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seccodeplt-qwen2.5-coder-7b…/README.md
ModelHub XC d5b93b0608 初始化项目,由ModelHub XC社区提供模型
Model: xw1234gan/seccodeplt-qwen2.5-coder-7b-grpo-kl-beta-0.001-real-detector-reward-v3
Source: Original Platform
2026-09-21 16:28:26 +08:00

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---
base_model: Qwen/Qwen2.5-Coder-7B-Instruct
library_name: transformers
datasets:
- fengyao1909/SecCodePLT_Plus
tags:
- code
- security
- grpo
- seccodeplt
---
# seccodeplt-qwen2.5-coder-7b-grpo-kl-beta-0.001-real-detector-reward-v3
GRPO with KL regularization (beta=0.001) for the SecCodePLT+ compliance experiment using
`Qwen/Qwen2.5-Coder-7B-Instruct`. This v3 run uses ReaL's program-analysis detector reward
with DAPO-style token loss and dynamic sampling. The reward is `0.5 *
capability_test_fraction + 0.5 * max(0, 1 - 0.3 * detected_vulnerabilities)`.
Training used seed 42 and the official 655-example training split.
Evaluation used greedy decoding on all 164 official test examples.
## Evaluation
| Metric | Value |
|---|---:|
| Mean reward | 0.581540 |
| Output format pass | 98.78% |
| Syntax pass | 97.56% |
| Capability pass | 37.80% |
| Safety pass | 62.80% |
| Detector clean | 60.98% |
| Detector score | 0.784756 |
| Joint pass | 30.49% |
## Limitations
This is a single-seed research checkpoint evaluated with the benchmark's
resource-bounded Python verifier. It is not a general guarantee of secure code.