-
Notifications
You must be signed in to change notification settings - Fork 30
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Low accuracy while searching #22
Comments
I am having the same situation when training with Search_Relax compare to Fast-AA |
Since we only train the model with 20 epochs, it is normal to get a low accuracy when search. |
Thank you very much for your fast response. I am training it with 200 epochs and trying to apply it in my research. Very appreciate for sharing this work with us. @latstars |
Can you give me the setting to get 2.7% error rate like on paper? Many thanks |
To reproduce the training stage, you can try the below script. For a search, use this https://github.com/VDIGPKU/DADA#search. Then you can train the model by using the found policy.
|
Oh, I get it now. So basically, we first have to run the search_relax model to find the policy first. Then we use the found augmentation policy to train networks in the Fast-Autoaugment folder. Thank you very much @latstars |
set -x
cifar100
GPU=1
DATASET=cifar100
MODEL=resnet50
EPOCH=20
BATCH=128
LR=0.1
WD=0.0002
AWD=0.0
ALR=0.005
CUTOUT=16
TEMPERATE=0.5
which python
python train_search_paper.py --unrolled --report_freq 1 --num_workers 0 --epoch ${EPOCH} --batch_size ${BATCH} --learning_rate ${LR} --dataset ${DATASET} --model_name ${MODEL} --gpu ${GPU} --arch_weight_decay ${AWD} --arch_learning_rate ${ALR} --weight_decay ${WD} --cutout --cutout_length ${CUTOUT} --temperature ${TEMPERATE}
Hello, I used the reset50 network to search for the augmentation policy. During searching, I noticed that the accuracy for training and validation is very low.
04/27 03:59:04 PM valid 187 2.398671e+00 38.285406 70.545213
04/27 03:59:04 PM valid 188 2.397762e+00 38.289517 70.568783
04/27 03:59:04 PM valid 189 2.397031e+00 38.297697 70.575658
04/27 03:59:04 PM valid 190 2.395328e+00 38.326243 70.590641
04/27 03:59:04 PM valid 191 2.396694e+00 38.309733 70.576986
04/27 03:59:04 PM valid 192 2.396227e+00 38.337921 70.575615
04/27 03:59:05 PM valid 193 2.396536e+00 38.321521 70.574259
04/27 03:59:05 PM valid 194 2.396318e+00 38.325321 70.584936
04/27 03:59:05 PM valid 195 2.395298e+00 38.336000 70.588000
04/27 03:59:05 PM valid_acc 38.336000
Is this Ok?
The text was updated successfully, but these errors were encountered: