Sequence Graph Transform (SGT) is a sequence embedding function. SGT extracts the short- and long-term sequence features and embeds them in a finite-dimensional feature space. With SGT you can tune the amount of short- to long-term patterns extracted in the embeddings without any increase in the computation.
Project description
# -*- coding: utf-8 -*-
# Authors: Chitta Ranjan <cran2367@gmail.com>
#
# License: BSD 3 clause
Sgt definition.
Purpose
Sequence Graph Transform (SGT) is a sequence embedding function. SGT extracts the short- and long-term sequence features and embeds them in a finite-dimensional feature space. With SGT you can tune the amount of short- to long-term patterns extracted in the embeddings without any increase in the computation."
'''
Compute embedding of a single or a collection of discrete item
sequences. A discrete item sequence is a sequence made from a set
discrete elements, also known as alphabet set. For example,
suppose the alphabet set is the set of roman letters,
{A, B, ..., Z}. This set is made of discrete elements. Examples of
sequences from such a set are AABADDSA, UADSFJPFFFOIHOUGD, etc.
Such sequence datasets are commonly found in online industry,
for example, item purchase history, where the alphabet set is
the set of all product items. Sequence datasets are abundant in
bioinformatics as protein sequences.
Using the embeddings created here, classification and clustering
models can be built for sequence datasets.
Read more in https://arxiv.org/pdf/1608.03533.pdf
'''
Parameters
----------
Input:
alphabets Optional, except if mode is Spark.
The set of alphabets that make up all
the sequences in the dataset. If not passed, the
alphabet set is automatically computed as the
unique set of elements that make all the sequences.
A list or 1d-array of the set of elements that make up the
sequences. For example, np.array(["A", "B", "C"].
If mode is 'spark', the alphabets are necessary.
kappa Tuning parameter, kappa > 0, to change the extraction of
long-term dependency. Higher the value the lesser
the long-term dependency captured in the embedding.
Typical values for kappa are 1, 5, 10.
lengthsensitive Default false. This is set to true if the embedding of
should have the information of the length of the sequence.
If set to false then the embedding of two sequences with
similar pattern but different lengths will be the same.
lengthsensitive = false is similar to length-normalization.
flatten Default True. If True the SGT embedding is flattened and returned as
a vector. Otherwise, it is returned as a matrix with the row and col
names same as the alphabets. The matrix form is used for
interpretation purposes. Especially, to understand how the alphabets
are "related". Otherwise, for applying machine learning or deep
learning algorithms, the embedding vectors are required.
mode Choices in {'default', 'multiprocessing', 'spark'}.
processors Used if mode is 'multiprocessing'. By default, the
number of processors used in multiprocessing is
number of available - 1.
lazy Used if mode is 'spark'. Default is False. If False,
the SGT embeddings are computed for each sequence
in the inputted RDD and returned as a list of
embedding vectors. Otherwise, the RDD map is returned.
'''
Attributes
----------
def fit(sequence)
Extract Sequence Graph Transform features using Algorithm-2 in https://arxiv.org/abs/1608.03533.
Input:
sequence An array of discrete elements. For example,
np.array(["B","B","A","C","A","C","A","A","B","A"].
Output:
sgt embedding sgt matrix or vector (depending on Flatten==False or True) of the sequence
--
def fit_transform(corpus)
Extract SGT embeddings for all sequences in a corpus. It finds
the alphabets encompassing all the sequences in the corpus, if not inputted.
However, if the mode is 'spark', then the alphabets list has to be
explicitly given in Sgt object declaration.
Input:
corpus A list of sequences. Each sequence is a list of alphabets.
Output:
sgt embedding of all sequences in the corpus.
--
def transform(corpus)
Find SGT embeddings of a new data sample belonging to the same population
of the corpus that was fitted initially.
Illustrative examples
import numpy as np
import pandas as pd
from itertools import chain
import warnings
########
from sklearn.preprocessing import LabelEncoder
import tensorflow as tf
from keras.datasets import imdb
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import LSTM
from tensorflow.keras.layers import Dropout
from tensorflow.keras.layers import Activation
from tensorflow.keras.layers import Flatten
from tensorflow.keras.layers import Embedding
from tensorflow.keras.preprocessing import sequence
from sklearn.model_selection import train_test_split
from sklearn.model_selection import KFold
from sklearn.model_selection import StratifiedKFold
import sklearn.metrics
import time
from sklearn.decomposition import PCA
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
%matplotlib inline
np.random.seed(7) # fix random seed for reproducibility
from sgt import Sgt
Using TensorFlow backend.
Installation Test Examples
# Learning a sgt embedding as a matrix with
# rows and columns as the sequence alphabets.
# This embedding shows the relationship between
# the alphabets. The higher the value the
# stronger the relationship.
sgt = Sgt(flatten=False)
sequence = np.array(["B","B","A","C","A","C","A","A","B","A"])
sgt.fit(sequence)
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| A | B | C | |
|---|---|---|---|
| A | 0.906163 | 1.310023 | 2.618487 |
| B | 0.865694 | 1.230423 | 0.525440 |
| C | 1.371416 | 0.282625 | 1.353353 |
# Learning the sgt embeddings as vector for
# all sequences in a corpus.
sgt = Sgt(kappa=1, lengthsensitive=False)
corpus = [["B","B","A","C","A","C","A","A","B","A"], ["C", "Z", "Z", "Z", "D"]]
s = sgt.fit_transform(corpus)
print(s)
[[0.90616284 1.31002279 2.6184865 0. 0. 0.86569371
1.23042262 0.52543984 0. 0. 1.37141609 0.28262508
1.35335283 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. ]
[0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0.09157819 0.92166965 0. 0. 0.
0. 0. 0. 0. 0. 0.92166965
1.45182361]]
# Change the parameters from default to
# a tuned value.
sgt = Sgt(kappa=5, lengthsensitive=True)
corpus = [["B","B","A","C","A","C","A","A","B","A"], ["C", "Z", "Z", "Z", "D"]]
s = sgt.fit_transform(corpus)
print(s)
[[0.23305129 0.2791752 0.33922608 0. 0. 0.26177435
0.29531212 0.10270374 0. 0. 0.28654051 0.04334255
0.13533528 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. ]
[0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0.01831564 0.29571168 0. 0. 0.
0. 0. 0. 0. 0. 0.29571168
0.3394528 ]]
# Change the mode for faster computation.
# Mode: 'multiprocessing'
# Uses the multiple processors (CPUs) avalaible.
corpus = [["B","B","A","C","A","C","A","A","B","A"], ["C", "Z", "Z", "Z", "D"]]
sgt = Sgt(mode='multiprocessing')
s = sgt.fit_transform(corpus)
print(s)
[[0.90616284 1.31002279 2.6184865 0. 0. 0.86569371
1.23042262 0.52543984 0. 0. 1.37141609 0.28262508
1.35335283 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. ]
[0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.
0. 0.09157819 0.92166965 0. 0. 0.
0. 0. 0. 0. 0. 0.92166965
1.45182361]]
# Change the mode for faster computation.
# Mode: 'spark'
# Uses spark RDD.
from pyspark import SparkContext
sc = SparkContext("local", "app")
corpus = [["B","B","A","C","A","C","A","A","B","A"], ["C", "Z", "Z", "Z", "D"]]
rdd = sc.parallelize(corpus)
sgt_sc = sgt.Sgt(kappa = 1,
lengthsensitive = False,
mode="spark",
alphabets=["A", "B", "C", "D", "Z"],
lazy=False)
s = sgt_sc.fit_transform(corpus=rdd)
print(s)
Real data examples
Protein Sequence Data Analysis
The data used here is taken from www.uniprot.org. This is a public database for proteins. The data contains the protein sequences and their functions. In the following, we will demonstrate
- clustering of the sequences.
- classification of the sequences with the functions as labels.
protein_data=pd.read_csv('../data/protein_classification.csv')
X=protein_data['Sequence']
def split(word):
return [char for char in word]
sequences = [split(x) for x in X]
print(sequences[0])
['M', 'E', 'I', 'E', 'K', 'T', 'N', 'R', 'M', 'N', 'A', 'L', 'F', 'E', 'F', 'Y', 'A', 'A', 'L', 'L', 'T', 'D', 'K', 'Q', 'M', 'N', 'Y', 'I', 'E', 'L', 'Y', 'Y', 'A', 'D', 'D', 'Y', 'S', 'L', 'A', 'E', 'I', 'A', 'E', 'E', 'F', 'G', 'V', 'S', 'R', 'Q', 'A', 'V', 'Y', 'D', 'N', 'I', 'K', 'R', 'T', 'E', 'K', 'I', 'L', 'E', 'D', 'Y', 'E', 'M', 'K', 'L', 'H', 'M', 'Y', 'S', 'D', 'Y', 'I', 'V', 'R', 'S', 'Q', 'I', 'F', 'D', 'Q', 'I', 'L', 'E', 'R', 'Y', 'P', 'K', 'D', 'D', 'F', 'L', 'Q', 'E', 'Q', 'I', 'E', 'I', 'L', 'T', 'S', 'I', 'D', 'N', 'R', 'E']
Generating sequence embeddings
sgt = Sgt(kappa=1, lengthsensitive=False, mode='multiprocessing')
%%time
embedding = sgt.fit_transform(corpus=sequences)
CPU times: user 79.5 ms, sys: 46 ms, total: 125 ms
Wall time: 6.61 s
embedding.shape
(2112, 400)
Sequence Clustering
We perform PCA on the sequence embeddings and then do kmeans clustering.
pca = PCA(n_components=2)
pca.fit(embedding)
X=pca.transform(embedding)
print(np.sum(pca.explained_variance_ratio_))
df = pd.DataFrame(data=X, columns=['x1', 'x2'])
df.head()
0.6432744907364913
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| x1 | x2 | |
|---|---|---|
| 0 | 0.384913 | -0.269873 |
| 1 | 0.022764 | 0.135995 |
| 2 | 0.177792 | -0.172454 |
| 3 | 0.168074 | -0.147334 |
| 4 | 0.383616 | -0.271163 |
kmeans = KMeans(n_clusters=3, max_iter =300)
kmeans.fit(df)
labels = kmeans.predict(df)
centroids = kmeans.cluster_centers_
fig = plt.figure(figsize=(5, 5))
colmap = {1: 'r', 2: 'g', 3: 'b'}
colors = list(map(lambda x: colmap[x+1], labels))
plt.scatter(df['x1'], df['x2'], color=colors, alpha=0.5, edgecolor=colors)
<matplotlib.collections.PathCollection at 0x13bd97438>
Sequence Classification
We perform PCA on the sequence embeddings and then do kmeans clustering.
y = protein_data['Function [CC]']
encoder = LabelEncoder()
encoder.fit(y)
encoded_y = encoder.transform(y)
We will perform a 10-fold cross-validation to measure the performance of the classification model.
kfold = 10
X = pd.DataFrame(embedding)
y = encoded_y
random_state = 1
test_F1 = np.zeros(kfold)
skf = KFold(n_splits = kfold, shuffle = True, random_state = random_state)
k = 0
epochs = 50
batch_size = 128
for train_index, test_index in skf.split(X, y):
X_train, X_test = X.iloc[train_index], X.iloc[test_index]
y_train, y_test = y[train_index], y[test_index]
model = Sequential()
model.add(Dense(64, input_shape = (X_train.shape[1],)))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(32))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(1))
model.add(Activation('sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(X_train, y_train ,batch_size=batch_size, epochs=epochs, verbose=0)
y_pred = model.predict_proba(X_test).round().astype(int)
y_train_pred = model.predict_proba(X_train).round().astype(int)
test_F1[k] = sklearn.metrics.f1_score(y_test, y_pred)
k+=1
print ('Average f1 score', np.mean(test_F1))
Average f1 score 1.0
Weblog Data Analysis
This data sample is taken from https://www.ll.mit.edu/r-d/datasets/1998-darpa-intrusion-detection-evaluation-dataset. This is a network intrusion data containing audit logs and any attack as a positive label. Since, network intrusion is a rare event, the data is unbalanced. Here we will,
- build a sequence classification model to predict a network intrusion.
