Antibodies are a class of protein produced by B-cells during an immune response. Antibody binding is controlled by six loops known as the complementarity determining regions, or CDRs. The large structural diversity of the CDR-H3 loop enables antibodies to bind with high affinity and specificity to almost any antigen. On the other hand, this diversity also makes CDR-H3 structure prediction one of the main challenges in antibody modelling. Recent advances in deep learning have been shown to greatly improve general protein structure prediction. Applying the deep learning methods developed for general protein structure prediction, I aim to improve structural modelling of the CDR-H3 loop.