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

low mAP, high classification loss in eval - object detection resnet 50 #11207

Open
qazalkz opened this issue May 11, 2024 · 0 comments
Open

low mAP, high classification loss in eval - object detection resnet 50 #11207

qazalkz opened this issue May 11, 2024 · 0 comments
Assignees
Labels
models:official models that come under official repository type:support

Comments

@qazalkz
Copy link

qazalkz commented May 11, 2024

Hi guys. I have about 4000 images and Im using resnrt50 640*640 with 70000 steps. but after all Im getting low mAP. could you please give me some advice.

p.n: also I divide original learning rate to my batch size

pipeline_config.model.ssd.num_classes = 1
pipeline_config.train_config.batch_size = 64//8
pipeline_config.train_config.fine_tune_checkpoint = "checkpointmodels/retina101/ssd_/checkpoint/ckpt-0"
pipeline_config.train_config.fine_tune_checkpoint_type = "detection"
pipeline_config.train_input_reader.label_map_path= LABELMAP
pipeline_config.train_config.optimizer.momentum_optimizer.learning_rate.cosine_decay_learning_rate.warmup_learning_rate=0.013333000242710114/8
pipeline_config.train_config.optimizer.momentum_optimizer.learning_rate.cosine_decay_learning_rate.learning_rate_base=0.03999999910593033/8

Screenshot from 2024-05-11 12-11-54
on 20000 stept eval
Screenshot from 2024-05-08 13-29-28
on 70000 steps
Screenshot from 2024-05-11 12-14-44
Uploading Screenshot from 2024-05-11 12-17-28.png…
also you can see that classification loss is high on eval output

@qazalkz qazalkz changed the title low mAP, high classification loss in eval low mAP, high classification loss in eval - object detection resnet 50 May 11, 2024
@laxmareddyp laxmareddyp added the models:official models that come under official repository label May 12, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
models:official models that come under official repository type:support
Projects
None yet
Development

No branches or pull requests

2 participants