APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Which of the following are advantages of Transformers over Recurrent Sequence Models?
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Better at learning long-range dependencies
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Faster to train and run on modern hardware
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Require many fewer parameters to achieve similar results
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None of the above
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Explanation:
Detailed explanation-1: -One aspect that differentiates the transformer from previous sequence models is that it does not take in the input embeddings sequentially; on the contraire, it takes in all the embeddings at once. This allows for parallelization and significantly decreases training time.
Detailed explanation-2: -They hold the potential to understand the relationship between sequential elements that are far from each other. They are way more accurate. They pay equal attention to all the elements in the sequence. Transformers can process and train more data in lesser time. More items •10-Aug-2022
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