train process problem
CS123n opened this issue · 1 comments
CS123n commented
ShihaoZhaoZSH commented
Thank you for your interest in our LaVi-Bridge! We haven't encountered such a situation in our experiment, and the released training and inference code has undergone thorough testing to ensure its correctness. We suggest checking the following points: 1. Adjust the learning rate appropriately. 2. Train using full precision. 3. Double-check the inference process to ensure the correct loading of LoRA and proper input of (un)conditional text embeddings into the adapter.