| --- |
| tags: |
| - mteb |
| - sentence_embedding |
| - feature_extraction |
| - transformers |
| - transformers.js |
| model-index: |
| - name: UAE-Large-V1 |
| results: |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_counterfactual |
| name: MTEB AmazonCounterfactualClassification (en) |
| config: en |
| split: test |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| metrics: |
| - type: accuracy |
| value: 75.55223880597015 |
| - type: ap |
| value: 38.264070815317794 |
| - type: f1 |
| value: 69.40977934769845 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_polarity |
| name: MTEB AmazonPolarityClassification |
| config: default |
| split: test |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| metrics: |
| - type: accuracy |
| value: 92.84267499999999 |
| - type: ap |
| value: 89.57568507997713 |
| - type: f1 |
| value: 92.82590734337774 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_reviews_multi |
| name: MTEB AmazonReviewsClassification (en) |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 48.292 |
| - type: f1 |
| value: 47.90257816032778 |
| - task: |
| type: Retrieval |
| dataset: |
| type: arguana |
| name: MTEB ArguAna |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 42.105 |
| - type: map_at_10 |
| value: 58.181000000000004 |
| - type: map_at_100 |
| value: 58.653999999999996 |
| - type: map_at_1000 |
| value: 58.657000000000004 |
| - type: map_at_3 |
| value: 54.386 |
| - type: map_at_5 |
| value: 56.757999999999996 |
| - type: mrr_at_1 |
| value: 42.745 |
| - type: mrr_at_10 |
| value: 58.437 |
| - type: mrr_at_100 |
| value: 58.894999999999996 |
| - type: mrr_at_1000 |
| value: 58.897999999999996 |
| - type: mrr_at_3 |
| value: 54.635 |
| - type: mrr_at_5 |
| value: 56.99999999999999 |
| - type: ndcg_at_1 |
| value: 42.105 |
| - type: ndcg_at_10 |
| value: 66.14999999999999 |
| - type: ndcg_at_100 |
| value: 68.048 |
| - type: ndcg_at_1000 |
| value: 68.11399999999999 |
| - type: ndcg_at_3 |
| value: 58.477000000000004 |
| - type: ndcg_at_5 |
| value: 62.768 |
| - type: precision_at_1 |
| value: 42.105 |
| - type: precision_at_10 |
| value: 9.110999999999999 |
| - type: precision_at_100 |
| value: 0.991 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_3 |
| value: 23.447000000000003 |
| - type: precision_at_5 |
| value: 16.159000000000002 |
| - type: recall_at_1 |
| value: 42.105 |
| - type: recall_at_10 |
| value: 91.11 |
| - type: recall_at_100 |
| value: 99.14699999999999 |
| - type: recall_at_1000 |
| value: 99.644 |
| - type: recall_at_3 |
| value: 70.341 |
| - type: recall_at_5 |
| value: 80.797 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-p2p |
| name: MTEB ArxivClusteringP2P |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 49.02580759154173 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/arxiv-clustering-s2s |
| name: MTEB ArxivClusteringS2S |
| config: default |
| split: test |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| metrics: |
| - type: v_measure |
| value: 43.093601280163554 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/askubuntudupquestions-reranking |
| name: MTEB AskUbuntuDupQuestions |
| config: default |
| split: test |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| metrics: |
| - type: map |
| value: 64.19590406875427 |
| - type: mrr |
| value: 77.09547992788991 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/biosses-sts |
| name: MTEB BIOSSES |
| config: default |
| split: test |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| metrics: |
| - type: cos_sim_pearson |
| value: 87.86678362843676 |
| - type: cos_sim_spearman |
| value: 86.1423242570783 |
| - type: euclidean_pearson |
| value: 85.98994198511751 |
| - type: euclidean_spearman |
| value: 86.48209103503942 |
| - type: manhattan_pearson |
| value: 85.6446436316182 |
| - type: manhattan_spearman |
| value: 86.21039809734357 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/banking77 |
| name: MTEB Banking77Classification |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 87.69155844155844 |
| - type: f1 |
| value: 87.68109381943547 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-p2p |
| name: MTEB BiorxivClusteringP2P |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 39.37501687500394 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/biorxiv-clustering-s2s |
| name: MTEB BiorxivClusteringS2S |
| config: default |
| split: test |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| metrics: |
| - type: v_measure |
| value: 37.23401405155885 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackAndroidRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 30.232 |
| - type: map_at_10 |
| value: 41.404999999999994 |
| - type: map_at_100 |
| value: 42.896 |
| - type: map_at_1000 |
| value: 43.028 |
| - type: map_at_3 |
| value: 37.925 |
| - type: map_at_5 |
| value: 39.865 |
| - type: mrr_at_1 |
| value: 36.338 |
| - type: mrr_at_10 |
| value: 46.969 |
| - type: mrr_at_100 |
| value: 47.684 |
| - type: mrr_at_1000 |
| value: 47.731 |
| - type: mrr_at_3 |
| value: 44.063 |
| - type: mrr_at_5 |
| value: 45.908 |
| - type: ndcg_at_1 |
| value: 36.338 |
| - type: ndcg_at_10 |
| value: 47.887 |
| - type: ndcg_at_100 |
| value: 53.357 |
| - type: ndcg_at_1000 |
| value: 55.376999999999995 |
| - type: ndcg_at_3 |
| value: 42.588 |
| - type: ndcg_at_5 |
| value: 45.132 |
| - type: precision_at_1 |
| value: 36.338 |
| - type: precision_at_10 |
| value: 9.17 |
| - type: precision_at_100 |
| value: 1.4909999999999999 |
| - type: precision_at_1000 |
| value: 0.196 |
| - type: precision_at_3 |
| value: 20.315 |
| - type: precision_at_5 |
| value: 14.793000000000001 |
| - type: recall_at_1 |
| value: 30.232 |
| - type: recall_at_10 |
| value: 60.67399999999999 |
| - type: recall_at_100 |
| value: 83.628 |
| - type: recall_at_1000 |
| value: 96.209 |
| - type: recall_at_3 |
| value: 45.48 |
| - type: recall_at_5 |
| value: 52.354 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackEnglishRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 32.237 |
| - type: map_at_10 |
| value: 42.829 |
| - type: map_at_100 |
| value: 44.065 |
| - type: map_at_1000 |
| value: 44.199 |
| - type: map_at_3 |
| value: 39.885999999999996 |
| - type: map_at_5 |
| value: 41.55 |
| - type: mrr_at_1 |
| value: 40.064 |
| - type: mrr_at_10 |
| value: 48.611 |
| - type: mrr_at_100 |
| value: 49.245 |
| - type: mrr_at_1000 |
| value: 49.29 |
| - type: mrr_at_3 |
| value: 46.561 |
| - type: mrr_at_5 |
| value: 47.771 |
| - type: ndcg_at_1 |
| value: 40.064 |
| - type: ndcg_at_10 |
| value: 48.388 |
| - type: ndcg_at_100 |
| value: 52.666999999999994 |
| - type: ndcg_at_1000 |
| value: 54.67100000000001 |
| - type: ndcg_at_3 |
| value: 44.504 |
| - type: ndcg_at_5 |
| value: 46.303 |
| - type: precision_at_1 |
| value: 40.064 |
| - type: precision_at_10 |
| value: 9.051 |
| - type: precision_at_100 |
| value: 1.4500000000000002 |
| - type: precision_at_1000 |
| value: 0.193 |
| - type: precision_at_3 |
| value: 21.444 |
| - type: precision_at_5 |
| value: 15.045 |
| - type: recall_at_1 |
| value: 32.237 |
| - type: recall_at_10 |
| value: 57.943999999999996 |
| - type: recall_at_100 |
| value: 75.98700000000001 |
| - type: recall_at_1000 |
| value: 88.453 |
| - type: recall_at_3 |
| value: 46.268 |
| - type: recall_at_5 |
| value: 51.459999999999994 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackGamingRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 38.797 |
| - type: map_at_10 |
| value: 51.263000000000005 |
| - type: map_at_100 |
| value: 52.333 |
| - type: map_at_1000 |
| value: 52.393 |
| - type: map_at_3 |
| value: 47.936 |
| - type: map_at_5 |
| value: 49.844 |
| - type: mrr_at_1 |
| value: 44.389 |
| - type: mrr_at_10 |
| value: 54.601 |
| - type: mrr_at_100 |
| value: 55.300000000000004 |
| - type: mrr_at_1000 |
| value: 55.333 |
| - type: mrr_at_3 |
| value: 52.068999999999996 |
| - type: mrr_at_5 |
| value: 53.627 |
| - type: ndcg_at_1 |
| value: 44.389 |
| - type: ndcg_at_10 |
| value: 57.193000000000005 |
| - type: ndcg_at_100 |
| value: 61.307 |
| - type: ndcg_at_1000 |
| value: 62.529 |
| - type: ndcg_at_3 |
| value: 51.607 |
| - type: ndcg_at_5 |
| value: 54.409 |
| - type: precision_at_1 |
| value: 44.389 |
| - type: precision_at_10 |
| value: 9.26 |
| - type: precision_at_100 |
| value: 1.222 |
| - type: precision_at_1000 |
| value: 0.13699999999999998 |
| - type: precision_at_3 |
| value: 23.03 |
| - type: precision_at_5 |
| value: 15.887 |
| - type: recall_at_1 |
| value: 38.797 |
| - type: recall_at_10 |
| value: 71.449 |
| - type: recall_at_100 |
| value: 88.881 |
| - type: recall_at_1000 |
| value: 97.52 |
| - type: recall_at_3 |
| value: 56.503 |
| - type: recall_at_5 |
| value: 63.392 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackGisRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 27.291999999999998 |
| - type: map_at_10 |
| value: 35.65 |
| - type: map_at_100 |
| value: 36.689 |
| - type: map_at_1000 |
| value: 36.753 |
| - type: map_at_3 |
| value: 32.995000000000005 |
| - type: map_at_5 |
| value: 34.409 |
| - type: mrr_at_1 |
| value: 29.04 |
| - type: mrr_at_10 |
| value: 37.486000000000004 |
| - type: mrr_at_100 |
| value: 38.394 |
| - type: mrr_at_1000 |
| value: 38.445 |
| - type: mrr_at_3 |
| value: 35.028 |
| - type: mrr_at_5 |
| value: 36.305 |
| - type: ndcg_at_1 |
| value: 29.04 |
| - type: ndcg_at_10 |
| value: 40.613 |
| - type: ndcg_at_100 |
| value: 45.733000000000004 |
| - type: ndcg_at_1000 |
| value: 47.447 |
| - type: ndcg_at_3 |
| value: 35.339999999999996 |
| - type: ndcg_at_5 |
| value: 37.706 |
| - type: precision_at_1 |
| value: 29.04 |
| - type: precision_at_10 |
| value: 6.192 |
| - type: precision_at_100 |
| value: 0.9249999999999999 |
| - type: precision_at_1000 |
| value: 0.11 |
| - type: precision_at_3 |
| value: 14.802000000000001 |
| - type: precision_at_5 |
| value: 10.305 |
| - type: recall_at_1 |
| value: 27.291999999999998 |
| - type: recall_at_10 |
| value: 54.25299999999999 |
| - type: recall_at_100 |
| value: 77.773 |
| - type: recall_at_1000 |
| value: 90.795 |
| - type: recall_at_3 |
| value: 39.731 |
| - type: recall_at_5 |
| value: 45.403999999999996 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackMathematicaRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 18.326 |
| - type: map_at_10 |
| value: 26.290999999999997 |
| - type: map_at_100 |
| value: 27.456999999999997 |
| - type: map_at_1000 |
| value: 27.583000000000002 |
| - type: map_at_3 |
| value: 23.578 |
| - type: map_at_5 |
| value: 25.113000000000003 |
| - type: mrr_at_1 |
| value: 22.637 |
| - type: mrr_at_10 |
| value: 31.139 |
| - type: mrr_at_100 |
| value: 32.074999999999996 |
| - type: mrr_at_1000 |
| value: 32.147 |
| - type: mrr_at_3 |
| value: 28.483000000000004 |
| - type: mrr_at_5 |
| value: 29.963 |
| - type: ndcg_at_1 |
| value: 22.637 |
| - type: ndcg_at_10 |
| value: 31.717000000000002 |
| - type: ndcg_at_100 |
| value: 37.201 |
| - type: ndcg_at_1000 |
| value: 40.088 |
| - type: ndcg_at_3 |
| value: 26.686 |
| - type: ndcg_at_5 |
| value: 29.076999999999998 |
| - type: precision_at_1 |
| value: 22.637 |
| - type: precision_at_10 |
| value: 5.7090000000000005 |
| - type: precision_at_100 |
| value: 0.979 |
| - type: precision_at_1000 |
| value: 0.13799999999999998 |
| - type: precision_at_3 |
| value: 12.894 |
| - type: precision_at_5 |
| value: 9.328 |
| - type: recall_at_1 |
| value: 18.326 |
| - type: recall_at_10 |
| value: 43.824999999999996 |
| - type: recall_at_100 |
| value: 67.316 |
| - type: recall_at_1000 |
| value: 87.481 |
| - type: recall_at_3 |
| value: 29.866999999999997 |
| - type: recall_at_5 |
| value: 35.961999999999996 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackPhysicsRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 29.875 |
| - type: map_at_10 |
| value: 40.458 |
| - type: map_at_100 |
| value: 41.772 |
| - type: map_at_1000 |
| value: 41.882999999999996 |
| - type: map_at_3 |
| value: 37.086999999999996 |
| - type: map_at_5 |
| value: 39.153 |
| - type: mrr_at_1 |
| value: 36.381 |
| - type: mrr_at_10 |
| value: 46.190999999999995 |
| - type: mrr_at_100 |
| value: 46.983999999999995 |
| - type: mrr_at_1000 |
| value: 47.032000000000004 |
| - type: mrr_at_3 |
| value: 43.486999999999995 |
| - type: mrr_at_5 |
| value: 45.249 |
| - type: ndcg_at_1 |
| value: 36.381 |
| - type: ndcg_at_10 |
| value: 46.602 |
| - type: ndcg_at_100 |
| value: 51.885999999999996 |
| - type: ndcg_at_1000 |
| value: 53.895 |
| - type: ndcg_at_3 |
| value: 41.155 |
| - type: ndcg_at_5 |
| value: 44.182 |
| - type: precision_at_1 |
| value: 36.381 |
| - type: precision_at_10 |
| value: 8.402 |
| - type: precision_at_100 |
| value: 1.278 |
| - type: precision_at_1000 |
| value: 0.16199999999999998 |
| - type: precision_at_3 |
| value: 19.346 |
| - type: precision_at_5 |
| value: 14.09 |
| - type: recall_at_1 |
| value: 29.875 |
| - type: recall_at_10 |
| value: 59.065999999999995 |
| - type: recall_at_100 |
| value: 80.923 |
| - type: recall_at_1000 |
| value: 93.927 |
| - type: recall_at_3 |
| value: 44.462 |
| - type: recall_at_5 |
| value: 51.89 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackProgrammersRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 24.94 |
| - type: map_at_10 |
| value: 35.125 |
| - type: map_at_100 |
| value: 36.476 |
| - type: map_at_1000 |
| value: 36.579 |
| - type: map_at_3 |
| value: 31.840000000000003 |
| - type: map_at_5 |
| value: 33.647 |
| - type: mrr_at_1 |
| value: 30.936000000000003 |
| - type: mrr_at_10 |
| value: 40.637 |
| - type: mrr_at_100 |
| value: 41.471000000000004 |
| - type: mrr_at_1000 |
| value: 41.525 |
| - type: mrr_at_3 |
| value: 38.013999999999996 |
| - type: mrr_at_5 |
| value: 39.469 |
| - type: ndcg_at_1 |
| value: 30.936000000000003 |
| - type: ndcg_at_10 |
| value: 41.295 |
| - type: ndcg_at_100 |
| value: 46.92 |
| - type: ndcg_at_1000 |
| value: 49.183 |
| - type: ndcg_at_3 |
| value: 35.811 |
| - type: ndcg_at_5 |
| value: 38.306000000000004 |
| - type: precision_at_1 |
| value: 30.936000000000003 |
| - type: precision_at_10 |
| value: 7.728 |
| - type: precision_at_100 |
| value: 1.226 |
| - type: precision_at_1000 |
| value: 0.158 |
| - type: precision_at_3 |
