Secrets Sentinel — small-v1 (deberta-v3-small)
Variant of hypn05/secrets-sentinel Architecture: deberta-v3-small · Parameters: 141M · Speed: 3.5× vs base · pos_att_type:
p2c + c2p (default)
Full fine-tune on data_v10 (1.14M lines, 195 negative + 162 positive patterns, 37,866 real-world labeled examples). 6 transformer layers vs 12 in base. Identical accuracy to base on all 9 test scenarios.
Benchmark (test_cases_realistic · 700 lines · 9 scenarios · private_key excluded)
| Model | F1 | Prec | Rec | FP | ms/line | Speedup |
|---|---|---|---|---|---|---|
| base v5.0.0 (reference) | 1.0000 | 1.0000 | 1.0000 | 0 | 0.938ms | 1× |
| small-v1 (this model) | see notes | — | 1.0000 | see notes | ~3.5× faster | 3.5× |
Usage
from transformers import pipeline
detector = pipeline("text-classification", model="hypn05/secrets-sentinel-small")
lines = [
"AWS_SECRET_ACCESS_KEY = 'wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY'",
"password = os.environ.get('DB_PASSWORD')",
"uses: docker/login-action@5e57cd118135c172c3672efd75eb46360885c0ef",
"DB_PASSWORD=null",
]
for line, result in zip(lines, detector(lines)):
label = "SECRET" if result["label"] == "LABEL_1" else "safe "
print(f"[{label}] {result['score']:.1%} {line[:70]}")
Expected output:
[SECRET] 100.0% AWS_SECRET_ACCESS_KEY = 'wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY'
[safe ] 0.0% password = os.environ.get('DB_PASSWORD')
[safe ] 0.0% uses: docker/login-action@5e57cd118135c172c3672efd75eb46360885c0ef
[safe ] 0.0% DB_PASSWORD=null
Parent model
See hypn05/secrets-sentinel for full documentation, integration examples (pre-receive hooks, GitHub Actions, pre-commit), training data details, and complete benchmark numbers across all variants.