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Hi, thanks for providing this amazing quantization framework ! I want to reproduce the Top1@acc of mobilenet_v2 a4w4 LSQ under academic setting. The quantization configuration is as below:
For the training strategy, I set weght decay=0, lr = 1e-3 and batch_size=128 per GPU using 8 cards Nvidia A100. And the adjust_learning_rate strategy is remained the same as main.py. However, the highest top1@Acc I reproduced in the validation set was only 68.66%, which is far from the 70.6% as the paper presented.
Which part I have missed ?
The text was updated successfully, but these errors were encountered:
Hi, thanks for providing this amazing quantization framework ! I want to reproduce the Top1@acc of mobilenet_v2 a4w4 LSQ under academic setting. The quantization configuration is as below:
For the training strategy, I set
weght decay=0
,lr = 1e-3
andbatch_size=128
per GPU using 8 cards Nvidia A100. And theadjust_learning_rate
strategy is remained the same asmain.py
. However, the highest top1@Acc I reproduced in the validation set was only68.66%
, which is far from the70.6%
as the paper presented.Which part I have missed ?
The text was updated successfully, but these errors were encountered: