-
-
Notifications
You must be signed in to change notification settings - Fork 16k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Question about v4.0 release - 'Transferred 642/650 items from yolov5l.pt' #1934
Comments
👋 Hello @Transigent, 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. If this is a 🐛 Bug Report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you. If this is a custom training ❓ Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available. For business inquiries or professional support requests please visit https://www.ultralytics.com or email Glenn Jocher at glenn.jocher@ultralytics.com. RequirementsPython 3.8 or later with all requirements.txt dependencies installed, including $ pip install -r requirements.txt EnvironmentsYOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
StatusIf this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training (train.py), testing (test.py), inference (detect.py) and export (export.py) on MacOS, Windows, and Ubuntu every 24 hours and on every commit. |
@Transigent you shouldn't mix pretrained weights from earlier releases with the current release. If in doubt simply reclone a fresh copy of the repo and let it autodownload new pretrained weights. Only layers with identical names and shapes are transferred, so for example if you are training a model on a different dataset from coco pretrained weights the output layers would not normally transfer (being a different shape due to their different class count). |
Thanks for the response @glenn-jocher much appreciated. |
❔Question
I am trying to train a custom dataset using a Colab notebook from some months ago. I noticed that recent training produced somewhat poorer results. I noted that Yolov5 v4.0 has been released 9 days ago and I am wondering if the architecture changes are incompatible with the code I have been using.
One thing I did note was the line from the training output shown below:
and I wondered whether the difference of 8 items is a result of the removal of one convolution layer from BottleneckCSP (one for each of the eight new C3 layers).
My training line contains the parameter "--weights yolov5l.pt" so I am pulling the .pt file from the repository. Would I be right to assume that the stock .pt file might still contain the additional layers that were part of the v3.1 release. Should this be an issue?
Additional context
The text was updated successfully, but these errors were encountered: