I used your test code from the " High-level Pruners" section in the documentation:
Instead of using "resnet18" I used resnet50 on an easy classification task. the accuracy without pruning is 99% after 5 epochs but I get a very low accuracy after, unlike your data that suggests that at worst the accuracy drops only by 1%.
Note: (I didn't use the last part: # finetune the pruned model here), I used the model as it is after pruning.
My results are:
pruning ratio = 0.1 gives 94% accuracy
pruning ratio = 0.5 gives 65% accuracy
I used your test code from the " High-level Pruners" section in the documentation:
Instead of using "resnet18" I used resnet50 on an easy classification task. the accuracy without pruning is 99% after 5 epochs but I get a very low accuracy after, unlike your data that suggests that at worst the accuracy drops only by 1%.
Note: (I didn't use the last part: # finetune the pruned model here), I used the model as it is after pruning.
My results are: pruning ratio = 0.1 gives 94% accuracy pruning ratio = 0.5 gives 65% accuracy
Do you think I missed something?
Thank you.