G-U-N / G-U-N/a-PyTorch-Tutorial-to-Class-Incremental-Learning
results on cifar-100
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 109
- Forks
- 10
- PR merge metrics
- No merged PRs in 30d
Description
I tested it with cifar100. However, it can not achieve the desired effect, especially in the incremental stage.
train 140 epoch：
task id = 5 @Acc1 = 25.73000, acc1s = [77.32000010986329, 27.400000030517578, 32.328571446010045, 29.5625, 30.6, 25.73]
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
No file, test, or entry point is named. Start by locating the repository's CIFAR-100 training and incremental-stage entry points, then reproduce the reported 140-epoch run and compare its accuracy sequence with the expected behavior. Done should include a specific cause and a verified correction or a documented explanation of the results.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100