question-mark
Stuck on an issue?

Lightrun Answers was designed to reduce the constant googling that comes with debugging 3rd party libraries. It collects links to all the places you might be looking at while hunting down a tough bug.

And, if you’re still stuck at the end, we’re happy to hop on a call to see how we can help out.

Refactor training hyperparameters in `SetFitTrainer` to dedicated class

See original GitHub issue

The current implementation of SetFitTrainer has become a bit bloated because it accepts all the hyperparameters for training as separate arguments. In hindsight, it would have been better to collect all the hyperparameters in a separate data class (similar to the TrainingArguments of transformers). At the same time, it doesn’t seem necessary to prepend SetFit to the name of these classes.

To that end, it would be great to:

  • Create new TrainingArguments and Trainer classes, where Trainer accepts all the hyperparameters as an args parameter.
  • Add a deprecation notice on SetFitTrainer to inform users about the new Trainer (and let them know it will be removed in 2 minor releases time)

Issue Analytics

  • State:open
  • Created 10 months ago
  • Reactions:1
  • Comments:5 (1 by maintainers)

github_iconTop GitHub Comments

1reaction
lewtuncommented, Nov 15, 2022

Thanks @tomaarsen - that would be wonderful! Feel free to ping me if you need any guidance 😃

1reaction
tomaarsencommented, Nov 14, 2022

I’ll get working on this in a week on the 21st, if it hasn’t been claimed by then!

  • Tom Aarsen
Read more comments on GitHub >

github_iconTop Results From Across the Web

CNN Training Loop Refactoring - deeplizard
Deep Learning Course 4 of 7 - Level: Intermediate. CNN Training Loop Refactoring - Simultaneous Hyperparameter Testing ...
Read more >
Using hyperparameter tuning | AI Platform Training
This page shows you how to use AI Platform Training hyperparameter tuning when training your model. Hyperparameter tuning optimizes a target variable that ......
Read more >
Use your own training scripts and automatically select the best ...
Use your own training scripts and automatically select the best model using hyperparameter optimization in Amazon SageMaker.
Read more >
Hyperparameter tuning a model (v2) - Azure Machine Learning
To use sobol, use the RandomParameterSampling class to add the seed and rule as shown in the example below. Python Copy. from azure.ai....
Read more >
Parameters, Hyperparameters, Machine Learning
As a machine learning engineer designing a model, you choose and set hyperparameter values that your learning algorithm will use before the training...
Read more >

github_iconTop Related Medium Post

No results found

github_iconTop Related StackOverflow Question

No results found

github_iconTroubleshoot Live Code

Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start Free

github_iconTop Related Reddit Thread

No results found

github_iconTop Related Hackernoon Post

No results found

github_iconTop Related Tweet

No results found

github_iconTop Related Dev.to Post

No results found

github_iconTop Related Hashnode Post

No results found