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Hi, when I saw your code, I found that only the first 11 layers of the transformer are loaded (when feature_fusion == True)
And the "ff_last_layer" and "ff_encoder_norm" are trained from scratch, am I right?
If so, what is the performance when loading 12th layer weights to ff_last_layer and norm to off_encoder_norm?
Thanks
The text was updated successfully, but these errors were encountered:
Hi, thanks for your interest.
Yes exactly, we only load the pretrained weights of the first 11 layers when feature fusion is enabled. The intuition behind is that the input distribution of the ff_last_layer and the pretraiend layer is quite different.
Sorry, we didn't conduct the experients of loading all the 12 layers weights. Loading the pretrained norm weights give slightly worser results on some datasets if I remember correctly.
And the "ff_last_layer" and "ff_encoder_norm" are trained from scratch, am I right?
Thanks
The text was updated successfully, but these errors were encountered: