--- tags: - mteb model-index: - name: andersonbcdefg/bge-small-4096 results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 68.74626865671641 - type: ap value: 31.113961861085855 - type: f1 value: 62.628656720790275 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 81.30347499999999 - type: ap value: 76.05639977935193 - type: f1 value: 81.23180016825499 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 38.566 - type: f1 value: 38.014543974125615 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 29.445 - type: map_at_10 value: 44.157999999999994 - type: map_at_100 value: 45.169 - type: map_at_1000 value: 45.178000000000004 - type: map_at_3 value: 39.545 - type: map_at_5 value: 42.233 - type: mrr_at_1 value: 29.445 - type: mrr_at_10 value: 44.157999999999994 - type: mrr_at_100 value: 45.169 - type: mrr_at_1000 value: 45.178000000000004 - type: mrr_at_3 value: 39.545 - type: mrr_at_5 value: 42.233 - type: ndcg_at_1 value: 29.445 - type: ndcg_at_10 value: 52.446000000000005 - type: ndcg_at_100 value: 56.782 - type: ndcg_at_1000 value: 56.989999999999995 - type: ndcg_at_3 value: 42.935 - type: ndcg_at_5 value: 47.833999999999996 - type: precision_at_1 value: 29.445 - type: precision_at_10 value: 7.8950000000000005 - type: precision_at_100 value: 0.979 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 17.591 - type: precision_at_5 value: 12.959000000000001 - type: recall_at_1 value: 29.445 - type: recall_at_10 value: 78.947 - type: recall_at_100 value: 97.937 - type: recall_at_1000 value: 99.502 - type: recall_at_3 value: 52.774 - type: recall_at_5 value: 64.794 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 43.85187820924144 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 29.5939502757938 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 58.539409343284674 - type: mrr value: 71.58982983775228 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 82.31440765254087 - type: cos_sim_spearman value: 81.59884723689632 - type: euclidean_pearson value: 80.65818473893147 - type: euclidean_spearman value: 81.40004752638717 - type: manhattan_pearson value: 80.52256901536644 - type: manhattan_spearman value: 80.57292024599603 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 79.98376623376623 - type: f1 value: 79.91981901371503 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 37.79541356345093 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 26.760513681350375 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 23.794 - type: map_at_10 value: 33.361000000000004 - type: map_at_100 value: 34.86 - type: map_at_1000 value: 35.0 - type: map_at_3 value: 30.579 - type: map_at_5 value: 31.996000000000002 - type: mrr_at_1 value: 30.186 - type: mrr_at_10 value: 39.681 - type: mrr_at_100 value: 40.616 - type: mrr_at_1000 value: 40.669 - type: mrr_at_3 value: 37.244 - type: mrr_at_5 value: 38.588 - type: ndcg_at_1 value: 30.186 - type: ndcg_at_10 value: 39.34 - type: ndcg_at_100 value: 45.266 - type: ndcg_at_1000 value: 47.9 - type: ndcg_at_3 value: 35.164 - type: ndcg_at_5 value: 36.854 - type: precision_at_1 value: 30.186 - type: precision_at_10 value: 7.639 - type: precision_at_100 value: 1.328 - type: precision_at_1000 value: 0.183 - type: precision_at_3 value: 17.31 - type: precision_at_5 value: 12.275 - type: recall_at_1 value: 23.794 - type: recall_at_10 value: 50.463 - type: recall_at_100 value: 75.268 - type: recall_at_1000 value: 93.138 - type: recall_at_3 value: 37.797 - type: recall_at_5 value: 42.985 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.968999999999998 - type: map_at_10 value: 23.846999999999998 - type: map_at_100 value: 24.712999999999997 - type: map_at_1000 value: 24.833 - type: map_at_3 value: 22.024 - type: map_at_5 value: 23.087 - type: mrr_at_1 value: 22.038 - type: mrr_at_10 value: 27.808 - type: mrr_at_100 value: 28.532999999999998 - type: mrr_at_1000 value: 28.604000000000003 - type: mrr_at_3 value: 26.029999999999998 - type: mrr_at_5 value: 27.122 - type: ndcg_at_1 value: 22.038 - type: ndcg_at_10 value: 27.559 - type: ndcg_at_100 value: 31.541999999999998 - type: ndcg_at_1000 value: 34.343 - type: ndcg_at_3 value: 24.585 - type: ndcg_at_5 value: 26.026 - type: precision_at_1 value: 22.038 - type: precision_at_10 value: 5.019 - type: precision_at_100 value: 0.8920000000000001 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 11.423 - type: precision_at_5 value: 8.28 - type: recall_at_1 value: 17.968999999999998 - type: recall_at_10 value: 34.583000000000006 - type: recall_at_100 value: 51.849000000000004 - type: recall_at_1000 value: 70.832 - type: recall_at_3 value: 26.057000000000002 - type: recall_at_5 value: 29.816 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 29.183999999999997 - type: map_at_10 value: 40.245 - type: map_at_100 value: 41.324 - type: map_at_1000 value: 41.402 - type: map_at_3 value: 37.395 - type: map_at_5 value: 38.964999999999996 - type: mrr_at_1 value: 33.981 - type: mrr_at_10 value: 43.471 - type: mrr_at_100 value: 44.303 - type: mrr_at_1000 value: 44.352999999999994 - type: mrr_at_3 value: 41.149 - type: mrr_at_5 value: 42.466 - type: ndcg_at_1 value: 33.981 - type: ndcg_at_10 value: 45.776 - type: ndcg_at_100 value: 50.441 - type: ndcg_at_1000 value: 52.16 - type: ndcg_at_3 value: 40.756 - type: ndcg_at_5 value: 43.132 - type: precision_at_1 value: 33.981 - type: precision_at_10 value: 7.617999999999999 - type: precision_at_100 value: 1.083 - type: precision_at_1000 value: 0.129 - type: precision_at_3 value: 18.558 - type: precision_at_5 value: 12.915 - type: recall_at_1 value: 29.183999999999997 - type: recall_at_10 value: 59.114 - type: recall_at_100 value: 79.549 - type: recall_at_1000 value: 91.925 - type: recall_at_3 value: 45.551 - type: recall_at_5 value: 51.38399999999999 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 20.286 - type: map_at_10 value: 27.143 - type: map_at_100 value: 28.107 - type: map_at_1000 value: 28.212 - type: map_at_3 value: 25.149 - type: map_at_5 value: 26.179999999999996 - type: mrr_at_1 value: 22.034000000000002 - type: mrr_at_10 value: 28.875 - type: mrr_at_100 value: 29.785 - type: mrr_at_1000 value: 29.876 - type: mrr_at_3 value: 27.023999999999997 - type: mrr_at_5 value: 28.058 - type: ndcg_at_1 value: 22.034000000000002 - type: ndcg_at_10 value: 31.148999999999997 - type: ndcg_at_100 value: 35.936 - type: ndcg_at_1000 value: 38.682 - type: ndcg_at_3 value: 27.230999999999998 - type: ndcg_at_5 value: 29.034 - type: precision_at_1 value: 22.034000000000002 - type: precision_at_10 value: 4.836 - type: precision_at_100 value: 0.754 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 11.562999999999999 - type: precision_at_5 value: 8.068 - type: recall_at_1 value: 20.286 - type: recall_at_10 value: 41.827999999999996 - type: recall_at_100 value: 63.922000000000004 - type: recall_at_1000 value: 84.639 - type: recall_at_3 value: 31.227 - type: recall_at_5 value: 35.546 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 13.488 - type: map_at_10 value: 18.595 - type: map_at_100 value: 19.783 - type: map_at_1000 value: 19.918 - type: map_at_3 value: 16.274 - type: map_at_5 value: 17.558 - type: mrr_at_1 value: 16.791 - type: mrr_at_10 value: 22.53 - type: mrr_at_100 value: 23.651 - type: mrr_at_1000 value: 23.738999999999997 - type: mrr_at_3 value: 20.232 - type: mrr_at_5 value: 21.644 - type: ndcg_at_1 value: 16.791 - type: ndcg_at_10 value: 22.672 - type: ndcg_at_100 value: 28.663 - type: ndcg_at_1000 value: 31.954 - type: ndcg_at_3 value: 18.372 - type: ndcg_at_5 value: 20.47 - type: precision_at_1 value: 16.791 - type: precision_at_10 value: 4.2540000000000004 - type: precision_at_100 value: 0.8370000000000001 - type: precision_at_1000 value: 0.125 - type: precision_at_3 value: 8.706 - type: precision_at_5 value: 6.666999999999999 - type: recall_at_1 value: 13.488 - type: recall_at_10 value: 31.451 - type: recall_at_100 value: 58.085 - type: recall_at_1000 value: 81.792 - type: recall_at_3 value: 19.811 - type: recall_at_5 value: 24.973 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.436 - type: map_at_10 value: 29.105999999999998 - type: map_at_100 value: 30.442000000000004 - type: map_at_1000 value: 30.567 - type: map_at_3 value: 26.430999999999997 - type: map_at_5 value: 27.866000000000003 - type: mrr_at_1 value: 26.083000000000002 - type: mrr_at_10 value: 33.975 - type: mrr_at_100 value: 35.014 - type: mrr_at_1000 value: 35.07 - type: mrr_at_3 value: 31.649 - type: mrr_at_5 value: 32.944 - type: ndcg_at_1 value: 26.083000000000002 - type: ndcg_at_10 value: 34.229 - type: ndcg_at_100 value: 40.439 - type: ndcg_at_1000 value: 43.081 - type: ndcg_at_3 value: 29.64 - type: ndcg_at_5 value: 31.704 - type: precision_at_1 value: 26.083000000000002 - type: precision_at_10 value: 6.246 - type: precision_at_100 value: 1.1199999999999999 - type: precision_at_1000 value: 0.155 - type: precision_at_3 value: 13.858999999999998 - type: precision_at_5 value: 10.01 - type: recall_at_1 value: 21.436 - type: recall_at_10 value: 44.938 - type: recall_at_100 value: 72.029 - type: recall_at_1000 value: 90.009 - type: recall_at_3 value: 31.954 - type: recall_at_5 value: 37.303 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.217 - type: map_at_10 value: 25.16 - type: map_at_100 value: 26.490000000000002 - type: map_at_1000 value: 26.619 - type: map_at_3 value: 22.926 - type: map_at_5 value: 24.251 - type: mrr_at_1 value: 22.831000000000003 - type: mrr_at_10 value: 30.009000000000004 - type: mrr_at_100 value: 31.045 - type: mrr_at_1000 value: 31.122 - type: mrr_at_3 value: 28.025 - type: mrr_at_5 value: 29.07 - type: ndcg_at_1 value: 22.831000000000003 - type: ndcg_at_10 value: 29.664 - type: ndcg_at_100 value: 35.900999999999996 - type: ndcg_at_1000 value: 38.932 - type: ndcg_at_3 value: 26.051000000000002 - type: ndcg_at_5 value: 27.741 - type: precision_at_1 value: 22.831000000000003 - type: precision_at_10 value: 5.479 - type: precision_at_100 value: 1.027 - type: precision_at_1000 value: 0.146 - type: precision_at_3 