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I am a student researching video coding, and I must say your work has been truly outstanding and inspiring to me.
I have previously reproduced and fine-tuned the DCVC-HEM model, which has granted me a deeper understanding of the video coding field. However, recently, I encountered difficulties while trying to reproduce the DCVC-FM code. I consistently faced a situation where the bpp training easily becomes divergent. I have scrutinized the training process and found that it is particularly prone to training above 4.0, whether in training bpp_y or bpp_mv_y.
I attempted to import pre-trained parameters and train the model using only bpp as the loss, but unfortunately, I still could not achieve training below 0.6. The difference between the results and the pre-trained model, which achieved 0.01, is quite significant. Could you kindly provide me with some valuable advice regarding training the model? I am eagerly looking forward to your response.
The text was updated successfully, but these errors were encountered:
Dear author,
I am a student researching video coding, and I must say your work has been truly outstanding and inspiring to me.
I have previously reproduced and fine-tuned the DCVC-HEM model, which has granted me a deeper understanding of the video coding field. However, recently, I encountered difficulties while trying to reproduce the DCVC-FM code. I consistently faced a situation where the bpp training easily becomes divergent. I have scrutinized the training process and found that it is particularly prone to training above 4.0, whether in training bpp_y or bpp_mv_y.
I attempted to import pre-trained parameters and train the model using only bpp as the loss, but unfortunately, I still could not achieve training below 0.6. The difference between the results and the pre-trained model, which achieved 0.01, is quite significant. Could you kindly provide me with some valuable advice regarding training the model? I am eagerly looking forward to your response.
The text was updated successfully, but these errors were encountered: