--- tags: - mteb model-index: - name: multi-qa-MiniLM-L6-cos-v1 results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 61.791044776119406 - type: ap value: 25.829130082463124 - type: f1 value: 56.00432262887535 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 62.36077499999999 - type: ap value: 57.68938427410222 - type: f1 value: 62.247666843818436 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 29.59 - type: f1 value: 29.241975951560622 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 25.249 - type: map_at_10 value: 40.196 - type: map_at_100 value: 41.336 - type: map_at_1000 value: 41.343 - type: map_at_3 value: 34.934 - type: map_at_5 value: 37.871 - type: mrr_at_1 value: 26.031 - type: mrr_at_10 value: 40.488 - type: mrr_at_100 value: 41.628 - type: mrr_at_1000 value: 41.634 - type: mrr_at_3 value: 35.171 - type: mrr_at_5 value: 38.126 - type: ndcg_at_1 value: 25.249 - type: ndcg_at_10 value: 49.11 - type: ndcg_at_100 value: 53.827999999999996 - type: ndcg_at_1000 value: 53.993 - type: ndcg_at_3 value: 38.175 - type: ndcg_at_5 value: 43.488 - type: precision_at_1 value: 25.249 - type: precision_at_10 value: 7.788 - type: precision_at_100 value: 0.9820000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 15.861 - type: precision_at_5 value: 12.105 - type: recall_at_1 value: 25.249 - type: recall_at_10 value: 77.881 - type: recall_at_100 value: 98.222 - type: recall_at_1000 value: 99.502 - type: recall_at_3 value: 47.582 - type: recall_at_5 value: 60.526 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 37.75242616816114 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 27.70031808300247 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 63.09199068762668 - type: mrr value: 76.08055225783757 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 80.83007234777145 - type: cos_sim_spearman value: 79.76446808992547 - type: euclidean_pearson value: 80.24418669808917 - type: euclidean_spearman value: 79.76446808992547 - type: manhattan_pearson value: 79.58896133042379 - type: manhattan_spearman value: 78.9614377441415 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 78.6038961038961 - type: f1 value: 77.95572823168757 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 30.240388191413935 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 22.670413424756212 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 32.694 - type: map_at_10 value: 43.811 - type: map_at_100 value: 45.274 - type: map_at_1000 value: 45.393 - type: map_at_3 value: 40.043 - type: map_at_5 value: 41.983 - type: mrr_at_1 value: 39.628 - type: mrr_at_10 value: 49.748 - type: mrr_at_100 value: 50.356 - type: mrr_at_1000 value: 50.39900000000001 - type: mrr_at_3 value: 46.924 - type: mrr_at_5 value: 48.598 - type: ndcg_at_1 value: 39.628 - type: ndcg_at_10 value: 50.39 - type: ndcg_at_100 value: 55.489 - type: ndcg_at_1000 value: 57.291000000000004 - type: ndcg_at_3 value: 44.849 - type: ndcg_at_5 value: 47.195 - type: precision_at_1 value: 39.628 - type: precision_at_10 value: 9.714 - type: precision_at_100 value: 1.591 - type: precision_at_1000 value: 0.2 - type: precision_at_3 value: 21.507 - type: precision_at_5 value: 15.393 - type: recall_at_1 value: 32.694 - type: recall_at_10 value: 63.031000000000006 - type: recall_at_100 value: 84.49 - type: recall_at_1000 value: 96.148 - type: recall_at_3 value: 46.851 - type: recall_at_5 value: 53.64 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 28.183000000000003 - type: map_at_10 value: 38.796 - type: map_at_100 value: 40.117000000000004 - type: map_at_1000 value: 40.251 - type: map_at_3 value: 35.713 - type: map_at_5 value: 37.446 - type: mrr_at_1 value: 35.605 - type: mrr_at_10 value: 44.824000000000005 - type: mrr_at_100 value: 45.544000000000004 - type: mrr_at_1000 value: 45.59 - type: mrr_at_3 value: 42.452 - type: mrr_at_5 value: 43.891999999999996 - type: ndcg_at_1 value: 35.605 - type: ndcg_at_10 value: 44.857 - type: ndcg_at_100 value: 49.68 - type: ndcg_at_1000 value: 51.841 - type: ndcg_at_3 value: 40.445 - type: ndcg_at_5 value: 42.535000000000004 - type: precision_at_1 value: 35.605 - type: precision_at_10 value: 8.624 - type: precision_at_100 value: 1.438 - type: precision_at_1000 value: 0.193 - type: precision_at_3 value: 19.808999999999997 - type: precision_at_5 value: 14.191 - type: recall_at_1 value: 28.183000000000003 - type: recall_at_10 value: 55.742000000000004 - type: recall_at_100 value: 76.416 - type: recall_at_1000 value: 90.20899999999999 - type: recall_at_3 value: 42.488 - type: recall_at_5 value: 48.431999999999995 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 36.156 - type: map_at_10 value: 47.677 - type: map_at_100 value: 48.699999999999996 - type: map_at_1000 value: 48.756 - type: map_at_3 value: 44.467 - type: map_at_5 value: 46.132 - type: mrr_at_1 value: 41.567 - type: mrr_at_10 value: 51.06699999999999 - type: mrr_at_100 value: 51.800000000000004 - type: mrr_at_1000 value: 51.827999999999996 - type: mrr_at_3 value: 