Skip to content

Improve training loop: add validation split, early stopping, checkpoint, and ReduceLROnPlateau#10

Closed
SUJALGOYALL wants to merge 1 commit intoOPCODE-Open-Spring-Fest:mainfrom
SUJALGOYALL:feature-lstm-validation
Closed

Improve training loop: add validation split, early stopping, checkpoint, and ReduceLROnPlateau#10
SUJALGOYALL wants to merge 1 commit intoOPCODE-Open-Spring-Fest:mainfrom
SUJALGOYALL:feature-lstm-validation

Conversation

@SUJALGOYALL
Copy link
Copy Markdown
Contributor

Description

This pull request improves the LSTM model training loop by adding several enhancements to improve generalization, prevent overfitting, and stabilize learning.

Key Updates

  • Added a validation split (~15%) for monitoring validation metrics.
  • Implemented early stopping with best-weight restoration.
  • Added model checkpointing to automatically save the best model.
  • Applied ReduceLROnPlateau scheduler to dynamically adjust the learning rate when validation loss stalls.

These changes make the training process more efficient and robust while reducing overfitting.


Semver Changes

  • Patch (bug fix, no new features)
  • Minor (new features, no breaking changes)
  • Major (breaking changes)

Issues

Closes #3 >


Checklist

@SUJALGOYALL SUJALGOYALL force-pushed the feature-lstm-validation branch from 477f755 to f8f8c3b Compare October 21, 2025 17:05
@SUJALGOYALL
Copy link
Copy Markdown
Contributor Author

@gaurav12301010 Please add labels: Type: Medium, Semver: Minor, and PR:Accept.
I don’t have write access to add labels myself.

@gaurav12301010 gaurav12301010 added Medium enhancement New feature or request Task labels Oct 21, 2025
@gaurav12301010 gaurav12301010 self-assigned this Oct 21, 2025
@gaurav12301010 gaurav12301010 removed their assignment Oct 22, 2025
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

enhancement New feature or request Medium Task

Projects

None yet

Development

Successfully merging this pull request may close these issues.

Enhance Training Pipeline with Validation Split, EarlyStopping, Checkpointing and LR Scheduling

2 participants