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ultralytics 8.0.114 automatic optimizer selection (#3037)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Burhan <62214284+Burhan-Q@users.noreply.github.com>
This commit is contained in:
Glenn Jocher
2023-06-06 01:09:27 +02:00
committed by GitHub
parent 01273c5ca1
commit 8940a27bdb
11 changed files with 72 additions and 14 deletions
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2
ultralytics/yolo/cfg/default.yaml
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@ -20,7 +20,7 @@ project: # project name
name: # experiment name, results saved to 'project/name' directory
exist_ok: False # whether to overwrite existing experiment
pretrained: False # whether to use a pretrained model
optimizer: SGD # optimizer to use, choices=[SGD, Adam, Adamax, AdamW, NAdam, RAdam, RMSProp, auto]
optimizer: auto # optimizer to use, choices=[SGD, Adam, Adamax, AdamW, NAdam, RAdam, RMSProp, auto]
verbose: True # whether to print verbose output
seed: 0 # random seed for reproducibility
deterministic: True # whether to enable deterministic mode

6
ultralytics/yolo/engine/trainer.py
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@ -627,8 +627,10 @@ class BaseTrainer:
g = [], [], [] # optimizer parameter groups
bn = tuple(v for k, v in nn.__dict__.items() if 'Norm' in k) # normalization layers, i.e. BatchNorm2d()
if name == 'auto':
name, lr, momentum = ('SGD', 0.01, 0.9) if iterations > 6000 else ('NAdam', 0.001, 0.9)
self.args.warmup_bias_lr = 0.0 # no higher than 0.01 for NAdam
nc = getattr(model, 'nc', 10) # number of classes
lr_fit = round(0.002 * 5 / (4 + nc), 6) # lr0 fit equation to 6 decimal places
name, lr, momentum = ('SGD', 0.01, 0.9) if iterations > 10000 else ('AdamW', lr_fit, 0.9)
self.args.warmup_bias_lr = 0.0 # no higher than 0.01 for Adam
for module_name, module in model.named_modules():
for param_name, param in module.named_parameters(recurse=False):