| --- |
| pipeline_tag: sentence-similarity |
| tags: |
| - sentence-transformers |
| - feature-extraction |
| - sentence-similarity |
| - transformers |
| - mteb |
| model-index: |
| - name: bge_micro |
| results: |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (en) |
| config: en |
| split: test |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| metrics: |
| - type: accuracy |
| value: 67.76119402985074 |
| - type: ap |
| value: 29.637849284211114 |
| - type: f1 |
| value: 61.31181187111905 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_polarity |
| name: MTEB AmazonPolarityClassification |
| config: default |
| split: test |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| metrics: |
| - type: accuracy |
| value: 79.7547 |
| - type: ap |
| value: 74.21401629809145 |
| - type: f1 |
| value: 79.65319615433783 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (en) |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 37.452000000000005 |
| - type: f1 |
| value: 37.0245198854966 |
| - task: |
| type: Retrieval |
| dataset: |
| type: arguana |
| name: MTEB ArguAna |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 31.152 |
| - type: map_at_10 |
| value: 46.702 |
| - type: map_at_100 |
| value: 47.563 |
| - type: map_at_1000 |
| value: 47.567 |
| - type: map_at_3 |
| value: 42.058 |
| - type: map_at_5 |
| value: 44.608 |
| - type: mrr_at_1 |
| value: 32.006 |
| - type: mrr_at_10 |
| value: 47.064 |
| - type: mrr_at_100 |
| value: 47.910000000000004 |
| - type: mrr_at_1000 |
| value: 47.915 |
| - type: mrr_at_3 |
| value: 42.283 |
| - type: mrr_at_5 |
| value: 44.968 |
| - type: ndcg_at_1 |
| value: 31.152 |
| - type: ndcg_at_10 |
| value: 55.308 |
| - type: ndcg_at_100 |
| value: 58.965 |
| - type: ndcg_at_1000 |
| value: 59.067 |
| - type: ndcg_at_3 |
| value: 45.698 |
| - type: ndcg_at_5 |
| value: 50.296 |
| - type: precision_at_1 |
| value: 31.152 |
| - type: precision_at_10 |
| value: 8.279 |
| - type: precision_at_100 |
| value: 0.987 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_3 |
| value: 18.753 |
| - type: precision_at_5 |
| value: 13.485 |
| - type: recall_at_1 |
| value: 31.152 |
| - type: recall_at_10 |
| value: 82.788 |
| - type: recall_at_100 |
| value: 98.72 |
| - type: recall_at_1000 |
| value: 99.502 |
| - type: recall_at_3 |
| value: 56.259 |
| - type: recall_at_5 |
| value: 67.425 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-p2p |
| name: MTEB ArxivClusteringP2P |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 44.52692241938116 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-s2s |
| name: MTEB ArxivClusteringS2S |
| config: default |
| split: test |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| metrics: |
| - type: v_measure |
| value: 33.245710292773595 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/askubuntudupquestions-reranking |
| name: MTEB AskUbuntuDupQuestions |
| config: default |
| split: test |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| metrics: |
| - type: map |
| value: 58.08493637155168 |
| - type: mrr |
| value: 71.94378490084861 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/biosses-sts |
| name: MTEB BIOSSES |
| config: default |
| split: test |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| metrics: |
| - type: cos_sim_pearson |
| value: 84.1602804378326 |
| - type: cos_sim_spearman |
| value: 82.92478106365587 |
| - type: euclidean_pearson |
| value: 82.27930167277077 |
| - type: euclidean_spearman |
| value: 82.18560759458093 |
| - type: manhattan_pearson |
| value: 82.34277425888187 |
| - type: manhattan_spearman |
| value: 81.72776583704467 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/banking77 |
| name: MTEB Banking77Classification |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 81.17207792207792 |
| - type: f1 |
| value: 81.09893836310513 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-p2p |
| name: MTEB BiorxivClusteringP2P |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 36.109308463095516 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-s2s |
| name: MTEB BiorxivClusteringS2S |
| config: default |
| split: test |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| metrics: |
| - type: v_measure |
| value: 28.06048212317168 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackAndroidRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 28.233999999999998 |
| - type: map_at_10 |
| value: 38.092999999999996 |
| - type: map_at_100 |
| value: 39.473 |
| - type: map_at_1000 |
| value: 39.614 |
| - type: map_at_3 |
| value: 34.839 |
| - type: map_at_5 |
| value: 36.523 |
| - type: mrr_at_1 |
| value: 35.193000000000005 |
| - type: mrr_at_10 |
| value: 44.089 |
| - type: mrr_at_100 |
| value: 44.927 |
| - type: mrr_at_1000 |
| value: 44.988 |
| - type: mrr_at_3 |
| value: 41.559000000000005 |
| - type: mrr_at_5 |
| value: 43.162 |
| - type: ndcg_at_1 |
| value: 35.193000000000005 |
| - type: ndcg_at_10 |
| value: 44.04 |
| - type: ndcg_at_100 |
| value: 49.262 |
| - type: ndcg_at_1000 |
| value: 51.847 |
| - type: ndcg_at_3 |
| value: 39.248 |
| - type: ndcg_at_5 |
| value: 41.298 |
| - type: precision_at_1 |
| value: 35.193000000000005 |
| - type: precision_at_10 |
| value: 8.555 |
| - type: precision_at_100 |
| value: 1.3820000000000001 |
| - type: precision_at_1000 |
| value: 0.189 |
| - type: precision_at_3 |
| value: 19.123 |
| - type: precision_at_5 |
| value: 13.648 |
| - type: recall_at_1 |
| value: 28.233999999999998 |
| - type: recall_at_10 |
| value: 55.094 |
| - type: recall_at_100 |
| value: 76.85300000000001 |
| - type: recall_at_1000 |
| value: 94.163 |
| - type: recall_at_3 |
| value: 40.782000000000004 |
| - type: recall_at_5 |
| value: 46.796 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackEnglishRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 21.538 |
| - type: map_at_10 |
| value: 28.449 |
| - type: map_at_100 |
| value: 29.471000000000004 |
| - type: map_at_1000 |
| value: 29.599999999999998 |
| - type: map_at_3 |
| value: 26.371 |
| - type: map_at_5 |
| value: 27.58 |
| - type: mrr_at_1 |
| value: 26.815 |
| - type: mrr_at_10 |
| value: 33.331 |
| - type: mrr_at_100 |
| value: 34.114 |
| - type: mrr_at_1000 |
| value: 34.182 |
| - type: mrr_at_3 |
| value: 31.561 |
| - type: mrr_at_5 |
| value: 32.608 |
| - type: ndcg_at_1 |
| value: 26.815 |
| - type: ndcg_at_10 |
| value: 32.67 |
| - type: ndcg_at_100 |
| value: 37.039 |
| - type: ndcg_at_1000 |
| value: 39.769 |
| - type: ndcg_at_3 |
| value: 29.523 |
| - type: ndcg_at_5 |
| value: 31.048 |
| - type: precision_at_1 |
| value: 26.815 |
| - type: precision_at_10 |
| value: 5.955 |
| - type: precision_at_100 |
| value: 1.02 |
| - type: precision_at_1000 |
| value: 0.152 |
| - type: precision_at_3 |
| value: 14.033999999999999 |
| - type: precision_at_5 |
| value: 9.911 |
| - type: recall_at_1 |
| value: 21.538 |
| - type: recall_at_10 |
| value: 40.186 |
| - type: recall_at_100 |
| value: 58.948 |
| - type: recall_at_1000 |
| value: 77.158 |
| - type: recall_at_3 |
| value: 30.951 |
| - type: recall_at_5 |
| value: 35.276 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackGamingRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 35.211999999999996 |
