updates
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train.py
4
train.py
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@ -39,7 +39,7 @@ def train():
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cfg = opt.cfg
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data = opt.data
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img_size = opt.img_size
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epochs = 1 if opt.prebias else opt.epochs # 500200 batches at bs 16, 117263 images = 273 epochs
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epochs = 3 if opt.prebias else opt.epochs # 500200 batches at bs 16, 117263 images = 273 epochs
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batch_size = opt.batch_size
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accumulate = opt.accumulate # effective bs = batch_size * accumulate = 16 * 4 = 64
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weights = opt.weights # initial training weights
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@ -110,7 +110,7 @@ def train():
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for x in optimizer.param_groups:
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# lower param count allows more aggressive training settings: ~0.1 lr0, ~0.9 momentum
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x['lr'] *= 10
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x['lr'] *= 100
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x['momentum'] *= 0.9
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for p in model.parameters():
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