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AIF-C01 Practice Question: A team is using Amazon SageMaker to train a deep…
A team is using Amazon SageMaker to train a deep learning model. They notice that the training loss decreases steadily but the validation loss starts increasing after 10 epochs. Which technique should they apply to address this issue?
⚠ Common exam trap
AWS often tests the misconception that increasing model complexity or adjusting batch size can fix overfitting, when the correct first-line approach is early stopping or other regularization techniques.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Apply early stopping
The scenario describes overfitting, where the model memorizes training data but fails to generalize to validation data. Early stopping halts training when validation loss stops improving, preventing overfitting while preserving the best model weights. This is a standard regularization technique in SageMaker training jobs, configurable via the `use_early_stopping` parameter in the `Estimator` or `HyperparameterTuner`.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Apply early stopping
Why this is correct
Early stopping halts training once validation loss stops improving, directly countering the overfitting that emerges after epoch 10. By restoring the best-performing checkpoint, it prevents the model memorising training data while validation performance degrades, satisfying the scenario's need to arrest the diverging loss curves.
- ✗
Reduce the batch size
Why it's wrong here
Smaller batch sizes can add noise but are not the primary fix for overfitting.
- ✗
Increase the learning rate
Why it's wrong here
Increasing learning rate can cause divergence, not fix overfitting.
- ✗
Add more layers to the network
Why it's wrong here
Adding layers increases model capacity, likely worsening overfitting.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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