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数据集有196个样本,划分了39个验证集,使用语义分割模型PP-LiteSeg-T进行二次训练,设置epochs_iters: 19600,共训练252epoch,但是训练得到的每一个保存的模型,mIOU没有任何变化,保持在0.5063。
配置文件如下: 运行日志如下:
参照官方例子转换后的掩码图片和原始图片,以及对应的text文件
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部分数据集如下:
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训练后的模型与未训练跑出来的结果一样
已解决,是num_classes设置为1了,和用描点分割模型不一样,这里的类型是指前景和背景
好的,感谢反馈
liuhongen1234567
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描述问题
数据集有196个样本,划分了39个验证集,使用语义分割模型PP-LiteSeg-T进行二次训练,设置epochs_iters: 19600,共训练252epoch,但是训练得到的每一个保存的模型,mIOU没有任何变化,保持在0.5063。
复现
配置文件如下:
运行日志如下:
是
否
参照官方例子转换后的掩码图片和原始图片,以及对应的text文件
环境
PaddleX 3.0 Beta2
windows
3.10
cuda 12.6
The text was updated successfully, but these errors were encountered: