Files
ModelHub XC a52fcb1e1d 初始化项目,由ModelHub XC社区提供模型
Model: SeongryongJung/Qwen3-4B-Tooluse-RLSD-TR
Source: Original Platform
2026-08-20 04:49:19 +08:00

5.4 KiB

license, library_name, pipeline_tag, tags, base_model
license library_name pipeline_tag tags base_model
apache-2.0 transformers text-generation
qwen3
reinforcement-learning
rlsd-tr
text-generation
trust-region
Qwen/Qwen3-4B

Qwen3-4B-Tooluse-RLSD-TR

This repository contains the Qwen3-4B tooluse RLSD_TR batch-size-32 run.

The repository root contains the best validation checkpoint, 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 / tooluse RLSD_TR Qwen3-4B 32 61.03% 60 59.38% 100

Training and validation scores

Validation Mean@16

step val_mean16 percent
10 0.576286764706 57.63%
20 0.586397058824 58.64%
30 0.575367647059 57.54%
40 0.570772058824 57.08%
50 0.553308823529 55.33%
60 0.610294117647 61.03%
70 0.594669117647 59.47%
80 0.592830882353 59.28%
90 0.531250000000 53.12%
100 0.593750000000 59.38%

Detailed Training Hyperparameters

Section Parameter Value Source
Run identity Base model Qwen/Qwen3-4B queue/script override
Run identity Dataset Tool-use / tooluse run_qwen3_generalization.sh
Run identity Method RLSD_TR run_qwen3_generalization.sh
Run identity Config rlsd run_qwen3_generalization.sh
Run identity Experiment qwen3gen-tooluse-RLSD_TR-Qwen-Qwen3-4B-mbs8-decay0-tr0.1-train32-rollout8-lr1e-6-vllm0.8 run_qwen3_generalization.sh
Run identity W&B run run-20260702_154716-jrdzd11b wandb
Data Train file datasets/tooluse/train.parquet script override
Data Validation file datasets/tooluse/test.parquet script override
Data Train batch size 32 queue/script override
Data Train max samples 3200 queue/script override
Schedule Total training steps 100 queue/script override
Schedule Validation before train False queue/script override
Schedule Save frequency 10 queue/script override
Schedule Validation frequency 10 queue/script override
Sequence Max prompt length 2048 queue/script override
Sequence Max response length 8192 queue/script override
Sequence Max model length 10240 queue/script override
Rollout Train rollout n 8 queue/script override
Rollout Validation rollout n 16 queue/script override
Rollout vLLM GPU memory utilization 0.8 queue/script override
Optimization Learning rate 1e-6 RLSD_TR method override
Optimization Weight decay 0.01 script override
PPO/GRPO PPO mini batch size 8 queue/script override
PPO/GRPO Normalize GRPO advantages by std False baseline_grpo.yaml / script override
Rollout correction Importance sampling mode token script override
Rollout correction IS threshold 2.0 script override
Checkpoint/Logging Checkpoint root checkpoints/datasets/tooluse/qwen3gen-tooluse-RLSD_TR-Qwen-Qwen3-4B-mbs8-decay0-tr0.1-train32-rollout8-lr1e-6-vllm0.8 script override
Checkpoint/Logging Latest checkpointed iteration 100 latest_checkpointed_iteration.txt
Checkpoint/Logging External actor archive checkpoints/datasets/tooluse/qwen3gen-tooluse-RLSD_TR-Qwen-Qwen3-4B-mbs8-decay0-tr0.1-train32-rollout8-lr1e-6-vllm0.8/_actor_archive preserve_actor_checkpoints.py
Checkpoint/Logging Logger console, wandb ppo_trainer.yaml
RLSD_TR Policy loss mode rlsd method override
RLSD_TR Teacher regularization trust-region method override
RLSD_TR Trust-region mix / teacher update rate 0.1 queue/script override
RLSD_TR Token reweight lambda 0.5 queue/script override
RLSD_TR Token reweight eps_w 0.2 queue/script override
RLSD_TR Token reweight decay steps 0 queue/script override
RLSD_TR Fused kernels False method override

Raw result and artifact files:

  • results/validation_mean16.csv
  • results/training_scores.csv
  • results/hyperparameters.csv
  • results/training_score.png
  • results/training_score.svg
  • artifacts/config.yaml
  • artifacts/wandb-summary.json
  • artifacts/wandb-metadata.json
  • artifacts/output.log
  • artifacts/queue.log

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

repo_id = "SeongryongJung/Qwen3-4B-Tooluse-RLSD-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,
)

Source

  • Checkpoint: checkpoints/datasets/tooluse/qwen3gen-tooluse-RLSD_TR-Qwen-Qwen3-4B-mbs8-decay0-tr0.1-train32-rollout8-lr1e-6-vllm0.8
  • Root actor checkpoint: checkpoints/datasets/tooluse/qwen3gen-tooluse-RLSD_TR-Qwen-Qwen3-4B-mbs8-decay0-tr0.1-train32-rollout8-lr1e-6-vllm0.8/_actor_archive/global_step_60/actor
  • Last actor checkpoint: checkpoints/datasets/tooluse/qwen3gen-tooluse-RLSD_TR-Qwen-Qwen3-4B-mbs8-decay0-tr0.1-train32-rollout8-lr1e-6-vllm0.8/global_step_100/actor
  • W&B run: run-20260702_154716-jrdzd11b
  • Queue log: artifacts/queue.log