Each sequence contains in the data is a series of activity, for example, {login, password}. The alphabets in the input data sequences are already encoded into integers. The original sequences data file is also present in the /data directory.
darpa_data = pd.read_csv('../data/darpa_data.csv')
darpa_data.columns
Index(['timeduration', 'seqlen', 'seq', 'class'], dtype='object')
X = darpa_data['seq']
sequences = [x.split('~') for x in X]
y = darpa_data['class']
encoder = LabelEncoder()
encoder.fit(y)
y = encoder.transform(y)
Generating sequence embeddings
In this data, the sequence embeddings should be length-sensitive. The lengths are important here because sequences with similar patterns but different lengths can have different labels. Consider a simple example of two sessions: {login, pswd, login, pswd,...} and {login, pswd,...(repeated several times)..., login, pswd}. While the first session can be a regular user mistyping the password once, the other session is possibly an attack to guess the password. Thus, the sequence lengths are as important as the patterns.
sgt_darpa = Sgt(kappa=5, lengthsensitive=True, mode='multiprocessing')
embedding = sgt_darpa.fit_transform(corpus=sequences)
pd.DataFrame(embedding).to_csv(path_or_buf='tmp.csv', index=False)
pd.DataFrame(embedding).head()
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| 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ... | 2391 | 2392 | 2393 | 2394 | 2395 | 2396 | 2397 | 2398 | 2399 | 2400 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.069114 | 0.0 | 0.000000e+00 | 0.000000e+00 | 0.0 | 0.000000e+00 | 0.000000 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000e+00 | 0.0 | 0.000000e+00 | 0.000000e+00 |
| 1 | 0.000000 | 0.0 | 4.804190e-09 | 7.041516e-10 | 0.0 | 2.004958e-12 | 0.000132 | 1.046458e-07 | 5.863092e-16 | 7.568986e-23 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.540296 | 5.739230e-32 | 0.0 | 0.000000e+00 | 0.000000e+00 |
| 2 | 0.000000 | 0.0 | 0.000000e+00 | 0.000000e+00 | 0.0 | 0.000000e+00 | 0.000000 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000e+00 | 0.0 | 0.000000e+00 | 0.000000e+00 |
| 3 | 0.785666 | 0.0 | 0.000000e+00 | 0.000000e+00 | 0.0 | 0.000000e+00 | 0.000000 | 1.950089e-03 | 2.239981e-04 | 2.343180e-07 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.528133 | 1.576703e-09 | 0.0 | 2.516644e-29 | 1.484843e-57 |
| 4 | 0.000000 | 0.0 | 0.000000e+00 | 0.000000e+00 | 0.0 | 0.000000e+00 | 0.000000 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | ... | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000e+00 | 0.0 | 0.000000e+00 | 0.000000e+00 |
5 rows × 2401 columns
Applying PCA on the embeddings
The embeddings are sparse. We, therefore, apply PCA on the embeddings.
from sklearn.decomposition import PCA
pca = PCA(n_components=35)
pca.fit(embedding)
X = pca.transform(embedding)
print(np.sum(pca.explained_variance_ratio_))
0.9887812978739061
Building a Multi-Layer Perceptron Classifier
The PCA transforms of the embeddings are used directly as inputs to an MLP classifier.
kfold = 3
random_state = 11
test_F1 = np.zeros(kfold)
time_k = np.zeros(kfold)
skf = StratifiedKFold(n_splits=kfold, shuffle=True, random_state=random_state)
k = 0
epochs = 300
batch_size = 15
# class_weight = {0 : 1., 1: 1.,} # The weights can be changed and made inversely proportional to the class size to improve the accuracy.
class_weight = {0 : 0.12, 1: 0.88,}
for train_index, test_index in skf.split(X, y):
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
model = Sequential()
model.add(Dense(128, input_shape=(X_train.shape[1],)))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(1))
model.add(Activation('sigmoid'))
model.summary()
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
start_time = time.time()
model.fit(X_train, y_train ,batch_size=batch_size, epochs=epochs, verbose=1, class_weight=class_weight)
end_time = time.time()
time_k[k] = end_time-start_time
y_pred = model.predict_proba(X_test).round().astype(int)
y_train_pred = model.predict_proba(X_train).round().astype(int)
test_F1[k] = sklearn.metrics.f1_score(y_test, y_pred)
k += 1
Model: "sequential_10"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_30 (Dense) (None, 128) 4608
_________________________________________________________________
activation_30 (Activation) (None, 128) 0
_________________________________________________________________
dropout_20 (Dropout) (None, 128) 0
_________________________________________________________________
dense_31 (Dense) (None, 1) 129
_________________________________________________________________
activation_31 (Activation) (None, 1) 0
=================================================================
Total params: 4,737
Trainable params: 4,737
Non-trainable params: 0
_________________________________________________________________
WARNING:tensorflow:sample_weight modes were coerced from
...
to
['...']
Train on 74 samples
Epoch 1/300
74/74 [==============================] - 0s 6ms/sample - loss: 0.1404 - accuracy: 0.6216
Epoch 2/300
74/74 [==============================] - 0s 118us/sample - loss: 0.1386 - accuracy: 0.6486
Epoch 3/300
74/74 [==============================] - 0s 129us/sample - loss: 0.1404 - accuracy: 0.7568
Epoch 4/300
74/74 [==============================] - 0s 110us/sample - loss: 0.1309 - accuracy: 0.7297
Epoch 5/300
74/74 [==============================] - 0s 127us/sample - loss: 0.1274 - accuracy: 0.7162
Epoch 6/300
74/74 [==============================] - 0s 113us/sample - loss: 0.1142 - accuracy: 0.7568
Epoch 7/300
74/74 [==============================] - 0s 129us/sample - loss: 0.1041 - accuracy: 0.8784
Epoch 8/300
74/74 [==============================] - 0s 124us/sample - loss: 0.1027 - accuracy: 0.8243
Epoch 9/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0991 - accuracy: 0.8378
Epoch 10/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0862 - accuracy: 0.8649
Epoch 11/300
74/74 [==============================] - 0s 107us/sample - loss: 0.0930 - accuracy: 0.8649
Epoch 12/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0898 - accuracy: 0.8649
Epoch 13/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0827 - accuracy: 0.8784
Epoch 14/300
74/74 [==============================] - 0s 154us/sample - loss: 0.0790 - accuracy: 0.8784
Epoch 15/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0769 - accuracy: 0.8649
Epoch 16/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0801 - accuracy: 0.8514
Epoch 17/300
74/74 [==============================] - 0s 139us/sample - loss: 0.0740 - accuracy: 0.8784
Epoch 18/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0723 - accuracy: 0.8649
Epoch 19/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0679 - accuracy: 0.8649
Epoch 20/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0704 - accuracy: 0.8919
Epoch 21/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0621 - accuracy: 0.8649
Epoch 22/300
74/74 [==============================] - 0s 133us/sample - loss: 0.0627 - accuracy: 0.8919
Epoch 23/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0552 - accuracy: 0.8784
Epoch 24/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0599 - accuracy: 0.8784
Epoch 25/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0596 - accuracy: 0.8514
Epoch 26/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0579 - accuracy: 0.8784
Epoch 27/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0513 - accuracy: 0.8784
Epoch 28/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0533 - accuracy: 0.8784
Epoch 29/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0559 - accuracy: 0.8784
Epoch 30/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0537 - accuracy: 0.8649
Epoch 31/300
74/74 [==============================] - 0s 136us/sample - loss: 0.0472 - accuracy: 0.8649
Epoch 32/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0494 - accuracy: 0.8514
Epoch 33/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0511 - accuracy: 0.8649
Epoch 34/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0473 - accuracy: 0.8649
Epoch 35/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0507 - accuracy: 0.8649
Epoch 36/300
74/74 [==============================] - 0s 137us/sample - loss: 0.0468 - accuracy: 0.8649
Epoch 37/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0459 - accuracy: 0.8649
Epoch 38/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0428 - accuracy: 0.8649
Epoch 39/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0439 - accuracy: 0.8649
Epoch 40/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0388 - accuracy: 0.8649
Epoch 41/300
74/74 [==============================] - 0s 133us/sample - loss: 0.0406 - accuracy: 0.8649
Epoch 42/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0450 - accuracy: 0.8919
Epoch 43/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0403 - accuracy: 0.8784
Epoch 44/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0463 - accuracy: 0.8649
Epoch 45/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0443 - accuracy: 0.8784
Epoch 46/300
74/74 [==============================] - 0s 157us/sample - loss: 0.0437 - accuracy: 0.8514
Epoch 47/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0379 - accuracy: 0.8919
Epoch 48/300
74/74 [==============================] - 0s 138us/sample - loss: 0.0388 - accuracy: 0.8784
Epoch 49/300
74/74 [==============================] - 0s 142us/sample - loss: 0.0403 - accuracy: 0.8784
Epoch 50/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0344 - accuracy: 0.8919
Epoch 51/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0378 - accuracy: 0.8649
Epoch 52/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0403 - accuracy: 0.8784
Epoch 53/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0372 - accuracy: 0.9054
Epoch 54/300
74/74 [==============================] - 0s 146us/sample - loss: 0.0397 - accuracy: 0.8649
Epoch 55/300
74/74 [==============================] - 0s 141us/sample - loss: 0.0408 - accuracy: 0.8784
Epoch 56/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0422 - accuracy: 0.8649
Epoch 57/300
74/74 [==============================] - 0s 143us/sample - loss: 0.0372 - accuracy: 0.8649
Epoch 58/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0380 - accuracy: 0.8649
Epoch 59/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0413 - accuracy: 0.8649
Epoch 60/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0327 - accuracy: 0.8649
Epoch 61/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0358 - accuracy: 0.8649
Epoch 62/300
74/74 [==============================] - 0s 134us/sample - loss: 0.0359 - accuracy: 0.8649
Epoch 63/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0393 - accuracy: 0.8649
Epoch 64/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0387 - accuracy: 0.8784
Epoch 65/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0366 - accuracy: 0.8649
Epoch 66/300
74/74 [==============================] - 0s 136us/sample - loss: 0.0328 - accuracy: 0.8784
Epoch 67/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0390 - accuracy: 0.8649
Epoch 68/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0324 - accuracy: 0.8919
Epoch 69/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0349 - accuracy: 0.8649
Epoch 70/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0328 - accuracy: 0.8784
Epoch 71/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0359 - accuracy: 0.8649
Epoch 72/300
74/74 [==============================] - 0s 138us/sample - loss: 0.0383 - accuracy: 0.8514
Epoch 73/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0366 - accuracy: 0.8649
Epoch 74/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0359 - accuracy: 0.8919
Epoch 75/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0395 - accuracy: 0.8514
Epoch 76/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0363 - accuracy: 0.8649
Epoch 77/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0346 - accuracy: 0.8784
Epoch 78/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0370 - accuracy: 0.8649
Epoch 79/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0319 - accuracy: 0.8919
Epoch 80/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0349 - accuracy: 0.8649
Epoch 81/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0365 - accuracy: 0.8649
Epoch 82/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0359 - accuracy: 0.8514
Epoch 83/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0319 - accuracy: 0.8784
Epoch 84/300
74/74 [==============================] - 0s 138us/sample - loss: 0.0361 - accuracy: 0.8649
Epoch 85/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0294 - accuracy: 0.8784
Epoch 86/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0360 - accuracy: 0.8784
Epoch 87/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0325 - accuracy: 0.8784
Epoch 88/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0303 - accuracy: 0.8919
Epoch 89/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0309 - accuracy: 0.8784
Epoch 90/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0347 - accuracy: 0.8784
Epoch 91/300
74/74 [==============================] - 0s 139us/sample - loss: 0.0379 - accuracy: 0.8649
Epoch 92/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0382 - accuracy: 0.8514
Epoch 93/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0349 - accuracy: 0.8919
Epoch 94/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0274 - accuracy: 0.8919
Epoch 95/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0368 - accuracy: 0.8514
Epoch 96/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0281 - accuracy: 0.8649
Epoch 97/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0291 - accuracy: 0.9054
Epoch 98/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0299 - accuracy: 0.9054
Epoch 99/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0287 - accuracy: 0.8649
Epoch 100/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0353 - accuracy: 0.8649
Epoch 101/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0316 - accuracy: 0.8919
Epoch 102/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0299 - accuracy: 0.8649
Epoch 103/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0353 - accuracy: 0.8784
Epoch 104/300
74/74 [==============================] - 0s 105us/sample - loss: 0.0347 - accuracy: 0.8514
Epoch 105/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0294 - accuracy: 0.8784
Epoch 106/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0344 - accuracy: 0.8784
Epoch 107/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0323 - accuracy: 0.8919
Epoch 108/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0297 - accuracy: 0.9189
Epoch 109/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0333 - accuracy: 0.8649
Epoch 110/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0300 - accuracy: 0.8649
Epoch 111/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0369 - accuracy: 0.8514
Epoch 112/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0323 - accuracy: 0.8919
Epoch 113/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0361 - accuracy: 0.8919
Epoch 114/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0336 - accuracy: 0.8649
Epoch 115/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0291 - accuracy: 0.8649
Epoch 116/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0351 - accuracy: 0.8649
Epoch 117/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0288 - accuracy: 0.8649
Epoch 118/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0329 - accuracy: 0.8919
Epoch 119/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0393 - accuracy: 0.8784
Epoch 120/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0234 - accuracy: 0.8919
Epoch 121/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0381 - accuracy: 0.8784
Epoch 122/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0319 - accuracy: 0.8784
Epoch 123/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0286 - accuracy: 0.8919
Epoch 124/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0335 - accuracy: 0.8784
Epoch 125/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0324 - accuracy: 0.9054
