--- tags: - mteb model-index: - name: ALL_862873 results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 50.805970149253746 - type: ap value: 21.350961103104364 - type: f1 value: 46.546166439875044 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 52.567125000000004 - type: ap value: 51.37893936391345 - type: f1 value: 51.8411977908125 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 22.63 - type: f1 value: 21.964526516204575 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 1.991 - type: map_at_10 value: 4.095 - type: map_at_100 value: 4.763 - type: map_at_1000 value: 4.8759999999999994 - type: map_at_3 value: 3.3070000000000004 - type: map_at_5 value: 3.73 - type: mrr_at_1 value: 2.0629999999999997 - type: mrr_at_10 value: 4.119 - type: mrr_at_100 value: 4.787 - type: mrr_at_1000 value: 4.9 - type: mrr_at_3 value: 3.331 - type: mrr_at_5 value: 3.768 - type: ndcg_at_1 value: 1.991 - type: ndcg_at_10 value: 5.346 - type: ndcg_at_100 value: 9.181000000000001 - type: ndcg_at_1000 value: 13.004 - type: ndcg_at_3 value: 3.7199999999999998 - type: ndcg_at_5 value: 4.482 - type: precision_at_1 value: 1.991 - type: precision_at_10 value: 0.9390000000000001 - type: precision_at_100 value: 0.28700000000000003 - type: precision_at_1000 value: 0.061 - type: precision_at_3 value: 1.636 - type: precision_at_5 value: 1.351 - type: recall_at_1 value: 1.991 - type: recall_at_10 value: 9.388 - type: recall_at_100 value: 28.663 - type: recall_at_1000 value: 60.597 - type: recall_at_3 value: 4.9079999999999995 - type: recall_at_5 value: 6.757000000000001 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 14.790995349964428 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 12.248406292959412 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 44.88116875696166 - type: mrr value: 56.07439651760981 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 19.26573437410263 - type: cos_sim_spearman value: 21.34145013484056 - type: euclidean_pearson value: 22.39226418475093 - type: euclidean_spearman value: 23.511981519581447 - type: manhattan_pearson value: 22.14346931904813 - type: manhattan_spearman value: 23.39390654000631 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 36.42857142857143 - type: f1 value: 34.81640976406094 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 13.94296328377691 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 9.790764523161606 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 0.968 - type: map_at_10 value: 2.106 - type: map_at_100 value: 2.411 - type: map_at_1000 value: 2.4899999999999998 - type: map_at_3 value: 1.797 - type: map_at_5 value: 1.9959999999999998 - type: mrr_at_1 value: 1.717 - type: mrr_at_10 value: 3.0349999999999997 - type: mrr_at_100 value: 3.4029999999999996 - type: mrr_at_1000 value: 3.486 - type: mrr_at_3 value: 2.6470000000000002 - type: mrr_at_5 value: 2.876 - type: ndcg_at_1 value: 1.717 - type: ndcg_at_10 value: 2.9059999999999997 - type: ndcg_at_100 value: 4.715 - type: ndcg_at_1000 value: 7.318 - type: ndcg_at_3 value: 2.415 - type: ndcg_at_5 value: 2.682 - type: precision_at_1 value: 1.717 - type: precision_at_10 value: 0.658 - type: precision_at_100 value: 0.197 - type: precision_at_1000 value: 0.054 - type: precision_at_3 value: 1.431 - type: precision_at_5 value: 1.059 - type: recall_at_1 value: 0.968 - type: recall_at_10 value: 4.531000000000001 - type: recall_at_100 value: 13.081000000000001 - type: recall_at_1000 value: 32.443 - type: recall_at_3 value: 2.8850000000000002 - type: recall_at_5 value: 3.768 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 0.9390000000000001 - type: map_at_10 value: 1.516 - type: map_at_100 value: 1.6680000000000001 - type: map_at_1000 value: 1.701 - type: map_at_3 value: 1.314 - type: map_at_5 value: 1.388 - type: mrr_at_1 value: 1.146 - type: mrr_at_10 value: 1.96 - type: mrr_at_100 value: 2.166 - type: mrr_at_1000 value: 2.207 - type: mrr_at_3 value: 1.72 - type: mrr_at_5 value: 1.796 - type: ndcg_at_1 value: 1.146 - type: ndcg_at_10 value: 1.9769999999999999 - type: ndcg_at_100 value: 2.8400000000000003 - type: ndcg_at_1000 value: 4.035 - type: ndcg_at_3 value: 1.5859999999999999 - type: ndcg_at_5 value: 1.6709999999999998 - type: precision_at_1 value: 1.146 - type: precision_at_10 value: 0.43299999999999994 - type: precision_at_100 value: 0.11100000000000002 - type: precision_at_1000 value: 0.027999999999999997 - type: precision_at_3 value: 0.8699999999999999 - type: precision_at_5 value: 0.611 - type: recall_at_1 value: 0.9390000000000001 - type: recall_at_10 value: 2.949 - type: recall_at_100 value: 6.737 - type: recall_at_1000 value: 15.604999999999999 - type: recall_at_3 value: 1.846 - type: recall_at_5 value: 2.08 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 1.28 - type: map_at_10 value: 2.157 - type: map_at_100 value: 2.401 - type: map_at_1000 value: 2.4570000000000003 - type: map_at_3 value: 1.865 - type: map_at_5 value: 1.928 - type: mrr_at_1 value: 1.505 - type: mrr_at_10 value: 2.52 - type: mrr_at_100 value: 2.782 - type: mrr_at_1000 value: 2.8400000000000003 - type: mrr_at_3 value: 2.1839999999999997 - type: mrr_at_5 value: 2.2689999999999997 - type: ndcg_at_1 value: 1.505 - type: ndcg_at_10 value: 2.798 - type: ndcg_at_100 value: 4.2090000000000005 - type: ndcg_at_1000 value: 6.105 - type: ndcg_at_3 value: 2.157 - type: ndcg_at_5 value: 2.258 - type: precision_at_1 value: 1.505 - type: precision_at_10 value: 0.5519999999999999 - type: precision_at_100 value: 0.146 - type: precision_at_1000 value: 0.034999999999999996 - type: precision_at_3 value: 1.024 - type: precision_at_5 value: 0.7020000000000001 - type: recall_at_1 value: 1.28 - type: recall_at_10 value: 4.455 - type: recall_at_100 value: 11.169 - type: recall_at_1000 value: 26.046000000000003 - type: recall_at_3 value: 2.6270000000000002 - type: recall_at_5 value: 2.899 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 0.264 - type: map_at_10 value: 0.615 - type: map_at_100 value: 0.76 - type: map_at_1000 value: 0.803 - type: map_at_3 value: 0.40499999999999997 - type: map_at_5 value: 0.512 - type: mrr_at_1 value: 0.33899999999999997 - type: mrr_at_10 value: 0.718 - type: mrr_at_100 value: 0.8880000000000001 - type: mrr_at_1000 value: 0.935 - type: mrr_at_3 value: 0.508 - type: mrr_at_5 value: 0.616 - type: ndcg_at_1 value: 0.33899999999999997 - type: ndcg_at_10 value: 0.9079999999999999 - type: ndcg_at_100 value: 1.9029999999999998 - type: ndcg_at_1000 value: 3.4939999999999998 - type: ndcg_at_3 value: 0.46499999999999997 - type: ndcg_at_5 value: 0.655 - type: precision_at_1 value: 0.33899999999999997 - type: precision_at_10 value: 0.192 - type: precision_at_100 value: 0.079 - type: precision_at_1000 value: 0.023 - type: precision_at_3 value: 0.22599999999999998 - type: precision_at_5 value: 0.22599999999999998 - type: recall_at_1 value: 0.264 - type: recall_at_10 value: 1.789 - type: recall_at_100 value: 6.927 - type: recall_at_1000 value: 19.922 - type: recall_at_3 value: 0.5459999999999999 - type: recall_at_5 value: 0.9979999999999999 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 0.5599999999999999 - type: map_at_10 value: 0.9129999999999999 - type: map_at_100 value: 1.027 - type: map_at_1000 value: 1.072 - type: map_at_3 value: 0.715 - type: map_at_5 value: 0.826 - type: mrr_at_1 value: 0.8710000000000001 - type: mrr_at_10 value: 1.331 - type: mrr_at_100 value: 1.494 - type: mrr_at_1000 value: 1.547 - type: mrr_at_3 value: 1.119 - type: mrr_at_5 value: 1.269 - type: ndcg_at_1 value: 0.8710000000000001 - type: ndcg_at_10 value: 1.2590000000000001 - type: ndcg_at_100 value: 2.023 - type: ndcg_at_1000 value: 3.737 - type: ndcg_at_3 value: 0.8750000000000001 - type: ndcg_at_5 value: 1.079 - type: precision_at_1 value: 0.8710000000000001 - type: precision_at_10 value: 0.28600000000000003 - type: precision_at_100 value: 0.086 - type: precision_at_1000 value: 0.027999999999999997 - type: precision_at_3 value: 0.498 - type: precision_at_5 value: 0.42300000000000004 - type: recall_at_1 value: 0.5599999999999999 - type: recall_at_10 value: 1.907 - type: recall_at_100 value: 5.492 - type: recall_at_1000 value: 18.974 - type: recall_at_3 value: 0.943 - type: recall_at_5 value: 1.41 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 1.9720000000000002 - type: map_at_10 value: 2.968 - type: map_at_100 value: 3.2009999999999996 - type: map_at_1000 value: 3.2680000000000002 - type: map_at_3 value: 2.683 - type: map_at_5 value: 2.8369999999999997 - type: mrr_at_1 value: 2.406 - type: mrr_at_10 value: 3.567 - type: mrr_at_100 value: 3.884 - type: mrr_at_1000 value: 3.948 - type: mrr_at_3 value: 3.2239999999999998 - type: mrr_at_5 value: 3.383 - type: ndcg_at_1 value: 2.406 - type: ndcg_at_10 value: 3.63 - type: ndcg_at_100 value: 5.155 - type: ndcg_at_1000 value: 7.381 - type: ndcg_at_3 value: 3.078 - type: ndcg_at_5 value: 3.3070000000000004 - type: precision_at_1 value: 2.406 - type: precision_at_10 value: 0.635 - type: precision_at_100 value: 0.184 - type: precision_at_1000 value: 0.048 - type: precision_at_3 value: 1.4120000000000001 - type: precision_at_5 value: 1.001 - type: recall_at_1 value: 1.9720000000000002 - type: recall_at_10 value: 5.152 - type: recall_at_100 value: 12.173 - type: recall_at_1000 value: 28.811999999999998 - type: recall_at_3 value: 3.556 - type: recall_at_5 value: 4.181 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 0.346 - type: map_at_10 value: 0.619 - type: map_at_100 value: 0.743 - type: map_at_1000 value: 0.788 - type: map_at_3 value: 0.5369999999999999 - type: map_at_5 value: 0.551 - type: mrr_at_1 value: 0.571 - type: mrr_at_10 value: 1.0619999999999998 - type: mrr_at_100 value: 1.2109999999999999 - type: mrr_at_1000 value: 1.265 - type: mrr_at_3 value: 0.818 - type: mrr_at_5 value: 0.927 - type: ndcg_at_1 value: 0.571 - type: ndcg_at_10 value: 0.919 - type: ndcg_at_100 value: 1.688 - type: ndcg_at_1000 value: 3.3649999999999998 - type: ndcg_at_3 value: 0.6779999999999999 - type: ndcg_at_5 value: 0.7230000000000001 - type: precision_at_1 value: 0.571 - type: precision_at_10 value: 0.27399999999999997 - type: precision_at_100 value: 0.084 - type: precision_at_1000 value: 0.029 - type: precision_at_3 value: 0.381 - type: precision_at_5 value: 0.32 - type: recall_at_1 value: 0.346 - type: recall_at_10 value: 1.397 - type: recall_at_100 value: 5.079000000000001 - type: recall_at_1000 value: 18.060000000000002 - type: recall_at_3 value: 0.774 - type: recall_at_5 value: 0.8340000000000001 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 0.69 - type: map_at_10 value: 0.897 - type: map_at_100 value: 1.0030000000000001 - type: map_at_1000 value: 1.034 - type: map_at_3 value: 0.818 - type: map_at_5 value: 0.864 - type: mrr_at_1 value: 0.767 - type: mrr_at_10 value: 1.008 - type: mrr_at_100 value: 1.145 - type: mrr_at_1000 value: 1.183 - type: mrr_at_3 value: 0.895 - type: mrr_at_5 value: 0.9560000000000001 - type: ndcg_at_1 value: 0.767 - type: ndcg_at_10 value: 1.0739999999999998 - type: ndcg_at_100 value: 1.757 - type: ndcg_at_1000 value: 2.9090000000000003 - type: ndcg_at_3 value: 0.881 - type: ndcg_at_5 value: 0.9769999999999999 - type: precision_at_1 value: 0.767 - type: precision_at_10 value: 0.184 - type: precision_at_100 value: 0.06 - type: precision_at_1000 value: 0.018000000000000002 - type: precision_at_3 value: 0.358 - type: precision_at_5 value: 0.27599999999999997 - type: recall_at_1 value: 0.69 - type: recall_at_10 value: 1.508 - type: recall_at_100 value: 4.858 - type: recall_at_1000 value: 14.007 - type: recall_at_3 value: 0.997 - type: recall_at_5 value: 1.2269999999999999 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 0.338 - type: map_at_10 value: 0.661 - type: map_at_100 value: 0.7969999999999999 - type: map_at_1000 value: 0.8290000000000001 - type: map_at_3 value: 0.5559999999999999 - type: map_at_5 value: 0.5910000000000001 - type: mrr_at_1 value: 0.482 - type: mrr_at_10 value: 0.88 - type: mrr_at_100 value: 1.036 - type: mrr_at_1000 value: 1.075 - type: mrr_at_3 value: 0.74 - type: mrr_at_5 value: 0.779 - type: ndcg_at_1 value: 0.482 - type: ndcg_at_10 value: 0.924 - type: ndcg_at_100 value: 1.736 - type: ndcg_at_1000 value: 2.926 - type: ndcg_at_3 value: 0.677 - type: ndcg_at_5 value: 0.732 - type: precision_at_1 value: 0.482 - type: precision_at_10 value: 0.20600000000000002 - type: precision_at_100 value: 0.078 - type: precision_at_1000 value: 0.023 - type: precision_at_3 value: 0.367 - type: precision_at_5 value: 0.255 - type: recall_at_1 value: 0.338 - type: recall_at_10 value: 1.545 - type: recall_at_100 value: 5.38 - type: recall_at_1000 value: 14.609 - type: recall_at_3 value: 0.826 - type: recall_at_5 value: 0.975 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 0.8240000000000001 - type: map_at_10 value: 1.254 - type: map_at_100 value: 1.389 - type: map_at_1000 value: 1.419 - type: map_at_3 value: 1.158 - type: map_at_5 value: 1.189 - type: mrr_at_1 value: 0.9329999999999999 - type: mrr_at_10 value: 1.4200000000000002 - type: mrr_at_100 value: 1.59 - type: mrr_at_1000 value: 1.629 - type: mrr_at_3 value: 1.29 - type: mrr_at_5 value: 1.332 - type: ndcg_at_1 value: 0.9329999999999999 - type: ndcg_at_10 value: 1.53 - type: ndcg_at_100 value: 2.418 - type: ndcg_at_1000 value: 3.7310000000000003 - type: ndcg_at_3 value: 1.302 - type: ndcg_at_5 value: 1.363 - type: precision_at_1 value: 0.9329999999999999 - type: precision_at_10 value: 0.271 - type: precision_at_100 value: 0.083 - type: precision_at_1000 value: 0.024 - type: precision_at_3 value: 0.622 - type: precision_at_5 value: 0.41000000000000003 - type: recall_at_1 value: 0.8240000000000001 - type: recall_at_10 value: 2.1999999999999997 - type: recall_at_100 value: 6.584 - type: recall_at_1000 value: 17.068 - type: recall_at_3 value: 1.5859999999999999 - type: recall_at_5 value: 1.7260000000000002 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 0.404 - type: map_at_10 value: 0.788 - type: map_at_100 value: 0.9860000000000001 - type: map_at_1000 value: 1.04 - type: map_at_3 value: 0.676 - type: map_at_5 value: 0.733 - type: mrr_at_1 value: 0.5930000000000001 - type: mrr_at_10 value: 1.278 - type: mrr_at_100 value: 1.545 - type: mrr_at_1000 value: 1.599 - type: mrr_at_3 value: 1.054 - type: mrr_at_5 value: 1.192 - type: ndcg_at_1 value: 0.5930000000000001 - type: ndcg_at_10 value: 1.1280000000000001 - type: ndcg_at_100 value: 2.2689999999999997 - type: ndcg_at_1000 value: 4.274 - type: ndcg_at_3 value: 0.919 - type: ndcg_at_5 value: 1.038 - type: precision_at_1 value: 0.5930000000000001 - type: precision_at_10 value: 0.296 - type: precision_at_100 value: 0.152 - type: precision_at_1000 value: 0.05 - type: precision_at_3 value: 0.527 - type: precision_at_5 value: 0.47400000000000003 - type: recall_at_1 value: 0.404 - type: recall_at_10 value: 1.601 - type: recall_at_100 value: 6.885 - type: recall_at_1000 value: 22.356 - type: recall_at_3 value: 0.9490000000000001 - type: recall_at_5 value: 1.206 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 