Model gives zero error and zero accuracy after training

[ankit41093]

If you have an issue with training - no-detections / Nan avg-loss / low accuracy:

• read FAQ: https://github.com/AlexeyAB/darknet/wiki/FAQ---frequently-asked-questions
• what command do you use?
• what dataset do you use?
• what Loss and mAP did you get?
• show chart.png with Loss and mAP
• check your dataset - run training with flag -show_imgs i.e. ./darknet detector train ... -show_imgs and look at the aug_...jpg images, do you see correct truth bounded boxes?
• rename your cfg-file to txt-file and drag-n-drop (attach) to your message here
• show content of generated files bad.list and bad_label.list if they exist
• Read How to train (to detect your custom objects) and How to improve object detection in the Readme: https://github.com/AlexeyAB/darknet/blob/master/README.md
• show such screenshot with info

  ./darknet detector test cfg/coco.data cfg/yolov4.cfg yolov4.weights data/dog.jpg
  CUDA-version: 10000 (10000), cuDNN: 7.4.2, CUDNN_HALF=1, GPU count: 1
  CUDNN_HALF=1
  OpenCV version: 4.2.0
  0 : compute_capability = 750, cudnn_half = 1, GPU: GeForce RTX 2070
  net.optimized_memory = 0
  mini_batch = 1, batch = 8, time_steps = 1, train = 0
  layer   filters  size/strd(dil)      input                output

[LuoJianBin22]

Did you find the problem？@ankit41093