Epoch 126/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0268 - accuracy: 0.8784
Epoch 127/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0359 - accuracy: 0.8649
Epoch 128/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0326 - accuracy: 0.9054
Epoch 129/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0305 - accuracy: 0.8784
Epoch 130/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0306 - accuracy: 0.8784
Epoch 131/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0318 - accuracy: 0.8649
Epoch 132/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0312 - accuracy: 0.8784
Epoch 133/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0330 - accuracy: 0.8919
Epoch 134/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0323 - accuracy: 0.8649
Epoch 135/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0330 - accuracy: 0.8649
Epoch 136/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0335 - accuracy: 0.8649
Epoch 137/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0363 - accuracy: 0.8514
Epoch 138/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0363 - accuracy: 0.8649
Epoch 139/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0334 - accuracy: 0.8649
Epoch 140/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0341 - accuracy: 0.8649
Epoch 141/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0298 - accuracy: 0.8919
Epoch 142/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0370 - accuracy: 0.8514
Epoch 143/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0325 - accuracy: 0.8649
Epoch 144/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0293 - accuracy: 0.8649
Epoch 145/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0380 - accuracy: 0.8514
Epoch 146/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0315 - accuracy: 0.8784
Epoch 147/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0328 - accuracy: 0.8649
Epoch 148/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0321 - accuracy: 0.8649
Epoch 149/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0286 - accuracy: 0.8649
Epoch 150/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0278 - accuracy: 0.8784
Epoch 151/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0297 - accuracy: 0.8784
Epoch 152/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0302 - accuracy: 0.9189
Epoch 153/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0332 - accuracy: 0.8649
Epoch 154/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0299 - accuracy: 0.8784
Epoch 155/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0359 - accuracy: 0.8649
Epoch 156/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0325 - accuracy: 0.8649
Epoch 157/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0318 - accuracy: 0.8649
Epoch 158/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0308 - accuracy: 0.8784
Epoch 159/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0295 - accuracy: 0.8649
Epoch 160/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0323 - accuracy: 0.8514
Epoch 161/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0314 - accuracy: 0.8919
Epoch 162/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0309 - accuracy: 0.8784
Epoch 163/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0304 - accuracy: 0.9189
Epoch 164/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0275 - accuracy: 0.8919
Epoch 165/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0327 - accuracy: 0.8784
Epoch 166/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0359 - accuracy: 0.8649
Epoch 167/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0304 - accuracy: 0.8919
Epoch 168/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0341 - accuracy: 0.8649
Epoch 169/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0316 - accuracy: 0.8649
Epoch 170/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0270 - accuracy: 0.8649
Epoch 171/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0300 - accuracy: 0.8649
Epoch 172/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0298 - accuracy: 0.9054
Epoch 173/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0270 - accuracy: 0.8919
Epoch 174/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0293 - accuracy: 0.8649
Epoch 175/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0337 - accuracy: 0.8649
Epoch 176/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0313 - accuracy: 0.8784
Epoch 177/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0327 - accuracy: 0.8784
Epoch 178/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0380 - accuracy: 0.8649
Epoch 179/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0295 - accuracy: 0.8649
Epoch 180/300
74/74 [==============================] - 0s 133us/sample - loss: 0.0337 - accuracy: 0.8514
Epoch 181/300
74/74 [==============================] - 0s 137us/sample - loss: 0.0344 - accuracy: 0.8649
Epoch 182/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0355 - accuracy: 0.8514
Epoch 183/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0330 - accuracy: 0.8784
Epoch 184/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0295 - accuracy: 0.8784
Epoch 185/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0368 - accuracy: 0.8514
Epoch 186/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0339 - accuracy: 0.8649
Epoch 187/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0283 - accuracy: 0.8649
Epoch 188/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0309 - accuracy: 0.8649
Epoch 189/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0315 - accuracy: 0.8919
Epoch 190/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0285 - accuracy: 0.8649
Epoch 191/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0339 - accuracy: 0.8649
Epoch 192/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0285 - accuracy: 0.8784
Epoch 193/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0304 - accuracy: 0.8919
Epoch 194/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0355 - accuracy: 0.8784
Epoch 195/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0392 - accuracy: 0.8514
Epoch 196/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0282 - accuracy: 0.8784
Epoch 197/300
74/74 [==============================] - 0s 134us/sample - loss: 0.0302 - accuracy: 0.8649
Epoch 198/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0324 - accuracy: 0.8649
Epoch 199/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0274 - accuracy: 0.8784
Epoch 200/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0289 - accuracy: 0.8784
Epoch 201/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0375 - accuracy: 0.8514
Epoch 202/300
74/74 [==============================] - 0s 133us/sample - loss: 0.0337 - accuracy: 0.8649
Epoch 203/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0329 - accuracy: 0.8649
Epoch 204/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0303 - accuracy: 0.8649
Epoch 205/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0335 - accuracy: 0.8784
Epoch 206/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0304 - accuracy: 0.8649
Epoch 207/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0339 - accuracy: 0.8649
Epoch 208/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0261 - accuracy: 0.8784
Epoch 209/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0304 - accuracy: 0.8649
Epoch 210/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0303 - accuracy: 0.8649
Epoch 211/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0318 - accuracy: 0.8784
Epoch 212/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0358 - accuracy: 0.8919
Epoch 213/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0272 - accuracy: 0.8784
Epoch 214/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0293 - accuracy: 0.8649
Epoch 215/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0347 - accuracy: 0.8649
Epoch 216/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0302 - accuracy: 0.8649
Epoch 217/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0331 - accuracy: 0.8784
Epoch 218/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0283 - accuracy: 0.8784
Epoch 219/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0329 - accuracy: 0.8649
Epoch 220/300
74/74 [==============================] - 0s 136us/sample - loss: 0.0291 - accuracy: 0.8919
Epoch 221/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0323 - accuracy: 0.8784
Epoch 222/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0341 - accuracy: 0.8784
Epoch 223/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0310 - accuracy: 0.8919
Epoch 224/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0337 - accuracy: 0.8784
Epoch 225/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0359 - accuracy: 0.8649
Epoch 226/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0355 - accuracy: 0.8649
Epoch 227/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0321 - accuracy: 0.8649
Epoch 228/300
74/74 [==============================] - 0s 140us/sample - loss: 0.0353 - accuracy: 0.8649
Epoch 229/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0323 - accuracy: 0.8784
Epoch 230/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0332 - accuracy: 0.8649
Epoch 231/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0350 - accuracy: 0.8649
Epoch 232/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0279 - accuracy: 0.8919
Epoch 233/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0321 - accuracy: 0.8649
Epoch 234/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0334 - accuracy: 0.8649
Epoch 235/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0327 - accuracy: 0.8649
Epoch 236/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0316 - accuracy: 0.8649
Epoch 237/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0292 - accuracy: 0.8919
Epoch 238/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0320 - accuracy: 0.8919
Epoch 239/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0312 - accuracy: 0.8649
Epoch 240/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0332 - accuracy: 0.8649
Epoch 241/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0296 - accuracy: 0.8649
Epoch 242/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0331 - accuracy: 0.8649
Epoch 243/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0258 - accuracy: 0.8784
Epoch 244/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0316 - accuracy: 0.8919
Epoch 245/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0321 - accuracy: 0.8784
Epoch 246/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0306 - accuracy: 0.8649
Epoch 247/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0319 - accuracy: 0.8649
Epoch 248/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0275 - accuracy: 0.8784
Epoch 249/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0318 - accuracy: 0.8649
Epoch 250/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0324 - accuracy: 0.8649
Epoch 251/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0311 - accuracy: 0.8919
Epoch 252/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0335 - accuracy: 0.8649
Epoch 253/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0334 - accuracy: 0.8649
Epoch 254/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0359 - accuracy: 0.8514
Epoch 255/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0326 - accuracy: 0.8784
Epoch 256/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0321 - accuracy: 0.8649
Epoch 257/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0343 - accuracy: 0.8784
Epoch 258/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0309 - accuracy: 0.8649
Epoch 259/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0301 - accuracy: 0.8649
Epoch 260/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0315 - accuracy: 0.8649
Epoch 261/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0342 - accuracy: 0.8649
Epoch 262/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0300 - accuracy: 0.8649
Epoch 263/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0358 - accuracy: 0.8649
Epoch 264/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0295 - accuracy: 0.8649
Epoch 265/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0356 - accuracy: 0.8649
Epoch 266/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0318 - accuracy: 0.8649
Epoch 267/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0298 - accuracy: 0.8784
Epoch 268/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0278 - accuracy: 0.8649
Epoch 269/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0302 - accuracy: 0.8649
Epoch 270/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0305 - accuracy: 0.8649
Epoch 271/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0324 - accuracy: 0.8649
Epoch 272/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0322 - accuracy: 0.8784
Epoch 273/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0302 - accuracy: 0.8649
Epoch 274/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0309 - accuracy: 0.8649
Epoch 275/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0296 - accuracy: 0.8649
Epoch 276/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0285 - accuracy: 0.8649
Epoch 277/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0324 - accuracy: 0.8649
Epoch 278/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0349 - accuracy: 0.8514
Epoch 279/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0347 - accuracy: 0.8649
Epoch 280/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0320 - accuracy: 0.8649
Epoch 281/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0350 - accuracy: 0.8784
Epoch 282/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0320 - accuracy: 0.8649
Epoch 283/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0331 - accuracy: 0.8649
Epoch 284/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0283 - accuracy: 0.8649
Epoch 285/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0321 - accuracy: 0.8649
Epoch 286/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0306 - accuracy: 0.8649
Epoch 287/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0306 - accuracy: 0.8784
Epoch 288/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0324 - accuracy: 0.8649
Epoch 289/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0347 - accuracy: 0.8514
Epoch 290/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0362 - accuracy: 0.8514
Epoch 291/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0330 - accuracy: 0.8649
Epoch 292/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0306 - accuracy: 0.8649
Epoch 293/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0326 - accuracy: 0.8649
Epoch 294/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0346 - accuracy: 0.8649
Epoch 295/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0335 - accuracy: 0.8649
Epoch 296/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0304 - accuracy: 0.8649
Epoch 297/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0303 - accuracy: 0.8784
Epoch 298/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0324 - accuracy: 0.8649
Epoch 299/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0323 - accuracy: 0.8649
Epoch 300/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0297 - accuracy: 0.8649
Model: "sequential_11"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_32 (Dense) (None, 128) 4608
_________________________________________________________________
activation_32 (Activation) (None, 128) 0
_________________________________________________________________
dropout_21 (Dropout) (None, 128) 0
_________________________________________________________________
dense_33 (Dense) (None, 1) 129
_________________________________________________________________
activation_33 (Activation) (None, 1) 0
=================================================================
Total params: 4,737
Trainable params: 4,737
Non-trainable params: 0
_________________________________________________________________
WARNING:tensorflow:sample_weight modes were coerced from
...
to
['...']
Train on 74 samples
Epoch 1/300
74/74 [==============================] - 0s 6ms/sample - loss: 0.1394 - accuracy: 0.6757
Epoch 2/300
74/74 [==============================] - 0s 124us/sample - loss: 0.1322 - accuracy: 0.7568
Epoch 3/300
74/74 [==============================] - 0s 125us/sample - loss: 0.1254 - accuracy: 0.7973
Epoch 4/300
74/74 [==============================] - 0s 124us/sample - loss: 0.1130 - accuracy: 0.7973
Epoch 5/300
74/74 [==============================] - 0s 118us/sample - loss: 0.1276 - accuracy: 0.7568
Epoch 6/300
74/74 [==============================] - 0s 116us/sample - loss: 0.1141 - accuracy: 0.9054
Epoch 7/300
74/74 [==============================] - 0s 123us/sample - loss: 0.1047 - accuracy: 0.8514
Epoch 8/300
74/74 [==============================] - 0s 119us/sample - loss: 0.1044 - accuracy: 0.8784
Epoch 9/300
74/74 [==============================] - 0s 121us/sample - loss: 0.1066 - accuracy: 0.8919
Epoch 10/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0914 - accuracy: 0.8919
Epoch 11/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0893 - accuracy: 0.9054
Epoch 12/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0854 - accuracy: 0.9054
Epoch 13/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0835 - accuracy: 0.8919
Epoch 14/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0761 - accuracy: 0.9054
Epoch 15/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0776 - accuracy: 0.9189
Epoch 16/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0744 - accuracy: 0.9189
Epoch 17/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0717 - accuracy: 0.9189
Epoch 18/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0722 - accuracy: 0.9054
Epoch 19/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0662 - accuracy: 0.8919
Epoch 20/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0679 - accuracy: 0.9189
Epoch 21/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0633 - accuracy: 0.9189
Epoch 22/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0597 - accuracy: 0.9189
Epoch 23/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0615 - accuracy: 0.8919
Epoch 24/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0586 - accuracy: 0.9189
Epoch 25/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0625 - accuracy: 0.9054
Epoch 26/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0528 - accuracy: 0.9189
Epoch 27/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0592 - accuracy: 0.9054
Epoch 28/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0547 - accuracy: 0.9189
Epoch 29/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0532 - accuracy: 0.9054
Epoch 30/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0529 - accuracy: 0.9189
Epoch 31/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0491 - accuracy: 0.9189
Epoch 32/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0557 - accuracy: 0.9189
Epoch 33/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0480 - accuracy: 0.9189
Epoch 34/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0480 - accuracy: 0.9189
Epoch 35/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0449 - accuracy: 0.9189
Epoch 36/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0452 - accuracy: 0.9189
Epoch 37/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0472 - accuracy: 0.9189
Epoch 38/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0494 - accuracy: 0.9189
Epoch 39/300
74/74 [==============================] - 0s 171us/sample - loss: 0.0431 - accuracy: 0.9189
Epoch 40/300
74/74 [==============================] - 0s 157us/sample - loss: 0.0429 - accuracy: 0.9189
Epoch 41/300
74/74 [==============================] - 0s 151us/sample - loss: 0.0438 - accuracy: 0.9189
Epoch 42/300
74/74 [==============================] - 0s 177us/sample - loss: 0.0412 - accuracy: 0.9189
Epoch 43/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0427 - accuracy: 0.9189
Epoch 44/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0416 - accuracy: 0.9054
Epoch 45/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0382 - accuracy: 0.9189
Epoch 46/300
74/74 [==============================] - 0s 134us/sample - loss: 0.0392 - accuracy: 0.9189
Epoch 47/300
74/74 [==============================] - 0s 106us/sample - loss: 0.0406 - accuracy: 0.9189
Epoch 48/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0368 - accuracy: 0.9189
Epoch 49/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0412 - accuracy: 0.9189
Epoch 50/300
74/74 [==============================] - 0s 134us/sample - loss: 0.0352 - accuracy: 0.9189
Epoch 51/300
74/74 [==============================] - 0s 138us/sample - loss: 0.0420 - accuracy: 0.9189
Epoch 52/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0377 - accuracy: 0.9189
Epoch 53/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0392 - accuracy: 0.9189
Epoch 54/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0380 - accuracy: 0.9189
Epoch 55/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0352 - accuracy: 0.9189
Epoch 56/300
74/74 [==============================] - 0s 140us/sample - loss: 0.0348 - accuracy: 0.9189
Epoch 57/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0365 - accuracy: 0.9189
Epoch 58/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0319 - accuracy: 0.9189
Epoch 59/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0350 - accuracy: 0.9054
Epoch 60/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0373 - accuracy: 0.9189
Epoch 61/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0382 - accuracy: 0.9189
Epoch 62/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0346 - accuracy: 0.9189
Epoch 63/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0312 - accuracy: 0.9189
Epoch 64/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0349 - accuracy: 0.9189
Epoch 65/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0345 - accuracy: 0.9189
Epoch 66/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0312 - accuracy: 0.9189
Epoch 67/300
74/74 [==============================] - 0s 107us/sample - loss: 0.0322 - accuracy: 0.9189
Epoch 68/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0307 - accuracy: 0.9189
Epoch 69/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0308 - accuracy: 0.9189
Epoch 70/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0368 - accuracy: 0.9189
Epoch 71/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0312 - accuracy: 0.9189
Epoch 72/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0337 - accuracy: 0.9189
Epoch 73/300
74/74 [==============================] - 0s 136us/sample - loss: 0.0319 - accuracy: 0.9189
Epoch 74/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0344 - accuracy: 0.9189
Epoch 75/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0338 - accuracy: 0.9189
Epoch 76/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0303 - accuracy: 0.9189
Epoch 77/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0303 - accuracy: 0.9189
Epoch 78/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0250 - accuracy: 0.9189
Epoch 79/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0301 - accuracy: 0.9189
Epoch 80/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0333 - accuracy: 0.9189
Epoch 81/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0294 - accuracy: 0.9189
Epoch 82/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0271 - accuracy: 0.9189
Epoch 83/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0327 - accuracy: 0.9189
Epoch 84/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0297 - accuracy: 0.9189
Epoch 85/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0309 - accuracy: 0.9189
Epoch 86/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0331 - accuracy: 0.9189
Epoch 87/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0327 - accuracy: 0.9189
Epoch 88/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0323 - accuracy: 0.9189
Epoch 89/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0275 - accuracy: 0.9189
Epoch 90/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0304 - accuracy: 0.9189
Epoch 91/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0293 - accuracy: 0.9189
Epoch 92/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0331 - accuracy: 0.9189
Epoch 93/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0298 - accuracy: 0.9189
Epoch 94/300
74/74 [==============================] - 0s 136us/sample - loss: 0.0311 - accuracy: 0.9189
Epoch 95/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0310 - accuracy: 0.9189
Epoch 96/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0309 - accuracy: 0.9189
Epoch 97/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0292 - accuracy: 0.9189
Epoch 98/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0311 - accuracy: 0.9189
Epoch 99/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0261 - accuracy: 0.9189
Epoch 100/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0305 - accuracy: 0.9189
Epoch 101/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0282 - accuracy: 0.9189
Epoch 102/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0355 - accuracy: 0.9189
Epoch 103/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0281 - accuracy: 0.9189
Epoch 104/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0286 - accuracy: 0.9189
Epoch 105/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0310 - accuracy: 0.9189
Epoch 106/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0269 - accuracy: 0.9189
Epoch 107/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0344 - accuracy: 0.9189
Epoch 108/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0323 - accuracy: 0.9189
Epoch 109/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0309 - accuracy: 0.9189
Epoch 110/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0258 - accuracy: 0.9189
Epoch 111/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0305 - accuracy: 0.9189
Epoch 112/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0274 - accuracy: 0.9189
Epoch 113/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0268 - accuracy: 0.9189
Epoch 114/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0283 - accuracy: 0.9189
Epoch 115/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0274 - accuracy: 0.9189
Epoch 116/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0311 - accuracy: 0.9189
Epoch 117/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0318 - accuracy: 0.9189
Epoch 118/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0265 - accuracy: 0.9189
Epoch 119/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0305 - accuracy: 0.9189
Epoch 120/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0258 - accuracy: 0.9189
Epoch 121/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0269 - accuracy: 0.9189
Epoch 122/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0323 - accuracy: 0.9189
Epoch 123/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0291 - accuracy: 0.9189
Epoch 124/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0292 - accuracy: 0.9189
Epoch 125/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0258 - accuracy: 0.9189
Epoch 126/300
74/74 [==============================] - 0s 103us/sample - loss: 0.0257 - accuracy: 0.9189
Epoch 127/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0321 - accuracy: 0.9189
Epoch 128/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0274 - accuracy: 0.9189
Epoch 129/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0284 - accuracy: 0.9189
Epoch 130/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0285 - accuracy: 0.9189
Epoch 131/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0272 - accuracy: 0.9189
Epoch 132/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0295 - accuracy: 0.9189
Epoch 133/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0273 - accuracy: 0.9189
Epoch 134/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0293 - accuracy: 0.9189
Epoch 135/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0295 - accuracy: 0.9189
Epoch 136/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0271 - accuracy: 0.9189
Epoch 137/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0292 - accuracy: 0.9189
Epoch 138/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0285 - accuracy: 0.9189
Epoch 139/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0299 - accuracy: 0.9189
Epoch 140/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0308 - accuracy: 0.9189
Epoch 141/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0256 - accuracy: 0.9189
Epoch 142/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0259 - accuracy: 0.9189
Epoch 143/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0256 - accuracy: 0.9189
Epoch 144/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0294 - accuracy: 0.9189
Epoch 145/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0275 - accuracy: 0.9189
Epoch 146/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0321 - accuracy: 0.9189
Epoch 147/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0258 - accuracy: 0.9189
Epoch 148/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0271 - accuracy: 0.9189
Epoch 149/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0286 - accuracy: 0.9189
Epoch 150/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0337 - accuracy: 0.9189
Epoch 151/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0277 - accuracy: 0.9189
Epoch 152/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0290 - accuracy: 0.9189
Epoch 153/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0259 - accuracy: 0.9189
Epoch 154/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0257 - accuracy: 0.9189
Epoch 155/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0263 - accuracy: 0.9189
Epoch 156/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0299 - accuracy: 0.9189
Epoch 157/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0283 - accuracy: 0.9189
Epoch 158/300
74/74 [==============================] - 0s 134us/sample - loss: 0.0325 - accuracy: 0.9189
Epoch 159/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0247 - accuracy: 0.9189
Epoch 160/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0305 - accuracy: 0.9189
Epoch 161/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0252 - accuracy: 0.9189
Epoch 162/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0282 - accuracy: 0.9189
Epoch 163/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0255 - accuracy: 0.9189
Epoch 164/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0265 - accuracy: 0.9189
Epoch 165/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0250 - accuracy: 0.9189
Epoch 166/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0300 - accuracy: 0.9189
Epoch 167/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0283 - accuracy: 0.9189
Epoch 168/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0321 - accuracy: 0.9189
Epoch 169/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0246 - accuracy: 0.9189
Epoch 170/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0230 - accuracy: 0.9189
Epoch 171/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0268 - accuracy: 0.9189
Epoch 172/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0263 - accuracy: 0.9189
Epoch 173/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0305 - accuracy: 0.9189
Epoch 174/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0262 - accuracy: 0.9189
Epoch 175/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0276 - accuracy: 0.9189
Epoch 176/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0254 - accuracy: 0.9189
Epoch 177/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0311 - accuracy: 0.9189
Epoch 178/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0311 - accuracy: 0.9189
Epoch 179/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0278 - accuracy: 0.9189
Epoch 180/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0313 - accuracy: 0.9189
Epoch 181/300
74/74 [==============================] - 0s 133us/sample - loss: 0.0291 - accuracy: 0.9189
Epoch 182/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0277 - accuracy: 0.9189
Epoch 183/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0276 - accuracy: 0.9189
Epoch 184/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0247 - accuracy: 0.9189
Epoch 185/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0314 - accuracy: 0.9189
Epoch 186/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0270 - accuracy: 0.9189
Epoch 187/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0306 - accuracy: 0.9189
Epoch 188/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0250 - accuracy: 0.9189
Epoch 189/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0280 - accuracy: 0.9189
Epoch 190/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0304 - accuracy: 0.9189
Epoch 191/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0286 - accuracy: 0.9189
Epoch 192/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0278 - accuracy: 0.9189
Epoch 193/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0225 - accuracy: 0.9189
Epoch 194/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0266 - accuracy: 0.9189
Epoch 195/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0260 - accuracy: 0.9189
Epoch 196/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0254 - accuracy: 0.9189
Epoch 197/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0268 - accuracy: 0.9189
Epoch 198/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0248 - accuracy: 0.9189
Epoch 199/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0285 - accuracy: 0.9189
Epoch 200/300
74/74 [==============================] - 0s 140us/sample - loss: 0.0237 - accuracy: 0.9189
Epoch 201/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0291 - accuracy: 0.9189
Epoch 202/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0290 - accuracy: 0.9189
Epoch 203/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0292 - accuracy: 0.9189
Epoch 204/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0307 - accuracy: 0.9189
Epoch 205/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0264 - accuracy: 0.9189
Epoch 206/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0288 - accuracy: 0.9189
Epoch 207/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0305 - accuracy: 0.9189
Epoch 208/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0252 - accuracy: 0.9189
Epoch 209/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0273 - accuracy: 0.9189
Epoch 210/300
74/74 [==============================] - 0s 138us/sample - loss: 0.0268 - accuracy: 0.9189
Epoch 211/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0259 - accuracy: 0.9189
Epoch 212/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0253 - accuracy: 0.9189
Epoch 213/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0244 - accuracy: 0.9189
Epoch 214/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0276 - accuracy: 0.9189
Epoch 215/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0281 - accuracy: 0.9189
Epoch 216/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0260 - accuracy: 0.9189
Epoch 217/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0265 - accuracy: 0.9189
Epoch 218/300
74/74 [==============================] - 0s 135us/sample - loss: 0.0301 - accuracy: 0.9189
Epoch 219/300
74/74 [==============================] - 0s 143us/sample - loss: 0.0279 - accuracy: 0.9189
Epoch 220/300
74/74 [==============================] - 0s 144us/sample - loss: 0.0254 - accuracy: 0.9189
Epoch 221/300
74/74 [==============================] - 0s 140us/sample - loss: 0.0259 - accuracy: 0.9189
Epoch 222/300
74/74 [==============================] - 0s 140us/sample - loss: 0.0238 - accuracy: 0.9189
Epoch 223/300
74/74 [==============================] - 0s 135us/sample - loss: 0.0303 - accuracy: 0.9189
Epoch 224/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0244 - accuracy: 0.9189
Epoch 225/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0270 - accuracy: 0.9189
Epoch 226/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0297 - accuracy: 0.9189
Epoch 227/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0266 - accuracy: 0.9189
Epoch 228/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0265 - accuracy: 0.9189
Epoch 229/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0240 - accuracy: 0.9189
Epoch 230/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0268 - accuracy: 0.9189
Epoch 231/300
74/74 [==============================] - 0s 141us/sample - loss: 0.0309 - accuracy: 0.9189
Epoch 232/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0305 - accuracy: 0.9189
Epoch 233/300
74/74 [==============================] - 0s 143us/sample - loss: 0.0279 - accuracy: 0.9189
Epoch 234/300
74/74 [==============================] - 0s 149us/sample - loss: 0.0267 - accuracy: 0.9189
Epoch 235/300
74/74 [==============================] - 0s 140us/sample - loss: 0.0281 - accuracy: 0.9189
Epoch 236/300
74/74 [==============================] - 0s 145us/sample - loss: 0.0283 - accuracy: 0.9189
Epoch 237/300
74/74 [==============================] - 0s 160us/sample - loss: 0.0263 - accuracy: 0.9189
Epoch 238/300
74/74 [==============================] - 0s 135us/sample - loss: 0.0286 - accuracy: 0.9189
Epoch 239/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0279 - accuracy: 0.9189
Epoch 240/300
74/74 [==============================] - 0s 142us/sample - loss: 0.0254 - accuracy: 0.9189
Epoch 241/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0297 - accuracy: 0.9189
Epoch 242/300
74/74 [==============================] - 0s 146us/sample - loss: 0.0276 - accuracy: 0.9189
Epoch 243/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0280 - accuracy: 0.9189
Epoch 244/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0280 - accuracy: 0.9189
Epoch 245/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0295 - accuracy: 0.9189
Epoch 246/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0250 - accuracy: 0.9189
Epoch 247/300
74/74 [==============================] - 0s 133us/sample - loss: 0.0298 - accuracy: 0.9189
Epoch 248/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0273 - accuracy: 0.9189
Epoch 249/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0283 - accuracy: 0.9189
Epoch 250/300
74/74 [==============================] - 0s 136us/sample - loss: 0.0232 - accuracy: 0.9189
Epoch 251/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0288 - accuracy: 0.9189
Epoch 252/300
74/74 [==============================] - 0s 135us/sample - loss: 0.0255 - accuracy: 0.9189
Epoch 253/300
74/74 [==============================] - 0s 146us/sample - loss: 0.0268 - accuracy: 0.9189
Epoch 254/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0249 - accuracy: 0.9189
Epoch 255/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0269 - accuracy: 0.9189
Epoch 256/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0259 - accuracy: 0.9189
Epoch 257/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0259 - accuracy: 0.9189
Epoch 258/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0247 - accuracy: 0.9189
Epoch 259/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0288 - accuracy: 0.9189
Epoch 260/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0272 - accuracy: 0.9189
Epoch 261/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0262 - accuracy: 0.9189
Epoch 262/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0285 - accuracy: 0.9189
Epoch 263/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0269 - accuracy: 0.9189
Epoch 264/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0289 - accuracy: 0.9189
Epoch 265/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0248 - accuracy: 0.9189
Epoch 266/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0243 - accuracy: 0.9189
Epoch 267/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0282 - accuracy: 0.9189
Epoch 268/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0269 - accuracy: 0.9189
Epoch 269/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0268 - accuracy: 0.9189
Epoch 270/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0272 - accuracy: 0.9189
Epoch 271/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0258 - accuracy: 0.9189
Epoch 272/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0255 - accuracy: 0.9189
Epoch 273/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0279 - accuracy: 0.9189
Epoch 274/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0262 - accuracy: 0.9189
Epoch 275/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0281 - accuracy: 0.9189
Epoch 276/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0247 - accuracy: 0.9189
Epoch 277/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0245 - accuracy: 0.9189
Epoch 278/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0279 - accuracy: 0.9189
Epoch 279/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0309 - accuracy: 0.9189
Epoch 280/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0240 - accuracy: 0.9189
Epoch 281/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0265 - accuracy: 0.9189
Epoch 282/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0267 - accuracy: 0.9189
Epoch 283/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0292 - accuracy: 0.9189
Epoch 284/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0270 - accuracy: 0.9189
Epoch 285/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0267 - accuracy: 0.9189
Epoch 286/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0299 - accuracy: 0.9189
Epoch 287/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0283 - accuracy: 0.9189
Epoch 288/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0248 - accuracy: 0.9189
Epoch 289/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0257 - accuracy: 0.9189
Epoch 290/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0257 - accuracy: 0.9189
Epoch 291/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0272 - accuracy: 0.9189
Epoch 292/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0301 - accuracy: 0.9189
Epoch 293/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0321 - accuracy: 0.9189
Epoch 294/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0241 - accuracy: 0.9189
Epoch 295/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0277 - accuracy: 0.9189
Epoch 296/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0254 - accuracy: 0.9189
Epoch 297/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0263 - accuracy: 0.9189
Epoch 298/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0276 - accuracy: 0.9189
Epoch 299/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0225 - accuracy: 0.9189
Epoch 300/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0309 - accuracy: 0.9189
Model: "sequential_12"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense_34 (Dense) (None, 128) 4608
_________________________________________________________________
activation_34 (Activation) (None, 128) 0
_________________________________________________________________
dropout_22 (Dropout) (None, 128) 0
_________________________________________________________________
dense_35 (Dense) (None, 1) 129
_________________________________________________________________
activation_35 (Activation) (None, 1) 0
=================================================================
Total params: 4,737
Trainable params: 4,737
Non-trainable params: 0
_________________________________________________________________
WARNING:tensorflow:sample_weight modes were coerced from
...
to
['...']
Train on 74 samples
Epoch 1/300
74/74 [==============================] - 0s 6ms/sample - loss: 0.1366 - accuracy: 0.6081
Epoch 2/300
74/74 [==============================] - 0s 142us/sample - loss: 0.1310 - accuracy: 0.7027
Epoch 3/300
74/74 [==============================] - 0s 119us/sample - loss: 0.1200 - accuracy: 0.7027
Epoch 4/300
74/74 [==============================] - 0s 120us/sample - loss: 0.1165 - accuracy: 0.7568
Epoch 5/300
74/74 [==============================] - 0s 115us/sample - loss: 0.1130 - accuracy: 0.7973
Epoch 6/300
74/74 [==============================] - 0s 127us/sample - loss: 0.1052 - accuracy: 0.7973
Epoch 7/300
74/74 [==============================] - 0s 111us/sample - loss: 0.1005 - accuracy: 0.8649
Epoch 8/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0983 - accuracy: 0.7973
Epoch 9/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0957 - accuracy: 0.7838
Epoch 10/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0917 - accuracy: 0.8514
Epoch 11/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0894 - accuracy: 0.8243
Epoch 12/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0860 - accuracy: 0.8514
Epoch 13/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0821 - accuracy: 0.8243
Epoch 14/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0786 - accuracy: 0.8378
Epoch 15/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0756 - accuracy: 0.8514
Epoch 16/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0779 - accuracy: 0.8784
Epoch 17/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0761 - accuracy: 0.8514
Epoch 18/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0713 - accuracy: 0.8378
Epoch 19/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0686 - accuracy: 0.8649
Epoch 20/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0678 - accuracy: 0.8649
Epoch 21/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0627 - accuracy: 0.8784
Epoch 22/300
74/74 [==============================] - 0s 135us/sample - loss: 0.0680 - accuracy: 0.8649
Epoch 23/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0629 - accuracy: 0.8514
Epoch 24/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0601 - accuracy: 0.8649
Epoch 25/300
74/74 [==============================] - 0s 132us/sample - loss: 0.0617 - accuracy: 0.8514
Epoch 26/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0586 - accuracy: 0.8649
Epoch 27/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0536 - accuracy: 0.8784
Epoch 28/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0583 - accuracy: 0.8649
Epoch 29/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0503 - accuracy: 0.8784
Epoch 30/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0528 - accuracy: 0.8784
Epoch 31/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0542 - accuracy: 0.8514
Epoch 32/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0519 - accuracy: 0.8649
Epoch 33/300
74/74 [==============================] - 0s 105us/sample - loss: 0.0576 - accuracy: 0.8514
Epoch 34/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0538 - accuracy: 0.8649
Epoch 35/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0475 - accuracy: 0.8649
Epoch 36/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0530 - accuracy: 0.8514
Epoch 37/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0467 - accuracy: 0.8784
Epoch 38/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0480 - accuracy: 0.8649
Epoch 39/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0444 - accuracy: 0.8784
Epoch 40/300
74/74 [==============================] - 0s 107us/sample - loss: 0.0432 - accuracy: 0.8784
Epoch 41/300
74/74 [==============================] - 0s 138us/sample - loss: 0.0445 - accuracy: 0.8649
Epoch 42/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0530 - accuracy: 0.8514
Epoch 43/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0483 - accuracy: 0.8649
Epoch 44/300
74/74 [==============================] - 0s 151us/sample - loss: 0.0430 - accuracy: 0.8919
Epoch 45/300
74/74 [==============================] - 0s 159us/sample - loss: 0.0415 - accuracy: 0.8649
Epoch 46/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0478 - accuracy: 0.8514
Epoch 47/300
74/74 [==============================] - 0s 138us/sample - loss: 0.0407 - accuracy: 0.8649
Epoch 48/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0394 - accuracy: 0.8649
Epoch 49/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0384 - accuracy: 0.8649
Epoch 50/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0406 - accuracy: 0.8649
Epoch 51/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0440 - accuracy: 0.8649
Epoch 52/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0469 - accuracy: 0.8649
Epoch 53/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0407 - accuracy: 0.8649
Epoch 54/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0403 - accuracy: 0.8784
Epoch 55/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0400 - accuracy: 0.8649
Epoch 56/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0371 - accuracy: 0.8784
Epoch 57/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0431 - accuracy: 0.8784
Epoch 58/300
74/74 [==============================] - 0s 107us/sample - loss: 0.0351 - accuracy: 0.8649
Epoch 59/300
74/74 [==============================] - 0s 134us/sample - loss: 0.0371 - accuracy: 0.8649
Epoch 60/300
74/74 [==============================] - 0s 136us/sample - loss: 0.0380 - accuracy: 0.8784
Epoch 61/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0354 - accuracy: 0.8919
Epoch 62/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0371 - accuracy: 0.8649
Epoch 63/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0360 - accuracy: 0.8784
Epoch 64/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0401 - accuracy: 0.8649
Epoch 65/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0412 - accuracy: 0.8649
Epoch 66/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0402 - accuracy: 0.8649
Epoch 67/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0416 - accuracy: 0.8649
Epoch 68/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0368 - accuracy: 0.8649
Epoch 69/300
74/74 [==============================] - 0s 134us/sample - loss: 0.0395 - accuracy: 0.8649
Epoch 70/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0357 - accuracy: 0.8649
Epoch 71/300
74/74 [==============================] - 0s 135us/sample - loss: 0.0365 - accuracy: 0.8649
Epoch 72/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0360 - accuracy: 0.8784
Epoch 73/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0360 - accuracy: 0.8649
Epoch 74/300
74/74 [==============================] - 0s 134us/sample - loss: 0.0324 - accuracy: 0.8649
Epoch 75/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0328 - accuracy: 0.8649
Epoch 76/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0390 - accuracy: 0.8784
Epoch 77/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0297 - accuracy: 0.8919
Epoch 78/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0415 - accuracy: 0.8649
Epoch 79/300
74/74 [==============================] - 0s 142us/sample - loss: 0.0354 - accuracy: 0.8784
Epoch 80/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0345 - accuracy: 0.8784
Epoch 81/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0377 - accuracy: 0.8784
Epoch 82/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0308 - accuracy: 0.8649
Epoch 83/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0358 - accuracy: 0.8784
Epoch 84/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0334 - accuracy: 0.8649
Epoch 85/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0348 - accuracy: 0.8514
Epoch 86/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0329 - accuracy: 0.8784
Epoch 87/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0290 - accuracy: 0.8919
Epoch 88/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0323 - accuracy: 0.8649
Epoch 89/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0373 - accuracy: 0.8514
Epoch 90/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0381 - accuracy: 0.8649
Epoch 91/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0346 - accuracy: 0.8649
Epoch 92/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0322 - accuracy: 0.8649
Epoch 93/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0305 - accuracy: 0.8919
Epoch 94/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0336 - accuracy: 0.8649
Epoch 95/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0360 - accuracy: 0.8784
Epoch 96/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0322 - accuracy: 0.8784
Epoch 97/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0354 - accuracy: 0.8784
Epoch 98/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0312 - accuracy: 0.8919
Epoch 99/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0387 - accuracy: 0.8649
Epoch 100/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0311 - accuracy: 0.8784
Epoch 101/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0271 - accuracy: 0.8919
Epoch 102/300
74/74 [==============================] - 0s 130us/sample - loss: 0.0351 - accuracy: 0.8784
Epoch 103/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0384 - accuracy: 0.8919
Epoch 104/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0349 - accuracy: 0.8649
Epoch 105/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0350 - accuracy: 0.8649
Epoch 106/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0337 - accuracy: 0.9054
Epoch 107/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0355 - accuracy: 0.8649
Epoch 108/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0310 - accuracy: 0.8784
Epoch 109/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0339 - accuracy: 0.8649
Epoch 110/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0336 - accuracy: 0.8784
Epoch 111/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0296 - accuracy: 0.8649
Epoch 112/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0323 - accuracy: 0.8919
Epoch 113/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0323 - accuracy: 0.8784
Epoch 114/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0350 - accuracy: 0.8649
Epoch 115/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0325 - accuracy: 0.8649
Epoch 116/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0321 - accuracy: 0.8649
Epoch 117/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0316 - accuracy: 0.8784
Epoch 118/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0305 - accuracy: 0.9054
Epoch 119/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0377 - accuracy: 0.8784
Epoch 120/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0328 - accuracy: 0.8919
Epoch 121/300
74/74 [==============================] - 0s 134us/sample - loss: 0.0345 - accuracy: 0.8649
Epoch 122/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0392 - accuracy: 0.8649
Epoch 123/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0340 - accuracy: 0.8784
Epoch 124/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0294 - accuracy: 0.8919
Epoch 125/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0351 - accuracy: 0.8649
Epoch 126/300
74/74 [==============================] - 0s 128us/sample - loss: 0.0322 - accuracy: 0.8649
Epoch 127/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0325 - accuracy: 0.8649
Epoch 128/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0371 - accuracy: 0.8514
Epoch 129/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0303 - accuracy: 0.8784
Epoch 130/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0398 - accuracy: 0.8514
Epoch 131/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0323 - accuracy: 0.8784
Epoch 132/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0292 - accuracy: 0.8784
Epoch 133/300
74/74 [==============================] - 0s 123us/sample - loss: 0.0293 - accuracy: 0.9054
Epoch 134/300
74/74 [==============================] - 0s 106us/sample - loss: 0.0304 - accuracy: 0.8784
Epoch 135/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0292 - accuracy: 0.8919
Epoch 136/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0385 - accuracy: 0.8514
Epoch 137/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0302 - accuracy: 0.8784
Epoch 138/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0291 - accuracy: 0.8784
Epoch 139/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0323 - accuracy: 0.8919
Epoch 140/300
74/74 [==============================] - 0s 142us/sample - loss: 0.0307 - accuracy: 0.8784
Epoch 141/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0298 - accuracy: 0.8784
Epoch 142/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0295 - accuracy: 0.8784
Epoch 143/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0334 - accuracy: 0.8649
Epoch 144/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0319 - accuracy: 0.8649
Epoch 145/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0347 - accuracy: 0.8649
Epoch 146/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0310 - accuracy: 0.8649
Epoch 147/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0340 - accuracy: 0.8649
Epoch 148/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0349 - accuracy: 0.8784
Epoch 149/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0291 - accuracy: 0.8784
Epoch 150/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0288 - accuracy: 0.8649
Epoch 151/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0370 - accuracy: 0.8784
Epoch 152/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0298 - accuracy: 0.8784
Epoch 153/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0328 - accuracy: 0.8784
Epoch 154/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0327 - accuracy: 0.8649
Epoch 155/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0340 - accuracy: 0.8514
Epoch 156/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0276 - accuracy: 0.8649
Epoch 157/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0308 - accuracy: 0.8649
Epoch 158/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0373 - accuracy: 0.8649
Epoch 159/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0297 - accuracy: 0.8649
Epoch 160/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0347 - accuracy: 0.8784
Epoch 161/300
74/74 [==============================] - 0s 142us/sample - loss: 0.0319 - accuracy: 0.8784
Epoch 162/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0301 - accuracy: 0.8649
Epoch 163/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0305 - accuracy: 0.8919
Epoch 164/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0329 - accuracy: 0.8649
Epoch 165/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0336 - accuracy: 0.8649
Epoch 166/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0331 - accuracy: 0.8649
Epoch 167/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0319 - accuracy: 0.8784
Epoch 168/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0318 - accuracy: 0.8919
Epoch 169/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0302 - accuracy: 0.8784
Epoch 170/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0327 - accuracy: 0.8649
Epoch 171/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0303 - accuracy: 0.8784
Epoch 172/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0315 - accuracy: 0.8919
Epoch 173/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0319 - accuracy: 0.8649
Epoch 174/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0285 - accuracy: 0.8649
Epoch 175/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0320 - accuracy: 0.8919
Epoch 176/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0321 - accuracy: 0.8649
Epoch 177/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0338 - accuracy: 0.8919
Epoch 178/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0333 - accuracy: 0.8784
Epoch 179/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0242 - accuracy: 0.9054
Epoch 180/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0379 - accuracy: 0.8649
Epoch 181/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0308 - accuracy: 0.8919
Epoch 182/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0340 - accuracy: 0.8784
Epoch 183/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0352 - accuracy: 0.8784
Epoch 184/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0267 - accuracy: 0.9054
Epoch 185/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0274 - accuracy: 0.8784
Epoch 186/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0342 - accuracy: 0.8784
Epoch 187/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0351 - accuracy: 0.8649
Epoch 188/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0363 - accuracy: 0.8649
Epoch 189/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0295 - accuracy: 0.8784
Epoch 190/300
74/74 [==============================] - 0s 107us/sample - loss: 0.0323 - accuracy: 0.8649
Epoch 191/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0307 - accuracy: 0.8784
Epoch 192/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0287 - accuracy: 0.8784
Epoch 193/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0304 - accuracy: 0.8919
Epoch 194/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0301 - accuracy: 0.8649
Epoch 195/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0309 - accuracy: 0.8784
Epoch 196/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0355 - accuracy: 0.8514
Epoch 197/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0329 - accuracy: 0.8649
Epoch 198/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0389 - accuracy: 0.8514
Epoch 199/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0331 - accuracy: 0.8649
Epoch 200/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0315 - accuracy: 0.8919
Epoch 201/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0311 - accuracy: 0.8784
Epoch 202/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0384 - accuracy: 0.8649
Epoch 203/300
74/74 [==============================] - 0s 104us/sample - loss: 0.0288 - accuracy: 0.8649
Epoch 204/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0279 - accuracy: 0.8919
Epoch 205/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0381 - accuracy: 0.8514
Epoch 206/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0280 - accuracy: 0.8784
Epoch 207/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0319 - accuracy: 0.8514
Epoch 208/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0324 - accuracy: 0.8919
Epoch 209/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0294 - accuracy: 0.8784
Epoch 210/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0332 - accuracy: 0.8649
Epoch 211/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0329 - accuracy: 0.8649
Epoch 212/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0298 - accuracy: 0.8784
Epoch 213/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0333 - accuracy: 0.8514
Epoch 214/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0302 - accuracy: 0.8649
Epoch 215/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0306 - accuracy: 0.8919
Epoch 216/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0307 - accuracy: 0.8649
Epoch 217/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0318 - accuracy: 0.8649
Epoch 218/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0337 - accuracy: 0.8649
Epoch 219/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0311 - accuracy: 0.8649
Epoch 220/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0345 - accuracy: 0.8649
Epoch 221/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0351 - accuracy: 0.8649
Epoch 222/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0289 - accuracy: 0.8784
Epoch 223/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0295 - accuracy: 0.8649
Epoch 224/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0302 - accuracy: 0.8649
Epoch 225/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0366 - accuracy: 0.8514
Epoch 226/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0282 - accuracy: 0.8649
Epoch 227/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0323 - accuracy: 0.8649
Epoch 228/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0319 - accuracy: 0.8784
Epoch 229/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0349 - accuracy: 0.8649
Epoch 230/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0320 - accuracy: 0.8649
Epoch 231/300
74/74 [==============================] - 0s 125us/sample - loss: 0.0369 - accuracy: 0.8649
Epoch 232/300
74/74 [==============================] - 0s 104us/sample - loss: 0.0306 - accuracy: 0.8649
Epoch 233/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0324 - accuracy: 0.8784
Epoch 234/300
74/74 [==============================] - 0s 107us/sample - loss: 0.0245 - accuracy: 0.8919
Epoch 235/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0406 - accuracy: 0.8514
Epoch 236/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0310 - accuracy: 0.8649
Epoch 237/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0309 - accuracy: 0.8649
Epoch 238/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0309 - accuracy: 0.8784
Epoch 239/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0293 - accuracy: 0.8649
Epoch 240/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0354 - accuracy: 0.8649
Epoch 241/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0353 - accuracy: 0.8784
Epoch 242/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0329 - accuracy: 0.8649
Epoch 243/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0321 - accuracy: 0.8649
Epoch 244/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0279 - accuracy: 0.8649
Epoch 245/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0312 - accuracy: 0.8649
Epoch 246/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0355 - accuracy: 0.8649
Epoch 247/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0292 - accuracy: 0.8649
Epoch 248/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0353 - accuracy: 0.8649
Epoch 249/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0272 - accuracy: 0.9054
Epoch 250/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0301 - accuracy: 0.8649
Epoch 251/300
74/74 [==============================] - 0s 119us/sample - loss: 0.0294 - accuracy: 0.8784
Epoch 252/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0270 - accuracy: 0.8919
Epoch 253/300
74/74 [==============================] - 0s 117us/sample - loss: 0.0326 - accuracy: 0.8649
Epoch 254/300
74/74 [==============================] - 0s 107us/sample - loss: 0.0338 - accuracy: 0.8649
Epoch 255/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0295 - accuracy: 0.8784
Epoch 256/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0312 - accuracy: 0.8784
Epoch 257/300
74/74 [==============================] - 0s 124us/sample - loss: 0.0346 - accuracy: 0.8514
Epoch 258/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0323 - accuracy: 0.8649
Epoch 259/300
74/74 [==============================] - 0s 107us/sample - loss: 0.0308 - accuracy: 0.8649
Epoch 260/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0315 - accuracy: 0.8649
Epoch 261/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0296 - accuracy: 0.8649
Epoch 262/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0304 - accuracy: 0.8784
Epoch 263/300
74/74 [==============================] - 0s 110us/sample - loss: 0.0290 - accuracy: 0.8649
Epoch 264/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0315 - accuracy: 0.8784
Epoch 265/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0350 - accuracy: 0.8649
Epoch 266/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0328 - accuracy: 0.8649
Epoch 267/300
74/74 [==============================] - 0s 127us/sample - loss: 0.0289 - accuracy: 0.8784
Epoch 268/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0344 - accuracy: 0.8784
Epoch 269/300
74/74 [==============================] - 0s 126us/sample - loss: 0.0318 - accuracy: 0.8649
Epoch 270/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0305 - accuracy: 0.8649
Epoch 271/300
74/74 [==============================] - 0s 173us/sample - loss: 0.0291 - accuracy: 0.8649
Epoch 272/300
74/74 [==============================] - 0s 153us/sample - loss: 0.0323 - accuracy: 0.8649
Epoch 273/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0316 - accuracy: 0.8649
Epoch 274/300
74/74 [==============================] - 0s 122us/sample - loss: 0.0281 - accuracy: 0.8649
Epoch 275/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0291 - accuracy: 0.8649
Epoch 276/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0311 - accuracy: 0.8649
Epoch 277/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0309 - accuracy: 0.8919
Epoch 278/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0338 - accuracy: 0.8649
Epoch 279/300
74/74 [==============================] - 0s 129us/sample - loss: 0.0329 - accuracy: 0.8784
Epoch 280/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0331 - accuracy: 0.8919
Epoch 281/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0332 - accuracy: 0.8649
Epoch 282/300
74/74 [==============================] - 0s 112us/sample - loss: 0.0272 - accuracy: 0.8784
Epoch 283/300
74/74 [==============================] - 0s 113us/sample - loss: 0.0310 - accuracy: 0.8784
Epoch 284/300
74/74 [==============================] - 0s 116us/sample - loss: 0.0309 - accuracy: 0.8784
Epoch 285/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0332 - accuracy: 0.8649
Epoch 286/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0340 - accuracy: 0.8649
Epoch 287/300
74/74 [==============================] - 0s 108us/sample - loss: 0.0311 - accuracy: 0.8649
Epoch 288/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0328 - accuracy: 0.8649
Epoch 289/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0349 - accuracy: 0.8649
Epoch 290/300
74/74 [==============================] - 0s 118us/sample - loss: 0.0357 - accuracy: 0.8649
Epoch 291/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0334 - accuracy: 0.8784
Epoch 292/300
74/74 [==============================] - 0s 121us/sample - loss: 0.0343 - accuracy: 0.8649
Epoch 293/300
74/74 [==============================] - 0s 131us/sample - loss: 0.0305 - accuracy: 0.8649
Epoch 294/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0313 - accuracy: 0.8649
Epoch 295/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0342 - accuracy: 0.8649
Epoch 296/300
74/74 [==============================] - 0s 109us/sample - loss: 0.0319 - accuracy: 0.8649
Epoch 297/300
74/74 [==============================] - 0s 120us/sample - loss: 0.0323 - accuracy: 0.8649
Epoch 298/300
74/74 [==============================] - 0s 115us/sample - loss: 0.0349 - accuracy: 0.8649
Epoch 299/300
74/74 [==============================] - 0s 114us/sample - loss: 0.0316 - accuracy: 0.8649
Epoch 300/300
74/74 [==============================] - 0s 111us/sample - loss: 0.0330 - accuracy: 0.8649
print ('Average f1 score', np.mean(test_F1))
print ('Average Run time', np.mean(time_k))
Average f1 score 0.6
Average Run time 3.3290751775105796
Building an LSTM Classifier on the sequences for comparison
We built an LSTM Classifier on the sequences to compare the accuracy.
X = darpa_data['seq']
encoded_X = np.ndarray(shape=(len(X),), dtype=list)
for i in range(0,len(X)):
encoded_X[i]=X.iloc[i].split("~")
max_seq_length = np.max(darpa_data['seqlen'])
encoded_X = tf.keras.preprocessing.sequence.pad_sequences(encoded_X, maxlen=max_seq_length)
kfold = 3
random_state = 11
test_F1 = np.zeros(kfold)
time_k = np.zeros(kfold)
epochs = 50
batch_size = 15
skf = StratifiedKFold(n_splits=kfold, shuffle=True, random_state=random_state)
k = 0
for train_index, test_index in skf.split(encoded_X, y):
X_train, X_test = encoded_X[train_index], encoded_X[test_index]
y_train, y_test = y[train_index], y[test_index]
embedding_vecor_length = 32
top_words=50
model = Sequential()
model.add(Embedding(top_words, embedding_vecor_length, input_length=max_seq_length))
model.add(LSTM(32))
model.add(Dense(1))
model.add(Activation('sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
model.summary()
start_time = time.time()
model.fit(X_train, y_train, epochs=epochs, batch_size=batch_size, verbose=1)
end_time=time.time()
time_k[k]=end_time-start_time
y_pred = model.predict_proba(X_test).round().astype(int)
y_train_pred=model.predict_proba(X_train).round().astype(int)
test_F1[k]=sklearn.metrics.f1_score(y_test, y_pred)
k+=1
Model: "sequential_13"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
embedding (Embedding) (None, 1773, 32) 1600
_________________________________________________________________
lstm (LSTM) (None, 32) 8320
_________________________________________________________________
dense_36 (Dense) (None, 1) 33
_________________________________________________________________
activation_36 (Activation) (None, 1) 0
=================================================================
Total params: 9,953
Trainable params: 9,953
Non-trainable params: 0
_________________________________________________________________
Train on 74 samples
Epoch 1/50
74/74 [==============================] - 4s 60ms/sample - loss: 0.6934 - accuracy: 0.5135
Epoch 2/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.6591 - accuracy: 0.8784
Epoch 3/50
74/74 [==============================] - 3s 46ms/sample - loss: 0.6201 - accuracy: 0.8784
Epoch 4/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.5612 - accuracy: 0.8784
Epoch 5/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.4500 - accuracy: 0.8784
Epoch 6/50
74/74 [==============================] - 3s 46ms/sample - loss: 0.3808 - accuracy: 0.8784
Epoch 7/50
74/74 [==============================] - 4s 49ms/sample - loss: 0.3807 - accuracy: 0.8784
Epoch 8/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.3795 - accuracy: 0.8784
Epoch 9/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3718 - accuracy: 0.8784
Epoch 10/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3713 - accuracy: 0.8784
Epoch 11/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.3697 - accuracy: 0.8784
Epoch 12/50
74/74 [==============================] - 3s 46ms/sample - loss: 0.3696 - accuracy: 0.8784
Epoch 13/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.3696 - accuracy: 0.8784
Epoch 14/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.3677 - accuracy: 0.8784
Epoch 15/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3666 - accuracy: 0.8784
Epoch 16/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3661 - accuracy: 0.8784
Epoch 17/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3654 - accuracy: 0.8784
Epoch 18/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3634 - accuracy: 0.8784
Epoch 19/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3638 - accuracy: 0.8784
Epoch 20/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3598 - accuracy: 0.8784
Epoch 21/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.3584 - accuracy: 0.8784
Epoch 22/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3539 - accuracy: 0.8784
Epoch 23/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3588 - accuracy: 0.8784
Epoch 24/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3374 - accuracy: 0.8784
Epoch 25/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3356 - accuracy: 0.8784
Epoch 26/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3044 - accuracy: 0.8784
Epoch 27/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.2896 - accuracy: 0.8784
Epoch 28/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2864 - accuracy: 0.8784
Epoch 29/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2430 - accuracy: 0.8784
Epoch 30/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2675 - accuracy: 0.8784
Epoch 31/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2764 - accuracy: 0.8784
Epoch 32/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2404 - accuracy: 0.8784
Epoch 33/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2131 - accuracy: 0.8784
Epoch 34/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2109 - accuracy: 0.8784
Epoch 35/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2060 - accuracy: 0.8919
Epoch 36/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1925 - accuracy: 0.9054
Epoch 37/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1913 - accuracy: 0.9189
Epoch 38/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1947 - accuracy: 0.9324
Epoch 39/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1762 - accuracy: 0.9324
Epoch 40/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1856 - accuracy: 0.9459
Epoch 41/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1689 - accuracy: 0.9324
Epoch 42/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1762 - accuracy: 0.9324
Epoch 43/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.1914 - accuracy: 0.9459
Epoch 44/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.1867 - accuracy: 0.9595
Epoch 45/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.1602 - accuracy: 0.9459
Epoch 46/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1627 - accuracy: 0.9324
Epoch 47/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1475 - accuracy: 0.9595
Epoch 48/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1527 - accuracy: 0.9595
Epoch 49/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1408 - accuracy: 0.9595
Epoch 50/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1745 - accuracy: 0.9595
Model: "sequential_14"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
embedding_1 (Embedding) (None, 1773, 32) 1600
_________________________________________________________________
lstm_1 (LSTM) (None, 32) 8320
_________________________________________________________________
dense_37 (Dense) (None, 1) 33
_________________________________________________________________
activation_37 (Activation) (None, 1) 0
=================================================================
Total params: 9,953
Trainable params: 9,953
Non-trainable params: 0
_________________________________________________________________
Train on 74 samples
Epoch 1/50
74/74 [==============================] - 4s 59ms/sample - loss: 0.6898 - accuracy: 0.5676
Epoch 2/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.6513 - accuracy: 0.8784
Epoch 3/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.6120 - accuracy: 0.8784
Epoch 4/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.5458 - accuracy: 0.8784
Epoch 5/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.4240 - accuracy: 0.8784
Epoch 6/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3963 - accuracy: 0.8784
Epoch 7/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3924 - accuracy: 0.8784
Epoch 8/50
74/74 [==============================] - 3s 40ms/sample - loss: 0.3851 - accuracy: 0.8784
Epoch 9/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3731 - accuracy: 0.8784
Epoch 10/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3708 - accuracy: 0.8784
Epoch 11/50
74/74 [==============================] - 3s 46ms/sample - loss: 0.3737 - accuracy: 0.8784
Epoch 12/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.3716 - accuracy: 0.8784
Epoch 13/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.3706 - accuracy: 0.8784
Epoch 14/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3697 - accuracy: 0.8784
Epoch 15/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.3698 - accuracy: 0.8784
Epoch 16/50
74/74 [==============================] - 3s 44ms/sample - loss: 0.3686 - accuracy: 0.8784
Epoch 17/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3686 - accuracy: 0.8784
Epoch 18/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3682 - accuracy: 0.8784
Epoch 19/50
74/74 [==============================] - 3s 44ms/sample - loss: 0.3667 - accuracy: 0.8784
Epoch 20/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3678 - accuracy: 0.8784
Epoch 21/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.3640 - accuracy: 0.8784
Epoch 22/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3621 - accuracy: 0.8784
Epoch 23/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3601 - accuracy: 0.8784
Epoch 24/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3574 - accuracy: 0.8784
Epoch 25/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3514 - accuracy: 0.8784
Epoch 26/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3552 - accuracy: 0.8784
Epoch 27/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3381 - accuracy: 0.8784
Epoch 28/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3274 - accuracy: 0.8784
Epoch 29/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3118 - accuracy: 0.8784
Epoch 30/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2943 - accuracy: 0.8784
Epoch 31/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.2783 - accuracy: 0.8784
Epoch 32/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.2459 - accuracy: 0.8784
Epoch 33/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.2276 - accuracy: 0.8919
Epoch 34/50
74/74 [==============================] - 3s 46ms/sample - loss: 0.2345 - accuracy: 0.9189
Epoch 35/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.1888 - accuracy: 0.9189
Epoch 36/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.2413 - accuracy: 0.9189
Epoch 37/50
74/74 [==============================] - 3s 44ms/sample - loss: 0.2389 - accuracy: 0.8649
Epoch 38/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.2136 - accuracy: 0.9054
Epoch 39/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.1933 - accuracy: 0.9054
Epoch 40/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.1882 - accuracy: 0.8919
Epoch 41/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.1999 - accuracy: 0.9054
Epoch 42/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1760 - accuracy: 0.8919
Epoch 43/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.1990 - accuracy: 0.8243
Epoch 44/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1632 - accuracy: 0.9189
Epoch 45/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1626 - accuracy: 0.9189
Epoch 46/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1700 - accuracy: 0.8784
Epoch 47/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1529 - accuracy: 0.9189
Epoch 48/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1641 - accuracy: 0.9189
Epoch 49/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1482 - accuracy: 0.9189
Epoch 50/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.1661 - accuracy: 0.8784
Model: "sequential_15"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
embedding_2 (Embedding) (None, 1773, 32) 1600
_________________________________________________________________
lstm_2 (LSTM) (None, 32) 8320
_________________________________________________________________
dense_38 (Dense) (None, 1) 33
_________________________________________________________________
activation_38 (Activation) (None, 1) 0
=================================================================
Total params: 9,953
Trainable params: 9,953
Non-trainable params: 0
_________________________________________________________________
Train on 74 samples
Epoch 1/50
74/74 [==============================] - 5s 63ms/sample - loss: 0.6756 - accuracy: 0.8919
Epoch 2/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.6397 - accuracy: 0.8919
Epoch 3/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.5892 - accuracy: 0.8919
Epoch 4/50
74/74 [==============================] - 3s 40ms/sample - loss: 0.5005 - accuracy: 0.8919
Epoch 5/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3800 - accuracy: 0.8919
Epoch 6/50
74/74 [==============================] - 3s 40ms/sample - loss: 0.3459 - accuracy: 0.8919
Epoch 7/50
74/74 [==============================] - 3s 40ms/sample - loss: 0.3529 - accuracy: 0.8919
Epoch 8/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3502 - accuracy: 0.8919
Epoch 9/50
74/74 [==============================] - 3s 40ms/sample - loss: 0.3455 - accuracy: 0.8919
Epoch 10/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3438 - accuracy: 0.8919
Epoch 11/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3434 - accuracy: 0.8919
Epoch 12/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3431 - accuracy: 0.8919
Epoch 13/50
74/74 [==============================] - 3s 40ms/sample - loss: 0.3433 - accuracy: 0.8919
Epoch 14/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3433 - accuracy: 0.8919
Epoch 15/50
74/74 [==============================] - 3s 44ms/sample - loss: 0.3432 - accuracy: 0.8919
Epoch 16/50
74/74 [==============================] - 3s 44ms/sample - loss: 0.3421 - accuracy: 0.8919
Epoch 17/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3426 - accuracy: 0.8919
Epoch 18/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3423 - accuracy: 0.8919
Epoch 19/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3424 - accuracy: 0.8919
Epoch 20/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.3420 - accuracy: 0.8919
Epoch 21/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3429 - accuracy: 0.8919
Epoch 22/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.3412 - accuracy: 0.8919
Epoch 23/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.3402 - accuracy: 0.8919
Epoch 24/50
74/74 [==============================] - 3s 40ms/sample - loss: 0.3397 - accuracy: 0.8919
Epoch 25/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.3390 - accuracy: 0.8919
Epoch 26/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.3398 - accuracy: 0.8919
Epoch 27/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.3372 - accuracy: 0.8919
Epoch 28/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3374 - accuracy: 0.8919
Epoch 29/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3323 - accuracy: 0.8919
Epoch 30/50
74/74 [==============================] - 3s 44ms/sample - loss: 0.3323 - accuracy: 0.8919
Epoch 31/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.3253 - accuracy: 0.8919
Epoch 32/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.3228 - accuracy: 0.8919
Epoch 33/50
74/74 [==============================] - 3s 40ms/sample - loss: 0.3075 - accuracy: 0.8919
Epoch 34/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2985 - accuracy: 0.8919
Epoch 35/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.3000 - accuracy: 0.8919
Epoch 36/50
74/74 [==============================] - 3s 44ms/sample - loss: 0.2791 - accuracy: 0.8919
Epoch 37/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.2580 - accuracy: 0.8919
Epoch 38/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.2874 - accuracy: 0.8919
Epoch 39/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.2712 - accuracy: 0.8919
Epoch 40/50
74/74 [==============================] - 3s 44ms/sample - loss: 0.2432 - accuracy: 0.8919
Epoch 41/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.2231 - accuracy: 0.8919
Epoch 42/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.2146 - accuracy: 0.8919
Epoch 43/50
74/74 [==============================] - 3s 45ms/sample - loss: 0.2026 - accuracy: 0.8919
Epoch 44/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.2371 - accuracy: 0.9054
Epoch 45/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.2293 - accuracy: 0.9189
Epoch 46/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2524 - accuracy: 0.9324
Epoch 47/50
74/74 [==============================] - 3s 42ms/sample - loss: 0.2331 - accuracy: 0.9189
Epoch 48/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.2046 - accuracy: 0.8919
Epoch 49/50
74/74 [==============================] - 3s 43ms/sample - loss: 0.2020 - accuracy: 0.8919
Epoch 50/50
74/74 [==============================] - 3s 41ms/sample - loss: 0.1992 - accuracy: 0.9054
print ('Average f1 score', np.mean(test_F1))
print ('Average Run time', np.mean(time_k))
Average f1 score 0.3313492063492064
Average Run time 157.32080109914145
We find that the LSTM classifier gives a significantly lower F1 score. This may be improved by changing the model. However, we find that the SGT embedding could work with a small and unbalanced data without the need of a complicated classifier model.
LSTM models typically require more data for training and also has significantly more computation time. The LSTM model above took 425.6 secs while the MLP model took just 9.1 secs.
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