wrong results when saving and loading weights/model in Keras

I can't post the code I am using, but i will try to explain it. First I have defined a few functions to preprocess the raw data. Then, using keras I have the following arquitecture:

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% accuracy, but when I save the weights/model (following keras doc) and then I load them, I get garbage results.

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