Update Readme.md

README.md

@@ -251,11 +251,9 @@ More information about training by the link: http://pjreddie.com/darknet/yolo/#t
 
 1. Train it first on 1 GPU for like 1000 iterations: `darknet.exe detector train data/voc.data cfg/yolov3-voc.cfg darknet53.conv.74`
 
-2. For 4xGPUs - increase 4x times `burn_in =` and `max_batches =` in your cfg-file. I.e. use `burn_in = 4000` instead of `1000`.
+2. Then stop and by using partially-trained model `/backup/yolov3-voc_1000.weights` run training with multigpu (up to 4 GPUs): `darknet.exe detector train data/voc.data cfg/yolov3-voc.cfg /backup/yolov3-voc_1000.weights -gpus 0,1,2,3`
 
-3. Then stop and by using partially-trained model `/backup/yolov3-voc_1000.weights` run training with multigpu (up to 4 GPUs): `darknet.exe detector train data/voc.data cfg/yolov3-voc.cfg /backup/yolov3-voc_1000.weights -gpus 0,1,2,3`
-
-Only for small datasets sometimes better to decrease learning rate, for 4 GPUs set `learning_rate = 0.00025` (i.e. learning_rate = 0.001 / GPUs).
+Only for small datasets sometimes better to decrease learning rate, for 4 GPUs set `learning_rate = 0.00025` (i.e. learning_rate = 0.001 / GPUs). In this case also increase 4x times `burn_in =` and `max_batches =` in your cfg-file. I.e. use `burn_in = 4000` instead of `1000`.
 
 https://groups.google.com/d/msg/darknet/NbJqonJBTSY/Te5PfIpuCAAJ