bert
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chooses 15% of token
From paper, it mentioned
Instead, the training data generator chooses 15% of tokens at random, e.g., in the sentence my
dog is hairy it chooses hairy.
It means that 15% of token will be choose for sure.
From https://github.com/codertimo/BERT-pytorch/blob/master/bert_pytorch/dataset/dataset.py#L68,
for every single token, it has 15% of chance that go though the followup procedure.
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Describe the feature
I think enforcing typing in methods parameters can be helpful for robustness, readability and stability of the code.
By using mypy static type checker, we can see potential improvements for jina:
Usage:
pip install mypy
mypy --ignore-missing-imports jinaDo not get overwhelmed by the errors. Let's slowly keep improving until we can eve
If I want to use both of them, how to modify code in aen.py? Thanks a lot.
Ideally, we'd support something like mnli += {pretrain_data_fraction = 0.5}, pretrain_tasks = {mnli,boolq}. Currently, pretrain_data_fraction is just a global argument for all pretraining tasks.
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modeling_longformer.pyhas the classesLongformerForSequenceClassification,LongformerForMultipleChoiceandLongformerForTokenClassificationwhich are not present inmodeling_tf_longformer.pyat the moment.Those classes should be equally added to
modeling_tf_longformer.py.Motivation
The pretrained weights for TFLongformer are available so that these