[GitHub] javi-clear-image-ai commented on issue #5228: Good training and validation accuracy, poor testing accuracy

[GitBox <gi...@apache.org>]

javi-clear-image-ai commented on issue #5228: Good training and validation accuracy, poor testing accuracy
URL: https://github.com/apache/incubator-mxnet/issues/5228#issuecomment-436560631
 
 
   I have the same issue...
   **TRAIN-VALIDATION:**
   json_stats: {**"accuracy_cls": 0.977055**, "eta": "0:00:00", "iter": 89999, **"loss": 0.097330**, "loss_bbox": 0.015025, "loss_cls": 0.075462, "loss_rpn_bbox_fpn2": 0.000000, "loss_rpn_bbox_fpn3": 0.000000, "loss_rpn_bbox_fpn4": 0.000153, "loss_rpn_bbox_fpn5": 0.000106, "loss_rpn_bbox_fpn6": 0.000000, "loss_rpn_cls_fpn2": 0.000099, "loss_rpn_cls_fpn3": 0.000064, "loss_rpn_cls_fpn4": 0.000068, "loss_rpn_cls_fpn5": 0.000033, "loss_rpn_cls_fpn6": 0.000000, "lr": 0.000020, "mb_qsize": 64, "mem": 8932, "time": 0.372048}
   
   **TESTING:**
   INFO task_evaluation.py: 186: copypaste: AP,AP50,AP75,APs,APm,APl
   INFO task_evaluation.py: 187: copypaste: -1.0000,-1.0000,-1.0000,-1.0000,-1.0000,-1.0000
   
   And when I visualize the testing image results, only 4 out of 1000 show up, and some of the classes go wrong ... I am gonna try to change the visualization threshold from 0.9 to 0.4, to see what happens....
   
   Any help would be very much appreciated 

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