Comments (3)
jinkos
commented on July 28, 2024
I am also struggling to train from scratch on cityscapes
I am using the model with filter_scale=2 and I am using a flat learning rate of 0.01 using MomentumOptimizer. I am using proper data and have done plenty of testing to make sure that my evaluation is A OK.
I am wondering of the L2 loss is too heavily weighted. I know the paper mentions weight decay of 0.0001. After 10 hours of training, my L2 has come down from 1.0 to 0.5 and is still falling.
But has anyone actually successfully trained the cityscapes dataset from scratch using filter_scale=2? I would like to know how they have done it.
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harora
commented on July 28, 2024
Hi
Did you get success in training on cityscapes dataset? I'm not able to reproduce the result. The loss goes to around 0.5 but predictions are coming wrong(2-3% mIoU)
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tzhong518
commented on July 28, 2024
I'm having the same problem... Loss went down but the mIoU is only 2%.
Have you succeeded in training from scratch?
Thanks!
Hi
Did you get success in training on cityscapes dataset? I'm not able to reproduce the result. The loss goes to around 0.5 but predictions are coming wrong(2-3% mIoU)
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Related Issues (20)
- Errors in restoring the session evalucation.py and network.py
- ValueError: Shape must be rank 4 but is rank 3 for 'data_sub2' (op: 'ResizeBilinear') with input shapes: [720,720,3], [2]. HOT 3
- Why is it suddenly 'killed' run train.py? HOT 1
- How predict the result to use my training model ckpt.meta?
- Dimension not equal HOT 1
- ValueError:Variable conv does not exist
- ValueError when using own dataset HOT 2
- Training own dataset
- Inference time is too high(about 3.5x as supposed to be ~0.04s)
- multi GPU training?
- tensorflow's version HOT 1
- How to use the pre-trained modle of ade20k provided by author,I use the code in demo.ipynb,but it can't open the file,the cityscapes works well.
- Training over-fitting after every epochs
- same classification result with every pixel HOT 1
- can get correct result
- bad results of voc2012
- The update stops and the loss does not drop HOT 4
- Assign requires shapes of both tensors to match. lhs shape= [13] rhs shape= [150]
- 上一个项目
- 关于ade20k的分割结果，颜色和标签有对应关系吗？
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