--- tags: - mteb model-index: - name: bge_finetuned results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 61.64179104477612 - type: ap value: 25.20497978200253 - type: f1 value: 55.51169205110252 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 58.6114 - type: ap value: 55.013881977883706 - type: f1 value: 58.0798269108889 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 27.009999999999994 - type: f1 value: 26.230644551993027 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 14.011000000000001 - type: map_at_10 value: 24.082 - type: map_at_100 value: 25.273 - type: map_at_1000 value: 25.336 - type: map_at_3 value: 20.341 - type: map_at_5 value: 22.155 - type: mrr_at_1 value: 14.651 - type: mrr_at_10 value: 24.306 - type: mrr_at_100 value: 25.503999999999998 - type: mrr_at_1000 value: 25.566 - type: mrr_at_3 value: 20.59 - type: mrr_at_5 value: 22.400000000000002 - type: ndcg_at_1 value: 14.011000000000001 - type: ndcg_at_10 value: 30.316 - type: ndcg_at_100 value: 36.146 - type: ndcg_at_1000 value: 37.972 - type: ndcg_at_3 value: 22.422 - type: ndcg_at_5 value: 25.727 - type: precision_at_1 value: 14.011000000000001 - type: precision_at_10 value: 5.0569999999999995 - type: precision_at_100 value: 0.7799999999999999 - type: precision_at_1000 value: 0.093 - type: precision_at_3 value: 9.483 - type: precision_at_5 value: 7.312 - type: recall_at_1 value: 14.011000000000001 - type: recall_at_10 value: 50.568999999999996 - type: recall_at_100 value: 77.952 - type: recall_at_1000 value: 92.674 - type: recall_at_3 value: 28.449999999999996 - type: recall_at_5 value: 36.558 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 21.580787107217457 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 12.755947651867459 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 50.36895415359604 - type: mrr value: 62.93244075100032 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 54.84190098866484 - type: cos_sim_spearman value: 52.065644182348144 - type: euclidean_pearson value: 54.181073661388034 - type: euclidean_spearman value: 52.065644182348144 - type: manhattan_pearson value: 54.98368207013862 - type: manhattan_spearman value: 53.66387337016872 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 63.48051948051948 - type: f1 value: 61.45740352513437 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 16.23123129183937 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 6.846095550717324 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 14.587 - type: map_at_10 value: 20.032 - type: map_at_100 value: 21.2 - type: map_at_1000 value: 21.351 - type: map_at_3 value: 18.224 - type: map_at_5 value: 19.028 - type: mrr_at_1 value: 18.312 - type: mrr_at_10 value: 24.343999999999998 - type: mrr_at_100 value: 25.302000000000003 - type: mrr_at_1000 value: 25.385 - type: mrr_at_3 value: 22.461000000000002 - type: mrr_at_5 value: 23.219 - type: ndcg_at_1 value: 18.312 - type: ndcg_at_10 value: 24.05 - type: ndcg_at_100 value: 29.512 - type: ndcg_at_1000 value: 33.028999999999996 - type: ndcg_at_3 value: 20.947 - type: ndcg_at_5 value: 21.807000000000002 - type: precision_at_1 value: 18.312 - type: precision_at_10 value: 4.664 - type: precision_at_100 value: 0.9570000000000001 - type: precision_at_1000 value: 0.155 - type: precision_at_3 value: 10.11 - type: precision_at_5 value: 7.066999999999999 - type: recall_at_1 value: 14.587 - type: recall_at_10 value: 31.865 - type: recall_at_100 value: 55.922000000000004 - type: recall_at_1000 value: 80.878 - type: recall_at_3 value: 22.229 - type: recall_at_5 value: 25.09 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 8.456 - type: map_at_10 value: 11.429 - type: map_at_100 value: 11.956 - type: map_at_1000 value: 12.04 - type: map_at_3 value: 10.309 - type: map_at_5 value: 11.006 - type: mrr_at_1 value: 10.637 - type: mrr_at_10 value: 14.047 - type: mrr_at_100 value: 14.591999999999999 - type: mrr_at_1000 value: 14.66 - type: mrr_at_3 value: 12.876999999999999 - type: mrr_at_5 value: 13.644 - type: ndcg_at_1 value: 10.637 - type: ndcg_at_10 value: 13.623 - type: ndcg_at_100 value: 16.337 - type: ndcg_at_1000 value: 18.881 - type: ndcg_at_3 value: 11.76 - type: ndcg_at_5 value: 12.803 - type: precision_at_1 value: 10.637 - type: precision_at_10 value: 2.611 - type: precision_at_100 value: 0.49899999999999994 - type: precision_at_1000 value: 0.08800000000000001 - type: precision_at_3 value: 5.7540000000000004 - type: precision_at_5 value: 4.306 - type: recall_at_1 value: 8.456 - type: recall_at_10 value: 17.543 - type: recall_at_100 value: 29.696 - type: recall_at_1000 value: 48.433 - type: recall_at_3 value: 12.299 - type: recall_at_5 value: 15.126000000000001 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 10.517999999999999 - type: map_at_10 value: 14.924999999999999 - type: map_at_100 value: 15.716 - type: map_at_1000 value: 15.804000000000002 - type: map_at_3 value: 13.228000000000002 - type: map_at_5 value: 14.155999999999999 - type: mrr_at_1 value: 12.790000000000001 - type: mrr_at_10 value: 17.122999999999998 - type: mrr_at_100 value: 17.874000000000002 - type: mrr_at_1000 value: 17.947 - type: mrr_at_3 value: 15.528 - type: mrr_at_5 value: 16.421 - type: ndcg_at_1 value: 12.790000000000001 - type: ndcg_at_10 value: 17.967 - type: ndcg_at_100 value: 22.016 - type: ndcg_at_1000 value: 24.57 - type: ndcg_at_3 value: 14.745 - type: ndcg_at_5 value: 16.247 - type: precision_at_1 value: 12.790000000000001 - type: precision_at_10 value: 3.229 - type: precision_at_100 value: 0.592 - type: precision_at_1000 value: 0.087 - type: precision_at_3 value: 6.792 - type: precision_at_5 value: 5.066 - type: recall_at_1 value: 10.517999999999999 - type: recall_at_10 value: 25.194 - type: recall_at_100 value: 43.858999999999995 - type: recall_at_1000 value: 63.410999999999994 - type: recall_at_3 value: 16.384999999999998 - type: recall_at_5 value: 20.09 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 8.325000000000001 - type: map_at_10 value: 12.262 - type: map_at_100 value: 13.003 - type: map_at_1000 value: 13.126999999999999 - type: map_at_3 value: 10.946 - type: map_at_5 value: 11.581 - type: mrr_at_1 value: 9.379 - type: mrr_at_10 value: 13.527000000000001 - type: mrr_at_100 value: 14.249999999999998 - type: mrr_at_1000 value: 14.365 - type: mrr_at_3 value: 12.166 - type: mrr_at_5 value: 12.798000000000002 - type: ndcg_at_1 value: 9.379 - type: ndcg_at_10 value: 14.878 - type: ndcg_at_100 value: 19.17 - type: ndcg_at_1000 value: 22.861 - type: ndcg_at_3 value: 12.136 - type: ndcg_at_5 value: 13.209000000000001 - type: precision_at_1 value: 9.379 - type: precision_at_10 value: 2.5309999999999997 - type: precision_at_100 value: 0.505 - type: precision_at_1000 value: 0.086 - type: precision_at_3 value: 5.386 - type: precision_at_5 value: 3.887 - type: recall_at_1 value: 8.325000000000001 - type: recall_at_10 value: 21.886 - type: recall_at_100 value: 42.977 - type: recall_at_1000 value: 71.946 - type: recall_at_3 value: 14.123 - type: recall_at_5 value: 16.747 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 5.982 - type: map_at_10 value: 9.249 - type: map_at_100 value: 10.0 - type: map_at_1000 value: 10.127 - type: map_at_3 value: 7.913 - type: map_at_5 value: 8.540000000000001 - type: mrr_at_1 value: 7.960000000000001 - type: mrr_at_10 value: 11.703 - type: mrr_at_100 value: 12.43 - type: mrr_at_1000 value: 12.534999999999998 - type: mrr_at_3 value: 10.344000000000001 - type: mrr_at_5 value: 11.022 - type: ndcg_at_1 value: 7.960000000000001 - type: ndcg_at_10 value: 11.863 - type: ndcg_at_100 value: 16.086 - type: ndcg_at_1000 value: 19.738 - type: ndcg_at_3 value: 9.241000000000001 - type: ndcg_at_5 value: 10.228 - type: precision_at_1 value: 7.960000000000001 - type: precision_at_10 value: 2.4 - type: precision_at_100 value: 0.534 - type: precision_at_1000 value: 0.097 - type: precision_at_3 value: 4.561 - type: precision_at_5 value: 3.408 - type: recall_at_1 value: 5.982 - type: recall_at_10 value: 17.669999999999998 - type: recall_at_100 value: 37.261 - type: recall_at_1000 value: 64.416 - type: recall_at_3 value: 10.376000000000001 - type: recall_at_5 value: 12.933 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 9.068 - type: map_at_10 value: 12.101 - type: map_at_100 value: 12.828000000000001 - type: map_at_1000 value: 12.953000000000001 - type: map_at_3 value: 11.047 - type: map_at_5 value: 11.542 - type: mrr_at_1 value: 10.972 - type: mrr_at_10 value: 14.873 - type: mrr_at_100 value: 15.584000000000001 - type: mrr_at_1000 value: 15.681999999999999 - type: mrr_at_3 value: 13.523 - type: mrr_at_5 value: 14.254 - type: ndcg_at_1 value: 10.972 - type: ndcg_at_10 value: 14.557999999999998 - type: ndcg_at_100 value: 18.56 - type: ndcg_at_1000 value: 21.975 - type: ndcg_at_3 value: 12.436 - type: ndcg_at_5 value: 13.270999999999999 - type: precision_at_1 value: 10.972 - type: precision_at_10 value: 2.714 - type: precision_at_100 value: 0.5720000000000001 - type: precision_at_1000 value: 0.10200000000000001 - type: precision_at_3 value: 5.711 - type: precision_at_5 value: 4.1579999999999995 - type: recall_at_1 value: 9.068 - type: recall_at_10 value: 19.381999999999998 - type: recall_at_100 value: 37.602999999999994 - type: recall_at_1000 value: 62.376 - type: recall_at_3 value: 13.48 - type: recall_at_5 value: 15.506 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 8.206 - type: map_at_10 value: 12.032 - type: map_at_100 value: 12.992 - type: map_at_1000 value: 13.135 - type: map_at_3 value: 10.741 - type: map_at_5 value: 11.392 - type: mrr_at_1 value: 10.502 - type: mrr_at_10 