I am building an LSTM model with the following characteristics:
Model: "sequential"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 lstm (LSTM)                 (None, 2, 200)            164000    
                                                                 
 leaky_re_lu (LeakyReLU)     (None, 2, 200)            0         
                                                                 
 lstm_1 (LSTM)               (None, 2, 128)            168448    
                                                                 
 leaky_re_lu_1 (LeakyReLU)   (None, 2, 128)            0         
                                                                 
 dropout (Dropout)           (None, 2, 128)            0         
                                                                 
 lstm_2 (LSTM)               (None, 64)                49408     
                                                                 
 dropout_1 (Dropout)         (None, 64)                0         
                                                                 
 dense (Dense)               (None, 1)                 65        
                                                                 
=================================================================
Total params: 381,921
Trainable params: 381,921
Non-trainable params: 0
_________________________________________________________________


I am a beginner at forecasting and I would like to know if the chosen model is accurate.
These are the results for the plot of loss train and validation loss.

image862×608 75.1 KB

I saw that the loss for train is bigger than the one for validation. Can this be overfitting of the model?
What can be done about it to improve the model?