In this work, the model implemented was from the 2017 publication "Attention is All You Need" by Vaswani et al. . The transformer model implemented follows a contemporary architecture for sequence-to-sequence tasks, drawing on key elements from recent advances in deep learning. Here, the model features a stack of 4 transformer layers, each incorporating a multi-head attention mechanism with 8 heads and feed-forward networks with an internal dimension (dff) of 2048 and an embedding size (d_model) of 512, as detailed in the architecture proposed by Vaswani et al. A dropout rate of 0.1 is applied to prevent overfitting.