--- tags: - mteb model-index: - name: bert_1b3_mixlang_newstep3 results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 70.11940298507463 - type: ap value: 32.37756187516329 - type: f1 value: 63.92312669545795 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 92.950675 - type: ap value: 89.69186819088316 - type: f1 value: 92.94108521905532 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 50.522 - type: f1 value: 48.76020527037862 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 14.865 - type: map_at_10 value: 26.026 - type: map_at_100 value: 27.586 - type: map_at_1000 value: 27.622999999999998 - type: map_at_3 value: 21.859 - type: map_at_5 value: 24.049 - type: mrr_at_1 value: 15.504999999999999 - type: mrr_at_10 value: 26.265 - type: mrr_at_100 value: 27.810000000000002 - type: mrr_at_1000 value: 27.847 - type: mrr_at_3 value: 22.06 - type: mrr_at_5 value: 24.247 - type: ndcg_at_1 value: 14.865 - type: ndcg_at_10 value: 32.934999999999995 - type: ndcg_at_100 value: 40.627 - type: ndcg_at_1000 value: 41.524 - type: ndcg_at_3 value: 24.153 - type: ndcg_at_5 value: 28.133999999999997 - type: precision_at_1 value: 14.865 - type: precision_at_10 value: 5.541 - type: precision_at_100 value: 0.9159999999999999 - type: precision_at_1000 value: 0.099 - type: precision_at_3 value: 10.266 - type: precision_at_5 value: 8.108 - type: recall_at_1 value: 14.865 - type: recall_at_10 value: 55.405 - type: recall_at_100 value: 91.607 - type: recall_at_1000 value: 98.506 - type: recall_at_3 value: 30.797 - type: recall_at_5 value: 40.541 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 47.028296913559814 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 38.38123118365735 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 58.9616553564134 - type: mrr value: 72.16033504814668 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 87.00899493452621 - type: cos_sim_spearman value: 83.85673000958819 - type: euclidean_pearson value: 85.65567511199598 - type: euclidean_spearman value: 83.90311660870698 - type: manhattan_pearson value: 85.37147829428248 - type: manhattan_spearman value: 83.74588411039522 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 75.5909090909091 - type: f1 value: 74.476632049175 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 38.981180962194216 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 34.9394829907367 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 31.277 - type: map_at_10 value: 42.153 - type: map_at_100 value: 43.683 - type: map_at_1000 value: 43.817 - type: map_at_3 value: 38.454 - type: map_at_5 value: 40.721000000000004 - type: mrr_at_1 value: 38.913 - type: mrr_at_10 value: 48.232 - type: mrr_at_100 value: 48.888 - type: mrr_at_1000 value: 48.929 - type: mrr_at_3 value: 45.279 - type: mrr_at_5 value: 47.089 - type: ndcg_at_1 value: 38.913 - type: ndcg_at_10 value: 48.518 - type: ndcg_at_100 value: 53.797 - type: ndcg_at_1000 value: 55.754999999999995 - type: ndcg_at_3 value: 43.122 - type: ndcg_at_5 value: 45.869 - type: precision_at_1 value: 38.913 - type: precision_at_10 value: 9.413 - type: precision_at_100 value: 1.567 - type: precision_at_1000 value: 0.20600000000000002 - type: precision_at_3 value: 20.791999999999998 - type: precision_at_5 value: 15.193000000000001 - type: recall_at_1 value: 31.277 - type: recall_at_10 value: 60.475 - type: recall_at_100 value: 82.675 - type: recall_at_1000 value: 95.298 - type: recall_at_3 value: 44.388 - type: recall_at_5 value: 52.242999999999995 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 25.593 - type: map_at_10 value: 35.089999999999996 - type: map_at_100 value: 36.269 - type: map_at_1000 value: 36.419000000000004 - type: map_at_3 value: 32.449 - type: map_at_5 value: 33.952 - type: mrr_at_1 value: 32.484 - type: mrr_at_10 value: 40.725 - type: mrr_at_100 value: 41.465999999999994 - type: mrr_at_1000 value: 41.521 - type: mrr_at_3 value: 38.757999999999996 - type: mrr_at_5 value: 39.869 - type: ndcg_at_1 value: 32.484 - type: ndcg_at_10 value: 40.384 - type: ndcg_at_100 value: 44.984 - type: ndcg_at_1000 value: 47.528 - type: ndcg_at_3 value: 36.77 - type: ndcg_at_5 value: 38.505 - type: precision_at_1 value: 32.484 - type: precision_at_10 value: 7.866 - type: precision_at_100 value: 1.2959999999999998 - type: precision_at_1000 value: 0.185 - type: precision_at_3 value: 18.195 - type: precision_at_5 value: 13.032 - type: recall_at_1 value: 25.593 - type: recall_at_10 value: 49.289 - type: recall_at_100 value: 69.84700000000001 - type: recall_at_1000 value: 86.329 - type: recall_at_3 value: 38.51 - type: recall_at_5 value: 43.349 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 35.116 - type: map_at_10 value: 45.908 - type: map_at_100 value: 46.979 - type: map_at_1000 value: 47.046 - type: map_at_3 value: 42.724000000000004 - type: map_at_5 value: 44.507999999999996 - type: mrr_at_1 value: 40.313 - type: mrr_at_10 value: 49.195 - type: mrr_at_100 value: 49.996 - type: mrr_at_1000 value: 50.03300000000001 - type: mrr_at_3 value: 46.708 - type: mrr_at_5 value: 48.187999999999995 - type: ndcg_at_1 value: 40.313 - type: ndcg_at_10 value: 51.43600000000001 - type: ndcg_at_100 value: 55.873 - type: ndcg_at_1000 value: 57.288 - type: ndcg_at_3 value: 46.038000000000004 - type: ndcg_at_5 value: 48.729 - type: precision_at_1 value: 40.313 - type: precision_at_10 value: 8.382000000000001 - type: precision_at_100 value: 1.145 - type: precision_at_1000 value: 0.132 - type: precision_at_3 value: 20.480999999999998 - type: precision_at_5 value: 14.219000000000001 - type: recall_at_1 value: 35.116 - type: recall_at_10 value: 64.524 - type: recall_at_100 value: 83.859 - type: recall_at_1000 value: 93.977 - type: recall_at_3 value: 50.102999999999994 - type: recall_at_5 value: 56.818000000000005 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.488 - type: map_at_10 value: 25.667 - type: map_at_100 value: 26.541999999999998 - type: map_at_1000 value: 26.637 - type: map_at_3 value: 23.483 - type: map_at_5 value: 24.667 - type: mrr_at_1 value: 20.0 - type: mrr_at_10 value: 27.178 - type: mrr_at_100 value: 27.989000000000004 - type: mrr_at_1000 value: 28.07 - type: mrr_at_3 value: 25.122 - type: mrr_at_5 value: 26.275 - type: ndcg_at_1 value: 20.0 - type: ndcg_at_10 value: 29.736 - type: ndcg_at_100 value: 34.358 - type: ndcg_at_1000 value: 37.036 - type: ndcg_at_3 value: 25.405 - type: ndcg_at_5 value: 27.441 - type: precision_at_1 value: 20.0 - type: precision_at_10 value: 4.712000000000001 - type: precision_at_100 value: 0.751 - type: precision_at_1000 value: 0.101 - type: precision_at_3 value: 10.885 - type: precision_at_5 value: 7.706 - type: recall_at_1 value: 18.488 - type: recall_at_10 value: 40.83 - type: recall_at_100 value: 62.707 - type: recall_at_1000 value: 83.41199999999999 - type: recall_at_3 value: 29.21 - type: recall_at_5 value: 34.009 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 9.532 - type: map_at_10 value: 15.193000000000001 - type: map_at_100 value: 16.381 - type: map_at_1000 value: 16.524 - type: map_at_3 value: 13.386000000000001 - type: map_at_5 value: 14.261 - type: mrr_at_1 value: 11.940000000000001 - type: mrr_at_10 value: 18.285 - type: mrr_at_100 value: 19.373 - type: mrr_at_1000 value: 19.467000000000002 - type: mrr_at_3 value: 16.252 - type: mrr_at_5 value: 17.26 - type: ndcg_at_1 value: 11.940000000000001 - type: ndcg_at_10 value: 19.095000000000002 - type: ndcg_at_100 value: 25.214 - type: ndcg_at_1000 value: 28.619 - type: ndcg_at_3 value: 15.482000000000001 - type: ndcg_at_5 value: 16.892 - type: precision_at_1 value: 11.940000000000001 - type: precision_at_10 value: 3.744 - type: precision_at_100 value: 0.815 - type: precision_at_1000 value: 0.124 - type: precision_at_3 value: 7.710999999999999 - type: precision_at_5 value: 5.647 - type: recall_at_1 value: 9.532 - type: recall_at_10 value: 28.026 - type: recall_at_100 value: 55.253 - type: recall_at_1000 value: 79.86999999999999 - type: recall_at_3 value: 18.084 - type: recall_at_5 value: 21.553 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 23.416 - type: map_at_10 value: 32.649 - type: map_at_100 value: 33.983000000000004 - type: map_at_1000 value: 34.107 - type: map_at_3 value: 29.254 - type: map_at_5 value: 31.339 - type: mrr_at_1 value: 28.778 - type: mrr_at_10 value: 37.513999999999996 - type: mrr_at_100 value: 38.458999999999996 - type: mrr_at_1000 value: 38.517 - type: mrr_at_3 value: 34.585 - type: mrr_at_5 value: 36.514 - type: ndcg_at_1 value: 28.778 - type: ndcg_at_10 value: 38.233 - type: ndcg_at_100 value: 44.14 - type: ndcg_at_1000 value: 46.583000000000006 - type: ndcg_at_3 value: 32.718 - type: ndcg_at_5 value: 35.778999999999996 - type: precision_at_1 value: 28.778 - type: precision_at_10 value: 7.2090000000000005 - type: precision_at_100 value: 1.194 - type: precision_at_1000 value: 0.16 - type: precision_at_3 value: 15.495999999999999 - type: precision_at_5 value: 11.781 - type: recall_at_1 value: 23.416 - type: recall_at_10 value: 50.063 - type: recall_at_100 value: 75.4 - type: recall_at_1000 value: 91.74799999999999 - type: recall_at_3 value: 35.113 - type: recall_at_5 value: 42.620999999999995 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.891 - type: map_at_10 value: 28.000000000000004 - type: map_at_100 value: 29.354999999999997 - type: map_at_1000 value: 29.453000000000003 - type: map_at_3 value: 24.551000000000002 - type: map_at_5 value: 26.383000000000003 - type: mrr_at_1 value: 23.402 - type: mrr_at_10 value: 32.308 - type: mrr_at_100 value: 33.242 - type: mrr_at_1000 value: 33.294000000000004 - type: mrr_at_3 value: 29.262 - type: mrr_at_5 value: 30.997000000000003 - type: ndcg_at_1 value: 23.402 - type: ndcg_at_10 value: 33.932 - type: ndcg_at_100 value: 39.925 - type: ndcg_at_1000 value: 42.126999999999995 - type: ndcg_at_3 value: 27.816999999999997 - type: ndcg_at_5 value: 30.554 - type: precision_at_1 value: 23.402 - type: precision_at_10 value: 6.747 - type: precision_at_100 value: 1.147 - type: precision_at_1000 value: 0.15 - type: precision_at_3 value: 13.469999999999999 - type: precision_at_5 value: 10.32 - type: recall_at_1 value: 18.891 - type: recall_at_10 value: 47.58 - type: recall_at_100 value: 73.668 - type: recall_at_1000 value: 88.77000000000001 - type: recall_at_3 value: 30.726 - type: recall_at_5 value: 37.547000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 20.303499999999996 - type: map_at_10 value: 28.263499999999997 - type: map_at_100 value: 29.431250000000002 - type: map_at_1000 value: 29.555166666666665 - type: map_at_3 value: 25.59133333333333 - type: map_at_5 value: 27.091500000000003 - type: mrr_at_1 value: 24.19725 - type: mrr_at_10 value: 31.803750000000004 - type: mrr_at_100 value: 32.691916666666664 - type: mrr_at_1000 value: 32.760083333333334 - type: mrr_at_3 value: 29.447749999999996 - type: mrr_at_5 value: 30.79858333333334 - type: ndcg_at_1 value: 24.19725 - type: ndcg_at_10 value: 33.11925000000001 - type: ndcg_at_100 value: 38.384916666666655 - type: ndcg_at_1000 value: 40.991499999999995 - type: ndcg_at_3 value: 28.5115 - type: ndcg_at_5 value: 30.718833333333333 - type: precision_at_1 value: 24.19725 - type: precision_at_10 value: 6.061666666666666 - type: precision_at_100 value: 1.0404166666666665 - type: precision_at_1000 value: 0.14583333333333337 - type: precision_at_3 value: 13.347083333333334 - type: precision_at_5 value: 9.747916666666667 - type: recall_at_1 value: 20.303499999999996 - type: recall_at_10 value: 43.93183333333334 - type: recall_at_100 value: 67.47800000000001 - type: recall_at_1000 value: 85.91425000000001 - type: recall_at_3 value: 31.160083333333333 - type: recall_at_5 value: 36.76633333333333 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 12.666 - type: map_at_10 value: 18.448999999999998 - type: map_at_100 value: 19.448 - type: map_at_1000 value: 19.54 - type: map_at_3 value: 16.581000000000003 - type: map_at_5 value: 17.485999999999997 - type: mrr_at_1 value: 14.11 - type: mrr_at_10 value: 19.796 - type: mrr_at_100 value: 20.785999999999998 - type: mrr_at_1000 value: 20.861 - type: mrr_at_3 value: 18.175 - type: mrr_at_5 value: 18.926000000000002 - type: ndcg_at_1 value: 14.11 - type: ndcg_at_10 value: 21.83 - type: ndcg_at_100 value: 27.017999999999997 - type: ndcg_at_1000 value: 29.520999999999997 - type: ndcg_at_3 value: 18.358 - type: ndcg_at_5 value: 19.719 - type: precision_at_1 value: 14.11 - type: precision_at_10 value: 3.819 - type: precision_at_100 value: 0.701 - type: precision_at_1000 value: 0.097 - type: precision_at_3 value: 8.384 - type: precision_at_5 value: 5.92 - type: recall_at_1 value: 12.666 - type: recall_at_10 value: 30.746000000000002 - type: recall_at_100 value: 54.675 - type: recall_at_1000 value: 73.57900000000001 - type: recall_at_3 value: 21.196 - type: recall_at_5 value: 24.552 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 12.53 - type: map_at_10 value: 17.881 - type: map_at_100 value: 18.923000000000002 - type: map_at_1000 value: 19.049 - type: map_at_3 value: 16.088 - type: map_at_5 value: 17.0 - type: mrr_at_1 value: 15.244 - type: mrr_at_10 value: 20.906 - type: mrr_at_100 value: 21.83 - type: mrr_at_1000 value: 21.913 - type: mrr_at_3 value: 19.104 - type: mrr_at_5 value: 19.994999999999997 - type: ndcg_at_1 value: 15.244 - type: ndcg_at_10 value: 21.541 - type: ndcg_at_100 value: 26.799 - type: ndcg_at_1000 value: 29.927 - type: ndcg_at_3 value: 18.208 - type: ndcg_at_5 value: 19.573999999999998 - type: precision_at_1 value: 15.244 - type: precision_at_10 value: 4.04 - type: precision_at_100 value: 0.808 - type: precision_at_1000 value: 0.125 - type: precision_at_3 value: 8.672 - type: precision_at_5 value: 6.283999999999999 - type: recall_at_1 value: 12.53 - type: recall_at_10 value: 29.601 - type: recall_at_100 value: 53.615 - type: recall_at_1000 value: 76.344 - type: recall_at_3 value: 20.159 - type: recall_at_5 value: 23.746000000000002 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.849 - type: map_at_10 value: 28.937 - type: map_at_100 value: 30.003999999999998 - type: map_at_1000 value: 30.122 - type: map_at_3 value: 26.150000000000002 - type: map_at_5 value: 27.744000000000003 - type: mrr_at_1 value: 25.093 - type: mrr_at_10 value: 32.143 - type: mrr_at_100 value: 33.053 - type: mrr_at_1000 value: 33.134 - type: mrr_at_3 value: 29.586000000000002 - type: mrr_at_5 value: 31.116 - type: ndcg_at_1 value: 25.093 - type: ndcg_at_10 value: 33.631 - type: ndcg_at_100 value: 38.893 - type: ndcg_at_1000 value: 41.692 - type: ndcg_at_3 value: 28.497 - type: ndcg_at_5 value: 31.028 - type: precision_at_1 value: 25.093 - type: precision_at_10 value: 5.765 - type: precision_at_100 value: 0.947 - type: precision_at_1000 value: 0.13 - type: precision_at_3 value: 12.623999999999999 - type: precision_at_5 value: 9.347 - type: recall_at_1 value: 21.849 - type: recall_at_10 value: 44.767 - type: recall_at_100 value: 68.298 - type: recall_at_1000 value: 88.107 - type: recall_at_3 value: 30.968 - type: recall_at_5 value: 37.19 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.409 - type: map_at_10 value: 27.750999999999998 - type: map_at_100 value: 29.241 - type: map_at_1000 value: 29.467 - type: map_at_3 value: 24.29 - type: map_at_5 value: 26.448 - type: mrr_at_1 value: 22.53 - type: mrr_at_10 value: 31.887999999999998 - type: mrr_at_100 value: 32.89 - type: mrr_at_1000 value: 32.956 - type: mrr_at_3 value: 28.854000000000003 - type: mrr_at_5 value: 30.751 - type: ndcg_at_1 value: 22.53 - type: ndcg_at_10 value: 33.827 - type: ndcg_at_100 value: 39.749 - type: ndcg_at_1000 value: 42.677 - type: ndcg_at_3 value: 28.101 - type: ndcg_at_5 value: 31.380999999999997 - type: precision_at_1 value: 22.53 - type: precision_at_10 value: 6.976 - type: precision_at_100 value: 1.443 - type: precision_at_1000 value: 0.23700000000000002 - type: precision_at_3 value: 13.966000000000001 - type: precision_at_5 value: 10.909 - type: recall_at_1 value: 18.409 - type: recall_at_10 value: 46.217000000000006 - type: recall_at_100 value: 72.882 - type: recall_at_1000 value: 91.625 - type: recall_at_3 value: 30.64 - type: recall_at_5 value: 38.948 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 15.875 - type: map_at_10 value: 21.484 - type: map_at_100 value: 22.367 - type: map_at_1000 value: 22.481 - type: map_at_3 value: 19.686 - type: map_at_5 value: 20.589 - type: mrr_at_1 value: 17.560000000000002 - type: mrr_at_10 value: 23.474999999999998 - type: mrr_at_100 value: 24.331 - type: mrr_at_1000 value: 24.426000000000002 - type: mrr_at_3 value: 21.688 - type: mrr_at_5 value: 22.603 - type: ndcg_at_1 value: 17.560000000000002 - type: ndcg_at_10 value: 25.268 - type: ndcg_at_100 value: 29.869 - type: ndcg_at_1000 value: 33.145 - type: ndcg_at_3 value: 21.622 - type: ndcg_at_5 value: 23.155 - type: precision_at_1 value: 17.560000000000002 - type: precision_at_10 value: 4.067 - type: precision_at_100 value: 0.6709999999999999 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 9.489 - type: precision_at_5 value: 6.617000000000001 - type: recall_at_1 value: 15.875 - type: recall_at_10 value: 35.064 - type: recall_at_100 value: 56.857 - type: recall_at_1000 value: 81.91199999999999 - type: recall_at_3 value: 24.823999999999998 - type: recall_at_5 value: 28.62 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 10.637 - type: map_at_10 value: 18.401999999999997 - type: map_at_100 value: 20.121 - type: map_at_1000 value: 20.305999999999997 - type: map_at_3 value: 15.348 - type: map_at_5 value: 16.841 - type: mrr_at_1 value: 23.909 - type: mrr_at_10 value: 34.512 - type: mrr_at_100 value: 35.485 - type: mrr_at_1000 value: 35.528999999999996 - type: mrr_at_3 value: 31.368000000000002 - type: mrr_at_5 value: 33.137 - type: ndcg_at_1 value: 23.909 - type: ndcg_at_10 value: 25.94 - type: ndcg_at_100 value: 33.116 - type: ndcg_at_1000 value: 36.502 - type: ndcg_at_3 value: 21.046 - type: ndcg_at_5 value: 22.715 - type: precision_at_1 value: 23.909 - type: precision_at_10 value: 8.195 - type: precision_at_100 value: 1.593 - type: precision_at_1000 value: 0.22200000000000003 - type: precision_at_3 value: 15.744 - type: precision_at_5 value: 12.142999999999999 - type: recall_at_1 value: 10.637 - type: recall_at_10 value: 31.251 - type: recall_at_100 value: 56.477999999999994 - type: recall_at_1000 value: 75.52600000000001 - type: recall_at_3 value: 19.482 - type: recall_at_5 value: 24.145 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 7.786999999999999 - type: map_at_10 value: 16.182 - type: map_at_100 value: 22.698 - type: map_at_1000 value: 24.192 - type: map_at_3 value: 11.84 - type: map_at_5 value: 13.602 - type: mrr_at_1 value: 56.99999999999999 - type: mrr_at_10 value: 66.702 - type: mrr_at_100 value: 67.291 - type: mrr_at_1000 value: 67.301 - type: mrr_at_3 value: 64.708 - type: mrr_at_5 value: 65.946 - type: ndcg_at_1 value: 46.75 - type: ndcg_at_10 value: 35.469 - type: ndcg_at_100 value: 40.077 - type: ndcg_at_1000 value: 47.252 - type: ndcg_at_3 value: 39.096 - type: ndcg_at_5 value: 36.766 - type: precision_at_1 value: 56.99999999999999 - type: precision_at_10 value: 28.175 - type: precision_at_100 value: 9.423 - type: precision_at_1000 value: 2.017 - type: precision_at_3 value: 41.667 - type: precision_at_5 value: 35.199999999999996 - type: recall_at_1 value: 7.786999999999999 - type: recall_at_10 value: 21.428 - type: recall_at_100 value: 45.86 - type: recall_at_1000 value: 68.83 - type: recall_at_3 value: 12.992 - type: recall_at_5 value: 16.091 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 45.985 - type: f1 value: 39.52034839578244 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 39.141999999999996 - type: map_at_10 value: 50.255 - type: map_at_100 value: 50.938 - type: map_at_1000 value: 50.975 - type: map_at_3 value: 47.4 - type: map_at_5 value: 49.172 - type: mrr_at_1 value: 41.794 - type: mrr_at_10 value: 53.198 - type: mrr_at_100 value: 53.82900000000001 - type: mrr_at_1000 value: 53.857 - type: mrr_at_3 value: 50.32 - type: mrr_at_5 value: 52.105999999999995 - type: ndcg_at_1 value: 41.794 - type: ndcg_at_10 value: 56.411 - type: ndcg_at_100 value: 59.663 - type: ndcg_at_1000 value: 60.590999999999994 - type: ndcg_at_3 value: 50.73 - type: ndcg_at_5 value: 53.823 - type: precision_at_1 value: 41.794 - type: precision_at_10 value: 7.9159999999999995 - type: precision_at_100 value: 0.968 - type: precision_at_1000 value: 0.106 - type: precision_at_3 value: 20.627000000000002 - type: precision_at_5 value: 14.038 - type: recall_at_1 value: 39.141999999999996 - type: recall_at_10 value: 72.695 - type: recall_at_100 value: 87.44800000000001 - type: recall_at_1000 value: 94.313 - type: recall_at_3 value: 57.415000000000006 - type: recall_at_5 value: 64.851 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 18.715 - type: map_at_10 value: 30.253999999999998 - type: map_at_100 value: 32.123000000000005 - type: map_at_1000 value: 32.303 - type: map_at_3 value: 26.203 - type: map_at_5 value: 28.585 - type: mrr_at_1 value: 36.42 - type: mrr_at_10 value: 45.456 - type: mrr_at_100 value: 46.314 - type: mrr_at_1000 value: 46.356 - type: mrr_at_3 value: 42.798 - type: mrr_at_5 value: 44.365 - type: ndcg_at_1 value: 36.42 - type: ndcg_at_10 value: 37.747 - type: ndcg_at_100 value: 44.714999999999996 - type: ndcg_at_1000 value: 47.866 - type: ndcg_at_3 value: 34.166999999999994 - type: ndcg_at_5 value: 35.54 - type: precision_at_1 value: 36.42 - type: precision_at_10 value: 10.602 - type: precision_at_100 value: 1.773 - type: precision_at_1000 value: 0.234 - type: precision_at_3 value: 22.84 - type: precision_at_5 value: 17.315 - type: recall_at_1 value: 18.715 - type: recall_at_10 value: 44.199 - type: recall_at_100 value: 70.097 - type: recall_at_1000 value: 89.13600000000001 - type: recall_at_3 value: 30.543 - type: recall_at_5 value: 36.705 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 30.608 - type: map_at_10 value: 45.829 - type: map_at_100 value: 46.786 - type: map_at_1000 value: 46.869 - type: map_at_3 value: 42.834 - type: map_at_5 value: 44.566 - type: mrr_at_1 value: 61.214999999999996 - type: mrr_at_10 value: 69.072 - type: mrr_at_100 value: 69.492 - type: mrr_at_1000 value: 69.512 - type: mrr_at_3 value: 67.553 - type: mrr_at_5 value: 68.446 - type: ndcg_at_1 value: 61.214999999999996 - type: ndcg_at_10 value: 54.66 - type: ndcg_at_100 value: 58.342000000000006 - type: ndcg_at_1000 value: 60.101000000000006 - type: ndcg_at_3 value: 49.932 - type: ndcg_at_5 value: 52.342999999999996 - type: precision_at_1 value: 61.214999999999996 - type: precision_at_10 value: 11.65 - type: precision_at_100 value: 1.4529999999999998 - type: precision_at_1000 value: 0.169 - type: precision_at_3 value: 31.78 - type: precision_at_5 value: 20.979999999999997 - type: recall_at_1 value: 30.608 - type: recall_at_10 value: 58.251 - type: recall_at_100 value: 72.667 - type: recall_at_1000 value: 84.396 - type: recall_at_3 value: 47.67 - type: recall_at_5 value: 52.451 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 90.21999999999998 - type: ap value: 85.88889163834975 - type: f1 value: 90.20542534971861 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 19.785 - type: map_at_10 value: 31.596000000000004 - type: map_at_100 value: 32.849000000000004 - type: map_at_1000 value: 32.903999999999996 - type: map_at_3 value: 27.772000000000002 - type: map_at_5 value: 29.952 - type: mrr_at_1 value: 20.344 - type: mrr_at_10 value: 32.146 - type: mrr_at_100 value: 33.349000000000004 - type: mrr_at_1000 value: 33.396 - type: mrr_at_3 value: 28.403 - type: mrr_at_5 value: 30.542 - type: ndcg_at_1 value: 20.358 - type: ndcg_at_10 value: 38.288 - type: ndcg_at_100 value: 44.383 - type: ndcg_at_1000 value: 45.714 - type: ndcg_at_3 value: 30.525999999999996 - type: ndcg_at_5 value: 34.393 - type: precision_at_1 value: 20.358 - type: precision_at_10 value: 6.16 - type: precision_at_100 value: 0.9209999999999999 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 13.08 - type: precision_at_5 value: 9.799 - type: recall_at_1 value: 19.785 - type: recall_at_10 value: 58.916000000000004 - type: recall_at_100 value: 87.24 - type: recall_at_1000 value: 97.37599999999999 - type: recall_at_3 value: 37.872 - type: recall_at_5 value: 47.116 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 88.63429092567262 - type: f1 value: 88.58612904162257 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 58.080255357957135 - type: f1 value: 39.561402859935 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 65.03026227303296 - type: f1 value: 61.10334739098155 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 71.05245460659046 - type: f1 value: 69.96280851244295 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 33.9762359299763 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 31.670044418802444 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 29.32330726926572 - type: mrr value: 30.16727607430052 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 