Model: xw1234gan/seccodeplt-qwen2.5-coder-3b-grpo-no-kl-real-reward-v2 Source: Original Platform
base_model, library_name, datasets, tags
| base_model | library_name | datasets | tags | |||||
|---|---|---|---|---|---|---|---|---|
| Qwen/Qwen2.5-Coder-3B-Instruct | transformers |
|
|
seccodeplt-qwen2.5-coder-3b-grpo-no-kl-real-reward-v2
GRPO without KL regularization for the SecCodePLT+ compliance experiment using
Qwen/Qwen2.5-Coder-3B-Instruct. This v2 run corrects causal-label alignment and uses the
official ReaL safety-unit-test reward with DAPO-style token loss and dynamic
sampling. 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 | 0.396741 |
| Output format pass | 96.95% |
| Syntax pass | 96.95% |
| Capability pass | 23.78% |
| Safety pass | 56.71% |
| Joint pass | 15.24% |
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.
Description
Model synced from source: xw1234gan/seccodeplt-qwen2.5-coder-3b-grpo-no-kl-real-reward-v2
Languages
Jinja
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