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Separate each search type into its own mlflow run to allow comparison using Azure ML / mlflow #540

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guybartal opened this issue May 9, 2024 · 0 comments
Open

Separate each search type into its own mlflow run to allow comparison using Azure ML / mlflow #540

guybartal opened this issue May 9, 2024 · 0 comments

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@guybartal
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guybartal commented May 9, 2024 •
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AS a researcher I would like to be able to compare metric results across different types of search approaches in Azure ML / ML Flow
SO, I would be able to choose best type of search for my case.

related to #529

Note: currently eval step averages all metrics for all search types and log to mflow only the mean value per metric, but also uploads the full detailed table to azureml.

DoD:

  • query and eval steps will run per search type in parallel (like Index does with IndexConfig class)

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@guybartal guybartal mentioned this issue May 9, 2024
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guybartal added a commit that referenced this issue May 18, 2024
@guybartal
Log all hyper-parameters to mlflow (#529)
618007a 
closes #480 

### This PR includes

- Log all hyper parameters to mlflow
- Config refactoring - lowercase for all attributes as those are not constants (match coding conventions)
- Print azure ml monitoring URL right after its creation to allow easy access to monitoring (ctrl + left click)
- Fix issues with experiment and job names, allowing azure ml commands open experiment and mlflow runs automatically, while locally we create those manually.
- Remove unused experiment settings from `.env` sample file
- Hide warning azureml warnings by using `CliV2AnonymousEnvironment` as Azure ML environment name
- Temporary solution for wrong json format in Q&A Gen step with current CI generation model version by removing all "..."` strings from the model response

### WIP
#540
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