value: 14.818999999999999 - type: mrr_at_100 value: 15.716 - type: mrr_at_1000 value: 15.823 - type: mrr_at_3 value: 13.375 - type: mrr_at_5 value: 14.169 - type: ndcg_at_1 value: 10.502 - type: ndcg_at_10 value: 14.790000000000001 - type: ndcg_at_100 value: 19.881999999999998 - type: ndcg_at_1000 value: 23.703 - type: ndcg_at_3 value: 12.281 - type: ndcg_at_5 value: 13.33 - type: precision_at_1 value: 10.502 - type: precision_at_10 value: 2.911 - type: precision_at_100 value: 0.668 - type: precision_at_1000 value: 0.11499999999999999 - type: precision_at_3 value: 6.012 - type: precision_at_5 value: 4.475 - type: recall_at_1 value: 8.206 - type: recall_at_10 value: 20.508000000000003 - type: recall_at_100 value: 43.568 - type: recall_at_1000 value: 71.56400000000001 - type: recall_at_3 value: 13.607 - type: recall_at_5 value: 16.211000000000002 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 6.4159999999999995 - type: map_at_10 value: 9.581000000000001 - type: map_at_100 value: 10.123999999999999 - type: map_at_1000 value: 10.226 - type: map_at_3 value: 8.51 - type: map_at_5 value: 9.078999999999999 - type: mrr_at_1 value: 7.515 - type: mrr_at_10 value: 10.801 - type: mrr_at_100 value: 11.373 - type: mrr_at_1000 value: 11.466999999999999 - type: mrr_at_3 value: 9.637 - type: mrr_at_5 value: 10.197000000000001 - type: ndcg_at_1 value: 7.515 - type: ndcg_at_10 value: 11.776 - type: ndcg_at_100 value: 14.776 - type: ndcg_at_1000 value: 17.7 - type: ndcg_at_3 value: 9.515 - type: ndcg_at_5 value: 10.511 - type: precision_at_1 value: 7.515 - type: precision_at_10 value: 2.086 - type: precision_at_100 value: 0.402 - type: precision_at_1000 value: 0.07100000000000001 - type: precision_at_3 value: 4.397 - type: precision_at_5 value: 3.19 - type: recall_at_1 value: 6.4159999999999995 - type: recall_at_10 value: 17.468 - type: recall_at_100 value: 31.398 - type: recall_at_1000 value: 53.686 - type: recall_at_3 value: 11.379999999999999 - type: recall_at_5 value: 13.745 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 4.646 - type: map_at_10 value: 7.047000000000001 - type: map_at_100 value: 7.697 - type: map_at_1000 value: 7.806 - type: map_at_3 value: 6.258 - type: map_at_5 value: 6.628 - type: mrr_at_1 value: 5.919 - type: mrr_at_10 value: 8.767999999999999 - type: mrr_at_100 value: 9.434 - type: mrr_at_1000 value: 9.524000000000001 - type: mrr_at_3 value: 7.8 - type: mrr_at_5 value: 8.275 - type: ndcg_at_1 value: 5.919 - type: ndcg_at_10 value: 8.927999999999999 - type: ndcg_at_100 value: 12.467 - type: ndcg_at_1000 value: 15.674 - type: ndcg_at_3 value: 7.3260000000000005 - type: ndcg_at_5 value: 7.931000000000001 - type: precision_at_1 value: 5.919 - type: precision_at_10 value: 1.7760000000000002 - type: precision_at_100 value: 0.438 - type: precision_at_1000 value: 0.086 - type: precision_at_3 value: 3.6249999999999996 - type: precision_at_5 value: 2.657 - type: recall_at_1 value: 4.646 - type: recall_at_10 value: 12.973 - type: recall_at_100 value: 29.444 - type: recall_at_1000 value: 53.413999999999994 - type: recall_at_3 value: 8.378 - type: recall_at_5 value: 9.957 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 9.202 - type: map_at_10 value: 13.402 - type: map_at_100 value: 14.330000000000002 - type: map_at_1000 value: 14.455000000000002 - type: map_at_3 value: 11.916 - type: map_at_5 value: 12.828000000000001 - type: mrr_at_1 value: 10.634 - type: mrr_at_10 value: 15.528 - type: mrr_at_100 value: 16.393 - type: mrr_at_1000 value: 16.497999999999998 - type: mrr_at_3 value: 13.837 - type: mrr_at_5 value: 14.821000000000002 - type: ndcg_at_1 value: 10.634 - type: ndcg_at_10 value: 16.267 - type: ndcg_at_100 value: 21.149 - type: ndcg_at_1000 value: 24.509 - type: ndcg_at_3 value: 13.320000000000002 - type: ndcg_at_5 value: 14.857000000000001 - type: precision_at_1 value: 10.634 - type: precision_at_10 value: 2.948 - type: precision_at_100 value: 0.618 - type: precision_at_1000 value: 0.10200000000000001 - type: precision_at_3 value: 6.188 - type: precision_at_5 value: 4.7010000000000005 - type: recall_at_1 value: 9.202 - type: recall_at_10 value: 22.921 - type: recall_at_100 value: 45.292 - type: recall_at_1000 value: 69.853 - type: recall_at_3 value: 15.126000000000001 - type: recall_at_5 value: 18.863 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 11.278 - type: map_at_10 value: 15.72 - type: map_at_100 value: 16.832 - type: map_at_1000 value: 17.025000000000002 - type: map_at_3 value: 13.852999999999998 - type: map_at_5 value: 14.654 - type: mrr_at_1 value: 14.822 - type: mrr_at_10 value: 19.564 - type: mrr_at_100 value: 20.509 - type: mrr_at_1000 value: 20.607 - type: mrr_at_3 value: 17.721 - type: mrr_at_5 value: 18.451999999999998 - type: ndcg_at_1 value: 14.822 - type: ndcg_at_10 value: 19.548 - type: ndcg_at_100 value: 24.734 - type: ndcg_at_1000 value: 28.832 - type: ndcg_at_3 value: 16.14 - type: ndcg_at_5 value: 17.253 - type: precision_at_1 value: 14.822 - type: precision_at_10 value: 3.972 - type: precision_at_100 value: 0.943 - type: precision_at_1000 value: 0.183 - type: precision_at_3 value: 7.642 - type: precision_at_5 value: 5.6129999999999995 - type: recall_at_1 value: 11.278 - type: recall_at_10 value: 27.006999999999998 - type: recall_at_100 value: 51.012 - type: recall_at_1000 value: 79.833 - type: recall_at_3 value: 16.785 - type: recall_at_5 value: 19.82 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 5.305 - type: map_at_10 value: 9.099 - type: map_at_100 value: 9.927999999999999 - type: map_at_1000 value: 10.027 - type: map_at_3 value: 7.7700000000000005 - type: map_at_5 value: 8.333 - type: mrr_at_1 value: 6.1 - type: mrr_at_10 value: 10.227 - type: mrr_at_100 value: 11.057 - type: mrr_at_1000 value: 11.151 - type: mrr_at_3 value: 8.842 - type: mrr_at_5 value: 9.442 - type: ndcg_at_1 value: 6.1 - type: ndcg_at_10 value: 11.769 - type: ndcg_at_100 value: 16.378999999999998 - type: ndcg_at_1000 value: 19.517 - type: ndcg_at_3 value: 8.936 - type: ndcg_at_5 value: 9.907 - type: precision_at_1 value: 6.1 - type: precision_at_10 value: 2.181 - type: precision_at_100 value: 0.481 - type: precision_at_1000 value: 0.08099999999999999 - type: precision_at_3 value: 4.19 - type: precision_at_5 value: 3.031 - type: recall_at_1 value: 5.305 - type: recall_at_10 value: 19.236 - type: recall_at_100 value: 41.333999999999996 - type: recall_at_1000 value: 65.96600000000001 - type: recall_at_3 value: 11.189 - type: recall_at_5 value: 13.592 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 0.882 - type: map_at_10 value: 1.6 - type: map_at_100 value: 1.894 - type: map_at_1000 value: 1.9640000000000002 - type: map_at_3 value: 1.345 - type: map_at_5 value: 1.444 - type: mrr_at_1 value: 2.2800000000000002 - type: mrr_at_10 value: 3.8510000000000004 - type: mrr_at_100 value: 4.401 - type: mrr_at_1000 value: 4.472 - type: mrr_at_3 value: 3.2359999999999998 - type: mrr_at_5 value: 3.519 - type: ndcg_at_1 value: 2.2800000000000002 - type: ndcg_at_10 value: 2.5829999999999997 - type: ndcg_at_100 value: 4.629 - type: ndcg_at_1000 value: 6.709 - type: ndcg_at_3 value: 1.978 - type: ndcg_at_5 value: 2.133 - type: precision_at_1 value: 2.2800000000000002 - type: precision_at_10 value: 0.86 - type: precision_at_100 value: 0.298 - type: precision_at_1000 value: 0.065 - type: precision_at_3 value: 1.52 - type: precision_at_5 value: 1.173 - type: recall_at_1 value: 0.882 - type: recall_at_10 value: 3.273 - type: recall_at_100 value: 11.254 - type: recall_at_1000 value: 23.988 - type: recall_at_3 value: 1.818 - type: recall_at_5 value: 2.236 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 1.057 - type: map_at_10 value: 2.289 - type: map_at_100 value: 2.844 - type: map_at_1000 value: 3.026 - type: map_at_3 value: 1.661 - type: map_at_5 value: 1.931 - type: mrr_at_1 value: 12.75 - type: mrr_at_10 value: 17.645 - type: mrr_at_100 value: 18.312 - type: mrr_at_1000 value: 18.385 - type: mrr_at_3 value: 15.958 - type: mrr_at_5 value: 17.046 - type: ndcg_at_1 value: 10.0 - type: ndcg_at_10 value: 6.890000000000001 - type: ndcg_at_100 value: 7.131 - type: ndcg_at_1000 value: 9.725 - type: ndcg_at_3 value: 8.222 - type: ndcg_at_5 value: 7.536 - type: precision_at_1 value: 12.75 - type: precision_at_10 value: 5.925 - type: precision_at_100 value: 1.6469999999999998 - type: precision_at_1000 value: 0.40299999999999997 - type: precision_at_3 value: 9.667 - type: precision_at_5 value: 8.0 - type: recall_at_1 value: 1.057 - type: recall_at_10 value: 3.8580000000000005 - type: recall_at_100 value: 8.685 - type: recall_at_1000 value: 17.605 - type: recall_at_3 value: 2.041 - type: recall_at_5 value: 2.811 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 20.674999999999997 - type: f1 value: 17.79184478487413 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 2.637 - type: map_at_10 value: 3.9730000000000003 - type: map_at_100 value: 4.228 - type: map_at_1000 value: 4.268000000000001 - type: map_at_3 value: 3.542 - type: map_at_5 value: 3.763 - type: mrr_at_1 value: 2.7449999999999997 - type: mrr_at_10 value: 4.146 - type: mrr_at_100 value: 4.42 - type: mrr_at_1000 value: 4.460999999999999 - type: mrr_at_3 value: 3.695 - type: mrr_at_5 value: 3.925 - type: ndcg_at_1 value: 2.7449999999999997 - type: ndcg_at_10 value: 4.801 - type: ndcg_at_100 value: 6.198 - type: ndcg_at_1000 value: 7.468 - type: ndcg_at_3 value: 3.882 - type: ndcg_at_5 value: 4.283 - type: precision_at_1 value: 2.7449999999999997 - type: precision_at_10 value: 0.771 - type: precision_at_100 value: 0.152 - type: precision_at_1000 value: 0.027 - type: precision_at_3 value: 