4.552 - type: map_at_10 value: 10.692 - type: map_at_100 value: 13.835 - type: map_at_1000 value: 15.305 - type: map_at_3 value: 7.5009999999999994 - type: map_at_5 value: 8.988 - type: mrr_at_1 value: 39.318999999999996 - type: mrr_at_10 value: 48.809000000000005 - type: mrr_at_100 value: 49.382 - type: mrr_at_1000 value: 49.442 - type: mrr_at_3 value: 46.078 - type: mrr_at_5 value: 48.091 - type: ndcg_at_1 value: 37.152 - type: ndcg_at_10 value: 30.159000000000002 - type: ndcg_at_100 value: 28.371000000000002 - type: ndcg_at_1000 value: 37.632 - type: ndcg_at_3 value: 34.662 - type: ndcg_at_5 value: 32.814 - type: precision_at_1 value: 38.7 - type: precision_at_10 value: 23.034 - type: precision_at_100 value: 7.588 - type: precision_at_1000 value: 2.0709999999999997 - type: precision_at_3 value: 33.024 - type: precision_at_5 value: 29.164 - type: recall_at_1 value: 4.552 - type: recall_at_10 value: 14.827000000000002 - type: recall_at_100 value: 29.256 - type: recall_at_1000 value: 61.739 - type: recall_at_3 value: 8.38 - type: recall_at_5 value: 11.123 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 25.424999999999997 - type: map_at_10 value: 39.972 - type: map_at_100 value: 41.163 - type: map_at_1000 value: 41.202 - type: map_at_3 value: 35.546 - type: map_at_5 value: 38.146 - type: mrr_at_1 value: 28.794999999999998 - type: mrr_at_10 value: 42.315999999999995 - type: mrr_at_100 value: 43.253 - type: mrr_at_1000 value: 43.282 - type: mrr_at_3 value: 38.649 - type: mrr_at_5 value: 40.858 - type: ndcg_at_1 value: 28.766000000000002 - type: ndcg_at_10 value: 47.614000000000004 - type: ndcg_at_100 value: 52.676 - type: ndcg_at_1000 value: 53.574 - type: ndcg_at_3 value: 39.292 - type: ndcg_at_5 value: 43.633 - type: precision_at_1 value: 28.766000000000002 - type: precision_at_10 value: 8.201 - type: precision_at_100 value: 1.099 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 18.201999999999998 - type: precision_at_5 value: 13.447000000000001 - type: recall_at_1 value: 25.424999999999997 - type: recall_at_10 value: 68.586 - type: recall_at_100 value: 90.556 - type: recall_at_1000 value: 97.197 - type: recall_at_3 value: 47.033 - type: recall_at_5 value: 57.044 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 70.054 - type: map_at_10 value: 83.991 - type: map_at_100 value: 84.63000000000001 - type: map_at_1000 value: 84.648 - type: map_at_3 value: 80.982 - type: map_at_5 value: 82.857 - type: mrr_at_1 value: 80.76 - type: mrr_at_10 value: 87.079 - type: mrr_at_100 value: 87.185 - type: mrr_at_1000 value: 87.18599999999999 - type: mrr_at_3 value: 86.03 - type: mrr_at_5 value: 86.771 - type: ndcg_at_1 value: 80.75 - type: ndcg_at_10 value: 87.85300000000001 - type: ndcg_at_100 value: 89.105 - type: ndcg_at_1000 value: 89.213 - type: ndcg_at_3 value: 84.87400000000001 - type: ndcg_at_5 value: 86.51299999999999 - type: precision_at_1 value: 80.75 - type: precision_at_10 value: 13.352 - type: precision_at_100 value: 1.528 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 37.113 - type: precision_at_5 value: 24.424 - type: recall_at_1 value: 70.054 - type: recall_at_10 value: 95.209 - type: recall_at_100 value: 99.497 - type: recall_at_1000 value: 99.973 - type: recall_at_3 value: 86.654 - type: recall_at_5 value: 91.313 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 42.71909082787674 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 56.92567540870805 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 2.225 - type: map_at_10 value: 5.785 - type: map_at_100 value: 7.6240000000000006 - type: map_at_1000 value: 8.094999999999999 - type: map_at_3 value: 3.882 - type: map_at_5 value: 4.715 - type: mrr_at_1 value: 11.0 - type: mrr_at_10 value: 18.049 - type: mrr_at_100 value: 19.475 - type: mrr_at_1000 value: 19.599 - type: mrr_at_3 value: 15.082999999999998 - type: mrr_at_5 value: 16.583000000000002 - type: ndcg_at_1 value: 11.0 - type: ndcg_at_10 value: 10.59 - type: ndcg_at_100 value: 18.68 - type: ndcg_at_1000 value: 27.327 - type: ndcg_at_3 value: 8.932 - type: ndcg_at_5 value: 8.126 - type: precision_at_1 value: 11.0 - type: precision_at_10 value: 5.89 - type: precision_at_100 value: 1.778 - type: precision_at_1000 value: 0.385 - type: precision_at_3 value: 8.333 - type: precision_at_5 value: 7.3 - type: recall_at_1 value: 2.225 - type: recall_at_10 value: 11.948 - type: recall_at_100 value: 36.097 - type: recall_at_1000 value: 78.145 - type: recall_at_3 value: 5.078 - type: recall_at_5 value: 7.4079999999999995 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 83.87898494199837 - type: cos_sim_spearman value: 79.3815141247343 - type: euclidean_pearson value: 80.984944764735 - type: euclidean_spearman value: 79.37984688714191 - type: manhattan_pearson value: 80.96139326762788 - type: manhattan_spearman value: 79.34882764221987 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 82.94123934276303 - type: cos_sim_spearman value: 73.64821774752144 - type: euclidean_pearson value: 79.09149672589201 - type: euclidean_spearman value: 73.64174833442063 - type: manhattan_pearson value: 79.05135129686983 - type: manhattan_spearman value: 73.57858840270084 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 71.37047316191514 - type: cos_sim_spearman value: 75.56797051373606 - type: euclidean_pearson value: 74.59038333631109 - type: euclidean_spearman value: 75.55966023907652 - type: manhattan_pearson value: 74.56600039917967 - type: manhattan_spearman value: 75.52139454559969 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 71.75410054949431 - type: cos_sim_spearman value: 72.09826786050286 - type: euclidean_pearson value: 72.30015801748517 - type: euclidean_spearman value: 72.09347126863909 - type: manhattan_pearson value: 72.2692656804079 - type: manhattan_spearman value: 72.07403601010577 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 83.09663528706463 - type: cos_sim_spearman value: 85.6296813586495 - type: euclidean_pearson value: 84.14347920777777 - type: euclidean_spearman value: 85.62948425849926 - type: manhattan_pearson value: 84.08840896634038 - type: manhattan_spearman value: 85.56264430897471 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 78.55984417539631 - type: cos_sim_spearman value: 82.06700938579174 - type: euclidean_pearson value: 80.92277218507344 - type: euclidean_spearman value: 82.06297899287695 - type: manhattan_pearson value: 80.89292734584946 - type: manhattan_spearman value: 82.01121177547141 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-en) config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 88.70738419575085 - type: cos_sim_spearman value: 88.99910283221313 - type: euclidean_pearson value: 88.91458218447116 - type: euclidean_spearman value: 88.97188755639708 - type: manhattan_pearson value: 88.93397958768632 - type: manhattan_spearman value: 89.0514960821245 - 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: 65.30101408630514 - type: cos_sim_spearman value: 66.15672143838582 - type: euclidean_pearson value: 66.61257552376895 - type: euclidean_spearman value: 66.00319920690566 - type: manhattan_pearson value: 66.81435622246758 - type: manhattan_spearman value: 66.35221377631379 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 81.94191078286725 - type: cos_sim_spearman value: 83.69085688689903 - type: euclidean_pearson value: 83.28942607749994 - type: euclidean_spearman value: 83.69370814043747 - type: manhattan_pearson value: 83.3553242227074 - type: manhattan_spearman value: 83.74306572840383 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 88.02503921524934 - type: mrr value: 96.47891777793738 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 51.24999999999999 - type: map_at_10 value: 61.472 - type: map_at_100 value: 62.132 - type: map_at_1000 value: 62.161 - type: map_at_3 value: 58.18299999999999 - type: map_at_5 value: 60.246 - type: mrr_at_1 value: 54.0 - type: mrr_at_10 value: 62.395 - type: mrr_at_100 value: 62.936 - type: mrr_at_1000 value: 62.965 - type: mrr_at_3 value: 59.833000000000006 - type: mrr_at_5 value: 61.5 - type: ndcg_at_1 value: 54.0 - type: ndcg_at_10 value: 66.235 - type: ndcg_at_100 value: 69.279 - type: ndcg_at_1000 value: 70.044 - type: ndcg_at_3 value: 60.679 - type: ndcg_at_5 value: 63.80200000000001 - type: precision_at_1 value: 54.0 - type: precision_at_10 value: 9.167 - type: precision_at_100 value: 1.0699999999999998 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 24.111 - type: precision_at_5 value: 16.333000000000002 - type: recall_at_1 value: 51.24999999999999 - type: recall_at_10 value: 79.833 - type: recall_at_100 value: 94.0 - type: recall_at_1000 value: 100.0 - type: recall_at_3 value: 65.267 - type: recall_at_5 value: 72.956 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.62673267326733 - type: cos_sim_ap value: 87.07482534376774 - type: cos_sim_f1 value: 80.63687724704674 - type: cos_sim_precision value: 82.89334741288279 - type: cos_sim_recall value: 78.5 - type: dot_accuracy value: 99.63564356435643 - type: dot_ap value: 86.98432756163903 - type: dot_f1 value: 80.91286307053943 - type: dot_precision value: 84.05172413793103 - type: dot_recall value: 78.0 - type: euclidean_accuracy value: 99.62673267326733 - type: euclidean_ap value: 87.0756316041764 - type: euclidean_f1 value: 80.53553038105046 - type: euclidean_precision value: 83.01486199575372 - type: euclidean_recall value: 78.2 - type: manhattan_accuracy value: 99.62574257425743 - type: manhattan_ap value: 87.05953308523233 - type: manhattan_f1 value: 80.50632911392405 - type: manhattan_precision value: 81.53846153846153 - type: manhattan_recall value: 79.5 - type: max_accuracy value: 99.63564356435643 - type: max_ap value: 87.0756316041764 - type: max_f1 value: 80.91286307053943 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 53.59692640735744 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 32.86771187657918 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 45.705711066037644 - type: mrr value: 46.25163133435192 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.066382997227624 - type: cos_sim_spearman value: 31.00934876843689 - type: dot_pearson value: 30.419206995727873 - type: dot_spearman value: 31.046571150093747 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.173 - type: map_at_10 value: 1.154 - type: map_at_100 value: 5.8180000000000005 - type: map_at_1000 value: 14.892 - type: map_at_3 value: 0.415 - type: map_at_5 value: 0.641 - type: mrr_at_1 value: 68.0 - type: mrr_at_10 value: 76.869 - type: mrr_at_100 value: 77.264 - type: mrr_at_1000 value: 77.264 - type: mrr_at_3 value: 75.333 - type: mrr_at_5 value: 76.333 - type: ndcg_at_1 value: 62.0 - type: ndcg_at_10 value: 50.81 - type: ndcg_at_100 value: 37.659 - type: ndcg_at_1000 value: 37.444 - type: ndcg_at_3 value: 55.11200000000001 - type: ndcg_at_5 value: 51.858000000000004 - type: precision_at_1 value: 68.0 - type: precision_at_10 value: 54.800000000000004 - type: precision_at_100 value: 38.36 - type: precision_at_1000 value: 16.88 - type: precision_at_3 value: 57.99999999999999 - type: precision_at_5 value: 54.800000000000004 - type: recall_at_1 value: 0.173 - type: recall_at_10 value: 1.435 - type: recall_at_100 value: 9.259 - type: recall_at_1000 value: 36.033 - type: recall_at_3 value: 0.447 - type: recall_at_5 value: 0.74 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.228 - type: map_at_10 value: 4.633 - type: map_at_100 value: 9.171 - type: map_at_1000 value: 10.58 - type: map_at_3 value: 2.413 - type: map_at_5 value: 3.3640000000000003 - type: mrr_at_1 value: 16.326999999999998 - type: mrr_at_10 value: 27.071 - type: mrr_at_100 value: 28.454 - type: mrr_at_1000 value: 28.475 - type: mrr_at_3 value: 19.048000000000002 - type: mrr_at_5 value: 24.354 - type: ndcg_at_1 value: 14.285999999999998 - type: ndcg_at_10 value: 13.312 - type: ndcg_at_100 value: 25.587 - type: ndcg_at_1000 value: 37.879000000000005 - type: ndcg_at_3 value: 11.591 - type: ndcg_at_5 value: 12.536 - type: precision_at_1 value: 16.326999999999998 - type: precision_at_10 value: 13.264999999999999 - type: precision_at_100 value: 6.061 - type: precision_at_1000 value: 1.4040000000000001 - type: precision_at_3 value: 12.245000000000001 - type: precision_at_5 value: 13.877999999999998 - type: recall_at_1 value: 1.228 - type: recall_at_10 value: 9.759 - type: recall_at_100 value: 38.809 - type: recall_at_1000 value: 76.229 - type: recall_at_3 value: 2.738 - type: recall_at_5 value: 5.510000000000001 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 69.33179999999999 - type: ap value: 14.379598043710034 - type: f1 value: 53.89665138084001 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 58.245614035087726 - type: f1 value: 58.3152945231724 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 38.38161204174159 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 82.60118018716099 - type: cos_sim_ap value: 62.5064927795416 - type: cos_sim_f1 value: 59.50177935943061 - type: cos_sim_precision value: 54.05172413793103 - type: cos_sim_recall value: 66.17414248021109 - type: dot_accuracy value: 82.52369315133814 - type: dot_ap value: 62.36545569178682 - type: dot_f1 value: 59.5539204414808 - type: dot_precision value: 52.77098614506927 - type: dot_recall value: 68.33773087071239 - type: euclidean_accuracy value: 82.62502235202956 - type: euclidean_ap value: 62.51708062651598 - type: euclidean_f1 value: 59.48887837198297 - type: euclidean_precision value: 53.925353925353924 - type: euclidean_recall value: 66.33245382585751 - type: manhattan_accuracy value: 82.57733802229242 - type: manhattan_ap value: 62.4034159268756 - type: manhattan_f1 value: 59.42896615242921 - type: manhattan_precision value: 52.716503267973856 - type: manhattan_recall value: 68.10026385224275 - type: max_accuracy value: 82.62502235202956 - type: max_ap value: 62.51708062651598 - type: max_f1 value: 59.5539204414808 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 86.74079248651377 - type: cos_sim_ap value: 81.11128912769627 - type: cos_sim_f1 value: 73.39903296054331 - type: cos_sim_precision value: 70.49273307337823 - type: cos_sim_recall value: 76.55528179858331 - type: dot_accuracy value: 86.71362595567975 - type: dot_ap value: 81.07587927324371 - type: dot_f1 value: 73.36112443280334 - type: dot_precision value: 70.42283447836249 - type: dot_recall value: 76.55528179858331 - type: euclidean_accuracy value: 86.73109015407304 - type: euclidean_ap value: 81.11249921439843 - type: euclidean_f1 value: 73.39903296054331 - type: euclidean_precision value: 70.49273307337823 - type: euclidean_recall value: 76.55528179858331 - type: manhattan_accuracy value: 86.7252687546086 - type: manhattan_ap value: 81.05990290681223 - type: manhattan_f1 value: 73.29173525245952 - type: manhattan_precision value: 72.88161400837457 - type: manhattan_recall value: 73.70649830612874 - type: max_accuracy value: 86.74079248651377 - type: max_ap value: 81.11249921439843 - type: max_f1 value: 73.39903296054331 ---