AWS Certified AI Practitioner AIF-C01 Practice Question
During data curation for fine-tuning a foundation model on internal documents, which step primarily helps reduce overfitting and improves the model's ability to generalize to unseen text?
Increase the learning rate used during the fine-tuning job
Encrypt the training dataset with AWS Key Management Service
Convert every file in the corpus to UTF-8 encoding
Remove duplicate sentences and documents before training
Removing duplicate or near-duplicate records limits the model's exposure to identical examples, preventing it from memorizing repetitive patterns and thereby decreasing the risk of overfitting. Converting files to UTF-8 only standardizes encoding, encryption safeguards data but does not affect learning behavior, and increasing the learning rate is a training hyperparameter adjustment rather than a data-curation practice.
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AWS Certified AI Practitioner AIF-C01
Applications of Foundation Models
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