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README.md
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---
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tags:
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- mteb
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model-index:
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- name: conan-embedding
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results:
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- task:
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type: STS
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dataset:
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type: C-MTEB/AFQMC
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name: MTEB AFQMC
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config: default
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split: validation
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revision: None
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metrics:
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| 16 |
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- type: cos_sim_pearson
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value:
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| 18 |
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- type: cos_sim_spearman
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value: 60.
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| 20 |
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- type: euclidean_pearson
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value: 58.
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| 22 |
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- type: euclidean_spearman
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value:
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- type: manhattan_pearson
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value: 58.
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| 26 |
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- type: manhattan_spearman
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value:
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| 28 |
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- task:
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| 29 |
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type: STS
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dataset:
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| 31 |
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type: C-MTEB/ATEC
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| 32 |
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name: MTEB ATEC
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| 33 |
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config: default
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| 34 |
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split: test
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revision: None
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| 36 |
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metrics:
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| 37 |
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- type: cos_sim_pearson
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value:
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| 39 |
-
- type: cos_sim_spearman
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| 40 |
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value: 58.
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| 41 |
-
- type: euclidean_pearson
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| 42 |
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value: 62.
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| 43 |
-
- type: euclidean_spearman
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| 44 |
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value: 58.
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| 45 |
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- type: manhattan_pearson
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| 46 |
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value: 62.
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| 47 |
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- type: manhattan_spearman
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| 48 |
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value: 58.
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| 49 |
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- task:
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| 50 |
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type: Classification
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| 51 |
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dataset:
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| 52 |
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type: mteb/amazon_reviews_multi
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name: MTEB AmazonReviewsClassification (zh)
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| 54 |
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config: zh
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| 55 |
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split: test
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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| 57 |
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metrics:
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| 58 |
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- type: accuracy
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| 59 |
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value: 50.
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| 60 |
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- type: f1
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value:
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| 62 |
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- task:
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| 63 |
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type: STS
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dataset:
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| 65 |
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type: C-MTEB/BQ
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| 66 |
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name: MTEB BQ
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| 67 |
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config: default
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split: test
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revision: None
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| 70 |
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metrics:
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- type: cos_sim_pearson
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value:
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| 73 |
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- type: cos_sim_spearman
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| 74 |
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value: 74.
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| 75 |
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- type: euclidean_pearson
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value: 72.
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| 77 |
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- type: euclidean_spearman
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value:
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| 79 |
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- type: manhattan_pearson
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| 80 |
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value: 72.
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| 81 |
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- type: manhattan_spearman
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value:
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| 83 |
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- task:
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type: Clustering
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dataset:
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type: C-MTEB/CLSClusteringP2P
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name: MTEB CLSClusteringP2P
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| 88 |
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config: default
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| 89 |
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split: test
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| 90 |
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revision: None
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| 91 |
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metrics:
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| 92 |
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- type: v_measure
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value:
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- task:
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type: Clustering
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dataset:
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type: C-MTEB/CLSClusteringS2S
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name: MTEB CLSClusteringS2S
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config: default
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split: test
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revision: None
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metrics:
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- type: v_measure
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value:
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- task:
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type: Reranking
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dataset:
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type: C-MTEB/CMedQAv1-reranking
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name: MTEB CMedQAv1
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config: default
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split: test
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revision: None
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| 113 |
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metrics:
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- type: map
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value:
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- type: mrr
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value:
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- task:
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type: Reranking
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| 120 |
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dataset:
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type: C-MTEB/CMedQAv2-reranking
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| 122 |
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name: MTEB CMedQAv2
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| 123 |
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config: default
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| 124 |
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split: test
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revision: None
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| 126 |
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metrics:
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- type: map
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value:
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- type: mrr
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value:
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- task:
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type: Retrieval
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dataset:
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type: C-MTEB/CmedqaRetrieval
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name: MTEB CmedqaRetrieval
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config: default
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split: dev
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| 138 |
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revision: None
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| 139 |
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metrics:
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- type: map_at_1
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value: 26.
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| 142 |
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- type: map_at_10
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value: 40.
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- type: map_at_100
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value: 42.
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- type: map_at_1000
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value: 42.
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- type: map_at_3
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value:
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- type: map_at_5
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value: 38.
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| 152 |
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- type: mrr_at_1
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value:
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- type: mrr_at_10
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value:
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- type: mrr_at_100
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value:
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- type: mrr_at_1000
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value:
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- type: mrr_at_3
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value:
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- type: mrr_at_5
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value:
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- type: ndcg_at_1
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value:
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- type: ndcg_at_10
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value: 47.
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| 168 |
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- type: ndcg_at_100
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value: 54.
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| 170 |
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- type: ndcg_at_1000
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value:
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- type: ndcg_at_3
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value:
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- type: ndcg_at_5
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value:
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| 176 |
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- type: precision_at_1
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value:
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| 178 |
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- type: precision_at_10
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| 179 |
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value: 10.
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| 180 |
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- type: precision_at_100
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value: 1.
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- type: precision_at_1000
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value: 0.
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| 184 |
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- type: precision_at_3
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value: 23.
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| 186 |
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- type: precision_at_5
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value: 17.
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| 188 |
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- type: recall_at_1
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value: 26.
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| 190 |
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- type: recall_at_10
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value: 58.
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| 192 |
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- type: recall_at_100
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value: 87.
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- type: recall_at_1000
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value: 98.
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- type: recall_at_3
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value:
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- type: recall_at_5
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value: 49.
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- task:
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type: PairClassification
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dataset:
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type: C-MTEB/CMNLI
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name: MTEB Cmnli
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config: default
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split: validation
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revision: None
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metrics:
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- type: cos_sim_accuracy
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value:
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- type: cos_sim_ap
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value: 92.
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- type: cos_sim_f1
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value:
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- type: cos_sim_precision
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value:
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- type: cos_sim_recall
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value:
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- type: dot_accuracy
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value: 77.
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- type: dot_ap
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value: 85.
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- type: dot_f1
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value: 79.
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- type: dot_precision
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value:
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- type: dot_recall
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value:
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- type: euclidean_accuracy
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value: 84.
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- type: euclidean_ap
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value: 91.
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- type: euclidean_f1
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value: 85.
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- type: euclidean_precision
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value:
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- type: euclidean_recall
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value:
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- type: manhattan_accuracy
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value: 84.
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| 241 |
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- type: manhattan_ap
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value: 91.
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| 243 |
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- type: manhattan_f1
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value: 85.
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| 245 |
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- type: manhattan_precision
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value:
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| 247 |
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- type: manhattan_recall
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value:
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| 249 |
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- type: max_accuracy
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value:
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| 251 |
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- type: max_ap
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| 252 |
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value: 92.
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| 253 |
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- type: max_f1
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value:
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- task:
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type: Retrieval
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dataset:
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| 258 |
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type: C-MTEB/CovidRetrieval
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| 259 |
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name: MTEB CovidRetrieval
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| 260 |
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config: default
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| 261 |
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split: dev
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revision: None
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| 263 |
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metrics:
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| 264 |
-
- type: map_at_1
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| 265 |
-
value:
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| 266 |
-
- type: map_at_10
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| 267 |
-
value:
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| 268 |
-
- type: map_at_100
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-
value:
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- type: map_at_1000
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-
value:
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| 272 |
-
- type: map_at_3
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| 273 |
-
value: 89.
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| 274 |
-
- type: map_at_5
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| 275 |
-
value: 89.
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| 276 |
-
- type: mrr_at_1
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| 277 |
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value: 83.
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| 278 |
-
- type: mrr_at_10
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value:
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-
- type: mrr_at_100
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-
value:
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- type: mrr_at_1000
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value:
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- type: mrr_at_3
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value: 89.
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- type: mrr_at_5
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value: 89.
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| 288 |
-
- type: ndcg_at_1
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value:
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-
- type: ndcg_at_10
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value: 92.
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| 292 |
-
- type: ndcg_at_100
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| 293 |
-
value: 92.
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| 294 |
-
- type: ndcg_at_1000
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-
value: 92.
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| 296 |
-
- type: ndcg_at_3
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-
value: 91.
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| 298 |
-
- type: ndcg_at_5
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| 299 |
-
value: 91.
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| 300 |
-
- type: precision_at_1
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-
value:
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| 302 |
-
- type: precision_at_10
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value:
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| 304 |
-
- type: precision_at_100
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| 305 |
-
value: 1.009
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| 306 |
-
- type: precision_at_1000
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| 307 |
-
value: 0.101
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| 308 |
-
- type: precision_at_3
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| 309 |
-
value: 32.
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| 310 |
-
- type: precision_at_5
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| 311 |
-
value: 19.
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| 312 |
-
- type: recall_at_1
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value:
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-
- type: recall_at_10
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-
value:
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| 316 |
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- type: recall_at_100
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| 317 |
-
value: 99.895
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| 318 |
-
- type: recall_at_1000
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| 319 |
-
value: 100.0
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| 320 |
-
- type: recall_at_3
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value:
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| 322 |
-
- type: recall_at_5
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| 323 |
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value: 97.
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| 324 |
-
- task:
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| 325 |
-
type: Retrieval
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| 326 |
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dataset:
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| 327 |
-
type: C-MTEB/DuRetrieval
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| 328 |
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name: MTEB DuRetrieval
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| 329 |
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config: default
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| 330 |
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split: dev
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| 331 |
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revision: None
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| 332 |
-
metrics:
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| 333 |
-
- type: map_at_1
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| 334 |
-
value: 26.
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| 335 |
-
- type: map_at_10
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| 336 |
-
value: 81.
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| 337 |
-
- type: map_at_100
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| 338 |
-
value: 84.
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| 339 |
-
- type: map_at_1000
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| 340 |
-
value: 84.
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| 341 |
-
- type: map_at_3
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| 342 |
-
value: 56.
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| 343 |
-
- type: map_at_5
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| 344 |
-
value: 71.
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| 345 |
-
- type: mrr_at_1
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| 346 |
-
value: 91.
|
| 347 |
-
- type: mrr_at_10
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| 348 |
-
value: 94.
|
| 349 |
-
- type: mrr_at_100
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| 350 |
-
value: 94.
|
| 351 |
-
- type: mrr_at_1000
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| 352 |
-
value: 94.
|
| 353 |
-
- type: mrr_at_3
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| 354 |
-
value:
|
| 355 |
-
- type: mrr_at_5
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| 356 |
-
value:
|
| 357 |
-
- type: ndcg_at_1
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| 358 |
-
value: 91.
|
| 359 |
-
- type: ndcg_at_10
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| 360 |
-
value: 88.
|
| 361 |
-
- type: ndcg_at_100
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| 362 |
-
value: 91.
|
| 363 |
-
- type: ndcg_at_1000
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| 364 |
-
value: 91.
|
| 365 |
-
- type: ndcg_at_3
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| 366 |
-
value: 87.
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| 367 |
-
- type: ndcg_at_5
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| 368 |
-
value: 86.
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| 369 |
-
- type: precision_at_1
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| 370 |
-
value: 91.
|
| 371 |
-
- type: precision_at_10
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| 372 |
-
value: 42.
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| 373 |
-
- type: precision_at_100
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| 374 |
-
value: 4.
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| 375 |
-
- type: precision_at_1000
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| 376 |
-
value: 0.
|
| 377 |
-
- type: precision_at_3
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| 378 |
-
value: 78.
|
| 379 |
-
- type: precision_at_5
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| 380 |
-
value: 65.
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| 381 |
-
- type: recall_at_1
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| 382 |
-
value: 26.