| value: 17.237 |
| - type: precision_at_5 |
| value: 12.42 |
| - type: recall_at_1 |
| value: 24.94 |
| - type: recall_at_10 |
| value: 54.235 |
| - type: recall_at_100 |
| value: 78.314 |
| - type: recall_at_1000 |
| value: 93.973 |
| - type: recall_at_3 |
| value: 38.925 |
| - type: recall_at_5 |
| value: 45.505 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 26.250833333333333 |
| - type: map_at_10 |
| value: 35.46875 |
| - type: map_at_100 |
| value: 36.667 |
| - type: map_at_1000 |
| value: 36.78025 |
| - type: map_at_3 |
| value: 32.56733333333334 |
| - type: map_at_5 |
| value: 34.20333333333333 |
| - type: mrr_at_1 |
| value: 30.8945 |
| - type: mrr_at_10 |
| value: 39.636833333333335 |
| - type: mrr_at_100 |
| value: 40.46508333333333 |
| - type: mrr_at_1000 |
| value: 40.521249999999995 |
| - type: mrr_at_3 |
| value: 37.140166666666666 |
| - type: mrr_at_5 |
| value: 38.60999999999999 |
| - type: ndcg_at_1 |
| value: 30.8945 |
| - type: ndcg_at_10 |
| value: 40.93441666666667 |
| - type: ndcg_at_100 |
| value: 46.062416666666664 |
| - type: ndcg_at_1000 |
| value: 48.28341666666667 |
| - type: ndcg_at_3 |
| value: 35.97575 |
| - type: ndcg_at_5 |
| value: 38.3785 |
| - type: precision_at_1 |
| value: 30.8945 |
| - type: precision_at_10 |
| value: 7.180250000000001 |
| - type: precision_at_100 |
| value: 1.1468333333333334 |
| - type: precision_at_1000 |
| value: 0.15283333333333332 |
| - type: precision_at_3 |
| value: 16.525583333333334 |
| - type: precision_at_5 |
| value: 11.798333333333332 |
| - type: recall_at_1 |
| value: 26.250833333333333 |
| - type: recall_at_10 |
| value: 52.96108333333333 |
| - type: recall_at_100 |
| value: 75.45908333333334 |
| - type: recall_at_1000 |
| value: 90.73924999999998 |
| - type: recall_at_3 |
| value: 39.25483333333333 |
| - type: recall_at_5 |
| value: 45.37950000000001 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackStatsRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 24.595 |
| - type: map_at_10 |
| value: 31.747999999999998 |
| - type: map_at_100 |
| value: 32.62 |
| - type: map_at_1000 |
| value: 32.713 |
| - type: map_at_3 |
| value: 29.48 |
| - type: map_at_5 |
| value: 30.635 |
| - type: mrr_at_1 |
| value: 27.607 |
| - type: mrr_at_10 |
| value: 34.449000000000005 |
| - type: mrr_at_100 |
| value: 35.182 |
| - type: mrr_at_1000 |
| value: 35.254000000000005 |
| - type: mrr_at_3 |
| value: 32.413 |
| - type: mrr_at_5 |
| value: 33.372 |
| - type: ndcg_at_1 |
| value: 27.607 |
| - type: ndcg_at_10 |
| value: 36.041000000000004 |
| - type: ndcg_at_100 |
| value: 40.514 |
| - type: ndcg_at_1000 |
| value: 42.851 |
| - type: ndcg_at_3 |
| value: 31.689 |
| - type: ndcg_at_5 |
| value: 33.479 |
| - type: precision_at_1 |
| value: 27.607 |
| - type: precision_at_10 |
| value: 5.66 |
| - type: precision_at_100 |
| value: 0.868 |
| - type: precision_at_1000 |
| value: 0.11299999999999999 |
| - type: precision_at_3 |
| value: 13.446 |
| - type: precision_at_5 |
| value: 9.264 |
| - type: recall_at_1 |
| value: 24.595 |
| - type: recall_at_10 |
| value: 46.79 |
| - type: recall_at_100 |
| value: 67.413 |
| - type: recall_at_1000 |
| value: 84.753 |
| - type: recall_at_3 |
| value: 34.644999999999996 |
| - type: recall_at_5 |
| value: 39.09 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackTexRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 17.333000000000002 |
| - type: map_at_10 |
| value: 24.427 |
| - type: map_at_100 |
| value: 25.576 |
| - type: map_at_1000 |
| value: 25.692999999999998 |
| - type: map_at_3 |
| value: 22.002 |
| - type: map_at_5 |
| value: 23.249 |
| - type: mrr_at_1 |
| value: 20.716 |
| - type: mrr_at_10 |
| value: 28.072000000000003 |
| - type: mrr_at_100 |
| value: 29.067 |
| - type: mrr_at_1000 |
| value: 29.137 |
| - type: mrr_at_3 |
| value: 25.832 |
| - type: mrr_at_5 |
| value: 27.045 |
| - type: ndcg_at_1 |
| value: 20.716 |
| - type: ndcg_at_10 |
| value: 29.109 |
| - type: ndcg_at_100 |
| value: 34.797 |
| - type: ndcg_at_1000 |
| value: 37.503 |
| - type: ndcg_at_3 |
| value: 24.668 |
| - type: ndcg_at_5 |
| value: 26.552999999999997 |
| - type: precision_at_1 |
| value: 20.716 |
| - type: precision_at_10 |
| value: 5.351 |
| - type: precision_at_100 |
| value: 0.955 |
| - type: precision_at_1000 |
| value: 0.136 |
| - type: precision_at_3 |
| value: 11.584999999999999 |
| - type: precision_at_5 |
| value: 8.362 |
| - type: recall_at_1 |
| value: 17.333000000000002 |
| - type: recall_at_10 |
| value: 39.604 |
| - type: recall_at_100 |
| value: 65.525 |
| - type: recall_at_1000 |
| value: 84.651 |
| - type: recall_at_3 |
| value: 27.199 |
| - type: recall_at_5 |
| value: 32.019 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackUnixRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 26.342 |
| - type: map_at_10 |
| value: 35.349000000000004 |
| - type: map_at_100 |
| value: 36.443 |
| - type: map_at_1000 |
| value: 36.548 |
| - type: map_at_3 |
| value: 32.307 |
| - type: map_at_5 |
| value: 34.164 |
| - type: mrr_at_1 |
| value: 31.063000000000002 |
| - type: mrr_at_10 |
| value: 39.703 |
| - type: mrr_at_100 |
| value: 40.555 |
| - type: mrr_at_1000 |
| value: 40.614 |
| - type: mrr_at_3 |
| value: 37.141999999999996 |
| - type: mrr_at_5 |
| value: 38.812000000000005 |
| - type: ndcg_at_1 |
| value: 31.063000000000002 |
| - type: ndcg_at_10 |
| value: 40.873 |
| - type: ndcg_at_100 |
| value: 45.896 |
| - type: ndcg_at_1000 |
| value: 48.205999999999996 |
| - type: ndcg_at_3 |
| value: 35.522 |
| - type: ndcg_at_5 |
| value: 38.419 |
| - type: precision_at_1 |
| value: 31.063000000000002 |
| - type: precision_at_10 |
| value: 6.866 |
| - type: precision_at_100 |
| value: 1.053 |
| - type: precision_at_1000 |
| value: 0.13699999999999998 |
| - type: precision_at_3 |
| value: 16.014 |
| - type: precision_at_5 |
| value: 11.604000000000001 |
| - type: recall_at_1 |
| value: 26.342 |
| - type: recall_at_10 |
| value: 53.40200000000001 |
| - type: recall_at_100 |
| value: 75.251 |
| - type: recall_at_1000 |
| value: 91.13799999999999 |
| - type: recall_at_3 |
| value: 39.103 |
| - type: recall_at_5 |
| value: 46.357 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackWebmastersRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 23.71 |
| - type: map_at_10 |
| value: 32.153999999999996 |
| - type: map_at_100 |
| value: 33.821 |
| - type: map_at_1000 |
| value: 34.034 |
| - type: map_at_3 |
| value: 29.376 |
| - type: map_at_5 |
| value: 30.878 |
| - type: mrr_at_1 |
| value: 28.458 |
| - type: mrr_at_10 |
| value: 36.775999999999996 |
| - type: mrr_at_100 |
| value: 37.804 |
| - type: mrr_at_1000 |
| value: 37.858999999999995 |
| - type: mrr_at_3 |
| value: 34.123999999999995 |
| - type: mrr_at_5 |
| value: 35.596 |
| - type: ndcg_at_1 |
| value: 28.458 |
| - type: ndcg_at_10 |
| value: 37.858999999999995 |
| - type: ndcg_at_100 |
| value: 44.194 |
| - type: ndcg_at_1000 |
| value: 46.744 |
| - type: ndcg_at_3 |
| value: 33.348 |
| - type: ndcg_at_5 |
| value: 35.448 |
| - type: precision_at_1 |
| value: 28.458 |
| - type: precision_at_10 |
| value: 7.4510000000000005 |
| - type: precision_at_100 |
| value: 1.5 |
| - type: precision_at_1000 |
| value: 0.23700000000000002 |
| - type: precision_at_3 |
| value: 15.809999999999999 |
| - type: precision_at_5 |
| value: 11.462 |
| - type: recall_at_1 |
| value: 23.71 |
| - type: recall_at_10 |
| value: 48.272999999999996 |
| - type: recall_at_100 |
| value: 77.134 |
| - type: recall_at_1000 |
| value: 93.001 |
| - type: recall_at_3 |
| value: 35.480000000000004 |
| - type: recall_at_5 |
| value: 41.19 |
| - task: |
| type: Retrieval |
| dataset: |
| type: BeIR/cqadupstack |
| name: MTEB CQADupstackWordpressRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 21.331 |
| - type: map_at_10 |
| value: 28.926000000000002 |
| - type: map_at_100 |
| value: 29.855999999999998 |
| - type: map_at_1000 |
| value: 29.957 |
| - type: map_at_3 |
| value: 26.395999999999997 |
| - type: map_at_5 |
| value: 27.933000000000003 |
| - type: mrr_at_1 |
| value: 23.105 |
| - type: mrr_at_10 |
| value: 31.008000000000003 |
| - type: mrr_at_100 |
| value: 31.819999999999997 |
| - type: mrr_at_1000 |
| value: 31.887999999999998 |
| - type: mrr_at_3 |
| value: 28.466 |
| - type: mrr_at_5 |
| value: 30.203000000000003 |
| - type: ndcg_at_1 |
| value: 23.105 |
| - type: ndcg_at_10 |
| value: 33.635999999999996 |
| - type: ndcg_at_100 |
| value: 38.277 |
| - type: ndcg_at_1000 |
| value: 40.907 |
| - type: ndcg_at_3 |
| value: 28.791 |
| - type: ndcg_at_5 |
| value: 31.528 |
| - type: precision_at_1 |
| value: 23.105 |
| - type: precision_at_10 |
| value: 5.323 |
| - type: precision_at_100 |
| value: 0.815 |
| - type: precision_at_1000 |
| value: 0.117 |
| - type: precision_at_3 |
| value: 12.384 |
| - type: precision_at_5 |
| value: 9.02 |
| - type: recall_at_1 |
| value: 21.331 |
| - type: recall_at_10 |
| value: 46.018 |
| - type: recall_at_100 |
| value: 67.364 |
| - type: recall_at_1000 |
| value: 86.97 |
| - type: recall_at_3 |
| value: 33.395 |
| - type: recall_at_5 |
| value: 39.931 |
| - task: |
| type: Retrieval |
| dataset: |
| type: climate-fever |
| name: MTEB ClimateFEVER |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 17.011000000000003 |
| - type: map_at_10 |
| value: 28.816999999999997 |
| - type: map_at_100 |
| value: 30.761 |
| - type: map_at_1000 |
| value: 30.958000000000002 |
| - type: map_at_3 |
| value: 24.044999999999998 |
| - type: map_at_5 |
| value: 26.557 |
| - type: mrr_at_1 |
| value: 38.696999999999996 |
| - type: mrr_at_10 |
| value: 50.464 |
| - type: mrr_at_100 |
| value: 51.193999999999996 |
| - type: mrr_at_1000 |
| value: 51.219 |
| - type: mrr_at_3 |
| value: 47.339999999999996 |
| - type: mrr_at_5 |
| value: 49.346000000000004 |
| - type: ndcg_at_1 |
| value: 38.696999999999996 |
| - type: ndcg_at_10 |
| value: 38.53 |
| - type: ndcg_at_100 |
| value: 45.525 |
| - type: ndcg_at_1000 |
| value: 48.685 |
| - type: ndcg_at_3 |
| value: 32.282 |
| - type: ndcg_at_5 |
| value: 34.482 |
| - type: precision_at_1 |
| value: 38.696999999999996 |
| - type: precision_at_10 |
| value: 11.895999999999999 |
| - type: precision_at_100 |
| value: 1.95 |
| - type: precision_at_1000 |
| value: 0.254 |
| - type: precision_at_3 |
| value: 24.038999999999998 |
| - type: precision_at_5 |
| value: 18.332 |
| - type: recall_at_1 |
| value: 17.011000000000003 |
| - type: recall_at_10 |
| value: 44.452999999999996 |
| - type: recall_at_100 |
| value: 68.223 |
| - type: recall_at_1000 |
| value: 85.653 |
| - type: recall_at_3 |
| value: 28.784 |
| - type: recall_at_5 |
| value: 35.66 |
| - task: |
| type: Retrieval |
| dataset: |
| type: dbpedia-entity |
| name: MTEB DBPedia |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 9.516 |
| - type: map_at_10 |
| value: 21.439 |
| - type: map_at_100 |
| value: 31.517 |
| - type: map_at_1000 |
| value: 33.267 |
| - type: map_at_3 |
| value: 15.004999999999999 |
| - type: map_at_5 |
| value: 17.793999999999997 |
| - type: mrr_at_1 |
| value: 71.25 |
| - type: mrr_at_10 |
| value: 79.071 |
| - type: mrr_at_100 |
| value: 79.325 |
| - type: mrr_at_1000 |
| value: 79.33 |
| - type: mrr_at_3 |
| value: 77.708 |
| - type: mrr_at_5 |
| value: 78.546 |
| - type: ndcg_at_1 |
| value: 58.62500000000001 |
| - type: ndcg_at_10 |
| value: 44.889 |
| - type: ndcg_at_100 |
| value: 50.536 |
| - type: ndcg_at_1000 |
| value: 57.724 |
| - type: ndcg_at_3 |
| value: 49.32 |
| - type: ndcg_at_5 |
| value: 46.775 |
| - type: precision_at_1 |
| value: 71.25 |
| - type: precision_at_10 |
| value: 36.175000000000004 |
| - type: precision_at_100 |
| value: 11.940000000000001 |
| - type: precision_at_1000 |
| value: 2.178 |
| - type: precision_at_3 |
| value: 53.583000000000006 |
| - type: precision_at_5 |
| value: 45.550000000000004 |
| - type: recall_at_1 |
| value: 9.516 |
| - type: recall_at_10 |
| value: 27.028000000000002 |
| - type: recall_at_100 |
| value: 57.581 |
| - type: recall_at_1000 |
| value: 80.623 |
| - type: recall_at_3 |
| value: 16.313 |
| - type: recall_at_5 |
| value: 20.674 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/emotion |
| name: MTEB EmotionClassification |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 51.74999999999999 |
| - type: f1 |
| value: 46.46706502669774 |
| - task: |
| type: Retrieval |
| dataset: |
| type: fever |
| name: MTEB FEVER |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 77.266 |
| - type: map_at_10 |
| value: 84.89999999999999 |
| - type: map_at_100 |
| value: 85.109 |
| - type: map_at_1000 |
| value: 85.123 |
| - type: map_at_3 |
| value: 83.898 |
| - type: map_at_5 |
| value: 84.541 |
| - type: mrr_at_1 |
| value: 83.138 |
| - type: mrr_at_10 |
| value: 89.37 |
| - type: mrr_at_100 |
| value: 89.432 |
| - type: mrr_at_1000 |
| value: 89.43299999999999 |
| - type: mrr_at_3 |
| value: 88.836 |
| - type: mrr_at_5 |
| value: 89.21 |
| - type: ndcg_at_1 |
| value: 83.138 |
| - type: ndcg_at_10 |
| value: 88.244 |
| - type: ndcg_at_100 |
| value: 88.98700000000001 |
| - type: ndcg_at_1000 |
| value: 89.21900000000001 |
| - type: ndcg_at_3 |
| value: 86.825 |
| - type: ndcg_at_5 |
| value: 87.636 |
| - type: precision_at_1 |
| value: 83.138 |
| - type: precision_at_10 |
| value: 10.47 |
| - type: precision_at_100 |
| value: 1.1079999999999999 |
| - type: precision_at_1000 |
| value: 0.11499999999999999 |
| - type: precision_at_3 |
| value: 32.933 |
| - type: precision_at_5 |
| value: 20.36 |
| - type: recall_at_1 |
| value: 77.266 |
| - type: recall_at_10 |
| value: 94.063 |
| - type: recall_at_100 |
| value: 96.993 |
| - type: recall_at_1000 |
| value: 98.414 |
| - type: recall_at_3 |
| value: 90.228 |
| - type: recall_at_5 |
| value: 92.328 |
| - task: |
| type: Retrieval |
| dataset: |
| type: fiqa |
| name: MTEB FiQA2018 |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 22.319 |
| - type: map_at_10 |
| value: 36.943 |
| - type: map_at_100 |
| value: 38.951 |
| - type: map_at_1000 |
| value: 39.114 |
| - type: map_at_3 |
| value: 32.82 |
| - type: map_at_5 |
| value: 34.945 |
| - type: mrr_at_1 |
| value: 44.135999999999996 |
| - type: mrr_at_10 |
| value: 53.071999999999996 |
| - type: mrr_at_100 |
| value: 53.87 |
| - type: mrr_at_1000 |
| value: 53.90200000000001 |
