Comments (3)
We used exactly the same corpus.
The main difference is that we trained the base model with much bigger batch sizes (8x larger) for less iterations (300k instead of 2.4M, 8x less). We also had to change the learning rates accordingly.
When we tried to do the same for the large models, we ran into many stability issues. It is quite possible that some more optimization tricks could improve the large models as well.
from spanbert.
We used exactly the same corpus.
The main difference is that we trained the base model with much bigger batch sizes (8x larger) for less iterations (300k instead of 2.4M, 8x less). We also had to change the learning rates accordingly.
When we tried to do the same for the large models, we ran into many stability issues. It is quite possible that some more optimization tricks could improve the large models as well.
Can you tell me what is your learning rate in your base model training?
It will save much resource and convenient to us to reproduction.
Thanks you very much!
from spanbert.
LR = 0.0005
from spanbert.
Related Issues (20)
- What 's in train.txt and valid.txt these two files during preprocessing HOT 1
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