When using pre-trained model to fine-tune other task, the excluded pre-trained parameters can be set by finetune_exclude_pretrained_params in YAML config or -o finetune_exclude_pretrained_params in the arguments.
When using pre-trained model to fine-tune other task, two methods can be used:
1. The excluded pre-trained parameters can be set by `finetune_exclude_pretrained_params` in YAML config
2. Set -o finetune_exclude_pretrained_params in the arguments.
@@ -6,7 +6,10 @@ In transfer learning, if different dataset and the number of classes is used, th
## Transfer Learning in PaddleDetection
In transfer learning, it's needed to load pretrained model selectively. Set `finetune_exclude_pretrained_params` in YAML configuration files or set `-o finetune_exclude_pretrained_params` in command line.
In transfer learning, it's needed to load pretrained model selectively. The following two methods can be used:
1. Set `finetune_exclude_pretrained_params` in YAML configuration files. Please refer to [configure file](../configs/yolov3_mobilenet_v1_fruit.yml#L15)
2. Set -o finetune_exclude_pretrained_params in command line. For example: