thu-ml / thu-ml/TurboDiffusion
How is the performance if we train with sCM loss only?
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 3.7k
- Forks
- 277
- Avg merge
- 2h 57m
- Merged PRs (30d)
- 2
Description
Hi @zhengkw18,
In the paper, you compared the rCM with DMD loss, I am wondering what if you train the model with sCM loss only? Do I need to turn the hyperparameters a lot if I want to use sCM loss only?
Btw, would you mind sharing your loss curves/grad norms over training time?
Thanks in advance!
Meng
Contributor guide
No contributing guide indexed for this repository
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.
Research direction
The issue does not identify a file, test, or entry point to inspect. Begin by locating the training configuration and loss implementation for sCM, then compare sCM-only training with the paper's rCM and DMD setup. Done would include performance results, any required hyperparameter changes, and loss curves or gradient norms.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100