The Worth Of Prompts In Pre-trained Models

The Worth Of Prompts In Pre-trained Models

Fine-tuning via an explicit classifier head is one of the critical paradigms for adapting pretrained models for classification.

Recently, researchers from Hugging Face showed task-specific prompting provides several benefits while fine-tuning pre-trained language models. In a paper called “How Many Data Points is a Prompt Worth?”, researchers stated prompting impacts the pre-trained models’ efficiency and is often worth hundreds of data points on average across classification tasks.

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