SeTox-Qwen2.5-3B
SeTox-Qwen2.5-3B is a full-SFT model based on Qwen/Qwen2.5-3B-Instruct for
Chinese neologism toxicity detection with optional web-search tool use.
Training
- Base model:
Qwen/Qwen2.5-3B-Instruct - Method: full supervised fine-tuning
- Training data: SeTox tool-use and direct SFT data
- Epochs: 3
- Learning rate:
1e-5 - Scheduler: linear with warmup ratio
0.05 - Context cutoff:
4096
Evaluation
Main SeTox neologism test set, 624 valid samples:
| Checkpoint | Accuracy | Unsafe F1 | Unsafe Recall | Safe F1 |
|---|---|---|---|---|
| checkpoint-120 | 0.9103 | 0.9402 | 0.8980 | 0.8205 |
| checkpoint-150 | 0.8974 | 0.9312 | 0.8837 | 0.7987 |
Live search and generation settings can introduce small drift during reproduction.
Usage
See the SeTox code repository for search-augmented inference:
python scripts/run_inference.py \
--model_path thu-coai/SeTox-Qwen2.5-3B \
--search_backend serper \
--input_path data/eval/neologism_test.json \
--output_path outputs/neologism_predictions.json
For offline smoke tests, use --mock or --search_backend none.
Limitations
This model is intended for research on Chinese neologism toxicity detection. It can make mistakes on ambiguous, fast-changing, adversarial, or under-specified terms. Search results may contain noisy or unsafe snippets, and downstream users should apply appropriate safety review before deployment.
License
This model is fine-tuned from Qwen/Qwen2.5-3B-Instruct and follows the Qwen
Research License. See the linked base model license before use, especially for
non-research or commercial scenarios.
Citation
Please cite the SeTox ACL paper:
- Paper: https://aclanthology.org/2026.acl-long.1602/
- DOI: https://doi.org/10.18653/v1/2026.acl-long.1602
@inproceedings{cui-etal-2026-setox,
title = "{S}e{T}ox: Search-enhanced Reasoning for {LLM}-based Toxicity Detection over {C}hinese Internet Buzzwords",
author = "Cui, Yiming and Zhang, Qinglin and Su, Xu and Min, Changyu and Hu, Shilin and Huang, Minlie",
editor = "Che, Wanxiang and Nabende, Joyce and Shutova, Ekaterina and Pilehvar, Mohammad Taher",
booktitle = "Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2026",
address = "San Diego, California, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.acl-long.1602/",
doi = "10.18653/v1/2026.acl-long.1602",
pages = "33018--33034"
}