fine-tuning+stage

2024-12-20 15:46:04

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含义

• LLM Fine-Tuning技术笺疏 - Ray1997 - 博客园

  Fine-tuning stage,也就是微调阶段,其主要目的是「提高模型对指令(instruction)的遵循能力」。主要包括Instruction SFT(指令监督微调)、DPO、KTO等技术,本文重点讲解这三类微调技术; Prompting stage,也就是使用模型推理阶段,其主要目的是「让模型按照你的期望输出结果」。这个阶段所使用的模型学习技术主要是ICL(In-Conte...

• RankRAG:通过 fine-tuning 方式来实现检索文本的排序和答案生成...

  (2)若不带RQA或RAR两个微调任务(训练中的第二个阶段中的任务),则有近1个点的下降; (3)如果训练中只进行SFT模型,不进行Stage-II训练,则有10个点下降,这说明论文中设计的Stage-II指令任务的有效性。 总结一下:RankRAG框架思路比较简洁,且操作起来也很容易:就是增加一些检索相关则子任务训练,然后让LLM具备重排...

• fine-tuning第一层

  第一点是数据在 Stage 之间能够方便且高效的传输,应当尽量避免数据落盘带来的序列化开销,纯内存的... Fine Tune、强化学习等 ChatGPT 的训练。**Ray 基础架构**![picture.image](https://p6-volc-community-sign.byteimg.com/tos-cn-i-tlddhu82om/d5a4f9d8f47743fcb57c57b725f6972f~tplv-tlddhu82om...

• Tech football coach reaches stage two: fine-tuning

  Tech football coach reaches stage two: fine-tuningMike Whiteford

• A Deep Dive into Fine-Tuning. Stepping out of the “comfort...

  This leads to a two-stage alignment process heavily incurring resources. By combining these stages into one, ORPO aims to preserve the domain adaptation benefits of SFT while concurrently discerning and mitigating unwanted generation styles as aimed towards by preference-...

• [PDF] LLM4TS: Two-Stage Fine-Tuning for Time-Series...

  Inspired by the supervised fine-tuning in chatbot domains, we prioritize a two-stage fine-tuning process: first conducting supervised fine-tuning to orient the LLM towards time-series data, followed by task-specific downstream finetuning. Furthermore, to unlock the flexibility of pre-trained LLMs...

• A-2022-IJCAI-Fine-Tuning Graph Neural Networks via Graph Topolog...

  这句话里,要搞清楚的东西是pretrain-finetuning:它能够解决的问题是缺少label的问题。 Current studies use existing techniques, such as weight constraint, representation constraint, which are derived from images or text data, to transfer the invariant knowledge from the pre-train stage to fine-tuning...

• ...An Asymmetric LoRA Architecture for Efficient Fine-Tuning

  Figure 4: Architecture and workflow of HydraLoRA. During the fine-tuning stage, HydraLoRA first adaptively identifies and initializes N of intrinsic components without specific domain knowledge. It then employs a trainable MoE router that treats each intrinsic component as an expert to automatically ...

• ...version of AirDet: Few-Shot Detection without Fine-tuning...

  Few-shot object detection has attracted increasing attention and rapidly progressed in recent years. However, the requirement of an exhaustive offline fine-tuning stage in existing methods is time-consuming and significantly hinders their usage in online applications such as autonomous exploration of low...

• ...LEARNING FOR PRE-TRAINED LANGUAGE MODEL FINE-TUNING - 简书

  总结:在cross entory的基础上,引入SCL,仅此而已 论文:https://openreview.net/pdf?id=cu7IUiOhujH 资料:https://zhuanlan.zhihu.com/p/278127741 ABSTRACT we propose a supervised contrastive learning (SCL) objective for the fine-tuning stage INTRODUCTION ...

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