if i%2 == 0 :
   targets=targets.append({'seq_id':counter,'val':1},ignore_index=True)
else :
 targets=targets.append({'seq_id':counter,'val':-1},ignore_index=True)

...

model.add(LSTM(int(num_features*4),input_shape=(num_rows,num_cols),  return_sequences=True))
model.add(LSTM(int(num_features*4),   dropout=0.5, recurrent_dropout=0.5))
model.add(Dense(1, activation='sigmoid'))

if i%2 == 0 :
   targets=targets.append({'seq_id':counter,'val':'bic'},ignore_index=True)
else :
   targets=targets.append({'seq_id':counter,'val':'reno'},ignore_index=True)
...

targets = targets.values[:,1]
encoder = LabelEncoder()
encoder.fit(targets)
encoded_Y = encoder.transform(targets)
targets = np_utils.to_categorical(encoded_Y)

...

model.add(LSTM(int(num_features*4),input_shape=(num_rows,num_cols),  return_sequences=True))
model.add(LSTM(int(num_features*4),   dropout=0.5, recurrent_dropout=0.5))
model.add(Dense(2, activation='sigmoid')) #That line Changed