| - type: map_at_10 |
| value: 46.562 |
| - type: map_at_100 |
| value: 47.579 |
| - type: map_at_1000 |
| value: 47.646 |
| - type: map_at_3 |
| value: 43.485 |
| - type: map_at_5 |
| value: 45.206 |
| - type: mrr_at_1 |
| value: 40.627 |
| - type: mrr_at_10 |
| value: 49.928 |
| - type: mrr_at_100 |
| value: 50.647 |
| - type: mrr_at_1000 |
| value: 50.685 |
| - type: mrr_at_3 |
| value: 47.513 |
| - type: mrr_at_5 |
| value: 48.958 |
| - type: ndcg_at_1 |
| value: 40.627 |
| - type: ndcg_at_10 |
| value: 52.217 |
| - type: ndcg_at_100 |
| value: 56.423 |
| - type: ndcg_at_1000 |
| value: 57.821999999999996 |
| - type: ndcg_at_3 |
| value: 46.949000000000005 |
| - type: ndcg_at_5 |
| value: 49.534 |
| - type: precision_at_1 |
| value: 40.627 |
| - type: precision_at_10 |
| value: 8.476 |
| - type: precision_at_100 |
| value: 1.15 |
| - type: precision_at_1000 |
| value: 0.132 |
| - type: precision_at_3 |
| value: 21.003 |
| - type: precision_at_5 |
| value: 14.469999999999999 |
| - type: recall_at_1 |
| value: 35.211999999999996 |
| - type: recall_at_10 |
| value: 65.692 |
| - type: recall_at_100 |
| value: 84.011 |
| - type: recall_at_1000 |
| value: 94.03099999999999 |
| - type: recall_at_3 |
| value: 51.404 |
| - type: recall_at_5 |
| value: 57.882 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackGisRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 22.09 |
| - type: map_at_10 |
| value: 29.516 |
| - type: map_at_100 |
| value: 30.462 |
| - type: map_at_1000 |
| value: 30.56 |
| - type: map_at_3 |
| value: 26.945000000000004 |
| - type: map_at_5 |
| value: 28.421999999999997 |
| - type: mrr_at_1 |
| value: 23.616 |
| - type: mrr_at_10 |
| value: 31.221 |
| - type: mrr_at_100 |
| value: 32.057 |
| - type: mrr_at_1000 |
| value: 32.137 |
| - type: mrr_at_3 |
| value: 28.738000000000003 |
| - type: mrr_at_5 |
| value: 30.156 |
| - type: ndcg_at_1 |
| value: 23.616 |
| - type: ndcg_at_10 |
| value: 33.97 |
| - type: ndcg_at_100 |
| value: 38.806000000000004 |
| - type: ndcg_at_1000 |
| value: 41.393 |
| - type: ndcg_at_3 |
| value: 28.908 |
| - type: ndcg_at_5 |
| value: 31.433 |
| - type: precision_at_1 |
| value: 23.616 |
| - type: precision_at_10 |
| value: 5.299 |
| - type: precision_at_100 |
| value: 0.812 |
| - type: precision_at_1000 |
| value: 0.107 |
| - type: precision_at_3 |
| value: 12.015 |
| - type: precision_at_5 |
| value: 8.701 |
| - type: recall_at_1 |
| value: 22.09 |
| - type: recall_at_10 |
| value: 46.089999999999996 |
| - type: recall_at_100 |
| value: 68.729 |
| - type: recall_at_1000 |
| value: 88.435 |
| - type: recall_at_3 |
| value: 32.584999999999994 |
| - type: recall_at_5 |
| value: 38.550000000000004 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackMathematicaRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 15.469 |
| - type: map_at_10 |
| value: 22.436 |
| - type: map_at_100 |
| value: 23.465 |
| - type: map_at_1000 |
| value: 23.608999999999998 |
| - type: map_at_3 |
| value: 19.716 |
| - type: map_at_5 |
| value: 21.182000000000002 |
| - type: mrr_at_1 |
| value: 18.905 |
| - type: mrr_at_10 |
| value: 26.55 |
| - type: mrr_at_100 |
| value: 27.46 |
| - type: mrr_at_1000 |
| value: 27.553 |
| - type: mrr_at_3 |
| value: 23.921999999999997 |
| - type: mrr_at_5 |
| value: 25.302999999999997 |
| - type: ndcg_at_1 |
| value: 18.905 |
| - type: ndcg_at_10 |
| value: 27.437 |
| - type: ndcg_at_100 |
| value: 32.555 |
| - type: ndcg_at_1000 |
| value: 35.885 |
| - type: ndcg_at_3 |
| value: 22.439 |
| - type: ndcg_at_5 |
| value: 24.666 |
| - type: precision_at_1 |
| value: 18.905 |
| - type: precision_at_10 |
| value: 5.2490000000000006 |
| - type: precision_at_100 |
| value: 0.889 |
| - type: precision_at_1000 |
| value: 0.131 |
| - type: precision_at_3 |
| value: 10.862 |
| - type: precision_at_5 |
| value: 8.085 |
| - type: recall_at_1 |
| value: 15.469 |
| - type: recall_at_10 |
| value: 38.706 |
| - type: recall_at_100 |
| value: 61.242 |
| - type: recall_at_1000 |
| value: 84.84 |
| - type: recall_at_3 |
| value: 24.973 |
| - type: recall_at_5 |
| value: 30.603 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackPhysicsRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 24.918000000000003 |
| - type: map_at_10 |
| value: 34.296 |
| - type: map_at_100 |
| value: 35.632000000000005 |
| - type: map_at_1000 |
| value: 35.748999999999995 |
| - type: map_at_3 |
| value: 31.304 |
| - type: map_at_5 |
| value: 33.166000000000004 |
| - type: mrr_at_1 |
| value: 30.703000000000003 |
| - type: mrr_at_10 |
| value: 39.655 |
| - type: mrr_at_100 |
| value: 40.569 |
| - type: mrr_at_1000 |
| value: 40.621 |
| - type: mrr_at_3 |
| value: 37.023 |
| - type: mrr_at_5 |
| value: 38.664 |
| - type: ndcg_at_1 |
| value: 30.703000000000003 |
| - type: ndcg_at_10 |
| value: 39.897 |
| - type: ndcg_at_100 |
| value: 45.777 |
| - type: ndcg_at_1000 |
| value: 48.082 |
| - type: ndcg_at_3 |
| value: 35.122 |
| - type: ndcg_at_5 |
| value: 37.691 |
| - type: precision_at_1 |
| value: 30.703000000000003 |
| - type: precision_at_10 |
| value: 7.305000000000001 |
| - type: precision_at_100 |
| value: 1.208 |
| - type: precision_at_1000 |
| value: 0.159 |
| - type: precision_at_3 |
| value: 16.811 |
| - type: precision_at_5 |
| value: 12.203999999999999 |
| - type: recall_at_1 |
| value: 24.918000000000003 |
| - type: recall_at_10 |
| value: 51.31 |
| - type: recall_at_100 |
| value: 76.534 |
| - type: recall_at_1000 |
| value: 91.911 |
| - type: recall_at_3 |
| value: 37.855 |
| - type: recall_at_5 |
| value: 44.493 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackProgrammersRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 22.416 |
| - type: map_at_10 |
| value: 30.474 |
| - type: map_at_100 |
| value: 31.759999999999998 |
| - type: map_at_1000 |
| value: 31.891000000000002 |
| - type: map_at_3 |
| value: 27.728 |
| - type: map_at_5 |
| value: 29.247 |
| - type: mrr_at_1 |
| value: 28.881 |
| - type: mrr_at_10 |
| value: 36.418 |
| - type: mrr_at_100 |
| value: 37.347 |
| - type: mrr_at_1000 |
| value: 37.415 |
| - type: mrr_at_3 |
| value: 33.942 |
| - type: mrr_at_5 |
| value: 35.386 |
| - type: ndcg_at_1 |
| value: 28.881 |
| - type: ndcg_at_10 |
| value: 35.812 |
| - type: ndcg_at_100 |
| value: 41.574 |
| - type: ndcg_at_1000 |
| value: 44.289 |
| - type: ndcg_at_3 |
| value: 31.239 |
| - type: ndcg_at_5 |
| value: 33.302 |
| - type: precision_at_1 |
| value: 28.881 |
| - type: precision_at_10 |
| value: 6.598 |
| - type: precision_at_100 |
| value: 1.1079999999999999 |
| - type: precision_at_1000 |
| value: 0.151 |
| - type: precision_at_3 |
| value: 14.954 |
| - type: precision_at_5 |
| value: 10.776 |
| - type: recall_at_1 |
| value: 22.416 |
| - type: recall_at_10 |
| value: 46.243 |
| - type: recall_at_100 |
| value: 71.352 |
| - type: recall_at_1000 |
| value: 90.034 |
| - type: recall_at_3 |
| value: 32.873000000000005 |
| - type: recall_at_5 |
| value: 38.632 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 22.528166666666667 |
| - type: map_at_10 |
| value: 30.317833333333333 |
| - type: map_at_100 |
| value: 31.44108333333333 |
| - type: map_at_1000 |
| value: 31.566666666666666 |
| - type: map_at_3 |
| value: 27.84425 |
| - type: map_at_5 |
| value: 29.233333333333334 |
| - type: mrr_at_1 |
| value: 26.75733333333333 |
| - type: mrr_at_10 |
| value: 34.24425 |
| - type: mrr_at_100 |
| value: 35.11375 |
| - type: mrr_at_1000 |
| value: 35.184333333333335 |
| - type: mrr_at_3 |
| value: 32.01225 |
| - type: mrr_at_5 |
| value: 33.31225 |
| - type: ndcg_at_1 |
| value: 26.75733333333333 |
| - type: ndcg_at_10 |
| value: 35.072583333333334 |
| - type: ndcg_at_100 |
| value: 40.13358333333334 |
| - type: ndcg_at_1000 |
| value: 42.81825 |
| - type: ndcg_at_3 |
| value: 30.79275000000001 |
| - type: ndcg_at_5 |
| value: 32.822 |
| - type: precision_at_1 |
| value: 26.75733333333333 |
| - type: precision_at_10 |
| value: 6.128083333333334 |
| - type: precision_at_100 |
| value: 1.019 |
| - type: precision_at_1000 |
| value: 0.14391666666666664 |
| - type: precision_at_3 |
| value: 14.129916666666665 |
| - type: precision_at_5 |
| value: 10.087416666666668 |
| - type: recall_at_1 |
| value: 22.528166666666667 |
| - type: recall_at_10 |
| value: 45.38341666666667 |
| - type: recall_at_100 |
| value: 67.81791666666668 |
| - type: recall_at_1000 |
| value: 86.71716666666666 |
| - type: recall_at_3 |
| value: 33.38741666666667 |
| - type: recall_at_5 |
| value: 38.62041666666667 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackStatsRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 21.975 |
| - type: map_at_10 |
| value: 28.144999999999996 |
| - type: map_at_100 |
| value: 28.994999999999997 |
| - type: map_at_1000 |
| value: 29.086000000000002 |
| - type: map_at_3 |
| value: 25.968999999999998 |
| - type: map_at_5 |
| value: 27.321 |
| - type: mrr_at_1 |
| value: 25.0 |
| - type: mrr_at_10 |
| value: 30.822 |
| - type: mrr_at_100 |
| value: 31.647 |
| - type: mrr_at_1000 |
| value: 31.712 |
| - type: mrr_at_3 |
| value: 28.860000000000003 |
| - type: mrr_at_5 |
| value: 30.041 |
| - type: ndcg_at_1 |
| value: 25.0 |
| - type: ndcg_at_10 |
| value: 31.929999999999996 |
| - type: ndcg_at_100 |
| value: 36.258 |
| - type: ndcg_at_1000 |
| value: 38.682 |
| - type: ndcg_at_3 |
| value: 27.972 |
| - type: ndcg_at_5 |
| value: 30.089 |
| - type: precision_at_1 |
| value: 25.0 |
| - type: precision_at_10 |
| value: 4.923 |
| - type: precision_at_100 |
| value: 0.767 |
| - type: precision_at_1000 |
| value: 0.106 |
| - type: precision_at_3 |
| value: 11.860999999999999 |
| - type: precision_at_5 |
| value: 8.466 |
| - type: recall_at_1 |
| value: 21.975 |
| - type: recall_at_10 |
| value: 41.102 |
| - type: recall_at_100 |
| value: 60.866 |
| - type: recall_at_1000 |
| value: 78.781 |
| - type: recall_at_3 |
| value: 30.268 |
| - type: recall_at_5 |
| value: 35.552 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackTexRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 15.845999999999998 |
| - type: map_at_10 |
| value: 21.861 |
| - type: map_at_100 |
| value: 22.798 |
| - type: map_at_1000 |
| value: 22.925 |
| - type: map_at_3 |
| value: 19.922 |
| - type: map_at_5 |
| value: 21.054000000000002 |
| - type: mrr_at_1 |
| value: 19.098000000000003 |
| - type: mrr_at_10 |
| value: 25.397 |
| - type: mrr_at_100 |
| value: 26.246000000000002 |
| - type: mrr_at_1000 |
| value: 26.33 |
| - type: mrr_at_3 |
| value: 23.469 |
| - type: mrr_at_5 |
| value: 24.646 |
| - type: ndcg_at_1 |
| value: 19.098000000000003 |
| - type: ndcg_at_10 |
| value: 25.807999999999996 |
| - type: ndcg_at_100 |
| value: 30.445 |
| - type: ndcg_at_1000 |
| value: 33.666000000000004 |
| - type: ndcg_at_3 |
| value: 22.292 |
| - type: ndcg_at_5 |
| value: 24.075 |
| - type: precision_at_1 |
| value: 19.098000000000003 |
| - type: precision_at_10 |
| value: 4.58 |
| - type: precision_at_100 |
| value: 0.8099999999999999 |
| - type: precision_at_1000 |
| value: 0.126 |
| - type: precision_at_3 |
| value: 10.346 |
| - type: precision_at_5 |
| value: 7.542999999999999 |
| - type: recall_at_1 |
| value: 15.845999999999998 |
| - type: recall_at_10 |
| value: 34.172999999999995 |
| - type: recall_at_100 |
| value: 55.24099999999999 |
| - type: recall_at_1000 |
| value: 78.644 |
| - type: recall_at_3 |
| value: 24.401 |
| - type: recall_at_5 |
| value: 28.938000000000002 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackUnixRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 22.974 |
| - type: map_at_10 |
| value: 30.108 |
| - type: map_at_100 |
| value: 31.208000000000002 |
| - type: map_at_1000 |
| value: 31.330999999999996 |
| - type: map_at_3 |
| value: 27.889999999999997 |
| - type: map_at_5 |
| value: 29.023 |
| - type: mrr_at_1 |
| value: 26.493 |
| - type: mrr_at_10 |
| value: 33.726 |
| - type: mrr_at_100 |
| value: 34.622 |
| - type: mrr_at_1000 |
| value: 34.703 |
| - type: mrr_at_3 |
| value: 31.575999999999997 |
| - type: mrr_at_5 |
| value: 32.690999999999995 |
| - type: ndcg_at_1 |
| value: 26.493 |
| - type: ndcg_at_10 |
| value: 34.664 |
| - type: ndcg_at_100 |
| value: 39.725 |
| - type: ndcg_at_1000 |
| value: 42.648 |
| - type: ndcg_at_3 |
| value: 30.447999999999997 |
| - type: ndcg_at_5 |
| value: 32.145 |
| - type: precision_at_1 |
| value: 26.493 |
| - type: precision_at_10 |
| value: 5.7090000000000005 |
| - type: precision_at_100 |
| value: 0.9199999999999999 |
| - type: precision_at_1000 |
| value: 0.129 |
| - type: precision_at_3 |
| value: 13.464 |
| - type: precision_at_5 |
| value: 9.384 |
| - type: recall_at_1 |
| value: 22.974 |
| - type: recall_at_10 |
| value: 45.097 |
| - type: recall_at_100 |
| value: 66.908 |
| - type: recall_at_1000 |
| value: 87.495 |
| - type: recall_at_3 |
| value: 33.338 |
| - type: recall_at_5 |
| value: 37.499 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackWebmastersRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 22.408 |
| - type: map_at_10 |
| value: 29.580000000000002 |
| - type: map_at_100 |
| value: 31.145 |
| - type: map_at_1000 |
| value: 31.369000000000003 |
| - type: map_at_3 |
| value: 27.634999999999998 |
| - type: map_at_5 |
| value: 28.766000000000002 |
| - type: mrr_at_1 |
| value: 27.272999999999996 |
| - type: mrr_at_10 |
| value: 33.93 |
| - type: mrr_at_100 |
| value: 34.963 |
| - type: mrr_at_1000 |
| value: 35.031 |
| - type: mrr_at_3 |
| value: 32.016 |
| - type: mrr_at_5 |
| value: 33.221000000000004 |
| - type: ndcg_at_1 |
| value: 27.272999999999996 |
| - type: ndcg_at_10 |
| value: 33.993 |
| - type: ndcg_at_100 |
| value: 40.333999999999996 |
| - type: ndcg_at_1000 |
| value: 43.361 |
| - type: ndcg_at_3 |
| value: 30.918 |
| - type: ndcg_at_5 |
| value: 32.552 |
| - type: precision_at_1 |
| value: 27.272999999999996 |
| - type: precision_at_10 |
| value: 6.285 |
| - type: precision_at_100 |
| value: 1.389 |
| - type: precision_at_1000 |
| value: 0.232 |
| - type: precision_at_3 |
| value: 14.427000000000001 |
| - type: precision_at_5 |
| value: 10.356 |
| - type: recall_at_1 |
| value: 22.408 |
| - type: recall_at_10 |
| value: 41.318 |
| - type: recall_at_100 |
| value: 70.539 |
| - type: recall_at_1000 |
| value: 90.197 |
| - type: recall_at_3 |
| value: 32.513 |
| - type: recall_at_5 |
| value: 37.0 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackWordpressRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 17.258000000000003 |
