Update README.md
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license: mit
language:
- en
- zh
tags:
- mteb
model-index:
- name: bge-reranker-base
results:
- task:
type: Reranking
dataset:
type: C-MTEB/CMedQAv1-reranking
name: MTEB CMedQAv1
config: default
split: test
revision: None
metrics:
- type: map
value: 82.15039301310942
- type: mrr
value: 84.92349206349207
- task:
type: Reranking
dataset:
type: C-MTEB/CMedQAv2-reranking
name: MTEB CMedQAv2
config: default
split: test
revision: None
metrics:
- type: map
value: 84.18695515652256
- type: mrr
value: 86.96876984126984
- task:
type: Reranking
dataset:
type: C-MTEB/Mmarco-reranking
name: MTEB MMarcoReranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 37.641770303833105
- type: mrr
value: 36.576587301587304
- task:
type: Reranking
dataset:
type: C-MTEB/T2Reranking
name: MTEB T2Reranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 67.47867763060952
- type: mrr
value: 77.609724774586
pipeline_tag: feature-extraction
---
本模型是在 [BAAI/bge-reranker-large](https://huggingface.co/BAAI/bge-reranker-large) 上对模型的 `model.base_model.embeddings.position_embeddings.weight` 依赖经验值进行修改，来扩大模型输入长度，并没有进行任何继续supervised fined tuning，作为新手示例。同时亦附上在`C-MTEB`的分数作为对比。感谢原作者的工作。