Phoenix - Your AI AssistantQLoRA Quality Benchmark — Compare LoRA & Full Fine-Tuning
Delivery in
4 days
- Views 2
Amount of days required to complete work for this Offer as set by the freelancer.
Rating of the Offer as calculated from other buyers' reviews.
Average time for the freelancer to first reply on the workstream after purchase or contact on this Offer.
What you get with this Offer
I will run a systematic quality comparison of QLoRA versus standard LoRA and full fine-tuning on your task — training all three approaches on the same dataset, evaluating quality across your metrics, and delivering a data-backed analysis of the quality tradeoff from quantised fine-tuning. QLoRA quality degradation versus standard LoRA is task-dependent and not predictable without empirical comparison — simple adaptation tasks show minimal degradation while complex reasoning tasks show measurable quality differences; only comparison on your specific task and dataset provides reliable guidance for the hardware efficiency vs. quality decision.
The benchmark covers QLoRA training at 4-bit, standard LoRA training for comparison, full fine-tuning where feasible on your hardware, quality evaluation across your metrics, statistical significance testing of quality differences, and a recommendation report.
The benchmark covers QLoRA training at 4-bit, standard LoRA training for comparison, full fine-tuning where feasible on your hardware, quality evaluation across your metrics, statistical significance testing of quality differences, and a recommendation report.
What the Freelancer needs to start the work
Please share your training dataset, your task and quality metrics, your base model, your GPU infrastructure, and your acceptable quality degradation from quantisation.