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Loss is nan #35
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individual
Individual problem and need
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将模型类别改为2(实际GT只有一类),l_imgcls正常了,但是l_det_loc、L_det损失依旧是 nan |
你可以看看你的数据集本身的边界框标注信息是否有问题,或者尝试调整学习率,并重新做一下实验,看看实验结果。 You can see if there is any problem with the bounding box annotation of your dataset, or try to adjust the learning rate, and re-run the experiment to check the experiment results. |
已解决,排查是因为标签问题 |
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作者,您好!
当我使用自己数据集测试您代码时,l_det_loc、L_det损失是 nan,l_imgcls一直是0
自己数据集只有行人类,已经修改过datasets/voc.py中的CLASSES=('person',)
训练时使用的1个显卡
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