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Hi @LeighSu What results are you trying to reproduce? I believe you're using sample configs for ImageNet datasets, which are not tuned at all or whose results are not reported in some papers either. Please read configs/legacy/README.md
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I am trying to add new self-defined loss function, but when I want to compare the result with the existed loss function, the reproduced result seems unreasonable.
![image](https://private-user-images.githubusercontent.com/13862696/252008346-d14aa612-3154-427e-a9a6-a597e938f1f1.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.2GLE4wY6CrBewlEInu6gQe8J7GrTPxZtyEgpsBnT-qY)
![image](https://private-user-images.githubusercontent.com/13862696/252008696-e108127a-353c-4248-8a06-7517bf77b23e.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.4e_TCuxbiDdUvh0wSMtaHz-xZCFLyJbcmupuK7RGCNE)
I used the following two command to reproduce the result, and the teacher model seems normally, it can archive high accurate.
but the student model only 8% acc for Top1 and 22% acc for Top 5.
Is there anyting I misunderstand or how can I improve?
ilsvrc2012_cckd_resnet18_from_resnet50.txt
ilsvrc2012_kd_resnet18_from_resnet152.txt
python3 -m torch.distributed.launch --nproc_per_node=2 --use_env examples/image_classification.py --world_size 2 --config configs/sample/ilsvrc2012/single_stage/kd/resnet18_from_resnet152.yaml --log log/ilsvrc2012/kd/resnet18_from_resnet152.txt
python3 -m torch.distributed.launch --nproc_per_node=2 --use_env examples/image_classification.py --world_size 2 --config configs/sample/ilsvrc2012/single_stage/cckd/resnet18_from_resnet50.yaml --log log/ilsvrc2012/cckd/resnet18_from_resnet50.txt
Addition message:
![image](https://private-user-images.githubusercontent.com/13862696/252009828-1e8ac8f8-323d-44a6-b109-c3890e61e188.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.C54EZhs52RUa9dGa16Pr6lyY-SCZbhy460OU1lX4p00)
I checkout the branch t0 tag v0.3.3 .
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