flag `--patience` (epochs to wait for no observable improvement for early stopping of training)

[Egorundel]

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• [X] I have read the README carefully. 我已经仔细阅读了README上的操作指引。

• [X] I want to train my custom dataset, and I have read the tutorials for training your custom data carefully and organize my dataset correctly; (FYI: We recommand you to apply the config files of xx_finetune.py.) 我想训练自定义数据集，我已经仔细阅读了训练自定义数据的教程，以及按照正确的目录结构存放数据集。（FYI: 我们推荐使用xx_finetune.py等配置文件训练自定义数据集。）

• [X] I have pulled the latest code of main branch to run again and the problem still existed. 我已经拉取了主分支上最新的代码，重新运行之后，问题仍不能解决。

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Question

Do you have the possibility of stopping training if after a certain number of epochs there is no noticeable improvement in the neural network? If there is such a possibility, then what flag should be set for this during training?

Additional

No response

[Chilicyy]

Hi, you can check if total_loss stop decreasing or self.ap stop increasing to optimize your training epochs.