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

Adding improved MobileNetV2 weights #5560

Merged
merged 4 commits into from
Mar 7, 2022

Conversation

datumbox
Copy link
Contributor

@datumbox datumbox commented Mar 7, 2022

Fixes #3995

Updating the weights of MobileNetV2 using the new recipe:

torchrun --nproc_per_node=8 train.py --model mobilenet_v2 --batch-size 128 --lr 0.5 \
--lr-scheduler cosineannealinglr --lr-warmup-epochs 5 --lr-warmup-method linear --auto-augment ta_wide \
--epochs 600 --random-erase 0.1 --label-smoothing 0.1 --mixup-alpha 0.2 --cutmix-alpha 1.0 \
--weight-decay 0.00002 --norm-weight-decay 0.0 --train-crop-size 176 --model-ema --val-resize-size 232 \
--ra-sampler --ra-reps 4

Validated with:

torchrun --nproc_per_node=1 train.py --test-only --prototype --weights MobileNet_V2_Weights.IMAGENET1K_V2 --model mobilenet_v2 -b 1
Acc@1 72.154 Acc@5 90.822

@facebook-github-bot
Copy link

facebook-github-bot commented Mar 7, 2022

💊 CI failures summary and remediations

As of commit bb14c86 (more details on the Dr. CI page):


💚 💚 Looks good so far! There are no failures yet. 💚 💚


This comment was automatically generated by Dr. CI (expand for details).

Please report bugs/suggestions to the (internal) Dr. CI Users group.

Click here to manually regenerate this comment.

Copy link
Contributor

@jdsgomes jdsgomes left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM!

@datumbox datumbox merged commit 2b5ab1b into pytorch:main Mar 7, 2022
@datumbox datumbox deleted the modes/mobilenetv2_weights branch March 7, 2022 14:49
facebook-github-bot pushed a commit that referenced this pull request Mar 15, 2022
Summary:
* Adding improved MobileNetV2 weights

* Fix eval sizes.

* Update accuracy with batch-size 1 run

Reviewed By: vmoens

Differential Revision: D34879000

fbshipit-source-id: 759d7981e71c676fd2e0a04932323f245a69947b
@datumbox datumbox mentioned this pull request Apr 5, 2022
24 tasks
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

Successfully merging this pull request may close these issues.

Improve the accuracy of Classification models by using SOTA recipes and primitives
3 participants