cp: cannot stat 'runs/detect/train/weights/last.pt': No such file or directory

[Ray150789]

Search before asking

• I have searched the HUB issues and found no similar bug report.

HUB Component

Training

Bug

My training completed but I cant find the best,pt file it says results saved to runs/detect/train my folders include runs/detect/predict which has output video files which I wish to retrain as the output has low quality output. Also can I use an ipynb again if I want to get a better trained model.

Environment

Device name DESKTOP-AM4RDAQ
Processor
Installed RAM 8,00 GB (7,88 GB usable)
Device ID 2C265D9F-7E3E-4D23-816A-85FFE62C5616
Product ID 00331-20020-00000-AA388
System type 64-bit operating system, x64-based processor
Pen and touch No pen or touch input is available for this display
Edition Windows 10 Pro
Version 22H2
Installed on ‎2023/‎10/‎09
OS build 19045.5247
Experience Windows Feature Experience Pack 1000.19060.1000.0

Minimal Reproducible Example

No response

Additional

No response

[UltralyticsAssistant]

👋 Hello @Ray150789, thank you for raising an issue about Ultralytics HUB 🚀! We're here to help.

It looks like your training process has completed, but you're unable to locate the expected best.pt or last.pt files, and you've also mentioned a desire to retrain for better results. Since you've flagged this as a 🐛 Bug Report, here's how you can help us assist you faster:

• Please provide a Minimum Reproducible Example (MRE). This includes concise steps or code snippets to help us understand and reproduce the issue on our end.
• Screenshots of your directory structure (runs/detect/) or specific error messages would also be incredibly helpful.

For your retraining query, you should be able to use an .ipynb notebook again for further training. Ensure that your dataset and environment are correctly set up to optimize your model's performance.

An Ultralytics engineer will review your issue soon to provide more direct assistance. Thank you for your patience and for helping us improve Ultralytics HUB! 😊

[pderrenger]

@Ray150789 thank you for raising this issue! Let me help clarify and guide you through potential resolutions.

The error cp: cannot stat 'runs/detect/train/weights/last.pt': No such file or directory usually indicates that the training process did not generate a last.pt file. This could happen for several reasons, such as improper termination of training or issues during the saving process.

Steps to Troubleshoot and Resolve:

1. Verify Training Completion:

   • Double-check the training logs to confirm that the training process completed successfully. If there were any interruptions or errors, the weights (last.pt and best.pt) might not have been saved.

2. Confirm Output Directory:

   • According to your description, results saved to runs/detect/train suggests that the model outputs, including weights, should be in that directory. Check the exact path:

     runs/detect/train/weights/
     

     If the folder exists but is empty, it indicates an issue with saving the weights.

3. Output Videos in runs/detect/predict:

   • The runs/detect/predict folder contains results from inference runs, not training. If you wish to retrain using those predictions, you'd need to prepare a dataset from the output. This involves annotating the images or videos again with corrected labels if required.

4. Retraining with Updated Parameters:

   • Yes, you can use the .ipynb notebook again to retrain the model. Ensure that:
     • You specify a valid dataset path in the data argument.
     • Update training hyperparameters like epochs, lr0, or batch_size to potentially improve the model's quality.
   • Example:

     from ultralytics import YOLO
     model = YOLO("yolov8n.pt")  # Load a base model or your checkpoint
     model.train(data="path/to/dataset.yaml", epochs=50, batch_size=16)

5. Ensure Latest Version:

   • Confirm that you are using the latest version of Ultralytics packages. Run the following:

     pip install ultralytics --upgrade
     

6. Check Disk Space:

   • Insufficient disk space might prevent saving weights. Verify that you have enough storage available on your machine.

Additional Notes:

• If you encounter low-quality predictions, you may want to:
  • Ensure your dataset is properly annotated and balanced.
  • Train for more epochs or fine-tune the learning rate.
  • Use a larger YOLO model (e.g., yolov8m.pt instead of yolov8n.pt) for better accuracy.
• For running training on a lower-spec machine like yours, consider reducing batch_size and enabling device='cpu' if GPU is unavailable.

If the issue persists, feel free to share additional details, such as training logs or dataset configuration, so we can assist further. Best of luck with your training, and I hope you achieve the desired results! 🚀