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| 383 |
-
- type: recall_at_10
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| 384 |
-
value: 89.
|
| 385 |
-
- type: recall_at_100
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| 386 |
-
value:
|
| 387 |
-
- type: recall_at_1000
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| 388 |
-
value: 99.
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| 389 |
-
- type: recall_at_3
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| 390 |
-
value:
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| 391 |
-
- type: recall_at_5
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| 392 |
-
value: 75.
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| 393 |
-
- task:
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| 394 |
-
type: Retrieval
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| 395 |
-
dataset:
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| 396 |
-
type: C-MTEB/EcomRetrieval
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| 397 |
-
name: MTEB EcomRetrieval
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| 398 |
-
config: default
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| 399 |
-
split: dev
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| 400 |
-
revision: None
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| 401 |
-
metrics:
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| 402 |
-
- type: map_at_1
|
| 403 |
-
value:
|
| 404 |
-
- type: map_at_10
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| 405 |
-
value: 65.
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| 406 |
-
- type: map_at_100
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| 407 |
-
value: 66.
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| 408 |
-
- type: map_at_1000
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| 409 |
-
value: 66.
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| 410 |
-
- type: map_at_3
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| 411 |
-
value: 62.
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| 412 |
-
- type: map_at_5
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| 413 |
-
value: 64.
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| 414 |
-
- type: mrr_at_1
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| 415 |
-
value:
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| 416 |
-
- type: mrr_at_10
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| 417 |
-
value: 65.
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| 418 |
-
- type: mrr_at_100
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| 419 |
-
value: 66.
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| 420 |
-
- type: mrr_at_1000
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| 421 |
-
value: 66.
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| 422 |
-
- type: mrr_at_3
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| 423 |
-
value: 62.
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| 424 |
-
- type: mrr_at_5
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| 425 |
-
value: 64.
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| 426 |
-
- type: ndcg_at_1
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| 427 |
-
value:
|
| 428 |
-
- type: ndcg_at_10
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| 429 |
-
value: 70.
|
| 430 |
-
- type: ndcg_at_100
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| 431 |
-
value: 73.
|
| 432 |
-
- type: ndcg_at_1000
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| 433 |
-
value: 73.
|
| 434 |
-
- type: ndcg_at_3
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| 435 |
-
value: 65.
|
| 436 |
-
- type: ndcg_at_5
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| 437 |
-
value: 68.
|
| 438 |
-
- type: precision_at_1
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| 439 |
-
value:
|
| 440 |
-
- type: precision_at_10
|
| 441 |
-
value: 8.
|
| 442 |
-
- type: precision_at_100
|
| 443 |
-
value: 0.
|
| 444 |
-
- type: precision_at_1000
|
| 445 |
-
value: 0.1
|
| 446 |
-
- type: precision_at_3
|
| 447 |
-
value: 24.
|
| 448 |
-
- type: precision_at_5
|
| 449 |
-
value:
|
| 450 |
-
- type: recall_at_1
|
| 451 |
-
value:
|
| 452 |
-
- type: recall_at_10
|
| 453 |
-
value: 87.
|
| 454 |
-
- type: recall_at_100
|
| 455 |
-
value: 98.
|
| 456 |
-
- type: recall_at_1000
|
| 457 |
-
value: 99.
|
| 458 |
-
- type: recall_at_3
|
| 459 |
-
value: 72.
|
| 460 |
-
- type: recall_at_5
|
| 461 |
-
value:
|
| 462 |
-
- task:
|
| 463 |
-
type: Classification
|
| 464 |
-
dataset:
|
| 465 |
-
type: C-MTEB/IFlyTek-classification
|
| 466 |
-
name: MTEB IFlyTek
|
| 467 |
-
config: default
|
| 468 |
-
split: validation
|
| 469 |
-
revision: None
|
| 470 |
-
metrics:
|
| 471 |
-
- type: accuracy
|
| 472 |
-
value: 51.
|
| 473 |
-
- type: f1
|
| 474 |
-
value: 39.
|
| 475 |
-
- task:
|
| 476 |
-
type: Classification
|
| 477 |
-
dataset:
|
| 478 |
-
type: C-MTEB/JDReview-classification
|
| 479 |
-
name: MTEB JDReview
|
| 480 |
-
config: default
|
| 481 |
-
split: test
|
| 482 |
-
revision: None
|
| 483 |
-
metrics:
|
| 484 |
-
- type: accuracy
|
| 485 |
-
value:
|
| 486 |
-
- type: ap
|
| 487 |
-
value:
|
| 488 |
-
- type: f1
|
| 489 |
-
value:
|
| 490 |
-
- task:
|
| 491 |
-
type: STS
|
| 492 |
-
dataset:
|
| 493 |
-
type: C-MTEB/LCQMC
|
| 494 |
-
name: MTEB LCQMC
|
| 495 |
-
config: default
|
| 496 |
-
split: test
|
| 497 |
-
revision: None
|
| 498 |
-
metrics:
|
| 499 |
-
- type: cos_sim_pearson
|
| 500 |
-
value:
|
| 501 |
-
- type: cos_sim_spearman
|
| 502 |
-
value: 79.
|
| 503 |
-
- type: euclidean_pearson
|
| 504 |
-
value:
|
| 505 |
-
- type: euclidean_spearman
|
| 506 |
-
value: 79.
|
| 507 |
-
- type: manhattan_pearson
|
| 508 |
-
value:
|
| 509 |
-
- type: manhattan_spearman
|
| 510 |
-
value: 79.
|
| 511 |
-
- task:
|
| 512 |
-
type: Reranking
|
| 513 |
-
dataset:
|
| 514 |
-
type: C-MTEB/Mmarco-reranking
|
| 515 |
-
name: MTEB MMarcoReranking
|
| 516 |
-
config: default
|
| 517 |
-
split: dev
|
| 518 |
-
revision: None
|
| 519 |
-
metrics:
|
| 520 |
-
- type: map
|
| 521 |
-
value: 41.
|
| 522 |
-
- type: mrr
|
| 523 |
-
value: 41.
|
| 524 |
-
- task:
|
| 525 |
-
type: Retrieval
|
| 526 |
-
dataset:
|
| 527 |
-
type: C-MTEB/MMarcoRetrieval
|
| 528 |
-
name: MTEB MMarcoRetrieval
|
| 529 |
-
config: default
|
| 530 |
-
split: dev
|
| 531 |
-
revision: None
|
| 532 |
-
metrics:
|
| 533 |
-
- type: map_at_1
|
| 534 |
-
value: 68.
|
| 535 |
-
- type: map_at_10
|
| 536 |
-
value: 78.
|
| 537 |
-
- type: map_at_100
|
| 538 |
-
value: 78.
|
| 539 |
-
- type: map_at_1000
|
| 540 |
-
value: 78.
|
| 541 |
-
- type: map_at_3
|
| 542 |
-
value: 76.
|
| 543 |
-
- type: map_at_5
|
| 544 |
-
value: 77.
|
| 545 |
-
- type: mrr_at_1
|
| 546 |
-
value: 70.
|
| 547 |
-
- type: mrr_at_10
|
| 548 |
-
value: 78.
|
| 549 |
-
- type: mrr_at_100
|
| 550 |
-
value: 79.
|
| 551 |
-
- type: mrr_at_1000
|
| 552 |
-
value: 79.
|
| 553 |
-
- type: mrr_at_3
|
| 554 |
-
value: 77.
|
| 555 |
-
- type: mrr_at_5
|
| 556 |
-
value: 78.
|
| 557 |
-
- type: ndcg_at_1
|
| 558 |
-
value: 70.
|
| 559 |
-
- type: ndcg_at_10
|
| 560 |
-
value: 82.
|
| 561 |
-
- type: ndcg_at_100
|
| 562 |
-
value: 83.
|
| 563 |
-
- type: ndcg_at_1000
|
| 564 |
-
value: 83.
|
| 565 |
-
- type: ndcg_at_3
|
| 566 |
-
value: 78.
|
| 567 |
-
- type: ndcg_at_5
|
| 568 |
-
value: 80.
|
| 569 |
-
- type: precision_at_1
|
| 570 |
-
value: 70.
|
| 571 |
-
- type: precision_at_10
|
| 572 |
-
value: 9.
|
| 573 |
-
- type: precision_at_100
|
| 574 |
-
value: 1.05
|
| 575 |
-
- type: precision_at_1000
|
| 576 |
-
value: 0.106
|
| 577 |
-
- type: precision_at_3
|
| 578 |
-
value: 29.
|
| 579 |
-
- type: precision_at_5
|
| 580 |
-
value: 18.
|
| 581 |
-
- type: recall_at_1
|
| 582 |
-
value: 68.
|
| 583 |
-
- type: recall_at_10
|
| 584 |
-
value:
|
| 585 |
-
- type: recall_at_100
|
| 586 |
-
value: 98.
|
| 587 |
-
- type: recall_at_1000
|
| 588 |
-
value: 99.
|
| 589 |
-
- type: recall_at_3
|
| 590 |
-
value: 84.
|
| 591 |
-
- type: recall_at_5
|
| 592 |
-
value: 89.
|
| 593 |
-
- task:
|
| 594 |
-
type: Classification
|
| 595 |
-
dataset:
|
| 596 |
-
type: mteb/amazon_massive_intent
|
| 597 |
-
name: MTEB MassiveIntentClassification (zh-CN)
|
| 598 |
-
config: zh-CN
|
| 599 |
-
split: test
|
| 600 |
-
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 601 |
-
metrics:
|
| 602 |
-
- type: accuracy
|
| 603 |
-
value: 78.
|
| 604 |
-
- type: f1
|
| 605 |
-
value: 74.
|
| 606 |
-
- task:
|
| 607 |
-
type: Classification
|
| 608 |
-
dataset:
|
| 609 |
-
type: mteb/amazon_massive_scenario
|
| 610 |
-
name: MTEB MassiveScenarioClassification (zh-CN)
|
| 611 |
-
config: zh-CN
|
| 612 |
-
split: test
|
| 613 |
-
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 614 |
-
metrics:
|
| 615 |
-
- type: accuracy
|
| 616 |
-
value: 86.
|
| 617 |
-
- type: f1
|
| 618 |
-
value: 85.
|
| 619 |
-
- task:
|
| 620 |
-
type: Retrieval
|
| 621 |
-
dataset:
|
| 622 |
-
type: C-MTEB/MedicalRetrieval
|
| 623 |
-
name: MTEB MedicalRetrieval
|
| 624 |
-
config: default
|
| 625 |
-
split: dev
|
| 626 |
-
revision: None
|
| 627 |
-
metrics:
|
| 628 |
-
- type: map_at_1
|
| 629 |
-
value:
|
| 630 |
-
- type: map_at_10
|
| 631 |
-
value:
|
| 632 |
-
- type: map_at_100
|
| 633 |
-
value:
|
| 634 |
-
- type: map_at_1000
|
| 635 |
-
value:
|
| 636 |
-
- type: map_at_3
|
| 637 |
-
value:
|
| 638 |
-
- type: map_at_5
|
| 639 |
-
value:
|
| 640 |
-
- type: mrr_at_1
|
| 641 |
-
value:
|
| 642 |
-
- type: mrr_at_10
|
| 643 |
-
value:
|
| 644 |
-
- type: mrr_at_100
|
| 645 |
-
value:
|
| 646 |
-
- type: mrr_at_1000
|
| 647 |
-
value:
|
| 648 |
-
- type: mrr_at_3
|
| 649 |
-
value: 62.
|
| 650 |
-
- type: mrr_at_5
|
| 651 |
-
value:
|
| 652 |
-
- type: ndcg_at_1
|
| 653 |
-
value:
|
| 654 |
-
- type: ndcg_at_10
|
| 655 |
-
value:
|
| 656 |
-
- type: ndcg_at_100
|
| 657 |
-
value: 71.
|
| 658 |
-
- type: ndcg_at_1000
|
| 659 |
-
value:
|
| 660 |
-
- type: ndcg_at_3
|
| 661 |
-
value: 64.
|
| 662 |
-
- type: ndcg_at_5
|
| 663 |
-
value:
|
| 664 |
-
- type: precision_at_1
|
| 665 |
-
value:
|
| 666 |
-
- type: precision_at_10
|
| 667 |
-
value:
|
| 668 |
-
- type: precision_at_100
|
| 669 |
-
value: 0.
|
| 670 |
-
- type: precision_at_1000
|
| 671 |
-
value: 0.1
|
| 672 |
-
- type: precision_at_3
|
| 673 |
-
value: 23.
|
| 674 |
-
- type: precision_at_5
|
| 675 |
-
value: 14.
|
| 676 |
-
- type: recall_at_1
|
| 677 |
-
value:
|
| 678 |
-
- type: recall_at_10
|
| 679 |
-
value:
|
| 680 |
-
- type: recall_at_100
|
| 681 |
-
value: 95.
|
| 682 |
-
- type: recall_at_1000
|
| 683 |
-
value: 99.
|
| 684 |
-
- type: recall_at_3
|
| 685 |
-
value: 69.
|
| 686 |
-
- type: recall_at_5
|
| 687 |
-
value:
|
| 688 |
-
- task:
|
| 689 |
-
type: Classification
|
| 690 |
-
dataset:
|
| 691 |
-
type: C-MTEB/MultilingualSentiment-classification
|
| 692 |
-
name: MTEB MultilingualSentiment
|
| 693 |
-
config: default
|
| 694 |
-
split: validation
|
| 695 |
-
revision: None
|
| 696 |
-
metrics:
|
| 697 |
-
- type: accuracy
|
| 698 |
-
value:
|
| 699 |
-
- type: f1
|
| 700 |
-
value: 78.
|
| 701 |
-
- task:
|
| 702 |
-
type: PairClassification
|
| 703 |
-
dataset:
|
| 704 |
-
type: C-MTEB/OCNLI
|
| 705 |
-
name: MTEB Ocnli
|
| 706 |
-
config: default
|
| 707 |
-
split: validation
|
| 708 |
-
revision: None
|
| 709 |
-
metrics:
|
| 710 |
-
- type: cos_sim_accuracy
|
| 711 |
-
value: 85.
|
| 712 |
-
- type: cos_sim_ap
|
| 713 |
-
value:
|
| 714 |
-
- type: cos_sim_f1
|
| 715 |
-
value: 86.
|
| 716 |
-
- type: cos_sim_precision
|
| 717 |
-
value:
|
| 718 |
-
- type: cos_sim_recall
|
| 719 |
-
value:
|
| 720 |
-
- type: dot_accuracy
|
| 721 |
-
value:
|
| 722 |
-
- type: dot_ap
|
| 723 |
-
value:
|
| 724 |
-
- type: dot_f1
|
| 725 |
-
value:
|
| 726 |
-
- type: dot_precision
|
| 727 |
-
value:
|
| 728 |
-
- type: dot_recall
|
| 729 |
-
value:
|
| 730 |
-
- type: euclidean_accuracy
|
| 731 |
-
value: 84.
|
| 732 |
-
- type: euclidean_ap
|
| 733 |
-
value: 88.
|
| 734 |
-
- type: euclidean_f1
|
| 735 |
-
value: 85.
|
| 736 |
-
- type: euclidean_precision
|
| 737 |
-
value:
|
| 738 |
-
- type: euclidean_recall
|
| 739 |
-
value: 91.
|
| 740 |
-
- type: manhattan_accuracy
|
| 741 |
-
value: 84.
|
| 742 |
-
- type: manhattan_ap
|
| 743 |
-
value: 88.
|
| 744 |
-
- type: manhattan_f1
|
| 745 |
-
value: 85.
|
| 746 |
-
- type: manhattan_precision
|
| 747 |
-
value:
|
| 748 |
-
- type: manhattan_recall
|
| 749 |
-
value:
|
| 750 |
-
- type: max_accuracy
|
| 751 |
-
value: 85.
|
| 752 |
-
- type: max_ap
|
| 753 |
-
value:
|
| 754 |
-
- type: max_f1
|
| 755 |
-
value: 86.
|
| 756 |
-
- task:
|
| 757 |
-
type: Classification
|
| 758 |
-
dataset:
|
| 759 |
-
type: C-MTEB/OnlineShopping-classification
|
| 760 |
-
name: MTEB OnlineShopping
|
| 761 |
-
config: default
|
| 762 |
-
split: test
|
| 763 |
-
revision: None
|
| 764 |
-
metrics:
|
| 765 |
-
- type: accuracy
|
| 766 |
-
value: 95.
|
| 767 |
-
- type: ap
|
| 768 |
-
value: 93.
|
| 769 |
-
- type: f1
|
| 770 |
-
value: 95.
|
| 771 |
-
- task:
|
| 772 |
-
type: STS
|
| 773 |
-
dataset:
|
| 774 |
-
type: C-MTEB/PAWSX
|
| 775 |
-
name: MTEB PAWSX
|
| 776 |
-
config: default
|
| 777 |
-
split: test
|
| 778 |
-
revision: None
|
| 779 |
-
metrics:
|
| 780 |
-
- type: cos_sim_pearson
|
| 781 |
-
value:
|
| 782 |
-
- type: cos_sim_spearman
|
| 783 |
-
value:
|
| 784 |
-
- type: euclidean_pearson
|
| 785 |
-
value:
|
| 786 |
-
- type: euclidean_spearman
|
| 787 |
-
value:
|
| 788 |
-
- type: manhattan_pearson
|
| 789 |
-
value:
|
| 790 |
-
- type: manhattan_spearman
|
| 791 |
-
value:
|
| 792 |
-
- task:
|
| 793 |
-
type: STS
|
| 794 |
-
dataset:
|
| 795 |
-
type: C-MTEB/QBQTC
|
| 796 |
-
name: MTEB QBQTC
|
| 797 |
-
config: default
|
| 798 |
-
split: test
|
| 799 |
-
revision: None
|
| 800 |
-
metrics:
|
| 801 |
-
- type: cos_sim_pearson
|
| 802 |
-
value: 42.
|
| 803 |
-
- type: cos_sim_spearman
|
| 804 |
-
value:
|
| 805 |
-
- type: euclidean_pearson
|
| 806 |
-
value:
|
| 807 |
-
- type: euclidean_spearman
|
| 808 |
-
value: 40.
|
| 809 |
-
- type: manhattan_pearson
|
| 810 |
-
value:
|
| 811 |
-
- type: manhattan_spearman
|
| 812 |
-
value: 40.
|
| 813 |
-
- task:
|
| 814 |
-
type: STS
|
| 815 |
-
dataset:
|
| 816 |
-
type: mteb/sts22-crosslingual-sts
|
| 817 |
-
name: MTEB STS22 (zh)
|
| 818 |
-
config: zh
|
| 819 |
-
split: test
|
| 820 |
-
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 821 |
-
metrics:
|
| 822 |
-
- type: cos_sim_pearson
|
| 823 |
-
value:
|
| 824 |
-
- type: cos_sim_spearman
|
| 825 |
-
value:
|
| 826 |
-
- type: euclidean_pearson
|
| 827 |
-
value:
|
| 828 |
-
- type: euclidean_spearman
|
| 829 |
-
value: 67.
|
| 830 |
-
- type: manhattan_pearson
|
| 831 |
-
value:
|
| 832 |
-
- type: manhattan_spearman
|
| 833 |
-
value: 67.
|
| 834 |
-
- task:
|
| 835 |
-
type: STS
|
| 836 |
-
dataset:
|
| 837 |
-
type: C-MTEB/STSB
|
| 838 |
-
name: MTEB STSB
|
| 839 |
-
config: default
|
| 840 |
-
split: test
|
| 841 |
-
revision: None
|
| 842 |
-
metrics:
|
| 843 |
-
- type: cos_sim_pearson
|
| 844 |
-
value:
|
| 845 |
-
- type: cos_sim_spearman
|
| 846 |
-
value: 81.
|
| 847 |
-
- type: euclidean_pearson
|
| 848 |
-
value:
|
| 849 |
-
- type: euclidean_spearman
|
| 850 |
-
value:
|
| 851 |
-
- type: manhattan_pearson
|
| 852 |
-
value:
|
| 853 |
-
- type: manhattan_spearman
|
| 854 |
-
value:
|
| 855 |
-
- task:
|
| 856 |
-
type: Reranking
|
| 857 |
-
dataset:
|
| 858 |
-
type: C-MTEB/T2Reranking
|
| 859 |
-
name: MTEB T2Reranking
|
| 860 |
-
config: default
|
| 861 |
-
split: dev
|
| 862 |
-
revision: None
|
| 863 |
-
metrics:
|
| 864 |
-
- type: map
|
| 865 |
-
value:
|
| 866 |
-
- type: mrr
|
| 867 |
-
value: 79.
|
| 868 |
-
- task:
|
| 869 |
-
type: Retrieval
|
| 870 |
-
dataset:
|
| 871 |
-
type: C-MTEB/T2Retrieval
|
| 872 |
-
name: MTEB T2Retrieval
|
| 873 |
-
config: default
|
| 874 |
-
split: dev
|
| 875 |
-
revision: None
|
| 876 |
-
metrics:
|
| 877 |
-
- type: map_at_1
|
| 878 |
-
value:
|
| 879 |
-
- type: map_at_10
|
| 880 |
-
value:
|
| 881 |
-
- type: map_at_100
|
| 882 |
-
value:
|
| 883 |
-
- type: map_at_1000
|
| 884 |
-
value:
|
| 885 |
-
- type: map_at_3
|
| 886 |
-
value:
|
| 887 |
-
- type: map_at_5
|
| 888 |
-
value:
|
| 889 |
-
- type: mrr_at_1
|
| 890 |
-
value:
|
| 891 |
-
- type: mrr_at_10
|
| 892 |
-
value:
|
| 893 |
-
- type: mrr_at_100
|
| 894 |
-
value:
|
| 895 |
-
- type: mrr_at_1000
|
| 896 |
-
value:
|
| 897 |
-
- type: mrr_at_3
|
| 898 |
-
value:
|
| 899 |
-
- type: mrr_at_5
|
| 900 |
-
value:
|
| 901 |
-
- type: ndcg_at_1
|
| 902 |
-
value:
|
| 903 |
-
- type: ndcg_at_10
|
| 904 |
-
value:
|
| 905 |
-
- type: ndcg_at_100
|
| 906 |
-
value:
|
| 907 |
-
- type: ndcg_at_1000
|
| 908 |
-
value:
|
| 909 |
-
- type: ndcg_at_3
|
| 910 |
-
value:
|
| 911 |
-
- type: ndcg_at_5
|
| 912 |
-
value:
|
| 913 |
-
- type: precision_at_1
|
| 914 |
-
value:
|
| 915 |
-
- type: precision_at_10
|
| 916 |
-
value:
|
| 917 |
-
- type: precision_at_100
|
| 918 |
-
value: 5.
|
| 919 |
-
- type: precision_at_1000
|
| 920 |
-
value: 0.516
|
| 921 |
-
- type: precision_at_3
|
| 922 |
-
value:
|
| 923 |
-
- type: precision_at_5
|
| 924 |
-
value: 62.
|
| 925 |
-
- type: recall_at_1
|
| 926 |
-
value:
|
| 927 |
-
- type: recall_at_10
|
| 928 |
-
value:
|
| 929 |
-
- type: recall_at_100
|
| 930 |
-
value: 95.
|
| 931 |
-
- type: recall_at_1000
|
| 932 |
-
value: 98.
|
| 933 |
-
- type: recall_at_3
|
| 934 |
-
value:
|
| 935 |
-
- type: recall_at_5
|
| 936 |
-
value:
|
| 937 |
-
- task:
|
| 938 |
-
type: Classification
|
| 939 |
-
dataset:
|
| 940 |
-
type: C-MTEB/TNews-classification
|
| 941 |
-
name: MTEB TNews
|
| 942 |
-
config: default
|
| 943 |
-
split: validation
|
| 944 |
-
revision: None
|
| 945 |
-
metrics:
|
| 946 |
-
- type: accuracy
|
| 947 |
-
value:
|
| 948 |
-
- type: f1
|
| 949 |
-
value:
|
| 950 |
-
- task:
|
| 951 |
-
type: Clustering
|
| 952 |
-
dataset:
|
| 953 |
-
type: C-MTEB/ThuNewsClusteringP2P
|
| 954 |
-
name: MTEB ThuNewsClusteringP2P
|
| 955 |
-
config: default
|
| 956 |
-
split: test
|
| 957 |
-
revision: None
|
| 958 |
-
metrics:
|
| 959 |
-
- type: v_measure
|
| 960 |
-
value: 77.
|
| 961 |
-
- task:
|
| 962 |
-
type: Clustering
|
| 963 |
-
dataset:
|
| 964 |
-
type: C-MTEB/ThuNewsClusteringS2S
|
| 965 |
-
name: MTEB ThuNewsClusteringS2S
|
| 966 |
-
config: default
|
| 967 |
-
split: test
|
| 968 |
-
revision: None
|
| 969 |
-
metrics:
|
| 970 |
-
- type: v_measure
|
| 971 |
-
value:
|
| 972 |
-
- task:
|
| 973 |
-
type: Retrieval
|
| 974 |
-
dataset:
|
| 975 |
-
type: C-MTEB/VideoRetrieval
|
| 976 |
-
name: MTEB VideoRetrieval
|
| 977 |
-
config: default
|
| 978 |
-
split: dev
|
| 979 |
-
revision: None
|
| 980 |
-
metrics:
|
| 981 |
-
- type: map_at_1
|
| 982 |
-
value: 64.
|
| 983 |
-
- type: map_at_10
|
| 984 |
-
value: 75.
|
| 985 |
-
- type: map_at_100
|
| 986 |
-
value: 75.
|
| 987 |
-
- type: map_at_1000
|
| 988 |
-
value: 75.
|
| 989 |
-
- type: map_at_3
|
| 990 |
-
value: 73.
|
| 991 |
-
- type: map_at_5
|
| 992 |
-
value: 74.
|
| 993 |
-
- type: mrr_at_1
|
| 994 |
-
value: 64.
|
| 995 |
-
- type: mrr_at_10
|
| 996 |
-
value: 75.
|
| 997 |
-
- type: mrr_at_100
|
| 998 |
-
value: 75.
|
| 999 |
-
- type: mrr_at_1000
|
| 1000 |
-
value: 75.
|
| 1001 |
-
- type: mrr_at_3
|
| 1002 |
-
value: 73.
|
| 1003 |
-
- type: mrr_at_5
|
| 1004 |
-
value: 74.
|
| 1005 |
-
- type: ndcg_at_1
|
| 1006 |
-
value: 64.
|
| 1007 |
-
- type: ndcg_at_10
|
| 1008 |
-
value:
|
| 1009 |
-
- type: ndcg_at_100
|
| 1010 |
-
value: 81.
|
| 1011 |
-
- type: ndcg_at_1000
|
| 1012 |
-
value: 81.
|
| 1013 |
-
- type: ndcg_at_3
|
| 1014 |
-
value: 76.
|
| 1015 |
-
- type: ndcg_at_5
|
| 1016 |
-
value: 78.
|
| 1017 |
-
- type: precision_at_1
|
| 1018 |
-
value: 64.
|
| 1019 |
-
- type: precision_at_10
|
| 1020 |
-
value: 9.
|
| 1021 |
-
- type: precision_at_100
|
| 1022 |
-
value: 0
|
| 1023 |
-
- type: precision_at_1000
|
| 1024 |
-
value: 0.1
|
| 1025 |
-
- type: precision_at_3
|
| 1026 |
-
value: 28.
|
| 1027 |
-
- type: precision_at_5
|
| 1028 |
-
value:
|
| 1029 |
-
- type: recall_at_1
|
| 1030 |
-
value: 64.
|
| 1031 |
-
- type: recall_at_10
|
| 1032 |
-
value:
|
| 1033 |
-
- type: recall_at_100
|
| 1034 |
-
value:
|
| 1035 |
-
- type: recall_at_1000
|
| 1036 |
-
value: 100.0
|
| 1037 |
-
- type: recall_at_3
|
| 1038 |
-
value: 84.
|
| 1039 |
-
- type: recall_at_5
|
| 1040 |
-
value:
|
| 1041 |
-
- task:
|
| 1042 |
-
type: Classification
|
| 1043 |
-
dataset:
|
| 1044 |
-
type: C-MTEB/waimai-classification
|
| 1045 |
-
name: MTEB Waimai
|
| 1046 |
-
config: default
|
| 1047 |
-
split: test
|
| 1048 |
-
revision: None
|
| 1049 |
-
metrics:
|
| 1050 |
-
- type: accuracy
|
| 1051 |
-
value: 89.
|
| 1052 |
-
- type: ap
|
| 1053 |
-
value: 75.
|
| 1054 |
-
- type: f1
|
| 1055 |
-
value: 88.
|
| 1056 |
-
license: cc-by-nc-4.0
|
| 1057 |
-
---
|
| 1058 |
-
|
| 1059 |
-
# Conan-embedding-v1
|
| 1060 |
-
|
| 1061 |
-
## Performance
|
| 1062 |
-
|
| 1063 |
-
| Model | **Average** | **CLS** | **Clustering** | **Reranking** | **Retrieval** | **STS** | **Pair_CLS** |
|
| 1064 |
-
| :-------------------: | :---------: | :-------: | :------------: | :-----------: | :-----------: | :-------: | :----------: |
|
| 1065 |
-
| gte-Qwen2-7B-instruct | 72.05 | 75.09 | 66.06 | 68.92 | 76.03 | 65.33 | 87.48 |
|
| 1066 |
-
| xiaobu-embedding-v2 | 72.43 | 74.67 | 65.17 | 72.58 | 76.5 | 64.53 | 91.87 |
|
| 1067 |
-
| **Conan-embedding-v1** | **72.
|
| 1068 |
-
|
| 1069 |
-
*More details will be available soon.*
|
| 1070 |
-
|
| 1071 |
-
---
|
| 1072 |
-
|
| 1073 |
-
**About**
|
| 1074 |
-
|
| 1075 |
-
Created by the Tencent BAC Group. All rights reserved.
|
| 1076 |
-
|
| 1077 |
-
**License**
|
| 1078 |
-
|
| 1079 |
This work is licensed under a [Creative Commons Attribution-NonCommercial 4.0 International License](https://creativecommons.org/licenses/by-nc/4.0/).
|
|
|
|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- mteb
|
| 4 |
+
model-index:
|
| 5 |
+
- name: conan-embedding
|
| 6 |
+
results:
|
| 7 |
+
- task:
|
| 8 |
+
type: STS
|
| 9 |
+
dataset:
|
| 10 |
+
type: C-MTEB/AFQMC
|
| 11 |
+
name: MTEB AFQMC
|
| 12 |
+
config: default
|
| 13 |
+
split: validation
|
| 14 |
+
revision: None
|
| 15 |
+
metrics:
|
| 16 |
+
- type: cos_sim_pearson
|
| 17 |
+
value: 56.613572467148856
|
| 18 |
+
- type: cos_sim_spearman
|
| 19 |
+
value: 60.66446211824284
|
| 20 |
+
- type: euclidean_pearson
|
| 21 |
+
value: 58.42080485872613
|
| 22 |
+
- type: euclidean_spearman
|
| 23 |
+
value: 59.82750030458164
|
| 24 |
+
- type: manhattan_pearson
|
| 25 |
+
value: 58.39885271199772
|
| 26 |
+
- type: manhattan_spearman
|
| 27 |
+
value: 59.817749720366734
|
| 28 |
+
- task:
|
| 29 |
+
type: STS
|
| 30 |
+
dataset:
|
| 31 |
+
type: C-MTEB/ATEC
|
| 32 |
+
name: MTEB ATEC
|
| 33 |
+
config: default
|
| 34 |
+
split: test
|
| 35 |
+
revision: None
|
| 36 |
+
metrics:
|
| 37 |
+
- type: cos_sim_pearson
|
| 38 |
+
value: 56.60530380552331
|
| 39 |
+
- type: cos_sim_spearman
|
| 40 |
+
value: 58.63822441736707
|
| 41 |
+
- type: euclidean_pearson
|
| 42 |
+
value: 62.18551665180664
|
| 43 |
+
- type: euclidean_spearman
|
| 44 |
+
value: 58.23168804495912
|
| 45 |
+
- type: manhattan_pearson
|
| 46 |
+
value: 62.17191480770053
|
| 47 |
+
- type: manhattan_spearman
|
| 48 |
+
value: 58.22556219601401
|
| 49 |
+
- task:
|
| 50 |
+
type: Classification
|
| 51 |
+
dataset:
|
| 52 |
+
type: mteb/amazon_reviews_multi
|
| 53 |
+
name: MTEB AmazonReviewsClassification (zh)
|
| 54 |
+
config: zh
|
| 55 |
+
split: test
|
| 56 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| 57 |
+
metrics:
|
| 58 |
+
- type: accuracy
|
| 59 |
+
value: 50.308
|
| 60 |
+
- type: f1
|
| 61 |
+
value: 46.927458607895126
|
| 62 |
+
- task:
|
| 63 |
+
type: STS
|
| 64 |
+
dataset:
|
| 65 |
+
type: C-MTEB/BQ
|
| 66 |
+
name: MTEB BQ
|
| 67 |
+
config: default
|
| 68 |
+
split: test
|
| 69 |
+
revision: None
|
| 70 |
+
metrics:
|
| 71 |
+
- type: cos_sim_pearson
|
| 72 |
+
value: 72.6472074172711
|
| 73 |
+
- type: cos_sim_spearman
|
| 74 |
+
value: 74.50748447236577
|
| 75 |
+
- type: euclidean_pearson
|
| 76 |
+
value: 72.51833296451854
|
| 77 |
+
- type: euclidean_spearman
|
| 78 |
+
value: 73.9898922606105
|
| 79 |
+
- type: manhattan_pearson
|
| 80 |
+
value: 72.50184948939338
|
| 81 |
+
- type: manhattan_spearman
|
| 82 |
+
value: 73.97797921509638
|
| 83 |
+
- task:
|
| 84 |
+
type: Clustering
|
| 85 |
+
dataset:
|
| 86 |
+
type: C-MTEB/CLSClusteringP2P
|
| 87 |
+
name: MTEB CLSClusteringP2P
|
| 88 |
+
config: default
|
| 89 |
+
split: test
|
| 90 |
+
revision: None
|
| 91 |
+
metrics:
|
| 92 |
+
- type: v_measure
|
| 93 |
+
value: 60.63545326048343
|
| 94 |
+
- task:
|
| 95 |
+
type: Clustering
|
| 96 |
+
dataset:
|
| 97 |
+
type: C-MTEB/CLSClusteringS2S
|
| 98 |
+
name: MTEB CLSClusteringS2S
|
| 99 |
+
config: default
|
| 100 |
+
split: test
|
| 101 |
+
revision: None
|
| 102 |
+
metrics:
|
| 103 |
+
- type: v_measure
|
| 104 |
+
value: 52.64834762325994
|
| 105 |
+
- task:
|
| 106 |
+
type: Reranking
|
| 107 |
+
dataset:
|
| 108 |
+
type: C-MTEB/CMedQAv1-reranking
|
| 109 |
+
name: MTEB CMedQAv1
|
| 110 |
+
config: default
|
| 111 |
+
split: test
|
| 112 |
+
revision: None
|
| 113 |
+
metrics:
|
| 114 |
+
- type: map
|
| 115 |
+
value: 91.38528814655234
|
| 116 |
+
- type: mrr
|
| 117 |
+
value: 93.35857142857144
|
| 118 |
+
- task:
|
| 119 |
+
type: Reranking
|
| 120 |
+
dataset:
|
| 121 |
+
type: C-MTEB/CMedQAv2-reranking
|
| 122 |
+
name: MTEB CMedQAv2
|
| 123 |
+
config: default
|
| 124 |
+
split: test
|
| 125 |
+
revision: None
|
| 126 |
+
metrics:
|
| 127 |
+
- type: map
|
| 128 |
+
value: 89.72084678877096
|
| 129 |
+
- type: mrr
|
| 130 |
+
value: 91.74380952380953
|
| 131 |
+
- task:
|
| 132 |
+
type: Retrieval
|
| 133 |
+
dataset:
|
| 134 |
+
type: C-MTEB/CmedqaRetrieval
|
| 135 |
+
name: MTEB CmedqaRetrieval
|
| 136 |
+
config: default
|
| 137 |
+
split: dev
|
| 138 |
+
revision: None
|
| 139 |
+
metrics:
|
| 140 |
+
- type: map_at_1
|
| 141 |
+
value: 26.987
|
| 142 |
+
- type: map_at_10
|
| 143 |
+
value: 40.675
|
| 144 |
+
- type: map_at_100
|
| 145 |
+
value: 42.495
|
| 146 |
+
- type: map_at_1000
|
| 147 |
+
value: 42.596000000000004
|
| 148 |
+
- type: map_at_3
|
| 149 |
+
value: 36.195
|
| 150 |
+
- type: map_at_5
|
| 151 |
+
value: 38.704
|
| 152 |
+
- type: mrr_at_1
|
| 153 |
+
value: 41.21
|
| 154 |
+
- type: mrr_at_10
|
| 155 |
+
value: 49.816
|
| 156 |
+
- type: mrr_at_100
|
| 157 |
+
value: 50.743
|
| 158 |
+
- type: mrr_at_1000
|
| 159 |
+
value: 50.77700000000001
|
| 160 |
+
- type: mrr_at_3
|
| 161 |
+
value: 47.312
|
| 162 |
+
- type: mrr_at_5
|
| 163 |
+
value: 48.699999999999996
|
| 164 |
+
- type: ndcg_at_1
|
| 165 |
+
value: 41.21
|
| 166 |
+
- type: ndcg_at_10
|
| 167 |
+
value: 47.606
|
| 168 |
+
- type: ndcg_at_100
|
| 169 |
+
value: 54.457
|
| 170 |
+
- type: ndcg_at_1000
|
| 171 |
+
value: 56.16100000000001
|
| 172 |
+
- type: ndcg_at_3
|
| 173 |
+
value: 42.108000000000004
|
| 174 |
+
- type: ndcg_at_5
|
| 175 |
+
value: 44.393
|
| 176 |
+
- type: precision_at_1
|
| 177 |
+
value: 41.21
|
| 178 |
+
- type: precision_at_10
|
| 179 |
+
value: 10.593
|
| 180 |
+
- type: precision_at_100
|
| 181 |
+
value: 1.609
|
| 182 |
+
- type: precision_at_1000
|
| 183 |
+
value: 0.183
|
| 184 |
+
- type: precision_at_3
|
| 185 |
+
value: 23.881
|
| 186 |
+
- type: precision_at_5
|
| 187 |
+
value: 17.339
|
| 188 |
+
- type: recall_at_1
|
| 189 |
+
value: 26.987
|
| 190 |
+
- type: recall_at_10
|
| 191 |
+
value: 58.875
|
| 192 |
+
- type: recall_at_100
|
| 193 |
+
value: 87.023
|
| 194 |
+
- type: recall_at_1000
|
| 195 |
+
value: 98.328
|
| 196 |
+
- type: recall_at_3
|
| 197 |
+
value: 42.265
|
| 198 |
+
- type: recall_at_5
|
| 199 |
+
value: 49.334
|
| 200 |
+
- task:
|
| 201 |
+
type: PairClassification
|
| 202 |
+
dataset:
|
| 203 |
+
type: C-MTEB/CMNLI
|
| 204 |
+
name: MTEB Cmnli
|
| 205 |
+
config: default
|
| 206 |
+
split: validation
|
| 207 |
+
revision: None
|
| 208 |
+
metrics:
|
| 209 |
+
- type: cos_sim_accuracy
|
| 210 |
+
value: 85.91701743836441
|
| 211 |
+
- type: cos_sim_ap
|
| 212 |
+
value: 92.53650618807644
|
| 213 |
+
- type: cos_sim_f1
|
| 214 |
+
value: 86.80265975431082
|
| 215 |
+
- type: cos_sim_precision
|
| 216 |
+
value: 83.79025239338556
|
| 217 |
+
- type: cos_sim_recall
|
| 218 |
+
value: 90.039747486556
|
| 219 |
+
- type: dot_accuracy
|
| 220 |
+
value: 77.17378232110643
|
| 221 |
+
- type: dot_ap
|
| 222 |
+
value: 85.40244368166546
|
| 223 |
+
- type: dot_f1
|
| 224 |
+
value: 79.03038001481951
|
| 225 |
+
- type: dot_precision
|
| 226 |
+
value: 72.20502901353966
|
| 227 |
+
- type: dot_recall
|
| 228 |
+
value: 87.2808043020809
|
| 229 |
+
- type: euclidean_accuracy
|
| 230 |
+
value: 84.65423932651834
|
| 231 |
+
- type: euclidean_ap
|
| 232 |
+
value: 91.47775530034588
|
| 233 |
+
- type: euclidean_f1
|
| 234 |
+
value: 85.64471499723298
|
| 235 |
+
- type: euclidean_precision
|
| 236 |
+
value: 81.31567885666246
|
| 237 |
+
- type: euclidean_recall
|
| 238 |
+
value: 90.46060322656068
|
| 239 |
+
- type: manhattan_accuracy
|
| 240 |
+
value: 84.58208057726999
|
| 241 |
+
- type: manhattan_ap
|
| 242 |
+
value: 91.46228709402014
|
| 243 |
+
- type: manhattan_f1
|
| 244 |
+
value: 85.6631626034444
|
| 245 |
+
- type: manhattan_precision
|
| 246 |
+
value: 82.10075026795283
|
| 247 |
+
- type: manhattan_recall
|
| 248 |
+
value: 89.5487491232172
|
| 249 |
+
- type: max_accuracy
|
| 250 |
+
value: 85.91701743836441
|
| 251 |
+
- type: max_ap
|
| 252 |
+
value: 92.53650618807644
|
| 253 |
+
- type: max_f1
|
| 254 |
+
value: 86.80265975431082
|
| 255 |
+
- task:
|
| 256 |
+
type: Retrieval
|
| 257 |
+
dataset:
|
| 258 |
+
type: C-MTEB/CovidRetrieval
|
| 259 |
+
name: MTEB CovidRetrieval
|
| 260 |
+
config: default
|
| 261 |
+
split: dev
|
| 262 |
+
revision: None
|
| 263 |
+
metrics:
|
| 264 |
+
- type: map_at_1
|
| 265 |
+
value: 83.693
|
| 266 |
+
- type: map_at_10
|
| 267 |
+
value: 90.098
|
| 268 |
+
- type: map_at_100
|
| 269 |
+
value: 90.145
|
| 270 |
+
- type: map_at_1000
|
| 271 |
+
value: 90.146
|
| 272 |
+
- type: map_at_3
|
| 273 |
+
value: 89.445
|
| 274 |
+
- type: map_at_5
|
| 275 |
+
value: 89.935
|
| 276 |
+
- type: mrr_at_1
|
| 277 |
+
value: 83.878
|
| 278 |
+
- type: mrr_at_10
|
| 279 |
+
value: 90.007
|
| 280 |
+
- type: mrr_at_100
|
| 281 |
+
value: 90.045
|
| 282 |
+
- type: mrr_at_1000
|
| 283 |
+
value: 90.046
|
| 284 |
+
- type: mrr_at_3
|
| 285 |
+
value: 89.34
|
| 286 |
+
- type: mrr_at_5
|
| 287 |
+
value: 89.835
|
| 288 |
+
- type: ndcg_at_1
|
| 289 |
+
value: 84.089
|
| 290 |
+
- type: ndcg_at_10
|
| 291 |
+
value: 92.351
|
| 292 |
+
- type: ndcg_at_100
|
| 293 |
+
value: 92.54599999999999
|
| 294 |
+
- type: ndcg_at_1000
|
| 295 |
+
value: 92.561
|
| 296 |
+
- type: ndcg_at_3
|
| 297 |
+
value: 91.15299999999999
|
| 298 |
+
- type: ndcg_at_5
|
| 299 |
+
value: 91.968
|
| 300 |
+
- type: precision_at_1
|
| 301 |
+
value: 84.089
|
| 302 |
+
- type: precision_at_10
|
| 303 |
+
value: 10.011000000000001
|
| 304 |
+
- type: precision_at_100
|
| 305 |
+
value: 1.009
|
| 306 |
+
- type: precision_at_1000
|
| 307 |
+
value: 0.101
|
| 308 |
+
- type: precision_at_3
|
| 309 |
+
value: 32.28
|
| 310 |
+
- type: precision_at_5
|
| 311 |
+
value: 19.789
|
| 312 |
+
- type: recall_at_1
|
| 313 |
+
value: 83.693
|
| 314 |
+
- type: recall_at_10
|
| 315 |
+
value: 99.05199999999999
|
| 316 |
+
- type: recall_at_100
|
| 317 |
+
value: 99.895
|
| 318 |
+
- type: recall_at_1000
|
| 319 |
+
value: 100.0
|
| 320 |
+
- type: recall_at_3
|
| 321 |
+
value: 95.917
|
| 322 |
+
- type: recall_at_5
|
| 323 |
+
value: 97.893
|
| 324 |
+
- task:
|
| 325 |
+
type: Retrieval
|
| 326 |
+
dataset:
|
| 327 |
+
type: C-MTEB/DuRetrieval
|
| 328 |
+
name: MTEB DuRetrieval
|
| 329 |
+
config: default
|
| 330 |
+
split: dev
|
| 331 |
+
revision: None
|
| 332 |
+
metrics:
|
| 333 |
+
- type: map_at_1
|
| 334 |
+
value: 26.924
|
| 335 |
+
- type: map_at_10
|
| 336 |
+
value: 81.392
|
| 337 |
+
- type: map_at_100
|
| 338 |
+
value: 84.209
|
| 339 |
+
- type: map_at_1000
|
| 340 |
+
value: 84.237
|
| 341 |
+
- type: map_at_3
|
| 342 |
+
value: 56.998000000000005
|
| 343 |
+
- type: map_at_5
|
| 344 |
+
value: 71.40100000000001
|
| 345 |
+
- type: mrr_at_1
|
| 346 |
+
value: 91.75
|
| 347 |
+
- type: mrr_at_10
|
| 348 |
+
value: 94.45
|
| 349 |
+
- type: mrr_at_100
|
| 350 |
+
value: 94.503
|
| 351 |
+
- type: mrr_at_1000
|
| 352 |
+
value: 94.505
|
| 353 |
+
- type: mrr_at_3
|
| 354 |
+
value: 94.258
|
| 355 |
+
- type: mrr_at_5
|
| 356 |
+
value: 94.381
|
| 357 |
+
- type: ndcg_at_1
|
| 358 |
+
value: 91.75
|
| 359 |
+
- type: ndcg_at_10
|
| 360 |
+
value: 88.53
|
| 361 |
+
- type: ndcg_at_100
|
| 362 |
+
value: 91.13900000000001
|
| 363 |
+
- type: ndcg_at_1000
|
| 364 |
+
value: 91.387
|
| 365 |
+
- type: ndcg_at_3
|
| 366 |
+
value: 87.925
|
| 367 |
+
- type: ndcg_at_5
|
| 368 |
+
value: 86.461
|
| 369 |
+
- type: precision_at_1
|
| 370 |
+
value: 91.75
|
| 371 |
+
- type: precision_at_10
|
| 372 |
+
value: 42.05
|
| 373 |
+
- type: precision_at_100
|
| 374 |
+
value: 4.827
|
| 375 |
+
- type: precision_at_1000
|
| 376 |
+
value: 0.48900000000000005
|
| 377 |
+
- type: precision_at_3
|
| 378 |
+
value: 78.55
|
| 379 |
+
- type: precision_at_5
|
| 380 |
+
value: 65.82000000000001
|
| 381 |
+
- type: recall_at_1
|
| 382 |
+
value: 26.924
|
| 383 |
+
- type: recall_at_10
|
| 384 |
+
value: 89.338
|
| 385 |
+
- type: recall_at_100
|
| 386 |
+
value: 97.856
|
| 387 |
+
- type: recall_at_1000
|
| 388 |
+
value: 99.11
|
| 389 |
+
- type: recall_at_3
|
| 390 |
+
value: 59.202999999999996
|
| 391 |
+
- type: recall_at_5
|
| 392 |
+
value: 75.642
|
| 393 |
+
- task:
|
| 394 |
+
type: Retrieval
|
| 395 |
+
dataset:
|
| 396 |
+
type: C-MTEB/EcomRetrieval
|
| 397 |
+
name: MTEB EcomRetrieval
|
| 398 |
+
config: default
|
| 399 |
+
split: dev
|
| 400 |
+
revision: None
|
| 401 |
+
metrics:
|
| 402 |
+
- type: map_at_1
|
| 403 |
+
value: 54.800000000000004
|
| 404 |
+
- type: map_at_10
|
| 405 |
+
value: 65.613
|
| 406 |
+
- type: map_at_100
|
| 407 |
+
value: 66.185
|
| 408 |
+
- type: map_at_1000
|
| 409 |
+
value: 66.191
|
| 410 |
+
- type: map_at_3
|
| 411 |
+
value: 62.8
|
| 412 |
+
- type: map_at_5
|
| 413 |
+
value: 64.535
|
| 414 |
+
- type: mrr_at_1
|
| 415 |
+
value: 54.800000000000004
|
| 416 |
+
- type: mrr_at_10
|
| 417 |
+
value: 65.613
|
| 418 |
+
- type: mrr_at_100
|
| 419 |
+
value: 66.185
|
| 420 |
+
- type: mrr_at_1000
|
| 421 |
+
value: 66.191
|
| 422 |
+
- type: mrr_at_3
|
| 423 |
+
value: 62.8
|
| 424 |
+
- type: mrr_at_5
|
| 425 |
+
value: 64.535
|
| 426 |
+
- type: ndcg_at_1
|
| 427 |
+
value: 54.800000000000004
|
| 428 |
+
- type: ndcg_at_10
|
| 429 |
+
value: 70.991
|
| 430 |
+
- type: ndcg_at_100
|
| 431 |
+
value: 73.434
|
| 432 |
+
- type: ndcg_at_1000
|
| 433 |
+
value: 73.587
|
| 434 |
+
- type: ndcg_at_3
|
| 435 |
+
value: 65.324
|
| 436 |
+
- type: ndcg_at_5
|
| 437 |
+
value: 68.431
|
| 438 |
+
- type: precision_at_1
|
| 439 |
+
value: 54.800000000000004
|
| 440 |
+
- type: precision_at_10
|
| 441 |
+
value: 8.790000000000001
|
| 442 |
+
- type: precision_at_100
|
| 443 |
+
value: 0.9860000000000001
|
| 444 |
+
- type: precision_at_1000
|
| 445 |
+
value: 0.1
|
| 446 |
+
- type: precision_at_3
|
| 447 |
+
value: 24.2
|
| 448 |
+
- type: precision_at_5
|
| 449 |
+
value: 16.02
|
| 450 |
+
- type: recall_at_1
|
| 451 |
+
value: 54.800000000000004
|
| 452 |
+
- type: recall_at_10
|
| 453 |
+
value: 87.9
|
| 454 |
+
- type: recall_at_100
|
| 455 |
+
value: 98.6
|
| 456 |
+
- type: recall_at_1000
|
| 457 |
+
value: 99.8
|
| 458 |
+
- type: recall_at_3
|
| 459 |
+
value: 72.6
|
| 460 |
+
- type: recall_at_5
|
| 461 |
+
value: 80.10000000000001
|
| 462 |
+
- task:
|
| 463 |
+
type: Classification
|
| 464 |
+
dataset:
|
| 465 |
+
type: C-MTEB/IFlyTek-classification
|
| 466 |
+
name: MTEB IFlyTek
|
| 467 |
+
config: default
|
| 468 |
+
split: validation
|
| 469 |
+
revision: None
|
| 470 |
+
metrics:
|
| 471 |
+
- type: accuracy
|
| 472 |
+
value: 51.94305502116199
|
| 473 |
+
- type: f1
|
| 474 |
+
value: 39.82197338426721
|
| 475 |
+
- task:
|
| 476 |
+
type: Classification
|
| 477 |
+
dataset:
|
| 478 |
+
type: C-MTEB/JDReview-classification
|
| 479 |
+
name: MTEB JDReview
|
| 480 |
+
config: default
|
| 481 |
+
split: test
|
| 482 |
+
revision: None
|
| 483 |
+
metrics:
|
| 484 |
+
- type: accuracy
|
| 485 |
+
value: 90.31894934333957
|
| 486 |
+
- type: ap
|
| 487 |
+
value: 63.89821836499594
|
| 488 |
+
- type: f1
|
| 489 |
+
value: 85.93687177603624
|
| 490 |
+
- task:
|
| 491 |
+
type: STS
|
| 492 |
+
dataset:
|
| 493 |
+
type: C-MTEB/LCQMC
|
| 494 |
+
name: MTEB LCQMC
|
| 495 |
+
config: default
|
| 496 |
+
split: test
|
| 497 |
+
revision: None
|
| 498 |
+
metrics:
|
| 499 |
+
- type: cos_sim_pearson
|
| 500 |
+
value: 73.18906216730208
|
| 501 |
+
- type: cos_sim_spearman
|
| 502 |
+
value: 79.44570226735877
|
| 503 |
+
- type: euclidean_pearson
|
| 504 |
+
value: 78.8105072242798
|
| 505 |
+
- type: euclidean_spearman
|
| 506 |
+
value: 79.15605680863212
|
| 507 |
+
- type: manhattan_pearson
|
| 508 |
+
value: 78.80576507484064
|
| 509 |
+
- type: manhattan_spearman
|
| 510 |
+
value: 79.14625534068364
|
| 511 |
+
- task:
|
| 512 |
+
type: Reranking
|
| 513 |
+
dataset:
|
| 514 |
+
type: C-MTEB/Mmarco-reranking
|
| 515 |
+
name: MTEB MMarcoReranking
|
| 516 |
+
config: default
|
| 517 |
+
split: dev
|
| 518 |
+
revision: None
|
| 519 |
+
metrics:
|
| 520 |
+
- type: map
|
| 521 |
+
value: 41.58107192600853
|
| 522 |
+
- type: mrr
|
| 523 |
+
value: 41.37063492063492
|
| 524 |
+
- task:
|
| 525 |
+
type: Retrieval
|
| 526 |
+
dataset:
|
| 527 |
+
type: C-MTEB/MMarcoRetrieval
|
| 528 |
+
name: MTEB MMarcoRetrieval
|
| 529 |
+
config: default
|
| 530 |
+
split: dev
|
| 531 |
+
revision: None
|
| 532 |
+
metrics:
|
| 533 |
+
- type: map_at_1
|
| 534 |
+
value: 68.33
|
| 535 |
+
- type: map_at_10
|
| 536 |
+
value: 78.261
|
| 537 |
+
- type: map_at_100
|
| 538 |
+
value: 78.522
|
| 539 |
+
- type: map_at_1000
|
| 540 |
+
value: 78.527
|
| 541 |
+
- type: map_at_3
|
| 542 |
+
value: 76.236
|
| 543 |
+
- type: map_at_5
|
| 544 |
+
value: 77.557
|
| 545 |
+
- type: mrr_at_1
|
| 546 |
+
value: 70.602
|
| 547 |
+
- type: mrr_at_10
|
| 548 |
+
value: 78.779
|
| 549 |
+
- type: mrr_at_100
|
| 550 |
+
value: 79.00500000000001
|
| 551 |
+
- type: mrr_at_1000
|
| 552 |
+
value: 79.01
|
| 553 |
+
- type: mrr_at_3
|
| 554 |
+
value: 77.037
|
| 555 |
+
- type: mrr_at_5
|
| 556 |
+
value: 78.157
|
| 557 |
+
- type: ndcg_at_1
|
| 558 |
+
value: 70.602
|
| 559 |
+
- type: ndcg_at_10
|
| 560 |
+
value: 82.254
|
| 561 |
+
- type: ndcg_at_100
|
| 562 |
+
value: 83.319
|
| 563 |
+
- type: ndcg_at_1000
|
| 564 |
+
value: 83.449
|
| 565 |
+
- type: ndcg_at_3
|
| 566 |
+
value: 78.46
|
| 567 |
+
- type: ndcg_at_5
|
| 568 |
+
value: 80.679
|
| 569 |
+
- type: precision_at_1
|
| 570 |
+
value: 70.602
|
| 571 |
+
- type: precision_at_10
|
| 572 |
+
value: 9.989
|
| 573 |
+
- type: precision_at_100
|
| 574 |
+
value: 1.05
|
| 575 |
+
- type: precision_at_1000
|
| 576 |
+
value: 0.106
|
| 577 |
+
- type: precision_at_3
|
| 578 |
+
value: 29.598999999999997
|
| 579 |
+
- type: precision_at_5
|
| 580 |
+
value: 18.948
|
| 581 |
+
- type: recall_at_1
|
| 582 |
+
value: 68.33
|
| 583 |
+
- type: recall_at_10
|
| 584 |
+
value: 94.00800000000001
|
| 585 |
+
- type: recall_at_100
|
| 586 |
+
value: 98.589
|
| 587 |
+
- type: recall_at_1000
|
| 588 |
+
value: 99.60799999999999
|
| 589 |
+
- type: recall_at_3
|
| 590 |
+
value: 84.057
|
| 591 |
+
- type: recall_at_5
|
| 592 |
+
value: 89.32900000000001
|
| 593 |
+
- task:
|
| 594 |
+
type: Classification
|
| 595 |
+
dataset:
|
| 596 |
+
type: mteb/amazon_massive_intent
|
| 597 |
+
name: MTEB MassiveIntentClassification (zh-CN)
|
| 598 |
+
config: zh-CN
|
| 599 |
+
split: test
|
| 600 |
+
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 601 |
+
metrics:
|
| 602 |
+
- type: accuracy
|
| 603 |
+
value: 78.13718897108272
|
| 604 |
+
- type: f1
|
| 605 |
+
value: 74.07613180855328
|
| 606 |
+
- task:
|
| 607 |
+
type: Classification
|
| 608 |
+
dataset:
|
| 609 |
+
type: mteb/amazon_massive_scenario
|
| 610 |
+
name: MTEB MassiveScenarioClassification (zh-CN)
|
| 611 |
+
config: zh-CN
|
| 612 |
+
split: test
|
| 613 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 614 |
+
metrics:
|
| 615 |
+
- type: accuracy
|
| 616 |
+
value: 86.20040349697376
|
| 617 |
+
- type: f1
|
| 618 |
+
value: 85.05282136519973
|
| 619 |
+
- task:
|
| 620 |
+
type: Retrieval
|
| 621 |
+
dataset:
|
| 622 |
+
type: C-MTEB/MedicalRetrieval
|
| 623 |
+
name: MTEB MedicalRetrieval
|
| 624 |
+
config: default
|
| 625 |
+
split: dev
|
| 626 |
+
revision: None
|
| 627 |
+
metrics:
|
| 628 |
+
- type: map_at_1
|
| 629 |
+
value: 56.8
|
| 630 |
+
- type: map_at_10
|
| 631 |
+
value: 64.199
|
| 632 |
+
- type: map_at_100
|
| 633 |
+
value: 64.89
|
| 634 |
+
- type: map_at_1000
|
| 635 |
+
value: 64.917
|
| 636 |
+
- type: map_at_3
|
| 637 |
+
value: 62.383
|
| 638 |
+
- type: map_at_5
|
| 639 |
+
value: 63.378
|
| 640 |
+
- type: mrr_at_1
|
| 641 |
+
value: 56.8
|
| 642 |
+
- type: mrr_at_10
|
| 643 |
+
value: 64.199
|
| 644 |
+
- type: mrr_at_100
|
| 645 |
+
value: 64.89
|
| 646 |
+
- type: mrr_at_1000
|
| 647 |
+
value: 64.917
|
| 648 |
+
- type: mrr_at_3
|
| 649 |
+
value: 62.383
|
| 650 |
+
- type: mrr_at_5
|
| 651 |
+
value: 63.378
|
| 652 |
+
- type: ndcg_at_1
|
| 653 |
+
value: 56.8
|
| 654 |
+
- type: ndcg_at_10
|
| 655 |
+
value: 67.944
|
| 656 |
+
- type: ndcg_at_100
|
| 657 |
+
value: 71.286
|
| 658 |
+
- type: ndcg_at_1000
|
| 659 |
+
value: 71.879
|
| 660 |
+
- type: ndcg_at_3
|
| 661 |
+
value: 64.163
|
| 662 |
+
- type: ndcg_at_5
|
| 663 |
+
value: 65.96600000000001
|
| 664 |
+
- type: precision_at_1
|
| 665 |
+
value: 56.8
|
| 666 |
+
- type: precision_at_10
|
| 667 |
+
value: 7.9799999999999995
|
| 668 |
+
- type: precision_at_100
|
| 669 |
+
value: 0.954
|
| 670 |
+
- type: precision_at_1000
|
| 671 |
+
value: 0.1
|
| 672 |
+
- type: precision_at_3
|
| 673 |
+
value: 23.1
|
| 674 |
+
- type: precision_at_5
|
| 675 |
+
value: 14.74
|
| 676 |
+
- type: recall_at_1
|
| 677 |
+
value: 56.8
|
| 678 |
+
- type: recall_at_10
|
| 679 |
+
value: 79.80000000000001
|
| 680 |
+
- type: recall_at_100
|
| 681 |
+
value: 95.39999999999999
|
| 682 |
+
- type: recall_at_1000
|
| 683 |
+
value: 99.8
|
| 684 |
+
- type: recall_at_3
|
| 685 |
+
value: 69.3
|
| 686 |
+
- type: recall_at_5
|
| 687 |
+
value: 73.7
|
| 688 |
+
- task:
|
| 689 |
+
type: Classification
|
| 690 |
+
dataset:
|
| 691 |
+
type: C-MTEB/MultilingualSentiment-classification
|
| 692 |
+
name: MTEB MultilingualSentiment
|
| 693 |
+
config: default
|
| 694 |
+
split: validation
|
| 695 |
+
revision: None
|
| 696 |
+
metrics:
|
| 697 |
+
- type: accuracy
|
| 698 |
+
value: 78.57666666666667
|
| 699 |
+
- type: f1
|
| 700 |
+
value: 78.23373528202681
|
| 701 |
+
- task:
|
| 702 |
+
type: PairClassification
|
| 703 |
+
dataset:
|
| 704 |
+
type: C-MTEB/OCNLI
|
| 705 |
+
name: MTEB Ocnli
|
| 706 |
+
config: default
|
| 707 |
+
split: validation
|
| 708 |
+
revision: None
|
| 709 |
+
metrics:
|
| 710 |
+
- type: cos_sim_accuracy
|
| 711 |
+
value: 85.43584190579317
|
| 712 |
+
- type: cos_sim_ap
|
| 713 |
+
value: 90.76665640338129
|
| 714 |
+
- type: cos_sim_f1
|
| 715 |
+
value: 86.5021770682148
|
| 716 |
+
- type: cos_sim_precision
|
| 717 |
+
value: 79.82142857142858
|
| 718 |
+
- type: cos_sim_recall
|
| 719 |
+
value: 94.40337909186906
|
| 720 |
+
- type: dot_accuracy
|
| 721 |
+
value: 78.66811044937737
|
| 722 |
+
- type: dot_ap
|
| 723 |
+
value: 85.84084363880804
|
| 724 |
+
- type: dot_f1
|
| 725 |
+
value: 80.10075566750629
|
| 726 |
+
- type: dot_precision
|
| 727 |
+
value: 76.58959537572254
|
| 728 |
+
- type: dot_recall
|
| 729 |
+
value: 83.9493136219641
|
| 730 |
+
- type: euclidean_accuracy
|
| 731 |
+
value: 84.46128857606931
|
| 732 |
+
- type: euclidean_ap
|
| 733 |
+
value: 88.62351100230491
|
| 734 |
+
- type: euclidean_f1
|
| 735 |
+
value: 85.7709469509172
|
| 736 |
+
- type: euclidean_precision
|
| 737 |
+
value: 80.8411214953271
|
| 738 |
+
- type: euclidean_recall
|
| 739 |
+
value: 91.34107708553326
|
| 740 |
+
- type: manhattan_accuracy
|
| 741 |
+
value: 84.51543042772063
|
| 742 |
+
- type: manhattan_ap
|
| 743 |
+
value: 88.53975607870393
|
| 744 |
+
- type: manhattan_f1
|
| 745 |
+
value: 85.75697211155378
|
| 746 |
+
- type: manhattan_precision
|
| 747 |
+
value: 81.14985862393968
|
| 748 |
+
- type: manhattan_recall
|
| 749 |
+
value: 90.91869060190075
|
| 750 |
+
- type: max_accuracy
|
| 751 |
+
value: 85.43584190579317
|
| 752 |
+
- type: max_ap
|
| 753 |
+
value: 90.76665640338129
|
| 754 |
+
- type: max_f1
|
| 755 |
+
value: 86.5021770682148
|
| 756 |
+
- task:
|
| 757 |
+
type: Classification
|
| 758 |
+
dataset:
|
| 759 |
+
type: C-MTEB/OnlineShopping-classification
|
| 760 |
+
name: MTEB OnlineShopping
|
| 761 |
+
config: default
|
| 762 |
+
split: test
|
| 763 |
+
revision: None
|
| 764 |
+
metrics:
|
| 765 |
+
- type: accuracy
|
| 766 |
+
value: 95.06999999999998
|
| 767 |
+
- type: ap
|
| 768 |
+
value: 93.45104559324996
|
| 769 |
+
- type: f1
|
| 770 |
+
value: 95.06036329426092
|
| 771 |
+
- task:
|
| 772 |
+
type: STS
|
| 773 |
+
dataset:
|
| 774 |
+
type: C-MTEB/PAWSX
|
| 775 |
+
name: MTEB PAWSX
|
| 776 |
+
config: default
|
| 777 |
+
split: test
|
| 778 |
+
revision: None
|
| 779 |
+
metrics:
|
| 780 |
+
- type: cos_sim_pearson
|
| 781 |
+
value: 40.01998290519605
|
| 782 |
+
- type: cos_sim_spearman
|
| 783 |
+
value: 46.5989769986853
|
| 784 |
+
- type: euclidean_pearson
|
| 785 |
+
value: 45.37905883182924
|
| 786 |
+
- type: euclidean_spearman
|
| 787 |
+
value: 46.22213849806378
|
| 788 |
+
- type: manhattan_pearson
|
| 789 |
+
value: 45.40925124776211
|
| 790 |
+
- type: manhattan_spearman
|
| 791 |
+
value: 46.250705124226386
|
| 792 |
+
- task:
|
| 793 |
+
type: STS
|
| 794 |
+
dataset:
|
| 795 |
+
type: C-MTEB/QBQTC
|
| 796 |
+
name: MTEB QBQTC
|
| 797 |
+
config: default
|
| 798 |
+
split: test
|
| 799 |
+
revision: None
|
| 800 |
+
metrics:
|
| 801 |
+
- type: cos_sim_pearson
|
| 802 |
+
value: 42.719516197112526
|
| 803 |
+
- type: cos_sim_spearman
|
| 804 |
+
value: 44.57507789581106
|
| 805 |
+
- type: euclidean_pearson
|
| 806 |
+
value: 35.73062264160721
|
| 807 |
+
- type: euclidean_spearman
|
| 808 |
+
value: 40.473523909913695
|
| 809 |
+
- type: manhattan_pearson
|
| 810 |
+
value: 35.69868964086357
|
| 811 |
+
- type: manhattan_spearman
|
| 812 |
+
value: 40.46349925372903
|
| 813 |
+
- task:
|
| 814 |
+
type: STS
|
| 815 |
+
dataset:
|
| 816 |
+
type: mteb/sts22-crosslingual-sts
|
| 817 |
+
name: MTEB STS22 (zh)
|
| 818 |
+
config: zh
|
| 819 |
+
split: test
|
| 820 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 821 |
+
metrics:
|
| 822 |
+
- type: cos_sim_pearson
|
| 823 |
+
value: 62.340118285801104
|
| 824 |
+
- type: cos_sim_spearman
|
| 825 |
+
value: 67.72781908620632
|
| 826 |
+
- type: euclidean_pearson
|
| 827 |
+
value: 63.161965746091596
|
| 828 |
+
- type: euclidean_spearman
|
| 829 |
+
value: 67.36825684340769
|
| 830 |
+
- type: manhattan_pearson
|
| 831 |
+
value: 63.089863788261425
|
| 832 |
+
- type: manhattan_spearman
|
| 833 |
+
value: 67.40868898995384
|
| 834 |
+
- task:
|
| 835 |
+
type: STS
|
| 836 |
+
dataset:
|
| 837 |
+
type: C-MTEB/STSB
|
| 838 |
+
name: MTEB STSB
|
| 839 |
+
config: default
|
| 840 |
+
split: test
|
| 841 |
+
revision: None
|
| 842 |
+
metrics:
|
| 843 |
+
- type: cos_sim_pearson
|
| 844 |
+
value: 79.1646360962365
|
| 845 |
+
- type: cos_sim_spearman
|
| 846 |
+
value: 81.24426700767087
|
| 847 |
+
- type: euclidean_pearson
|
| 848 |
+
value: 79.43826409936123
|
| 849 |
+
- type: euclidean_spearman
|
| 850 |
+
value: 79.71787965300125
|
| 851 |
+
- type: manhattan_pearson
|
| 852 |
+
value: 79.43377784961737
|
| 853 |
+
- type: manhattan_spearman
|
| 854 |
+
value: 79.69348376886967
|
| 855 |
+
- task:
|
| 856 |
+
type: Reranking
|
| 857 |
+
dataset:
|
| 858 |
+
type: C-MTEB/T2Reranking
|
| 859 |
+
name: MTEB T2Reranking
|
| 860 |
+
config: default
|
| 861 |
+
split: dev
|
| 862 |
+
revision: None
|
| 863 |
+
metrics:
|
| 864 |
+
- type: map
|
| 865 |
+
value: 68.35595092507496
|
| 866 |
+
- type: mrr
|
| 867 |
+
value: 79.00244892585788
|
| 868 |
+
- task:
|
| 869 |
+
type: Retrieval
|
| 870 |
+
dataset:
|
| 871 |
+
type: C-MTEB/T2Retrieval
|
| 872 |
+
name: MTEB T2Retrieval
|
| 873 |
+
config: default
|
| 874 |
+
split: dev
|
| 875 |
+
revision: None
|
| 876 |
+
metrics:
|
| 877 |
+
- type: map_at_1
|
| 878 |
+
value: 26.588
|
| 879 |
+
- type: map_at_10
|
| 880 |
+
value: 75.327
|
| 881 |
+
- type: map_at_100
|
| 882 |
+
value: 79.095
|
| 883 |
+
- type: map_at_1000
|
| 884 |
+
value: 79.163
|
| 885 |
+
- type: map_at_3
|
| 886 |
+
value: 52.637
|
| 887 |
+
- type: map_at_5
|
| 888 |
+
value: 64.802
|
| 889 |
+
- type: mrr_at_1
|
| 890 |
+
value: 88.103
|
| 891 |
+
- type: mrr_at_10
|
| 892 |
+
value: 91.29899999999999
|
| 893 |
+
- type: mrr_at_100
|
| 894 |
+
value: 91.408
|
| 895 |
+
- type: mrr_at_1000
|
| 896 |
+
value: 91.411
|
| 897 |
+
- type: mrr_at_3
|
| 898 |
+
value: 90.801
|
| 899 |
+
- type: mrr_at_5
|
| 900 |
+
value: 91.12700000000001
|
| 901 |
+
- type: ndcg_at_1
|
| 902 |
+
value: 88.103
|
| 903 |
+
- type: ndcg_at_10
|
| 904 |
+
value: 83.314
|
| 905 |
+
- type: ndcg_at_100
|
| 906 |
+
value: 87.201
|
| 907 |
+
- type: ndcg_at_1000
|
| 908 |
+
value: 87.83999999999999
|
| 909 |
+
- type: ndcg_at_3
|
| 910 |
+
value: 84.408
|
| 911 |
+
- type: ndcg_at_5
|
| 912 |
+
value: 83.078
|
| 913 |
+
- type: precision_at_1
|
| 914 |
+
value: 88.103
|
| 915 |
+
- type: precision_at_10
|
| 916 |
+
value: 41.638999999999996
|
| 917 |
+
- type: precision_at_100
|
| 918 |
+
value: 5.006
|
| 919 |
+
- type: precision_at_1000
|
| 920 |
+
value: 0.516
|
| 921 |
+
- type: precision_at_3
|
| 922 |
+
value: 73.942
|
| 923 |
+
- type: precision_at_5
|
| 924 |
+
value: 62.056
|
| 925 |
+
- type: recall_at_1
|
| 926 |
+
value: 26.588
|
| 927 |
+
- type: recall_at_10
|
| 928 |
+
value: 82.819
|
| 929 |
+
- type: recall_at_100
|
| 930 |
+
value: 95.334
|
| 931 |
+
- type: recall_at_1000
|
| 932 |
+
value: 98.51299999999999
|
| 933 |
+
- type: recall_at_3
|
| 934 |
+
value: 54.74
|
| 935 |
+
- type: recall_at_5
|
| 936 |
+
value: 68.864
|
| 937 |
+
- task:
|
| 938 |
+
type: Classification
|
| 939 |
+
dataset:
|
| 940 |
+
type: C-MTEB/TNews-classification
|
| 941 |
+
name: MTEB TNews
|
| 942 |
+
config: default
|
| 943 |
+
split: validation
|
| 944 |
+
revision: None
|
| 945 |
+
metrics:
|
| 946 |
+
- type: accuracy
|
| 947 |
+
value: 55.029
|
| 948 |
+
- type: f1
|
| 949 |
+
value: 53.043617905026764
|
| 950 |
+
- task:
|
| 951 |
+
type: Clustering
|
| 952 |
+
dataset:
|
| 953 |
+
type: C-MTEB/ThuNewsClusteringP2P
|
| 954 |
+
name: MTEB ThuNewsClusteringP2P
|
| 955 |
+
config: default
|
| 956 |
+
split: test
|
| 957 |
+
revision: None
|
| 958 |
+
metrics:
|
| 959 |
+
- type: v_measure
|
| 960 |
+
value: 77.83675116835911
|
| 961 |
+
- task:
|
| 962 |
+
type: Clustering
|
| 963 |
+
dataset:
|
| 964 |
+
type: C-MTEB/ThuNewsClusteringS2S
|
| 965 |
+
name: MTEB ThuNewsClusteringS2S
|
| 966 |
+
config: default
|
| 967 |
+
split: test
|
| 968 |
+
revision: None
|
| 969 |
+
metrics:
|
| 970 |
+
- type: v_measure
|
| 971 |
+
value: 74.19701455865277
|
| 972 |
+
- task:
|
| 973 |
+
type: Retrieval
|
| 974 |
+
dataset:
|
| 975 |
+
type: C-MTEB/VideoRetrieval
|
| 976 |
+
name: MTEB VideoRetrieval
|
| 977 |
+
config: default
|
| 978 |
+
split: dev
|
| 979 |
+
revision: None
|
| 980 |
+
metrics:
|
| 981 |
+
- type: map_at_1
|
| 982 |
+
value: 64.7
|
| 983 |
+
- type: map_at_10
|
| 984 |
+
value: 75.593
|
| 985 |
+
- type: map_at_100
|
| 986 |
+
value: 75.863
|
| 987 |
+
- type: map_at_1000
|
| 988 |
+
value: 75.863
|
| 989 |
+
- type: map_at_3
|
| 990 |
+
value: 73.63300000000001
|
| 991 |
+
- type: map_at_5
|
| 992 |
+
value: 74.923
|
| 993 |
+
- type: mrr_at_1
|
| 994 |
+
value: 64.7
|
| 995 |
+
- type: mrr_at_10
|
| 996 |
+
value: 75.593
|
| 997 |
+
- type: mrr_at_100
|
| 998 |
+
value: 75.863
|
| 999 |
+
- type: mrr_at_1000
|
| 1000 |
+
value: 75.863
|
| 1001 |
+
- type: mrr_at_3
|
| 1002 |
+
value: 73.63300000000001
|
| 1003 |
+
- type: mrr_at_5
|
| 1004 |
+
value: 74.923
|
| 1005 |
+
- type: ndcg_at_1
|
| 1006 |
+
value: 64.7
|
| 1007 |
+
- type: ndcg_at_10
|
| 1008 |
+
value: 80.399
|
| 1009 |
+
- type: ndcg_at_100
|
| 1010 |
+
value: 81.517
|
| 1011 |
+
- type: ndcg_at_1000
|
| 1012 |
+
value: 81.517
|
| 1013 |
+
- type: ndcg_at_3
|
| 1014 |
+
value: 76.504
|
| 1015 |
+
- type: ndcg_at_5
|
| 1016 |
+
value: 78.79899999999999
|
| 1017 |
+
- type: precision_at_1
|
| 1018 |
+
value: 64.7
|
| 1019 |
+
- type: precision_at_10
|
| 1020 |
+
value: 9.520000000000001
|
| 1021 |
+
- type: precision_at_100
|
| 1022 |
+
value: 1.0
|
| 1023 |
+
- type: precision_at_1000
|
| 1024 |
+
value: 0.1
|
| 1025 |
+
- type: precision_at_3
|
| 1026 |
+
value: 28.266999999999996
|
| 1027 |
+
- type: precision_at_5
|
| 1028 |
+
value: 18.060000000000002
|
| 1029 |
+
- type: recall_at_1
|
| 1030 |
+
value: 64.7
|
| 1031 |
+
- type: recall_at_10
|
| 1032 |
+
value: 95.19999999999999
|
| 1033 |
+
- type: recall_at_100
|
| 1034 |
+
value: 100.0
|
| 1035 |
+
- type: recall_at_1000
|
| 1036 |
+
value: 100.0
|
| 1037 |
+
- type: recall_at_3
|
| 1038 |
+
value: 84.8
|
| 1039 |
+
- type: recall_at_5
|
| 1040 |
+
value: 90.3
|
| 1041 |
+
- task:
|
| 1042 |
+
type: Classification
|
| 1043 |
+
dataset:
|
| 1044 |
+
type: C-MTEB/waimai-classification
|
| 1045 |
+
name: MTEB Waimai
|
| 1046 |
+
config: default
|
| 1047 |
+
split: test
|
| 1048 |
+
revision: None
|
| 1049 |
+
metrics:
|
| 1050 |
+
- type: accuracy
|
| 1051 |
+
value: 89.69999999999999
|
| 1052 |
+
- type: ap
|
| 1053 |
+
value: 75.91371640164184
|
| 1054 |
+
- type: f1
|
| 1055 |
+
value: 88.34067777698694
|
| 1056 |
+
license: cc-by-nc-4.0
|
| 1057 |
+
---
|
| 1058 |
+
|
| 1059 |
+
# Conan-embedding-v1
|
| 1060 |
+
|
| 1061 |
+
## Performance
|
| 1062 |
+
|
| 1063 |
+
| Model | **Average** | **CLS** | **Clustering** | **Reranking** | **Retrieval** | **STS** | **Pair_CLS** |
|
| 1064 |
+
| :-------------------: | :---------: | :-------: | :------------: | :-----------: | :-----------: | :-------: | :----------: |
|
| 1065 |
+
| gte-Qwen2-7B-instruct | 72.05 | 75.09 | 66.06 | 68.92 | 76.03 | 65.33 | 87.48 |
|
| 1066 |
+
| xiaobu-embedding-v2 | 72.43 | 74.67 | 65.17 | 72.58 | 76.5 | 64.53 | 91.87 |
|
| 1067 |
+
| **Conan-embedding-v1** | **72.62** | 75.03 | 66.33 | 72.76 | 76.67 | 64.18 | 91.66 |
|
| 1068 |
+
|
| 1069 |
+
*More details will be available soon.*
|
| 1070 |
+
|
| 1071 |
+
---
|
| 1072 |
+
|
| 1073 |
+
**About**
|
| 1074 |
+
|
| 1075 |
+
Created by the Tencent BAC Group. All rights reserved.
|
| 1076 |
+
|
| 1077 |
+
**License**
|
| 1078 |
+
|
| 1079 |
This work is licensed under a [Creative Commons Attribution-NonCommercial 4.0 International License](https://creativecommons.org/licenses/by-nc/4.0/).
|