The proposed model architecture combines recurrent neural networks (RNN) with CNN-based attention mechanisms. The model extracts high-level contextual features from input representation using a CNN layer and calculates attention scores to identify important features. These features and attention scores are then used as input to the RNN layer for sentiment analysis.