yj12869741

TA-OPD-27B

README

License: apache-2.0

Model details

Table

Base model	Qwen3.5-27B
Training dataset	TA-OPD-10K
Weight format	BF16 Safetensors
License	Apache 2.0

Use the supplied tokenizer and chat template when preparing inputs, following the inference workflow for Qwen3.5-27B.

OmicsBench results

Evaluated on 1,160 questions with five inference seeds, temperature 1.0 and a maximum output length of 16,384 tokens. Values are mean ± sample standard deviation after removing the highest and lowest of the five scores independently for each metric. All metrics are multiplied by 100.

Predictive performance

EMP: epigenetic mark prediction; Prom: promoter prediction; TFBS: transcription factor binding site prediction; Mod: RNA modification prediction; ncRNA: non-coding RNA family classification; EC: enzyme function prediction.

Table with columns: Model, EMP MCC, Prom MCC, TFBS MCC, Mod AUC, ncRNA Acc, EC Fmax
Model	EMP MCC	Prom MCC	TFBS MCC	Mod AUC	ncRNA Acc	EC Fmax
Qwen3.5-27B	-5.69 ± 1.42	6.10 ± 3.64	16.29 ± 1.70	50.83 ± 2.19	5.12 ± 0.47	0.90 ± 0.02
TA-OPD-27B	28.35 ± 1.27	39.22 ± 0.25	23.18 ± 1.14	53.52 ± 2.19	19.22 ± 0.54

Rubric Recall (%)

Table with columns: Model, EMP, Prom, TFBS, Mod, ncRNA, EC, Avg Recall
Model	EMP	Prom	TFBS	Mod	ncRNA	EC	Avg Recall
Qwen3.5-27B	7.42 ± 0.16	19.40 ± 0.95	24.30 ± 0.81	2.12 ± 0.18	3.58 ± 0.36	0.36 ± 0.24	9.63 ± 0.36
TA-OPD-27B	35.69 ± 0.38	46.80 ± 0.41	36.61 ± 1.58

Judge: DeepSeek-V3.2. Avg Recall is the unweighted mean of the six task-level recalls, computed within each seed before trimming.

Project: OmicsBench.

📚 Citation

If you find this model useful, please consider citing:

bibtex

@misc{ying2026toolaugmentedonpolicydistillationllm,  title={Tool-Augmented On-Policy Distillation for LLM Domain Adaptation in Sequence-Based Omics Tasks},  author={Jie Ying and Zhefan Wang and Zihong Chen and Zhengqing Li and Jinzhe Li and Gang Li and Jian Liu and Fang Hu and Tao Luo and Zhonghang Yuan and Wanli Ouyang and Stan Z. Li and Fan Yang and Nanqing Dong},  year={2026},  eprint={2609.23435},  archivePrefix={arXiv},  primaryClass={cs.LG},  url={https://arxiv.org/abs/2609.23435}}

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Model Details

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yj12869741

Model Tree

Base

Qwen/Qwen3.5-27B

Fine-tuned

this model

Input Modalities

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Output Modalities

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Supported Functionality