| - type: map_at_10 |
| value: 24.294 |
| - type: map_at_100 |
| value: 25.305 |
| - type: map_at_1000 |
| value: 25.419999999999998 |
| - type: map_at_3 |
| value: 22.326999999999998 |
| - type: map_at_5 |
| value: 23.31 |
| - type: mrr_at_1 |
| value: 18.484 |
| - type: mrr_at_10 |
| value: 25.863999999999997 |
| - type: mrr_at_100 |
| value: 26.766000000000002 |
| - type: mrr_at_1000 |
| value: 26.855 |
| - type: mrr_at_3 |
| value: 23.968 |
| - type: mrr_at_5 |
| value: 24.911 |
| - type: ndcg_at_1 |
| value: 18.484 |
| - type: ndcg_at_10 |
| value: 28.433000000000003 |
| - type: ndcg_at_100 |
| value: 33.405 |
| - type: ndcg_at_1000 |
| value: 36.375 |
| - type: ndcg_at_3 |
| value: 24.455 |
| - type: ndcg_at_5 |
| value: 26.031 |
| - type: precision_at_1 |
| value: 18.484 |
| - type: precision_at_10 |
| value: 4.603 |
| - type: precision_at_100 |
| value: 0.773 |
| - type: precision_at_1000 |
| value: 0.11299999999999999 |
| - type: precision_at_3 |
| value: 10.659 |
| - type: precision_at_5 |
| value: 7.505000000000001 |
| - type: recall_at_1 |
| value: 17.258000000000003 |
| - type: recall_at_10 |
| value: 39.589999999999996 |
| - type: recall_at_100 |
| value: 62.592000000000006 |
| - type: recall_at_1000 |
| value: 84.917 |
| - type: recall_at_3 |
| value: 28.706 |
| - type: recall_at_5 |
| value: 32.224000000000004 |
| - task: |
| type: Retrieval |
| dataset: |
| type: climate-fever |
| name: MTEB ClimateFEVER |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 10.578999999999999 |
| - type: map_at_10 |
| value: 17.642 |
| - type: map_at_100 |
| value: 19.451 |
| - type: map_at_1000 |
| value: 19.647000000000002 |
| - type: map_at_3 |
| value: 14.618 |
| - type: map_at_5 |
| value: 16.145 |
| - type: mrr_at_1 |
| value: 23.322000000000003 |
| - type: mrr_at_10 |
| value: 34.204 |
| - type: mrr_at_100 |
| value: 35.185 |
| - type: mrr_at_1000 |
| value: 35.235 |
| - type: mrr_at_3 |
| value: 30.847 |
| - type: mrr_at_5 |
| value: 32.824 |
| - type: ndcg_at_1 |
| value: 23.322000000000003 |
| - type: ndcg_at_10 |
| value: 25.352999999999998 |
| - type: ndcg_at_100 |
| value: 32.574 |
| - type: ndcg_at_1000 |
| value: 36.073 |
| - type: ndcg_at_3 |
| value: 20.318 |
| - type: ndcg_at_5 |
| value: 22.111 |
| - type: precision_at_1 |
| value: 23.322000000000003 |
| - type: precision_at_10 |
| value: 8.02 |
| - type: precision_at_100 |
| value: 1.5730000000000002 |
| - type: precision_at_1000 |
| value: 0.22200000000000003 |
| - type: precision_at_3 |
| value: 15.049000000000001 |
| - type: precision_at_5 |
| value: 11.87 |
| - type: recall_at_1 |
| value: 10.578999999999999 |
| - type: recall_at_10 |
| value: 30.964999999999996 |
| - type: recall_at_100 |
| value: 55.986000000000004 |
| - type: recall_at_1000 |
| value: 75.565 |
| - type: recall_at_3 |
| value: 18.686 |
| - type: recall_at_5 |
| value: 23.629 |
| - task: |
| type: Retrieval |
| dataset: |
| type: dbpedia-entity |
| name: MTEB DBPedia |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 7.327 |
| - type: map_at_10 |
| value: 14.904 |
| - type: map_at_100 |
| value: 20.29 |
| - type: map_at_1000 |
| value: 21.42 |
| - type: map_at_3 |
| value: 10.911 |
| - type: map_at_5 |
| value: 12.791 |
| - type: mrr_at_1 |
| value: 57.25 |
| - type: mrr_at_10 |
| value: 66.62700000000001 |
| - type: mrr_at_100 |
| value: 67.035 |
| - type: mrr_at_1000 |
| value: 67.052 |
| - type: mrr_at_3 |
| value: 64.833 |
| - type: mrr_at_5 |
| value: 65.908 |
| - type: ndcg_at_1 |
| value: 43.75 |
| - type: ndcg_at_10 |
| value: 32.246 |
| - type: ndcg_at_100 |
| value: 35.774 |
| - type: ndcg_at_1000 |
| value: 42.872 |
| - type: ndcg_at_3 |
| value: 36.64 |
| - type: ndcg_at_5 |
| value: 34.487 |
| - type: precision_at_1 |
| value: 57.25 |
| - type: precision_at_10 |
| value: 25.924999999999997 |
| - type: precision_at_100 |
| value: 7.670000000000001 |
| - type: precision_at_1000 |
| value: 1.599 |
| - type: precision_at_3 |
| value: 41.167 |
| - type: precision_at_5 |
| value: 34.65 |
| - type: recall_at_1 |
| value: 7.327 |
| - type: recall_at_10 |
| value: 19.625 |
| - type: recall_at_100 |
| value: 41.601 |
| - type: recall_at_1000 |
| value: 65.117 |
| - type: recall_at_3 |
| value: 12.308 |
| - type: recall_at_5 |
| value: 15.437999999999999 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/emotion |
| name: MTEB EmotionClassification |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 44.53 |
| - type: f1 |
| value: 39.39884255816736 |
| - task: |
| type: Retrieval |
| dataset: |
| type: fever |
| name: MTEB FEVER |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 58.913000000000004 |
| - type: map_at_10 |
| value: 69.592 |
| - type: map_at_100 |
| value: 69.95599999999999 |
| - type: map_at_1000 |
| value: 69.973 |
| - type: map_at_3 |
| value: 67.716 |
| - type: map_at_5 |
| value: 68.899 |
| - type: mrr_at_1 |
| value: 63.561 |
| - type: mrr_at_10 |
| value: 74.2 |
| - type: mrr_at_100 |
| value: 74.468 |
| - type: mrr_at_1000 |
| value: 74.47500000000001 |
| - type: mrr_at_3 |
| value: 72.442 |
| - type: mrr_at_5 |
| value: 73.58 |
| - type: ndcg_at_1 |
| value: 63.561 |
| - type: ndcg_at_10 |
| value: 74.988 |
| - type: ndcg_at_100 |
| value: 76.52799999999999 |
| - type: ndcg_at_1000 |
| value: 76.88000000000001 |
| - type: ndcg_at_3 |
| value: 71.455 |
| - type: ndcg_at_5 |
| value: 73.42699999999999 |
| - type: precision_at_1 |
| value: 63.561 |
| - type: precision_at_10 |
| value: 9.547 |
| - type: precision_at_100 |
| value: 1.044 |
| - type: precision_at_1000 |
| value: 0.109 |
| - type: precision_at_3 |
| value: 28.143 |
| - type: precision_at_5 |
| value: 18.008 |
| - type: recall_at_1 |
| value: 58.913000000000004 |
| - type: recall_at_10 |
| value: 87.18 |
| - type: recall_at_100 |
| value: 93.852 |
| - type: recall_at_1000 |
| value: 96.256 |
| - type: recall_at_3 |
| value: 77.55199999999999 |
| - type: recall_at_5 |
| value: 82.42399999999999 |
| - task: |
| type: Retrieval |
| dataset: |
| type: fiqa |
| name: MTEB FiQA2018 |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 11.761000000000001 |
| - type: map_at_10 |
| value: 19.564999999999998 |
| - type: map_at_100 |
| value: 21.099 |
| - type: map_at_1000 |
| value: 21.288999999999998 |
| - type: map_at_3 |
| value: 16.683999999999997 |
| - type: map_at_5 |
| value: 18.307000000000002 |
| - type: mrr_at_1 |
| value: 23.302 |
| - type: mrr_at_10 |
| value: 30.979 |
| - type: mrr_at_100 |
| value: 32.121 |
| - type: mrr_at_1000 |
| value: 32.186 |
| - type: mrr_at_3 |
| value: 28.549000000000003 |
| - type: mrr_at_5 |
| value: 30.038999999999998 |
| - type: ndcg_at_1 |
| value: 23.302 |
| - type: ndcg_at_10 |
| value: 25.592 |
| - type: ndcg_at_100 |
| value: 32.416 |
| - type: ndcg_at_1000 |
| value: 36.277 |
| - type: ndcg_at_3 |
| value: 22.151 |
| - type: ndcg_at_5 |
| value: 23.483999999999998 |
| - type: precision_at_1 |
| value: 23.302 |
| - type: precision_at_10 |
| value: 7.377000000000001 |
| - type: precision_at_100 |
| value: 1.415 |
| - type: precision_at_1000 |
| value: 0.212 |
| - type: precision_at_3 |
| value: 14.712 |
| - type: precision_at_5 |
| value: 11.358 |
| - type: recall_at_1 |
