How to implement a Bayesian optimizer to fine-tune Transformer hyperparameters

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With the help of code can you tell me How to implement a Bayesian optimizer to fine-tune Transformer hyperparameters.
9 hours ago in Generative AI by Ashutosh
• 28,650 points
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1 answer to this question.

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You can fine-tune Transformer hyperparameters by using a Bayesian optimizer like Optuna to efficiently search the hyperparameter space.

Here is the code snippet below:

In the above code we are using the following key points:

  • Optuna’s trial object to sample hyperparameters like learning rate, batch size, epochs, and weight decay.

  • Hugging Face Trainer API to easily manage training and evaluation.

  • IMDB dataset as a sample text classification task.

Hence, this allows efficient and intelligent exploration of hyperparameters to improve model performance with minimal manual tuning.


answered 8 hours ago by tommy

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