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Re:Scaling Down Deep Learning by danieldk on Saturday December 05, 2020 @02:42PM (#25317634)
There's nothing preventing you from sharing weights across layers, and would be interesting to see some research about that.

E.g. the ALBERT model does that:

https://arxiv.org/abs/1909.11942

I have done model distillation of XLM-RoBERTa into ALBERT-based models with multiple layer groups and for the tasks that I was working on (syntax) it works really well.

E.g. we have gone from a finetuned ~1000MiB XLM-R base model to a 74MiB ALBERT-based model with barely any loss in accuracy.

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