OpenEuroLLM / OpenEuroLLM/training-data-packer
"Split out" validation dataset
Open
Nobody has claimed this yet.
idea
- Dominant language
- Python
- Stars
- 1
- Forks
- 2
- Avg merge
- 18h 22m
- Merged PRs (30d)
- 12
Description
It would be good if we could split out a tiny part (e.g. 0.1%) of all of our source datasets early on in processing to serve as a validation dataset that we don't train on.
Relevant for post-flag efforts.
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.
Research direction
Locate the early processing path that handles all source datasets and determine where a validation subset can be separated before training data is produced. The work is done when a small, consistent portion of each source dataset is available for validation and is excluded from training, including the post-flag workflow mentioned in the issue.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100