Lightning-AI / Lightning-AI/torchmetrics

Support sequence tagging evaluation metrics (NLP)

Open
#1,158 7 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

enhancement New metric waiting on author
Dominant language
Python
Stars
2.5k
Forks
526
Avg merge
6d 11h
Merged PRs (30d)
5

Description

🚀 Feature

Support for sequence tagging evaluation metrics à la seqeval. That is, support the evaluation of the performance of chunking tasks such as named-entity recognition, part-of-speech tagging, semantic role labeling and so on.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No files or tests are named in the issue. Start by comparing the requested sequence-tagging metrics with seqeval, then identify the relevant torchmetrics entry point. Done means supporting evaluation for chunking tasks such as named-entity recognition, part-of-speech tagging, and semantic role labeling.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.