keras-arcface
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why I get a 100% acc on the valid data?
Any luck solving this? I haven't been able to reproduce the clusters in the original script yet consistently achieve 100% accuracy on the train and test data for MNIST.
Any luck solving this? I haven't been able to reproduce the clusters in the original script yet consistently achieve 100% accuracy on the train and test data for MNIST.
please can you help me in input dataset to thate model
No description provided.
have you done your problem ? let help me pls
I have the same issue, I am consistently getting 100% accuracy on the validation dataset, has anyone been able to solve this?
Any luck solving this?
I have the same issue, I am consistently getting 100% accuracy on the validation dataset, has anyone been able to solve this? Any luck solving this?
No, no luck in solving it, but I came across the following article https://yiwenlai.medium.com/how-to-train-with-arcface-loss-to-improve-model-classification-accuracy-d4035195aeb9. It mentions about the 100% accuracy error and how to solve it. Please go through it.
thanks
---Original--- From: @.> Date: Wed, Jun 22, 2022 20:10 PM To: @.>; Cc: @.@.>; Subject: Re: [4uiiurz1/keras-arcface] why I get a 100% acc on the valid data?(#14)
No, no luck in solving it, but I came across the following article https://yiwenlai.medium.com/how-to-train-with-arcface-loss-to-improve-model-classification-accuracy-d4035195aeb9. It mentions about the 100% accuracy error and how to solve it. Please go through it.
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No, no luck in solving it, but I came across the following article https://yiwenlai.medium.com/how-to-train-with-arcface-loss-to-improve-model-classification-accuracy-d4035195aeb9. It mentions about the 100% accuracy error and how to solve it. Please go through it.
not work
Same problem here.
2 ways ,it works 1.use tf 2+ 2. trans speech brain ArcFace to tf version
---Original--- From: "Kevin @.> Date: Sun, Aug 28, 2022 06:55 AM To: @.>; Cc: @.@.>; Subject: Re: [4uiiurz1/keras-arcface] why I get a 100% acc on the valid data?(#14)
Same problem here.
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