48.620999999999995 - type: mrr_at_5 value: 50.013 - type: ndcg_at_1 value: 41.567 - type: ndcg_at_10 value: 53.418 - type: ndcg_at_100 value: 57.743 - type: ndcg_at_1000 value: 58.940000000000005 - type: ndcg_at_3 value: 47.923 - type: ndcg_at_5 value: 50.352 - type: precision_at_1 value: 41.567 - type: precision_at_10 value: 8.74 - type: precision_at_100 value: 1.1809999999999998 - type: precision_at_1000 value: 0.133 - type: precision_at_3 value: 21.337999999999997 - type: precision_at_5 value: 14.646 - type: recall_at_1 value: 36.156 - type: recall_at_10 value: 67.084 - type: recall_at_100 value: 86.299 - type: recall_at_1000 value: 94.82000000000001 - type: recall_at_3 value: 52.209 - type: recall_at_5 value: 58.175 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 23.513 - type: map_at_10 value: 32.699 - type: map_at_100 value: 33.788000000000004 - type: map_at_1000 value: 33.878 - type: map_at_3 value: 30.044999999999998 - type: map_at_5 value: 31.506 - type: mrr_at_1 value: 25.311 - type: mrr_at_10 value: 34.457 - type: mrr_at_100 value: 35.443999999999996 - type: mrr_at_1000 value: 35.504999999999995 - type: mrr_at_3 value: 31.902 - type: mrr_at_5 value: 33.36 - type: ndcg_at_1 value: 25.311 - type: ndcg_at_10 value: 37.929 - type: ndcg_at_100 value: 43.1 - type: ndcg_at_1000 value: 45.275999999999996 - type: ndcg_at_3 value: 32.745999999999995 - type: ndcg_at_5 value: 35.235 - type: precision_at_1 value: 25.311 - type: precision_at_10 value: 6.034 - type: precision_at_100 value: 0.8959999999999999 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 14.237 - type: precision_at_5 value: 10.034 - type: recall_at_1 value: 23.513 - type: recall_at_10 value: 52.312999999999995 - type: recall_at_100 value: 75.762 - type: recall_at_1000 value: 91.85799999999999 - type: recall_at_3 value: 38.222 - type: recall_at_5 value: 44.316 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 16.333000000000002 - type: map_at_10 value: 24.605 - type: map_at_100 value: 25.924000000000003 - type: map_at_1000 value: 26.039 - type: map_at_3 value: 21.907 - type: map_at_5 value: 23.294999999999998 - type: mrr_at_1 value: 20.647 - type: mrr_at_10 value: 29.442 - type: mrr_at_100 value: 30.54 - type: mrr_at_1000 value: 30.601 - type: mrr_at_3 value: 26.802999999999997 - type: mrr_at_5 value: 28.147 - type: ndcg_at_1 value: 20.647 - type: ndcg_at_10 value: 30.171999999999997 - type: ndcg_at_100 value: 36.466 - type: ndcg_at_1000 value: 39.095 - type: ndcg_at_3 value: 25.134 - type: ndcg_at_5 value: 27.211999999999996 - type: precision_at_1 value: 20.647 - type: precision_at_10 value: 5.659 - type: precision_at_100 value: 1.012 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 12.148 - type: precision_at_5 value: 8.881 - type: recall_at_1 value: 16.333000000000002 - type: recall_at_10 value: 42.785000000000004 - type: recall_at_100 value: 70.282 - type: recall_at_1000 value: 88.539 - type: recall_at_3 value: 28.307 - type: recall_at_5 value: 33.751 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.821 - type: map_at_10 value: 37.188 - type: map_at_100 value: 38.516 - type: map_at_1000 value: 38.635000000000005 - type: map_at_3 value: 33.821 - type: map_at_5 value: 35.646 - type: mrr_at_1 value: 33.109 - type: mrr_at_10 value: 43.003 - type: mrr_at_100 value: 43.849 - type: mrr_at_1000 value: 43.889 - type: mrr_at_3 value: 40.263 - type: mrr_at_5 value: 41.957 - type: ndcg_at_1 value: 33.109 - type: ndcg_at_10 value: 43.556 - type: ndcg_at_100 value: 49.197 - type: ndcg_at_1000 value: 51.269 - type: ndcg_at_3 value: 38.01 - type: ndcg_at_5 value: 40.647 - type: precision_at_1 value: 33.109 - type: precision_at_10 value: 8.085 - type: precision_at_100 value: 1.286 - type: precision_at_1000 value: 0.166 - type: precision_at_3 value: 18.191 - type: precision_at_5 value: 13.050999999999998 - type: recall_at_1 value: 26.821 - type: recall_at_10 value: 56.818000000000005 - type: recall_at_100 value: 80.63 - type: recall_at_1000 value: 94.042 - type: recall_at_3 value: 41.266000000000005 - type: recall_at_5 value: 48.087999999999994 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.169 - type: map_at_10 value: 31.682 - type: map_at_100 value: 32.988 - type: map_at_1000 value: 33.097 - type: map_at_3 value: 28.708 - type: map_at_5 value: 30.319000000000003 - type: mrr_at_1 value: 27.854 - type: mrr_at_10 value: 36.814 - type: mrr_at_100 value: 37.741 - type: mrr_at_1000 value: 37.798 - type: mrr_at_3 value: 34.418 - type: mrr_at_5 value: 35.742000000000004 - type: ndcg_at_1 value: 27.854 - type: ndcg_at_10 value: 37.388 - type: ndcg_at_100 value: 43.342999999999996 - type: ndcg_at_1000 value: 45.829 - type: ndcg_at_3 value: 32.512 - type: ndcg_at_5 value: 34.613 - type: precision_at_1 value: 27.854 - type: precision_at_10 value: 7.031999999999999 - type: precision_at_100 value: 1.18 - type: precision_at_1000 value: 0.158 - type: precision_at_3 value: 15.753 - type: precision_at_5 value: 11.301 - type: recall_at_1 value: 22.169 - type: recall_at_10 value: 49.44 - type: recall_at_100 value: 75.644 - type: recall_at_1000 value: 92.919 - type: recall_at_3 value: 35.528999999999996 - type: recall_at_5 value: 41.271 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.20158333333334 - type: map_at_10 value: 33.509 - type: map_at_100 value: 34.76525 - type: map_at_1000 value: 34.885999999999996 - type: map_at_3 value: 30.594333333333335 - type: map_at_5 value: 32.160666666666664 - type: mrr_at_1 value: 28.803833333333333 - type: mrr_at_10 value: 37.61358333333333 - type: mrr_at_100 value: 38.5105 - type: mrr_at_1000 value: 38.56841666666667 - type: mrr_at_3 value: 35.090666666666664 - type: mrr_at_5 value: 36.49575 - type: ndcg_at_1 value: 28.803833333333333 - type: ndcg_at_10 value: 39.038333333333334 - type: ndcg_at_100 value: 44.49175 - type: ndcg_at_1000 value: 46.835499999999996 - type: ndcg_at_3 value: 34.011916666666664 - type: ndcg_at_5 value: 36.267 - type: precision_at_1 value: 28.803833333333333 - type: precision_at_10 value: 6.974583333333334 - type: precision_at_100 value: 1.1565 - type: precision_at_1000 value: 0.15533333333333332 - type: precision_at_3 value: 15.78025 - type: precision_at_5 value: 11.279583333333333 - type: recall_at_1 value: 24.20158333333334 - type: recall_at_10 value: 51.408 - type: recall_at_100 value: 75.36958333333334 - type: recall_at_1000 value: 91.5765 - type: recall_at_3 value: 37.334500000000006 - type: recall_at_5 value: 43.14666666666667 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.394 - type: map_at_10 value: 28.807 - type: map_at_100 value: 29.851 - type: map_at_1000 value: 29.959999999999997 - type: map_at_3 value: 26.694000000000003 - type: map_at_5 value: 27.805999999999997 - type: mrr_at_1 value: 23.773 - type: mrr_at_10 value: 30.895 - type: mrr_at_100 value: 31.894 - type: mrr_at_1000 value: 31.971 - type: mrr_at_3 value: 28.988000000000003 - type: mrr_at_5 value: 29.908 - type: ndcg_at_1 value: 23.773 - type: ndcg_at_10 value: 32.976 - type: ndcg_at_100 value: 38.109 - type: ndcg_at_1000 value: 40.797 - type: ndcg_at_3 value: 28.993999999999996 - type: ndcg_at_5 value: 30.659999999999997 - type: precision_at_1 value: 23.773 - type: precision_at_10 value: 5.2299999999999995 - type: precision_at_100 value: 0.857 - type: precision_at_1000 value: 0.117 - type: precision_at_3 value: 12.73 - type: precision_at_5 value: 8.741999999999999 - type: recall_at_1 value: 21.394 - type: recall_at_10 value: 43.75 - type: recall_at_100 value: 66.765 - type: recall_at_1000 value: 86.483 - type: recall_at_3 value: 32.542 - type: recall_at_5 value: 36.689 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 16.266 - type: map_at_10 value: 23.639 - type: map_at_100 value: 24.814 - type: map_at_1000 value: 24.948 - type: map_at_3 value: 21.401999999999997 - type: map_at_5 value: 22.581 - type: mrr_at_1 value: 19.718 - type: mrr_at_10 value: 27.276 - type: mrr_at_100 value: 28.252 - type: mrr_at_1000 value: 28.33 - type: mrr_at_3 value: 25.086000000000002 - type: mrr_at_5 value: 26.304 - type: ndcg_at_1 value: 19.718 - type: ndcg_at_10 value: 28.254 - type: ndcg_at_100 value: 34.022999999999996 - type: ndcg_at_1000 value: 37.031 - type: ndcg_at_3 value: 24.206 - type: ndcg_at_5 value: 26.009 - type: precision_at_1 value: 19.718 - type: precision_at_10 value: 5.189 - type: precision_at_100 value: 0.9690000000000001 - type: precision_at_1000 value: 0.14200000000000002 - type: precision_at_3 value: 11.551 - type: precision_at_5 value: 8.362 - type: recall_at_1 value: 16.266 - type: recall_at_10 value: 38.550000000000004 - type: recall_at_100 value: 64.63499999999999 - type: recall_at_1000 value: 86.059 - type: recall_at_3 value: 27.156000000000002 - type: recall_at_5 value: 31.829 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.124000000000002 - type: map_at_10 value: 35.099000000000004 - type: map_at_100 value: 36.269 - type: map_at_1000 value: 36.388999999999996 - type: map_at_3 value: 32.017 - type: map_at_5 value: 33.614 - type: mrr_at_1 value: 31.25 - type: mrr_at_10 value: 39.269999999999996 - type: mrr_at_100 value: 40.134 - type: mrr_at_1000 value: 40.197 - type: mrr_at_3 value: 36.536 - type: mrr_at_5 value: 37.842 - type: ndcg_at_1 value: 31.25 - type: ndcg_at_10 value: 40.643 - type: ndcg_at_100 value: 45.967999999999996 - type: ndcg_at_1000 value: 48.455999999999996 - type: ndcg_at_3 value: 34.954 - type: ndcg_at_5 value: 37.273 - type: precision_at_1 value: 31.25 - type: precision_at_10 value: 6.894 - type: precision_at_100 value: 1.086 - type: precision_at_1000 value: 0.14200000000000002 - type: precision_at_3 value: 15.672 - type: precision_at_5 value: 11.082 - type: recall_at_1 value: 26.124000000000002 - type: recall_at_10 value: 53.730999999999995 - type: recall_at_100 value: 76.779 - type: recall_at_1000 value: 93.908 - type: recall_at_3 value: 37.869 - type: recall_at_5 value: 43.822 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.776 - type: map_at_10 value: 31.384 - type: map_at_100 value: 33.108 - type: map_at_1000 value: 33.339 - type: map_at_3 value: 28.269 - type: map_at_5 value: 30.108 - type: mrr_at_1 value: 26.482 - type: mrr_at_10 value: 35.876000000000005 - type: mrr_at_100 value: 36.887 - type: mrr_at_1000 value: 36.949 - type: mrr_at_3 value: 32.971000000000004 - type: mrr_at_5 value: 34.601 - type: ndcg_at_1 value: 26.482 - type: ndcg_at_10 value: 37.403999999999996 - type: ndcg_at_100 value: 43.722 - type: ndcg_at_1000 value: 46.417 - type: ndcg_at_3 value: 32.149 - type: ndcg_at_5 value: 34.818 - type: precision_at_1 value: 26.482 - type: precision_at_10 value: 7.411 - type: precision_at_100 value: 1.532 - type: precision_at_1000 value: 0.24 - type: precision_at_3 value: 15.152 - type: precision_at_5 value: 11.501999999999999 - type: recall_at_1 value: 21.776 - type: recall_at_10 value: 49.333 - type: recall_at_100 value: 76.753 - type: recall_at_1000 value: 93.762 - type: recall_at_3 value: 35.329 - type: recall_at_5 value: 41.82 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.990000000000002 - type: map_at_10 value: 26.721 - type: map_at_100 value: 27.833999999999996 - type: map_at_1000 value: 27.947 - type: map_at_3 value: 24.046 - type: map_at_5 value: 25.491999999999997 - type: mrr_at_1 value: 20.702 - type: mrr_at_10 value: 28.691 - type: mrr_at_100 value: 29.685 - type: mrr_at_1000 value: 29.764000000000003 - type: mrr_at_3 value: 26.124000000000002 - type: mrr_at_5 value: 27.584999999999997 - type: ndcg_at_1 value: 20.702 - type: ndcg_at_10 value: 31.473000000000003 - type: ndcg_at_100 value: 37.061 - type: ndcg_at_1000 value: 39.784000000000006 - type: ndcg_at_3 value: 26.221 - type: ndcg_at_5 value: 28.655 - type: precision_at_1 value: 20.702 - type: precision_at_10 value: 5.083 - type: precision_at_100 value: 0.8500000000000001 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 11.275 - type: precision_at_5 value: 8.17 - type: recall_at_1 value: 18.990000000000002 - type: recall_at_10 value: 44.318999999999996 - type: recall_at_100 value: 69.98 - type: recall_at_1000 value: 90.171 - type: recall_at_3 value: 30.246000000000002 - type: recall_at_5 value: 35.927 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 9.584 - type: map_at_10 value: 16.148 - type: map_at_100 value: 17.727 - type: map_at_1000 value: 17.913999999999998 - type: map_at_3 value: 13.456000000000001 - type: map_at_5 value: 14.841999999999999 - type: mrr_at_1 value: 21.564 - type: mrr_at_10 value: 31.579 - type: mrr_at_100 value: 32.586999999999996 - type: mrr_at_1000 value: 32.638 - type: mrr_at_3 value: 28.294999999999998 - type: mrr_at_5 value: 30.064 - type: ndcg_at_1 value: 21.564 - type: ndcg_at_10 value: 23.294999999999998 - type: ndcg_at_100 value: 29.997 - type: ndcg_at_1000 value: 33.517 - type: ndcg_at_3 value: 18.759 - type: ndcg_at_5 value: 20.324 - type: precision_at_1 value: 21.564 - type: precision_at_10 value: 7.362 - type: precision_at_100 value: 1.451 - type: precision_at_1000 value: 0.21 - type: precision_at_3 value: 13.919999999999998 - type: precision_at_5 value: 10.879 - type: recall_at_1 value: 9.584 - type: recall_at_10 value: 28.508 - type: recall_at_100 value: 51.873999999999995 - type: recall_at_1000 value: 71.773 - type: recall_at_3 value: 17.329 - type: recall_at_5 value: 21.823 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 7.034 - type: map_at_10 value: 14.664 - type: map_at_100 value: 19.652 - type: map_at_1000 value: 20.701 - type: map_at_3 value: 10.626 - type: map_at_5 value: 12.334 - type: mrr_at_1 value: 54.0 - type: mrr_at_10 value: 63.132 - type: mrr_at_100 value: 63.639 - type: mrr_at_1000 value: 63.663000000000004 - type: mrr_at_3 value: 61.083 - type: mrr_at_5 value: 62.483 - type: ndcg_at_1 value: 42.875 - type: ndcg_at_10 value: 32.04 - type: ndcg_at_100 value: 35.157 - type: ndcg_at_1000 value: 41.4 - type: ndcg_at_3 value: 35.652 - type: ndcg_at_5 value: 33.617000000000004 - type: precision_at_1 value: 54.0 - type: precision_at_10 value: 25.55 - type: precision_at_100 value: 7.5600000000000005 - type: precision_at_1000 value: 1.577 - type: precision_at_3 value: 38.833 - type: precision_at_5 value: 33.15 - type: recall_at_1 value: 7.034 - type: recall_at_10 value: 19.627 - type: recall_at_100 value: 40.528 - type: recall_at_1000 value: 60.789 - type: recall_at_3 value: 11.833 - type: recall_at_5 value: 14.804 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 39.6 - type: f1 value: 35.3770765501984 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 35.098 - type: map_at_10 value: 46.437 - type: map_at_100 value: 47.156 - type: map_at_1000 value: 47.193000000000005 - type: map_at_3 value: 43.702000000000005 - type: map_at_5 value: 45.326 - type: mrr_at_1 value: 37.774 - type: mrr_at_10 value: 49.512 - type: mrr_at_100 value: 50.196 - type: mrr_at_1000 value: 50.224000000000004 - type: mrr_at_3 value: 46.747 - type: mrr_at_5 value: 48.415 - type: ndcg_at_1 value: 37.774 - type: ndcg_at_10 value: 52.629000000000005 - type: ndcg_at_100 value: 55.995 - type: ndcg_at_1000 value: 56.962999999999994 - type: ndcg_at_3 value: 47.188 - type: ndcg_at_5 value: 50.019000000000005 - type: precision_at_1 value: 37.774 - type: precision_at_10 value: 7.541 - type: precision_at_100 value: 0.931 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 19.572 - type: precision_at_5 value: 13.288 - type: recall_at_1 value: 35.098 - type: recall_at_10 value: 68.818 - type: recall_at_100 value: 84.004 - type: recall_at_1000 value: 91.36800000000001 - type: recall_at_3 value: 54.176 - type: recall_at_5 value: 60.968999999999994 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 17.982 - type: map_at_10 value: 28.994999999999997 - type: map_at_100 value: 30.868000000000002 - type: map_at_1000 value: 31.045 - type: map_at_3 value: 25.081999999999997 - type: map_at_5 value: 27.303 - type: mrr_at_1 value: 35.031 - type: mrr_at_10 value: 43.537 - type: mrr_at_100 value: 44.422 - type: mrr_at_1000 value: 44.471 - type: mrr_at_3 value: 41.024 - type: mrr_at_5 value: 42.42 - type: ndcg_at_1 value: 35.031 - type: ndcg_at_10 value: 36.346000000000004 - type: ndcg_at_100 value: 43.275000000000006 - type: ndcg_at_1000 value: 46.577 - type: ndcg_at_3 value: 32.42 - type: ndcg_at_5 value: 33.841 - type: precision_at_1 value: 35.031 - type: precision_at_10 value: 10.231 - type: precision_at_100 value: 1.728 - type: precision_at_1000 value: 0.231 - type: precision_at_3 value: 21.553 - type: precision_at_5 value: 16.204 - type: recall_at_1 value: 17.982 - type: recall_at_10 value: 43.169000000000004 - type: recall_at_100 value: 68.812 - type: recall_at_1000 value: 89.008 - type: recall_at_3 value: 29.309 - type: recall_at_5 value: 35.514 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 27.387 - type: map_at_10 value: 36.931000000000004 - type: map_at_100 value: 37.734 - type: map_at_1000 value: 37.818000000000005 - type: map_at_3 value: 34.691 - type: map_at_5 value: 36.016999999999996 - type: mrr_at_1 value: 54.774 - type: mrr_at_10 value: 62.133 - type: mrr_at_100 value: 62.587 - type: mrr_at_1000 value: 62.61600000000001 - type: mrr_at_3 value: 60.49099999999999 - type: mrr_at_5 value: 61.480999999999995 - type: ndcg_at_1 value: 54.774 - type: ndcg_at_10 value: 45.657 - type: ndcg_at_100 value: 48.954 - type: ndcg_at_1000 value: 50.78 - type: ndcg_at_3 value: 41.808 - type: ndcg_at_5 value: 43.816 - type: precision_at_1 value: 54.774 - type: precision_at_10 value: 9.479 - type: precision_at_100 value: 1.208 - type: precision_at_1000 value: 0.145 - type: precision_at_3 value: 25.856 - type: precision_at_5 value: 17.102 - type: recall_at_1 value: 27.387 - type: recall_at_10 value: 47.394 - type: recall_at_100 value: 60.397999999999996 - type: recall_at_1000 value: 72.54599999999999 - type: recall_at_3 value: 38.785 - type: recall_at_5 value: 42.754999999999995 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 61.217999999999996 - type: ap value: 56.84286974948407 - type: f1 value: 60.99211195455131 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 19.224 - type: map_at_10 value: 30.448999999999998 - type: map_at_100 value: 31.663999999999998 - type: map_at_1000 value: 31.721 - type: map_at_3 value: 26.922 - type: map_at_5 value: 28.906 - type: mrr_at_1 value: 19.756 - type: mrr_at_10 value: 30.994 - type: mrr_at_100 value: 32.161 - type: mrr_at_1000 value: 32.213 - type: mrr_at_3 value: 27.502 - type: mrr_at_5 value: 29.48 - type: ndcg_at_1 value: 19.742 - type: ndcg_at_10 value: 36.833 - type: ndcg_at_100 value: 42.785000000000004 - type: ndcg_at_1000 value: 44.291000000000004 - type: ndcg_at_3 value: 29.580000000000002 - type: ndcg_at_5 value: 33.139 - type: precision_at_1 value: 19.742 - type: precision_at_10 value: 5.894 - type: precision_at_100 value: 0.889 - type: precision_at_1000 value: 0.10200000000000001 - type: precision_at_3 value: 12.665000000000001 - type: precision_at_5 value: 9.393 - type: recall_at_1 value: 19.224 - type: recall_at_10 value: 56.538999999999994 - type: recall_at_100 value: 84.237 - type: recall_at_1000 value: 95.965 - type: recall_at_3 value: 36.71 - type: recall_at_5 value: 45.283 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 89.97264021887824 - type: f1 value: 89.53607318488027 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 59.566803465572285 - type: f1 value: 40.94003955225124 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 66.7787491593813 - type: f1 value: 64.51190971513093 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 73.7794216543376 - type: f1 value: 72.71852261076475 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 28.40883054472429 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 26.144338339113617 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 30.894071459751267 - type: mrr value: 31.965886150526256 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 5.024 - type: map_at_10 value: 10.533 - type: map_at_100 value: 12.97 - type: map_at_1000 value: 14.163 - type: map_at_3 value: 7.971 - type: map_at_5 