Comments (1)
Changed the training parameters and now it works fine for some reason
from super-gradients.
Related Issues (20)
- ImportError: cannot import name 'utils' from partially initialized module 'super_gradients.training' (most likely due to a circular import HOT 4
- yolo-nas-sat model availability
- AttributeError: 'RegSeg48' object has no attribute 'set_dataset_processing_params' HOT 1
- How to set different weight decay values for different modules of the model
- yolo nas pose demo/colab is broken HOT 1
- How to get edge_links, edge_colors, keypoint_colors when using yolo nas pose onnx?
- Validation metrics = 0.0 during training yolo-nas
- YOLO NAS'S Precision is significantly lower compare to other later YOLO model even when using same dataset ? HOT 4
- BaseSGLogger storage_location parameter is systematically overriden, why?
- Access Joints Coordinate
- Issue when training and predicting with a custom dataset and the YOLO_NAS_S model HOT 2
- Model training process halted for small dataset HOT 4
- Inquiry About Official Release Date of OBB Detection Models for YOLO-NAS and Training HOT 1
- ONNX Export Output has Incorrect Class Labels but Correct Box and Confidence HOT 1
- Procuring license for commerical application of YOLO - NAS (with pre-trained weights)
- Cannot import name 'CrowdDetectionCollateFN' from 'super_gradients.training.utils.detection_utils
- pop_local_rank disrupts click argparser
- Incorrect Website Link in Repository Description HOT 5
- Why is there a large size difference between ckpt_best.pth and average_model.pth? HOT 1
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from super-gradients.