title: LSTM in Keras returns always the same output
body: <p>I have a dataset of size (5358,293,30) and I want to train a LSTM network to predict a value between 0 and 1.</p>
  
  <p>My neural network is defined as follow:</p>
  
  <pre><code>model = Sequential()
  model.add(LSTM(10, input_shape=(293, 30)))
  model.add(Dense(1, activation="sigmoid"))
  model.compile(loss="mean_squared_error", optimizer="adam")
  model.fit(Xtrain, Ytrain, epochs=20, batch_size=38, shuffle=False)
  </code></pre>
  
  <p>The loss value for all the epochs during the train is ~0.04.
  When I test the neural network on the test data, I get always the same output as result, ~0.80.
  I tried a bigger network too, but the output didn't change.</p>
  
  <p>I used default parameters and I scaled the data in range [0,1].</p>
  
  <p>What are the possible causes for this problem? And how can I fix it?</p>
  
  <p>UPDATE:
  The ouput of the model.summary() for the simplified version:</p>
  
  <pre><code>Layer (type)                 Output Shape              Param #   
  =================================================================
  lstm_1 (LSTM)                (None, 10)                1640      
  _________________________________________________________________
  dense_1 (Dense)              (None, 1)                 11        
  =================================================================
  Total params: 1,651
  Trainable params: 1,651
  Non-trainable params: 0
  _________________________________________________________________
  </code></pre>
  
  <p>And for the full version:</p>
  
  <pre><code>Layer (type)                 Output Shape              Param #   
  =================================================================
  lstm_2 (LSTM)                (None, 293, 64)           24320     
  _________________________________________________________________
  lstm_3 (LSTM)                (None, 64)                33024     
  _________________________________________________________________
  dense_2 (Dense)              (None, 64)                4160      
  _________________________________________________________________
  dense_3 (Dense)              (None, 1)                 65        
  =================================================================
  Total params: 61,569
  Trainable params: 61,569
  Non-trainable params: 0
  _________________________________________________________________
  </code></pre>