0.185 - type: map_at_10 value: 0.192 - type: map_at_100 value: 0.271 - type: map_at_1000 value: 0.307 - type: map_at_3 value: 0.185 - type: map_at_5 value: 0.185 - type: mrr_at_1 value: 0.185 - type: mrr_at_10 value: 0.20500000000000002 - type: mrr_at_100 value: 0.292 - type: mrr_at_1000 value: 0.331 - type: mrr_at_3 value: 0.185 - type: mrr_at_5 value: 0.185 - type: ndcg_at_1 value: 0.185 - type: ndcg_at_10 value: 0.211 - type: ndcg_at_100 value: 0.757 - type: ndcg_at_1000 value: 1.928 - type: ndcg_at_3 value: 0.185 - type: ndcg_at_5 value: 0.185 - type: precision_at_1 value: 0.185 - type: precision_at_10 value: 0.037 - type: precision_at_100 value: 0.039 - type: precision_at_1000 value: 0.015 - type: precision_at_3 value: 0.062 - type: precision_at_5 value: 0.037 - type: recall_at_1 value: 0.185 - type: recall_at_10 value: 0.246 - type: recall_at_100 value: 3.05 - type: recall_at_1000 value: 12.5 - type: recall_at_3 value: 0.185 - type: recall_at_5 value: 0.185 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 0.241 - type: map_at_10 value: 0.372 - type: map_at_100 value: 0.45999999999999996 - type: map_at_1000 value: 0.47600000000000003 - type: map_at_3 value: 0.33999999999999997 - type: map_at_5 value: 0.359 - type: mrr_at_1 value: 0.651 - type: mrr_at_10 value: 1.03 - type: mrr_at_100 value: 1.2489999999999999 - type: mrr_at_1000 value: 1.282 - type: mrr_at_3 value: 0.9450000000000001 - type: mrr_at_5 value: 1.0030000000000001 - type: ndcg_at_1 value: 0.651 - type: ndcg_at_10 value: 0.588 - type: ndcg_at_100 value: 1.2550000000000001 - type: ndcg_at_1000 value: 1.9040000000000001 - type: ndcg_at_3 value: 0.547 - type: ndcg_at_5 value: 0.549 - type: precision_at_1 value: 0.651 - type: precision_at_10 value: 0.182 - type: precision_at_100 value: 0.086 - type: precision_at_1000 value: 0.02 - type: precision_at_3 value: 0.434 - type: precision_at_5 value: 0.313 - type: recall_at_1 value: 0.241 - type: recall_at_10 value: 0.63 - type: recall_at_100 value: 3.1759999999999997 - type: recall_at_1000 value: 7.175 - type: recall_at_3 value: 0.46299999999999997 - type: recall_at_5 value: 0.543 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 0.04 - type: map_at_10 value: 0.089 - type: map_at_100 value: 0.133 - type: map_at_1000 value: 0.165 - type: map_at_3 value: 0.054 - type: map_at_5 value: 0.056999999999999995 - type: mrr_at_1 value: 0.75 - type: mrr_at_10 value: 1.4749999999999999 - type: mrr_at_100 value: 1.8010000000000002 - type: mrr_at_1000 value: 1.847 - type: mrr_at_3 value: 1.208 - type: mrr_at_5 value: 1.333 - type: ndcg_at_1 value: 0.625 - type: ndcg_at_10 value: 0.428 - type: ndcg_at_100 value: 0.705 - type: ndcg_at_1000 value: 1.564 - type: ndcg_at_3 value: 0.5369999999999999 - type: ndcg_at_5 value: 0.468 - type: precision_at_1 value: 0.75 - type: precision_at_10 value: 0.375 - type: precision_at_100 value: 0.27499999999999997 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 0.583 - type: precision_at_5 value: 0.5 - type: recall_at_1 value: 0.04 - type: recall_at_10 value: 0.385 - type: recall_at_100 value: 1.2670000000000001 - type: recall_at_1000 value: 4.522 - type: recall_at_3 value: 0.07100000000000001 - type: recall_at_5 value: 0.08099999999999999 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 22.749999999999996 - type: f1 value: 19.335020165482693 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 0.257 - type: map_at_10 value: 0.416 - type: map_at_100 value: 0.451 - type: map_at_1000 value: 0.46499999999999997 - type: map_at_3 value: 0.37 - type: map_at_5 value: 0.386 - type: mrr_at_1 value: 0.27 - type: mrr_at_10 value: 0.44200000000000006 - type: mrr_at_100 value: 0.48 - type: mrr_at_1000 value: 0.49500000000000005 - type: mrr_at_3 value: 0.38999999999999996 - type: mrr_at_5 value: 0.411 - type: ndcg_at_1 value: 0.27 - type: ndcg_at_10 value: 0.51 - type: ndcg_at_100 value: 0.738 - type: ndcg_at_1000 value: 1.2630000000000001 - type: ndcg_at_3 value: 0.41000000000000003 - type: ndcg_at_5 value: 0.439 - type: precision_at_1 value: 0.27 - type: precision_at_10 value: 0.084 - type: precision_at_100 value: 0.021 - type: precision_at_1000 value: 0.006999999999999999 - type: precision_at_3 value: 0.17500000000000002 - type: precision_at_5 value: 0.123 - type: recall_at_1 value: 0.257 - type: recall_at_10 value: 0.786 - type: recall_at_100 value: 1.959 - type: recall_at_1000 value: 6.334 - type: recall_at_3 value: 0.49699999999999994 - type: recall_at_5 value: 0.5680000000000001 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 0.28900000000000003 - type: map_at_10 value: 0.475 - type: map_at_100 value: 0.559 - type: map_at_1000 value: 0.5930000000000001 - type: map_at_3 value: 0.38999999999999996 - type: map_at_5 value: 0.41700000000000004 - type: mrr_at_1 value: 0.772 - type: mrr_at_10 value: 1.107 - type: mrr_at_100 value: 1.269 - type: mrr_at_1000 value: 1.323 - type: mrr_at_3 value: 0.9520000000000001 - type: mrr_at_5 value: 1.0290000000000001 - type: ndcg_at_1 value: 0.772 - type: ndcg_at_10 value: 0.755 - type: ndcg_at_100 value: 1.256 - type: ndcg_at_1000 value: 2.55 - type: ndcg_at_3 value: 0.633 - type: ndcg_at_5 value: 0.639 - type: precision_at_1 value: 0.772 - type: precision_at_10 value: 0.262 - type: precision_at_100 value: 0.082 - type: precision_at_1000 value: 0.03 - type: precision_at_3 value: 0.46299999999999997 - type: precision_at_5 value: 0.33999999999999997 - type: recall_at_1 value: 0.28900000000000003 - type: recall_at_10 value: 0.976 - type: recall_at_100 value: 2.802 - type: recall_at_1000 value: 11.466 - type: recall_at_3 value: 0.54 - type: recall_at_5 value: 0.6479999999999999 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 0.257 - type: map_at_10 value: 0.395 - type: map_at_100 value: 0.436 - type: map_at_1000 value: 0.447 - type: map_at_3 value: 0.347 - type: map_at_5 value: 0.369 - type: mrr_at_1 value: 0.513 - type: mrr_at_10 value: 0.787 - type: mrr_at_100 value: 0.865 - type: mrr_at_1000 value: 0.8840000000000001 - type: mrr_at_3 value: 0.6930000000000001 - type: mrr_at_5 value: 0.738 - type: ndcg_at_1 value: 0.513 - type: ndcg_at_10 value: 0.587 - type: ndcg_at_100 value: 0.881 - type: ndcg_at_1000 value: 1.336 - type: ndcg_at_3 value: 0.46299999999999997 - type: ndcg_at_5 value: 0.511 - type: precision_at_1 value: 0.513 - type: precision_at_10 value: 0.151 - type: precision_at_100 value: 0.04 - type: precision_at_1000 value: 0.01 - type: precision_at_3 value: 0.311 - type: precision_at_5 value: 0.22399999999999998 - type: recall_at_1 value: 0.257 - type: recall_at_10 value: 0.756 - type: recall_at_100 value: 1.9849999999999999 - type: recall_at_1000 value: 5.111000000000001 - type: recall_at_3 value: 0.466 - type: recall_at_5 value: 0.5599999999999999 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 50.76400000000001 - type: ap value: 50.41569411130455 - type: f1 value: 50.14266303576945 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 0.14300000000000002 - type: map_at_10 value: 0.23700000000000002 - type: map_at_100 value: 0.27799999999999997 - type: map_at_1000 value: 0.291 - type: map_at_3 value: 0.197 - type: map_at_5 value: 0.215 - type: mrr_at_1 value: 0.14300000000000002 - type: mrr_at_10 value: 0.247 - type: mrr_at_100 value: 0.29 - type: mrr_at_1000 value: 0.303 - type: mrr_at_3 value: 0.201 - type: mrr_at_5 value: 0.219 - type: ndcg_at_1 value: 0.14300000000000002 - type: ndcg_at_10 value: 0.307 - type: ndcg_at_100 value: 0.5720000000000001 - type: ndcg_at_1000 value: 1.053 - type: ndcg_at_3 value: 0.215 - type: ndcg_at_5 value: 0.248 - type: precision_at_1 value: 0.14300000000000002 - type: precision_at_10 value: 0.056999999999999995 - type: precision_at_100 value: 0.02 - type: precision_at_1000 value: 0.006 - type: precision_at_3 value: 0.091 - type: precision_at_5 value: 0.07200000000000001 - type: recall_at_1 value: 0.14300000000000002 - type: recall_at_10 value: 0.522 - type: recall_at_100 value: 1.9009999999999998 - type: recall_at_1000 value: 5.893000000000001 - type: recall_at_3 value: 0.263 - type: recall_at_5 value: 0.34099999999999997 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 61.03283173734611 - type: f1 value: 61.24012492746259 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 29.68308253533972 - type: f1 value: 16.243459114946905 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 34.330867518493605 - type: f1 value: 33.176158044175935 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 44.13248150638871 - type: f1 value: 44.24904249078732 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 15.698400177259078 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 14.888797785310235 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 25.652445385382126 - type: mrr value: 25.891573325600227 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 0.322 - type: map_at_10 value: 0.7230000000000001 - type: map_at_100 value: 1.248 - type: map_at_1000 value: 1.873 - type: map_at_3 value: 0.479 - type: map_at_5 value: 0.5700000000000001 - type: mrr_at_1 value: 6.502 - type: mrr_at_10 value: 10.735 - type: mrr_at_100 value: 11.848 - type: mrr_at_1000 value: 11.995000000000001 - type: mrr_at_3 value: 9.391 - type: mrr_at_5 value: 9.732000000000001 - type: ndcg_at_1 value: 6.037 - type: ndcg_at_10 value: 4.873 - type: ndcg_at_100 value: 5.959 - type: ndcg_at_1000 value: 14.424000000000001 - type: ndcg_at_3 value: 5.4559999999999995 - type: ndcg_at_5 value: 5.074 - type: precision_at_1 value: 6.192 - type: precision_at_10 value: 4.458 - type: precision_at_100 value: 2.5700000000000003 - type: precision_at_1000 value: 1.3679999999999999 - type: precision_at_3 value: 5.676 - type: precision_at_5 value: 4.954 - type: recall_at_1 value: 0.322 - type: recall_at_10 value: 1.545 - type: recall_at_100 value: 8.301 - type: recall_at_1000 value: 37.294 - type: recall_at_3 value: 0.623 - type: recall_at_5 value: 0.865 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 0.188 - type: map_at_10 value: 0.27 - type: map_at_100 value: 0.322 - type: map_at_1000 value: 0.335 - type: map_at_3 value: 0.246 - type: map_at_5 value: 0.246 - type: mrr_at_1 value: 0.203 - type: mrr_at_10 value: 0.28300000000000003 - type: mrr_at_100 value: 0.344 - type: mrr_at_1000 value: 0.357 - type: mrr_at_3 value: 0.261 - type: mrr_at_5 value: 0.261 - type: ndcg_at_1 value: 0.203 - type: ndcg_at_10 value: 0.329 - type: ndcg_at_100 value: 0.628 - type: ndcg_at_1000 value: 1.0959999999999999 - type: ndcg_at_3 value: 0.272 - type: ndcg_at_5 value: 0.272 - type: precision_at_1 value: 0.203 - type: precision_at_10 value: 0.055 - type: precision_at_100 value: 0.024 - type: precision_at_1000 value: 0.006999999999999999 - type: precision_at_3 value: 0.116 - type: precision_at_5 value: 0.06999999999999999 - type: recall_at_1 value: 0.188 - type: recall_at_10 value: 0.507 - type: recall_at_100 value: 1.883 - type: recall_at_1000 value: 5.609999999999999 - type: recall_at_3 value: 0.333 - type: recall_at_5 value: 0.333 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.016000000000002 - type: map_at_10 value: 28.977999999999998 - type: map_at_100 value: 29.579 - type: map_at_1000 value: 29.648999999999997 - type: map_at_3 value: 27.673 - type: map_at_5 value: 28.427000000000003 - type: mrr_at_1 value: 27.93 - type: mrr_at_10 value: 32.462999999999994 - type: mrr_at_100 value: 32.993 - type: mrr_at_1000 value: 33.044000000000004 - type: mrr_at_3 value: 31.252000000000002 - type: mrr_at_5 value: 31.968999999999998 - type: ndcg_at_1 value: 27.96 - type: ndcg_at_10 value: 31.954 - type: ndcg_at_100 value: 34.882000000000005 - type: ndcg_at_1000 value: 36.751 - type: ndcg_at_3 value: 29.767 - type: ndcg_at_5 value: 30.816 - type: precision_at_1 value: 27.96 - type: precision_at_10 value: 4.826 - type: precision_at_100 value: 0.697 - type: precision_at_1000 value: 0.093 - type: precision_at_3 value: 12.837000000000002 - type: precision_at_5 value: 8.559999999999999 - type: recall_at_1 value: 24.016000000000002 - type: recall_at_10 value: 37.574999999999996 - type: recall_at_100 value: 50.843 - type: recall_at_1000 value: 64.654 - type: recall_at_3 value: 31.182 - type: recall_at_5 value: 34.055 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 18.38048892083281 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 27.103011764141478 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 0.18 - type: map_at_10 value: 0.457 - type: map_at_100 value: 0.634 - type: map_at_1000 value: 0.7000000000000001 - type: map_at_3 value: 0.333 - type: map_at_5 value: 0.387 - type: mrr_at_1 value: 0.8999999999999999 - type: mrr_at_10 value: 1.967 - type: mrr_at_100 value: 2.396 - type: mrr_at_1000 value: 2.495 - type: mrr_at_3 value: 1.567 - type: mrr_at_5 value: 1.7670000000000001 - type: ndcg_at_1 value: 0.8999999999999999 - type: ndcg_at_10 value: 1.022 - type: ndcg_at_100 value: 2.366 - type: ndcg_at_1000 value: 4.689 - type: ndcg_at_3 value: 0.882 - type: ndcg_at_5 value: 0.7929999999999999 - type: precision_at_1 value: 0.8999999999999999 - type: precision_at_10 value: 0.58 - type: precision_at_100 value: 0.263 - type: precision_at_1000 value: 0.084 - type: precision_at_3 value: 0.8999999999999999 - type: precision_at_5 value: 0.74 - type: recall_at_1 value: 0.18 - type: recall_at_10 value: 1.208 - type: recall_at_100 value: 5.373 - type: recall_at_1000 value: 17.112 - type: recall_at_3 value: 0.5579999999999999 - type: recall_at_5 value: 0.7779999999999999 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 55.229896309578905 - type: cos_sim_spearman value: 48.54616726085393 - type: euclidean_pearson value: 53.828130644322 - type: euclidean_spearman value: 48.2907441223958 - type: manhattan_pearson value: 53.72684612327582 - type: manhattan_spearman value: 48.228319721712744 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 57.73555535277214 - type: cos_sim_spearman value: 55.58790083939622 - type: euclidean_pearson value: 61.009463373795384 - type: euclidean_spearman value: 56.696846101196044 - type: manhattan_pearson value: 60.875111392597894 - type: manhattan_spearman value: 56.63100766160946 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 19.47269635955134 - type: cos_sim_spearman value: 18.35951746300603 - type: euclidean_pearson value: 23.130707248318714 - type: euclidean_spearman value: 22.92241668287248 - type: manhattan_pearson value: 22.99371642148021 - type: manhattan_spearman value: 22.770233678121897 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 31.78346805351368 - type: cos_sim_spearman value: 28.84281669682782 - type: euclidean_pearson value: 34.508176962091156 - type: euclidean_spearman value: 32.269242265609975 - type: manhattan_pearson value: 34.41366600914297 - type: manhattan_spearman value: 32.15352239729175 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 29.550332218260465 - type: cos_sim_spearman value: 29.188654452524528 - type: euclidean_pearson value: 33.80339596511417 - type: euclidean_spearman value: 33.49607278843874 - type: manhattan_pearson value: 33.589427741967334 - type: manhattan_spearman value: 33.288312003652884 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 27.163752699585885 - type: cos_sim_spearman value: 39.0544187582685 - type: euclidean_pearson value: 38.93841642732113 - type: euclidean_spearman value: 42.861814968921294 - type: manhattan_pearson value: 38.78821319739337 - type: manhattan_spearman value: 42.757121435678954 - 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: 57.15429605615292 - type: cos_sim_spearman value: 61.21576579300284 - type: euclidean_pearson value: 59.2835939062064 - type: euclidean_spearman value: 60.902713241808236 - type: manhattan_pearson value: 59.510770285546364 - type: manhattan_spearman value: 61.02979474159327 - 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: 41.81726547830133 - type: cos_sim_spearman value: 44.45123398124273 - type: euclidean_pearson value: 46.44144033159064 - type: euclidean_spearman value: 46.61348337508052 - type: manhattan_pearson value: 46.48092744041165 - type: manhattan_spearman value: 46.78049599791891 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 46.085942179295465 - type: cos_sim_spearman value: 44.394736992467365 - type: euclidean_pearson value: 47.06981069147408 - type: euclidean_spearman value: 45.40499474054004 - type: manhattan_pearson value: 46.96497631950794 - type: manhattan_spearman value: 45.31936619298336 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 43.89526517578129 - type: mrr value: 64.30753070458954 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 1.417 - type: map_at_10 value: 2.189 - type: map_at_100 value: 2.5669999999999997 - type: map_at_1000 value: 2.662 - type: map_at_3 value: 1.694 - type: map_at_5 value: 1.928 - type: mrr_at_1 value: 1.667 - type: mrr_at_10 value: 2.4899999999999998 - type: mrr_at_100 value: 2.8400000000000003 - type: mrr_at_1000 value: 2.928 - type: mrr_at_3 value: 1.944 - type: mrr_at_5 value: 2.178 - type: ndcg_at_1 value: 1.667 - type: ndcg_at_10 value: 2.913 - type: ndcg_at_100 value: 5.482 - type: ndcg_at_1000 value: 8.731 - type: ndcg_at_3 value: 1.867 - type: ndcg_at_5 value: 2.257 - type: precision_at_1 value: 1.667 - type: precision_at_10 value: 0.567 - type: precision_at_100 value: 0.213 - type: precision_at_1000 value: 0.053 - type: precision_at_3 value: 0.7779999999999999 - type: precision_at_5 value: 0.6669999999999999 - type: recall_at_1 value: 1.417 - type: recall_at_10 value: 5.028 - type: recall_at_100 value: 18.5 - type: recall_at_1000 value: 45.072 - type: recall_at_3 value: 2.083 - type: recall_at_5 value: 3.083 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.02871287128713 - type: cos_sim_ap value: 17.404404071912694 - type: cos_sim_f1 value: 25.89285714285714 - type: cos_sim_precision value: 29.292929292929294 - type: cos_sim_recall value: 23.200000000000003 - type: dot_accuracy value: 99.0118811881188 - type: dot_ap value: 5.4739000785007335 - type: dot_f1 value: 12.178702570379436 - type: dot_precision value: 8.774250440917108 - type: dot_recall value: 19.900000000000002 - type: euclidean_accuracy value: 99.03663366336633 - type: euclidean_ap value: 19.20851069839796 - type: euclidean_f1 value: 27.16555612506407 - type: euclidean_precision value: 27.865404837013667 - type: euclidean_recall value: 26.5 - type: manhattan_accuracy value: 99.03663366336633 - type: manhattan_ap value: 19.12862913626528 - type: manhattan_f1 value: 26.96629213483146 - type: manhattan_precision value: 28.99884925201381 - type: manhattan_recall value: 25.2 - type: max_accuracy value: 99.03663366336633 - type: max_ap value: 19.20851069839796 - type: max_f1 value: 27.16555612506407 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 23.657118721775905 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 27.343558395037043 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 23.346327148080043 - type: mrr value: 21.99097063067651 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.032 - type: map_at_10 value: 0.157 - type: map_at_100 value: 0.583 - type: map_at_1000 value: 1.48 - type: map_at_3 value: 0.066 - type: map_at_5 value: 0.105 - type: mrr_at_1 value: 10 - type: mrr_at_10 value: 16.99 - type: mrr_at_100 value: 18.284 - type: mrr_at_1000 value: 18.394 - type: mrr_at_3 value: 14.000000000000002 - type: mrr_at_5 value: 15.8 - type: ndcg_at_1 value: 8 - type: ndcg_at_10 value: 7.504 - type: ndcg_at_100 value: 5.339 - type: ndcg_at_1000 value: 6.046 - type: ndcg_at_3 value: 8.358 - type: ndcg_at_5 value: 8.142000000000001 - type: precision_at_1 value: 10 - type: precision_at_10 value: 8.6 - type: precision_at_100 value: 5.9799999999999995 - type: precision_at_1000 value: 2.976 - type: precision_at_3 value: 9.333 - type: precision_at_5 value: 9.2 - type: recall_at_1 value: 0.032 - type: recall_at_10 value: 0.252 - type: recall_at_100 value: 1.529 - type: recall_at_1000 value: 6.364 - type: recall_at_3 value: 0.08499999999999999 - type: recall_at_5 value: 0.154 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 0.44200000000000006 - type: map_at_10 value: 0.996 - type: map_at_100 value: 1.317 - type: map_at_1000 value: 1.624 - type: map_at_3 value: 0.736 - type: map_at_5 value: 0.951 - type: mrr_at_1 value: 4.082 - type: mrr_at_10 value: 10.102 - type: mrr_at_100 value: 10.978 - type: mrr_at_1000 value: 11.1 - type: mrr_at_3 value: 7.8229999999999995 - type: mrr_at_5 value: 9.252 - type: ndcg_at_1 value: 4.082 - type: ndcg_at_10 value: 3.821 - type: ndcg_at_100 value: 5.682 - type: ndcg_at_1000 value: 10.96 - type: ndcg_at_3 value: 4.813 - type: ndcg_at_5 value: 4.757 - type: precision_at_1 value: 4.082 - type: precision_at_10 value: 3.061 - type: precision_at_100 value: 1.367 - type: precision_at_1000 value: 0.46299999999999997 - type: precision_at_3 value: 4.7620000000000005 - type: precision_at_5 value: 4.898000000000001 - type: recall_at_1 value: 0.44200000000000006 - type: recall_at_10 value: 2.059 - type: recall_at_100 value: 7.439 - type: recall_at_1000 value: 25.191000000000003 - type: recall_at_3 value: 1.095 - type: recall_at_5 value: 1.725 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 54.925999999999995 - type: ap value: 9.658236434063275 - type: f1 value: 43.469829154993064 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 40.7498585172609 - type: f1 value: 40.720120106546574 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 20.165152514024733 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 77.59432556476128 - type: cos_sim_ap value: 30.37846072188074 - type: cos_sim_f1 value: 37.9231242656521 - type: cos_sim_precision value: 24.064474898814172 - type: cos_sim_recall value: 89.41952506596306 - type: dot_accuracy value: 77.42146986946415 - type: dot_ap value: 24.073476661930034 - type: dot_f1 value: 37.710580857735025 - type: dot_precision value: 23.61083383243495 - type: dot_recall value: 93.61477572559367 - type: euclidean_accuracy value: 77.64797043571556 - type: euclidean_ap value: 31.892152386237594 - type: euclidean_f1 value: 38.21154759481647 - type: euclidean_precision value: 25.719243766554023 - type: euclidean_recall value: 74.30079155672823 - type: manhattan_accuracy value: 77.6539309769327 - type: manhattan_ap value: 31.89545356309865 - type: manhattan_f1 value: 38.16428166172855 - type: manhattan_precision value: 25.07247577238466 - type: manhattan_recall value: 79.86807387862797 - type: max_accuracy value: 77.6539309769327 - type: max_ap value: 31.89545356309865 - type: max_f1 