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license: mit
library_name: sentence-transformers
pipeline_tag: text-ranking
tags:
- cross-encoder
- reranker
- climate-fact-checking
- comp90042
---
# New-Methodology finetuned rerankers
Cross-encoder / reranker checkpoints produced by `scripts/02_train_reranker.py` and related experiments.
## Subfolders
| HF path | Local source |
|---------|--------------|
| `finetuned_reranker/` | `outputs/retrieval/models/finetuned_reranker` |
| `ce_minilm_hybrid_hard_epochs2/` | `outputs/retrieval/models/ce_cross-encoder__ms-marco-MiniLM-L6-v2__hybrid_hard__epochs2` |
| `finetuned_bge_reranker/` | `outputs/retrieval/models/finetuned_bge_reranker` |
| `finetuned_minilm_hardneg/` | `outputs/retrieval/models/finetuned_minilm_hardneg` |
| `finetuned_reranker_s60/` | `outputs/retrieval/models/finetuned_reranker_s60` |
| `pairwise_reranker/` | `outputs/reranker/pairwise/pairwise_reranker` |
## Load example (sentence-transformers)
```python
from sentence_transformers import CrossEncoder
model = CrossEncoder("jasperyeoh2/new-methodology-rerankers", trust_remote_code=True)
# For a specific checkpoint, clone and point model_name_or_path to the subfolder.
```
## Recommended for MMR pipeline
Production MMR (λ=0.5) uses **zero-shot** `cross-encoder/ms-marco-MiniLM-L6-v2`, not these finetuned weights.
Finetuned checkpoints are kept for reproducibility and ablation.
|