Summary of Scalebio: Scalable Bilevel Optimization For Llm Data Reweighting, by Rui Pan et al.
ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting
by Rui Pan, Jipeng Zhang, Xingyuan Pan, Renjie Pi, Xiaoyu Wang, Tong Zhang
First submitted to arxiv on: 28 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Optimization and Control (math.OC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces ScaleBiO, a scalable algorithm for bilevel optimization in large language models (LLMs). Bilevel optimization is useful in various machine learning settings, but most algorithms require second-order information, making them challenging to scale. The recent emergence of first-order algorithms capable of addressing bilevel optimization problems has shown promise, but their practical efficiency remains unverified, particularly for LLMs. ScaleBiO combines with a memory-efficient training technique called LISA to allow the paradigm to scale to 34-billion-parameter LLMs on eight A40 GPUs. The algorithm successfully applies bilevel optimization under practical scenarios for large-sized LLMs, including GPT-2, LLaMA-3-8B, GPT-NeoX-20B, and Yi-34B. ScaleBiO ensures the optimality of learned data weights and provides a convergence guarantee matching conventional first-order bilevel optimization on smooth and strongly convex objectives. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper introduces a new algorithm called ScaleBiO that helps big language models learn better from their data. It uses a special kind of math problem-solving to find the right balance between different types of data. This is important because it helps the model ignore unimportant information and focus on what’s really useful. The algorithm works well even with very large models, which is great news for people who want to use these models for things like language translation or text summarization. |
Keywords
» Artificial intelligence » Gpt » Llama » Machine learning » Optimization » Summarization » Translation
