ModelHub XC 9aabae373d 初始化项目,由ModelHub XC社区提供模型
Model: SeongryongJung/qwen3-4b-tooluse-srpo-ema005
Source: Original Platform
2026-09-20 16:14:29 +08:00

license, base_model, library_name, tags
license base_model library_name tags
apache-2.0 Qwen/Qwen3-4B transformers
qwen3
reinforcement-learning
sdpo
srpo
ema

qwen3-4b-tooluse-srpo-ema005

This repository contains the last checkpoint (global_step_100) for qwen3gen-tooluse-SRPO-Qwen-Qwen3-4B-mbs32-ema0.05-dwtrue-train64-rollout8-lr5e-6-vllm0.8, converted to Hugging Face Transformers format.

Evaluation

The reported headline score is the best validation mean@16 observed during training. It is not necessarily the score of the uploaded last checkpoint.

Dataset Method Model Uploaded checkpoint Best val mean@16 Best step Final val mean@16
tooluse SRPO Qwen3-4B global_step_100 62.59% 40 57.26%

Training and validation scores

Raw result files:

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

Training Setup

  • Base model: Qwen/Qwen3-4B
  • Dataset: tooluse
  • Method: SRPO
  • EMA teacher update rate: 0.05
  • Uploaded weights: last checkpoint, global_step_100
  • Validation metric used for headline score: val-aux/*/mean@16
  • Validation sampling: n=16

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

repo_id = "SeongryongJung/qwen3-4b-tooluse-srpo-ema005"
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,
)

Notes

Most best-validation intermediate checkpoints were not retained as full actor checkpoints because training kept only the latest actor checkpoint. Therefore, this repository publishes the last checkpoint and records the best validation score separately.

Description
Model synced from source: SeongryongJung/qwen3-4b-tooluse-srpo-ema005
Readme 13 MiB
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