---
license: other
pipeline_tag: text-classification
library_name: setfit
base_model: sentence-transformers/all-MiniLM-L6-v2
tags:
  - setfit
  - sentence-transformers
  - text-classification
  - crp
  - context-relay-protocol
  - intent-classification
  - speech-acts
datasets:
  - banking77
  - snips_built_in_intents
metrics:
  - accuracy
model-index:
  - name: crp-intent-setfit
    results:
      - task:
          type: text-classification
          name: Speech-act classification (4-class)
        dataset:
          type: banking77
          name: CRP speech-act held-out mix
        metrics:
          - type: accuracy
            value: 0.9340
            name: Held-out accuracy (2,000 examples)
widget:
  - text: "Please scan the repository for compliance issues."
  - text: "What is the current deployment status?"
  - text: "I believe the server is down."
  - text: "This is frustrating and slow."
inference: true
---

# CRP Intent SetFit — speech-act classifier

Part of the [Context Relay Protocol (CRP)](https://crprotocol.io) ML-first
governance layer. Classifies a user turn into one of four CRP speech acts —
**request, question, assertion, expressive** — used by `crp/isa/intent.py`
(SPEC-051 Intent & Speech Acts) to drive routing and operation framing in
agentic pipelines.

Few-shot SetFit model: contrastive-tuned `all-MiniLM-L6-v2` body +
LogisticRegression head fit on the full training mix.

## Verified results (independent harness, 2026-07-28)

| Metric | Value |
|---|---|
| Held-out accuracy (2,000 unseen examples) | **0.9340** |
| F1 assertion / expressive / question / request | 0.980 / 1.000 / 0.880 / 0.933 |
| Production-style CRP prompts | **18/20** |

## Training data

Banking77 + SNIPS (intent names heuristically mapped to the four CRP speech
acts) + templated synthetic examples per class. 64-shot contrastive body
tuning, then the classifier head refit on the full mix.

## Usage

```python
from setfit import SetFitModel

model = SetFitModel.from_pretrained("AutoCyberAI/crp-intent-setfit")
model.predict(["Please scan the repository for compliance issues."])
# -> ['request']
```

In the CRP SDK this model is the default intent backend:

```bash
CRP_INTENT_MODEL=AutoCyberAI/crp-intent-setfit  # default; no env needed
```

## Limitations

Four speech acts only; trained on English service/assistant phrasing. The
held-out score is in-distribution (same data mix); the production-prompt
score above is the out-of-distribution signal.

## License

Elastic License 2.0 — see the CRP repository for details.