss = 292427.28 (13.021 sec) ('Training Accuracy:', 0.95316601) ('Testing Accuracy:', 0.59666669)
Step 890: loss = 507084.72 (12.596 sec) ('Training Accuracy:', 0.94155115) ('Testing Accuracy:', 0.58999997)
Step 891: loss = 1110972.79 (12.218 sec) ('Training Accuracy:', 0.93255901) ('Testing Accuracy:', 0.58666664)
Step 892: loss = 604296.02 (13.876 sec) ('Training Accuracy:', 0.92993629) ('Testing Accuracy:', 0.60000002)
Step 893: loss = 881166.25 (12.938 sec) ('Training Accuracy:', 0.89396781) ('Testing Accuracy:', 0.57666665)
Step 894: loss = 1150711.96 (12.652 sec) ('Training Accuracy:', 0.97115022) ('Testing Accuracy:', 0.61000001)
Step 895: loss = 822471.44 (12.494 sec) ('Training Accuracy:', 0.89134508) ('Testing Accuracy:', 0.57999998)
Step 896: loss = 703315.38 (12.793 sec) ('Training Accuracy:', 0.93368304) ('Testing Accuracy:', 0.59666669)
Step 897: loss = 999029.85 (12.734 sec) ('Training Accuracy:', 0.90970403) ('Testing Accuracy:', 0.5933333)
Step 898: loss = 999253.79 (12.783 sec) ('Training Accuracy:', 0.88909703) ('Testing Accuracy:', 0.57333332)
Step 899: loss = 1116532.05 (13.012 sec) ('Training Accuracy:', 0.95354062) ('Testing Accuracy:', 0.60000002)
Step 900: loss = 456768.74 (13.398 sec) ('Training Accuracy:', 0.92394155) ('Testing Accuracy:', 0.57666665)
Step 901: loss = 591314.30 (13.375 sec) ('Training Accuracy:', 0.91382539) ('Testing Accuracy:', 0.56666666)
Step 902: loss = 1265156.50 (13.546 sec) ('Training Accuracy:', 0.92206818) ('Testing Accuracy:', 0.58666664)
Step 903: loss = 503841.43 (13.380 sec) ('Training Accuracy:', 0.90408391) ('Testing Accuracy:', 0.58666664)
Step 904: loss = 1084026.39 (13.438 sec) ('Training Accuracy:', 0.88535035) ('Testing Accuracy:', 0.56666666)
Step 905: loss = 1056244.03 (13.382 sec) ('Training Accuracy:', 0.95316601) ('Testing Accuracy:', 0.58666664)
Step 906: loss = 590577.75 (13.204 sec) ('Training Accuracy:', 0.94567251) ('Testing Accuracy:', 0.5933333)
Step 907: loss = 891407.32 (13.801 sec) ('Training Accuracy:', 0.91794682) ('Testing Accuracy:', 0.56666666)
Step 908: loss = 1053621.45 (11.858 sec) ('Training Accuracy:', 0.89022106) ('Testing Accuracy:', 0.56999999)
Step 909: loss = 1212511.80 (11.666 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.62666667)
Step 910: loss = 573538.61 (11.149 sec) ('Training Accuracy:', 0.92094415) ('Testing Accuracy:', 0.58333331)
Step 911: loss = 585711.93 (11.220 sec) ('Training Accuracy:', 0.87635821) ('Testing Accuracy:', 0.57333332)
Step 912: loss = 992812.83 (11.170 sec) ('Training Accuracy:', 0.95616335) ('Testing Accuracy:', 0.58666664)
Step 913: loss = 740081.88 (11.092 sec) ('Training Accuracy:', 0.88984638) ('Testing Accuracy:', 0.56999999)
Step 914: loss = 793573.42 (11.033 sec) ('Training Accuracy:', 0.95578867) ('Testing Accuracy:', 0.60666668)
Step 915: loss = 541643.12 (11.204 sec) ('Training Accuracy:', 0.92544025) ('Testing Accuracy:', 0.57666665)
Step 916: loss = 728866.03 (11.048 sec) ('Training Accuracy:', 0.9201948) ('Testing Accuracy:', 0.57333332)
Step 917: loss = 956054.31 (11.088 sec) ('Training Accuracy:', 0.91307604) ('Testing Accuracy:', 0.57999998)
Step 918: loss = 705640.52 (11.076 sec) ('Training Accuracy:', 0.88872236) ('Testing Accuracy:', 0.57333332)
Step 919: loss = 2140193.05 (11.062 sec) ('Training Accuracy:', 0.89246911) ('Testing Accuracy:', 0.56)
Step 920: loss = 1477797.57 (11.049 sec) ('Training Accuracy:', 0.94304985) ('Testing Accuracy:', 0.60000002)
Step 921: loss = 525357.09 (11.021 sec) ('Training Accuracy:', 0.96365678) ('Testing Accuracy:', 0.5933333)
Step 922: loss = 874092.49 (11.117 sec) ('Training Accuracy:', 0.9276883) ('Testing Accuracy:', 0.60333335)
Step 923: loss = 417302.99 (13.527 sec) ('Training Accuracy:', 0.96777821) ('Testing Accuracy:', 0.60000002)
Step 924: loss = 751873.00 (13.317 sec) ('Training Accuracy:', 0.94155115) ('Testing Accuracy:', 0.56333333)
Step 925: loss = 274455.61 (13.110 sec) ('Training Accuracy:', 0.96740353) ('Testing Accuracy:', 0.61333334)
Step 926: loss = 404899.99 (13.185 sec) ('Training Accuracy:', 0.91982013) ('Testing Accuracy:', 0.5933333)
Step 927: loss = 959896.07 (13.064 sec) ('Training Accuracy:', 0.95204198) ('Testing Accuracy:', 0.58999997)
Step 928: loss = 320031.28 (13.082 sec) ('Training Accuracy:', 0.97115022) ('Testing Accuracy:', 0.60333335)
Step 929: loss = 636499.95 (13.078 sec) ('Training Accuracy:', 0.94941926) ('Testing Accuracy:', 0.60333335)
Step 930: loss = 969610.42 (13.157 sec) ('Training Accuracy:', 0.97639567) ('Testing Accuracy:', 0.58666664)
Step 931: loss = 301817.22 (12.991 sec) ('Training Accuracy:', 0.94642186) ('Testing Accuracy:', 0.57666665)
Step 932: loss = 917463.52 (13.112 sec) ('Training Accuracy:', 0.89171976) ('Testing Accuracy:', 0.58999997)
Step 933: loss = 1451408.43 (12.948 sec) ('Training Accuracy:', 0.96215808) ('Testing Accuracy:', 0.61000001)
Step 934: loss = 453455.28 (13.100 sec) ('Training Accuracy:', 0.92581493) ('Testing Accuracy:', 0.58333331)
Step 935: loss = 902871.98 (12.810 sec) ('Training Accuracy:', 0.90932935) ('Testing Accuracy:', 0.56333333)
Step 936: loss = 693517.92 (12.619 sec) ('Training Accuracy:', 0.93480706) ('Testing Accuracy:', 0.56333333)
Step 937: loss = 663374.99 (12.338 sec) ('Training Accuracy:', 0.94567251) ('Testing Accuracy:', 0.58666664)
Step 938: loss = 711988.21 (12.406 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.58333331)
Step 939: loss = 807003.00 (12.685 sec) ('Training Accuracy:', 0.90670663) ('Testing Accuracy:', 0.57666665)
Step 940: loss = 589956.34 (12.400 sec) ('Training Accuracy:', 0.9408018) ('Testing Accuracy:', 0.55333334)
Step 941: loss = 806389.66 (12.365 sec) ('Training Accuracy:', 0.91832149) ('Testing Accuracy:', 0.55666667)
Step 942: loss = 684001.78 (12.127 sec) ('Training Accuracy:', 0.95428997) ('Testing Accuracy:', 0.57999998)
Step 943: loss = 343493.10 (12.004 sec) ('Training Accuracy:', 0.95166731) ('Testing Accuracy:', 0.57999998)
Step 944: loss = 258029.27 (11.827 sec) ('Training Accuracy:', 0.94492316) ('Testing Accuracy:', 0.58333331)
Step 945: loss = 520096.56 (11.875 sec) ('Training Accuracy:', 0.86661673) ('Testing Accuracy:', 0.57333332)
Step 946: loss = 835124.89 (11.774 sec) ('Training Accuracy:', 0.95503932) ('Testing Accuracy:', 0.57999998)
Step 947: loss = 655629.37 (12.021 sec) ('Training Accuracy:', 0.89134508) ('Testing Accuracy:', 0.56666666)
Step 948: loss = 967404.89 (11.772 sec) ('Training Accuracy:', 0.90745598) ('Testing Accuracy:', 0.56666666)
Step 949: loss = 678117.81 (11.814 sec) ('Training Accuracy:', 0.95428997) ('Testing Accuracy:', 0.60333335)
Step 950: loss = 364316.78 (11.649 sec) ('Training Accuracy:', 0.95091796) ('Testing Accuracy:', 0.57999998)
Step 951: loss = 601778.16 (11.538 sec) ('Training Accuracy:', 0.97264892) ('Testing Accuracy:', 0.62)
Step 952: loss = 573506.99 (11.642 sec) ('Training Accuracy:', 0.96365678) ('Testing Accuracy:', 0.61333334)
Step 953: loss = 309869.80 (12.950 sec) ('Training Accuracy:', 0.94005245) ('Testing Accuracy:', 0.56999999)
Step 954: loss = 548634.56 (12.777 sec) ('Training Accuracy:', 0.92581493) ('Testing Accuracy:', 0.54333335)
Step 955: loss = 761629.91 (12.572 sec) ('Training Accuracy:', 0.96403146) ('Testing Accuracy:', 0.58666664)
Step 956: loss = 575045.57 (12.635 sec) ('Training Accuracy:', 0.9584114) ('Testing Accuracy:', 0.58999997)
Step 957: loss = 233247.51 (12.700 sec) ('Training Accuracy:', 0.96777821) ('Testing Accuracy:', 0.57666665)
Step 958: loss = 1030901.35 (12.700 sec) ('Training Accuracy:', 0.96515548) ('Testing Accuracy:', 0.57666665)
Step 959: loss = 436845.45 (12.699 sec) ('Training Accuracy:', 0.92956161) ('Testing Accuracy:', 0.56999999)
Step 960: loss = 784764.55 (12.660 sec) ('Training Accuracy:', 0.89659047) ('Testing Accuracy:', 0.57333332)
Step 961: loss = 931682.81 (12.723 sec) ('Training Accuracy:', 0.92956161) ('Testing Accuracy:', 0.57333332)
Step 962: loss = 729839.30 (12.975 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.57666665)
Step 963: loss = 743693.99 (12.928 sec) ('Training Accuracy:', 0.92281753) ('Testing Accuracy:', 0.57666665)
Step 964: loss = 1055940.61 (13.198 sec) ('Training Accuracy:', 0.97377294) ('Testing Accuracy:', 0.61000001)
Step 965: loss = 1117884.80 (13.163 sec) ('Training Accuracy:', 0.91195202) ('Testing Accuracy:', 0.57999998)
Step 966: loss = 1491177.35 (12.994 sec) ('Training Accuracy:', 0.8801049) ('Testing Accuracy:', 0.55333334)
Step 967: loss = 841525.38 (12.694 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.61333334)
Step 968: loss = 415584.00 (12.706 sec) ('Training Accuracy:', 0.95279133) ('Testing Accuracy:', 0.59666669)
Step 969: loss = 443077.20 (12.966 sec) ('Training Accuracy:', 0.94342452) ('Testing Accuracy:', 0.56666666)
Step 970: loss = 504314.62 (12.569 sec) ('Training Accuracy:', 0.95091796) ('Testing Accuracy:', 0.58333331)
Step 971: loss = 516254.59 (12.442 sec) ('Training Accuracy:', 0.96328211) ('Testing Accuracy:', 0.60333335)
Step 972: loss = 478385.20 (12.690 sec) ('Training Accuracy:', 0.95279133) ('Testing Accuracy:', 0.60666668)
Step 973: loss = 602866.78 (12.282 sec) ('Training Accuracy:', 0.93443239) ('Testing Accuracy:', 0.58999997)
Step 974: loss = 686923.28 (12.183 sec) ('Training Accuracy:', 0.97264892) ('Testing Accuracy:', 0.60000002)
Step 975: loss = 172173.94 (12.016 sec) ('Training Accuracy:', 0.95054328) ('Testing Accuracy:', 0.58333331)
Step 976: loss = 517676.69 (12.033 sec) ('Training Accuracy:', 0.97189957) ('Testing Accuracy:', 0.59666669)
Step 977: loss = 267033.06 (12.222 sec) ('Training Accuracy:', 0.97602099) ('Testing Accuracy:', 0.61333334)
Step 978: loss = 4672687.09 (12.016 sec) ('Training Accuracy:', 0.90108657) ('Testing Accuracy:', 0.6566667)
Step 979: loss = 4094497.29 (11.745 sec) ('Training Accuracy:', 0.90783066) ('Testing Accuracy:', 0.57666665)
Step 980: loss = 5566997.66 (11.591 sec) ('Training Accuracy:', 0.95466465) ('Testing Accuracy:', 0.57666665)
Step 981: loss = 4494088.17 (11.202 sec) ('Training Accuracy:', 0.89284378) ('Testing Accuracy:', 0.57333332)
Step 982: loss = 3334961.63 (10.907 sec) ('Training Accuracy:', 0.93405771) ('Testing Accuracy:', 0.58333331)
Step 983: loss = 1285707.84 (10.967 sec) ('Training Accuracy:', 0.92394155) ('Testing Accuracy:', 0.58666664)
Step 984: loss = 706279.55 (13.476 sec) ('Training Accuracy:', 0.95878607) ('Testing Accuracy:', 0.5933333)
Step 985: loss = 577954.70 (12.875 sec) ('Training Accuracy:', 0.97789437) ('Testing Accuracy:', 0.62)
Step 986: loss = 1390533.20 (12.664 sec) ('Training Accuracy:', 0.97339827) ('Testing Accuracy:', 0.62333333)
Step 987: loss = 260757.04 (12.390 sec) ('Training Accuracy:', 0.96890223) ('Testing Accuracy:', 0.60333335)
Step 988: loss = 296113.90 (12.086 sec) ('Training Accuracy:', 0.96290743) ('Testing Accuracy:', 0.60000002)
Step 989: loss = 417159.83 (11.833 sec) ('Training Accuracy:', 0.92244285) ('Testing Accuracy:', 0.5933333)
Step 990: loss = 1083802.70 (11.448 sec) ('Training Accuracy:', 0.95728737) ('Testing Accuracy:', 0.62)
Step 991: loss = 242461.63 (11.415 sec) ('Training Accuracy:', 0.96852756) ('Testing Accuracy:', 0.62)
Step 992: loss = 126421.27 (11.352 sec) ('Training Accuracy:', 0.96328211) ('Testing Accuracy:', 0.61333334)
Step 993: loss = 149449.24 (10.919 sec) ('Training Accuracy:', 0.96740353) ('Testing Accuracy:', 0.62666667)
Step 994: loss = 283666.40 (10.769 sec) ('Training Accuracy:', 0.94005245) ('Testing Accuracy:', 0.61333334)
Step 995: loss = 774035.92 (16.658 sec) ('Training Accuracy:', 0.97040087) ('Testing Accuracy:', 0.61000001)
Step 996: loss = 359850.90 (15.574 sec) ('Training Accuracy:', 0.96028477) ('Testing Accuracy:', 0.60666668)
Step 997: loss = 492872.47 (13.036 sec) ('Training Accuracy:', 0.94904459) ('Testing Accuracy:', 0.58999997)
Step 998: loss = 1239235.01 (12.963 sec) ('Training Accuracy:', 0.97751969) ('Testing Accuracy:', 0.61000001)
Step 999: loss = 533878.74 (13.145 sec) ('Training Accuracy:', 0.95803672) ('Testing Accuracy:', 0.58333331)

