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Regarding the accuracy after pruning #347

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zirid opened this issue Mar 6, 2024 · 0 comments
Open

Regarding the accuracy after pruning #347

zirid opened this issue Mar 6, 2024 · 0 comments

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@zirid
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zirid commented Mar 6, 2024

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.

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