Qwen3-8B-ToolUse-SDPO-TR

This repository contains the Qwen3-8B Tool use SDPO-TR run trained with batch size 32.

The repository root contains the best validation checkpoint (global_step_40), selected by validation mean@16. checkpoints/last/ contains the final checkpoint.

Performance

Dataset	Method	Base model	Train batch size	Best val mean@16	Best checkpoint	Final val mean@16	Final checkpoint
Tool use	SDPO-TR	Qwen3-8B	32	66.36%	40	61.40%	100

Raw result files:

• results/validation_mean16.csv
• results/training_scores.csv
• artifacts/config.yaml
• artifacts/wandb-summary.json

Training Hyperparameters

Hyperparameter	Value
Base model	Qwen/Qwen3-8B
Method	SDPO-TR
Train batch size	32
Train max samples	3200
Total training steps	100
Save frequency	10
Test frequency	10
Teacher regularization	trust-region
Teacher update rate	0.1
Rollout samples per prompt	8
Validation samples per prompt	16
Learning rate	1e-5
vLLM GPU memory utilization	0.8

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

repo_id = "SeongryongJung/Qwen3-8B-ToolUse-SDPO-TR"
tokenizer = AutoTokenizer.from_pretrained(repo_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    repo_id,
    torch_dtype="auto",
    device_map="auto",
    trust_remote_code=True,
)