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How to judge whether the model is trained properly based on OpencDet #3

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strugglingguoguo opened this issue Jul 8, 2022 · 2 comments

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@strugglingguoguo
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Dear author,hello.The pretrained model Voxel-MAE you proposed is very ingenious.I'm trying to replicate your work.
我做了两组实验:
实验1:SECOND训练20轮,V-M训练20轮后再训练SECOND20轮,后者效果显著好于前者。
实验2:SECOND训练200轮,V-M训练20轮后再训练SECOND200轮,前者效果好于后者。
考虑到训练过拟合,我又补充实验3:SECOND训练80轮,发现其在Car和骑行者的检测结果好于SECOND训练200轮,但是在行人检测上SECOND训练200轮效果更好。
我很疑惑,目前怀疑训练过拟合,但是我无法将loss曲线与eval准确率曲线在同一张图中可视化,无法判断合适的模型训练轮数。
请问作者如何判断模型训练恰到好处呢?
I would appreciate it if you could reply to me.

@chaytonmin
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Dear author,hello.The pretrained model Voxel-MAE you proposed is very ingenious.I'm trying to replicate your work. 我做了两组实验: 实验1:SECOND训练20轮,V-M训练20轮后再训练SECOND20轮,后者效果显著好于前者。 实验2:SECOND训练200轮,V-M训练20轮后再训练SECOND200轮,前者效果好于后者。 考虑到训练过拟合,我又补充实验3:SECOND训练80轮,发现其在Car和骑行者的检测结果好于SECOND训练200轮,但是在行人检测上SECOND训练200轮效果更好。 我很疑惑,目前怀疑训练过拟合,但是我无法将loss曲线与eval准确率曲线在同一张图中可视化,无法判断合适的模型训练轮数。 请问作者如何判断模型训练恰到好处呢? I would appreciate it if you could reply to me.

是在KITTI上做的实验吗?KITTI数据量小,结果不稳定,会有小的变化。我也不知道啥时候最好。也还在做实验。

@strugglingguoguo
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感谢作者!我是在kitti上做的实验,后续也在其他更大型数据集做一下实验

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