value: 12.481 - type: precision_at_5 value: 8.973 - type: recall_at_1 value: 18.217 - type: recall_at_10 value: 38.336 - type: recall_at_100 value: 65.854 - type: recall_at_1000 value: 87.498 - type: recall_at_3 value: 28.158 - type: recall_at_5 value: 32.841 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 19.100666666666665 - type: map_at_10 value: 26.22883333333333 - type: map_at_100 value: 27.34241666666667 - type: map_at_1000 value: 27.468416666666666 - type: map_at_3 value: 23.953916666666668 - type: map_at_5 value: 25.20125 - type: mrr_at_1 value: 22.729249999999997 - type: mrr_at_10 value: 29.86491666666667 - type: mrr_at_100 value: 30.76925 - type: mrr_at_1000 value: 30.846333333333337 - type: mrr_at_3 value: 27.733999999999998 - type: mrr_at_5 value: 28.94058333333333 - type: ndcg_at_1 value: 22.729249999999997 - type: ndcg_at_10 value: 30.708250000000003 - type: ndcg_at_100 value: 35.89083333333333 - type: ndcg_at_1000 value: 38.75891666666666 - type: ndcg_at_3 value: 26.661083333333334 - type: ndcg_at_5 value: 28.54 - type: precision_at_1 value: 22.729249999999997 - type: precision_at_10 value: 5.433833333333333 - type: precision_at_100 value: 0.9486666666666665 - type: precision_at_1000 value: 0.13808333333333334 - type: precision_at_3 value: 12.292166666666668 - type: precision_at_5 value: 8.825 - type: recall_at_1 value: 19.100666666666665 - type: recall_at_10 value: 40.54208333333334 - type: recall_at_100 value: 63.67975 - type: recall_at_1000 value: 84.13574999999999 - type: recall_at_3 value: 29.311000000000003 - type: recall_at_5 value: 34.1105 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.762 - type: map_at_10 value: 23.905 - type: map_at_100 value: 24.663 - type: map_at_1000 value: 24.765 - type: map_at_3 value: 22.032 - type: map_at_5 value: 23.025000000000002 - type: mrr_at_1 value: 20.244999999999997 - type: mrr_at_10 value: 26.162999999999997 - type: mrr_at_100 value: 26.907999999999998 - type: mrr_at_1000 value: 26.987 - type: mrr_at_3 value: 24.361 - type: mrr_at_5 value: 25.326999999999998 - type: ndcg_at_1 value: 20.244999999999997 - type: ndcg_at_10 value: 27.577 - type: ndcg_at_100 value: 31.473000000000003 - type: ndcg_at_1000 value: 34.217999999999996 - type: ndcg_at_3 value: 24.092 - type: ndcg_at_5 value: 25.657000000000004 - type: precision_at_1 value: 20.244999999999997 - type: precision_at_10 value: 4.433 - type: precision_at_100 value: 0.692 - type: precision_at_1000 value: 0.099 - type: precision_at_3 value: 10.634 - type: precision_at_5 value: 7.362 - type: recall_at_1 value: 17.762 - type: recall_at_10 value: 36.661 - type: recall_at_100 value: 54.581999999999994 - type: recall_at_1000 value: 75.28099999999999 - type: recall_at_3 value: 27.084999999999997 - type: recall_at_5 value: 31.064999999999998 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 12.998000000000001 - type: map_at_10 value: 18.926000000000002 - type: map_at_100 value: 19.836000000000002 - type: map_at_1000 value: 19.96 - type: map_at_3 value: 16.932 - type: map_at_5 value: 17.963 - type: mrr_at_1 value: 15.692 - type: mrr_at_10 value: 22.206 - type: mrr_at_100 value: 23.021 - type: mrr_at_1000 value: 23.108999999999998 - type: mrr_at_3 value: 20.114 - type: mrr_at_5 value: 21.241 - type: ndcg_at_1 value: 15.692 - type: ndcg_at_10 value: 22.997999999999998 - type: ndcg_at_100 value: 27.541 - type: ndcg_at_1000 value: 30.758000000000003 - type: ndcg_at_3 value: 19.117 - type: ndcg_at_5 value: 20.778 - type: precision_at_1 value: 15.692 - type: precision_at_10 value: 4.277 - type: precision_at_100 value: 0.774 - type: precision_at_1000 value: 0.122 - type: precision_at_3 value: 9.027000000000001 - type: precision_at_5 value: 6.641 - type: recall_at_1 value: 12.998000000000001 - type: recall_at_10 value: 32.135999999999996 - type: recall_at_100 value: 52.937 - type: recall_at_1000 value: 76.348 - type: recall_at_3 value: 21.292 - type: recall_at_5 value: 25.439 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 20.219 - type: map_at_10 value: 27.306 - type: map_at_100 value: 28.337 - type: map_at_1000 value: 28.459 - type: map_at_3 value: 25.423000000000002 - type: map_at_5 value: 26.375999999999998 - type: mrr_at_1 value: 23.787 - type: mrr_at_10 value: 30.977 - type: mrr_at_100 value: 31.85 - type: mrr_at_1000 value: 31.939 - type: mrr_at_3 value: 29.073 - type: mrr_at_5 value: 30.095 - type: ndcg_at_1 value: 23.787 - type: ndcg_at_10 value: 31.615 - type: ndcg_at_100 value: 36.641 - type: ndcg_at_1000 value: 39.707 - type: ndcg_at_3 value: 27.994000000000003 - type: ndcg_at_5 value: 29.508000000000003 - type: precision_at_1 value: 23.787 - type: precision_at_10 value: 5.271 - type: precision_at_100 value: 0.865 - type: precision_at_1000 value: 0.125 - type: precision_at_3 value: 12.748999999999999 - type: precision_at_5 value: 8.806 - type: recall_at_1 value: 20.219 - type: recall_at_10 value: 41.108 - type: recall_at_100 value: 63.596 - type: recall_at_1000 value: 85.54899999999999 - type: recall_at_3 value: 31.129 - type: recall_at_5 value: 34.845 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 19.949 - type: map_at_10 value: 26.629 - type: map_at_100 value: 28.006999999999998 - type: map_at_1000 value: 28.221 - type: map_at_3 value: 24.099999999999998 - type: map_at_5 value: 25.487 - type: mrr_at_1 value: 24.111 - type: mrr_at_10 value: 30.592000000000002 - type: mrr_at_100 value: 31.448999999999998 - type: mrr_at_1000 value: 31.538 - type: mrr_at_3 value: 28.128999999999998 - type: mrr_at_5 value: 29.503 - type: ndcg_at_1 value: 24.111 - type: ndcg_at_10 value: 31.373 - type: ndcg_at_100 value: 36.897999999999996 - type: ndcg_at_1000 value: 40.288000000000004 - type: ndcg_at_3 value: 26.895000000000003 - type: ndcg_at_5 value: 29.009 - type: precision_at_1 value: 24.111 - type: precision_at_10 value: 6.067 - type: precision_at_100 value: 1.269 - type: precision_at_1000 value: 0.22 - type: precision_at_3 value: 12.385 - type: precision_at_5 value: 9.249 - type: recall_at_1 value: 19.949 - type: recall_at_10 value: 40.394000000000005 - type: recall_at_100 value: 65.812 - type: recall_at_1000 value: 88.247 - type: recall_at_3 value: 28.116000000000003 - type: recall_at_5 value: 33.4 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 13.905999999999999 - type: map_at_10 value: 20.523 - type: map_at_100 value: 21.547 - type: map_at_1000 value: 21.665 - type: map_at_3 value: 18.182000000000002 - type: map_at_5 value: 19.661 - type: mrr_at_1 value: 14.972 - type: mrr_at_10 value: 22.092 - type: mrr_at_100 value: 23.055999999999997 - type: mrr_at_1000 value: 23.150000000000002 - type: mrr_at_3 value: 19.778000000000002 - type: mrr_at_5 value: 21.229 - type: ndcg_at_1 value: 14.972 - type: ndcg_at_10 value: 24.547 - type: ndcg_at_100 value: 29.948999999999998 - type: ndcg_at_1000 value: 33.084 - type: ndcg_at_3 value: 20.036 - type: ndcg_at_5 value: 22.567 - type: precision_at_1 value: 14.972 - type: precision_at_10 value: 4.067 - type: precision_at_100 value: 0.743 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 8.811 - type: precision_at_5 value: 6.654 - type: recall_at_1 value: 13.905999999999999 - type: recall_at_10 value: 35.493 - type: recall_at_100 value: 60.67399999999999 - type: recall_at_1000 value: 84.371 - type: recall_at_3 value: 23.555 - type: recall_at_5 value: 29.729 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 7.529 - type: map_at_10 value: 12.794 - type: map_at_100 value: 14.315 - type: map_at_1000 value: 14.523 - type: map_at_3 value: 10.367999999999999 - type: map_at_5 value: 11.546 - type: mrr_at_1 value: 16.872999999999998 - type: mrr_at_10 value: 25.709 - type: mrr_at_100 value: 26.907999999999998 - type: mrr_at_1000 value: 26.962000000000003 - type: mrr_at_3 value: 22.486 - type: mrr_at_5 value: 24.245 - type: ndcg_at_1 value: 16.872999999999998 - type: ndcg_at_10 value: 19.005 - type: ndcg_at_100 value: 25.990999999999996 - type: ndcg_at_1000 value: 29.955 - type: ndcg_at_3 value: 14.573 - type: ndcg_at_5 value: 16.118 - type: precision_at_1 value: 16.872999999999998 - type: precision_at_10 value: 6.235 - type: precision_at_100 value: 1.374 - type: precision_at_1000 value: 0.21 - type: precision_at_3 value: 10.793 - type: precision_at_5 value: 8.73 - type: recall_at_1 value: 7.529 - type: recall_at_10 value: 24.007 - type: recall_at_100 value: 48.742000000000004 - type: recall_at_1000 value: 71.35000000000001 - type: recall_at_3 value: 13.467 - type: recall_at_5 value: 17.502000000000002 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 5.614 - type: map_at_10 value: 11.42 - type: map_at_100 value: 15.873000000000001 - type: map_at_1000 value: 17.021 - type: map_at_3 value: 8.495 - type: map_at_5 value: 9.790000000000001 - type: mrr_at_1 value: 42.0 - type: mrr_at_10 value: 52.477 - type: mrr_at_100 value: 53.095000000000006 - type: mrr_at_1000 value: 53.135 - type: mrr_at_3 value: 49.833 - type: mrr_at_5 value: 51.183 - type: ndcg_at_1 value: 31.374999999999996 - type: ndcg_at_10 value: 25.27 - type: ndcg_at_100 value: 29.709999999999997 - type: ndcg_at_1000 value: 36.975 - type: ndcg_at_3 value: 27.688000000000002 - type: ndcg_at_5 value: 25.987 - type: precision_at_1 value: 42.0 - type: precision_at_10 value: 21.2 - type: precision_at_100 value: 7.053 - type: precision_at_1000 value: 1.512 - type: precision_at_3 value: 32.333 - type: precision_at_5 value: 26.6 - type: recall_at_1 value: 5.614 - type: recall_at_10 value: 16.112000000000002 - type: recall_at_100 value: 36.165000000000006 - type: recall_at_1000 value: 60.362 - type: recall_at_3 value: 9.761000000000001 - type: recall_at_5 value: 12.279 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 40.085 - type: f1 value: 35.53934111316537 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 34.185 - type: map_at_10 value: 44.491 - type: map_at_100 value: 45.204 - type: map_at_1000 value: 45.254 - type: map_at_3 value: 42.006 - type: map_at_5 value: 43.516 - type: mrr_at_1 value: 37.024 - type: mrr_at_10 value: 47.524 - type: mrr_at_100 value: 48.185 - type: mrr_at_1000 value: 48.227 - type: mrr_at_3 value: 45.086999999999996 - type: mrr_at_5 value: 46.575 - type: ndcg_at_1 value: 37.024 - type: ndcg_at_10 value: 50.126000000000005 - type: ndcg_at_100 value: 53.577 - type: ndcg_at_1000 value: 54.906 - type: ndcg_at_3 value: 45.25 - type: ndcg_at_5 value: 47.842 - type: precision_at_1 value: 37.024 - type: precision_at_10 value: 7.132 - type: precision_at_100 value: 0.898 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 18.767 - type: precision_at_5 value: 12.676000000000002 - type: recall_at_1 value: 34.185 - type: recall_at_10 value: 64.703 - type: recall_at_100 value: 80.58 - type: recall_at_1000 value: 90.742 - type: recall_at_3 value: 51.483000000000004 - type: recall_at_5 value: 57.775 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 9.358 - type: map_at_10 value: 16.391 - type: map_at_100 value: 17.698 - type: map_at_1000 value: 17.912 - type: map_at_3 value: 13.831 - type: map_at_5 value: 15.187000000000001 - type: mrr_at_1 value: 18.673000000000002 - type: mrr_at_10 value: 26.907999999999998 - type: mrr_at_100 value: 27.842 - type: mrr_at_1000 value: 27.933000000000003 - type: mrr_at_3 value: 24.486 - type: mrr_at_5 value: 25.766 - type: ndcg_at_1 value: 18.673000000000002 - type: ndcg_at_10 value: 22.137 - type: ndcg_at_100 value: 28.126 - type: ndcg_at_1000 value: 32.489000000000004 - type: ndcg_at_3 value: 18.723 - type: ndcg_at_5 value: 19.858 - type: precision_at_1 value: 18.673000000000002 - type: precision_at_10 value: 6.389 - type: precision_at_100 value: 1.262 - type: precision_at_1000 value: 0.202 - type: precision_at_3 value: 12.757 - type: precision_at_5 value: 9.753 - type: recall_at_1 value: 9.358 - type: recall_at_10 value: 28.605000000000004 - type: recall_at_100 value: 51.713 - type: recall_at_1000 value: 78.408 - type: recall_at_3 value: 17.674 - type: recall_at_5 value: 21.97 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 22.997999999999998 - type: map_at_10 value: 32.957 - type: map_at_100 value: 33.972 - type: map_at_1000 value: 34.072 - type: map_at_3 value: 30.44 - type: map_at_5 value: 31.869999999999997 - type: mrr_at_1 value: 45.995999999999995 - type: mrr_at_10 value: 54.473000000000006 - type: mrr_at_100 value: 55.103 - type: mrr_at_1000 value: 55.139 - type: mrr_at_3 value: 52.349999999999994 - type: mrr_at_5 value: 53.61900000000001 - type: ndcg_at_1 value: 45.995999999999995 - type: ndcg_at_10 value: 41.333 - type: ndcg_at_100 value: 45.635999999999996 - type: ndcg_at_1000 value: 47.847 - type: ndcg_at_3 value: 36.825 - type: ndcg_at_5 value: 39.099000000000004 - type: precision_at_1 value: 45.995999999999995 - type: precision_at_10 value: 9.020999999999999 - type: precision_at_100 value: 1.244 - type: precision_at_1000 value: 0.154 - type: precision_at_3 value: 23.34 - type: precision_at_5 value: 15.8 - type: recall_at_1 value: 22.997999999999998 - type: recall_at_10 value: 45.105000000000004 - type: recall_at_100 value: 62.188 - type: recall_at_1000 value: 76.907 - type: recall_at_3 value: 35.010000000000005 - type: recall_at_5 value: 39.5 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 80.0944 - type: ap value: 74.43301569395831 - type: f1 value: 80.04407647044388 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 10.171 - type: map_at_10 value: 17.558 - type: map_at_100 value: 18.694 - type: map_at_1000 value: 18.787000000000003 - type: map_at_3 value: 14.826 - type: map_at_5 value: 16.249 - type: mrr_at_1 value: 10.473 - type: mrr_at_10 value: 17.967 - type: mrr_at_100 value: 19.089 - type: mrr_at_1000 value: 19.177 - type: mrr_at_3 value: 15.222 - type: mrr_at_5 value: 16.655 - type: ndcg_at_1 value: 10.473 - type: ndcg_at_10 value: 22.148 - type: ndcg_at_100 value: 28.028 - type: ndcg_at_1000 value: 30.659 - type: ndcg_at_3 value: 16.474 - type: ndcg_at_5 value: 19.017 - type: precision_at_1 value: 10.473 - type: precision_at_10 value: 3.7969999999999997 - type: precision_at_100 value: 0.6779999999999999 - type: precision_at_1000 value: 0.09 - type: precision_at_3 value: 7.187 - type: precision_at_5 value: 5.599 - type: recall_at_1 value: 10.171 - type: recall_at_10 value: 36.459 - type: recall_at_100 value: 64.512 - type: recall_at_1000 value: 85.27900000000001 - type: recall_at_3 value: 20.868000000000002 - type: recall_at_5 value: 26.933 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 90.35795713634292 - type: f1 value: 89.72064544336776 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 66.4546283629731 - type: f1 value: 49.487271168215095 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 67.58238063214527 - type: f1 value: 65.54281371907213 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 73.47343644922664 - type: f1 value: 72.80522894672785 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 32.53600917473176 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 28.04699774280647 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 30.984352865575797 - type: mrr value: 32.02736001972659 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 4.666 - type: map_at_10 value: 10.066 - type: map_at_100 value: 12.794 - type: map_at_1000 value: 14.184 - type: map_at_3 value: 7.622 - type: map_at_5 value: 8.587 - type: mrr_at_1 value: 39.318999999999996 - type: mrr_at_10 value: 47.678 - type: mrr_at_100 value: 48.355 - type: mrr_at_1000 value: 48.400999999999996 - type: mrr_at_3 value: 45.82 - type: mrr_at_5 value: 46.656 - type: ndcg_at_1 value: 37.926 - type: ndcg_at_10 value: 29.049999999999997 - type: ndcg_at_100 value: 26.826 - type: ndcg_at_1000 value: 35.841 - type: ndcg_at_3 value: 33.513 - type: ndcg_at_5 value: 31.227 - type: precision_at_1 value: 39.318999999999996 - type: precision_at_10 value: 21.424000000000003 - type: precision_at_100 value: 7.231999999999999 - type: precision_at_1000 value: 2.012 - type: precision_at_3 value: 30.857 - type: precision_at_5 value: 26.378 - type: recall_at_1 value: 4.666 - type: recall_at_10 value: 13.898 - type: recall_at_100 value: 26.983 - type: recall_at_1000 value: 59.485 - type: recall_at_3 value: 8.953 - type: recall_at_5 value: 10.496 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 9.26 - type: map_at_10 value: 17.907999999999998 - type: map_at_100 value: 19.245 - type: map_at_1000 value: 19.339000000000002 - type: map_at_3 value: 14.634 - type: map_at_5 value: 16.386 - type: mrr_at_1 value: 10.574 - type: mrr_at_10 value: 19.438 - type: mrr_at_100 value: 20.638 - type: mrr_at_1000 value: 20.715 - type: mrr_at_3 value: 16.276 - type: mrr_at_5 value: 17.971999999999998 - type: ndcg_at_1 value: 10.574 - type: ndcg_at_10 value: 23.451 - type: ndcg_at_100 value: 29.982 - type: ndcg_at_1000 value: 32.449 - type: ndcg_at_3 value: 16.817 - type: ndcg_at_5 value: 19.867 - type: precision_at_1 value: 10.574 - type: precision_at_10 value: 4.609 - type: precision_at_100 value: 0.8330000000000001 - type: precision_at_1000 value: 0.107 - type: precision_at_3 value: 8.266 - type: precision_at_5 value: 6.6739999999999995 - type: recall_at_1 value: 9.26 - type: recall_at_10 value: 39.224 - type: recall_at_100 value: 69.107 - type: recall_at_1000 value: 87.908 - type: recall_at_3 value: 21.490000000000002 - type: recall_at_5 value: 28.560999999999996 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 65.655 - type: map_at_10 value: 79.199 - type: map_at_100 value: 79.937 - type: map_at_1000 value: 79.964 - type: map_at_3 value: 76.19399999999999 - type: map_at_5 value: 78.08800000000001 - type: mrr_at_1 value: 75.53999999999999 - type: mrr_at_10 value: 82.89 - type: mrr_at_100 value: 83.074 - type: mrr_at_1000 value: 83.077 - type: mrr_at_3 value: 81.577 - type: mrr_at_5 value: 82.452 - type: ndcg_at_1 value: 75.53999999999999 - type: ndcg_at_10 value: 83.62899999999999 - type: ndcg_at_100 value: 85.411 - type: ndcg_at_1000 value: 85.646 - type: ndcg_at_3 value: 80.23700000000001 - type: ndcg_at_5 value: 82.107 - type: precision_at_1 value: 75.53999999999999 - type: precision_at_10 value: 12.695 - type: precision_at_100 value: 1.493 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 34.983 - type: precision_at_5 value: 23.164 - type: recall_at_1 value: 65.655 - type: recall_at_10 value: 92.269 - type: recall_at_100 value: 98.598 - type: recall_at_1000 value: 99.815 - type: recall_at_3 value: 82.616 - type: recall_at_5 value: 87.75800000000001 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 43.67844919460687 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 54.32866004447611 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 3.238 - type: map_at_10 value: 8.539 - type: map_at_100 value: 10.267 - type: map_at_1000 value: 10.552999999999999 - type: map_at_3 value: 6.165 - type: map_at_5 value: 7.22 - type: mrr_at_1 value: 15.9 - type: mrr_at_10 value: 25.557999999999996 - type: mrr_at_100 value: 26.867 - type: mrr_at_1000 value: 26.939 - type: mrr_at_3 value: 22.633 - type: mrr_at_5 value: 24.233 - type: ndcg_at_1 value: 15.9 - type: ndcg_at_10 value: 14.954 - type: ndcg_at_100 value: 22.486 - type: ndcg_at_1000 value: 27.986 - type: ndcg_at_3 value: 14.069 - type: ndcg_at_5 value: 12.200999999999999 - type: precision_at_1 value: 15.9 - type: precision_at_10 value: 7.9399999999999995 - type: precision_at_100 value: 1.8929999999999998 - type: precision_at_1000 value: 0.32299999999999995 - type: precision_at_3 value: 13.5 - type: precision_at_5 value: 10.9 - type: recall_at_1 value: 3.238 - type: recall_at_10 value: 16.1 - type: recall_at_100 value: 38.427 - type: recall_at_1000 value: 65.498 - type: recall_at_3 value: 8.212 - type: recall_at_5 value: 11.032 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 80.7612029200118 - type: cos_sim_spearman value: 74.17706899450974 - type: euclidean_pearson value: 78.6240925347838 - type: euclidean_spearman value: 74.22104652352341 - type: manhattan_pearson value: 78.49956480878576 - type: manhattan_spearman value: 74.0528957569391 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 80.0377294417705 - type: cos_sim_spearman value: 72.19570903733732 - type: euclidean_pearson value: 77.060604990743 - type: euclidean_spearman value: 71.54251658956483 - type: manhattan_pearson value: 77.28301977645965 - type: manhattan_spearman value: 71.77449045278667 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 79.69841558517969 - type: cos_sim_spearman value: 80.54022353649157 - type: euclidean_pearson value: 80.03651743688496 - type: euclidean_spearman value: 80.45116824930123 - type: manhattan_pearson value: 79.89688370680031 - type: manhattan_spearman value: 80.27208259746283 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 79.92235427443056 - type: cos_sim_spearman value: 76.20243980748161 - type: euclidean_pearson value: 79.28031963400572 - type: euclidean_spearman value: 76.3568261868673 - type: manhattan_pearson value: 79.24527845959733 - type: manhattan_spearman value: 76.39886696744185 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 84.2762365324788 - type: cos_sim_spearman value: 85.19929628214842 - type: euclidean_pearson value: 84.82568872953075 - type: euclidean_spearman value: 85.11039387706913 - type: manhattan_pearson value: 84.72922084197847 - type: manhattan_spearman value: 85.04448532444505 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 80.23256564746382 - type: cos_sim_spearman value: 81.92968415429543 - type: euclidean_pearson value: 81.12612888308936 - type: euclidean_spearman value: 81.97396557448675 - type: manhattan_pearson value: 81.15685601512081 - type: manhattan_spearman value: 82.01929408689 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-en) config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 85.35057935029289 - type: cos_sim_spearman value: 86.60658025867397 - type: euclidean_pearson value: 86.48666975508912 - type: euclidean_spearman value: 86.70310223264862 - type: manhattan_pearson value: 86.23959282751626 - type: manhattan_spearman value: 86.48318896577922 - 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: 63.15375299804011 - type: cos_sim_spearman value: 65.4588500819246 - type: euclidean_pearson value: 65.60180021985416 - type: euclidean_spearman value: 65.55596512146833 - type: manhattan_pearson value: 66.12421335157649 - type: manhattan_spearman value: 66.05163838991123 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 81.82391915730462 - type: cos_sim_spearman value: 81.93942545767499 - type: euclidean_pearson value: 83.16752744889406 - type: euclidean_spearman value: 82.31380947581034 - type: manhattan_pearson value: 82.98915741609575 - type: manhattan_spearman value: 82.16585239338073 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 77.19504204180527 - type: mrr value: 92.85429983959396 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 49.528 - type: map_at_10 value: 57.62199999999999 - type: map_at_100 value: 58.544 - type: map_at_1000 value: 58.573 - type: map_at_3 value: 54.56999999999999 - type: map_at_5 value: 56.552 - type: mrr_at_1 value: 52.0 - type: mrr_at_10 value: 58.939 - type: mrr_at_100 value: 59.653 - type: mrr_at_1000 value: 59.68 - type: mrr_at_3 value: 56.389 - type: mrr_at_5 value: 57.989000000000004 - type: ndcg_at_1 value: 52.0 - type: ndcg_at_10 value: 61.964 - type: ndcg_at_100 value: 65.871 - type: ndcg_at_1000 value: 66.724 - type: ndcg_at_3 value: 56.621 - type: ndcg_at_5 value: 59.551 - type: precision_at_1 value: 52.0 - type: precision_at_10 value: 8.333 - type: precision_at_100 value: 1.04 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 21.778 - type: precision_at_5 value: 14.933 - type: recall_at_1 value: 49.528 - type: recall_at_10 value: 74.2 - type: recall_at_100 value: 91.5 - type: recall_at_1000 value: 98.333 - type: recall_at_3 value: 60.06700000000001 - type: recall_at_5 value: 67.133 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.81287128712871 - type: cos_sim_ap value: 95.15039468118793 - type: cos_sim_f1 value: 90.48817312531455 - type: cos_sim_precision value: 91.08409321175279 - type: cos_sim_recall value: 89.9 - type: dot_accuracy value: 99.78019801980199 - type: dot_ap value: 93.60256835857994 - type: dot_f1 value: 88.73096446700508 - type: dot_precision value: 90.10309278350516 - type: dot_recall value: 87.4 - type: euclidean_accuracy value: 99.81188118811882 - type: euclidean_ap value: 95.15954231276913 - type: euclidean_f1 value: 90.48096192384769 - type: euclidean_precision value: 90.66265060240963 - type: euclidean_recall value: 90.3 - type: manhattan_accuracy value: 99.81188118811882 - type: manhattan_ap value: 95.17107000565468 - type: manhattan_f1 value: 90.5 - type: manhattan_precision value: 90.5 - type: manhattan_recall value: 90.5 - type: max_accuracy value: 99.81287128712871 - type: max_ap value: 95.17107000565468 - type: max_f1 value: 90.5 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 51.77488276525734 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 33.30657214418171 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 47.84571922992432 - type: mrr value: 48.549107142857146 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 29.840750357585556 - type: cos_sim_spearman value: 29.832953864936567 - type: dot_pearson value: 30.499687946740657 - type: dot_spearman value: 30.73436062481656 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.16999999999999998 - type: map_at_10 value: 1.014 - type: map_at_100 value: 5.623 - type: map_at_1000 value: 15.190999999999999 - type: map_at_3 value: 0.377 - type: map_at_5 value: 0.577 - type: mrr_at_1 value: 68.0 - type: mrr_at_10 value: 74.45 - type: mrr_at_100 value: 74.846 - type: mrr_at_1000 value: 74.846 - type: mrr_at_3 value: 71.333 - type: mrr_at_5 value: 73.533 - type: ndcg_at_1 value: 64.0 - type: ndcg_at_10 value: 47.52 - type: ndcg_at_100 value: 37.419999999999995 - type: ndcg_at_1000 value: 36.318 - type: ndcg_at_3 value: 51.13999999999999 - type: ndcg_at_5 value: 49.101 - type: precision_at_1 value: 68.0 - type: precision_at_10 value: 50.8 - type: precision_at_100 value: 39.160000000000004 - type: precision_at_1000 value: 16.948 - type: precision_at_3 value: 52.0 - type: precision_at_5 value: 51.6 - type: recall_at_1 value: 0.16999999999999998 - type: recall_at_10 value: 1.269 - type: recall_at_100 value: 8.937000000000001 - type: recall_at_1000 value: 35.036 - type: recall_at_3 value: 0.396 - type: recall_at_5 value: 0.6669999999999999 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.672 - type: map_at_10 value: 6.739000000000001 - type: map_at_100 value: 12.006 - type: map_at_1000 value: 13.474 - type: map_at_3 value: 2.617 - type: map_at_5 value: 4.329000000000001 - type: mrr_at_1 value: 20.408 - type: mrr_at_10 value: 30.764000000000003 - type: mrr_at_100 value: 32.457 - type: mrr_at_1000 value: 32.481 - type: mrr_at_3 value: 26.531 - type: mrr_at_5 value: 28.877999999999997 - type: ndcg_at_1 value: 18.367 - type: ndcg_at_10 value: 17.471999999999998 - type: ndcg_at_100 value: 29.341 - type: ndcg_at_1000 value: 41.005 - type: ndcg_at_3 value: 14.64 - type: ndcg_at_5 value: 17.039 - type: precision_at_1 value: 20.408 - type: precision_at_10 value: 17.551 - type: precision_at_100 value: 6.673 - type: precision_at_1000 value: 1.4160000000000001 - type: precision_at_3 value: 14.966 - type: precision_at_5 value: 18.776 - type: recall_at_1 value: 1.672 - type: recall_at_10 value: 12.795000000000002 - type: recall_at_100 value: 41.289 - type: recall_at_1000 value: 76.947 - type: recall_at_3 value: 3.334 - type: recall_at_5 value: 6.864000000000001 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 69.3424 - type: ap value: 13.45149708639965 - type: f1 value: 53.278180518373574 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 57.60045274476513 - type: f1 value: 57.9395926195531 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 36.649067825169446 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 83.68599868868093 - type: cos_sim_ap value: 65.7938550603812 - type: cos_sim_f1 value: 61.81946735800141 - type: cos_sim_precision value: 55.85604770017035 - type: cos_sim_recall value: 69.2084432717678 - type: dot_accuracy value: 82.09453418370389 - type: dot_ap value: 61.00867337905922 - type: dot_f1 value: 58.56196783349101 - type: dot_precision value: 53.06472353193313 - type: dot_recall value: 65.32981530343008 - type: euclidean_accuracy value: 83.68599868868093 - type: euclidean_ap value: 66.17065796133883 - type: euclidean_f1 value: 62.440610152538135 - type: euclidean_precision value: 59.3393536121673 - type: euclidean_recall value: 65.88390501319262 - type: manhattan_accuracy value: 83.57870894677237 - type: manhattan_ap value: 65.89925640001532 - type: manhattan_f1 value: 62.2255119664446 - type: manhattan_precision value: 58.43373493975904 - type: manhattan_recall value: 66.54353562005278 - type: max_accuracy value: 83.68599868868093 - type: max_ap value: 66.17065796133883 - type: max_f1 value: 62.440610152538135 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 87.68579966623976 - type: cos_sim_ap value: 83.2666595805096 - type: cos_sim_f1 value: 75.11536297129996 - type: cos_sim_precision value: 73.24943294065999 - type: cos_sim_recall value: 77.07884200800738 - type: dot_accuracy value: 86.76213761788334 - type: dot_ap value: 80.85199640255004 - type: dot_f1 value: 73.27634898520165 - type: dot_precision value: 71.70756872282409 - type: dot_recall value: 74.91530643671081 - type: euclidean_accuracy value: 87.79640625606395 - type: euclidean_ap value: 83.52666327503474 - type: euclidean_f1 value: 75.37022886875523 - type: euclidean_precision value: 71.4522249051397 - type: euclidean_recall value: 79.74283954419464 - type: manhattan_accuracy value: 87.80804905499282 - type: manhattan_ap value: 83.4995899990913 - type: manhattan_f1 value: 75.44320420223242 - type: manhattan_precision value: 71.68307223069458 - type: manhattan_recall value: 79.6196489066831 - type: max_accuracy value: 87.80804905499282 - type: max_ap value: 83.52666327503474 - type: max_f1 value: 75.44320420223242 ---