Inconsistent results of each training under the same parameter configuration even when seed is fixed.
Opened this issue · 2 comments
Hello!
I want to ask why the model evaluation results of each training under the same parameter configuration are inconsistent. My environment is exactly the same as the environment.yaml file provided, and I have not modified any code. I want to know if this is normal when the random seed is fixed.
Hi, thanks for using our code.
We found that the random seed for train_vq is not set and just fixed it. Please pull the latest code to use it.
Feel free to create a pull request to contribute to MoMask.
Hi, thanks for using our code.
We found that the random seed for train_vq is not set and just fixed it. Please pull the latest code to use it.
Feel free to create a pull request to contribute to MoMask.
It seems that the eval_val_loader in train_vq.py should use the validation set instead of the test set?