Comments (10)
@hustzeyu 这个没有测,自己只是随便跑的一个。抱歉
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Can I use this caffemodel on Android platform or linux platform? Is this your already trained "mobilefacenet" model?
Thank you!
best regards!
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@hustzeyu 这个没有测,自己只是随便跑的一个。抱歉
作者您好,
我用的vggface2,下载的训练集8631,的数据进行训练,损失函数和您的模型也是一样的,训练的时候从12左右的损失值开始减少,但是,并没有收敛,损失值在10左右震荡,不继续减小,作者您遇到过这个情况吗???可能有哪些原因昵
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@piaopiaoxiaoye
Andrioid : using ncnn and convert caffe model to ncnn model
linux : Just compile caffe
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@shiyuanyin learning_rate and batch_size ?
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@zhanglaplace
lr 0.1 开始, batchsize=64
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@shiyuanyin learning_rate and batch_size
需要,预训练sortmax 的model吗?我直接训练,除了数据不是9136(我的8136),不能收敛,一直震荡
@zhanglaplace
Andrioid : using ncnn and convert caffe model to ncnn model
linux : Just compile caffe
需要,预训练sortmax 的model吗?我直接训练,除了数据不是9136(我的8136),不能收敛,一直震荡
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@shiyuanyin Try to increase the learning rate. In addition, make sure your training data and labels are aligned。
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@shiyuanyin Did you solve the problem? I see the same behavior with ResNet-18 with ArcLoss and VGG2 training set, I guess that alignment is important
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@shiyuanyin I guess I fixed the problem, in case of not aligned vgg2 dataset training is very sensitive to M parameter, try to change
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Related Issues (14)
- Could you please provide the training log file? HOT 1
- about result HOT 4
- 人脸检测和对齐
- 请问有没有测试代码呀
- 模型与论文不一致的地方
- 训练问题 HOT 5
- About the normalize_layer in the network
- 请问你的normlize层是怎么实现的? HOT 3
- Your num_output of fc6_l2 is 9131? HOT 1
- accuracy on the test set HOT 1
- LFW验证精度
- about the lfw accuracy HOT 1
- 关于训练之后的精度 HOT 1
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