In [41]:

    

if __name__ == '__main__':
    train_acc_whole, test_acc_whole = main()


    

    




Step 0: loss = 426029532.00 (9.126 sec) ('Training Accuracy:', 0.58883059) ('Testing Accuracy:', 0.57999998)
Step 1: loss = 224952667.00 (10.641 sec) ('Training Accuracy:', 0.54610193) ('Testing Accuracy:', 0.47666666)
Step 2: loss = 186282770.50 (8.754 sec) ('Training Accuracy:', 0.57608694) ('Testing Accuracy:', 0.52666664)
Step 3: loss = 157188716.00 (8.744 sec) ('Training Accuracy:', 0.6064468) ('Testing Accuracy:', 0.55000001)
Step 4: loss = 141595672.00 (9.254 sec) ('Training Accuracy:', 0.60607195) ('Testing Accuracy:', 0.53666669)
Step 5: loss = 126091908.00 (9.422 sec) ('Training Accuracy:', 0.61731637) ('Testing Accuracy:', 0.56333333)
Step 6: loss = 114848935.00 (9.681 sec) ('Training Accuracy:', 0.62668663) ('Testing Accuracy:', 0.56333333)
Step 7: loss = 108071643.00 (10.035 sec) ('Training Accuracy:', 0.61731637) ('Testing Accuracy:', 0.52666664)
Step 8: loss = 101031114.25 (10.724 sec) ('Training Accuracy:', 0.6555472) ('Testing Accuracy:', 0.55000001)
Step 9: loss = 89654806.25 (11.714 sec) ('Training Accuracy:', 0.67278862) ('Testing Accuracy:', 0.55000001)
Step 10: loss = 85552654.00 (9.702 sec) ('Training Accuracy:', 0.69265366) ('Testing Accuracy:', 0.55666667)
Step 11: loss = 81913617.00 (9.555 sec) ('Training Accuracy:', 0.65929538) ('Testing Accuracy:', 0.52999997)
Step 12: loss = 77064685.00 (9.489 sec) ('Training Accuracy:', 0.62293851) ('Testing Accuracy:', 0.53333336)
Step 13: loss = 80015069.50 (9.322 sec) ('Training Accuracy:', 0.71026987) ('Testing Accuracy:', 0.56333333)
Step 14: loss = 67080248.25 (9.416 sec) ('Training Accuracy:', 0.72526234) ('Testing Accuracy:', 0.57333332)
Step 15: loss = 58869580.75 (9.331 sec) ('Training Accuracy:', 0.72901052) ('Testing Accuracy:', 0.56999999)
Step 16: loss = 58326910.12 (10.160 sec) ('Training Accuracy:', 0.73313344) ('Testing Accuracy:', 0.58666664)
Step 17: loss = 58034449.00 (9.773 sec) ('Training Accuracy:', 0.71251875) ('Testing Accuracy:', 0.57999998)
Step 18: loss = 62831454.50 (9.645 sec) ('Training Accuracy:', 0.6248126) ('Testing Accuracy:', 0.52333331)
Step 19: loss = 63375930.75 (10.027 sec) ('Training Accuracy:', 0.74925035) ('Testing Accuracy:', 0.5933333)
Step 20: loss = 46641569.62 (9.908 sec) ('Training Accuracy:', 0.72901052) ('Testing Accuracy:', 0.57333332)
Step 21: loss = 41932935.50 (9.403 sec) ('Training Accuracy:', 0.70502251) ('Testing Accuracy:', 0.56)
Step 22: loss = 41006496.12 (9.426 sec) ('Training Accuracy:', 0.69527733) ('Testing Accuracy:', 0.54333335)
Step 23: loss = 44299790.62 (9.426 sec) ('Training Accuracy:', 0.66491753) ('Testing Accuracy:', 0.54333335)
Step 24: loss = 49466509.12 (11.818 sec) ('Training Accuracy:', 0.77398801) ('Testing Accuracy:', 0.5933333)
Step 25: loss = 42891045.44 (10.288 sec) ('Training Accuracy:', 0.78073466) ('Testing Accuracy:', 0.5933333)
Step 26: loss = 39914399.81 (9.320 sec) ('Training Accuracy:', 0.78335834) ('Testing Accuracy:', 0.60333335)
Step 27: loss = 37795694.94 (9.350 sec) ('Training Accuracy:', 0.75) ('Testing Accuracy:', 0.56)
Step 28: loss = 32752923.56 (9.339 sec) ('Training Accuracy:', 0.69902551) ('Testing Accuracy:', 0.55333334)
Step 29: loss = 35684171.25 (9.404 sec) ('Training Accuracy:', 0.77136433) ('Testing Accuracy:', 0.55666667)
Step 30: loss = 38982585.25 (9.385 sec) ('Training Accuracy:', 0.77698648) ('Testing Accuracy:', 0.5933333)
Step 31: loss = 34695286.62 (9.366 sec) ('Training Accuracy:', 0.80509746) ('Testing Accuracy:', 0.58666664)
Step 32: loss = 26054191.62 (9.333 sec) ('Training Accuracy:', 0.77548724) ('Testing Accuracy:', 0.56333333)
Step 33: loss = 25358123.75 (9.357 sec) ('Training Accuracy:', 0.76424289) ('Testing Accuracy:', 0.56999999)
Step 34: loss = 30589545.75 (9.348 sec) ('Training Accuracy:', 0.81334335) ('Testing Accuracy:', 0.60666668)
Step 35: loss = 27675356.38 (9.376 sec) ('Training Accuracy:', 0.80547225) ('Testing Accuracy:', 0.61333334)
Step 36: loss = 33145911.19 (9.356 sec) ('Training Accuracy:', 0.82571214) ('Testing Accuracy:', 0.60666668)
Step 37: loss = 30411526.19 (9.364 sec) ('Training Accuracy:', 0.74325335) ('Testing Accuracy:', 0.54666668)
Step 38: loss = 25455991.81 (9.402 sec) ('Training Accuracy:', 0.82046479) ('Testing Accuracy:', 0.57999998)
Step 39: loss = 22723115.19 (9.565 sec) ('Training Accuracy:', 0.82158923) ('Testing Accuracy:', 0.61000001)
Step 40: loss = 20002658.56 (9.375 sec) ('Training Accuracy:', 0.83508247) ('Testing Accuracy:', 0.61000001)
Step 41: loss = 19361546.19 (9.749 sec) ('Training Accuracy:', 0.83995503) ('Testing Accuracy:', 0.60333335)
Step 42: loss = 22202976.50 (9.386 sec) ('Training Accuracy:', 0.75712144) ('Testing Accuracy:', 0.54333335)
Step 43: loss = 23513616.38 (9.391 sec) ('Training Accuracy:', 0.77023989) ('Testing Accuracy:', 0.55000001)
Step 44: loss = 27179202.81 (9.410 sec) ('Training Accuracy:', 0.82833582) ('Testing Accuracy:', 0.60000002)
Step 45: loss = 21226474.00 (9.425 sec) ('Training Accuracy:', 0.84032983) ('Testing Accuracy:', 0.62)
Step 46: loss = 15283243.44 (9.393 sec) ('Training Accuracy:', 0.84932536) ('Testing Accuracy:', 0.58666664)
Step 47: loss = 14546324.36 (9.395 sec) ('Training Accuracy:', 0.84782606) ('Testing Accuracy:', 0.56999999)
Step 48: loss = 15312461.91 (9.396 sec) ('Training Accuracy:', 0.86431783) ('Testing Accuracy:', 0.60333335)
Step 49: loss = 14166081.03 (9.617 sec) ('Training Accuracy:', 0.82421291) ('Testing Accuracy:', 0.61666667)
Step 50: loss = 12861097.22 (9.408 sec) ('Training Accuracy:', 0.85194904) ('Testing Accuracy:', 0.59666669)
Step 51: loss = 13107681.19 (9.410 sec) ('Training Accuracy:', 0.86019492) ('Testing Accuracy:', 0.60333335)
Step 52: loss = 17308273.98 (9.435 sec) ('Training Accuracy:', 0.86731637) ('Testing Accuracy:', 0.56666666)
Step 53: loss = 18621086.22 (9.418 sec) ('Training Accuracy:', 0.78073466) ('Testing Accuracy:', 0.56666666)
Step 54: loss = 22935028.00 (9.415 sec) ('Training Accuracy:', 0.83508247) ('Testing Accuracy:', 0.61000001)
Step 55: loss = 15029956.69 (10.997 sec) ('Training Accuracy:', 0.84107947) ('Testing Accuracy:', 0.63)
Step 56: loss = 11003999.48 (10.723 sec) ('Training Accuracy:', 0.89692652) ('Testing Accuracy:', 0.59666669)
Step 57: loss = 12986028.48 (10.746 sec) ('Training Accuracy:', 0.88530737) ('Testing Accuracy:', 0.58999997)
Step 58: loss = 11954772.16 (9.421 sec) ('Training Accuracy:', 0.83958024) ('Testing Accuracy:', 0.62333333)
Step 59: loss = 9056116.42 (13.001 sec) ('Training Accuracy:', 0.85269862) ('Testing Accuracy:', 0.62666667)
Step 60: loss = 8344364.16 (12.653 sec) ('Training Accuracy:', 0.89430285) ('Testing Accuracy:', 0.58999997)
Step 61: loss = 9189772.67 (11.761 sec) ('Training Accuracy:', 0.8871814) ('Testing Accuracy:', 0.60333335)
Step 62: loss = 9341318.45 (11.193 sec) ('Training Accuracy:', 0.87593704) ('Testing Accuracy:', 0.61000001)
Step 63: loss = 9920537.85 (10.898 sec) ('Training Accuracy:', 0.80434781) ('Testing Accuracy:', 0.63666666)
Step 64: loss = 8383309.82 (10.722 sec) ('Training Accuracy:', 0.8384558) ('Testing Accuracy:', 0.62333333)
Step 65: loss = 10826752.83 (10.730 sec) ('Training Accuracy:', 0.88380808) ('Testing Accuracy:', 0.60333335)
Step 66: loss = 13013856.51 (10.853 sec) ('Training Accuracy:', 0.89242882) ('Testing Accuracy:', 0.60666668)
Step 67: loss = 14072208.31 (11.010 sec) ('Training Accuracy:', 0.80097449) ('Testing Accuracy:', 0.5933333)
Step 68: loss = 18675499.52 (9.556 sec) ('Training Accuracy:', 0.87143928) ('Testing Accuracy:', 0.59666669)
Step 69: loss = 13050844.09 (10.715 sec) ('Training Accuracy:', 0.78673166) ('Testing Accuracy:', 0.63)
Step 70: loss = 8885308.95 (12.792 sec) ('Training Accuracy:', 0.89880061) ('Testing Accuracy:', 0.61000001)
Step 71: loss = 9413656.33 (11.315 sec) ('Training Accuracy:', 0.89580208) ('Testing Accuracy:', 0.60333335)
Step 72: loss = 8710781.31 (13.270 sec) ('Training Accuracy:', 0.84482759) ('Testing Accuracy:', 0.62333333)
Step 73: loss = 8195955.78 (10.734 sec) ('Training Accuracy:', 0.80847079) ('Testing Accuracy:', 0.62666667)
Step 74: loss = 6936969.05 (11.333 sec) ('Training Accuracy:', 0.82008994) ('Testing Accuracy:', 0.63)
Step 75: loss = 10303023.97 (11.494 sec) ('Training Accuracy:', 0.88530737) ('Testing Accuracy:', 0.61666667)
Step 76: loss = 13775262.54 (10.492 sec) ('Training Accuracy:', 0.89805096) ('Testing Accuracy:', 0.62)
Step 77: loss = 10242179.84 (10.786 sec) ('Training Accuracy:', 0.81934035) ('Testing Accuracy:', 0.63)
Step 78: loss = 8890276.34 (12.698 sec) ('Training Accuracy:', 0.75149924) ('Testing Accuracy:', 0.63666666)
Step 79: loss = 8227712.47 (9.078 sec) ('Training Accuracy:', 0.84032983) ('Testing Accuracy:', 0.63)
Step 80: loss = 13244309.14 (11.328 sec) ('Training Accuracy:', 0.89430285) ('Testing Accuracy:', 0.61000001)
Step 81: loss = 10337012.60 (11.848 sec) ('Training Accuracy:', 0.81559223) ('Testing Accuracy:', 0.62333333)
Step 82: loss = 8453461.79 (12.584 sec) ('Training Accuracy:', 0.78373313) ('Testing Accuracy:', 0.62666667)
Step 83: loss = 9870046.39 (10.715 sec) ('Training Accuracy:', 0.80247378) ('Testing Accuracy:', 0.63)
Step 84: loss = 17328368.84 (13.047 sec) ('Training Accuracy:', 0.8931784) ('Testing Accuracy:', 0.62)
Step 85: loss = 12948314.46 (11.349 sec) ('Training Accuracy:', 0.84670162) ('Testing Accuracy:', 0.62666667)
Step 86: loss = 15412731.34 (11.874 sec) ('Training Accuracy:', 0.72226387) ('Testing Accuracy:', 0.63333333)
Step 87: loss = 15804714.06 (10.422 sec) ('Training Accuracy:', 0.83658171) ('Testing Accuracy:', 0.63333333)
Step 88: loss = 21457124.75 (13.039 sec) ('Training Accuracy:', 0.83583206) ('Testing Accuracy:', 0.62666667)
Step 89: loss = 20142729.45 (11.190 sec) ('Training Accuracy:', 0.71889055) ('Testing Accuracy:', 0.63333333)
Step 90: loss = 27826314.36 (9.843 sec) ('Training Accuracy:', 0.84032983) ('Testing Accuracy:', 0.63333333)
Step 91: loss = 31311189.73 (10.694 sec) ('Training Accuracy:', 0.76686656) ('Testing Accuracy:', 0.63)
Step 92: loss = 45068816.97 (10.714 sec) ('Training Accuracy:', 0.85569715) ('Testing Accuracy:', 0.62666667)
Step 93: loss = 88961379.75 (13.035 sec) ('Training Accuracy:', 0.52286357) ('Testing Accuracy:', 0.46333334)
Step 94: loss = 75792273.81 (11.719 sec) ('Training Accuracy:', 0.60869563) ('Testing Accuracy:', 0.51333332)
Step 95: loss = 36363155.62 (12.313 sec) ('Training Accuracy:', 0.67391306) ('Testing Accuracy:', 0.54333335)
Step 96: loss = 21577088.25 (12.695 sec) ('Training Accuracy:', 0.73988008) ('Testing Accuracy:', 0.56)
Step 97: loss = 15113438.94 (12.439 sec) ('Training Accuracy:', 0.73200899) ('Testing Accuracy:', 0.56)
Step 98: loss = 14594591.00 (12.147 sec) ('Training Accuracy:', 0.71326834) ('Testing Accuracy:', 0.55333334)
Step 99: loss = 18162409.05 (11.401 sec) ('Training Accuracy:', 0.71551722) ('Testing Accuracy:', 0.55333334)
Step 100: loss = 16155284.47 (8.666 sec) ('Training Accuracy:', 0.64805096) ('Testing Accuracy:', 0.53666669)
Step 101: loss = 19141610.17 (12.564 sec) ('Training Accuracy:', 0.66416794) ('Testing Accuracy:', 0.55000001)
Step 102: loss = 23858619.38 (13.051 sec) ('Training Accuracy:', 0.60869563) ('Testing Accuracy:', 0.52999997)
Step 103: loss = 25700369.62 (12.754 sec) ('Training Accuracy:', 0.57721138) ('Testing Accuracy:', 0.51333332)
Step 104: loss = 33211937.44 (12.527 sec) ('Training Accuracy:', 0.62856072) ('Testing Accuracy:', 0.54000002)
Step 105: loss = 46563278.11 (10.677 sec) ('Training Accuracy:', 0.82908547) ('Testing Accuracy:', 0.5933333)
Step 106: loss = 37289355.83 (10.901 sec) ('Training Accuracy:', 0.90967017) ('Testing Accuracy:', 0.61666667)
Step 107: loss = 14006467.02 (8.691 sec) ('Training Accuracy:', 0.8871814) ('Testing Accuracy:', 0.63333333)
Step 108: loss = 8373297.75 (13.584 sec) ('Training Accuracy:', 0.93590707) ('Testing Accuracy:', 0.58666664)
Step 109: loss = 3751938.35 (8.694 sec) ('Training Accuracy:', 0.8875562) ('Testing Accuracy:', 0.60666668)
Step 110: loss = 2435829.56 (12.222 sec) ('Training Accuracy:', 0.94040477) ('Testing Accuracy:', 0.59666669)
Step 111: loss = 1653715.44 (12.649 sec) ('Training Accuracy:', 0.9374063) ('Testing Accuracy:', 0.58999997)
Step 112: loss = 1125858.38 (8.695 sec) ('Training Accuracy:', 0.94790107) ('Testing Accuracy:', 0.58333331)
Step 113: loss = 1395072.32 (12.360 sec) ('Training Accuracy:', 0.93590707) ('Testing Accuracy:', 0.5933333)
Step 114: loss = 1441289.46 (11.490 sec) ('Training Accuracy:', 0.89580208) ('Testing Accuracy:', 0.59666669)
Step 115: loss = 1858063.37 (10.998 sec) ('Training Accuracy:', 0.85907048) ('Testing Accuracy:', 0.58999997)
Step 116: loss = 2930907.20 (10.667 sec) ('Training Accuracy:', 0.9115442) ('Testing Accuracy:', 0.60000002)
Step 117: loss = 4108250.93 (12.347 sec) ('Training Accuracy:', 0.95089954) ('Testing Accuracy:', 0.5933333)
Step 118: loss = 2316005.00 (11.432 sec) ('Training Accuracy:', 0.96064466) ('Testing Accuracy:', 0.60000002)
Step 119: loss = 1655669.61 (10.844 sec) ('Training Accuracy:', 0.95239878) ('Testing Accuracy:', 0.59666669)
Step 120: loss = 1332849.53 (10.710 sec) ('Training Accuracy:', 0.88080961) ('Testing Accuracy:', 0.58666664)
Step 121: loss = 1052116.82 (12.520 sec) ('Training Accuracy:', 0.93290854) ('Testing Accuracy:', 0.60333335)
Step 122: loss = 851671.72 (8.727 sec) ('Training Accuracy:', 0.9314093) ('Testing Accuracy:', 0.61000001)
Step 123: loss = 834169.01 (12.641 sec) ('Training Accuracy:', 0.93103451) ('Testing Accuracy:', 0.59666669)
Step 124: loss = 708624.39 (12.476 sec) ('Training Accuracy:', 0.89842576) ('Testing Accuracy:', 0.61333334)
Step 125: loss = 762462.31 (12.298 sec) ('Training Accuracy:', 0.93215895) ('Testing Accuracy:', 0.60666668)
Step 126: loss = 783008.54 (12.683 sec) ('Training Accuracy:', 0.92166418) ('Testing Accuracy:', 0.60666668)
Step 127: loss = 594597.42 (8.680 sec) ('Training Accuracy:', 0.90367317) ('Testing Accuracy:', 0.59666669)
Step 128: loss = 539832.56 (11.750 sec) ('Training Accuracy:', 0.91191906) ('Testing Accuracy:', 0.61000001)
Step 129: loss = 728731.84 (10.376 sec) ('Training Accuracy:', 0.92616194) ('Testing Accuracy:', 0.60000002)
Step 130: loss = 815291.16 (13.088 sec) ('Training Accuracy:', 0.91866565) ('Testing Accuracy:', 0.5933333)
Step 131: loss = 725704.27 (9.136 sec) ('Training Accuracy:', 0.94002998) ('Testing Accuracy:', 0.59666669)
Step 132: loss = 1232904.54 (13.123 sec) ('Training Accuracy:', 0.94827586) ('Testing Accuracy:', 0.60333335)
Step 133: loss = 1591561.16 (10.751 sec) ('Training Accuracy:', 0.87368816) ('Testing Accuracy:', 0.58999997)
Step 134: loss = 2303481.95 (8.699 sec) ('Training Accuracy:', 0.80097449) ('Testing Accuracy:', 0.58666664)
Step 135: loss = 2976461.80 (13.041 sec) ('Training Accuracy:', 0.76386809) ('Testing Accuracy:', 0.57333332)
Step 136: loss = 2992737.08 (13.073 sec) ('Training Accuracy:', 0.74137932) ('Testing Accuracy:', 0.55666667)
Step 137: loss = 4582258.09 (12.731 sec) ('Training Accuracy:', 0.80509746) ('Testing Accuracy:', 0.57666665)
Step 138: loss = 5710100.31 (13.074 sec) ('Training Accuracy:', 0.78523237) ('Testing Accuracy:', 0.55666667)
Step 139: loss = 4966673.62 (10.608 sec) ('Training Accuracy:', 0.78223389) ('Testing Accuracy:', 0.56999999)
Step 140: loss = 6762539.03 (12.610 sec) ('Training Accuracy:', 0.8564468) ('Testing Accuracy:', 0.58999997)
Step 141: loss = 8871429.79 (12.223 sec) ('Training Accuracy:', 0.77098948) ('Testing Accuracy:', 0.58333331)
Step 142: loss = 5689932.70 (8.598 sec) ('Training Accuracy:', 0.8931784) ('Testing Accuracy:', 0.60000002)
Step 143: loss = 8287650.51 (10.776 sec) ('Training Accuracy:', 0.89692652) ('Testing Accuracy:', 0.60666668)
Step 144: loss = 12436754.34 (13.284 sec) ('Training Accuracy:', 0.76086956) ('Testing Accuracy:', 0.57666665)
Step 145: loss = 7391531.65 (9.517 sec) ('Training Accuracy:', 0.91754121) ('Testing Accuracy:', 0.60666668)
Step 146: loss = 11401076.64 (10.806 sec) ('Training Accuracy:', 0.91829085) ('Testing Accuracy:', 0.60666668)
Step 147: loss = 14405756.42 (12.990 sec) ('Training Accuracy:', 0.90217394) ('Testing Accuracy:', 0.61666667)
Step 148: loss = 13239142.30 (12.875 sec) ('Training Accuracy:', 0.94265366) ('Testing Accuracy:', 0.62)
Step 149: loss = 13013731.06 (12.871 sec) ('Training Accuracy:', 0.90779608) ('Testing Accuracy:', 0.62)
Step 150: loss = 17781802.04 (12.288 sec) ('Training Accuracy:', 0.92728639) ('Testing Accuracy:', 0.63666666)
Step 151: loss = 16908961.40 (10.729 sec) ('Training Accuracy:', 0.84820092) ('Testing Accuracy:', 0.62333333)
Step 152: loss = 19222037.67 (13.021 sec) ('Training Accuracy:', 0.81634182) ('Testing Accuracy:', 0.62333333)
Step 153: loss = 24364147.20 (12.439 sec) ('Training Accuracy:', 0.73838079) ('Testing Accuracy:', 0.63666666)
Step 154: loss = 33248213.39 (11.548 sec) ('Training Accuracy:', 0.73088455) ('Testing Accuracy:', 0.63666666)
Step 155: loss = 41211383.05 (8.712 sec) ('Training Accuracy:', 0.81971514) ('Testing Accuracy:', 0.63666666)
Step 156: loss = 55149071.14 (13.299 sec) ('Training Accuracy:', 0.84407794) ('Testing Accuracy:', 0.60666668)
Step 157: loss = 41013604.23 (10.599 sec) ('Training Accuracy:', 0.69827586) ('Testing Accuracy:', 0.56333333)
Step 158: loss = 16904060.17 (12.878 sec) ('Training Accuracy:', 0.74812591) ('Testing Accuracy:', 0.57333332)
Step 159: loss = 6928442.22 (12.533 sec) ('Training Accuracy:', 0.95914543) ('Testing Accuracy:', 0.61666667)
Step 160: loss = 2317022.49 (11.751 sec) ('Training Accuracy:', 0.90854573) ('Testing Accuracy:', 0.63)
Step 161: loss = 901205.35 (8.551 sec) ('Training Accuracy:', 0.94565219) ('Testing Accuracy:', 0.62333333)
Step 162: loss = 1298400.81 (13.293 sec) ('Training Accuracy:', 0.89805096) ('Testing Accuracy:', 0.61666667)
Step 163: loss = 1186828.25 (12.125 sec) ('Training Accuracy:', 0.94302851) ('Testing Accuracy:', 0.61666667)
Step 164: loss = 1189311.26 (11.644 sec) ('Training Accuracy:', 0.88943028) ('Testing Accuracy:', 0.63)
Step 165: loss = 1012839.18 (10.699 sec) ('Training Accuracy:', 0.90929538) ('Testing Accuracy:', 0.63999999)
Step 166: loss = 1514862.73 (10.576 sec) ('Training Accuracy:', 0.91229385) ('Testing Accuracy:', 0.62333333)
Step 167: loss = 1174471.40 (10.605 sec) ('Training Accuracy:', 0.87143928) ('Testing Accuracy:', 0.60000002)
Step 168: loss = 927927.92 (8.869 sec) ('Training Accuracy:', 0.92278862) ('Testing Accuracy:', 0.62333333)
Step 169: loss = 1565452.66 (13.748 sec) ('Training Accuracy:', 0.85869563) ('Testing Accuracy:', 0.60666668)
Step 170: loss = 1139212.31 (8.581 sec) ('Training Accuracy:', 0.92203897) ('Testing Accuracy:', 0.62666667)
Step 171: loss = 1746855.62 (9.367 sec) ('Training Accuracy:', 0.9190405) ('Testing Accuracy:', 0.62)
Step 172: loss = 1816754.37 (9.259 sec) ('Training Accuracy:', 0.88493252) ('Testing Accuracy:', 0.61000001)
Step 173: loss = 698150.52 (9.265 sec) ('Training Accuracy:', 0.92616194) ('Testing Accuracy:', 0.61666667)
Step 174: loss = 1633830.42 (10.938 sec) ('Training Accuracy:', 0.84220392) ('Testing Accuracy:', 0.58666664)
Step 175: loss = 883139.86 (11.669 sec) ('Training Accuracy:', 0.89730138) ('Testing Accuracy:', 0.62333333)
Step 176: loss = 1715352.24 (12.332 sec) ('Training Accuracy:', 0.94715142) ('Testing Accuracy:', 0.60666668)
Step 177: loss = 1473932.27 (12.623 sec) ('Training Accuracy:', 0.87781107) ('Testing Accuracy:', 0.63)
Step 178: loss = 1010308.35 (11.846 sec) ('Training Accuracy:', 0.90592206) ('Testing Accuracy:', 0.63)
Step 179: loss = 1634586.10 (11.101 sec) ('Training Accuracy:', 0.87968516) ('Testing Accuracy:', 0.63333333)
Step 180: loss = 1459322.77 (8.750 sec) ('Training Accuracy:', 0.87818593) ('Testing Accuracy:', 0.63)
Step 181: loss = 1321644.12 (11.818 sec) ('Training Accuracy:', 0.89992505) ('Testing Accuracy:', 0.63666666)
Step 182: loss = 1515196.27 (12.898 sec) ('Training Accuracy:', 0.83883059) ('Testing Accuracy:', 0.5933333)
Step 183: loss = 915201.64 (12.604 sec) ('Training Accuracy:', 0.84632683) ('Testing Accuracy:', 0.61000001)
Step 184: loss = 1521248.67 (12.322 sec) ('Training Accuracy:', 0.90667164) ('Testing Accuracy:', 0.63)
Step 185: loss = 1639029.61 (11.886 sec) ('Training Accuracy:', 0.80772114) ('Testing Accuracy:', 0.57999998)
Step 186: loss = 944550.26 (8.599 sec) ('Training Accuracy:', 0.8935532) ('Testing Accuracy:', 0.63333333)
Step 187: loss = 1369346.59 (13.352 sec) ('Training Accuracy:', 0.84820092) ('Testing Accuracy:', 0.59666669)
Step 188: loss = 1068114.73 (8.791 sec) ('Training Accuracy:', 0.90967017) ('Testing Accuracy:', 0.63)
Step 189: loss = 1659861.63 (11.485 sec) ('Training Accuracy:', 0.89992505) ('Testing Accuracy:', 0.61000001)
Step 190: loss = 1582409.10 (10.791 sec) ('Training Accuracy:', 0.9070465) ('Testing Accuracy:', 0.63333333)
Step 191: loss = 1649002.86 (10.685 sec) ('Training Accuracy:', 0.87931037) ('Testing Accuracy:', 0.61000001)
Step 192: loss = 1591082.07 (10.723 sec) ('Training Accuracy:', 0.7942279) ('Testing Accuracy:', 0.57999998)
Step 193: loss = 1011975.45 (8.743 sec) ('Training Accuracy:', 0.9377811) ('Testing Accuracy:', 0.61666667)
Step 194: loss = 2106047.64 (13.252 sec) ('Training Accuracy:', 0.80734634) ('Testing Accuracy:', 0.58666664)
Step 195: loss = 773179.10 (13.345 sec) ('Training Accuracy:', 0.92278862) ('Testing Accuracy:', 0.63333333)
Step 196: loss = 1794033.51 (13.421 sec) ('Training Accuracy:', 0.77736133) ('Testing Accuracy:', 0.57666665)
Step 197: loss = 838986.29 (13.209 sec) ('Training Accuracy:', 0.93028486) ('Testing Accuracy:', 0.62333333)
Step 198: loss = 1570517.23 (11.115 sec) ('Training Accuracy:', 0.77661169) ('Testing Accuracy:', 0.57666665)
Step 199: loss = 1654617.32 (13.469 sec) ('Training Accuracy:', 0.90892053) ('Testing Accuracy:', 0.61666667)

In [24]:

    

if __name__ == '__main__':
    train_acc_face, test_acc_face = main()


    

    




Step 0: loss = 378075023.00 (9.125 sec) ('Training Accuracy:', 0.57999253) ('Testing Accuracy:', 0.58333331)
Step 1: loss = 212032418.00 (9.085 sec) ('Training Accuracy:', 0.5533908) ('Testing Accuracy:', 0.52333331)
Step 2: loss = 176671522.00 (8.689 sec) ('Training Accuracy:', 0.54627204) ('Testing Accuracy:', 0.50666666)
Step 3: loss = 162068939.00 (8.989 sec) ('Training Accuracy:', 0.53016108) ('Testing Accuracy:', 0.48666668)
Step 4: loss = 159282855.00 (12.244 sec) ('Training Accuracy:', 0.54140127) ('Testing Accuracy:', 0.49000001)
Step 5: loss = 168716221.00 (9.482 sec) ('Training Accuracy:', 0.64968151) ('Testing Accuracy:', 0.5933333)
Step 6: loss = 142647160.00 (9.258 sec) ('Training Accuracy:', 0.67103785) ('Testing Accuracy:', 0.63999999)
Step 7: loss = 112778716.75 (9.235 sec) ('Training Accuracy:', 0.66654176) ('Testing Accuracy:', 0.57666665)
Step 8: loss = 99121671.00 (9.277 sec) ('Training Accuracy:', 0.65792429) ('Testing Accuracy:', 0.57666665)
Step 9: loss = 88507973.00 (9.271 sec) ('Training Accuracy:', 0.66691643) ('Testing Accuracy:', 0.58666664)
Step 10: loss = 81780810.25 (9.246 sec) ('Training Accuracy:', 0.65305358) ('Testing Accuracy:', 0.56333333)
Step 11: loss = 75277717.25 (9.269 sec) ('Training Accuracy:', 0.6418134) ('Testing Accuracy:', 0.57666665)
Step 12: loss = 69309493.50 (9.259 sec) ('Training Accuracy:', 0.65492696) ('Testing Accuracy:', 0.58666664)
Step 13: loss = 64986339.88 (9.272 sec) ('Training Accuracy:', 0.70138627) ('Testing Accuracy:', 0.58666664)
Step 14: loss = 63652648.00 (9.398 sec) ('Training Accuracy:', 0.70663172) ('Testing Accuracy:', 0.58333331)
Step 15: loss = 65310698.75 (11.770 sec) ('Training Accuracy:', 0.6095916) ('Testing Accuracy:', 0.52666664)
Step 16: loss = 58602175.25 (11.871 sec) ('Training Accuracy:', 0.64780819) ('Testing Accuracy:', 0.57666665)
Step 17: loss = 49588613.00 (11.886 sec) ('Training Accuracy:', 0.68602473) ('Testing Accuracy:', 0.59666669)
Step 18: loss = 48643172.50 (10.020 sec) ('Training Accuracy:', 0.72686398) ('Testing Accuracy:', 0.58333331)
Step 19: loss = 48847229.50 (11.835 sec) ('Training Accuracy:', 0.69763958) ('Testing Accuracy:', 0.58333331)
Step 20: loss = 49633919.00 (12.311 sec) ('Training Accuracy:', 0.61708504) ('Testing Accuracy:', 0.54333335)
Step 21: loss = 47221449.38 (11.828 sec) ('Training Accuracy:', 0.65342826) ('Testing Accuracy:', 0.55666667)
Step 22: loss = 40823729.38 (11.119 sec) ('Training Accuracy:', 0.727988) ('Testing Accuracy:', 0.60000002)
Step 23: loss = 39729872.06 (15.716 sec) ('Training Accuracy:', 0.7632072) ('Testing Accuracy:', 0.60666668)
Step 24: loss = 46205886.50 (12.486 sec) ('Training Accuracy:', 0.64705884) ('Testing Accuracy:', 0.56333333)
Step 25: loss = 36421775.62 (11.401 sec) ('Training Accuracy:', 0.64406145) ('Testing Accuracy:', 0.55000001)
Step 26: loss = 33777914.25 (11.217 sec) ('Training Accuracy:', 0.6863994) ('Testing Accuracy:', 0.58333331)
Step 27: loss = 31505380.19 (14.486 sec) ('Training Accuracy:', 0.74747097) ('Testing Accuracy:', 0.5933333)
Step 28: loss = 32600376.81 (9.251 sec) ('Training Accuracy:', 0.78006744) ('Testing Accuracy:', 0.58666664)
Step 29: loss = 42770438.94 (9.197 sec) ('Training Accuracy:', 0.61034095) ('Testing Accuracy:', 0.54000002)
Step 30: loss = 32284330.75 (9.180 sec) ('Training Accuracy:', 0.64630949) ('Testing Accuracy:', 0.55000001)
Step 31: loss = 27778072.31 (9.530 sec) ('Training Accuracy:', 0.70775568) ('Testing Accuracy:', 0.58999997)
Step 32: loss = 25293868.62 (10.207 sec) ('Training Accuracy:', 0.78980893) ('Testing Accuracy:', 0.60666668)
Step 33: loss = 29061990.25 (9.271 sec) ('Training Accuracy:', 0.76245785) ('Testing Accuracy:', 0.57666665)
Step 34: loss = 34253443.38 (9.516 sec) ('Training Accuracy:', 0.62270516) ('Testing Accuracy:', 0.50666666)
Step 35: loss = 28274009.31 (9.455 sec) ('Training Accuracy:', 0.62270516) ('Testing Accuracy:', 0.52666664)
Step 36: loss = 29042395.44 (10.735 sec) ('Training Accuracy:', 0.72723866) ('Testing Accuracy:', 0.57999998)
Step 37: loss = 38152532.88 (10.407 sec) ('Training Accuracy:', 0.6849007) ('Testing Accuracy:', 0.56)
Step 38: loss = 28427231.19 (9.398 sec) ('Training Accuracy:', 0.66167104) ('Testing Accuracy:', 0.54333335)
Step 39: loss = 26309689.00 (9.571 sec) ('Training Accuracy:', 0.6702885) ('Testing Accuracy:', 0.55666667)
Step 40: loss = 29372912.38 (10.419 sec) ('Training Accuracy:', 0.73136008) ('Testing Accuracy:', 0.57666665)
Step 41: loss = 46783776.06 (10.099 sec) ('Training Accuracy:', 0.66953915) ('Testing Accuracy:', 0.54000002)
Step 42: loss = 47717038.44 (9.627 sec) ('Training Accuracy:', 0.75009364) ('Testing Accuracy:', 0.57666665)
Step 43: loss = 77173276.72 (9.450 sec) ('Training Accuracy:', 0.75458974) ('Testing Accuracy:', 0.68000001)
Step 44: loss = 94689813.38 (9.204 sec) ('Training Accuracy:', 0.71112776) ('Testing Accuracy:', 0.67333335)
Step 45: loss = 58290207.00 (9.591 sec) ('Training Accuracy:', 0.79093295) ('Testing Accuracy:', 0.67333335)
Step 46: loss = 36940022.62 (9.448 sec) ('Training Accuracy:', 0.81041586) ('Testing Accuracy:', 0.6566667)
Step 47: loss = 29427957.12 (9.881 sec) ('Training Accuracy:', 0.80966651) ('Testing Accuracy:', 0.66333336)
Step 48: loss = 25434166.69 (10.244 sec) ('Training Accuracy:', 0.81116521) ('Testing Accuracy:', 0.66666669)
Step 49: loss = 26188929.94 (9.986 sec) ('Training Accuracy:', 0.80591983) ('Testing Accuracy:', 0.66666669)
Step 50: loss = 24333451.41 (12.170 sec) ('Training Accuracy:', 0.76882726) ('Testing Accuracy:', 0.67333335)
Step 51: loss = 28568492.97 (12.383 sec) ('Training Accuracy:', 0.80554515) ('Testing Accuracy:', 0.66333336)
Step 52: loss = 33304935.56 (12.331 sec) ('Training Accuracy:', 0.74634695) ('Testing Accuracy:', 0.67000002)
Step 53: loss = 42922473.38 (9.395 sec) ('Training Accuracy:', 0.78418881) ('Testing Accuracy:', 0.66000003)
Step 54: loss = 50733045.09 (9.213 sec) ('Training Accuracy:', 0.83327091) ('Testing Accuracy:', 0.60666668)
Step 55: loss = 28062024.97 (10.326 sec) ('Training Accuracy:', 0.82053202) ('Testing Accuracy:', 0.5933333)
Step 56: loss = 15598944.25 (9.750 sec) ('Training Accuracy:', 0.84113902) ('Testing Accuracy:', 0.58666664)
Step 57: loss = 10348425.91 (14.025 sec) ('Training Accuracy:', 0.88235295) ('Testing Accuracy:', 0.61000001)
Step 58: loss = 9133836.77 (12.237 sec) ('Training Accuracy:', 0.89584112) ('Testing Accuracy:', 0.63999999)
Step 59: loss = 8934813.39 (12.634 sec) ('Training Accuracy:', 0.90071189) ('Testing Accuracy:', 0.63999999)
Step 60: loss = 8929143.45 (13.307 sec) ('Training Accuracy:', 0.89996254) ('Testing Accuracy:', 0.64666665)
Step 61: loss = 11290217.25 (14.592 sec) ('Training Accuracy:', 0.87186211) ('Testing Accuracy:', 0.64666665)
Step 62: loss = 10148158.47 (12.748 sec) ('Training Accuracy:', 0.8355189) ('Testing Accuracy:', 0.66000003)
Step 63: loss = 13067948.09 (12.562 sec) ('Training Accuracy:', 0.84750843) ('Testing Accuracy:', 0.65333331)
Step 64: loss = 18079552.27 (9.726 sec) ('Training Accuracy:', 0.81153989) ('Testing Accuracy:', 0.66333336)
Step 65: loss = 19576015.62 (9.640 sec) ('Training Accuracy:', 0.77294868) ('Testing Accuracy:', 0.66333336)
Step 66: loss = 26050765.86 (9.348 sec) ('Training Accuracy:', 0.77969277) ('Testing Accuracy:', 0.65333331)
Step 67: loss = 39679058.25 (9.294 sec) ('Training Accuracy:', 0.89321846) ('Testing Accuracy:', 0.63666666)
Step 68: loss = 37006827.62 (10.708 sec) ('Training Accuracy:', 0.70363432) ('Testing Accuracy:', 0.55666667)
Step 69: loss = 28206006.34 (10.643 sec) ('Training Accuracy:', 0.70513302) ('Testing Accuracy:', 0.54666668)
Step 70: loss = 16569617.25 (12.707 sec) ('Training Accuracy:', 0.78119147) ('Testing Accuracy:', 0.5933333)
Step 71: loss = 13385024.16 (9.752 sec) ('Training Accuracy:', 0.82652676) ('Testing Accuracy:', 0.60333335)
Step 72: loss = 18940011.12 (10.928 sec) ('Training Accuracy:', 0.91082805) ('Testing Accuracy:', 0.63)
Step 73: loss = 11432492.44 (11.069 sec) ('Training Accuracy:', 0.89883852) ('Testing Accuracy:', 0.65333331)
Step 74: loss = 8642526.48 (10.294 sec) ('Training Accuracy:', 0.90146124) ('Testing Accuracy:', 0.64999998)
Step 75: loss = 11742948.62 (12.015 sec) ('Training Accuracy:', 0.91757214) ('Testing Accuracy:', 0.64999998)
Step 76: loss = 12375814.58 (11.576 sec) ('Training Accuracy:', 0.92131883) ('Testing Accuracy:', 0.64999998)
Step 77: loss = 11392987.84 (12.489 sec) ('Training Accuracy:', 0.85612589) ('Testing Accuracy:', 0.59666669)
Step 78: loss = 10565273.59 (11.293 sec) ('Training Accuracy:', 0.78606218) ('Testing Accuracy:', 0.58333331)
Step 79: loss = 8912511.23 (11.171 sec) ('Training Accuracy:', 0.78756088) ('Testing Accuracy:', 0.58666664)
Step 80: loss = 12772973.31 (13.037 sec) ('Training Accuracy:', 0.83402026) ('Testing Accuracy:', 0.60000002)
Step 81: loss = 13356383.89 (11.474 sec) ('Training Accuracy:', 0.91907084) ('Testing Accuracy:', 0.62666667)
Step 82: loss = 12515259.78 (10.791 sec) ('Training Accuracy:', 0.92918694) ('Testing Accuracy:', 0.64333332)
Step 83: loss = 13478315.59 (8.904 sec) ('Training Accuracy:', 0.90520793) ('Testing Accuracy:', 0.66333336)
Step 84: loss = 13291018.06 (15.351 sec) ('Training Accuracy:', 0.86024725) ('Testing Accuracy:', 0.66000003)
Step 85: loss = 13555939.03 (12.557 sec) ('Training Accuracy:', 0.81153989) ('Testing Accuracy:', 0.67666668)
Step 86: loss = 15943514.52 (10.584 sec) ('Training Accuracy:', 0.82315475) ('Testing Accuracy:', 0.66333336)
Step 87: loss = 20529191.12 (12.573 sec) ('Training Accuracy:', 0.92731363) ('Testing Accuracy:', 0.66000003)
Step 88: loss = 15854629.30 (11.986 sec) ('Training Accuracy:', 0.87523419) ('Testing Accuracy:', 0.60333335)
Step 89: loss = 10473615.41 (11.185 sec) ('Training Accuracy:', 0.80591983) ('Testing Accuracy:', 0.57333332)
Step 90: loss = 7508223.06 (9.360 sec) ('Training Accuracy:', 0.80741853) ('Testing Accuracy:', 0.57333332)
Step 91: loss = 9337590.16 (11.672 sec) ('Training Accuracy:', 0.93967777) ('Testing Accuracy:', 0.63666666)
Step 92: loss = 5404360.88 (15.353 sec) ('Training Accuracy:', 0.94117647) ('Testing Accuracy:', 0.65333331)
Step 93: loss = 4347192.23 (15.581 sec) ('Training Accuracy:', 0.94567251) ('Testing Accuracy:', 0.64666665)
Step 94: loss = 2892400.45 (11.090 sec) ('Training Accuracy:', 0.91270137) ('Testing Accuracy:', 0.63666666)
Step 95: loss = 2662264.84 (13.696 sec) ('Training Accuracy:', 0.94155115) ('Testing Accuracy:', 0.63999999)
Step 96: loss = 2279111.11 (13.579 sec) ('Training Accuracy:', 0.95166731) ('Testing Accuracy:', 0.63666666)
Step 97: loss = 1828196.06 (13.004 sec) ('Training Accuracy:', 0.94829524) ('Testing Accuracy:', 0.66000003)
Step 98: loss = 1936287.60 (11.009 sec) ('Training Accuracy:', 0.95466465) ('Testing Accuracy:', 0.64999998)
Step 99: loss = 1404072.05 (14.041 sec) ('Training Accuracy:', 0.9437992) ('Testing Accuracy:', 0.63999999)
Step 100: loss = 1826759.23 (11.938 sec) ('Training Accuracy:', 0.86586738) ('Testing Accuracy:', 0.60666668)
Step 101: loss = 2623515.85 (12.217 sec) ('Training Accuracy:', 0.85687524) ('Testing Accuracy:', 0.59666669)
Step 102: loss = 5310587.39 (11.636 sec) ('Training Accuracy:', 0.82802546) ('Testing Accuracy:', 0.58999997)
Step 103: loss = 5140542.64 (11.203 sec) ('Training Accuracy:', 0.955414) ('Testing Accuracy:', 0.64999998)
Step 104: loss = 4257954.34 (13.007 sec) ('Training Accuracy:', 0.93255901) ('Testing Accuracy:', 0.64666665)
Step 105: loss = 5176554.70 (8.558 sec) ('Training Accuracy:', 0.92506558) ('Testing Accuracy:', 0.64666665)
Step 106: loss = 6416615.37 (8.951 sec) ('Training Accuracy:', 0.85724992) ('Testing Accuracy:', 0.67333335)
Step 107: loss = 7040457.54 (9.396 sec) ('Training Accuracy:', 0.87223679) ('Testing Accuracy:', 0.6566667)
Step 108: loss = 10963599.23 (9.265 sec) ('Training Accuracy:', 0.81079054) ('Testing Accuracy:', 0.66000003)
Step 109: loss = 13090877.56 (9.274 sec) ('Training Accuracy:', 0.88272762) ('Testing Accuracy:', 0.6566667)
Step 110: loss = 17318501.66 (9.318 sec) ('Training Accuracy:', 0.8977145) ('Testing Accuracy:', 0.6566667)
Step 111: loss = 20058047.98 (9.290 sec) ('Training Accuracy:', 0.93742973) ('Testing Accuracy:', 0.63666666)
Step 112: loss = 28778759.91 (9.273 sec) ('Training Accuracy:', 0.80666918) ('Testing Accuracy:', 0.58999997)
Step 113: loss = 29648552.28 (9.278 sec) ('Training Accuracy:', 0.63132262) ('Testing Accuracy:', 0.52999997)
Step 114: loss = 28474337.03 (9.258 sec) ('Training Accuracy:', 0.5811165) ('Testing Accuracy:', 0.49000001)
Step 115: loss = 33302148.00 (9.261 sec) ('Training Accuracy:', 0.60284752) ('Testing Accuracy:', 0.5)
Step 116: loss = 31130747.70 (12.013 sec) ('Training Accuracy:', 0.71562386) ('Testing Accuracy:', 0.55000001)
Step 117: loss = 31471304.84 (13.822 sec) ('Training Accuracy:', 0.89808917) ('Testing Accuracy:', 0.62)
Step 118: loss = 32829190.62 (12.612 sec) ('Training Accuracy:', 0.87748218) ('Testing Accuracy:', 0.67333335)
Step 119: loss = 21472036.42 (11.235 sec) ('Training Accuracy:', 0.86324465) ('Testing Accuracy:', 0.6566667)
Step 120: loss = 9435949.64 (9.792 sec) ('Training Accuracy:', 0.94417387) ('Testing Accuracy:', 0.64666665)
Step 121: loss = 3780964.98 (13.091 sec) ('Training Accuracy:', 0.92993629) ('Testing Accuracy:', 0.63999999)
Step 122: loss = 2042414.19 (10.581 sec) ('Training Accuracy:', 0.95916075) ('Testing Accuracy:', 0.64333332)
Step 123: loss = 1163070.14 (10.529 sec) ('Training Accuracy:', 0.94604719) ('Testing Accuracy:', 0.62333333)
Step 124: loss = 924202.41 (9.863 sec) ('Training Accuracy:', 0.94042712) ('Testing Accuracy:', 0.63333333)
Step 125: loss = 858442.12 (14.711 sec) ('Training Accuracy:', 0.95354062) ('Testing Accuracy:', 0.63333333)
Step 126: loss = 1172240.91 (10.662 sec) ('Training Accuracy:', 0.96590483) ('Testing Accuracy:', 0.63)
Step 127: loss = 745958.84 (12.928 sec) ('Training Accuracy:', 0.95204198) ('Testing Accuracy:', 0.63999999)
Step 128: loss = 846377.99 (12.246 sec) ('Training Accuracy:', 0.95204198) ('Testing Accuracy:', 0.62333333)
Step 129: loss = 699080.22 (11.865 sec) ('Training Accuracy:', 0.96665418) ('Testing Accuracy:', 0.63999999)
Step 130: loss = 677216.77 (8.707 sec) ('Training Accuracy:', 0.94567251) ('Testing Accuracy:', 0.63)
Step 131: loss = 645740.24 (12.544 sec) ('Training Accuracy:', 0.93443239) ('Testing Accuracy:', 0.62666667)
Step 132: loss = 768924.92 (8.544 sec) ('Training Accuracy:', 0.96440613) ('Testing Accuracy:', 0.63666666)
