Yes. It worked.
As far as I remember, the model was very tolerant to the introduced noise and was able to adapt and recover very quickly. After being hit by the first noise multiply, the MSE (or whatever metric used) was reduced a bit, but not drastically. Then, it started to recover and tolerate the noise. I was trying to generate different models at the mid-epoch training journey. Then, by having a noise generator, I aimed at building a high-level ensemble by combining all the models.
Training Configuration:
I don’t remember the exact configuration; but I can give an example about what I had in mine: suppose my training goes up to 100 epochs, the model learns normally and after epoch 50, it is hit with this noise at every 10 epochs {50, 60, 70, 80, 90} and it stops at epoch 100.  Something like that.
No harm to model’s performance?
The Model performance depends on what you are trying to achieve, and how you are manipulating the weights.