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glample avatar glample commented on July 17, 2024

Hi,

Not sure about what you mean by frequent outputs, but the code that selects the words to mask is here: https://github.com/facebookresearch/XLM/blob/master/src/trainer.py#L295-L305

sample_alpha == 0 will do the same thing as in the original BERT paper, i.e. sample 15% of words at random. A non-zero value of sample_alpha will sample 15% of the words in a batch, but each word will have a different probability of being masked out (i.e. the rare words will have a higher probability to be masked out than the frequent ones).

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stephanpeitz avatar stephanpeitz commented on July 17, 2024

Yes, I was referring to

we also subsample the frequent outputs using an approach similar to Mikolov et al. (2013b)

Thanks for pointing me to the function.

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stephanpeitz avatar stephanpeitz commented on July 17, 2024

Sorry, one more question: which value for sample_alpha have you used in your experiments?

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glample avatar glample commented on July 17, 2024

We used sample_alpha = 0.5

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