Tuning hyper-parameters with bayesian optimization

[taylort139 (Tommy Taylor)]

Hi @muellerzr and anyone else interested. I have stumbled on an error implementing your code in the context of my segmentation problem. I wondered whether you could possibly give me a push in the right direction?

I made a new question here:

Bayesian Optimization for Hyperparameter Tuning

Hi all, I am attempting to apply Bayesian Optimization to discover the best combination of hyperparameters for my image segmentation model. For now, this is only the learning rate (lr) and weight decay (wd). Please would someone kindly troubleshoot my error message. Note for legacy reasons, I am using Fastai1. > RuntimeError: The size of tensor a (3744) must match the size of tensor b (101376) at non-singleton dimension 1 CODE: # source: https://github.com/muellerzr/BaysianOptimizationFastAI…

Thanks!