What should I do to make low loss average? : I'm an student in hydraulic engineering, working on a neural network in my internship so it's something new for me.
I created my neural network but it gives me a high loss and I don't know what is the problem ... you can see the code : 

    def create_model():
        model = Sequential()
        # Adding the input layer
        model.add(Dense(26,activation='relu',input_shape=(n_cols,)))
        # Adding the hidden layer
        model.add(Dense(60,activation='relu'))
        model.add(Dense(60,activation='relu'))
        model.add(Dense(60,activation='relu'))
        # Adding the output layer
        model.add(Dense(2))
        # Compiling the RNN
        model.compile(optimizer='adam', loss='mean_squared_error', metrics=['accuracy'])
        return model

    kf = KFold(n_splits = 5, shuffle = True)
    model = create_model()
    scores = []
    for i in range(5):
        result = next(kf.split(data_input), None)
        input_train = data_input[result[0]]
        input_test = data_input[result[1]]
        output_train = data_output[result[0]]
        output_test = data_output[result[1]]
        # Fitting the RNN to the Training set
        model.fit(input_train, output_train, epochs=5000, batch_size=200 ,verbose=2)
        predictions = model.predict(input_test) 
        scores.append(model.evaluate(input_test, output_test))
    
    print('Scores from each Iteration: ', scores)
    print('Average K-Fold Score :' , np.mean(scores))

And whene I execute my code, the result is like :

    Scores from each Iteration:  [[93.90406122928908, 0.8907562990148529], [89.5892979597845, 0.8907563030218878], [81.26530176050522, 0.9327731132507324], [56.46526102659081, 0.9495798339362905], [54.314151876112994, 0.9579831877676379]]
    Average K-Fold Score : 38.0159922589274

Can anyone help me please ? how could I do to make the loss low ?  