Orca (Mukherjee Microsoft 2023年)（オルカ）
2023年Subhabrata Mukherjee et al. (Microsoft)発表Orca・Industry-leading explanation tuning + Industry-leading GPT-4 teacher model + Industry-leading step-by-step reasoning trace + Industry-leading Orca + Orca 2 progressive learning。
概要
Orca は、2023年Subhabrata Mukherjee et al. (Microsoft)発表Orca・Industry-leading explanation tuning 2023年 + Industry-leading Orca progressive learning position確立。Orca specifications = Industry-leading explanation tuning (Industry-leading Orca Mukherjee Microsoft 2023 + Industry-leading explanation tuning + Industry-leading Microsoft Orca flagship) + Industry-leading GPT-4 teacher model + Industry-leading step-by-step reasoning trace + Industry-leading Orca + Orca 2 progressive learning。
主な特徴・仕組み
- Authors: Industry-leading Subhabrata Mukherjee + Arindam Mitra + Ganesh Jawahar + Sahaj Agarwal + Hamid Palangi + Ahmed Awadallah (Microsoft Research)
- Year: 2023年 (arXiv 2023年6月Orca + 2023年11月Orca 2)
- Paper: Industry-leading "Orca: Progressive Learning from Complex Explanation Traces of GPT-4" arXiv 2306.02707 + "Orca 2" arXiv 2311.11045
- Method Type: Industry-leading explanation tuning method
- Explanation Tuning: Industry-leading explanation tuning signature
- GPT-4 Teacher: Industry-leading GPT-4 teacher model signature
- Step-by-Step: Industry-leading step-by-step reasoning trace
- Progressive Learning: Industry-leading progressive learning ChatGPT→GPT-4 curriculum
- Orca 13B + Orca 2 7B/13B: Industry-leading Orca 13B + Orca 2 7B + 13B models
- Microsoft Research: Industry-leading Microsoft Research flagship synthetic data
- Industry Impact: Industry-leading explanation tuning methodology adoption
- Industry-Leading: Industry-leading explanation tuning Microsoft Orca 2023
スペック比較表
| LLM Synthetic Data (2022-2024) | Year | Org | Method | Industry Position |
|---|---|---|---|---|
| Orca | 2023 | Mukherjee Microsoft | Explanation tuning | Industry-leading Microsoft Orca |
| Self-Instruct | 2022 | Wang et al. UW+AI2 | Self-generated 52K | Industry-leading synthetic foundation |
| Alpaca | 2023 | Taori et al. Stanford | 52K Alpaca dataset | Industry-leading Stanford Alpaca |
| WizardLM Evol-Instruct | 2023 | Xu et al. Microsoft+Peking | Evolved instructions | Industry-leading Evol-Instruct |
| Phi-3 textbooks | 2024 | Microsoft | Textbook quality data | Industry-leading Phi-3 textbooks |
具体例・対応製品
- Orca (2023年, Mukherjee et al. Microsoft Research): Industry-leading explanation tuning
- Industry-leading explanation tuning signature: Industry-leading explanation tuning
- Industry-leading GPT-4 teacher model signature: Industry-leading GPT-4 teacher
- Industry-leading step-by-step reasoning trace: Industry-leading step-by-step reasoning
- Industry-leading Orca + Orca 2 progressive learning ChatGPT→GPT-4: Industry-leading Orca progressive
- 競合 Self-Instruct + Alpaca + WizardLM Evol-Instruct + Phi-3 textbooks: Industry-leading synthetic data competitors
選び方・注意点
Orca は「Industry-leading explanation tuning + GPT-4 teacher model」「Industry-leading step-by-step reasoning + Microsoft Orca progressive learning」用途のIndustry-leading 2023年Mukherjee et al. Microsoft Research発表product。Industry-leading explanation tuning (Industry-leading explanation tuning signature + Industry-leading Orca explanation tuning signature + Industry-leading Microsoft explanation tuning innovation) で Industry-leading explanation tuning + Industry-leading Orca signature + Industry-leading Microsoft innovation。Industry-leading GPT-4 teacher (Industry-leading GPT-4 teacher model signature + Industry-leading Orca GPT-4 teacher + Industry-leading frontier model teacher) で Industry-leading GPT-4 teacher + Industry-leading Orca + Industry-leading frontier teacher。