Key Metrics
- Training vs. Validation Loss: Ensure the model is learning without over-fitting.
- Accuracy Improvement: Verify the model correctly predicts outputs in your validation set compared to the base model.
- Regression Check: Run your Test Set against the new weights to ensure general performance remains high and no regressions were introduced.
Next
- Deploy a successful run: Deployment
- Benchmark the candidate model on golden cases: Test Sets