revise sentences: Decentralized learning is widely used to collaboratively train models using distributed data over wireless networks. Existing decentralized learning methods focus on training single-modal network. For decentralized multi-modal learning (DMML), the modality heterogeneity and the non-independent and non-identically distributed (non-IID) data across devices make it difficult for the training model to capture the correlated features across different modalities. Additionally, the modality competition lead to the training imbalance of different modalities, which significantly impact the performance of DMML.