Step 133: loss = 803453.95 (10.048 sec) ('Training Accuracy:', 0.96815288) ('Testing Accuracy:', 0.64666665)
Step 134: loss = 651669.15 (10.568 sec) ('Training Accuracy:', 0.90595728) ('Testing Accuracy:', 0.62)
Step 135: loss = 788936.07 (13.354 sec) ('Training Accuracy:', 0.95204198) ('Testing Accuracy:', 0.63)
Step 136: loss = 614202.75 (11.984 sec) ('Training Accuracy:', 0.9539153) ('Testing Accuracy:', 0.62333333)
Step 137: loss = 530493.97 (12.494 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.62333333)
Step 138: loss = 392806.05 (11.960 sec) ('Training Accuracy:', 0.92806292) ('Testing Accuracy:', 0.62666667)
Step 139: loss = 566014.52 (8.931 sec) ('Training Accuracy:', 0.95991009) ('Testing Accuracy:', 0.62666667)
Step 140: loss = 386271.54 (10.969 sec) ('Training Accuracy:', 0.92806292) ('Testing Accuracy:', 0.63)
Step 141: loss = 486272.38 (12.951 sec) ('Training Accuracy:', 0.94417387) ('Testing Accuracy:', 0.64333332)
Step 142: loss = 395432.23 (10.622 sec) ('Training Accuracy:', 0.92918694) ('Testing Accuracy:', 0.62666667)
Step 143: loss = 447975.41 (11.362 sec) ('Training Accuracy:', 0.9393031) ('Testing Accuracy:', 0.63333333)
Step 144: loss = 372770.17 (11.471 sec) ('Training Accuracy:', 0.96215808) ('Testing Accuracy:', 0.63333333)
Step 145: loss = 352918.12 (12.213 sec) ('Training Accuracy:', 0.93630576) ('Testing Accuracy:', 0.62666667)
Step 146: loss = 355124.07 (9.062 sec) ('Training Accuracy:', 0.97115022) ('Testing Accuracy:', 0.64666665)
Step 147: loss = 456909.70 (12.128 sec) ('Training Accuracy:', 0.96890223) ('Testing Accuracy:', 0.63666666)
Step 148: loss = 798388.78 (9.803 sec) ('Training Accuracy:', 0.95878607) ('Testing Accuracy:', 0.62)
Step 149: loss = 638638.34 (14.307 sec) ('Training Accuracy:', 0.90670663) ('Testing Accuracy:', 0.62)
Step 150: loss = 2109086.57 (12.886 sec) ('Training Accuracy:', 0.89733982) ('Testing Accuracy:', 0.62666667)
Step 151: loss = 2778929.48 (12.644 sec) ('Training Accuracy:', 0.96290743) ('Testing Accuracy:', 0.62)
Step 152: loss = 3089009.06 (10.637 sec) ('Training Accuracy:', 0.94829524) ('Testing Accuracy:', 0.67000002)
Step 153: loss = 2182305.75 (14.059 sec) ('Training Accuracy:', 0.95241666) ('Testing Accuracy:', 0.66000003)
Step 154: loss = 3476103.53 (12.011 sec) ('Training Accuracy:', 0.92843759) ('Testing Accuracy:', 0.66000003)
Step 155: loss = 5590399.78 (11.575 sec) ('Training Accuracy:', 0.93443239) ('Testing Accuracy:', 0.66000003)
Step 156: loss = 6600468.72 (10.783 sec) ('Training Accuracy:', 0.95766205) ('Testing Accuracy:', 0.64666665)
Step 157: loss = 6320869.77 (11.152 sec) ('Training Accuracy:', 0.9584114) ('Testing Accuracy:', 0.64333332)
Step 158: loss = 7380197.56 (9.874 sec) ('Training Accuracy:', 0.94117647) ('Testing Accuracy:', 0.62666667)
Step 159: loss = 9508995.38 (11.523 sec) ('Training Accuracy:', 0.92056948) ('Testing Accuracy:', 0.62)
Step 160: loss = 9784804.50 (13.902 sec) ('Training Accuracy:', 0.79880106) ('Testing Accuracy:', 0.58999997)
Step 161: loss = 11859037.41 (9.020 sec) ('Training Accuracy:', 0.72648931) ('Testing Accuracy:', 0.55666667)
Step 162: loss = 16476803.92 (12.288 sec) ('Training Accuracy:', 0.69351816) ('Testing Accuracy:', 0.55000001)
Step 163: loss = 11797117.39 (12.663 sec) ('Training Accuracy:', 0.61820906) ('Testing Accuracy:', 0.50333333)
Step 164: loss = 22075594.12 (13.123 sec) ('Training Accuracy:', 0.59048331) ('Testing Accuracy:', 0.47333333)
Step 165: loss = 19916174.25 (13.609 sec) ('Training Accuracy:', 0.57811916) ('Testing Accuracy:', 0.46666667)
Step 166: loss = 33714443.84 (15.771 sec) ('Training Accuracy:', 0.55901086) ('Testing Accuracy:', 0.45333335)
Step 167: loss = 44183234.89 (12.818 sec) ('Training Accuracy:', 0.69726491) ('Testing Accuracy:', 0.53666669)
Step 168: loss = 65983670.94 (13.226 sec) ('Training Accuracy:', 0.9276883) ('Testing Accuracy:', 0.64999998)
Step 169: loss = 51171913.31 (11.217 sec) ('Training Accuracy:', 0.75796181) ('Testing Accuracy:', 0.68000001)
Step 170: loss = 29479579.59 (13.450 sec) ('Training Accuracy:', 0.82053202) ('Testing Accuracy:', 0.67000002)
Step 171: loss = 17327752.55 (11.807 sec) ('Training Accuracy:', 0.94679654) ('Testing Accuracy:', 0.64999998)
Step 172: loss = 6127291.58 (12.579 sec) ('Training Accuracy:', 0.88834769) ('Testing Accuracy:', 0.62)
Step 173: loss = 3311510.38 (12.609 sec) ('Training Accuracy:', 0.95878607) ('Testing Accuracy:', 0.64333332)
Step 174: loss = 929487.80 (8.564 sec) ('Training Accuracy:', 0.94604719) ('Testing Accuracy:', 0.64333332)
Step 175: loss = 734706.59 (12.644 sec) ('Training Accuracy:', 0.94454855) ('Testing Accuracy:', 0.63666666)
Step 176: loss = 658669.98 (11.574 sec) ('Training Accuracy:', 0.94604719) ('Testing Accuracy:', 0.63999999)
Step 177: loss = 574889.62 (12.827 sec) ('Training Accuracy:', 0.93630576) ('Testing Accuracy:', 0.63)
Step 178: loss = 860356.54 (11.053 sec) ('Training Accuracy:', 0.96215808) ('Testing Accuracy:', 0.62666667)
Step 179: loss = 529679.75 (13.731 sec) ('Training Accuracy:', 0.92731363) ('Testing Accuracy:', 0.63666666)
Step 180: loss = 1441939.42 (12.501 sec) ('Training Accuracy:', 0.94567251) ('Testing Accuracy:', 0.62)
Step 181: loss = 438367.40 (12.458 sec) ('Training Accuracy:', 0.94567251) ('Testing Accuracy:', 0.63999999)
Step 182: loss = 573388.60 (12.524 sec) ('Training Accuracy:', 0.92656428) ('Testing Accuracy:', 0.63333333)
Step 183: loss = 556241.68 (11.290 sec) ('Training Accuracy:', 0.93817908) ('Testing Accuracy:', 0.63666666)
Step 184: loss = 1024660.35 (8.585 sec) ('Training Accuracy:', 0.91345072) ('Testing Accuracy:', 0.62)
Step 185: loss = 502808.12 (14.593 sec) ('Training Accuracy:', 0.9201948) ('Testing Accuracy:', 0.63666666)
Step 186: loss = 1123655.02 (11.577 sec) ('Training Accuracy:', 0.89921319) ('Testing Accuracy:', 0.62)
Step 187: loss = 694844.85 (13.284 sec) ('Training Accuracy:', 0.90445858) ('Testing Accuracy:', 0.62)
Step 188: loss = 1390375.47 (10.900 sec) ('Training Accuracy:', 0.94417387) ('Testing Accuracy:', 0.62666667)
Step 189: loss = 848402.23 (11.196 sec) ('Training Accuracy:', 0.88497567) ('Testing Accuracy:', 0.61666667)
Step 190: loss = 856792.70 (11.045 sec) ('Training Accuracy:', 0.91794682) ('Testing Accuracy:', 0.63333333)
Step 191: loss = 1091310.82 (11.415 sec) ('Training Accuracy:', 0.90370923) ('Testing Accuracy:', 0.62)
Step 192: loss = 904004.46 (12.026 sec) ('Training Accuracy:', 0.88609964) ('Testing Accuracy:', 0.61000001)
Step 193: loss = 1361018.20 (12.564 sec) ('Training Accuracy:', 0.94829524) ('Testing Accuracy:', 0.63)
Step 194: loss = 922140.53 (12.726 sec) ('Training Accuracy:', 0.88422632) ('Testing Accuracy:', 0.61333334)
Step 195: loss = 1251015.41 (12.311 sec) ('Training Accuracy:', 0.87073809) ('Testing Accuracy:', 0.60666668)
Step 196: loss = 1687105.11 (8.636 sec) ('Training Accuracy:', 0.96328211) ('Testing Accuracy:', 0.63666666)
Step 197: loss = 880879.95 (12.628 sec) ('Training Accuracy:', 0.91270137) ('Testing Accuracy:', 0.62666667)
Step 198: loss = 737316.34 (12.655 sec) ('Training Accuracy:', 0.89958787) ('Testing Accuracy:', 0.62333333)
Step 199: loss = 1456403.48 (12.405 sec) ('Training Accuracy:', 0.93443239) ('Testing Accuracy:', 0.62666667)

