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language:
- en
- code
library_name: sentence-transformers
pipeline_tag: text-classification
tags:
- cross-encoder
- reranker
- code-search
- onnx
- bert
datasets:
- code_search_net
license: apache-2.0
---
# code-reranker-v1
A cross-encoder reranker for code search, trained on CodeSearchNet pairs. **Experimental — does not improve retrieval in our benchmarks.** Published for reproducibility.
## Status: Negative Result
This reranker **regresses** retrieval quality on our hard eval (55 confusable function pairs):
| Config | Recall@1 | Delta |
|--------|----------|-------|
| No reranker | 90.9% | — |
| Web-trained cross-encoder | 80.0% | **-10.9pp** |
| **This model (code-trained)** | **9.1%** | **-81.8pp** |
**Root cause:** Trained with random same-language negatives, which are too easy for cross-encoders. The model learns surface-level language patterns instead of semantic code discrimination. A V2 with BM25 hard negatives may fix this.
## Training
- **Architecture:** Cross-encoder (BERT-base)
- **Data:** 50,000 CodeSearchNet pairs + 7,500 docstring pairs
- **Epochs:** 3
- **Negatives:** Random same-language (this was the mistake)
## Usage (if you want to experiment)
```bash
# In cqs — NOT default, opt-in only
CQS_RERANKER_MODEL=jamie8johnson/code-reranker-v1 cqs "query" --rerank
```
## License
Apache 2.0.
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