how to stop Early stop function

[JustinNober]

❔Question

Additional context

[github-actions]

👋 Hello @JustinNober, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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Requirements

Python>=3.6.0 with all requirements.txt installed including PyTorch>=1.7. To get started:

$ git clone https://github.com/ultralytics/yolov5
$ cd yolov5
$ pip install -r requirements.txt

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• Google Cloud Deep Learning VM. See GCP Quickstart Guide
• Amazon Deep Learning AMI. See AWS Quickstart Guide
• Docker Image. See Docker Quickstart Guide

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[glenn-jocher]

@JustinNober you can disable early stopping by passing 0, or the same value as --epochs for --patience:

python train.py --patience 0  # EarlyStopping disabled
python train.py --patience 300 --epochs 300  # EarlyStopping will not happen

[glenn-jocher]

@JustinNober good news 😃! Your original issue may now be fixed ✅ in PR #5303. This PR implements a more informative EarlyStopping message explaining the reason for stopping and steps you can take to update or disable EarlyStopping behavior.

To receive this update:

• Git – git pull from within your yolov5/ directory or git clone https://github.com/ultralytics/yolov5 again
• PyTorch Hub – Force-reload with model = torch.hub.load('ultralytics/yolov5', 'yolov5s', force_reload=True)
• Notebooks – View updated notebooks
• Docker – sudo docker pull ultralytics/yolov5:latest to update your image

Thank you for spotting this issue and informing us of the problem. Please let us know if this update resolves the issue for you, and feel free to inform us of any other issues you discover or feature requests that come to mind. Happy trainings with YOLOv5 🚀!

[chiragpandav]

usage: train.py [-h] [--model MODEL] [--data DATA] [--epochs EPOCHS]
[--batch-size BATCH_SIZE] [--imgsz IMGSZ] [--nosave]
[--cache [CACHE]] [--device DEVICE] [--workers WORKERS]
[--project PROJECT] [--name NAME] [--exist-ok]
[--pretrained [PRETRAINED]]
[--optimizer {SGD,Adam,AdamW,RMSProp}] [--lr0 LR0]
[--decay DECAY] [--label-smoothing LABEL_SMOOTHING]
[--cutoff CUTOFF] [--dropout DROPOUT] [--verbose]
[--seed SEED] [--local_rank LOCAL_RANK]

train.py: error: unrecognized arguments: --patience 2

[glenn-jocher]

@chiragp007 hi there! It seems that the train.py script does not have a --patience argument. The available arguments for train.py are listed in the usage section below:

usage: train.py [-h] [--model MODEL] [--data DATA] [--epochs EPOCHS]
                [--batch-size BATCH_SIZE] [--imgsz IMGSZ] [--nosave]
                [--cache [CACHE]] [--device DEVICE] [--workers WORKERS]
                [--project PROJECT] [--name NAME] [--exist-ok]
                [--pretrained [PRETRAINED]]
                [--optimizer {SGD,Adam,AdamW,RMSProp}] [--lr0 LR0]
                [--decay DECAY] [--label-smoothing LABEL_SMOOTHING]
                [--cutoff CUTOFF] [--dropout DROPOUT] [--verbose]
                [--seed SEED] [--local_rank LOCAL_RANK]

If you have any more questions or need further assistance, please feel free to ask.