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?