Measure performance and accuracy on customized dataset
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- c
- Domain
- machine-learning, performance
Research direction
Start by reproducing the medium-performance benchmark with EE_MODEL_VERSION set to the custom dataset and the dataset under /ulp-mlperf/datasets/. Trace why benchmark mode reports “Need at least 5 inputs” and determine the requirements for measuring performance and accuracy on datasets beyond ad, vww, kws, and ic. Done means custom-dataset evaluation works or its supported limitations are documented.
Written by the indexing model from the issue text.
Description
Hi,
Is there any way to measure performance and accuracy on customized dataset (other than ad, vww, kws, ic) ?
I have tried setting EE_MODEL_VERSION to my own dataset and put the dataset under /ulp-mlperf/datasets/ directory, but I got the following error when running medium performance:
Need at least 5 inputs to run benchmark mode
- Dominant language
- C
- Stars
- 479
- Forks
- 116
- PR merge metrics
- No merged PRs in 30d
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.
More from mlcommons/tiny
-
Difficulty 1/5 Under an hour Newbie friendliness 68/100
-
Difficulty 5/5 Over a week Newbie friendliness 20/100
-
Difficulty 4/5 3-5 days Newbie friendliness 25/100
-
Difficulty 3/5 1-2 days Newbie friendliness 35/100
Similar issues
-
bug
Difficulty 1/5 Under an hour Newbie friendliness 60/100
-
Nmap
Difficulty 1/5 Under an hour Newbie friendliness 85/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 65/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 65/100
-
flang:fir-hlfir
Difficulty 2/5 1-3 hours Newbie friendliness 70/100
llvm/llvm-project#225935 ·