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YOLOv7 minimum in training loss
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:
- My dataset has one class only. I followed the README to adapt the config files
yolov4-custom.cfg
andyolov7.cfg
accordingly - I used the pretrained weights
yolov4.conv.137
andyolov7.conv.132
. The minimum in the loss curve is still there if I start training from scratch. - I used the following commands for training:
./darknet detector train data/obj.data yolov4-custom.cfg yolov4.conv.137 -dont_show -map -mAP_epochs 1
./darknet detector train data/obj.data yolov7.cfg yolov7.conv.132 -dont_show -map -mAP_epochs 1
- I have played around with learning rate, decay, momentum, and burn-in, but this only shifts the minimum horizontally and/or makes it wider.
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!