| - type: mrr_at_3 |
| value: 50.77199999999999 |
| - type: mrr_at_5 |
| value: 52.129999999999995 |
| - type: ndcg_at_1 |
| value: 44.135999999999996 |
| - type: ndcg_at_10 |
| value: 44.836 |
| - type: ndcg_at_100 |
| value: 51.754 |
| - type: ndcg_at_1000 |
| value: 54.36 |
| - type: ndcg_at_3 |
| value: 41.658 |
| - type: ndcg_at_5 |
| value: 42.354 |
| - type: precision_at_1 |
| value: 44.135999999999996 |
| - type: precision_at_10 |
| value: 12.284 |
| - type: precision_at_100 |
| value: 1.952 |
| - type: precision_at_1000 |
| value: 0.242 |
| - type: precision_at_3 |
| value: 27.828999999999997 |
| - type: precision_at_5 |
| value: 20.093 |
| - type: recall_at_1 |
| value: 22.319 |
| - type: recall_at_10 |
| value: 51.528 |
| - type: recall_at_100 |
| value: 76.70700000000001 |
| - type: recall_at_1000 |
| value: 92.143 |
| - type: recall_at_3 |
| value: 38.641 |
| - type: recall_at_5 |
| value: 43.653999999999996 |
| - task: |
| type: Retrieval |
| dataset: |
| type: hotpotqa |
| name: MTEB HotpotQA |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 40.182 |
| - type: map_at_10 |
| value: 65.146 |
| - type: map_at_100 |
| value: 66.023 |
| - type: map_at_1000 |
| value: 66.078 |
| - type: map_at_3 |
| value: 61.617999999999995 |
| - type: map_at_5 |
| value: 63.82299999999999 |
| - type: mrr_at_1 |
| value: 80.365 |
| - type: mrr_at_10 |
| value: 85.79 |
| - type: mrr_at_100 |
| value: 85.963 |
| - type: mrr_at_1000 |
| value: 85.968 |
| - type: mrr_at_3 |
| value: 84.952 |
| - type: mrr_at_5 |
| value: 85.503 |
| - type: ndcg_at_1 |
| value: 80.365 |
| - type: ndcg_at_10 |
| value: 73.13499999999999 |
| - type: ndcg_at_100 |
| value: 76.133 |
| - type: ndcg_at_1000 |
| value: 77.151 |
| - type: ndcg_at_3 |
| value: 68.255 |
| - type: ndcg_at_5 |
| value: 70.978 |
| - type: precision_at_1 |
| value: 80.365 |
| - type: precision_at_10 |
| value: 15.359 |
| - type: precision_at_100 |
| value: 1.7690000000000001 |
| - type: precision_at_1000 |
| value: 0.19 |
| - type: precision_at_3 |
| value: 44.024 |
| - type: precision_at_5 |
| value: 28.555999999999997 |
| - type: recall_at_1 |
| value: 40.182 |
| - type: recall_at_10 |
| value: 76.793 |
| - type: recall_at_100 |
| value: 88.474 |
| - type: recall_at_1000 |
| value: 95.159 |
| - type: recall_at_3 |
| value: 66.036 |
| - type: recall_at_5 |
| value: 71.391 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/imdb |
| name: MTEB ImdbClassification |
| config: default |
| split: test |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| metrics: |
| - type: accuracy |
| value: 92.7796 |
| - type: ap |
| value: 89.24883716810874 |
| - type: f1 |
| value: 92.7706903433313 |
| - task: |
| type: Retrieval |
| dataset: |
| type: msmarco |
| name: MTEB MSMARCO |
| config: default |
| split: dev |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 22.016 |
| - type: map_at_10 |
| value: 34.408 |
| - type: map_at_100 |
| value: 35.592 |
| - type: map_at_1000 |
| value: 35.64 |
| - type: map_at_3 |
| value: 30.459999999999997 |
| - type: map_at_5 |
| value: 32.721000000000004 |
| - type: mrr_at_1 |
| value: 22.593 |
| - type: mrr_at_10 |
| value: 34.993 |
| - type: mrr_at_100 |
| value: 36.113 |
| - type: mrr_at_1000 |
| value: 36.156 |
| - type: mrr_at_3 |
| value: 31.101 |
| - type: mrr_at_5 |
| value: 33.364 |
| - type: ndcg_at_1 |
| value: 22.579 |
| - type: ndcg_at_10 |
| value: 41.404999999999994 |
| - type: ndcg_at_100 |
| value: 47.018 |
| - type: ndcg_at_1000 |
| value: 48.211999999999996 |
| - type: ndcg_at_3 |
| value: 33.389 |
| - type: ndcg_at_5 |
| value: 37.425000000000004 |
| - type: precision_at_1 |
| value: 22.579 |
| - type: precision_at_10 |
| value: 6.59 |
| - type: precision_at_100 |
| value: 0.938 |
| - type: precision_at_1000 |
| value: 0.104 |
| - type: precision_at_3 |
| value: 14.241000000000001 |
| - type: precision_at_5 |
| value: 10.59 |
| - type: recall_at_1 |
| value: 22.016 |
| - type: recall_at_10 |
| value: 62.927 |
| - type: recall_at_100 |
| value: 88.72 |
| - type: recall_at_1000 |
| value: 97.80799999999999 |
| - type: recall_at_3 |
| value: 41.229 |
| - type: recall_at_5 |
| value: 50.88 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_domain |
| name: MTEB MTOPDomainClassification (en) |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 94.01732786137711 |
| - type: f1 |
| value: 93.76353126402202 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/mtop_intent |
| name: MTEB MTOPIntentClassification (en) |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 76.91746466028272 |
| - type: f1 |
| value: 57.715651682646765 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_intent |
| name: MTEB MassiveIntentClassification (en) |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 76.5030262273033 |
| - type: f1 |
| value: 74.6693629986121 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/amazon_massive_scenario |
| name: MTEB MassiveScenarioClassification (en) |
| config: en |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 79.74781439139207 |
| - type: f1 |
| value: 79.96684171018774 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-p2p |
| name: MTEB MedrxivClusteringP2P |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 33.2156206892017 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/medrxiv-clustering-s2s |
| name: MTEB MedrxivClusteringS2S |
| config: default |
| split: test |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| metrics: |
| - type: v_measure |
| value: 31.180539484816137 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/mind_small |
| name: MTEB MindSmallReranking |
| config: default |
| split: test |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| metrics: |
| - type: map |
| value: 32.51125957874274 |
| - type: mrr |
| value: 33.777037359249995 |
| - task: |
| type: Retrieval |
| dataset: |
| type: nfcorpus |
| name: MTEB NFCorpus |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 7.248 |
| - type: map_at_10 |
| value: 15.340000000000002 |
| - type: map_at_100 |
| value: 19.591 |
| - type: map_at_1000 |
| value: 21.187 |
| - type: map_at_3 |
| value: 11.329 |
| - type: map_at_5 |
| value: 13.209999999999999 |
| - type: mrr_at_1 |
| value: 47.678 |
| - type: mrr_at_10 |
| value: 57.493 |
| - type: mrr_at_100 |
| value: 58.038999999999994 |
| - type: mrr_at_1000 |
| value: 58.07 |
| - type: mrr_at_3 |
| value: 55.36600000000001 |
| - type: mrr_at_5 |
| value: 56.635999999999996 |
| - type: ndcg_at_1 |
| value: 46.129999999999995 |
| - type: ndcg_at_10 |
| value: 38.653999999999996 |
| - type: ndcg_at_100 |
| value: 36.288 |
| - type: ndcg_at_1000 |
| value: 44.765 |
| - type: ndcg_at_3 |
| value: 43.553 |
| - type: ndcg_at_5 |
| value: 41.317 |
| - type: precision_at_1 |
| value: 47.368 |
| - type: precision_at_10 |
| value: 28.669 |
| - type: precision_at_100 |
| value: 9.158 |
| - type: precision_at_1000 |
| value: 2.207 |
| - type: precision_at_3 |
| value: 40.97 |
| - type: precision_at_5 |
| value: 35.604 |
| - type: recall_at_1 |
| value: 7.248 |
| - type: recall_at_10 |
| value: 19.46 |
| - type: recall_at_100 |
| value: 37.214000000000006 |
| - type: recall_at_1000 |
| value: 67.64099999999999 |
| - type: recall_at_3 |
| value: 12.025 |
| - type: recall_at_5 |
| value: 15.443999999999999 |
| - task: |
| type: Retrieval |
| dataset: |
| type: nq |
| name: MTEB NQ |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 31.595000000000002 |
| - type: map_at_10 |
| value: 47.815999999999995 |
| - type: map_at_100 |
| value: 48.811 |
| - type: map_at_1000 |
| value: 48.835 |
| - type: map_at_3 |
| value: 43.225 |
| - type: map_at_5 |
| value: 46.017 |
| - type: mrr_at_1 |
| value: 35.689 |
| - type: mrr_at_10 |
| value: 50.341 |
| - type: mrr_at_100 |
| value: 51.044999999999995 |
| - type: mrr_at_1000 |
| value: 51.062 |
| - type: mrr_at_3 |
| value: 46.553 |
| - type: mrr_at_5 |
| value: 48.918 |
| - type: ndcg_at_1 |
| value: 35.66 |
| - type: ndcg_at_10 |
| value: 55.859 |
| - type: ndcg_at_100 |
| value: 59.864 |
| - type: ndcg_at_1000 |
| value: 60.419999999999995 |
| - type: ndcg_at_3 |
| value: 47.371 |
| - type: ndcg_at_5 |
| value: 51.995000000000005 |
| - type: precision_at_1 |
| value: 35.66 |
| - type: precision_at_10 |
| value: 9.27 |
| - type: precision_at_100 |
| value: 1.1520000000000001 |
| - type: precision_at_1000 |
| value: 0.12 |
| - type: precision_at_3 |
| value: 21.63 |
| - type: precision_at_5 |
| value: 15.655 |
| - type: recall_at_1 |
| value: 31.595000000000002 |
| - type: recall_at_10 |
| value: 77.704 |
| - type: recall_at_100 |
| value: 94.774 |
| - type: recall_at_1000 |
| value: 98.919 |
| - type: recall_at_3 |
| value: 56.052 |
| - type: recall_at_5 |
| value: 66.623 |
| - task: |
| type: Retrieval |
| dataset: |
| type: quora |
| name: MTEB QuoraRetrieval |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 71.489 |
| - type: map_at_10 |
| value: 85.411 |
| - type: map_at_100 |
| value: 86.048 |
| - type: map_at_1000 |
| value: 86.064 |
| - type: map_at_3 |
| value: 82.587 |
| - type: map_at_5 |
| value: 84.339 |
| - type: mrr_at_1 |
| value: 82.28 |
| - type: mrr_at_10 |
| value: 88.27199999999999 |
| - type: mrr_at_100 |
| value: 88.362 |
| - type: mrr_at_1000 |
| value: 88.362 |
| - type: mrr_at_3 |
| value: 87.372 |
| - type: mrr_at_5 |
| value: 87.995 |
| - type: ndcg_at_1 |
| value: 82.27 |
| - type: ndcg_at_10 |
| value: 89.023 |
| - type: ndcg_at_100 |
| value: 90.191 |
| - type: ndcg_at_1000 |
| value: 90.266 |
| - type: ndcg_at_3 |
| value: 86.37 |
| - type: ndcg_at_5 |
| value: 87.804 |
| - type: precision_at_1 |
| value: 82.27 |
| - type: precision_at_10 |
| value: 13.469000000000001 |
| - type: precision_at_100 |
| value: 1.533 |
| - type: precision_at_1000 |
| value: 0.157 |
| - type: precision_at_3 |
| value: 37.797 |
| - type: precision_at_5 |
| value: 24.734 |
| - type: recall_at_1 |
| value: 71.489 |
| - type: recall_at_10 |
| value: 95.824 |
| - type: recall_at_100 |
| value: 99.70599999999999 |
| - type: recall_at_1000 |
| value: 99.979 |
| - type: recall_at_3 |
| value: 88.099 |
| - type: recall_at_5 |
| value: 92.285 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering |
| name: MTEB RedditClustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 60.52398807444541 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/reddit-clustering-p2p |
| name: MTEB RedditClusteringP2P |
| config: default |
| split: test |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| metrics: |
| - type: v_measure |
| value: 65.34855891507871 |
| - task: |
| type: Retrieval |
| dataset: |
| type: scidocs |
| name: MTEB SCIDOCS |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 5.188000000000001 |
| - type: map_at_10 |
| value: 13.987 |
| - type: map_at_100 |
| value: 16.438 |
| - type: map_at_1000 |
| value: 16.829 |
| - type: map_at_3 |
| value: 9.767000000000001 |
| - type: map_at_5 |
| value: 11.912 |
| - type: mrr_at_1 |
| value: 25.6 |
| - type: mrr_at_10 |
| value: 37.744 |
| - type: mrr_at_100 |
| value: 38.847 |
| - type: mrr_at_1000 |
| value: 38.894 |
| - type: mrr_at_3 |
| value: 34.166999999999994 |
| - type: mrr_at_5 |
| value: 36.207 |
| - type: ndcg_at_1 |
| value: 25.6 |
| - type: ndcg_at_10 |
| value: 22.980999999999998 |
| - type: ndcg_at_100 |
| value: 32.039 |
| - type: ndcg_at_1000 |
| value: 38.157000000000004 |
| - type: ndcg_at_3 |
| value: 21.567 |
| - type: ndcg_at_5 |
| value: 19.070999999999998 |
| - type: precision_at_1 |
| value: 25.6 |
| - type: precision_at_10 |
| value: 12.02 |
| - type: precision_at_100 |
| value: 2.5100000000000002 |
| - type: precision_at_1000 |
| value: 0.396 |
| - type: precision_at_3 |
| value: 20.333000000000002 |
| - type: precision_at_5 |
| value: 16.98 |
| - type: recall_at_1 |
| value: 5.188000000000001 |
| - type: recall_at_10 |
| value: 24.372 |
| - type: recall_at_100 |
| value: 50.934999999999995 |
| - type: recall_at_1000 |
| value: 80.477 |
| - type: recall_at_3 |
| value: 12.363 |
| - type: recall_at_5 |
| value: 17.203 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sickr-sts |
| name: MTEB SICK-R |
| config: default |
| split: test |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| metrics: |
| - type: cos_sim_pearson |
| value: 87.24286275535398 |
| - type: cos_sim_spearman |
| value: 82.62333770991818 |
| - type: euclidean_pearson |
| value: 84.60353717637284 |
| - type: euclidean_spearman |
| value: 82.32990108810047 |
| - type: manhattan_pearson |
| value: 84.6089049738196 |
| - type: manhattan_spearman |
| value: 82.33361785438936 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts12-sts |
| name: MTEB STS12 |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 87.87428858503165 |
| - type: cos_sim_spearman |
| value: 79.09145886519929 |
| - type: euclidean_pearson |
| value: 86.42669231664036 |
| - type: euclidean_spearman |
| value: 80.03127375435449 |
| - type: manhattan_pearson |
| value: 86.41330338305022 |
| - type: manhattan_spearman |
| value: 80.02492538673368 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts13-sts |
| name: MTEB STS13 |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 88.67912277322645 |
| - type: cos_sim_spearman |
| value: 89.6171319711762 |
| - type: euclidean_pearson |
| value: 86.56571917398725 |
| - type: euclidean_spearman |
| value: 87.71216907898948 |
| - type: manhattan_pearson |
| value: 86.57459050182473 |
| - type: manhattan_spearman |
| value: 87.71916648349993 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts14-sts |
| name: MTEB STS14 |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 86.71957379085862 |
| - type: cos_sim_spearman |
| value: 85.01784075851465 |
| - type: euclidean_pearson |
| value: 84.7407848472801 |
| - type: euclidean_spearman |
| value: 84.61063091345538 |
| - type: manhattan_pearson |
| value: 84.71494352494403 |
| - type: manhattan_spearman |
| value: 84.58772077604254 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts15-sts |
| name: MTEB STS15 |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 88.40508326325175 |
| - type: cos_sim_spearman |
| value: 89.50912897763186 |
| - type: euclidean_pearson |
| value: 87.82349070086627 |
| - type: euclidean_spearman |
| value: 88.44179162727521 |
| - type: manhattan_pearson |
