Adding Model Checkpointing and Logging Enhancements#233
Open
shreyaskamathkm wants to merge 2 commits intoMultimediaTechLab:mainfrom
Open
Adding Model Checkpointing and Logging Enhancements#233shreyaskamathkm wants to merge 2 commits intoMultimediaTechLab:mainfrom
shreyaskamathkm wants to merge 2 commits intoMultimediaTechLab:mainfrom
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
✨ [Feat] Add Model Checkpointing and Logging Enhancements
Description
This pull request introduces robust model checkpointing using PyTorch Lightning's
ModelCheckpointcallback. It ensures that the best models are saved based on Mean Average Precision (mAP) during training. Additionally, it refines the logging utilities to support improved experiment tracking.key Changes
ModelCheckpointtologging_utils.pyto save top 3 models based onmap.setup_loggerand logging configurations.Changelog
e923b830a3159b