This work describes the development of different models to detect patronising and condescending language within extracts of news articles as part of the SemEval 2022 competition (Task-4). This work explores different models based on the pre-trained RoBERTa language model coupled with LSTM and CNN layers. The best models achieved 15^th rank with an F1-score of 0.5924 for subtask-A and 12^th in subtask-B with a macro-F1 score of 0.3763.