value: 9.15 - type: mrr_at_1 value: 40.867 - type: mrr_at_10 value: 48.837 - type: mrr_at_100 value: 49.464999999999996 - type: mrr_at_1000 value: 49.509 - type: mrr_at_3 value: 46.800999999999995 - type: mrr_at_5 value: 47.745 - type: ndcg_at_1 value: 38.854 - type: ndcg_at_10 value: 29.674 - type: ndcg_at_100 value: 26.66 - type: ndcg_at_1000 value: 35.088 - type: ndcg_at_3 value: 34.838 - type: ndcg_at_5 value: 32.423 - type: precision_at_1 value: 40.248 - type: precision_at_10 value: 21.826999999999998 - type: precision_at_100 value: 6.78 - type: precision_at_1000 value: 1.889 - type: precision_at_3 value: 32.405 - type: precision_at_5 value: 27.74 - type: recall_at_1 value: 5.024 - type: recall_at_10 value: 13.996 - type: recall_at_100 value: 26.636 - type: recall_at_1000 value: 57.816 - type: recall_at_3 value: 9.063 - type: recall_at_5 value: 10.883 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 23.088 - type: map_at_10 value: 36.915 - type: map_at_100 value: 38.141999999999996 - type: map_at_1000 value: 38.191 - type: map_at_3 value: 32.458999999999996 - type: map_at_5 value: 35.004999999999995 - type: mrr_at_1 value: 26.101000000000003 - type: mrr_at_10 value: 39.1 - type: mrr_at_100 value: 40.071 - type: mrr_at_1000 value: 40.106 - type: mrr_at_3 value: 35.236000000000004 - type: mrr_at_5 value: 37.43 - type: ndcg_at_1 value: 26.072 - type: ndcg_at_10 value: 44.482 - type: ndcg_at_100 value: 49.771 - type: ndcg_at_1000 value: 50.903 - type: ndcg_at_3 value: 35.922 - type: ndcg_at_5 value: 40.178000000000004 - type: precision_at_1 value: 26.072 - type: precision_at_10 value: 7.795000000000001 - type: precision_at_100 value: 1.072 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 16.725 - type: precision_at_5 value: 12.468 - type: recall_at_1 value: 23.088 - type: recall_at_10 value: 65.534 - type: recall_at_100 value: 88.68 - type: recall_at_1000 value: 97.101 - type: recall_at_3 value: 43.161 - type: recall_at_5 value: 52.959999999999994 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 69.612 - type: map_at_10 value: 83.292 - type: map_at_100 value: 83.96000000000001 - type: map_at_1000 value: 83.978 - type: map_at_3 value: 80.26299999999999 - type: map_at_5 value: 82.11500000000001 - type: mrr_at_1 value: 80.21000000000001 - type: mrr_at_10 value: 86.457 - type: mrr_at_100 value: 86.58500000000001 - type: mrr_at_1000 value: 86.587 - type: mrr_at_3 value: 85.452 - type: mrr_at_5 value: 86.101 - type: ndcg_at_1 value: 80.21000000000001 - type: ndcg_at_10 value: 87.208 - type: ndcg_at_100 value: 88.549 - type: ndcg_at_1000 value: 88.683 - type: ndcg_at_3 value: 84.20400000000001 - type: ndcg_at_5 value: 85.768 - type: precision_at_1 value: 80.21000000000001 - type: precision_at_10 value: 13.29 - type: precision_at_100 value: 1.5230000000000001 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 36.767 - type: precision_at_5 value: 24.2 - type: recall_at_1 value: 69.612 - type: recall_at_10 value: 94.651 - type: recall_at_100 value: 99.297 - type: recall_at_1000 value: 99.95100000000001 - type: recall_at_3 value: 86.003 - type: recall_at_5 value: 90.45100000000001 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 46.28945925252077 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 50.954446620859684 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 3.888 - type: map_at_10 value: 9.21 - type: map_at_100 value: 10.629 - type: map_at_1000 value: 10.859 - type: map_at_3 value: 6.743 - type: map_at_5 value: 7.982 - type: mrr_at_1 value: 19.1 - type: mrr_at_10 value: 28.294000000000004 - type: mrr_at_100 value: 29.326999999999998 - type: mrr_at_1000 value: 29.414 - type: mrr_at_3 value: 25.367 - type: mrr_at_5 value: 27.002 - type: ndcg_at_1 value: 19.1 - type: ndcg_at_10 value: 15.78 - type: ndcg_at_100 value: 21.807000000000002 - type: ndcg_at_1000 value: 26.593 - type: ndcg_at_3 value: 15.204999999999998 - type: ndcg_at_5 value: 13.217 - type: precision_at_1 value: 19.1 - type: precision_at_10 value: 7.9799999999999995 - type: precision_at_100 value: 1.667 - type: precision_at_1000 value: 0.28300000000000003 - type: precision_at_3 value: 13.933000000000002 - type: precision_at_5 value: 11.379999999999999 - type: recall_at_1 value: 3.888 - type: recall_at_10 value: 16.17 - type: recall_at_100 value: 33.848 - type: recall_at_1000 value: 57.345 - type: recall_at_3 value: 8.468 - type: recall_at_5 value: 11.540000000000001 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 79.05803116288386 - type: cos_sim_spearman value: 70.0403855402571 - type: euclidean_pearson value: 75.59006280166072 - type: euclidean_spearman value: 70.04038926247613 - type: manhattan_pearson value: 75.48136278078455 - type: manhattan_spearman value: 69.9608897701754 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 68.56836430603597 - type: cos_sim_spearman value: 64.38407759822387 - type: euclidean_pearson value: 65.93619045541732 - type: euclidean_spearman value: 64.38184049884836 - type: manhattan_pearson value: 