--- tags: - mteb model-index: - name: mteb_metrics results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 76.22388059701493 - type: ap value: 40.27466219523129 - type: f1 value: 70.60533006025108 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 87.525775 - type: ap value: 83.51063993897611 - type: f1 value: 87.49342736805572 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 42.611999999999995 - type: f1 value: 42.05088045932892 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 23.826 - type: map_at_10 value: 38.269 - type: map_at_100 value: 39.322 - type: map_at_1000 value: 39.344 - type: map_at_3 value: 33.428000000000004 - type: map_at_5 value: 36.063 - type: mrr_at_1 value: 24.253 - type: mrr_at_10 value: 38.425 - type: mrr_at_100 value: 39.478 - type: mrr_at_1000 value: 39.5 - type: mrr_at_3 value: 33.606 - type: mrr_at_5 value: 36.195 - type: ndcg_at_1 value: 23.826 - type: ndcg_at_10 value: 46.693 - type: ndcg_at_100 value: 51.469 - type: ndcg_at_1000 value: 52.002 - type: ndcg_at_3 value: 36.603 - type: ndcg_at_5 value: 41.365 - type: precision_at_1 value: 23.826 - type: precision_at_10 value: 7.383000000000001 - type: precision_at_100 value: 0.9530000000000001 - type: precision_at_1000 value: 0.099 - type: precision_at_3 value: 15.268 - type: precision_at_5 value: 11.479000000000001 - type: recall_at_1 value: 23.826 - type: recall_at_10 value: 73.82600000000001 - type: recall_at_100 value: 95.306 - type: recall_at_1000 value: 99.431 - type: recall_at_3 value: 45.804 - type: recall_at_5 value: 57.397 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 44.13995374767436 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 37.13950072624313 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 59.35843292105327 - type: mrr value: 73.72312359846987 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 84.55140418324174 - type: cos_sim_spearman value: 84.21637675860022 - type: euclidean_pearson value: 81.26069614610006 - type: euclidean_spearman value: 83.25069210421785 - type: manhattan_pearson value: 80.17441422581014 - type: manhattan_spearman value: 81.87596198487877 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 81.87337662337661 - type: f1 value: 81.76647866926402 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 35.80600542614507 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 31.86321613256603 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 32.054 - type: map_at_10 value: 40.699999999999996 - type: map_at_100 value: 41.818 - type: map_at_1000 value: 41.959999999999994 - type: map_at_3 value: 37.742 - type: map_at_5 value: 39.427 - type: mrr_at_1 value: 38.769999999999996 - type: mrr_at_10 value: 46.150000000000006 - type: mrr_at_100 value: 46.865 - type: mrr_at_1000 value: 46.925 - type: mrr_at_3 value: 43.705 - type: mrr_at_5 value: 45.214999999999996 - type: ndcg_at_1 value: 38.769999999999996 - type: ndcg_at_10 value: 45.778 - type: ndcg_at_100 value: 50.38 - type: ndcg_at_1000 value: 52.922999999999995 - type: ndcg_at_3 value: 41.597 - type: ndcg_at_5 value: 43.631 - type: precision_at_1 value: 38.769999999999996 - type: precision_at_10 value: 8.269 - type: precision_at_100 value: 1.278 - type: precision_at_1000 value: 0.178 - type: precision_at_3 value: 19.266 - type: precision_at_5 value: 13.705 - type: recall_at_1 value: 32.054 - type: recall_at_10 value: 54.947 - type: recall_at_100 value: 74.79599999999999 - type: recall_at_1000 value: 91.40899999999999 - type: recall_at_3 value: 42.431000000000004 - type: recall_at_5 value: 48.519 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 29.035 - type: map_at_10 value: 38.007000000000005 - type: map_at_100 value: 39.125 - type: map_at_1000 value: 39.251999999999995 - type: map_at_3 value: 35.77 - type: map_at_5 value: 37.057 - type: mrr_at_1 value: 36.497 - type: mrr_at_10 value: 44.077 - type: mrr_at_100 value: 44.743 - type: mrr_at_1000 value: 44.79 - type: mrr_at_3 value: 42.123 - type: mrr_at_5 value: 43.308 - type: ndcg_at_1 value: 36.497 - type: ndcg_at_10 value: 42.986000000000004 - type: ndcg_at_100 value: 47.323 - type: ndcg_at_1000 value: 49.624 - type: ndcg_at_3 value: 39.805 - type: ndcg_at_5 value: 41.286 - type: precision_at_1 value: 36.497 - type: precision_at_10 value: 7.8340000000000005 - type: precision_at_100 value: 1.269 - type: precision_at_1000 value: 0.178 - type: precision_at_3 value: 19.023 - type: precision_at_5 value: 13.248 - type: recall_at_1 value: 29.035 - type: recall_at_10 value: 51.06 - type: recall_at_100 value: 69.64099999999999 - type: recall_at_1000 value: 84.49 - type: recall_at_3 value: 41.333999999999996 - type: recall_at_5 value: 45.663 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 37.239 - type: map_at_10 value: 47.873 - type: map_at_100 value: 48.842999999999996 - type: map_at_1000 value: 48.913000000000004 - type: map_at_3 value: 45.050000000000004 - type: map_at_5 value: 46.498 - type: mrr_at_1 value: 42.508 - type: mrr_at_10 value: 51.44 - type: mrr_at_100 value: 52.087 - type: mrr_at_1000 value: 52.129999999999995 - type: mrr_at_3 value: 49.164 - type: mrr_at_5 value: 50.343 - type: ndcg_at_1 value: 42.508 - type: ndcg_at_10 value: 53.31399999999999 - type: ndcg_at_100 value: 57.245000000000005 - type: ndcg_at_1000 value: 58.794000000000004 - type: ndcg_at_3 value: 48.295 - type: ndcg_at_5 value: 50.415 - type: precision_at_1 value: 42.508 - type: precision_at_10 value: 8.458 - type: precision_at_100 value: 1.133 - type: precision_at_1000 value: 0.132 - type: precision_at_3 value: 21.191 - type: precision_at_5 value: 14.307 - type: recall_at_1 value: 37.239 - type: recall_at_10 value: 65.99000000000001 - type: recall_at_100 value: 82.99499999999999 - type: recall_at_1000 value: 94.128 - type: recall_at_3 value: 52.382 - type: recall_at_5 value: 57.648999999999994 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 23.039 - type: map_at_10 value: 29.694 - type: map_at_100 value: 30.587999999999997 - type: map_at_1000 value: 30.692999999999998 - type: map_at_3 value: 27.708 - type: map_at_5 value: 28.774 - type: mrr_at_1 value: 24.633 - type: mrr_at_10 value: 31.478 - type: mrr_at_100 value: 32.299 - type: mrr_at_1000 value: 32.381 - type: mrr_at_3 value: 29.435 - type: mrr_at_5 value: 30.446 - type: ndcg_at_1 value: 24.633 - type: ndcg_at_10 value: 33.697 - type: ndcg_at_100 value: 38.080000000000005 - type: ndcg_at_1000 value: 40.812 - type: ndcg_at_3 value: 29.654000000000003 - type: ndcg_at_5 value: 31.474000000000004 - type: precision_at_1 value: 24.633 - type: precision_at_10 value: 5.0729999999999995 - type: precision_at_100 value: 0.753 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 12.279 - type: precision_at_5 value: 8.452 - type: recall_at_1 value: 23.039 - type: recall_at_10 value: 44.275999999999996 - type: recall_at_100 value: 64.4 - type: recall_at_1000 value: 85.135 - type: recall_at_3 value: 33.394 - type: recall_at_5 value: 37.687 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 13.594999999999999 - type: map_at_10 value: 19.933999999999997 - type: map_at_100 value: 20.966 - type: map_at_1000 value: 21.087 - type: map_at_3 value: 17.749000000000002 - type: map_at_5 value: 19.156000000000002 - type: mrr_at_1 value: 17.662 - type: mrr_at_10 value: 24.407 - type: mrr_at_100 value: 25.385 - type: mrr_at_1000 value: 25.465 - type: mrr_at_3 value: 22.056 - type: mrr_at_5 value: 23.630000000000003 - type: ndcg_at_1 value: 17.662 - type: ndcg_at_10 value: 24.391 - type: ndcg_at_100 value: 29.681 - type: ndcg_at_1000 value: 32.923 - type: ndcg_at_3 value: 20.271 - type: ndcg_at_5 value: 22.621 - type: precision_at_1 value: 17.662 - type: precision_at_10 value: 4.44 - type: precision_at_100 value: 0.8200000000000001 - type: precision_at_1000 value: 0.125 - type: precision_at_3 value: 9.577 - type: precision_at_5 value: 7.313 - type: recall_at_1 value: 13.594999999999999 - type: recall_at_10 value: 33.976 - type: recall_at_100 value: 57.43000000000001 - type: recall_at_1000 value: 80.958 - type: recall_at_3 value: 22.897000000000002 - type: recall_at_5 value: 28.714000000000002 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.683 - type: map_at_10 value: 35.068 - type: map_at_100 value: 36.311 - type: map_at_1000 value: 36.436 - type: map_at_3 value: 32.371 - type: map_at_5 value: 33.761 - type: mrr_at_1 value: 32.435 - type: mrr_at_10 value: 40.721000000000004 - type: mrr_at_100 value: 41.535 - type: mrr_at_1000 value: 41.593 - type: mrr_at_3 value: 38.401999999999994 - type: mrr_at_5 value: 39.567 - type: ndcg_at_1 value: 32.435 - type: ndcg_at_10 value: 40.538000000000004 - type: ndcg_at_100 value: 45.963 - type: ndcg_at_1000 value: 48.400999999999996 - type: ndcg_at_3 value: 36.048 - type: ndcg_at_5 value: 37.899 - type: precision_at_1 value: 32.435 - type: precision_at_10 value: 7.1129999999999995 - type: precision_at_100 value: 1.162 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 16.683 - type: precision_at_5 value: 11.684 - type: recall_at_1 value: 26.683 - type: recall_at_10 value: 51.517 - type: recall_at_100 value: 74.553 - type: recall_at_1000 value: 90.649 - type: recall_at_3 value: 38.495000000000005 - type: recall_at_5 value: 43.495 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.186 - type: map_at_10 value: 31.972 - type: map_at_100 value: 33.117000000000004 - type: map_at_1000 value: 33.243 - type: map_at_3 value: 29.423 - type: map_at_5 value: 30.847 - type: mrr_at_1 value: 29.794999999999998 - type: mrr_at_10 value: 36.767 - type: mrr_at_100 value: 37.645 - type: mrr_at_1000 value: 37.716 - type: mrr_at_3 value: 34.513 - type: mrr_at_5 value: 35.791000000000004 - type: ndcg_at_1 value: 29.794999999999998 - type: ndcg_at_10 value: 36.786 - type: ndcg_at_100 value: 41.94 - type: ndcg_at_1000 value: 44.830999999999996 - type: ndcg_at_3 value: 32.504 - type: ndcg_at_5 value: 34.404 - type: precision_at_1 value: 29.794999999999998 - type: precision_at_10 value: 6.518 - type: precision_at_100 value: 1.0659999999999998 - type: precision_at_1000 value: 0.149 - type: precision_at_3 value: 15.296999999999999 - type: precision_at_5 value: 10.731 - type: recall_at_1 value: 24.186 - type: recall_at_10 value: 46.617 - type: recall_at_100 value: 68.75 - type: recall_at_1000 value: 88.864 - type: recall_at_3 value: 34.199 - type: recall_at_5 value: 39.462 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.22083333333333 - type: map_at_10 value: 31.606666666666662 - type: map_at_100 value: 32.6195 - type: map_at_1000 value: 32.739999999999995 - type: map_at_3 value: 29.37825 - type: map_at_5 value: 30.596083333333336 - type: mrr_at_1 value: 28.607916666666668 - type: mrr_at_10 value: 35.54591666666666 - type: mrr_at_100 value: 36.33683333333333 - type: mrr_at_1000 value: 36.40624999999999 - type: mrr_at_3 value: 33.526250000000005 - type: mrr_at_5 value: 34.6605 - type: ndcg_at_1 value: 28.607916666666668 - type: ndcg_at_10 value: 36.07966666666667 - type: ndcg_at_100 value: 40.73308333333333 - type: ndcg_at_1000 value: 43.40666666666666 - type: ndcg_at_3 value: 32.23525 - type: ndcg_at_5 value: 33.97083333333333 - type: precision_at_1 value: 28.607916666666668 - type: precision_at_10 value: 6.120333333333335 - type: precision_at_100 value: 0.9921666666666668 - type: precision_at_1000 value: 0.14091666666666666 - type: precision_at_3 value: 14.54975 - type: precision_at_5 value: 10.153166666666667 - type: recall_at_1 value: 24.22083333333333 - type: recall_at_10 value: 45.49183333333334 - type: recall_at_100 value: 66.28133333333332 - type: recall_at_1000 value: 85.16541666666667 - type: recall_at_3 value: 34.6485 - type: recall_at_5 value: 39.229749999999996 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.842 - type: map_at_10 value: 27.573999999999998 - type: map_at_100 value: 28.410999999999998 - type: map_at_1000 value: 28.502 - type: map_at_3 value: 25.921 - type: map_at_5 value: 26.888 - type: mrr_at_1 value: 24.08 - type: mrr_at_10 value: 29.915999999999997 - type: mrr_at_100 value: 30.669 - type: mrr_at_1000 value: 30.746000000000002 - type: mrr_at_3 value: 28.349000000000004 - type: mrr_at_5 value: 29.246 - type: ndcg_at_1 value: 24.08 - type: ndcg_at_10 value: 30.898999999999997 - type: ndcg_at_100 value: 35.272999999999996 - type: ndcg_at_1000 value: 37.679 - type: ndcg_at_3 value: 27.881 - type: ndcg_at_5 value: 29.432000000000002 - type: precision_at_1 value: 24.08 - type: precision_at_10 value: 4.678 - type: precision_at_100 value: 0.744 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 11.860999999999999 - type: precision_at_5 value: 8.16 - type: recall_at_1 value: 21.842 - type: recall_at_10 value: 38.66 - type: recall_at_100 value: 59.169000000000004 - type: recall_at_1000 value: 76.887 - type: recall_at_3 value: 30.532999999999998 - type: recall_at_5 value: 34.354 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.145 - type: map_at_10 value: 22.729 - type: map_at_100 value: 23.574 - type: map_at_1000 value: 23.695 - type: map_at_3 value: 21.044 - type: map_at_5 value: 21.981 - type: mrr_at_1 value: 20.888 - type: mrr_at_10 value: 26.529000000000003 - type: mrr_at_100 value: 27.308 - type: mrr_at_1000 value: 27.389000000000003 - type: mrr_at_3 value: 24.868000000000002 - type: mrr_at_5 value: 25.825 - type: ndcg_at_1 value: 20.888 - type: ndcg_at_10 value: 26.457000000000004 - type: ndcg_at_100 value: 30.764000000000003 - type: ndcg_at_1000 value: 33.825 - type: ndcg_at_3 value: 23.483999999999998 - type: ndcg_at_5 value: 24.836 - type: precision_at_1 value: 20.888 - type: precision_at_10 value: 4.58 - type: precision_at_100 value: 0.784 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 10.874 - type: precision_at_5 value: 7.639 - type: recall_at_1 value: 17.145 - type: recall_at_10 value: 33.938 - type: recall_at_100 value: 53.672 - type: recall_at_1000 value: 76.023 - type: recall_at_3 value: 25.363000000000003 - type: recall_at_5 value: 29.023 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.275 - type: map_at_10 value: 30.438 - type: map_at_100 value: 31.489 - type: map_at_1000 value: 31.601000000000003 - type: map_at_3 value: 28.647 - type: map_at_5 value: 29.660999999999998 - type: mrr_at_1 value: 28.077999999999996 - type: mrr_at_10 value: 34.098 - type: mrr_at_100 value: 35.025 - type: mrr_at_1000 value: 35.109 - type: mrr_at_3 value: 32.4 - type: mrr_at_5 value: 33.379999999999995 - type: ndcg_at_1 value: 28.077999999999996 - type: ndcg_at_10 value: 34.271 - type: ndcg_at_100 value: 39.352 - type: ndcg_at_1000 value: 42.199 - type: ndcg_at_3 value: 30.978 - type: ndcg_at_5 value: 32.498 - type: precision_at_1 value: 28.077999999999996 - type: precision_at_10 value: 5.345 - type: precision_at_100 value: 0.897 - type: precision_at_1000 value: 0.125 - type: precision_at_3 value: 13.526 - type: precision_at_5 value: 9.16 - type: recall_at_1 value: 24.275 - type: recall_at_10 value: 42.362 - type: recall_at_100 value: 64.461 - type: recall_at_1000 value: 84.981 - type: recall_at_3 value: 33.249 - type: recall_at_5 value: 37.214999999999996 