1.6549999999999998 - type: precision_at_5 value: 1.206 - type: recall_at_1 value: 2.637 - type: recall_at_10 value: 7.2669999999999995 - type: recall_at_100 value: 13.982 - type: recall_at_1000 value: 24.192 - type: recall_at_3 value: 4.712000000000001 - type: recall_at_5 value: 5.6739999999999995 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 2.91 - type: map_at_10 value: 5.721 - type: map_at_100 value: 6.489000000000001 - type: map_at_1000 value: 6.642 - type: map_at_3 value: 4.797 - type: map_at_5 value: 5.292 - type: mrr_at_1 value: 6.481000000000001 - type: mrr_at_10 value: 10.624 - type: mrr_at_100 value: 11.498999999999999 - type: mrr_at_1000 value: 11.599 - type: mrr_at_3 value: 9.285 - type: mrr_at_5 value: 10.003 - type: ndcg_at_1 value: 6.481000000000001 - type: ndcg_at_10 value: 8.303 - type: ndcg_at_100 value: 12.512 - type: ndcg_at_1000 value: 16.665 - type: ndcg_at_3 value: 6.827 - type: ndcg_at_5 value: 7.367 - type: precision_at_1 value: 6.481000000000001 - type: precision_at_10 value: 2.485 - type: precision_at_100 value: 0.668 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 4.733 - type: precision_at_5 value: 3.642 - type: recall_at_1 value: 2.91 - type: recall_at_10 value: 11.239 - type: recall_at_100 value: 27.877999999999997 - type: recall_at_1000 value: 54.507000000000005 - type: recall_at_3 value: 6.683 - type: recall_at_5 value: 8.591 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 2.073 - type: map_at_10 value: 2.919 - type: map_at_100 value: 3.107 - type: map_at_1000 value: 3.143 - type: map_at_3 value: 2.6100000000000003 - type: map_at_5 value: 2.773 - type: mrr_at_1 value: 4.146 - type: mrr_at_10 value: 5.657 - type: mrr_at_100 value: 5.970000000000001 - type: mrr_at_1000 value: 6.022 - type: mrr_at_3 value: 5.116 - type: mrr_at_5 value: 5.411 - type: ndcg_at_1 value: 4.146 - type: ndcg_at_10 value: 4.115 - type: ndcg_at_100 value: 5.319 - type: ndcg_at_1000 value: 6.584 - type: ndcg_at_3 value: 3.3709999999999996 - type: ndcg_at_5 value: 3.7159999999999997 - type: precision_at_1 value: 4.146 - type: precision_at_10 value: 0.983 - type: precision_at_100 value: 0.197 - type: precision_at_1000 value: 0.037 - type: precision_at_3 value: 2.152 - type: precision_at_5 value: 1.564 - type: recall_at_1 value: 2.073 - type: recall_at_10 value: 4.916 - type: recall_at_100 value: 9.844999999999999 - type: recall_at_1000 value: 18.454 - type: recall_at_3 value: 3.228 - type: recall_at_5 value: 3.91 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 53.28480000000001 - type: ap value: 51.81084207241404 - type: f1 value: 52.83683146513476 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 2.613 - type: map_at_10 value: 4.33 - type: map_at_100 value: 4.681 - type: map_at_1000 value: 4.731 - type: map_at_3 value: 3.7560000000000002 - type: map_at_5 value: 4.035 - type: mrr_at_1 value: 2.665 - type: mrr_at_10 value: 4.436 - type: mrr_at_100 value: 4.797 - type: mrr_at_1000 value: 4.848 - type: mrr_at_3 value: 3.83 - type: mrr_at_5 value: 4.123 - type: ndcg_at_1 value: 2.665 - type: ndcg_at_10 value: 5.399 - type: ndcg_at_100 value: 7.402 - type: ndcg_at_1000 value: 9.08 - type: ndcg_at_3 value: 4.1579999999999995 - type: ndcg_at_5 value: 4.664 - type: precision_at_1 value: 2.665 - type: precision_at_10 value: 0.907 - type: precision_at_100 value: 0.19499999999999998 - type: precision_at_1000 value: 0.034 - type: precision_at_3 value: 1.791 - type: precision_at_5 value: 1.3299999999999998 - type: recall_at_1 value: 2.613 - type: recall_at_10 value: 8.729000000000001 - type: recall_at_100 value: 18.668000000000003 - type: recall_at_1000 value: 32.387 - type: recall_at_3 value: 5.25 - type: recall_at_5 value: 6.465 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 73.57729138166896 - type: f1 value: 71.0267308110663 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 38.76652986776106 - type: f1 value: 24.385724192837007 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 43.43308675184936 - type: f1 value: 39.072401899805016 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 55.225285810356425 - type: f1 value: 49.81719052485716 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 20.583405653329283 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 17.155646378261917 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 24.26316550665883 - type: mrr value: 23.951621402458755 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 1.4040000000000001 - type: map_at_10 value: 2.199 - type: map_at_100 value: 2.597 - type: map_at_1000 value: 3.15 - type: map_at_3 value: 1.7850000000000001 - type: map_at_5 value: 2.005 - type: mrr_at_1 value: 13.932 - type: mrr_at_10 value: 19.529 - type: mrr_at_100 value: 20.53 - type: mrr_at_1000 value: 20.635 - type: mrr_at_3 value: 17.647 - type: mrr_at_5 value: 18.731 - type: ndcg_at_1 value: 12.539 - type: ndcg_at_10 value: 8.676 - type: ndcg_at_100 value: 8.092 - type: ndcg_at_1000 value: 16.375999999999998 - type: ndcg_at_3 value: 10.615 - type: ndcg_at_5 value: 9.690999999999999 - type: precision_at_1 value: 13.622 - type: precision_at_10 value: 6.315999999999999 - type: precision_at_100 value: 2.486 - type: precision_at_1000 value: 1.317 - type: precision_at_3 value: 10.113999999999999 - type: precision_at_5 value: 8.235000000000001 - type: recall_at_1 value: 1.4040000000000001 - type: recall_at_10 value: 3.794 - type: recall_at_100 value: 9.71 - type: recall_at_1000 value: 37.476 - type: recall_at_3 value: 2.197 - type: recall_at_5 value: 2.929 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 1.299 - type: map_at_10 value: 2.7279999999999998 - type: map_at_100 value: 3.065 - type: map_at_1000 value: 3.118 - type: map_at_3 value: 2.182 - type: map_at_5 value: 2.48 - type: mrr_at_1 value: 1.6219999999999999 - type: mrr_at_10 value: 3.237 - type: mrr_at_100 value: 3.5749999999999997 - type: mrr_at_1000 value: 3.626 - type: mrr_at_3 value: 2.6550000000000002 - type: mrr_at_5 value: 2.9770000000000003 - type: ndcg_at_1 value: 1.6219999999999999 - type: ndcg_at_10 value: 3.768 - type: ndcg_at_100 value: 5.721 - type: ndcg_at_1000 value: 7.346 - type: ndcg_at_3 value: 2.604 - type: ndcg_at_5 value: 3.1530000000000005 - type: precision_at_1 value: 1.6219999999999999 - type: precision_at_10 value: 0.776 - type: precision_at_100 value: 0.194 - type: precision_at_1000 value: 0.034999999999999996 - type: precision_at_3 value: 1.371 - type: precision_at_5 value: 1.1119999999999999 - type: recall_at_1 value: 1.299 - type: recall_at_10 value: 6.54 - type: recall_at_100 value: 16.014999999999997 - type: recall_at_1000 value: 28.776000000000003 - type: recall_at_3 value: 3.37 - type: recall_at_5 value: 4.676 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 50.827 - type: map_at_10 value: 60.903 - type: map_at_100 value: 61.67700000000001 - type: map_at_1000 value: 61.729 - type: map_at_3 value: 58.411 - type: map_at_5 value: 59.854 - type: mrr_at_1 value: 58.52 - type: mrr_at_10 value: 65.53999999999999 - type: mrr_at_100 value: 65.94 - type: mrr_at_1000 value: 65.962 - type: mrr_at_3 value: 63.905 - type: mrr_at_5 value: 64.883 - type: ndcg_at_1 value: 58.51 - type: ndcg_at_10 value: 65.458 - type: ndcg_at_100 value: 68.245 - type: ndcg_at_1000 value: 69.244 - type: ndcg_at_3 value: 61.970000000000006 - type: ndcg_at_5 value: 63.664 - type: precision_at_1 value: 58.51 - type: precision_at_10 value: 9.873999999999999 - type: precision_at_100 value: 1.24 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 26.650000000000002 - type: precision_at_5 value: 17.666 - type: recall_at_1 value: 50.827 - type: recall_at_10 value: 74.13300000000001 - type: recall_at_100 value: 85.724 - type: recall_at_1000 value: 92.551 - type: recall_at_3 value: 64.122 - type: recall_at_5 value: 68.757 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 15.106948858308094 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 30.968103547012337 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 1.4749999999999999 - type: map_at_10 value: 3.434 - type: map_at_100 value: 4.139 - type: map_at_1000 value: 4.312 - type: map_at_3 value: 2.554 - type: map_at_5 value: 2.999 - type: mrr_at_1 value: 7.3 - type: mrr_at_10 value: 12.031 - type: mrr_at_100 value: 12.97 - type: mrr_at_1000 value: 13.092 - type: mrr_at_3 value: 10.217 - type: mrr_at_5 value: 11.172 - type: ndcg_at_1 value: 7.3 - type: ndcg_at_10 value: 6.406000000000001 - type: ndcg_at_100 value: 10.302999999999999 - type: ndcg_at_1000 value: 14.791000000000002 - type: ndcg_at_3 value: 5.982 - type: ndcg_at_5 value: 5.274 - type: precision_at_1 value: 7.3 - type: precision_at_10 value: 3.37 - type: precision_at_100 value: 0.914 - type: precision_at_1000 value: 0.201 - type: precision_at_3 value: 5.567 - type: precision_at_5 value: 4.68 - type: recall_at_1 value: 1.4749999999999999 - type: recall_at_10 value: 6.79 - type: recall_at_100 value: 18.55 - type: recall_at_1000 value: 40.842 - type: recall_at_3 value: 3.36 - type: recall_at_5 value: 4.72 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 59.464420082440526 - type: cos_sim_spearman value: 54.319988337451704 - type: euclidean_pearson value: 57.042312873314295 - type: euclidean_spearman value: 54.31996388571784 - type: manhattan_pearson value: 57.078786802338435 - type: manhattan_spearman value: 54.323312153757456 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 60.08105871689929 - type: cos_sim_spearman value: 57.53293836132526 - type: euclidean_pearson value: 57.69984777047449 - type: euclidean_spearman value: 57.534154476967345 - type: manhattan_pearson value: 57.661519973840946 - type: manhattan_spearman value: 57.447636234309854 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 57.12692049687197 - type: cos_sim_spearman value: 57.4759438730368 - type: euclidean_pearson value: 58.41782334532981 - type: euclidean_spearman value: 57.47613008122331 - type: manhattan_pearson value: 58.41335837274888 - type: manhattan_spearman value: 57.465936751045746 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 53.84165004759765 - type: cos_sim_spearman value: 52.32112048731462 - type: euclidean_pearson value: 52.790405817119094 - type: euclidean_spearman value: 52.32112268628659 - type: manhattan_pearson value: 52.804939090733804 - type: manhattan_spearman value: 52.31750678935915 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 63.555819199866036 - type: cos_sim_spearman value: 64.05841117331784 - type: euclidean_pearson value: 63.659991414541786 - type: euclidean_spearman value: 64.05841071779129 - type: manhattan_pearson value: 63.6915442281397 - type: manhattan_spearman value: 64.07728265258595 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 63.03024268207247 - type: cos_sim_spearman value: 63.53003651570799 - type: euclidean_pearson value: 64.09620752390686 - type: euclidean_spearman value: 63.530036058718096 - type: manhattan_pearson value: 64.07468313413827 - type: manhattan_spearman value: 63.526415746516285 - 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: 70.18862439704168 - type: cos_sim_spearman value: 70.97966882821095 - type: euclidean_pearson value: 71.04858522892525 - type: euclidean_spearman value: 70.97966882821095 - type: manhattan_pearson value: 71.0777838495318 - type: manhattan_spearman value: 71.08141859528023 - 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: 49.680993011354964 - type: cos_sim_spearman value: 55.990646519065734 - type: euclidean_pearson value: 52.53309325175639 - type: euclidean_spearman value: 55.990646519065734 - type: manhattan_pearson value: 52.55809108662631 - type: manhattan_spearman value: 55.65236114980215 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 61.18394695826386 - type: cos_sim_spearman value: 60.77402126712771 - type: euclidean_pearson value: 61.202070794992736 - type: euclidean_spearman value: 60.77402126712771 - type: manhattan_pearson value: 61.2505175850885 - type: manhattan_spearman value: 60.77213463387346 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 58.251838750265804 - type: mrr value: 81.27406090641384 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 8.833 - type: map_at_10 value: 11.219999999999999 - type: map_at_100 value: 12.086 - type: map_at_1000 value: 12.200999999999999 - type: map_at_3 value: 10.056 - type: map_at_5 value: 10.664 - type: mrr_at_1 value: 9.0 - type: mrr_at_10 value: 11.875 - type: mrr_at_100 value: 12.757 - type: mrr_at_1000 value: 12.864 - type: mrr_at_3 value: 10.722 - type: mrr_at_5 value: 11.322000000000001 - type: ndcg_at_1 value: 9.0 - type: ndcg_at_10 value: 13.001 - type: ndcg_at_100 value: 17.784 - type: ndcg_at_1000 value: 21.695 - type: ndcg_at_3 value: 10.63 - type: ndcg_at_5 value: 11.693000000000001 - type: precision_at_1 value: 9.0 - type: precision_at_10 value: 2.0 - type: precision_at_100 value: 0.46299999999999997 - type: precision_at_1000 value: 0.083 - type: precision_at_3 value: 4.222 - type: precision_at_5 value: 3.1329999999999996 - type: recall_at_1 value: 8.833 - type: recall_at_10 value: 18.0 - type: recall_at_100 value: 41.211 - type: recall_at_1000 value: 73.14399999999999 - type: recall_at_3 value: 11.5 - type: recall_at_5 value: 14.083000000000002 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.44455445544554 - type: cos_sim_ap value: 68.76115592640271 - type: cos_sim_f1 value: 67.29805013927577 - type: cos_sim_precision value: 75.9748427672956 - type: cos_sim_recall value: 60.4 - type: dot_accuracy value: 99.44455445544554 - type: dot_ap value: 68.76115778951738 - type: dot_f1 value: 67.29805013927577 - type: dot_precision value: 75.9748427672956 - type: dot_recall value: 60.4 - type: euclidean_accuracy value: 99.44455445544554 - type: euclidean_ap value: 68.76115530286063 - type: euclidean_f1 value: 67.29805013927577 - type: euclidean_precision value: 75.9748427672956 - type: euclidean_recall value: 60.4 - type: manhattan_accuracy value: 99.44653465346535 - type: manhattan_ap value: 68.76446446842253 - type: manhattan_f1 value: 67.34926052332196 - type: manhattan_precision value: 78.10026385224275 - type: manhattan_recall value: 59.199999999999996 - type: max_accuracy value: 99.44653465346535 - type: max_ap value: 68.76446446842253 - type: max_f1 value: 67.34926052332196 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 28.486032726226675 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 29.654061810103283 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 39.81455140801657 - type: mrr value: 40.09712407690349 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.05 - type: map_at_10 value: 0.191 - type: map_at_100 value: 0.346 - type: map_at_1000 value: 0.553 - type: map_at_3 value: 0.11299999999999999 - type: map_at_5 value: 0.148 - type: mrr_at_1 value: 22.0 - type: mrr_at_10 value: 30.091 - type: mrr_at_100 value: 31.241999999999997 - type: mrr_at_1000 value: 31.298 - type: mrr_at_3 value: 28.000000000000004 - type: mrr_at_5 value: 28.999999999999996 - type: ndcg_at_1 value: 18.0 - type: ndcg_at_10 value: 12.501000000000001 - type: ndcg_at_100 value: 5.605 - type: ndcg_at_1000 value: 4.543 - type: ndcg_at_3 value: 17.531 - type: ndcg_at_5 value: 15.254999999999999 - type: precision_at_1 value: 22.0 - type: precision_at_10 value: 12.6 - type: precision_at_100 value: 5.06 - type: precision_at_1000 value: 2.028 - type: precision_at_3 value: 20.666999999999998 - type: precision_at_5 value: 16.8 - type: recall_at_1 value: 0.05 - type: recall_at_10 value: 0.267 - type: recall_at_100 value: 1.102 - type: recall_at_1000 value: 4.205 - type: recall_at_3 value: 0.134 - type: recall_at_5 value: 0.182 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 0.45199999999999996 - type: map_at_10 value: 1.986 - type: map_at_100 value: 3.887 - type: map_at_1000 value: 4.5809999999999995 - type: map_at_3 value: 0.9299999999999999 - type: map_at_5 value: 1.287 - type: mrr_at_1 value: 8.163 - type: mrr_at_10 value: 16.152 - type: mrr_at_100 value: 17.187 - type: mrr_at_1000 value: 17.301 - type: mrr_at_3 value: 11.224 - type: mrr_at_5 value: 12.653 - type: ndcg_at_1 value: 4.082 - type: ndcg_at_10 value: 6.687 - type: ndcg_at_100 value: 13.158 - type: ndcg_at_1000 value: 22.259 - type: ndcg_at_3 value: 5.039 - type: ndcg_at_5 value: 5.519 - type: precision_at_1 value: 8.163 - type: precision_at_10 value: 8.163 - type: precision_at_100 value: 3.51 - type: precision_at_1000 value: 0.9159999999999999 - type: precision_at_3 value: 7.483 - type: precision_at_5 value: 7.3469999999999995 - type: recall_at_1 value: 0.45199999999999996 - type: recall_at_10 value: 5.27 - type: recall_at_100 value: 20.75 - type: recall_at_1000 value: 49.236999999999995 - type: recall_at_3 value: 1.28 - type: recall_at_5 value: 2.045 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 57.08740000000001 - type: ap value: 9.092681400063896 - type: f1 value: 43.966684273361125 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 42.314657611771366 - type: f1 value: 42.2349043058169 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 15.71319288909283 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 78.84007867914407 - type: cos_sim_ap value: 42.2183603452187 - type: cos_sim_f1 value: 43.1781412906705 - type: cos_sim_precision value: 32.74263904034896 - type: cos_sim_recall value: 63.377308707124016 - type: dot_accuracy value: 78.84007867914407 - type: dot_ap value: 42.21836359699547 - type: dot_f1 value: 43.1781412906705 - type: dot_precision value: 32.74263904034896 - type: dot_recall value: 63.377308707124016 - type: euclidean_accuracy value: 78.84007867914407 - type: euclidean_ap value: 42.218363575958854 - type: euclidean_f1 value: 43.1781412906705 - type: euclidean_precision value: 32.74263904034896 - type: euclidean_recall value: 63.377308707124016 - type: manhattan_accuracy value: 78.79239434940692 - type: manhattan_ap value: 42.178124350579 - type: manhattan_f1 value: 43.16231513602337 - type: manhattan_precision value: 32.99832495812395 - type: manhattan_recall value: 62.37467018469657 - type: max_accuracy value: 78.84007867914407 - type: max_ap value: 42.21836359699547 - type: max_f1 value: 43.1781412906705 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 82.51445647533667 - type: cos_sim_ap value: 69.65701766911302 - type: cos_sim_f1 value: 62.92060699362217 - type: cos_sim_precision value: 60.046173219532676 - type: cos_sim_recall value: 66.08407761010163 - type: dot_accuracy value: 82.51445647533667 - type: dot_ap value: 69.6569952654014 - type: dot_f1 value: 62.92060699362217 - type: dot_precision value: 60.046173219532676 - type: dot_recall value: 66.08407761010163 - type: euclidean_accuracy value: 82.51445647533667 - type: euclidean_ap value: 69.65697749857492 - type: euclidean_f1 value: 62.92060699362217 - type: euclidean_precision value: 60.046173219532676 - type: euclidean_recall value: 66.08407761010163 - type: manhattan_accuracy value: 82.52221834128925 - type: manhattan_ap value: 69.65965534790995 - type: manhattan_f1 value: 62.865817064991006 - type: manhattan_precision value: 58.04811265401917 - type: manhattan_recall value: 68.55558977517708 - type: max_accuracy value: 82.52221834128925 - type: max_ap value: 69.65965534790995 - type: max_f1 value: 62.92060699362217 ---