Hacktoberfest 2026: the issues maintainers tagged for October, open and beginner-friendly. Browse Hacktoberfest issues

Ablation on data size

Open
#66 2 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
20/100
Issue type
Feature
Clarity
Needs clarification
Activity status
Stale
Tech stack
python

Research direction

No files, tests, or entry points are named in the issue. Start by locating the TransCoder training-data configuration and evaluation workflow, then determine how reduced data sizes can be compared across the three languages; done means reporting the ablation results and their effect on performance.

Written by the indexing model from the issue text.

Description

question

Hi, appreciate the amazing work in unsupervised code translation!
I wonder if you have done ablation study on the training data size of TransCoder? Since the unsupervised model needs way much more training data (over 500M functions for 3 languages ) than the existing code PLMs, like CodeT5 (8.35M for 7 languages).
How's the performance of Transcoder if less data provided?

Dominant language
Python
Stars
777
Forks
144
PR merge metrics
No merged PRs in 30d

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.

More from facebookresearch/CodeGen

All issues in facebookresearch/CodeGen

Similar issues

More Python issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.