| value: 11.761000000000001 |
| - type: recall_at_10 |
| value: 31.696 |
| - type: recall_at_100 |
| value: 58.01500000000001 |
| - type: recall_at_1000 |
| value: 81.572 |
| - type: recall_at_3 |
| value: 20.742 |
| - type: recall_at_5 |
| value: 25.707 |
| - task: |
| type: Retrieval |
| dataset: |
| type: hotpotqa |
| name: MTEB HotpotQA |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 32.275 |
| - type: map_at_10 |
| value: 44.712 |
| - type: map_at_100 |
| value: 45.621 |
| - type: map_at_1000 |
| value: 45.698 |
| - type: map_at_3 |
| value: 42.016999999999996 |
| - type: map_at_5 |
| value: 43.659 |
| - type: mrr_at_1 |
| value: 64.551 |
| - type: mrr_at_10 |
| value: 71.58099999999999 |
| - type: mrr_at_100 |
| value: 71.952 |
| - type: mrr_at_1000 |
| value: 71.96900000000001 |
| - type: mrr_at_3 |
| value: 70.236 |
| - type: mrr_at_5 |
| value: 71.051 |
| - type: ndcg_at_1 |
| value: 64.551 |
| - type: ndcg_at_10 |
| value: 53.913999999999994 |
| - type: ndcg_at_100 |
| value: 57.421 |
| - type: ndcg_at_1000 |
| value: 59.06 |
| - type: ndcg_at_3 |
| value: 49.716 |
| - type: ndcg_at_5 |
| value: 51.971999999999994 |
| - type: precision_at_1 |
| value: 64.551 |
| - type: precision_at_10 |
| value: 11.110000000000001 |
| - type: precision_at_100 |
| value: 1.388 |
| - type: precision_at_1000 |
| value: 0.161 |
| - type: precision_at_3 |
| value: 30.822 |
| - type: precision_at_5 |
| value: 20.273 |
| - type: recall_at_1 |
| value: 32.275 |
| - type: recall_at_10 |
| value: 55.55 |
| - type: recall_at_100 |
| value: 69.38600000000001 |
| - type: recall_at_1000 |
| value: 80.35799999999999 |
| - type: recall_at_3 |
| value: 46.232 |
| - type: recall_at_5 |
| value: 50.682 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/imdb |
| name: MTEB ImdbClassification |
| config: default |
| split: test |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| metrics: |
| - type: accuracy |
| value: 76.4604 |
| - type: ap |
| value: 70.40498168422701 |
| - type: f1 |
| value: 76.38572688476046 |
| - task: |
| type: Retrieval |
| dataset: |
| type: msmarco |
| name: MTEB MSMARCO |
| config: default |
| split: dev |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 15.065999999999999 |
| - type: map_at_10 |
| value: 25.058000000000003 |
| - type: map_at_100 |
| value: 26.268 |
| - type: map_at_1000 |
| value: 26.344 |
| - type: map_at_3 |
| value: 21.626 |
| - type: map_at_5 |
| value: 23.513 |
| - type: mrr_at_1 |
| value: 15.501000000000001 |
| - type: mrr_at_10 |
| value: 25.548 |
| - type: mrr_at_100 |
| value: 26.723000000000003 |
| - type: mrr_at_1000 |
| value: 26.793 |
| - type: mrr_at_3 |
| value: 22.142 |
| - type: mrr_at_5 |
| value: 24.024 |
| - type: ndcg_at_1 |
| value: 15.501000000000001 |
| - type: ndcg_at_10 |
| value: 31.008000000000003 |
| - type: ndcg_at_100 |
| value: 37.08 |
| - type: ndcg_at_1000 |
| value: 39.102 |
| - type: ndcg_at_3 |
| value: 23.921999999999997 |
| - type: ndcg_at_5 |
| value: 27.307 |
| - type: precision_at_1 |
| value: 15.501000000000001 |
| - type: precision_at_10 |
| value: 5.155 |
| - type: precision_at_100 |
| value: 0.822 |
| - type: precision_at_1000 |
| value: 0.099 |
| - type: precision_at_3 |
| value: 10.363 |
| - type: precision_at_5 |
| value: 7.917000000000001 |
| - type: recall_at_1 |
| value: 15.065999999999999 |
| - type: recall_at_10 |
| value: 49.507 |
| - type: recall_at_100 |
| value: 78.118 |
| - type: recall_at_1000 |
| value: 93.881 |
| - type: recall_at_3 |
| value: 30.075000000000003 |
| - type: recall_at_5 |
| value: 38.222 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (en) |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 90.6703146374829 |
| - type: f1 |
| value: 90.1258004293966 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (en) |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 68.29229366165072 |
| - type: f1 |
| value: 50.016194478997875 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (en) |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 68.57767316745124 |
| - type: f1 |
| value: 67.16194062146954 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (en) |
| config: en |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 73.92064559515804 |
| - type: f1 |
| value: 73.6680729569968 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-p2p |
| name: MTEB MedrxivClusteringP2P |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 31.56335607367883 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-s2s |
| name: MTEB MedrxivClusteringS2S |
| config: default |
| split: test |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| metrics: |
| - type: v_measure |
| value: 28.131807833734268 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/mind_small |
| name: MTEB MindSmallReranking |
| config: default |
| split: test |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| metrics: |
| - type: map |
| value: 31.07390328719844 |
| - type: mrr |
| value: 32.117370992867905 |
| - task: |
| type: Retrieval |
| dataset: |
| type: nfcorpus |
| name: MTEB NFCorpus |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 5.274 |
| - type: map_at_10 |
| value: 11.489 |
| - type: map_at_100 |
| value: 14.518 |
| - type: map_at_1000 |
| value: 15.914 |
| - type: map_at_3 |
| value: 8.399 |
| - type: map_at_5 |
| value: 9.889000000000001 |
| - type: mrr_at_1 |
| value: 42.724000000000004 |
| - type: mrr_at_10 |
| value: 51.486 |
| - type: mrr_at_100 |
| value: 51.941 |
| - type: mrr_at_1000 |
| value: 51.99 |
| - type: mrr_at_3 |
| value: 49.278 |
| - type: mrr_at_5 |
| value: 50.485 |
| - type: ndcg_at_1 |
| value: 39.938 |
| - type: ndcg_at_10 |
| value: 31.862000000000002 |
| - type: ndcg_at_100 |
| value: 29.235 |
| - type: ndcg_at_1000 |
| value: 37.802 |
| - type: ndcg_at_3 |
| value: 35.754999999999995 |
| - type: ndcg_at_5 |
| value: 34.447 |
| - type: precision_at_1 |
| value: 42.105 |
| - type: precision_at_10 |
| value: 23.901 |
| - type: precision_at_100 |
| value: 7.715 |
| - type: precision_at_1000 |
| value: 2.045 |
| - type: precision_at_3 |
| value: 33.437 |
| - type: precision_at_5 |
| value: 29.782999999999998 |
| - type: recall_at_1 |
| value: 5.274 |
| - type: recall_at_10 |
| value: 15.351 |
| - type: recall_at_100 |
| value: 29.791 |
| - type: recall_at_1000 |
| value: 60.722 |
| - type: recall_at_3 |
| value: 9.411 |
| - type: recall_at_5 |
| value: 12.171999999999999 |
| - task: |
| type: Retrieval |
| dataset: |
| type: nq |
| name: MTEB NQ |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 16.099 |
| - type: map_at_10 |
| value: 27.913 |
| - type: map_at_100 |
| value: 29.281000000000002 |
| - type: map_at_1000 |
| value: 29.343999999999998 |
| - type: map_at_3 |
| value: 23.791 |
| - type: map_at_5 |
| value: 26.049 |
| - type: mrr_at_1 |
| value: 18.337 |
| - type: mrr_at_10 |
| value: 29.953999999999997 |
| - type: mrr_at_100 |
| value: 31.080999999999996 |
| - type: mrr_at_1000 |
| value: 31.130000000000003 |
| - type: mrr_at_3 |
| value: 26.168000000000003 |
| - type: mrr_at_5 |
| value: 28.277 |
| - type: ndcg_at_1 |
| value: 18.308 |
| - type: ndcg_at_10 |
| value: 34.938 |
| - type: ndcg_at_100 |
| value: 41.125 |
| - type: ndcg_at_1000 |
