Comments (2)
Hi, I have lost the network weights to reproduce the results that are shared in the paper.
Due to time constraints, I tried to rerun the codes again with other configurations, but the results obtained are lower than the reported ones. Hope you can understand.
The jupyter notebook file which consists of all steps is in the link:
https://drive.google.com/file/d/16sUEb3RmIaDh-IvrcT6L9sRHGuG-t6mJ/view?usp=sharing
Note that I used a high learning rate in this notebook, so the val_loss values in the graph fluctuated. A slightly better result and a nicer loss graph can be obtained if a lower learning rate is used.
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Hi, I have lost the network weights to reproduce the results that are shared in the paper. Due to time constraints, I tried to rerun the codes again with other configurations, but the results obtained are lower than the reported ones. Hope you can understand. The jupyter notebook file which consists of all steps is in the link: https://drive.google.com/file/d/16sUEb3RmIaDh-IvrcT6L9sRHGuG-t6mJ/view?usp=sharing
Thank you so much for your patience and kindness!
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Related Issues (8)
- train code HOT 1
- some question HOT 2
- Feature extraction process? HOT 5
- 代码训练结果复现 HOT 1
- Problems on result reproduction on MEGC2021 Benchmark HOT 5
- about megc2022-processed-data HOT 1
- megc2021-processed date zip HOT 2
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