This paper presents the application of BERT inSemEval 2024 Task 2, Safe Biomedical Natu-ral Language Inference for Clinical Trials. Themain objectives of this task were: First, to in-vestigate the consistency of BERT in its rep-resentation of semantic phenomena necessaryfor complex inference in clinical NLI settings.Second, to investigate the ability of BERT toperform faithful reasoning, i.e., make correctpredictions for the correct reasons. The submit-ted model is fine-tuned on the NLI4CT dataset,which is enhanced with a novel contrast set,using binary cross entropy loss.