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fine tune the pre-trained model on UCF101 #38

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Yueeeeee-1 opened this issue Jun 29, 2020 · 4 comments
Open

fine tune the pre-trained model on UCF101 #38

Yueeeeee-1 opened this issue Jun 29, 2020 · 4 comments

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@Yueeeeee-1
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if I want to fine tune the pre-trained model on UCF101, how could I get the performance of 96.8%?
In my settings, fine-tuning was only performed to train layer4 and the fully connected layer, and the learning rate is 0.0001, am I wrong? Cause the result I got just 78.5%, can you help me? Thank you!

@bjuncek
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bjuncek commented Jun 29, 2020

Other than parameter fine-tuning (I'd say 15 epochs, LR:1e-4 for the convolutional blocks and 1e-3 for the FC layer), make sure the evaluation script is correct.

If I recall correctly, the results are reported as video level accuracy on 10 uniformly sampled clips per video, averaged over 3 cross validation splits. I'd expect the clip level accuracy (what you're likely measuring) to be around >80%.

@Yueeeeee-1
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@bjuncek Thanks for your reply, I did test the clip level accuracy, and I didn't notice the difference between the video level and clip level, I will check it.
and for the parameter fine-tuning, ''LR:1e-4 for the convolutional blocks '' , it means all convolutional blocks or just the last one?
thanks for your patience!

@bjuncek
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bjuncek commented Jul 4, 2020

Make sure you're averaging softmaxes rather than predictions (w.r.t. the video level acc).

For all conv blocks

@paden118
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paden118 commented Dec 9, 2021

Hi, what is the accuracy of your final fine-tuning on ucf101?

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