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qwen3-4b-tooluse-grpo/README.md
ModelHub XC 62e6b3603c 初始化项目,由ModelHub XC社区提供模型
Model: SeongryongJung/qwen3-4b-tooluse-grpo
Source: Original Platform
2026-08-21 00:51:49 +08:00

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---
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- qwen3
- reinforcement-learning
- grpo
---
# qwen3-4b-tooluse-grpo
Fine-tuned from `Qwen/Qwen3-4B` with GRPO on the `tooluse` split.
## Validation Performance
Metric: `val-aux/tooluse/reward/mean@16` from 10-step validation logs.
| best mean@16 | best step | final mean@16 | final step |
|---:|---:|---:|---:|
| 61.31% | 80 | 60.29% | 100 |
![Validation mean@16](eval_mean16.png)
| step | mean@16 |
|---:|---:|
| 10 | 58.00% |
| 20 | 60.11% |
| 30 | 61.21% |
| 40 | 60.11% |
| 50 | 60.94% |
| 60 | 59.28% |
| 70 | 58.64% |
| 80 | 61.31% |
| 90 | 57.72% |
| 100 | 60.29% |
Files included with this repo:
- `metrics.json`: parsed validation summary
- `eval_mean16.csv`: step-level validation curve data
- `eval_mean16.png`: validation curve plot
Important: the uploaded weights are the final `global_step_100/actor` checkpoint. If `best step` is earlier than 100, the best validation point is reported for tracking, but the corresponding actor weights may not be retained locally.
Checkpoint source:
`/mnt/mole/SDPO/L2T/checkpoints/datasets/tooluse/qwen3gen-tooluse-GRPO-Qwen-Qwen3-4B-mbs8-train64-rollout8-lr1e-6-vllm0.8`
W&B run: `run-20260630_031808-osu8wla2`
This upload uses `global_step_100/actor` converted from VERL FSDP shards to Hugging Face format.