| value: 87.80181927025595 |
| - type: manhattan_spearman |
| value: 88.43205129636243 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/sts16-sts |
| name: MTEB STS16 |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 85.35846741715478 |
| - type: cos_sim_spearman |
| value: 86.61172476741842 |
| - type: euclidean_pearson |
| value: 84.60123125491637 |
| - type: euclidean_spearman |
| value: 85.3001948141827 |
| - type: manhattan_pearson |
| value: 84.56231142658329 |
| - type: manhattan_spearman |
| value: 85.23579900798813 |
| - 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: 88.94539129818824 |
| - type: cos_sim_spearman |
| value: 88.99349064256742 |
| - type: euclidean_pearson |
| value: 88.7142444640351 |
| - type: euclidean_spearman |
| value: 88.34120813505011 |
| - type: manhattan_pearson |
| value: 88.70363008238084 |
| - type: manhattan_spearman |
| value: 88.31952816956954 |
| - 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: 68.29910260369893 |
| - type: cos_sim_spearman |
| value: 68.79263346213466 |
| - type: euclidean_pearson |
| value: 68.41627521422252 |
| - type: euclidean_spearman |
| value: 66.61602587398579 |
| - type: manhattan_pearson |
| value: 68.49402183447361 |
| - type: manhattan_spearman |
| value: 66.80157792354453 |
| - task: |
| type: STS |
| dataset: |
| type: mteb/stsbenchmark-sts |
| name: MTEB STSBenchmark |
| config: default |
| split: test |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| metrics: |
| - type: cos_sim_pearson |
| value: 87.43703906343708 |
| - type: cos_sim_spearman |
| value: 89.06081805093662 |
| - type: euclidean_pearson |
| value: 87.48311456299662 |
| - type: euclidean_spearman |
| value: 88.07417597580013 |
| - type: manhattan_pearson |
| value: 87.48202249768894 |
| - type: manhattan_spearman |
| value: 88.04758031111642 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/scidocs-reranking |
| name: MTEB SciDocsRR |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 87.49080620485203 |
| - type: mrr |
| value: 96.19145378949301 |
| - task: |
| type: Retrieval |
| dataset: |
| type: scifact |
| name: MTEB SciFact |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 59.317 |
| - type: map_at_10 |
| value: 69.296 |
| - type: map_at_100 |
| value: 69.738 |
| - type: map_at_1000 |
| value: 69.759 |
| - type: map_at_3 |
| value: 66.12599999999999 |
| - type: map_at_5 |
| value: 67.532 |
| - type: mrr_at_1 |
| value: 62 |
| - type: mrr_at_10 |
| value: 70.176 |
| - type: mrr_at_100 |
| value: 70.565 |
| - type: mrr_at_1000 |
| value: 70.583 |
| - type: mrr_at_3 |
| value: 67.833 |
| - type: mrr_at_5 |
| value: 68.93299999999999 |
| - type: ndcg_at_1 |
| value: 62 |
| - type: ndcg_at_10 |
| value: 74.069 |
| - type: ndcg_at_100 |
| value: 76.037 |
| - type: ndcg_at_1000 |
| value: 76.467 |
| - type: ndcg_at_3 |
| value: 68.628 |
| - type: ndcg_at_5 |
| value: 70.57600000000001 |
| - type: precision_at_1 |
| value: 62 |
| - type: precision_at_10 |
| value: 10 |
| - type: precision_at_100 |
| value: 1.097 |
| - type: precision_at_1000 |
| value: 0.11299999999999999 |
| - type: precision_at_3 |
| value: 26.667 |
| - type: precision_at_5 |
| value: 17.4 |
| - type: recall_at_1 |
| value: 59.317 |
| - type: recall_at_10 |
| value: 87.822 |
| - type: recall_at_100 |
| value: 96.833 |
| - type: recall_at_1000 |
| value: 100 |
| - type: recall_at_3 |
| value: 73.06099999999999 |
| - type: recall_at_5 |
| value: 77.928 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/sprintduplicatequestions-pairclassification |
| name: MTEB SprintDuplicateQuestions |
| config: default |
| split: test |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 99.88910891089108 |
| - type: cos_sim_ap |
| value: 97.236958456951 |
| - type: cos_sim_f1 |
| value: 94.39999999999999 |
| - type: cos_sim_precision |
| value: 94.39999999999999 |
| - type: cos_sim_recall |
| value: 94.39999999999999 |
| - type: dot_accuracy |
| value: 99.82574257425742 |
| - type: dot_ap |
| value: 94.94344759441888 |
| - type: dot_f1 |
| value: 91.17352056168507 |
| - type: dot_precision |
| value: 91.44869215291752 |
| - type: dot_recall |
| value: 90.9 |
| - type: euclidean_accuracy |
| value: 99.88415841584158 |
| - type: euclidean_ap |
| value: 97.2044250782305 |
| - type: euclidean_f1 |
| value: 94.210786739238 |
| - type: euclidean_precision |
| value: 93.24191968658178 |
| - type: euclidean_recall |
| value: 95.19999999999999 |
| - type: manhattan_accuracy |
| value: 99.88613861386139 |
| - type: manhattan_ap |
| value: 97.20683205497689 |
| - type: manhattan_f1 |
| value: 94.2643391521197 |
| - type: manhattan_precision |
| value: 94.02985074626866 |
| - type: manhattan_recall |
| value: 94.5 |
| - type: max_accuracy |
| value: 99.88910891089108 |
| - type: max_ap |
| value: 97.236958456951 |
| - type: max_f1 |
| value: 94.39999999999999 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering |
| name: MTEB StackExchangeClustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 66.53940781726187 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/stackexchange-clustering-p2p |
| name: MTEB StackExchangeClusteringP2P |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 36.71865011295108 |
| - task: |
| type: Reranking |
| dataset: |
| type: mteb/stackoverflowdupquestions-reranking |
| name: MTEB StackOverflowDupQuestions |
| config: default |
| split: test |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| metrics: |
| - type: map |
| value: 55.3218674533331 |
| - type: mrr |
| value: 56.28279910449028 |
| - task: |
| type: Summarization |
| dataset: |
| type: mteb/summeval |
| name: MTEB SummEval |
| config: default |
| split: test |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| metrics: |
| - type: cos_sim_pearson |
| value: 30.723915667479673 |
| - type: cos_sim_spearman |
| value: 32.029070449745234 |
| - type: dot_pearson |
| value: 28.864944212481454 |
| - type: dot_spearman |
| value: 27.939266999596725 |
| - task: |
| type: Retrieval |
| dataset: |
| type: trec-covid |
| name: MTEB TRECCOVID |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 0.231 |
| - type: map_at_10 |
| value: 1.949 |
| - type: map_at_100 |
| value: 10.023 |
| - type: map_at_1000 |
| value: 23.485 |
| - type: map_at_3 |
| value: 0.652 |
| - type: map_at_5 |
| value: 1.054 |
| - type: mrr_at_1 |
| value: 86 |
| - type: mrr_at_10 |
| value: 92.067 |
| - type: mrr_at_100 |
| value: 92.067 |
| - type: mrr_at_1000 |
| value: 92.067 |
| - type: mrr_at_3 |
| value: 91.667 |
| - type: mrr_at_5 |
| value: 92.067 |
| - type: ndcg_at_1 |
| value: 83 |
| - type: ndcg_at_10 |
| value: 76.32900000000001 |
| - type: ndcg_at_100 |
| value: 54.662 |
| - type: ndcg_at_1000 |
| value: 48.062 |
| - type: ndcg_at_3 |
| value: 81.827 |
| - type: ndcg_at_5 |
| value: 80.664 |
| - type: precision_at_1 |
| value: 86 |
| - type: precision_at_10 |
| value: 80 |
| - type: precision_at_100 |
| value: 55.48 |
| - type: precision_at_1000 |
| value: 20.938000000000002 |
| - type: precision_at_3 |
| value: 85.333 |
| - type: precision_at_5 |
| value: 84.39999999999999 |
| - type: recall_at_1 |
| value: 0.231 |
