this post was submitted on 25 Nov 2023
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LocalLLaMA

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Community to discuss about Llama, the family of large language models created by Meta AI.

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Is there a good way (or rule of thumb) to decide when looking at a problem if peft/lora finetuning might be successful or if it only makes sense to do a complete finetuning of all weights? Given the big difference in cost knowing if peft/lora might work for a problem feels pretty essential.

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[–] sshh12@alien.top 1 points 11 months ago

My rule of thumb has been to LoRA (r between 4 and 16) until unsatisfied with results. It of course depends on data/task but imo most cases don't require full fine-tune and perf/compute ROI is low.