This paper introduces the model and settings submitted to the INLG 2022 DialogSum Chal- lenge, a shared task to generate summaries of real-life scenario dialogues between two peo- ple. In this paper, we explored using interme- diate task transfer learning, reported speech, and the use of a supplementary dataset in addi- tion to our base fine-tuned BART model. How- ever, we did not use such a method in our final model, as none improved our results. Our final model for this dialogue task achieved scores only slightly below the top submission, with hidden test set scores of 49.62, 24.98, 46.25 and 91.54 for ROUGE-1, ROUGE-2, ROUGE-L and BERTSCORE respectively. The top submitted models will also receive human evaluation.