updates
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train.py
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train.py
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@ -128,7 +128,7 @@ def train():
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if opt.transfer: # transfer learning
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if opt.transfer: # transfer learning
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nf = int(model.module_defs[model.yolo_layers[0] - 1]['filters']) # yolo layer size (i.e. 255)
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nf = int(model.module_defs[model.yolo_layers[0] - 1]['filters']) # yolo layer size (i.e. 255)
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for x in optimizer.param_groups:
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for x in optimizer.param_groups: # lower parameter count can handle more aggressive training hyps
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x['lr'] *= 10
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x['lr'] *= 10
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x['momentum'] *= 0.9
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x['momentum'] *= 0.9
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