Lightning-AI/lit-llama

Resume in the pretraining code

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#359 创建于 2023年6月2日

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 (2 评论) (1 反应) (0 负责人)Python (5,533 star) (473 fork)batch import
help wanted

描述

I would like to request a new feature in the code: the ability to resume training from a checkpoint.

Currently, the code can save a checkpoint of the model's state at any point during training. However, there is no way to resume training from a checkpoint.

The code can save two things along with the model state_dict: 1)the optimizer, 2)the id of the last example it has seen (assuming the data is fed sequentially to the model not randomly)

贡献者指南

技术栈
pythonpytorch
领域
machine learningai
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
3
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
1-2 days
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
fresh
清晰度议题是否清楚说明期望改动、验收标准和下一步。
clear
前置要求
Basic Python and PyTorch knowledgeUnderstanding of training loop checkpoints
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
60
研究方向
First, examine the current checkpoint saving logic in the pretraining code (likely in the `train.py` or similar file). The implementation should add a ` resume from checkpoint` argument that loads the model state dict, optimizer state dict, and the last processed example ID. Then, modify the data loading to skip already processed examples and continue training from that point. Refer to the existing saving logic and any comments in the code for guidance.