prithivi1
commented
2 months ago Hi @charlescwwang , I tried to train my model with 1 labels. However I'm unable to load the pretrained weights with 80 classes to my 1 class model. I could see that you have passed that layer in your error logs. Can you help me figure out how to do that.
`[07/16 10:00:40] INFO | π Created log folder: runs/train/v9-dev [07/16 10:00:40] INFO | π¦ Loaded train cache [07/16 10:00:40] INFO | π Building YOLO [07/16 10:00:40] INFO | ποΈ Building backbone [07/16 10:00:40] INFO | ποΈ Building neck [07/16 10:00:41] INFO | ποΈ Building head [07/16 10:00:41] INFO | ποΈ Building detection [07/16 10:00:41] INFO | ποΈ Building auxiliary [07/16 10:00:41] INFO | π Weight weights/v9-c.pt not found, try downloading π₯ Downloading v9-c.pt... βββββββββββββββββββββββββββββ 100.0% β’ 102895262/102895262 bytes β’ 0:00:00 [07/16 10:00:42] INFO | β Download completed. Error executing job with overrides: ['task=train', 'task.data.batch_size=8', 'task.epoch=10', 'model=v9-c', 'class_num=1', 'dataset=dev.yaml', 'device=cuda'] Traceback (most recent call last): File "/content/drive/MyDrive/Colab-Notebooks/yolov9/YOLO/yolo/lazy.py", line 27, in main model = create_model(cfg.model, class_num=cfg.class_num, weight_path=cfg.weight) File "/usr/local/lib/python3.10/dist-packages/yolo/model/yolo.py", line 136, in create_model model.model.load_state_dict(torch.load(weight_path, map_location=torch.device("cpu")), strict=False) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 2189, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for ModuleList: size mismatch for 22.heads.0.class_conv.2.weight: copying a param with shape torch.Size([80, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 256, 1, 1]). size mismatch for 22.heads.0.class_conv.2.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([1]). size mismatch for 22.heads.1.class_conv.2.weight: copying a param with shape torch.Size([80, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 256, 1, 1]). size mismatch for 22.heads.1.class_conv.2.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([1]). size mismatch for 22.heads.2.class_conv.2.weight: copying a param with shape torch.Size([80, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 256, 1, 1]). size mismatch for 22.heads.2.class_conv.2.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([1]). size mismatch for 38.heads.0.class_conv.2.weight: copying a param with shape torch.Size([80, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 512, 1, 1]). size mismatch for 38.heads.0.class_conv.2.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([1]). size mismatch for 38.heads.1.class_conv.2.weight: copying a param with shape torch.Size([80, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 512, 1, 1]). size mismatch for 38.heads.1.class_conv.2.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([1]). size mismatch for 38.heads.2.class_conv.2.weight: copying a param with shape torch.Size([80, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 512, 1, 1]). size mismatch for 38.heads.2.class_conv.2.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([1]).
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.`
charlescwwang
Abdul-Mukit
Issue Description I tried to train model using my data with 12 labels. (coco dataset format) When I try to train the model, the following error occurs.
Additional Context This is my command
This is log
Future Considerations Please suggest any potential future improvements related to this issue.