Light-MER Checkpoints
This repository hosts model checkpoints for Light-MER, the official implementation of:
Do We Really Need Multimodal Emotion Language Models Larger Than 1B Parameters?
- Paper: Hugging Face Papers / arXiv
- Code: GAIR-Lab/Light-MER
Checkpoints
| File | Description | Status |
|---|---|---|
light-mer-teacher-qwen3-8b.pth | Qwen3-8B teacher checkpoint for Stage 1 SWD-H distillation | Released |
stage1-swdh-qwen3-0.6b/checkpoint_000060_loss_1.291.pth | Recommended Qwen3-0.6B student checkpoint after Stage 1 SWD-H distillation | Released |
stage1-swdh-qwen3-0.6b/checkpoint_*.pth | Stage 1 SWD-H checkpoint trajectory from epoch 5 to epoch 60 | Released |
stage1-swdh-qwen3-0.6b/config.yaml | Stage 1 SWD-H training config used for the released checkpoints | Released |
stage2-mgrpo-qwen3-0.6b/checkpoint_*.pth | Stage 2 M-GRPO checkpoint sweep for steps 50, 500, ..., 5000 | Released |
stage2-mgrpo-qwen3-0.6b/config.yaml | Stage 2 M-GRPO training config used for the released checkpoint sweep | Released |
Usage
Download the teacher checkpoint and place it under the GitHub repo checkpoint directory:
checkpoints/light-mer-teacher-qwen3-8b.pth
Then run Stage 1 SWD-H distillation with:
CONDA_ENV_NAME=swdh-stage1 \
TEACHER_CKPT=checkpoints/light-mer-teacher-qwen3-8b.pth \
bash scripts/train_stage1_swdh.sh
For Stage 1 inference or evaluation, download one of the released student checkpoints, for example:
checkpoints/light-mer-stage1-swdh-qwen3-0.6b.pth
The recommended Stage 1 checkpoint is:
stage1-swdh-qwen3-0.6b/checkpoint_000060_loss_1.291.pth
For Stage 2 M-GRPO inference and evaluation, download the released sweep directory:
stage2-mgrpo-qwen3-0.6b/
It contains checkpoints for steps 50, 500, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, and 5000. Use this directory as STAGE2_CKPT_ROOT in the GitHub codebase.
License
This checkpoint repository is released under the Apache License 2.0. Please also follow the licenses and usage terms of the external datasets and pretrained models used with Light-MER.
Citation
If you find Light-MER useful, please cite:
@misc{zheng2026lightmer,
title = {Do We Really Need Multimodal Emotion Language Models Larger Than 1B Parameters?},
author = {Zheng, Kaiwen and Fu, Junchen and Deng, Wenhao and Han, Hu and Jose, Joemon M. and Ge, Xuri},
year = {2026},
eprint = {2607.12787},
archivePrefix = {arXiv},
primaryClass = {cs.AI},
url = {https://arxiv.org/abs/2607.12787},
note = {Accepted by ACM MM 2026}
}