65.97148637646873 - type: manhattan_spearman value: 64.48011982438929 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 75.990362280318 - type: cos_sim_spearman value: 76.40621890996734 - type: euclidean_pearson value: 76.01739766577184 - type: euclidean_spearman value: 76.4062736496846 - type: manhattan_pearson value: 76.04738378838042 - type: manhattan_spearman value: 76.44991409719592 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 74.8516957692617 - type: cos_sim_spearman value: 69.325199098278 - type: euclidean_pearson value: 73.37922793254768 - type: euclidean_spearman value: 69.32520119670215 - type: manhattan_pearson value: 73.3795212376615 - type: manhattan_spearman value: 69.35306787926315 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 78.644002190612 - type: cos_sim_spearman value: 80.18337978181648 - type: euclidean_pearson value: 79.7628642371887 - type: euclidean_spearman value: 80.18337906907526 - type: manhattan_pearson value: 79.68810722704522 - type: manhattan_spearman value: 80.10664518173466 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 77.8303940874723 - type: cos_sim_spearman value: 79.56812599677549 - type: euclidean_pearson value: 79.38928950396344 - type: euclidean_spearman value: 79.56812556750812 - type: manhattan_pearson value: 79.41057583507681 - type: manhattan_spearman value: 79.57604428731142 - 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: 78.90792116013353 - type: cos_sim_spearman value: 81.18059230233499 - type: euclidean_pearson value: 80.2622631297375 - type: euclidean_spearman value: 81.18059230233499 - type: manhattan_pearson value: 80.23946026135997 - type: manhattan_spearman value: 81.11947325071426 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) config: en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 64.46850619973324 - type: cos_sim_spearman value: 65.50839374141563 - type: euclidean_pearson value: 66.60130812260707 - type: euclidean_spearman value: 65.50839374141563 - type: manhattan_pearson value: 66.58871918195092 - type: manhattan_spearman value: 65.7347325297592 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 75.71536124107834 - type: cos_sim_spearman value: 75.98365906208434 - type: euclidean_pearson value: 76.64573753881218 - type: euclidean_spearman value: 75.98365906208434 - type: manhattan_pearson value: 76.63637189172626 - type: manhattan_spearman value: 75.9660207821009 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 74.27669440147513 - type: mrr value: 91.7729356699945 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 41.028 - type: map_at_10 value: 49.919000000000004 - type: map_at_100 value: 50.91 - type: map_at_1000 value: 50.955 - type: map_at_3 value: 47.785 - type: map_at_5 value: 49.084 - type: mrr_at_1 value: 43.667 - type: mrr_at_10 value: 51.342 - type: mrr_at_100 value: 52.197 - type: mrr_at_1000 value: 52.236000000000004 - type: mrr_at_3 value: 49.667 - type: mrr_at_5 value: 50.766999999999996 - type: ndcg_at_1 value: 43.667 - type: ndcg_at_10 value: 54.029 - type: ndcg_at_100 value: 58.909 - type: ndcg_at_1000 value: 60.131 - type: ndcg_at_3 value: 50.444 - type: ndcg_at_5 value: 52.354 - type: precision_at_1 value: 43.667 - type: precision_at_10 value: 7.432999999999999 - type: precision_at_100 value: 1.0 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 20.444000000000003 - type: precision_at_5 value: 13.533000000000001 - type: recall_at_1 value: 41.028 - type: recall_at_10 value: 65.011 - type: recall_at_100 value: 88.033 - type: recall_at_1000 value: 97.667 - type: recall_at_3 value: 55.394 - type: recall_at_5 value: 60.183 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.76534653465346 - type: cos_sim_ap value: 93.83756773536699 - type: cos_sim_f1 value: 87.91097622660598 - type: cos_sim_precision value: 88.94575230296827 - type: cos_sim_recall value: 86.9 - type: dot_accuracy value: 99.76534653465346 - type: dot_ap value: 93.83756773536699 - type: dot_f1 value: 87.91097622660598 - type: dot_precision value: 88.94575230296827 - type: dot_recall value: 86.9 - type: euclidean_accuracy value: 99.76534653465346 - type: euclidean_ap value: 93.837567735367 - type: euclidean_f1 value: 87.91097622660598 - type: euclidean_precision value: 88.94575230296827 - type: euclidean_recall value: 86.9 - type: manhattan_accuracy value: 99.76633663366337 - type: manhattan_ap value: 93.84480825492724 - type: manhattan_f1 value: 87.97145769622833 - type: manhattan_precision value: 89.70893970893971 - type: manhattan_recall value: 86.3 - type: max_accuracy value: 99.76633663366337 - type: max_ap value: 93.84480825492724 - type: max_f1 value: 87.97145769622833 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 48.078155553339585 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 33.34857297824906 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 50.06219491505384 - type: mrr value: 50.77479097699686 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.48401937651373 - type: cos_sim_spearman value: 31.048654273022606 - type: dot_pearson value: 30.484020082707847 - type: dot_spearman value: 31.048654273022606 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.183 - type: map_at_10 value: 1.32 - type: map_at_100 value: 7.01 - type: map_at_1000 value: 16.957 - type: map_at_3 value: 0.481 - type: map_at_5 value: 0.737 - type: mrr_at_1 value: 66.0 - type: mrr_at_10 value: 78.7 - type: mrr_at_100 value: 78.7 - type: mrr_at_1000 value: 78.7 - type: mrr_at_3 value: 76.0 - type: mrr_at_5 value: 78.7 - type: ndcg_at_1 value: 56.99999999999999 - type: ndcg_at_10 value: 55.846 - type: ndcg_at_100 value: 43.138 - type: ndcg_at_1000 value: 39.4 - type: ndcg_at_3 value: 57.306999999999995 - type: ndcg_at_5 value: 57.294 - type: precision_at_1 value: 66.0 - type: precision_at_10 value: 60.0 - type: precision_at_100 value: 44.6 - type: precision_at_1000 value: 17.8 - type: precision_at_3 value: 62.0 - type: precision_at_5 value: 62.0 - type: recall_at_1 value: 0.183 - type: recall_at_10 value: 1.583 - type: recall_at_100 value: 10.412 - type: recall_at_1000 value: 37.358999999999995 - type: recall_at_3 value: 0.516 - type: recall_at_5 value: 0.845 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.7420000000000002 - type: map_at_10 value: 6.4879999999999995 - type: map_at_100 value: 11.654 - type: map_at_1000 value: 13.23 - type: map_at_3 value: 3.148 - type: map_at_5 value: 4.825 - type: mrr_at_1 value: 18.367 - type: mrr_at_10 value: 30.258000000000003 - type: mrr_at_100 value: 31.570999999999998 - type: mrr_at_1000 value: 31.594 - type: mrr_at_3 value: 26.19 - type: mrr_at_5 value: 28.027 - type: ndcg_at_1 value: 15.306000000000001 - type: ndcg_at_10 value: 15.608 - type: ndcg_at_100 value: 28.808 - type: ndcg_at_1000 value: 41.603 - type: ndcg_at_3 value: 13.357 - type: ndcg_at_5 value: 15.306000000000001 - type: precision_at_1 value: 18.367 - type: precision_at_10 value: 15.101999999999999 - type: precision_at_100 value: 6.49 - type: precision_at_1000 value: 1.488 - type: precision_at_3 value: 14.966 - type: precision_at_5 value: 17.143 - type: recall_at_1 value: 1.7420000000000002 - type: recall_at_10 value: 12.267 - type: recall_at_100 value: 41.105999999999995 - type: recall_at_1000 value: 80.569 - type: recall_at_3 value: 4.009 - type: recall_at_5 value: 7.417999999999999 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 65.1178 - type: ap value: 11.974961582206614 - type: f1 value: 50.24491996814835 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 51.63271080928127 - type: f1 value: 51.81589904316042 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 40.791709673552276 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 83.05418131966383 - type: cos_sim_ap value: 64.72353098186304 - type: cos_sim_f1 value: 61.313330054107226 - type: cos_sim_precision value: 57.415937356057114 - type: cos_sim_recall value: 65.77836411609499 - type: dot_accuracy value: 83.05418131966383 - type: dot_ap value: 64.72352701424393 - type: dot_f1 value: 61.313330054107226 - type: dot_precision value: 57.415937356057114 - type: dot_recall value: 65.77836411609499 - type: euclidean_accuracy value: 83.05418131966383 - type: euclidean_ap value: 64.72353124585976 - type: euclidean_f1 value: 61.313330054107226 - type: euclidean_precision value: 57.415937356057114 - type: euclidean_recall value: 65.77836411609499 - type: manhattan_accuracy value: 82.98861536627525 - type: manhattan_ap value: 64.53981837182303 - type: manhattan_f1 value: 60.94911377930246 - type: manhattan_precision value: 53.784056508577194 - type: manhattan_recall value: 70.31662269129288 - type: max_accuracy value: 83.05418131966383 - type: max_ap value: 64.72353124585976 - type: max_f1 value: 61.313330054107226 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.06225016493966 - type: cos_sim_ap value: 84.00829172423475 - type: cos_sim_f1 value: 76.1288446157202 - type: cos_sim_precision value: 72.11737153877945 - type: cos_sim_recall value: 80.61287342161995 - type: dot_accuracy value: 88.06225016493966 - type: dot_ap value: 84.00827913374181 - type: dot_f1 value: 76.1288446157202 - type: dot_precision value: 72.11737153877945 - type: dot_recall value: 80.61287342161995 - type: euclidean_accuracy value: 88.06225016493966 - type: euclidean_ap value: 84.00827099295034 - type: euclidean_f1 value: 76.1288446157202 - type: euclidean_precision value: 72.11737153877945 - type: euclidean_recall value: 80.61287342161995 - type: manhattan_accuracy value: 88.05642876547523 - type: manhattan_ap value: 83.9157542691417 - type: manhattan_f1 value: 76.09045667447307 - type: manhattan_precision value: 72.50348675034869 - type: manhattan_recall value: 80.05081613797351 - type: max_accuracy value: 88.06225016493966 - type: max_ap value: 84.00829172423475 - type: max_f1 value: 76.1288446157202 --- MTEB evaluation results on English language for 'multi-qa-MiniLM-L6-cos-v1' sbert model Model and licence can be found [here](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1)