Exploring Deep Learning Hyperparameters with Random Forests

W&B
W&B
Nov 5 · 5 min read

My colleague Lavanya ran a large hyperparameter sweep on a Kaggle simpsons dataset in colab here. She ran a large search with the intention of finding the best model for the data. In the process of running the sweep she created a lot of hyperparameter data, and I was wondering if I could find useful insights in it.

Here’s a parallel co-ordinates plot visualizing the results of the hyperparameter search. As you can see she tried a lot of different values for epochs, learning rate, weight decay, optimizers and batch size. In this…

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W&B

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Building developer tools for deep learning.

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