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.

Sign up for GitHub

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

Jump to bottom

cannot train loss all nan batch =8 #13

Closed
hexiangquan opened this issue Jun 3, 2018 · 2 comments
Closed

cannot train loss all nan batch =8 #13

hexiangquan opened this issue Jun 3, 2018 · 2 comments

Comments

@hexiangquan
Copy link

No description provided.

@wangzhaolei
Copy link

my loss is all nan too :( ,who can tell me why?Thanks.
[Epoch 0/30, Batch 323/1313] [Losses: x nan, y nan, w nan, h nan, conf 0.755184, cls nan, total nan]
[Epoch 0/30, Batch 324/1313] [Losses: x nan, y nan, w nan, h nan, conf 0.760500, cls nan, total nan]
[Epoch 0/30, Batch 325/1313] [Losses: x nan, y nan, w nan, h nan, conf 0.755139, cls nan, total nan]
[Epoch 0/30, Batch 326/1313] [Losses: x nan, y nan, w nan, h nan, conf 0.757809, cls nan, total nan]

eriklindernoren added a commit that referenced this issue Jun 7, 2018
@eriklindernoren
Fix to utils.bbox_iou. Stabilizes training. Resolves #25 #23 #18 #13 #12
122c24b
@eriklindernoren
Copy link
Owner

Hi, this problem is fixed in 6727086.

colmanAstrobotic pushed a commit to colmanAstrobotic/PyTorch-YOLOv3 that referenced this issue Jul 2, 2021
@eriklindernoren
Fix to utils.bbox_iou. Stabilizes training. Resolves eriklindernoren#25
5a98972 
eriklindernoren#23 eriklindernoren#18 eriklindernoren#13 eriklindernoren#12
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
3 participants
@eriklindernoren @hexiangquan @wangzhaolei