title: CNN give less accuracy when I train it on more class
body: <p>I have a CNN for skin diseases and when I train it on ~5K picture I got 92% network accuracy and 83% val acc but when I train the same network with 25K picture in the same data shape I got 0.08% acc 
  *the data shape: clinical images for Patients hands, faces, etc.
  I train the network with augmentation that I found online using ImageDataGenerator</p>
  
  <pre><code>model = Sequential()
  # 1st layer
  model.add(Conv2D(32, (3, 3), input_shape=(img_rows, img_cols,img_channels)))
  model.add(Activation('relu'))
  model.add(MaxPooling2D(pool_size=(2, 2),data_format = "channels_last"))
  
  model.add(Conv2D(32, (3, 3)))
  model.add(Activation('relu'))
  model.add(MaxPooling2D(pool_size=(2, 2),data_format = "channels_last"))
  
  model.add(Conv2D(64, (3, 3)))
  model.add(Activation('relu'))
  model.add(MaxPooling2D(pool_size=(2, 2),data_format = "channels_last"))
  
  #last
  model.add(Flatten())  # this converts our 3D feature maps to 1D feature vectors
  model.add(Dense(512))
  model.add(Activation('relu'))
  model.add(Dropout(0.5))
  model.add(Dense(512))
  model.add(Activation('sigmoid'))
  model.add(Dense(nb_classes))
  model.add(Activation('softmax'))
  </code></pre>