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Deep Learning Fundamentals

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    Deep Learning Fundamentals > Unit 9 > Unit 9 Exercises
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    Unit 9 – Exercises

    Exercise 1: Evaluating Mixed-Precision Performance

    I recommend trying out the different mixed-precision choices on your GPU (if you have one):

    • regular float32 ("32-true")

    • regular float16 ("16-true")

    • regular float64 ("64-true")

    • mixed precision with float16 ("16-mixed")

    • mixed-precision with bfloat16 ("bf16-mixed")

    For this, you can modify the precision argument of the Trainer in the DistillBert model from lecture 9.1here.

    Please also fell free to share your results in the discussion here — I’d be interested to hear what you find on various GPU architectures!

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    Unit 9 Exercises

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