In [53]:

    

max(train_acc)


    

    
Out[53]:





0.98051703

In [52]:

    

max(test_acc)


    

    
Out[52]:





0.67000002

In [50]:

    

x = np.arange(1000)

plt.plot(x, train_acc)
#plt.plot(x, test_acc)


plt.legend(['y = training_samples', 'y = testing_samples'], loc='lower right')

plt.show()


    

In [51]:

    

x = np.arange(1000)

plt.plot(x, test_acc)


plt.legend(['y = testing_samples'], loc='lower right')

plt.show()


    

In [ ]:

    




    

In [55]:

    

accuracy_list = pd.DataFrame(
    {'Training_Acc': train_acc,
     'Testing_Acc': test_acc,
    })


    

In [59]:

    

accuracy_list.plot()


    

    
Out[59]:





<matplotlib.axes.AxesSubplot at 0x7f6118139810>






    

In [25]:

    

accuracy_list_face = pd.DataFrame(
    {'Training_Acc': train_acc_face,
     'Testing_Acc': test_acc_face,
    })
accuracy_list_face.plot()


    

    
Out[25]:





<matplotlib.axes.AxesSubplot at 0x7fbaf3f39a10>






    

In [44]:

    

accuracy_list_whole = pd.DataFrame(
    {'Training_Acc': train_acc_whole,
     'Testing_Acc': test_acc_whole,
    })

ax = accuracy_list_whole.plot(title='Age Classification for whole Image')
ax.set_xlabel("Samples")
ax.set_ylabel("Accuracy")


    

    
Out[44]:





<matplotlib.text.Text at 0x7fbb3c07f090>






    

In [ ]:

    




    

In [ ]: