Comments (3)
Just to add to this, even with the lr_scheduler set, the learning rate never seems to change during training.
from pretrained-backbones-unet.
Hello @bc-bytes, firstly, thank you for bringing up the issue. The library can not support the "REDUCELRONPLATEAU" and "COSINEANNEALINGWARMRESTARTS" lr schedulers. However, all other schedulers are supported. Therefore, receiving this error message is quite normal. If you use either of these two schedulers, the learning rate will not change. I intend to add additional support soon, thus making all lr scheduler classes available. Until then, you may use all other schedulers except for these two.
Supported Schedulers:
- LAMBDALR
- MULTIPLICATIVELR
- STEPLR
- MULTISTEPLR
- CONSTANTLR
- LINEARLR
- EXPONENTIALLR
- POLYNOMIALLR
- COSINEANNEALINGLR
- CHAINEDSCHEDULER
- SEQUENTIALLR
- CYCLICLR
- ONECYCLELR
from pretrained-backbones-unet.
Many thanks for the suggestions. However, I am currently producing a set of baseline results from other repositories, and I have trained all those models using ReduceLROnPlateau, so changing the scheduler type would mean that the results would not be comparable to my previous ones.
from pretrained-backbones-unet.
Related Issues (8)
- Model saving functionality missing HOT 1
- Test script? HOT 2
- Unable to train on small patches (64x48) HOT 3
- Training loss is not decreasing HOT 2
- 'DataLoader' is not defined HOT 1
- DiceLoss question in pretrained-backbones-unet/backbones_unet/model /losses.py HOT 1
- Dimension issues with predict method HOT 2
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from pretrained-backbones-unet.