Read Data Sample

In [1]:

    

import pandas as pd
import numpy as np
import os
from collections import namedtuple
pd.set_option("display.max_rows",1000)
%matplotlib inline


    

In [2]:

    

class dataset:
    kdd_train_2labels = pd.read_pickle("dataset/kdd_train__2labels.pkl")
    kdd_test_2labels = pd.read_pickle("dataset/kdd_test_2labels.pkl")
    kdd_test__2labels = pd.read_pickle("dataset/kdd_test__2labels.pkl")

    kdd_train_5labels = pd.read_pickle("dataset/kdd_train_5labels.pkl")
    kdd_test_5labels = pd.read_pickle("dataset/kdd_test_5labels.pkl")


    

In [3]:

    

dataset.kdd_train_2labels.shape


    

    
Out[3]:





(25192, 124)

In [4]:

    

dataset.kdd_test_2labels.shape


    

    
Out[4]:





(22544, 124)

In [5]:

    

from sklearn import model_selection as ms
from sklearn import preprocessing as pp

class preprocess:
    
    output_columns_2labels = ['is_Normal','is_Attack']
    
    x_input = dataset.kdd_train_2labels.drop(output_columns_2labels, axis = 1)
    y_output = dataset.kdd_train_2labels.loc[:,output_columns_2labels]

    x_test_input = dataset.kdd_test_2labels.drop(output_columns_2labels, axis = 1)
    y_test = dataset.kdd_test_2labels.loc[:,output_columns_2labels]
    
    x_test__input = dataset.kdd_test__2labels.drop(output_columns_2labels, axis = 1)
    y_test_ = dataset.kdd_test__2labels.loc[:,output_columns_2labels]

    ss = pp.StandardScaler()

    x_train = ss.fit_transform(x_input)
    x_test = ss.transform(x_test_input)
    x_test_ = ss.transform(x_test__input)

    y_train = y_output.values
    y_test = y_test.values
    y_test_ = y_test_.values

preprocess.x_train.shape


    

    
Out[5]:





(25192, 122)

In [6]:

    

import tensorflow as tf


    

In [7]:

    

class network(object):
    
    input_dim = 122
    classes = 2
    hidden_encoder_dim = 122
    hidden_layers = 1
    latent_dim = 18

    def __init__(self, classes, hidden_layers, num_of_features):
        self.classes = classes
        self.hidden_layers = hidden_layers
        self.latent_dim = num_of_features
            
    def build_layers(self):
        tf.reset_default_graph()
        #learning_rate = tf.Variable(initial_value=0.001)

        input_dim = self.input_dim
        classes = self.classes
        hidden_encoder_dim = self.hidden_encoder_dim
        hidden_layers = self.hidden_layers
        latent_dim = self.latent_dim
        
        with tf.variable_scope("Input"):
            self.x = tf.placeholder("float", shape=[None, input_dim])
            self.y_ = tf.placeholder("float", shape=[None, classes])
            self.keep_prob = tf.placeholder("float")
            self.lr = tf.placeholder("float")
        
        with tf.variable_scope("Layer_Encoder"):

            hidden_encoder = tf.layers.dense(self.x, hidden_encoder_dim, activation = tf.nn.relu, kernel_regularizer=tf.nn.l2_loss)
            hidden_encoder = tf.nn.dropout(hidden_encoder, self.keep_prob)
            for h in range(hidden_layers - 1):
                hidden_encoder = tf.layers.dense(hidden_encoder, latent_dim, activation = tf.nn.relu, kernel_regularizer=tf.nn.l2_loss)
                hidden_encoder = tf.nn.dropout(hidden_encoder, self.keep_prob)
            
            #hidden_encoder = tf.layers.dense(self.x, latent_dim, activation = tf.nn.relu, kernel_regularizer=tf.nn.l2_loss)
            #hidden_encoder = tf.nn.dropout(hidden_encoder, self.keep_prob)
            
        with tf.variable_scope("Layer_Dense_Softmax"):
            self.y = tf.layers.dense(hidden_encoder, classes, activation=tf.nn.softmax)
            
        with tf.variable_scope("Loss"):
            
            loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels = self.y_, logits = self.y))

            #loss = tf.clip_by_value(loss, -1e-1, 1e-1)
            #loss = tf.where(tf.is_nan(loss), 1e-1, loss)
            #loss = tf.where(tf.equal(loss, -1e-1), tf.random_normal(loss.shape), loss)
            #loss = tf.where(tf.equal(loss, 1e-1), tf.random_normal(loss.shape), loss)
            
            self.regularized_loss = loss
            correct_prediction = tf.equal(tf.argmax(self.y_, 1), tf.argmax(self.y, 1))
            self.tf_accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32), name = "Accuracy")

        with tf.variable_scope("Optimizer"):
            learning_rate=self.lr
            optimizer = tf.train.AdamOptimizer(learning_rate)
            gradients, variables = zip(*optimizer.compute_gradients(self.regularized_loss))
            gradients = [
                None if gradient is None else tf.clip_by_value(gradient, -1, 1)
                for gradient in gradients]
            self.train_op = optimizer.apply_gradients(zip(gradients, variables))
            #self.train_op = optimizer.minimize(self.regularized_loss)
            
        # add op for merging summary
        #self.summary_op = tf.summary.merge_all()
        self.pred = tf.argmax(self.y, axis = 1)
        self.actual = tf.argmax(self.y_, axis = 1)

        # add Saver ops
        self.saver = tf.train.Saver()


    

In [8]:

    

import collections
import time

class Train:    
    
    result = namedtuple("score", ['epoch', 'no_of_features','hidden_layers','train_score', 'test_score', 'test_score_20', 'time_taken'])

    predictions = {}
    predictions_ = {}

    results = []
    
    best_acc = 0
    best_acc_global = 0
    
    def train(epochs, net, h,f, lrs):
        batch_iterations = 200
        train_loss = None
        Train.best_acc = 0
        os.makedirs("dataset/tf_dense_only_nsl_kdd-/hidden layers_{}_features count_{}".format(epochs,h,f),
                    exist_ok = True)
        with tf.Session() as sess:
            #summary_writer_train = tf.summary.FileWriter('./logs/kdd/VAE/training', graph=sess.graph)
            #summary_writer_valid = tf.summary.FileWriter('./logs/kdd/VAE/validation')

            sess.run(tf.global_variables_initializer())
            start_time = time.perf_counter()
            for c, lr in enumerate(lrs):
                for epoch in range(1, (epochs+1)):
                    x_train, x_valid, y_train, y_valid, = ms.train_test_split(preprocess.x_train, 
                                                                              preprocess.y_train, 
                                                                              test_size=0.1)
                    batch_indices = np.array_split(np.arange(x_train.shape[0]), 
                                               batch_iterations)

                    for i in batch_indices:

                        def train_batch():
                            nonlocal train_loss
                            _, train_loss = sess.run([net.train_op, 
                                                               net.regularized_loss, 
                                                               ], #net.summary_op
                                                              feed_dict={net.x: x_train[i,:], 
                                                                         net.y_: y_train[i,:], 
                                                                         net.keep_prob:0.5, net.lr:lr})

                        train_batch()
                        #summary_writer_train.add_summary(summary_str, epoch)
                        while((train_loss > 1e4 or np.isnan(train_loss)) and epoch > 1):
                            print("Step {} | Training Loss: {:.6f}".format(epoch, train_loss))
                            net.saver.restore(sess, 
                                              tf.train.latest_checkpoint('dataset/tf_dense_only_nsl_kdd/hidden_layers_{}_features_count_{}'
                                                                         .format(epochs,h,f)))
                            train_batch()


                    valid_accuracy = sess.run(net.tf_accuracy, #net.summary_op 
                                                          feed_dict={net.x: x_valid, 
                                                                     net.y_: y_valid, 
                                                                     net.keep_prob:1, net.lr:lr})
                    #summary_writer_valid.add_summary(summary_str, epoch)


                    accuracy, pred_value, actual_value, y_pred = sess.run([net.tf_accuracy, 
                                                                   net.pred, 
                                                                   net.actual, net.y], 
                                                                  feed_dict={net.x: preprocess.x_test, 
                                                                             net.y_: preprocess.y_test, 
                                                                             net.keep_prob:1, net.lr:lr})
                    
                    accuracy_, pred_value_, actual_value_, y_pred_ = sess.run([net.tf_accuracy, 
                                                                   net.pred, 
                                                                   net.actual, net.y], 
                                                                  feed_dict={net.x: preprocess.x_test_, 
                                                                             net.y_: preprocess.y_test_, 
                                                                             net.keep_prob:1, net.lr:lr})

                    print("Step {} | Training Loss: {:.6f} | Validation Accuracy: {:.6f}".format(epoch, train_loss, valid_accuracy))
                    print("Accuracy on Test data: {}, {}".format(accuracy, accuracy_))

                    if accuracy > Train.best_acc_global:
                        Train.best_acc_global = accuracy
                        Train.pred_value = pred_value
                        Train.actual_value = actual_value
                        Train.pred_value_ = pred_value_
                        Train.actual_value_ = actual_value_
                        Train.best_parameters = "Hidden Layers:{}, Features Count:{}".format(h, f)

                    if accuracy > Train.best_acc:
                        Train.best_acc = accuracy

                        if not (np.isnan(train_loss)):
                            net.saver.save(sess, 
                                       "dataset/tf_dense_only_nsl_kdd-/hidden_layers_{}_features_count_{}".format(h,f),
                                        global_step = epochs)
                        curr_pred = pd.DataFrame({"Attack_prob":y_pred[:,-2], "Normal_prob":y_pred[:, -1], "Prediction":pred_value})
                        curr_pred_ = pd.DataFrame({"Attack_prob":y_pred_[:,-2], "Normal_prob":y_pred_[:, -1], "Prediction":pred_value_})
                        
                        Train.predictions.update({"{}_{}_{}".format((epoch+1)*(c+1),f,h):(curr_pred,
                                                   Train.result((epoch+1)*(c+1), f, h, valid_accuracy, accuracy, accuracy_, time.perf_counter() - start_time))})
                        Train.predictions_.update({"{}_{}_{}".format((epoch+1)*(c+1),f,h):(curr_pred_,
                                                   Train.result((epoch+1)*(c+1), f, h, valid_accuracy, accuracy, accuracy_, time.perf_counter() - start_time))})

                        #Train.results.append(Train.result(epochs, f, h,valid_accuracy, accuracy))


    

In [9]:

    

import itertools
df_results = []
past_scores = []

class Hyperparameters:
#    features_arr = [2, 4, 8, 16, 32, 64, 128, 256]
#    hidden_layers_arr = [2, 4, 6, 10]

    def start_training():
        global df_results
        global past_scores
        
        features_arr = [1, 12, 24, 48, 122]
        hidden_layers_arr = [1, 3]

        Train.predictions = {}
        Train.results = []

        epochs = [10]
        lrs = [1e-5, 1e-6]
        for e, h, f in itertools.product(epochs, hidden_layers_arr, features_arr):
            print("Current Layer Attributes - epochs:{} hidden layers:{} features count:{}".format(e,h,f))
            n = network(2,h,f)
            n.build_layers()
            Train.train(e, n, h,f, lrs)
        dict1 = {}
        dict1_ = {}

        dict2 = []
        for k, (v1, v2) in Train.predictions.items():
            dict1.update({k: v1})
            dict2.append(v2)
            
        for k, (v1_, v2) in Train.predictions.items():
            dict1_.update({k: v1_})

        Train.predictions = dict1
        Train.predictions_ = dict1_

        Train.results = dict2
        df_results = pd.DataFrame(Train.results)
        temp = df_results.set_index(['no_of_features', 'hidden_layers'])

        if not os.path.isfile('dataset/scores/tf_dense_only_nsl_kdd_scores_all-.pkl'):
            past_scores = temp
        else:
            past_scores = pd.read_pickle("dataset/scores/tf_dense_only_nsl_kdd_scores_all-.pkl")

        past_scores.append(temp).to_pickle("dataset/scores/tf_dense_only_nsl_kdd_scores_all-.pkl")


    

In [10]:

    

%%timeit -r 10
Hyperparameters.start_training()


    

    




Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.696619 | Validation Accuracy: 0.621825
Accuracy on Test data: 0.6084102392196655, 0.39240506291389465
Step 2 | Training Loss: 0.630072 | Validation Accuracy: 0.742063
Accuracy on Test data: 0.68461674451828, 0.42683544754981995
Step 3 | Training Loss: 0.660342 | Validation Accuracy: 0.785714
Accuracy on Test data: 0.7082594037055969, 0.46000000834465027
Step 4 | Training Loss: 0.541829 | Validation Accuracy: 0.850000
Accuracy on Test data: 0.7194375395774841, 0.4780590832233429
Step 5 | Training Loss: 0.556526 | Validation Accuracy: 0.883333
Accuracy on Test data: 0.737358033657074, 0.5112236142158508
Step 6 | Training Loss: 0.485439 | Validation Accuracy: 0.897222
Accuracy on Test data: 0.7456085681915283, 0.5263291001319885
Step 7 | Training Loss: 0.474231 | Validation Accuracy: 0.915079
Accuracy on Test data: 0.7519074082374573, 0.5383122563362122
Step 8 | Training Loss: 0.492558 | Validation Accuracy: 0.932936
Accuracy on Test data: 0.7621539831161499, 0.5562869310379028
Step 9 | Training Loss: 0.448800 | Validation Accuracy: 0.932936
Accuracy on Test data: 0.7729329466819763, 0.5764557123184204
Step 10 | Training Loss: 0.475091 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.7781671285629272, 0.5857384204864502
Step 1 | Training Loss: 0.440640 | Validation Accuracy: 0.946032
Accuracy on Test data: 0.7784332633018494, 0.5859915614128113
Step 2 | Training Loss: 0.418244 | Validation Accuracy: 0.942064
Accuracy on Test data: 0.7790542840957642, 0.5870042443275452
Step 3 | Training Loss: 0.485042 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.7799414396286011, 0.5883544087409973
Step 4 | Training Loss: 0.410913 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.7806068062782288, 0.5892826914787292
Step 5 | Training Loss: 0.442045 | Validation Accuracy: 0.942857
Accuracy on Test data: 0.7809616923332214, 0.5897046327590942
Step 6 | Training Loss: 0.439277 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.7818044424057007, 0.5911392569541931
Step 7 | Training Loss: 0.458564 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.782514214515686, 0.5919831395149231
Step 8 | Training Loss: 0.442809 | Validation Accuracy: 0.944048
Accuracy on Test data: 0.7835787534713745, 0.5934177041053772
Step 9 | Training Loss: 0.441603 | Validation Accuracy: 0.948016
Accuracy on Test data: 0.7843772172927856, 0.5948523283004761
Step 10 | Training Loss: 0.407254 | Validation Accuracy: 0.942460
Accuracy on Test data: 0.7854418158531189, 0.5967932343482971
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.676125 | Validation Accuracy: 0.682936
Accuracy on Test data: 0.7106103897094727, 0.6418565511703491
Step 2 | Training Loss: 0.623865 | Validation Accuracy: 0.829762
Accuracy on Test data: 0.8160929679870605, 0.6786497831344604
Step 3 | Training Loss: 0.598203 | Validation Accuracy: 0.848810
Accuracy on Test data: 0.8289123773574829, 0.6926582455635071
Step 4 | Training Loss: 0.557506 | Validation Accuracy: 0.859921
Accuracy on Test data: 0.8297995328903198, 0.6933333277702332
Step 5 | Training Loss: 0.540771 | Validation Accuracy: 0.875397
Accuracy on Test data: 0.8296664357185364, 0.6922363042831421
Step 6 | Training Loss: 0.503479 | Validation Accuracy: 0.892857
Accuracy on Test data: 0.8282470107078552, 0.6882700324058533
Step 7 | Training Loss: 0.502244 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.8237224817276001, 0.6794936656951904
Step 8 | Training Loss: 0.482900 | Validation Accuracy: 0.901190
Accuracy on Test data: 0.8249645233154297, 0.6810970306396484
Step 9 | Training Loss: 0.464183 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.8252306580543518, 0.6805063486099243
Step 10 | Training Loss: 0.428869 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8239886164665222, 0.6772995591163635
Step 1 | Training Loss: 0.460218 | Validation Accuracy: 0.916667
Accuracy on Test data: 0.8240330219268799, 0.6772152185440063
Step 2 | Training Loss: 0.470758 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8241660594940186, 0.6773839592933655
Step 3 | Training Loss: 0.478213 | Validation Accuracy: 0.918651
Accuracy on Test data: 0.8243435025215149, 0.6774683594703674
Step 4 | Training Loss: 0.414661 | Validation Accuracy: 0.909524
Accuracy on Test data: 0.8229240775108337, 0.6746835708618164
Step 5 | Training Loss: 0.428124 | Validation Accuracy: 0.915079
Accuracy on Test data: 0.8205287456512451, 0.6701265573501587
Step 6 | Training Loss: 0.445458 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.8193311095237732, 0.6677637100219727
Step 7 | Training Loss: 0.454886 | Validation Accuracy: 0.924206
Accuracy on Test data: 0.818222165107727, 0.6654008626937866
Step 8 | Training Loss: 0.439139 | Validation Accuracy: 0.920238
Accuracy on Test data: 0.8166696429252625, 0.6624472737312317
Step 9 | Training Loss: 0.415393 | Validation Accuracy: 0.914683
Accuracy on Test data: 0.8117902874946594, 0.6530801653862
Step 10 | Training Loss: 0.468507 | Validation Accuracy: 0.917460
Accuracy on Test data: 0.8106813430786133, 0.650970458984375
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.666625 | Validation Accuracy: 0.750000
Accuracy on Test data: 0.7734208703041077, 0.6368776559829712
Step 2 | Training Loss: 0.627066 | Validation Accuracy: 0.850397
Accuracy on Test data: 0.8238555788993835, 0.6929113864898682
Step 3 | Training Loss: 0.575635 | Validation Accuracy: 0.864286
Accuracy on Test data: 0.8196415901184082, 0.6821097135543823
Step 4 | Training Loss: 0.523073 | Validation Accuracy: 0.881746
Accuracy on Test data: 0.8329489231109619, 0.6978902816772461
Step 5 | Training Loss: 0.526373 | Validation Accuracy: 0.895238
Accuracy on Test data: 0.8386266827583313, 0.7066666483879089
Step 6 | Training Loss: 0.458571 | Validation Accuracy: 0.909524
Accuracy on Test data: 0.8447480201721191, 0.7174683809280396
Step 7 | Training Loss: 0.487480 | Validation Accuracy: 0.909921
Accuracy on Test data: 0.8484297394752502, 0.7242193818092346
Step 8 | Training Loss: 0.471518 | Validation Accuracy: 0.923413
Accuracy on Test data: 0.8315737843513489, 0.6917299628257751
Step 9 | Training Loss: 0.460414 | Validation Accuracy: 0.926984
Accuracy on Test data: 0.8122338652610779, 0.652658224105835
Step 10 | Training Loss: 0.435614 | Validation Accuracy: 0.942857
Accuracy on Test data: 0.8156493902206421, 0.6575527191162109
Step 1 | Training Loss: 0.466321 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8156050443649292, 0.6572151780128479
Step 2 | Training Loss: 0.417137 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.8157824873924255, 0.6573839783668518
Step 3 | Training Loss: 0.440400 | Validation Accuracy: 0.942857
Accuracy on Test data: 0.8158711791038513, 0.6574683785438538
Step 4 | Training Loss: 0.443070 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.8158711791038513, 0.6574683785438538
Step 5 | Training Loss: 0.415735 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.8159155249595642, 0.6575527191162109
Step 6 | Training Loss: 0.433120 | Validation Accuracy: 0.939683
Accuracy on Test data: 0.8158711791038513, 0.6574683785438538
Step 7 | Training Loss: 0.461276 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.8156493902206421, 0.6569620370864868
Step 8 | Training Loss: 0.423820 | Validation Accuracy: 0.953175
Accuracy on Test data: 0.8156050443649292, 0.6568776369094849
Step 9 | Training Loss: 0.446898 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.8151614665985107, 0.6559493541717529
Step 10 | Training Loss: 0.444677 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.8152501583099365, 0.6560337543487549
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.650872 | Validation Accuracy: 0.708730
Accuracy on Test data: 0.7995918989181519, 0.751645565032959
Step 2 | Training Loss: 0.600901 | Validation Accuracy: 0.745635
Accuracy on Test data: 0.8135645985603333, 0.7403375506401062
Step 3 | Training Loss: 0.616212 | Validation Accuracy: 0.819444
Accuracy on Test data: 0.853397786617279, 0.7603375315666199
Step 4 | Training Loss: 0.493843 | Validation Accuracy: 0.878571
Accuracy on Test data: 0.8600514531135559, 0.7566244602203369
Step 5 | Training Loss: 0.476521 | Validation Accuracy: 0.902778
Accuracy on Test data: 0.8636444211006165, 0.7553586363792419
Step 6 | Training Loss: 0.471299 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8704311847686768, 0.7649788856506348
Step 7 | Training Loss: 0.471719 | Validation Accuracy: 0.915079
Accuracy on Test data: 0.8685237765312195, 0.7594936490058899
Step 8 | Training Loss: 0.449003 | Validation Accuracy: 0.919841
Accuracy on Test data: 0.8554826378822327, 0.7325738668441772
Step 9 | Training Loss: 0.426383 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.8494055867195129, 0.7194092869758606
Step 10 | Training Loss: 0.425396 | Validation Accuracy: 0.932936
Accuracy on Test data: 0.8455021381378174, 0.7108016610145569
Step 1 | Training Loss: 0.454522 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.845014214515686, 0.7098734378814697
Step 2 | Training Loss: 0.429308 | Validation Accuracy: 0.938095
Accuracy on Test data: 0.8447036743164062, 0.7092826962471008
Step 3 | Training Loss: 0.424828 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.8443931937217712, 0.7086076140403748
Step 4 | Training Loss: 0.440937 | Validation Accuracy: 0.940476
Accuracy on Test data: 0.844171404838562, 0.7081012725830078
Step 5 | Training Loss: 0.425006 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8439496159553528, 0.7072573900222778
Step 6 | Training Loss: 0.414437 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.8429293632507324, 0.7052320837974548
Step 7 | Training Loss: 0.428736 | Validation Accuracy: 0.936508
Accuracy on Test data: 0.8427519798278809, 0.7046413421630859
Step 8 | Training Loss: 0.424546 | Validation Accuracy: 0.940873
Accuracy on Test data: 0.8428850173950195, 0.7046413421630859
Step 9 | Training Loss: 0.430987 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8428406715393066, 0.7044726014137268
Step 10 | Training Loss: 0.408853 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.8428406715393066, 0.7043882012367249
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.800004 | Validation Accuracy: 0.544444
Accuracy on Test data: 0.47804293036460876, 0.27569618821144104
Step 2 | Training Loss: 0.708409 | Validation Accuracy: 0.556349
Accuracy on Test data: 0.4778655171394348, 0.2675105631351471
Step 3 | Training Loss: 0.690698 | Validation Accuracy: 0.596032
Accuracy on Test data: 0.4943222105503082, 0.2929113805294037
Step 4 | Training Loss: 0.613808 | Validation Accuracy: 0.734127
Accuracy on Test data: 0.5590844750404358, 0.33864977955818176
Step 5 | Training Loss: 0.571005 | Validation Accuracy: 0.766667
Accuracy on Test data: 0.661018431186676, 0.4011814296245575
Step 6 | Training Loss: 0.557245 | Validation Accuracy: 0.806746
Accuracy on Test data: 0.694419801235199, 0.4317299723625183
Step 7 | Training Loss: 0.528039 | Validation Accuracy: 0.859127
Accuracy on Test data: 0.7198367714881897, 0.47594937682151794
Step 8 | Training Loss: 0.509090 | Validation Accuracy: 0.895238
Accuracy on Test data: 0.7413058876991272, 0.5157805681228638
Step 9 | Training Loss: 0.530673 | Validation Accuracy: 0.909921
Accuracy on Test data: 0.7594925761222839, 0.5484388470649719
Step 10 | Training Loss: 0.471612 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.7665454149246216, 0.5610970258712769
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Accuracy on Test data: 0.7667672038078308, 0.5615189671516418
Step 2 | Training Loss: 0.508951 | Validation Accuracy: 0.929365
Accuracy on Test data: 0.7672107815742493, 0.5623628497123718
Step 3 | Training Loss: 0.469541 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.7677430510520935, 0.5633755326271057
Step 4 | Training Loss: 0.462666 | Validation Accuracy: 0.924206
Accuracy on Test data: 0.7683640718460083, 0.5645569562911987
Step 5 | Training Loss: 0.445665 | Validation Accuracy: 0.923810
Accuracy on Test data: 0.7702271342277527, 0.5677636861801147
Step 6 | Training Loss: 0.429909 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.7709811925888062, 0.5692827105522156
Step 7 | Training Loss: 0.480571 | Validation Accuracy: 0.930556
Accuracy on Test data: 0.7715578675270081, 0.5703797340393066
Step 8 | Training Loss: 0.472183 | Validation Accuracy: 0.927381
Accuracy on Test data: 0.7722232341766357, 0.5715611577033997
Step 9 | Training Loss: 0.458403 | Validation Accuracy: 0.932540
Accuracy on Test data: 0.77275550365448, 0.5725738406181335
Step 10 | Training Loss: 0.476464 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.7734208703041077, 0.5738396644592285
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.698713 | Validation Accuracy: 0.519048
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.716827 | Validation Accuracy: 0.525000
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.706949 | Validation Accuracy: 0.540873
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.703631 | Validation Accuracy: 0.564683
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.683113 | Validation Accuracy: 0.533333
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.678657 | Validation Accuracy: 0.532143
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.682055 | Validation Accuracy: 0.542063
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.665721 | Validation Accuracy: 0.521032
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.668206 | Validation Accuracy: 0.536905
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.685350 | Validation Accuracy: 0.534127
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 1 | Training Loss: 0.643748 | Validation Accuracy: 0.535714
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.657927 | Validation Accuracy: 0.532540
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.655756 | Validation Accuracy: 0.521032
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.669921 | Validation Accuracy: 0.536508
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.656489 | Validation Accuracy: 0.540079
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.678307 | Validation Accuracy: 0.518651
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.666066 | Validation Accuracy: 0.521825
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.657714 | Validation Accuracy: 0.534127
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.665817 | Validation Accuracy: 0.549603
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.648753 | Validation Accuracy: 0.515873
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.698084 | Validation Accuracy: 0.636111
Accuracy on Test data: 0.4571061134338379, 0.163459911942482
Step 2 | Training Loss: 0.675415 | Validation Accuracy: 0.645238
Accuracy on Test data: 0.4626508057117462, 0.1692827045917511
Step 3 | Training Loss: 0.725736 | Validation Accuracy: 0.689683
Accuracy on Test data: 0.4676632285118103, 0.17729957401752472
Step 4 | Training Loss: 0.682474 | Validation Accuracy: 0.712302
Accuracy on Test data: 0.4754258394241333, 0.1908016949892044
Step 5 | Training Loss: 0.682762 | Validation Accuracy: 0.712302
Accuracy on Test data: 0.48398688435554504, 0.20514768362045288
Step 6 | Training Loss: 0.703629 | Validation Accuracy: 0.742063
Accuracy on Test data: 0.4913058876991272, 0.21763713657855988
Step 7 | Training Loss: 0.661561 | Validation Accuracy: 0.760714
Accuracy on Test data: 0.4975603222846985, 0.2282700389623642
Step 8 | Training Loss: 0.661222 | Validation Accuracy: 0.776190
Accuracy on Test data: 0.5193843245506287, 0.26455697417259216
Step 9 | Training Loss: 0.654404 | Validation Accuracy: 0.790873
Accuracy on Test data: 0.5501685738563538, 0.3206751048564911
Step 10 | Training Loss: 0.614166 | Validation Accuracy: 0.814286
Accuracy on Test data: 0.5615241527557373, 0.33890295028686523
Step 1 | Training Loss: 0.682278 | Validation Accuracy: 0.807540
Accuracy on Test data: 0.5623225569725037, 0.34008437395095825
Step 2 | Training Loss: 0.638704 | Validation Accuracy: 0.809921
Accuracy on Test data: 0.5632984638214111, 0.3416033685207367
Step 3 | Training Loss: 0.682334 | Validation Accuracy: 0.826984
Accuracy on Test data: 0.5640968680381775, 0.34286919236183167
Step 4 | Training Loss: 0.627990 | Validation Accuracy: 0.819048
Accuracy on Test data: 0.5651171207427979, 0.3446413576602936
Step 5 | Training Loss: 0.602297 | Validation Accuracy: 0.838889
Accuracy on Test data: 0.5661373138427734, 0.346160352230072
Step 6 | Training Loss: 0.663095 | Validation Accuracy: 0.815873
Accuracy on Test data: 0.5672019124031067, 0.3478480875492096
Step 7 | Training Loss: 0.654036 | Validation Accuracy: 0.842063
Accuracy on Test data: 0.568222165107727, 0.34953585267066956
Step 8 | Training Loss: 0.616350 | Validation Accuracy: 0.833333
Accuracy on Test data: 0.5691980123519897, 0.351054847240448
Step 9 | Training Loss: 0.636103 | Validation Accuracy: 0.832143
Accuracy on Test data: 0.5703956484794617, 0.35316455364227295
Step 10 | Training Loss: 0.633458 | Validation Accuracy: 0.834921
Accuracy on Test data: 0.5716820359230042, 0.3551054894924164
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
Step 1 | Training Loss: 0.733933 | Validation Accuracy: 0.470238
Accuracy on Test data: 0.5637863874435425, 0.8085231781005859
Step 2 | Training Loss: 0.677271 | Validation Accuracy: 0.471825
Accuracy on Test data: 0.5630766749382019, 0.8059915900230408
Step 3 | Training Loss: 0.683476 | Validation Accuracy: 0.568254
Accuracy on Test data: 0.6612846255302429, 0.7949367165565491
Step 4 | Training Loss: 0.666758 | Validation Accuracy: 0.738095
Accuracy on Test data: 0.8442600965499878, 0.803966224193573
Step 5 | Training Loss: 0.642595 | Validation Accuracy: 0.777778
Accuracy on Test data: 0.8485628366470337, 0.7865822911262512
Step 6 | Training Loss: 0.667581 | Validation Accuracy: 0.773810
Accuracy on Test data: 0.8537526726722717, 0.7885231971740723
Step 7 | Training Loss: 0.671569 | Validation Accuracy: 0.784524
Accuracy on Test data: 0.854284942150116, 0.7882700562477112
Step 8 | Training Loss: 0.634152 | Validation Accuracy: 0.780159
Accuracy on Test data: 0.8581884503364563, 0.7875105738639832
Step 9 | Training Loss: 0.625654 | Validation Accuracy: 0.776190
Accuracy on Test data: 0.8580553531646729, 0.7859915494918823
Step 10 | Training Loss: 0.642924 | Validation Accuracy: 0.794048
Accuracy on Test data: 0.8595191836357117, 0.7804219126701355
Step 1 | Training Loss: 0.647104 | Validation Accuracy: 0.784524
Accuracy on Test data: 0.8599627614021301, 0.7794092893600464
Step 2 | Training Loss: 0.619690 | Validation Accuracy: 0.796825
Accuracy on Test data: 0.8607168197631836, 0.7789873480796814
Step 3 | Training Loss: 0.620933 | Validation Accuracy: 0.801190
Accuracy on Test data: 0.8609386086463928, 0.7779746651649475
Step 4 | Training Loss: 0.598655 | Validation Accuracy: 0.798810
Accuracy on Test data: 0.8616483211517334, 0.7774683833122253
Step 5 | Training Loss: 0.636483 | Validation Accuracy: 0.800794
Accuracy on Test data: 0.8613821864128113, 0.7753586769104004
Step 6 | Training Loss: 0.632391 | Validation Accuracy: 0.782143
Accuracy on Test data: 0.8527324199676514, 0.7578902840614319
Step 7 | Training Loss: 0.636696 | Validation Accuracy: 0.798810
Accuracy on Test data: 0.8496717810630798, 0.7514767646789551
Step 8 | Training Loss: 0.629840 | Validation Accuracy: 0.801587
Accuracy on Test data: 0.8498048186302185, 0.7513924241065979
Step 9 | Training Loss: 0.624921 | Validation Accuracy: 0.813095
Accuracy on Test data: 0.849937915802002, 0.7510548233985901
Step 10 | Training Loss: 0.639450 | Validation Accuracy: 0.803175
Accuracy on Test data: 0.8501153588294983, 0.750801682472229
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.716404 | Validation Accuracy: 0.585317
Accuracy on Test data: 0.5695084929466248, 0.5223628878593445
Step 2 | Training Loss: 0.704238 | Validation Accuracy: 0.685317
Accuracy on Test data: 0.6870564222335815, 0.5399156212806702
Step 3 | Training Loss: 0.682472 | Validation Accuracy: 0.824603
Accuracy on Test data: 0.7586497664451599, 0.5691139101982117
Step 4 | Training Loss: 0.697217 | Validation Accuracy: 0.885714
Accuracy on Test data: 0.7928051948547363, 0.6210970282554626
Step 5 | Training Loss: 0.641662 | Validation Accuracy: 0.902778
Accuracy on Test data: 0.7986160516738892, 0.6294514536857605
Step 6 | Training Loss: 0.606705 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.8034066557884216, 0.6374683380126953
Step 7 | Training Loss: 0.563823 | Validation Accuracy: 0.909921
Accuracy on Test data: 0.8046930432319641, 0.6394936442375183
Step 8 | Training Loss: 0.616304 | Validation Accuracy: 0.917857
Accuracy on Test data: 0.8054027557373047, 0.6396624445915222
Step 9 | Training Loss: 0.570046 | Validation Accuracy: 0.923016
Accuracy on Test data: 0.8076649904251099, 0.6432911157608032
Step 10 | Training Loss: 0.535518 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.8116128444671631, 0.65054851770401
Step 1 | Training Loss: 0.561643 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.8118346333503723, 0.650970458984375
Step 2 | Training Loss: 0.576047 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.8120564222335815, 0.65139240026474
Step 3 | Training Loss: 0.571387 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8122338652610779, 0.651729941368103
Step 4 | Training Loss: 0.524196 | Validation Accuracy: 0.936111
Accuracy on Test data: 0.8123669028282166, 0.6519831418991089
Step 5 | Training Loss: 0.524919 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8124113082885742, 0.6520674824714661
Step 6 | Training Loss: 0.518458 | Validation Accuracy: 0.926984
Accuracy on Test data: 0.8123225569725037, 0.6518987417221069
Step 7 | Training Loss: 0.611675 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.8124113082885742, 0.6520674824714661
Step 8 | Training Loss: 0.543882 | Validation Accuracy: 0.928968
Accuracy on Test data: 0.8125443458557129, 0.65223628282547
Step 9 | Training Loss: 0.589435 | Validation Accuracy: 0.926190
Accuracy on Test data: 0.8127217888832092, 0.6524050831794739
Step 10 | Training Loss: 0.538671 | Validation Accuracy: 0.932540
Accuracy on Test data: 0.8125443458557129, 0.6519831418991089
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.671870 | Validation Accuracy: 0.764683
Accuracy on Test data: 0.6343151330947876, 0.5134177207946777
Step 2 | Training Loss: 0.681299 | Validation Accuracy: 0.898016
Accuracy on Test data: 0.7436568737030029, 0.6232911348342896
Step 3 | Training Loss: 0.657457 | Validation Accuracy: 0.916270
Accuracy on Test data: 0.8093949556350708, 0.647679328918457
Step 4 | Training Loss: 0.621810 | Validation Accuracy: 0.926190
Accuracy on Test data: 0.8328601717948914, 0.6902953386306763
Step 5 | Training Loss: 0.585013 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8262952566146851, 0.6765400767326355
Step 6 | Training Loss: 0.565141 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.8289123773574829, 0.6807594895362854
Step 7 | Training Loss: 0.526524 | Validation Accuracy: 0.942460
Accuracy on Test data: 0.8190205693244934, 0.6609282493591309
Step 8 | Training Loss: 0.545763 | Validation Accuracy: 0.953571
Accuracy on Test data: 0.8147622346878052, 0.6520674824714661
Step 9 | Training Loss: 0.503629 | Validation Accuracy: 0.951190
Accuracy on Test data: 0.8148065805435181, 0.65139240026474
Step 10 | Training Loss: 0.512662 | Validation Accuracy: 0.948413
Accuracy on Test data: 0.8140968680381775, 0.6498734354972839
Step 1 | Training Loss: 0.469955 | Validation Accuracy: 0.946032
Accuracy on Test data: 0.8139638304710388, 0.6496202349662781
Step 2 | Training Loss: 0.475418 | Validation Accuracy: 0.955159
Accuracy on Test data: 0.8139638304710388, 0.6496202349662781
Step 3 | Training Loss: 0.475644 | Validation Accuracy: 0.952778
Accuracy on Test data: 0.8140525221824646, 0.64970463514328
Step 4 | Training Loss: 0.483259 | Validation Accuracy: 0.953968
Accuracy on Test data: 0.8140525221824646, 0.6495358943939209
Step 5 | Training Loss: 0.450222 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.8140968680381775, 0.6496202349662781
Step 6 | Training Loss: 0.518096 | Validation Accuracy: 0.952778
Accuracy on Test data: 0.8141412138938904, 0.64970463514328
Step 7 | Training Loss: 0.478529 | Validation Accuracy: 0.955159
Accuracy on Test data: 0.8140968680381775, 0.6496202349662781
Step 8 | Training Loss: 0.453239 | Validation Accuracy: 0.954762
Accuracy on Test data: 0.8139194250106812, 0.649282693862915
Step 9 | Training Loss: 0.499037 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.8139194250106812, 0.6491982936859131
Step 10 | Training Loss: 0.451632 | Validation Accuracy: 0.950794
Accuracy on Test data: 0.8139638304710388, 0.649282693862915
Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.673826 | Validation Accuracy: 0.762698
Accuracy on Test data: 0.6945972442626953, 0.4383966326713562
Step 2 | Training Loss: 0.606951 | Validation Accuracy: 0.810317
Accuracy on Test data: 0.7118523716926575, 0.4674261510372162
Step 3 | Training Loss: 0.572831 | Validation Accuracy: 0.842460
Accuracy on Test data: 0.7298616170883179, 0.49966245889663696
Step 4 | Training Loss: 0.566432 | Validation Accuracy: 0.861905
Accuracy on Test data: 0.75, 0.5341772437095642
Step 5 | Training Loss: 0.494209 | Validation Accuracy: 0.875397
Accuracy on Test data: 0.7689407467842102, 0.5679324865341187
Step 6 | Training Loss: 0.504036 | Validation Accuracy: 0.896825
Accuracy on Test data: 0.7766146063804626, 0.5808438658714294
Step 7 | Training Loss: 0.444554 | Validation Accuracy: 0.911508
Accuracy on Test data: 0.7779896855354309, 0.5815190076828003
Step 8 | Training Loss: 0.480121 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.7821149826049805, 0.5886920094490051
Step 9 | Training Loss: 0.439711 | Validation Accuracy: 0.943651
Accuracy on Test data: 0.7765259146690369, 0.5770463943481445
Step 10 | Training Loss: 0.424194 | Validation Accuracy: 0.950000
Accuracy on Test data: 0.7757274508476257, 0.5752742886543274
Step 1 | Training Loss: 0.440410 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.7754169702529907, 0.5746835470199585
Step 2 | Training Loss: 0.436354 | Validation Accuracy: 0.957937
Accuracy on Test data: 0.7744854688644409, 0.5729113817214966
Step 3 | Training Loss: 0.441327 | Validation Accuracy: 0.960317
Accuracy on Test data: 0.7742193341255188, 0.5724050402641296
Step 4 | Training Loss: 0.455289 | Validation Accuracy: 0.957937
Accuracy on Test data: 0.7739975452423096, 0.5719830989837646
Step 5 | Training Loss: 0.445293 | Validation Accuracy: 0.955556
Accuracy on Test data: 0.7739531397819519, 0.5718987584114075
Step 6 | Training Loss: 0.445345 | Validation Accuracy: 0.954762
Accuracy on Test data: 0.7735095620155334, 0.5709704756736755
Step 7 | Training Loss: 0.431692 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.7735095620155334, 0.5709704756736755
Step 8 | Training Loss: 0.444863 | Validation Accuracy: 0.952778
Accuracy on Test data: 0.7733321785926819, 0.5706329345703125
Step 9 | Training Loss: 0.426695 | Validation Accuracy: 0.959921
Accuracy on Test data: 0.7731547355651855, 0.5702953338623047
Step 10 | Training Loss: 0.421607 | Validation Accuracy: 0.964683
Accuracy on Test data: 0.7730216383934021, 0.5700421929359436
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.582474 | Validation Accuracy: 0.788889
Accuracy on Test data: 0.8517122268676758, 0.7603375315666199
Step 2 | Training Loss: 0.550560 | Validation Accuracy: 0.861508
Accuracy on Test data: 0.8772178888320923, 0.7900422215461731
Step 3 | Training Loss: 0.518329 | Validation Accuracy: 0.869841
Accuracy on Test data: 0.8737136125564575, 0.7822784781455994
Step 4 | Training Loss: 0.488385 | Validation Accuracy: 0.893254
Accuracy on Test data: 0.8743789792060852, 0.7800843715667725
Step 5 | Training Loss: 0.433795 | Validation Accuracy: 0.893651
Accuracy on Test data: 0.8732256889343262, 0.7743459939956665
Step 6 | Training Loss: 0.444807 | Validation Accuracy: 0.903571
Accuracy on Test data: 0.8727377653121948, 0.7706329226493835
Step 7 | Training Loss: 0.440816 | Validation Accuracy: 0.896429
Accuracy on Test data: 0.8742902874946594, 0.7714768052101135
Step 8 | Training Loss: 0.452431 | Validation Accuracy: 0.905952
Accuracy on Test data: 0.8629790544509888, 0.748860776424408
Step 9 | Training Loss: 0.446355 | Validation Accuracy: 0.909921
Accuracy on Test data: 0.8596522212028503, 0.7421941161155701
Step 10 | Training Loss: 0.437144 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8586763739585876, 0.7397468090057373
Step 1 | Training Loss: 0.433527 | Validation Accuracy: 0.929365
Accuracy on Test data: 0.8586763739585876, 0.7396624684333801
Step 2 | Training Loss: 0.391359 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.8585432767868042, 0.7393248677253723
Step 3 | Training Loss: 0.412083 | Validation Accuracy: 0.944048
Accuracy on Test data: 0.8582771420478821, 0.7387341856956482
Step 4 | Training Loss: 0.431073 | Validation Accuracy: 0.938095
Accuracy on Test data: 0.8582327961921692, 0.7385653853416443
Step 5 | Training Loss: 0.415573 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.8580996990203857, 0.7383122444152832
Step 6 | Training Loss: 0.411868 | Validation Accuracy: 0.941667
Accuracy on Test data: 0.8580553531646729, 0.7382278442382812
Step 7 | Training Loss: 0.411536 | Validation Accuracy: 0.943651
Accuracy on Test data: 0.8577448725700378, 0.7374683618545532
Step 8 | Training Loss: 0.403431 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.8574787378311157, 0.7369620203971863
Step 9 | Training Loss: 0.410918 | Validation Accuracy: 0.946032
Accuracy on Test data: 0.8573456406593323, 0.7367088794708252
Step 10 | Training Loss: 0.423158 | Validation Accuracy: 0.945238
Accuracy on Test data: 0.8568577170372009, 0.7357805967330933
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.682041 | Validation Accuracy: 0.555159
Accuracy on Test data: 0.6694020628929138, 0.7772151827812195
Step 2 | Training Loss: 0.656250 | Validation Accuracy: 0.706349
Accuracy on Test data: 0.7875266075134277, 0.7659915685653687
Step 3 | Training Loss: 0.557503 | Validation Accuracy: 0.815873
Accuracy on Test data: 0.8626242280006409, 0.7927426099777222
Step 4 | Training Loss: 0.519679 | Validation Accuracy: 0.857143
Accuracy on Test data: 0.879036545753479, 0.8021097183227539
Step 5 | Training Loss: 0.505367 | Validation Accuracy: 0.885714
Accuracy on Test data: 0.8824520707130432, 0.8014345765113831
Step 6 | Training Loss: 0.515720 | Validation Accuracy: 0.884524
Accuracy on Test data: 0.8743346333503723, 0.7775527238845825
Step 7 | Training Loss: 0.532101 | Validation Accuracy: 0.907143
Accuracy on Test data: 0.8703424334526062, 0.7651476860046387
Step 8 | Training Loss: 0.478462 | Validation Accuracy: 0.911111
Accuracy on Test data: 0.8605393767356873, 0.7445569634437561
Step 9 | Training Loss: 0.464418 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.8510468602180481, 0.7254008650779724
Step 10 | Training Loss: 0.482828 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.8459900617599487, 0.7153586745262146
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Accuracy on Test data: 0.8458126187324524, 0.7149367332458496
Step 2 | Training Loss: 0.416988 | Validation Accuracy: 0.930556
Accuracy on Test data: 0.8455908298492432, 0.7144303917884827
Step 3 | Training Loss: 0.440137 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8452360033988953, 0.7135021090507507
Step 4 | Training Loss: 0.420628 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8447924256324768, 0.7125738263130188
Step 5 | Training Loss: 0.433634 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.844481885433197, 0.7118143439292908
Step 6 | Training Loss: 0.388081 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8442157506942749, 0.7113080024719238
Step 7 | Training Loss: 0.419587 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.8439939618110657, 0.7108860611915588
Step 8 | Training Loss: 0.436847 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.8438165187835693, 0.7104641199111938
Step 9 | Training Loss: 0.415148 | Validation Accuracy: 0.932143
Accuracy on Test data: 0.8438608646392822, 0.7105485200881958
Step 10 | Training Loss: 0.437735 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.8434616923332214, 0.7097046375274658
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.705090 | Validation Accuracy: 0.416270
Accuracy on Test data: 0.41022002696990967, 0.6125738620758057
Step 2 | Training Loss: 0.658635 | Validation Accuracy: 0.730952
Accuracy on Test data: 0.7484918236732483, 0.6111392378807068
Step 3 | Training Loss: 0.592087 | Validation Accuracy: 0.862698
Accuracy on Test data: 0.8206618428230286, 0.6880168914794922
Step 4 | Training Loss: 0.576446 | Validation Accuracy: 0.861905
Accuracy on Test data: 0.8245209455490112, 0.6913080215454102
Step 5 | Training Loss: 0.543725 | Validation Accuracy: 0.879365
Accuracy on Test data: 0.8317068815231323, 0.701603353023529
Step 6 | Training Loss: 0.518714 | Validation Accuracy: 0.884524
Accuracy on Test data: 0.8276259899139404, 0.6913080215454102
Step 7 | Training Loss: 0.495479 | Validation Accuracy: 0.897222
Accuracy on Test data: 0.8243878483772278, 0.6814345717430115
Step 8 | Training Loss: 0.492144 | Validation Accuracy: 0.892063
Accuracy on Test data: 0.8037171959877014, 0.6409282684326172
Step 9 | Training Loss: 0.523258 | Validation Accuracy: 0.901190
Accuracy on Test data: 0.8065560460090637, 0.6458227634429932
Step 10 | Training Loss: 0.449513 | Validation Accuracy: 0.916270
Accuracy on Test data: 0.816226065158844, 0.6622784733772278
Step 1 | Training Loss: 0.456334 | Validation Accuracy: 0.919841
Accuracy on Test data: 0.8178672790527344, 0.6650632619857788
Step 2 | Training Loss: 0.455884 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.8196415901184082, 0.6681856513023376
Step 3 | Training Loss: 0.482686 | Validation Accuracy: 0.911905
Accuracy on Test data: 0.8209723234176636, 0.6706328988075256
Step 4 | Training Loss: 0.451554 | Validation Accuracy: 0.908730
Accuracy on Test data: 0.8216376900672913, 0.6718143224716187
Step 5 | Training Loss: 0.469324 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8224361538887024, 0.6731645464897156
Step 6 | Training Loss: 0.431252 | Validation Accuracy: 0.923413
Accuracy on Test data: 0.823456346988678, 0.6750211119651794
Step 7 | Training Loss: 0.459589 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.8238555788993835, 0.6757805943489075
Step 8 | Training Loss: 0.431281 | Validation Accuracy: 0.927381
Accuracy on Test data: 0.8242548108100891, 0.6765400767326355
Step 9 | Training Loss: 0.430161 | Validation Accuracy: 0.923810
Accuracy on Test data: 0.8246983885765076, 0.6773839592933655
Step 10 | Training Loss: 0.440858 | Validation Accuracy: 0.920238
Accuracy on Test data: 0.8251863121986389, 0.6783122420310974
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.656293 | Validation Accuracy: 0.726190
Accuracy on Test data: 0.5212916731834412, 0.27789029479026794
Step 2 | Training Loss: 0.655933 | Validation Accuracy: 0.760714
Accuracy on Test data: 0.5469304323196411, 0.322447270154953
Step 3 | Training Loss: 0.588864 | Validation Accuracy: 0.786508
Accuracy on Test data: 0.561657190322876, 0.3471730053424835
Step 4 | Training Loss: 0.535257 | Validation Accuracy: 0.850397
Accuracy on Test data: 0.659022331237793, 0.3719831109046936
Step 5 | Training Loss: 0.532160 | Validation Accuracy: 0.896429
Accuracy on Test data: 0.6782292127609253, 0.40168777108192444
Step 6 | Training Loss: 0.521929 | Validation Accuracy: 0.917857
Accuracy on Test data: 0.6933108568191528, 0.4285232126712799
Step 7 | Training Loss: 0.485261 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.7044003009796143, 0.4460759460926056
Step 8 | Training Loss: 0.455235 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.7103441953659058, 0.45586496591567993
Step 9 | Training Loss: 0.472032 | Validation Accuracy: 0.943651
Accuracy on Test data: 0.7152235507965088, 0.4631223678588867
Step 10 | Training Loss: 0.442101 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.7219215631484985, 0.474683552980423
Step 1 | Training Loss: 0.442184 | Validation Accuracy: 0.951190
Accuracy on Test data: 0.7227643728256226, 0.47620251774787903
Step 2 | Training Loss: 0.430020 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.7237402200698853, 0.4780590832233429
Step 3 | Training Loss: 0.426315 | Validation Accuracy: 0.957540
Accuracy on Test data: 0.7240064144134521, 0.4784810245037079
Step 4 | Training Loss: 0.442783 | Validation Accuracy: 0.952381
Accuracy on Test data: 0.7247604727745056, 0.4799156188964844
Step 5 | Training Loss: 0.423257 | Validation Accuracy: 0.950000
Accuracy on Test data: 0.7251153588294983, 0.48059073090553284
Step 6 | Training Loss: 0.447688 | Validation Accuracy: 0.948413
Accuracy on Test data: 0.7256476283073425, 0.48160338401794434
Step 7 | Training Loss: 0.421495 | Validation Accuracy: 0.944048
Accuracy on Test data: 0.7260468602180481, 0.48236286640167236
Step 8 | Training Loss: 0.430782 | Validation Accuracy: 0.956349
Accuracy on Test data: 0.7263129949569702, 0.4828692078590393
Step 9 | Training Loss: 0.435432 | Validation Accuracy: 0.955159
Accuracy on Test data: 0.7265791296958923, 0.48337551951408386
Step 10 | Training Loss: 0.446765 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.7268896102905273, 0.48396623134613037
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.693100 | Validation Accuracy: 0.530159
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.693095 | Validation Accuracy: 0.525794
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.693102 | Validation Accuracy: 0.523810
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.693256 | Validation Accuracy: 0.510317
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.692654 | Validation Accuracy: 0.535714
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692748 | Validation Accuracy: 0.528968
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692829 | Validation Accuracy: 0.534127
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.693034 | Validation Accuracy: 0.522619
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.693115 | Validation Accuracy: 0.513492
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.692598 | Validation Accuracy: 0.533730
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 1 | Training Loss: 0.692489 | Validation Accuracy: 0.536905
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.692903 | Validation Accuracy: 0.551587
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692055 | Validation Accuracy: 0.543254
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.692899 | Validation Accuracy: 0.532143
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.692358 | Validation Accuracy: 0.528175
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692460 | Validation Accuracy: 0.536508
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692892 | Validation Accuracy: 0.535317
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.692780 | Validation Accuracy: 0.534127
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.692554 | Validation Accuracy: 0.540476
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.692773 | Validation Accuracy: 0.519048
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.692682 | Validation Accuracy: 0.722619
Accuracy on Test data: 0.5186746120452881, 0.27468353509902954
Step 2 | Training Loss: 0.719414 | Validation Accuracy: 0.743254
Accuracy on Test data: 0.5526525974273682, 0.33544304966926575
Step 3 | Training Loss: 0.667304 | Validation Accuracy: 0.794048
Accuracy on Test data: 0.5964779853820801, 0.3584810197353363
Step 4 | Training Loss: 0.632227 | Validation Accuracy: 0.813492
Accuracy on Test data: 0.6771202683448792, 0.40691983699798584
Step 5 | Training Loss: 0.650929 | Validation Accuracy: 0.833333
Accuracy on Test data: 0.6903389096260071, 0.43088608980178833
Step 6 | Training Loss: 0.685725 | Validation Accuracy: 0.860317
Accuracy on Test data: 0.7136266827583313, 0.47333332896232605
Step 7 | Training Loss: 0.646188 | Validation Accuracy: 0.853968
Accuracy on Test data: 0.72724449634552, 0.4982278347015381
Step 8 | Training Loss: 0.619929 | Validation Accuracy: 0.861508
Accuracy on Test data: 0.7379347085952759, 0.5170463919639587
Step 9 | Training Loss: 0.639527 | Validation Accuracy: 0.870238
Accuracy on Test data: 0.7445883750915527, 0.5286920070648193
Step 10 | Training Loss: 0.645159 | Validation Accuracy: 0.886905
Accuracy on Test data: 0.7533268332481384, 0.544641375541687
Step 1 | Training Loss: 0.638498 | Validation Accuracy: 0.880952
Accuracy on Test data: 0.7541252374649048, 0.5459915399551392
Step 2 | Training Loss: 0.580023 | Validation Accuracy: 0.881746
Accuracy on Test data: 0.7550567984580994, 0.54751056432724
Step 3 | Training Loss: 0.604954 | Validation Accuracy: 0.903175
Accuracy on Test data: 0.7564762234687805, 0.5496202707290649
Step 4 | Training Loss: 0.582423 | Validation Accuracy: 0.903968
Accuracy on Test data: 0.7575851678848267, 0.5513923764228821
Step 5 | Training Loss: 0.612737 | Validation Accuracy: 0.896429
Accuracy on Test data: 0.7583392262458801, 0.5525738596916199
Step 6 | Training Loss: 0.595497 | Validation Accuracy: 0.895238
Accuracy on Test data: 0.758915901184082, 0.5536708831787109
Step 7 | Training Loss: 0.611740 | Validation Accuracy: 0.900000
Accuracy on Test data: 0.7600248456001282, 0.5557805895805359
Step 8 | Training Loss: 0.595593 | Validation Accuracy: 0.893651
Accuracy on Test data: 0.7606902122497559, 0.5570464134216309
Step 9 | Training Loss: 0.590177 | Validation Accuracy: 0.899206
Accuracy on Test data: 0.7616660594940186, 0.5589029788970947
Step 10 | Training Loss: 0.591144 | Validation Accuracy: 0.889683
Accuracy on Test data: 0.7624201774597168, 0.5601688027381897
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
Step 1 | Training Loss: 0.668258 | Validation Accuracy: 0.534524
Accuracy on Test data: 0.6314318776130676, 0.7915611863136292
Step 2 | Training Loss: 0.721940 | Validation Accuracy: 0.734127
Accuracy on Test data: 0.8381831049919128, 0.8340928554534912
Step 3 | Training Loss: 0.649041 | Validation Accuracy: 0.773016
Accuracy on Test data: 0.8446149826049805, 0.8150210976600647
Step 4 | Training Loss: 0.653050 | Validation Accuracy: 0.799206
Accuracy on Test data: 0.8553495407104492, 0.8211814165115356
Step 5 | Training Loss: 0.677737 | Validation Accuracy: 0.804365
Accuracy on Test data: 0.8654187321662903, 0.8267510533332825
Step 6 | Training Loss: 0.650170 | Validation Accuracy: 0.805159
Accuracy on Test data: 0.8742902874946594, 0.8289451599121094
Step 7 | Training Loss: 0.657501 | Validation Accuracy: 0.828968
Accuracy on Test data: 0.878726065158844, 0.8298734426498413
Step 8 | Training Loss: 0.587645 | Validation Accuracy: 0.827381
Accuracy on Test data: 0.8765081763267517, 0.8163713216781616
Step 9 | Training Loss: 0.610045 | Validation Accuracy: 0.840079
Accuracy on Test data: 0.8757097125053406, 0.8108860850334167
Step 10 | Training Loss: 0.635093 | Validation Accuracy: 0.877778
Accuracy on Test data: 0.8796575665473938, 0.8075105547904968
Step 1 | Training Loss: 0.608923 | Validation Accuracy: 0.869841
Accuracy on Test data: 0.8801454901695251, 0.8068354725837708
Step 2 | Training Loss: 0.633844 | Validation Accuracy: 0.867857
Accuracy on Test data: 0.8802341818809509, 0.8054008483886719
Step 3 | Training Loss: 0.595726 | Validation Accuracy: 0.865476
Accuracy on Test data: 0.8807665109634399, 0.8050633072853088
Step 4 | Training Loss: 0.617605 | Validation Accuracy: 0.868254
Accuracy on Test data: 0.8808995485305786, 0.8043038249015808
Step 5 | Training Loss: 0.606337 | Validation Accuracy: 0.871429
Accuracy on Test data: 0.8808108568191528, 0.80362868309021
Step 6 | Training Loss: 0.623009 | Validation Accuracy: 0.878175
Accuracy on Test data: 0.8808552026748657, 0.8032911419868469
Step 7 | Training Loss: 0.602514 | Validation Accuracy: 0.875000
Accuracy on Test data: 0.8808108568191528, 0.80278480052948
Step 8 | Training Loss: 0.595059 | Validation Accuracy: 0.884127
Accuracy on Test data: 0.8804559707641602, 0.801856517791748
Step 9 | Training Loss: 0.577496 | Validation Accuracy: 0.868254
Accuracy on Test data: 0.8801454901695251, 0.8010126352310181
Step 10 | Training Loss: 0.584548 | Validation Accuracy: 0.880556
Accuracy on Test data: 0.879036545753479, 0.7989029288291931
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.662488 | Validation Accuracy: 0.754762
Accuracy on Test data: 0.7023154497146606, 0.4706329107284546
Step 2 | Training Loss: 0.656126 | Validation Accuracy: 0.803175
Accuracy on Test data: 0.7465400695800781, 0.5348523259162903
Step 3 | Training Loss: 0.619524 | Validation Accuracy: 0.886508
Accuracy on Test data: 0.7813165187835693, 0.598227858543396
Step 4 | Training Loss: 0.622733 | Validation Accuracy: 0.886111
Accuracy on Test data: 0.8132540583610535, 0.6584810018539429
Step 5 | Training Loss: 0.637013 | Validation Accuracy: 0.881349
Accuracy on Test data: 0.8260291218757629, 0.6816877722740173
Step 6 | Training Loss: 0.638238 | Validation Accuracy: 0.892063
Accuracy on Test data: 0.8329489231109619, 0.6935864686965942
Step 7 | Training Loss: 0.596811 | Validation Accuracy: 0.903175
Accuracy on Test data: 0.8377395272254944, 0.702447235584259
Step 8 | Training Loss: 0.559466 | Validation Accuracy: 0.901984
Accuracy on Test data: 0.8386266827583313, 0.7034599184989929
Step 9 | Training Loss: 0.561425 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.8386266827583313, 0.7032067775726318
Step 10 | Training Loss: 0.543846 | Validation Accuracy: 0.923810
Accuracy on Test data: 0.8393363952636719, 0.7038818597793579
Step 1 | Training Loss: 0.534783 | Validation Accuracy: 0.911905
Accuracy on Test data: 0.8395138382911682, 0.704135000705719
Step 2 | Training Loss: 0.545325 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.839602530002594, 0.704219400882721
Step 3 | Training Loss: 0.510395 | Validation Accuracy: 0.920238
Accuracy on Test data: 0.8395581841468811, 0.704135000705719
Step 4 | Training Loss: 0.524454 | Validation Accuracy: 0.918254
Accuracy on Test data: 0.8394251465797424, 0.7038818597793579
Step 5 | Training Loss: 0.501285 | Validation Accuracy: 0.917460
Accuracy on Test data: 0.8394694924354553, 0.7039662599563599
Step 6 | Training Loss: 0.572812 | Validation Accuracy: 0.924206
Accuracy on Test data: 0.8395581841468811, 0.704135000705719
Step 7 | Training Loss: 0.515774 | Validation Accuracy: 0.921032
Accuracy on Test data: 0.8399130702018738, 0.7047257423400879
Step 8 | Training Loss: 0.543856 | Validation Accuracy: 0.921032
Accuracy on Test data: 0.8397356271743774, 0.7043038010597229
Step 9 | Training Loss: 0.515720 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8398687243461609, 0.7044726014137268
Step 10 | Training Loss: 0.535957 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.8398243188858032, 0.7043038010597229
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.695120 | Validation Accuracy: 0.610317
Accuracy on Test data: 0.5602821111679077, 0.375189870595932
Step 2 | Training Loss: 0.660552 | Validation Accuracy: 0.815873
Accuracy on Test data: 0.7616660594940186, 0.5670042037963867
Step 3 | Training Loss: 0.623373 | Validation Accuracy: 0.882540
Accuracy on Test data: 0.8219038248062134, 0.6778903007507324
Step 4 | Training Loss: 0.629889 | Validation Accuracy: 0.897619
Accuracy on Test data: 0.8461675047874451, 0.7217721343040466
Step 5 | Training Loss: 0.626747 | Validation Accuracy: 0.902381
Accuracy on Test data: 0.8419091701507568, 0.7113924026489258
Step 6 | Training Loss: 0.573192 | Validation Accuracy: 0.907540
Accuracy on Test data: 0.8411107063293457, 0.7059071660041809
Step 7 | Training Loss: 0.547752 | Validation Accuracy: 0.914683
Accuracy on Test data: 0.8390259146690369, 0.69974684715271
Step 8 | Training Loss: 0.523875 | Validation Accuracy: 0.914286
Accuracy on Test data: 0.8366305828094482, 0.695189893245697
Step 9 | Training Loss: 0.486426 | Validation Accuracy: 0.915079
Accuracy on Test data: 0.8345457911491394, 0.6909704804420471
Step 10 | Training Loss: 0.462855 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8324609398841858, 0.6869198083877563
Step 1 | Training Loss: 0.508775 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8322391510009766, 0.6864135265350342
Step 2 | Training Loss: 0.483329 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.8318843245506287, 0.6857383847236633
Step 3 | Training Loss: 0.460773 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.8317955732345581, 0.6855696439743042
Step 4 | Training Loss: 0.472317 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.8316181898117065, 0.6852320432662964
Step 5 | Training Loss: 0.493245 | Validation Accuracy: 0.923016
Accuracy on Test data: 0.8314850926399231, 0.6848945021629333
Step 6 | Training Loss: 0.458536 | Validation Accuracy: 0.920635
Accuracy on Test data: 0.8313076496124268, 0.6845569610595703
Step 7 | Training Loss: 0.443293 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.8310858607292175, 0.6841350197792053
Step 8 | Training Loss: 0.464267 | Validation Accuracy: 0.932540
Accuracy on Test data: 0.8308197259902954, 0.6836286783218384
Step 9 | Training Loss: 0.469244 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.830686628818512, 0.6833755373954773
Step 10 | Training Loss: 0.464370 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8305979371070862, 0.6832067370414734
Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.683240 | Validation Accuracy: 0.483730
Accuracy on Test data: 0.5551809668540955, 0.7886075973510742
Step 2 | Training Loss: 0.628144 | Validation Accuracy: 0.606746
Accuracy on Test data: 0.6861249208450317, 0.7836287021636963
Step 3 | Training Loss: 0.619903 | Validation Accuracy: 0.778571
Accuracy on Test data: 0.8605837225914001, 0.8537552952766418
Step 4 | Training Loss: 0.596097 | Validation Accuracy: 0.840873
Accuracy on Test data: 0.8915454149246216, 0.8456540107727051
Step 5 | Training Loss: 0.545713 | Validation Accuracy: 0.869841
Accuracy on Test data: 0.901481568813324, 0.8410970568656921
Step 6 | Training Loss: 0.480834 | Validation Accuracy: 0.882937
Accuracy on Test data: 0.9074698090553284, 0.8424472808837891
Step 7 | Training Loss: 0.514278 | Validation Accuracy: 0.908333
Accuracy on Test data: 0.8821415901184082, 0.7877637147903442
Step 8 | Training Loss: 0.465134 | Validation Accuracy: 0.911111
Accuracy on Test data: 0.8681688904762268, 0.7591561079025269
Step 9 | Training Loss: 0.454755 | Validation Accuracy: 0.908333
Accuracy on Test data: 0.85512775182724, 0.7339240312576294
Step 10 | Training Loss: 0.435497 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.8470990061759949, 0.7175527215003967
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Accuracy on Test data: 0.8467441201210022, 0.7167932391166687
Step 2 | Training Loss: 0.455051 | Validation Accuracy: 0.921032
Accuracy on Test data: 0.8459900617599487, 0.7151054739952087
Step 3 | Training Loss: 0.441595 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.8443931937217712, 0.7120674848556519
Step 4 | Training Loss: 0.407686 | Validation Accuracy: 0.907937
Accuracy on Test data: 0.8436834812164307, 0.7107173204421997
Step 5 | Training Loss: 0.411223 | Validation Accuracy: 0.909127
Accuracy on Test data: 0.8431511521339417, 0.7096202373504639
Step 6 | Training Loss: 0.451034 | Validation Accuracy: 0.911111
Accuracy on Test data: 0.8419535160064697, 0.7072573900222778
Step 7 | Training Loss: 0.429666 | Validation Accuracy: 0.917857
Accuracy on Test data: 0.8410220146179199, 0.7054852247238159
Step 8 | Training Loss: 0.419797 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.8408889174461365, 0.704978883266449
Step 9 | Training Loss: 0.426789 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.8401792049407959, 0.7036287188529968
Step 10 | Training Loss: 0.425938 | Validation Accuracy: 0.918254
Accuracy on Test data: 0.8394694924354553, 0.702109694480896
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.705905 | Validation Accuracy: 0.650794
Accuracy on Test data: 0.474228173494339, 0.19763712584972382
Step 2 | Training Loss: 0.653529 | Validation Accuracy: 0.696825
Accuracy on Test data: 0.4853619635105133, 0.2111392468214035
Step 3 | Training Loss: 0.663189 | Validation Accuracy: 0.692857
Accuracy on Test data: 0.4980482757091522, 0.23282700777053833
Step 4 | Training Loss: 0.648770 | Validation Accuracy: 0.735714
Accuracy on Test data: 0.514150083065033, 0.25814345479011536
Step 5 | Training Loss: 0.546386 | Validation Accuracy: 0.785317
Accuracy on Test data: 0.5499467849731445, 0.3212658166885376
Step 6 | Training Loss: 0.556205 | Validation Accuracy: 0.817460
Accuracy on Test data: 0.6643896102905273, 0.3868354558944702
Step 7 | Training Loss: 0.535881 | Validation Accuracy: 0.838095
Accuracy on Test data: 0.683773934841156, 0.41392403841018677
Step 8 | Training Loss: 0.583606 | Validation Accuracy: 0.872619
Accuracy on Test data: 0.6973474025726318, 0.4362025260925293
Step 9 | Training Loss: 0.496912 | Validation Accuracy: 0.903571
Accuracy on Test data: 0.7149130702018738, 0.4658227860927582
Step 10 | Training Loss: 0.477875 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.725248396396637, 0.4832911491394043
Step 1 | Training Loss: 0.428195 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.726401686668396, 0.4854852259159088
Step 2 | Training Loss: 0.424124 | Validation Accuracy: 0.920635
Accuracy on Test data: 0.7277324199676514, 0.4879325032234192
Step 3 | Training Loss: 0.457274 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.7288857102394104, 0.49004217982292175
Step 4 | Training Loss: 0.479830 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.7306600213050842, 0.4934177100658417
Step 5 | Training Loss: 0.438482 | Validation Accuracy: 0.932936
Accuracy on Test data: 0.7324787378311157, 0.49687764048576355
Step 6 | Training Loss: 0.445216 | Validation Accuracy: 0.932540
Accuracy on Test data: 0.7335432767868042, 0.49890294671058655
Step 7 | Training Loss: 0.440132 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.7347853183746338, 0.501265823841095
Step 8 | Training Loss: 0.434766 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.735317587852478, 0.5022785067558289
Step 9 | Training Loss: 0.477610 | Validation Accuracy: 0.932936
Accuracy on Test data: 0.7362047433853149, 0.5039662718772888
Step 10 | Training Loss: 0.422839 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.7371806502342224, 0.5056540369987488
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.650577 | Validation Accuracy: 0.719444
Accuracy on Test data: 0.4916163980960846, 0.2133333384990692
Step 2 | Training Loss: 0.648512 | Validation Accuracy: 0.778968
Accuracy on Test data: 0.5994055867195129, 0.2605063319206238
Step 3 | Training Loss: 0.591696 | Validation Accuracy: 0.848016
Accuracy on Test data: 0.6419003009796143, 0.33763712644577026
Step 4 | Training Loss: 0.553540 | Validation Accuracy: 0.860714
Accuracy on Test data: 0.6633694171905518, 0.37586498260498047
Step 5 | Training Loss: 0.539500 | Validation Accuracy: 0.888889
Accuracy on Test data: 0.6876330971717834, 0.4174683690071106
Step 6 | Training Loss: 0.489102 | Validation Accuracy: 0.900000
Accuracy on Test data: 0.7014282941818237, 0.4421941041946411
Step 7 | Training Loss: 0.502714 | Validation Accuracy: 0.913492
Accuracy on Test data: 0.713981568813324, 0.46447256207466125
Step 8 | Training Loss: 0.455328 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.7282203435897827, 0.4911392331123352
Step 9 | Training Loss: 0.461497 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.7443665862083435, 0.5204219222068787
Step 10 | Training Loss: 0.436993 | Validation Accuracy: 0.941667
Accuracy on Test data: 0.7578069567680359, 0.5445569753646851
Step 1 | Training Loss: 0.411039 | Validation Accuracy: 0.952381
Accuracy on Test data: 0.7596256136894226, 0.5477637052536011
Step 2 | Training Loss: 0.464011 | Validation Accuracy: 0.942460
Accuracy on Test data: 0.7603353261947632, 0.5489451289176941
Step 3 | Training Loss: 0.444773 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.7610450387001038, 0.5501265525817871
Step 4 | Training Loss: 0.424294 | Validation Accuracy: 0.950794
Accuracy on Test data: 0.7621983885765076, 0.552320659160614
Step 5 | Training Loss: 0.411484 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.7639282941818237, 0.5554430484771729
Step 6 | Training Loss: 0.409193 | Validation Accuracy: 0.953571
Accuracy on Test data: 0.7655695676803589, 0.5584810376167297
Step 7 | Training Loss: 0.452699 | Validation Accuracy: 0.945238
Accuracy on Test data: 0.7665897607803345, 0.5603375434875488
Step 8 | Training Loss: 0.433482 | Validation Accuracy: 0.953968
Accuracy on Test data: 0.76698899269104, 0.5608438849449158
Step 9 | Training Loss: 0.406326 | Validation Accuracy: 0.947222
Accuracy on Test data: 0.7675212621688843, 0.5616033673286438
Step 10 | Training Loss: 0.422596 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.7679204940795898, 0.5623628497123718
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.651358 | Validation Accuracy: 0.588095
Accuracy on Test data: 0.7310149073600769, 0.749620258808136
Step 2 | Training Loss: 0.607094 | Validation Accuracy: 0.735714
Accuracy on Test data: 0.8121007680892944, 0.7389873266220093
Step 3 | Training Loss: 0.600913 | Validation Accuracy: 0.793254
Accuracy on Test data: 0.8378726243972778, 0.746329128742218
Step 4 | Training Loss: 0.542735 | Validation Accuracy: 0.824603
Accuracy on Test data: 0.8594304323196411, 0.7711392641067505
Step 5 | Training Loss: 0.543790 | Validation Accuracy: 0.850397
Accuracy on Test data: 0.8567246198654175, 0.7509704828262329
Step 6 | Training Loss: 0.507520 | Validation Accuracy: 0.888492
Accuracy on Test data: 0.8523775935173035, 0.7348523139953613
Step 7 | Training Loss: 0.492590 | Validation Accuracy: 0.898016
Accuracy on Test data: 0.8505145311355591, 0.7289451360702515
Step 8 | Training Loss: 0.487839 | Validation Accuracy: 0.903571
Accuracy on Test data: 0.8511798977851868, 0.7269198298454285
Step 9 | Training Loss: 0.474790 | Validation Accuracy: 0.914286
Accuracy on Test data: 0.8506919741630554, 0.7243037819862366
Step 10 | Training Loss: 0.417204 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8464336395263672, 0.7151054739952087
Step 1 | Training Loss: 0.435691 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8459457159042358, 0.7140084505081177
Step 2 | Training Loss: 0.431399 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.8455021381378174, 0.7130801677703857
Step 3 | Training Loss: 0.479658 | Validation Accuracy: 0.926984
Accuracy on Test data: 0.845014214515686, 0.7121518850326538
Step 4 | Training Loss: 0.457613 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8441270589828491, 0.7102953791618347
Step 5 | Training Loss: 0.412875 | Validation Accuracy: 0.926587
Accuracy on Test data: 0.8427519798278809, 0.7075949311256409
Step 6 | Training Loss: 0.429037 | Validation Accuracy: 0.929365
Accuracy on Test data: 0.8412438035011292, 0.7046413421630859
Step 7 | Training Loss: 0.439051 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8393363952636719, 0.7010126709938049
Step 8 | Training Loss: 0.422567 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8386266827583313, 0.699662446975708
Step 9 | Training Loss: 0.446597 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8377838730812073, 0.6978902816772461
Step 10 | Training Loss: 0.422712 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8374290466308594, 0.6970463991165161
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.672192 | Validation Accuracy: 0.601587
Accuracy on Test data: 0.6231369972229004, 0.5653164386749268
Step 2 | Training Loss: 0.609515 | Validation Accuracy: 0.754762
Accuracy on Test data: 0.6798261404037476, 0.5778902769088745
Step 3 | Training Loss: 0.604544 | Validation Accuracy: 0.819444
Accuracy on Test data: 0.7626863121986389, 0.5991561412811279
Step 4 | Training Loss: 0.571957 | Validation Accuracy: 0.836508
Accuracy on Test data: 0.790897786617279, 0.6202531456947327
Step 5 | Training Loss: 0.516549 | Validation Accuracy: 0.853571
Accuracy on Test data: 0.7973740100860596, 0.6304641366004944
Step 6 | Training Loss: 0.466741 | Validation Accuracy: 0.849603
Accuracy on Test data: 0.8026525974273682, 0.6394936442375183
Step 7 | Training Loss: 0.543326 | Validation Accuracy: 0.867857
Accuracy on Test data: 0.8159599304199219, 0.6637130975723267
Step 8 | Training Loss: 0.478861 | Validation Accuracy: 0.908730
Accuracy on Test data: 0.8324609398841858, 0.6915611624717712
Step 9 | Training Loss: 0.524538 | Validation Accuracy: 0.906746
Accuracy on Test data: 0.8412438035011292, 0.7076793313026428
Step 10 | Training Loss: 0.446406 | Validation Accuracy: 0.905159
Accuracy on Test data: 0.844171404838562, 0.7136709094047546
Step 1 | Training Loss: 0.453631 | Validation Accuracy: 0.914286
Accuracy on Test data: 0.8445262312889099, 0.7142615914344788
Step 2 | Training Loss: 0.435481 | Validation Accuracy: 0.920635
Accuracy on Test data: 0.8449254631996155, 0.7150210738182068
Step 3 | Training Loss: 0.433149 | Validation Accuracy: 0.917063
Accuracy on Test data: 0.8453690409660339, 0.7158649563789368
Step 4 | Training Loss: 0.451488 | Validation Accuracy: 0.920635
Accuracy on Test data: 0.8459457159042358, 0.7167932391166687
Step 5 | Training Loss: 0.445983 | Validation Accuracy: 0.921825
Accuracy on Test data: 0.8464779853820801, 0.7179746627807617
Step 6 | Training Loss: 0.447492 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.8469659090042114, 0.7189873456954956
Step 7 | Training Loss: 0.439902 | Validation Accuracy: 0.915476
Accuracy on Test data: 0.8470990061759949, 0.7192404866218567
Step 8 | Training Loss: 0.444052 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8472764492034912, 0.7194936871528625
Step 9 | Training Loss: 0.410377 | Validation Accuracy: 0.918651
Accuracy on Test data: 0.8474094867706299, 0.7196624279022217
Step 10 | Training Loss: 0.462310 | Validation Accuracy: 0.909127
Accuracy on Test data: 0.8474094867706299, 0.7194936871528625
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.693173 | Validation Accuracy: 0.540873
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.693039 | Validation Accuracy: 0.547619
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692953 | Validation Accuracy: 0.523810
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.692685 | Validation Accuracy: 0.532937
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.693126 | Validation Accuracy: 0.527381
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692760 | Validation Accuracy: 0.527381
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692908 | Validation Accuracy: 0.539286
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.693278 | Validation Accuracy: 0.537302
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.693475 | Validation Accuracy: 0.526984
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.691717 | Validation Accuracy: 0.525397
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 1 | Training Loss: 0.692407 | Validation Accuracy: 0.543254
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.693520 | Validation Accuracy: 0.534127
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692599 | Validation Accuracy: 0.519444
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.693113 | Validation Accuracy: 0.541270
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.693008 | Validation Accuracy: 0.538095
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692901 | Validation Accuracy: 0.523016
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.693219 | Validation Accuracy: 0.532540
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.693650 | Validation Accuracy: 0.549206
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.694524 | Validation Accuracy: 0.526190
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.693002 | Validation Accuracy: 0.530159
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.720491 | Validation Accuracy: 0.633333
Accuracy on Test data: 0.6304116249084473, 0.36118143796920776
Step 2 | Training Loss: 0.699399 | Validation Accuracy: 0.670635
Accuracy on Test data: 0.6430535912513733, 0.37713080644607544
Step 3 | Training Loss: 0.710373 | Validation Accuracy: 0.697619
Accuracy on Test data: 0.6423438787460327, 0.35940927267074585
Step 4 | Training Loss: 0.652065 | Validation Accuracy: 0.768651
Accuracy on Test data: 0.6583126187324524, 0.38075950741767883
Step 5 | Training Loss: 0.669078 | Validation Accuracy: 0.817857
Accuracy on Test data: 0.6812455654144287, 0.41898733377456665
Step 6 | Training Loss: 0.637139 | Validation Accuracy: 0.838492
Accuracy on Test data: 0.7141589522361755, 0.47594937682151794
Step 7 | Training Loss: 0.622535 | Validation Accuracy: 0.855556
Accuracy on Test data: 0.7232522964477539, 0.4891139268875122
Step 8 | Training Loss: 0.637866 | Validation Accuracy: 0.865079
Accuracy on Test data: 0.7310592532157898, 0.502362847328186
Step 9 | Training Loss: 0.615460 | Validation Accuracy: 0.886111
Accuracy on Test data: 0.7392654418945312, 0.5158649682998657
Step 10 | Training Loss: 0.663402 | Validation Accuracy: 0.884127
Accuracy on Test data: 0.7493346333503723, 0.5335865020751953
Step 1 | Training Loss: 0.595137 | Validation Accuracy: 0.878571
Accuracy on Test data: 0.7503992319107056, 0.5352742671966553
Step 2 | Training Loss: 0.634373 | Validation Accuracy: 0.875000
Accuracy on Test data: 0.7504435777664185, 0.5352742671966553
Step 3 | Training Loss: 0.600545 | Validation Accuracy: 0.871032
Accuracy on Test data: 0.7508871555328369, 0.5357806086540222
Step 4 | Training Loss: 0.637083 | Validation Accuracy: 0.882937
Accuracy on Test data: 0.7510645985603333, 0.5360337495803833
Step 5 | Training Loss: 0.591993 | Validation Accuracy: 0.865873
Accuracy on Test data: 0.7508871555328369, 0.5356962084770203
Step 6 | Training Loss: 0.640063 | Validation Accuracy: 0.874603
Accuracy on Test data: 0.7505766749382019, 0.5350211262702942
Step 7 | Training Loss: 0.567454 | Validation Accuracy: 0.883730
Accuracy on Test data: 0.7502661347389221, 0.5341772437095642
Step 8 | Training Loss: 0.612293 | Validation Accuracy: 0.875397
Accuracy on Test data: 0.7498669028282166, 0.5332489609718323
Step 9 | Training Loss: 0.609455 | Validation Accuracy: 0.888889
Accuracy on Test data: 0.7491128444671631, 0.5317299365997314
Step 10 | Training Loss: 0.630708 | Validation Accuracy: 0.891270
Accuracy on Test data: 0.7484031319618225, 0.5302953720092773
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
Step 1 | Training Loss: 0.694996 | Validation Accuracy: 0.633333
Accuracy on Test data: 0.7238289713859558, 0.797468364238739
Step 2 | Training Loss: 0.685773 | Validation Accuracy: 0.750397
Accuracy on Test data: 0.8178672790527344, 0.7685232162475586
Step 3 | Training Loss: 0.692638 | Validation Accuracy: 0.782143
Accuracy on Test data: 0.8352998495101929, 0.7637974619865417
Step 4 | Training Loss: 0.661395 | Validation Accuracy: 0.807936
Accuracy on Test data: 0.8437278270721436, 0.7614346146583557
Step 5 | Training Loss: 0.641245 | Validation Accuracy: 0.828175
Accuracy on Test data: 0.8449254631996155, 0.7578058838844299
Step 6 | Training Loss: 0.706467 | Validation Accuracy: 0.828571
Accuracy on Test data: 0.8436834812164307, 0.748016893863678
Step 7 | Training Loss: 0.639771 | Validation Accuracy: 0.837302
Accuracy on Test data: 0.8292228579521179, 0.7178903222084045
Step 8 | Training Loss: 0.656786 | Validation Accuracy: 0.909524
Accuracy on Test data: 0.8513129949569702, 0.7452320456504822
Step 9 | Training Loss: 0.574072 | Validation Accuracy: 0.890873
Accuracy on Test data: 0.8554826378822327, 0.7443881630897522
Step 10 | Training Loss: 0.584728 | Validation Accuracy: 0.900794
Accuracy on Test data: 0.8451915979385376, 0.7190717458724976
Step 1 | Training Loss: 0.603377 | Validation Accuracy: 0.893254
Accuracy on Test data: 0.8452360033988953, 0.7190717458724976
Step 2 | Training Loss: 0.597298 | Validation Accuracy: 0.913492
Accuracy on Test data: 0.8453690409660339, 0.7191561460494995
Step 3 | Training Loss: 0.552120 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.845324695110321, 0.7190717458724976
Step 4 | Training Loss: 0.594733 | Validation Accuracy: 0.909127
Accuracy on Test data: 0.8455908298492432, 0.7192404866218567
Step 5 | Training Loss: 0.623434 | Validation Accuracy: 0.909524