value: 38.21154759481647 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 76.56886715566422 - type: cos_sim_ap value: 44.04480929059786 - type: cos_sim_f1 value: 43.73100054674686 - type: cos_sim_precision value: 30.540367168647098 - type: cos_sim_recall value: 76.97874961502926 - type: dot_accuracy value: 74.80110218496526 - type: dot_ap value: 26.487746384962758 - type: dot_f1 value: 40.91940608182585 - type: dot_precision value: 25.9157358738502 - type: dot_recall value: 97.18201416692331 - type: euclidean_accuracy value: 76.97054371870998 - type: euclidean_ap value: 47.079120397438416 - type: euclidean_f1 value: 45.866182572614115 - type: euclidean_precision value: 34.580791490692945 - type: euclidean_recall value: 68.0859254696643 - type: manhattan_accuracy value: 76.96084138626927 - type: manhattan_ap value: 47.168701873575976 - type: manhattan_f1 value: 45.985439966237614 - type: manhattan_precision value: 34.974321938693635 - type: manhattan_recall value: 67.11579919926086 - type: max_accuracy value: 76.97054371870998 - type: max_ap value: 47.168701873575976 - type: max_f1 value: 45.985439966237614 - task: type: STS dataset: type: C-MTEB/AFQMC name: MTEB AFQMC config: default split: validation revision: None metrics: - type: cos_sim_pearson value: 3.322530620021471 - type: cos_sim_spearman value: 3.7583567993545195 - type: euclidean_pearson value: 3.743782192206081 - type: euclidean_spearman value: 3.758336694921531 - type: manhattan_pearson value: 3.845233721819267 - type: manhattan_spearman value: 3.8542743797718026 - task: type: STS dataset: type: C-MTEB/ATEC name: MTEB ATEC config: default split: test revision: None metrics: - type: cos_sim_pearson value: 8.552640773272078 - type: cos_sim_spearman value: 10.086360519713061 - type: euclidean_pearson value: 9.902099049347935 - type: euclidean_spearman value: 10.086351512635042 - type: manhattan_pearson value: 9.898006826713932 - type: manhattan_spearman value: 10.076531690161783 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (zh) config: zh split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 21.955999999999996 - type: f1 value: 20.596128116112816 - task: type: STS dataset: type: C-MTEB/BQ name: MTEB BQ config: default split: test revision: None metrics: - type: cos_sim_pearson value: 17.6945509937099 - type: cos_sim_spearman value: 19.312286927022825 - type: euclidean_pearson value: 19.259393744977515 - type: euclidean_spearman value: 19.312290390892713 - type: manhattan_pearson value: 19.223527109645772 - type: manhattan_spearman value: 19.32655209742963 - task: type: Clustering dataset: type: C-MTEB/CLSClusteringP2P name: MTEB CLSClusteringP2P config: default split: test revision: None metrics: - type: v_measure value: 18.657841790313405 - task: type: Clustering dataset: type: C-MTEB/CLSClusteringS2S name: MTEB CLSClusteringS2S config: default split: test revision: None metrics: - type: v_measure value: 16.82483158478091 - task: type: Reranking dataset: type: C-MTEB/CMedQAv1-reranking name: MTEB CMedQAv1 config: default split: test revision: None metrics: - type: map value: 19.71658789133091 - type: mrr value: 23.480595238095237 - task: type: Reranking dataset: type: C-MTEB/CMedQAv2-reranking name: MTEB CMedQAv2 config: default split: test revision: None metrics: - type: map value: 22.475972401039495 - type: mrr value: 25.993650793650797 - task: type: Retrieval dataset: type: C-MTEB/CmedqaRetrieval name: MTEB CmedqaRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 1.026 - type: map_at_10 value: 1.6389999999999998 - type: map_at_100 value: 1.875 - type: map_at_1000 value: 1.9529999999999998 - type: map_at_3 value: 1.417 - type: map_at_5 value: 1.5110000000000001 - type: mrr_at_1 value: 1.525 - type: mrr_at_10 value: 2.478 - type: mrr_at_100 value: 2.779 - type: mrr_at_1000 value: 2.861 - type: mrr_at_3 value: 2.105 - type: mrr_at_5 value: 2.283 - type: ndcg_at_1 value: 1.525 - type: ndcg_at_10 value: 2.222 - type: ndcg_at_100 value: 3.81 - type: ndcg_at_1000 value: 6.465999999999999 - type: ndcg_at_3 value: 1.7489999999999999 - type: ndcg_at_5 value: 1.8980000000000001 - type: precision_at_1 value: 1.525 - type: precision_at_10 value: 0.543 - type: precision_at_100 value: 0.187 - type: precision_at_1000 value: 0.055 - type: precision_at_3 value: 0.992 - type: precision_at_5 value: 0.76 - type: recall_at_1 value: 1.026 - type: recall_at_10 value: 3.1780000000000004 - type: recall_at_100 value: 10.481 - type: recall_at_1000 value: 29.735 - type: recall_at_3 value: 1.8849999999999998 - type: recall_at_5 value: 2.2560000000000002 - task: type: PairClassification dataset: type: C-MTEB/CMNLI name: MTEB Cmnli config: default split: validation revision: None metrics: - type: cos_sim_accuracy value: 54.99699338544799 - type: cos_sim_ap value: 57.78007274332544 - type: cos_sim_f1 value: 67.95391338895512 - type: cos_sim_precision value: 51.46846413095811 - type: cos_sim_recall value: 99.9766191255553 - type: dot_accuracy value: 54.99699338544799 - type: dot_ap value: 57.7791056074979 - type: dot_f1 value: 67.95391338895512 - type: dot_precision value: 51.46846413095811 - type: dot_recall value: 99.9766191255553 - type: euclidean_accuracy value: 54.99699338544799 - type: euclidean_ap value: 57.7800760462191 - type: euclidean_f1 value: 67.95391338895512 - type: euclidean_precision value: 51.46846413095811 - type: euclidean_recall value: 99.9766191255553 - type: manhattan_accuracy value: 55.05712567648827 - type: manhattan_ap value: 57.8146828916844 - type: manhattan_f1 value: 67.95900532295227 - type: manhattan_precision value: 51.46811070998797 - type: manhattan_recall value: 100 - type: max_accuracy value: 55.05712567648827 - type: max_ap value: 57.8146828916844 - type: max_f1 value: 67.95900532295227 - task: type: Retrieval dataset: type: C-MTEB/CovidRetrieval name: MTEB CovidRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 0.632 - type: map_at_10 value: 1.7510000000000001 - type: map_at_100 value: 2.004 - type: map_at_1000 value: 2.0660000000000003 - type: map_at_3 value: 1.493 - type: map_at_5 value: 1.635 - type: mrr_at_1 value: 0.632 - type: mrr_at_10 value: 1.7670000000000001 - type: mrr_at_100 value: 2.02 - type: mrr_at_1000 value: 2.081 - type: mrr_at_3 value: 1.528 - type: mrr_at_5 value: 1.649 - type: ndcg_at_1 value: 0.632 - type: ndcg_at_10 value: 2.32 - type: ndcg_at_100 value: 3.758 - type: ndcg_at_1000 value: 5.894 - type: ndcg_at_3 value: 1.7850000000000001 - type: ndcg_at_5 value: 2.044 - type: precision_at_1 value: 0.632 - type: precision_at_10 value: 0.411 - type: precision_at_100 value: 0.11399999999999999 - type: precision_at_1000 value: 0.03 - type: precision_at_3 value: 0.878 - type: precision_at_5 value: 0.653 - type: recall_at_1 value: 0.632 - type: recall_at_10 value: 4.109999999999999 - type: recall_at_100 value: 11.222 - type: recall_at_1000 value: 29.083 - type: recall_at_3 value: 2.634 - type: recall_at_5 value: 3.267 - task: type: Retrieval dataset: type: C-MTEB/DuRetrieval name: MTEB DuRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 1.436 - type: map_at_10 value: 3.4099999999999997 - type: map_at_100 value: 4.128 - type: map_at_1000 value: 4.282 - type: map_at_3 value: 2.423 - type: map_at_5 value: 2.927 - type: mrr_at_1 value: 6 - type: mrr_at_10 value: 9.701 - type: mrr_at_100 value: 10.347000000000001 - type: mrr_at_1000 value: 10.427999999999999 - type: mrr_at_3 value: 8.267 - type: mrr_at_5 value: 9.004 - type: ndcg_at_1 value: 6 - type: ndcg_at_10 value: 5.856 - type: ndcg_at_100 value: 9.063 - type: ndcg_at_1000 value: 12.475999999999999 - type: ndcg_at_3 value: 5.253 - type: ndcg_at_5 value: 5.223 - type: precision_at_1 value: 6 - type: precision_at_10 value: 3.125 - type: precision_at_100 value: 0.812 - type: precision_at_1000 value: 0.169 - type: precision_at_3 value: 4.7669999999999995 - type: precision_at_5 value: 4.15 - type: recall_at_1 value: 1.436 - type: recall_at_10 value: 6.544999999999999 - type: recall_at_100 value: 16.634999999999998 - type: recall_at_1000 value: 33.987 - type: recall_at_3 value: 3.144 - type: recall_at_5 value: 4.519 - task: type: Retrieval dataset: type: C-MTEB/EcomRetrieval name: MTEB EcomRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 4.1000000000000005 - type: map_at_10 value: 7.911 - type: map_at_100 value: 8.92 - type: map_at_1000 value: 9.033 - type: map_at_3 value: 6.4 - type: map_at_5 value: 7.23 - type: mrr_at_1 value: 4.1000000000000005 - type: mrr_at_10 value: 7.911 - type: mrr_at_100 value: 8.92 - type: mrr_at_1000 value: 9.033 - type: mrr_at_3 value: 6.4 - type: mrr_at_5 value: 7.23 - type: ndcg_at_1 value: 4.1000000000000005 - type: ndcg_at_10 value: 10.374 - type: ndcg_at_100 value: 15.879999999999999 - type: ndcg_at_1000 value: 19.246 - type: ndcg_at_3 value: 7.217 - type: ndcg_at_5 value: 8.706 - type: precision_at_1 value: 4.1000000000000005 - type: precision_at_10 value: 1.8399999999999999 - type: precision_at_100 value: 0.45599999999999996 - type: precision_at_1000 value: 0.073 - type: precision_at_3 value: 3.2 - type: precision_at_5 value: 2.64 - type: recall_at_1 value: 4.1000000000000005 - type: recall_at_10 value: 18.4 - type: recall_at_100 value: 45.6 - type: recall_at_1000 value: 72.89999999999999 - type: recall_at_3 value: 9.6 - type: recall_at_5 value: 13.200000000000001 - task: type: Classification dataset: type: C-MTEB/IFlyTek-classification name: MTEB IFlyTek config: default split: validation revision: None metrics: - type: accuracy value: 20.353982300884958 - type: f1 value: 12.69588085868714 - task: type: Classification dataset: type: C-MTEB/JDReview-classification name: MTEB JDReview config: default split: test revision: None metrics: - type: accuracy value: 55.497185741088174 - type: ap value: 20.43046737602198 - type: f1 value: 48.93980371558734 - task: type: STS dataset: type: C-MTEB/LCQMC name: MTEB LCQMC config: default split: test revision: None metrics: - type: cos_sim_pearson value: 32.588967426128654 - type: cos_sim_spearman value: 42.14900040682406 - type: euclidean_pearson value: 39.568373451615685 - type: euclidean_spearman value: 42.14899152396297 - type: manhattan_pearson value: 39.5220710244444 - type: manhattan_spearman value: 42.14787636056146 - task: type: Reranking dataset: type: C-MTEB/Mmarco-reranking name: MTEB MMarcoReranking config: default split: dev revision: None metrics: - type: map value: 1.1655156335725807 - type: mrr value: 0.2361111111111111 - task: type: Retrieval dataset: type: C-MTEB/MMarcoRetrieval name: MTEB MMarcoRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 1.9029999999999998 - type: map_at_10 value: 2.9139999999999997 - type: map_at_100 value: 3.2259999999999995 - type: map_at_1000 value: 3.2870000000000004 - type: map_at_3 value: 2.483 - type: map_at_5 value: 2.71 - type: mrr_at_1 value: 2.02 - type: mrr_at_10 value: 3.064 - type: mrr_at_100 value: 3.382 - type: mrr_at_1000 value: 3.4419999999999997 - type: mrr_at_3 value: 2.622 - type: mrr_at_5 value: 2.855 - type: ndcg_at_1 value: 2.02 - type: ndcg_at_10 value: 3.639 - type: ndcg_at_100 value: 5.431 - type: ndcg_at_1000 value: 7.404 - type: ndcg_at_3 value: 2.723 - type: ndcg_at_5 value: 3.1350000000000002 - type: precision_at_1 value: 2.02 - type: precision_at_10 value: 0.626 - type: precision_at_100 value: 0.159 - type: precision_at_1000 value: 0.033 - type: precision_at_3 value: 1.17 - type: precision_at_5 value: 0.9199999999999999 - type: recall_at_1 value: 1.9029999999999998 - type: recall_at_10 value: 5.831 - type: recall_at_100 value: 14.737 - type: recall_at_1000 value: 30.84 - type: recall_at_3 value: 3.2870000000000004 - type: recall_at_5 value: 4.282 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (zh-CN) config: zh-CN split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 25.3866845998655 - type: f1 value: 23.404809615998495 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (zh-CN) config: zh-CN split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 40.34969737726966 - type: f1 value: 37.88244646590394 - task: type: Retrieval dataset: type: C-MTEB/MedicalRetrieval name: MTEB MedicalRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 1.5 - type: map_at_10 value: 2.0740000000000003 - type: map_at_100 value: 2.2079999999999997 - type: map_at_1000 value: 2.241 - type: map_at_3 value: 1.933 - type: map_at_5 value: 2.023 - type: mrr_at_1 value: 1.5 - type: mrr_at_10 value: 2.0740000000000003 - type: mrr_at_100 value: 2.2079999999999997 - type: mrr_at_1000 value: 2.241 - type: mrr_at_3 value: 1.933 - type: mrr_at_5 value: 2.023 - type: ndcg_at_1 value: 1.5 - type: ndcg_at_10 value: 2.368 - type: ndcg_at_100 value: 3.309 - type: ndcg_at_1000 value: 4.593 - type: ndcg_at_3 value: 2.0789999999999997 - type: ndcg_at_5 value: 2.242 - type: precision_at_1 value: 1.5 - type: precision_at_10 value: 0.33 - type: precision_at_100 value: 0.084 - type: precision_at_1000 value: 0.019 - type: precision_at_3 value: 0.8330000000000001 - type: precision_at_5 value: 0.58 - type: recall_at_1 value: 1.5 - type: recall_at_10 value: 3.3000000000000003 - type: recall_at_100 value: 8.4 - type: recall_at_1000 value: 19.400000000000002 - type: recall_at_3 value: 2.5 - type: recall_at_5 value: 2.9000000000000004 - task: type: Classification dataset: type: C-MTEB/MultilingualSentiment-classification name: MTEB MultilingualSentiment config: default split: validation revision: None metrics: - type: accuracy value: 38.94 - type: f1 value: 38.4171730136538 - task: type: PairClassification dataset: type: C-MTEB/OCNLI name: MTEB Ocnli config: default split: validation revision: None metrics: - type: cos_sim_accuracy value: 54.141851651326476 - type: cos_sim_ap value: 55.63298007661861 - type: cos_sim_f1 value: 67.85195936139333 - type: cos_sim_precision value: 51.68601437258153 - type: cos_sim_recall value: 98.73284054910243 - type: dot_accuracy value: 54.141851651326476 - type: dot_ap value: 55.63298007661861 - type: dot_f1 value: 67.85195936139333 - type: dot_precision value: 51.68601437258153 - type: dot_recall value: 98.73284054910243 - type: euclidean_accuracy value: 54.141851651326476 - type: euclidean_ap value: 55.63298007661861 - type: euclidean_f1 value: 67.85195936139333 - type: euclidean_precision value: 51.68601437258153 - type: euclidean_recall value: 98.73284054910243 - type: manhattan_accuracy value: 54.03356794802382 - type: manhattan_ap value: 55.650247173847944 - type: manhattan_f1 value: 67.83667621776503 - type: manhattan_precision value: 51.32791327913279 - type: manhattan_recall value: 100 - type: max_accuracy value: 54.141851651326476 - type: max_ap value: 55.650247173847944 - type: max_f1 value: 67.85195936139333 - task: type: Classification dataset: type: C-MTEB/OnlineShopping-classification name: MTEB OnlineShopping config: default split: test revision: None metrics: - type: accuracy value: 56.88999999999999 - type: ap value: 56.075855594697835 - type: f1 value: 56.31094564241924 - task: type: STS dataset: type: C-MTEB/PAWSX name: MTEB PAWSX config: default split: test revision: None metrics: - type: cos_sim_pearson value: 10.023575042969506 - type: cos_sim_spearman value: 6.135169971774927 - type: euclidean_pearson value: 9.219072035876794 - type: euclidean_spearman value: 6.147945631319713 - type: manhattan_pearson value: 9.208267921398097 - type: manhattan_spearman value: 6.156480815791583 - task: type: STS dataset: type: C-MTEB/QBQTC name: MTEB QBQTC config: default split: test revision: None metrics: - type: cos_sim_pearson value: 5.7230819885069435 - type: cos_sim_spearman value: 6.116111130034651 - type: euclidean_pearson value: 5.9142712292657205 - type: euclidean_spearman value: 6.115732664912588 - type: manhattan_pearson value: 5.892970378623552 - type: manhattan_spearman value: 6.100463075081302 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (zh) config: zh split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 18.353401358720397 - type: cos_sim_spearman value: 33.700002511275095 - type: euclidean_pearson value: 27.654605278731136 - type: euclidean_spearman value: 33.700002511275095 - type: manhattan_pearson value: 29.174977260571083 - type: manhattan_spearman value: 33.901862553268366 - task: type: STS dataset: type: C-MTEB/STSB name: MTEB STSB config: default split: test revision: None metrics: - type: cos_sim_pearson value: 44.66287398363386 - type: cos_sim_spearman value: 45.60317964713117 - type: euclidean_pearson value: 47.434263079423 - type: euclidean_spearman value: 45.603111040461606 - type: manhattan_pearson value: 47.3272049502668 - type: manhattan_spearman value: 45.506449459872805 - task: type: Reranking dataset: type: C-MTEB/T2Reranking name: MTEB T2Reranking config: default split: dev revision: None metrics: - type: map value: 60.05480951659048 - type: mrr value: 69.58201013422746 - task: type: Retrieval dataset: type: C-MTEB/T2Retrieval name: MTEB T2Retrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 1.159 - type: map_at_10 value: 2.624 - type: map_at_100 value: 3.259 - type: map_at_1000 value: 3.4090000000000003 - type: map_at_3 value: 1.9109999999999998 - type: map_at_5 value: 2.254 - type: mrr_at_1 value: 5.87 - type: mrr_at_10 value: 8.530999999999999 - type: mrr_at_100 value: 9.142999999999999 - type: mrr_at_1000 value: 9.229 - type: mrr_at_3 value: 7.498 - type: mrr_at_5 value: 8.056000000000001 - type: ndcg_at_1 value: 5.87 - type: ndcg_at_10 value: 4.641 - type: ndcg_at_100 value: 7.507999999999999 - type: ndcg_at_1000 value: 10.823 - type: ndcg_at_3 value: 4.775 - type: ndcg_at_5 value: 4.515000000000001 - type: precision_at_1 value: 5.87 - type: precision_at_10 value: 2.632 - type: precision_at_100 value: 0.762 - type: precision_at_1000 value: 0.166 - type: precision_at_3 value: 4.2299999999999995 - type: precision_at_5 value: 3.5450000000000004 - type: recall_at_1 value: 1.159 - type: recall_at_10 value: 4.816 - type: recall_at_100 value: 13.841999999999999 - type: recall_at_1000 value: 30.469 - type: recall_at_3 value: 2.413 - type: recall_at_5 value: 3.3300000000000005 - task: type: Classification dataset: type: C-MTEB/TNews-classification name: MTEB TNews config: default split: validation revision: None metrics: - type: accuracy value: 26.786000000000005 - type: f1 value: 25.70512339530705 - task: type: Clustering dataset: type: C-MTEB/ThuNewsClusteringP2P name: MTEB ThuNewsClusteringP2P config: default split: test revision: None metrics: - type: v_measure value: 20.691386720429243 - task: type: Clustering dataset: type: C-MTEB/ThuNewsClusteringS2S name: MTEB ThuNewsClusteringS2S config: default split: test revision: None metrics: - type: v_measure value: 17.1882521768033 - task: type: Retrieval dataset: type: C-MTEB/VideoRetrieval name: MTEB VideoRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 2.9000000000000004 - type: map_at_10 value: 4.051 - type: map_at_100 value: 4.277 - type: map_at_1000 value: 4.315 - type: map_at_3 value: 3.567 - type: map_at_5 value: 3.897 - type: mrr_at_1 value: 2.9000000000000004 - type: mrr_at_10 value: 4.051 - type: mrr_at_100 value: 4.277 - type: mrr_at_1000 value: 4.315 - type: mrr_at_3 value: 3.567 - type: mrr_at_5 value: 3.897 - type: ndcg_at_1 value: 2.9000000000000004 - type: ndcg_at_10 value: 4.772 - type: ndcg_at_100 value: 6.214 - type: ndcg_at_1000 value: 7.456 - type: ndcg_at_3 value: 3.805 - type: ndcg_at_5 value: 4.390000000000001 - type: precision_at_1 value: 2.9000000000000004 - type: precision_at_10 value: 0.7100000000000001 - type: precision_at_100 value: 0.146 - type: precision_at_1000 value: 0.025 - type: precision_at_3 value: 1.5 - type: precision_at_5 value: 1.18 - type: recall_at_1 value: 2.9000000000000004 - type: recall_at_10 value: 7.1 - type: recall_at_100 value: 14.6 - type: recall_at_1000 value: 24.9 - type: recall_at_3 value: 4.5 - type: recall_at_5 value: 5.8999999999999995 - task: type: Classification dataset: type: C-MTEB/waimai-classification name: MTEB Waimai config: default split: test revision: None metrics: - type: accuracy value: 56.21999999999999 - type: ap value: 36.53654363772411 - type: f1 value: 54.922396485449674 --- # {MODEL_NAME} This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. ## Usage (Sentence-Transformers) Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: ``` pip install -U sentence-transformers ``` Then you can use the model like this: ```python from sentence_transformers import SentenceTransformer sentences = ["This is an example sentence", "Each sentence is converted"] model = SentenceTransformer('{MODEL_NAME}') embeddings = model.encode(sentences) print(embeddings) ``` ## Usage (HuggingFace Transformers) Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings. ```python from transformers import AutoTokenizer, AutoModel import torch #Mean Pooling - Take attention mask into account for correct averaging def mean_pooling(model_output, attention_mask): token_embeddings = model_output[0] #First element of model_output contains all token embeddings input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float() return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9) # Sentences we want sentence embeddings for sentences = ['This is an example sentence', 'Each sentence is converted'] # Load model from HuggingFace Hub tokenizer = AutoTokenizer.from_pretrained('{MODEL_NAME}') model = AutoModel.from_pretrained('{MODEL_NAME}') # Tokenize sentences encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt') # Compute token embeddings with torch.no_grad(): model_output = model(**encoded_input) # Perform pooling. In this case, mean pooling. sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask']) print("Sentence embeddings:") print(sentence_embeddings) ``` ## Evaluation Results For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name={MODEL_NAME}) ## Training The model was trained with the parameters: **DataLoader**: `torch.utils.data.dataloader.DataLoader` of length 1468721 with parameters: ``` {'batch_size': 160, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'} ``` **Loss**: `sentence_transformers.losses.CosineSimilarityLoss.CosineSimilarityLoss` Parameters of the fit()-Method: ``` { "epochs": 1, "evaluation_steps": 0, "evaluator": "NoneType", "max_grad_norm": 1, "optimizer_class": "", "optimizer_params": { "lr": 2e-05 }, "scheduler": "WarmupLinear", "steps_per_epoch": null, "warmup_steps": 100, "weight_decay": 0.01 } ``` ## Full Model Architecture ``` SentenceTransformer( (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False}) ) ``` ## Citing & Authors