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I'm trying to solve a multiclass classification problem with BERT by leveraging the Ktrain wrapper. Having a large amount of data, I wanted to know if it is possible to parallelize the learner.fit_onecycle (3e-4, 5) function or the autofit () function.

For example as happens with sklerarn where you specify the number of parallel jobs, with the n_jobs parameter.

You can help me? Thanks

SviluppatoreSeriale
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First, if you use DistilBert instead of BERT in ktrain, it will cut your training time in half. Second, multiple cores should be used by default by TensorFlow2 when calling any of the fit methods in ktrain using a CPU. You can control the number of CPU cores, if you want.

blustax
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