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rcmalli / keras-vggface

VGGFace implementation with Keras Framework
MIT License
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How did you train vggface model, what parameters did you use? #60

Open marinkreso95 opened 4 years ago

marinkreso95 commented 4 years ago

I would like to know how did you train model whose weights are loaded into chosen model (Resnet, Senet).

Did you train the model in keras, how you implemented triplet loss, what training parameters did you use (iterations, learning rate etc.) to get amazing results?

The information that I asked about above is for Resnet50 architecture.

zewenli98 commented 4 years ago

Hi, there. Do u figure out those parameters? Why the loss(softmax) does not reduce when I use the pre-trained model?

sherlockchou86 commented 4 years ago

I guess there is no triplet loss used in training the model. Just use softmax loss for classification and then we can remove top layers to use features for generic usage such as fine-tuning.

ritikjain51 commented 3 years ago

For the training of the model, I guess they have used multi-class cross-entropy loss. But not able to understand why have used softmax activation on the last layer.