diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -1,2515 +1,3565 @@ --- tags: -- mteb + - 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 - 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- 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: 10.0 - - 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: 8.0 - - 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: 10.0 - - 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 + - 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}