翻訳言語

スクラッチからのLLM構築、パート32m -- 介入: 結論

著者は、自前のマシンで44時間かけてトレーニングしたモデルがGPT-2 smallにほぼ匹敵する性能に達し、「スクラッチからのLLM構築」プロジェクトの介入シリーズを完了した。学習率調整、ドロップアウト除去、重み減衰などの様々な介入を試し、最終的にローカルトレーニングで良好な結果を得た。次は書籍の付録を確認し、最終目標としてJAXフレームワークを使用した完全独自実装に挑戦する予定。

LLM from scratch (32l) – Interventions: updated instruction fine-tuning results
2.5
The article presents updated results from instruction fine-tuning experiments on a 32-layer language model built from scratch. It discusses interventions and performance improvements achieved through the fine-tuning process.
LLM from scratch, part 33 – what I learned from the appendices
2.0
The author reflects on insights gained from working through appendices in their LLM from scratch series, noting that these supplementary materials provided valuable practical knowledge and deeper understanding of implementation details beyond the main content.

出典 gilesthomas.com原文を表示 ↗

翻訳言語

スクラッチからのLLM構築、パート32m -- 介入: 結論

LLM from scratch (32l) – Interventions: updated instruction fine-tuning results
2.5
The article presents updated results from instruction fine-tuning experiments on a 32-layer language model built from scratch. It discusses interventions and performance improvements achieved through the fine-tuning process.
LLM from scratch, part 33 – what I learned from the appendices
2.0
The author reflects on insights gained from working through appendices in their LLM from scratch series, noting that these supplementary materials provided valuable practical knowledge and deeper understanding of implementation details beyond the main content.

スクラッチからのLLM構築、パート32m -- 介入: 結論

関連記事

LLM from scratch (32l) – Interventions: updated instruction fine-tuning results

LLM from scratch, part 33 – what I learned from the appendices

スクラッチからのLLM構築、パート32m -- 介入: 結論

関連記事

LLM from scratch (32l) – Interventions: updated instruction fine-tuning results

LLM from scratch, part 33 – what I learned from the appendices