top-1 accuracy is very low

[408550969]

Hi
I test the SE-BN-Inception and use the pre-trained caffemodel, but the accuracy is 0.00018 on Imagenet2012.
May I ask why this could happen, is it a problem with my dataset?
Thanks.

[hujie-frank]

Please refer to #5.

[408550969]

Thanks!

[408550969]

Hi,I am training the SE-BN-Inception, but I find the acuuracy is only 68% now.(accurate learning rate is 0.0001)
My learning rate is set wrong,I set it to 0.1 from the beginning.
And I only use mirror true.Others are same.
I am set the use_global_status to false in train.prototxt,and set it to true in test.prototxt.
Do you know why the accuracy is so low?How to implement the augmentation list in the form?Thank you!

[hujie-frank]

@408550969 The data augmentation don't bring significant improvement. It must be something wrong in your experiments. Additionally, you can refer here to find the implementation of the augmentation in list.

[408550969]

This is the top and bottom of the train.prototxt.Can you help me see what's wrong?Thanks!
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 224
mean_value: 104.0
mean_value: 117.0
mean_value: 123.0
}
data_param {
source: "/media/cll/Seagate/ilsvrc12_train_lmdb"
batch_size: 32
backend: LMDB
}
}

layer {
name: "classifier"
type: "InnerProduct"
bottom: "pool5/7x7_s1"
top: "classifier"
inner_product_param {
num_output: 1000
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "classifier"
bottom: "label"
top: "loss"
}