Accuracy on Test data: 0.8454577922821045, 0.7189873456954956
Step 6 | Training Loss: 0.595293 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.8454133868217468, 0.7189029455184937
Step 7 | Training Loss: 0.553951 | Validation Accuracy: 0.903968
Accuracy on Test data: 0.8454577922821045, 0.7189029455184937
Step 8 | Training Loss: 0.601343 | Validation Accuracy: 0.917063
Accuracy on Test data: 0.8455021381378174, 0.7189029455184937
Step 9 | Training Loss: 0.587721 | Validation Accuracy: 0.909524
Accuracy on Test data: 0.8455021381378174, 0.7189029455184937
Step 10 | Training Loss: 0.596083 | Validation Accuracy: 0.910317
Accuracy on Test data: 0.8455464839935303, 0.7189873456954956
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.674197 | Validation Accuracy: 0.716667
Accuracy on Test data: 0.8100159764289856, 0.8524894714355469
Step 2 | Training Loss: 0.661934 | Validation Accuracy: 0.785317
Accuracy on Test data: 0.862358033657074, 0.8448101282119751
Step 3 | Training Loss: 0.632108 | Validation Accuracy: 0.814683
Accuracy on Test data: 0.8843151330947876, 0.8426160216331482
Step 4 | Training Loss: 0.670609 | Validation Accuracy: 0.833333
Accuracy on Test data: 0.8809882998466492, 0.8152742385864258
Step 5 | Training Loss: 0.611444 | Validation Accuracy: 0.843254
Accuracy on Test data: 0.8857345581054688, 0.8173839449882507
Step 6 | Training Loss: 0.611900 | Validation Accuracy: 0.861111
Accuracy on Test data: 0.8892831802368164, 0.8174683451652527
Step 7 | Training Loss: 0.594286 | Validation Accuracy: 0.873810
Accuracy on Test data: 0.8896380662918091, 0.8158649802207947
Step 8 | Training Loss: 0.637401 | Validation Accuracy: 0.890476
Accuracy on Test data: 0.8824077248573303, 0.7992405295372009
Step 9 | Training Loss: 0.524148 | Validation Accuracy: 0.898413
Accuracy on Test data: 0.8739354014396667, 0.7776371240615845
Step 10 | Training Loss: 0.566216 | Validation Accuracy: 0.903571
Accuracy on Test data: 0.8694996237754822, 0.7644725441932678
Step 1 | Training Loss: 0.540101 | Validation Accuracy: 0.914286
Accuracy on Test data: 0.8700762987136841, 0.7651476860046387
Step 2 | Training Loss: 0.552633 | Validation Accuracy: 0.908333
Accuracy on Test data: 0.8702980875968933, 0.7652320861816406
Step 3 | Training Loss: 0.564915 | Validation Accuracy: 0.905952
Accuracy on Test data: 0.8700319528579712, 0.7646413445472717
Step 4 | Training Loss: 0.519248 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.8696770668029785, 0.7637974619865417
Step 5 | Training Loss: 0.550367 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.8695883750915527, 0.7632911205291748
Step 6 | Training Loss: 0.567420 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.8693222403526306, 0.7627004384994507
Step 7 | Training Loss: 0.504278 | Validation Accuracy: 0.918651
Accuracy on Test data: 0.8690560460090637, 0.7621096968650818
Step 8 | Training Loss: 0.522890 | Validation Accuracy: 0.917857
Accuracy on Test data: 0.8688342571258545, 0.7614346146583557
Step 9 | Training Loss: 0.542984 | Validation Accuracy: 0.919841
Accuracy on Test data: 0.8685681223869324, 0.7607594728469849
Step 10 | Training Loss: 0.500592 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.8682132959365845, 0.7600843906402588
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.654347 | Validation Accuracy: 0.742857
Accuracy on Test data: 0.8440826535224915, 0.794177234172821
Step 2 | Training Loss: 0.613005 | Validation Accuracy: 0.786111
Accuracy on Test data: 0.8592086434364319, 0.7869198322296143
Step 3 | Training Loss: 0.583966 | Validation Accuracy: 0.836111
Accuracy on Test data: 0.8601401448249817, 0.7705485224723816
Step 4 | Training Loss: 0.544836 | Validation Accuracy: 0.887302
Accuracy on Test data: 0.865196943283081, 0.7589029669761658
Step 5 | Training Loss: 0.537357 | Validation Accuracy: 0.906746
Accuracy on Test data: 0.8671930432319641, 0.7559493780136108
Step 6 | Training Loss: 0.568722 | Validation Accuracy: 0.921032
Accuracy on Test data: 0.8676809668540955, 0.7551898956298828
Step 7 | Training Loss: 0.531322 | Validation Accuracy: 0.917460
Accuracy on Test data: 0.8679915070533752, 0.754514753818512
Step 8 | Training Loss: 0.481520 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.8668825626373291, 0.7518143653869629
Step 9 | Training Loss: 0.454613 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.862890362739563, 0.74388188123703
Step 10 | Training Loss: 0.451661 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8347232341766357, 0.6900421977043152
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Accuracy on Test data: 0.8335698843002319, 0.6878480911254883
Step 2 | Training Loss: 0.430812 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.833215057849884, 0.6871730089187622
Step 3 | Training Loss: 0.463640 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.8328601717948914, 0.6864978671073914
Step 4 | Training Loss: 0.450704 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.8323279023170471, 0.6854852437973022
Step 5 | Training Loss: 0.465463 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.8316181898117065, 0.6841350197792053
Step 6 | Training Loss: 0.430366 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.8310858607292175, 0.6831223368644714
Step 7 | Training Loss: 0.452485 | Validation Accuracy: 0.932143
Accuracy on Test data: 0.8307310342788696, 0.6824472546577454
Step 8 | Training Loss: 0.423325 | Validation Accuracy: 0.920238
Accuracy on Test data: 0.8302430510520935, 0.6815189719200134
Step 9 | Training Loss: 0.440535 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.82948899269104, 0.6800844073295593
Step 10 | Training Loss: 0.436593 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.8290454149246216, 0.6791561245918274
Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.677952 | Validation Accuracy: 0.496825
Accuracy on Test data: 0.46469128131866455, 0.5757805705070496
Step 2 | Training Loss: 0.672981 | Validation Accuracy: 0.599603
Accuracy on Test data: 0.5747427344322205, 0.5865823030471802
Step 3 | Training Loss: 0.655341 | Validation Accuracy: 0.846429
Accuracy on Test data: 0.7873491644859314, 0.6145991683006287
Step 4 | Training Loss: 0.564717 | Validation Accuracy: 0.862302
Accuracy on Test data: 0.78974449634552, 0.6174683570861816
Step 5 | Training Loss: 0.611295 | Validation Accuracy: 0.876190
Accuracy on Test data: 0.7806511521339417, 0.598565399646759
Step 6 | Training Loss: 0.485849 | Validation Accuracy: 0.876587
Accuracy on Test data: 0.7829577922821045, 0.6020253300666809
Step 7 | Training Loss: 0.472327 | Validation Accuracy: 0.886508
Accuracy on Test data: 0.7849982380867004, 0.603459894657135
Step 8 | Training Loss: 0.496154 | Validation Accuracy: 0.892460
Accuracy on Test data: 0.7886355519294739, 0.6082700490951538
Step 9 | Training Loss: 0.433144 | Validation Accuracy: 0.899206
Accuracy on Test data: 0.7912970185279846, 0.6118143200874329
Step 10 | Training Loss: 0.454923 | Validation Accuracy: 0.900794
Accuracy on Test data: 0.7966199517250061, 0.6197468638420105
Step 1 | Training Loss: 0.461170 | Validation Accuracy: 0.903968
Accuracy on Test data: 0.7968417406082153, 0.6200000047683716
Step 2 | Training Loss: 0.430804 | Validation Accuracy: 0.922222
Accuracy on Test data: 0.7985273003578186, 0.6230379939079285
Step 3 | Training Loss: 0.489416 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.7999911308288574, 0.6258227825164795
Step 4 | Training Loss: 0.475861 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.8021202683448792, 0.6297046542167664
Step 5 | Training Loss: 0.445020 | Validation Accuracy: 0.926984
Accuracy on Test data: 0.8031405210494995, 0.6314768195152283
Step 6 | Training Loss: 0.455097 | Validation Accuracy: 0.928175
Accuracy on Test data: 0.8030074238777161, 0.6311392188072205
Step 7 | Training Loss: 0.453361 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8030961751937866, 0.6313080191612244
Step 8 | Training Loss: 0.450888 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.8032292127609253, 0.6313080191612244
Step 9 | Training Loss: 0.454033 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8033623099327087, 0.6314768195152283
Step 10 | Training Loss: 0.459188 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.8034510016441345, 0.6316455602645874
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.704588 | Validation Accuracy: 0.528175
Accuracy on Test data: 0.4981813430786133, 0.5344303846359253
Step 2 | Training Loss: 0.659759 | Validation Accuracy: 0.729365
Accuracy on Test data: 0.6438519954681396, 0.5297890305519104
Step 3 | Training Loss: 0.585712 | Validation Accuracy: 0.858333
Accuracy on Test data: 0.7441447973251343, 0.5342615842819214
Step 4 | Training Loss: 0.546930 | Validation Accuracy: 0.880952
Accuracy on Test data: 0.748314380645752, 0.5368776321411133
Step 5 | Training Loss: 0.530453 | Validation Accuracy: 0.885714
Accuracy on Test data: 0.7548350095748901, 0.5448101162910461
Step 6 | Training Loss: 0.506566 | Validation Accuracy: 0.915079
Accuracy on Test data: 0.7598917484283447, 0.551476776599884
Step 7 | Training Loss: 0.476792 | Validation Accuracy: 0.926190
Accuracy on Test data: 0.7618435025215149, 0.554345965385437
Step 8 | Training Loss: 0.500576 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.7659243941307068, 0.5612658262252808
Step 9 | Training Loss: 0.419683 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.7662792801856995, 0.5610126852989197
Step 10 | Training Loss: 0.446631 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.7633960247039795, 0.5551055073738098
Step 1 | Training Loss: 0.438551 | Validation Accuracy: 0.942064
Accuracy on Test data: 0.7633960247039795, 0.5551055073738098
Step 2 | Training Loss: 0.441539 | Validation Accuracy: 0.933730
Accuracy on Test data: 0.7633516788482666, 0.5551055073738098
Step 3 | Training Loss: 0.420653 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.763262927532196, 0.554852306842804
Step 4 | Training Loss: 0.466701 | Validation Accuracy: 0.945238
Accuracy on Test data: 0.7633073329925537, 0.5549367070198059
Step 5 | Training Loss: 0.443039 | Validation Accuracy: 0.956349
Accuracy on Test data: 0.7633960247039795, 0.5551055073738098
Step 6 | Training Loss: 0.424539 | Validation Accuracy: 0.949206
Accuracy on Test data: 0.7633073329925537, 0.5551055073738098
Step 7 | Training Loss: 0.437550 | Validation Accuracy: 0.942064
Accuracy on Test data: 0.7632185816764832, 0.554852306842804
Step 8 | Training Loss: 0.429481 | Validation Accuracy: 0.947222
Accuracy on Test data: 0.7632185816764832, 0.5546835660934448
Step 9 | Training Loss: 0.434610 | Validation Accuracy: 0.942064
Accuracy on Test data: 0.7630855441093445, 0.5545147657394409
Step 10 | Training Loss: 0.424302 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.7631298899650574, 0.554430365562439
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.661364 | Validation Accuracy: 0.730159
Accuracy on Test data: 0.5217796564102173, 0.27122363448143005
Step 2 | Training Loss: 0.635159 | Validation Accuracy: 0.755952
Accuracy on Test data: 0.5389460325241089, 0.2977215051651001
Step 3 | Training Loss: 0.617150 | Validation Accuracy: 0.816270
Accuracy on Test data: 0.5770493149757385, 0.36565402150154114
Step 4 | Training Loss: 0.556307 | Validation Accuracy: 0.850794
Accuracy on Test data: 0.6061480045318604, 0.41434597969055176
Step 5 | Training Loss: 0.535421 | Validation Accuracy: 0.879762
Accuracy on Test data: 0.7077271342277527, 0.45485231280326843
Step 6 | Training Loss: 0.487212 | Validation Accuracy: 0.899603
Accuracy on Test data: 0.7189939618110657, 0.47493672370910645
Step 7 | Training Loss: 0.500562 | Validation Accuracy: 0.915476
Accuracy on Test data: 0.728397786617279, 0.49223628640174866
Step 8 | Training Loss: 0.472547 | Validation Accuracy: 0.917063
Accuracy on Test data: 0.7405518293380737, 0.5146835446357727
Step 9 | Training Loss: 0.462272 | Validation Accuracy: 0.923016
Accuracy on Test data: 0.7482256889343262, 0.5288607478141785
Step 10 | Training Loss: 0.433209 | Validation Accuracy: 0.953571
Accuracy on Test data: 0.7603353261947632, 0.550295352935791
Step 1 | Training Loss: 0.426087 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.7610894441604614, 0.551476776599884
Step 2 | Training Loss: 0.433798 | Validation Accuracy: 0.960317
Accuracy on Test data: 0.7617104053497314, 0.552320659160614
Step 3 | Training Loss: 0.443154 | Validation Accuracy: 0.952381
Accuracy on Test data: 0.7629967927932739, 0.5541772246360779
Step 4 | Training Loss: 0.429782 | Validation Accuracy: 0.953175
Accuracy on Test data: 0.7643718719482422, 0.5562869310379028
Step 5 | Training Loss: 0.473760 | Validation Accuracy: 0.960317
Accuracy on Test data: 0.7656582593917847, 0.5586497783660889
Step 6 | Training Loss: 0.425294 | Validation Accuracy: 0.960714
Accuracy on Test data: 0.7661018371582031, 0.5592405200004578
Step 7 | Training Loss: 0.429852 | Validation Accuracy: 0.961111
Accuracy on Test data: 0.7667672038078308, 0.5600000023841858
Step 8 | Training Loss: 0.439671 | Validation Accuracy: 0.955159
Accuracy on Test data: 0.7672551274299622, 0.5606750845909119
Step 9 | Training Loss: 0.423632 | Validation Accuracy: 0.952381
Accuracy on Test data: 0.7676100134849548, 0.5612658262252808
Step 10 | Training Loss: 0.435612 | Validation Accuracy: 0.956349
Accuracy on Test data: 0.7679204940795898, 0.5618565678596497
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.636687 | Validation Accuracy: 0.724206
Accuracy on Test data: 0.7848207950592041, 0.7139240503311157
Step 2 | Training Loss: 0.603518 | Validation Accuracy: 0.782937
Accuracy on Test data: 0.8004790544509888, 0.6762025356292725
Step 3 | Training Loss: 0.558731 | Validation Accuracy: 0.821032
Accuracy on Test data: 0.8148065805435181, 0.6662447452545166
Step 4 | Training Loss: 0.516378 | Validation Accuracy: 0.873016
Accuracy on Test data: 0.8268718719482422, 0.6837974786758423
Step 5 | Training Loss: 0.508401 | Validation Accuracy: 0.894841
Accuracy on Test data: 0.822613537311554, 0.6737552881240845
Step 6 | Training Loss: 0.488547 | Validation Accuracy: 0.911508
Accuracy on Test data: 0.8239886164665222, 0.6753586530685425
Step 7 | Training Loss: 0.467604 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8247427344322205, 0.6756961941719055
Step 8 | Training Loss: 0.461499 | Validation Accuracy: 0.917460
Accuracy on Test data: 0.8243878483772278, 0.6735864877700806
Step 9 | Training Loss: 0.440867 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.8238555788993835, 0.6721519231796265
Step 10 | Training Loss: 0.455344 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.8207948803901672, 0.6659071445465088
Step 1 | Training Loss: 0.412263 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.820262610912323, 0.6648101210594177
Step 2 | Training Loss: 0.415664 | Validation Accuracy: 0.929365
Accuracy on Test data: 0.8200408220291138, 0.6643881797790527
Step 3 | Training Loss: 0.411972 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.8199520707130432, 0.6640506386756897
Step 4 | Training Loss: 0.425523 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.8198190331459045, 0.6637130975723267
Step 5 | Training Loss: 0.421360 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.8194641470909119, 0.6630379557609558
Step 6 | Training Loss: 0.433482 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.8191536664962769, 0.6624472737312317
Step 7 | Training Loss: 0.467874 | Validation Accuracy: 0.939683
Accuracy on Test data: 0.8190649151802063, 0.6621940732002258
Step 8 | Training Loss: 0.434142 | Validation Accuracy: 0.932143
Accuracy on Test data: 0.8189318776130676, 0.6616877913475037
Step 9 | Training Loss: 0.435005 | Validation Accuracy: 0.941667
Accuracy on Test data: 0.8186657428741455, 0.6611814498901367
Step 10 | Training Loss: 0.416219 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8184882998466492, 0.6606751084327698
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.687147 | Validation Accuracy: 0.772222
Accuracy on Test data: 0.7924946546554565, 0.6712236404418945
Step 2 | Training Loss: 0.624546 | Validation Accuracy: 0.850000
Accuracy on Test data: 0.8142299652099609, 0.6681012511253357
Step 3 | Training Loss: 0.566469 | Validation Accuracy: 0.882143
Accuracy on Test data: 0.8091288208961487, 0.6531645655632019
Step 4 | Training Loss: 0.540415 | Validation Accuracy: 0.899603
Accuracy on Test data: 0.8095280528068542, 0.6508016586303711
Step 5 | Training Loss: 0.497224 | Validation Accuracy: 0.898810
Accuracy on Test data: 0.8131210207939148, 0.6564556956291199
Step 6 | Training Loss: 0.465531 | Validation Accuracy: 0.920635
Accuracy on Test data: 0.8130766749382019, 0.6556118130683899
Step 7 | Training Loss: 0.484654 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8134758472442627, 0.6557806134223938
Step 8 | Training Loss: 0.448423 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.813342809677124, 0.6552742719650269
Step 9 | Training Loss: 0.454694 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.8139194250106812, 0.6563712954521179
Step 10 | Training Loss: 0.424600 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.8137420415878296, 0.6556962132453918
Step 1 | Training Loss: 0.446985 | Validation Accuracy: 0.946032
Accuracy on Test data: 0.8137420415878296, 0.6555274128913879
Step 2 | Training Loss: 0.444470 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8136976361274719, 0.655443012714386
Step 3 | Training Loss: 0.449211 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.8135645985603333, 0.6551898717880249
Step 4 | Training Loss: 0.413689 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.8135202527046204, 0.655105471611023
Step 5 | Training Loss: 0.419892 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8134315013885498, 0.6549367308616638
Step 6 | Training Loss: 0.439355 | Validation Accuracy: 0.949603
Accuracy on Test data: 0.8133871555328369, 0.6547679305076599
Step 7 | Training Loss: 0.380982 | Validation Accuracy: 0.942460
Accuracy on Test data: 0.8132984638214111, 0.654599130153656
Step 8 | Training Loss: 0.442472 | Validation Accuracy: 0.949206
Accuracy on Test data: 0.8131210207939148, 0.654261589050293
Step 9 | Training Loss: 0.425359 | Validation Accuracy: 0.949206
Accuracy on Test data: 0.8130766749382019, 0.654177188873291
Step 10 | Training Loss: 0.427421 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.8134315013885498, 0.6548523306846619
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.693063 | Validation Accuracy: 0.547222
Accuracy on Test data: 0.4394073784351349, 0.19662447273731232
Step 2 | Training Loss: 0.692987 | Validation Accuracy: 0.536508
Accuracy on Test data: 0.4381210207939148, 0.1934177279472351
Step 3 | Training Loss: 0.692907 | Validation Accuracy: 0.557936
Accuracy on Test data: 0.43829843401908875, 0.19350211322307587
Step 4 | Training Loss: 0.693034 | Validation Accuracy: 0.537302
Accuracy on Test data: 0.43891945481300354, 0.19434599578380585
Step 5 | Training Loss: 0.691914 | Validation Accuracy: 0.568254
Accuracy on Test data: 0.4422019124031067, 0.19991561770439148
Step 6 | Training Loss: 0.691438 | Validation Accuracy: 0.580159
Accuracy on Test data: 0.4658889174461365, 0.24270042777061462
Step 7 | Training Loss: 0.691204 | Validation Accuracy: 0.682936
Accuracy on Test data: 0.5130411386489868, 0.26016879081726074
Step 8 | Training Loss: 0.693265 | Validation Accuracy: 0.742857
Accuracy on Test data: 0.5805092453956604, 0.2859915494918823
Step 9 | Training Loss: 0.690320 | Validation Accuracy: 0.790476
Accuracy on Test data: 0.6267743110656738, 0.3099578022956848
Step 10 | Training Loss: 0.690682 | Validation Accuracy: 0.827778
Accuracy on Test data: 0.646025538444519, 0.3423628807067871
Step 1 | Training Loss: 0.688777 | Validation Accuracy: 0.829365
Accuracy on Test data: 0.647445023059845, 0.34489452838897705
Step 2 | Training Loss: 0.689789 | Validation Accuracy: 0.837302
Accuracy on Test data: 0.6484208703041077, 0.3466666638851166
Step 3 | Training Loss: 0.689146 | Validation Accuracy: 0.832540
Accuracy on Test data: 0.6500177383422852, 0.34945148229599
Step 4 | Training Loss: 0.690214 | Validation Accuracy: 0.834127
Accuracy on Test data: 0.6513041257858276, 0.3516455590724945
Step 5 | Training Loss: 0.691653 | Validation Accuracy: 0.846032
Accuracy on Test data: 0.6527235507965088, 0.3540928363800049
Step 6 | Training Loss: 0.689352 | Validation Accuracy: 0.837698
Accuracy on Test data: 0.6539212465286255, 0.35637131333351135
Step 7 | Training Loss: 0.688342 | Validation Accuracy: 0.833333
Accuracy on Test data: 0.6547196507453918, 0.3577215075492859
Step 8 | Training Loss: 0.692078 | Validation Accuracy: 0.839286
Accuracy on Test data: 0.6562721729278564, 0.3605063259601593
Step 9 | Training Loss: 0.689387 | Validation Accuracy: 0.851587
Accuracy on Test data: 0.6576915979385376, 0.36303797364234924
Step 10 | Training Loss: 0.689915 | Validation Accuracy: 0.838889
Accuracy on Test data: 0.6588892936706543, 0.36464133858680725
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.673877 | Validation Accuracy: 0.614683
Accuracy on Test data: 0.720901370048523, 0.797046422958374
Step 2 | Training Loss: 0.673931 | Validation Accuracy: 0.724603
Accuracy on Test data: 0.8453690409660339, 0.801181435585022
Step 3 | Training Loss: 0.658810 | Validation Accuracy: 0.764683
Accuracy on Test data: 0.8496717810630798, 0.796286940574646
Step 4 | Training Loss: 0.692749 | Validation Accuracy: 0.804762
Accuracy on Test data: 0.8358321785926819, 0.7518987059593201
Step 5 | Training Loss: 0.689353 | Validation Accuracy: 0.846032
Accuracy on Test data: 0.8491394519805908, 0.7618565559387207
Step 6 | Training Loss: 0.632527 | Validation Accuracy: 0.881349
Accuracy on Test data: 0.8662615418434143, 0.7772151827812195
Step 7 | Training Loss: 0.673166 | Validation Accuracy: 0.891667
Accuracy on Test data: 0.8703424334526062, 0.7794092893600464
Step 8 | Training Loss: 0.621597 | Validation Accuracy: 0.896032
Accuracy on Test data: 0.8743346333503723, 0.7810970544815063
Step 9 | Training Loss: 0.614134 | Validation Accuracy: 0.911508
Accuracy on Test data: 0.8750886917114258, 0.7791560888290405
Step 10 | Training Loss: 0.615622 | Validation Accuracy: 0.916667
Accuracy on Test data: 0.8757540583610535, 0.7787341475486755
Step 1 | Training Loss: 0.593523 | Validation Accuracy: 0.909127
Accuracy on Test data: 0.8717618584632874, 0.7710548639297485
Step 2 | Training Loss: 0.635315 | Validation Accuracy: 0.911905
Accuracy on Test data: 0.8682576417922974, 0.7641350030899048
Step 3 | Training Loss: 0.607584 | Validation Accuracy: 0.912302
Accuracy on Test data: 0.8638218641281128, 0.7555274367332458
Step 4 | Training Loss: 0.670006 | Validation Accuracy: 0.918651
Accuracy on Test data: 0.8639549612998962, 0.755696177482605
Step 5 | Training Loss: 0.626130 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8635557293891907, 0.754936695098877
Step 6 | Training Loss: 0.610956 | Validation Accuracy: 0.915079
Accuracy on Test data: 0.8636887669563293, 0.7551054954528809
Step 7 | Training Loss: 0.633534 | Validation Accuracy: 0.927381
Accuracy on Test data: 0.863200843334198, 0.754092812538147
Step 8 | Training Loss: 0.605641 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.8631564974784851, 0.7539240717887878
Step 9 | Training Loss: 0.584796 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8634226322174072, 0.7543460130691528
Step 10 | Training Loss: 0.644811 | Validation Accuracy: 0.922222
Accuracy on Test data: 0.8634669780731201, 0.75443035364151
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
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Accuracy on Test data: 0.44983142614364624, 0.21729958057403564
Step 2 | Training Loss: 0.700032 | Validation Accuracy: 0.607540
Accuracy on Test data: 0.4835876524448395, 0.2272573858499527
Step 3 | Training Loss: 0.681356 | Validation Accuracy: 0.677381
Accuracy on Test data: 0.5026614665985107, 0.23721519112586975
Step 4 | Training Loss: 0.668578 | Validation Accuracy: 0.711508
Accuracy on Test data: 0.5856990814208984, 0.24008439481258392
Step 5 | Training Loss: 0.631740 | Validation Accuracy: 0.734127
Accuracy on Test data: 0.6113378405570984, 0.2866666615009308
Step 6 | Training Loss: 0.649678 | Validation Accuracy: 0.775794
Accuracy on Test data: 0.6230925917625427, 0.30725738406181335
Step 7 | Training Loss: 0.611974 | Validation Accuracy: 0.815873
Accuracy on Test data: 0.6378637552261353, 0.3331645429134369
Step 8 | Training Loss: 0.596150 | Validation Accuracy: 0.829365
Accuracy on Test data: 0.6576029062271118, 0.36843881011009216
Step 9 | Training Loss: 0.595785 | Validation Accuracy: 0.855556
Accuracy on Test data: 0.6698899865150452, 0.38894516229629517
Step 10 | Training Loss: 0.556482 | Validation Accuracy: 0.877778
Accuracy on Test data: 0.6859474778175354, 0.4151054918766022
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Accuracy on Test data: 0.6877217888832092, 0.41839662194252014
Step 2 | Training Loss: 0.599030 | Validation Accuracy: 0.888095
Accuracy on Test data: 0.6901171207427979, 0.4229535758495331
Step 3 | Training Loss: 0.667021 | Validation Accuracy: 0.887302
Accuracy on Test data: 0.6921132206916809, 0.426751047372818
Step 4 | Training Loss: 0.558025 | Validation Accuracy: 0.878968
Accuracy on Test data: 0.6934882998466492, 0.42919832468032837
Step 5 | Training Loss: 0.607616 | Validation Accuracy: 0.884127
Accuracy on Test data: 0.6946859359741211, 0.4313924014568329
Step 6 | Training Loss: 0.569873 | Validation Accuracy: 0.887302
Accuracy on Test data: 0.6965489983558655, 0.43468353152275085
Step 7 | Training Loss: 0.599622 | Validation Accuracy: 0.892857
Accuracy on Test data: 0.6985006928443909, 0.4378059208393097
Step 8 | Training Loss: 0.584390 | Validation Accuracy: 0.892063
Accuracy on Test data: 0.7002306580543518, 0.44109705090522766
Step 9 | Training Loss: 0.572836 | Validation Accuracy: 0.896032
Accuracy on Test data: 0.7011178135871887, 0.4427848160266876
Step 10 | Training Loss: 0.581638 | Validation Accuracy: 0.893651
Accuracy on Test data: 0.7020049691200256, 0.44438818097114563
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.674120 | Validation Accuracy: 0.672619
Accuracy on Test data: 0.5823279023170471, 0.6183122396469116
Step 2 | Training Loss: 0.651275 | Validation Accuracy: 0.822222
Accuracy on Test data: 0.7797196507453918, 0.6556118130683899
Step 3 | Training Loss: 0.629393 | Validation Accuracy: 0.832937
Accuracy on Test data: 0.8017654418945312, 0.6791561245918274
Step 4 | Training Loss: 0.631256 | Validation Accuracy: 0.841270
Accuracy on Test data: 0.8219925761222839, 0.702025294303894
Step 5 | Training Loss: 0.618366 | Validation Accuracy: 0.852381
Accuracy on Test data: 0.8307753801345825, 0.7063291072845459
Step 6 | Training Loss: 0.597137 | Validation Accuracy: 0.871032
Accuracy on Test data: 0.8310415148735046, 0.69974684715271
Step 7 | Training Loss: 0.594264 | Validation Accuracy: 0.882937
Accuracy on Test data: 0.8160486221313477, 0.6672573685646057
Step 8 | Training Loss: 0.607783 | Validation Accuracy: 0.890476
Accuracy on Test data: 0.8149396777153015, 0.6637130975723267
Step 9 | Training Loss: 0.564399 | Validation Accuracy: 0.905556
Accuracy on Test data: 0.813653290271759, 0.6599156260490417
Step 10 | Training Loss: 0.558876 | Validation Accuracy: 0.912302
Accuracy on Test data: 0.8137863874435425, 0.6589873433113098
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Accuracy on Test data: 0.8125443458557129, 0.6565400958061218
Step 2 | Training Loss: 0.571064 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8124113082885742, 0.656286895275116
Step 3 | Training Loss: 0.525460 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.8126774430274963, 0.6567932367324829
Step 4 | Training Loss: 0.542171 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.8123225569725037, 0.6561181545257568
Step 5 | Training Loss: 0.549845 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.8120564222335815, 0.6555274128913879
Step 6 | Training Loss: 0.534080 | Validation Accuracy: 0.927381
Accuracy on Test data: 0.812189519405365, 0.6556962132453918
Step 7 | Training Loss: 0.566619 | Validation Accuracy: 0.914286
Accuracy on Test data: 0.8119677305221558, 0.6552742719650269
Step 8 | Training Loss: 0.548004 | Validation Accuracy: 0.924206
Accuracy on Test data: 0.8116128444671631, 0.6545147895812988
Step 9 | Training Loss: 0.537644 | Validation Accuracy: 0.915476
Accuracy on Test data: 0.8112579584121704, 0.653839647769928
Step 10 | Training Loss: 0.563511 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.8109474778175354, 0.6531645655632019
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.695275 | Validation Accuracy: 0.721032
Accuracy on Test data: 0.7192157506942749, 0.6224472522735596
Step 2 | Training Loss: 0.661552 | Validation Accuracy: 0.794841
Accuracy on Test data: 0.8200851678848267, 0.7048101425170898
Step 3 | Training Loss: 0.617277 | Validation Accuracy: 0.848810
Accuracy on Test data: 0.8369410634040833, 0.7124894261360168
Step 4 | Training Loss: 0.607751 | Validation Accuracy: 0.913492
Accuracy on Test data: 0.8577892184257507, 0.7427847981452942
Step 5 | Training Loss: 0.566211 | Validation Accuracy: 0.911905
Accuracy on Test data: 0.8592086434364319, 0.744303822517395
Step 6 | Training Loss: 0.535724 | Validation Accuracy: 0.924206
Accuracy on Test data: 0.8574343323707581, 0.7391561269760132
Step 7 | Training Loss: 0.567525 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.8469659090042114, 0.7185654044151306
Step 8 | Training Loss: 0.467065 | Validation Accuracy: 0.923016
Accuracy on Test data: 0.8424414396286011, 0.7094514966011047
Step 9 | Training Loss: 0.505844 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8427963256835938, 0.7101265788078308
Step 10 | Training Loss: 0.458680 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.8384935855865479, 0.701603353023529
Step 1 | Training Loss: 0.467905 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8387597799301147, 0.702109694480896
Step 2 | Training Loss: 0.450754 | Validation Accuracy: 0.933333
Accuracy on Test data: 0.8380056619644165, 0.7006751298904419
Step 3 | Training Loss: 0.470326 | Validation Accuracy: 0.934127
Accuracy on Test data: 0.8376951813697815, 0.700084388256073
Step 4 | Training Loss: 0.446108 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8372072577476501, 0.6991561055183411
Step 5 | Training Loss: 0.464782 | Validation Accuracy: 0.942460
Accuracy on Test data: 0.8370741605758667, 0.698818564414978
Step 6 | Training Loss: 0.470170 | Validation Accuracy: 0.933730
Accuracy on Test data: 0.8369410634040833, 0.6985654234886169
Step 7 | Training Loss: 0.438572 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8359652161598206, 0.6967088580131531
Step 8 | Training Loss: 0.458166 | Validation Accuracy: 0.934127
Accuracy on Test data: 0.8348562717437744, 0.6945147514343262
Step 9 | Training Loss: 0.492045 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8336586356163025, 0.6921519041061401
Step 10 | Training Loss: 0.459956 | Validation Accuracy: 0.933333
Accuracy on Test data: 0.8330819606781006, 0.6910548806190491
Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.677522 | Validation Accuracy: 0.678571
Accuracy on Test data: 0.6083658337593079, 0.551476776599884
Step 2 | Training Loss: 0.621664 | Validation Accuracy: 0.811111
Accuracy on Test data: 0.6935326457023621, 0.6108016967773438
Step 3 | Training Loss: 0.607377 | Validation Accuracy: 0.826190
Accuracy on Test data: 0.6969925761222839, 0.5958649516105652
Step 4 | Training Loss: 0.565843 | Validation Accuracy: 0.885714
Accuracy on Test data: 0.7904542088508606, 0.6112236380577087
Step 5 | Training Loss: 0.523955 | Validation Accuracy: 0.911111
Accuracy on Test data: 0.8235450387001038, 0.6725738644599915
Step 6 | Training Loss: 0.475074 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.821415901184082, 0.6671729683876038
Step 7 | Training Loss: 0.474063 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.8238555788993835, 0.6706328988075256
Step 8 | Training Loss: 0.442432 | Validation Accuracy: 0.929365
Accuracy on Test data: 0.8272711038589478, 0.6768776178359985
Step 9 | Training Loss: 0.458479 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.82948899269104, 0.6803375482559204
Step 10 | Training Loss: 0.428880 | Validation Accuracy: 0.945238
Accuracy on Test data: 0.8224804997444153, 0.6669198274612427
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Accuracy on Test data: 0.8187544345855713, 0.6598312258720398
Step 2 | Training Loss: 0.477474 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.8136976361274719, 0.650210976600647
Step 3 | Training Loss: 0.416786 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.8089957237243652, 0.6412658095359802
Step 4 | Training Loss: 0.435863 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.8046486973762512, 0.6327426433563232
Step 5 | Training Loss: 0.432077 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.8036284446716309, 0.6308016777038574
Step 6 | Training Loss: 0.421386 | Validation Accuracy: 0.958333
Accuracy on Test data: 0.8031848669052124, 0.6299577951431274
Step 7 | Training Loss: 0.424550 | Validation Accuracy: 0.954762
Accuracy on Test data: 0.8021646738052368, 0.6280168890953064
Step 8 | Training Loss: 0.420930 | Validation Accuracy: 0.952778
Accuracy on Test data: 0.8017654418945312, 0.6272574067115784
Step 9 | Training Loss: 0.418368 | Validation Accuracy: 0.942857
Accuracy on Test data: 0.8014549612998962, 0.6266666650772095
Step 10 | Training Loss: 0.439268 | Validation Accuracy: 0.945635
Accuracy on Test data: 0.801543653011322, 0.6267510652542114
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.700626 | Validation Accuracy: 0.542857
Accuracy on Test data: 0.4536462128162384, 0.2205907106399536
Step 2 | Training Loss: 0.683508 | Validation Accuracy: 0.682936
Accuracy on Test data: 0.5147267580032349, 0.2600843906402588
Step 3 | Training Loss: 0.686013 | Validation Accuracy: 0.715873
Accuracy on Test data: 0.6344481706619263, 0.325654000043869
Step 4 | Training Loss: 0.640443 | Validation Accuracy: 0.767063
Accuracy on Test data: 0.6586231589317322, 0.3670042157173157
Step 5 | Training Loss: 0.574762 | Validation Accuracy: 0.800000
Accuracy on Test data: 0.6729950308799744, 0.3911392390727997
Step 6 | Training Loss: 0.582021 | Validation Accuracy: 0.838492
Accuracy on Test data: 0.7015613913536072, 0.4430379867553711
Step 7 | Training Loss: 0.554168 | Validation Accuracy: 0.848810
Accuracy on Test data: 0.718018114566803, 0.472573846578598
Step 8 | Training Loss: 0.507814 | Validation Accuracy: 0.885714
Accuracy on Test data: 0.7257363200187683, 0.48658227920532227
Step 9 | Training Loss: 0.490023 | Validation Accuracy: 0.886111
Accuracy on Test data: 0.7335876226425171, 0.5009282827377319
Step 10 | Training Loss: 0.511685 | Validation Accuracy: 0.893651
Accuracy on Test data: 0.7414833307266235, 0.5143460035324097
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Accuracy on Test data: 0.7421043515205383, 0.5155274271965027
Step 2 | Training Loss: 0.480977 | Validation Accuracy: 0.896429
Accuracy on Test data: 0.7429915070533752, 0.5172995924949646
Step 3 | Training Loss: 0.454192 | Validation Accuracy: 0.892460
Accuracy on Test data: 0.7441891431808472, 0.5195780396461487
Step 4 | Training Loss: 0.464956 | Validation Accuracy: 0.882143
Accuracy on Test data: 0.7453424334526062, 0.5216033458709717
Step 5 | Training Loss: 0.496506 | Validation Accuracy: 0.894048
Accuracy on Test data: 0.7461852431297302, 0.5230379700660706
Step 6 | Training Loss: 0.506985 | Validation Accuracy: 0.894444
Accuracy on Test data: 0.7469836473464966, 0.5245569348335266
Step 7 | Training Loss: 0.421883 | Validation Accuracy: 0.899206
Accuracy on Test data: 0.7477821111679077, 0.5259915590286255
Step 8 | Training Loss: 0.503288 | Validation Accuracy: 0.900397
Accuracy on Test data: 0.7492015361785889, 0.5285232067108154
Step 9 | Training Loss: 0.451988 | Validation Accuracy: 0.896429
Accuracy on Test data: 0.7497338652610779, 0.5295358896255493
Step 10 | Training Loss: 0.426996 | Validation Accuracy: 0.901190
Accuracy on Test data: 0.7508871555328369, 0.5316455960273743
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.626393 | Validation Accuracy: 0.823016
Accuracy on Test data: 0.7058197259902954, 0.498818576335907
Step 2 | Training Loss: 0.556652 | Validation Accuracy: 0.855952
Accuracy on Test data: 0.7300390601158142, 0.5091139078140259
Step 3 | Training Loss: 0.522642 | Validation Accuracy: 0.881746
Accuracy on Test data: 0.742237389087677, 0.5267510414123535
Step 4 | Training Loss: 0.510134 | Validation Accuracy: 0.897619
Accuracy on Test data: 0.7503992319107056, 0.5392404794692993
Step 5 | Training Loss: 0.516486 | Validation Accuracy: 0.909127
Accuracy on Test data: 0.7527501583099365, 0.5424472689628601
Step 6 | Training Loss: 0.465994 | Validation Accuracy: 0.922222
Accuracy on Test data: 0.7560326457023621, 0.5469198226928711
Step 7 | Training Loss: 0.476885 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.7594481706619263, 0.5522362589836121
Step 8 | Training Loss: 0.472546 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.7650372385978699, 0.5620253086090088
Step 9 | Training Loss: 0.456143 | Validation Accuracy: 0.948413
Accuracy on Test data: 0.7779009938240051, 0.5854852199554443
Step 10 | Training Loss: 0.438764 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.7924946546554565, 0.6113080382347107
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Accuracy on Test data: 0.7927164435386658, 0.6116455793380737
Step 2 | Training Loss: 0.439666 | Validation Accuracy: 0.951587
Accuracy on Test data: 0.7923616170883179, 0.6108860969543457
Step 3 | Training Loss: 0.433804 | Validation Accuracy: 0.948413
Accuracy on Test data: 0.792317271232605, 0.6106328964233398
Step 4 | Training Loss: 0.444950 | Validation Accuracy: 0.948810
Accuracy on Test data: 0.7921841740608215, 0.6103797554969788
Step 5 | Training Loss: 0.434940 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.7917405962944031, 0.6095358729362488
Step 6 | Training Loss: 0.429753 | Validation Accuracy: 0.950794
Accuracy on Test data: 0.7911195755004883, 0.6083544492721558
Step 7 | Training Loss: 0.385985 | Validation Accuracy: 0.946032
Accuracy on Test data: 0.7899662852287292, 0.6061603426933289
Step 8 | Training Loss: 0.409584 | Validation Accuracy: 0.948810
Accuracy on Test data: 0.7891678214073181, 0.6046413779258728
Step 9 | Training Loss: 0.420274 | Validation Accuracy: 0.958333
Accuracy on Test data: 0.788591206073761, 0.603544294834137
Step 10 | Training Loss: 0.460217 | Validation Accuracy: 0.950794
Accuracy on Test data: 0.7873491644859314, 0.6011814475059509
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.740275 | Validation Accuracy: 0.510714
Accuracy on Test data: 0.5398775935173035, 0.5609282851219177
Step 2 | Training Loss: 0.641448 | Validation Accuracy: 0.660317
Accuracy on Test data: 0.6429204940795898, 0.596202552318573
Step 3 | Training Loss: 0.576629 | Validation Accuracy: 0.840873
Accuracy on Test data: 0.7777235507965088, 0.6228691935539246
Step 4 | Training Loss: 0.581998 | Validation Accuracy: 0.878571
Accuracy on Test data: 0.7980837225914001, 0.6319831013679504
Step 5 | Training Loss: 0.497206 | Validation Accuracy: 0.880556
Accuracy on Test data: 0.8006564974784851, 0.6335021257400513
Step 6 | Training Loss: 0.504190 | Validation Accuracy: 0.898413
Accuracy on Test data: 0.8008782863616943, 0.6312236189842224
Step 7 | Training Loss: 0.496960 | Validation Accuracy: 0.894444
Accuracy on Test data: 0.8011887669563293, 0.6308016777038574
Step 8 | Training Loss: 0.494713 | Validation Accuracy: 0.923413
Accuracy on Test data: 0.8010113835334778, 0.6302953362464905
Step 9 | Training Loss: 0.454368 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.7932487726211548, 0.6146835684776306
Step 10 | Training Loss: 0.433201 | Validation Accuracy: 0.936111
Accuracy on Test data: 0.7928938865661621, 0.6135020852088928
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Accuracy on Test data: 0.7926720976829529, 0.6129958033561707
Step 2 | Training Loss: 0.458253 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.7923616170883179, 0.6123206615447998
Step 3 | Training Loss: 0.477346 | Validation Accuracy: 0.926587
Accuracy on Test data: 0.7924059629440308, 0.6124050617218018
Step 4 | Training Loss: 0.460963 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.7922285199165344, 0.6119831204414368
Step 5 | Training Loss: 0.457205 | Validation Accuracy: 0.936508
Accuracy on Test data: 0.7918736934661865, 0.6112236380577087
Step 6 | Training Loss: 0.427011 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.7916519045829773, 0.6107172966003418
Step 7 | Training Loss: 0.426900 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.7913857102394104, 0.6102109551429749
Step 8 | Training Loss: 0.437091 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.791474461555481, 0.6103797554969788
Step 9 | Training Loss: 0.455769 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.7911639213562012, 0.6096202731132507
Step 10 | Training Loss: 0.439554 | Validation Accuracy: 0.940476
Accuracy on Test data: 0.7909865379333496, 0.6089451313018799
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.659970 | Validation Accuracy: 0.642857
Accuracy on Test data: 0.7087473273277283, 0.5641350150108337
Step 2 | Training Loss: 0.586200 | Validation Accuracy: 0.794841
Accuracy on Test data: 0.7916074991226196, 0.6279324889183044
Step 3 | Training Loss: 0.576643 | Validation Accuracy: 0.841667
Accuracy on Test data: 0.8094836473464966, 0.6539240479469299
Step 4 | Training Loss: 0.549837 | Validation Accuracy: 0.875397
Accuracy on Test data: 0.8215045928955078, 0.6715611815452576
Step 5 | Training Loss: 0.547593 | Validation Accuracy: 0.896429
Accuracy on Test data: 0.8250975608825684, 0.6755274534225464
Step 6 | Training Loss: 0.455088 | Validation Accuracy: 0.916667
Accuracy on Test data: 0.8275372385978699, 0.6789029240608215
Step 7 | Training Loss: 0.501299 | Validation Accuracy: 0.919048
Accuracy on Test data: 0.8270936608314514, 0.6775527596473694
Step 8 | Training Loss: 0.488933 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8265170454978943, 0.6763713359832764
Step 9 | Training Loss: 0.482712 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.8267831802368164, 0.6766244769096375
Step 10 | Training Loss: 0.431244 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.8253637552261353, 0.6736708879470825
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Accuracy on Test data: 0.8254081010818481, 0.6736708879470825
Step 2 | Training Loss: 0.456346 | Validation Accuracy: 0.926984
Accuracy on Test data: 0.8253637552261353, 0.6735864877700806
Step 3 | Training Loss: 0.430146 | Validation Accuracy: 0.940476
Accuracy on Test data: 0.8253193497657776, 0.6735020875930786
Step 4 | Training Loss: 0.455064 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.8250975608825684, 0.6730801463127136
Step 5 | Training Loss: 0.431418 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.8249201774597168, 0.6727426052093506
Step 6 | Training Loss: 0.438076 | Validation Accuracy: 0.942460
Accuracy on Test data: 0.8249201774597168, 0.6727426052093506
Step 7 | Training Loss: 0.418243 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8249201774597168, 0.6727426052093506
Step 8 | Training Loss: 0.422538 | Validation Accuracy: 0.936111
Accuracy on Test data: 0.8245652914047241, 0.6720675230026245
Step 9 | Training Loss: 0.420511 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.824299156665802, 0.6715611815452576
Step 10 | Training Loss: 0.419378 | Validation Accuracy: 0.939286
Accuracy on Test data: 0.8241660594940186, 0.6713080406188965
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.707739 | Validation Accuracy: 0.527381
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.701140 | Validation Accuracy: 0.529762
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.689011 | Validation Accuracy: 0.559921
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.688159 | Validation Accuracy: 0.516667
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.672713 | Validation Accuracy: 0.539683
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.702308 | Validation Accuracy: 0.529365
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.671768 | Validation Accuracy: 0.532540
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.656738 | Validation Accuracy: 0.529762
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.670383 | Validation Accuracy: 0.540079
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.652311 | Validation Accuracy: 0.526984
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 1 | Training Loss: 0.661280 | Validation Accuracy: 0.544444
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.679913 | Validation Accuracy: 0.532540
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.668328 | Validation Accuracy: 0.535714
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.653142 | Validation Accuracy: 0.537698
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.651726 | Validation Accuracy: 0.539683
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.652429 | Validation Accuracy: 0.540476
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.672052 | Validation Accuracy: 0.526190
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.672441 | Validation Accuracy: 0.527381
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.647983 | Validation Accuracy: 0.530952
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.683216 | Validation Accuracy: 0.533333
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.648386 | Validation Accuracy: 0.797222
Accuracy on Test data: 0.8128548860549927, 0.7190717458724976
Step 2 | Training Loss: 0.676625 | Validation Accuracy: 0.805159
Accuracy on Test data: 0.8208836317062378, 0.7151054739952087
Step 3 | Training Loss: 0.656458 | Validation Accuracy: 0.830159
Accuracy on Test data: 0.830686628818512, 0.7105485200881958
Step 4 | Training Loss: 0.676221 | Validation Accuracy: 0.861111
Accuracy on Test data: 0.8431511521339417, 0.7240506410598755
Step 5 | Training Loss: 0.650915 | Validation Accuracy: 0.871825
Accuracy on Test data: 0.8514460325241089, 0.7350211143493652
Step 6 | Training Loss: 0.612846 | Validation Accuracy: 0.884524
Accuracy on Test data: 0.85224449634552, 0.7350211143493652
Step 7 | Training Loss: 0.653966 | Validation Accuracy: 0.895635
Accuracy on Test data: 0.8531759977340698, 0.7343459725379944
Step 8 | Training Loss: 0.626661 | Validation Accuracy: 0.886508
Accuracy on Test data: 0.8455908298492432, 0.7187342047691345
Step 9 | Training Loss: 0.634473 | Validation Accuracy: 0.905952
Accuracy on Test data: 0.8353441953659058, 0.6973839402198792
Step 10 | Training Loss: 0.636796 | Validation Accuracy: 0.901984
Accuracy on Test data: 0.8278034329414368, 0.6822784543037415
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Accuracy on Test data: 0.8279364705085754, 0.6824472546577454
Step 2 | Training Loss: 0.615720 | Validation Accuracy: 0.895238
Accuracy on Test data: 0.8279808163642883, 0.6824472546577454
Step 3 | Training Loss: 0.645993 | Validation Accuracy: 0.903968
Accuracy on Test data: 0.8277590274810791, 0.6819409132003784
Step 4 | Training Loss: 0.630247 | Validation Accuracy: 0.907937
Accuracy on Test data: 0.827492892742157, 0.6813502311706543
Step 5 | Training Loss: 0.619886 | Validation Accuracy: 0.898413
Accuracy on Test data: 0.8276259899139404, 0.6816033720970154
Step 6 | Training Loss: 0.641881 | Validation Accuracy: 0.911111
Accuracy on Test data: 0.8269606232643127, 0.6801687479019165
Step 7 | Training Loss: 0.616905 | Validation Accuracy: 0.906746
Accuracy on Test data: 0.8258516788482666, 0.6779747009277344
Step 8 | Training Loss: 0.624828 | Validation Accuracy: 0.909921
Accuracy on Test data: 0.8255855441093445, 0.6773839592933655
Step 9 | Training Loss: 0.581095 | Validation Accuracy: 0.904762
Accuracy on Test data: 0.8253193497657776, 0.6768776178359985
Step 10 | Training Loss: 0.649522 | Validation Accuracy: 0.900794
Accuracy on Test data: 0.8245652914047241, 0.6753586530685425
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
Step 1 | Training Loss: 0.735964 | Validation Accuracy: 0.634127
Accuracy on Test data: 0.5324698090553284, 0.38092827796936035
Step 2 | Training Loss: 0.711714 | Validation Accuracy: 0.711111
Accuracy on Test data: 0.5833925008773804, 0.4027848243713379
Step 3 | Training Loss: 0.691288 | Validation Accuracy: 0.734524
Accuracy on Test data: 0.5992282032966614, 0.4281012713909149
Step 4 | Training Loss: 0.671583 | Validation Accuracy: 0.753175
Accuracy on Test data: 0.6125798225402832, 0.448016881942749
Step 5 | Training Loss: 0.664708 | Validation Accuracy: 0.816667
Accuracy on Test data: 0.6326738595962524, 0.4792405068874359
Step 6 | Training Loss: 0.646630 | Validation Accuracy: 0.838492
Accuracy on Test data: 0.728087306022644, 0.5083544254302979
Step 7 | Training Loss: 0.636528 | Validation Accuracy: 0.884524
Accuracy on Test data: 0.7571859359741211, 0.5584810376167297
Step 8 | Training Loss: 0.579515 | Validation Accuracy: 0.884921
Accuracy on Test data: 0.7667228579521179, 0.5735021233558655
Step 9 | Training Loss: 0.686004 | Validation Accuracy: 0.890873
Accuracy on Test data: 0.7826029062271118, 0.6016877889633179
Step 10 | Training Loss: 0.598271 | Validation Accuracy: 0.899603
Accuracy on Test data: 0.797817587852478, 0.6291139125823975
Step 1 | Training Loss: 0.617785 | Validation Accuracy: 0.900794
Accuracy on Test data: 0.7989708781242371, 0.6311392188072205
Step 2 | Training Loss: 0.648395 | Validation Accuracy: 0.919048
Accuracy on Test data: 0.7991039752960205, 0.6313924193382263
Step 3 | Training Loss: 0.620021 | Validation Accuracy: 0.901984
Accuracy on Test data: 0.7996362447738647, 0.6316455602645874
Step 4 | Training Loss: 0.588161 | Validation Accuracy: 0.911111
Accuracy on Test data: 0.7999024391174316, 0.6317299604415894
Step 5 | Training Loss: 0.580504 | Validation Accuracy: 0.911905
Accuracy on Test data: 0.8003016114234924, 0.6324894428253174
Step 6 | Training Loss: 0.610891 | Validation Accuracy: 0.903571
Accuracy on Test data: 0.8009226322174072, 0.6329957842826843
Step 7 | Training Loss: 0.603797 | Validation Accuracy: 0.908730
Accuracy on Test data: 0.8013662099838257, 0.6336708664894104
Step 8 | Training Loss: 0.579425 | Validation Accuracy: 0.905159
Accuracy on Test data: 0.8021202683448792, 0.6351054906845093
Step 9 | Training Loss: 0.601571 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8028300404548645, 0.6363713145256042
Step 10 | Training Loss: 0.614538 | Validation Accuracy: 0.920238
Accuracy on Test data: 0.8040720224380493, 0.6383966207504272
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.688161 | Validation Accuracy: 0.746032
Accuracy on Test data: 0.707061767578125, 0.5457383990287781
Step 2 | Training Loss: 0.676604 | Validation Accuracy: 0.810714
Accuracy on Test data: 0.7244055867195129, 0.5652320384979248
Step 3 | Training Loss: 0.672206 | Validation Accuracy: 0.828571
Accuracy on Test data: 0.7441891431808472, 0.5770463943481445
Step 4 | Training Loss: 0.646096 | Validation Accuracy: 0.863492
Accuracy on Test data: 0.7540808916091919, 0.5784810185432434
Step 5 | Training Loss: 0.621007 | Validation Accuracy: 0.894444
Accuracy on Test data: 0.7619765996932983, 0.5703797340393066
Step 6 | Training Loss: 0.642897 | Validation Accuracy: 0.900397
Accuracy on Test data: 0.7647711038589478, 0.5733333230018616
Step 7 | Training Loss: 0.591927 | Validation Accuracy: 0.899206
Accuracy on Test data: 0.7688076496124268, 0.5784810185432434
Step 8 | Training Loss: 0.602874 | Validation Accuracy: 0.908333
Accuracy on Test data: 0.7773687243461609, 0.5929113626480103
Step 9 | Training Loss: 0.576862 | Validation Accuracy: 0.919841
Accuracy on Test data: 0.7805624604225159, 0.5980590581893921
Step 10 | Training Loss: 0.571652 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.775949239730835, 0.5866666436195374
Step 1 | Training Loss: 0.556296 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.7743523716926575, 0.5832911133766174
Step 2 | Training Loss: 0.614986 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.773598313331604, 0.5816877484321594
Step 3 | Training Loss: 0.547522 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.7731103897094727, 0.5804219245910645
Step 4 | Training Loss: 0.556650 | Validation Accuracy: 0.932540
Accuracy on Test data: 0.7726668119430542, 0.5794936418533325
Step 5 | Training Loss: 0.568067 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.7726224064826965, 0.5793249011039734
Step 6 | Training Loss: 0.565965 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.7718683481216431, 0.5777215361595154
Step 7 | Training Loss: 0.569765 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.7711142897605896, 0.5762025117874146
Step 8 | Training Loss: 0.581032 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.7706263065338135, 0.5752742886543274
Step 9 | Training Loss: 0.551982 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.7700940370559692, 0.5742616057395935
Step 10 | Training Loss: 0.538583 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.7692512273788452, 0.5724050402641296
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.677408 | Validation Accuracy: 0.757937
Accuracy on Test data: 0.7114975452423096, 0.46793249249458313
Step 2 | Training Loss: 0.625989 | Validation Accuracy: 0.809524
Accuracy on Test data: 0.757230281829834, 0.550801694393158
Step 3 | Training Loss: 0.616962 | Validation Accuracy: 0.854762
Accuracy on Test data: 0.794313371181488, 0.6179746985435486
Step 4 | Training Loss: 0.603850 | Validation Accuracy: 0.885714
Accuracy on Test data: 0.8149840235710144, 0.6567932367324829
Step 5 | Training Loss: 0.583449 | Validation Accuracy: 0.884524
Accuracy on Test data: 0.8227909803390503, 0.6713080406188965
Step 6 | Training Loss: 0.512971 | Validation Accuracy: 0.902381
Accuracy on Test data: 0.8135202527046204, 0.6524050831794739
Step 7 | Training Loss: 0.511530 | Validation Accuracy: 0.920238
Accuracy on Test data: 0.8105482459068298, 0.6466666460037231
Step 8 | Training Loss: 0.539288 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.7923616170883179, 0.6119831204414368
Step 9 | Training Loss: 0.483647 | Validation Accuracy: 0.926587
Accuracy on Test data: 0.7743523716926575, 0.5776371359825134
Step 10 | Training Loss: 0.500466 | Validation Accuracy: 0.933333
Accuracy on Test data: 0.7773687243461609, 0.5829535722732544
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Accuracy on Test data: 0.7751951813697815, 0.5787341594696045
Step 2 | Training Loss: 0.463331 | Validation Accuracy: 0.929365
Accuracy on Test data: 0.7716909050941467, 0.5719830989837646
Step 3 | Training Loss: 0.500457 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.7721788287162781, 0.5728269815444946
Step 4 | Training Loss: 0.492165 | Validation Accuracy: 0.940873
Accuracy on Test data: 0.771025538444519, 0.5706329345703125
Step 5 | Training Loss: 0.427308 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.7704045176506042, 0.5694514513015747
Step 6 | Training Loss: 0.470360 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.770182728767395, 0.5689451694488525
Step 7 | Training Loss: 0.451619 | Validation Accuracy: 0.941667
Accuracy on Test data: 0.770182728767395, 0.5688607692718506
Step 8 | Training Loss: 0.473216 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.7693843245506287, 0.5672574043273926
Step 9 | Training Loss: 0.455865 | Validation Accuracy: 0.939286
Accuracy on Test data: 0.7689407467842102, 0.5664135217666626
Step 10 | Training Loss: 0.458298 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.7684528231620789, 0.5654852390289307
Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.634514 | Validation Accuracy: 0.690079
Accuracy on Test data: 0.5093151330947876, 0.24312236905097961
Step 2 | Training Loss: 0.628080 | Validation Accuracy: 0.764286
Accuracy on Test data: 0.6037526726722717, 0.2729957699775696
Step 3 | Training Loss: 0.620433 | Validation Accuracy: 0.807143
Accuracy on Test data: 0.6375088691711426, 0.33282700181007385
Step 4 | Training Loss: 0.519709 | Validation Accuracy: 0.868254
Accuracy on Test data: 0.6713094115257263, 0.39485231041908264
Step 5 | Training Loss: 0.559398 | Validation Accuracy: 0.880952
Accuracy on Test data: 0.6900283694267273, 0.4297046363353729
Step 6 | Training Loss: 0.513416 | Validation Accuracy: 0.895635
Accuracy on Test data: 0.7037349343299866, 0.4524894654750824
Step 7 | Training Loss: 0.479462 | Validation Accuracy: 0.913492
Accuracy on Test data: 0.7176188826560974, 0.47476792335510254
Step 8 | Training Loss: 0.507989 | Validation Accuracy: 0.923016
Accuracy on Test data: 0.7328335642814636, 0.5010126829147339
Step 9 | Training Loss: 0.466108 | Validation Accuracy: 0.942064
Accuracy on Test data: 0.7419712543487549, 0.5174683332443237
Step 10 | Training Loss: 0.417791 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.7490684986114502, 0.5292826890945435
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Accuracy on Test data: 0.7492902874946594, 0.5297046303749084
Step 2 | Training Loss: 0.414845 | Validation Accuracy: 0.936508
Accuracy on Test data: 0.7496007680892944, 0.5302109718322754
Step 3 | Training Loss: 0.450315 | Validation Accuracy: 0.945635
Accuracy on Test data: 0.7499556541442871, 0.5307173132896423
Step 4 | Training Loss: 0.427583 | Validation Accuracy: 0.936111
Accuracy on Test data: 0.7502217888832092, 0.5312236547470093
Step 5 | Training Loss: 0.433311 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.7501774430274963, 0.5311392545700073
Step 6 | Training Loss: 0.462555 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.7503548860549927, 0.5313923954963684
Step 7 | Training Loss: 0.474380 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.7505322694778442, 0.5316455960273743
Step 8 | Training Loss: 0.487839 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.7504879236221313, 0.5315611958503723
Step 9 | Training Loss: 0.429149 | Validation Accuracy: 0.945238
Accuracy on Test data: 0.7507097125053406, 0.5319831371307373
Step 10 | Training Loss: 0.421329 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.7506653666496277, 0.5318987369537354
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.701053 | Validation Accuracy: 0.579365
Accuracy on Test data: 0.5544712543487549, 0.47054851055145264
Step 2 | Training Loss: 0.650388 | Validation Accuracy: 0.735317
Accuracy on Test data: 0.6542317271232605, 0.5033755302429199
Step 3 | Training Loss: 0.680797 | Validation Accuracy: 0.780556
Accuracy on Test data: 0.7310149073600769, 0.5305485129356384
Step 4 | Training Loss: 0.660234 | Validation Accuracy: 0.810714
Accuracy on Test data: 0.760645866394043, 0.5602531433105469
Step 5 | Training Loss: 0.590869 | Validation Accuracy: 0.861905
Accuracy on Test data: 0.7802963256835938, 0.5945991277694702
Step 6 | Training Loss: 0.577350 | Validation Accuracy: 0.876984
Accuracy on Test data: 0.779675304889679, 0.5929113626480103
Step 7 | Training Loss: 0.480116 | Validation Accuracy: 0.893651
Accuracy on Test data: 0.7855748534202576, 0.6029536128044128
Step 8 | Training Loss: 0.504290 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.7918736934661865, 0.6135864853858948
Step 9 | Training Loss: 0.469817 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.7968860864639282, 0.6228691935539246
Step 10 | Training Loss: 0.455082 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8018097877502441, 0.6320675015449524
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Accuracy on Test data: 0.8020759224891663, 0.6325738430023193
Step 2 | Training Loss: 0.460734 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.8050035238265991, 0.6381434798240662
Step 3 | Training Loss: 0.473784 | Validation Accuracy: 0.932143
Accuracy on Test data: 0.8062455654144287, 0.6405063271522522
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Accuracy on Test data: 0.8075762987136841, 0.6430379748344421
Step 5 | Training Loss: 0.478669 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8100159764289856, 0.647257387638092
Step 6 | Training Loss: 0.437118 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.8123225569725037, 0.6515612006187439
Step 7 | Training Loss: 0.444263 | Validation Accuracy: 0.932143
Accuracy on Test data: 0.8148509860038757, 0.6563712954521179
Step 8 | Training Loss: 0.436740 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8170244693756104, 0.6605063080787659
Step 9 | Training Loss: 0.434395 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8183552026748657, 0.6631223559379578
Step 10 | Training Loss: 0.443289 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8192867040634155, 0.6647257208824158
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.816600 | Validation Accuracy: 0.560714
Accuracy on Test data: 0.5030163526535034, 0.2107173055410385
Step 2 | Training Loss: 0.701832 | Validation Accuracy: 0.679762
Accuracy on Test data: 0.5955021381378174, 0.2707172930240631
Step 3 | Training Loss: 0.603577 | Validation Accuracy: 0.729365
Accuracy on Test data: 0.6135113835334778, 0.29080167412757874
Step 4 | Training Loss: 0.585662 | Validation Accuracy: 0.759127
Accuracy on Test data: 0.632762610912323, 0.324894517660141
Step 5 | Training Loss: 0.559770 | Validation Accuracy: 0.798016
Accuracy on Test data: 0.6495298147201538, 0.35417720675468445
Step 6 | Training Loss: 0.577556 | Validation Accuracy: 0.838889
Accuracy on Test data: 0.6639460325241089, 0.3783966302871704
Step 7 | Training Loss: 0.551867 | Validation Accuracy: 0.853175
Accuracy on Test data: 0.676233172416687, 0.40067511796951294
Step 8 | Training Loss: 0.474794 | Validation Accuracy: 0.863889
Accuracy on Test data: 0.6908711791038513, 0.4276793301105499
Step 9 | Training Loss: 0.534620 | Validation Accuracy: 0.887698
Accuracy on Test data: 0.7023154497146606, 0.4462447166442871
Step 10 | Training Loss: 0.489927 | Validation Accuracy: 0.879762
Accuracy on Test data: 0.712562084197998, 0.46329113841056824
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Accuracy on Test data: 0.713449239730835, 0.46489450335502625
Step 2 | Training Loss: 0.486050 | Validation Accuracy: 0.874206
Accuracy on Test data: 0.7141146063804626, 0.4659915566444397
Step 3 | Training Loss: 0.451362 | Validation Accuracy: 0.895635
Accuracy on Test data: 0.7156227827072144, 0.4687763750553131
Step 4 | Training Loss: 0.475880 | Validation Accuracy: 0.890873
Accuracy on Test data: 0.7165542840957642, 0.47054851055145264
Step 5 | Training Loss: 0.441494 | Validation Accuracy: 0.886508
Accuracy on Test data: 0.717485785484314, 0.47232067584991455
Step 6 | Training Loss: 0.461842 | Validation Accuracy: 0.891667
Accuracy on Test data: 0.7182842493057251, 0.473839670419693
Step 7 | Training Loss: 0.486917 | Validation Accuracy: 0.888492
Accuracy on Test data: 0.7189496159553528, 0.475021094083786
Step 8 | Training Loss: 0.456529 | Validation Accuracy: 0.896429
Accuracy on Test data: 0.7201029062271118, 0.4772152006626129
Step 9 | Training Loss: 0.466395 | Validation Accuracy: 0.891270
Accuracy on Test data: 0.7210344076156616, 0.47898733615875244
Step 10 | Training Loss: 0.462796 | Validation Accuracy: 0.893254
Accuracy on Test data: 0.7218772172927856, 0.48033756017684937
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.672406 | Validation Accuracy: 0.706349
Accuracy on Test data: 0.7454755306243896, 0.6048945188522339
Step 2 | Training Loss: 0.568802 | Validation Accuracy: 0.818651
Accuracy on Test data: 0.8162704110145569, 0.6673417687416077
Step 3 | Training Loss: 0.581592 | Validation Accuracy: 0.867460
Accuracy on Test data: 0.8311746120452881, 0.6892827153205872
Step 4 | Training Loss: 0.522586 | Validation Accuracy: 0.900000
Accuracy on Test data: 0.8377395272254944, 0.700843870639801
Step 5 | Training Loss: 0.494834 | Validation Accuracy: 0.915476
Accuracy on Test data: 0.8376064300537109, 0.7005907297134399
Step 6 | Training Loss: 0.489196 | Validation Accuracy: 0.919841
Accuracy on Test data: 0.8481192588806152, 0.7188185453414917
Step 7 | Training Loss: 0.462393 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.8506032824516296, 0.7232067584991455
Step 8 | Training Loss: 0.472594 | Validation Accuracy: 0.928175
Accuracy on Test data: 0.8525106310844421, 0.7261603474617004
Step 9 | Training Loss: 0.437431 | Validation Accuracy: 0.939683
Accuracy on Test data: 0.8534865379333496, 0.7263290882110596
Step 10 | Training Loss: 0.463362 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.8521113991737366, 0.7227004170417786
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Accuracy on Test data: 0.8521558046340942, 0.7227004170417786
Step 2 | Training Loss: 0.425381 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.8520670533180237, 0.7224472761154175
Step 3 | Training Loss: 0.426639 | Validation Accuracy: 0.947222
Accuracy on Test data: 0.8518896102905273, 0.7221096754074097
Step 4 | Training Loss: 0.435035 | Validation Accuracy: 0.944841
Accuracy on Test data: 0.8516234755516052, 0.7216033935546875
Step 5 | Training Loss: 0.413669 | Validation Accuracy: 0.945238
Accuracy on Test data: 0.8517122268676758, 0.7216033935546875
Step 6 | Training Loss: 0.416473 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.8514904379844666, 0.7209282517433167
Step 7 | Training Loss: 0.425263 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.8513129949569702, 0.7204219698905945
Step 8 | Training Loss: 0.417076 | Validation Accuracy: 0.955556
Accuracy on Test data: 0.8506476283073425, 0.7190717458724976
Step 9 | Training Loss: 0.394421 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.8500709533691406, 0.7178903222084045
Step 10 | Training Loss: 0.416676 | Validation Accuracy: 0.955159
Accuracy on Test data: 0.8499822616577148, 0.7177215218544006
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.780910 | Validation Accuracy: 0.534921
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.690368 | Validation Accuracy: 0.534127
Accuracy on Test data: 0.4324875771999359, 0.1839662492275238
Step 3 | Training Loss: 0.677957 | Validation Accuracy: 0.657540
Accuracy on Test data: 0.4726756513118744, 0.18751055002212524
Step 4 | Training Loss: 0.645787 | Validation Accuracy: 0.664286
Accuracy on Test data: 0.4795067310333252, 0.19400843977928162
Step 5 | Training Loss: 0.629358 | Validation Accuracy: 0.735714
Accuracy on Test data: 0.5999822616577148, 0.26540085673332214
Step 6 | Training Loss: 0.570299 | Validation Accuracy: 0.784524
Accuracy on Test data: 0.6163502335548401, 0.2935021221637726
Step 7 | Training Loss: 0.554354 | Validation Accuracy: 0.809127
Accuracy on Test data: 0.6512597799301147, 0.3590717315673828
Step 8 | Training Loss: 0.572835 | Validation Accuracy: 0.855952
Accuracy on Test data: 0.6817334890365601, 0.4100421965122223
Step 9 | Training Loss: 0.500140 | Validation Accuracy: 0.869048
Accuracy on Test data: 0.6993435025215149, 0.4410126507282257
Step 10 | Training Loss: 0.480009 | Validation Accuracy: 0.893254
Accuracy on Test data: 0.709945023059845, 0.45898735523223877
Step 1 | Training Loss: 0.439751 | Validation Accuracy: 0.904365
Accuracy on Test data: 0.7108765244483948, 0.46042194962501526
Step 2 | Training Loss: 0.468868 | Validation Accuracy: 0.884524
Accuracy on Test data: 0.7122959494590759, 0.4629535973072052
Step 3 | Training Loss: 0.460023 | Validation Accuracy: 0.901984
Accuracy on Test data: 0.7146469354629517, 0.46708860993385315
Step 4 | Training Loss: 0.477517 | Validation Accuracy: 0.903175
Accuracy on Test data: 0.7166430354118347, 0.4706329107284546
Step 5 | Training Loss: 0.498049 | Validation Accuracy: 0.903175
Accuracy on Test data: 0.7175745368003845, 0.4722362756729126
Step 6 | Training Loss: 0.475751 | Validation Accuracy: 0.903571
Accuracy on Test data: 0.7186834812164307, 0.47417721152305603
Step 7 | Training Loss: 0.464870 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.7200585603713989, 0.47670885920524597
Step 8 | Training Loss: 0.437806 | Validation Accuracy: 0.899603
Accuracy on Test data: 0.7220103144645691, 0.48042193055152893
Step 9 | Training Loss: 0.443514 | Validation Accuracy: 0.914683
Accuracy on Test data: 0.723518431186676, 0.4830379784107208
Step 10 | Training Loss: 0.417529 | Validation Accuracy: 0.910317
Accuracy on Test data: 0.7254258394241333, 0.4864978790283203
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.693131 | Validation Accuracy: 0.525794
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.693013 | Validation Accuracy: 0.547619
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692917 | Validation Accuracy: 0.544444
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.692593 | Validation Accuracy: 0.525794
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.693075 | Validation Accuracy: 0.545635
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.693244 | Validation Accuracy: 0.545238
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692484 | Validation Accuracy: 0.527778
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.692064 | Validation Accuracy: 0.527778
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.692390 | Validation Accuracy: 0.542460
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.691512 | Validation Accuracy: 0.535317
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 1 | Training Loss: 0.693720 | Validation Accuracy: 0.530556
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.692499 | Validation Accuracy: 0.532143
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692906 | Validation Accuracy: 0.539286
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.692904 | Validation Accuracy: 0.541667
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.692377 | Validation Accuracy: 0.548810
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692794 | Validation Accuracy: 0.530556
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692042 | Validation Accuracy: 0.540079
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.692788 | Validation Accuracy: 0.538889
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.692349 | Validation Accuracy: 0.532540
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.693551 | Validation Accuracy: 0.534524
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.674602 | Validation Accuracy: 0.517460
Accuracy on Test data: 0.44175833463668823, 0.22033755481243134
Step 2 | Training Loss: 0.668052 | Validation Accuracy: 0.630159
Accuracy on Test data: 0.4894428551197052, 0.23400843143463135
Step 3 | Training Loss: 0.682673 | Validation Accuracy: 0.682936
Accuracy on Test data: 0.5122870802879333, 0.2643038034439087
Step 4 | Training Loss: 0.700573 | Validation Accuracy: 0.734127
Accuracy on Test data: 0.5390347838401794, 0.3118143379688263
Step 5 | Training Loss: 0.677936 | Validation Accuracy: 0.743651
Accuracy on Test data: 0.5877395272254944, 0.33603376150131226
Step 6 | Training Loss: 0.658254 | Validation Accuracy: 0.793254
Accuracy on Test data: 0.6486870050430298, 0.35940927267074585
Step 7 | Training Loss: 0.678377 | Validation Accuracy: 0.800397
Accuracy on Test data: 0.654675304889679, 0.36928269267082214
Step 8 | Training Loss: 0.672955 | Validation Accuracy: 0.825000
Accuracy on Test data: 0.6629258394241333, 0.3830379843711853
Step 9 | Training Loss: 0.656626 | Validation Accuracy: 0.840873
Accuracy on Test data: 0.6721078753471375, 0.39848101139068604
Step 10 | Training Loss: 0.640856 | Validation Accuracy: 0.844841
Accuracy on Test data: 0.6795156002044678, 0.41071730852127075
Step 1 | Training Loss: 0.630917 | Validation Accuracy: 0.855952
Accuracy on Test data: 0.680580198764801, 0.41232067346572876
Step 2 | Training Loss: 0.618076 | Validation Accuracy: 0.855556
Accuracy on Test data: 0.6818665862083435, 0.41417720913887024
Step 3 | Training Loss: 0.635209 | Validation Accuracy: 0.854365
Accuracy on Test data: 0.6832860112190247, 0.41611814498901367
Step 4 | Training Loss: 0.621957 | Validation Accuracy: 0.847222
Accuracy on Test data: 0.6848828792572021, 0.4184810221195221
Step 5 | Training Loss: 0.649242 | Validation Accuracy: 0.868254
Accuracy on Test data: 0.6862136125564575, 0.42059072852134705
Step 6 | Training Loss: 0.676349 | Validation Accuracy: 0.870635
Accuracy on Test data: 0.687189519405365, 0.4221096932888031
Step 7 | Training Loss: 0.662504 | Validation Accuracy: 0.852381
Accuracy on Test data: 0.6880766749382019, 0.4232911467552185
Step 8 | Training Loss: 0.646080 | Validation Accuracy: 0.864286
Accuracy on Test data: 0.6890968680381775, 0.42497891187667847
Step 9 | Training Loss: 0.629912 | Validation Accuracy: 0.854365
Accuracy on Test data: 0.6899840235710144, 0.4265822768211365
Step 10 | Training Loss: 0.650375 | Validation Accuracy: 0.865873
Accuracy on Test data: 0.691226065158844, 0.4287763833999634
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
Step 1 | Training Loss: 0.725629 | Validation Accuracy: 0.722619
Accuracy on Test data: 0.7485361695289612, 0.6205063462257385
Step 2 | Training Loss: 0.728004 | Validation Accuracy: 0.737698
Accuracy on Test data: 0.7706263065338135, 0.6437974572181702
Step 3 | Training Loss: 0.665736 | Validation Accuracy: 0.777778
Accuracy on Test data: 0.7813608646392822, 0.6504641175270081
Step 4 | Training Loss: 0.675929 | Validation Accuracy: 0.815873
Accuracy on Test data: 0.7920954823493958, 0.6600843667984009
Step 5 | Training Loss: 0.700924 | Validation Accuracy: 0.825000
Accuracy on Test data: 0.801543653011322, 0.6723206639289856
Step 6 | Training Loss: 0.668931 | Validation Accuracy: 0.845635
Accuracy on Test data: 0.8115241527557373, 0.6792405247688293
Step 7 | Training Loss: 0.605888 | Validation Accuracy: 0.864286
Accuracy on Test data: 0.8183995485305786, 0.6809282898902893
Step 8 | Training Loss: 0.620740 | Validation Accuracy: 0.882937
Accuracy on Test data: 0.8232789039611816, 0.6845569610595703
Step 9 | Training Loss: 0.558930 | Validation Accuracy: 0.896032
Accuracy on Test data: 0.8263839483261108, 0.6868354678153992
Step 10 | Training Loss: 0.604543 | Validation Accuracy: 0.907540
Accuracy on Test data: 0.8283800482749939, 0.6886919736862183
Step 1 | Training Loss: 0.610870 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.828646183013916, 0.6890295147895813
Step 2 | Training Loss: 0.621719 | Validation Accuracy: 0.904365
Accuracy on Test data: 0.8288679718971252, 0.6891139149665833
Step 3 | Training Loss: 0.594200 | Validation Accuracy: 0.907937
Accuracy on Test data: 0.8294003009796143, 0.6898733973503113
Step 4 | Training Loss: 0.618861 | Validation Accuracy: 0.905556
Accuracy on Test data: 0.8293559551239014, 0.6896202564239502
Step 5 | Training Loss: 0.584291 | Validation Accuracy: 0.917460
Accuracy on Test data: 0.8295777440071106, 0.6898733973503113
Step 6 | Training Loss: 0.600628 | Validation Accuracy: 0.917460
Accuracy on Test data: 0.8301987051963806, 0.6905485391616821
Step 7 | Training Loss: 0.580113 | Validation Accuracy: 0.914683
Accuracy on Test data: 0.830376148223877, 0.6904641389846802
Step 8 | Training Loss: 0.607300 | Validation Accuracy: 0.912698
Accuracy on Test data: 0.8304204940795898, 0.6901265978813171
Step 9 | Training Loss: 0.608019 | Validation Accuracy: 0.914683
Accuracy on Test data: 0.8309528231620789, 0.6908860802650452
Step 10 | Training Loss: 0.596796 | Validation Accuracy: 0.911508
Accuracy on Test data: 0.8312633037567139, 0.6913080215454102
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.666365 | Validation Accuracy: 0.749206
Accuracy on Test data: 0.6994321942329407, 0.46725738048553467
Step 2 | Training Loss: 0.721750 | Validation Accuracy: 0.805556
Accuracy on Test data: 0.7362934947013855, 0.5205063223838806
Step 3 | Training Loss: 0.656314 | Validation Accuracy: 0.839286
Accuracy on Test data: 0.7583836317062378, 0.5583122372627258
Step 4 | Training Loss: 0.700008 | Validation Accuracy: 0.859524
Accuracy on Test data: 0.7751951813697815, 0.5875105261802673
Step 5 | Training Loss: 0.631244 | Validation Accuracy: 0.888095
Accuracy on Test data: 0.7917405962944031, 0.6166244745254517
Step 6 | Training Loss: 0.639342 | Validation Accuracy: 0.898810
Accuracy on Test data: 0.8046486973762512, 0.6384810209274292
Step 7 | Training Loss: 0.593647 | Validation Accuracy: 0.910317
Accuracy on Test data: 0.8129435777664185, 0.652995765209198
Step 8 | Training Loss: 0.608210 | Validation Accuracy: 0.920238
Accuracy on Test data: 0.818222165107727, 0.6621097326278687
Step 9 | Training Loss: 0.613670 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8333037495613098, 0.6907172799110413
Step 10 | Training Loss: 0.586045 | Validation Accuracy: 0.922222
Accuracy on Test data: 0.843018114566803, 0.7087763547897339
Step 1 | Training Loss: 0.532670 | Validation Accuracy: 0.924206
Accuracy on Test data: 0.8436391353607178, 0.7097046375274658
Step 2 | Training Loss: 0.594499 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8431068062782288, 0.7088607549667358
Step 3 | Training Loss: 0.587000 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.8431511521339417, 0.7089451551437378
Step 4 | Training Loss: 0.561092 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.8433729410171509, 0.7092826962471008
Step 5 | Training Loss: 0.566076 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.8434173464775085, 0.7092826962471008
Step 6 | Training Loss: 0.555511 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8436834812164307, 0.7096202373504639
Step 7 | Training Loss: 0.566734 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8438608646392822, 0.7099577784538269
Step 8 | Training Loss: 0.528194 | Validation Accuracy: 0.926984
Accuracy on Test data: 0.8438608646392822, 0.7099577784538269
Step 9 | Training Loss: 0.557023 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.8441270589828491, 0.7103797197341919
Step 10 | Training Loss: 0.535637 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.844481885433197, 0.7110548615455627
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.650653 | Validation Accuracy: 0.800397
Accuracy on Test data: 0.7495564222335815, 0.595780611038208
Step 2 | Training Loss: 0.608130 | Validation Accuracy: 0.880952
Accuracy on Test data: 0.7938697934150696, 0.6302953362464905
Step 3 | Training Loss: 0.590446 | Validation Accuracy: 0.917460
Accuracy on Test data: 0.803584098815918, 0.6425316333770752
Step 4 | Training Loss: 0.555322 | Validation Accuracy: 0.927381
Accuracy on Test data: 0.7896558046340942, 0.6130801439285278
Step 5 | Training Loss: 0.559482 | Validation Accuracy: 0.944048
Accuracy on Test data: 0.7751064300537109, 0.5841349959373474
Step 6 | Training Loss: 0.539721 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.7791873812675476, 0.5911392569541931
Step 7 | Training Loss: 0.524516 | Validation Accuracy: 0.954365
Accuracy on Test data: 0.7879258394241333, 0.6044725775718689
Step 8 | Training Loss: 0.522994 | Validation Accuracy: 0.949206
Accuracy on Test data: 0.7935149073600769, 0.6130801439285278
Step 9 | Training Loss: 0.463488 | Validation Accuracy: 0.944841
Accuracy on Test data: 0.79551100730896, 0.6150211095809937
Step 10 | Training Loss: 0.474918 | Validation Accuracy: 0.949206
Accuracy on Test data: 0.7957771420478821, 0.6151055097579956
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Accuracy on Test data: 0.7960876226425171, 0.6156961917877197
Step 2 | Training Loss: 0.507862 | Validation Accuracy: 0.950397
Accuracy on Test data: 0.7964868545532227, 0.6164556741714478
Step 3 | Training Loss: 0.465778 | Validation Accuracy: 0.957937
Accuracy on Test data: 0.796974778175354, 0.6173839569091797
Step 4 | Training Loss: 0.481921 | Validation Accuracy: 0.959127
Accuracy on Test data: 0.7971522212028503, 0.6177214980125427
Step 5 | Training Loss: 0.467142 | Validation Accuracy: 0.954365
Accuracy on Test data: 0.7972853183746338, 0.6179746985435486
Step 6 | Training Loss: 0.469813 | Validation Accuracy: 0.951587
Accuracy on Test data: 0.7972853183746338, 0.6179746985435486
Step 7 | Training Loss: 0.447416 | Validation Accuracy: 0.954762
Accuracy on Test data: 0.7976401448249817, 0.6186497807502747
Step 8 | Training Loss: 0.444935 | Validation Accuracy: 0.961905
Accuracy on Test data: 0.7979506850242615, 0.6192405223846436
Step 9 | Training Loss: 0.458315 | Validation Accuracy: 0.953571
Accuracy on Test data: 0.7983942627906799, 0.6200844049453735
Step 10 | Training Loss: 0.439899 | Validation Accuracy: 0.955556
Accuracy on Test data: 0.7988821864128113, 0.6210126876831055
Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.664869 | Validation Accuracy: 0.497222
Accuracy on Test data: 0.4430890679359436, 0.5031223893165588
Step 2 | Training Loss: 0.646337 | Validation Accuracy: 0.781746
Accuracy on Test data: 0.7225425839424133, 0.5286920070648193
Step 3 | Training Loss: 0.581629 | Validation Accuracy: 0.834921
Accuracy on Test data: 0.7565649151802063, 0.550717294216156
Step 4 | Training Loss: 0.533676 | Validation Accuracy: 0.861111
Accuracy on Test data: 0.7666341662406921, 0.5647257566452026
Step 5 | Training Loss: 0.532177 | Validation Accuracy: 0.886905
Accuracy on Test data: 0.7656582593917847, 0.5610970258712769
Step 6 | Training Loss: 0.468242 | Validation Accuracy: 0.915476
Accuracy on Test data: 0.787748396396637, 0.602278470993042
Step 7 | Training Loss: 0.484245 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.7882806658744812, 0.601940929889679
Step 8 | Training Loss: 0.471693 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.7862846255302429, 0.5975527167320251
Step 9 | Training Loss: 0.441798 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.7859297394752502, 0.5960337519645691
Step 10 | Training Loss: 0.444633 | Validation Accuracy: 0.942460
Accuracy on Test data: 0.7836675047874451, 0.5914767980575562
Step 1 | Training Loss: 0.432826 | Validation Accuracy: 0.947222
Accuracy on Test data: 0.783401370048523, 0.5909704566001892
Step 2 | Training Loss: 0.456161 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.7831795811653137, 0.5905485153198242
Step 3 | Training Loss: 0.431300 | Validation Accuracy: 0.947222
Accuracy on Test data: 0.7829577922821045, 0.5901265740394592
Step 4 | Training Loss: 0.451154 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.7826915979385376, 0.5896202325820923
Step 5 | Training Loss: 0.444473 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.7822924256324768, 0.5888607501983643
Step 6 | Training Loss: 0.436841 | Validation Accuracy: 0.948810
Accuracy on Test data: 0.7821149826049805, 0.5885232090950012
Step 7 | Training Loss: 0.430338 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.7818044424057007, 0.5879324674606323
Step 8 | Training Loss: 0.468322 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.7817600965499878, 0.5878481268882751
Step 9 | Training Loss: 0.432195 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.7814939618110657, 0.5873417854309082
Step 10 | Training Loss: 0.402866 | Validation Accuracy: 0.950397
Accuracy on Test data: 0.7811834812164307, 0.5867510437965393
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.589425 | Validation Accuracy: 0.840476
Accuracy on Test data: 0.8049148321151733, 0.6491982936859131
Step 2 | Training Loss: 0.563550 | Validation Accuracy: 0.876190
Accuracy on Test data: 0.8116128444671631, 0.6512235999107361
Step 3 | Training Loss: 0.508408 | Validation Accuracy: 0.901587
Accuracy on Test data: 0.814540445804596, 0.655105471611023
Step 4 | Training Loss: 0.527197 | Validation Accuracy: 0.911508
Accuracy on Test data: 0.8196415901184082, 0.6647257208824158
Step 5 | Training Loss: 0.477479 | Validation Accuracy: 0.916270
Accuracy on Test data: 0.8239886164665222, 0.6724894642829895
Step 6 | Training Loss: 0.469425 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.8234120011329651, 0.6708860993385315
Step 7 | Training Loss: 0.436845 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.8253637552261353, 0.6735020875930786
Step 8 | Training Loss: 0.445295 | Validation Accuracy: 0.950397
Accuracy on Test data: 0.8257185816764832, 0.6734177470207214
Step 9 | Training Loss: 0.429894 | Validation Accuracy: 0.951190
Accuracy on Test data: 0.8243878483772278, 0.6705484986305237
Step 10 | Training Loss: 0.412607 | Validation Accuracy: 0.952778
Accuracy on Test data: 0.8240773677825928, 0.6691983342170715
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Accuracy on Test data: 0.8239442706108093, 0.6689451336860657
Step 2 | Training Loss: 0.407254 | Validation Accuracy: 0.944841
Accuracy on Test data: 0.8239442706108093, 0.6687763929367065
Step 3 | Training Loss: 0.453395 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.8238999247550964, 0.6686919927597046
Step 4 | Training Loss: 0.459912 | Validation Accuracy: 0.952381
Accuracy on Test data: 0.8237224817276001, 0.6683544516563416
Step 5 | Training Loss: 0.401353 | Validation Accuracy: 0.962302
Accuracy on Test data: 0.8236337900161743, 0.6681012511253357
Step 6 | Training Loss: 0.435515 | Validation Accuracy: 0.948413
Accuracy on Test data: 0.8235006928443909, 0.6677637100219727
Step 7 | Training Loss: 0.395880 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.8235450387001038, 0.6677637100219727
Step 8 | Training Loss: 0.434277 | Validation Accuracy: 0.953968
Accuracy on Test data: 0.8235450387001038, 0.6675949096679688
Step 9 | Training Loss: 0.420926 | Validation Accuracy: 0.953968
Accuracy on Test data: 0.823456346988678, 0.6673417687416077
Step 10 | Training Loss: 0.413906 | Validation Accuracy: 0.950794
Accuracy on Test data: 0.8233232498168945, 0.6670886278152466
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.653998 | Validation Accuracy: 0.726984
Accuracy on Test data: 0.7276880741119385, 0.5215190052986145
Step 2 | Training Loss: 0.625685 | Validation Accuracy: 0.765873
Accuracy on Test data: 0.7365596294403076, 0.5217721462249756
Step 3 | Training Loss: 0.573115 | Validation Accuracy: 0.780556
Accuracy on Test data: 0.7529719471931458, 0.548607587814331
Step 4 | Training Loss: 0.559331 | Validation Accuracy: 0.828968
Accuracy on Test data: 0.7681422829627991, 0.5758649706840515
Step 5 | Training Loss: 0.550663 | Validation Accuracy: 0.838492
Accuracy on Test data: 0.7833569645881653, 0.601772129535675
Step 6 | Training Loss: 0.512026 | Validation Accuracy: 0.869841
Accuracy on Test data: 0.7940915822982788, 0.6196624636650085
Step 7 | Training Loss: 0.494505 | Validation Accuracy: 0.882540
Accuracy on Test data: 0.8025638461112976, 0.6349366903305054
Step 8 | Training Loss: 0.508502 | Validation Accuracy: 0.899206
Accuracy on Test data: 0.8111692667007446, 0.6503797173500061
Step 9 | Training Loss: 0.504787 | Validation Accuracy: 0.911508
Accuracy on Test data: 0.8171575665473938, 0.6607595086097717
Step 10 | Training Loss: 0.436321 | Validation Accuracy: 0.929365
Accuracy on Test data: 0.8235006928443909, 0.6713923811912537
Step 1 | Training Loss: 0.482871 | Validation Accuracy: 0.932936
Accuracy on Test data: 0.8253193497657776, 0.6746835708618164
Step 2 | Training Loss: 0.455188 | Validation Accuracy: 0.930556
Accuracy on Test data: 0.8270049691200256, 0.6775527596473694
Step 3 | Training Loss: 0.435345 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.8279364705085754, 0.6791561245918274
Step 4 | Training Loss: 0.438341 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8284687995910645, 0.6800000071525574
Step 5 | Training Loss: 0.426743 | Validation Accuracy: 0.933730
Accuracy on Test data: 0.8290454149246216, 0.6809282898902893
Step 6 | Training Loss: 0.430071 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8294003009796143, 0.6815189719200134
Step 7 | Training Loss: 0.436922 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8299325704574585, 0.6822784543037415
Step 8 | Training Loss: 0.429799 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8305979371070862, 0.6832067370414734
Step 9 | Training Loss: 0.430236 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.8313964009284973, 0.6843038201332092
Step 10 | Training Loss: 0.438966 | Validation Accuracy: 0.933333
Accuracy on Test data: 0.8318843245506287, 0.6848101019859314
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.612803 | Validation Accuracy: 0.754762
Accuracy on Test data: 0.7948012948036194, 0.6987341642379761
Step 2 | Training Loss: 0.580267 | Validation Accuracy: 0.794444
Accuracy on Test data: 0.8097941875457764, 0.7043038010597229
Step 3 | Training Loss: 0.561358 | Validation Accuracy: 0.874603
Accuracy on Test data: 0.839292049407959, 0.7158649563789368
Step 4 | Training Loss: 0.496500 | Validation Accuracy: 0.896825
Accuracy on Test data: 0.8457682728767395, 0.7212658524513245
Step 5 | Training Loss: 0.496553 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.8356547355651855, 0.6999155879020691
Step 6 | Training Loss: 0.454943 | Validation Accuracy: 0.926190
Accuracy on Test data: 0.8326383829116821, 0.6914768218994141
Step 7 | Training Loss: 0.404323 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8317955732345581, 0.6894514560699463
Step 8 | Training Loss: 0.418696 | Validation Accuracy: 0.926984
Accuracy on Test data: 0.8310858607292175, 0.6877636909484863
Step 9 | Training Loss: 0.442707 | Validation Accuracy: 0.928968
Accuracy on Test data: 0.8313519954681396, 0.6870886087417603
Step 10 | Training Loss: 0.446168 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.8309971690177917, 0.6852320432662964
Step 1 | Training Loss: 0.404353 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.8309084177017212, 0.6850633025169373
Step 2 | Training Loss: 0.405492 | Validation Accuracy: 0.928968
Accuracy on Test data: 0.8309528231620789, 0.6849789023399353
Step 3 | Training Loss: 0.455058 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8309528231620789, 0.6848101019859314
Step 4 | Training Loss: 0.404041 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.8308197259902954, 0.6844725608825684
Step 5 | Training Loss: 0.367971 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.8308197259902954, 0.6843881607055664
Step 6 | Training Loss: 0.424454 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.8304648399353027, 0.6837130784988403
Step 7 | Training Loss: 0.431875 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8304204940795898, 0.6832067370414734
Step 8 | Training Loss: 0.414714 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.8303318023681641, 0.6827847957611084
Step 9 | Training Loss: 0.454564 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.8303318023681641, 0.6825316548347473
Step 10 | Training Loss: 0.420728 | Validation Accuracy: 0.932540
Accuracy on Test data: 0.8301543593406677, 0.6819409132003784
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.694126 | Validation Accuracy: 0.455556
Accuracy on Test data: 0.5479063391685486, 0.7900422215461731
Step 2 | Training Loss: 0.632025 | Validation Accuracy: 0.780952
Accuracy on Test data: 0.841864824295044, 0.8167932629585266
Step 3 | Training Loss: 0.608314 | Validation Accuracy: 0.845635
Accuracy on Test data: 0.8438165187835693, 0.7656540274620056
Step 4 | Training Loss: 0.572632 | Validation Accuracy: 0.845238
Accuracy on Test data: 0.851401686668396, 0.7705485224723816
Step 5 | Training Loss: 0.533772 | Validation Accuracy: 0.867857
Accuracy on Test data: 0.8575230836868286, 0.7740928530693054
Step 6 | Training Loss: 0.591408 | Validation Accuracy: 0.920635
Accuracy on Test data: 0.8700762987136841, 0.7729957699775696
Step 7 | Training Loss: 0.526547 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8702093958854675, 0.7629535794258118
Step 8 | Training Loss: 0.491442 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.8631121516227722, 0.74725741147995
Step 9 | Training Loss: 0.450870 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.8561035990715027, 0.7336708903312683
Step 10 | Training Loss: 0.451040 | Validation Accuracy: 0.948413
Accuracy on Test data: 0.8521113991737366, 0.7255696058273315
Step 1 | Training Loss: 0.469236 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.8517122268676758, 0.7248101234436035
Step 2 | Training Loss: 0.462070 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8512242436408997, 0.7238818407058716
Step 3 | Training Loss: 0.449469 | Validation Accuracy: 0.944841
Accuracy on Test data: 0.8506032824516296, 0.7226160168647766
Step 4 | Training Loss: 0.449389 | Validation Accuracy: 0.939683
Accuracy on Test data: 0.8500266075134277, 0.7215189933776855
Step 5 | Training Loss: 0.416672 | Validation Accuracy: 0.950000
Accuracy on Test data: 0.8495386838912964, 0.7205907106399536
Step 6 | Training Loss: 0.463863 | Validation Accuracy: 0.949603
Accuracy on Test data: 0.8492282032966614, 0.7200000286102295
Step 7 | Training Loss: 0.444846 | Validation Accuracy: 0.950397
Accuracy on Test data: 0.8482522964477539, 0.7180590629577637
Step 8 | Training Loss: 0.454912 | Validation Accuracy: 0.952778
Accuracy on Test data: 0.8475869297981262, 0.7167932391166687
Step 9 | Training Loss: 0.453878 | Validation Accuracy: 0.950794
Accuracy on Test data: 0.8466554284095764, 0.7150210738182068
Step 10 | Training Loss: 0.430441 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.8461675047874451, 0.7140928506851196
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.692977 | Validation Accuracy: 0.526587
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.693095 | Validation Accuracy: 0.537302
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692979 | Validation Accuracy: 0.547222
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.692718 | Validation Accuracy: 0.540873
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.692972 | Validation Accuracy: 0.527381
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692877 | Validation Accuracy: 0.528968
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692546 | Validation Accuracy: 0.521429
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.692872 | Validation Accuracy: 0.530556
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.693115 | Validation Accuracy: 0.527778
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.692506 | Validation Accuracy: 0.534524
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 1 | Training Loss: 0.693215 | Validation Accuracy: 0.544841
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.693216 | Validation Accuracy: 0.525000
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692383 | Validation Accuracy: 0.525397
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.693007 | Validation Accuracy: 0.533730
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.692794 | Validation Accuracy: 0.534524
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692898 | Validation Accuracy: 0.521429
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.693004 | Validation Accuracy: 0.544048
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.692893 | Validation Accuracy: 0.530556
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.692671 | Validation Accuracy: 0.530952
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.691890 | Validation Accuracy: 0.538889
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.691931 | Validation Accuracy: 0.734127
Accuracy on Test data: 0.813342809677124, 0.6985654234886169
Step 2 | Training Loss: 0.668223 | Validation Accuracy: 0.773413
Accuracy on Test data: 0.8168026804924011, 0.6777215003967285
Step 3 | Training Loss: 0.659383 | Validation Accuracy: 0.818651
Accuracy on Test data: 0.8191536664962769, 0.6737552881240845
Step 4 | Training Loss: 0.709997 | Validation Accuracy: 0.841270
Accuracy on Test data: 0.8188875317573547, 0.6703797578811646
Step 5 | Training Loss: 0.704000 | Validation Accuracy: 0.846825
Accuracy on Test data: 0.8144960999488831, 0.6606751084327698
Step 6 | Training Loss: 0.643223 | Validation Accuracy: 0.856746
Accuracy on Test data: 0.8156050443649292, 0.6619409322738647
Step 7 | Training Loss: 0.648264 | Validation Accuracy: 0.873016
Accuracy on Test data: 0.8179559707641602, 0.6655696034431458
Step 8 | Training Loss: 0.660275 | Validation Accuracy: 0.882540
Accuracy on Test data: 0.8220369219779968, 0.6727426052093506
Step 9 | Training Loss: 0.628110 | Validation Accuracy: 0.896032
Accuracy on Test data: 0.8214602470397949, 0.6711392402648926
Step 10 | Training Loss: 0.655740 | Validation Accuracy: 0.918254
Accuracy on Test data: 0.819730281829834, 0.6675949096679688
Step 1 | Training Loss: 0.652830 | Validation Accuracy: 0.913492
Accuracy on Test data: 0.8196859359741211, 0.6675105690956116
Step 2 | Training Loss: 0.653694 | Validation Accuracy: 0.920635
Accuracy on Test data: 0.8195528984069824, 0.6671729683876038
Step 3 | Training Loss: 0.635673 | Validation Accuracy: 0.914683
Accuracy on Test data: 0.8192867040634155, 0.6666666865348816
Step 4 | Training Loss: 0.652892 | Validation Accuracy: 0.908333
Accuracy on Test data: 0.8196415901184082, 0.6670042276382446
Step 5 | Training Loss: 0.644060 | Validation Accuracy: 0.903175
Accuracy on Test data: 0.8198633790016174, 0.6670042276382446
Step 6 | Training Loss: 0.680189 | Validation Accuracy: 0.915079
Accuracy on Test data: 0.8198190331459045, 0.6669198274612427
Step 7 | Training Loss: 0.651579 | Validation Accuracy: 0.912698
Accuracy on Test data: 0.8196859359741211, 0.6665822863578796
Step 8 | Training Loss: 0.680889 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.8194641470909119, 0.6659915447235107
Step 9 | Training Loss: 0.627540 | Validation Accuracy: 0.916270
Accuracy on Test data: 0.8195528984069824, 0.6659915447235107
Step 10 | Training Loss: 0.626697 | Validation Accuracy: 0.926984
Accuracy on Test data: 0.8192867040634155, 0.6654852032661438
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
Step 1 | Training Loss: 0.702601 | Validation Accuracy: 0.496825
Accuracy on Test data: 0.5121539831161499, 0.6954430341720581
Step 2 | Training Loss: 0.676910 | Validation Accuracy: 0.644048
Accuracy on Test data: 0.6612846255302429, 0.7364556789398193
Step 3 | Training Loss: 0.721454 | Validation Accuracy: 0.787302
Accuracy on Test data: 0.8196859359741211, 0.7393248677253723
Step 4 | Training Loss: 0.686265 | Validation Accuracy: 0.830952
Accuracy on Test data: 0.8471433520317078, 0.7570464015007019
Step 5 | Training Loss: 0.637322 | Validation Accuracy: 0.863492
Accuracy on Test data: 0.8555713295936584, 0.7592405080795288
Step 6 | Training Loss: 0.581510 | Validation Accuracy: 0.865873
Accuracy on Test data: 0.848207950592041, 0.7313923835754395
Step 7 | Training Loss: 0.608428 | Validation Accuracy: 0.883333
Accuracy on Test data: 0.8499822616577148, 0.7317299842834473
Step 8 | Training Loss: 0.641269 | Validation Accuracy: 0.884524
Accuracy on Test data: 0.849937915802002, 0.7297890186309814
Step 9 | Training Loss: 0.592612 | Validation Accuracy: 0.901984
Accuracy on Test data: 0.8502040505409241, 0.7288607358932495
Step 10 | Training Loss: 0.644354 | Validation Accuracy: 0.889286
Accuracy on Test data: 0.8524662852287292, 0.7318143248558044
Step 1 | Training Loss: 0.619906 | Validation Accuracy: 0.897222
Accuracy on Test data: 0.8523331880569458, 0.7315611839294434
Step 2 | Training Loss: 0.623730 | Validation Accuracy: 0.908730
Accuracy on Test data: 0.8522888422012329, 0.7313923835754395
Step 3 | Training Loss: 0.555214 | Validation Accuracy: 0.886508
Accuracy on Test data: 0.8521558046340942, 0.7311392426490784
Step 4 | Training Loss: 0.597120 | Validation Accuracy: 0.901190
Accuracy on Test data: 0.8523775935173035, 0.7314767837524414
Step 5 | Training Loss: 0.574108 | Validation Accuracy: 0.901190
Accuracy on Test data: 0.8524662852287292, 0.7316455841064453
Step 6 | Training Loss: 0.631343 | Validation Accuracy: 0.900397
Accuracy on Test data: 0.8527324199676514, 0.7318987250328064
Step 7 | Training Loss: 0.586399 | Validation Accuracy: 0.901190
Accuracy on Test data: 0.8526437282562256, 0.7316455841064453
Step 8 | Training Loss: 0.598379 | Validation Accuracy: 0.893254
Accuracy on Test data: 0.8528211712837219, 0.7319831252098083
Step 9 | Training Loss: 0.607378 | Validation Accuracy: 0.901587
Accuracy on Test data: 0.8528211712837219, 0.7318987250328064
Step 10 | Training Loss: 0.575046 | Validation Accuracy: 0.905159
Accuracy on Test data: 0.8527324199676514, 0.7314767837524414
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.717214 | Validation Accuracy: 0.638889
Accuracy on Test data: 0.47564762830734253, 0.19535864889621735
Step 2 | Training Loss: 0.718317 | Validation Accuracy: 0.679762
Accuracy on Test data: 0.5, 0.23721519112586975
Step 3 | Training Loss: 0.660299 | Validation Accuracy: 0.784921
Accuracy on Test data: 0.5591288208961487, 0.3466666638851166
Step 4 | Training Loss: 0.670138 | Validation Accuracy: 0.826190
Accuracy on Test data: 0.6038857102394104, 0.42784810066223145
Step 5 | Training Loss: 0.634420 | Validation Accuracy: 0.854365
Accuracy on Test data: 0.686346709728241, 0.5042194128036499
Step 6 | Training Loss: 0.660137 | Validation Accuracy: 0.897222
Accuracy on Test data: 0.76987224817276, 0.5744304060935974
Step 7 | Training Loss: 0.621017 | Validation Accuracy: 0.910714
Accuracy on Test data: 0.8012775182723999, 0.6306329369544983
Step 8 | Training Loss: 0.623037 | Validation Accuracy: 0.914286
Accuracy on Test data: 0.8227466344833374, 0.6697046160697937
Step 9 | Training Loss: 0.554928 | Validation Accuracy: 0.928175
Accuracy on Test data: 0.8373402953147888, 0.6962025165557861
Step 10 | Training Loss: 0.582059 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.8451029062271118, 0.7122362852096558
Step 1 | Training Loss: 0.556614 | Validation Accuracy: 0.938095
Accuracy on Test data: 0.8455908298492432, 0.7131645679473877
Step 2 | Training Loss: 0.530850 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.8466997742652893, 0.7152742743492126
Step 3 | Training Loss: 0.501216 | Validation Accuracy: 0.933333
Accuracy on Test data: 0.8476312756538391, 0.7169620394706726
Step 4 | Training Loss: 0.582262 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8484740853309631, 0.7184810042381287
Step 5 | Training Loss: 0.521577 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.8492725491523743, 0.7200000286102295
Step 6 | Training Loss: 0.562213 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.849937915802002, 0.7210970520973206
Step 7 | Training Loss: 0.573537 | Validation Accuracy: 0.933730
Accuracy on Test data: 0.8500266075134277, 0.7212658524513245
Step 8 | Training Loss: 0.617855 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8507363200187683, 0.7226160168647766
Step 9 | Training Loss: 0.565426 | Validation Accuracy: 0.930556
Accuracy on Test data: 0.8506919741630554, 0.7224472761154175
Step 10 | Training Loss: 0.557457 | Validation Accuracy: 0.934127
Accuracy on Test data: 0.8510024547576904, 0.7230379581451416
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.686758 | Validation Accuracy: 0.607540
Accuracy on Test data: 0.6889194250106812, 0.7514767646789551
Step 2 | Training Loss: 0.665358 | Validation Accuracy: 0.763492
Accuracy on Test data: 0.8183995485305786, 0.7335020899772644
Step 3 | Training Loss: 0.632740 | Validation Accuracy: 0.853571
Accuracy on Test data: 0.8425301909446716, 0.7399156093597412
Step 4 | Training Loss: 0.590730 | Validation Accuracy: 0.895635
Accuracy on Test data: 0.8431511521339417, 0.7227848172187805
Step 5 | Training Loss: 0.574531 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.8416873812675476, 0.7125738263130188
Step 6 | Training Loss: 0.519842 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.8354772925376892, 0.699240505695343
Step 7 | Training Loss: 0.522926 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.833215057849884, 0.6945147514343262
Step 8 | Training Loss: 0.486926 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.8254967927932739, 0.6791561245918274
Step 9 | Training Loss: 0.508210 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.824609637260437, 0.6770464181900024
Step 10 | Training Loss: 0.457895 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.8247427344322205, 0.6769620180130005
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Accuracy on Test data: 0.8247427344322205, 0.6769620180130005
Step 2 | Training Loss: 0.497946 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8245652914047241, 0.6763713359832764
Step 3 | Training Loss: 0.462751 | Validation Accuracy: 0.938095
Accuracy on Test data: 0.8245652914047241, 0.6763713359832764
Step 4 | Training Loss: 0.480183 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8245652914047241, 0.6760337352752686
Step 5 | Training Loss: 0.482385 | Validation Accuracy: 0.921032
Accuracy on Test data: 0.8246539831161499, 0.6761181354522705
Step 6 | Training Loss: 0.445129 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.8246539831161499, 0.6761181354522705
Step 7 | Training Loss: 0.454202 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8247427344322205, 0.6762025356292725
Step 8 | Training Loss: 0.474418 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.8247870802879333, 0.6761181354522705
Step 9 | Training Loss: 0.481775 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8246983885765076, 0.6759493947029114
Step 10 | Training Loss: 0.462712 | Validation Accuracy: 0.941667
Accuracy on Test data: 0.8248314261436462, 0.6762025356292725
Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.597511 | Validation Accuracy: 0.910714
Accuracy on Test data: 0.7952448725700378, 0.6205063462257385
Step 2 | Training Loss: 0.555913 | Validation Accuracy: 0.907937
Accuracy on Test data: 0.7946681976318359, 0.6181434392929077
Step 3 | Training Loss: 0.511178 | Validation Accuracy: 0.906746
Accuracy on Test data: 0.79551100730896, 0.6193249225616455
Step 4 | Training Loss: 0.468651 | Validation Accuracy: 0.917857
Accuracy on Test data: 0.7931156754493713, 0.6145991683006287
Step 5 | Training Loss: 0.476205 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.7953335642814636, 0.6181434392929077
Step 6 | Training Loss: 0.447017 | Validation Accuracy: 0.936508
Accuracy on Test data: 0.7981281280517578, 0.6232067346572876
Step 7 | Training Loss: 0.470718 | Validation Accuracy: 0.936508
Accuracy on Test data: 0.8005234003067017, 0.6274261474609375
Step 8 | Training Loss: 0.447599 | Validation Accuracy: 0.949206
Accuracy on Test data: 0.8040276765823364, 0.6336708664894104
Step 9 | Training Loss: 0.425799 | Validation Accuracy: 0.955556
Accuracy on Test data: 0.799547553062439, 0.6245569586753845
Step 10 | Training Loss: 0.427697 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.7989708781242371, 0.6232067346572876
Step 1 | Training Loss: 0.431990 | Validation Accuracy: 0.956349
Accuracy on Test data: 0.7991483211517334, 0.6235442757606506
Step 2 | Training Loss: 0.405276 | Validation Accuracy: 0.950397
Accuracy on Test data: 0.7992814183235168, 0.6237130761146545
Step 3 | Training Loss: 0.423262 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.7995032072067261, 0.6239662170410156
Step 4 | Training Loss: 0.376019 | Validation Accuracy: 0.956349
Accuracy on Test data: 0.8000354766845703, 0.6248100996017456
Step 5 | Training Loss: 0.421670 | Validation Accuracy: 0.954762
Accuracy on Test data: 0.8005234003067017, 0.6256539821624756
Step 6 | Training Loss: 0.398255 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.8007895946502686, 0.6259071826934814
Step 7 | Training Loss: 0.403782 | Validation Accuracy: 0.957937
Accuracy on Test data: 0.8009226322174072, 0.6260759234428406
Step 8 | Training Loss: 0.395043 | Validation Accuracy: 0.952381
Accuracy on Test data: 0.8010113835334778, 0.6262447237968445
Step 9 | Training Loss: 0.396767 | Validation Accuracy: 0.953175
Accuracy on Test data: 0.8014993071556091, 0.6270042061805725
Step 10 | Training Loss: 0.391655 | Validation Accuracy: 0.954365
Accuracy on Test data: 0.801854133605957, 0.6275949478149414
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.685276 | Validation Accuracy: 0.692064
Accuracy on Test data: 0.709412693977356, 0.6356962323188782
Step 2 | Training Loss: 0.644687 | Validation Accuracy: 0.754762
Accuracy on Test data: 0.773065984249115, 0.6459915637969971
Step 3 | Training Loss: 0.564244 | Validation Accuracy: 0.777381
Accuracy on Test data: 0.7856192588806152, 0.652995765209198
Step 4 | Training Loss: 0.551196 | Validation Accuracy: 0.866270
Accuracy on Test data: 0.8131210207939148, 0.6854852437973022
Step 5 | Training Loss: 0.488799 | Validation Accuracy: 0.890079
Accuracy on Test data: 0.8348562717437744, 0.7053164839744568
Step 6 | Training Loss: 0.473321 | Validation Accuracy: 0.911111
Accuracy on Test data: 0.8458126187324524, 0.7188185453414917
Step 7 | Training Loss: 0.483861 | Validation Accuracy: 0.918651
Accuracy on Test data: 0.8504701852798462, 0.7230379581451416
Step 8 | Training Loss: 0.450949 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.8368523716926575, 0.6938396692276001
Step 9 | Training Loss: 0.407456 | Validation Accuracy: 0.939683
Accuracy on Test data: 0.8366305828094482, 0.6924050450325012
Step 10 | Training Loss: 0.456510 | Validation Accuracy: 0.948016
Accuracy on Test data: 0.8238112330436707, 0.6675949096679688
Step 1 | Training Loss: 0.427949 | Validation Accuracy: 0.955159
Accuracy on Test data: 0.8233232498168945, 0.6666666865348816
Step 2 | Training Loss: 0.447332 | Validation Accuracy: 0.954365
Accuracy on Test data: 0.8228797316551208, 0.6658228039741516
Step 3 | Training Loss: 0.443942 | Validation Accuracy: 0.945238
Accuracy on Test data: 0.822613537311554, 0.6653164625167847
Step 4 | Training Loss: 0.452127 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.8225691914558411, 0.6650632619857788
Step 5 | Training Loss: 0.442442 | Validation Accuracy: 0.947222
Accuracy on Test data: 0.8223917484283447, 0.6647257208824158
Step 6 | Training Loss: 0.453039 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.8221256136894226, 0.6642194390296936
Step 7 | Training Loss: 0.470756 | Validation Accuracy: 0.948810
Accuracy on Test data: 0.8220369219779968, 0.6640506386756897
Step 8 | Training Loss: 0.416580 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.8211941123008728, 0.6624472737312317
Step 9 | Training Loss: 0.438177 | Validation Accuracy: 0.950000
Accuracy on Test data: 0.8206174373626709, 0.6613501906394958
Step 10 | Training Loss: 0.434558 | Validation Accuracy: 0.950397
Accuracy on Test data: 0.8199077248573303, 0.6600000262260437
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.711239 | Validation Accuracy: 0.657143
Accuracy on Test data: 0.47706708312034607, 0.3231223523616791
Step 2 | Training Loss: 0.668185 | Validation Accuracy: 0.758730
Accuracy on Test data: 0.5452448725700378, 0.3381434679031372
Step 3 | Training Loss: 0.622716 | Validation Accuracy: 0.803571
Accuracy on Test data: 0.5687987804412842, 0.3647257387638092
Step 4 | Training Loss: 0.572492 | Validation Accuracy: 0.841270
Accuracy on Test data: 0.5935060381889343, 0.4035443067550659
Step 5 | Training Loss: 0.582139 | Validation Accuracy: 0.871429
Accuracy on Test data: 0.7048438787460327, 0.4529114067554474
Step 6 | Training Loss: 0.526232 | Validation Accuracy: 0.912302
Accuracy on Test data: 0.7365152835845947, 0.5115611553192139
Step 7 | Training Loss: 0.515628 | Validation Accuracy: 0.914683
Accuracy on Test data: 0.7444109320640564, 0.5250632762908936
Step 8 | Training Loss: 0.473605 | Validation Accuracy: 0.915079
Accuracy on Test data: 0.7569641470909119, 0.5481012463569641
Step 9 | Training Loss: 0.503093 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.7600248456001282, 0.552827000617981
Step 10 | Training Loss: 0.475460 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.7623314261436462, 0.5570464134216309
Step 1 | Training Loss: 0.476315 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.7625532150268555, 0.5573839545249939
Step 2 | Training Loss: 0.480512 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.7629967927932739, 0.5581434369087219
Step 3 | Training Loss: 0.439609 | Validation Accuracy: 0.933730
Accuracy on Test data: 0.7639282941818237, 0.5599156022071838
Step 4 | Training Loss: 0.442043 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.7649042010307312, 0.5617721676826477
Step 5 | Training Loss: 0.444520 | Validation Accuracy: 0.933730
Accuracy on Test data: 0.7654364705085754, 0.5627847909927368
Step 6 | Training Loss: 0.468808 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.7659687995910645, 0.5637130737304688
Step 7 | Training Loss: 0.436801 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.7665897607803345, 0.5646413564682007
Step 8 | Training Loss: 0.426007 | Validation Accuracy: 0.929365
Accuracy on Test data: 0.7672551274299622, 0.5652320384979248
Step 9 | Training Loss: 0.450346 | Validation Accuracy: 0.932936
Accuracy on Test data: 0.7674325704574585, 0.5652320384979248
Step 10 | Training Loss: 0.405150 | Validation Accuracy: 0.926587
Accuracy on Test data: 0.7676987051963806, 0.5657383799552917
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.646812 | Validation Accuracy: 0.618651
Accuracy on Test data: 0.5704400539398193, 0.5921518802642822
Step 2 | Training Loss: 0.627499 | Validation Accuracy: 0.783730
Accuracy on Test data: 0.7158889174461365, 0.6121519207954407
Step 3 | Training Loss: 0.596540 | Validation Accuracy: 0.877778
Accuracy on Test data: 0.7902324199676514, 0.6380590796470642
Step 4 | Training Loss: 0.557724 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.8307753801345825, 0.6924894452095032
Step 5 | Training Loss: 0.509376 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.8409332633018494, 0.7075949311256409
Step 6 | Training Loss: 0.463679 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.8423970937728882, 0.7090295553207397
Step 7 | Training Loss: 0.463332 | Validation Accuracy: 0.942064
Accuracy on Test data: 0.8265613913536072, 0.6773839592933655
Step 8 | Training Loss: 0.444123 | Validation Accuracy: 0.944048
Accuracy on Test data: 0.8050479292869568, 0.6360337734222412
Step 9 | Training Loss: 0.455680 | Validation Accuracy: 0.933730
Accuracy on Test data: 0.7940471768379211, 0.6142616271972656
Step 10 | Training Loss: 0.428842 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.7929826378822327, 0.6124050617218018
Step 1 | Training Loss: 0.392396 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.792938232421875, 0.6123206615447998
Step 2 | Training Loss: 0.436978 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.7927608489990234, 0.6118987202644348
Step 3 | Training Loss: 0.440402 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.7924946546554565, 0.6115611791610718
Step 4 | Training Loss: 0.450673 | Validation Accuracy: 0.946032
Accuracy on Test data: 0.7922728657722473, 0.6108860969543457
Step 5 | Training Loss: 0.445966 | Validation Accuracy: 0.952381
Accuracy on Test data: 0.7922285199165344, 0.6103797554969788
Step 6 | Training Loss: 0.430984 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.7921841740608215, 0.6099578142166138
Step 7 | Training Loss: 0.390841 | Validation Accuracy: 0.951587
Accuracy on Test data: 0.7919623851776123, 0.6094514727592468
Step 8 | Training Loss: 0.456879 | Validation Accuracy: 0.947222
Accuracy on Test data: 0.7916519045829773, 0.6087763905525208
Step 9 | Training Loss: 0.418521 | Validation Accuracy: 0.940873
Accuracy on Test data: 0.7912970185279846, 0.6081012487411499
Step 10 | Training Loss: 0.470465 | Validation Accuracy: 0.951190
Accuracy on Test data: 0.7907647490501404, 0.6069198250770569
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.625234 | Validation Accuracy: 0.765873
Accuracy on Test data: 0.6851490139961243, 0.4228692054748535
Step 2 | Training Loss: 0.616017 | Validation Accuracy: 0.788889
Accuracy on Test data: 0.6930447220802307, 0.4311392307281494
Step 3 | Training Loss: 0.595882 | Validation Accuracy: 0.831349
Accuracy on Test data: 0.7341199517250061, 0.5066666603088379
Step 4 | Training Loss: 0.538641 | Validation Accuracy: 0.853571
Accuracy on Test data: 0.751685619354248, 0.5380590558052063
Step 5 | Training Loss: 0.525605 | Validation Accuracy: 0.884921
Accuracy on Test data: 0.7706263065338135, 0.5715611577033997
Step 6 | Training Loss: 0.482921 | Validation Accuracy: 0.909524
Accuracy on Test data: 0.7838449478149414, 0.5955274105072021
Step 7 | Training Loss: 0.478436 | Validation Accuracy: 0.911111
Accuracy on Test data: 0.7893009185791016, 0.6056540012359619
Step 8 | Training Loss: 0.472196 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.7926720976829529, 0.6114767789840698
Step 9 | Training Loss: 0.471774 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.7899219393730164, 0.605991542339325
Step 10 | Training Loss: 0.449106 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.78974449634552, 0.6036286950111389
Step 1 | Training Loss: 0.422229 | Validation Accuracy: 0.942460
Accuracy on Test data: 0.7897888422012329, 0.6037130951881409
Step 2 | Training Loss: 0.479440 | Validation Accuracy: 0.940873
Accuracy on Test data: 0.790054976940155, 0.6041350364685059
Step 3 | Training Loss: 0.440423 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.7903211712837219, 0.6044725775718689
Step 4 | Training Loss: 0.459038 | Validation Accuracy: 0.936508
Accuracy on Test data: 0.7904985547065735, 0.6044725775718689
Step 5 | Training Loss: 0.451387 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.790587306022644, 0.6044725775718689
Step 6 | Training Loss: 0.424390 | Validation Accuracy: 0.944048
Accuracy on Test data: 0.7905429601669312, 0.604303777217865
Step 7 | Training Loss: 0.437329 | Validation Accuracy: 0.932143
Accuracy on Test data: 0.7905429601669312, 0.604303777217865
Step 8 | Training Loss: 0.425404 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.7908534407615662, 0.6048945188522339
Step 9 | Training Loss: 0.421577 | Validation Accuracy: 0.938095
Accuracy on Test data: 0.7909421324729919, 0.6050633192062378
Step 10 | Training Loss: 0.447294 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.7908534407615662, 0.6048945188522339
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.693194 | Validation Accuracy: 0.519444
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.692996 | Validation Accuracy: 0.531349
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.693222 | Validation Accuracy: 0.552381
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.693443 | Validation Accuracy: 0.528175
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.692930 | Validation Accuracy: 0.535714
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692595 | Validation Accuracy: 0.541270
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692915 | Validation Accuracy: 0.538095
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.693196 | Validation Accuracy: 0.537302
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.692850 | Validation Accuracy: 0.527778
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.692331 | Validation Accuracy: 0.542857
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 1 | Training Loss: 0.691828 | Validation Accuracy: 0.538095
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.692514 | Validation Accuracy: 0.530159
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692609 | Validation Accuracy: 0.534127
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.692604 | Validation Accuracy: 0.525794
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.692804 | Validation Accuracy: 0.559127
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692801 | Validation Accuracy: 0.540476
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692379 | Validation Accuracy: 0.522222
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.693112 | Validation Accuracy: 0.540873
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.692899 | Validation Accuracy: 0.532937
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.692897 | Validation Accuracy: 0.541270
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.711835 | Validation Accuracy: 0.453175
Accuracy on Test data: 0.5666252374649048, 0.8110548257827759
Step 2 | Training Loss: 0.703032 | Validation Accuracy: 0.694048
Accuracy on Test data: 0.8105482459068298, 0.8005063533782959
Step 3 | Training Loss: 0.690341 | Validation Accuracy: 0.729365
Accuracy on Test data: 0.8415099382400513, 0.7953586578369141
Step 4 | Training Loss: 0.631821 | Validation Accuracy: 0.729762
Accuracy on Test data: 0.8477643728256226, 0.796624481678009
Step 5 | Training Loss: 0.654214 | Validation Accuracy: 0.773810
Accuracy on Test data: 0.8566802740097046, 0.797552764415741
Step 6 | Training Loss: 0.632235 | Validation Accuracy: 0.803175
Accuracy on Test data: 0.8562366962432861, 0.7839662432670593
Step 7 | Training Loss: 0.653441 | Validation Accuracy: 0.810317
Accuracy on Test data: 0.8555269837379456, 0.7722362875938416
Step 8 | Training Loss: 0.636940 | Validation Accuracy: 0.811905
Accuracy on Test data: 0.8471433520317078, 0.745147705078125
Step 9 | Training Loss: 0.608553 | Validation Accuracy: 0.873413
Accuracy on Test data: 0.8610717058181763, 0.7609282732009888
Step 10 | Training Loss: 0.612059 | Validation Accuracy: 0.897222
Accuracy on Test data: 0.8607611656188965, 0.752067506313324
Step 1 | Training Loss: 0.599603 | Validation Accuracy: 0.894048
Accuracy on Test data: 0.8612047433853149, 0.7521519064903259
Step 2 | Training Loss: 0.588163 | Validation Accuracy: 0.898016
Accuracy on Test data: 0.8613378405570984, 0.751983106136322
Step 3 | Training Loss: 0.628237 | Validation Accuracy: 0.890476
Accuracy on Test data: 0.8611160516738892, 0.751223623752594
Step 4 | Training Loss: 0.608137 | Validation Accuracy: 0.885714
Accuracy on Test data: 0.8607168197631836, 0.7502109408378601
Step 5 | Training Loss: 0.621982 | Validation Accuracy: 0.893651
Accuracy on Test data: 0.8605393767356873, 0.7497046589851379
Step 6 | Training Loss: 0.609397 | Validation Accuracy: 0.896032
Accuracy on Test data: 0.8606724739074707, 0.7494514584541321
Step 7 | Training Loss: 0.618595 | Validation Accuracy: 0.897619
Accuracy on Test data: 0.8606281280517578, 0.749198317527771
Step 8 | Training Loss: 0.622119 | Validation Accuracy: 0.886508
Accuracy on Test data: 0.8600514531135559, 0.747594952583313
Step 9 | Training Loss: 0.591745 | Validation Accuracy: 0.909524
Accuracy on Test data: 0.8510468602180481, 0.7299578189849854
Step 10 | Training Loss: 0.638768 | Validation Accuracy: 0.896429
Accuracy on Test data: 0.8484740853309631, 0.7246413230895996
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
Step 1 | Training Loss: 0.675512 | Validation Accuracy: 0.714286
Accuracy on Test data: 0.7251153588294983, 0.6199156045913696
Step 2 | Training Loss: 0.713261 | Validation Accuracy: 0.794841
Accuracy on Test data: 0.7733765244483948, 0.6345991492271423
Step 3 | Training Loss: 0.658268 | Validation Accuracy: 0.807936
Accuracy on Test data: 0.7841997742652893, 0.6349366903305054
Step 4 | Training Loss: 0.687683 | Validation Accuracy: 0.832143
Accuracy on Test data: 0.7933818101882935, 0.6367932558059692
Step 5 | Training Loss: 0.613650 | Validation Accuracy: 0.844841
Accuracy on Test data: 0.7933374643325806, 0.6299577951431274
Step 6 | Training Loss: 0.610066 | Validation Accuracy: 0.851190
Accuracy on Test data: 0.7989265322685242, 0.6378058791160583
Step 7 | Training Loss: 0.591063 | Validation Accuracy: 0.841270
Accuracy on Test data: 0.8025195002555847, 0.6430379748344421
Step 8 | Training Loss: 0.585287 | Validation Accuracy: 0.864683
Accuracy on Test data: 0.8057132959365845, 0.647257387638092
Step 9 | Training Loss: 0.593968 | Validation Accuracy: 0.873810
Accuracy on Test data: 0.8095280528068542, 0.6524050831794739
Step 10 | Training Loss: 0.569856 | Validation Accuracy: 0.883730
Accuracy on Test data: 0.8138307332992554, 0.6600000262260437
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Accuracy on Test data: 0.8141412138938904, 0.6605063080787659
Step 2 | Training Loss: 0.595880 | Validation Accuracy: 0.892063
Accuracy on Test data: 0.8144074082374573, 0.6608439087867737
Step 3 | Training Loss: 0.585826 | Validation Accuracy: 0.889683
Accuracy on Test data: 0.8144960999488831, 0.6609282493591309
Step 4 | Training Loss: 0.564447 | Validation Accuracy: 0.887698
Accuracy on Test data: 0.8147622346878052, 0.6612658500671387
Step 5 | Training Loss: 0.573700 | Validation Accuracy: 0.885317
Accuracy on Test data: 0.8149840235710144, 0.6616877913475037
Step 6 | Training Loss: 0.541798 | Validation Accuracy: 0.889683
Accuracy on Test data: 0.8153389096260071, 0.6621097326278687
Step 7 | Training Loss: 0.585719 | Validation Accuracy: 0.883730
Accuracy on Test data: 0.8157824873924255, 0.6628692150115967
Step 8 | Training Loss: 0.551881 | Validation Accuracy: 0.888889
Accuracy on Test data: 0.8158711791038513, 0.6630379557609558
Step 9 | Training Loss: 0.582297 | Validation Accuracy: 0.882143
Accuracy on Test data: 0.8159599304199219, 0.6630379557609558
Step 10 | Training Loss: 0.570393 | Validation Accuracy: 0.877381
Accuracy on Test data: 0.8159599304199219, 0.6629536151885986
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.678088 | Validation Accuracy: 0.604762
Accuracy on Test data: 0.6869677305221558, 0.7235442996025085
Step 2 | Training Loss: 0.657782 | Validation Accuracy: 0.778175
Accuracy on Test data: 0.8247427344322205, 0.7498733997344971
Step 3 | Training Loss: 0.664318 | Validation Accuracy: 0.803968
Accuracy on Test data: 0.844171404838562, 0.7686076164245605
Step 4 | Training Loss: 0.590671 | Validation Accuracy: 0.835714
Accuracy on Test data: 0.8435947299003601, 0.7594936490058899
Step 5 | Training Loss: 0.585796 | Validation Accuracy: 0.854762
Accuracy on Test data: 0.8375177383422852, 0.7303797602653503
Step 6 | Training Loss: 0.577828 | Validation Accuracy: 0.892063
Accuracy on Test data: 0.8422196507453918, 0.7255696058273315
Step 7 | Training Loss: 0.546672 | Validation Accuracy: 0.906349
Accuracy on Test data: 0.842175304889679, 0.7194936871528625
Step 8 | Training Loss: 0.551687 | Validation Accuracy: 0.918651
Accuracy on Test data: 0.8404896855354309, 0.7118987441062927
Step 9 | Training Loss: 0.518157 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.8369410634040833, 0.7019409537315369
Step 10 | Training Loss: 0.522850 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.8301987051963806, 0.6886075735092163
Step 1 | Training Loss: 0.504923 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8299325704574585, 0.6879324913024902
Step 2 | Training Loss: 0.558597 | Validation Accuracy: 0.921032
Accuracy on Test data: 0.8298882246017456, 0.6878480911254883
Step 3 | Training Loss: 0.569669 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8296664357185364, 0.6874261498451233
Step 4 | Training Loss: 0.526993 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.8290010690689087, 0.6859915852546692
Step 5 | Training Loss: 0.559182 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.8289567232131958, 0.6858227849006653
Step 6 | Training Loss: 0.517693 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.828646183013916, 0.6852320432662964
Step 7 | Training Loss: 0.510088 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.8281582593917847, 0.6842194199562073
Step 8 | Training Loss: 0.552179 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.8279364705085754, 0.6837974786758423
Step 9 | Training Loss: 0.494122 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.8276703357696533, 0.6832911372184753
Step 10 | Training Loss: 0.566281 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.8273154497146606, 0.6825316548347473
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.725356 | Validation Accuracy: 0.722619
Accuracy on Test data: 0.7666341662406921, 0.8214346170425415
Step 2 | Training Loss: 0.667352 | Validation Accuracy: 0.857937
Accuracy on Test data: 0.8697658181190491, 0.797130823135376
Step 3 | Training Loss: 0.643155 | Validation Accuracy: 0.896429
Accuracy on Test data: 0.859474778175354, 0.7669198513031006
Step 4 | Training Loss: 0.588855 | Validation Accuracy: 0.908730
Accuracy on Test data: 0.8854240775108337, 0.8005906939506531
Step 5 | Training Loss: 0.545068 | Validation Accuracy: 0.911111
Accuracy on Test data: 0.8841820359230042, 0.7913923859596252
Step 6 | Training Loss: 0.559044 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.873846709728241, 0.7704641222953796
Step 7 | Training Loss: 0.499997 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.8649308085441589, 0.752826988697052
Step 8 | Training Loss: 0.480775 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.8573012948036194, 0.7371308207511902
Step 9 | Training Loss: 0.520776 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8545954823493958, 0.7315611839294434
Step 10 | Training Loss: 0.475770 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8511798977851868, 0.7244725823402405
Step 1 | Training Loss: 0.468499 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.8511798977851868, 0.7244725823402405
Step 2 | Training Loss: 0.437161 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8504701852798462, 0.7231223583221436
Step 3 | Training Loss: 0.464455 | Validation Accuracy: 0.923016
Accuracy on Test data: 0.8503814935684204, 0.7228692173957825
Step 4 | Training Loss: 0.463175 | Validation Accuracy: 0.932143
Accuracy on Test data: 0.8501597046852112, 0.7224472761154175
Step 5 | Training Loss: 0.451576 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.8498048186302185, 0.7217721343040466
Step 6 | Training Loss: 0.468416 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8494943380355835, 0.7211814522743225
Step 7 | Training Loss: 0.443862 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.849050760269165, 0.7203375697135925
Step 8 | Training Loss: 0.507671 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.8488733172416687, 0.7200000286102295
Step 9 | Training Loss: 0.464983 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.8485628366470337, 0.7193248867988586
Step 10 | Training Loss: 0.437347 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.8483410477638245, 0.7189029455184937
Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.597483 | Validation Accuracy: 0.844444
Accuracy on Test data: 0.8098828792572021, 0.6648945212364197
Step 2 | Training Loss: 0.541182 | Validation Accuracy: 0.868651
Accuracy on Test data: 0.8223474025726318, 0.6800844073295593
Step 3 | Training Loss: 0.533863 | Validation Accuracy: 0.900000
Accuracy on Test data: 0.8332594037055969, 0.6953586339950562
Step 4 | Training Loss: 0.481789 | Validation Accuracy: 0.909921
Accuracy on Test data: 0.83525550365448, 0.696793258190155
Step 5 | Training Loss: 0.497574 | Validation Accuracy: 0.910714
Accuracy on Test data: 0.8270049691200256, 0.6800844073295593
Step 6 | Training Loss: 0.464508 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.822613537311554, 0.6715611815452576
Step 7 | Training Loss: 0.434082 | Validation Accuracy: 0.932936
Accuracy on Test data: 0.8201295137405396, 0.6656540036201477
Step 8 | Training Loss: 0.453369 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.8171132206916809, 0.6597468256950378
Step 9 | Training Loss: 0.434051 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.8142743110656738, 0.6543459892272949
Step 10 | Training Loss: 0.415164 | Validation Accuracy: 0.942460
Accuracy on Test data: 0.8111692667007446, 0.648185670375824
Step 1 | Training Loss: 0.453860 | Validation Accuracy: 0.948810
Accuracy on Test data: 0.8109918236732483, 0.6478481292724609
Step 2 | Training Loss: 0.447004 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.8107700347900391, 0.647426187992096
Step 3 | Training Loss: 0.420165 | Validation Accuracy: 0.943651
Accuracy on Test data: 0.810459554195404, 0.646835446357727
Step 4 | Training Loss: 0.441780 | Validation Accuracy: 0.945635
Accuracy on Test data: 0.8101046681404114, 0.646160364151001
Step 5 | Training Loss: 0.414090 | Validation Accuracy: 0.956349
Accuracy on Test data: 0.8097941875457764, 0.6454852223396301
Step 6 | Training Loss: 0.429659 | Validation Accuracy: 0.950794
Accuracy on Test data: 0.8096610903739929, 0.6451476812362671
Step 7 | Training Loss: 0.435729 | Validation Accuracy: 0.949603
Accuracy on Test data: 0.8089513778686523, 0.6437974572181702
Step 8 | Training Loss: 0.405102 | Validation Accuracy: 0.949603
Accuracy on Test data: 0.8087295889854431, 0.6432911157608032
Step 9 | Training Loss: 0.416760 | Validation Accuracy: 0.948810
Accuracy on Test data: 0.8086408972740173, 0.6429535746574402
Step 10 | Training Loss: 0.414547 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.8087295889854431, 0.6428691744804382
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.617006 | Validation Accuracy: 0.774603
Accuracy on Test data: 0.7382451891899109, 0.5636286735534668
Step 2 | Training Loss: 0.607943 | Validation Accuracy: 0.855159
Accuracy on Test data: 0.7734208703041077, 0.5864979028701782
Step 3 | Training Loss: 0.552410 | Validation Accuracy: 0.890079
Accuracy on Test data: 0.7877040505409241, 0.6090295314788818
Step 4 | Training Loss: 0.504479 | Validation Accuracy: 0.916270
Accuracy on Test data: 0.7737313508987427, 0.5799155831336975
Step 5 | Training Loss: 0.519247 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.7559882998466492, 0.543375551700592
Step 6 | Training Loss: 0.495744 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.7578069567680359, 0.5452320575714111
Step 7 | Training Loss: 0.437229 | Validation Accuracy: 0.949603
Accuracy on Test data: 0.7610450387001038, 0.549957811832428
Step 8 | Training Loss: 0.455807 | Validation Accuracy: 0.955952
Accuracy on Test data: 0.7619765996932983, 0.551223635673523
Step 9 | Training Loss: 0.417626 | Validation Accuracy: 0.960317
Accuracy on Test data: 0.7688076496124268, 0.5632067322731018
Step 10 | Training Loss: 0.433366 | Validation Accuracy: 0.956349
Accuracy on Test data: 0.7717796564102173, 0.5685232281684875
Step 1 | Training Loss: 0.446512 | Validation Accuracy: 0.960317
Accuracy on Test data: 0.7718683481216431, 0.5686919689178467
Step 2 | Training Loss: 0.441959 | Validation Accuracy: 0.961508
Accuracy on Test data: 0.7720457911491394, 0.5688607692718506
Step 3 | Training Loss: 0.457564 | Validation Accuracy: 0.959921
Accuracy on Test data: 0.7722675800323486, 0.5691983103752136
Step 4 | Training Loss: 0.408241 | Validation Accuracy: 0.959127
Accuracy on Test data: 0.7723562717437744, 0.5693671107292175
Step 5 | Training Loss: 0.410523 | Validation Accuracy: 0.963095
Accuracy on Test data: 0.7725337147712708, 0.5697046518325806
Step 6 | Training Loss: 0.421309 | Validation Accuracy: 0.961111
Accuracy on Test data: 0.7727998495101929, 0.5702109932899475
Step 7 | Training Loss: 0.412625 | Validation Accuracy: 0.957937
Accuracy on Test data: 0.7729772925376892, 0.5705485343933105
Step 8 | Training Loss: 0.429061 | Validation Accuracy: 0.964286
Accuracy on Test data: 0.7731990814208984, 0.5709704756736755
Step 9 | Training Loss: 0.422732 | Validation Accuracy: 0.964286
Accuracy on Test data: 0.7732434272766113, 0.5710548758506775
Step 10 | Training Loss: 0.401546 | Validation Accuracy: 0.968254
Accuracy on Test data: 0.7732877731323242, 0.5711392164230347
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.658309 | Validation Accuracy: 0.735714
Accuracy on Test data: 0.5419623851776123, 0.3677637279033661
Step 2 | Training Loss: 0.594321 | Validation Accuracy: 0.802778
Accuracy on Test data: 0.5953690409660339, 0.4212658107280731
Step 3 | Training Loss: 0.553387 | Validation Accuracy: 0.832540
Accuracy on Test data: 0.6125354766845703, 0.4359493553638458
Step 4 | Training Loss: 0.570066 | Validation Accuracy: 0.885714
Accuracy on Test data: 0.7151792049407959, 0.4710548520088196
Step 5 | Training Loss: 0.517392 | Validation Accuracy: 0.912302
Accuracy on Test data: 0.7519960999488831, 0.5393248796463013
Step 6 | Training Loss: 0.527377 | Validation Accuracy: 0.909524
Accuracy on Test data: 0.7570972442626953, 0.5477637052536011
Step 7 | Training Loss: 0.445396 | Validation Accuracy: 0.933730
Accuracy on Test data: 0.7598917484283447, 0.552405059337616
Step 8 | Training Loss: 0.474668 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.7604684233665466, 0.553080141544342
Step 9 | Training Loss: 0.441159 | Validation Accuracy: 0.939286
Accuracy on Test data: 0.7629081010818481, 0.5570464134216309
Step 10 | Training Loss: 0.451910 | Validation Accuracy: 0.944048
Accuracy on Test data: 0.7672551274299622, 0.5639662742614746
Step 1 | Training Loss: 0.444735 | Validation Accuracy: 0.952381
Accuracy on Test data: 0.7684528231620789, 0.5661603212356567
Step 2 | Training Loss: 0.420754 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.769029438495636, 0.5672574043273926
Step 3 | Training Loss: 0.460344 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.7689407467842102, 0.5670886039733887
Step 4 | Training Loss: 0.453697 | Validation Accuracy: 0.942064
Accuracy on Test data: 0.768718957901001, 0.5666666626930237
Step 5 | Training Loss: 0.434750 | Validation Accuracy: 0.950000
Accuracy on Test data: 0.7685858607292175, 0.5663291215896606
Step 6 | Training Loss: 0.411500 | Validation Accuracy: 0.949603
Accuracy on Test data: 0.7685858607292175, 0.5663291215896606
Step 7 | Training Loss: 0.391820 | Validation Accuracy: 0.948810
Accuracy on Test data: 0.7686302065849304, 0.5664135217666626
Step 8 | Training Loss: 0.440449 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.7688076496124268, 0.5667510628700256
Step 9 | Training Loss: 0.443733 | Validation Accuracy: 0.946032
Accuracy on Test data: 0.769029438495636, 0.5671730041503906
Step 10 | Training Loss: 0.427463 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.7689407467842102, 0.5670042037963867
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.690714 | Validation Accuracy: 0.714683
Accuracy on Test data: 0.7558108568191528, 0.6773839592933655
Step 2 | Training Loss: 0.603602 | Validation Accuracy: 0.815476
Accuracy on Test data: 0.8101490139961243, 0.7131645679473877
Step 3 | Training Loss: 0.573154 | Validation Accuracy: 0.863095
Accuracy on Test data: 0.8353886008262634, 0.7227848172187805
Step 4 | Training Loss: 0.585312 | Validation Accuracy: 0.875000
Accuracy on Test data: 0.8494499921798706, 0.7340928316116333
Step 5 | Training Loss: 0.476392 | Validation Accuracy: 0.889286
Accuracy on Test data: 0.8524219393730164, 0.7327426075935364
Step 6 | Training Loss: 0.501306 | Validation Accuracy: 0.905556
Accuracy on Test data: 0.8573012948036194, 0.7372995615005493
Step 7 | Training Loss: 0.532143 | Validation Accuracy: 0.914286
Accuracy on Test data: 0.8704311847686768, 0.7606751322746277
Step 8 | Training Loss: 0.439931 | Validation Accuracy: 0.912302
Accuracy on Test data: 0.8732700347900391, 0.7645569443702698
Step 9 | Training Loss: 0.459460 | Validation Accuracy: 0.930556
Accuracy on Test data: 0.8602288961410522, 0.7386497855186462
Step 10 | Training Loss: 0.441300 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.842485785484314, 0.7040506601333618
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Accuracy on Test data: 0.841598629951477, 0.7023628950119019
Step 2 | Training Loss: 0.441843 | Validation Accuracy: 0.936508
Accuracy on Test data: 0.8408445715904236, 0.700928270816803
Step 3 | Training Loss: 0.454313 | Validation Accuracy: 0.936111
Accuracy on Test data: 0.8401792049407959, 0.699578046798706
Step 4 | Training Loss: 0.427321 | Validation Accuracy: 0.939683
Accuracy on Test data: 0.838981568813324, 0.697299599647522
Step 5 | Training Loss: 0.424375 | Validation Accuracy: 0.936508
Accuracy on Test data: 0.8384048938751221, 0.6962025165557861
Step 6 | Training Loss: 0.463034 | Validation Accuracy: 0.932540
Accuracy on Test data: 0.8374290466308594, 0.694346010684967
Step 7 | Training Loss: 0.434071 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.8367636799812317, 0.6930801868438721
Step 8 | Training Loss: 0.425761 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8364531397819519, 0.6924050450325012
Step 9 | Training Loss: 0.410511 | Validation Accuracy: 0.942064
Accuracy on Test data: 0.8359208703041077, 0.6913924217224121
Step 10 | Training Loss: 0.392254 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.8354329466819763, 0.6903797388076782
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.643037 | Validation Accuracy: 0.684127
Accuracy on Test data: 0.5672019124031067, 0.37763711810112
Step 2 | Training Loss: 0.670753 | Validation Accuracy: 0.738889
Accuracy on Test data: 0.6243789792060852, 0.39822784066200256
Step 3 | Training Loss: 0.586194 | Validation Accuracy: 0.781349
Accuracy on Test data: 0.6931777596473694, 0.4313080310821533
Step 4 | Training Loss: 0.577397 | Validation Accuracy: 0.811111
Accuracy on Test data: 0.7111426591873169, 0.46430379152297974
Step 5 | Training Loss: 0.543930 | Validation Accuracy: 0.835714
Accuracy on Test data: 0.7453867793083191, 0.5283544063568115
Step 6 | Training Loss: 0.478987 | Validation Accuracy: 0.869048
Accuracy on Test data: 0.7558552026748657, 0.546751081943512
Step 7 | Training Loss: 0.463547 | Validation Accuracy: 0.909127
Accuracy on Test data: 0.7758605480194092, 0.5818565487861633
Step 8 | Training Loss: 0.443105 | Validation Accuracy: 0.906746
Accuracy on Test data: 0.7815826535224915, 0.5918143391609192
Step 9 | Training Loss: 0.444435 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.789434015750885, 0.6065822839736938
Step 10 | Training Loss: 0.439014 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8097941875457764, 0.6438818573951721
Step 1 | Training Loss: 0.460896 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.8101934194564819, 0.6446413397789001
Step 2 | Training Loss: 0.420504 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.8107700347900391, 0.6454852223396301
Step 3 | Training Loss: 0.441159 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8114797472953796, 0.646497905254364
Step 4 | Training Loss: 0.458317 | Validation Accuracy: 0.948810
Accuracy on Test data: 0.8115684986114502, 0.646582305431366
Step 5 | Training Loss: 0.455393 | Validation Accuracy: 0.941667
Accuracy on Test data: 0.8123669028282166, 0.6478481292724609
Step 6 | Training Loss: 0.447992 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8130766749382019, 0.64886075258255
Step 7 | Training Loss: 0.425109 | Validation Accuracy: 0.948016
Accuracy on Test data: 0.8136089444160461, 0.64970463514328
Step 8 | Training Loss: 0.436681 | Validation Accuracy: 0.939286
Accuracy on Test data: 0.8140968680381775, 0.6504641175270081
Step 9 | Training Loss: 0.457797 | Validation Accuracy: 0.945238
Accuracy on Test data: 0.8142743110656738, 0.6507173180580139
Step 10 | Training Loss: 0.457768 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.8146291971206665, 0.6512235999107361
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.693343 | Validation Accuracy: 0.599603
Accuracy on Test data: 0.4595457911491394, 0.23383966088294983
Step 2 | Training Loss: 0.690998 | Validation Accuracy: 0.657143
Accuracy on Test data: 0.4950762987136841, 0.29924049973487854
Step 3 | Training Loss: 0.685526 | Validation Accuracy: 0.755556
Accuracy on Test data: 0.5516323447227478, 0.3321518898010254
Step 4 | Training Loss: 0.692359 | Validation Accuracy: 0.765079
Accuracy on Test data: 0.5843240022659302, 0.36303797364234924
Step 5 | Training Loss: 0.690848 | Validation Accuracy: 0.808730
Accuracy on Test data: 0.6439850926399231, 0.40042194724082947
Step 6 | Training Loss: 0.679884 | Validation Accuracy: 0.835317
Accuracy on Test data: 0.6851934194564819, 0.42219409346580505
Step 7 | Training Loss: 0.680988 | Validation Accuracy: 0.851587
Accuracy on Test data: 0.6922906041145325, 0.43426159024238586
Step 8 | Training Loss: 0.677236 | Validation Accuracy: 0.881349
Accuracy on Test data: 0.7076383829116821, 0.46270042657852173
Step 9 | Training Loss: 0.678792 | Validation Accuracy: 0.877778
Accuracy on Test data: 0.7193488478660583, 0.4840506315231323
Step 10 | Training Loss: 0.672187 | Validation Accuracy: 0.891270
Accuracy on Test data: 0.7306156754493713, 0.5029535889625549
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Accuracy on Test data: 0.7313697934150696, 0.5043882131576538
Step 2 | Training Loss: 0.668381 | Validation Accuracy: 0.895238
Accuracy on Test data: 0.7327004671096802, 0.5067510604858398
Step 3 | Training Loss: 0.668265 | Validation Accuracy: 0.894841
Accuracy on Test data: 0.7335432767868042, 0.508185625076294
Step 4 | Training Loss: 0.669761 | Validation Accuracy: 0.891270
Accuracy on Test data: 0.7345191836357117, 0.5097046494483948
Step 5 | Training Loss: 0.672139 | Validation Accuracy: 0.893651
Accuracy on Test data: 0.7354063391685486, 0.5111392140388489
Step 6 | Training Loss: 0.653941 | Validation Accuracy: 0.893651
Accuracy on Test data: 0.737047553062439, 0.5140084624290466
Step 7 | Training Loss: 0.666023 | Validation Accuracy: 0.903175
Accuracy on Test data: 0.7382451891899109, 0.5161181688308716
Step 8 | Training Loss: 0.675088 | Validation Accuracy: 0.897619
Accuracy on Test data: 0.7395315766334534, 0.5183966159820557
Step 9 | Training Loss: 0.673380 | Validation Accuracy: 0.903175
Accuracy on Test data: 0.7405074238777161, 0.5202531814575195
Step 10 | Training Loss: 0.683343 | Validation Accuracy: 0.902381
Accuracy on Test data: 0.7415720224380493, 0.5221096873283386
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.709006 | Validation Accuracy: 0.734524
Accuracy on Test data: 0.7374467849731445, 0.6279324889183044
Step 2 | Training Loss: 0.660652 | Validation Accuracy: 0.794444
Accuracy on Test data: 0.7717796564102173, 0.6394093036651611
Step 3 | Training Loss: 0.659662 | Validation Accuracy: 0.809921
Accuracy on Test data: 0.777102530002594, 0.6285232305526733
Step 4 | Training Loss: 0.640532 | Validation Accuracy: 0.846429
Accuracy on Test data: 0.785397469997406, 0.6286075711250305
Step 5 | Training Loss: 0.632545 | Validation Accuracy: 0.851190
Accuracy on Test data: 0.7946681976318359, 0.6407594680786133
Step 6 | Training Loss: 0.655284 | Validation Accuracy: 0.872619
Accuracy on Test data: 0.8010113835334778, 0.6500421762466431
Step 7 | Training Loss: 0.627954 | Validation Accuracy: 0.895635
Accuracy on Test data: 0.8076649904251099, 0.6575527191162109
Step 8 | Training Loss: 0.605021 | Validation Accuracy: 0.902778
Accuracy on Test data: 0.8152501583099365, 0.6638818383216858
Step 9 | Training Loss: 0.607644 | Validation Accuracy: 0.923016
Accuracy on Test data: 0.8200851678848267, 0.6686075925827026
Step 10 | Training Loss: 0.602791 | Validation Accuracy: 0.920635
Accuracy on Test data: 0.8235006928443909, 0.6725738644599915
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Accuracy on Test data: 0.8238555788993835, 0.6731645464897156
Step 2 | Training Loss: 0.618814 | Validation Accuracy: 0.921032
Accuracy on Test data: 0.8243878483772278, 0.6740928292274475
Step 3 | Training Loss: 0.587425 | Validation Accuracy: 0.922222
Accuracy on Test data: 0.8245652914047241, 0.6744303703308105
Step 4 | Training Loss: 0.578001 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.8248314261436462, 0.6748523116111755
Step 5 | Training Loss: 0.601311 | Validation Accuracy: 0.922222
Accuracy on Test data: 0.8250975608825684, 0.6753586530685425
Step 6 | Training Loss: 0.600273 | Validation Accuracy: 0.917857
Accuracy on Test data: 0.8250975608825684, 0.6754430532455444
Step 7 | Training Loss: 0.591688 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8250975608825684, 0.6754430532455444
Step 8 | Training Loss: 0.611174 | Validation Accuracy: 0.919841
Accuracy on Test data: 0.8253193497657776, 0.6757805943489075
Step 9 | Training Loss: 0.580932 | Validation Accuracy: 0.927381
Accuracy on Test data: 0.8254081010818481, 0.6759493947029114
Step 10 | Training Loss: 0.622751 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.8253637552261353, 0.6758649945259094
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
Step 1 | Training Loss: 0.676507 | Validation Accuracy: 0.455159
Accuracy on Test data: 0.5344659090042114, 0.7489451766014099
Step 2 | Training Loss: 0.701306 | Validation Accuracy: 0.602778
Accuracy on Test data: 0.6641234755516052, 0.7371308207511902
Step 3 | Training Loss: 0.666532 | Validation Accuracy: 0.679762
Accuracy on Test data: 0.7548350095748901, 0.7457383871078491
Step 4 | Training Loss: 0.699594 | Validation Accuracy: 0.761508
Accuracy on Test data: 0.8166696429252625, 0.7270886301994324
Step 5 | Training Loss: 0.647242 | Validation Accuracy: 0.817064
Accuracy on Test data: 0.840977668762207, 0.753248929977417
Step 6 | Training Loss: 0.628010 | Validation Accuracy: 0.831349
Accuracy on Test data: 0.8597409725189209, 0.7681012749671936
Step 7 | Training Loss: 0.624328 | Validation Accuracy: 0.859127
Accuracy on Test data: 0.8639993071556091, 0.7691982984542847
Step 8 | Training Loss: 0.644475 | Validation Accuracy: 0.882540
Accuracy on Test data: 0.8686568737030029, 0.7720674872398376
Step 9 | Training Loss: 0.636686 | Validation Accuracy: 0.899603
Accuracy on Test data: 0.8718949556350708, 0.7738396525382996
Step 10 | Training Loss: 0.624266 | Validation Accuracy: 0.892063
Accuracy on Test data: 0.8744233250617981, 0.7749367356300354
Step 1 | Training Loss: 0.682210 | Validation Accuracy: 0.892460
Accuracy on Test data: 0.8743789792060852, 0.7745147943496704
Step 2 | Training Loss: 0.652531 | Validation Accuracy: 0.893651
Accuracy on Test data: 0.8744677305221558, 0.7742615938186646
Step 3 | Training Loss: 0.603160 | Validation Accuracy: 0.899206
Accuracy on Test data: 0.8746007680892944, 0.7741771936416626
Step 4 | Training Loss: 0.571847 | Validation Accuracy: 0.896032
Accuracy on Test data: 0.8747338652610779, 0.7740928530693054
Step 5 | Training Loss: 0.564304 | Validation Accuracy: 0.896032
Accuracy on Test data: 0.8750443458557129, 0.7742615938186646
Step 6 | Training Loss: 0.618003 | Validation Accuracy: 0.903571
Accuracy on Test data: 0.8751774430274963, 0.7741771936416626
Step 7 | Training Loss: 0.644191 | Validation Accuracy: 0.908730
Accuracy on Test data: 0.8752661347389221, 0.7740928530693054
Step 8 | Training Loss: 0.613471 | Validation Accuracy: 0.899206
Accuracy on Test data: 0.8749556541442871, 0.7731645703315735
Step 9 | Training Loss: 0.616389 | Validation Accuracy: 0.897619
Accuracy on Test data: 0.873846709728241, 0.7708860635757446
Step 10 | Training Loss: 0.633085 | Validation Accuracy: 0.898810
Accuracy on Test data: 0.8732256889343262, 0.7696202397346497
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.672199 | Validation Accuracy: 0.458333
Accuracy on Test data: 0.5706618428230286, 0.8198312520980835
Step 2 | Training Loss: 0.620560 | Validation Accuracy: 0.689683
Accuracy on Test data: 0.789434015750885, 0.8070886135101318
Step 3 | Training Loss: 0.614150 | Validation Accuracy: 0.801984
Accuracy on Test data: 0.8420422077178955, 0.7878481149673462
Step 4 | Training Loss: 0.678400 | Validation Accuracy: 0.862698
Accuracy on Test data: 0.8813875317573547, 0.8142616152763367
Step 5 | Training Loss: 0.628679 | Validation Accuracy: 0.867063
Accuracy on Test data: 0.8727377653121948, 0.7875949144363403
Step 6 | Training Loss: 0.607436 | Validation Accuracy: 0.904762
Accuracy on Test data: 0.8797906041145325, 0.7826160192489624
Step 7 | Training Loss: 0.576137 | Validation Accuracy: 0.913492
Accuracy on Test data: 0.8793026804924011, 0.7783122658729553
Step 8 | Training Loss: 0.548365 | Validation Accuracy: 0.921825
Accuracy on Test data: 0.8712295889854431, 0.7618565559387207
Step 9 | Training Loss: 0.572935 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8602288961410522, 0.7408438920974731
Step 10 | Training Loss: 0.567939 | Validation Accuracy: 0.936111
Accuracy on Test data: 0.8518452644348145, 0.7247257232666016
Step 1 | Training Loss: 0.564364 | Validation Accuracy: 0.936508
Accuracy on Test data: 0.8513573408126831, 0.7237130999565125
Step 2 | Training Loss: 0.536607 | Validation Accuracy: 0.929365
Accuracy on Test data: 0.8501153588294983, 0.7213501930236816
Step 3 | Training Loss: 0.542414 | Validation Accuracy: 0.932936
Accuracy on Test data: 0.8488733172416687, 0.7189873456954956
Step 4 | Training Loss: 0.552728 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.8476756811141968, 0.7166244983673096
Step 5 | Training Loss: 0.515897 | Validation Accuracy: 0.941667
Accuracy on Test data: 0.8461231589317322, 0.7136709094047546
Step 6 | Training Loss: 0.515423 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8448811173439026, 0.7113924026489258
Step 7 | Training Loss: 0.521187 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8439052700996399, 0.7093670964241028
Step 8 | Training Loss: 0.515792 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.8433729410171509, 0.7081856727600098
Step 9 | Training Loss: 0.562222 | Validation Accuracy: 0.933333
Accuracy on Test data: 0.8420422077178955, 0.7055696249008179
Step 10 | Training Loss: 0.524896 | Validation Accuracy: 0.950000
Accuracy on Test data: 0.8409332633018494, 0.7034599184989929
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.667404 | Validation Accuracy: 0.814683
Accuracy on Test data: 0.6625266075134277, 0.5385653972625732
Step 2 | Training Loss: 0.658525 | Validation Accuracy: 0.883333
Accuracy on Test data: 0.7271113991737366, 0.647257387638092
Step 3 | Training Loss: 0.607844 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.8595635294914246, 0.7481856346130371
Step 4 | Training Loss: 0.619875 | Validation Accuracy: 0.897222
Accuracy on Test data: 0.8801011443138123, 0.7847257256507874
Step 5 | Training Loss: 0.590402 | Validation Accuracy: 0.903968
Accuracy on Test data: 0.8831618428230286, 0.7884387969970703
Step 6 | Training Loss: 0.528730 | Validation Accuracy: 0.908333
Accuracy on Test data: 0.8835166692733765, 0.7875105738639832
Step 7 | Training Loss: 0.534611 | Validation Accuracy: 0.907143
Accuracy on Test data: 0.8777501583099365, 0.7759493589401245
Step 8 | Training Loss: 0.535255 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.8754435777664185, 0.7713080048561096
Step 9 | Training Loss: 0.528475 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.8704755306243896, 0.7616877555847168
Step 10 | Training Loss: 0.485998 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8679027557373047, 0.7564557194709778
Step 1 | Training Loss: 0.461329 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.867769718170166, 0.7562025189399719
Step 2 | Training Loss: 0.488839 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8673704862594604, 0.7554430365562439
Step 3 | Training Loss: 0.457580 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.866926908493042, 0.7545991539955139
Step 4 | Training Loss: 0.477877 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.8665720224380493, 0.7539240717887878
Step 5 | Training Loss: 0.511020 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.866394579410553, 0.75358647108078
Step 6 | Training Loss: 0.450740 | Validation Accuracy: 0.932143
Accuracy on Test data: 0.8659510016441345, 0.75274258852005
Step 7 | Training Loss: 0.449850 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.8657292127609253, 0.7523206472396851
Step 8 | Training Loss: 0.503275 | Validation Accuracy: 0.926984
Accuracy on Test data: 0.865196943283081, 0.751223623752594
Step 9 | Training Loss: 0.498929 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8643985390663147, 0.7497046589851379
Step 10 | Training Loss: 0.479838 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8633782863616943, 0.7477636933326721
Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.678274 | Validation Accuracy: 0.673810
Accuracy on Test data: 0.6263750791549683, 0.5431223511695862
Step 2 | Training Loss: 0.631988 | Validation Accuracy: 0.725000
Accuracy on Test data: 0.6564496159553528, 0.5744304060935974
Step 3 | Training Loss: 0.617910 | Validation Accuracy: 0.787698
Accuracy on Test data: 0.7182842493057251, 0.5593249201774597
Step 4 | Training Loss: 0.560697 | Validation Accuracy: 0.856349
Accuracy on Test data: 0.766678512096405, 0.5829535722732544
Step 5 | Training Loss: 0.553952 | Validation Accuracy: 0.879365
Accuracy on Test data: 0.7817600965499878, 0.601097047328949
Step 6 | Training Loss: 0.453717 | Validation Accuracy: 0.899206
Accuracy on Test data: 0.8055358529090881, 0.6410126686096191
Step 7 | Training Loss: 0.468382 | Validation Accuracy: 0.923810
Accuracy on Test data: 0.8250975608825684, 0.6760337352752686
Step 8 | Training Loss: 0.479441 | Validation Accuracy: 0.932936
Accuracy on Test data: 0.8397356271743774, 0.702953577041626
Step 9 | Training Loss: 0.490064 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.8454577922821045, 0.7133333086967468
Step 10 | Training Loss: 0.464183 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.8481636047363281, 0.7181434631347656
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Accuracy on Test data: 0.8484740853309631, 0.7185654044151306
Step 2 | Training Loss: 0.445503 | Validation Accuracy: 0.950000
Accuracy on Test data: 0.8484740853309631, 0.7185654044151306
Step 3 | Training Loss: 0.436421 | Validation Accuracy: 0.953968
Accuracy on Test data: 0.8486958742141724, 0.7189029455184937
Step 4 | Training Loss: 0.429886 | Validation Accuracy: 0.959127
Accuracy on Test data: 0.8486958742141724, 0.7188185453414917
Step 5 | Training Loss: 0.442861 | Validation Accuracy: 0.950000
Accuracy on Test data: 0.8488289713859558, 0.7190717458724976
Step 6 | Training Loss: 0.466741 | Validation Accuracy: 0.949206
Accuracy on Test data: 0.8488733172416687, 0.7191561460494995
Step 7 | Training Loss: 0.436502 | Validation Accuracy: 0.947222
Accuracy on Test data: 0.8487846255302429, 0.7189029455184937
Step 8 | Training Loss: 0.443686 | Validation Accuracy: 0.952381
Accuracy on Test data: 0.8488289713859558, 0.7189873456954956
Step 9 | Training Loss: 0.419290 | Validation Accuracy: 0.953175
Accuracy on Test data: 0.8489176630973816, 0.7190717458724976
Step 10 | Training Loss: 0.427250 | Validation Accuracy: 0.946032
Accuracy on Test data: 0.8489620089530945, 0.7190717458724976
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.716544 | Validation Accuracy: 0.633730
Accuracy on Test data: 0.4879347085952759, 0.2672573924064636
Step 2 | Training Loss: 0.647118 | Validation Accuracy: 0.721032
Accuracy on Test data: 0.529675304889679, 0.28869199752807617
Step 3 | Training Loss: 0.593776 | Validation Accuracy: 0.794841
Accuracy on Test data: 0.6372870802879333, 0.33299577236175537
Step 4 | Training Loss: 0.583078 | Validation Accuracy: 0.830159
Accuracy on Test data: 0.6619943380355835, 0.3770464062690735
Step 5 | Training Loss: 0.512966 | Validation Accuracy: 0.863889
Accuracy on Test data: 0.6813342571258545, 0.40835443139076233
Step 6 | Training Loss: 0.483888 | Validation Accuracy: 0.880159
Accuracy on Test data: 0.6955287456512451, 0.4315611720085144
Step 7 | Training Loss: 0.507726 | Validation Accuracy: 0.896032
Accuracy on Test data: 0.7117193341255188, 0.4591561257839203
Step 8 | Training Loss: 0.465859 | Validation Accuracy: 0.906349
Accuracy on Test data: 0.7245830297470093, 0.4819409251213074
Step 9 | Training Loss: 0.467561 | Validation Accuracy: 0.923016
Accuracy on Test data: 0.7351401448249817, 0.5017721652984619
Step 10 | Training Loss: 0.445854 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.7431245446205139, 0.5157805681228638
Step 1 | Training Loss: 0.456274 | Validation Accuracy: 0.938095
Accuracy on Test data: 0.7434350848197937, 0.5162869095802307
Step 2 | Training Loss: 0.426828 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.7437899112701416, 0.5169620513916016
Step 3 | Training Loss: 0.475308 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.743923008441925, 0.5173839926719666
Step 4 | Training Loss: 0.491916 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.7443665862083435, 0.5179746747016907
Step 5 | Training Loss: 0.476422 | Validation Accuracy: 0.934524
Accuracy on Test data: 0.7448988556861877, 0.5188185572624207
Step 6 | Training Loss: 0.442293 | Validation Accuracy: 0.928968
Accuracy on Test data: 0.7456973195075989, 0.5203375816345215
Step 7 | Training Loss: 0.448656 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.7466288208961487, 0.5220252871513367
Step 8 | Training Loss: 0.466332 | Validation Accuracy: 0.939286
Accuracy on Test data: 0.7475159764289856, 0.5235443115234375
Step 9 | Training Loss: 0.430548 | Validation Accuracy: 0.940873
Accuracy on Test data: 0.7490241527557373, 0.5263291001319885
Step 10 | Training Loss: 0.449695 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.7500443458557129, 0.5281856656074524
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.644231 | Validation Accuracy: 0.695635
Accuracy on Test data: 0.6577803492546082, 0.5669198036193848
Step 2 | Training Loss: 0.634722 | Validation Accuracy: 0.747222
Accuracy on Test data: 0.6568931937217712, 0.5594936609268188
Step 3 | Training Loss: 0.580348 | Validation Accuracy: 0.843651
Accuracy on Test data: 0.7696948051452637, 0.5952742695808411
Step 4 | Training Loss: 0.514642 | Validation Accuracy: 0.871429
Accuracy on Test data: 0.7873935699462891, 0.6156117916107178
Step 5 | Training Loss: 0.487536 | Validation Accuracy: 0.884524
Accuracy on Test data: 0.8009669780731201, 0.6378058791160583
Step 6 | Training Loss: 0.456041 | Validation Accuracy: 0.902778
Accuracy on Test data: 0.8125443458557129, 0.656708836555481
Step 7 | Training Loss: 0.484349 | Validation Accuracy: 0.908333
Accuracy on Test data: 0.818222165107727, 0.6665822863578796
Step 8 | Training Loss: 0.443672 | Validation Accuracy: 0.923810
Accuracy on Test data: 0.8243878483772278, 0.6767088770866394
Step 9 | Training Loss: 0.438353 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8290454149246216, 0.6843038201332092
Step 10 | Training Loss: 0.408771 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8322835564613342, 0.6896202564239502
Step 1 | Training Loss: 0.420233 | Validation Accuracy: 0.933333
Accuracy on Test data: 0.8324165940284729, 0.6897890567779541
Step 2 | Training Loss: 0.428030 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.8327271342277527, 0.6900421977043152
Step 3 | Training Loss: 0.448563 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8330819606781006, 0.6905485391616821
Step 4 | Training Loss: 0.438855 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.8334368467330933, 0.6910548806190491
Step 5 | Training Loss: 0.447411 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.8337029814720154, 0.6914768218994141
Step 6 | Training Loss: 0.415915 | Validation Accuracy: 0.947619
Accuracy on Test data: 0.8340134620666504, 0.6917299628257751
Step 7 | Training Loss: 0.442359 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8345457911491394, 0.6926582455635071
Step 8 | Training Loss: 0.444521 | Validation Accuracy: 0.941270
Accuracy on Test data: 0.8347675800323486, 0.6929957866668701
Step 9 | Training Loss: 0.441745 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.834945023059845, 0.6933333277702332
Step 10 | Training Loss: 0.431333 | Validation Accuracy: 0.946032
Accuracy on Test data: 0.8350337147712708, 0.6934177279472351
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.671292 | Validation Accuracy: 0.708333
Accuracy on Test data: 0.7333658337593079, 0.6110548377037048
Step 2 | Training Loss: 0.647159 | Validation Accuracy: 0.804762
Accuracy on Test data: 0.7873935699462891, 0.6341772079467773
Step 3 | Training Loss: 0.628559 | Validation Accuracy: 0.818254
Accuracy on Test data: 0.7954222559928894, 0.6427004337310791
Step 4 | Training Loss: 0.545910 | Validation Accuracy: 0.852381
Accuracy on Test data: 0.8018985390663147, 0.6464135050773621
Step 5 | Training Loss: 0.498666 | Validation Accuracy: 0.851190
Accuracy on Test data: 0.7941359281539917, 0.6254852414131165
Step 6 | Training Loss: 0.489462 | Validation Accuracy: 0.874206
Accuracy on Test data: 0.7976845502853394, 0.6288607716560364
Step 7 | Training Loss: 0.509629 | Validation Accuracy: 0.891270
Accuracy on Test data: 0.7986160516738892, 0.6285232305526733
Step 8 | Training Loss: 0.511992 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.803273618221283, 0.6351054906845093
Step 9 | Training Loss: 0.438199 | Validation Accuracy: 0.930556
Accuracy on Test data: 0.8037615418434143, 0.6357805728912354
Step 10 | Training Loss: 0.419296 | Validation Accuracy: 0.926587
Accuracy on Test data: 0.8048261404037476, 0.6372151970863342
Step 1 | Training Loss: 0.449268 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8053140640258789, 0.6376371383666992
Step 2 | Training Loss: 0.426267 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.8056245446205139, 0.6379746794700623
Step 3 | Training Loss: 0.404282 | Validation Accuracy: 0.927381
Accuracy on Test data: 0.8053584098815918, 0.6373839378356934
Step 4 | Training Loss: 0.458081 | Validation Accuracy: 0.942857
Accuracy on Test data: 0.805269718170166, 0.6372151970863342
Step 5 | Training Loss: 0.458500 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.8054471015930176, 0.6375527381896973
Step 6 | Training Loss: 0.448714 | Validation Accuracy: 0.932540
Accuracy on Test data: 0.8054915070533752, 0.6375527381896973
Step 7 | Training Loss: 0.423007 | Validation Accuracy: 0.932540
Accuracy on Test data: 0.8056688904762268, 0.6377215385437012
Step 8 | Training Loss: 0.465170 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8056245446205139, 0.6376371383666992
Step 9 | Training Loss: 0.447695 | Validation Accuracy: 0.939286
Accuracy on Test data: 0.8056688904762268, 0.6377215385437012
Step 10 | Training Loss: 0.471186 | Validation Accuracy: 0.936905
Accuracy on Test data: 0.8056688904762268, 0.6377215385437012
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.617134 | Validation Accuracy: 0.689683
Accuracy on Test data: 0.6719304323196411, 0.46303796768188477
Step 2 | Training Loss: 0.616653 | Validation Accuracy: 0.748016
Accuracy on Test data: 0.6898953318595886, 0.4719831347465515
Step 3 | Training Loss: 0.588957 | Validation Accuracy: 0.831746
Accuracy on Test data: 0.7325674295425415, 0.5259071588516235
Step 4 | Training Loss: 0.557049 | Validation Accuracy: 0.875397
Accuracy on Test data: 0.7482256889343262, 0.5424472689628601
Step 5 | Training Loss: 0.563769 | Validation Accuracy: 0.884921
Accuracy on Test data: 0.7586497664451599, 0.556877613067627
Step 6 | Training Loss: 0.512108 | Validation Accuracy: 0.904365
Accuracy on Test data: 0.7630411386489868, 0.5629535913467407
Step 7 | Training Loss: 0.484166 | Validation Accuracy: 0.925794
Accuracy on Test data: 0.7672995328903198, 0.5697046518325806
Step 8 | Training Loss: 0.473977 | Validation Accuracy: 0.933730
Accuracy on Test data: 0.770715057849884, 0.5747679471969604
Step 9 | Training Loss: 0.473300 | Validation Accuracy: 0.934127
Accuracy on Test data: 0.7733765244483948, 0.5794093012809753
Step 10 | Training Loss: 0.432038 | Validation Accuracy: 0.943254
Accuracy on Test data: 0.7737313508987427, 0.5794936418533325
Step 1 | Training Loss: 0.444602 | Validation Accuracy: 0.935714
Accuracy on Test data: 0.7736426591873169, 0.5793249011039734
Step 2 | Training Loss: 0.447341 | Validation Accuracy: 0.940476
Accuracy on Test data: 0.7731547355651855, 0.5783966183662415
Step 3 | Training Loss: 0.457475 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.7716465592384338, 0.5755274295806885
Step 4 | Training Loss: 0.438023 | Validation Accuracy: 0.953968
Accuracy on Test data: 0.7693399786949158, 0.5711392164230347
Step 5 | Training Loss: 0.438565 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.7680092453956604, 0.5685232281684875
Step 6 | Training Loss: 0.464510 | Validation Accuracy: 0.951984
Accuracy on Test data: 0.7679648399353027, 0.5684388279914856
Step 7 | Training Loss: 0.420339 | Validation Accuracy: 0.947222
Accuracy on Test data: 0.7679648399353027, 0.5681856274604797
Step 8 | Training Loss: 0.438993 | Validation Accuracy: 0.946825
Accuracy on Test data: 0.7673882246017456, 0.5668354630470276
Step 9 | Training Loss: 0.414694 | Validation Accuracy: 0.950000
Accuracy on Test data: 0.7677430510520935, 0.5675105452537537
Step 10 | Training Loss: 0.442244 | Validation Accuracy: 0.955952
Accuracy on Test data: 0.7684528231620789, 0.5687763690948486
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.693162 | Validation Accuracy: 0.540079
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.693138 | Validation Accuracy: 0.522619
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692981 | Validation Accuracy: 0.523810
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.692888 | Validation Accuracy: 0.537698
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.693026 | Validation Accuracy: 0.532540
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.693063 | Validation Accuracy: 0.541270
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692911 | Validation Accuracy: 0.524206
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.692318 | Validation Accuracy: 0.532937
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.692220 | Validation Accuracy: 0.525397
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.692915 | Validation Accuracy: 0.540476
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 1 | Training Loss: 0.692813 | Validation Accuracy: 0.527778
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.692810 | Validation Accuracy: 0.540079
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692095 | Validation Accuracy: 0.534921
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.692804 | Validation Accuracy: 0.528175
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.692698 | Validation Accuracy: 0.538492
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.693217 | Validation Accuracy: 0.544841
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692795 | Validation Accuracy: 0.529365
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.693006 | Validation Accuracy: 0.539683
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.692467 | Validation Accuracy: 0.540476
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.692352 | Validation Accuracy: 0.527381
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.712486 | Validation Accuracy: 0.401587
Accuracy on Test data: 0.4126596748828888, 0.4844725728034973
Step 2 | Training Loss: 0.685245 | Validation Accuracy: 0.460714
Accuracy on Test data: 0.4623403251171112, 0.48177215456962585
Step 3 | Training Loss: 0.681166 | Validation Accuracy: 0.580159
Accuracy on Test data: 0.5932842493057251, 0.4913924038410187
Step 4 | Training Loss: 0.670817 | Validation Accuracy: 0.680952
Accuracy on Test data: 0.6941536664962769, 0.5066666603088379
Step 5 | Training Loss: 0.675091 | Validation Accuracy: 0.716667
Accuracy on Test data: 0.7132717967033386, 0.5146835446357727
Step 6 | Training Loss: 0.681704 | Validation Accuracy: 0.736508
Accuracy on Test data: 0.7226312756538391, 0.5594092607498169
Step 7 | Training Loss: 0.713746 | Validation Accuracy: 0.750397
Accuracy on Test data: 0.7232966423034668, 0.5809282660484314
Step 8 | Training Loss: 0.678665 | Validation Accuracy: 0.795635
Accuracy on Test data: 0.7322125434875488, 0.5900421738624573
Step 9 | Training Loss: 0.648992 | Validation Accuracy: 0.807936
Accuracy on Test data: 0.7445883750915527, 0.6059072017669678
Step 10 | Training Loss: 0.697915 | Validation Accuracy: 0.796429
Accuracy on Test data: 0.7562987804412842, 0.6139240264892578
Step 1 | Training Loss: 0.644115 | Validation Accuracy: 0.819444
Accuracy on Test data: 0.7579843997955322, 0.6147679090499878
Step 2 | Training Loss: 0.670104 | Validation Accuracy: 0.811111
Accuracy on Test data: 0.7594038248062134, 0.6155274510383606
Step 3 | Training Loss: 0.666771 | Validation Accuracy: 0.797222
Accuracy on Test data: 0.7611337900161743, 0.6167932748794556
Step 4 | Training Loss: 0.638149 | Validation Accuracy: 0.813492
Accuracy on Test data: 0.7618878483772278, 0.6178058981895447
Step 5 | Training Loss: 0.665071 | Validation Accuracy: 0.801984
Accuracy on Test data: 0.7630411386489868, 0.6189029812812805
Step 6 | Training Loss: 0.675673 | Validation Accuracy: 0.803571
Accuracy on Test data: 0.7651703357696533, 0.6205063462257385
Step 7 | Training Loss: 0.661568 | Validation Accuracy: 0.818254
Accuracy on Test data: 0.7670777440071106, 0.6216877698898315
Step 8 | Training Loss: 0.682282 | Validation Accuracy: 0.805952
Accuracy on Test data: 0.7689850926399231, 0.6227847933769226
Step 9 | Training Loss: 0.657124 | Validation Accuracy: 0.826190
Accuracy on Test data: 0.7704932689666748, 0.6236286759376526
Step 10 | Training Loss: 0.657591 | Validation Accuracy: 0.807540
Accuracy on Test data: 0.7720014452934265, 0.6243038177490234
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
Step 1 | Training Loss: 0.672524 | Validation Accuracy: 0.748810
Accuracy on Test data: 0.7123402953147888, 0.4799156188964844
Step 2 | Training Loss: 0.708504 | Validation Accuracy: 0.782540
Accuracy on Test data: 0.7359386086463928, 0.5173839926719666
Step 3 | Training Loss: 0.711852 | Validation Accuracy: 0.817064
Accuracy on Test data: 0.7625532150268555, 0.5645569562911987
Step 4 | Training Loss: 0.621271 | Validation Accuracy: 0.842063
Accuracy on Test data: 0.7851756811141968, 0.6045569777488708
Step 5 | Training Loss: 0.666263 | Validation Accuracy: 0.850000
Accuracy on Test data: 0.7995032072067261, 0.6319831013679504
Step 6 | Training Loss: 0.660104 | Validation Accuracy: 0.865476
Accuracy on Test data: 0.8093949556350708, 0.649282693862915
Step 7 | Training Loss: 0.644506 | Validation Accuracy: 0.875397
Accuracy on Test data: 0.814185619354248, 0.6573839783668518
Step 8 | Training Loss: 0.617934 | Validation Accuracy: 0.882143
Accuracy on Test data: 0.8185326457023621, 0.6642194390296936
Step 9 | Training Loss: 0.547193 | Validation Accuracy: 0.891667
Accuracy on Test data: 0.8223917484283447, 0.6709704399108887
Step 10 | Training Loss: 0.623826 | Validation Accuracy: 0.880556
Accuracy on Test data: 0.8244321942329407, 0.6744303703308105
Step 1 | Training Loss: 0.599884 | Validation Accuracy: 0.889286
Accuracy on Test data: 0.8244321942329407, 0.6743459701538086
Step 2 | Training Loss: 0.583727 | Validation Accuracy: 0.891270
Accuracy on Test data: 0.8244765996932983, 0.6744303703308105
Step 3 | Training Loss: 0.628264 | Validation Accuracy: 0.881349
Accuracy on Test data: 0.8242104053497314, 0.6736708879470825
Step 4 | Training Loss: 0.653319 | Validation Accuracy: 0.886111
Accuracy on Test data: 0.8229240775108337, 0.6712236404418945
Step 5 | Training Loss: 0.601120 | Validation Accuracy: 0.894048
Accuracy on Test data: 0.8219925761222839, 0.6694514751434326
Step 6 | Training Loss: 0.616744 | Validation Accuracy: 0.879365
Accuracy on Test data: 0.821415901184082, 0.6682700514793396
Step 7 | Training Loss: 0.559821 | Validation Accuracy: 0.883730
Accuracy on Test data: 0.8204843997955322, 0.6664134860038757
Step 8 | Training Loss: 0.594883 | Validation Accuracy: 0.880952
Accuracy on Test data: 0.8192867040634155, 0.6641350388526917
Step 9 | Training Loss: 0.572105 | Validation Accuracy: 0.893254
Accuracy on Test data: 0.8172906041145325, 0.6603375673294067
Step 10 | Training Loss: 0.579632 | Validation Accuracy: 0.883730
Accuracy on Test data: 0.816847026348114, 0.6594936847686768
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.798465 | Validation Accuracy: 0.523413
Accuracy on Test data: 0.44144782423973083, 0.1968776434659958
Step 2 | Training Loss: 0.758372 | Validation Accuracy: 0.551984
Accuracy on Test data: 0.4560858905315399, 0.2226160317659378
Step 3 | Training Loss: 0.725772 | Validation Accuracy: 0.603175
Accuracy on Test data: 0.5005322694778442, 0.3037974536418915
Step 4 | Training Loss: 0.714224 | Validation Accuracy: 0.737302
Accuracy on Test data: 0.6496628522872925, 0.3540928363800049
Step 5 | Training Loss: 0.678372 | Validation Accuracy: 0.786508
Accuracy on Test data: 0.6966376900672913, 0.43932488560676575
Step 6 | Training Loss: 0.617848 | Validation Accuracy: 0.831746
Accuracy on Test data: 0.7253371477127075, 0.48902952671051025
Step 7 | Training Loss: 0.602573 | Validation Accuracy: 0.876190
Accuracy on Test data: 0.7590045928955078, 0.551898717880249
Step 8 | Training Loss: 0.624981 | Validation Accuracy: 0.901190
Accuracy on Test data: 0.778477668762207, 0.5876793265342712
Step 9 | Training Loss: 0.584152 | Validation Accuracy: 0.902778
Accuracy on Test data: 0.7855748534202576, 0.6008439064025879
Step 10 | Training Loss: 0.556384 | Validation Accuracy: 0.916667
Accuracy on Test data: 0.7978619337081909, 0.6224472522735596
Step 1 | Training Loss: 0.565137 | Validation Accuracy: 0.920635
Accuracy on Test data: 0.8005678057670593, 0.6275105476379395
Step 2 | Training Loss: 0.574848 | Validation Accuracy: 0.906746
Accuracy on Test data: 0.8020759224891663, 0.6303797364234924
Step 3 | Training Loss: 0.601320 | Validation Accuracy: 0.923413
Accuracy on Test data: 0.8034954071044922, 0.6328269839286804
Step 4 | Training Loss: 0.544954 | Validation Accuracy: 0.905952
Accuracy on Test data: 0.804737389087677, 0.6346835494041443
Step 5 | Training Loss: 0.576689 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8060681223869324, 0.6372151970863342
Step 6 | Training Loss: 0.559750 | Validation Accuracy: 0.922619
Accuracy on Test data: 0.8074876070022583, 0.6399155855178833
Step 7 | Training Loss: 0.544933 | Validation Accuracy: 0.919444
Accuracy on Test data: 0.8091288208961487, 0.6431223750114441
Step 8 | Training Loss: 0.585544 | Validation Accuracy: 0.917063
Accuracy on Test data: 0.8103264570236206, 0.6454008221626282
Step 9 | Training Loss: 0.541036 | Validation Accuracy: 0.920238
Accuracy on Test data: 0.8111692667007446, 0.647004246711731
Step 10 | Training Loss: 0.511779 | Validation Accuracy: 0.907540
Accuracy on Test data: 0.8118346333503723, 0.6482700705528259
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.673574 | Validation Accuracy: 0.756746
Accuracy on Test data: 0.7351845502853394, 0.5636286735534668
Step 2 | Training Loss: 0.665653 | Validation Accuracy: 0.812302
Accuracy on Test data: 0.7529276013374329, 0.5818565487861633
Step 3 | Training Loss: 0.615730 | Validation Accuracy: 0.811508
Accuracy on Test data: 0.8061568737030029, 0.6783122420310974
Step 4 | Training Loss: 0.636863 | Validation Accuracy: 0.809524
Accuracy on Test data: 0.8163591027259827, 0.6949366927146912
Step 5 | Training Loss: 0.582661 | Validation Accuracy: 0.863889
Accuracy on Test data: 0.8451472520828247, 0.7340084314346313
Step 6 | Training Loss: 0.549062 | Validation Accuracy: 0.889286
Accuracy on Test data: 0.8517565727233887, 0.7333333492279053
Step 7 | Training Loss: 0.558681 | Validation Accuracy: 0.896825
Accuracy on Test data: 0.8291341662406921, 0.6850633025169373
Step 8 | Training Loss: 0.512716 | Validation Accuracy: 0.906349
Accuracy on Test data: 0.8203956484794617, 0.6675949096679688
Step 9 | Training Loss: 0.530932 | Validation Accuracy: 0.918254
Accuracy on Test data: 0.8072214126586914, 0.6399155855178833
Step 10 | Training Loss: 0.487926 | Validation Accuracy: 0.911508
Accuracy on Test data: 0.8000798225402832, 0.6251477003097534
Step 1 | Training Loss: 0.498202 | Validation Accuracy: 0.908730
Accuracy on Test data: 0.7996806502342224, 0.6242194175720215
Step 2 | Training Loss: 0.485956 | Validation Accuracy: 0.921429
Accuracy on Test data: 0.7991926670074463, 0.6230379939079285
Step 3 | Training Loss: 0.503555 | Validation Accuracy: 0.921825
Accuracy on Test data: 0.7986160516738892, 0.6218565106391907
Step 4 | Training Loss: 0.465370 | Validation Accuracy: 0.922222
Accuracy on Test data: 0.7980837225914001, 0.6208438873291016
Step 5 | Training Loss: 0.468696 | Validation Accuracy: 0.928968
Accuracy on Test data: 0.7976845502853394, 0.6200844049453735
Step 6 | Training Loss: 0.496921 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.7971965670585632, 0.6191561222076416
Step 7 | Training Loss: 0.444896 | Validation Accuracy: 0.918651
Accuracy on Test data: 0.7967973947525024, 0.6182278394699097
Step 8 | Training Loss: 0.471772 | Validation Accuracy: 0.917857
Accuracy on Test data: 0.796353816986084, 0.6173839569091797
Step 9 | Training Loss: 0.471214 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.7956884503364563, 0.6159493923187256
Step 10 | Training Loss: 0.502042 | Validation Accuracy: 0.917857
Accuracy on Test data: 0.7944464087486267, 0.6133333444595337
Current Layer Attributes - epochs:10 hidden layers:1 features count:1
Step 1 | Training Loss: 0.634457 | Validation Accuracy: 0.767857
Accuracy on Test data: 0.7056422829627991, 0.4818565547466278
Step 2 | Training Loss: 0.593831 | Validation Accuracy: 0.852778
Accuracy on Test data: 0.7527058124542236, 0.544641375541687
Step 3 | Training Loss: 0.573505 | Validation Accuracy: 0.890476
Accuracy on Test data: 0.7696504592895508, 0.5727426409721375
Step 4 | Training Loss: 0.538186 | Validation Accuracy: 0.898016
Accuracy on Test data: 0.7769694924354553, 0.5861603617668152
Step 5 | Training Loss: 0.507895 | Validation Accuracy: 0.903175
Accuracy on Test data: 0.783135175704956, 0.5963712930679321
Step 6 | Training Loss: 0.462028 | Validation Accuracy: 0.913889
Accuracy on Test data: 0.7891234755516052, 0.6073417663574219
Step 7 | Training Loss: 0.471538 | Validation Accuracy: 0.923016
Accuracy on Test data: 0.7951117753982544, 0.6186497807502747
Step 8 | Training Loss: 0.476728 | Validation Accuracy: 0.931349
Accuracy on Test data: 0.7985273003578186, 0.6247257590293884
Step 9 | Training Loss: 0.438594 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8013662099838257, 0.6300421953201294
Step 10 | Training Loss: 0.451600 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8050479292869568, 0.6367088556289673
Step 1 | Training Loss: 0.446525 | Validation Accuracy: 0.933333
Accuracy on Test data: 0.8053140640258789, 0.6372151970863342
Step 2 | Training Loss: 0.415783 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8055358529090881, 0.6376371383666992
Step 3 | Training Loss: 0.400128 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.8060237765312195, 0.6384810209274292
Step 4 | Training Loss: 0.434832 | Validation Accuracy: 0.944841
Accuracy on Test data: 0.8063786625862122, 0.6391561031341553
Step 5 | Training Loss: 0.429359 | Validation Accuracy: 0.953175
Accuracy on Test data: 0.8069109320640564, 0.6401687860488892
Step 6 | Training Loss: 0.425168 | Validation Accuracy: 0.946429
Accuracy on Test data: 0.8072658181190491, 0.6408438682556152
Step 7 | Training Loss: 0.401036 | Validation Accuracy: 0.938095
Accuracy on Test data: 0.8075762987136841, 0.6413502097129822
Step 8 | Training Loss: 0.419451 | Validation Accuracy: 0.942857
Accuracy on Test data: 0.8079755306243896, 0.6421096920967102
Step 9 | Training Loss: 0.400345 | Validation Accuracy: 0.948413
Accuracy on Test data: 0.8080642223358154, 0.6422784924507141
Step 10 | Training Loss: 0.440958 | Validation Accuracy: 0.944444
Accuracy on Test data: 0.8082416653633118, 0.6426160335540771
Current Layer Attributes - epochs:10 hidden layers:1 features count:12
Step 1 | Training Loss: 0.717074 | Validation Accuracy: 0.629762
Accuracy on Test data: 0.6613733172416687, 0.6172995567321777
Step 2 | Training Loss: 0.625743 | Validation Accuracy: 0.785714
Accuracy on Test data: 0.7724006175994873, 0.5869198441505432
Step 3 | Training Loss: 0.604886 | Validation Accuracy: 0.838889
Accuracy on Test data: 0.7919623851776123, 0.6196624636650085
Step 4 | Training Loss: 0.556251 | Validation Accuracy: 0.862302
Accuracy on Test data: 0.801233172416687, 0.6362025141716003
Step 5 | Training Loss: 0.559502 | Validation Accuracy: 0.884524
Accuracy on Test data: 0.8024751543998718, 0.6379746794700623
Step 6 | Training Loss: 0.496559 | Validation Accuracy: 0.881349
Accuracy on Test data: 0.8041163682937622, 0.6394936442375183
Step 7 | Training Loss: 0.514024 | Validation Accuracy: 0.880159
Accuracy on Test data: 0.8066447973251343, 0.6435443162918091
Step 8 | Training Loss: 0.442718 | Validation Accuracy: 0.896032
Accuracy on Test data: 0.8131210207939148, 0.6555274128913879
Step 9 | Training Loss: 0.462284 | Validation Accuracy: 0.893254
Accuracy on Test data: 0.8179559707641602, 0.6641350388526917
Step 10 | Training Loss: 0.446628 | Validation Accuracy: 0.906746
Accuracy on Test data: 0.8195972442626953, 0.6668354272842407
Step 1 | Training Loss: 0.437003 | Validation Accuracy: 0.910317
Accuracy on Test data: 0.819730281829834, 0.6670042276382446
Step 2 | Training Loss: 0.414189 | Validation Accuracy: 0.905556
Accuracy on Test data: 0.8196415901184082, 0.6668354272842407
Step 3 | Training Loss: 0.443753 | Validation Accuracy: 0.896825
Accuracy on Test data: 0.8194641470909119, 0.6664978861808777
Step 4 | Training Loss: 0.445605 | Validation Accuracy: 0.911905
Accuracy on Test data: 0.819730281829834, 0.6668354272842407
Step 5 | Training Loss: 0.425793 | Validation Accuracy: 0.911508
Accuracy on Test data: 0.8198190331459045, 0.6669198274612427
Step 6 | Training Loss: 0.414333 | Validation Accuracy: 0.905952
Accuracy on Test data: 0.8200408220291138, 0.6671729683876038
Step 7 | Training Loss: 0.426744 | Validation Accuracy: 0.901190
Accuracy on Test data: 0.8203513026237488, 0.6672573685646057
Step 8 | Training Loss: 0.420870 | Validation Accuracy: 0.902778
Accuracy on Test data: 0.8204843997955322, 0.6674261689186096
Step 9 | Training Loss: 0.449902 | Validation Accuracy: 0.903968
Accuracy on Test data: 0.8206618428230286, 0.6677637100219727
Step 10 | Training Loss: 0.457960 | Validation Accuracy: 0.915873
Accuracy on Test data: 0.8207505345344543, 0.6677637100219727
Current Layer Attributes - epochs:10 hidden layers:1 features count:24
Step 1 | Training Loss: 0.666880 | Validation Accuracy: 0.716667
Accuracy on Test data: 0.6829755306243896, 0.4287763833999634
Step 2 | Training Loss: 0.627725 | Validation Accuracy: 0.763492
Accuracy on Test data: 0.6957505345344543, 0.4430379867553711
Step 3 | Training Loss: 0.567120 | Validation Accuracy: 0.796429
Accuracy on Test data: 0.7077714800834656, 0.4627847969532013
Step 4 | Training Loss: 0.521963 | Validation Accuracy: 0.868651
Accuracy on Test data: 0.7175301909446716, 0.477468341588974
Step 5 | Training Loss: 0.519057 | Validation Accuracy: 0.902381
Accuracy on Test data: 0.740773618221283, 0.5161181688308716
Step 6 | Training Loss: 0.539169 | Validation Accuracy: 0.926190
Accuracy on Test data: 0.7694730162620544, 0.5687763690948486
Step 7 | Training Loss: 0.457191 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.7613999247550964, 0.552658200263977
Step 8 | Training Loss: 0.454548 | Validation Accuracy: 0.948413
Accuracy on Test data: 0.7629967927932739, 0.5551055073738098
Step 9 | Training Loss: 0.425283 | Validation Accuracy: 0.956349
Accuracy on Test data: 0.762109637260437, 0.553248941898346
Step 10 | Training Loss: 0.424967 | Validation Accuracy: 0.955556
Accuracy on Test data: 0.762109637260437, 0.552658200263977
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Accuracy on Test data: 0.7619765996932983, 0.552405059337616
Step 2 | Training Loss: 0.451642 | Validation Accuracy: 0.956746
Accuracy on Test data: 0.7620652914047241, 0.5525738596916199
Step 3 | Training Loss: 0.440847 | Validation Accuracy: 0.949206
Accuracy on Test data: 0.7620209455490112, 0.552320659160614
Step 4 | Training Loss: 0.450469 | Validation Accuracy: 0.954365
Accuracy on Test data: 0.7625088691711426, 0.5529114007949829
Step 5 | Training Loss: 0.445305 | Validation Accuracy: 0.953968
Accuracy on Test data: 0.7629081010818481, 0.553248941898346
Step 6 | Training Loss: 0.436587 | Validation Accuracy: 0.957143
Accuracy on Test data: 0.7632185816764832, 0.553502082824707
Step 7 | Training Loss: 0.411490 | Validation Accuracy: 0.957143
Accuracy on Test data: 0.7632185816764832, 0.5534177422523499
Step 8 | Training Loss: 0.400167 | Validation Accuracy: 0.953175
Accuracy on Test data: 0.7634847164154053, 0.553924024105072
Step 9 | Training Loss: 0.431218 | Validation Accuracy: 0.956349
Accuracy on Test data: 0.7637065052986145, 0.5542616248130798
Step 10 | Training Loss: 0.411811 | Validation Accuracy: 0.951587
Accuracy on Test data: 0.7634403705596924, 0.5537552833557129
Current Layer Attributes - epochs:10 hidden layers:1 features count:48
Step 1 | Training Loss: 0.695716 | Validation Accuracy: 0.648810
Accuracy on Test data: 0.49055179953575134, 0.2415189892053604
Step 2 | Training Loss: 0.657457 | Validation Accuracy: 0.746032
Accuracy on Test data: 0.5217352509498596, 0.26599156856536865
Step 3 | Training Loss: 0.577753 | Validation Accuracy: 0.795238
Accuracy on Test data: 0.6045954823493958, 0.30421939492225647
Step 4 | Training Loss: 0.620505 | Validation Accuracy: 0.826587
Accuracy on Test data: 0.6475780606269836, 0.34329113364219666
Step 5 | Training Loss: 0.526357 | Validation Accuracy: 0.848413
Accuracy on Test data: 0.6623935699462891, 0.36945146322250366
Step 6 | Training Loss: 0.581242 | Validation Accuracy: 0.886508
Accuracy on Test data: 0.7108765244483948, 0.46025317907333374
Step 7 | Training Loss: 0.491185 | Validation Accuracy: 0.913492
Accuracy on Test data: 0.7429027557373047, 0.5204219222068787
Step 8 | Training Loss: 0.459930 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.7594481706619263, 0.550717294216156
Step 9 | Training Loss: 0.475067 | Validation Accuracy: 0.940079
Accuracy on Test data: 0.7687633037567139, 0.5681012868881226
Step 10 | Training Loss: 0.466838 | Validation Accuracy: 0.943651
Accuracy on Test data: 0.7773243188858032, 0.5837974548339844
Step 1 | Training Loss: 0.423484 | Validation Accuracy: 0.948810
Accuracy on Test data: 0.7779009938240051, 0.5848101377487183
Step 2 | Training Loss: 0.449523 | Validation Accuracy: 0.951587
Accuracy on Test data: 0.7783889174461365, 0.5854852199554443
Step 3 | Training Loss: 0.437433 | Validation Accuracy: 0.950397
Accuracy on Test data: 0.7794978618621826, 0.5874261856079102
Step 4 | Training Loss: 0.463657 | Validation Accuracy: 0.950794
Accuracy on Test data: 0.7800301909446716, 0.5881856679916382
Step 5 | Training Loss: 0.455339 | Validation Accuracy: 0.947222
Accuracy on Test data: 0.7808729410171509, 0.5897890329360962
Step 6 | Training Loss: 0.478033 | Validation Accuracy: 0.953571
Accuracy on Test data: 0.7819375395774841, 0.5916455984115601
Step 7 | Training Loss: 0.430545 | Validation Accuracy: 0.942460
Accuracy on Test data: 0.7824254631996155, 0.59248948097229
Step 8 | Training Loss: 0.458292 | Validation Accuracy: 0.948413
Accuracy on Test data: 0.7833569645881653, 0.594092845916748
Step 9 | Training Loss: 0.465228 | Validation Accuracy: 0.938889
Accuracy on Test data: 0.7841997742652893, 0.5955274105072021
Step 10 | Training Loss: 0.424569 | Validation Accuracy: 0.939286
Accuracy on Test data: 0.7849094867706299, 0.5967932343482971
Current Layer Attributes - epochs:10 hidden layers:1 features count:122
Step 1 | Training Loss: 0.729039 | Validation Accuracy: 0.542460
Accuracy on Test data: 0.610007107257843, 0.698818564414978
Step 2 | Training Loss: 0.688058 | Validation Accuracy: 0.687698
Accuracy on Test data: 0.7564762234687805, 0.7167088389396667
Step 3 | Training Loss: 0.628953 | Validation Accuracy: 0.733333
Accuracy on Test data: 0.8161373138427734, 0.752489447593689
Step 4 | Training Loss: 0.606961 | Validation Accuracy: 0.789286
Accuracy on Test data: 0.8443931937217712, 0.7801687717437744
Step 5 | Training Loss: 0.559508 | Validation Accuracy: 0.871032
Accuracy on Test data: 0.8792583346366882, 0.7829535603523254
Step 6 | Training Loss: 0.548479 | Validation Accuracy: 0.915476
Accuracy on Test data: 0.8854240775108337, 0.7903797626495361
Step 7 | Training Loss: 0.514406 | Validation Accuracy: 0.923413
Accuracy on Test data: 0.8904808163642883, 0.7994092702865601
Step 8 | Training Loss: 0.489972 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.8904364705085754, 0.7992405295372009
Step 9 | Training Loss: 0.494152 | Validation Accuracy: 0.935317
Accuracy on Test data: 0.8896380662918091, 0.796708881855011
Step 10 | Training Loss: 0.453773 | Validation Accuracy: 0.939683
Accuracy on Test data: 0.8880411386489868, 0.7934176921844482
Step 1 | Training Loss: 0.454881 | Validation Accuracy: 0.932143
Accuracy on Test data: 0.8877750039100647, 0.7928270101547241
Step 2 | Training Loss: 0.482963 | Validation Accuracy: 0.937698
Accuracy on Test data: 0.8875088691711426, 0.7924050688743591
Step 3 | Training Loss: 0.443929 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8874645233154297, 0.7922362685203552
Step 4 | Training Loss: 0.446339 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.8871539831161499, 0.7916455864906311
Step 5 | Training Loss: 0.485699 | Validation Accuracy: 0.929762
Accuracy on Test data: 0.8871983885765076, 0.7917299866676331
Step 6 | Training Loss: 0.427288 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8867548108100891, 0.7908017039299011
Step 7 | Training Loss: 0.451785 | Validation Accuracy: 0.940476
Accuracy on Test data: 0.8866660594940186, 0.7907173037528992
Step 8 | Training Loss: 0.433219 | Validation Accuracy: 0.941667
Accuracy on Test data: 0.8864886164665222, 0.7902953624725342
Step 9 | Training Loss: 0.426709 | Validation Accuracy: 0.932143
Accuracy on Test data: 0.8861337900161743, 0.7894514799118042
Step 10 | Training Loss: 0.421854 | Validation Accuracy: 0.938492
Accuracy on Test data: 0.8858676552772522, 0.7889451384544373
Current Layer Attributes - epochs:10 hidden layers:3 features count:1
Step 1 | Training Loss: 0.693142 | Validation Accuracy: 0.519841
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.693118 | Validation Accuracy: 0.513095
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.693104 | Validation Accuracy: 0.538095
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.692932 | Validation Accuracy: 0.520635
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.692336 | Validation Accuracy: 0.532937
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692944 | Validation Accuracy: 0.519048
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692493 | Validation Accuracy: 0.522222
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.693355 | Validation Accuracy: 0.539683
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.692225 | Validation Accuracy: 0.521032
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.692323 | Validation Accuracy: 0.535714
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 1 | Training Loss: 0.692814 | Validation Accuracy: 0.527381
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 2 | Training Loss: 0.692811 | Validation Accuracy: 0.535317
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 3 | Training Loss: 0.692502 | Validation Accuracy: 0.523016
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 4 | Training Loss: 0.693627 | Validation Accuracy: 0.525000
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 5 | Training Loss: 0.692594 | Validation Accuracy: 0.545238
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 6 | Training Loss: 0.692589 | Validation Accuracy: 0.524206
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 7 | Training Loss: 0.692584 | Validation Accuracy: 0.534524
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 8 | Training Loss: 0.692152 | Validation Accuracy: 0.525000
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 9 | Training Loss: 0.693542 | Validation Accuracy: 0.551984
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Step 10 | Training Loss: 0.692786 | Validation Accuracy: 0.544841
Accuracy on Test data: 0.43075764179229736, 0.18160337209701538
Current Layer Attributes - epochs:10 hidden layers:3 features count:12
Step 1 | Training Loss: 0.727892 | Validation Accuracy: 0.693651
Accuracy on Test data: 0.6739265322685242, 0.43628692626953125
Step 2 | Training Loss: 0.651970 | Validation Accuracy: 0.727381
Accuracy on Test data: 0.690693736076355, 0.450126588344574
Step 3 | Training Loss: 0.677152 | Validation Accuracy: 0.759524
Accuracy on Test data: 0.7102998495101929, 0.4703797399997711
Step 4 | Training Loss: 0.630961 | Validation Accuracy: 0.795238
Accuracy on Test data: 0.7173970937728882, 0.48118144273757935
Step 5 | Training Loss: 0.691499 | Validation Accuracy: 0.808730
Accuracy on Test data: 0.7257363200187683, 0.4947679340839386
Step 6 | Training Loss: 0.645986 | Validation Accuracy: 0.823413
Accuracy on Test data: 0.729284942150116, 0.499578058719635
Step 7 | Training Loss: 0.628049 | Validation Accuracy: 0.834127
Accuracy on Test data: 0.7307487726211548, 0.501603364944458
Step 8 | Training Loss: 0.625487 | Validation Accuracy: 0.855952
Accuracy on Test data: 0.7330553531646729, 0.504472553730011
Step 9 | Training Loss: 0.589104 | Validation Accuracy: 0.861905
Accuracy on Test data: 0.7397090196609497, 0.5164557099342346
Step 10 | Training Loss: 0.570778 | Validation Accuracy: 0.867460
Accuracy on Test data: 0.7505322694778442, 0.5358649492263794
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Accuracy on Test data: 0.7510202527046204, 0.5365400910377502
Step 2 | Training Loss: 0.588785 | Validation Accuracy: 0.877381
Accuracy on Test data: 0.7518630027770996, 0.5381434559822083
Step 3 | Training Loss: 0.573079 | Validation Accuracy: 0.885317
Accuracy on Test data: 0.7523953318595886, 0.5391561388969421
Step 4 | Training Loss: 0.574406 | Validation Accuracy: 0.863095
Accuracy on Test data: 0.7530163526535034, 0.5403375625610352
Step 5 | Training Loss: 0.580861 | Validation Accuracy: 0.880556
Accuracy on Test data: 0.7536373138427734, 0.5415189862251282
Step 6 | Training Loss: 0.615947 | Validation Accuracy: 0.887698
Accuracy on Test data: 0.754036545753479, 0.5421940684318542
Step 7 | Training Loss: 0.605499 | Validation Accuracy: 0.886905
Accuracy on Test data: 0.754347026348114, 0.5427848100662231
Step 8 | Training Loss: 0.628538 | Validation Accuracy: 0.886905
Accuracy on Test data: 0.754879355430603, 0.543797492980957
Step 9 | Training Loss: 0.570749 | Validation Accuracy: 0.891270
Accuracy on Test data: 0.7554559707641602, 0.5448945164680481
Step 10 | Training Loss: 0.599167 | Validation Accuracy: 0.895635
Accuracy on Test data: 0.7560326457023621, 0.545907199382782
Current Layer Attributes - epochs:10 hidden layers:3 features count:24
Step 1 | Training Loss: 0.719382 | Validation Accuracy: 0.650794
Accuracy on Test data: 0.5951029062271118, 0.3421940803527832
Step 2 | Training Loss: 0.713435 | Validation Accuracy: 0.766270
Accuracy on Test data: 0.6786727905273438, 0.40911391377449036
Step 3 | Training Loss: 0.682904 | Validation Accuracy: 0.778175
Accuracy on Test data: 0.6959723234176636, 0.44033753871917725
Step 4 | Training Loss: 0.731447 | Validation Accuracy: 0.826587
Accuracy on Test data: 0.7077714800834656, 0.46084389090538025
Step 5 | Training Loss: 0.642505 | Validation Accuracy: 0.840079
Accuracy on Test data: 0.7198367714881897, 0.48219409584999084
Step 6 | Training Loss: 0.629227 | Validation Accuracy: 0.850794
Accuracy on Test data: 0.7305269837379456, 0.50168776512146
Step 7 | Training Loss: 0.641998 | Validation Accuracy: 0.848810
Accuracy on Test data: 0.7376242280006409, 0.5149366855621338
Step 8 | Training Loss: 0.629238 | Validation Accuracy: 0.850794
Accuracy on Test data: 0.7460521459579468, 0.5300421714782715
Step 9 | Training Loss: 0.630353 | Validation Accuracy: 0.871825
Accuracy on Test data: 0.7575408220291138, 0.551476776599884
Step 10 | Training Loss: 0.582988 | Validation Accuracy: 0.871825
Accuracy on Test data: 0.7660131454467773, 0.5661603212356567
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Accuracy on Test data: 0.7672995328903198, 0.5684388279914856
Step 2 | Training Loss: 0.571080 | Validation Accuracy: 0.875397
Accuracy on Test data: 0.7684971690177917, 0.5704641342163086
Step 3 | Training Loss: 0.563159 | Validation Accuracy: 0.883333
Accuracy on Test data: 0.7696061134338379, 0.5724050402641296
Step 4 | Training Loss: 0.585291 | Validation Accuracy: 0.881349
Accuracy on Test data: 0.7702714800834656, 0.5735865235328674
Step 5 | Training Loss: 0.607150 | Validation Accuracy: 0.865079
Accuracy on Test data: 0.7705819606781006, 0.5741772055625916
Step 6 | Training Loss: 0.632317 | Validation Accuracy: 0.880952
Accuracy on Test data: 0.771025538444519, 0.5750210881233215
Step 7 | Training Loss: 0.567099 | Validation Accuracy: 0.881349
Accuracy on Test data: 0.7712916731834412, 0.5755274295806885
Step 8 | Training Loss: 0.571259 | Validation Accuracy: 0.880159
Accuracy on Test data: 0.7717352509498596, 0.5763713121414185
Step 9 | Training Loss: 0.620894 | Validation Accuracy: 0.865476
Accuracy on Test data: 0.7723562717437744, 0.5775527358055115
Step 10 | Training Loss: 0.559228 | Validation Accuracy: 0.879365
Accuracy on Test data: 0.7731547355651855, 0.5789873600006104
Current Layer Attributes - epochs:10 hidden layers:3 features count:48
Step 1 | Training Loss: 0.706394 | Validation Accuracy: 0.559524
Accuracy on Test data: 0.6743701100349426, 0.8024472594261169
Step 2 | Training Loss: 0.647156 | Validation Accuracy: 0.704365
Accuracy on Test data: 0.8287792801856995, 0.8059071898460388
Step 3 | Training Loss: 0.656966 | Validation Accuracy: 0.749206
Accuracy on Test data: 0.8483853936195374, 0.8061603307723999
Step 4 | Training Loss: 0.634181 | Validation Accuracy: 0.828175
Accuracy on Test data: 0.8822746872901917, 0.8443037867546082
Step 5 | Training Loss: 0.647169 | Validation Accuracy: 0.847222
Accuracy on Test data: 0.9095103144645691, 0.8741772174835205
Step 6 | Training Loss: 0.591617 | Validation Accuracy: 0.869048
Accuracy on Test data: 0.9012597799301147, 0.8414345979690552
Step 7 | Training Loss: 0.616981 | Validation Accuracy: 0.871429
Accuracy on Test data: 0.8947391510009766, 0.8223628401756287
Step 8 | Training Loss: 0.588465 | Validation Accuracy: 0.913095
Accuracy on Test data: 0.891146183013916, 0.8046413660049438
Step 9 | Training Loss: 0.609957 | Validation Accuracy: 0.924603
Accuracy on Test data: 0.8840933442115784, 0.7864134907722473
Step 10 | Training Loss: 0.567523 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.869277834892273, 0.7562869191169739
Step 1 | Training Loss: 0.587105 | Validation Accuracy: 0.926984
Accuracy on Test data: 0.8688786625862122, 0.7554430365562439
Step 2 | Training Loss: 0.583821 | Validation Accuracy: 0.917063
Accuracy on Test data: 0.8689673542976379, 0.7554430365562439
Step 3 | Training Loss: 0.580775 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8684794306755066, 0.75443035364151
Step 4 | Training Loss: 0.570522 | Validation Accuracy: 0.928175
Accuracy on Test data: 0.8679471015930176, 0.753248929977417
Step 5 | Training Loss: 0.528829 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8668825626373291, 0.751223623752594
Step 6 | Training Loss: 0.580121 | Validation Accuracy: 0.925397
Accuracy on Test data: 0.8650195002555847, 0.7476793527603149
Step 7 | Training Loss: 0.557064 | Validation Accuracy: 0.930159
Accuracy on Test data: 0.8644428849220276, 0.7465822696685791
Step 8 | Training Loss: 0.564991 | Validation Accuracy: 0.931746
Accuracy on Test data: 0.8641323447227478, 0.745907187461853
Step 9 | Training Loss: 0.583907 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8636887669563293, 0.745063304901123
Step 10 | Training Loss: 0.538996 | Validation Accuracy: 0.937302
Accuracy on Test data: 0.8636000752449036, 0.7448945045471191
Current Layer Attributes - epochs:10 hidden layers:3 features count:122
Step 1 | Training Loss: 0.722231 | Validation Accuracy: 0.680159
Accuracy on Test data: 0.617237389087677, 0.44995781779289246
Step 2 | Training Loss: 0.662457 | Validation Accuracy: 0.818254
Accuracy on Test data: 0.758915901184082, 0.5577214956283569
Step 3 | Training Loss: 0.641045 | Validation Accuracy: 0.871429
Accuracy on Test data: 0.8162704110145569, 0.6623628735542297
Step 4 | Training Loss: 0.624617 | Validation Accuracy: 0.891270
Accuracy on Test data: 0.8206174373626709, 0.6696202754974365
Step 5 | Training Loss: 0.562983 | Validation Accuracy: 0.901984
Accuracy on Test data: 0.7996806502342224, 0.6282700300216675
Step 6 | Training Loss: 0.583474 | Validation Accuracy: 0.907540
Accuracy on Test data: 0.8024308085441589, 0.6324050426483154
Step 7 | Training Loss: 0.557322 | Validation Accuracy: 0.909524
Accuracy on Test data: 0.7997249960899353, 0.6267510652542114
Step 8 | Training Loss: 0.501231 | Validation Accuracy: 0.923810
Accuracy on Test data: 0.7991483211517334, 0.6245569586753845
Step 9 | Training Loss: 0.492655 | Validation Accuracy: 0.923810
Accuracy on Test data: 0.8006564974784851, 0.6273417472839355
Step 10 | Training Loss: 0.480259 | Validation Accuracy: 0.934921
Accuracy on Test data: 0.8014993071556091, 0.6288607716560364
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Accuracy on Test data: 0.8017210960388184, 0.6292827129364014
Step 2 | Training Loss: 0.451087 | Validation Accuracy: 0.932540
Accuracy on Test data: 0.8017654418945312, 0.6293671131134033
Step 3 | Training Loss: 0.459189 | Validation Accuracy: 0.928571
Accuracy on Test data: 0.8018097877502441, 0.6294514536857605
Step 4 | Training Loss: 0.487975 | Validation Accuracy: 0.930952
Accuracy on Test data: 0.8018097877502441, 0.6294514536857605
Step 5 | Training Loss: 0.474214 | Validation Accuracy: 0.933730
Accuracy on Test data: 0.8018097877502441, 0.6294514536857605
Step 6 | Training Loss: 0.425902 | Validation Accuracy: 0.925000
Accuracy on Test data: 0.8018985390663147, 0.6296202540397644
Step 7 | Training Loss: 0.486625 | Validation Accuracy: 0.927778
Accuracy on Test data: 0.8019428849220276, 0.6296202540397644
Step 8 | Training Loss: 0.484455 | Validation Accuracy: 0.936111
Accuracy on Test data: 0.8021646738052368, 0.6300421953201294
Step 9 | Training Loss: 0.465279 | Validation Accuracy: 0.926190
Accuracy on Test data: 0.8022090196609497, 0.6301265954971313
Step 10 | Training Loss: 0.417278 | Validation Accuracy: 0.934127
Accuracy on Test data: 0.8022533655166626, 0.6302109956741333
2min 50s ± 9.38 s per loop (mean ± std. dev. of 10 runs, 1 loop each)

In [ ]:

    




    

In [ ]:

    




    

In [11]:

    

g = df_results.groupby(by=['no_of_features'])
idx = g['test_score'].transform(max) == df_results['test_score']
df_results[idx].sort_values(by = 'test_score', ascending = False)


    

    
Out[11]:







  

    

      

      
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test_score_20
      
time_taken
    
  
  

    

      
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5.548434
    
    

      
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15.698435
    
    

      
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0.808242
      
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16.788981
    
    

      
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0.773155
      
0.578987
      
21.901474
    
  

In [12]:

    

g = df_results.groupby(by=['no_of_features'])
idx = g['test_score_20'].transform(max) == df_results['test_score_20']
df_results[idx].sort_values(by = 'test_score_20', ascending = False)


    

    
Out[12]:







  

    

      

      
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hidden_layers
      
train_score
      
test_score
      
test_score_20
      
time_taken
    
  
  

    

      
98
      
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0.890481
      
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15.698435
    
    

      
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1
      
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0.808242
      
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16.788981
    
    

      
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24
      
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0.773155
      
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21.901474
    
  

In [13]:

    

df_results.sort_values(by = 'test_score', ascending = False)


    

    
Out[13]:







  

    

      

      
epoch
      
no_of_features
      
hidden_layers
      
train_score
      
test_score
      
test_score_20
      
time_taken
    
  
  

    

      
98
      
6
      
48
      
3
      
0.847222
      
0.909510
      
0.874177
      
5.548434
    
    

      
60
      
8
      
122
      
1
      
0.923413
      
0.890481
      
0.799409
      
6.170311
    
    

      
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122
      
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0.915476
      
0.885424
      
0.790380
      
5.214121
    
    

      
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0.882275
      
0.844304
      
4.351358
    
    

      
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0.782954
      
4.389015
    
    

      
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0.848385
      
0.806160
      
3.141691
    
    

      
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0.844393
      
0.780169
      
3.541118
    
    

      
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0.828779
      
0.805907
      
2.006240
    
    

      
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0.820751
      
0.667764
      
15.698435
    
    

      
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0.820662
      
0.667764
      
14.949828
    
    

      
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0.891270
      
0.820617
      
0.669620
      
5.514633
    
    

      
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0.902778
      
0.820484
      
0.667426
      
14.090263
    
    

      
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0.901190
      
0.820351
      
0.667257
      
13.258659
    
    

      
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0.905952
      
0.820041
      
0.667173
      
12.505358
    
    

      
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0.911508
      
0.819819
      
0.666920
      
11.752340
    
    

      
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0.819730
      
0.667004
      
9.238146
    
    

      
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0.819597
      
0.666835
      
8.278834
    
    

      
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7.436796
    
    

      
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4.178486
    
    

      
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0.752489
      
2.637325
    
    

      
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0.813121
      
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6.647932
    
    

      
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16.788981
    
    

      
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0.642278
      
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15.144928
    
    

      
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10.743485
    
    

      
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9.115473
    
    

      
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0.770271
      
0.573587
      
15.240586
    
    

      
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0.769606
      
0.572405
      
14.196526
    
    

      
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0.769473
      
0.568776
      
5.267488
    
    

      
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0.875397
      
0.768497
      
0.570464
      
13.085671
    
    

      
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0.880556
      
0.767300
      
0.568439
      
12.012670
    
    

      
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0.766013
      
0.566160
      
11.000057
    
    

      
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0.925397
      
0.759448
      
0.550717
      
6.679805
    
    

      
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0.758916
      
0.557721
      
2.804342
    
    

      
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0.687698
      
0.756476
      
0.716709
      
1.618722
    
    

      
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0.756033
      
0.545907
      
20.815290
    
    

      
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0.755456
      
0.544895
      
19.615030
    
    

      
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0.754879
      
0.543797
      
18.620883
    
    

      
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0.754347
      
0.542785
      
17.690050
    
    

      
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0.754037
      
0.542194
      
16.709647
    
    

      
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0.753637
      
0.541519
      
15.785249
    
    

      
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0.753016
      
0.540338
      
14.873307
    
    

      
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0.852778
      
0.752706
      
0.544641
      
1.611163
    
    

      
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0.885317
      
0.752395
      
0.539156
      
13.678719
    
    

      
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0.877381
      
0.751863
      
0.538143
      
12.616991
    
    

      
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0.871429
      
0.751020
      
0.536540
      
11.616187
    
    

      
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0.867460
      
0.750532
      
0.535865
      
10.612506
    
    

      
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24
      
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0.850794
      
0.746052
      
0.530042
      
8.713374
    
    

      
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6
      
24
      
1
      
0.902381
      
0.740774
      
0.516118
      
4.414896
    
    

      
69
      
9
      
12
      
3
      
0.855952
      
0.733055
      
0.504473
      
8.419276
    
    

      
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7
      
24
      
3
      
0.850794
      
0.730527
      
0.501688
      
6.662893
    
    

      
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7
      
12
      
3
      
0.823413
      
0.729285
      
0.499578
      
6.426563
    
    

      
35
      
5
      
24
      
1
      
0.868651
      
0.717530
      
0.477468
      
3.516901
    
    

      
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5
      
12
      
3
      
0.795238
      
0.717397
      
0.481181
      
4.444997
    
    

      
43
      
7
      
48
      
1
      
0.886508
      
0.710877
      
0.460253
      
5.038838
    
    

      
34
      
4
      
24
      
1
      
0.796429
      
0.707771
      
0.462785
      
2.827811
    
    

      
81
      
5
      
24
      
3
      
0.826587
      
0.707771
      
0.460844
      
4.514104
    
    

      
0
      
2
      
1
      
1
      
0.767857
      
0.705642
      
0.481857
      
0.924821
    
    

      
33
      
3
      
24
      
1
      
0.763492
      
0.695751
      
0.443038
      
1.977054
    
    

      
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3
      
12
      
3
      
0.727381
      
0.690694
      
0.450127
      
2.462493
    
    

      
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24
      
1
      
0.716667
      
0.682976
      
0.428776
      
1.139127
    
    

      
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3
      
0.766270
      
0.678673
      
0.409114
      
2.178618
    
    

      
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48
      
3
      
0.559524
      
0.674370
      
0.802447
      
1.035756
    
    

      
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12
      
3
      
0.693651
      
0.673927
      
0.436287
      
1.274621
    
    

      
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12
      
1
      
0.629762
      
0.661373
      
0.617300
      
0.848062
    
    

      
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48
      
1
      
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0.647578
      
0.343291
      
3.499857
    
    

      
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122
      
3
      
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0.617237
      
0.449958
      
1.446712
    
    

      
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122
      
1
      
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0.610007
      
0.698819
      
0.926697
    
    

      
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24
      
3
      
0.650794
      
0.595103
      
0.342194
      
1.068785
    
    

      
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48
      
1
      
0.746032
      
0.521735
      
0.265992
      
1.698168
    
    

      
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48
      
1
      
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0.490552
      
0.241519
      
0.857782
    
    

      
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1
      
3
      
0.519841
      
0.430758
      
0.181603
      
1.069580
    
  

In [14]:

    

pd.Panel(Train.predictions).to_pickle("dataset/tf_dense_only_nsl_kdd_predictions-.pkl")
pd.Panel(Train.predictions_).to_pickle("dataset/tf_dense_only_nsl_kdd_predictions-__.pkl")

df_results.to_pickle("dataset/tf_dense_only_nsl_kdd_scores-.pkl")


    

In [15]:

    

import numpy as np
import matplotlib.pyplot as plt
import itertools

def plot_confusion_matrix(cm, classes,
                          normalize=False,
                          title='Confusion matrix',
                          cmap=plt.cm.Blues):
    """
    This function prints and plots the confusion matrix.
    Normalization can be applied by setting `normalize=True`.
    """
    np.set_printoptions(precision=4)

    plt.imshow(cm, interpolation='nearest', cmap=cmap)
    plt.title(title)
    plt.colorbar()
    tick_marks = np.arange(len(classes))
    plt.xticks(tick_marks, classes, rotation=45)
    plt.yticks(tick_marks, classes)

    if normalize:
        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
        print("Normalized confusion matrix")
    else:
        print('Confusion matrix, without normalization')

    print(cm)

    thresh = cm.max() / 2.
    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):
        plt.text(j, i, cm[i, j].round(4),
                 horizontalalignment="center",
                 color="white" if cm[i, j] > thresh else "black")

    plt.tight_layout()
    plt.ylabel('True label')
    plt.xlabel('Predicted label')

def plot(actual_value, pred_value):
    from sklearn.metrics import confusion_matrix
    cm_2labels = confusion_matrix(y_pred = pred_value, y_true = actual_value)
    plt.figure(figsize=[6,6])
    plot_confusion_matrix(cm_2labels, preprocess.output_columns_2labels, normalize = True,
                         title = Train.best_parameters)


    

In [16]:

    

plot(actual_value = Train.actual_value, pred_value = Train.pred_value)


    

    




Normalized confusion matrix
[[ 0.8359  0.1641]
 [ 0.0348  0.9652]]






    

In [17]:

    

plot(actual_value = Train.actual_value_, pred_value = Train.pred_value_)


    

    




Normalized confusion matrix
[[ 0.5144  0.4856]
 [ 0.046   0.954 ]]






    

In [18]:

    

past_scores = pd.read_pickle("dataset/tf_dense_only_nsl_kdd_scores_all-.pkl")


    

In [19]:

    

past_scores


    

    
Out[19]:







  

    

      

      

      
epoch
      
train_score
      
test_score
      
test_score_20
      
time_taken
    
    

      
no_of_features
      
hidden_layers
      

      

      

      

      

    
  
  

    

      
1
      
1
      
2
      
0.500000
      
0.583259
      
0.823207
      
1.737384
    
    

      
1
      
3
      
0.773810
      
0.853132
      
0.821350
      
2.746407
    
    

      
1
      
4
      
0.819444
      
0.873181
      
0.817215
      
3.780096
    
    

      
1
      
5
      
0.857143
      
0.885247
      
0.815274
      
4.823596
    
    

      
1
      
6
      
0.858730
      
0.886533
      
0.812489
      
5.901322
    
    

      
8
      
1
      
2
      
0.552778
      
0.696460
      
0.657553
      
1.041274
    
    

      
1
      
3
      
0.641667
      
0.776393
      
0.669705
      
2.013830
    
    

      
1
      
4
      
0.681746
      
0.800435
      
0.688439
      
3.030958
    
    

      
1
      
5
      
0.791270
      
0.834634
      
0.718987
      
4.018355
    
    

      
1
      
6
      
0.851587
      
0.848829
      
0.738228
      
4.996470
    
    

      
1
      
7
      
0.872222
      
0.855305
      
0.746414
      
5.974369
    
    

      
1
      
8
      
0.892063
      
0.861693
      
0.757637
      
7.018800
    
    

      
1
      
9
      
0.909921
      
0.862890
      
0.759409
      
8.021910
    
    

      
32
      
1
      
2
      
0.724603
      
0.734120
      
0.525485
      
1.510834
    
    

      
1
      
3
      
0.771825
      
0.750665
      
0.542785
      
2.517899
    
    

      
1
      
4
      
0.911905
      
0.814319
      
0.651308
      
11.737579
    
    

      
1
      
5
      
0.830952
      
0.786152
      
0.606245
      
4.757215
    
    

      
1
      
6
      
0.922619
      
0.814807
      
0.652827
      
12.685921
    
    

      
1
      
7
      
0.868651
      
0.796576
      
0.623460
      
6.851718
    
    

      
1
      
8
      
0.931349
      
0.815871
      
0.654430
      
13.714334
    
    

      
1
      
9
      
0.894048
      
0.806379
      
0.640928
      
8.793038
    
    

      
1
      
10
      
0.905952
      
0.809173
      
0.644810
      
9.762101
    
    

      
1
      
11
      
0.922222
      
0.812544
      
0.648692
      
10.796256
    
    

      
122
      
1
      
2
      
0.679365
      
0.775328
      
0.778819
      
0.966112
    
    

      
1
      
3
      
0.798810
      
0.852466
      
0.768692
      
2.016091
    
    

      
1
      
4
      
0.860317
      
0.879702
      
0.804810
      
3.078858
    
    

      
1
      
5
      
0.885714
      
0.892965
      
0.813502
      
4.012818
    
    

      
1
      
6
      
0.894048
      
0.896425
      
0.816203
      
5.040853
    
    

      
1
      
3
      
2
      
0.538492
      
0.430758
      
0.181603
      
1.323962
    
    

      
8
      
3
      
2
      
0.486508
      
0.553584
      
0.777300
      
1.417094
    
    

      
3
      
3
      
0.734127
      
0.799104
      
0.784473
      
2.576081
    
    

      
3
      
4
      
0.774603
      
0.841820
      
0.804979
      
3.832223
    
    

      
3
      
5
      
0.785714
      
0.857745
      
0.814430
      
5.245420
    
    

      
3
      
6
      
0.811111
      
0.861382
      
0.805823
      
6.504427
    
    

      
3
      
7
      
0.843651
      
0.871540
      
0.804473
      
7.869504
    
    

      
3
      
8
      
0.869841
      
0.880988
      
0.799578
      
9.173052
    
    

      
3
      
9
      
0.894048
      
0.884847
      
0.796540
      
10.463114
    
    

      
32
      
3
      
2
      
0.776190
      
0.749202
      
0.626414
      
1.831090
    
    

      
3
      
3
      
0.842857
      
0.786773
      
0.629705
      
3.321462
    
    

      
3
      
4
      
0.875000
      
0.803983
      
0.643122
      
4.869611
    
    

      
3
      
5
      
0.882937
      
0.805492
      
0.641857
      
6.326309
    
    

      
122
      
3
      
2
      
0.722222
      
0.736072
      
0.587342
      
2.207851
    
    

      
3
      
3
      
0.858730
      
0.842486
      
0.737890
      
4.287650
    
    

      
3
      
4
      
0.903571
      
0.868701
      
0.771308
      
6.335766
    
    

      
1
      
5
      
2
      
0.553968
      
0.430758
      
0.181603
      
1.559099
    
    

      
8
      
5
      
2
      
0.423016
      
0.321061
      
0.499325
      
1.659954
    
    

      
5
      
3
      
0.540079
      
0.414257
      
0.487511
      
3.252145
    
    

      
5
      
4
      
0.620238
      
0.485318
      
0.471561
      
5.009747
    
    

      
5
      
6
      
0.679762
      
0.507630
      
0.443966
      
7.373743
    
    

      
5
      
7
      
0.724206
      
0.560903
      
0.440506
      
8.960562
    
    

      
5
      
8
      
0.773413
      
0.584546
      
0.432068
      
10.671936
    
    

      
32
      
5
      
2
      
0.553571
      
0.483898
      
0.326329
      
2.087397
    
    

      
5
      
3
      
0.621825
      
0.524973
      
0.344473
      
4.483478
    
    

      
5
      
4
      
0.876984
      
0.761089
      
0.572489
      
23.032310
    
    

      
5
      
5
      
0.709127
      
0.599273
      
0.387173
      
8.734228
    
    

      
5
      
6
      
0.924603
      
0.858721
      
0.741772
      
42.926213
    
    

      
5
      
7
      
0.748810
      
0.654986
      
0.459325
      
12.542290
    
    

      
5
      
8
      
0.905556
      
0.807044
      
0.652996
      
27.134876
    
    

      
5
      
9
      
0.925794
      
0.858854
      
0.742025
      
44.073521
    
    

      
5
      
10
      
0.906349
      
0.815871
      
0.665654
      
29.257227
    
    

      
5
      
11
      
0.838492
      
0.749068
      
0.554262
      
21.210851
    
    

      
5
      
12
      
0.937698
      
0.859519
      
0.743122
      
45.863152
    
    

      
5
      
14
      
0.913889
      
0.831840
      
0.692405
      
33.607411
    
    

      
5
      
16
      
0.923810
      
0.839070
      
0.705316
      
35.433949
    
    

      
5
      
18
      
0.926587
      
0.861027
      
0.745907
      
49.986061
    
    

      
5
      
20
      
0.936905
      
0.851801
      
0.728861
      
39.395359
    
    

      
5
      
22
      
0.924603
      
0.857745
      
0.739916
      
41.226033
    
    

      
5
      
15
      
0.927381
      
0.860140
      
0.744304
      
47.749661
    
    

      
5
      
21
      
0.926984
      
0.861160
      
0.746160
      
51.940331
    
    

      
5
      
27
      
0.929762
      
0.861560
      
0.746751
      
54.844048
    
    

      
5
      
30
      
0.924603
      
0.861648
      
0.746920
      
56.632432
    
    

      
5
      
33
      
0.937698
      
0.861737
      
0.747089
      
58.477479
    
    

      
122
      
5
      
2
      
0.742460
      
0.748758
      
0.637637
      
3.137511
    
    

      
5
      
3
      
0.792460
      
0.791031
      
0.662700
      
6.090391
    
    

      
5
      
4
      
0.848810
      
0.807177
      
0.669620
      
9.000678
    
    

      
5
      
5
      
0.898810
      
0.810016
      
0.657890
      
11.817174
    
    

      
1
      
1
      
2
      
0.500000
      
0.583259
      
0.823207
      
1.737384
    
    

      
1
      
3
      
0.773810
      
0.853132
      
0.821350
      
2.746407
    
    

      
1
      
4
      
0.819444
      
0.873181
      
0.817215
      
3.780096
    
    

      
1
      
5
      
0.857143
      
0.885247
      
0.815274
      
4.823596
    
    

      
1
      
6
      
0.858730
      
0.886533
      
0.812489
      
5.901322
    
    

      
8
      
1
      
2
      
0.552778
      
0.696460
      
0.657553
      
1.041274
    
    

      
1
      
3
      
0.641667
      
0.776393
      
0.669705
      
2.013830
    
    

      
1
      
4
      
0.681746
      
0.800435
      
0.688439
      
3.030958
    
    

      
1
      
5
      
0.791270
      
0.834634
      
0.718987
      
4.018355
    
    

      
1
      
6
      
0.851587
      
0.848829
      
0.738228
      
4.996470
    
    

      
1
      
7
      
0.872222
      
0.855305
      
0.746414
      
5.974369
    
    

      
1
      
8
      
0.892063
      
0.861693
      
0.757637
      
7.018800
    
    

      
1
      
9
      
0.909921
      
0.862890
      
0.759409
      
8.021910
    
    

      
32
      
1
      
2
      
0.724603
      
0.734120
      
0.525485
      
1.510834
    
    

      
1
      
3
      
0.771825
      
0.750665
      
0.542785
      
2.517899
    
    

      
1
      
4
      
0.911905
      
0.814319
      
0.651308
      
11.737579
    
    

      
1
      
5
      
0.830952
      
0.786152
      
0.606245
      
4.757215
    
    

      
1
      
6
      
0.922619
      
0.814807
      
0.652827
      
12.685921
    
    

      
1
      
7
      
0.868651
      
0.796576
      
0.623460
      
6.851718
    
    

      
1
      
8
      
0.931349
      
0.815871
      
0.654430
      
13.714334
    
    

      
1
      
9
      
0.894048
      
0.806379
      
0.640928
      
8.793038
    
    

      
1
      
10
      
0.905952
      
0.809173
      
0.644810
      
9.762101
    
    

      
1
      
11
      
0.922222
      
0.812544
      
0.648692
      
10.796256
    
    

      
122
      
1
      
2
      
0.679365
      
0.775328
      
0.778819
      
0.966112
    
    

      
1
      
3
      
0.798810
      
0.852466
      
0.768692
      
2.016091
    
    

      
1
      
4
      
0.860317
      
0.879702
      
0.804810
      
3.078858
    
    

      
1
      
5
      
0.885714
      
0.892965
      
0.813502
      
4.012818
    
    

      
1
      
6
      
0.894048
      
0.896425
      
0.816203
      
5.040853
    
    

      
1
      
3
      
2
      
0.538492
      
0.430758
      
0.181603
      
1.323962
    
    

      
8
      
3
      
2
      
0.486508
      
0.553584
      
0.777300
      
1.417094
    
    

      
3
      
3
      
0.734127
      
0.799104
      
0.784473
      
2.576081
    
    

      
3
      
4
      
0.774603
      
0.841820
      
0.804979
      
3.832223
    
    

      
3
      
5
      
0.785714
      
0.857745
      
0.814430
      
5.245420
    
    

      
3
      
6
      
0.811111
      
0.861382
      
0.805823
      
6.504427
    
    

      
3
      
7
      
0.843651
      
0.871540
      
0.804473
      
7.869504
    
    

      
3
      
8
      
0.869841
      
0.880988
      
0.799578
      
9.173052
    
    

      
3
      
9
      
0.894048
      
0.884847
      
0.796540
      
10.463114
    
    

      
32
      
3
      
2
      
0.776190
      
0.749202
      
0.626414
      
1.831090
    
    

      
3
      
3
      
0.842857
      
0.786773
      
0.629705
      
3.321462
    
    

      
3
      
4
      
0.875000
      
0.803983
      
0.643122
      
4.869611
    
    

      
3
      
5
      
0.882937
      
0.805492
      
0.641857
      
6.326309
    
    

      
122
      
3
      
2
      
0.722222
      
0.736072
      
0.587342
      
2.207851
    
    

      
3
      
3
      
0.858730
      
0.842486
      
0.737890
      
4.287650
    
    

      
3
      
4
      
0.903571
      
0.868701
      
0.771308
      
6.335766
    
    

      
1
      
5
      
2
      
0.553968
      
0.430758
      
0.181603
      
1.559099
    
    

      
8
      
5
      
2
      
0.423016
      
0.321061
      
0.499325
      
1.659954
    
    

      
5
      
3
      
0.540079
      
0.414257
      
0.487511
      
3.252145
    
    

      
5
      
4
      
0.620238
      
0.485318
      
0.471561
      
5.009747
    
    

      
5
      
6
      
0.679762
      
0.507630
      
0.443966
      
7.373743
    
    

      
5
      
7
      
0.724206
      
0.560903
      
0.440506
      
8.960562
    
    

      
5
      
8
      
0.773413
      
0.584546
      
0.432068
      
10.671936
    
    

      
32
      
5
      
2
      
0.553571
      
0.483898
      
0.326329
      
2.087397
    
    

      
5
      
3
      
0.621825
      
0.524973
      
0.344473
      
4.483478
    
    

      
5
      
4
      
0.876984
      
0.761089
      
0.572489
      
23.032310
    
    

      
5
      
5
      
0.709127
      
0.599273
      
0.387173
      
8.734228
    
    

      
5
      
6
      
0.924603
      
0.858721
      
0.741772
      
42.926213
    
    

      
5
      
7
      
0.748810
      
0.654986
      
0.459325
      
12.542290
    
    

      
5
      
8
      
0.905556
      
0.807044
      
0.652996
      
27.134876
    
    

      
5
      
9
      
0.925794
      
0.858854
      
0.742025
      
44.073521
    
    

      
5
      
10
      
0.906349
      
0.815871
      
0.665654
      
29.257227
    
    

      
5
      
11
      
0.838492
      
0.749068
      
0.554262
      
21.210851
    
    

      
5
      
12
      
0.937698
      
0.859519
      
0.743122
      
45.863152
    
    

      
5
      
14
      
0.913889
      
0.831840
      
0.692405
      
33.607411
    
    

      
5
      
16
      
0.923810
      
0.839070
      
0.705316
      
35.433949
    
    

      
5
      
18
      
0.926587
      
0.861027
      
0.745907
      
49.986061
    
    

      
5
      
20
      
0.936905
      
0.851801
      
0.728861
      
39.395359
    
    

      
5
      
22
      
0.924603
      
0.857745
      
0.739916
      
41.226033
    
    

      
5
      
15
      
0.927381
      
0.860140
      
0.744304
      
47.749661
    
    

      
5
      
21
      
0.926984
      
0.861160
      
0.746160
      
51.940331
    
    

      
5
      
27
      
0.929762
      
0.861560
      
0.746751
      
54.844048
    
    

      
5
      
30
      
0.924603
      
0.861648
      
0.746920
      
56.632432
    
    

      
5
      
33
      
0.937698
      
0.861737
      
0.747089
      
58.477479
    
    

      
122
      
5
      
2
      
0.742460
      
0.748758
      
0.637637
      
3.137511
    
    

      
5
      
3
      
0.792460
      
0.791031
      
0.662700
      
6.090391
    
    

      
5
      
4
      
0.848810
      
0.807177
      
0.669620
      
9.000678
    
    

      
5
      
5
      
0.898810
      
0.810016
      
0.657890
      
11.817174
    
    

      
1
      
1
      
2
      
0.752381
      
0.609430
      
0.435612
      
1.013389
    
    

      
1
      
3
      
0.800794
      
0.711631
      
0.468861
      
1.974355
    
    

      
1
      
4
      
0.942460
      
0.785442
      
0.596371
      
11.192840
    
    

      
1
      
5
      
0.862302
      
0.736781
      
0.511561
      
4.032335
    
    

      
1
      
6
      
0.950794
      
0.787571
      
0.598819
      
12.205366
    
    

      
1
      
7
      
0.909127
      
0.755279
      
0.543122
      
5.938341
    
    

      
1
      
8
      
0.951587
      
0.788502
      
0.599747
      
13.187299
    
    

      
1
      
9
      
0.932540
      
0.775018
      
0.579156
      
7.954791
    
    

      
1
      
10
      
0.930159
      
0.779143
      
0.586245
      
9.007837
    
    

      
1
      
11
      
0.932540
      
0.783224
      
0.592405
      
10.062756
    
    

      
8
      
1
      
2
      
0.305556
      
0.333659
      
0.559156
      
1.034562
    
    

      
1
      
3
      
0.513492
      
0.502750
      
0.648945
      
2.082721
    
    

      
1
      
4
      
0.947619
      
0.838183
      
0.693080
      
9.227789
    
    

      
1
      
5
      
0.850794
      
0.781804
      
0.705992
      
3.902641
    
    

      
1
      
6
      
0.953175
      
0.838361
      
0.693333
      
10.224311
    
    

      
32
      
1
      
2
      
0.553571
      
0.570884
      
0.553080
      
0.995917
    
    

      
1
      
3
      
0.734127
      
0.740641
      
0.601857
      
1.934400
    
    

      
1
      
4
      
0.826587
      
0.788369
      
0.651055
      
2.920137
    
    

      
1
      
5
      
0.863492
      
0.806556
      
0.665232
      
4.063429
    
    

      
1
      
6
      
0.897222
      
0.811214
      
0.662025
      
5.163448
    
    

      
122
      
1
      
2
      
0.757937
      
0.771425
      
0.584051
      
0.985263
    
    

      
1
      
3
      
0.792857
      
0.785885
      
0.606920
      
2.065951
    
    

      
1
      
4
      
0.830159
      
0.791785
      
0.617131
      
3.111821
    
    

      
1
      
5
      
0.834921
      
0.800257
      
0.632405
      
4.120334
    
    

      
1
      
6
      
0.841270
      
0.803673
      
0.637890
      
5.114748
    
    

      
1
      
7
      
0.863492
      
0.805758
      
0.641603
      
6.066829
    
    

      
1
      
8
      
0.901587
      
0.811968
      
0.652152
      
7.070870
    
    

      
1
      
3
      
2
      
0.531349
      
0.430758
      
0.181603
      
1.809197
    
    

      
8
      
3
      
2
      
0.451190
      
0.540454
      
0.759325
      
1.415778
    
    

      
3
      
3
      
0.575000
      
0.635468
      
0.745063
      
2.665348
    
    

      
3
      
4
      
0.908333
      
0.846966
      
0.724135
      
14.896438
    
    

      
3
      
6
      
0.912302
      
0.851180
      
0.729283
      
16.263383
    
    

      
3
      
7
      
0.809127
      
0.818178
      
0.694093
      
7.452541
    
    

      
3
      
8
      
0.926984
      
0.854640
      
0.735274
      
17.669458
    
    

      
3
      
9
      
0.861111
      
0.829400
      
0.701941
      
10.311922
    
    

      
3
      
10
      
0.930159
      
0.858055
      
0.740169
      
19.286822
    
    

      
3
      
11
      
0.890873
      
0.842708
      
0.719072
      
13.495634
    
    

      
3
      
12
      
0.947222
      
0.861160
      
0.740338
      
27.856055
    
    

      
3
      
14
      
0.934127
      
0.860939
      
0.743629
      
21.985776
    
    

      
3
      
15
      
0.939683
      
0.861737
      
0.741435
      
29.036748
    
    

      
3
      
18
      
0.944444
      
0.862314
      
0.742447
      
30.103149
    
    

      
3
      
21
      
0.947619
      
0.862713
      
0.743207
      
31.433573
    
    

      
3
      
24
      
0.948413
      
0.862890
      
0.743544
      
32.769451
    
    

      
32
      
3
      
2
      
0.545238
      
0.433109
      
0.184979
      
1.423730
    
    

      
3
      
3
      
0.660317
      
0.479196
      
0.196878
      
3.023336
    
    

      
3
      
4
      
0.928571
      
0.812500
      
0.651561
      
16.916582
    
    

      
3
      
5
      
0.774603
      
0.538103
      
0.304641
      
6.090839
    
    

      
3
      
6
      
0.945238
      
0.838094
      
0.699747
      
18.565713
    
    

      
3
      
7
      
0.841667
      
0.595369
      
0.404895
      
8.980543
    
    

      
3
      
8
      
0.946032
      
0.846123
      
0.713502
      
20.113684
    
    

      
3
      
9
      
0.897619
      
0.746851
      
0.529958
      
12.313494
    
    

      
3
      
10
      
0.911905
      
0.783268
      
0.596878
      
13.687260
    
    

      
3
      
11
      
0.928571
      
0.797330
      
0.623038
      
15.197614
    
    

      
122
      
3
      
2
      
0.746825
      
0.613778
      
0.283376
      
2.396187
    
    

      
3
      
3
      
0.821032
      
0.688165
      
0.417384
      
4.404867
    
    

      
3
      
4
      
0.937698
      
0.773377
      
0.574515
      
23.059733
    
    

      
3
      
5
      
0.888492
      
0.753194
      
0.539831
      
8.638499
    
    

      
3
      
6
      
0.935714
      
0.776748
      
0.580759
      
25.213438
    
    

      
3
      
7
      
0.898016
      
0.765747
      
0.561435
      
12.886271
    
    

      
3
      
8
      
0.940079
      
0.778877
      
0.584810
      
27.123679
    
    

      
3
      
9
      
0.911905
      
0.766812
      
0.563038
      
16.882940
    
    

      
3
      
10
      
0.950000
      
0.781716
      
0.590211
      
29.040926
    
    

      
3
      
11
      
0.925397
      
0.768408
      
0.565738
      
20.753421
    
    

      
3
      
12
      
0.950000
      
0.783357
      
0.593165
      
31.049070
    
    

      
1
      
5
      
2
      
0.555952
      
0.430758
      
0.181603
      
1.699689
    
    

      
8
      
5
      
2
      
0.489683
      
0.592308
      
0.793333
      
1.587398
    
    

      
5
      
3
      
0.518254
      
0.612802
      
0.778059
      
3.335802
    
    

      
5
      
6
      
0.836905
      
0.693444
      
0.592321
      
16.502883
    
    

      
5
      
7
      
0.734127
      
0.671620
      
0.639494
      
8.295849
    
    

      
5
      
8
      
0.754365
      
0.677564
      
0.600760
      
9.963014
    
    

      
5
      
10
      
0.770635
      
0.680092
      
0.580675
      
12.484927
    
    

      
5
      
4
      
0.831746
      
0.686879
      
0.581519
      
14.902415
    
    

      
32
      
5
      
2
      
0.550397
      
0.441004
      
0.200760
      
1.896466
    
    

      
5
      
3
      
0.564683
      
0.460699
      
0.237806
      
3.721369
    
    

      
5
      
4
      
0.830556
      
0.666918
      
0.382110
      
20.478017
    
    

      
5
      
5
      
0.578175
      
0.508428
      
0.257131
      
7.663091
    
    

      
5
      
6
      
0.898016
      
0.756343
      
0.542532
      
39.714115
    
    

      
5
      
7
      
0.658333
      
0.590002
      
0.282785
      
11.360219
    
    

      
5
      
8
      
0.851984
      
0.691625
      
0.424979
      
24.273933
    
    

      
5
      
9
      
0.907937
      
0.757008
      
0.543797
      
41.467146
    
    

      
5
      
10
      
0.872222
      
0.705908
      
0.449958
      
26.162183
    
    

      
5
      
11
      
0.810317
      
0.651570
      
0.354093
      
18.679377
    
    

      
5
      
12
      
0.891667
      
0.757674
      
0.545063
      
43.798101
    
    

      
5
      
14
      
0.894841
      
0.724361
      
0.483629
      
30.126800
    
    

      
5
      
16
      
0.888492
      
0.732080
      
0.498228
      
31.975581
    
    

      
5
      
18
      
0.894444
      
0.758605
      
0.546835
      
47.764469
    
    

      
5
      
20
      
0.896032
      
0.750177
      
0.530970
      
35.611126
    
    

      
5
      
22
      
0.903175
      
0.755722
      
0.541350
      
37.668527
    
    

      
5
      
15
      
0.903175
      
0.758206
      
0.546076
      
45.657773
    
    

      
5
      
21
      
0.896429
      
0.758872
      
0.547342
      
49.662081
    
    

      
5
      
24
      
0.897222
      
0.759315
      
0.548186
      
52.129842
    
    

      
5
      
27
      
0.894444
      
0.759581
      
0.548692
      
53.982351
    
    

      
5
      
30
      
0.887302
      
0.759892
      
0.549283
      
55.768187
    
    

      
5
      
33
      
0.895238
      
0.760114
      
0.549705
      
57.759473
    
    

      
122
      
5
      
2
      
0.394048
      
0.338449
      
0.311224
      
2.851944
    
    

      
5
      
3
      
0.688889
      
0.678007
      
0.499494
      
5.889095
    
    

      
5
      
4
      
0.862698
      
0.807754
      
0.662194
      
8.706509
    
    

      
5
      
5
      
0.881746
      
0.826384
      
0.692152
      
11.832607
    
    

      
5
      
6
      
0.890873
      
0.837917
      
0.712996
      
14.944608
    
    

      
5
      
7
      
0.905952
      
0.841022
      
0.717637
      
18.392418
    
    

      
5
      
8
      
0.906349
      
0.843861
      
0.722447
      
21.449749
    
    

      
5
      
9
      
0.900794
      
0.844881
      
0.723882
      
24.750123
    
    

      
5
      
10
      
0.919841
      
0.845724
      
0.723207
      
27.521660
    
    

      
1
      
1
      
2
      
0.532143
      
0.552919
      
0.282532
      
0.894731
    
    

      
1
      
3
      
0.678968
      
0.635114
      
0.367089
      
1.677100
    
    

      
1
      
4
      
0.925397
      
0.753682
      
0.538312
      
8.936324
    
    

      
1
      
5
      
0.810317
      
0.694065
      
0.439156
      
3.277389
    
    

      
1
      
6
      
0.936111
      
0.758162
      
0.546582
      
9.707876
    
    

      
1
      
7
      
0.849206
      
0.720369
      
0.484135
      
4.877893
    
    

      
1
      
8
      
0.944048
      
0.759448
      
0.549030
      
10.586093
    
    

      
1
      
9
      
0.888889
      
0.731725
      
0.498650
      
6.523361
    
    

      
1
      
10
      
0.955159
      
0.760912
      
0.551308
      
11.379750
    
    

      
1
      
11
      
0.919048
      
0.744899
      
0.522447
      
8.160818
    
    

      
1
      
16
      
0.961111
      
0.761001
      
0.548945
      
13.221132
    
    

      
1
      
18
      
0.959524
      
0.761844
      
0.550295
      
14.015121
    
    

      
8
      
1
      
2
      
0.226587
      
0.262952
      
0.458650
      
0.809756
    
    

      
1
      
3
      
0.322619
      
0.306645
      
0.518650
      
1.591012
    
    

      
1
      
4
      
0.523810
      
0.430669
      
0.567173
      
2.453870
    
    

      
1
      
5
      
0.806349
      
0.722010
      
0.655865
      
3.231255
    
    

      
1
      
6
      
0.856349
      
0.837961
      
0.712236
      
4.068311
    
    

      
1
      
7
      
0.880556
      
0.841111
      
0.709958
      
4.927074
    
    

      
1
      
9
      
0.892063
      
0.846478
      
0.715612
      
6.192449
    
    

      
1
      
10
      
0.910317
      
0.847276
      
0.716371
      
7.008124
    
    

      
32
      
1
      
2
      
0.707540
      
0.739798
      
0.532405
      
0.815554
    
    

      
1
      
3
      
0.784524
      
0.773510
      
0.583038
      
1.616658
    
    

      
1
      
4
      
0.855952
      
0.784022
      
0.597300
      
2.473630
    
    

      
1
      
5
      
0.871429
      
0.787970
      
0.601603
      
3.252410
    
    

      
1
      
6
      
0.907937
      
0.791031
      
0.606160
      
4.003867
    
    

      
1
      
7
      
0.906349
      
0.793914
      
0.611899
      
4.837522
    
    

      
1
      
9
      
0.934921
      
0.795200
      
0.613755
      
6.127309
    
    

      
122
      
1
      
2
      
0.661111
      
0.641767
      
0.640000
      
0.916941
    
    

      
1
      
3
      
0.815476
      
0.764461
      
0.629789
      
1.740327
    
    

      
1
      
4
      
0.863889
      
0.798572
      
0.658143
      
2.566799
    
    

      
1
      
5
      
0.888889
      
0.806733
      
0.659494
      
3.414125
    
    

      
1
      
6
      
0.917460
      
0.816137
      
0.662616
      
4.222251
    
    

      
1
      
3
      
2
      
0.544444
      
0.430758
      
0.181603
      
1.185713
    
    

      
8
      
3
      
2
      
0.524603
      
0.430802
      
0.181688
      
0.844786
    
    

      
3
      
3
      
0.550794
      
0.490995
      
0.185654
      
1.651068
    
    

      
3
      
4
      
0.763095
      
0.627307
      
0.308861
      
11.345461
    
    

      
3
      
5
      
0.570635
      
0.523643
      
0.195781
      
3.504687
    
    

      
3
      
6
      
0.884127
      
0.686391
      
0.410717
      
21.949679
    
    

      
3
      
7
      
0.695635
      
0.574033
      
0.216118
      
5.791350
    
    

      
3
      
8
      
0.783333
      
0.641501
      
0.332743
      
13.551845
    
    

      
3
      
9
      
0.879365
      
0.687500
      
0.412827
      
23.062431
    
    

      
3
      
10
      
0.719444
      
0.615951
      
0.289114
      
9.119050
    
    

      
3
      
11
      
0.748810
      
0.622383
      
0.300169
      
10.237164
    
    

      
3
      
12
      
0.882540
      
0.688387
      
0.414515
      
24.189863
    
    

      
3
      
14
      
0.836905
      
0.650816
      
0.346667
      
16.295669
    
    

      
3
      
16
      
0.821825
      
0.658934
      
0.361519
      
17.445726
    
    

      
3
      
18
      
0.878571
      
0.689762
      
0.417131
      
26.434530
    
    

      
3
      
20
      
0.857540
      
0.674148
      
0.388439
      
19.644563
    
    

      
3
      
22
      
0.872222
      
0.685593
      
0.409198
      
20.869996
    
    

      
3
      
15
      
0.873016
      
0.689053
      
0.415781
      
25.303043
    
    

      
3
      
21
      
0.890476
      
0.690383
      
0.418312
      
27.565497
    
    

      
3
      
24
      
0.894841
      
0.691315
      
0.420084
      
28.660675
    
    

      
3
      
27
      
0.895635
      
0.692424
      
0.422194
      
29.767123
    
    

      
3
      
30
      
0.903968
      
0.694154
      
0.425485
      
30.917812
    
    

      
3
      
33
      
0.908333
      
0.695263
      
0.427595
      
32.010602
    
    

      
32
      
3
      
2
      
0.683730
      
0.506875
      
0.259662
      
1.216905
    
    

      
3
      
3
      
0.740079
      
0.587873
      
0.297553
      
2.472625
    
    

      
3
      
4
      
0.909921
      
0.803362
      
0.632574
      
13.271930
    
    

      
3
      
5
      
0.832937
      
0.689097
      
0.431983
      
4.909210
    
    

      
3
      
6
      
0.909524
      
0.813298
      
0.651814
      
14.483956
    
    

      
3
      
7
      
0.877381
      
0.740286
      
0.520675
      
7.311148
    
    

      
3
      
8
      
0.930556
      
0.819508
      
0.663460
      
15.621841
    
    

      
3
      
9
      
0.944048
      
0.830199
      
0.683291
      
25.742428
    
    

      
3
      
10
      
0.940873
      
0.824033
      
0.671899
      
16.823827
    
    

      
3
      
11
      
0.910714
      
0.795422
      
0.617806
      
12.062848
    
    

      
3
      
12
      
0.938095
      
0.830332
      
0.683460
      
27.110594
    
    

      
3
      
14
      
0.938889
      
0.827537
      
0.678312
      
19.163795
    
    

      
3
      
16
      
0.935714
      
0.828735
      
0.680759
      
20.362294
    
    

      
3
      
18
      
0.933730
      
0.830465
      
0.683713
      
29.460092
    
    

      
3
      
20
      
0.936508
      
0.829933
      
0.683122
      
22.672202
    
    

      
3
      
22
      
0.935714
      
0.830154
      
0.683122
      
23.830000
    
    

      
3
      
15
      
0.940873
      
0.830420
      
0.683629
      
28.270326
    
    

      
3
      
21
      
0.945238
      
0.830509
      
0.683797
      
30.650142
    
    

      
3
      
24
      
0.939683
      
0.830554
      
0.683882
      
31.840021
    
    

      
3
      
27
      
0.940079
      
0.830598
      
0.683966
      
33.030833
    
    

      
3
      
30
      
0.931349
      
0.830642
      
0.684051
      
34.194960
    
    

      
122
      
3
      
2
      
0.707143
      
0.813520
      
0.824473
      
1.606288
    
    

      
3
      
3
      
0.823016
      
0.890924
      
0.859409
      
3.097433
    
    

      
3
      
4
      
0.866270
      
0.907337
      
0.855359
      
4.684720
    
    

      
1
      
5
      
2
      
0.548810
      
0.430758
      
0.181603
      
1.428904
    
    

      
8
      
5
      
2
      
0.345238
      
0.349184
      
0.470042
      
1.460850
    
    

      
5
      
3
      
0.549206
      
0.511533
      
0.453249
      
2.885396
    
    

      
5
      
4
      
0.782143
      
0.665720
      
0.482194
      
15.451152
    
    

      
5
      
5
      
0.696032
      
0.603043
      
0.452152
      
5.598635
    
    

      
5
      
6
      
0.790476
      
0.704888
      
0.466329
      
16.918474
    
    

      
5
      
7
      
0.729762
      
0.612535
      
0.457384
      
8.406757
    
    

      
5
      
8
      
0.790476
      
0.705864
      
0.466160
      
18.299810
    
    

      
5
      
9
      
0.780952
      
0.623093
      
0.467426
      
11.201339
    
    

      
5
      
10
      
0.807540
      
0.706441
      
0.466413
      
19.644307
    
    

      
5
      
11
      
0.782143
      
0.631476
      
0.479831
      
14.077168
    
    

      
5
      
12
      
0.798016
      
0.706884
      
0.466076
      
21.059023
    
    

      
5
      
14
      
0.817064
      
0.709457
      
0.470127
      
22.393581
    
    

      
5
      
16
      
0.816270
      
0.712074
      
0.474599
      
23.821218
    
    

      
5
      
18
      
0.815873
      
0.712385
      
0.474008
      
25.311138
    
    

      
5
      
20
      
0.834127
      
0.715002
      
0.476709
      
26.797488
    
    

      
5
      
33
      
0.844841
      
0.715268
      
0.476624
      
34.629877
    
    

      
32
      
5
      
2
      
0.664683
      
0.483721
      
0.208101
      
1.624394
    
    

      
5
      
3
      
0.651984
      
0.487225
      
0.213671
      
3.194861
    
    

      
5
      
4
      
0.784127
      
0.629347
      
0.319494
      
17.155831
    
    

      
5
      
5
      
0.690873
      
0.492459
      
0.222532
      
6.421164
    
    

      
5
      
6
      
0.897222
      
0.675257
      
0.390295
      
31.138687
    
    

      
5
      
7
      
0.706746
      
0.568311
      
0.241350
      
9.491996
    
    

      
5
      
8
      
0.804365
      
0.641856
      
0.337468
      
20.202149
    
    

      
5
      
9
      
0.898016
      
0.675790
      
0.391139
      
32.651873
    
    

      
5
      
10
      
0.800000
      
0.648332
      
0.347257
      
21.835074
    
    

      
5
      
11
      
0.745635
      
0.625399
      
0.314262
      
15.704401
    
    

      
5
      
12
      
0.888492
      
0.676455
      
0.392405
      
34.194099
    
    

      
5
      
14
      
0.828175
      
0.664212
      
0.373333
      
24.864797
    
    

      
5
      
20
      
0.864683
      
0.668870
      
0.379241
      
28.021445
    
    

      
5
      
22
      
0.889683
      
0.674459
      
0.389030
      
29.626286
    
    

      
5
      
15
      
0.887302
      
0.676588
      
0.392658
      
35.847988
    
    

      
5
      
18
      
0.890873
      
0.677120
      
0.393502
      
37.454581
    
    

      
5
      
21
      
0.890079
      
0.677741
      
0.394515
      
39.075829
    
    

      
5
      
24
      
0.885714
      
0.678850
      
0.396456
      
40.641193
    
    

      
5
      
27
      
0.909921
      
0.679915
      
0.398312
      
42.206608
    
    

      
5
      
30
      
0.896825
      
0.680447
      
0.399409
      
43.848318
    
    

      
5
      
33
      
0.902778
      
0.681201
      
0.400759
      
45.428985
    
    

      
122
      
5
      
2
      
0.759127
      
0.832328
      
0.750802
      
2.225065
    
    

      
5
      
3
      
0.784524
      
0.875754
      
0.817975
      
4.425601
    
    

      
5
      
4
      
0.828968
      
0.886666
      
0.823797
      
6.734693
    
    

      
5
      
5
      
0.846825
      
0.898998
      
0.836962
      
8.911242
    
    

      
1
      
1
      
2
      
0.391667
      
0.570440
      
0.809620
      
0.853173
    
    

      
1
      
3
      
0.647619
      
0.768364
      
0.816118
      
1.723129
    
    

      
1
      
4
      
0.748810
      
0.840224
      
0.803122
      
2.562127
    
    

      
1
      
5
      
0.767063
      
0.847809
      
0.794852
      
3.373452
    
    

      
1
      
6
      
0.796032
      
0.850293
      
0.774684
      
4.169492
    
    

      
1
      
7
      
0.856746
      
0.876508
      
0.795105
      
5.030710
    
    

      
8
      
1
      
2
      
0.598016
      
0.624423
      
0.391224
      
0.829649
    
    

      
1
      
3
      
0.610317
      
0.637819
      
0.411392
      
1.595178
    
    

      
1
      
4
      
0.931746
      
0.785353
      
0.600253
      
9.353316
    
    

      
1
      
5
      
0.665079
      
0.670866
      
0.464810
      
3.260125
    
    

      
1
      
6
      
0.951190
      
0.787216
      
0.602447
      
10.201704
    
    

      
1
      
7
      
0.855159
      
0.741395
      
0.523376
      
4.934201
    
    

      
1
      
8
      
0.876984
      
0.751907
      
0.542278
      
5.757595
    
    

      
1
      
9
      
0.889286
      
0.759936
      
0.556540
      
6.686191
    
    

      
1
      
10
      
0.909921
      
0.767344
      
0.569283
      
7.540108
    
    

      
1
      
11
      
0.923810
      
0.775816
      
0.584557
      
8.430636
    
    

      
32
      
1
      
2
      
0.650397
      
0.630944
      
0.432405
      
0.831454
    
    

      
1
      
3
      
0.781746
      
0.711276
      
0.470464
      
1.628624
    
    

      
1
      
4
      
0.942857
      
0.760956
      
0.550548
      
8.921503
    
    

      
1
      
5
      
0.851587
      
0.734209
      
0.506329
      
3.328953
    
    

      
1
      
6
      
0.863889
      
0.739753
      
0.515612
      
4.109403
    
    

      
1
      
7
      
0.896032
      
0.748802
      
0.531730
      
4.942526
    
    

      
1
      
9
      
0.916667
      
0.749246
      
0.531899
      
6.354565
    
    

      
1
      
10
      
0.960714
      
0.761489
      
0.549198
      
10.726503
    
    

      
1
      
11
      
0.936905
      
0.758561
      
0.546667
      
8.009633
    
    

      
1
      
12
      
0.962302
      
0.763840
      
0.553249
      
11.594158
    
    

      
122
      
1
      
2
      
0.575794
      
0.571372
      
0.478397
      
0.888204
    
    

      
1
      
3
      
0.730952
      
0.705154
      
0.498397
      
1.795293
    
    

      
1
      
4
      
0.934524
      
0.795378
      
0.614008
      
9.253452
    
    

      
1
      
5
      
0.864683
      
0.748447
      
0.552236
      
3.401129
    
    

      
1
      
6
      
0.938095
      
0.795999
      
0.614852
      
10.054116
    
    

      
1
      
7
      
0.885317
      
0.774441
      
0.582869
      
5.085820
    
    

      
1
      
8
      
0.948016
      
0.798128
      
0.618734
      
10.973660
    
    

      
1
      
9
      
0.926587
      
0.789789
      
0.605401
      
6.692780
    
    

      
1
      
10
      
0.928571
      
0.792938
      
0.610464
      
7.556019
    
    

      
1
      
11
      
0.936111
      
0.794801
      
0.613418
      
8.391512
    
    

      
1
      
3
      
2
      
0.534524
      
0.430758
      
0.181603
      
1.132610
    
    

      
8
      
3
      
2
      
0.560714
      
0.618213
      
0.383629
      
0.830756
    
    

      
3
      
3
      
0.615079
      
0.637331
      
0.416287
      
1.636556
    
    

      
3
      
4
      
0.863492
      
0.750976
      
0.540760
      
11.132442
    
    

      
3
      
5
      
0.747619
      
0.688032
      
0.435021
      
3.608488
    
    

      
3
      
6
      
0.912698
      
0.784998
      
0.600675
      
21.808366
    
    

      
3
      
7
      
0.769444
      
0.700231
      
0.455612
      
5.832074
    
    

      
3
      
8
      
0.882143
      
0.766324
      
0.568354
      
13.330746
    
    

      
3
      
9
      
0.918651
      
0.785176
      
0.600928
      
22.864484
    
    

      
3
      
10
      
0.886111
      
0.771691
      
0.578397
      
14.415001
    
    

      
3
      
11
      
0.859524
      
0.740108
      
0.524219
      
10.040499
    
    

      
3
      
12
      
0.917460
      
0.785264
      
0.601013
      
23.909596
    
    

      
3
      
14
      
0.894444
      
0.778211
      
0.590042
      
16.491284
    
    

      
3
      
16
      
0.903571
      
0.780429
      
0.593502
      
17.593741
    
    

      
3
      
18
      
0.918651
      
0.785353
      
0.600928
      
26.096862
    
    

      
3
      
20
      
0.902778
      
0.783934
      
0.599409
      
19.757640
    
    

      
3
      
22
      
0.910714
      
0.784865
      
0.600422
      
20.776468
    
    

      
3
      
15
      
0.916667
      
0.785309
      
0.601097
      
25.002603
    
    

      
3
      
21
      
0.916270
      
0.785531
      
0.601181
      
27.154573
    
    

      
3
      
27
      
0.912302
      
0.785575
      
0.601266
      
28.818199
    
    

      
3
      
30
      
0.916667
      
0.785885
      
0.601772
      
29.927739
    
    

      
32
      
3
      
2
      
0.751984
      
0.526437
      
0.309958
      
1.155823
    
    

      
3
      
3
      
0.803968
      
0.600115
      
0.382110
      
2.306064
    
    

      
3
      
4
      
0.928175
      
0.775949
      
0.582616
      
12.056652
    
    

      
3
      
5
      
0.873810
      
0.719526
      
0.492321
      
4.633337
    
    

      
3
      
6
      
0.928968
      
0.781849
      
0.593418
      
13.251858
    
    

      
3
      
7
      
0.902778
      
0.745121
      
0.534599
      
6.861597
    
    

      
3
      
8
      
0.940873
      
0.787482
      
0.603460
      
14.374617
    
    

      
3
      
9
      
0.925000
      
0.761755
      
0.558903
      
8.770915
    
    

      
3
      
10
      
0.931746
      
0.789966
      
0.607764
      
15.494554
    
    

      
3
      
11
      
0.914683
      
0.772134
      
0.576118
      
10.928107
    
    

      
3
      
12
      
0.943254
      
0.791430
      
0.610464
      
16.673812
    
    

      
3
      
14
      
0.935714
      
0.792406
      
0.611646
      
17.841789
    
    

      
3
      
16
      
0.935714
      
0.795821
      
0.617806
      
19.042862
    
    

      
3
      
18
      
0.939683
      
0.795955
      
0.617384
      
20.175138
    
    

      
3
      
20
      
0.949603
      
0.796443
      
0.617975
      
21.317807
    
    

      
122
      
3
      
2
      
0.812698
      
0.855527
      
0.788439
      
1.509054
    
    

      
3
      
3
      
0.857540
      
0.888795
      
0.822954
      
2.939840
    
    

      
1
      
5
      
2
      
0.544444
      
0.430758
      
0.181603
      
1.337012
    
    

      
8
      
5
      
2
      
0.528968
      
0.430758
      
0.181603
      
1.339978
    
    

      
5
      
8
      
0.724603
      
0.609120
      
0.283207
      
14.178145
    
    

      
5
      
9
      
0.690873
      
0.572037
      
0.215021
      
7.297212
    
    

      
5
      
10
      
0.745635
      
0.613778
      
0.291477
      
15.507364
    
    

      
5
      
11
      
0.697619
      
0.579400
      
0.228608
      
10.018889
    
    

      
5
      
4
      
0.682540
      
0.582417
      
0.234093
      
11.364162
    
    

      
5
      
6
      
0.815873
      
0.643364
      
0.344388
      
24.305655
    
    

      
5
      
12
      
0.816667
      
0.643542
      
0.344557
      
26.380527
    
    

      
5
      
14
      
0.783730
      
0.626730
      
0.313840
      
17.905989
    
    

      
5
      
16
      
0.773016
      
0.631742
      
0.323122
      
18.965414
    
    

      
5
      
18
      
0.805556
      
0.644029
      
0.345232
      
29.082980
    
    

      
5
      
20
      
0.800397
      
0.641013
      
0.340253
      
21.614187
    
    

      
5
      
22
      
0.811905
      
0.643142
      
0.344051
      
23.008507
    
    

      
5
      
15
      
0.816270
      
0.643808
      
0.344895
      
27.748586
    
    

      
5
      
21
      
0.799603
      
0.644296
      
0.345570
      
30.551478
    
    

      
5
      
24
      
0.813889
      
0.644606
      
0.346076
      
31.993179
    
    

      
5
      
27
      
0.810317
      
0.644784
      
0.346413
      
33.392151
    
    

      
5
      
30
      
0.791270
      
0.644872
      
0.346498
      
34.839391
    
    

      
5
      
33
      
0.808333
      
0.645138
      
0.347004
      
36.295973
    
    

      
32
      
5
      
2
      
0.540079
      
0.430758
      
0.181603
      
1.552075
    
    

      
5
      
5
      
0.547619
      
0.430846
      
0.181772
      
4.564710
    
    

      
5
      
6
      
0.793254
      
0.640880
      
0.338650
      
29.554761
    
    

      
5
      
9
      
0.776587
      
0.642033
      
0.340759
      
31.047097
    
    

      
5
      
10
      
0.654365
      
0.483854
      
0.210295
      
18.755310
    
    

      
5
      
11
      
0.549603
      
0.435238
      
0.189873
      
12.362426
    
    

      
5
      
4
      
0.550000
      
0.439186
      
0.196287
      
13.932996
    
    

      
5
      
8
      
0.609127
      
0.466332
      
0.199241
      
17.042776
    
    

      
5
      
12
      
0.787302
      
0.643231
      
0.342954
      
32.574180
    
    

      
5
      
14
      
0.690873
      
0.556689
      
0.251561
      
21.784815
    
    

      
5
      
16
      
0.725397
      
0.600648
      
0.266498
      
23.275492
    
    

      
5
      
18
      
0.782540
      
0.645183
      
0.346329
      
35.753286
    
    

      
5
      
20
      
0.767857
      
0.626153
      
0.312236
      
26.442977
    
    

      
5
      
22
      
0.788095
      
0.639594
      
0.336540
      
28.004313
    
    

      
5
      
15
      
0.792460
      
0.644384
      
0.344979
      
34.159954
    
    

      
5
      
21
      
0.788889
      
0.645981
      
0.347511
      
37.346119
    
    

      
5
      
24
      
0.771429
      
0.646780
      
0.348776
      
38.887693
    
    

      
5
      
27
      
0.805556
      
0.647667
      
0.350295
      
40.420472
    
    

      
5
      
30
      
0.788889
      
0.648687
      
0.351730
      
41.793969
    
    

      
5
      
33
      
0.794048
      
0.649885
      
0.353586
      
42.929612
    
    

      
122
      
5
      
2
      
0.460317
      
0.572791
      
0.810295
      
2.196937
    
    

      
5
      
3
      
0.676984
      
0.771868
      
0.799072
      
4.308048
    
    

      
5
      
4
      
0.751190
      
0.827981
      
0.780338
      
6.438229
    
    

      
5
      
5
      
0.785714
      
0.836098
      
0.757215
      
8.596534
    
    

      
5
      
6
      
0.836905
      
0.860140
      
0.779072
      
10.736500
    
    

      
5
      
7
      
0.857143
      
0.869322
      
0.783797
      
12.943809
    
    

      
5
      
8
      
0.875397
      
0.870963
      
0.779662
      
15.156112
    
    

      
5
      
9
      
0.884524
      
0.872028
      
0.775443
      
17.370901
    
    

      
1
      
1
      
2
      
0.590873
      
0.628105
      
0.682278
      
0.815069
    
    

      
1
      
3
      
0.748016
      
0.755367
      
0.700506
      
1.626414
    
    

      
...
      
