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?
Remove duplicate sentences and documents before training
Convert every file in the corpus to UTF-8 encoding
Increase the learning rate used during the fine-tuning job
Encrypt the training dataset with AWS Key Management Service
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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