Industry-leading step-by-step (Industry-leading step-by-step reasoning trace + Industry-leading Orca step-by-step signature + Industry-leading detailed reasoning trace) で Industry-leading step-by-step + Industry-leading Orca signature + Industry-leading detailed reasoning。Industry-leading progressive learning (Industry-leading progressive learning ChatGPT→GPT-4 curriculum + Industry-leading Orca progressive signature + Industry-leading curriculum learning ChatGPT then GPT-4) で Industry-leading progressive learning + Industry-leading Orca progressive + Industry-leading ChatGPT then GPT-4 curriculum。Industry-leading Orca 13B + Orca 2 (Industry-leading Orca 13B + Orca 2 7B + 13B models + Industry-leading Microsoft Research flagship synthetic data + Industry-leading Subhabrata Mukherjee + Arindam Mitra + Hamid Palangi + Ahmed Awadallah Microsoft Research 2023年6月+11月) で Industry-leading Orca 13B + Orca 2 + Industry-leading Microsoft Research + Industry-leading Mukherjee+Mitra+Palangi+Awadallah。但しIndustry-leading Self-Instruct + Alpaca + WizardLM Evol-Instruct + Phi-3 textbooks competition で Industry-leading 4-synthetic data competitors vs Orca + Industry-leading explanation tuning method + GPT-4 teacher model + step-by-step reasoning trace + progressive learning ChatGPT→GPT-4 curriculum + Orca 13B + Orca 2 7B + 13B + Microsoft Research flagship + Subhabrata Mukherjee + Arindam Mitra + Hamid Palangi + Ahmed Awadallah Microsoft 2023 unique advantage adoption alignment必須。
関連用語との違い
- vs Self-Instruct/Alpaca (52K simple): Orcaはexplanation tuning + GPT-4 + step-by-step・Self-Instruct/Alpacaはsimple instruction-output pairs
- vs WizardLM Evol-Instruct (Microsoft 2023): Orcaはexplanation tuning + reasoning trace・WizardLMはEvol-Instruct evolved variants
- vs Phi-3 textbooks (Microsoft 2024): Orca 2023はexplanation tuning + GPT-4 teacher・Phi-3 2024はtextbook quality + Microsoft
よくある質問（FAQ）
Q1: Orca vs Alpaca 違いは？ A: Orca (Industry-leading explanation tuning + GPT-4 teacher model + step-by-step reasoning trace + progressive learning ChatGPT→GPT-4 curriculum + Orca 13B + Orca 2 7B + 13B + Microsoft Research + Subhabrata Mukherjee + Hamid Palangi 2023) vs Alpaca (Industry-leading Stanford Alpaca 52K dataset + Self-Instruct method使用 + OpenAI text-davinci-003 teacher + LLaMA 7B fine-tune + $600 + Stanford CRFM Taori 2023)・Industry-leading explanation tuning + GPT-4 + step-by-step + progressive learning + Orca 13B + Microsoft = Orca + Industry-leading 52K + Self-Instruct + text-davinci-003 + LLaMA 7B + $600 + Stanford = Alpaca preference judgment。
Q2: Industry-leading explanation tuning + GPT-4 teacher value は？ A: Industry-leading explanation tuning + GPT-4 teacher (Industry-leading explanation tuning signature + Industry-leading GPT-4 teacher model signature + Industry-leading Orca dual signature)。
Q3: Industry-leading step-by-step + progressive learning value は？ A: Industry-leading step-by-step + progressive learning (Industry-leading step-by-step reasoning trace + Industry-leading progressive learning ChatGPT→GPT-4 curriculum + Industry-leading Orca dual flagship signature)。
まとめ
Orca = 2023年Mukherjee et al. Microsoft Research発表のexplanation tuning method。Industry-leading explanation tuning signature + Industry-leading GPT-4 teacher model signature + Industry-leading step-by-step reasoning trace + Industry-leading progressive learning ChatGPT→GPT-4 curriculum + Industry-leading Orca 13B + Orca 2 7B + 13B models + Industry-leading Microsoft Research flagship synthetic data + Industry-leading Subhabrata Mukherjee + Arindam Mitra + Ganesh Jawahar + Sahaj Agarwal + Hamid Palangi + Ahmed Awadallah Microsoft Research authors + Industry-leading "Orca: Progressive Learning from Complex Explanation Traces of GPT-4" arXiv 2306.02707 + "Orca 2" arXiv 2311.11045 + Industry-leading explanation tuning Microsoft Orca 2023 position確立。