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.358 - type: map_at_10 value: 30.062 - type: map_at_100 value: 31.189 - type: map_at_1000 value: 31.386999999999997 - type: map_at_3 value: 27.672 - type: map_at_5 value: 28.76 - type: mrr_at_1 value: 26.877000000000002 - type: mrr_at_10 value: 33.948 - type: mrr_at_100 value: 34.746 - type: mrr_at_1000 value: 34.816 - type: mrr_at_3 value: 31.884 - type: mrr_at_5 value: 33.001000000000005 - type: ndcg_at_1 value: 26.877000000000002 - type: ndcg_at_10 value: 34.977000000000004 - type: ndcg_at_100 value: 39.753 - type: ndcg_at_1000 value: 42.866 - type: ndcg_at_3 value: 30.956 - type: ndcg_at_5 value: 32.381 - type: precision_at_1 value: 26.877000000000002 - type: precision_at_10 value: 6.7 - type: precision_at_100 value: 1.287 - type: precision_at_1000 value: 0.215 - type: precision_at_3 value: 14.360999999999999 - type: precision_at_5 value: 10.119 - type: recall_at_1 value: 22.358 - type: recall_at_10 value: 44.183 - type: recall_at_100 value: 67.14 - type: recall_at_1000 value: 87.53999999999999 - type: recall_at_3 value: 32.79 - type: recall_at_5 value: 36.829 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 19.198999999999998 - type: map_at_10 value: 25.229000000000003 - type: map_at_100 value: 26.003 - type: map_at_1000 value: 26.111 - type: map_at_3 value: 23.442 - type: map_at_5 value: 24.343 - type: mrr_at_1 value: 21.072 - type: mrr_at_10 value: 27.02 - type: mrr_at_100 value: 27.735 - type: mrr_at_1000 value: 27.815 - type: mrr_at_3 value: 25.416 - type: mrr_at_5 value: 26.173999999999996 - type: ndcg_at_1 value: 21.072 - type: ndcg_at_10 value: 28.862 - type: ndcg_at_100 value: 33.043 - type: ndcg_at_1000 value: 36.003 - type: ndcg_at_3 value: 25.35 - type: ndcg_at_5 value: 26.773000000000003 - type: precision_at_1 value: 21.072 - type: precision_at_10 value: 4.436 - type: precision_at_100 value: 0.713 - type: precision_at_1000 value: 0.106 - type: precision_at_3 value: 10.659 - type: precision_at_5 value: 7.32 - type: recall_at_1 value: 19.198999999999998 - type: recall_at_10 value: 38.376 - type: recall_at_100 value: 58.36900000000001 - type: recall_at_1000 value: 80.92099999999999 - type: recall_at_3 value: 28.715000000000003 - type: recall_at_5 value: 32.147 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 5.9319999999999995 - type: map_at_10 value: 10.483 - type: map_at_100 value: 11.97 - type: map_at_1000 value: 12.171999999999999 - type: map_at_3 value: 8.477 - type: map_at_5 value: 9.495000000000001 - type: mrr_at_1 value: 13.094 - type: mrr_at_10 value: 21.282 - type: mrr_at_100 value: 22.556 - type: mrr_at_1000 value: 22.628999999999998 - type: mrr_at_3 value: 18.218999999999998 - type: mrr_at_5 value: 19.900000000000002 - type: ndcg_at_1 value: 13.094 - type: ndcg_at_10 value: 15.811 - type: ndcg_at_100 value: 23.035 - type: ndcg_at_1000 value: 27.089999999999996 - type: ndcg_at_3 value: 11.905000000000001 - type: ndcg_at_5 value: 13.377 - type: precision_at_1 value: 13.094 - type: precision_at_10 value: 5.225 - type: precision_at_100 value: 1.2970000000000002 - type: precision_at_1000 value: 0.203 - type: precision_at_3 value: 8.86 - type: precision_at_5 value: 7.309 - type: recall_at_1 value: 5.9319999999999995 - type: recall_at_10 value: 20.305 - type: recall_at_100 value: 46.314 - type: recall_at_1000 value: 69.612 - type: recall_at_3 value: 11.21 - type: recall_at_5 value: 14.773 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 8.674 - type: map_at_10 value: 17.822 - type: map_at_100 value: 24.794 - type: map_at_1000 value: 26.214 - type: map_at_3 value: 12.690999999999999 - type: map_at_5 value: 15.033 - type: mrr_at_1 value: 61.75000000000001 - type: mrr_at_10 value: 71.58 - type: mrr_at_100 value: 71.923 - type: mrr_at_1000 value: 71.932 - type: mrr_at_3 value: 70.125 - type: mrr_at_5 value: 71.038 - type: ndcg_at_1 value: 51.0 - type: ndcg_at_10 value: 38.637 - type: ndcg_at_100 value: 42.398 - type: ndcg_at_1000 value: 48.962 - type: ndcg_at_3 value: 43.29 - type: ndcg_at_5 value: 40.763 - type: precision_at_1 value: 61.75000000000001 - type: precision_at_10 value: 30.125 - type: precision_at_100 value: 9.53 - type: precision_at_1000 value: 1.9619999999999997 - type: precision_at_3 value: 45.583 - type: precision_at_5 value: 38.95 - type: recall_at_1 value: 8.674 - type: recall_at_10 value: 23.122 - type: recall_at_100 value: 47.46 - type: recall_at_1000 value: 67.662 - type: recall_at_3 value: 13.946 - type: recall_at_5 value: 17.768 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 46.86000000000001 - type: f1 value: 41.343580452760776 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 36.609 - type: map_at_10 value: 47.552 - type: map_at_100 value: 48.283 - type: map_at_1000 value: 48.321 - type: map_at_3 value: 44.869 - type: map_at_5 value: 46.509 - type: mrr_at_1 value: 39.214 - type: mrr_at_10 value: 50.434999999999995 - type: mrr_at_100 value: 51.122 - type: mrr_at_1000 value: 51.151 - type: mrr_at_3 value: 47.735 - type: mrr_at_5 value: 49.394 - type: ndcg_at_1 value: 39.214 - type: ndcg_at_10 value: 53.52400000000001 - type: ndcg_at_100 value: 56.997 - type: ndcg_at_1000 value: 57.975 - type: ndcg_at_3 value: 48.173 - type: ndcg_at_5 value: 51.05800000000001 - type: precision_at_1 value: 39.214 - type: precision_at_10 value: 7.573 - type: precision_at_100 value: 0.9440000000000001 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 19.782 - type: precision_at_5 value: 13.453000000000001 - type: recall_at_1 value: 36.609 - type: recall_at_10 value: 69.247 - type: recall_at_100 value: 84.99600000000001 - type: recall_at_1000 value: 92.40899999999999 - type: recall_at_3 value: 54.856 - type: recall_at_5 value: 61.797000000000004 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 16.466 - type: map_at_10 value: 27.060000000000002 - type: map_at_100 value: 28.511999999999997 - type: map_at_1000 value: 28.693 - type: map_at_3 value: 22.777 - type: map_at_5 value: 25.086000000000002 - type: mrr_at_1 value: 32.716 - type: mrr_at_10 value: 41.593999999999994 - type: mrr_at_100 value: 42.370000000000005 - type: mrr_at_1000 value: 42.419000000000004 - type: mrr_at_3 value: 38.143 - type: mrr_at_5 value: 40.288000000000004 - type: ndcg_at_1 value: 32.716 - type: ndcg_at_10 value: 34.795 - type: ndcg_at_100 value: 40.58 - type: ndcg_at_1000 value: 43.993 - type: ndcg_at_3 value: 29.573 - type: ndcg_at_5 value: 31.583 - type: precision_at_1 value: 32.716 - type: precision_at_10 value: 9.937999999999999 - type: precision_at_100 value: 1.585 - type: precision_at_1000 value: 0.22 - type: precision_at_3 value: 19.496 - type: precision_at_5 value: 15.247 - type: recall_at_1 value: 16.466 - type: recall_at_10 value: 42.886 - type: recall_at_100 value: 64.724 - type: recall_at_1000 value: 85.347 - type: recall_at_3 value: 26.765 - type: recall_at_5 value: 33.603 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 33.025 - type: map_at_10 value: 47.343 - type: map_at_100 value: 48.207 - type: map_at_1000 value: 48.281 - type: map_at_3 value: 44.519 - type: map_at_5 value: 46.217000000000006 - type: mrr_at_1 value: 66.05 - type: mrr_at_10 value: 72.94699999999999 - type: mrr_at_100 value: 73.289 - type: mrr_at_1000 value: 73.30499999999999 - type: mrr_at_3 value: 71.686 - type: mrr_at_5 value: 72.491 - type: ndcg_at_1 value: 66.05 - type: ndcg_at_10 value: 56.338 - type: ndcg_at_100 value: 59.599999999999994 - type: ndcg_at_1000 value: 61.138000000000005 - type: ndcg_at_3 value: 52.034000000000006 - type: ndcg_at_5 value: 54.352000000000004 - type: precision_at_1 value: 66.05 - type: precision_at_10 value: 11.693000000000001 - type: precision_at_100 value: 1.425 - type: precision_at_1000 value: 0.163 - type: precision_at_3 value: 32.613 - type: precision_at_5 value: 21.401999999999997 - type: recall_at_1 value: 33.025 - type: recall_at_10 value: 58.467 - type: recall_at_100 value: 71.242 - type: recall_at_1000 value: 81.452 - type: recall_at_3 value: 48.92 - type: recall_at_5 value: 53.504 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 75.5492 - type: ap value: 69.42911637216271 - type: f1 value: 75.39113704261024 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 23.173 - type: map_at_10 value: 35.453 - type: map_at_100 value: 36.573 - type: map_at_1000 value: 36.620999999999995 - type: map_at_3 value: 31.655 - type: map_at_5 value: 33.823 - type: mrr_at_1 value: 23.868000000000002 - type: mrr_at_10 value: 36.085 - type: mrr_at_100 value: 37.15 - type: mrr_at_1000 value: 37.193 - type: mrr_at_3 value: 32.376 - type: mrr_at_5 value: 34.501 - type: ndcg_at_1 value: 23.854 - type: ndcg_at_10 value: 42.33 - type: ndcg_at_100 value: 47.705999999999996 - type: ndcg_at_1000 value: 48.91 - type: ndcg_at_3 value: 34.604 - type: ndcg_at_5 value: 38.473 - type: precision_at_1 value: 23.854 - type: precision_at_10 value: 6.639 - type: precision_at_100 value: 0.932 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 14.685 - type: precision_at_5 value: 10.782 - type: recall_at_1 value: 23.173 - type: recall_at_10 value: 63.441 - type: recall_at_100 value: 88.25 - type: recall_at_1000 value: 97.438 - type: recall_at_3 value: 42.434 - type: recall_at_5 value: 51.745 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 92.05426356589147 - type: f1 value: 91.88068588063942 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 73.23985408116735 - type: f1 value: 55.858906745287506 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 72.21923335574984 - type: f1 value: 70.0174116204253 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 75.77673167451245 - type: f1 value: 75.44811354778666 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 31.340414710728737 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 28.196676760061578 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 29.564149683482206 - type: mrr value: 30.28995474250486 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 5.93 - type: map_at_10 value: 12.828000000000001 - type: map_at_100 value: 15.501000000000001 - type: map_at_1000 value: 16.791 - type: map_at_3 value: 9.727 - type: map_at_5 value: 11.318999999999999 - type: mrr_at_1 value: 47.678 - type: mrr_at_10 value: 55.893 - type: mrr_at_100 value: 56.491 - type: mrr_at_1000 value: 56.53 - type: mrr_at_3 value: 54.386 - type: mrr_at_5 value: 55.516 - type: ndcg_at_1 value: 45.975 - type: ndcg_at_10 value: 33.928999999999995 - type: ndcg_at_100 value: 30.164 - type: ndcg_at_1000 value: 38.756 - type: ndcg_at_3 value: 41.077000000000005 - type: ndcg_at_5 value: 38.415 - type: precision_at_1 value: 47.678 - type: precision_at_10 value: 24.365000000000002 - type: precision_at_100 value: 7.344 - type: precision_at_1000 value: 1.994 - type: precision_at_3 value: 38.184000000000005 - type: precision_at_5 value: 33.003 - type: recall_at_1 value: 5.93 - type: recall_at_10 value: 16.239 - type: recall_at_100 value: 28.782999999999998 - type: recall_at_1000 value: 60.11 - type: recall_at_3 value: 10.700999999999999 - type: recall_at_5 value: 13.584 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 36.163000000000004 - type: map_at_10 value: 51.520999999999994 - type: map_at_100 value: 52.449 - type: map_at_1000 value: 52.473000000000006 - type: map_at_3 value: 47.666 - type: map_at_5 value: 50.043000000000006 - type: mrr_at_1 value: 40.266999999999996 - type: mrr_at_10 value: 54.074 - type: mrr_at_100 value: 54.722 - type: mrr_at_1000 value: 54.739000000000004 - type: mrr_at_3 value: 51.043000000000006 - type: mrr_at_5 value: 52.956 - type: ndcg_at_1 value: 40.238 - type: ndcg_at_10 value: 58.73199999999999 - type: ndcg_at_100 value: 62.470000000000006 - type: ndcg_at_1000 value: 63.083999999999996 - type: ndcg_at_3 value: 51.672 - type: ndcg_at_5 value: 55.564 - type: precision_at_1 value: 40.238 - type: precision_at_10 value: 9.279 - type: precision_at_100 value: 1.139 - type: precision_at_1000 value: 0.12 - type: precision_at_3 value: 23.078000000000003 - type: precision_at_5 value: 16.176 - type: recall_at_1 value: 36.163000000000004 - type: recall_at_10 value: 77.88199999999999 - type: recall_at_100 value: 93.83399999999999 - type: recall_at_1000 value: 98.465 - type: recall_at_3 value: 59.857000000000006 - type: recall_at_5 value: 68.73599999999999 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 70.344 - type: map_at_10 value: 83.907 - type: map_at_100 value: 84.536 - type: map_at_1000 value: 84.557 - type: map_at_3 value: 80.984 - type: map_at_5 value: 82.844 - type: mrr_at_1 value: 81.02000000000001 - type: mrr_at_10 value: 87.158 - type: mrr_at_100 value: 87.268 - type: mrr_at_1000 value: 87.26899999999999 - type: mrr_at_3 value: 86.17 - type: mrr_at_5 value: 86.87 - type: ndcg_at_1 value: 81.02000000000001 - type: ndcg_at_10 value: 87.70700000000001 - type: ndcg_at_100 value: 89.004 - type: ndcg_at_1000 value: 89.139 - type: ndcg_at_3 value: 84.841 - type: ndcg_at_5 value: 86.455 - type: precision_at_1 value: 81.02000000000001 - type: precision_at_10 value: 13.248999999999999 - type: precision_at_100 value: 1.516 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 36.963 - type: precision_at_5 value: 24.33 - type: recall_at_1 value: 70.344 - type: recall_at_10 value: 94.75099999999999 - type: recall_at_100 value: 99.30499999999999 - type: recall_at_1000 value: 99.928 - type: recall_at_3 value: 86.506 - type: recall_at_5 value: 91.083 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 42.873718018378305 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 56.39477366450528 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 3.868 - type: map_at_10 value: 9.611 - type: map_at_100 value: 11.087 - type: map_at_1000 value: 11.332 - type: map_at_3 value: 6.813 - type: map_at_5 value: 8.233 - type: mrr_at_1 value: 19.0 - type: mrr_at_10 value: 28.457 - type: mrr_at_100 value: 29.613 - type: mrr_at_1000 value: 29.695 - type: mrr_at_3 value: 25.55 - type: mrr_at_5 value: 27.29 - type: ndcg_at_1 value: 19.0 - type: ndcg_at_10 value: 16.419 - type: ndcg_at_100 value: 22.817999999999998 - type: ndcg_at_1000 value: 27.72 - type: ndcg_at_3 value: 15.379000000000001 - type: ndcg_at_5 value: 13.645 - type: precision_at_1 value: 19.0 - type: precision_at_10 value: 8.540000000000001 - type: precision_at_100 value: 1.7819999999999998 - type: precision_at_1000 value: 0.297 - type: precision_at_3 value: 14.267 - type: precision_at_5 value: 12.04 - type: recall_at_1 value: 3.868 - type: recall_at_10 value: 17.288 - type: recall_at_100 value: 36.144999999999996 - type: recall_at_1000 value: 60.199999999999996 - type: recall_at_3 value: 8.688 - type: recall_at_5 value: 12.198 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 83.96614722598582 - type: cos_sim_spearman value: 78.9003023008781 - type: euclidean_pearson value: 81.01829384436505 - type: euclidean_spearman value: 78.93248416788914 - type: manhattan_pearson value: 81.1665428926402 - type: manhattan_spearman value: 78.93264116287453 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 83.54613363895993 - type: cos_sim_spearman value: 75.1883451602451 - type: euclidean_pearson value: 79.70320886899894 - type: euclidean_spearman value: 74.5917140136796 - type: manhattan_pearson value: 79.82157067185999 - type: manhattan_spearman value: 74.74185720594735 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 81.30430156721782 - type: cos_sim_spearman value: 81.79962989974364 - type: euclidean_pearson value: 80.89058823224924 - type: euclidean_spearman value: 81.35929372984597 - type: manhattan_pearson value: 81.12204370487478 - type: manhattan_spearman value: 81.6248963282232 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 81.13064504403134 - type: cos_sim_spearman value: 78.48371403924872 - type: euclidean_pearson value: 80.16794919665591 - type: euclidean_spearman value: 78.29216082221699 - type: manhattan_pearson value: 80.22308565207301 - type: manhattan_spearman value: 78.37829229948022 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 86.52918899541099 - type: cos_sim_spearman value: 87.49276894673142 - type: euclidean_pearson value: 86.77440570164254 - type: euclidean_spearman value: 87.5753295736756 - type: manhattan_pearson value: 86.86098573892133 - type: manhattan_spearman value: 87.65848591821947 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 82.86805307244882 - type: cos_sim_spearman value: 84.58066253757511 - type: euclidean_pearson value: 84.38377000876991 - type: euclidean_spearman value: 85.1837278784528 - type: manhattan_pearson value: 84.41903291363842 - type: manhattan_spearman value: 85.19023736251052 - 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: 86.77218560282436 - type: cos_sim_spearman value: 87.94243515296604 - type: euclidean_pearson value: 88.22800939214864 - type: euclidean_spearman value: 87.91106839439841 - type: manhattan_pearson value: 88.17063269848741 - type: manhattan_spearman value: 87.72751904126062 - 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: 60.40731554300387 - type: cos_sim_spearman value: 63.76300532966479 - type: euclidean_pearson value: 62.94727878229085 - type: euclidean_spearman value: 63.678039531461216 - type: manhattan_pearson value: 63.00661039863549 - type: manhattan_spearman value: 63.6282591984376 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 84.92731569745344 - type: cos_sim_spearman value: 86.36336704300167 - type: euclidean_pearson value: 86.09122224841195 - type: euclidean_spearman value: 86.2116149319238 - type: manhattan_pearson value: 86.07879456717032 - type: manhattan_spearman value: 86.2022069635119 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 79.75976311752326 - type: mrr value: 94.15782837351466 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 51.193999999999996 - type: map_at_10 value: 61.224999999999994 - type: map_at_100 value: 62.031000000000006 - type: map_at_1000 value: 62.066 - type: map_at_3 value: 59.269000000000005 - type: map_at_5 value: 60.159 - type: mrr_at_1 value: 53.667 - type: mrr_at_10 value: 62.74999999999999 - type: mrr_at_100 value: 63.39399999999999 - type: mrr_at_1000 value: 63.425 - type: mrr_at_3 value: 61.389 - type: mrr_at_5 value: 61.989000000000004 - type: ndcg_at_1 value: 53.667 - type: ndcg_at_10 value: 65.596 - type: ndcg_at_100 value: 68.906 - type: ndcg_at_1000 value: 69.78999999999999 - type: ndcg_at_3 value: 62.261 - type: ndcg_at_5 value: 63.453 - type: precision_at_1 value: 53.667 - type: precision_at_10 value: 8.667 - type: precision_at_100 value: 1.04 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 24.556 - type: precision_at_5 value: 15.6 - type: recall_at_1 value: 51.193999999999996 - type: recall_at_10 value: 77.156 - type: recall_at_100 value: 91.43299999999999 - type: recall_at_1000 value: 98.333 - type: recall_at_3 value: 67.994 - type: recall_at_5 value: 71.14399999999999 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.81485148514851 - type: cos_sim_ap value: 95.28896513388551 - type: cos_sim_f1 value: 90.43478260869566 - type: cos_sim_precision value: 92.56544502617801 - type: cos_sim_recall value: 88.4 - type: dot_accuracy value: 99.30594059405941 - type: dot_ap value: 61.6432597455472 - type: dot_f1 value: 59.46481665014866 - type: dot_precision value: 58.93909626719057 - type: dot_recall value: 60.0 - type: euclidean_accuracy value: 99.81980198019802 - type: euclidean_ap value: 95.21411049527 - type: euclidean_f1 value: 91.06090373280944 - type: euclidean_precision value: 89.47876447876449 - type: euclidean_recall value: 92.7 - type: manhattan_accuracy value: 99.81782178217821 - type: manhattan_ap value: 95.32449994414968 - type: manhattan_f1 value: 90.86395233366436 - type: manhattan_precision value: 90.23668639053254 - type: manhattan_recall value: 91.5 - type: max_accuracy value: 99.81980198019802 - type: max_ap value: 95.32449994414968 - type: max_f1 value: 91.06090373280944 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 59.08045614613064 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 30.297802606804748 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 49.12801740706292 - type: mrr value: 50.05592956879722 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 23.380995453661917 - type: cos_sim_spearman value: 24.941761858688917 - type: dot_pearson value: 24.930577961642413 - type: dot_spearman value: 24.804715835064492 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.243 - type: map_at_10 value: 1.886 - type: map_at_100 value: 10.040000000000001 - type: map_at_1000 value: 23.768 - type: map_at_3 value: 0.674 - type: map_at_5 value: 1.079 - type: mrr_at_1 value: 88.0 - type: mrr_at_10 value: 93.667 - type: mrr_at_100 value: 93.667 - type: mrr_at_1000 value: 93.667 - type: mrr_at_3 value: 93.667 - type: mrr_at_5 value: 93.667 - type: ndcg_at_1 value: 83.0 - type: ndcg_at_10 value: 76.777 - type: ndcg_at_100 value: 55.153 - type: ndcg_at_1000 value: 47.912 - type: ndcg_at_3 value: 81.358 - type: ndcg_at_5 value: 80.74799999999999 - type: precision_at_1 value: 88.0 - type: precision_at_10 value: 80.80000000000001 - type: precision_at_100 value: 56.02 - type: precision_at_1000 value: 21.51 - type: precision_at_3 value: 86.0 - type: precision_at_5 value: 86.0 - type: recall_at_1 value: 0.243 - type: recall_at_10 value: 2.0869999999999997 - type: recall_at_100 value: 13.014000000000001 - type: recall_at_1000 value: 44.433 - type: recall_at_3 value: 0.6910000000000001 - type: recall_at_5 value: 1.1440000000000001 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 3.066 - type: map_at_10 value: 10.615 - type: map_at_100 value: 16.463 - type: map_at_1000 value: 17.815 - type: map_at_3 value: 5.7860000000000005 - type: map_at_5 value: 7.353999999999999 - type: mrr_at_1 value: 38.775999999999996 - type: mrr_at_10 value: 53.846000000000004 - type: mrr_at_100 value: 54.37 - type: mrr_at_1000 value: 54.37 - type: mrr_at_3 value: 48.980000000000004 - type: mrr_at_5 value: 51.735 - type: ndcg_at_1 value: 34.694 - type: ndcg_at_10 value: 26.811 - type: ndcg_at_100 value: 37.342999999999996 - type: ndcg_at_1000 value: 47.964 - type: ndcg_at_3 value: 30.906 - type: ndcg_at_5 value: 27.77 - type: precision_at_1 value: 38.775999999999996 - type: precision_at_10 value: 23.878 - type: precision_at_100 value: 7.632999999999999 - type: precision_at_1000 value: 1.469 - type: precision_at_3 value: 31.973000000000003 - type: precision_at_5 value: 26.939 - type: recall_at_1 value: 3.066 - type: recall_at_10 value: 17.112 - type: recall_at_100 value: 47.723 - type: recall_at_1000 value: 79.50500000000001 - type: recall_at_3 value: 6.825 - type: recall_at_5 value: 9.584 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 72.76460000000002 - type: ap value: 14.944240012137053 - type: f1 value: 55.89805777266571 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 63.30503678551217 - type: f1 value: 63.57492701921179 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 37.51066495006874 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 86.07021517553794 - type: cos_sim_ap value: 74.15520712370555 - type: cos_sim_f1 value: 68.64321608040201 - type: cos_sim_precision value: 65.51558752997602 - type: cos_sim_recall value: 72.0844327176781 - type: dot_accuracy value: 80.23484532395541 - type: dot_ap value: 54.298763810214176 - type: dot_f1 value: 53.22254659779924 - type: dot_precision value: 46.32525410476936 - type: dot_recall value: 62.532981530343015 - type: euclidean_accuracy value: 86.04637301066937 - type: euclidean_ap value: 73.85333854233123 - type: euclidean_f1 value: 68.77723660599845 - type: euclidean_precision value: 66.87437686939182 - type: euclidean_recall value: 70.79155672823218 - type: manhattan_accuracy value: 85.98676759849795 - type: manhattan_ap value: 73.56016090035973 - type: manhattan_f1 value: 68.48878539036647 - type: manhattan_precision value: 63.9505607690547 - type: manhattan_recall value: 73.7203166226913 - type: max_accuracy value: 86.07021517553794 - type: max_ap value: 74.15520712370555 - type: max_f1 value: 68.77723660599845 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.92769821865176 - type: cos_sim_ap value: 85.78879502899773 - type: cos_sim_f1 value: 78.14414083990464 - type: cos_sim_precision value: 74.61651607480563 - type: cos_sim_recall value: 82.0218663381583 - type: dot_accuracy value: 84.95750378390964 - type: dot_ap value: 75.80219641857563 - type: dot_f1 value: 70.13966179585681 - type: dot_precision value: 65.71140262361251 - type: dot_recall value: 75.20788420080073 - type: euclidean_accuracy value: 88.93546008460433 - type: euclidean_ap value: 85.72056428301667 - type: euclidean_f1 value: 78.14387902598124 - type: euclidean_precision value: 75.3376688344172 - type: euclidean_recall value: 81.16723129042192 - type: manhattan_accuracy value: 88.96262661543835 - type: manhattan_ap value: 85.76605136314335 - type: manhattan_f1 value: 78.26696165191743 - type: manhattan_precision value: 75.0990659496179 - type: manhattan_recall value: 81.71388974437943 - type: max_accuracy value: 88.96262661543835 - type: max_ap value: 85.78879502899773 - type: max_f1 value: 78.26696165191743 ---