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[D] NLP Researchers: what is your workflow?

I started working on the Toxicity Detection Kaggle challenge. I’d be curious to know how people familiar with NLP handle this kind of problems.

My problem is that I want to try things out, but running anything on the full model takes hours, and running on a subset of the data doesn’t always tell me how good the result is.

I have multiple computers and GPUs at home so I juggle between them but my workflow is generally a mess. It’s difficult to keep track of what I’m doing, what experiments I should prioritize, optimize hyperparameters etc.

Is there an all-in-one solution out there to manage my experiments? I’m starting to experiment with Kubernetes but it’s a lot of overhead to configure and run jobs.

I guess I could use a beefier tool like Kubeflow but I’m wondering if that wouldn’t be too big of a tool for the job.

How are professionals handling things?

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.