• Hardware: NVIDIA GeForce RTX 4090
• Network Type: Yolo_v4
• TLT Version: TAO 5.5.0
• Training spec file:
yolo_v4_train_cspdarknet19_kitti_seq.txt (2.6 KB)
yolo_v4_retrain_cspdarknet19_kitti_seq.txt (2.6 KB)
I am using YOLOv4 with my own dataset, and I encountered some issues when pruning my model. Before training, my model’s mAP is around 0.50. However, when I try to prune with different thresholds (the suggested ones and many others), I always get either an extremely low prune ratio (less than 0.008) or an extremely high prune ratio (greater than 0.98).
I am unable to achieve a prune ratio between 10-20%, which is typically recommended. Additionally, even when I retrain with a prune ratio of 1 or 0.008, my mAP drops to 0 after retraining.
Any insights on what might be causing this or how to resolve it? Thanks in advance.
2 posts - 2 participants
