training yolov4 with my own dataset shows final mAP values around 75% and an almost monotonic loss decay. I am very happy with the results.
However, I wanted to check if I can get even better results with yolov7. Using the same dataset, I see a minimum in the training loss at around 600 iterations, and then the loss settles at a higher value. Nevertheless, the mAP values are very good and approach 77%.
Some additional information:
My dataset has one class only. I followed the README to adapt the config files yolov4-custom.cfg and yolov7.cfg accordingly
I used the pretrained weights yolov4.conv.137 and yolov7.conv.132. The minimum in the loss curve is still there if I start training from scratch.
Dear all,
training yolov4 with my own dataset shows final mAP values around 75% and an almost monotonic loss decay. I am very happy with the results. However, I wanted to check if I can get even better results with yolov7. Using the same dataset, I see a minimum in the training loss at around 600 iterations, and then the loss settles at a higher value. Nevertheless, the mAP values are very good and approach 77%.
Some additional information:
yolov4-custom.cfg
andyolov7.cfg
accordinglyyolov4.conv.137
andyolov7.conv.132
. The minimum in the loss curve is still there if I start training from scratch.Does anyone have a clue why the training loss curves of yolov4 and yolov7 look so differently? The minimum in the loss curve really bothers me.
Thanks for your help!