Previous literature on deep learning theory has focused on implicit bias with small learning rates. In this work. we explore the impact of data separability on the implicit bias of deep learning algorithms under the large learning rate. Using deep linear networks for binary classification with the logistic loss under the large learning rate regime. https://darthomes.shop/product-category/chimes/