Skip to content
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

Re-training SSD-Mobilenet - loss going up and down #172

Open
Ufosek opened this issue Jan 26, 2022 · 0 comments
Open

Re-training SSD-Mobilenet - loss going up and down #172

Ufosek opened this issue Jan 26, 2022 · 0 comments

Comments

@Ufosek
Copy link

Ufosek commented Jan 26, 2022

Hi,

I am using transfer learning with Re-training SSD-Mobilenet like here.
My dataset contains 8000+ images (annotated sport players) (I have grayscale camera so all images are in grayscale (edit: turned into RGB by copying channel)).

EDIT - learning size:

test: 827
train: 5947
trainval: 7434
val: 1488

I used this script to generate test data with:

trainval_percent = 0.9
train_percent = 0.8

I see that until 100 epochs loss is going down but then it is spiking and after exactly 200 epochs reaches new minimum.

  1. I am wondering what does it mean (overfitting? or maybe that's just normal optimization)?
  2. After each spike there is new minimum (100 - 1.47, 300 - 1.41, 500 - 1.39, 700 - 1.38) - Which one should I use? The lowest (at 700)? or at 100 (because later it may actually be not improving or even breaking)?

image

I would be glad for some help!
Regards

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant