title: accuracy for 1D CNN model is very low
body: <p>I tried to build 1D CNN model to DNA mutation classification I built the model and it works correctly but I get test data with low accuracy I have dataset like the picture bellow<img src="https://i.stack.imgur.com/JsBg9.png" alt="1" /></p>
  <p>and this is my model</p>
  <pre><code>vocab_size = 100
  embedding_dim = 150
  max_len = 90
  X_train = pad_sequences(X_train,padding ='post', maxlen = max_len)
  X_test = pad_sequences(X_test,padding ='post', maxlen = max_len)
  model = Sequential()
  model.add(layers.Embedding(vocab_size,embedding_dim,input_length = max_len))
  model.add(layers.Conv1D(128, 7, activation = 'relu'))
  model.add(layers.GlobalMaxPooling1D())
  model.add(layers.Dense(10, activation = 'relu'))
  model.add(layers.Dense(1, activation = 'sigmoid'))
  model.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics= ['accuracy'])
  model.summary()
  history = model.fit(X_train,y_train,epochs = 10, verbose = False,validation_data = (X_test,y_test),batch_size = 10)
  loss,accuracy = model.evaluate(X_train,y_train, verbose = False)
  accuracy = accuracy*100
  print(&quot;training accuracy = {:.2f}&quot;.format(accuracy))
  loss,accuracy = model.evaluate(X_test,y_test, verbose = False)
  accuracy = accuracy*100
  print(&quot;test accuracy = {:.2f}&quot;.format(accuracy))
  </code></pre>
  <p>my input is ['sequence','normal','mutated','position']
  and target column is ['class'] column
  so what is the problem with my test accuracy.</p>
  <p><strong>Edit:</strong>
  I tried to change percent of test data in train_test_split function and increased percent of test data to avoid overfitting but test accuracy still low</p>