Closed Mayur28 closed 3 years ago
@Mayur28 , Hi, did you use the LRS2 dataset or other dataset? The loss plot was drawed by tensorboard?
Hi @zhanghming,
I was using LRS2 and I was using weights and biases to plot the loss function. I realized my mistake when I posted my previous mistake - I erroneously ran my code on my small subset of the dataset instead of the full dataset, therefore the model converged quickly. Apologies for that.
@Mayur28 , Hi, thanks for you reply. I wonder whether you continued do some work based on this repo? Have you re-implemented the performance similar with the author's?
Hi @zhanghm1995 ,
I have continued to work and extend the code in the repo - My re-implementation is able to double the performance of the code in the repo. From my several executions of the code in the repo, I am only able to achieve 40% GPU utilization at most, and with my implementation, I can achieve 90% on a GTX 3090 GPU. Unfortunately I am unable to share my implementation as it is currently being used for my research. Once I am done, I may consider making it public.
Hi @Mayur28! How is your research work going? I'm quite interested in yours implementation of wav2lip. Do you plan on open-sourcing it any time soon? Thanks anyway!
Hi @xopclabs ,
My research has been delayed by a few months unfortunately, I am expecting to complete my research by the end of the year and at that point I will decide whether I will open-source the implementation or not. I will keep you posted.
Hi,
I am trying to train the expert lip sync discriminator using LRS2 and using the code from the repo as is (without any changes), but I am unsure why is the model converging much quicker than it should be. Default parameters are used. As mentioned in one of the previous issues, I was expecting the loss to be around 0.69 for quite some time, and to only start to decrease after 150K steps. I have a loss curve that I am getting.
Any assistance would be highly appreciated. Thanks