| value: 42.708 |
| - type: ndcg_at_3 |
| value: 26.805 |
| - type: ndcg_at_5 |
| value: 30.686999999999998 |
| - type: precision_at_1 |
| value: 18.308 |
| - type: precision_at_10 |
| value: 6.476999999999999 |
| - type: precision_at_100 |
| value: 0.9939999999999999 |
| - type: precision_at_1000 |
| value: 0.11399999999999999 |
| - type: precision_at_3 |
| value: 12.784999999999998 |
| - type: precision_at_5 |
| value: 9.878 |
| - type: recall_at_1 |
| value: 16.099 |
| - type: recall_at_10 |
| value: 54.63 |
| - type: recall_at_100 |
| value: 82.24900000000001 |
| - type: recall_at_1000 |
| value: 94.242 |
| - type: recall_at_3 |
| value: 33.174 |
| - type: recall_at_5 |
| value: 42.164 |
| - task: |
| type: Retrieval |
| dataset: |
| type: quora |
| name: MTEB QuoraRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 67.947 |
| - type: map_at_10 |
| value: 81.499 |
| - type: map_at_100 |
| value: 82.17 |
| - type: map_at_1000 |
| value: 82.194 |
| - type: map_at_3 |
| value: 78.567 |
| - type: map_at_5 |
| value: 80.34400000000001 |
| - type: mrr_at_1 |
| value: 78.18 |
| - type: mrr_at_10 |
| value: 85.05 |
| - type: mrr_at_100 |
| value: 85.179 |
| - type: mrr_at_1000 |
| value: 85.181 |
| - type: mrr_at_3 |
| value: 83.91 |
| - type: mrr_at_5 |
| value: 84.638 |
| - type: ndcg_at_1 |
| value: 78.2 |
| - type: ndcg_at_10 |
| value: 85.715 |
| - type: ndcg_at_100 |
| value: 87.2 |
| - type: ndcg_at_1000 |
| value: 87.39 |
| - type: ndcg_at_3 |
| value: 82.572 |
| - type: ndcg_at_5 |
| value: 84.176 |
| - type: precision_at_1 |
| value: 78.2 |
| - type: precision_at_10 |
| value: 12.973 |
| - type: precision_at_100 |
| value: 1.5010000000000001 |
| - type: precision_at_1000 |
| value: 0.156 |
| - type: precision_at_3 |
| value: 35.949999999999996 |
| - type: precision_at_5 |
| value: 23.62 |
| - type: recall_at_1 |
| value: 67.947 |
| - type: recall_at_10 |
| value: 93.804 |
| - type: recall_at_100 |
| value: 98.971 |
| - type: recall_at_1000 |
| value: 99.91600000000001 |
| - type: recall_at_3 |
| value: 84.75399999999999 |
| - type: recall_at_5 |
| value: 89.32 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering |
| name: MTEB RedditClustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 45.457201684255104 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering-p2p |
| name: MTEB RedditClusteringP2P |
| config: default |
| split: test |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| metrics: |
| - type: v_measure |
| value: 55.162226937477875 |
| - task: |
| type: Retrieval |
| dataset: |
| type: scidocs |
| name: MTEB SCIDOCS |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 4.173 |
| - type: map_at_10 |
| value: 10.463000000000001 |
| - type: map_at_100 |
| value: 12.278 |
| - type: map_at_1000 |
| value: 12.572 |
| - type: map_at_3 |
| value: 7.528 |
| - type: map_at_5 |
| value: 8.863 |
| - type: mrr_at_1 |
| value: 20.599999999999998 |
| - type: mrr_at_10 |
| value: 30.422 |
| - type: mrr_at_100 |
| value: 31.6 |
| - type: mrr_at_1000 |
| value: 31.663000000000004 |
| - type: mrr_at_3 |
| value: 27.400000000000002 |
| - type: mrr_at_5 |
| value: 29.065 |
| - type: ndcg_at_1 |
| value: 20.599999999999998 |
| - type: ndcg_at_10 |
| value: 17.687 |
| - type: ndcg_at_100 |
| value: 25.172 |
| - type: ndcg_at_1000 |
| value: 30.617 |
| - type: ndcg_at_3 |
| value: 16.81 |
| - type: ndcg_at_5 |
| value: 14.499 |
| - type: precision_at_1 |
| value: 20.599999999999998 |
| - type: precision_at_10 |
| value: 9.17 |
| - type: precision_at_100 |
| value: 2.004 |
| - type: precision_at_1000 |
| value: 0.332 |
| - type: precision_at_3 |
| value: 15.6 |
| - type: precision_at_5 |
| value: 12.58 |
| - type: recall_at_1 |
| value: 4.173 |
| - type: recall_at_10 |
| value: 18.575 |
| - type: recall_at_100 |
| value: 40.692 |
| - type: recall_at_1000 |
| value: 67.467 |
| - type: recall_at_3 |
| value: 9.488000000000001 |
| - type: recall_at_5 |
| value: 12.738 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sickr-sts |
| name: MTEB SICK-R |
| config: default |
| split: test |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| metrics: |
| - type: cos_sim_pearson |
| value: 81.12603499315416 |
| - type: cos_sim_spearman |
| value: 73.62060290948378 |
| - type: euclidean_pearson |
| value: 78.14083565781135 |
| - type: euclidean_spearman |
| value: 73.16840437541543 |
| - type: manhattan_pearson |
| value: 77.92017261109734 |
| - type: manhattan_spearman |
| value: 72.8805059949965 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts12-sts |
| name: MTEB STS12 |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 79.75955377133172 |
| - type: cos_sim_spearman |
| value: 71.8872633964069 |
| - type: euclidean_pearson |
| value: 76.31922068538256 |
| - type: euclidean_spearman |
| value: 70.86449661855376 |
| - type: manhattan_pearson |
| value: 76.47852229730407 |
| - type: manhattan_spearman |
| value: 70.99367421984789 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts13-sts |
| name: MTEB STS13 |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 78.80762722908158 |
| - type: cos_sim_spearman |
| value: 79.84588978756372 |
| - type: euclidean_pearson |
| value: 79.8216849781164 |
| - type: euclidean_spearman |
| value: 80.22647061695481 |
| - type: manhattan_pearson |
| value: 79.56604194112572 |
| - type: manhattan_spearman |
| value: 79.96495189862462 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts14-sts |
| name: MTEB STS14 |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 80.1012718092742 |
| - type: cos_sim_spearman |
| value: 76.86011381793661 |
| - type: euclidean_pearson |
| value: 79.94426039862019 |
| - type: euclidean_spearman |
| value: 77.36751135465131 |
| - type: manhattan_pearson |
| value: 79.87959373304288 |
| - type: manhattan_spearman |
| value: 77.37717129004746 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts15-sts |
| name: MTEB STS15 |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 83.90618420346104 |
| - type: cos_sim_spearman |
| value: 84.77290791243722 |
| - type: euclidean_pearson |
| value: 84.64732258073293 |
| - type: euclidean_spearman |
| value: 85.21053649543357 |
| - type: manhattan_pearson |
| value: 84.61616883522647 |
| - type: manhattan_spearman |
| value: 85.19803126766931 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts16-sts |
| name: MTEB STS16 |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 80.52192114059063 |
| - type: cos_sim_spearman |
| value: 81.9103244827937 |
| - type: euclidean_pearson |
| value: 80.99375176138985 |
| - type: euclidean_spearman |
| value: 81.540250641079 |
| - type: manhattan_pearson |
| value: 80.84979573396426 |
| - type: manhattan_spearman |
| value: 81.3742591621492 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts17-crosslingual-sts |
| name: MTEB STS17 (en-en) |
| config: en-en |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.82166001234197 |
| - type: cos_sim_spearman |
| value: 86.81857495659123 |
| - type: euclidean_pearson |
| value: 85.72798403202849 |
| - type: euclidean_spearman |
| value: 85.70482438950965 |
| - type: manhattan_pearson |
| value: 85.51579093130357 |
| - type: manhattan_spearman |
| value: 85.41233705379751 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts22-crosslingual-sts |
| name: MTEB STS22 (en) |
| config: en |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 64.48071151079803 |
| - type: cos_sim_spearman |
| value: 65.37838108084044 |
| - type: euclidean_pearson |
| value: 64.67378947096257 |
| - type: euclidean_spearman |
| value: 65.39187147219869 |
| - type: manhattan_pearson |
| value: 65.35487466133208 |
| - type: manhattan_spearman |
| value: 65.51328499442272 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/stsbenchmark-sts |
| name: MTEB STSBenchmark |
| config: default |
| split: test |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| metrics: |
| - type: cos_sim_pearson |
| value: 82.64702367823314 |
| - type: cos_sim_spearman |
| value: 82.49732953181818 |
| - type: euclidean_pearson |
| value: 83.05996062475664 |
| - type: euclidean_spearman |
| value: 82.28159546751176 |
| - type: manhattan_pearson |
| value: 82.98305503664952 |
| - type: manhattan_spearman |
| value: 82.18405771943928 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/scidocs-reranking |
| name: MTEB SciDocsRR |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 78.5744649318696 |
| - type: mrr |
| value: 93.35386291268645 |
| - task: |
| type: Retrieval |
| dataset: |
| type: scifact |
| name: MTEB SciFact |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 52.093999999999994 |
| - type: map_at_10 |
| value: 61.646 |
| - type: map_at_100 |
| value: 62.197 |
| - type: map_at_1000 |
| value: 62.22800000000001 |
| - type: map_at_3 |
| value: 58.411 |
| - type: map_at_5 |
| value: 60.585 |
| - type: mrr_at_1 |
| value: 55.00000000000001 |
| - type: mrr_at_10 |
| value: 62.690999999999995 |
| - type: mrr_at_100 |
| value: 63.139 |
| - type: mrr_at_1000 |
| value: 63.166999999999994 |
| - type: mrr_at_3 |
| value: 60.111000000000004 |
| - type: mrr_at_5 |
| value: 61.778 |
| - type: ndcg_at_1 |
| value: 55.00000000000001 |
| - type: ndcg_at_10 |
| value: 66.271 |
| - type: ndcg_at_100 |
| value: 68.879 |
| - type: ndcg_at_1000 |
| value: 69.722 |
| - type: ndcg_at_3 |
| value: 60.672000000000004 |
| - type: ndcg_at_5 |
| value: 63.929 |
| - type: precision_at_1 |
| value: 55.00000000000001 |
| - type: precision_at_10 |
| value: 9.0 |
| - type: precision_at_100 |
| value: 1.043 |
| - type: precision_at_1000 |
| value: 0.11100000000000002 |
| - type: precision_at_3 |
| value: 23.555999999999997 |
| - type: precision_at_5 |
| value: 16.2 |
| - type: recall_at_1 |
| value: 52.093999999999994 |
| - type: recall_at_10 |
| value: 79.567 |
| - type: recall_at_100 |
| value: 91.60000000000001 |
| - type: recall_at_1000 |
| value: 98.333 |
| - type: recall_at_3 |
| value: 64.633 |
| - type: recall_at_5 |
| value: 72.68299999999999 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/sprintduplicatequestions-pairclassification |
| name: MTEB SprintDuplicateQuestions |
| config: default |
| split: test |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 99.83267326732673 |
| - type: cos_sim_ap |
| value: 95.77995366495178 |
| - type: cos_sim_f1 |
| value: 91.51180311401306 |
| - type: cos_sim_precision |
| value: 91.92734611503532 |
| - type: cos_sim_recall |
| value: 91.10000000000001 |
| - type: dot_accuracy |
| value: 99.63366336633663 |
| - type: dot_ap |
| value: 88.53996286967461 |
| - type: dot_f1 |
| value: 81.06537530266343 |
| - type: dot_precision |
| value: 78.59154929577464 |
| - type: dot_recall |
| value: 83.7 |
| - type: euclidean_accuracy |
| value: 99.82376237623762 |
| - type: euclidean_ap |
| value: 95.53192209281187 |
| - type: euclidean_f1 |
| value: 91.19683481701286 |
| - type: euclidean_precision |
| value: 90.21526418786692 |
| - type: euclidean_recall |
| value: 92.2 |
| - type: manhattan_accuracy |
| value: 99.82376237623762 |
| - type: manhattan_ap |
| value: 95.55642082191741 |
| - type: manhattan_f1 |
| value: 91.16186693147964 |
| - type: manhattan_precision |
| value: 90.53254437869822 |
| - type: manhattan_recall |
| value: 91.8 |
| - type: max_accuracy |
| value: 99.83267326732673 |
| - type: max_ap |
| value: 95.77995366495178 |
| - type: max_f1 |
| value: 91.51180311401306 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering |
| name: MTEB StackExchangeClustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 54.508462134213474 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering-p2p |
| name: MTEB StackExchangeClusteringP2P |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 34.06549765184959 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/stackoverflowdupquestions-reranking |
| name: MTEB StackOverflowDupQuestions |
| config: default |
| split: test |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| metrics: |
| - type: map |
| value: 49.43129549466616 |
| - type: mrr |
| value: 50.20613169510227 |
| - task: |
| type: Summarization |
| dataset: |
| type: mteb/summeval |
| name: MTEB SummEval |
| config: default |
| split: test |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| metrics: |
| - type: cos_sim_pearson |
| value: 30.069516173193044 |
| - type: cos_sim_spearman |
| value: 29.872498354017353 |
| - type: dot_pearson |
| value: 28.80761257516063 |
| - type: dot_spearman |
| value: 28.397422678527708 |
| - task: |
| type: Retrieval |
| dataset: |
| type: trec-covid |
| name: MTEB TRECCOVID |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 0.169 |
| - type: map_at_10 |
| value: 1.208 |
| - type: map_at_100 |
| value: 5.925 |
| - type: map_at_1000 |
| value: 14.427000000000001 |
| - type: map_at_3 |
| value: 0.457 |
| - type: map_at_5 |
| value: 0.716 |
| - type: mrr_at_1 |
| value: 64.0 |
| - type: mrr_at_10 |
| value: 74.075 |
| - type: mrr_at_100 |
| value: 74.303 |
| - type: mrr_at_1000 |
| value: 74.303 |
| - type: mrr_at_3 |
| value: 71.0 |
| - type: mrr_at_5 |
| value: 72.89999999999999 |
| - type: ndcg_at_1 |
| value: 57.99999999999999 |
| - type: ndcg_at_10 |
| value: 50.376 |
| - type: ndcg_at_100 |
| value: 38.582 |
| - type: ndcg_at_1000 |
| value: 35.663 |
| - type: ndcg_at_3 |
| value: 55.592 |
| - type: ndcg_at_5 |
| value: 53.647999999999996 |
| - type: precision_at_1 |
| value: 64.0 |
| - type: precision_at_10 |
| value: 53.2 |
| - type: precision_at_100 |
| value: 39.6 |
| - type: precision_at_1000 |
| value: 16.218 |
| - type: precision_at_3 |
| value: 59.333000000000006 |
| - type: precision_at_5 |
| value: 57.599999999999994 |
| - type: recall_at_1 |
| value: 0.169 |
| - type: recall_at_10 |
| value: 1.423 |
| - type: recall_at_100 |
| value: 9.049999999999999 |
| - type: recall_at_1000 |
| value: 34.056999999999995 |
| - type: recall_at_3 |
| value: 0.48700000000000004 |
| - type: recall_at_5 |
| value: 0.792 |
| - task: |
| type: Retrieval |
| dataset: |
| type: webis-touche2020 |
| name: MTEB Touche2020 |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 1.319 |
| - type: map_at_10 |
| value: 7.112 |
| - type: map_at_100 |
| value: 12.588 |
| - type: map_at_1000 |
| value: 14.056 |
| - type: map_at_3 |
| value: 2.8049999999999997 |
| - type: map_at_5 |
| value: 4.68 |
| - type: mrr_at_1 |
| value: 18.367 |
| - type: mrr_at_10 |
| value: 33.94 |
| - type: mrr_at_100 |
