metadata
license: mit
language:
- zh
- en
tags:
- mteb
model-index:
- name: bge-reranker-large-1k
results:
- task:
type: Reranking
dataset:
type: C-MTEB/CMedQAv1-reranking
name: MTEB CMedQAv1
config: default
split: test
revision: None
metrics:
- type: map
value: 81.26301528052902
- type: mrr
value: 84.13043650793651
- task:
type: Reranking
dataset:
type: C-MTEB/CMedQAv2-reranking
name: MTEB CMedQAv2
config: default
split: test
revision: None
metrics:
- type: map
value: 84.10748270282731
- type: mrr
value: 86.79376984126984
- task:
type: Reranking
dataset:
type: C-MTEB/Mmarco-reranking
name: MTEB MMarcoReranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 35.46065069588283
- type: mrr
value: 34.60238095238095
- task:
type: Reranking
dataset:
type: C-MTEB/T2Reranking
name: MTEB T2Reranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 67.25376077716552
- type: mrr
value: 77.1615431322608
本模型是在 BAAI/bge-reranker-base 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。