NVIDIA-NeMo / NVIDIA-NeMo/Megatron-Bridge

Feature Request: Support for multiple validation sets + separate loss validation reporting

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area:training feature waiting-on-customer
Dominant language
Python
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Forks
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Avg merge
1d 16h
Merged PRs (30d)
236

Description

Currently, Megatron-Bridge supports evaluating on a single validation set. For many workflows (e.g., multi-domain SFT, benchmarking across datasets), it is useful to:

  1. Define multiple validation datasets in the config.
  2. Report losses separately for each validation set (instead of aggregating).

This would allow fine-grained monitoring of model performance across domains or tasks without maintaining separate training runs.

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First steps

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  4. Open a pull request that references the issue number.

Research direction

The issue does not name files or tests. Start by locating the configuration for validation datasets and the evaluation and loss-reporting entry points, then trace how the current single validation set is defined and evaluated. Done means multiple validation datasets can be configured and losses are reported separately for each set, with coverage for both behaviors.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
45/100

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