| value: 35.193000000000005 |
| - type: mrr_at_1000 |
| value: 35.193000000000005 |
| - type: mrr_at_3 |
| value: 29.932 |
| - type: mrr_at_5 |
| value: 32.279 |
| - type: ndcg_at_1 |
| value: 15.306000000000001 |
| - type: ndcg_at_10 |
| value: 18.096 |
| - type: ndcg_at_100 |
| value: 30.512 |
| - type: ndcg_at_1000 |
| value: 42.148 |
| - type: ndcg_at_3 |
| value: 17.034 |
| - type: ndcg_at_5 |
| value: 18.509 |
| - type: precision_at_1 |
| value: 18.367 |
| - type: precision_at_10 |
| value: 18.776 |
| - type: precision_at_100 |
| value: 7.02 |
| - type: precision_at_1000 |
| value: 1.467 |
| - type: precision_at_3 |
| value: 19.048000000000002 |
| - type: precision_at_5 |
| value: 22.041 |
| - type: recall_at_1 |
| value: 1.319 |
| - type: recall_at_10 |
| value: 13.748 |
| - type: recall_at_100 |
| value: 43.972 |
| - type: recall_at_1000 |
| value: 79.557 |
| - type: recall_at_3 |
| value: 4.042 |
| - type: recall_at_5 |
| value: 7.742 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/toxic_conversations_50k |
| name: MTEB ToxicConversationsClassification |
| config: default |
| split: test |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
| metrics: |
| - type: accuracy |
| value: 70.2282 |
| - type: ap |
| value: 13.995763859570426 |
| - type: f1 |
| value: 54.08126256731344 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/tweet_sentiment_extraction |
| name: MTEB TweetSentimentExtractionClassification |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 57.64006791171477 |
| - type: f1 |
| value: 57.95841320748957 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/twentynewsgroups-clustering |
| name: MTEB TwentyNewsgroupsClustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 40.19267841788564 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twittersemeval2015-pairclassification |
| name: MTEB TwitterSemEval2015 |
| config: default |
| split: test |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 83.96614412588663 |
| - type: cos_sim_ap |
| value: 67.75985678572738 |
| - type: cos_sim_f1 |
| value: 64.04661542276222 |
| - type: cos_sim_precision |
| value: 60.406922357343305 |
| - type: cos_sim_recall |
| value: 68.15303430079156 |
| - type: dot_accuracy |
| value: 79.5732252488526 |
| - type: dot_ap |
| value: 51.30562107572645 |
| - type: dot_f1 |
| value: 53.120759837177744 |
| - type: dot_precision |
| value: 46.478037198258804 |
| - type: dot_recall |
| value: 61.97889182058047 |
| - type: euclidean_accuracy |
| value: 84.00786791440663 |
| - type: euclidean_ap |
| value: 67.58930214486998 |
| - type: euclidean_f1 |
| value: 64.424821579775 |
| - type: euclidean_precision |
| value: 59.4817958454322 |
| - type: euclidean_recall |
| value: 70.26385224274406 |
| - type: manhattan_accuracy |
| value: 83.87673600762949 |
| - type: manhattan_ap |
| value: 67.4250981523309 |
| - type: manhattan_f1 |
| value: 64.10286658015808 |
| - type: manhattan_precision |
| value: 57.96885001066781 |
| - type: manhattan_recall |
| value: 71.68865435356201 |
| - type: max_accuracy |
| value: 84.00786791440663 |
| - type: max_ap |
| value: 67.75985678572738 |
| - type: max_f1 |
| value: 64.424821579775 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twitterurlcorpus-pairclassification |
| name: MTEB TwitterURLCorpus |
| config: default |
| split: test |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| metrics: |
| - type: cos_sim_accuracy |
| value: 88.41347459929368 |
| - type: cos_sim_ap |
| value: 84.89261930113058 |
| - type: cos_sim_f1 |
| value: 77.13677607258877 |
| - type: cos_sim_precision |
| value: 74.88581164358733 |
| - type: cos_sim_recall |
| value: 79.52725592854944 |
| - type: dot_accuracy |
| value: 86.32359219156285 |
| - type: dot_ap |
| value: 79.29794992131094 |
| - type: dot_f1 |
| value: 72.84356337679777 |
| - type: dot_precision |
| value: 67.31761478675462 |
| - type: dot_recall |
| value: 79.35786880197105 |
| - type: euclidean_accuracy |
| value: 88.33585593976791 |
| - type: euclidean_ap |
| value: 84.73257641312746 |
| - type: euclidean_f1 |
| value: 76.83529582788195 |
| - type: euclidean_precision |
| value: 72.76294052863436 |
| - type: euclidean_recall |
| value: 81.3905143209116 |
| - type: manhattan_accuracy |
| value: 88.3086894089339 |
| - type: manhattan_ap |
| value: 84.66304891729399 |
| - type: manhattan_f1 |
| value: 76.8181650632165 |
| - type: manhattan_precision |
| value: 73.6864436744219 |
| - type: manhattan_recall |
| value: 80.22790267939637 |
| - type: max_accuracy |
| value: 88.41347459929368 |
| - type: max_ap |
| value: 84.89261930113058 |
| - type: max_f1 |
| value: 77.13677607258877 |
| --- |
| |
| # bge-micro-v2 |
|
|
| > Forked from https://huggingface.co/TaylorAI/bge-micro-v2 purely to ensure it remains available. See also [license](LICENSE). |
|
|
| This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. |
|
|
| Distilled in a 2-step training process (bge-micro was step 1) from `BAAI/bge-small-en-v1.5`. |
|
|
| ## Usage (Sentence-Transformers) |
|
|
| Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: |
|
|
| ``` |
| pip install -U sentence-transformers |
| ``` |
|
|
| Then you can use the model like this: |
|
|
| ```python |
| from sentence_transformers import SentenceTransformer |
| sentences = ["This is an example sentence", "Each sentence is converted"] |
| |
| model = SentenceTransformer('{MODEL_NAME}') |
| embeddings = model.encode(sentences) |
| print(embeddings) |
| ``` |
|
|
|
|
|
|
| ## Usage (HuggingFace Transformers) |
| Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings. |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModel |
| import torch |
| |
| |
| #Mean Pooling - Take attention mask into account for correct averaging |
| def mean_pooling(model_output, attention_mask): |
| token_embeddings = model_output[0] #First element of model_output contains all token embeddings |
| input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float() |
| return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9) |
| |
| |
| # Sentences we want sentence embeddings for |
| sentences = ['This is an example sentence', 'Each sentence is converted'] |
| |
| # Load model from HuggingFace Hub |
| tokenizer = AutoTokenizer.from_pretrained('{MODEL_NAME}') |
| model = AutoModel.from_pretrained('{MODEL_NAME}') |
| |
| # Tokenize sentences |
| encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt') |
| |
| # Compute token embeddings |
| with torch.no_grad(): |
| model_output = model(**encoded_input) |
| |
| # Perform pooling. In this case, mean pooling. |
| sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask']) |
| |
| print("Sentence embeddings:") |
| print(sentence_embeddings) |
| ``` |
|
|
|
|
|
|
| ## Evaluation Results |
|
|
| <!--- Describe how your model was evaluated --> |
|
|
| For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name={MODEL_NAME}) |
|
|
|
|
|
|
| ## Full Model Architecture |
| ``` |
| SentenceTransformer( |
| (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel |
| (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False}) |
| ) |
| ``` |
|
|
| ## Citing & Authors |
|
|
| <!--- Describe where people can find more information --> |