| - type: recall_at_10 |
| value: 2.158 |
| - type: recall_at_100 |
| value: 13.344000000000001 |
| - type: recall_at_1000 |
| value: 44.31 |
| - type: recall_at_3 |
| value: 0.6779999999999999 |
| - type: recall_at_5 |
| value: 1.13 |
| - task: |
| type: Retrieval |
| dataset: |
| type: webis-touche2020 |
| name: MTEB Touche2020 |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 2.524 |
| - type: map_at_10 |
| value: 10.183 |
| - type: map_at_100 |
| value: 16.625 |
| - type: map_at_1000 |
| value: 18.017 |
| - type: map_at_3 |
| value: 5.169 |
| - type: map_at_5 |
| value: 6.772 |
| - type: mrr_at_1 |
| value: 32.653 |
| - type: mrr_at_10 |
| value: 47.128 |
| - type: mrr_at_100 |
| value: 48.458 |
| - type: mrr_at_1000 |
| value: 48.473 |
| - type: mrr_at_3 |
| value: 44.897999999999996 |
| - type: mrr_at_5 |
| value: 45.306000000000004 |
| - type: ndcg_at_1 |
| value: 30.612000000000002 |
| - type: ndcg_at_10 |
| value: 24.928 |
| - type: ndcg_at_100 |
| value: 37.613 |
| - type: ndcg_at_1000 |
| value: 48.528 |
| - type: ndcg_at_3 |
| value: 28.829 |
| - type: ndcg_at_5 |
| value: 25.237 |
| - type: precision_at_1 |
| value: 32.653 |
| - type: precision_at_10 |
| value: 22.448999999999998 |
| - type: precision_at_100 |
| value: 8.02 |
| - type: precision_at_1000 |
| value: 1.537 |
| - type: precision_at_3 |
| value: 30.612000000000002 |
| - type: precision_at_5 |
| value: 24.490000000000002 |
| - type: recall_at_1 |
| value: 2.524 |
| - type: recall_at_10 |
| value: 16.38 |
| - type: recall_at_100 |
| value: 49.529 |
| - type: recall_at_1000 |
| value: 83.598 |
| - type: recall_at_3 |
| value: 6.411 |
| - type: recall_at_5 |
| value: 8.932 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/toxic_conversations_50k |
| name: MTEB ToxicConversationsClassification |
| config: default |
| split: test |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
| metrics: |
| - type: accuracy |
| value: 71.09020000000001 |
| - type: ap |
| value: 14.451710060978993 |
| - type: f1 |
| value: 54.7874410609049 |
| - task: |
| type: Classification |
| dataset: |
| type: mteb/tweet_sentiment_extraction |
| name: MTEB TweetSentimentExtractionClassification |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 59.745331069609506 |
| - type: f1 |
| value: 60.08387848592697 |
| - task: |
| type: Clustering |
| dataset: |
| type: mteb/twentynewsgroups-clustering |
| name: MTEB TwentyNewsgroupsClustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 51.71549485462037 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twittersemeval2015-pairclassification |
| name: MTEB TwitterSemEval2015 |
| config: default |
| split: test |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 87.39345532574357 |
| - type: cos_sim_ap |
| value: 78.16796549696478 |
| - type: cos_sim_f1 |
| value: 71.27713276123171 |
| - type: cos_sim_precision |
| value: 68.3115626511853 |
| - type: cos_sim_recall |
| value: 74.51187335092348 |
| - type: dot_accuracy |
| value: 85.12248912201228 |
| - type: dot_ap |
| value: 69.26039256107077 |
| - type: dot_f1 |
| value: 65.04294321240867 |
| - type: dot_precision |
| value: 63.251059586138126 |
| - type: dot_recall |
| value: 66.93931398416886 |
| - type: euclidean_accuracy |
| value: 87.07754664123503 |
| - type: euclidean_ap |
| value: 77.7872176038945 |
| - type: euclidean_f1 |
| value: 70.85587801278899 |
| - type: euclidean_precision |
| value: 66.3519115614924 |
| - type: euclidean_recall |
| value: 76.01583113456465 |
| - type: manhattan_accuracy |
| value: 87.07754664123503 |
| - type: manhattan_ap |
| value: 77.7341400185556 |
| - type: manhattan_f1 |
| value: 70.80310880829015 |
| - type: manhattan_precision |
| value: 69.54198473282443 |
| - type: manhattan_recall |
| value: 72.1108179419525 |
| - type: max_accuracy |
| value: 87.39345532574357 |
| - type: max_ap |
| value: 78.16796549696478 |
| - type: max_f1 |
| value: 71.27713276123171 |
| - task: |
| type: PairClassification |
| dataset: |
| type: mteb/twitterurlcorpus-pairclassification |
| name: MTEB TwitterURLCorpus |
| config: default |
| split: test |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| metrics: |
| - type: cos_sim_accuracy |
| value: 89.09457833663213 |
| - type: cos_sim_ap |
| value: 86.33024314706873 |
| - type: cos_sim_f1 |
| value: 78.59623733719248 |
| - type: cos_sim_precision |
| value: 74.13322413322413 |
| - type: cos_sim_recall |
| value: 83.63104404065291 |
| - type: dot_accuracy |
| value: 88.3086894089339 |
| - type: dot_ap |
| value: 83.92225241805097 |
| - type: dot_f1 |
| value: 76.8721826377781 |
| - type: dot_precision |
| value: 72.8168044077135 |
| - type: dot_recall |
| value: 81.40591315060055 |
| - type: euclidean_accuracy |
| value: 88.77052043311213 |
| - type: euclidean_ap |
| value: 85.7410710218755 |
| - type: euclidean_f1 |
| value: 77.97705489398781 |
| - type: euclidean_precision |
| value: 73.77713657598241 |
| - type: euclidean_recall |
| value: 82.68401601478288 |
| - type: manhattan_accuracy |
| value: 88.73753250281368 |
| - type: manhattan_ap |
| value: 85.72867199072802 |
| - type: manhattan_f1 |
| value: 77.89774182922812 |
| - type: manhattan_precision |
| value: 74.23787931635857 |
| - type: manhattan_recall |
| value: 81.93717277486911 |
| - type: max_accuracy |
| value: 89.09457833663213 |
| - type: max_ap |
| value: 86.33024314706873 |
| - type: max_f1 |
| value: 78.59623733719248 |
| license: mit |
| language: |
| - en |
| library_name: sentence-transformers |
| --- |
| |
|
|
| # [Universal AnglE Embedding](https://github.com/SeanLee97/AnglE) |
|
|
| Follow us on: |
|
|
| - GitHub: https://github.com/SeanLee97/AnglE. |
| - Arxiv: https://arxiv.org/abs/2309.12871 |
|
|
|
|
| 🔥 Our universal English sentence embedding `WhereIsAI/UAE-Large-V1` achieves **SOTA** on the [MTEB Leaderboard](https://huggingface.co/spaces/mteb/leaderboard) with an average score of 64.64! |
|
|
|
|
|  |
|
|
|
|
| # Usage |
|
|
|
|
| ```bash |
| python -m pip install -U angle-emb |
| ``` |
|
|
| 1) Non-Retrieval Tasks |
|
|
| ```python |
| from angle_emb import AnglE |
| |
| angle = AnglE.from_pretrained('WhereIsAI/UAE-Large-V1', pooling_strategy='cls').cuda() |
| vec = angle.encode('hello world', to_numpy=True) |
| print(vec) |
| vecs = angle.encode(['hello world1', 'hello world2'], to_numpy=True) |
| print(vecs) |
| ``` |
|
|
| 2) Retrieval Tasks |
|
|
| For retrieval purposes, please use the prompt `Prompts.C`. |
|
|
| ```python |
| from angle_emb import AnglE, Prompts |
| |
| angle = AnglE.from_pretrained('WhereIsAI/UAE-Large-V1', pooling_strategy='cls').cuda() |
| angle.set_prompt(prompt=Prompts.C) |
| vec = angle.encode({'text': 'hello world'}, to_numpy=True) |
| print(vec) |
| vecs = angle.encode([{'text': 'hello world1'}, {'text': 'hello world2'}], to_numpy=True) |
| print(vecs) |
| ``` |
|
|
| # Citation |
|
|
| If you use our pre-trained models, welcome to support us by citing our work: |
|
|
| ``` |
| @article{li2023angle, |
| title={AnglE-optimized Text Embeddings}, |
| author={Li, Xianming and Li, Jing}, |
| journal={arXiv preprint arXiv:2309.12871}, |
| year={2023} |
| } |
| ``` |