...
      
...
      
...
      
...
      
...
    
    

      
1
      
7
      
0.863889
      
0.851801
      
0.743629
      
4.881256
    
    

      
1
      
8
      
0.880556
      
0.857168
      
0.751308
      
5.683805
    
    

      
1
      
9
      
0.903571
      
0.858543
      
0.750464
      
6.550267
    
    

      
8
      
1
      
2
      
0.723413
      
0.684129
      
0.489030
      
0.884177
    
    

      
1
      
3
      
0.789683
      
0.709856
      
0.468945
      
1.626995
    
    

      
1
      
4
      
0.846032
      
0.720990
      
0.486835
      
2.474918
    
    

      
1
      
5
      
0.859524
      
0.741838
      
0.523544
      
3.262308
    
    

      
1
      
6
      
0.877778
      
0.749379
      
0.536203
      
4.056794
    
    

      
1
      
7
      
0.889286
      
0.759138
      
0.552405
      
4.833454
    
    

      
1
      
8
      
0.905556
      
0.770981
      
0.570211
      
5.670228
    
    

      
1
      
9
      
0.917063
      
0.780474
      
0.587764
      
6.450147
    
    

      
1
      
10
      
0.939683
      
0.786329
      
0.598734
      
7.243138
    
    

      
1
      
11
      
0.948016
      
0.789257
      
0.603713
      
8.060955
    
    

      
32
      
1
      
2
      
0.582143
      
0.657159
      
0.669789
      
0.788849
    
    

      
1
      
3
      
0.812302
      
0.814363
      
0.710464
      
1.604884
    
    

      
1
      
4
      
0.846429
      
0.825852
      
0.696709
      
2.400253
    
    

      
122
      
1
      
2
      
0.713492
      
0.663636
      
0.538481
      
0.863470
    
    

      
1
      
3
      
0.802778
      
0.776703
      
0.611814
      
1.678402
    
    

      
1
      
4
      
0.855952
      
0.789611
      
0.620422
      
2.471157
    
    

      
1
      
5
      
0.875794
      
0.803407
      
0.638734
      
3.256718
    
    

      
1
      
6
      
0.894444
      
0.805004
      
0.638987
      
4.119869
    
    

      
1
      
7
      
0.922619
      
0.810681
      
0.647511
      
4.896393
    
    

      
1
      
8
      
0.930952
      
0.817912
      
0.660675
      
5.754048
    
    

      
1
      
9
      
0.939286
      
0.820174
      
0.663882
      
6.539913
    
    

      
1
      
10
      
0.948810
      
0.822214
      
0.666667
      
7.365450
    
    

      
1
      
11
      
0.941667
      
0.822569
      
0.666751
      
8.129808
    
    

      
1
      
3
      
2
      
0.545635
      
0.430758
      
0.181603
      
1.110077
    
    

      
8
      
3
      
2
      
0.482937
      
0.583259
      
0.817890
      
1.107688
    
    

      
3
      
3
      
0.531746
      
0.636799
      
0.806835
      
2.236085
    
    

      
3
      
4
      
0.630556
      
0.742016
      
0.805401
      
3.375321
    
    

      
3
      
5
      
0.683730
      
0.800302
      
0.800422
      
4.415340
    
    

      
3
      
6
      
0.801587
      
0.864132
      
0.832743
      
5.555745
    
    

      
3
      
7
      
0.808333
      
0.866927
      
0.817046
      
6.661717
    
    

      
3
      
9
      
0.858333
      
0.868346
      
0.792321
      
8.268404
    
    

      
3
      
10
      
0.907540
      
0.877928
      
0.787511
      
13.263709
    
    

      
3
      
8
      
0.896825
      
0.875798
      
0.786160
      
12.189661
    
    

      
3
      
12
      
0.901190
      
0.878903
      
0.788354
      
14.208657
    
    

      
3
      
18
      
0.914683
      
0.879791
      
0.788270
      
15.938927
    
    

      
32
      
3
      
2
      
0.546032
      
0.661285
      
0.810464
      
1.223749
    
    

      
3
      
3
      
0.604365
      
0.704844
      
0.805232
      
2.482930
    
    

      
3
      
4
      
0.911905
      
0.869588
      
0.761857
      
12.638566
    
    

      
3
      
5
      
0.750794
      
0.835522
      
0.838565
      
4.846637
    
    

      
3
      
6
      
0.909524
      
0.870476
      
0.761688
      
13.807913
    
    

      
3
      
8
      
0.924206
      
0.871496
      
0.762363
      
14.972590
    
    

      
3
      
9
      
0.880159
      
0.862935
      
0.771392
      
9.065159
    
    

      
3
      
10
      
0.892460
      
0.866661
      
0.763629
      
10.282121
    
    

      
3
      
11
      
0.912302
      
0.868346
      
0.761857
      
11.469874
    
    

      
122
      
3
      
2
      
0.738889
      
0.755057
      
0.678397
      
1.503476
    
    

      
3
      
3
      
0.831349
      
0.773909
      
0.610802
      
2.965688
    
    

      
3
      
4
      
0.842063
      
0.781006
      
0.600591
      
4.469086
    
    

      
3
      
5
      
0.904365
      
0.788281
      
0.605907
      
6.037410
    
    

      
1
      
5
      
2
      
0.532540
      
0.430758
      
0.181603
      
1.406102
    
    

      
8
      
5
      
2
      
0.606746
      
0.689363
      
0.798650
      
1.546546
    
    

      
5
      
3
      
0.750794
      
0.821815
      
0.783713
      
2.926043
    
    

      
5
      
4
      
0.925000
      
0.859697
      
0.742954
      
14.970328
    
    

      
5
      
6
      
0.812302
      
0.830642
      
0.723544
      
6.420013
    
    

      
5
      
7
      
0.840873
      
0.837030
      
0.726329
      
7.906267
    
    

      
5
      
8
      
0.863889
      
0.851845
      
0.748861
      
9.324220
    
    

      
5
      
9
      
0.873810
      
0.852244
      
0.746835
      
10.695553
    
    

      
5
      
10
      
0.900000
      
0.856325
      
0.748523
      
12.195689
    
    

      
5
      
11
      
0.905952
      
0.859475
      
0.746160
      
13.659519
    
    

      
32
      
5
      
2
      
0.687698
      
0.519074
      
0.276034
      
1.662758
    
    

      
5
      
3
      
0.723413
      
0.533756
      
0.302616
      
3.245816
    
    

      
5
      
4
      
0.828571
      
0.699743
      
0.503629
      
17.418769
    
    

      
5
      
5
      
0.748016
      
0.559794
      
0.347595
      
6.329365
    
    

      
5
      
6
      
0.857937
      
0.718107
      
0.510970
      
18.917744
    
    

      
5
      
7
      
0.758730
      
0.584235
      
0.381350
      
9.515561
    
    

      
5
      
8
      
0.871032
      
0.741927
      
0.533165
      
20.516767
    
    

      
5
      
9
      
0.907937
      
0.780740
      
0.592911
      
33.884772
    
    

      
5
      
10
      
0.873413
      
0.753637
      
0.546329
      
22.121617
    
    

      
5
      
11
      
0.816667
      
0.694021
      
0.496034
      
15.874558
    
    

      
5
      
12
      
0.914683
      
0.781183
      
0.593755
      
35.417294
    
    

      
5
      
14
      
0.875794
      
0.759404
      
0.555190
      
25.144929
    
    

      
5
      
16
      
0.882937
      
0.763840
      
0.562363
      
26.802735
    
    

      
5
      
18
      
0.904762
      
0.781405
      
0.594177
      
37.753927
    
    

      
5
      
20
      
0.892063
      
0.778744
      
0.589536
      
29.976984
    
    

      
5
      
22
      
0.906746
      
0.780651
      
0.592911
      
31.512580
    
    

      
5
      
21
      
0.902778
      
0.781671
      
0.594684
      
39.392730
    
    

      
5
      
24
      
0.905556
      
0.781982
      
0.595190
      
40.967759
    
    

      
5
      
27
      
0.911111
      
0.782159
      
0.595190
      
42.512189
    
    

      
5
      
30
      
0.909921
      
0.782603
      
0.595612
      
44.022404
    
    

      
5
      
33
      
0.907540
      
0.783224
      
0.596456
      
45.668234
    
    

      
122
      
5
      
2
      
0.664286
      
0.718950
      
0.694008
      
2.368267
    
    

      
5
      
3
      
0.758333
      
0.835610
      
0.739578
      
4.307094
    
    

      
5
      
4
      
0.803968
      
0.869189
      
0.779494
      
5.914198
    
    

      
5
      
5
      
0.840079
      
0.874468
      
0.782700
      
7.686258
    
    

      
5
      
6
      
0.854365
      
0.883650
      
0.796793
      
9.796137
    
    

      
5
      
7
      
0.859524
      
0.889549
      
0.805654
      
11.863852
    
    

      
5
      
8
      
0.890476
      
0.892610
      
0.807595
      
14.130155
    
    

      
5
      
9
      
0.894841
      
0.892787
      
0.806582
      
16.372354
    
    

      
1
      
1
      
2
      
0.652381
      
0.685282
      
0.575527
      
0.808839
    
    

      
1
      
3
      
0.750397
      
0.770804
      
0.596540
      
1.658094
    
    

      
1
      
4
      
0.810317
      
0.794624
      
0.622447
      
2.427193
    
    

      
1
      
5
      
0.850397
      
0.811702
      
0.653080
      
3.195342
    
    

      
8
      
1
      
2
      
0.560714
      
0.480749
      
0.284051
      
0.869449
    
    

      
1
      
3
      
0.581349
      
0.522800
      
0.351646
      
1.660651
    
    

      
1
      
4
      
0.916270
      
0.789744
      
0.604810
      
8.973582
    
    

      
1
      
5
      
0.668651
      
0.574610
      
0.432152
      
3.296970
    
    

      
1
      
6
      
0.944048
      
0.794313
      
0.613249
      
9.758208
    
    

      
1
      
7
      
0.868651
      
0.739975
      
0.518143
      
4.891582
    
    

      
1
      
8
      
0.950794
      
0.797019
      
0.618397
      
10.618801
    
    

      
1
      
9
      
0.901190
      
0.762065
      
0.553502
      
6.562347
    
    

      
1
      
10
      
0.961111
      
0.803407
      
0.629114
      
11.382821
    
    

      
1
      
11
      
0.923016
      
0.780341
      
0.587004
      
8.183582
    
    

      
1
      
12
      
0.950794
      
0.805092
      
0.632321
      
12.163382
    
    

      
1
      
14
      
0.955952
      
0.805935
      
0.633755
      
12.949762
    
    

      
1
      
16
      
0.957540
      
0.806822
      
0.634684
      
13.772568
    
    

      
32
      
1
      
2
      
0.649206
      
0.655917
      
0.439916
      
0.770497
    
    

      
1
      
3
      
0.673810
      
0.668692
      
0.459747
      
1.556703
    
    

      
1
      
4
      
0.927778
      
0.784998
      
0.599240
      
8.939052
    
    

      
1
      
5
      
0.836905
      
0.730350
      
0.503207
      
3.214957
    
    

      
1
      
6
      
0.934127
      
0.788591
      
0.605485
      
9.761599
    
    

      
1
      
7
      
0.842063
      
0.743391
      
0.526245
      
4.847553
    
    

      
1
      
8
      
0.940079
      
0.790632
      
0.607595
      
10.591540
    
    

      
1
      
9
      
0.882937
      
0.765791
      
0.565823
      
6.441645
    
    

      
1
      
10
      
0.901984
      
0.771203
      
0.574937
      
7.283155
    
    

      
1
      
11
      
0.916270
      
0.777236
      
0.584979
      
8.117945
    
    

      
1
      
14
      
0.955556
      
0.790987
      
0.606498
      
12.410293
    
    

      
1
      
16
      
0.964286
      
0.791253
      
0.606835
      
13.192645
    
    

      
122
      
1
      
2
      
0.592857
      
0.480571
      
0.303207
      
0.815238
    
    

      
1
      
3
      
0.739683
      
0.560903
      
0.355190
      
1.603127
    
    

      
1
      
4
      
0.780556
      
0.582949
      
0.391814
      
2.419888
    
    

      
1
      
5
      
0.853571
      
0.686968
      
0.432152
      
3.267168
    
    

      
1
      
6
      
0.964286
      
0.756476
      
0.541688
      
14.314391
    
    

      
1
      
7
      
0.895238
      
0.712207
      
0.474852
      
4.960418
    
    

      
1
      
8
      
0.955952
      
0.746451
      
0.527679
      
8.596934
    
    

      
1
      
9
      
0.920635
      
0.737092
      
0.518059
      
6.169476
    
    

      
1
      
10
      
0.956746
      
0.748181
      
0.529283
      
9.370682
    
    

      
1
      
12
      
0.964286
      
0.756609
      
0.541857
      
15.632658
    
    

      
1
      
14
      
0.961111
      
0.753770
      
0.538987
      
11.019704
    
    

      
1
      
16
      
0.959921
      
0.756033
      
0.541941
      
11.794474
    
    

      
1
      
22
      
0.967460
      
0.756432
      
0.541688
      
13.534852
    
    

      
1
      
15
      
0.959524
      
0.756698
      
0.542025
      
16.480554
    
    

      
1
      
18
      
0.966270
      
0.756787
      
0.542194
      
17.254168
    
    

      
1
      
3
      
2
      
0.525000
      
0.430758
      
0.181603
      
1.136044
    
    

      
8
      
3
      
2
      
0.516667
      
0.478487
      
0.331983
      
1.153312
    
    

      
3
      
3
      
0.633333
      
0.536684
      
0.356371
      
2.236713
    
    

      
3
      
4
      
0.890873
      
0.777014
      
0.595190
      
11.856152
    
    

      
3
      
5
      
0.746032
      
0.616661
      
0.471055
      
4.481458
    
    

      
3
      
7
      
0.810317
      
0.684129
      
0.490042
      
6.198583
    
    

      
3
      
8
      
0.923413
      
0.780385
      
0.597046
      
14.076809
    
    

      
3
      
9
      
0.932936
      
0.795067
      
0.616456
      
23.555041
    
    

      
3
      
10
      
0.936905
      
0.782425
      
0.598987
      
15.148457
    
    

      
3
      
11
      
0.880159
      
0.768408
      
0.582363
      
10.676322
    
    

      
3
      
6
      
0.907937
      
0.779675
      
0.597637
      
12.946444
    
    

      
3
      
12
      
0.917460
      
0.784333
      
0.601603
      
16.264792
    
    

      
3
      
14
      
0.943651
      
0.785974
      
0.603038
      
17.363150
    
    

      
3
      
16
      
0.931746
      
0.787793
      
0.605485
      
18.517551
    
    

      
3
      
18
      
0.938492
      
0.789656
      
0.608439
      
19.630407
    
    

      
3
      
20
      
0.934921
      
0.792583
      
0.612658
      
20.741610
    
    

      
3
      
22
      
0.927381
      
0.794890
      
0.616287
      
21.830405
    
    

      
3
      
15
      
0.936905
      
0.795200
      
0.616624
      
25.206463
    
    

      
3
      
21
      
0.938095
      
0.795334
      
0.616878
      
26.945656
    
    

      
3
      
27
      
0.932936
      
0.795378
      
0.616878
      
28.628550
    
    

      
3
      
30
      
0.939286
      
0.795555
      
0.617131
      
29.705958
    
    

      
32
      
3
      
2
      
0.676984
      
0.509315
      
0.247595
      
1.170462
    
    

      
3
      
3
      
0.702381
      
0.512287
      
0.252068
      
2.400195
    
    

      
3
      
4
      
0.874206
      
0.703380
      
0.444979
      
13.039391
    
    

      
3
      
5
      
0.760714
      
0.529143
      
0.279747
      
4.735582
    
    

      
3
      
6
      
0.920635
      
0.771513
      
0.569789
      
25.140305
    
    

      
3
      
7
      
0.803571
      
0.627528
      
0.308776
      
7.078616
    
    

      
3
      
8
      
0.871032
      
0.725160
      
0.483629
      
15.349843
    
    

      
3
      
9
      
0.916270
      
0.773421
      
0.573418
      
26.354444
    
    

      
3
      
10
      
0.894841
      
0.732346
      
0.497046
      
16.467137
    
    

      
3
      
11
      
0.852381
      
0.687810
      
0.416287
      
11.858376
    
    

      
3
      
12
      
0.926190
      
0.774619
      
0.575696
      
27.695649
    
    

      
3
      
14
      
0.896429
      
0.747250
      
0.524641
      
18.937314
    
    

      
3
      
16
      
0.907143
      
0.756077
      
0.541350
      
20.204582
    
    

      
3
      
18
      
0.918254
      
0.775727
      
0.577806
      
30.061926
    
    

      
3
      
20
      
0.917857
      
0.766545
      
0.560591
      
22.598675
    
    

      
3
      
22
      
0.918254
      
0.770538
      
0.567932
      
23.816767
    
    

      
3
      
15
      
0.927778
      
0.775639
      
0.577637
      
28.838756
    
    

      
3
      
21
      
0.925794
      
0.776171
      
0.578650
      
31.220424
    
    

      
3
      
30
      
0.924206
      
0.776393
      
0.578987
      
33.839890
    
    

      
3
      
33
      
0.922619
      
0.776792
      
0.579747
      
35.120372
    
    

      
122
      
3
      
2
      
0.726984
      
0.578380
      
0.450211
      
1.667094
    
    

      
3
      
3
      
0.841667
      
0.723918
      
0.560084
      
3.179127
    
    

      
3
      
4
      
0.890476
      
0.810415
      
0.665907
      
4.544612
    
    

      
3
      
5
      
0.891270
      
0.827315
      
0.692658
      
5.726158
    
    

      
3
      
6
      
0.909127
      
0.834235
      
0.701266
      
6.902444
    
    

      
3
      
8
      
0.927778
      
0.837873
      
0.704219
      
9.157604
    
    

      
3
      
9
      
0.928571
      
0.846700
      
0.718819
      
10.720084
    
    

      
1
      
5
      
2
      
0.532540
      
0.430758
      
0.181603
      
1.318899
    
    

      
8
      
5
      
2
      
0.398810
      
0.438786
      
0.734768
      
1.401034
    
    

      
5
      
3
      
0.417460
      
0.440295
      
0.737046
      
2.789525
    
    

      
5
      
4
      
0.421429
      
0.444331
      
0.740506
      
4.197622
    
    

      
5
      
5
      
0.484127
      
0.505412
      
0.741688
      
5.546883
    
    

      
5
      
6
      
0.882143
      
0.744633
      
0.641013
      
22.220947
    
    

      
5
      
7
      
0.693254
      
0.712252
      
0.714852
      
8.283814
    
    

      
5
      
8
      
0.707540
      
0.716643
      
0.712152
      
9.670416
    
    

      
5
      
9
      
0.881746
      
0.745963
      
0.641941
      
23.707702
    
    

      
5
      
10
      
0.730159
      
0.721478
      
0.699662
      
12.403055
    
    

      
5
      
20
      
0.846429
      
0.721700
      
0.634852
      
19.431136
    
    

      
5
      
22
      
0.880556
      
0.743080
      
0.639831
      
20.878179
    
    

      
5
      
12
      
0.888095
      
0.747516
      
0.643291
      
25.089557
    
    

      
5
      
15
      
0.874206
      
0.750133
      
0.646920
      
26.446527
    
    

      
5
      
18
      
0.876190
      
0.753637
      
0.651730
      
27.857000
    
    

      
5
      
21
      
0.884127
      
0.755767
      
0.654768
      
29.209456
    
    

      
5
      
24
      
0.888095
      
0.756654
      
0.655190
      
30.606091
    
    

      
5
      
27
      
0.894444
      
0.757363
      
0.655190
      
31.951760
    
    

      
5
      
30
      
0.897222
      
0.757541
      
0.654093
      
33.399226
    
    

      
5
      
33
      
0.894444
      
0.758206
      
0.653249
      
34.715635
    
    

      
32
      
5
      
2
      
0.509921
      
0.430758
      
0.181603
      
1.603045
    
    

      
5
      
7
      
0.546825
      
0.431024
      
0.181772
      
6.192066
    
    

      
5
      
8
      
0.757540
      
0.604107
      
0.273587
      
16.881149
    
    

      
5
      
9
      
0.863889
      
0.728132
      
0.499747
      
29.490173
    
    

      
5
      
10
      
0.773413
      
0.629613
      
0.320591
      
18.322043
    
    

      
5
      
11
      
0.675000
      
0.566847
      
0.209873
      
12.285737
    
    

      
5
      
4
      
0.678968
      
0.572924
      
0.218312
      
13.705929
    
    

      
5
      
6
      
0.874206
      
0.727599
      
0.498903
      
28.020595
    
    

      
5
      
12
      
0.869048
      
0.728974
      
0.500675
      
31.071805
    
    

      
5
      
14
      
0.802381
      
0.673394
      
0.400169
      
21.395666
    
    

      
5
      
16
      
0.833730
      
0.689274
      
0.428776
      
23.060187
    
    

      
5
      
18
      
0.867460
      
0.730926
      
0.502616
      
34.265042
    
    

      
5
      
20
      
0.863889
      
0.717663
      
0.481603
      
25.683904
    
    

      
5
      
22
      
0.862698
      
0.727067
      
0.497975
      
26.825816
    
    

      
5
      
15
      
0.876190
      
0.729862
      
0.501772
      
32.594195
    
    

      
5
      
21
      
0.864286
      
0.731813
      
0.503797
      
35.816563
    
    

      
5
      
24
      
0.867857
      
0.732434
      
0.504726
      
37.506815
    
    

      
5
      
27
      
0.886905
      
0.733188
      
0.505992
      
39.048521
    
    

      
5
      
30
      
0.875397
      
0.733632
      
0.506835
      
40.633031
    
    

      
5
      
33
      
0.872222
      
0.734031
      
0.507595
      
42.204596
    
    

      
122
      
5
      
2
      
0.827381
      
0.841998
      
0.770380
      
2.376861
    
    

      
5
      
3
      
0.828175
      
0.877262
      
0.824135
      
4.570594
    
    

      
5
      
4
      
0.844444
      
0.888840
      
0.834008
      
6.760869
    
    

      
5
      
5
      
0.842460
      
0.893808
      
0.837637
      
8.998884
    
    

      
5
      
6
      
0.863492
      
0.895715
      
0.835190
      
11.282426
    
    

      
1
      
1
      
2
      
0.694444
      
0.503016
      
0.243376
      
0.910504
    
    

      
1
      
3
      
0.736111
      
0.517255
      
0.266835
      
1.687136
    
    

      
1
      
4
      
0.946032
      
0.751109
      
0.533502
      
8.941634
    
    

      
1
      
5
      
0.790873
      
0.562722
      
0.349030
      
3.272226
    
    

      
1
      
6
      
0.944048
      
0.759670
      
0.549198
      
9.833709
    
    

      
1
      
7
      
0.864683
      
0.691182
      
0.434177
      
4.904266
    
    

      
1
      
8
      
0.944048
      
0.768408
      
0.565316
      
10.641123
    
    

      
1
      
9
      
0.911111
      
0.723785
      
0.486667
      
6.528325
    
    

      
1
      
10
      
0.961508
      
0.779276
      
0.586245
      
11.456399
    
    

      
1
      
11
      
0.928175
      
0.742903
      
0.519325
      
8.138729
    
    

      
1
      
12
      
0.953968
      
0.785442
      
0.595105
      
12.201887
    
    

      
1
      
14
      
0.961508
      
0.789611
      
0.602954
      
13.061194
    
    

      
1
      
16
      
0.963095
      
0.790809
      
0.605148
      
13.888129
    
    

      
1
      
18
      
0.957937
      
0.790853
      
0.605148
      
14.680479
    
    

      
1
      
20
      
0.969048
      
0.791741
      
0.606329
      
15.529244
    
    

      
8
      
1
      
2
      
0.791270
      
0.738644
      
0.529451
      
0.860585
    
    

      
1
      
3
      
0.851587
      
0.768231
      
0.571224
      
1.668629
    
    

      
1
      
4
      
0.870635
      
0.781804
      
0.595021
      
2.464633
    
    

      
1
      
5
      
0.891270
      
0.792938
      
0.613080
      
3.402384
    
    

      
1
      
6
      
0.908333
      
0.809173
      
0.642110
      
4.239686
    
    

      
1
      
7
      
0.901984
      
0.819331
      
0.660928
      
5.030024
    
    

      
1
      
8
      
0.924603
      
0.820928
      
0.663544
      
5.840948
    
    

      
1
      
9
      
0.921429
      
0.821904
      
0.664979
      
6.670229
    
    

      
32
      
1
      
2
      
0.728175
      
0.666519
      
0.385654
      
0.899783
    
    

      
1
      
3
      
0.773810
      
0.683641
      
0.414515
      
1.714528
    
    

      
1
      
4
      
0.802778
      
0.702537
      
0.447089
      
2.484719
    
    

      
1
      
5
      
0.828968
      
0.717663
      
0.471899
      
3.368358
    
    

      
1
      
6
      
0.858730
      
0.731148
      
0.495527
      
4.190599
    
    

      
1
      
7
      
0.873810
      
0.741439
      
0.514599
      
5.004562
    
    

      
1
      
8
      
0.897619
      
0.753815
      
0.537722
      
5.826692
    
    

      
1
      
9
      
0.908333
      
0.763352
      
0.555612
      
6.681455
    
    

      
1
      
10
      
0.923413
      
0.770937
      
0.569789
      
7.490652
    
    

      
1
      
11
      
0.944048
      
0.782825
      
0.589789
      
8.270839
    
    

      
122
      
1
      
2
      
0.653571
      
0.677475
      
0.486498
      
0.641767
    
    

      
1
      
3
      
0.762302
      
0.718595
      
0.503038
      
1.235688
    
    

      
1
      
4
      
0.919048
      
0.789123
      
0.607679
      
7.860441
    
    

      
1
      
5
      
0.836508
      
0.741794
      
0.530127
      
2.433098
    
    

      
1
      
6
      
0.860317
      
0.754170
      
0.551308
      
3.157930
    
    

      
1
      
7
      
0.871429
      
0.763928
      
0.567342
      
3.955057
    
    

      
1
      
8
      
0.886905
      
0.773288
      
0.584135
      
4.727972
    
    

      
1
      
9
      
0.880556
      
0.777324
      
0.590127
      
5.474877
    
    

      
1
      
10
      
0.881349
      
0.781139
      
0.593080
      
6.217043
    
    

      
1
      
11
      
0.919444
      
0.787349
      
0.604641
      
7.046358
    
    

      
1
      
3
      
2
      
0.545238
      
0.430758
      
0.181603
      
1.038483
    
    

      
8
      
3
      
2
      
0.515873
      
0.424414
      
0.179747
      
1.097890
    
    

      
3
      
3
      
0.536905
      
0.425790
      
0.180759
      
2.143623
    
    

      
3
      
4
      
0.744444
      
0.530208
      
0.289620
      
11.259707
    
    

      
3
      
5
      
0.561508
      
0.438831
      
0.181181
      
4.255471
    
    

      
3
      
6
      
0.898413
      
0.691093
      
0.429367
      
22.300597
    
    

      
3
      
7
      
0.642460
      
0.472410
      
0.189958
      
6.194484
    
    

      
3
      
8
      
0.798810
      
0.586010
      
0.316456
      
13.533677
    
    

      
3
      
9
      
0.897222
      
0.692113
      
0.431055
      
23.404547
    
    

      
3
      
10
      
0.832540
      
0.633561
      
0.328776
      
14.577337
    
    

      
3
      
11
      
0.731746
      
0.505323
      
0.244473
      
10.171338
    
    

      
3
      
12
      
0.898413
      
0.692867
      
0.432321
      
24.543459
    
    

      
3
      
14
      
0.853968
      
0.649530
      
0.355274
      
16.771005
    
    

      
3
      
16
      
0.864286
      
0.656405
      
0.368017
      
17.882679
    
    

      
3
      
18
      
0.902381
      
0.694464
      
0.435021
      
26.844587
    
    

      
3
      
20
      
0.886111
      
0.680713
      
0.411899
      
20.058650
    
    

      
3
      
22
      
0.896032
      
0.690161
      
0.427848
      
21.185926
    
    

      
3
      
15
      
0.896032
      
0.693976
      
0.434093
      
25.716757
    
    

      
3
      
21
      
0.895238
      
0.694863
      
0.435781
      
27.960191
    
    

      
3
      
24
      
0.900000
      
0.695529
      
0.436962
      
29.027340
    
    

      
3
      
27
      
0.903571
      
0.696150
      
0.438143
      
30.049937
    
    

      
3
      
30
      
0.905556
      
0.696593
      
0.438903
      
31.125288
    
    

      
3
      
33
      
0.905556
      
0.696726
      
0.439156
      
32.222431
    
    

      
32
      
3
      
2
      
0.691667
      
0.616971
      
0.426414
      
1.195384
    
    

      
3
      
3
      
0.826587
      
0.726712
      
0.527595
      
2.318904
    
    

      
3
      
4
      
0.930556
      
0.803983
      
0.632321
      
12.117837
    
    

      
3
      
5
      
0.883333
      
0.753637
      
0.553333
      
4.590592
    
    

      
3
      
6
      
0.939286
      
0.815250
      
0.653840
      
13.141996
    
    

      
3
      
7
      
0.915476
      
0.776171
      
0.586751
      
6.918323
    
    

      
3
      
9
      
0.909524
      
0.778256
      
0.584979
      
8.676533
    
    

      
3
      
10
      
0.931746
      
0.826961
      
0.675359
      
15.049278
    
    

      
3
      
11
      
0.924603
      
0.796709
      
0.618734
      
10.999747
    
    

      
3
      
8
      
0.941667
      
0.822347
      
0.667004
      
14.017167
    
    

      
3
      
12
      
0.934127
      
0.829179
      
0.679578
      
16.208178
    
    

      
3
      
14
      
0.935714
      
0.829933
      
0.681013
      
17.381170
    
    

      
3
      
18
      
0.944048
      
0.830199
      
0.681266
      
19.179069
    
    

      
3
      
20
      
0.939286
      
0.830554
      
0.681772
      
20.313943
    
    

      
122
      
3
      
2
      
0.633333
      
0.630412
      
0.659747
      
1.532302
    
    

      
3
      
3
      
0.846825
      
0.834812
      
0.706667
      
3.066649
    
    

      
3
      
5
      
0.869048
      
0.839026
      
0.709030
      
5.453015
    
    

      
3
      
6
      
0.863889
      
0.844571
      
0.716878
      
6.928237
    
    

      
3
      
7
      
0.879762
      
0.846833
      
0.718481
      
8.421714
    
    

      
3
      
8
      
0.934921
      
0.852067
      
0.724641
      
16.195730
    
    

      
3
      
10
      
0.948016
      
0.853886
      
0.728017
      
17.664799
    
    

      
1
      
5
      
2
      
0.521032
      
0.430758
      
0.181603
      
1.331508
    
    

      
8
      
5
      
2
      
0.455556
      
0.569242
      
0.818397
      
1.405436
    
    

      
5
      
3
      
0.450397
      
0.569508
      
0.818734
      
2.777832
    
    

      
5
      
4
      
0.793651
      
0.863068
      
0.795612
      
14.802773
    
    

      
5
      
5
      
0.459524
      
0.571505
      
0.821350
      
5.437043
    
    

      
5
      
6
      
0.810714
      
0.866306
      
0.795781
      
16.250514
    
    

      
5
      
7
      
0.676984
      
0.793426
      
0.813165
      
7.986766
    
    

      
5
      
8
      
0.829365
      
0.866971
      
0.795274
      
17.737847
    
    

      
5
      
9
      
0.755556
      
0.838893
      
0.794346
      
10.757020
    
    

      
5
      
10
      
0.776190
      
0.845413
      
0.792152
      
12.104453
    
    

      
5
      
11
      
0.789286
      
0.851712
      
0.793502
      
13.462587
    
    

      
5
      
20
      
0.877381
      
0.874423
      
0.776962
      
22.464884
    
    

      
32
      
5
      
2
      
0.467857
      
0.569331
      
0.818397
      
1.640981
    
    

      
5
      
3
      
0.469048
      
0.570263
      
0.818312
      
3.389922
    
    

      
5
      
4
      
0.478571
      
0.574255
      
0.820084
      
4.984748
    
    

      
5
      
5
      
0.507540
      
0.586276
      
0.820844
      
6.491150
    
    

      
5
      
6
      
0.707540
      
0.777945
      
0.801013
      
8.023460
    
    

      
5
      
7
      
0.788492
      
0.853974
      
0.812743
      
9.607423
    
    

      
5
      
8
      
0.833333
      
0.881521
      
0.822363
      
11.145439
    
    

      
5
      
9
      
0.858333
      
0.889727
      
0.817131
      
12.703154
    
    

      
5
      
10
      
0.875794
      
0.895050
      
0.819494
      
14.221701
    
    

      
122
      
5
      
2
      
0.693254
      
0.619012
      
0.620591
      
2.205522
    
    

      
5
      
3
      
0.798016
      
0.789567
      
0.769114
      
4.312284
    
    

      
5
      
4
      
0.859127
      
0.863778
      
0.809030
      
6.395371
    
    

      
5
      
5
      
0.880952
      
0.874823
      
0.809536
      
8.521467
    
    

      
5
      
6
      
0.880952
      
0.876553
      
0.806835
      
10.668059
    
    

      
5
      
7
      
0.891270
      
0.877839
      
0.798650
      
12.819965
    
    

      
5
      
8
      
0.903968
      
0.884271
      
0.796793
      
14.985993
    
    

      
1
      
1
      
2
      
0.493651
      
0.423838
      
0.195696
      
0.807331
    
    

      
1
      
3
      
0.522619
      
0.430979
      
0.192827
      
1.596510
    
    

      
1
      
4
      
0.881746
      
0.721744
      
0.483291
      
8.853109
    
    

      
1
      
5
      
0.582937
      
0.484164
      
0.276962
      
3.191427
    
    

      
1
      
6
      
0.960317
      
0.778832
      
0.584641
      
16.026343
    
    

      
1
      
7
      
0.744048
      
0.563742
      
0.334177
      
4.781629
    
    

      
1
      
8
      
0.927778
      
0.756787
      
0.547004
      
10.412220
    
    

      
1
      
9
      
0.955952
      
0.779143
      
0.585232
      
16.817441
    
    

      
1
      
10
      
0.946825
      
0.761356
      
0.555106
      
11.200721
    
    

      
1
      
11
      
0.854365
      
0.706707
      
0.456118
      
8.028947
    
    

      
1
      
12
      
0.964683
      
0.779276
      
0.585485
      
17.569122
    
    

      
1
      
14
      
0.954365
      
0.768941
      
0.567679
      
12.652271
    
    

      
1
      
16
      
0.952778
      
0.770715
      
0.570717
      
13.253711
    
    

      
1
      
18
      
0.962698
      
0.779542
      
0.585992
      
19.157119
    
    

      
1
      
20
      
0.955159
      
0.777280
      
0.582363
      
14.447026
    
    

      
1
      
22
      
0.957540
      
0.778611
      
0.584388
      
15.205530
    
    

      
1
      
15
      
0.958333
      
0.779454
      
0.585823
      
18.398555
    
    

      
1
      
21
      
0.967857
      
0.779853
      
0.586582
      
19.983089
    
    

      
1
      
24
      
0.969841
      
0.780119
      
0.587089
      
20.762034
    
    

      
1
      
27
      
0.962302
      
0.780385
      
0.587511
      
21.580799
    
    

      
1
      
30
      
0.961508
      
0.780429
      
0.587595
      
22.352542
    
    

      
1
      
33
      
0.963889
      
0.780784
      
0.588270
      
23.211684
    
    

      
8
      
1
      
2
      
0.420635
      
0.429826
      
0.610886
      
0.769770
    
    

      
1
      
3
      
0.737302
      
0.680669
      
0.610211
      
1.608776
    
    

      
1
      
4
      
0.813492
      
0.758339
      
0.587173
      
2.349010
    
    

      
1
      
5
      
0.854762
      
0.776393
      
0.597890
      
3.219053
    
    

      
1
      
6
      
0.873413
      
0.791785
      
0.621688
      
3.978208
    
    

      
1
      
7
      
0.892460
      
0.805846
      
0.640506
      
4.819912
    
    

      
1
      
8
      
0.895238
      
0.809351
      
0.644557
      
5.625120
    
    

      
1
      
9
      
0.909921
      
0.810814
      
0.645907
      
6.522778
    
    

      
1
      
10
      
0.917063
      
0.811790
      
0.646920
      
7.331714
    
    

      
32
      
1
      
2
      
0.753571
      
0.713405
      
0.473840
      
0.840305
    
    

      
1
      
3
      
0.816270
      
0.742947
      
0.525823
      
1.625310
    
    

      
1
      
4
      
0.941667
      
0.812544
      
0.650549
      
8.782956
    
    

      
1
      
5
      
0.882540
      
0.774619
      
0.582532
      
3.201481
    
    

      
1
      
6
      
0.937302
      
0.812677
      
0.650464
      
9.596403
    
    

      
1
      
7
      
0.909524
      
0.784954
      
0.600928
      
4.833746
    
    

      
1
      
8
      
0.916270
      
0.792273
      
0.613671
      
5.602313
    
    

      
1
      
9
      
0.926587
      
0.800435
      
0.629367
      
6.412395
    
    

      
1
      
10
      
0.941270
      
0.805358
      
0.638228
      
7.183477
    
    

      
1
      
11
      
0.933730
      
0.809661
      
0.645992
      
8.012530
    
    

      
122
      
1
      
2
      
0.729365
      
0.610406
      
0.304726
      
0.841745
    
    

      
1
      
3
      
0.811508
      
0.673705
      
0.404557
      
1.695190
    
    

      
1
      
4
      
0.938889
      
0.751641
      
0.536962
      
8.785692
    
    

      
1
      
5
      
0.867857
      
0.691137
      
0.428608
      
3.253160
    
    

      
1
      
6
      
0.945238
      
0.754524
      
0.541603
      
9.645123
    
    

      
1
      
7
      
0.882143
      
0.707505
      
0.458143
      
4.797040
    
    

      
1
      
8
      
0.946032
      
0.757142
      
0.544979
      
10.489040
    
    

      
1
      
9
      
0.900000
      
0.728176
      
0.494093
      
6.365857
    
    

      
1
      
10
      
0.961508
      
0.761489
      
0.551561
      
11.270747
    
    

      
1
      
11
      
0.946825
      
0.745875
      
0.526414
      
7.940228
    
    

      
1
      
12
      
0.956746
      
0.764372
      
0.556371
      
12.076853
    
    

      
1
      
14
      
0.964286
      
0.765791
      
0.558734
      
12.866027
    
    

      
1
      
3
      
2
      
0.519444
      
0.430758
      
0.181603
      
1.093403
    
    

      
3
      
11
      
0.847222
      
0.757674
      
0.550633
      
6.181096
    
    

      
3
      
6
      
0.919444
      
0.782071
      
0.590717
      
17.835649
    
    

      
3
      
8
      
0.882540
      
0.764949
      
0.561013
      
8.806329
    
    

      
3
      
10
      
0.905952
      
0.768763
      
0.567004
      
9.904373
    
    

      
3
      
12
      
0.918651
      
0.782204
      
0.590970
      
20.038939
    
    

      
3
      
14
      
0.900397
      
0.773909
      
0.576624
      
12.157693
    
    

      
3
      
16
      
0.907540
      
0.775683
      
0.579831
      
13.306773
    
    

      
3
      
18
      
0.930952
      
0.776437
      
0.581266
      
14.452175
    
    

      
3
      
20
      
0.919444
      
0.777768
      
0.583797
      
15.543692
    
    

      
3
      
22
      
0.914286
      
0.782026
      
0.590633
      
16.732997
    
    

      
3
      
9
      
0.925397
      
0.782115
      
0.590802
      
18.944045
    
    

      
3
      
15
      
0.919444
      
0.782381
      
0.591308
      
21.114165
    
    

      
3
      
24
      
0.924206
      
0.782559
      
0.591646
      
23.359160
    
    

      
3
      
27
      
0.916270
      
0.782736
      
0.591983
      
24.386522
    
    

      
8
      
3
      
2
      
0.563889
      
0.625621
      
0.693671
      
1.187153
    
    

      
3
      
3
      
0.678571
      
0.737269
      
0.672911
      
2.314086
    
    

      
3
      
4
      
0.880159
      
0.821150
      
0.672827
      
10.685101
    
    

      
3
      
5
      
0.823413
      
0.812145
      
0.684557
      
4.496789
    
    

      
3
      
8
      
0.849206
      
0.813964
      
0.668692
      
6.777124
    
    

      
3
      
9
      
0.923016
      
0.827005
      
0.677384
      
20.235193
    
    

      
3
      
10
      
0.859127
      
0.820263
      
0.675696
      
8.968101
    
    

      
3
      
16
      
0.921429
      
0.823501
      
0.671224
      
14.632145
    
    

      
3
      
18
      
0.912302
      
0.824521
      
0.672911
      
15.710437
    
    

      
3
      
20
      
0.907540
      
0.825763
      
0.675190
      
16.846556
    
    

      
3
      
22
      
0.923016
      
0.826694
      
0.676878
      
17.945738
    
    

      
3
      
6
      
0.909127
      
0.826783
      
0.676962
      
19.093679
    
    

      
3
      
12
      
0.921032
      
0.827182
      
0.677722
      
21.320162
    
    

      
3
      
24
      
0.922619
      
0.827271
      
0.677806
      
24.279881
    
    

      
3
      
30
      
0.921429
      
0.827315
      
0.677806
      
25.972584
    
    

      
3
      
33
      
0.918651
      
0.827404
      
0.677890
      
27.045139
    
    

      
32
      
3
      
2
      
0.666270
      
0.696238
      
0.557975
      
1.247300
    
    

      
3
      
3
      
0.803175
      
0.763840
      
0.581181
      
2.442370
    
    

      
3
      
4
      
0.908730
      
0.798039
      
0.624388
      
12.652347
    
    

      
3
      
5
      
0.868651
      
0.776570
      
0.594599
      
4.858522
    
    

      
3
      
6
      
0.920635
      
0.802520
      
0.632574
      
13.861901
    
    

      
3
      
7
      
0.882540
      
0.783668
      
0.602025
      
7.257311
    
    

      
3
      
8
      
0.923016
      
0.806334
      
0.638481
      
15.031495
    
    

      
3
      
10
      
0.937698
      
0.807754
      
0.641013
      
16.278363
    
    

      
3
      
11
      
0.911508
      
0.792140
      
0.613586
      
11.410274
    
    

      
3
      
12
      
0.936111
      
0.809661
      
0.644641
      
17.451793
    
    

      
3
      
14
      
0.937698
      
0.814319
      
0.651392
      
18.608358
    
    

      
3
      
16
      
0.938492
      
0.818400
      
0.659072
      
19.794503
    
    

      
122
      
3
      
2
      
0.728175
      
0.699787
      
0.486835
      
1.123082
    
    

      
3
      
3
      
0.803968
      
0.797463
      
0.659578
      
2.612590
    
    

      
3
      
4
      
0.884524
      
0.875133
      
0.792827
      
4.247366
    
    

      
3
      
5
      
0.908730
      
0.890969
      
0.804641
      
5.754416
    
    

      
3
      
6
      
0.910714
      
0.893630
      
0.808945
      
7.219536
    
    

      
1
      
5
      
2
      
0.500397
      
0.471123
      
0.271392
      
1.376509
    
    

      
5
      
3
      
0.507937
      
0.473075
      
0.269789
      
2.793978
    
    

      
5
      
4
      
0.750794
      
0.556112
      
0.338481
      
14.227843
    
    

      
5
      
5
      
0.631349
      
0.513751
      
0.276034
      
5.504664
    
    

      
5
      
6
      
0.820635
      
0.624956
      
0.425401
      
28.022108
    
    

      
5
      
7
      
0.708730
      
0.533357
      
0.301013
      
8.269593
    
    

      
5
      
8
      
0.783333
      
0.572525
      
0.368523
      
16.913385
    
    

      
5
      
10
      
0.790476
      
0.586409
      
0.394093
      
18.364748
    
    

      
5
      
11
      
0.760714
      
0.550612
      
0.329114
      
12.886392
    
    

      
5
      
12
      
0.823810
      
0.634626
      
0.428101
      
30.803165
    
    

      
5
      
14
      
0.805159
      
0.594837
      
0.408776
      
21.142184
    
    

      
5
      
16
      
0.821032
      
0.598563
      
0.414852
      
22.553295
    
    

      
5
      
18
      
0.829365
      
0.642699
      
0.429114
      
33.540665
    
    

      
5
      
20
      
0.821032
      
0.602067
      
0.419494
      
25.264237
    
    

      
5
      
22
      
0.817857
      
0.620697
      
0.424557
      
26.673722
    
    

      
5
      
9
      
0.823413
      
0.629524
      
0.426076
      
29.328593
    
    

      
5
      
15
      
0.831349
      
0.640836
      
0.428776
      
32.154849
    
    

      
5
      
21
      
0.818254
      
0.646159
      
0.429536
      
34.924899
    
    

      
5
      
24
      
0.828175
      
0.650018
      
0.430464
      
36.292585
    
    

      
5
      
27
      
0.814286
      
0.654276
      
0.431308
      
37.616300
    
    

      
5
      
30
      
0.830952
      
0.656893
      
0.431983
      
38.982371
    
    

      
5
      
33
      
0.824206
      
0.658534
      
0.432658
      
40.437156
    
    

      
8
      
5
      
2
      
0.468651
      
0.505101
      
0.616878
      
1.471498
    
    

      
5
      
3
      
0.692460
      
0.681201
      
0.622700
      
2.879770
    
    

      
5
      
4
      
0.783333
      
0.728442
      
0.620759
      
4.227787
    
    

      
5
      
18
      
0.869841
      
0.749601
      
0.532405
      
23.238795
    
    

      
5
      
20
      
0.868651
      
0.739044
      
0.512574
      
15.625380
    
    

      
5
      
22
      
0.867857
      
0.744500
      
0.522785
      
16.633543
    
    

      
5
      
6
      
0.863492
      
0.745076
      
0.523882
      
17.731955
    
    

      
5
      
9
      
0.868651
      
0.746141
      
0.525823
      
19.028329
    
    

      
5
      
12
      
0.874603
      
0.747649
      
0.528692
      
20.448555
    
    

      
5
      
15
      
0.869841
      
0.748536
      
0.530380
      
21.791425
    
    

      
5
      
21
      
0.876587
      
0.750798
      
0.534684
      
24.596785
    
    

      
5
      
24
      
0.884127
      
0.752928
      
0.538397
      
25.994330
    
    

      
5
      
27
      
0.879365
      
0.756210
      
0.544473
      
27.368817
    
    

      
5
      
30
      
0.884127
      
0.757186
      
0.546160
      
28.746180
    
    

      
5
      
33
      
0.868651
      
0.757452
      
0.546498
      
30.116699
    
    

      
32
      
5
      
2
      
0.477778
      
0.532958
      
0.749030
      
1.629867
    
    

      
5
      
3
      
0.496825
      
0.551366
      
0.767764
      
3.185793
    
    

      
5
      
4
      
0.881349
      
0.873891
      
0.775021
      
16.964964
    
    

      
5
      
5
      
0.668254
      
0.685016
      
0.762110
      
6.242048
    
    

      
5
      
6
      
0.892460
      
0.878282
      
0.779831
      
30.114800
    
    

      
5
      
7
      
0.812698
      
0.807488
      
0.746835
      
9.253996
    
    

      
5
      
8
      
0.879365
      
0.876198
      
0.776878
      
20.063834
    
    

      
5
      
9
      
0.851190
      
0.866528
      
0.779747
      
12.327079
    
    

      
5
      
10
      
0.886508
      
0.877040
      
0.777806
      
21.599068
    
    

      
5
      
11
      
0.865873
      
0.873270
      
0.775527
      
15.472204
    
    

      
5
      
12
      
0.887698
      
0.877129
      
0.777975
      
23.123441
    
    

      
5
      
18
      
0.894444
      
0.878194
      
0.779831
      
26.295696
    
    

      
5
      
22
      
0.904365
      
0.878238
      
0.779747
      
28.607611
    
    

      
5
      
15
      
0.903571
      
0.878460
      
0.780084
      
33.232840
    
    

      
122
      
5
      
2
      
0.597222
      
0.678007
      
0.731392
      
2.281325
    
    

      
5
      
3
      
0.730159
      
0.797995
      
0.731308
      
4.541728
    
    

      
5
      
4
      
0.778968
      
0.820617
      
0.727848
      
6.730656
    
    

      
5
      
5
      
0.800397
      
0.830642
      
0.729789
      
8.857712
    
    

      
5
      
6
      
0.827381
      
0.833481
      
0.715359
      
11.024981
    
    

      
5
      
9
      
0.871825
      
0.837074
      
0.704979
      
16.240678
    
  

1335 rows × 5 columns