Lightning-AI/lit-llama

Resume in the pretraining code

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#359 opened on 2023年6月2日

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help wanted

説明

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)

コントリビューターガイド

技術スタック
pythonpytorch
領域
machine learningai
Issue 種別
feature
難度新しい貢献者にとっての実装難度です。1 は非常に小さな変更、5 は専門的な作業です。
3
推定時間経験ある貢献者が調査、実装、テスト、pull request 準備にかけるおおよその時間範囲です。
1-2 days
活動状況Issue が今どれだけ取り組みやすいかを示します。新しい、活発、古い、ブロック中、またはメンテナー入力待ちなどです。
fresh
明確さ期待される変更、受け入れ条件、次の手順がどれだけ明確かを示します。
clear
前提条件
Basic Python and PyTorch knowledgeUnderstanding of training loop checkpoints
初心者向け度初回貢献者にどれだけ取り組みやすいかを 1-100 で推定したスコアです。
60
調査方針
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.