Invalid results when saving and loading balance / model in Keras

I cannot post the code I am using, but I will try to explain it. I first defined a few functions to preprocess the raw data. Then using keras I have the following architecture:

model = Sequential()

model.add(Dense(10, input_dim=230, init='uniform',activation='sigmoid'))  

model.add(Dense(5, init='uniform', activation='sigmoid'))

model.add(Dense(2, init='uniform', activation='sigmoid'))

model.compile(loss='mse', optimizer='RMSprop', metrics=['binary_accuracy'])

model.fit(trainX, trainY, nb_epoch=1000, batch_size=1, callbacks=[history], verbose=2)

      

        
        
        
      

    

Now about the problem. When I run the code I get> 98% precision, but when I save the weight / model (following the keras doc) and then load them I get garbage results.

I tried loading after and before the compile line, saving / loading weights / model, nothing works (I keep getting wrong results after loading them in another python session)