A developer is fine-tuning a language model on a dataset of [instruction, response] pairs. Initially, the training process calculated the prediction loss across all tokens in both the instruction and the response. The developer then modifies the process to calculate loss only on the tokens in the response. What is the primary effect of this change on the model's training objective?
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Ch.4 Alignment - Foundations of Large Language Models
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Ch.5 Inference - Foundations of Large Language Models
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A developer is fine-tuning a language model on a dataset of
[instruction, response]pairs. Initially, the training process calculated the prediction loss across all tokens in both theinstructionand theresponse. The developer then modifies the process to calculate loss only on the tokens in theresponse. What is the primary effect of this change on the model's training objective?Analysis of Language Model Training Objectives
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