tensorflow / tensorflow/models
question of hard_example_mining_step in loss
@aquariusjay is already working on this.
Since Jul 24, 2020.
- Dominant language
- Python
- Stars
- 77.7k
- Forks
- 44.8k
- PR merge metrics
- No merged PRs in 30d
Description
Hi, I try to train the a new model for semantic segmentation by using our own dataset.
At first, I use the add_softmax_cross_entropy_loss_for_each_scale, which didn't contain hard_example_mining_step, top_k_percent_pixels and loss_weight. The result is good, but I want to improve the performance of this model, thus using loss with hard_example_mining_step and top_k_percent_pixels. And I set these two parameters as 300k(all training steps is 600k) and 0.25, but the result is much worse(declined 20%) than the former loss. I'm courious about this bad result, and cannot figure out what's the problem of the number I set.
Could anyone help me?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Assessment
This issue has not been assessed yet.