Thanks for the nice code! I was wondering whether there is a mode collapse issue witnessed in the generation. For instance, for the greeting case, the generated sample always starts with i's or i'm, but the original dataset seems more diverse.
i's that to see
i's nice are see you right
i'm let everyone you
i's stopped a you you!
i's glad hi see you right
i's glad to you
i's that to you you!
i's glad to you you right
i've chance to you you!
i's greetings a you
I have also tried my own dataset (6000+ data) and the mode collapse remains. Do you have any idea what might is going wrong? Or it is simply because of the size of the dataset?
Thanks for the nice code! I was wondering whether there is a mode collapse issue witnessed in the generation. For instance, for the greeting case, the generated sample always starts with i's or i'm, but the original dataset seems more diverse.
i's that to see
i's nice are see you right
i'm let everyone you
i's stopped a you you!
i's glad hi see you right
i's glad to you
i's that to you you!
i's glad to you you right
i've chance to you you!
i's greetings a you
I have also tried my own dataset (6000+ data) and the mode collapse remains. Do you have any idea what might is going wrong? Or it is simply because of the size of the dataset?