Hello,
I am working on word detection and using MMOCR’s ‘DBNetpp’ detection model, please refer [2202.10304] Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion.
I want to use this pre-trained model and fine tune on my dataset.
Therefore, I need to update the configuration file for ‘DBNetpp’.
here is the part of config file. I would like to know which parameters (specifically the learning rates) can be changed to have descent first results (decrease in loss).
# optimizer
optimizer = dict(type="SGD", lr=0.007, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(policy="poly", power=0.9, min_lr=1e-7, by_epoch=False)
Any help would be appreciated.
Thank you in advance.