posts/prompt_weight_experiments_for_llm_instruction_fine_tuning/2024-01-24-prompt_weight_experiments_for_llm_instruction_fine_tuning

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Bayesian beagle - Prompt Weight Experiments for LLM Instruction Fine-Tuning

Study examines impact of prompt token classification loss weighting on LLaMA models fine-tuned on instruction tasks. Results vary based on dataset length.

https://bayesian-beagle.netlify.app/posts/prompt_weight_experiments_for_llm_instruction_fine_tuning/2024-01-24-prompt_weight_experiments_for_llm_instruction_fine_tuning

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Motivation

To investigate validating OpenAI’s claim on prompt loss weighting (PLW) for fine-tuning LLMs. How does this parameter affect training? How important is it for model performance on instruction tasks?