[2019.3.1 16:44] uploading mask file
- python==3.6
- torch==0.4.1
- torchvision==0.2.1
https://www.kaggle.com/c/humpback-whale-identification/discussion/82366
trainset -> ./input/train
testset -> ./input/test
cd input
unzip mask.zip
download model_50A_slim_ensemble.csv(https://drive.google.com/file/d/1hfOu3_JR0vWJkNlRhKwhqJDaF3ID2vRs/view?usp=sharing) into ./input
download playground data, then put them into input/train
https://www.kaggle.com/c/whale-categorization-playground/data
line 301 in train.py
step 1.
freeze = False
model_name = 'senet154'
min_num_class = 10
checkPoint_start = 0
lr = 3e-4
#until train map5 >= 0.98
step 2.
freeze = True
model_name = 'senet154'
min_num_class = 0
checkPoint_start = best checkPoint of step 1
lr = 3e-4
step 3.
freeze = True
model_name = 'senet154'
min_num_class = 0
checkPoint_start = best checkPoint of step 2
lr = 3e-5
line 99 in test.py
checkPoint_start = best checkPoint of step 3