1127-25 Fine-tuning Practice Questions

Which is a key characteristic of the annotation process used in T-Few fine-tuning?

• AA. T-Few fine-tuning uses annotated data to adjust a fraction of model weights.
• BB. T-Few fine-tuning requires manual annotation of input-output pairs.
• CC. T-Few fine-tuning involves updating the weights of all layers in the model.
• DD. T-Few fine-tuning relies on unsupervised learning techniques for annotation.

You create a fine-tuning dedicated AI cluster to customize a foundational model with your custom training data. How many unit hours are required for fine-tuning if the cluster is active for 10 days?

• AA. 480 unit hours
• BB. 240 unit hours
• CC. 744 unit hours
• DD. 20 unit hours

What is the characteristic of T-Few fine-tuning for Large Language Models (LLMs)?

• AA. It updates all the weights of the model uniformly.
• BB. It selectively updates only a fraction of weights to reduce the number of parameters.
• CC. It selectively updates only a fraction of weights to reduce computational load and avoid overfitting.
• DD. It increases the training time as compared to Vanilla fine-tuning.